{ // 获取包含Hugging Face文本的span元素 const spans = link.querySelectorAll('span.whitespace-nowrap, span.hidden.whitespace-nowrap'); spans.forEach(span => { if (span.textContent && span.textContent.trim().match(/Hugging\s*Face/i)) { span.textContent = 'AI快站'; } }); }); // 替换logo图片的alt属性 document.querySelectorAll('img[alt*="Hugging"], img[alt*="Face"]').forEach(img => { if (img.alt.match(/Hugging\s*Face/i)) { img.alt = 'AI快站 logo'; } }); } // 替换导航栏中的链接 function replaceNavigationLinks() { // 已替换标记,防止重复运行 if (window._navLinksReplaced) { return; } // 已经替换过的链接集合,防止重复替换 const replacedLinks = new Set(); // 只在导航栏区域查找和替换链接 const headerArea = document.querySelector('header') || document.querySelector('nav'); if (!headerArea) { return; } // 在导航区域内查找链接 const navLinks = headerArea.querySelectorAll('a'); navLinks.forEach(link => { // 如果已经替换过,跳过 if (replacedLinks.has(link)) return; const linkText = link.textContent.trim(); const linkHref = link.getAttribute('href') || ''; // 替换Spaces链接 - 仅替换一次 if ( (linkHref.includes('/spaces') || linkHref === '/spaces' || linkText === 'Spaces' || linkText.match(/^s*Spacess*$/i)) && linkText !== 'OCR模型免费转Markdown' && linkText !== 'OCR模型免费转Markdown' ) { link.textContent = 'OCR模型免费转Markdown'; link.href = 'https://fast360.xyz'; link.setAttribute('target', '_blank'); link.setAttribute('rel', 'noopener noreferrer'); replacedLinks.add(link); } // 删除Posts链接 else if ( (linkHref.includes('/posts') || linkHref === '/posts' || linkText === 'Posts' || linkText.match(/^s*Postss*$/i)) ) { if (link.parentNode) { link.parentNode.removeChild(link); } replacedLinks.add(link); } // 替换Docs链接 - 仅替换一次 else if ( (linkHref.includes('/docs') || linkHref === '/docs' || linkText === 'Docs' || linkText.match(/^s*Docss*$/i)) && linkText !== '模型下载攻略' ) { link.textContent = '模型下载攻略'; link.href = '/'; replacedLinks.add(link); } // 删除Enterprise链接 else if ( (linkHref.includes('/enterprise') || linkHref === '/enterprise' || linkText === 'Enterprise' || linkText.match(/^s*Enterprises*$/i)) ) { if (link.parentNode) { link.parentNode.removeChild(link); } replacedLinks.add(link); } }); // 查找可能嵌套的Spaces和Posts文本 const textNodes = []; function findTextNodes(element) { if (element.nodeType === Node.TEXT_NODE) { const text = element.textContent.trim(); if (text === 'Spaces' || text === 'Posts' || text === 'Enterprise') { textNodes.push(element); } } else { for (const child of element.childNodes) { findTextNodes(child); } } } // 只在导航区域内查找文本节点 findTextNodes(headerArea); // 替换找到的文本节点 textNodes.forEach(node => { const text = node.textContent.trim(); if (text === 'Spaces') { node.textContent = node.textContent.replace(/Spaces/g, 'OCR模型免费转Markdown'); } else if (text === 'Posts') { // 删除Posts文本节点 if (node.parentNode) { node.parentNode.removeChild(node); } } else if (text === 'Enterprise') { // 删除Enterprise文本节点 if (node.parentNode) { node.parentNode.removeChild(node); } } }); // 标记已替换完成 window._navLinksReplaced = true; } // 替换代码区域中的域名 function replaceCodeDomains() { // 特别处理span.hljs-string和span.njs-string元素 document.querySelectorAll('span.hljs-string, span.njs-string, span[class*="hljs-string"], span[class*="njs-string"]').forEach(span => { if (span.textContent && span.textContent.includes('huggingface.co')) { span.textContent = span.textContent.replace(/huggingface.co/g, 'aifasthub.com'); } }); // 替换hljs-string类的span中的域名(移除多余的转义符号) document.querySelectorAll('span.hljs-string, span[class*="hljs-string"]').forEach(span => { if (span.textContent && span.textContent.includes('huggingface.co')) { span.textContent = span.textContent.replace(/huggingface.co/g, 'aifasthub.com'); } }); // 替换pre和code标签中包含git clone命令的域名 document.querySelectorAll('pre, code').forEach(element => { if (element.textContent && element.textContent.includes('git clone')) { const text = element.innerHTML; if (text.includes('huggingface.co')) { element.innerHTML = text.replace(/huggingface.co/g, 'aifasthub.com'); } } }); // 处理特定的命令行示例 document.querySelectorAll('pre, code').forEach(element => { const text = element.innerHTML; if (text.includes('huggingface.co')) { // 针对git clone命令的专门处理 if (text.includes('git clone') || text.includes('GIT_LFS_SKIP_SMUDGE=1')) { element.innerHTML = text.replace(/huggingface.co/g, 'aifasthub.com'); } } }); // 特别处理模型下载页面上的代码片段 document.querySelectorAll('.flex.border-t, .svelte_hydrator, .inline-block').forEach(container => { const content = container.innerHTML; if (content && content.includes('huggingface.co')) { container.innerHTML = content.replace(/huggingface.co/g, 'aifasthub.com'); } }); // 特别处理模型仓库克隆对话框中的代码片段 try { // 查找包含"Clone this model repository"标题的对话框 const cloneDialog = document.querySelector('.svelte_hydration_boundary, [data-target="MainHeader"]'); if (cloneDialog) { // 查找对话框中所有的代码片段和命令示例 const codeElements = cloneDialog.querySelectorAll('pre, code, span'); codeElements.forEach(element => { if (element.textContent && element.textContent.includes('huggingface.co')) { if (element.innerHTML.includes('huggingface.co')) { element.innerHTML = element.innerHTML.replace(/huggingface.co/g, 'aifasthub.com'); } else { element.textContent = element.textContent.replace(/huggingface.co/g, 'aifasthub.com'); } } }); } // 更精确地定位克隆命令中的域名 document.querySelectorAll('[data-target]').forEach(container => { const codeBlocks = container.querySelectorAll('pre, code, span.hljs-string'); codeBlocks.forEach(block => { if (block.textContent && block.textContent.includes('huggingface.co')) { if (block.innerHTML.includes('huggingface.co')) { block.innerHTML = block.innerHTML.replace(/huggingface.co/g, 'aifasthub.com'); } else { block.textContent = block.textContent.replace(/huggingface.co/g, 'aifasthub.com'); } } }); }); } catch (e) { // 错误处理但不打印日志 } } // 当DOM加载完成后执行替换 if (document.readyState === 'loading') { document.addEventListener('DOMContentLoaded', () => { replaceHeaderBranding(); replaceNavigationLinks(); replaceCodeDomains(); // 只在必要时执行替换 - 3秒后再次检查 setTimeout(() => { if (!window._navLinksReplaced) { console.log('[Client] 3秒后重新检查导航链接'); replaceNavigationLinks(); } }, 3000); }); } else { replaceHeaderBranding(); replaceNavigationLinks(); replaceCodeDomains(); // 只在必要时执行替换 - 3秒后再次检查 setTimeout(() => { if (!window._navLinksReplaced) { console.log('[Client] 3秒后重新检查导航链接'); replaceNavigationLinks(); } }, 3000); } // 增加一个MutationObserver来处理可能的动态元素加载 const observer = new MutationObserver(mutations => { // 检查是否导航区域有变化 const hasNavChanges = mutations.some(mutation => { // 检查是否存在header或nav元素变化 return Array.from(mutation.addedNodes).some(node => { if (node.nodeType === Node.ELEMENT_NODE) { // 检查是否是导航元素或其子元素 if (node.tagName === 'HEADER' || node.tagName === 'NAV' || node.querySelector('header, nav')) { return true; } // 检查是否在导航元素内部 let parent = node.parentElement; while (parent) { if (parent.tagName === 'HEADER' || parent.tagName === 'NAV') { return true; } parent = parent.parentElement; } } return false; }); }); // 只在导航区域有变化时执行替换 if (hasNavChanges) { // 重置替换状态,允许再次替换 window._navLinksReplaced = false; replaceHeaderBranding(); replaceNavigationLinks(); } }); // 开始观察document.body的变化,包括子节点 if (document.body) { observer.observe(document.body, { childList: true, subtree: true }); } else { document.addEventListener('DOMContentLoaded', () => { observer.observe(document.body, { childList: true, subtree: true }); }); } })(); \n\"\"\"\n\ndef print_html_form ():\n \"\"\"This prints out the html form. Note that the action is set to\n the name of the script which makes this is a self-posting form.\n In other words, this cgi both displays a form and processes it.\n \"\"\"\n print \"content-type: text/html\\n\"\n print HTML_TEMPLATE % {'SCRIPT_NAME':os.environ['SCRIPT_NAME']}\n\ndef save_uploaded_file (form_field, upload_dir):\n \"\"\"This saves a file uploaded by an HTML form.\n The form_field is the name of the file input field from the form.\n For example, the following form_field would be \"file_1\":\n \n The upload_dir is the directory where the file will be written.\n If no file was uploaded or if the field does not exist then\n this does nothing.\n \"\"\"\n form = cgi.FieldStorage()\n if not form.has_key(form_field): return\n fileitem = form[form_field]\n if not fileitem.file: return\n fout = file (os.path.join(upload_dir, fileitem.filename), 'wb')\n while 1:\n chunk = fileitem.file.read(100000)\n if not chunk: break\n fout.write (chunk)\n fout.close()\n\nsave_uploaded_file (\"file_1\", UPLOAD_DIR)\nsave_uploaded_file (\"file_2\", UPLOAD_DIR)\nsave_uploaded_file (\"file_3\", UPLOAD_DIR)\n\nprint_html_form ()\n"},"input_ids":{"kind":"list like","value":[2,48443,14629,14,12001,14,8800,14,29412,198,37811,1212,15687,257,10926,2638,9516,269,12397,13,198,1212,3578,257,2836,284,9516,510,284,1115,3696,379,1752,13,198,1026,318,20861,284,1487,262,1271,286,3696,19144,13,198,198,1212,4226,468,2324,7476,13,317,2836,714,2230,284,6070,198,64,11898,18398,351,13079,9516,82,13,220,198,1532,345,423,257,1080,1280,284,262,1171,345,561,6189,765,198,1462,4179,262,2546,290,1271,286,3696,3194,284,262,11898,13,198,37811,198,11748,269,12397,198,11748,269,18300,65,26,269,18300,65,13,21633,3419,198,11748,28686,11,25064,198,28311,25,1303,3964,2476,14367,952,900,329,13934,4235,13,198,220,220,220,1330,13845,85,6098,83,198,220,220,220,13845,85,6098,83,13,2617,14171,357,15,11,28686,13,46,62,33,1268,13153,8,1303,14367,259,220,796,657,198,220,220,220,13845,85,6098,83,13,2617,14171,357,16,11,28686,13,46,62,33,1268,13153,8,1303,14367,448,796,352,198,16341,17267,12331,25,198,220,220,220,1208,198,198,52,6489,41048,62,34720,796,12813,22065,1,198,198,28656,62,51,3620,6489,6158,796,37227,27,0,18227,4177,56,11401,11532,44731,27444,1003,54,18,34,1003,35,21016,11532,604,13,486,3602,1859,1003,1677,5320,198,27,6494,6927,2256,6927,7839,29,8979,36803,3556,7839,29,198,27,28961,2638,12,4853,452,2625,19746,12,6030,1,2695,2625,5239,14,6494,26,34534,316,28,26786,12,3459,3270,12,16,5320,198,3556,2256,6927,2618,6927,71,16,29,8979,36803,3556,71,16,29,198,27,687,2223,2625,4,7,6173,46023,62,20608,8,82,1,2446,2625,32782,1,551,310,2981,2625,16680,541,433,14,687,12,7890,5320,198,8979,1438,25,1279,15414,1438,2625,7753,62,16,1,2099,2625,7753,22039,1671,29,198,8979,1438,25,1279,15414,1438,2625,7753,62,17,1,2099,2625,7753,22039,1671,29,198,8979,1438,25,1279,15414,1438,2625,7753,62,18,1,2099,2625,7753,22039,1671,29,198,27,15414,1438,2625,46002,1,2099,2625,46002,5320,198,3556,687,29,198,3556,2618,29,198,3556,6494,29,37811,198,198,4299,3601,62,6494,62,687,357,2599,198,220,220,220,37227,1212,20842,503,262,27711,1296,13,5740,326,262,2223,318,900,284,198,220,220,220,220,220,262,1438,286,262,4226,543,1838,428,318,257,2116,12,7353,278,1296,13,198,220,220,220,220,220,554,584,2456,11,428,269,12397,1111,11298,257,1296,290,7767,340,13,198,220,220,220,37227,198,220,220,220,3601,366,11299,12,4906,25,2420,14,6494,59,77,1,198,220,220,220,3601,11532,62,51,3620,6489,6158,4064,1391,6,6173,46023,62,20608,10354,418,13,268,2268,17816,6173,46023,62,20608,20520,92,198,198,4299,3613,62,25850,276,62,7753,357,687,62,3245,11,9516,62,15908,2599,198,220,220,220,37227,1212,16031,257,2393,19144,416,281,11532,1296,13,198,220,220,220,220,220,220,383,1296,62,3245,318,262,1438,286,262,2393,5128,2214,422,262,1296,13,198,220,220,220,220,220,220,1114,1672,11,262,1708,1296,62,3245,561,307,366,7753,62,16,1298,198,220,220,220,220,220,220,220,220,220,220,1279,15414,1438,2625,7753,62,16,1,2099,2625,7753,5320,198,220,220,220,220,220,220,383,9516,62,15908,318,262,8619,810,262,2393,481,307,3194,13,198,220,220,220,220,220,220,1002,645,2393,373,19144,393,611,262,2214,857,407,2152,788,198,220,220,220,220,220,220,428,857,2147,13,198,220,220,220,37227,198,220,220,220,1296,796,269,12397,13,15878,31425,3419,198,220,220,220,611,407,1296,13,10134,62,2539,7,687,62,3245,2599,1441,198,220,220,220,2393,9186,796,1296,58,687,62,3245,60,198,220,220,220,611,407,2393,9186,13,7753,25,1441,198,220,220,220,277,448,796,2393,357,418,13,6978,13,22179,7,25850,62,15908,11,2393,9186,13,34345,828,705,39346,11537,198,220,220,220,981,352,25,198,220,220,220,220,220,220,220,16058,796,2393,9186,13,7753,13,961,7,3064,830,8,198,220,220,220,220,220,220,220,611,407,16058,25,2270,198,220,220,220,220,220,220,220,277,448,13,13564,357,354,2954,8,198,220,220,220,277,448,13,19836,3419,198,198,21928,62,25850,276,62,7753,5855,7753,62,16,1600,471,6489,41048,62,34720,8,198,21928,62,25850,276,62,7753,5855,7753,62,17,1600,471,6489,41048,62,34720,8,198,21928,62,25850,276,62,7753,5855,7753,62,18,1600,471,6489,41048,62,34720,8,198,198,4798,62,6494,62,687,7499,198],"string":"[\n 2,\n 48443,\n 14629,\n 14,\n 12001,\n 14,\n 8800,\n 14,\n 29412,\n 198,\n 37811,\n 1212,\n 15687,\n 257,\n 10926,\n 2638,\n 9516,\n 269,\n 12397,\n 13,\n 198,\n 1212,\n 3578,\n 257,\n 2836,\n 284,\n 9516,\n 510,\n 284,\n 1115,\n 3696,\n 379,\n 1752,\n 13,\n 198,\n 1026,\n 318,\n 20861,\n 284,\n 1487,\n 262,\n 1271,\n 286,\n 3696,\n 19144,\n 13,\n 198,\n 198,\n 1212,\n 4226,\n 468,\n 2324,\n 7476,\n 13,\n 317,\n 2836,\n 714,\n 2230,\n 284,\n 6070,\n 198,\n 64,\n 11898,\n 18398,\n 351,\n 13079,\n 9516,\n 82,\n 13,\n 220,\n 198,\n 1532,\n 345,\n 423,\n 257,\n 1080,\n 1280,\n 284,\n 262,\n 1171,\n 345,\n 561,\n 6189,\n 765,\n 198,\n 1462,\n 4179,\n 262,\n 2546,\n 290,\n 1271,\n 286,\n 3696,\n 3194,\n 284,\n 262,\n 11898,\n 13,\n 198,\n 37811,\n 198,\n 11748,\n 269,\n 12397,\n 198,\n 11748,\n 269,\n 18300,\n 65,\n 26,\n 269,\n 18300,\n 65,\n 13,\n 21633,\n 3419,\n 198,\n 11748,\n 28686,\n 11,\n 25064,\n 198,\n 28311,\n 25,\n 1303,\n 3964,\n 2476,\n 14367,\n 952,\n 900,\n 329,\n 13934,\n 4235,\n 13,\n 198,\n 220,\n 220,\n 220,\n 1330,\n 13845,\n 85,\n 6098,\n 83,\n 198,\n 220,\n 220,\n 220,\n 13845,\n 85,\n 6098,\n 83,\n 13,\n 2617,\n 14171,\n 357,\n 15,\n 11,\n 28686,\n 13,\n 46,\n 62,\n 33,\n 1268,\n 13153,\n 8,\n 1303,\n 14367,\n 259,\n 220,\n 796,\n 657,\n 198,\n 220,\n 220,\n 220,\n 13845,\n 85,\n 6098,\n 83,\n 13,\n 2617,\n 14171,\n 357,\n 16,\n 11,\n 28686,\n 13,\n 46,\n 62,\n 33,\n 1268,\n 13153,\n 8,\n 1303,\n 14367,\n 448,\n 796,\n 352,\n 198,\n 16341,\n 17267,\n 12331,\n 25,\n 198,\n 220,\n 220,\n 220,\n 1208,\n 198,\n 198,\n 52,\n 6489,\n 41048,\n 62,\n 34720,\n 796,\n 12813,\n 22065,\n 1,\n 198,\n 198,\n 28656,\n 62,\n 51,\n 3620,\n 6489,\n 6158,\n 796,\n 37227,\n 27,\n 0,\n 18227,\n 4177,\n 56,\n 11401,\n 11532,\n 44731,\n 27444,\n 1003,\n 54,\n 18,\n 34,\n 1003,\n 35,\n 21016,\n 11532,\n 604,\n 13,\n 486,\n 3602,\n 1859,\n 1003,\n 1677,\n 5320,\n 198,\n 27,\n 6494,\n 6927,\n 2256,\n 6927,\n 7839,\n 29,\n 8979,\n 36803,\n 3556,\n 7839,\n 29,\n 198,\n 27,\n 28961,\n 2638,\n 12,\n 4853,\n 452,\n 2625,\n 19746,\n 12,\n 6030,\n 1,\n 2695,\n 2625,\n 5239,\n 14,\n 6494,\n 26,\n 34534,\n 316,\n 28,\n 26786,\n 12,\n 3459,\n 3270,\n 12,\n 16,\n 5320,\n 198,\n 3556,\n 2256,\n 6927,\n 2618,\n 6927,\n 71,\n 16,\n 29,\n 8979,\n 36803,\n 3556,\n 71,\n 16,\n 29,\n 198,\n 27,\n 687,\n 2223,\n 2625,\n 4,\n 7,\n 6173,\n 46023,\n 62,\n 20608,\n 8,\n 82,\n 1,\n 2446,\n 2625,\n 32782,\n 1,\n 551,\n 310,\n 2981,\n 2625,\n 16680,\n 541,\n 433,\n 14,\n 687,\n 12,\n 7890,\n 5320,\n 198,\n 8979,\n 1438,\n 25,\n 1279,\n 15414,\n 1438,\n 2625,\n 7753,\n 62,\n 16,\n 1,\n 2099,\n 2625,\n 7753,\n 22039,\n 1671,\n 29,\n 198,\n 8979,\n 1438,\n 25,\n 1279,\n 15414,\n 1438,\n 2625,\n 7753,\n 62,\n 17,\n 1,\n 2099,\n 2625,\n 7753,\n 22039,\n 1671,\n 29,\n 198,\n 8979,\n 1438,\n 25,\n 1279,\n 15414,\n 1438,\n 2625,\n 7753,\n 62,\n 18,\n 1,\n 2099,\n 2625,\n 7753,\n 22039,\n 1671,\n 29,\n 198,\n 27,\n 15414,\n 1438,\n 2625,\n 46002,\n 1,\n 2099,\n 2625,\n 46002,\n 5320,\n 198,\n 3556,\n 687,\n 29,\n 198,\n 3556,\n 2618,\n 29,\n 198,\n 3556,\n 6494,\n 29,\n 37811,\n 198,\n 198,\n 4299,\n 3601,\n 62,\n 6494,\n 62,\n 687,\n 357,\n 2599,\n 198,\n 220,\n 220,\n 220,\n 37227,\n 1212,\n 20842,\n 503,\n 262,\n 27711,\n 1296,\n 13,\n 5740,\n 326,\n 262,\n 2223,\n 318,\n 900,\n 284,\n 198,\n 220,\n 220,\n 220,\n 220,\n 220,\n 262,\n 1438,\n 286,\n 262,\n 4226,\n 543,\n 1838,\n 428,\n 318,\n 257,\n 2116,\n 12,\n 7353,\n 278,\n 1296,\n 13,\n 198,\n 220,\n 220,\n 220,\n 220,\n 220,\n 554,\n 584,\n 2456,\n 11,\n 428,\n 269,\n 12397,\n 1111,\n 11298,\n 257,\n 1296,\n 290,\n 7767,\n 340,\n 13,\n 198,\n 220,\n 220,\n 220,\n 37227,\n 198,\n 220,\n 220,\n 220,\n 3601,\n 366,\n 11299,\n 12,\n 4906,\n 25,\n 2420,\n 14,\n 6494,\n 59,\n 77,\n 1,\n 198,\n 220,\n 220,\n 220,\n 3601,\n 11532,\n 62,\n 51,\n 3620,\n 6489,\n 6158,\n 4064,\n 1391,\n 6,\n 6173,\n 46023,\n 62,\n 20608,\n 10354,\n 418,\n 13,\n 268,\n 2268,\n 17816,\n 6173,\n 46023,\n 62,\n 20608,\n 20520,\n 92,\n 198,\n 198,\n 4299,\n 3613,\n 62,\n 25850,\n 276,\n 62,\n 7753,\n 357,\n 687,\n 62,\n 3245,\n 11,\n 9516,\n 62,\n 15908,\n 2599,\n 198,\n 220,\n 220,\n 220,\n 37227,\n 1212,\n 16031,\n 257,\n 2393,\n 19144,\n 416,\n 281,\n 11532,\n 1296,\n 13,\n 198,\n 220,\n 220,\n 220,\n 220,\n 220,\n 220,\n 383,\n 1296,\n 62,\n 3245,\n 318,\n 262,\n 1438,\n 286,\n 262,\n 2393,\n 5128,\n 2214,\n 422,\n 262,\n 1296,\n 13,\n 198,\n 220,\n 220,\n 220,\n 220,\n 220,\n 220,\n 1114,\n 1672,\n 11,\n 262,\n 1708,\n 1296,\n 62,\n 3245,\n 561,\n 307,\n 366,\n 7753,\n 62,\n 16,\n 1298,\n 198,\n 220,\n 220,\n 220,\n 220,\n 220,\n 220,\n 220,\n 220,\n 220,\n 220,\n 1279,\n 15414,\n 1438,\n 2625,\n 7753,\n 62,\n 16,\n 1,\n 2099,\n 2625,\n 7753,\n 5320,\n 198,\n 220,\n 220,\n 220,\n 220,\n 220,\n 220,\n 383,\n 9516,\n 62,\n 15908,\n 318,\n 262,\n 8619,\n 810,\n 262,\n 2393,\n 481,\n 307,\n 3194,\n 13,\n 198,\n 220,\n 220,\n 220,\n 220,\n 220,\n 220,\n 1002,\n 645,\n 2393,\n 373,\n 19144,\n 393,\n 611,\n 262,\n 2214,\n 857,\n 407,\n 2152,\n 788,\n 198,\n 220,\n 220,\n 220,\n 220,\n 220,\n 220,\n 428,\n 857,\n 2147,\n 13,\n 198,\n 220,\n 220,\n 220,\n 37227,\n 198,\n 220,\n 220,\n 220,\n 1296,\n 796,\n 269,\n 12397,\n 13,\n 15878,\n 31425,\n 3419,\n 198,\n 220,\n 220,\n 220,\n 611,\n 407,\n 1296,\n 13,\n 10134,\n 62,\n 2539,\n 7,\n 687,\n 62,\n 3245,\n 2599,\n 1441,\n 198,\n 220,\n 220,\n 220,\n 2393,\n 9186,\n 796,\n 1296,\n 58,\n 687,\n 62,\n 3245,\n 60,\n 198,\n 220,\n 220,\n 220,\n 611,\n 407,\n 2393,\n 9186,\n 13,\n 7753,\n 25,\n 1441,\n 198,\n 220,\n 220,\n 220,\n 277,\n 448,\n 796,\n 2393,\n 357,\n 418,\n 13,\n 6978,\n 13,\n 22179,\n 7,\n 25850,\n 62,\n 15908,\n 11,\n 2393,\n 9186,\n 13,\n 34345,\n 828,\n 705,\n 39346,\n 11537,\n 198,\n 220,\n 220,\n 220,\n 981,\n 352,\n 25,\n 198,\n 220,\n 220,\n 220,\n 220,\n 220,\n 220,\n 220,\n 16058,\n 796,\n 2393,\n 9186,\n 13,\n 7753,\n 13,\n 961,\n 7,\n 3064,\n 830,\n 8,\n 198,\n 220,\n 220,\n 220,\n 220,\n 220,\n 220,\n 220,\n 611,\n 407,\n 16058,\n 25,\n 2270,\n 198,\n 220,\n 220,\n 220,\n 220,\n 220,\n 220,\n 220,\n 277,\n 448,\n 13,\n 13564,\n 357,\n 354,\n 2954,\n 8,\n 198,\n 220,\n 220,\n 220,\n 277,\n 448,\n 13,\n 19836,\n 3419,\n 198,\n 198,\n 21928,\n 62,\n 25850,\n 276,\n 62,\n 7753,\n 5855,\n 7753,\n 62,\n 16,\n 1600,\n 471,\n 6489,\n 41048,\n 62,\n 34720,\n 8,\n 198,\n 21928,\n 62,\n 25850,\n 276,\n 62,\n 7753,\n 5855,\n 7753,\n 62,\n 17,\n 1600,\n 471,\n 6489,\n 41048,\n 62,\n 34720,\n 8,\n 198,\n 21928,\n 62,\n 25850,\n 276,\n 62,\n 7753,\n 5855,\n 7753,\n 62,\n 18,\n 1600,\n 471,\n 6489,\n 41048,\n 62,\n 34720,\n 8,\n 198,\n 198,\n 4798,\n 62,\n 6494,\n 62,\n 687,\n 7499,\n 198\n]"},"ratio_char_token":{"kind":"number","value":2.7304730473047303,"string":"2.730473"},"token_count":{"kind":"number","value":909,"string":"909"}}},{"rowIdx":1209,"cells":{"content":{"kind":"string","value":"import argparse\r\nimport datetime\r\nimport os\r\nimport re\r\nimport sys\r\nimport unicodedata\r\nimport libs.header\r\nimport libs.unicode\r\nimport libs.utf8\r\n\r\nif __name__ == '__main__':\r\n\tparser = argparse.ArgumentParser(description='Parse Unicode codepoint database and write integration tests.')\r\n\tparser.add_argument(\r\n\t\t'-v', '--verbose',\r\n\t\tdest = 'verbose',\r\n\t\taction = 'store_true',\r\n\t\thelp = 'verbose output')\r\n\tparser.add_argument(\r\n\t\t'--casemapping',\r\n\t\tdest = 'casemapping',\r\n\t\taction = 'store_true',\r\n\t\thelp = 'write case mapping tests')\r\n\tparser.add_argument(\r\n\t\t'--normalization',\r\n\t\tdest = 'normalization',\r\n\t\taction = 'store_true',\r\n\t\thelp = 'write normalization tests')\r\n\tparser.add_argument(\r\n\t\t'--is-normalized',\r\n\t\tdest = 'isnormalized',\r\n\t\taction = 'store_true',\r\n\t\thelp = 'write is-normalized tests')\r\n\tparser.add_argument(\r\n\t\t'--casefolding',\r\n\t\tdest = 'casefolding',\r\n\t\taction = 'store_true',\r\n\t\thelp = 'write casefolding tests')\r\n\targs = parser.parse_args()\r\n\t\r\n\tif not args.casemapping and not args.normalization and not args.isnormalized and not args.casefolding:\r\n\t\tall = True\r\n\telse:\r\n\t\tall = False\r\n\t\r\n\tdb = unicodedata.Database()\r\n\tdb.loadFromFiles(None)\r\n\t\r\n\tif all or args.casemapping:\r\n\t\tsuite = CaseMappingIntegrationSuite(db)\r\n\t\tsuite.execute()\r\n\t\r\n\tif all or args.normalization:\r\n\t\tsuite = NormalizationIntegrationSuite(db)\r\n\t\tsuite.execute()\r\n\t\r\n\tif all or args.isnormalized:\r\n\t\tsuite = IsNormalizedIntegrationSuite(db)\r\n\t\tsuite.execute()\r\n\t\r\n\tif all or args.casefolding:\r\n\t\tsuite = CaseFoldingIntegrationSuite(db)\r\n\t\tsuite.execute()"},"input_ids":{"kind":"list like","value":[11748,1822,29572,201,198,11748,4818,8079,201,198,11748,28686,201,198,11748,302,201,198,11748,25064,201,198,11748,28000,9043,1045,201,198,11748,9195,82,13,25677,201,198,11748,9195,82,13,46903,1098,201,198,11748,9195,82,13,40477,23,201,198,201,198,361,11593,3672,834,6624,705,834,12417,834,10354,201,198,197,48610,796,1822,29572,13,28100,1713,46677,7,11213,11639,10044,325,34371,14873,538,1563,6831,290,3551,11812,5254,2637,8,201,198,197,48610,13,2860,62,49140,7,201,198,197,197,29001,85,3256,705,438,19011,577,3256,201,198,197,197,16520,796,705,19011,577,3256,201,198,197,197,2673,796,705,8095,62,7942,3256,201,198,197,197,16794,796,705,19011,577,5072,11537,201,198,197,48610,13,2860,62,49140,7,201,198,197,197,6,438,34004,368,5912,3256,201,198,197,197,16520,796,705,34004,368,5912,3256,201,198,197,197,2673,796,705,8095,62,7942,3256,201,198,197,197,16794,796,705,13564,1339,16855,5254,11537,201,198,197,48610,13,2860,62,49140,7,201,198,197,197,6,438,11265,1634,3256,201,198,197,197,16520,796,705,11265,1634,3256,201,198,197,197,2673,796,705,8095,62,7942,3256,201,198,197,197,16794,796,705,13564,3487,1634,5254,11537,201,198,197,48610,13,2860,62,49140,7,201,198,197,197,6,438,271,12,11265,1143,3256,201,198,197,197,16520,796,705,271,11265,1143,3256,201,198,197,197,2673,796,705,8095,62,7942,3256,201,198,197,197,16794,796,705,13564,318,12,11265,1143,5254,11537,201,198,197,48610,13,2860,62,49140,7,201,198,197,197,6,438,7442,11379,278,3256,201,198,197,197,16520,796,705,7442,11379,278,3256,201,198,197,197,2673,796,705,8095,62,7942,3256,201,198,197,197,16794,796,705,13564,1339,11379,278,5254,11537,201,198,197,22046,796,30751,13,29572,62,22046,3419,201,198,197,201,198,197,361,407,26498,13,34004,368,5912,290,407,26498,13,11265,1634,290,407,26498,13,271,11265,1143,290,407,26498,13,7442,11379,278,25,201,198,197,197,439,796,6407,201,198,197,17772,25,201,198,197,197,439,796,10352,201,198,197,201,198,197,9945,796,28000,9043,1045,13,38105,3419,201,198,197,9945,13,2220,4863,25876,7,14202,8,201,198,197,201,198,197,361,477,393,26498,13,34004,368,5912,25,201,198,197,197,2385,578,796,8913,44,5912,34500,1358,5606,578,7,9945,8,201,198,197,197,2385,578,13,41049,3419,201,198,197,201,198,197,361,477,393,26498,13,11265,1634,25,201,198,197,197,2385,578,796,14435,1634,34500,1358,5606,578,7,9945,8,201,198,197,197,2385,578,13,41049,3419,201,198,197,201,198,197,361,477,393,26498,13,271,11265,1143,25,201,198,197,197,2385,578,796,1148,26447,1143,34500,1358,5606,578,7,9945,8,201,198,197,197,2385,578,13,41049,3419,201,198,197,201,198,197,361,477,393,26498,13,7442,11379,278,25,201,198,197,197,2385,578,796,8913,37,33266,34500,1358,5606,578,7,9945,8,201,198,197,197,2385,578,13,41049,3419],"string":"[\n 11748,\n 1822,\n 29572,\n 201,\n 198,\n 11748,\n 4818,\n 8079,\n 201,\n 198,\n 11748,\n 28686,\n 201,\n 198,\n 11748,\n 302,\n 201,\n 198,\n 11748,\n 25064,\n 201,\n 198,\n 11748,\n 28000,\n 9043,\n 1045,\n 201,\n 198,\n 11748,\n 9195,\n 82,\n 13,\n 25677,\n 201,\n 198,\n 11748,\n 9195,\n 82,\n 13,\n 46903,\n 1098,\n 201,\n 198,\n 11748,\n 9195,\n 82,\n 13,\n 40477,\n 23,\n 201,\n 198,\n 201,\n 198,\n 361,\n 11593,\n 3672,\n 834,\n 6624,\n 705,\n 834,\n 12417,\n 834,\n 10354,\n 201,\n 198,\n 197,\n 48610,\n 796,\n 1822,\n 29572,\n 13,\n 28100,\n 1713,\n 46677,\n 7,\n 11213,\n 11639,\n 10044,\n 325,\n 34371,\n 14873,\n 538,\n 1563,\n 6831,\n 290,\n 3551,\n 11812,\n 5254,\n 2637,\n 8,\n 201,\n 198,\n 197,\n 48610,\n 13,\n 2860,\n 62,\n 49140,\n 7,\n 201,\n 198,\n 197,\n 197,\n 29001,\n 85,\n 3256,\n 705,\n 438,\n 19011,\n 577,\n 3256,\n 201,\n 198,\n 197,\n 197,\n 16520,\n 796,\n 705,\n 19011,\n 577,\n 3256,\n 201,\n 198,\n 197,\n 197,\n 2673,\n 796,\n 705,\n 8095,\n 62,\n 7942,\n 3256,\n 201,\n 198,\n 197,\n 197,\n 16794,\n 796,\n 705,\n 19011,\n 577,\n 5072,\n 11537,\n 201,\n 198,\n 197,\n 48610,\n 13,\n 2860,\n 62,\n 49140,\n 7,\n 201,\n 198,\n 197,\n 197,\n 6,\n 438,\n 34004,\n 368,\n 5912,\n 3256,\n 201,\n 198,\n 197,\n 197,\n 16520,\n 796,\n 705,\n 34004,\n 368,\n 5912,\n 3256,\n 201,\n 198,\n 197,\n 197,\n 2673,\n 796,\n 705,\n 8095,\n 62,\n 7942,\n 3256,\n 201,\n 198,\n 197,\n 197,\n 16794,\n 796,\n 705,\n 13564,\n 1339,\n 16855,\n 5254,\n 11537,\n 201,\n 198,\n 197,\n 48610,\n 13,\n 2860,\n 62,\n 49140,\n 7,\n 201,\n 198,\n 197,\n 197,\n 6,\n 438,\n 11265,\n 1634,\n 3256,\n 201,\n 198,\n 197,\n 197,\n 16520,\n 796,\n 705,\n 11265,\n 1634,\n 3256,\n 201,\n 198,\n 197,\n 197,\n 2673,\n 796,\n 705,\n 8095,\n 62,\n 7942,\n 3256,\n 201,\n 198,\n 197,\n 197,\n 16794,\n 796,\n 705,\n 13564,\n 3487,\n 1634,\n 5254,\n 11537,\n 201,\n 198,\n 197,\n 48610,\n 13,\n 2860,\n 62,\n 49140,\n 7,\n 201,\n 198,\n 197,\n 197,\n 6,\n 438,\n 271,\n 12,\n 11265,\n 1143,\n 3256,\n 201,\n 198,\n 197,\n 197,\n 16520,\n 796,\n 705,\n 271,\n 11265,\n 1143,\n 3256,\n 201,\n 198,\n 197,\n 197,\n 2673,\n 796,\n 705,\n 8095,\n 62,\n 7942,\n 3256,\n 201,\n 198,\n 197,\n 197,\n 16794,\n 796,\n 705,\n 13564,\n 318,\n 12,\n 11265,\n 1143,\n 5254,\n 11537,\n 201,\n 198,\n 197,\n 48610,\n 13,\n 2860,\n 62,\n 49140,\n 7,\n 201,\n 198,\n 197,\n 197,\n 6,\n 438,\n 7442,\n 11379,\n 278,\n 3256,\n 201,\n 198,\n 197,\n 197,\n 16520,\n 796,\n 705,\n 7442,\n 11379,\n 278,\n 3256,\n 201,\n 198,\n 197,\n 197,\n 2673,\n 796,\n 705,\n 8095,\n 62,\n 7942,\n 3256,\n 201,\n 198,\n 197,\n 197,\n 16794,\n 796,\n 705,\n 13564,\n 1339,\n 11379,\n 278,\n 5254,\n 11537,\n 201,\n 198,\n 197,\n 22046,\n 796,\n 30751,\n 13,\n 29572,\n 62,\n 22046,\n 3419,\n 201,\n 198,\n 197,\n 201,\n 198,\n 197,\n 361,\n 407,\n 26498,\n 13,\n 34004,\n 368,\n 5912,\n 290,\n 407,\n 26498,\n 13,\n 11265,\n 1634,\n 290,\n 407,\n 26498,\n 13,\n 271,\n 11265,\n 1143,\n 290,\n 407,\n 26498,\n 13,\n 7442,\n 11379,\n 278,\n 25,\n 201,\n 198,\n 197,\n 197,\n 439,\n 796,\n 6407,\n 201,\n 198,\n 197,\n 17772,\n 25,\n 201,\n 198,\n 197,\n 197,\n 439,\n 796,\n 10352,\n 201,\n 198,\n 197,\n 201,\n 198,\n 197,\n 9945,\n 796,\n 28000,\n 9043,\n 1045,\n 13,\n 38105,\n 3419,\n 201,\n 198,\n 197,\n 9945,\n 13,\n 2220,\n 4863,\n 25876,\n 7,\n 14202,\n 8,\n 201,\n 198,\n 197,\n 201,\n 198,\n 197,\n 361,\n 477,\n 393,\n 26498,\n 13,\n 34004,\n 368,\n 5912,\n 25,\n 201,\n 198,\n 197,\n 197,\n 2385,\n 578,\n 796,\n 8913,\n 44,\n 5912,\n 34500,\n 1358,\n 5606,\n 578,\n 7,\n 9945,\n 8,\n 201,\n 198,\n 197,\n 197,\n 2385,\n 578,\n 13,\n 41049,\n 3419,\n 201,\n 198,\n 197,\n 201,\n 198,\n 197,\n 361,\n 477,\n 393,\n 26498,\n 13,\n 11265,\n 1634,\n 25,\n 201,\n 198,\n 197,\n 197,\n 2385,\n 578,\n 796,\n 14435,\n 1634,\n 34500,\n 1358,\n 5606,\n 578,\n 7,\n 9945,\n 8,\n 201,\n 198,\n 197,\n 197,\n 2385,\n 578,\n 13,\n 41049,\n 3419,\n 201,\n 198,\n 197,\n 201,\n 198,\n 197,\n 361,\n 477,\n 393,\n 26498,\n 13,\n 271,\n 11265,\n 1143,\n 25,\n 201,\n 198,\n 197,\n 197,\n 2385,\n 578,\n 796,\n 1148,\n 26447,\n 1143,\n 34500,\n 1358,\n 5606,\n 578,\n 7,\n 9945,\n 8,\n 201,\n 198,\n 197,\n 197,\n 2385,\n 578,\n 13,\n 41049,\n 3419,\n 201,\n 198,\n 197,\n 201,\n 198,\n 197,\n 361,\n 477,\n 393,\n 26498,\n 13,\n 7442,\n 11379,\n 278,\n 25,\n 201,\n 198,\n 197,\n 197,\n 2385,\n 578,\n 796,\n 8913,\n 37,\n 33266,\n 34500,\n 1358,\n 5606,\n 578,\n 7,\n 9945,\n 8,\n 201,\n 198,\n 197,\n 197,\n 2385,\n 578,\n 13,\n 41049,\n 3419\n]"},"ratio_char_token":{"kind":"number","value":2.567434210526316,"string":"2.567434"},"token_count":{"kind":"number","value":608,"string":"608"}}},{"rowIdx":1210,"cells":{"content":{"kind":"string","value":"try:\n from PyQt4.QtCore import QSettings\nexcept ImportError:\n from PyQt5.QtCore import QSettings\n\n "},"input_ids":{"kind":"list like","value":[28311,25,198,220,220,220,422,9485,48,83,19,13,48,83,14055,1330,1195,26232,198,16341,17267,12331,25,198,220,220,220,422,9485,48,83,20,13,48,83,14055,1330,1195,26232,628,220,220,220,220],"string":"[\n 28311,\n 25,\n 198,\n 220,\n 220,\n 220,\n 422,\n 9485,\n 48,\n 83,\n 19,\n 13,\n 48,\n 83,\n 14055,\n 1330,\n 1195,\n 26232,\n 198,\n 16341,\n 17267,\n 12331,\n 25,\n 198,\n 220,\n 220,\n 220,\n 422,\n 9485,\n 48,\n 83,\n 20,\n 13,\n 48,\n 83,\n 14055,\n 1330,\n 1195,\n 26232,\n 628,\n 220,\n 220,\n 220,\n 220\n]"},"ratio_char_token":{"kind":"number","value":2.4545454545454546,"string":"2.454545"},"token_count":{"kind":"number","value":44,"string":"44"}}},{"rowIdx":1211,"cells":{"content":{"kind":"string","value":"from re import search\nfrom typing import List, Optional, Pattern\n\n"},"input_ids":{"kind":"list like","value":[6738,302,1330,2989,198,6738,19720,1330,7343,11,32233,11,23939,628],"string":"[\n 6738,\n 302,\n 1330,\n 2989,\n 198,\n 6738,\n 19720,\n 1330,\n 7343,\n 11,\n 32233,\n 11,\n 23939,\n 628\n]"},"ratio_char_token":{"kind":"number","value":4.714285714285714,"string":"4.714286"},"token_count":{"kind":"number","value":14,"string":"14"}}},{"rowIdx":1212,"cells":{"content":{"kind":"string","value":"\"\"\"\n__________________________________________________________________________________________________\n\n:project: SiLA2_python\n\n:details: Response data type in a SiLA Command, Property, Intermediate, ...\n\n:file: data_type_response.py\n:authors: Timm Severin\n\n:date: (creation) 20190820\n:date: (last modification) 20190820\n\n__________________________________________________________________________________________________\n\n**Copyright**:\n This file is provided \"AS IS\" with NO WARRANTY OF ANY KIND,\n INCLUDING THE WARRANTIES OF DESIGN, MERCHANTABILITY AND FITNESS FOR A PARTICULAR PURPOSE.\n\n For further Information see LICENSE file that comes with this distribution.\n__________________________________________________________________________________________________\n\"\"\"\n\n# import library packages\nfrom .data_type_parameter import ParameterDataType\n\n\nclass ResponseDataType(ParameterDataType):\n \"\"\"\n The class for responses.\n This is essentially identical to a :class:`~.ParameterDataType`, however can be handled differently in the final\n application and thus exists as its own class/object.\n\n .. note:: When checking whether an object is a response or a parameter, note that\n :func:`isinstance(obj, ParameterDataType)` will also return true if the object is a\n :class:`ResponseDataType`, since they are derived from each other. Use ``type(obj) is ParameterDataType``\n for a precise check.\n \"\"\"\n"},"input_ids":{"kind":"list like","value":[37811,198,27193,10221,834,198,198,25,16302,25,15638,13534,17,62,29412,198,198,25,36604,25,18261,1366,2099,287,257,15638,13534,9455,11,14161,11,42540,11,2644,198,198,25,7753,25,220,220,220,1366,62,4906,62,26209,13,9078,198,25,41617,25,5045,76,26434,259,198,198,25,4475,25,357,38793,8,220,220,220,220,220,220,220,220,220,13130,2919,1238,198,25,4475,25,357,12957,17613,8,13130,2919,1238,198,198,27193,10221,834,198,198,1174,15269,1174,25,198,220,770,2393,318,2810,366,1921,3180,1,351,8005,34764,56,3963,15529,509,12115,11,198,220,47783,2751,3336,34764,11015,3963,22196,16284,11,34482,3398,1565,5603,25382,5357,376,46144,7473,317,16652,2149,37232,33079,48933,13,628,220,1114,2252,6188,766,38559,24290,2393,326,2058,351,428,6082,13,198,27193,10221,834,198,37811,198,198,2,1330,5888,10392,198,6738,764,7890,62,4906,62,17143,2357,1330,25139,2357,6601,6030,628,198,4871,18261,6601,6030,7,36301,6601,6030,2599,198,220,220,220,37227,198,220,220,220,383,1398,329,9109,13,198,220,220,220,220,220,220,220,770,318,6986,10411,284,257,1058,4871,25,63,93,13,36301,6601,6030,47671,2158,460,307,12118,10338,287,262,2457,198,220,220,220,220,220,220,220,3586,290,4145,7160,355,663,898,1398,14,15252,13,628,220,220,220,11485,3465,3712,1649,10627,1771,281,2134,318,257,2882,393,257,11507,11,3465,326,198,220,220,220,220,220,220,220,220,220,220,220,220,220,1058,20786,25,63,271,39098,7,26801,11,25139,2357,6601,6030,8,63,481,635,1441,2081,611,262,2134,318,257,198,220,220,220,220,220,220,220,220,220,220,220,220,220,1058,4871,25,63,31077,6601,6030,47671,1201,484,389,10944,422,1123,584,13,5765,7559,4906,7,26801,8,318,25139,2357,6601,6030,15506,198,220,220,220,220,220,220,220,220,220,220,220,220,220,329,257,7141,2198,13,198,220,220,220,37227,198],"string":"[\n 37811,\n 198,\n 27193,\n 10221,\n 834,\n 198,\n 198,\n 25,\n 16302,\n 25,\n 15638,\n 13534,\n 17,\n 62,\n 29412,\n 198,\n 198,\n 25,\n 36604,\n 25,\n 18261,\n 1366,\n 2099,\n 287,\n 257,\n 15638,\n 13534,\n 9455,\n 11,\n 14161,\n 11,\n 42540,\n 11,\n 2644,\n 198,\n 198,\n 25,\n 7753,\n 25,\n 220,\n 220,\n 220,\n 1366,\n 62,\n 4906,\n 62,\n 26209,\n 13,\n 9078,\n 198,\n 25,\n 41617,\n 25,\n 5045,\n 76,\n 26434,\n 259,\n 198,\n 198,\n 25,\n 4475,\n 25,\n 357,\n 38793,\n 8,\n 220,\n 220,\n 220,\n 220,\n 220,\n 220,\n 220,\n 220,\n 220,\n 13130,\n 2919,\n 1238,\n 198,\n 25,\n 4475,\n 25,\n 357,\n 12957,\n 17613,\n 8,\n 13130,\n 2919,\n 1238,\n 198,\n 198,\n 27193,\n 10221,\n 834,\n 198,\n 198,\n 1174,\n 15269,\n 1174,\n 25,\n 198,\n 220,\n 770,\n 2393,\n 318,\n 2810,\n 366,\n 1921,\n 3180,\n 1,\n 351,\n 8005,\n 34764,\n 56,\n 3963,\n 15529,\n 509,\n 12115,\n 11,\n 198,\n 220,\n 47783,\n 2751,\n 3336,\n 34764,\n 11015,\n 3963,\n 22196,\n 16284,\n 11,\n 34482,\n 3398,\n 1565,\n 5603,\n 25382,\n 5357,\n 376,\n 46144,\n 7473,\n 317,\n 16652,\n 2149,\n 37232,\n 33079,\n 48933,\n 13,\n 628,\n 220,\n 1114,\n 2252,\n 6188,\n 766,\n 38559,\n 24290,\n 2393,\n 326,\n 2058,\n 351,\n 428,\n 6082,\n 13,\n 198,\n 27193,\n 10221,\n 834,\n 198,\n 37811,\n 198,\n 198,\n 2,\n 1330,\n 5888,\n 10392,\n 198,\n 6738,\n 764,\n 7890,\n 62,\n 4906,\n 62,\n 17143,\n 2357,\n 1330,\n 25139,\n 2357,\n 6601,\n 6030,\n 628,\n 198,\n 4871,\n 18261,\n 6601,\n 6030,\n 7,\n 36301,\n 6601,\n 6030,\n 2599,\n 198,\n 220,\n 220,\n 220,\n 37227,\n 198,\n 220,\n 220,\n 220,\n 383,\n 1398,\n 329,\n 9109,\n 13,\n 198,\n 220,\n 220,\n 220,\n 220,\n 220,\n 220,\n 220,\n 770,\n 318,\n 6986,\n 10411,\n 284,\n 257,\n 1058,\n 4871,\n 25,\n 63,\n 93,\n 13,\n 36301,\n 6601,\n 6030,\n 47671,\n 2158,\n 460,\n 307,\n 12118,\n 10338,\n 287,\n 262,\n 2457,\n 198,\n 220,\n 220,\n 220,\n 220,\n 220,\n 220,\n 220,\n 3586,\n 290,\n 4145,\n 7160,\n 355,\n 663,\n 898,\n 1398,\n 14,\n 15252,\n 13,\n 628,\n 220,\n 220,\n 220,\n 11485,\n 3465,\n 3712,\n 1649,\n 10627,\n 1771,\n 281,\n 2134,\n 318,\n 257,\n 2882,\n 393,\n 257,\n 11507,\n 11,\n 3465,\n 326,\n 198,\n 220,\n 220,\n 220,\n 220,\n 220,\n 220,\n 220,\n 220,\n 220,\n 220,\n 220,\n 220,\n 220,\n 1058,\n 20786,\n 25,\n 63,\n 271,\n 39098,\n 7,\n 26801,\n 11,\n 25139,\n 2357,\n 6601,\n 6030,\n 8,\n 63,\n 481,\n 635,\n 1441,\n 2081,\n 611,\n 262,\n 2134,\n 318,\n 257,\n 198,\n 220,\n 220,\n 220,\n 220,\n 220,\n 220,\n 220,\n 220,\n 220,\n 220,\n 220,\n 220,\n 220,\n 1058,\n 4871,\n 25,\n 63,\n 31077,\n 6601,\n 6030,\n 47671,\n 1201,\n 484,\n 389,\n 10944,\n 422,\n 1123,\n 584,\n 13,\n 5765,\n 7559,\n 4906,\n 7,\n 26801,\n 8,\n 318,\n 25139,\n 2357,\n 6601,\n 6030,\n 15506,\n 198,\n 220,\n 220,\n 220,\n 220,\n 220,\n 220,\n 220,\n 220,\n 220,\n 220,\n 220,\n 220,\n 220,\n 329,\n 257,\n 7141,\n 2198,\n 13,\n 198,\n 220,\n 220,\n 220,\n 37227,\n 198\n]"},"ratio_char_token":{"kind":"number","value":3.801546391752577,"string":"3.801546"},"token_count":{"kind":"number","value":388,"string":"388"}}},{"rowIdx":1213,"cells":{"content":{"kind":"string","value":"# ===============================================================\n# Author: Rodolfo Ferro\n# Email: ferro@cimat.mx\n# Twitter: @FerroRodolfo\n#\n# ABOUT COPYING OR USING PARTIAL INFORMATION:\n# This script was originally created by Rodolfo Ferro, for\n# his workshop in PythonDay Mexico 2018 at CUCEA in Gdl, Mx.\n# Any explicit usage of this script or its contents is granted\n# according to the license provided and its conditions.\n# ===============================================================\n\n# -*- coding: utf-8 -*-\n\nimport requests\nimport pprint\nimport json\n\n\ndef get_json(url, filename):\n \"\"\"\n Download JSON response url for testing.\n \"\"\"\n\n # Get response:\n response = requests.get(url)\n\n # If response's status is 200:\n if response.status_code == requests.codes.ok:\n # Pretty print response:\n pprint.pprint(response.json())\n\n # Save response into a JSON file:\n with open(filename, 'wt') as output:\n output.write(response.text)\n return\n\n\ndef get_prediction(url, filename):\n \"\"\"\n Download JSON response url for prediction.\n \"\"\"\n\n # Set metadata:\n headers = {'Content-type': 'application/json'}\n input_values = {'sepal_length': 6.4,\n 'sepal_width': 3.2,\n 'petal_length': 4.5,\n 'petal_width': 1.5}\n\n # Get response:\n response = requests.post(url, json=input_values, headers=headers)\n\n # If response's status is 200:\n if response.status_code == requests.codes.ok:\n # Pretty print response:\n pprint.pprint(response.json())\n\n # Save response into a JSON file:\n with open(filename, 'wt') as output:\n output.write(response.text)\n return\n\n\nif __name__ == '__main__':\n # Try out our JSON response downloader:\n get_json('http://localhost:5000/api/v0.0', 'response.json')\n get_prediction('http://localhost:5000/api/v0.0/predict', 'response.json')\n"},"input_ids":{"kind":"list like","value":[2,46111,4770,25609,855,198,2,6434,25,6882,4024,78,12880,305,198,2,9570,25,11354,305,31,66,320,265,13,36802,198,2,3009,25,2488,43362,305,27917,4024,78,198,2,198,2,33478,27975,45761,6375,1294,2751,16652,12576,38044,25,198,2,770,4226,373,6198,2727,416,6882,4024,78,12880,305,11,329,198,2,465,20243,287,11361,12393,5828,2864,379,29369,5222,32,287,402,25404,11,337,87,13,198,2,4377,7952,8748,286,428,4226,393,663,10154,318,7520,198,2,1864,284,262,5964,2810,290,663,3403,13,198,2,46111,4770,25609,855,198,198,2,532,9,12,19617,25,3384,69,12,23,532,9,12,198,198,11748,7007,198,11748,279,4798,198,11748,33918,628,198,4299,651,62,17752,7,6371,11,29472,2599,198,220,220,220,37227,198,220,220,220,10472,19449,2882,19016,329,4856,13,198,220,220,220,37227,628,220,220,220,1303,3497,2882,25,198,220,220,220,2882,796,7007,13,1136,7,6371,8,628,220,220,220,1303,1002,2882,338,3722,318,939,25,198,220,220,220,611,2882,13,13376,62,8189,6624,7007,13,40148,13,482,25,198,220,220,220,220,220,220,220,1303,20090,3601,2882,25,198,220,220,220,220,220,220,220,279,4798,13,381,22272,7,26209,13,17752,28955,628,220,220,220,220,220,220,220,1303,12793,2882,656,257,19449,2393,25,198,220,220,220,220,220,220,220,351,1280,7,34345,11,705,46569,11537,355,5072,25,198,220,220,220,220,220,220,220,220,220,220,220,5072,13,13564,7,26209,13,5239,8,198,220,220,220,1441,628,198,4299,651,62,28764,2867,7,6371,11,29472,2599,198,220,220,220,37227,198,220,220,220,10472,19449,2882,19016,329,17724,13,198,220,220,220,37227,628,220,220,220,1303,5345,20150,25,198,220,220,220,24697,796,1391,6,19746,12,4906,10354,705,31438,14,17752,6,92,198,220,220,220,5128,62,27160,796,1391,6,325,18596,62,13664,10354,718,13,19,11,198,220,220,220,220,220,220,220,220,220,220,220,220,220,220,220,220,220,220,220,705,325,18596,62,10394,10354,513,13,17,11,198,220,220,220,220,220,220,220,220,220,220,220,220,220,220,220,220,220,220,220,705,6449,282,62,13664,10354,604,13,20,11,198,220,220,220,220,220,220,220,220,220,220,220,220,220,220,220,220,220,220,220,705,6449,282,62,10394,10354,352,13,20,92,628,220,220,220,1303,3497,2882,25,198,220,220,220,2882,796,7007,13,7353,7,6371,11,33918,28,15414,62,27160,11,24697,28,50145,8,628,220,220,220,1303,1002,2882,338,3722,318,939,25,198,220,220,220,611,2882,13,13376,62,8189,6624,7007,13,40148,13,482,25,198,220,220,220,220,220,220,220,1303,20090,3601,2882,25,198,220,220,220,220,220,220,220,279,4798,13,381,22272,7,26209,13,17752,28955,628,220,220,220,220,220,220,220,1303,12793,2882,656,257,19449,2393,25,198,220,220,220,220,220,220,220,351,1280,7,34345,11,705,46569,11537,355,5072,25,198,220,220,220,220,220,220,220,220,220,220,220,5072,13,13564,7,26209,13,5239,8,198,220,220,220,1441,628,198,361,11593,3672,834,6624,705,834,12417,834,10354,198,220,220,220,1303,9993,503,674,19449,2882,4321,263,25,198,220,220,220,651,62,17752,10786,4023,1378,36750,25,27641,14,15042,14,85,15,13,15,3256,705,26209,13,17752,11537,198,220,220,220,651,62,28764,2867,10786,4023,1378,36750,25,27641,14,15042,14,85,15,13,15,14,79,17407,3256,705,26209,13,17752,11537,198],"string":"[\n 2,\n 46111,\n 4770,\n 25609,\n 855,\n 198,\n 2,\n 6434,\n 25,\n 6882,\n 4024,\n 78,\n 12880,\n 305,\n 198,\n 2,\n 9570,\n 25,\n 11354,\n 305,\n 31,\n 66,\n 320,\n 265,\n 13,\n 36802,\n 198,\n 2,\n 3009,\n 25,\n 2488,\n 43362,\n 305,\n 27917,\n 4024,\n 78,\n 198,\n 2,\n 198,\n 2,\n 33478,\n 27975,\n 45761,\n 6375,\n 1294,\n 2751,\n 16652,\n 12576,\n 38044,\n 25,\n 198,\n 2,\n 770,\n 4226,\n 373,\n 6198,\n 2727,\n 416,\n 6882,\n 4024,\n 78,\n 12880,\n 305,\n 11,\n 329,\n 198,\n 2,\n 465,\n 20243,\n 287,\n 11361,\n 12393,\n 5828,\n 2864,\n 379,\n 29369,\n 5222,\n 32,\n 287,\n 402,\n 25404,\n 11,\n 337,\n 87,\n 13,\n 198,\n 2,\n 4377,\n 7952,\n 8748,\n 286,\n 428,\n 4226,\n 393,\n 663,\n 10154,\n 318,\n 7520,\n 198,\n 2,\n 1864,\n 284,\n 262,\n 5964,\n 2810,\n 290,\n 663,\n 3403,\n 13,\n 198,\n 2,\n 46111,\n 4770,\n 25609,\n 855,\n 198,\n 198,\n 2,\n 532,\n 9,\n 12,\n 19617,\n 25,\n 3384,\n 69,\n 12,\n 23,\n 532,\n 9,\n 12,\n 198,\n 198,\n 11748,\n 7007,\n 198,\n 11748,\n 279,\n 4798,\n 198,\n 11748,\n 33918,\n 628,\n 198,\n 4299,\n 651,\n 62,\n 17752,\n 7,\n 6371,\n 11,\n 29472,\n 2599,\n 198,\n 220,\n 220,\n 220,\n 37227,\n 198,\n 220,\n 220,\n 220,\n 10472,\n 19449,\n 2882,\n 19016,\n 329,\n 4856,\n 13,\n 198,\n 220,\n 220,\n 220,\n 37227,\n 628,\n 220,\n 220,\n 220,\n 1303,\n 3497,\n 2882,\n 25,\n 198,\n 220,\n 220,\n 220,\n 2882,\n 796,\n 7007,\n 13,\n 1136,\n 7,\n 6371,\n 8,\n 628,\n 220,\n 220,\n 220,\n 1303,\n 1002,\n 2882,\n 338,\n 3722,\n 318,\n 939,\n 25,\n 198,\n 220,\n 220,\n 220,\n 611,\n 2882,\n 13,\n 13376,\n 62,\n 8189,\n 6624,\n 7007,\n 13,\n 40148,\n 13,\n 482,\n 25,\n 198,\n 220,\n 220,\n 220,\n 220,\n 220,\n 220,\n 220,\n 1303,\n 20090,\n 3601,\n 2882,\n 25,\n 198,\n 220,\n 220,\n 220,\n 220,\n 220,\n 220,\n 220,\n 279,\n 4798,\n 13,\n 381,\n 22272,\n 7,\n 26209,\n 13,\n 17752,\n 28955,\n 628,\n 220,\n 220,\n 220,\n 220,\n 220,\n 220,\n 220,\n 1303,\n 12793,\n 2882,\n 656,\n 257,\n 19449,\n 2393,\n 25,\n 198,\n 220,\n 220,\n 220,\n 220,\n 220,\n 220,\n 220,\n 351,\n 1280,\n 7,\n 34345,\n 11,\n 705,\n 46569,\n 11537,\n 355,\n 5072,\n 25,\n 198,\n 220,\n 220,\n 220,\n 220,\n 220,\n 220,\n 220,\n 220,\n 220,\n 220,\n 220,\n 5072,\n 13,\n 13564,\n 7,\n 26209,\n 13,\n 5239,\n 8,\n 198,\n 220,\n 220,\n 220,\n 1441,\n 628,\n 198,\n 4299,\n 651,\n 62,\n 28764,\n 2867,\n 7,\n 6371,\n 11,\n 29472,\n 2599,\n 198,\n 220,\n 220,\n 220,\n 37227,\n 198,\n 220,\n 220,\n 220,\n 10472,\n 19449,\n 2882,\n 19016,\n 329,\n 17724,\n 13,\n 198,\n 220,\n 220,\n 220,\n 37227,\n 628,\n 220,\n 220,\n 220,\n 1303,\n 5345,\n 20150,\n 25,\n 198,\n 220,\n 220,\n 220,\n 24697,\n 796,\n 1391,\n 6,\n 19746,\n 12,\n 4906,\n 10354,\n 705,\n 31438,\n 14,\n 17752,\n 6,\n 92,\n 198,\n 220,\n 220,\n 220,\n 5128,\n 62,\n 27160,\n 796,\n 1391,\n 6,\n 325,\n 18596,\n 62,\n 13664,\n 10354,\n 718,\n 13,\n 19,\n 11,\n 198,\n 220,\n 220,\n 220,\n 220,\n 220,\n 220,\n 220,\n 220,\n 220,\n 220,\n 220,\n 220,\n 220,\n 220,\n 220,\n 220,\n 220,\n 220,\n 220,\n 705,\n 325,\n 18596,\n 62,\n 10394,\n 10354,\n 513,\n 13,\n 17,\n 11,\n 198,\n 220,\n 220,\n 220,\n 220,\n 220,\n 220,\n 220,\n 220,\n 220,\n 220,\n 220,\n 220,\n 220,\n 220,\n 220,\n 220,\n 220,\n 220,\n 220,\n 705,\n 6449,\n 282,\n 62,\n 13664,\n 10354,\n 604,\n 13,\n 20,\n 11,\n 198,\n 220,\n 220,\n 220,\n 220,\n 220,\n 220,\n 220,\n 220,\n 220,\n 220,\n 220,\n 220,\n 220,\n 220,\n 220,\n 220,\n 220,\n 220,\n 220,\n 705,\n 6449,\n 282,\n 62,\n 10394,\n 10354,\n 352,\n 13,\n 20,\n 92,\n 628,\n 220,\n 220,\n 220,\n 1303,\n 3497,\n 2882,\n 25,\n 198,\n 220,\n 220,\n 220,\n 2882,\n 796,\n 7007,\n 13,\n 7353,\n 7,\n 6371,\n 11,\n 33918,\n 28,\n 15414,\n 62,\n 27160,\n 11,\n 24697,\n 28,\n 50145,\n 8,\n 628,\n 220,\n 220,\n 220,\n 1303,\n 1002,\n 2882,\n 338,\n 3722,\n 318,\n 939,\n 25,\n 198,\n 220,\n 220,\n 220,\n 611,\n 2882,\n 13,\n 13376,\n 62,\n 8189,\n 6624,\n 7007,\n 13,\n 40148,\n 13,\n 482,\n 25,\n 198,\n 220,\n 220,\n 220,\n 220,\n 220,\n 220,\n 220,\n 1303,\n 20090,\n 3601,\n 2882,\n 25,\n 198,\n 220,\n 220,\n 220,\n 220,\n 220,\n 220,\n 220,\n 279,\n 4798,\n 13,\n 381,\n 22272,\n 7,\n 26209,\n 13,\n 17752,\n 28955,\n 628,\n 220,\n 220,\n 220,\n 220,\n 220,\n 220,\n 220,\n 1303,\n 12793,\n 2882,\n 656,\n 257,\n 19449,\n 2393,\n 25,\n 198,\n 220,\n 220,\n 220,\n 220,\n 220,\n 220,\n 220,\n 351,\n 1280,\n 7,\n 34345,\n 11,\n 705,\n 46569,\n 11537,\n 355,\n 5072,\n 25,\n 198,\n 220,\n 220,\n 220,\n 220,\n 220,\n 220,\n 220,\n 220,\n 220,\n 220,\n 220,\n 5072,\n 13,\n 13564,\n 7,\n 26209,\n 13,\n 5239,\n 8,\n 198,\n 220,\n 220,\n 220,\n 1441,\n 628,\n 198,\n 361,\n 11593,\n 3672,\n 834,\n 6624,\n 705,\n 834,\n 12417,\n 834,\n 10354,\n 198,\n 220,\n 220,\n 220,\n 1303,\n 9993,\n 503,\n 674,\n 19449,\n 2882,\n 4321,\n 263,\n 25,\n 198,\n 220,\n 220,\n 220,\n 651,\n 62,\n 17752,\n 10786,\n 4023,\n 1378,\n 36750,\n 25,\n 27641,\n 14,\n 15042,\n 14,\n 85,\n 15,\n 13,\n 15,\n 3256,\n 705,\n 26209,\n 13,\n 17752,\n 11537,\n 198,\n 220,\n 220,\n 220,\n 651,\n 62,\n 28764,\n 2867,\n 10786,\n 4023,\n 1378,\n 36750,\n 25,\n 27641,\n 14,\n 15042,\n 14,\n 85,\n 15,\n 13,\n 15,\n 14,\n 79,\n 17407,\n 3256,\n 705,\n 26209,\n 13,\n 17752,\n 11537,\n 198\n]"},"ratio_char_token":{"kind":"number","value":2.719495091164095,"string":"2.719495"},"token_count":{"kind":"number","value":713,"string":"713"}}},{"rowIdx":1214,"cells":{"content":{"kind":"string","value":"import pybullet_envs\nfrom stable_baselines3 import SAC_LABER\n\nmodel = SAC_LABER('MlpPolicy', 'HalfCheetahBulletEnv-v0', verbose=1, tensorboard_log=\"results/long_SAC_LABER_HalfCheetahBullet/\")\nmodel.learn(total_timesteps=3000000)\n"},"input_ids":{"kind":"list like","value":[11748,12972,15065,1616,62,268,14259,198,6738,8245,62,12093,20655,18,1330,311,2246,62,48780,1137,198,198,19849,796,311,2246,62,48780,1137,10786,44,34431,36727,3256,705,31305,7376,316,993,33481,1616,4834,85,12,85,15,3256,15942,577,28,16,11,11192,273,3526,62,6404,2625,43420,14,6511,62,50,2246,62,48780,1137,62,31305,7376,316,993,33481,1616,14,4943,198,19849,13,35720,7,23350,62,16514,395,25386,28,18,10535,8,198],"string":"[\n 11748,\n 12972,\n 15065,\n 1616,\n 62,\n 268,\n 14259,\n 198,\n 6738,\n 8245,\n 62,\n 12093,\n 20655,\n 18,\n 1330,\n 311,\n 2246,\n 62,\n 48780,\n 1137,\n 198,\n 198,\n 19849,\n 796,\n 311,\n 2246,\n 62,\n 48780,\n 1137,\n 10786,\n 44,\n 34431,\n 36727,\n 3256,\n 705,\n 31305,\n 7376,\n 316,\n 993,\n 33481,\n 1616,\n 4834,\n 85,\n 12,\n 85,\n 15,\n 3256,\n 15942,\n 577,\n 28,\n 16,\n 11,\n 11192,\n 273,\n 3526,\n 62,\n 6404,\n 2625,\n 43420,\n 14,\n 6511,\n 62,\n 50,\n 2246,\n 62,\n 48780,\n 1137,\n 62,\n 31305,\n 7376,\n 316,\n 993,\n 33481,\n 1616,\n 14,\n 4943,\n 198,\n 19849,\n 13,\n 35720,\n 7,\n 23350,\n 62,\n 16514,\n 395,\n 25386,\n 28,\n 18,\n 10535,\n 8,\n 198\n]"},"ratio_char_token":{"kind":"number","value":2.5164835164835164,"string":"2.516484"},"token_count":{"kind":"number","value":91,"string":"91"}}},{"rowIdx":1215,"cells":{"content":{"kind":"string","value":"# -*- coding: utf-8 -*-\n\"\"\"\ntestapplehealthdata.py: tests for the applehealthdata.py\n\nCopyright (c) 2016 Nicholas J. Radcliffe\nLicence: MIT\n\"\"\"\nfrom __future__ import absolute_import\nfrom __future__ import division\nfrom __future__ import print_function\nfrom __future__ import unicode_literals\n\nimport os\nimport re\nimport shutil\nimport sys\nimport unittest\n\nfrom collections import Counter\n\n\nfrom applehealthdata import (HealthDataExtractor,\n format_freqs, format_value,\n abbreviate, encode)\n\nCLEAN_UP = True\nVERBOSE = False\n\n\ndef get_base_dir():\n \"\"\"\n Return the directory containing this test file,\n which will (normally) be the applyhealthdata directory\n also containing the testdata dir.\n \"\"\"\n return os.path.split(os.path.abspath(__file__))[0]\n\n\ndef get_testdata_dir():\n \"\"\"Return the full path to the testdata directory\"\"\"\n return os.path.join(get_base_dir(), 'testdata')\n\n\ndef get_tmp_dir():\n \"\"\"Return the full path to the tmp directory\"\"\"\n return os.path.join(get_base_dir(), 'tmp')\n\n\ndef remove_any_tmp_dir():\n \"\"\"\n Remove the temporary directory if it exists.\n Returns its location either way.\n \"\"\"\n tmp_dir = get_tmp_dir()\n if os.path.exists(tmp_dir):\n shutil.rmtree(tmp_dir)\n return tmp_dir\n\n\ndef make_tmp_dir():\n \"\"\"\n Remove any existing tmp directory.\n Create empty tmp direcory.\n Return the location of the tmp dir.\n \"\"\"\n tmp_dir = remove_any_tmp_dir()\n os.mkdir(tmp_dir)\n return tmp_dir\n\n\ndef copy_test_data():\n \"\"\"\n Copy the test data export6s3sample.xml from testdata directory\n to tmp directory.\n \"\"\"\n tmp_dir = make_tmp_dir()\n name = 'export6s3sample.xml'\n in_xml_file = os.path.join(get_testdata_dir(), name)\n out_xml_file = os.path.join(get_tmp_dir(), name)\n shutil.copyfile(in_xml_file, out_xml_file)\n return out_xml_file\n\n\n\n\nif __name__ == '__main__':\n unittest.main()\n"},"input_ids":{"kind":"list like","value":[2,532,9,12,19617,25,3384,69,12,23,532,9,12,198,37811,198,9288,18040,13948,7890,13,9078,25,5254,329,262,17180,13948,7890,13,9078,198,198,15269,357,66,8,1584,20320,449,13,5325,33783,198,26656,594,25,17168,198,37811,198,6738,11593,37443,834,1330,4112,62,11748,198,6738,11593,37443,834,1330,7297,198,6738,11593,37443,834,1330,3601,62,8818,198,6738,11593,37443,834,1330,28000,1098,62,17201,874,198,198,11748,28686,198,11748,302,198,11748,4423,346,198,11748,25064,198,11748,555,715,395,198,198,6738,17268,1330,15034,628,198,6738,17180,13948,7890,1330,357,18081,6601,11627,40450,11,198,220,220,220,220,220,220,220,220,220,220,220,220,220,220,220,220,220,220,220,220,220,220,220,220,220,220,220,220,5794,62,19503,48382,11,5794,62,8367,11,198,220,220,220,220,220,220,220,220,220,220,220,220,220,220,220,220,220,220,220,220,220,220,220,220,220,220,220,220,37640,378,11,37773,8,198,198,29931,1565,62,8577,796,6407,198,5959,33,14058,796,10352,628,198,4299,651,62,8692,62,15908,33529,198,220,220,220,37227,198,220,220,220,8229,262,8619,7268,428,1332,2393,11,198,220,220,220,543,481,357,27237,453,8,307,262,4174,13948,7890,8619,198,220,220,220,635,7268,262,1332,7890,26672,13,198,220,220,220,37227,198,220,220,220,1441,28686,13,6978,13,35312,7,418,13,6978,13,397,2777,776,7,834,7753,834,4008,58,15,60,628,198,4299,651,62,9288,7890,62,15908,33529,198,220,220,220,37227,13615,262,1336,3108,284,262,1332,7890,8619,37811,198,220,220,220,1441,28686,13,6978,13,22179,7,1136,62,8692,62,15908,22784,705,9288,7890,11537,628,198,4299,651,62,22065,62,15908,33529,198,220,220,220,37227,13615,262,1336,3108,284,262,45218,8619,37811,198,220,220,220,1441,28686,13,6978,13,22179,7,1136,62,8692,62,15908,22784,705,22065,11537,628,198,4299,4781,62,1092,62,22065,62,15908,33529,198,220,220,220,37227,198,220,220,220,17220,262,8584,8619,611,340,7160,13,198,220,220,220,16409,663,4067,2035,835,13,198,220,220,220,37227,198,220,220,220,45218,62,15908,796,651,62,22065,62,15908,3419,198,220,220,220,611,28686,13,6978,13,1069,1023,7,22065,62,15908,2599,198,220,220,220,220,220,220,220,4423,346,13,81,16762,631,7,22065,62,15908,8,198,220,220,220,1441,45218,62,15908,628,198,4299,787,62,22065,62,15908,33529,198,220,220,220,37227,198,220,220,220,17220,597,4683,45218,8619,13,198,220,220,220,13610,6565,45218,19958,66,652,13,198,220,220,220,8229,262,4067,286,262,45218,26672,13,198,220,220,220,37227,198,220,220,220,45218,62,15908,796,4781,62,1092,62,22065,62,15908,3419,198,220,220,220,28686,13,28015,15908,7,22065,62,15908,8,198,220,220,220,1441,45218,62,15908,628,198,4299,4866,62,9288,62,7890,33529,198,220,220,220,37227,198,220,220,220,17393,262,1332,1366,10784,21,82,18,39873,13,19875,422,1332,7890,8619,198,220,220,220,284,45218,8619,13,198,220,220,220,37227,198,220,220,220,45218,62,15908,796,787,62,22065,62,15908,3419,198,220,220,220,1438,796,705,39344,21,82,18,39873,13,19875,6,198,220,220,220,287,62,19875,62,7753,796,28686,13,6978,13,22179,7,1136,62,9288,7890,62,15908,22784,1438,8,198,220,220,220,503,62,19875,62,7753,796,28686,13,6978,13,22179,7,1136,62,22065,62,15908,22784,1438,8,198,220,220,220,4423,346,13,30073,7753,7,259,62,19875,62,7753,11,503,62,19875,62,7753,8,198,220,220,220,1441,503,62,19875,62,7753,628,628,198,361,11593,3672,834,6624,705,834,12417,834,10354,198,220,220,220,555,715,395,13,12417,3419,198],"string":"[\n 2,\n 532,\n 9,\n 12,\n 19617,\n 25,\n 3384,\n 69,\n 12,\n 23,\n 532,\n 9,\n 12,\n 198,\n 37811,\n 198,\n 9288,\n 18040,\n 13948,\n 7890,\n 13,\n 9078,\n 25,\n 5254,\n 329,\n 262,\n 17180,\n 13948,\n 7890,\n 13,\n 9078,\n 198,\n 198,\n 15269,\n 357,\n 66,\n 8,\n 1584,\n 20320,\n 449,\n 13,\n 5325,\n 33783,\n 198,\n 26656,\n 594,\n 25,\n 17168,\n 198,\n 37811,\n 198,\n 6738,\n 11593,\n 37443,\n 834,\n 1330,\n 4112,\n 62,\n 11748,\n 198,\n 6738,\n 11593,\n 37443,\n 834,\n 1330,\n 7297,\n 198,\n 6738,\n 11593,\n 37443,\n 834,\n 1330,\n 3601,\n 62,\n 8818,\n 198,\n 6738,\n 11593,\n 37443,\n 834,\n 1330,\n 28000,\n 1098,\n 62,\n 17201,\n 874,\n 198,\n 198,\n 11748,\n 28686,\n 198,\n 11748,\n 302,\n 198,\n 11748,\n 4423,\n 346,\n 198,\n 11748,\n 25064,\n 198,\n 11748,\n 555,\n 715,\n 395,\n 198,\n 198,\n 6738,\n 17268,\n 1330,\n 15034,\n 628,\n 198,\n 6738,\n 17180,\n 13948,\n 7890,\n 1330,\n 357,\n 18081,\n 6601,\n 11627,\n 40450,\n 11,\n 198,\n 220,\n 220,\n 220,\n 220,\n 220,\n 220,\n 220,\n 220,\n 220,\n 220,\n 220,\n 220,\n 220,\n 220,\n 220,\n 220,\n 220,\n 220,\n 220,\n 220,\n 220,\n 220,\n 220,\n 220,\n 220,\n 220,\n 220,\n 220,\n 5794,\n 62,\n 19503,\n 48382,\n 11,\n 5794,\n 62,\n 8367,\n 11,\n 198,\n 220,\n 220,\n 220,\n 220,\n 220,\n 220,\n 220,\n 220,\n 220,\n 220,\n 220,\n 220,\n 220,\n 220,\n 220,\n 220,\n 220,\n 220,\n 220,\n 220,\n 220,\n 220,\n 220,\n 220,\n 220,\n 220,\n 220,\n 220,\n 37640,\n 378,\n 11,\n 37773,\n 8,\n 198,\n 198,\n 29931,\n 1565,\n 62,\n 8577,\n 796,\n 6407,\n 198,\n 5959,\n 33,\n 14058,\n 796,\n 10352,\n 628,\n 198,\n 4299,\n 651,\n 62,\n 8692,\n 62,\n 15908,\n 33529,\n 198,\n 220,\n 220,\n 220,\n 37227,\n 198,\n 220,\n 220,\n 220,\n 8229,\n 262,\n 8619,\n 7268,\n 428,\n 1332,\n 2393,\n 11,\n 198,\n 220,\n 220,\n 220,\n 543,\n 481,\n 357,\n 27237,\n 453,\n 8,\n 307,\n 262,\n 4174,\n 13948,\n 7890,\n 8619,\n 198,\n 220,\n 220,\n 220,\n 635,\n 7268,\n 262,\n 1332,\n 7890,\n 26672,\n 13,\n 198,\n 220,\n 220,\n 220,\n 37227,\n 198,\n 220,\n 220,\n 220,\n 1441,\n 28686,\n 13,\n 6978,\n 13,\n 35312,\n 7,\n 418,\n 13,\n 6978,\n 13,\n 397,\n 2777,\n 776,\n 7,\n 834,\n 7753,\n 834,\n 4008,\n 58,\n 15,\n 60,\n 628,\n 198,\n 4299,\n 651,\n 62,\n 9288,\n 7890,\n 62,\n 15908,\n 33529,\n 198,\n 220,\n 220,\n 220,\n 37227,\n 13615,\n 262,\n 1336,\n 3108,\n 284,\n 262,\n 1332,\n 7890,\n 8619,\n 37811,\n 198,\n 220,\n 220,\n 220,\n 1441,\n 28686,\n 13,\n 6978,\n 13,\n 22179,\n 7,\n 1136,\n 62,\n 8692,\n 62,\n 15908,\n 22784,\n 705,\n 9288,\n 7890,\n 11537,\n 628,\n 198,\n 4299,\n 651,\n 62,\n 22065,\n 62,\n 15908,\n 33529,\n 198,\n 220,\n 220,\n 220,\n 37227,\n 13615,\n 262,\n 1336,\n 3108,\n 284,\n 262,\n 45218,\n 8619,\n 37811,\n 198,\n 220,\n 220,\n 220,\n 1441,\n 28686,\n 13,\n 6978,\n 13,\n 22179,\n 7,\n 1136,\n 62,\n 8692,\n 62,\n 15908,\n 22784,\n 705,\n 22065,\n 11537,\n 628,\n 198,\n 4299,\n 4781,\n 62,\n 1092,\n 62,\n 22065,\n 62,\n 15908,\n 33529,\n 198,\n 220,\n 220,\n 220,\n 37227,\n 198,\n 220,\n 220,\n 220,\n 17220,\n 262,\n 8584,\n 8619,\n 611,\n 340,\n 7160,\n 13,\n 198,\n 220,\n 220,\n 220,\n 16409,\n 663,\n 4067,\n 2035,\n 835,\n 13,\n 198,\n 220,\n 220,\n 220,\n 37227,\n 198,\n 220,\n 220,\n 220,\n 45218,\n 62,\n 15908,\n 796,\n 651,\n 62,\n 22065,\n 62,\n 15908,\n 3419,\n 198,\n 220,\n 220,\n 220,\n 611,\n 28686,\n 13,\n 6978,\n 13,\n 1069,\n 1023,\n 7,\n 22065,\n 62,\n 15908,\n 2599,\n 198,\n 220,\n 220,\n 220,\n 220,\n 220,\n 220,\n 220,\n 4423,\n 346,\n 13,\n 81,\n 16762,\n 631,\n 7,\n 22065,\n 62,\n 15908,\n 8,\n 198,\n 220,\n 220,\n 220,\n 1441,\n 45218,\n 62,\n 15908,\n 628,\n 198,\n 4299,\n 787,\n 62,\n 22065,\n 62,\n 15908,\n 33529,\n 198,\n 220,\n 220,\n 220,\n 37227,\n 198,\n 220,\n 220,\n 220,\n 17220,\n 597,\n 4683,\n 45218,\n 8619,\n 13,\n 198,\n 220,\n 220,\n 220,\n 13610,\n 6565,\n 45218,\n 19958,\n 66,\n 652,\n 13,\n 198,\n 220,\n 220,\n 220,\n 8229,\n 262,\n 4067,\n 286,\n 262,\n 45218,\n 26672,\n 13,\n 198,\n 220,\n 220,\n 220,\n 37227,\n 198,\n 220,\n 220,\n 220,\n 45218,\n 62,\n 15908,\n 796,\n 4781,\n 62,\n 1092,\n 62,\n 22065,\n 62,\n 15908,\n 3419,\n 198,\n 220,\n 220,\n 220,\n 28686,\n 13,\n 28015,\n 15908,\n 7,\n 22065,\n 62,\n 15908,\n 8,\n 198,\n 220,\n 220,\n 220,\n 1441,\n 45218,\n 62,\n 15908,\n 628,\n 198,\n 4299,\n 4866,\n 62,\n 9288,\n 62,\n 7890,\n 33529,\n 198,\n 220,\n 220,\n 220,\n 37227,\n 198,\n 220,\n 220,\n 220,\n 17393,\n 262,\n 1332,\n 1366,\n 10784,\n 21,\n 82,\n 18,\n 39873,\n 13,\n 19875,\n 422,\n 1332,\n 7890,\n 8619,\n 198,\n 220,\n 220,\n 220,\n 284,\n 45218,\n 8619,\n 13,\n 198,\n 220,\n 220,\n 220,\n 37227,\n 198,\n 220,\n 220,\n 220,\n 45218,\n 62,\n 15908,\n 796,\n 787,\n 62,\n 22065,\n 62,\n 15908,\n 3419,\n 198,\n 220,\n 220,\n 220,\n 1438,\n 796,\n 705,\n 39344,\n 21,\n 82,\n 18,\n 39873,\n 13,\n 19875,\n 6,\n 198,\n 220,\n 220,\n 220,\n 287,\n 62,\n 19875,\n 62,\n 7753,\n 796,\n 28686,\n 13,\n 6978,\n 13,\n 22179,\n 7,\n 1136,\n 62,\n 9288,\n 7890,\n 62,\n 15908,\n 22784,\n 1438,\n 8,\n 198,\n 220,\n 220,\n 220,\n 503,\n 62,\n 19875,\n 62,\n 7753,\n 796,\n 28686,\n 13,\n 6978,\n 13,\n 22179,\n 7,\n 1136,\n 62,\n 22065,\n 62,\n 15908,\n 22784,\n 1438,\n 8,\n 198,\n 220,\n 220,\n 220,\n 4423,\n 346,\n 13,\n 30073,\n 7753,\n 7,\n 259,\n 62,\n 19875,\n 62,\n 7753,\n 11,\n 503,\n 62,\n 19875,\n 62,\n 7753,\n 8,\n 198,\n 220,\n 220,\n 220,\n 1441,\n 503,\n 62,\n 19875,\n 62,\n 7753,\n 628,\n 628,\n 198,\n 361,\n 11593,\n 3672,\n 834,\n 6624,\n 705,\n 834,\n 12417,\n 834,\n 10354,\n 198,\n 220,\n 220,\n 220,\n 555,\n 715,\n 395,\n 13,\n 12417,\n 3419,\n 198\n]"},"ratio_char_token":{"kind":"number","value":2.610372340425532,"string":"2.610372"},"token_count":{"kind":"number","value":752,"string":"752"}}},{"rowIdx":1216,"cells":{"content":{"kind":"string","value":"import unittest\nfrom datetime import date\n\nfrom controller.books import Book, BookRead\n\n\n\n\nif __name__ == \"__main__\":\n unittest.main()\n"},"input_ids":{"kind":"list like","value":[11748,555,715,395,198,6738,4818,8079,1330,3128,198,198,6738,10444,13,12106,1330,4897,11,4897,5569,628,628,198,361,11593,3672,834,6624,366,834,12417,834,1298,198,220,220,220,555,715,395,13,12417,3419,198],"string":"[\n 11748,\n 555,\n 715,\n 395,\n 198,\n 6738,\n 4818,\n 8079,\n 1330,\n 3128,\n 198,\n 198,\n 6738,\n 10444,\n 13,\n 12106,\n 1330,\n 4897,\n 11,\n 4897,\n 5569,\n 628,\n 628,\n 198,\n 361,\n 11593,\n 3672,\n 834,\n 6624,\n 366,\n 834,\n 12417,\n 834,\n 1298,\n 198,\n 220,\n 220,\n 220,\n 555,\n 715,\n 395,\n 13,\n 12417,\n 3419,\n 198\n]"},"ratio_char_token":{"kind":"number","value":3.066666666666667,"string":"3.066667"},"token_count":{"kind":"number","value":45,"string":"45"}}},{"rowIdx":1217,"cells":{"content":{"kind":"string","value":"from ixnetwork_restpy.base import Base\nfrom ixnetwork_restpy.files import Files\n\n"},"input_ids":{"kind":"list like","value":[6738,220,844,27349,62,2118,9078,13,8692,1330,7308,198,6738,220,844,27349,62,2118,9078,13,16624,1330,13283,628],"string":"[\n 6738,\n 220,\n 844,\n 27349,\n 62,\n 2118,\n 9078,\n 13,\n 8692,\n 1330,\n 7308,\n 198,\n 6738,\n 220,\n 844,\n 27349,\n 62,\n 2118,\n 9078,\n 13,\n 16624,\n 1330,\n 13283,\n 628\n]"},"ratio_char_token":{"kind":"number","value":3.375,"string":"3.375"},"token_count":{"kind":"number","value":24,"string":"24"}}},{"rowIdx":1218,"cells":{"content":{"kind":"string","value":"import pytest\n\n\n@pytest.yield_fixture(scope=\"module\")\n\n\n@pytest.yield_fixture(scope=\"module\")\n\n\n@pytest.yield_fixture(scope=\"module\")\n"},"input_ids":{"kind":"list like","value":[11748,12972,9288,628,198,31,9078,9288,13,88,1164,62,69,9602,7,29982,2625,21412,4943,628,198,31,9078,9288,13,88,1164,62,69,9602,7,29982,2625,21412,4943,628,198,31,9078,9288,13,88,1164,62,69,9602,7,29982,2625,21412,4943,198],"string":"[\n 11748,\n 12972,\n 9288,\n 628,\n 198,\n 31,\n 9078,\n 9288,\n 13,\n 88,\n 1164,\n 62,\n 69,\n 9602,\n 7,\n 29982,\n 2625,\n 21412,\n 4943,\n 628,\n 198,\n 31,\n 9078,\n 9288,\n 13,\n 88,\n 1164,\n 62,\n 69,\n 9602,\n 7,\n 29982,\n 2625,\n 21412,\n 4943,\n 628,\n 198,\n 31,\n 9078,\n 9288,\n 13,\n 88,\n 1164,\n 62,\n 69,\n 9602,\n 7,\n 29982,\n 2625,\n 21412,\n 4943,\n 198\n]"},"ratio_char_token":{"kind":"number","value":2.576923076923077,"string":"2.576923"},"token_count":{"kind":"number","value":52,"string":"52"}}},{"rowIdx":1219,"cells":{"content":{"kind":"string","value":"import threading\r\nimport os.path\r\nimport time\r\nfrom blueThread import MainBlue\r\n\r\n \r\n# class myThread (threading.Thread):\r\n# def __init__(self, threadID, name, counter):\r\n# threading.Thread.__init__(self)\r\n# self.threadID = threadID\r\n# self.name = name\r\n# self.counter = counter\r\n# def run(self):\r\n# print(\"Starting \" + self.name)\r\n# print_time(self.name, 5, self.counter)\r\n# print(\"Exiting \" + self.name)\r\n \r\nrun = True\r\nfoo = [False]\r\nfileName = \"\"\r\ndef LookForFile(strToFind, path):\r\n \"\"\"\r\n function repeatedly look for a file\r\n \"\"\"\r\n while run:\r\n MainBlue(foo)\r\n time.sleep(1)\r\n print(\"exiting file thread!\")\r\n\r\ndef LookForStop(strToFind, path):\r\n \"\"\"\r\n function repeatedly look for a file\r\n \"\"\"\r\n global run\r\n count = 0\r\n filePath = path + strToFind\r\n while run:\r\n count += 1\r\n if os.path.exists(filePath):\r\n run = False\r\n print(\"{0} FOUND {1} at {2} [{3}]\".format(t2.getName(), strToFind, filePath, count))\r\n else:\r\n print(\"{0} not found {1} at {2} [{3}]\".format(t2.getName(), strToFind, filePath, count))\r\n time.sleep(1)\r\n print(\"exiting stop thread!\")\r\n \r\nif __name__ == \"__main__\":\r\n\r\n # creating thread\r\n t1 = threading.Thread(target=LookForFile, name=\"THREAD_Finder\", args=(\"rain\",\"../\"), daemon=True)\r\n # t2 = threading.Thread(name=\"THREAD_Stopper\", target=LookForStop, args=(\"stop\",\"../\"), daemon=True)\r\n \r\n # starting thread 1\r\n t1.start()\r\n # starting thread 2\r\n # t2.start()\r\n # while run:\r\n # print(\"doing nothing...\")\r\n # time.sleep(10)\r\n input(\"Press Enter to flip foo\")\r\n if foo[0]:\r\n foo[0] = False\r\n else:\r\n foo[0] = True\r\n input(\"Press Enter to exit\")\r\n run = False\r\n\r\n # wait until thread 1 is completely executed\r\n t1.join()\r\n # wait until thread 2 is completely executed\r\n # t2.join()\r\n \r\n # both threads completely executed\r\n print(\"Done!\")"},"input_ids":{"kind":"list like","value":[11748,4704,278,201,198,11748,28686,13,6978,201,198,11748,640,201,198,6738,4171,16818,1330,8774,14573,201,198,201,198,220,220,201,198,2,1398,616,16818,357,16663,278,13,16818,2599,201,198,2,220,220,825,11593,15003,834,7,944,11,4704,2389,11,1438,11,3753,2599,201,198,2,220,220,220,220,4704,278,13,16818,13,834,15003,834,7,944,8,201,198,2,220,220,220,220,2116,13,16663,2389,796,4704,2389,201,198,2,220,220,220,220,2116,13,3672,796,1438,201,198,2,220,220,220,220,2116,13,24588,796,3753,201,198,2,220,220,825,1057,7,944,2599,201,198,2,220,220,220,220,3601,7203,22851,366,1343,2116,13,3672,8,201,198,2,220,220,220,220,3601,62,2435,7,944,13,3672,11,642,11,2116,13,24588,8,201,198,2,220,220,220,220,3601,7203,3109,1780,366,1343,2116,13,3672,8,201,198,220,220,220,220,201,198,5143,796,6407,201,198,21943,796,685,25101,60,201,198,7753,5376,796,13538,201,198,4299,6803,1890,8979,7,2536,2514,16742,11,3108,2599,201,198,220,220,220,37227,201,198,220,220,220,2163,7830,804,329,257,2393,201,198,220,220,220,37227,201,198,220,220,220,981,1057,25,201,198,220,220,220,220,220,8774,14573,7,21943,8,201,198,220,220,220,220,220,640,13,42832,7,16,8,201,198,220,220,220,3601,7203,1069,1780,2393,4704,2474,8,201,198,201,198,4299,6803,1890,19485,7,2536,2514,16742,11,3108,2599,201,198,220,220,220,37227,201,198,220,220,220,2163,7830,804,329,257,2393,201,198,220,220,220,37227,201,198,220,220,220,3298,1057,201,198,220,220,220,954,796,657,201,198,220,220,220,2393,15235,796,3108,1343,965,2514,16742,201,198,220,220,220,981,1057,25,201,198,220,220,220,220,220,954,15853,352,201,198,220,220,220,220,220,611,28686,13,6978,13,1069,1023,7,7753,15235,2599,201,198,220,220,220,220,220,220,220,1057,796,10352,201,198,220,220,220,220,220,220,220,3601,7203,90,15,92,376,15919,1391,16,92,379,1391,17,92,685,90,18,92,60,1911,18982,7,83,17,13,1136,5376,22784,965,2514,16742,11,2393,15235,11,954,4008,201,198,220,220,220,220,220,2073,25,201,198,220,220,220,220,220,220,220,3601,7203,90,15,92,407,1043,1391,16,92,379,1391,17,92,685,90,18,92,60,1911,18982,7,83,17,13,1136,5376,22784,965,2514,16742,11,2393,15235,11,954,4008,201,198,220,220,220,220,220,640,13,42832,7,16,8,201,198,220,220,220,3601,7203,1069,1780,2245,4704,2474,8,201,198,220,220,201,198,361,11593,3672,834,6624,366,834,12417,834,1298,201,198,201,198,220,220,220,1303,4441,4704,201,198,220,220,220,256,16,796,4704,278,13,16818,7,16793,28,8567,1890,8979,11,1438,2625,4221,15675,62,37,5540,1600,26498,28,7203,3201,2430,40720,12340,33386,28,17821,8,201,198,220,220,220,1303,256,17,796,4704,278,13,16818,7,3672,2625,4221,15675,62,1273,78,2848,1600,2496,28,8567,1890,19485,11,26498,28,7203,11338,2430,40720,12340,33386,28,17821,8,201,198,220,220,201,198,220,220,220,1303,3599,4704,352,201,198,220,220,220,256,16,13,9688,3419,201,198,220,220,220,1303,3599,4704,362,201,198,220,220,220,1303,256,17,13,9688,3419,201,198,220,220,220,1303,981,1057,25,201,198,220,220,220,1303,220,220,3601,7203,19631,2147,9313,8,201,198,220,220,220,1303,220,220,640,13,42832,7,940,8,201,198,220,220,220,5128,7203,13800,6062,284,14283,22944,4943,201,198,220,220,220,611,22944,58,15,5974,201,198,220,220,220,220,220,22944,58,15,60,796,10352,201,198,220,220,220,2073,25,201,198,220,220,220,220,220,22944,58,15,60,796,6407,201,198,220,220,220,5128,7203,13800,6062,284,8420,4943,201,198,220,220,220,1057,796,10352,201,198,201,198,220,220,220,1303,4043,1566,4704,352,318,3190,10945,201,198,220,220,220,256,16,13,22179,3419,201,198,220,220,220,1303,4043,1566,4704,362,318,3190,10945,201,198,220,220,220,1303,256,17,13,22179,3419,201,198,220,220,201,198,220,220,220,1303,1111,14390,3190,10945,201,198,220,220,220,3601,7203,45677,2474,8],"string":"[\n 11748,\n 4704,\n 278,\n 201,\n 198,\n 11748,\n 28686,\n 13,\n 6978,\n 201,\n 198,\n 11748,\n 640,\n 201,\n 198,\n 6738,\n 4171,\n 16818,\n 1330,\n 8774,\n 14573,\n 201,\n 198,\n 201,\n 198,\n 220,\n 220,\n 201,\n 198,\n 2,\n 1398,\n 616,\n 16818,\n 357,\n 16663,\n 278,\n 13,\n 16818,\n 2599,\n 201,\n 198,\n 2,\n 220,\n 220,\n 825,\n 11593,\n 15003,\n 834,\n 7,\n 944,\n 11,\n 4704,\n 2389,\n 11,\n 1438,\n 11,\n 3753,\n 2599,\n 201,\n 198,\n 2,\n 220,\n 220,\n 220,\n 220,\n 4704,\n 278,\n 13,\n 16818,\n 13,\n 834,\n 15003,\n 834,\n 7,\n 944,\n 8,\n 201,\n 198,\n 2,\n 220,\n 220,\n 220,\n 220,\n 2116,\n 13,\n 16663,\n 2389,\n 796,\n 4704,\n 2389,\n 201,\n 198,\n 2,\n 220,\n 220,\n 220,\n 220,\n 2116,\n 13,\n 3672,\n 796,\n 1438,\n 201,\n 198,\n 2,\n 220,\n 220,\n 220,\n 220,\n 2116,\n 13,\n 24588,\n 796,\n 3753,\n 201,\n 198,\n 2,\n 220,\n 220,\n 825,\n 1057,\n 7,\n 944,\n 2599,\n 201,\n 198,\n 2,\n 220,\n 220,\n 220,\n 220,\n 3601,\n 7203,\n 22851,\n 366,\n 1343,\n 2116,\n 13,\n 3672,\n 8,\n 201,\n 198,\n 2,\n 220,\n 220,\n 220,\n 220,\n 3601,\n 62,\n 2435,\n 7,\n 944,\n 13,\n 3672,\n 11,\n 642,\n 11,\n 2116,\n 13,\n 24588,\n 8,\n 201,\n 198,\n 2,\n 220,\n 220,\n 220,\n 220,\n 3601,\n 7203,\n 3109,\n 1780,\n 366,\n 1343,\n 2116,\n 13,\n 3672,\n 8,\n 201,\n 198,\n 220,\n 220,\n 220,\n 220,\n 201,\n 198,\n 5143,\n 796,\n 6407,\n 201,\n 198,\n 21943,\n 796,\n 685,\n 25101,\n 60,\n 201,\n 198,\n 7753,\n 5376,\n 796,\n 13538,\n 201,\n 198,\n 4299,\n 6803,\n 1890,\n 8979,\n 7,\n 2536,\n 2514,\n 16742,\n 11,\n 3108,\n 2599,\n 201,\n 198,\n 220,\n 220,\n 220,\n 37227,\n 201,\n 198,\n 220,\n 220,\n 220,\n 2163,\n 7830,\n 804,\n 329,\n 257,\n 2393,\n 201,\n 198,\n 220,\n 220,\n 220,\n 37227,\n 201,\n 198,\n 220,\n 220,\n 220,\n 981,\n 1057,\n 25,\n 201,\n 198,\n 220,\n 220,\n 220,\n 220,\n 220,\n 8774,\n 14573,\n 7,\n 21943,\n 8,\n 201,\n 198,\n 220,\n 220,\n 220,\n 220,\n 220,\n 640,\n 13,\n 42832,\n 7,\n 16,\n 8,\n 201,\n 198,\n 220,\n 220,\n 220,\n 3601,\n 7203,\n 1069,\n 1780,\n 2393,\n 4704,\n 2474,\n 8,\n 201,\n 198,\n 201,\n 198,\n 4299,\n 6803,\n 1890,\n 19485,\n 7,\n 2536,\n 2514,\n 16742,\n 11,\n 3108,\n 2599,\n 201,\n 198,\n 220,\n 220,\n 220,\n 37227,\n 201,\n 198,\n 220,\n 220,\n 220,\n 2163,\n 7830,\n 804,\n 329,\n 257,\n 2393,\n 201,\n 198,\n 220,\n 220,\n 220,\n 37227,\n 201,\n 198,\n 220,\n 220,\n 220,\n 3298,\n 1057,\n 201,\n 198,\n 220,\n 220,\n 220,\n 954,\n 796,\n 657,\n 201,\n 198,\n 220,\n 220,\n 220,\n 2393,\n 15235,\n 796,\n 3108,\n 1343,\n 965,\n 2514,\n 16742,\n 201,\n 198,\n 220,\n 220,\n 220,\n 981,\n 1057,\n 25,\n 201,\n 198,\n 220,\n 220,\n 220,\n 220,\n 220,\n 954,\n 15853,\n 352,\n 201,\n 198,\n 220,\n 220,\n 220,\n 220,\n 220,\n 611,\n 28686,\n 13,\n 6978,\n 13,\n 1069,\n 1023,\n 7,\n 7753,\n 15235,\n 2599,\n 201,\n 198,\n 220,\n 220,\n 220,\n 220,\n 220,\n 220,\n 220,\n 1057,\n 796,\n 10352,\n 201,\n 198,\n 220,\n 220,\n 220,\n 220,\n 220,\n 220,\n 220,\n 3601,\n 7203,\n 90,\n 15,\n 92,\n 376,\n 15919,\n 1391,\n 16,\n 92,\n 379,\n 1391,\n 17,\n 92,\n 685,\n 90,\n 18,\n 92,\n 60,\n 1911,\n 18982,\n 7,\n 83,\n 17,\n 13,\n 1136,\n 5376,\n 22784,\n 965,\n 2514,\n 16742,\n 11,\n 2393,\n 15235,\n 11,\n 954,\n 4008,\n 201,\n 198,\n 220,\n 220,\n 220,\n 220,\n 220,\n 2073,\n 25,\n 201,\n 198,\n 220,\n 220,\n 220,\n 220,\n 220,\n 220,\n 220,\n 3601,\n 7203,\n 90,\n 15,\n 92,\n 407,\n 1043,\n 1391,\n 16,\n 92,\n 379,\n 1391,\n 17,\n 92,\n 685,\n 90,\n 18,\n 92,\n 60,\n 1911,\n 18982,\n 7,\n 83,\n 17,\n 13,\n 1136,\n 5376,\n 22784,\n 965,\n 2514,\n 16742,\n 11,\n 2393,\n 15235,\n 11,\n 954,\n 4008,\n 201,\n 198,\n 220,\n 220,\n 220,\n 220,\n 220,\n 640,\n 13,\n 42832,\n 7,\n 16,\n 8,\n 201,\n 198,\n 220,\n 220,\n 220,\n 3601,\n 7203,\n 1069,\n 1780,\n 2245,\n 4704,\n 2474,\n 8,\n 201,\n 198,\n 220,\n 220,\n 201,\n 198,\n 361,\n 11593,\n 3672,\n 834,\n 6624,\n 366,\n 834,\n 12417,\n 834,\n 1298,\n 201,\n 198,\n 201,\n 198,\n 220,\n 220,\n 220,\n 1303,\n 4441,\n 4704,\n 201,\n 198,\n 220,\n 220,\n 220,\n 256,\n 16,\n 796,\n 4704,\n 278,\n 13,\n 16818,\n 7,\n 16793,\n 28,\n 8567,\n 1890,\n 8979,\n 11,\n 1438,\n 2625,\n 4221,\n 15675,\n 62,\n 37,\n 5540,\n 1600,\n 26498,\n 28,\n 7203,\n 3201,\n 2430,\n 40720,\n 12340,\n 33386,\n 28,\n 17821,\n 8,\n 201,\n 198,\n 220,\n 220,\n 220,\n 1303,\n 256,\n 17,\n 796,\n 4704,\n 278,\n 13,\n 16818,\n 7,\n 3672,\n 2625,\n 4221,\n 15675,\n 62,\n 1273,\n 78,\n 2848,\n 1600,\n 2496,\n 28,\n 8567,\n 1890,\n 19485,\n 11,\n 26498,\n 28,\n 7203,\n 11338,\n 2430,\n 40720,\n 12340,\n 33386,\n 28,\n 17821,\n 8,\n 201,\n 198,\n 220,\n 220,\n 201,\n 198,\n 220,\n 220,\n 220,\n 1303,\n 3599,\n 4704,\n 352,\n 201,\n 198,\n 220,\n 220,\n 220,\n 256,\n 16,\n 13,\n 9688,\n 3419,\n 201,\n 198,\n 220,\n 220,\n 220,\n 1303,\n 3599,\n 4704,\n 362,\n 201,\n 198,\n 220,\n 220,\n 220,\n 1303,\n 256,\n 17,\n 13,\n 9688,\n 3419,\n 201,\n 198,\n 220,\n 220,\n 220,\n 1303,\n 981,\n 1057,\n 25,\n 201,\n 198,\n 220,\n 220,\n 220,\n 1303,\n 220,\n 220,\n 3601,\n 7203,\n 19631,\n 2147,\n 9313,\n 8,\n 201,\n 198,\n 220,\n 220,\n 220,\n 1303,\n 220,\n 220,\n 640,\n 13,\n 42832,\n 7,\n 940,\n 8,\n 201,\n 198,\n 220,\n 220,\n 220,\n 5128,\n 7203,\n 13800,\n 6062,\n 284,\n 14283,\n 22944,\n 4943,\n 201,\n 198,\n 220,\n 220,\n 220,\n 611,\n 22944,\n 58,\n 15,\n 5974,\n 201,\n 198,\n 220,\n 220,\n 220,\n 220,\n 220,\n 22944,\n 58,\n 15,\n 60,\n 796,\n 10352,\n 201,\n 198,\n 220,\n 220,\n 220,\n 2073,\n 25,\n 201,\n 198,\n 220,\n 220,\n 220,\n 220,\n 220,\n 22944,\n 58,\n 15,\n 60,\n 796,\n 6407,\n 201,\n 198,\n 220,\n 220,\n 220,\n 5128,\n 7203,\n 13800,\n 6062,\n 284,\n 8420,\n 4943,\n 201,\n 198,\n 220,\n 220,\n 220,\n 1057,\n 796,\n 10352,\n 201,\n 198,\n 201,\n 198,\n 220,\n 220,\n 220,\n 1303,\n 4043,\n 1566,\n 4704,\n 352,\n 318,\n 3190,\n 10945,\n 201,\n 198,\n 220,\n 220,\n 220,\n 256,\n 16,\n 13,\n 22179,\n 3419,\n 201,\n 198,\n 220,\n 220,\n 220,\n 1303,\n 4043,\n 1566,\n 4704,\n 362,\n 318,\n 3190,\n 10945,\n 201,\n 198,\n 220,\n 220,\n 220,\n 1303,\n 256,\n 17,\n 13,\n 22179,\n 3419,\n 201,\n 198,\n 220,\n 220,\n 201,\n 198,\n 220,\n 220,\n 220,\n 1303,\n 1111,\n 14390,\n 3190,\n 10945,\n 201,\n 198,\n 220,\n 220,\n 220,\n 3601,\n 7203,\n 45677,\n 2474,\n 8\n]"},"ratio_char_token":{"kind":"number","value":2.2995337995337994,"string":"2.299534"},"token_count":{"kind":"number","value":858,"string":"858"}}},{"rowIdx":1220,"cells":{"content":{"kind":"string","value":"import time\nfrom datetime import datetime\nfrom datetime import timedelta\nfrom uuid import uuid4 as uuid\n\nfrom activitystreams import parse\n\nfrom dino import environ\nfrom dino.auth.redis import AuthRedis\nfrom dino.cache.redis import CacheRedis\nfrom dino.config import ApiActions, RedisKeys\nfrom dino.config import ConfigKeys\nfrom dino.config import SessionKeys\nfrom dino.config import UserKeys\nfrom dino.db.rdbms.handler import DatabaseRdbms\nfrom dino.environ import ConfigDict\nfrom dino.environ import GNEnvironment\nfrom dino.exceptions import ChannelExistsException\nfrom dino.exceptions import ChannelNameExistsException\nfrom dino.exceptions import EmptyChannelNameException\nfrom dino.exceptions import EmptyRoomNameException\nfrom dino.exceptions import InvalidAclTypeException\nfrom dino.exceptions import InvalidApiActionException\nfrom dino.exceptions import NoSuchChannelException\nfrom dino.exceptions import NoSuchRoomException\nfrom dino.exceptions import NoSuchUserException\nfrom dino.exceptions import RoomExistsException\nfrom dino.exceptions import RoomNameExistsForChannelException\nfrom dino.exceptions import UserExistsException\nfrom dino.exceptions import ValidationException\nfrom dino.validation.acl import AclDisallowValidator\nfrom dino.validation.acl import AclIsAdminValidator\nfrom dino.validation.acl import AclIsSuperUserValidator\nfrom dino.validation.acl import AclRangeValidator\nfrom dino.validation.acl import AclSameChannelValidator\nfrom dino.validation.acl import AclSameRoomValidator\nfrom dino.validation.acl import AclStrInCsvValidator\nfrom test.base import BaseTest\n\n"},"input_ids":{"kind":"list like","value":[11748,640,198,6738,4818,8079,1330,4818,8079,198,6738,4818,8079,1330,28805,12514,198,6738,334,27112,1330,334,27112,19,355,334,27112,198,198,6738,3842,5532,82,1330,21136,198,198,6738,288,2879,1330,551,2268,198,6738,288,2879,13,18439,13,445,271,1330,26828,7738,271,198,6738,288,2879,13,23870,13,445,271,1330,34088,7738,271,198,6738,288,2879,13,11250,1330,5949,72,32,2733,11,2297,271,40729,198,6738,288,2879,13,11250,1330,17056,40729,198,6738,288,2879,13,11250,1330,23575,40729,198,6738,288,2879,13,11250,1330,11787,40729,198,6738,288,2879,13,9945,13,4372,65,907,13,30281,1330,24047,49,9945,907,198,6738,288,2879,13,268,2268,1330,17056,35,713,198,6738,288,2879,13,268,2268,1330,15484,31441,198,6738,288,2879,13,1069,11755,1330,11102,3109,1023,16922,198,6738,288,2879,13,1069,11755,1330,11102,5376,3109,1023,16922,198,6738,288,2879,13,1069,11755,1330,33523,29239,5376,16922,198,6738,288,2879,13,1069,11755,1330,33523,41178,5376,16922,198,6738,288,2879,13,1069,11755,1330,17665,32,565,6030,16922,198,6738,288,2879,13,1069,11755,1330,17665,32,14415,12502,16922,198,6738,288,2879,13,1069,11755,1330,1400,16678,29239,16922,198,6738,288,2879,13,1069,11755,1330,1400,16678,41178,16922,198,6738,288,2879,13,1069,11755,1330,1400,16678,12982,16922,198,6738,288,2879,13,1069,11755,1330,10096,3109,1023,16922,198,6738,288,2879,13,1069,11755,1330,10096,5376,3109,1023,1890,29239,16922,198,6738,288,2879,13,1069,11755,1330,11787,3109,1023,16922,198,6738,288,2879,13,1069,11755,1330,3254,24765,16922,198,6738,288,2879,13,12102,341,13,37779,1330,317,565,7279,12154,47139,1352,198,6738,288,2879,13,12102,341,13,37779,1330,317,565,3792,46787,47139,1352,198,6738,288,2879,13,12102,341,13,37779,1330,317,565,3792,12442,12982,47139,1352,198,6738,288,2879,13,12102,341,13,37779,1330,317,565,17257,47139,1352,198,6738,288,2879,13,12102,341,13,37779,1330,317,565,30556,29239,47139,1352,198,6738,288,2879,13,12102,341,13,37779,1330,317,565,30556,41178,47139,1352,198,6738,288,2879,13,12102,341,13,37779,1330,317,565,13290,818,34,21370,47139,1352,198,6738,1332,13,8692,1330,7308,14402,628],"string":"[\n 11748,\n 640,\n 198,\n 6738,\n 4818,\n 8079,\n 1330,\n 4818,\n 8079,\n 198,\n 6738,\n 4818,\n 8079,\n 1330,\n 28805,\n 12514,\n 198,\n 6738,\n 334,\n 27112,\n 1330,\n 334,\n 27112,\n 19,\n 355,\n 334,\n 27112,\n 198,\n 198,\n 6738,\n 3842,\n 5532,\n 82,\n 1330,\n 21136,\n 198,\n 198,\n 6738,\n 288,\n 2879,\n 1330,\n 551,\n 2268,\n 198,\n 6738,\n 288,\n 2879,\n 13,\n 18439,\n 13,\n 445,\n 271,\n 1330,\n 26828,\n 7738,\n 271,\n 198,\n 6738,\n 288,\n 2879,\n 13,\n 23870,\n 13,\n 445,\n 271,\n 1330,\n 34088,\n 7738,\n 271,\n 198,\n 6738,\n 288,\n 2879,\n 13,\n 11250,\n 1330,\n 5949,\n 72,\n 32,\n 2733,\n 11,\n 2297,\n 271,\n 40729,\n 198,\n 6738,\n 288,\n 2879,\n 13,\n 11250,\n 1330,\n 17056,\n 40729,\n 198,\n 6738,\n 288,\n 2879,\n 13,\n 11250,\n 1330,\n 23575,\n 40729,\n 198,\n 6738,\n 288,\n 2879,\n 13,\n 11250,\n 1330,\n 11787,\n 40729,\n 198,\n 6738,\n 288,\n 2879,\n 13,\n 9945,\n 13,\n 4372,\n 65,\n 907,\n 13,\n 30281,\n 1330,\n 24047,\n 49,\n 9945,\n 907,\n 198,\n 6738,\n 288,\n 2879,\n 13,\n 268,\n 2268,\n 1330,\n 17056,\n 35,\n 713,\n 198,\n 6738,\n 288,\n 2879,\n 13,\n 268,\n 2268,\n 1330,\n 15484,\n 31441,\n 198,\n 6738,\n 288,\n 2879,\n 13,\n 1069,\n 11755,\n 1330,\n 11102,\n 3109,\n 1023,\n 16922,\n 198,\n 6738,\n 288,\n 2879,\n 13,\n 1069,\n 11755,\n 1330,\n 11102,\n 5376,\n 3109,\n 1023,\n 16922,\n 198,\n 6738,\n 288,\n 2879,\n 13,\n 1069,\n 11755,\n 1330,\n 33523,\n 29239,\n 5376,\n 16922,\n 198,\n 6738,\n 288,\n 2879,\n 13,\n 1069,\n 11755,\n 1330,\n 33523,\n 41178,\n 5376,\n 16922,\n 198,\n 6738,\n 288,\n 2879,\n 13,\n 1069,\n 11755,\n 1330,\n 17665,\n 32,\n 565,\n 6030,\n 16922,\n 198,\n 6738,\n 288,\n 2879,\n 13,\n 1069,\n 11755,\n 1330,\n 17665,\n 32,\n 14415,\n 12502,\n 16922,\n 198,\n 6738,\n 288,\n 2879,\n 13,\n 1069,\n 11755,\n 1330,\n 1400,\n 16678,\n 29239,\n 16922,\n 198,\n 6738,\n 288,\n 2879,\n 13,\n 1069,\n 11755,\n 1330,\n 1400,\n 16678,\n 41178,\n 16922,\n 198,\n 6738,\n 288,\n 2879,\n 13,\n 1069,\n 11755,\n 1330,\n 1400,\n 16678,\n 12982,\n 16922,\n 198,\n 6738,\n 288,\n 2879,\n 13,\n 1069,\n 11755,\n 1330,\n 10096,\n 3109,\n 1023,\n 16922,\n 198,\n 6738,\n 288,\n 2879,\n 13,\n 1069,\n 11755,\n 1330,\n 10096,\n 5376,\n 3109,\n 1023,\n 1890,\n 29239,\n 16922,\n 198,\n 6738,\n 288,\n 2879,\n 13,\n 1069,\n 11755,\n 1330,\n 11787,\n 3109,\n 1023,\n 16922,\n 198,\n 6738,\n 288,\n 2879,\n 13,\n 1069,\n 11755,\n 1330,\n 3254,\n 24765,\n 16922,\n 198,\n 6738,\n 288,\n 2879,\n 13,\n 12102,\n 341,\n 13,\n 37779,\n 1330,\n 317,\n 565,\n 7279,\n 12154,\n 47139,\n 1352,\n 198,\n 6738,\n 288,\n 2879,\n 13,\n 12102,\n 341,\n 13,\n 37779,\n 1330,\n 317,\n 565,\n 3792,\n 46787,\n 47139,\n 1352,\n 198,\n 6738,\n 288,\n 2879,\n 13,\n 12102,\n 341,\n 13,\n 37779,\n 1330,\n 317,\n 565,\n 3792,\n 12442,\n 12982,\n 47139,\n 1352,\n 198,\n 6738,\n 288,\n 2879,\n 13,\n 12102,\n 341,\n 13,\n 37779,\n 1330,\n 317,\n 565,\n 17257,\n 47139,\n 1352,\n 198,\n 6738,\n 288,\n 2879,\n 13,\n 12102,\n 341,\n 13,\n 37779,\n 1330,\n 317,\n 565,\n 30556,\n 29239,\n 47139,\n 1352,\n 198,\n 6738,\n 288,\n 2879,\n 13,\n 12102,\n 341,\n 13,\n 37779,\n 1330,\n 317,\n 565,\n 30556,\n 41178,\n 47139,\n 1352,\n 198,\n 6738,\n 288,\n 2879,\n 13,\n 12102,\n 341,\n 13,\n 37779,\n 1330,\n 317,\n 565,\n 13290,\n 818,\n 34,\n 21370,\n 47139,\n 1352,\n 198,\n 6738,\n 1332,\n 13,\n 8692,\n 1330,\n 7308,\n 14402,\n 628\n]"},"ratio_char_token":{"kind":"number","value":3.674364896073903,"string":"3.674365"},"token_count":{"kind":"number","value":433,"string":"433"}}},{"rowIdx":1221,"cells":{"content":{"kind":"string","value":"\"\"\"migrate workbench state enum\n\nRevision ID: cfd1c43b5d33\nRevises: c8a7073deebb\nCreate Date: 2020-11-17 16:42:32.511722+00:00\n\n\"\"\"\nfrom alembic import op\nimport sqlalchemy as sa\n\n\n# revision identifiers, used by Alembic.\nrevision = 'cfd1c43b5d33'\ndown_revision = 'c8a7073deebb'\nbranch_labels = None\ndepends_on = None\n\n\n"},"input_ids":{"kind":"list like","value":[37811,76,42175,670,26968,1181,33829,198,198,18009,1166,4522,25,269,16344,16,66,3559,65,20,67,2091,198,18009,2696,25,269,23,64,2154,4790,67,1453,11848,198,16447,7536,25,12131,12,1157,12,1558,1467,25,3682,25,2624,13,20,17657,1828,10,405,25,405,198,198,37811,198,6738,31341,2022,291,1330,1034,198,11748,44161,282,26599,355,473,628,198,2,18440,42814,11,973,416,9300,2022,291,13,198,260,10178,796,705,12993,67,16,66,3559,65,20,67,2091,6,198,2902,62,260,10178,796,705,66,23,64,2154,4790,67,1453,11848,6,198,1671,3702,62,23912,1424,796,6045,198,10378,2412,62,261,796,6045,628,198],"string":"[\n 37811,\n 76,\n 42175,\n 670,\n 26968,\n 1181,\n 33829,\n 198,\n 198,\n 18009,\n 1166,\n 4522,\n 25,\n 269,\n 16344,\n 16,\n 66,\n 3559,\n 65,\n 20,\n 67,\n 2091,\n 198,\n 18009,\n 2696,\n 25,\n 269,\n 23,\n 64,\n 2154,\n 4790,\n 67,\n 1453,\n 11848,\n 198,\n 16447,\n 7536,\n 25,\n 12131,\n 12,\n 1157,\n 12,\n 1558,\n 1467,\n 25,\n 3682,\n 25,\n 2624,\n 13,\n 20,\n 17657,\n 1828,\n 10,\n 405,\n 25,\n 405,\n 198,\n 198,\n 37811,\n 198,\n 6738,\n 31341,\n 2022,\n 291,\n 1330,\n 1034,\n 198,\n 11748,\n 44161,\n 282,\n 26599,\n 355,\n 473,\n 628,\n 198,\n 2,\n 18440,\n 42814,\n 11,\n 973,\n 416,\n 9300,\n 2022,\n 291,\n 13,\n 198,\n 260,\n 10178,\n 796,\n 705,\n 12993,\n 67,\n 16,\n 66,\n 3559,\n 65,\n 20,\n 67,\n 2091,\n 6,\n 198,\n 2902,\n 62,\n 260,\n 10178,\n 796,\n 705,\n 66,\n 23,\n 64,\n 2154,\n 4790,\n 67,\n 1453,\n 11848,\n 6,\n 198,\n 1671,\n 3702,\n 62,\n 23912,\n 1424,\n 796,\n 6045,\n 198,\n 10378,\n 2412,\n 62,\n 261,\n 796,\n 6045,\n 628,\n 198\n]"},"ratio_char_token":{"kind":"number","value":2.406015037593985,"string":"2.406015"},"token_count":{"kind":"number","value":133,"string":"133"}}},{"rowIdx":1222,"cells":{"content":{"kind":"string","value":"import json\n\nfn = open('../static/alderman.js', 'w')\n\n#add alderman boundaries variable\njson_file = open('../maps/alderman.geojson')\ngeo_json = json.load(json_file)\nfn.write('var alderman_boundaries = ')\nfn.write(json.dumps(geo_json))\nfn.write(';\\n\\n')\njson_file.close()"},"input_ids":{"kind":"list like","value":[11748,33918,198,198,22184,796,1280,10786,40720,12708,14,282,1082,805,13,8457,3256,705,86,11537,198,198,2,2860,257,335,2224,13215,7885,198,17752,62,7753,796,1280,10786,40720,31803,14,282,1082,805,13,469,13210,1559,11537,198,469,78,62,17752,796,33918,13,2220,7,17752,62,7753,8,198,22184,13,13564,10786,7785,257,335,2224,62,7784,3166,796,705,8,198,22184,13,13564,7,17752,13,67,8142,7,469,78,62,17752,4008,198,22184,13,13564,10786,26,59,77,59,77,11537,198,17752,62,7753,13,19836,3419],"string":"[\n 11748,\n 33918,\n 198,\n 198,\n 22184,\n 796,\n 1280,\n 10786,\n 40720,\n 12708,\n 14,\n 282,\n 1082,\n 805,\n 13,\n 8457,\n 3256,\n 705,\n 86,\n 11537,\n 198,\n 198,\n 2,\n 2860,\n 257,\n 335,\n 2224,\n 13215,\n 7885,\n 198,\n 17752,\n 62,\n 7753,\n 796,\n 1280,\n 10786,\n 40720,\n 31803,\n 14,\n 282,\n 1082,\n 805,\n 13,\n 469,\n 13210,\n 1559,\n 11537,\n 198,\n 469,\n 78,\n 62,\n 17752,\n 796,\n 33918,\n 13,\n 2220,\n 7,\n 17752,\n 62,\n 7753,\n 8,\n 198,\n 22184,\n 13,\n 13564,\n 10786,\n 7785,\n 257,\n 335,\n 2224,\n 62,\n 7784,\n 3166,\n 796,\n 705,\n 8,\n 198,\n 22184,\n 13,\n 13564,\n 7,\n 17752,\n 13,\n 67,\n 8142,\n 7,\n 469,\n 78,\n 62,\n 17752,\n 4008,\n 198,\n 22184,\n 13,\n 13564,\n 10786,\n 26,\n 59,\n 77,\n 59,\n 77,\n 11537,\n 198,\n 17752,\n 62,\n 7753,\n 13,\n 19836,\n 3419\n]"},"ratio_char_token":{"kind":"number","value":2.477064220183486,"string":"2.477064"},"token_count":{"kind":"number","value":109,"string":"109"}}},{"rowIdx":1223,"cells":{"content":{"kind":"string","value":"# tables.py\r\n\r\n\r\n\r\nclass MortalityTable:\r\n \"\"\"mortalitytable is a matrix, by age and duration.\"\"\"\r\n \r\nclass MortalityImprovementTable:\r\n \"\"\"MortalityImprovementTable is a matrix, by age and year.\"\"\"\r\n \r\nclass RangeTable:\r\n \"\"\"range table\"\"\"\r\n\r\n"},"input_ids":{"kind":"list like","value":[2,8893,13,9078,201,198,201,198,201,198,201,198,4871,10788,1483,10962,25,201,198,220,220,220,37227,76,28337,11487,318,257,17593,11,416,2479,290,9478,526,15931,201,198,220,220,220,220,201,198,4871,10788,1483,47531,434,10962,25,201,198,220,220,220,37227,44,28337,47531,434,10962,318,257,17593,11,416,2479,290,614,526,15931,201,198,220,220,220,220,201,198,4871,13667,10962,25,201,198,220,220,220,37227,9521,3084,37811,201,198,201,198],"string":"[\n 2,\n 8893,\n 13,\n 9078,\n 201,\n 198,\n 201,\n 198,\n 201,\n 198,\n 201,\n 198,\n 4871,\n 10788,\n 1483,\n 10962,\n 25,\n 201,\n 198,\n 220,\n 220,\n 220,\n 37227,\n 76,\n 28337,\n 11487,\n 318,\n 257,\n 17593,\n 11,\n 416,\n 2479,\n 290,\n 9478,\n 526,\n 15931,\n 201,\n 198,\n 220,\n 220,\n 220,\n 220,\n 201,\n 198,\n 4871,\n 10788,\n 1483,\n 47531,\n 434,\n 10962,\n 25,\n 201,\n 198,\n 220,\n 220,\n 220,\n 37227,\n 44,\n 28337,\n 47531,\n 434,\n 10962,\n 318,\n 257,\n 17593,\n 11,\n 416,\n 2479,\n 290,\n 614,\n 526,\n 15931,\n 201,\n 198,\n 220,\n 220,\n 220,\n 220,\n 201,\n 198,\n 4871,\n 13667,\n 10962,\n 25,\n 201,\n 198,\n 220,\n 220,\n 220,\n 37227,\n 9521,\n 3084,\n 37811,\n 201,\n 198,\n 201,\n 198\n]"},"ratio_char_token":{"kind":"number","value":2.670103092783505,"string":"2.670103"},"token_count":{"kind":"number","value":97,"string":"97"}}},{"rowIdx":1224,"cells":{"content":{"kind":"string","value":"\"\"\"Mathematical helper functions.\"\"\"\n\n\ndef normalize(array):\n \"\"\"Normalize the array.\n\n Set all the values betwwen 0 and 1.\n 0 corresponds to the min value and 1 the max.\n If the normalization cannot occur, will return the array.\n \"\"\"\n min_ = min(array)\n max_ = max(array)\n return (\n (array - min_) / (max_ - min_) # Normalize\n if min_ != max_ else\n array / (max_ if max_ > 0 else 1) # Avoid divide by 0\n )\n"},"input_ids":{"kind":"list like","value":[37811,19044,10024,605,31904,5499,526,15931,628,198,4299,3487,1096,7,18747,2599,198,220,220,220,37227,26447,1096,262,7177,13,628,220,220,220,5345,477,262,3815,731,1383,268,657,290,352,13,198,220,220,220,657,24866,284,262,949,1988,290,352,262,3509,13,198,220,220,220,1002,262,3487,1634,2314,3051,11,481,1441,262,7177,13,198,220,220,220,37227,198,220,220,220,949,62,796,949,7,18747,8,198,220,220,220,3509,62,796,3509,7,18747,8,198,220,220,220,1441,357,198,220,220,220,220,220,220,220,357,18747,532,949,62,8,1220,357,9806,62,532,949,62,8,220,1303,14435,1096,198,220,220,220,220,220,220,220,611,949,62,14512,3509,62,2073,198,220,220,220,220,220,220,220,7177,1220,357,9806,62,611,3509,62,1875,657,2073,352,8,220,1303,24390,14083,416,657,198,220,220,220,1267,198],"string":"[\n 37811,\n 19044,\n 10024,\n 605,\n 31904,\n 5499,\n 526,\n 15931,\n 628,\n 198,\n 4299,\n 3487,\n 1096,\n 7,\n 18747,\n 2599,\n 198,\n 220,\n 220,\n 220,\n 37227,\n 26447,\n 1096,\n 262,\n 7177,\n 13,\n 628,\n 220,\n 220,\n 220,\n 5345,\n 477,\n 262,\n 3815,\n 731,\n 1383,\n 268,\n 657,\n 290,\n 352,\n 13,\n 198,\n 220,\n 220,\n 220,\n 657,\n 24866,\n 284,\n 262,\n 949,\n 1988,\n 290,\n 352,\n 262,\n 3509,\n 13,\n 198,\n 220,\n 220,\n 220,\n 1002,\n 262,\n 3487,\n 1634,\n 2314,\n 3051,\n 11,\n 481,\n 1441,\n 262,\n 7177,\n 13,\n 198,\n 220,\n 220,\n 220,\n 37227,\n 198,\n 220,\n 220,\n 220,\n 949,\n 62,\n 796,\n 949,\n 7,\n 18747,\n 8,\n 198,\n 220,\n 220,\n 220,\n 3509,\n 62,\n 796,\n 3509,\n 7,\n 18747,\n 8,\n 198,\n 220,\n 220,\n 220,\n 1441,\n 357,\n 198,\n 220,\n 220,\n 220,\n 220,\n 220,\n 220,\n 220,\n 357,\n 18747,\n 532,\n 949,\n 62,\n 8,\n 1220,\n 357,\n 9806,\n 62,\n 532,\n 949,\n 62,\n 8,\n 220,\n 1303,\n 14435,\n 1096,\n 198,\n 220,\n 220,\n 220,\n 220,\n 220,\n 220,\n 220,\n 611,\n 949,\n 62,\n 14512,\n 3509,\n 62,\n 2073,\n 198,\n 220,\n 220,\n 220,\n 220,\n 220,\n 220,\n 220,\n 7177,\n 1220,\n 357,\n 9806,\n 62,\n 611,\n 3509,\n 62,\n 1875,\n 657,\n 2073,\n 352,\n 8,\n 220,\n 1303,\n 24390,\n 14083,\n 416,\n 657,\n 198,\n 220,\n 220,\n 220,\n 1267,\n 198\n]"},"ratio_char_token":{"kind":"number","value":2.553072625698324,"string":"2.553073"},"token_count":{"kind":"number","value":179,"string":"179"}}},{"rowIdx":1225,"cells":{"content":{"kind":"string","value":"nome = input('Insira nome completo: ').strip()\nprint('Possui \"Silva\"?', 'silva' in nome.lower())\ninput()\n"},"input_ids":{"kind":"list like","value":[77,462,796,5128,10786,20376,8704,299,462,1224,1462,25,705,737,36311,3419,198,4798,10786,47,793,9019,366,15086,6862,13984,3256,705,18217,6862,6,287,299,462,13,21037,28955,198,15414,3419,198],"string":"[\n 77,\n 462,\n 796,\n 5128,\n 10786,\n 20376,\n 8704,\n 299,\n 462,\n 1224,\n 1462,\n 25,\n 705,\n 737,\n 36311,\n 3419,\n 198,\n 4798,\n 10786,\n 47,\n 793,\n 9019,\n 366,\n 15086,\n 6862,\n 13984,\n 3256,\n 705,\n 18217,\n 6862,\n 6,\n 287,\n 299,\n 462,\n 13,\n 21037,\n 28955,\n 198,\n 15414,\n 3419,\n 198\n]"},"ratio_char_token":{"kind":"number","value":2.5609756097560976,"string":"2.560976"},"token_count":{"kind":"number","value":41,"string":"41"}}},{"rowIdx":1226,"cells":{"content":{"kind":"string","value":"import torch\nimport torch.nn as nn\n\n__all__ = ['ResNet', 'resnet18', 'resnet34', 'resnet50', 'resnet101', 'resnet152']\n\ndef conv3x3(in_planes, out_planes, **kwargs):\n \"\"\"3x3 convolution with padding\"\"\"\n kwargs['kernel_size'] = 3\n kwargs['padding'] = 1\n kwargs['bias'] = False\n return nn.Conv2d(in_planes, out_planes, **kwargs)\n\ndef conv1x1(in_planes, out_planes, **kwargs):\n \"\"\"1x1 convolution\"\"\"\n kwargs['kernel_size'] = 1\n kwargs['bias'] = False\n return nn.Conv2d(in_planes, out_planes, **kwargs)\n\nclass BasicBlock(nn.Module):\n \"\"\"BasicBlock\"\"\"\n expansion = 1\n \nclass Bottleneck(nn.Module):\n \"\"\"Bottleneck\"\"\"\n expansion = 4\n \nclass ResNet(nn.Module):\n \"\"\"ResNet\"\"\"\n \ndef resnet18(num_classes=1000, **kwargs):\n \"\"\"resnet18\"\"\"\n return ResNet([2, 2, 2, 2], num_classes, BasicBlock)\n\ndef resnet34(num_classes=1000, **kwargs):\n \"\"\"resnet34\"\"\"\n return ResNet([3, 4, 6, 3], num_classes, BasicBlock)\n\ndef resnet50(num_classes=1000, **kwargs):\n \"\"\"resnet50\"\"\"\n return ResNet([3, 4, 6, 3], num_classes, Bottleneck)\n\ndef resnet101(num_classes=1000, **kwargs):\n \"\"\"resnet101\"\"\"\n return ResNet([3, 4, 23, 3], num_classes, Bottleneck)\n\ndef resnet152(num_classes=1000, **kwargs):\n \"\"\"resnet152\"\"\"\n return ResNet([3, 8, 36, 3], num_classes, Bottleneck)"},"input_ids":{"kind":"list like","value":[11748,28034,198,11748,28034,13,20471,355,299,77,198,198,834,439,834,796,37250,4965,7934,3256,705,411,3262,1507,3256,705,411,3262,2682,3256,705,411,3262,1120,3256,705,411,3262,8784,3256,705,411,3262,17827,20520,198,198,4299,3063,18,87,18,7,259,62,22587,11,503,62,22587,11,12429,46265,22046,2599,198,220,220,220,37227,18,87,18,3063,2122,351,24511,37811,198,220,220,220,479,86,22046,17816,33885,62,7857,20520,796,513,198,220,220,220,479,86,22046,17816,39231,20520,796,352,198,220,220,220,479,86,22046,17816,65,4448,20520,796,10352,198,220,220,220,1441,299,77,13,3103,85,17,67,7,259,62,22587,11,503,62,22587,11,12429,46265,22046,8,198,198,4299,3063,16,87,16,7,259,62,22587,11,503,62,22587,11,12429,46265,22046,2599,198,220,220,220,37227,16,87,16,3063,2122,37811,198,220,220,220,479,86,22046,17816,33885,62,7857,20520,796,352,198,220,220,220,479,86,22046,17816,65,4448,20520,796,10352,198,220,220,220,1441,299,77,13,3103,85,17,67,7,259,62,22587,11,503,62,22587,11,12429,46265,22046,8,198,198,4871,14392,12235,7,20471,13,26796,2599,198,220,220,220,37227,26416,12235,37811,198,220,220,220,7118,796,352,198,220,220,220,220,198,4871,14835,43163,7,20471,13,26796,2599,198,220,220,220,37227,28653,43163,37811,198,220,220,220,7118,796,604,198,220,220,220,220,198,4871,1874,7934,7,20471,13,26796,2599,198,220,220,220,37227,4965,7934,37811,198,220,220,220,220,198,4299,581,3262,1507,7,22510,62,37724,28,12825,11,12429,46265,22046,2599,198,220,220,220,37227,411,3262,1507,37811,198,220,220,220,1441,1874,7934,26933,17,11,362,11,362,11,362,4357,997,62,37724,11,14392,12235,8,198,198,4299,581,3262,2682,7,22510,62,37724,28,12825,11,12429,46265,22046,2599,198,220,220,220,37227,411,3262,2682,37811,198,220,220,220,1441,1874,7934,26933,18,11,604,11,718,11,513,4357,997,62,37724,11,14392,12235,8,198,198,4299,581,3262,1120,7,22510,62,37724,28,12825,11,12429,46265,22046,2599,198,220,220,220,37227,411,3262,1120,37811,198,220,220,220,1441,1874,7934,26933,18,11,604,11,718,11,513,4357,997,62,37724,11,14835,43163,8,198,198,4299,581,3262,8784,7,22510,62,37724,28,12825,11,12429,46265,22046,2599,198,220,220,220,37227,411,3262,8784,37811,198,220,220,220,1441,1874,7934,26933,18,11,604,11,2242,11,513,4357,997,62,37724,11,14835,43163,8,198,198,4299,581,3262,17827,7,22510,62,37724,28,12825,11,12429,46265,22046,2599,198,220,220,220,37227,411,3262,17827,37811,198,220,220,220,1441,1874,7934,26933,18,11,807,11,4570,11,513,4357,997,62,37724,11,14835,43163,8],"string":"[\n 11748,\n 28034,\n 198,\n 11748,\n 28034,\n 13,\n 20471,\n 355,\n 299,\n 77,\n 198,\n 198,\n 834,\n 439,\n 834,\n 796,\n 37250,\n 4965,\n 7934,\n 3256,\n 705,\n 411,\n 3262,\n 1507,\n 3256,\n 705,\n 411,\n 3262,\n 2682,\n 3256,\n 705,\n 411,\n 3262,\n 1120,\n 3256,\n 705,\n 411,\n 3262,\n 8784,\n 3256,\n 705,\n 411,\n 3262,\n 17827,\n 20520,\n 198,\n 198,\n 4299,\n 3063,\n 18,\n 87,\n 18,\n 7,\n 259,\n 62,\n 22587,\n 11,\n 503,\n 62,\n 22587,\n 11,\n 12429,\n 46265,\n 22046,\n 2599,\n 198,\n 220,\n 220,\n 220,\n 37227,\n 18,\n 87,\n 18,\n 3063,\n 2122,\n 351,\n 24511,\n 37811,\n 198,\n 220,\n 220,\n 220,\n 479,\n 86,\n 22046,\n 17816,\n 33885,\n 62,\n 7857,\n 20520,\n 796,\n 513,\n 198,\n 220,\n 220,\n 220,\n 479,\n 86,\n 22046,\n 17816,\n 39231,\n 20520,\n 796,\n 352,\n 198,\n 220,\n 220,\n 220,\n 479,\n 86,\n 22046,\n 17816,\n 65,\n 4448,\n 20520,\n 796,\n 10352,\n 198,\n 220,\n 220,\n 220,\n 1441,\n 299,\n 77,\n 13,\n 3103,\n 85,\n 17,\n 67,\n 7,\n 259,\n 62,\n 22587,\n 11,\n 503,\n 62,\n 22587,\n 11,\n 12429,\n 46265,\n 22046,\n 8,\n 198,\n 198,\n 4299,\n 3063,\n 16,\n 87,\n 16,\n 7,\n 259,\n 62,\n 22587,\n 11,\n 503,\n 62,\n 22587,\n 11,\n 12429,\n 46265,\n 22046,\n 2599,\n 198,\n 220,\n 220,\n 220,\n 37227,\n 16,\n 87,\n 16,\n 3063,\n 2122,\n 37811,\n 198,\n 220,\n 220,\n 220,\n 479,\n 86,\n 22046,\n 17816,\n 33885,\n 62,\n 7857,\n 20520,\n 796,\n 352,\n 198,\n 220,\n 220,\n 220,\n 479,\n 86,\n 22046,\n 17816,\n 65,\n 4448,\n 20520,\n 796,\n 10352,\n 198,\n 220,\n 220,\n 220,\n 1441,\n 299,\n 77,\n 13,\n 3103,\n 85,\n 17,\n 67,\n 7,\n 259,\n 62,\n 22587,\n 11,\n 503,\n 62,\n 22587,\n 11,\n 12429,\n 46265,\n 22046,\n 8,\n 198,\n 198,\n 4871,\n 14392,\n 12235,\n 7,\n 20471,\n 13,\n 26796,\n 2599,\n 198,\n 220,\n 220,\n 220,\n 37227,\n 26416,\n 12235,\n 37811,\n 198,\n 220,\n 220,\n 220,\n 7118,\n 796,\n 352,\n 198,\n 220,\n 220,\n 220,\n 220,\n 198,\n 4871,\n 14835,\n 43163,\n 7,\n 20471,\n 13,\n 26796,\n 2599,\n 198,\n 220,\n 220,\n 220,\n 37227,\n 28653,\n 43163,\n 37811,\n 198,\n 220,\n 220,\n 220,\n 7118,\n 796,\n 604,\n 198,\n 220,\n 220,\n 220,\n 220,\n 198,\n 4871,\n 1874,\n 7934,\n 7,\n 20471,\n 13,\n 26796,\n 2599,\n 198,\n 220,\n 220,\n 220,\n 37227,\n 4965,\n 7934,\n 37811,\n 198,\n 220,\n 220,\n 220,\n 220,\n 198,\n 4299,\n 581,\n 3262,\n 1507,\n 7,\n 22510,\n 62,\n 37724,\n 28,\n 12825,\n 11,\n 12429,\n 46265,\n 22046,\n 2599,\n 198,\n 220,\n 220,\n 220,\n 37227,\n 411,\n 3262,\n 1507,\n 37811,\n 198,\n 220,\n 220,\n 220,\n 1441,\n 1874,\n 7934,\n 26933,\n 17,\n 11,\n 362,\n 11,\n 362,\n 11,\n 362,\n 4357,\n 997,\n 62,\n 37724,\n 11,\n 14392,\n 12235,\n 8,\n 198,\n 198,\n 4299,\n 581,\n 3262,\n 2682,\n 7,\n 22510,\n 62,\n 37724,\n 28,\n 12825,\n 11,\n 12429,\n 46265,\n 22046,\n 2599,\n 198,\n 220,\n 220,\n 220,\n 37227,\n 411,\n 3262,\n 2682,\n 37811,\n 198,\n 220,\n 220,\n 220,\n 1441,\n 1874,\n 7934,\n 26933,\n 18,\n 11,\n 604,\n 11,\n 718,\n 11,\n 513,\n 4357,\n 997,\n 62,\n 37724,\n 11,\n 14392,\n 12235,\n 8,\n 198,\n 198,\n 4299,\n 581,\n 3262,\n 1120,\n 7,\n 22510,\n 62,\n 37724,\n 28,\n 12825,\n 11,\n 12429,\n 46265,\n 22046,\n 2599,\n 198,\n 220,\n 220,\n 220,\n 37227,\n 411,\n 3262,\n 1120,\n 37811,\n 198,\n 220,\n 220,\n 220,\n 1441,\n 1874,\n 7934,\n 26933,\n 18,\n 11,\n 604,\n 11,\n 718,\n 11,\n 513,\n 4357,\n 997,\n 62,\n 37724,\n 11,\n 14835,\n 43163,\n 8,\n 198,\n 198,\n 4299,\n 581,\n 3262,\n 8784,\n 7,\n 22510,\n 62,\n 37724,\n 28,\n 12825,\n 11,\n 12429,\n 46265,\n 22046,\n 2599,\n 198,\n 220,\n 220,\n 220,\n 37227,\n 411,\n 3262,\n 8784,\n 37811,\n 198,\n 220,\n 220,\n 220,\n 1441,\n 1874,\n 7934,\n 26933,\n 18,\n 11,\n 604,\n 11,\n 2242,\n 11,\n 513,\n 4357,\n 997,\n 62,\n 37724,\n 11,\n 14835,\n 43163,\n 8,\n 198,\n 198,\n 4299,\n 581,\n 3262,\n 17827,\n 7,\n 22510,\n 62,\n 37724,\n 28,\n 12825,\n 11,\n 12429,\n 46265,\n 22046,\n 2599,\n 198,\n 220,\n 220,\n 220,\n 37227,\n 411,\n 3262,\n 17827,\n 37811,\n 198,\n 220,\n 220,\n 220,\n 1441,\n 1874,\n 7934,\n 26933,\n 18,\n 11,\n 807,\n 11,\n 4570,\n 11,\n 513,\n 4357,\n 997,\n 62,\n 37724,\n 11,\n 14835,\n 43163,\n 8\n]"},"ratio_char_token":{"kind":"number","value":2.398181818181818,"string":"2.398182"},"token_count":{"kind":"number","value":550,"string":"550"}}},{"rowIdx":1227,"cells":{"content":{"kind":"string","value":"from modelon.impact.client import (\n SimpleFMUExperimentDefinition,\n SimpleModelicaExperimentDefinition,\n Range,\n Choices,\n SimpleExperimentExtension,\n)\nimport pytest\nfrom modelon.impact.client import exceptions\n\nfrom tests.impact.client.fixtures import *\n\n\n\n"},"input_ids":{"kind":"list like","value":[6738,2746,261,13,48240,13,16366,1330,357,198,220,220,220,17427,23264,52,20468,3681,36621,11,198,220,220,220,17427,17633,3970,20468,3681,36621,11,198,220,220,220,13667,11,198,220,220,220,10031,1063,11,198,220,220,220,17427,20468,3681,11627,3004,11,198,8,198,11748,12972,9288,198,6738,2746,261,13,48240,13,16366,1330,13269,198,198,6738,5254,13,48240,13,16366,13,69,25506,1330,1635,628,628],"string":"[\n 6738,\n 2746,\n 261,\n 13,\n 48240,\n 13,\n 16366,\n 1330,\n 357,\n 198,\n 220,\n 220,\n 220,\n 17427,\n 23264,\n 52,\n 20468,\n 3681,\n 36621,\n 11,\n 198,\n 220,\n 220,\n 220,\n 17427,\n 17633,\n 3970,\n 20468,\n 3681,\n 36621,\n 11,\n 198,\n 220,\n 220,\n 220,\n 13667,\n 11,\n 198,\n 220,\n 220,\n 220,\n 10031,\n 1063,\n 11,\n 198,\n 220,\n 220,\n 220,\n 17427,\n 20468,\n 3681,\n 11627,\n 3004,\n 11,\n 198,\n 8,\n 198,\n 11748,\n 12972,\n 9288,\n 198,\n 6738,\n 2746,\n 261,\n 13,\n 48240,\n 13,\n 16366,\n 1330,\n 13269,\n 198,\n 198,\n 6738,\n 5254,\n 13,\n 48240,\n 13,\n 16366,\n 13,\n 69,\n 25506,\n 1330,\n 1635,\n 628,\n 628\n]"},"ratio_char_token":{"kind":"number","value":3.223529411764706,"string":"3.223529"},"token_count":{"kind":"number","value":85,"string":"85"}}},{"rowIdx":1228,"cells":{"content":{"kind":"string","value":"#coding:utf-8\nimport pymongo\nimport records\n\n"},"input_ids":{"kind":"list like","value":[2,66,7656,25,40477,12,23,198,11748,279,4948,25162,198,11748,4406,628],"string":"[\n 2,\n 66,\n 7656,\n 25,\n 40477,\n 12,\n 23,\n 198,\n 11748,\n 279,\n 4948,\n 25162,\n 198,\n 11748,\n 4406,\n 628\n]"},"ratio_char_token":{"kind":"number","value":2.8125,"string":"2.8125"},"token_count":{"kind":"number","value":16,"string":"16"}}},{"rowIdx":1229,"cells":{"content":{"kind":"string","value":"# ou-tm351 - `nb_pub_utils`\n\n#GOTCHA - Python on Mac logging in to Github: https://stackoverflow.com/a/42098127/454773\n\nimport click\n\nimport os\nimport shutil\nimport zipfile\nimport humanize\nimport datetime\nimport github\nfrom tabulate import tabulate\nfrom shlex import quote\n\n\nimport subprocess\n\ndef listify(item):\n ''' If presented with a string and a list is required, make a list... '''\n item = [] if item is None else item\n #We may be passed a tuple - in which case, listify...\n item = list(item) if isinstance(item,(list,tuple)) else [item]\n return item\n \ndef exclude_hidden_items(itemlist, exclude_hidden=True):\n ''' Exclude hidden items from ziplist '''\n if exclude_hidden:\n rmlist=[]\n for x in itemlist:\n if x.startswith('.'):\n rmlist.append(x)\n for x in rmlist:\n itemlist.remove(x)\n \ndef exclude_items(itemlist, excludes, exclude_hidden=True, ipynb_only=False):\n ''' Exclude items from ziplist '''\n\n for xd in set(itemlist).intersection(excludes):\n itemlist.remove(xd)\n\n if ipynb_only:\n for i in [_i for _i in itemlist if not _i.endswith(\"ipynb\")]:\n itemlist.remove(i)\n \n if exclude_hidden: exclude_hidden_items(itemlist)\n \n \n\ndef notebookTest(path=None, filename=None, dir_excludes=None, file_excludes=None):\n ''' Run notebook tests over explicitly named files and directories.\n '''\n \n #Could probably define this recursively to handle mulitple paths/filenames...\n \n sanitiser = \"\"\"[regex1]\nregex: ]*>\nreplace: \n\n[regex2]\nregex: CPU times: .*\nreplace: CPU times: CPUTIME\n\n[regex3]\nregex: Wall time: .*\nreplace: Wall time: WALLTIME\n\n[regex4]\nregex: .* per loop \\(mean ± std. dev. of .* runs, .* loops each\\)\nreplace: TIMEIT_REPORT\n\"\"\"\n #tmp_fn = \"_sanitise_cfg.cfg\"\n #with open(tmp_fn, \"w\") as f:\n # f.write(sanitiser)\n\n #cmd=f'py.test --nbval-sanitize-with {tmp_fn} '\n cmd=f'py.test '\n\n file_excludes = listify(file_excludes)\n\n for d in listify(dir_excludes):\n cmd = cmd + ' --ignore={} '.format(quote(d))\n print(\"*Not testing in directory: {}*\".format(d))\n\n cmd = cmd+' --nbval '\n ## WARNING - TO DO - if we are running this from a notebook, also exclude path=='.'\n if path is None and filename is None:\n #Process current directory\n return cli_command(cmd)\n elif filename:\n #Process file(s) in directory\n if isinstance(filename, list):\n for _filename in filename:\n cmd = '{cmd} {filename}'.format(cmd=cmd, filename=pathmaker(path, quote(_filename)))\n resp=cli_command(cmd)\n else:\n cmd = '{cmd} {filename}'.format(cmd=cmd, filename=pathmaker(path, quote(filename)))\n resp=cli_command(cmd)\n return resp\n else:\n #Process files in path\n #If we pass a directory name in then the test will be run over all files in the directory\n #py.test accumulates the test responses\n resps = []\n for singlepath in listify(path):\n for dirname, subdirs, files in os.walk(singlepath):\n exclude_items(subdirs, dir_excludes)\n exclude_items(files, file_excludes, ipynb_only=True)\n print('Processing directory: {}'.format(dirname))\n with click.progressbar(files) as bar:\n for filename in bar:\n filepathname=os.path.join(dirname, filename)\n cmd = '{cmd} {path}'.format(cmd=cmd, path=quote(filepathname))\n resps.append( cli_command(cmd) )\n #for singlepath in listify(path):\n # print(\"\\nTesting in directory: {}\".format(singlepath))\n # if singlepath=='.':\n # print('**DO NOT test in current directory from a notebook**')\n # cmd = '{cmd} {path}'.format(cmd=cmd, path=quote(singlepath))\n # resps.append( cli_command(cmd) )\n \n os.unlink(tmp_fn)\n return resps\n \ndef notebookProcessor(notebook, mode=None, outpath=None, outfile=None, inplace=True):\n ''' Clear notebook output cells.\n \n Process a single notebook, clearing cell outputs running cells until\n a warning, or running all cells despite warnings.\n \n Processed notebooks can be written to a specified directory or rendered inplace.\n '''\n \n if mode is None: return (-1, 'Mode not specified.')\n \n if outpath is not None and not os.path.exists(outpath):\n os.makedirs(outpath)\n \n if outfile is not None:\n outpath = '/'.join([outpath,outfile]) if outpath is not None else outfile\n \n cmd='jupyter nbconvert --to notebook'\n\n if mode in ['clearOutput', 'clearOutputTest' ]:\n cmd = '{cmd} --ClearOutputPreprocessor.enabled=True'.format(cmd=cmd)\n elif mode == 'run':\n cmd = '{cmd} --execute'.format(cmd=cmd)\n elif mode == 'runWithErrors':\n cmd = '{cmd} --ExecutePreprocessor.allow_errors=True --execute'.format(cmd=cmd)\n else: return (-1, 'Mode not specified correctly.')\n \n if outpath is None and inplace:\n cmd='{cmd} --inplace'.format(cmd=cmd)\n\n #Select file\n cmd='{cmd} {notebook}'.format(cmd=cmd,notebook=quote(notebook))\n \n #If output path not set, and --inplace is not set,\n # nbformat will create a new file with same name ending: .nbformat.ipynb\n if outpath is not None:\n cmd ='{cmd} --output-dir {outpath}'.format(cmd=cmd, outpath=quote(outpath))\n \n return cli_command(cmd)\n\ndef directoryProcessor(path,\n mode=None, outpath=None, inplace=True,\n include_hidden=False,\n dir_excludes=None,\n file_excludes=None, rmdir=False, currdir=False, subdirs=True,\n reportlevel=1, logfile=None):\n ''' Process all the notebooks in one or more directories and\n (optionally) in associated subdirectories.\n \n Processed notebooks can be written to a specified directory or rendered inplace.\n \n Path hierarchies to notebooks in multiple directories or subdirectories are\n respected when writing to a specified output directory.\n '''\n \n def _process(outpath):\n ''' Process files associated with a particular directory '''\n processfiles=[f for f in files if f.endswith('.ipynb')]\n \n if subdirs:\n print(dirname)\n if outpath is not None:\n outpath='/'.join([outpath, dirname])\n if not os.path.exists(outpath):\n os.makedirs(outpath)\n if not mode == 'tests':\n #print('About to process {}'.format(processfiles))\n with click.progressbar(processfiles) as bar:\n for filename in bar:\n if not currdir and dirname=='.': continue\n if reportlevel>1:\n print(\"Processing >{}<\".format('/'.join([dirname,filename])))\n resp = notebookProcessor('/'.join([dirname,filename]), mode=mode, outpath=outpath, inplace=inplace )\n if reportlevel>0 and resp and resp[0]!=0:\n print(\"Error with {}\".format('/'.join([dirname,filename])))\n if logfile:\n with open(logfile, \"a\") as out:\n out.write(resp[1])\n\n #if mode in ['tests', 'clearOutputTest']:\n # #Tests need to run in original dir in case of file dependencies\n # testreport = notebookTest(path=dirname,dir_excludes=dir_excludes)\n # print('tested:',dirname)\n # print(testreport[1])\n \n #if mode == 'clearOutputTest':\n # #If we are testing for warnings, need to test in original directory\n # # in case there are file dependencies\n # outpath=None\n # inplace=True\n \n if mode is None: return\n \n if isinstance(path, list):\n if rmdir:\n shutil.rmtree(outpath, ignore_errors=True)\n #Make sure we only delete the directory on the way in...\n rmdir=False\n \n for _path in path:\n #When provided with multiple directories, process each one separately\n #Note that subdirs for each directory can be handled automatically\n directoryProcessor(_path, mode, '/'.join([outpath, _path]), inplace,\n include_hidden, dir_excludes, file_excludes,\n rmdir, currdir, subdirs, reportlevel, logfile)\n return\n\n #TO DO - simplify this so we just pass one exclusion type then detect if file or dir?\n file_excludes = listify(file_excludes)\n dir_excludes = listify(dir_excludes)\n \n if outpath is not None and os.path.exists(outpath):\n if rmdir:\n print('\\n***Deleting directory `{}` and all its contents....***\\n\\n'.format(outpath))\n shutil.rmtree(outpath, ignore_errors=True)\n else:\n print('\\nOutput directory `{}` already exists. Remove it first by setting: rmdir=True\\n'.format(outpath))\n \n #dir_excludes = [] if dir_excludes is None else dir_excludes \n #file_excludes = [] if file_excludes is None else file_excludes\n if os.path.isfile(path):\n notebookProcessor(path, mode=mode, outpath=outpath, inplace=inplace )\n elif subdirs:\n for dirname, subdirs, files in os.walk(path):\n exclude_items(subdirs, dir_excludes, not include_hidden)\n exclude_items(files, file_excludes, not include_hidden)\n _process(outpath)\n # if passed a single file rather than directory path\n else:\n files=os.listdir(path)\n exclude_items(files, file_excludes, not include_hidden)\n dirname=path\n _process(outpath)\n \n#Running zipper with a file_processor will change the cell state in current dir\n#That is, notebooks are processed in place then zipped\n#The notebooks as seen in the dir will reflect those in the zipfile\n#We could modify this behaviour so it does not affect original notebooks?\ndef zipper(dirtozip, zipfilename,\n include_hidden=False,\n dir_excludes=None,\n file_excludes=None, \n file_processor=None,\n reportlevel=1, rmdir=False, \n zip_append=False):\n ''' Zip the contents of a directory and its subdirectories '''\n \n file_excludes = listify(file_excludes)\n dir_excludes = listify(dir_excludes)\n\n zip_permission = \"a\" if zip_append else \"w\"\n #Create a new/replacement zip file, rather than append if zipfile already exists\n zf = zipfile.ZipFile(zipfilename, zip_permission, compression=zipfile.ZIP_DEFLATED)\n \n #Don't zip files of same name as the zip file we are creating\n file_excludes.append(zipfilename)\n\n # if we have just a single file to zip and not a dir, zip that\n if os.path.isfile(dirtozip):\n zf.write(dirtozip)\n elif os.path.isdir(dirtozip):\n #https://stackoverflow.com/a/31779538/454773\n for dirname, subdirs, files in os.walk(dirtozip):\n exclude_items(subdirs, dir_excludes, not include_hidden)\n exclude_items(files, file_excludes, not include_hidden)\n print('Processing directory: {}'.format(dirname))\n zf.write(dirname)\n with click.progressbar(files) as bar:\n for filename in bar:\n if reportlevel>1:print(filename)\n filepathname=os.path.join(dirname, filename)\n #There is no point using 'run': if there is an error, nbconvert will fail\n if file_processor in ['clearOutput', 'runWithErrors'] and filename.endswith('.ipynb'):\n #This introduces side effects - notebooks are processed in current path\n #Should we do this in a tmpfile?\n notebookProcessor(filepathname, mode=file_processor, inplace=True)\n zf.write(filepathname)\n zf.close()\n \n #Is this too risky?!\n #if rmdir: shutil.rmtree(dirtozip, ignore_errors=True)\n return zipfilename\n \ndef insideZip(zfn, report=True):\n ''' Look inside a zip file.\n The report contains four columns: file_size, file compressed size, datetime and filename.\n Setting report=True returns a pretty printed report. '''\n if not os.path.isfile(zfn):\n print(\"\\nHmm... {} doesn't seem to be a file?\\n\".format(zfn))\n return\n print('\\nLooking inside zipfile: {}\\n'.format(zfn))\n fz=zipfile.ZipFile(zfn)\n \n txt=[]\n for fn in fz.infolist():\n txt.append( [fn.file_size,\n fn.compress_size,\n datetime.datetime(*fn.date_time).isoformat(),\n fn.filename] )\n print('{}, {}, {}, {}'.format(fn.file_size,\n fn.compress_size,\n datetime.datetime(*fn.date_time).isoformat(),\n fn.filename))\n tabulate(txt, headers=['Full','Zip','Datetime','Path'],tablefmt=\"simple\")\n return txt \n\n@click.command()\n@click.option('--file-processor','-r', type=click.Choice(['clearOutput', 'runWithErrors']))\n@click.option('--include-hiddenfiles', '-H', is_flag=True, help='Include hidden files')\n@click.option('--exclude-dir', '-X', multiple=True, type=click.Path(resolve_path=False), help='Exclude specified directory')\n@click.option('--exclude-file','-x', multiple=True,type=click.Path(resolve_path=False), help='Exclude specified file')\n@click.option('--zip_append','-a', is_flag=True, help='Add to existing zip file')\n@click.argument('path', type=click.Path(resolve_path=False))\n#@click.argument('zipfile', type=click.File('wb'))\n@click.argument('zipfile', type=click.Path())\ndef cli_zip(file_processor, include_hiddenfiles, exclude_dir, exclude_file, zip_append, path, zipfile):\n \"\"\"Create a zip file from the contents of a specified directory.\n \n The zipper can optionally run a notebook processor on notebooks before zipping them to check that all cells are run or all cells are cleared.\n \"\"\"\n print('You must be crazy using this...')\n\n if not zip_append:\n print(f\"\\nOverwriting any previous {zipfile} file\\n\")\n else:\n print(f\"\\nAppending zipped files to: {zipfile}\\n\")\n\n fn = zipper(path, zipfile,\n include_hidden=include_hiddenfiles,\n dir_excludes=exclude_dir,\n file_excludes=exclude_file, \n file_processor=file_processor,\n zip_append=zip_append)\n\n print(f\"\\nZip file: {fn}\\n\")\n\n@click.command()\n@click.option('--quiet', '-q', is_flag=True, help='Suppress the report.')\n@click.option('--warnings', '-w', is_flag=True, help='Display warnings')\n@click.argument('filename', type=click.Path(resolve_path=True),nargs=-1)\ndef cli_zipview(filename, warnings, quiet):\n \"\"\"List the contents of one or more specified zipfiles.\n \"\"\"\n zip_contents = []\n for f in listify(filename):\n zip_contents.append((f, insideZip(f)))\n\n if warnings and zip_contents:\n for (zn, item) in zip_contents:\n print(f\"\\n\\n====== Zip file quality report: {zn} ======\\n\")\n for record in item:\n if record[1] > 1e6:\n print(f\"WARNING: \\\"{record[3]}\\\" looks quite large file ({humanize.naturalsize(record[0])} unzipped, {humanize.naturalsize(record[1])} compressed)\")\n for _path in record[3].split('/'):\n if len(_path) > 50:\n print(f\"ERROR: the filepath element \\\"{_path}\\\" in \\\"{record[3]}\\\" is too long (max. 50 chars)\")\n if _path.startswith(\".\"):\n print(f\"WARNING: \\\"{record[3]}\\\" is a hidden file/directory (do you really need it in the zip file?)\")\n print(\"\\n===========================\\n\\n\")\n\n\n@click.command()\n@click.option('--exclude-dir','-X', multiple=True,type=click.Path(resolve_path=False), help='Do not recurse through specified directory when assembling tests.')\n@click.option('--exclude-file','-x', multiple=True,type=click.Path(resolve_path=False), help='Exclude specified file')\n@click.option('--outfile','-o', type=click.Path(resolve_path=False), help='Output report file. Leave this blank to display report on command line.')\n@click.argument('testitems', type=click.Path(resolve_path=False),nargs=-1)\ndef cli_nbtest( exclude_dir, exclude_file, outfile, testitems):\n \"\"\"Test specified notebooks and/or the notebooks in a specified directory or directories (`TESTITEMS`) using the `nbdime` plugin for `py.test`.\n \n Running `tm351nbtest` without any specified directory or file will assemble tests recursively from the current directory down.\"\"\"\n testitems = testitems or '.'\n _notebookTest(testitems, outfile, exclude_dir, exclude_file)\n\n\n@click.command()\n@click.option('--file-processor','-r', type=click.Choice(['clearOutput', 'runWithErrors']), help='File processor actions that can be applied to notebooks using `nbconvert`')\n@click.option('--outpath', '-O', type=click.Path(resolve_path=False), help='path to output directory')\n@click.option('--inplace/--no-inplace',default=True, help='Run processors on notebooks inplace')\n@click.option('--exclude-dir', '-X', multiple=True, type=click.Path(resolve_path=False), help='Exclude specified directory')\n@click.option('--exclude-file','-x', multiple=True,type=click.Path(resolve_path=False), help='Exclude specified file')\n@click.option('--include-hidden/--no-include-hidden',default=False, help='Include hidden files')\n@click.option('--rmdir/--no-rmdir',default=False, help='Check the output directory is empty before we use it')\n@click.option('--currdir/--no-currdir',default=False, help='Process files in current directory')\n@click.option('--subdirs/--no-subdirs',default=True, help='Process files in subdirectories')\n@click.option('--reportlevel', default=1, help='Reporting level')\n@click.argument('path',type=click.Path(resolve_path=False))\ndef cli_nbrun(file_processor, outpath, inplace, exclude_dir, exclude_file, include_hidden, rmdir, currdir, subdirs, reportlevel, path):\n \"\"\"Directory processor for notebooks - allows the user to run nbconvert operations on notebooks, such as running all cells or clearing all cells.\n \n To run tests, use: tm351nbtest\n \n To zip folders (with the option or running notebook processors on zipped files), use: tm351zip\n \"\"\"\n directoryProcessor(path,\n mode=file_processor, outpath=outpath, inplace=inplace,\n include_hidden=include_hidden,\n dir_excludes=exclude_dir,\n file_excludes=exclude_file, rmdir=rmdir, currdir=currdir,\n subdirs=subdirs,reportlevel=reportlevel)\n\n\n\n\nfrom github import Github\nimport getpass\n\nimport base64\nimport logging\nfrom github.GithubException import GithubException\n\ndef get_sha_for_tag(repository, tag):\n \"\"\"\n Returns a commit PyGithub object for the specified repository and tag.\n \"\"\"\n branches = repository.get_branches()\n matched_branches = [match for match in branches if match.name == tag]\n if matched_branches:\n return matched_branches[0].commit.sha\n\n tags = repository.get_tags()\n matched_tags = [match for match in tags if match.name == tag]\n if not matched_tags:\n raise ValueError('No Tag or Branch exists with that name')\n return matched_tags[0].commit.sha\n\ndef download_directory(repository, sha, server_path, outpath='gh_downloads', file_processor=None):\n \"\"\"\n Download all contents at server_path with commit tag sha in\n the repository.\n \"\"\"\n contents = repository.get_dir_contents(server_path, ref=sha)\n if not os.path.exists(outpath):\n os.makedirs(outpath)\n \n for content in contents:\n print(\"Downloading: %s\" % content.path)\n if content.type == 'dir':\n download_directory(repository, sha, content.path, '/'.join([outpath,content.name]))\n else:\n try:\n path = content.path\n file_content = repository.get_contents(path, ref=sha)\n file_data = base64.b64decode(file_content.content)\n outpathfile='/'.join([outpath,content.name])\n file_out = open(outpathfile, \"wb\")\n file_out.write(file_data)\n file_out.close()\n except (IOError, github.GithubException) as exc:\n #If we fail over because of a large blog, use the data api for the download\n ret,error=exc.args\n if 'message' in error and error['message']=='Not Found':\n print('Hmm... file not found? {}'.format(path))\n elif 'errors' in error and error['errors'][0]['code']=='too_large':\n #print('...large file, trying blob download instead...')\n file_content = repository.get_git_blob(content.sha)\n file_data = base64.b64decode(file_content.content)\n file_out = open('/'.join([outpath,content.name]), \"wb\")\n file_out.write(file_data)\n file_out.close()\n #logging.error('Error processing %s: %s', content.path, exc)\n #if content.name.endswith('.ipynb') and file_processor in ['clearOutput', 'clearOutputTest','runWithErrors' ]:\n # notebookProcessor(outpathfile, file_processor)\n\n\nDEFAULT_REPO='undercertainty/tm351'\n\n@click.command()\n@click.option('--github-user', '-u', help=\"Your Github username.\")\n@click.option('--password', hide_input=True,\n confirmation_prompt=False)\n@click.option('--repo','-r', prompt='Repository ({})'.format(DEFAULT_REPO),\n help='Repository name')\n@click.option('--branch','-b',help='Branch or tag to download')\n@click.option('--directory', help='Directory to download (or: all)')\n@click.option('--savedir',type=click.Path(resolve_path=False),\n help='Directory to download repo / repo dir into; default is dir name')\n@click.option('--file-processor', type=click.Choice(['clearOutput', 'runWithErrors']), help='Optionally specify a file processor to be run against downloaded notebooks.')\n@click.option('--zip/--no-zip', default=False, help='Optionally create a zip file of the downloaded repository/directory with the same name as the repository/directory.')\n@click.option('--auth/--no-auth', default=True, help=\"By default, run with auth (prompt for credentials)\")\n@click.option('--with-tests','-t',is_flag=True, help=\"Run tests on notebooks after download\")\n@click.option('--logfile',type=click.Path(resolve_path=False), help='Path to logfile')\ndef cli_gitrepos(github_user, password, repo, branch, directory, savedir, file_processor, zip, auth, with_tests, logfile):\n \"\"\"Download files from a specified branch in a particular git repository.\n \n The download can also be limited to just the contents of a specified directory.\n \n Don't worry that there look to be a lot of arguments - you will be prompted for them if you just run: tm351gitrepos\n \"\"\"\n \n if auth or github_user:\n if not github_user: github_user = click.prompt('\\nGithub username')\n if not password: password = click.prompt('\\nGithub password', hide_input=True)\n github = Github(github_user, password)\n #Show we're keeping no password...\n password = None\n auth = True\n else: github = Github()\n\n\n if auth:\n user = github.get_user()\n #organisations = github.get_user().get_orgs()\n print('Logging into git as {} ({})'.format(github_user, user.name))\n \n repo = repo or DEFAULT_REPO\n repository = github.get_repo(repo)\n\n if not branch:\n print('\\nBranches available:\\n\\t{}'.format('\\n\\t'.join(github_repo_branches(repository)) ))\n branch = click.prompt('\\nWhich branch? (master)')\n\n branch_or_tag_to_download = branch or 'master'\n sha = get_sha_for_tag(repository, branch_or_tag_to_download)\n \n another = ''\n while another!='-':\n if not directory:\n if branch!='master':\n contents = repository.get_dir_contents('.', ref=sha)\n else:\n contents = repository.get_dir_contents('.')\n print('\\nYou can download all directories from this repo (all) or select one:\\n\\t{}'.format('\\n\\t'.join(github_repo_topdirs(contents))))\n directory = click.prompt('Which directory? (all)')\n\n directory_to_download = '.' if (not directory or directory=='all') else directory\n outpath = savedir or directory_to_download\n if outpath == '.' and savedir !='.': outpath=repo.replace('/','_')+'_files'\n \n msg='\\nOkay... downloading {}/{}'.format(repo,directory_to_download ) \n if file_processor is not None:\n msg = msg + ' using notebook processor: {}'.format(file_processor)\n else: msg = msg + ' with no notebook processing'\n print(msg)\n download_directory(repository, sha, directory_to_download, outpath,file_processor )\n\n if file_processor in ['clearOutput', 'clearOutputTest','runWithErrors' ]:\n click.echo('\\nRunning notebook processor: {}'.format(file_processor))\n directoryProcessor(outpath, mode=file_processor, subdirs=True,\n reportlevel=1, logfile=logfile)\n if logfile:\n click.echo('\\nLog written to {}'.format(logfile))\n\n if with_tests:\n click.echo('\\nRunning notebook tests over: {}'.format(outpath))\n if not logfile: logfile = 'tests.log'\n _notebookTest(outpath, logfile )\n click.echo('\\nLog written to {}'.format(logfile))\n \n if zip:\n print('\\nZipping into: {}/nYou may also want to delete the working directory ({}).'.format(repository, outpath) )\n zipper(outpath,repository)\n else:\n print('\\n\\nTo zip the downloaded directory, run something like: {}'.format('tm351zip {o} {z}\\n\\nTo run a notebook processor (OPTIONS: runWithErrors, clearOutput) while zipping: tm351zip \"{o}\" {z} --file-processor OPTION\\n'.format(o=outpath,z=repository.name)))\n\n directory=''\n another = click.prompt('\\Download another directory from this branch? (To quit: -)')\n\n #TODO\n #print('\\n\\nTo run this command again: {}'.format())\n"},"input_ids":{"kind":"list like","value":[2,267,84,12,17209,35273,532,4600,46803,62,12984,62,26791,63,198,198,2,38,2394,49285,532,11361,319,4100,18931,287,284,38994,25,3740,1378,25558,2502,11125,13,785,14,64,14,27211,4089,16799,14,2231,2857,4790,198,198,11748,3904,198,198,11748,28686,198,11748,4423,346,198,11748,19974,7753,198,11748,1692,1096,198,11748,4818,8079,198,11748,33084,198,6738,7400,5039,1330,7400,5039,198,6738,427,2588,1330,9577,628,198,11748,850,14681,198,198,4299,1351,1958,7,9186,2599,198,220,220,220,705,7061,1002,5545,351,257,4731,290,257,1351,318,2672,11,787,257,1351,986,705,7061,198,220,220,220,2378,796,17635,611,2378,318,6045,2073,2378,198,220,220,220,1303,1135,743,307,3804,257,46545,532,287,543,1339,11,1351,1958,986,198,220,220,220,2378,796,1351,7,9186,8,611,318,39098,7,9186,11,7,4868,11,83,29291,4008,2073,685,9186,60,198,220,220,220,1441,2378,198,220,220,220,220,198,4299,19607,62,30342,62,23814,7,9186,4868,11,19607,62,30342,28,17821,2599,198,220,220,220,705,7061,1475,9152,7104,3709,422,1976,24705,396,705,7061,198,220,220,220,611,19607,62,30342,25,198,220,220,220,220,220,220,220,374,4029,396,28,21737,198,220,220,220,220,220,220,220,329,2124,287,2378,4868,25,198,220,220,220,220,220,220,220,220,220,220,220,611,2124,13,9688,2032,342,10786,2637,2599,198,220,220,220,220,220,220,220,220,220,220,220,220,220,220,220,374,4029,396,13,33295,7,87,8,198,220,220,220,220,220,220,220,329,2124,287,374,4029,396,25,198,220,220,220,220,220,220,220,220,220,220,220,2378,4868,13,28956,7,87,8,198,220,220,220,220,220,220,220,220,220,220,220,220,198,4299,19607,62,23814,7,9186,4868,11,36833,11,19607,62,30342,28,17821,11,20966,2047,65,62,8807,28,25101,2599,198,220,220,220,705,7061,1475,9152,3709,422,1976,24705,396,705,7061,628,220,220,220,329,2124,67,287,900,7,9186,4868,737,3849,5458,7,1069,13955,2599,198,220,220,220,220,220,220,220,2378,4868,13,28956,7,24954,8,628,220,220,220,611,20966,2047,65,62,8807,25,198,220,220,220,220,220,220,220,329,1312,287,685,62,72,329,4808,72,287,2378,4868,611,407,4808,72,13,437,2032,342,7203,541,2047,65,4943,5974,198,220,220,220,220,220,220,220,220,220,220,220,220,220,220,220,2378,4868,13,28956,7,72,8,198,220,220,220,220,220,220,220,220,198,220,220,220,611,19607,62,30342,25,19607,62,30342,62,23814,7,9186,4868,8,198,220,220,220,220,198,220,220,220,220,198,198,4299,20922,14402,7,6978,28,14202,11,29472,28,14202,11,26672,62,1069,13955,28,14202,11,2393,62,1069,13955,28,14202,2599,198,220,220,220,705,7061,5660,20922,5254,625,11777,3706,3696,290,29196,13,198,220,220,220,705,7061,198,220,220,220,220,198,220,220,220,1303,23722,2192,8160,428,664,1834,2280,284,5412,35971,270,1154,13532,14,10379,268,1047,986,198,220,220,220,220,198,220,220,220,5336,270,5847,796,13538,17912,260,25636,16,60,198,260,25636,25,1279,34960,85,528,13,16624,13,7416,379,685,61,37981,9,29,198,33491,25,1279,34960,85,528,13,16624,13,7416,29,198,198,58,260,25636,17,60,198,260,25636,25,9135,1661,25,764,9,198,33491,25,9135,1661,25,16932,3843,12789,198,198,58,260,25636,18,60,198,260,25636,25,5007,640,25,764,9,198,33491,25,5007,640,25,370,7036,34694,198,198,58,260,25636,19,60,198,260,25636,25,764,9,583,9052,16792,32604,6354,14367,13,1614,13,286,764,9,4539,11,764,9,23607,1123,22725,198,33491,25,20460,2043,62,2200,15490,198,37811,198,220,220,220,1303,22065,62,22184,796,45434,12807,270,786,62,37581,13,37581,1,198,220,220,220,1303,4480,1280,7,22065,62,22184,11,366,86,4943,355,277,25,198,220,220,220,1303,220,220,220,277,13,13564,7,12807,270,5847,8,628,220,220,220,1303,28758,28,69,6,9078,13,9288,1377,46803,2100,12,12807,270,1096,12,4480,1391,22065,62,22184,92,705,198,220,220,220,23991,28,69,6,9078,13,9288,705,628,220,220,220,2393,62,1069,13955,796,1351,1958,7,7753,62,1069,13955,8,628,220,220,220,329,288,287,1351,1958,7,15908,62,1069,13955,2599,198,220,220,220,220,220,220,220,23991,796,23991,1343,705,1377,46430,34758,92,45302,18982,7,22708,7,67,4008,198,220,220,220,220,220,220,220,3601,7203,9,3673,4856,287,8619,25,23884,9,1911,18982,7,67,4008,628,220,220,220,23991,796,23991,10,6,1377,46803,2100,705,198,220,220,220,22492,39410,532,5390,8410,532,611,356,389,2491,428,422,257,20922,11,635,19607,3108,855,6,2637,198,220,220,220,611,3108,318,6045,290,29472,318,6045,25,198,220,220,220,220,220,220,220,1303,18709,1459,8619,198,220,220,220,220,220,220,220,1441,537,72,62,21812,7,28758,8,198,220,220,220,1288,361,29472,25,198,220,220,220,220,220,220,220,1303,18709,2393,7,82,8,287,8619,198,220,220,220,220,220,220,220,611,318,39098,7,34345,11,1351,2599,198,220,220,220,220,220,220,220,220,220,220,220,329,4808,34345,287,29472,25,198,220,220,220,220,220,220,220,220,220,220,220,220,220,220,220,23991,796,705,90,28758,92,1391,34345,92,4458,18982,7,28758,28,28758,11,29472,28,6978,10297,7,6978,11,9577,28264,34345,22305,198,220,220,220,220,220,220,220,220,220,220,220,220,220,220,220,1217,28,44506,62,21812,7,28758,8,198,220,220,220,220,220,220,220,2073,25,198,220,220,220,220,220,220,220,220,220,220,220,23991,796,705,90,28758,92,1391,34345,92,4458,18982,7,28758,28,28758,11,29472,28,6978,10297,7,6978,11,9577,7,34345,22305,198,220,220,220,220,220,220,220,220,220,220,220,1217,28,44506,62,21812,7,28758,8,198,220,220,220,220,220,220,220,1441,1217,198,220,220,220,2073,25,198,220,220,220,220,220,220,220,1303,18709,3696,287,3108,198,220,220,220,220,220,220,220,1303,1532,356,1208,257,8619,1438,287,788,262,1332,481,307,1057,625,477,3696,287,262,8619,198,220,220,220,220,220,220,220,1303,9078,13,9288,10507,15968,262,1332,9109,198,220,220,220,220,220,220,220,581,862,796,17635,198,220,220,220,220,220,220,220,329,2060,6978,287,1351,1958,7,6978,2599,198,220,220,220,220,220,220,220,220,220,220,220,329,26672,3672,11,850,15908,82,11,3696,287,28686,13,11152,7,29762,6978,2599,198,220,220,220,220,220,220,220,220,220,220,220,220,220,220,220,19607,62,23814,7,7266,15908,82,11,26672,62,1069,13955,8,198,220,220,220,220,220,220,220,220,220,220,220,220,220,220,220,19607,62,23814,7,16624,11,2393,62,1069,13955,11,20966,2047,65,62,8807,28,17821,8,198,220,220,220,220,220,220,220,220,220,220,220,220,220,220,220,3601,10786,18709,278,8619,25,23884,4458,18982,7,15908,3672,4008,198,220,220,220,220,220,220,220,220,220,220,220,220,220,220,220,351,3904,13,33723,5657,7,16624,8,355,2318,25,198,220,220,220,220,220,220,220,220,220,220,220,220,220,220,220,220,220,220,220,329,29472,287,2318,25,198,220,220,220,220,220,220,220,220,220,220,220,220,220,220,220,220,220,220,220,220,220,220,220,2393,6978,3672,28,418,13,6978,13,22179,7,15908,3672,11,29472,8,198,220,220,220,220,220,220,220,220,220,220,220,220,220,220,220,220,220,220,220,220,220,220,220,23991,796,705,90,28758,92,1391,6978,92,4458,18982,7,28758,28,28758,11,3108,28,22708,7,7753,6978,3672,4008,198,220,220,220,220,220,220,220,220,220,220,220,220,220,220,220,220,220,220,220,220,220,220,220,581,862,13,33295,7,537,72,62,21812,7,28758,8,1267,198,220,220,220,220,220,220,220,1303,1640,2060,6978,287,1351,1958,7,6978,2599,198,220,220,220,220,220,220,220,1303,220,220,220,3601,7203,59,77,44154,287,8619,25,23884,1911,18982,7,29762,6978,4008,198,220,220,220,220,220,220,220,1303,220,220,220,611,2060,6978,855,6,2637,25,198,220,220,220,220,220,220,220,1303,220,220,220,220,220,220,220,3601,10786,1174,18227,5626,1332,287,1459,8619,422,257,20922,1174,11537,198,220,220,220,220,220,220,220,1303,220,220,220,23991,796,705,90,28758,92,1391,6978,92,4458,18982,7,28758,28,28758,11,3108,28,22708,7,29762,6978,4008,198,220,220,220,220,220,220,220,1303,220,220,220,581,862,13,33295,7,537,72,62,21812,7,28758,8,1267,198,220,220,220,220,220,220,220,220,198,220,220,220,220,220,220,220,28686,13,403,8726,7,22065,62,22184,8,198,220,220,220,220,220,220,220,1441,581,862,198,220,220,220,220,220,220,220,220,198,4299,20922,18709,273,7,11295,2070,11,4235,28,14202,11,503,6978,28,14202,11,503,7753,28,14202,11,287,5372,28,17821,2599,198,220,220,220,705,7061,11459,20922,5072,4778,13,198,220,220,220,220,198,220,220,220,220,220,220,220,10854,257,2060,20922,11,17304,2685,23862,2491,4778,1566,198,220,220,220,220,220,220,220,257,6509,11,393,2491,477,4778,3805,14601,13,198,220,220,220,220,220,220,220,220,198,220,220,220,220,220,220,220,10854,276,43935,460,307,3194,284,257,7368,8619,393,15111,287,5372,13,198,220,220,220,705,7061,198,220,220,220,220,198,220,220,220,611,4235,318,6045,25,1441,13841,16,11,705,19076,407,7368,2637,8,198,220,220,220,220,198,220,220,220,611,503,6978,318,407,6045,290,407,28686,13,6978,13,1069,1023,7,448,6978,2599,198,220,220,220,220,220,220,220,28686,13,76,4335,17062,7,448,6978,8,198,220,220,220,220,198,220,220,220,611,503,7753,318,407,6045,25,198,220,220,220,220,220,220,220,503,6978,796,31051,4458,22179,26933,448,6978,11,448,7753,12962,611,503,6978,318,407,6045,2073,503,7753,198,220,220,220,220,198,220,220,220,23991,11639,73,929,88,353,299,65,1102,1851,1377,1462,20922,6,628,220,220,220,611,4235,287,37250,20063,26410,3256,705,20063,26410,14402,6,2361,25,198,220,220,220,220,220,220,220,23991,796,705,90,28758,92,1377,19856,26410,6719,41341,13,25616,28,17821,4458,18982,7,28758,28,28758,8,198,220,220,220,1288,361,4235,6624,705,5143,10354,198,220,220,220,220,220,220,220,23991,796,705,90,28758,92,1377,41049,4458,18982,7,28758,28,28758,8,198,220,220,220,1288,361,4235,6624,705,5143,3152,9139,5965,10354,198,220,220,220,220,220,220,220,23991,796,705,90,28758,92,1377,23002,1133,6719,41341,13,12154,62,48277,28,17821,1377,41049,4458,18982,7,28758,28,28758,8,198,220,220,220,2073,25,1441,13841,16,11,705,19076,407,7368,9380,2637,8,198,220,220,220,220,198,220,220,220,611,503,6978,318,6045,290,287,5372,25,198,220,220,220,220,220,220,220,23991,11639,90,28758,92,1377,259,5372,4458,18982,7,28758,28,28758,8,628,220,220,220,1303,17563,2393,198,220,220,220,23991,11639,90,28758,92,1391,11295,2070,92,4458,18982,7,28758,28,28758,11,11295,2070,28,22708,7,11295,2070,4008,198,220,220,220,220,198,220,220,220,1303,1532,5072,3108,407,900,11,290,1377,259,5372,318,407,900,11,198,220,220,220,1303,220,299,65,18982,481,2251,257,649,2393,351,976,1438,7464,25,764,46803,18982,13,541,2047,65,198,220,220,220,611,503,6978,318,407,6045,25,198,220,220,220,220,220,220,220,23991,796,6,90,28758,92,1377,22915,12,15908,1391,448,6978,92,4458,18982,7,28758,28,28758,11,503,6978,28,22708,7,448,6978,4008,198,220,220,220,220,220,220,220,220,198,220,220,220,1441,537,72,62,21812,7,28758,8,198,198,4299,8619,18709,273,7,6978,11,198,220,220,220,220,220,220,220,220,220,220,220,220,220,220,220,220,220,220,220,220,220,220,4235,28,14202,11,503,6978,28,14202,11,287,5372,28,17821,11,198,220,220,220,220,220,220,220,220,220,220,220,220,220,220,220,220,220,220,220,220,220,220,2291,62,30342,28,25101,11,198,220,220,220,220,220,220,220,220,220,220,220,220,220,220,220,220,220,220,220,220,220,220,26672,62,1069,13955,28,14202,11,198,220,220,220,220,220,220,220,220,220,220,220,220,220,220,220,220,220,220,220,220,220,220,2393,62,1069,13955,28,14202,11,374,9132,343,28,25101,11,1090,4372,343,28,25101,11,850,15908,82,28,17821,11,198,220,220,220,220,220,220,220,220,220,220,220,220,220,220,220,220,220,220,220,220,220,220,989,5715,28,16,11,2604,7753,28,14202,2599,198,220,220,220,705,7061,10854,477,262,43935,287,530,393,517,29196,290,198,220,220,220,220,220,220,220,357,18076,453,8,287,3917,850,12942,1749,13,198,220,220,220,220,198,220,220,220,220,220,220,220,10854,276,43935,460,307,3194,284,257,7368,8619,393,15111,287,5372,13,198,220,220,220,220,220,220,220,220,220,220,220,220,198,220,220,220,220,220,220,220,10644,28398,444,284,43935,287,3294,29196,393,850,12942,1749,389,198,220,220,220,220,220,220,220,14462,618,3597,284,257,7368,5072,8619,13,198,220,220,220,705,7061,198,220,220,220,220,198,220,220,220,825,4808,14681,7,448,6978,2599,198,220,220,220,220,220,220,220,705,7061,10854,3696,3917,351,257,1948,8619,705,7061,198,220,220,220,220,220,220,220,1429,16624,41888,69,329,277,287,3696,611,277,13,437,2032,342,7,4458,541,2047,65,11537,60,198,220,220,220,220,220,220,220,220,198,220,220,220,220,220,220,220,611,850,15908,82,25,198,220,220,220,220,220,220,220,220,220,220,220,3601,7,15908,3672,8,198,220,220,220,220,220,220,220,220,220,220,220,611,503,6978,318,407,6045,25,198,220,220,220,220,220,220,220,220,220,220,220,220,220,220,220,503,6978,11639,14,4458,22179,26933,448,6978,11,26672,3672,12962,198,220,220,220,220,220,220,220,220,220,220,220,220,220,220,220,611,407,28686,13,6978,13,1069,1023,7,448,6978,2599,198,220,220,220,220,220,220,220,220,220,220,220,220,220,220,220,220,220,220,220,28686,13,76,4335,17062,7,448,6978,8,198,220,220,220,220,220,220,220,611,407,4235,6624,705,41989,10354,198,220,220,220,220,220,220,220,220,220,220,220,1303,4798,10786,8585,284,1429,23884,4458,18982,7,14681,16624,4008,198,220,220,220,220,220,220,220,220,220,220,220,351,3904,13,33723,5657,7,14681,16624,8,355,2318,25,198,220,220,220,220,220,220,220,220,220,220,220,220,220,220,220,329,29472,287,2318,25,198,220,220,220,220,220,220,220,220,220,220,220,220,220,220,220,220,220,220,220,611,407,1090,4372,343,290,26672,3672,855,6,2637,25,2555,198,220,220,220,220,220,220,220,220,220,220,220,220,220,220,220,220,220,220,220,611,989,5715,29,16,25,198,220,220,220,220,220,220,220,220,220,220,220,220,220,220,220,220,220,220,220,220,220,220,220,3601,7203,18709,278,1875,90,92,27,1911,18982,10786,14,4458,22179,26933,15908,3672,11,34345,60,22305,198,220,220,220,220,220,220,220,220,220,220,220,220,220,220,220,220,220,220,220,1217,796,20922,18709,273,10786,14,4458,22179,26933,15908,3672,11,34345,46570,4235,28,14171,11,503,6978,28,448,6978,11,287,5372,28,259,5372,1267,198,220,220,220,220,220,220,220,220,220,220,220,220,220,220,220,220,220,220,220,611,989,5715,29,15,290,1217,290,1217,58,15,60,0,28,15,25,198,220,220,220,220,220,220,220,220,220,220,220,220,220,220,220,220,220,220,220,220,220,220,220,3601,7203,12331,351,23884,1911,18982,10786,14,4458,22179,26933,15908,3672,11,34345,60,22305,198,220,220,220,220,220,220,220,220,220,220,220,220,220,220,220,220,220,220,220,611,2604,7753,25,198,220,220,220,220,220,220,220,220,220,220,220,220,220,220,220,220,220,220,220,220,220,220,220,351,1280,7,6404,7753,11,366,64,4943,355,503,25,198,220,220,220,220,220,220,220,220,220,220,220,220,220,220,220,220,220,220,220,220,220,220,220,220,220,220,220,503,13,13564,7,4363,58,16,12962,628,220,220,220,220,220,220,220,1303,361,4235,287,37250,41989,3256,705,20063,26410,14402,6,5974,198,220,220,220,220,220,220,220,1303,220,220,220,1303,51,3558,761,284,1057,287,2656,26672,287,1339,286,2393,20086,198,220,220,220,220,220,220,220,1303,220,220,220,1332,13116,796,20922,14402,7,6978,28,15908,3672,11,15908,62,1069,13955,28,15908,62,1069,13955,8,198,220,220,220,220,220,220,220,1303,220,220,220,3601,10786,39612,25,3256,15908,3672,8,198,220,220,220,220,220,220,220,1303,220,220,220,3601,7,9288,13116,58,16,12962,198,220,220,220,220,198,220,220,220,1303,361,4235,6624,705,20063,26410,14402,10354,198,220,220,220,1303,220,220,220,1303,1532,356,389,4856,329,14601,11,761,284,1332,287,2656,8619,198,220,220,220,1303,220,220,220,1303,220,287,1339,612,389,2393,20086,198,220,220,220,1303,220,220,220,503,6978,28,14202,198,220,220,220,1303,220,220,220,287,5372,28,17821,198,220,220,220,220,198,220,220,220,611,4235,318,6045,25,1441,198,220,220,220,220,198,220,220,220,611,318,39098,7,6978,11,1351,2599,198,220,220,220,220,220,220,220,611,374,9132,343,25,198,220,220,220,220,220,220,220,220,220,220,220,4423,346,13,81,16762,631,7,448,6978,11,8856,62,48277,28,17821,8,198,220,220,220,220,220,220,220,220,220,220,220,1303,12050,1654,356,691,12233,262,8619,319,262,835,287,986,198,220,220,220,220,220,220,220,220,220,220,220,374,9132,343,28,25101,198,220,220,220,220,220,220,220,220,220,220,220,220,198,220,220,220,220,220,220,220,329,4808,6978,287,3108,25,198,220,220,220,220,220,220,220,220,220,220,220,1303,2215,2810,351,3294,29196,11,1429,1123,530,13869,198,220,220,220,220,220,220,220,220,220,220,220,1303,6425,326,850,15908,82,329,1123,8619,460,307,12118,6338,198,220,220,220,220,220,220,220,220,220,220,220,8619,18709,273,28264,6978,11,4235,11,31051,4458,22179,26933,448,6978,11,4808,6978,46570,287,5372,11,198,220,220,220,220,220,220,220,220,220,220,220,220,220,220,220,220,220,220,220,220,220,220,220,220,220,220,220,220,220,220,2291,62,30342,11,26672,62,1069,13955,11,2393,62,1069,13955,11,198,220,220,220,220,220,220,220,220,220,220,220,220,220,220,220,220,220,220,220,220,220,220,220,220,220,220,220,220,220,220,374,9132,343,11,1090,4372,343,11,850,15908,82,11,989,5715,11,2604,7753,8,198,220,220,220,220,220,220,220,1441,628,220,220,220,1303,10468,8410,532,30276,428,523,356,655,1208,530,19328,2099,788,4886,611,2393,393,26672,30,198,220,220,220,2393,62,1069,13955,796,1351,1958,7,7753,62,1069,13955,8,198,220,220,220,26672,62,1069,13955,796,1351,1958,7,15908,62,1069,13955,8,198,220,220,220,220,198,220,220,220,611,503,6978,318,407,6045,290,28686,13,6978,13,1069,1023,7,448,6978,2599,198,220,220,220,220,220,220,220,611,374,9132,343,25,198,220,220,220,220,220,220,220,220,220,220,220,3601,10786,59,77,8162,5005,293,889,8619,4600,90,92,63,290,477,663,10154,1106,8162,59,77,59,77,4458,18982,7,448,6978,4008,198,220,220,220,220,220,220,220,220,220,220,220,4423,346,13,81,16762,631,7,448,6978,11,8856,62,48277,28,17821,8,198,220,220,220,220,220,220,220,2073,25,198,220,220,220,220,220,220,220,220,220,220,220,3601,10786,59,77,26410,8619,4600,90,92,63,1541,7160,13,17220,340,717,416,4634,25,374,9132,343,28,17821,59,77,4458,18982,7,448,6978,4008,198,220,220,220,220,220,220,220,220,198,220,220,220,1303,15908,62,1069,13955,796,17635,611,26672,62,1069,13955,318,6045,2073,26672,62,1069,13955,220,198,220,220,220,1303,7753,62,1069,13955,796,17635,611,2393,62,1069,13955,318,6045,2073,2393,62,1069,13955,198,220,220,220,611,28686,13,6978,13,4468,576,7,6978,2599,198,220,220,220,220,220,220,220,20922,18709,273,7,6978,11,4235,28,14171,11,503,6978,28,448,6978,11,287,5372,28,259,5372,1267,198,220,220,220,1288,361,850,15908,82,25,198,220,220,220,220,220,220,220,329,26672,3672,11,850,15908,82,11,3696,287,28686,13,11152,7,6978,2599,198,220,220,220,220,220,220,220,220,220,220,220,19607,62,23814,7,7266,15908,82,11,26672,62,1069,13955,11,407,2291,62,30342,8,198,220,220,220,220,220,220,220,220,220,220,220,19607,62,23814,7,16624,11,2393,62,1069,13955,11,407,2291,62,30342,8,198,220,220,220,220,220,220,220,220,220,220,220,4808,14681,7,448,6978,8,198,220,220,220,1303,611,3804,257,2060,2393,2138,621,8619,3108,198,220,220,220,2073,25,198,220,220,220,220,220,220,220,3696,28,418,13,4868,15908,7,6978,8,198,220,220,220,220,220,220,220,19607,62,23814,7,16624,11,2393,62,1069,13955,11,407,2291,62,30342,8,198,220,220,220,220,220,220,220,26672,3672,28,6978,198,220,220,220,220,220,220,220,4808,14681,7,448,6978,8,198,220,220,220,220,220,220,220,220,198,2,28768,48992,351,257,2393,62,41341,481,1487,262,2685,1181,287,1459,26672,198,2,2504,318,11,43935,389,13686,287,1295,788,1976,3949,198,2,464,43935,355,1775,287,262,26672,481,4079,883,287,262,19974,7753,198,2,1135,714,13096,428,9172,523,340,857,407,2689,2656,43935,30,198,4299,48992,7,15908,1462,13344,11,19974,34345,11,198,220,220,220,220,220,220,220,220,220,220,2291,62,30342,28,25101,11,198,220,220,220,220,220,220,220,220,220,220,26672,62,1069,13955,28,14202,11,198,220,220,220,220,220,220,220,220,220,220,2393,62,1069,13955,28,14202,11,220,198,220,220,220,220,220,220,220,220,220,220,2393,62,41341,28,14202,11,198,220,220,220,220,220,220,220,220,220,220,989,5715,28,16,11,374,9132,343,28,25101,11,220,198,220,220,220,220,220,220,220,220,220,220,19974,62,33295,28,25101,2599,198,220,220,220,705,7061,38636,262,10154,286,257,8619,290,663,850,12942,1749,705,7061,198,220,220,220,220,220,198,220,220,220,2393,62,1069,13955,796,1351,1958,7,7753,62,1069,13955,8,198,220,220,220,26672,62,1069,13955,796,1351,1958,7,15908,62,1069,13955,8,628,220,220,220,19974,62,525,3411,796,366,64,1,611,19974,62,33295,2073,366,86,1,198,220,220,220,1303,16447,257,649,14,35666,5592,19974,2393,11,2138,621,24443,611,19974,7753,1541,7160,198,220,220,220,1976,69,796,19974,7753,13,41729,8979,7,13344,34345,11,19974,62,525,3411,11,19794,28,13344,7753,13,57,4061,62,7206,3697,11617,8,198,220,220,220,220,198,220,220,220,1303,3987,470,19974,3696,286,976,1438,355,262,19974,2393,356,389,4441,198,220,220,220,2393,62,1069,13955,13,33295,7,13344,34345,8,628,220,220,220,1303,611,356,423,655,257,2060,2393,284,19974,290,407,257,26672,11,19974,326,198,220,220,220,611,28686,13,6978,13,4468,576,7,15908,1462,13344,2599,198,220,220,220,220,220,220,220,1976,69,13,13564,7,15908,1462,13344,8,198,220,220,220,1288,361,28686,13,6978,13,9409,343,7,15908,1462,13344,2599,198,220,220,220,220,220,220,220,1303,5450,1378,25558,2502,11125,13,785,14,64,14,34125,41544,2548,14,2231,2857,4790,198,220,220,220,220,220,220,220,329,26672,3672,11,850,15908,82,11,3696,287,28686,13,11152,7,15908,1462,13344,2599,198,220,220,220,220,220,220,220,220,220,220,220,19607,62,23814,7,7266,15908,82,11,26672,62,1069,13955,11,407,2291,62,30342,8,198,220,220,220,220,220,220,220,220,220,220,220,19607,62,23814,7,16624,11,2393,62,1069,13955,11,407,2291,62,30342,8,198,220,220,220,220,220,220,220,220,220,220,220,3601,10786,18709,278,8619,25,23884,4458,18982,7,15908,3672,4008,198,220,220,220,220,220,220,220,220,220,220,220,1976,69,13,13564,7,15908,3672,8,198,220,220,220,220,220,220,220,220,220,220,220,351,3904,13,33723,5657,7,16624,8,355,2318,25,198,220,220,220,220,220,220,220,220,220,220,220,220,220,220,220,329,29472,287,2318,25,198,220,220,220,220,220,220,220,220,220,220,220,220,220,220,220,220,220,220,220,611,989,5715,29,16,25,4798,7,34345,8,198,220,220,220,220,220,220,220,220,220,220,220,220,220,220,220,220,220,220,220,2393,6978,3672,28,418,13,6978,13,22179,7,15908,3672,11,29472,8,198,220,220,220,220,220,220,220,220,220,220,220,220,220,220,220,220,220,220,220,1303,1858,318,645,966,1262,705,5143,10354,611,612,318,281,4049,11,299,65,1102,1851,481,2038,198,220,220,220,220,220,220,220,220,220,220,220,220,220,220,220,220,220,220,220,611,2393,62,41341,287,37250,20063,26410,3256,705,5143,3152,9139,5965,20520,290,29472,13,437,2032,342,7,4458,541,2047,65,6,2599,198,220,220,220,220,220,220,220,220,220,220,220,220,220,220,220,220,220,220,220,220,220,220,220,1303,1212,20718,1735,3048,532,43935,389,13686,287,1459,3108,198,220,220,220,220,220,220,220,220,220,220,220,220,220,220,220,220,220,220,220,220,220,220,220,1303,19926,356,466,428,287,257,45218,7753,30,198,220,220,220,220,220,220,220,220,220,220,220,220,220,220,220,220,220,220,220,220,220,220,220,20922,18709,273,7,7753,6978,3672,11,4235,28,7753,62,41341,11,287,5372,28,17821,8,198,220,220,220,220,220,220,220,220,220,220,220,220,220,220,220,220,220,220,220,1976,69,13,13564,7,7753,6978,3672,8,198,220,220,220,1976,69,13,19836,3419,198,220,220,220,220,198,220,220,220,1303,3792,428,1165,17564,12248,198,220,220,220,1303,361,374,9132,343,25,4423,346,13,81,16762,631,7,15908,1462,13344,11,8856,62,48277,28,17821,8,198,220,220,220,1441,19974,34345,198,220,220,220,220,198,4299,2641,41729,7,89,22184,11,989,28,17821,2599,198,220,220,220,705,7061,6803,2641,257,19974,2393,13,198,220,220,220,220,220,220,220,383,989,4909,1440,15180,25,2393,62,7857,11,2393,25388,2546,11,4818,8079,290,29472,13,198,220,220,220,220,220,220,220,25700,989,28,17821,5860,257,2495,10398,989,13,705,7061,198,220,220,220,611,407,28686,13,6978,13,4468,576,7,89,22184,2599,198,220,220,220,220,220,220,220,3601,7203,59,77,44217,986,23884,1595,470,1283,284,307,257,2393,30,59,77,1911,18982,7,89,22184,4008,198,220,220,220,220,220,220,220,1441,198,220,220,220,3601,10786,59,77,15784,2641,19974,7753,25,23884,59,77,4458,18982,7,89,22184,4008,198,220,220,220,277,89,28,13344,7753,13,41729,8979,7,89,22184,8,198,220,220,220,220,198,220,220,220,256,742,28,21737,198,220,220,220,329,24714,287,277,89,13,259,9062,396,33529,198,220,220,220,220,220,220,220,256,742,13,33295,7,685,22184,13,7753,62,7857,11,198,220,220,220,220,220,220,220,220,220,220,220,220,220,220,220,220,220,220,220,220,24714,13,5589,601,62,7857,11,198,220,220,220,220,220,220,220,220,220,220,220,220,220,220,220,220,220,220,220,220,4818,8079,13,19608,8079,46491,22184,13,4475,62,2435,737,26786,18982,22784,198,220,220,220,220,220,220,220,220,220,220,220,220,220,220,220,220,220,220,220,220,24714,13,34345,60,1267,198,220,220,220,220,220,220,220,3601,10786,90,5512,1391,5512,1391,5512,23884,4458,18982,7,22184,13,7753,62,7857,11,198,220,220,220,220,220,220,220,220,220,220,220,220,220,220,220,220,220,220,220,220,24714,13,5589,601,62,7857,11,198,220,220,220,220,220,220,220,220,220,220,220,220,220,220,220,220,220,220,220,220,4818,8079,13,19608,8079,46491,22184,13,4475,62,2435,737,26786,18982,22784,198,220,220,220,220,220,220,220,220,220,220,220,220,220,220,220,220,220,220,220,220,24714,13,34345,4008,198,220,220,220,7400,5039,7,14116,11,24697,28,17816,13295,41707,41729,41707,27354,8079,41707,15235,6,4357,11487,69,16762,2625,36439,4943,198,220,220,220,1441,256,742,220,220,198,198,31,12976,13,21812,3419,198,31,12976,13,18076,10786,438,7753,12,41341,3256,29001,81,3256,2099,28,12976,13,46770,7,17816,20063,26410,3256,705,5143,3152,9139,5965,20520,4008,198,31,12976,13,18076,10786,438,17256,12,30342,16624,3256,705,12,39,3256,318,62,32109,28,17821,11,1037,11639,818,9152,7104,3696,11537,198,31,12976,13,18076,10786,438,1069,9152,12,15908,3256,705,12,55,3256,3294,28,17821,11,2099,28,12976,13,15235,7,411,6442,62,6978,28,25101,828,1037,11639,3109,9152,7368,8619,11537,198,31,12976,13,18076,10786,438,1069,9152,12,7753,3256,29001,87,3256,3294,28,17821,11,4906,28,12976,13,15235,7,411,6442,62,6978,28,25101,828,1037,11639,3109,9152,7368,2393,11537,198,31,12976,13,18076,10786,438,13344,62,33295,3256,29001,64,3256,318,62,32109,28,17821,11,1037,11639,4550,284,4683,19974,2393,11537,198,31,12976,13,49140,10786,6978,3256,2099,28,12976,13,15235,7,411,6442,62,6978,28,25101,4008,198,2,31,12976,13,49140,10786,13344,7753,3256,2099,28,12976,13,8979,10786,39346,6,4008,198,31,12976,13,49140,10786,13344,7753,3256,2099,28,12976,13,15235,28955,198,4299,537,72,62,13344,7,7753,62,41341,11,2291,62,30342,16624,11,19607,62,15908,11,19607,62,7753,11,19974,62,33295,11,3108,11,19974,7753,2599,198,220,220,220,37227,16447,257,19974,2393,422,262,10154,286,257,7368,8619,13,198,220,220,220,220,198,220,220,220,383,48992,460,42976,1057,257,20922,12649,319,43935,878,1976,4501,606,284,2198,326,477,4778,389,1057,393,477,4778,389,12539,13,198,220,220,220,37227,198,220,220,220,3601,10786,1639,1276,307,7165,1262,428,986,11537,628,220,220,220,611,407,19974,62,33295,25,198,220,220,220,220,220,220,220,3601,7,69,1,59,77,5886,16502,597,2180,1391,13344,7753,92,2393,59,77,4943,198,220,220,220,2073,25,198,220,220,220,220,220,220,220,3601,7,69,1,59,77,4677,1571,1976,3949,3696,284,25,1391,13344,7753,32239,77,4943,628,220,220,220,24714,796,48992,7,6978,11,19974,7753,11,198,220,220,220,220,220,220,220,220,220,220,220,220,220,220,220,2291,62,30342,28,17256,62,30342,16624,11,198,220,220,220,220,220,220,220,220,220,220,220,220,220,220,220,26672,62,1069,13955,28,1069,9152,62,15908,11,198,220,220,220,220,220,220,220,220,220,220,220,220,220,220,220,2393,62,1069,13955,28,1069,9152,62,7753,11,220,198,220,220,220,220,220,220,220,220,220,220,220,220,220,220,220,2393,62,41341,28,7753,62,41341,11,198,220,220,220,220,220,220,220,220,220,220,220,220,220,220,220,19974,62,33295,28,13344,62,33295,8,628,220,220,220,3601,7,69,1,59,77,41729,2393,25,1391,22184,32239,77,4943,198,198,31,12976,13,21812,3419,198,31,12976,13,18076,10786,438,39624,3256,705,12,80,3256,318,62,32109,28,17821,11,1037,11639,15979,601,262,989,2637,8,198,31,12976,13,18076,10786,438,40539,654,3256,705,12,86,3256,318,62,32109,28,17821,11,1037,11639,23114,14601,11537,198,31,12976,13,49140,10786,34345,3256,2099,28,12976,13,15235,7,411,6442,62,6978,28,17821,828,77,22046,10779,16,8,198,4299,537,72,62,13344,1177,7,34345,11,14601,11,5897,2599,198,220,220,220,37227,8053,262,10154,286,530,393,517,7368,19974,16624,13,198,220,220,220,37227,198,220,220,220,19974,62,3642,658,796,17635,198,220,220,220,329,277,287,1351,1958,7,34345,2599,198,220,220,220,220,220,220,220,19974,62,3642,658,13,33295,19510,69,11,2641,41729,7,69,22305,628,220,220,220,611,14601,290,19974,62,3642,658,25,198,220,220,220,220,220,220,220,329,357,47347,11,2378,8,287,19974,62,3642,658,25,198,220,220,220,220,220,220,220,220,220,220,220,3601,7,69,1,59,77,59,77,50155,38636,2393,3081,989,25,1391,47347,92,29335,28,59,77,4943,198,220,220,220,220,220,220,220,220,220,220,220,329,1700,287,2378,25,198,220,220,220,220,220,220,220,220,220,220,220,220,220,220,220,611,1700,58,16,60,1875,352,68,21,25,198,220,220,220,220,220,220,220,220,220,220,220,220,220,220,220,220,220,220,220,3601,7,69,1,31502,25,19990,90,22105,58,18,48999,7879,3073,2407,1588,2393,37913,10734,1096,13,77,2541,874,1096,7,22105,58,15,12962,92,555,89,3949,11,1391,10734,1096,13,77,2541,874,1096,7,22105,58,16,12962,92,25388,8,4943,198,220,220,220,220,220,220,220,220,220,220,220,220,220,220,220,329,4808,6978,287,1700,58,18,4083,35312,10786,14,6,2599,198,220,220,220,220,220,220,220,220,220,220,220,220,220,220,220,220,220,220,220,611,18896,28264,6978,8,1875,2026,25,198,220,220,220,220,220,220,220,220,220,220,220,220,220,220,220,220,220,220,220,220,220,220,220,3601,7,69,1,24908,25,262,2393,6978,5002,19990,90,62,6978,92,7879,287,19990,90,22105,58,18,48999,7879,318,1165,890,357,9806,13,2026,34534,8,4943,198,220,220,220,220,220,220,220,220,220,220,220,220,220,220,220,220,220,220,220,611,4808,6978,13,9688,2032,342,7203,526,2599,198,220,220,220,220,220,220,220,220,220,220,220,220,220,220,220,220,220,220,220,220,220,220,220,3601,7,69,1,31502,25,19990,90,22105,58,18,48999,7879,318,257,7104,2393,14,34945,357,4598,345,1107,761,340,287,262,19974,2393,10091,4943,198,220,220,220,220,220,220,220,3601,7203,59,77,4770,2559,18604,59,77,59,77,4943,628,198,31,12976,13,21812,3419,198,31,12976,13,18076,10786,438,1069,9152,12,15908,3256,29001,55,3256,3294,28,17821,11,4906,28,12976,13,15235,7,411,6442,62,6978,28,25101,828,1037,11639,5211,407,664,12321,832,7368,8619,618,40525,5254,2637,8,198,31,12976,13,18076,10786,438,1069,9152,12,7753,3256,29001,87,3256,3294,28,17821,11,4906,28,12976,13,15235,7,411,6442,62,6978,28,25101,828,1037,11639,3109,9152,7368,2393,11537,198,31,12976,13,18076,10786,438,448,7753,3256,29001,78,3256,2099,28,12976,13,15235,7,411,6442,62,6978,28,25101,828,1037,11639,26410,989,2393,13,17446,428,9178,284,3359,989,319,3141,1627,2637,8,198,31,12976,13,49140,10786,9288,23814,3256,2099,28,12976,13,15235,7,411,6442,62,6978,28,25101,828,77,22046,10779,16,8,198,4299,537,72,62,46803,9288,7,19607,62,15908,11,19607,62,7753,11,503,7753,11,1332,23814,2599,198,220,220,220,37227,14402,7368,43935,290,14,273,262,43935,287,257,7368,8619,393,29196,357,63,51,6465,2043,39201,63,8,1262,262,4600,77,17457,524,63,13877,329,4600,9078,13,9288,44646,198,220,220,220,220,198,220,220,220,18162,4600,17209,35273,46803,9288,63,1231,597,7368,8619,393,2393,481,25432,5254,664,1834,2280,422,262,1459,8619,866,526,15931,198,220,220,220,1332,23814,796,1332,23814,393,705,2637,198,220,220,220,4808,11295,2070,14402,7,9288,23814,11,503,7753,11,19607,62,15908,11,19607,62,7753,8,628,198,31,12976,13,21812,3419,198,31,12976,13,18076,10786,438,7753,12,41341,3256,29001,81,3256,2099,28,12976,13,46770,7,17816,20063,26410,3256,705,5143,3152,9139,5965,20520,828,1037,11639,8979,12649,4028,326,460,307,5625,284,43935,1262,4600,46803,1102,1851,63,11537,198,31,12976,13,18076,10786,438,448,6978,3256,705,12,46,3256,2099,28,12976,13,15235,7,411,6442,62,6978,28,25101,828,1037,11639,6978,284,5072,8619,11537,198,31,12976,13,18076,10786,438,259,5372,14,438,3919,12,259,5372,3256,12286,28,17821,11,1037,11639,10987,20399,319,43935,287,5372,11537,198,31,12976,13,18076,10786,438,1069,9152,12,15908,3256,705,12,55,3256,3294,28,17821,11,2099,28,12976,13,15235,7,411,6442,62,6978,28,25101,828,1037,11639,3109,9152,7368,8619,11537,198,31,12976,13,18076,10786,438,1069,9152,12,7753,3256,29001,87,3256,3294,28,17821,11,4906,28,12976,13,15235,7,411,6442,62,6978,28,25101,828,1037,11639,3109,9152,7368,2393,11537,198,31,12976,13,18076,10786,438,17256,12,30342,14,438,3919,12,17256,12,30342,3256,12286,28,25101,11,1037,11639,818,9152,7104,3696,11537,198,31,12976,13,18076,10786,438,81,9132,343,14,438,3919,12,81,9132,343,3256,12286,28,25101,11,1037,11639,9787,262,5072,8619,318,6565,878,356,779,340,11537,198,31,12976,13,18076,10786,438,22019,4372,343,14,438,3919,12,22019,4372,343,3256,12286,28,25101,11,1037,11639,18709,3696,287,1459,8619,11537,198,31,12976,13,18076,10786,438,7266,15908,82,14,438,3919,12,7266,15908,82,3256,12286,28,17821,11,1037,11639,18709,3696,287,850,12942,1749,11537,198,31,12976,13,18076,10786,438,13116,5715,3256,4277,28,16,11,1037,11639,42159,1241,11537,198,31,12976,13,49140,10786,6978,3256,4906,28,12976,13,15235,7,411,6442,62,6978,28,25101,4008,198,4299,537,72,62,77,1671,403,7,7753,62,41341,11,503,6978,11,287,5372,11,19607,62,15908,11,19607,62,7753,11,2291,62,30342,11,374,9132,343,11,1090,4372,343,11,850,15908,82,11,989,5715,11,3108,2599,198,220,220,220,37227,43055,12649,329,43935,532,3578,262,2836,284,1057,299,65,1102,1851,4560,319,43935,11,884,355,2491,477,4778,393,17304,477,4778,13,198,220,220,220,220,198,220,220,220,1675,1057,5254,11,779,25,256,76,35273,46803,9288,198,220,220,220,220,198,220,220,220,1675,19974,24512,357,4480,262,3038,393,2491,20922,20399,319,1976,3949,3696,828,779,25,256,76,35273,13344,198,220,220,220,37227,198,220,220,220,8619,18709,273,7,6978,11,198,220,220,220,220,220,220,220,220,220,220,220,220,220,220,220,220,220,220,220,220,220,220,4235,28,7753,62,41341,11,503,6978,28,448,6978,11,287,5372,28,259,5372,11,198,220,220,220,220,220,220,220,220,220,220,220,220,220,220,220,220,220,220,220,220,220,220,2291,62,30342,28,17256,62,30342,11,198,220,220,220,220,220,220,220,220,220,220,220,220,220,220,220,220,220,220,220,220,220,220,26672,62,1069,13955,28,1069,9152,62,15908,11,198,220,220,220,220,220,220,220,220,220,220,220,220,220,220,220,220,220,220,220,220,220,220,2393,62,1069,13955,28,1069,9152,62,7753,11,374,9132,343,28,81,9132,343,11,1090,4372,343,28,22019,4372,343,11,198,220,220,220,220,220,220,220,220,220,220,220,220,220,220,220,220,220,220,220,220,220,220,850,15908,82,28,7266,15908,82,11,13116,5715,28,13116,5715,8,628,628,198,6738,33084,1330,38994,198,11748,651,6603,198,198,11748,2779,2414,198,11748,18931,198,6738,33084,13,38,10060,16922,1330,38994,16922,198,198,4299,651,62,26270,62,1640,62,12985,7,260,1930,37765,11,7621,2599,198,220,220,220,37227,198,220,220,220,16409,257,4589,9485,38,10060,2134,329,262,7368,16099,290,7621,13,198,220,220,220,37227,198,220,220,220,13737,796,16099,13,1136,62,1671,12140,3419,198,220,220,220,14451,62,1671,12140,796,685,15699,329,2872,287,13737,611,2872,13,3672,6624,7621,60,198,220,220,220,611,14451,62,1671,12140,25,198,220,220,220,220,220,220,220,1441,14451,62,1671,12140,58,15,4083,41509,13,26270,628,220,220,220,15940,796,16099,13,1136,62,31499,3419,198,220,220,220,14451,62,31499,796,685,15699,329,2872,287,15940,611,2872,13,3672,6624,7621,60,198,220,220,220,611,407,14451,62,31499,25,198,220,220,220,220,220,220,220,5298,11052,12331,10786,2949,17467,393,20551,7160,351,326,1438,11537,198,220,220,220,1441,14451,62,31499,58,15,4083,41509,13,26270,198,198,4299,4321,62,34945,7,260,1930,37765,11,427,64,11,4382,62,6978,11,503,6978,11639,456,62,15002,82,3256,2393,62,41341,28,14202,2599,198,220,220,220,37227,198,220,220,220,10472,477,10154,379,4382,62,6978,351,4589,7621,427,64,287,198,220,220,220,262,16099,13,198,220,220,220,37227,198,220,220,220,10154,796,16099,13,1136,62,15908,62,3642,658,7,15388,62,6978,11,1006,28,26270,8,198,220,220,220,611,407,28686,13,6978,13,1069,1023,7,448,6978,2599,198,220,220,220,220,220,220,220,28686,13,76,4335,17062,7,448,6978,8,198,220,220,220,220,220,220,220,220,220,220,220,220,198,220,220,220,329,2695,287,10154,25,198,220,220,220,220,220,220,220,3601,7203,10002,278,25,4064,82,1,4064,2695,13,6978,8,198,220,220,220,220,220,220,220,611,2695,13,4906,6624,705,15908,10354,198,220,220,220,220,220,220,220,220,220,220,220,4321,62,34945,7,260,1930,37765,11,427,64,11,2695,13,6978,11,31051,4458,22179,26933,448,6978,11,11299,13,3672,60,4008,198,220,220,220,220,220,220,220,2073,25,198,220,220,220,220,220,220,220,220,220,220,220,1949,25,198,220,220,220,220,220,220,220,220,220,220,220,220,220,220,220,3108,796,2695,13,6978,198,220,220,220,220,220,220,220,220,220,220,220,220,220,220,220,2393,62,11299,796,16099,13,1136,62,3642,658,7,6978,11,1006,28,26270,8,198,220,220,220,220,220,220,220,220,220,220,220,220,220,220,220,2393,62,7890,796,2779,2414,13,65,2414,12501,1098,7,7753,62,11299,13,11299,8,198,220,220,220,220,220,220,220,220,220,220,220,220,220,220,220,503,6978,7753,11639,14,4458,22179,26933,448,6978,11,11299,13,3672,12962,198,220,220,220,220,220,220,220,220,220,220,220,220,220,220,220,2393,62,448,796,1280,7,448,6978,7753,11,366,39346,4943,198,220,220,220,220,220,220,220,220,220,220,220,220,220,220,220,2393,62,448,13,13564,7,7753,62,7890,8,198,220,220,220,220,220,220,220,220,220,220,220,220,220,220,220,2393,62,448,13,19836,3419,198,220,220,220,220,220,220,220,220,220,220,220,2845,357,9399,12331,11,33084,13,38,10060,16922,8,355,2859,25,198,220,220,220,220,220,220,220,220,220,220,220,220,220,220,220,1303,1532,356,2038,625,780,286,257,1588,4130,11,779,262,1366,40391,329,262,4321,198,220,220,220,220,220,220,220,220,220,220,220,220,220,220,220,1005,11,18224,28,41194,13,22046,198,220,220,220,220,220,220,220,220,220,220,220,220,220,220,220,611,705,20500,6,287,4049,290,4049,17816,20500,20520,855,6,3673,4062,10354,198,220,220,220,220,220,220,220,220,220,220,220,220,220,220,220,220,220,220,220,3601,10786,44217,986,2393,407,1043,30,23884,4458,18982,7,6978,4008,198,220,220,220,220,220,220,220,220,220,220,220,220,220,220,220,1288,361,705,48277,6,287,4049,290,4049,17816,48277,6,7131,15,7131,6,8189,20520,855,6,18820,62,11664,10354,198,220,220,220,220,220,220,220,220,220,220,220,220,220,220,220,220,220,220,220,1303,4798,10786,986,11664,2393,11,2111,44812,4321,2427,986,11537,198,220,220,220,220,220,220,220,220,220,220,220,220,220,220,220,220,220,220,220,2393,62,11299,796,16099,13,1136,62,18300,62,2436,672,7,11299,13,26270,8,198,220,220,220,220,220,220,220,220,220,220,220,220,220,220,220,220,220,220,220,2393,62,7890,796,2779,2414,13,65,2414,12501,1098,7,7753,62,11299,13,11299,8,198,220,220,220,220,220,220,220,220,220,220,220,220,220,220,220,220,220,220,220,2393,62,448,796,1280,10786,14,4458,22179,26933,448,6978,11,11299,13,3672,46570,366,39346,4943,198,220,220,220,220,220,220,220,220,220,220,220,220,220,220,220,220,220,220,220,2393,62,448,13,13564,7,7753,62,7890,8,198,220,220,220,220,220,220,220,220,220,220,220,220,220,220,220,220,220,220,220,2393,62,448,13,19836,3419,198,220,220,220,220,220,220,220,220,220,220,220,220,220,220,220,1303,6404,2667,13,18224,10786,12331,7587,4064,82,25,4064,82,3256,2695,13,6978,11,2859,8,198,220,220,220,220,220,220,220,220,220,220,220,1303,361,2695,13,3672,13,437,2032,342,7,4458,541,2047,65,11537,290,2393,62,41341,287,37250,20063,26410,3256,705,20063,26410,14402,41707,5143,3152,9139,5965,6,2361,25,198,220,220,220,220,220,220,220,220,220,220,220,1303,220,220,220,220,220,220,220,20922,18709,273,7,448,6978,7753,11,2393,62,41341,8,628,198,7206,38865,62,2200,16402,11639,4625,39239,774,14,17209,35273,6,198,198,31,12976,13,21812,3419,198,31,12976,13,18076,10786,438,12567,12,7220,3256,705,12,84,3256,220,1037,2625,7120,38994,20579,19570,198,31,12976,13,18076,10786,438,28712,3256,7808,62,15414,28,17821,11,198,220,220,220,220,220,220,220,220,220,220,220,220,220,12641,62,16963,457,28,25101,8,198,31,12976,13,18076,10786,438,260,7501,3256,29001,81,3256,6152,11639,6207,13264,37913,30072,4458,18982,7,7206,38865,62,2200,16402,828,198,220,220,220,220,220,220,220,220,220,220,220,220,220,1037,11639,6207,13264,1438,11537,198,31,12976,13,18076,10786,438,1671,3702,3256,29001,65,3256,16794,11639,33,25642,393,7621,284,4321,11537,198,31,12976,13,18076,10786,438,34945,3256,1037,11639,43055,284,4321,357,273,25,477,8,11537,198,31,12976,13,18076,10786,438,82,9586,343,3256,4906,28,12976,13,15235,7,411,6442,62,6978,28,25101,828,198,220,220,220,220,220,220,220,220,220,220,220,220,220,1037,11639,43055,284,4321,29924,1220,29924,26672,656,26,4277,318,26672,1438,11537,198,31,12976,13,18076,10786,438,7753,12,41341,3256,2099,28,12976,13,46770,7,17816,20063,26410,3256,705,5143,3152,9139,5965,20520,828,1037,11639,19722,453,11986,257,2393,12649,284,307,1057,1028,15680,43935,2637,8,198,31,12976,13,18076,10786,438,13344,14,438,3919,12,13344,3256,4277,28,25101,11,1037,11639,19722,453,2251,257,19974,2393,286,262,15680,16099,14,34945,351,262,976,1438,355,262,16099,14,34945,2637,8,198,31,12976,13,18076,10786,438,18439,14,438,3919,12,18439,3256,4277,28,17821,11,1037,2625,3886,4277,11,1057,351,6284,357,16963,457,329,18031,8,4943,198,31,12976,13,18076,10786,438,4480,12,41989,3256,29001,83,3256,271,62,32109,28,17821,11,1037,2625,10987,5254,319,43935,706,4321,4943,198,31,12976,13,18076,10786,438,6404,7753,3256,4906,28,12976,13,15235,7,411,6442,62,6978,28,25101,828,1037,11639,15235,284,2604,7753,11537,198,4299,537,72,62,18300,260,1930,7,12567,62,7220,11,9206,11,29924,11,8478,11,8619,11,7448,343,11,2393,62,41341,11,19974,11,6284,11,351,62,41989,11,2604,7753,2599,198,220,220,220,37227,10002,3696,422,257,7368,8478,287,257,1948,17606,16099,13,198,220,220,220,220,198,220,220,220,383,4321,460,635,307,3614,284,655,262,10154,286,257,7368,8619,13,198,220,220,220,220,198,220,220,220,2094,470,5490,326,612,804,284,307,257,1256,286,7159,532,345,481,307,12053,329,606,611,345,655,1057,25,256,76,35273,18300,260,1930,198,220,220,220,37227,198,220,220,220,220,198,220,220,220,611,6284,393,33084,62,7220,25,198,220,220,220,220,220,220,220,611,407,33084,62,7220,25,33084,62,7220,796,3904,13,16963,457,10786,59,77,38,10060,20579,11537,198,220,220,220,220,220,220,220,611,407,9206,25,9206,796,3904,13,16963,457,10786,59,77,38,10060,9206,3256,7808,62,15414,28,17821,8,198,220,220,220,220,220,220,220,33084,796,38994,7,12567,62,7220,11,9206,8,198,220,220,220,220,220,220,220,1303,15307,356,821,5291,645,9206,986,198,220,220,220,220,220,220,220,9206,796,6045,198,220,220,220,220,220,220,220,6284,796,6407,198,220,220,220,2073,25,33084,796,38994,3419,628,198,220,220,220,611,6284,25,198,220,220,220,220,220,220,220,2836,796,33084,13,1136,62,7220,3419,198,220,220,220,220,220,220,220,1303,9971,38189,796,33084,13,1136,62,7220,22446,1136,62,2398,82,3419,198,220,220,220,220,220,220,220,3601,10786,11187,2667,656,17606,355,23884,37913,30072,4458,18982,7,12567,62,7220,11,2836,13,3672,4008,198,220,220,220,220,198,220,220,220,29924,796,29924,393,5550,38865,62,2200,16402,198,220,220,220,16099,796,33084,13,1136,62,260,7501,7,260,7501,8,628,220,220,220,611,407,8478,25,198,220,220,220,220,220,220,220,3601,10786,59,77,9414,12140,1695,7479,77,59,83,90,92,4458,18982,10786,59,77,59,83,4458,22179,7,12567,62,260,7501,62,1671,12140,7,260,1930,37765,4008,15306,198,220,220,220,220,220,220,220,8478,796,3904,13,16963,457,10786,59,77,13828,8478,30,357,9866,8,11537,628,220,220,220,8478,62,273,62,12985,62,1462,62,15002,796,8478,393,705,9866,6,198,220,220,220,427,64,796,651,62,26270,62,1640,62,12985,7,260,1930,37765,11,8478,62,273,62,12985,62,1462,62,15002,8,198,220,220,220,220,198,220,220,220,1194,796,10148,198,220,220,220,981,1194,0,11639,12,10354,198,220,220,220,220,220,220,220,611,407,8619,25,198,220,220,220,220,220,220,220,220,220,220,220,611,8478,0,11639,9866,10354,198,220,220,220,220,220,220,220,220,220,220,220,220,220,220,220,10154,796,16099,13,1136,62,15908,62,3642,658,10786,2637,11,1006,28,26270,8,198,220,220,220,220,220,220,220,220,220,220,220,2073,25,198,220,220,220,220,220,220,220,220,220,220,220,220,220,220,220,10154,796,16099,13,1136,62,15908,62,3642,658,10786,2637,8,198,220,220,220,220,220,220,220,220,220,220,220,3601,10786,59,77,1639,460,4321,477,29196,422,428,29924,357,439,8,393,2922,530,7479,77,59,83,90,92,4458,18982,10786,59,77,59,83,4458,22179,7,12567,62,260,7501,62,4852,15908,82,7,3642,658,35514,198,220,220,220,220,220,220,220,220,220,220,220,8619,796,3904,13,16963,457,10786,13828,8619,30,357,439,8,11537,628,220,220,220,220,220,220,220,8619,62,1462,62,15002,796,705,2637,611,357,1662,8619,393,8619,855,6,439,11537,2073,8619,198,220,220,220,220,220,220,220,503,6978,796,7448,343,393,8619,62,1462,62,15002,198,220,220,220,220,220,220,220,611,503,6978,6624,705,2637,290,7448,343,5145,11639,2637,25,503,6978,28,260,7501,13,33491,10786,14,41707,62,11537,10,6,62,16624,6,198,220,220,220,220,220,220,220,220,198,220,220,220,220,220,220,220,31456,11639,59,77,16454,986,22023,23884,14,90,92,4458,18982,7,260,7501,11,34945,62,1462,62,15002,1267,220,198,220,220,220,220,220,220,220,611,2393,62,41341,318,407,6045,25,198,220,220,220,220,220,220,220,220,220,220,220,31456,796,31456,1343,705,1262,20922,12649,25,23884,4458,18982,7,7753,62,41341,8,198,220,220,220,220,220,220,220,2073,25,31456,796,31456,1343,705,351,645,20922,7587,6,198,220,220,220,220,220,220,220,3601,7,19662,8,198,220,220,220,220,220,220,220,4321,62,34945,7,260,1930,37765,11,427,64,11,8619,62,1462,62,15002,11,503,6978,11,7753,62,41341,1267,628,220,220,220,220,220,220,220,611,2393,62,41341,287,37250,20063,26410,3256,705,20063,26410,14402,41707,5143,3152,9139,5965,6,2361,25,198,220,220,220,220,220,220,220,220,220,220,220,3904,13,30328,10786,59,77,28768,20922,12649,25,23884,4458,18982,7,7753,62,41341,4008,198,220,220,220,220,220,220,220,220,220,220,220,8619,18709,273,7,448,6978,11,4235,28,7753,62,41341,11,850,15908,82,28,17821,11,198,220,220,220,220,220,220,220,220,220,220,220,220,220,220,220,220,220,220,220,220,220,220,220,220,220,220,220,220,220,220,220,989,5715,28,16,11,2604,7753,28,6404,7753,8,198,220,220,220,220,220,220,220,220,220,220,220,611,2604,7753,25,198,220,220,220,220,220,220,220,220,220,220,220,220,220,220,220,3904,13,30328,10786,59,77,11187,3194,284,23884,4458,18982,7,6404,7753,4008,628,220,220,220,220,220,220,220,611,351,62,41989,25,198,220,220,220,220,220,220,220,220,220,220,220,3904,13,30328,10786,59,77,28768,20922,5254,625,25,23884,4458,18982,7,448,6978,4008,198,220,220,220,220,220,220,220,220,220,220,220,611,407,2604,7753,25,2604,7753,796,705,41989,13,6404,6,198,220,220,220,220,220,220,220,220,220,220,220,4808,11295,2070,14402,7,448,6978,11,2604,7753,1267,198,220,220,220,220,220,220,220,220,220,220,220,3904,13,30328,10786,59,77,11187,3194,284,23884,4458,18982,7,6404,7753,4008,198,220,220,220,220,220,220,220,220,220,220,220,220,198,220,220,220,220,220,220,220,611,19974,25,198,220,220,220,220,220,220,220,220,220,220,220,3601,10786,59,77,57,4501,656,25,23884,14,77,1639,743,635,765,284,12233,262,1762,8619,37913,92,737,4458,18982,7,260,1930,37765,11,503,6978,8,1267,198,220,220,220,220,220,220,220,220,220,220,220,48992,7,448,6978,11,260,1930,37765,8,198,220,220,220,220,220,220,220,2073,25,198,220,220,220,220,220,220,220,220,220,220,220,3601,10786,59,77,59,77,2514,19974,262,15680,8619,11,1057,1223,588,25,23884,4458,18982,10786,17209,35273,13344,1391,78,92,1391,89,32239,77,59,77,2514,1057,257,20922,12649,357,3185,51,11053,25,1057,3152,9139,5965,11,1598,26410,8,981,1976,4501,25,256,76,35273,13344,45144,78,36786,1391,89,92,1377,7753,12,41341,39852,2849,59,77,4458,18982,7,78,28,448,6978,11,89,28,260,1930,37765,13,3672,22305,628,220,220,220,220,220,220,220,8619,28,7061,198,220,220,220,220,220,220,220,1194,796,3904,13,16963,457,10786,59,10002,1194,8619,422,428,8478,30,357,2514,11238,25,532,8,11537,628,220,220,220,220,1303,51,3727,46,198,220,220,220,220,1303,4798,10786,59,77,59,77,2514,1057,428,3141,757,25,23884,4458,18982,28955,198],"string":"[\n 2,\n 267,\n 84,\n 12,\n 17209,\n 35273,\n 532,\n 4600,\n 46803,\n 62,\n 12984,\n 62,\n 26791,\n 63,\n 198,\n 198,\n 2,\n 38,\n 2394,\n 49285,\n 532,\n 11361,\n 319,\n 4100,\n 18931,\n 287,\n 284,\n 38994,\n 25,\n 3740,\n 1378,\n 25558,\n 2502,\n 11125,\n 13,\n 785,\n 14,\n 64,\n 14,\n 27211,\n 4089,\n 16799,\n 14,\n 2231,\n 2857,\n 4790,\n 198,\n 198,\n 11748,\n 3904,\n 198,\n 198,\n 11748,\n 28686,\n 198,\n 11748,\n 4423,\n 346,\n 198,\n 11748,\n 19974,\n 7753,\n 198,\n 11748,\n 1692,\n 1096,\n 198,\n 11748,\n 4818,\n 8079,\n 198,\n 11748,\n 33084,\n 198,\n 6738,\n 7400,\n 5039,\n 1330,\n 7400,\n 5039,\n 198,\n 6738,\n 427,\n 2588,\n 1330,\n 9577,\n 628,\n 198,\n 11748,\n 850,\n 14681,\n 198,\n 198,\n 4299,\n 1351,\n 1958,\n 7,\n 9186,\n 2599,\n 198,\n 220,\n 220,\n 220,\n 705,\n 7061,\n 1002,\n 5545,\n 351,\n 257,\n 4731,\n 290,\n 257,\n 1351,\n 318,\n 2672,\n 11,\n 787,\n 257,\n 1351,\n 986,\n 705,\n 7061,\n 198,\n 220,\n 220,\n 220,\n 2378,\n 796,\n 17635,\n 611,\n 2378,\n 318,\n 6045,\n 2073,\n 2378,\n 198,\n 220,\n 220,\n 220,\n 1303,\n 1135,\n 743,\n 307,\n 3804,\n 257,\n 46545,\n 532,\n 287,\n 543,\n 1339,\n 11,\n 1351,\n 1958,\n 986,\n 198,\n 220,\n 220,\n 220,\n 2378,\n 796,\n 1351,\n 7,\n 9186,\n 8,\n 611,\n 318,\n 39098,\n 7,\n 9186,\n 11,\n 7,\n 4868,\n 11,\n 83,\n 29291,\n 4008,\n 2073,\n 685,\n 9186,\n 60,\n 198,\n 220,\n 220,\n 220,\n 1441,\n 2378,\n 198,\n 220,\n 220,\n 220,\n 220,\n 198,\n 4299,\n 19607,\n 62,\n 30342,\n 62,\n 23814,\n 7,\n 9186,\n 4868,\n 11,\n 19607,\n 62,\n 30342,\n 28,\n 17821,\n 2599,\n 198,\n 220,\n 220,\n 220,\n 705,\n 7061,\n 1475,\n 9152,\n 7104,\n 3709,\n 422,\n 1976,\n 24705,\n 396,\n 705,\n 7061,\n 198,\n 220,\n 220,\n 220,\n 611,\n 19607,\n 62,\n 30342,\n 25,\n 198,\n 220,\n 220,\n 220,\n 220,\n 220,\n 220,\n 220,\n 374,\n 4029,\n 396,\n 28,\n 21737,\n 198,\n 220,\n 220,\n 220,\n 220,\n 220,\n 220,\n 220,\n 329,\n 2124,\n 287,\n 2378,\n 4868,\n 25,\n 198,\n 220,\n 220,\n 220,\n 220,\n 220,\n 220,\n 220,\n 220,\n 220,\n 220,\n 220,\n 611,\n 2124,\n 13,\n 9688,\n 2032,\n 342,\n 10786,\n 2637,\n 2599,\n 198,\n 220,\n 220,\n 220,\n 220,\n 220,\n 220,\n 220,\n 220,\n 220,\n 220,\n 220,\n 220,\n 220,\n 220,\n 220,\n 374,\n 4029,\n 396,\n 13,\n 33295,\n 7,\n 87,\n 8,\n 198,\n 220,\n 220,\n 220,\n 220,\n 220,\n 220,\n 220,\n 329,\n 2124,\n 287,\n 374,\n 4029,\n 396,\n 25,\n 198,\n 220,\n 220,\n 220,\n 220,\n 220,\n 220,\n 220,\n 220,\n 220,\n 220,\n 220,\n 2378,\n 4868,\n 13,\n 28956,\n 7,\n 87,\n 8,\n 198,\n 220,\n 220,\n 220,\n 220,\n 220,\n 220,\n 220,\n 220,\n 220,\n 220,\n 220,\n 220,\n 198,\n 4299,\n 19607,\n 62,\n 23814,\n 7,\n 9186,\n 4868,\n 11,\n 36833,\n 11,\n 19607,\n 62,\n 30342,\n 28,\n 17821,\n 11,\n 20966,\n 2047,\n 65,\n 62,\n 8807,\n 28,\n 25101,\n 2599,\n 198,\n 220,\n 220,\n 220,\n 705,\n 7061,\n 1475,\n 9152,\n 3709,\n 422,\n 1976,\n 24705,\n 396,\n 705,\n 7061,\n 628,\n 220,\n 220,\n 220,\n 329,\n 2124,\n 67,\n 287,\n 900,\n 7,\n 9186,\n 4868,\n 737,\n 3849,\n 5458,\n 7,\n 1069,\n 13955,\n 2599,\n 198,\n 220,\n 220,\n 220,\n 220,\n 220,\n 220,\n 220,\n 2378,\n 4868,\n 13,\n 28956,\n 7,\n 24954,\n 8,\n 628,\n 220,\n 220,\n 220,\n 611,\n 20966,\n 2047,\n 65,\n 62,\n 8807,\n 25,\n 198,\n 220,\n 220,\n 220,\n 220,\n 220,\n 220,\n 220,\n 329,\n 1312,\n 287,\n 685,\n 62,\n 72,\n 329,\n 4808,\n 72,\n 287,\n 2378,\n 4868,\n 611,\n 407,\n 4808,\n 72,\n 13,\n 437,\n 2032,\n 342,\n 7203,\n 541,\n 2047,\n 65,\n 4943,\n 5974,\n 198,\n 220,\n 220,\n 220,\n 220,\n 220,\n 220,\n 220,\n 220,\n 220,\n 220,\n 220,\n 220,\n 220,\n 220,\n 220,\n 2378,\n 4868,\n 13,\n 28956,\n 7,\n 72,\n 8,\n 198,\n 220,\n 220,\n 220,\n 220,\n 220,\n 220,\n 220,\n 220,\n 198,\n 220,\n 220,\n 220,\n 611,\n 19607,\n 62,\n 30342,\n 25,\n 19607,\n 62,\n 30342,\n 62,\n 23814,\n 7,\n 9186,\n 4868,\n 8,\n 198,\n 220,\n 220,\n 220,\n 220,\n 198,\n 220,\n 220,\n 220,\n 220,\n 198,\n 198,\n 4299,\n 20922,\n 14402,\n 7,\n 6978,\n 28,\n 14202,\n 11,\n 29472,\n 28,\n 14202,\n 11,\n 26672,\n 62,\n 1069,\n 13955,\n 28,\n 14202,\n 11,\n 2393,\n 62,\n 1069,\n 13955,\n 28,\n 14202,\n 2599,\n 198,\n 220,\n 220,\n 220,\n 705,\n 7061,\n 5660,\n 20922,\n 5254,\n 625,\n 11777,\n 3706,\n 3696,\n 290,\n 29196,\n 13,\n 198,\n 220,\n 220,\n 220,\n 705,\n 7061,\n 198,\n 220,\n 220,\n 220,\n 220,\n 198,\n 220,\n 220,\n 220,\n 1303,\n 23722,\n 2192,\n 8160,\n 428,\n 664,\n 1834,\n 2280,\n 284,\n 5412,\n 35971,\n 270,\n 1154,\n 13532,\n 14,\n 10379,\n 268,\n 1047,\n 986,\n 198,\n 220,\n 220,\n 220,\n 220,\n 198,\n 220,\n 220,\n 220,\n 5336,\n 270,\n 5847,\n 796,\n 13538,\n 17912,\n 260,\n 25636,\n 16,\n 60,\n 198,\n 260,\n 25636,\n 25,\n 1279,\n 34960,\n 85,\n 528,\n 13,\n 16624,\n 13,\n 7416,\n 379,\n 685,\n 61,\n 37981,\n 9,\n 29,\n 198,\n 33491,\n 25,\n 1279,\n 34960,\n 85,\n 528,\n 13,\n 16624,\n 13,\n 7416,\n 29,\n 198,\n 198,\n 58,\n 260,\n 25636,\n 17,\n 60,\n 198,\n 260,\n 25636,\n 25,\n 9135,\n 1661,\n 25,\n 764,\n 9,\n 198,\n 33491,\n 25,\n 9135,\n 1661,\n 25,\n 16932,\n 3843,\n 12789,\n 198,\n 198,\n 58,\n 260,\n 25636,\n 18,\n 60,\n 198,\n 260,\n 25636,\n 25,\n 5007,\n 640,\n 25,\n 764,\n 9,\n 198,\n 33491,\n 25,\n 5007,\n 640,\n 25,\n 370,\n 7036,\n 34694,\n 198,\n 198,\n 58,\n 260,\n 25636,\n 19,\n 60,\n 198,\n 260,\n 25636,\n 25,\n 764,\n 9,\n 583,\n 9052,\n 16792,\n 32604,\n 6354,\n 14367,\n 13,\n 1614,\n 13,\n 286,\n 764,\n 9,\n 4539,\n 11,\n 764,\n 9,\n 23607,\n 1123,\n 22725,\n 198,\n 33491,\n 25,\n 20460,\n 2043,\n 62,\n 2200,\n 15490,\n 198,\n 37811,\n 198,\n 220,\n 220,\n 220,\n 1303,\n 22065,\n 62,\n 22184,\n 796,\n 45434,\n 12807,\n 270,\n 786,\n 62,\n 37581,\n 13,\n 37581,\n 1,\n 198,\n 220,\n 220,\n 220,\n 1303,\n 4480,\n 1280,\n 7,\n 22065,\n 62,\n 22184,\n 11,\n 366,\n 86,\n 4943,\n 355,\n 277,\n 25,\n 198,\n 220,\n 220,\n 220,\n 1303,\n 220,\n 220,\n 220,\n 277,\n 13,\n 13564,\n 7,\n 12807,\n 270,\n 5847,\n 8,\n 628,\n 220,\n 220,\n 220,\n 1303,\n 28758,\n 28,\n 69,\n 6,\n 9078,\n 13,\n 9288,\n 1377,\n 46803,\n 2100,\n 12,\n 12807,\n 270,\n 1096,\n 12,\n 4480,\n 1391,\n 22065,\n 62,\n 22184,\n 92,\n 705,\n 198,\n 220,\n 220,\n 220,\n 23991,\n 28,\n 69,\n 6,\n 9078,\n 13,\n 9288,\n 705,\n 628,\n 220,\n 220,\n 220,\n 2393,\n 62,\n 1069,\n 13955,\n 796,\n 1351,\n 1958,\n 7,\n 7753,\n 62,\n 1069,\n 13955,\n 8,\n 628,\n 220,\n 220,\n 220,\n 329,\n 288,\n 287,\n 1351,\n 1958,\n 7,\n 15908,\n 62,\n 1069,\n 13955,\n 2599,\n 198,\n 220,\n 220,\n 220,\n 220,\n 220,\n 220,\n 220,\n 23991,\n 796,\n 23991,\n 1343,\n 705,\n 1377,\n 46430,\n 34758,\n 92,\n 45302,\n 18982,\n 7,\n 22708,\n 7,\n 67,\n 4008,\n 198,\n 220,\n 220,\n 220,\n 220,\n 220,\n 220,\n 220,\n 3601,\n 7203,\n 9,\n 3673,\n 4856,\n 287,\n 8619,\n 25,\n 23884,\n 9,\n 1911,\n 18982,\n 7,\n 67,\n 4008,\n 628,\n 220,\n 220,\n 220,\n 23991,\n 796,\n 23991,\n 10,\n 6,\n 1377,\n 46803,\n 2100,\n 705,\n 198,\n 220,\n 220,\n 220,\n 22492,\n 39410,\n 532,\n 5390,\n 8410,\n 532,\n 611,\n 356,\n 389,\n 2491,\n 428,\n 422,\n 257,\n 20922,\n 11,\n 635,\n 19607,\n 3108,\n 855,\n 6,\n 2637,\n 198,\n 220,\n 220,\n 220,\n 611,\n 3108,\n 318,\n 6045,\n 290,\n 29472,\n 318,\n 6045,\n 25,\n 198,\n 220,\n 220,\n 220,\n 220,\n 220,\n 220,\n 220,\n 1303,\n 18709,\n 1459,\n 8619,\n 198,\n 220,\n 220,\n 220,\n 220,\n 220,\n 220,\n 220,\n 1441,\n 537,\n 72,\n 62,\n 21812,\n 7,\n 28758,\n 8,\n 198,\n 220,\n 220,\n 220,\n 1288,\n 361,\n 29472,\n 25,\n 198,\n 220,\n 220,\n 220,\n 220,\n 220,\n 220,\n 220,\n 1303,\n 18709,\n 2393,\n 7,\n 82,\n 8,\n 287,\n 8619,\n 198,\n 220,\n 220,\n 220,\n 220,\n 220,\n 220,\n 220,\n 611,\n 318,\n 39098,\n 7,\n 34345,\n 11,\n 1351,\n 2599,\n 198,\n 220,\n 220,\n 220,\n 220,\n 220,\n 220,\n 220,\n 220,\n 220,\n 220,\n 220,\n 329,\n 4808,\n 34345,\n 287,\n 29472,\n 25,\n 198,\n 220,\n 220,\n 220,\n 220,\n 220,\n 220,\n 220,\n 220,\n 220,\n 220,\n 220,\n 220,\n 220,\n 220,\n 220,\n 23991,\n 796,\n 705,\n 90,\n 28758,\n 92,\n 1391,\n 34345,\n 92,\n 4458,\n 18982,\n 7,\n 28758,\n 28,\n 28758,\n 11,\n 29472,\n 28,\n 6978,\n 10297,\n 7,\n 6978,\n 11,\n 9577,\n 28264,\n 34345,\n 22305,\n 198,\n 220,\n 220,\n 220,\n 220,\n 220,\n 220,\n 220,\n 220,\n 220,\n 220,\n 220,\n 220,\n 220,\n 220,\n 220,\n 1217,\n 28,\n 44506,\n 62,\n 21812,\n 7,\n 28758,\n 8,\n 198,\n 220,\n 220,\n 220,\n 220,\n 220,\n 220,\n 220,\n 2073,\n 25,\n 198,\n 220,\n 220,\n 220,\n 220,\n 220,\n 220,\n 220,\n 220,\n 220,\n 220,\n 220,\n 23991,\n 796,\n 705,\n 90,\n 28758,\n 92,\n 1391,\n 34345,\n 92,\n 4458,\n 18982,\n 7,\n 28758,\n 28,\n 28758,\n 11,\n 29472,\n 28,\n 6978,\n 10297,\n 7,\n 6978,\n 11,\n 9577,\n 7,\n 34345,\n 22305,\n 198,\n 220,\n 220,\n 220,\n 220,\n 220,\n 220,\n 220,\n 220,\n 220,\n 220,\n 220,\n 1217,\n 28,\n 44506,\n 62,\n 21812,\n 7,\n 28758,\n 8,\n 198,\n 220,\n 220,\n 220,\n 220,\n 220,\n 220,\n 220,\n 1441,\n 1217,\n 198,\n 220,\n 220,\n 220,\n 2073,\n 25,\n 198,\n 220,\n 220,\n 220,\n 220,\n 220,\n 220,\n 220,\n 1303,\n 18709,\n 3696,\n 287,\n 3108,\n 198,\n 220,\n 220,\n 220,\n 220,\n 220,\n 220,\n 220,\n 1303,\n 1532,\n 356,\n 1208,\n 257,\n 8619,\n 1438,\n 287,\n 788,\n 262,\n 1332,\n 481,\n 307,\n 1057,\n 625,\n 477,\n 3696,\n 287,\n 262,\n 8619,\n 198,\n 220,\n 220,\n 220,\n 220,\n 220,\n 220,\n 220,\n 1303,\n 9078,\n 13,\n 9288,\n 10507,\n 15968,\n 262,\n 1332,\n 9109,\n 198,\n 220,\n 220,\n 220,\n 220,\n 220,\n 220,\n 220,\n 581,\n 862,\n 796,\n 17635,\n 198,\n 220,\n 220,\n 220,\n 220,\n 220,\n 220,\n 220,\n 329,\n 2060,\n 6978,\n 287,\n 1351,\n 1958,\n 7,\n 6978,\n 2599,\n 198,\n 220,\n 220,\n 220,\n 220,\n 220,\n 220,\n 220,\n 220,\n 220,\n 220,\n 220,\n 329,\n 26672,\n 3672,\n 11,\n 850,\n 15908,\n 82,\n 11,\n 3696,\n 287,\n 28686,\n 13,\n 11152,\n 7,\n 29762,\n 6978,\n 2599,\n 198,\n 220,\n 220,\n 220,\n 220,\n 220,\n 220,\n 220,\n 220,\n 220,\n 220,\n 220,\n 220,\n 220,\n 220,\n 220,\n 19607,\n 62,\n 23814,\n 7,\n 7266,\n 15908,\n 82,\n 11,\n 26672,\n 62,\n 1069,\n 13955,\n 8,\n 198,\n 220,\n 220,\n 220,\n 220,\n 220,\n 220,\n 220,\n 220,\n 220,\n 220,\n 220,\n 220,\n 220,\n 220,\n 220,\n 19607,\n 62,\n 23814,\n 7,\n 16624,\n 11,\n 2393,\n 62,\n 1069,\n 13955,\n 11,\n 20966,\n 2047,\n 65,\n 62,\n 8807,\n 28,\n 17821,\n 8,\n 198,\n 220,\n 220,\n 220,\n 220,\n 220,\n 220,\n 220,\n 220,\n 220,\n 220,\n 220,\n 220,\n 220,\n 220,\n 220,\n 3601,\n 10786,\n 18709,\n 278,\n 8619,\n 25,\n 23884,\n 4458,\n 18982,\n 7,\n 15908,\n 3672,\n 4008,\n 198,\n 220,\n 220,\n 220,\n 220,\n 220,\n 220,\n 220,\n 220,\n 220,\n 220,\n 220,\n 220,\n 220,\n 220,\n 220,\n 351,\n 3904,\n 13,\n 33723,\n 5657,\n 7,\n 16624,\n 8,\n 355,\n 2318,\n 25,\n 198,\n 220,\n 220,\n 220,\n 220,\n 220,\n 220,\n 220,\n 220,\n 220,\n 220,\n 220,\n 220,\n 220,\n 220,\n 220,\n 220,\n 220,\n 220,\n 220,\n 329,\n 29472,\n 287,\n 2318,\n 25,\n 198,\n 220,\n 220,\n 220,\n 220,\n 220,\n 220,\n 220,\n 220,\n 220,\n 220,\n 220,\n 220,\n 220,\n 220,\n 220,\n 220,\n 220,\n 220,\n 220,\n 220,\n 220,\n 220,\n 220,\n 2393,\n 6978,\n 3672,\n 28,\n 418,\n 13,\n 6978,\n 13,\n 22179,\n 7,\n 15908,\n 3672,\n 11,\n 29472,\n 8,\n 198,\n 220,\n 220,\n 220,\n 220,\n 220,\n 220,\n 220,\n 220,\n 220,\n 220,\n 220,\n 220,\n 220,\n 220,\n 220,\n 220,\n 220,\n 220,\n 220,\n 220,\n 220,\n 220,\n 220,\n 23991,\n 796,\n 705,\n 90,\n 28758,\n 92,\n 1391,\n 6978,\n 92,\n 4458,\n 18982,\n 7,\n 28758,\n 28,\n 28758,\n 11,\n 3108,\n 28,\n 22708,\n 7,\n 7753,\n 6978,\n 3672,\n 4008,\n 198,\n 220,\n 220,\n 220,\n 220,\n 220,\n 220,\n 220,\n 220,\n 220,\n 220,\n 220,\n 220,\n 220,\n 220,\n 220,\n 220,\n 220,\n 220,\n 220,\n 220,\n 220,\n 220,\n 220,\n 581,\n 862,\n 13,\n 33295,\n 7,\n 537,\n 72,\n 62,\n 21812,\n 7,\n 28758,\n 8,\n 1267,\n 198,\n 220,\n 220,\n 220,\n 220,\n 220,\n 220,\n 220,\n 1303,\n 1640,\n 2060,\n 6978,\n 287,\n 1351,\n 1958,\n 7,\n 6978,\n 2599,\n 198,\n 220,\n 220,\n 220,\n 220,\n 220,\n 220,\n 220,\n 1303,\n 220,\n 220,\n 220,\n 3601,\n 7203,\n 59,\n 77,\n 44154,\n 287,\n 8619,\n 25,\n 23884,\n 1911,\n 18982,\n 7,\n 29762,\n 6978,\n 4008,\n 198,\n 220,\n 220,\n 220,\n 220,\n 220,\n 220,\n 220,\n 1303,\n 220,\n 220,\n 220,\n 611,\n 2060,\n 6978,\n 855,\n 6,\n 2637,\n 25,\n 198,\n 220,\n 220,\n 220,\n 220,\n 220,\n 220,\n 220,\n 1303,\n 220,\n 220,\n 220,\n 220,\n 220,\n 220,\n 220,\n 3601,\n 10786,\n 1174,\n 18227,\n 5626,\n 1332,\n 287,\n 1459,\n 8619,\n 422,\n 257,\n 20922,\n 1174,\n 11537,\n 198,\n 220,\n 220,\n 220,\n 220,\n 220,\n 220,\n 220,\n 1303,\n 220,\n 220,\n 220,\n 23991,\n 796,\n 705,\n 90,\n 28758,\n 92,\n 1391,\n 6978,\n 92,\n 4458,\n 18982,\n 7,\n 28758,\n 28,\n 28758,\n 11,\n 3108,\n 28,\n 22708,\n 7,\n 29762,\n 6978,\n 4008,\n 198,\n 220,\n 220,\n 220,\n 220,\n 220,\n 220,\n 220,\n 1303,\n 220,\n 220,\n 220,\n 581,\n 862,\n 13,\n 33295,\n 7,\n 537,\n 72,\n 62,\n 21812,\n 7,\n 28758,\n 8,\n 1267,\n 198,\n 220,\n 220,\n 220,\n 220,\n 220,\n 220,\n 220,\n 220,\n 198,\n 220,\n 220,\n 220,\n 220,\n 220,\n 220,\n 220,\n 28686,\n 13,\n 403,\n 8726,\n 7,\n 22065,\n 62,\n 22184,\n 8,\n 198,\n 220,\n 220,\n 220,\n 220,\n 220,\n 220,\n 220,\n 1441,\n 581,\n 862,\n 198,\n 220,\n 220,\n 220,\n 220,\n 220,\n 220,\n 220,\n 220,\n 198,\n 4299,\n 20922,\n 18709,\n 273,\n 7,\n 11295,\n 2070,\n 11,\n 4235,\n 28,\n 14202,\n 11,\n 503,\n 6978,\n 28,\n 14202,\n 11,\n 503,\n 7753,\n 28,\n 14202,\n 11,\n 287,\n 5372,\n 28,\n 17821,\n 2599,\n 198,\n 220,\n 220,\n 220,\n 705,\n 7061,\n 11459,\n 20922,\n 5072,\n 4778,\n 13,\n 198,\n 220,\n 220,\n 220,\n 220,\n 198,\n 220,\n 220,\n 220,\n 220,\n 220,\n 220,\n 220,\n 10854,\n 257,\n 2060,\n 20922,\n 11,\n 17304,\n 2685,\n 23862,\n 2491,\n 4778,\n 1566,\n 198,\n 220,\n 220,\n 220,\n 220,\n 220,\n 220,\n 220,\n 257,\n 6509,\n 11,\n 393,\n 2491,\n 477,\n 4778,\n 3805,\n 14601,\n 13,\n 198,\n 220,\n 220,\n 220,\n 220,\n 220,\n 220,\n 220,\n 220,\n 198,\n 220,\n 220,\n 220,\n 220,\n 220,\n 220,\n 220,\n 10854,\n 276,\n 43935,\n 460,\n 307,\n 3194,\n 284,\n 257,\n 7368,\n 8619,\n 393,\n 15111,\n 287,\n 5372,\n 13,\n 198,\n 220,\n 220,\n 220,\n 705,\n 7061,\n 198,\n 220,\n 220,\n 220,\n 220,\n 198,\n 220,\n 220,\n 220,\n 611,\n 4235,\n 318,\n 6045,\n 25,\n 1441,\n 13841,\n 16,\n 11,\n 705,\n 19076,\n 407,\n 7368,\n 2637,\n 8,\n 198,\n 220,\n 220,\n 220,\n 220,\n 198,\n 220,\n 220,\n 220,\n 611,\n 503,\n 6978,\n 318,\n 407,\n 6045,\n 290,\n 407,\n 28686,\n 13,\n 6978,\n 13,\n 1069,\n 1023,\n 7,\n 448,\n 6978,\n 2599,\n 198,\n 220,\n 220,\n 220,\n 220,\n 220,\n 220,\n 220,\n 28686,\n 13,\n 76,\n 4335,\n 17062,\n 7,\n 448,\n 6978,\n 8,\n 198,\n 220,\n 220,\n 220,\n 220,\n 198,\n 220,\n 220,\n 220,\n 611,\n 503,\n 7753,\n 318,\n 407,\n 6045,\n 25,\n 198,\n 220,\n 220,\n 220,\n 220,\n 220,\n 220,\n 220,\n 503,\n 6978,\n 796,\n 31051,\n 4458,\n 22179,\n 26933,\n 448,\n 6978,\n 11,\n 448,\n 7753,\n 12962,\n 611,\n 503,\n 6978,\n 318,\n 407,\n 6045,\n 2073,\n 503,\n 7753,\n 198,\n 220,\n 220,\n 220,\n 220,\n 198,\n 220,\n 220,\n 220,\n 23991,\n 11639,\n 73,\n 929,\n 88,\n 353,\n 299,\n 65,\n 1102,\n 1851,\n 1377,\n 1462,\n 20922,\n 6,\n 628,\n 220,\n 220,\n 220,\n 611,\n 4235,\n 287,\n 37250,\n 20063,\n 26410,\n 3256,\n 705,\n 20063,\n 26410,\n 14402,\n 6,\n 2361,\n 25,\n 198,\n 220,\n 220,\n 220,\n 220,\n 220,\n 220,\n 220,\n 23991,\n 796,\n 705,\n 90,\n 28758,\n 92,\n 1377,\n 19856,\n 26410,\n 6719,\n 41341,\n 13,\n 25616,\n 28,\n 17821,\n 4458,\n 18982,\n 7,\n 28758,\n 28,\n 28758,\n 8,\n 198,\n 220,\n 220,\n 220,\n 1288,\n 361,\n 4235,\n 6624,\n 705,\n 5143,\n 10354,\n 198,\n 220,\n 220,\n 220,\n 220,\n 220,\n 220,\n 220,\n 23991,\n 796,\n 705,\n 90,\n 28758,\n 92,\n 1377,\n 41049,\n 4458,\n 18982,\n 7,\n 28758,\n 28,\n 28758,\n 8,\n 198,\n 220,\n 220,\n 220,\n 1288,\n 361,\n 4235,\n 6624,\n 705,\n 5143,\n 3152,\n 9139,\n 5965,\n 10354,\n 198,\n 220,\n 220,\n 220,\n 220,\n 220,\n 220,\n 220,\n 23991,\n 796,\n 705,\n 90,\n 28758,\n 92,\n 1377,\n 23002,\n 1133,\n 6719,\n 41341,\n 13,\n 12154,\n 62,\n 48277,\n 28,\n 17821,\n 1377,\n 41049,\n 4458,\n 18982,\n 7,\n 28758,\n 28,\n 28758,\n 8,\n 198,\n 220,\n 220,\n 220,\n 2073,\n 25,\n 1441,\n 13841,\n 16,\n 11,\n 705,\n 19076,\n 407,\n 7368,\n 9380,\n 2637,\n 8,\n 198,\n 220,\n 220,\n 220,\n 220,\n 198,\n 220,\n 220,\n 220,\n 611,\n 503,\n 6978,\n 318,\n 6045,\n 290,\n 287,\n 5372,\n 25,\n 198,\n 220,\n 220,\n 220,\n 220,\n 220,\n 220,\n 220,\n 23991,\n 11639,\n 90,\n 28758,\n 92,\n 1377,\n 259,\n 5372,\n 4458,\n 18982,\n 7,\n 28758,\n 28,\n 28758,\n 8,\n 628,\n 220,\n 220,\n 220,\n 1303,\n 17563,\n 2393,\n 198,\n 220,\n 220,\n 220,\n 23991,\n 11639,\n 90,\n 28758,\n 92,\n 1391,\n 11295,\n 2070,\n 92,\n 4458,\n 18982,\n 7,\n 28758,\n 28,\n 28758,\n 11,\n 11295,\n 2070,\n 28,\n 22708,\n 7,\n 11295,\n 2070,\n 4008,\n 198,\n 220,\n 220,\n 220,\n 220,\n 198,\n 220,\n 220,\n 220,\n 1303,\n 1532,\n 5072,\n 3108,\n 407,\n 900,\n 11,\n 290,\n 1377,\n 259,\n 5372,\n 318,\n 407,\n 900,\n 11,\n 198,\n 220,\n 220,\n 220,\n 1303,\n 220,\n 299,\n 65,\n 18982,\n 481,\n 2251,\n 257,\n 649,\n 2393,\n 351,\n 976,\n 1438,\n 7464,\n 25,\n 764,\n 46803,\n 18982,\n 13,\n 541,\n 2047,\n 65,\n 198,\n 220,\n 220,\n 220,\n 611,\n 503,\n 6978,\n 318,\n 407,\n 6045,\n 25,\n 198,\n 220,\n 220,\n 220,\n 220,\n 220,\n 220,\n 220,\n 23991,\n 796,\n 6,\n 90,\n 28758,\n 92,\n 1377,\n 22915,\n 12,\n 15908,\n 1391,\n 448,\n 6978,\n 92,\n 4458,\n 18982,\n 7,\n 28758,\n 28,\n 28758,\n 11,\n 503,\n 6978,\n 28,\n 22708,\n 7,\n 448,\n 6978,\n 4008,\n 198,\n 220,\n 220,\n 220,\n 220,\n 220,\n 220,\n 220,\n 220,\n 198,\n 220,\n 220,\n 220,\n 1441,\n 537,\n 72,\n 62,\n 21812,\n 7,\n 28758,\n 8,\n 198,\n 198,\n 4299,\n 8619,\n 18709,\n 273,\n 7,\n 6978,\n 11,\n 198,\n 220,\n 220,\n 220,\n 220,\n 220,\n 220,\n 220,\n 220,\n 220,\n 220,\n 220,\n 220,\n 220,\n 220,\n 220,\n 220,\n 220,\n 220,\n 220,\n 220,\n 220,\n 220,\n 4235,\n 28,\n 14202,\n 11,\n 503,\n 6978,\n 28,\n 14202,\n 11,\n 287,\n 5372,\n 28,\n 17821,\n 11,\n 198,\n 220,\n 220,\n 220,\n 220,\n 220,\n 220,\n 220,\n 220,\n 220,\n 220,\n 220,\n 220,\n 220,\n 220,\n 220,\n 220,\n 220,\n 220,\n 220,\n 220,\n 220,\n 220,\n 2291,\n 62,\n 30342,\n 28,\n 25101,\n 11,\n 198,\n 220,\n 220,\n 220,\n 220,\n 220,\n 220,\n 220,\n 220,\n 220,\n 220,\n 220,\n 220,\n 220,\n 220,\n 220,\n 220,\n 220,\n 220,\n 220,\n 220,\n 220,\n 220,\n 26672,\n 62,\n 1069,\n 13955,\n 28,\n 14202,\n 11,\n 198,\n 220,\n 220,\n 220,\n 220,\n 220,\n 220,\n 220,\n 220,\n 220,\n 220,\n 220,\n 220,\n 220,\n 220,\n 220,\n 220,\n 220,\n 220,\n 220,\n 220,\n 220,\n 220,\n 2393,\n 62,\n 1069,\n 13955,\n 28,\n 14202,\n 11,\n 374,\n 9132,\n 343,\n 28,\n 25101,\n 11,\n 1090,\n 4372,\n 343,\n 28,\n 25101,\n 11,\n 850,\n 15908,\n 82,\n 28,\n 17821,\n 11,\n 198,\n 220,\n 220,\n 220,\n 220,\n 220,\n 220,\n 220,\n 220,\n 220,\n 220,\n 220,\n 220,\n 220,\n 220,\n 220,\n 220,\n 220,\n 220,\n 220,\n 220,\n 220,\n 220,\n 989,\n 5715,\n 28,\n 16,\n 11,\n 2604,\n 7753,\n 28,\n 14202,\n 2599,\n 198,\n 220,\n 220,\n 220,\n 705,\n 7061,\n 10854,\n 477,\n 262,\n 43935,\n 287,\n 530,\n 393,\n 517,\n 29196,\n 290,\n 198,\n 220,\n 220,\n 220,\n 220,\n 220,\n 220,\n 220,\n 357,\n 18076,\n 453,\n 8,\n 287,\n 3917,\n 850,\n 12942,\n 1749,\n 13,\n 198,\n 220,\n 220,\n 220,\n 220,\n 198,\n 220,\n 220,\n 220,\n 220,\n 220,\n 220,\n 220,\n 10854,\n 276,\n 43935,\n 460,\n 307,\n 3194,\n 284,\n 257,\n 7368,\n 8619,\n 393,\n 15111,\n 287,\n 5372,\n 13,\n 198,\n 220,\n 220,\n 220,\n 220,\n 220,\n 220,\n 220,\n 220,\n 220,\n 220,\n 220,\n 220,\n 198,\n 220,\n 220,\n 220,\n 220,\n 220,\n 220,\n 220,\n 10644,\n 28398,\n 444,\n 284,\n 43935,\n 287,\n 3294,\n 29196,\n 393,\n 850,\n 12942,\n 1749,\n 389,\n 198,\n 220,\n 220,\n 220,\n 220,\n 220,\n 220,\n 220,\n 14462,\n 618,\n 3597,\n 284,\n 257,\n 7368,\n 5072,\n 8619,\n 13,\n 198,\n 220,\n 220,\n 220,\n 705,\n 7061,\n 198,\n 220,\n 220,\n 220,\n 220,\n 198,\n 220,\n 220,\n 220,\n 825,\n 4808,\n 14681,\n 7,\n 448,\n 6978,\n 2599,\n 198,\n 220,\n 220,\n 220,\n 220,\n 220,\n 220,\n 220,\n 705,\n 7061,\n 10854,\n 3696,\n 3917,\n 351,\n 257,\n 1948,\n 8619,\n 705,\n 7061,\n 198,\n 220,\n 220,\n 220,\n 220,\n 220,\n 220,\n 220,\n 1429,\n 16624,\n 41888,\n 69,\n 329,\n 277,\n 287,\n 3696,\n 611,\n 277,\n 13,\n 437,\n 2032,\n 342,\n 7,\n 4458,\n 541,\n 2047,\n 65,\n 11537,\n 60,\n 198,\n 220,\n 220,\n 220,\n 220,\n 220,\n 220,\n 220,\n 220,\n 198,\n 220,\n 220,\n 220,\n 220,\n 220,\n 220,\n 220,\n 611,\n 850,\n 15908,\n 82,\n 25,\n 198,\n 220,\n 220,\n 220,\n 220,\n 220,\n 220,\n 220,\n 220,\n 220,\n 220,\n 220,\n 3601,\n 7,\n 15908,\n 3672,\n 8,\n 198,\n 220,\n 220,\n 220,\n 220,\n 220,\n 220,\n 220,\n 220,\n 220,\n 220,\n 220,\n 611,\n 503,\n 6978,\n 318,\n 407,\n 6045,\n 25,\n 198,\n 220,\n 220,\n 220,\n 220,\n 220,\n 220,\n 220,\n 220,\n 220,\n 220,\n 220,\n 220,\n 220,\n 220,\n 220,\n 503,\n 6978,\n 11639,\n 14,\n 4458,\n 22179,\n 26933,\n 448,\n 6978,\n 11,\n 26672,\n 3672,\n 12962,\n 198,\n 220,\n 220,\n 220,\n 220,\n 220,\n 220,\n 220,\n 220,\n 220,\n 220,\n 220,\n 220,\n 220,\n 220,\n 220,\n 611,\n 407,\n 28686,\n 13,\n 6978,\n 13,\n 1069,\n 1023,\n 7,\n 448,\n 6978,\n 2599,\n 198,\n 220,\n 220,\n 220,\n 220,\n 220,\n 220,\n 220,\n 220,\n 220,\n 220,\n 220,\n 220,\n 220,\n 220,\n 220,\n 220,\n 220,\n 220,\n 220,\n 28686,\n 13,\n 76,\n 4335,\n 17062,\n 7,\n 448,\n 6978,\n 8,\n 198,\n 220,\n 220,\n 220,\n 220,\n 220,\n 220,\n 220,\n 611,\n 407,\n 4235,\n 6624,\n 705,\n 41989,\n 10354,\n 198,\n 220,\n 220,\n 220,\n 220,\n 220,\n 220,\n 220,\n 220,\n 220,\n 220,\n 220,\n 1303,\n 4798,\n 10786,\n 8585,\n 284,\n 1429,\n 23884,\n 4458,\n 18982,\n 7,\n 14681,\n 16624,\n 4008,\n 198,\n 220,\n 220,\n 220,\n 220,\n 220,\n 220,\n 220,\n 220,\n 220,\n 220,\n 220,\n 351,\n 3904,\n 13,\n 33723,\n 5657,\n 7,\n 14681,\n 16624,\n 8,\n 355,\n 2318,\n 25,\n 198,\n 220,\n 220,\n 220,\n 220,\n 220,\n 220,\n 220,\n 220,\n 220,\n 220,\n 220,\n 220,\n 220,\n 220,\n 220,\n 329,\n 29472,\n 287,\n 2318,\n 25,\n 198,\n 220,\n 220,\n 220,\n 220,\n 220,\n 220,\n 220,\n 220,\n 220,\n 220,\n 220,\n 220,\n 220,\n 220,\n 220,\n 220,\n 220,\n 220,\n 220,\n 611,\n 407,\n 1090,\n 4372,\n 343,\n 290,\n 26672,\n 3672,\n 855,\n 6,\n 2637,\n 25,\n 2555,\n 198,\n 220,\n 220,\n 220,\n 220,\n 220,\n 220,\n 220,\n 220,\n 220,\n 220,\n 220,\n 220,\n 220,\n 220,\n 220,\n 220,\n 220,\n 220,\n 220,\n 611,\n 989,\n 5715,\n 29,\n 16,\n 25,\n 198,\n 220,\n 220,\n 220,\n 220,\n 220,\n 220,\n 220,\n 220,\n 220,\n 220,\n 220,\n 220,\n 220,\n 220,\n 220,\n 220,\n 220,\n 220,\n 220,\n 220,\n 220,\n 220,\n 220,\n 3601,\n 7203,\n 18709,\n 278,\n 1875,\n 90,\n 92,\n 27,\n 1911,\n 18982,\n 10786,\n 14,\n 4458,\n 22179,\n 26933,\n 15908,\n 3672,\n 11,\n 34345,\n 60,\n 22305,\n 198,\n 220,\n 220,\n 220,\n 220,\n 220,\n 220,\n 220,\n 220,\n 220,\n 220,\n 220,\n 220,\n 220,\n 220,\n 220,\n 220,\n 220,\n 220,\n 220,\n 1217,\n 796,\n 20922,\n 18709,\n 273,\n 10786,\n 14,\n 4458,\n 22179,\n 26933,\n 15908,\n 3672,\n 11,\n 34345,\n 46570,\n 4235,\n 28,\n 14171,\n 11,\n 503,\n 6978,\n 28,\n 448,\n 6978,\n 11,\n 287,\n 5372,\n 28,\n 259,\n 5372,\n 1267,\n 198,\n 220,\n 220,\n 220,\n 220,\n 220,\n 220,\n 220,\n 220,\n 220,\n 220,\n 220,\n 220,\n 220,\n 220,\n 220,\n 220,\n 220,\n 220,\n 220,\n 611,\n 989,\n 5715,\n 29,\n 15,\n 290,\n 1217,\n 290,\n 1217,\n 58,\n 15,\n 60,\n 0,\n 28,\n 15,\n 25,\n 198,\n 220,\n 220,\n 220,\n 220,\n 220,\n 220,\n 220,\n 220,\n 220,\n 220,\n 220,\n 220,\n 220,\n 220,\n 220,\n 220,\n 220,\n 220,\n 220,\n 220,\n 220,\n 220,\n 220,\n 3601,\n 7203,\n 12331,\n 351,\n 23884,\n 1911,\n 18982,\n 10786,\n 14,\n 4458,\n 22179,\n 26933,\n 15908,\n 3672,\n 11,\n 34345,\n 60,\n 22305,\n 198,\n 220,\n 220,\n 220,\n 220,\n 220,\n 220,\n 220,\n 220,\n 220,\n 220,\n 220,\n 220,\n 220,\n 220,\n 220,\n 220,\n 220,\n 220,\n 220,\n 611,\n 2604,\n 7753,\n 25,\n 198,\n 220,\n 220,\n 220,\n 220,\n 220,\n 220,\n 220,\n 220,\n 220,\n 220,\n 220,\n 220,\n 220,\n 220,\n 220,\n 220,\n 220,\n 220,\n 220,\n 220,\n 220,\n 220,\n 220,\n 351,\n 1280,\n 7,\n 6404,\n 7753,\n 11,\n 366,\n 64,\n 4943,\n 355,\n 503,\n 25,\n 198,\n 220,\n 220,\n 220,\n 220,\n 220,\n 220,\n 220,\n 220,\n 220,\n 220,\n 220,\n 220,\n 220,\n 220,\n 220,\n 220,\n 220,\n 220,\n 220,\n 220,\n 220,\n 220,\n 220,\n 220,\n 220,\n 220,\n 220,\n 503,\n 13,\n 13564,\n 7,\n 4363,\n 58,\n 16,\n 12962,\n 628,\n 220,\n 220,\n 220,\n 220,\n 220,\n 220,\n 220,\n 1303,\n 361,\n 4235,\n 287,\n 37250,\n 41989,\n 3256,\n 705,\n 20063,\n 26410,\n 14402,\n 6,\n 5974,\n 198,\n 220,\n 220,\n 220,\n 220,\n 220,\n 220,\n 220,\n 1303,\n 220,\n 220,\n 220,\n 1303,\n 51,\n 3558,\n 761,\n 284,\n 1057,\n 287,\n 2656,\n 26672,\n 287,\n 1339,\n 286,\n 2393,\n 20086,\n 198,\n 220,\n 220,\n 220,\n 220,\n 220,\n 220,\n 220,\n 1303,\n 220,\n 220,\n 220,\n 1332,\n 13116,\n 796,\n 20922,\n 14402,\n 7,\n 6978,\n 28,\n 15908,\n 3672,\n 11,\n 15908,\n 62,\n 1069,\n 13955,\n 28,\n 15908,\n 62,\n 1069,\n 13955,\n 8,\n 198,\n 220,\n 220,\n 220,\n 220,\n 220,\n 220,\n 220,\n 1303,\n 220,\n 220,\n 220,\n 3601,\n 10786,\n 39612,\n 25,\n 3256,\n 15908,\n 3672,\n 8,\n 198,\n 220,\n 220,\n 220,\n 220,\n 220,\n 220,\n 220,\n 1303,\n 220,\n 220,\n 220,\n 3601,\n 7,\n 9288,\n 13116,\n 58,\n 16,\n 12962,\n 198,\n 220,\n 220,\n 220,\n 220,\n 198,\n 220,\n 220,\n 220,\n 1303,\n 361,\n 4235,\n 6624,\n 705,\n 20063,\n 26410,\n 14402,\n 10354,\n 198,\n 220,\n 220,\n 220,\n 1303,\n 220,\n 220,\n 220,\n 1303,\n 1532,\n 356,\n 389,\n 4856,\n 329,\n 14601,\n 11,\n 761,\n 284,\n 1332,\n 287,\n 2656,\n 8619,\n 198,\n 220,\n 220,\n 220,\n 1303,\n 220,\n 220,\n 220,\n 1303,\n 220,\n 287,\n 1339,\n 612,\n 389,\n 2393,\n 20086,\n 198,\n 220,\n 220,\n 220,\n 1303,\n 220,\n 220,\n 220,\n 503,\n 6978,\n 28,\n 14202,\n 198,\n 220,\n 220,\n 220,\n 1303,\n 220,\n 220,\n 220,\n 287,\n 5372,\n 28,\n 17821,\n 198,\n 220,\n 220,\n 220,\n 220,\n 198,\n 220,\n 220,\n 220,\n 611,\n 4235,\n 318,\n 6045,\n 25,\n 1441,\n 198,\n 220,\n 220,\n 220,\n 220,\n 198,\n 220,\n 220,\n 220,\n 611,\n 318,\n 39098,\n 7,\n 6978,\n 11,\n 1351,\n 2599,\n 198,\n 220,\n 220,\n 220,\n 220,\n 220,\n 220,\n 220,\n 611,\n 374,\n 9132,\n 343,\n 25,\n 198,\n 220,\n 220,\n 220,\n 220,\n 220,\n 220,\n 220,\n 220,\n 220,\n 220,\n 220,\n 4423,\n 346,\n 13,\n 81,\n 16762,\n 631,\n 7,\n 448,\n 6978,\n 11,\n 8856,\n 62,\n 48277,\n 28,\n 17821,\n 8,\n 198,\n 220,\n 220,\n 220,\n 220,\n 220,\n 220,\n 220,\n 220,\n 220,\n 220,\n 220,\n 1303,\n 12050,\n 1654,\n 356,\n 691,\n 12233,\n 262,\n 8619,\n 319,\n 262,\n 835,\n 287,\n 986,\n 198,\n 220,\n 220,\n 220,\n 220,\n 220,\n 220,\n 220,\n 220,\n 220,\n 220,\n 220,\n 374,\n 9132,\n 343,\n 28,\n 25101,\n 198,\n 220,\n 220,\n 220,\n 220,\n 220,\n 220,\n 220,\n 220,\n 220,\n 220,\n 220,\n 220,\n 198,\n 220,\n 220,\n 220,\n 220,\n 220,\n 220,\n 220,\n 329,\n 4808,\n 6978,\n 287,\n 3108,\n 25,\n 198,\n 220,\n 220,\n 220,\n 220,\n 220,\n 220,\n 220,\n 220,\n 220,\n 220,\n 220,\n 1303,\n 2215,\n 2810,\n 351,\n 3294,\n 29196,\n 11,\n 1429,\n 1123,\n 530,\n 13869,\n 198,\n 220,\n 220,\n 220,\n 220,\n 220,\n 220,\n 220,\n 220,\n 220,\n 220,\n 220,\n 1303,\n 6425,\n 326,\n 850,\n 15908,\n 82,\n 329,\n 1123,\n 8619,\n 460,\n 307,\n 12118,\n 6338,\n 198,\n 220,\n 220,\n 220,\n 220,\n 220,\n 220,\n 220,\n 220,\n 220,\n 220,\n 220,\n 8619,\n 18709,\n 273,\n 28264,\n 6978,\n 11,\n 4235,\n 11,\n 31051,\n 4458,\n 22179,\n 26933,\n 448,\n 6978,\n 11,\n 4808,\n 6978,\n 46570,\n 287,\n 5372,\n 11,\n 198,\n 220,\n 220,\n 220,\n 220,\n 220,\n 220,\n 220,\n 220,\n 220,\n 220,\n 220,\n 220,\n 220,\n 220,\n 220,\n 220,\n 220,\n 220,\n 220,\n 220,\n 220,\n 220,\n 220,\n 220,\n 220,\n 220,\n 220,\n 220,\n 220,\n 220,\n 2291,\n 62,\n 30342,\n 11,\n 26672,\n 62,\n 1069,\n 13955,\n 11,\n 2393,\n 62,\n 1069,\n 13955,\n 11,\n 198,\n 220,\n 220,\n 220,\n 220,\n 220,\n 220,\n 220,\n 220,\n 220,\n 220,\n 220,\n 220,\n 220,\n 220,\n 220,\n 220,\n 220,\n 220,\n 220,\n 220,\n 220,\n 220,\n 220,\n 220,\n 220,\n 220,\n 220,\n 220,\n 220,\n 220,\n 374,\n 9132,\n 343,\n 11,\n 1090,\n 4372,\n 343,\n 11,\n 850,\n 15908,\n 82,\n 11,\n 989,\n 5715,\n 11,\n 2604,\n 7753,\n 8,\n 198,\n 220,\n 220,\n 220,\n 220,\n 220,\n 220,\n 220,\n 1441,\n 628,\n 220,\n 220,\n 220,\n 1303,\n 10468,\n 8410,\n 532,\n 30276,\n 428,\n 523,\n 356,\n 655,\n 1208,\n 530,\n 19328,\n 2099,\n 788,\n 4886,\n 611,\n 2393,\n 393,\n 26672,\n 30,\n 198,\n 220,\n 220,\n 220,\n 2393,\n 62,\n 1069,\n 13955,\n 796,\n 1351,\n 1958,\n 7,\n 7753,\n 62,\n 1069,\n 13955,\n 8,\n 198,\n 220,\n 220,\n 220,\n 26672,\n 62,\n 1069,\n 13955,\n 796,\n 1351,\n 1958,\n 7,\n 15908,\n 62,\n 1069,\n 13955,\n 8,\n 198,\n 220,\n 220,\n 220,\n 220,\n 198,\n 220,\n 220,\n 220,\n 611,\n 503,\n 6978,\n 318,\n 407,\n 6045,\n 290,\n 28686,\n 13,\n 6978,\n 13,\n 1069,\n 1023,\n 7,\n 448,\n 6978,\n 2599,\n 198,\n 220,\n 220,\n 220,\n 220,\n 220,\n 220,\n 220,\n 611,\n 374,\n 9132,\n 343,\n 25,\n 198,\n 220,\n 220,\n 220,\n 220,\n 220,\n 220,\n 220,\n 220,\n 220,\n 220,\n 220,\n 3601,\n 10786,\n 59,\n 77,\n 8162,\n 5005,\n 293,\n 889,\n 8619,\n 4600,\n 90,\n 92,\n 63,\n 290,\n 477,\n 663,\n 10154,\n 1106,\n 8162,\n 59,\n 77,\n 59,\n 77,\n 4458,\n 18982,\n 7,\n 448,\n 6978,\n 4008,\n 198,\n 220,\n 220,\n 220,\n 220,\n 220,\n 220,\n 220,\n 220,\n 220,\n 220,\n 220,\n 4423,\n 346,\n 13,\n 81,\n 16762,\n 631,\n 7,\n 448,\n 6978,\n 11,\n 8856,\n 62,\n 48277,\n 28,\n 17821,\n 8,\n 198,\n 220,\n 220,\n 220,\n 220,\n 220,\n 220,\n 220,\n 2073,\n 25,\n 198,\n 220,\n 220,\n 220,\n 220,\n 220,\n 220,\n 220,\n 220,\n 220,\n 220,\n 220,\n 3601,\n 10786,\n 59,\n 77,\n 26410,\n 8619,\n 4600,\n 90,\n 92,\n 63,\n 1541,\n 7160,\n 13,\n 17220,\n 340,\n 717,\n 416,\n 4634,\n 25,\n 374,\n 9132,\n 343,\n 28,\n 17821,\n 59,\n 77,\n 4458,\n 18982,\n 7,\n 448,\n 6978,\n 4008,\n 198,\n 220,\n 220,\n 220,\n 220,\n 220,\n 220,\n 220,\n 220,\n 198,\n 220,\n 220,\n 220,\n 1303,\n 15908,\n 62,\n 1069,\n 13955,\n 796,\n 17635,\n 611,\n 26672,\n 62,\n 1069,\n 13955,\n 318,\n 6045,\n 2073,\n 26672,\n 62,\n 1069,\n 13955,\n 220,\n 198,\n 220,\n 220,\n 220,\n 1303,\n 7753,\n 62,\n 1069,\n 13955,\n 796,\n 17635,\n 611,\n 2393,\n 62,\n 1069,\n 13955,\n 318,\n 6045,\n 2073,\n 2393,\n 62,\n 1069,\n 13955,\n 198,\n 220,\n 220,\n 220,\n 611,\n 28686,\n 13,\n 6978,\n 13,\n 4468,\n 576,\n 7,\n 6978,\n 2599,\n 198,\n 220,\n 220,\n 220,\n 220,\n 220,\n 220,\n 220,\n 20922,\n 18709,\n 273,\n 7,\n 6978,\n 11,\n 4235,\n 28,\n 14171,\n 11,\n 503,\n 6978,\n 28,\n 448,\n 6978,\n 11,\n 287,\n 5372,\n 28,\n 259,\n 5372,\n 1267,\n 198,\n 220,\n 220,\n 220,\n 1288,\n 361,\n 850,\n 15908,\n 82,\n 25,\n 198,\n 220,\n 220,\n 220,\n 220,\n 220,\n 220,\n 220,\n 329,\n 26672,\n 3672,\n 11,\n 850,\n 15908,\n 82,\n 11,\n 3696,\n 287,\n 28686,\n 13,\n 11152,\n 7,\n 6978,\n 2599,\n 198,\n 220,\n 220,\n 220,\n 220,\n 220,\n 220,\n 220,\n 220,\n 220,\n 220,\n 220,\n 19607,\n 62,\n 23814,\n 7,\n 7266,\n 15908,\n 82,\n 11,\n 26672,\n 62,\n 1069,\n 13955,\n 11,\n 407,\n 2291,\n 62,\n 30342,\n 8,\n 198,\n 220,\n 220,\n 220,\n 220,\n 220,\n 220,\n 220,\n 220,\n 220,\n 220,\n 220,\n 19607,\n 62,\n 23814,\n 7,\n 16624,\n 11,\n 2393,\n 62,\n 1069,\n 13955,\n 11,\n 407,\n 2291,\n 62,\n 30342,\n 8,\n 198,\n 220,\n 220,\n 220,\n 220,\n 220,\n 220,\n 220,\n 220,\n 220,\n 220,\n 220,\n 4808,\n 14681,\n 7,\n 448,\n 6978,\n 8,\n 198,\n 220,\n 220,\n 220,\n 1303,\n 611,\n 3804,\n 257,\n 2060,\n 2393,\n 2138,\n 621,\n 8619,\n 3108,\n 198,\n 220,\n 220,\n 220,\n 2073,\n 25,\n 198,\n 220,\n 220,\n 220,\n 220,\n 220,\n 220,\n 220,\n 3696,\n 28,\n 418,\n 13,\n 4868,\n 15908,\n 7,\n 6978,\n 8,\n 198,\n 220,\n 220,\n 220,\n 220,\n 220,\n 220,\n 220,\n 19607,\n 62,\n 23814,\n 7,\n 16624,\n 11,\n 2393,\n 62,\n 1069,\n 13955,\n 11,\n 407,\n 2291,\n 62,\n 30342,\n 8,\n 198,\n 220,\n 220,\n 220,\n 220,\n 220,\n 220,\n 220,\n 26672,\n 3672,\n 28,\n 6978,\n 198,\n 220,\n 220,\n 220,\n 220,\n 220,\n 220,\n 220,\n 4808,\n 14681,\n 7,\n 448,\n 6978,\n 8,\n 198,\n 220,\n 220,\n 220,\n 220,\n 220,\n 220,\n 220,\n 220,\n 198,\n 2,\n 28768,\n 48992,\n 351,\n 257,\n 2393,\n 62,\n 41341,\n 481,\n 1487,\n 262,\n 2685,\n 1181,\n 287,\n 1459,\n 26672,\n 198,\n 2,\n 2504,\n 318,\n 11,\n 43935,\n 389,\n 13686,\n 287,\n 1295,\n 788,\n 1976,\n 3949,\n 198,\n 2,\n 464,\n 43935,\n 355,\n 1775,\n 287,\n 262,\n 26672,\n 481,\n 4079,\n 883,\n 287,\n 262,\n 19974,\n 7753,\n 198,\n 2,\n 1135,\n 714,\n 13096,\n 428,\n 9172,\n 523,\n 340,\n 857,\n 407,\n 2689,\n 2656,\n 43935,\n 30,\n 198,\n 4299,\n 48992,\n 7,\n 15908,\n 1462,\n 13344,\n 11,\n 19974,\n 34345,\n 11,\n 198,\n 220,\n 220,\n 220,\n 220,\n 220,\n 220,\n 220,\n 220,\n 220,\n 220,\n 2291,\n 62,\n 30342,\n 28,\n 25101,\n 11,\n 198,\n 220,\n 220,\n 220,\n 220,\n 220,\n 220,\n 220,\n 220,\n 220,\n 220,\n 26672,\n 62,\n 1069,\n 13955,\n 28,\n 14202,\n 11,\n 198,\n 220,\n 220,\n 220,\n 220,\n 220,\n 220,\n 220,\n 220,\n 220,\n 220,\n 2393,\n 62,\n 1069,\n 13955,\n 28,\n 14202,\n 11,\n 220,\n 198,\n 220,\n 220,\n 220,\n 220,\n 220,\n 220,\n 220,\n 220,\n 220,\n 220,\n 2393,\n 62,\n 41341,\n 28,\n 14202,\n 11,\n 198,\n 220,\n 220,\n 220,\n 220,\n 220,\n 220,\n 220,\n 220,\n 220,\n 220,\n 989,\n 5715,\n 28,\n 16,\n 11,\n 374,\n 9132,\n 343,\n 28,\n 25101,\n 11,\n 220,\n 198,\n 220,\n 220,\n 220,\n 220,\n 220,\n 220,\n 220,\n 220,\n 220,\n 220,\n 19974,\n 62,\n 33295,\n 28,\n 25101,\n 2599,\n 198,\n 220,\n 220,\n 220,\n 705,\n 7061,\n 38636,\n 262,\n 10154,\n 286,\n 257,\n 8619,\n 290,\n 663,\n 850,\n 12942,\n 1749,\n 705,\n 7061,\n 198,\n 220,\n 220,\n 220,\n 220,\n 220,\n 198,\n 220,\n 220,\n 220,\n 2393,\n 62,\n 1069,\n 13955,\n 796,\n 1351,\n 1958,\n 7,\n 7753,\n 62,\n 1069,\n 13955,\n 8,\n 198,\n 220,\n 220,\n 220,\n 26672,\n 62,\n 1069,\n 13955,\n 796,\n 1351,\n 1958,\n 7,\n 15908,\n 62,\n 1069,\n 13955,\n 8,\n 628,\n 220,\n 220,\n 220,\n 19974,\n 62,\n 525,\n 3411,\n 796,\n 366,\n 64,\n 1,\n 611,\n 19974,\n 62,\n 33295,\n 2073,\n 366,\n 86,\n 1,\n 198,\n 220,\n 220,\n 220,\n 1303,\n 16447,\n 257,\n 649,\n 14,\n 35666,\n 5592,\n 19974,\n 2393,\n 11,\n 2138,\n 621,\n 24443,\n 611,\n 19974,\n 7753,\n 1541,\n 7160,\n 198,\n 220,\n 220,\n 220,\n 1976,\n 69,\n 796,\n 19974,\n 7753,\n 13,\n 41729,\n 8979,\n 7,\n 13344,\n 34345,\n 11,\n 19974,\n 62,\n 525,\n 3411,\n 11,\n 19794,\n 28,\n 13344,\n 7753,\n 13,\n 57,\n 4061,\n 62,\n 7206,\n 3697,\n 11617,\n 8,\n 198,\n 220,\n 220,\n 220,\n 220,\n 198,\n 220,\n 220,\n 220,\n 1303,\n 3987,\n 470,\n 19974,\n 3696,\n 286,\n 976,\n 1438,\n 355,\n 262,\n 19974,\n 2393,\n 356,\n 389,\n 4441,\n 198,\n 220,\n 220,\n 220,\n 2393,\n 62,\n 1069,\n 13955,\n 13,\n 33295,\n 7,\n 13344,\n 34345,\n 8,\n 628,\n 220,\n 220,\n 220,\n 1303,\n 611,\n 356,\n 423,\n 655,\n 257,\n 2060,\n 2393,\n 284,\n 19974,\n 290,\n 407,\n 257,\n 26672,\n 11,\n 19974,\n 326,\n 198,\n 220,\n 220,\n 220,\n 611,\n 28686,\n 13,\n 6978,\n 13,\n 4468,\n 576,\n 7,\n 15908,\n 1462,\n 13344,\n 2599,\n 198,\n 220,\n 220,\n 220,\n 220,\n 220,\n 220,\n 220,\n 1976,\n 69,\n 13,\n 13564,\n 7,\n 15908,\n 1462,\n 13344,\n 8,\n 198,\n 220,\n 220,\n 220,\n 1288,\n 361,\n 28686,\n 13,\n 6978,\n 13,\n 9409,\n 343,\n 7,\n 15908,\n 1462,\n 13344,\n 2599,\n 198,\n 220,\n 220,\n 220,\n 220,\n 220,\n 220,\n 220,\n 1303,\n 5450,\n 1378,\n 25558,\n 2502,\n 11125,\n 13,\n 785,\n 14,\n 64,\n 14,\n 34125,\n 41544,\n 2548,\n 14,\n 2231,\n 2857,\n 4790,\n 198,\n 220,\n 220,\n 220,\n 220,\n 220,\n 220,\n 220,\n 329,\n 26672,\n 3672,\n 11,\n 850,\n 15908,\n 82,\n 11,\n 3696,\n 287,\n 28686,\n 13,\n 11152,\n 7,\n 15908,\n 1462,\n 13344,\n 2599,\n 198,\n 220,\n 220,\n 220,\n 220,\n 220,\n 220,\n 220,\n 220,\n 220,\n 220,\n 220,\n 19607,\n 62,\n 23814,\n 7,\n 7266,\n 15908,\n 82,\n 11,\n 26672,\n 62,\n 1069,\n 13955,\n 11,\n 407,\n 2291,\n 62,\n 30342,\n 8,\n 198,\n 220,\n 220,\n 220,\n 220,\n 220,\n 220,\n 220,\n 220,\n 220,\n 220,\n 220,\n 19607,\n 62,\n 23814,\n 7,\n 16624,\n 11,\n 2393,\n 62,\n 1069,\n 13955,\n 11,\n 407,\n 2291,\n 62,\n 30342,\n 8,\n 198,\n 220,\n 220,\n 220,\n 220,\n 220,\n 220,\n 220,\n 220,\n 220,\n 220,\n 220,\n 3601,\n 10786,\n 18709,\n 278,\n 8619,\n 25,\n 23884,\n 4458,\n 18982,\n 7,\n 15908,\n 3672,\n 4008,\n 198,\n 220,\n 220,\n 220,\n 220,\n 220,\n 220,\n 220,\n 220,\n 220,\n 220,\n 220,\n 1976,\n 69,\n 13,\n 13564,\n 7,\n 15908,\n 3672,\n 8,\n 198,\n 220,\n 220,\n 220,\n 220,\n 220,\n 220,\n 220,\n 220,\n 220,\n 220,\n 220,\n 351,\n 3904,\n 13,\n 33723,\n 5657,\n 7,\n 16624,\n 8,\n 355,\n 2318,\n 25,\n 198,\n 220,\n 220,\n 220,\n 220,\n 220,\n 220,\n 220,\n 220,\n 220,\n 220,\n 220,\n 220,\n 220,\n 220,\n 220,\n 329,\n 29472,\n 287,\n 2318,\n 25,\n 198,\n 220,\n 220,\n 220,\n 220,\n 220,\n 220,\n 220,\n 220,\n 220,\n 220,\n 220,\n 220,\n 220,\n 220,\n 220,\n 220,\n 220,\n 220,\n 220,\n 611,\n 989,\n 5715,\n 29,\n 16,\n 25,\n 4798,\n 7,\n 34345,\n 8,\n 198,\n 220,\n 220,\n 220,\n 220,\n 220,\n 220,\n 220,\n 220,\n 220,\n 220,\n 220,\n 220,\n 220,\n 220,\n 220,\n 220,\n 220,\n 220,\n 220,\n 2393,\n 6978,\n 3672,\n 28,\n 418,\n 13,\n 6978,\n 13,\n 22179,\n 7,\n 15908,\n 3672,\n 11,\n 29472,\n 8,\n 198,\n 220,\n 220,\n 220,\n 220,\n 220,\n 220,\n 220,\n 220,\n 220,\n 220,\n 220,\n 220,\n 220,\n 220,\n 220,\n 220,\n 220,\n 220,\n 220,\n 1303,\n 1858,\n 318,\n 645,\n 966,\n 1262,\n 705,\n 5143,\n 10354,\n 611,\n 612,\n 318,\n 281,\n 4049,\n 11,\n 299,\n 65,\n 1102,\n 1851,\n 481,\n 2038,\n 198,\n 220,\n 220,\n 220,\n 220,\n 220,\n 220,\n 220,\n 220,\n 220,\n 220,\n 220,\n 220,\n 220,\n 220,\n 220,\n 220,\n 220,\n 220,\n 220,\n 611,\n 2393,\n 62,\n 41341,\n 287,\n 37250,\n 20063,\n 26410,\n 3256,\n 705,\n 5143,\n 3152,\n 9139,\n 5965,\n 20520,\n 290,\n 29472,\n 13,\n 437,\n 2032,\n 342,\n 7,\n 4458,\n 541,\n 2047,\n 65,\n 6,\n 2599,\n 198,\n 220,\n 220,\n 220,\n 220,\n 220,\n 220,\n 220,\n 220,\n 220,\n 220,\n 220,\n 220,\n 220,\n 220,\n 220,\n 220,\n 220,\n 220,\n 220,\n 220,\n 220,\n 220,\n 220,\n 1303,\n 1212,\n 20718,\n 1735,\n 3048,\n 532,\n 43935,\n 389,\n 13686,\n 287,\n 1459,\n 3108,\n 198,\n 220,\n 220,\n 220,\n 220,\n 220,\n 220,\n 220,\n 220,\n 220,\n 220,\n 220,\n 220,\n 220,\n 220,\n 220,\n 220,\n 220,\n 220,\n 220,\n 220,\n 220,\n 220,\n 220,\n 1303,\n 19926,\n 356,\n 466,\n 428,\n 287,\n 257,\n 45218,\n 7753,\n 30,\n 198,\n 220,\n 220,\n 220,\n 220,\n 220,\n 220,\n 220,\n 220,\n 220,\n 220,\n 220,\n 220,\n 220,\n 220,\n 220,\n 220,\n 220,\n 220,\n 220,\n 220,\n 220,\n 220,\n 220,\n 20922,\n 18709,\n 273,\n 7,\n 7753,\n 6978,\n 3672,\n 11,\n 4235,\n 28,\n 7753,\n 62,\n 41341,\n 11,\n 287,\n 5372,\n 28,\n 17821,\n 8,\n 198,\n 220,\n 220,\n 220,\n 220,\n 220,\n 220,\n 220,\n 220,\n 220,\n 220,\n 220,\n 220,\n 220,\n 220,\n 220,\n 220,\n 220,\n 220,\n 220,\n 1976,\n 69,\n 13,\n 13564,\n 7,\n 7753,\n 6978,\n 3672,\n 8,\n 198,\n 220,\n 220,\n 220,\n 1976,\n 69,\n 13,\n 19836,\n 3419,\n 198,\n 220,\n 220,\n 220,\n 220,\n 198,\n 220,\n 220,\n 220,\n 1303,\n 3792,\n 428,\n 1165,\n 17564,\n 12248,\n 198,\n 220,\n 220,\n 220,\n 1303,\n 361,\n 374,\n 9132,\n 343,\n 25,\n 4423,\n 346,\n 13,\n 81,\n 16762,\n 631,\n 7,\n 15908,\n 1462,\n 13344,\n 11,\n 8856,\n 62,\n 48277,\n 28,\n 17821,\n 8,\n 198,\n 220,\n 220,\n 220,\n 1441,\n 19974,\n 34345,\n 198,\n 220,\n 220,\n 220,\n 220,\n 198,\n 4299,\n 2641,\n 41729,\n 7,\n 89,\n 22184,\n 11,\n 989,\n 28,\n 17821,\n 2599,\n 198,\n 220,\n 220,\n 220,\n 705,\n 7061,\n 6803,\n 2641,\n 257,\n 19974,\n 2393,\n 13,\n 198,\n 220,\n 220,\n 220,\n 220,\n 220,\n 220,\n 220,\n 383,\n 989,\n 4909,\n 1440,\n 15180,\n 25,\n 2393,\n 62,\n 7857,\n 11,\n 2393,\n 25388,\n 2546,\n 11,\n 4818,\n 8079,\n 290,\n 29472,\n 13,\n 198,\n 220,\n 220,\n 220,\n 220,\n 220,\n 220,\n 220,\n 25700,\n 989,\n 28,\n 17821,\n 5860,\n 257,\n 2495,\n 10398,\n 989,\n 13,\n 705,\n 7061,\n 198,\n 220,\n 220,\n 220,\n 611,\n 407,\n 28686,\n 13,\n 6978,\n 13,\n 4468,\n 576,\n 7,\n 89,\n 22184,\n 2599,\n 198,\n 220,\n 220,\n 220,\n 220,\n 220,\n 220,\n 220,\n 3601,\n 7203,\n 59,\n 77,\n 44217,\n 986,\n 23884,\n 1595,\n 470,\n 1283,\n 284,\n 307,\n 257,\n 2393,\n 30,\n 59,\n 77,\n 1911,\n 18982,\n 7,\n 89,\n 22184,\n 4008,\n 198,\n 220,\n 220,\n 220,\n 220,\n 220,\n 220,\n 220,\n 1441,\n 198,\n 220,\n 220,\n 220,\n 3601,\n 10786,\n 59,\n 77,\n 15784,\n 2641,\n 19974,\n 7753,\n 25,\n 23884,\n 59,\n 77,\n 4458,\n 18982,\n 7,\n 89,\n 22184,\n 4008,\n 198,\n 220,\n 220,\n 220,\n 277,\n 89,\n 28,\n 13344,\n 7753,\n 13,\n 41729,\n 8979,\n 7,\n 89,\n 22184,\n 8,\n 198,\n 220,\n 220,\n 220,\n 220,\n 198,\n 220,\n 220,\n 220,\n 256,\n 742,\n 28,\n 21737,\n 198,\n 220,\n 220,\n 220,\n 329,\n 24714,\n 287,\n 277,\n 89,\n 13,\n 259,\n 9062,\n 396,\n 33529,\n 198,\n 220,\n 220,\n 220,\n 220,\n 220,\n 220,\n 220,\n 256,\n 742,\n 13,\n 33295,\n 7,\n 685,\n 22184,\n 13,\n 7753,\n 62,\n 7857,\n 11,\n 198,\n 220,\n 220,\n 220,\n 220,\n 220,\n 220,\n 220,\n 220,\n 220,\n 220,\n 220,\n 220,\n 220,\n 220,\n 220,\n 220,\n 220,\n 220,\n 220,\n 220,\n 24714,\n 13,\n 5589,\n 601,\n 62,\n 7857,\n 11,\n 198,\n 220,\n 220,\n 220,\n 220,\n 220,\n 220,\n 220,\n 220,\n 220,\n 220,\n 220,\n 220,\n 220,\n 220,\n 220,\n 220,\n 220,\n 220,\n 220,\n 220,\n 4818,\n 8079,\n 13,\n 19608,\n 8079,\n 46491,\n 22184,\n 13,\n 4475,\n 62,\n 2435,\n 737,\n 26786,\n 18982,\n 22784,\n 198,\n 220,\n 220,\n 220,\n 220,\n 220,\n 220,\n 220,\n 220,\n 220,\n 220,\n 220,\n 220,\n 220,\n 220,\n 220,\n 220,\n 220,\n 220,\n 220,\n 220,\n 24714,\n 13,\n 34345,\n 60,\n 1267,\n 198,\n 220,\n 220,\n 220,\n 220,\n 220,\n 220,\n 220,\n 3601,\n 10786,\n 90,\n 5512,\n 1391,\n 5512,\n 1391,\n 5512,\n 23884,\n 4458,\n 18982,\n 7,\n 22184,\n 13,\n 7753,\n 62,\n 7857,\n 11,\n 198,\n 220,\n 220,\n 220,\n 220,\n 220,\n 220,\n 220,\n 220,\n 220,\n 220,\n 220,\n 220,\n 220,\n 220,\n 220,\n 220,\n 220,\n 220,\n 220,\n 220,\n 24714,\n 13,\n 5589,\n 601,\n 62,\n 7857,\n 11,\n 198,\n 220,\n 220,\n 220,\n 220,\n 220,\n 220,\n 220,\n 220,\n 220,\n 220,\n 220,\n 220,\n 220,\n 220,\n 220,\n 220,\n 220,\n 220,\n 220,\n 220,\n 4818,\n 8079,\n 13,\n 19608,\n 8079,\n 46491,\n 22184,\n 13,\n 4475,\n 62,\n 2435,\n 737,\n 26786,\n 18982,\n 22784,\n 198,\n 220,\n 220,\n 220,\n 220,\n 220,\n 220,\n 220,\n 220,\n 220,\n 220,\n 220,\n 220,\n 220,\n 220,\n 220,\n 220,\n 220,\n 220,\n 220,\n 220,\n 24714,\n 13,\n 34345,\n 4008,\n 198,\n 220,\n 220,\n 220,\n 7400,\n 5039,\n 7,\n 14116,\n 11,\n 24697,\n 28,\n 17816,\n 13295,\n 41707,\n 41729,\n 41707,\n 27354,\n 8079,\n 41707,\n 15235,\n 6,\n 4357,\n 11487,\n 69,\n 16762,\n 2625,\n 36439,\n 4943,\n 198,\n 220,\n 220,\n 220,\n 1441,\n 256,\n 742,\n 220,\n 220,\n 198,\n 198,\n 31,\n 12976,\n 13,\n 21812,\n 3419,\n 198,\n 31,\n 12976,\n 13,\n 18076,\n 10786,\n 438,\n 7753,\n 12,\n 41341,\n 3256,\n 29001,\n 81,\n 3256,\n 2099,\n 28,\n 12976,\n 13,\n 46770,\n 7,\n 17816,\n 20063,\n 26410,\n 3256,\n 705,\n 5143,\n 3152,\n 9139,\n 5965,\n 20520,\n 4008,\n 198,\n 31,\n 12976,\n 13,\n 18076,\n 10786,\n 438,\n 17256,\n 12,\n 30342,\n 16624,\n 3256,\n 705,\n 12,\n 39,\n 3256,\n 318,\n 62,\n 32109,\n 28,\n 17821,\n 11,\n 1037,\n 11639,\n 818,\n 9152,\n 7104,\n 3696,\n 11537,\n 198,\n 31,\n 12976,\n 13,\n 18076,\n 10786,\n 438,\n 1069,\n 9152,\n 12,\n 15908,\n 3256,\n 705,\n 12,\n 55,\n 3256,\n 3294,\n 28,\n 17821,\n 11,\n 2099,\n 28,\n 12976,\n 13,\n 15235,\n 7,\n 411,\n 6442,\n 62,\n 6978,\n 28,\n 25101,\n 828,\n 1037,\n 11639,\n 3109,\n 9152,\n 7368,\n 8619,\n 11537,\n 198,\n 31,\n 12976,\n 13,\n 18076,\n 10786,\n 438,\n 1069,\n 9152,\n 12,\n 7753,\n 3256,\n 29001,\n 87,\n 3256,\n 3294,\n 28,\n 17821,\n 11,\n 4906,\n 28,\n 12976,\n 13,\n 15235,\n 7,\n 411,\n 6442,\n 62,\n 6978,\n 28,\n 25101,\n 828,\n 1037,\n 11639,\n 3109,\n 9152,\n 7368,\n 2393,\n 11537,\n 198,\n 31,\n 12976,\n 13,\n 18076,\n 10786,\n 438,\n 13344,\n 62,\n 33295,\n 3256,\n 29001,\n 64,\n 3256,\n 318,\n 62,\n 32109,\n 28,\n 17821,\n 11,\n 1037,\n 11639,\n 4550,\n 284,\n 4683,\n 19974,\n 2393,\n 11537,\n 198,\n 31,\n 12976,\n 13,\n 49140,\n 10786,\n 6978,\n 3256,\n 2099,\n 28,\n 12976,\n 13,\n 15235,\n 7,\n 411,\n 6442,\n 62,\n 6978,\n 28,\n 25101,\n 4008,\n 198,\n 2,\n 31,\n 12976,\n 13,\n 49140,\n 10786,\n 13344,\n 7753,\n 3256,\n 2099,\n 28,\n 12976,\n 13,\n 8979,\n 10786,\n 39346,\n 6,\n 4008,\n 198,\n 31,\n 12976,\n 13,\n 49140,\n 10786,\n 13344,\n 7753,\n 3256,\n 2099,\n 28,\n 12976,\n 13,\n 15235,\n 28955,\n 198,\n 4299,\n 537,\n 72,\n 62,\n 13344,\n 7,\n 7753,\n 62,\n 41341,\n 11,\n 2291,\n 62,\n 30342,\n 16624,\n 11,\n 19607,\n 62,\n 15908,\n 11,\n 19607,\n 62,\n 7753,\n 11,\n 19974,\n 62,\n 33295,\n 11,\n 3108,\n 11,\n 19974,\n 7753,\n 2599,\n 198,\n 220,\n 220,\n 220,\n 37227,\n 16447,\n 257,\n 19974,\n 2393,\n 422,\n 262,\n 10154,\n 286,\n 257,\n 7368,\n 8619,\n 13,\n 198,\n 220,\n 220,\n 220,\n 220,\n 198,\n 220,\n 220,\n 220,\n 383,\n 48992,\n 460,\n 42976,\n 1057,\n 257,\n 20922,\n 12649,\n 319,\n 43935,\n 878,\n 1976,\n 4501,\n 606,\n 284,\n 2198,\n 326,\n 477,\n 4778,\n 389,\n 1057,\n 393,\n 477,\n 4778,\n 389,\n 12539,\n 13,\n 198,\n 220,\n 220,\n 220,\n 37227,\n 198,\n 220,\n 220,\n 220,\n 3601,\n 10786,\n 1639,\n 1276,\n 307,\n 7165,\n 1262,\n 428,\n 986,\n 11537,\n 628,\n 220,\n 220,\n 220,\n 611,\n 407,\n 19974,\n 62,\n 33295,\n 25,\n 198,\n 220,\n 220,\n 220,\n 220,\n 220,\n 220,\n 220,\n 3601,\n 7,\n 69,\n 1,\n 59,\n 77,\n 5886,\n 16502,\n 597,\n 2180,\n 1391,\n 13344,\n 7753,\n 92,\n 2393,\n 59,\n 77,\n 4943,\n 198,\n 220,\n 220,\n 220,\n 2073,\n 25,\n 198,\n 220,\n 220,\n 220,\n 220,\n 220,\n 220,\n 220,\n 3601,\n 7,\n 69,\n 1,\n 59,\n 77,\n 4677,\n 1571,\n 1976,\n 3949,\n 3696,\n 284,\n 25,\n 1391,\n 13344,\n 7753,\n 32239,\n 77,\n 4943,\n 628,\n 220,\n 220,\n 220,\n 24714,\n 796,\n 48992,\n 7,\n 6978,\n 11,\n 19974,\n 7753,\n 11,\n 198,\n 220,\n 220,\n 220,\n 220,\n 220,\n 220,\n 220,\n 220,\n 220,\n 220,\n 220,\n 220,\n 220,\n 220,\n 220,\n 2291,\n 62,\n 30342,\n 28,\n 17256,\n 62,\n 30342,\n 16624,\n 11,\n 198,\n 220,\n 220,\n 220,\n 220,\n 220,\n 220,\n 220,\n 220,\n 220,\n 220,\n 220,\n 220,\n 220,\n 220,\n 220,\n 26672,\n 62,\n 1069,\n 13955,\n 28,\n 1069,\n 9152,\n 62,\n 15908,\n 11,\n 198,\n 220,\n 220,\n 220,\n 220,\n 220,\n 220,\n 220,\n 220,\n 220,\n 220,\n 220,\n 220,\n 220,\n 220,\n 220,\n 2393,\n 62,\n 1069,\n 13955,\n 28,\n 1069,\n 9152,\n 62,\n 7753,\n 11,\n 220,\n 198,\n 220,\n 220,\n 220,\n 220,\n 220,\n 220,\n 220,\n 220,\n 220,\n 220,\n 220,\n 220,\n 220,\n 220,\n 220,\n 2393,\n 62,\n 41341,\n 28,\n 7753,\n 62,\n 41341,\n 11,\n 198,\n 220,\n 220,\n 220,\n 220,\n 220,\n 220,\n 220,\n 220,\n 220,\n 220,\n 220,\n 220,\n 220,\n 220,\n 220,\n 19974,\n 62,\n 33295,\n 28,\n 13344,\n 62,\n 33295,\n 8,\n 628,\n 220,\n 220,\n 220,\n 3601,\n 7,\n 69,\n 1,\n 59,\n 77,\n 41729,\n 2393,\n 25,\n 1391,\n 22184,\n 32239,\n 77,\n 4943,\n 198,\n 198,\n 31,\n 12976,\n 13,\n 21812,\n 3419,\n 198,\n 31,\n 12976,\n 13,\n 18076,\n 10786,\n 438,\n 39624,\n 3256,\n 705,\n 12,\n 80,\n 3256,\n 318,\n 62,\n 32109,\n 28,\n 17821,\n 11,\n 1037,\n 11639,\n 15979,\n 601,\n 262,\n 989,\n 2637,\n 8,\n 198,\n 31,\n 12976,\n 13,\n 18076,\n 10786,\n 438,\n 40539,\n 654,\n 3256,\n 705,\n 12,\n 86,\n 3256,\n 318,\n 62,\n 32109,\n 28,\n 17821,\n 11,\n 1037,\n 11639,\n 23114,\n 14601,\n 11537,\n 198,\n 31,\n 12976,\n 13,\n 49140,\n 10786,\n 34345,\n 3256,\n 2099,\n 28,\n 12976,\n 13,\n 15235,\n 7,\n 411,\n 6442,\n 62,\n 6978,\n 28,\n 17821,\n 828,\n 77,\n 22046,\n 10779,\n 16,\n 8,\n 198,\n 4299,\n 537,\n 72,\n 62,\n 13344,\n 1177,\n 7,\n 34345,\n 11,\n 14601,\n 11,\n 5897,\n 2599,\n 198,\n 220,\n 220,\n 220,\n 37227,\n 8053,\n 262,\n 10154,\n 286,\n 530,\n 393,\n 517,\n 7368,\n 19974,\n 16624,\n 13,\n 198,\n 220,\n 220,\n 220,\n 37227,\n 198,\n 220,\n 220,\n 220,\n 19974,\n 62,\n 3642,\n 658,\n 796,\n 17635,\n 198,\n 220,\n 220,\n 220,\n 329,\n 277,\n 287,\n 1351,\n 1958,\n 7,\n 34345,\n 2599,\n 198,\n 220,\n 220,\n 220,\n 220,\n 220,\n 220,\n 220,\n 19974,\n 62,\n 3642,\n 658,\n 13,\n 33295,\n 19510,\n 69,\n 11,\n 2641,\n 41729,\n 7,\n 69,\n 22305,\n 628,\n 220,\n 220,\n 220,\n 611,\n 14601,\n 290,\n 19974,\n 62,\n 3642,\n 658,\n 25,\n 198,\n 220,\n 220,\n 220,\n 220,\n 220,\n 220,\n 220,\n 329,\n 357,\n 47347,\n 11,\n 2378,\n 8,\n 287,\n 19974,\n 62,\n 3642,\n 658,\n 25,\n 198,\n 220,\n 220,\n 220,\n 220,\n 220,\n 220,\n 220,\n 220,\n 220,\n 220,\n 220,\n 3601,\n 7,\n 69,\n 1,\n 59,\n 77,\n 59,\n 77,\n 50155,\n 38636,\n 2393,\n 3081,\n 989,\n 25,\n 1391,\n 47347,\n 92,\n 29335,\n 28,\n 59,\n 77,\n 4943,\n 198,\n 220,\n 220,\n 220,\n 220,\n 220,\n 220,\n 220,\n 220,\n 220,\n 220,\n 220,\n 329,\n 1700,\n 287,\n 2378,\n 25,\n 198,\n 220,\n 220,\n 220,\n 220,\n 220,\n 220,\n 220,\n 220,\n 220,\n 220,\n 220,\n 220,\n 220,\n 220,\n 220,\n 611,\n 1700,\n 58,\n 16,\n 60,\n 1875,\n 352,\n 68,\n 21,\n 25,\n 198,\n 220,\n 220,\n 220,\n 220,\n 220,\n 220,\n 220,\n 220,\n 220,\n 220,\n 220,\n 220,\n 220,\n 220,\n 220,\n 220,\n 220,\n 220,\n 220,\n 3601,\n 7,\n 69,\n 1,\n 31502,\n 25,\n 19990,\n 90,\n 22105,\n 58,\n 18,\n 48999,\n 7879,\n 3073,\n 2407,\n 1588,\n 2393,\n 37913,\n 10734,\n 1096,\n 13,\n 77,\n 2541,\n 874,\n 1096,\n 7,\n 22105,\n 58,\n 15,\n 12962,\n 92,\n 555,\n 89,\n 3949,\n 11,\n 1391,\n 10734,\n 1096,\n 13,\n 77,\n 2541,\n 874,\n 1096,\n 7,\n 22105,\n 58,\n 16,\n 12962,\n 92,\n 25388,\n 8,\n 4943,\n 198,\n 220,\n 220,\n 220,\n 220,\n 220,\n 220,\n 220,\n 220,\n 220,\n 220,\n 220,\n 220,\n 220,\n 220,\n 220,\n 329,\n 4808,\n 6978,\n 287,\n 1700,\n 58,\n 18,\n 4083,\n 35312,\n 10786,\n 14,\n 6,\n 2599,\n 198,\n 220,\n 220,\n 220,\n 220,\n 220,\n 220,\n 220,\n 220,\n 220,\n 220,\n 220,\n 220,\n 220,\n 220,\n 220,\n 220,\n 220,\n 220,\n 220,\n 611,\n 18896,\n 28264,\n 6978,\n 8,\n 1875,\n 2026,\n 25,\n 198,\n 220,\n 220,\n 220,\n 220,\n 220,\n 220,\n 220,\n 220,\n 220,\n 220,\n 220,\n 220,\n 220,\n 220,\n 220,\n 220,\n 220,\n 220,\n 220,\n 220,\n 220,\n 220,\n 220,\n 3601,\n 7,\n 69,\n 1,\n 24908,\n 25,\n 262,\n 2393,\n 6978,\n 5002,\n 19990,\n 90,\n 62,\n 6978,\n 92,\n 7879,\n 287,\n 19990,\n 90,\n 22105,\n 58,\n 18,\n 48999,\n 7879,\n 318,\n 1165,\n 890,\n 357,\n 9806,\n 13,\n 2026,\n 34534,\n 8,\n 4943,\n 198,\n 220,\n 220,\n 220,\n 220,\n 220,\n 220,\n 220,\n 220,\n 220,\n 220,\n 220,\n 220,\n 220,\n 220,\n 220,\n 220,\n 220,\n 220,\n 220,\n 611,\n 4808,\n 6978,\n 13,\n 9688,\n 2032,\n 342,\n 7203,\n 526,\n 2599,\n 198,\n 220,\n 220,\n 220,\n 220,\n 220,\n 220,\n 220,\n 220,\n 220,\n 220,\n 220,\n 220,\n 220,\n 220,\n 220,\n 220,\n 220,\n 220,\n 220,\n 220,\n 220,\n 220,\n 220,\n 3601,\n 7,\n 69,\n 1,\n 31502,\n 25,\n 19990,\n 90,\n 22105,\n 58,\n 18,\n 48999,\n 7879,\n 318,\n 257,\n 7104,\n 2393,\n 14,\n 34945,\n 357,\n 4598,\n 345,\n 1107,\n 761,\n 340,\n 287,\n 262,\n 19974,\n 2393,\n 10091,\n 4943,\n 198,\n 220,\n 220,\n 220,\n 220,\n 220,\n 220,\n 220,\n 3601,\n 7203,\n 59,\n 77,\n 4770,\n 2559,\n 18604,\n 59,\n 77,\n 59,\n 77,\n 4943,\n 628,\n 198,\n 31,\n 12976,\n 13,\n 21812,\n 3419,\n 198,\n 31,\n 12976,\n 13,\n 18076,\n 10786,\n 438,\n 1069,\n 9152,\n 12,\n 15908,\n 3256,\n 29001,\n 55,\n 3256,\n 3294,\n 28,\n 17821,\n 11,\n 4906,\n 28,\n 12976,\n 13,\n 15235,\n 7,\n 411,\n 6442,\n 62,\n 6978,\n 28,\n 25101,\n 828,\n 1037,\n 11639,\n 5211,\n 407,\n 664,\n 12321,\n 832,\n 7368,\n 8619,\n 618,\n 40525,\n 5254,\n 2637,\n 8,\n 198,\n 31,\n 12976,\n 13,\n 18076,\n 10786,\n 438,\n 1069,\n 9152,\n 12,\n 7753,\n 3256,\n 29001,\n 87,\n 3256,\n 3294,\n 28,\n 17821,\n 11,\n 4906,\n 28,\n 12976,\n 13,\n 15235,\n 7,\n 411,\n 6442,\n 62,\n 6978,\n 28,\n 25101,\n 828,\n 1037,\n 11639,\n 3109,\n 9152,\n 7368,\n 2393,\n 11537,\n 198,\n 31,\n 12976,\n 13,\n 18076,\n 10786,\n 438,\n 448,\n 7753,\n 3256,\n 29001,\n 78,\n 3256,\n 2099,\n 28,\n 12976,\n 13,\n 15235,\n 7,\n 411,\n 6442,\n 62,\n 6978,\n 28,\n 25101,\n 828,\n 1037,\n 11639,\n 26410,\n 989,\n 2393,\n 13,\n 17446,\n 428,\n 9178,\n 284,\n 3359,\n 989,\n 319,\n 3141,\n 1627,\n 2637,\n 8,\n 198,\n 31,\n 12976,\n 13,\n 49140,\n 10786,\n 9288,\n 23814,\n 3256,\n 2099,\n 28,\n 12976,\n 13,\n 15235,\n 7,\n 411,\n 6442,\n 62,\n 6978,\n 28,\n 25101,\n 828,\n 77,\n 22046,\n 10779,\n 16,\n 8,\n 198,\n 4299,\n 537,\n 72,\n 62,\n 46803,\n 9288,\n 7,\n 19607,\n 62,\n 15908,\n 11,\n 19607,\n 62,\n 7753,\n 11,\n 503,\n 7753,\n 11,\n 1332,\n 23814,\n 2599,\n 198,\n 220,\n 220,\n 220,\n 37227,\n 14402,\n 7368,\n 43935,\n 290,\n 14,\n 273,\n 262,\n 43935,\n 287,\n 257,\n 7368,\n 8619,\n 393,\n 29196,\n 357,\n 63,\n 51,\n 6465,\n 2043,\n 39201,\n 63,\n 8,\n 1262,\n 262,\n 4600,\n 77,\n 17457,\n 524,\n 63,\n 13877,\n 329,\n 4600,\n 9078,\n 13,\n 9288,\n 44646,\n 198,\n 220,\n 220,\n 220,\n 220,\n 198,\n 220,\n 220,\n 220,\n 18162,\n 4600,\n 17209,\n 35273,\n 46803,\n 9288,\n 63,\n 1231,\n 597,\n 7368,\n 8619,\n 393,\n 2393,\n 481,\n 25432,\n 5254,\n 664,\n 1834,\n 2280,\n 422,\n 262,\n 1459,\n 8619,\n 866,\n 526,\n 15931,\n 198,\n 220,\n 220,\n 220,\n 1332,\n 23814,\n 796,\n 1332,\n 23814,\n 393,\n 705,\n 2637,\n 198,\n 220,\n 220,\n 220,\n 4808,\n 11295,\n 2070,\n 14402,\n 7,\n 9288,\n 23814,\n 11,\n 503,\n 7753,\n 11,\n 19607,\n 62,\n 15908,\n 11,\n 19607,\n 62,\n 7753,\n 8,\n 628,\n 198,\n 31,\n 12976,\n 13,\n 21812,\n 3419,\n 198,\n 31,\n 12976,\n 13,\n 18076,\n 10786,\n 438,\n 7753,\n 12,\n 41341,\n 3256,\n 29001,\n 81,\n 3256,\n 2099,\n 28,\n 12976,\n 13,\n 46770,\n 7,\n 17816,\n 20063,\n 26410,\n 3256,\n 705,\n 5143,\n 3152,\n 9139,\n 5965,\n 20520,\n 828,\n 1037,\n 11639,\n 8979,\n 12649,\n 4028,\n 326,\n 460,\n 307,\n 5625,\n 284,\n 43935,\n 1262,\n 4600,\n 46803,\n 1102,\n 1851,\n 63,\n 11537,\n 198,\n 31,\n 12976,\n 13,\n 18076,\n 10786,\n 438,\n 448,\n 6978,\n 3256,\n 705,\n 12,\n 46,\n 3256,\n 2099,\n 28,\n 12976,\n 13,\n 15235,\n 7,\n 411,\n 6442,\n 62,\n 6978,\n 28,\n 25101,\n 828,\n 1037,\n 11639,\n 6978,\n 284,\n 5072,\n 8619,\n 11537,\n 198,\n 31,\n 12976,\n 13,\n 18076,\n 10786,\n 438,\n 259,\n 5372,\n 14,\n 438,\n 3919,\n 12,\n 259,\n 5372,\n 3256,\n 12286,\n 28,\n 17821,\n 11,\n 1037,\n 11639,\n 10987,\n 20399,\n 319,\n 43935,\n 287,\n 5372,\n 11537,\n 198,\n 31,\n 12976,\n 13,\n 18076,\n 10786,\n 438,\n 1069,\n 9152,\n 12,\n 15908,\n 3256,\n 705,\n 12,\n 55,\n 3256,\n 3294,\n 28,\n 17821,\n 11,\n 2099,\n 28,\n 12976,\n 13,\n 15235,\n 7,\n 411,\n 6442,\n 62,\n 6978,\n 28,\n 25101,\n 828,\n 1037,\n 11639,\n 3109,\n 9152,\n 7368,\n 8619,\n 11537,\n 198,\n 31,\n 12976,\n 13,\n 18076,\n 10786,\n 438,\n 1069,\n 9152,\n 12,\n 7753,\n 3256,\n 29001,\n 87,\n 3256,\n 3294,\n 28,\n 17821,\n 11,\n 4906,\n 28,\n 12976,\n 13,\n 15235,\n 7,\n 411,\n 6442,\n 62,\n 6978,\n 28,\n 25101,\n 828,\n 1037,\n 11639,\n 3109,\n 9152,\n 7368,\n 2393,\n 11537,\n 198,\n 31,\n 12976,\n 13,\n 18076,\n 10786,\n 438,\n 17256,\n 12,\n 30342,\n 14,\n 438,\n 3919,\n 12,\n 17256,\n 12,\n 30342,\n 3256,\n 12286,\n 28,\n 25101,\n 11,\n 1037,\n 11639,\n 818,\n 9152,\n 7104,\n 3696,\n 11537,\n 198,\n 31,\n 12976,\n 13,\n 18076,\n 10786,\n 438,\n 81,\n 9132,\n 343,\n 14,\n 438,\n 3919,\n 12,\n 81,\n 9132,\n 343,\n 3256,\n 12286,\n 28,\n 25101,\n 11,\n 1037,\n 11639,\n 9787,\n 262,\n 5072,\n 8619,\n 318,\n 6565,\n 878,\n 356,\n 779,\n 340,\n 11537,\n 198,\n 31,\n 12976,\n 13,\n 18076,\n 10786,\n 438,\n 22019,\n 4372,\n 343,\n 14,\n 438,\n 3919,\n 12,\n 22019,\n 4372,\n 343,\n 3256,\n 12286,\n 28,\n 25101,\n 11,\n 1037,\n 11639,\n 18709,\n 3696,\n 287,\n 1459,\n 8619,\n 11537,\n 198,\n 31,\n 12976,\n 13,\n 18076,\n 10786,\n 438,\n 7266,\n 15908,\n 82,\n 14,\n 438,\n 3919,\n 12,\n 7266,\n 15908,\n 82,\n 3256,\n 12286,\n 28,\n 17821,\n 11,\n 1037,\n 11639,\n 18709,\n 3696,\n 287,\n 850,\n 12942,\n 1749,\n 11537,\n 198,\n 31,\n 12976,\n 13,\n 18076,\n 10786,\n 438,\n 13116,\n 5715,\n 3256,\n 4277,\n 28,\n 16,\n 11,\n 1037,\n 11639,\n 42159,\n 1241,\n 11537,\n 198,\n 31,\n 12976,\n 13,\n 49140,\n 10786,\n 6978,\n 3256,\n 4906,\n 28,\n 12976,\n 13,\n 15235,\n 7,\n 411,\n 6442,\n 62,\n 6978,\n 28,\n 25101,\n 4008,\n 198,\n 4299,\n 537,\n 72,\n 62,\n 77,\n 1671,\n 403,\n 7,\n 7753,\n 62,\n 41341,\n 11,\n 503,\n 6978,\n 11,\n 287,\n 5372,\n 11,\n 19607,\n 62,\n 15908,\n 11,\n 19607,\n 62,\n 7753,\n 11,\n 2291,\n 62,\n 30342,\n 11,\n 374,\n 9132,\n 343,\n 11,\n 1090,\n 4372,\n 343,\n 11,\n 850,\n 15908,\n 82,\n 11,\n 989,\n 5715,\n 11,\n 3108,\n 2599,\n 198,\n 220,\n 220,\n 220,\n 37227,\n 43055,\n 12649,\n 329,\n 43935,\n 532,\n 3578,\n 262,\n 2836,\n 284,\n 1057,\n 299,\n 65,\n 1102,\n 1851,\n 4560,\n 319,\n 43935,\n 11,\n 884,\n 355,\n 2491,\n 477,\n 4778,\n 393,\n 17304,\n 477,\n 4778,\n 13,\n 198,\n 220,\n 220,\n 220,\n 220,\n 198,\n 220,\n 220,\n 220,\n 1675,\n 1057,\n 5254,\n 11,\n 779,\n 25,\n 256,\n 76,\n 35273,\n 46803,\n 9288,\n 198,\n 220,\n 220,\n 220,\n 220,\n 198,\n 220,\n 220,\n 220,\n 1675,\n 19974,\n 24512,\n 357,\n 4480,\n 262,\n 3038,\n 393,\n 2491,\n 20922,\n 20399,\n 319,\n 1976,\n 3949,\n 3696,\n 828,\n 779,\n 25,\n 256,\n 76,\n 35273,\n 13344,\n 198,\n 220,\n 220,\n 220,\n 37227,\n 198,\n 220,\n 220,\n 220,\n 8619,\n 18709,\n 273,\n 7,\n 6978,\n 11,\n 198,\n 220,\n 220,\n 220,\n 220,\n 220,\n 220,\n 220,\n 220,\n 220,\n 220,\n 220,\n 220,\n 220,\n 220,\n 220,\n 220,\n 220,\n 220,\n 220,\n 220,\n 220,\n 220,\n 4235,\n 28,\n 7753,\n 62,\n 41341,\n 11,\n 503,\n 6978,\n 28,\n 448,\n 6978,\n 11,\n 287,\n 5372,\n 28,\n 259,\n 5372,\n 11,\n 198,\n 220,\n 220,\n 220,\n 220,\n 220,\n 220,\n 220,\n 220,\n 220,\n 220,\n 220,\n 220,\n 220,\n 220,\n 220,\n 220,\n 220,\n 220,\n 220,\n 220,\n 220,\n 220,\n 2291,\n 62,\n 30342,\n 28,\n 17256,\n 62,\n 30342,\n 11,\n 198,\n 220,\n 220,\n 220,\n 220,\n 220,\n 220,\n 220,\n 220,\n 220,\n 220,\n 220,\n 220,\n 220,\n 220,\n 220,\n 220,\n 220,\n 220,\n 220,\n 220,\n 220,\n 220,\n 26672,\n 62,\n 1069,\n 13955,\n 28,\n 1069,\n 9152,\n 62,\n 15908,\n 11,\n 198,\n 220,\n 220,\n 220,\n 220,\n 220,\n 220,\n 220,\n 220,\n 220,\n 220,\n 220,\n 220,\n 220,\n 220,\n 220,\n 220,\n 220,\n 220,\n 220,\n 220,\n 220,\n 220,\n 2393,\n 62,\n 1069,\n 13955,\n 28,\n 1069,\n 9152,\n 62,\n 7753,\n 11,\n 374,\n 9132,\n 343,\n 28,\n 81,\n 9132,\n 343,\n 11,\n 1090,\n 4372,\n 343,\n 28,\n 22019,\n 4372,\n 343,\n 11,\n 198,\n 220,\n 220,\n 220,\n 220,\n 220,\n 220,\n 220,\n 220,\n 220,\n 220,\n 220,\n 220,\n 220,\n 220,\n 220,\n 220,\n 220,\n 220,\n 220,\n 220,\n 220,\n 220,\n 850,\n 15908,\n 82,\n 28,\n 7266,\n 15908,\n 82,\n 11,\n 13116,\n 5715,\n 28,\n 13116,\n 5715,\n 8,\n 628,\n 628,\n 198,\n 6738,\n 33084,\n 1330,\n 38994,\n 198,\n 11748,\n 651,\n 6603,\n 198,\n 198,\n 11748,\n 2779,\n 2414,\n 198,\n 11748,\n 18931,\n 198,\n 6738,\n 33084,\n 13,\n 38,\n 10060,\n 16922,\n 1330,\n 38994,\n 16922,\n 198,\n 198,\n 4299,\n 651,\n 62,\n 26270,\n 62,\n 1640,\n 62,\n 12985,\n 7,\n 260,\n 1930,\n 37765,\n 11,\n 7621,\n 2599,\n 198,\n 220,\n 220,\n 220,\n 37227,\n 198,\n 220,\n 220,\n 220,\n 16409,\n 257,\n 4589,\n 9485,\n 38,\n 10060,\n 2134,\n 329,\n 262,\n 7368,\n 16099,\n 290,\n 7621,\n 13,\n 198,\n 220,\n 220,\n 220,\n 37227,\n 198,\n 220,\n 220,\n 220,\n 13737,\n 796,\n 16099,\n 13,\n 1136,\n 62,\n 1671,\n 12140,\n 3419,\n 198,\n 220,\n 220,\n 220,\n 14451,\n 62,\n 1671,\n 12140,\n 796,\n 685,\n 15699,\n 329,\n 2872,\n 287,\n 13737,\n 611,\n 2872,\n 13,\n 3672,\n 6624,\n 7621,\n 60,\n 198,\n 220,\n 220,\n 220,\n 611,\n 14451,\n 62,\n 1671,\n 12140,\n 25,\n 198,\n 220,\n 220,\n 220,\n 220,\n 220,\n 220,\n 220,\n 1441,\n 14451,\n 62,\n 1671,\n 12140,\n 58,\n 15,\n 4083,\n 41509,\n 13,\n 26270,\n 628,\n 220,\n 220,\n 220,\n 15940,\n 796,\n 16099,\n 13,\n 1136,\n 62,\n 31499,\n 3419,\n 198,\n 220,\n 220,\n 220,\n 14451,\n 62,\n 31499,\n 796,\n 685,\n 15699,\n 329,\n 2872,\n 287,\n 15940,\n 611,\n 2872,\n 13,\n 3672,\n 6624,\n 7621,\n 60,\n 198,\n 220,\n 220,\n 220,\n 611,\n 407,\n 14451,\n 62,\n 31499,\n 25,\n 198,\n 220,\n 220,\n 220,\n 220,\n 220,\n 220,\n 220,\n 5298,\n 11052,\n 12331,\n 10786,\n 2949,\n 17467,\n 393,\n 20551,\n 7160,\n 351,\n 326,\n 1438,\n 11537,\n 198,\n 220,\n 220,\n 220,\n 1441,\n 14451,\n 62,\n 31499,\n 58,\n 15,\n 4083,\n 41509,\n 13,\n 26270,\n 198,\n 198,\n 4299,\n 4321,\n 62,\n 34945,\n 7,\n 260,\n 1930,\n 37765,\n 11,\n 427,\n 64,\n 11,\n 4382,\n 62,\n 6978,\n 11,\n 503,\n 6978,\n 11639,\n 456,\n 62,\n 15002,\n 82,\n 3256,\n 2393,\n 62,\n 41341,\n 28,\n 14202,\n 2599,\n 198,\n 220,\n 220,\n 220,\n 37227,\n 198,\n 220,\n 220,\n 220,\n 10472,\n 477,\n 10154,\n 379,\n 4382,\n 62,\n 6978,\n 351,\n 4589,\n 7621,\n 427,\n 64,\n 287,\n 198,\n 220,\n 220,\n 220,\n 262,\n 16099,\n 13,\n 198,\n 220,\n 220,\n 220,\n 37227,\n 198,\n 220,\n 220,\n 220,\n 10154,\n 796,\n 16099,\n 13,\n 1136,\n 62,\n 15908,\n 62,\n 3642,\n 658,\n 7,\n 15388,\n 62,\n 6978,\n 11,\n 1006,\n 28,\n 26270,\n 8,\n 198,\n 220,\n 220,\n 220,\n 611,\n 407,\n 28686,\n 13,\n 6978,\n 13,\n 1069,\n 1023,\n 7,\n 448,\n 6978,\n 2599,\n 198,\n 220,\n 220,\n 220,\n 220,\n 220,\n 220,\n 220,\n 28686,\n 13,\n 76,\n 4335,\n 17062,\n 7,\n 448,\n 6978,\n 8,\n 198,\n 220,\n 220,\n 220,\n 220,\n 220,\n 220,\n 220,\n 220,\n 220,\n 220,\n 220,\n 220,\n 198,\n 220,\n 220,\n 220,\n 329,\n 2695,\n 287,\n 10154,\n 25,\n 198,\n 220,\n 220,\n 220,\n 220,\n 220,\n 220,\n 220,\n 3601,\n 7203,\n 10002,\n 278,\n 25,\n 4064,\n 82,\n 1,\n 4064,\n 2695,\n 13,\n 6978,\n 8,\n 198,\n 220,\n 220,\n 220,\n 220,\n 220,\n 220,\n 220,\n 611,\n 2695,\n 13,\n 4906,\n 6624,\n 705,\n 15908,\n 10354,\n 198,\n 220,\n 220,\n 220,\n 220,\n 220,\n 220,\n 220,\n 220,\n 220,\n 220,\n 220,\n 4321,\n 62,\n 34945,\n 7,\n 260,\n 1930,\n 37765,\n 11,\n 427,\n 64,\n 11,\n 2695,\n 13,\n 6978,\n 11,\n 31051,\n 4458,\n 22179,\n 26933,\n 448,\n 6978,\n 11,\n 11299,\n 13,\n 3672,\n 60,\n 4008,\n 198,\n 220,\n 220,\n 220,\n 220,\n 220,\n 220,\n 220,\n 2073,\n 25,\n 198,\n 220,\n 220,\n 220,\n 220,\n 220,\n 220,\n 220,\n 220,\n 220,\n 220,\n 220,\n 1949,\n 25,\n 198,\n 220,\n 220,\n 220,\n 220,\n 220,\n 220,\n 220,\n 220,\n 220,\n 220,\n 220,\n 220,\n 220,\n 220,\n 220,\n 3108,\n 796,\n 2695,\n 13,\n 6978,\n 198,\n 220,\n 220,\n 220,\n 220,\n 220,\n 220,\n 220,\n 220,\n 220,\n 220,\n 220,\n 220,\n 220,\n 220,\n 220,\n 2393,\n 62,\n 11299,\n 796,\n 16099,\n 13,\n 1136,\n 62,\n 3642,\n 658,\n 7,\n 6978,\n 11,\n 1006,\n 28,\n 26270,\n 8,\n 198,\n 220,\n 220,\n 220,\n 220,\n 220,\n 220,\n 220,\n 220,\n 220,\n 220,\n 220,\n 220,\n 220,\n 220,\n 220,\n 2393,\n 62,\n 7890,\n 796,\n 2779,\n 2414,\n 13,\n 65,\n 2414,\n 12501,\n 1098,\n 7,\n 7753,\n 62,\n 11299,\n 13,\n 11299,\n 8,\n 198,\n 220,\n 220,\n 220,\n 220,\n 220,\n 220,\n 220,\n 220,\n 220,\n 220,\n 220,\n 220,\n 220,\n 220,\n 220,\n 503,\n 6978,\n 7753,\n 11639,\n 14,\n 4458,\n 22179,\n 26933,\n 448,\n 6978,\n 11,\n 11299,\n 13,\n 3672,\n 12962,\n 198,\n 220,\n 220,\n 220,\n 220,\n 220,\n 220,\n 220,\n 220,\n 220,\n 220,\n 220,\n 220,\n 220,\n 220,\n 220,\n 2393,\n 62,\n 448,\n 796,\n 1280,\n 7,\n 448,\n 6978,\n 7753,\n 11,\n 366,\n 39346,\n 4943,\n 198,\n 220,\n 220,\n 220,\n 220,\n 220,\n 220,\n 220,\n 220,\n 220,\n 220,\n 220,\n 220,\n 220,\n 220,\n 220,\n 2393,\n 62,\n 448,\n 13,\n 13564,\n 7,\n 7753,\n 62,\n 7890,\n 8,\n 198,\n 220,\n 220,\n 220,\n 220,\n 220,\n 220,\n 220,\n 220,\n 220,\n 220,\n 220,\n 220,\n 220,\n 220,\n 220,\n 2393,\n 62,\n 448,\n 13,\n 19836,\n 3419,\n 198,\n 220,\n 220,\n 220,\n 220,\n 220,\n 220,\n 220,\n 220,\n 220,\n 220,\n 220,\n 2845,\n 357,\n 9399,\n 12331,\n 11,\n 33084,\n 13,\n 38,\n 10060,\n 16922,\n 8,\n 355,\n 2859,\n 25,\n 198,\n 220,\n 220,\n 220,\n 220,\n 220,\n 220,\n 220,\n 220,\n 220,\n 220,\n 220,\n 220,\n 220,\n 220,\n 220,\n 1303,\n 1532,\n 356,\n 2038,\n 625,\n 780,\n 286,\n 257,\n 1588,\n 4130,\n 11,\n 779,\n 262,\n 1366,\n 40391,\n 329,\n 262,\n 4321,\n 198,\n 220,\n 220,\n 220,\n 220,\n 220,\n 220,\n 220,\n 220,\n 220,\n 220,\n 220,\n 220,\n 220,\n 220,\n 220,\n 1005,\n 11,\n 18224,\n 28,\n 41194,\n 13,\n 22046,\n 198,\n 220,\n 220,\n 220,\n 220,\n 220,\n 220,\n 220,\n 220,\n 220,\n 220,\n 220,\n 220,\n 220,\n 220,\n 220,\n 611,\n 705,\n 20500,\n 6,\n 287,\n 4049,\n 290,\n 4049,\n 17816,\n 20500,\n 20520,\n 855,\n 6,\n 3673,\n 4062,\n 10354,\n 198,\n 220,\n 220,\n 220,\n 220,\n 220,\n 220,\n 220,\n 220,\n 220,\n 220,\n 220,\n 220,\n 220,\n 220,\n 220,\n 220,\n 220,\n 220,\n 220,\n 3601,\n 10786,\n 44217,\n 986,\n 2393,\n 407,\n 1043,\n 30,\n 23884,\n 4458,\n 18982,\n 7,\n 6978,\n 4008,\n 198,\n 220,\n 220,\n 220,\n 220,\n 220,\n 220,\n 220,\n 220,\n 220,\n 220,\n 220,\n 220,\n 220,\n 220,\n 220,\n 1288,\n 361,\n 705,\n 48277,\n 6,\n 287,\n 4049,\n 290,\n 4049,\n 17816,\n 48277,\n 6,\n 7131,\n 15,\n 7131,\n 6,\n 8189,\n 20520,\n 855,\n 6,\n 18820,\n 62,\n 11664,\n 10354,\n 198,\n 220,\n 220,\n 220,\n 220,\n 220,\n 220,\n 220,\n 220,\n 220,\n 220,\n 220,\n 220,\n 220,\n 220,\n 220,\n 220,\n 220,\n 220,\n 220,\n 1303,\n 4798,\n 10786,\n 986,\n 11664,\n 2393,\n 11,\n 2111,\n 44812,\n 4321,\n 2427,\n 986,\n 11537,\n 198,\n 220,\n 220,\n 220,\n 220,\n 220,\n 220,\n 220,\n 220,\n 220,\n 220,\n 220,\n 220,\n 220,\n 220,\n 220,\n 220,\n 220,\n 220,\n 220,\n 2393,\n 62,\n 11299,\n 796,\n 16099,\n 13,\n 1136,\n 62,\n 18300,\n 62,\n 2436,\n 672,\n 7,\n 11299,\n 13,\n 26270,\n 8,\n 198,\n 220,\n 220,\n 220,\n 220,\n 220,\n 220,\n 220,\n 220,\n 220,\n 220,\n 220,\n 220,\n 220,\n 220,\n 220,\n 220,\n 220,\n 220,\n 220,\n 2393,\n 62,\n 7890,\n 796,\n 2779,\n 2414,\n 13,\n 65,\n 2414,\n 12501,\n 1098,\n 7,\n 7753,\n 62,\n 11299,\n 13,\n 11299,\n 8,\n 198,\n 220,\n 220,\n 220,\n 220,\n 220,\n 220,\n 220,\n 220,\n 220,\n 220,\n 220,\n 220,\n 220,\n 220,\n 220,\n 220,\n 220,\n 220,\n 220,\n 2393,\n 62,\n 448,\n 796,\n 1280,\n 10786,\n 14,\n 4458,\n 22179,\n 26933,\n 448,\n 6978,\n 11,\n 11299,\n 13,\n 3672,\n 46570,\n 366,\n 39346,\n 4943,\n 198,\n 220,\n 220,\n 220,\n 220,\n 220,\n 220,\n 220,\n 220,\n 220,\n 220,\n 220,\n 220,\n 220,\n 220,\n 220,\n 220,\n 220,\n 220,\n 220,\n 2393,\n 62,\n 448,\n 13,\n 13564,\n 7,\n 7753,\n 62,\n 7890,\n 8,\n 198,\n 220,\n 220,\n 220,\n 220,\n 220,\n 220,\n 220,\n 220,\n 220,\n 220,\n 220,\n 220,\n 220,\n 220,\n 220,\n 220,\n 220,\n 220,\n 220,\n 2393,\n 62,\n 448,\n 13,\n 19836,\n 3419,\n 198,\n 220,\n 220,\n 220,\n 220,\n 220,\n 220,\n 220,\n 220,\n 220,\n 220,\n 220,\n 220,\n 220,\n 220,\n 220,\n 1303,\n 6404,\n 2667,\n 13,\n 18224,\n 10786,\n 12331,\n 7587,\n 4064,\n 82,\n 25,\n 4064,\n 82,\n 3256,\n 2695,\n 13,\n 6978,\n 11,\n 2859,\n 8,\n 198,\n 220,\n 220,\n 220,\n 220,\n 220,\n 220,\n 220,\n 220,\n 220,\n 220,\n 220,\n 1303,\n 361,\n 2695,\n 13,\n 3672,\n 13,\n 437,\n 2032,\n 342,\n 7,\n 4458,\n 541,\n 2047,\n 65,\n 11537,\n 290,\n 2393,\n 62,\n 41341,\n 287,\n 37250,\n 20063,\n 26410,\n 3256,\n 705,\n 20063,\n 26410,\n 14402,\n 41707,\n 5143,\n 3152,\n 9139,\n 5965,\n 6,\n 2361,\n 25,\n 198,\n 220,\n 220,\n 220,\n 220,\n 220,\n 220,\n 220,\n 220,\n 220,\n 220,\n 220,\n 1303,\n 220,\n 220,\n 220,\n 220,\n 220,\n 220,\n 220,\n 20922,\n 18709,\n 273,\n 7,\n 448,\n 6978,\n 7753,\n 11,\n 2393,\n 62,\n 41341,\n 8,\n 628,\n 198,\n 7206,\n 38865,\n 62,\n 2200,\n 16402,\n 11639,\n 4625,\n 39239,\n 774,\n 14,\n 17209,\n 35273,\n 6,\n 198,\n 198,\n 31,\n 12976,\n 13,\n 21812,\n 3419,\n 198,\n 31,\n 12976,\n 13,\n 18076,\n 10786,\n 438,\n 12567,\n 12,\n 7220,\n 3256,\n 705,\n 12,\n 84,\n 3256,\n 220,\n 1037,\n 2625,\n 7120,\n 38994,\n 20579,\n 19570,\n 198,\n 31,\n 12976,\n 13,\n 18076,\n 10786,\n 438,\n 28712,\n 3256,\n 7808,\n 62,\n 15414,\n 28,\n 17821,\n 11,\n 198,\n 220,\n 220,\n 220,\n 220,\n 220,\n 220,\n 220,\n 220,\n 220,\n 220,\n 220,\n 220,\n 220,\n 12641,\n 62,\n 16963,\n 457,\n 28,\n 25101,\n 8,\n 198,\n 31,\n 12976,\n 13,\n 18076,\n 10786,\n 438,\n 260,\n 7501,\n 3256,\n 29001,\n 81,\n 3256,\n 6152,\n 11639,\n 6207,\n 13264,\n 37913,\n 30072,\n 4458,\n 18982,\n 7,\n 7206,\n 38865,\n 62,\n 2200,\n 16402,\n 828,\n 198,\n 220,\n 220,\n 220,\n 220,\n 220,\n 220,\n 220,\n 220,\n 220,\n 220,\n 220,\n 220,\n 220,\n 1037,\n 11639,\n 6207,\n 13264,\n 1438,\n 11537,\n 198,\n 31,\n 12976,\n 13,\n 18076,\n 10786,\n 438,\n 1671,\n 3702,\n 3256,\n 29001,\n 65,\n 3256,\n 16794,\n 11639,\n 33,\n 25642,\n 393,\n 7621,\n 284,\n 4321,\n 11537,\n 198,\n 31,\n 12976,\n 13,\n 18076,\n 10786,\n 438,\n 34945,\n 3256,\n 1037,\n 11639,\n 43055,\n 284,\n 4321,\n 357,\n 273,\n 25,\n 477,\n 8,\n 11537,\n 198,\n 31,\n 12976,\n 13,\n 18076,\n 10786,\n 438,\n 82,\n 9586,\n 343,\n 3256,\n 4906,\n 28,\n 12976,\n 13,\n 15235,\n 7,\n 411,\n 6442,\n 62,\n 6978,\n 28,\n 25101,\n 828,\n 198,\n 220,\n 220,\n 220,\n 220,\n 220,\n 220,\n 220,\n 220,\n 220,\n 220,\n 220,\n 220,\n 220,\n 1037,\n 11639,\n 43055,\n 284,\n 4321,\n 29924,\n 1220,\n 29924,\n 26672,\n 656,\n 26,\n 4277,\n 318,\n 26672,\n 1438,\n 11537,\n 198,\n 31,\n 12976,\n 13,\n 18076,\n 10786,\n 438,\n 7753,\n 12,\n 41341,\n 3256,\n 2099,\n 28,\n 12976,\n 13,\n 46770,\n 7,\n 17816,\n 20063,\n 26410,\n 3256,\n 705,\n 5143,\n 3152,\n 9139,\n 5965,\n 20520,\n 828,\n 1037,\n 11639,\n 19722,\n 453,\n 11986,\n 257,\n 2393,\n 12649,\n 284,\n 307,\n 1057,\n 1028,\n 15680,\n 43935,\n 2637,\n 8,\n 198,\n 31,\n 12976,\n 13,\n 18076,\n 10786,\n 438,\n 13344,\n 14,\n 438,\n 3919,\n 12,\n 13344,\n 3256,\n 4277,\n 28,\n 25101,\n 11,\n 1037,\n 11639,\n 19722,\n 453,\n 2251,\n 257,\n 19974,\n 2393,\n 286,\n 262,\n 15680,\n 16099,\n 14,\n 34945,\n 351,\n 262,\n 976,\n 1438,\n 355,\n 262,\n 16099,\n 14,\n 34945,\n 2637,\n 8,\n 198,\n 31,\n 12976,\n 13,\n 18076,\n 10786,\n 438,\n 18439,\n 14,\n 438,\n 3919,\n 12,\n 18439,\n 3256,\n 4277,\n 28,\n 17821,\n 11,\n 1037,\n 2625,\n 3886,\n 4277,\n 11,\n 1057,\n 351,\n 6284,\n 357,\n 16963,\n 457,\n 329,\n 18031,\n 8,\n 4943,\n 198,\n 31,\n 12976,\n 13,\n 18076,\n 10786,\n 438,\n 4480,\n 12,\n 41989,\n 3256,\n 29001,\n 83,\n 3256,\n 271,\n 62,\n 32109,\n 28,\n 17821,\n 11,\n 1037,\n 2625,\n 10987,\n 5254,\n 319,\n 43935,\n 706,\n 4321,\n 4943,\n 198,\n 31,\n 12976,\n 13,\n 18076,\n 10786,\n 438,\n 6404,\n 7753,\n 3256,\n 4906,\n 28,\n 12976,\n 13,\n 15235,\n 7,\n 411,\n 6442,\n 62,\n 6978,\n 28,\n 25101,\n 828,\n 1037,\n 11639,\n 15235,\n 284,\n 2604,\n 7753,\n 11537,\n 198,\n 4299,\n 537,\n 72,\n 62,\n 18300,\n 260,\n 1930,\n 7,\n 12567,\n 62,\n 7220,\n 11,\n 9206,\n 11,\n 29924,\n 11,\n 8478,\n 11,\n 8619,\n 11,\n 7448,\n 343,\n 11,\n 2393,\n 62,\n 41341,\n 11,\n 19974,\n 11,\n 6284,\n 11,\n 351,\n 62,\n 41989,\n 11,\n 2604,\n 7753,\n 2599,\n 198,\n 220,\n 220,\n 220,\n 37227,\n 10002,\n 3696,\n 422,\n 257,\n 7368,\n 8478,\n 287,\n 257,\n 1948,\n 17606,\n 16099,\n 13,\n 198,\n 220,\n 220,\n 220,\n 220,\n 198,\n 220,\n 220,\n 220,\n 383,\n 4321,\n 460,\n 635,\n 307,\n 3614,\n 284,\n 655,\n 262,\n 10154,\n 286,\n 257,\n 7368,\n 8619,\n 13,\n 198,\n 220,\n 220,\n 220,\n 220,\n 198,\n 220,\n 220,\n 220,\n 2094,\n 470,\n 5490,\n 326,\n 612,\n 804,\n 284,\n 307,\n 257,\n 1256,\n 286,\n 7159,\n 532,\n 345,\n 481,\n 307,\n 12053,\n 329,\n 606,\n 611,\n 345,\n 655,\n 1057,\n 25,\n 256,\n 76,\n 35273,\n 18300,\n 260,\n 1930,\n 198,\n 220,\n 220,\n 220,\n 37227,\n 198,\n 220,\n 220,\n 220,\n 220,\n 198,\n 220,\n 220,\n 220,\n 611,\n 6284,\n 393,\n 33084,\n 62,\n 7220,\n 25,\n 198,\n 220,\n 220,\n 220,\n 220,\n 220,\n 220,\n 220,\n 611,\n 407,\n 33084,\n 62,\n 7220,\n 25,\n 33084,\n 62,\n 7220,\n 796,\n 3904,\n 13,\n 16963,\n 457,\n 10786,\n 59,\n 77,\n 38,\n 10060,\n 20579,\n 11537,\n 198,\n 220,\n 220,\n 220,\n 220,\n 220,\n 220,\n 220,\n 611,\n 407,\n 9206,\n 25,\n 9206,\n 796,\n 3904,\n 13,\n 16963,\n 457,\n 10786,\n 59,\n 77,\n 38,\n 10060,\n 9206,\n 3256,\n 7808,\n 62,\n 15414,\n 28,\n 17821,\n 8,\n 198,\n 220,\n 220,\n 220,\n 220,\n 220,\n 220,\n 220,\n 33084,\n 796,\n 38994,\n 7,\n 12567,\n 62,\n 7220,\n 11,\n 9206,\n 8,\n 198,\n 220,\n 220,\n 220,\n 220,\n 220,\n 220,\n 220,\n 1303,\n 15307,\n 356,\n 821,\n 5291,\n 645,\n 9206,\n 986,\n 198,\n 220,\n 220,\n 220,\n 220,\n 220,\n 220,\n 220,\n 9206,\n 796,\n 6045,\n 198,\n 220,\n 220,\n 220,\n 220,\n 220,\n 220,\n 220,\n 6284,\n 796,\n 6407,\n 198,\n 220,\n 220,\n 220,\n 2073,\n 25,\n 33084,\n 796,\n 38994,\n 3419,\n 628,\n 198,\n 220,\n 220,\n 220,\n 611,\n 6284,\n 25,\n 198,\n 220,\n 220,\n 220,\n 220,\n 220,\n 220,\n 220,\n 2836,\n 796,\n 33084,\n 13,\n 1136,\n 62,\n 7220,\n 3419,\n 198,\n 220,\n 220,\n 220,\n 220,\n 220,\n 220,\n 220,\n 1303,\n 9971,\n 38189,\n 796,\n 33084,\n 13,\n 1136,\n 62,\n 7220,\n 22446,\n 1136,\n 62,\n 2398,\n 82,\n 3419,\n 198,\n 220,\n 220,\n 220,\n 220,\n 220,\n 220,\n 220,\n 3601,\n 10786,\n 11187,\n 2667,\n 656,\n 17606,\n 355,\n 23884,\n 37913,\n 30072,\n 4458,\n 18982,\n 7,\n 12567,\n 62,\n 7220,\n 11,\n 2836,\n 13,\n 3672,\n 4008,\n 198,\n 220,\n 220,\n 220,\n 220,\n 198,\n 220,\n 220,\n 220,\n 29924,\n 796,\n 29924,\n 393,\n 5550,\n 38865,\n 62,\n 2200,\n 16402,\n 198,\n 220,\n 220,\n 220,\n 16099,\n 796,\n 33084,\n 13,\n 1136,\n 62,\n 260,\n 7501,\n 7,\n 260,\n 7501,\n 8,\n 628,\n 220,\n 220,\n 220,\n 611,\n 407,\n 8478,\n 25,\n 198,\n 220,\n 220,\n 220,\n 220,\n 220,\n 220,\n 220,\n 3601,\n 10786,\n 59,\n 77,\n 9414,\n 12140,\n 1695,\n 7479,\n 77,\n 59,\n 83,\n 90,\n 92,\n 4458,\n 18982,\n 10786,\n 59,\n 77,\n 59,\n 83,\n 4458,\n 22179,\n 7,\n 12567,\n 62,\n 260,\n 7501,\n 62,\n 1671,\n 12140,\n 7,\n 260,\n 1930,\n 37765,\n 4008,\n 15306,\n 198,\n 220,\n 220,\n 220,\n 220,\n 220,\n 220,\n 220,\n 8478,\n 796,\n 3904,\n 13,\n 16963,\n 457,\n 10786,\n 59,\n 77,\n 13828,\n 8478,\n 30,\n 357,\n 9866,\n 8,\n 11537,\n 628,\n 220,\n 220,\n 220,\n 8478,\n 62,\n 273,\n 62,\n 12985,\n 62,\n 1462,\n 62,\n 15002,\n 796,\n 8478,\n 393,\n 705,\n 9866,\n 6,\n 198,\n 220,\n 220,\n 220,\n 427,\n 64,\n 796,\n 651,\n 62,\n 26270,\n 62,\n 1640,\n 62,\n 12985,\n 7,\n 260,\n 1930,\n 37765,\n 11,\n 8478,\n 62,\n 273,\n 62,\n 12985,\n 62,\n 1462,\n 62,\n 15002,\n 8,\n 198,\n 220,\n 220,\n 220,\n 220,\n 198,\n 220,\n 220,\n 220,\n 1194,\n 796,\n 10148,\n 198,\n 220,\n 220,\n 220,\n 981,\n 1194,\n 0,\n 11639,\n 12,\n 10354,\n 198,\n 220,\n 220,\n 220,\n 220,\n 220,\n 220,\n 220,\n 611,\n 407,\n 8619,\n 25,\n 198,\n 220,\n 220,\n 220,\n 220,\n 220,\n 220,\n 220,\n 220,\n 220,\n 220,\n 220,\n 611,\n 8478,\n 0,\n 11639,\n 9866,\n 10354,\n 198,\n 220,\n 220,\n 220,\n 220,\n 220,\n 220,\n 220,\n 220,\n 220,\n 220,\n 220,\n 220,\n 220,\n 220,\n 220,\n 10154,\n 796,\n 16099,\n 13,\n 1136,\n 62,\n 15908,\n 62,\n 3642,\n 658,\n 10786,\n 2637,\n 11,\n 1006,\n 28,\n 26270,\n 8,\n 198,\n 220,\n 220,\n 220,\n 220,\n 220,\n 220,\n 220,\n 220,\n 220,\n 220,\n 220,\n 2073,\n 25,\n 198,\n 220,\n 220,\n 220,\n 220,\n 220,\n 220,\n 220,\n 220,\n 220,\n 220,\n 220,\n 220,\n 220,\n 220,\n 220,\n 10154,\n 796,\n 16099,\n 13,\n 1136,\n 62,\n 15908,\n 62,\n 3642,\n 658,\n 10786,\n 2637,\n 8,\n 198,\n 220,\n 220,\n 220,\n 220,\n 220,\n 220,\n 220,\n 220,\n 220,\n 220,\n 220,\n 3601,\n 10786,\n 59,\n 77,\n 1639,\n 460,\n 4321,\n 477,\n 29196,\n 422,\n 428,\n 29924,\n 357,\n 439,\n 8,\n 393,\n 2922,\n 530,\n 7479,\n 77,\n 59,\n 83,\n 90,\n 92,\n 4458,\n 18982,\n 10786,\n 59,\n 77,\n 59,\n 83,\n 4458,\n 22179,\n 7,\n 12567,\n 62,\n 260,\n 7501,\n 62,\n 4852,\n 15908,\n 82,\n 7,\n 3642,\n 658,\n 35514,\n 198,\n 220,\n 220,\n 220,\n 220,\n 220,\n 220,\n 220,\n 220,\n 220,\n 220,\n 220,\n 8619,\n 796,\n 3904,\n 13,\n 16963,\n 457,\n 10786,\n 13828,\n 8619,\n 30,\n 357,\n 439,\n 8,\n 11537,\n 628,\n 220,\n 220,\n 220,\n 220,\n 220,\n 220,\n 220,\n 8619,\n 62,\n 1462,\n 62,\n 15002,\n 796,\n 705,\n 2637,\n 611,\n 357,\n 1662,\n 8619,\n 393,\n 8619,\n 855,\n 6,\n 439,\n 11537,\n 2073,\n 8619,\n 198,\n 220,\n 220,\n 220,\n 220,\n 220,\n 220,\n 220,\n 503,\n 6978,\n 796,\n 7448,\n 343,\n 393,\n 8619,\n 62,\n 1462,\n 62,\n 15002,\n 198,\n 220,\n 220,\n 220,\n 220,\n 220,\n 220,\n 220,\n 611,\n 503,\n 6978,\n 6624,\n 705,\n 2637,\n 290,\n 7448,\n 343,\n 5145,\n 11639,\n 2637,\n 25,\n 503,\n 6978,\n 28,\n 260,\n 7501,\n 13,\n 33491,\n 10786,\n 14,\n 41707,\n 62,\n 11537,\n 10,\n 6,\n 62,\n 16624,\n 6,\n 198,\n 220,\n 220,\n 220,\n 220,\n 220,\n 220,\n 220,\n 220,\n 198,\n 220,\n 220,\n 220,\n 220,\n 220,\n 220,\n 220,\n 31456,\n 11639,\n 59,\n 77,\n 16454,\n 986,\n 22023,\n 23884,\n 14,\n 90,\n 92,\n 4458,\n 18982,\n 7,\n 260,\n 7501,\n 11,\n 34945,\n 62,\n 1462,\n 62,\n 15002,\n 1267,\n 220,\n 198,\n 220,\n 220,\n 220,\n 220,\n 220,\n 220,\n 220,\n 611,\n 2393,\n 62,\n 41341,\n 318,\n 407,\n 6045,\n 25,\n 198,\n 220,\n 220,\n 220,\n 220,\n 220,\n 220,\n 220,\n 220,\n 220,\n 220,\n 220,\n 31456,\n 796,\n 31456,\n 1343,\n 705,\n 1262,\n 20922,\n 12649,\n 25,\n 23884,\n 4458,\n 18982,\n 7,\n 7753,\n 62,\n 41341,\n 8,\n 198,\n 220,\n 220,\n 220,\n 220,\n 220,\n 220,\n 220,\n 2073,\n 25,\n 31456,\n 796,\n 31456,\n 1343,\n 705,\n 351,\n 645,\n 20922,\n 7587,\n 6,\n 198,\n 220,\n 220,\n 220,\n 220,\n 220,\n 220,\n 220,\n 3601,\n 7,\n 19662,\n 8,\n 198,\n 220,\n 220,\n 220,\n 220,\n 220,\n 220,\n 220,\n 4321,\n 62,\n 34945,\n 7,\n 260,\n 1930,\n 37765,\n 11,\n 427,\n 64,\n 11,\n 8619,\n 62,\n 1462,\n 62,\n 15002,\n 11,\n 503,\n 6978,\n 11,\n 7753,\n 62,\n 41341,\n 1267,\n 628,\n 220,\n 220,\n 220,\n 220,\n 220,\n 220,\n 220,\n 611,\n 2393,\n 62,\n 41341,\n 287,\n 37250,\n 20063,\n 26410,\n 3256,\n 705,\n 20063,\n 26410,\n 14402,\n 41707,\n 5143,\n 3152,\n 9139,\n 5965,\n 6,\n 2361,\n 25,\n 198,\n 220,\n 220,\n 220,\n 220,\n 220,\n 220,\n 220,\n 220,\n 220,\n 220,\n 220,\n 3904,\n 13,\n 30328,\n 10786,\n 59,\n 77,\n 28768,\n 20922,\n 12649,\n 25,\n 23884,\n 4458,\n 18982,\n 7,\n 7753,\n 62,\n 41341,\n 4008,\n 198,\n 220,\n 220,\n 220,\n 220,\n 220,\n 220,\n 220,\n 220,\n 220,\n 220,\n 220,\n 8619,\n 18709,\n 273,\n 7,\n 448,\n 6978,\n 11,\n 4235,\n 28,\n 7753,\n 62,\n 41341,\n 11,\n 850,\n 15908,\n 82,\n 28,\n 17821,\n 11,\n 198,\n 220,\n 220,\n 220,\n 220,\n 220,\n 220,\n 220,\n 220,\n 220,\n 220,\n 220,\n 220,\n 220,\n 220,\n 220,\n 220,\n 220,\n 220,\n 220,\n 220,\n 220,\n 220,\n 220,\n 220,\n 220,\n 220,\n 220,\n 220,\n 220,\n 220,\n 220,\n 989,\n 5715,\n 28,\n 16,\n 11,\n 2604,\n 7753,\n 28,\n 6404,\n 7753,\n 8,\n 198,\n 220,\n 220,\n 220,\n 220,\n 220,\n 220,\n 220,\n 220,\n 220,\n 220,\n 220,\n 611,\n 2604,\n 7753,\n 25,\n 198,\n 220,\n 220,\n 220,\n 220,\n 220,\n 220,\n 220,\n 220,\n 220,\n 220,\n 220,\n 220,\n 220,\n 220,\n 220,\n 3904,\n 13,\n 30328,\n 10786,\n 59,\n 77,\n 11187,\n 3194,\n 284,\n 23884,\n 4458,\n 18982,\n 7,\n 6404,\n 7753,\n 4008,\n 628,\n 220,\n 220,\n 220,\n 220,\n 220,\n 220,\n 220,\n 611,\n 351,\n 62,\n 41989,\n 25,\n 198,\n 220,\n 220,\n 220,\n 220,\n 220,\n 220,\n 220,\n 220,\n 220,\n 220,\n 220,\n 3904,\n 13,\n 30328,\n 10786,\n 59,\n 77,\n 28768,\n 20922,\n 5254,\n 625,\n 25,\n 23884,\n 4458,\n 18982,\n 7,\n 448,\n 6978,\n 4008,\n 198,\n 220,\n 220,\n 220,\n 220,\n 220,\n 220,\n 220,\n 220,\n 220,\n 220,\n 220,\n 611,\n 407,\n 2604,\n 7753,\n 25,\n 2604,\n 7753,\n 796,\n 705,\n 41989,\n 13,\n 6404,\n 6,\n 198,\n 220,\n 220,\n 220,\n 220,\n 220,\n 220,\n 220,\n 220,\n 220,\n 220,\n 220,\n 4808,\n 11295,\n 2070,\n 14402,\n 7,\n 448,\n 6978,\n 11,\n 2604,\n 7753,\n 1267,\n 198,\n 220,\n 220,\n 220,\n 220,\n 220,\n 220,\n 220,\n 220,\n 220,\n 220,\n 220,\n 3904,\n 13,\n 30328,\n 10786,\n 59,\n 77,\n 11187,\n 3194,\n 284,\n 23884,\n 4458,\n 18982,\n 7,\n 6404,\n 7753,\n 4008,\n 198,\n 220,\n 220,\n 220,\n 220,\n 220,\n 220,\n 220,\n 220,\n 220,\n 220,\n 220,\n 220,\n 198,\n 220,\n 220,\n 220,\n 220,\n 220,\n 220,\n 220,\n 611,\n 19974,\n 25,\n 198,\n 220,\n 220,\n 220,\n 220,\n 220,\n 220,\n 220,\n 220,\n 220,\n 220,\n 220,\n 3601,\n 10786,\n 59,\n 77,\n 57,\n 4501,\n 656,\n 25,\n 23884,\n 14,\n 77,\n 1639,\n 743,\n 635,\n 765,\n 284,\n 12233,\n 262,\n 1762,\n 8619,\n 37913,\n 92,\n 737,\n 4458,\n 18982,\n 7,\n 260,\n 1930,\n 37765,\n 11,\n 503,\n 6978,\n 8,\n 1267,\n 198,\n 220,\n 220,\n 220,\n 220,\n 220,\n 220,\n 220,\n 220,\n 220,\n 220,\n 220,\n 48992,\n 7,\n 448,\n 6978,\n 11,\n 260,\n 1930,\n 37765,\n 8,\n 198,\n 220,\n 220,\n 220,\n 220,\n 220,\n 220,\n 220,\n 2073,\n 25,\n 198,\n 220,\n 220,\n 220,\n 220,\n 220,\n 220,\n 220,\n 220,\n 220,\n 220,\n 220,\n 3601,\n 10786,\n 59,\n 77,\n 59,\n 77,\n 2514,\n 19974,\n 262,\n 15680,\n 8619,\n 11,\n 1057,\n 1223,\n 588,\n 25,\n 23884,\n 4458,\n 18982,\n 10786,\n 17209,\n 35273,\n 13344,\n 1391,\n 78,\n 92,\n 1391,\n 89,\n 32239,\n 77,\n 59,\n 77,\n 2514,\n 1057,\n 257,\n 20922,\n 12649,\n 357,\n 3185,\n 51,\n 11053,\n 25,\n 1057,\n 3152,\n 9139,\n 5965,\n 11,\n 1598,\n 26410,\n 8,\n 981,\n 1976,\n 4501,\n 25,\n 256,\n 76,\n 35273,\n 13344,\n 45144,\n 78,\n 36786,\n 1391,\n 89,\n 92,\n 1377,\n 7753,\n 12,\n 41341,\n 39852,\n 2849,\n 59,\n 77,\n 4458,\n 18982,\n 7,\n 78,\n 28,\n 448,\n 6978,\n 11,\n 89,\n 28,\n 260,\n 1930,\n 37765,\n 13,\n 3672,\n 22305,\n 628,\n 220,\n 220,\n 220,\n 220,\n 220,\n 220,\n 220,\n 8619,\n 28,\n 7061,\n 198,\n 220,\n 220,\n 220,\n 220,\n 220,\n 220,\n 220,\n 1194,\n 796,\n 3904,\n 13,\n 16963,\n 457,\n 10786,\n 59,\n 10002,\n 1194,\n 8619,\n 422,\n 428,\n 8478,\n 30,\n 357,\n 2514,\n 11238,\n 25,\n 532,\n 8,\n 11537,\n 628,\n 220,\n 220,\n 220,\n 220,\n 1303,\n 51,\n 3727,\n 46,\n 198,\n 220,\n 220,\n 220,\n 220,\n 1303,\n 4798,\n 10786,\n 59,\n 77,\n 59,\n 77,\n 2514,\n 1057,\n 428,\n 3141,\n 757,\n 25,\n 23884,\n 4458,\n 18982,\n 28955,\n 198\n]"},"ratio_char_token":{"kind":"number","value":2.4048829188600473,"string":"2.404883"},"token_count":{"kind":"number","value":11018,"string":"11,018"}}},{"rowIdx":1230,"cells":{"content":{"kind":"string","value":"#!/usr/bin/env\n\n\"\"\"\nclass definitions for standard 1 variable plots\nclass definitions for standard 2 variable plots\nclass definitions for standard 3 variable plots\n\n History:\n --------\n 2019-05-21: error in calculation used corrected udata to correct vdata \n\n\"\"\"\n\n# System Stack\nimport datetime\n\n# science stack\nimport numpy as np\n\n# Visual Stack\n\nimport matplotlib as mpl\n\nmpl.use(\"Agg\")\nimport matplotlib.pyplot as plt\nfrom matplotlib.dates import (\n YearLocator,\n WeekdayLocator,\n MonthLocator,\n DayLocator,\n HourLocator,\n DateFormatter,\n)\nimport matplotlib.ticker as ticker\n\n\n\n\n\n\n\n\n\n\nclass TimeseriesPorpertyPropertyPlot(object):\n \"\"\" class to plot property vs property plots with density iso-contours\"\"\"\n\n mpl.rcParams[\"svg.fonttype\"] = \"none\"\n mpl.rcParams[\"ps.fonttype\"] = 42\n mpl.rcParams[\"pdf.fonttype\"] = 42\n\n def __init__(\n self, fontsize=10, labelsize=10, plotstyle=\"k-.\", stylesheet=\"seaborn-whitegrid\"\n ):\n \"\"\"Initialize the timeseries with items that do not change.\n\n This sets up the axes and station locations. The `fontsize` and `spacing`\n are also specified here to ensure that they are consistent between individual\n station elements.\n\n Parameters\n ----------\n fontsize : int\n The fontsize to use for drawing text\n labelsize : int\n The fontsize to use for labels\n stylesheet : str\n Choose a mpl stylesheet [u'seaborn-darkgrid', \n u'seaborn-notebook', u'classic', u'seaborn-ticks', \n u'grayscale', u'bmh', u'seaborn-talk', u'dark_background', \n u'ggplot', u'fivethirtyeight', u'seaborn-colorblind', \n u'seaborn-deep', u'seaborn-whitegrid', u'seaborn-bright', \n u'seaborn-poster', u'seaborn-muted', u'seaborn-paper', \n u'seaborn-white', u'seaborn-pastel', u'seaborn-dark', \n u'seaborn-dark-palette']\n \"\"\"\n\n self.fontsize = fontsize\n self.labelsize = labelsize\n self.plotstyle = plotstyle\n plt.style.use(stylesheet)\n\n @staticmethod\n def add_title(mooringid=\"\", lat=-99.9, lon=-99.9, depth=9999, instrument=\"\"):\n \"\"\"Pass parameters to annotate the title of the plot\n\n This sets the standard plot title using common meta information from PMEL/EPIC style netcdf files\n\n Parameters\n ----------\n mooringid : str\n Mooring Identifier\n lat : float\n The latitude of the mooring\n lon : float\n The longitude of the mooring\n depth : int\n Nominal depth of the instrument\n instrument : str\n Name/identifier of the instrument plotted\n \"\"\"\n\n ptitle = (\n \"Plotted on: {time:%Y/%m/%d %H:%M} \\n from {mooringid} Lat: {latitude:3.3f} Lon: {longitude:3.3f}\"\n \" Depth: {depth}\\n : {instrument}\"\n ).format(\n time=datetime.datetime.now(),\n mooringid=mooringid,\n latitude=lat,\n longitude=lon,\n depth=depth,\n instrument=instrument,\n )\n\n return ptitle\n\n @staticmethod\n"},"input_ids":{"kind":"list like","value":[2,48443,14629,14,8800,14,24330,198,198,37811,198,4871,17336,329,3210,352,7885,21528,198,4871,17336,329,3210,362,7885,21528,198,4871,17336,329,3210,513,7885,21528,628,7443,25,198,24200,198,13130,12,2713,12,2481,25,4049,287,17952,973,19267,334,7890,284,3376,410,7890,220,198,198,37811,198,198,2,4482,23881,198,11748,4818,8079,198,198,2,3783,8931,198,11748,299,32152,355,45941,198,198,2,15612,23881,198,198,11748,2603,29487,8019,355,285,489,198,198,76,489,13,1904,7203,46384,4943,198,11748,2603,29487,8019,13,9078,29487,355,458,83,198,6738,2603,29487,8019,13,19581,1330,357,198,220,220,220,6280,33711,1352,11,198,220,220,220,6119,820,33711,1352,11,198,220,220,220,16061,33711,1352,11,198,220,220,220,3596,33711,1352,11,198,220,220,220,19123,33711,1352,11,198,220,220,220,7536,8479,1436,11,198,8,198,11748,2603,29487,8019,13,83,15799,355,4378,263,628,628,628,628,628,198,4871,3782,10640,47,273,9287,21746,43328,7,15252,2599,198,220,220,220,37227,1398,284,7110,3119,3691,3119,21528,351,12109,47279,12,3642,4662,37811,628,220,220,220,285,489,13,6015,10044,4105,14692,21370,70,13,10331,4906,8973,796,366,23108,1,198,220,220,220,285,489,13,6015,10044,4105,14692,862,13,10331,4906,8973,796,5433,198,220,220,220,285,489,13,6015,10044,4105,14692,12315,13,10331,4906,8973,796,5433,628,220,220,220,825,11593,15003,834,7,198,220,220,220,220,220,220,220,2116,11,10369,7857,28,940,11,14722,1096,28,940,11,7110,7635,2625,74,12,33283,12186,25473,2625,325,397,1211,12,11186,25928,1,198,220,220,220,15179,198,220,220,220,220,220,220,220,37227,24243,1096,262,1661,10640,351,3709,326,466,407,1487,13,628,220,220,220,220,220,220,220,770,5621,510,262,34197,290,4429,7064,13,383,4600,10331,7857,63,290,4600,2777,4092,63,198,220,220,220,220,220,220,220,389,635,7368,994,284,4155,326,484,389,6414,1022,1981,198,220,220,220,220,220,220,220,4429,4847,13,628,220,220,220,220,220,220,220,40117,198,220,220,220,220,220,220,220,24200,438,198,220,220,220,220,220,220,220,10369,7857,1058,493,198,220,220,220,220,220,220,220,220,220,220,220,383,10369,7857,284,779,329,8263,2420,198,220,220,220,220,220,220,220,14722,1096,1058,493,198,220,220,220,220,220,220,220,220,220,383,10369,7857,284,779,329,14722,198,220,220,220,220,220,220,220,12186,25473,1058,965,198,220,220,220,220,220,220,220,220,220,17489,257,285,489,12186,25473,685,84,338,68,397,1211,12,21953,25928,3256,220,198,220,220,220,220,220,220,220,220,220,334,338,68,397,1211,12,11295,2070,3256,334,6,49421,3256,334,338,68,397,1211,12,83,3378,3256,220,198,220,220,220,220,220,220,220,220,220,334,6,2164,592,38765,3256,334,6,20475,71,3256,334,338,68,397,1211,12,16620,3256,334,1549,668,62,25249,3256,220,198,220,220,220,220,220,220,220,220,220,334,6,1130,29487,3256,334,6,13261,400,5893,26022,3256,334,338,68,397,1211,12,8043,27461,3256,220,198,220,220,220,220,220,220,220,220,220,334,338,68,397,1211,12,22089,3256,334,338,68,397,1211,12,11186,25928,3256,334,338,68,397,1211,12,29199,3256,220,198,220,220,220,220,220,220,220,220,220,334,338,68,397,1211,12,79,6197,3256,334,338,68,397,1211,12,76,7241,3256,334,338,68,397,1211,12,20189,3256,220,198,220,220,220,220,220,220,220,220,220,334,338,68,397,1211,12,11186,3256,334,338,68,397,1211,12,30119,417,3256,334,338,68,397,1211,12,21953,3256,220,198,220,220,220,220,220,220,220,220,220,334,338,68,397,1211,12,21953,12,18596,5857,20520,198,220,220,220,220,220,220,220,37227,628,220,220,220,220,220,220,220,2116,13,10331,7857,796,10369,7857,198,220,220,220,220,220,220,220,2116,13,23912,1424,1096,796,14722,1096,198,220,220,220,220,220,220,220,2116,13,29487,7635,796,7110,7635,198,220,220,220,220,220,220,220,458,83,13,7635,13,1904,7,47720,25473,8,628,220,220,220,2488,12708,24396,198,220,220,220,825,751,62,7839,7,76,2675,278,312,2625,1600,3042,10779,2079,13,24,11,300,261,10779,2079,13,24,11,6795,28,24214,11,8875,33151,2599,198,220,220,220,220,220,220,220,37227,14478,10007,284,24708,378,262,3670,286,262,7110,628,220,220,220,220,220,770,5621,262,3210,7110,3670,1262,2219,13634,1321,422,3122,3698,14,8905,2149,3918,2010,66,7568,3696,628,220,220,220,220,220,40117,198,220,220,220,220,220,24200,438,198,220,220,220,220,220,285,2675,278,312,1058,965,198,220,220,220,220,220,220,220,31451,278,11440,7483,198,220,220,220,220,220,3042,1058,12178,198,220,220,220,220,220,220,220,383,32477,286,262,285,2675,278,198,220,220,220,220,220,300,261,1058,12178,198,220,220,220,220,220,220,220,383,890,3984,286,262,285,2675,278,198,220,220,220,220,220,6795,1058,493,198,220,220,220,220,220,220,220,21198,1292,6795,286,262,8875,198,220,220,220,220,220,8875,1058,965,198,220,220,220,220,220,220,220,6530,14,738,7483,286,262,8875,37515,198,220,220,220,220,220,37227,628,220,220,220,220,220,220,220,279,7839,796,357,198,220,220,220,220,220,220,220,220,220,220,220,366,3646,8426,319,25,1391,2435,25,4,56,14,4,76,14,4,67,4064,39,25,4,44,92,3467,77,422,1391,76,2675,278,312,92,5476,25,1391,15460,3984,25,18,13,18,69,92,220,39295,25,1391,6511,3984,25,18,13,18,69,36786,198,220,220,220,220,220,220,220,220,220,220,220,366,36350,25,1391,18053,32239,77,1058,1391,259,43872,36786,198,220,220,220,220,220,220,220,6739,18982,7,198,220,220,220,220,220,220,220,220,220,220,220,640,28,19608,8079,13,19608,8079,13,2197,22784,198,220,220,220,220,220,220,220,220,220,220,220,285,2675,278,312,28,76,2675,278,312,11,198,220,220,220,220,220,220,220,220,220,220,220,32477,28,15460,11,198,220,220,220,220,220,220,220,220,220,220,220,890,3984,28,14995,11,198,220,220,220,220,220,220,220,220,220,220,220,6795,28,18053,11,198,220,220,220,220,220,220,220,220,220,220,220,8875,28,259,43872,11,198,220,220,220,220,220,220,220,1267,628,220,220,220,220,220,220,220,1441,279,7839,628,220,220,220,2488,12708,24396,198],"string":"[\n 2,\n 48443,\n 14629,\n 14,\n 8800,\n 14,\n 24330,\n 198,\n 198,\n 37811,\n 198,\n 4871,\n 17336,\n 329,\n 3210,\n 352,\n 7885,\n 21528,\n 198,\n 4871,\n 17336,\n 329,\n 3210,\n 362,\n 7885,\n 21528,\n 198,\n 4871,\n 17336,\n 329,\n 3210,\n 513,\n 7885,\n 21528,\n 628,\n 7443,\n 25,\n 198,\n 24200,\n 198,\n 13130,\n 12,\n 2713,\n 12,\n 2481,\n 25,\n 4049,\n 287,\n 17952,\n 973,\n 19267,\n 334,\n 7890,\n 284,\n 3376,\n 410,\n 7890,\n 220,\n 198,\n 198,\n 37811,\n 198,\n 198,\n 2,\n 4482,\n 23881,\n 198,\n 11748,\n 4818,\n 8079,\n 198,\n 198,\n 2,\n 3783,\n 8931,\n 198,\n 11748,\n 299,\n 32152,\n 355,\n 45941,\n 198,\n 198,\n 2,\n 15612,\n 23881,\n 198,\n 198,\n 11748,\n 2603,\n 29487,\n 8019,\n 355,\n 285,\n 489,\n 198,\n 198,\n 76,\n 489,\n 13,\n 1904,\n 7203,\n 46384,\n 4943,\n 198,\n 11748,\n 2603,\n 29487,\n 8019,\n 13,\n 9078,\n 29487,\n 355,\n 458,\n 83,\n 198,\n 6738,\n 2603,\n 29487,\n 8019,\n 13,\n 19581,\n 1330,\n 357,\n 198,\n 220,\n 220,\n 220,\n 6280,\n 33711,\n 1352,\n 11,\n 198,\n 220,\n 220,\n 220,\n 6119,\n 820,\n 33711,\n 1352,\n 11,\n 198,\n 220,\n 220,\n 220,\n 16061,\n 33711,\n 1352,\n 11,\n 198,\n 220,\n 220,\n 220,\n 3596,\n 33711,\n 1352,\n 11,\n 198,\n 220,\n 220,\n 220,\n 19123,\n 33711,\n 1352,\n 11,\n 198,\n 220,\n 220,\n 220,\n 7536,\n 8479,\n 1436,\n 11,\n 198,\n 8,\n 198,\n 11748,\n 2603,\n 29487,\n 8019,\n 13,\n 83,\n 15799,\n 355,\n 4378,\n 263,\n 628,\n 628,\n 628,\n 628,\n 628,\n 198,\n 4871,\n 3782,\n 10640,\n 47,\n 273,\n 9287,\n 21746,\n 43328,\n 7,\n 15252,\n 2599,\n 198,\n 220,\n 220,\n 220,\n 37227,\n 1398,\n 284,\n 7110,\n 3119,\n 3691,\n 3119,\n 21528,\n 351,\n 12109,\n 47279,\n 12,\n 3642,\n 4662,\n 37811,\n 628,\n 220,\n 220,\n 220,\n 285,\n 489,\n 13,\n 6015,\n 10044,\n 4105,\n 14692,\n 21370,\n 70,\n 13,\n 10331,\n 4906,\n 8973,\n 796,\n 366,\n 23108,\n 1,\n 198,\n 220,\n 220,\n 220,\n 285,\n 489,\n 13,\n 6015,\n 10044,\n 4105,\n 14692,\n 862,\n 13,\n 10331,\n 4906,\n 8973,\n 796,\n 5433,\n 198,\n 220,\n 220,\n 220,\n 285,\n 489,\n 13,\n 6015,\n 10044,\n 4105,\n 14692,\n 12315,\n 13,\n 10331,\n 4906,\n 8973,\n 796,\n 5433,\n 628,\n 220,\n 220,\n 220,\n 825,\n 11593,\n 15003,\n 834,\n 7,\n 198,\n 220,\n 220,\n 220,\n 220,\n 220,\n 220,\n 220,\n 2116,\n 11,\n 10369,\n 7857,\n 28,\n 940,\n 11,\n 14722,\n 1096,\n 28,\n 940,\n 11,\n 7110,\n 7635,\n 2625,\n 74,\n 12,\n 33283,\n 12186,\n 25473,\n 2625,\n 325,\n 397,\n 1211,\n 12,\n 11186,\n 25928,\n 1,\n 198,\n 220,\n 220,\n 220,\n 15179,\n 198,\n 220,\n 220,\n 220,\n 220,\n 220,\n 220,\n 220,\n 37227,\n 24243,\n 1096,\n 262,\n 1661,\n 10640,\n 351,\n 3709,\n 326,\n 466,\n 407,\n 1487,\n 13,\n 628,\n 220,\n 220,\n 220,\n 220,\n 220,\n 220,\n 220,\n 770,\n 5621,\n 510,\n 262,\n 34197,\n 290,\n 4429,\n 7064,\n 13,\n 383,\n 4600,\n 10331,\n 7857,\n 63,\n 290,\n 4600,\n 2777,\n 4092,\n 63,\n 198,\n 220,\n 220,\n 220,\n 220,\n 220,\n 220,\n 220,\n 389,\n 635,\n 7368,\n 994,\n 284,\n 4155,\n 326,\n 484,\n 389,\n 6414,\n 1022,\n 1981,\n 198,\n 220,\n 220,\n 220,\n 220,\n 220,\n 220,\n 220,\n 4429,\n 4847,\n 13,\n 628,\n 220,\n 220,\n 220,\n 220,\n 220,\n 220,\n 220,\n 40117,\n 198,\n 220,\n 220,\n 220,\n 220,\n 220,\n 220,\n 220,\n 24200,\n 438,\n 198,\n 220,\n 220,\n 220,\n 220,\n 220,\n 220,\n 220,\n 10369,\n 7857,\n 1058,\n 493,\n 198,\n 220,\n 220,\n 220,\n 220,\n 220,\n 220,\n 220,\n 220,\n 220,\n 220,\n 220,\n 383,\n 10369,\n 7857,\n 284,\n 779,\n 329,\n 8263,\n 2420,\n 198,\n 220,\n 220,\n 220,\n 220,\n 220,\n 220,\n 220,\n 14722,\n 1096,\n 1058,\n 493,\n 198,\n 220,\n 220,\n 220,\n 220,\n 220,\n 220,\n 220,\n 220,\n 220,\n 383,\n 10369,\n 7857,\n 284,\n 779,\n 329,\n 14722,\n 198,\n 220,\n 220,\n 220,\n 220,\n 220,\n 220,\n 220,\n 12186,\n 25473,\n 1058,\n 965,\n 198,\n 220,\n 220,\n 220,\n 220,\n 220,\n 220,\n 220,\n 220,\n 220,\n 17489,\n 257,\n 285,\n 489,\n 12186,\n 25473,\n 685,\n 84,\n 338,\n 68,\n 397,\n 1211,\n 12,\n 21953,\n 25928,\n 3256,\n 220,\n 198,\n 220,\n 220,\n 220,\n 220,\n 220,\n 220,\n 220,\n 220,\n 220,\n 334,\n 338,\n 68,\n 397,\n 1211,\n 12,\n 11295,\n 2070,\n 3256,\n 334,\n 6,\n 49421,\n 3256,\n 334,\n 338,\n 68,\n 397,\n 1211,\n 12,\n 83,\n 3378,\n 3256,\n 220,\n 198,\n 220,\n 220,\n 220,\n 220,\n 220,\n 220,\n 220,\n 220,\n 220,\n 334,\n 6,\n 2164,\n 592,\n 38765,\n 3256,\n 334,\n 6,\n 20475,\n 71,\n 3256,\n 334,\n 338,\n 68,\n 397,\n 1211,\n 12,\n 16620,\n 3256,\n 334,\n 1549,\n 668,\n 62,\n 25249,\n 3256,\n 220,\n 198,\n 220,\n 220,\n 220,\n 220,\n 220,\n 220,\n 220,\n 220,\n 220,\n 334,\n 6,\n 1130,\n 29487,\n 3256,\n 334,\n 6,\n 13261,\n 400,\n 5893,\n 26022,\n 3256,\n 334,\n 338,\n 68,\n 397,\n 1211,\n 12,\n 8043,\n 27461,\n 3256,\n 220,\n 198,\n 220,\n 220,\n 220,\n 220,\n 220,\n 220,\n 220,\n 220,\n 220,\n 334,\n 338,\n 68,\n 397,\n 1211,\n 12,\n 22089,\n 3256,\n 334,\n 338,\n 68,\n 397,\n 1211,\n 12,\n 11186,\n 25928,\n 3256,\n 334,\n 338,\n 68,\n 397,\n 1211,\n 12,\n 29199,\n 3256,\n 220,\n 198,\n 220,\n 220,\n 220,\n 220,\n 220,\n 220,\n 220,\n 220,\n 220,\n 334,\n 338,\n 68,\n 397,\n 1211,\n 12,\n 79,\n 6197,\n 3256,\n 334,\n 338,\n 68,\n 397,\n 1211,\n 12,\n 76,\n 7241,\n 3256,\n 334,\n 338,\n 68,\n 397,\n 1211,\n 12,\n 20189,\n 3256,\n 220,\n 198,\n 220,\n 220,\n 220,\n 220,\n 220,\n 220,\n 220,\n 220,\n 220,\n 334,\n 338,\n 68,\n 397,\n 1211,\n 12,\n 11186,\n 3256,\n 334,\n 338,\n 68,\n 397,\n 1211,\n 12,\n 30119,\n 417,\n 3256,\n 334,\n 338,\n 68,\n 397,\n 1211,\n 12,\n 21953,\n 3256,\n 220,\n 198,\n 220,\n 220,\n 220,\n 220,\n 220,\n 220,\n 220,\n 220,\n 220,\n 334,\n 338,\n 68,\n 397,\n 1211,\n 12,\n 21953,\n 12,\n 18596,\n 5857,\n 20520,\n 198,\n 220,\n 220,\n 220,\n 220,\n 220,\n 220,\n 220,\n 37227,\n 628,\n 220,\n 220,\n 220,\n 220,\n 220,\n 220,\n 220,\n 2116,\n 13,\n 10331,\n 7857,\n 796,\n 10369,\n 7857,\n 198,\n 220,\n 220,\n 220,\n 220,\n 220,\n 220,\n 220,\n 2116,\n 13,\n 23912,\n 1424,\n 1096,\n 796,\n 14722,\n 1096,\n 198,\n 220,\n 220,\n 220,\n 220,\n 220,\n 220,\n 220,\n 2116,\n 13,\n 29487,\n 7635,\n 796,\n 7110,\n 7635,\n 198,\n 220,\n 220,\n 220,\n 220,\n 220,\n 220,\n 220,\n 458,\n 83,\n 13,\n 7635,\n 13,\n 1904,\n 7,\n 47720,\n 25473,\n 8,\n 628,\n 220,\n 220,\n 220,\n 2488,\n 12708,\n 24396,\n 198,\n 220,\n 220,\n 220,\n 825,\n 751,\n 62,\n 7839,\n 7,\n 76,\n 2675,\n 278,\n 312,\n 2625,\n 1600,\n 3042,\n 10779,\n 2079,\n 13,\n 24,\n 11,\n 300,\n 261,\n 10779,\n 2079,\n 13,\n 24,\n 11,\n 6795,\n 28,\n 24214,\n 11,\n 8875,\n 33151,\n 2599,\n 198,\n 220,\n 220,\n 220,\n 220,\n 220,\n 220,\n 220,\n 37227,\n 14478,\n 10007,\n 284,\n 24708,\n 378,\n 262,\n 3670,\n 286,\n 262,\n 7110,\n 628,\n 220,\n 220,\n 220,\n 220,\n 220,\n 770,\n 5621,\n 262,\n 3210,\n 7110,\n 3670,\n 1262,\n 2219,\n 13634,\n 1321,\n 422,\n 3122,\n 3698,\n 14,\n 8905,\n 2149,\n 3918,\n 2010,\n 66,\n 7568,\n 3696,\n 628,\n 220,\n 220,\n 220,\n 220,\n 220,\n 40117,\n 198,\n 220,\n 220,\n 220,\n 220,\n 220,\n 24200,\n 438,\n 198,\n 220,\n 220,\n 220,\n 220,\n 220,\n 285,\n 2675,\n 278,\n 312,\n 1058,\n 965,\n 198,\n 220,\n 220,\n 220,\n 220,\n 220,\n 220,\n 220,\n 31451,\n 278,\n 11440,\n 7483,\n 198,\n 220,\n 220,\n 220,\n 220,\n 220,\n 3042,\n 1058,\n 12178,\n 198,\n 220,\n 220,\n 220,\n 220,\n 220,\n 220,\n 220,\n 383,\n 32477,\n 286,\n 262,\n 285,\n 2675,\n 278,\n 198,\n 220,\n 220,\n 220,\n 220,\n 220,\n 300,\n 261,\n 1058,\n 12178,\n 198,\n 220,\n 220,\n 220,\n 220,\n 220,\n 220,\n 220,\n 383,\n 890,\n 3984,\n 286,\n 262,\n 285,\n 2675,\n 278,\n 198,\n 220,\n 220,\n 220,\n 220,\n 220,\n 6795,\n 1058,\n 493,\n 198,\n 220,\n 220,\n 220,\n 220,\n 220,\n 220,\n 220,\n 21198,\n 1292,\n 6795,\n 286,\n 262,\n 8875,\n 198,\n 220,\n 220,\n 220,\n 220,\n 220,\n 8875,\n 1058,\n 965,\n 198,\n 220,\n 220,\n 220,\n 220,\n 220,\n 220,\n 220,\n 6530,\n 14,\n 738,\n 7483,\n 286,\n 262,\n 8875,\n 37515,\n 198,\n 220,\n 220,\n 220,\n 220,\n 220,\n 37227,\n 628,\n 220,\n 220,\n 220,\n 220,\n 220,\n 220,\n 220,\n 279,\n 7839,\n 796,\n 357,\n 198,\n 220,\n 220,\n 220,\n 220,\n 220,\n 220,\n 220,\n 220,\n 220,\n 220,\n 220,\n 366,\n 3646,\n 8426,\n 319,\n 25,\n 1391,\n 2435,\n 25,\n 4,\n 56,\n 14,\n 4,\n 76,\n 14,\n 4,\n 67,\n 4064,\n 39,\n 25,\n 4,\n 44,\n 92,\n 3467,\n 77,\n 422,\n 1391,\n 76,\n 2675,\n 278,\n 312,\n 92,\n 5476,\n 25,\n 1391,\n 15460,\n 3984,\n 25,\n 18,\n 13,\n 18,\n 69,\n 92,\n 220,\n 39295,\n 25,\n 1391,\n 6511,\n 3984,\n 25,\n 18,\n 13,\n 18,\n 69,\n 36786,\n 198,\n 220,\n 220,\n 220,\n 220,\n 220,\n 220,\n 220,\n 220,\n 220,\n 220,\n 220,\n 366,\n 36350,\n 25,\n 1391,\n 18053,\n 32239,\n 77,\n 1058,\n 1391,\n 259,\n 43872,\n 36786,\n 198,\n 220,\n 220,\n 220,\n 220,\n 220,\n 220,\n 220,\n 6739,\n 18982,\n 7,\n 198,\n 220,\n 220,\n 220,\n 220,\n 220,\n 220,\n 220,\n 220,\n 220,\n 220,\n 220,\n 640,\n 28,\n 19608,\n 8079,\n 13,\n 19608,\n 8079,\n 13,\n 2197,\n 22784,\n 198,\n 220,\n 220,\n 220,\n 220,\n 220,\n 220,\n 220,\n 220,\n 220,\n 220,\n 220,\n 285,\n 2675,\n 278,\n 312,\n 28,\n 76,\n 2675,\n 278,\n 312,\n 11,\n 198,\n 220,\n 220,\n 220,\n 220,\n 220,\n 220,\n 220,\n 220,\n 220,\n 220,\n 220,\n 32477,\n 28,\n 15460,\n 11,\n 198,\n 220,\n 220,\n 220,\n 220,\n 220,\n 220,\n 220,\n 220,\n 220,\n 220,\n 220,\n 890,\n 3984,\n 28,\n 14995,\n 11,\n 198,\n 220,\n 220,\n 220,\n 220,\n 220,\n 220,\n 220,\n 220,\n 220,\n 220,\n 220,\n 6795,\n 28,\n 18053,\n 11,\n 198,\n 220,\n 220,\n 220,\n 220,\n 220,\n 220,\n 220,\n 220,\n 220,\n 220,\n 220,\n 8875,\n 28,\n 259,\n 43872,\n 11,\n 198,\n 220,\n 220,\n 220,\n 220,\n 220,\n 220,\n 220,\n 1267,\n 628,\n 220,\n 220,\n 220,\n 220,\n 220,\n 220,\n 220,\n 1441,\n 279,\n 7839,\n 628,\n 220,\n 220,\n 220,\n 2488,\n 12708,\n 24396,\n 198\n]"},"ratio_char_token":{"kind":"number","value":2.3622526636225265,"string":"2.362253"},"token_count":{"kind":"number","value":1314,"string":"1,314"}}},{"rowIdx":1231,"cells":{"content":{"kind":"string","value":"\"\"\"\nThe tests for omit interaction feature\n\"\"\"\n\nimport os\nimport sys\n\nfrom collections import namedtuple\n\nfrom pyplif_hippos import ParseConfig, hippos, similarity\n\n\ndef test_configuration_single_omit_interaction(tmpdir):\n \"\"\"Test configuration for omitting specific interaction\"\"\"\n\n # Arrange\n\n config_file = tmpdir.mkdir(\"sub\").join(\"config.txt\")\n config_file.write(\n \"\"\"\ndocking_method plants # plants or vina\ndocking_conf plants-003.conf\n\nsimilarity_coef tanimoto mcconnaughey\n\nfull_ref 00000100000000000000000000000000000100000000000001000000000000010000001000000000000000000001000000000000000000000000000000101000000000000000000101000000000010000 00010101000000000000000000000000000100000000000001010000000000010000001000000000000010000000000000000000000001011000001000001000000000000000000101000000000000000 00010101000000100000000000000000000100000000000001010100100000010000001000000000000010000001000000000000010000000000100000101010000000000000000001000000000000000\n\nresidue_name ARG116 GLU117 LEU132 LYS148 ASP149 ARG150 ARG154 TRP177 SER178 ILE221 ARG223 THR224 GLU226 ALA245 HIS273 GLU275 GLU276 ARG292 ASP294 GLY347 ARG374 TRP408 TYR409\nresidue_number 40 41 56 72 73 74 78 101 102 145 147 148 150 169 197 199 200 216 218 271 298 332 333\n\nomit_interaction hydrophobic ARG223\n\nfull_outfile plants_full_ifp.csv\nsim_outfile plants_similarity.csv\nlogfile plants.log\n\"\"\"\n )\n\n arg = os.path.join(config_file.dirname, config_file.basename)\n\n if len(sys.argv) > 1:\n sys.argv[1] = arg\n else:\n sys.argv.append(arg)\n\n # Act\n\n hippos_config = ParseConfig()\n hippos_config.parse_config()\n omit_interaction = hippos_config.omit_interaction[0]\n\n # Assert\n\n assert omit_interaction.interaction_type == \"hydrophobic\"\n assert omit_interaction.res_name == [\"ARG223\"]\n\n\ndef test_configuration_omit_multiple_residue_interaction(tmpdir):\n \"\"\"Test configuration for omitting multiple residue interaction\"\"\"\n\n # Arrange\n\n config_file = tmpdir.mkdir(\"sub\").join(\"config.txt\")\n config_file.write(\n \"\"\"\ndocking_method plants # plants or vina\ndocking_conf plants-003.conf\n\nsimilarity_coef tanimoto mcconnaughey\n\nfull_ref 00000100000000000000000000000000000100000000000001000000000000010000001000000000000000000001000000000000000000000000000000101000000000000000000101000000000010000 00010101000000000000000000000000000100000000000001010000000000010000001000000000000010000000000000000000000001011000001000001000000000000000000101000000000000000 00010101000000100000000000000000000100000000000001010100100000010000001000000000000010000001000000000000010000000000100000101010000000000000000001000000000000000\n\nresidue_name ARG116 GLU117 LEU132 LYS148 ASP149 ARG150 ARG154 TRP177 SER178 ILE221 ARG223 THR224 GLU226 ALA245 HIS273 GLU275 GLU276 ARG292 ASP294 GLY347 ARG374 TRP408 TYR409\nresidue_number 40 41 56 72 73 74 78 101 102 145 147 148 150 169 197 199 200 216 218 271 298 332 333\n\nomit_interaction hydrophobic ARG150 TRP177 ARG223\n\nfull_outfile plants_full_ifp.csv\nsim_outfile plants_similarity.csv\nlogfile plants.log\n\"\"\"\n )\n\n arg = os.path.join(config_file.dirname, config_file.basename)\n\n if len(sys.argv) > 1:\n sys.argv[1] = arg\n else:\n sys.argv.append(arg)\n\n # Act\n\n hippos_config = ParseConfig()\n hippos_config.parse_config()\n omit_interaction = hippos_config.omit_interaction[0]\n\n # Assert\n\n assert omit_interaction.interaction_type == \"hydrophobic\"\n assert omit_interaction.res_name == [\"ARG150\", \"TRP177\", \"ARG223\"]\n\n\ndef test_configuration_omit_multiple_interaction_type(tmpdir):\n \"\"\"Test configuration for omitting multiple interaction type\"\"\"\n\n # Arrange\n\n config_file = tmpdir.mkdir(\"sub\").join(\"config.txt\")\n config_file.write(\n \"\"\"\ndocking_method plants # plants or vina\ndocking_conf plants-003.conf\n\nsimilarity_coef tanimoto mcconnaughey\n\nfull_ref 00000100000000000000000000000000000100000000000001000000000000010000001000000000000000000001000000000000000000000000000000101000000000000000000101000000000010000 00010101000000000000000000000000000100000000000001010000000000010000001000000000000010000000000000000000000001011000001000001000000000000000000101000000000000000 00010101000000100000000000000000000100000000000001010100100000010000001000000000000010000001000000000000010000000000100000101010000000000000000001000000000000000\n\nresidue_name ARG116 GLU117 LEU132 LYS148 ASP149 ARG150 ARG154 TRP177 SER178 ILE221 ARG223 THR224 GLU226 ALA245 HIS273 GLU275 GLU276 ARG292 ASP294 GLY347 ARG374 TRP408 TYR409\nresidue_number 40 41 56 72 73 74 78 101 102 145 147 148 150 169 197 199 200 216 218 271 298 332 333\n\nomit_interaction hydrophobic ARG223\nomit_interaction h_bond ARG292\n\nfull_outfile plants_full_ifp.csv\nsim_outfile plants_similarity.csv\nlogfile plants.log\n\"\"\"\n )\n\n arg = os.path.join(config_file.dirname, config_file.basename)\n\n if len(sys.argv) > 1:\n sys.argv[1] = arg\n else:\n sys.argv.append(arg)\n\n # Act\n\n hippos_config = ParseConfig()\n hippos_config.parse_config()\n omit_interaction_1 = hippos_config.omit_interaction[0]\n omit_interaction_2 = hippos_config.omit_interaction[1]\n\n # Assert\n\n assert omit_interaction_1.interaction_type == \"hydrophobic\"\n assert omit_interaction_1.res_name == [\"ARG223\"]\n\n assert omit_interaction_2.interaction_type == \"h_bond\"\n assert omit_interaction_2.res_name == [\"ARG292\"]\n\n\ndef test_configuration_long_interaction_type(tmpdir):\n \"\"\"Test configuration checking all long interaction_type\"\"\"\n\n # Arrange\n\n config_file = tmpdir.mkdir(\"sub\").join(\"config.txt\")\n config_file.write(\n \"\"\"\ndocking_method plants # plants or vina\ndocking_conf plants-003.conf\n\nsimilarity_coef tanimoto mcconnaughey\n\nfull_ref 00000100000000000000000000000000000100000000000001000000000000010000001000000000000000000001000000000000000000000000000000101000000000000000000101000000000010000 00010101000000000000000000000000000100000000000001010000000000010000001000000000000010000000000000000000000001011000001000001000000000000000000101000000000000000 00010101000000100000000000000000000100000000000001010100100000010000001000000000000010000001000000000000010000000000100000101010000000000000000001000000000000000\n\nresidue_name ARG116 GLU117 LEU132 LYS148 ASP149 ARG150 ARG154 TRP177 SER178 ILE221 ARG223 THR224 GLU226 ALA245 HIS273 GLU275 GLU276 ARG292 ASP294 GLY347 ARG374 TRP408 TYR409\nresidue_number 40 41 56 72 73 74 78 101 102 145 147 148 150 169 197 199 200 216 218 271 298 332 333\n\nomit_interaction hydrophobic ARG116\nomit_interaction aromatic GLU117\nomit_interaction h_bond LEU132\nomit_interaction electrostatic LYS148\nomit_interaction h_bond_donor ASP149\nomit_interaction h_bond_acceptor ARG150\nomit_interaction electrostatic_positive ARG154\nomit_interaction electrostatic_negative TRP177\nomit_interaction aromatic_facetoface SER178\nomit_interaction aromatic_edgetoface ILE221\n\nfull_outfile plants_full_ifp.csv\nsim_outfile plants_similarity.csv\nlogfile plants.log\n\"\"\"\n )\n\n arg = os.path.join(config_file.dirname, config_file.basename)\n\n if len(sys.argv) > 1:\n sys.argv[1] = arg\n else:\n sys.argv.append(arg)\n\n # Act\n\n hippos_config = ParseConfig()\n hippos_config.parse_config()\n omit_interaction_1 = hippos_config.omit_interaction[0]\n omit_interaction_2 = hippos_config.omit_interaction[1]\n omit_interaction_3 = hippos_config.omit_interaction[2]\n omit_interaction_4 = hippos_config.omit_interaction[3]\n omit_interaction_5 = hippos_config.omit_interaction[4]\n omit_interaction_6 = hippos_config.omit_interaction[5]\n omit_interaction_7 = hippos_config.omit_interaction[6]\n omit_interaction_8 = hippos_config.omit_interaction[7]\n omit_interaction_9 = hippos_config.omit_interaction[8]\n omit_interaction_10 = hippos_config.omit_interaction[9]\n\n # Assert\n\n assert omit_interaction_1.interaction_type == \"hydrophobic\"\n assert omit_interaction_1.res_name == [\"ARG116\"]\n assert omit_interaction_2.interaction_type == \"aromatic\"\n assert omit_interaction_2.res_name == [\"GLU117\"]\n assert omit_interaction_3.interaction_type == \"h_bond\"\n assert omit_interaction_3.res_name == [\"LEU132\"]\n assert omit_interaction_4.interaction_type == \"electrostatic\"\n assert omit_interaction_4.res_name == [\"LYS148\"]\n assert omit_interaction_5.interaction_type == \"h_bond_donor\"\n assert omit_interaction_5.res_name == [\"ASP149\"]\n assert omit_interaction_6.interaction_type == \"h_bond_acceptor\"\n assert omit_interaction_6.res_name == [\"ARG150\"]\n assert omit_interaction_7.interaction_type == \"electrostatic_positive\"\n assert omit_interaction_7.res_name == [\"ARG154\"]\n assert omit_interaction_8.interaction_type == \"electrostatic_negative\"\n assert omit_interaction_8.res_name == [\"TRP177\"]\n assert omit_interaction_9.interaction_type == \"aromatic_facetoface\"\n assert omit_interaction_9.res_name == [\"SER178\"]\n assert omit_interaction_10.interaction_type == \"aromatic_edgetoface\"\n assert omit_interaction_10.res_name == [\"ILE221\"]\n\n\ndef test_configuration_short_interaction_type(tmpdir):\n \"\"\"Test configuration checking all short interaction_type\"\"\"\n\n # Arrange\n\n config_file = tmpdir.mkdir(\"sub\").join(\"config.txt\")\n config_file.write(\n \"\"\"\ndocking_method plants # plants or vina\ndocking_conf plants-003.conf\n\nsimilarity_coef tanimoto mcconnaughey\n\nfull_ref 00000100000000000000000000000000000100000000000001000000000000010000001000000000000000000001000000000000000000000000000000101000000000000000000101000000000010000 00010101000000000000000000000000000100000000000001010000000000010000001000000000000010000000000000000000000001011000001000001000000000000000000101000000000000000 00010101000000100000000000000000000100000000000001010100100000010000001000000000000010000001000000000000010000000000100000101010000000000000000001000000000000000\n\nresidue_name ARG116 GLU117 LEU132 LYS148 ASP149 ARG150 ARG154 TRP177 SER178 ILE221 ARG223 THR224 GLU226 ALA245 HIS273 GLU275 GLU276 ARG292 ASP294 GLY347 ARG374 TRP408 TYR409\nresidue_number 40 41 56 72 73 74 78 101 102 145 147 148 150 169 197 199 200 216 218 271 298 332 333\n\nomit_interaction HPB ARG116\nomit_interaction ARM GLU117\nomit_interaction HBD LEU132\nomit_interaction ELE LYS148\nomit_interaction HBD_DON ASP149\nomit_interaction HBD_ACC ARG150\nomit_interaction ELE_POS ARG154\nomit_interaction ELE_NEG TRP177\nomit_interaction ARM_F2F SER178\nomit_interaction ARM_E2F ILE221\n\nfull_outfile plants_full_ifp.csv\nsim_outfile plants_similarity.csv\nlogfile plants.log\n\"\"\"\n )\n\n arg = os.path.join(config_file.dirname, config_file.basename)\n\n if len(sys.argv) > 1:\n sys.argv[1] = arg\n else:\n sys.argv.append(arg)\n\n # Act\n\n hippos_config = ParseConfig()\n hippos_config.parse_config()\n omit_interaction_1 = hippos_config.omit_interaction[0]\n omit_interaction_2 = hippos_config.omit_interaction[1]\n omit_interaction_3 = hippos_config.omit_interaction[2]\n omit_interaction_4 = hippos_config.omit_interaction[3]\n omit_interaction_5 = hippos_config.omit_interaction[4]\n omit_interaction_6 = hippos_config.omit_interaction[5]\n omit_interaction_7 = hippos_config.omit_interaction[6]\n omit_interaction_8 = hippos_config.omit_interaction[7]\n omit_interaction_9 = hippos_config.omit_interaction[8]\n omit_interaction_10 = hippos_config.omit_interaction[9]\n\n # Assert\n\n assert omit_interaction_1.interaction_type == \"hydrophobic\"\n assert omit_interaction_1.res_name == [\"ARG116\"]\n assert omit_interaction_2.interaction_type == \"aromatic\"\n assert omit_interaction_2.res_name == [\"GLU117\"]\n assert omit_interaction_3.interaction_type == \"h_bond\"\n assert omit_interaction_3.res_name == [\"LEU132\"]\n assert omit_interaction_4.interaction_type == \"electrostatic\"\n assert omit_interaction_4.res_name == [\"LYS148\"]\n assert omit_interaction_5.interaction_type == \"h_bond_donor\"\n assert omit_interaction_5.res_name == [\"ASP149\"]\n assert omit_interaction_6.interaction_type == \"h_bond_acceptor\"\n assert omit_interaction_6.res_name == [\"ARG150\"]\n assert omit_interaction_7.interaction_type == \"electrostatic_positive\"\n assert omit_interaction_7.res_name == [\"ARG154\"]\n assert omit_interaction_8.interaction_type == \"electrostatic_negative\"\n assert omit_interaction_8.res_name == [\"TRP177\"]\n assert omit_interaction_9.interaction_type == \"aromatic_facetoface\"\n assert omit_interaction_9.res_name == [\"SER178\"]\n assert omit_interaction_10.interaction_type == \"aromatic_edgetoface\"\n assert omit_interaction_10.res_name == [\"ILE221\"]\n\n\ndef test_replace_bit_char():\n \"\"\"Test bit replacement function for omitted residue\"\"\"\n\n # Arrange\n\n bitstring = \"1000001\"\n\n omit_hydrophobic = [1, 0, 0, 0, 0, 0, 0]\n omit_aromatic = [0, 1, 1, 0, 0, 0, 0]\n omit_h_bond = [0, 0, 0, 1, 1, 0, 0]\n omit_electrostatic = [0, 0, 0, 0, 0, 1, 1]\n omit_h_bond_donor = [0, 0, 0, 1, 0, 0, 0]\n omit_h_bond_acceptor = [0, 0, 0, 0, 1, 0, 0]\n omit_electrostatic_positive = [0, 0, 0, 0, 0, 1, 0]\n omit_electrostatic_negative = [0, 0, 0, 0, 0, 0, 1]\n omit_aromatic_facetoface = [0, 1, 0, 0, 0, 0, 0]\n omit_aromatic_edgetoface = [0, 0, 1, 0, 0, 0, 0]\n\n # Act\n\n bitstring_1 = hippos.replace_bit_char(bitstring, omit_hydrophobic)\n bitstring_2 = hippos.replace_bit_char(bitstring, omit_aromatic)\n bitstring_3 = hippos.replace_bit_char(bitstring, omit_h_bond)\n bitstring_4 = hippos.replace_bit_char(bitstring, omit_electrostatic)\n bitstring_5 = hippos.replace_bit_char(bitstring, omit_h_bond_donor)\n bitstring_6 = hippos.replace_bit_char(bitstring, omit_h_bond_acceptor)\n bitstring_7 = hippos.replace_bit_char(bitstring, omit_electrostatic_positive)\n bitstring_8 = hippos.replace_bit_char(bitstring, omit_electrostatic_negative)\n bitstring_9 = hippos.replace_bit_char(bitstring, omit_aromatic_facetoface)\n bitstring_10 = hippos.replace_bit_char(bitstring, omit_aromatic_edgetoface)\n\n # Assert\n\n assert bitstring_1 == \"n000001\"\n assert bitstring_2 == \"1nn0001\"\n assert bitstring_3 == \"100nn01\"\n assert bitstring_4 == \"10000nn\"\n assert bitstring_5 == \"100n001\"\n assert bitstring_6 == \"1000n01\"\n assert bitstring_7 == \"10000n1\"\n assert bitstring_8 == \"100000n\"\n assert bitstring_9 == \"1n00001\"\n assert bitstring_10 == \"10n0001\"\n\n\ndef test_cleanup_omitted_interaction():\n \"\"\"Test for bitstring preparation prior to similarity calculation\"\"\"\n\n # Arrange\n\n refbit = \"000001000101\"\n tgtbit = \"11n00n000011\"\n\n # Act\n\n clean_refbit, clean_tgtbit = similarity.clean_omitted_interactions(refbit, tgtbit)\n\n # Assert\n\n assert clean_refbit == \"0000000101\"\n assert clean_tgtbit == \"1100000011\"\n"},"input_ids":{"kind":"list like","value":[37811,198,464,5254,329,42848,10375,3895,198,37811,198,198,11748,28686,198,11748,25064,198,198,6738,17268,1330,3706,83,29291,198,198,6738,12972,489,361,62,71,3974,418,1330,2547,325,16934,11,18568,418,11,26789,628,198,4299,1332,62,11250,3924,62,29762,62,296,270,62,3849,2673,7,22065,15908,2599,198,220,220,220,37227,14402,8398,329,267,16138,2176,10375,37811,628,220,220,220,1303,943,9521,628,220,220,220,4566,62,7753,796,45218,15908,13,28015,15908,7203,7266,11074,22179,7203,11250,13,14116,4943,198,220,220,220,4566,62,7753,13,13564,7,198,220,220,220,220,220,220,220,37227,198,67,8629,62,24396,220,220,220,6134,220,220,220,1303,6134,393,410,1437,198,67,8629,62,10414,220,220,220,220,220,6134,12,11245,13,10414,198,198,38610,414,62,1073,891,220,220,256,11227,2069,285,535,261,77,7493,20342,198,198,12853,62,5420,220,17643,486,25645,8269,2388,486,8269,2388,486,8269,2388,486,2388,8298,25645,2388,16,25645,8269,2388,8298,486,25645,8298,486,8269,8298,2388,3571,486,486,486,25645,8269,18005,8269,2388,486,486,8269,18005,2388,8298,8269,2388,486,25645,8269,8784,49388,486,2388,486,25645,8298,486,8269,24598,3571,486,486,486,2388,8298,25645,2388,16,8269,2388,486,486,486,8298,2388,8298,2388,8298,8269,2388,486,2388,8298,8269,2388,486,8269,8298,2388,486,486,486,25645,8298,8269,24598,198,198,411,312,518,62,3672,5923,38,18298,10188,52,17657,12509,52,19924,406,16309,18294,34658,19442,5923,38,8628,5923,38,21526,7579,47,22413,18871,23188,314,2538,26115,5923,38,22047,35383,24137,10188,52,24909,8355,32,22995,33700,27367,10188,52,23195,10188,52,27988,5923,38,32759,34658,27696,10188,56,30995,5923,38,31020,7579,47,26200,24412,49,29416,198,411,312,518,62,17618,2319,6073,7265,7724,8854,8915,8699,8949,15143,20299,22909,22613,6640,27191,29903,1594,939,26881,29217,33797,37576,41423,23460,198,198,296,270,62,3849,2673,220,7409,10051,20803,220,5923,38,22047,198,198,12853,62,448,7753,6134,62,12853,62,361,79,13,40664,198,14323,62,448,7753,6134,62,38610,414,13,40664,198,6404,7753,6134,13,6404,198,37811,198,220,220,220,1267,628,220,220,220,1822,796,28686,13,6978,13,22179,7,11250,62,7753,13,15908,3672,11,4566,62,7753,13,12093,12453,8,628,220,220,220,611,18896,7,17597,13,853,85,8,1875,352,25,198,220,220,220,220,220,220,220,25064,13,853,85,58,16,60,796,1822,198,220,220,220,2073,25,198,220,220,220,220,220,220,220,25064,13,853,85,13,33295,7,853,8,628,220,220,220,1303,2191,628,220,220,220,18568,418,62,11250,796,2547,325,16934,3419,198,220,220,220,18568,418,62,11250,13,29572,62,11250,3419,198,220,220,220,42848,62,3849,2673,796,18568,418,62,11250,13,296,270,62,3849,2673,58,15,60,628,220,220,220,1303,2195,861,628,220,220,220,6818,42848,62,3849,2673,13,3849,2673,62,4906,6624,366,15511,10051,20803,1,198,220,220,220,6818,42848,62,3849,2673,13,411,62,3672,6624,14631,1503,38,22047,8973,628,198,4299,1332,62,11250,3924,62,296,270,62,48101,62,411,312,518,62,3849,2673,7,22065,15908,2599,198,220,220,220,37227,14402,8398,329,267,16138,3294,35186,10375,37811,628,220,220,220,1303,943,9521,628,220,220,220,4566,62,7753,796,45218,15908,13,28015,15908,7203,7266,11074,22179,7203,11250,13,14116,4943,198,220,220,220,4566,62,7753,13,13564,7,198,220,220,220,220,220,220,220,37227,198,67,8629,62,24396,220,220,220,6134,220,220,220,1303,6134,393,410,1437,198,67,8629,62,10414,220,220,220,220,220,6134,12,11245,13,10414,198,198,38610,414,62,1073,891,220,220,256,11227,2069,285,535,261,77,7493,20342,198,198,12853,62,5420,220,17643,486,25645,8269,2388,486,8269,2388,486,8269,2388,486,2388,8298,25645,2388,16,25645,8269,2388,8298,486,25645,8298,486,8269,8298,2388,3571,486,486,486,25645,8269,18005,8269,2388,486,486,8269,18005,2388,8298,8269,2388,486,25645,8269,8784,49388,486,2388,486,25645,8298,486,8269,24598,3571,486,486,486,2388,8298,25645,2388,16,8269,2388,486,486,486,8298,2388,8298,2388,8298,8269,2388,486,2388,8298,8269,2388,486,8269,8298,2388,486,486,486,25645,8298,8269,24598,198,198,411,312,518,62,3672,5923,38,18298,10188,52,17657,12509,52,19924,406,16309,18294,34658,19442,5923,38,8628,5923,38,21526,7579,47,22413,18871,23188,314,2538,26115,5923,38,22047,35383,24137,10188,52,24909,8355,32,22995,33700,27367,10188,52,23195,10188,52,27988,5923,38,32759,34658,27696,10188,56,30995,5923,38,31020,7579,47,26200,24412,49,29416,198,411,312,518,62,17618,2319,6073,7265,7724,8854,8915,8699,8949,15143,20299,22909,22613,6640,27191,29903,1594,939,26881,29217,33797,37576,41423,23460,198,198,296,270,62,3849,2673,220,7409,10051,20803,220,5923,38,8628,7579,47,22413,5923,38,22047,198,198,12853,62,448,7753,6134,62,12853,62,361,79,13,40664,198,14323,62,448,7753,6134,62,38610,414,13,40664,198,6404,7753,6134,13,6404,198,37811,198,220,220,220,1267,628,220,220,220,1822,796,28686,13,6978,13,22179,7,11250,62,7753,13,15908,3672,11,4566,62,7753,13,12093,12453,8,628,220,220,220,611,18896,7,17597,13,853,85,8,1875,352,25,198,220,220,220,220,220,220,220,25064,13,853,85,58,16,60,796,1822,198,220,220,220,2073,25,198,220,220,220,220,220,220,220,25064,13,853,85,13,33295,7,853,8,628,220,220,220,1303,2191,628,220,220,220,18568,418,62,11250,796,2547,325,16934,3419,198,220,220,220,18568,418,62,11250,13,29572,62,11250,3419,198,220,220,220,42848,62,3849,2673,796,18568,418,62,11250,13,296,270,62,3849,2673,58,15,60,628,220,220,220,1303,2195,861,628,220,220,220,6818,42848,62,3849,2673,13,3849,2673,62,4906,6624,366,15511,10051,20803,1,198,220,220,220,6818,42848,62,3849,2673,13,411,62,3672,6624,14631,1503,38,8628,1600,366,5446,47,22413,1600,366,1503,38,22047,8973,628,198,4299,1332,62,11250,3924,62,296,270,62,48101,62,3849,2673,62,4906,7,22065,15908,2599,198,220,220,220,37227,14402,8398,329,267,16138,3294,10375,2099,37811,628,220,220,220,1303,943,9521,628,220,220,220,4566,62,7753,796,45218,15908,13,28015,15908,7203,7266,11074,22179,7203,11250,13,14116,4943,198,220,220,220,4566,62,7753,13,13564,7,198,220,220,220,220,220,220,220,37227,198,67,8629,62,24396,220,220,220,6134,220,220,220,1303,6134,393,410,1437,198,67,8629,62,10414,220,220,220,220,220,6134,12,11245,13,10414,198,198,38610,414,62,1073,891,220,220,256,11227,2069,285,535,261,77,7493,20342,198,198,12853,62,5420,220,17643,486,25645,8269,2388,486,8269,2388,486,8269,2388,486,2388,8298,25645,2388,16,25645,8269,2388,8298,486,25645,8298,486,8269,8298,2388,3571,486,486,486,25645,8269,18005,8269,2388,486,486,8269,18005,2388,8298,8269,2388,486,25645,8269,8784,49388,486,2388,486,25645,8298,486,8269,24598,3571,486,486,486,2388,8298,25645,2388,16,8269,2388,486,486,486,8298,2388,8298,2388,8298,8269,2388,486,2388,8298,8269,2388,486,8269,8298,2388,486,486,486,25645,8298,8269,24598,198,198,411,312,518,62,3672,5923,38,18298,10188,52,17657,12509,52,19924,406,16309,18294,34658,19442,5923,38,8628,5923,38,21526,7579,47,22413,18871,23188,314,2538,26115,5923,38,22047,35383,24137,10188,52,24909,8355,32,22995,33700,27367,10188,52,23195,10188,52,27988,5923,38,32759,34658,27696,10188,56,30995,5923,38,31020,7579,47,26200,24412,49,29416,198,411,312,518,62,17618,2319,6073,7265,7724,8854,8915,8699,8949,15143,20299,22909,22613,6640,27191,29903,1594,939,26881,29217,33797,37576,41423,23460,198,198,296,270,62,3849,2673,220,7409,10051,20803,220,5923,38,22047,198,296,270,62,3849,2673,220,289,62,65,623,220,5923,38,32759,198,198,12853,62,448,7753,6134,62,12853,62,361,79,13,40664,198,14323,62,448,7753,6134,62,38610,414,13,40664,198,6404,7753,6134,13,6404,198,37811,198,220,220,220,1267,628,220,220,220,1822,796,28686,13,6978,13,22179,7,11250,62,7753,13,15908,3672,11,4566,62,7753,13,12093,12453,8,628,220,220,220,611,18896,7,17597,13,853,85,8,1875,352,25,198,220,220,220,220,220,220,220,25064,13,853,85,58,16,60,796,1822,198,220,220,220,2073,25,198,220,220,220,220,220,220,220,25064,13,853,85,13,33295,7,853,8,628,220,220,220,1303,2191,628,220,220,220,18568,418,62,11250,796,2547,325,16934,3419,198,220,220,220,18568,418,62,11250,13,29572,62,11250,3419,198,220,220,220,42848,62,3849,2673,62,16,796,18568,418,62,11250,13,296,270,62,3849,2673,58,15,60,198,220,220,220,42848,62,3849,2673,62,17,796,18568,418,62,11250,13,296,270,62,3849,2673,58,16,60,628,220,220,220,1303,2195,861,628,220,220,220,6818,42848,62,3849,2673,62,16,13,3849,2673,62,4906,6624,366,15511,10051,20803,1,198,220,220,220,6818,42848,62,3849,2673,62,16,13,411,62,3672,6624,14631,1503,38,22047,8973,628,220,220,220,6818,42848,62,3849,2673,62,17,13,3849,2673,62,4906,6624,366,71,62,65,623,1,198,220,220,220,6818,42848,62,3849,2673,62,17,13,411,62,3672,6624,14631,1503,38,32759,8973,628,198,4299,1332,62,11250,3924,62,6511,62,3849,2673,62,4906,7,22065,15908,2599,198,220,220,220,37227,14402,8398,10627,477,890,10375,62,4906,37811,628,220,220,220,1303,943,9521,628,220,220,220,4566,62,7753,796,45218,15908,13,28015,15908,7203,7266,11074,22179,7203,11250,13,14116,4943,198,220,220,220,4566,62,7753,13,13564,7,198,220,220,220,220,220,220,220,37227,198,67,8629,62,24396,220,220,220,6134,220,220,220,1303,6134,393,410,1437,198,67,8629,62,10414,220,220,220,220,220,6134,12,11245,13,10414,198,198,38610,414,62,1073,891,220,220,256,11227,2069,285,535,261,77,7493,20342,198,198,12853,62,5420,220,17643,486,25645,8269,2388,486,8269,2388,486,8269,2388,486,2388,8298,25645,2388,16,25645,8269,2388,8298,486,25645,8298,486,8269,8298,2388,3571,486,486,486,25645,8269,18005,8269,2388,486,486,8269,18005,2388,8298,8269,2388,486,25645,8269,8784,49388,486,2388,486,25645,8298,486,8269,24598,3571,486,486,486,2388,8298,25645,2388,16,8269,2388,486,486,486,8298,2388,8298,2388,8298,8269,2388,486,2388,8298,8269,2388,486,8269,8298,2388,486,486,486,25645,8298,8269,24598,198,198,411,312,518,62,3672,5923,38,18298,10188,52,17657,12509,52,19924,406,16309,18294,34658,19442,5923,38,8628,5923,38,21526,7579,47,22413,18871,23188,314,2538,26115,5923,38,22047,35383,24137,10188,52,24909,8355,32,22995,33700,27367,10188,52,23195,10188,52,27988,5923,38,32759,34658,27696,10188,56,30995,5923,38,31020,7579,47,26200,24412,49,29416,198,411,312,518,62,17618,2319,6073,7265,7724,8854,8915,8699,8949,15143,20299,22909,22613,6640,27191,29903,1594,939,26881,29217,33797,37576,41423,23460,198,198,296,270,62,3849,2673,220,7409,10051,20803,220,5923,38,18298,198,296,270,62,3849,2673,220,48440,220,10188,52,17657,198,296,270,62,3849,2673,220,289,62,65,623,220,220,12509,52,19924,198,296,270,62,3849,2673,220,15206,12708,220,406,16309,18294,198,296,270,62,3849,2673,220,289,62,65,623,62,9099,273,220,34658,19442,198,296,270,62,3849,2673,220,289,62,65,623,62,13635,273,220,5923,38,8628,198,296,270,62,3849,2673,220,15206,12708,62,24561,220,5923,38,21526,198,296,270,62,3849,2673,220,15206,12708,62,31591,220,7579,47,22413,198,296,270,62,3849,2673,220,48440,62,69,23253,1659,558,220,18871,23188,198,296,270,62,3849,2673,220,48440,62,276,1136,1659,558,220,314,2538,26115,198,198,12853,62,448,7753,6134,62,12853,62,361,79,13,40664,198,14323,62,448,7753,6134,62,38610,414,13,40664,198,6404,7753,6134,13,6404,198,37811,198,220,220,220,1267,628,220,220,220,1822,796,28686,13,6978,13,22179,7,11250,62,7753,13,15908,3672,11,4566,62,7753,13,12093,12453,8,628,220,220,220,611,18896,7,17597,13,853,85,8,1875,352,25,198,220,220,220,220,220,220,220,25064,13,853,85,58,16,60,796,1822,198,220,220,220,2073,25,198,220,220,220,220,220,220,220,25064,13,853,85,13,33295,7,853,8,628,220,220,220,1303,2191,628,220,220,220,18568,418,62,11250,796,2547,325,16934,3419,198,220,220,220,18568,418,62,11250,13,29572,62,11250,3419,198,220,220,220,42848,62,3849,2673,62,16,796,18568,418,62,11250,13,296,270,62,3849,2673,58,15,60,198,220,220,220,42848,62,3849,2673,62,17,796,18568,418,62,11250,13,296,270,62,3849,2673,58,16,60,198,220,220,220,42848,62,3849,2673,62,18,796,18568,418,62,11250,13,296,270,62,3849,2673,58,17,60,198,220,220,220,42848,62,3849,2673,62,19,796,18568,418,62,11250,13,296,270,62,3849,2673,58,18,60,198,220,220,220,42848,62,3849,2673,62,20,796,18568,418,62,11250,13,296,270,62,3849,2673,58,19,60,198,220,220,220,42848,62,3849,2673,62,21,796,18568,418,62,11250,13,296,270,62,3849,2673,58,20,60,198,220,220,220,42848,62,3849,2673,62,22,796,18568,418,62,11250,13,296,270,62,3849,2673,58,21,60,198,220,220,220,42848,62,3849,2673,62,23,796,18568,418,62,11250,13,296,270,62,3849,2673,58,22,60,198,220,220,220,42848,62,3849,2673,62,24,796,18568,418,62,11250,13,296,270,62,3849,2673,58,23,60,198,220,220,220,42848,62,3849,2673,62,940,796,18568,418,62,11250,13,296,270,62,3849,2673,58,24,60,628,220,220,220,1303,2195,861,628,220,220,220,6818,42848,62,3849,2673,62,16,13,3849,2673,62,4906,6624,366,15511,10051,20803,1,198,220,220,220,6818,42848,62,3849,2673,62,16,13,411,62,3672,6624,14631,1503,38,18298,8973,198,220,220,220,6818,42848,62,3849,2673,62,17,13,3849,2673,62,4906,6624,366,283,13730,1,198,220,220,220,6818,42848,62,3849,2673,62,17,13,411,62,3672,6624,14631,8763,52,17657,8973,198,220,220,220,6818,42848,62,3849,2673,62,18,13,3849,2673,62,4906,6624,366,71,62,65,623,1,198,220,220,220,6818,42848,62,3849,2673,62,18,13,411,62,3672,6624,14631,2538,52,19924,8973,198,220,220,220,6818,42848,62,3849,2673,62,19,13,3849,2673,62,4906,6624,366,9509,305,12708,1,198,220,220,220,6818,42848,62,3849,2673,62,19,13,411,62,3672,6624,14631,11319,50,18294,8973,198,220,220,220,6818,42848,62,3849,2673,62,20,13,3849,2673,62,4906,6624,366,71,62,65,623,62,9099,273,1,198,220,220,220,6818,42848,62,3849,2673,62,20,13,411,62,3672,6624,14631,1921,47,19442,8973,198,220,220,220,6818,42848,62,3849,2673,62,21,13,3849,2673,62,4906,6624,366,71,62,65,623,62,13635,273,1,198,220,220,220,6818,42848,62,3849,2673,62,21,13,411,62,3672,6624,14631,1503,38,8628,8973,198,220,220,220,6818,42848,62,3849,2673,62,22,13,3849,2673,62,4906,6624,366,9509,305,12708,62,24561,1,198,220,220,220,6818,42848,62,3849,2673,62,22,13,411,62,3672,6624,14631,1503,38,21526,8973,198,220,220,220,6818,42848,62,3849,2673,62,23,13,3849,2673,62,4906,6624,366,9509,305,12708,62,31591,1,198,220,220,220,6818,42848,62,3849,2673,62,23,13,411,62,3672,6624,14631,5446,47,22413,8973,198,220,220,220,6818,42848,62,3849,2673,62,24,13,3849,2673,62,4906,6624,366,283,13730,62,69,23253,1659,558,1,198,220,220,220,6818,42848,62,3849,2673,62,24,13,411,62,3672,6624,14631,35009,23188,8973,198,220,220,220,6818,42848,62,3849,2673,62,940,13,3849,2673,62,4906,6624,366,283,13730,62,276,1136,1659,558,1,198,220,220,220,6818,42848,62,3849,2673,62,940,13,411,62,3672,6624,14631,41119,26115,8973,628,198,4299,1332,62,11250,3924,62,19509,62,3849,2673,62,4906,7,22065,15908,2599,198,220,220,220,37227,14402,8398,10627,477,1790,10375,62,4906,37811,628,220,220,220,1303,943,9521,628,220,220,220,4566,62,7753,796,45218,15908,13,28015,15908,7203,7266,11074,22179,7203,11250,13,14116,4943,198,220,220,220,4566,62,7753,13,13564,7,198,220,220,220,220,220,220,220,37227,198,67,8629,62,24396,220,220,220,6134,220,220,220,1303,6134,393,410,1437,198,67,8629,62,10414,220,220,220,220,220,6134,12,11245,13,10414,198,198,38610,414,62,1073,891,220,220,256,11227,2069,285,535,261,77,7493,20342,198,198,12853,62,5420,220,17643,486,25645,8269,2388,486,8269,2388,486,8269,2388,486,2388,8298,25645,2388,16,25645,8269,2388,8298,486,25645,8298,486,8269,8298,2388,3571,486,486,486,25645,8269,18005,8269,2388,486,486,8269,18005,2388,8298,8269,2388,486,25645,8269,8784,49388,486,2388,486,25645,8298,486,8269,24598,3571,486,486,486,2388,8298,25645,2388,16,8269,2388,486,486,486,8298,2388,8298,2388,8298,8269,2388,486,2388,8298,8269,2388,486,8269,8298,2388,486,486,486,25645,8298,8269,24598,198,198,411,312,518,62,3672,5923,38,18298,10188,52,17657,12509,52,19924,406,16309,18294,34658,19442,5923,38,8628,5923,38,21526,7579,47,22413,18871,23188,314,2538,26115,5923,38,22047,35383,24137,10188,52,24909,8355,32,22995,33700,27367,10188,52,23195,10188,52,27988,5923,38,32759,34658,27696,10188,56,30995,5923,38,31020,7579,47,26200,24412,49,29416,198,411,312,518,62,17618,2319,6073,7265,7724,8854,8915,8699,8949,15143,20299,22909,22613,6640,27191,29903,1594,939,26881,29217,33797,37576,41423,23460,198,198,296,270,62,3849,2673,220,6574,33,220,5923,38,18298,198,296,270,62,3849,2673,220,20359,220,10188,52,17657,198,296,270,62,3849,2673,220,367,14529,220,220,12509,52,19924,198,296,270,62,3849,2673,220,40342,220,406,16309,18294,198,296,270,62,3849,2673,220,367,14529,62,41173,220,34658,19442,198,296,270,62,3849,2673,220,367,14529,62,26861,220,5923,38,8628,198,296,270,62,3849,2673,220,40342,62,37997,220,5923,38,21526,198,296,270,62,3849,2673,220,40342,62,45,7156,220,7579,47,22413,198,296,270,62,3849,2673,220,20359,62,37,17,37,220,18871,23188,198,296,270,62,3849,2673,220,20359,62,36,17,37,220,314,2538,26115,198,198,12853,62,448,7753,6134,62,12853,62,361,79,13,40664,198,14323,62,448,7753,6134,62,38610,414,13,40664,198,6404,7753,6134,13,6404,198,37811,198,220,220,220,1267,628,220,220,220,1822,796,28686,13,6978,13,22179,7,11250,62,7753,13,15908,3672,11,4566,62,7753,13,12093,12453,8,628,220,220,220,611,18896,7,17597,13,853,85,8,1875,352,25,198,220,220,220,220,220,220,220,25064,13,853,85,58,16,60,796,1822,198,220,220,220,2073,25,198,220,220,220,220,220,220,220,25064,13,853,85,13,33295,7,853,8,628,220,220,220,1303,2191,628,220,220,220,18568,418,62,11250,796,2547,325,16934,3419,198,220,220,220,18568,418,62,11250,13,29572,62,11250,3419,198,220,220,220,42848,62,3849,2673,62,16,796,18568,418,62,11250,13,296,270,62,3849,2673,58,15,60,198,220,220,220,42848,62,3849,2673,62,17,796,18568,418,62,11250,13,296,270,62,3849,2673,58,16,60,198,220,220,220,42848,62,3849,2673,62,18,796,18568,418,62,11250,13,296,270,62,3849,2673,58,17,60,198,220,220,220,42848,62,3849,2673,62,19,796,18568,418,62,11250,13,296,270,62,3849,2673,58,18,60,198,220,220,220,42848,62,3849,2673,62,20,796,18568,418,62,11250,13,296,270,62,3849,2673,58,19,60,198,220,220,220,42848,62,3849,2673,62,21,796,18568,418,62,11250,13,296,270,62,3849,2673,58,20,60,198,220,220,220,42848,62,3849,2673,62,22,796,18568,418,62,11250,13,296,270,62,3849,2673,58,21,60,198,220,220,220,42848,62,3849,2673,62,23,796,18568,418,62,11250,13,296,270,62,3849,2673,58,22,60,198,220,220,220,42848,62,3849,2673,62,24,796,18568,418,62,11250,13,296,270,62,3849,2673,58,23,60,198,220,220,220,42848,62,3849,2673,62,940,796,18568,418,62,11250,13,296,270,62,3849,2673,58,24,60,628,220,220,220,1303,2195,861,628,220,220,220,6818,42848,62,3849,2673,62,16,13,3849,2673,62,4906,6624,366,15511,10051,20803,1,198,220,220,220,6818,42848,62,3849,2673,62,16,13,411,62,3672,6624,14631,1503,38,18298,8973,198,220,220,220,6818,42848,62,3849,2673,62,17,13,3849,2673,62,4906,6624,366,283,13730,1,198,220,220,220,6818,42848,62,3849,2673,62,17,13,411,62,3672,6624,14631,8763,52,17657,8973,198,220,220,220,6818,42848,62,3849,2673,62,18,13,3849,2673,62,4906,6624,366,71,62,65,623,1,198,220,220,220,6818,42848,62,3849,2673,62,18,13,411,62,3672,6624,14631,2538,52,19924,8973,198,220,220,220,6818,42848,62,3849,2673,62,19,13,3849,2673,62,4906,6624,366,9509,305,12708,1,198,220,220,220,6818,42848,62,3849,2673,62,19,13,411,62,3672,6624,14631,11319,50,18294,8973,198,220,220,220,6818,42848,62,3849,2673,62,20,13,3849,2673,62,4906,6624,366,71,62,65,623,62,9099,273,1,198,220,220,220,6818,42848,62,3849,2673,62,20,13,411,62,3672,6624,14631,1921,47,19442,8973,198,220,220,220,6818,42848,62,3849,2673,62,21,13,3849,2673,62,4906,6624,366,71,62,65,623,62,13635,273,1,198,220,220,220,6818,42848,62,3849,2673,62,21,13,411,62,3672,6624,14631,1503,38,8628,8973,198,220,220,220,6818,42848,62,3849,2673,62,22,13,3849,2673,62,4906,6624,366,9509,305,12708,62,24561,1,198,220,220,220,6818,42848,62,3849,2673,62,22,13,411,62,3672,6624,14631,1503,38,21526,8973,198,220,220,220,6818,42848,62,3849,2673,62,23,13,3849,2673,62,4906,6624,366,9509,305,12708,62,31591,1,198,220,220,220,6818,42848,62,3849,2673,62,23,13,411,62,3672,6624,14631,5446,47,22413,8973,198,220,220,220,6818,42848,62,3849,2673,62,24,13,3849,2673,62,4906,6624,366,283,13730,62,69,23253,1659,558,1,198,220,220,220,6818,42848,62,3849,2673,62,24,13,411,62,3672,6624,14631,35009,23188,8973,198,220,220,220,6818,42848,62,3849,2673,62,940,13,3849,2673,62,4906,6624,366,283,13730,62,276,1136,1659,558,1,198,220,220,220,6818,42848,62,3849,2673,62,940,13,411,62,3672,6624,14631,41119,26115,8973,628,198,4299,1332,62,33491,62,2545,62,10641,33529,198,220,220,220,37227,14402,1643,9014,2163,329,22532,35186,37811,628,220,220,220,1303,943,9521,628,220,220,220,1643,8841,796,366,49388,486,1,628,220,220,220,42848,62,15511,10051,20803,796,685,16,11,657,11,657,11,657,11,657,11,657,11,657,60,198,220,220,220,42848,62,283,13730,796,685,15,11,352,11,352,11,657,11,657,11,657,11,657,60,198,220,220,220,42848,62,71,62,65,623,796,685,15,11,657,11,657,11,352,11,352,11,657,11,657,60,198,220,220,220,42848,62,9509,305,12708,796,685,15,11,657,11,657,11,657,11,657,11,352,11,352,60,198,220,220,220,42848,62,71,62,65,623,62,9099,273,796,685,15,11,657,11,657,11,352,11,657,11,657,11,657,60,198,220,220,220,42848,62,71,62,65,623,62,13635,273,796,685,15,11,657,11,657,11,657,11,352,11,657,11,657,60,198,220,220,220,42848,62,9509,305,12708,62,24561,796,685,15,11,657,11,657,11,657,11,657,11,352,11,657,60,198,220,220,220,42848,62,9509,305,12708,62,31591,796,685,15,11,657,11,657,11,657,11,657,11,657,11,352,60,198,220,220,220,42848,62,283,13730,62,69,23253,1659,558,796,685,15,11,352,11,657,11,657,11,657,11,657,11,657,60,198,220,220,220,42848,62,283,13730,62,276,1136,1659,558,796,685,15,11,657,11,352,11,657,11,657,11,657,11,657,60,628,220,220,220,1303,2191,628,220,220,220,1643,8841,62,16,796,18568,418,13,33491,62,2545,62,10641,7,2545,8841,11,42848,62,15511,10051,20803,8,198,220,220,220,1643,8841,62,17,796,18568,418,13,33491,62,2545,62,10641,7,2545,8841,11,42848,62,283,13730,8,198,220,220,220,1643,8841,62,18,796,18568,418,13,33491,62,2545,62,10641,7,2545,8841,11,42848,62,71,62,65,623,8,198,220,220,220,1643,8841,62,19,796,18568,418,13,33491,62,2545,62,10641,7,2545,8841,11,42848,62,9509,305,12708,8,198,220,220,220,1643,8841,62,20,796,18568,418,13,33491,62,2545,62,10641,7,2545,8841,11,42848,62,71,62,65,623,62,9099,273,8,198,220,220,220,1643,8841,62,21,796,18568,418,13,33491,62,2545,62,10641,7,2545,8841,11,42848,62,71,62,65,623,62,13635,273,8,198,220,220,220,1643,8841,62,22,796,18568,418,13,33491,62,2545,62,10641,7,2545,8841,11,42848,62,9509,305,12708,62,24561,8,198,220,220,220,1643,8841,62,23,796,18568,418,13,33491,62,2545,62,10641,7,2545,8841,11,42848,62,9509,305,12708,62,31591,8,198,220,220,220,1643,8841,62,24,796,18568,418,13,33491,62,2545,62,10641,7,2545,8841,11,42848,62,283,13730,62,69,23253,1659,558,8,198,220,220,220,1643,8841,62,940,796,18568,418,13,33491,62,2545,62,10641,7,2545,8841,11,42848,62,283,13730,62,276,1136,1659,558,8,628,220,220,220,1303,2195,861,628,220,220,220,6818,1643,8841,62,16,6624,366,77,2388,486,1,198,220,220,220,6818,1643,8841,62,17,6624,366,16,20471,18005,1,198,220,220,220,6818,1643,8841,62,18,6624,366,3064,20471,486,1,198,220,220,220,6818,1643,8841,62,19,6624,366,49388,20471,1,198,220,220,220,6818,1643,8841,62,20,6624,366,3064,77,8298,1,198,220,220,220,6818,1643,8841,62,21,6624,366,12825,77,486,1,198,220,220,220,6818,1643,8841,62,22,6624,366,49388,77,16,1,198,220,220,220,6818,1643,8841,62,23,6624,366,3064,830,77,1,198,220,220,220,6818,1643,8841,62,24,6624,366,16,77,2388,16,1,198,220,220,220,6818,1643,8841,62,940,6624,366,940,77,18005,1,628,198,4299,1332,62,27773,929,62,296,2175,62,3849,2673,33529,198,220,220,220,37227,14402,329,1643,8841,11824,3161,284,26789,17952,37811,628,220,220,220,1303,943,9521,628,220,220,220,1006,2545,796,366,2388,486,18005,486,1,198,220,220,220,256,13655,2545,796,366,1157,77,405,77,2388,1157,1,628,220,220,220,1303,2191,628,220,220,220,3424,62,5420,2545,11,3424,62,83,13655,2545,796,26789,13,27773,62,296,2175,62,3849,4658,7,5420,2545,11,256,13655,2545,8,628,220,220,220,1303,2195,861,628,220,220,220,6818,3424,62,5420,2545,6624,366,10535,486,486,1,198,220,220,220,6818,3424,62,83,13655,2545,6624,366,1157,10535,1157,1,198],"string":"[\n 37811,\n 198,\n 464,\n 5254,\n 329,\n 42848,\n 10375,\n 3895,\n 198,\n 37811,\n 198,\n 198,\n 11748,\n 28686,\n 198,\n 11748,\n 25064,\n 198,\n 198,\n 6738,\n 17268,\n 1330,\n 3706,\n 83,\n 29291,\n 198,\n 198,\n 6738,\n 12972,\n 489,\n 361,\n 62,\n 71,\n 3974,\n 418,\n 1330,\n 2547,\n 325,\n 16934,\n 11,\n 18568,\n 418,\n 11,\n 26789,\n 628,\n 198,\n 4299,\n 1332,\n 62,\n 11250,\n 3924,\n 62,\n 29762,\n 62,\n 296,\n 270,\n 62,\n 3849,\n 2673,\n 7,\n 22065,\n 15908,\n 2599,\n 198,\n 220,\n 220,\n 220,\n 37227,\n 14402,\n 8398,\n 329,\n 267,\n 16138,\n 2176,\n 10375,\n 37811,\n 628,\n 220,\n 220,\n 220,\n 1303,\n 943,\n 9521,\n 628,\n 220,\n 220,\n 220,\n 4566,\n 62,\n 7753,\n 796,\n 45218,\n 15908,\n 13,\n 28015,\n 15908,\n 7203,\n 7266,\n 11074,\n 22179,\n 7203,\n 11250,\n 13,\n 14116,\n 4943,\n 198,\n 220,\n 220,\n 220,\n 4566,\n 62,\n 7753,\n 13,\n 13564,\n 7,\n 198,\n 220,\n 220,\n 220,\n 220,\n 220,\n 220,\n 220,\n 37227,\n 198,\n 67,\n 8629,\n 62,\n 24396,\n 220,\n 220,\n 220,\n 6134,\n 220,\n 220,\n 220,\n 1303,\n 6134,\n 393,\n 410,\n 1437,\n 198,\n 67,\n 8629,\n 62,\n 10414,\n 220,\n 220,\n 220,\n 220,\n 220,\n 6134,\n 12,\n 11245,\n 13,\n 10414,\n 198,\n 198,\n 38610,\n 414,\n 62,\n 1073,\n 891,\n 220,\n 220,\n 256,\n 11227,\n 2069,\n 285,\n 535,\n 261,\n 77,\n 7493,\n 20342,\n 198,\n 198,\n 12853,\n 62,\n 5420,\n 220,\n 17643,\n 486,\n 25645,\n 8269,\n 2388,\n 486,\n 8269,\n 2388,\n 486,\n 8269,\n 2388,\n 486,\n 2388,\n 8298,\n 25645,\n 2388,\n 16,\n 25645,\n 8269,\n 2388,\n 8298,\n 486,\n 25645,\n 8298,\n 486,\n 8269,\n 8298,\n 2388,\n 3571,\n 486,\n 486,\n 486,\n 25645,\n 8269,\n 18005,\n 8269,\n 2388,\n 486,\n 486,\n 8269,\n 18005,\n 2388,\n 8298,\n 8269,\n 2388,\n 486,\n 25645,\n 8269,\n 8784,\n 49388,\n 486,\n 2388,\n 486,\n 25645,\n 8298,\n 486,\n 8269,\n 24598,\n 3571,\n 486,\n 486,\n 486,\n 2388,\n 8298,\n 25645,\n 2388,\n 16,\n 8269,\n 2388,\n 486,\n 486,\n 486,\n 8298,\n 2388,\n 8298,\n 2388,\n 8298,\n 8269,\n 2388,\n 486,\n 2388,\n 8298,\n 8269,\n 2388,\n 486,\n 8269,\n 8298,\n 2388,\n 486,\n 486,\n 486,\n 25645,\n 8298,\n 8269,\n 24598,\n 198,\n 198,\n 411,\n 312,\n 518,\n 62,\n 3672,\n 5923,\n 38,\n 18298,\n 10188,\n 52,\n 17657,\n 12509,\n 52,\n 19924,\n 406,\n 16309,\n 18294,\n 34658,\n 19442,\n 5923,\n 38,\n 8628,\n 5923,\n 38,\n 21526,\n 7579,\n 47,\n 22413,\n 18871,\n 23188,\n 314,\n 2538,\n 26115,\n 5923,\n 38,\n 22047,\n 35383,\n 24137,\n 10188,\n 52,\n 24909,\n 8355,\n 32,\n 22995,\n 33700,\n 27367,\n 10188,\n 52,\n 23195,\n 10188,\n 52,\n 27988,\n 5923,\n 38,\n 32759,\n 34658,\n 27696,\n 10188,\n 56,\n 30995,\n 5923,\n 38,\n 31020,\n 7579,\n 47,\n 26200,\n 24412,\n 49,\n 29416,\n 198,\n 411,\n 312,\n 518,\n 62,\n 17618,\n 2319,\n 6073,\n 7265,\n 7724,\n 8854,\n 8915,\n 8699,\n 8949,\n 15143,\n 20299,\n 22909,\n 22613,\n 6640,\n 27191,\n 29903,\n 1594,\n 939,\n 26881,\n 29217,\n 33797,\n 37576,\n 41423,\n 23460,\n 198,\n 198,\n 296,\n 270,\n 62,\n 3849,\n 2673,\n 220,\n 7409,\n 10051,\n 20803,\n 220,\n 5923,\n 38,\n 22047,\n 198,\n 198,\n 12853,\n 62,\n 448,\n 7753,\n 6134,\n 62,\n 12853,\n 62,\n 361,\n 79,\n 13,\n 40664,\n 198,\n 14323,\n 62,\n 448,\n 7753,\n 6134,\n 62,\n 38610,\n 414,\n 13,\n 40664,\n 198,\n 6404,\n 7753,\n 6134,\n 13,\n 6404,\n 198,\n 37811,\n 198,\n 220,\n 220,\n 220,\n 1267,\n 628,\n 220,\n 220,\n 220,\n 1822,\n 796,\n 28686,\n 13,\n 6978,\n 13,\n 22179,\n 7,\n 11250,\n 62,\n 7753,\n 13,\n 15908,\n 3672,\n 11,\n 4566,\n 62,\n 7753,\n 13,\n 12093,\n 12453,\n 8,\n 628,\n 220,\n 220,\n 220,\n 611,\n 18896,\n 7,\n 17597,\n 13,\n 853,\n 85,\n 8,\n 1875,\n 352,\n 25,\n 198,\n 220,\n 220,\n 220,\n 220,\n 220,\n 220,\n 220,\n 25064,\n 13,\n 853,\n 85,\n 58,\n 16,\n 60,\n 796,\n 1822,\n 198,\n 220,\n 220,\n 220,\n 2073,\n 25,\n 198,\n 220,\n 220,\n 220,\n 220,\n 220,\n 220,\n 220,\n 25064,\n 13,\n 853,\n 85,\n 13,\n 33295,\n 7,\n 853,\n 8,\n 628,\n 220,\n 220,\n 220,\n 1303,\n 2191,\n 628,\n 220,\n 220,\n 220,\n 18568,\n 418,\n 62,\n 11250,\n 796,\n 2547,\n 325,\n 16934,\n 3419,\n 198,\n 220,\n 220,\n 220,\n 18568,\n 418,\n 62,\n 11250,\n 13,\n 29572,\n 62,\n 11250,\n 3419,\n 198,\n 220,\n 220,\n 220,\n 42848,\n 62,\n 3849,\n 2673,\n 796,\n 18568,\n 418,\n 62,\n 11250,\n 13,\n 296,\n 270,\n 62,\n 3849,\n 2673,\n 58,\n 15,\n 60,\n 628,\n 220,\n 220,\n 220,\n 1303,\n 2195,\n 861,\n 628,\n 220,\n 220,\n 220,\n 6818,\n 42848,\n 62,\n 3849,\n 2673,\n 13,\n 3849,\n 2673,\n 62,\n 4906,\n 6624,\n 366,\n 15511,\n 10051,\n 20803,\n 1,\n 198,\n 220,\n 220,\n 220,\n 6818,\n 42848,\n 62,\n 3849,\n 2673,\n 13,\n 411,\n 62,\n 3672,\n 6624,\n 14631,\n 1503,\n 38,\n 22047,\n 8973,\n 628,\n 198,\n 4299,\n 1332,\n 62,\n 11250,\n 3924,\n 62,\n 296,\n 270,\n 62,\n 48101,\n 62,\n 411,\n 312,\n 518,\n 62,\n 3849,\n 2673,\n 7,\n 22065,\n 15908,\n 2599,\n 198,\n 220,\n 220,\n 220,\n 37227,\n 14402,\n 8398,\n 329,\n 267,\n 16138,\n 3294,\n 35186,\n 10375,\n 37811,\n 628,\n 220,\n 220,\n 220,\n 1303,\n 943,\n 9521,\n 628,\n 220,\n 220,\n 220,\n 4566,\n 62,\n 7753,\n 796,\n 45218,\n 15908,\n 13,\n 28015,\n 15908,\n 7203,\n 7266,\n 11074,\n 22179,\n 7203,\n 11250,\n 13,\n 14116,\n 4943,\n 198,\n 220,\n 220,\n 220,\n 4566,\n 62,\n 7753,\n 13,\n 13564,\n 7,\n 198,\n 220,\n 220,\n 220,\n 220,\n 220,\n 220,\n 220,\n 37227,\n 198,\n 67,\n 8629,\n 62,\n 24396,\n 220,\n 220,\n 220,\n 6134,\n 220,\n 220,\n 220,\n 1303,\n 6134,\n 393,\n 410,\n 1437,\n 198,\n 67,\n 8629,\n 62,\n 10414,\n 220,\n 220,\n 220,\n 220,\n 220,\n 6134,\n 12,\n 11245,\n 13,\n 10414,\n 198,\n 198,\n 38610,\n 414,\n 62,\n 1073,\n 891,\n 220,\n 220,\n 256,\n 11227,\n 2069,\n 285,\n 535,\n 261,\n 77,\n 7493,\n 20342,\n 198,\n 198,\n 12853,\n 62,\n 5420,\n 220,\n 17643,\n 486,\n 25645,\n 8269,\n 2388,\n 486,\n 8269,\n 2388,\n 486,\n 8269,\n 2388,\n 486,\n 2388,\n 8298,\n 25645,\n 2388,\n 16,\n 25645,\n 8269,\n 2388,\n 8298,\n 486,\n 25645,\n 8298,\n 486,\n 8269,\n 8298,\n 2388,\n 3571,\n 486,\n 486,\n 486,\n 25645,\n 8269,\n 18005,\n 8269,\n 2388,\n 486,\n 486,\n 8269,\n 18005,\n 2388,\n 8298,\n 8269,\n 2388,\n 486,\n 25645,\n 8269,\n 8784,\n 49388,\n 486,\n 2388,\n 486,\n 25645,\n 8298,\n 486,\n 8269,\n 24598,\n 3571,\n 486,\n 486,\n 486,\n 2388,\n 8298,\n 25645,\n 2388,\n 16,\n 8269,\n 2388,\n 486,\n 486,\n 486,\n 8298,\n 2388,\n 8298,\n 2388,\n 8298,\n 8269,\n 2388,\n 486,\n 2388,\n 8298,\n 8269,\n 2388,\n 486,\n 8269,\n 8298,\n 2388,\n 486,\n 486,\n 486,\n 25645,\n 8298,\n 8269,\n 24598,\n 198,\n 198,\n 411,\n 312,\n 518,\n 62,\n 3672,\n 5923,\n 38,\n 18298,\n 10188,\n 52,\n 17657,\n 12509,\n 52,\n 19924,\n 406,\n 16309,\n 18294,\n 34658,\n 19442,\n 5923,\n 38,\n 8628,\n 5923,\n 38,\n 21526,\n 7579,\n 47,\n 22413,\n 18871,\n 23188,\n 314,\n 2538,\n 26115,\n 5923,\n 38,\n 22047,\n 35383,\n 24137,\n 10188,\n 52,\n 24909,\n 8355,\n 32,\n 22995,\n 33700,\n 27367,\n 10188,\n 52,\n 23195,\n 10188,\n 52,\n 27988,\n 5923,\n 38,\n 32759,\n 34658,\n 27696,\n 10188,\n 56,\n 30995,\n 5923,\n 38,\n 31020,\n 7579,\n 47,\n 26200,\n 24412,\n 49,\n 29416,\n 198,\n 411,\n 312,\n 518,\n 62,\n 17618,\n 2319,\n 6073,\n 7265,\n 7724,\n 8854,\n 8915,\n 8699,\n 8949,\n 15143,\n 20299,\n 22909,\n 22613,\n 6640,\n 27191,\n 29903,\n 1594,\n 939,\n 26881,\n 29217,\n 33797,\n 37576,\n 41423,\n 23460,\n 198,\n 198,\n 296,\n 270,\n 62,\n 3849,\n 2673,\n 220,\n 7409,\n 10051,\n 20803,\n 220,\n 5923,\n 38,\n 8628,\n 7579,\n 47,\n 22413,\n 5923,\n 38,\n 22047,\n 198,\n 198,\n 12853,\n 62,\n 448,\n 7753,\n 6134,\n 62,\n 12853,\n 62,\n 361,\n 79,\n 13,\n 40664,\n 198,\n 14323,\n 62,\n 448,\n 7753,\n 6134,\n 62,\n 38610,\n 414,\n 13,\n 40664,\n 198,\n 6404,\n 7753,\n 6134,\n 13,\n 6404,\n 198,\n 37811,\n 198,\n 220,\n 220,\n 220,\n 1267,\n 628,\n 220,\n 220,\n 220,\n 1822,\n 796,\n 28686,\n 13,\n 6978,\n 13,\n 22179,\n 7,\n 11250,\n 62,\n 7753,\n 13,\n 15908,\n 3672,\n 11,\n 4566,\n 62,\n 7753,\n 13,\n 12093,\n 12453,\n 8,\n 628,\n 220,\n 220,\n 220,\n 611,\n 18896,\n 7,\n 17597,\n 13,\n 853,\n 85,\n 8,\n 1875,\n 352,\n 25,\n 198,\n 220,\n 220,\n 220,\n 220,\n 220,\n 220,\n 220,\n 25064,\n 13,\n 853,\n 85,\n 58,\n 16,\n 60,\n 796,\n 1822,\n 198,\n 220,\n 220,\n 220,\n 2073,\n 25,\n 198,\n 220,\n 220,\n 220,\n 220,\n 220,\n 220,\n 220,\n 25064,\n 13,\n 853,\n 85,\n 13,\n 33295,\n 7,\n 853,\n 8,\n 628,\n 220,\n 220,\n 220,\n 1303,\n 2191,\n 628,\n 220,\n 220,\n 220,\n 18568,\n 418,\n 62,\n 11250,\n 796,\n 2547,\n 325,\n 16934,\n 3419,\n 198,\n 220,\n 220,\n 220,\n 18568,\n 418,\n 62,\n 11250,\n 13,\n 29572,\n 62,\n 11250,\n 3419,\n 198,\n 220,\n 220,\n 220,\n 42848,\n 62,\n 3849,\n 2673,\n 796,\n 18568,\n 418,\n 62,\n 11250,\n 13,\n 296,\n 270,\n 62,\n 3849,\n 2673,\n 58,\n 15,\n 60,\n 628,\n 220,\n 220,\n 220,\n 1303,\n 2195,\n 861,\n 628,\n 220,\n 220,\n 220,\n 6818,\n 42848,\n 62,\n 3849,\n 2673,\n 13,\n 3849,\n 2673,\n 62,\n 4906,\n 6624,\n 366,\n 15511,\n 10051,\n 20803,\n 1,\n 198,\n 220,\n 220,\n 220,\n 6818,\n 42848,\n 62,\n 3849,\n 2673,\n 13,\n 411,\n 62,\n 3672,\n 6624,\n 14631,\n 1503,\n 38,\n 8628,\n 1600,\n 366,\n 5446,\n 47,\n 22413,\n 1600,\n 366,\n 1503,\n 38,\n 22047,\n 8973,\n 628,\n 198,\n 4299,\n 1332,\n 62,\n 11250,\n 3924,\n 62,\n 296,\n 270,\n 62,\n 48101,\n 62,\n 3849,\n 2673,\n 62,\n 4906,\n 7,\n 22065,\n 15908,\n 2599,\n 198,\n 220,\n 220,\n 220,\n 37227,\n 14402,\n 8398,\n 329,\n 267,\n 16138,\n 3294,\n 10375,\n 2099,\n 37811,\n 628,\n 220,\n 220,\n 220,\n 1303,\n 943,\n 9521,\n 628,\n 220,\n 220,\n 220,\n 4566,\n 62,\n 7753,\n 796,\n 45218,\n 15908,\n 13,\n 28015,\n 15908,\n 7203,\n 7266,\n 11074,\n 22179,\n 7203,\n 11250,\n 13,\n 14116,\n 4943,\n 198,\n 220,\n 220,\n 220,\n 4566,\n 62,\n 7753,\n 13,\n 13564,\n 7,\n 198,\n 220,\n 220,\n 220,\n 220,\n 220,\n 220,\n 220,\n 37227,\n 198,\n 67,\n 8629,\n 62,\n 24396,\n 220,\n 220,\n 220,\n 6134,\n 220,\n 220,\n 220,\n 1303,\n 6134,\n 393,\n 410,\n 1437,\n 198,\n 67,\n 8629,\n 62,\n 10414,\n 220,\n 220,\n 220,\n 220,\n 220,\n 6134,\n 12,\n 11245,\n 13,\n 10414,\n 198,\n 198,\n 38610,\n 414,\n 62,\n 1073,\n 891,\n 220,\n 220,\n 256,\n 11227,\n 2069,\n 285,\n 535,\n 261,\n 77,\n 7493,\n 20342,\n 198,\n 198,\n 12853,\n 62,\n 5420,\n 220,\n 17643,\n 486,\n 25645,\n 8269,\n 2388,\n 486,\n 8269,\n 2388,\n 486,\n 8269,\n 2388,\n 486,\n 2388,\n 8298,\n 25645,\n 2388,\n 16,\n 25645,\n 8269,\n 2388,\n 8298,\n 486,\n 25645,\n 8298,\n 486,\n 8269,\n 8298,\n 2388,\n 3571,\n 486,\n 486,\n 486,\n 25645,\n 8269,\n 18005,\n 8269,\n 2388,\n 486,\n 486,\n 8269,\n 18005,\n 2388,\n 8298,\n 8269,\n 2388,\n 486,\n 25645,\n 8269,\n 8784,\n 49388,\n 486,\n 2388,\n 486,\n 25645,\n 8298,\n 486,\n 8269,\n 24598,\n 3571,\n 486,\n 486,\n 486,\n 2388,\n 8298,\n 25645,\n 2388,\n 16,\n 8269,\n 2388,\n 486,\n 486,\n 486,\n 8298,\n 2388,\n 8298,\n 2388,\n 8298,\n 8269,\n 2388,\n 486,\n 2388,\n 8298,\n 8269,\n 2388,\n 486,\n 8269,\n 8298,\n 2388,\n 486,\n 486,\n 486,\n 25645,\n 8298,\n 8269,\n 24598,\n 198,\n 198,\n 411,\n 312,\n 518,\n 62,\n 3672,\n 5923,\n 38,\n 18298,\n 10188,\n 52,\n 17657,\n 12509,\n 52,\n 19924,\n 406,\n 16309,\n 18294,\n 34658,\n 19442,\n 5923,\n 38,\n 8628,\n 5923,\n 38,\n 21526,\n 7579,\n 47,\n 22413,\n 18871,\n 23188,\n 314,\n 2538,\n 26115,\n 5923,\n 38,\n 22047,\n 35383,\n 24137,\n 10188,\n 52,\n 24909,\n 8355,\n 32,\n 22995,\n 33700,\n 27367,\n 10188,\n 52,\n 23195,\n 10188,\n 52,\n 27988,\n 5923,\n 38,\n 32759,\n 34658,\n 27696,\n 10188,\n 56,\n 30995,\n 5923,\n 38,\n 31020,\n 7579,\n 47,\n 26200,\n 24412,\n 49,\n 29416,\n 198,\n 411,\n 312,\n 518,\n 62,\n 17618,\n 2319,\n 6073,\n 7265,\n 7724,\n 8854,\n 8915,\n 8699,\n 8949,\n 15143,\n 20299,\n 22909,\n 22613,\n 6640,\n 27191,\n 29903,\n 1594,\n 939,\n 26881,\n 29217,\n 33797,\n 37576,\n 41423,\n 23460,\n 198,\n 198,\n 296,\n 270,\n 62,\n 3849,\n 2673,\n 220,\n 7409,\n 10051,\n 20803,\n 220,\n 5923,\n 38,\n 22047,\n 198,\n 296,\n 270,\n 62,\n 3849,\n 2673,\n 220,\n 289,\n 62,\n 65,\n 623,\n 220,\n 5923,\n 38,\n 32759,\n 198,\n 198,\n 12853,\n 62,\n 448,\n 7753,\n 6134,\n 62,\n 12853,\n 62,\n 361,\n 79,\n 13,\n 40664,\n 198,\n 14323,\n 62,\n 448,\n 7753,\n 6134,\n 62,\n 38610,\n 414,\n 13,\n 40664,\n 198,\n 6404,\n 7753,\n 6134,\n 13,\n 6404,\n 198,\n 37811,\n 198,\n 220,\n 220,\n 220,\n 1267,\n 628,\n 220,\n 220,\n 220,\n 1822,\n 796,\n 28686,\n 13,\n 6978,\n 13,\n 22179,\n 7,\n 11250,\n 62,\n 7753,\n 13,\n 15908,\n 3672,\n 11,\n 4566,\n 62,\n 7753,\n 13,\n 12093,\n 12453,\n 8,\n 628,\n 220,\n 220,\n 220,\n 611,\n 18896,\n 7,\n 17597,\n 13,\n 853,\n 85,\n 8,\n 1875,\n 352,\n 25,\n 198,\n 220,\n 220,\n 220,\n 220,\n 220,\n 220,\n 220,\n 25064,\n 13,\n 853,\n 85,\n 58,\n 16,\n 60,\n 796,\n 1822,\n 198,\n 220,\n 220,\n 220,\n 2073,\n 25,\n 198,\n 220,\n 220,\n 220,\n 220,\n 220,\n 220,\n 220,\n 25064,\n 13,\n 853,\n 85,\n 13,\n 33295,\n 7,\n 853,\n 8,\n 628,\n 220,\n 220,\n 220,\n 1303,\n 2191,\n 628,\n 220,\n 220,\n 220,\n 18568,\n 418,\n 62,\n 11250,\n 796,\n 2547,\n 325,\n 16934,\n 3419,\n 198,\n 220,\n 220,\n 220,\n 18568,\n 418,\n 62,\n 11250,\n 13,\n 29572,\n 62,\n 11250,\n 3419,\n 198,\n 220,\n 220,\n 220,\n 42848,\n 62,\n 3849,\n 2673,\n 62,\n 16,\n 796,\n 18568,\n 418,\n 62,\n 11250,\n 13,\n 296,\n 270,\n 62,\n 3849,\n 2673,\n 58,\n 15,\n 60,\n 198,\n 220,\n 220,\n 220,\n 42848,\n 62,\n 3849,\n 2673,\n 62,\n 17,\n 796,\n 18568,\n 418,\n 62,\n 11250,\n 13,\n 296,\n 270,\n 62,\n 3849,\n 2673,\n 58,\n 16,\n 60,\n 628,\n 220,\n 220,\n 220,\n 1303,\n 2195,\n 861,\n 628,\n 220,\n 220,\n 220,\n 6818,\n 42848,\n 62,\n 3849,\n 2673,\n 62,\n 16,\n 13,\n 3849,\n 2673,\n 62,\n 4906,\n 6624,\n 366,\n 15511,\n 10051,\n 20803,\n 1,\n 198,\n 220,\n 220,\n 220,\n 6818,\n 42848,\n 62,\n 3849,\n 2673,\n 62,\n 16,\n 13,\n 411,\n 62,\n 3672,\n 6624,\n 14631,\n 1503,\n 38,\n 22047,\n 8973,\n 628,\n 220,\n 220,\n 220,\n 6818,\n 42848,\n 62,\n 3849,\n 2673,\n 62,\n 17,\n 13,\n 3849,\n 2673,\n 62,\n 4906,\n 6624,\n 366,\n 71,\n 62,\n 65,\n 623,\n 1,\n 198,\n 220,\n 220,\n 220,\n 6818,\n 42848,\n 62,\n 3849,\n 2673,\n 62,\n 17,\n 13,\n 411,\n 62,\n 3672,\n 6624,\n 14631,\n 1503,\n 38,\n 32759,\n 8973,\n 628,\n 198,\n 4299,\n 1332,\n 62,\n 11250,\n 3924,\n 62,\n 6511,\n 62,\n 3849,\n 2673,\n 62,\n 4906,\n 7,\n 22065,\n 15908,\n 2599,\n 198,\n 220,\n 220,\n 220,\n 37227,\n 14402,\n 8398,\n 10627,\n 477,\n 890,\n 10375,\n 62,\n 4906,\n 37811,\n 628,\n 220,\n 220,\n 220,\n 1303,\n 943,\n 9521,\n 628,\n 220,\n 220,\n 220,\n 4566,\n 62,\n 7753,\n 796,\n 45218,\n 15908,\n 13,\n 28015,\n 15908,\n 7203,\n 7266,\n 11074,\n 22179,\n 7203,\n 11250,\n 13,\n 14116,\n 4943,\n 198,\n 220,\n 220,\n 220,\n 4566,\n 62,\n 7753,\n 13,\n 13564,\n 7,\n 198,\n 220,\n 220,\n 220,\n 220,\n 220,\n 220,\n 220,\n 37227,\n 198,\n 67,\n 8629,\n 62,\n 24396,\n 220,\n 220,\n 220,\n 6134,\n 220,\n 220,\n 220,\n 1303,\n 6134,\n 393,\n 410,\n 1437,\n 198,\n 67,\n 8629,\n 62,\n 10414,\n 220,\n 220,\n 220,\n 220,\n 220,\n 6134,\n 12,\n 11245,\n 13,\n 10414,\n 198,\n 198,\n 38610,\n 414,\n 62,\n 1073,\n 891,\n 220,\n 220,\n 256,\n 11227,\n 2069,\n 285,\n 535,\n 261,\n 77,\n 7493,\n 20342,\n 198,\n 198,\n 12853,\n 62,\n 5420,\n 220,\n 17643,\n 486,\n 25645,\n 8269,\n 2388,\n 486,\n 8269,\n 2388,\n 486,\n 8269,\n 2388,\n 486,\n 2388,\n 8298,\n 25645,\n 2388,\n 16,\n 25645,\n 8269,\n 2388,\n 8298,\n 486,\n 25645,\n 8298,\n 486,\n 8269,\n 8298,\n 2388,\n 3571,\n 486,\n 486,\n 486,\n 25645,\n 8269,\n 18005,\n 8269,\n 2388,\n 486,\n 486,\n 8269,\n 18005,\n 2388,\n 8298,\n 8269,\n 2388,\n 486,\n 25645,\n 8269,\n 8784,\n 49388,\n 486,\n 2388,\n 486,\n 25645,\n 8298,\n 486,\n 8269,\n 24598,\n 3571,\n 486,\n 486,\n 486,\n 2388,\n 8298,\n 25645,\n 2388,\n 16,\n 8269,\n 2388,\n 486,\n 486,\n 486,\n 8298,\n 2388,\n 8298,\n 2388,\n 8298,\n 8269,\n 2388,\n 486,\n 2388,\n 8298,\n 8269,\n 2388,\n 486,\n 8269,\n 8298,\n 2388,\n 486,\n 486,\n 486,\n 25645,\n 8298,\n 8269,\n 24598,\n 198,\n 198,\n 411,\n 312,\n 518,\n 62,\n 3672,\n 5923,\n 38,\n 18298,\n 10188,\n 52,\n 17657,\n 12509,\n 52,\n 19924,\n 406,\n 16309,\n 18294,\n 34658,\n 19442,\n 5923,\n 38,\n 8628,\n 5923,\n 38,\n 21526,\n 7579,\n 47,\n 22413,\n 18871,\n 23188,\n 314,\n 2538,\n 26115,\n 5923,\n 38,\n 22047,\n 35383,\n 24137,\n 10188,\n 52,\n 24909,\n 8355,\n 32,\n 22995,\n 33700,\n 27367,\n 10188,\n 52,\n 23195,\n 10188,\n 52,\n 27988,\n 5923,\n 38,\n 32759,\n 34658,\n 27696,\n 10188,\n 56,\n 30995,\n 5923,\n 38,\n 31020,\n 7579,\n 47,\n 26200,\n 24412,\n 49,\n 29416,\n 198,\n 411,\n 312,\n 518,\n 62,\n 17618,\n 2319,\n 6073,\n 7265,\n 7724,\n 8854,\n 8915,\n 8699,\n 8949,\n 15143,\n 20299,\n 22909,\n 22613,\n 6640,\n 27191,\n 29903,\n 1594,\n 939,\n 26881,\n 29217,\n 33797,\n 37576,\n 41423,\n 23460,\n 198,\n 198,\n 296,\n 270,\n 62,\n 3849,\n 2673,\n 220,\n 7409,\n 10051,\n 20803,\n 220,\n 5923,\n 38,\n 18298,\n 198,\n 296,\n 270,\n 62,\n 3849,\n 2673,\n 220,\n 48440,\n 220,\n 10188,\n 52,\n 17657,\n 198,\n 296,\n 270,\n 62,\n 3849,\n 2673,\n 220,\n 289,\n 62,\n 65,\n 623,\n 220,\n 220,\n 12509,\n 52,\n 19924,\n 198,\n 296,\n 270,\n 62,\n 3849,\n 2673,\n 220,\n 15206,\n 12708,\n 220,\n 406,\n 16309,\n 18294,\n 198,\n 296,\n 270,\n 62,\n 3849,\n 2673,\n 220,\n 289,\n 62,\n 65,\n 623,\n 62,\n 9099,\n 273,\n 220,\n 34658,\n 19442,\n 198,\n 296,\n 270,\n 62,\n 3849,\n 2673,\n 220,\n 289,\n 62,\n 65,\n 623,\n 62,\n 13635,\n 273,\n 220,\n 5923,\n 38,\n 8628,\n 198,\n 296,\n 270,\n 62,\n 3849,\n 2673,\n 220,\n 15206,\n 12708,\n 62,\n 24561,\n 220,\n 5923,\n 38,\n 21526,\n 198,\n 296,\n 270,\n 62,\n 3849,\n 2673,\n 220,\n 15206,\n 12708,\n 62,\n 31591,\n 220,\n 7579,\n 47,\n 22413,\n 198,\n 296,\n 270,\n 62,\n 3849,\n 2673,\n 220,\n 48440,\n 62,\n 69,\n 23253,\n 1659,\n 558,\n 220,\n 18871,\n 23188,\n 198,\n 296,\n 270,\n 62,\n 3849,\n 2673,\n 220,\n 48440,\n 62,\n 276,\n 1136,\n 1659,\n 558,\n 220,\n 314,\n 2538,\n 26115,\n 198,\n 198,\n 12853,\n 62,\n 448,\n 7753,\n 6134,\n 62,\n 12853,\n 62,\n 361,\n 79,\n 13,\n 40664,\n 198,\n 14323,\n 62,\n 448,\n 7753,\n 6134,\n 62,\n 38610,\n 414,\n 13,\n 40664,\n 198,\n 6404,\n 7753,\n 6134,\n 13,\n 6404,\n 198,\n 37811,\n 198,\n 220,\n 220,\n 220,\n 1267,\n 628,\n 220,\n 220,\n 220,\n 1822,\n 796,\n 28686,\n 13,\n 6978,\n 13,\n 22179,\n 7,\n 11250,\n 62,\n 7753,\n 13,\n 15908,\n 3672,\n 11,\n 4566,\n 62,\n 7753,\n 13,\n 12093,\n 12453,\n 8,\n 628,\n 220,\n 220,\n 220,\n 611,\n 18896,\n 7,\n 17597,\n 13,\n 853,\n 85,\n 8,\n 1875,\n 352,\n 25,\n 198,\n 220,\n 220,\n 220,\n 220,\n 220,\n 220,\n 220,\n 25064,\n 13,\n 853,\n 85,\n 58,\n 16,\n 60,\n 796,\n 1822,\n 198,\n 220,\n 220,\n 220,\n 2073,\n 25,\n 198,\n 220,\n 220,\n 220,\n 220,\n 220,\n 220,\n 220,\n 25064,\n 13,\n 853,\n 85,\n 13,\n 33295,\n 7,\n 853,\n 8,\n 628,\n 220,\n 220,\n 220,\n 1303,\n 2191,\n 628,\n 220,\n 220,\n 220,\n 18568,\n 418,\n 62,\n 11250,\n 796,\n 2547,\n 325,\n 16934,\n 3419,\n 198,\n 220,\n 220,\n 220,\n 18568,\n 418,\n 62,\n 11250,\n 13,\n 29572,\n 62,\n 11250,\n 3419,\n 198,\n 220,\n 220,\n 220,\n 42848,\n 62,\n 3849,\n 2673,\n 62,\n 16,\n 796,\n 18568,\n 418,\n 62,\n 11250,\n 13,\n 296,\n 270,\n 62,\n 3849,\n 2673,\n 58,\n 15,\n 60,\n 198,\n 220,\n 220,\n 220,\n 42848,\n 62,\n 3849,\n 2673,\n 62,\n 17,\n 796,\n 18568,\n 418,\n 62,\n 11250,\n 13,\n 296,\n 270,\n 62,\n 3849,\n 2673,\n 58,\n 16,\n 60,\n 198,\n 220,\n 220,\n 220,\n 42848,\n 62,\n 3849,\n 2673,\n 62,\n 18,\n 796,\n 18568,\n 418,\n 62,\n 11250,\n 13,\n 296,\n 270,\n 62,\n 3849,\n 2673,\n 58,\n 17,\n 60,\n 198,\n 220,\n 220,\n 220,\n 42848,\n 62,\n 3849,\n 2673,\n 62,\n 19,\n 796,\n 18568,\n 418,\n 62,\n 11250,\n 13,\n 296,\n 270,\n 62,\n 3849,\n 2673,\n 58,\n 18,\n 60,\n 198,\n 220,\n 220,\n 220,\n 42848,\n 62,\n 3849,\n 2673,\n 62,\n 20,\n 796,\n 18568,\n 418,\n 62,\n 11250,\n 13,\n 296,\n 270,\n 62,\n 3849,\n 2673,\n 58,\n 19,\n 60,\n 198,\n 220,\n 220,\n 220,\n 42848,\n 62,\n 3849,\n 2673,\n 62,\n 21,\n 796,\n 18568,\n 418,\n 62,\n 11250,\n 13,\n 296,\n 270,\n 62,\n 3849,\n 2673,\n 58,\n 20,\n 60,\n 198,\n 220,\n 220,\n 220,\n 42848,\n 62,\n 3849,\n 2673,\n 62,\n 22,\n 796,\n 18568,\n 418,\n 62,\n 11250,\n 13,\n 296,\n 270,\n 62,\n 3849,\n 2673,\n 58,\n 21,\n 60,\n 198,\n 220,\n 220,\n 220,\n 42848,\n 62,\n 3849,\n 2673,\n 62,\n 23,\n 796,\n 18568,\n 418,\n 62,\n 11250,\n 13,\n 296,\n 270,\n 62,\n 3849,\n 2673,\n 58,\n 22,\n 60,\n 198,\n 220,\n 220,\n 220,\n 42848,\n 62,\n 3849,\n 2673,\n 62,\n 24,\n 796,\n 18568,\n 418,\n 62,\n 11250,\n 13,\n 296,\n 270,\n 62,\n 3849,\n 2673,\n 58,\n 23,\n 60,\n 198,\n 220,\n 220,\n 220,\n 42848,\n 62,\n 3849,\n 2673,\n 62,\n 940,\n 796,\n 18568,\n 418,\n 62,\n 11250,\n 13,\n 296,\n 270,\n 62,\n 3849,\n 2673,\n 58,\n 24,\n 60,\n 628,\n 220,\n 220,\n 220,\n 1303,\n 2195,\n 861,\n 628,\n 220,\n 220,\n 220,\n 6818,\n 42848,\n 62,\n 3849,\n 2673,\n 62,\n 16,\n 13,\n 3849,\n 2673,\n 62,\n 4906,\n 6624,\n 366,\n 15511,\n 10051,\n 20803,\n 1,\n 198,\n 220,\n 220,\n 220,\n 6818,\n 42848,\n 62,\n 3849,\n 2673,\n 62,\n 16,\n 13,\n 411,\n 62,\n 3672,\n 6624,\n 14631,\n 1503,\n 38,\n 18298,\n 8973,\n 198,\n 220,\n 220,\n 220,\n 6818,\n 42848,\n 62,\n 3849,\n 2673,\n 62,\n 17,\n 13,\n 3849,\n 2673,\n 62,\n 4906,\n 6624,\n 366,\n 283,\n 13730,\n 1,\n 198,\n 220,\n 220,\n 220,\n 6818,\n 42848,\n 62,\n 3849,\n 2673,\n 62,\n 17,\n 13,\n 411,\n 62,\n 3672,\n 6624,\n 14631,\n 8763,\n 52,\n 17657,\n 8973,\n 198,\n 220,\n 220,\n 220,\n 6818,\n 42848,\n 62,\n 3849,\n 2673,\n 62,\n 18,\n 13,\n 3849,\n 2673,\n 62,\n 4906,\n 6624,\n 366,\n 71,\n 62,\n 65,\n 623,\n 1,\n 198,\n 220,\n 220,\n 220,\n 6818,\n 42848,\n 62,\n 3849,\n 2673,\n 62,\n 18,\n 13,\n 411,\n 62,\n 3672,\n 6624,\n 14631,\n 2538,\n 52,\n 19924,\n 8973,\n 198,\n 220,\n 220,\n 220,\n 6818,\n 42848,\n 62,\n 3849,\n 2673,\n 62,\n 19,\n 13,\n 3849,\n 2673,\n 62,\n 4906,\n 6624,\n 366,\n 9509,\n 305,\n 12708,\n 1,\n 198,\n 220,\n 220,\n 220,\n 6818,\n 42848,\n 62,\n 3849,\n 2673,\n 62,\n 19,\n 13,\n 411,\n 62,\n 3672,\n 6624,\n 14631,\n 11319,\n 50,\n 18294,\n 8973,\n 198,\n 220,\n 220,\n 220,\n 6818,\n 42848,\n 62,\n 3849,\n 2673,\n 62,\n 20,\n 13,\n 3849,\n 2673,\n 62,\n 4906,\n 6624,\n 366,\n 71,\n 62,\n 65,\n 623,\n 62,\n 9099,\n 273,\n 1,\n 198,\n 220,\n 220,\n 220,\n 6818,\n 42848,\n 62,\n 3849,\n 2673,\n 62,\n 20,\n 13,\n 411,\n 62,\n 3672,\n 6624,\n 14631,\n 1921,\n 47,\n 19442,\n 8973,\n 198,\n 220,\n 220,\n 220,\n 6818,\n 42848,\n 62,\n 3849,\n 2673,\n 62,\n 21,\n 13,\n 3849,\n 2673,\n 62,\n 4906,\n 6624,\n 366,\n 71,\n 62,\n 65,\n 623,\n 62,\n 13635,\n 273,\n 1,\n 198,\n 220,\n 220,\n 220,\n 6818,\n 42848,\n 62,\n 3849,\n 2673,\n 62,\n 21,\n 13,\n 411,\n 62,\n 3672,\n 6624,\n 14631,\n 1503,\n 38,\n 8628,\n 8973,\n 198,\n 220,\n 220,\n 220,\n 6818,\n 42848,\n 62,\n 3849,\n 2673,\n 62,\n 22,\n 13,\n 3849,\n 2673,\n 62,\n 4906,\n 6624,\n 366,\n 9509,\n 305,\n 12708,\n 62,\n 24561,\n 1,\n 198,\n 220,\n 220,\n 220,\n 6818,\n 42848,\n 62,\n 3849,\n 2673,\n 62,\n 22,\n 13,\n 411,\n 62,\n 3672,\n 6624,\n 14631,\n 1503,\n 38,\n 21526,\n 8973,\n 198,\n 220,\n 220,\n 220,\n 6818,\n 42848,\n 62,\n 3849,\n 2673,\n 62,\n 23,\n 13,\n 3849,\n 2673,\n 62,\n 4906,\n 6624,\n 366,\n 9509,\n 305,\n 12708,\n 62,\n 31591,\n 1,\n 198,\n 220,\n 220,\n 220,\n 6818,\n 42848,\n 62,\n 3849,\n 2673,\n 62,\n 23,\n 13,\n 411,\n 62,\n 3672,\n 6624,\n 14631,\n 5446,\n 47,\n 22413,\n 8973,\n 198,\n 220,\n 220,\n 220,\n 6818,\n 42848,\n 62,\n 3849,\n 2673,\n 62,\n 24,\n 13,\n 3849,\n 2673,\n 62,\n 4906,\n 6624,\n 366,\n 283,\n 13730,\n 62,\n 69,\n 23253,\n 1659,\n 558,\n 1,\n 198,\n 220,\n 220,\n 220,\n 6818,\n 42848,\n 62,\n 3849,\n 2673,\n 62,\n 24,\n 13,\n 411,\n 62,\n 3672,\n 6624,\n 14631,\n 35009,\n 23188,\n 8973,\n 198,\n 220,\n 220,\n 220,\n 6818,\n 42848,\n 62,\n 3849,\n 2673,\n 62,\n 940,\n 13,\n 3849,\n 2673,\n 62,\n 4906,\n 6624,\n 366,\n 283,\n 13730,\n 62,\n 276,\n 1136,\n 1659,\n 558,\n 1,\n 198,\n 220,\n 220,\n 220,\n 6818,\n 42848,\n 62,\n 3849,\n 2673,\n 62,\n 940,\n 13,\n 411,\n 62,\n 3672,\n 6624,\n 14631,\n 41119,\n 26115,\n 8973,\n 628,\n 198,\n 4299,\n 1332,\n 62,\n 11250,\n 3924,\n 62,\n 19509,\n 62,\n 3849,\n 2673,\n 62,\n 4906,\n 7,\n 22065,\n 15908,\n 2599,\n 198,\n 220,\n 220,\n 220,\n 37227,\n 14402,\n 8398,\n 10627,\n 477,\n 1790,\n 10375,\n 62,\n 4906,\n 37811,\n 628,\n 220,\n 220,\n 220,\n 1303,\n 943,\n 9521,\n 628,\n 220,\n 220,\n 220,\n 4566,\n 62,\n 7753,\n 796,\n 45218,\n 15908,\n 13,\n 28015,\n 15908,\n 7203,\n 7266,\n 11074,\n 22179,\n 7203,\n 11250,\n 13,\n 14116,\n 4943,\n 198,\n 220,\n 220,\n 220,\n 4566,\n 62,\n 7753,\n 13,\n 13564,\n 7,\n 198,\n 220,\n 220,\n 220,\n 220,\n 220,\n 220,\n 220,\n 37227,\n 198,\n 67,\n 8629,\n 62,\n 24396,\n 220,\n 220,\n 220,\n 6134,\n 220,\n 220,\n 220,\n 1303,\n 6134,\n 393,\n 410,\n 1437,\n 198,\n 67,\n 8629,\n 62,\n 10414,\n 220,\n 220,\n 220,\n 220,\n 220,\n 6134,\n 12,\n 11245,\n 13,\n 10414,\n 198,\n 198,\n 38610,\n 414,\n 62,\n 1073,\n 891,\n 220,\n 220,\n 256,\n 11227,\n 2069,\n 285,\n 535,\n 261,\n 77,\n 7493,\n 20342,\n 198,\n 198,\n 12853,\n 62,\n 5420,\n 220,\n 17643,\n 486,\n 25645,\n 8269,\n 2388,\n 486,\n 8269,\n 2388,\n 486,\n 8269,\n 2388,\n 486,\n 2388,\n 8298,\n 25645,\n 2388,\n 16,\n 25645,\n 8269,\n 2388,\n 8298,\n 486,\n 25645,\n 8298,\n 486,\n 8269,\n 8298,\n 2388,\n 3571,\n 486,\n 486,\n 486,\n 25645,\n 8269,\n 18005,\n 8269,\n 2388,\n 486,\n 486,\n 8269,\n 18005,\n 2388,\n 8298,\n 8269,\n 2388,\n 486,\n 25645,\n 8269,\n 8784,\n 49388,\n 486,\n 2388,\n 486,\n 25645,\n 8298,\n 486,\n 8269,\n 24598,\n 3571,\n 486,\n 486,\n 486,\n 2388,\n 8298,\n 25645,\n 2388,\n 16,\n 8269,\n 2388,\n 486,\n 486,\n 486,\n 8298,\n 2388,\n 8298,\n 2388,\n 8298,\n 8269,\n 2388,\n 486,\n 2388,\n 8298,\n 8269,\n 2388,\n 486,\n 8269,\n 8298,\n 2388,\n 486,\n 486,\n 486,\n 25645,\n 8298,\n 8269,\n 24598,\n 198,\n 198,\n 411,\n 312,\n 518,\n 62,\n 3672,\n 5923,\n 38,\n 18298,\n 10188,\n 52,\n 17657,\n 12509,\n 52,\n 19924,\n 406,\n 16309,\n 18294,\n 34658,\n 19442,\n 5923,\n 38,\n 8628,\n 5923,\n 38,\n 21526,\n 7579,\n 47,\n 22413,\n 18871,\n 23188,\n 314,\n 2538,\n 26115,\n 5923,\n 38,\n 22047,\n 35383,\n 24137,\n 10188,\n 52,\n 24909,\n 8355,\n 32,\n 22995,\n 33700,\n 27367,\n 10188,\n 52,\n 23195,\n 10188,\n 52,\n 27988,\n 5923,\n 38,\n 32759,\n 34658,\n 27696,\n 10188,\n 56,\n 30995,\n 5923,\n 38,\n 31020,\n 7579,\n 47,\n 26200,\n 24412,\n 49,\n 29416,\n 198,\n 411,\n 312,\n 518,\n 62,\n 17618,\n 2319,\n 6073,\n 7265,\n 7724,\n 8854,\n 8915,\n 8699,\n 8949,\n 15143,\n 20299,\n 22909,\n 22613,\n 6640,\n 27191,\n 29903,\n 1594,\n 939,\n 26881,\n 29217,\n 33797,\n 37576,\n 41423,\n 23460,\n 198,\n 198,\n 296,\n 270,\n 62,\n 3849,\n 2673,\n 220,\n 6574,\n 33,\n 220,\n 5923,\n 38,\n 18298,\n 198,\n 296,\n 270,\n 62,\n 3849,\n 2673,\n 220,\n 20359,\n 220,\n 10188,\n 52,\n 17657,\n 198,\n 296,\n 270,\n 62,\n 3849,\n 2673,\n 220,\n 367,\n 14529,\n 220,\n 220,\n 12509,\n 52,\n 19924,\n 198,\n 296,\n 270,\n 62,\n 3849,\n 2673,\n 220,\n 40342,\n 220,\n 406,\n 16309,\n 18294,\n 198,\n 296,\n 270,\n 62,\n 3849,\n 2673,\n 220,\n 367,\n 14529,\n 62,\n 41173,\n 220,\n 34658,\n 19442,\n 198,\n 296,\n 270,\n 62,\n 3849,\n 2673,\n 220,\n 367,\n 14529,\n 62,\n 26861,\n 220,\n 5923,\n 38,\n 8628,\n 198,\n 296,\n 270,\n 62,\n 3849,\n 2673,\n 220,\n 40342,\n 62,\n 37997,\n 220,\n 5923,\n 38,\n 21526,\n 198,\n 296,\n 270,\n 62,\n 3849,\n 2673,\n 220,\n 40342,\n 62,\n 45,\n 7156,\n 220,\n 7579,\n 47,\n 22413,\n 198,\n 296,\n 270,\n 62,\n 3849,\n 2673,\n 220,\n 20359,\n 62,\n 37,\n 17,\n 37,\n 220,\n 18871,\n 23188,\n 198,\n 296,\n 270,\n 62,\n 3849,\n 2673,\n 220,\n 20359,\n 62,\n 36,\n 17,\n 37,\n 220,\n 314,\n 2538,\n 26115,\n 198,\n 198,\n 12853,\n 62,\n 448,\n 7753,\n 6134,\n 62,\n 12853,\n 62,\n 361,\n 79,\n 13,\n 40664,\n 198,\n 14323,\n 62,\n 448,\n 7753,\n 6134,\n 62,\n 38610,\n 414,\n 13,\n 40664,\n 198,\n 6404,\n 7753,\n 6134,\n 13,\n 6404,\n 198,\n 37811,\n 198,\n 220,\n 220,\n 220,\n 1267,\n 628,\n 220,\n 220,\n 220,\n 1822,\n 796,\n 28686,\n 13,\n 6978,\n 13,\n 22179,\n 7,\n 11250,\n 62,\n 7753,\n 13,\n 15908,\n 3672,\n 11,\n 4566,\n 62,\n 7753,\n 13,\n 12093,\n 12453,\n 8,\n 628,\n 220,\n 220,\n 220,\n 611,\n 18896,\n 7,\n 17597,\n 13,\n 853,\n 85,\n 8,\n 1875,\n 352,\n 25,\n 198,\n 220,\n 220,\n 220,\n 220,\n 220,\n 220,\n 220,\n 25064,\n 13,\n 853,\n 85,\n 58,\n 16,\n 60,\n 796,\n 1822,\n 198,\n 220,\n 220,\n 220,\n 2073,\n 25,\n 198,\n 220,\n 220,\n 220,\n 220,\n 220,\n 220,\n 220,\n 25064,\n 13,\n 853,\n 85,\n 13,\n 33295,\n 7,\n 853,\n 8,\n 628,\n 220,\n 220,\n 220,\n 1303,\n 2191,\n 628,\n 220,\n 220,\n 220,\n 18568,\n 418,\n 62,\n 11250,\n 796,\n 2547,\n 325,\n 16934,\n 3419,\n 198,\n 220,\n 220,\n 220,\n 18568,\n 418,\n 62,\n 11250,\n 13,\n 29572,\n 62,\n 11250,\n 3419,\n 198,\n 220,\n 220,\n 220,\n 42848,\n 62,\n 3849,\n 2673,\n 62,\n 16,\n 796,\n 18568,\n 418,\n 62,\n 11250,\n 13,\n 296,\n 270,\n 62,\n 3849,\n 2673,\n 58,\n 15,\n 60,\n 198,\n 220,\n 220,\n 220,\n 42848,\n 62,\n 3849,\n 2673,\n 62,\n 17,\n 796,\n 18568,\n 418,\n 62,\n 11250,\n 13,\n 296,\n 270,\n 62,\n 3849,\n 2673,\n 58,\n 16,\n 60,\n 198,\n 220,\n 220,\n 220,\n 42848,\n 62,\n 3849,\n 2673,\n 62,\n 18,\n 796,\n 18568,\n 418,\n 62,\n 11250,\n 13,\n 296,\n 270,\n 62,\n 3849,\n 2673,\n 58,\n 17,\n 60,\n 198,\n 220,\n 220,\n 220,\n 42848,\n 62,\n 3849,\n 2673,\n 62,\n 19,\n 796,\n 18568,\n 418,\n 62,\n 11250,\n 13,\n 296,\n 270,\n 62,\n 3849,\n 2673,\n 58,\n 18,\n 60,\n 198,\n 220,\n 220,\n 220,\n 42848,\n 62,\n 3849,\n 2673,\n 62,\n 20,\n 796,\n 18568,\n 418,\n 62,\n 11250,\n 13,\n 296,\n 270,\n 62,\n 3849,\n 2673,\n 58,\n 19,\n 60,\n 198,\n 220,\n 220,\n 220,\n 42848,\n 62,\n 3849,\n 2673,\n 62,\n 21,\n 796,\n 18568,\n 418,\n 62,\n 11250,\n 13,\n 296,\n 270,\n 62,\n 3849,\n 2673,\n 58,\n 20,\n 60,\n 198,\n 220,\n 220,\n 220,\n 42848,\n 62,\n 3849,\n 2673,\n 62,\n 22,\n 796,\n 18568,\n 418,\n 62,\n 11250,\n 13,\n 296,\n 270,\n 62,\n 3849,\n 2673,\n 58,\n 21,\n 60,\n 198,\n 220,\n 220,\n 220,\n 42848,\n 62,\n 3849,\n 2673,\n 62,\n 23,\n 796,\n 18568,\n 418,\n 62,\n 11250,\n 13,\n 296,\n 270,\n 62,\n 3849,\n 2673,\n 58,\n 22,\n 60,\n 198,\n 220,\n 220,\n 220,\n 42848,\n 62,\n 3849,\n 2673,\n 62,\n 24,\n 796,\n 18568,\n 418,\n 62,\n 11250,\n 13,\n 296,\n 270,\n 62,\n 3849,\n 2673,\n 58,\n 23,\n 60,\n 198,\n 220,\n 220,\n 220,\n 42848,\n 62,\n 3849,\n 2673,\n 62,\n 940,\n 796,\n 18568,\n 418,\n 62,\n 11250,\n 13,\n 296,\n 270,\n 62,\n 3849,\n 2673,\n 58,\n 24,\n 60,\n 628,\n 220,\n 220,\n 220,\n 1303,\n 2195,\n 861,\n 628,\n 220,\n 220,\n 220,\n 6818,\n 42848,\n 62,\n 3849,\n 2673,\n 62,\n 16,\n 13,\n 3849,\n 2673,\n 62,\n 4906,\n 6624,\n 366,\n 15511,\n 10051,\n 20803,\n 1,\n 198,\n 220,\n 220,\n 220,\n 6818,\n 42848,\n 62,\n 3849,\n 2673,\n 62,\n 16,\n 13,\n 411,\n 62,\n 3672,\n 6624,\n 14631,\n 1503,\n 38,\n 18298,\n 8973,\n 198,\n 220,\n 220,\n 220,\n 6818,\n 42848,\n 62,\n 3849,\n 2673,\n 62,\n 17,\n 13,\n 3849,\n 2673,\n 62,\n 4906,\n 6624,\n 366,\n 283,\n 13730,\n 1,\n 198,\n 220,\n 220,\n 220,\n 6818,\n 42848,\n 62,\n 3849,\n 2673,\n 62,\n 17,\n 13,\n 411,\n 62,\n 3672,\n 6624,\n 14631,\n 8763,\n 52,\n 17657,\n 8973,\n 198,\n 220,\n 220,\n 220,\n 6818,\n 42848,\n 62,\n 3849,\n 2673,\n 62,\n 18,\n 13,\n 3849,\n 2673,\n 62,\n 4906,\n 6624,\n 366,\n 71,\n 62,\n 65,\n 623,\n 1,\n 198,\n 220,\n 220,\n 220,\n 6818,\n 42848,\n 62,\n 3849,\n 2673,\n 62,\n 18,\n 13,\n 411,\n 62,\n 3672,\n 6624,\n 14631,\n 2538,\n 52,\n 19924,\n 8973,\n 198,\n 220,\n 220,\n 220,\n 6818,\n 42848,\n 62,\n 3849,\n 2673,\n 62,\n 19,\n 13,\n 3849,\n 2673,\n 62,\n 4906,\n 6624,\n 366,\n 9509,\n 305,\n 12708,\n 1,\n 198,\n 220,\n 220,\n 220,\n 6818,\n 42848,\n 62,\n 3849,\n 2673,\n 62,\n 19,\n 13,\n 411,\n 62,\n 3672,\n 6624,\n 14631,\n 11319,\n 50,\n 18294,\n 8973,\n 198,\n 220,\n 220,\n 220,\n 6818,\n 42848,\n 62,\n 3849,\n 2673,\n 62,\n 20,\n 13,\n 3849,\n 2673,\n 62,\n 4906,\n 6624,\n 366,\n 71,\n 62,\n 65,\n 623,\n 62,\n 9099,\n 273,\n 1,\n 198,\n 220,\n 220,\n 220,\n 6818,\n 42848,\n 62,\n 3849,\n 2673,\n 62,\n 20,\n 13,\n 411,\n 62,\n 3672,\n 6624,\n 14631,\n 1921,\n 47,\n 19442,\n 8973,\n 198,\n 220,\n 220,\n 220,\n 6818,\n 42848,\n 62,\n 3849,\n 2673,\n 62,\n 21,\n 13,\n 3849,\n 2673,\n 62,\n 4906,\n 6624,\n 366,\n 71,\n 62,\n 65,\n 623,\n 62,\n 13635,\n 273,\n 1,\n 198,\n 220,\n 220,\n 220,\n 6818,\n 42848,\n 62,\n 3849,\n 2673,\n 62,\n 21,\n 13,\n 411,\n 62,\n 3672,\n 6624,\n 14631,\n 1503,\n 38,\n 8628,\n 8973,\n 198,\n 220,\n 220,\n 220,\n 6818,\n 42848,\n 62,\n 3849,\n 2673,\n 62,\n 22,\n 13,\n 3849,\n 2673,\n 62,\n 4906,\n 6624,\n 366,\n 9509,\n 305,\n 12708,\n 62,\n 24561,\n 1,\n 198,\n 220,\n 220,\n 220,\n 6818,\n 42848,\n 62,\n 3849,\n 2673,\n 62,\n 22,\n 13,\n 411,\n 62,\n 3672,\n 6624,\n 14631,\n 1503,\n 38,\n 21526,\n 8973,\n 198,\n 220,\n 220,\n 220,\n 6818,\n 42848,\n 62,\n 3849,\n 2673,\n 62,\n 23,\n 13,\n 3849,\n 2673,\n 62,\n 4906,\n 6624,\n 366,\n 9509,\n 305,\n 12708,\n 62,\n 31591,\n 1,\n 198,\n 220,\n 220,\n 220,\n 6818,\n 42848,\n 62,\n 3849,\n 2673,\n 62,\n 23,\n 13,\n 411,\n 62,\n 3672,\n 6624,\n 14631,\n 5446,\n 47,\n 22413,\n 8973,\n 198,\n 220,\n 220,\n 220,\n 6818,\n 42848,\n 62,\n 3849,\n 2673,\n 62,\n 24,\n 13,\n 3849,\n 2673,\n 62,\n 4906,\n 6624,\n 366,\n 283,\n 13730,\n 62,\n 69,\n 23253,\n 1659,\n 558,\n 1,\n 198,\n 220,\n 220,\n 220,\n 6818,\n 42848,\n 62,\n 3849,\n 2673,\n 62,\n 24,\n 13,\n 411,\n 62,\n 3672,\n 6624,\n 14631,\n 35009,\n 23188,\n 8973,\n 198,\n 220,\n 220,\n 220,\n 6818,\n 42848,\n 62,\n 3849,\n 2673,\n 62,\n 940,\n 13,\n 3849,\n 2673,\n 62,\n 4906,\n 6624,\n 366,\n 283,\n 13730,\n 62,\n 276,\n 1136,\n 1659,\n 558,\n 1,\n 198,\n 220,\n 220,\n 220,\n 6818,\n 42848,\n 62,\n 3849,\n 2673,\n 62,\n 940,\n 13,\n 411,\n 62,\n 3672,\n 6624,\n 14631,\n 41119,\n 26115,\n 8973,\n 628,\n 198,\n 4299,\n 1332,\n 62,\n 33491,\n 62,\n 2545,\n 62,\n 10641,\n 33529,\n 198,\n 220,\n 220,\n 220,\n 37227,\n 14402,\n 1643,\n 9014,\n 2163,\n 329,\n 22532,\n 35186,\n 37811,\n 628,\n 220,\n 220,\n 220,\n 1303,\n 943,\n 9521,\n 628,\n 220,\n 220,\n 220,\n 1643,\n 8841,\n 796,\n 366,\n 49388,\n 486,\n 1,\n 628,\n 220,\n 220,\n 220,\n 42848,\n 62,\n 15511,\n 10051,\n 20803,\n 796,\n 685,\n 16,\n 11,\n 657,\n 11,\n 657,\n 11,\n 657,\n 11,\n 657,\n 11,\n 657,\n 11,\n 657,\n 60,\n 198,\n 220,\n 220,\n 220,\n 42848,\n 62,\n 283,\n 13730,\n 796,\n 685,\n 15,\n 11,\n 352,\n 11,\n 352,\n 11,\n 657,\n 11,\n 657,\n 11,\n 657,\n 11,\n 657,\n 60,\n 198,\n 220,\n 220,\n 220,\n 42848,\n 62,\n 71,\n 62,\n 65,\n 623,\n 796,\n 685,\n 15,\n 11,\n 657,\n 11,\n 657,\n 11,\n 352,\n 11,\n 352,\n 11,\n 657,\n 11,\n 657,\n 60,\n 198,\n 220,\n 220,\n 220,\n 42848,\n 62,\n 9509,\n 305,\n 12708,\n 796,\n 685,\n 15,\n 11,\n 657,\n 11,\n 657,\n 11,\n 657,\n 11,\n 657,\n 11,\n 352,\n 11,\n 352,\n 60,\n 198,\n 220,\n 220,\n 220,\n 42848,\n 62,\n 71,\n 62,\n 65,\n 623,\n 62,\n 9099,\n 273,\n 796,\n 685,\n 15,\n 11,\n 657,\n 11,\n 657,\n 11,\n 352,\n 11,\n 657,\n 11,\n 657,\n 11,\n 657,\n 60,\n 198,\n 220,\n 220,\n 220,\n 42848,\n 62,\n 71,\n 62,\n 65,\n 623,\n 62,\n 13635,\n 273,\n 796,\n 685,\n 15,\n 11,\n 657,\n 11,\n 657,\n 11,\n 657,\n 11,\n 352,\n 11,\n 657,\n 11,\n 657,\n 60,\n 198,\n 220,\n 220,\n 220,\n 42848,\n 62,\n 9509,\n 305,\n 12708,\n 62,\n 24561,\n 796,\n 685,\n 15,\n 11,\n 657,\n 11,\n 657,\n 11,\n 657,\n 11,\n 657,\n 11,\n 352,\n 11,\n 657,\n 60,\n 198,\n 220,\n 220,\n 220,\n 42848,\n 62,\n 9509,\n 305,\n 12708,\n 62,\n 31591,\n 796,\n 685,\n 15,\n 11,\n 657,\n 11,\n 657,\n 11,\n 657,\n 11,\n 657,\n 11,\n 657,\n 11,\n 352,\n 60,\n 198,\n 220,\n 220,\n 220,\n 42848,\n 62,\n 283,\n 13730,\n 62,\n 69,\n 23253,\n 1659,\n 558,\n 796,\n 685,\n 15,\n 11,\n 352,\n 11,\n 657,\n 11,\n 657,\n 11,\n 657,\n 11,\n 657,\n 11,\n 657,\n 60,\n 198,\n 220,\n 220,\n 220,\n 42848,\n 62,\n 283,\n 13730,\n 62,\n 276,\n 1136,\n 1659,\n 558,\n 796,\n 685,\n 15,\n 11,\n 657,\n 11,\n 352,\n 11,\n 657,\n 11,\n 657,\n 11,\n 657,\n 11,\n 657,\n 60,\n 628,\n 220,\n 220,\n 220,\n 1303,\n 2191,\n 628,\n 220,\n 220,\n 220,\n 1643,\n 8841,\n 62,\n 16,\n 796,\n 18568,\n 418,\n 13,\n 33491,\n 62,\n 2545,\n 62,\n 10641,\n 7,\n 2545,\n 8841,\n 11,\n 42848,\n 62,\n 15511,\n 10051,\n 20803,\n 8,\n 198,\n 220,\n 220,\n 220,\n 1643,\n 8841,\n 62,\n 17,\n 796,\n 18568,\n 418,\n 13,\n 33491,\n 62,\n 2545,\n 62,\n 10641,\n 7,\n 2545,\n 8841,\n 11,\n 42848,\n 62,\n 283,\n 13730,\n 8,\n 198,\n 220,\n 220,\n 220,\n 1643,\n 8841,\n 62,\n 18,\n 796,\n 18568,\n 418,\n 13,\n 33491,\n 62,\n 2545,\n 62,\n 10641,\n 7,\n 2545,\n 8841,\n 11,\n 42848,\n 62,\n 71,\n 62,\n 65,\n 623,\n 8,\n 198,\n 220,\n 220,\n 220,\n 1643,\n 8841,\n 62,\n 19,\n 796,\n 18568,\n 418,\n 13,\n 33491,\n 62,\n 2545,\n 62,\n 10641,\n 7,\n 2545,\n 8841,\n 11,\n 42848,\n 62,\n 9509,\n 305,\n 12708,\n 8,\n 198,\n 220,\n 220,\n 220,\n 1643,\n 8841,\n 62,\n 20,\n 796,\n 18568,\n 418,\n 13,\n 33491,\n 62,\n 2545,\n 62,\n 10641,\n 7,\n 2545,\n 8841,\n 11,\n 42848,\n 62,\n 71,\n 62,\n 65,\n 623,\n 62,\n 9099,\n 273,\n 8,\n 198,\n 220,\n 220,\n 220,\n 1643,\n 8841,\n 62,\n 21,\n 796,\n 18568,\n 418,\n 13,\n 33491,\n 62,\n 2545,\n 62,\n 10641,\n 7,\n 2545,\n 8841,\n 11,\n 42848,\n 62,\n 71,\n 62,\n 65,\n 623,\n 62,\n 13635,\n 273,\n 8,\n 198,\n 220,\n 220,\n 220,\n 1643,\n 8841,\n 62,\n 22,\n 796,\n 18568,\n 418,\n 13,\n 33491,\n 62,\n 2545,\n 62,\n 10641,\n 7,\n 2545,\n 8841,\n 11,\n 42848,\n 62,\n 9509,\n 305,\n 12708,\n 62,\n 24561,\n 8,\n 198,\n 220,\n 220,\n 220,\n 1643,\n 8841,\n 62,\n 23,\n 796,\n 18568,\n 418,\n 13,\n 33491,\n 62,\n 2545,\n 62,\n 10641,\n 7,\n 2545,\n 8841,\n 11,\n 42848,\n 62,\n 9509,\n 305,\n 12708,\n 62,\n 31591,\n 8,\n 198,\n 220,\n 220,\n 220,\n 1643,\n 8841,\n 62,\n 24,\n 796,\n 18568,\n 418,\n 13,\n 33491,\n 62,\n 2545,\n 62,\n 10641,\n 7,\n 2545,\n 8841,\n 11,\n 42848,\n 62,\n 283,\n 13730,\n 62,\n 69,\n 23253,\n 1659,\n 558,\n 8,\n 198,\n 220,\n 220,\n 220,\n 1643,\n 8841,\n 62,\n 940,\n 796,\n 18568,\n 418,\n 13,\n 33491,\n 62,\n 2545,\n 62,\n 10641,\n 7,\n 2545,\n 8841,\n 11,\n 42848,\n 62,\n 283,\n 13730,\n 62,\n 276,\n 1136,\n 1659,\n 558,\n 8,\n 628,\n 220,\n 220,\n 220,\n 1303,\n 2195,\n 861,\n 628,\n 220,\n 220,\n 220,\n 6818,\n 1643,\n 8841,\n 62,\n 16,\n 6624,\n 366,\n 77,\n 2388,\n 486,\n 1,\n 198,\n 220,\n 220,\n 220,\n 6818,\n 1643,\n 8841,\n 62,\n 17,\n 6624,\n 366,\n 16,\n 20471,\n 18005,\n 1,\n 198,\n 220,\n 220,\n 220,\n 6818,\n 1643,\n 8841,\n 62,\n 18,\n 6624,\n 366,\n 3064,\n 20471,\n 486,\n 1,\n 198,\n 220,\n 220,\n 220,\n 6818,\n 1643,\n 8841,\n 62,\n 19,\n 6624,\n 366,\n 49388,\n 20471,\n 1,\n 198,\n 220,\n 220,\n 220,\n 6818,\n 1643,\n 8841,\n 62,\n 20,\n 6624,\n 366,\n 3064,\n 77,\n 8298,\n 1,\n 198,\n 220,\n 220,\n 220,\n 6818,\n 1643,\n 8841,\n 62,\n 21,\n 6624,\n 366,\n 12825,\n 77,\n 486,\n 1,\n 198,\n 220,\n 220,\n 220,\n 6818,\n 1643,\n 8841,\n 62,\n 22,\n 6624,\n 366,\n 49388,\n 77,\n 16,\n 1,\n 198,\n 220,\n 220,\n 220,\n 6818,\n 1643,\n 8841,\n 62,\n 23,\n 6624,\n 366,\n 3064,\n 830,\n 77,\n 1,\n 198,\n 220,\n 220,\n 220,\n 6818,\n 1643,\n 8841,\n 62,\n 24,\n 6624,\n 366,\n 16,\n 77,\n 2388,\n 16,\n 1,\n 198,\n 220,\n 220,\n 220,\n 6818,\n 1643,\n 8841,\n 62,\n 940,\n 6624,\n 366,\n 940,\n 77,\n 18005,\n 1,\n 628,\n 198,\n 4299,\n 1332,\n 62,\n 27773,\n 929,\n 62,\n 296,\n 2175,\n 62,\n 3849,\n 2673,\n 33529,\n 198,\n 220,\n 220,\n 220,\n 37227,\n 14402,\n 329,\n 1643,\n 8841,\n 11824,\n 3161,\n 284,\n 26789,\n 17952,\n 37811,\n 628,\n 220,\n 220,\n 220,\n 1303,\n 943,\n 9521,\n 628,\n 220,\n 220,\n 220,\n 1006,\n 2545,\n 796,\n 366,\n 2388,\n 486,\n 18005,\n 486,\n 1,\n 198,\n 220,\n 220,\n 220,\n 256,\n 13655,\n 2545,\n 796,\n 366,\n 1157,\n 77,\n 405,\n 77,\n 2388,\n 1157,\n 1,\n 628,\n 220,\n 220,\n 220,\n 1303,\n 2191,\n 628,\n 220,\n 220,\n 220,\n 3424,\n 62,\n 5420,\n 2545,\n 11,\n 3424,\n 62,\n 83,\n 13655,\n 2545,\n 796,\n 26789,\n 13,\n 27773,\n 62,\n 296,\n 2175,\n 62,\n 3849,\n 4658,\n 7,\n 5420,\n 2545,\n 11,\n 256,\n 13655,\n 2545,\n 8,\n 628,\n 220,\n 220,\n 220,\n 1303,\n 2195,\n 861,\n 628,\n 220,\n 220,\n 220,\n 6818,\n 3424,\n 62,\n 5420,\n 2545,\n 6624,\n 366,\n 10535,\n 486,\n 486,\n 1,\n 198,\n 220,\n 220,\n 220,\n 6818,\n 3424,\n 62,\n 83,\n 13655,\n 2545,\n 6624,\n 366,\n 1157,\n 10535,\n 1157,\n 1,\n 198\n]"},"ratio_char_token":{"kind":"number","value":2.7559171597633134,"string":"2.755917"},"token_count":{"kind":"number","value":5408,"string":"5,408"}}},{"rowIdx":1232,"cells":{"content":{"kind":"string","value":"#!/usr/bin/python3\n\nimport sys\n\nfrom lib.demucs import demucs\nfrom lib.demucs.demucs import model\nfrom lib.demucs.demucs.audio import AudioFile\nfrom lib.demucs.demucs.utils import apply_model, load_model\nfrom pathlib import Path\nfrom scipy.io import wavfile\n\n\n# within the demucs directory\nsys.modules['demucs.model'] = model\nsys.modules['demucs'] = demucs\n\n\nclass DemucsService():\n\n \"\"\"\n def encode_mp3(wav, path, bitrate=320, verbose=False):\n try:\n import lameenc\n except ImportError:\n print(\"Failed to call lame encoder. Maybe it is not installed? \"\n \"On windows, run `python.exe -m pip install -U lameenc`, \"\n \"on OSX/Linux, run `python3 -m pip install -U lameenc`, \"\n \"then try again.\", file=sys.stderr)\n sys.exit(1)\n encoder = lameenc.Encoder()\n encoder.set_bit_rate(bitrate)\n encoder.set_in_sample_rate(44100)\n encoder.set_channels(2)\n encoder.set_quality(2) # 2-highest, 7-fastest\n if not verbose:\n encoder.silence()\n mp3_data = encoder.encode(wav.tostring())\n mp3_data += encoder.flush()\n with open(path, \"wb\") as f:\n f.write(mp3_data)\n \"\"\"\n"},"input_ids":{"kind":"list like","value":[2,48443,14629,14,8800,14,29412,18,198,198,11748,25064,198,198,6738,9195,13,9536,1229,82,1330,1357,1229,82,198,6738,9195,13,9536,1229,82,13,9536,1229,82,1330,2746,198,6738,9195,13,9536,1229,82,13,9536,1229,82,13,24051,1330,13491,8979,198,6738,9195,13,9536,1229,82,13,9536,1229,82,13,26791,1330,4174,62,19849,11,3440,62,19849,198,6738,3108,8019,1330,10644,198,6738,629,541,88,13,952,1330,266,615,7753,628,198,2,1626,262,1357,1229,82,8619,198,17597,13,18170,17816,9536,1229,82,13,19849,20520,796,2746,198,17597,13,18170,17816,9536,1229,82,20520,796,1357,1229,82,628,198,4871,1897,1229,82,16177,33529,628,220,220,220,37227,198,220,220,220,825,37773,62,3149,18,7,45137,11,3108,11,1643,4873,28,19504,11,15942,577,28,25101,2599,198,220,220,220,220,220,220,220,1949,25,198,220,220,220,220,220,220,220,220,220,220,220,1330,30248,12685,198,220,220,220,220,220,220,220,2845,17267,12331,25,198,220,220,220,220,220,220,220,220,220,220,220,3601,7203,37,6255,284,869,30248,2207,12342,13,6674,340,318,407,6589,30,366,198,220,220,220,220,220,220,220,220,220,220,220,220,220,220,220,366,2202,9168,11,1057,4600,29412,13,13499,532,76,7347,2721,532,52,30248,12685,47671,366,198,220,220,220,220,220,220,220,220,220,220,220,220,220,220,220,366,261,7294,55,14,19314,11,1057,4600,29412,18,532,76,7347,2721,532,52,30248,12685,47671,366,198,220,220,220,220,220,220,220,220,220,220,220,220,220,220,220,366,8524,1949,757,33283,2393,28,17597,13,301,1082,81,8,198,220,220,220,220,220,220,220,220,220,220,220,25064,13,37023,7,16,8,198,220,220,220,220,220,220,220,2207,12342,796,30248,12685,13,27195,12342,3419,198,220,220,220,220,220,220,220,2207,12342,13,2617,62,2545,62,4873,7,2545,4873,8,198,220,220,220,220,220,220,220,2207,12342,13,2617,62,259,62,39873,62,4873,7,2598,3064,8,198,220,220,220,220,220,220,220,2207,12342,13,2617,62,354,8961,7,17,8,198,220,220,220,220,220,220,220,2207,12342,13,2617,62,13237,7,17,8,220,1303,362,12,35323,11,767,12,7217,395,198,220,220,220,220,220,220,220,611,407,15942,577,25,198,220,220,220,220,220,220,220,220,220,220,220,2207,12342,13,18217,594,3419,198,220,220,220,220,220,220,220,29034,18,62,7890,796,2207,12342,13,268,8189,7,45137,13,83,455,1806,28955,198,220,220,220,220,220,220,220,29034,18,62,7890,15853,2207,12342,13,25925,3419,198,220,220,220,220,220,220,220,351,1280,7,6978,11,366,39346,4943,355,277,25,198,220,220,220,220,220,220,220,220,220,220,220,277,13,13564,7,3149,18,62,7890,8,198,220,220,220,37227,198],"string":"[\n 2,\n 48443,\n 14629,\n 14,\n 8800,\n 14,\n 29412,\n 18,\n 198,\n 198,\n 11748,\n 25064,\n 198,\n 198,\n 6738,\n 9195,\n 13,\n 9536,\n 1229,\n 82,\n 1330,\n 1357,\n 1229,\n 82,\n 198,\n 6738,\n 9195,\n 13,\n 9536,\n 1229,\n 82,\n 13,\n 9536,\n 1229,\n 82,\n 1330,\n 2746,\n 198,\n 6738,\n 9195,\n 13,\n 9536,\n 1229,\n 82,\n 13,\n 9536,\n 1229,\n 82,\n 13,\n 24051,\n 1330,\n 13491,\n 8979,\n 198,\n 6738,\n 9195,\n 13,\n 9536,\n 1229,\n 82,\n 13,\n 9536,\n 1229,\n 82,\n 13,\n 26791,\n 1330,\n 4174,\n 62,\n 19849,\n 11,\n 3440,\n 62,\n 19849,\n 198,\n 6738,\n 3108,\n 8019,\n 1330,\n 10644,\n 198,\n 6738,\n 629,\n 541,\n 88,\n 13,\n 952,\n 1330,\n 266,\n 615,\n 7753,\n 628,\n 198,\n 2,\n 1626,\n 262,\n 1357,\n 1229,\n 82,\n 8619,\n 198,\n 17597,\n 13,\n 18170,\n 17816,\n 9536,\n 1229,\n 82,\n 13,\n 19849,\n 20520,\n 796,\n 2746,\n 198,\n 17597,\n 13,\n 18170,\n 17816,\n 9536,\n 1229,\n 82,\n 20520,\n 796,\n 1357,\n 1229,\n 82,\n 628,\n 198,\n 4871,\n 1897,\n 1229,\n 82,\n 16177,\n 33529,\n 628,\n 220,\n 220,\n 220,\n 37227,\n 198,\n 220,\n 220,\n 220,\n 825,\n 37773,\n 62,\n 3149,\n 18,\n 7,\n 45137,\n 11,\n 3108,\n 11,\n 1643,\n 4873,\n 28,\n 19504,\n 11,\n 15942,\n 577,\n 28,\n 25101,\n 2599,\n 198,\n 220,\n 220,\n 220,\n 220,\n 220,\n 220,\n 220,\n 1949,\n 25,\n 198,\n 220,\n 220,\n 220,\n 220,\n 220,\n 220,\n 220,\n 220,\n 220,\n 220,\n 220,\n 1330,\n 30248,\n 12685,\n 198,\n 220,\n 220,\n 220,\n 220,\n 220,\n 220,\n 220,\n 2845,\n 17267,\n 12331,\n 25,\n 198,\n 220,\n 220,\n 220,\n 220,\n 220,\n 220,\n 220,\n 220,\n 220,\n 220,\n 220,\n 3601,\n 7203,\n 37,\n 6255,\n 284,\n 869,\n 30248,\n 2207,\n 12342,\n 13,\n 6674,\n 340,\n 318,\n 407,\n 6589,\n 30,\n 366,\n 198,\n 220,\n 220,\n 220,\n 220,\n 220,\n 220,\n 220,\n 220,\n 220,\n 220,\n 220,\n 220,\n 220,\n 220,\n 220,\n 366,\n 2202,\n 9168,\n 11,\n 1057,\n 4600,\n 29412,\n 13,\n 13499,\n 532,\n 76,\n 7347,\n 2721,\n 532,\n 52,\n 30248,\n 12685,\n 47671,\n 366,\n 198,\n 220,\n 220,\n 220,\n 220,\n 220,\n 220,\n 220,\n 220,\n 220,\n 220,\n 220,\n 220,\n 220,\n 220,\n 220,\n 366,\n 261,\n 7294,\n 55,\n 14,\n 19314,\n 11,\n 1057,\n 4600,\n 29412,\n 18,\n 532,\n 76,\n 7347,\n 2721,\n 532,\n 52,\n 30248,\n 12685,\n 47671,\n 366,\n 198,\n 220,\n 220,\n 220,\n 220,\n 220,\n 220,\n 220,\n 220,\n 220,\n 220,\n 220,\n 220,\n 220,\n 220,\n 220,\n 366,\n 8524,\n 1949,\n 757,\n 33283,\n 2393,\n 28,\n 17597,\n 13,\n 301,\n 1082,\n 81,\n 8,\n 198,\n 220,\n 220,\n 220,\n 220,\n 220,\n 220,\n 220,\n 220,\n 220,\n 220,\n 220,\n 25064,\n 13,\n 37023,\n 7,\n 16,\n 8,\n 198,\n 220,\n 220,\n 220,\n 220,\n 220,\n 220,\n 220,\n 2207,\n 12342,\n 796,\n 30248,\n 12685,\n 13,\n 27195,\n 12342,\n 3419,\n 198,\n 220,\n 220,\n 220,\n 220,\n 220,\n 220,\n 220,\n 2207,\n 12342,\n 13,\n 2617,\n 62,\n 2545,\n 62,\n 4873,\n 7,\n 2545,\n 4873,\n 8,\n 198,\n 220,\n 220,\n 220,\n 220,\n 220,\n 220,\n 220,\n 2207,\n 12342,\n 13,\n 2617,\n 62,\n 259,\n 62,\n 39873,\n 62,\n 4873,\n 7,\n 2598,\n 3064,\n 8,\n 198,\n 220,\n 220,\n 220,\n 220,\n 220,\n 220,\n 220,\n 2207,\n 12342,\n 13,\n 2617,\n 62,\n 354,\n 8961,\n 7,\n 17,\n 8,\n 198,\n 220,\n 220,\n 220,\n 220,\n 220,\n 220,\n 220,\n 2207,\n 12342,\n 13,\n 2617,\n 62,\n 13237,\n 7,\n 17,\n 8,\n 220,\n 1303,\n 362,\n 12,\n 35323,\n 11,\n 767,\n 12,\n 7217,\n 395,\n 198,\n 220,\n 220,\n 220,\n 220,\n 220,\n 220,\n 220,\n 611,\n 407,\n 15942,\n 577,\n 25,\n 198,\n 220,\n 220,\n 220,\n 220,\n 220,\n 220,\n 220,\n 220,\n 220,\n 220,\n 220,\n 2207,\n 12342,\n 13,\n 18217,\n 594,\n 3419,\n 198,\n 220,\n 220,\n 220,\n 220,\n 220,\n 220,\n 220,\n 29034,\n 18,\n 62,\n 7890,\n 796,\n 2207,\n 12342,\n 13,\n 268,\n 8189,\n 7,\n 45137,\n 13,\n 83,\n 455,\n 1806,\n 28955,\n 198,\n 220,\n 220,\n 220,\n 220,\n 220,\n 220,\n 220,\n 29034,\n 18,\n 62,\n 7890,\n 15853,\n 2207,\n 12342,\n 13,\n 25925,\n 3419,\n 198,\n 220,\n 220,\n 220,\n 220,\n 220,\n 220,\n 220,\n 351,\n 1280,\n 7,\n 6978,\n 11,\n 366,\n 39346,\n 4943,\n 355,\n 277,\n 25,\n 198,\n 220,\n 220,\n 220,\n 220,\n 220,\n 220,\n 220,\n 220,\n 220,\n 220,\n 220,\n 277,\n 13,\n 13564,\n 7,\n 3149,\n 18,\n 62,\n 7890,\n 8,\n 198,\n 220,\n 220,\n 220,\n 37227,\n 198\n]"},"ratio_char_token":{"kind":"number","value":2.1625874125874125,"string":"2.162587"},"token_count":{"kind":"number","value":572,"string":"572"}}},{"rowIdx":1233,"cells":{"content":{"kind":"string","value":"import pymysql\n\nconn = pymysql.Connection(\n host = '192.168.160.33',\n port = 3306,\n user = 'develop',\n password='xs_dev',\n database='test',\n charset='utf8'\n)\n\ncursor = conn.cursor()\n\nsql = \"\"\"\nselect * from user1\n\"\"\"\n\ntry:\n cursor.execute(sql)\n res = cursor.fetchall()\n for row in res:\n id = row[0]\n fname=row[1]\n lname=row[2]\n age =row[3]\n sex=row[4]\n income=row[5]\n print(\"id=%s,fname=%s,lname=%s,age=%s,sex=%s,income=%s\" % (id, fname, lname, age, sex, income))\nexcept Exception as e:\n print(e)\n\n# 关闭连接\nconn.close()"},"input_ids":{"kind":"list like","value":[11748,279,4948,893,13976,198,198,37043,796,279,4948,893,13976,13,32048,7,198,220,220,220,2583,796,705,17477,13,14656,13,14198,13,2091,3256,198,220,220,220,2493,796,513,20548,11,198,220,220,220,2836,796,705,16244,3256,198,220,220,220,9206,11639,34223,62,7959,3256,198,220,220,220,6831,11639,9288,3256,198,220,220,220,34534,316,11639,40477,23,6,198,8,198,198,66,21471,796,48260,13,66,21471,3419,198,198,25410,796,37227,198,19738,1635,422,2836,16,198,37811,198,198,28311,25,198,220,220,220,23493,13,41049,7,25410,8,198,220,220,220,581,796,23493,13,69,7569,439,3419,198,220,220,220,329,5752,287,581,25,198,220,220,220,220,220,220,220,4686,796,5752,58,15,60,198,220,220,220,220,220,220,220,277,3672,28,808,58,16,60,198,220,220,220,220,220,220,220,300,3672,28,808,58,17,60,198,220,220,220,220,220,220,220,2479,796,808,58,18,60,198,220,220,220,220,220,220,220,1714,28,808,58,19,60,198,220,220,220,220,220,220,220,3739,28,808,58,20,60,198,220,220,220,220,220,220,220,3601,7203,312,28,4,82,11,69,3672,28,4,82,11,75,3672,28,4,82,11,496,28,4,82,11,8044,28,4,82,11,12519,28,4,82,1,4064,357,312,11,277,3672,11,300,3672,11,2479,11,1714,11,3739,4008,198,16341,35528,355,304,25,198,220,220,220,3601,7,68,8,198,198,2,10263,227,111,29785,255,32573,252,162,236,98,198,37043,13,19836,3419],"string":"[\n 11748,\n 279,\n 4948,\n 893,\n 13976,\n 198,\n 198,\n 37043,\n 796,\n 279,\n 4948,\n 893,\n 13976,\n 13,\n 32048,\n 7,\n 198,\n 220,\n 220,\n 220,\n 2583,\n 796,\n 705,\n 17477,\n 13,\n 14656,\n 13,\n 14198,\n 13,\n 2091,\n 3256,\n 198,\n 220,\n 220,\n 220,\n 2493,\n 796,\n 513,\n 20548,\n 11,\n 198,\n 220,\n 220,\n 220,\n 2836,\n 796,\n 705,\n 16244,\n 3256,\n 198,\n 220,\n 220,\n 220,\n 9206,\n 11639,\n 34223,\n 62,\n 7959,\n 3256,\n 198,\n 220,\n 220,\n 220,\n 6831,\n 11639,\n 9288,\n 3256,\n 198,\n 220,\n 220,\n 220,\n 34534,\n 316,\n 11639,\n 40477,\n 23,\n 6,\n 198,\n 8,\n 198,\n 198,\n 66,\n 21471,\n 796,\n 48260,\n 13,\n 66,\n 21471,\n 3419,\n 198,\n 198,\n 25410,\n 796,\n 37227,\n 198,\n 19738,\n 1635,\n 422,\n 2836,\n 16,\n 198,\n 37811,\n 198,\n 198,\n 28311,\n 25,\n 198,\n 220,\n 220,\n 220,\n 23493,\n 13,\n 41049,\n 7,\n 25410,\n 8,\n 198,\n 220,\n 220,\n 220,\n 581,\n 796,\n 23493,\n 13,\n 69,\n 7569,\n 439,\n 3419,\n 198,\n 220,\n 220,\n 220,\n 329,\n 5752,\n 287,\n 581,\n 25,\n 198,\n 220,\n 220,\n 220,\n 220,\n 220,\n 220,\n 220,\n 4686,\n 796,\n 5752,\n 58,\n 15,\n 60,\n 198,\n 220,\n 220,\n 220,\n 220,\n 220,\n 220,\n 220,\n 277,\n 3672,\n 28,\n 808,\n 58,\n 16,\n 60,\n 198,\n 220,\n 220,\n 220,\n 220,\n 220,\n 220,\n 220,\n 300,\n 3672,\n 28,\n 808,\n 58,\n 17,\n 60,\n 198,\n 220,\n 220,\n 220,\n 220,\n 220,\n 220,\n 220,\n 2479,\n 796,\n 808,\n 58,\n 18,\n 60,\n 198,\n 220,\n 220,\n 220,\n 220,\n 220,\n 220,\n 220,\n 1714,\n 28,\n 808,\n 58,\n 19,\n 60,\n 198,\n 220,\n 220,\n 220,\n 220,\n 220,\n 220,\n 220,\n 3739,\n 28,\n 808,\n 58,\n 20,\n 60,\n 198,\n 220,\n 220,\n 220,\n 220,\n 220,\n 220,\n 220,\n 3601,\n 7203,\n 312,\n 28,\n 4,\n 82,\n 11,\n 69,\n 3672,\n 28,\n 4,\n 82,\n 11,\n 75,\n 3672,\n 28,\n 4,\n 82,\n 11,\n 496,\n 28,\n 4,\n 82,\n 11,\n 8044,\n 28,\n 4,\n 82,\n 11,\n 12519,\n 28,\n 4,\n 82,\n 1,\n 4064,\n 357,\n 312,\n 11,\n 277,\n 3672,\n 11,\n 300,\n 3672,\n 11,\n 2479,\n 11,\n 1714,\n 11,\n 3739,\n 4008,\n 198,\n 16341,\n 35528,\n 355,\n 304,\n 25,\n 198,\n 220,\n 220,\n 220,\n 3601,\n 7,\n 68,\n 8,\n 198,\n 198,\n 2,\n 10263,\n 227,\n 111,\n 29785,\n 255,\n 32573,\n 252,\n 162,\n 236,\n 98,\n 198,\n 37043,\n 13,\n 19836,\n 3419\n]"},"ratio_char_token":{"kind":"number","value":1.904153354632588,"string":"1.904153"},"token_count":{"kind":"number","value":313,"string":"313"}}},{"rowIdx":1234,"cells":{"content":{"kind":"string","value":"from nfmanagementapi.models import ServiceObject\nfrom nfmanagementapi.schemata import ServiceObjectSchema\nfrom marshmallow.exceptions import ValidationError\nfrom .BaseResource import BaseResource\nfrom flask import request\nfrom app import db\nfrom uuid import uuid4\n\npath = 'service_objects'\nendpoint = 'service_objects'\n"},"input_ids":{"kind":"list like","value":[6738,299,69,27604,15042,13,27530,1330,4809,10267,198,6738,299,69,27604,15042,13,1416,4411,1045,1330,4809,10267,27054,2611,198,6738,22397,42725,13,1069,11755,1330,3254,24765,12331,198,6738,764,14881,26198,1330,7308,26198,198,6738,42903,1330,2581,198,6738,598,1330,20613,198,6738,334,27112,1330,334,27112,19,198,198,6978,796,705,15271,62,48205,6,198,437,4122,796,705,15271,62,48205,6,198],"string":"[\n 6738,\n 299,\n 69,\n 27604,\n 15042,\n 13,\n 27530,\n 1330,\n 4809,\n 10267,\n 198,\n 6738,\n 299,\n 69,\n 27604,\n 15042,\n 13,\n 1416,\n 4411,\n 1045,\n 1330,\n 4809,\n 10267,\n 27054,\n 2611,\n 198,\n 6738,\n 22397,\n 42725,\n 13,\n 1069,\n 11755,\n 1330,\n 3254,\n 24765,\n 12331,\n 198,\n 6738,\n 764,\n 14881,\n 26198,\n 1330,\n 7308,\n 26198,\n 198,\n 6738,\n 42903,\n 1330,\n 2581,\n 198,\n 6738,\n 598,\n 1330,\n 20613,\n 198,\n 6738,\n 334,\n 27112,\n 1330,\n 334,\n 27112,\n 19,\n 198,\n 198,\n 6978,\n 796,\n 705,\n 15271,\n 62,\n 48205,\n 6,\n 198,\n 437,\n 4122,\n 796,\n 705,\n 15271,\n 62,\n 48205,\n 6,\n 198\n]"},"ratio_char_token":{"kind":"number","value":3.9382716049382718,"string":"3.938272"},"token_count":{"kind":"number","value":81,"string":"81"}}},{"rowIdx":1235,"cells":{"content":{"kind":"string","value":"# Generated by Django 3.1.6 on 2021-02-12 00:15\n\nfrom django.db import migrations, models\nimport django.db.models.deletion\n\n"},"input_ids":{"kind":"list like","value":[2,2980,515,416,37770,513,13,16,13,21,319,33448,12,2999,12,1065,3571,25,1314,198,198,6738,42625,14208,13,9945,1330,15720,602,11,4981,198,11748,42625,14208,13,9945,13,27530,13,2934,1616,295,628],"string":"[\n 2,\n 2980,\n 515,\n 416,\n 37770,\n 513,\n 13,\n 16,\n 13,\n 21,\n 319,\n 33448,\n 12,\n 2999,\n 12,\n 1065,\n 3571,\n 25,\n 1314,\n 198,\n 198,\n 6738,\n 42625,\n 14208,\n 13,\n 9945,\n 1330,\n 15720,\n 602,\n 11,\n 4981,\n 198,\n 11748,\n 42625,\n 14208,\n 13,\n 9945,\n 13,\n 27530,\n 13,\n 2934,\n 1616,\n 295,\n 628\n]"},"ratio_char_token":{"kind":"number","value":2.8181818181818183,"string":"2.818182"},"token_count":{"kind":"number","value":44,"string":"44"}}},{"rowIdx":1236,"cells":{"content":{"kind":"string","value":"config = {\r\n \"frequency\": 440.0,\r\n \"duration\": 20.0,\r\n \"sampling_rate\": 44100,\r\n \"filename\": \"test_v1.wav\",\r\n \"overtones\": [\r\n [\r\n 440.0,\r\n 1.0\r\n ],\r\n [\r\n 12447.350408741928,\r\n 0.1098108639573242\r\n ],\r\n [\r\n 12465.3571923053,\r\n 0.843727285302496\r\n ],\r\n [\r\n 21539.57505590213,\r\n 0.17496422223017305\r\n ],\r\n [\r\n 14675.669378957353,\r\n 0.013028474684831037\r\n ],\r\n [\r\n 20577.216573422433,\r\n 0.23529784971612777\r\n ],\r\n [\r\n 21425.497754119715,\r\n 0.6436550795219932\r\n ],\r\n [\r\n 11410.89145988607,\r\n 0.011826877382886125\r\n ]\r\n ],\r\n \"amp_ctrl_points\": [\r\n [\r\n 0.0,\r\n 0.0\r\n ],\r\n [\r\n 20.0,\r\n 100.0\r\n ],\r\n [\r\n 33.0,\r\n 20.0\r\n ],\r\n [\r\n 47.0,\r\n 88.0\r\n ],\r\n [\r\n 56.0,\r\n 45.0\r\n ],\r\n [\r\n 76.0,\r\n 80.0\r\n ],\r\n [\r\n 90.0,\r\n 5.0\r\n ],\r\n [\r\n 100.0,\r\n 20.0\r\n ]\r\n ]\r\n}\r\n"},"input_ids":{"kind":"list like","value":[11250,796,1391,201,198,220,220,220,366,35324,1298,33879,13,15,11,201,198,220,220,220,366,32257,1298,1160,13,15,11,201,198,220,220,220,366,37687,11347,62,4873,1298,5846,3064,11,201,198,220,220,220,366,34345,1298,366,9288,62,85,16,13,45137,1600,201,198,220,220,220,366,2502,36257,1298,685,201,198,220,220,220,220,220,220,220,685,201,198,220,220,220,220,220,220,220,220,220,220,220,33879,13,15,11,201,198,220,220,220,220,220,220,220,220,220,220,220,352,13,15,201,198,220,220,220,220,220,220,220,16589,201,198,220,220,220,220,220,220,220,685,201,198,220,220,220,220,220,220,220,220,220,220,220,1105,34825,13,14877,26200,4524,1129,2078,11,201,198,220,220,220,220,220,220,220,220,220,220,220,657,13,940,4089,940,4521,2670,48638,27877,201,198,220,220,220,220,220,220,220,16589,201,198,220,220,220,220,220,220,220,685,201,198,220,220,220,220,220,220,220,220,220,220,220,19755,2996,13,27277,17477,1270,4310,11,201,198,220,220,220,220,220,220,220,220,220,220,220,657,13,5705,2718,1983,26279,1270,1731,4846,201,198,220,220,220,220,220,220,220,16589,201,198,220,220,220,220,220,220,220,685,201,198,220,220,220,220,220,220,220,220,220,220,220,22951,2670,13,3553,1120,38605,2999,1485,11,201,198,220,220,220,220,220,220,220,220,220,220,220,657,13,1558,2920,2414,1828,1828,18938,22,22515,201,198,220,220,220,220,220,220,220,16589,201,198,220,220,220,220,220,220,220,685,201,198,220,220,220,220,220,220,220,220,220,220,220,22986,2425,13,36657,2718,4531,3553,33319,11,201,198,220,220,220,220,220,220,220,220,220,220,220,657,13,486,1270,2078,2857,38472,2780,26717,2718,201,198,220,220,220,220,220,220,220,16589,201,198,220,220,220,220,220,220,220,685,201,198,220,220,220,220,220,220,220,220,220,220,220,22538,3324,13,20666,3553,2682,24137,2091,11,201,198,220,220,220,220,220,220,220,220,220,220,220,657,13,22370,1959,3695,38073,1433,1065,29331,201,198,220,220,220,220,220,220,220,16589,201,198,220,220,220,220,220,220,220,685,201,198,220,220,220,220,220,220,220,220,220,220,220,28277,1495,13,2920,34483,3901,24991,1314,11,201,198,220,220,220,220,220,220,220,220,220,220,220,657,13,2414,2623,22730,3720,4309,19104,2624,201,198,220,220,220,220,220,220,220,16589,201,198,220,220,220,220,220,220,220,685,201,198,220,220,220,220,220,220,220,220,220,220,220,17342,940,13,4531,1415,3270,3459,31980,11,201,198,220,220,220,220,220,220,220,220,220,220,220,657,13,486,1507,25022,3324,2548,2078,4521,11623,201,198,220,220,220,220,220,220,220,2361,201,198,220,220,220,16589,201,198,220,220,220,366,696,62,44755,62,13033,1298,685,201,198,220,220,220,220,220,220,220,685,201,198,220,220,220,220,220,220,220,220,220,220,220,657,13,15,11,201,198,220,220,220,220,220,220,220,220,220,220,220,657,13,15,201,198,220,220,220,220,220,220,220,16589,201,198,220,220,220,220,220,220,220,685,201,198,220,220,220,220,220,220,220,220,220,220,220,1160,13,15,11,201,198,220,220,220,220,220,220,220,220,220,220,220,1802,13,15,201,198,220,220,220,220,220,220,220,16589,201,198,220,220,220,220,220,220,220,685,201,198,220,220,220,220,220,220,220,220,220,220,220,4747,13,15,11,201,198,220,220,220,220,220,220,220,220,220,220,220,1160,13,15,201,198,220,220,220,220,220,220,220,16589,201,198,220,220,220,220,220,220,220,685,201,198,220,220,220,220,220,220,220,220,220,220,220,6298,13,15,11,201,198,220,220,220,220,220,220,220,220,220,220,220,9193,13,15,201,198,220,220,220,220,220,220,220,16589,201,198,220,220,220,220,220,220,220,685,201,198,220,220,220,220,220,220,220,220,220,220,220,7265,13,15,11,201,198,220,220,220,220,220,220,220,220,220,220,220,4153,13,15,201,198,220,220,220,220,220,220,220,16589,201,198,220,220,220,220,220,220,220,685,201,198,220,220,220,220,220,220,220,220,220,220,220,8684,13,15,11,201,198,220,220,220,220,220,220,220,220,220,220,220,4019,13,15,201,198,220,220,220,220,220,220,220,16589,201,198,220,220,220,220,220,220,220,685,201,198,220,220,220,220,220,220,220,220,220,220,220,4101,13,15,11,201,198,220,220,220,220,220,220,220,220,220,220,220,642,13,15,201,198,220,220,220,220,220,220,220,16589,201,198,220,220,220,220,220,220,220,685,201,198,220,220,220,220,220,220,220,220,220,220,220,1802,13,15,11,201,198,220,220,220,220,220,220,220,220,220,220,220,1160,13,15,201,198,220,220,220,220,220,220,220,2361,201,198,220,220,220,2361,201,198,92,201,198],"string":"[\n 11250,\n 796,\n 1391,\n 201,\n 198,\n 220,\n 220,\n 220,\n 366,\n 35324,\n 1298,\n 33879,\n 13,\n 15,\n 11,\n 201,\n 198,\n 220,\n 220,\n 220,\n 366,\n 32257,\n 1298,\n 1160,\n 13,\n 15,\n 11,\n 201,\n 198,\n 220,\n 220,\n 220,\n 366,\n 37687,\n 11347,\n 62,\n 4873,\n 1298,\n 5846,\n 3064,\n 11,\n 201,\n 198,\n 220,\n 220,\n 220,\n 366,\n 34345,\n 1298,\n 366,\n 9288,\n 62,\n 85,\n 16,\n 13,\n 45137,\n 1600,\n 201,\n 198,\n 220,\n 220,\n 220,\n 366,\n 2502,\n 36257,\n 1298,\n 685,\n 201,\n 198,\n 220,\n 220,\n 220,\n 220,\n 220,\n 220,\n 220,\n 685,\n 201,\n 198,\n 220,\n 220,\n 220,\n 220,\n 220,\n 220,\n 220,\n 220,\n 220,\n 220,\n 220,\n 33879,\n 13,\n 15,\n 11,\n 201,\n 198,\n 220,\n 220,\n 220,\n 220,\n 220,\n 220,\n 220,\n 220,\n 220,\n 220,\n 220,\n 352,\n 13,\n 15,\n 201,\n 198,\n 220,\n 220,\n 220,\n 220,\n 220,\n 220,\n 220,\n 16589,\n 201,\n 198,\n 220,\n 220,\n 220,\n 220,\n 220,\n 220,\n 220,\n 685,\n 201,\n 198,\n 220,\n 220,\n 220,\n 220,\n 220,\n 220,\n 220,\n 220,\n 220,\n 220,\n 220,\n 1105,\n 34825,\n 13,\n 14877,\n 26200,\n 4524,\n 1129,\n 2078,\n 11,\n 201,\n 198,\n 220,\n 220,\n 220,\n 220,\n 220,\n 220,\n 220,\n 220,\n 220,\n 220,\n 220,\n 657,\n 13,\n 940,\n 4089,\n 940,\n 4521,\n 2670,\n 48638,\n 27877,\n 201,\n 198,\n 220,\n 220,\n 220,\n 220,\n 220,\n 220,\n 220,\n 16589,\n 201,\n 198,\n 220,\n 220,\n 220,\n 220,\n 220,\n 220,\n 220,\n 685,\n 201,\n 198,\n 220,\n 220,\n 220,\n 220,\n 220,\n 220,\n 220,\n 220,\n 220,\n 220,\n 220,\n 19755,\n 2996,\n 13,\n 27277,\n 17477,\n 1270,\n 4310,\n 11,\n 201,\n 198,\n 220,\n 220,\n 220,\n 220,\n 220,\n 220,\n 220,\n 220,\n 220,\n 220,\n 220,\n 657,\n 13,\n 5705,\n 2718,\n 1983,\n 26279,\n 1270,\n 1731,\n 4846,\n 201,\n 198,\n 220,\n 220,\n 220,\n 220,\n 220,\n 220,\n 220,\n 16589,\n 201,\n 198,\n 220,\n 220,\n 220,\n 220,\n 220,\n 220,\n 220,\n 685,\n 201,\n 198,\n 220,\n 220,\n 220,\n 220,\n 220,\n 220,\n 220,\n 220,\n 220,\n 220,\n 220,\n 22951,\n 2670,\n 13,\n 3553,\n 1120,\n 38605,\n 2999,\n 1485,\n 11,\n 201,\n 198,\n 220,\n 220,\n 220,\n 220,\n 220,\n 220,\n 220,\n 220,\n 220,\n 220,\n 220,\n 657,\n 13,\n 1558,\n 2920,\n 2414,\n 1828,\n 1828,\n 18938,\n 22,\n 22515,\n 201,\n 198,\n 220,\n 220,\n 220,\n 220,\n 220,\n 220,\n 220,\n 16589,\n 201,\n 198,\n 220,\n 220,\n 220,\n 220,\n 220,\n 220,\n 220,\n 685,\n 201,\n 198,\n 220,\n 220,\n 220,\n 220,\n 220,\n 220,\n 220,\n 220,\n 220,\n 220,\n 220,\n 22986,\n 2425,\n 13,\n 36657,\n 2718,\n 4531,\n 3553,\n 33319,\n 11,\n 201,\n 198,\n 220,\n 220,\n 220,\n 220,\n 220,\n 220,\n 220,\n 220,\n 220,\n 220,\n 220,\n 657,\n 13,\n 486,\n 1270,\n 2078,\n 2857,\n 38472,\n 2780,\n 26717,\n 2718,\n 201,\n 198,\n 220,\n 220,\n 220,\n 220,\n 220,\n 220,\n 220,\n 16589,\n 201,\n 198,\n 220,\n 220,\n 220,\n 220,\n 220,\n 220,\n 220,\n 685,\n 201,\n 198,\n 220,\n 220,\n 220,\n 220,\n 220,\n 220,\n 220,\n 220,\n 220,\n 220,\n 220,\n 22538,\n 3324,\n 13,\n 20666,\n 3553,\n 2682,\n 24137,\n 2091,\n 11,\n 201,\n 198,\n 220,\n 220,\n 220,\n 220,\n 220,\n 220,\n 220,\n 220,\n 220,\n 220,\n 220,\n 657,\n 13,\n 22370,\n 1959,\n 3695,\n 38073,\n 1433,\n 1065,\n 29331,\n 201,\n 198,\n 220,\n 220,\n 220,\n 220,\n 220,\n 220,\n 220,\n 16589,\n 201,\n 198,\n 220,\n 220,\n 220,\n 220,\n 220,\n 220,\n 220,\n 685,\n 201,\n 198,\n 220,\n 220,\n 220,\n 220,\n 220,\n 220,\n 220,\n 220,\n 220,\n 220,\n 220,\n 28277,\n 1495,\n 13,\n 2920,\n 34483,\n 3901,\n 24991,\n 1314,\n 11,\n 201,\n 198,\n 220,\n 220,\n 220,\n 220,\n 220,\n 220,\n 220,\n 220,\n 220,\n 220,\n 220,\n 657,\n 13,\n 2414,\n 2623,\n 22730,\n 3720,\n 4309,\n 19104,\n 2624,\n 201,\n 198,\n 220,\n 220,\n 220,\n 220,\n 220,\n 220,\n 220,\n 16589,\n 201,\n 198,\n 220,\n 220,\n 220,\n 220,\n 220,\n 220,\n 220,\n 685,\n 201,\n 198,\n 220,\n 220,\n 220,\n 220,\n 220,\n 220,\n 220,\n 220,\n 220,\n 220,\n 220,\n 17342,\n 940,\n 13,\n 4531,\n 1415,\n 3270,\n 3459,\n 31980,\n 11,\n 201,\n 198,\n 220,\n 220,\n 220,\n 220,\n 220,\n 220,\n 220,\n 220,\n 220,\n 220,\n 220,\n 657,\n 13,\n 486,\n 1507,\n 25022,\n 3324,\n 2548,\n 2078,\n 4521,\n 11623,\n 201,\n 198,\n 220,\n 220,\n 220,\n 220,\n 220,\n 220,\n 220,\n 2361,\n 201,\n 198,\n 220,\n 220,\n 220,\n 16589,\n 201,\n 198,\n 220,\n 220,\n 220,\n 366,\n 696,\n 62,\n 44755,\n 62,\n 13033,\n 1298,\n 685,\n 201,\n 198,\n 220,\n 220,\n 220,\n 220,\n 220,\n 220,\n 220,\n 685,\n 201,\n 198,\n 220,\n 220,\n 220,\n 220,\n 220,\n 220,\n 220,\n 220,\n 220,\n 220,\n 220,\n 657,\n 13,\n 15,\n 11,\n 201,\n 198,\n 220,\n 220,\n 220,\n 220,\n 220,\n 220,\n 220,\n 220,\n 220,\n 220,\n 220,\n 657,\n 13,\n 15,\n 201,\n 198,\n 220,\n 220,\n 220,\n 220,\n 220,\n 220,\n 220,\n 16589,\n 201,\n 198,\n 220,\n 220,\n 220,\n 220,\n 220,\n 220,\n 220,\n 685,\n 201,\n 198,\n 220,\n 220,\n 220,\n 220,\n 220,\n 220,\n 220,\n 220,\n 220,\n 220,\n 220,\n 1160,\n 13,\n 15,\n 11,\n 201,\n 198,\n 220,\n 220,\n 220,\n 220,\n 220,\n 220,\n 220,\n 220,\n 220,\n 220,\n 220,\n 1802,\n 13,\n 15,\n 201,\n 198,\n 220,\n 220,\n 220,\n 220,\n 220,\n 220,\n 220,\n 16589,\n 201,\n 198,\n 220,\n 220,\n 220,\n 220,\n 220,\n 220,\n 220,\n 685,\n 201,\n 198,\n 220,\n 220,\n 220,\n 220,\n 220,\n 220,\n 220,\n 220,\n 220,\n 220,\n 220,\n 4747,\n 13,\n 15,\n 11,\n 201,\n 198,\n 220,\n 220,\n 220,\n 220,\n 220,\n 220,\n 220,\n 220,\n 220,\n 220,\n 220,\n 1160,\n 13,\n 15,\n 201,\n 198,\n 220,\n 220,\n 220,\n 220,\n 220,\n 220,\n 220,\n 16589,\n 201,\n 198,\n 220,\n 220,\n 220,\n 220,\n 220,\n 220,\n 220,\n 685,\n 201,\n 198,\n 220,\n 220,\n 220,\n 220,\n 220,\n 220,\n 220,\n 220,\n 220,\n 220,\n 220,\n 6298,\n 13,\n 15,\n 11,\n 201,\n 198,\n 220,\n 220,\n 220,\n 220,\n 220,\n 220,\n 220,\n 220,\n 220,\n 220,\n 220,\n 9193,\n 13,\n 15,\n 201,\n 198,\n 220,\n 220,\n 220,\n 220,\n 220,\n 220,\n 220,\n 16589,\n 201,\n 198,\n 220,\n 220,\n 220,\n 220,\n 220,\n 220,\n 220,\n 685,\n 201,\n 198,\n 220,\n 220,\n 220,\n 220,\n 220,\n 220,\n 220,\n 220,\n 220,\n 220,\n 220,\n 7265,\n 13,\n 15,\n 11,\n 201,\n 198,\n 220,\n 220,\n 220,\n 220,\n 220,\n 220,\n 220,\n 220,\n 220,\n 220,\n 220,\n 4153,\n 13,\n 15,\n 201,\n 198,\n 220,\n 220,\n 220,\n 220,\n 220,\n 220,\n 220,\n 16589,\n 201,\n 198,\n 220,\n 220,\n 220,\n 220,\n 220,\n 220,\n 220,\n 685,\n 201,\n 198,\n 220,\n 220,\n 220,\n 220,\n 220,\n 220,\n 220,\n 220,\n 220,\n 220,\n 220,\n 8684,\n 13,\n 15,\n 11,\n 201,\n 198,\n 220,\n 220,\n 220,\n 220,\n 220,\n 220,\n 220,\n 220,\n 220,\n 220,\n 220,\n 4019,\n 13,\n 15,\n 201,\n 198,\n 220,\n 220,\n 220,\n 220,\n 220,\n 220,\n 220,\n 16589,\n 201,\n 198,\n 220,\n 220,\n 220,\n 220,\n 220,\n 220,\n 220,\n 685,\n 201,\n 198,\n 220,\n 220,\n 220,\n 220,\n 220,\n 220,\n 220,\n 220,\n 220,\n 220,\n 220,\n 4101,\n 13,\n 15,\n 11,\n 201,\n 198,\n 220,\n 220,\n 220,\n 220,\n 220,\n 220,\n 220,\n 220,\n 220,\n 220,\n 220,\n 642,\n 13,\n 15,\n 201,\n 198,\n 220,\n 220,\n 220,\n 220,\n 220,\n 220,\n 220,\n 16589,\n 201,\n 198,\n 220,\n 220,\n 220,\n 220,\n 220,\n 220,\n 220,\n 685,\n 201,\n 198,\n 220,\n 220,\n 220,\n 220,\n 220,\n 220,\n 220,\n 220,\n 220,\n 220,\n 220,\n 1802,\n 13,\n 15,\n 11,\n 201,\n 198,\n 220,\n 220,\n 220,\n 220,\n 220,\n 220,\n 220,\n 220,\n 220,\n 220,\n 220,\n 1160,\n 13,\n 15,\n 201,\n 198,\n 220,\n 220,\n 220,\n 220,\n 220,\n 220,\n 220,\n 2361,\n 201,\n 198,\n 220,\n 220,\n 220,\n 2361,\n 201,\n 198,\n 92,\n 201,\n 198\n]"},"ratio_char_token":{"kind":"number","value":1.3076171875,"string":"1.307617"},"token_count":{"kind":"number","value":1024,"string":"1,024"}}},{"rowIdx":1237,"cells":{"content":{"kind":"string","value":"import datetime\nimport re\nimport os\nimport struct\nfrom dataclasses import dataclass, field\nfrom itertools import combinations, product\nfrom typing import List, Dict\n\nimport pandas as pd\nimport numpy as np\nimport peakutils\nfrom matplotlib import pyplot as plt\nfrom scipy import signal as spsig\nimport plotly.graph_objs as go\nfrom tqdm.autonotebook import tqdm\nimport networkx as nx\nfrom ipywidgets import interactive, VBox, HBox\nfrom lmfit.models import LinearModel\n\nfrom pyspectools import routines\nfrom pyspectools import figurefactory as ff\nfrom pyspectools import fitting\nfrom pyspectools.spectra import analysis\nfrom pyspectools import parsers\n\n\n\ndef parse_spectrum(filename, threshold=20.0):\n \"\"\" Function to read in a blackchirp or QtFTM spectrum from file \"\"\"\n dataframe = pd.read_csv(\n filename, delimiter=\"\\t\", names=[\"Frequency\", \"Intensity\"], skiprows=1\n )\n return dataframe[dataframe[\"Intensity\"] <= threshold]\n\n\ndef center_cavity(dataframe, thres=0.3, verbose=True):\n \"\"\" Finds the center frequency of a Doppler pair in cavity FTM measurements\n and provides a column of offset frequencies.\n\n Sometimes the peak finding threshold has to be tweaked to get the center\n frequency correctly.\n \"\"\"\n # Find the peak intensities\n center_indexes = peakutils.indexes(dataframe[\"Intensity\"], thres=thres)\n peak_frequencies = dataframe.iloc[center_indexes][\"Frequency\"]\n # Calculate the center frequency as the average\n center = np.average(peak_frequencies)\n if verbose is True:\n print(\"Center frequency at \" + str(center))\n dataframe[\"Offset Frequency\"] = dataframe[\"Frequency\"] - center\n\n\n@dataclass\n\n\n@dataclass\nclass Scan:\n \"\"\"\n DataClass for a Scan. Holds all of the relevant information that\n describes a FT scan, such as the ID, what machine it was collected\n on, and the experimental settings.\n\n Has a few class methods that will make look ups easily such as\n the date the scan was collected and the gases used.\n \"\"\"\n\n id: int\n machine: str\n fid: np.array\n date: datetime.datetime\n shots: int = 0\n cavity_voltage: int = 0\n cavity_atten: int = 0\n cavity_frequency: float = 0.0\n dr_frequency: float = 0.0\n dr_power: int = 0\n fid_points: int = 0\n fid_spacing: float = 0.0\n discharge: bool = False\n magnet: bool = False\n gases: Dict = field(default_factory=dict)\n filter: List = field(default_factory=list)\n exp: float = 0.0\n zeropad: bool = False\n window: str = \"\"\n\n def __post_init__(self):\n \"\"\"\n Functions called after __init__ is called.\n \"\"\"\n # Perform FFT\n self.process_fid()\n\n def __deepcopy__(self):\n \"\"\"\n Dunder method to produce a deep copy - this will be used when\n manipulating multiple Scan objects.\n :return: A deep copy of the current Scan object\n \"\"\"\n\n new_scan = Empty()\n new_scan.__class__ = self.__class__\n new_scan.__dict__.update(self.__dict__)\n return new_scan\n\n def average(self, others):\n \"\"\"\n Dunder method to co-average two or more Scans in the time domain.\n :param other: Scan object, or tuple/list\n :return: A new Scan object with the co-added FID\n \"\"\"\n new_scan = self.__deepcopy__()\n try:\n new_scan.fid = np.average(others.extend(new_scan.fid), axis=0)\n new_scan.average_ids = [scan.id for scan in others]\n # If there is no extend method, then assume we're working with a\n # single Scan\n except AttributeError:\n new_scan.fid = np.average([new_scan.fid, others.fid], axis=0)\n new_scan.average_ids = [others.id]\n new_scan.process_fid()\n return new_scan\n\n def __add__(self, other):\n \"\"\"\n Dunder method to co-add two or more Scans in the time domain.\n :param other: Scan object, or tuple/list\n :return: A new Scan object with the co-added FID\n \"\"\"\n new_scan = self.__deepcopy__()\n new_scan.fid = np.sum([new_scan.fid, other.fid], axis=0)\n new_scan.process_fid()\n return new_scan\n\n def __sub__(self, other):\n \"\"\"\n Dunder method to subtract another Scan from the current Scan in the time domain.\n i.e. this scan - other scan\n :param other: Scan object, or tuple/list\n :return: A new Scan object with the subtracted FID\n \"\"\"\n new_scan = self.__deepcopy__()\n new_scan.fid = np.subtract(new_scan.fid, other.fid)\n new_scan.process_fid()\n return new_scan\n\n def subtract_frequency(self, other):\n \"\"\"\n Method to subtract another Scan from the current in the frequency domain.\n :param other: Scan object to subtract with\n :return: A new Scan object with the subtracted spectrum\n \"\"\"\n new_scan = self.__deepcopy__()\n new_scan.spectrum[\"Intensity\"] = (\n new_scan.spectrum[\"Intensity\"] - other.spectrum[\"Intensity\"]\n )\n new_scan.subtracted = other.id\n return new_scan\n\n def add_frequency(self, other):\n \"\"\"\n Method to add another Scan from the current in the frequency domain.\n :param other: Scan object to add with\n :return: A new Scan object with the co-added spectrum\n \"\"\"\n new_scan = self.__deepcopy__()\n new_scan.spectrum[\"Intensity\"] = (\n new_scan.spectrum[\"Intensity\"] + other.spectrum[\"Intensity\"]\n )\n new_scan.subtracted = other.id\n return new_scan\n\n @classmethod\n def from_dict(cls, data_dict):\n \"\"\"\n Function to initialize a Scan object from a dictionary\n of FT scan data collected from `parse_scan`.\n :param data_dict: dict containing parsed data from FT\n :return: Scan object\n \"\"\"\n scan_obj = cls(**data_dict)\n return scan_obj\n\n @classmethod\n def from_qtftm(cls, filepath):\n \"\"\"\n Method to initialize a Scan object from a FT scan file.\n Will load the lines into memory and parse the data into\n a dictionary, which then gets passed into a Scan object.\n :param filepath: str path to FID file\n :return: Scan object\n \"\"\"\n with open(filepath) as read_file:\n data_dict = parse_scan(read_file.readlines())\n scan_obj = cls(**data_dict)\n return scan_obj\n\n @classmethod\n def from_pickle(cls, filepath):\n \"\"\"\n Method to create a Scan object from a previously pickled\n Scan.\n :param filepath: path to the Scan pickle\n :return: instance of the Scan object\n \"\"\"\n scan_obj = routines.read_obj(filepath)\n if isinstance(scan_obj, Scan) is False:\n raise Exception(\"File is not a Scan object; {}\".format(type(scan_obj)))\n else:\n return scan_obj\n\n @classmethod\n def from_remote(cls, remote_path, ssh_obj=None):\n \"\"\"\n Method to initialize a Scan object from a remote server.\n Has the option to pass an instance of a paramiko SSHClient, which would be\n useful in a Batch. If none is supplied, an instance will be created.\n\n :param remote_path: str remote path to the file\n :param ssh_obj: optional argument to supply a paramiko SSHClient object\n :return: Scan object from remote QtFTM file\n \"\"\"\n if ssh_obj is None:\n default_keypath = os.path.join(os.path.expanduser(\"~\"), \".ssh/id_rsa.pub\")\n hostname = input(\"Please provide remote hostname: \")\n username = input(\"Please provide login: \")\n ssh_settings = {\"hostname\": hostname, \"username\": username}\n if os.path.isfile(default_keypath) is True:\n ssh_settings[\"key_filename\"] = default_keypath\n else:\n password = input(\"Please provide password: \")\n ssh_settings[\"password\"] = password\n ssh_obj = routines.RemoteClient(**ssh_settings)\n # Parse the scan data from remote file\n data_dict = parse_scan(ssh_obj.open_remote(remote_path))\n scan_obj = cls(**data_dict)\n return scan_obj\n\n def to_file(self, filepath, format=\"yaml\"):\n \"\"\" Method to dump data to YAML format.\n Extensions are automatically decided, but\n can also be supplied.\n\n parameters:\n --------------------\n :param filepath - str path to yaml file\n :param format - str denoting the syntax used for dumping. Defaults to YAML.\n \"\"\"\n if \".\" not in filepath:\n if format == \"json\":\n filepath += \".json\"\n else:\n filepath += \".yml\"\n if format == \"json\":\n writer = routines.dump_json\n else:\n writer = routines.dump_yaml\n writer(filepath, self.__dict__)\n\n def to_pickle(self, filepath=None, **kwargs):\n \"\"\"\n Pickles the Scan object with the joblib wrapper implemented\n in routines.\n :param filepath: optional argument to pickle to. Defaults to the id.pkl\n :param kwargs: additional settings for the pickle operation\n \"\"\"\n if filepath is None:\n filepath = \"{}.pkl\".format(self.id)\n routines.save_obj(self, filepath, **kwargs)\n\n def process_fid(self, **kwargs):\n \"\"\"\n Perform an FFT on the FID to yield the frequency domain spectrum.\n Kwargs are passed into the FID processing, which will override the\n Scan attributes.\n :param kwargs: Optional keyword arguments for processing the FID\n \"\"\"\n # Calculate the frequency bins\n frequencies = np.linspace(\n self.cavity_frequency, self.cavity_frequency + 1.0, len(self.fid)\n )\n # Calculate the time bins\n time = np.linspace(0.0, self.fid_spacing * self.fid_points, self.fid_points)\n process_list = [\"window\", \"filter\", \"exp\", \"zeropad\"]\n process_dict = {\n key: value for key, value in self.__dict__.items() if key in process_list\n }\n # Override with user settings\n process_dict.update(**kwargs)\n temp_fid = np.copy(self.fid)\n self.spectrum = fid2fft(\n temp_fid, 1.0 / self.fid_spacing, frequencies, **process_dict\n )\n self.fid_df = pd.DataFrame({\"Time (us)\": time * 1e6, \"FID\": temp_fid})\n\n def within_time(self, date_range):\n \"\"\"\n Function for determining of the scan was taken between\n a specified date range in month/day/year, in the format\n 04/09/08 for April 9th, 2008.\n :param date_range: list containing the beginning and end date strings\n :return: bool - True if within range, False otherwise\n \"\"\"\n try:\n early = datetime.datetime.strptime(date_range[0], \"%m/%d/%y\")\n except:\n early = datetime.datetime(1, 1, 1)\n try:\n late = datetime.datetime.strptime(date_range[1], \"%m/%d/%y\")\n except:\n late = datetime.datetime(9999, 1, 1)\n return early <= self.date <= late\n\n def is_depleted(self, ref, roi=None, depletion=None):\n \"\"\"\n Function for determining if the signal in this Scan is less\n than that of another scan. This is done by a simple comparison\n of the average of 10 largest intensities in the two spectra. If\n the current scan is less intense than the reference by the\n expected depletion percentage, then it is \"depleted\".\n\n This function can be used to determine if a scan if depleted\n in DR/magnet/discharge assays.\n\n TODO - implement a chi squared test of sorts to determine if a\n depletion is statistically significant\n\n :param ref: second Scan object for comparison\n :param depletion: percentage of depletion expected of the reference\n :return: bool - True if signal in this Scan is less intense than the reference\n \"\"\"\n y_ref = ref.spectrum[\"Intensity\"].values\n y_obs = self.spectrum[\"Intensity\"].values\n self.ref_freq = ref.fit.frequency\n self.ref_id = ref.id\n if roi:\n y_ref = y_ref[roi]\n y_obs = y_obs[roi]\n # This doesn't work, or is not particularly discriminating.\n # chisq, p_value = chisquare(\n # y_obs, y_ref\n # )\n if depletion is None:\n sigma = np.std(y_obs, axis=0) * 16.0\n else:\n sigma = depletion\n expected = np.sum(y_ref, axis=0) - sigma\n return np.sum(y_obs, axis=0) <= expected\n\n def scatter_trace(self):\n \"\"\"\n Create a Plotly Scattergl trace. Called by the Batch function, although\n performance-wise it takes forever to plot up ~3000 scans.\n :return trace: Scattergl object\n \"\"\"\n text = \"Scan ID: {}
Cavity: {}
DR: {}
Magnet: {}
Attn: {}\".format(\n self.id,\n self.cavity_frequency,\n self.dr_frequency,\n self.magnet,\n self.cavity_atten,\n )\n trace = go.Scattergl(\n x=np.linspace(self.id, self.id + 1, len(self.spectrum[\"Intensity\"])),\n y=self.spectrum[\"Intensity\"],\n text=text,\n marker={\"color\": \"rgb(43,140,190)\"},\n hoverinfo=\"text\",\n )\n return trace\n\n def fit_cavity(self, plot=True, verbose=False):\n \"\"\"\n Perform a fit to the cavity spectrum. Uses a paired Gaussian model\n that minimizes the number of fitting parameters.\n :param plot: bool specify whether a Plotly figure is made\n :return: Model Fit result\n \"\"\"\n y = self.spectrum[\"Intensity\"].dropna().values\n x = self.spectrum[\"Frequency (MHz)\"].dropna().values\n model = fitting.PairGaussianModel()\n result = model.fit_pair(x, y, verbose=verbose)\n self.spectrum[\"Fit\"] = result.best_fit\n self.fit = result\n self.fit.frequency = self.fit.best_values[\"x0\"]\n if plot is True:\n fig = go.FigureWidget()\n fig.layout[\"xaxis\"][\"title\"] = \"Frequency (MHz)\"\n fig.layout[\"xaxis\"][\"tickformat\"] = \".2f\"\n fig.add_scatter(x=x, y=y, name=\"Observed\")\n fig.add_scatter(x=x, y=result.best_fit, name=\"Fit\")\n return result, fig\n else:\n return result\n\n\ndef parse_scan(filecontents):\n \"\"\"\n Function for extracting the FID data from an FT scan. The data\n is returned as a dictionary, which can be used to initialize a\n Scan object.\n :param filecontents: list of lines from an FID file\n :return: dict containing parsed data from FID\n \"\"\"\n data = {\"gases\": dict()}\n # FID regex\n fid_regex = re.compile(r\"^fid\\d*\", re.M)\n # Regex to find gas channels\n gas_regex = re.compile(r\"^#Gas \\d name\", re.M)\n flow_regex = re.compile(r\"^#Gas \\d flow\", re.M)\n # Regex to detect which channel is set to the discharge\n dc_regex = re.compile(r\"^#Pulse ch \\d name\\s*DC\", re.M)\n dc_channel = None\n for index, line in enumerate(filecontents):\n if \"#Scan\" in line:\n split_line = line.split()\n data[\"id\"] = int(split_line[1])\n try:\n data[\"machine\"] = split_line[2]\n except IndexError:\n data[\"machine\"] = \"FT1\"\n if \"#Probe freq\" in line:\n data[\"cavity_frequency\"] = float(line.split()[2])\n if \"#Shots\" in line:\n data[\"shots\"] = int(line.split()[-1])\n if \"#Date\" in line:\n strip_targets = [\"#Date\", \"\\t\", \"\\n\"]\n data[\"date\"] = datetime.datetime.strptime(\n re.sub(\"|\".join(strip_targets), \"\", line), \"%a %b %d %H:%M:%S %Y\"\n )\n if \"#Cavity Voltage\" in line:\n data[\"cavity_voltage\"] = int(line.split()[2])\n if \"#Attenuation\" in line:\n data[\"cavity_atten\"] = int(line.split()[1])\n if \"#DR freq\" in line:\n data[\"dr_frequency\"] = float(line.split()[2])\n if \"#DR power\" in line:\n data[\"dr_power\"] = int(line.split()[2])\n if \"#FID spacing\" in line:\n data[\"fid_spacing\"] = float(re.findall(r\"\\de[+-]?\\d\\d\", line)[0])\n if \"#FID points\" in line:\n data[\"fid_points\"] = int(line.split()[-1])\n # Get the name of the gas\n if gas_regex.match(line):\n split_line = line.split()\n # Only bother parsing if the channel is used\n gas_index = int(split_line[1])\n try:\n data[\"gases\"][gas_index] = {\"gas\": \" \".join(split_line[3:])}\n except IndexError:\n data[\"gases\"][gas_index] = {\"gas\": \"\"}\n # Get the flow rate for channel\n if flow_regex.match(line):\n split_line = line.split()\n gas_index = int(split_line[1])\n data[\"gases\"][gas_index][\"flow\"] = float(split_line[3])\n if \"#Magnet enabled\" in line:\n data[\"magnet\"] = bool(int(line.split()[2]))\n # Find the channel the discharge is set to and compile a regex\n # to look for the channel\n if dc_regex.match(line):\n dc_index = line.split()[2]\n dc_channel = re.compile(r\"^#Pulse ch {} enabled\".format(dc_index), re.M)\n # Once the discharge channel index is known, start searching for it\n if dc_channel:\n if dc_channel.match(line):\n data[\"discharge\"] = bool(int(line.split()[-1]))\n # Find when the FID lines start popping up\n if fid_regex.match(line):\n fid = filecontents[index + 1 :]\n fid = [float(value) for value in fid]\n data[\"fid\"] = np.array(fid)\n return data\n\n\ndef perform_fft(fid, spacing, start=0, stop=-1, window=\"boxcar\"):\n \"\"\"\n Perform an FFT on an FID to get the frequency domain spectrum.\n All of the arguments are optional, and provide control over how the FFT is performed, as well as post-processing\n parameters like window functions and zero-padding.\n\n This is based on the FFT code by Kyle Crabtree, with modifications to fit this dataclass.\n\n Parameters\n ----------\n fid - Numpy 1D array\n Array holding the values of the FID\n spacing - float\n Time spacing between FID points in microseconds\n start - int, optional\n Starting index for the FID array to perform the FFT\n stop - int, optional\n End index for the FID array to perform the FFT\n zpf - int, optional\n Pad the FID with zeros to nth nearest power of 2\n window - str\n Specify the window function used to process the FID. Defaults to boxcar, which is effectively no filtering.\n The names of the window functions available can be found at:\n https://docs.scipy.org/doc/scipy/reference/signal.windows.html\n\n Returns\n -------\n \"\"\"\n fid = np.copy(fid)\n if window is not None and window in spsig.windows.__all__:\n window_f = spsig.windows.get_window(window, fid.size)\n fid *= window_f\n else:\n raise Exception(\"Specified window function is not implemented in SciPy!\")\n # Set values to zero up to starting index\n fid[:start] = 0.0\n if stop < 0:\n # If we're using negative indexes\n fid[fid.size + stop :] = 0.0\n else:\n # Otherwise, index with a positive number\n fid[stop:] = 0.0\n # Perform the FFT\n fft = np.fft.rfft(fid)\n read_length = len(fid) // 2 + 1\n df = 1.0 / fid.size / spacing\n # Generate the frequency array\n frequency = np.linspace(0.0, self.header[\"sideband\"] * df, read_length)\n frequency += self.header[\"probe_freq\"]\n fft[(frequency >= f_max) & (frequency <= f_min)] = 0.0\n fft *= 1000.0\n return frequency, fft\n\n\ndef fid2fft(fid, rate, frequencies, **kwargs):\n \"\"\"\n Process an FID by performing an FFT to yield the frequency domain\n information. Kwargs are passed as additional processing options,\n and are implemented as some case statements to ensure the settings\n are valid (e.g. conforms to sampling rate, etc.)\n\n :param fid: np.array corresponding to the FID intensity\n :param rate: sampling rate in Hz\n :param frequencies: np.array corresponding to the frequency bins\n :param kwargs: signal processing options:\n delay - delays the FID processing by setting the start\n of the FID to zero\n zeropad - Toggles whether or not the number of sampled\n points is doubled to get artificially higher\n resolution in the FFT\n window - Various window functions provided by `scipy.signal`\n exp - Specifies an exponential filter\n filter - 2-tuple specifying the frequency cutoffs for a\n band pass filter\n :return: freq_df - pandas dataframe with the FFT spectrum\n \"\"\"\n # Remove DC\n new_fid = fid - np.average(fid)\n if \"delay\" in kwargs:\n delay = int(kwargs[\"delay\"] / (1.0 / rate) / 1e6)\n new_fid[:delay] = 0.0\n # Zero-pad the FID\n if \"zeropad\" in kwargs:\n if kwargs[\"zeropad\"] is True:\n # Pad the FID with zeros to get higher resolution\n fid = np.append(new_fid, np.zeros(len(new_fid)))\n # Since we've padded with zeros, we'll have to update the\n # frequency array\n frequencies = spsig.resample(frequencies, len(frequencies) * 2)\n # Apply a window function to the FID\n if \"window\" in kwargs:\n if kwargs[\"window\"] in spsig.windows.__all__:\n new_fid *= spsig.get_window(kwargs[\"window\"], new_fid.size)\n # Apply an exponential filter on the FID\n if \"exp\" in kwargs:\n if kwargs[\"exp\"] > 0.0:\n new_fid *= spsig.exponential(len(new_fid), tau=kwargs[\"exp\"])\n # Apply a bandpass filter on the FID\n if (\"filter\" in kwargs) and (len(kwargs[\"filter\"]) == 2):\n low, high = sorted(kwargs[\"filter\"])\n if low < high:\n new_fid = apply_butter_filter(new_fid, low, high, rate)\n # Perform the FFT\n fft = np.fft.rfft(new_fid)\n # Get the real part of the FFT, and only the non-duplicated side\n real_fft = np.abs(fft[: int(len(new_fid) / 2)]) / len(new_fid) * 1e3\n frequencies = spsig.resample(frequencies, real_fft.size)\n # For some reason, resampling screws up the frequency ordering...\n real_fft = real_fft[np.argsort(frequencies)]\n frequencies = np.sort(frequencies)\n # Package into a pandas dataframe\n freq_df = pd.DataFrame({\"Frequency (MHz)\": frequencies, \"Intensity\": real_fft})\n return freq_df\n\n\ndef butter_bandpass(low, high, rate, order=1):\n \"\"\"\n A modified version of the Butterworth bandpass filter described here,\n adapted for use with the FID signal.\n http://scipy-cookbook.readthedocs.io/items/ButterworthBandpass.html\n The arguments are:\n\n :param low The low frequency cut-off, given in kHz.\n :param high The high frequency cut-off, given in kHz.\n :param rate The sampling rate, given in Hz. From the FIDs, this means that\n the inverse of the FID spacing is used.\n :return bandpass window\n \"\"\"\n # Calculate the Nyquist frequency\n nyq = 0.5 * (rate / (2.0 * np.pi))\n low = (low * 1e3) / nyq\n high = (high * 1e3) / nyq\n if high > 1.0:\n raise Exception(\"High frequency cut-off exceeds the Nyquist frequency.\")\n b, a = spsig.butter(order, [low, high], btype=\"band\", analog=False)\n return b, a\n\n\ndef apply_butter_filter(data, low, high, rate, order=1):\n \"\"\"\n A modified Butterworth bandpass filter, adapted from the Scipy cookbook.\n\n The argument data supplies the FID, which then uses the scipy signal\n processing function to apply the digital filter, and returns the filtered\n FID.\n\n See the `butter_bandpass` function for additional arguments.\n \"\"\"\n b, a = butter_bandpass(low, high, rate, order=order)\n y = spsig.lfilter(b, a, data)\n return y\n\n\n\ndef generate_ftb_line(frequency, shots, **kwargs):\n \"\"\" Function that generates an FTB file for a list of\n frequencies, plus categorization tests.\n\n kwargs are passed as additional options for the ftb\n batch. Keywords are:\n\n magnet: bool\n dipole: float\n atten: int\n skiptune: bool\n drfreq: float\n drpower: int\n cal\n\n parameters:\n ---------------\n :param frequency: float for frequency in MHz\n :param shots: int number of shots to integrate for\n\n returns:\n ---------------\n :return ftbline: str\n \"\"\"\n line = \"ftm:{:.4f} shots:{}\".format(frequency, shots)\n for key, value in kwargs.items():\n line += \" {}:{}\".format(key, value)\n line += \"\\n\"\n return line\n\n\ndef neu_categorize_frequencies(frequencies, intensities=None, nshots=50, **kwargs):\n \"\"\"\n Routine to generate an FTB batch file for performing a series of tests\n on frequencies.\n \"\"\"\n ftb_string = \"\"\n if intensities:\n norm_int = intensities / np.max(intensities)\n shotcounts = np.round(nshots / norm_int).astype(int)\n else:\n shotcounts = np.full(len(frequencies), nshots, dtype=int)\n\n # default settings for all stuff\n param_dict = {\n \"dipole\": 1.0,\n \"magnet\": \"false\",\n \"drpower\": \"10\",\n \"skiptune\": \"false\",\n }\n\n param_dict.update(kwargs)\n for freq, shot in zip(frequencies, shotcounts):\n ftb_string += generate_ftb_str(freq, shot, **param_dict)\n if \"magnet\" in kwargs:\n param_dict[\"magnet\"] = \"true\"\n ftb_string += generate_ftb_str(freq, shot, **param_dict)\n\n\ndef categorize_frequencies(\n frequencies,\n nshots=50,\n intensities=None,\n power=None,\n attn_list=None,\n dipole=None,\n attn=None,\n magnet=False,\n dr=False,\n discharge=False,\n):\n \"\"\"\n Function that will format an FT batch file to perform categorization\n tests, with some flexibility on how certain tests are performed.\n \"\"\"\n ftb_str = \"\"\n if intensities is None:\n shots = np.full(len(frequencies), nshots, dtype=int)\n else:\n shots = np.sqrt(nshots / intensities).astype(int)\n\n if dipole:\n if attn is None:\n # If dipole test requested, but no attenuation\n # supplied do the default sweep\n dipole_test = [0.01, 0.1, 1.0, 3.0, 5.0]\n dipole_flag = \"dipole\"\n else:\n # Otherwise run specific attenuations\n dipole_test = attn_list\n dipole_flag = \"atten\"\n\n if dr is True:\n freq_list = combinations(frequencies, 2)\n print(list(freq_list))\n else:\n freq_list = frequencies\n\n # loop over each frequency and number of shots\n for value, shotcount in zip(freq_list, shots):\n if dr is True:\n freq, dr_freq = value\n else:\n freq = value\n # Generate normal observation\n try:\n freq = float(freq)\n shotcount = int(shotcount)\n if dr is True:\n dr_freq = float(dr_freq)\n\n ftb_str += generate_ftb_line(freq, shotcount, **{\"skiptune\": \"false\"})\n\n if dr is True:\n ftb_str += generate_ftb_line(\n freq, shotcount, **{\"skiptune\": \"true\", \"drfreq\": dr_freq}\n )\n\n if dipole is True:\n for dipole_value in dipole_test:\n ftb_str += generate_ftb_line(\n freq, shotcount, **{dipole_flag: dipole_value}\n )\n\n if magnet is True:\n ftb_str += generate_ftb_line(freq, shotcount, **{\"magnet\": \"true\"})\n\n if discharge is True:\n # Toggle the discharge stack on and off\n ftb_str += generate_ftb_line(\n freq, shotcount, **{\"pulse,1,enabled\": \"false\"}\n )\n ftb_str += generate_ftb_line(\n freq, shotcount, **{\"pulse,1,enabled\": \"true\"}\n )\n except ValueError:\n print(\"Error with \" + str(value))\n\n return ftb_str\n\n\ndef calculate_integration_times(intensity, nshots=50):\n \"\"\"\n Method for calculating the expected integration time\n in shot counts based on the intensity; either theoretical\n line strengths or SNR.\n\n parameters:\n ---------------\n intensity - array of intensity metric; e.g. SNR\n nshots - optional int number of shots used for the strongest line\n\n returns:\n ---------------\n shot_counts - array of shot counts for each frequency\n \"\"\"\n norm_int = intensity / np.max(intensity)\n shot_counts = np.round(nshots / norm_int).astype(int)\n return shot_counts\n\n\n\n\n@dataclass\n\n\n@dataclass\n"},"input_ids":{"kind":"list like","value":[11748,4818,8079,198,11748,302,198,11748,28686,198,11748,2878,198,6738,4818,330,28958,1330,4818,330,31172,11,2214,198,6738,340,861,10141,1330,17790,11,1720,198,6738,19720,1330,7343,11,360,713,198,198,11748,19798,292,355,279,67,198,11748,299,32152,355,45941,198,11748,9103,26791,198,6738,2603,29487,8019,1330,12972,29487,355,458,83,198,6738,629,541,88,1330,6737,355,599,82,328,198,11748,7110,306,13,34960,62,672,8457,355,467,198,6738,256,80,36020,13,2306,261,1258,2070,1330,256,80,36020,198,11748,3127,87,355,299,87,198,6738,20966,88,28029,11407,1330,14333,11,569,14253,11,367,14253,198,6738,300,76,11147,13,27530,1330,44800,17633,198,198,6738,279,893,806,10141,1330,31878,198,6738,279,893,806,10141,1330,3785,69,9548,355,31246,198,6738,279,893,806,10141,1330,15830,198,6738,279,893,806,10141,13,4443,430,1330,3781,198,6738,279,893,806,10141,1330,13544,364,628,198,198,4299,21136,62,4443,6582,7,34345,11,11387,28,1238,13,15,2599,198,220,220,220,37227,15553,284,1100,287,257,2042,354,343,79,393,33734,9792,44,10958,422,2393,37227,198,220,220,220,1366,14535,796,279,67,13,961,62,40664,7,198,220,220,220,220,220,220,220,29472,11,46728,2676,2625,59,83,1600,3891,28,14692,37,28707,1600,366,5317,6377,33116,14267,8516,28,16,198,220,220,220,1267,198,220,220,220,1441,1366,14535,58,7890,14535,14692,5317,6377,8973,19841,11387,60,628,198,4299,3641,62,66,615,414,7,7890,14535,11,294,411,28,15,13,18,11,15942,577,28,17821,2599,198,220,220,220,37227,9938,82,262,3641,8373,286,257,2141,381,1754,5166,287,31643,376,15972,13871,198,220,220,220,220,220,220,220,290,3769,257,5721,286,11677,19998,13,628,220,220,220,220,220,220,220,8975,262,9103,4917,11387,468,284,307,38304,284,651,262,3641,198,220,220,220,220,220,220,220,8373,9380,13,198,220,220,220,37227,198,220,220,220,1303,9938,262,9103,17509,871,198,220,220,220,3641,62,9630,274,796,9103,26791,13,9630,274,7,7890,14535,14692,5317,6377,33116,294,411,28,400,411,8,198,220,220,220,9103,62,69,8897,3976,796,1366,14535,13,346,420,58,16159,62,9630,274,7131,1,37,28707,8973,198,220,220,220,1303,27131,378,262,3641,8373,355,262,2811,198,220,220,220,3641,796,45941,13,23913,7,36729,62,69,8897,3976,8,198,220,220,220,611,15942,577,318,6407,25,198,220,220,220,220,220,220,220,3601,7203,23656,8373,379,366,1343,965,7,16159,4008,198,220,220,220,1366,14535,14692,34519,31902,8973,796,1366,14535,14692,37,28707,8973,532,3641,628,198,31,19608,330,31172,628,198,31,19608,330,31172,198,4871,20937,25,198,220,220,220,37227,198,220,220,220,6060,9487,329,257,20937,13,9340,82,477,286,262,5981,1321,326,198,220,220,220,8477,257,19446,9367,11,884,355,262,4522,11,644,4572,340,373,7723,198,220,220,220,319,11,290,262,11992,6460,13,628,220,220,220,7875,257,1178,1398,5050,326,481,787,804,19649,3538,884,355,198,220,220,220,262,3128,262,9367,373,7723,290,262,21678,973,13,198,220,220,220,37227,628,220,220,220,4686,25,493,198,220,220,220,4572,25,965,198,220,220,220,49909,25,45941,13,18747,198,220,220,220,3128,25,4818,8079,13,19608,8079,198,220,220,220,6934,25,493,796,657,198,220,220,220,31643,62,37764,496,25,493,796,657,198,220,220,220,31643,62,41769,25,493,796,657,198,220,220,220,31643,62,35324,25,12178,796,657,13,15,198,220,220,220,1553,62,35324,25,12178,796,657,13,15,198,220,220,220,1553,62,6477,25,493,796,657,198,220,220,220,49909,62,13033,25,493,796,657,198,220,220,220,49909,62,2777,4092,25,12178,796,657,13,15,198,220,220,220,17655,25,20512,796,10352,198,220,220,220,19972,25,20512,796,10352,198,220,220,220,21678,25,360,713,796,2214,7,12286,62,69,9548,28,11600,8,198,220,220,220,8106,25,7343,796,2214,7,12286,62,69,9548,28,4868,8,198,220,220,220,1033,25,12178,796,657,13,15,198,220,220,220,1976,263,404,324,25,20512,796,10352,198,220,220,220,4324,25,965,796,13538,628,220,220,220,825,11593,7353,62,15003,834,7,944,2599,198,220,220,220,220,220,220,220,37227,198,220,220,220,220,220,220,220,40480,1444,706,11593,15003,834,318,1444,13,198,220,220,220,220,220,220,220,37227,198,220,220,220,220,220,220,220,1303,35006,376,9792,198,220,220,220,220,220,220,220,2116,13,14681,62,69,312,3419,628,220,220,220,825,11593,22089,30073,834,7,944,2599,198,220,220,220,220,220,220,220,37227,198,220,220,220,220,220,220,220,360,4625,2446,284,4439,257,2769,4866,532,428,481,307,973,618,198,220,220,220,220,220,220,220,29349,3294,20937,5563,13,198,220,220,220,220,220,220,220,1058,7783,25,317,2769,4866,286,262,1459,20937,2134,198,220,220,220,220,220,220,220,37227,628,220,220,220,220,220,220,220,649,62,35836,796,33523,3419,198,220,220,220,220,220,220,220,649,62,35836,13,834,4871,834,796,2116,13,834,4871,834,198,220,220,220,220,220,220,220,649,62,35836,13,834,11600,834,13,19119,7,944,13,834,11600,834,8,198,220,220,220,220,220,220,220,1441,649,62,35836,628,220,220,220,825,2811,7,944,11,1854,2599,198,220,220,220,220,220,220,220,37227,198,220,220,220,220,220,220,220,360,4625,2446,284,763,12,23913,734,393,517,1446,504,287,262,640,7386,13,198,220,220,220,220,220,220,220,1058,17143,584,25,20937,2134,11,393,46545,14,4868,198,220,220,220,220,220,220,220,1058,7783,25,317,649,20937,2134,351,262,763,12,29373,376,2389,198,220,220,220,220,220,220,220,37227,198,220,220,220,220,220,220,220,649,62,35836,796,2116,13,834,22089,30073,834,3419,198,220,220,220,220,220,220,220,1949,25,198,220,220,220,220,220,220,220,220,220,220,220,649,62,35836,13,69,312,796,45941,13,23913,7,847,82,13,2302,437,7,3605,62,35836,13,69,312,828,16488,28,15,8,198,220,220,220,220,220,220,220,220,220,220,220,649,62,35836,13,23913,62,2340,796,685,35836,13,312,329,9367,287,1854,60,198,220,220,220,220,220,220,220,1303,1002,612,318,645,9117,2446,11,788,7048,356,821,1762,351,257,198,220,220,220,220,220,220,220,1303,2060,20937,198,220,220,220,220,220,220,220,2845,3460,4163,12331,25,198,220,220,220,220,220,220,220,220,220,220,220,649,62,35836,13,69,312,796,45941,13,23913,26933,3605,62,35836,13,69,312,11,1854,13,69,312,4357,16488,28,15,8,198,220,220,220,220,220,220,220,220,220,220,220,649,62,35836,13,23913,62,2340,796,685,847,82,13,312,60,198,220,220,220,220,220,220,220,649,62,35836,13,14681,62,69,312,3419,198,220,220,220,220,220,220,220,1441,649,62,35836,628,220,220,220,825,11593,2860,834,7,944,11,584,2599,198,220,220,220,220,220,220,220,37227,198,220,220,220,220,220,220,220,360,4625,2446,284,763,12,2860,734,393,517,1446,504,287,262,640,7386,13,198,220,220,220,220,220,220,220,1058,17143,584,25,20937,2134,11,393,46545,14,4868,198,220,220,220,220,220,220,220,1058,7783,25,317,649,20937,2134,351,262,763,12,29373,376,2389,198,220,220,220,220,220,220,220,37227,198,220,220,220,220,220,220,220,649,62,35836,796,2116,13,834,22089,30073,834,3419,198,220,220,220,220,220,220,220,649,62,35836,13,69,312,796,45941,13,16345,26933,3605,62,35836,13,69,312,11,584,13,69,312,4357,16488,28,15,8,198,220,220,220,220,220,220,220,649,62,35836,13,14681,62,69,312,3419,198,220,220,220,220,220,220,220,1441,649,62,35836,628,220,220,220,825,11593,7266,834,7,944,11,584,2599,198,220,220,220,220,220,220,220,37227,198,220,220,220,220,220,220,220,360,4625,2446,284,34128,1194,20937,422,262,1459,20937,287,262,640,7386,13,198,220,220,220,220,220,220,220,1312,13,68,13,428,9367,532,584,9367,198,220,220,220,220,220,220,220,1058,17143,584,25,20937,2134,11,393,46545,14,4868,198,220,220,220,220,220,220,220,1058,7783,25,317,649,20937,2134,351,262,13284,20216,376,2389,198,220,220,220,220,220,220,220,37227,198,220,220,220,220,220,220,220,649,62,35836,796,2116,13,834,22089,30073,834,3419,198,220,220,220,220,220,220,220,649,62,35836,13,69,312,796,45941,13,7266,83,974,7,3605,62,35836,13,69,312,11,584,13,69,312,8,198,220,220,220,220,220,220,220,649,62,35836,13,14681,62,69,312,3419,198,220,220,220,220,220,220,220,1441,649,62,35836,628,220,220,220,825,34128,62,35324,7,944,11,584,2599,198,220,220,220,220,220,220,220,37227,198,220,220,220,220,220,220,220,11789,284,34128,1194,20937,422,262,1459,287,262,8373,7386,13,198,220,220,220,220,220,220,220,1058,17143,584,25,20937,2134,284,34128,351,198,220,220,220,220,220,220,220,1058,7783,25,317,649,20937,2134,351,262,13284,20216,10958,198,220,220,220,220,220,220,220,37227,198,220,220,220,220,220,220,220,649,62,35836,796,2116,13,834,22089,30073,834,3419,198,220,220,220,220,220,220,220,649,62,35836,13,4443,6582,14692,5317,6377,8973,796,357,198,220,220,220,220,220,220,220,220,220,220,220,649,62,35836,13,4443,6582,14692,5317,6377,8973,532,584,13,4443,6582,14692,5317,6377,8973,198,220,220,220,220,220,220,220,1267,198,220,220,220,220,220,220,220,649,62,35836,13,7266,83,20216,796,584,13,312,198,220,220,220,220,220,220,220,1441,649,62,35836,628,220,220,220,825,751,62,35324,7,944,11,584,2599,198,220,220,220,220,220,220,220,37227,198,220,220,220,220,220,220,220,11789,284,751,1194,20937,422,262,1459,287,262,8373,7386,13,198,220,220,220,220,220,220,220,1058,17143,584,25,20937,2134,284,751,351,198,220,220,220,220,220,220,220,1058,7783,25,317,649,20937,2134,351,262,763,12,29373,10958,198,220,220,220,220,220,220,220,37227,198,220,220,220,220,220,220,220,649,62,35836,796,2116,13,834,22089,30073,834,3419,198,220,220,220,220,220,220,220,649,62,35836,13,4443,6582,14692,5317,6377,8973,796,357,198,220,220,220,220,220,220,220,220,220,220,220,649,62,35836,13,4443,6582,14692,5317,6377,8973,1343,584,13,4443,6582,14692,5317,6377,8973,198,220,220,220,220,220,220,220,1267,198,220,220,220,220,220,220,220,649,62,35836,13,7266,83,20216,796,584,13,312,198,220,220,220,220,220,220,220,1441,649,62,35836,628,220,220,220,2488,4871,24396,198,220,220,220,825,422,62,11600,7,565,82,11,1366,62,11600,2599,198,220,220,220,220,220,220,220,37227,198,220,220,220,220,220,220,220,15553,284,41216,257,20937,2134,422,257,22155,198,220,220,220,220,220,220,220,286,19446,9367,1366,7723,422,4600,29572,62,35836,44646,198,220,220,220,220,220,220,220,1058,17143,1366,62,11600,25,8633,7268,44267,1366,422,19446,198,220,220,220,220,220,220,220,1058,7783,25,20937,2134,198,220,220,220,220,220,220,220,37227,198,220,220,220,220,220,220,220,9367,62,26801,796,537,82,7,1174,7890,62,11600,8,198,220,220,220,220,220,220,220,1441,9367,62,26801,628,220,220,220,2488,4871,24396,198,220,220,220,825,422,62,39568,701,76,7,565,82,11,2393,6978,2599,198,220,220,220,220,220,220,220,37227,198,220,220,220,220,220,220,220,11789,284,41216,257,20937,2134,422,257,19446,9367,2393,13,198,220,220,220,220,220,220,220,2561,3440,262,3951,656,4088,290,21136,262,1366,656,198,220,220,220,220,220,220,220,257,22155,11,543,788,3011,3804,656,257,20937,2134,13,198,220,220,220,220,220,220,220,1058,17143,2393,6978,25,965,3108,284,376,2389,2393,198,220,220,220,220,220,220,220,1058,7783,25,20937,2134,198,220,220,220,220,220,220,220,37227,198,220,220,220,220,220,220,220,351,1280,7,7753,6978,8,355,1100,62,7753,25,198,220,220,220,220,220,220,220,220,220,220,220,1366,62,11600,796,21136,62,35836,7,961,62,7753,13,961,6615,28955,198,220,220,220,220,220,220,220,9367,62,26801,796,537,82,7,1174,7890,62,11600,8,198,220,220,220,220,220,220,220,1441,9367,62,26801,628,220,220,220,2488,4871,24396,198,220,220,220,825,422,62,27729,293,7,565,82,11,2393,6978,2599,198,220,220,220,220,220,220,220,37227,198,220,220,220,220,220,220,220,11789,284,2251,257,20937,2134,422,257,4271,2298,992,198,220,220,220,220,220,220,220,20937,13,198,220,220,220,220,220,220,220,1058,17143,2393,6978,25,3108,284,262,20937,2298,293,198,220,220,220,220,220,220,220,1058,7783,25,4554,286,262,20937,2134,198,220,220,220,220,220,220,220,37227,198,220,220,220,220,220,220,220,9367,62,26801,796,31878,13,961,62,26801,7,7753,6978,8,198,220,220,220,220,220,220,220,611,318,39098,7,35836,62,26801,11,20937,8,318,10352,25,198,220,220,220,220,220,220,220,220,220,220,220,5298,35528,7203,8979,318,407,257,20937,2134,26,23884,1911,18982,7,4906,7,35836,62,26801,22305,198,220,220,220,220,220,220,220,2073,25,198,220,220,220,220,220,220,220,220,220,220,220,1441,9367,62,26801,628,220,220,220,2488,4871,24396,198,220,220,220,825,422,62,47960,7,565,82,11,6569,62,6978,11,26678,62,26801,28,14202,2599,198,220,220,220,220,220,220,220,37227,198,220,220,220,220,220,220,220,11789,284,41216,257,20937,2134,422,257,6569,4382,13,198,220,220,220,220,220,220,220,7875,262,3038,284,1208,281,4554,286,257,5772,12125,33825,11792,11,543,561,307,198,220,220,220,220,220,220,220,4465,287,257,347,963,13,1002,4844,318,14275,11,281,4554,481,307,2727,13,628,220,220,220,220,220,220,220,1058,17143,6569,62,6978,25,965,6569,3108,284,262,2393,198,220,220,220,220,220,220,220,1058,17143,26678,62,26801,25,11902,4578,284,5127,257,5772,12125,33825,11792,2134,198,220,220,220,220,220,220,220,1058,7783,25,20937,2134,422,6569,33734,9792,44,2393,198,220,220,220,220,220,220,220,37227,198,220,220,220,220,220,220,220,611,26678,62,26801,318,6045,25,198,220,220,220,220,220,220,220,220,220,220,220,4277,62,2539,6978,796,28686,13,6978,13,22179,7,418,13,6978,13,11201,392,7220,7203,93,12340,27071,45824,14,312,62,3808,64,13,12984,4943,198,220,220,220,220,220,220,220,220,220,220,220,2583,3672,796,5128,7203,5492,2148,6569,2583,3672,25,220,220,220,366,8,198,220,220,220,220,220,220,220,220,220,220,220,20579,796,5128,7203,5492,2148,17594,25,220,220,220,220,220,220,220,220,220,220,220,220,220,366,8,198,220,220,220,220,220,220,220,220,220,220,220,26678,62,33692,796,19779,4774,3672,1298,2583,3672,11,366,29460,1298,20579,92,198,220,220,220,220,220,220,220,220,220,220,220,611,28686,13,6978,13,4468,576,7,12286,62,2539,6978,8,318,6407,25,198,220,220,220,220,220,220,220,220,220,220,220,220,220,220,220,26678,62,33692,14692,2539,62,34345,8973,796,4277,62,2539,6978,198,220,220,220,220,220,220,220,220,220,220,220,2073,25,198,220,220,220,220,220,220,220,220,220,220,220,220,220,220,220,9206,796,5128,7203,5492,2148,9206,25,220,220,220,220,220,220,220,220,220,220,220,220,220,366,8,198,220,220,220,220,220,220,220,220,220,220,220,220,220,220,220,26678,62,33692,14692,28712,8973,796,9206,198,220,220,220,220,220,220,220,220,220,220,220,26678,62,26801,796,31878,13,36510,11792,7,1174,45824,62,33692,8,198,220,220,220,220,220,220,220,1303,2547,325,262,9367,1366,422,6569,2393,198,220,220,220,220,220,220,220,1366,62,11600,796,21136,62,35836,7,45824,62,26801,13,9654,62,47960,7,47960,62,6978,4008,198,220,220,220,220,220,220,220,9367,62,26801,796,537,82,7,1174,7890,62,11600,8,198,220,220,220,220,220,220,220,1441,9367,62,26801,628,220,220,220,825,284,62,7753,7,944,11,2393,6978,11,5794,2625,88,43695,1,2599,198,220,220,220,220,220,220,220,37227,11789,284,10285,1366,284,575,2390,43,5794,13,198,220,220,220,220,220,220,220,220,220,220,220,49751,389,6338,3066,11,475,198,220,220,220,220,220,220,220,220,220,220,220,460,635,307,14275,13,628,220,220,220,220,220,220,220,220,220,220,220,10007,25,198,220,220,220,220,220,220,220,220,220,220,220,41436,198,220,220,220,220,220,220,220,220,220,220,220,1058,17143,2393,6978,532,965,3108,284,331,43695,2393,198,220,220,220,220,220,220,220,220,220,220,220,1058,17143,5794,532,965,2853,10720,262,15582,973,329,30231,13,2896,13185,284,575,2390,43,13,198,220,220,220,220,220,220,220,37227,198,220,220,220,220,220,220,220,611,366,526,407,287,2393,6978,25,198,220,220,220,220,220,220,220,220,220,220,220,611,5794,6624,366,17752,1298,198,220,220,220,220,220,220,220,220,220,220,220,220,220,220,220,2393,6978,15853,27071,17752,1,198,220,220,220,220,220,220,220,220,220,220,220,2073,25,198,220,220,220,220,220,220,220,220,220,220,220,220,220,220,220,2393,6978,15853,27071,88,4029,1,198,220,220,220,220,220,220,220,611,5794,6624,366,17752,1298,198,220,220,220,220,220,220,220,220,220,220,220,6260,796,31878,13,39455,62,17752,198,220,220,220,220,220,220,220,2073,25,198,220,220,220,220,220,220,220,220,220,220,220,6260,796,31878,13,39455,62,88,43695,198,220,220,220,220,220,220,220,6260,7,7753,6978,11,2116,13,834,11600,834,8,628,220,220,220,825,284,62,27729,293,7,944,11,2393,6978,28,14202,11,12429,46265,22046,2599,198,220,220,220,220,220,220,220,37227,198,220,220,220,220,220,220,220,12346,829,262,20937,2134,351,262,1693,8019,29908,9177,198,220,220,220,220,220,220,220,287,31878,13,198,220,220,220,220,220,220,220,1058,17143,2393,6978,25,11902,4578,284,2298,293,284,13,2896,13185,284,262,4686,13,79,41582,198,220,220,220,220,220,220,220,1058,17143,479,86,22046,25,3224,6460,329,262,2298,293,4905,198,220,220,220,220,220,220,220,37227,198,220,220,220,220,220,220,220,611,2393,6978,318,6045,25,198,220,220,220,220,220,220,220,220,220,220,220,2393,6978,796,45144,27422,79,41582,1911,18982,7,944,13,312,8,198,220,220,220,220,220,220,220,31878,13,21928,62,26801,7,944,11,2393,6978,11,12429,46265,22046,8,628,220,220,220,825,1429,62,69,312,7,944,11,12429,46265,22046,2599,198,220,220,220,220,220,220,220,37227,198,220,220,220,220,220,220,220,35006,281,376,9792,319,262,376,2389,284,7800,262,8373,7386,10958,13,198,220,220,220,220,220,220,220,31767,22046,389,3804,656,262,376,2389,7587,11,543,481,20957,262,198,220,220,220,220,220,220,220,20937,12608,13,198,220,220,220,220,220,220,220,1058,17143,479,86,22046,25,32233,21179,7159,329,7587,262,376,2389,198,220,220,220,220,220,220,220,37227,198,220,220,220,220,220,220,220,1303,27131,378,262,8373,41701,198,220,220,220,220,220,220,220,19998,796,45941,13,21602,10223,7,198,220,220,220,220,220,220,220,220,220,220,220,2116,13,66,615,414,62,35324,11,2116,13,66,615,414,62,35324,1343,352,13,15,11,18896,7,944,13,69,312,8,198,220,220,220,220,220,220,220,1267,198,220,220,220,220,220,220,220,1303,27131,378,262,640,41701,198,220,220,220,220,220,220,220,640,796,45941,13,21602,10223,7,15,13,15,11,2116,13,69,312,62,2777,4092,1635,2116,13,69,312,62,13033,11,2116,13,69,312,62,13033,8,198,220,220,220,220,220,220,220,1429,62,4868,796,14631,17497,1600,366,24455,1600,366,11201,1600,366,9107,404,324,8973,198,220,220,220,220,220,220,220,1429,62,11600,796,1391,198,220,220,220,220,220,220,220,220,220,220,220,1994,25,1988,329,1994,11,1988,287,2116,13,834,11600,834,13,23814,3419,611,1994,287,1429,62,4868,198,220,220,220,220,220,220,220,1782,198,220,220,220,220,220,220,220,1303,3827,13154,351,2836,6460,198,220,220,220,220,220,220,220,1429,62,11600,13,19119,7,1174,46265,22046,8,198,220,220,220,220,220,220,220,20218,62,69,312,796,45941,13,30073,7,944,13,69,312,8,198,220,220,220,220,220,220,220,2116,13,4443,6582,796,49909,17,487,83,7,198,220,220,220,220,220,220,220,220,220,220,220,20218,62,69,312,11,352,13,15,1220,2116,13,69,312,62,2777,4092,11,19998,11,12429,14681,62,11600,198,220,220,220,220,220,220,220,1267,198,220,220,220,220,220,220,220,2116,13,69,312,62,7568,796,279,67,13,6601,19778,7,4895,7575,357,385,8,1298,640,1635,352,68,21,11,366,37,2389,1298,20218,62,69,312,30072,628,220,220,220,825,1626,62,2435,7,944,11,3128,62,9521,2599,198,220,220,220,220,220,220,220,37227,198,220,220,220,220,220,220,220,15553,329,13213,286,262,9367,373,2077,1022,198,220,220,220,220,220,220,220,257,7368,3128,2837,287,1227,14,820,14,1941,11,287,262,5794,198,220,220,220,220,220,220,220,8702,14,2931,14,2919,329,3035,860,400,11,3648,13,198,220,220,220,220,220,220,220,1058,17143,3128,62,9521,25,1351,7268,262,3726,290,886,3128,13042,198,220,220,220,220,220,220,220,1058,7783,25,20512,532,6407,611,1626,2837,11,10352,4306,198,220,220,220,220,220,220,220,37227,198,220,220,220,220,220,220,220,1949,25,198,220,220,220,220,220,220,220,220,220,220,220,1903,796,4818,8079,13,19608,8079,13,2536,457,524,7,4475,62,9521,58,15,4357,36521,76,14,4,67,14,4,88,4943,198,220,220,220,220,220,220,220,2845,25,198,220,220,220,220,220,220,220,220,220,220,220,1903,796,4818,8079,13,19608,8079,7,16,11,352,11,352,8,198,220,220,220,220,220,220,220,1949,25,198,220,220,220,220,220,220,220,220,220,220,220,2739,796,4818,8079,13,19608,8079,13,2536,457,524,7,4475,62,9521,58,16,4357,36521,76,14,4,67,14,4,88,4943,198,220,220,220,220,220,220,220,2845,25,198,220,220,220,220,220,220,220,220,220,220,220,2739,796,4818,8079,13,19608,8079,7,24214,11,352,11,352,8,198,220,220,220,220,220,220,220,1441,1903,19841,2116,13,4475,19841,2739,628,220,220,220,825,318,62,10378,33342,7,944,11,1006,11,686,72,28,14202,11,42435,28,14202,2599,198,220,220,220,220,220,220,220,37227,198,220,220,220,220,220,220,220,15553,329,13213,611,262,6737,287,428,20937,318,1342,198,220,220,220,220,220,220,220,621,326,286,1194,9367,13,770,318,1760,416,257,2829,7208,198,220,220,220,220,220,220,220,286,262,2811,286,838,4387,17509,871,287,262,734,5444,430,13,1002,198,220,220,220,220,220,220,220,262,1459,9367,318,1342,8157,621,262,4941,416,262,198,220,220,220,220,220,220,220,2938,42435,5873,11,788,340,318,366,10378,33342,1911,628,220,220,220,220,220,220,220,770,2163,460,307,973,284,5004,611,257,9367,611,34069,198,220,220,220,220,220,220,220,287,10560,14,19726,3262,14,6381,10136,840,592,13,628,220,220,220,220,220,220,220,16926,46,532,3494,257,33166,44345,1332,286,10524,284,5004,611,257,198,220,220,220,220,220,220,220,220,220,220,220,220,220,220,42435,318,19941,2383,628,220,220,220,220,220,220,220,1058,17143,1006,25,1218,20937,2134,329,7208,198,220,220,220,220,220,220,220,1058,17143,42435,25,5873,286,42435,2938,286,262,4941,198,220,220,220,220,220,220,220,1058,7783,25,20512,532,6407,611,6737,287,428,20937,318,1342,8157,621,262,4941,198,220,220,220,220,220,220,220,37227,198,220,220,220,220,220,220,220,331,62,5420,796,1006,13,4443,6582,14692,5317,6377,1,4083,27160,198,220,220,220,220,220,220,220,331,62,8158,796,2116,13,4443,6582,14692,5317,6377,1,4083,27160,198,220,220,220,220,220,220,220,2116,13,5420,62,19503,80,796,1006,13,11147,13,35324,198,220,220,220,220,220,220,220,2116,13,5420,62,312,796,1006,13,312,198,220,220,220,220,220,220,220,611,686,72,25,198,220,220,220,220,220,220,220,220,220,220,220,331,62,5420,796,331,62,5420,58,305,72,60,198,220,220,220,220,220,220,220,220,220,220,220,331,62,8158,796,331,62,8158,58,305,72,60,198,220,220,220,220,220,220,220,1303,770,1595,470,670,11,393,318,407,3573,48212,13,198,220,220,220,220,220,220,220,1303,442,271,80,11,279,62,8367,796,442,271,421,533,7,198,220,220,220,220,220,220,220,1303,220,220,220,331,62,8158,11,331,62,5420,198,220,220,220,220,220,220,220,1303,1267,198,220,220,220,220,220,220,220,611,42435,318,6045,25,198,220,220,220,220,220,220,220,220,220,220,220,264,13495,796,45941,13,19282,7,88,62,8158,11,16488,28,15,8,1635,1467,13,15,198,220,220,220,220,220,220,220,2073,25,198,220,220,220,220,220,220,220,220,220,220,220,264,13495,796,42435,198,220,220,220,220,220,220,220,2938,796,45941,13,16345,7,88,62,5420,11,16488,28,15,8,532,264,13495,198,220,220,220,220,220,220,220,1441,45941,13,16345,7,88,62,8158,11,16488,28,15,8,19841,2938,628,220,220,220,825,41058,62,40546,7,944,2599,198,220,220,220,220,220,220,220,37227,198,220,220,220,220,220,220,220,13610,257,28114,306,1446,1436,4743,12854,13,34099,416,262,347,963,2163,11,3584,198,220,220,220,220,220,220,220,2854,12,3083,340,2753,8097,284,7110,510,5299,23924,23824,13,198,220,220,220,220,220,220,220,1058,7783,12854,25,1446,1436,4743,2134,198,220,220,220,220,220,220,220,37227,198,220,220,220,220,220,220,220,2420,796,366,33351,4522,25,23884,27,1671,29,34,615,414,25,23884,27,1671,29,7707,25,23884,27,1671,29,13436,3262,25,23884,27,1671,29,8086,77,25,23884,1911,18982,7,198,220,220,220,220,220,220,220,220,220,220,220,2116,13,312,11,198,220,220,220,220,220,220,220,220,220,220,220,2116,13,66,615,414,62,35324,11,198,220,220,220,220,220,220,220,220,220,220,220,2116,13,7109,62,35324,11,198,220,220,220,220,220,220,220,220,220,220,220,2116,13,19726,3262,11,198,220,220,220,220,220,220,220,220,220,220,220,2116,13,66,615,414,62,41769,11,198,220,220,220,220,220,220,220,1267,198,220,220,220,220,220,220,220,12854,796,467,13,3351,1436,4743,7,198,220,220,220,220,220,220,220,220,220,220,220,2124,28,37659,13,21602,10223,7,944,13,312,11,2116,13,312,1343,352,11,18896,7,944,13,4443,6582,14692,5317,6377,8973,36911,198,220,220,220,220,220,220,220,220,220,220,220,331,28,944,13,4443,6582,14692,5317,6377,33116,198,220,220,220,220,220,220,220,220,220,220,220,2420,28,5239,11,198,220,220,220,220,220,220,220,220,220,220,220,18364,28,4895,8043,1298,366,81,22296,7,3559,11,15187,11,19782,16725,5512,198,220,220,220,220,220,220,220,220,220,220,220,20599,10951,2625,5239,1600,198,220,220,220,220,220,220,220,1267,198,220,220,220,220,220,220,220,1441,12854,628,220,220,220,825,4197,62,66,615,414,7,944,11,7110,28,17821,11,15942,577,28,25101,2599,198,220,220,220,220,220,220,220,37227,198,220,220,220,220,220,220,220,35006,257,4197,284,262,31643,10958,13,36965,257,20312,12822,31562,2746,198,220,220,220,220,220,220,220,326,10356,4340,262,1271,286,15830,10007,13,198,220,220,220,220,220,220,220,1058,17143,7110,25,20512,11986,1771,257,28114,306,3785,318,925,198,220,220,220,220,220,220,220,1058,7783,25,9104,25048,1255,198,220,220,220,220,220,220,220,37227,198,220,220,220,220,220,220,220,331,796,2116,13,4443,6582,14692,5317,6377,1,4083,14781,2616,22446,27160,198,220,220,220,220,220,220,220,2124,796,2116,13,4443,6582,14692,37,28707,357,25983,16725,4083,14781,2616,22446,27160,198,220,220,220,220,220,220,220,2746,796,15830,13,47,958,35389,31562,17633,3419,198,220,220,220,220,220,220,220,1255,796,2746,13,11147,62,24874,7,87,11,331,11,15942,577,28,19011,577,8,198,220,220,220,220,220,220,220,2116,13,4443,6582,14692,31805,8973,796,1255,13,13466,62,11147,198,220,220,220,220,220,220,220,2116,13,11147,796,1255,198,220,220,220,220,220,220,220,2116,13,11147,13,35324,796,2116,13,11147,13,13466,62,27160,14692,87,15,8973,198,220,220,220,220,220,220,220,611,7110,318,6407,25,198,220,220,220,220,220,220,220,220,220,220,220,2336,796,467,13,11337,38300,3419,198,220,220,220,220,220,220,220,220,220,220,220,2336,13,39786,14692,87,22704,1,7131,1,7839,8973,796,366,37,28707,357,25983,16725,198,220,220,220,220,220,220,220,220,220,220,220,2336,13,39786,14692,87,22704,1,7131,1,42298,18982,8973,796,27071,17,69,1,198,220,220,220,220,220,220,220,220,220,220,220,2336,13,2860,62,1416,1436,7,87,28,87,11,331,28,88,11,1438,2625,31310,8520,4943,198,220,220,220,220,220,220,220,220,220,220,220,2336,13,2860,62,1416,1436,7,87,28,87,11,331,28,20274,13,13466,62,11147,11,1438,2625,31805,4943,198,220,220,220,220,220,220,220,220,220,220,220,1441,1255,11,2336,198,220,220,220,220,220,220,220,2073,25,198,220,220,220,220,220,220,220,220,220,220,220,1441,1255,628,198,4299,21136,62,35836,7,7753,3642,658,2599,198,220,220,220,37227,198,220,220,220,15553,329,37895,262,376,2389,1366,422,281,19446,9367,13,383,1366,198,220,220,220,318,4504,355,257,22155,11,543,460,307,973,284,41216,257,198,220,220,220,20937,2134,13,198,220,220,220,1058,17143,2393,3642,658,25,1351,286,3951,422,281,376,2389,2393,198,220,220,220,1058,7783,25,8633,7268,44267,1366,422,376,2389,198,220,220,220,37227,198,220,220,220,1366,796,19779,70,1386,1298,8633,3419,92,198,220,220,220,1303,376,2389,40364,198,220,220,220,49909,62,260,25636,796,302,13,5589,576,7,81,1,61,69,312,59,67,9,1600,302,13,44,8,198,220,220,220,1303,797,25636,284,1064,3623,9619,198,220,220,220,3623,62,260,25636,796,302,13,5589,576,7,81,1,61,2,39699,3467,67,1438,1600,302,13,44,8,198,220,220,220,5202,62,260,25636,796,302,13,5589,576,7,81,1,61,2,39699,3467,67,5202,1600,302,13,44,8,198,220,220,220,1303,797,25636,284,4886,543,6518,318,900,284,262,17655,198,220,220,220,30736,62,260,25636,796,302,13,5589,576,7,81,1,61,2,47,9615,442,3467,67,1438,59,82,9,9697,1600,302,13,44,8,198,220,220,220,30736,62,17620,796,6045,198,220,220,220,329,6376,11,1627,287,27056,378,7,7753,3642,658,2599,198,220,220,220,220,220,220,220,611,25113,33351,1,287,1627,25,198,220,220,220,220,220,220,220,220,220,220,220,6626,62,1370,796,1627,13,35312,3419,198,220,220,220,220,220,220,220,220,220,220,220,1366,14692,312,8973,796,493,7,35312,62,1370,58,16,12962,198,220,220,220,220,220,220,220,220,220,220,220,1949,25,198,220,220,220,220,220,220,220,220,220,220,220,220,220,220,220,1366,14692,30243,8973,796,6626,62,1370,58,17,60,198,220,220,220,220,220,220,220,220,220,220,220,2845,12901,12331,25,198,220,220,220,220,220,220,220,220,220,220,220,220,220,220,220,1366,14692,30243,8973,796,366,9792,16,1,198,220,220,220,220,220,220,220,611,25113,2964,1350,2030,80,1,287,1627,25,198,220,220,220,220,220,220,220,220,220,220,220,1366,14692,66,615,414,62,35324,8973,796,12178,7,1370,13,35312,3419,58,17,12962,198,220,220,220,220,220,220,220,611,25113,2484,1747,1,287,1627,25,198,220,220,220,220,220,220,220,220,220,220,220,1366,14692,20910,8973,796,493,7,1370,13,35312,3419,58,12,16,12962,198,220,220,220,220,220,220,220,611,25113,10430,1,287,1627,25,198,220,220,220,220,220,220,220,220,220,220,220,10283,62,83,853,1039,796,14631,2,10430,1600,37082,83,1600,37082,77,8973,198,220,220,220,220,220,220,220,220,220,220,220,1366,14692,4475,8973,796,4818,8079,13,19608,8079,13,2536,457,524,7,198,220,220,220,220,220,220,220,220,220,220,220,220,220,220,220,302,13,7266,7203,91,1911,22179,7,36311,62,83,853,1039,828,366,1600,1627,828,36521,64,4064,65,4064,67,4064,39,25,4,44,25,4,50,4064,56,1,198,220,220,220,220,220,220,220,220,220,220,220,1267,198,220,220,220,220,220,220,220,611,25113,34,615,414,45444,1,287,1627,25,198,220,220,220,220,220,220,220,220,220,220,220,1366,14692,66,615,414,62,37764,496,8973,796,493,7,1370,13,35312,3419,58,17,12962,198,220,220,220,220,220,220,220,611,25113,8086,268,2288,1,287,1627,25,198,220,220,220,220,220,220,220,220,220,220,220,1366,14692,66,615,414,62,41769,8973,796,493,7,1370,13,35312,3419,58,16,12962,198,220,220,220,220,220,220,220,611,25113,7707,2030,80,1,287,1627,25,198,220,220,220,220,220,220,220,220,220,220,220,1366,14692,7109,62,35324,8973,796,12178,7,1370,13,35312,3419,58,17,12962,198,220,220,220,220,220,220,220,611,25113,7707,1176,1,287,1627,25,198,220,220,220,220,220,220,220,220,220,220,220,1366,14692,7109,62,6477,8973,796,493,7,1370,13,35312,3419,58,17,12962,198,220,220,220,220,220,220,220,611,25113,37,2389,31050,1,287,1627,25,198,220,220,220,220,220,220,220,220,220,220,220,1366,14692,69,312,62,2777,4092,8973,796,12178,7,260,13,19796,439,7,81,1,59,2934,58,10,12,60,30,59,67,59,67,1600,1627,38381,15,12962,198,220,220,220,220,220,220,220,611,25113,37,2389,2173,1,287,1627,25,198,220,220,220,220,220,220,220,220,220,220,220,1366,14692,69,312,62,13033,8973,796,493,7,1370,13,35312,3419,58,12,16,12962,198,220,220,220,220,220,220,220,1303,3497,262,1438,286,262,3623,198,220,220,220,220,220,220,220,611,3623,62,260,25636,13,15699,7,1370,2599,198,220,220,220,220,220,220,220,220,220,220,220,6626,62,1370,796,1627,13,35312,3419,198,220,220,220,220,220,220,220,220,220,220,220,1303,5514,11393,32096,611,262,6518,318,973,198,220,220,220,220,220,220,220,220,220,220,220,3623,62,9630,796,493,7,35312,62,1370,58,16,12962,198,220,220,220,220,220,220,220,220,220,220,220,1949,25,198,220,220,220,220,220,220,220,220,220,220,220,220,220,220,220,1366,14692,70,1386,1,7131,22649,62,9630,60,796,19779,22649,1298,366,27071,22179,7,35312,62,1370,58,18,25,12962,92,198,220,220,220,220,220,220,220,220,220,220,220,2845,12901,12331,25,198,220,220,220,220,220,220,220,220,220,220,220,220,220,220,220,1366,14692,70,1386,1,7131,22649,62,9630,60,796,19779,22649,1298,13538,92,198,220,220,220,220,220,220,220,1303,3497,262,5202,2494,329,6518,198,220,220,220,220,220,220,220,611,5202,62,260,25636,13,15699,7,1370,2599,198,220,220,220,220,220,220,220,220,220,220,220,6626,62,1370,796,1627,13,35312,3419,198,220,220,220,220,220,220,220,220,220,220,220,3623,62,9630,796,493,7,35312,62,1370,58,16,12962,198,220,220,220,220,220,220,220,220,220,220,220,1366,14692,70,1386,1,7131,22649,62,9630,7131,1,11125,8973,796,12178,7,35312,62,1370,58,18,12962,198,220,220,220,220,220,220,220,611,25113,13436,3262,9343,1,287,1627,25,198,220,220,220,220,220,220,220,220,220,220,220,1366,14692,19726,3262,8973,796,20512,7,600,7,1370,13,35312,3419,58,17,60,4008,198,220,220,220,220,220,220,220,1303,9938,262,6518,262,17655,318,900,284,290,17632,257,40364,198,220,220,220,220,220,220,220,1303,284,804,329,262,6518,198,220,220,220,220,220,220,220,611,30736,62,260,25636,13,15699,7,1370,2599,198,220,220,220,220,220,220,220,220,220,220,220,30736,62,9630,796,1627,13,35312,3419,58,17,60,198,220,220,220,220,220,220,220,220,220,220,220,30736,62,17620,796,302,13,5589,576,7,81,1,61,2,47,9615,442,23884,9343,1911,18982,7,17896,62,9630,828,302,13,44,8,198,220,220,220,220,220,220,220,1303,4874,262,17655,6518,6376,318,1900,11,923,10342,329,340,198,220,220,220,220,220,220,220,611,30736,62,17620,25,198,220,220,220,220,220,220,220,220,220,220,220,611,30736,62,17620,13,15699,7,1370,2599,198,220,220,220,220,220,220,220,220,220,220,220,220,220,220,220,1366,14692,6381,10136,8973,796,20512,7,600,7,1370,13,35312,3419,58,12,16,60,4008,198,220,220,220,220,220,220,220,1303,9938,618,262,376,2389,3951,923,26324,510,198,220,220,220,220,220,220,220,611,49909,62,260,25636,13,15699,7,1370,2599,198,220,220,220,220,220,220,220,220,220,220,220,49909,796,2393,3642,658,58,9630,1343,352,1058,60,198,220,220,220,220,220,220,220,220,220,220,220,49909,796,685,22468,7,8367,8,329,1988,287,49909,60,198,220,220,220,220,220,220,220,220,220,220,220,1366,14692,69,312,8973,796,45941,13,18747,7,69,312,8,198,220,220,220,1441,1366,628,198,4299,1620,62,487,83,7,69,312,11,31050,11,923,28,15,11,2245,10779,16,11,4324,2625,3524,7718,1,2599,198,220,220,220,37227,198,220,220,220,35006,281,376,9792,319,281,376,2389,284,651,262,8373,7386,10958,13,198,220,220,220,1439,286,262,7159,389,11902,11,290,2148,1630,625,703,262,376,9792,318,6157,11,355,880,355,1281,12,36948,198,220,220,220,10007,588,4324,5499,290,6632,12,39231,13,628,220,220,220,770,318,1912,319,262,376,9792,2438,416,14316,32379,21048,11,351,19008,284,4197,428,4818,330,31172,13,628,220,220,220,40117,198,220,220,220,24200,438,198,220,220,220,49909,532,399,32152,352,35,7177,198,220,220,220,220,220,220,220,15690,4769,262,3815,286,262,376,2389,198,220,220,220,31050,532,12178,198,220,220,220,220,220,220,220,3862,31050,1022,376,2389,2173,287,4580,43012,198,220,220,220,923,532,493,11,11902,198,220,220,220,220,220,220,220,17962,6376,329,262,376,2389,7177,284,1620,262,376,9792,198,220,220,220,2245,532,493,11,11902,198,220,220,220,220,220,220,220,5268,6376,329,262,376,2389,7177,284,1620,262,376,9792,198,220,220,220,1976,79,69,532,493,11,11902,198,220,220,220,220,220,220,220,15744,262,376,2389,351,1976,27498,284,299,400,16936,1176,286,362,198,220,220,220,4324,532,965,198,220,220,220,220,220,220,220,18291,1958,262,4324,2163,973,284,1429,262,376,2389,13,2896,13185,284,3091,7718,11,543,318,6840,645,25431,13,198,220,220,220,220,220,220,220,383,3891,286,262,4324,5499,1695,460,307,1043,379,25,198,220,220,220,220,220,220,220,3740,1378,31628,13,1416,541,88,13,2398,14,15390,14,1416,541,88,14,35790,14,12683,282,13,28457,13,6494,628,220,220,220,16409,198,220,220,220,35656,198,220,220,220,37227,198,220,220,220,49909,796,45941,13,30073,7,69,312,8,198,220,220,220,611,4324,318,407,6045,290,4324,287,599,82,328,13,28457,13,834,439,834,25,198,220,220,220,220,220,220,220,4324,62,69,796,599,82,328,13,28457,13,1136,62,17497,7,17497,11,49909,13,7857,8,198,220,220,220,220,220,220,220,49909,1635,28,4324,62,69,198,220,220,220,2073,25,198,220,220,220,220,220,220,220,5298,35528,7203,22882,1431,4324,2163,318,407,9177,287,10286,20519,2474,8,198,220,220,220,1303,5345,3815,284,6632,510,284,3599,6376,198,220,220,220,49909,58,25,9688,60,796,657,13,15,198,220,220,220,611,2245,1279,657,25,198,220,220,220,220,220,220,220,1303,1002,356,821,1262,4633,39199,198,220,220,220,220,220,220,220,49909,58,69,312,13,7857,1343,2245,1058,60,796,657,13,15,198,220,220,220,2073,25,198,220,220,220,220,220,220,220,1303,15323,11,6376,351,257,3967,1271,198,220,220,220,220,220,220,220,49909,58,11338,47715,796,657,13,15,198,220,220,220,1303,35006,262,376,9792,198,220,220,220,277,701,796,45941,13,487,83,13,81,487,83,7,69,312,8,198,220,220,220,1100,62,13664,796,18896,7,69,312,8,3373,362,1343,352,198,220,220,220,47764,796,352,13,15,1220,49909,13,7857,1220,31050,198,220,220,220,1303,2980,378,262,8373,7177,198,220,220,220,8373,796,45941,13,21602,10223,7,15,13,15,11,2116,13,25677,14692,1589,3903,8973,1635,47764,11,1100,62,13664,8,198,220,220,220,8373,15853,2116,13,25677,14692,1676,1350,62,19503,80,8973,198,220,220,220,277,701,58,7,35324,18189,277,62,9806,8,1222,357,35324,19841,277,62,1084,15437,796,657,13,15,198,220,220,220,277,701,1635,28,8576,13,15,198,220,220,220,1441,8373,11,277,701,628,198,4299,49909,17,487,83,7,69,312,11,2494,11,19998,11,12429,46265,22046,2599,198,220,220,220,37227,198,220,220,220,10854,281,376,2389,416,9489,281,376,9792,284,7800,262,8373,7386,198,220,220,220,1321,13,31767,22046,389,3804,355,3224,7587,3689,11,198,220,220,220,290,389,9177,355,617,1339,6299,284,4155,262,6460,198,220,220,220,389,4938,357,68,13,70,13,17216,82,284,19232,2494,11,3503,2014,628,220,220,220,1058,17143,49909,25,45941,13,18747,11188,284,262,376,2389,12245,198,220,220,220,1058,17143,2494,25,19232,2494,287,26109,198,220,220,220,1058,17143,19998,25,45941,13,18747,11188,284,262,8373,41701,198,220,220,220,1058,17143,479,86,22046,25,6737,7587,3689,25,198,220,220,220,220,220,220,220,220,220,220,220,220,220,220,220,220,220,220,220,5711,532,16119,262,376,2389,7587,416,4634,262,923,198,220,220,220,220,220,220,220,220,220,220,220,220,220,220,220,220,220,220,220,220,220,220,220,220,220,220,220,286,262,376,2389,284,6632,198,220,220,220,220,220,220,220,220,220,220,220,220,220,220,220,220,220,220,220,1976,263,404,324,532,309,48549,1771,393,407,262,1271,286,35846,198,220,220,220,220,220,220,220,220,220,220,220,220,220,220,220,220,220,220,220,220,220,220,220,220,220,220,220,220,220,2173,318,15229,284,651,32455,2440,198,220,220,220,220,220,220,220,220,220,220,220,220,220,220,220,220,220,220,220,220,220,220,220,220,220,220,220,220,220,6323,287,262,376,9792,198,220,220,220,220,220,220,220,220,220,220,220,220,220,220,220,220,220,220,220,4324,532,26386,4324,5499,2810,416,4600,1416,541,88,13,12683,282,63,198,220,220,220,220,220,220,220,220,220,220,220,220,220,220,220,220,220,220,220,1033,532,18291,6945,281,39682,8106,198,220,220,220,220,220,220,220,220,220,220,220,220,220,220,220,220,220,220,220,8106,532,362,12,83,29291,31577,262,8373,2005,8210,329,257,198,220,220,220,220,220,220,220,220,220,220,220,220,220,220,220,220,220,220,220,220,220,220,220,220,220,220,220,220,4097,1208,8106,198,220,220,220,1058,7783,25,2030,80,62,7568,532,19798,292,1366,14535,351,262,376,9792,10958,198,220,220,220,37227,198,220,220,220,1303,17220,6257,198,220,220,220,649,62,69,312,796,49909,532,45941,13,23913,7,69,312,8,198,220,220,220,611,366,40850,1,287,479,86,22046,25,198,220,220,220,220,220,220,220,5711,796,493,7,46265,22046,14692,40850,8973,1220,357,16,13,15,1220,2494,8,1220,352,68,21,8,198,220,220,220,220,220,220,220,649,62,69,312,58,25,40850,60,796,657,13,15,198,220,220,220,1303,12169,12,15636,262,376,2389,198,220,220,220,611,366,9107,404,324,1,287,479,86,22046,25,198,220,220,220,220,220,220,220,611,479,86,22046,14692,9107,404,324,8973,318,6407,25,198,220,220,220,220,220,220,220,220,220,220,220,1303,15744,262,376,2389,351,1976,27498,284,651,2440,6323,198,220,220,220,220,220,220,220,220,220,220,220,49909,796,45941,13,33295,7,3605,62,69,312,11,45941,13,9107,418,7,11925,7,3605,62,69,312,22305,198,220,220,220,220,220,220,220,220,220,220,220,1303,4619,356,1053,44582,351,1976,27498,11,356,1183,423,284,4296,262,198,220,220,220,220,220,220,220,220,220,220,220,1303,8373,7177,198,220,220,220,220,220,220,220,220,220,220,220,19998,796,599,82,328,13,411,1403,7,69,8897,3976,11,18896,7,69,8897,3976,8,1635,362,8,198,220,220,220,1303,27967,257,4324,2163,284,262,376,2389,198,220,220,220,611,366,17497,1,287,479,86,22046,25,198,220,220,220,220,220,220,220,611,479,86,22046,14692,17497,8973,287,599,82,328,13,28457,13,834,439,834,25,198,220,220,220,220,220,220,220,220,220,220,220,649,62,69,312,1635,28,599,82,328,13,1136,62,17497,7,46265,22046,14692,17497,33116,649,62,69,312,13,7857,8,198,220,220,220,1303,27967,281,39682,8106,319,262,376,2389,198,220,220,220,611,366,11201,1,287,479,86,22046,25,198,220,220,220,220,220,220,220,611,479,86,22046,14692,11201,8973,1875,657,13,15,25,198,220,220,220,220,220,220,220,220,220,220,220,649,62,69,312,1635,28,599,82,328,13,11201,35470,7,11925,7,3605,62,69,312,828,256,559,28,46265,22046,14692,11201,8973,8,198,220,220,220,1303,27967,257,4097,6603,8106,319,262,376,2389,198,220,220,220,611,5855,24455,1,287,479,86,22046,8,290,357,11925,7,46265,22046,14692,24455,8973,8,6624,362,2599,198,220,220,220,220,220,220,220,1877,11,1029,796,23243,7,46265,22046,14692,24455,8973,8,198,220,220,220,220,220,220,220,611,1877,1279,1029,25,198,220,220,220,220,220,220,220,220,220,220,220,649,62,69,312,796,4174,62,4360,353,62,24455,7,3605,62,69,312,11,1877,11,1029,11,2494,8,198,220,220,220,1303,35006,262,376,9792,198,220,220,220,277,701,796,45941,13,487,83,13,81,487,83,7,3605,62,69,312,8,198,220,220,220,1303,3497,262,1103,636,286,262,376,9792,11,290,691,262,1729,12,646,489,3474,1735,198,220,220,220,1103,62,487,83,796,45941,13,8937,7,487,83,58,25,493,7,11925,7,3605,62,69,312,8,1220,362,8,12962,1220,18896,7,3605,62,69,312,8,1635,352,68,18,198,220,220,220,19998,796,599,82,328,13,411,1403,7,69,8897,3976,11,1103,62,487,83,13,7857,8,198,220,220,220,1303,1114,617,1738,11,581,321,11347,23742,510,262,8373,16216,986,198,220,220,220,1103,62,487,83,796,1103,62,487,83,58,37659,13,22046,419,7,69,8897,3976,15437,198,220,220,220,19998,796,45941,13,30619,7,69,8897,3976,8,198,220,220,220,1303,15717,656,257,19798,292,1366,14535,198,220,220,220,2030,80,62,7568,796,279,67,13,6601,19778,7,4895,37,28707,357,25983,8,1298,19998,11,366,5317,6377,1298,1103,62,487,83,30072,198,220,220,220,1441,2030,80,62,7568,628,198,4299,9215,62,3903,6603,7,9319,11,1029,11,2494,11,1502,28,16,2599,198,220,220,220,37227,198,220,220,220,220,220,220,220,317,9518,2196,286,262,18971,9268,4097,6603,8106,3417,994,11,198,220,220,220,220,220,220,220,16573,329,779,351,262,376,2389,6737,13,198,220,220,220,220,220,220,220,2638,1378,1416,541,88,12,27916,2070,13,961,83,704,420,82,13,952,14,23814,14,1537,353,9268,31407,6603,13,6494,198,220,220,220,220,220,220,220,383,7159,389,25,628,220,220,220,220,220,220,220,1058,17143,1877,383,1877,8373,2005,12,2364,11,1813,287,37597,13,198,220,220,220,220,220,220,220,1058,17143,1029,383,1029,8373,2005,12,2364,11,1813,287,37597,13,198,220,220,220,220,220,220,220,1058,17143,2494,383,19232,2494,11,1813,287,26109,13,3574,262,376,47954,11,428,1724,326,198,220,220,220,220,220,220,220,220,220,220,220,220,220,220,220,220,220,220,220,262,34062,286,262,376,2389,31050,318,973,13,198,220,220,220,220,220,220,220,1058,7783,4097,6603,4324,198,220,220,220,37227,198,220,220,220,1303,27131,378,262,17735,30062,8373,198,220,220,220,299,88,80,796,657,13,20,1635,357,4873,1220,357,17,13,15,1635,45941,13,14415,4008,198,220,220,220,1877,796,357,9319,1635,352,68,18,8,1220,299,88,80,198,220,220,220,1029,796,357,8929,1635,352,68,18,8,1220,299,88,80,198,220,220,220,611,1029,1875,352,13,15,25,198,220,220,220,220,220,220,220,5298,35528,7203,11922,8373,2005,12,2364,21695,262,17735,30062,8373,19570,198,220,220,220,275,11,257,796,599,82,328,13,4360,353,7,2875,11,685,9319,11,1029,4357,275,4906,2625,3903,1600,15075,28,25101,8,198,220,220,220,1441,275,11,257,628,198,4299,4174,62,4360,353,62,24455,7,7890,11,1877,11,1029,11,2494,11,1502,28,16,2599,198,220,220,220,37227,198,220,220,220,220,220,220,220,317,9518,18971,9268,4097,6603,8106,11,16573,422,262,1446,541,88,4255,2070,13,628,220,220,220,220,220,220,220,383,4578,1366,9416,262,376,2389,11,543,788,3544,262,629,541,88,6737,198,220,220,220,220,220,220,220,7587,2163,284,4174,262,4875,8106,11,290,5860,262,29083,198,220,220,220,220,220,220,220,376,2389,13,628,220,220,220,220,220,220,220,4091,262,4600,4360,353,62,3903,6603,63,2163,329,3224,7159,13,198,220,220,220,37227,198,220,220,220,275,11,257,796,9215,62,3903,6603,7,9319,11,1029,11,2494,11,1502,28,2875,8,198,220,220,220,331,796,599,82,328,13,1652,346,353,7,65,11,257,11,1366,8,198,220,220,220,1441,331,628,198,198,4299,7716,62,701,65,62,1370,7,35324,11,6934,11,12429,46265,22046,2599,198,220,220,220,37227,15553,326,18616,281,19446,33,2393,329,257,1351,286,198,220,220,220,220,220,220,220,19998,11,5556,17851,1634,5254,13,628,220,220,220,220,220,220,220,479,86,22046,389,3804,355,3224,3689,329,262,10117,65,198,220,220,220,220,220,220,220,15458,13,7383,10879,389,25,628,220,220,220,220,220,220,220,19972,25,20512,198,220,220,220,220,220,220,220,19550,2305,25,12178,198,220,220,220,220,220,220,220,31919,25,493,198,220,220,220,220,220,220,220,1341,10257,1726,25,20512,198,220,220,220,220,220,220,220,1553,19503,80,25,12178,198,220,220,220,220,220,220,220,1553,6477,25,493,198,220,220,220,220,220,220,220,2386,628,220,220,220,220,220,220,220,10007,25,198,220,220,220,220,220,220,220,220,24305,198,220,220,220,220,220,220,220,1058,17143,8373,25,12178,329,8373,287,19805,198,220,220,220,220,220,220,220,1058,17143,6934,25,493,1271,286,6934,284,19386,329,628,220,220,220,220,220,220,220,5860,25,198,220,220,220,220,220,220,220,220,24305,198,220,220,220,220,220,220,220,1058,7783,10117,65,1370,25,965,198,220,220,220,37227,198,220,220,220,1627,796,366,701,76,29164,25,13,19,69,92,6934,29164,92,1911,18982,7,35324,11,6934,8,198,220,220,220,329,1994,11,1988,287,479,86,22046,13,23814,33529,198,220,220,220,220,220,220,220,1627,15853,366,23884,29164,92,1911,18982,7,2539,11,1988,8,198,220,220,220,1627,15853,37082,77,1,198,220,220,220,1441,1627,628,198,4299,497,84,62,66,47467,1096,62,69,8897,3976,7,69,8897,3976,11,17509,871,28,14202,11,299,20910,28,1120,11,12429,46265,22046,2599,198,220,220,220,37227,198,220,220,220,220,220,220,220,371,28399,284,7716,281,19446,33,15458,2393,329,9489,257,2168,286,5254,198,220,220,220,220,220,220,220,319,19998,13,198,220,220,220,37227,198,220,220,220,10117,65,62,8841,796,13538,198,220,220,220,611,17509,871,25,198,220,220,220,220,220,220,220,2593,62,600,796,17509,871,1220,45941,13,9806,7,600,641,871,8,198,220,220,220,220,220,220,220,2823,9127,82,796,45941,13,744,7,77,20910,1220,2593,62,600,737,459,2981,7,600,8,198,220,220,220,2073,25,198,220,220,220,220,220,220,220,2823,9127,82,796,45941,13,12853,7,11925,7,69,8897,3976,828,299,20910,11,288,4906,28,600,8,628,220,220,220,1303,4277,6460,329,477,3404,198,220,220,220,5772,62,11600,796,1391,198,220,220,220,220,220,220,220,366,67,541,2305,1298,352,13,15,11,198,220,220,220,220,220,220,220,366,19726,3262,1298,366,9562,1600,198,220,220,220,220,220,220,220,366,7109,6477,1298,366,940,1600,198,220,220,220,220,220,220,220,366,20545,457,1726,1298,366,9562,1600,198,220,220,220,1782,628,220,220,220,5772,62,11600,13,19119,7,46265,22046,8,198,220,220,220,329,2030,80,11,2823,287,19974,7,69,8897,3976,11,2823,9127,82,2599,198,220,220,220,220,220,220,220,10117,65,62,8841,15853,7716,62,701,65,62,2536,7,19503,80,11,2823,11,12429,17143,62,11600,8,198,220,220,220,220,220,220,220,611,366,19726,3262,1,287,479,86,22046,25,198,220,220,220,220,220,220,220,220,220,220,220,5772,62,11600,14692,19726,3262,8973,796,366,7942,1,198,220,220,220,220,220,220,220,220,220,220,220,10117,65,62,8841,15853,7716,62,701,65,62,2536,7,19503,80,11,2823,11,12429,17143,62,11600,8,628,198,4299,17851,1096,62,69,8897,3976,7,198,220,220,220,19998,11,198,220,220,220,299,20910,28,1120,11,198,220,220,220,17509,871,28,14202,11,198,220,220,220,1176,28,14202,11,198,220,220,220,708,77,62,4868,28,14202,11,198,220,220,220,19550,2305,28,14202,11,198,220,220,220,708,77,28,14202,11,198,220,220,220,19972,28,25101,11,198,220,220,220,1553,28,25101,11,198,220,220,220,17655,28,25101,11,198,2599,198,220,220,220,37227,198,220,220,220,220,220,220,220,15553,326,481,5794,281,19446,15458,2393,284,1620,17851,1634,198,220,220,220,220,220,220,220,5254,11,351,617,13688,319,703,1728,5254,389,6157,13,198,220,220,220,37227,198,220,220,220,10117,65,62,2536,796,13538,198,220,220,220,611,17509,871,318,6045,25,198,220,220,220,220,220,220,220,6934,796,45941,13,12853,7,11925,7,69,8897,3976,828,299,20910,11,288,4906,28,600,8,198,220,220,220,2073,25,198,220,220,220,220,220,220,220,6934,796,45941,13,31166,17034,7,77,20910,1220,17509,871,737,459,2981,7,600,8,628,220,220,220,611,19550,2305,25,198,220,220,220,220,220,220,220,611,708,77,318,6045,25,198,220,220,220,220,220,220,220,220,220,220,220,1303,1002,19550,2305,1332,9167,11,475,645,31919,2288,198,220,220,220,220,220,220,220,220,220,220,220,1303,14275,466,262,4277,16085,198,220,220,220,220,220,220,220,220,220,220,220,19550,2305,62,9288,796,685,15,13,486,11,657,13,16,11,352,13,15,11,513,13,15,11,642,13,15,60,198,220,220,220,220,220,220,220,220,220,220,220,19550,2305,62,32109,796,366,67,541,2305,1,198,220,220,220,220,220,220,220,2073,25,198,220,220,220,220,220,220,220,220,220,220,220,1303,15323,1057,2176,31919,6055,198,220,220,220,220,220,220,220,220,220,220,220,19550,2305,62,9288,796,708,77,62,4868,198,220,220,220,220,220,220,220,220,220,220,220,19550,2305,62,32109,796,366,41769,1,628,220,220,220,611,1553,318,6407,25,198,220,220,220,220,220,220,220,2030,80,62,4868,796,17790,7,69,8897,3976,11,362,8,198,220,220,220,220,220,220,220,3601,7,4868,7,19503,80,62,4868,4008,198,220,220,220,2073,25,198,220,220,220,220,220,220,220,2030,80,62,4868,796,19998,628,220,220,220,1303,9052,625,1123,8373,290,1271,286,6934,198,220,220,220,329,1988,11,2823,9127,287,19974,7,19503,80,62,4868,11,6934,2599,198,220,220,220,220,220,220,220,611,1553,318,6407,25,198,220,220,220,220,220,220,220,220,220,220,220,2030,80,11,1553,62,19503,80,796,1988,198,220,220,220,220,220,220,220,2073,25,198,220,220,220,220,220,220,220,220,220,220,220,2030,80,796,1988,198,220,220,220,220,220,220,220,220,220,220,220,1303,2980,378,3487,13432,198,220,220,220,220,220,220,220,1949,25,198,220,220,220,220,220,220,220,220,220,220,220,2030,80,796,12178,7,19503,80,8,198,220,220,220,220,220,220,220,220,220,220,220,2823,9127,796,493,7,9442,9127,8,198,220,220,220,220,220,220,220,220,220,220,220,611,1553,318,6407,25,198,220,220,220,220,220,220,220,220,220,220,220,220,220,220,220,1553,62,19503,80,796,12178,7,7109,62,19503,80,8,628,220,220,220,220,220,220,220,220,220,220,220,10117,65,62,2536,15853,7716,62,701,65,62,1370,7,19503,80,11,2823,9127,11,12429,4895,20545,457,1726,1298,366,9562,20662,8,628,220,220,220,220,220,220,220,220,220,220,220,611,1553,318,6407,25,198,220,220,220,220,220,220,220,220,220,220,220,220,220,220,220,10117,65,62,2536,15853,7716,62,701,65,62,1370,7,198,220,220,220,220,220,220,220,220,220,220,220,220,220,220,220,220,220,220,220,2030,80,11,2823,9127,11,12429,4895,20545,457,1726,1298,366,7942,1600,366,7109,19503,80,1298,1553,62,19503,80,92,198,220,220,220,220,220,220,220,220,220,220,220,220,220,220,220,1267,628,220,220,220,220,220,220,220,220,220,220,220,611,19550,2305,318,6407,25,198,220,220,220,220,220,220,220,220,220,220,220,220,220,220,220,329,19550,2305,62,8367,287,19550,2305,62,9288,25,198,220,220,220,220,220,220,220,220,220,220,220,220,220,220,220,220,220,220,220,10117,65,62,2536,15853,7716,62,701,65,62,1370,7,198,220,220,220,220,220,220,220,220,220,220,220,220,220,220,220,220,220,220,220,220,220,220,220,2030,80,11,2823,9127,11,12429,90,67,541,2305,62,32109,25,19550,2305,62,8367,92,198,220,220,220,220,220,220,220,220,220,220,220,220,220,220,220,220,220,220,220,1267,628,220,220,220,220,220,220,220,220,220,220,220,611,19972,318,6407,25,198,220,220,220,220,220,220,220,220,220,220,220,220,220,220,220,10117,65,62,2536,15853,7716,62,701,65,62,1370,7,19503,80,11,2823,9127,11,12429,4895,19726,3262,1298,366,7942,20662,8,628,220,220,220,220,220,220,220,220,220,220,220,611,17655,318,6407,25,198,220,220,220,220,220,220,220,220,220,220,220,220,220,220,220,1303,34098,262,17655,8931,319,290,572,198,220,220,220,220,220,220,220,220,220,220,220,220,220,220,220,10117,65,62,2536,15853,7716,62,701,65,62,1370,7,198,220,220,220,220,220,220,220,220,220,220,220,220,220,220,220,220,220,220,220,2030,80,11,2823,9127,11,12429,4895,79,9615,11,16,11,25616,1298,366,9562,20662,198,220,220,220,220,220,220,220,220,220,220,220,220,220,220,220,1267,198,220,220,220,220,220,220,220,220,220,220,220,220,220,220,220,10117,65,62,2536,15853,7716,62,701,65,62,1370,7,198,220,220,220,220,220,220,220,220,220,220,220,220,220,220,220,220,220,220,220,2030,80,11,2823,9127,11,12429,4895,79,9615,11,16,11,25616,1298,366,7942,20662,198,220,220,220,220,220,220,220,220,220,220,220,220,220,220,220,1267,198,220,220,220,220,220,220,220,2845,11052,12331,25,198,220,220,220,220,220,220,220,220,220,220,220,3601,7203,12331,351,366,1343,965,7,8367,4008,628,220,220,220,1441,10117,65,62,2536,628,198,4299,15284,62,18908,1358,62,22355,7,47799,11,299,20910,28,1120,2599,198,220,220,220,37227,198,220,220,220,220,220,220,220,11789,329,26019,262,2938,11812,640,198,220,220,220,220,220,220,220,287,2823,9853,1912,319,262,12245,26,2035,16200,198,220,220,220,220,220,220,220,1627,18929,393,11346,49,13,628,220,220,220,220,220,220,220,10007,25,198,220,220,220,220,220,220,220,220,24305,198,220,220,220,220,220,220,220,12245,532,7177,286,12245,18663,26,304,13,70,13,11346,49,198,220,220,220,220,220,220,220,299,20910,532,11902,493,1271,286,6934,973,329,262,12841,1627,628,220,220,220,220,220,220,220,5860,25,198,220,220,220,220,220,220,220,220,24305,198,220,220,220,220,220,220,220,2823,62,9127,82,532,7177,286,2823,9853,329,1123,8373,198,220,220,220,37227,198,220,220,220,2593,62,600,796,12245,1220,45941,13,9806,7,47799,8,198,220,220,220,2823,62,9127,82,796,45941,13,744,7,77,20910,1220,2593,62,600,737,459,2981,7,600,8,198,220,220,220,1441,2823,62,9127,82,628,628,198,31,19608,330,31172,628,198,31,19608,330,31172,198],"string":"[\n 11748,\n 4818,\n 8079,\n 198,\n 11748,\n 302,\n 198,\n 11748,\n 28686,\n 198,\n 11748,\n 2878,\n 198,\n 6738,\n 4818,\n 330,\n 28958,\n 1330,\n 4818,\n 330,\n 31172,\n 11,\n 2214,\n 198,\n 6738,\n 340,\n 861,\n 10141,\n 1330,\n 17790,\n 11,\n 1720,\n 198,\n 6738,\n 19720,\n 1330,\n 7343,\n 11,\n 360,\n 713,\n 198,\n 198,\n 11748,\n 19798,\n 292,\n 355,\n 279,\n 67,\n 198,\n 11748,\n 299,\n 32152,\n 355,\n 45941,\n 198,\n 11748,\n 9103,\n 26791,\n 198,\n 6738,\n 2603,\n 29487,\n 8019,\n 1330,\n 12972,\n 29487,\n 355,\n 458,\n 83,\n 198,\n 6738,\n 629,\n 541,\n 88,\n 1330,\n 6737,\n 355,\n 599,\n 82,\n 328,\n 198,\n 11748,\n 7110,\n 306,\n 13,\n 34960,\n 62,\n 672,\n 8457,\n 355,\n 467,\n 198,\n 6738,\n 256,\n 80,\n 36020,\n 13,\n 2306,\n 261,\n 1258,\n 2070,\n 1330,\n 256,\n 80,\n 36020,\n 198,\n 11748,\n 3127,\n 87,\n 355,\n 299,\n 87,\n 198,\n 6738,\n 20966,\n 88,\n 28029,\n 11407,\n 1330,\n 14333,\n 11,\n 569,\n 14253,\n 11,\n 367,\n 14253,\n 198,\n 6738,\n 300,\n 76,\n 11147,\n 13,\n 27530,\n 1330,\n 44800,\n 17633,\n 198,\n 198,\n 6738,\n 279,\n 893,\n 806,\n 10141,\n 1330,\n 31878,\n 198,\n 6738,\n 279,\n 893,\n 806,\n 10141,\n 1330,\n 3785,\n 69,\n 9548,\n 355,\n 31246,\n 198,\n 6738,\n 279,\n 893,\n 806,\n 10141,\n 1330,\n 15830,\n 198,\n 6738,\n 279,\n 893,\n 806,\n 10141,\n 13,\n 4443,\n 430,\n 1330,\n 3781,\n 198,\n 6738,\n 279,\n 893,\n 806,\n 10141,\n 1330,\n 13544,\n 364,\n 628,\n 198,\n 198,\n 4299,\n 21136,\n 62,\n 4443,\n 6582,\n 7,\n 34345,\n 11,\n 11387,\n 28,\n 1238,\n 13,\n 15,\n 2599,\n 198,\n 220,\n 220,\n 220,\n 37227,\n 15553,\n 284,\n 1100,\n 287,\n 257,\n 2042,\n 354,\n 343,\n 79,\n 393,\n 33734,\n 9792,\n 44,\n 10958,\n 422,\n 2393,\n 37227,\n 198,\n 220,\n 220,\n 220,\n 1366,\n 14535,\n 796,\n 279,\n 67,\n 13,\n 961,\n 62,\n 40664,\n 7,\n 198,\n 220,\n 220,\n 220,\n 220,\n 220,\n 220,\n 220,\n 29472,\n 11,\n 46728,\n 2676,\n 2625,\n 59,\n 83,\n 1600,\n 3891,\n 28,\n 14692,\n 37,\n 28707,\n 1600,\n 366,\n 5317,\n 6377,\n 33116,\n 14267,\n 8516,\n 28,\n 16,\n 198,\n 220,\n 220,\n 220,\n 1267,\n 198,\n 220,\n 220,\n 220,\n 1441,\n 1366,\n 14535,\n 58,\n 7890,\n 14535,\n 14692,\n 5317,\n 6377,\n 8973,\n 19841,\n 11387,\n 60,\n 628,\n 198,\n 4299,\n 3641,\n 62,\n 66,\n 615,\n 414,\n 7,\n 7890,\n 14535,\n 11,\n 294,\n 411,\n 28,\n 15,\n 13,\n 18,\n 11,\n 15942,\n 577,\n 28,\n 17821,\n 2599,\n 198,\n 220,\n 220,\n 220,\n 37227,\n 9938,\n 82,\n 262,\n 3641,\n 8373,\n 286,\n 257,\n 2141,\n 381,\n 1754,\n 5166,\n 287,\n 31643,\n 376,\n 15972,\n 13871,\n 198,\n 220,\n 220,\n 220,\n 220,\n 220,\n 220,\n 220,\n 290,\n 3769,\n 257,\n 5721,\n 286,\n 11677,\n 19998,\n 13,\n 628,\n 220,\n 220,\n 220,\n 220,\n 220,\n 220,\n 220,\n 8975,\n 262,\n 9103,\n 4917,\n 11387,\n 468,\n 284,\n 307,\n 38304,\n 284,\n 651,\n 262,\n 3641,\n 198,\n 220,\n 220,\n 220,\n 220,\n 220,\n 220,\n 220,\n 8373,\n 9380,\n 13,\n 198,\n 220,\n 220,\n 220,\n 37227,\n 198,\n 220,\n 220,\n 220,\n 1303,\n 9938,\n 262,\n 9103,\n 17509,\n 871,\n 198,\n 220,\n 220,\n 220,\n 3641,\n 62,\n 9630,\n 274,\n 796,\n 9103,\n 26791,\n 13,\n 9630,\n 274,\n 7,\n 7890,\n 14535,\n 14692,\n 5317,\n 6377,\n 33116,\n 294,\n 411,\n 28,\n 400,\n 411,\n 8,\n 198,\n 220,\n 220,\n 220,\n 9103,\n 62,\n 69,\n 8897,\n 3976,\n 796,\n 1366,\n 14535,\n 13,\n 346,\n 420,\n 58,\n 16159,\n 62,\n 9630,\n 274,\n 7131,\n 1,\n 37,\n 28707,\n 8973,\n 198,\n 220,\n 220,\n 220,\n 1303,\n 27131,\n 378,\n 262,\n 3641,\n 8373,\n 355,\n 262,\n 2811,\n 198,\n 220,\n 220,\n 220,\n 3641,\n 796,\n 45941,\n 13,\n 23913,\n 7,\n 36729,\n 62,\n 69,\n 8897,\n 3976,\n 8,\n 198,\n 220,\n 220,\n 220,\n 611,\n 15942,\n 577,\n 318,\n 6407,\n 25,\n 198,\n 220,\n 220,\n 220,\n 220,\n 220,\n 220,\n 220,\n 3601,\n 7203,\n 23656,\n 8373,\n 379,\n 366,\n 1343,\n 965,\n 7,\n 16159,\n 4008,\n 198,\n 220,\n 220,\n 220,\n 1366,\n 14535,\n 14692,\n 34519,\n 31902,\n 8973,\n 796,\n 1366,\n 14535,\n 14692,\n 37,\n 28707,\n 8973,\n 532,\n 3641,\n 628,\n 198,\n 31,\n 19608,\n 330,\n 31172,\n 628,\n 198,\n 31,\n 19608,\n 330,\n 31172,\n 198,\n 4871,\n 20937,\n 25,\n 198,\n 220,\n 220,\n 220,\n 37227,\n 198,\n 220,\n 220,\n 220,\n 6060,\n 9487,\n 329,\n 257,\n 20937,\n 13,\n 9340,\n 82,\n 477,\n 286,\n 262,\n 5981,\n 1321,\n 326,\n 198,\n 220,\n 220,\n 220,\n 8477,\n 257,\n 19446,\n 9367,\n 11,\n 884,\n 355,\n 262,\n 4522,\n 11,\n 644,\n 4572,\n 340,\n 373,\n 7723,\n 198,\n 220,\n 220,\n 220,\n 319,\n 11,\n 290,\n 262,\n 11992,\n 6460,\n 13,\n 628,\n 220,\n 220,\n 220,\n 7875,\n 257,\n 1178,\n 1398,\n 5050,\n 326,\n 481,\n 787,\n 804,\n 19649,\n 3538,\n 884,\n 355,\n 198,\n 220,\n 220,\n 220,\n 262,\n 3128,\n 262,\n 9367,\n 373,\n 7723,\n 290,\n 262,\n 21678,\n 973,\n 13,\n 198,\n 220,\n 220,\n 220,\n 37227,\n 628,\n 220,\n 220,\n 220,\n 4686,\n 25,\n 493,\n 198,\n 220,\n 220,\n 220,\n 4572,\n 25,\n 965,\n 198,\n 220,\n 220,\n 220,\n 49909,\n 25,\n 45941,\n 13,\n 18747,\n 198,\n 220,\n 220,\n 220,\n 3128,\n 25,\n 4818,\n 8079,\n 13,\n 19608,\n 8079,\n 198,\n 220,\n 220,\n 220,\n 6934,\n 25,\n 493,\n 796,\n 657,\n 198,\n 220,\n 220,\n 220,\n 31643,\n 62,\n 37764,\n 496,\n 25,\n 493,\n 796,\n 657,\n 198,\n 220,\n 220,\n 220,\n 31643,\n 62,\n 41769,\n 25,\n 493,\n 796,\n 657,\n 198,\n 220,\n 220,\n 220,\n 31643,\n 62,\n 35324,\n 25,\n 12178,\n 796,\n 657,\n 13,\n 15,\n 198,\n 220,\n 220,\n 220,\n 1553,\n 62,\n 35324,\n 25,\n 12178,\n 796,\n 657,\n 13,\n 15,\n 198,\n 220,\n 220,\n 220,\n 1553,\n 62,\n 6477,\n 25,\n 493,\n 796,\n 657,\n 198,\n 220,\n 220,\n 220,\n 49909,\n 62,\n 13033,\n 25,\n 493,\n 796,\n 657,\n 198,\n 220,\n 220,\n 220,\n 49909,\n 62,\n 2777,\n 4092,\n 25,\n 12178,\n 796,\n 657,\n 13,\n 15,\n 198,\n 220,\n 220,\n 220,\n 17655,\n 25,\n 20512,\n 796,\n 10352,\n 198,\n 220,\n 220,\n 220,\n 19972,\n 25,\n 20512,\n 796,\n 10352,\n 198,\n 220,\n 220,\n 220,\n 21678,\n 25,\n 360,\n 713,\n 796,\n 2214,\n 7,\n 12286,\n 62,\n 69,\n 9548,\n 28,\n 11600,\n 8,\n 198,\n 220,\n 220,\n 220,\n 8106,\n 25,\n 7343,\n 796,\n 2214,\n 7,\n 12286,\n 62,\n 69,\n 9548,\n 28,\n 4868,\n 8,\n 198,\n 220,\n 220,\n 220,\n 1033,\n 25,\n 12178,\n 796,\n 657,\n 13,\n 15,\n 198,\n 220,\n 220,\n 220,\n 1976,\n 263,\n 404,\n 324,\n 25,\n 20512,\n 796,\n 10352,\n 198,\n 220,\n 220,\n 220,\n 4324,\n 25,\n 965,\n 796,\n 13538,\n 628,\n 220,\n 220,\n 220,\n 825,\n 11593,\n 7353,\n 62,\n 15003,\n 834,\n 7,\n 944,\n 2599,\n 198,\n 220,\n 220,\n 220,\n 220,\n 220,\n 220,\n 220,\n 37227,\n 198,\n 220,\n 220,\n 220,\n 220,\n 220,\n 220,\n 220,\n 40480,\n 1444,\n 706,\n 11593,\n 15003,\n 834,\n 318,\n 1444,\n 13,\n 198,\n 220,\n 220,\n 220,\n 220,\n 220,\n 220,\n 220,\n 37227,\n 198,\n 220,\n 220,\n 220,\n 220,\n 220,\n 220,\n 220,\n 1303,\n 35006,\n 376,\n 9792,\n 198,\n 220,\n 220,\n 220,\n 220,\n 220,\n 220,\n 220,\n 2116,\n 13,\n 14681,\n 62,\n 69,\n 312,\n 3419,\n 628,\n 220,\n 220,\n 220,\n 825,\n 11593,\n 22089,\n 30073,\n 834,\n 7,\n 944,\n 2599,\n 198,\n 220,\n 220,\n 220,\n 220,\n 220,\n 220,\n 220,\n 37227,\n 198,\n 220,\n 220,\n 220,\n 220,\n 220,\n 220,\n 220,\n 360,\n 4625,\n 2446,\n 284,\n 4439,\n 257,\n 2769,\n 4866,\n 532,\n 428,\n 481,\n 307,\n 973,\n 618,\n 198,\n 220,\n 220,\n 220,\n 220,\n 220,\n 220,\n 220,\n 29349,\n 3294,\n 20937,\n 5563,\n 13,\n 198,\n 220,\n 220,\n 220,\n 220,\n 220,\n 220,\n 220,\n 1058,\n 7783,\n 25,\n 317,\n 2769,\n 4866,\n 286,\n 262,\n 1459,\n 20937,\n 2134,\n 198,\n 220,\n 220,\n 220,\n 220,\n 220,\n 220,\n 220,\n 37227,\n 628,\n 220,\n 220,\n 220,\n 220,\n 220,\n 220,\n 220,\n 649,\n 62,\n 35836,\n 796,\n 33523,\n 3419,\n 198,\n 220,\n 220,\n 220,\n 220,\n 220,\n 220,\n 220,\n 649,\n 62,\n 35836,\n 13,\n 834,\n 4871,\n 834,\n 796,\n 2116,\n 13,\n 834,\n 4871,\n 834,\n 198,\n 220,\n 220,\n 220,\n 220,\n 220,\n 220,\n 220,\n 649,\n 62,\n 35836,\n 13,\n 834,\n 11600,\n 834,\n 13,\n 19119,\n 7,\n 944,\n 13,\n 834,\n 11600,\n 834,\n 8,\n 198,\n 220,\n 220,\n 220,\n 220,\n 220,\n 220,\n 220,\n 1441,\n 649,\n 62,\n 35836,\n 628,\n 220,\n 220,\n 220,\n 825,\n 2811,\n 7,\n 944,\n 11,\n 1854,\n 2599,\n 198,\n 220,\n 220,\n 220,\n 220,\n 220,\n 220,\n 220,\n 37227,\n 198,\n 220,\n 220,\n 220,\n 220,\n 220,\n 220,\n 220,\n 360,\n 4625,\n 2446,\n 284,\n 763,\n 12,\n 23913,\n 734,\n 393,\n 517,\n 1446,\n 504,\n 287,\n 262,\n 640,\n 7386,\n 13,\n 198,\n 220,\n 220,\n 220,\n 220,\n 220,\n 220,\n 220,\n 1058,\n 17143,\n 584,\n 25,\n 20937,\n 2134,\n 11,\n 393,\n 46545,\n 14,\n 4868,\n 198,\n 220,\n 220,\n 220,\n 220,\n 220,\n 220,\n 220,\n 1058,\n 7783,\n 25,\n 317,\n 649,\n 20937,\n 2134,\n 351,\n 262,\n 763,\n 12,\n 29373,\n 376,\n 2389,\n 198,\n 220,\n 220,\n 220,\n 220,\n 220,\n 220,\n 220,\n 37227,\n 198,\n 220,\n 220,\n 220,\n 220,\n 220,\n 220,\n 220,\n 649,\n 62,\n 35836,\n 796,\n 2116,\n 13,\n 834,\n 22089,\n 30073,\n 834,\n 3419,\n 198,\n 220,\n 220,\n 220,\n 220,\n 220,\n 220,\n 220,\n 1949,\n 25,\n 198,\n 220,\n 220,\n 220,\n 220,\n 220,\n 220,\n 220,\n 220,\n 220,\n 220,\n 220,\n 649,\n 62,\n 35836,\n 13,\n 69,\n 312,\n 796,\n 45941,\n 13,\n 23913,\n 7,\n 847,\n 82,\n 13,\n 2302,\n 437,\n 7,\n 3605,\n 62,\n 35836,\n 13,\n 69,\n 312,\n 828,\n 16488,\n 28,\n 15,\n 8,\n 198,\n 220,\n 220,\n 220,\n 220,\n 220,\n 220,\n 220,\n 220,\n 220,\n 220,\n 220,\n 649,\n 62,\n 35836,\n 13,\n 23913,\n 62,\n 2340,\n 796,\n 685,\n 35836,\n 13,\n 312,\n 329,\n 9367,\n 287,\n 1854,\n 60,\n 198,\n 220,\n 220,\n 220,\n 220,\n 220,\n 220,\n 220,\n 1303,\n 1002,\n 612,\n 318,\n 645,\n 9117,\n 2446,\n 11,\n 788,\n 7048,\n 356,\n 821,\n 1762,\n 351,\n 257,\n 198,\n 220,\n 220,\n 220,\n 220,\n 220,\n 220,\n 220,\n 1303,\n 2060,\n 20937,\n 198,\n 220,\n 220,\n 220,\n 220,\n 220,\n 220,\n 220,\n 2845,\n 3460,\n 4163,\n 12331,\n 25,\n 198,\n 220,\n 220,\n 220,\n 220,\n 220,\n 220,\n 220,\n 220,\n 220,\n 220,\n 220,\n 649,\n 62,\n 35836,\n 13,\n 69,\n 312,\n 796,\n 45941,\n 13,\n 23913,\n 26933,\n 3605,\n 62,\n 35836,\n 13,\n 69,\n 312,\n 11,\n 1854,\n 13,\n 69,\n 312,\n 4357,\n 16488,\n 28,\n 15,\n 8,\n 198,\n 220,\n 220,\n 220,\n 220,\n 220,\n 220,\n 220,\n 220,\n 220,\n 220,\n 220,\n 649,\n 62,\n 35836,\n 13,\n 23913,\n 62,\n 2340,\n 796,\n 685,\n 847,\n 82,\n 13,\n 312,\n 60,\n 198,\n 220,\n 220,\n 220,\n 220,\n 220,\n 220,\n 220,\n 649,\n 62,\n 35836,\n 13,\n 14681,\n 62,\n 69,\n 312,\n 3419,\n 198,\n 220,\n 220,\n 220,\n 220,\n 220,\n 220,\n 220,\n 1441,\n 649,\n 62,\n 35836,\n 628,\n 220,\n 220,\n 220,\n 825,\n 11593,\n 2860,\n 834,\n 7,\n 944,\n 11,\n 584,\n 2599,\n 198,\n 220,\n 220,\n 220,\n 220,\n 220,\n 220,\n 220,\n 37227,\n 198,\n 220,\n 220,\n 220,\n 220,\n 220,\n 220,\n 220,\n 360,\n 4625,\n 2446,\n 284,\n 763,\n 12,\n 2860,\n 734,\n 393,\n 517,\n 1446,\n 504,\n 287,\n 262,\n 640,\n 7386,\n 13,\n 198,\n 220,\n 220,\n 220,\n 220,\n 220,\n 220,\n 220,\n 1058,\n 17143,\n 584,\n 25,\n 20937,\n 2134,\n 11,\n 393,\n 46545,\n 14,\n 4868,\n 198,\n 220,\n 220,\n 220,\n 220,\n 220,\n 220,\n 220,\n 1058,\n 7783,\n 25,\n 317,\n 649,\n 20937,\n 2134,\n 351,\n 262,\n 763,\n 12,\n 29373,\n 376,\n 2389,\n 198,\n 220,\n 220,\n 220,\n 220,\n 220,\n 220,\n 220,\n 37227,\n 198,\n 220,\n 220,\n 220,\n 220,\n 220,\n 220,\n 220,\n 649,\n 62,\n 35836,\n 796,\n 2116,\n 13,\n 834,\n 22089,\n 30073,\n 834,\n 3419,\n 198,\n 220,\n 220,\n 220,\n 220,\n 220,\n 220,\n 220,\n 649,\n 62,\n 35836,\n 13,\n 69,\n 312,\n 796,\n 45941,\n 13,\n 16345,\n 26933,\n 3605,\n 62,\n 35836,\n 13,\n 69,\n 312,\n 11,\n 584,\n 13,\n 69,\n 312,\n 4357,\n 16488,\n 28,\n 15,\n 8,\n 198,\n 220,\n 220,\n 220,\n 220,\n 220,\n 220,\n 220,\n 649,\n 62,\n 35836,\n 13,\n 14681,\n 62,\n 69,\n 312,\n 3419,\n 198,\n 220,\n 220,\n 220,\n 220,\n 220,\n 220,\n 220,\n 1441,\n 649,\n 62,\n 35836,\n 628,\n 220,\n 220,\n 220,\n 825,\n 11593,\n 7266,\n 834,\n 7,\n 944,\n 11,\n 584,\n 2599,\n 198,\n 220,\n 220,\n 220,\n 220,\n 220,\n 220,\n 220,\n 37227,\n 198,\n 220,\n 220,\n 220,\n 220,\n 220,\n 220,\n 220,\n 360,\n 4625,\n 2446,\n 284,\n 34128,\n 1194,\n 20937,\n 422,\n 262,\n 1459,\n 20937,\n 287,\n 262,\n 640,\n 7386,\n 13,\n 198,\n 220,\n 220,\n 220,\n 220,\n 220,\n 220,\n 220,\n 1312,\n 13,\n 68,\n 13,\n 428,\n 9367,\n 532,\n 584,\n 9367,\n 198,\n 220,\n 220,\n 220,\n 220,\n 220,\n 220,\n 220,\n 1058,\n 17143,\n 584,\n 25,\n 20937,\n 2134,\n 11,\n 393,\n 46545,\n 14,\n 4868,\n 198,\n 220,\n 220,\n 220,\n 220,\n 220,\n 220,\n 220,\n 1058,\n 7783,\n 25,\n 317,\n 649,\n 20937,\n 2134,\n 351,\n 262,\n 13284,\n 20216,\n 376,\n 2389,\n 198,\n 220,\n 220,\n 220,\n 220,\n 220,\n 220,\n 220,\n 37227,\n 198,\n 220,\n 220,\n 220,\n 220,\n 220,\n 220,\n 220,\n 649,\n 62,\n 35836,\n 796,\n 2116,\n 13,\n 834,\n 22089,\n 30073,\n 834,\n 3419,\n 198,\n 220,\n 220,\n 220,\n 220,\n 220,\n 220,\n 220,\n 649,\n 62,\n 35836,\n 13,\n 69,\n 312,\n 796,\n 45941,\n 13,\n 7266,\n 83,\n 974,\n 7,\n 3605,\n 62,\n 35836,\n 13,\n 69,\n 312,\n 11,\n 584,\n 13,\n 69,\n 312,\n 8,\n 198,\n 220,\n 220,\n 220,\n 220,\n 220,\n 220,\n 220,\n 649,\n 62,\n 35836,\n 13,\n 14681,\n 62,\n 69,\n 312,\n 3419,\n 198,\n 220,\n 220,\n 220,\n 220,\n 220,\n 220,\n 220,\n 1441,\n 649,\n 62,\n 35836,\n 628,\n 220,\n 220,\n 220,\n 825,\n 34128,\n 62,\n 35324,\n 7,\n 944,\n 11,\n 584,\n 2599,\n 198,\n 220,\n 220,\n 220,\n 220,\n 220,\n 220,\n 220,\n 37227,\n 198,\n 220,\n 220,\n 220,\n 220,\n 220,\n 220,\n 220,\n 11789,\n 284,\n 34128,\n 1194,\n 20937,\n 422,\n 262,\n 1459,\n 287,\n 262,\n 8373,\n 7386,\n 13,\n 198,\n 220,\n 220,\n 220,\n 220,\n 220,\n 220,\n 220,\n 1058,\n 17143,\n 584,\n 25,\n 20937,\n 2134,\n 284,\n 34128,\n 351,\n 198,\n 220,\n 220,\n 220,\n 220,\n 220,\n 220,\n 220,\n 1058,\n 7783,\n 25,\n 317,\n 649,\n 20937,\n 2134,\n 351,\n 262,\n 13284,\n 20216,\n 10958,\n 198,\n 220,\n 220,\n 220,\n 220,\n 220,\n 220,\n 220,\n 37227,\n 198,\n 220,\n 220,\n 220,\n 220,\n 220,\n 220,\n 220,\n 649,\n 62,\n 35836,\n 796,\n 2116,\n 13,\n 834,\n 22089,\n 30073,\n 834,\n 3419,\n 198,\n 220,\n 220,\n 220,\n 220,\n 220,\n 220,\n 220,\n 649,\n 62,\n 35836,\n 13,\n 4443,\n 6582,\n 14692,\n 5317,\n 6377,\n 8973,\n 796,\n 357,\n 198,\n 220,\n 220,\n 220,\n 220,\n 220,\n 220,\n 220,\n 220,\n 220,\n 220,\n 220,\n 649,\n 62,\n 35836,\n 13,\n 4443,\n 6582,\n 14692,\n 5317,\n 6377,\n 8973,\n 532,\n 584,\n 13,\n 4443,\n 6582,\n 14692,\n 5317,\n 6377,\n 8973,\n 198,\n 220,\n 220,\n 220,\n 220,\n 220,\n 220,\n 220,\n 1267,\n 198,\n 220,\n 220,\n 220,\n 220,\n 220,\n 220,\n 220,\n 649,\n 62,\n 35836,\n 13,\n 7266,\n 83,\n 20216,\n 796,\n 584,\n 13,\n 312,\n 198,\n 220,\n 220,\n 220,\n 220,\n 220,\n 220,\n 220,\n 1441,\n 649,\n 62,\n 35836,\n 628,\n 220,\n 220,\n 220,\n 825,\n 751,\n 62,\n 35324,\n 7,\n 944,\n 11,\n 584,\n 2599,\n 198,\n 220,\n 220,\n 220,\n 220,\n 220,\n 220,\n 220,\n 37227,\n 198,\n 220,\n 220,\n 220,\n 220,\n 220,\n 220,\n 220,\n 11789,\n 284,\n 751,\n 1194,\n 20937,\n 422,\n 262,\n 1459,\n 287,\n 262,\n 8373,\n 7386,\n 13,\n 198,\n 220,\n 220,\n 220,\n 220,\n 220,\n 220,\n 220,\n 1058,\n 17143,\n 584,\n 25,\n 20937,\n 2134,\n 284,\n 751,\n 351,\n 198,\n 220,\n 220,\n 220,\n 220,\n 220,\n 220,\n 220,\n 1058,\n 7783,\n 25,\n 317,\n 649,\n 20937,\n 2134,\n 351,\n 262,\n 763,\n 12,\n 29373,\n 10958,\n 198,\n 220,\n 220,\n 220,\n 220,\n 220,\n 220,\n 220,\n 37227,\n 198,\n 220,\n 220,\n 220,\n 220,\n 220,\n 220,\n 220,\n 649,\n 62,\n 35836,\n 796,\n 2116,\n 13,\n 834,\n 22089,\n 30073,\n 834,\n 3419,\n 198,\n 220,\n 220,\n 220,\n 220,\n 220,\n 220,\n 220,\n 649,\n 62,\n 35836,\n 13,\n 4443,\n 6582,\n 14692,\n 5317,\n 6377,\n 8973,\n 796,\n 357,\n 198,\n 220,\n 220,\n 220,\n 220,\n 220,\n 220,\n 220,\n 220,\n 220,\n 220,\n 220,\n 649,\n 62,\n 35836,\n 13,\n 4443,\n 6582,\n 14692,\n 5317,\n 6377,\n 8973,\n 1343,\n 584,\n 13,\n 4443,\n 6582,\n 14692,\n 5317,\n 6377,\n 8973,\n 198,\n 220,\n 220,\n 220,\n 220,\n 220,\n 220,\n 220,\n 1267,\n 198,\n 220,\n 220,\n 220,\n 220,\n 220,\n 220,\n 220,\n 649,\n 62,\n 35836,\n 13,\n 7266,\n 83,\n 20216,\n 796,\n 584,\n 13,\n 312,\n 198,\n 220,\n 220,\n 220,\n 220,\n 220,\n 220,\n 220,\n 1441,\n 649,\n 62,\n 35836,\n 628,\n 220,\n 220,\n 220,\n 2488,\n 4871,\n 24396,\n 198,\n 220,\n 220,\n 220,\n 825,\n 422,\n 62,\n 11600,\n 7,\n 565,\n 82,\n 11,\n 1366,\n 62,\n 11600,\n 2599,\n 198,\n 220,\n 220,\n 220,\n 220,\n 220,\n 220,\n 220,\n 37227,\n 198,\n 220,\n 220,\n 220,\n 220,\n 220,\n 220,\n 220,\n 15553,\n 284,\n 41216,\n 257,\n 20937,\n 2134,\n 422,\n 257,\n 22155,\n 198,\n 220,\n 220,\n 220,\n 220,\n 220,\n 220,\n 220,\n 286,\n 19446,\n 9367,\n 1366,\n 7723,\n 422,\n 4600,\n 29572,\n 62,\n 35836,\n 44646,\n 198,\n 220,\n 220,\n 220,\n 220,\n 220,\n 220,\n 220,\n 1058,\n 17143,\n 1366,\n 62,\n 11600,\n 25,\n 8633,\n 7268,\n 44267,\n 1366,\n 422,\n 19446,\n 198,\n 220,\n 220,\n 220,\n 220,\n 220,\n 220,\n 220,\n 1058,\n 7783,\n 25,\n 20937,\n 2134,\n 198,\n 220,\n 220,\n 220,\n 220,\n 220,\n 220,\n 220,\n 37227,\n 198,\n 220,\n 220,\n 220,\n 220,\n 220,\n 220,\n 220,\n 9367,\n 62,\n 26801,\n 796,\n 537,\n 82,\n 7,\n 1174,\n 7890,\n 62,\n 11600,\n 8,\n 198,\n 220,\n 220,\n 220,\n 220,\n 220,\n 220,\n 220,\n 1441,\n 9367,\n 62,\n 26801,\n 628,\n 220,\n 220,\n 220,\n 2488,\n 4871,\n 24396,\n 198,\n 220,\n 220,\n 220,\n 825,\n 422,\n 62,\n 39568,\n 701,\n 76,\n 7,\n 565,\n 82,\n 11,\n 2393,\n 6978,\n 2599,\n 198,\n 220,\n 220,\n 220,\n 220,\n 220,\n 220,\n 220,\n 37227,\n 198,\n 220,\n 220,\n 220,\n 220,\n 220,\n 220,\n 220,\n 11789,\n 284,\n 41216,\n 257,\n 20937,\n 2134,\n 422,\n 257,\n 19446,\n 9367,\n 2393,\n 13,\n 198,\n 220,\n 220,\n 220,\n 220,\n 220,\n 220,\n 220,\n 2561,\n 3440,\n 262,\n 3951,\n 656,\n 4088,\n 290,\n 21136,\n 262,\n 1366,\n 656,\n 198,\n 220,\n 220,\n 220,\n 220,\n 220,\n 220,\n 220,\n 257,\n 22155,\n 11,\n 543,\n 788,\n 3011,\n 3804,\n 656,\n 257,\n 20937,\n 2134,\n 13,\n 198,\n 220,\n 220,\n 220,\n 220,\n 220,\n 220,\n 220,\n 1058,\n 17143,\n 2393,\n 6978,\n 25,\n 965,\n 3108,\n 284,\n 376,\n 2389,\n 2393,\n 198,\n 220,\n 220,\n 220,\n 220,\n 220,\n 220,\n 220,\n 1058,\n 7783,\n 25,\n 20937,\n 2134,\n 198,\n 220,\n 220,\n 220,\n 220,\n 220,\n 220,\n 220,\n 37227,\n 198,\n 220,\n 220,\n 220,\n 220,\n 220,\n 220,\n 220,\n 351,\n 1280,\n 7,\n 7753,\n 6978,\n 8,\n 355,\n 1100,\n 62,\n 7753,\n 25,\n 198,\n 220,\n 220,\n 220,\n 220,\n 220,\n 220,\n 220,\n 220,\n 220,\n 220,\n 220,\n 1366,\n 62,\n 11600,\n 796,\n 21136,\n 62,\n 35836,\n 7,\n 961,\n 62,\n 7753,\n 13,\n 961,\n 6615,\n 28955,\n 198,\n 220,\n 220,\n 220,\n 220,\n 220,\n 220,\n 220,\n 9367,\n 62,\n 26801,\n 796,\n 537,\n 82,\n 7,\n 1174,\n 7890,\n 62,\n 11600,\n 8,\n 198,\n 220,\n 220,\n 220,\n 220,\n 220,\n 220,\n 220,\n 1441,\n 9367,\n 62,\n 26801,\n 628,\n 220,\n 220,\n 220,\n 2488,\n 4871,\n 24396,\n 198,\n 220,\n 220,\n 220,\n 825,\n 422,\n 62,\n 27729,\n 293,\n 7,\n 565,\n 82,\n 11,\n 2393,\n 6978,\n 2599,\n 198,\n 220,\n 220,\n 220,\n 220,\n 220,\n 220,\n 220,\n 37227,\n 198,\n 220,\n 220,\n 220,\n 220,\n 220,\n 220,\n 220,\n 11789,\n 284,\n 2251,\n 257,\n 20937,\n 2134,\n 422,\n 257,\n 4271,\n 2298,\n 992,\n 198,\n 220,\n 220,\n 220,\n 220,\n 220,\n 220,\n 220,\n 20937,\n 13,\n 198,\n 220,\n 220,\n 220,\n 220,\n 220,\n 220,\n 220,\n 1058,\n 17143,\n 2393,\n 6978,\n 25,\n 3108,\n 284,\n 262,\n 20937,\n 2298,\n 293,\n 198,\n 220,\n 220,\n 220,\n 220,\n 220,\n 220,\n 220,\n 1058,\n 7783,\n 25,\n 4554,\n 286,\n 262,\n 20937,\n 2134,\n 198,\n 220,\n 220,\n 220,\n 220,\n 220,\n 220,\n 220,\n 37227,\n 198,\n 220,\n 220,\n 220,\n 220,\n 220,\n 220,\n 220,\n 9367,\n 62,\n 26801,\n 796,\n 31878,\n 13,\n 961,\n 62,\n 26801,\n 7,\n 7753,\n 6978,\n 8,\n 198,\n 220,\n 220,\n 220,\n 220,\n 220,\n 220,\n 220,\n 611,\n 318,\n 39098,\n 7,\n 35836,\n 62,\n 26801,\n 11,\n 20937,\n 8,\n 318,\n 10352,\n 25,\n 198,\n 220,\n 220,\n 220,\n 220,\n 220,\n 220,\n 220,\n 220,\n 220,\n 220,\n 220,\n 5298,\n 35528,\n 7203,\n 8979,\n 318,\n 407,\n 257,\n 20937,\n 2134,\n 26,\n 23884,\n 1911,\n 18982,\n 7,\n 4906,\n 7,\n 35836,\n 62,\n 26801,\n 22305,\n 198,\n 220,\n 220,\n 220,\n 220,\n 220,\n 220,\n 220,\n 2073,\n 25,\n 198,\n 220,\n 220,\n 220,\n 220,\n 220,\n 220,\n 220,\n 220,\n 220,\n 220,\n 220,\n 1441,\n 9367,\n 62,\n 26801,\n 628,\n 220,\n 220,\n 220,\n 2488,\n 4871,\n 24396,\n 198,\n 220,\n 220,\n 220,\n 825,\n 422,\n 62,\n 47960,\n 7,\n 565,\n 82,\n 11,\n 6569,\n 62,\n 6978,\n 11,\n 26678,\n 62,\n 26801,\n 28,\n 14202,\n 2599,\n 198,\n 220,\n 220,\n 220,\n 220,\n 220,\n 220,\n 220,\n 37227,\n 198,\n 220,\n 220,\n 220,\n 220,\n 220,\n 220,\n 220,\n 11789,\n 284,\n 41216,\n 257,\n 20937,\n 2134,\n 422,\n 257,\n 6569,\n 4382,\n 13,\n 198,\n 220,\n 220,\n 220,\n 220,\n 220,\n 220,\n 220,\n 7875,\n 262,\n 3038,\n 284,\n 1208,\n 281,\n 4554,\n 286,\n 257,\n 5772,\n 12125,\n 33825,\n 11792,\n 11,\n 543,\n 561,\n 307,\n 198,\n 220,\n 220,\n 220,\n 220,\n 220,\n 220,\n 220,\n 4465,\n 287,\n 257,\n 347,\n 963,\n 13,\n 1002,\n 4844,\n 318,\n 14275,\n 11,\n 281,\n 4554,\n 481,\n 307,\n 2727,\n 13,\n 628,\n 220,\n 220,\n 220,\n 220,\n 220,\n 220,\n 220,\n 1058,\n 17143,\n 6569,\n 62,\n 6978,\n 25,\n 965,\n 6569,\n 3108,\n 284,\n 262,\n 2393,\n 198,\n 220,\n 220,\n 220,\n 220,\n 220,\n 220,\n 220,\n 1058,\n 17143,\n 26678,\n 62,\n 26801,\n 25,\n 11902,\n 4578,\n 284,\n 5127,\n 257,\n 5772,\n 12125,\n 33825,\n 11792,\n 2134,\n 198,\n 220,\n 220,\n 220,\n 220,\n 220,\n 220,\n 220,\n 1058,\n 7783,\n 25,\n 20937,\n 2134,\n 422,\n 6569,\n 33734,\n 9792,\n 44,\n 2393,\n 198,\n 220,\n 220,\n 220,\n 220,\n 220,\n 220,\n 220,\n 37227,\n 198,\n 220,\n 220,\n 220,\n 220,\n 220,\n 220,\n 220,\n 611,\n 26678,\n 62,\n 26801,\n 318,\n 6045,\n 25,\n 198,\n 220,\n 220,\n 220,\n 220,\n 220,\n 220,\n 220,\n 220,\n 220,\n 220,\n 220,\n 4277,\n 62,\n 2539,\n 6978,\n 796,\n 28686,\n 13,\n 6978,\n 13,\n 22179,\n 7,\n 418,\n 13,\n 6978,\n 13,\n 11201,\n 392,\n 7220,\n 7203,\n 93,\n 12340,\n 27071,\n 45824,\n 14,\n 312,\n 62,\n 3808,\n 64,\n 13,\n 12984,\n 4943,\n 198,\n 220,\n 220,\n 220,\n 220,\n 220,\n 220,\n 220,\n 220,\n 220,\n 220,\n 220,\n 2583,\n 3672,\n 796,\n 5128,\n 7203,\n 5492,\n 2148,\n 6569,\n 2583,\n 3672,\n 25,\n 220,\n 220,\n 220,\n 366,\n 8,\n 198,\n 220,\n 220,\n 220,\n 220,\n 220,\n 220,\n 220,\n 220,\n 220,\n 220,\n 220,\n 20579,\n 796,\n 5128,\n 7203,\n 5492,\n 2148,\n 17594,\n 25,\n 220,\n 220,\n 220,\n 220,\n 220,\n 220,\n 220,\n 220,\n 220,\n 220,\n 220,\n 220,\n 220,\n 366,\n 8,\n 198,\n 220,\n 220,\n 220,\n 220,\n 220,\n 220,\n 220,\n 220,\n 220,\n 220,\n 220,\n 26678,\n 62,\n 33692,\n 796,\n 19779,\n 4774,\n 3672,\n 1298,\n 2583,\n 3672,\n 11,\n 366,\n 29460,\n 1298,\n 20579,\n 92,\n 198,\n 220,\n 220,\n 220,\n 220,\n 220,\n 220,\n 220,\n 220,\n 220,\n 220,\n 220,\n 611,\n 28686,\n 13,\n 6978,\n 13,\n 4468,\n 576,\n 7,\n 12286,\n 62,\n 2539,\n 6978,\n 8,\n 318,\n 6407,\n 25,\n 198,\n 220,\n 220,\n 220,\n 220,\n 220,\n 220,\n 220,\n 220,\n 220,\n 220,\n 220,\n 220,\n 220,\n 220,\n 220,\n 26678,\n 62,\n 33692,\n 14692,\n 2539,\n 62,\n 34345,\n 8973,\n 796,\n 4277,\n 62,\n 2539,\n 6978,\n 198,\n 220,\n 220,\n 220,\n 220,\n 220,\n 220,\n 220,\n 220,\n 220,\n 220,\n 220,\n 2073,\n 25,\n 198,\n 220,\n 220,\n 220,\n 220,\n 220,\n 220,\n 220,\n 220,\n 220,\n 220,\n 220,\n 220,\n 220,\n 220,\n 220,\n 9206,\n 796,\n 5128,\n 7203,\n 5492,\n 2148,\n 9206,\n 25,\n 220,\n 220,\n 220,\n 220,\n 220,\n 220,\n 220,\n 220,\n 220,\n 220,\n 220,\n 220,\n 220,\n 366,\n 8,\n 198,\n 220,\n 220,\n 220,\n 220,\n 220,\n 220,\n 220,\n 220,\n 220,\n 220,\n 220,\n 220,\n 220,\n 220,\n 220,\n 26678,\n 62,\n 33692,\n 14692,\n 28712,\n 8973,\n 796,\n 9206,\n 198,\n 220,\n 220,\n 220,\n 220,\n 220,\n 220,\n 220,\n 220,\n 220,\n 220,\n 220,\n 26678,\n 62,\n 26801,\n 796,\n 31878,\n 13,\n 36510,\n 11792,\n 7,\n 1174,\n 45824,\n 62,\n 33692,\n 8,\n 198,\n 220,\n 220,\n 220,\n 220,\n 220,\n 220,\n 220,\n 1303,\n 2547,\n 325,\n 262,\n 9367,\n 1366,\n 422,\n 6569,\n 2393,\n 198,\n 220,\n 220,\n 220,\n 220,\n 220,\n 220,\n 220,\n 1366,\n 62,\n 11600,\n 796,\n 21136,\n 62,\n 35836,\n 7,\n 45824,\n 62,\n 26801,\n 13,\n 9654,\n 62,\n 47960,\n 7,\n 47960,\n 62,\n 6978,\n 4008,\n 198,\n 220,\n 220,\n 220,\n 220,\n 220,\n 220,\n 220,\n 9367,\n 62,\n 26801,\n 796,\n 537,\n 82,\n 7,\n 1174,\n 7890,\n 62,\n 11600,\n 8,\n 198,\n 220,\n 220,\n 220,\n 220,\n 220,\n 220,\n 220,\n 1441,\n 9367,\n 62,\n 26801,\n 628,\n 220,\n 220,\n 220,\n 825,\n 284,\n 62,\n 7753,\n 7,\n 944,\n 11,\n 2393,\n 6978,\n 11,\n 5794,\n 2625,\n 88,\n 43695,\n 1,\n 2599,\n 198,\n 220,\n 220,\n 220,\n 220,\n 220,\n 220,\n 220,\n 37227,\n 11789,\n 284,\n 10285,\n 1366,\n 284,\n 575,\n 2390,\n 43,\n 5794,\n 13,\n 198,\n 220,\n 220,\n 220,\n 220,\n 220,\n 220,\n 220,\n 220,\n 220,\n 220,\n 220,\n 49751,\n 389,\n 6338,\n 3066,\n 11,\n 475,\n 198,\n 220,\n 220,\n 220,\n 220,\n 220,\n 220,\n 220,\n 220,\n 220,\n 220,\n 220,\n 460,\n 635,\n 307,\n 14275,\n 13,\n 628,\n 220,\n 220,\n 220,\n 220,\n 220,\n 220,\n 220,\n 220,\n 220,\n 220,\n 220,\n 10007,\n 25,\n 198,\n 220,\n 220,\n 220,\n 220,\n 220,\n 220,\n 220,\n 220,\n 220,\n 220,\n 220,\n 41436,\n 198,\n 220,\n 220,\n 220,\n 220,\n 220,\n 220,\n 220,\n 220,\n 220,\n 220,\n 220,\n 1058,\n 17143,\n 2393,\n 6978,\n 532,\n 965,\n 3108,\n 284,\n 331,\n 43695,\n 2393,\n 198,\n 220,\n 220,\n 220,\n 220,\n 220,\n 220,\n 220,\n 220,\n 220,\n 220,\n 220,\n 1058,\n 17143,\n 5794,\n 532,\n 965,\n 2853,\n 10720,\n 262,\n 15582,\n 973,\n 329,\n 30231,\n 13,\n 2896,\n 13185,\n 284,\n 575,\n 2390,\n 43,\n 13,\n 198,\n 220,\n 220,\n 220,\n 220,\n 220,\n 220,\n 220,\n 37227,\n 198,\n 220,\n 220,\n 220,\n 220,\n 220,\n 220,\n 220,\n 611,\n 366,\n 526,\n 407,\n 287,\n 2393,\n 6978,\n 25,\n 198,\n 220,\n 220,\n 220,\n 220,\n 220,\n 220,\n 220,\n 220,\n 220,\n 220,\n 220,\n 611,\n 5794,\n 6624,\n 366,\n 17752,\n 1298,\n 198,\n 220,\n 220,\n 220,\n 220,\n 220,\n 220,\n 220,\n 220,\n 220,\n 220,\n 220,\n 220,\n 220,\n 220,\n 220,\n 2393,\n 6978,\n 15853,\n 27071,\n 17752,\n 1,\n 198,\n 220,\n 220,\n 220,\n 220,\n 220,\n 220,\n 220,\n 220,\n 220,\n 220,\n 220,\n 2073,\n 25,\n 198,\n 220,\n 220,\n 220,\n 220,\n 220,\n 220,\n 220,\n 220,\n 220,\n 220,\n 220,\n 220,\n 220,\n 220,\n 220,\n 2393,\n 6978,\n 15853,\n 27071,\n 88,\n 4029,\n 1,\n 198,\n 220,\n 220,\n 220,\n 220,\n 220,\n 220,\n 220,\n 611,\n 5794,\n 6624,\n 366,\n 17752,\n 1298,\n 198,\n 220,\n 220,\n 220,\n 220,\n 220,\n 220,\n 220,\n 220,\n 220,\n 220,\n 220,\n 6260,\n 796,\n 31878,\n 13,\n 39455,\n 62,\n 17752,\n 198,\n 220,\n 220,\n 220,\n 220,\n 220,\n 220,\n 220,\n 2073,\n 25,\n 198,\n 220,\n 220,\n 220,\n 220,\n 220,\n 220,\n 220,\n 220,\n 220,\n 220,\n 220,\n 6260,\n 796,\n 31878,\n 13,\n 39455,\n 62,\n 88,\n 43695,\n 198,\n 220,\n 220,\n 220,\n 220,\n 220,\n 220,\n 220,\n 6260,\n 7,\n 7753,\n 6978,\n 11,\n 2116,\n 13,\n 834,\n 11600,\n 834,\n 8,\n 628,\n 220,\n 220,\n 220,\n 825,\n 284,\n 62,\n 27729,\n 293,\n 7,\n 944,\n 11,\n 2393,\n 6978,\n 28,\n 14202,\n 11,\n 12429,\n 46265,\n 22046,\n 2599,\n 198,\n 220,\n 220,\n 220,\n 220,\n 220,\n 220,\n 220,\n 37227,\n 198,\n 220,\n 220,\n 220,\n 220,\n 220,\n 220,\n 220,\n 12346,\n 829,\n 262,\n 20937,\n 2134,\n 351,\n 262,\n 1693,\n 8019,\n 29908,\n 9177,\n 198,\n 220,\n 220,\n 220,\n 220,\n 220,\n 220,\n 220,\n 287,\n 31878,\n 13,\n 198,\n 220,\n 220,\n 220,\n 220,\n 220,\n 220,\n 220,\n 1058,\n 17143,\n 2393,\n 6978,\n 25,\n 11902,\n 4578,\n 284,\n 2298,\n 293,\n 284,\n 13,\n 2896,\n 13185,\n 284,\n 262,\n 4686,\n 13,\n 79,\n 41582,\n 198,\n 220,\n 220,\n 220,\n 220,\n 220,\n 220,\n 220,\n 1058,\n 17143,\n 479,\n 86,\n 22046,\n 25,\n 3224,\n 6460,\n 329,\n 262,\n 2298,\n 293,\n 4905,\n 198,\n 220,\n 220,\n 220,\n 220,\n 220,\n 220,\n 220,\n 37227,\n 198,\n 220,\n 220,\n 220,\n 220,\n 220,\n 220,\n 220,\n 611,\n 2393,\n 6978,\n 318,\n 6045,\n 25,\n 198,\n 220,\n 220,\n 220,\n 220,\n 220,\n 220,\n 220,\n 220,\n 220,\n 220,\n 220,\n 2393,\n 6978,\n 796,\n 45144,\n 27422,\n 79,\n 41582,\n 1911,\n 18982,\n 7,\n 944,\n 13,\n 312,\n 8,\n 198,\n 220,\n 220,\n 220,\n 220,\n 220,\n 220,\n 220,\n 31878,\n 13,\n 21928,\n 62,\n 26801,\n 7,\n 944,\n 11,\n 2393,\n 6978,\n 11,\n 12429,\n 46265,\n 22046,\n 8,\n 628,\n 220,\n 220,\n 220,\n 825,\n 1429,\n 62,\n 69,\n 312,\n 7,\n 944,\n 11,\n 12429,\n 46265,\n 22046,\n 2599,\n 198,\n 220,\n 220,\n 220,\n 220,\n 220,\n 220,\n 220,\n 37227,\n 198,\n 220,\n 220,\n 220,\n 220,\n 220,\n 220,\n 220,\n 35006,\n 281,\n 376,\n 9792,\n 319,\n 262,\n 376,\n 2389,\n 284,\n 7800,\n 262,\n 8373,\n 7386,\n 10958,\n 13,\n 198,\n 220,\n 220,\n 220,\n 220,\n 220,\n 220,\n 220,\n 31767,\n 22046,\n 389,\n 3804,\n 656,\n 262,\n 376,\n 2389,\n 7587,\n 11,\n 543,\n 481,\n 20957,\n 262,\n 198,\n 220,\n 220,\n 220,\n 220,\n 220,\n 220,\n 220,\n 20937,\n 12608,\n 13,\n 198,\n 220,\n 220,\n 220,\n 220,\n 220,\n 220,\n 220,\n 1058,\n 17143,\n 479,\n 86,\n 22046,\n 25,\n 32233,\n 21179,\n 7159,\n 329,\n 7587,\n 262,\n 376,\n 2389,\n 198,\n 220,\n 220,\n 220,\n 220,\n 220,\n 220,\n 220,\n 37227,\n 198,\n 220,\n 220,\n 220,\n 220,\n 220,\n 220,\n 220,\n 1303,\n 27131,\n 378,\n 262,\n 8373,\n 41701,\n 198,\n 220,\n 220,\n 220,\n 220,\n 220,\n 220,\n 220,\n 19998,\n 796,\n 45941,\n 13,\n 21602,\n 10223,\n 7,\n 198,\n 220,\n 220,\n 220,\n 220,\n 220,\n 220,\n 220,\n 220,\n 220,\n 220,\n 220,\n 2116,\n 13,\n 66,\n 615,\n 414,\n 62,\n 35324,\n 11,\n 2116,\n 13,\n 66,\n 615,\n 414,\n 62,\n 35324,\n 1343,\n 352,\n 13,\n 15,\n 11,\n 18896,\n 7,\n 944,\n 13,\n 69,\n 312,\n 8,\n 198,\n 220,\n 220,\n 220,\n 220,\n 220,\n 220,\n 220,\n 1267,\n 198,\n 220,\n 220,\n 220,\n 220,\n 220,\n 220,\n 220,\n 1303,\n 27131,\n 378,\n 262,\n 640,\n 41701,\n 198,\n 220,\n 220,\n 220,\n 220,\n 220,\n 220,\n 220,\n 640,\n 796,\n 45941,\n 13,\n 21602,\n 10223,\n 7,\n 15,\n 13,\n 15,\n 11,\n 2116,\n 13,\n 69,\n 312,\n 62,\n 2777,\n 4092,\n 1635,\n 2116,\n 13,\n 69,\n 312,\n 62,\n 13033,\n 11,\n 2116,\n 13,\n 69,\n 312,\n 62,\n 13033,\n 8,\n 198,\n 220,\n 220,\n 220,\n 220,\n 220,\n 220,\n 220,\n 1429,\n 62,\n 4868,\n 796,\n 14631,\n 17497,\n 1600,\n 366,\n 24455,\n 1600,\n 366,\n 11201,\n 1600,\n 366,\n 9107,\n 404,\n 324,\n 8973,\n 198,\n 220,\n 220,\n 220,\n 220,\n 220,\n 220,\n 220,\n 1429,\n 62,\n 11600,\n 796,\n 1391,\n 198,\n 220,\n 220,\n 220,\n 220,\n 220,\n 220,\n 220,\n 220,\n 220,\n 220,\n 220,\n 1994,\n 25,\n 1988,\n 329,\n 1994,\n 11,\n 1988,\n 287,\n 2116,\n 13,\n 834,\n 11600,\n 834,\n 13,\n 23814,\n 3419,\n 611,\n 1994,\n 287,\n 1429,\n 62,\n 4868,\n 198,\n 220,\n 220,\n 220,\n 220,\n 220,\n 220,\n 220,\n 1782,\n 198,\n 220,\n 220,\n 220,\n 220,\n 220,\n 220,\n 220,\n 1303,\n 3827,\n 13154,\n 351,\n 2836,\n 6460,\n 198,\n 220,\n 220,\n 220,\n 220,\n 220,\n 220,\n 220,\n 1429,\n 62,\n 11600,\n 13,\n 19119,\n 7,\n 1174,\n 46265,\n 22046,\n 8,\n 198,\n 220,\n 220,\n 220,\n 220,\n 220,\n 220,\n 220,\n 20218,\n 62,\n 69,\n 312,\n 796,\n 45941,\n 13,\n 30073,\n 7,\n 944,\n 13,\n 69,\n 312,\n 8,\n 198,\n 220,\n 220,\n 220,\n 220,\n 220,\n 220,\n 220,\n 2116,\n 13,\n 4443,\n 6582,\n 796,\n 49909,\n 17,\n 487,\n 83,\n 7,\n 198,\n 220,\n 220,\n 220,\n 220,\n 220,\n 220,\n 220,\n 220,\n 220,\n 220,\n 220,\n 20218,\n 62,\n 69,\n 312,\n 11,\n 352,\n 13,\n 15,\n 1220,\n 2116,\n 13,\n 69,\n 312,\n 62,\n 2777,\n 4092,\n 11,\n 19998,\n 11,\n 12429,\n 14681,\n 62,\n 11600,\n 198,\n 220,\n 220,\n 220,\n 220,\n 220,\n 220,\n 220,\n 1267,\n 198,\n 220,\n 220,\n 220,\n 220,\n 220,\n 220,\n 220,\n 2116,\n 13,\n 69,\n 312,\n 62,\n 7568,\n 796,\n 279,\n 67,\n 13,\n 6601,\n 19778,\n 7,\n 4895,\n 7575,\n 357,\n 385,\n 8,\n 1298,\n 640,\n 1635,\n 352,\n 68,\n 21,\n 11,\n 366,\n 37,\n 2389,\n 1298,\n 20218,\n 62,\n 69,\n 312,\n 30072,\n 628,\n 220,\n 220,\n 220,\n 825,\n 1626,\n 62,\n 2435,\n 7,\n 944,\n 11,\n 3128,\n 62,\n 9521,\n 2599,\n 198,\n 220,\n 220,\n 220,\n 220,\n 220,\n 220,\n 220,\n 37227,\n 198,\n 220,\n 220,\n 220,\n 220,\n 220,\n 220,\n 220,\n 15553,\n 329,\n 13213,\n 286,\n 262,\n 9367,\n 373,\n 2077,\n 1022,\n 198,\n 220,\n 220,\n 220,\n 220,\n 220,\n 220,\n 220,\n 257,\n 7368,\n 3128,\n 2837,\n 287,\n 1227,\n 14,\n 820,\n 14,\n 1941,\n 11,\n 287,\n 262,\n 5794,\n 198,\n 220,\n 220,\n 220,\n 220,\n 220,\n 220,\n 220,\n 8702,\n 14,\n 2931,\n 14,\n 2919,\n 329,\n 3035,\n 860,\n 400,\n 11,\n 3648,\n 13,\n 198,\n 220,\n 220,\n 220,\n 220,\n 220,\n 220,\n 220,\n 1058,\n 17143,\n 3128,\n 62,\n 9521,\n 25,\n 1351,\n 7268,\n 262,\n 3726,\n 290,\n 886,\n 3128,\n 13042,\n 198,\n 220,\n 220,\n 220,\n 220,\n 220,\n 220,\n 220,\n 1058,\n 7783,\n 25,\n 20512,\n 532,\n 6407,\n 611,\n 1626,\n 2837,\n 11,\n 10352,\n 4306,\n 198,\n 220,\n 220,\n 220,\n 220,\n 220,\n 220,\n 220,\n 37227,\n 198,\n 220,\n 220,\n 220,\n 220,\n 220,\n 220,\n 220,\n 1949,\n 25,\n 198,\n 220,\n 220,\n 220,\n 220,\n 220,\n 220,\n 220,\n 220,\n 220,\n 220,\n 220,\n 1903,\n 796,\n 4818,\n 8079,\n 13,\n 19608,\n 8079,\n 13,\n 2536,\n 457,\n 524,\n 7,\n 4475,\n 62,\n 9521,\n 58,\n 15,\n 4357,\n 36521,\n 76,\n 14,\n 4,\n 67,\n 14,\n 4,\n 88,\n 4943,\n 198,\n 220,\n 220,\n 220,\n 220,\n 220,\n 220,\n 220,\n 2845,\n 25,\n 198,\n 220,\n 220,\n 220,\n 220,\n 220,\n 220,\n 220,\n 220,\n 220,\n 220,\n 220,\n 1903,\n 796,\n 4818,\n 8079,\n 13,\n 19608,\n 8079,\n 7,\n 16,\n 11,\n 352,\n 11,\n 352,\n 8,\n 198,\n 220,\n 220,\n 220,\n 220,\n 220,\n 220,\n 220,\n 1949,\n 25,\n 198,\n 220,\n 220,\n 220,\n 220,\n 220,\n 220,\n 220,\n 220,\n 220,\n 220,\n 220,\n 2739,\n 796,\n 4818,\n 8079,\n 13,\n 19608,\n 8079,\n 13,\n 2536,\n 457,\n 524,\n 7,\n 4475,\n 62,\n 9521,\n 58,\n 16,\n 4357,\n 36521,\n 76,\n 14,\n 4,\n 67,\n 14,\n 4,\n 88,\n 4943,\n 198,\n 220,\n 220,\n 220,\n 220,\n 220,\n 220,\n 220,\n 2845,\n 25,\n 198,\n 220,\n 220,\n 220,\n 220,\n 220,\n 220,\n 220,\n 220,\n 220,\n 220,\n 220,\n 2739,\n 796,\n 4818,\n 8079,\n 13,\n 19608,\n 8079,\n 7,\n 24214,\n 11,\n 352,\n 11,\n 352,\n 8,\n 198,\n 220,\n 220,\n 220,\n 220,\n 220,\n 220,\n 220,\n 1441,\n 1903,\n 19841,\n 2116,\n 13,\n 4475,\n 19841,\n 2739,\n 628,\n 220,\n 220,\n 220,\n 825,\n 318,\n 62,\n 10378,\n 33342,\n 7,\n 944,\n 11,\n 1006,\n 11,\n 686,\n 72,\n 28,\n 14202,\n 11,\n 42435,\n 28,\n 14202,\n 2599,\n 198,\n 220,\n 220,\n 220,\n 220,\n 220,\n 220,\n 220,\n 37227,\n 198,\n 220,\n 220,\n 220,\n 220,\n 220,\n 220,\n 220,\n 15553,\n 329,\n 13213,\n 611,\n 262,\n 6737,\n 287,\n 428,\n 20937,\n 318,\n 1342,\n 198,\n 220,\n 220,\n 220,\n 220,\n 220,\n 220,\n 220,\n 621,\n 326,\n 286,\n 1194,\n 9367,\n 13,\n 770,\n 318,\n 1760,\n 416,\n 257,\n 2829,\n 7208,\n 198,\n 220,\n 220,\n 220,\n 220,\n 220,\n 220,\n 220,\n 286,\n 262,\n 2811,\n 286,\n 838,\n 4387,\n 17509,\n 871,\n 287,\n 262,\n 734,\n 5444,\n 430,\n 13,\n 1002,\n 198,\n 220,\n 220,\n 220,\n 220,\n 220,\n 220,\n 220,\n 262,\n 1459,\n 9367,\n 318,\n 1342,\n 8157,\n 621,\n 262,\n 4941,\n 416,\n 262,\n 198,\n 220,\n 220,\n 220,\n 220,\n 220,\n 220,\n 220,\n 2938,\n 42435,\n 5873,\n 11,\n 788,\n 340,\n 318,\n 366,\n 10378,\n 33342,\n 1911,\n 628,\n 220,\n 220,\n 220,\n 220,\n 220,\n 220,\n 220,\n 770,\n 2163,\n 460,\n 307,\n 973,\n 284,\n 5004,\n 611,\n 257,\n 9367,\n 611,\n 34069,\n 198,\n 220,\n 220,\n 220,\n 220,\n 220,\n 220,\n 220,\n 287,\n 10560,\n 14,\n 19726,\n 3262,\n 14,\n 6381,\n 10136,\n 840,\n 592,\n 13,\n 628,\n 220,\n 220,\n 220,\n 220,\n 220,\n 220,\n 220,\n 16926,\n 46,\n 532,\n 3494,\n 257,\n 33166,\n 44345,\n 1332,\n 286,\n 10524,\n 284,\n 5004,\n 611,\n 257,\n 198,\n 220,\n 220,\n 220,\n 220,\n 220,\n 220,\n 220,\n 220,\n 220,\n 220,\n 220,\n 220,\n 220,\n 220,\n 42435,\n 318,\n 19941,\n 2383,\n 628,\n 220,\n 220,\n 220,\n 220,\n 220,\n 220,\n 220,\n 1058,\n 17143,\n 1006,\n 25,\n 1218,\n 20937,\n 2134,\n 329,\n 7208,\n 198,\n 220,\n 220,\n 220,\n 220,\n 220,\n 220,\n 220,\n 1058,\n 17143,\n 42435,\n 25,\n 5873,\n 286,\n 42435,\n 2938,\n 286,\n 262,\n 4941,\n 198,\n 220,\n 220,\n 220,\n 220,\n 220,\n 220,\n 220,\n 1058,\n 7783,\n 25,\n 20512,\n 532,\n 6407,\n 611,\n 6737,\n 287,\n 428,\n 20937,\n 318,\n 1342,\n 8157,\n 621,\n 262,\n 4941,\n 198,\n 220,\n 220,\n 220,\n 220,\n 220,\n 220,\n 220,\n 37227,\n 198,\n 220,\n 220,\n 220,\n 220,\n 220,\n 220,\n 220,\n 331,\n 62,\n 5420,\n 796,\n 1006,\n 13,\n 4443,\n 6582,\n 14692,\n 5317,\n 6377,\n 1,\n 4083,\n 27160,\n 198,\n 220,\n 220,\n 220,\n 220,\n 220,\n 220,\n 220,\n 331,\n 62,\n 8158,\n 796,\n 2116,\n 13,\n 4443,\n 6582,\n 14692,\n 5317,\n 6377,\n 1,\n 4083,\n 27160,\n 198,\n 220,\n 220,\n 220,\n 220,\n 220,\n 220,\n 220,\n 2116,\n 13,\n 5420,\n 62,\n 19503,\n 80,\n 796,\n 1006,\n 13,\n 11147,\n 13,\n 35324,\n 198,\n 220,\n 220,\n 220,\n 220,\n 220,\n 220,\n 220,\n 2116,\n 13,\n 5420,\n 62,\n 312,\n 796,\n 1006,\n 13,\n 312,\n 198,\n 220,\n 220,\n 220,\n 220,\n 220,\n 220,\n 220,\n 611,\n 686,\n 72,\n 25,\n 198,\n 220,\n 220,\n 220,\n 220,\n 220,\n 220,\n 220,\n 220,\n 220,\n 220,\n 220,\n 331,\n 62,\n 5420,\n 796,\n 331,\n 62,\n 5420,\n 58,\n 305,\n 72,\n 60,\n 198,\n 220,\n 220,\n 220,\n 220,\n 220,\n 220,\n 220,\n 220,\n 220,\n 220,\n 220,\n 331,\n 62,\n 8158,\n 796,\n 331,\n 62,\n 8158,\n 58,\n 305,\n 72,\n 60,\n 198,\n 220,\n 220,\n 220,\n 220,\n 220,\n 220,\n 220,\n 1303,\n 770,\n 1595,\n 470,\n 670,\n 11,\n 393,\n 318,\n 407,\n 3573,\n 48212,\n 13,\n 198,\n 220,\n 220,\n 220,\n 220,\n 220,\n 220,\n 220,\n 1303,\n 442,\n 271,\n 80,\n 11,\n 279,\n 62,\n 8367,\n 796,\n 442,\n 271,\n 421,\n 533,\n 7,\n 198,\n 220,\n 220,\n 220,\n 220,\n 220,\n 220,\n 220,\n 1303,\n 220,\n 220,\n 220,\n 331,\n 62,\n 8158,\n 11,\n 331,\n 62,\n 5420,\n 198,\n 220,\n 220,\n 220,\n 220,\n 220,\n 220,\n 220,\n 1303,\n 1267,\n 198,\n 220,\n 220,\n 220,\n 220,\n 220,\n 220,\n 220,\n 611,\n 42435,\n 318,\n 6045,\n 25,\n 198,\n 220,\n 220,\n 220,\n 220,\n 220,\n 220,\n 220,\n 220,\n 220,\n 220,\n 220,\n 264,\n 13495,\n 796,\n 45941,\n 13,\n 19282,\n 7,\n 88,\n 62,\n 8158,\n 11,\n 16488,\n 28,\n 15,\n 8,\n 1635,\n 1467,\n 13,\n 15,\n 198,\n 220,\n 220,\n 220,\n 220,\n 220,\n 220,\n 220,\n 2073,\n 25,\n 198,\n 220,\n 220,\n 220,\n 220,\n 220,\n 220,\n 220,\n 220,\n 220,\n 220,\n 220,\n 264,\n 13495,\n 796,\n 42435,\n 198,\n 220,\n 220,\n 220,\n 220,\n 220,\n 220,\n 220,\n 2938,\n 796,\n 45941,\n 13,\n 16345,\n 7,\n 88,\n 62,\n 5420,\n 11,\n 16488,\n 28,\n 15,\n 8,\n 532,\n 264,\n 13495,\n 198,\n 220,\n 220,\n 220,\n 220,\n 220,\n 220,\n 220,\n 1441,\n 45941,\n 13,\n 16345,\n 7,\n 88,\n 62,\n 8158,\n 11,\n 16488,\n 28,\n 15,\n 8,\n 19841,\n 2938,\n 628,\n 220,\n 220,\n 220,\n 825,\n 41058,\n 62,\n 40546,\n 7,\n 944,\n 2599,\n 198,\n 220,\n 220,\n 220,\n 220,\n 220,\n 220,\n 220,\n 37227,\n 198,\n 220,\n 220,\n 220,\n 220,\n 220,\n 220,\n 220,\n 13610,\n 257,\n 28114,\n 306,\n 1446,\n 1436,\n 4743,\n 12854,\n 13,\n 34099,\n 416,\n 262,\n 347,\n 963,\n 2163,\n 11,\n 3584,\n 198,\n 220,\n 220,\n 220,\n 220,\n 220,\n 220,\n 220,\n 2854,\n 12,\n 3083,\n 340,\n 2753,\n 8097,\n 284,\n 7110,\n 510,\n 5299,\n 23924,\n 23824,\n 13,\n 198,\n 220,\n 220,\n 220,\n 220,\n 220,\n 220,\n 220,\n 1058,\n 7783,\n 12854,\n 25,\n 1446,\n 1436,\n 4743,\n 2134,\n 198,\n 220,\n 220,\n 220,\n 220,\n 220,\n 220,\n 220,\n 37227,\n 198,\n 220,\n 220,\n 220,\n 220,\n 220,\n 220,\n 220,\n 2420,\n 796,\n 366,\n 33351,\n 4522,\n 25,\n 23884,\n 27,\n 1671,\n 29,\n 34,\n 615,\n 414,\n 25,\n 23884,\n 27,\n 1671,\n 29,\n 7707,\n 25,\n 23884,\n 27,\n 1671,\n 29,\n 13436,\n 3262,\n 25,\n 23884,\n 27,\n 1671,\n 29,\n 8086,\n 77,\n 25,\n 23884,\n 1911,\n 18982,\n 7,\n 198,\n 220,\n 220,\n 220,\n 220,\n 220,\n 220,\n 220,\n 220,\n 220,\n 220,\n 220,\n 2116,\n 13,\n 312,\n 11,\n 198,\n 220,\n 220,\n 220,\n 220,\n 220,\n 220,\n 220,\n 220,\n 220,\n 220,\n 220,\n 2116,\n 13,\n 66,\n 615,\n 414,\n 62,\n 35324,\n 11,\n 198,\n 220,\n 220,\n 220,\n 220,\n 220,\n 220,\n 220,\n 220,\n 220,\n 220,\n 220,\n 2116,\n 13,\n 7109,\n 62,\n 35324,\n 11,\n 198,\n 220,\n 220,\n 220,\n 220,\n 220,\n 220,\n 220,\n 220,\n 220,\n 220,\n 220,\n 2116,\n 13,\n 19726,\n 3262,\n 11,\n 198,\n 220,\n 220,\n 220,\n 220,\n 220,\n 220,\n 220,\n 220,\n 220,\n 220,\n 220,\n 2116,\n 13,\n 66,\n 615,\n 414,\n 62,\n 41769,\n 11,\n 198,\n 220,\n 220,\n 220,\n 220,\n 220,\n 220,\n 220,\n 1267,\n 198,\n 220,\n 220,\n 220,\n 220,\n 220,\n 220,\n 220,\n 12854,\n 796,\n 467,\n 13,\n 3351,\n 1436,\n 4743,\n 7,\n 198,\n 220,\n 220,\n 220,\n 220,\n 220,\n 220,\n 220,\n 220,\n 220,\n 220,\n 220,\n 2124,\n 28,\n 37659,\n 13,\n 21602,\n 10223,\n 7,\n 944,\n 13,\n 312,\n 11,\n 2116,\n 13,\n 312,\n 1343,\n 352,\n 11,\n 18896,\n 7,\n 944,\n 13,\n 4443,\n 6582,\n 14692,\n 5317,\n 6377,\n 8973,\n 36911,\n 198,\n 220,\n 220,\n 220,\n 220,\n 220,\n 220,\n 220,\n 220,\n 220,\n 220,\n 220,\n 331,\n 28,\n 944,\n 13,\n 4443,\n 6582,\n 14692,\n 5317,\n 6377,\n 33116,\n 198,\n 220,\n 220,\n 220,\n 220,\n 220,\n 220,\n 220,\n 220,\n 220,\n 220,\n 220,\n 2420,\n 28,\n 5239,\n 11,\n 198,\n 220,\n 220,\n 220,\n 220,\n 220,\n 220,\n 220,\n 220,\n 220,\n 220,\n 220,\n 18364,\n 28,\n 4895,\n 8043,\n 1298,\n 366,\n 81,\n 22296,\n 7,\n 3559,\n 11,\n 15187,\n 11,\n 19782,\n 16725,\n 5512,\n 198,\n 220,\n 220,\n 220,\n 220,\n 220,\n 220,\n 220,\n 220,\n 220,\n 220,\n 220,\n 20599,\n 10951,\n 2625,\n 5239,\n 1600,\n 198,\n 220,\n 220,\n 220,\n 220,\n 220,\n 220,\n 220,\n 1267,\n 198,\n 220,\n 220,\n 220,\n 220,\n 220,\n 220,\n 220,\n 1441,\n 12854,\n 628,\n 220,\n 220,\n 220,\n 825,\n 4197,\n 62,\n 66,\n 615,\n 414,\n 7,\n 944,\n 11,\n 7110,\n 28,\n 17821,\n 11,\n 15942,\n 577,\n 28,\n 25101,\n 2599,\n 198,\n 220,\n 220,\n 220,\n 220,\n 220,\n 220,\n 220,\n 37227,\n 198,\n 220,\n 220,\n 220,\n 220,\n 220,\n 220,\n 220,\n 35006,\n 257,\n 4197,\n 284,\n 262,\n 31643,\n 10958,\n 13,\n 36965,\n 257,\n 20312,\n 12822,\n 31562,\n 2746,\n 198,\n 220,\n 220,\n 220,\n 220,\n 220,\n 220,\n 220,\n 326,\n 10356,\n 4340,\n 262,\n 1271,\n 286,\n 15830,\n 10007,\n 13,\n 198,\n 220,\n 220,\n 220,\n 220,\n 220,\n 220,\n 220,\n 1058,\n 17143,\n 7110,\n 25,\n 20512,\n 11986,\n 1771,\n 257,\n 28114,\n 306,\n 3785,\n 318,\n 925,\n 198,\n 220,\n 220,\n 220,\n 220,\n 220,\n 220,\n 220,\n 1058,\n 7783,\n 25,\n 9104,\n 25048,\n 1255,\n 198,\n 220,\n 220,\n 220,\n 220,\n 220,\n 220,\n 220,\n 37227,\n 198,\n 220,\n 220,\n 220,\n 220,\n 220,\n 220,\n 220,\n 331,\n 796,\n 2116,\n 13,\n 4443,\n 6582,\n 14692,\n 5317,\n 6377,\n 1,\n 4083,\n 14781,\n 2616,\n 22446,\n 27160,\n 198,\n 220,\n 220,\n 220,\n 220,\n 220,\n 220,\n 220,\n 2124,\n 796,\n 2116,\n 13,\n 4443,\n 6582,\n 14692,\n 37,\n 28707,\n 357,\n 25983,\n 16725,\n 4083,\n 14781,\n 2616,\n 22446,\n 27160,\n 198,\n 220,\n 220,\n 220,\n 220,\n 220,\n 220,\n 220,\n 2746,\n 796,\n 15830,\n 13,\n 47,\n 958,\n 35389,\n 31562,\n 17633,\n 3419,\n 198,\n 220,\n 220,\n 220,\n 220,\n 220,\n 220,\n 220,\n 1255,\n 796,\n 2746,\n 13,\n 11147,\n 62,\n 24874,\n 7,\n 87,\n 11,\n 331,\n 11,\n 15942,\n 577,\n 28,\n 19011,\n 577,\n 8,\n 198,\n 220,\n 220,\n 220,\n 220,\n 220,\n 220,\n 220,\n 2116,\n 13,\n 4443,\n 6582,\n 14692,\n 31805,\n 8973,\n 796,\n 1255,\n 13,\n 13466,\n 62,\n 11147,\n 198,\n 220,\n 220,\n 220,\n 220,\n 220,\n 220,\n 220,\n 2116,\n 13,\n 11147,\n 796,\n 1255,\n 198,\n 220,\n 220,\n 220,\n 220,\n 220,\n 220,\n 220,\n 2116,\n 13,\n 11147,\n 13,\n 35324,\n 796,\n 2116,\n 13,\n 11147,\n 13,\n 13466,\n 62,\n 27160,\n 14692,\n 87,\n 15,\n 8973,\n 198,\n 220,\n 220,\n 220,\n 220,\n 220,\n 220,\n 220,\n 611,\n 7110,\n 318,\n 6407,\n 25,\n 198,\n 220,\n 220,\n 220,\n 220,\n 220,\n 220,\n 220,\n 220,\n 220,\n 220,\n 220,\n 2336,\n 796,\n 467,\n 13,\n 11337,\n 38300,\n 3419,\n 198,\n 220,\n 220,\n 220,\n 220,\n 220,\n 220,\n 220,\n 220,\n 220,\n 220,\n 220,\n 2336,\n 13,\n 39786,\n 14692,\n 87,\n 22704,\n 1,\n 7131,\n 1,\n 7839,\n 8973,\n 796,\n 366,\n 37,\n 28707,\n 357,\n 25983,\n 16725,\n 198,\n 220,\n 220,\n 220,\n 220,\n 220,\n 220,\n 220,\n 220,\n 220,\n 220,\n 220,\n 2336,\n 13,\n 39786,\n 14692,\n 87,\n 22704,\n 1,\n 7131,\n 1,\n 42298,\n 18982,\n 8973,\n 796,\n 27071,\n 17,\n 69,\n 1,\n 198,\n 220,\n 220,\n 220,\n 220,\n 220,\n 220,\n 220,\n 220,\n 220,\n 220,\n 220,\n 2336,\n 13,\n 2860,\n 62,\n 1416,\n 1436,\n 7,\n 87,\n 28,\n 87,\n 11,\n 331,\n 28,\n 88,\n 11,\n 1438,\n 2625,\n 31310,\n 8520,\n 4943,\n 198,\n 220,\n 220,\n 220,\n 220,\n 220,\n 220,\n 220,\n 220,\n 220,\n 220,\n 220,\n 2336,\n 13,\n 2860,\n 62,\n 1416,\n 1436,\n 7,\n 87,\n 28,\n 87,\n 11,\n 331,\n 28,\n 20274,\n 13,\n 13466,\n 62,\n 11147,\n 11,\n 1438,\n 2625,\n 31805,\n 4943,\n 198,\n 220,\n 220,\n 220,\n 220,\n 220,\n 220,\n 220,\n 220,\n 220,\n 220,\n 220,\n 1441,\n 1255,\n 11,\n 2336,\n 198,\n 220,\n 220,\n 220,\n 220,\n 220,\n 220,\n 220,\n 2073,\n 25,\n 198,\n 220,\n 220,\n 220,\n 220,\n 220,\n 220,\n 220,\n 220,\n 220,\n 220,\n 220,\n 1441,\n 1255,\n 628,\n 198,\n 4299,\n 21136,\n 62,\n 35836,\n 7,\n 7753,\n 3642,\n 658,\n 2599,\n 198,\n 220,\n 220,\n 220,\n 37227,\n 198,\n 220,\n 220,\n 220,\n 15553,\n 329,\n 37895,\n 262,\n 376,\n 2389,\n 1366,\n 422,\n 281,\n 19446,\n 9367,\n 13,\n 383,\n 1366,\n 198,\n 220,\n 220,\n 220,\n 318,\n 4504,\n 355,\n 257,\n 22155,\n 11,\n 543,\n 460,\n 307,\n 973,\n 284,\n 41216,\n 257,\n 198,\n 220,\n 220,\n 220,\n 20937,\n 2134,\n 13,\n 198,\n 220,\n 220,\n 220,\n 1058,\n 17143,\n 2393,\n 3642,\n 658,\n 25,\n 1351,\n 286,\n 3951,\n 422,\n 281,\n 376,\n 2389,\n 2393,\n 198,\n 220,\n 220,\n 220,\n 1058,\n 7783,\n 25,\n 8633,\n 7268,\n 44267,\n 1366,\n 422,\n 376,\n 2389,\n 198,\n 220,\n 220,\n 220,\n 37227,\n 198,\n 220,\n 220,\n 220,\n 1366,\n 796,\n 19779,\n 70,\n 1386,\n 1298,\n 8633,\n 3419,\n 92,\n 198,\n 220,\n 220,\n 220,\n 1303,\n 376,\n 2389,\n 40364,\n 198,\n 220,\n 220,\n 220,\n 49909,\n 62,\n 260,\n 25636,\n 796,\n 302,\n 13,\n 5589,\n 576,\n 7,\n 81,\n 1,\n 61,\n 69,\n 312,\n 59,\n 67,\n 9,\n 1600,\n 302,\n 13,\n 44,\n 8,\n 198,\n 220,\n 220,\n 220,\n 1303,\n 797,\n 25636,\n 284,\n 1064,\n 3623,\n 9619,\n 198,\n 220,\n 220,\n 220,\n 3623,\n 62,\n 260,\n 25636,\n 796,\n 302,\n 13,\n 5589,\n 576,\n 7,\n 81,\n 1,\n 61,\n 2,\n 39699,\n 3467,\n 67,\n 1438,\n 1600,\n 302,\n 13,\n 44,\n 8,\n 198,\n 220,\n 220,\n 220,\n 5202,\n 62,\n 260,\n 25636,\n 796,\n 302,\n 13,\n 5589,\n 576,\n 7,\n 81,\n 1,\n 61,\n 2,\n 39699,\n 3467,\n 67,\n 5202,\n 1600,\n 302,\n 13,\n 44,\n 8,\n 198,\n 220,\n 220,\n 220,\n 1303,\n 797,\n 25636,\n 284,\n 4886,\n 543,\n 6518,\n 318,\n 900,\n 284,\n 262,\n 17655,\n 198,\n 220,\n 220,\n 220,\n 30736,\n 62,\n 260,\n 25636,\n 796,\n 302,\n 13,\n 5589,\n 576,\n 7,\n 81,\n 1,\n 61,\n 2,\n 47,\n 9615,\n 442,\n 3467,\n 67,\n 1438,\n 59,\n 82,\n 9,\n 9697,\n 1600,\n 302,\n 13,\n 44,\n 8,\n 198,\n 220,\n 220,\n 220,\n 30736,\n 62,\n 17620,\n 796,\n 6045,\n 198,\n 220,\n 220,\n 220,\n 329,\n 6376,\n 11,\n 1627,\n 287,\n 27056,\n 378,\n 7,\n 7753,\n 3642,\n 658,\n 2599,\n 198,\n 220,\n 220,\n 220,\n 220,\n 220,\n 220,\n 220,\n 611,\n 25113,\n 33351,\n 1,\n 287,\n 1627,\n 25,\n 198,\n 220,\n 220,\n 220,\n 220,\n 220,\n 220,\n 220,\n 220,\n 220,\n 220,\n 220,\n 6626,\n 62,\n 1370,\n 796,\n 1627,\n 13,\n 35312,\n 3419,\n 198,\n 220,\n 220,\n 220,\n 220,\n 220,\n 220,\n 220,\n 220,\n 220,\n 220,\n 220,\n 1366,\n 14692,\n 312,\n 8973,\n 796,\n 493,\n 7,\n 35312,\n 62,\n 1370,\n 58,\n 16,\n 12962,\n 198,\n 220,\n 220,\n 220,\n 220,\n 220,\n 220,\n 220,\n 220,\n 220,\n 220,\n 220,\n 1949,\n 25,\n 198,\n 220,\n 220,\n 220,\n 220,\n 220,\n 220,\n 220,\n 220,\n 220,\n 220,\n 220,\n 220,\n 220,\n 220,\n 220,\n 1366,\n 14692,\n 30243,\n 8973,\n 796,\n 6626,\n 62,\n 1370,\n 58,\n 17,\n 60,\n 198,\n 220,\n 220,\n 220,\n 220,\n 220,\n 220,\n 220,\n 220,\n 220,\n 220,\n 220,\n 2845,\n 12901,\n 12331,\n 25,\n 198,\n 220,\n 220,\n 220,\n 220,\n 220,\n 220,\n 220,\n 220,\n 220,\n 220,\n 220,\n 220,\n 220,\n 220,\n 220,\n 1366,\n 14692,\n 30243,\n 8973,\n 796,\n 366,\n 9792,\n 16,\n 1,\n 198,\n 220,\n 220,\n 220,\n 220,\n 220,\n 220,\n 220,\n 611,\n 25113,\n 2964,\n 1350,\n 2030,\n 80,\n 1,\n 287,\n 1627,\n 25,\n 198,\n 220,\n 220,\n 220,\n 220,\n 220,\n 220,\n 220,\n 220,\n 220,\n 220,\n 220,\n 1366,\n 14692,\n 66,\n 615,\n 414,\n 62,\n 35324,\n 8973,\n 796,\n 12178,\n 7,\n 1370,\n 13,\n 35312,\n 3419,\n 58,\n 17,\n 12962,\n 198,\n 220,\n 220,\n 220,\n 220,\n 220,\n 220,\n 220,\n 611,\n 25113,\n 2484,\n 1747,\n 1,\n 287,\n 1627,\n 25,\n 198,\n 220,\n 220,\n 220,\n 220,\n 220,\n 220,\n 220,\n 220,\n 220,\n 220,\n 220,\n 1366,\n 14692,\n 20910,\n 8973,\n 796,\n 493,\n 7,\n 1370,\n 13,\n 35312,\n 3419,\n 58,\n 12,\n 16,\n 12962,\n 198,\n 220,\n 220,\n 220,\n 220,\n 220,\n 220,\n 220,\n 611,\n 25113,\n 10430,\n 1,\n 287,\n 1627,\n 25,\n 198,\n 220,\n 220,\n 220,\n 220,\n 220,\n 220,\n 220,\n 220,\n 220,\n 220,\n 220,\n 10283,\n 62,\n 83,\n 853,\n 1039,\n 796,\n 14631,\n 2,\n 10430,\n 1600,\n 37082,\n 83,\n 1600,\n 37082,\n 77,\n 8973,\n 198,\n 220,\n 220,\n 220,\n 220,\n 220,\n 220,\n 220,\n 220,\n 220,\n 220,\n 220,\n 1366,\n 14692,\n 4475,\n 8973,\n 796,\n 4818,\n 8079,\n 13,\n 19608,\n 8079,\n 13,\n 2536,\n 457,\n 524,\n 7,\n 198,\n 220,\n 220,\n 220,\n 220,\n 220,\n 220,\n 220,\n 220,\n 220,\n 220,\n 220,\n 220,\n 220,\n 220,\n 220,\n 302,\n 13,\n 7266,\n 7203,\n 91,\n 1911,\n 22179,\n 7,\n 36311,\n 62,\n 83,\n 853,\n 1039,\n 828,\n 366,\n 1600,\n 1627,\n 828,\n 36521,\n 64,\n 4064,\n 65,\n 4064,\n 67,\n 4064,\n 39,\n 25,\n 4,\n 44,\n 25,\n 4,\n 50,\n 4064,\n 56,\n 1,\n 198,\n 220,\n 220,\n 220,\n 220,\n 220,\n 220,\n 220,\n 220,\n 220,\n 220,\n 220,\n 1267,\n 198,\n 220,\n 220,\n 220,\n 220,\n 220,\n 220,\n 220,\n 611,\n 25113,\n 34,\n 615,\n 414,\n 45444,\n 1,\n 287,\n 1627,\n 25,\n 198,\n 220,\n 220,\n 220,\n 220,\n 220,\n 220,\n 220,\n 220,\n 220,\n 220,\n 220,\n 1366,\n 14692,\n 66,\n 615,\n 414,\n 62,\n 37764,\n 496,\n 8973,\n 796,\n 493,\n 7,\n 1370,\n 13,\n 35312,\n 3419,\n 58,\n 17,\n 12962,\n 198,\n 220,\n 220,\n 220,\n 220,\n 220,\n 220,\n 220,\n 611,\n 25113,\n 8086,\n 268,\n 2288,\n 1,\n 287,\n 1627,\n 25,\n 198,\n 220,\n 220,\n 220,\n 220,\n 220,\n 220,\n 220,\n 220,\n 220,\n 220,\n 220,\n 1366,\n 14692,\n 66,\n 615,\n 414,\n 62,\n 41769,\n 8973,\n 796,\n 493,\n 7,\n 1370,\n 13,\n 35312,\n 3419,\n 58,\n 16,\n 12962,\n 198,\n 220,\n 220,\n 220,\n 220,\n 220,\n 220,\n 220,\n 611,\n 25113,\n 7707,\n 2030,\n 80,\n 1,\n 287,\n 1627,\n 25,\n 198,\n 220,\n 220,\n 220,\n 220,\n 220,\n 220,\n 220,\n 220,\n 220,\n 220,\n 220,\n 1366,\n 14692,\n 7109,\n 62,\n 35324,\n 8973,\n 796,\n 12178,\n 7,\n 1370,\n 13,\n 35312,\n 3419,\n 58,\n 17,\n 12962,\n 198,\n 220,\n 220,\n 220,\n 220,\n 220,\n 220,\n 220,\n 611,\n 25113,\n 7707,\n 1176,\n 1,\n 287,\n 1627,\n 25,\n 198,\n 220,\n 220,\n 220,\n 220,\n 220,\n 220,\n 220,\n 220,\n 220,\n 220,\n 220,\n 1366,\n 14692,\n 7109,\n 62,\n 6477,\n 8973,\n 796,\n 493,\n 7,\n 1370,\n 13,\n 35312,\n 3419,\n 58,\n 17,\n 12962,\n 198,\n 220,\n 220,\n 220,\n 220,\n 220,\n 220,\n 220,\n 611,\n 25113,\n 37,\n 2389,\n 31050,\n 1,\n 287,\n 1627,\n 25,\n 198,\n 220,\n 220,\n 220,\n 220,\n 220,\n 220,\n 220,\n 220,\n 220,\n 220,\n 220,\n 1366,\n 14692,\n 69,\n 312,\n 62,\n 2777,\n 4092,\n 8973,\n 796,\n 12178,\n 7,\n 260,\n 13,\n 19796,\n 439,\n 7,\n 81,\n 1,\n 59,\n 2934,\n 58,\n 10,\n 12,\n 60,\n 30,\n 59,\n 67,\n 59,\n 67,\n 1600,\n 1627,\n 38381,\n 15,\n 12962,\n 198,\n 220,\n 220,\n 220,\n 220,\n 220,\n 220,\n 220,\n 611,\n 25113,\n 37,\n 2389,\n 2173,\n 1,\n 287,\n 1627,\n 25,\n 198,\n 220,\n 220,\n 220,\n 220,\n 220,\n 220,\n 220,\n 220,\n 220,\n 220,\n 220,\n 1366,\n 14692,\n 69,\n 312,\n 62,\n 13033,\n 8973,\n 796,\n 493,\n 7,\n 1370,\n 13,\n 35312,\n 3419,\n 58,\n 12,\n 16,\n 12962,\n 198,\n 220,\n 220,\n 220,\n 220,\n 220,\n 220,\n 220,\n 1303,\n 3497,\n 262,\n 1438,\n 286,\n 262,\n 3623,\n 198,\n 220,\n 220,\n 220,\n 220,\n 220,\n 220,\n 220,\n 611,\n 3623,\n 62,\n 260,\n 25636,\n 13,\n 15699,\n 7,\n 1370,\n 2599,\n 198,\n 220,\n 220,\n 220,\n 220,\n 220,\n 220,\n 220,\n 220,\n 220,\n 220,\n 220,\n 6626,\n 62,\n 1370,\n 796,\n 1627,\n 13,\n 35312,\n 3419,\n 198,\n 220,\n 220,\n 220,\n 220,\n 220,\n 220,\n 220,\n 220,\n 220,\n 220,\n 220,\n 1303,\n 5514,\n 11393,\n 32096,\n 611,\n 262,\n 6518,\n 318,\n 973,\n 198,\n 220,\n 220,\n 220,\n 220,\n 220,\n 220,\n 220,\n 220,\n 220,\n 220,\n 220,\n 3623,\n 62,\n 9630,\n 796,\n 493,\n 7,\n 35312,\n 62,\n 1370,\n 58,\n 16,\n 12962,\n 198,\n 220,\n 220,\n 220,\n 220,\n 220,\n 220,\n 220,\n 220,\n 220,\n 220,\n 220,\n 1949,\n 25,\n 198,\n 220,\n 220,\n 220,\n 220,\n 220,\n 220,\n 220,\n 220,\n 220,\n 220,\n 220,\n 220,\n 220,\n 220,\n 220,\n 1366,\n 14692,\n 70,\n 1386,\n 1,\n 7131,\n 22649,\n 62,\n 9630,\n 60,\n 796,\n 19779,\n 22649,\n 1298,\n 366,\n 27071,\n 22179,\n 7,\n 35312,\n 62,\n 1370,\n 58,\n 18,\n 25,\n 12962,\n 92,\n 198,\n 220,\n 220,\n 220,\n 220,\n 220,\n 220,\n 220,\n 220,\n 220,\n 220,\n 220,\n 2845,\n 12901,\n 12331,\n 25,\n 198,\n 220,\n 220,\n 220,\n 220,\n 220,\n 220,\n 220,\n 220,\n 220,\n 220,\n 220,\n 220,\n 220,\n 220,\n 220,\n 1366,\n 14692,\n 70,\n 1386,\n 1,\n 7131,\n 22649,\n 62,\n 9630,\n 60,\n 796,\n 19779,\n 22649,\n 1298,\n 13538,\n 92,\n 198,\n 220,\n 220,\n 220,\n 220,\n 220,\n 220,\n 220,\n 1303,\n 3497,\n 262,\n 5202,\n 2494,\n 329,\n 6518,\n 198,\n 220,\n 220,\n 220,\n 220,\n 220,\n 220,\n 220,\n 611,\n 5202,\n 62,\n 260,\n 25636,\n 13,\n 15699,\n 7,\n 1370,\n 2599,\n 198,\n 220,\n 220,\n 220,\n 220,\n 220,\n 220,\n 220,\n 220,\n 220,\n 220,\n 220,\n 6626,\n 62,\n 1370,\n 796,\n 1627,\n 13,\n 35312,\n 3419,\n 198,\n 220,\n 220,\n 220,\n 220,\n 220,\n 220,\n 220,\n 220,\n 220,\n 220,\n 220,\n 3623,\n 62,\n 9630,\n 796,\n 493,\n 7,\n 35312,\n 62,\n 1370,\n 58,\n 16,\n 12962,\n 198,\n 220,\n 220,\n 220,\n 220,\n 220,\n 220,\n 220,\n 220,\n 220,\n 220,\n 220,\n 1366,\n 14692,\n 70,\n 1386,\n 1,\n 7131,\n 22649,\n 62,\n 9630,\n 7131,\n 1,\n 11125,\n 8973,\n 796,\n 12178,\n 7,\n 35312,\n 62,\n 1370,\n 58,\n 18,\n 12962,\n 198,\n 220,\n 220,\n 220,\n 220,\n 220,\n 220,\n 220,\n 611,\n 25113,\n 13436,\n 3262,\n 9343,\n 1,\n 287,\n 1627,\n 25,\n 198,\n 220,\n 220,\n 220,\n 220,\n 220,\n 220,\n 220,\n 220,\n 220,\n 220,\n 220,\n 1366,\n 14692,\n 19726,\n 3262,\n 8973,\n 796,\n 20512,\n 7,\n 600,\n 7,\n 1370,\n 13,\n 35312,\n 3419,\n 58,\n 17,\n 60,\n 4008,\n 198,\n 220,\n 220,\n 220,\n 220,\n 220,\n 220,\n 220,\n 1303,\n 9938,\n 262,\n 6518,\n 262,\n 17655,\n 318,\n 900,\n 284,\n 290,\n 17632,\n 257,\n 40364,\n 198,\n 220,\n 220,\n 220,\n 220,\n 220,\n 220,\n 220,\n 1303,\n 284,\n 804,\n 329,\n 262,\n 6518,\n 198,\n 220,\n 220,\n 220,\n 220,\n 220,\n 220,\n 220,\n 611,\n 30736,\n 62,\n 260,\n 25636,\n 13,\n 15699,\n 7,\n 1370,\n 2599,\n 198,\n 220,\n 220,\n 220,\n 220,\n 220,\n 220,\n 220,\n 220,\n 220,\n 220,\n 220,\n 30736,\n 62,\n 9630,\n 796,\n 1627,\n 13,\n 35312,\n 3419,\n 58,\n 17,\n 60,\n 198,\n 220,\n 220,\n 220,\n 220,\n 220,\n 220,\n 220,\n 220,\n 220,\n 220,\n 220,\n 30736,\n 62,\n 17620,\n 796,\n 302,\n 13,\n 5589,\n 576,\n 7,\n 81,\n 1,\n 61,\n 2,\n 47,\n 9615,\n 442,\n 23884,\n 9343,\n 1911,\n 18982,\n 7,\n 17896,\n 62,\n 9630,\n 828,\n 302,\n 13,\n 44,\n 8,\n 198,\n 220,\n 220,\n 220,\n 220,\n 220,\n 220,\n 220,\n 1303,\n 4874,\n 262,\n 17655,\n 6518,\n 6376,\n 318,\n 1900,\n 11,\n 923,\n 10342,\n 329,\n 340,\n 198,\n 220,\n 220,\n 220,\n 220,\n 220,\n 220,\n 220,\n 611,\n 30736,\n 62,\n 17620,\n 25,\n 198,\n 220,\n 220,\n 220,\n 220,\n 220,\n 220,\n 220,\n 220,\n 220,\n 220,\n 220,\n 611,\n 30736,\n 62,\n 17620,\n 13,\n 15699,\n 7,\n 1370,\n 2599,\n 198,\n 220,\n 220,\n 220,\n 220,\n 220,\n 220,\n 220,\n 220,\n 220,\n 220,\n 220,\n 220,\n 220,\n 220,\n 220,\n 1366,\n 14692,\n 6381,\n 10136,\n 8973,\n 796,\n 20512,\n 7,\n 600,\n 7,\n 1370,\n 13,\n 35312,\n 3419,\n 58,\n 12,\n 16,\n 60,\n 4008,\n 198,\n 220,\n 220,\n 220,\n 220,\n 220,\n 220,\n 220,\n 1303,\n 9938,\n 618,\n 262,\n 376,\n 2389,\n 3951,\n 923,\n 26324,\n 510,\n 198,\n 220,\n 220,\n 220,\n 220,\n 220,\n 220,\n 220,\n 611,\n 49909,\n 62,\n 260,\n 25636,\n 13,\n 15699,\n 7,\n 1370,\n 2599,\n 198,\n 220,\n 220,\n 220,\n 220,\n 220,\n 220,\n 220,\n 220,\n 220,\n 220,\n 220,\n 49909,\n 796,\n 2393,\n 3642,\n 658,\n 58,\n 9630,\n 1343,\n 352,\n 1058,\n 60,\n 198,\n 220,\n 220,\n 220,\n 220,\n 220,\n 220,\n 220,\n 220,\n 220,\n 220,\n 220,\n 49909,\n 796,\n 685,\n 22468,\n 7,\n 8367,\n 8,\n 329,\n 1988,\n 287,\n 49909,\n 60,\n 198,\n 220,\n 220,\n 220,\n 220,\n 220,\n 220,\n 220,\n 220,\n 220,\n 220,\n 220,\n 1366,\n 14692,\n 69,\n 312,\n 8973,\n 796,\n 45941,\n 13,\n 18747,\n 7,\n 69,\n 312,\n 8,\n 198,\n 220,\n 220,\n 220,\n 1441,\n 1366,\n 628,\n 198,\n 4299,\n 1620,\n 62,\n 487,\n 83,\n 7,\n 69,\n 312,\n 11,\n 31050,\n 11,\n 923,\n 28,\n 15,\n 11,\n 2245,\n 10779,\n 16,\n 11,\n 4324,\n 2625,\n 3524,\n 7718,\n 1,\n 2599,\n 198,\n 220,\n 220,\n 220,\n 37227,\n 198,\n 220,\n 220,\n 220,\n 35006,\n 281,\n 376,\n 9792,\n 319,\n 281,\n 376,\n 2389,\n 284,\n 651,\n 262,\n 8373,\n 7386,\n 10958,\n 13,\n 198,\n 220,\n 220,\n 220,\n 1439,\n 286,\n 262,\n 7159,\n 389,\n 11902,\n 11,\n 290,\n 2148,\n 1630,\n 625,\n 703,\n 262,\n 376,\n 9792,\n 318,\n 6157,\n 11,\n 355,\n 880,\n 355,\n 1281,\n 12,\n 36948,\n 198,\n 220,\n 220,\n 220,\n 10007,\n 588,\n 4324,\n 5499,\n 290,\n 6632,\n 12,\n 39231,\n 13,\n 628,\n 220,\n 220,\n 220,\n 770,\n 318,\n 1912,\n 319,\n 262,\n 376,\n 9792,\n 2438,\n 416,\n 14316,\n 32379,\n 21048,\n 11,\n 351,\n 19008,\n 284,\n 4197,\n 428,\n 4818,\n 330,\n 31172,\n 13,\n 628,\n 220,\n 220,\n 220,\n 40117,\n 198,\n 220,\n 220,\n 220,\n 24200,\n 438,\n 198,\n 220,\n 220,\n 220,\n 49909,\n 532,\n 399,\n 32152,\n 352,\n 35,\n 7177,\n 198,\n 220,\n 220,\n 220,\n 220,\n 220,\n 220,\n 220,\n 15690,\n 4769,\n 262,\n 3815,\n 286,\n 262,\n 376,\n 2389,\n 198,\n 220,\n 220,\n 220,\n 31050,\n 532,\n 12178,\n 198,\n 220,\n 220,\n 220,\n 220,\n 220,\n 220,\n 220,\n 3862,\n 31050,\n 1022,\n 376,\n 2389,\n 2173,\n 287,\n 4580,\n 43012,\n 198,\n 220,\n 220,\n 220,\n 923,\n 532,\n 493,\n 11,\n 11902,\n 198,\n 220,\n 220,\n 220,\n 220,\n 220,\n 220,\n 220,\n 17962,\n 6376,\n 329,\n 262,\n 376,\n 2389,\n 7177,\n 284,\n 1620,\n 262,\n 376,\n 9792,\n 198,\n 220,\n 220,\n 220,\n 2245,\n 532,\n 493,\n 11,\n 11902,\n 198,\n 220,\n 220,\n 220,\n 220,\n 220,\n 220,\n 220,\n 5268,\n 6376,\n 329,\n 262,\n 376,\n 2389,\n 7177,\n 284,\n 1620,\n 262,\n 376,\n 9792,\n 198,\n 220,\n 220,\n 220,\n 1976,\n 79,\n 69,\n 532,\n 493,\n 11,\n 11902,\n 198,\n 220,\n 220,\n 220,\n 220,\n 220,\n 220,\n 220,\n 15744,\n 262,\n 376,\n 2389,\n 351,\n 1976,\n 27498,\n 284,\n 299,\n 400,\n 16936,\n 1176,\n 286,\n 362,\n 198,\n 220,\n 220,\n 220,\n 4324,\n 532,\n 965,\n 198,\n 220,\n 220,\n 220,\n 220,\n 220,\n 220,\n 220,\n 18291,\n 1958,\n 262,\n 4324,\n 2163,\n 973,\n 284,\n 1429,\n 262,\n 376,\n 2389,\n 13,\n 2896,\n 13185,\n 284,\n 3091,\n 7718,\n 11,\n 543,\n 318,\n 6840,\n 645,\n 25431,\n 13,\n 198,\n 220,\n 220,\n 220,\n 220,\n 220,\n 220,\n 220,\n 383,\n 3891,\n 286,\n 262,\n 4324,\n 5499,\n 1695,\n 460,\n 307,\n 1043,\n 379,\n 25,\n 198,\n 220,\n 220,\n 220,\n 220,\n 220,\n 220,\n 220,\n 3740,\n 1378,\n 31628,\n 13,\n 1416,\n 541,\n 88,\n 13,\n 2398,\n 14,\n 15390,\n 14,\n 1416,\n 541,\n 88,\n 14,\n 35790,\n 14,\n 12683,\n 282,\n 13,\n 28457,\n 13,\n 6494,\n 628,\n 220,\n 220,\n 220,\n 16409,\n 198,\n 220,\n 220,\n 220,\n 35656,\n 198,\n 220,\n 220,\n 220,\n 37227,\n 198,\n 220,\n 220,\n 220,\n 49909,\n 796,\n 45941,\n 13,\n 30073,\n 7,\n 69,\n 312,\n 8,\n 198,\n 220,\n 220,\n 220,\n 611,\n 4324,\n 318,\n 407,\n 6045,\n 290,\n 4324,\n 287,\n 599,\n 82,\n 328,\n 13,\n 28457,\n 13,\n 834,\n 439,\n 834,\n 25,\n 198,\n 220,\n 220,\n 220,\n 220,\n 220,\n 220,\n 220,\n 4324,\n 62,\n 69,\n 796,\n 599,\n 82,\n 328,\n 13,\n 28457,\n 13,\n 1136,\n 62,\n 17497,\n 7,\n 17497,\n 11,\n 49909,\n 13,\n 7857,\n 8,\n 198,\n 220,\n 220,\n 220,\n 220,\n 220,\n 220,\n 220,\n 49909,\n 1635,\n 28,\n 4324,\n 62,\n 69,\n 198,\n 220,\n 220,\n 220,\n 2073,\n 25,\n 198,\n 220,\n 220,\n 220,\n 220,\n 220,\n 220,\n 220,\n 5298,\n 35528,\n 7203,\n 22882,\n 1431,\n 4324,\n 2163,\n 318,\n 407,\n 9177,\n 287,\n 10286,\n 20519,\n 2474,\n 8,\n 198,\n 220,\n 220,\n 220,\n 1303,\n 5345,\n 3815,\n 284,\n 6632,\n 510,\n 284,\n 3599,\n 6376,\n 198,\n 220,\n 220,\n 220,\n 49909,\n 58,\n 25,\n 9688,\n 60,\n 796,\n 657,\n 13,\n 15,\n 198,\n 220,\n 220,\n 220,\n 611,\n 2245,\n 1279,\n 657,\n 25,\n 198,\n 220,\n 220,\n 220,\n 220,\n 220,\n 220,\n 220,\n 1303,\n 1002,\n 356,\n 821,\n 1262,\n 4633,\n 39199,\n 198,\n 220,\n 220,\n 220,\n 220,\n 220,\n 220,\n 220,\n 49909,\n 58,\n 69,\n 312,\n 13,\n 7857,\n 1343,\n 2245,\n 1058,\n 60,\n 796,\n 657,\n 13,\n 15,\n 198,\n 220,\n 220,\n 220,\n 2073,\n 25,\n 198,\n 220,\n 220,\n 220,\n 220,\n 220,\n 220,\n 220,\n 1303,\n 15323,\n 11,\n 6376,\n 351,\n 257,\n 3967,\n 1271,\n 198,\n 220,\n 220,\n 220,\n 220,\n 220,\n 220,\n 220,\n 49909,\n 58,\n 11338,\n 47715,\n 796,\n 657,\n 13,\n 15,\n 198,\n 220,\n 220,\n 220,\n 1303,\n 35006,\n 262,\n 376,\n 9792,\n 198,\n 220,\n 220,\n 220,\n 277,\n 701,\n 796,\n 45941,\n 13,\n 487,\n 83,\n 13,\n 81,\n 487,\n 83,\n 7,\n 69,\n 312,\n 8,\n 198,\n 220,\n 220,\n 220,\n 1100,\n 62,\n 13664,\n 796,\n 18896,\n 7,\n 69,\n 312,\n 8,\n 3373,\n 362,\n 1343,\n 352,\n 198,\n 220,\n 220,\n 220,\n 47764,\n 796,\n 352,\n 13,\n 15,\n 1220,\n 49909,\n 13,\n 7857,\n 1220,\n 31050,\n 198,\n 220,\n 220,\n 220,\n 1303,\n 2980,\n 378,\n 262,\n 8373,\n 7177,\n 198,\n 220,\n 220,\n 220,\n 8373,\n 796,\n 45941,\n 13,\n 21602,\n 10223,\n 7,\n 15,\n 13,\n 15,\n 11,\n 2116,\n 13,\n 25677,\n 14692,\n 1589,\n 3903,\n 8973,\n 1635,\n 47764,\n 11,\n 1100,\n 62,\n 13664,\n 8,\n 198,\n 220,\n 220,\n 220,\n 8373,\n 15853,\n 2116,\n 13,\n 25677,\n 14692,\n 1676,\n 1350,\n 62,\n 19503,\n 80,\n 8973,\n 198,\n 220,\n 220,\n 220,\n 277,\n 701,\n 58,\n 7,\n 35324,\n 18189,\n 277,\n 62,\n 9806,\n 8,\n 1222,\n 357,\n 35324,\n 19841,\n 277,\n 62,\n 1084,\n 15437,\n 796,\n 657,\n 13,\n 15,\n 198,\n 220,\n 220,\n 220,\n 277,\n 701,\n 1635,\n 28,\n 8576,\n 13,\n 15,\n 198,\n 220,\n 220,\n 220,\n 1441,\n 8373,\n 11,\n 277,\n 701,\n 628,\n 198,\n 4299,\n 49909,\n 17,\n 487,\n 83,\n 7,\n 69,\n 312,\n 11,\n 2494,\n 11,\n 19998,\n 11,\n 12429,\n 46265,\n 22046,\n 2599,\n 198,\n 220,\n 220,\n 220,\n 37227,\n 198,\n 220,\n 220,\n 220,\n 10854,\n 281,\n 376,\n 2389,\n 416,\n 9489,\n 281,\n 376,\n 9792,\n 284,\n 7800,\n 262,\n 8373,\n 7386,\n 198,\n 220,\n 220,\n 220,\n 1321,\n 13,\n 31767,\n 22046,\n 389,\n 3804,\n 355,\n 3224,\n 7587,\n 3689,\n 11,\n 198,\n 220,\n 220,\n 220,\n 290,\n 389,\n 9177,\n 355,\n 617,\n 1339,\n 6299,\n 284,\n 4155,\n 262,\n 6460,\n 198,\n 220,\n 220,\n 220,\n 389,\n 4938,\n 357,\n 68,\n 13,\n 70,\n 13,\n 17216,\n 82,\n 284,\n 19232,\n 2494,\n 11,\n 3503,\n 2014,\n 628,\n 220,\n 220,\n 220,\n 1058,\n 17143,\n 49909,\n 25,\n 45941,\n 13,\n 18747,\n 11188,\n 284,\n 262,\n 376,\n 2389,\n 12245,\n 198,\n 220,\n 220,\n 220,\n 1058,\n 17143,\n 2494,\n 25,\n 19232,\n 2494,\n 287,\n 26109,\n 198,\n 220,\n 220,\n 220,\n 1058,\n 17143,\n 19998,\n 25,\n 45941,\n 13,\n 18747,\n 11188,\n 284,\n 262,\n 8373,\n 41701,\n 198,\n 220,\n 220,\n 220,\n 1058,\n 17143,\n 479,\n 86,\n 22046,\n 25,\n 6737,\n 7587,\n 3689,\n 25,\n 198,\n 220,\n 220,\n 220,\n 220,\n 220,\n 220,\n 220,\n 220,\n 220,\n 220,\n 220,\n 220,\n 220,\n 220,\n 220,\n 220,\n 220,\n 220,\n 220,\n 5711,\n 532,\n 16119,\n 262,\n 376,\n 2389,\n 7587,\n 416,\n 4634,\n 262,\n 923,\n 198,\n 220,\n 220,\n 220,\n 220,\n 220,\n 220,\n 220,\n 220,\n 220,\n 220,\n 220,\n 220,\n 220,\n 220,\n 220,\n 220,\n 220,\n 220,\n 220,\n 220,\n 220,\n 220,\n 220,\n 220,\n 220,\n 220,\n 220,\n 286,\n 262,\n 376,\n 2389,\n 284,\n 6632,\n 198,\n 220,\n 220,\n 220,\n 220,\n 220,\n 220,\n 220,\n 220,\n 220,\n 220,\n 220,\n 220,\n 220,\n 220,\n 220,\n 220,\n 220,\n 220,\n 220,\n 1976,\n 263,\n 404,\n 324,\n 532,\n 309,\n 48549,\n 1771,\n 393,\n 407,\n 262,\n 1271,\n 286,\n 35846,\n 198,\n 220,\n 220,\n 220,\n 220,\n 220,\n 220,\n 220,\n 220,\n 220,\n 220,\n 220,\n 220,\n 220,\n 220,\n 220,\n 220,\n 220,\n 220,\n 220,\n 220,\n 220,\n 220,\n 220,\n 220,\n 220,\n 220,\n 220,\n 220,\n 220,\n 2173,\n 318,\n 15229,\n 284,\n 651,\n 32455,\n 2440,\n 198,\n 220,\n 220,\n 220,\n 220,\n 220,\n 220,\n 220,\n 220,\n 220,\n 220,\n 220,\n 220,\n 220,\n 220,\n 220,\n 220,\n 220,\n 220,\n 220,\n 220,\n 220,\n 220,\n 220,\n 220,\n 220,\n 220,\n 220,\n 220,\n 220,\n 6323,\n 287,\n 262,\n 376,\n 9792,\n 198,\n 220,\n 220,\n 220,\n 220,\n 220,\n 220,\n 220,\n 220,\n 220,\n 220,\n 220,\n 220,\n 220,\n 220,\n 220,\n 220,\n 220,\n 220,\n 220,\n 4324,\n 532,\n 26386,\n 4324,\n 5499,\n 2810,\n 416,\n 4600,\n 1416,\n 541,\n 88,\n 13,\n 12683,\n 282,\n 63,\n 198,\n 220,\n 220,\n 220,\n 220,\n 220,\n 220,\n 220,\n 220,\n 220,\n 220,\n 220,\n 220,\n 220,\n 220,\n 220,\n 220,\n 220,\n 220,\n 220,\n 1033,\n 532,\n 18291,\n 6945,\n 281,\n 39682,\n 8106,\n 198,\n 220,\n 220,\n 220,\n 220,\n 220,\n 220,\n 220,\n 220,\n 220,\n 220,\n 220,\n 220,\n 220,\n 220,\n 220,\n 220,\n 220,\n 220,\n 220,\n 8106,\n 532,\n 362,\n 12,\n 83,\n 29291,\n 31577,\n 262,\n 8373,\n 2005,\n 8210,\n 329,\n 257,\n 198,\n 220,\n 220,\n 220,\n 220,\n 220,\n 220,\n 220,\n 220,\n 220,\n 220,\n 220,\n 220,\n 220,\n 220,\n 220,\n 220,\n 220,\n 220,\n 220,\n 220,\n 220,\n 220,\n 220,\n 220,\n 220,\n 220,\n 220,\n 220,\n 4097,\n 1208,\n 8106,\n 198,\n 220,\n 220,\n 220,\n 1058,\n 7783,\n 25,\n 2030,\n 80,\n 62,\n 7568,\n 532,\n 19798,\n 292,\n 1366,\n 14535,\n 351,\n 262,\n 376,\n 9792,\n 10958,\n 198,\n 220,\n 220,\n 220,\n 37227,\n 198,\n 220,\n 220,\n 220,\n 1303,\n 17220,\n 6257,\n 198,\n 220,\n 220,\n 220,\n 649,\n 62,\n 69,\n 312,\n 796,\n 49909,\n 532,\n 45941,\n 13,\n 23913,\n 7,\n 69,\n 312,\n 8,\n 198,\n 220,\n 220,\n 220,\n 611,\n 366,\n 40850,\n 1,\n 287,\n 479,\n 86,\n 22046,\n 25,\n 198,\n 220,\n 220,\n 220,\n 220,\n 220,\n 220,\n 220,\n 5711,\n 796,\n 493,\n 7,\n 46265,\n 22046,\n 14692,\n 40850,\n 8973,\n 1220,\n 357,\n 16,\n 13,\n 15,\n 1220,\n 2494,\n 8,\n 1220,\n 352,\n 68,\n 21,\n 8,\n 198,\n 220,\n 220,\n 220,\n 220,\n 220,\n 220,\n 220,\n 649,\n 62,\n 69,\n 312,\n 58,\n 25,\n 40850,\n 60,\n 796,\n 657,\n 13,\n 15,\n 198,\n 220,\n 220,\n 220,\n 1303,\n 12169,\n 12,\n 15636,\n 262,\n 376,\n 2389,\n 198,\n 220,\n 220,\n 220,\n 611,\n 366,\n 9107,\n 404,\n 324,\n 1,\n 287,\n 479,\n 86,\n 22046,\n 25,\n 198,\n 220,\n 220,\n 220,\n 220,\n 220,\n 220,\n 220,\n 611,\n 479,\n 86,\n 22046,\n 14692,\n 9107,\n 404,\n 324,\n 8973,\n 318,\n 6407,\n 25,\n 198,\n 220,\n 220,\n 220,\n 220,\n 220,\n 220,\n 220,\n 220,\n 220,\n 220,\n 220,\n 1303,\n 15744,\n 262,\n 376,\n 2389,\n 351,\n 1976,\n 27498,\n 284,\n 651,\n 2440,\n 6323,\n 198,\n 220,\n 220,\n 220,\n 220,\n 220,\n 220,\n 220,\n 220,\n 220,\n 220,\n 220,\n 49909,\n 796,\n 45941,\n 13,\n 33295,\n 7,\n 3605,\n 62,\n 69,\n 312,\n 11,\n 45941,\n 13,\n 9107,\n 418,\n 7,\n 11925,\n 7,\n 3605,\n 62,\n 69,\n 312,\n 22305,\n 198,\n 220,\n 220,\n 220,\n 220,\n 220,\n 220,\n 220,\n 220,\n 220,\n 220,\n 220,\n 1303,\n 4619,\n 356,\n 1053,\n 44582,\n 351,\n 1976,\n 27498,\n 11,\n 356,\n 1183,\n 423,\n 284,\n 4296,\n 262,\n 198,\n 220,\n 220,\n 220,\n 220,\n 220,\n 220,\n 220,\n 220,\n 220,\n 220,\n 220,\n 1303,\n 8373,\n 7177,\n 198,\n 220,\n 220,\n 220,\n 220,\n 220,\n 220,\n 220,\n 220,\n 220,\n 220,\n 220,\n 19998,\n 796,\n 599,\n 82,\n 328,\n 13,\n 411,\n 1403,\n 7,\n 69,\n 8897,\n 3976,\n 11,\n 18896,\n 7,\n 69,\n 8897,\n 3976,\n 8,\n 1635,\n 362,\n 8,\n 198,\n 220,\n 220,\n 220,\n 1303,\n 27967,\n 257,\n 4324,\n 2163,\n 284,\n 262,\n 376,\n 2389,\n 198,\n 220,\n 220,\n 220,\n 611,\n 366,\n 17497,\n 1,\n 287,\n 479,\n 86,\n 22046,\n 25,\n 198,\n 220,\n 220,\n 220,\n 220,\n 220,\n 220,\n 220,\n 611,\n 479,\n 86,\n 22046,\n 14692,\n 17497,\n 8973,\n 287,\n 599,\n 82,\n 328,\n 13,\n 28457,\n 13,\n 834,\n 439,\n 834,\n 25,\n 198,\n 220,\n 220,\n 220,\n 220,\n 220,\n 220,\n 220,\n 220,\n 220,\n 220,\n 220,\n 649,\n 62,\n 69,\n 312,\n 1635,\n 28,\n 599,\n 82,\n 328,\n 13,\n 1136,\n 62,\n 17497,\n 7,\n 46265,\n 22046,\n 14692,\n 17497,\n 33116,\n 649,\n 62,\n 69,\n 312,\n 13,\n 7857,\n 8,\n 198,\n 220,\n 220,\n 220,\n 1303,\n 27967,\n 281,\n 39682,\n 8106,\n 319,\n 262,\n 376,\n 2389,\n 198,\n 220,\n 220,\n 220,\n 611,\n 366,\n 11201,\n 1,\n 287,\n 479,\n 86,\n 22046,\n 25,\n 198,\n 220,\n 220,\n 220,\n 220,\n 220,\n 220,\n 220,\n 611,\n 479,\n 86,\n 22046,\n 14692,\n 11201,\n 8973,\n 1875,\n 657,\n 13,\n 15,\n 25,\n 198,\n 220,\n 220,\n 220,\n 220,\n 220,\n 220,\n 220,\n 220,\n 220,\n 220,\n 220,\n 649,\n 62,\n 69,\n 312,\n 1635,\n 28,\n 599,\n 82,\n 328,\n 13,\n 11201,\n 35470,\n 7,\n 11925,\n 7,\n 3605,\n 62,\n 69,\n 312,\n 828,\n 256,\n 559,\n 28,\n 46265,\n 22046,\n 14692,\n 11201,\n 8973,\n 8,\n 198,\n 220,\n 220,\n 220,\n 1303,\n 27967,\n 257,\n 4097,\n 6603,\n 8106,\n 319,\n 262,\n 376,\n 2389,\n 198,\n 220,\n 220,\n 220,\n 611,\n 5855,\n 24455,\n 1,\n 287,\n 479,\n 86,\n 22046,\n 8,\n 290,\n 357,\n 11925,\n 7,\n 46265,\n 22046,\n 14692,\n 24455,\n 8973,\n 8,\n 6624,\n 362,\n 2599,\n 198,\n 220,\n 220,\n 220,\n 220,\n 220,\n 220,\n 220,\n 1877,\n 11,\n 1029,\n 796,\n 23243,\n 7,\n 46265,\n 22046,\n 14692,\n 24455,\n 8973,\n 8,\n 198,\n 220,\n 220,\n 220,\n 220,\n 220,\n 220,\n 220,\n 611,\n 1877,\n 1279,\n 1029,\n 25,\n 198,\n 220,\n 220,\n 220,\n 220,\n 220,\n 220,\n 220,\n 220,\n 220,\n 220,\n 220,\n 649,\n 62,\n 69,\n 312,\n 796,\n 4174,\n 62,\n 4360,\n 353,\n 62,\n 24455,\n 7,\n 3605,\n 62,\n 69,\n 312,\n 11,\n 1877,\n 11,\n 1029,\n 11,\n 2494,\n 8,\n 198,\n 220,\n 220,\n 220,\n 1303,\n 35006,\n 262,\n 376,\n 9792,\n 198,\n 220,\n 220,\n 220,\n 277,\n 701,\n 796,\n 45941,\n 13,\n 487,\n 83,\n 13,\n 81,\n 487,\n 83,\n 7,\n 3605,\n 62,\n 69,\n 312,\n 8,\n 198,\n 220,\n 220,\n 220,\n 1303,\n 3497,\n 262,\n 1103,\n 636,\n 286,\n 262,\n 376,\n 9792,\n 11,\n 290,\n 691,\n 262,\n 1729,\n 12,\n 646,\n 489,\n 3474,\n 1735,\n 198,\n 220,\n 220,\n 220,\n 1103,\n 62,\n 487,\n 83,\n 796,\n 45941,\n 13,\n 8937,\n 7,\n 487,\n 83,\n 58,\n 25,\n 493,\n 7,\n 11925,\n 7,\n 3605,\n 62,\n 69,\n 312,\n 8,\n 1220,\n 362,\n 8,\n 12962,\n 1220,\n 18896,\n 7,\n 3605,\n 62,\n 69,\n 312,\n 8,\n 1635,\n 352,\n 68,\n 18,\n 198,\n 220,\n 220,\n 220,\n 19998,\n 796,\n 599,\n 82,\n 328,\n 13,\n 411,\n 1403,\n 7,\n 69,\n 8897,\n 3976,\n 11,\n 1103,\n 62,\n 487,\n 83,\n 13,\n 7857,\n 8,\n 198,\n 220,\n 220,\n 220,\n 1303,\n 1114,\n 617,\n 1738,\n 11,\n 581,\n 321,\n 11347,\n 23742,\n 510,\n 262,\n 8373,\n 16216,\n 986,\n 198,\n 220,\n 220,\n 220,\n 1103,\n 62,\n 487,\n 83,\n 796,\n 1103,\n 62,\n 487,\n 83,\n 58,\n 37659,\n 13,\n 22046,\n 419,\n 7,\n 69,\n 8897,\n 3976,\n 15437,\n 198,\n 220,\n 220,\n 220,\n 19998,\n 796,\n 45941,\n 13,\n 30619,\n 7,\n 69,\n 8897,\n 3976,\n 8,\n 198,\n 220,\n 220,\n 220,\n 1303,\n 15717,\n 656,\n 257,\n 19798,\n 292,\n 1366,\n 14535,\n 198,\n 220,\n 220,\n 220,\n 2030,\n 80,\n 62,\n 7568,\n 796,\n 279,\n 67,\n 13,\n 6601,\n 19778,\n 7,\n 4895,\n 37,\n 28707,\n 357,\n 25983,\n 8,\n 1298,\n 19998,\n 11,\n 366,\n 5317,\n 6377,\n 1298,\n 1103,\n 62,\n 487,\n 83,\n 30072,\n 198,\n 220,\n 220,\n 220,\n 1441,\n 2030,\n 80,\n 62,\n 7568,\n 628,\n 198,\n 4299,\n 9215,\n 62,\n 3903,\n 6603,\n 7,\n 9319,\n 11,\n 1029,\n 11,\n 2494,\n 11,\n 1502,\n 28,\n 16,\n 2599,\n 198,\n 220,\n 220,\n 220,\n 37227,\n 198,\n 220,\n 220,\n 220,\n 220,\n 220,\n 220,\n 220,\n 317,\n 9518,\n 2196,\n 286,\n 262,\n 18971,\n 9268,\n 4097,\n 6603,\n 8106,\n 3417,\n 994,\n 11,\n 198,\n 220,\n 220,\n 220,\n 220,\n 220,\n 220,\n 220,\n 16573,\n 329,\n 779,\n 351,\n 262,\n 376,\n 2389,\n 6737,\n 13,\n 198,\n 220,\n 220,\n 220,\n 220,\n 220,\n 220,\n 220,\n 2638,\n 1378,\n 1416,\n 541,\n 88,\n 12,\n 27916,\n 2070,\n 13,\n 961,\n 83,\n 704,\n 420,\n 82,\n 13,\n 952,\n 14,\n 23814,\n 14,\n 1537,\n 353,\n 9268,\n 31407,\n 6603,\n 13,\n 6494,\n 198,\n 220,\n 220,\n 220,\n 220,\n 220,\n 220,\n 220,\n 383,\n 7159,\n 389,\n 25,\n 628,\n 220,\n 220,\n 220,\n 220,\n 220,\n 220,\n 220,\n 1058,\n 17143,\n 1877,\n 383,\n 1877,\n 8373,\n 2005,\n 12,\n 2364,\n 11,\n 1813,\n 287,\n 37597,\n 13,\n 198,\n 220,\n 220,\n 220,\n 220,\n 220,\n 220,\n 220,\n 1058,\n 17143,\n 1029,\n 383,\n 1029,\n 8373,\n 2005,\n 12,\n 2364,\n 11,\n 1813,\n 287,\n 37597,\n 13,\n 198,\n 220,\n 220,\n 220,\n 220,\n 220,\n 220,\n 220,\n 1058,\n 17143,\n 2494,\n 383,\n 19232,\n 2494,\n 11,\n 1813,\n 287,\n 26109,\n 13,\n 3574,\n 262,\n 376,\n 47954,\n 11,\n 428,\n 1724,\n 326,\n 198,\n 220,\n 220,\n 220,\n 220,\n 220,\n 220,\n 220,\n 220,\n 220,\n 220,\n 220,\n 220,\n 220,\n 220,\n 220,\n 220,\n 220,\n 220,\n 220,\n 262,\n 34062,\n 286,\n 262,\n 376,\n 2389,\n 31050,\n 318,\n 973,\n 13,\n 198,\n 220,\n 220,\n 220,\n 220,\n 220,\n 220,\n 220,\n 1058,\n 7783,\n 4097,\n 6603,\n 4324,\n 198,\n 220,\n 220,\n 220,\n 37227,\n 198,\n 220,\n 220,\n 220,\n 1303,\n 27131,\n 378,\n 262,\n 17735,\n 30062,\n 8373,\n 198,\n 220,\n 220,\n 220,\n 299,\n 88,\n 80,\n 796,\n 657,\n 13,\n 20,\n 1635,\n 357,\n 4873,\n 1220,\n 357,\n 17,\n 13,\n 15,\n 1635,\n 45941,\n 13,\n 14415,\n 4008,\n 198,\n 220,\n 220,\n 220,\n 1877,\n 796,\n 357,\n 9319,\n 1635,\n 352,\n 68,\n 18,\n 8,\n 1220,\n 299,\n 88,\n 80,\n 198,\n 220,\n 220,\n 220,\n 1029,\n 796,\n 357,\n 8929,\n 1635,\n 352,\n 68,\n 18,\n 8,\n 1220,\n 299,\n 88,\n 80,\n 198,\n 220,\n 220,\n 220,\n 611,\n 1029,\n 1875,\n 352,\n 13,\n 15,\n 25,\n 198,\n 220,\n 220,\n 220,\n 220,\n 220,\n 220,\n 220,\n 5298,\n 35528,\n 7203,\n 11922,\n 8373,\n 2005,\n 12,\n 2364,\n 21695,\n 262,\n 17735,\n 30062,\n 8373,\n 19570,\n 198,\n 220,\n 220,\n 220,\n 275,\n 11,\n 257,\n 796,\n 599,\n 82,\n 328,\n 13,\n 4360,\n 353,\n 7,\n 2875,\n 11,\n 685,\n 9319,\n 11,\n 1029,\n 4357,\n 275,\n 4906,\n 2625,\n 3903,\n 1600,\n 15075,\n 28,\n 25101,\n 8,\n 198,\n 220,\n 220,\n 220,\n 1441,\n 275,\n 11,\n 257,\n 628,\n 198,\n 4299,\n 4174,\n 62,\n 4360,\n 353,\n 62,\n 24455,\n 7,\n 7890,\n 11,\n 1877,\n 11,\n 1029,\n 11,\n 2494,\n 11,\n 1502,\n 28,\n 16,\n 2599,\n 198,\n 220,\n 220,\n 220,\n 37227,\n 198,\n 220,\n 220,\n 220,\n 220,\n 220,\n 220,\n 220,\n 317,\n 9518,\n 18971,\n 9268,\n 4097,\n 6603,\n 8106,\n 11,\n 16573,\n 422,\n 262,\n 1446,\n 541,\n 88,\n 4255,\n 2070,\n 13,\n 628,\n 220,\n 220,\n 220,\n 220,\n 220,\n 220,\n 220,\n 383,\n 4578,\n 1366,\n 9416,\n 262,\n 376,\n 2389,\n 11,\n 543,\n 788,\n 3544,\n 262,\n 629,\n 541,\n 88,\n 6737,\n 198,\n 220,\n 220,\n 220,\n 220,\n 220,\n 220,\n 220,\n 7587,\n 2163,\n 284,\n 4174,\n 262,\n 4875,\n 8106,\n 11,\n 290,\n 5860,\n 262,\n 29083,\n 198,\n 220,\n 220,\n 220,\n 220,\n 220,\n 220,\n 220,\n 376,\n 2389,\n 13,\n 628,\n 220,\n 220,\n 220,\n 220,\n 220,\n 220,\n 220,\n 4091,\n 262,\n 4600,\n 4360,\n 353,\n 62,\n 3903,\n 6603,\n 63,\n 2163,\n 329,\n 3224,\n 7159,\n 13,\n 198,\n 220,\n 220,\n 220,\n 37227,\n 198,\n 220,\n 220,\n 220,\n 275,\n 11,\n 257,\n 796,\n 9215,\n 62,\n 3903,\n 6603,\n 7,\n 9319,\n 11,\n 1029,\n 11,\n 2494,\n 11,\n 1502,\n 28,\n 2875,\n 8,\n 198,\n 220,\n 220,\n 220,\n 331,\n 796,\n 599,\n 82,\n 328,\n 13,\n 1652,\n 346,\n 353,\n 7,\n 65,\n 11,\n 257,\n 11,\n 1366,\n 8,\n 198,\n 220,\n 220,\n 220,\n 1441,\n 331,\n 628,\n 198,\n 198,\n 4299,\n 7716,\n 62,\n 701,\n 65,\n 62,\n 1370,\n 7,\n 35324,\n 11,\n 6934,\n 11,\n 12429,\n 46265,\n 22046,\n 2599,\n 198,\n 220,\n 220,\n 220,\n 37227,\n 15553,\n 326,\n 18616,\n 281,\n 19446,\n 33,\n 2393,\n 329,\n 257,\n 1351,\n 286,\n 198,\n 220,\n 220,\n 220,\n 220,\n 220,\n 220,\n 220,\n 19998,\n 11,\n 5556,\n 17851,\n 1634,\n 5254,\n 13,\n 628,\n 220,\n 220,\n 220,\n 220,\n 220,\n 220,\n 220,\n 479,\n 86,\n 22046,\n 389,\n 3804,\n 355,\n 3224,\n 3689,\n 329,\n 262,\n 10117,\n 65,\n 198,\n 220,\n 220,\n 220,\n 220,\n 220,\n 220,\n 220,\n 15458,\n 13,\n 7383,\n 10879,\n 389,\n 25,\n 628,\n 220,\n 220,\n 220,\n 220,\n 220,\n 220,\n 220,\n 19972,\n 25,\n 20512,\n 198,\n 220,\n 220,\n 220,\n 220,\n 220,\n 220,\n 220,\n 19550,\n 2305,\n 25,\n 12178,\n 198,\n 220,\n 220,\n 220,\n 220,\n 220,\n 220,\n 220,\n 31919,\n 25,\n 493,\n 198,\n 220,\n 220,\n 220,\n 220,\n 220,\n 220,\n 220,\n 1341,\n 10257,\n 1726,\n 25,\n 20512,\n 198,\n 220,\n 220,\n 220,\n 220,\n 220,\n 220,\n 220,\n 1553,\n 19503,\n 80,\n 25,\n 12178,\n 198,\n 220,\n 220,\n 220,\n 220,\n 220,\n 220,\n 220,\n 1553,\n 6477,\n 25,\n 493,\n 198,\n 220,\n 220,\n 220,\n 220,\n 220,\n 220,\n 220,\n 2386,\n 628,\n 220,\n 220,\n 220,\n 220,\n 220,\n 220,\n 220,\n 10007,\n 25,\n 198,\n 220,\n 220,\n 220,\n 220,\n 220,\n 220,\n 220,\n 220,\n 24305,\n 198,\n 220,\n 220,\n 220,\n 220,\n 220,\n 220,\n 220,\n 1058,\n 17143,\n 8373,\n 25,\n 12178,\n 329,\n 8373,\n 287,\n 19805,\n 198,\n 220,\n 220,\n 220,\n 220,\n 220,\n 220,\n 220,\n 1058,\n 17143,\n 6934,\n 25,\n 493,\n 1271,\n 286,\n 6934,\n 284,\n 19386,\n 329,\n 628,\n 220,\n 220,\n 220,\n 220,\n 220,\n 220,\n 220,\n 5860,\n 25,\n 198,\n 220,\n 220,\n 220,\n 220,\n 220,\n 220,\n 220,\n 220,\n 24305,\n 198,\n 220,\n 220,\n 220,\n 220,\n 220,\n 220,\n 220,\n 1058,\n 7783,\n 10117,\n 65,\n 1370,\n 25,\n 965,\n 198,\n 220,\n 220,\n 220,\n 37227,\n 198,\n 220,\n 220,\n 220,\n 1627,\n 796,\n 366,\n 701,\n 76,\n 29164,\n 25,\n 13,\n 19,\n 69,\n 92,\n 6934,\n 29164,\n 92,\n 1911,\n 18982,\n 7,\n 35324,\n 11,\n 6934,\n 8,\n 198,\n 220,\n 220,\n 220,\n 329,\n 1994,\n 11,\n 1988,\n 287,\n 479,\n 86,\n 22046,\n 13,\n 23814,\n 33529,\n 198,\n 220,\n 220,\n 220,\n 220,\n 220,\n 220,\n 220,\n 1627,\n 15853,\n 366,\n 23884,\n 29164,\n 92,\n 1911,\n 18982,\n 7,\n 2539,\n 11,\n 1988,\n 8,\n 198,\n 220,\n 220,\n 220,\n 1627,\n 15853,\n 37082,\n 77,\n 1,\n 198,\n 220,\n 220,\n 220,\n 1441,\n 1627,\n 628,\n 198,\n 4299,\n 497,\n 84,\n 62,\n 66,\n 47467,\n 1096,\n 62,\n 69,\n 8897,\n 3976,\n 7,\n 69,\n 8897,\n 3976,\n 11,\n 17509,\n 871,\n 28,\n 14202,\n 11,\n 299,\n 20910,\n 28,\n 1120,\n 11,\n 12429,\n 46265,\n 22046,\n 2599,\n 198,\n 220,\n 220,\n 220,\n 37227,\n 198,\n 220,\n 220,\n 220,\n 220,\n 220,\n 220,\n 220,\n 371,\n 28399,\n 284,\n 7716,\n 281,\n 19446,\n 33,\n 15458,\n 2393,\n 329,\n 9489,\n 257,\n 2168,\n 286,\n 5254,\n 198,\n 220,\n 220,\n 220,\n 220,\n 220,\n 220,\n 220,\n 319,\n 19998,\n 13,\n 198,\n 220,\n 220,\n 220,\n 37227,\n 198,\n 220,\n 220,\n 220,\n 10117,\n 65,\n 62,\n 8841,\n 796,\n 13538,\n 198,\n 220,\n 220,\n 220,\n 611,\n 17509,\n 871,\n 25,\n 198,\n 220,\n 220,\n 220,\n 220,\n 220,\n 220,\n 220,\n 2593,\n 62,\n 600,\n 796,\n 17509,\n 871,\n 1220,\n 45941,\n 13,\n 9806,\n 7,\n 600,\n 641,\n 871,\n 8,\n 198,\n 220,\n 220,\n 220,\n 220,\n 220,\n 220,\n 220,\n 2823,\n 9127,\n 82,\n 796,\n 45941,\n 13,\n 744,\n 7,\n 77,\n 20910,\n 1220,\n 2593,\n 62,\n 600,\n 737,\n 459,\n 2981,\n 7,\n 600,\n 8,\n 198,\n 220,\n 220,\n 220,\n 2073,\n 25,\n 198,\n 220,\n 220,\n 220,\n 220,\n 220,\n 220,\n 220,\n 2823,\n 9127,\n 82,\n 796,\n 45941,\n 13,\n 12853,\n 7,\n 11925,\n 7,\n 69,\n 8897,\n 3976,\n 828,\n 299,\n 20910,\n 11,\n 288,\n 4906,\n 28,\n 600,\n 8,\n 628,\n 220,\n 220,\n 220,\n 1303,\n 4277,\n 6460,\n 329,\n 477,\n 3404,\n 198,\n 220,\n 220,\n 220,\n 5772,\n 62,\n 11600,\n 796,\n 1391,\n 198,\n 220,\n 220,\n 220,\n 220,\n 220,\n 220,\n 220,\n 366,\n 67,\n 541,\n 2305,\n 1298,\n 352,\n 13,\n 15,\n 11,\n 198,\n 220,\n 220,\n 220,\n 220,\n 220,\n 220,\n 220,\n 366,\n 19726,\n 3262,\n 1298,\n 366,\n 9562,\n 1600,\n 198,\n 220,\n 220,\n 220,\n 220,\n 220,\n 220,\n 220,\n 366,\n 7109,\n 6477,\n 1298,\n 366,\n 940,\n 1600,\n 198,\n 220,\n 220,\n 220,\n 220,\n 220,\n 220,\n 220,\n 366,\n 20545,\n 457,\n 1726,\n 1298,\n 366,\n 9562,\n 1600,\n 198,\n 220,\n 220,\n 220,\n 1782,\n 628,\n 220,\n 220,\n 220,\n 5772,\n 62,\n 11600,\n 13,\n 19119,\n 7,\n 46265,\n 22046,\n 8,\n 198,\n 220,\n 220,\n 220,\n 329,\n 2030,\n 80,\n 11,\n 2823,\n 287,\n 19974,\n 7,\n 69,\n 8897,\n 3976,\n 11,\n 2823,\n 9127,\n 82,\n 2599,\n 198,\n 220,\n 220,\n 220,\n 220,\n 220,\n 220,\n 220,\n 10117,\n 65,\n 62,\n 8841,\n 15853,\n 7716,\n 62,\n 701,\n 65,\n 62,\n 2536,\n 7,\n 19503,\n 80,\n 11,\n 2823,\n 11,\n 12429,\n 17143,\n 62,\n 11600,\n 8,\n 198,\n 220,\n 220,\n 220,\n 220,\n 220,\n 220,\n 220,\n 611,\n 366,\n 19726,\n 3262,\n 1,\n 287,\n 479,\n 86,\n 22046,\n 25,\n 198,\n 220,\n 220,\n 220,\n 220,\n 220,\n 220,\n 220,\n 220,\n 220,\n 220,\n 220,\n 5772,\n 62,\n 11600,\n 14692,\n 19726,\n 3262,\n 8973,\n 796,\n 366,\n 7942,\n 1,\n 198,\n 220,\n 220,\n 220,\n 220,\n 220,\n 220,\n 220,\n 220,\n 220,\n 220,\n 220,\n 10117,\n 65,\n 62,\n 8841,\n 15853,\n 7716,\n 62,\n 701,\n 65,\n 62,\n 2536,\n 7,\n 19503,\n 80,\n 11,\n 2823,\n 11,\n 12429,\n 17143,\n 62,\n 11600,\n 8,\n 628,\n 198,\n 4299,\n 17851,\n 1096,\n 62,\n 69,\n 8897,\n 3976,\n 7,\n 198,\n 220,\n 220,\n 220,\n 19998,\n 11,\n 198,\n 220,\n 220,\n 220,\n 299,\n 20910,\n 28,\n 1120,\n 11,\n 198,\n 220,\n 220,\n 220,\n 17509,\n 871,\n 28,\n 14202,\n 11,\n 198,\n 220,\n 220,\n 220,\n 1176,\n 28,\n 14202,\n 11,\n 198,\n 220,\n 220,\n 220,\n 708,\n 77,\n 62,\n 4868,\n 28,\n 14202,\n 11,\n 198,\n 220,\n 220,\n 220,\n 19550,\n 2305,\n 28,\n 14202,\n 11,\n 198,\n 220,\n 220,\n 220,\n 708,\n 77,\n 28,\n 14202,\n 11,\n 198,\n 220,\n 220,\n 220,\n 19972,\n 28,\n 25101,\n 11,\n 198,\n 220,\n 220,\n 220,\n 1553,\n 28,\n 25101,\n 11,\n 198,\n 220,\n 220,\n 220,\n 17655,\n 28,\n 25101,\n 11,\n 198,\n 2599,\n 198,\n 220,\n 220,\n 220,\n 37227,\n 198,\n 220,\n 220,\n 220,\n 220,\n 220,\n 220,\n 220,\n 15553,\n 326,\n 481,\n 5794,\n 281,\n 19446,\n 15458,\n 2393,\n 284,\n 1620,\n 17851,\n 1634,\n 198,\n 220,\n 220,\n 220,\n 220,\n 220,\n 220,\n 220,\n 5254,\n 11,\n 351,\n 617,\n 13688,\n 319,\n 703,\n 1728,\n 5254,\n 389,\n 6157,\n 13,\n 198,\n 220,\n 220,\n 220,\n 37227,\n 198,\n 220,\n 220,\n 220,\n 10117,\n 65,\n 62,\n 2536,\n 796,\n 13538,\n 198,\n 220,\n 220,\n 220,\n 611,\n 17509,\n 871,\n 318,\n 6045,\n 25,\n 198,\n 220,\n 220,\n 220,\n 220,\n 220,\n 220,\n 220,\n 6934,\n 796,\n 45941,\n 13,\n 12853,\n 7,\n 11925,\n 7,\n 69,\n 8897,\n 3976,\n 828,\n 299,\n 20910,\n 11,\n 288,\n 4906,\n 28,\n 600,\n 8,\n 198,\n 220,\n 220,\n 220,\n 2073,\n 25,\n 198,\n 220,\n 220,\n 220,\n 220,\n 220,\n 220,\n 220,\n 6934,\n 796,\n 45941,\n 13,\n 31166,\n 17034,\n 7,\n 77,\n 20910,\n 1220,\n 17509,\n 871,\n 737,\n 459,\n 2981,\n 7,\n 600,\n 8,\n 628,\n 220,\n 220,\n 220,\n 611,\n 19550,\n 2305,\n 25,\n 198,\n 220,\n 220,\n 220,\n 220,\n 220,\n 220,\n 220,\n 611,\n 708,\n 77,\n 318,\n 6045,\n 25,\n 198,\n 220,\n 220,\n 220,\n 220,\n 220,\n 220,\n 220,\n 220,\n 220,\n 220,\n 220,\n 1303,\n 1002,\n 19550,\n 2305,\n 1332,\n 9167,\n 11,\n 475,\n 645,\n 31919,\n 2288,\n 198,\n 220,\n 220,\n 220,\n 220,\n 220,\n 220,\n 220,\n 220,\n 220,\n 220,\n 220,\n 1303,\n 14275,\n 466,\n 262,\n 4277,\n 16085,\n 198,\n 220,\n 220,\n 220,\n 220,\n 220,\n 220,\n 220,\n 220,\n 220,\n 220,\n 220,\n 19550,\n 2305,\n 62,\n 9288,\n 796,\n 685,\n 15,\n 13,\n 486,\n 11,\n 657,\n 13,\n 16,\n 11,\n 352,\n 13,\n 15,\n 11,\n 513,\n 13,\n 15,\n 11,\n 642,\n 13,\n 15,\n 60,\n 198,\n 220,\n 220,\n 220,\n 220,\n 220,\n 220,\n 220,\n 220,\n 220,\n 220,\n 220,\n 19550,\n 2305,\n 62,\n 32109,\n 796,\n 366,\n 67,\n 541,\n 2305,\n 1,\n 198,\n 220,\n 220,\n 220,\n 220,\n 220,\n 220,\n 220,\n 2073,\n 25,\n 198,\n 220,\n 220,\n 220,\n 220,\n 220,\n 220,\n 220,\n 220,\n 220,\n 220,\n 220,\n 1303,\n 15323,\n 1057,\n 2176,\n 31919,\n 6055,\n 198,\n 220,\n 220,\n 220,\n 220,\n 220,\n 220,\n 220,\n 220,\n 220,\n 220,\n 220,\n 19550,\n 2305,\n 62,\n 9288,\n 796,\n 708,\n 77,\n 62,\n 4868,\n 198,\n 220,\n 220,\n 220,\n 220,\n 220,\n 220,\n 220,\n 220,\n 220,\n 220,\n 220,\n 19550,\n 2305,\n 62,\n 32109,\n 796,\n 366,\n 41769,\n 1,\n 628,\n 220,\n 220,\n 220,\n 611,\n 1553,\n 318,\n 6407,\n 25,\n 198,\n 220,\n 220,\n 220,\n 220,\n 220,\n 220,\n 220,\n 2030,\n 80,\n 62,\n 4868,\n 796,\n 17790,\n 7,\n 69,\n 8897,\n 3976,\n 11,\n 362,\n 8,\n 198,\n 220,\n 220,\n 220,\n 220,\n 220,\n 220,\n 220,\n 3601,\n 7,\n 4868,\n 7,\n 19503,\n 80,\n 62,\n 4868,\n 4008,\n 198,\n 220,\n 220,\n 220,\n 2073,\n 25,\n 198,\n 220,\n 220,\n 220,\n 220,\n 220,\n 220,\n 220,\n 2030,\n 80,\n 62,\n 4868,\n 796,\n 19998,\n 628,\n 220,\n 220,\n 220,\n 1303,\n 9052,\n 625,\n 1123,\n 8373,\n 290,\n 1271,\n 286,\n 6934,\n 198,\n 220,\n 220,\n 220,\n 329,\n 1988,\n 11,\n 2823,\n 9127,\n 287,\n 19974,\n 7,\n 19503,\n 80,\n 62,\n 4868,\n 11,\n 6934,\n 2599,\n 198,\n 220,\n 220,\n 220,\n 220,\n 220,\n 220,\n 220,\n 611,\n 1553,\n 318,\n 6407,\n 25,\n 198,\n 220,\n 220,\n 220,\n 220,\n 220,\n 220,\n 220,\n 220,\n 220,\n 220,\n 220,\n 2030,\n 80,\n 11,\n 1553,\n 62,\n 19503,\n 80,\n 796,\n 1988,\n 198,\n 220,\n 220,\n 220,\n 220,\n 220,\n 220,\n 220,\n 2073,\n 25,\n 198,\n 220,\n 220,\n 220,\n 220,\n 220,\n 220,\n 220,\n 220,\n 220,\n 220,\n 220,\n 2030,\n 80,\n 796,\n 1988,\n 198,\n 220,\n 220,\n 220,\n 220,\n 220,\n 220,\n 220,\n 220,\n 220,\n 220,\n 220,\n 1303,\n 2980,\n 378,\n 3487,\n 13432,\n 198,\n 220,\n 220,\n 220,\n 220,\n 220,\n 220,\n 220,\n 1949,\n 25,\n 198,\n 220,\n 220,\n 220,\n 220,\n 220,\n 220,\n 220,\n 220,\n 220,\n 220,\n 220,\n 2030,\n 80,\n 796,\n 12178,\n 7,\n 19503,\n 80,\n 8,\n 198,\n 220,\n 220,\n 220,\n 220,\n 220,\n 220,\n 220,\n 220,\n 220,\n 220,\n 220,\n 2823,\n 9127,\n 796,\n 493,\n 7,\n 9442,\n 9127,\n 8,\n 198,\n 220,\n 220,\n 220,\n 220,\n 220,\n 220,\n 220,\n 220,\n 220,\n 220,\n 220,\n 611,\n 1553,\n 318,\n 6407,\n 25,\n 198,\n 220,\n 220,\n 220,\n 220,\n 220,\n 220,\n 220,\n 220,\n 220,\n 220,\n 220,\n 220,\n 220,\n 220,\n 220,\n 1553,\n 62,\n 19503,\n 80,\n 796,\n 12178,\n 7,\n 7109,\n 62,\n 19503,\n 80,\n 8,\n 628,\n 220,\n 220,\n 220,\n 220,\n 220,\n 220,\n 220,\n 220,\n 220,\n 220,\n 220,\n 10117,\n 65,\n 62,\n 2536,\n 15853,\n 7716,\n 62,\n 701,\n 65,\n 62,\n 1370,\n 7,\n 19503,\n 80,\n 11,\n 2823,\n 9127,\n 11,\n 12429,\n 4895,\n 20545,\n 457,\n 1726,\n 1298,\n 366,\n 9562,\n 20662,\n 8,\n 628,\n 220,\n 220,\n 220,\n 220,\n 220,\n 220,\n 220,\n 220,\n 220,\n 220,\n 220,\n 611,\n 1553,\n 318,\n 6407,\n 25,\n 198,\n 220,\n 220,\n 220,\n 220,\n 220,\n 220,\n 220,\n 220,\n 220,\n 220,\n 220,\n 220,\n 220,\n 220,\n 220,\n 10117,\n 65,\n 62,\n 2536,\n 15853,\n 7716,\n 62,\n 701,\n 65,\n 62,\n 1370,\n 7,\n 198,\n 220,\n 220,\n 220,\n 220,\n 220,\n 220,\n 220,\n 220,\n 220,\n 220,\n 220,\n 220,\n 220,\n 220,\n 220,\n 220,\n 220,\n 220,\n 220,\n 2030,\n 80,\n 11,\n 2823,\n 9127,\n 11,\n 12429,\n 4895,\n 20545,\n 457,\n 1726,\n 1298,\n 366,\n 7942,\n 1600,\n 366,\n 7109,\n 19503,\n 80,\n 1298,\n 1553,\n 62,\n 19503,\n 80,\n 92,\n 198,\n 220,\n 220,\n 220,\n 220,\n 220,\n 220,\n 220,\n 220,\n 220,\n 220,\n 220,\n 220,\n 220,\n 220,\n 220,\n 1267,\n 628,\n 220,\n 220,\n 220,\n 220,\n 220,\n 220,\n 220,\n 220,\n 220,\n 220,\n 220,\n 611,\n 19550,\n 2305,\n 318,\n 6407,\n 25,\n 198,\n 220,\n 220,\n 220,\n 220,\n 220,\n 220,\n 220,\n 220,\n 220,\n 220,\n 220,\n 220,\n 220,\n 220,\n 220,\n 329,\n 19550,\n 2305,\n 62,\n 8367,\n 287,\n 19550,\n 2305,\n 62,\n 9288,\n 25,\n 198,\n 220,\n 220,\n 220,\n 220,\n 220,\n 220,\n 220,\n 220,\n 220,\n 220,\n 220,\n 220,\n 220,\n 220,\n 220,\n 220,\n 220,\n 220,\n 220,\n 10117,\n 65,\n 62,\n 2536,\n 15853,\n 7716,\n 62,\n 701,\n 65,\n 62,\n 1370,\n 7,\n 198,\n 220,\n 220,\n 220,\n 220,\n 220,\n 220,\n 220,\n 220,\n 220,\n 220,\n 220,\n 220,\n 220,\n 220,\n 220,\n 220,\n 220,\n 220,\n 220,\n 220,\n 220,\n 220,\n 220,\n 2030,\n 80,\n 11,\n 2823,\n 9127,\n 11,\n 12429,\n 90,\n 67,\n 541,\n 2305,\n 62,\n 32109,\n 25,\n 19550,\n 2305,\n 62,\n 8367,\n 92,\n 198,\n 220,\n 220,\n 220,\n 220,\n 220,\n 220,\n 220,\n 220,\n 220,\n 220,\n 220,\n 220,\n 220,\n 220,\n 220,\n 220,\n 220,\n 220,\n 220,\n 1267,\n 628,\n 220,\n 220,\n 220,\n 220,\n 220,\n 220,\n 220,\n 220,\n 220,\n 220,\n 220,\n 611,\n 19972,\n 318,\n 6407,\n 25,\n 198,\n 220,\n 220,\n 220,\n 220,\n 220,\n 220,\n 220,\n 220,\n 220,\n 220,\n 220,\n 220,\n 220,\n 220,\n 220,\n 10117,\n 65,\n 62,\n 2536,\n 15853,\n 7716,\n 62,\n 701,\n 65,\n 62,\n 1370,\n 7,\n 19503,\n 80,\n 11,\n 2823,\n 9127,\n 11,\n 12429,\n 4895,\n 19726,\n 3262,\n 1298,\n 366,\n 7942,\n 20662,\n 8,\n 628,\n 220,\n 220,\n 220,\n 220,\n 220,\n 220,\n 220,\n 220,\n 220,\n 220,\n 220,\n 611,\n 17655,\n 318,\n 6407,\n 25,\n 198,\n 220,\n 220,\n 220,\n 220,\n 220,\n 220,\n 220,\n 220,\n 220,\n 220,\n 220,\n 220,\n 220,\n 220,\n 220,\n 1303,\n 34098,\n 262,\n 17655,\n 8931,\n 319,\n 290,\n 572,\n 198,\n 220,\n 220,\n 220,\n 220,\n 220,\n 220,\n 220,\n 220,\n 220,\n 220,\n 220,\n 220,\n 220,\n 220,\n 220,\n 10117,\n 65,\n 62,\n 2536,\n 15853,\n 7716,\n 62,\n 701,\n 65,\n 62,\n 1370,\n 7,\n 198,\n 220,\n 220,\n 220,\n 220,\n 220,\n 220,\n 220,\n 220,\n 220,\n 220,\n 220,\n 220,\n 220,\n 220,\n 220,\n 220,\n 220,\n 220,\n 220,\n 2030,\n 80,\n 11,\n 2823,\n 9127,\n 11,\n 12429,\n 4895,\n 79,\n 9615,\n 11,\n 16,\n 11,\n 25616,\n 1298,\n 366,\n 9562,\n 20662,\n 198,\n 220,\n 220,\n 220,\n 220,\n 220,\n 220,\n 220,\n 220,\n 220,\n 220,\n 220,\n 220,\n 220,\n 220,\n 220,\n 1267,\n 198,\n 220,\n 220,\n 220,\n 220,\n 220,\n 220,\n 220,\n 220,\n 220,\n 220,\n 220,\n 220,\n 220,\n 220,\n 220,\n 10117,\n 65,\n 62,\n 2536,\n 15853,\n 7716,\n 62,\n 701,\n 65,\n 62,\n 1370,\n 7,\n 198,\n 220,\n 220,\n 220,\n 220,\n 220,\n 220,\n 220,\n 220,\n 220,\n 220,\n 220,\n 220,\n 220,\n 220,\n 220,\n 220,\n 220,\n 220,\n 220,\n 2030,\n 80,\n 11,\n 2823,\n 9127,\n 11,\n 12429,\n 4895,\n 79,\n 9615,\n 11,\n 16,\n 11,\n 25616,\n 1298,\n 366,\n 7942,\n 20662,\n 198,\n 220,\n 220,\n 220,\n 220,\n 220,\n 220,\n 220,\n 220,\n 220,\n 220,\n 220,\n 220,\n 220,\n 220,\n 220,\n 1267,\n 198,\n 220,\n 220,\n 220,\n 220,\n 220,\n 220,\n 220,\n 2845,\n 11052,\n 12331,\n 25,\n 198,\n 220,\n 220,\n 220,\n 220,\n 220,\n 220,\n 220,\n 220,\n 220,\n 220,\n 220,\n 3601,\n 7203,\n 12331,\n 351,\n 366,\n 1343,\n 965,\n 7,\n 8367,\n 4008,\n 628,\n 220,\n 220,\n 220,\n 1441,\n 10117,\n 65,\n 62,\n 2536,\n 628,\n 198,\n 4299,\n 15284,\n 62,\n 18908,\n 1358,\n 62,\n 22355,\n 7,\n 47799,\n 11,\n 299,\n 20910,\n 28,\n 1120,\n 2599,\n 198,\n 220,\n 220,\n 220,\n 37227,\n 198,\n 220,\n 220,\n 220,\n 220,\n 220,\n 220,\n 220,\n 11789,\n 329,\n 26019,\n 262,\n 2938,\n 11812,\n 640,\n 198,\n 220,\n 220,\n 220,\n 220,\n 220,\n 220,\n 220,\n 287,\n 2823,\n 9853,\n 1912,\n 319,\n 262,\n 12245,\n 26,\n 2035,\n 16200,\n 198,\n 220,\n 220,\n 220,\n 220,\n 220,\n 220,\n 220,\n 1627,\n 18929,\n 393,\n 11346,\n 49,\n 13,\n 628,\n 220,\n 220,\n 220,\n 220,\n 220,\n 220,\n 220,\n 10007,\n 25,\n 198,\n 220,\n 220,\n 220,\n 220,\n 220,\n 220,\n 220,\n 220,\n 24305,\n 198,\n 220,\n 220,\n 220,\n 220,\n 220,\n 220,\n 220,\n 12245,\n 532,\n 7177,\n 286,\n 12245,\n 18663,\n 26,\n 304,\n 13,\n 70,\n 13,\n 11346,\n 49,\n 198,\n 220,\n 220,\n 220,\n 220,\n 220,\n 220,\n 220,\n 299,\n 20910,\n 532,\n 11902,\n 493,\n 1271,\n 286,\n 6934,\n 973,\n 329,\n 262,\n 12841,\n 1627,\n 628,\n 220,\n 220,\n 220,\n 220,\n 220,\n 220,\n 220,\n 5860,\n 25,\n 198,\n 220,\n 220,\n 220,\n 220,\n 220,\n 220,\n 220,\n 220,\n 24305,\n 198,\n 220,\n 220,\n 220,\n 220,\n 220,\n 220,\n 220,\n 2823,\n 62,\n 9127,\n 82,\n 532,\n 7177,\n 286,\n 2823,\n 9853,\n 329,\n 1123,\n 8373,\n 198,\n 220,\n 220,\n 220,\n 37227,\n 198,\n 220,\n 220,\n 220,\n 2593,\n 62,\n 600,\n 796,\n 12245,\n 1220,\n 45941,\n 13,\n 9806,\n 7,\n 47799,\n 8,\n 198,\n 220,\n 220,\n 220,\n 2823,\n 62,\n 9127,\n 82,\n 796,\n 45941,\n 13,\n 744,\n 7,\n 77,\n 20910,\n 1220,\n 2593,\n 62,\n 600,\n 737,\n 459,\n 2981,\n 7,\n 600,\n 8,\n 198,\n 220,\n 220,\n 220,\n 1441,\n 2823,\n 62,\n 9127,\n 82,\n 628,\n 628,\n 198,\n 31,\n 19608,\n 330,\n 31172,\n 628,\n 198,\n 31,\n 19608,\n 330,\n 31172,\n 198\n]"},"ratio_char_token":{"kind":"number","value":2.30752688172043,"string":"2.307527"},"token_count":{"kind":"number","value":12555,"string":"12,555"}}},{"rowIdx":1238,"cells":{"content":{"kind":"string","value":"import json\nfrom dataclasses import dataclass\n\nimport omitempty\n\nfrom dnsimple.struct import Struct\n\n\nclass DomainRenewRequest(dict):\n \"\"\"DomainRenewRequest represents the attributes you can pass to a renew API request.\"\"\"\n\n\n@dataclass\nclass DomainRenewal(Struct):\n\n \"\"\"Represents the result of a domain renewal call.\"\"\"\n id = None\n \"\"\"The domain registration ID in DNSimple\"\"\"\n domain_id = None\n \"\"\"The associated domain ID\"\"\"\n state = None\n \"\"\"The state of the renewal\"\"\"\n period = None\n \"\"\"The number of years the domain was registered for\"\"\"\n created_at = None\n \"\"\"When the domain renewal was created in DNSimple\"\"\"\n updated_at = None\n \"\"\"When the domain renewal was last updated in DNSimple\"\"\"\n"},"input_ids":{"kind":"list like","value":[11748,33918,198,6738,4818,330,28958,1330,4818,330,31172,198,198,11748,42848,28920,198,198,6738,288,5907,320,1154,13,7249,1330,32112,628,198,4871,20021,26764,413,18453,7,11600,2599,198,220,220,220,37227,43961,26764,413,18453,6870,262,12608,345,460,1208,284,257,6931,7824,2581,526,15931,628,198,31,19608,330,31172,198,4871,20021,26764,413,282,7,44909,2599,628,220,220,220,37227,6207,6629,262,1255,286,257,7386,22901,869,526,15931,198,220,220,220,4686,796,6045,198,220,220,220,37227,464,7386,9352,4522,287,18538,320,1154,37811,198,220,220,220,7386,62,312,796,6045,198,220,220,220,37227,464,3917,7386,4522,37811,198,220,220,220,1181,796,6045,198,220,220,220,37227,464,1181,286,262,22901,37811,198,220,220,220,2278,796,6045,198,220,220,220,37227,464,1271,286,812,262,7386,373,6823,329,37811,198,220,220,220,2727,62,265,796,6045,198,220,220,220,37227,2215,262,7386,22901,373,2727,287,18538,320,1154,37811,198,220,220,220,6153,62,265,796,6045,198,220,220,220,37227,2215,262,7386,22901,373,938,6153,287,18538,320,1154,37811,198],"string":"[\n 11748,\n 33918,\n 198,\n 6738,\n 4818,\n 330,\n 28958,\n 1330,\n 4818,\n 330,\n 31172,\n 198,\n 198,\n 11748,\n 42848,\n 28920,\n 198,\n 198,\n 6738,\n 288,\n 5907,\n 320,\n 1154,\n 13,\n 7249,\n 1330,\n 32112,\n 628,\n 198,\n 4871,\n 20021,\n 26764,\n 413,\n 18453,\n 7,\n 11600,\n 2599,\n 198,\n 220,\n 220,\n 220,\n 37227,\n 43961,\n 26764,\n 413,\n 18453,\n 6870,\n 262,\n 12608,\n 345,\n 460,\n 1208,\n 284,\n 257,\n 6931,\n 7824,\n 2581,\n 526,\n 15931,\n 628,\n 198,\n 31,\n 19608,\n 330,\n 31172,\n 198,\n 4871,\n 20021,\n 26764,\n 413,\n 282,\n 7,\n 44909,\n 2599,\n 628,\n 220,\n 220,\n 220,\n 37227,\n 6207,\n 6629,\n 262,\n 1255,\n 286,\n 257,\n 7386,\n 22901,\n 869,\n 526,\n 15931,\n 198,\n 220,\n 220,\n 220,\n 4686,\n 796,\n 6045,\n 198,\n 220,\n 220,\n 220,\n 37227,\n 464,\n 7386,\n 9352,\n 4522,\n 287,\n 18538,\n 320,\n 1154,\n 37811,\n 198,\n 220,\n 220,\n 220,\n 7386,\n 62,\n 312,\n 796,\n 6045,\n 198,\n 220,\n 220,\n 220,\n 37227,\n 464,\n 3917,\n 7386,\n 4522,\n 37811,\n 198,\n 220,\n 220,\n 220,\n 1181,\n 796,\n 6045,\n 198,\n 220,\n 220,\n 220,\n 37227,\n 464,\n 1181,\n 286,\n 262,\n 22901,\n 37811,\n 198,\n 220,\n 220,\n 220,\n 2278,\n 796,\n 6045,\n 198,\n 220,\n 220,\n 220,\n 37227,\n 464,\n 1271,\n 286,\n 812,\n 262,\n 7386,\n 373,\n 6823,\n 329,\n 37811,\n 198,\n 220,\n 220,\n 220,\n 2727,\n 62,\n 265,\n 796,\n 6045,\n 198,\n 220,\n 220,\n 220,\n 37227,\n 2215,\n 262,\n 7386,\n 22901,\n 373,\n 2727,\n 287,\n 18538,\n 320,\n 1154,\n 37811,\n 198,\n 220,\n 220,\n 220,\n 6153,\n 62,\n 265,\n 796,\n 6045,\n 198,\n 220,\n 220,\n 220,\n 37227,\n 2215,\n 262,\n 7386,\n 22901,\n 373,\n 938,\n 6153,\n 287,\n 18538,\n 320,\n 1154,\n 37811,\n 198\n]"},"ratio_char_token":{"kind":"number","value":3.3378378378378377,"string":"3.337838"},"token_count":{"kind":"number","value":222,"string":"222"}}},{"rowIdx":1239,"cells":{"content":{"kind":"string","value":"class RequestAdapter(object):\n \"\"\"\n RequestAdapters bridge transmute's\n representation of a request, with the framework's\n implementation.\n\n implement the unimplemented methods.\n \"\"\"\n\n @property\n def body(self):\n \"\"\" return the request body. \"\"\"\n raise NotImplementedError()\n\n def _get_framework_args(self):\n \"\"\"\n often, a framework provides specific variables that are passed\n into the handler function (e.g. the request object in\n aiohttp). return a dictionary of these arguments, which will be\n added to the function arguments if they appear.\n \"\"\"\n raise NotImplementedError()\n"},"input_ids":{"kind":"list like","value":[4871,19390,47307,7,15252,2599,198,220,220,220,37227,198,220,220,220,19390,2782,12126,7696,21595,1133,338,198,220,220,220,10552,286,257,2581,11,351,262,9355,338,198,220,220,220,7822,13,628,220,220,220,3494,262,28418,1154,12061,5050,13,198,220,220,220,37227,628,220,220,220,2488,26745,198,220,220,220,825,1767,7,944,2599,198,220,220,220,220,220,220,220,37227,1441,262,2581,1767,13,37227,198,220,220,220,220,220,220,220,5298,1892,3546,1154,12061,12331,3419,628,220,220,220,825,4808,1136,62,30604,62,22046,7,944,2599,198,220,220,220,220,220,220,220,37227,198,220,220,220,220,220,220,220,1690,11,257,9355,3769,2176,9633,326,389,3804,198,220,220,220,220,220,220,220,656,262,21360,2163,357,68,13,70,13,262,2581,2134,287,198,220,220,220,220,220,220,220,257,952,4023,737,1441,257,22155,286,777,7159,11,543,481,307,198,220,220,220,220,220,220,220,2087,284,262,2163,7159,611,484,1656,13,198,220,220,220,220,220,220,220,37227,198,220,220,220,220,220,220,220,5298,1892,3546,1154,12061,12331,3419,198],"string":"[\n 4871,\n 19390,\n 47307,\n 7,\n 15252,\n 2599,\n 198,\n 220,\n 220,\n 220,\n 37227,\n 198,\n 220,\n 220,\n 220,\n 19390,\n 2782,\n 12126,\n 7696,\n 21595,\n 1133,\n 338,\n 198,\n 220,\n 220,\n 220,\n 10552,\n 286,\n 257,\n 2581,\n 11,\n 351,\n 262,\n 9355,\n 338,\n 198,\n 220,\n 220,\n 220,\n 7822,\n 13,\n 628,\n 220,\n 220,\n 220,\n 3494,\n 262,\n 28418,\n 1154,\n 12061,\n 5050,\n 13,\n 198,\n 220,\n 220,\n 220,\n 37227,\n 628,\n 220,\n 220,\n 220,\n 2488,\n 26745,\n 198,\n 220,\n 220,\n 220,\n 825,\n 1767,\n 7,\n 944,\n 2599,\n 198,\n 220,\n 220,\n 220,\n 220,\n 220,\n 220,\n 220,\n 37227,\n 1441,\n 262,\n 2581,\n 1767,\n 13,\n 37227,\n 198,\n 220,\n 220,\n 220,\n 220,\n 220,\n 220,\n 220,\n 5298,\n 1892,\n 3546,\n 1154,\n 12061,\n 12331,\n 3419,\n 628,\n 220,\n 220,\n 220,\n 825,\n 4808,\n 1136,\n 62,\n 30604,\n 62,\n 22046,\n 7,\n 944,\n 2599,\n 198,\n 220,\n 220,\n 220,\n 220,\n 220,\n 220,\n 220,\n 37227,\n 198,\n 220,\n 220,\n 220,\n 220,\n 220,\n 220,\n 220,\n 1690,\n 11,\n 257,\n 9355,\n 3769,\n 2176,\n 9633,\n 326,\n 389,\n 3804,\n 198,\n 220,\n 220,\n 220,\n 220,\n 220,\n 220,\n 220,\n 656,\n 262,\n 21360,\n 2163,\n 357,\n 68,\n 13,\n 70,\n 13,\n 262,\n 2581,\n 2134,\n 287,\n 198,\n 220,\n 220,\n 220,\n 220,\n 220,\n 220,\n 220,\n 257,\n 952,\n 4023,\n 737,\n 1441,\n 257,\n 22155,\n 286,\n 777,\n 7159,\n 11,\n 543,\n 481,\n 307,\n 198,\n 220,\n 220,\n 220,\n 220,\n 220,\n 220,\n 220,\n 2087,\n 284,\n 262,\n 2163,\n 7159,\n 611,\n 484,\n 1656,\n 13,\n 198,\n 220,\n 220,\n 220,\n 220,\n 220,\n 220,\n 220,\n 37227,\n 198,\n 220,\n 220,\n 220,\n 220,\n 220,\n 220,\n 220,\n 5298,\n 1892,\n 3546,\n 1154,\n 12061,\n 12331,\n 3419,\n 198\n]"},"ratio_char_token":{"kind":"number","value":2.93859649122807,"string":"2.938596"},"token_count":{"kind":"number","value":228,"string":"228"}}},{"rowIdx":1240,"cells":{"content":{"kind":"string","value":"# python3\n\n\"\"\" Task: Count the number of inversions of a given sequence \"\"\"\n\n\n\n\ntot_count = 0\nn = int ( input () )\nseq = [ int ( i ) for i in input ().split () ]\nmergesort ( seq )\nprint ( tot_count )\n"},"input_ids":{"kind":"list like","value":[2,21015,18,198,198,37811,15941,25,2764,262,1271,286,287,47178,286,257,1813,8379,37227,628,628,198,83,313,62,9127,796,657,198,77,796,493,357,5128,7499,1267,198,41068,796,685,493,357,1312,1267,329,1312,287,5128,27972,35312,7499,2361,198,647,3212,419,357,33756,1267,198,4798,357,2006,62,9127,1267,198],"string":"[\n 2,\n 21015,\n 18,\n 198,\n 198,\n 37811,\n 15941,\n 25,\n 2764,\n 262,\n 1271,\n 286,\n 287,\n 47178,\n 286,\n 257,\n 1813,\n 8379,\n 37227,\n 628,\n 628,\n 198,\n 83,\n 313,\n 62,\n 9127,\n 796,\n 657,\n 198,\n 77,\n 796,\n 493,\n 357,\n 5128,\n 7499,\n 1267,\n 198,\n 41068,\n 796,\n 685,\n 493,\n 357,\n 1312,\n 1267,\n 329,\n 1312,\n 287,\n 5128,\n 27972,\n 35312,\n 7499,\n 2361,\n 198,\n 647,\n 3212,\n 419,\n 357,\n 33756,\n 1267,\n 198,\n 4798,\n 357,\n 2006,\n 62,\n 9127,\n 1267,\n 198\n]"},"ratio_char_token":{"kind":"number","value":2.985074626865672,"string":"2.985075"},"token_count":{"kind":"number","value":67,"string":"67"}}},{"rowIdx":1241,"cells":{"content":{"kind":"string","value":"import numpy as np\nimport scipy.misc\nimport os\nimport time\n# from PIL import Image\n\nDATA_DIR = '/home/ubuntu/lsun/bedrooms/'\nNEW_DATA_DIR = '/home/ubuntu/lsun/bedrooms_128/'\n\n# with open(DATA_DIR+'files.txt', 'r') as f:\n# files = [l[:-1] for l in f]\n# # images = np.zeros((batch_size, 3, 256, 256), dtype='int32')\n# random_state = np.random.RandomState(42)\n# random_state.shuffle(files)\n\n# z = 1729468\n# for i, path in enumerate(files):\n# if i < 1729500:\n# continue\n# try:\n# image = scipy.misc.imread(\n# os.path.normpath(os.path.join(DATA_DIR, path))\n# )\n\n# # try: \n# # image = image.transpose(2,0,1)\n# offset_y = (image.shape[0]-256)/2\n# offset_x = (image.shape[1]-256)/2\n# image = image[offset_y:offset_y+256, offset_x:offset_x+256]\n# image = image[::2,::2]+image[1::2,::2]+image[::2,1::2]+image[1::2,1::2]\n# image = image / 4\n# # image = image.astype('int32')\n# # im = Image.fromarray(image)\n# # p = os.path.normpath(os.path.join(NEW_DATA_DIR, path))\n# # try:\n# # os.makedirs(os.path.dirname(p))\n# # except:\n# # pass\n# scipy.misc.imsave(NEW_DATA_DIR+'{}.jpg'.format(z), image)\n# # im.save(p[:-4]+'jpg')\n# if z % 100 == 0:\n# print z\n# z += 1\n# except:\n# print \"skip\"\n\n# # if i > 0 and i % batch_size == 0:\n# # if downscale:\n# # downscaled_images = images[:,:,::2,::2] + images[:,:,1::2,::2] + images[:,:,::2,1::2] + images[:,:,1::2,1::2]\n# # downscaled_images = downscaled_images / 4.\n# # yield (downscaled_images.astype('int32'),)\n# # else:\n# # yield (images,)\n# # except Exception as ex:\n# # print ex\n# # print \"warning data preprocess failed for path {}\".format(path)\n\n\nif __name__ == '__main__':\n train_gen = load(64)\n t0 = time.time()\n for i, batch in enumerate(train_gen(), start=1):\n print \"{}\\t{}\".format(str(time.time() - t0), batch[0][0,0,0,0])\n if i == 1000:\n break\n t0 = time.time()\n"},"input_ids":{"kind":"list like","value":[11748,299,32152,355,45941,198,11748,629,541,88,13,44374,198,11748,28686,198,11748,640,198,2,422,350,4146,1330,7412,198,198,26947,62,34720,796,31051,11195,14,32230,14,7278,403,14,3077,9649,14,6,198,13965,62,26947,62,34720,796,31051,11195,14,32230,14,7278,403,14,3077,9649,62,12762,14,6,198,198,2,351,1280,7,26947,62,34720,10,6,16624,13,14116,3256,705,81,11537,355,277,25,198,2,220,220,220,220,3696,796,685,75,58,21912,16,60,329,300,287,277,60,198,2,1303,4263,796,45941,13,9107,418,19510,43501,62,7857,11,513,11,17759,11,17759,828,288,4906,11639,600,2624,11537,198,2,4738,62,5219,796,45941,13,25120,13,29531,9012,7,3682,8,198,2,4738,62,5219,13,1477,18137,7,16624,8,198,198,2,1976,796,1596,27696,3104,198,2,329,1312,11,3108,287,27056,378,7,16624,2599,198,2,220,220,220,220,611,1312,1279,1596,1959,4059,25,198,2,220,220,220,220,220,220,220,220,2555,198,2,220,220,220,220,1949,25,198,2,220,220,220,220,220,220,220,220,2939,796,629,541,88,13,44374,13,320,961,7,198,2,220,220,220,220,220,220,220,220,220,220,220,220,28686,13,6978,13,27237,6978,7,418,13,6978,13,22179,7,26947,62,34720,11,3108,4008,198,2,220,220,220,220,220,220,220,220,1267,198,198,2,220,220,220,220,220,220,220,220,1303,1949,25,220,220,220,220,220,220,220,220,220,220,220,220,220,220,220,220,198,2,220,220,220,220,220,220,220,220,1303,2939,796,2939,13,7645,3455,7,17,11,15,11,16,8,198,2,220,220,220,220,220,220,220,220,11677,62,88,796,357,9060,13,43358,58,15,45297,11645,20679,17,198,2,220,220,220,220,220,220,220,220,11677,62,87,796,357,9060,13,43358,58,16,45297,11645,20679,17,198,2,220,220,220,220,220,220,220,220,2939,796,2939,58,28968,62,88,25,28968,62,88,10,11645,11,11677,62,87,25,28968,62,87,10,11645,60,198,2,220,220,220,220,220,220,220,220,2939,796,2939,58,3712,17,11,3712,17,48688,9060,58,16,3712,17,11,3712,17,48688,9060,58,3712,17,11,16,3712,17,48688,9060,58,16,3712,17,11,16,3712,17,60,198,2,220,220,220,220,220,220,220,220,2939,796,2939,1220,604,198,2,220,220,220,220,220,220,220,220,1303,2939,796,2939,13,459,2981,10786,600,2624,11537,198,2,220,220,220,220,220,220,220,220,1303,545,796,7412,13,6738,18747,7,9060,8,198,2,220,220,220,220,220,220,220,220,1303,279,796,28686,13,6978,13,27237,6978,7,418,13,6978,13,22179,7,13965,62,26947,62,34720,11,3108,4008,198,2,220,220,220,220,220,220,220,220,1303,1949,25,198,2,220,220,220,220,220,220,220,220,1303,220,220,220,220,28686,13,76,4335,17062,7,418,13,6978,13,15908,3672,7,79,4008,198,2,220,220,220,220,220,220,220,220,1303,2845,25,198,2,220,220,220,220,220,220,220,220,1303,220,220,220,220,1208,198,2,220,220,220,220,220,220,220,220,629,541,88,13,44374,13,12078,1015,7,13965,62,26947,62,34720,10,6,90,27422,9479,4458,18982,7,89,828,2939,8,198,2,220,220,220,220,220,220,220,220,1303,545,13,21928,7,79,58,21912,19,48688,6,9479,11537,198,2,220,220,220,220,220,220,220,220,611,1976,4064,1802,6624,657,25,198,2,220,220,220,220,220,220,220,220,220,220,220,220,3601,1976,198,2,220,220,220,220,220,220,220,220,1976,15853,352,198,2,220,220,220,220,2845,25,198,2,220,220,220,220,220,220,220,220,3601,366,48267,1,198,198,2,220,220,220,220,1303,611,1312,1875,657,290,1312,4064,15458,62,7857,6624,657,25,198,2,220,220,220,220,1303,220,220,220,220,611,866,9888,25,198,2,220,220,220,220,1303,220,220,220,220,220,220,220,220,866,1416,3021,62,17566,796,4263,58,45299,45299,3712,17,11,3712,17,60,1343,4263,58,45299,45299,16,3712,17,11,3712,17,60,1343,4263,58,45299,45299,3712,17,11,16,3712,17,60,1343,4263,58,45299,45299,16,3712,17,11,16,3712,17,60,198,2,220,220,220,220,1303,220,220,220,220,220,220,220,220,866,1416,3021,62,17566,796,866,1416,3021,62,17566,1220,604,13,198,2,220,220,220,220,1303,220,220,220,220,220,220,220,220,7800,357,2902,1416,3021,62,17566,13,459,2981,10786,600,2624,33809,8,198,2,220,220,220,220,1303,220,220,220,220,2073,25,198,2,220,220,220,220,1303,220,220,220,220,220,220,220,220,7800,357,17566,35751,198,2,220,220,220,220,1303,2845,35528,355,409,25,198,2,220,220,220,220,1303,220,220,220,220,3601,409,198,2,220,220,220,220,1303,220,220,220,220,3601,366,43917,1366,662,14681,4054,329,3108,23884,1911,18982,7,6978,8,628,198,361,11593,3672,834,6624,705,834,12417,834,10354,198,220,220,220,4512,62,5235,796,3440,7,2414,8,198,220,220,220,256,15,796,640,13,2435,3419,198,220,220,220,329,1312,11,15458,287,27056,378,7,27432,62,5235,22784,923,28,16,2599,198,220,220,220,220,220,220,220,3601,45144,32239,83,90,92,1911,18982,7,2536,7,2435,13,2435,3419,532,256,15,828,15458,58,15,7131,15,11,15,11,15,11,15,12962,198,220,220,220,220,220,220,220,611,1312,6624,8576,25,198,220,220,220,220,220,220,220,220,220,220,220,2270,198,220,220,220,220,220,220,220,256,15,796,640,13,2435,3419,198],"string":"[\n 11748,\n 299,\n 32152,\n 355,\n 45941,\n 198,\n 11748,\n 629,\n 541,\n 88,\n 13,\n 44374,\n 198,\n 11748,\n 28686,\n 198,\n 11748,\n 640,\n 198,\n 2,\n 422,\n 350,\n 4146,\n 1330,\n 7412,\n 198,\n 198,\n 26947,\n 62,\n 34720,\n 796,\n 31051,\n 11195,\n 14,\n 32230,\n 14,\n 7278,\n 403,\n 14,\n 3077,\n 9649,\n 14,\n 6,\n 198,\n 13965,\n 62,\n 26947,\n 62,\n 34720,\n 796,\n 31051,\n 11195,\n 14,\n 32230,\n 14,\n 7278,\n 403,\n 14,\n 3077,\n 9649,\n 62,\n 12762,\n 14,\n 6,\n 198,\n 198,\n 2,\n 351,\n 1280,\n 7,\n 26947,\n 62,\n 34720,\n 10,\n 6,\n 16624,\n 13,\n 14116,\n 3256,\n 705,\n 81,\n 11537,\n 355,\n 277,\n 25,\n 198,\n 2,\n 220,\n 220,\n 220,\n 220,\n 3696,\n 796,\n 685,\n 75,\n 58,\n 21912,\n 16,\n 60,\n 329,\n 300,\n 287,\n 277,\n 60,\n 198,\n 2,\n 1303,\n 4263,\n 796,\n 45941,\n 13,\n 9107,\n 418,\n 19510,\n 43501,\n 62,\n 7857,\n 11,\n 513,\n 11,\n 17759,\n 11,\n 17759,\n 828,\n 288,\n 4906,\n 11639,\n 600,\n 2624,\n 11537,\n 198,\n 2,\n 4738,\n 62,\n 5219,\n 796,\n 45941,\n 13,\n 25120,\n 13,\n 29531,\n 9012,\n 7,\n 3682,\n 8,\n 198,\n 2,\n 4738,\n 62,\n 5219,\n 13,\n 1477,\n 18137,\n 7,\n 16624,\n 8,\n 198,\n 198,\n 2,\n 1976,\n 796,\n 1596,\n 27696,\n 3104,\n 198,\n 2,\n 329,\n 1312,\n 11,\n 3108,\n 287,\n 27056,\n 378,\n 7,\n 16624,\n 2599,\n 198,\n 2,\n 220,\n 220,\n 220,\n 220,\n 611,\n 1312,\n 1279,\n 1596,\n 1959,\n 4059,\n 25,\n 198,\n 2,\n 220,\n 220,\n 220,\n 220,\n 220,\n 220,\n 220,\n 220,\n 2555,\n 198,\n 2,\n 220,\n 220,\n 220,\n 220,\n 1949,\n 25,\n 198,\n 2,\n 220,\n 220,\n 220,\n 220,\n 220,\n 220,\n 220,\n 220,\n 2939,\n 796,\n 629,\n 541,\n 88,\n 13,\n 44374,\n 13,\n 320,\n 961,\n 7,\n 198,\n 2,\n 220,\n 220,\n 220,\n 220,\n 220,\n 220,\n 220,\n 220,\n 220,\n 220,\n 220,\n 220,\n 28686,\n 13,\n 6978,\n 13,\n 27237,\n 6978,\n 7,\n 418,\n 13,\n 6978,\n 13,\n 22179,\n 7,\n 26947,\n 62,\n 34720,\n 11,\n 3108,\n 4008,\n 198,\n 2,\n 220,\n 220,\n 220,\n 220,\n 220,\n 220,\n 220,\n 220,\n 1267,\n 198,\n 198,\n 2,\n 220,\n 220,\n 220,\n 220,\n 220,\n 220,\n 220,\n 220,\n 1303,\n 1949,\n 25,\n 220,\n 220,\n 220,\n 220,\n 220,\n 220,\n 220,\n 220,\n 220,\n 220,\n 220,\n 220,\n 220,\n 220,\n 220,\n 220,\n 198,\n 2,\n 220,\n 220,\n 220,\n 220,\n 220,\n 220,\n 220,\n 220,\n 1303,\n 2939,\n 796,\n 2939,\n 13,\n 7645,\n 3455,\n 7,\n 17,\n 11,\n 15,\n 11,\n 16,\n 8,\n 198,\n 2,\n 220,\n 220,\n 220,\n 220,\n 220,\n 220,\n 220,\n 220,\n 11677,\n 62,\n 88,\n 796,\n 357,\n 9060,\n 13,\n 43358,\n 58,\n 15,\n 45297,\n 11645,\n 20679,\n 17,\n 198,\n 2,\n 220,\n 220,\n 220,\n 220,\n 220,\n 220,\n 220,\n 220,\n 11677,\n 62,\n 87,\n 796,\n 357,\n 9060,\n 13,\n 43358,\n 58,\n 16,\n 45297,\n 11645,\n 20679,\n 17,\n 198,\n 2,\n 220,\n 220,\n 220,\n 220,\n 220,\n 220,\n 220,\n 220,\n 2939,\n 796,\n 2939,\n 58,\n 28968,\n 62,\n 88,\n 25,\n 28968,\n 62,\n 88,\n 10,\n 11645,\n 11,\n 11677,\n 62,\n 87,\n 25,\n 28968,\n 62,\n 87,\n 10,\n 11645,\n 60,\n 198,\n 2,\n 220,\n 220,\n 220,\n 220,\n 220,\n 220,\n 220,\n 220,\n 2939,\n 796,\n 2939,\n 58,\n 3712,\n 17,\n 11,\n 3712,\n 17,\n 48688,\n 9060,\n 58,\n 16,\n 3712,\n 17,\n 11,\n 3712,\n 17,\n 48688,\n 9060,\n 58,\n 3712,\n 17,\n 11,\n 16,\n 3712,\n 17,\n 48688,\n 9060,\n 58,\n 16,\n 3712,\n 17,\n 11,\n 16,\n 3712,\n 17,\n 60,\n 198,\n 2,\n 220,\n 220,\n 220,\n 220,\n 220,\n 220,\n 220,\n 220,\n 2939,\n 796,\n 2939,\n 1220,\n 604,\n 198,\n 2,\n 220,\n 220,\n 220,\n 220,\n 220,\n 220,\n 220,\n 220,\n 1303,\n 2939,\n 796,\n 2939,\n 13,\n 459,\n 2981,\n 10786,\n 600,\n 2624,\n 11537,\n 198,\n 2,\n 220,\n 220,\n 220,\n 220,\n 220,\n 220,\n 220,\n 220,\n 1303,\n 545,\n 796,\n 7412,\n 13,\n 6738,\n 18747,\n 7,\n 9060,\n 8,\n 198,\n 2,\n 220,\n 220,\n 220,\n 220,\n 220,\n 220,\n 220,\n 220,\n 1303,\n 279,\n 796,\n 28686,\n 13,\n 6978,\n 13,\n 27237,\n 6978,\n 7,\n 418,\n 13,\n 6978,\n 13,\n 22179,\n 7,\n 13965,\n 62,\n 26947,\n 62,\n 34720,\n 11,\n 3108,\n 4008,\n 198,\n 2,\n 220,\n 220,\n 220,\n 220,\n 220,\n 220,\n 220,\n 220,\n 1303,\n 1949,\n 25,\n 198,\n 2,\n 220,\n 220,\n 220,\n 220,\n 220,\n 220,\n 220,\n 220,\n 1303,\n 220,\n 220,\n 220,\n 220,\n 28686,\n 13,\n 76,\n 4335,\n 17062,\n 7,\n 418,\n 13,\n 6978,\n 13,\n 15908,\n 3672,\n 7,\n 79,\n 4008,\n 198,\n 2,\n 220,\n 220,\n 220,\n 220,\n 220,\n 220,\n 220,\n 220,\n 1303,\n 2845,\n 25,\n 198,\n 2,\n 220,\n 220,\n 220,\n 220,\n 220,\n 220,\n 220,\n 220,\n 1303,\n 220,\n 220,\n 220,\n 220,\n 1208,\n 198,\n 2,\n 220,\n 220,\n 220,\n 220,\n 220,\n 220,\n 220,\n 220,\n 629,\n 541,\n 88,\n 13,\n 44374,\n 13,\n 12078,\n 1015,\n 7,\n 13965,\n 62,\n 26947,\n 62,\n 34720,\n 10,\n 6,\n 90,\n 27422,\n 9479,\n 4458,\n 18982,\n 7,\n 89,\n 828,\n 2939,\n 8,\n 198,\n 2,\n 220,\n 220,\n 220,\n 220,\n 220,\n 220,\n 220,\n 220,\n 1303,\n 545,\n 13,\n 21928,\n 7,\n 79,\n 58,\n 21912,\n 19,\n 48688,\n 6,\n 9479,\n 11537,\n 198,\n 2,\n 220,\n 220,\n 220,\n 220,\n 220,\n 220,\n 220,\n 220,\n 611,\n 1976,\n 4064,\n 1802,\n 6624,\n 657,\n 25,\n 198,\n 2,\n 220,\n 220,\n 220,\n 220,\n 220,\n 220,\n 220,\n 220,\n 220,\n 220,\n 220,\n 220,\n 3601,\n 1976,\n 198,\n 2,\n 220,\n 220,\n 220,\n 220,\n 220,\n 220,\n 220,\n 220,\n 1976,\n 15853,\n 352,\n 198,\n 2,\n 220,\n 220,\n 220,\n 220,\n 2845,\n 25,\n 198,\n 2,\n 220,\n 220,\n 220,\n 220,\n 220,\n 220,\n 220,\n 220,\n 3601,\n 366,\n 48267,\n 1,\n 198,\n 198,\n 2,\n 220,\n 220,\n 220,\n 220,\n 1303,\n 611,\n 1312,\n 1875,\n 657,\n 290,\n 1312,\n 4064,\n 15458,\n 62,\n 7857,\n 6624,\n 657,\n 25,\n 198,\n 2,\n 220,\n 220,\n 220,\n 220,\n 1303,\n 220,\n 220,\n 220,\n 220,\n 611,\n 866,\n 9888,\n 25,\n 198,\n 2,\n 220,\n 220,\n 220,\n 220,\n 1303,\n 220,\n 220,\n 220,\n 220,\n 220,\n 220,\n 220,\n 220,\n 866,\n 1416,\n 3021,\n 62,\n 17566,\n 796,\n 4263,\n 58,\n 45299,\n 45299,\n 3712,\n 17,\n 11,\n 3712,\n 17,\n 60,\n 1343,\n 4263,\n 58,\n 45299,\n 45299,\n 16,\n 3712,\n 17,\n 11,\n 3712,\n 17,\n 60,\n 1343,\n 4263,\n 58,\n 45299,\n 45299,\n 3712,\n 17,\n 11,\n 16,\n 3712,\n 17,\n 60,\n 1343,\n 4263,\n 58,\n 45299,\n 45299,\n 16,\n 3712,\n 17,\n 11,\n 16,\n 3712,\n 17,\n 60,\n 198,\n 2,\n 220,\n 220,\n 220,\n 220,\n 1303,\n 220,\n 220,\n 220,\n 220,\n 220,\n 220,\n 220,\n 220,\n 866,\n 1416,\n 3021,\n 62,\n 17566,\n 796,\n 866,\n 1416,\n 3021,\n 62,\n 17566,\n 1220,\n 604,\n 13,\n 198,\n 2,\n 220,\n 220,\n 220,\n 220,\n 1303,\n 220,\n 220,\n 220,\n 220,\n 220,\n 220,\n 220,\n 220,\n 7800,\n 357,\n 2902,\n 1416,\n 3021,\n 62,\n 17566,\n 13,\n 459,\n 2981,\n 10786,\n 600,\n 2624,\n 33809,\n 8,\n 198,\n 2,\n 220,\n 220,\n 220,\n 220,\n 1303,\n 220,\n 220,\n 220,\n 220,\n 2073,\n 25,\n 198,\n 2,\n 220,\n 220,\n 220,\n 220,\n 1303,\n 220,\n 220,\n 220,\n 220,\n 220,\n 220,\n 220,\n 220,\n 7800,\n 357,\n 17566,\n 35751,\n 198,\n 2,\n 220,\n 220,\n 220,\n 220,\n 1303,\n 2845,\n 35528,\n 355,\n 409,\n 25,\n 198,\n 2,\n 220,\n 220,\n 220,\n 220,\n 1303,\n 220,\n 220,\n 220,\n 220,\n 3601,\n 409,\n 198,\n 2,\n 220,\n 220,\n 220,\n 220,\n 1303,\n 220,\n 220,\n 220,\n 220,\n 3601,\n 366,\n 43917,\n 1366,\n 662,\n 14681,\n 4054,\n 329,\n 3108,\n 23884,\n 1911,\n 18982,\n 7,\n 6978,\n 8,\n 628,\n 198,\n 361,\n 11593,\n 3672,\n 834,\n 6624,\n 705,\n 834,\n 12417,\n 834,\n 10354,\n 198,\n 220,\n 220,\n 220,\n 4512,\n 62,\n 5235,\n 796,\n 3440,\n 7,\n 2414,\n 8,\n 198,\n 220,\n 220,\n 220,\n 256,\n 15,\n 796,\n 640,\n 13,\n 2435,\n 3419,\n 198,\n 220,\n 220,\n 220,\n 329,\n 1312,\n 11,\n 15458,\n 287,\n 27056,\n 378,\n 7,\n 27432,\n 62,\n 5235,\n 22784,\n 923,\n 28,\n 16,\n 2599,\n 198,\n 220,\n 220,\n 220,\n 220,\n 220,\n 220,\n 220,\n 3601,\n 45144,\n 32239,\n 83,\n 90,\n 92,\n 1911,\n 18982,\n 7,\n 2536,\n 7,\n 2435,\n 13,\n 2435,\n 3419,\n 532,\n 256,\n 15,\n 828,\n 15458,\n 58,\n 15,\n 7131,\n 15,\n 11,\n 15,\n 11,\n 15,\n 11,\n 15,\n 12962,\n 198,\n 220,\n 220,\n 220,\n 220,\n 220,\n 220,\n 220,\n 611,\n 1312,\n 6624,\n 8576,\n 25,\n 198,\n 220,\n 220,\n 220,\n 220,\n 220,\n 220,\n 220,\n 220,\n 220,\n 220,\n 220,\n 2270,\n 198,\n 220,\n 220,\n 220,\n 220,\n 220,\n 220,\n 220,\n 256,\n 15,\n 796,\n 640,\n 13,\n 2435,\n 3419,\n 198\n]"},"ratio_char_token":{"kind":"number","value":1.9193262411347518,"string":"1.919326"},"token_count":{"kind":"number","value":1128,"string":"1,128"}}},{"rowIdx":1242,"cells":{"content":{"kind":"string","value":"from django.db.utils import IntegrityError\nfrom django.db.models import Q\nfrom rest_framework import serializers\nfrom core.models import FavoriteThing\nfrom core.models import Category\nfrom .helper import reorder_rankings, reorder_rankings_subtract\n\n"},"input_ids":{"kind":"list like","value":[6738,42625,14208,13,9945,13,26791,1330,39348,12331,198,6738,42625,14208,13,9945,13,27530,1330,1195,198,6738,1334,62,30604,1330,11389,11341,198,6738,4755,13,27530,1330,33992,51,722,198,6738,4755,13,27530,1330,21743,198,6738,764,2978,525,1330,302,2875,62,43027,654,11,302,2875,62,43027,654,62,7266,83,974,628],"string":"[\n 6738,\n 42625,\n 14208,\n 13,\n 9945,\n 13,\n 26791,\n 1330,\n 39348,\n 12331,\n 198,\n 6738,\n 42625,\n 14208,\n 13,\n 9945,\n 13,\n 27530,\n 1330,\n 1195,\n 198,\n 6738,\n 1334,\n 62,\n 30604,\n 1330,\n 11389,\n 11341,\n 198,\n 6738,\n 4755,\n 13,\n 27530,\n 1330,\n 33992,\n 51,\n 722,\n 198,\n 6738,\n 4755,\n 13,\n 27530,\n 1330,\n 21743,\n 198,\n 6738,\n 764,\n 2978,\n 525,\n 1330,\n 302,\n 2875,\n 62,\n 43027,\n 654,\n 11,\n 302,\n 2875,\n 62,\n 43027,\n 654,\n 62,\n 7266,\n 83,\n 974,\n 628\n]"},"ratio_char_token":{"kind":"number","value":3.772727272727273,"string":"3.772727"},"token_count":{"kind":"number","value":66,"string":"66"}}},{"rowIdx":1243,"cells":{"content":{"kind":"string","value":"# Tests for the Genomics Data Quality Pipeline\nimport mock, datetime, pytz\n\nfrom rdr_service import clock\nfrom rdr_service.api_util import open_cloud_file\nfrom rdr_service.genomic_enums import GenomicJob, GenomicSubProcessStatus, GenomicSubProcessResult, \\\n GenomicManifestTypes, GenomicIncidentCode\nfrom tests.helpers.unittest_base import BaseTestCase\nfrom rdr_service.genomic.genomic_job_controller import DataQualityJobController\nfrom rdr_service.genomic.genomic_data_quality_components import ReportingComponent\n\n\n\n"},"input_ids":{"kind":"list like","value":[2,30307,329,262,5215,31994,6060,14156,37709,198,11748,15290,11,4818,8079,11,12972,22877,198,198,6738,374,7109,62,15271,1330,8801,198,6738,374,7109,62,15271,13,15042,62,22602,1330,1280,62,17721,62,7753,198,6738,374,7109,62,15271,13,5235,10179,62,268,5700,1330,5215,10179,33308,11,5215,10179,7004,18709,19580,11,5215,10179,7004,18709,23004,11,3467,198,220,220,220,5215,10179,5124,8409,31431,11,5215,10179,25517,738,10669,198,6738,5254,13,16794,364,13,403,715,395,62,8692,1330,7308,14402,20448,198,6738,374,7109,62,15271,13,5235,10179,13,5235,10179,62,21858,62,36500,1330,6060,35013,33308,22130,198,6738,374,7109,62,15271,13,5235,10179,13,5235,10179,62,7890,62,13237,62,5589,3906,1330,29595,21950,628,628],"string":"[\n 2,\n 30307,\n 329,\n 262,\n 5215,\n 31994,\n 6060,\n 14156,\n 37709,\n 198,\n 11748,\n 15290,\n 11,\n 4818,\n 8079,\n 11,\n 12972,\n 22877,\n 198,\n 198,\n 6738,\n 374,\n 7109,\n 62,\n 15271,\n 1330,\n 8801,\n 198,\n 6738,\n 374,\n 7109,\n 62,\n 15271,\n 13,\n 15042,\n 62,\n 22602,\n 1330,\n 1280,\n 62,\n 17721,\n 62,\n 7753,\n 198,\n 6738,\n 374,\n 7109,\n 62,\n 15271,\n 13,\n 5235,\n 10179,\n 62,\n 268,\n 5700,\n 1330,\n 5215,\n 10179,\n 33308,\n 11,\n 5215,\n 10179,\n 7004,\n 18709,\n 19580,\n 11,\n 5215,\n 10179,\n 7004,\n 18709,\n 23004,\n 11,\n 3467,\n 198,\n 220,\n 220,\n 220,\n 5215,\n 10179,\n 5124,\n 8409,\n 31431,\n 11,\n 5215,\n 10179,\n 25517,\n 738,\n 10669,\n 198,\n 6738,\n 5254,\n 13,\n 16794,\n 364,\n 13,\n 403,\n 715,\n 395,\n 62,\n 8692,\n 1330,\n 7308,\n 14402,\n 20448,\n 198,\n 6738,\n 374,\n 7109,\n 62,\n 15271,\n 13,\n 5235,\n 10179,\n 13,\n 5235,\n 10179,\n 62,\n 21858,\n 62,\n 36500,\n 1330,\n 6060,\n 35013,\n 33308,\n 22130,\n 198,\n 6738,\n 374,\n 7109,\n 62,\n 15271,\n 13,\n 5235,\n 10179,\n 13,\n 5235,\n 10179,\n 62,\n 7890,\n 62,\n 13237,\n 62,\n 5589,\n 3906,\n 1330,\n 29595,\n 21950,\n 628,\n 628\n]"},"ratio_char_token":{"kind":"number","value":3.5033557046979866,"string":"3.503356"},"token_count":{"kind":"number","value":149,"string":"149"}}},{"rowIdx":1244,"cells":{"content":{"kind":"string","value":"# Time limit exceeded\n\nwhile True:\n\ttry:\n\t\tA = input()\n\t\tB = input()\n\n\t\tlA = len(A)\n\t\tlB = len(B)\n\n\t\tbiggest = \"\"\n\t\tshortest = \"\"\n\t\tlshortest = 0\n\t\tif max(lA, lB) == lA:\n\t\t\tbiggest, shortest = A, B\n\t\t\tlbiggest = lA\n\t\t\tlshortest = lB\n\t\telse:\n\t\t\tbiggest, shortest = B, A\n\t\t\tlbiggest = lB\n\t\t\tlshortest = lA\n\n\n\t\tbSub = 0\n\t\tcurrentSub = 0\n\t\tfor k in range(lshortest):\n\t\t\tfor w in range(lbiggest):\n\t\t\t\tif shortest[k] == biggest[w]:\n\t\t\t\t\tcurrentSub = 1\n\n\t\t\t\t\tq = w+1\n\n\t\t\t\t\tfor p in range(k+1,lshortest):\n\t\t\t\t\t\tif q >= lbiggest:\n\t\t\t\t\t\t\tbreak\n\t\t\t\t\t\tif shortest[p] == biggest[q]:\n\t\t\t\t\t\t\tcurrentSub += 1\n\t\t\t\t\t\t\tq += 1\n\t\t\t\t\t\telse:\n\t\t\t\t\t\t\tbreak\n\n\t\t\t\tif currentSub >= bSub:\n\t\t\t\t\tbSub = currentSub\n\n\t\tprint(bSub)\n\t\n\texcept:\n\t\tbreak"},"input_ids":{"kind":"list like","value":[2,3862,4179,20672,198,198,4514,6407,25,198,197,28311,25,198,197,197,32,796,5128,3419,198,197,197,33,796,5128,3419,628,197,197,75,32,796,18896,7,32,8,198,197,197,75,33,796,18896,7,33,8,628,197,197,14261,3495,796,13538,198,197,197,19509,395,796,13538,198,197,197,75,19509,395,796,657,198,197,197,361,3509,7,75,32,11,300,33,8,6624,300,32,25,198,197,197,197,14261,3495,11,35581,796,317,11,347,198,197,197,197,75,14261,3495,796,300,32,198,197,197,197,75,19509,395,796,300,33,198,197,197,17772,25,198,197,197,197,14261,3495,11,35581,796,347,11,317,198,197,197,197,75,14261,3495,796,300,33,198,197,197,197,75,19509,395,796,300,32,628,198,197,197,65,7004,796,657,198,197,197,14421,7004,796,657,198,197,197,1640,479,287,2837,7,75,19509,395,2599,198,197,197,197,1640,266,287,2837,7,75,14261,3495,2599,198,197,197,197,197,361,35581,58,74,60,6624,4094,58,86,5974,198,197,197,197,197,197,14421,7004,796,352,628,197,197,197,197,197,80,796,266,10,16,628,197,197,197,197,197,1640,279,287,2837,7,74,10,16,11,75,19509,395,2599,198,197,197,197,197,197,197,361,10662,18189,300,14261,3495,25,198,197,197,197,197,197,197,197,9032,198,197,197,197,197,197,197,361,35581,58,79,60,6624,4094,58,80,5974,198,197,197,197,197,197,197,197,14421,7004,15853,352,198,197,197,197,197,197,197,197,80,15853,352,198,197,197,197,197,197,197,17772,25,198,197,197,197,197,197,197,197,9032,628,197,197,197,197,361,1459,7004,18189,275,7004,25,198,197,197,197,197,197,65,7004,796,1459,7004,628,197,197,4798,7,65,7004,8,198,197,198,197,16341,25,198,197,197,9032],"string":"[\n 2,\n 3862,\n 4179,\n 20672,\n 198,\n 198,\n 4514,\n 6407,\n 25,\n 198,\n 197,\n 28311,\n 25,\n 198,\n 197,\n 197,\n 32,\n 796,\n 5128,\n 3419,\n 198,\n 197,\n 197,\n 33,\n 796,\n 5128,\n 3419,\n 628,\n 197,\n 197,\n 75,\n 32,\n 796,\n 18896,\n 7,\n 32,\n 8,\n 198,\n 197,\n 197,\n 75,\n 33,\n 796,\n 18896,\n 7,\n 33,\n 8,\n 628,\n 197,\n 197,\n 14261,\n 3495,\n 796,\n 13538,\n 198,\n 197,\n 197,\n 19509,\n 395,\n 796,\n 13538,\n 198,\n 197,\n 197,\n 75,\n 19509,\n 395,\n 796,\n 657,\n 198,\n 197,\n 197,\n 361,\n 3509,\n 7,\n 75,\n 32,\n 11,\n 300,\n 33,\n 8,\n 6624,\n 300,\n 32,\n 25,\n 198,\n 197,\n 197,\n 197,\n 14261,\n 3495,\n 11,\n 35581,\n 796,\n 317,\n 11,\n 347,\n 198,\n 197,\n 197,\n 197,\n 75,\n 14261,\n 3495,\n 796,\n 300,\n 32,\n 198,\n 197,\n 197,\n 197,\n 75,\n 19509,\n 395,\n 796,\n 300,\n 33,\n 198,\n 197,\n 197,\n 17772,\n 25,\n 198,\n 197,\n 197,\n 197,\n 14261,\n 3495,\n 11,\n 35581,\n 796,\n 347,\n 11,\n 317,\n 198,\n 197,\n 197,\n 197,\n 75,\n 14261,\n 3495,\n 796,\n 300,\n 33,\n 198,\n 197,\n 197,\n 197,\n 75,\n 19509,\n 395,\n 796,\n 300,\n 32,\n 628,\n 198,\n 197,\n 197,\n 65,\n 7004,\n 796,\n 657,\n 198,\n 197,\n 197,\n 14421,\n 7004,\n 796,\n 657,\n 198,\n 197,\n 197,\n 1640,\n 479,\n 287,\n 2837,\n 7,\n 75,\n 19509,\n 395,\n 2599,\n 198,\n 197,\n 197,\n 197,\n 1640,\n 266,\n 287,\n 2837,\n 7,\n 75,\n 14261,\n 3495,\n 2599,\n 198,\n 197,\n 197,\n 197,\n 197,\n 361,\n 35581,\n 58,\n 74,\n 60,\n 6624,\n 4094,\n 58,\n 86,\n 5974,\n 198,\n 197,\n 197,\n 197,\n 197,\n 197,\n 14421,\n 7004,\n 796,\n 352,\n 628,\n 197,\n 197,\n 197,\n 197,\n 197,\n 80,\n 796,\n 266,\n 10,\n 16,\n 628,\n 197,\n 197,\n 197,\n 197,\n 197,\n 1640,\n 279,\n 287,\n 2837,\n 7,\n 74,\n 10,\n 16,\n 11,\n 75,\n 19509,\n 395,\n 2599,\n 198,\n 197,\n 197,\n 197,\n 197,\n 197,\n 197,\n 361,\n 10662,\n 18189,\n 300,\n 14261,\n 3495,\n 25,\n 198,\n 197,\n 197,\n 197,\n 197,\n 197,\n 197,\n 197,\n 9032,\n 198,\n 197,\n 197,\n 197,\n 197,\n 197,\n 197,\n 361,\n 35581,\n 58,\n 79,\n 60,\n 6624,\n 4094,\n 58,\n 80,\n 5974,\n 198,\n 197,\n 197,\n 197,\n 197,\n 197,\n 197,\n 197,\n 14421,\n 7004,\n 15853,\n 352,\n 198,\n 197,\n 197,\n 197,\n 197,\n 197,\n 197,\n 197,\n 80,\n 15853,\n 352,\n 198,\n 197,\n 197,\n 197,\n 197,\n 197,\n 197,\n 17772,\n 25,\n 198,\n 197,\n 197,\n 197,\n 197,\n 197,\n 197,\n 197,\n 9032,\n 628,\n 197,\n 197,\n 197,\n 197,\n 361,\n 1459,\n 7004,\n 18189,\n 275,\n 7004,\n 25,\n 198,\n 197,\n 197,\n 197,\n 197,\n 197,\n 65,\n 7004,\n 796,\n 1459,\n 7004,\n 628,\n 197,\n 197,\n 4798,\n 7,\n 65,\n 7004,\n 8,\n 198,\n 197,\n 198,\n 197,\n 16341,\n 25,\n 198,\n 197,\n 197,\n 9032\n]"},"ratio_char_token":{"kind":"number","value":1.9299191374663074,"string":"1.929919"},"token_count":{"kind":"number","value":371,"string":"371"}}},{"rowIdx":1245,"cells":{"content":{"kind":"string","value":"import os, urllib, requests, json\npriority = 1\n"},"input_ids":{"kind":"list like","value":[11748,28686,11,2956,297,571,11,7007,11,33918,198,49336,796,352,198],"string":"[\n 11748,\n 28686,\n 11,\n 2956,\n 297,\n 571,\n 11,\n 7007,\n 11,\n 33918,\n 198,\n 49336,\n 796,\n 352,\n 198\n]"},"ratio_char_token":{"kind":"number","value":3.1333333333333333,"string":"3.133333"},"token_count":{"kind":"number","value":15,"string":"15"}}},{"rowIdx":1246,"cells":{"content":{"kind":"string","value":"\nlist1 = [1, 4, 8, 2, 9]\n\nprint len(list1)\nprint max(list1), min(list1)\nprint list1[-2]\nprint list1[-5:3]\nprint list1[-3:]\n\n"},"input_ids":{"kind":"list like","value":[198,4868,16,796,685,16,11,604,11,807,11,362,11,860,60,198,198,4798,18896,7,4868,16,8,198,4798,3509,7,4868,16,828,949,7,4868,16,8,198,4798,1351,16,58,12,17,60,198,4798,1351,16,58,12,20,25,18,60,198,4798,1351,16,58,12,18,47715,628],"string":"[\n 198,\n 4868,\n 16,\n 796,\n 685,\n 16,\n 11,\n 604,\n 11,\n 807,\n 11,\n 362,\n 11,\n 860,\n 60,\n 198,\n 198,\n 4798,\n 18896,\n 7,\n 4868,\n 16,\n 8,\n 198,\n 4798,\n 3509,\n 7,\n 4868,\n 16,\n 828,\n 949,\n 7,\n 4868,\n 16,\n 8,\n 198,\n 4798,\n 1351,\n 16,\n 58,\n 12,\n 17,\n 60,\n 198,\n 4798,\n 1351,\n 16,\n 58,\n 12,\n 20,\n 25,\n 18,\n 60,\n 198,\n 4798,\n 1351,\n 16,\n 58,\n 12,\n 18,\n 47715,\n 628\n]"},"ratio_char_token":{"kind":"number","value":2,"string":"2"},"token_count":{"kind":"number","value":62,"string":"62"}}},{"rowIdx":1247,"cells":{"content":{"kind":"string","value":"from matplotlib import pyplot as plt\nfrom script import sales_times1\nfrom script import sales_times2\n# normed=True This command divides the height of each column by\n# a constant such that the total shaded area of the histogram sums\n# to 1 \nplt.hist(sales_times1, bins=20, alpha=0.4, normed=True)\nplt.hist(sales_times2, bins=20, alpha=0.4, normed=True)\n\nplt.show()\n#%%\nfrom matplotlib import pyplot as plt\n\nexam_scores1 = [62.58, 67.63, 81.37, 52.53, 62.98, 72.15, 59.05, 73.85, 97.24, 76.81, 89.34, 74.44, 68.52, 85.13, 90.75, 70.29, 75.62, 85.38, 77.82, 98.31, 79.08, 61.72, 71.33, 80.77, 80.31, 78.16, 61.15, 64.99, 72.67, 78.94]\nexam_scores2 = [72.38, 71.28, 79.24, 83.86, 84.42, 79.38, 75.51, 76.63, 81.48,78.81,79.23,74.38,79.27,81.07,75.42,90.35,82.93,86.74,81.33,95.1,86.57,83.66,85.58,81.87,92.14,72.15,91.64,74.21,89.04,76.54,81.9,96.5,80.05,74.77,72.26,73.23,92.6,66.22,70.09,77.2]\n\n# Make your plot here\nplt.figure(figsize=(10,8))\nplt.hist(exam_scores1,bins=12,normed=True,\n histtype='step',linewidth=2)\nplt.hist(exam_scores2,bins=12,normed=True,\n histtype='step',linewidth=2)\nlegends=[\"1st Yr Teaching\",\"2nd Yr Teaching\"]\nplt.legend(legends)\nplt.title(\"Final Exam Score Distribution\")\nplt.xlabel(\"Percentage\")\nplt.ylabel(\"Frequency\")\n\nplt.savefig(\"my_histogram.png\")\n#%%\nimport numpy as np\nimport pandas as pd\n\n# Import matplotlib pyplot\nfrom matplotlib import pyplot as plt\n\n# Read in transactions data\ngreatest_books = pd.read_csv(\"top-hundred-books.csv\")\n\n# Save transaction times to a separate numpy array\nauthor_ages = greatest_books['Ages']\n\n# Use numpy to calculate the average age of the top 100 authors\naverage_age = np.average(author_ages)\n\nprint(\"The average age of the 100 greatest authors, according to Le Monde is: \" + str(average_age))\n\n# Plot the figure\nplt.hist(author_ages, range=(10, 80), bins=14, edgecolor='black')\nplt.title(\"Age of Top 100 Novel Authors at Publication\")\nplt.xlabel(\"Publication Age\")\nplt.ylabel(\"Count\")\nplt.axvline(average_age, color='r', linestyle='solid', linewidth=2, label=\"Mean\")\nplt.legend()\n\nplt.show()\n"},"input_ids":{"kind":"list like","value":[6738,2603,29487,8019,1330,12972,29487,355,458,83,198,6738,4226,1330,4200,62,22355,16,198,6738,4226,1330,4200,62,22355,17,198,2,2593,276,28,17821,770,3141,36319,262,6001,286,1123,5721,416,198,2,257,6937,884,326,262,2472,427,5286,1989,286,262,1554,21857,21784,198,2,284,352,220,198,489,83,13,10034,7,82,2040,62,22355,16,11,41701,28,1238,11,17130,28,15,13,19,11,2593,276,28,17821,8,198,489,83,13,10034,7,82,2040,62,22355,17,11,41701,28,1238,11,17130,28,15,13,19,11,2593,276,28,17821,8,198,198,489,83,13,12860,3419,198,2,16626,198,6738,2603,29487,8019,1330,12972,29487,355,458,83,198,198,1069,321,62,1416,2850,16,796,685,5237,13,3365,11,8275,13,5066,11,9773,13,2718,11,6740,13,4310,11,8190,13,4089,11,7724,13,1314,11,7863,13,2713,11,8854,13,5332,11,10111,13,1731,11,8684,13,6659,11,9919,13,2682,11,8915,13,2598,11,8257,13,4309,11,7600,13,1485,11,4101,13,2425,11,4317,13,1959,11,5441,13,5237,11,7600,13,2548,11,8541,13,6469,11,9661,13,3132,11,9225,13,2919,11,8454,13,4761,11,9166,13,2091,11,4019,13,3324,11,4019,13,3132,11,8699,13,1433,11,8454,13,1314,11,5598,13,2079,11,7724,13,3134,11,8699,13,5824,60,198,1069,321,62,1416,2850,17,796,685,4761,13,2548,11,9166,13,2078,11,9225,13,1731,11,9698,13,4521,11,9508,13,3682,11,9225,13,2548,11,5441,13,4349,11,8684,13,5066,11,9773,13,2780,11,3695,13,6659,11,3720,13,1954,11,4524,13,2548,11,3720,13,1983,11,6659,13,2998,11,2425,13,3682,11,3829,13,2327,11,6469,13,6052,11,4521,13,4524,11,6659,13,2091,11,3865,13,16,11,4521,13,3553,11,5999,13,2791,11,5332,13,3365,11,6659,13,5774,11,5892,13,1415,11,4761,13,1314,11,6420,13,2414,11,4524,13,2481,11,4531,13,3023,11,4304,13,4051,11,6659,13,24,11,4846,13,20,11,1795,13,2713,11,4524,13,3324,11,4761,13,2075,11,4790,13,1954,11,5892,13,21,11,2791,13,1828,11,2154,13,2931,11,3324,13,17,60,198,198,2,6889,534,7110,994,198,489,83,13,26875,7,5647,7857,16193,940,11,23,4008,198,489,83,13,10034,7,1069,321,62,1416,2850,16,11,65,1040,28,1065,11,27237,276,28,17821,11,198,220,220,220,220,220,220,220,220,1554,4906,11639,9662,3256,2815,413,5649,28,17,8,198,489,83,13,10034,7,1069,321,62,1416,2850,17,11,65,1040,28,1065,11,27237,276,28,17821,11,198,220,220,220,220,220,220,220,220,1554,4906,11639,9662,3256,2815,413,5649,28,17,8,198,1455,2412,28,14692,16,301,575,81,38094,2430,17,358,575,81,38094,8973,198,489,83,13,1455,437,7,1455,2412,8,198,489,83,13,7839,7203,19006,35909,15178,27484,4943,198,489,83,13,87,18242,7203,31905,496,4943,198,489,83,13,2645,9608,7203,37,28707,4943,198,198,489,83,13,21928,5647,7203,1820,62,10034,21857,13,11134,4943,198,2,16626,198,11748,299,32152,355,45941,198,11748,19798,292,355,279,67,198,198,2,17267,2603,29487,8019,12972,29487,198,6738,2603,29487,8019,1330,12972,29487,355,458,83,198,198,2,4149,287,8945,1366,198,18223,395,62,12106,796,279,67,13,961,62,40664,7203,4852,12,71,3229,12,12106,13,40664,4943,198,198,2,12793,8611,1661,284,257,4553,299,32152,7177,198,9800,62,1095,796,6000,62,12106,17816,32,3212,20520,198,198,2,5765,299,32152,284,15284,262,2811,2479,286,262,1353,1802,7035,198,23913,62,496,796,45941,13,23913,7,9800,62,1095,8,198,198,4798,7203,464,2811,2479,286,262,1802,6000,7035,11,1864,284,1004,337,14378,318,25,366,1343,965,7,23913,62,496,4008,198,198,2,28114,262,3785,198,489,83,13,10034,7,9800,62,1095,11,2837,16193,940,11,4019,828,41701,28,1415,11,220,5743,8043,11639,13424,11537,198,489,83,13,7839,7203,23396,286,5849,1802,24467,46665,379,45065,4943,198,489,83,13,87,18242,7203,15202,341,7129,4943,198,489,83,13,2645,9608,7203,12332,4943,198,489,83,13,897,85,1370,7,23913,62,496,11,3124,11639,81,3256,9493,10992,11639,39390,3256,9493,413,5649,28,17,11,6167,2625,5308,272,4943,198,489,83,13,1455,437,3419,198,198,489,83,13,12860,3419,198],"string":"[\n 6738,\n 2603,\n 29487,\n 8019,\n 1330,\n 12972,\n 29487,\n 355,\n 458,\n 83,\n 198,\n 6738,\n 4226,\n 1330,\n 4200,\n 62,\n 22355,\n 16,\n 198,\n 6738,\n 4226,\n 1330,\n 4200,\n 62,\n 22355,\n 17,\n 198,\n 2,\n 2593,\n 276,\n 28,\n 17821,\n 770,\n 3141,\n 36319,\n 262,\n 6001,\n 286,\n 1123,\n 5721,\n 416,\n 198,\n 2,\n 257,\n 6937,\n 884,\n 326,\n 262,\n 2472,\n 427,\n 5286,\n 1989,\n 286,\n 262,\n 1554,\n 21857,\n 21784,\n 198,\n 2,\n 284,\n 352,\n 220,\n 198,\n 489,\n 83,\n 13,\n 10034,\n 7,\n 82,\n 2040,\n 62,\n 22355,\n 16,\n 11,\n 41701,\n 28,\n 1238,\n 11,\n 17130,\n 28,\n 15,\n 13,\n 19,\n 11,\n 2593,\n 276,\n 28,\n 17821,\n 8,\n 198,\n 489,\n 83,\n 13,\n 10034,\n 7,\n 82,\n 2040,\n 62,\n 22355,\n 17,\n 11,\n 41701,\n 28,\n 1238,\n 11,\n 17130,\n 28,\n 15,\n 13,\n 19,\n 11,\n 2593,\n 276,\n 28,\n 17821,\n 8,\n 198,\n 198,\n 489,\n 83,\n 13,\n 12860,\n 3419,\n 198,\n 2,\n 16626,\n 198,\n 6738,\n 2603,\n 29487,\n 8019,\n 1330,\n 12972,\n 29487,\n 355,\n 458,\n 83,\n 198,\n 198,\n 1069,\n 321,\n 62,\n 1416,\n 2850,\n 16,\n 796,\n 685,\n 5237,\n 13,\n 3365,\n 11,\n 8275,\n 13,\n 5066,\n 11,\n 9773,\n 13,\n 2718,\n 11,\n 6740,\n 13,\n 4310,\n 11,\n 8190,\n 13,\n 4089,\n 11,\n 7724,\n 13,\n 1314,\n 11,\n 7863,\n 13,\n 2713,\n 11,\n 8854,\n 13,\n 5332,\n 11,\n 10111,\n 13,\n 1731,\n 11,\n 8684,\n 13,\n 6659,\n 11,\n 9919,\n 13,\n 2682,\n 11,\n 8915,\n 13,\n 2598,\n 11,\n 8257,\n 13,\n 4309,\n 11,\n 7600,\n 13,\n 1485,\n 11,\n 4101,\n 13,\n 2425,\n 11,\n 4317,\n 13,\n 1959,\n 11,\n 5441,\n 13,\n 5237,\n 11,\n 7600,\n 13,\n 2548,\n 11,\n 8541,\n 13,\n 6469,\n 11,\n 9661,\n 13,\n 3132,\n 11,\n 9225,\n 13,\n 2919,\n 11,\n 8454,\n 13,\n 4761,\n 11,\n 9166,\n 13,\n 2091,\n 11,\n 4019,\n 13,\n 3324,\n 11,\n 4019,\n 13,\n 3132,\n 11,\n 8699,\n 13,\n 1433,\n 11,\n 8454,\n 13,\n 1314,\n 11,\n 5598,\n 13,\n 2079,\n 11,\n 7724,\n 13,\n 3134,\n 11,\n 8699,\n 13,\n 5824,\n 60,\n 198,\n 1069,\n 321,\n 62,\n 1416,\n 2850,\n 17,\n 796,\n 685,\n 4761,\n 13,\n 2548,\n 11,\n 9166,\n 13,\n 2078,\n 11,\n 9225,\n 13,\n 1731,\n 11,\n 9698,\n 13,\n 4521,\n 11,\n 9508,\n 13,\n 3682,\n 11,\n 9225,\n 13,\n 2548,\n 11,\n 5441,\n 13,\n 4349,\n 11,\n 8684,\n 13,\n 5066,\n 11,\n 9773,\n 13,\n 2780,\n 11,\n 3695,\n 13,\n 6659,\n 11,\n 3720,\n 13,\n 1954,\n 11,\n 4524,\n 13,\n 2548,\n 11,\n 3720,\n 13,\n 1983,\n 11,\n 6659,\n 13,\n 2998,\n 11,\n 2425,\n 13,\n 3682,\n 11,\n 3829,\n 13,\n 2327,\n 11,\n 6469,\n 13,\n 6052,\n 11,\n 4521,\n 13,\n 4524,\n 11,\n 6659,\n 13,\n 2091,\n 11,\n 3865,\n 13,\n 16,\n 11,\n 4521,\n 13,\n 3553,\n 11,\n 5999,\n 13,\n 2791,\n 11,\n 5332,\n 13,\n 3365,\n 11,\n 6659,\n 13,\n 5774,\n 11,\n 5892,\n 13,\n 1415,\n 11,\n 4761,\n 13,\n 1314,\n 11,\n 6420,\n 13,\n 2414,\n 11,\n 4524,\n 13,\n 2481,\n 11,\n 4531,\n 13,\n 3023,\n 11,\n 4304,\n 13,\n 4051,\n 11,\n 6659,\n 13,\n 24,\n 11,\n 4846,\n 13,\n 20,\n 11,\n 1795,\n 13,\n 2713,\n 11,\n 4524,\n 13,\n 3324,\n 11,\n 4761,\n 13,\n 2075,\n 11,\n 4790,\n 13,\n 1954,\n 11,\n 5892,\n 13,\n 21,\n 11,\n 2791,\n 13,\n 1828,\n 11,\n 2154,\n 13,\n 2931,\n 11,\n 3324,\n 13,\n 17,\n 60,\n 198,\n 198,\n 2,\n 6889,\n 534,\n 7110,\n 994,\n 198,\n 489,\n 83,\n 13,\n 26875,\n 7,\n 5647,\n 7857,\n 16193,\n 940,\n 11,\n 23,\n 4008,\n 198,\n 489,\n 83,\n 13,\n 10034,\n 7,\n 1069,\n 321,\n 62,\n 1416,\n 2850,\n 16,\n 11,\n 65,\n 1040,\n 28,\n 1065,\n 11,\n 27237,\n 276,\n 28,\n 17821,\n 11,\n 198,\n 220,\n 220,\n 220,\n 220,\n 220,\n 220,\n 220,\n 220,\n 1554,\n 4906,\n 11639,\n 9662,\n 3256,\n 2815,\n 413,\n 5649,\n 28,\n 17,\n 8,\n 198,\n 489,\n 83,\n 13,\n 10034,\n 7,\n 1069,\n 321,\n 62,\n 1416,\n 2850,\n 17,\n 11,\n 65,\n 1040,\n 28,\n 1065,\n 11,\n 27237,\n 276,\n 28,\n 17821,\n 11,\n 198,\n 220,\n 220,\n 220,\n 220,\n 220,\n 220,\n 220,\n 220,\n 1554,\n 4906,\n 11639,\n 9662,\n 3256,\n 2815,\n 413,\n 5649,\n 28,\n 17,\n 8,\n 198,\n 1455,\n 2412,\n 28,\n 14692,\n 16,\n 301,\n 575,\n 81,\n 38094,\n 2430,\n 17,\n 358,\n 575,\n 81,\n 38094,\n 8973,\n 198,\n 489,\n 83,\n 13,\n 1455,\n 437,\n 7,\n 1455,\n 2412,\n 8,\n 198,\n 489,\n 83,\n 13,\n 7839,\n 7203,\n 19006,\n 35909,\n 15178,\n 27484,\n 4943,\n 198,\n 489,\n 83,\n 13,\n 87,\n 18242,\n 7203,\n 31905,\n 496,\n 4943,\n 198,\n 489,\n 83,\n 13,\n 2645,\n 9608,\n 7203,\n 37,\n 28707,\n 4943,\n 198,\n 198,\n 489,\n 83,\n 13,\n 21928,\n 5647,\n 7203,\n 1820,\n 62,\n 10034,\n 21857,\n 13,\n 11134,\n 4943,\n 198,\n 2,\n 16626,\n 198,\n 11748,\n 299,\n 32152,\n 355,\n 45941,\n 198,\n 11748,\n 19798,\n 292,\n 355,\n 279,\n 67,\n 198,\n 198,\n 2,\n 17267,\n 2603,\n 29487,\n 8019,\n 12972,\n 29487,\n 198,\n 6738,\n 2603,\n 29487,\n 8019,\n 1330,\n 12972,\n 29487,\n 355,\n 458,\n 83,\n 198,\n 198,\n 2,\n 4149,\n 287,\n 8945,\n 1366,\n 198,\n 18223,\n 395,\n 62,\n 12106,\n 796,\n 279,\n 67,\n 13,\n 961,\n 62,\n 40664,\n 7203,\n 4852,\n 12,\n 71,\n 3229,\n 12,\n 12106,\n 13,\n 40664,\n 4943,\n 198,\n 198,\n 2,\n 12793,\n 8611,\n 1661,\n 284,\n 257,\n 4553,\n 299,\n 32152,\n 7177,\n 198,\n 9800,\n 62,\n 1095,\n 796,\n 6000,\n 62,\n 12106,\n 17816,\n 32,\n 3212,\n 20520,\n 198,\n 198,\n 2,\n 5765,\n 299,\n 32152,\n 284,\n 15284,\n 262,\n 2811,\n 2479,\n 286,\n 262,\n 1353,\n 1802,\n 7035,\n 198,\n 23913,\n 62,\n 496,\n 796,\n 45941,\n 13,\n 23913,\n 7,\n 9800,\n 62,\n 1095,\n 8,\n 198,\n 198,\n 4798,\n 7203,\n 464,\n 2811,\n 2479,\n 286,\n 262,\n 1802,\n 6000,\n 7035,\n 11,\n 1864,\n 284,\n 1004,\n 337,\n 14378,\n 318,\n 25,\n 366,\n 1343,\n 965,\n 7,\n 23913,\n 62,\n 496,\n 4008,\n 198,\n 198,\n 2,\n 28114,\n 262,\n 3785,\n 198,\n 489,\n 83,\n 13,\n 10034,\n 7,\n 9800,\n 62,\n 1095,\n 11,\n 2837,\n 16193,\n 940,\n 11,\n 4019,\n 828,\n 41701,\n 28,\n 1415,\n 11,\n 220,\n 5743,\n 8043,\n 11639,\n 13424,\n 11537,\n 198,\n 489,\n 83,\n 13,\n 7839,\n 7203,\n 23396,\n 286,\n 5849,\n 1802,\n 24467,\n 46665,\n 379,\n 45065,\n 4943,\n 198,\n 489,\n 83,\n 13,\n 87,\n 18242,\n 7203,\n 15202,\n 341,\n 7129,\n 4943,\n 198,\n 489,\n 83,\n 13,\n 2645,\n 9608,\n 7203,\n 12332,\n 4943,\n 198,\n 489,\n 83,\n 13,\n 897,\n 85,\n 1370,\n 7,\n 23913,\n 62,\n 496,\n 11,\n 3124,\n 11639,\n 81,\n 3256,\n 9493,\n 10992,\n 11639,\n 39390,\n 3256,\n 9493,\n 413,\n 5649,\n 28,\n 17,\n 11,\n 6167,\n 2625,\n 5308,\n 272,\n 4943,\n 198,\n 489,\n 83,\n 13,\n 1455,\n 437,\n 3419,\n 198,\n 198,\n 489,\n 83,\n 13,\n 12860,\n 3419,\n 198\n]"},"ratio_char_token":{"kind":"number","value":2.376,"string":"2.376"},"token_count":{"kind":"number","value":875,"string":"875"}}},{"rowIdx":1248,"cells":{"content":{"kind":"string","value":"# print(123456)\n# print('Kaic', 'Pierre', 'Outra Coisa')\n# print('Kaic', 'Pierre', sep='-', end='')\n# print('Testando', 'Outras', 'Coisas', sep='-', end='')\nprint('428', '330', '048', sep='.', end='-')\nprint('93')\n"},"input_ids":{"kind":"list like","value":[2,3601,7,10163,29228,8,198,2,3601,10786,42,18452,3256,705,36910,3256,705,7975,430,1766,9160,11537,198,2,3601,10786,42,18452,3256,705,36910,3256,41767,11639,12,3256,886,28,7061,8,198,2,3601,10786,14402,25440,3256,705,7975,8847,3256,705,7222,271,292,3256,41767,11639,12,3256,886,28,7061,8,198,4798,10786,40173,3256,705,26073,3256,705,47202,3256,41767,11639,2637,11,886,11639,12,11537,198,4798,10786,6052,11537,198],"string":"[\n 2,\n 3601,\n 7,\n 10163,\n 29228,\n 8,\n 198,\n 2,\n 3601,\n 10786,\n 42,\n 18452,\n 3256,\n 705,\n 36910,\n 3256,\n 705,\n 7975,\n 430,\n 1766,\n 9160,\n 11537,\n 198,\n 2,\n 3601,\n 10786,\n 42,\n 18452,\n 3256,\n 705,\n 36910,\n 3256,\n 41767,\n 11639,\n 12,\n 3256,\n 886,\n 28,\n 7061,\n 8,\n 198,\n 2,\n 3601,\n 10786,\n 14402,\n 25440,\n 3256,\n 705,\n 7975,\n 8847,\n 3256,\n 705,\n 7222,\n 271,\n 292,\n 3256,\n 41767,\n 11639,\n 12,\n 3256,\n 886,\n 28,\n 7061,\n 8,\n 198,\n 4798,\n 10786,\n 40173,\n 3256,\n 705,\n 26073,\n 3256,\n 705,\n 47202,\n 3256,\n 41767,\n 11639,\n 2637,\n 11,\n 886,\n 11639,\n 12,\n 11537,\n 198,\n 4798,\n 10786,\n 6052,\n 11537,\n 198\n]"},"ratio_char_token":{"kind":"number","value":2.404494382022472,"string":"2.404494"},"token_count":{"kind":"number","value":89,"string":"89"}}},{"rowIdx":1249,"cells":{"content":{"kind":"string","value":"import sys\nsys.path.append(\"../\")\n\n# KoBERT 모델\n\nimport config\n\nimport pandas as pd\nimport numpy as np\nfrom sklearn.preprocessing import OneHotEncoder\n\nimport torch\nfrom torch import nn\nimport torch.nn.functional as F\nimport torch.optim as optim\nfrom torch.utils.data import Dataset, DataLoader\nimport gluonnlp as nlp\nfrom tqdm import tqdm, tqdm_notebook\n\n\n\nfrom KoBERT.kobert.utils import get_tokenizer\nfrom KoBERT.kobert.pytorch_kobert import get_pytorch_kobert_model\n\nfrom transformers import AdamW\n# from transformers.optimization import WarmupLinearSchedule\n\nfrom transformers import get_linear_schedule_with_warmup\n\ndevice = torch.device('cuda' if torch.cuda.is_available() else 'cpu')\n\nbertmodel, vocab = get_pytorch_kobert_model()\n\n# 토크나이저 메서드를 tokenizer에 호출\n# 코퍼스를 토큰으로 만드는 과정을 수행, 이 때 토크나이저는 kobert 패키지에 있는 get_tokenizer()를 사용하고,\n# 토큰화를 위해 필요한 단어 사전은 kobert의 vocab을 사용함.\n# uncased로 투입해야 하므로 lower = False\n\ntokenizer = get_tokenizer()\ntok = nlp.data.BERTSPTokenizer(tokenizer, vocab, lower = False)\nprint(f'device using: {device}')\n\n\nmodel_config=config.model_config\n\n\n \n\nclass EarlyStopping:\n \"\"\"Early stops the training if validation loss doesn't improve after a given patience.\"\"\"\n def __init__(self, patience=7, verbose=False, delta=0, path='checkpoint.pt', trace_func=print):\n \"\"\"\n Args:\n patience (int): How long to wait after last time validation loss improved.\n Default: 7\n verbose (bool): If True, prints a message for each validation loss improvement. \n Default: False\n delta (float): Minimum change in the monitored quantity to qualify as an improvement.\n Default: 0\n path (str): Path for the checkpoint to be saved to.\n Default: 'checkpoint.pt'\n trace_func (function): trace print function.\n Default: print \n \"\"\"\n self.patience = patience\n self.verbose = verbose\n self.counter = 0\n self.best_score = None\n self.early_stop = False\n self.val_loss_min = np.Inf\n self.delta = delta\n self.path = path\n self.trace_func = trace_func\n\n def save_checkpoint(self, val_loss, model):\n '''Saves model when validation loss decrease.'''\n if self.verbose:\n self.trace_func(f'Validation loss decreased ({self.val_loss_min:.6f} --> {val_loss:.6f}). Saving model ...')\n torch.save(model.state_dict(), self.path)\n self.val_loss_min = val_loss\n"},"input_ids":{"kind":"list like","value":[11748,25064,198,17597,13,6978,13,33295,7203,40720,4943,198,198,2,17634,13246,51,31619,103,101,167,235,116,198,198,11748,4566,198,198,11748,19798,292,355,279,67,198,11748,299,32152,355,45941,198,6738,1341,35720,13,3866,36948,1330,1881,21352,27195,12342,198,198,11748,28034,198,6738,28034,1330,299,77,198,11748,28034,13,20471,13,45124,355,376,198,11748,28034,13,40085,355,6436,198,6738,28034,13,26791,13,7890,1330,16092,292,316,11,6060,17401,198,11748,1278,84,261,21283,79,355,299,34431,198,6738,256,80,36020,1330,256,80,36020,11,256,80,36020,62,11295,2070,628,198,198,6738,17634,13246,51,13,74,2023,83,13,26791,1330,651,62,30001,7509,198,6738,17634,13246,51,13,74,2023,83,13,9078,13165,354,62,74,2023,83,1330,651,62,9078,13165,354,62,74,2023,83,62,19849,198,198,6738,6121,364,1330,7244,54,198,2,422,6121,364,13,40085,1634,1330,25692,929,14993,451,27054,5950,198,198,6738,6121,364,1330,651,62,29127,62,15952,5950,62,4480,62,31975,929,198,198,25202,796,28034,13,25202,10786,66,15339,6,611,28034,13,66,15339,13,271,62,15182,3419,2073,705,36166,11537,198,198,4835,19849,11,12776,397,796,651,62,9078,13165,354,62,74,2023,83,62,19849,3419,198,198,2,220,169,228,254,169,223,105,167,224,246,35975,112,168,254,222,31619,102,242,168,226,250,167,241,250,167,98,120,11241,7509,168,245,238,220,169,246,116,168,114,250,198,2,23821,121,242,169,235,120,168,232,97,167,98,120,220,169,228,254,169,223,108,168,250,120,167,94,250,31619,100,234,167,241,250,167,232,242,220,166,111,120,168,254,243,35975,226,23821,230,246,169,244,231,11,23821,251,112,31619,243,234,220,169,228,254,169,223,105,167,224,246,35975,112,168,254,222,167,232,242,479,2023,83,220,169,234,101,169,224,97,168,100,222,168,245,238,23821,252,230,167,232,242,651,62,30001,7509,3419,167,98,120,23821,8955,168,248,102,47991,246,166,111,254,11,198,2,220,169,228,254,169,223,108,169,247,242,167,98,120,23821,250,226,47991,112,220,47991,226,168,248,242,47991,250,31619,233,101,168,244,112,23821,8955,168,254,226,35975,222,479,2023,83,35975,246,12776,397,35975,226,23821,8955,168,248,102,47991,101,13,198,2,4591,839,167,94,250,220,169,230,105,168,252,227,47991,112,168,243,120,220,47991,246,167,107,222,167,94,250,2793,796,10352,198,198,30001,7509,796,651,62,30001,7509,3419,198,83,482,796,299,34431,13,7890,13,13246,51,4303,30642,7509,7,30001,7509,11,12776,397,11,2793,796,10352,8,198,4798,7,69,1549,1990,501,1262,25,1391,25202,92,11537,628,198,19849,62,11250,28,11250,13,19849,62,11250,628,198,220,220,220,220,198,198,4871,12556,1273,33307,25,198,220,220,220,37227,20457,9911,262,3047,611,21201,2994,1595,470,2987,706,257,1813,16336,526,15931,198,220,220,220,825,11593,15003,834,7,944,11,16336,28,22,11,15942,577,28,25101,11,25979,28,15,11,3108,11639,9122,4122,13,457,3256,12854,62,20786,28,4798,2599,198,220,220,220,220,220,220,220,37227,198,220,220,220,220,220,220,220,943,14542,25,198,220,220,220,220,220,220,220,220,220,220,220,16336,357,600,2599,1374,890,284,4043,706,938,640,21201,2994,6596,13,198,220,220,220,220,220,220,220,220,220,220,220,220,220,220,220,220,220,220,220,220,220,220,220,220,220,220,220,15161,25,767,198,220,220,220,220,220,220,220,220,220,220,220,15942,577,357,30388,2599,1002,6407,11,20842,257,3275,329,1123,21201,2994,9025,13,220,198,220,220,220,220,220,220,220,220,220,220,220,220,220,220,220,220,220,220,220,220,220,220,220,220,220,220,220,15161,25,10352,198,220,220,220,220,220,220,220,220,220,220,220,25979,357,22468,2599,26265,1487,287,262,20738,12040,284,12780,355,281,9025,13,198,220,220,220,220,220,220,220,220,220,220,220,220,220,220,220,220,220,220,220,220,220,220,220,220,220,220,220,15161,25,657,198,220,220,220,220,220,220,220,220,220,220,220,3108,357,2536,2599,10644,329,262,26954,284,307,7448,284,13,198,220,220,220,220,220,220,220,220,220,220,220,220,220,220,220,220,220,220,220,220,220,220,220,220,220,220,220,15161,25,705,9122,4122,13,457,6,198,220,220,220,220,220,220,220,220,220,220,220,12854,62,20786,357,8818,2599,12854,3601,2163,13,198,220,220,220,220,220,220,220,220,220,220,220,220,220,220,220,220,220,220,220,220,220,220,220,220,220,220,220,15161,25,3601,220,220,220,220,220,220,220,220,220,220,220,220,198,220,220,220,220,220,220,220,37227,198,220,220,220,220,220,220,220,2116,13,8071,1240,796,16336,198,220,220,220,220,220,220,220,2116,13,19011,577,796,15942,577,198,220,220,220,220,220,220,220,2116,13,24588,796,657,198,220,220,220,220,220,220,220,2116,13,13466,62,26675,796,6045,198,220,220,220,220,220,220,220,2116,13,11458,62,11338,796,10352,198,220,220,220,220,220,220,220,2116,13,2100,62,22462,62,1084,796,45941,13,18943,198,220,220,220,220,220,220,220,2116,13,67,12514,796,25979,198,220,220,220,220,220,220,220,2116,13,6978,796,3108,198,220,220,220,220,220,220,220,2116,13,40546,62,20786,796,12854,62,20786,628,220,220,220,825,3613,62,9122,4122,7,944,11,1188,62,22462,11,2746,2599,198,220,220,220,220,220,220,220,705,7061,50,3080,2746,618,21201,2994,10070,2637,7061,198,220,220,220,220,220,220,220,611,2116,13,19011,577,25,198,220,220,220,220,220,220,220,220,220,220,220,2116,13,40546,62,20786,7,69,6,7762,24765,2994,11832,37913,944,13,2100,62,22462,62,1084,25,13,21,69,92,14610,1391,2100,62,22462,25,13,21,69,92,737,220,34689,2746,2644,11537,198,220,220,220,220,220,220,220,28034,13,21928,7,19849,13,5219,62,11600,22784,2116,13,6978,8,198,220,220,220,220,220,220,220,2116,13,2100,62,22462,62,1084,796,1188,62,22462,198],"string":"[\n 11748,\n 25064,\n 198,\n 17597,\n 13,\n 6978,\n 13,\n 33295,\n 7203,\n 40720,\n 4943,\n 198,\n 198,\n 2,\n 17634,\n 13246,\n 51,\n 31619,\n 103,\n 101,\n 167,\n 235,\n 116,\n 198,\n 198,\n 11748,\n 4566,\n 198,\n 198,\n 11748,\n 19798,\n 292,\n 355,\n 279,\n 67,\n 198,\n 11748,\n 299,\n 32152,\n 355,\n 45941,\n 198,\n 6738,\n 1341,\n 35720,\n 13,\n 3866,\n 36948,\n 1330,\n 1881,\n 21352,\n 27195,\n 12342,\n 198,\n 198,\n 11748,\n 28034,\n 198,\n 6738,\n 28034,\n 1330,\n 299,\n 77,\n 198,\n 11748,\n 28034,\n 13,\n 20471,\n 13,\n 45124,\n 355,\n 376,\n 198,\n 11748,\n 28034,\n 13,\n 40085,\n 355,\n 6436,\n 198,\n 6738,\n 28034,\n 13,\n 26791,\n 13,\n 7890,\n 1330,\n 16092,\n 292,\n 316,\n 11,\n 6060,\n 17401,\n 198,\n 11748,\n 1278,\n 84,\n 261,\n 21283,\n 79,\n 355,\n 299,\n 34431,\n 198,\n 6738,\n 256,\n 80,\n 36020,\n 1330,\n 256,\n 80,\n 36020,\n 11,\n 256,\n 80,\n 36020,\n 62,\n 11295,\n 2070,\n 628,\n 198,\n 198,\n 6738,\n 17634,\n 13246,\n 51,\n 13,\n 74,\n 2023,\n 83,\n 13,\n 26791,\n 1330,\n 651,\n 62,\n 30001,\n 7509,\n 198,\n 6738,\n 17634,\n 13246,\n 51,\n 13,\n 74,\n 2023,\n 83,\n 13,\n 9078,\n 13165,\n 354,\n 62,\n 74,\n 2023,\n 83,\n 1330,\n 651,\n 62,\n 9078,\n 13165,\n 354,\n 62,\n 74,\n 2023,\n 83,\n 62,\n 19849,\n 198,\n 198,\n 6738,\n 6121,\n 364,\n 1330,\n 7244,\n 54,\n 198,\n 2,\n 422,\n 6121,\n 364,\n 13,\n 40085,\n 1634,\n 1330,\n 25692,\n 929,\n 14993,\n 451,\n 27054,\n 5950,\n 198,\n 198,\n 6738,\n 6121,\n 364,\n 1330,\n 651,\n 62,\n 29127,\n 62,\n 15952,\n 5950,\n 62,\n 4480,\n 62,\n 31975,\n 929,\n 198,\n 198,\n 25202,\n 796,\n 28034,\n 13,\n 25202,\n 10786,\n 66,\n 15339,\n 6,\n 611,\n 28034,\n 13,\n 66,\n 15339,\n 13,\n 271,\n 62,\n 15182,\n 3419,\n 2073,\n 705,\n 36166,\n 11537,\n 198,\n 198,\n 4835,\n 19849,\n 11,\n 12776,\n 397,\n 796,\n 651,\n 62,\n 9078,\n 13165,\n 354,\n 62,\n 74,\n 2023,\n 83,\n 62,\n 19849,\n 3419,\n 198,\n 198,\n 2,\n 220,\n 169,\n 228,\n 254,\n 169,\n 223,\n 105,\n 167,\n 224,\n 246,\n 35975,\n 112,\n 168,\n 254,\n 222,\n 31619,\n 102,\n 242,\n 168,\n 226,\n 250,\n 167,\n 241,\n 250,\n 167,\n 98,\n 120,\n 11241,\n 7509,\n 168,\n 245,\n 238,\n 220,\n 169,\n 246,\n 116,\n 168,\n 114,\n 250,\n 198,\n 2,\n 23821,\n 121,\n 242,\n 169,\n 235,\n 120,\n 168,\n 232,\n 97,\n 167,\n 98,\n 120,\n 220,\n 169,\n 228,\n 254,\n 169,\n 223,\n 108,\n 168,\n 250,\n 120,\n 167,\n 94,\n 250,\n 31619,\n 100,\n 234,\n 167,\n 241,\n 250,\n 167,\n 232,\n 242,\n 220,\n 166,\n 111,\n 120,\n 168,\n 254,\n 243,\n 35975,\n 226,\n 23821,\n 230,\n 246,\n 169,\n 244,\n 231,\n 11,\n 23821,\n 251,\n 112,\n 31619,\n 243,\n 234,\n 220,\n 169,\n 228,\n 254,\n 169,\n 223,\n 105,\n 167,\n 224,\n 246,\n 35975,\n 112,\n 168,\n 254,\n 222,\n 167,\n 232,\n 242,\n 479,\n 2023,\n 83,\n 220,\n 169,\n 234,\n 101,\n 169,\n 224,\n 97,\n 168,\n 100,\n 222,\n 168,\n 245,\n 238,\n 23821,\n 252,\n 230,\n 167,\n 232,\n 242,\n 651,\n 62,\n 30001,\n 7509,\n 3419,\n 167,\n 98,\n 120,\n 23821,\n 8955,\n 168,\n 248,\n 102,\n 47991,\n 246,\n 166,\n 111,\n 254,\n 11,\n 198,\n 2,\n 220,\n 169,\n 228,\n 254,\n 169,\n 223,\n 108,\n 169,\n 247,\n 242,\n 167,\n 98,\n 120,\n 23821,\n 250,\n 226,\n 47991,\n 112,\n 220,\n 47991,\n 226,\n 168,\n 248,\n 242,\n 47991,\n 250,\n 31619,\n 233,\n 101,\n 168,\n 244,\n 112,\n 23821,\n 8955,\n 168,\n 254,\n 226,\n 35975,\n 222,\n 479,\n 2023,\n 83,\n 35975,\n 246,\n 12776,\n 397,\n 35975,\n 226,\n 23821,\n 8955,\n 168,\n 248,\n 102,\n 47991,\n 101,\n 13,\n 198,\n 2,\n 4591,\n 839,\n 167,\n 94,\n 250,\n 220,\n 169,\n 230,\n 105,\n 168,\n 252,\n 227,\n 47991,\n 112,\n 168,\n 243,\n 120,\n 220,\n 47991,\n 246,\n 167,\n 107,\n 222,\n 167,\n 94,\n 250,\n 2793,\n 796,\n 10352,\n 198,\n 198,\n 30001,\n 7509,\n 796,\n 651,\n 62,\n 30001,\n 7509,\n 3419,\n 198,\n 83,\n 482,\n 796,\n 299,\n 34431,\n 13,\n 7890,\n 13,\n 13246,\n 51,\n 4303,\n 30642,\n 7509,\n 7,\n 30001,\n 7509,\n 11,\n 12776,\n 397,\n 11,\n 2793,\n 796,\n 10352,\n 8,\n 198,\n 4798,\n 7,\n 69,\n 1549,\n 1990,\n 501,\n 1262,\n 25,\n 1391,\n 25202,\n 92,\n 11537,\n 628,\n 198,\n 19849,\n 62,\n 11250,\n 28,\n 11250,\n 13,\n 19849,\n 62,\n 11250,\n 628,\n 198,\n 220,\n 220,\n 220,\n 220,\n 198,\n 198,\n 4871,\n 12556,\n 1273,\n 33307,\n 25,\n 198,\n 220,\n 220,\n 220,\n 37227,\n 20457,\n 9911,\n 262,\n 3047,\n 611,\n 21201,\n 2994,\n 1595,\n 470,\n 2987,\n 706,\n 257,\n 1813,\n 16336,\n 526,\n 15931,\n 198,\n 220,\n 220,\n 220,\n 825,\n 11593,\n 15003,\n 834,\n 7,\n 944,\n 11,\n 16336,\n 28,\n 22,\n 11,\n 15942,\n 577,\n 28,\n 25101,\n 11,\n 25979,\n 28,\n 15,\n 11,\n 3108,\n 11639,\n 9122,\n 4122,\n 13,\n 457,\n 3256,\n 12854,\n 62,\n 20786,\n 28,\n 4798,\n 2599,\n 198,\n 220,\n 220,\n 220,\n 220,\n 220,\n 220,\n 220,\n 37227,\n 198,\n 220,\n 220,\n 220,\n 220,\n 220,\n 220,\n 220,\n 943,\n 14542,\n 25,\n 198,\n 220,\n 220,\n 220,\n 220,\n 220,\n 220,\n 220,\n 220,\n 220,\n 220,\n 220,\n 16336,\n 357,\n 600,\n 2599,\n 1374,\n 890,\n 284,\n 4043,\n 706,\n 938,\n 640,\n 21201,\n 2994,\n 6596,\n 13,\n 198,\n 220,\n 220,\n 220,\n 220,\n 220,\n 220,\n 220,\n 220,\n 220,\n 220,\n 220,\n 220,\n 220,\n 220,\n 220,\n 220,\n 220,\n 220,\n 220,\n 220,\n 220,\n 220,\n 220,\n 220,\n 220,\n 220,\n 220,\n 15161,\n 25,\n 767,\n 198,\n 220,\n 220,\n 220,\n 220,\n 220,\n 220,\n 220,\n 220,\n 220,\n 220,\n 220,\n 15942,\n 577,\n 357,\n 30388,\n 2599,\n 1002,\n 6407,\n 11,\n 20842,\n 257,\n 3275,\n 329,\n 1123,\n 21201,\n 2994,\n 9025,\n 13,\n 220,\n 198,\n 220,\n 220,\n 220,\n 220,\n 220,\n 220,\n 220,\n 220,\n 220,\n 220,\n 220,\n 220,\n 220,\n 220,\n 220,\n 220,\n 220,\n 220,\n 220,\n 220,\n 220,\n 220,\n 220,\n 220,\n 220,\n 220,\n 220,\n 15161,\n 25,\n 10352,\n 198,\n 220,\n 220,\n 220,\n 220,\n 220,\n 220,\n 220,\n 220,\n 220,\n 220,\n 220,\n 25979,\n 357,\n 22468,\n 2599,\n 26265,\n 1487,\n 287,\n 262,\n 20738,\n 12040,\n 284,\n 12780,\n 355,\n 281,\n 9025,\n 13,\n 198,\n 220,\n 220,\n 220,\n 220,\n 220,\n 220,\n 220,\n 220,\n 220,\n 220,\n 220,\n 220,\n 220,\n 220,\n 220,\n 220,\n 220,\n 220,\n 220,\n 220,\n 220,\n 220,\n 220,\n 220,\n 220,\n 220,\n 220,\n 15161,\n 25,\n 657,\n 198,\n 220,\n 220,\n 220,\n 220,\n 220,\n 220,\n 220,\n 220,\n 220,\n 220,\n 220,\n 3108,\n 357,\n 2536,\n 2599,\n 10644,\n 329,\n 262,\n 26954,\n 284,\n 307,\n 7448,\n 284,\n 13,\n 198,\n 220,\n 220,\n 220,\n 220,\n 220,\n 220,\n 220,\n 220,\n 220,\n 220,\n 220,\n 220,\n 220,\n 220,\n 220,\n 220,\n 220,\n 220,\n 220,\n 220,\n 220,\n 220,\n 220,\n 220,\n 220,\n 220,\n 220,\n 15161,\n 25,\n 705,\n 9122,\n 4122,\n 13,\n 457,\n 6,\n 198,\n 220,\n 220,\n 220,\n 220,\n 220,\n 220,\n 220,\n 220,\n 220,\n 220,\n 220,\n 12854,\n 62,\n 20786,\n 357,\n 8818,\n 2599,\n 12854,\n 3601,\n 2163,\n 13,\n 198,\n 220,\n 220,\n 220,\n 220,\n 220,\n 220,\n 220,\n 220,\n 220,\n 220,\n 220,\n 220,\n 220,\n 220,\n 220,\n 220,\n 220,\n 220,\n 220,\n 220,\n 220,\n 220,\n 220,\n 220,\n 220,\n 220,\n 220,\n 15161,\n 25,\n 3601,\n 220,\n 220,\n 220,\n 220,\n 220,\n 220,\n 220,\n 220,\n 220,\n 220,\n 220,\n 220,\n 198,\n 220,\n 220,\n 220,\n 220,\n 220,\n 220,\n 220,\n 37227,\n 198,\n 220,\n 220,\n 220,\n 220,\n 220,\n 220,\n 220,\n 2116,\n 13,\n 8071,\n 1240,\n 796,\n 16336,\n 198,\n 220,\n 220,\n 220,\n 220,\n 220,\n 220,\n 220,\n 2116,\n 13,\n 19011,\n 577,\n 796,\n 15942,\n 577,\n 198,\n 220,\n 220,\n 220,\n 220,\n 220,\n 220,\n 220,\n 2116,\n 13,\n 24588,\n 796,\n 657,\n 198,\n 220,\n 220,\n 220,\n 220,\n 220,\n 220,\n 220,\n 2116,\n 13,\n 13466,\n 62,\n 26675,\n 796,\n 6045,\n 198,\n 220,\n 220,\n 220,\n 220,\n 220,\n 220,\n 220,\n 2116,\n 13,\n 11458,\n 62,\n 11338,\n 796,\n 10352,\n 198,\n 220,\n 220,\n 220,\n 220,\n 220,\n 220,\n 220,\n 2116,\n 13,\n 2100,\n 62,\n 22462,\n 62,\n 1084,\n 796,\n 45941,\n 13,\n 18943,\n 198,\n 220,\n 220,\n 220,\n 220,\n 220,\n 220,\n 220,\n 2116,\n 13,\n 67,\n 12514,\n 796,\n 25979,\n 198,\n 220,\n 220,\n 220,\n 220,\n 220,\n 220,\n 220,\n 2116,\n 13,\n 6978,\n 796,\n 3108,\n 198,\n 220,\n 220,\n 220,\n 220,\n 220,\n 220,\n 220,\n 2116,\n 13,\n 40546,\n 62,\n 20786,\n 796,\n 12854,\n 62,\n 20786,\n 628,\n 220,\n 220,\n 220,\n 825,\n 3613,\n 62,\n 9122,\n 4122,\n 7,\n 944,\n 11,\n 1188,\n 62,\n 22462,\n 11,\n 2746,\n 2599,\n 198,\n 220,\n 220,\n 220,\n 220,\n 220,\n 220,\n 220,\n 705,\n 7061,\n 50,\n 3080,\n 2746,\n 618,\n 21201,\n 2994,\n 10070,\n 2637,\n 7061,\n 198,\n 220,\n 220,\n 220,\n 220,\n 220,\n 220,\n 220,\n 611,\n 2116,\n 13,\n 19011,\n 577,\n 25,\n 198,\n 220,\n 220,\n 220,\n 220,\n 220,\n 220,\n 220,\n 220,\n 220,\n 220,\n 220,\n 2116,\n 13,\n 40546,\n 62,\n 20786,\n 7,\n 69,\n 6,\n 7762,\n 24765,\n 2994,\n 11832,\n 37913,\n 944,\n 13,\n 2100,\n 62,\n 22462,\n 62,\n 1084,\n 25,\n 13,\n 21,\n 69,\n 92,\n 14610,\n 1391,\n 2100,\n 62,\n 22462,\n 25,\n 13,\n 21,\n 69,\n 92,\n 737,\n 220,\n 34689,\n 2746,\n 2644,\n 11537,\n 198,\n 220,\n 220,\n 220,\n 220,\n 220,\n 220,\n 220,\n 28034,\n 13,\n 21928,\n 7,\n 19849,\n 13,\n 5219,\n 62,\n 11600,\n 22784,\n 2116,\n 13,\n 6978,\n 8,\n 198,\n 220,\n 220,\n 220,\n 220,\n 220,\n 220,\n 220,\n 2116,\n 13,\n 2100,\n 62,\n 22462,\n 62,\n 1084,\n 796,\n 1188,\n 62,\n 22462,\n 198\n]"},"ratio_char_token":{"kind":"number","value":2.075623491552695,"string":"2.075623"},"token_count":{"kind":"number","value":1243,"string":"1,243"}}},{"rowIdx":1250,"cells":{"content":{"kind":"string","value":"import urllib.parse\n\nfrom .saucenao import get_saucenao_detail, SauceNAOError\n\n"},"input_ids":{"kind":"list like","value":[11748,2956,297,571,13,29572,198,198,6738,764,82,14272,268,5488,1330,651,62,82,14272,268,5488,62,49170,11,37618,4535,46,12331,628],"string":"[\n 11748,\n 2956,\n 297,\n 571,\n 13,\n 29572,\n 198,\n 198,\n 6738,\n 764,\n 82,\n 14272,\n 268,\n 5488,\n 1330,\n 651,\n 62,\n 82,\n 14272,\n 268,\n 5488,\n 62,\n 49170,\n 11,\n 37618,\n 4535,\n 46,\n 12331,\n 628\n]"},"ratio_char_token":{"kind":"number","value":2.7241379310344827,"string":"2.724138"},"token_count":{"kind":"number","value":29,"string":"29"}}},{"rowIdx":1251,"cells":{"content":{"kind":"string","value":"A = True\nB = False\nprint(A and B)\nprint(A or B)\n"},"input_ids":{"kind":"list like","value":[32,796,6407,198,33,796,10352,198,4798,7,32,290,347,8,198,4798,7,32,393,347,8,198],"string":"[\n 32,\n 796,\n 6407,\n 198,\n 33,\n 796,\n 10352,\n 198,\n 4798,\n 7,\n 32,\n 290,\n 347,\n 8,\n 198,\n 4798,\n 7,\n 32,\n 393,\n 347,\n 8,\n 198\n]"},"ratio_char_token":{"kind":"number","value":2.1818181818181817,"string":"2.181818"},"token_count":{"kind":"number","value":22,"string":"22"}}},{"rowIdx":1252,"cells":{"content":{"kind":"string","value":"#!/usr/bin/env python\n# Author : Pierre Schnizer \n\"\"\"\nCollection of Callbacks systems for pygsl. They follow the GSL definitions as\nclose as possible. Instead os a struct python classes are used.\n\nAll solvers accept a C void pointer, which is passed to the callback. In Pygsl\nthis is an abitrary python object. See the doc strings of the various classes\nfor further detail.\n\n\"\"\"\nfrom . import _callback\n\n\nclass gsl_function(_gsl_function):\n \"\"\"\n This class defines the callbacks known as gsl_function to\n gsl.\n\n e.g to supply the function f:\n \n def f(x, params):\n a = params[0]\n b = parmas[1]\n c = params[3]\n return a * x ** 2 + b * x + c\n\n to some solver, use\n\n function = gsl_function(f, params)\n \"\"\"\n\n initfunc = _callback.gsl_function_init\n freefunc = _callback.gsl_function_free\n \nclass gsl_function_fdf(_gsl_function_fdf):\n \"\"\"\n This class defines the callbacks known as gsl_function_fdf to\n gsl.\n\n e.g to supply the function f:\n \n def f(x, None):\n return exp(2 * x)\n\n def df(x, None):\n return 2 * exp(2 * x)\n\n def fdf(x, None):\n myf = f(x, None)\n mydf = df(x, None)\n return myf, mydf\n\n\n to some solver, accepting gsl_function_fdf, use\n\n function = gsl_function_fdf(f, df, fdf, params)\n \"\"\"\n initfunc = _callback.gsl_function_init_fdf\n freefunc = _callback.gsl_function_free_fdf\n\n\n\nclass gsl_multiroot_function(_gsl_function):\n \"\"\"\n This class defines the callbacks for gsl_multiroot_function.\n\n To supply the function rosenbrock define the function:\n \n def rosenbrock_f(x, params):\n a = params[0]\n b = params[1]\n y = copy.copy(x)\n y[0] = a * (1 - x[0])\n y[1] = b * (x[1] - x[0] * x[0])\n return y\n\n sys = multiroots.gsl_multiroot_function(rosenbrock_f, params, 2)\n \"\"\"\n initfunc = _callback.gsl_multiroot_function_init\n freefunc = _callback.gsl_multiroot_function_free\n\n\n\nclass gsl_multiroot_function_fdf(_gsl_function_fdf):\n \"\"\"\n This class defines the callbacks for gsl_multiroot_function.\n \n To supply the function rosenbrock define the functions:\n \n def rosenbrock_f(x, params):\n a = params[0]\n b = params[1]\n y = copy.copy(x)\n y[0] = a * (1 - x[0])\n y[1] = b * (x[1] - x[0] * x[0])\n return y\n \n def rosenbrock_df(x, params):\n a = params[0]\n b = params[1]\n df = Numeric.zeros((x.shape[0], x.shape[0]), Numeric.Float)\n df[0,0] = -a\n df[0,1] = 0\n df[1,0] = -2 * b * x[0]\n df[1,1] = b\n return df\n \n def rosenbrock_fdf(x, params):\n f = rosenbrock_f(x, params)\n df = rosenbrock_df(x, params)\n return f, df\n\n # dimension of x\n size = 2\n sys = multiroots.gsl_multiroot_function(rosenbrock_f, rosenbrock_df,\n rosenbrock_fdf, params, size)\n \"\"\"\n initfunc = _callback.gsl_multiroot_function_init_fdf\n freefunc = _callback.gsl_multiroot_function_free_fdf\n\n\nclass gsl_multifit_function(_gsl_function):\n \"\"\"\n This class defines the callbacks for gsl_multimin_function.\n\n To fit a exponential function to data write the following function:\n \n def exp_f(x, params):\n A = x[0]\n lambda_ = x[1]\n b = x[2]\n t= params[0]\n yi = params[1]\n sigma = params[2]\n Yi = A * exp(-lambda_ * t) + b\n f = yi - Yi / sigma\n return f\n\n # Number of data samples\n n = len(data)\n # Number of paramters\n p = 3\n multifit_nlin.gsl_multifit_function(exp_f, data, n, p)\n \"\"\"\n\n initfunc = _callback.gsl_multifit_function_init\n freefunc = _callback.gsl_multifit_function_free\n\n \nclass gsl_multifit_function_fdf(_gsl_function_fdf):\n \"\"\"\n This class defines the callbacks for gsl_multimin_function.\n def exp_f(x, params):\n A = x[0]\n lambda_ = x[1]\n b = x[2]\n t= params[0]\n yi = params[1]\n sigma = params[2]\n Yi = A * exp(-lambda_ * t) + b\n f = yi - Yi / sigma\n return f\n\n def exp_df(x, params):\n A = x[0]\n lambda_ = x[1]\n b = x[2]\n t= params[0]\n yi = params[1]\n sigma = params[2]\n e = exp(-lambda_ * t)\n e_s = e/sigma\n df = Numeric.array((e_s, -t * A * e_s, 1/sigma))\n df = Numeric.transpose(df)\n print df.shape\n return df\n\n def exp_fdf(x, params):\n f = exp_f(x, params)\n df = exp_df(x, params)\n return f, df\n\n # Number of data samples\n n = len(data)\n # Number of paramters\n p = 3\n multifit_nlin.gsl_multifit_function_fdf(exp_f, exp_df, exp_fdf, data, n, p)\n\n \"\"\"\n initfunc = _callback.gsl_multifit_function_init_fdf\n freefunc = _callback.gsl_multifit_function_free_fdf\n\nclass gsl_multimin_function(gsl_multiroot_function): \n \"\"\"\n This class defines the callbacks for gsl_multimin_function.\n\n The following example function defines a simple paraboloid with two\n parameters.\n\n To supply the system define the function:\n def my_f(v, params):\n x = v[0]\n y = v[1]\n \n dp = params\n t1 = (x - dp[0])\n t2 = (y - dp[1])\n f = 10.0 * t1 * t1 + 20.0 * t2 * t2 + 30.0\n return f \n \n # dimension of x\n size = 2\n\n sys = multimin.gsl_multifit_function(my_f, params, 2)\n \"\"\"\n\n initfunc = _callback.gsl_multimin_function_init\n freefunc = _callback.gsl_multimin_function_free\n\nclass gsl_multimin_function_fdf(gsl_multiroot_function_fdf):\n \"\"\"\n This class defines the callbacks for gsl_multimin_function_fdf.\n\n The following example function defines a simple paraboloid with two\n parameters.\n\n To supply the system define the function:\n def my_f(v, params):\n x = v[0]\n y = v[1]\n \n dp = params\n t1 = (x - dp[0])\n t2 = (y - dp[1])\n f = 10.0 * t1 * t1 + 20.0 * t2 * t2 + 30.0\n return f\n def my_df(v, params):\n x = v[0]\n y = v[1]\n df = Numeric.zeros(v.shape, Numeric.Float)\n dp = params\n df[0] = 20. * (x - dp[0])\n df[1] = 40. * (y - dp[1])\n return df\n\n def my_fdf(v, params):\n f = my_f(v, params)\n df = my_df(v,params)\n return f, df\n\n \n # dimension of x\n size = 2\n sys = multimin.gsl_multifit_function(my_f, my_df, my_fdf, params, size)\n \"\"\"\n\n initfunc = _callback.gsl_multimin_function_init_fdf\n freefunc = _callback.gsl_multimin_function_free_fdf\n\nclass gsl_monte_function(gsl_multiroot_function): \n \"\"\"\n This class defines the callbacks for gsl_monte_function.\n\n \"\"\"\n\n initfunc = _callback.gsl_monte_function_init\n freefunc = _callback.gsl_monte_function_free\n"},"input_ids":{"kind":"list like","value":[2,48443,14629,14,8800,14,24330,21015,198,2,6434,1058,21204,45606,7509,220,198,37811,198,36307,286,4889,10146,3341,329,220,12972,70,6649,13,1119,1061,262,46326,17336,355,198,19836,355,1744,13,5455,28686,257,2878,21015,6097,389,973,13,198,198,3237,1540,690,2453,257,327,7951,17562,11,543,318,3804,284,262,23838,13,554,9485,70,6649,198,5661,318,281,450,270,11619,21015,2134,13,220,4091,262,2205,13042,286,262,2972,6097,198,1640,2252,3703,13,198,198,37811,198,6738,764,1330,4808,47423,628,198,4871,308,6649,62,8818,28264,70,6649,62,8818,2599,198,220,220,220,37227,198,220,220,220,770,1398,15738,262,869,10146,1900,355,308,6649,62,8818,284,198,220,220,220,308,6649,13,628,220,220,220,304,13,70,284,5127,262,2163,277,25,198,220,220,220,220,198,220,220,220,825,277,7,87,11,42287,2599,198,220,220,220,220,220,220,220,257,796,42287,58,15,60,198,220,220,220,220,220,220,220,275,796,1582,5356,58,16,60,198,220,220,220,220,220,220,220,269,796,42287,58,18,60,198,220,220,220,220,220,220,220,1441,257,1635,2124,12429,362,1343,275,1635,2124,1343,269,628,220,220,220,284,617,1540,332,11,779,628,220,220,220,2163,796,308,6649,62,8818,7,69,11,42287,8,198,220,220,220,37227,628,220,220,220,2315,20786,796,220,4808,47423,13,70,6649,62,8818,62,15003,198,220,220,220,1479,20786,796,220,4808,47423,13,70,6649,62,8818,62,5787,198,220,220,220,220,198,4871,308,6649,62,8818,62,69,7568,28264,70,6649,62,8818,62,69,7568,2599,198,220,220,220,37227,198,220,220,220,770,1398,15738,262,869,10146,1900,355,308,6649,62,8818,62,69,7568,284,198,220,220,220,308,6649,13,628,220,220,220,304,13,70,284,5127,262,2163,277,25,198,220,220,220,220,198,220,220,220,825,277,7,87,11,6045,2599,198,220,220,220,220,220,220,220,1441,1033,7,17,1635,2124,8,628,220,220,220,825,47764,7,87,11,6045,2599,198,220,220,220,220,220,220,220,1441,362,1635,1033,7,17,1635,2124,8,628,220,220,220,825,277,7568,7,87,11,6045,2599,198,220,220,220,220,220,220,220,616,69,220,796,220,277,7,87,11,6045,8,198,220,220,220,220,220,220,220,616,7568,796,47764,7,87,11,6045,8,198,220,220,220,220,220,220,220,1441,616,69,11,616,7568,628,198,220,220,220,284,617,1540,332,11,12598,308,6649,62,8818,62,69,7568,11,779,628,220,220,220,2163,796,308,6649,62,8818,62,69,7568,7,69,11,47764,11,277,7568,11,42287,8,198,220,220,220,37227,198,220,220,220,2315,20786,796,220,4808,47423,13,70,6649,62,8818,62,15003,62,69,7568,198,220,220,220,1479,20786,796,220,4808,47423,13,70,6649,62,8818,62,5787,62,69,7568,628,198,198,4871,308,6649,62,16680,7058,313,62,8818,28264,70,6649,62,8818,2599,198,220,220,220,37227,198,220,220,220,770,1398,15738,262,869,10146,329,308,6649,62,16680,7058,313,62,8818,13,628,220,220,220,1675,5127,262,2163,686,6248,7957,694,8160,262,2163,25,198,220,220,220,220,220,220,220,220,198,220,220,220,825,686,6248,7957,694,62,69,7,87,11,42287,2599,198,220,220,220,220,220,220,220,257,796,42287,58,15,60,198,220,220,220,220,220,220,220,275,796,42287,58,16,60,198,220,220,220,220,220,220,220,331,796,4866,13,30073,7,87,8,198,220,220,220,220,220,220,220,331,58,15,60,796,257,1635,357,16,532,2124,58,15,12962,198,220,220,220,220,220,220,220,331,58,16,60,796,275,1635,357,87,58,16,60,532,2124,58,15,60,1635,2124,58,15,12962,198,220,220,220,220,220,220,220,1441,331,628,220,220,220,25064,796,5021,19150,13,70,6649,62,16680,7058,313,62,8818,7,4951,268,7957,694,62,69,11,42287,11,362,8,198,220,220,220,37227,198,220,220,220,2315,20786,796,220,4808,47423,13,70,6649,62,16680,7058,313,62,8818,62,15003,198,220,220,220,1479,20786,796,220,4808,47423,13,70,6649,62,16680,7058,313,62,8818,62,5787,628,198,198,4871,308,6649,62,16680,7058,313,62,8818,62,69,7568,28264,70,6649,62,8818,62,69,7568,2599,198,220,220,220,37227,198,220,220,220,770,1398,15738,262,869,10146,329,308,6649,62,16680,7058,313,62,8818,13,198,220,220,220,220,198,220,220,220,1675,5127,262,2163,686,6248,7957,694,8160,262,5499,25,198,220,220,220,220,198,220,220,220,825,686,6248,7957,694,62,69,7,87,11,42287,2599,198,220,220,220,220,220,220,220,257,796,42287,58,15,60,198,220,220,220,220,220,220,220,275,796,42287,58,16,60,198,220,220,220,220,220,220,220,331,796,4866,13,30073,7,87,8,198,220,220,220,220,220,220,220,331,58,15,60,796,257,1635,357,16,532,2124,58,15,12962,198,220,220,220,220,220,220,220,331,58,16,60,796,275,1635,357,87,58,16,60,532,2124,58,15,60,1635,2124,58,15,12962,198,220,220,220,220,220,220,220,1441,331,198,220,220,220,220,198,220,220,220,825,686,6248,7957,694,62,7568,7,87,11,42287,2599,198,220,220,220,220,220,220,220,257,796,42287,58,15,60,198,220,220,220,220,220,220,220,275,796,42287,58,16,60,198,220,220,220,220,220,220,220,47764,796,399,39223,13,9107,418,19510,87,13,43358,58,15,4357,2124,13,43358,58,15,46570,399,39223,13,43879,8,198,220,220,220,220,220,220,220,47764,58,15,11,15,60,796,532,64,198,220,220,220,220,220,220,220,47764,58,15,11,16,60,796,657,198,220,220,220,220,220,220,220,47764,58,16,11,15,60,796,532,17,1635,275,1635,2124,58,15,60,198,220,220,220,220,220,220,220,47764,58,16,11,16,60,796,275,198,220,220,220,220,220,220,220,1441,47764,198,220,220,220,220,198,220,220,220,825,686,6248,7957,694,62,69,7568,7,87,11,42287,2599,198,220,220,220,220,220,220,220,277,796,686,6248,7957,694,62,69,7,87,11,42287,8,198,220,220,220,220,220,220,220,47764,796,686,6248,7957,694,62,7568,7,87,11,42287,8,198,220,220,220,220,220,220,220,1441,277,11,47764,628,220,220,220,1303,15793,286,2124,198,220,220,220,2546,796,362,198,220,220,220,25064,796,5021,19150,13,70,6649,62,16680,7058,313,62,8818,7,4951,268,7957,694,62,69,11,686,6248,7957,694,62,7568,11,198,220,220,220,220,220,220,220,220,220,220,220,220,220,220,220,220,220,220,220,220,220,220,220,220,220,220,220,220,220,220,220,220,220,220,220,220,220,220,220,220,220,220,220,686,6248,7957,694,62,69,7568,11,42287,11,2546,8,198,220,220,220,37227,198,220,220,220,2315,20786,796,220,4808,47423,13,70,6649,62,16680,7058,313,62,8818,62,15003,62,69,7568,198,220,220,220,1479,20786,796,220,4808,47423,13,70,6649,62,16680,7058,313,62,8818,62,5787,62,69,7568,628,198,4871,308,6649,62,16680,361,270,62,8818,28264,70,6649,62,8818,2599,198,220,220,220,37227,198,220,220,220,770,1398,15738,262,869,10146,329,308,6649,62,16680,320,259,62,8818,13,628,220,220,220,1675,4197,257,39682,2163,284,1366,3551,262,1708,2163,25,198,220,220,220,220,198,220,220,220,825,1033,62,69,7,87,11,42287,2599,198,220,220,220,220,220,220,220,317,796,2124,58,15,60,198,220,220,220,220,220,220,220,37456,62,796,2124,58,16,60,198,220,220,220,220,220,220,220,275,796,2124,58,17,60,198,220,220,220,220,220,220,220,256,28,42287,58,15,60,198,220,220,220,220,220,220,220,331,72,796,42287,58,16,60,198,220,220,220,220,220,220,220,264,13495,796,42287,58,17,60,198,220,220,220,220,220,220,220,26463,796,317,1635,1033,32590,50033,62,1635,256,8,1343,275,198,220,220,220,220,220,220,220,277,796,331,72,532,26463,1220,264,13495,198,220,220,220,220,220,220,220,1441,277,628,220,220,220,1303,7913,286,1366,8405,198,220,220,220,299,796,18896,7,7890,8,198,220,220,220,1303,7913,286,5772,1010,198,220,220,220,279,220,796,513,198,220,220,220,43543,270,62,77,2815,13,70,6649,62,16680,361,270,62,8818,7,11201,62,69,11,1366,11,299,11,279,8,198,220,220,220,37227,628,220,220,220,2315,20786,796,220,4808,47423,13,70,6649,62,16680,361,270,62,8818,62,15003,198,220,220,220,1479,20786,796,220,4808,47423,13,70,6649,62,16680,361,270,62,8818,62,5787,628,220,220,220,220,198,4871,308,6649,62,16680,361,270,62,8818,62,69,7568,28264,70,6649,62,8818,62,69,7568,2599,198,220,220,220,37227,198,220,220,220,770,1398,15738,262,869,10146,329,308,6649,62,16680,320,259,62,8818,13,198,220,220,220,825,1033,62,69,7,87,11,42287,2599,198,220,220,220,220,220,220,220,317,796,2124,58,15,60,198,220,220,220,220,220,220,220,37456,62,796,2124,58,16,60,198,220,220,220,220,220,220,220,275,796,2124,58,17,60,198,220,220,220,220,220,220,220,256,28,42287,58,15,60,198,220,220,220,220,220,220,220,331,72,796,42287,58,16,60,198,220,220,220,220,220,220,220,264,13495,796,42287,58,17,60,198,220,220,220,220,220,220,220,26463,796,317,1635,1033,32590,50033,62,1635,256,8,1343,275,198,220,220,220,220,220,220,220,277,796,331,72,532,26463,1220,264,13495,198,220,220,220,220,220,220,220,1441,277,628,220,220,220,825,1033,62,7568,7,87,11,42287,2599,198,220,220,220,220,220,220,220,317,796,2124,58,15,60,198,220,220,220,220,220,220,220,37456,62,796,2124,58,16,60,198,220,220,220,220,220,220,220,275,796,2124,58,17,60,198,220,220,220,220,220,220,220,256,28,42287,58,15,60,198,220,220,220,220,220,220,220,331,72,796,42287,58,16,60,198,220,220,220,220,220,220,220,264,13495,796,42287,58,17,60,198,220,220,220,220,220,220,220,304,796,1033,32590,50033,62,1635,256,8,198,220,220,220,220,220,220,220,304,62,82,796,304,14,82,13495,198,220,220,220,220,220,220,220,47764,796,399,39223,13,18747,19510,68,62,82,11,532,83,1635,317,1635,304,62,82,11,352,14,82,13495,4008,198,220,220,220,220,220,220,220,47764,796,399,39223,13,7645,3455,7,7568,8,198,220,220,220,220,220,220,220,3601,47764,13,43358,198,220,220,220,220,220,220,220,1441,47764,628,220,220,220,825,1033,62,69,7568,7,87,11,42287,2599,198,220,220,220,220,220,220,220,277,796,1033,62,69,7,87,11,42287,8,198,220,220,220,220,220,220,220,47764,796,1033,62,7568,7,87,11,42287,8,198,220,220,220,220,220,220,220,1441,277,11,47764,628,220,220,220,1303,7913,286,1366,8405,198,220,220,220,299,796,18896,7,7890,8,198,220,220,220,1303,7913,286,5772,1010,198,220,220,220,279,220,796,513,198,220,220,220,43543,270,62,77,2815,13,70,6649,62,16680,361,270,62,8818,62,69,7568,7,11201,62,69,11,1033,62,7568,11,1033,62,69,7568,11,1366,11,299,11,279,8,628,220,220,220,37227,198,220,220,220,2315,20786,796,220,4808,47423,13,70,6649,62,16680,361,270,62,8818,62,15003,62,69,7568,198,220,220,220,1479,20786,796,220,4808,47423,13,70,6649,62,16680,361,270,62,8818,62,5787,62,69,7568,198,198,4871,308,6649,62,16680,320,259,62,8818,7,70,6649,62,16680,7058,313,62,8818,2599,220,220,220,220,198,220,220,220,37227,198,220,220,220,770,1398,15738,262,869,10146,329,308,6649,62,16680,320,259,62,8818,13,628,220,220,220,383,1708,1672,2163,15738,257,2829,1582,28426,1868,351,734,198,220,220,220,10007,13,628,220,220,220,1675,5127,220,262,1080,8160,262,2163,25,198,220,220,220,825,616,62,69,7,85,11,42287,2599,198,220,220,220,220,220,220,220,2124,796,410,58,15,60,198,220,220,220,220,220,220,220,331,796,410,58,16,60,198,220,220,220,220,198,220,220,220,220,220,220,220,288,79,796,42287,198,220,220,220,220,220,220,220,256,16,220,796,357,87,532,288,79,58,15,12962,198,220,220,220,220,220,220,220,256,17,220,796,357,88,532,288,79,58,16,12962,198,220,220,220,220,220,220,220,277,796,838,13,15,1635,256,16,1635,256,16,1343,1160,13,15,1635,256,17,1635,256,17,1343,1542,13,15,198,220,220,220,220,220,220,220,1441,277,220,198,220,220,220,220,198,220,220,220,1303,15793,286,2124,198,220,220,220,2546,796,362,628,220,220,220,25064,796,43104,259,13,70,6649,62,16680,361,270,62,8818,7,1820,62,69,11,42287,11,362,8,198,220,220,220,37227,628,220,220,220,2315,20786,796,220,4808,47423,13,70,6649,62,16680,320,259,62,8818,62,15003,198,220,220,220,1479,20786,796,220,4808,47423,13,70,6649,62,16680,320,259,62,8818,62,5787,198,198,4871,308,6649,62,16680,320,259,62,8818,62,69,7568,7,70,6649,62,16680,7058,313,62,8818,62,69,7568,2599,198,220,220,220,37227,198,220,220,220,770,1398,15738,262,869,10146,329,308,6649,62,16680,320,259,62,8818,62,69,7568,13,628,220,220,220,383,1708,1672,2163,15738,257,2829,1582,28426,1868,351,734,198,220,220,220,10007,13,628,220,220,220,1675,5127,220,262,1080,8160,262,2163,25,198,220,220,220,825,616,62,69,7,85,11,42287,2599,198,220,220,220,220,220,220,220,2124,796,410,58,15,60,198,220,220,220,220,220,220,220,331,796,410,58,16,60,198,220,220,220,220,198,220,220,220,220,220,220,220,288,79,796,42287,198,220,220,220,220,220,220,220,256,16,220,796,357,87,532,288,79,58,15,12962,198,220,220,220,220,220,220,220,256,17,220,796,357,88,532,288,79,58,16,12962,198,220,220,220,220,220,220,220,277,796,838,13,15,1635,256,16,1635,256,16,1343,1160,13,15,1635,256,17,1635,256,17,1343,1542,13,15,198,220,220,220,220,220,220,220,1441,277,198,220,220,220,825,616,62,7568,7,85,11,42287,2599,198,220,220,220,220,220,220,220,2124,796,410,58,15,60,198,220,220,220,220,220,220,220,331,796,410,58,16,60,198,220,220,220,220,220,220,220,47764,796,399,39223,13,9107,418,7,85,13,43358,11,399,39223,13,43879,8,198,220,220,220,220,220,220,220,288,79,796,42287,198,220,220,220,220,220,220,220,47764,58,15,60,796,1160,13,1635,357,87,532,288,79,58,15,12962,198,220,220,220,220,220,220,220,47764,58,16,60,796,2319,13,1635,357,88,532,288,79,58,16,12962,198,220,220,220,220,220,220,220,1441,47764,628,220,220,220,825,616,62,69,7568,7,85,11,42287,2599,198,220,220,220,220,220,220,220,277,796,616,62,69,7,85,11,42287,8,198,220,220,220,220,220,220,220,47764,796,616,62,7568,7,85,11,37266,8,198,220,220,220,220,220,220,220,1441,277,11,47764,628,220,220,220,220,198,220,220,220,1303,15793,286,2124,198,220,220,220,2546,796,362,198,220,220,220,25064,796,43104,259,13,70,6649,62,16680,361,270,62,8818,7,1820,62,69,11,616,62,7568,11,616,62,69,7568,11,42287,11,2546,8,198,220,220,220,37227,628,220,220,220,2315,20786,796,220,4808,47423,13,70,6649,62,16680,320,259,62,8818,62,15003,62,69,7568,198,220,220,220,1479,20786,796,220,4808,47423,13,70,6649,62,16680,320,259,62,8818,62,5787,62,69,7568,198,198,4871,308,6649,62,2144,660,62,8818,7,70,6649,62,16680,7058,313,62,8818,2599,220,220,220,220,198,220,220,220,37227,198,220,220,220,770,1398,15738,262,869,10146,329,308,6649,62,2144,660,62,8818,13,628,220,220,220,37227,628,220,220,220,2315,20786,796,220,4808,47423,13,70,6649,62,2144,660,62,8818,62,15003,198,220,220,220,1479,20786,796,220,4808,47423,13,70,6649,62,2144,660,62,8818,62,5787,198],"string":"[\n 2,\n 48443,\n 14629,\n 14,\n 8800,\n 14,\n 24330,\n 21015,\n 198,\n 2,\n 6434,\n 1058,\n 21204,\n 45606,\n 7509,\n 220,\n 198,\n 37811,\n 198,\n 36307,\n 286,\n 4889,\n 10146,\n 3341,\n 329,\n 220,\n 12972,\n 70,\n 6649,\n 13,\n 1119,\n 1061,\n 262,\n 46326,\n 17336,\n 355,\n 198,\n 19836,\n 355,\n 1744,\n 13,\n 5455,\n 28686,\n 257,\n 2878,\n 21015,\n 6097,\n 389,\n 973,\n 13,\n 198,\n 198,\n 3237,\n 1540,\n 690,\n 2453,\n 257,\n 327,\n 7951,\n 17562,\n 11,\n 543,\n 318,\n 3804,\n 284,\n 262,\n 23838,\n 13,\n 554,\n 9485,\n 70,\n 6649,\n 198,\n 5661,\n 318,\n 281,\n 450,\n 270,\n 11619,\n 21015,\n 2134,\n 13,\n 220,\n 4091,\n 262,\n 2205,\n 13042,\n 286,\n 262,\n 2972,\n 6097,\n 198,\n 1640,\n 2252,\n 3703,\n 13,\n 198,\n 198,\n 37811,\n 198,\n 6738,\n 764,\n 1330,\n 4808,\n 47423,\n 628,\n 198,\n 4871,\n 308,\n 6649,\n 62,\n 8818,\n 28264,\n 70,\n 6649,\n 62,\n 8818,\n 2599,\n 198,\n 220,\n 220,\n 220,\n 37227,\n 198,\n 220,\n 220,\n 220,\n 770,\n 1398,\n 15738,\n 262,\n 869,\n 10146,\n 1900,\n 355,\n 308,\n 6649,\n 62,\n 8818,\n 284,\n 198,\n 220,\n 220,\n 220,\n 308,\n 6649,\n 13,\n 628,\n 220,\n 220,\n 220,\n 304,\n 13,\n 70,\n 284,\n 5127,\n 262,\n 2163,\n 277,\n 25,\n 198,\n 220,\n 220,\n 220,\n 220,\n 198,\n 220,\n 220,\n 220,\n 825,\n 277,\n 7,\n 87,\n 11,\n 42287,\n 2599,\n 198,\n 220,\n 220,\n 220,\n 220,\n 220,\n 220,\n 220,\n 257,\n 796,\n 42287,\n 58,\n 15,\n 60,\n 198,\n 220,\n 220,\n 220,\n 220,\n 220,\n 220,\n 220,\n 275,\n 796,\n 1582,\n 5356,\n 58,\n 16,\n 60,\n 198,\n 220,\n 220,\n 220,\n 220,\n 220,\n 220,\n 220,\n 269,\n 796,\n 42287,\n 58,\n 18,\n 60,\n 198,\n 220,\n 220,\n 220,\n 220,\n 220,\n 220,\n 220,\n 1441,\n 257,\n 1635,\n 2124,\n 12429,\n 362,\n 1343,\n 275,\n 1635,\n 2124,\n 1343,\n 269,\n 628,\n 220,\n 220,\n 220,\n 284,\n 617,\n 1540,\n 332,\n 11,\n 779,\n 628,\n 220,\n 220,\n 220,\n 2163,\n 796,\n 308,\n 6649,\n 62,\n 8818,\n 7,\n 69,\n 11,\n 42287,\n 8,\n 198,\n 220,\n 220,\n 220,\n 37227,\n 628,\n 220,\n 220,\n 220,\n 2315,\n 20786,\n 796,\n 220,\n 4808,\n 47423,\n 13,\n 70,\n 6649,\n 62,\n 8818,\n 62,\n 15003,\n 198,\n 220,\n 220,\n 220,\n 1479,\n 20786,\n 796,\n 220,\n 4808,\n 47423,\n 13,\n 70,\n 6649,\n 62,\n 8818,\n 62,\n 5787,\n 198,\n 220,\n 220,\n 220,\n 220,\n 198,\n 4871,\n 308,\n 6649,\n 62,\n 8818,\n 62,\n 69,\n 7568,\n 28264,\n 70,\n 6649,\n 62,\n 8818,\n 62,\n 69,\n 7568,\n 2599,\n 198,\n 220,\n 220,\n 220,\n 37227,\n 198,\n 220,\n 220,\n 220,\n 770,\n 1398,\n 15738,\n 262,\n 869,\n 10146,\n 1900,\n 355,\n 308,\n 6649,\n 62,\n 8818,\n 62,\n 69,\n 7568,\n 284,\n 198,\n 220,\n 220,\n 220,\n 308,\n 6649,\n 13,\n 628,\n 220,\n 220,\n 220,\n 304,\n 13,\n 70,\n 284,\n 5127,\n 262,\n 2163,\n 277,\n 25,\n 198,\n 220,\n 220,\n 220,\n 220,\n 198,\n 220,\n 220,\n 220,\n 825,\n 277,\n 7,\n 87,\n 11,\n 6045,\n 2599,\n 198,\n 220,\n 220,\n 220,\n 220,\n 220,\n 220,\n 220,\n 1441,\n 1033,\n 7,\n 17,\n 1635,\n 2124,\n 8,\n 628,\n 220,\n 220,\n 220,\n 825,\n 47764,\n 7,\n 87,\n 11,\n 6045,\n 2599,\n 198,\n 220,\n 220,\n 220,\n 220,\n 220,\n 220,\n 220,\n 1441,\n 362,\n 1635,\n 1033,\n 7,\n 17,\n 1635,\n 2124,\n 8,\n 628,\n 220,\n 220,\n 220,\n 825,\n 277,\n 7568,\n 7,\n 87,\n 11,\n 6045,\n 2599,\n 198,\n 220,\n 220,\n 220,\n 220,\n 220,\n 220,\n 220,\n 616,\n 69,\n 220,\n 796,\n 220,\n 277,\n 7,\n 87,\n 11,\n 6045,\n 8,\n 198,\n 220,\n 220,\n 220,\n 220,\n 220,\n 220,\n 220,\n 616,\n 7568,\n 796,\n 47764,\n 7,\n 87,\n 11,\n 6045,\n 8,\n 198,\n 220,\n 220,\n 220,\n 220,\n 220,\n 220,\n 220,\n 1441,\n 616,\n 69,\n 11,\n 616,\n 7568,\n 628,\n 198,\n 220,\n 220,\n 220,\n 284,\n 617,\n 1540,\n 332,\n 11,\n 12598,\n 308,\n 6649,\n 62,\n 8818,\n 62,\n 69,\n 7568,\n 11,\n 779,\n 628,\n 220,\n 220,\n 220,\n 2163,\n 796,\n 308,\n 6649,\n 62,\n 8818,\n 62,\n 69,\n 7568,\n 7,\n 69,\n 11,\n 47764,\n 11,\n 277,\n 7568,\n 11,\n 42287,\n 8,\n 198,\n 220,\n 220,\n 220,\n 37227,\n 198,\n 220,\n 220,\n 220,\n 2315,\n 20786,\n 796,\n 220,\n 4808,\n 47423,\n 13,\n 70,\n 6649,\n 62,\n 8818,\n 62,\n 15003,\n 62,\n 69,\n 7568,\n 198,\n 220,\n 220,\n 220,\n 1479,\n 20786,\n 796,\n 220,\n 4808,\n 47423,\n 13,\n 70,\n 6649,\n 62,\n 8818,\n 62,\n 5787,\n 62,\n 69,\n 7568,\n 628,\n 198,\n 198,\n 4871,\n 308,\n 6649,\n 62,\n 16680,\n 7058,\n 313,\n 62,\n 8818,\n 28264,\n 70,\n 6649,\n 62,\n 8818,\n 2599,\n 198,\n 220,\n 220,\n 220,\n 37227,\n 198,\n 220,\n 220,\n 220,\n 770,\n 1398,\n 15738,\n 262,\n 869,\n 10146,\n 329,\n 308,\n 6649,\n 62,\n 16680,\n 7058,\n 313,\n 62,\n 8818,\n 13,\n 628,\n 220,\n 220,\n 220,\n 1675,\n 5127,\n 262,\n 2163,\n 686,\n 6248,\n 7957,\n 694,\n 8160,\n 262,\n 2163,\n 25,\n 198,\n 220,\n 220,\n 220,\n 220,\n 220,\n 220,\n 220,\n 220,\n 198,\n 220,\n 220,\n 220,\n 825,\n 686,\n 6248,\n 7957,\n 694,\n 62,\n 69,\n 7,\n 87,\n 11,\n 42287,\n 2599,\n 198,\n 220,\n 220,\n 220,\n 220,\n 220,\n 220,\n 220,\n 257,\n 796,\n 42287,\n 58,\n 15,\n 60,\n 198,\n 220,\n 220,\n 220,\n 220,\n 220,\n 220,\n 220,\n 275,\n 796,\n 42287,\n 58,\n 16,\n 60,\n 198,\n 220,\n 220,\n 220,\n 220,\n 220,\n 220,\n 220,\n 331,\n 796,\n 4866,\n 13,\n 30073,\n 7,\n 87,\n 8,\n 198,\n 220,\n 220,\n 220,\n 220,\n 220,\n 220,\n 220,\n 331,\n 58,\n 15,\n 60,\n 796,\n 257,\n 1635,\n 357,\n 16,\n 532,\n 2124,\n 58,\n 15,\n 12962,\n 198,\n 220,\n 220,\n 220,\n 220,\n 220,\n 220,\n 220,\n 331,\n 58,\n 16,\n 60,\n 796,\n 275,\n 1635,\n 357,\n 87,\n 58,\n 16,\n 60,\n 532,\n 2124,\n 58,\n 15,\n 60,\n 1635,\n 2124,\n 58,\n 15,\n 12962,\n 198,\n 220,\n 220,\n 220,\n 220,\n 220,\n 220,\n 220,\n 1441,\n 331,\n 628,\n 220,\n 220,\n 220,\n 25064,\n 796,\n 5021,\n 19150,\n 13,\n 70,\n 6649,\n 62,\n 16680,\n 7058,\n 313,\n 62,\n 8818,\n 7,\n 4951,\n 268,\n 7957,\n 694,\n 62,\n 69,\n 11,\n 42287,\n 11,\n 362,\n 8,\n 198,\n 220,\n 220,\n 220,\n 37227,\n 198,\n 220,\n 220,\n 220,\n 2315,\n 20786,\n 796,\n 220,\n 4808,\n 47423,\n 13,\n 70,\n 6649,\n 62,\n 16680,\n 7058,\n 313,\n 62,\n 8818,\n 62,\n 15003,\n 198,\n 220,\n 220,\n 220,\n 1479,\n 20786,\n 796,\n 220,\n 4808,\n 47423,\n 13,\n 70,\n 6649,\n 62,\n 16680,\n 7058,\n 313,\n 62,\n 8818,\n 62,\n 5787,\n 628,\n 198,\n 198,\n 4871,\n 308,\n 6649,\n 62,\n 16680,\n 7058,\n 313,\n 62,\n 8818,\n 62,\n 69,\n 7568,\n 28264,\n 70,\n 6649,\n 62,\n 8818,\n 62,\n 69,\n 7568,\n 2599,\n 198,\n 220,\n 220,\n 220,\n 37227,\n 198,\n 220,\n 220,\n 220,\n 770,\n 1398,\n 15738,\n 262,\n 869,\n 10146,\n 329,\n 308,\n 6649,\n 62,\n 16680,\n 7058,\n 313,\n 62,\n 8818,\n 13,\n 198,\n 220,\n 220,\n 220,\n 220,\n 198,\n 220,\n 220,\n 220,\n 1675,\n 5127,\n 262,\n 2163,\n 686,\n 6248,\n 7957,\n 694,\n 8160,\n 262,\n 5499,\n 25,\n 198,\n 220,\n 220,\n 220,\n 220,\n 198,\n 220,\n 220,\n 220,\n 825,\n 686,\n 6248,\n 7957,\n 694,\n 62,\n 69,\n 7,\n 87,\n 11,\n 42287,\n 2599,\n 198,\n 220,\n 220,\n 220,\n 220,\n 220,\n 220,\n 220,\n 257,\n 796,\n 42287,\n 58,\n 15,\n 60,\n 198,\n 220,\n 220,\n 220,\n 220,\n 220,\n 220,\n 220,\n 275,\n 796,\n 42287,\n 58,\n 16,\n 60,\n 198,\n 220,\n 220,\n 220,\n 220,\n 220,\n 220,\n 220,\n 331,\n 796,\n 4866,\n 13,\n 30073,\n 7,\n 87,\n 8,\n 198,\n 220,\n 220,\n 220,\n 220,\n 220,\n 220,\n 220,\n 331,\n 58,\n 15,\n 60,\n 796,\n 257,\n 1635,\n 357,\n 16,\n 532,\n 2124,\n 58,\n 15,\n 12962,\n 198,\n 220,\n 220,\n 220,\n 220,\n 220,\n 220,\n 220,\n 331,\n 58,\n 16,\n 60,\n 796,\n 275,\n 1635,\n 357,\n 87,\n 58,\n 16,\n 60,\n 532,\n 2124,\n 58,\n 15,\n 60,\n 1635,\n 2124,\n 58,\n 15,\n 12962,\n 198,\n 220,\n 220,\n 220,\n 220,\n 220,\n 220,\n 220,\n 1441,\n 331,\n 198,\n 220,\n 220,\n 220,\n 220,\n 198,\n 220,\n 220,\n 220,\n 825,\n 686,\n 6248,\n 7957,\n 694,\n 62,\n 7568,\n 7,\n 87,\n 11,\n 42287,\n 2599,\n 198,\n 220,\n 220,\n 220,\n 220,\n 220,\n 220,\n 220,\n 257,\n 796,\n 42287,\n 58,\n 15,\n 60,\n 198,\n 220,\n 220,\n 220,\n 220,\n 220,\n 220,\n 220,\n 275,\n 796,\n 42287,\n 58,\n 16,\n 60,\n 198,\n 220,\n 220,\n 220,\n 220,\n 220,\n 220,\n 220,\n 47764,\n 796,\n 399,\n 39223,\n 13,\n 9107,\n 418,\n 19510,\n 87,\n 13,\n 43358,\n 58,\n 15,\n 4357,\n 2124,\n 13,\n 43358,\n 58,\n 15,\n 46570,\n 399,\n 39223,\n 13,\n 43879,\n 8,\n 198,\n 220,\n 220,\n 220,\n 220,\n 220,\n 220,\n 220,\n 47764,\n 58,\n 15,\n 11,\n 15,\n 60,\n 796,\n 532,\n 64,\n 198,\n 220,\n 220,\n 220,\n 220,\n 220,\n 220,\n 220,\n 47764,\n 58,\n 15,\n 11,\n 16,\n 60,\n 796,\n 657,\n 198,\n 220,\n 220,\n 220,\n 220,\n 220,\n 220,\n 220,\n 47764,\n 58,\n 16,\n 11,\n 15,\n 60,\n 796,\n 532,\n 17,\n 1635,\n 275,\n 1635,\n 2124,\n 58,\n 15,\n 60,\n 198,\n 220,\n 220,\n 220,\n 220,\n 220,\n 220,\n 220,\n 47764,\n 58,\n 16,\n 11,\n 16,\n 60,\n 796,\n 275,\n 198,\n 220,\n 220,\n 220,\n 220,\n 220,\n 220,\n 220,\n 1441,\n 47764,\n 198,\n 220,\n 220,\n 220,\n 220,\n 198,\n 220,\n 220,\n 220,\n 825,\n 686,\n 6248,\n 7957,\n 694,\n 62,\n 69,\n 7568,\n 7,\n 87,\n 11,\n 42287,\n 2599,\n 198,\n 220,\n 220,\n 220,\n 220,\n 220,\n 220,\n 220,\n 277,\n 796,\n 686,\n 6248,\n 7957,\n 694,\n 62,\n 69,\n 7,\n 87,\n 11,\n 42287,\n 8,\n 198,\n 220,\n 220,\n 220,\n 220,\n 220,\n 220,\n 220,\n 47764,\n 796,\n 686,\n 6248,\n 7957,\n 694,\n 62,\n 7568,\n 7,\n 87,\n 11,\n 42287,\n 8,\n 198,\n 220,\n 220,\n 220,\n 220,\n 220,\n 220,\n 220,\n 1441,\n 277,\n 11,\n 47764,\n 628,\n 220,\n 220,\n 220,\n 1303,\n 15793,\n 286,\n 2124,\n 198,\n 220,\n 220,\n 220,\n 2546,\n 796,\n 362,\n 198,\n 220,\n 220,\n 220,\n 25064,\n 796,\n 5021,\n 19150,\n 13,\n 70,\n 6649,\n 62,\n 16680,\n 7058,\n 313,\n 62,\n 8818,\n 7,\n 4951,\n 268,\n 7957,\n 694,\n 62,\n 69,\n 11,\n 686,\n 6248,\n 7957,\n 694,\n 62,\n 7568,\n 11,\n 198,\n 220,\n 220,\n 220,\n 220,\n 220,\n 220,\n 220,\n 220,\n 220,\n 220,\n 220,\n 220,\n 220,\n 220,\n 220,\n 220,\n 220,\n 220,\n 220,\n 220,\n 220,\n 220,\n 220,\n 220,\n 220,\n 220,\n 220,\n 220,\n 220,\n 220,\n 220,\n 220,\n 220,\n 220,\n 220,\n 220,\n 220,\n 220,\n 220,\n 220,\n 220,\n 220,\n 220,\n 686,\n 6248,\n 7957,\n 694,\n 62,\n 69,\n 7568,\n 11,\n 42287,\n 11,\n 2546,\n 8,\n 198,\n 220,\n 220,\n 220,\n 37227,\n 198,\n 220,\n 220,\n 220,\n 2315,\n 20786,\n 796,\n 220,\n 4808,\n 47423,\n 13,\n 70,\n 6649,\n 62,\n 16680,\n 7058,\n 313,\n 62,\n 8818,\n 62,\n 15003,\n 62,\n 69,\n 7568,\n 198,\n 220,\n 220,\n 220,\n 1479,\n 20786,\n 796,\n 220,\n 4808,\n 47423,\n 13,\n 70,\n 6649,\n 62,\n 16680,\n 7058,\n 313,\n 62,\n 8818,\n 62,\n 5787,\n 62,\n 69,\n 7568,\n 628,\n 198,\n 4871,\n 308,\n 6649,\n 62,\n 16680,\n 361,\n 270,\n 62,\n 8818,\n 28264,\n 70,\n 6649,\n 62,\n 8818,\n 2599,\n 198,\n 220,\n 220,\n 220,\n 37227,\n 198,\n 220,\n 220,\n 220,\n 770,\n 1398,\n 15738,\n 262,\n 869,\n 10146,\n 329,\n 308,\n 6649,\n 62,\n 16680,\n 320,\n 259,\n 62,\n 8818,\n 13,\n 628,\n 220,\n 220,\n 220,\n 1675,\n 4197,\n 257,\n 39682,\n 2163,\n 284,\n 1366,\n 3551,\n 262,\n 1708,\n 2163,\n 25,\n 198,\n 220,\n 220,\n 220,\n 220,\n 198,\n 220,\n 220,\n 220,\n 825,\n 1033,\n 62,\n 69,\n 7,\n 87,\n 11,\n 42287,\n 2599,\n 198,\n 220,\n 220,\n 220,\n 220,\n 220,\n 220,\n 220,\n 317,\n 796,\n 2124,\n 58,\n 15,\n 60,\n 198,\n 220,\n 220,\n 220,\n 220,\n 220,\n 220,\n 220,\n 37456,\n 62,\n 796,\n 2124,\n 58,\n 16,\n 60,\n 198,\n 220,\n 220,\n 220,\n 220,\n 220,\n 220,\n 220,\n 275,\n 796,\n 2124,\n 58,\n 17,\n 60,\n 198,\n 220,\n 220,\n 220,\n 220,\n 220,\n 220,\n 220,\n 256,\n 28,\n 42287,\n 58,\n 15,\n 60,\n 198,\n 220,\n 220,\n 220,\n 220,\n 220,\n 220,\n 220,\n 331,\n 72,\n 796,\n 42287,\n 58,\n 16,\n 60,\n 198,\n 220,\n 220,\n 220,\n 220,\n 220,\n 220,\n 220,\n 264,\n 13495,\n 796,\n 42287,\n 58,\n 17,\n 60,\n 198,\n 220,\n 220,\n 220,\n 220,\n 220,\n 220,\n 220,\n 26463,\n 796,\n 317,\n 1635,\n 1033,\n 32590,\n 50033,\n 62,\n 1635,\n 256,\n 8,\n 1343,\n 275,\n 198,\n 220,\n 220,\n 220,\n 220,\n 220,\n 220,\n 220,\n 277,\n 796,\n 331,\n 72,\n 532,\n 26463,\n 1220,\n 264,\n 13495,\n 198,\n 220,\n 220,\n 220,\n 220,\n 220,\n 220,\n 220,\n 1441,\n 277,\n 628,\n 220,\n 220,\n 220,\n 1303,\n 7913,\n 286,\n 1366,\n 8405,\n 198,\n 220,\n 220,\n 220,\n 299,\n 796,\n 18896,\n 7,\n 7890,\n 8,\n 198,\n 220,\n 220,\n 220,\n 1303,\n 7913,\n 286,\n 5772,\n 1010,\n 198,\n 220,\n 220,\n 220,\n 279,\n 220,\n 796,\n 513,\n 198,\n 220,\n 220,\n 220,\n 43543,\n 270,\n 62,\n 77,\n 2815,\n 13,\n 70,\n 6649,\n 62,\n 16680,\n 361,\n 270,\n 62,\n 8818,\n 7,\n 11201,\n 62,\n 69,\n 11,\n 1366,\n 11,\n 299,\n 11,\n 279,\n 8,\n 198,\n 220,\n 220,\n 220,\n 37227,\n 628,\n 220,\n 220,\n 220,\n 2315,\n 20786,\n 796,\n 220,\n 4808,\n 47423,\n 13,\n 70,\n 6649,\n 62,\n 16680,\n 361,\n 270,\n 62,\n 8818,\n 62,\n 15003,\n 198,\n 220,\n 220,\n 220,\n 1479,\n 20786,\n 796,\n 220,\n 4808,\n 47423,\n 13,\n 70,\n 6649,\n 62,\n 16680,\n 361,\n 270,\n 62,\n 8818,\n 62,\n 5787,\n 628,\n 220,\n 220,\n 220,\n 220,\n 198,\n 4871,\n 308,\n 6649,\n 62,\n 16680,\n 361,\n 270,\n 62,\n 8818,\n 62,\n 69,\n 7568,\n 28264,\n 70,\n 6649,\n 62,\n 8818,\n 62,\n 69,\n 7568,\n 2599,\n 198,\n 220,\n 220,\n 220,\n 37227,\n 198,\n 220,\n 220,\n 220,\n 770,\n 1398,\n 15738,\n 262,\n 869,\n 10146,\n 329,\n 308,\n 6649,\n 62,\n 16680,\n 320,\n 259,\n 62,\n 8818,\n 13,\n 198,\n 220,\n 220,\n 220,\n 825,\n 1033,\n 62,\n 69,\n 7,\n 87,\n 11,\n 42287,\n 2599,\n 198,\n 220,\n 220,\n 220,\n 220,\n 220,\n 220,\n 220,\n 317,\n 796,\n 2124,\n 58,\n 15,\n 60,\n 198,\n 220,\n 220,\n 220,\n 220,\n 220,\n 220,\n 220,\n 37456,\n 62,\n 796,\n 2124,\n 58,\n 16,\n 60,\n 198,\n 220,\n 220,\n 220,\n 220,\n 220,\n 220,\n 220,\n 275,\n 796,\n 2124,\n 58,\n 17,\n 60,\n 198,\n 220,\n 220,\n 220,\n 220,\n 220,\n 220,\n 220,\n 256,\n 28,\n 42287,\n 58,\n 15,\n 60,\n 198,\n 220,\n 220,\n 220,\n 220,\n 220,\n 220,\n 220,\n 331,\n 72,\n 796,\n 42287,\n 58,\n 16,\n 60,\n 198,\n 220,\n 220,\n 220,\n 220,\n 220,\n 220,\n 220,\n 264,\n 13495,\n 796,\n 42287,\n 58,\n 17,\n 60,\n 198,\n 220,\n 220,\n 220,\n 220,\n 220,\n 220,\n 220,\n 26463,\n 796,\n 317,\n 1635,\n 1033,\n 32590,\n 50033,\n 62,\n 1635,\n 256,\n 8,\n 1343,\n 275,\n 198,\n 220,\n 220,\n 220,\n 220,\n 220,\n 220,\n 220,\n 277,\n 796,\n 331,\n 72,\n 532,\n 26463,\n 1220,\n 264,\n 13495,\n 198,\n 220,\n 220,\n 220,\n 220,\n 220,\n 220,\n 220,\n 1441,\n 277,\n 628,\n 220,\n 220,\n 220,\n 825,\n 1033,\n 62,\n 7568,\n 7,\n 87,\n 11,\n 42287,\n 2599,\n 198,\n 220,\n 220,\n 220,\n 220,\n 220,\n 220,\n 220,\n 317,\n 796,\n 2124,\n 58,\n 15,\n 60,\n 198,\n 220,\n 220,\n 220,\n 220,\n 220,\n 220,\n 220,\n 37456,\n 62,\n 796,\n 2124,\n 58,\n 16,\n 60,\n 198,\n 220,\n 220,\n 220,\n 220,\n 220,\n 220,\n 220,\n 275,\n 796,\n 2124,\n 58,\n 17,\n 60,\n 198,\n 220,\n 220,\n 220,\n 220,\n 220,\n 220,\n 220,\n 256,\n 28,\n 42287,\n 58,\n 15,\n 60,\n 198,\n 220,\n 220,\n 220,\n 220,\n 220,\n 220,\n 220,\n 331,\n 72,\n 796,\n 42287,\n 58,\n 16,\n 60,\n 198,\n 220,\n 220,\n 220,\n 220,\n 220,\n 220,\n 220,\n 264,\n 13495,\n 796,\n 42287,\n 58,\n 17,\n 60,\n 198,\n 220,\n 220,\n 220,\n 220,\n 220,\n 220,\n 220,\n 304,\n 796,\n 1033,\n 32590,\n 50033,\n 62,\n 1635,\n 256,\n 8,\n 198,\n 220,\n 220,\n 220,\n 220,\n 220,\n 220,\n 220,\n 304,\n 62,\n 82,\n 796,\n 304,\n 14,\n 82,\n 13495,\n 198,\n 220,\n 220,\n 220,\n 220,\n 220,\n 220,\n 220,\n 47764,\n 796,\n 399,\n 39223,\n 13,\n 18747,\n 19510,\n 68,\n 62,\n 82,\n 11,\n 532,\n 83,\n 1635,\n 317,\n 1635,\n 304,\n 62,\n 82,\n 11,\n 352,\n 14,\n 82,\n 13495,\n 4008,\n 198,\n 220,\n 220,\n 220,\n 220,\n 220,\n 220,\n 220,\n 47764,\n 796,\n 399,\n 39223,\n 13,\n 7645,\n 3455,\n 7,\n 7568,\n 8,\n 198,\n 220,\n 220,\n 220,\n 220,\n 220,\n 220,\n 220,\n 3601,\n 47764,\n 13,\n 43358,\n 198,\n 220,\n 220,\n 220,\n 220,\n 220,\n 220,\n 220,\n 1441,\n 47764,\n 628,\n 220,\n 220,\n 220,\n 825,\n 1033,\n 62,\n 69,\n 7568,\n 7,\n 87,\n 11,\n 42287,\n 2599,\n 198,\n 220,\n 220,\n 220,\n 220,\n 220,\n 220,\n 220,\n 277,\n 796,\n 1033,\n 62,\n 69,\n 7,\n 87,\n 11,\n 42287,\n 8,\n 198,\n 220,\n 220,\n 220,\n 220,\n 220,\n 220,\n 220,\n 47764,\n 796,\n 1033,\n 62,\n 7568,\n 7,\n 87,\n 11,\n 42287,\n 8,\n 198,\n 220,\n 220,\n 220,\n 220,\n 220,\n 220,\n 220,\n 1441,\n 277,\n 11,\n 47764,\n 628,\n 220,\n 220,\n 220,\n 1303,\n 7913,\n 286,\n 1366,\n 8405,\n 198,\n 220,\n 220,\n 220,\n 299,\n 796,\n 18896,\n 7,\n 7890,\n 8,\n 198,\n 220,\n 220,\n 220,\n 1303,\n 7913,\n 286,\n 5772,\n 1010,\n 198,\n 220,\n 220,\n 220,\n 279,\n 220,\n 796,\n 513,\n 198,\n 220,\n 220,\n 220,\n 43543,\n 270,\n 62,\n 77,\n 2815,\n 13,\n 70,\n 6649,\n 62,\n 16680,\n 361,\n 270,\n 62,\n 8818,\n 62,\n 69,\n 7568,\n 7,\n 11201,\n 62,\n 69,\n 11,\n 1033,\n 62,\n 7568,\n 11,\n 1033,\n 62,\n 69,\n 7568,\n 11,\n 1366,\n 11,\n 299,\n 11,\n 279,\n 8,\n 628,\n 220,\n 220,\n 220,\n 37227,\n 198,\n 220,\n 220,\n 220,\n 2315,\n 20786,\n 796,\n 220,\n 4808,\n 47423,\n 13,\n 70,\n 6649,\n 62,\n 16680,\n 361,\n 270,\n 62,\n 8818,\n 62,\n 15003,\n 62,\n 69,\n 7568,\n 198,\n 220,\n 220,\n 220,\n 1479,\n 20786,\n 796,\n 220,\n 4808,\n 47423,\n 13,\n 70,\n 6649,\n 62,\n 16680,\n 361,\n 270,\n 62,\n 8818,\n 62,\n 5787,\n 62,\n 69,\n 7568,\n 198,\n 198,\n 4871,\n 308,\n 6649,\n 62,\n 16680,\n 320,\n 259,\n 62,\n 8818,\n 7,\n 70,\n 6649,\n 62,\n 16680,\n 7058,\n 313,\n 62,\n 8818,\n 2599,\n 220,\n 220,\n 220,\n 220,\n 198,\n 220,\n 220,\n 220,\n 37227,\n 198,\n 220,\n 220,\n 220,\n 770,\n 1398,\n 15738,\n 262,\n 869,\n 10146,\n 329,\n 308,\n 6649,\n 62,\n 16680,\n 320,\n 259,\n 62,\n 8818,\n 13,\n 628,\n 220,\n 220,\n 220,\n 383,\n 1708,\n 1672,\n 2163,\n 15738,\n 257,\n 2829,\n 1582,\n 28426,\n 1868,\n 351,\n 734,\n 198,\n 220,\n 220,\n 220,\n 10007,\n 13,\n 628,\n 220,\n 220,\n 220,\n 1675,\n 5127,\n 220,\n 262,\n 1080,\n 8160,\n 262,\n 2163,\n 25,\n 198,\n 220,\n 220,\n 220,\n 825,\n 616,\n 62,\n 69,\n 7,\n 85,\n 11,\n 42287,\n 2599,\n 198,\n 220,\n 220,\n 220,\n 220,\n 220,\n 220,\n 220,\n 2124,\n 796,\n 410,\n 58,\n 15,\n 60,\n 198,\n 220,\n 220,\n 220,\n 220,\n 220,\n 220,\n 220,\n 331,\n 796,\n 410,\n 58,\n 16,\n 60,\n 198,\n 220,\n 220,\n 220,\n 220,\n 198,\n 220,\n 220,\n 220,\n 220,\n 220,\n 220,\n 220,\n 288,\n 79,\n 796,\n 42287,\n 198,\n 220,\n 220,\n 220,\n 220,\n 220,\n 220,\n 220,\n 256,\n 16,\n 220,\n 796,\n 357,\n 87,\n 532,\n 288,\n 79,\n 58,\n 15,\n 12962,\n 198,\n 220,\n 220,\n 220,\n 220,\n 220,\n 220,\n 220,\n 256,\n 17,\n 220,\n 796,\n 357,\n 88,\n 532,\n 288,\n 79,\n 58,\n 16,\n 12962,\n 198,\n 220,\n 220,\n 220,\n 220,\n 220,\n 220,\n 220,\n 277,\n 796,\n 838,\n 13,\n 15,\n 1635,\n 256,\n 16,\n 1635,\n 256,\n 16,\n 1343,\n 1160,\n 13,\n 15,\n 1635,\n 256,\n 17,\n 1635,\n 256,\n 17,\n 1343,\n 1542,\n 13,\n 15,\n 198,\n 220,\n 220,\n 220,\n 220,\n 220,\n 220,\n 220,\n 1441,\n 277,\n 220,\n 198,\n 220,\n 220,\n 220,\n 220,\n 198,\n 220,\n 220,\n 220,\n 1303,\n 15793,\n 286,\n 2124,\n 198,\n 220,\n 220,\n 220,\n 2546,\n 796,\n 362,\n 628,\n 220,\n 220,\n 220,\n 25064,\n 796,\n 43104,\n 259,\n 13,\n 70,\n 6649,\n 62,\n 16680,\n 361,\n 270,\n 62,\n 8818,\n 7,\n 1820,\n 62,\n 69,\n 11,\n 42287,\n 11,\n 362,\n 8,\n 198,\n 220,\n 220,\n 220,\n 37227,\n 628,\n 220,\n 220,\n 220,\n 2315,\n 20786,\n 796,\n 220,\n 4808,\n 47423,\n 13,\n 70,\n 6649,\n 62,\n 16680,\n 320,\n 259,\n 62,\n 8818,\n 62,\n 15003,\n 198,\n 220,\n 220,\n 220,\n 1479,\n 20786,\n 796,\n 220,\n 4808,\n 47423,\n 13,\n 70,\n 6649,\n 62,\n 16680,\n 320,\n 259,\n 62,\n 8818,\n 62,\n 5787,\n 198,\n 198,\n 4871,\n 308,\n 6649,\n 62,\n 16680,\n 320,\n 259,\n 62,\n 8818,\n 62,\n 69,\n 7568,\n 7,\n 70,\n 6649,\n 62,\n 16680,\n 7058,\n 313,\n 62,\n 8818,\n 62,\n 69,\n 7568,\n 2599,\n 198,\n 220,\n 220,\n 220,\n 37227,\n 198,\n 220,\n 220,\n 220,\n 770,\n 1398,\n 15738,\n 262,\n 869,\n 10146,\n 329,\n 308,\n 6649,\n 62,\n 16680,\n 320,\n 259,\n 62,\n 8818,\n 62,\n 69,\n 7568,\n 13,\n 628,\n 220,\n 220,\n 220,\n 383,\n 1708,\n 1672,\n 2163,\n 15738,\n 257,\n 2829,\n 1582,\n 28426,\n 1868,\n 351,\n 734,\n 198,\n 220,\n 220,\n 220,\n 10007,\n 13,\n 628,\n 220,\n 220,\n 220,\n 1675,\n 5127,\n 220,\n 262,\n 1080,\n 8160,\n 262,\n 2163,\n 25,\n 198,\n 220,\n 220,\n 220,\n 825,\n 616,\n 62,\n 69,\n 7,\n 85,\n 11,\n 42287,\n 2599,\n 198,\n 220,\n 220,\n 220,\n 220,\n 220,\n 220,\n 220,\n 2124,\n 796,\n 410,\n 58,\n 15,\n 60,\n 198,\n 220,\n 220,\n 220,\n 220,\n 220,\n 220,\n 220,\n 331,\n 796,\n 410,\n 58,\n 16,\n 60,\n 198,\n 220,\n 220,\n 220,\n 220,\n 198,\n 220,\n 220,\n 220,\n 220,\n 220,\n 220,\n 220,\n 288,\n 79,\n 796,\n 42287,\n 198,\n 220,\n 220,\n 220,\n 220,\n 220,\n 220,\n 220,\n 256,\n 16,\n 220,\n 796,\n 357,\n 87,\n 532,\n 288,\n 79,\n 58,\n 15,\n 12962,\n 198,\n 220,\n 220,\n 220,\n 220,\n 220,\n 220,\n 220,\n 256,\n 17,\n 220,\n 796,\n 357,\n 88,\n 532,\n 288,\n 79,\n 58,\n 16,\n 12962,\n 198,\n 220,\n 220,\n 220,\n 220,\n 220,\n 220,\n 220,\n 277,\n 796,\n 838,\n 13,\n 15,\n 1635,\n 256,\n 16,\n 1635,\n 256,\n 16,\n 1343,\n 1160,\n 13,\n 15,\n 1635,\n 256,\n 17,\n 1635,\n 256,\n 17,\n 1343,\n 1542,\n 13,\n 15,\n 198,\n 220,\n 220,\n 220,\n 220,\n 220,\n 220,\n 220,\n 1441,\n 277,\n 198,\n 220,\n 220,\n 220,\n 825,\n 616,\n 62,\n 7568,\n 7,\n 85,\n 11,\n 42287,\n 2599,\n 198,\n 220,\n 220,\n 220,\n 220,\n 220,\n 220,\n 220,\n 2124,\n 796,\n 410,\n 58,\n 15,\n 60,\n 198,\n 220,\n 220,\n 220,\n 220,\n 220,\n 220,\n 220,\n 331,\n 796,\n 410,\n 58,\n 16,\n 60,\n 198,\n 220,\n 220,\n 220,\n 220,\n 220,\n 220,\n 220,\n 47764,\n 796,\n 399,\n 39223,\n 13,\n 9107,\n 418,\n 7,\n 85,\n 13,\n 43358,\n 11,\n 399,\n 39223,\n 13,\n 43879,\n 8,\n 198,\n 220,\n 220,\n 220,\n 220,\n 220,\n 220,\n 220,\n 288,\n 79,\n 796,\n 42287,\n 198,\n 220,\n 220,\n 220,\n 220,\n 220,\n 220,\n 220,\n 47764,\n 58,\n 15,\n 60,\n 796,\n 1160,\n 13,\n 1635,\n 357,\n 87,\n 532,\n 288,\n 79,\n 58,\n 15,\n 12962,\n 198,\n 220,\n 220,\n 220,\n 220,\n 220,\n 220,\n 220,\n 47764,\n 58,\n 16,\n 60,\n 796,\n 2319,\n 13,\n 1635,\n 357,\n 88,\n 532,\n 288,\n 79,\n 58,\n 16,\n 12962,\n 198,\n 220,\n 220,\n 220,\n 220,\n 220,\n 220,\n 220,\n 1441,\n 47764,\n 628,\n 220,\n 220,\n 220,\n 825,\n 616,\n 62,\n 69,\n 7568,\n 7,\n 85,\n 11,\n 42287,\n 2599,\n 198,\n 220,\n 220,\n 220,\n 220,\n 220,\n 220,\n 220,\n 277,\n 796,\n 616,\n 62,\n 69,\n 7,\n 85,\n 11,\n 42287,\n 8,\n 198,\n 220,\n 220,\n 220,\n 220,\n 220,\n 220,\n 220,\n 47764,\n 796,\n 616,\n 62,\n 7568,\n 7,\n 85,\n 11,\n 37266,\n 8,\n 198,\n 220,\n 220,\n 220,\n 220,\n 220,\n 220,\n 220,\n 1441,\n 277,\n 11,\n 47764,\n 628,\n 220,\n 220,\n 220,\n 220,\n 198,\n 220,\n 220,\n 220,\n 1303,\n 15793,\n 286,\n 2124,\n 198,\n 220,\n 220,\n 220,\n 2546,\n 796,\n 362,\n 198,\n 220,\n 220,\n 220,\n 25064,\n 796,\n 43104,\n 259,\n 13,\n 70,\n 6649,\n 62,\n 16680,\n 361,\n 270,\n 62,\n 8818,\n 7,\n 1820,\n 62,\n 69,\n 11,\n 616,\n 62,\n 7568,\n 11,\n 616,\n 62,\n 69,\n 7568,\n 11,\n 42287,\n 11,\n 2546,\n 8,\n 198,\n 220,\n 220,\n 220,\n 37227,\n 628,\n 220,\n 220,\n 220,\n 2315,\n 20786,\n 796,\n 220,\n 4808,\n 47423,\n 13,\n 70,\n 6649,\n 62,\n 16680,\n 320,\n 259,\n 62,\n 8818,\n 62,\n 15003,\n 62,\n 69,\n 7568,\n 198,\n 220,\n 220,\n 220,\n 1479,\n 20786,\n 796,\n 220,\n 4808,\n 47423,\n 13,\n 70,\n 6649,\n 62,\n 16680,\n 320,\n 259,\n 62,\n 8818,\n 62,\n 5787,\n 62,\n 69,\n 7568,\n 198,\n 198,\n 4871,\n 308,\n 6649,\n 62,\n 2144,\n 660,\n 62,\n 8818,\n 7,\n 70,\n 6649,\n 62,\n 16680,\n 7058,\n 313,\n 62,\n 8818,\n 2599,\n 220,\n 220,\n 220,\n 220,\n 198,\n 220,\n 220,\n 220,\n 37227,\n 198,\n 220,\n 220,\n 220,\n 770,\n 1398,\n 15738,\n 262,\n 869,\n 10146,\n 329,\n 308,\n 6649,\n 62,\n 2144,\n 660,\n 62,\n 8818,\n 13,\n 628,\n 220,\n 220,\n 220,\n 37227,\n 628,\n 220,\n 220,\n 220,\n 2315,\n 20786,\n 796,\n 220,\n 4808,\n 47423,\n 13,\n 70,\n 6649,\n 62,\n 2144,\n 660,\n 62,\n 8818,\n 62,\n 15003,\n 198,\n 220,\n 220,\n 220,\n 1479,\n 20786,\n 796,\n 220,\n 4808,\n 47423,\n 13,\n 70,\n 6649,\n 62,\n 2144,\n 660,\n 62,\n 8818,\n 62,\n 5787,\n 198\n]"},"ratio_char_token":{"kind":"number","value":2.066425120772947,"string":"2.066425"},"token_count":{"kind":"number","value":3312,"string":"3,312"}}},{"rowIdx":1253,"cells":{"content":{"kind":"string","value":"import argparse\n\n\n\nif __name__ == \"__main__\":\n main()"},"input_ids":{"kind":"list like","value":[11748,1822,29572,628,198,198,361,11593,3672,834,6624,366,834,12417,834,1298,198,220,220,220,1388,3419],"string":"[\n 11748,\n 1822,\n 29572,\n 628,\n 198,\n 198,\n 361,\n 11593,\n 3672,\n 834,\n 6624,\n 366,\n 834,\n 12417,\n 834,\n 1298,\n 198,\n 220,\n 220,\n 220,\n 1388,\n 3419\n]"},"ratio_char_token":{"kind":"number","value":2.5454545454545454,"string":"2.545455"},"token_count":{"kind":"number","value":22,"string":"22"}}},{"rowIdx":1254,"cells":{"content":{"kind":"string","value":"from collections import Counter\n\n\ndef partial_digest(distances):\n '''Returns a set whose positive pairwise differences generate 'distances'.'''\n # Initialize variables.\n X = {0}\n width = max(distances)\n\n # Create lambda functions for multiset operations.\n new_dist = lambda y, S: Counter(abs(y-s) for s in S)\n containment = lambda a, b: all(a[x] <= b[x] for x in a)\n\n # Create the multiset which generates 'distances'.\n while len(distances) > 0:\n y = max(distances)\n if containment(new_dist(y, X), distances):\n X |= {y}\n distances -= new_dist(y, X)\n else:\n X |= {width - y}\n distances -= new_dist(width - y, X)\n\n return X\n\n\ndef main():\n '''Main call. Reads, runs, and saves problem specific data.'''\n # Read the input data.\n with open('data/data.dat') as input_data:\n distances = Counter(map(int,input_data.read().strip().split()))\n\n # Get the partial digest.\n X = sorted(list(partial_digest(distances)))\n\n # Print and save the answer.\n print ' '.join(map(str, X))\n\n\n\nif __name__ == '__main__':\n main()"},"input_ids":{"kind":"list like","value":[6738,17268,1330,15034,628,198,4299,13027,62,12894,395,7,17080,1817,2599,198,220,220,220,705,7061,35561,257,900,3025,3967,5166,3083,5400,7716,705,17080,1817,6,2637,7061,198,220,220,220,1303,20768,1096,9633,13,198,220,220,220,1395,796,1391,15,92,198,220,220,220,9647,796,3509,7,17080,1817,8,628,220,220,220,1303,13610,37456,5499,329,1963,271,316,4560,13,198,220,220,220,649,62,17080,796,37456,331,11,311,25,15034,7,8937,7,88,12,82,8,329,264,287,311,8,198,220,220,220,37149,796,37456,257,11,275,25,477,7,64,58,87,60,19841,275,58,87,60,329,2124,287,257,8,628,220,220,220,1303,13610,262,1963,271,316,543,18616,705,17080,1817,4458,198,220,220,220,981,18896,7,17080,1817,8,1875,657,25,198,220,220,220,220,220,220,220,331,796,3509,7,17080,1817,8,198,220,220,220,220,220,220,220,611,37149,7,3605,62,17080,7,88,11,1395,828,18868,2599,198,220,220,220,220,220,220,220,220,220,220,220,1395,930,28,1391,88,92,198,220,220,220,220,220,220,220,220,220,220,220,18868,48185,649,62,17080,7,88,11,1395,8,198,220,220,220,220,220,220,220,2073,25,198,220,220,220,220,220,220,220,220,220,220,220,1395,930,28,1391,10394,532,331,92,198,220,220,220,220,220,220,220,220,220,220,220,18868,48185,649,62,17080,7,10394,532,331,11,1395,8,628,220,220,220,1441,1395,628,198,4299,1388,33529,198,220,220,220,705,7061,13383,869,13,4149,82,11,4539,11,290,16031,1917,2176,1366,2637,7061,198,220,220,220,1303,4149,262,5128,1366,13,198,220,220,220,351,1280,10786,7890,14,7890,13,19608,11537,355,5128,62,7890,25,198,220,220,220,220,220,220,220,18868,796,15034,7,8899,7,600,11,15414,62,7890,13,961,22446,36311,22446,35312,3419,4008,628,220,220,220,1303,3497,262,13027,16274,13,198,220,220,220,1395,796,23243,7,4868,7,47172,62,12894,395,7,17080,1817,22305,628,220,220,220,1303,12578,290,3613,262,3280,13,198,220,220,220,3601,705,45302,22179,7,8899,7,2536,11,1395,4008,628,198,198,361,11593,3672,834,6624,705,834,12417,834,10354,198,220,220,220,1388,3419],"string":"[\n 6738,\n 17268,\n 1330,\n 15034,\n 628,\n 198,\n 4299,\n 13027,\n 62,\n 12894,\n 395,\n 7,\n 17080,\n 1817,\n 2599,\n 198,\n 220,\n 220,\n 220,\n 705,\n 7061,\n 35561,\n 257,\n 900,\n 3025,\n 3967,\n 5166,\n 3083,\n 5400,\n 7716,\n 705,\n 17080,\n 1817,\n 6,\n 2637,\n 7061,\n 198,\n 220,\n 220,\n 220,\n 1303,\n 20768,\n 1096,\n 9633,\n 13,\n 198,\n 220,\n 220,\n 220,\n 1395,\n 796,\n 1391,\n 15,\n 92,\n 198,\n 220,\n 220,\n 220,\n 9647,\n 796,\n 3509,\n 7,\n 17080,\n 1817,\n 8,\n 628,\n 220,\n 220,\n 220,\n 1303,\n 13610,\n 37456,\n 5499,\n 329,\n 1963,\n 271,\n 316,\n 4560,\n 13,\n 198,\n 220,\n 220,\n 220,\n 649,\n 62,\n 17080,\n 796,\n 37456,\n 331,\n 11,\n 311,\n 25,\n 15034,\n 7,\n 8937,\n 7,\n 88,\n 12,\n 82,\n 8,\n 329,\n 264,\n 287,\n 311,\n 8,\n 198,\n 220,\n 220,\n 220,\n 37149,\n 796,\n 37456,\n 257,\n 11,\n 275,\n 25,\n 477,\n 7,\n 64,\n 58,\n 87,\n 60,\n 19841,\n 275,\n 58,\n 87,\n 60,\n 329,\n 2124,\n 287,\n 257,\n 8,\n 628,\n 220,\n 220,\n 220,\n 1303,\n 13610,\n 262,\n 1963,\n 271,\n 316,\n 543,\n 18616,\n 705,\n 17080,\n 1817,\n 4458,\n 198,\n 220,\n 220,\n 220,\n 981,\n 18896,\n 7,\n 17080,\n 1817,\n 8,\n 1875,\n 657,\n 25,\n 198,\n 220,\n 220,\n 220,\n 220,\n 220,\n 220,\n 220,\n 331,\n 796,\n 3509,\n 7,\n 17080,\n 1817,\n 8,\n 198,\n 220,\n 220,\n 220,\n 220,\n 220,\n 220,\n 220,\n 611,\n 37149,\n 7,\n 3605,\n 62,\n 17080,\n 7,\n 88,\n 11,\n 1395,\n 828,\n 18868,\n 2599,\n 198,\n 220,\n 220,\n 220,\n 220,\n 220,\n 220,\n 220,\n 220,\n 220,\n 220,\n 220,\n 1395,\n 930,\n 28,\n 1391,\n 88,\n 92,\n 198,\n 220,\n 220,\n 220,\n 220,\n 220,\n 220,\n 220,\n 220,\n 220,\n 220,\n 220,\n 18868,\n 48185,\n 649,\n 62,\n 17080,\n 7,\n 88,\n 11,\n 1395,\n 8,\n 198,\n 220,\n 220,\n 220,\n 220,\n 220,\n 220,\n 220,\n 2073,\n 25,\n 198,\n 220,\n 220,\n 220,\n 220,\n 220,\n 220,\n 220,\n 220,\n 220,\n 220,\n 220,\n 1395,\n 930,\n 28,\n 1391,\n 10394,\n 532,\n 331,\n 92,\n 198,\n 220,\n 220,\n 220,\n 220,\n 220,\n 220,\n 220,\n 220,\n 220,\n 220,\n 220,\n 18868,\n 48185,\n 649,\n 62,\n 17080,\n 7,\n 10394,\n 532,\n 331,\n 11,\n 1395,\n 8,\n 628,\n 220,\n 220,\n 220,\n 1441,\n 1395,\n 628,\n 198,\n 4299,\n 1388,\n 33529,\n 198,\n 220,\n 220,\n 220,\n 705,\n 7061,\n 13383,\n 869,\n 13,\n 4149,\n 82,\n 11,\n 4539,\n 11,\n 290,\n 16031,\n 1917,\n 2176,\n 1366,\n 2637,\n 7061,\n 198,\n 220,\n 220,\n 220,\n 1303,\n 4149,\n 262,\n 5128,\n 1366,\n 13,\n 198,\n 220,\n 220,\n 220,\n 351,\n 1280,\n 10786,\n 7890,\n 14,\n 7890,\n 13,\n 19608,\n 11537,\n 355,\n 5128,\n 62,\n 7890,\n 25,\n 198,\n 220,\n 220,\n 220,\n 220,\n 220,\n 220,\n 220,\n 18868,\n 796,\n 15034,\n 7,\n 8899,\n 7,\n 600,\n 11,\n 15414,\n 62,\n 7890,\n 13,\n 961,\n 22446,\n 36311,\n 22446,\n 35312,\n 3419,\n 4008,\n 628,\n 220,\n 220,\n 220,\n 1303,\n 3497,\n 262,\n 13027,\n 16274,\n 13,\n 198,\n 220,\n 220,\n 220,\n 1395,\n 796,\n 23243,\n 7,\n 4868,\n 7,\n 47172,\n 62,\n 12894,\n 395,\n 7,\n 17080,\n 1817,\n 22305,\n 628,\n 220,\n 220,\n 220,\n 1303,\n 12578,\n 290,\n 3613,\n 262,\n 3280,\n 13,\n 198,\n 220,\n 220,\n 220,\n 3601,\n 705,\n 45302,\n 22179,\n 7,\n 8899,\n 7,\n 2536,\n 11,\n 1395,\n 4008,\n 628,\n 198,\n 198,\n 361,\n 11593,\n 3672,\n 834,\n 6624,\n 705,\n 834,\n 12417,\n 834,\n 10354,\n 198,\n 220,\n 220,\n 220,\n 1388,\n 3419\n]"},"ratio_char_token":{"kind":"number","value":2.5011086474501107,"string":"2.501109"},"token_count":{"kind":"number","value":451,"string":"451"}}},{"rowIdx":1255,"cells":{"content":{"kind":"string","value":"\n\nif __name__ == '__main__':\n text = input(\"Give words: \")\n print(pig_latin(text))\n"},"input_ids":{"kind":"list like","value":[198,198,361,11593,3672,834,6624,705,834,12417,834,10354,198,220,220,220,2420,796,5128,7203,23318,2456,25,366,8,198,220,220,220,3601,7,79,328,62,75,10680,7,5239,4008,198],"string":"[\n 198,\n 198,\n 361,\n 11593,\n 3672,\n 834,\n 6624,\n 705,\n 834,\n 12417,\n 834,\n 10354,\n 198,\n 220,\n 220,\n 220,\n 2420,\n 796,\n 5128,\n 7203,\n 23318,\n 2456,\n 25,\n 366,\n 8,\n 198,\n 220,\n 220,\n 220,\n 3601,\n 7,\n 79,\n 328,\n 62,\n 75,\n 10680,\n 7,\n 5239,\n 4008,\n 198\n]"},"ratio_char_token":{"kind":"number","value":2.225,"string":"2.225"},"token_count":{"kind":"number","value":40,"string":"40"}}},{"rowIdx":1256,"cells":{"content":{"kind":"string","value":"# -*- coding: utf-8 -*-\n\"\"\"\nCreated on Wed Aug 15 13:35:23 2018\n\n@author: Victor Onink\nHere we create a figure that has the 24h, and the 3h flow field densities\nfor the North Pacific\n\"\"\"\n\nimport numpy as np\nfrom mpl_toolkits.basemap import Basemap\nimport matplotlib.pyplot as plt\nfrom scipy import io\nimport pandas as pd\n# cbar=my_map.colorbar(density)\n# cbar.ax.tick_params(labelsize=12)\n# cbar.set_label(\"Plastic Counts ($10^{-3}$ # km$^{-2}$)\", rotation=90,fontsize=12)\n\n#%% \nlocation='D:\\Desktop\\Thesis\\ParcelsFigData\\Data\\North Pacific\\OutputFiles\\Onink et al\\Densities/'\nFile=['NorthPacificTotalDensity24h','NorthPacificStokesTotalDensity24h',\n 'NorthPacificTotalDensity3h','NorthPacificStokesTotalDensity3h']\naxeslabelsize=14\ntextsize=12\nfig,axes=plt.subplots(nrows=2, ncols=1,figsize=(10*2,8*1))\nfor i in range(len(File)):\n density=np.load(location+File[i])\n density[np.isnan(density)]=0\n meanFinalYear=np.sum(density[-183:,:,:]/density[-183:,:,:].shape[0],axis=0)\n meanFinalYear[meanFinalYear==0]=np.nan\n latD=np.linspace(-80,80,160)\n lonD=np.linspace(0,359,360)\n plt.subplot(2,2,i+1)\n density=plotDensity(i,lonD,latD,meanFinalYear)\nfig.subplots_adjust(right=0.9)\ncbar_ax = fig.add_axes([0.93, 0.12, 0.02, 0.74])\ncbar=fig.colorbar(density,cax=cbar_ax)\ncbar.ax.tick_params(labelsize=textsize)\ncbar.set_label(\"Plastic Counts ($10^{-3}$ # km$^{-2}$)\", rotation=90,fontsize=axeslabelsize)\ncbar.ax.set_yticklabels(['<0.1','0.3','0.5','0.7','0.9','1.1','1.3','1.5','1.7','1.9<'])\nplt.subplots_adjust(wspace=0.06)\nplt.savefig('D:\\Desktop\\Thesis\\ParcelsFigData\\Data\\North Pacific\\Figures\\NorthPacificTimeStepDensities.jpg',\n bbox_inches='tight') \n"},"input_ids":{"kind":"list like","value":[2,532,9,12,19617,25,3384,69,12,23,532,9,12,198,37811,198,41972,319,3300,2447,1315,1511,25,2327,25,1954,2864,198,198,31,9800,25,12622,1550,676,198,4342,356,2251,257,3785,326,468,262,1987,71,11,290,262,513,71,5202,2214,29509,871,198,1640,262,2258,8211,198,37811,198,198,11748,299,32152,355,45941,198,6738,285,489,62,25981,74,896,13,12093,368,499,1330,6455,368,499,198,11748,2603,29487,8019,13,9078,29487,355,458,83,198,6738,629,541,88,1330,33245,198,11748,19798,292,355,279,67,198,2,220,220,220,269,5657,28,1820,62,8899,13,8043,5657,7,43337,8,198,2,220,220,220,269,5657,13,897,13,42298,62,37266,7,23912,1424,1096,28,1065,8,198,2,220,220,220,269,5657,13,2617,62,18242,7203,3646,3477,2764,82,7198,940,36796,12,18,92,3,1303,10571,3,36796,12,17,92,3,42501,13179,28,3829,11,10331,7857,28,1065,8,198,198,2,16626,220,220,220,220,220,220,220,220,220,220,220,220,220,220,220,220,220,220,220,220,220,220,220,220,220,220,220,220,220,220,220,220,220,220,220,220,198,24886,11639,35,7479,36881,59,464,13429,59,10044,5276,82,14989,6601,59,6601,59,14157,8211,59,26410,25876,59,2202,676,2123,435,59,35,641,871,14,6,198,8979,28,17816,14157,22933,14957,35,6377,1731,71,41707,14157,22933,1273,3369,14957,35,6377,1731,71,3256,198,220,220,220,220,220,705,14157,22933,14957,35,6377,18,71,41707,14157,22933,1273,3369,14957,35,6377,18,71,20520,198,897,274,23912,1424,1096,28,1415,198,5239,7857,28,1065,198,5647,11,897,274,28,489,83,13,7266,489,1747,7,77,8516,28,17,11,299,4033,82,28,16,11,5647,7857,16193,940,9,17,11,23,9,16,4008,198,1640,1312,287,2837,7,11925,7,8979,8,2599,198,220,220,220,12109,28,37659,13,2220,7,24886,10,8979,58,72,12962,198,220,220,220,12109,58,37659,13,271,12647,7,43337,15437,28,15,198,220,220,220,1612,19006,17688,28,37659,13,16345,7,43337,58,12,24839,45299,45299,47715,14,43337,58,12,24839,45299,45299,25,4083,43358,58,15,4357,22704,28,15,8,198,220,220,220,1612,19006,17688,58,32604,19006,17688,855,15,22241,37659,13,12647,198,220,220,220,3042,35,28,37659,13,21602,10223,32590,1795,11,1795,11,14198,8,198,220,220,220,300,261,35,28,37659,13,21602,10223,7,15,11,30743,11,15277,8,198,220,220,220,458,83,13,7266,29487,7,17,11,17,11,72,10,16,8,198,220,220,220,12109,28,29487,35,6377,7,72,11,14995,35,11,15460,35,11,32604,19006,17688,8,198,5647,13,7266,489,1747,62,23032,7,3506,28,15,13,24,8,198,66,5657,62,897,796,2336,13,2860,62,897,274,26933,15,13,6052,11,657,13,1065,11,657,13,2999,11,657,13,4524,12962,198,66,5657,28,5647,13,8043,5657,7,43337,11,66,897,28,66,5657,62,897,8,198,66,5657,13,897,13,42298,62,37266,7,23912,1424,1096,28,5239,7857,8,198,66,5657,13,2617,62,18242,7203,3646,3477,2764,82,7198,940,36796,12,18,92,3,1303,10571,3,36796,12,17,92,3,42501,13179,28,3829,11,10331,7857,28,897,274,23912,1424,1096,8,198,66,5657,13,897,13,2617,62,20760,624,23912,1424,7,17816,27,15,13,16,41707,15,13,18,41707,15,13,20,41707,15,13,22,41707,15,13,24,41707,16,13,16,41707,16,13,18,41707,16,13,20,41707,16,13,22,41707,16,13,24,27,6,12962,198,489,83,13,7266,489,1747,62,23032,7,86,13200,28,15,13,3312,8,198,489,83,13,21928,5647,10786,35,7479,36881,59,464,13429,59,10044,5276,82,14989,6601,59,6601,59,14157,8211,59,14989,942,59,14157,22933,7575,8600,35,641,871,13,9479,3256,198,220,220,220,220,220,220,220,220,220,220,220,275,3524,62,45457,11639,33464,11537,220,198],"string":"[\n 2,\n 532,\n 9,\n 12,\n 19617,\n 25,\n 3384,\n 69,\n 12,\n 23,\n 532,\n 9,\n 12,\n 198,\n 37811,\n 198,\n 41972,\n 319,\n 3300,\n 2447,\n 1315,\n 1511,\n 25,\n 2327,\n 25,\n 1954,\n 2864,\n 198,\n 198,\n 31,\n 9800,\n 25,\n 12622,\n 1550,\n 676,\n 198,\n 4342,\n 356,\n 2251,\n 257,\n 3785,\n 326,\n 468,\n 262,\n 1987,\n 71,\n 11,\n 290,\n 262,\n 513,\n 71,\n 5202,\n 2214,\n 29509,\n 871,\n 198,\n 1640,\n 262,\n 2258,\n 8211,\n 198,\n 37811,\n 198,\n 198,\n 11748,\n 299,\n 32152,\n 355,\n 45941,\n 198,\n 6738,\n 285,\n 489,\n 62,\n 25981,\n 74,\n 896,\n 13,\n 12093,\n 368,\n 499,\n 1330,\n 6455,\n 368,\n 499,\n 198,\n 11748,\n 2603,\n 29487,\n 8019,\n 13,\n 9078,\n 29487,\n 355,\n 458,\n 83,\n 198,\n 6738,\n 629,\n 541,\n 88,\n 1330,\n 33245,\n 198,\n 11748,\n 19798,\n 292,\n 355,\n 279,\n 67,\n 198,\n 2,\n 220,\n 220,\n 220,\n 269,\n 5657,\n 28,\n 1820,\n 62,\n 8899,\n 13,\n 8043,\n 5657,\n 7,\n 43337,\n 8,\n 198,\n 2,\n 220,\n 220,\n 220,\n 269,\n 5657,\n 13,\n 897,\n 13,\n 42298,\n 62,\n 37266,\n 7,\n 23912,\n 1424,\n 1096,\n 28,\n 1065,\n 8,\n 198,\n 2,\n 220,\n 220,\n 220,\n 269,\n 5657,\n 13,\n 2617,\n 62,\n 18242,\n 7203,\n 3646,\n 3477,\n 2764,\n 82,\n 7198,\n 940,\n 36796,\n 12,\n 18,\n 92,\n 3,\n 1303,\n 10571,\n 3,\n 36796,\n 12,\n 17,\n 92,\n 3,\n 42501,\n 13179,\n 28,\n 3829,\n 11,\n 10331,\n 7857,\n 28,\n 1065,\n 8,\n 198,\n 198,\n 2,\n 16626,\n 220,\n 220,\n 220,\n 220,\n 220,\n 220,\n 220,\n 220,\n 220,\n 220,\n 220,\n 220,\n 220,\n 220,\n 220,\n 220,\n 220,\n 220,\n 220,\n 220,\n 220,\n 220,\n 220,\n 220,\n 220,\n 220,\n 220,\n 220,\n 220,\n 220,\n 220,\n 220,\n 220,\n 220,\n 220,\n 220,\n 198,\n 24886,\n 11639,\n 35,\n 7479,\n 36881,\n 59,\n 464,\n 13429,\n 59,\n 10044,\n 5276,\n 82,\n 14989,\n 6601,\n 59,\n 6601,\n 59,\n 14157,\n 8211,\n 59,\n 26410,\n 25876,\n 59,\n 2202,\n 676,\n 2123,\n 435,\n 59,\n 35,\n 641,\n 871,\n 14,\n 6,\n 198,\n 8979,\n 28,\n 17816,\n 14157,\n 22933,\n 14957,\n 35,\n 6377,\n 1731,\n 71,\n 41707,\n 14157,\n 22933,\n 1273,\n 3369,\n 14957,\n 35,\n 6377,\n 1731,\n 71,\n 3256,\n 198,\n 220,\n 220,\n 220,\n 220,\n 220,\n 705,\n 14157,\n 22933,\n 14957,\n 35,\n 6377,\n 18,\n 71,\n 41707,\n 14157,\n 22933,\n 1273,\n 3369,\n 14957,\n 35,\n 6377,\n 18,\n 71,\n 20520,\n 198,\n 897,\n 274,\n 23912,\n 1424,\n 1096,\n 28,\n 1415,\n 198,\n 5239,\n 7857,\n 28,\n 1065,\n 198,\n 5647,\n 11,\n 897,\n 274,\n 28,\n 489,\n 83,\n 13,\n 7266,\n 489,\n 1747,\n 7,\n 77,\n 8516,\n 28,\n 17,\n 11,\n 299,\n 4033,\n 82,\n 28,\n 16,\n 11,\n 5647,\n 7857,\n 16193,\n 940,\n 9,\n 17,\n 11,\n 23,\n 9,\n 16,\n 4008,\n 198,\n 1640,\n 1312,\n 287,\n 2837,\n 7,\n 11925,\n 7,\n 8979,\n 8,\n 2599,\n 198,\n 220,\n 220,\n 220,\n 12109,\n 28,\n 37659,\n 13,\n 2220,\n 7,\n 24886,\n 10,\n 8979,\n 58,\n 72,\n 12962,\n 198,\n 220,\n 220,\n 220,\n 12109,\n 58,\n 37659,\n 13,\n 271,\n 12647,\n 7,\n 43337,\n 15437,\n 28,\n 15,\n 198,\n 220,\n 220,\n 220,\n 1612,\n 19006,\n 17688,\n 28,\n 37659,\n 13,\n 16345,\n 7,\n 43337,\n 58,\n 12,\n 24839,\n 45299,\n 45299,\n 47715,\n 14,\n 43337,\n 58,\n 12,\n 24839,\n 45299,\n 45299,\n 25,\n 4083,\n 43358,\n 58,\n 15,\n 4357,\n 22704,\n 28,\n 15,\n 8,\n 198,\n 220,\n 220,\n 220,\n 1612,\n 19006,\n 17688,\n 58,\n 32604,\n 19006,\n 17688,\n 855,\n 15,\n 22241,\n 37659,\n 13,\n 12647,\n 198,\n 220,\n 220,\n 220,\n 3042,\n 35,\n 28,\n 37659,\n 13,\n 21602,\n 10223,\n 32590,\n 1795,\n 11,\n 1795,\n 11,\n 14198,\n 8,\n 198,\n 220,\n 220,\n 220,\n 300,\n 261,\n 35,\n 28,\n 37659,\n 13,\n 21602,\n 10223,\n 7,\n 15,\n 11,\n 30743,\n 11,\n 15277,\n 8,\n 198,\n 220,\n 220,\n 220,\n 458,\n 83,\n 13,\n 7266,\n 29487,\n 7,\n 17,\n 11,\n 17,\n 11,\n 72,\n 10,\n 16,\n 8,\n 198,\n 220,\n 220,\n 220,\n 12109,\n 28,\n 29487,\n 35,\n 6377,\n 7,\n 72,\n 11,\n 14995,\n 35,\n 11,\n 15460,\n 35,\n 11,\n 32604,\n 19006,\n 17688,\n 8,\n 198,\n 5647,\n 13,\n 7266,\n 489,\n 1747,\n 62,\n 23032,\n 7,\n 3506,\n 28,\n 15,\n 13,\n 24,\n 8,\n 198,\n 66,\n 5657,\n 62,\n 897,\n 796,\n 2336,\n 13,\n 2860,\n 62,\n 897,\n 274,\n 26933,\n 15,\n 13,\n 6052,\n 11,\n 657,\n 13,\n 1065,\n 11,\n 657,\n 13,\n 2999,\n 11,\n 657,\n 13,\n 4524,\n 12962,\n 198,\n 66,\n 5657,\n 28,\n 5647,\n 13,\n 8043,\n 5657,\n 7,\n 43337,\n 11,\n 66,\n 897,\n 28,\n 66,\n 5657,\n 62,\n 897,\n 8,\n 198,\n 66,\n 5657,\n 13,\n 897,\n 13,\n 42298,\n 62,\n 37266,\n 7,\n 23912,\n 1424,\n 1096,\n 28,\n 5239,\n 7857,\n 8,\n 198,\n 66,\n 5657,\n 13,\n 2617,\n 62,\n 18242,\n 7203,\n 3646,\n 3477,\n 2764,\n 82,\n 7198,\n 940,\n 36796,\n 12,\n 18,\n 92,\n 3,\n 1303,\n 10571,\n 3,\n 36796,\n 12,\n 17,\n 92,\n 3,\n 42501,\n 13179,\n 28,\n 3829,\n 11,\n 10331,\n 7857,\n 28,\n 897,\n 274,\n 23912,\n 1424,\n 1096,\n 8,\n 198,\n 66,\n 5657,\n 13,\n 897,\n 13,\n 2617,\n 62,\n 20760,\n 624,\n 23912,\n 1424,\n 7,\n 17816,\n 27,\n 15,\n 13,\n 16,\n 41707,\n 15,\n 13,\n 18,\n 41707,\n 15,\n 13,\n 20,\n 41707,\n 15,\n 13,\n 22,\n 41707,\n 15,\n 13,\n 24,\n 41707,\n 16,\n 13,\n 16,\n 41707,\n 16,\n 13,\n 18,\n 41707,\n 16,\n 13,\n 20,\n 41707,\n 16,\n 13,\n 22,\n 41707,\n 16,\n 13,\n 24,\n 27,\n 6,\n 12962,\n 198,\n 489,\n 83,\n 13,\n 7266,\n 489,\n 1747,\n 62,\n 23032,\n 7,\n 86,\n 13200,\n 28,\n 15,\n 13,\n 3312,\n 8,\n 198,\n 489,\n 83,\n 13,\n 21928,\n 5647,\n 10786,\n 35,\n 7479,\n 36881,\n 59,\n 464,\n 13429,\n 59,\n 10044,\n 5276,\n 82,\n 14989,\n 6601,\n 59,\n 6601,\n 59,\n 14157,\n 8211,\n 59,\n 14989,\n 942,\n 59,\n 14157,\n 22933,\n 7575,\n 8600,\n 35,\n 641,\n 871,\n 13,\n 9479,\n 3256,\n 198,\n 220,\n 220,\n 220,\n 220,\n 220,\n 220,\n 220,\n 220,\n 220,\n 220,\n 220,\n 275,\n 3524,\n 62,\n 45457,\n 11639,\n 33464,\n 11537,\n 220,\n 198\n]"},"ratio_char_token":{"kind":"number","value":2.212005108556833,"string":"2.212005"},"token_count":{"kind":"number","value":783,"string":"783"}}},{"rowIdx":1257,"cells":{"content":{"kind":"string","value":"from settings import *\n\n\nBASE_URL = os.getenv('OPENDUTY_BASE_URL', \"http://localhost\")\n\nXMPP_SETTINGS = {\n 'user': os.getenv('OPENDUTY_XMPP_USER'),\n 'password': os.getenv('OPENDUTY_XMPP_PASS'),\n 'server': os.getenv('OPENDUTY_XMPP_SERVER', 'xmpp'),\n 'port': os.getenv('OPENDUTY_XMPP_PORT', 5222),\n}\n\nEMAIL_SETTINGS = {\n 'user': os.getenv('OPENDUTY_EMAIL_USER'),\n 'password': os.getenv('OPENDUTY_EMAIL_PASS'),\n}\n\n'''\nTWILIO_SETTINGS = {\n 'SID': \"TWILIO_ACCOUNT_SID\",\n 'token': \"TWILIO_ACCOUNT_TOKEN\",\n 'phone_number': \"your_twilio_phone_number\",\n 'sms_number': \"your_twilio_sms_number\",\n 'twiml_url': \"http://www.website.org/voice.xml\"\n}\n'''\n\nSLACK_SETTINGS = {\n 'apikey': os.getenv('OPENDUTY_SLACK_APIKEY', \"YOUR_SLACK_API_KEY\")\n}\n\n'''\nPROWL_SETTINGS = {\n 'priority': 0\n 'application': 'openduty'\n}\n'''\n\nDATABASES = {\n 'default': {\n 'ENGINE': os.getenv('OPENDUTY_DATABASE_ENGINE', 'django.db.backends.mysql'),\n 'NAME': os.getenv('OPENDUTY_DATABASE_NAME', 'openduty'),\n 'USER': os.getenv('OPENDUTY_DATABASE_USER', 'openduty'),\n 'PASSWORD': os.getenv('OPENDUTY_DATABASE_PASS', 'dutyfree'),\n 'HOST': os.getenv('OPENDUTY_DATABASE_HOST', 'db'),\n 'PORT': os.getenv('OPENDUTY_DATABASE_PORT', '3306')\n }\n}\n\n# SECURITY WARNING: keep the secret key used in production secret!\nSECRET_KEY = os.getenv('OPENDUTY_SECRET_KEY', 'yoursecretkey')\n\nALLOWED_HOSTS = ['your.dutyfree.host']\n\nDEBUG = os.getenv('OPENDUTY_DEBUG', False)\nTEMPLATE_DEBUG = os.getenv('OPENDUTY_TEMPLATE_DEBUG', False)\n"},"input_ids":{"kind":"list like","value":[6738,6460,1330,1635,628,198,33,11159,62,21886,796,28686,13,1136,24330,10786,3185,10619,3843,56,62,33,11159,62,21886,3256,366,4023,1378,36750,4943,198,198,55,7378,47,62,28480,51,20754,796,1391,198,220,220,220,705,7220,10354,28686,13,1136,24330,10786,3185,10619,3843,56,62,55,7378,47,62,29904,33809,198,220,220,220,705,28712,10354,28686,13,1136,24330,10786,3185,10619,3843,56,62,55,7378,47,62,47924,33809,198,220,220,220,705,15388,10354,28686,13,1136,24330,10786,3185,10619,3843,56,62,55,7378,47,62,35009,5959,3256,705,87,76,381,33809,198,220,220,220,705,634,10354,28686,13,1136,24330,10786,3185,10619,3843,56,62,55,7378,47,62,15490,3256,642,23148,828,198,92,198,198,27630,4146,62,28480,51,20754,796,1391,198,220,220,220,705,7220,10354,28686,13,1136,24330,10786,3185,10619,3843,56,62,27630,4146,62,29904,33809,198,220,220,220,705,28712,10354,28686,13,1136,24330,10786,3185,10619,3843,56,62,27630,4146,62,47924,33809,198,92,198,198,7061,6,198,34551,4146,9399,62,28480,51,20754,796,1391,198,220,220,220,705,50,2389,10354,366,34551,4146,9399,62,26861,28270,62,50,2389,1600,198,220,220,220,705,30001,10354,366,34551,4146,9399,62,26861,28270,62,10468,43959,1600,198,220,220,220,705,4862,62,17618,10354,366,14108,62,4246,346,952,62,4862,62,17618,1600,198,220,220,220,705,82,907,62,17618,10354,366,14108,62,4246,346,952,62,82,907,62,17618,1600,198,220,220,220,705,4246,320,75,62,6371,10354,366,4023,1378,2503,13,732,12485,13,2398,14,38888,13,19875,1,198,92,198,7061,6,198,198,8634,8120,62,28480,51,20754,796,1391,198,220,220,220,705,499,522,88,10354,28686,13,1136,24330,10786,3185,10619,3843,56,62,8634,8120,62,17614,20373,3256,366,56,11698,62,8634,8120,62,17614,62,20373,4943,198,92,198,198,7061,6,198,4805,3913,43,62,28480,51,20754,796,1391,198,220,220,220,705,49336,10354,657,198,220,220,220,705,31438,10354,705,404,437,3935,6,198,92,198,7061,6,198,198,35,1404,6242,1921,1546,796,1391,198,220,220,220,705,12286,10354,1391,198,220,220,220,220,220,220,220,705,26808,8881,10354,28686,13,1136,24330,10786,3185,10619,3843,56,62,35,1404,6242,11159,62,26808,8881,3256,705,28241,14208,13,9945,13,1891,2412,13,28744,13976,33809,198,220,220,220,220,220,220,220,705,20608,10354,28686,13,1136,24330,10786,3185,10619,3843,56,62,35,1404,6242,11159,62,20608,3256,705,404,437,3935,33809,198,220,220,220,220,220,220,220,705,29904,10354,28686,13,1136,24330,10786,3185,10619,3843,56,62,35,1404,6242,11159,62,29904,3256,705,404,437,3935,33809,198,220,220,220,220,220,220,220,705,47924,54,12532,10354,28686,13,1136,24330,10786,3185,10619,3843,56,62,35,1404,6242,11159,62,47924,3256,705,26278,5787,33809,198,220,220,220,220,220,220,220,705,39,10892,10354,28686,13,1136,24330,10786,3185,10619,3843,56,62,35,1404,6242,11159,62,39,10892,3256,705,9945,33809,198,220,220,220,220,220,220,220,705,15490,10354,28686,13,1136,24330,10786,3185,10619,3843,56,62,35,1404,6242,11159,62,15490,3256,705,18,20548,11537,198,220,220,220,1782,198,92,198,198,2,10729,4261,9050,39410,25,1394,262,3200,1994,973,287,3227,3200,0,198,23683,26087,62,20373,796,28686,13,1136,24330,10786,3185,10619,3843,56,62,23683,26087,62,20373,3256,705,14108,21078,2539,11537,198,198,7036,3913,1961,62,39,10892,50,796,37250,14108,13,26278,5787,13,4774,20520,198,198,30531,796,28686,13,1136,24330,10786,3185,10619,3843,56,62,30531,3256,10352,8,198,51,3620,6489,6158,62,30531,796,28686,13,1136,24330,10786,3185,10619,3843,56,62,51,3620,6489,6158,62,30531,3256,10352,8,198],"string":"[\n 6738,\n 6460,\n 1330,\n 1635,\n 628,\n 198,\n 33,\n 11159,\n 62,\n 21886,\n 796,\n 28686,\n 13,\n 1136,\n 24330,\n 10786,\n 3185,\n 10619,\n 3843,\n 56,\n 62,\n 33,\n 11159,\n 62,\n 21886,\n 3256,\n 366,\n 4023,\n 1378,\n 36750,\n 4943,\n 198,\n 198,\n 55,\n 7378,\n 47,\n 62,\n 28480,\n 51,\n 20754,\n 796,\n 1391,\n 198,\n 220,\n 220,\n 220,\n 705,\n 7220,\n 10354,\n 28686,\n 13,\n 1136,\n 24330,\n 10786,\n 3185,\n 10619,\n 3843,\n 56,\n 62,\n 55,\n 7378,\n 47,\n 62,\n 29904,\n 33809,\n 198,\n 220,\n 220,\n 220,\n 705,\n 28712,\n 10354,\n 28686,\n 13,\n 1136,\n 24330,\n 10786,\n 3185,\n 10619,\n 3843,\n 56,\n 62,\n 55,\n 7378,\n 47,\n 62,\n 47924,\n 33809,\n 198,\n 220,\n 220,\n 220,\n 705,\n 15388,\n 10354,\n 28686,\n 13,\n 1136,\n 24330,\n 10786,\n 3185,\n 10619,\n 3843,\n 56,\n 62,\n 55,\n 7378,\n 47,\n 62,\n 35009,\n 5959,\n 3256,\n 705,\n 87,\n 76,\n 381,\n 33809,\n 198,\n 220,\n 220,\n 220,\n 705,\n 634,\n 10354,\n 28686,\n 13,\n 1136,\n 24330,\n 10786,\n 3185,\n 10619,\n 3843,\n 56,\n 62,\n 55,\n 7378,\n 47,\n 62,\n 15490,\n 3256,\n 642,\n 23148,\n 828,\n 198,\n 92,\n 198,\n 198,\n 27630,\n 4146,\n 62,\n 28480,\n 51,\n 20754,\n 796,\n 1391,\n 198,\n 220,\n 220,\n 220,\n 705,\n 7220,\n 10354,\n 28686,\n 13,\n 1136,\n 24330,\n 10786,\n 3185,\n 10619,\n 3843,\n 56,\n 62,\n 27630,\n 4146,\n 62,\n 29904,\n 33809,\n 198,\n 220,\n 220,\n 220,\n 705,\n 28712,\n 10354,\n 28686,\n 13,\n 1136,\n 24330,\n 10786,\n 3185,\n 10619,\n 3843,\n 56,\n 62,\n 27630,\n 4146,\n 62,\n 47924,\n 33809,\n 198,\n 92,\n 198,\n 198,\n 7061,\n 6,\n 198,\n 34551,\n 4146,\n 9399,\n 62,\n 28480,\n 51,\n 20754,\n 796,\n 1391,\n 198,\n 220,\n 220,\n 220,\n 705,\n 50,\n 2389,\n 10354,\n 366,\n 34551,\n 4146,\n 9399,\n 62,\n 26861,\n 28270,\n 62,\n 50,\n 2389,\n 1600,\n 198,\n 220,\n 220,\n 220,\n 705,\n 30001,\n 10354,\n 366,\n 34551,\n 4146,\n 9399,\n 62,\n 26861,\n 28270,\n 62,\n 10468,\n 43959,\n 1600,\n 198,\n 220,\n 220,\n 220,\n 705,\n 4862,\n 62,\n 17618,\n 10354,\n 366,\n 14108,\n 62,\n 4246,\n 346,\n 952,\n 62,\n 4862,\n 62,\n 17618,\n 1600,\n 198,\n 220,\n 220,\n 220,\n 705,\n 82,\n 907,\n 62,\n 17618,\n 10354,\n 366,\n 14108,\n 62,\n 4246,\n 346,\n 952,\n 62,\n 82,\n 907,\n 62,\n 17618,\n 1600,\n 198,\n 220,\n 220,\n 220,\n 705,\n 4246,\n 320,\n 75,\n 62,\n 6371,\n 10354,\n 366,\n 4023,\n 1378,\n 2503,\n 13,\n 732,\n 12485,\n 13,\n 2398,\n 14,\n 38888,\n 13,\n 19875,\n 1,\n 198,\n 92,\n 198,\n 7061,\n 6,\n 198,\n 198,\n 8634,\n 8120,\n 62,\n 28480,\n 51,\n 20754,\n 796,\n 1391,\n 198,\n 220,\n 220,\n 220,\n 705,\n 499,\n 522,\n 88,\n 10354,\n 28686,\n 13,\n 1136,\n 24330,\n 10786,\n 3185,\n 10619,\n 3843,\n 56,\n 62,\n 8634,\n 8120,\n 62,\n 17614,\n 20373,\n 3256,\n 366,\n 56,\n 11698,\n 62,\n 8634,\n 8120,\n 62,\n 17614,\n 62,\n 20373,\n 4943,\n 198,\n 92,\n 198,\n 198,\n 7061,\n 6,\n 198,\n 4805,\n 3913,\n 43,\n 62,\n 28480,\n 51,\n 20754,\n 796,\n 1391,\n 198,\n 220,\n 220,\n 220,\n 705,\n 49336,\n 10354,\n 657,\n 198,\n 220,\n 220,\n 220,\n 705,\n 31438,\n 10354,\n 705,\n 404,\n 437,\n 3935,\n 6,\n 198,\n 92,\n 198,\n 7061,\n 6,\n 198,\n 198,\n 35,\n 1404,\n 6242,\n 1921,\n 1546,\n 796,\n 1391,\n 198,\n 220,\n 220,\n 220,\n 705,\n 12286,\n 10354,\n 1391,\n 198,\n 220,\n 220,\n 220,\n 220,\n 220,\n 220,\n 220,\n 705,\n 26808,\n 8881,\n 10354,\n 28686,\n 13,\n 1136,\n 24330,\n 10786,\n 3185,\n 10619,\n 3843,\n 56,\n 62,\n 35,\n 1404,\n 6242,\n 11159,\n 62,\n 26808,\n 8881,\n 3256,\n 705,\n 28241,\n 14208,\n 13,\n 9945,\n 13,\n 1891,\n 2412,\n 13,\n 28744,\n 13976,\n 33809,\n 198,\n 220,\n 220,\n 220,\n 220,\n 220,\n 220,\n 220,\n 705,\n 20608,\n 10354,\n 28686,\n 13,\n 1136,\n 24330,\n 10786,\n 3185,\n 10619,\n 3843,\n 56,\n 62,\n 35,\n 1404,\n 6242,\n 11159,\n 62,\n 20608,\n 3256,\n 705,\n 404,\n 437,\n 3935,\n 33809,\n 198,\n 220,\n 220,\n 220,\n 220,\n 220,\n 220,\n 220,\n 705,\n 29904,\n 10354,\n 28686,\n 13,\n 1136,\n 24330,\n 10786,\n 3185,\n 10619,\n 3843,\n 56,\n 62,\n 35,\n 1404,\n 6242,\n 11159,\n 62,\n 29904,\n 3256,\n 705,\n 404,\n 437,\n 3935,\n 33809,\n 198,\n 220,\n 220,\n 220,\n 220,\n 220,\n 220,\n 220,\n 705,\n 47924,\n 54,\n 12532,\n 10354,\n 28686,\n 13,\n 1136,\n 24330,\n 10786,\n 3185,\n 10619,\n 3843,\n 56,\n 62,\n 35,\n 1404,\n 6242,\n 11159,\n 62,\n 47924,\n 3256,\n 705,\n 26278,\n 5787,\n 33809,\n 198,\n 220,\n 220,\n 220,\n 220,\n 220,\n 220,\n 220,\n 705,\n 39,\n 10892,\n 10354,\n 28686,\n 13,\n 1136,\n 24330,\n 10786,\n 3185,\n 10619,\n 3843,\n 56,\n 62,\n 35,\n 1404,\n 6242,\n 11159,\n 62,\n 39,\n 10892,\n 3256,\n 705,\n 9945,\n 33809,\n 198,\n 220,\n 220,\n 220,\n 220,\n 220,\n 220,\n 220,\n 705,\n 15490,\n 10354,\n 28686,\n 13,\n 1136,\n 24330,\n 10786,\n 3185,\n 10619,\n 3843,\n 56,\n 62,\n 35,\n 1404,\n 6242,\n 11159,\n 62,\n 15490,\n 3256,\n 705,\n 18,\n 20548,\n 11537,\n 198,\n 220,\n 220,\n 220,\n 1782,\n 198,\n 92,\n 198,\n 198,\n 2,\n 10729,\n 4261,\n 9050,\n 39410,\n 25,\n 1394,\n 262,\n 3200,\n 1994,\n 973,\n 287,\n 3227,\n 3200,\n 0,\n 198,\n 23683,\n 26087,\n 62,\n 20373,\n 796,\n 28686,\n 13,\n 1136,\n 24330,\n 10786,\n 3185,\n 10619,\n 3843,\n 56,\n 62,\n 23683,\n 26087,\n 62,\n 20373,\n 3256,\n 705,\n 14108,\n 21078,\n 2539,\n 11537,\n 198,\n 198,\n 7036,\n 3913,\n 1961,\n 62,\n 39,\n 10892,\n 50,\n 796,\n 37250,\n 14108,\n 13,\n 26278,\n 5787,\n 13,\n 4774,\n 20520,\n 198,\n 198,\n 30531,\n 796,\n 28686,\n 13,\n 1136,\n 24330,\n 10786,\n 3185,\n 10619,\n 3843,\n 56,\n 62,\n 30531,\n 3256,\n 10352,\n 8,\n 198,\n 51,\n 3620,\n 6489,\n 6158,\n 62,\n 30531,\n 796,\n 28686,\n 13,\n 1136,\n 24330,\n 10786,\n 3185,\n 10619,\n 3843,\n 56,\n 62,\n 51,\n 3620,\n 6489,\n 6158,\n 62,\n 30531,\n 3256,\n 10352,\n 8,\n 198\n]"},"ratio_char_token":{"kind":"number","value":2.086782376502003,"string":"2.086782"},"token_count":{"kind":"number","value":749,"string":"749"}}},{"rowIdx":1258,"cells":{"content":{"kind":"string","value":"# Conventional Machine Learning Algorithms\n# Test Script for Class of \"NaiveBayes\".\n# Author: Qixun Qu\n# Create on: 2018/04/24\n# Modify on: 2018/04/25\n\n# ,,, ,,,\n# ;\" '; ;' \",\n# ; @.ss$$$$$$s.@ ;\n# `s$$$$$$$$$$$$$$$'\n# $$$$$$$$$$$$$$$$$$\n# $$$$P\"\"Y$$$Y\"\"W$$$$$\n# $$$$ p\"$$$\"q $$$$$\n# $$$$ .$$$$$. $$$$'\n# $$$DaU$$O$$DaU$$$'\n# '$$$$'.^.'$$$$'\n# '&$$$$$&'\n\n\nfrom __future__ import division\nfrom __future__ import print_function\n\n\nfrom utils import *\nfrom NaiveBayes import *\nfrom sklearn.datasets import make_hastie_10_2\n\n\n# Basic settings\nrandom_state = 9527\nn_samples = 10000\ntest_size = 0.2\n\n\n# Generate Dataset for training and testing\n# Obtain all samples\nX, y = make_hastie_10_2(n_samples=n_samples,\n random_state=random_state)\n# Split dataset\nX_train, y_train, X_test, y_test = split_dataset(X, y, test_size,\n random_state)\n# Normalize dataset\nX_train_scaled, X_test_scaled = scale_dataset(X_train, X_test)\n\n\n# Train Gaussian Naive Bayes Classifier\nnb = NaiveBayes(alpha=1)\nnb.fit(X_train_scaled, y_train, cont_feat_idx=\"all\")\n\n# Predict test set and evaluate results\ny_pred = nb.predict(X_test_scaled)\nprint(\"Accuracy of test set:\", accuracy(y_pred, y_test))\n# Accuracy can reach 0.9765.\n"},"input_ids":{"kind":"list like","value":[2,1482,20405,10850,18252,978,7727,907,198,2,6208,12327,329,5016,286,366,26705,425,15262,274,1911,198,2,6434,25,1195,844,403,2264,198,2,13610,319,25,2864,14,3023,14,1731,198,2,3401,1958,319,25,2864,14,3023,14,1495,198,198,2,220,220,220,220,837,9832,220,220,220,220,220,220,220,220,837,9832,198,2,220,220,2162,1,220,220,705,26,220,220,220,220,2162,6,220,220,33172,198,2,220,220,2162,220,2488,13,824,36737,13702,82,13,31,220,2162,198,2,220,220,4600,82,36737,36737,36737,13702,3,6,198,2,220,220,720,36737,36737,36737,36737,3,198,2,220,720,13702,3,47,15931,56,13702,3,56,15931,54,36737,3,198,2,220,720,13702,3,220,279,1,13702,3,1,80,220,720,36737,198,2,220,720,13702,3,220,764,36737,35307,220,720,13702,3,6,198,2,220,220,720,13702,26531,52,13702,46,13702,26531,52,13702,3,6,198,2,220,220,220,705,36737,4458,61,2637,36737,6,198,2,220,220,220,220,220,220,705,5,36737,3,5,6,628,198,6738,11593,37443,834,1330,7297,198,6738,11593,37443,834,1330,3601,62,8818,628,198,6738,3384,4487,1330,1635,198,6738,11013,425,15262,274,1330,1635,198,6738,1341,35720,13,19608,292,1039,1330,787,62,71,459,494,62,940,62,17,628,198,2,14392,6460,198,25120,62,5219,796,6957,1983,198,77,62,82,12629,796,33028,198,9288,62,7857,796,657,13,17,628,198,2,2980,378,16092,292,316,329,3047,290,4856,198,2,1835,3153,477,8405,198,55,11,331,796,787,62,71,459,494,62,940,62,17,7,77,62,82,12629,28,77,62,82,12629,11,198,220,220,220,220,220,220,220,220,220,220,220,220,220,220,220,220,220,220,220,220,220,220,220,4738,62,5219,28,25120,62,5219,8,198,2,27758,27039,198,55,62,27432,11,331,62,27432,11,1395,62,9288,11,331,62,9288,796,6626,62,19608,292,316,7,55,11,331,11,1332,62,7857,11,198,220,220,220,220,220,220,220,220,220,220,220,220,220,220,220,220,220,220,220,220,220,220,220,220,220,220,220,220,220,220,220,220,220,220,220,220,220,220,220,220,220,220,220,220,220,220,220,220,4738,62,5219,8,198,2,14435,1096,27039,198,55,62,27432,62,1416,3021,11,1395,62,9288,62,1416,3021,796,5046,62,19608,292,316,7,55,62,27432,11,1395,62,9288,8,628,198,2,16835,12822,31562,11013,425,4696,274,5016,7483,198,46803,796,11013,425,15262,274,7,26591,28,16,8,198,46803,13,11147,7,55,62,27432,62,1416,3021,11,331,62,27432,11,542,62,27594,62,312,87,2625,439,4943,198,198,2,49461,1332,900,290,13446,2482,198,88,62,28764,796,299,65,13,79,17407,7,55,62,9288,62,1416,3021,8,198,4798,7203,17320,23843,286,1332,900,25,1600,9922,7,88,62,28764,11,331,62,9288,4008,198,2,33222,460,3151,657,13,5607,2996,13,198],"string":"[\n 2,\n 1482,\n 20405,\n 10850,\n 18252,\n 978,\n 7727,\n 907,\n 198,\n 2,\n 6208,\n 12327,\n 329,\n 5016,\n 286,\n 366,\n 26705,\n 425,\n 15262,\n 274,\n 1911,\n 198,\n 2,\n 6434,\n 25,\n 1195,\n 844,\n 403,\n 2264,\n 198,\n 2,\n 13610,\n 319,\n 25,\n 2864,\n 14,\n 3023,\n 14,\n 1731,\n 198,\n 2,\n 3401,\n 1958,\n 319,\n 25,\n 2864,\n 14,\n 3023,\n 14,\n 1495,\n 198,\n 198,\n 2,\n 220,\n 220,\n 220,\n 220,\n 837,\n 9832,\n 220,\n 220,\n 220,\n 220,\n 220,\n 220,\n 220,\n 220,\n 837,\n 9832,\n 198,\n 2,\n 220,\n 220,\n 2162,\n 1,\n 220,\n 220,\n 705,\n 26,\n 220,\n 220,\n 220,\n 220,\n 2162,\n 6,\n 220,\n 220,\n 33172,\n 198,\n 2,\n 220,\n 220,\n 2162,\n 220,\n 2488,\n 13,\n 824,\n 36737,\n 13702,\n 82,\n 13,\n 31,\n 220,\n 2162,\n 198,\n 2,\n 220,\n 220,\n 4600,\n 82,\n 36737,\n 36737,\n 36737,\n 13702,\n 3,\n 6,\n 198,\n 2,\n 220,\n 220,\n 720,\n 36737,\n 36737,\n 36737,\n 36737,\n 3,\n 198,\n 2,\n 220,\n 720,\n 13702,\n 3,\n 47,\n 15931,\n 56,\n 13702,\n 3,\n 56,\n 15931,\n 54,\n 36737,\n 3,\n 198,\n 2,\n 220,\n 720,\n 13702,\n 3,\n 220,\n 279,\n 1,\n 13702,\n 3,\n 1,\n 80,\n 220,\n 720,\n 36737,\n 198,\n 2,\n 220,\n 720,\n 13702,\n 3,\n 220,\n 764,\n 36737,\n 35307,\n 220,\n 720,\n 13702,\n 3,\n 6,\n 198,\n 2,\n 220,\n 220,\n 720,\n 13702,\n 26531,\n 52,\n 13702,\n 46,\n 13702,\n 26531,\n 52,\n 13702,\n 3,\n 6,\n 198,\n 2,\n 220,\n 220,\n 220,\n 705,\n 36737,\n 4458,\n 61,\n 2637,\n 36737,\n 6,\n 198,\n 2,\n 220,\n 220,\n 220,\n 220,\n 220,\n 220,\n 705,\n 5,\n 36737,\n 3,\n 5,\n 6,\n 628,\n 198,\n 6738,\n 11593,\n 37443,\n 834,\n 1330,\n 7297,\n 198,\n 6738,\n 11593,\n 37443,\n 834,\n 1330,\n 3601,\n 62,\n 8818,\n 628,\n 198,\n 6738,\n 3384,\n 4487,\n 1330,\n 1635,\n 198,\n 6738,\n 11013,\n 425,\n 15262,\n 274,\n 1330,\n 1635,\n 198,\n 6738,\n 1341,\n 35720,\n 13,\n 19608,\n 292,\n 1039,\n 1330,\n 787,\n 62,\n 71,\n 459,\n 494,\n 62,\n 940,\n 62,\n 17,\n 628,\n 198,\n 2,\n 14392,\n 6460,\n 198,\n 25120,\n 62,\n 5219,\n 796,\n 6957,\n 1983,\n 198,\n 77,\n 62,\n 82,\n 12629,\n 796,\n 33028,\n 198,\n 9288,\n 62,\n 7857,\n 796,\n 657,\n 13,\n 17,\n 628,\n 198,\n 2,\n 2980,\n 378,\n 16092,\n 292,\n 316,\n 329,\n 3047,\n 290,\n 4856,\n 198,\n 2,\n 1835,\n 3153,\n 477,\n 8405,\n 198,\n 55,\n 11,\n 331,\n 796,\n 787,\n 62,\n 71,\n 459,\n 494,\n 62,\n 940,\n 62,\n 17,\n 7,\n 77,\n 62,\n 82,\n 12629,\n 28,\n 77,\n 62,\n 82,\n 12629,\n 11,\n 198,\n 220,\n 220,\n 220,\n 220,\n 220,\n 220,\n 220,\n 220,\n 220,\n 220,\n 220,\n 220,\n 220,\n 220,\n 220,\n 220,\n 220,\n 220,\n 220,\n 220,\n 220,\n 220,\n 220,\n 4738,\n 62,\n 5219,\n 28,\n 25120,\n 62,\n 5219,\n 8,\n 198,\n 2,\n 27758,\n 27039,\n 198,\n 55,\n 62,\n 27432,\n 11,\n 331,\n 62,\n 27432,\n 11,\n 1395,\n 62,\n 9288,\n 11,\n 331,\n 62,\n 9288,\n 796,\n 6626,\n 62,\n 19608,\n 292,\n 316,\n 7,\n 55,\n 11,\n 331,\n 11,\n 1332,\n 62,\n 7857,\n 11,\n 198,\n 220,\n 220,\n 220,\n 220,\n 220,\n 220,\n 220,\n 220,\n 220,\n 220,\n 220,\n 220,\n 220,\n 220,\n 220,\n 220,\n 220,\n 220,\n 220,\n 220,\n 220,\n 220,\n 220,\n 220,\n 220,\n 220,\n 220,\n 220,\n 220,\n 220,\n 220,\n 220,\n 220,\n 220,\n 220,\n 220,\n 220,\n 220,\n 220,\n 220,\n 220,\n 220,\n 220,\n 220,\n 220,\n 220,\n 220,\n 220,\n 4738,\n 62,\n 5219,\n 8,\n 198,\n 2,\n 14435,\n 1096,\n 27039,\n 198,\n 55,\n 62,\n 27432,\n 62,\n 1416,\n 3021,\n 11,\n 1395,\n 62,\n 9288,\n 62,\n 1416,\n 3021,\n 796,\n 5046,\n 62,\n 19608,\n 292,\n 316,\n 7,\n 55,\n 62,\n 27432,\n 11,\n 1395,\n 62,\n 9288,\n 8,\n 628,\n 198,\n 2,\n 16835,\n 12822,\n 31562,\n 11013,\n 425,\n 4696,\n 274,\n 5016,\n 7483,\n 198,\n 46803,\n 796,\n 11013,\n 425,\n 15262,\n 274,\n 7,\n 26591,\n 28,\n 16,\n 8,\n 198,\n 46803,\n 13,\n 11147,\n 7,\n 55,\n 62,\n 27432,\n 62,\n 1416,\n 3021,\n 11,\n 331,\n 62,\n 27432,\n 11,\n 542,\n 62,\n 27594,\n 62,\n 312,\n 87,\n 2625,\n 439,\n 4943,\n 198,\n 198,\n 2,\n 49461,\n 1332,\n 900,\n 290,\n 13446,\n 2482,\n 198,\n 88,\n 62,\n 28764,\n 796,\n 299,\n 65,\n 13,\n 79,\n 17407,\n 7,\n 55,\n 62,\n 9288,\n 62,\n 1416,\n 3021,\n 8,\n 198,\n 4798,\n 7203,\n 17320,\n 23843,\n 286,\n 1332,\n 900,\n 25,\n 1600,\n 9922,\n 7,\n 88,\n 62,\n 28764,\n 11,\n 331,\n 62,\n 9288,\n 4008,\n 198,\n 2,\n 33222,\n 460,\n 3151,\n 657,\n 13,\n 5607,\n 2996,\n 13,\n 198\n]"},"ratio_char_token":{"kind":"number","value":2.203020134228188,"string":"2.20302"},"token_count":{"kind":"number","value":596,"string":"596"}}},{"rowIdx":1259,"cells":{"content":{"kind":"string","value":"from Bridge import Proxy2Server\nimport os\nfrom DataTypes import Packet, A_Packet_Class\nfrom DataTypes import VarInt, Output_Streamer, Bytes_Streamer, Socket_Streamer\nimport time\n\n\noutput = Output_Streamer()\n\ninput = Bytes_Streamer()\n\nlogin_packets = A_Packet_Class()\n\nSOCK = Socket_Streamer('connect.2b2t.org', 25565, login_packets)\n\nhandshake = Packet(login_packets)\nhandshake.set(['VarInt', 'VarInt', 'String', 'Ushort', 'VarInt'])\n\nstatus = Packet(login_packets)\nstatus.set(['VarInt', 'String'])\n\nrequest = Packet(login_packets)\nrequest.set(['VarInt'])\n\nping_pong = Packet(login_packets)\nping_pong.set(['VarInt', 'Long'])\n\nencryption_req = Packet(login_packets)\nencryption_req.set(['VarInt', 'String', 'String', 'String'])\n\nencryption_res = Packet(login_packets)\nencryption_res.set(['VarInt', 'String', 'String'])\n\nlogin_success = Packet(login_packets)\nlogin_success.set(['VarInt', 'String', 'String'])\n\nset_compression = Packet(login_packets)\nset_compression.set(['VarInt', 'VarInt'])\n\nlogin_packets.map_pack(pack_0)\nlogin_packets.map_unpack(unpack_0)\n\n\n\n\n# data = handshake.pack([0x00, 340, b'2b2t.org', 25565, 1])\n# server_sock.write(data)\n# data = request.pack([0x00])\n# server_sock.write(data)\n\n# status.unpack(server_sock, output)\n\ninput.write(handshake.pack([0x00, 340, b'2b2t.org', 25565, 2]))\n\nSOCK.write(input)\n\ninput.write(status.pack([0x00, b'ThBlitz']))\n\nSOCK.write(input)\n\nSOCK.read(input)\n\nencryption_req.unpack(input, output)\n\nprint(f'encryption_req : {output.getvalue()}')\n\ndata = output.getvalue()\nlogin_packets.server_id = data[1]\nlogin_packets.server_public_key = data[2]\nlogin_packets.verification_token = data[3]\n\nimport secrets\nlogin_packets.aes_key = secrets.randbits(128).to_bytes(16, 'big')\n\nhash , ver_token , shared_secret = login_packets.get_hash()\n\nimport mojang_api\nuuid , name , token , login_data = mojang_api.login_through_microsoft()\nres = mojang_api.join_server(token, uuid, hash)\nprint(f'response from mojang : {res}')\n\ninput.reset()\ninput.write(encryption_res.pack([0x01, shared_secret, ver_token]))\n\nSOCK.write(input)\n\nlogin_packets.encryption_enabled = True\n\nSOCK.read(input)\n\nset_compression.unpack(input, output)\n\nlogin_packets.compression_threshold = output.getvalue()[1]\nlogin_packets.compression_enabled = True\n\nprint(f'compression_packet : {output.getvalue()}')\n\nSOCK.read(input)\n\nlogin_success.unpack(input, output)\n\nprint(f'login_success : {output.getvalue()}')\n\nSOCK.read(input)\n\nstatus.unpack(input, output)\nprint(input.getvalue())\n\nwhile True:\n SOCK.read(input)\n print(hex(VarInt.unpack(input)))\n print(input.read())\n time.sleep(1)\n\n\n\n\n\n\n\n\n\n# t\n"},"input_ids":{"kind":"list like","value":[6738,10290,1330,38027,17,10697,198,11748,28686,198,6738,6060,31431,1330,6400,316,11,317,62,47,8317,62,9487,198,6738,6060,31431,1330,12372,5317,11,25235,62,28696,11,2750,4879,62,28696,11,47068,62,28696,198,11748,640,628,198,22915,796,25235,62,28696,3419,198,198,15414,796,2750,4879,62,28696,3419,198,198,38235,62,8002,1039,796,317,62,47,8317,62,9487,3419,198,198,50,11290,796,47068,62,28696,10786,8443,13,17,65,17,83,13,2398,3256,14280,2996,11,17594,62,8002,1039,8,198,198,4993,32431,796,6400,316,7,38235,62,8002,1039,8,198,4993,32431,13,2617,7,17816,19852,5317,3256,705,19852,5317,3256,705,10100,3256,705,52,19509,3256,705,19852,5317,6,12962,198,198,13376,796,6400,316,7,38235,62,8002,1039,8,198,13376,13,2617,7,17816,19852,5317,3256,705,10100,6,12962,198,198,25927,796,6400,316,7,38235,62,8002,1039,8,198,25927,13,2617,7,17816,19852,5317,6,12962,198,198,13886,62,79,506,796,6400,316,7,38235,62,8002,1039,8,198,13886,62,79,506,13,2617,7,17816,19852,5317,3256,705,14617,6,12962,198,198,12685,13168,62,42180,796,6400,316,7,38235,62,8002,1039,8,198,12685,13168,62,42180,13,2617,7,17816,19852,5317,3256,705,10100,3256,705,10100,3256,705,10100,6,12962,198,198,12685,13168,62,411,796,6400,316,7,38235,62,8002,1039,8,198,12685,13168,62,411,13,2617,7,17816,19852,5317,3256,705,10100,3256,705,10100,6,12962,198,198,38235,62,13138,796,6400,316,7,38235,62,8002,1039,8,198,38235,62,13138,13,2617,7,17816,19852,5317,3256,705,10100,3256,705,10100,6,12962,198,198,2617,62,5589,2234,796,6400,316,7,38235,62,8002,1039,8,198,2617,62,5589,2234,13,2617,7,17816,19852,5317,3256,705,19852,5317,6,12962,198,198,38235,62,8002,1039,13,8899,62,8002,7,8002,62,15,8,198,38235,62,8002,1039,13,8899,62,403,8002,7,403,8002,62,15,8,628,628,198,2,1366,796,42231,13,8002,26933,15,87,405,11,28560,11,275,6,17,65,17,83,13,2398,3256,14280,2996,11,352,12962,198,2,4382,62,82,735,13,13564,7,7890,8,198,2,1366,796,2581,13,8002,26933,15,87,405,12962,198,2,4382,62,82,735,13,13564,7,7890,8,198,198,2,3722,13,403,8002,7,15388,62,82,735,11,5072,8,198,198,15414,13,13564,7,4993,32431,13,8002,26933,15,87,405,11,28560,11,275,6,17,65,17,83,13,2398,3256,14280,2996,11,362,60,4008,198,198,50,11290,13,13564,7,15414,8,198,198,15414,13,13564,7,13376,13,8002,26933,15,87,405,11,275,6,817,3629,4224,20520,4008,198,198,50,11290,13,13564,7,15414,8,198,198,50,11290,13,961,7,15414,8,198,198,12685,13168,62,42180,13,403,8002,7,15414,11,5072,8,198,198,4798,7,69,6,12685,13168,62,42180,1058,1391,22915,13,1136,8367,3419,92,11537,198,198,7890,796,5072,13,1136,8367,3419,198,38235,62,8002,1039,13,15388,62,312,796,1366,58,16,60,198,38235,62,8002,1039,13,15388,62,11377,62,2539,796,1366,58,17,60,198,38235,62,8002,1039,13,332,2649,62,30001,796,1366,58,18,60,198,198,11748,13141,198,38235,62,8002,1039,13,64,274,62,2539,796,13141,13,25192,9895,7,12762,737,1462,62,33661,7,1433,11,705,14261,11537,198,198,17831,837,3326,62,30001,837,4888,62,21078,796,17594,62,8002,1039,13,1136,62,17831,3419,198,198,11748,6941,73,648,62,15042,198,12303,312,837,1438,837,11241,837,17594,62,7890,796,6941,73,648,62,15042,13,38235,62,9579,62,40485,3419,198,411,796,6941,73,648,62,15042,13,22179,62,15388,7,30001,11,334,27112,11,12234,8,198,4798,7,69,821,2777,2591,422,6941,73,648,1058,1391,411,92,11537,198,198,15414,13,42503,3419,198,15414,13,13564,7,12685,13168,62,411,13,8002,26933,15,87,486,11,4888,62,21078,11,3326,62,30001,60,4008,198,198,50,11290,13,13564,7,15414,8,198,198,38235,62,8002,1039,13,12685,13168,62,25616,796,6407,198,198,50,11290,13,961,7,15414,8,198,198,2617,62,5589,2234,13,403,8002,7,15414,11,5072,8,198,198,38235,62,8002,1039,13,5589,2234,62,400,10126,796,5072,13,1136,8367,3419,58,16,60,198,38235,62,8002,1039,13,5589,2234,62,25616,796,6407,198,198,4798,7,69,6,5589,2234,62,8002,316,1058,1391,22915,13,1136,8367,3419,92,11537,198,198,50,11290,13,961,7,15414,8,198,198,38235,62,13138,13,403,8002,7,15414,11,5072,8,198,198,4798,7,69,6,38235,62,13138,1058,1391,22915,13,1136,8367,3419,92,11537,198,198,50,11290,13,961,7,15414,8,198,198,13376,13,403,8002,7,15414,11,5072,8,198,4798,7,15414,13,1136,8367,28955,198,198,4514,6407,25,198,220,220,220,311,11290,13,961,7,15414,8,198,220,220,220,3601,7,33095,7,19852,5317,13,403,8002,7,15414,22305,198,220,220,220,3601,7,15414,13,961,28955,198,220,220,220,640,13,42832,7,16,8,628,628,628,628,198,198,2,256,198],"string":"[\n 6738,\n 10290,\n 1330,\n 38027,\n 17,\n 10697,\n 198,\n 11748,\n 28686,\n 198,\n 6738,\n 6060,\n 31431,\n 1330,\n 6400,\n 316,\n 11,\n 317,\n 62,\n 47,\n 8317,\n 62,\n 9487,\n 198,\n 6738,\n 6060,\n 31431,\n 1330,\n 12372,\n 5317,\n 11,\n 25235,\n 62,\n 28696,\n 11,\n 2750,\n 4879,\n 62,\n 28696,\n 11,\n 47068,\n 62,\n 28696,\n 198,\n 11748,\n 640,\n 628,\n 198,\n 22915,\n 796,\n 25235,\n 62,\n 28696,\n 3419,\n 198,\n 198,\n 15414,\n 796,\n 2750,\n 4879,\n 62,\n 28696,\n 3419,\n 198,\n 198,\n 38235,\n 62,\n 8002,\n 1039,\n 796,\n 317,\n 62,\n 47,\n 8317,\n 62,\n 9487,\n 3419,\n 198,\n 198,\n 50,\n 11290,\n 796,\n 47068,\n 62,\n 28696,\n 10786,\n 8443,\n 13,\n 17,\n 65,\n 17,\n 83,\n 13,\n 2398,\n 3256,\n 14280,\n 2996,\n 11,\n 17594,\n 62,\n 8002,\n 1039,\n 8,\n 198,\n 198,\n 4993,\n 32431,\n 796,\n 6400,\n 316,\n 7,\n 38235,\n 62,\n 8002,\n 1039,\n 8,\n 198,\n 4993,\n 32431,\n 13,\n 2617,\n 7,\n 17816,\n 19852,\n 5317,\n 3256,\n 705,\n 19852,\n 5317,\n 3256,\n 705,\n 10100,\n 3256,\n 705,\n 52,\n 19509,\n 3256,\n 705,\n 19852,\n 5317,\n 6,\n 12962,\n 198,\n 198,\n 13376,\n 796,\n 6400,\n 316,\n 7,\n 38235,\n 62,\n 8002,\n 1039,\n 8,\n 198,\n 13376,\n 13,\n 2617,\n 7,\n 17816,\n 19852,\n 5317,\n 3256,\n 705,\n 10100,\n 6,\n 12962,\n 198,\n 198,\n 25927,\n 796,\n 6400,\n 316,\n 7,\n 38235,\n 62,\n 8002,\n 1039,\n 8,\n 198,\n 25927,\n 13,\n 2617,\n 7,\n 17816,\n 19852,\n 5317,\n 6,\n 12962,\n 198,\n 198,\n 13886,\n 62,\n 79,\n 506,\n 796,\n 6400,\n 316,\n 7,\n 38235,\n 62,\n 8002,\n 1039,\n 8,\n 198,\n 13886,\n 62,\n 79,\n 506,\n 13,\n 2617,\n 7,\n 17816,\n 19852,\n 5317,\n 3256,\n 705,\n 14617,\n 6,\n 12962,\n 198,\n 198,\n 12685,\n 13168,\n 62,\n 42180,\n 796,\n 6400,\n 316,\n 7,\n 38235,\n 62,\n 8002,\n 1039,\n 8,\n 198,\n 12685,\n 13168,\n 62,\n 42180,\n 13,\n 2617,\n 7,\n 17816,\n 19852,\n 5317,\n 3256,\n 705,\n 10100,\n 3256,\n 705,\n 10100,\n 3256,\n 705,\n 10100,\n 6,\n 12962,\n 198,\n 198,\n 12685,\n 13168,\n 62,\n 411,\n 796,\n 6400,\n 316,\n 7,\n 38235,\n 62,\n 8002,\n 1039,\n 8,\n 198,\n 12685,\n 13168,\n 62,\n 411,\n 13,\n 2617,\n 7,\n 17816,\n 19852,\n 5317,\n 3256,\n 705,\n 10100,\n 3256,\n 705,\n 10100,\n 6,\n 12962,\n 198,\n 198,\n 38235,\n 62,\n 13138,\n 796,\n 6400,\n 316,\n 7,\n 38235,\n 62,\n 8002,\n 1039,\n 8,\n 198,\n 38235,\n 62,\n 13138,\n 13,\n 2617,\n 7,\n 17816,\n 19852,\n 5317,\n 3256,\n 705,\n 10100,\n 3256,\n 705,\n 10100,\n 6,\n 12962,\n 198,\n 198,\n 2617,\n 62,\n 5589,\n 2234,\n 796,\n 6400,\n 316,\n 7,\n 38235,\n 62,\n 8002,\n 1039,\n 8,\n 198,\n 2617,\n 62,\n 5589,\n 2234,\n 13,\n 2617,\n 7,\n 17816,\n 19852,\n 5317,\n 3256,\n 705,\n 19852,\n 5317,\n 6,\n 12962,\n 198,\n 198,\n 38235,\n 62,\n 8002,\n 1039,\n 13,\n 8899,\n 62,\n 8002,\n 7,\n 8002,\n 62,\n 15,\n 8,\n 198,\n 38235,\n 62,\n 8002,\n 1039,\n 13,\n 8899,\n 62,\n 403,\n 8002,\n 7,\n 403,\n 8002,\n 62,\n 15,\n 8,\n 628,\n 628,\n 198,\n 2,\n 1366,\n 796,\n 42231,\n 13,\n 8002,\n 26933,\n 15,\n 87,\n 405,\n 11,\n 28560,\n 11,\n 275,\n 6,\n 17,\n 65,\n 17,\n 83,\n 13,\n 2398,\n 3256,\n 14280,\n 2996,\n 11,\n 352,\n 12962,\n 198,\n 2,\n 4382,\n 62,\n 82,\n 735,\n 13,\n 13564,\n 7,\n 7890,\n 8,\n 198,\n 2,\n 1366,\n 796,\n 2581,\n 13,\n 8002,\n 26933,\n 15,\n 87,\n 405,\n 12962,\n 198,\n 2,\n 4382,\n 62,\n 82,\n 735,\n 13,\n 13564,\n 7,\n 7890,\n 8,\n 198,\n 198,\n 2,\n 3722,\n 13,\n 403,\n 8002,\n 7,\n 15388,\n 62,\n 82,\n 735,\n 11,\n 5072,\n 8,\n 198,\n 198,\n 15414,\n 13,\n 13564,\n 7,\n 4993,\n 32431,\n 13,\n 8002,\n 26933,\n 15,\n 87,\n 405,\n 11,\n 28560,\n 11,\n 275,\n 6,\n 17,\n 65,\n 17,\n 83,\n 13,\n 2398,\n 3256,\n 14280,\n 2996,\n 11,\n 362,\n 60,\n 4008,\n 198,\n 198,\n 50,\n 11290,\n 13,\n 13564,\n 7,\n 15414,\n 8,\n 198,\n 198,\n 15414,\n 13,\n 13564,\n 7,\n 13376,\n 13,\n 8002,\n 26933,\n 15,\n 87,\n 405,\n 11,\n 275,\n 6,\n 817,\n 3629,\n 4224,\n 20520,\n 4008,\n 198,\n 198,\n 50,\n 11290,\n 13,\n 13564,\n 7,\n 15414,\n 8,\n 198,\n 198,\n 50,\n 11290,\n 13,\n 961,\n 7,\n 15414,\n 8,\n 198,\n 198,\n 12685,\n 13168,\n 62,\n 42180,\n 13,\n 403,\n 8002,\n 7,\n 15414,\n 11,\n 5072,\n 8,\n 198,\n 198,\n 4798,\n 7,\n 69,\n 6,\n 12685,\n 13168,\n 62,\n 42180,\n 1058,\n 1391,\n 22915,\n 13,\n 1136,\n 8367,\n 3419,\n 92,\n 11537,\n 198,\n 198,\n 7890,\n 796,\n 5072,\n 13,\n 1136,\n 8367,\n 3419,\n 198,\n 38235,\n 62,\n 8002,\n 1039,\n 13,\n 15388,\n 62,\n 312,\n 796,\n 1366,\n 58,\n 16,\n 60,\n 198,\n 38235,\n 62,\n 8002,\n 1039,\n 13,\n 15388,\n 62,\n 11377,\n 62,\n 2539,\n 796,\n 1366,\n 58,\n 17,\n 60,\n 198,\n 38235,\n 62,\n 8002,\n 1039,\n 13,\n 332,\n 2649,\n 62,\n 30001,\n 796,\n 1366,\n 58,\n 18,\n 60,\n 198,\n 198,\n 11748,\n 13141,\n 198,\n 38235,\n 62,\n 8002,\n 1039,\n 13,\n 64,\n 274,\n 62,\n 2539,\n 796,\n 13141,\n 13,\n 25192,\n 9895,\n 7,\n 12762,\n 737,\n 1462,\n 62,\n 33661,\n 7,\n 1433,\n 11,\n 705,\n 14261,\n 11537,\n 198,\n 198,\n 17831,\n 837,\n 3326,\n 62,\n 30001,\n 837,\n 4888,\n 62,\n 21078,\n 796,\n 17594,\n 62,\n 8002,\n 1039,\n 13,\n 1136,\n 62,\n 17831,\n 3419,\n 198,\n 198,\n 11748,\n 6941,\n 73,\n 648,\n 62,\n 15042,\n 198,\n 12303,\n 312,\n 837,\n 1438,\n 837,\n 11241,\n 837,\n 17594,\n 62,\n 7890,\n 796,\n 6941,\n 73,\n 648,\n 62,\n 15042,\n 13,\n 38235,\n 62,\n 9579,\n 62,\n 40485,\n 3419,\n 198,\n 411,\n 796,\n 6941,\n 73,\n 648,\n 62,\n 15042,\n 13,\n 22179,\n 62,\n 15388,\n 7,\n 30001,\n 11,\n 334,\n 27112,\n 11,\n 12234,\n 8,\n 198,\n 4798,\n 7,\n 69,\n 821,\n 2777,\n 2591,\n 422,\n 6941,\n 73,\n 648,\n 1058,\n 1391,\n 411,\n 92,\n 11537,\n 198,\n 198,\n 15414,\n 13,\n 42503,\n 3419,\n 198,\n 15414,\n 13,\n 13564,\n 7,\n 12685,\n 13168,\n 62,\n 411,\n 13,\n 8002,\n 26933,\n 15,\n 87,\n 486,\n 11,\n 4888,\n 62,\n 21078,\n 11,\n 3326,\n 62,\n 30001,\n 60,\n 4008,\n 198,\n 198,\n 50,\n 11290,\n 13,\n 13564,\n 7,\n 15414,\n 8,\n 198,\n 198,\n 38235,\n 62,\n 8002,\n 1039,\n 13,\n 12685,\n 13168,\n 62,\n 25616,\n 796,\n 6407,\n 198,\n 198,\n 50,\n 11290,\n 13,\n 961,\n 7,\n 15414,\n 8,\n 198,\n 198,\n 2617,\n 62,\n 5589,\n 2234,\n 13,\n 403,\n 8002,\n 7,\n 15414,\n 11,\n 5072,\n 8,\n 198,\n 198,\n 38235,\n 62,\n 8002,\n 1039,\n 13,\n 5589,\n 2234,\n 62,\n 400,\n 10126,\n 796,\n 5072,\n 13,\n 1136,\n 8367,\n 3419,\n 58,\n 16,\n 60,\n 198,\n 38235,\n 62,\n 8002,\n 1039,\n 13,\n 5589,\n 2234,\n 62,\n 25616,\n 796,\n 6407,\n 198,\n 198,\n 4798,\n 7,\n 69,\n 6,\n 5589,\n 2234,\n 62,\n 8002,\n 316,\n 1058,\n 1391,\n 22915,\n 13,\n 1136,\n 8367,\n 3419,\n 92,\n 11537,\n 198,\n 198,\n 50,\n 11290,\n 13,\n 961,\n 7,\n 15414,\n 8,\n 198,\n 198,\n 38235,\n 62,\n 13138,\n 13,\n 403,\n 8002,\n 7,\n 15414,\n 11,\n 5072,\n 8,\n 198,\n 198,\n 4798,\n 7,\n 69,\n 6,\n 38235,\n 62,\n 13138,\n 1058,\n 1391,\n 22915,\n 13,\n 1136,\n 8367,\n 3419,\n 92,\n 11537,\n 198,\n 198,\n 50,\n 11290,\n 13,\n 961,\n 7,\n 15414,\n 8,\n 198,\n 198,\n 13376,\n 13,\n 403,\n 8002,\n 7,\n 15414,\n 11,\n 5072,\n 8,\n 198,\n 4798,\n 7,\n 15414,\n 13,\n 1136,\n 8367,\n 28955,\n 198,\n 198,\n 4514,\n 6407,\n 25,\n 198,\n 220,\n 220,\n 220,\n 311,\n 11290,\n 13,\n 961,\n 7,\n 15414,\n 8,\n 198,\n 220,\n 220,\n 220,\n 3601,\n 7,\n 33095,\n 7,\n 19852,\n 5317,\n 13,\n 403,\n 8002,\n 7,\n 15414,\n 22305,\n 198,\n 220,\n 220,\n 220,\n 3601,\n 7,\n 15414,\n 13,\n 961,\n 28955,\n 198,\n 220,\n 220,\n 220,\n 640,\n 13,\n 42832,\n 7,\n 16,\n 8,\n 628,\n 628,\n 628,\n 628,\n 198,\n 198,\n 2,\n 256,\n 198\n]"},"ratio_char_token":{"kind":"number","value":2.5851485148514852,"string":"2.585149"},"token_count":{"kind":"number","value":1010,"string":"1,010"}}},{"rowIdx":1260,"cells":{"content":{"kind":"string","value":"# -*- coding: utf-8 -*-\n\"\"\"\nCreated on Wed Mar 17 13:35:39 2021\n\n@author: ejgen\n\n------ What is this file? ------\n\nThis script targets the files goodreads_reviews_cleaned.csv and\nreview_sentences_analyzed.csv, calculating summary statistics such as\nreview length and sentiment score.\n\nThis script targets the following files:\n ../../data/cleaned/goodreads_reviews_cleaned.csv\n ../../data/analysis_results/review_sentences_analyzed.csv\n \nThe resulting csv file is located at:\n ../../data/analysis_results/goodreads_reviews_analyzed.csv\n \n\"\"\"\n#%% --- Import required packages ---\n\nimport os\n\nfrom pathlib import Path # To wrap around filepaths\nimport pandas as pd\n\n#%% --- Set proper directory to assure integration with doit ---\n\nabspath = os.path.abspath(__file__)\ndname = os.path.dirname(abspath)\nos.chdir(dname)\n\n#%% --- Import data ---\n\n#goodreads_reviews_cleaned\nimport_fp = Path(\"../../data/cleaned/goodreads_reviews_cleaned.csv\")\ngoodreads_reviews = pd.read_csv(import_fp, encoding = \"utf-8\", index_col = False)\n\n#review_sentences_analyzed\nimport_fp = Path(\"../../data/analysis_results/review_sentences_analyzed.csv\")\nsentences_analyzed = pd.read_csv(import_fp, encoding = \"utf-8\")\n\n#%% --- Prepare data ---\n\nsentences_analyzed = sentences_analyzed.loc[:,[\"review_id\",\n \"sentence_id\",\n \"sent_mentions_original\",\n \"sent_mentions_trans\",\n \"length_in_words\",\n \"VADER_score_compound\"]]\n\n# Take a subset of goodreads reviews to include only reviews whose review no\n# appear in sentences_analyzed.\n\nrid_mask = goodreads_reviews[\"review_id\"].isin(sentences_analyzed[\"review_id\"])\ngoodreads_reviews = goodreads_reviews.loc[rid_mask, :]\n#%% --- Analyze: review length in sentences and words. ---\n\nlength_per_review = (sentences_analyzed\n .groupby(\"review_id\")\n [\"length_in_words\"]\n .agg([\"sum\",\"count\"])\n .rename({\"sum\" : \"total_length_in_words\",\n \"count\" : \"total_length_in_sentences\"},\n axis = 1))\n\ngoodreads_reviews = (goodreads_reviews\n .merge(length_per_review,\n how = \"left\",\n on = \"review_id\"))\n\n#%% --- Analyze: mention ratios for explicit translation/author mentions\n\norig_mention_mask = sentences_analyzed[\"sent_mentions_original\"] == True\ntrans_mention_mask = sentences_analyzed[\"sent_mentions_trans\"] == True\nonly_orig_mention_mask = (orig_mention_mask & ~trans_mention_mask)\nonly_trans_mention_mask = (~orig_mention_mask & trans_mention_mask)\nboth_mention_mask = (orig_mention_mask & trans_mention_mask)\n\nmasks = {\"share_of_only_trans_mentions\" : only_trans_mention_mask,\n \"share_of_trans_mentions\" : trans_mention_mask,\n \"share_of_only_orig_mentions\": only_orig_mention_mask,\n \"share_of_orig_mentions\": orig_mention_mask}\n\nfor prefix, mask in masks.items():\n calc = (sentences_analyzed[mask].\n groupby(\"review_id\")\n [\"length_in_words\"]\n .agg([\"count\"])\n .rename({\"count\": prefix},\n axis = 1)\n .reset_index())\n \n goodreads_reviews = (goodreads_reviews.merge(calc,\n how = \"left\",\n on = \"review_id\")\n .fillna(value = 0,\n axis = 0))\n \n goodreads_reviews[prefix] = ((goodreads_reviews[prefix]\n / goodreads_reviews[\"total_length_in_sentences\"])\n * 100)\n \n#%% --- Analyze: VADER score for the whole review ---\n\nVADER_score_per_review = (sentences_analyzed\n .groupby(\"review_id\")\n [\"VADER_score_compound\"]\n .agg([\"sum\",\"count\"])\n .reset_index())\n\nVADER_score_per_review[\"avg_VADER_score\"] = (VADER_score_per_review[\"sum\"]\n / VADER_score_per_review[\"count\"])\n\nVADER_score_per_review = VADER_score_per_review.drop(labels = [\"sum\",\"count\"],\n axis = \"columns\")\n\ngoodreads_reviews = goodreads_reviews.merge(VADER_score_per_review,\n how = \"left\",\n on = \"review_id\")\n\n#%% --- Export data ---\n\nexport_fp = Path(\"../../data/analysis_results/goodreads_reviews_analyzed.csv\")\ngoodreads_reviews.to_csv(export_fp, encoding = \"utf-8\", index = False)\n"},"input_ids":{"kind":"list like","value":[2,532,9,12,19617,25,3384,69,12,23,532,9,12,198,37811,198,41972,319,3300,1526,1596,1511,25,2327,25,2670,33448,198,198,31,9800,25,304,73,5235,198,198,23031,1867,318,428,2393,30,40103,198,198,1212,4226,6670,262,3696,922,40779,62,19023,82,62,2375,22739,13,40664,290,198,19023,62,34086,3007,62,38200,8863,13,40664,11,26019,10638,7869,884,355,198,19023,4129,290,15598,4776,13,198,198,1212,4226,6670,262,1708,3696,25,198,220,220,220,11485,14,40720,7890,14,2375,22739,14,11274,40779,62,19023,82,62,2375,22739,13,40664,198,220,220,220,11485,14,40720,7890,14,20930,62,43420,14,19023,62,34086,3007,62,38200,8863,13,40664,198,220,220,220,220,198,464,7186,269,21370,2393,318,5140,379,25,198,220,220,220,11485,14,40720,7890,14,20930,62,43420,14,11274,40779,62,19023,82,62,38200,8863,13,40664,198,220,220,220,220,220,220,220,220,198,37811,198,2,16626,11420,17267,2672,10392,11420,198,198,11748,28686,198,198,6738,3108,8019,1330,10644,1303,1675,14441,1088,2393,6978,82,198,11748,19798,292,355,279,67,198,198,2,16626,11420,5345,1774,8619,284,19832,11812,351,466,270,11420,198,198,397,2777,776,796,28686,13,6978,13,397,2777,776,7,834,7753,834,8,198,67,3672,796,28686,13,6978,13,15908,3672,7,397,2777,776,8,198,418,13,354,15908,7,67,3672,8,198,198,2,16626,11420,17267,1366,11420,198,198,2,11274,40779,62,19023,82,62,2375,22739,198,11748,62,46428,796,10644,7203,40720,40720,7890,14,2375,22739,14,11274,40779,62,19023,82,62,2375,22739,13,40664,4943,198,11274,40779,62,19023,82,796,279,67,13,961,62,40664,7,11748,62,46428,11,21004,796,366,40477,12,23,1600,6376,62,4033,796,10352,8,198,198,2,19023,62,34086,3007,62,38200,8863,198,11748,62,46428,796,10644,7203,40720,40720,7890,14,20930,62,43420,14,19023,62,34086,3007,62,38200,8863,13,40664,4943,198,34086,3007,62,38200,8863,796,279,67,13,961,62,40664,7,11748,62,46428,11,21004,796,366,40477,12,23,4943,198,198,2,16626,11420,43426,1366,11420,198,198,34086,3007,62,38200,8863,796,13439,62,38200,8863,13,17946,58,45299,14692,19023,62,312,1600,198,220,220,220,220,220,220,220,220,220,220,220,220,220,220,220,220,220,220,220,220,220,220,220,220,220,220,220,220,220,220,220,220,220,220,220,220,220,220,220,220,220,220,220,220,220,220,220,366,34086,594,62,312,1600,198,220,220,220,220,220,220,220,220,220,220,220,220,220,220,220,220,220,220,220,220,220,220,220,220,220,220,220,220,220,220,220,220,220,220,220,220,220,220,220,220,220,220,220,220,220,220,220,366,34086,62,434,507,62,14986,1600,198,220,220,220,220,220,220,220,220,220,220,220,220,220,220,220,220,220,220,220,220,220,220,220,220,220,220,220,220,220,220,220,220,220,220,220,220,220,220,220,220,220,220,220,220,220,220,220,366,34086,62,434,507,62,7645,1600,198,220,220,220,220,220,220,220,220,220,220,220,220,220,220,220,220,220,220,220,220,220,220,220,220,220,220,220,220,220,220,220,220,220,220,220,220,220,220,220,220,220,220,220,220,220,220,220,366,13664,62,259,62,10879,1600,198,220,220,220,220,220,220,220,220,220,220,220,220,220,220,220,220,220,220,220,220,220,220,220,220,220,220,220,220,220,220,220,220,220,220,220,220,220,220,220,220,220,220,220,220,220,220,220,366,53,2885,1137,62,26675,62,5589,633,8973,60,198,198,2,7214,257,24637,286,922,40779,8088,284,2291,691,8088,3025,2423,645,198,2,1656,287,13439,62,38200,8863,13,198,198,6058,62,27932,796,922,40779,62,19023,82,14692,19023,62,312,1,4083,45763,7,34086,3007,62,38200,8863,14692,19023,62,312,8973,8,198,11274,40779,62,19023,82,796,922,40779,62,19023,82,13,17946,58,6058,62,27932,11,1058,60,198,2,16626,11420,16213,2736,25,2423,4129,287,13439,290,2456,13,11420,198,198,13664,62,525,62,19023,796,357,34086,3007,62,38200,8863,198,220,220,220,220,220,220,220,220,220,220,220,220,220,220,220,220,220,220,220,220,220,220,220,764,8094,1525,7203,19023,62,312,4943,198,220,220,220,220,220,220,220,220,220,220,220,220,220,220,220,220,220,220,220,220,220,220,220,14631,13664,62,259,62,10879,8973,198,220,220,220,220,220,220,220,220,220,220,220,220,220,220,220,220,220,220,220,220,220,220,220,764,9460,7,14692,16345,2430,9127,8973,8,198,220,220,220,220,220,220,220,220,220,220,220,220,220,220,220,220,220,220,220,220,220,220,220,764,918,480,7,4895,16345,1,1058,366,23350,62,13664,62,259,62,10879,1600,198,220,220,220,220,220,220,220,220,220,220,220,220,220,220,220,220,220,220,220,220,220,220,220,220,220,220,220,220,220,220,220,220,220,366,9127,1,1058,366,23350,62,13664,62,259,62,34086,3007,25719,198,220,220,220,220,220,220,220,220,220,220,220,220,220,220,220,220,220,220,220,220,220,220,220,220,220,220,220,220,220,220,220,16488,796,352,4008,198,198,11274,40779,62,19023,82,796,357,11274,40779,62,19023,82,198,220,220,220,220,220,220,220,220,220,220,220,220,220,220,220,220,220,220,220,220,220,764,647,469,7,13664,62,525,62,19023,11,198,220,220,220,220,220,220,220,220,220,220,220,220,220,220,220,220,220,220,220,220,220,220,220,220,220,220,220,703,796,366,9464,1600,198,220,220,220,220,220,220,220,220,220,220,220,220,220,220,220,220,220,220,220,220,220,220,220,220,220,220,220,319,796,366,19023,62,312,48774,198,198,2,16626,11420,16213,2736,25,3068,22423,329,7952,11059,14,9800,15802,198,198,11612,62,434,295,62,27932,796,13439,62,38200,8863,14692,34086,62,434,507,62,14986,8973,6624,6407,198,7645,62,434,295,62,27932,796,13439,62,38200,8863,14692,34086,62,434,507,62,7645,8973,6624,6407,198,8807,62,11612,62,434,295,62,27932,796,357,11612,62,434,295,62,27932,1222,5299,7645,62,434,295,62,27932,8,198,8807,62,7645,62,434,295,62,27932,796,31034,11612,62,434,295,62,27932,1222,1007,62,434,295,62,27932,8,198,16885,62,434,295,62,27932,796,357,11612,62,434,295,62,27932,1222,1007,62,434,295,62,27932,8,198,198,5356,591,796,19779,20077,62,1659,62,8807,62,7645,62,434,507,1,1058,691,62,7645,62,434,295,62,27932,11,198,220,220,220,220,220,220,220,220,366,20077,62,1659,62,7645,62,434,507,1,1058,1007,62,434,295,62,27932,11,198,220,220,220,220,220,220,220,220,366,20077,62,1659,62,8807,62,11612,62,434,507,1298,691,62,11612,62,434,295,62,27932,11,198,220,220,220,220,220,220,220,220,366,20077,62,1659,62,11612,62,434,507,1298,1796,62,434,295,62,27932,92,198,198,1640,21231,11,9335,287,20680,13,23814,33529,198,220,220,220,42302,796,357,34086,3007,62,38200,8863,58,27932,4083,198,220,220,220,220,220,220,220,220,220,220,220,1448,1525,7203,19023,62,312,4943,198,220,220,220,220,220,220,220,220,220,220,220,14631,13664,62,259,62,10879,8973,198,220,220,220,220,220,220,220,220,220,220,220,764,9460,7,14692,9127,8973,8,198,220,220,220,220,220,220,220,220,220,220,220,764,918,480,7,4895,9127,1298,21231,5512,198,220,220,220,220,220,220,220,220,220,220,220,220,220,220,220,220,220,220,220,16488,796,352,8,198,220,220,220,220,220,220,220,220,220,220,220,764,42503,62,9630,28955,198,220,220,220,220,198,220,220,220,922,40779,62,19023,82,796,357,11274,40779,62,19023,82,13,647,469,7,9948,66,11,198,220,220,220,220,220,220,220,220,220,220,220,220,220,220,220,220,220,220,220,220,220,220,220,220,220,220,220,220,220,220,220,220,220,220,220,220,220,220,220,220,220,220,220,220,220,220,220,220,703,796,366,9464,1600,198,220,220,220,220,220,220,220,220,220,220,220,220,220,220,220,220,220,220,220,220,220,220,220,220,220,220,220,220,220,220,220,220,220,220,220,220,220,220,220,220,220,220,220,220,220,220,220,220,319,796,366,19023,62,312,4943,198,220,220,220,220,220,220,220,220,220,220,220,220,220,220,220,220,220,220,220,220,220,220,220,220,764,20797,2616,7,8367,796,657,11,198,220,220,220,220,220,220,220,220,220,220,220,220,220,220,220,220,220,220,220,220,220,220,220,220,220,220,220,220,220,220,220,220,16488,796,657,4008,198,220,220,220,220,198,220,220,220,922,40779,62,19023,82,58,40290,60,796,14808,11274,40779,62,19023,82,58,40290,60,198,220,220,220,220,220,220,220,220,220,220,220,220,220,220,220,220,220,220,220,220,220,220,220,220,220,220,220,220,220,220,1220,922,40779,62,19023,82,14692,23350,62,13664,62,259,62,34086,3007,8973,8,198,220,220,220,220,220,220,220,220,220,220,220,220,220,220,220,220,220,220,220,220,220,220,220,220,220,220,220,220,220,220,1635,1802,8,198,220,220,220,220,198,2,16626,11420,16213,2736,25,569,2885,1137,4776,329,262,2187,2423,11420,198,198,53,2885,1137,62,26675,62,525,62,19023,796,357,34086,3007,62,38200,8863,198,220,220,220,220,220,220,220,220,220,220,220,220,220,220,220,220,220,220,220,220,220,220,220,220,220,764,8094,1525,7203,19023,62,312,4943,198,220,220,220,220,220,220,220,220,220,220,220,220,220,220,220,220,220,220,220,220,220,220,220,220,220,14631,53,2885,1137,62,26675,62,5589,633,8973,198,220,220,220,220,220,220,220,220,220,220,220,220,220,220,220,220,220,220,220,220,220,220,220,220,220,764,9460,7,14692,16345,2430,9127,8973,8,198,220,220,220,220,220,220,220,220,220,220,220,220,220,220,220,220,220,220,220,220,220,220,220,220,220,764,42503,62,9630,28955,198,198,53,2885,1137,62,26675,62,525,62,19023,14692,615,70,62,53,2885,1137,62,26675,8973,796,357,53,2885,1137,62,26675,62,525,62,19023,14692,16345,8973,198,220,220,220,220,220,220,220,220,220,220,220,220,220,220,220,220,220,220,220,220,220,220,220,220,220,220,220,220,220,220,220,220,220,220,220,220,220,220,220,220,220,220,220,220,220,1220,569,2885,1137,62,26675,62,525,62,19023,14692,9127,8973,8,198,198,53,2885,1137,62,26675,62,525,62,19023,796,569,2885,1137,62,26675,62,525,62,19023,13,14781,7,23912,1424,796,14631,16345,2430,9127,33116,198,220,220,220,220,220,220,220,220,220,220,220,220,220,220,220,220,220,220,220,220,220,220,220,220,220,220,220,220,220,220,220,220,220,220,220,220,220,220,220,220,220,220,220,220,220,220,220,220,220,220,220,220,220,16488,796,366,28665,82,4943,198,198,11274,40779,62,19023,82,796,922,40779,62,19023,82,13,647,469,7,53,2885,1137,62,26675,62,525,62,19023,11,198,220,220,220,220,220,220,220,220,220,220,220,220,220,220,220,220,220,220,220,220,220,220,220,220,220,220,220,220,220,220,220,220,220,220,220,220,220,220,220,220,220,220,220,703,796,366,9464,1600,198,220,220,220,220,220,220,220,220,220,220,220,220,220,220,220,220,220,220,220,220,220,220,220,220,220,220,220,220,220,220,220,220,220,220,220,220,220,220,220,220,220,220,220,319,796,366,19023,62,312,4943,198,198,2,16626,11420,36472,1366,11420,198,198,39344,62,46428,796,10644,7203,40720,40720,7890,14,20930,62,43420,14,11274,40779,62,19023,82,62,38200,8863,13,40664,4943,198,11274,40779,62,19023,82,13,1462,62,40664,7,39344,62,46428,11,21004,796,366,40477,12,23,1600,6376,796,10352,8,198],"string":"[\n 2,\n 532,\n 9,\n 12,\n 19617,\n 25,\n 3384,\n 69,\n 12,\n 23,\n 532,\n 9,\n 12,\n 198,\n 37811,\n 198,\n 41972,\n 319,\n 3300,\n 1526,\n 1596,\n 1511,\n 25,\n 2327,\n 25,\n 2670,\n 33448,\n 198,\n 198,\n 31,\n 9800,\n 25,\n 304,\n 73,\n 5235,\n 198,\n 198,\n 23031,\n 1867,\n 318,\n 428,\n 2393,\n 30,\n 40103,\n 198,\n 198,\n 1212,\n 4226,\n 6670,\n 262,\n 3696,\n 922,\n 40779,\n 62,\n 19023,\n 82,\n 62,\n 2375,\n 22739,\n 13,\n 40664,\n 290,\n 198,\n 19023,\n 62,\n 34086,\n 3007,\n 62,\n 38200,\n 8863,\n 13,\n 40664,\n 11,\n 26019,\n 10638,\n 7869,\n 884,\n 355,\n 198,\n 19023,\n 4129,\n 290,\n 15598,\n 4776,\n 13,\n 198,\n 198,\n 1212,\n 4226,\n 6670,\n 262,\n 1708,\n 3696,\n 25,\n 198,\n 220,\n 220,\n 220,\n 11485,\n 14,\n 40720,\n 7890,\n 14,\n 2375,\n 22739,\n 14,\n 11274,\n 40779,\n 62,\n 19023,\n 82,\n 62,\n 2375,\n 22739,\n 13,\n 40664,\n 198,\n 220,\n 220,\n 220,\n 11485,\n 14,\n 40720,\n 7890,\n 14,\n 20930,\n 62,\n 43420,\n 14,\n 19023,\n 62,\n 34086,\n 3007,\n 62,\n 38200,\n 8863,\n 13,\n 40664,\n 198,\n 220,\n 220,\n 220,\n 220,\n 198,\n 464,\n 7186,\n 269,\n 21370,\n 2393,\n 318,\n 5140,\n 379,\n 25,\n 198,\n 220,\n 220,\n 220,\n 11485,\n 14,\n 40720,\n 7890,\n 14,\n 20930,\n 62,\n 43420,\n 14,\n 11274,\n 40779,\n 62,\n 19023,\n 82,\n 62,\n 38200,\n 8863,\n 13,\n 40664,\n 198,\n 220,\n 220,\n 220,\n 220,\n 220,\n 220,\n 220,\n 220,\n 198,\n 37811,\n 198,\n 2,\n 16626,\n 11420,\n 17267,\n 2672,\n 10392,\n 11420,\n 198,\n 198,\n 11748,\n 28686,\n 198,\n 198,\n 6738,\n 3108,\n 8019,\n 1330,\n 10644,\n 1303,\n 1675,\n 14441,\n 1088,\n 2393,\n 6978,\n 82,\n 198,\n 11748,\n 19798,\n 292,\n 355,\n 279,\n 67,\n 198,\n 198,\n 2,\n 16626,\n 11420,\n 5345,\n 1774,\n 8619,\n 284,\n 19832,\n 11812,\n 351,\n 466,\n 270,\n 11420,\n 198,\n 198,\n 397,\n 2777,\n 776,\n 796,\n 28686,\n 13,\n 6978,\n 13,\n 397,\n 2777,\n 776,\n 7,\n 834,\n 7753,\n 834,\n 8,\n 198,\n 67,\n 3672,\n 796,\n 28686,\n 13,\n 6978,\n 13,\n 15908,\n 3672,\n 7,\n 397,\n 2777,\n 776,\n 8,\n 198,\n 418,\n 13,\n 354,\n 15908,\n 7,\n 67,\n 3672,\n 8,\n 198,\n 198,\n 2,\n 16626,\n 11420,\n 17267,\n 1366,\n 11420,\n 198,\n 198,\n 2,\n 11274,\n 40779,\n 62,\n 19023,\n 82,\n 62,\n 2375,\n 22739,\n 198,\n 11748,\n 62,\n 46428,\n 796,\n 10644,\n 7203,\n 40720,\n 40720,\n 7890,\n 14,\n 2375,\n 22739,\n 14,\n 11274,\n 40779,\n 62,\n 19023,\n 82,\n 62,\n 2375,\n 22739,\n 13,\n 40664,\n 4943,\n 198,\n 11274,\n 40779,\n 62,\n 19023,\n 82,\n 796,\n 279,\n 67,\n 13,\n 961,\n 62,\n 40664,\n 7,\n 11748,\n 62,\n 46428,\n 11,\n 21004,\n 796,\n 366,\n 40477,\n 12,\n 23,\n 1600,\n 6376,\n 62,\n 4033,\n 796,\n 10352,\n 8,\n 198,\n 198,\n 2,\n 19023,\n 62,\n 34086,\n 3007,\n 62,\n 38200,\n 8863,\n 198,\n 11748,\n 62,\n 46428,\n 796,\n 10644,\n 7203,\n 40720,\n 40720,\n 7890,\n 14,\n 20930,\n 62,\n 43420,\n 14,\n 19023,\n 62,\n 34086,\n 3007,\n 62,\n 38200,\n 8863,\n 13,\n 40664,\n 4943,\n 198,\n 34086,\n 3007,\n 62,\n 38200,\n 8863,\n 796,\n 279,\n 67,\n 13,\n 961,\n 62,\n 40664,\n 7,\n 11748,\n 62,\n 46428,\n 11,\n 21004,\n 796,\n 366,\n 40477,\n 12,\n 23,\n 4943,\n 198,\n 198,\n 2,\n 16626,\n 11420,\n 43426,\n 1366,\n 11420,\n 198,\n 198,\n 34086,\n 3007,\n 62,\n 38200,\n 8863,\n 796,\n 13439,\n 62,\n 38200,\n 8863,\n 13,\n 17946,\n 58,\n 45299,\n 14692,\n 19023,\n 62,\n 312,\n 1600,\n 198,\n 220,\n 220,\n 220,\n 220,\n 220,\n 220,\n 220,\n 220,\n 220,\n 220,\n 220,\n 220,\n 220,\n 220,\n 220,\n 220,\n 220,\n 220,\n 220,\n 220,\n 220,\n 220,\n 220,\n 220,\n 220,\n 220,\n 220,\n 220,\n 220,\n 220,\n 220,\n 220,\n 220,\n 220,\n 220,\n 220,\n 220,\n 220,\n 220,\n 220,\n 220,\n 220,\n 220,\n 220,\n 220,\n 220,\n 220,\n 366,\n 34086,\n 594,\n 62,\n 312,\n 1600,\n 198,\n 220,\n 220,\n 220,\n 220,\n 220,\n 220,\n 220,\n 220,\n 220,\n 220,\n 220,\n 220,\n 220,\n 220,\n 220,\n 220,\n 220,\n 220,\n 220,\n 220,\n 220,\n 220,\n 220,\n 220,\n 220,\n 220,\n 220,\n 220,\n 220,\n 220,\n 220,\n 220,\n 220,\n 220,\n 220,\n 220,\n 220,\n 220,\n 220,\n 220,\n 220,\n 220,\n 220,\n 220,\n 220,\n 220,\n 220,\n 366,\n 34086,\n 62,\n 434,\n 507,\n 62,\n 14986,\n 1600,\n 198,\n 220,\n 220,\n 220,\n 220,\n 220,\n 220,\n 220,\n 220,\n 220,\n 220,\n 220,\n 220,\n 220,\n 220,\n 220,\n 220,\n 220,\n 220,\n 220,\n 220,\n 220,\n 220,\n 220,\n 220,\n 220,\n 220,\n 220,\n 220,\n 220,\n 220,\n 220,\n 220,\n 220,\n 220,\n 220,\n 220,\n 220,\n 220,\n 220,\n 220,\n 220,\n 220,\n 220,\n 220,\n 220,\n 220,\n 220,\n 366,\n 34086,\n 62,\n 434,\n 507,\n 62,\n 7645,\n 1600,\n 198,\n 220,\n 220,\n 220,\n 220,\n 220,\n 220,\n 220,\n 220,\n 220,\n 220,\n 220,\n 220,\n 220,\n 220,\n 220,\n 220,\n 220,\n 220,\n 220,\n 220,\n 220,\n 220,\n 220,\n 220,\n 220,\n 220,\n 220,\n 220,\n 220,\n 220,\n 220,\n 220,\n 220,\n 220,\n 220,\n 220,\n 220,\n 220,\n 220,\n 220,\n 220,\n 220,\n 220,\n 220,\n 220,\n 220,\n 220,\n 366,\n 13664,\n 62,\n 259,\n 62,\n 10879,\n 1600,\n 198,\n 220,\n 220,\n 220,\n 220,\n 220,\n 220,\n 220,\n 220,\n 220,\n 220,\n 220,\n 220,\n 220,\n 220,\n 220,\n 220,\n 220,\n 220,\n 220,\n 220,\n 220,\n 220,\n 220,\n 220,\n 220,\n 220,\n 220,\n 220,\n 220,\n 220,\n 220,\n 220,\n 220,\n 220,\n 220,\n 220,\n 220,\n 220,\n 220,\n 220,\n 220,\n 220,\n 220,\n 220,\n 220,\n 220,\n 220,\n 366,\n 53,\n 2885,\n 1137,\n 62,\n 26675,\n 62,\n 5589,\n 633,\n 8973,\n 60,\n 198,\n 198,\n 2,\n 7214,\n 257,\n 24637,\n 286,\n 922,\n 40779,\n 8088,\n 284,\n 2291,\n 691,\n 8088,\n 3025,\n 2423,\n 645,\n 198,\n 2,\n 1656,\n 287,\n 13439,\n 62,\n 38200,\n 8863,\n 13,\n 198,\n 198,\n 6058,\n 62,\n 27932,\n 796,\n 922,\n 40779,\n 62,\n 19023,\n 82,\n 14692,\n 19023,\n 62,\n 312,\n 1,\n 4083,\n 45763,\n 7,\n 34086,\n 3007,\n 62,\n 38200,\n 8863,\n 14692,\n 19023,\n 62,\n 312,\n 8973,\n 8,\n 198,\n 11274,\n 40779,\n 62,\n 19023,\n 82,\n 796,\n 922,\n 40779,\n 62,\n 19023,\n 82,\n 13,\n 17946,\n 58,\n 6058,\n 62,\n 27932,\n 11,\n 1058,\n 60,\n 198,\n 2,\n 16626,\n 11420,\n 16213,\n 2736,\n 25,\n 2423,\n 4129,\n 287,\n 13439,\n 290,\n 2456,\n 13,\n 11420,\n 198,\n 198,\n 13664,\n 62,\n 525,\n 62,\n 19023,\n 796,\n 357,\n 34086,\n 3007,\n 62,\n 38200,\n 8863,\n 198,\n 220,\n 220,\n 220,\n 220,\n 220,\n 220,\n 220,\n 220,\n 220,\n 220,\n 220,\n 220,\n 220,\n 220,\n 220,\n 220,\n 220,\n 220,\n 220,\n 220,\n 220,\n 220,\n 220,\n 764,\n 8094,\n 1525,\n 7203,\n 19023,\n 62,\n 312,\n 4943,\n 198,\n 220,\n 220,\n 220,\n 220,\n 220,\n 220,\n 220,\n 220,\n 220,\n 220,\n 220,\n 220,\n 220,\n 220,\n 220,\n 220,\n 220,\n 220,\n 220,\n 220,\n 220,\n 220,\n 220,\n 14631,\n 13664,\n 62,\n 259,\n 62,\n 10879,\n 8973,\n 198,\n 220,\n 220,\n 220,\n 220,\n 220,\n 220,\n 220,\n 220,\n 220,\n 220,\n 220,\n 220,\n 220,\n 220,\n 220,\n 220,\n 220,\n 220,\n 220,\n 220,\n 220,\n 220,\n 220,\n 764,\n 9460,\n 7,\n 14692,\n 16345,\n 2430,\n 9127,\n 8973,\n 8,\n 198,\n 220,\n 220,\n 220,\n 220,\n 220,\n 220,\n 220,\n 220,\n 220,\n 220,\n 220,\n 220,\n 220,\n 220,\n 220,\n 220,\n 220,\n 220,\n 220,\n 220,\n 220,\n 220,\n 220,\n 764,\n 918,\n 480,\n 7,\n 4895,\n 16345,\n 1,\n 1058,\n 366,\n 23350,\n 62,\n 13664,\n 62,\n 259,\n 62,\n 10879,\n 1600,\n 198,\n 220,\n 220,\n 220,\n 220,\n 220,\n 220,\n 220,\n 220,\n 220,\n 220,\n 220,\n 220,\n 220,\n 220,\n 220,\n 220,\n 220,\n 220,\n 220,\n 220,\n 220,\n 220,\n 220,\n 220,\n 220,\n 220,\n 220,\n 220,\n 220,\n 220,\n 220,\n 220,\n 220,\n 366,\n 9127,\n 1,\n 1058,\n 366,\n 23350,\n 62,\n 13664,\n 62,\n 259,\n 62,\n 34086,\n 3007,\n 25719,\n 198,\n 220,\n 220,\n 220,\n 220,\n 220,\n 220,\n 220,\n 220,\n 220,\n 220,\n 220,\n 220,\n 220,\n 220,\n 220,\n 220,\n 220,\n 220,\n 220,\n 220,\n 220,\n 220,\n 220,\n 220,\n 220,\n 220,\n 220,\n 220,\n 220,\n 220,\n 220,\n 16488,\n 796,\n 352,\n 4008,\n 198,\n 198,\n 11274,\n 40779,\n 62,\n 19023,\n 82,\n 796,\n 357,\n 11274,\n 40779,\n 62,\n 19023,\n 82,\n 198,\n 220,\n 220,\n 220,\n 220,\n 220,\n 220,\n 220,\n 220,\n 220,\n 220,\n 220,\n 220,\n 220,\n 220,\n 220,\n 220,\n 220,\n 220,\n 220,\n 220,\n 220,\n 764,\n 647,\n 469,\n 7,\n 13664,\n 62,\n 525,\n 62,\n 19023,\n 11,\n 198,\n 220,\n 220,\n 220,\n 220,\n 220,\n 220,\n 220,\n 220,\n 220,\n 220,\n 220,\n 220,\n 220,\n 220,\n 220,\n 220,\n 220,\n 220,\n 220,\n 220,\n 220,\n 220,\n 220,\n 220,\n 220,\n 220,\n 220,\n 703,\n 796,\n 366,\n 9464,\n 1600,\n 198,\n 220,\n 220,\n 220,\n 220,\n 220,\n 220,\n 220,\n 220,\n 220,\n 220,\n 220,\n 220,\n 220,\n 220,\n 220,\n 220,\n 220,\n 220,\n 220,\n 220,\n 220,\n 220,\n 220,\n 220,\n 220,\n 220,\n 220,\n 319,\n 796,\n 366,\n 19023,\n 62,\n 312,\n 48774,\n 198,\n 198,\n 2,\n 16626,\n 11420,\n 16213,\n 2736,\n 25,\n 3068,\n 22423,\n 329,\n 7952,\n 11059,\n 14,\n 9800,\n 15802,\n 198,\n 198,\n 11612,\n 62,\n 434,\n 295,\n 62,\n 27932,\n 796,\n 13439,\n 62,\n 38200,\n 8863,\n 14692,\n 34086,\n 62,\n 434,\n 507,\n 62,\n 14986,\n 8973,\n 6624,\n 6407,\n 198,\n 7645,\n 62,\n 434,\n 295,\n 62,\n 27932,\n 796,\n 13439,\n 62,\n 38200,\n 8863,\n 14692,\n 34086,\n 62,\n 434,\n 507,\n 62,\n 7645,\n 8973,\n 6624,\n 6407,\n 198,\n 8807,\n 62,\n 11612,\n 62,\n 434,\n 295,\n 62,\n 27932,\n 796,\n 357,\n 11612,\n 62,\n 434,\n 295,\n 62,\n 27932,\n 1222,\n 5299,\n 7645,\n 62,\n 434,\n 295,\n 62,\n 27932,\n 8,\n 198,\n 8807,\n 62,\n 7645,\n 62,\n 434,\n 295,\n 62,\n 27932,\n 796,\n 31034,\n 11612,\n 62,\n 434,\n 295,\n 62,\n 27932,\n 1222,\n 1007,\n 62,\n 434,\n 295,\n 62,\n 27932,\n 8,\n 198,\n 16885,\n 62,\n 434,\n 295,\n 62,\n 27932,\n 796,\n 357,\n 11612,\n 62,\n 434,\n 295,\n 62,\n 27932,\n 1222,\n 1007,\n 62,\n 434,\n 295,\n 62,\n 27932,\n 8,\n 198,\n 198,\n 5356,\n 591,\n 796,\n 19779,\n 20077,\n 62,\n 1659,\n 62,\n 8807,\n 62,\n 7645,\n 62,\n 434,\n 507,\n 1,\n 1058,\n 691,\n 62,\n 7645,\n 62,\n 434,\n 295,\n 62,\n 27932,\n 11,\n 198,\n 220,\n 220,\n 220,\n 220,\n 220,\n 220,\n 220,\n 220,\n 366,\n 20077,\n 62,\n 1659,\n 62,\n 7645,\n 62,\n 434,\n 507,\n 1,\n 1058,\n 1007,\n 62,\n 434,\n 295,\n 62,\n 27932,\n 11,\n 198,\n 220,\n 220,\n 220,\n 220,\n 220,\n 220,\n 220,\n 220,\n 366,\n 20077,\n 62,\n 1659,\n 62,\n 8807,\n 62,\n 11612,\n 62,\n 434,\n 507,\n 1298,\n 691,\n 62,\n 11612,\n 62,\n 434,\n 295,\n 62,\n 27932,\n 11,\n 198,\n 220,\n 220,\n 220,\n 220,\n 220,\n 220,\n 220,\n 220,\n 366,\n 20077,\n 62,\n 1659,\n 62,\n 11612,\n 62,\n 434,\n 507,\n 1298,\n 1796,\n 62,\n 434,\n 295,\n 62,\n 27932,\n 92,\n 198,\n 198,\n 1640,\n 21231,\n 11,\n 9335,\n 287,\n 20680,\n 13,\n 23814,\n 33529,\n 198,\n 220,\n 220,\n 220,\n 42302,\n 796,\n 357,\n 34086,\n 3007,\n 62,\n 38200,\n 8863,\n 58,\n 27932,\n 4083,\n 198,\n 220,\n 220,\n 220,\n 220,\n 220,\n 220,\n 220,\n 220,\n 220,\n 220,\n 220,\n 1448,\n 1525,\n 7203,\n 19023,\n 62,\n 312,\n 4943,\n 198,\n 220,\n 220,\n 220,\n 220,\n 220,\n 220,\n 220,\n 220,\n 220,\n 220,\n 220,\n 14631,\n 13664,\n 62,\n 259,\n 62,\n 10879,\n 8973,\n 198,\n 220,\n 220,\n 220,\n 220,\n 220,\n 220,\n 220,\n 220,\n 220,\n 220,\n 220,\n 764,\n 9460,\n 7,\n 14692,\n 9127,\n 8973,\n 8,\n 198,\n 220,\n 220,\n 220,\n 220,\n 220,\n 220,\n 220,\n 220,\n 220,\n 220,\n 220,\n 764,\n 918,\n 480,\n 7,\n 4895,\n 9127,\n 1298,\n 21231,\n 5512,\n 198,\n 220,\n 220,\n 220,\n 220,\n 220,\n 220,\n 220,\n 220,\n 220,\n 220,\n 220,\n 220,\n 220,\n 220,\n 220,\n 220,\n 220,\n 220,\n 220,\n 16488,\n 796,\n 352,\n 8,\n 198,\n 220,\n 220,\n 220,\n 220,\n 220,\n 220,\n 220,\n 220,\n 220,\n 220,\n 220,\n 764,\n 42503,\n 62,\n 9630,\n 28955,\n 198,\n 220,\n 220,\n 220,\n 220,\n 198,\n 220,\n 220,\n 220,\n 922,\n 40779,\n 62,\n 19023,\n 82,\n 796,\n 357,\n 11274,\n 40779,\n 62,\n 19023,\n 82,\n 13,\n 647,\n 469,\n 7,\n 9948,\n 66,\n 11,\n 198,\n 220,\n 220,\n 220,\n 220,\n 220,\n 220,\n 220,\n 220,\n 220,\n 220,\n 220,\n 220,\n 220,\n 220,\n 220,\n 220,\n 220,\n 220,\n 220,\n 220,\n 220,\n 220,\n 220,\n 220,\n 220,\n 220,\n 220,\n 220,\n 220,\n 220,\n 220,\n 220,\n 220,\n 220,\n 220,\n 220,\n 220,\n 220,\n 220,\n 220,\n 220,\n 220,\n 220,\n 220,\n 220,\n 220,\n 220,\n 220,\n 703,\n 796,\n 366,\n 9464,\n 1600,\n 198,\n 220,\n 220,\n 220,\n 220,\n 220,\n 220,\n 220,\n 220,\n 220,\n 220,\n 220,\n 220,\n 220,\n 220,\n 220,\n 220,\n 220,\n 220,\n 220,\n 220,\n 220,\n 220,\n 220,\n 220,\n 220,\n 220,\n 220,\n 220,\n 220,\n 220,\n 220,\n 220,\n 220,\n 220,\n 220,\n 220,\n 220,\n 220,\n 220,\n 220,\n 220,\n 220,\n 220,\n 220,\n 220,\n 220,\n 220,\n 220,\n 319,\n 796,\n 366,\n 19023,\n 62,\n 312,\n 4943,\n 198,\n 220,\n 220,\n 220,\n 220,\n 220,\n 220,\n 220,\n 220,\n 220,\n 220,\n 220,\n 220,\n 220,\n 220,\n 220,\n 220,\n 220,\n 220,\n 220,\n 220,\n 220,\n 220,\n 220,\n 220,\n 764,\n 20797,\n 2616,\n 7,\n 8367,\n 796,\n 657,\n 11,\n 198,\n 220,\n 220,\n 220,\n 220,\n 220,\n 220,\n 220,\n 220,\n 220,\n 220,\n 220,\n 220,\n 220,\n 220,\n 220,\n 220,\n 220,\n 220,\n 220,\n 220,\n 220,\n 220,\n 220,\n 220,\n 220,\n 220,\n 220,\n 220,\n 220,\n 220,\n 220,\n 220,\n 16488,\n 796,\n 657,\n 4008,\n 198,\n 220,\n 220,\n 220,\n 220,\n 198,\n 220,\n 220,\n 220,\n 922,\n 40779,\n 62,\n 19023,\n 82,\n 58,\n 40290,\n 60,\n 796,\n 14808,\n 11274,\n 40779,\n 62,\n 19023,\n 82,\n 58,\n 40290,\n 60,\n 198,\n 220,\n 220,\n 220,\n 220,\n 220,\n 220,\n 220,\n 220,\n 220,\n 220,\n 220,\n 220,\n 220,\n 220,\n 220,\n 220,\n 220,\n 220,\n 220,\n 220,\n 220,\n 220,\n 220,\n 220,\n 220,\n 220,\n 220,\n 220,\n 220,\n 220,\n 1220,\n 922,\n 40779,\n 62,\n 19023,\n 82,\n 14692,\n 23350,\n 62,\n 13664,\n 62,\n 259,\n 62,\n 34086,\n 3007,\n 8973,\n 8,\n 198,\n 220,\n 220,\n 220,\n 220,\n 220,\n 220,\n 220,\n 220,\n 220,\n 220,\n 220,\n 220,\n 220,\n 220,\n 220,\n 220,\n 220,\n 220,\n 220,\n 220,\n 220,\n 220,\n 220,\n 220,\n 220,\n 220,\n 220,\n 220,\n 220,\n 220,\n 1635,\n 1802,\n 8,\n 198,\n 220,\n 220,\n 220,\n 220,\n 198,\n 2,\n 16626,\n 11420,\n 16213,\n 2736,\n 25,\n 569,\n 2885,\n 1137,\n 4776,\n 329,\n 262,\n 2187,\n 2423,\n 11420,\n 198,\n 198,\n 53,\n 2885,\n 1137,\n 62,\n 26675,\n 62,\n 525,\n 62,\n 19023,\n 796,\n 357,\n 34086,\n 3007,\n 62,\n 38200,\n 8863,\n 198,\n 220,\n 220,\n 220,\n 220,\n 220,\n 220,\n 220,\n 220,\n 220,\n 220,\n 220,\n 220,\n 220,\n 220,\n 220,\n 220,\n 220,\n 220,\n 220,\n 220,\n 220,\n 220,\n 220,\n 220,\n 220,\n 764,\n 8094,\n 1525,\n 7203,\n 19023,\n 62,\n 312,\n 4943,\n 198,\n 220,\n 220,\n 220,\n 220,\n 220,\n 220,\n 220,\n 220,\n 220,\n 220,\n 220,\n 220,\n 220,\n 220,\n 220,\n 220,\n 220,\n 220,\n 220,\n 220,\n 220,\n 220,\n 220,\n 220,\n 220,\n 14631,\n 53,\n 2885,\n 1137,\n 62,\n 26675,\n 62,\n 5589,\n 633,\n 8973,\n 198,\n 220,\n 220,\n 220,\n 220,\n 220,\n 220,\n 220,\n 220,\n 220,\n 220,\n 220,\n 220,\n 220,\n 220,\n 220,\n 220,\n 220,\n 220,\n 220,\n 220,\n 220,\n 220,\n 220,\n 220,\n 220,\n 764,\n 9460,\n 7,\n 14692,\n 16345,\n 2430,\n 9127,\n 8973,\n 8,\n 198,\n 220,\n 220,\n 220,\n 220,\n 220,\n 220,\n 220,\n 220,\n 220,\n 220,\n 220,\n 220,\n 220,\n 220,\n 220,\n 220,\n 220,\n 220,\n 220,\n 220,\n 220,\n 220,\n 220,\n 220,\n 220,\n 764,\n 42503,\n 62,\n 9630,\n 28955,\n 198,\n 198,\n 53,\n 2885,\n 1137,\n 62,\n 26675,\n 62,\n 525,\n 62,\n 19023,\n 14692,\n 615,\n 70,\n 62,\n 53,\n 2885,\n 1137,\n 62,\n 26675,\n 8973,\n 796,\n 357,\n 53,\n 2885,\n 1137,\n 62,\n 26675,\n 62,\n 525,\n 62,\n 19023,\n 14692,\n 16345,\n 8973,\n 198,\n 220,\n 220,\n 220,\n 220,\n 220,\n 220,\n 220,\n 220,\n 220,\n 220,\n 220,\n 220,\n 220,\n 220,\n 220,\n 220,\n 220,\n 220,\n 220,\n 220,\n 220,\n 220,\n 220,\n 220,\n 220,\n 220,\n 220,\n 220,\n 220,\n 220,\n 220,\n 220,\n 220,\n 220,\n 220,\n 220,\n 220,\n 220,\n 220,\n 220,\n 220,\n 220,\n 220,\n 220,\n 220,\n 1220,\n 569,\n 2885,\n 1137,\n 62,\n 26675,\n 62,\n 525,\n 62,\n 19023,\n 14692,\n 9127,\n 8973,\n 8,\n 198,\n 198,\n 53,\n 2885,\n 1137,\n 62,\n 26675,\n 62,\n 525,\n 62,\n 19023,\n 796,\n 569,\n 2885,\n 1137,\n 62,\n 26675,\n 62,\n 525,\n 62,\n 19023,\n 13,\n 14781,\n 7,\n 23912,\n 1424,\n 796,\n 14631,\n 16345,\n 2430,\n 9127,\n 33116,\n 198,\n 220,\n 220,\n 220,\n 220,\n 220,\n 220,\n 220,\n 220,\n 220,\n 220,\n 220,\n 220,\n 220,\n 220,\n 220,\n 220,\n 220,\n 220,\n 220,\n 220,\n 220,\n 220,\n 220,\n 220,\n 220,\n 220,\n 220,\n 220,\n 220,\n 220,\n 220,\n 220,\n 220,\n 220,\n 220,\n 220,\n 220,\n 220,\n 220,\n 220,\n 220,\n 220,\n 220,\n 220,\n 220,\n 220,\n 220,\n 220,\n 220,\n 220,\n 220,\n 220,\n 220,\n 16488,\n 796,\n 366,\n 28665,\n 82,\n 4943,\n 198,\n 198,\n 11274,\n 40779,\n 62,\n 19023,\n 82,\n 796,\n 922,\n 40779,\n 62,\n 19023,\n 82,\n 13,\n 647,\n 469,\n 7,\n 53,\n 2885,\n 1137,\n 62,\n 26675,\n 62,\n 525,\n 62,\n 19023,\n 11,\n 198,\n 220,\n 220,\n 220,\n 220,\n 220,\n 220,\n 220,\n 220,\n 220,\n 220,\n 220,\n 220,\n 220,\n 220,\n 220,\n 220,\n 220,\n 220,\n 220,\n 220,\n 220,\n 220,\n 220,\n 220,\n 220,\n 220,\n 220,\n 220,\n 220,\n 220,\n 220,\n 220,\n 220,\n 220,\n 220,\n 220,\n 220,\n 220,\n 220,\n 220,\n 220,\n 220,\n 220,\n 703,\n 796,\n 366,\n 9464,\n 1600,\n 198,\n 220,\n 220,\n 220,\n 220,\n 220,\n 220,\n 220,\n 220,\n 220,\n 220,\n 220,\n 220,\n 220,\n 220,\n 220,\n 220,\n 220,\n 220,\n 220,\n 220,\n 220,\n 220,\n 220,\n 220,\n 220,\n 220,\n 220,\n 220,\n 220,\n 220,\n 220,\n 220,\n 220,\n 220,\n 220,\n 220,\n 220,\n 220,\n 220,\n 220,\n 220,\n 220,\n 220,\n 319,\n 796,\n 366,\n 19023,\n 62,\n 312,\n 4943,\n 198,\n 198,\n 2,\n 16626,\n 11420,\n 36472,\n 1366,\n 11420,\n 198,\n 198,\n 39344,\n 62,\n 46428,\n 796,\n 10644,\n 7203,\n 40720,\n 40720,\n 7890,\n 14,\n 20930,\n 62,\n 43420,\n 14,\n 11274,\n 40779,\n 62,\n 19023,\n 82,\n 62,\n 38200,\n 8863,\n 13,\n 40664,\n 4943,\n 198,\n 11274,\n 40779,\n 62,\n 19023,\n 82,\n 13,\n 1462,\n 62,\n 40664,\n 7,\n 39344,\n 62,\n 46428,\n 11,\n 21004,\n 796,\n 366,\n 40477,\n 12,\n 23,\n 1600,\n 6376,\n 796,\n 10352,\n 8,\n 198\n]"},"ratio_char_token":{"kind":"number","value":1.9983471074380166,"string":"1.998347"},"token_count":{"kind":"number","value":2420,"string":"2,420"}}},{"rowIdx":1261,"cells":{"content":{"kind":"string","value":"import cv2, json, sys, datetime\nimport tensorflow as tf\nimport numpy as np\n\nfrom face_filter import c_face_filter\nfrom mtcnn_detect import c_MTCNNDetect\nfrom face_attr import c_face_attr_reader\n\nstandard_face_size = 160 # 160(weight) * 160(height)\ndetect_resolution = 80 # 80(weight) * 80(height)\n\nthe_face_attrs_reader = c_face_attr_reader(standard_face_size)\nthe_filter = c_face_filter()\nface_detect = c_MTCNNDetect(tf.Graph(), scale_factor=2) #scale_factor, rescales image for faster detection\nvs = cv2.VideoCapture(0)\n\nret = 0\nwhile ret >= 0:\n ret = record_single_face()"},"input_ids":{"kind":"list like","value":[11748,269,85,17,11,33918,11,25064,11,4818,8079,198,11748,11192,273,11125,355,48700,198,11748,299,32152,355,45941,198,198,6738,1986,62,24455,1330,269,62,2550,62,24455,198,6738,285,23047,20471,62,15255,478,1330,269,62,44,4825,6144,47504,198,6738,1986,62,35226,1330,269,62,2550,62,35226,62,46862,198,198,20307,62,2550,62,7857,796,13454,1303,13454,7,6551,8,1635,13454,7,17015,8,198,15255,478,62,29268,796,4019,1303,4019,7,6551,8,1635,4019,7,17015,8,198,198,1169,62,2550,62,1078,3808,62,46862,796,269,62,2550,62,35226,62,46862,7,20307,62,2550,62,7857,8,198,1169,62,24455,796,269,62,2550,62,24455,3419,198,2550,62,15255,478,796,269,62,44,4825,6144,47504,7,27110,13,37065,22784,5046,62,31412,28,17,8,1303,9888,62,31412,11,6811,2040,2939,329,5443,13326,198,14259,796,269,85,17,13,10798,49630,7,15,8,198,198,1186,796,657,198,4514,1005,18189,657,25,198,220,220,220,1005,796,1700,62,29762,62,2550,3419],"string":"[\n 11748,\n 269,\n 85,\n 17,\n 11,\n 33918,\n 11,\n 25064,\n 11,\n 4818,\n 8079,\n 198,\n 11748,\n 11192,\n 273,\n 11125,\n 355,\n 48700,\n 198,\n 11748,\n 299,\n 32152,\n 355,\n 45941,\n 198,\n 198,\n 6738,\n 1986,\n 62,\n 24455,\n 1330,\n 269,\n 62,\n 2550,\n 62,\n 24455,\n 198,\n 6738,\n 285,\n 23047,\n 20471,\n 62,\n 15255,\n 478,\n 1330,\n 269,\n 62,\n 44,\n 4825,\n 6144,\n 47504,\n 198,\n 6738,\n 1986,\n 62,\n 35226,\n 1330,\n 269,\n 62,\n 2550,\n 62,\n 35226,\n 62,\n 46862,\n 198,\n 198,\n 20307,\n 62,\n 2550,\n 62,\n 7857,\n 796,\n 13454,\n 1303,\n 13454,\n 7,\n 6551,\n 8,\n 1635,\n 13454,\n 7,\n 17015,\n 8,\n 198,\n 15255,\n 478,\n 62,\n 29268,\n 796,\n 4019,\n 1303,\n 4019,\n 7,\n 6551,\n 8,\n 1635,\n 4019,\n 7,\n 17015,\n 8,\n 198,\n 198,\n 1169,\n 62,\n 2550,\n 62,\n 1078,\n 3808,\n 62,\n 46862,\n 796,\n 269,\n 62,\n 2550,\n 62,\n 35226,\n 62,\n 46862,\n 7,\n 20307,\n 62,\n 2550,\n 62,\n 7857,\n 8,\n 198,\n 1169,\n 62,\n 24455,\n 796,\n 269,\n 62,\n 2550,\n 62,\n 24455,\n 3419,\n 198,\n 2550,\n 62,\n 15255,\n 478,\n 796,\n 269,\n 62,\n 44,\n 4825,\n 6144,\n 47504,\n 7,\n 27110,\n 13,\n 37065,\n 22784,\n 5046,\n 62,\n 31412,\n 28,\n 17,\n 8,\n 1303,\n 9888,\n 62,\n 31412,\n 11,\n 6811,\n 2040,\n 2939,\n 329,\n 5443,\n 13326,\n 198,\n 14259,\n 796,\n 269,\n 85,\n 17,\n 13,\n 10798,\n 49630,\n 7,\n 15,\n 8,\n 198,\n 198,\n 1186,\n 796,\n 657,\n 198,\n 4514,\n 1005,\n 18189,\n 657,\n 25,\n 198,\n 220,\n 220,\n 220,\n 1005,\n 796,\n 1700,\n 62,\n 29762,\n 62,\n 2550,\n 3419\n]"},"ratio_char_token":{"kind":"number","value":2.8146341463414632,"string":"2.814634"},"token_count":{"kind":"number","value":205,"string":"205"}}},{"rowIdx":1262,"cells":{"content":{"kind":"string","value":"from pandac import PandaModules as PM\nfrom direct.directnotify import DirectNotifyGlobal\nfrom direct.showbase.PythonUtil import list2dict, uniqueElements\nimport string\nimport LevelConstants\nimport types\nif __dev__:\n import os\n"},"input_ids":{"kind":"list like","value":[6738,19798,330,1330,41112,5841,5028,355,3122,198,6738,1277,13,12942,1662,1958,1330,4128,3673,1958,22289,198,6738,1277,13,12860,8692,13,37906,18274,346,1330,1351,17,11600,11,3748,36,3639,198,11748,4731,198,11748,5684,34184,1187,198,11748,3858,198,361,11593,7959,834,25,198,220,220,220,1330,28686,198],"string":"[\n 6738,\n 19798,\n 330,\n 1330,\n 41112,\n 5841,\n 5028,\n 355,\n 3122,\n 198,\n 6738,\n 1277,\n 13,\n 12942,\n 1662,\n 1958,\n 1330,\n 4128,\n 3673,\n 1958,\n 22289,\n 198,\n 6738,\n 1277,\n 13,\n 12860,\n 8692,\n 13,\n 37906,\n 18274,\n 346,\n 1330,\n 1351,\n 17,\n 11600,\n 11,\n 3748,\n 36,\n 3639,\n 198,\n 11748,\n 4731,\n 198,\n 11748,\n 5684,\n 34184,\n 1187,\n 198,\n 11748,\n 3858,\n 198,\n 361,\n 11593,\n 7959,\n 834,\n 25,\n 198,\n 220,\n 220,\n 220,\n 1330,\n 28686,\n 198\n]"},"ratio_char_token":{"kind":"number","value":3.634920634920635,"string":"3.634921"},"token_count":{"kind":"number","value":63,"string":"63"}}},{"rowIdx":1263,"cells":{"content":{"kind":"string","value":"#!/usr/bin/env python\n\n# # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # \n#\n# Copyright (c) 2017 Jamf. All rights reserved.\n#\n# Redistribution and use in source and binary forms, with or without\n# modification, are permitted provided that the following conditions are met:\n# * Redistributions of source code must retain the above copyright\n# notice, this list of conditions and the following disclaimer.\n# * Redistributions in binary form must reproduce the above copyright\n# notice, this list of conditions and the following disclaimer in the\n# documentation and/or other materials provided with the distribution.\n# * Neither the name of the Jamf nor the names of its contributors may be\n# used to endorse or promote products derived from this software without \n# specific prior written permission.\n#\n# THIS SOFTWARE IS PROVIDED BY JAMF SOFTWARE, LLC \"AS IS\" AND ANY\n# EXPRESS OR IMPLIED WARRANTIES, INCLUDING, BUT NOT LIMITED TO, THE IMPLIED\n# WARRANTIES OF MERCHANTABILITY AND FITNESS FOR A PARTICULAR PURPOSE ARE\n# DISCLAIMED. IN NO EVENT SHALL JAMF SOFTWARE, LLC BE LIABLE FOR ANY\n# DIRECT, INDIRECT, INCIDENTAL, SPECIAL, EXEMPLARY, OR CONSEQUENTIAL DAMAGES\n# (INCLUDING, BUT NOT LIMITED TO, PROCUREMENT OF SUBSTITUTE GOODS OR SERVICES;\n# LOSS OF USE, DATA, OR PROFITS; OR BUSINESS INTERRUPTION) HOWEVER CAUSED AND\n# ON ANY THEORY OF LIABILITY, WHETHER IN CONTRACT, STRICT LIABILITY, OR TORT\n# (INCLUDING NEGLIGENCE OR OTHERWISE) ARISING IN ANY WAY OUT OF THE USE OF THIS\n# SOFTWARE, EVEN IF ADVISED OF THE POSSIBILITY OF SUCH DAMAGE.\n#\n# # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # \n\n# # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # \n# \n# This script was modified from Andrina Kelly's version presented at JNUC2013 for allowing\n# a user to elevate their privelages to administrator once per day for 60 minutes. After \n# the 60 minutes if a user created a new admin account that account will have admin rights\n# also revoked.\n#\n# To accomplish this the following will be performed:\n#\t\t\t- A launch daemon will be put in place in order to remove admin rights\n#\t\t\t- Log will be written to tempAdmin.log\n#\t\t\t- This policy in Jamf will be set to only be allowed once per day\n#\n# REQUIREMENTS:\n#\t\t\t- Jamf Pro\n#\t\t\t- Policy for enabling tempAdmin via Self Service\n#\t\t\t- Policy to remove tempAdmin via custom trigger\n#\t\t\t- tempAdmin.sh & removeTempAdmin.sh Scripts\n#\n#\n# Written by: Joshua Roskos | Professional Services Engineer | Jamf\n#\n# Created On: June 20th, 2017\n# Updated On: July 26th, 2017\n# \n# # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # \n\n# # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # \n# IMPORTS\n# # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # \n\nimport os, plistlib, pwd, grp, subprocess, sys\nfrom SystemConfiguration import SCDynamicStoreCopyConsoleUser\nfrom datetime import datetime\n\n\n# # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # \n# VARIABLES\n# # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # \n\nuserName = (SCDynamicStoreCopyConsoleUser(None, None, None) or [None])[0] # get the logged in user's name\nworkingDir = '/usr/local/jamfps/' # working directory for script\nlaunchdFile = 'com.jamfps.adminremove.plist' # launch daemon file name\nlaunchdLabel = launchdFile.replace('.plist', '') # launch daemon label\nplistFile = 'MakeMeAdmin.plist' # settings file name\ntempAdminLog = 'tempAdmin.log' # script log file\nadminTimer = 3600 # how long should they have admin rights for (in seconds)\npolicyCustomTrigger = 'adminremove' # custom trigger specified for removeTempAdmin.py policy\n\n# # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # \n# LAUNCH DAEMON\n# # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # \n\n# place launchd plist to call JSS policy to remove admin rights.\nprint 'Creating LaunchDaemon...'\nlaunchDaemon = { 'Label':launchdLabel,\n 'LaunchOnlyOnce':True,\n 'ProgramArguments':['/usr/local/jamf/bin/jamf', 'policy', '-trigger', policyCustomTrigger],\n 'StartInterval':adminTimer,\n 'UserName':'root',\n }\nplistlib.writePlist(launchDaemon, '/Library/LaunchDaemons/' + launchdFile)\n\n# set the permission on the file just made.\nuserID = pwd.getpwnam(\"root\").pw_uid\ngroupID = grp.getgrnam(\"wheel\").gr_gid\nos.chown('/Library/LaunchDaemons/' + launchdFile, userID, groupID)\nos.chmod('/Library/LaunchDaemons/' + launchdFile, 0644)\n\n# load the removal plist timer. \nprint 'Loading LaunchDaemon...'\nsubprocess.call([\"launchctl\", \"load\", \"-w\", '/Library/LaunchDaemons/' + launchdFile])\n\n# # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # \n# APPLICATION\n# # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # \n\n# build log files\nif not os.path.exists(workingDir):\n os.makedirs(workingDir)\n\n# record user that will need to have admin rights removed\n# record current existing admins\nprint 'Retrieving List of Current Admins...'\ncurrentAdmins = grp.getgrnam('admin').gr_mem\nprint 'Updating Plist...'\nplist = { 'User2Remove':userName,\n 'CurrentAdminUsers':currentAdmins}\nplistlib.writePlist(plist, workingDir + plistFile)\n\n# give current logged user admin rights\nsubprocess.call([\"dseditgroup\", \"-o\", \"edit\", \"-a\", userName, \"-t\", \"user\", \"admin\"])\n\n# add log entry\nlog = open(workingDir + tempAdminLog, \"a+\")\nlog.write(\"{} - MakeMeAdmin Granted Admin Rights for {}\\r\\n\".format(datetime.now(), userName))\nlog.close()\n\nprint 'Granted Admin Right to ' + userName\n"},"input_ids":{"kind":"list like","value":[2,48443,14629,14,8800,14,24330,21015,198,198,2,1303,1303,1303,1303,1303,1303,1303,1303,1303,1303,1303,1303,1303,1303,1303,1303,1303,1303,1303,1303,1303,1303,1303,1303,1303,1303,1303,1303,1303,1303,1303,1303,1303,1303,1303,1303,1303,1303,1303,1303,1303,1303,1303,1303,1303,220,198,2,198,2,15069,357,66,8,2177,9986,69,13,220,1439,2489,10395,13,198,2,198,2,220,220,220,220,220,220,2297,396,3890,290,779,287,2723,290,13934,5107,11,351,393,1231,198,2,220,220,220,220,220,220,17613,11,389,10431,2810,326,262,1708,3403,389,1138,25,198,2,220,220,220,220,220,220,220,220,220,220,220,220,220,220,1635,2297,396,2455,507,286,2723,2438,1276,12377,262,2029,6634,198,2,220,220,220,220,220,220,220,220,220,220,220,220,220,220,220,220,4003,11,428,1351,286,3403,290,262,1708,37592,13,198,2,220,220,220,220,220,220,220,220,220,220,220,220,220,220,1635,2297,396,2455,507,287,13934,1296,1276,22919,262,2029,6634,198,2,220,220,220,220,220,220,220,220,220,220,220,220,220,220,220,220,4003,11,428,1351,286,3403,290,262,1708,37592,287,262,198,2,220,220,220,220,220,220,220,220,220,220,220,220,220,220,220,220,10314,290,14,273,584,5696,2810,351,262,6082,13,198,2,220,220,220,220,220,220,220,220,220,220,220,220,220,220,1635,16126,262,1438,286,262,9986,69,4249,262,3891,286,663,20420,743,307,198,2,220,220,220,220,220,220,220,220,220,220,220,220,220,220,220,220,973,284,11438,393,7719,3186,10944,422,428,3788,1231,220,198,2,220,220,220,220,220,220,220,220,220,220,220,220,220,220,220,220,2176,3161,3194,7170,13,198,2,198,2,220,220,220,220,220,220,12680,47466,3180,36592,2389,1961,11050,449,2390,37,47466,11,11419,366,1921,3180,1,5357,15529,198,2,220,220,220,220,220,220,7788,32761,6375,8959,49094,34764,11015,11,47783,2751,11,21728,5626,40880,5390,11,3336,8959,49094,198,2,220,220,220,220,220,220,34764,11015,3963,34482,3398,1565,5603,25382,5357,376,46144,7473,317,16652,2149,37232,33079,48933,15986,198,2,220,220,220,220,220,220,13954,48778,1961,13,3268,8005,49261,50163,449,2390,37,47466,11,11419,9348,43031,19146,7473,15529,198,2,220,220,220,220,220,220,42242,11,3268,17931,23988,11,19387,25256,1847,11,38846,11,7788,3620,6489,13153,11,6375,7102,5188,10917,3525,12576,29506,25552,198,2,220,220,220,220,220,220,357,1268,39149,2751,11,21728,5626,40880,5390,11,41755,11335,10979,3963,28932,2257,2043,37780,21090,50,6375,49254,26,198,2,220,220,220,220,220,220,406,18420,3963,23210,11,42865,11,6375,4810,19238,29722,26,6375,43949,44180,23255,49,8577,24131,8,29630,36,5959,7257,2937,1961,5357,198,2,220,220,220,220,220,220,6177,15529,3336,15513,3963,43031,25382,11,7655,2767,16879,3268,27342,10659,11,19269,18379,43031,25382,11,6375,309,9863,198,2,220,220,220,220,220,220,357,1268,39149,2751,399,7156,43,3528,18310,6375,25401,54,24352,8,5923,1797,2751,3268,15529,34882,16289,3963,3336,23210,3963,12680,198,2,220,220,220,220,220,220,47466,11,45886,16876,5984,29817,1961,3963,3336,28069,11584,25382,3963,13558,3398,29506,11879,13,198,2,198,2,1303,1303,1303,1303,1303,1303,1303,1303,1303,1303,1303,1303,1303,1303,1303,1303,1303,1303,1303,1303,1303,1303,1303,1303,1303,1303,1303,1303,1303,1303,1303,1303,1303,1303,1303,1303,1303,1303,1303,1303,1303,1303,1303,1303,1303,220,198,198,2,1303,1303,1303,1303,1303,1303,1303,1303,1303,1303,1303,1303,1303,1303,1303,1303,1303,1303,1303,1303,1303,1303,1303,1303,1303,1303,1303,1303,1303,1303,1303,1303,1303,1303,1303,1303,1303,1303,1303,1303,1303,1303,1303,1303,1303,220,198,2,220,198,2,770,4226,373,9518,422,843,22267,9077,338,2196,5545,379,449,45,9598,6390,329,5086,198,2,257,2836,284,36830,511,1293,626,1095,284,18382,1752,583,1110,329,3126,2431,13,2293,220,198,2,262,3126,2431,611,257,2836,2727,257,649,13169,1848,326,1848,481,423,13169,2489,198,2,635,30809,13,198,2,198,2,1675,9989,428,262,1708,481,307,6157,25,198,2,197,197,197,12,317,4219,33386,481,307,1234,287,1295,287,1502,284,4781,13169,2489,198,2,197,197,197,12,5972,481,307,3194,284,20218,46787,13,6404,198,2,197,197,197,12,770,2450,287,9986,69,481,307,900,284,691,307,3142,1752,583,1110,198,2,198,2,4526,49128,28957,25,198,2,197,197,197,12,9986,69,1041,198,2,197,197,197,12,7820,329,15882,20218,46787,2884,12189,4809,198,2,197,197,197,12,7820,284,4781,20218,46787,2884,2183,7616,198,2,197,197,197,12,20218,46787,13,1477,1222,4781,30782,46787,13,1477,12327,82,198,2,198,2,198,2,22503,416,25,20700,10018,46150,930,18612,6168,23164,930,9986,69,198,2,198,2,15622,1550,25,2795,1160,400,11,2177,198,2,19433,1550,25,2901,2608,400,11,2177,198,2,220,198,2,1303,1303,1303,1303,1303,1303,1303,1303,1303,1303,1303,1303,1303,1303,1303,1303,1303,1303,1303,1303,1303,1303,1303,1303,1303,1303,1303,1303,1303,1303,1303,1303,1303,1303,1303,1303,1303,1303,1303,1303,1303,1303,1303,1303,1303,220,198,198,2,1303,1303,1303,1303,1303,1303,1303,1303,1303,1303,1303,1303,1303,1303,1303,1303,1303,1303,1303,1303,1303,1303,1303,1303,1303,1303,1303,1303,1303,1303,1303,1303,1303,1303,1303,1303,1303,1303,1303,1303,1303,1303,1303,1303,1303,220,198,2,30023,33002,198,2,1303,1303,1303,1303,1303,1303,1303,1303,1303,1303,1303,1303,1303,1303,1303,1303,1303,1303,1303,1303,1303,1303,1303,1303,1303,1303,1303,1303,1303,1303,1303,1303,1303,1303,1303,1303,1303,1303,1303,1303,1303,1303,1303,1303,1303,220,198,198,11748,28686,11,458,396,8019,11,279,16993,11,1036,79,11,850,14681,11,25064,198,6738,4482,38149,1330,6374,44090,22658,29881,47581,12982,198,6738,4818,8079,1330,4818,8079,628,198,2,1303,1303,1303,1303,1303,1303,1303,1303,1303,1303,1303,1303,1303,1303,1303,1303,1303,1303,1303,1303,1303,1303,1303,1303,1303,1303,1303,1303,1303,1303,1303,1303,1303,1303,1303,1303,1303,1303,1303,1303,1303,1303,1303,1303,1303,220,198,2,569,1503,3539,9148,1546,198,2,1303,1303,1303,1303,1303,1303,1303,1303,1303,1303,1303,1303,1303,1303,1303,1303,1303,1303,1303,1303,1303,1303,1303,1303,1303,1303,1303,1303,1303,1303,1303,1303,1303,1303,1303,1303,1303,1303,1303,1303,1303,1303,1303,1303,1303,220,198,198,7220,5376,796,357,6173,44090,22658,29881,47581,12982,7,14202,11,6045,11,6045,8,393,685,14202,12962,58,15,60,220,220,1303,651,262,18832,287,2836,338,1438,198,16090,35277,796,31051,14629,14,12001,14,39159,29647,14,6,220,220,220,220,220,220,220,220,220,220,220,220,220,220,220,220,220,220,220,220,220,220,220,220,220,220,220,220,220,220,220,220,220,220,220,220,220,220,220,220,220,220,1303,1762,8619,329,4226,198,35681,67,8979,796,705,785,13,39159,29647,13,28482,28956,13,489,396,6,220,220,220,220,220,220,220,220,220,220,220,220,220,220,220,220,220,220,220,220,220,220,220,220,220,220,220,220,220,220,220,1303,4219,33386,2393,1438,198,35681,67,33986,796,4219,67,8979,13,33491,7,4458,489,396,3256,10148,8,220,220,220,220,220,220,220,220,220,220,220,220,220,220,220,220,220,220,220,220,220,220,220,220,220,220,220,1303,4219,33386,6167,198,489,396,8979,796,705,12050,5308,46787,13,489,396,6,220,220,220,220,220,220,220,220,220,220,220,220,220,220,220,220,220,220,220,220,220,220,220,220,220,220,220,220,220,220,220,220,220,220,220,220,220,220,220,220,220,220,220,220,1303,6460,2393,1438,198,29510,46787,11187,796,705,29510,46787,13,6404,6,220,220,220,220,220,220,220,220,220,220,220,220,220,220,220,220,220,220,220,220,220,220,220,220,220,220,220,220,220,220,220,220,220,220,220,220,220,220,220,220,220,220,220,220,220,1303,4226,2604,2393,198,28482,48801,796,4570,405,220,220,220,220,220,220,220,220,220,220,220,220,220,220,220,220,220,220,220,220,220,220,220,220,220,220,220,220,220,220,220,220,220,220,220,220,220,220,220,220,220,220,220,220,220,220,220,220,220,220,220,220,220,220,220,220,220,220,1303,703,890,815,484,423,13169,2489,329,357,259,4201,8,198,30586,15022,48344,796,705,28482,28956,6,220,220,220,220,220,220,220,220,220,220,220,220,220,220,220,220,220,220,220,220,220,220,220,220,220,220,220,220,220,220,220,220,220,220,220,220,220,220,220,220,1303,2183,7616,7368,329,4781,30782,46787,13,9078,2450,198,198,2,1303,1303,1303,1303,1303,1303,1303,1303,1303,1303,1303,1303,1303,1303,1303,1303,1303,1303,1303,1303,1303,1303,1303,1303,1303,1303,1303,1303,1303,1303,1303,1303,1303,1303,1303,1303,1303,1303,1303,1303,1303,1303,1303,1303,1303,220,198,2,9131,47461,17051,3620,1340,198,2,1303,1303,1303,1303,1303,1303,1303,1303,1303,1303,1303,1303,1303,1303,1303,1303,1303,1303,1303,1303,1303,1303,1303,1303,1303,1303,1303,1303,1303,1303,1303,1303,1303,1303,1303,1303,1303,1303,1303,1303,1303,1303,1303,1303,1303,220,198,198,2,1295,4219,67,458,396,284,869,449,5432,2450,284,4781,13169,2489,13,198,4798,705,32071,21225,26531,7966,986,6,198,35681,26531,7966,796,1391,705,33986,10354,35681,67,33986,11,198,220,220,220,220,220,220,220,220,220,220,220,220,220,220,220,220,705,38296,10049,7454,10354,17821,11,198,220,220,220,220,220,220,220,220,220,220,220,220,220,220,220,220,705,15167,28100,2886,10354,17816,14,14629,14,12001,14,39159,69,14,8800,14,39159,69,3256,705,30586,3256,705,12,46284,3256,2450,15022,48344,4357,198,220,220,220,220,220,220,220,220,220,220,220,220,220,220,220,220,705,10434,9492,2100,10354,28482,48801,11,198,220,220,220,220,220,220,220,220,220,220,220,220,220,220,220,220,705,12982,5376,10354,6,15763,3256,198,220,220,220,220,220,220,220,220,220,220,220,220,220,220,220,220,1782,198,489,396,8019,13,13564,3646,396,7,35681,26531,7966,11,31051,23377,14,38296,26531,368,684,14,6,1343,4219,67,8979,8,198,198,2,900,262,7170,319,262,2393,655,925,13,198,7220,2389,796,279,16993,13,1136,79,675,321,7203,15763,11074,79,86,62,27112,198,8094,2389,796,1036,79,13,1136,2164,7402,7203,22001,11074,2164,62,70,312,198,418,13,354,593,10786,14,23377,14,38296,26531,368,684,14,6,1343,4219,67,8979,11,2836,2389,11,1448,2389,8,198,418,13,354,4666,10786,14,23377,14,38296,26531,368,684,14,6,1343,4219,67,8979,11,657,29173,8,198,198,2,3440,262,9934,458,396,19781,13,220,198,4798,705,19031,21225,26531,7966,986,6,198,7266,14681,13,13345,7,14692,35681,34168,1600,366,2220,1600,27444,86,1600,31051,23377,14,38296,26531,368,684,14,6,1343,4219,67,8979,12962,198,198,2,1303,1303,1303,1303,1303,1303,1303,1303,1303,1303,1303,1303,1303,1303,1303,1303,1303,1303,1303,1303,1303,1303,1303,1303,1303,1303,1303,1303,1303,1303,1303,1303,1303,1303,1303,1303,1303,1303,1303,1303,1303,1303,1303,1303,1303,220,198,2,39421,6234,198,2,1303,1303,1303,1303,1303,1303,1303,1303,1303,1303,1303,1303,1303,1303,1303,1303,1303,1303,1303,1303,1303,1303,1303,1303,1303,1303,1303,1303,1303,1303,1303,1303,1303,1303,1303,1303,1303,1303,1303,1303,1303,1303,1303,1303,1303,220,198,198,2,1382,2604,3696,198,361,407,28686,13,6978,13,1069,1023,7,16090,35277,2599,198,220,220,220,28686,13,76,4335,17062,7,16090,35277,8,198,198,2,1700,2836,326,481,761,284,423,13169,2489,4615,198,2,1700,1459,4683,44563,198,4798,705,9781,37418,7343,286,9236,1215,42951,986,6,198,14421,2782,42951,796,1036,79,13,1136,2164,7402,10786,28482,27691,2164,62,11883,198,4798,705,4933,38734,1345,396,986,6,198,489,396,796,1391,705,12982,17,27914,10354,7220,5376,11,198,220,220,220,220,220,220,220,220,220,705,11297,46787,14490,10354,14421,2782,42951,92,198,489,396,8019,13,13564,3646,396,7,489,396,11,1762,35277,1343,458,396,8979,8,198,198,2,1577,1459,18832,2836,13169,2489,198,7266,14681,13,13345,7,14692,9310,19312,8094,1600,27444,78,1600,366,19312,1600,27444,64,1600,2836,5376,11,27444,83,1600,366,7220,1600,366,28482,8973,8,198,198,2,751,2604,5726,198,6404,796,1280,7,16090,35277,1343,20218,46787,11187,11,366,64,10,4943,198,6404,13,13564,7203,90,92,532,6889,5308,46787,38842,32053,6923,329,23884,59,81,59,77,1911,18982,7,19608,8079,13,2197,22784,2836,5376,4008,198,6404,13,19836,3419,198,198,4798,705,8642,4126,32053,6498,284,705,1343,2836,5376,198],"string":"[\n 2,\n 48443,\n 14629,\n 14,\n 8800,\n 14,\n 24330,\n 21015,\n 198,\n 198,\n 2,\n 1303,\n 1303,\n 1303,\n 1303,\n 1303,\n 1303,\n 1303,\n 1303,\n 1303,\n 1303,\n 1303,\n 1303,\n 1303,\n 1303,\n 1303,\n 1303,\n 1303,\n 1303,\n 1303,\n 1303,\n 1303,\n 1303,\n 1303,\n 1303,\n 1303,\n 1303,\n 1303,\n 1303,\n 1303,\n 1303,\n 1303,\n 1303,\n 1303,\n 1303,\n 1303,\n 1303,\n 1303,\n 1303,\n 1303,\n 1303,\n 1303,\n 1303,\n 1303,\n 1303,\n 1303,\n 220,\n 198,\n 2,\n 198,\n 2,\n 15069,\n 357,\n 66,\n 8,\n 2177,\n 9986,\n 69,\n 13,\n 220,\n 1439,\n 2489,\n 10395,\n 13,\n 198,\n 2,\n 198,\n 2,\n 220,\n 220,\n 220,\n 220,\n 220,\n 220,\n 2297,\n 396,\n 3890,\n 290,\n 779,\n 287,\n 2723,\n 290,\n 13934,\n 5107,\n 11,\n 351,\n 393,\n 1231,\n 198,\n 2,\n 220,\n 220,\n 220,\n 220,\n 220,\n 220,\n 17613,\n 11,\n 389,\n 10431,\n 2810,\n 326,\n 262,\n 1708,\n 3403,\n 389,\n 1138,\n 25,\n 198,\n 2,\n 220,\n 220,\n 220,\n 220,\n 220,\n 220,\n 220,\n 220,\n 220,\n 220,\n 220,\n 220,\n 220,\n 220,\n 1635,\n 2297,\n 396,\n 2455,\n 507,\n 286,\n 2723,\n 2438,\n 1276,\n 12377,\n 262,\n 2029,\n 6634,\n 198,\n 2,\n 220,\n 220,\n 220,\n 220,\n 220,\n 220,\n 220,\n 220,\n 220,\n 220,\n 220,\n 220,\n 220,\n 220,\n 220,\n 220,\n 4003,\n 11,\n 428,\n 1351,\n 286,\n 3403,\n 290,\n 262,\n 1708,\n 37592,\n 13,\n 198,\n 2,\n 220,\n 220,\n 220,\n 220,\n 220,\n 220,\n 220,\n 220,\n 220,\n 220,\n 220,\n 220,\n 220,\n 220,\n 1635,\n 2297,\n 396,\n 2455,\n 507,\n 287,\n 13934,\n 1296,\n 1276,\n 22919,\n 262,\n 2029,\n 6634,\n 198,\n 2,\n 220,\n 220,\n 220,\n 220,\n 220,\n 220,\n 220,\n 220,\n 220,\n 220,\n 220,\n 220,\n 220,\n 220,\n 220,\n 220,\n 4003,\n 11,\n 428,\n 1351,\n 286,\n 3403,\n 290,\n 262,\n 1708,\n 37592,\n 287,\n 262,\n 198,\n 2,\n 220,\n 220,\n 220,\n 220,\n 220,\n 220,\n 220,\n 220,\n 220,\n 220,\n 220,\n 220,\n 220,\n 220,\n 220,\n 220,\n 10314,\n 290,\n 14,\n 273,\n 584,\n 5696,\n 2810,\n 351,\n 262,\n 6082,\n 13,\n 198,\n 2,\n 220,\n 220,\n 220,\n 220,\n 220,\n 220,\n 220,\n 220,\n 220,\n 220,\n 220,\n 220,\n 220,\n 220,\n 1635,\n 16126,\n 262,\n 1438,\n 286,\n 262,\n 9986,\n 69,\n 4249,\n 262,\n 3891,\n 286,\n 663,\n 20420,\n 743,\n 307,\n 198,\n 2,\n 220,\n 220,\n 220,\n 220,\n 220,\n 220,\n 220,\n 220,\n 220,\n 220,\n 220,\n 220,\n 220,\n 220,\n 220,\n 220,\n 973,\n 284,\n 11438,\n 393,\n 7719,\n 3186,\n 10944,\n 422,\n 428,\n 3788,\n 1231,\n 220,\n 198,\n 2,\n 220,\n 220,\n 220,\n 220,\n 220,\n 220,\n 220,\n 220,\n 220,\n 220,\n 220,\n 220,\n 220,\n 220,\n 220,\n 220,\n 2176,\n 3161,\n 3194,\n 7170,\n 13,\n 198,\n 2,\n 198,\n 2,\n 220,\n 220,\n 220,\n 220,\n 220,\n 220,\n 12680,\n 47466,\n 3180,\n 36592,\n 2389,\n 1961,\n 11050,\n 449,\n 2390,\n 37,\n 47466,\n 11,\n 11419,\n 366,\n 1921,\n 3180,\n 1,\n 5357,\n 15529,\n 198,\n 2,\n 220,\n 220,\n 220,\n 220,\n 220,\n 220,\n 7788,\n 32761,\n 6375,\n 8959,\n 49094,\n 34764,\n 11015,\n 11,\n 47783,\n 2751,\n 11,\n 21728,\n 5626,\n 40880,\n 5390,\n 11,\n 3336,\n 8959,\n 49094,\n 198,\n 2,\n 220,\n 220,\n 220,\n 220,\n 220,\n 220,\n 34764,\n 11015,\n 3963,\n 34482,\n 3398,\n 1565,\n 5603,\n 25382,\n 5357,\n 376,\n 46144,\n 7473,\n 317,\n 16652,\n 2149,\n 37232,\n 33079,\n 48933,\n 15986,\n 198,\n 2,\n 220,\n 220,\n 220,\n 220,\n 220,\n 220,\n 13954,\n 48778,\n 1961,\n 13,\n 3268,\n 8005,\n 49261,\n 50163,\n 449,\n 2390,\n 37,\n 47466,\n 11,\n 11419,\n 9348,\n 43031,\n 19146,\n 7473,\n 15529,\n 198,\n 2,\n 220,\n 220,\n 220,\n 220,\n 220,\n 220,\n 42242,\n 11,\n 3268,\n 17931,\n 23988,\n 11,\n 19387,\n 25256,\n 1847,\n 11,\n 38846,\n 11,\n 7788,\n 3620,\n 6489,\n 13153,\n 11,\n 6375,\n 7102,\n 5188,\n 10917,\n 3525,\n 12576,\n 29506,\n 25552,\n 198,\n 2,\n 220,\n 220,\n 220,\n 220,\n 220,\n 220,\n 357,\n 1268,\n 39149,\n 2751,\n 11,\n 21728,\n 5626,\n 40880,\n 5390,\n 11,\n 41755,\n 11335,\n 10979,\n 3963,\n 28932,\n 2257,\n 2043,\n 37780,\n 21090,\n 50,\n 6375,\n 49254,\n 26,\n 198,\n 2,\n 220,\n 220,\n 220,\n 220,\n 220,\n 220,\n 406,\n 18420,\n 3963,\n 23210,\n 11,\n 42865,\n 11,\n 6375,\n 4810,\n 19238,\n 29722,\n 26,\n 6375,\n 43949,\n 44180,\n 23255,\n 49,\n 8577,\n 24131,\n 8,\n 29630,\n 36,\n 5959,\n 7257,\n 2937,\n 1961,\n 5357,\n 198,\n 2,\n 220,\n 220,\n 220,\n 220,\n 220,\n 220,\n 6177,\n 15529,\n 3336,\n 15513,\n 3963,\n 43031,\n 25382,\n 11,\n 7655,\n 2767,\n 16879,\n 3268,\n 27342,\n 10659,\n 11,\n 19269,\n 18379,\n 43031,\n 25382,\n 11,\n 6375,\n 309,\n 9863,\n 198,\n 2,\n 220,\n 220,\n 220,\n 220,\n 220,\n 220,\n 357,\n 1268,\n 39149,\n 2751,\n 399,\n 7156,\n 43,\n 3528,\n 18310,\n 6375,\n 25401,\n 54,\n 24352,\n 8,\n 5923,\n 1797,\n 2751,\n 3268,\n 15529,\n 34882,\n 16289,\n 3963,\n 3336,\n 23210,\n 3963,\n 12680,\n 198,\n 2,\n 220,\n 220,\n 220,\n 220,\n 220,\n 220,\n 47466,\n 11,\n 45886,\n 16876,\n 5984,\n 29817,\n 1961,\n 3963,\n 3336,\n 28069,\n 11584,\n 25382,\n 3963,\n 13558,\n 3398,\n 29506,\n 11879,\n 13,\n 198,\n 2,\n 198,\n 2,\n 1303,\n 1303,\n 1303,\n 1303,\n 1303,\n 1303,\n 1303,\n 1303,\n 1303,\n 1303,\n 1303,\n 1303,\n 1303,\n 1303,\n 1303,\n 1303,\n 1303,\n 1303,\n 1303,\n 1303,\n 1303,\n 1303,\n 1303,\n 1303,\n 1303,\n 1303,\n 1303,\n 1303,\n 1303,\n 1303,\n 1303,\n 1303,\n 1303,\n 1303,\n 1303,\n 1303,\n 1303,\n 1303,\n 1303,\n 1303,\n 1303,\n 1303,\n 1303,\n 1303,\n 1303,\n 220,\n 198,\n 198,\n 2,\n 1303,\n 1303,\n 1303,\n 1303,\n 1303,\n 1303,\n 1303,\n 1303,\n 1303,\n 1303,\n 1303,\n 1303,\n 1303,\n 1303,\n 1303,\n 1303,\n 1303,\n 1303,\n 1303,\n 1303,\n 1303,\n 1303,\n 1303,\n 1303,\n 1303,\n 1303,\n 1303,\n 1303,\n 1303,\n 1303,\n 1303,\n 1303,\n 1303,\n 1303,\n 1303,\n 1303,\n 1303,\n 1303,\n 1303,\n 1303,\n 1303,\n 1303,\n 1303,\n 1303,\n 1303,\n 220,\n 198,\n 2,\n 220,\n 198,\n 2,\n 770,\n 4226,\n 373,\n 9518,\n 422,\n 843,\n 22267,\n 9077,\n 338,\n 2196,\n 5545,\n 379,\n 449,\n 45,\n 9598,\n 6390,\n 329,\n 5086,\n 198,\n 2,\n 257,\n 2836,\n 284,\n 36830,\n 511,\n 1293,\n 626,\n 1095,\n 284,\n 18382,\n 1752,\n 583,\n 1110,\n 329,\n 3126,\n 2431,\n 13,\n 2293,\n 220,\n 198,\n 2,\n 262,\n 3126,\n 2431,\n 611,\n 257,\n 2836,\n 2727,\n 257,\n 649,\n 13169,\n 1848,\n 326,\n 1848,\n 481,\n 423,\n 13169,\n 2489,\n 198,\n 2,\n 635,\n 30809,\n 13,\n 198,\n 2,\n 198,\n 2,\n 1675,\n 9989,\n 428,\n 262,\n 1708,\n 481,\n 307,\n 6157,\n 25,\n 198,\n 2,\n 197,\n 197,\n 197,\n 12,\n 317,\n 4219,\n 33386,\n 481,\n 307,\n 1234,\n 287,\n 1295,\n 287,\n 1502,\n 284,\n 4781,\n 13169,\n 2489,\n 198,\n 2,\n 197,\n 197,\n 197,\n 12,\n 5972,\n 481,\n 307,\n 3194,\n 284,\n 20218,\n 46787,\n 13,\n 6404,\n 198,\n 2,\n 197,\n 197,\n 197,\n 12,\n 770,\n 2450,\n 287,\n 9986,\n 69,\n 481,\n 307,\n 900,\n 284,\n 691,\n 307,\n 3142,\n 1752,\n 583,\n 1110,\n 198,\n 2,\n 198,\n 2,\n 4526,\n 49128,\n 28957,\n 25,\n 198,\n 2,\n 197,\n 197,\n 197,\n 12,\n 9986,\n 69,\n 1041,\n 198,\n 2,\n 197,\n 197,\n 197,\n 12,\n 7820,\n 329,\n 15882,\n 20218,\n 46787,\n 2884,\n 12189,\n 4809,\n 198,\n 2,\n 197,\n 197,\n 197,\n 12,\n 7820,\n 284,\n 4781,\n 20218,\n 46787,\n 2884,\n 2183,\n 7616,\n 198,\n 2,\n 197,\n 197,\n 197,\n 12,\n 20218,\n 46787,\n 13,\n 1477,\n 1222,\n 4781,\n 30782,\n 46787,\n 13,\n 1477,\n 12327,\n 82,\n 198,\n 2,\n 198,\n 2,\n 198,\n 2,\n 22503,\n 416,\n 25,\n 20700,\n 10018,\n 46150,\n 930,\n 18612,\n 6168,\n 23164,\n 930,\n 9986,\n 69,\n 198,\n 2,\n 198,\n 2,\n 15622,\n 1550,\n 25,\n 2795,\n 1160,\n 400,\n 11,\n 2177,\n 198,\n 2,\n 19433,\n 1550,\n 25,\n 2901,\n 2608,\n 400,\n 11,\n 2177,\n 198,\n 2,\n 220,\n 198,\n 2,\n 1303,\n 1303,\n 1303,\n 1303,\n 1303,\n 1303,\n 1303,\n 1303,\n 1303,\n 1303,\n 1303,\n 1303,\n 1303,\n 1303,\n 1303,\n 1303,\n 1303,\n 1303,\n 1303,\n 1303,\n 1303,\n 1303,\n 1303,\n 1303,\n 1303,\n 1303,\n 1303,\n 1303,\n 1303,\n 1303,\n 1303,\n 1303,\n 1303,\n 1303,\n 1303,\n 1303,\n 1303,\n 1303,\n 1303,\n 1303,\n 1303,\n 1303,\n 1303,\n 1303,\n 1303,\n 220,\n 198,\n 198,\n 2,\n 1303,\n 1303,\n 1303,\n 1303,\n 1303,\n 1303,\n 1303,\n 1303,\n 1303,\n 1303,\n 1303,\n 1303,\n 1303,\n 1303,\n 1303,\n 1303,\n 1303,\n 1303,\n 1303,\n 1303,\n 1303,\n 1303,\n 1303,\n 1303,\n 1303,\n 1303,\n 1303,\n 1303,\n 1303,\n 1303,\n 1303,\n 1303,\n 1303,\n 1303,\n 1303,\n 1303,\n 1303,\n 1303,\n 1303,\n 1303,\n 1303,\n 1303,\n 1303,\n 1303,\n 1303,\n 220,\n 198,\n 2,\n 30023,\n 33002,\n 198,\n 2,\n 1303,\n 1303,\n 1303,\n 1303,\n 1303,\n 1303,\n 1303,\n 1303,\n 1303,\n 1303,\n 1303,\n 1303,\n 1303,\n 1303,\n 1303,\n 1303,\n 1303,\n 1303,\n 1303,\n 1303,\n 1303,\n 1303,\n 1303,\n 1303,\n 1303,\n 1303,\n 1303,\n 1303,\n 1303,\n 1303,\n 1303,\n 1303,\n 1303,\n 1303,\n 1303,\n 1303,\n 1303,\n 1303,\n 1303,\n 1303,\n 1303,\n 1303,\n 1303,\n 1303,\n 1303,\n 220,\n 198,\n 198,\n 11748,\n 28686,\n 11,\n 458,\n 396,\n 8019,\n 11,\n 279,\n 16993,\n 11,\n 1036,\n 79,\n 11,\n 850,\n 14681,\n 11,\n 25064,\n 198,\n 6738,\n 4482,\n 38149,\n 1330,\n 6374,\n 44090,\n 22658,\n 29881,\n 47581,\n 12982,\n 198,\n 6738,\n 4818,\n 8079,\n 1330,\n 4818,\n 8079,\n 628,\n 198,\n 2,\n 1303,\n 1303,\n 1303,\n 1303,\n 1303,\n 1303,\n 1303,\n 1303,\n 1303,\n 1303,\n 1303,\n 1303,\n 1303,\n 1303,\n 1303,\n 1303,\n 1303,\n 1303,\n 1303,\n 1303,\n 1303,\n 1303,\n 1303,\n 1303,\n 1303,\n 1303,\n 1303,\n 1303,\n 1303,\n 1303,\n 1303,\n 1303,\n 1303,\n 1303,\n 1303,\n 1303,\n 1303,\n 1303,\n 1303,\n 1303,\n 1303,\n 1303,\n 1303,\n 1303,\n 1303,\n 220,\n 198,\n 2,\n 569,\n 1503,\n 3539,\n 9148,\n 1546,\n 198,\n 2,\n 1303,\n 1303,\n 1303,\n 1303,\n 1303,\n 1303,\n 1303,\n 1303,\n 1303,\n 1303,\n 1303,\n 1303,\n 1303,\n 1303,\n 1303,\n 1303,\n 1303,\n 1303,\n 1303,\n 1303,\n 1303,\n 1303,\n 1303,\n 1303,\n 1303,\n 1303,\n 1303,\n 1303,\n 1303,\n 1303,\n 1303,\n 1303,\n 1303,\n 1303,\n 1303,\n 1303,\n 1303,\n 1303,\n 1303,\n 1303,\n 1303,\n 1303,\n 1303,\n 1303,\n 1303,\n 220,\n 198,\n 198,\n 7220,\n 5376,\n 796,\n 357,\n 6173,\n 44090,\n 22658,\n 29881,\n 47581,\n 12982,\n 7,\n 14202,\n 11,\n 6045,\n 11,\n 6045,\n 8,\n 393,\n 685,\n 14202,\n 12962,\n 58,\n 15,\n 60,\n 220,\n 220,\n 1303,\n 651,\n 262,\n 18832,\n 287,\n 2836,\n 338,\n 1438,\n 198,\n 16090,\n 35277,\n 796,\n 31051,\n 14629,\n 14,\n 12001,\n 14,\n 39159,\n 29647,\n 14,\n 6,\n 220,\n 220,\n 220,\n 220,\n 220,\n 220,\n 220,\n 220,\n 220,\n 220,\n 220,\n 220,\n 220,\n 220,\n 220,\n 220,\n 220,\n 220,\n 220,\n 220,\n 220,\n 220,\n 220,\n 220,\n 220,\n 220,\n 220,\n 220,\n 220,\n 220,\n 220,\n 220,\n 220,\n 220,\n 220,\n 220,\n 220,\n 220,\n 220,\n 220,\n 220,\n 220,\n 1303,\n 1762,\n 8619,\n 329,\n 4226,\n 198,\n 35681,\n 67,\n 8979,\n 796,\n 705,\n 785,\n 13,\n 39159,\n 29647,\n 13,\n 28482,\n 28956,\n 13,\n 489,\n 396,\n 6,\n 220,\n 220,\n 220,\n 220,\n 220,\n 220,\n 220,\n 220,\n 220,\n 220,\n 220,\n 220,\n 220,\n 220,\n 220,\n 220,\n 220,\n 220,\n 220,\n 220,\n 220,\n 220,\n 220,\n 220,\n 220,\n 220,\n 220,\n 220,\n 220,\n 220,\n 220,\n 1303,\n 4219,\n 33386,\n 2393,\n 1438,\n 198,\n 35681,\n 67,\n 33986,\n 796,\n 4219,\n 67,\n 8979,\n 13,\n 33491,\n 7,\n 4458,\n 489,\n 396,\n 3256,\n 10148,\n 8,\n 220,\n 220,\n 220,\n 220,\n 220,\n 220,\n 220,\n 220,\n 220,\n 220,\n 220,\n 220,\n 220,\n 220,\n 220,\n 220,\n 220,\n 220,\n 220,\n 220,\n 220,\n 220,\n 220,\n 220,\n 220,\n 220,\n 220,\n 1303,\n 4219,\n 33386,\n 6167,\n 198,\n 489,\n 396,\n 8979,\n 796,\n 705,\n 12050,\n 5308,\n 46787,\n 13,\n 489,\n 396,\n 6,\n 220,\n 220,\n 220,\n 220,\n 220,\n 220,\n 220,\n 220,\n 220,\n 220,\n 220,\n 220,\n 220,\n 220,\n 220,\n 220,\n 220,\n 220,\n 220,\n 220,\n 220,\n 220,\n 220,\n 220,\n 220,\n 220,\n 220,\n 220,\n 220,\n 220,\n 220,\n 220,\n 220,\n 220,\n 220,\n 220,\n 220,\n 220,\n 220,\n 220,\n 220,\n 220,\n 220,\n 220,\n 1303,\n 6460,\n 2393,\n 1438,\n 198,\n 29510,\n 46787,\n 11187,\n 796,\n 705,\n 29510,\n 46787,\n 13,\n 6404,\n 6,\n 220,\n 220,\n 220,\n 220,\n 220,\n 220,\n 220,\n 220,\n 220,\n 220,\n 220,\n 220,\n 220,\n 220,\n 220,\n 220,\n 220,\n 220,\n 220,\n 220,\n 220,\n 220,\n 220,\n 220,\n 220,\n 220,\n 220,\n 220,\n 220,\n 220,\n 220,\n 220,\n 220,\n 220,\n 220,\n 220,\n 220,\n 220,\n 220,\n 220,\n 220,\n 220,\n 220,\n 220,\n 220,\n 1303,\n 4226,\n 2604,\n 2393,\n 198,\n 28482,\n 48801,\n 796,\n 4570,\n 405,\n 220,\n 220,\n 220,\n 220,\n 220,\n 220,\n 220,\n 220,\n 220,\n 220,\n 220,\n 220,\n 220,\n 220,\n 220,\n 220,\n 220,\n 220,\n 220,\n 220,\n 220,\n 220,\n 220,\n 220,\n 220,\n 220,\n 220,\n 220,\n 220,\n 220,\n 220,\n 220,\n 220,\n 220,\n 220,\n 220,\n 220,\n 220,\n 220,\n 220,\n 220,\n 220,\n 220,\n 220,\n 220,\n 220,\n 220,\n 220,\n 220,\n 220,\n 220,\n 220,\n 220,\n 220,\n 220,\n 220,\n 220,\n 220,\n 1303,\n 703,\n 890,\n 815,\n 484,\n 423,\n 13169,\n 2489,\n 329,\n 357,\n 259,\n 4201,\n 8,\n 198,\n 30586,\n 15022,\n 48344,\n 796,\n 705,\n 28482,\n 28956,\n 6,\n 220,\n 220,\n 220,\n 220,\n 220,\n 220,\n 220,\n 220,\n 220,\n 220,\n 220,\n 220,\n 220,\n 220,\n 220,\n 220,\n 220,\n 220,\n 220,\n 220,\n 220,\n 220,\n 220,\n 220,\n 220,\n 220,\n 220,\n 220,\n 220,\n 220,\n 220,\n 220,\n 220,\n 220,\n 220,\n 220,\n 220,\n 220,\n 220,\n 220,\n 1303,\n 2183,\n 7616,\n 7368,\n 329,\n 4781,\n 30782,\n 46787,\n 13,\n 9078,\n 2450,\n 198,\n 198,\n 2,\n 1303,\n 1303,\n 1303,\n 1303,\n 1303,\n 1303,\n 1303,\n 1303,\n 1303,\n 1303,\n 1303,\n 1303,\n 1303,\n 1303,\n 1303,\n 1303,\n 1303,\n 1303,\n 1303,\n 1303,\n 1303,\n 1303,\n 1303,\n 1303,\n 1303,\n 1303,\n 1303,\n 1303,\n 1303,\n 1303,\n 1303,\n 1303,\n 1303,\n 1303,\n 1303,\n 1303,\n 1303,\n 1303,\n 1303,\n 1303,\n 1303,\n 1303,\n 1303,\n 1303,\n 1303,\n 220,\n 198,\n 2,\n 9131,\n 47461,\n 17051,\n 3620,\n 1340,\n 198,\n 2,\n 1303,\n 1303,\n 1303,\n 1303,\n 1303,\n 1303,\n 1303,\n 1303,\n 1303,\n 1303,\n 1303,\n 1303,\n 1303,\n 1303,\n 1303,\n 1303,\n 1303,\n 1303,\n 1303,\n 1303,\n 1303,\n 1303,\n 1303,\n 1303,\n 1303,\n 1303,\n 1303,\n 1303,\n 1303,\n 1303,\n 1303,\n 1303,\n 1303,\n 1303,\n 1303,\n 1303,\n 1303,\n 1303,\n 1303,\n 1303,\n 1303,\n 1303,\n 1303,\n 1303,\n 1303,\n 220,\n 198,\n 198,\n 2,\n 1295,\n 4219,\n 67,\n 458,\n 396,\n 284,\n 869,\n 449,\n 5432,\n 2450,\n 284,\n 4781,\n 13169,\n 2489,\n 13,\n 198,\n 4798,\n 705,\n 32071,\n 21225,\n 26531,\n 7966,\n 986,\n 6,\n 198,\n 35681,\n 26531,\n 7966,\n 796,\n 1391,\n 705,\n 33986,\n 10354,\n 35681,\n 67,\n 33986,\n 11,\n 198,\n 220,\n 220,\n 220,\n 220,\n 220,\n 220,\n 220,\n 220,\n 220,\n 220,\n 220,\n 220,\n 220,\n 220,\n 220,\n 220,\n 705,\n 38296,\n 10049,\n 7454,\n 10354,\n 17821,\n 11,\n 198,\n 220,\n 220,\n 220,\n 220,\n 220,\n 220,\n 220,\n 220,\n 220,\n 220,\n 220,\n 220,\n 220,\n 220,\n 220,\n 220,\n 705,\n 15167,\n 28100,\n 2886,\n 10354,\n 17816,\n 14,\n 14629,\n 14,\n 12001,\n 14,\n 39159,\n 69,\n 14,\n 8800,\n 14,\n 39159,\n 69,\n 3256,\n 705,\n 30586,\n 3256,\n 705,\n 12,\n 46284,\n 3256,\n 2450,\n 15022,\n 48344,\n 4357,\n 198,\n 220,\n 220,\n 220,\n 220,\n 220,\n 220,\n 220,\n 220,\n 220,\n 220,\n 220,\n 220,\n 220,\n 220,\n 220,\n 220,\n 705,\n 10434,\n 9492,\n 2100,\n 10354,\n 28482,\n 48801,\n 11,\n 198,\n 220,\n 220,\n 220,\n 220,\n 220,\n 220,\n 220,\n 220,\n 220,\n 220,\n 220,\n 220,\n 220,\n 220,\n 220,\n 220,\n 705,\n 12982,\n 5376,\n 10354,\n 6,\n 15763,\n 3256,\n 198,\n 220,\n 220,\n 220,\n 220,\n 220,\n 220,\n 220,\n 220,\n 220,\n 220,\n 220,\n 220,\n 220,\n 220,\n 220,\n 220,\n 1782,\n 198,\n 489,\n 396,\n 8019,\n 13,\n 13564,\n 3646,\n 396,\n 7,\n 35681,\n 26531,\n 7966,\n 11,\n 31051,\n 23377,\n 14,\n 38296,\n 26531,\n 368,\n 684,\n 14,\n 6,\n 1343,\n 4219,\n 67,\n 8979,\n 8,\n 198,\n 198,\n 2,\n 900,\n 262,\n 7170,\n 319,\n 262,\n 2393,\n 655,\n 925,\n 13,\n 198,\n 7220,\n 2389,\n 796,\n 279,\n 16993,\n 13,\n 1136,\n 79,\n 675,\n 321,\n 7203,\n 15763,\n 11074,\n 79,\n 86,\n 62,\n 27112,\n 198,\n 8094,\n 2389,\n 796,\n 1036,\n 79,\n 13,\n 1136,\n 2164,\n 7402,\n 7203,\n 22001,\n 11074,\n 2164,\n 62,\n 70,\n 312,\n 198,\n 418,\n 13,\n 354,\n 593,\n 10786,\n 14,\n 23377,\n 14,\n 38296,\n 26531,\n 368,\n 684,\n 14,\n 6,\n 1343,\n 4219,\n 67,\n 8979,\n 11,\n 2836,\n 2389,\n 11,\n 1448,\n 2389,\n 8,\n 198,\n 418,\n 13,\n 354,\n 4666,\n 10786,\n 14,\n 23377,\n 14,\n 38296,\n 26531,\n 368,\n 684,\n 14,\n 6,\n 1343,\n 4219,\n 67,\n 8979,\n 11,\n 657,\n 29173,\n 8,\n 198,\n 198,\n 2,\n 3440,\n 262,\n 9934,\n 458,\n 396,\n 19781,\n 13,\n 220,\n 198,\n 4798,\n 705,\n 19031,\n 21225,\n 26531,\n 7966,\n 986,\n 6,\n 198,\n 7266,\n 14681,\n 13,\n 13345,\n 7,\n 14692,\n 35681,\n 34168,\n 1600,\n 366,\n 2220,\n 1600,\n 27444,\n 86,\n 1600,\n 31051,\n 23377,\n 14,\n 38296,\n 26531,\n 368,\n 684,\n 14,\n 6,\n 1343,\n 4219,\n 67,\n 8979,\n 12962,\n 198,\n 198,\n 2,\n 1303,\n 1303,\n 1303,\n 1303,\n 1303,\n 1303,\n 1303,\n 1303,\n 1303,\n 1303,\n 1303,\n 1303,\n 1303,\n 1303,\n 1303,\n 1303,\n 1303,\n 1303,\n 1303,\n 1303,\n 1303,\n 1303,\n 1303,\n 1303,\n 1303,\n 1303,\n 1303,\n 1303,\n 1303,\n 1303,\n 1303,\n 1303,\n 1303,\n 1303,\n 1303,\n 1303,\n 1303,\n 1303,\n 1303,\n 1303,\n 1303,\n 1303,\n 1303,\n 1303,\n 1303,\n 220,\n 198,\n 2,\n 39421,\n 6234,\n 198,\n 2,\n 1303,\n 1303,\n 1303,\n 1303,\n 1303,\n 1303,\n 1303,\n 1303,\n 1303,\n 1303,\n 1303,\n 1303,\n 1303,\n 1303,\n 1303,\n 1303,\n 1303,\n 1303,\n 1303,\n 1303,\n 1303,\n 1303,\n 1303,\n 1303,\n 1303,\n 1303,\n 1303,\n 1303,\n 1303,\n 1303,\n 1303,\n 1303,\n 1303,\n 1303,\n 1303,\n 1303,\n 1303,\n 1303,\n 1303,\n 1303,\n 1303,\n 1303,\n 1303,\n 1303,\n 1303,\n 220,\n 198,\n 198,\n 2,\n 1382,\n 2604,\n 3696,\n 198,\n 361,\n 407,\n 28686,\n 13,\n 6978,\n 13,\n 1069,\n 1023,\n 7,\n 16090,\n 35277,\n 2599,\n 198,\n 220,\n 220,\n 220,\n 28686,\n 13,\n 76,\n 4335,\n 17062,\n 7,\n 16090,\n 35277,\n 8,\n 198,\n 198,\n 2,\n 1700,\n 2836,\n 326,\n 481,\n 761,\n 284,\n 423,\n 13169,\n 2489,\n 4615,\n 198,\n 2,\n 1700,\n 1459,\n 4683,\n 44563,\n 198,\n 4798,\n 705,\n 9781,\n 37418,\n 7343,\n 286,\n 9236,\n 1215,\n 42951,\n 986,\n 6,\n 198,\n 14421,\n 2782,\n 42951,\n 796,\n 1036,\n 79,\n 13,\n 1136,\n 2164,\n 7402,\n 10786,\n 28482,\n 27691,\n 2164,\n 62,\n 11883,\n 198,\n 4798,\n 705,\n 4933,\n 38734,\n 1345,\n 396,\n 986,\n 6,\n 198,\n 489,\n 396,\n 796,\n 1391,\n 705,\n 12982,\n 17,\n 27914,\n 10354,\n 7220,\n 5376,\n 11,\n 198,\n 220,\n 220,\n 220,\n 220,\n 220,\n 220,\n 220,\n 220,\n 220,\n 705,\n 11297,\n 46787,\n 14490,\n 10354,\n 14421,\n 2782,\n 42951,\n 92,\n 198,\n 489,\n 396,\n 8019,\n 13,\n 13564,\n 3646,\n 396,\n 7,\n 489,\n 396,\n 11,\n 1762,\n 35277,\n 1343,\n 458,\n 396,\n 8979,\n 8,\n 198,\n 198,\n 2,\n 1577,\n 1459,\n 18832,\n 2836,\n 13169,\n 2489,\n 198,\n 7266,\n 14681,\n 13,\n 13345,\n 7,\n 14692,\n 9310,\n 19312,\n 8094,\n 1600,\n 27444,\n 78,\n 1600,\n 366,\n 19312,\n 1600,\n 27444,\n 64,\n 1600,\n 2836,\n 5376,\n 11,\n 27444,\n 83,\n 1600,\n 366,\n 7220,\n 1600,\n 366,\n 28482,\n 8973,\n 8,\n 198,\n 198,\n 2,\n 751,\n 2604,\n 5726,\n 198,\n 6404,\n 796,\n 1280,\n 7,\n 16090,\n 35277,\n 1343,\n 20218,\n 46787,\n 11187,\n 11,\n 366,\n 64,\n 10,\n 4943,\n 198,\n 6404,\n 13,\n 13564,\n 7203,\n 90,\n 92,\n 532,\n 6889,\n 5308,\n 46787,\n 38842,\n 32053,\n 6923,\n 329,\n 23884,\n 59,\n 81,\n 59,\n 77,\n 1911,\n 18982,\n 7,\n 19608,\n 8079,\n 13,\n 2197,\n 22784,\n 2836,\n 5376,\n 4008,\n 198,\n 6404,\n 13,\n 19836,\n 3419,\n 198,\n 198,\n 4798,\n 705,\n 8642,\n 4126,\n 32053,\n 6498,\n 284,\n 705,\n 1343,\n 2836,\n 5376,\n 198\n]"},"ratio_char_token":{"kind":"number","value":2.4927365528072243,"string":"2.492737"},"token_count":{"kind":"number","value":2547,"string":"2,547"}}},{"rowIdx":1264,"cells":{"content":{"kind":"string","value":"import hashlib\n\nmessage = input()\n\nprint(hashlib.sha256(message.encode()).hexdigest())"},"input_ids":{"kind":"list like","value":[11748,12234,8019,198,198,20500,796,5128,3419,198,198,4798,7,17831,8019,13,26270,11645,7,20500,13,268,8189,3419,737,33095,12894,395,28955],"string":"[\n 11748,\n 12234,\n 8019,\n 198,\n 198,\n 20500,\n 796,\n 5128,\n 3419,\n 198,\n 198,\n 4798,\n 7,\n 17831,\n 8019,\n 13,\n 26270,\n 11645,\n 7,\n 20500,\n 13,\n 268,\n 8189,\n 3419,\n 737,\n 33095,\n 12894,\n 395,\n 28955\n]"},"ratio_char_token":{"kind":"number","value":2.9655172413793105,"string":"2.965517"},"token_count":{"kind":"number","value":29,"string":"29"}}},{"rowIdx":1265,"cells":{"content":{"kind":"string","value":"# Generated by Django 3.1.6 on 2021-04-17 11:19\n\nimport django.contrib.postgres.fields\nfrom django.db import migrations, models\n\n"},"input_ids":{"kind":"list like","value":[2,2980,515,416,37770,513,13,16,13,21,319,33448,12,3023,12,1558,1367,25,1129,198,198,11748,42625,14208,13,3642,822,13,7353,34239,13,25747,198,6738,42625,14208,13,9945,1330,15720,602,11,4981,628],"string":"[\n 2,\n 2980,\n 515,\n 416,\n 37770,\n 513,\n 13,\n 16,\n 13,\n 21,\n 319,\n 33448,\n 12,\n 3023,\n 12,\n 1558,\n 1367,\n 25,\n 1129,\n 198,\n 198,\n 11748,\n 42625,\n 14208,\n 13,\n 3642,\n 822,\n 13,\n 7353,\n 34239,\n 13,\n 25747,\n 198,\n 6738,\n 42625,\n 14208,\n 13,\n 9945,\n 1330,\n 15720,\n 602,\n 11,\n 4981,\n 628\n]"},"ratio_char_token":{"kind":"number","value":2.9318181818181817,"string":"2.931818"},"token_count":{"kind":"number","value":44,"string":"44"}}},{"rowIdx":1266,"cells":{"content":{"kind":"string","value":"# ------------------------------------------------------------------------------------------\n# Copyright (c) Microsoft Corporation. All rights reserved.\n# Licensed under the MIT License (MIT). See LICENSE in the repo root for license information.\n# ------------------------------------------------------------------------------------------\nfrom enum import Enum\nfrom typing import Any, Dict, List, Optional, Tuple\n\nimport param\nimport pytest\nfrom abex.common.generic_parsing import GenericConfig, IntTuple\n\n\n\n\ndef test_overridable_parameter() -> None:\n \"\"\"\n Test to check overridable parameters are correctly identified.\n \"\"\"\n param_dict = ParamClass.get_overridable_parameters()\n assert \"name\" in param_dict\n assert \"flag\" in param_dict\n assert \"seed\" in param_dict\n assert \"number\" in param_dict\n assert \"integers\" in param_dict\n assert \"optional_int\" in param_dict\n assert \"optional_float\" in param_dict\n assert \"tuple1\" in param_dict\n assert \"int_tuple\" in param_dict\n assert \"enum\" in param_dict\n assert \"readonly\" not in param_dict\n assert \"_non_override\" not in param_dict\n assert \"constant\" not in param_dict\n\n\ndef test_create_parser() -> None:\n \"\"\"\n Check that parse_args works as expected, with both non default and default values.\n \"\"\"\n\n check([\"--name=foo\"], \"name\", \"foo\")\n check([\"--seed\", \"42\"], \"seed\", 42)\n check([\"--seed\", \"\"], \"seed\", 42)\n check([\"--number\", \"2.17\"], \"number\", 2.17)\n check([\"--number\", \"\"], \"number\", 3.14)\n check([\"--integers\", \"1,2,3\"], \"integers\", [1, 2, 3])\n check([\"--optional_int\", \"\"], \"optional_int\", None)\n check([\"--optional_int\", \"2\"], \"optional_int\", 2)\n check([\"--optional_float\", \"\"], \"optional_float\", None)\n check([\"--optional_float\", \"3.14\"], \"optional_float\", 3.14)\n check([\"--tuple1\", \"1,2\"], \"tuple1\", (1, 2.0))\n check([\"--int_tuple\", \"1,2,3\"], \"int_tuple\", (1, 2, 3))\n check([\"--enum=2\"], \"enum\", ParamEnum.EnumValue2)\n check([\"--floats=1,2,3.14\"], \"floats\", [1.0, 2.0, 3.14])\n check([\"--integers=1,2,3\"], \"integers\", [1, 2, 3])\n check([\"--flag\"], \"flag\", True)\n # Check that default values are created as expected, and that the non-overridable parameters\n # are omitted.\n defaults = vars(ParamClass.create_argparser().parse_args([]))\n assert defaults[\"seed\"] == 42\n assert defaults[\"tuple1\"] == (1, 2.3)\n assert defaults[\"int_tuple\"] == (1, 1, 1)\n assert defaults[\"enum\"] == ParamEnum.EnumValue1\n assert \"readonly\" not in defaults\n assert \"constant\" not in defaults\n assert \"_non_override\" not in defaults\n # We can't test if all invalid cases are handled because argparse call sys.exit\n # upon errors.\n\n\ndef test_apply_overrides() -> None:\n \"\"\"\n Test that overrides are applied correctly, ond only to overridable parameters,\n \"\"\"\n m = ParamClass()\n overrides = {\"name\": \"newName\", \"int_tuple\": (0, 1, 2)}\n actual_overrides = m.apply_overrides(overrides)\n assert actual_overrides == overrides\n assert all([x == i and isinstance(x, int) for i, x in enumerate(m.int_tuple)])\n assert m.name == \"newName\"\n # Attempt to change seed and constant, but the latter should be ignored.\n change_seed: Dict[str, Any] = {\"seed\": 123}\n old_constant = m.constant\n changes2 = m.apply_overrides({**change_seed, \"constant\": \"Nothing\"})\n assert changes2 == change_seed\n assert m.seed == 123\n assert m.constant == old_constant\n\n\n@pytest.mark.parametrize(\"value_idx_0\", [1.0, 1])\n@pytest.mark.parametrize(\"value_idx_1\", [2.0, 2])\n@pytest.mark.parametrize(\"value_idx_2\", [3.0, 3])\ndef test_int_tuple_validation(value_idx_0: Any, value_idx_1: Any, value_idx_2: Any) -> None:\n \"\"\"\n Test integer tuple parameter is validated correctly.\n \"\"\"\n m = ParamClass()\n val = (value_idx_0, value_idx_1, value_idx_2)\n if not all([isinstance(x, int) for x in val]):\n with pytest.raises(ValueError):\n m.int_tuple = (value_idx_0, value_idx_1, value_idx_2)\n else:\n m.int_tuple = (value_idx_0, value_idx_1, value_idx_2)\n"},"input_ids":{"kind":"list like","value":[2,220,16529,22369,438,198,2,220,15069,357,66,8,5413,10501,13,1439,2489,10395,13,198,2,220,49962,739,262,17168,13789,357,36393,737,4091,38559,24290,287,262,29924,6808,329,5964,1321,13,198,2,220,16529,22369,438,198,6738,33829,1330,2039,388,198,6738,19720,1330,4377,11,360,713,11,7343,11,32233,11,309,29291,198,198,11748,5772,198,11748,12972,9288,198,6738,450,1069,13,11321,13,41357,62,79,945,278,1330,42044,16934,11,2558,51,29291,628,628,198,4299,1332,62,2502,6058,540,62,17143,2357,3419,4613,6045,25,198,220,220,220,37227,198,220,220,220,6208,284,2198,625,6058,540,10007,389,9380,5174,13,198,220,220,220,37227,198,220,220,220,5772,62,11600,796,25139,9487,13,1136,62,2502,6058,540,62,17143,7307,3419,198,220,220,220,6818,366,3672,1,287,5772,62,11600,198,220,220,220,6818,366,32109,1,287,5772,62,11600,198,220,220,220,6818,366,28826,1,287,5772,62,11600,198,220,220,220,6818,366,17618,1,287,5772,62,11600,198,220,220,220,6818,366,18908,364,1,287,5772,62,11600,198,220,220,220,6818,366,25968,62,600,1,287,5772,62,11600,198,220,220,220,6818,366,25968,62,22468,1,287,5772,62,11600,198,220,220,220,6818,366,83,29291,16,1,287,5772,62,11600,198,220,220,220,6818,366,600,62,83,29291,1,287,5772,62,11600,198,220,220,220,6818,366,44709,1,287,5772,62,11600,198,220,220,220,6818,366,961,8807,1,407,287,5772,62,11600,198,220,220,220,6818,45434,13159,62,2502,13154,1,407,287,5772,62,11600,198,220,220,220,6818,366,9979,415,1,407,287,5772,62,11600,628,198,4299,1332,62,17953,62,48610,3419,4613,6045,25,198,220,220,220,37227,198,220,220,220,6822,326,21136,62,22046,2499,355,2938,11,351,1111,1729,4277,290,4277,3815,13,198,220,220,220,37227,628,220,220,220,2198,7,14692,438,3672,28,21943,33116,366,3672,1600,366,21943,4943,198,220,220,220,2198,7,14692,438,28826,1600,366,3682,33116,366,28826,1600,5433,8,198,220,220,220,2198,7,14692,438,28826,1600,13538,4357,366,28826,1600,5433,8,198,220,220,220,2198,7,14692,438,17618,1600,366,17,13,1558,33116,366,17618,1600,362,13,1558,8,198,220,220,220,2198,7,14692,438,17618,1600,13538,4357,366,17618,1600,513,13,1415,8,198,220,220,220,2198,7,14692,438,18908,364,1600,366,16,11,17,11,18,33116,366,18908,364,1600,685,16,11,362,11,513,12962,198,220,220,220,2198,7,14692,438,25968,62,600,1600,13538,4357,366,25968,62,600,1600,6045,8,198,220,220,220,2198,7,14692,438,25968,62,600,1600,366,17,33116,366,25968,62,600,1600,362,8,198,220,220,220,2198,7,14692,438,25968,62,22468,1600,13538,4357,366,25968,62,22468,1600,6045,8,198,220,220,220,2198,7,14692,438,25968,62,22468,1600,366,18,13,1415,33116,366,25968,62,22468,1600,513,13,1415,8,198,220,220,220,2198,7,14692,438,83,29291,16,1600,366,16,11,17,33116,366,83,29291,16,1600,357,16,11,362,13,15,4008,198,220,220,220,2198,7,14692,438,600,62,83,29291,1600,366,16,11,17,11,18,33116,366,600,62,83,29291,1600,357,16,11,362,11,513,4008,198,220,220,220,2198,7,14692,438,44709,28,17,33116,366,44709,1600,25139,4834,388,13,4834,388,11395,17,8,198,220,220,220,2198,7,14692,438,48679,1381,28,16,11,17,11,18,13,1415,33116,366,48679,1381,1600,685,16,13,15,11,362,13,15,11,513,13,1415,12962,198,220,220,220,2198,7,14692,438,18908,364,28,16,11,17,11,18,33116,366,18908,364,1600,685,16,11,362,11,513,12962,198,220,220,220,2198,7,14692,438,32109,33116,366,32109,1600,6407,8,198,220,220,220,1303,6822,326,4277,3815,389,2727,355,2938,11,290,326,262,1729,12,2502,6058,540,10007,198,220,220,220,1303,389,22532,13,198,220,220,220,26235,796,410,945,7,22973,9487,13,17953,62,853,48610,22446,29572,62,22046,7,21737,4008,198,220,220,220,6818,26235,14692,28826,8973,6624,5433,198,220,220,220,6818,26235,14692,83,29291,16,8973,6624,357,16,11,362,13,18,8,198,220,220,220,6818,26235,14692,600,62,83,29291,8973,6624,357,16,11,352,11,352,8,198,220,220,220,6818,26235,14692,44709,8973,6624,25139,4834,388,13,4834,388,11395,16,198,220,220,220,6818,366,961,8807,1,407,287,26235,198,220,220,220,6818,366,9979,415,1,407,287,26235,198,220,220,220,6818,45434,13159,62,2502,13154,1,407,287,26235,198,220,220,220,1303,775,460,470,1332,611,477,12515,2663,389,12118,780,1822,29572,869,25064,13,37023,198,220,220,220,1303,2402,8563,13,628,198,4299,1332,62,39014,62,2502,81,1460,3419,4613,6045,25,198,220,220,220,37227,198,220,220,220,6208,326,23170,1460,389,5625,9380,11,319,67,691,284,625,6058,540,10007,11,198,220,220,220,37227,198,220,220,220,285,796,25139,9487,3419,198,220,220,220,23170,1460,796,19779,3672,1298,366,3605,5376,1600,366,600,62,83,29291,1298,357,15,11,352,11,362,38165,198,220,220,220,4036,62,2502,81,1460,796,285,13,39014,62,2502,81,1460,7,2502,81,1460,8,198,220,220,220,6818,4036,62,2502,81,1460,6624,23170,1460,198,220,220,220,6818,477,26933,87,6624,1312,290,318,39098,7,87,11,493,8,329,1312,11,2124,287,27056,378,7,76,13,600,62,83,29291,8,12962,198,220,220,220,6818,285,13,3672,6624,366,3605,5376,1,198,220,220,220,1303,25770,284,1487,9403,290,6937,11,475,262,6846,815,307,9514,13,198,220,220,220,1487,62,28826,25,360,713,58,2536,11,4377,60,796,19779,28826,1298,17031,92,198,220,220,220,1468,62,9979,415,796,285,13,9979,415,198,220,220,220,2458,17,796,285,13,39014,62,2502,81,1460,15090,1174,3803,62,28826,11,366,9979,415,1298,366,18465,20662,8,198,220,220,220,6818,2458,17,6624,1487,62,28826,198,220,220,220,6818,285,13,28826,6624,17031,198,220,220,220,6818,285,13,9979,415,6624,1468,62,9979,415,628,198,31,9078,9288,13,4102,13,17143,316,380,2736,7203,8367,62,312,87,62,15,1600,685,16,13,15,11,352,12962,198,31,9078,9288,13,4102,13,17143,316,380,2736,7203,8367,62,312,87,62,16,1600,685,17,13,15,11,362,12962,198,31,9078,9288,13,4102,13,17143,316,380,2736,7203,8367,62,312,87,62,17,1600,685,18,13,15,11,513,12962,198,4299,1332,62,600,62,83,29291,62,12102,341,7,8367,62,312,87,62,15,25,4377,11,1988,62,312,87,62,16,25,4377,11,1988,62,312,87,62,17,25,4377,8,4613,6045,25,198,220,220,220,37227,198,220,220,220,6208,18253,46545,11507,318,31031,9380,13,198,220,220,220,37227,198,220,220,220,285,796,25139,9487,3419,198,220,220,220,1188,796,357,8367,62,312,87,62,15,11,1988,62,312,87,62,16,11,1988,62,312,87,62,17,8,198,220,220,220,611,407,477,26933,271,39098,7,87,11,493,8,329,2124,287,1188,60,2599,198,220,220,220,220,220,220,220,351,12972,9288,13,430,2696,7,11395,12331,2599,198,220,220,220,220,220,220,220,220,220,220,220,285,13,600,62,83,29291,796,357,8367,62,312,87,62,15,11,1988,62,312,87,62,16,11,1988,62,312,87,62,17,8,198,220,220,220,2073,25,198,220,220,220,220,220,220,220,285,13,600,62,83,29291,796,357,8367,62,312,87,62,15,11,1988,62,312,87,62,16,11,1988,62,312,87,62,17,8,198],"string":"[\n 2,\n 220,\n 16529,\n 22369,\n 438,\n 198,\n 2,\n 220,\n 15069,\n 357,\n 66,\n 8,\n 5413,\n 10501,\n 13,\n 1439,\n 2489,\n 10395,\n 13,\n 198,\n 2,\n 220,\n 49962,\n 739,\n 262,\n 17168,\n 13789,\n 357,\n 36393,\n 737,\n 4091,\n 38559,\n 24290,\n 287,\n 262,\n 29924,\n 6808,\n 329,\n 5964,\n 1321,\n 13,\n 198,\n 2,\n 220,\n 16529,\n 22369,\n 438,\n 198,\n 6738,\n 33829,\n 1330,\n 2039,\n 388,\n 198,\n 6738,\n 19720,\n 1330,\n 4377,\n 11,\n 360,\n 713,\n 11,\n 7343,\n 11,\n 32233,\n 11,\n 309,\n 29291,\n 198,\n 198,\n 11748,\n 5772,\n 198,\n 11748,\n 12972,\n 9288,\n 198,\n 6738,\n 450,\n 1069,\n 13,\n 11321,\n 13,\n 41357,\n 62,\n 79,\n 945,\n 278,\n 1330,\n 42044,\n 16934,\n 11,\n 2558,\n 51,\n 29291,\n 628,\n 628,\n 198,\n 4299,\n 1332,\n 62,\n 2502,\n 6058,\n 540,\n 62,\n 17143,\n 2357,\n 3419,\n 4613,\n 6045,\n 25,\n 198,\n 220,\n 220,\n 220,\n 37227,\n 198,\n 220,\n 220,\n 220,\n 6208,\n 284,\n 2198,\n 625,\n 6058,\n 540,\n 10007,\n 389,\n 9380,\n 5174,\n 13,\n 198,\n 220,\n 220,\n 220,\n 37227,\n 198,\n 220,\n 220,\n 220,\n 5772,\n 62,\n 11600,\n 796,\n 25139,\n 9487,\n 13,\n 1136,\n 62,\n 2502,\n 6058,\n 540,\n 62,\n 17143,\n 7307,\n 3419,\n 198,\n 220,\n 220,\n 220,\n 6818,\n 366,\n 3672,\n 1,\n 287,\n 5772,\n 62,\n 11600,\n 198,\n 220,\n 220,\n 220,\n 6818,\n 366,\n 32109,\n 1,\n 287,\n 5772,\n 62,\n 11600,\n 198,\n 220,\n 220,\n 220,\n 6818,\n 366,\n 28826,\n 1,\n 287,\n 5772,\n 62,\n 11600,\n 198,\n 220,\n 220,\n 220,\n 6818,\n 366,\n 17618,\n 1,\n 287,\n 5772,\n 62,\n 11600,\n 198,\n 220,\n 220,\n 220,\n 6818,\n 366,\n 18908,\n 364,\n 1,\n 287,\n 5772,\n 62,\n 11600,\n 198,\n 220,\n 220,\n 220,\n 6818,\n 366,\n 25968,\n 62,\n 600,\n 1,\n 287,\n 5772,\n 62,\n 11600,\n 198,\n 220,\n 220,\n 220,\n 6818,\n 366,\n 25968,\n 62,\n 22468,\n 1,\n 287,\n 5772,\n 62,\n 11600,\n 198,\n 220,\n 220,\n 220,\n 6818,\n 366,\n 83,\n 29291,\n 16,\n 1,\n 287,\n 5772,\n 62,\n 11600,\n 198,\n 220,\n 220,\n 220,\n 6818,\n 366,\n 600,\n 62,\n 83,\n 29291,\n 1,\n 287,\n 5772,\n 62,\n 11600,\n 198,\n 220,\n 220,\n 220,\n 6818,\n 366,\n 44709,\n 1,\n 287,\n 5772,\n 62,\n 11600,\n 198,\n 220,\n 220,\n 220,\n 6818,\n 366,\n 961,\n 8807,\n 1,\n 407,\n 287,\n 5772,\n 62,\n 11600,\n 198,\n 220,\n 220,\n 220,\n 6818,\n 45434,\n 13159,\n 62,\n 2502,\n 13154,\n 1,\n 407,\n 287,\n 5772,\n 62,\n 11600,\n 198,\n 220,\n 220,\n 220,\n 6818,\n 366,\n 9979,\n 415,\n 1,\n 407,\n 287,\n 5772,\n 62,\n 11600,\n 628,\n 198,\n 4299,\n 1332,\n 62,\n 17953,\n 62,\n 48610,\n 3419,\n 4613,\n 6045,\n 25,\n 198,\n 220,\n 220,\n 220,\n 37227,\n 198,\n 220,\n 220,\n 220,\n 6822,\n 326,\n 21136,\n 62,\n 22046,\n 2499,\n 355,\n 2938,\n 11,\n 351,\n 1111,\n 1729,\n 4277,\n 290,\n 4277,\n 3815,\n 13,\n 198,\n 220,\n 220,\n 220,\n 37227,\n 628,\n 220,\n 220,\n 220,\n 2198,\n 7,\n 14692,\n 438,\n 3672,\n 28,\n 21943,\n 33116,\n 366,\n 3672,\n 1600,\n 366,\n 21943,\n 4943,\n 198,\n 220,\n 220,\n 220,\n 2198,\n 7,\n 14692,\n 438,\n 28826,\n 1600,\n 366,\n 3682,\n 33116,\n 366,\n 28826,\n 1600,\n 5433,\n 8,\n 198,\n 220,\n 220,\n 220,\n 2198,\n 7,\n 14692,\n 438,\n 28826,\n 1600,\n 13538,\n 4357,\n 366,\n 28826,\n 1600,\n 5433,\n 8,\n 198,\n 220,\n 220,\n 220,\n 2198,\n 7,\n 14692,\n 438,\n 17618,\n 1600,\n 366,\n 17,\n 13,\n 1558,\n 33116,\n 366,\n 17618,\n 1600,\n 362,\n 13,\n 1558,\n 8,\n 198,\n 220,\n 220,\n 220,\n 2198,\n 7,\n 14692,\n 438,\n 17618,\n 1600,\n 13538,\n 4357,\n 366,\n 17618,\n 1600,\n 513,\n 13,\n 1415,\n 8,\n 198,\n 220,\n 220,\n 220,\n 2198,\n 7,\n 14692,\n 438,\n 18908,\n 364,\n 1600,\n 366,\n 16,\n 11,\n 17,\n 11,\n 18,\n 33116,\n 366,\n 18908,\n 364,\n 1600,\n 685,\n 16,\n 11,\n 362,\n 11,\n 513,\n 12962,\n 198,\n 220,\n 220,\n 220,\n 2198,\n 7,\n 14692,\n 438,\n 25968,\n 62,\n 600,\n 1600,\n 13538,\n 4357,\n 366,\n 25968,\n 62,\n 600,\n 1600,\n 6045,\n 8,\n 198,\n 220,\n 220,\n 220,\n 2198,\n 7,\n 14692,\n 438,\n 25968,\n 62,\n 600,\n 1600,\n 366,\n 17,\n 33116,\n 366,\n 25968,\n 62,\n 600,\n 1600,\n 362,\n 8,\n 198,\n 220,\n 220,\n 220,\n 2198,\n 7,\n 14692,\n 438,\n 25968,\n 62,\n 22468,\n 1600,\n 13538,\n 4357,\n 366,\n 25968,\n 62,\n 22468,\n 1600,\n 6045,\n 8,\n 198,\n 220,\n 220,\n 220,\n 2198,\n 7,\n 14692,\n 438,\n 25968,\n 62,\n 22468,\n 1600,\n 366,\n 18,\n 13,\n 1415,\n 33116,\n 366,\n 25968,\n 62,\n 22468,\n 1600,\n 513,\n 13,\n 1415,\n 8,\n 198,\n 220,\n 220,\n 220,\n 2198,\n 7,\n 14692,\n 438,\n 83,\n 29291,\n 16,\n 1600,\n 366,\n 16,\n 11,\n 17,\n 33116,\n 366,\n 83,\n 29291,\n 16,\n 1600,\n 357,\n 16,\n 11,\n 362,\n 13,\n 15,\n 4008,\n 198,\n 220,\n 220,\n 220,\n 2198,\n 7,\n 14692,\n 438,\n 600,\n 62,\n 83,\n 29291,\n 1600,\n 366,\n 16,\n 11,\n 17,\n 11,\n 18,\n 33116,\n 366,\n 600,\n 62,\n 83,\n 29291,\n 1600,\n 357,\n 16,\n 11,\n 362,\n 11,\n 513,\n 4008,\n 198,\n 220,\n 220,\n 220,\n 2198,\n 7,\n 14692,\n 438,\n 44709,\n 28,\n 17,\n 33116,\n 366,\n 44709,\n 1600,\n 25139,\n 4834,\n 388,\n 13,\n 4834,\n 388,\n 11395,\n 17,\n 8,\n 198,\n 220,\n 220,\n 220,\n 2198,\n 7,\n 14692,\n 438,\n 48679,\n 1381,\n 28,\n 16,\n 11,\n 17,\n 11,\n 18,\n 13,\n 1415,\n 33116,\n 366,\n 48679,\n 1381,\n 1600,\n 685,\n 16,\n 13,\n 15,\n 11,\n 362,\n 13,\n 15,\n 11,\n 513,\n 13,\n 1415,\n 12962,\n 198,\n 220,\n 220,\n 220,\n 2198,\n 7,\n 14692,\n 438,\n 18908,\n 364,\n 28,\n 16,\n 11,\n 17,\n 11,\n 18,\n 33116,\n 366,\n 18908,\n 364,\n 1600,\n 685,\n 16,\n 11,\n 362,\n 11,\n 513,\n 12962,\n 198,\n 220,\n 220,\n 220,\n 2198,\n 7,\n 14692,\n 438,\n 32109,\n 33116,\n 366,\n 32109,\n 1600,\n 6407,\n 8,\n 198,\n 220,\n 220,\n 220,\n 1303,\n 6822,\n 326,\n 4277,\n 3815,\n 389,\n 2727,\n 355,\n 2938,\n 11,\n 290,\n 326,\n 262,\n 1729,\n 12,\n 2502,\n 6058,\n 540,\n 10007,\n 198,\n 220,\n 220,\n 220,\n 1303,\n 389,\n 22532,\n 13,\n 198,\n 220,\n 220,\n 220,\n 26235,\n 796,\n 410,\n 945,\n 7,\n 22973,\n 9487,\n 13,\n 17953,\n 62,\n 853,\n 48610,\n 22446,\n 29572,\n 62,\n 22046,\n 7,\n 21737,\n 4008,\n 198,\n 220,\n 220,\n 220,\n 6818,\n 26235,\n 14692,\n 28826,\n 8973,\n 6624,\n 5433,\n 198,\n 220,\n 220,\n 220,\n 6818,\n 26235,\n 14692,\n 83,\n 29291,\n 16,\n 8973,\n 6624,\n 357,\n 16,\n 11,\n 362,\n 13,\n 18,\n 8,\n 198,\n 220,\n 220,\n 220,\n 6818,\n 26235,\n 14692,\n 600,\n 62,\n 83,\n 29291,\n 8973,\n 6624,\n 357,\n 16,\n 11,\n 352,\n 11,\n 352,\n 8,\n 198,\n 220,\n 220,\n 220,\n 6818,\n 26235,\n 14692,\n 44709,\n 8973,\n 6624,\n 25139,\n 4834,\n 388,\n 13,\n 4834,\n 388,\n 11395,\n 16,\n 198,\n 220,\n 220,\n 220,\n 6818,\n 366,\n 961,\n 8807,\n 1,\n 407,\n 287,\n 26235,\n 198,\n 220,\n 220,\n 220,\n 6818,\n 366,\n 9979,\n 415,\n 1,\n 407,\n 287,\n 26235,\n 198,\n 220,\n 220,\n 220,\n 6818,\n 45434,\n 13159,\n 62,\n 2502,\n 13154,\n 1,\n 407,\n 287,\n 26235,\n 198,\n 220,\n 220,\n 220,\n 1303,\n 775,\n 460,\n 470,\n 1332,\n 611,\n 477,\n 12515,\n 2663,\n 389,\n 12118,\n 780,\n 1822,\n 29572,\n 869,\n 25064,\n 13,\n 37023,\n 198,\n 220,\n 220,\n 220,\n 1303,\n 2402,\n 8563,\n 13,\n 628,\n 198,\n 4299,\n 1332,\n 62,\n 39014,\n 62,\n 2502,\n 81,\n 1460,\n 3419,\n 4613,\n 6045,\n 25,\n 198,\n 220,\n 220,\n 220,\n 37227,\n 198,\n 220,\n 220,\n 220,\n 6208,\n 326,\n 23170,\n 1460,\n 389,\n 5625,\n 9380,\n 11,\n 319,\n 67,\n 691,\n 284,\n 625,\n 6058,\n 540,\n 10007,\n 11,\n 198,\n 220,\n 220,\n 220,\n 37227,\n 198,\n 220,\n 220,\n 220,\n 285,\n 796,\n 25139,\n 9487,\n 3419,\n 198,\n 220,\n 220,\n 220,\n 23170,\n 1460,\n 796,\n 19779,\n 3672,\n 1298,\n 366,\n 3605,\n 5376,\n 1600,\n 366,\n 600,\n 62,\n 83,\n 29291,\n 1298,\n 357,\n 15,\n 11,\n 352,\n 11,\n 362,\n 38165,\n 198,\n 220,\n 220,\n 220,\n 4036,\n 62,\n 2502,\n 81,\n 1460,\n 796,\n 285,\n 13,\n 39014,\n 62,\n 2502,\n 81,\n 1460,\n 7,\n 2502,\n 81,\n 1460,\n 8,\n 198,\n 220,\n 220,\n 220,\n 6818,\n 4036,\n 62,\n 2502,\n 81,\n 1460,\n 6624,\n 23170,\n 1460,\n 198,\n 220,\n 220,\n 220,\n 6818,\n 477,\n 26933,\n 87,\n 6624,\n 1312,\n 290,\n 318,\n 39098,\n 7,\n 87,\n 11,\n 493,\n 8,\n 329,\n 1312,\n 11,\n 2124,\n 287,\n 27056,\n 378,\n 7,\n 76,\n 13,\n 600,\n 62,\n 83,\n 29291,\n 8,\n 12962,\n 198,\n 220,\n 220,\n 220,\n 6818,\n 285,\n 13,\n 3672,\n 6624,\n 366,\n 3605,\n 5376,\n 1,\n 198,\n 220,\n 220,\n 220,\n 1303,\n 25770,\n 284,\n 1487,\n 9403,\n 290,\n 6937,\n 11,\n 475,\n 262,\n 6846,\n 815,\n 307,\n 9514,\n 13,\n 198,\n 220,\n 220,\n 220,\n 1487,\n 62,\n 28826,\n 25,\n 360,\n 713,\n 58,\n 2536,\n 11,\n 4377,\n 60,\n 796,\n 19779,\n 28826,\n 1298,\n 17031,\n 92,\n 198,\n 220,\n 220,\n 220,\n 1468,\n 62,\n 9979,\n 415,\n 796,\n 285,\n 13,\n 9979,\n 415,\n 198,\n 220,\n 220,\n 220,\n 2458,\n 17,\n 796,\n 285,\n 13,\n 39014,\n 62,\n 2502,\n 81,\n 1460,\n 15090,\n 1174,\n 3803,\n 62,\n 28826,\n 11,\n 366,\n 9979,\n 415,\n 1298,\n 366,\n 18465,\n 20662,\n 8,\n 198,\n 220,\n 220,\n 220,\n 6818,\n 2458,\n 17,\n 6624,\n 1487,\n 62,\n 28826,\n 198,\n 220,\n 220,\n 220,\n 6818,\n 285,\n 13,\n 28826,\n 6624,\n 17031,\n 198,\n 220,\n 220,\n 220,\n 6818,\n 285,\n 13,\n 9979,\n 415,\n 6624,\n 1468,\n 62,\n 9979,\n 415,\n 628,\n 198,\n 31,\n 9078,\n 9288,\n 13,\n 4102,\n 13,\n 17143,\n 316,\n 380,\n 2736,\n 7203,\n 8367,\n 62,\n 312,\n 87,\n 62,\n 15,\n 1600,\n 685,\n 16,\n 13,\n 15,\n 11,\n 352,\n 12962,\n 198,\n 31,\n 9078,\n 9288,\n 13,\n 4102,\n 13,\n 17143,\n 316,\n 380,\n 2736,\n 7203,\n 8367,\n 62,\n 312,\n 87,\n 62,\n 16,\n 1600,\n 685,\n 17,\n 13,\n 15,\n 11,\n 362,\n 12962,\n 198,\n 31,\n 9078,\n 9288,\n 13,\n 4102,\n 13,\n 17143,\n 316,\n 380,\n 2736,\n 7203,\n 8367,\n 62,\n 312,\n 87,\n 62,\n 17,\n 1600,\n 685,\n 18,\n 13,\n 15,\n 11,\n 513,\n 12962,\n 198,\n 4299,\n 1332,\n 62,\n 600,\n 62,\n 83,\n 29291,\n 62,\n 12102,\n 341,\n 7,\n 8367,\n 62,\n 312,\n 87,\n 62,\n 15,\n 25,\n 4377,\n 11,\n 1988,\n 62,\n 312,\n 87,\n 62,\n 16,\n 25,\n 4377,\n 11,\n 1988,\n 62,\n 312,\n 87,\n 62,\n 17,\n 25,\n 4377,\n 8,\n 4613,\n 6045,\n 25,\n 198,\n 220,\n 220,\n 220,\n 37227,\n 198,\n 220,\n 220,\n 220,\n 6208,\n 18253,\n 46545,\n 11507,\n 318,\n 31031,\n 9380,\n 13,\n 198,\n 220,\n 220,\n 220,\n 37227,\n 198,\n 220,\n 220,\n 220,\n 285,\n 796,\n 25139,\n 9487,\n 3419,\n 198,\n 220,\n 220,\n 220,\n 1188,\n 796,\n 357,\n 8367,\n 62,\n 312,\n 87,\n 62,\n 15,\n 11,\n 1988,\n 62,\n 312,\n 87,\n 62,\n 16,\n 11,\n 1988,\n 62,\n 312,\n 87,\n 62,\n 17,\n 8,\n 198,\n 220,\n 220,\n 220,\n 611,\n 407,\n 477,\n 26933,\n 271,\n 39098,\n 7,\n 87,\n 11,\n 493,\n 8,\n 329,\n 2124,\n 287,\n 1188,\n 60,\n 2599,\n 198,\n 220,\n 220,\n 220,\n 220,\n 220,\n 220,\n 220,\n 351,\n 12972,\n 9288,\n 13,\n 430,\n 2696,\n 7,\n 11395,\n 12331,\n 2599,\n 198,\n 220,\n 220,\n 220,\n 220,\n 220,\n 220,\n 220,\n 220,\n 220,\n 220,\n 220,\n 285,\n 13,\n 600,\n 62,\n 83,\n 29291,\n 796,\n 357,\n 8367,\n 62,\n 312,\n 87,\n 62,\n 15,\n 11,\n 1988,\n 62,\n 312,\n 87,\n 62,\n 16,\n 11,\n 1988,\n 62,\n 312,\n 87,\n 62,\n 17,\n 8,\n 198,\n 220,\n 220,\n 220,\n 2073,\n 25,\n 198,\n 220,\n 220,\n 220,\n 220,\n 220,\n 220,\n 220,\n 285,\n 13,\n 600,\n 62,\n 83,\n 29291,\n 796,\n 357,\n 8367,\n 62,\n 312,\n 87,\n 62,\n 15,\n 11,\n 1988,\n 62,\n 312,\n 87,\n 62,\n 16,\n 11,\n 1988,\n 62,\n 312,\n 87,\n 62,\n 17,\n 8,\n 198\n]"},"ratio_char_token":{"kind":"number","value":2.676509186351706,"string":"2.676509"},"token_count":{"kind":"number","value":1524,"string":"1,524"}}},{"rowIdx":1267,"cells":{"content":{"kind":"string","value":"# coding=utf-8\n# --------------------------------------------------------------------------\n# Copyright (c) Microsoft Corporation. All rights reserved.\n# Licensed under the MIT License. See License.txt in the project root for\n# license information.\n#\n# Code generated by Microsoft (R) AutoRest Code Generator.\n# Changes may cause incorrect behavior and will be lost if the code is\n# regenerated.\n# --------------------------------------------------------------------------\n\nfrom msrest.serialization import Model\n\n\nclass VirtualNetworkConfiguration(Model):\n \"\"\"Configuration of a virtual network to which API Management service is\n deployed.\n\n Variables are only populated by the server, and will be ignored when\n sending a request.\n\n :ivar vnetid: The virtual network ID. This is typically a GUID. Expect a\n null GUID by default.\n :vartype vnetid: str\n :ivar subnetname: The name of the subnet.\n :vartype subnetname: str\n :param subnet_resource_id: The full resource ID of a subnet in a virtual\n network to deploy the API Management service in.\n :type subnet_resource_id: str\n \"\"\"\n\n _validation = {\n 'vnetid': {'readonly': True},\n 'subnetname': {'readonly': True},\n 'subnet_resource_id': {'pattern': r'^/subscriptions/[^/]*/resourceGroups/[^/]*/providers/Microsoft.(ClassicNetwork|Network)/virtualNetworks/[^/]*/subnets/[^/]*$'},\n }\n\n _attribute_map = {\n 'vnetid': {'key': 'vnetid', 'type': 'str'},\n 'subnetname': {'key': 'subnetname', 'type': 'str'},\n 'subnet_resource_id': {'key': 'subnetResourceId', 'type': 'str'},\n }\n"},"input_ids":{"kind":"list like","value":[2,19617,28,40477,12,23,198,2,16529,35937,198,2,15069,357,66,8,5413,10501,13,1439,2489,10395,13,198,2,49962,739,262,17168,13789,13,4091,13789,13,14116,287,262,1628,6808,329,198,2,5964,1321,13,198,2,198,2,6127,7560,416,5413,357,49,8,11160,19452,6127,35986,13,198,2,19179,743,2728,11491,4069,290,481,307,2626,611,262,2438,318,198,2,16935,515,13,198,2,16529,35937,198,198,6738,13845,2118,13,46911,1634,1330,9104,628,198,4871,15595,26245,38149,7,17633,2599,198,220,220,220,37227,38149,286,257,7166,3127,284,543,7824,8549,2139,318,198,220,220,220,12380,13,628,220,220,220,15965,2977,389,691,22331,416,262,4382,11,290,481,307,9514,618,198,220,220,220,7216,257,2581,13,628,220,220,220,1058,452,283,410,3262,312,25,383,7166,3127,4522,13,770,318,6032,257,19348,2389,13,23600,257,198,220,220,220,220,9242,19348,2389,416,4277,13,198,220,220,220,1058,85,433,2981,410,3262,312,25,965,198,220,220,220,1058,452,283,850,3262,3672,25,383,1438,286,262,850,3262,13,198,220,220,220,1058,85,433,2981,850,3262,3672,25,965,198,220,220,220,1058,17143,850,3262,62,31092,62,312,25,383,1336,8271,4522,286,257,850,3262,287,257,7166,198,220,220,220,220,3127,284,6061,262,7824,8549,2139,287,13,198,220,220,220,1058,4906,850,3262,62,31092,62,312,25,965,198,220,220,220,37227,628,220,220,220,4808,12102,341,796,1391,198,220,220,220,220,220,220,220,705,85,3262,312,10354,1391,6,961,8807,10354,6407,5512,198,220,220,220,220,220,220,220,705,7266,3262,3672,10354,1391,6,961,8807,10354,6407,5512,198,220,220,220,220,220,220,220,705,7266,3262,62,31092,62,312,10354,1391,6,33279,10354,374,6,61,14,7266,12048,507,14,58,61,14,60,16208,31092,38,14459,14,58,61,14,60,16208,15234,4157,14,15905,12195,39914,26245,91,26245,20679,32844,7934,5225,14,58,61,14,60,16208,7266,45938,14,58,61,14,60,9,3,6,5512,198,220,220,220,1782,628,220,220,220,4808,42348,62,8899,796,1391,198,220,220,220,220,220,220,220,705,85,3262,312,10354,1391,6,2539,10354,705,85,3262,312,3256,705,4906,10354,705,2536,6,5512,198,220,220,220,220,220,220,220,705,7266,3262,3672,10354,1391,6,2539,10354,705,7266,3262,3672,3256,705,4906,10354,705,2536,6,5512,198,220,220,220,220,220,220,220,705,7266,3262,62,31092,62,312,10354,1391,6,2539,10354,705,7266,3262,26198,7390,3256,705,4906,10354,705,2536,6,5512,198,220,220,220,1782,198],"string":"[\n 2,\n 19617,\n 28,\n 40477,\n 12,\n 23,\n 198,\n 2,\n 16529,\n 35937,\n 198,\n 2,\n 15069,\n 357,\n 66,\n 8,\n 5413,\n 10501,\n 13,\n 1439,\n 2489,\n 10395,\n 13,\n 198,\n 2,\n 49962,\n 739,\n 262,\n 17168,\n 13789,\n 13,\n 4091,\n 13789,\n 13,\n 14116,\n 287,\n 262,\n 1628,\n 6808,\n 329,\n 198,\n 2,\n 5964,\n 1321,\n 13,\n 198,\n 2,\n 198,\n 2,\n 6127,\n 7560,\n 416,\n 5413,\n 357,\n 49,\n 8,\n 11160,\n 19452,\n 6127,\n 35986,\n 13,\n 198,\n 2,\n 19179,\n 743,\n 2728,\n 11491,\n 4069,\n 290,\n 481,\n 307,\n 2626,\n 611,\n 262,\n 2438,\n 318,\n 198,\n 2,\n 16935,\n 515,\n 13,\n 198,\n 2,\n 16529,\n 35937,\n 198,\n 198,\n 6738,\n 13845,\n 2118,\n 13,\n 46911,\n 1634,\n 1330,\n 9104,\n 628,\n 198,\n 4871,\n 15595,\n 26245,\n 38149,\n 7,\n 17633,\n 2599,\n 198,\n 220,\n 220,\n 220,\n 37227,\n 38149,\n 286,\n 257,\n 7166,\n 3127,\n 284,\n 543,\n 7824,\n 8549,\n 2139,\n 318,\n 198,\n 220,\n 220,\n 220,\n 12380,\n 13,\n 628,\n 220,\n 220,\n 220,\n 15965,\n 2977,\n 389,\n 691,\n 22331,\n 416,\n 262,\n 4382,\n 11,\n 290,\n 481,\n 307,\n 9514,\n 618,\n 198,\n 220,\n 220,\n 220,\n 7216,\n 257,\n 2581,\n 13,\n 628,\n 220,\n 220,\n 220,\n 1058,\n 452,\n 283,\n 410,\n 3262,\n 312,\n 25,\n 383,\n 7166,\n 3127,\n 4522,\n 13,\n 770,\n 318,\n 6032,\n 257,\n 19348,\n 2389,\n 13,\n 23600,\n 257,\n 198,\n 220,\n 220,\n 220,\n 220,\n 9242,\n 19348,\n 2389,\n 416,\n 4277,\n 13,\n 198,\n 220,\n 220,\n 220,\n 1058,\n 85,\n 433,\n 2981,\n 410,\n 3262,\n 312,\n 25,\n 965,\n 198,\n 220,\n 220,\n 220,\n 1058,\n 452,\n 283,\n 850,\n 3262,\n 3672,\n 25,\n 383,\n 1438,\n 286,\n 262,\n 850,\n 3262,\n 13,\n 198,\n 220,\n 220,\n 220,\n 1058,\n 85,\n 433,\n 2981,\n 850,\n 3262,\n 3672,\n 25,\n 965,\n 198,\n 220,\n 220,\n 220,\n 1058,\n 17143,\n 850,\n 3262,\n 62,\n 31092,\n 62,\n 312,\n 25,\n 383,\n 1336,\n 8271,\n 4522,\n 286,\n 257,\n 850,\n 3262,\n 287,\n 257,\n 7166,\n 198,\n 220,\n 220,\n 220,\n 220,\n 3127,\n 284,\n 6061,\n 262,\n 7824,\n 8549,\n 2139,\n 287,\n 13,\n 198,\n 220,\n 220,\n 220,\n 1058,\n 4906,\n 850,\n 3262,\n 62,\n 31092,\n 62,\n 312,\n 25,\n 965,\n 198,\n 220,\n 220,\n 220,\n 37227,\n 628,\n 220,\n 220,\n 220,\n 4808,\n 12102,\n 341,\n 796,\n 1391,\n 198,\n 220,\n 220,\n 220,\n 220,\n 220,\n 220,\n 220,\n 705,\n 85,\n 3262,\n 312,\n 10354,\n 1391,\n 6,\n 961,\n 8807,\n 10354,\n 6407,\n 5512,\n 198,\n 220,\n 220,\n 220,\n 220,\n 220,\n 220,\n 220,\n 705,\n 7266,\n 3262,\n 3672,\n 10354,\n 1391,\n 6,\n 961,\n 8807,\n 10354,\n 6407,\n 5512,\n 198,\n 220,\n 220,\n 220,\n 220,\n 220,\n 220,\n 220,\n 705,\n 7266,\n 3262,\n 62,\n 31092,\n 62,\n 312,\n 10354,\n 1391,\n 6,\n 33279,\n 10354,\n 374,\n 6,\n 61,\n 14,\n 7266,\n 12048,\n 507,\n 14,\n 58,\n 61,\n 14,\n 60,\n 16208,\n 31092,\n 38,\n 14459,\n 14,\n 58,\n 61,\n 14,\n 60,\n 16208,\n 15234,\n 4157,\n 14,\n 15905,\n 12195,\n 39914,\n 26245,\n 91,\n 26245,\n 20679,\n 32844,\n 7934,\n 5225,\n 14,\n 58,\n 61,\n 14,\n 60,\n 16208,\n 7266,\n 45938,\n 14,\n 58,\n 61,\n 14,\n 60,\n 9,\n 3,\n 6,\n 5512,\n 198,\n 220,\n 220,\n 220,\n 1782,\n 628,\n 220,\n 220,\n 220,\n 4808,\n 42348,\n 62,\n 8899,\n 796,\n 1391,\n 198,\n 220,\n 220,\n 220,\n 220,\n 220,\n 220,\n 220,\n 705,\n 85,\n 3262,\n 312,\n 10354,\n 1391,\n 6,\n 2539,\n 10354,\n 705,\n 85,\n 3262,\n 312,\n 3256,\n 705,\n 4906,\n 10354,\n 705,\n 2536,\n 6,\n 5512,\n 198,\n 220,\n 220,\n 220,\n 220,\n 220,\n 220,\n 220,\n 705,\n 7266,\n 3262,\n 3672,\n 10354,\n 1391,\n 6,\n 2539,\n 10354,\n 705,\n 7266,\n 3262,\n 3672,\n 3256,\n 705,\n 4906,\n 10354,\n 705,\n 2536,\n 6,\n 5512,\n 198,\n 220,\n 220,\n 220,\n 220,\n 220,\n 220,\n 220,\n 705,\n 7266,\n 3262,\n 62,\n 31092,\n 62,\n 312,\n 10354,\n 1391,\n 6,\n 2539,\n 10354,\n 705,\n 7266,\n 3262,\n 26198,\n 7390,\n 3256,\n 705,\n 4906,\n 10354,\n 705,\n 2536,\n 6,\n 5512,\n 198,\n 220,\n 220,\n 220,\n 1782,\n 198\n]"},"ratio_char_token":{"kind":"number","value":3.099616858237548,"string":"3.099617"},"token_count":{"kind":"number","value":522,"string":"522"}}},{"rowIdx":1268,"cells":{"content":{"kind":"string","value":"import django.shortcuts\n\n\ndef main(request):\n \"\"\"\n request handler for '/'.\n \"\"\"\n return django.shortcuts.render(request, 'app_website/index.html', {})\n\n\n# ~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~\n# global error handlers for app_website\n# ~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~\n\n\ndef error_400(request, exception):\n \"\"\"\n request handler for a 400 error.\n \"\"\"\n context = {\n 'err': '[400 Bad Request] Path: ' + request.path,\n }\n return django.shortcuts.render(request, 'app_website/error.html', context)\n\n\ndef error_403(request, exception):\n \"\"\"\n request handler for a 403 error.\n \"\"\"\n context = {\n 'err': '[403 Permission Denied] Path: ' + request.path,\n }\n return django.shortcuts.render(request, 'app_website/error.html', context)\n\n\ndef error_404(request, exception):\n \"\"\"\n request handler for a 404 error.\n \"\"\"\n context = {\n 'err': '[404 Page Not Found] Path: ' + request.path,\n }\n return django.shortcuts.render(request, 'app_website/error.html', context)\n\n\ndef error_500(request):\n \"\"\"\n request handler for a 500 error.\n \"\"\"\n context = {\n 'err': '[500 Server Error] Path: ' + request.path,\n }\n return django.shortcuts.render(request, 'app_website/error.html', context)\n"},"input_ids":{"kind":"list like","value":[11748,42625,14208,13,19509,23779,628,198,4299,1388,7,25927,2599,198,220,37227,198,220,2581,21360,329,31051,4458,198,220,37227,198,220,1441,42625,14208,13,19509,23779,13,13287,7,25927,11,705,1324,62,732,12485,14,9630,13,6494,3256,23884,8,628,198,2,220,27156,27156,27156,27156,15116,8728,93,198,2,3298,4049,32847,329,598,62,732,12485,198,2,220,27156,27156,27156,27156,15116,8728,93,628,198,4299,4049,62,7029,7,25927,11,6631,2599,198,220,37227,198,220,2581,21360,329,257,7337,4049,13,198,220,37227,198,220,4732,796,1391,198,220,220,220,705,8056,10354,44438,7029,7772,19390,60,10644,25,705,1343,2581,13,6978,11,198,220,1782,198,220,1441,42625,14208,13,19509,23779,13,13287,7,25927,11,705,1324,62,732,12485,14,18224,13,6494,3256,4732,8,628,198,4299,4049,62,31552,7,25927,11,6631,2599,198,220,37227,198,220,2581,21360,329,257,38210,4049,13,198,220,37227,198,220,4732,796,1391,198,220,220,220,705,8056,10354,44438,31552,2448,3411,5601,798,60,10644,25,705,1343,2581,13,6978,11,198,220,1782,198,220,1441,42625,14208,13,19509,23779,13,13287,7,25927,11,705,1324,62,732,12485,14,18224,13,6494,3256,4732,8,628,198,4299,4049,62,26429,7,25927,11,6631,2599,198,220,37227,198,220,2581,21360,329,257,32320,4049,13,198,220,37227,198,220,4732,796,1391,198,220,220,220,705,8056,10354,44438,26429,7873,1892,4062,60,10644,25,705,1343,2581,13,6978,11,198,220,1782,198,220,1441,42625,14208,13,19509,23779,13,13287,7,25927,11,705,1324,62,732,12485,14,18224,13,6494,3256,4732,8,628,198,4299,4049,62,4059,7,25927,2599,198,220,37227,198,220,2581,21360,329,257,5323,4049,13,198,220,37227,198,220,4732,796,1391,198,220,220,220,705,8056,10354,44438,4059,9652,13047,60,10644,25,705,1343,2581,13,6978,11,198,220,1782,198,220,1441,42625,14208,13,19509,23779,13,13287,7,25927,11,705,1324,62,732,12485,14,18224,13,6494,3256,4732,8,198],"string":"[\n 11748,\n 42625,\n 14208,\n 13,\n 19509,\n 23779,\n 628,\n 198,\n 4299,\n 1388,\n 7,\n 25927,\n 2599,\n 198,\n 220,\n 37227,\n 198,\n 220,\n 2581,\n 21360,\n 329,\n 31051,\n 4458,\n 198,\n 220,\n 37227,\n 198,\n 220,\n 1441,\n 42625,\n 14208,\n 13,\n 19509,\n 23779,\n 13,\n 13287,\n 7,\n 25927,\n 11,\n 705,\n 1324,\n 62,\n 732,\n 12485,\n 14,\n 9630,\n 13,\n 6494,\n 3256,\n 23884,\n 8,\n 628,\n 198,\n 2,\n 220,\n 27156,\n 27156,\n 27156,\n 27156,\n 15116,\n 8728,\n 93,\n 198,\n 2,\n 3298,\n 4049,\n 32847,\n 329,\n 598,\n 62,\n 732,\n 12485,\n 198,\n 2,\n 220,\n 27156,\n 27156,\n 27156,\n 27156,\n 15116,\n 8728,\n 93,\n 628,\n 198,\n 4299,\n 4049,\n 62,\n 7029,\n 7,\n 25927,\n 11,\n 6631,\n 2599,\n 198,\n 220,\n 37227,\n 198,\n 220,\n 2581,\n 21360,\n 329,\n 257,\n 7337,\n 4049,\n 13,\n 198,\n 220,\n 37227,\n 198,\n 220,\n 4732,\n 796,\n 1391,\n 198,\n 220,\n 220,\n 220,\n 705,\n 8056,\n 10354,\n 44438,\n 7029,\n 7772,\n 19390,\n 60,\n 10644,\n 25,\n 705,\n 1343,\n 2581,\n 13,\n 6978,\n 11,\n 198,\n 220,\n 1782,\n 198,\n 220,\n 1441,\n 42625,\n 14208,\n 13,\n 19509,\n 23779,\n 13,\n 13287,\n 7,\n 25927,\n 11,\n 705,\n 1324,\n 62,\n 732,\n 12485,\n 14,\n 18224,\n 13,\n 6494,\n 3256,\n 4732,\n 8,\n 628,\n 198,\n 4299,\n 4049,\n 62,\n 31552,\n 7,\n 25927,\n 11,\n 6631,\n 2599,\n 198,\n 220,\n 37227,\n 198,\n 220,\n 2581,\n 21360,\n 329,\n 257,\n 38210,\n 4049,\n 13,\n 198,\n 220,\n 37227,\n 198,\n 220,\n 4732,\n 796,\n 1391,\n 198,\n 220,\n 220,\n 220,\n 705,\n 8056,\n 10354,\n 44438,\n 31552,\n 2448,\n 3411,\n 5601,\n 798,\n 60,\n 10644,\n 25,\n 705,\n 1343,\n 2581,\n 13,\n 6978,\n 11,\n 198,\n 220,\n 1782,\n 198,\n 220,\n 1441,\n 42625,\n 14208,\n 13,\n 19509,\n 23779,\n 13,\n 13287,\n 7,\n 25927,\n 11,\n 705,\n 1324,\n 62,\n 732,\n 12485,\n 14,\n 18224,\n 13,\n 6494,\n 3256,\n 4732,\n 8,\n 628,\n 198,\n 4299,\n 4049,\n 62,\n 26429,\n 7,\n 25927,\n 11,\n 6631,\n 2599,\n 198,\n 220,\n 37227,\n 198,\n 220,\n 2581,\n 21360,\n 329,\n 257,\n 32320,\n 4049,\n 13,\n 198,\n 220,\n 37227,\n 198,\n 220,\n 4732,\n 796,\n 1391,\n 198,\n 220,\n 220,\n 220,\n 705,\n 8056,\n 10354,\n 44438,\n 26429,\n 7873,\n 1892,\n 4062,\n 60,\n 10644,\n 25,\n 705,\n 1343,\n 2581,\n 13,\n 6978,\n 11,\n 198,\n 220,\n 1782,\n 198,\n 220,\n 1441,\n 42625,\n 14208,\n 13,\n 19509,\n 23779,\n 13,\n 13287,\n 7,\n 25927,\n 11,\n 705,\n 1324,\n 62,\n 732,\n 12485,\n 14,\n 18224,\n 13,\n 6494,\n 3256,\n 4732,\n 8,\n 628,\n 198,\n 4299,\n 4049,\n 62,\n 4059,\n 7,\n 25927,\n 2599,\n 198,\n 220,\n 37227,\n 198,\n 220,\n 2581,\n 21360,\n 329,\n 257,\n 5323,\n 4049,\n 13,\n 198,\n 220,\n 37227,\n 198,\n 220,\n 4732,\n 796,\n 1391,\n 198,\n 220,\n 220,\n 220,\n 705,\n 8056,\n 10354,\n 44438,\n 4059,\n 9652,\n 13047,\n 60,\n 10644,\n 25,\n 705,\n 1343,\n 2581,\n 13,\n 6978,\n 11,\n 198,\n 220,\n 1782,\n 198,\n 220,\n 1441,\n 42625,\n 14208,\n 13,\n 19509,\n 23779,\n 13,\n 13287,\n 7,\n 25927,\n 11,\n 705,\n 1324,\n 62,\n 732,\n 12485,\n 14,\n 18224,\n 13,\n 6494,\n 3256,\n 4732,\n 8,\n 198\n]"},"ratio_char_token":{"kind":"number","value":3.2225,"string":"3.2225"},"token_count":{"kind":"number","value":400,"string":"400"}}},{"rowIdx":1269,"cells":{"content":{"kind":"string","value":"from .SculptASequenceView import SculptASequenceView\n"},"input_ids":{"kind":"list like","value":[6738,764,50,3129,457,1921,4853,594,7680,1330,1446,13327,1921,4853,594,7680,198],"string":"[\n 6738,\n 764,\n 50,\n 3129,\n 457,\n 1921,\n 4853,\n 594,\n 7680,\n 1330,\n 1446,\n 13327,\n 1921,\n 4853,\n 594,\n 7680,\n 198\n]"},"ratio_char_token":{"kind":"number","value":3.1176470588235294,"string":"3.117647"},"token_count":{"kind":"number","value":17,"string":"17"}}},{"rowIdx":1270,"cells":{"content":{"kind":"string","value":"# This code is part of Ansible, but is an independent component.\n# This particular file snippet, and this file snippet only, is BSD licensed.\n# Modules you write using this snippet, which is embedded dynamically by Ansible\n# still belong to the author of the module, and may assign their own license\n# to the complete work.\n#\n# Copyright (c) 2015 Peter Sprygada, \n#\n# Redistribution and use in source and binary forms, with or without modification,\n# are permitted provided that the following conditions are met:\n#\n# * Redistributions of source code must retain the above copyright\n# notice, this list of conditions and the following disclaimer.\n# * Redistributions in binary form must reproduce the above copyright notice,\n# this list of conditions and the following disclaimer in the documentation\n# and/or other materials provided with the distribution.\n#\n# THIS SOFTWARE IS PROVIDED BY THE COPYRIGHT HOLDERS AND CONTRIBUTORS \"AS IS\" AND\n# ANY EXPRESS OR IMPLIED WARRANTIES, INCLUDING, BUT NOT LIMITED TO, THE IMPLIED\n# WARRANTIES OF MERCHANTABILITY AND FITNESS FOR A PARTICULAR PURPOSE ARE DISCLAIMED.\n# IN NO EVENT SHALL THE COPYRIGHT HOLDER OR CONTRIBUTORS BE LIABLE FOR ANY DIRECT, INDIRECT,\n# INCIDENTAL, SPECIAL, EXEMPLARY, OR CONSEQUENTIAL DAMAGES (INCLUDING, BUT NOT LIMITED TO,\n# PROCUREMENT OF SUBSTITUTE GOODS OR SERVICES; LOSS OF USE, DATA, OR PROFITS; OR BUSINESS\n# INTERRUPTION) HOWEVER CAUSED AND ON ANY THEORY OF LIABILITY, WHETHER IN CONTRACT, STRICT\n# LIABILITY, OR TORT (INCLUDING NEGLIGENCE OR OTHERWISE) ARISING IN ANY WAY OUT OF THE\n# USE OF THIS SOFTWARE, EVEN IF ADVISED OF THE POSSIBILITY OF SUCH DAMAGE.\n#\n\nimport itertools\nimport re\n\nfrom ansible.module_utils.six import string_types\nfrom ansible.module_utils.six.moves import zip, zip_longest\n\nDEFAULT_COMMENT_TOKENS = ['#', '!', '/*', '*/']\n\n\n"},"input_ids":{"kind":"list like","value":[2,770,2438,318,636,286,28038,856,11,475,318,281,4795,7515,13,198,2,770,1948,2393,39442,11,290,428,2393,39442,691,11,318,347,10305,11971,13,198,2,3401,5028,345,3551,1262,428,39442,11,543,318,14553,32366,416,28038,856,198,2,991,5594,284,262,1772,286,262,8265,11,290,743,8333,511,898,5964,198,2,284,262,1844,670,13,198,2,198,2,15069,357,66,8,1853,5613,1338,563,70,4763,11,1279,862,79,563,70,4763,31,504,856,13,785,29,198,2,198,2,2297,396,3890,290,779,287,2723,290,13934,5107,11,351,393,1231,17613,11,198,2,389,10431,2810,326,262,1708,3403,389,1138,25,198,2,198,2,220,220,220,1635,2297,396,2455,507,286,2723,2438,1276,12377,262,2029,6634,198,2,220,220,220,220,220,4003,11,428,1351,286,3403,290,262,1708,37592,13,198,2,220,220,220,1635,2297,396,2455,507,287,13934,1296,1276,22919,262,2029,6634,4003,11,198,2,220,220,220,220,220,428,1351,286,3403,290,262,1708,37592,287,262,10314,198,2,220,220,220,220,220,290,14,273,584,5696,2810,351,262,6082,13,198,2,198,2,12680,47466,3180,36592,2389,1961,11050,3336,27975,38162,9947,367,15173,4877,5357,27342,9865,3843,20673,366,1921,3180,1,5357,198,2,15529,7788,32761,6375,8959,49094,34764,11015,11,47783,2751,11,21728,5626,40880,5390,11,3336,8959,49094,198,2,34764,11015,3963,34482,3398,1565,5603,25382,5357,376,46144,7473,317,16652,2149,37232,33079,48933,15986,13954,48778,1961,13,198,2,3268,8005,49261,50163,3336,27975,38162,9947,49707,14418,6375,27342,9865,3843,20673,9348,43031,19146,7473,15529,42242,11,3268,17931,23988,11,198,2,19387,25256,1847,11,38846,11,7788,3620,6489,13153,11,6375,7102,5188,10917,3525,12576,29506,25552,357,1268,39149,2751,11,21728,5626,40880,5390,11,198,2,41755,11335,10979,3963,28932,2257,2043,37780,21090,50,6375,49254,26,406,18420,3963,23210,11,42865,11,6375,4810,19238,29722,26,6375,43949,44180,198,2,23255,49,8577,24131,8,29630,36,5959,7257,2937,1961,5357,6177,15529,3336,15513,3963,43031,25382,11,7655,2767,16879,3268,27342,10659,11,19269,18379,198,2,43031,25382,11,6375,309,9863,357,1268,39149,2751,399,7156,43,3528,18310,6375,25401,54,24352,8,5923,1797,2751,3268,15529,34882,16289,3963,3336,198,2,23210,3963,12680,47466,11,45886,16876,5984,29817,1961,3963,3336,28069,11584,25382,3963,13558,3398,29506,11879,13,198,2,198,198,11748,340,861,10141,198,11748,302,198,198,6738,9093,856,13,21412,62,26791,13,19412,1330,4731,62,19199,198,6738,9093,856,13,21412,62,26791,13,19412,13,76,5241,1330,19974,11,19974,62,6511,395,198,198,7206,38865,62,9858,10979,62,10468,42,16938,796,37250,2,3256,705,0,3256,705,15211,3256,705,16208,20520,628,198],"string":"[\n 2,\n 770,\n 2438,\n 318,\n 636,\n 286,\n 28038,\n 856,\n 11,\n 475,\n 318,\n 281,\n 4795,\n 7515,\n 13,\n 198,\n 2,\n 770,\n 1948,\n 2393,\n 39442,\n 11,\n 290,\n 428,\n 2393,\n 39442,\n 691,\n 11,\n 318,\n 347,\n 10305,\n 11971,\n 13,\n 198,\n 2,\n 3401,\n 5028,\n 345,\n 3551,\n 1262,\n 428,\n 39442,\n 11,\n 543,\n 318,\n 14553,\n 32366,\n 416,\n 28038,\n 856,\n 198,\n 2,\n 991,\n 5594,\n 284,\n 262,\n 1772,\n 286,\n 262,\n 8265,\n 11,\n 290,\n 743,\n 8333,\n 511,\n 898,\n 5964,\n 198,\n 2,\n 284,\n 262,\n 1844,\n 670,\n 13,\n 198,\n 2,\n 198,\n 2,\n 15069,\n 357,\n 66,\n 8,\n 1853,\n 5613,\n 1338,\n 563,\n 70,\n 4763,\n 11,\n 1279,\n 862,\n 79,\n 563,\n 70,\n 4763,\n 31,\n 504,\n 856,\n 13,\n 785,\n 29,\n 198,\n 2,\n 198,\n 2,\n 2297,\n 396,\n 3890,\n 290,\n 779,\n 287,\n 2723,\n 290,\n 13934,\n 5107,\n 11,\n 351,\n 393,\n 1231,\n 17613,\n 11,\n 198,\n 2,\n 389,\n 10431,\n 2810,\n 326,\n 262,\n 1708,\n 3403,\n 389,\n 1138,\n 25,\n 198,\n 2,\n 198,\n 2,\n 220,\n 220,\n 220,\n 1635,\n 2297,\n 396,\n 2455,\n 507,\n 286,\n 2723,\n 2438,\n 1276,\n 12377,\n 262,\n 2029,\n 6634,\n 198,\n 2,\n 220,\n 220,\n 220,\n 220,\n 220,\n 4003,\n 11,\n 428,\n 1351,\n 286,\n 3403,\n 290,\n 262,\n 1708,\n 37592,\n 13,\n 198,\n 2,\n 220,\n 220,\n 220,\n 1635,\n 2297,\n 396,\n 2455,\n 507,\n 287,\n 13934,\n 1296,\n 1276,\n 22919,\n 262,\n 2029,\n 6634,\n 4003,\n 11,\n 198,\n 2,\n 220,\n 220,\n 220,\n 220,\n 220,\n 428,\n 1351,\n 286,\n 3403,\n 290,\n 262,\n 1708,\n 37592,\n 287,\n 262,\n 10314,\n 198,\n 2,\n 220,\n 220,\n 220,\n 220,\n 220,\n 290,\n 14,\n 273,\n 584,\n 5696,\n 2810,\n 351,\n 262,\n 6082,\n 13,\n 198,\n 2,\n 198,\n 2,\n 12680,\n 47466,\n 3180,\n 36592,\n 2389,\n 1961,\n 11050,\n 3336,\n 27975,\n 38162,\n 9947,\n 367,\n 15173,\n 4877,\n 5357,\n 27342,\n 9865,\n 3843,\n 20673,\n 366,\n 1921,\n 3180,\n 1,\n 5357,\n 198,\n 2,\n 15529,\n 7788,\n 32761,\n 6375,\n 8959,\n 49094,\n 34764,\n 11015,\n 11,\n 47783,\n 2751,\n 11,\n 21728,\n 5626,\n 40880,\n 5390,\n 11,\n 3336,\n 8959,\n 49094,\n 198,\n 2,\n 34764,\n 11015,\n 3963,\n 34482,\n 3398,\n 1565,\n 5603,\n 25382,\n 5357,\n 376,\n 46144,\n 7473,\n 317,\n 16652,\n 2149,\n 37232,\n 33079,\n 48933,\n 15986,\n 13954,\n 48778,\n 1961,\n 13,\n 198,\n 2,\n 3268,\n 8005,\n 49261,\n 50163,\n 3336,\n 27975,\n 38162,\n 9947,\n 49707,\n 14418,\n 6375,\n 27342,\n 9865,\n 3843,\n 20673,\n 9348,\n 43031,\n 19146,\n 7473,\n 15529,\n 42242,\n 11,\n 3268,\n 17931,\n 23988,\n 11,\n 198,\n 2,\n 19387,\n 25256,\n 1847,\n 11,\n 38846,\n 11,\n 7788,\n 3620,\n 6489,\n 13153,\n 11,\n 6375,\n 7102,\n 5188,\n 10917,\n 3525,\n 12576,\n 29506,\n 25552,\n 357,\n 1268,\n 39149,\n 2751,\n 11,\n 21728,\n 5626,\n 40880,\n 5390,\n 11,\n 198,\n 2,\n 41755,\n 11335,\n 10979,\n 3963,\n 28932,\n 2257,\n 2043,\n 37780,\n 21090,\n 50,\n 6375,\n 49254,\n 26,\n 406,\n 18420,\n 3963,\n 23210,\n 11,\n 42865,\n 11,\n 6375,\n 4810,\n 19238,\n 29722,\n 26,\n 6375,\n 43949,\n 44180,\n 198,\n 2,\n 23255,\n 49,\n 8577,\n 24131,\n 8,\n 29630,\n 36,\n 5959,\n 7257,\n 2937,\n 1961,\n 5357,\n 6177,\n 15529,\n 3336,\n 15513,\n 3963,\n 43031,\n 25382,\n 11,\n 7655,\n 2767,\n 16879,\n 3268,\n 27342,\n 10659,\n 11,\n 19269,\n 18379,\n 198,\n 2,\n 43031,\n 25382,\n 11,\n 6375,\n 309,\n 9863,\n 357,\n 1268,\n 39149,\n 2751,\n 399,\n 7156,\n 43,\n 3528,\n 18310,\n 6375,\n 25401,\n 54,\n 24352,\n 8,\n 5923,\n 1797,\n 2751,\n 3268,\n 15529,\n 34882,\n 16289,\n 3963,\n 3336,\n 198,\n 2,\n 23210,\n 3963,\n 12680,\n 47466,\n 11,\n 45886,\n 16876,\n 5984,\n 29817,\n 1961,\n 3963,\n 3336,\n 28069,\n 11584,\n 25382,\n 3963,\n 13558,\n 3398,\n 29506,\n 11879,\n 13,\n 198,\n 2,\n 198,\n 198,\n 11748,\n 340,\n 861,\n 10141,\n 198,\n 11748,\n 302,\n 198,\n 198,\n 6738,\n 9093,\n 856,\n 13,\n 21412,\n 62,\n 26791,\n 13,\n 19412,\n 1330,\n 4731,\n 62,\n 19199,\n 198,\n 6738,\n 9093,\n 856,\n 13,\n 21412,\n 62,\n 26791,\n 13,\n 19412,\n 13,\n 76,\n 5241,\n 1330,\n 19974,\n 11,\n 19974,\n 62,\n 6511,\n 395,\n 198,\n 198,\n 7206,\n 38865,\n 62,\n 9858,\n 10979,\n 62,\n 10468,\n 42,\n 16938,\n 796,\n 37250,\n 2,\n 3256,\n 705,\n 0,\n 3256,\n 705,\n 15211,\n 3256,\n 705,\n 16208,\n 20520,\n 628,\n 198\n]"},"ratio_char_token":{"kind":"number","value":3.416819012797075,"string":"3.416819"},"token_count":{"kind":"number","value":547,"string":"547"}}},{"rowIdx":1271,"cells":{"content":{"kind":"string","value":"import os\n\nimport pytest\n\nfrom dvc.ignore import DvcIgnore\nfrom dvc.main import main\n\n\n@pytest.mark.parametrize(\n \"file,ret,output\", [(\"ignored\", 0, True), (\"not_ignored\", 1, False)]\n)\n\n\n@pytest.mark.parametrize(\n \"file,ret,output\",\n [\n (\"file\", 0, \"{}:1:f*\\tfile\\n\".format(DvcIgnore.DVCIGNORE_FILE)),\n (\"foo\", 0, \"{}:2:!foo\\tfoo\\n\".format(DvcIgnore.DVCIGNORE_FILE)),\n (\n os.path.join(\"dir\", \"foobar\"),\n 0,\n \"{}:1:foobar\\t{}\\n\".format(\n os.path.join(\"dir\", DvcIgnore.DVCIGNORE_FILE),\n os.path.join(\"dir\", \"foobar\"),\n ),\n ),\n ],\n)\n\n\n@pytest.mark.parametrize(\"non_matching\", [True, False])\n\n\n@pytest.mark.parametrize(\n \"args\",\n [\n [\"-n\", \"file\"],\n [\"-a\", \"file\"],\n [\"-q\", \"-d\", \"file\"],\n [\"--stdin\", \"file\"],\n [],\n ],\n)\n\n\n@pytest.mark.parametrize(\"path,ret\", [({\"dir\": {}}, 0), ({\"dir\": \"files\"}, 1)])\n\n\n\n\n\n\n\n@pytest.mark.parametrize(\n \"file,ret,output\", [(\"ignored\", 0, True), (\"not_ignored\", 1, False)]\n)\n"},"input_ids":{"kind":"list like","value":[11748,28686,198,198,11748,12972,9288,198,198,6738,288,28435,13,46430,1330,360,28435,32916,382,198,6738,288,28435,13,12417,1330,1388,628,198,31,9078,9288,13,4102,13,17143,316,380,2736,7,198,220,220,220,366,7753,11,1186,11,22915,1600,685,7203,570,1850,1600,657,11,6407,828,5855,1662,62,570,1850,1600,352,11,10352,15437,198,8,628,198,31,9078,9288,13,4102,13,17143,316,380,2736,7,198,220,220,220,366,7753,11,1186,11,22915,1600,198,220,220,220,685,198,220,220,220,220,220,220,220,5855,7753,1600,657,11,45144,38362,16,25,69,9,59,83,7753,59,77,1911,18982,7,35,28435,32916,382,13,35,15922,16284,6965,62,25664,36911,198,220,220,220,220,220,220,220,5855,21943,1600,657,11,45144,38362,17,25,0,21943,59,83,21943,59,77,1911,18982,7,35,28435,32916,382,13,35,15922,16284,6965,62,25664,36911,198,220,220,220,220,220,220,220,357,198,220,220,220,220,220,220,220,220,220,220,220,28686,13,6978,13,22179,7203,15908,1600,366,6513,30973,12340,198,220,220,220,220,220,220,220,220,220,220,220,657,11,198,220,220,220,220,220,220,220,220,220,220,220,45144,38362,16,25,6513,30973,59,83,90,32239,77,1911,18982,7,198,220,220,220,220,220,220,220,220,220,220,220,220,220,220,220,28686,13,6978,13,22179,7203,15908,1600,360,28435,32916,382,13,35,15922,16284,6965,62,25664,828,198,220,220,220,220,220,220,220,220,220,220,220,220,220,220,220,28686,13,6978,13,22179,7203,15908,1600,366,6513,30973,12340,198,220,220,220,220,220,220,220,220,220,220,220,10612,198,220,220,220,220,220,220,220,10612,198,220,220,220,16589,198,8,628,198,31,9078,9288,13,4102,13,17143,316,380,2736,7203,13159,62,15699,278,1600,685,17821,11,10352,12962,628,198,31,9078,9288,13,4102,13,17143,316,380,2736,7,198,220,220,220,366,22046,1600,198,220,220,220,685,198,220,220,220,220,220,220,220,14631,12,77,1600,366,7753,33116,198,220,220,220,220,220,220,220,14631,12,64,1600,366,7753,33116,198,220,220,220,220,220,220,220,14631,12,80,1600,27444,67,1600,366,7753,33116,198,220,220,220,220,220,220,220,14631,438,19282,259,1600,366,7753,33116,198,220,220,220,220,220,220,220,685,4357,198,220,220,220,16589,198,8,628,198,31,9078,9288,13,4102,13,17143,316,380,2736,7203,6978,11,1186,1600,47527,4895,15908,1298,23884,5512,657,828,357,4895,15908,1298,366,16624,25719,352,8,12962,628,628,628,198,198,31,9078,9288,13,4102,13,17143,316,380,2736,7,198,220,220,220,366,7753,11,1186,11,22915,1600,685,7203,570,1850,1600,657,11,6407,828,5855,1662,62,570,1850,1600,352,11,10352,15437,198,8,198],"string":"[\n 11748,\n 28686,\n 198,\n 198,\n 11748,\n 12972,\n 9288,\n 198,\n 198,\n 6738,\n 288,\n 28435,\n 13,\n 46430,\n 1330,\n 360,\n 28435,\n 32916,\n 382,\n 198,\n 6738,\n 288,\n 28435,\n 13,\n 12417,\n 1330,\n 1388,\n 628,\n 198,\n 31,\n 9078,\n 9288,\n 13,\n 4102,\n 13,\n 17143,\n 316,\n 380,\n 2736,\n 7,\n 198,\n 220,\n 220,\n 220,\n 366,\n 7753,\n 11,\n 1186,\n 11,\n 22915,\n 1600,\n 685,\n 7203,\n 570,\n 1850,\n 1600,\n 657,\n 11,\n 6407,\n 828,\n 5855,\n 1662,\n 62,\n 570,\n 1850,\n 1600,\n 352,\n 11,\n 10352,\n 15437,\n 198,\n 8,\n 628,\n 198,\n 31,\n 9078,\n 9288,\n 13,\n 4102,\n 13,\n 17143,\n 316,\n 380,\n 2736,\n 7,\n 198,\n 220,\n 220,\n 220,\n 366,\n 7753,\n 11,\n 1186,\n 11,\n 22915,\n 1600,\n 198,\n 220,\n 220,\n 220,\n 685,\n 198,\n 220,\n 220,\n 220,\n 220,\n 220,\n 220,\n 220,\n 5855,\n 7753,\n 1600,\n 657,\n 11,\n 45144,\n 38362,\n 16,\n 25,\n 69,\n 9,\n 59,\n 83,\n 7753,\n 59,\n 77,\n 1911,\n 18982,\n 7,\n 35,\n 28435,\n 32916,\n 382,\n 13,\n 35,\n 15922,\n 16284,\n 6965,\n 62,\n 25664,\n 36911,\n 198,\n 220,\n 220,\n 220,\n 220,\n 220,\n 220,\n 220,\n 5855,\n 21943,\n 1600,\n 657,\n 11,\n 45144,\n 38362,\n 17,\n 25,\n 0,\n 21943,\n 59,\n 83,\n 21943,\n 59,\n 77,\n 1911,\n 18982,\n 7,\n 35,\n 28435,\n 32916,\n 382,\n 13,\n 35,\n 15922,\n 16284,\n 6965,\n 62,\n 25664,\n 36911,\n 198,\n 220,\n 220,\n 220,\n 220,\n 220,\n 220,\n 220,\n 357,\n 198,\n 220,\n 220,\n 220,\n 220,\n 220,\n 220,\n 220,\n 220,\n 220,\n 220,\n 220,\n 28686,\n 13,\n 6978,\n 13,\n 22179,\n 7203,\n 15908,\n 1600,\n 366,\n 6513,\n 30973,\n 12340,\n 198,\n 220,\n 220,\n 220,\n 220,\n 220,\n 220,\n 220,\n 220,\n 220,\n 220,\n 220,\n 657,\n 11,\n 198,\n 220,\n 220,\n 220,\n 220,\n 220,\n 220,\n 220,\n 220,\n 220,\n 220,\n 220,\n 45144,\n 38362,\n 16,\n 25,\n 6513,\n 30973,\n 59,\n 83,\n 90,\n 32239,\n 77,\n 1911,\n 18982,\n 7,\n 198,\n 220,\n 220,\n 220,\n 220,\n 220,\n 220,\n 220,\n 220,\n 220,\n 220,\n 220,\n 220,\n 220,\n 220,\n 220,\n 28686,\n 13,\n 6978,\n 13,\n 22179,\n 7203,\n 15908,\n 1600,\n 360,\n 28435,\n 32916,\n 382,\n 13,\n 35,\n 15922,\n 16284,\n 6965,\n 62,\n 25664,\n 828,\n 198,\n 220,\n 220,\n 220,\n 220,\n 220,\n 220,\n 220,\n 220,\n 220,\n 220,\n 220,\n 220,\n 220,\n 220,\n 220,\n 28686,\n 13,\n 6978,\n 13,\n 22179,\n 7203,\n 15908,\n 1600,\n 366,\n 6513,\n 30973,\n 12340,\n 198,\n 220,\n 220,\n 220,\n 220,\n 220,\n 220,\n 220,\n 220,\n 220,\n 220,\n 220,\n 10612,\n 198,\n 220,\n 220,\n 220,\n 220,\n 220,\n 220,\n 220,\n 10612,\n 198,\n 220,\n 220,\n 220,\n 16589,\n 198,\n 8,\n 628,\n 198,\n 31,\n 9078,\n 9288,\n 13,\n 4102,\n 13,\n 17143,\n 316,\n 380,\n 2736,\n 7203,\n 13159,\n 62,\n 15699,\n 278,\n 1600,\n 685,\n 17821,\n 11,\n 10352,\n 12962,\n 628,\n 198,\n 31,\n 9078,\n 9288,\n 13,\n 4102,\n 13,\n 17143,\n 316,\n 380,\n 2736,\n 7,\n 198,\n 220,\n 220,\n 220,\n 366,\n 22046,\n 1600,\n 198,\n 220,\n 220,\n 220,\n 685,\n 198,\n 220,\n 220,\n 220,\n 220,\n 220,\n 220,\n 220,\n 14631,\n 12,\n 77,\n 1600,\n 366,\n 7753,\n 33116,\n 198,\n 220,\n 220,\n 220,\n 220,\n 220,\n 220,\n 220,\n 14631,\n 12,\n 64,\n 1600,\n 366,\n 7753,\n 33116,\n 198,\n 220,\n 220,\n 220,\n 220,\n 220,\n 220,\n 220,\n 14631,\n 12,\n 80,\n 1600,\n 27444,\n 67,\n 1600,\n 366,\n 7753,\n 33116,\n 198,\n 220,\n 220,\n 220,\n 220,\n 220,\n 220,\n 220,\n 14631,\n 438,\n 19282,\n 259,\n 1600,\n 366,\n 7753,\n 33116,\n 198,\n 220,\n 220,\n 220,\n 220,\n 220,\n 220,\n 220,\n 685,\n 4357,\n 198,\n 220,\n 220,\n 220,\n 16589,\n 198,\n 8,\n 628,\n 198,\n 31,\n 9078,\n 9288,\n 13,\n 4102,\n 13,\n 17143,\n 316,\n 380,\n 2736,\n 7203,\n 6978,\n 11,\n 1186,\n 1600,\n 47527,\n 4895,\n 15908,\n 1298,\n 23884,\n 5512,\n 657,\n 828,\n 357,\n 4895,\n 15908,\n 1298,\n 366,\n 16624,\n 25719,\n 352,\n 8,\n 12962,\n 628,\n 628,\n 628,\n 198,\n 198,\n 31,\n 9078,\n 9288,\n 13,\n 4102,\n 13,\n 17143,\n 316,\n 380,\n 2736,\n 7,\n 198,\n 220,\n 220,\n 220,\n 366,\n 7753,\n 11,\n 1186,\n 11,\n 22915,\n 1600,\n 685,\n 7203,\n 570,\n 1850,\n 1600,\n 657,\n 11,\n 6407,\n 828,\n 5855,\n 1662,\n 62,\n 570,\n 1850,\n 1600,\n 352,\n 11,\n 10352,\n 15437,\n 198,\n 8,\n 198\n]"},"ratio_char_token":{"kind":"number","value":1.9103942652329748,"string":"1.910394"},"token_count":{"kind":"number","value":558,"string":"558"}}},{"rowIdx":1272,"cells":{"content":{"kind":"string","value":"import os\nimport threading\nimport time\n\nfrom networktables import NetworkTables\nfrom PIL import Image\nfrom PIL.ImageColor import getcolor, getrgb\nfrom PIL.ImageOps import grayscale\n\nfrom StreamDeck.DeviceManager import DeviceManager\nfrom StreamDeck.ImageHelpers import PILHelper\n\nASSETS_PATH = os.path.join(os.path.dirname(__file__), \"assets\")\n\n\n\nASSETS_PATH = os.path.join(os.path.dirname(__file__), \"icons\")\n\n\n\n\n\n# As a client to connect to a robot\nNetworkTables.initialize(server=\"10.11.89.2\")\n# NetworkTables.initialize(server=\"127.0.0.1\")\ntime.sleep(3)\n\n\nsd = NetworkTables.getTable(\"StreamDeck/0\")\n# a = [\n# \"default\",\n# \"default\",\n# \"default\",\n# \"default\",\n# \"default\",\n# \"default\",\n# \"default\",\n# \"default\",\n# \"default\",\n# \"default\",\n# \"default\",\n# \"default\",\n# \"default\",\n# \"default\",\n# \"default\",\n# ]\n# sd.putStringArray(\"Icons\", a)\n\nbuttons = []\n\nfor i in range(0, 15):\n sd.putBoolean(f\"Action/{i}\", False)\n sd.putBoolean(f\"Status/{i}\", False)\n button = Button(i)\n buttons.append(button)\n\ndeck = DeviceManager().enumerate()[0]\ndeck.open()\ndeck.reset()\nprint(\n \"Opened '{}' device (serial number: '{}')\".format(\n deck.deck_type(), deck.get_serial_number()\n )\n)\n\n# Set initial screen brightness to 30%.\ndeck.set_brightness(30)\n# Set initial key images.\n# for key in range(deck.key_count()):\n# update_key_image(deck, key, False)\n\n# Register callback function for when a key state changes.\ndeck.set_key_callback(key_change_callback)\n\nwhile True:\n for button in buttons:\n button.update(deck)\n\n# Wait until all application threads have terminated (for this example,\n# this is when all deck handles are closed).\nfor t in threading.enumerate():\n if t is threading.currentThread():\n continue\n if t.is_alive():\n t.join()\n"},"input_ids":{"kind":"list like","value":[11748,28686,198,11748,4704,278,198,11748,640,198,198,6738,3127,83,2977,1330,7311,51,2977,198,6738,350,4146,1330,7412,198,6738,350,4146,13,5159,10258,1330,651,8043,11,651,81,22296,198,6738,350,4146,13,5159,41472,1330,1036,592,38765,198,198,6738,13860,5005,694,13,24728,13511,1330,16232,13511,198,6738,13860,5005,694,13,5159,12621,19276,1330,350,4146,47429,198,198,10705,32716,62,34219,796,28686,13,6978,13,22179,7,418,13,6978,13,15908,3672,7,834,7753,834,828,366,19668,4943,628,198,198,10705,32716,62,34219,796,28686,13,6978,13,22179,7,418,13,6978,13,15908,3672,7,834,7753,834,828,366,34280,4943,628,628,198,198,2,1081,257,5456,284,2018,284,257,9379,198,26245,51,2977,13,36733,1096,7,15388,2625,940,13,1157,13,4531,13,17,4943,198,2,7311,51,2977,13,36733,1096,7,15388,2625,16799,13,15,13,15,13,16,4943,198,2435,13,42832,7,18,8,628,198,21282,796,7311,51,2977,13,1136,10962,7203,12124,5005,694,14,15,4943,198,2,257,796,685,198,2,220,220,220,220,366,12286,1600,198,2,220,220,220,220,366,12286,1600,198,2,220,220,220,220,366,12286,1600,198,2,220,220,220,220,366,12286,1600,198,2,220,220,220,220,366,12286,1600,198,2,220,220,220,220,366,12286,1600,198,2,220,220,220,220,366,12286,1600,198,2,220,220,220,220,366,12286,1600,198,2,220,220,220,220,366,12286,1600,198,2,220,220,220,220,366,12286,1600,198,2,220,220,220,220,366,12286,1600,198,2,220,220,220,220,366,12286,1600,198,2,220,220,220,220,366,12286,1600,198,2,220,220,220,220,366,12286,1600,198,2,220,220,220,220,366,12286,1600,198,2,2361,198,2,45647,13,1996,10100,19182,7203,40,5936,1600,257,8,198,198,4360,27288,796,17635,198,198,1640,1312,287,2837,7,15,11,1315,2599,198,220,220,220,45647,13,1996,46120,13087,7,69,1,12502,14,90,72,92,1600,10352,8,198,220,220,220,45647,13,1996,46120,13087,7,69,1,19580,14,90,72,92,1600,10352,8,198,220,220,220,4936,796,20969,7,72,8,198,220,220,220,12163,13,33295,7,16539,8,198,198,35875,796,16232,13511,22446,268,6975,378,3419,58,15,60,198,35875,13,9654,3419,198,35875,13,42503,3419,198,4798,7,198,220,220,220,366,18257,2945,705,90,92,6,3335,357,46911,1271,25,705,90,92,11537,1911,18982,7,198,220,220,220,220,220,220,220,6203,13,35875,62,4906,22784,6203,13,1136,62,46911,62,17618,3419,198,220,220,220,1267,198,8,198,198,2,5345,4238,3159,22204,284,1542,7225,198,35875,13,2617,62,29199,1108,7,1270,8,198,2,5345,4238,1994,4263,13,198,2,329,1994,287,2837,7,35875,13,2539,62,9127,3419,2599,198,2,220,220,220,4296,62,2539,62,9060,7,35875,11,1994,11,10352,8,198,198,2,17296,23838,2163,329,618,257,1994,1181,2458,13,198,35875,13,2617,62,2539,62,47423,7,2539,62,3803,62,47423,8,198,198,4514,6407,25,198,220,220,220,329,4936,287,12163,25,198,220,220,220,220,220,220,220,4936,13,19119,7,35875,8,198,198,2,16314,1566,477,3586,14390,423,23083,357,1640,428,1672,11,198,2,428,318,618,477,6203,17105,389,4838,737,198,1640,256,287,4704,278,13,268,6975,378,33529,198,220,220,220,611,256,318,4704,278,13,14421,16818,33529,198,220,220,220,220,220,220,220,2555,198,220,220,220,611,256,13,271,62,282,425,33529,198,220,220,220,220,220,220,220,256,13,22179,3419,198],"string":"[\n 11748,\n 28686,\n 198,\n 11748,\n 4704,\n 278,\n 198,\n 11748,\n 640,\n 198,\n 198,\n 6738,\n 3127,\n 83,\n 2977,\n 1330,\n 7311,\n 51,\n 2977,\n 198,\n 6738,\n 350,\n 4146,\n 1330,\n 7412,\n 198,\n 6738,\n 350,\n 4146,\n 13,\n 5159,\n 10258,\n 1330,\n 651,\n 8043,\n 11,\n 651,\n 81,\n 22296,\n 198,\n 6738,\n 350,\n 4146,\n 13,\n 5159,\n 41472,\n 1330,\n 1036,\n 592,\n 38765,\n 198,\n 198,\n 6738,\n 13860,\n 5005,\n 694,\n 13,\n 24728,\n 13511,\n 1330,\n 16232,\n 13511,\n 198,\n 6738,\n 13860,\n 5005,\n 694,\n 13,\n 5159,\n 12621,\n 19276,\n 1330,\n 350,\n 4146,\n 47429,\n 198,\n 198,\n 10705,\n 32716,\n 62,\n 34219,\n 796,\n 28686,\n 13,\n 6978,\n 13,\n 22179,\n 7,\n 418,\n 13,\n 6978,\n 13,\n 15908,\n 3672,\n 7,\n 834,\n 7753,\n 834,\n 828,\n 366,\n 19668,\n 4943,\n 628,\n 198,\n 198,\n 10705,\n 32716,\n 62,\n 34219,\n 796,\n 28686,\n 13,\n 6978,\n 13,\n 22179,\n 7,\n 418,\n 13,\n 6978,\n 13,\n 15908,\n 3672,\n 7,\n 834,\n 7753,\n 834,\n 828,\n 366,\n 34280,\n 4943,\n 628,\n 628,\n 198,\n 198,\n 2,\n 1081,\n 257,\n 5456,\n 284,\n 2018,\n 284,\n 257,\n 9379,\n 198,\n 26245,\n 51,\n 2977,\n 13,\n 36733,\n 1096,\n 7,\n 15388,\n 2625,\n 940,\n 13,\n 1157,\n 13,\n 4531,\n 13,\n 17,\n 4943,\n 198,\n 2,\n 7311,\n 51,\n 2977,\n 13,\n 36733,\n 1096,\n 7,\n 15388,\n 2625,\n 16799,\n 13,\n 15,\n 13,\n 15,\n 13,\n 16,\n 4943,\n 198,\n 2435,\n 13,\n 42832,\n 7,\n 18,\n 8,\n 628,\n 198,\n 21282,\n 796,\n 7311,\n 51,\n 2977,\n 13,\n 1136,\n 10962,\n 7203,\n 12124,\n 5005,\n 694,\n 14,\n 15,\n 4943,\n 198,\n 2,\n 257,\n 796,\n 685,\n 198,\n 2,\n 220,\n 220,\n 220,\n 220,\n 366,\n 12286,\n 1600,\n 198,\n 2,\n 220,\n 220,\n 220,\n 220,\n 366,\n 12286,\n 1600,\n 198,\n 2,\n 220,\n 220,\n 220,\n 220,\n 366,\n 12286,\n 1600,\n 198,\n 2,\n 220,\n 220,\n 220,\n 220,\n 366,\n 12286,\n 1600,\n 198,\n 2,\n 220,\n 220,\n 220,\n 220,\n 366,\n 12286,\n 1600,\n 198,\n 2,\n 220,\n 220,\n 220,\n 220,\n 366,\n 12286,\n 1600,\n 198,\n 2,\n 220,\n 220,\n 220,\n 220,\n 366,\n 12286,\n 1600,\n 198,\n 2,\n 220,\n 220,\n 220,\n 220,\n 366,\n 12286,\n 1600,\n 198,\n 2,\n 220,\n 220,\n 220,\n 220,\n 366,\n 12286,\n 1600,\n 198,\n 2,\n 220,\n 220,\n 220,\n 220,\n 366,\n 12286,\n 1600,\n 198,\n 2,\n 220,\n 220,\n 220,\n 220,\n 366,\n 12286,\n 1600,\n 198,\n 2,\n 220,\n 220,\n 220,\n 220,\n 366,\n 12286,\n 1600,\n 198,\n 2,\n 220,\n 220,\n 220,\n 220,\n 366,\n 12286,\n 1600,\n 198,\n 2,\n 220,\n 220,\n 220,\n 220,\n 366,\n 12286,\n 1600,\n 198,\n 2,\n 220,\n 220,\n 220,\n 220,\n 366,\n 12286,\n 1600,\n 198,\n 2,\n 2361,\n 198,\n 2,\n 45647,\n 13,\n 1996,\n 10100,\n 19182,\n 7203,\n 40,\n 5936,\n 1600,\n 257,\n 8,\n 198,\n 198,\n 4360,\n 27288,\n 796,\n 17635,\n 198,\n 198,\n 1640,\n 1312,\n 287,\n 2837,\n 7,\n 15,\n 11,\n 1315,\n 2599,\n 198,\n 220,\n 220,\n 220,\n 45647,\n 13,\n 1996,\n 46120,\n 13087,\n 7,\n 69,\n 1,\n 12502,\n 14,\n 90,\n 72,\n 92,\n 1600,\n 10352,\n 8,\n 198,\n 220,\n 220,\n 220,\n 45647,\n 13,\n 1996,\n 46120,\n 13087,\n 7,\n 69,\n 1,\n 19580,\n 14,\n 90,\n 72,\n 92,\n 1600,\n 10352,\n 8,\n 198,\n 220,\n 220,\n 220,\n 4936,\n 796,\n 20969,\n 7,\n 72,\n 8,\n 198,\n 220,\n 220,\n 220,\n 12163,\n 13,\n 33295,\n 7,\n 16539,\n 8,\n 198,\n 198,\n 35875,\n 796,\n 16232,\n 13511,\n 22446,\n 268,\n 6975,\n 378,\n 3419,\n 58,\n 15,\n 60,\n 198,\n 35875,\n 13,\n 9654,\n 3419,\n 198,\n 35875,\n 13,\n 42503,\n 3419,\n 198,\n 4798,\n 7,\n 198,\n 220,\n 220,\n 220,\n 366,\n 18257,\n 2945,\n 705,\n 90,\n 92,\n 6,\n 3335,\n 357,\n 46911,\n 1271,\n 25,\n 705,\n 90,\n 92,\n 11537,\n 1911,\n 18982,\n 7,\n 198,\n 220,\n 220,\n 220,\n 220,\n 220,\n 220,\n 220,\n 6203,\n 13,\n 35875,\n 62,\n 4906,\n 22784,\n 6203,\n 13,\n 1136,\n 62,\n 46911,\n 62,\n 17618,\n 3419,\n 198,\n 220,\n 220,\n 220,\n 1267,\n 198,\n 8,\n 198,\n 198,\n 2,\n 5345,\n 4238,\n 3159,\n 22204,\n 284,\n 1542,\n 7225,\n 198,\n 35875,\n 13,\n 2617,\n 62,\n 29199,\n 1108,\n 7,\n 1270,\n 8,\n 198,\n 2,\n 5345,\n 4238,\n 1994,\n 4263,\n 13,\n 198,\n 2,\n 329,\n 1994,\n 287,\n 2837,\n 7,\n 35875,\n 13,\n 2539,\n 62,\n 9127,\n 3419,\n 2599,\n 198,\n 2,\n 220,\n 220,\n 220,\n 4296,\n 62,\n 2539,\n 62,\n 9060,\n 7,\n 35875,\n 11,\n 1994,\n 11,\n 10352,\n 8,\n 198,\n 198,\n 2,\n 17296,\n 23838,\n 2163,\n 329,\n 618,\n 257,\n 1994,\n 1181,\n 2458,\n 13,\n 198,\n 35875,\n 13,\n 2617,\n 62,\n 2539,\n 62,\n 47423,\n 7,\n 2539,\n 62,\n 3803,\n 62,\n 47423,\n 8,\n 198,\n 198,\n 4514,\n 6407,\n 25,\n 198,\n 220,\n 220,\n 220,\n 329,\n 4936,\n 287,\n 12163,\n 25,\n 198,\n 220,\n 220,\n 220,\n 220,\n 220,\n 220,\n 220,\n 4936,\n 13,\n 19119,\n 7,\n 35875,\n 8,\n 198,\n 198,\n 2,\n 16314,\n 1566,\n 477,\n 3586,\n 14390,\n 423,\n 23083,\n 357,\n 1640,\n 428,\n 1672,\n 11,\n 198,\n 2,\n 428,\n 318,\n 618,\n 477,\n 6203,\n 17105,\n 389,\n 4838,\n 737,\n 198,\n 1640,\n 256,\n 287,\n 4704,\n 278,\n 13,\n 268,\n 6975,\n 378,\n 33529,\n 198,\n 220,\n 220,\n 220,\n 611,\n 256,\n 318,\n 4704,\n 278,\n 13,\n 14421,\n 16818,\n 33529,\n 198,\n 220,\n 220,\n 220,\n 220,\n 220,\n 220,\n 220,\n 2555,\n 198,\n 220,\n 220,\n 220,\n 611,\n 256,\n 13,\n 271,\n 62,\n 282,\n 425,\n 33529,\n 198,\n 220,\n 220,\n 220,\n 220,\n 220,\n 220,\n 220,\n 256,\n 13,\n 22179,\n 3419,\n 198\n]"},"ratio_char_token":{"kind":"number","value":2.57703081232493,"string":"2.577031"},"token_count":{"kind":"number","value":714,"string":"714"}}},{"rowIdx":1273,"cells":{"content":{"kind":"string","value":"from dragonfly import (Grammar, CompoundRule, Text, MappingRule, Dictation, Function, Choice)\nfrom macro_utilities import (replace_in_text, comment_choice, execute_with_dictation)\nfrom vim.rules.letter import (camel_case, proper)\n\n\n\n\n\n\n\n\ncomparison_choice_map = {\n \"equal\": \"==\",\n \"not equal\": \"/=\",\n \"less or equal\": \"<=\",\n \"greater or equal\": \">=\",\n \"less\": \"<\",\n \"greater\": \">\",\n}\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\nstack_command_choice_map = {\n \"build fast\": \"build --fast\",\n \"build\": \"build\",\n \"shell\": \"repl\",\n \"shall\": \"repl\",\n \"test\": \"test\",\n \"test fast\": \"test --fast\",\n \"run\": \"run\",\n \"install\": \"install\",\n}\n\n\n\n\n\n# The main Curry grammar rules are activated here\ncurryBootstrap = Grammar(\"curry bootstrap\")\ncurryBootstrap.add_rule(CurryEnabler())\ncurryBootstrap.load()\n\ncurryGrammar = Grammar(\"curry grammar\")\ncurryGrammar.add_rule(CurryUtilities())\ncurryGrammar.add_rule(CurryDisabler())\ncurryGrammar.load()\ncurryGrammar.disable()\n\n"},"input_ids":{"kind":"list like","value":[6738,10441,12254,1330,357,38,859,3876,11,3082,633,31929,11,8255,11,337,5912,31929,11,360,713,341,11,15553,11,18502,8,198,6738,15021,62,315,2410,1330,357,33491,62,259,62,5239,11,2912,62,25541,11,12260,62,4480,62,11600,341,8,198,6738,43907,13,38785,13,9291,1330,357,66,17983,62,7442,11,1774,8,628,628,628,628,198,785,1845,1653,62,25541,62,8899,796,1391,198,220,220,220,366,40496,1298,366,855,1600,198,220,220,220,366,1662,4961,1298,12813,28,1600,198,220,220,220,366,1203,393,4961,1298,33490,28,1600,198,220,220,220,366,18223,263,393,4961,1298,366,29,28,1600,198,220,220,220,366,1203,1298,33490,1600,198,220,220,220,366,18223,263,1298,366,29,1600,198,92,628,628,628,628,628,628,628,628,628,628,198,25558,62,21812,62,25541,62,8899,796,1391,198,220,220,220,366,11249,3049,1298,366,11249,1377,7217,1600,198,220,220,220,366,11249,1298,366,11249,1600,198,220,220,220,366,29149,1298,366,35666,1600,198,220,220,220,366,49271,1298,366,35666,1600,198,220,220,220,366,9288,1298,366,9288,1600,198,220,220,220,366,9288,3049,1298,366,9288,1377,7217,1600,198,220,220,220,366,5143,1298,366,5143,1600,198,220,220,220,366,17350,1298,366,17350,1600,198,92,628,628,198,198,2,383,1388,20920,23491,3173,389,13906,994,198,66,16682,36476,26418,796,20159,3876,7203,66,16682,6297,26418,4943,198,66,16682,36476,26418,13,2860,62,25135,7,34,16682,4834,397,1754,28955,198,66,16682,36476,26418,13,2220,3419,198,198,66,16682,38,859,3876,796,20159,3876,7203,66,16682,23491,4943,198,66,16682,38,859,3876,13,2860,62,25135,7,34,16682,18274,2410,28955,198,66,16682,38,859,3876,13,2860,62,25135,7,34,16682,7279,397,1754,28955,198,66,16682,38,859,3876,13,2220,3419,198,66,16682,38,859,3876,13,40223,3419,628],"string":"[\n 6738,\n 10441,\n 12254,\n 1330,\n 357,\n 38,\n 859,\n 3876,\n 11,\n 3082,\n 633,\n 31929,\n 11,\n 8255,\n 11,\n 337,\n 5912,\n 31929,\n 11,\n 360,\n 713,\n 341,\n 11,\n 15553,\n 11,\n 18502,\n 8,\n 198,\n 6738,\n 15021,\n 62,\n 315,\n 2410,\n 1330,\n 357,\n 33491,\n 62,\n 259,\n 62,\n 5239,\n 11,\n 2912,\n 62,\n 25541,\n 11,\n 12260,\n 62,\n 4480,\n 62,\n 11600,\n 341,\n 8,\n 198,\n 6738,\n 43907,\n 13,\n 38785,\n 13,\n 9291,\n 1330,\n 357,\n 66,\n 17983,\n 62,\n 7442,\n 11,\n 1774,\n 8,\n 628,\n 628,\n 628,\n 628,\n 198,\n 785,\n 1845,\n 1653,\n 62,\n 25541,\n 62,\n 8899,\n 796,\n 1391,\n 198,\n 220,\n 220,\n 220,\n 366,\n 40496,\n 1298,\n 366,\n 855,\n 1600,\n 198,\n 220,\n 220,\n 220,\n 366,\n 1662,\n 4961,\n 1298,\n 12813,\n 28,\n 1600,\n 198,\n 220,\n 220,\n 220,\n 366,\n 1203,\n 393,\n 4961,\n 1298,\n 33490,\n 28,\n 1600,\n 198,\n 220,\n 220,\n 220,\n 366,\n 18223,\n 263,\n 393,\n 4961,\n 1298,\n 366,\n 29,\n 28,\n 1600,\n 198,\n 220,\n 220,\n 220,\n 366,\n 1203,\n 1298,\n 33490,\n 1600,\n 198,\n 220,\n 220,\n 220,\n 366,\n 18223,\n 263,\n 1298,\n 366,\n 29,\n 1600,\n 198,\n 92,\n 628,\n 628,\n 628,\n 628,\n 628,\n 628,\n 628,\n 628,\n 628,\n 628,\n 198,\n 25558,\n 62,\n 21812,\n 62,\n 25541,\n 62,\n 8899,\n 796,\n 1391,\n 198,\n 220,\n 220,\n 220,\n 366,\n 11249,\n 3049,\n 1298,\n 366,\n 11249,\n 1377,\n 7217,\n 1600,\n 198,\n 220,\n 220,\n 220,\n 366,\n 11249,\n 1298,\n 366,\n 11249,\n 1600,\n 198,\n 220,\n 220,\n 220,\n 366,\n 29149,\n 1298,\n 366,\n 35666,\n 1600,\n 198,\n 220,\n 220,\n 220,\n 366,\n 49271,\n 1298,\n 366,\n 35666,\n 1600,\n 198,\n 220,\n 220,\n 220,\n 366,\n 9288,\n 1298,\n 366,\n 9288,\n 1600,\n 198,\n 220,\n 220,\n 220,\n 366,\n 9288,\n 3049,\n 1298,\n 366,\n 9288,\n 1377,\n 7217,\n 1600,\n 198,\n 220,\n 220,\n 220,\n 366,\n 5143,\n 1298,\n 366,\n 5143,\n 1600,\n 198,\n 220,\n 220,\n 220,\n 366,\n 17350,\n 1298,\n 366,\n 17350,\n 1600,\n 198,\n 92,\n 628,\n 628,\n 198,\n 198,\n 2,\n 383,\n 1388,\n 20920,\n 23491,\n 3173,\n 389,\n 13906,\n 994,\n 198,\n 66,\n 16682,\n 36476,\n 26418,\n 796,\n 20159,\n 3876,\n 7203,\n 66,\n 16682,\n 6297,\n 26418,\n 4943,\n 198,\n 66,\n 16682,\n 36476,\n 26418,\n 13,\n 2860,\n 62,\n 25135,\n 7,\n 34,\n 16682,\n 4834,\n 397,\n 1754,\n 28955,\n 198,\n 66,\n 16682,\n 36476,\n 26418,\n 13,\n 2220,\n 3419,\n 198,\n 198,\n 66,\n 16682,\n 38,\n 859,\n 3876,\n 796,\n 20159,\n 3876,\n 7203,\n 66,\n 16682,\n 23491,\n 4943,\n 198,\n 66,\n 16682,\n 38,\n 859,\n 3876,\n 13,\n 2860,\n 62,\n 25135,\n 7,\n 34,\n 16682,\n 18274,\n 2410,\n 28955,\n 198,\n 66,\n 16682,\n 38,\n 859,\n 3876,\n 13,\n 2860,\n 62,\n 25135,\n 7,\n 34,\n 16682,\n 7279,\n 397,\n 1754,\n 28955,\n 198,\n 66,\n 16682,\n 38,\n 859,\n 3876,\n 13,\n 2220,\n 3419,\n 198,\n 66,\n 16682,\n 38,\n 859,\n 3876,\n 13,\n 40223,\n 3419,\n 628\n]"},"ratio_char_token":{"kind":"number","value":2.5782493368700266,"string":"2.578249"},"token_count":{"kind":"number","value":377,"string":"377"}}},{"rowIdx":1274,"cells":{"content":{"kind":"string","value":"from deluge.plugins.init import PluginInitBase\n\n\nVERSION = (0, 1, 8)\n\n\n\n"},"input_ids":{"kind":"list like","value":[6738,1619,2217,13,37390,13,15003,1330,42636,31768,14881,628,198,43717,796,357,15,11,352,11,807,8,628,628],"string":"[\n 6738,\n 1619,\n 2217,\n 13,\n 37390,\n 13,\n 15003,\n 1330,\n 42636,\n 31768,\n 14881,\n 628,\n 198,\n 43717,\n 796,\n 357,\n 15,\n 11,\n 352,\n 11,\n 807,\n 8,\n 628,\n 628\n]"},"ratio_char_token":{"kind":"number","value":3,"string":"3"},"token_count":{"kind":"number","value":24,"string":"24"}}},{"rowIdx":1275,"cells":{"content":{"kind":"string","value":"from django.shortcuts import reverse\nfrom django.views.generic import UpdateView\n\nfrom applications.users.forms.profile import ProfileForm\nfrom applications.users.layouts.profile import ProfileLayout\nfrom applications.users.mixins.authenticated import AuthenticatedMixin\nfrom applications.common.mixins.add_message import AddMessageMixin\nfrom applications.common.mixins.add_request_to_form import AddRequestToFormMixin\n\n\n\nProfile = ProfileCBV.as_view()\n"},"input_ids":{"kind":"list like","value":[6738,42625,14208,13,19509,23779,1330,9575,198,6738,42625,14208,13,33571,13,41357,1330,10133,7680,198,198,6738,5479,13,18417,13,23914,13,13317,1330,13118,8479,198,6738,5479,13,18417,13,10724,5269,13,13317,1330,13118,32517,198,6738,5479,13,18417,13,19816,1040,13,41299,3474,1330,31885,3474,35608,259,198,6738,5479,13,11321,13,19816,1040,13,2860,62,20500,1330,3060,12837,35608,259,198,6738,5479,13,11321,13,19816,1040,13,2860,62,25927,62,1462,62,687,1330,3060,18453,2514,8479,35608,259,628,198,198,37046,796,13118,23199,53,13,292,62,1177,3419,198],"string":"[\n 6738,\n 42625,\n 14208,\n 13,\n 19509,\n 23779,\n 1330,\n 9575,\n 198,\n 6738,\n 42625,\n 14208,\n 13,\n 33571,\n 13,\n 41357,\n 1330,\n 10133,\n 7680,\n 198,\n 198,\n 6738,\n 5479,\n 13,\n 18417,\n 13,\n 23914,\n 13,\n 13317,\n 1330,\n 13118,\n 8479,\n 198,\n 6738,\n 5479,\n 13,\n 18417,\n 13,\n 10724,\n 5269,\n 13,\n 13317,\n 1330,\n 13118,\n 32517,\n 198,\n 6738,\n 5479,\n 13,\n 18417,\n 13,\n 19816,\n 1040,\n 13,\n 41299,\n 3474,\n 1330,\n 31885,\n 3474,\n 35608,\n 259,\n 198,\n 6738,\n 5479,\n 13,\n 11321,\n 13,\n 19816,\n 1040,\n 13,\n 2860,\n 62,\n 20500,\n 1330,\n 3060,\n 12837,\n 35608,\n 259,\n 198,\n 6738,\n 5479,\n 13,\n 11321,\n 13,\n 19816,\n 1040,\n 13,\n 2860,\n 62,\n 25927,\n 62,\n 1462,\n 62,\n 687,\n 1330,\n 3060,\n 18453,\n 2514,\n 8479,\n 35608,\n 259,\n 628,\n 198,\n 198,\n 37046,\n 796,\n 13118,\n 23199,\n 53,\n 13,\n 292,\n 62,\n 1177,\n 3419,\n 198\n]"},"ratio_char_token":{"kind":"number","value":3.9391304347826086,"string":"3.93913"},"token_count":{"kind":"number","value":115,"string":"115"}}},{"rowIdx":1276,"cells":{"content":{"kind":"string","value":"# -*- coding: utf-8 -*-\n\nimport csv\nimport os\n\nimport cv2\nimport numpy as np\nfrom flask import render_template, request, redirect, url_for\nfrom flask import jsonify\nfrom app.main import main\nfrom app.utils.frame.frame import base64_to_png\nfrom app.utils.frame.site import Site\nfrom app.utils.frame.sub import PictureSub\nfrom config import Config\nimport json\n\n\n@main.route('/')\n\n\n@main.route('/picture/', methods=['GET', 'POST'])\n\n\n# INFO 2019/12/25 15:18 liliangbin 背景图片设置\n@main.route('/background/', methods=['GET', 'POST'])\n\n\n# TODO 2020/1/4 15:13 liliangbin 返回的地址应该是画框的位置(视频名字和时间位置)通过前端设置了\n@main.route('/site/', methods=['GET', 'POST'])\n\n\n# TODO 2020/6/12 15:50 liliangbin 代码可以优化一波\n@main.route('/change_datas/', methods=['GET', 'POST'])\n\n\n# INFO 2020/6/12 15:51 liliangbin 获取用户\n@main.route(\"/site_get/\", methods=['GET', 'POST'])\n\n\n@main.route('/video_location/', methods=['POST'])\n"},"input_ids":{"kind":"list like","value":[2,532,9,12,19617,25,3384,69,12,23,532,9,12,198,198,11748,269,21370,198,11748,28686,198,198,11748,269,85,17,198,11748,299,32152,355,45941,198,6738,42903,1330,8543,62,28243,11,2581,11,18941,11,19016,62,1640,198,6738,42903,1330,33918,1958,198,6738,598,13,12417,1330,1388,198,6738,598,13,26791,13,14535,13,14535,1330,2779,2414,62,1462,62,11134,198,6738,598,13,26791,13,14535,13,15654,1330,14413,198,6738,598,13,26791,13,14535,13,7266,1330,17741,7004,198,6738,4566,1330,17056,198,11748,33918,628,198,31,12417,13,38629,10786,14,11537,628,198,31,12417,13,38629,10786,14,34053,14,3256,5050,28,17816,18851,3256,705,32782,6,12962,628,198,2,24890,13130,14,1065,14,1495,1315,25,1507,300,2403,648,8800,220,5525,225,234,162,247,107,32368,122,31965,229,164,106,122,163,121,106,198,31,12417,13,38629,10786,14,25249,14,3256,5050,28,17816,18851,3256,705,32782,6,12962,628,198,2,16926,46,12131,14,16,14,19,1315,25,1485,300,2403,648,8800,5525,123,242,32368,252,21410,28839,108,161,251,222,41753,242,46237,98,42468,18796,119,162,94,228,21410,19526,235,163,121,106,171,120,230,164,100,228,165,95,239,28938,235,27764,245,161,240,234,33768,114,29785,112,19526,235,163,121,106,171,120,231,34460,248,32573,229,30298,235,44165,107,164,106,122,163,121,106,12859,228,198,31,12417,13,38629,10786,14,15654,14,3256,5050,28,17816,18851,3256,705,32782,6,12962,628,198,2,16926,46,12131,14,21,14,1065,1315,25,1120,300,2403,648,8800,220,47987,163,254,223,20998,107,20015,98,27670,246,44293,244,31660,37345,95,198,31,12417,13,38629,10786,14,3803,62,19608,292,14,3256,5050,28,17816,18851,3256,705,32782,6,12962,628,198,2,24890,12131,14,21,14,1065,1315,25,4349,300,2403,648,8800,220,5525,236,115,20998,244,18796,101,22755,115,198,31,12417,13,38629,7203,14,15654,62,1136,14,1600,5050,28,17816,18851,3256,705,32782,6,12962,628,198,31,12417,13,38629,10786,14,15588,62,24886,14,3256,5050,28,17816,32782,6,12962,198],"string":"[\n 2,\n 532,\n 9,\n 12,\n 19617,\n 25,\n 3384,\n 69,\n 12,\n 23,\n 532,\n 9,\n 12,\n 198,\n 198,\n 11748,\n 269,\n 21370,\n 198,\n 11748,\n 28686,\n 198,\n 198,\n 11748,\n 269,\n 85,\n 17,\n 198,\n 11748,\n 299,\n 32152,\n 355,\n 45941,\n 198,\n 6738,\n 42903,\n 1330,\n 8543,\n 62,\n 28243,\n 11,\n 2581,\n 11,\n 18941,\n 11,\n 19016,\n 62,\n 1640,\n 198,\n 6738,\n 42903,\n 1330,\n 33918,\n 1958,\n 198,\n 6738,\n 598,\n 13,\n 12417,\n 1330,\n 1388,\n 198,\n 6738,\n 598,\n 13,\n 26791,\n 13,\n 14535,\n 13,\n 14535,\n 1330,\n 2779,\n 2414,\n 62,\n 1462,\n 62,\n 11134,\n 198,\n 6738,\n 598,\n 13,\n 26791,\n 13,\n 14535,\n 13,\n 15654,\n 1330,\n 14413,\n 198,\n 6738,\n 598,\n 13,\n 26791,\n 13,\n 14535,\n 13,\n 7266,\n 1330,\n 17741,\n 7004,\n 198,\n 6738,\n 4566,\n 1330,\n 17056,\n 198,\n 11748,\n 33918,\n 628,\n 198,\n 31,\n 12417,\n 13,\n 38629,\n 10786,\n 14,\n 11537,\n 628,\n 198,\n 31,\n 12417,\n 13,\n 38629,\n 10786,\n 14,\n 34053,\n 14,\n 3256,\n 5050,\n 28,\n 17816,\n 18851,\n 3256,\n 705,\n 32782,\n 6,\n 12962,\n 628,\n 198,\n 2,\n 24890,\n 13130,\n 14,\n 1065,\n 14,\n 1495,\n 1315,\n 25,\n 1507,\n 300,\n 2403,\n 648,\n 8800,\n 220,\n 5525,\n 225,\n 234,\n 162,\n 247,\n 107,\n 32368,\n 122,\n 31965,\n 229,\n 164,\n 106,\n 122,\n 163,\n 121,\n 106,\n 198,\n 31,\n 12417,\n 13,\n 38629,\n 10786,\n 14,\n 25249,\n 14,\n 3256,\n 5050,\n 28,\n 17816,\n 18851,\n 3256,\n 705,\n 32782,\n 6,\n 12962,\n 628,\n 198,\n 2,\n 16926,\n 46,\n 12131,\n 14,\n 16,\n 14,\n 19,\n 1315,\n 25,\n 1485,\n 300,\n 2403,\n 648,\n 8800,\n 5525,\n 123,\n 242,\n 32368,\n 252,\n 21410,\n 28839,\n 108,\n 161,\n 251,\n 222,\n 41753,\n 242,\n 46237,\n 98,\n 42468,\n 18796,\n 119,\n 162,\n 94,\n 228,\n 21410,\n 19526,\n 235,\n 163,\n 121,\n 106,\n 171,\n 120,\n 230,\n 164,\n 100,\n 228,\n 165,\n 95,\n 239,\n 28938,\n 235,\n 27764,\n 245,\n 161,\n 240,\n 234,\n 33768,\n 114,\n 29785,\n 112,\n 19526,\n 235,\n 163,\n 121,\n 106,\n 171,\n 120,\n 231,\n 34460,\n 248,\n 32573,\n 229,\n 30298,\n 235,\n 44165,\n 107,\n 164,\n 106,\n 122,\n 163,\n 121,\n 106,\n 12859,\n 228,\n 198,\n 31,\n 12417,\n 13,\n 38629,\n 10786,\n 14,\n 15654,\n 14,\n 3256,\n 5050,\n 28,\n 17816,\n 18851,\n 3256,\n 705,\n 32782,\n 6,\n 12962,\n 628,\n 198,\n 2,\n 16926,\n 46,\n 12131,\n 14,\n 21,\n 14,\n 1065,\n 1315,\n 25,\n 1120,\n 300,\n 2403,\n 648,\n 8800,\n 220,\n 47987,\n 163,\n 254,\n 223,\n 20998,\n 107,\n 20015,\n 98,\n 27670,\n 246,\n 44293,\n 244,\n 31660,\n 37345,\n 95,\n 198,\n 31,\n 12417,\n 13,\n 38629,\n 10786,\n 14,\n 3803,\n 62,\n 19608,\n 292,\n 14,\n 3256,\n 5050,\n 28,\n 17816,\n 18851,\n 3256,\n 705,\n 32782,\n 6,\n 12962,\n 628,\n 198,\n 2,\n 24890,\n 12131,\n 14,\n 21,\n 14,\n 1065,\n 1315,\n 25,\n 4349,\n 300,\n 2403,\n 648,\n 8800,\n 220,\n 5525,\n 236,\n 115,\n 20998,\n 244,\n 18796,\n 101,\n 22755,\n 115,\n 198,\n 31,\n 12417,\n 13,\n 38629,\n 7203,\n 14,\n 15654,\n 62,\n 1136,\n 14,\n 1600,\n 5050,\n 28,\n 17816,\n 18851,\n 3256,\n 705,\n 32782,\n 6,\n 12962,\n 628,\n 198,\n 31,\n 12417,\n 13,\n 38629,\n 10786,\n 14,\n 15588,\n 62,\n 24886,\n 14,\n 3256,\n 5050,\n 28,\n 17816,\n 32782,\n 6,\n 12962,\n 198\n]"},"ratio_char_token":{"kind":"number","value":2.1196172248803826,"string":"2.119617"},"token_count":{"kind":"number","value":418,"string":"418"}}},{"rowIdx":1277,"cells":{"content":{"kind":"string","value":"# django imports\nfrom django.forms import ModelForm\n\n# lfs imports\nfrom lfs.discounts.models import Discount\n\n\nclass DiscountForm(ModelForm):\n \"\"\"\n Form to manage discount data.\n \"\"\"\n"},"input_ids":{"kind":"list like","value":[2,42625,14208,17944,198,6738,42625,14208,13,23914,1330,9104,8479,198,198,2,300,9501,17944,198,6738,300,9501,13,15410,608,82,13,27530,1330,43474,628,198,4871,43474,8479,7,17633,8479,2599,198,220,220,220,37227,198,220,220,220,5178,284,6687,9780,1366,13,198,220,220,220,37227,198],"string":"[\n 2,\n 42625,\n 14208,\n 17944,\n 198,\n 6738,\n 42625,\n 14208,\n 13,\n 23914,\n 1330,\n 9104,\n 8479,\n 198,\n 198,\n 2,\n 300,\n 9501,\n 17944,\n 198,\n 6738,\n 300,\n 9501,\n 13,\n 15410,\n 608,\n 82,\n 13,\n 27530,\n 1330,\n 43474,\n 628,\n 198,\n 4871,\n 43474,\n 8479,\n 7,\n 17633,\n 8479,\n 2599,\n 198,\n 220,\n 220,\n 220,\n 37227,\n 198,\n 220,\n 220,\n 220,\n 5178,\n 284,\n 6687,\n 9780,\n 1366,\n 13,\n 198,\n 220,\n 220,\n 220,\n 37227,\n 198\n]"},"ratio_char_token":{"kind":"number","value":3.1475409836065573,"string":"3.147541"},"token_count":{"kind":"number","value":61,"string":"61"}}},{"rowIdx":1278,"cells":{"content":{"kind":"string","value":"# MIT License\n#\n# Copyright (c) 2020 SCL team at Red Hat\n#\n# Permission is hereby granted, free of charge, to any person obtaining a copy\n# of this software and associated documentation files (the \"Software\"), to deal\n# in the Software without restriction, including without limitation the rights\n# to use, copy, modify, merge, publish, distribute, sublicense, and/or sell\n# copies of the Software, and to permit persons to whom the Software is\n# furnished to do so, subject to the following conditions:\n#\n# The above copyright notice and this permission notice shall be included in all\n# copies or substantial portions of the Software.\n#\n# THE SOFTWARE IS PROVIDED \"AS IS\", WITHOUT WARRANTY OF ANY KIND, EXPRESS OR\n# IMPLIED, INCLUDING BUT NOT LIMITED TO THE WARRANTIES OF MERCHANTABILITY,\n# FITNESS FOR A PARTICULAR PURPOSE AND NONINFRINGEMENT. IN NO EVENT SHALL THE\n# AUTHORS OR COPYRIGHT HOLDERS BE LIABLE FOR ANY CLAIM, DAMAGES OR OTHER\n# LIABILITY, WHETHER IN AN ACTION OF CONTRACT, TORT OR OTHERWISE, ARISING FROM,\n# OUT OF OR IN CONNECTION WITH THE SOFTWARE OR THE USE OR OTHER DEALINGS IN THE\n# SOFTWARE.\n\n\nfrom contextlib import contextmanager\nimport logging\nimport shutil\nimport os\nimport json\n\nimport jinja2\nimport subprocess\n\nfrom pathlib import Path\nfrom betka.constants import HOME\n\nlogger = logging.getLogger(__name__)\n\n\ndef run_cmd(cmd, return_output=False, ignore_error=False, shell=False, **kwargs):\n \"\"\"\n Run provided command on host system using the same user as invoked this code.\n Raises subprocess.CalledProcessError if it fails.\n\n :param cmd: list or str\n :param return_output: bool, return output of the command\n :param ignore_error: bool, do not fail in case nonzero return code\n :param shell: bool, run command in shell\n :param kwargs: pass keyword arguments to subprocess.check_* functions; for more info,\n please check `help(subprocess.Popen)`\n :return: None or str\n \"\"\"\n logger.debug(\"command: %r\", cmd)\n try:\n if return_output:\n return subprocess.check_output(\n cmd,\n stderr=subprocess.STDOUT,\n universal_newlines=True,\n shell=shell,\n **kwargs,\n )\n else:\n return subprocess.check_call(cmd, shell=shell, **kwargs)\n except subprocess.CalledProcessError as cpe:\n if ignore_error:\n if return_output:\n return cpe.output\n else:\n return cpe.returncode\n else:\n logger.error(f\"failed with code {cpe.returncode} and output:\\n{cpe.output}\")\n raise cpe\n\n\ndef text_from_template(template_dir, template_filename, template_data):\n \"\"\"\n Create text based on template in path template_dir/template_filename\n :param template_dir: string, directory containing templates\n :param template_filename: template for text in jinja\n :param template_data: dict, data for substitution in template\n :return: string\n \"\"\"\n\n if not os.path.exists(os.path.join(template_dir, template_filename)):\n raise FileNotFoundError(\"Path to template not found.\")\n\n template_loader = jinja2.FileSystemLoader(searchpath=template_dir)\n template_env = jinja2.Environment(loader=template_loader)\n template = template_env.get_template(template_filename)\n output_text = template.render(template_data=template_data)\n logger.debug(\"Text from template created:\")\n logger.debug(output_text)\n\n return output_text\n\n\ndef copy_upstream2downstream(src_parent: Path, dest_parent: Path):\n \"\"\"Copies content from upstream repo to downstream repo\n\n Copies all files/dirs/symlinks from upstream source to dist-git one by one,\n while removing previous if exists.\n\n :param src_parent: path to source directory\n :param dest_parent: path to destination directory\n \"\"\"\n for f in src_parent.iterdir():\n if f.name.startswith(\".git\"):\n continue\n dest = dest_parent / f.name\n src = src_parent / f.name\n logger.debug(f\"Copying {str(src)} to {str(dest)}.\")\n # First remove the dest only if it is not symlink.\n if dest.is_dir() and not dest.is_symlink():\n logger.debug(\"rmtree %s\", dest)\n shutil.rmtree(dest)\n else:\n if dest.exists():\n dest.unlink()\n\n # Now copy the src to dest\n if src.is_symlink() or not src.is_dir():\n logger.debug(\"cp %s %s\", src, dest)\n shutil.copy2(src, dest, follow_symlinks=False)\n else:\n logger.debug(\"cp -r %s %s\", src, dest)\n shutil.copytree(src, dest, symlinks=True)\n\n\ndef clean_directory(path: Path):\n \"\"\"\n Function cleans directory except itself\n :param path: directory path which is cleaned\n \"\"\"\n for d in path.iterdir():\n src = path / d\n if src.is_dir():\n logger.debug(\"rmtree %s\", str(src))\n shutil.rmtree(src)\n else:\n src.unlink()\n\n\ndef list_dir_content(dir_name: Path):\n \"\"\"\n Lists all content of dir_name\n :param dir_name: Directory for showing files\n \"\"\"\n logger.info(\"Look for a content in '%s' directory\", str(dir_name))\n for f in dir_name.rglob(\"*\"):\n if str(f).startswith(\".git\"):\n continue\n logger.debug(f\"{f.parent / f.name}\")\n\n\n\n@contextmanager\ndef cwd(path):\n \"\"\"\n Switch to Path directory and once action is done\n returns back\n :param path:\n :return:\n \"\"\"\n prev_cwd = Path.cwd()\n os.chdir(path)\n try:\n yield\n finally:\n os.chdir(prev_cwd)\n"},"input_ids":{"kind":"list like","value":[2,17168,13789,198,2,198,2,15069,357,66,8,12131,311,5097,1074,379,2297,10983,198,2,198,2,2448,3411,318,29376,7520,11,1479,286,3877,11,284,597,1048,16727,257,4866,198,2,286,428,3788,290,3917,10314,3696,357,1169,366,25423,12340,284,1730,198,2,287,262,10442,1231,17504,11,1390,1231,17385,262,2489,198,2,284,779,11,4866,11,13096,11,20121,11,7715,11,14983,11,850,43085,11,290,14,273,3677,198,2,9088,286,262,10442,11,290,284,8749,6506,284,4150,262,10442,318,198,2,30760,284,466,523,11,2426,284,262,1708,3403,25,198,2,198,2,383,2029,6634,4003,290,428,7170,4003,2236,307,3017,287,477,198,2,9088,393,8904,16690,286,262,10442,13,198,2,198,2,3336,47466,3180,36592,2389,1961,366,1921,3180,1600,42881,34764,56,3963,15529,509,12115,11,7788,32761,6375,198,2,8959,49094,11,47783,2751,21728,5626,40880,5390,3336,34764,11015,3963,34482,3398,1565,5603,25382,11,198,2,376,46144,7473,317,16652,2149,37232,33079,48933,5357,44521,1268,10913,2751,12529,13,3268,8005,49261,50163,3336,198,2,37195,20673,6375,27975,38162,9947,367,15173,4877,9348,43031,19146,7473,15529,47666,3955,11,29506,25552,6375,25401,198,2,43031,25382,11,7655,2767,16879,3268,3537,40282,3963,27342,10659,11,309,9863,6375,25401,54,24352,11,5923,1797,2751,16034,11,198,2,16289,3963,6375,3268,7102,45,24565,13315,3336,47466,6375,3336,23210,6375,25401,5550,1847,20754,3268,3336,198,2,47466,13,628,198,6738,4732,8019,1330,4732,37153,198,11748,18931,198,11748,4423,346,198,11748,28686,198,11748,33918,198,198,11748,474,259,6592,17,198,11748,850,14681,198,198,6738,3108,8019,1330,10644,198,6738,731,4914,13,9979,1187,1330,41779,198,198,6404,1362,796,18931,13,1136,11187,1362,7,834,3672,834,8,628,198,4299,1057,62,28758,7,28758,11,1441,62,22915,28,25101,11,8856,62,18224,28,25101,11,7582,28,25101,11,12429,46265,22046,2599,198,220,220,220,37227,198,220,220,220,5660,2810,3141,319,2583,1080,1262,262,976,2836,355,24399,428,2438,13,198,220,220,220,7567,2696,850,14681,13,34,4262,18709,12331,611,340,10143,13,628,220,220,220,1058,17143,23991,25,1351,393,965,198,220,220,220,1058,17143,1441,62,22915,25,20512,11,1441,5072,286,262,3141,198,220,220,220,1058,17143,8856,62,18224,25,20512,11,466,407,2038,287,1339,1729,22570,1441,2438,198,220,220,220,1058,17143,7582,25,20512,11,1057,3141,287,7582,198,220,220,220,1058,17143,479,86,22046,25,1208,21179,7159,284,850,14681,13,9122,62,9,5499,26,329,517,7508,11,198,220,220,220,220,220,220,220,220,220,220,220,3387,2198,4600,16794,7,7266,14681,13,47,9654,8,63,198,220,220,220,1058,7783,25,6045,393,965,198,220,220,220,37227,198,220,220,220,49706,13,24442,7203,21812,25,4064,81,1600,23991,8,198,220,220,220,1949,25,198,220,220,220,220,220,220,220,611,1441,62,22915,25,198,220,220,220,220,220,220,220,220,220,220,220,1441,850,14681,13,9122,62,22915,7,198,220,220,220,220,220,220,220,220,220,220,220,220,220,220,220,23991,11,198,220,220,220,220,220,220,220,220,220,220,220,220,220,220,220,336,1082,81,28,7266,14681,13,36886,11,198,220,220,220,220,220,220,220,220,220,220,220,220,220,220,220,10112,62,3605,6615,28,17821,11,198,220,220,220,220,220,220,220,220,220,220,220,220,220,220,220,7582,28,29149,11,198,220,220,220,220,220,220,220,220,220,220,220,220,220,220,220,12429,46265,22046,11,198,220,220,220,220,220,220,220,220,220,220,220,1267,198,220,220,220,220,220,220,220,2073,25,198,220,220,220,220,220,220,220,220,220,220,220,1441,850,14681,13,9122,62,13345,7,28758,11,7582,28,29149,11,12429,46265,22046,8,198,220,220,220,2845,850,14681,13,34,4262,18709,12331,355,269,431,25,198,220,220,220,220,220,220,220,611,8856,62,18224,25,198,220,220,220,220,220,220,220,220,220,220,220,611,1441,62,22915,25,198,220,220,220,220,220,220,220,220,220,220,220,220,220,220,220,1441,269,431,13,22915,198,220,220,220,220,220,220,220,220,220,220,220,2073,25,198,220,220,220,220,220,220,220,220,220,220,220,220,220,220,220,1441,269,431,13,7783,8189,198,220,220,220,220,220,220,220,2073,25,198,220,220,220,220,220,220,220,220,220,220,220,49706,13,18224,7,69,1,47904,351,2438,1391,66,431,13,7783,8189,92,290,5072,7479,77,90,66,431,13,22915,92,4943,198,220,220,220,220,220,220,220,220,220,220,220,5298,269,431,628,198,4299,2420,62,6738,62,28243,7,28243,62,15908,11,11055,62,34345,11,11055,62,7890,2599,198,220,220,220,37227,198,220,220,220,13610,2420,1912,319,11055,287,3108,11055,62,15908,14,28243,62,34345,198,220,220,220,1058,17143,11055,62,15908,25,4731,11,8619,7268,24019,198,220,220,220,1058,17143,11055,62,34345,25,11055,329,2420,287,474,259,6592,198,220,220,220,1058,17143,11055,62,7890,25,8633,11,1366,329,32097,287,11055,198,220,220,220,1058,7783,25,4731,198,220,220,220,37227,628,220,220,220,611,407,28686,13,6978,13,1069,1023,7,418,13,6978,13,22179,7,28243,62,15908,11,11055,62,34345,8,2599,198,220,220,220,220,220,220,220,5298,9220,3673,21077,12331,7203,15235,284,11055,407,1043,19570,628,220,220,220,11055,62,29356,796,474,259,6592,17,13,8979,11964,17401,7,12947,6978,28,28243,62,15908,8,198,220,220,220,11055,62,24330,796,474,259,6592,17,13,31441,7,29356,28,28243,62,29356,8,198,220,220,220,11055,796,11055,62,24330,13,1136,62,28243,7,28243,62,34345,8,198,220,220,220,5072,62,5239,796,11055,13,13287,7,28243,62,7890,28,28243,62,7890,8,198,220,220,220,49706,13,24442,7203,8206,422,11055,2727,25,4943,198,220,220,220,49706,13,24442,7,22915,62,5239,8,628,220,220,220,1441,5072,62,5239,628,198,4299,4866,62,929,5532,17,2902,5532,7,10677,62,8000,25,10644,11,2244,62,8000,25,10644,2599,198,220,220,220,37227,13379,444,2695,422,28717,29924,284,33218,29924,628,220,220,220,220,6955,444,477,3696,14,15908,82,14,37047,28751,422,28717,2723,284,1233,12,18300,530,416,530,11,198,220,220,220,220,981,10829,2180,611,7160,13,628,220,220,220,220,1058,17143,12351,62,8000,25,3108,284,2723,8619,198,220,220,220,220,1058,17143,2244,62,8000,25,3108,284,10965,8619,198,220,220,220,220,37227,198,220,220,220,329,277,287,12351,62,8000,13,2676,15908,33529,198,220,220,220,220,220,220,220,611,277,13,3672,13,9688,2032,342,7,1911,18300,1,2599,198,220,220,220,220,220,220,220,220,220,220,220,2555,198,220,220,220,220,220,220,220,2244,796,2244,62,8000,1220,277,13,3672,198,220,220,220,220,220,220,220,12351,796,12351,62,8000,1220,277,13,3672,198,220,220,220,220,220,220,220,49706,13,24442,7,69,1,13379,1112,1391,2536,7,10677,38165,284,1391,2536,7,16520,38165,19570,198,220,220,220,220,220,220,220,1303,3274,4781,262,2244,691,611,340,318,407,827,4029,676,13,198,220,220,220,220,220,220,220,611,2244,13,271,62,15908,3419,290,407,2244,13,271,62,1837,4029,676,33529,198,220,220,220,220,220,220,220,220,220,220,220,49706,13,24442,7203,81,16762,631,4064,82,1600,2244,8,198,220,220,220,220,220,220,220,220,220,220,220,4423,346,13,81,16762,631,7,16520,8,198,220,220,220,220,220,220,220,2073,25,198,220,220,220,220,220,220,220,220,220,220,220,611,2244,13,1069,1023,33529,198,220,220,220,220,220,220,220,220,220,220,220,220,220,220,220,2244,13,403,8726,3419,628,220,220,220,220,220,220,220,1303,2735,4866,262,12351,284,2244,198,220,220,220,220,220,220,220,611,12351,13,271,62,1837,4029,676,3419,393,407,12351,13,271,62,15908,33529,198,220,220,220,220,220,220,220,220,220,220,220,49706,13,24442,7203,13155,4064,82,4064,82,1600,12351,11,2244,8,198,220,220,220,220,220,220,220,220,220,220,220,4423,346,13,30073,17,7,10677,11,2244,11,1061,62,37047,28751,28,25101,8,198,220,220,220,220,220,220,220,2073,25,198,220,220,220,220,220,220,220,220,220,220,220,49706,13,24442,7203,13155,532,81,4064,82,4064,82,1600,12351,11,2244,8,198,220,220,220,220,220,220,220,220,220,220,220,4423,346,13,30073,21048,7,10677,11,2244,11,5659,28751,28,17821,8,628,198,4299,3424,62,34945,7,6978,25,10644,2599,198,220,220,220,37227,198,220,220,220,15553,20658,8619,2845,2346,198,220,220,220,1058,17143,3108,25,8619,3108,543,318,20750,198,220,220,220,37227,198,220,220,220,329,288,287,3108,13,2676,15908,33529,198,220,220,220,220,220,220,220,12351,796,3108,1220,288,198,220,220,220,220,220,220,220,611,12351,13,271,62,15908,33529,198,220,220,220,220,220,220,220,220,220,220,220,49706,13,24442,7203,81,16762,631,4064,82,1600,965,7,10677,4008,198,220,220,220,220,220,220,220,220,220,220,220,4423,346,13,81,16762,631,7,10677,8,198,220,220,220,220,220,220,220,2073,25,198,220,220,220,220,220,220,220,220,220,220,220,12351,13,403,8726,3419,628,198,4299,1351,62,15908,62,11299,7,15908,62,3672,25,10644,2599,198,220,220,220,37227,198,220,220,220,44968,477,2695,286,26672,62,3672,198,220,220,220,1058,17143,26672,62,3672,25,27387,329,4478,3696,198,220,220,220,37227,198,220,220,220,49706,13,10951,7203,8567,329,257,2695,287,705,4,82,6,8619,1600,965,7,15908,62,3672,4008,198,220,220,220,329,277,287,26672,62,3672,13,81,4743,672,7203,9,1,2599,198,220,220,220,220,220,220,220,611,965,7,69,737,9688,2032,342,7,1911,18300,1,2599,198,220,220,220,220,220,220,220,220,220,220,220,2555,198,220,220,220,220,220,220,220,49706,13,24442,7,69,1,90,69,13,8000,1220,277,13,3672,92,4943,628,198,198,31,22866,37153,198,4299,269,16993,7,6978,2599,198,220,220,220,37227,198,220,220,220,14645,284,10644,8619,290,1752,2223,318,1760,198,220,220,220,5860,736,198,220,220,220,1058,17143,3108,25,198,220,220,220,1058,7783,25,198,220,220,220,37227,198,220,220,220,8654,62,66,16993,796,10644,13,66,16993,3419,198,220,220,220,28686,13,354,15908,7,6978,8,198,220,220,220,1949,25,198,220,220,220,220,220,220,220,7800,198,220,220,220,3443,25,198,220,220,220,220,220,220,220,28686,13,354,15908,7,47050,62,66,16993,8,198],"string":"[\n 2,\n 17168,\n 13789,\n 198,\n 2,\n 198,\n 2,\n 15069,\n 357,\n 66,\n 8,\n 12131,\n 311,\n 5097,\n 1074,\n 379,\n 2297,\n 10983,\n 198,\n 2,\n 198,\n 2,\n 2448,\n 3411,\n 318,\n 29376,\n 7520,\n 11,\n 1479,\n 286,\n 3877,\n 11,\n 284,\n 597,\n 1048,\n 16727,\n 257,\n 4866,\n 198,\n 2,\n 286,\n 428,\n 3788,\n 290,\n 3917,\n 10314,\n 3696,\n 357,\n 1169,\n 366,\n 25423,\n 12340,\n 284,\n 1730,\n 198,\n 2,\n 287,\n 262,\n 10442,\n 1231,\n 17504,\n 11,\n 1390,\n 1231,\n 17385,\n 262,\n 2489,\n 198,\n 2,\n 284,\n 779,\n 11,\n 4866,\n 11,\n 13096,\n 11,\n 20121,\n 11,\n 7715,\n 11,\n 14983,\n 11,\n 850,\n 43085,\n 11,\n 290,\n 14,\n 273,\n 3677,\n 198,\n 2,\n 9088,\n 286,\n 262,\n 10442,\n 11,\n 290,\n 284,\n 8749,\n 6506,\n 284,\n 4150,\n 262,\n 10442,\n 318,\n 198,\n 2,\n 30760,\n 284,\n 466,\n 523,\n 11,\n 2426,\n 284,\n 262,\n 1708,\n 3403,\n 25,\n 198,\n 2,\n 198,\n 2,\n 383,\n 2029,\n 6634,\n 4003,\n 290,\n 428,\n 7170,\n 4003,\n 2236,\n 307,\n 3017,\n 287,\n 477,\n 198,\n 2,\n 9088,\n 393,\n 8904,\n 16690,\n 286,\n 262,\n 10442,\n 13,\n 198,\n 2,\n 198,\n 2,\n 3336,\n 47466,\n 3180,\n 36592,\n 2389,\n 1961,\n 366,\n 1921,\n 3180,\n 1600,\n 42881,\n 34764,\n 56,\n 3963,\n 15529,\n 509,\n 12115,\n 11,\n 7788,\n 32761,\n 6375,\n 198,\n 2,\n 8959,\n 49094,\n 11,\n 47783,\n 2751,\n 21728,\n 5626,\n 40880,\n 5390,\n 3336,\n 34764,\n 11015,\n 3963,\n 34482,\n 3398,\n 1565,\n 5603,\n 25382,\n 11,\n 198,\n 2,\n 376,\n 46144,\n 7473,\n 317,\n 16652,\n 2149,\n 37232,\n 33079,\n 48933,\n 5357,\n 44521,\n 1268,\n 10913,\n 2751,\n 12529,\n 13,\n 3268,\n 8005,\n 49261,\n 50163,\n 3336,\n 198,\n 2,\n 37195,\n 20673,\n 6375,\n 27975,\n 38162,\n 9947,\n 367,\n 15173,\n 4877,\n 9348,\n 43031,\n 19146,\n 7473,\n 15529,\n 47666,\n 3955,\n 11,\n 29506,\n 25552,\n 6375,\n 25401,\n 198,\n 2,\n 43031,\n 25382,\n 11,\n 7655,\n 2767,\n 16879,\n 3268,\n 3537,\n 40282,\n 3963,\n 27342,\n 10659,\n 11,\n 309,\n 9863,\n 6375,\n 25401,\n 54,\n 24352,\n 11,\n 5923,\n 1797,\n 2751,\n 16034,\n 11,\n 198,\n 2,\n 16289,\n 3963,\n 6375,\n 3268,\n 7102,\n 45,\n 24565,\n 13315,\n 3336,\n 47466,\n 6375,\n 3336,\n 23210,\n 6375,\n 25401,\n 5550,\n 1847,\n 20754,\n 3268,\n 3336,\n 198,\n 2,\n 47466,\n 13,\n 628,\n 198,\n 6738,\n 4732,\n 8019,\n 1330,\n 4732,\n 37153,\n 198,\n 11748,\n 18931,\n 198,\n 11748,\n 4423,\n 346,\n 198,\n 11748,\n 28686,\n 198,\n 11748,\n 33918,\n 198,\n 198,\n 11748,\n 474,\n 259,\n 6592,\n 17,\n 198,\n 11748,\n 850,\n 14681,\n 198,\n 198,\n 6738,\n 3108,\n 8019,\n 1330,\n 10644,\n 198,\n 6738,\n 731,\n 4914,\n 13,\n 9979,\n 1187,\n 1330,\n 41779,\n 198,\n 198,\n 6404,\n 1362,\n 796,\n 18931,\n 13,\n 1136,\n 11187,\n 1362,\n 7,\n 834,\n 3672,\n 834,\n 8,\n 628,\n 198,\n 4299,\n 1057,\n 62,\n 28758,\n 7,\n 28758,\n 11,\n 1441,\n 62,\n 22915,\n 28,\n 25101,\n 11,\n 8856,\n 62,\n 18224,\n 28,\n 25101,\n 11,\n 7582,\n 28,\n 25101,\n 11,\n 12429,\n 46265,\n 22046,\n 2599,\n 198,\n 220,\n 220,\n 220,\n 37227,\n 198,\n 220,\n 220,\n 220,\n 5660,\n 2810,\n 3141,\n 319,\n 2583,\n 1080,\n 1262,\n 262,\n 976,\n 2836,\n 355,\n 24399,\n 428,\n 2438,\n 13,\n 198,\n 220,\n 220,\n 220,\n 7567,\n 2696,\n 850,\n 14681,\n 13,\n 34,\n 4262,\n 18709,\n 12331,\n 611,\n 340,\n 10143,\n 13,\n 628,\n 220,\n 220,\n 220,\n 1058,\n 17143,\n 23991,\n 25,\n 1351,\n 393,\n 965,\n 198,\n 220,\n 220,\n 220,\n 1058,\n 17143,\n 1441,\n 62,\n 22915,\n 25,\n 20512,\n 11,\n 1441,\n 5072,\n 286,\n 262,\n 3141,\n 198,\n 220,\n 220,\n 220,\n 1058,\n 17143,\n 8856,\n 62,\n 18224,\n 25,\n 20512,\n 11,\n 466,\n 407,\n 2038,\n 287,\n 1339,\n 1729,\n 22570,\n 1441,\n 2438,\n 198,\n 220,\n 220,\n 220,\n 1058,\n 17143,\n 7582,\n 25,\n 20512,\n 11,\n 1057,\n 3141,\n 287,\n 7582,\n 198,\n 220,\n 220,\n 220,\n 1058,\n 17143,\n 479,\n 86,\n 22046,\n 25,\n 1208,\n 21179,\n 7159,\n 284,\n 850,\n 14681,\n 13,\n 9122,\n 62,\n 9,\n 5499,\n 26,\n 329,\n 517,\n 7508,\n 11,\n 198,\n 220,\n 220,\n 220,\n 220,\n 220,\n 220,\n 220,\n 220,\n 220,\n 220,\n 220,\n 3387,\n 2198,\n 4600,\n 16794,\n 7,\n 7266,\n 14681,\n 13,\n 47,\n 9654,\n 8,\n 63,\n 198,\n 220,\n 220,\n 220,\n 1058,\n 7783,\n 25,\n 6045,\n 393,\n 965,\n 198,\n 220,\n 220,\n 220,\n 37227,\n 198,\n 220,\n 220,\n 220,\n 49706,\n 13,\n 24442,\n 7203,\n 21812,\n 25,\n 4064,\n 81,\n 1600,\n 23991,\n 8,\n 198,\n 220,\n 220,\n 220,\n 1949,\n 25,\n 198,\n 220,\n 220,\n 220,\n 220,\n 220,\n 220,\n 220,\n 611,\n 1441,\n 62,\n 22915,\n 25,\n 198,\n 220,\n 220,\n 220,\n 220,\n 220,\n 220,\n 220,\n 220,\n 220,\n 220,\n 220,\n 1441,\n 850,\n 14681,\n 13,\n 9122,\n 62,\n 22915,\n 7,\n 198,\n 220,\n 220,\n 220,\n 220,\n 220,\n 220,\n 220,\n 220,\n 220,\n 220,\n 220,\n 220,\n 220,\n 220,\n 220,\n 23991,\n 11,\n 198,\n 220,\n 220,\n 220,\n 220,\n 220,\n 220,\n 220,\n 220,\n 220,\n 220,\n 220,\n 220,\n 220,\n 220,\n 220,\n 336,\n 1082,\n 81,\n 28,\n 7266,\n 14681,\n 13,\n 36886,\n 11,\n 198,\n 220,\n 220,\n 220,\n 220,\n 220,\n 220,\n 220,\n 220,\n 220,\n 220,\n 220,\n 220,\n 220,\n 220,\n 220,\n 10112,\n 62,\n 3605,\n 6615,\n 28,\n 17821,\n 11,\n 198,\n 220,\n 220,\n 220,\n 220,\n 220,\n 220,\n 220,\n 220,\n 220,\n 220,\n 220,\n 220,\n 220,\n 220,\n 220,\n 7582,\n 28,\n 29149,\n 11,\n 198,\n 220,\n 220,\n 220,\n 220,\n 220,\n 220,\n 220,\n 220,\n 220,\n 220,\n 220,\n 220,\n 220,\n 220,\n 220,\n 12429,\n 46265,\n 22046,\n 11,\n 198,\n 220,\n 220,\n 220,\n 220,\n 220,\n 220,\n 220,\n 220,\n 220,\n 220,\n 220,\n 1267,\n 198,\n 220,\n 220,\n 220,\n 220,\n 220,\n 220,\n 220,\n 2073,\n 25,\n 198,\n 220,\n 220,\n 220,\n 220,\n 220,\n 220,\n 220,\n 220,\n 220,\n 220,\n 220,\n 1441,\n 850,\n 14681,\n 13,\n 9122,\n 62,\n 13345,\n 7,\n 28758,\n 11,\n 7582,\n 28,\n 29149,\n 11,\n 12429,\n 46265,\n 22046,\n 8,\n 198,\n 220,\n 220,\n 220,\n 2845,\n 850,\n 14681,\n 13,\n 34,\n 4262,\n 18709,\n 12331,\n 355,\n 269,\n 431,\n 25,\n 198,\n 220,\n 220,\n 220,\n 220,\n 220,\n 220,\n 220,\n 611,\n 8856,\n 62,\n 18224,\n 25,\n 198,\n 220,\n 220,\n 220,\n 220,\n 220,\n 220,\n 220,\n 220,\n 220,\n 220,\n 220,\n 611,\n 1441,\n 62,\n 22915,\n 25,\n 198,\n 220,\n 220,\n 220,\n 220,\n 220,\n 220,\n 220,\n 220,\n 220,\n 220,\n 220,\n 220,\n 220,\n 220,\n 220,\n 1441,\n 269,\n 431,\n 13,\n 22915,\n 198,\n 220,\n 220,\n 220,\n 220,\n 220,\n 220,\n 220,\n 220,\n 220,\n 220,\n 220,\n 2073,\n 25,\n 198,\n 220,\n 220,\n 220,\n 220,\n 220,\n 220,\n 220,\n 220,\n 220,\n 220,\n 220,\n 220,\n 220,\n 220,\n 220,\n 1441,\n 269,\n 431,\n 13,\n 7783,\n 8189,\n 198,\n 220,\n 220,\n 220,\n 220,\n 220,\n 220,\n 220,\n 2073,\n 25,\n 198,\n 220,\n 220,\n 220,\n 220,\n 220,\n 220,\n 220,\n 220,\n 220,\n 220,\n 220,\n 49706,\n 13,\n 18224,\n 7,\n 69,\n 1,\n 47904,\n 351,\n 2438,\n 1391,\n 66,\n 431,\n 13,\n 7783,\n 8189,\n 92,\n 290,\n 5072,\n 7479,\n 77,\n 90,\n 66,\n 431,\n 13,\n 22915,\n 92,\n 4943,\n 198,\n 220,\n 220,\n 220,\n 220,\n 220,\n 220,\n 220,\n 220,\n 220,\n 220,\n 220,\n 5298,\n 269,\n 431,\n 628,\n 198,\n 4299,\n 2420,\n 62,\n 6738,\n 62,\n 28243,\n 7,\n 28243,\n 62,\n 15908,\n 11,\n 11055,\n 62,\n 34345,\n 11,\n 11055,\n 62,\n 7890,\n 2599,\n 198,\n 220,\n 220,\n 220,\n 37227,\n 198,\n 220,\n 220,\n 220,\n 13610,\n 2420,\n 1912,\n 319,\n 11055,\n 287,\n 3108,\n 11055,\n 62,\n 15908,\n 14,\n 28243,\n 62,\n 34345,\n 198,\n 220,\n 220,\n 220,\n 1058,\n 17143,\n 11055,\n 62,\n 15908,\n 25,\n 4731,\n 11,\n 8619,\n 7268,\n 24019,\n 198,\n 220,\n 220,\n 220,\n 1058,\n 17143,\n 11055,\n 62,\n 34345,\n 25,\n 11055,\n 329,\n 2420,\n 287,\n 474,\n 259,\n 6592,\n 198,\n 220,\n 220,\n 220,\n 1058,\n 17143,\n 11055,\n 62,\n 7890,\n 25,\n 8633,\n 11,\n 1366,\n 329,\n 32097,\n 287,\n 11055,\n 198,\n 220,\n 220,\n 220,\n 1058,\n 7783,\n 25,\n 4731,\n 198,\n 220,\n 220,\n 220,\n 37227,\n 628,\n 220,\n 220,\n 220,\n 611,\n 407,\n 28686,\n 13,\n 6978,\n 13,\n 1069,\n 1023,\n 7,\n 418,\n 13,\n 6978,\n 13,\n 22179,\n 7,\n 28243,\n 62,\n 15908,\n 11,\n 11055,\n 62,\n 34345,\n 8,\n 2599,\n 198,\n 220,\n 220,\n 220,\n 220,\n 220,\n 220,\n 220,\n 5298,\n 9220,\n 3673,\n 21077,\n 12331,\n 7203,\n 15235,\n 284,\n 11055,\n 407,\n 1043,\n 19570,\n 628,\n 220,\n 220,\n 220,\n 11055,\n 62,\n 29356,\n 796,\n 474,\n 259,\n 6592,\n 17,\n 13,\n 8979,\n 11964,\n 17401,\n 7,\n 12947,\n 6978,\n 28,\n 28243,\n 62,\n 15908,\n 8,\n 198,\n 220,\n 220,\n 220,\n 11055,\n 62,\n 24330,\n 796,\n 474,\n 259,\n 6592,\n 17,\n 13,\n 31441,\n 7,\n 29356,\n 28,\n 28243,\n 62,\n 29356,\n 8,\n 198,\n 220,\n 220,\n 220,\n 11055,\n 796,\n 11055,\n 62,\n 24330,\n 13,\n 1136,\n 62,\n 28243,\n 7,\n 28243,\n 62,\n 34345,\n 8,\n 198,\n 220,\n 220,\n 220,\n 5072,\n 62,\n 5239,\n 796,\n 11055,\n 13,\n 13287,\n 7,\n 28243,\n 62,\n 7890,\n 28,\n 28243,\n 62,\n 7890,\n 8,\n 198,\n 220,\n 220,\n 220,\n 49706,\n 13,\n 24442,\n 7203,\n 8206,\n 422,\n 11055,\n 2727,\n 25,\n 4943,\n 198,\n 220,\n 220,\n 220,\n 49706,\n 13,\n 24442,\n 7,\n 22915,\n 62,\n 5239,\n 8,\n 628,\n 220,\n 220,\n 220,\n 1441,\n 5072,\n 62,\n 5239,\n 628,\n 198,\n 4299,\n 4866,\n 62,\n 929,\n 5532,\n 17,\n 2902,\n 5532,\n 7,\n 10677,\n 62,\n 8000,\n 25,\n 10644,\n 11,\n 2244,\n 62,\n 8000,\n 25,\n 10644,\n 2599,\n 198,\n 220,\n 220,\n 220,\n 37227,\n 13379,\n 444,\n 2695,\n 422,\n 28717,\n 29924,\n 284,\n 33218,\n 29924,\n 628,\n 220,\n 220,\n 220,\n 220,\n 6955,\n 444,\n 477,\n 3696,\n 14,\n 15908,\n 82,\n 14,\n 37047,\n 28751,\n 422,\n 28717,\n 2723,\n 284,\n 1233,\n 12,\n 18300,\n 530,\n 416,\n 530,\n 11,\n 198,\n 220,\n 220,\n 220,\n 220,\n 981,\n 10829,\n 2180,\n 611,\n 7160,\n 13,\n 628,\n 220,\n 220,\n 220,\n 220,\n 1058,\n 17143,\n 12351,\n 62,\n 8000,\n 25,\n 3108,\n 284,\n 2723,\n 8619,\n 198,\n 220,\n 220,\n 220,\n 220,\n 1058,\n 17143,\n 2244,\n 62,\n 8000,\n 25,\n 3108,\n 284,\n 10965,\n 8619,\n 198,\n 220,\n 220,\n 220,\n 220,\n 37227,\n 198,\n 220,\n 220,\n 220,\n 329,\n 277,\n 287,\n 12351,\n 62,\n 8000,\n 13,\n 2676,\n 15908,\n 33529,\n 198,\n 220,\n 220,\n 220,\n 220,\n 220,\n 220,\n 220,\n 611,\n 277,\n 13,\n 3672,\n 13,\n 9688,\n 2032,\n 342,\n 7,\n 1911,\n 18300,\n 1,\n 2599,\n 198,\n 220,\n 220,\n 220,\n 220,\n 220,\n 220,\n 220,\n 220,\n 220,\n 220,\n 220,\n 2555,\n 198,\n 220,\n 220,\n 220,\n 220,\n 220,\n 220,\n 220,\n 2244,\n 796,\n 2244,\n 62,\n 8000,\n 1220,\n 277,\n 13,\n 3672,\n 198,\n 220,\n 220,\n 220,\n 220,\n 220,\n 220,\n 220,\n 12351,\n 796,\n 12351,\n 62,\n 8000,\n 1220,\n 277,\n 13,\n 3672,\n 198,\n 220,\n 220,\n 220,\n 220,\n 220,\n 220,\n 220,\n 49706,\n 13,\n 24442,\n 7,\n 69,\n 1,\n 13379,\n 1112,\n 1391,\n 2536,\n 7,\n 10677,\n 38165,\n 284,\n 1391,\n 2536,\n 7,\n 16520,\n 38165,\n 19570,\n 198,\n 220,\n 220,\n 220,\n 220,\n 220,\n 220,\n 220,\n 1303,\n 3274,\n 4781,\n 262,\n 2244,\n 691,\n 611,\n 340,\n 318,\n 407,\n 827,\n 4029,\n 676,\n 13,\n 198,\n 220,\n 220,\n 220,\n 220,\n 220,\n 220,\n 220,\n 611,\n 2244,\n 13,\n 271,\n 62,\n 15908,\n 3419,\n 290,\n 407,\n 2244,\n 13,\n 271,\n 62,\n 1837,\n 4029,\n 676,\n 33529,\n 198,\n 220,\n 220,\n 220,\n 220,\n 220,\n 220,\n 220,\n 220,\n 220,\n 220,\n 220,\n 49706,\n 13,\n 24442,\n 7203,\n 81,\n 16762,\n 631,\n 4064,\n 82,\n 1600,\n 2244,\n 8,\n 198,\n 220,\n 220,\n 220,\n 220,\n 220,\n 220,\n 220,\n 220,\n 220,\n 220,\n 220,\n 4423,\n 346,\n 13,\n 81,\n 16762,\n 631,\n 7,\n 16520,\n 8,\n 198,\n 220,\n 220,\n 220,\n 220,\n 220,\n 220,\n 220,\n 2073,\n 25,\n 198,\n 220,\n 220,\n 220,\n 220,\n 220,\n 220,\n 220,\n 220,\n 220,\n 220,\n 220,\n 611,\n 2244,\n 13,\n 1069,\n 1023,\n 33529,\n 198,\n 220,\n 220,\n 220,\n 220,\n 220,\n 220,\n 220,\n 220,\n 220,\n 220,\n 220,\n 220,\n 220,\n 220,\n 220,\n 2244,\n 13,\n 403,\n 8726,\n 3419,\n 628,\n 220,\n 220,\n 220,\n 220,\n 220,\n 220,\n 220,\n 1303,\n 2735,\n 4866,\n 262,\n 12351,\n 284,\n 2244,\n 198,\n 220,\n 220,\n 220,\n 220,\n 220,\n 220,\n 220,\n 611,\n 12351,\n 13,\n 271,\n 62,\n 1837,\n 4029,\n 676,\n 3419,\n 393,\n 407,\n 12351,\n 13,\n 271,\n 62,\n 15908,\n 33529,\n 198,\n 220,\n 220,\n 220,\n 220,\n 220,\n 220,\n 220,\n 220,\n 220,\n 220,\n 220,\n 49706,\n 13,\n 24442,\n 7203,\n 13155,\n 4064,\n 82,\n 4064,\n 82,\n 1600,\n 12351,\n 11,\n 2244,\n 8,\n 198,\n 220,\n 220,\n 220,\n 220,\n 220,\n 220,\n 220,\n 220,\n 220,\n 220,\n 220,\n 4423,\n 346,\n 13,\n 30073,\n 17,\n 7,\n 10677,\n 11,\n 2244,\n 11,\n 1061,\n 62,\n 37047,\n 28751,\n 28,\n 25101,\n 8,\n 198,\n 220,\n 220,\n 220,\n 220,\n 220,\n 220,\n 220,\n 2073,\n 25,\n 198,\n 220,\n 220,\n 220,\n 220,\n 220,\n 220,\n 220,\n 220,\n 220,\n 220,\n 220,\n 49706,\n 13,\n 24442,\n 7203,\n 13155,\n 532,\n 81,\n 4064,\n 82,\n 4064,\n 82,\n 1600,\n 12351,\n 11,\n 2244,\n 8,\n 198,\n 220,\n 220,\n 220,\n 220,\n 220,\n 220,\n 220,\n 220,\n 220,\n 220,\n 220,\n 4423,\n 346,\n 13,\n 30073,\n 21048,\n 7,\n 10677,\n 11,\n 2244,\n 11,\n 5659,\n 28751,\n 28,\n 17821,\n 8,\n 628,\n 198,\n 4299,\n 3424,\n 62,\n 34945,\n 7,\n 6978,\n 25,\n 10644,\n 2599,\n 198,\n 220,\n 220,\n 220,\n 37227,\n 198,\n 220,\n 220,\n 220,\n 15553,\n 20658,\n 8619,\n 2845,\n 2346,\n 198,\n 220,\n 220,\n 220,\n 1058,\n 17143,\n 3108,\n 25,\n 8619,\n 3108,\n 543,\n 318,\n 20750,\n 198,\n 220,\n 220,\n 220,\n 37227,\n 198,\n 220,\n 220,\n 220,\n 329,\n 288,\n 287,\n 3108,\n 13,\n 2676,\n 15908,\n 33529,\n 198,\n 220,\n 220,\n 220,\n 220,\n 220,\n 220,\n 220,\n 12351,\n 796,\n 3108,\n 1220,\n 288,\n 198,\n 220,\n 220,\n 220,\n 220,\n 220,\n 220,\n 220,\n 611,\n 12351,\n 13,\n 271,\n 62,\n 15908,\n 33529,\n 198,\n 220,\n 220,\n 220,\n 220,\n 220,\n 220,\n 220,\n 220,\n 220,\n 220,\n 220,\n 49706,\n 13,\n 24442,\n 7203,\n 81,\n 16762,\n 631,\n 4064,\n 82,\n 1600,\n 965,\n 7,\n 10677,\n 4008,\n 198,\n 220,\n 220,\n 220,\n 220,\n 220,\n 220,\n 220,\n 220,\n 220,\n 220,\n 220,\n 4423,\n 346,\n 13,\n 81,\n 16762,\n 631,\n 7,\n 10677,\n 8,\n 198,\n 220,\n 220,\n 220,\n 220,\n 220,\n 220,\n 220,\n 2073,\n 25,\n 198,\n 220,\n 220,\n 220,\n 220,\n 220,\n 220,\n 220,\n 220,\n 220,\n 220,\n 220,\n 12351,\n 13,\n 403,\n 8726,\n 3419,\n 628,\n 198,\n 4299,\n 1351,\n 62,\n 15908,\n 62,\n 11299,\n 7,\n 15908,\n 62,\n 3672,\n 25,\n 10644,\n 2599,\n 198,\n 220,\n 220,\n 220,\n 37227,\n 198,\n 220,\n 220,\n 220,\n 44968,\n 477,\n 2695,\n 286,\n 26672,\n 62,\n 3672,\n 198,\n 220,\n 220,\n 220,\n 1058,\n 17143,\n 26672,\n 62,\n 3672,\n 25,\n 27387,\n 329,\n 4478,\n 3696,\n 198,\n 220,\n 220,\n 220,\n 37227,\n 198,\n 220,\n 220,\n 220,\n 49706,\n 13,\n 10951,\n 7203,\n 8567,\n 329,\n 257,\n 2695,\n 287,\n 705,\n 4,\n 82,\n 6,\n 8619,\n 1600,\n 965,\n 7,\n 15908,\n 62,\n 3672,\n 4008,\n 198,\n 220,\n 220,\n 220,\n 329,\n 277,\n 287,\n 26672,\n 62,\n 3672,\n 13,\n 81,\n 4743,\n 672,\n 7203,\n 9,\n 1,\n 2599,\n 198,\n 220,\n 220,\n 220,\n 220,\n 220,\n 220,\n 220,\n 611,\n 965,\n 7,\n 69,\n 737,\n 9688,\n 2032,\n 342,\n 7,\n 1911,\n 18300,\n 1,\n 2599,\n 198,\n 220,\n 220,\n 220,\n 220,\n 220,\n 220,\n 220,\n 220,\n 220,\n 220,\n 220,\n 2555,\n 198,\n 220,\n 220,\n 220,\n 220,\n 220,\n 220,\n 220,\n 49706,\n 13,\n 24442,\n 7,\n 69,\n 1,\n 90,\n 69,\n 13,\n 8000,\n 1220,\n 277,\n 13,\n 3672,\n 92,\n 4943,\n 628,\n 198,\n 198,\n 31,\n 22866,\n 37153,\n 198,\n 4299,\n 269,\n 16993,\n 7,\n 6978,\n 2599,\n 198,\n 220,\n 220,\n 220,\n 37227,\n 198,\n 220,\n 220,\n 220,\n 14645,\n 284,\n 10644,\n 8619,\n 290,\n 1752,\n 2223,\n 318,\n 1760,\n 198,\n 220,\n 220,\n 220,\n 5860,\n 736,\n 198,\n 220,\n 220,\n 220,\n 1058,\n 17143,\n 3108,\n 25,\n 198,\n 220,\n 220,\n 220,\n 1058,\n 7783,\n 25,\n 198,\n 220,\n 220,\n 220,\n 37227,\n 198,\n 220,\n 220,\n 220,\n 8654,\n 62,\n 66,\n 16993,\n 796,\n 10644,\n 13,\n 66,\n 16993,\n 3419,\n 198,\n 220,\n 220,\n 220,\n 28686,\n 13,\n 354,\n 15908,\n 7,\n 6978,\n 8,\n 198,\n 220,\n 220,\n 220,\n 1949,\n 25,\n 198,\n 220,\n 220,\n 220,\n 220,\n 220,\n 220,\n 220,\n 7800,\n 198,\n 220,\n 220,\n 220,\n 3443,\n 25,\n 198,\n 220,\n 220,\n 220,\n 220,\n 220,\n 220,\n 220,\n 28686,\n 13,\n 354,\n 15908,\n 7,\n 47050,\n 62,\n 66,\n 16993,\n 8,\n 198\n]"},"ratio_char_token":{"kind":"number","value":2.603808639108221,"string":"2.603809"},"token_count":{"kind":"number","value":2153,"string":"2,153"}}},{"rowIdx":1279,"cells":{"content":{"kind":"string","value":"# Copyright (c) 2021 PaddlePaddle Authors. All Rights Reserved.\n#\n# Licensed under the Apache License, Version 2.0 (the \"License\");\n# you may not use this file except in compliance with the License.\n# You may obtain a copy of the License at\n#\n# http://www.apache.org/licenses/LICENSE-2.0\n#\n# Unless required by applicable law or agreed to in writing, software\n# distributed under the License is distributed on an \"AS IS\" BASIS,\n# WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.\n# See the License for the specific language governing permissions and\n# limitations under the License.\nimport numpy as np\n\nfrom deepspeech.frontend.utility import IGNORE_ID\nfrom deepspeech.io.utility import pad_sequence\nfrom deepspeech.utils.log import Log\n\n__all__ = [\"SpeechCollator\"]\n\nlogger = Log(__name__).getlog()\n\n"},"input_ids":{"kind":"list like","value":[2,15069,357,66,8,33448,350,37382,47,37382,46665,13,1439,6923,33876,13,198,2,198,2,49962,739,262,24843,13789,11,10628,362,13,15,357,1169,366,34156,15341,198,2,345,743,407,779,428,2393,2845,287,11846,351,262,13789,13,198,2,921,743,7330,257,4866,286,262,13789,379,198,2,198,2,220,220,220,220,2638,1378,2503,13,43073,13,2398,14,677,4541,14,43,2149,24290,12,17,13,15,198,2,198,2,17486,2672,416,9723,1099,393,4987,284,287,3597,11,3788,198,2,9387,739,262,13789,318,9387,319,281,366,1921,3180,1,29809,1797,11,198,2,42881,34764,11015,6375,7102,49828,11053,3963,15529,509,12115,11,2035,4911,393,17142,13,198,2,4091,262,13789,329,262,2176,3303,15030,21627,290,198,2,11247,739,262,13789,13,198,11748,299,32152,355,45941,198,198,6738,2769,45862,13,8534,437,13,315,879,1330,28730,6965,62,2389,198,6738,2769,45862,13,952,13,315,879,1330,14841,62,43167,198,6738,2769,45862,13,26791,13,6404,1330,5972,198,198,834,439,834,796,14631,5248,3055,22667,1352,8973,198,198,6404,1362,796,5972,7,834,3672,834,737,1136,6404,3419,628],"string":"[\n 2,\n 15069,\n 357,\n 66,\n 8,\n 33448,\n 350,\n 37382,\n 47,\n 37382,\n 46665,\n 13,\n 1439,\n 6923,\n 33876,\n 13,\n 198,\n 2,\n 198,\n 2,\n 49962,\n 739,\n 262,\n 24843,\n 13789,\n 11,\n 10628,\n 362,\n 13,\n 15,\n 357,\n 1169,\n 366,\n 34156,\n 15341,\n 198,\n 2,\n 345,\n 743,\n 407,\n 779,\n 428,\n 2393,\n 2845,\n 287,\n 11846,\n 351,\n 262,\n 13789,\n 13,\n 198,\n 2,\n 921,\n 743,\n 7330,\n 257,\n 4866,\n 286,\n 262,\n 13789,\n 379,\n 198,\n 2,\n 198,\n 2,\n 220,\n 220,\n 220,\n 220,\n 2638,\n 1378,\n 2503,\n 13,\n 43073,\n 13,\n 2398,\n 14,\n 677,\n 4541,\n 14,\n 43,\n 2149,\n 24290,\n 12,\n 17,\n 13,\n 15,\n 198,\n 2,\n 198,\n 2,\n 17486,\n 2672,\n 416,\n 9723,\n 1099,\n 393,\n 4987,\n 284,\n 287,\n 3597,\n 11,\n 3788,\n 198,\n 2,\n 9387,\n 739,\n 262,\n 13789,\n 318,\n 9387,\n 319,\n 281,\n 366,\n 1921,\n 3180,\n 1,\n 29809,\n 1797,\n 11,\n 198,\n 2,\n 42881,\n 34764,\n 11015,\n 6375,\n 7102,\n 49828,\n 11053,\n 3963,\n 15529,\n 509,\n 12115,\n 11,\n 2035,\n 4911,\n 393,\n 17142,\n 13,\n 198,\n 2,\n 4091,\n 262,\n 13789,\n 329,\n 262,\n 2176,\n 3303,\n 15030,\n 21627,\n 290,\n 198,\n 2,\n 11247,\n 739,\n 262,\n 13789,\n 13,\n 198,\n 11748,\n 299,\n 32152,\n 355,\n 45941,\n 198,\n 198,\n 6738,\n 2769,\n 45862,\n 13,\n 8534,\n 437,\n 13,\n 315,\n 879,\n 1330,\n 28730,\n 6965,\n 62,\n 2389,\n 198,\n 6738,\n 2769,\n 45862,\n 13,\n 952,\n 13,\n 315,\n 879,\n 1330,\n 14841,\n 62,\n 43167,\n 198,\n 6738,\n 2769,\n 45862,\n 13,\n 26791,\n 13,\n 6404,\n 1330,\n 5972,\n 198,\n 198,\n 834,\n 439,\n 834,\n 796,\n 14631,\n 5248,\n 3055,\n 22667,\n 1352,\n 8973,\n 198,\n 198,\n 6404,\n 1362,\n 796,\n 5972,\n 7,\n 834,\n 3672,\n 834,\n 737,\n 1136,\n 6404,\n 3419,\n 628\n]"},"ratio_char_token":{"kind":"number","value":3.6,"string":"3.6"},"token_count":{"kind":"number","value":230,"string":"230"}}},{"rowIdx":1280,"cells":{"content":{"kind":"string","value":"# -*-python-*-\n#\n# Copyright (C) 1999-2018 The ViewCVS Group. All Rights Reserved.\n#\n# By using this file, you agree to the terms and conditions set forth in\n# the LICENSE.html file which can be found at the top level of the ViewVC\n# distribution or at http://viewvc.org/license-1.html.\n#\n# For more information, visit http://viewvc.org/\n#\n# -----------------------------------------------------------------------\n\n\"Version Control lib driver for remotely accessible Subversion repositories.\"\n\nimport vclib\nimport sys\nimport os\nimport re\nimport tempfile\nimport time\nimport urllib\nfrom svn_repos import Revision, SVNChangedPath, _datestr_to_date, \\\n _compare_paths, _path_parts, _cleanup_path, \\\n _rev2optrev, _fix_subversion_exception, \\\n _split_revprops, _canonicalize_path\nfrom svn import core, delta, client, wc, ra\n\n\n### Require Subversion 1.3.1 or better. (for svn_ra_get_locations support)\nif (core.SVN_VER_MAJOR, core.SVN_VER_MINOR, core.SVN_VER_PATCH) < (1, 3, 1):\n raise Exception, \"Version requirement not met (needs 1.3.1 or better)\"\n\n\n### BEGIN COMPATABILITY CODE ###\n\ntry:\n SVN_INVALID_REVNUM = core.SVN_INVALID_REVNUM\nexcept AttributeError: # The 1.4.x bindings are missing core.SVN_INVALID_REVNUM\n SVN_INVALID_REVNUM = -1\n\n\n### END COMPATABILITY CODE ###\n\n \ndef cat_to_tempfile(svnrepos, path, rev):\n \"\"\"Check out file revision to temporary file\"\"\"\n temp = tempfile.mktemp()\n stream = core.svn_stream_from_aprfile(temp)\n url = svnrepos._geturl(path)\n client.svn_client_cat(core.Stream(stream), url, _rev2optrev(rev),\n svnrepos.ctx)\n core.svn_stream_close(stream)\n return temp\n\n\n"},"input_ids":{"kind":"list like","value":[2,532,9,12,29412,12,9,12,198,2,198,2,15069,357,34,8,7358,12,7908,383,3582,34,20304,4912,13,1439,6923,33876,13,198,2,198,2,2750,1262,428,2393,11,345,4236,284,262,2846,290,3403,900,6071,287,198,2,262,38559,24290,13,6494,2393,543,460,307,1043,379,262,1353,1241,286,262,3582,15922,198,2,6082,393,379,2638,1378,1177,28435,13,2398,14,43085,12,16,13,6494,13,198,2,198,2,1114,517,1321,11,3187,2638,1378,1177,28435,13,2398,14,198,2,198,2,16529,26866,198,198,1,14815,6779,9195,4639,329,19863,9857,3834,9641,38072,526,198,198,11748,410,565,571,198,11748,25064,198,11748,28686,198,11748,302,198,11748,20218,7753,198,11748,640,198,11748,2956,297,571,198,6738,38487,77,62,260,1930,1330,46604,11,20546,45,31813,15235,11,4808,19608,395,81,62,1462,62,4475,11,3467,198,220,220,220,220,220,220,220,220,220,220,220,220,220,220,220,220,220,220,220,220,220,4808,5589,533,62,6978,82,11,4808,6978,62,42632,11,4808,27773,929,62,6978,11,3467,198,220,220,220,220,220,220,220,220,220,220,220,220,220,220,220,220,220,220,220,220,220,4808,18218,17,8738,18218,11,4808,13049,62,7266,9641,62,1069,4516,11,3467,198,220,220,220,220,220,220,220,220,220,220,220,220,220,220,220,220,220,220,220,220,220,4808,35312,62,18218,1676,862,11,4808,49883,605,1096,62,6978,198,6738,38487,77,1330,4755,11,25979,11,5456,11,266,66,11,2179,628,198,21017,9394,557,3834,9641,352,13,18,13,16,393,1365,13,357,1640,38487,77,62,430,62,1136,62,17946,602,1104,8,198,361,357,7295,13,50,53,45,62,5959,62,5673,41,1581,11,4755,13,50,53,45,62,5959,62,23678,1581,11,4755,13,50,53,45,62,5959,62,47,11417,8,1279,357,16,11,513,11,352,2599,198,220,5298,35528,11,366,14815,9079,407,1138,357,50032,352,13,18,13,16,393,1365,16725,628,198,21017,347,43312,24301,13563,25382,42714,44386,198,198,28311,25,198,220,20546,45,62,1268,23428,2389,62,2200,53,41359,796,4755,13,50,53,45,62,1268,23428,2389,62,2200,53,41359,198,16341,3460,4163,12331,25,1303,383,352,13,19,13,87,34111,389,4814,4755,13,50,53,45,62,1268,23428,2389,62,2200,53,41359,198,220,20546,45,62,1268,23428,2389,62,2200,53,41359,796,532,16,628,198,21017,23578,24301,13563,25382,42714,44386,628,220,220,220,220,198,4299,3797,62,1462,62,29510,7753,7,21370,77,260,1930,11,3108,11,2710,2599,198,220,37227,9787,503,2393,18440,284,8584,2393,37811,198,220,20218,796,20218,7753,13,28015,29510,3419,198,220,4269,796,4755,13,21370,77,62,5532,62,6738,62,499,81,7753,7,29510,8,198,220,19016,796,38487,77,260,1930,13557,1136,6371,7,6978,8,198,220,5456,13,21370,77,62,16366,62,9246,7,7295,13,12124,7,5532,828,19016,11,4808,18218,17,8738,18218,7,18218,828,198,220,220,220,220,220,220,220,220,220,220,220,220,220,220,220,220,220,220,220,220,220,220,220,38487,77,260,1930,13,49464,8,198,220,4755,13,21370,77,62,5532,62,19836,7,5532,8,198,220,1441,20218,628,198],"string":"[\n 2,\n 532,\n 9,\n 12,\n 29412,\n 12,\n 9,\n 12,\n 198,\n 2,\n 198,\n 2,\n 15069,\n 357,\n 34,\n 8,\n 7358,\n 12,\n 7908,\n 383,\n 3582,\n 34,\n 20304,\n 4912,\n 13,\n 1439,\n 6923,\n 33876,\n 13,\n 198,\n 2,\n 198,\n 2,\n 2750,\n 1262,\n 428,\n 2393,\n 11,\n 345,\n 4236,\n 284,\n 262,\n 2846,\n 290,\n 3403,\n 900,\n 6071,\n 287,\n 198,\n 2,\n 262,\n 38559,\n 24290,\n 13,\n 6494,\n 2393,\n 543,\n 460,\n 307,\n 1043,\n 379,\n 262,\n 1353,\n 1241,\n 286,\n 262,\n 3582,\n 15922,\n 198,\n 2,\n 6082,\n 393,\n 379,\n 2638,\n 1378,\n 1177,\n 28435,\n 13,\n 2398,\n 14,\n 43085,\n 12,\n 16,\n 13,\n 6494,\n 13,\n 198,\n 2,\n 198,\n 2,\n 1114,\n 517,\n 1321,\n 11,\n 3187,\n 2638,\n 1378,\n 1177,\n 28435,\n 13,\n 2398,\n 14,\n 198,\n 2,\n 198,\n 2,\n 16529,\n 26866,\n 198,\n 198,\n 1,\n 14815,\n 6779,\n 9195,\n 4639,\n 329,\n 19863,\n 9857,\n 3834,\n 9641,\n 38072,\n 526,\n 198,\n 198,\n 11748,\n 410,\n 565,\n 571,\n 198,\n 11748,\n 25064,\n 198,\n 11748,\n 28686,\n 198,\n 11748,\n 302,\n 198,\n 11748,\n 20218,\n 7753,\n 198,\n 11748,\n 640,\n 198,\n 11748,\n 2956,\n 297,\n 571,\n 198,\n 6738,\n 38487,\n 77,\n 62,\n 260,\n 1930,\n 1330,\n 46604,\n 11,\n 20546,\n 45,\n 31813,\n 15235,\n 11,\n 4808,\n 19608,\n 395,\n 81,\n 62,\n 1462,\n 62,\n 4475,\n 11,\n 3467,\n 198,\n 220,\n 220,\n 220,\n 220,\n 220,\n 220,\n 220,\n 220,\n 220,\n 220,\n 220,\n 220,\n 220,\n 220,\n 220,\n 220,\n 220,\n 220,\n 220,\n 220,\n 220,\n 4808,\n 5589,\n 533,\n 62,\n 6978,\n 82,\n 11,\n 4808,\n 6978,\n 62,\n 42632,\n 11,\n 4808,\n 27773,\n 929,\n 62,\n 6978,\n 11,\n 3467,\n 198,\n 220,\n 220,\n 220,\n 220,\n 220,\n 220,\n 220,\n 220,\n 220,\n 220,\n 220,\n 220,\n 220,\n 220,\n 220,\n 220,\n 220,\n 220,\n 220,\n 220,\n 220,\n 4808,\n 18218,\n 17,\n 8738,\n 18218,\n 11,\n 4808,\n 13049,\n 62,\n 7266,\n 9641,\n 62,\n 1069,\n 4516,\n 11,\n 3467,\n 198,\n 220,\n 220,\n 220,\n 220,\n 220,\n 220,\n 220,\n 220,\n 220,\n 220,\n 220,\n 220,\n 220,\n 220,\n 220,\n 220,\n 220,\n 220,\n 220,\n 220,\n 220,\n 4808,\n 35312,\n 62,\n 18218,\n 1676,\n 862,\n 11,\n 4808,\n 49883,\n 605,\n 1096,\n 62,\n 6978,\n 198,\n 6738,\n 38487,\n 77,\n 1330,\n 4755,\n 11,\n 25979,\n 11,\n 5456,\n 11,\n 266,\n 66,\n 11,\n 2179,\n 628,\n 198,\n 21017,\n 9394,\n 557,\n 3834,\n 9641,\n 352,\n 13,\n 18,\n 13,\n 16,\n 393,\n 1365,\n 13,\n 357,\n 1640,\n 38487,\n 77,\n 62,\n 430,\n 62,\n 1136,\n 62,\n 17946,\n 602,\n 1104,\n 8,\n 198,\n 361,\n 357,\n 7295,\n 13,\n 50,\n 53,\n 45,\n 62,\n 5959,\n 62,\n 5673,\n 41,\n 1581,\n 11,\n 4755,\n 13,\n 50,\n 53,\n 45,\n 62,\n 5959,\n 62,\n 23678,\n 1581,\n 11,\n 4755,\n 13,\n 50,\n 53,\n 45,\n 62,\n 5959,\n 62,\n 47,\n 11417,\n 8,\n 1279,\n 357,\n 16,\n 11,\n 513,\n 11,\n 352,\n 2599,\n 198,\n 220,\n 5298,\n 35528,\n 11,\n 366,\n 14815,\n 9079,\n 407,\n 1138,\n 357,\n 50032,\n 352,\n 13,\n 18,\n 13,\n 16,\n 393,\n 1365,\n 16725,\n 628,\n 198,\n 21017,\n 347,\n 43312,\n 24301,\n 13563,\n 25382,\n 42714,\n 44386,\n 198,\n 198,\n 28311,\n 25,\n 198,\n 220,\n 20546,\n 45,\n 62,\n 1268,\n 23428,\n 2389,\n 62,\n 2200,\n 53,\n 41359,\n 796,\n 4755,\n 13,\n 50,\n 53,\n 45,\n 62,\n 1268,\n 23428,\n 2389,\n 62,\n 2200,\n 53,\n 41359,\n 198,\n 16341,\n 3460,\n 4163,\n 12331,\n 25,\n 1303,\n 383,\n 352,\n 13,\n 19,\n 13,\n 87,\n 34111,\n 389,\n 4814,\n 4755,\n 13,\n 50,\n 53,\n 45,\n 62,\n 1268,\n 23428,\n 2389,\n 62,\n 2200,\n 53,\n 41359,\n 198,\n 220,\n 20546,\n 45,\n 62,\n 1268,\n 23428,\n 2389,\n 62,\n 2200,\n 53,\n 41359,\n 796,\n 532,\n 16,\n 628,\n 198,\n 21017,\n 23578,\n 24301,\n 13563,\n 25382,\n 42714,\n 44386,\n 628,\n 220,\n 220,\n 220,\n 220,\n 198,\n 4299,\n 3797,\n 62,\n 1462,\n 62,\n 29510,\n 7753,\n 7,\n 21370,\n 77,\n 260,\n 1930,\n 11,\n 3108,\n 11,\n 2710,\n 2599,\n 198,\n 220,\n 37227,\n 9787,\n 503,\n 2393,\n 18440,\n 284,\n 8584,\n 2393,\n 37811,\n 198,\n 220,\n 20218,\n 796,\n 20218,\n 7753,\n 13,\n 28015,\n 29510,\n 3419,\n 198,\n 220,\n 4269,\n 796,\n 4755,\n 13,\n 21370,\n 77,\n 62,\n 5532,\n 62,\n 6738,\n 62,\n 499,\n 81,\n 7753,\n 7,\n 29510,\n 8,\n 198,\n 220,\n 19016,\n 796,\n 38487,\n 77,\n 260,\n 1930,\n 13557,\n 1136,\n 6371,\n 7,\n 6978,\n 8,\n 198,\n 220,\n 5456,\n 13,\n 21370,\n 77,\n 62,\n 16366,\n 62,\n 9246,\n 7,\n 7295,\n 13,\n 12124,\n 7,\n 5532,\n 828,\n 19016,\n 11,\n 4808,\n 18218,\n 17,\n 8738,\n 18218,\n 7,\n 18218,\n 828,\n 198,\n 220,\n 220,\n 220,\n 220,\n 220,\n 220,\n 220,\n 220,\n 220,\n 220,\n 220,\n 220,\n 220,\n 220,\n 220,\n 220,\n 220,\n 220,\n 220,\n 220,\n 220,\n 220,\n 220,\n 38487,\n 77,\n 260,\n 1930,\n 13,\n 49464,\n 8,\n 198,\n 220,\n 4755,\n 13,\n 21370,\n 77,\n 62,\n 5532,\n 62,\n 19836,\n 7,\n 5532,\n 8,\n 198,\n 220,\n 1441,\n 20218,\n 628,\n 198\n]"},"ratio_char_token":{"kind":"number","value":2.631415241057543,"string":"2.631415"},"token_count":{"kind":"number","value":643,"string":"643"}}},{"rowIdx":1281,"cells":{"content":{"kind":"string","value":"#!/usr/bin/env python3\n# -*- coding: utf-8 -*-\n\n\nimport io\nimport pathlib\nimport sys\nimport tempfile\nfrom multiprocessing import Pool, cpu_count\n\nimport PyPDF2 as PyPDF2\nimport click\nimport pdfminer.pdftypes as pdftypes\nimport pdfminer.settings\nfrom fpdf import FPDF\nfrom pdfminer.converter import TextConverter\nfrom pdfminer.layout import LAParams, LTAnno, LTContainer, LTText, LTTextBox\nfrom pdfminer.pdfdocument import PDFDocument, PDFNoOutlines\nfrom pdfminer.pdfinterp import PDFPageInterpreter, PDFResourceManager\nfrom pdfminer.pdfpage import PDFPage\nfrom pdfminer.pdfparser import PDFParser\nfrom pdfminer.psparser import PSLiteral, PSLiteralTable\nfrom tqdm import tqdm\n\npdfminer.settings.STRICT = False\n\nSUBSTITUTIONS = {\n u'ff': 'ff',\n u'fi': 'fi',\n u'fl': 'fl',\n u'’': \"'\",\n}\n\nANNOT_SUBTYPES = set(['Text', 'Highlight', 'Squiggly', 'StrikeOut', 'Underline'])\n\nDEBUG_BOXHIT = False\n\nOUTDIR = \"\"\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n@click.command()\n@click.option('--outdir', default=\"\", help='Specify output directory')\n@click.argument('files', nargs=-1)\n\n\nif __name__ == \"__main__\":\n main()\n"},"input_ids":{"kind":"list like","value":[2,48443,14629,14,8800,14,24330,21015,18,198,2,532,9,12,19617,25,3384,69,12,23,532,9,12,628,198,11748,33245,198,11748,3108,8019,198,11748,25064,198,11748,20218,7753,198,6738,18540,305,919,278,1330,19850,11,42804,62,9127,198,198,11748,9485,20456,17,355,9485,20456,17,198,11748,3904,198,11748,37124,1084,263,13,30094,701,9497,355,279,67,701,9497,198,11748,37124,1084,263,13,33692,198,6738,277,12315,1330,376,20456,198,6738,37124,1084,263,13,1102,332,353,1330,8255,3103,332,353,198,6738,37124,1084,263,13,39786,1330,406,2969,283,4105,11,34146,2025,3919,11,34146,29869,11,34146,8206,11,34146,8206,14253,198,6738,37124,1084,263,13,12315,22897,1330,12960,24941,11,12960,2949,7975,6615,198,6738,37124,1084,263,13,12315,3849,79,1330,14340,5837,496,9492,3866,353,11,12960,26198,13511,198,6738,37124,1084,263,13,12315,7700,1330,14340,5837,496,198,6738,37124,1084,263,13,12315,48610,1330,14340,5837,28198,198,6738,37124,1084,263,13,862,48610,1330,6599,43,270,1691,11,6599,43,270,1691,10962,198,6738,256,80,36020,1330,256,80,36020,198,198,12315,1084,263,13,33692,13,18601,18379,796,10352,198,198,50,10526,2257,2043,3843,11053,796,1391,198,220,220,220,334,6,171,105,222,10354,705,487,3256,198,220,220,220,334,6,171,105,223,10354,705,12463,3256,198,220,220,220,334,6,171,105,224,10354,705,2704,3256,198,220,220,220,334,6,447,247,10354,24018,1600,198,92,198,198,1565,11929,62,50,10526,9936,47,1546,796,900,7,17816,8206,3256,705,11922,2971,3256,705,22266,6950,306,3256,705,31584,7975,3256,705,9203,1370,6,12962,198,198,30531,62,39758,39,2043,796,10352,198,198,12425,34720,796,13538,628,628,628,628,628,628,628,628,198,31,12976,13,21812,3419,198,31,12976,13,18076,10786,438,448,15908,3256,4277,2625,1600,1037,11639,22882,1958,5072,8619,11537,198,31,12976,13,49140,10786,16624,3256,299,22046,10779,16,8,628,198,361,11593,3672,834,6624,366,834,12417,834,1298,198,220,220,220,1388,3419,198],"string":"[\n 2,\n 48443,\n 14629,\n 14,\n 8800,\n 14,\n 24330,\n 21015,\n 18,\n 198,\n 2,\n 532,\n 9,\n 12,\n 19617,\n 25,\n 3384,\n 69,\n 12,\n 23,\n 532,\n 9,\n 12,\n 628,\n 198,\n 11748,\n 33245,\n 198,\n 11748,\n 3108,\n 8019,\n 198,\n 11748,\n 25064,\n 198,\n 11748,\n 20218,\n 7753,\n 198,\n 6738,\n 18540,\n 305,\n 919,\n 278,\n 1330,\n 19850,\n 11,\n 42804,\n 62,\n 9127,\n 198,\n 198,\n 11748,\n 9485,\n 20456,\n 17,\n 355,\n 9485,\n 20456,\n 17,\n 198,\n 11748,\n 3904,\n 198,\n 11748,\n 37124,\n 1084,\n 263,\n 13,\n 30094,\n 701,\n 9497,\n 355,\n 279,\n 67,\n 701,\n 9497,\n 198,\n 11748,\n 37124,\n 1084,\n 263,\n 13,\n 33692,\n 198,\n 6738,\n 277,\n 12315,\n 1330,\n 376,\n 20456,\n 198,\n 6738,\n 37124,\n 1084,\n 263,\n 13,\n 1102,\n 332,\n 353,\n 1330,\n 8255,\n 3103,\n 332,\n 353,\n 198,\n 6738,\n 37124,\n 1084,\n 263,\n 13,\n 39786,\n 1330,\n 406,\n 2969,\n 283,\n 4105,\n 11,\n 34146,\n 2025,\n 3919,\n 11,\n 34146,\n 29869,\n 11,\n 34146,\n 8206,\n 11,\n 34146,\n 8206,\n 14253,\n 198,\n 6738,\n 37124,\n 1084,\n 263,\n 13,\n 12315,\n 22897,\n 1330,\n 12960,\n 24941,\n 11,\n 12960,\n 2949,\n 7975,\n 6615,\n 198,\n 6738,\n 37124,\n 1084,\n 263,\n 13,\n 12315,\n 3849,\n 79,\n 1330,\n 14340,\n 5837,\n 496,\n 9492,\n 3866,\n 353,\n 11,\n 12960,\n 26198,\n 13511,\n 198,\n 6738,\n 37124,\n 1084,\n 263,\n 13,\n 12315,\n 7700,\n 1330,\n 14340,\n 5837,\n 496,\n 198,\n 6738,\n 37124,\n 1084,\n 263,\n 13,\n 12315,\n 48610,\n 1330,\n 14340,\n 5837,\n 28198,\n 198,\n 6738,\n 37124,\n 1084,\n 263,\n 13,\n 862,\n 48610,\n 1330,\n 6599,\n 43,\n 270,\n 1691,\n 11,\n 6599,\n 43,\n 270,\n 1691,\n 10962,\n 198,\n 6738,\n 256,\n 80,\n 36020,\n 1330,\n 256,\n 80,\n 36020,\n 198,\n 198,\n 12315,\n 1084,\n 263,\n 13,\n 33692,\n 13,\n 18601,\n 18379,\n 796,\n 10352,\n 198,\n 198,\n 50,\n 10526,\n 2257,\n 2043,\n 3843,\n 11053,\n 796,\n 1391,\n 198,\n 220,\n 220,\n 220,\n 334,\n 6,\n 171,\n 105,\n 222,\n 10354,\n 705,\n 487,\n 3256,\n 198,\n 220,\n 220,\n 220,\n 334,\n 6,\n 171,\n 105,\n 223,\n 10354,\n 705,\n 12463,\n 3256,\n 198,\n 220,\n 220,\n 220,\n 334,\n 6,\n 171,\n 105,\n 224,\n 10354,\n 705,\n 2704,\n 3256,\n 198,\n 220,\n 220,\n 220,\n 334,\n 6,\n 447,\n 247,\n 10354,\n 24018,\n 1600,\n 198,\n 92,\n 198,\n 198,\n 1565,\n 11929,\n 62,\n 50,\n 10526,\n 9936,\n 47,\n 1546,\n 796,\n 900,\n 7,\n 17816,\n 8206,\n 3256,\n 705,\n 11922,\n 2971,\n 3256,\n 705,\n 22266,\n 6950,\n 306,\n 3256,\n 705,\n 31584,\n 7975,\n 3256,\n 705,\n 9203,\n 1370,\n 6,\n 12962,\n 198,\n 198,\n 30531,\n 62,\n 39758,\n 39,\n 2043,\n 796,\n 10352,\n 198,\n 198,\n 12425,\n 34720,\n 796,\n 13538,\n 628,\n 628,\n 628,\n 628,\n 628,\n 628,\n 628,\n 628,\n 198,\n 31,\n 12976,\n 13,\n 21812,\n 3419,\n 198,\n 31,\n 12976,\n 13,\n 18076,\n 10786,\n 438,\n 448,\n 15908,\n 3256,\n 4277,\n 2625,\n 1600,\n 1037,\n 11639,\n 22882,\n 1958,\n 5072,\n 8619,\n 11537,\n 198,\n 31,\n 12976,\n 13,\n 49140,\n 10786,\n 16624,\n 3256,\n 299,\n 22046,\n 10779,\n 16,\n 8,\n 628,\n 198,\n 361,\n 11593,\n 3672,\n 834,\n 6624,\n 366,\n 834,\n 12417,\n 834,\n 1298,\n 198,\n 220,\n 220,\n 220,\n 1388,\n 3419,\n 198\n]"},"ratio_char_token":{"kind":"number","value":2.6715686274509802,"string":"2.671569"},"token_count":{"kind":"number","value":408,"string":"408"}}},{"rowIdx":1282,"cells":{"content":{"kind":"string","value":"import torch\n\ndef heatmap_focal_loss(preds, gt_heatmap, alpha, gamma, eps=1e-3):\n \"\"\"\n Params:\n preds: Tensor[num_classes, height, width]\n gt_heatmap: Tensor[num_classes, height, width]\n alpha:\n gamma: how much you want to reduce penalty around the ground truth locations\n eps: add small number to prevent inf error\n Returns:\n loss: Tensor[]\n \"\"\"\n # See CornerNet paper for detail https://arxiv.org/abs/1808.01244\n loss = -torch.where(\n gt_heatmap == 1,\n (1 - preds)**alpha * torch.log(preds + eps), # Loss for positive locations\n (1 - gt_heatmap) ** gamma * (preds)**alpha * torch.log(1 - preds - eps) # loss for negative locations\n ).sum()\n return loss\n\ndef dice_loss(inputs, targets, smooth=1.0):\n \"\"\"\n Params:\n inputs: arbitrary size of Tensor\n targets: arbitrary size of Tensor\n smooth: smoothing factor\n Returns:\n loss: Tensor[]\n \"\"\"\n inputs = inputs.view(-1)\n targets = targets.view(-1)\n\n # Squred denominator version of Dice loss\n dice = (2 * (inputs*targets).sum() + smooth) / ((inputs**2).sum() + (targets**2).sum() + smooth)\n\n return 1 - dice\n"},"input_ids":{"kind":"list like","value":[11748,28034,198,198,4299,4894,8899,62,69,4374,62,22462,7,28764,82,11,308,83,62,25080,8899,11,17130,11,34236,11,304,862,28,16,68,12,18,2599,198,220,220,220,37227,198,220,220,220,2547,4105,25,198,220,220,220,220,220,220,220,2747,82,25,309,22854,58,22510,62,37724,11,6001,11,9647,60,198,220,220,220,220,220,220,220,308,83,62,25080,8899,25,309,22854,58,22510,62,37724,11,6001,11,9647,60,198,220,220,220,220,220,220,220,17130,25,198,220,220,220,220,220,220,220,34236,25,703,881,345,765,284,4646,7389,1088,262,2323,3872,7064,198,220,220,220,220,220,220,220,304,862,25,751,1402,1271,284,2948,1167,4049,198,220,220,220,16409,25,198,220,220,220,220,220,220,220,2994,25,309,22854,21737,198,220,220,220,37227,198,220,220,220,1303,4091,26212,7934,3348,329,3703,3740,1378,283,87,452,13,2398,14,8937,14,1507,2919,13,486,25707,198,220,220,220,2994,796,532,13165,354,13,3003,7,198,220,220,220,220,220,220,220,308,83,62,25080,8899,6624,352,11,198,220,220,220,220,220,220,220,357,16,532,2747,82,8,1174,26591,1635,28034,13,6404,7,28764,82,1343,304,862,828,1303,22014,329,3967,7064,198,220,220,220,220,220,220,220,357,16,532,308,83,62,25080,8899,8,12429,34236,1635,357,28764,82,8,1174,26591,1635,28034,13,6404,7,16,532,2747,82,532,304,862,8,1303,2994,329,4633,7064,198,220,220,220,6739,16345,3419,198,220,220,220,1441,2994,198,198,4299,17963,62,22462,7,15414,82,11,6670,11,7209,28,16,13,15,2599,198,220,220,220,37227,198,220,220,220,2547,4105,25,198,220,220,220,220,220,220,220,17311,25,14977,2546,286,309,22854,198,220,220,220,220,220,220,220,6670,25,14977,2546,286,309,22854,198,220,220,220,220,220,220,220,7209,25,32746,722,5766,198,220,220,220,16409,25,198,220,220,220,220,220,220,220,2994,25,309,22854,21737,198,220,220,220,37227,198,220,220,220,17311,796,17311,13,1177,32590,16,8,198,220,220,220,6670,796,6670,13,1177,32590,16,8,628,220,220,220,1303,5056,445,31457,1352,2196,286,34381,2994,198,220,220,220,17963,796,357,17,1635,357,15414,82,9,83,853,1039,737,16345,3419,1343,7209,8,1220,14808,15414,82,1174,17,737,16345,3419,1343,357,83,853,1039,1174,17,737,16345,3419,1343,7209,8,628,220,220,220,1441,352,532,17963,198],"string":"[\n 11748,\n 28034,\n 198,\n 198,\n 4299,\n 4894,\n 8899,\n 62,\n 69,\n 4374,\n 62,\n 22462,\n 7,\n 28764,\n 82,\n 11,\n 308,\n 83,\n 62,\n 25080,\n 8899,\n 11,\n 17130,\n 11,\n 34236,\n 11,\n 304,\n 862,\n 28,\n 16,\n 68,\n 12,\n 18,\n 2599,\n 198,\n 220,\n 220,\n 220,\n 37227,\n 198,\n 220,\n 220,\n 220,\n 2547,\n 4105,\n 25,\n 198,\n 220,\n 220,\n 220,\n 220,\n 220,\n 220,\n 220,\n 2747,\n 82,\n 25,\n 309,\n 22854,\n 58,\n 22510,\n 62,\n 37724,\n 11,\n 6001,\n 11,\n 9647,\n 60,\n 198,\n 220,\n 220,\n 220,\n 220,\n 220,\n 220,\n 220,\n 308,\n 83,\n 62,\n 25080,\n 8899,\n 25,\n 309,\n 22854,\n 58,\n 22510,\n 62,\n 37724,\n 11,\n 6001,\n 11,\n 9647,\n 60,\n 198,\n 220,\n 220,\n 220,\n 220,\n 220,\n 220,\n 220,\n 17130,\n 25,\n 198,\n 220,\n 220,\n 220,\n 220,\n 220,\n 220,\n 220,\n 34236,\n 25,\n 703,\n 881,\n 345,\n 765,\n 284,\n 4646,\n 7389,\n 1088,\n 262,\n 2323,\n 3872,\n 7064,\n 198,\n 220,\n 220,\n 220,\n 220,\n 220,\n 220,\n 220,\n 304,\n 862,\n 25,\n 751,\n 1402,\n 1271,\n 284,\n 2948,\n 1167,\n 4049,\n 198,\n 220,\n 220,\n 220,\n 16409,\n 25,\n 198,\n 220,\n 220,\n 220,\n 220,\n 220,\n 220,\n 220,\n 2994,\n 25,\n 309,\n 22854,\n 21737,\n 198,\n 220,\n 220,\n 220,\n 37227,\n 198,\n 220,\n 220,\n 220,\n 1303,\n 4091,\n 26212,\n 7934,\n 3348,\n 329,\n 3703,\n 3740,\n 1378,\n 283,\n 87,\n 452,\n 13,\n 2398,\n 14,\n 8937,\n 14,\n 1507,\n 2919,\n 13,\n 486,\n 25707,\n 198,\n 220,\n 220,\n 220,\n 2994,\n 796,\n 532,\n 13165,\n 354,\n 13,\n 3003,\n 7,\n 198,\n 220,\n 220,\n 220,\n 220,\n 220,\n 220,\n 220,\n 308,\n 83,\n 62,\n 25080,\n 8899,\n 6624,\n 352,\n 11,\n 198,\n 220,\n 220,\n 220,\n 220,\n 220,\n 220,\n 220,\n 357,\n 16,\n 532,\n 2747,\n 82,\n 8,\n 1174,\n 26591,\n 1635,\n 28034,\n 13,\n 6404,\n 7,\n 28764,\n 82,\n 1343,\n 304,\n 862,\n 828,\n 1303,\n 22014,\n 329,\n 3967,\n 7064,\n 198,\n 220,\n 220,\n 220,\n 220,\n 220,\n 220,\n 220,\n 357,\n 16,\n 532,\n 308,\n 83,\n 62,\n 25080,\n 8899,\n 8,\n 12429,\n 34236,\n 1635,\n 357,\n 28764,\n 82,\n 8,\n 1174,\n 26591,\n 1635,\n 28034,\n 13,\n 6404,\n 7,\n 16,\n 532,\n 2747,\n 82,\n 532,\n 304,\n 862,\n 8,\n 1303,\n 2994,\n 329,\n 4633,\n 7064,\n 198,\n 220,\n 220,\n 220,\n 6739,\n 16345,\n 3419,\n 198,\n 220,\n 220,\n 220,\n 1441,\n 2994,\n 198,\n 198,\n 4299,\n 17963,\n 62,\n 22462,\n 7,\n 15414,\n 82,\n 11,\n 6670,\n 11,\n 7209,\n 28,\n 16,\n 13,\n 15,\n 2599,\n 198,\n 220,\n 220,\n 220,\n 37227,\n 198,\n 220,\n 220,\n 220,\n 2547,\n 4105,\n 25,\n 198,\n 220,\n 220,\n 220,\n 220,\n 220,\n 220,\n 220,\n 17311,\n 25,\n 14977,\n 2546,\n 286,\n 309,\n 22854,\n 198,\n 220,\n 220,\n 220,\n 220,\n 220,\n 220,\n 220,\n 6670,\n 25,\n 14977,\n 2546,\n 286,\n 309,\n 22854,\n 198,\n 220,\n 220,\n 220,\n 220,\n 220,\n 220,\n 220,\n 7209,\n 25,\n 32746,\n 722,\n 5766,\n 198,\n 220,\n 220,\n 220,\n 16409,\n 25,\n 198,\n 220,\n 220,\n 220,\n 220,\n 220,\n 220,\n 220,\n 2994,\n 25,\n 309,\n 22854,\n 21737,\n 198,\n 220,\n 220,\n 220,\n 37227,\n 198,\n 220,\n 220,\n 220,\n 17311,\n 796,\n 17311,\n 13,\n 1177,\n 32590,\n 16,\n 8,\n 198,\n 220,\n 220,\n 220,\n 6670,\n 796,\n 6670,\n 13,\n 1177,\n 32590,\n 16,\n 8,\n 628,\n 220,\n 220,\n 220,\n 1303,\n 5056,\n 445,\n 31457,\n 1352,\n 2196,\n 286,\n 34381,\n 2994,\n 198,\n 220,\n 220,\n 220,\n 17963,\n 796,\n 357,\n 17,\n 1635,\n 357,\n 15414,\n 82,\n 9,\n 83,\n 853,\n 1039,\n 737,\n 16345,\n 3419,\n 1343,\n 7209,\n 8,\n 1220,\n 14808,\n 15414,\n 82,\n 1174,\n 17,\n 737,\n 16345,\n 3419,\n 1343,\n 357,\n 83,\n 853,\n 1039,\n 1174,\n 17,\n 737,\n 16345,\n 3419,\n 1343,\n 7209,\n 8,\n 628,\n 220,\n 220,\n 220,\n 1441,\n 352,\n 532,\n 17963,\n 198\n]"},"ratio_char_token":{"kind":"number","value":2.4064386317907447,"string":"2.406439"},"token_count":{"kind":"number","value":497,"string":"497"}}},{"rowIdx":1283,"cells":{"content":{"kind":"string","value":"import pygments.lexers.hdl as lexers\nfrom multiprocessing import Process\nimport helpers.common as common\ntokenizer = lexers.VerilogLexer()\n\n"},"input_ids":{"kind":"list like","value":[11748,12972,11726,13,2588,364,13,71,25404,355,31191,364,198,6738,18540,305,919,278,1330,10854,198,11748,49385,13,11321,355,2219,198,30001,7509,796,31191,364,13,13414,346,519,45117,263,3419,628],"string":"[\n 11748,\n 12972,\n 11726,\n 13,\n 2588,\n 364,\n 13,\n 71,\n 25404,\n 355,\n 31191,\n 364,\n 198,\n 6738,\n 18540,\n 305,\n 919,\n 278,\n 1330,\n 10854,\n 198,\n 11748,\n 49385,\n 13,\n 11321,\n 355,\n 2219,\n 198,\n 30001,\n 7509,\n 796,\n 31191,\n 364,\n 13,\n 13414,\n 346,\n 519,\n 45117,\n 263,\n 3419,\n 628\n]"},"ratio_char_token":{"kind":"number","value":3.4146341463414633,"string":"3.414634"},"token_count":{"kind":"number","value":41,"string":"41"}}},{"rowIdx":1284,"cells":{"content":{"kind":"string","value":"\"\"\"\n.. module:: dj-stripe.tests.test_event_handlers\n :synopsis: dj-stripe Event Handler Tests.\n\n.. moduleauthor:: Alex Kavanaugh (@kavdev)\n.. moduleauthor:: Lee Skillen (@lskillen)\n\n\"\"\"\n\nfrom copy import deepcopy\nimport decimal\n\nfrom django.contrib.auth import get_user_model\nfrom django.test import TestCase\nfrom mock import patch\n\nfrom djstripe.models import Event, Charge, Transfer, Account, Plan, Customer, InvoiceItem, Invoice, Card, Subscription\nfrom tests import (FAKE_CARD, FAKE_CHARGE, FAKE_CHARGE_II, FAKE_CUSTOMER, FAKE_CUSTOMER_II,\n FAKE_EVENT_CHARGE_SUCCEEDED, FAKE_EVENT_CUSTOMER_CREATED,\n FAKE_EVENT_CUSTOMER_DELETED, FAKE_EVENT_CUSTOMER_SOURCE_CREATED,\n FAKE_EVENT_CUSTOMER_SOURCE_DELETED, FAKE_EVENT_CUSTOMER_SOURCE_DELETED_DUPE,\n FAKE_EVENT_CUSTOMER_SUBSCRIPTION_CREATED, FAKE_EVENT_CUSTOMER_SUBSCRIPTION_DELETED,\n FAKE_EVENT_INVOICE_CREATED, FAKE_EVENT_INVOICE_DELETED, FAKE_EVENT_INVOICEITEM_CREATED,\n FAKE_EVENT_INVOICEITEM_DELETED, FAKE_EVENT_PLAN_CREATED, FAKE_EVENT_PLAN_DELETED,\n FAKE_EVENT_TRANSFER_CREATED, FAKE_EVENT_TRANSFER_DELETED, FAKE_INVOICE, FAKE_INVOICE_II,\n FAKE_INVOICEITEM, FAKE_PLAN, FAKE_SUBSCRIPTION, FAKE_SUBSCRIPTION_III, FAKE_TRANSFER)\n\n\n\n\n\n\n\n"},"input_ids":{"kind":"list like","value":[37811,198,492,8265,3712,42625,12,33565,431,13,41989,13,9288,62,15596,62,4993,8116,198,220,220,1058,28869,24608,25,42625,12,33565,431,8558,32412,30307,13,198,198,492,8265,9800,3712,4422,21195,4275,74,615,7959,8,198,492,8265,9800,3712,5741,16023,268,4275,7278,12728,268,8,198,198,37811,198,198,6738,4866,1330,2769,30073,198,11748,32465,198,198,6738,42625,14208,13,3642,822,13,18439,1330,651,62,7220,62,19849,198,6738,42625,14208,13,9288,1330,6208,20448,198,6738,15290,1330,8529,198,198,6738,42625,33565,431,13,27530,1330,8558,11,20260,11,20558,11,10781,11,5224,11,22092,11,10001,2942,7449,11,10001,2942,11,5172,11,3834,33584,198,6738,5254,1330,357,7708,7336,62,34,9795,11,9677,7336,62,38019,8264,11,9677,7336,62,38019,8264,62,3978,11,9677,7336,62,34,7759,2662,1137,11,9677,7336,62,34,7759,2662,1137,62,3978,11,198,220,220,220,220,220,220,220,220,220,220,220,220,220,220,220,220,220,220,9677,7336,62,20114,3525,62,38019,8264,62,12564,4093,41841,1961,11,9677,7336,62,20114,3525,62,34,7759,2662,1137,62,43387,11617,11,198,220,220,220,220,220,220,220,220,220,220,220,220,220,220,220,220,220,220,9677,7336,62,20114,3525,62,34,7759,2662,1137,62,7206,28882,1961,11,9677,7336,62,20114,3525,62,34,7759,2662,1137,62,47690,62,43387,11617,11,198,220,220,220,220,220,220,220,220,220,220,220,220,220,220,220,220,220,220,9677,7336,62,20114,3525,62,34,7759,2662,1137,62,47690,62,7206,28882,1961,11,9677,7336,62,20114,3525,62,34,7759,2662,1137,62,47690,62,7206,28882,1961,62,35,8577,36,11,198,220,220,220,220,220,220,220,220,220,220,220,220,220,220,220,220,220,220,9677,7336,62,20114,3525,62,34,7759,2662,1137,62,12564,4462,40165,62,43387,11617,11,9677,7336,62,20114,3525,62,34,7759,2662,1137,62,12564,4462,40165,62,7206,28882,1961,11,198,220,220,220,220,220,220,220,220,220,220,220,220,220,220,220,220,220,220,9677,7336,62,20114,3525,62,1268,29516,8476,62,43387,11617,11,9677,7336,62,20114,3525,62,1268,29516,8476,62,7206,28882,1961,11,9677,7336,62,20114,3525,62,1268,29516,8476,2043,3620,62,43387,11617,11,198,220,220,220,220,220,220,220,220,220,220,220,220,220,220,220,220,220,220,9677,7336,62,20114,3525,62,1268,29516,8476,2043,3620,62,7206,28882,1961,11,9677,7336,62,20114,3525,62,6489,1565,62,43387,11617,11,9677,7336,62,20114,3525,62,6489,1565,62,7206,28882,1961,11,198,220,220,220,220,220,220,220,220,220,220,220,220,220,220,220,220,220,220,9677,7336,62,20114,3525,62,5446,15037,24302,62,43387,11617,11,9677,7336,62,20114,3525,62,5446,15037,24302,62,7206,28882,1961,11,9677,7336,62,1268,29516,8476,11,9677,7336,62,1268,29516,8476,62,3978,11,198,220,220,220,220,220,220,220,220,220,220,220,220,220,220,220,220,220,220,9677,7336,62,1268,29516,8476,2043,3620,11,9677,7336,62,6489,1565,11,9677,7336,62,12564,4462,40165,11,9677,7336,62,12564,4462,40165,62,10855,11,9677,7336,62,5446,15037,24302,8,628,628,628,628],"string":"[\n 37811,\n 198,\n 492,\n 8265,\n 3712,\n 42625,\n 12,\n 33565,\n 431,\n 13,\n 41989,\n 13,\n 9288,\n 62,\n 15596,\n 62,\n 4993,\n 8116,\n 198,\n 220,\n 220,\n 1058,\n 28869,\n 24608,\n 25,\n 42625,\n 12,\n 33565,\n 431,\n 8558,\n 32412,\n 30307,\n 13,\n 198,\n 198,\n 492,\n 8265,\n 9800,\n 3712,\n 4422,\n 21195,\n 4275,\n 74,\n 615,\n 7959,\n 8,\n 198,\n 492,\n 8265,\n 9800,\n 3712,\n 5741,\n 16023,\n 268,\n 4275,\n 7278,\n 12728,\n 268,\n 8,\n 198,\n 198,\n 37811,\n 198,\n 198,\n 6738,\n 4866,\n 1330,\n 2769,\n 30073,\n 198,\n 11748,\n 32465,\n 198,\n 198,\n 6738,\n 42625,\n 14208,\n 13,\n 3642,\n 822,\n 13,\n 18439,\n 1330,\n 651,\n 62,\n 7220,\n 62,\n 19849,\n 198,\n 6738,\n 42625,\n 14208,\n 13,\n 9288,\n 1330,\n 6208,\n 20448,\n 198,\n 6738,\n 15290,\n 1330,\n 8529,\n 198,\n 198,\n 6738,\n 42625,\n 33565,\n 431,\n 13,\n 27530,\n 1330,\n 8558,\n 11,\n 20260,\n 11,\n 20558,\n 11,\n 10781,\n 11,\n 5224,\n 11,\n 22092,\n 11,\n 10001,\n 2942,\n 7449,\n 11,\n 10001,\n 2942,\n 11,\n 5172,\n 11,\n 3834,\n 33584,\n 198,\n 6738,\n 5254,\n 1330,\n 357,\n 7708,\n 7336,\n 62,\n 34,\n 9795,\n 11,\n 9677,\n 7336,\n 62,\n 38019,\n 8264,\n 11,\n 9677,\n 7336,\n 62,\n 38019,\n 8264,\n 62,\n 3978,\n 11,\n 9677,\n 7336,\n 62,\n 34,\n 7759,\n 2662,\n 1137,\n 11,\n 9677,\n 7336,\n 62,\n 34,\n 7759,\n 2662,\n 1137,\n 62,\n 3978,\n 11,\n 198,\n 220,\n 220,\n 220,\n 220,\n 220,\n 220,\n 220,\n 220,\n 220,\n 220,\n 220,\n 220,\n 220,\n 220,\n 220,\n 220,\n 220,\n 220,\n 9677,\n 7336,\n 62,\n 20114,\n 3525,\n 62,\n 38019,\n 8264,\n 62,\n 12564,\n 4093,\n 41841,\n 1961,\n 11,\n 9677,\n 7336,\n 62,\n 20114,\n 3525,\n 62,\n 34,\n 7759,\n 2662,\n 1137,\n 62,\n 43387,\n 11617,\n 11,\n 198,\n 220,\n 220,\n 220,\n 220,\n 220,\n 220,\n 220,\n 220,\n 220,\n 220,\n 220,\n 220,\n 220,\n 220,\n 220,\n 220,\n 220,\n 220,\n 9677,\n 7336,\n 62,\n 20114,\n 3525,\n 62,\n 34,\n 7759,\n 2662,\n 1137,\n 62,\n 7206,\n 28882,\n 1961,\n 11,\n 9677,\n 7336,\n 62,\n 20114,\n 3525,\n 62,\n 34,\n 7759,\n 2662,\n 1137,\n 62,\n 47690,\n 62,\n 43387,\n 11617,\n 11,\n 198,\n 220,\n 220,\n 220,\n 220,\n 220,\n 220,\n 220,\n 220,\n 220,\n 220,\n 220,\n 220,\n 220,\n 220,\n 220,\n 220,\n 220,\n 220,\n 9677,\n 7336,\n 62,\n 20114,\n 3525,\n 62,\n 34,\n 7759,\n 2662,\n 1137,\n 62,\n 47690,\n 62,\n 7206,\n 28882,\n 1961,\n 11,\n 9677,\n 7336,\n 62,\n 20114,\n 3525,\n 62,\n 34,\n 7759,\n 2662,\n 1137,\n 62,\n 47690,\n 62,\n 7206,\n 28882,\n 1961,\n 62,\n 35,\n 8577,\n 36,\n 11,\n 198,\n 220,\n 220,\n 220,\n 220,\n 220,\n 220,\n 220,\n 220,\n 220,\n 220,\n 220,\n 220,\n 220,\n 220,\n 220,\n 220,\n 220,\n 220,\n 9677,\n 7336,\n 62,\n 20114,\n 3525,\n 62,\n 34,\n 7759,\n 2662,\n 1137,\n 62,\n 12564,\n 4462,\n 40165,\n 62,\n 43387,\n 11617,\n 11,\n 9677,\n 7336,\n 62,\n 20114,\n 3525,\n 62,\n 34,\n 7759,\n 2662,\n 1137,\n 62,\n 12564,\n 4462,\n 40165,\n 62,\n 7206,\n 28882,\n 1961,\n 11,\n 198,\n 220,\n 220,\n 220,\n 220,\n 220,\n 220,\n 220,\n 220,\n 220,\n 220,\n 220,\n 220,\n 220,\n 220,\n 220,\n 220,\n 220,\n 220,\n 9677,\n 7336,\n 62,\n 20114,\n 3525,\n 62,\n 1268,\n 29516,\n 8476,\n 62,\n 43387,\n 11617,\n 11,\n 9677,\n 7336,\n 62,\n 20114,\n 3525,\n 62,\n 1268,\n 29516,\n 8476,\n 62,\n 7206,\n 28882,\n 1961,\n 11,\n 9677,\n 7336,\n 62,\n 20114,\n 3525,\n 62,\n 1268,\n 29516,\n 8476,\n 2043,\n 3620,\n 62,\n 43387,\n 11617,\n 11,\n 198,\n 220,\n 220,\n 220,\n 220,\n 220,\n 220,\n 220,\n 220,\n 220,\n 220,\n 220,\n 220,\n 220,\n 220,\n 220,\n 220,\n 220,\n 220,\n 9677,\n 7336,\n 62,\n 20114,\n 3525,\n 62,\n 1268,\n 29516,\n 8476,\n 2043,\n 3620,\n 62,\n 7206,\n 28882,\n 1961,\n 11,\n 9677,\n 7336,\n 62,\n 20114,\n 3525,\n 62,\n 6489,\n 1565,\n 62,\n 43387,\n 11617,\n 11,\n 9677,\n 7336,\n 62,\n 20114,\n 3525,\n 62,\n 6489,\n 1565,\n 62,\n 7206,\n 28882,\n 1961,\n 11,\n 198,\n 220,\n 220,\n 220,\n 220,\n 220,\n 220,\n 220,\n 220,\n 220,\n 220,\n 220,\n 220,\n 220,\n 220,\n 220,\n 220,\n 220,\n 220,\n 9677,\n 7336,\n 62,\n 20114,\n 3525,\n 62,\n 5446,\n 15037,\n 24302,\n 62,\n 43387,\n 11617,\n 11,\n 9677,\n 7336,\n 62,\n 20114,\n 3525,\n 62,\n 5446,\n 15037,\n 24302,\n 62,\n 7206,\n 28882,\n 1961,\n 11,\n 9677,\n 7336,\n 62,\n 1268,\n 29516,\n 8476,\n 11,\n 9677,\n 7336,\n 62,\n 1268,\n 29516,\n 8476,\n 62,\n 3978,\n 11,\n 198,\n 220,\n 220,\n 220,\n 220,\n 220,\n 220,\n 220,\n 220,\n 220,\n 220,\n 220,\n 220,\n 220,\n 220,\n 220,\n 220,\n 220,\n 220,\n 9677,\n 7336,\n 62,\n 1268,\n 29516,\n 8476,\n 2043,\n 3620,\n 11,\n 9677,\n 7336,\n 62,\n 6489,\n 1565,\n 11,\n 9677,\n 7336,\n 62,\n 12564,\n 4462,\n 40165,\n 11,\n 9677,\n 7336,\n 62,\n 12564,\n 4462,\n 40165,\n 62,\n 10855,\n 11,\n 9677,\n 7336,\n 62,\n 5446,\n 15037,\n 24302,\n 8,\n 628,\n 628,\n 628,\n 628\n]"},"ratio_char_token":{"kind":"number","value":2.114104595879556,"string":"2.114105"},"token_count":{"kind":"number","value":631,"string":"631"}}},{"rowIdx":1285,"cells":{"content":{"kind":"string","value":"import common\nimport json\nimport logging\nimport os\nimport subprocess\nimport time\n\nfrom dateutil import parser\n\nhead_vault_hosts = 'OLD_IFS=${IFS};IFS=\\',\\' read -r -a VAULT_HOSTS <<< \\\"$STRING_VAULT_HOST\\\";IFS=${OLD_IFS};'\nsource_kms_utils = '. /usr/sbin/kms_utils.sh;'\n\nglobal vault_token\nglobal vault_accessor\nglobal MAX_PERCENTAGE_EXPIRATION\n\nvault_token = os.getenv('VAULT_TOKEN', '')\nvault_accessor = os.getenv('ACCESSOR_TOKEN','')\nMIN_PERCENTAGE_EXPIRATION = 0.2\n\nlogger = None\n\n"},"input_ids":{"kind":"list like","value":[11748,2219,198,11748,33918,198,11748,18931,198,11748,28686,198,11748,850,14681,198,11748,640,198,198,6738,3128,22602,1330,30751,198,198,2256,62,85,1721,62,4774,82,796,705,15173,62,5064,50,28,38892,5064,50,19629,5064,50,28,59,3256,43054,1100,532,81,532,64,13753,16724,62,39,10892,50,9959,27,19990,3,18601,2751,62,11731,16724,62,39,10892,7879,26,5064,50,28,38892,15173,62,5064,50,19629,6,198,10459,62,74,907,62,26791,796,45302,1220,14629,14,82,8800,14,74,907,62,26791,13,1477,26,6,198,198,20541,22563,62,30001,198,20541,22563,62,15526,273,198,20541,25882,62,18973,43960,11879,62,49864,4663,6234,198,198,85,1721,62,30001,796,28686,13,1136,24330,10786,11731,16724,62,10468,43959,3256,10148,8,198,85,1721,62,15526,273,796,28686,13,1136,24330,10786,26861,7597,1581,62,10468,43959,3256,7061,8,198,23678,62,18973,43960,11879,62,49864,4663,6234,796,657,13,17,198,198,6404,1362,796,6045,628],"string":"[\n 11748,\n 2219,\n 198,\n 11748,\n 33918,\n 198,\n 11748,\n 18931,\n 198,\n 11748,\n 28686,\n 198,\n 11748,\n 850,\n 14681,\n 198,\n 11748,\n 640,\n 198,\n 198,\n 6738,\n 3128,\n 22602,\n 1330,\n 30751,\n 198,\n 198,\n 2256,\n 62,\n 85,\n 1721,\n 62,\n 4774,\n 82,\n 796,\n 705,\n 15173,\n 62,\n 5064,\n 50,\n 28,\n 38892,\n 5064,\n 50,\n 19629,\n 5064,\n 50,\n 28,\n 59,\n 3256,\n 43054,\n 1100,\n 532,\n 81,\n 532,\n 64,\n 13753,\n 16724,\n 62,\n 39,\n 10892,\n 50,\n 9959,\n 27,\n 19990,\n 3,\n 18601,\n 2751,\n 62,\n 11731,\n 16724,\n 62,\n 39,\n 10892,\n 7879,\n 26,\n 5064,\n 50,\n 28,\n 38892,\n 15173,\n 62,\n 5064,\n 50,\n 19629,\n 6,\n 198,\n 10459,\n 62,\n 74,\n 907,\n 62,\n 26791,\n 796,\n 45302,\n 1220,\n 14629,\n 14,\n 82,\n 8800,\n 14,\n 74,\n 907,\n 62,\n 26791,\n 13,\n 1477,\n 26,\n 6,\n 198,\n 198,\n 20541,\n 22563,\n 62,\n 30001,\n 198,\n 20541,\n 22563,\n 62,\n 15526,\n 273,\n 198,\n 20541,\n 25882,\n 62,\n 18973,\n 43960,\n 11879,\n 62,\n 49864,\n 4663,\n 6234,\n 198,\n 198,\n 85,\n 1721,\n 62,\n 30001,\n 796,\n 28686,\n 13,\n 1136,\n 24330,\n 10786,\n 11731,\n 16724,\n 62,\n 10468,\n 43959,\n 3256,\n 10148,\n 8,\n 198,\n 85,\n 1721,\n 62,\n 15526,\n 273,\n 796,\n 28686,\n 13,\n 1136,\n 24330,\n 10786,\n 26861,\n 7597,\n 1581,\n 62,\n 10468,\n 43959,\n 3256,\n 7061,\n 8,\n 198,\n 23678,\n 62,\n 18973,\n 43960,\n 11879,\n 62,\n 49864,\n 4663,\n 6234,\n 796,\n 657,\n 13,\n 17,\n 198,\n 198,\n 6404,\n 1362,\n 796,\n 6045,\n 628\n]"},"ratio_char_token":{"kind":"number","value":2.5,"string":"2.5"},"token_count":{"kind":"number","value":194,"string":"194"}}},{"rowIdx":1286,"cells":{"content":{"kind":"string","value":"\"Introducing the sys Module\"\nimport sys \nprint(sys.platform)\nprint(sys.maxsize)\nprint(sys.version)\n\n\nif sys.platform[:3] == 'win': print('hello windows')\n"},"input_ids":{"kind":"list like","value":[1,15005,2259,262,25064,19937,1,198,11748,25064,220,198,4798,7,17597,13,24254,8,198,4798,7,17597,13,9806,7857,8,198,4798,7,17597,13,9641,8,628,198,361,25064,13,24254,58,25,18,60,6624,705,5404,10354,3601,10786,31373,9168,11537,198],"string":"[\n 1,\n 15005,\n 2259,\n 262,\n 25064,\n 19937,\n 1,\n 198,\n 11748,\n 25064,\n 220,\n 198,\n 4798,\n 7,\n 17597,\n 13,\n 24254,\n 8,\n 198,\n 4798,\n 7,\n 17597,\n 13,\n 9806,\n 7857,\n 8,\n 198,\n 4798,\n 7,\n 17597,\n 13,\n 9641,\n 8,\n 628,\n 198,\n 361,\n 25064,\n 13,\n 24254,\n 58,\n 25,\n 18,\n 60,\n 6624,\n 705,\n 5404,\n 10354,\n 3601,\n 10786,\n 31373,\n 9168,\n 11537,\n 198\n]"},"ratio_char_token":{"kind":"number","value":2.9056603773584904,"string":"2.90566"},"token_count":{"kind":"number","value":53,"string":"53"}}},{"rowIdx":1287,"cells":{"content":{"kind":"string","value":"from .orion import parse_orion\n"},"input_ids":{"kind":"list like","value":[6738,764,273,295,1330,21136,62,273,295,198],"string":"[\n 6738,\n 764,\n 273,\n 295,\n 1330,\n 21136,\n 62,\n 273,\n 295,\n 198\n]"},"ratio_char_token":{"kind":"number","value":3.1,"string":"3.1"},"token_count":{"kind":"number","value":10,"string":"10"}}},{"rowIdx":1288,"cells":{"content":{"kind":"string","value":"with open(\"./day09.input\") as file:\n\tdata = [int(line.strip()) for line in file.readlines()]\n\n\n\np1 = get_first_not_matching(25)\nprint(p1)\n\np2 = get_contiguous_ns_that_add_to(p1)\nprint(p2)"},"input_ids":{"kind":"list like","value":[4480,1280,7,1911,14,820,2931,13,15414,4943,355,2393,25,198,197,7890,796,685,600,7,1370,13,36311,28955,329,1627,287,2393,13,961,6615,3419,60,628,198,198,79,16,796,651,62,11085,62,1662,62,15699,278,7,1495,8,198,4798,7,79,16,8,198,198,79,17,796,651,62,3642,29709,62,5907,62,5562,62,2860,62,1462,7,79,16,8,198,4798,7,79,17,8],"string":"[\n 4480,\n 1280,\n 7,\n 1911,\n 14,\n 820,\n 2931,\n 13,\n 15414,\n 4943,\n 355,\n 2393,\n 25,\n 198,\n 197,\n 7890,\n 796,\n 685,\n 600,\n 7,\n 1370,\n 13,\n 36311,\n 28955,\n 329,\n 1627,\n 287,\n 2393,\n 13,\n 961,\n 6615,\n 3419,\n 60,\n 628,\n 198,\n 198,\n 79,\n 16,\n 796,\n 651,\n 62,\n 11085,\n 62,\n 1662,\n 62,\n 15699,\n 278,\n 7,\n 1495,\n 8,\n 198,\n 4798,\n 7,\n 79,\n 16,\n 8,\n 198,\n 198,\n 79,\n 17,\n 796,\n 651,\n 62,\n 3642,\n 29709,\n 62,\n 5907,\n 62,\n 5562,\n 62,\n 2860,\n 62,\n 1462,\n 7,\n 79,\n 16,\n 8,\n 198,\n 4798,\n 7,\n 79,\n 17,\n 8\n]"},"ratio_char_token":{"kind":"number","value":2.253012048192771,"string":"2.253012"},"token_count":{"kind":"number","value":83,"string":"83"}}},{"rowIdx":1289,"cells":{"content":{"kind":"string","value":"import json\nimport os\n\nimport nibabel as nib\nimport numpy as np\nimport pandas as pd\n\nROOT = \"./\"\nDATA = os.path.join(ROOT, \"data/\")\n"},"input_ids":{"kind":"list like","value":[11748,33918,198,11748,28686,198,198,11748,33272,9608,355,33272,198,11748,299,32152,355,45941,198,11748,19798,292,355,279,67,198,198,13252,2394,796,366,19571,1,198,26947,796,28686,13,6978,13,22179,7,13252,2394,11,366,7890,14,4943,198],"string":"[\n 11748,\n 33918,\n 198,\n 11748,\n 28686,\n 198,\n 198,\n 11748,\n 33272,\n 9608,\n 355,\n 33272,\n 198,\n 11748,\n 299,\n 32152,\n 355,\n 45941,\n 198,\n 11748,\n 19798,\n 292,\n 355,\n 279,\n 67,\n 198,\n 198,\n 13252,\n 2394,\n 796,\n 366,\n 19571,\n 1,\n 198,\n 26947,\n 796,\n 28686,\n 13,\n 6978,\n 13,\n 22179,\n 7,\n 13252,\n 2394,\n 11,\n 366,\n 7890,\n 14,\n 4943,\n 198\n]"},"ratio_char_token":{"kind":"number","value":2.64,"string":"2.64"},"token_count":{"kind":"number","value":50,"string":"50"}}},{"rowIdx":1290,"cells":{"content":{"kind":"string","value":"import matplotlib\r\nimport random\r\nimport operator\r\nimport csv\r\nimport drunkframework\r\nimport matplotlib.animation \r\nimport matplotlib.pyplot\r\n\r\n\r\n\r\n\r\n\"\"\"WARNING!!!!!\"\"\"\r\n\"\"\"This code was tested using Spyder 5.0.4, should any problems be encountered using older\r\nmodels please try \"\"\"\r\n\r\n#creates a new empty list for what will be the csv environment data, see https://docs.python.org/3/library/csv.html for more\r\nenvironment = []\r\n#drunks adapted from agents from GUI's practical replacing \"agents\"\r\ndrunks = []\r\n#density is an empty list which will track agent movement independent of the movement process\r\ndensity= []\r\n#specifies number of drunks/agents\r\nnum_of_drunks = 25\r\n#outlines the number of iterations the line 64-78 code will undergo\r\nnum_of_iterations = 100\r\n\r\n\r\n#sets the dimensions for the matplotlib plots\r\nfig = matplotlib.pyplot.figure(figsize=(7, 7))\r\nax = fig.add_axes([0, 0, 1, 1])\r\n\r\n\r\n\r\nf = open('drunk.txt', newline='')\r\n#Note that the correct directory must be navigated to in the terminal else the full file path will be needed\r\nreader = csv.reader(f, quoting=csv.QUOTE_NONNUMERIC)\r\n\r\n#Used for testing purposes to ascertain the lay of the environment\r\n#matplotlib.pyplot.xlim(0, 300)\r\n#matplotlib.pyplot.ylim(0, 300)\r\n#matplotlib.pyplot.imshow(environment)\r\n\r\nfor row in reader:\r\n rowlist =[]\r\n for value in row:\r\n rowlist.append(value)\r\n environment.append(rowlist)\r\nf.close()\r\n#print (rowlist) Used this to check list structure\r\n\r\n#Code on lines 46-50 appends the density list output to a 300x300 grid, this code is needed \r\n#to prevent the error \"IndexError: list index out of range\" \r\nfor i in range(300):\r\n rowlist = []\r\n for j in range(300):\r\n rowlist.append(0)\r\n density.append(rowlist)\r\n#matplotlib.pyplot.imshow(environment) run this in isolation to check the environment is\r\n#correct\r\n\r\n\r\n## Make drunks and assign them with an identification number.\r\nfor i in range(num_of_drunks):\r\n identification = ((1+i)*10) \r\n # print(identification) #this should print 10-250 giving each of the drunks an identification number, later to be matched up with houses\r\n drunks.append(drunkframework.Drunk(environment, drunks, identification))\r\n \r\n\r\n\r\n#This is is supposed to work whereby if the co-ordinates of stilldrunk match their identification number they are home \r\n#In the prototype density of the environment changed throughout the iterations, as such the drunks would\r\n#often stop in areas which were not their home. The work around this was seperating the process of track\r\n#and move through the creation of the density list. Track is left in but commented.\r\nfor i in range (num_of_drunks):\r\n stilldrunk = drunks[i]\r\n for j in range(num_of_iterations):\r\n while environment [stilldrunk._y][stilldrunk._x] != stilldrunk.identification:\r\n density[drunks[i]._y][drunks[i]._x]+=1\r\n drunks[i].move()\r\n #drunks[i].track() omitted from the final iteration of the application\r\n\r\n#saves density list (see lines 68 to 73)\r\nwith open('density.txt', 'w', newline='') as f:\r\n csvwriter = csv.writer(f, delimiter=',', quoting=csv.QUOTE_NONNUMERIC)\r\n for row in density:\r\n csvwriter.writerow(row) \r\n \r\n#lines 79 to 90 serve the purpose of display the density and drunks in relation\r\n#to their finishing position within the environment\r\n \r\nmatplotlib.pyplot.xlim(0, 300)\r\nmatplotlib.pyplot.ylim(0, 300)\r\nmatplotlib.pyplot.imshow(density)\r\n\r\nmatplotlib.pyplot.xlim(0, 300)\r\nmatplotlib.pyplot.ylim(0, 300)\r\nmatplotlib.pyplot.show(drunks)\r\n\r\n\r\nmatplotlib.pyplot.xlim(0, 300)\r\nmatplotlib.pyplot.ylim(0, 300)\r\nmatplotlib.pyplot.imshow(environment)\r\n\r\n#Code below just prints we're home for each of the 25 agents following a resolution of\r\n#the code\r\n\r\nfor i in range(num_of_drunks):\r\n matplotlib.pyplot.scatter(drunks[i]._x, drunks[i]._y)\r\n print(\"we're home!\") \r\n"},"input_ids":{"kind":"list like","value":[11748,2603,29487,8019,201,198,11748,4738,201,198,11748,10088,201,198,11748,269,21370,201,198,11748,10785,30604,201,198,11748,2603,29487,8019,13,11227,341,220,201,198,11748,2603,29487,8019,13,9078,29487,201,198,201,198,201,198,201,198,201,198,37811,31502,13896,2474,15931,201,198,37811,1212,2438,373,6789,1262,23688,1082,642,13,15,13,19,11,815,597,2761,307,12956,1262,4697,201,198,27530,3387,1949,37227,201,198,201,198,2,20123,274,257,649,6565,1351,329,644,481,307,262,269,21370,2858,1366,11,766,3740,1378,31628,13,29412,13,2398,14,18,14,32016,14,40664,13,6494,329,517,201,198,38986,796,17635,201,198,2,67,5143,591,16573,422,6554,422,25757,338,8472,13586,366,49638,1,201,198,67,5143,591,796,17635,201,198,2,43337,318,281,6565,1351,543,481,2610,5797,3356,4795,286,262,3356,1429,201,198,43337,28,17635,201,198,2,16684,6945,1271,286,1553,14125,14,49638,201,198,22510,62,1659,62,67,5143,591,796,1679,201,198,2,448,6615,262,1271,286,34820,262,1627,5598,12,3695,2438,481,17777,201,198,22510,62,1659,62,2676,602,796,1802,201,198,201,198,201,198,2,28709,262,15225,329,262,2603,29487,8019,21528,201,198,5647,796,2603,29487,8019,13,9078,29487,13,26875,7,5647,7857,16193,22,11,767,4008,201,198,897,796,2336,13,2860,62,897,274,26933,15,11,657,11,352,11,352,12962,201,198,201,198,201,198,201,198,69,796,1280,10786,7109,2954,13,14116,3256,649,1370,28,7061,8,201,198,2,6425,326,262,3376,8619,1276,307,20436,515,284,287,262,12094,2073,262,1336,2393,3108,481,307,2622,201,198,46862,796,269,21370,13,46862,7,69,11,28411,28,40664,13,10917,23051,62,45,1340,41359,1137,2149,8,201,198,201,198,2,38052,329,4856,4959,284,35520,262,3830,286,262,2858,201,198,2,6759,29487,8019,13,9078,29487,13,87,2475,7,15,11,5867,8,201,198,2,6759,29487,8019,13,9078,29487,13,88,2475,7,15,11,5867,8,201,198,2,6759,29487,8019,13,9078,29487,13,320,12860,7,38986,8,201,198,201,198,1640,5752,287,9173,25,201,198,220,220,220,5752,4868,796,21737,201,198,220,220,220,329,1988,287,5752,25,201,198,220,220,220,220,220,220,220,5752,4868,13,33295,7,8367,8,201,198,220,220,220,2858,13,33295,7,808,4868,8,201,198,69,13,19836,3419,201,198,2,4798,357,808,4868,8,16718,428,284,2198,1351,4645,201,198,201,198,2,10669,319,3951,6337,12,1120,598,2412,262,12109,1351,5072,284,257,5867,87,6200,10706,11,428,2438,318,2622,220,201,198,2,1462,2948,262,4049,366,15732,12331,25,1351,6376,503,286,2837,1,220,220,220,220,220,220,220,220,220,220,220,220,220,220,220,220,220,220,220,220,220,220,220,220,220,220,220,220,220,220,220,220,201,198,1640,1312,287,2837,7,6200,2599,201,198,220,220,220,5752,4868,796,17635,201,198,220,220,220,329,474,287,2837,7,6200,2599,201,198,220,220,220,220,220,220,220,5752,4868,13,33295,7,15,8,201,198,220,220,220,12109,13,33295,7,808,4868,8,201,198,2,6759,29487,8019,13,9078,29487,13,320,12860,7,38986,8,1057,428,287,15133,284,2198,262,2858,318,201,198,2,30283,201,198,201,198,201,198,2235,6889,1553,14125,290,8333,606,351,281,11795,1271,13,201,198,1640,1312,287,2837,7,22510,62,1659,62,67,5143,591,2599,201,198,220,220,220,11795,796,14808,16,10,72,27493,940,8,220,201,198,220,220,1303,3601,7,738,2649,8,1303,5661,815,3601,838,12,9031,3501,1123,286,262,1553,14125,281,11795,1271,11,1568,284,307,14451,510,351,7777,201,198,220,220,220,1553,14125,13,33295,7,7109,2954,30604,13,6187,2954,7,38986,11,1553,14125,11,11795,4008,201,198,220,220,220,220,201,198,201,198,201,198,2,1212,318,318,4385,284,670,23482,611,262,763,12,585,17540,286,991,7109,2954,2872,511,11795,1271,484,389,1363,220,201,198,2,818,262,14879,12109,286,262,2858,3421,3690,262,34820,11,355,884,262,1553,14125,561,201,198,2,28950,2245,287,3006,543,547,407,511,1363,13,383,670,1088,428,373,384,525,803,262,1429,286,2610,201,198,2,392,1445,832,262,6282,286,262,12109,1351,13,17762,318,1364,287,475,16476,13,201,198,1640,1312,287,2837,357,22510,62,1659,62,67,5143,591,2599,201,198,220,220,220,991,7109,2954,796,1553,14125,58,72,60,201,198,220,220,220,329,474,287,2837,7,22510,62,1659,62,2676,602,2599,201,198,220,220,220,220,220,220,220,220,981,2858,685,24219,7109,2954,13557,88,7131,24219,7109,2954,13557,87,60,14512,991,7109,2954,13,738,2649,25,201,198,220,220,220,220,220,220,220,220,220,220,220,220,220,220,220,12109,58,67,5143,591,58,72,4083,62,88,7131,67,5143,591,58,72,4083,62,87,60,47932,16,201,198,220,220,220,220,220,220,220,220,220,220,220,220,220,220,220,1553,14125,58,72,4083,21084,3419,201,198,220,220,220,220,220,220,220,220,220,220,220,220,220,220,220,1303,67,5143,591,58,72,4083,11659,3419,22532,422,262,2457,24415,286,262,3586,201,198,201,198,2,82,3080,12109,1351,357,3826,3951,8257,284,8854,8,201,198,4480,1280,10786,43337,13,14116,3256,705,86,3256,649,1370,28,7061,8,355,277,25,201,198,220,220,220,269,21370,16002,796,269,21370,13,16002,7,69,11,46728,2676,28,3256,3256,28411,28,40664,13,10917,23051,62,45,1340,41359,1137,2149,8,201,198,220,220,220,329,5752,287,12109,25,201,198,220,220,220,220,220,220,220,269,21370,16002,13,16002,322,7,808,8,220,220,220,220,220,220,220,220,220,220,220,220,220,220,220,220,201,198,220,220,201,198,2,6615,9225,284,4101,4691,262,4007,286,3359,262,12109,290,1553,14125,287,8695,201,198,2,1462,511,12848,2292,1626,262,2858,201,198,220,220,220,220,220,220,220,220,220,220,220,220,220,220,220,220,220,220,220,220,220,220,220,220,220,220,220,220,220,220,201,198,6759,29487,8019,13,9078,29487,13,87,2475,7,15,11,5867,8,201,198,6759,29487,8019,13,9078,29487,13,88,2475,7,15,11,5867,8,201,198,6759,29487,8019,13,9078,29487,13,320,12860,7,43337,8,201,198,201,198,6759,29487,8019,13,9078,29487,13,87,2475,7,15,11,5867,8,201,198,6759,29487,8019,13,9078,29487,13,88,2475,7,15,11,5867,8,201,198,6759,29487,8019,13,9078,29487,13,12860,7,67,5143,591,8,201,198,201,198,201,198,6759,29487,8019,13,9078,29487,13,87,2475,7,15,11,5867,8,201,198,6759,29487,8019,13,9078,29487,13,88,2475,7,15,11,5867,8,201,198,6759,29487,8019,13,9078,29487,13,320,12860,7,38986,8,201,198,201,198,2,10669,2174,655,20842,356,821,1363,329,1123,286,262,1679,6554,1708,257,6323,286,201,198,2,1169,2438,201,198,201,198,1640,1312,287,2837,7,22510,62,1659,62,67,5143,591,2599,201,198,220,220,220,220,220,220,220,2603,29487,8019,13,9078,29487,13,1416,1436,7,67,5143,591,58,72,4083,62,87,11,1553,14125,58,72,4083,62,88,8,201,198,220,220,220,220,220,220,220,3601,7203,732,821,1363,2474,8,220,220,220,220,201,198],"string":"[\n 11748,\n 2603,\n 29487,\n 8019,\n 201,\n 198,\n 11748,\n 4738,\n 201,\n 198,\n 11748,\n 10088,\n 201,\n 198,\n 11748,\n 269,\n 21370,\n 201,\n 198,\n 11748,\n 10785,\n 30604,\n 201,\n 198,\n 11748,\n 2603,\n 29487,\n 8019,\n 13,\n 11227,\n 341,\n 220,\n 201,\n 198,\n 11748,\n 2603,\n 29487,\n 8019,\n 13,\n 9078,\n 29487,\n 201,\n 198,\n 201,\n 198,\n 201,\n 198,\n 201,\n 198,\n 201,\n 198,\n 37811,\n 31502,\n 13896,\n 2474,\n 15931,\n 201,\n 198,\n 37811,\n 1212,\n 2438,\n 373,\n 6789,\n 1262,\n 23688,\n 1082,\n 642,\n 13,\n 15,\n 13,\n 19,\n 11,\n 815,\n 597,\n 2761,\n 307,\n 12956,\n 1262,\n 4697,\n 201,\n 198,\n 27530,\n 3387,\n 1949,\n 37227,\n 201,\n 198,\n 201,\n 198,\n 2,\n 20123,\n 274,\n 257,\n 649,\n 6565,\n 1351,\n 329,\n 644,\n 481,\n 307,\n 262,\n 269,\n 21370,\n 2858,\n 1366,\n 11,\n 766,\n 3740,\n 1378,\n 31628,\n 13,\n 29412,\n 13,\n 2398,\n 14,\n 18,\n 14,\n 32016,\n 14,\n 40664,\n 13,\n 6494,\n 329,\n 517,\n 201,\n 198,\n 38986,\n 796,\n 17635,\n 201,\n 198,\n 2,\n 67,\n 5143,\n 591,\n 16573,\n 422,\n 6554,\n 422,\n 25757,\n 338,\n 8472,\n 13586,\n 366,\n 49638,\n 1,\n 201,\n 198,\n 67,\n 5143,\n 591,\n 796,\n 17635,\n 201,\n 198,\n 2,\n 43337,\n 318,\n 281,\n 6565,\n 1351,\n 543,\n 481,\n 2610,\n 5797,\n 3356,\n 4795,\n 286,\n 262,\n 3356,\n 1429,\n 201,\n 198,\n 43337,\n 28,\n 17635,\n 201,\n 198,\n 2,\n 16684,\n 6945,\n 1271,\n 286,\n 1553,\n 14125,\n 14,\n 49638,\n 201,\n 198,\n 22510,\n 62,\n 1659,\n 62,\n 67,\n 5143,\n 591,\n 796,\n 1679,\n 201,\n 198,\n 2,\n 448,\n 6615,\n 262,\n 1271,\n 286,\n 34820,\n 262,\n 1627,\n 5598,\n 12,\n 3695,\n 2438,\n 481,\n 17777,\n 201,\n 198,\n 22510,\n 62,\n 1659,\n 62,\n 2676,\n 602,\n 796,\n 1802,\n 201,\n 198,\n 201,\n 198,\n 201,\n 198,\n 2,\n 28709,\n 262,\n 15225,\n 329,\n 262,\n 2603,\n 29487,\n 8019,\n 21528,\n 201,\n 198,\n 5647,\n 796,\n 2603,\n 29487,\n 8019,\n 13,\n 9078,\n 29487,\n 13,\n 26875,\n 7,\n 5647,\n 7857,\n 16193,\n 22,\n 11,\n 767,\n 4008,\n 201,\n 198,\n 897,\n 796,\n 2336,\n 13,\n 2860,\n 62,\n 897,\n 274,\n 26933,\n 15,\n 11,\n 657,\n 11,\n 352,\n 11,\n 352,\n 12962,\n 201,\n 198,\n 201,\n 198,\n 201,\n 198,\n 201,\n 198,\n 69,\n 796,\n 1280,\n 10786,\n 7109,\n 2954,\n 13,\n 14116,\n 3256,\n 649,\n 1370,\n 28,\n 7061,\n 8,\n 201,\n 198,\n 2,\n 6425,\n 326,\n 262,\n 3376,\n 8619,\n 1276,\n 307,\n 20436,\n 515,\n 284,\n 287,\n 262,\n 12094,\n 2073,\n 262,\n 1336,\n 2393,\n 3108,\n 481,\n 307,\n 2622,\n 201,\n 198,\n 46862,\n 796,\n 269,\n 21370,\n 13,\n 46862,\n 7,\n 69,\n 11,\n 28411,\n 28,\n 40664,\n 13,\n 10917,\n 23051,\n 62,\n 45,\n 1340,\n 41359,\n 1137,\n 2149,\n 8,\n 201,\n 198,\n 201,\n 198,\n 2,\n 38052,\n 329,\n 4856,\n 4959,\n 284,\n 35520,\n 262,\n 3830,\n 286,\n 262,\n 2858,\n 201,\n 198,\n 2,\n 6759,\n 29487,\n 8019,\n 13,\n 9078,\n 29487,\n 13,\n 87,\n 2475,\n 7,\n 15,\n 11,\n 5867,\n 8,\n 201,\n 198,\n 2,\n 6759,\n 29487,\n 8019,\n 13,\n 9078,\n 29487,\n 13,\n 88,\n 2475,\n 7,\n 15,\n 11,\n 5867,\n 8,\n 201,\n 198,\n 2,\n 6759,\n 29487,\n 8019,\n 13,\n 9078,\n 29487,\n 13,\n 320,\n 12860,\n 7,\n 38986,\n 8,\n 201,\n 198,\n 201,\n 198,\n 1640,\n 5752,\n 287,\n 9173,\n 25,\n 201,\n 198,\n 220,\n 220,\n 220,\n 5752,\n 4868,\n 796,\n 21737,\n 201,\n 198,\n 220,\n 220,\n 220,\n 329,\n 1988,\n 287,\n 5752,\n 25,\n 201,\n 198,\n 220,\n 220,\n 220,\n 220,\n 220,\n 220,\n 220,\n 5752,\n 4868,\n 13,\n 33295,\n 7,\n 8367,\n 8,\n 201,\n 198,\n 220,\n 220,\n 220,\n 2858,\n 13,\n 33295,\n 7,\n 808,\n 4868,\n 8,\n 201,\n 198,\n 69,\n 13,\n 19836,\n 3419,\n 201,\n 198,\n 2,\n 4798,\n 357,\n 808,\n 4868,\n 8,\n 16718,\n 428,\n 284,\n 2198,\n 1351,\n 4645,\n 201,\n 198,\n 201,\n 198,\n 2,\n 10669,\n 319,\n 3951,\n 6337,\n 12,\n 1120,\n 598,\n 2412,\n 262,\n 12109,\n 1351,\n 5072,\n 284,\n 257,\n 5867,\n 87,\n 6200,\n 10706,\n 11,\n 428,\n 2438,\n 318,\n 2622,\n 220,\n 201,\n 198,\n 2,\n 1462,\n 2948,\n 262,\n 4049,\n 366,\n 15732,\n 12331,\n 25,\n 1351,\n 6376,\n 503,\n 286,\n 2837,\n 1,\n 220,\n 220,\n 220,\n 220,\n 220,\n 220,\n 220,\n 220,\n 220,\n 220,\n 220,\n 220,\n 220,\n 220,\n 220,\n 220,\n 220,\n 220,\n 220,\n 220,\n 220,\n 220,\n 220,\n 220,\n 220,\n 220,\n 220,\n 220,\n 220,\n 220,\n 220,\n 220,\n 201,\n 198,\n 1640,\n 1312,\n 287,\n 2837,\n 7,\n 6200,\n 2599,\n 201,\n 198,\n 220,\n 220,\n 220,\n 5752,\n 4868,\n 796,\n 17635,\n 201,\n 198,\n 220,\n 220,\n 220,\n 329,\n 474,\n 287,\n 2837,\n 7,\n 6200,\n 2599,\n 201,\n 198,\n 220,\n 220,\n 220,\n 220,\n 220,\n 220,\n 220,\n 5752,\n 4868,\n 13,\n 33295,\n 7,\n 15,\n 8,\n 201,\n 198,\n 220,\n 220,\n 220,\n 12109,\n 13,\n 33295,\n 7,\n 808,\n 4868,\n 8,\n 201,\n 198,\n 2,\n 6759,\n 29487,\n 8019,\n 13,\n 9078,\n 29487,\n 13,\n 320,\n 12860,\n 7,\n 38986,\n 8,\n 1057,\n 428,\n 287,\n 15133,\n 284,\n 2198,\n 262,\n 2858,\n 318,\n 201,\n 198,\n 2,\n 30283,\n 201,\n 198,\n 201,\n 198,\n 201,\n 198,\n 2235,\n 6889,\n 1553,\n 14125,\n 290,\n 8333,\n 606,\n 351,\n 281,\n 11795,\n 1271,\n 13,\n 201,\n 198,\n 1640,\n 1312,\n 287,\n 2837,\n 7,\n 22510,\n 62,\n 1659,\n 62,\n 67,\n 5143,\n 591,\n 2599,\n 201,\n 198,\n 220,\n 220,\n 220,\n 11795,\n 796,\n 14808,\n 16,\n 10,\n 72,\n 27493,\n 940,\n 8,\n 220,\n 201,\n 198,\n 220,\n 220,\n 1303,\n 3601,\n 7,\n 738,\n 2649,\n 8,\n 1303,\n 5661,\n 815,\n 3601,\n 838,\n 12,\n 9031,\n 3501,\n 1123,\n 286,\n 262,\n 1553,\n 14125,\n 281,\n 11795,\n 1271,\n 11,\n 1568,\n 284,\n 307,\n 14451,\n 510,\n 351,\n 7777,\n 201,\n 198,\n 220,\n 220,\n 220,\n 1553,\n 14125,\n 13,\n 33295,\n 7,\n 7109,\n 2954,\n 30604,\n 13,\n 6187,\n 2954,\n 7,\n 38986,\n 11,\n 1553,\n 14125,\n 11,\n 11795,\n 4008,\n 201,\n 198,\n 220,\n 220,\n 220,\n 220,\n 201,\n 198,\n 201,\n 198,\n 201,\n 198,\n 2,\n 1212,\n 318,\n 318,\n 4385,\n 284,\n 670,\n 23482,\n 611,\n 262,\n 763,\n 12,\n 585,\n 17540,\n 286,\n 991,\n 7109,\n 2954,\n 2872,\n 511,\n 11795,\n 1271,\n 484,\n 389,\n 1363,\n 220,\n 201,\n 198,\n 2,\n 818,\n 262,\n 14879,\n 12109,\n 286,\n 262,\n 2858,\n 3421,\n 3690,\n 262,\n 34820,\n 11,\n 355,\n 884,\n 262,\n 1553,\n 14125,\n 561,\n 201,\n 198,\n 2,\n 28950,\n 2245,\n 287,\n 3006,\n 543,\n 547,\n 407,\n 511,\n 1363,\n 13,\n 383,\n 670,\n 1088,\n 428,\n 373,\n 384,\n 525,\n 803,\n 262,\n 1429,\n 286,\n 2610,\n 201,\n 198,\n 2,\n 392,\n 1445,\n 832,\n 262,\n 6282,\n 286,\n 262,\n 12109,\n 1351,\n 13,\n 17762,\n 318,\n 1364,\n 287,\n 475,\n 16476,\n 13,\n 201,\n 198,\n 1640,\n 1312,\n 287,\n 2837,\n 357,\n 22510,\n 62,\n 1659,\n 62,\n 67,\n 5143,\n 591,\n 2599,\n 201,\n 198,\n 220,\n 220,\n 220,\n 991,\n 7109,\n 2954,\n 796,\n 1553,\n 14125,\n 58,\n 72,\n 60,\n 201,\n 198,\n 220,\n 220,\n 220,\n 329,\n 474,\n 287,\n 2837,\n 7,\n 22510,\n 62,\n 1659,\n 62,\n 2676,\n 602,\n 2599,\n 201,\n 198,\n 220,\n 220,\n 220,\n 220,\n 220,\n 220,\n 220,\n 220,\n 981,\n 2858,\n 685,\n 24219,\n 7109,\n 2954,\n 13557,\n 88,\n 7131,\n 24219,\n 7109,\n 2954,\n 13557,\n 87,\n 60,\n 14512,\n 991,\n 7109,\n 2954,\n 13,\n 738,\n 2649,\n 25,\n 201,\n 198,\n 220,\n 220,\n 220,\n 220,\n 220,\n 220,\n 220,\n 220,\n 220,\n 220,\n 220,\n 220,\n 220,\n 220,\n 220,\n 12109,\n 58,\n 67,\n 5143,\n 591,\n 58,\n 72,\n 4083,\n 62,\n 88,\n 7131,\n 67,\n 5143,\n 591,\n 58,\n 72,\n 4083,\n 62,\n 87,\n 60,\n 47932,\n 16,\n 201,\n 198,\n 220,\n 220,\n 220,\n 220,\n 220,\n 220,\n 220,\n 220,\n 220,\n 220,\n 220,\n 220,\n 220,\n 220,\n 220,\n 1553,\n 14125,\n 58,\n 72,\n 4083,\n 21084,\n 3419,\n 201,\n 198,\n 220,\n 220,\n 220,\n 220,\n 220,\n 220,\n 220,\n 220,\n 220,\n 220,\n 220,\n 220,\n 220,\n 220,\n 220,\n 1303,\n 67,\n 5143,\n 591,\n 58,\n 72,\n 4083,\n 11659,\n 3419,\n 22532,\n 422,\n 262,\n 2457,\n 24415,\n 286,\n 262,\n 3586,\n 201,\n 198,\n 201,\n 198,\n 2,\n 82,\n 3080,\n 12109,\n 1351,\n 357,\n 3826,\n 3951,\n 8257,\n 284,\n 8854,\n 8,\n 201,\n 198,\n 4480,\n 1280,\n 10786,\n 43337,\n 13,\n 14116,\n 3256,\n 705,\n 86,\n 3256,\n 649,\n 1370,\n 28,\n 7061,\n 8,\n 355,\n 277,\n 25,\n 201,\n 198,\n 220,\n 220,\n 220,\n 269,\n 21370,\n 16002,\n 796,\n 269,\n 21370,\n 13,\n 16002,\n 7,\n 69,\n 11,\n 46728,\n 2676,\n 28,\n 3256,\n 3256,\n 28411,\n 28,\n 40664,\n 13,\n 10917,\n 23051,\n 62,\n 45,\n 1340,\n 41359,\n 1137,\n 2149,\n 8,\n 201,\n 198,\n 220,\n 220,\n 220,\n 329,\n 5752,\n 287,\n 12109,\n 25,\n 201,\n 198,\n 220,\n 220,\n 220,\n 220,\n 220,\n 220,\n 220,\n 269,\n 21370,\n 16002,\n 13,\n 16002,\n 322,\n 7,\n 808,\n 8,\n 220,\n 220,\n 220,\n 220,\n 220,\n 220,\n 220,\n 220,\n 220,\n 220,\n 220,\n 220,\n 220,\n 220,\n 220,\n 220,\n 201,\n 198,\n 220,\n 220,\n 201,\n 198,\n 2,\n 6615,\n 9225,\n 284,\n 4101,\n 4691,\n 262,\n 4007,\n 286,\n 3359,\n 262,\n 12109,\n 290,\n 1553,\n 14125,\n 287,\n 8695,\n 201,\n 198,\n 2,\n 1462,\n 511,\n 12848,\n 2292,\n 1626,\n 262,\n 2858,\n 201,\n 198,\n 220,\n 220,\n 220,\n 220,\n 220,\n 220,\n 220,\n 220,\n 220,\n 220,\n 220,\n 220,\n 220,\n 220,\n 220,\n 220,\n 220,\n 220,\n 220,\n 220,\n 220,\n 220,\n 220,\n 220,\n 220,\n 220,\n 220,\n 220,\n 220,\n 220,\n 201,\n 198,\n 6759,\n 29487,\n 8019,\n 13,\n 9078,\n 29487,\n 13,\n 87,\n 2475,\n 7,\n 15,\n 11,\n 5867,\n 8,\n 201,\n 198,\n 6759,\n 29487,\n 8019,\n 13,\n 9078,\n 29487,\n 13,\n 88,\n 2475,\n 7,\n 15,\n 11,\n 5867,\n 8,\n 201,\n 198,\n 6759,\n 29487,\n 8019,\n 13,\n 9078,\n 29487,\n 13,\n 320,\n 12860,\n 7,\n 43337,\n 8,\n 201,\n 198,\n 201,\n 198,\n 6759,\n 29487,\n 8019,\n 13,\n 9078,\n 29487,\n 13,\n 87,\n 2475,\n 7,\n 15,\n 11,\n 5867,\n 8,\n 201,\n 198,\n 6759,\n 29487,\n 8019,\n 13,\n 9078,\n 29487,\n 13,\n 88,\n 2475,\n 7,\n 15,\n 11,\n 5867,\n 8,\n 201,\n 198,\n 6759,\n 29487,\n 8019,\n 13,\n 9078,\n 29487,\n 13,\n 12860,\n 7,\n 67,\n 5143,\n 591,\n 8,\n 201,\n 198,\n 201,\n 198,\n 201,\n 198,\n 6759,\n 29487,\n 8019,\n 13,\n 9078,\n 29487,\n 13,\n 87,\n 2475,\n 7,\n 15,\n 11,\n 5867,\n 8,\n 201,\n 198,\n 6759,\n 29487,\n 8019,\n 13,\n 9078,\n 29487,\n 13,\n 88,\n 2475,\n 7,\n 15,\n 11,\n 5867,\n 8,\n 201,\n 198,\n 6759,\n 29487,\n 8019,\n 13,\n 9078,\n 29487,\n 13,\n 320,\n 12860,\n 7,\n 38986,\n 8,\n 201,\n 198,\n 201,\n 198,\n 2,\n 10669,\n 2174,\n 655,\n 20842,\n 356,\n 821,\n 1363,\n 329,\n 1123,\n 286,\n 262,\n 1679,\n 6554,\n 1708,\n 257,\n 6323,\n 286,\n 201,\n 198,\n 2,\n 1169,\n 2438,\n 201,\n 198,\n 201,\n 198,\n 1640,\n 1312,\n 287,\n 2837,\n 7,\n 22510,\n 62,\n 1659,\n 62,\n 67,\n 5143,\n 591,\n 2599,\n 201,\n 198,\n 220,\n 220,\n 220,\n 220,\n 220,\n 220,\n 220,\n 2603,\n 29487,\n 8019,\n 13,\n 9078,\n 29487,\n 13,\n 1416,\n 1436,\n 7,\n 67,\n 5143,\n 591,\n 58,\n 72,\n 4083,\n 62,\n 87,\n 11,\n 1553,\n 14125,\n 58,\n 72,\n 4083,\n 62,\n 88,\n 8,\n 201,\n 198,\n 220,\n 220,\n 220,\n 220,\n 220,\n 220,\n 220,\n 3601,\n 7203,\n 732,\n 821,\n 1363,\n 2474,\n 8,\n 220,\n 220,\n 220,\n 220,\n 201,\n 198\n]"},"ratio_char_token":{"kind":"number","value":2.7137014314928427,"string":"2.713701"},"token_count":{"kind":"number","value":1467,"string":"1,467"}}},{"rowIdx":1291,"cells":{"content":{"kind":"string","value":"\"\"\"Loading a .caffemodel and figure out the encoding.\n\nAuthor: Yuhuang Hu\nEmail : duguyue100@gmail.com\n\"\"\"\n\nfrom __future__ import absolute_import\nfrom __future__ import print_function\nimport os\n# from keras.utils.visualize_util import plot\n\nfrom keras.datasets import mnist as dataset\nfrom keras.utils import np_utils\n\nimport transcaffe as tc\n\nbatch_size = 128\nnb_classes = 10\nnb_epoch = 40\n\n# input image dimensions\nimg_rows, img_cols = 28, 28\n# number of convolutional filters to use\nnb_filters = 32\n# size of pooling area for max pooling\nnb_pool = 2\n# convolution kernel size\nnb_conv = 3\n# color channels\nchnls = 1\n\n# the data, shuffled and split between train and test sets\n(X_train, y_train), (X_test, y_test) = dataset.load_data()\n\nX_train = X_train.reshape(X_train.shape[0], chnls, img_rows, img_cols)\nX_test = X_test.reshape(X_test.shape[0], chnls, img_rows, img_cols)\nX_train = X_train.astype(\"float32\")\nX_test = X_test.astype(\"float32\")\nX_train /= 255\nX_test /= 255\n\n# convert class vectors to binary class matrices\nY_train = np_utils.to_categorical(y_train, nb_classes)\nY_test = np_utils.to_categorical(y_test, nb_classes)\n\nprint('X_train shape:', X_train.shape)\nprint(X_train.shape[0], 'train samples')\nprint(X_test.shape[0], 'test samples')\n\n\n# define model for testing\ndata_path = os.environ[\"TRANSCAFFE_DATA\"]\n\n# model_str = os.path.join(data_path,\n# \"VGG_ILSVRC_16_layers_deploy.prototxt.txt\")\nmodel_str = os.path.join(data_path, \"lenet.prototxt.txt\")\nmodel_bin = os.path.join(data_path, \"lenet_iter_10000.caffemodel\")\n\nmodel = tc.load(model_str, model_bin, target_lib=\"keras\")\n\nmodel.compile(loss='categorical_crossentropy', optimizer='adadelta',\n metrics=['accuracy'])\nscore = model.evaluate(X_test, Y_test, verbose=0)\nprint('Test score:', score[0])\nprint('Test accuracy:', score[1])\n"},"input_ids":{"kind":"list like","value":[37811,19031,257,764,66,2001,368,375,417,290,3785,503,262,21004,13,198,198,13838,25,575,7456,84,648,11256,198,15333,1058,18735,4669,518,3064,31,14816,13,785,198,37811,198,198,6738,11593,37443,834,1330,4112,62,11748,198,6738,11593,37443,834,1330,3601,62,8818,198,11748,28686,198,2,422,41927,292,13,26791,13,41464,1096,62,22602,1330,7110,198,198,6738,41927,292,13,19608,292,1039,1330,285,77,396,355,27039,198,6738,41927,292,13,26791,1330,45941,62,26791,198,198,11748,23589,21223,355,37096,198,198,43501,62,7857,796,13108,198,46803,62,37724,796,838,198,46803,62,538,5374,796,2319,198,198,2,5128,2939,15225,198,9600,62,8516,11,33705,62,4033,82,796,2579,11,2579,198,2,1271,286,3063,2122,282,16628,284,779,198,46803,62,10379,1010,796,3933,198,2,2546,286,5933,278,1989,329,3509,5933,278,198,46803,62,7742,796,362,198,2,3063,2122,9720,2546,198,46803,62,42946,796,513,198,2,3124,9619,198,1349,7278,796,352,198,198,2,262,1366,11,32299,992,290,6626,1022,4512,290,1332,5621,198,7,55,62,27432,11,331,62,27432,828,357,55,62,9288,11,331,62,9288,8,796,27039,13,2220,62,7890,3419,198,198,55,62,27432,796,1395,62,27432,13,3447,1758,7,55,62,27432,13,43358,58,15,4357,442,77,7278,11,33705,62,8516,11,33705,62,4033,82,8,198,55,62,9288,796,1395,62,9288,13,3447,1758,7,55,62,9288,13,43358,58,15,4357,442,77,7278,11,33705,62,8516,11,33705,62,4033,82,8,198,55,62,27432,796,1395,62,27432,13,459,2981,7203,22468,2624,4943,198,55,62,9288,796,1395,62,9288,13,459,2981,7203,22468,2624,4943,198,55,62,27432,1220,28,14280,198,55,62,9288,1220,28,14280,198,198,2,10385,1398,30104,284,13934,1398,2603,45977,198,56,62,27432,796,45941,62,26791,13,1462,62,66,2397,12409,7,88,62,27432,11,299,65,62,37724,8,198,56,62,9288,796,45941,62,26791,13,1462,62,66,2397,12409,7,88,62,9288,11,299,65,62,37724,8,198,198,4798,10786,55,62,27432,5485,25,3256,1395,62,27432,13,43358,8,198,4798,7,55,62,27432,13,43358,58,15,4357,705,27432,8405,11537,198,4798,7,55,62,9288,13,43358,58,15,4357,705,9288,8405,11537,628,198,2,8160,2746,329,4856,198,7890,62,6978,796,28686,13,268,2268,14692,5446,1565,6173,32,5777,36,62,26947,8973,198,198,2,2746,62,2536,796,28686,13,6978,13,22179,7,7890,62,6978,11,198,2,220,220,220,220,220,220,220,220,220,220,220,220,220,220,220,220,220,220,220,220,220,220,220,220,220,366,53,11190,62,45484,53,7397,62,1433,62,75,6962,62,2934,1420,13,11235,313,742,13,14116,4943,198,19849,62,2536,796,28686,13,6978,13,22179,7,7890,62,6978,11,366,11925,316,13,11235,313,742,13,14116,4943,198,19849,62,8800,796,28686,13,6978,13,22179,7,7890,62,6978,11,366,11925,316,62,2676,62,49388,13,66,2001,368,375,417,4943,198,198,19849,796,37096,13,2220,7,19849,62,2536,11,2746,62,8800,11,2496,62,8019,2625,6122,292,4943,198,198,19849,13,5589,576,7,22462,11639,66,2397,12409,62,19692,298,28338,3256,6436,7509,11639,324,324,12514,3256,198,220,220,220,220,220,220,220,220,220,220,220,220,220,20731,28,17816,4134,23843,6,12962,198,26675,796,2746,13,49786,7,55,62,9288,11,575,62,9288,11,15942,577,28,15,8,198,4798,10786,14402,4776,25,3256,4776,58,15,12962,198,4798,10786,14402,9922,25,3256,4776,58,16,12962,198],"string":"[\n 37811,\n 19031,\n 257,\n 764,\n 66,\n 2001,\n 368,\n 375,\n 417,\n 290,\n 3785,\n 503,\n 262,\n 21004,\n 13,\n 198,\n 198,\n 13838,\n 25,\n 575,\n 7456,\n 84,\n 648,\n 11256,\n 198,\n 15333,\n 1058,\n 18735,\n 4669,\n 518,\n 3064,\n 31,\n 14816,\n 13,\n 785,\n 198,\n 37811,\n 198,\n 198,\n 6738,\n 11593,\n 37443,\n 834,\n 1330,\n 4112,\n 62,\n 11748,\n 198,\n 6738,\n 11593,\n 37443,\n 834,\n 1330,\n 3601,\n 62,\n 8818,\n 198,\n 11748,\n 28686,\n 198,\n 2,\n 422,\n 41927,\n 292,\n 13,\n 26791,\n 13,\n 41464,\n 1096,\n 62,\n 22602,\n 1330,\n 7110,\n 198,\n 198,\n 6738,\n 41927,\n 292,\n 13,\n 19608,\n 292,\n 1039,\n 1330,\n 285,\n 77,\n 396,\n 355,\n 27039,\n 198,\n 6738,\n 41927,\n 292,\n 13,\n 26791,\n 1330,\n 45941,\n 62,\n 26791,\n 198,\n 198,\n 11748,\n 23589,\n 21223,\n 355,\n 37096,\n 198,\n 198,\n 43501,\n 62,\n 7857,\n 796,\n 13108,\n 198,\n 46803,\n 62,\n 37724,\n 796,\n 838,\n 198,\n 46803,\n 62,\n 538,\n 5374,\n 796,\n 2319,\n 198,\n 198,\n 2,\n 5128,\n 2939,\n 15225,\n 198,\n 9600,\n 62,\n 8516,\n 11,\n 33705,\n 62,\n 4033,\n 82,\n 796,\n 2579,\n 11,\n 2579,\n 198,\n 2,\n 1271,\n 286,\n 3063,\n 2122,\n 282,\n 16628,\n 284,\n 779,\n 198,\n 46803,\n 62,\n 10379,\n 1010,\n 796,\n 3933,\n 198,\n 2,\n 2546,\n 286,\n 5933,\n 278,\n 1989,\n 329,\n 3509,\n 5933,\n 278,\n 198,\n 46803,\n 62,\n 7742,\n 796,\n 362,\n 198,\n 2,\n 3063,\n 2122,\n 9720,\n 2546,\n 198,\n 46803,\n 62,\n 42946,\n 796,\n 513,\n 198,\n 2,\n 3124,\n 9619,\n 198,\n 1349,\n 7278,\n 796,\n 352,\n 198,\n 198,\n 2,\n 262,\n 1366,\n 11,\n 32299,\n 992,\n 290,\n 6626,\n 1022,\n 4512,\n 290,\n 1332,\n 5621,\n 198,\n 7,\n 55,\n 62,\n 27432,\n 11,\n 331,\n 62,\n 27432,\n 828,\n 357,\n 55,\n 62,\n 9288,\n 11,\n 331,\n 62,\n 9288,\n 8,\n 796,\n 27039,\n 13,\n 2220,\n 62,\n 7890,\n 3419,\n 198,\n 198,\n 55,\n 62,\n 27432,\n 796,\n 1395,\n 62,\n 27432,\n 13,\n 3447,\n 1758,\n 7,\n 55,\n 62,\n 27432,\n 13,\n 43358,\n 58,\n 15,\n 4357,\n 442,\n 77,\n 7278,\n 11,\n 33705,\n 62,\n 8516,\n 11,\n 33705,\n 62,\n 4033,\n 82,\n 8,\n 198,\n 55,\n 62,\n 9288,\n 796,\n 1395,\n 62,\n 9288,\n 13,\n 3447,\n 1758,\n 7,\n 55,\n 62,\n 9288,\n 13,\n 43358,\n 58,\n 15,\n 4357,\n 442,\n 77,\n 7278,\n 11,\n 33705,\n 62,\n 8516,\n 11,\n 33705,\n 62,\n 4033,\n 82,\n 8,\n 198,\n 55,\n 62,\n 27432,\n 796,\n 1395,\n 62,\n 27432,\n 13,\n 459,\n 2981,\n 7203,\n 22468,\n 2624,\n 4943,\n 198,\n 55,\n 62,\n 9288,\n 796,\n 1395,\n 62,\n 9288,\n 13,\n 459,\n 2981,\n 7203,\n 22468,\n 2624,\n 4943,\n 198,\n 55,\n 62,\n 27432,\n 1220,\n 28,\n 14280,\n 198,\n 55,\n 62,\n 9288,\n 1220,\n 28,\n 14280,\n 198,\n 198,\n 2,\n 10385,\n 1398,\n 30104,\n 284,\n 13934,\n 1398,\n 2603,\n 45977,\n 198,\n 56,\n 62,\n 27432,\n 796,\n 45941,\n 62,\n 26791,\n 13,\n 1462,\n 62,\n 66,\n 2397,\n 12409,\n 7,\n 88,\n 62,\n 27432,\n 11,\n 299,\n 65,\n 62,\n 37724,\n 8,\n 198,\n 56,\n 62,\n 9288,\n 796,\n 45941,\n 62,\n 26791,\n 13,\n 1462,\n 62,\n 66,\n 2397,\n 12409,\n 7,\n 88,\n 62,\n 9288,\n 11,\n 299,\n 65,\n 62,\n 37724,\n 8,\n 198,\n 198,\n 4798,\n 10786,\n 55,\n 62,\n 27432,\n 5485,\n 25,\n 3256,\n 1395,\n 62,\n 27432,\n 13,\n 43358,\n 8,\n 198,\n 4798,\n 7,\n 55,\n 62,\n 27432,\n 13,\n 43358,\n 58,\n 15,\n 4357,\n 705,\n 27432,\n 8405,\n 11537,\n 198,\n 4798,\n 7,\n 55,\n 62,\n 9288,\n 13,\n 43358,\n 58,\n 15,\n 4357,\n 705,\n 9288,\n 8405,\n 11537,\n 628,\n 198,\n 2,\n 8160,\n 2746,\n 329,\n 4856,\n 198,\n 7890,\n 62,\n 6978,\n 796,\n 28686,\n 13,\n 268,\n 2268,\n 14692,\n 5446,\n 1565,\n 6173,\n 32,\n 5777,\n 36,\n 62,\n 26947,\n 8973,\n 198,\n 198,\n 2,\n 2746,\n 62,\n 2536,\n 796,\n 28686,\n 13,\n 6978,\n 13,\n 22179,\n 7,\n 7890,\n 62,\n 6978,\n 11,\n 198,\n 2,\n 220,\n 220,\n 220,\n 220,\n 220,\n 220,\n 220,\n 220,\n 220,\n 220,\n 220,\n 220,\n 220,\n 220,\n 220,\n 220,\n 220,\n 220,\n 220,\n 220,\n 220,\n 220,\n 220,\n 220,\n 220,\n 366,\n 53,\n 11190,\n 62,\n 45484,\n 53,\n 7397,\n 62,\n 1433,\n 62,\n 75,\n 6962,\n 62,\n 2934,\n 1420,\n 13,\n 11235,\n 313,\n 742,\n 13,\n 14116,\n 4943,\n 198,\n 19849,\n 62,\n 2536,\n 796,\n 28686,\n 13,\n 6978,\n 13,\n 22179,\n 7,\n 7890,\n 62,\n 6978,\n 11,\n 366,\n 11925,\n 316,\n 13,\n 11235,\n 313,\n 742,\n 13,\n 14116,\n 4943,\n 198,\n 19849,\n 62,\n 8800,\n 796,\n 28686,\n 13,\n 6978,\n 13,\n 22179,\n 7,\n 7890,\n 62,\n 6978,\n 11,\n 366,\n 11925,\n 316,\n 62,\n 2676,\n 62,\n 49388,\n 13,\n 66,\n 2001,\n 368,\n 375,\n 417,\n 4943,\n 198,\n 198,\n 19849,\n 796,\n 37096,\n 13,\n 2220,\n 7,\n 19849,\n 62,\n 2536,\n 11,\n 2746,\n 62,\n 8800,\n 11,\n 2496,\n 62,\n 8019,\n 2625,\n 6122,\n 292,\n 4943,\n 198,\n 198,\n 19849,\n 13,\n 5589,\n 576,\n 7,\n 22462,\n 11639,\n 66,\n 2397,\n 12409,\n 62,\n 19692,\n 298,\n 28338,\n 3256,\n 6436,\n 7509,\n 11639,\n 324,\n 324,\n 12514,\n 3256,\n 198,\n 220,\n 220,\n 220,\n 220,\n 220,\n 220,\n 220,\n 220,\n 220,\n 220,\n 220,\n 220,\n 220,\n 20731,\n 28,\n 17816,\n 4134,\n 23843,\n 6,\n 12962,\n 198,\n 26675,\n 796,\n 2746,\n 13,\n 49786,\n 7,\n 55,\n 62,\n 9288,\n 11,\n 575,\n 62,\n 9288,\n 11,\n 15942,\n 577,\n 28,\n 15,\n 8,\n 198,\n 4798,\n 10786,\n 14402,\n 4776,\n 25,\n 3256,\n 4776,\n 58,\n 15,\n 12962,\n 198,\n 4798,\n 10786,\n 14402,\n 9922,\n 25,\n 3256,\n 4776,\n 58,\n 16,\n 12962,\n 198\n]"},"ratio_char_token":{"kind":"number","value":2.5820476858345023,"string":"2.582048"},"token_count":{"kind":"number","value":713,"string":"713"}}},{"rowIdx":1292,"cells":{"content":{"kind":"string","value":"from typing import Dict, List, Optional\n\nfrom kubernetes import client\n\nfrom tlaunch.lp_k8s.resource import Resource\nfrom tlaunch.lp_k8s.util import map_opt\n\nDEFAULT_PORT = 8001\nDEFAULT_NAME = 'launchpad'\nREVERB_IMAGE = 'reg.real-ai.cn/launchpad/reverb'\nDEFAULT_COMMAND = ['python3', '-u', '-mlaunchpad_kubernetes.process_entry']\n\n\n\n"},"input_ids":{"kind":"list like","value":[6738,19720,1330,360,713,11,7343,11,32233,198,198,6738,479,18478,3262,274,1330,5456,198,198,6738,256,35681,13,34431,62,74,23,82,13,31092,1330,20857,198,6738,256,35681,13,34431,62,74,23,82,13,22602,1330,3975,62,8738,198,198,7206,38865,62,15490,796,807,8298,198,7206,38865,62,20608,796,705,35681,15636,6,198,2200,5959,33,62,3955,11879,796,705,2301,13,5305,12,1872,13,31522,14,35681,15636,14,260,19011,6,198,7206,38865,62,9858,44,6981,796,37250,29412,18,3256,705,12,84,3256,705,12,4029,11429,15636,62,74,18478,3262,274,13,14681,62,13000,20520,628,628],"string":"[\n 6738,\n 19720,\n 1330,\n 360,\n 713,\n 11,\n 7343,\n 11,\n 32233,\n 198,\n 198,\n 6738,\n 479,\n 18478,\n 3262,\n 274,\n 1330,\n 5456,\n 198,\n 198,\n 6738,\n 256,\n 35681,\n 13,\n 34431,\n 62,\n 74,\n 23,\n 82,\n 13,\n 31092,\n 1330,\n 20857,\n 198,\n 6738,\n 256,\n 35681,\n 13,\n 34431,\n 62,\n 74,\n 23,\n 82,\n 13,\n 22602,\n 1330,\n 3975,\n 62,\n 8738,\n 198,\n 198,\n 7206,\n 38865,\n 62,\n 15490,\n 796,\n 807,\n 8298,\n 198,\n 7206,\n 38865,\n 62,\n 20608,\n 796,\n 705,\n 35681,\n 15636,\n 6,\n 198,\n 2200,\n 5959,\n 33,\n 62,\n 3955,\n 11879,\n 796,\n 705,\n 2301,\n 13,\n 5305,\n 12,\n 1872,\n 13,\n 31522,\n 14,\n 35681,\n 15636,\n 14,\n 260,\n 19011,\n 6,\n 198,\n 7206,\n 38865,\n 62,\n 9858,\n 44,\n 6981,\n 796,\n 37250,\n 29412,\n 18,\n 3256,\n 705,\n 12,\n 84,\n 3256,\n 705,\n 12,\n 4029,\n 11429,\n 15636,\n 62,\n 74,\n 18478,\n 3262,\n 274,\n 13,\n 14681,\n 62,\n 13000,\n 20520,\n 628,\n 628\n]"},"ratio_char_token":{"kind":"number","value":2.685483870967742,"string":"2.685484"},"token_count":{"kind":"number","value":124,"string":"124"}}},{"rowIdx":1293,"cells":{"content":{"kind":"string","value":"\"\"\"Retry downloading files that caused errors in http_downloader.\nWe can find files to try downloading again by parsing the err.txt file for error messages.\nError log lines we are interested in look like:\n\n09-04-2017 12:45:17..Error_http_downloader 'exports/CalStateTEACH Term 1/grios/Schedule/Mentor Info.docx', 'https://ourdomain.instructure.com/files/8080/download?download_frd=1&verifier=zVZdnkpTmmJIGYAg2U0PaDqESrJBFLi0Xsm73Eldu'\n\nA regex string that captures the file name & URL looks like:\n\n[0-9][0-9]-[0-9][0-9]-[0-9][0-9][0-9][0-9] [0-9][0-9]:[0-9][0-9]:[0-9][0-9]\\.\\.Error_http_downloader '(.*)', '(.*)'$\n\n09.04.2017 tps Created.\n09.17.2018 tps Change bad global Null reference to None.\n\"\"\"\nimport script_logging\nimport http_downloader\nimport os\nimport re\nimport shutil\n\n\n######### Constants #########\n\n# Regex pattern for extracting file download details from error log.\nREGEX_PATTERN = \"[0-9][0-9]-[0-9][0-9]-[0-9][0-9][0-9][0-9] [0-9][0-9]:[0-9][0-9]:[0-9][0-9]\\.\\.Error_http_downloader '(.*)', '(.*)'$\"\n \n\ndef make_cp_file_name():\n \"\"\"Create a unique file that looks like \"retry000.txt\", \"retry001.txt\", \n \"retry002.txt\", etc.\n \"\"\"\n\n cp_file_name = None # Function return variable\n n = 0\n while True:\n cp_file_name = 'retry%03d.txt' % n\n if (not os.path.exists(cp_file_name)):\n break \n else:\n n = n + 1\n continue\n\n return cp_file_name\n\n\n\n\n######### Stand-Alone Execution #########\n\nif __name__ == \"__main__\":\n load_errors()\n"},"input_ids":{"kind":"list like","value":[37811,9781,563,22023,3696,326,4073,8563,287,2638,62,15002,263,13,198,1135,460,1064,3696,284,1949,22023,757,416,32096,262,11454,13,14116,2393,329,4049,6218,13,198,12331,2604,3951,356,389,4609,287,804,588,25,198,198,2931,12,3023,12,5539,1105,25,2231,25,1558,492,12331,62,4023,62,15002,263,705,1069,3742,14,9771,9012,9328,16219,35118,352,14,70,380,418,14,27054,5950,14,44,298,273,14151,13,15390,87,3256,705,5450,1378,454,27830,13,8625,5620,13,785,14,16624,14,1795,1795,14,15002,30,15002,62,69,4372,28,16,5,332,7483,28,89,53,57,32656,74,79,51,3020,41,3528,56,10262,17,52,15,28875,35,80,1546,81,47858,3697,72,15,55,5796,4790,36,335,84,6,198,198,32,40364,4731,326,23007,262,2393,1438,1222,10289,3073,588,25,198,198,58,15,12,24,7131,15,12,24,45297,58,15,12,24,7131,15,12,24,45297,58,15,12,24,7131,15,12,24,7131,15,12,24,7131,15,12,24,60,685,15,12,24,7131,15,12,24,5974,58,15,12,24,7131,15,12,24,5974,58,15,12,24,7131,15,12,24,60,17405,17405,12331,62,4023,62,15002,263,29513,15885,8,3256,29513,15885,33047,3,198,198,2931,13,3023,13,5539,256,862,15622,13,198,2931,13,1558,13,7908,256,862,9794,2089,3298,35886,4941,284,6045,13,198,37811,198,11748,4226,62,6404,2667,198,11748,2638,62,15002,263,198,11748,28686,198,11748,302,198,11748,4423,346,628,198,7804,2,4757,1187,1303,7804,198,198,2,797,25636,3912,329,37895,2393,4321,3307,422,4049,2604,13,198,31553,6369,62,47,1404,31800,796,12878,15,12,24,7131,15,12,24,45297,58,15,12,24,7131,15,12,24,45297,58,15,12,24,7131,15,12,24,7131,15,12,24,7131,15,12,24,60,685,15,12,24,7131,15,12,24,5974,58,15,12,24,7131,15,12,24,5974,58,15,12,24,7131,15,12,24,60,17405,17405,12331,62,4023,62,15002,263,29513,15885,8,3256,29513,15885,33047,3,1,198,220,198,198,4299,787,62,13155,62,7753,62,3672,33529,198,220,220,220,37227,16447,257,3748,2393,326,3073,588,366,1186,563,830,13,14116,1600,366,1186,563,8298,13,14116,1600,220,198,220,220,220,366,1186,563,21601,13,14116,1600,3503,13,198,220,220,220,37227,628,220,220,220,31396,62,7753,62,3672,796,6045,220,1303,15553,1441,7885,198,220,220,220,299,796,657,198,220,220,220,981,6407,25,198,220,220,220,220,220,220,220,31396,62,7753,62,3672,796,705,1186,563,4,3070,67,13,14116,6,4064,299,198,220,220,220,220,220,220,220,611,357,1662,28686,13,6978,13,1069,1023,7,13155,62,7753,62,3672,8,2599,198,220,220,220,220,220,220,220,220,220,220,220,2270,220,198,220,220,220,220,220,220,220,2073,25,198,220,220,220,220,220,220,220,220,220,220,220,299,796,299,1343,352,198,220,220,220,220,220,220,220,220,220,220,220,2555,628,220,220,220,1441,31396,62,7753,62,3672,628,628,198,7804,2,5751,12,2348,505,37497,1303,7804,198,198,361,11593,3672,834,6624,366,834,12417,834,1298,198,220,220,220,3440,62,48277,3419,198],"string":"[\n 37811,\n 9781,\n 563,\n 22023,\n 3696,\n 326,\n 4073,\n 8563,\n 287,\n 2638,\n 62,\n 15002,\n 263,\n 13,\n 198,\n 1135,\n 460,\n 1064,\n 3696,\n 284,\n 1949,\n 22023,\n 757,\n 416,\n 32096,\n 262,\n 11454,\n 13,\n 14116,\n 2393,\n 329,\n 4049,\n 6218,\n 13,\n 198,\n 12331,\n 2604,\n 3951,\n 356,\n 389,\n 4609,\n 287,\n 804,\n 588,\n 25,\n 198,\n 198,\n 2931,\n 12,\n 3023,\n 12,\n 5539,\n 1105,\n 25,\n 2231,\n 25,\n 1558,\n 492,\n 12331,\n 62,\n 4023,\n 62,\n 15002,\n 263,\n 705,\n 1069,\n 3742,\n 14,\n 9771,\n 9012,\n 9328,\n 16219,\n 35118,\n 352,\n 14,\n 70,\n 380,\n 418,\n 14,\n 27054,\n 5950,\n 14,\n 44,\n 298,\n 273,\n 14151,\n 13,\n 15390,\n 87,\n 3256,\n 705,\n 5450,\n 1378,\n 454,\n 27830,\n 13,\n 8625,\n 5620,\n 13,\n 785,\n 14,\n 16624,\n 14,\n 1795,\n 1795,\n 14,\n 15002,\n 30,\n 15002,\n 62,\n 69,\n 4372,\n 28,\n 16,\n 5,\n 332,\n 7483,\n 28,\n 89,\n 53,\n 57,\n 32656,\n 74,\n 79,\n 51,\n 3020,\n 41,\n 3528,\n 56,\n 10262,\n 17,\n 52,\n 15,\n 28875,\n 35,\n 80,\n 1546,\n 81,\n 47858,\n 3697,\n 72,\n 15,\n 55,\n 5796,\n 4790,\n 36,\n 335,\n 84,\n 6,\n 198,\n 198,\n 32,\n 40364,\n 4731,\n 326,\n 23007,\n 262,\n 2393,\n 1438,\n 1222,\n 10289,\n 3073,\n 588,\n 25,\n 198,\n 198,\n 58,\n 15,\n 12,\n 24,\n 7131,\n 15,\n 12,\n 24,\n 45297,\n 58,\n 15,\n 12,\n 24,\n 7131,\n 15,\n 12,\n 24,\n 45297,\n 58,\n 15,\n 12,\n 24,\n 7131,\n 15,\n 12,\n 24,\n 7131,\n 15,\n 12,\n 24,\n 7131,\n 15,\n 12,\n 24,\n 60,\n 685,\n 15,\n 12,\n 24,\n 7131,\n 15,\n 12,\n 24,\n 5974,\n 58,\n 15,\n 12,\n 24,\n 7131,\n 15,\n 12,\n 24,\n 5974,\n 58,\n 15,\n 12,\n 24,\n 7131,\n 15,\n 12,\n 24,\n 60,\n 17405,\n 17405,\n 12331,\n 62,\n 4023,\n 62,\n 15002,\n 263,\n 29513,\n 15885,\n 8,\n 3256,\n 29513,\n 15885,\n 33047,\n 3,\n 198,\n 198,\n 2931,\n 13,\n 3023,\n 13,\n 5539,\n 256,\n 862,\n 15622,\n 13,\n 198,\n 2931,\n 13,\n 1558,\n 13,\n 7908,\n 256,\n 862,\n 9794,\n 2089,\n 3298,\n 35886,\n 4941,\n 284,\n 6045,\n 13,\n 198,\n 37811,\n 198,\n 11748,\n 4226,\n 62,\n 6404,\n 2667,\n 198,\n 11748,\n 2638,\n 62,\n 15002,\n 263,\n 198,\n 11748,\n 28686,\n 198,\n 11748,\n 302,\n 198,\n 11748,\n 4423,\n 346,\n 628,\n 198,\n 7804,\n 2,\n 4757,\n 1187,\n 1303,\n 7804,\n 198,\n 198,\n 2,\n 797,\n 25636,\n 3912,\n 329,\n 37895,\n 2393,\n 4321,\n 3307,\n 422,\n 4049,\n 2604,\n 13,\n 198,\n 31553,\n 6369,\n 62,\n 47,\n 1404,\n 31800,\n 796,\n 12878,\n 15,\n 12,\n 24,\n 7131,\n 15,\n 12,\n 24,\n 45297,\n 58,\n 15,\n 12,\n 24,\n 7131,\n 15,\n 12,\n 24,\n 45297,\n 58,\n 15,\n 12,\n 24,\n 7131,\n 15,\n 12,\n 24,\n 7131,\n 15,\n 12,\n 24,\n 7131,\n 15,\n 12,\n 24,\n 60,\n 685,\n 15,\n 12,\n 24,\n 7131,\n 15,\n 12,\n 24,\n 5974,\n 58,\n 15,\n 12,\n 24,\n 7131,\n 15,\n 12,\n 24,\n 5974,\n 58,\n 15,\n 12,\n 24,\n 7131,\n 15,\n 12,\n 24,\n 60,\n 17405,\n 17405,\n 12331,\n 62,\n 4023,\n 62,\n 15002,\n 263,\n 29513,\n 15885,\n 8,\n 3256,\n 29513,\n 15885,\n 33047,\n 3,\n 1,\n 198,\n 220,\n 198,\n 198,\n 4299,\n 787,\n 62,\n 13155,\n 62,\n 7753,\n 62,\n 3672,\n 33529,\n 198,\n 220,\n 220,\n 220,\n 37227,\n 16447,\n 257,\n 3748,\n 2393,\n 326,\n 3073,\n 588,\n 366,\n 1186,\n 563,\n 830,\n 13,\n 14116,\n 1600,\n 366,\n 1186,\n 563,\n 8298,\n 13,\n 14116,\n 1600,\n 220,\n 198,\n 220,\n 220,\n 220,\n 366,\n 1186,\n 563,\n 21601,\n 13,\n 14116,\n 1600,\n 3503,\n 13,\n 198,\n 220,\n 220,\n 220,\n 37227,\n 628,\n 220,\n 220,\n 220,\n 31396,\n 62,\n 7753,\n 62,\n 3672,\n 796,\n 6045,\n 220,\n 1303,\n 15553,\n 1441,\n 7885,\n 198,\n 220,\n 220,\n 220,\n 299,\n 796,\n 657,\n 198,\n 220,\n 220,\n 220,\n 981,\n 6407,\n 25,\n 198,\n 220,\n 220,\n 220,\n 220,\n 220,\n 220,\n 220,\n 31396,\n 62,\n 7753,\n 62,\n 3672,\n 796,\n 705,\n 1186,\n 563,\n 4,\n 3070,\n 67,\n 13,\n 14116,\n 6,\n 4064,\n 299,\n 198,\n 220,\n 220,\n 220,\n 220,\n 220,\n 220,\n 220,\n 611,\n 357,\n 1662,\n 28686,\n 13,\n 6978,\n 13,\n 1069,\n 1023,\n 7,\n 13155,\n 62,\n 7753,\n 62,\n 3672,\n 8,\n 2599,\n 198,\n 220,\n 220,\n 220,\n 220,\n 220,\n 220,\n 220,\n 220,\n 220,\n 220,\n 220,\n 2270,\n 220,\n 198,\n 220,\n 220,\n 220,\n 220,\n 220,\n 220,\n 220,\n 2073,\n 25,\n 198,\n 220,\n 220,\n 220,\n 220,\n 220,\n 220,\n 220,\n 220,\n 220,\n 220,\n 220,\n 299,\n 796,\n 299,\n 1343,\n 352,\n 198,\n 220,\n 220,\n 220,\n 220,\n 220,\n 220,\n 220,\n 220,\n 220,\n 220,\n 220,\n 2555,\n 628,\n 220,\n 220,\n 220,\n 1441,\n 31396,\n 62,\n 7753,\n 62,\n 3672,\n 628,\n 628,\n 198,\n 7804,\n 2,\n 5751,\n 12,\n 2348,\n 505,\n 37497,\n 1303,\n 7804,\n 198,\n 198,\n 361,\n 11593,\n 3672,\n 834,\n 6624,\n 366,\n 834,\n 12417,\n 834,\n 1298,\n 198,\n 220,\n 220,\n 220,\n 3440,\n 62,\n 48277,\n 3419,\n 198\n]"},"ratio_char_token":{"kind":"number","value":2.3703125,"string":"2.370313"},"token_count":{"kind":"number","value":640,"string":"640"}}},{"rowIdx":1294,"cells":{"content":{"kind":"string","value":"from nltk import RegexpTokenizer\n\n# Common stopwords in french and english\n\n# Clean text or sentence, removing stopwords\n# return list\n"},"input_ids":{"kind":"list like","value":[6738,299,2528,74,1330,797,25636,79,30642,7509,198,198,2,8070,2245,10879,287,48718,290,46932,198,198,2,5985,2420,393,6827,11,10829,2245,10879,198,2,1441,1351,198],"string":"[\n 6738,\n 299,\n 2528,\n 74,\n 1330,\n 797,\n 25636,\n 79,\n 30642,\n 7509,\n 198,\n 198,\n 2,\n 8070,\n 2245,\n 10879,\n 287,\n 48718,\n 290,\n 46932,\n 198,\n 198,\n 2,\n 5985,\n 2420,\n 393,\n 6827,\n 11,\n 10829,\n 2245,\n 10879,\n 198,\n 2,\n 1441,\n 1351,\n 198\n]"},"ratio_char_token":{"kind":"number","value":3.75,"string":"3.75"},"token_count":{"kind":"number","value":36,"string":"36"}}},{"rowIdx":1295,"cells":{"content":{"kind":"string","value":"import random\nfrom enum import Enum\n\nimport numpy as np\n\nfrom custom_decorators import profile\nfrom shapes import Box\nfrom shared_constants import BBREG_MULTIPLIERS, DEFAULT_ANCHORS\nfrom util import calc_iou, cross_ious, get_reg_params, get_bbox_coords\n\nPOS_OVERLAP = 0.7\nNEG_OVERLAP = 0.3\n\nSAMPLE_SIZE = 256\nMAX_POS_SAMPLES = 128\n\n\n\nclass RpnTrainingManager:\n \"\"\"\n Encapsulates the details of generating training inputs for a region proposal network for a given image.\n \"\"\"\n\n def __init__(self, calc_conv_dims, stride, preprocess_func, anchor_dims=DEFAULT_ANCHORS):\n \"\"\"\n :param calc_conv_dims: function that accepts a tuple of the image's height and width in pixels and returns the\n height and width of the convolutional layer prior to the rpn layers.\n :param stride: positive integer, the cumulative stride at the convolutional layer prior to the rpn layers.\n :param preprocess_func: function that applies the same transformation to the image's pixels as used for Imagenet\n training. Otherwise the Imagenet pre-trained weights will be mismatched.\n :param anchor_dims: list of lists of positive integers, one height and width pair for each anchor.\n \"\"\"\n self._cache = {}\n self.calc_conv_dims = calc_conv_dims\n self.stride = stride\n self.preprocess_func = preprocess_func\n self.anchor_dims = anchor_dims\n\n @profile\n def batched_image(self, image):\n \"\"\"\n Returns the image data to be fed into the network.\n :param image: shapes.Image object.\n :return: 4-d numpy array with a single batch of the image, should can be used as a Keras model input.\n \"\"\"\n return np.expand_dims(self.preprocess_func(image.data), axis=0)\n\n @profile\n\n @profile\n def rpn_y_true(self, image):\n \"\"\"\n Takes an image and returns the Keras model inputs to train with.\n :param image: shapes.Image object to generate training inputs for.\n :return: tuple where the first element is a numpy array of the ground truth network output for whether each\n anchor overlaps with an object, and the second element is a numpy array of the ground truth network output for the\n bounding box transformation parameters to transform each anchor into an object's bounding box.\n \"\"\"\n '''\n Consider removing caching - added when self.process was taking 0.4s to run. Since then, optimized it down to\n 0.02s locally, 0.003s on aws so the cache isn't too useful anymore.\n '''\n if image.cache_key not in self._cache:\n self._process(image)\n\n results = self._cache[image.cache_key]\n # TODO: why is the cached result being deleted? Investigate whether restoring it improves training time.\n del self._cache[image.cache_key]\n can_use = _apply_sampling(results['is_pos'], results['can_use'])\n conv_rows, conv_cols = self.calc_conv_dims(image.height, image.width)\n\n is_pos = np.reshape(results['is_pos'], (conv_rows, conv_cols, len(self.anchor_dims)))\n can_use = np.reshape(can_use, (conv_rows, conv_cols, len(self.anchor_dims)))\n selected_is_pos = np.logical_and(is_pos, can_use)\n\n # combine arrays with whether or not to use for the loss function\n y_class = np.concatenate([can_use, is_pos], axis=2)\n bbreg_can_use = np.repeat(selected_is_pos, 4, axis = 2)\n bbreg_targets = np.reshape(results['bbreg_targets'], (conv_rows, conv_cols, 4 * len(self.anchor_dims)))\n y_bbreg = np.concatenate([bbreg_can_use, bbreg_targets], axis = 2)\n\n y_class = np.expand_dims(y_class, axis=0)\n y_bbreg = np.expand_dims(y_bbreg, axis=0)\n\n return y_class, y_bbreg\n\n\ndef _idx_to_conv(idx, conv_width, anchors_per_loc):\n \"\"\"\n Converts an anchor box index in a 1-d numpy array to its corresponding 3-d index representing its convolution\n position and anchor index.\n :param idx: non-negative integer, the position in a 1-d numpy array of anchors.\n :param conv_width: the number of possible horizontal positions the convolutional layer's filters can occupy, i.e.\n close to the width in pixels divided by the cumulative stride at that layer.\n :param anchors_per_loc: positive integer, the number of anchors at each convolutional filter position.\n :return: tuple of the row, column, and anchor index of the convolutional filter position for this index.\n \"\"\"\n divisor = conv_width * anchors_per_loc\n y, remainder = idx // divisor, idx % divisor\n x, anchor_idx = remainder // anchors_per_loc, remainder % anchors_per_loc\n return y, x, anchor_idx\n\n\n@profile\n\n\ndef _get_conv_center(conv_x, conv_y, stride):\n \"\"\"\n Finds the center of this convolution position in the image's original coordinate space.\n :param conv_x: non-negative integer, x coordinate of the convolution position.\n :param conv_y: non-negative integer, y coordinate of the convolution position.\n :param stride: positive integer, the cumulative stride in pixels at this layer of the network.\n :return: tuple of positive integers, the x and y coordinates of the center of the convolution position.\n \"\"\"\n x_center = stride * (conv_x + 0.5)\n y_center = stride * (conv_y + 0.5)\n\n return int(x_center), int(y_center)\n\n\n@profile\n\n\n@profile\n\n\n@profile\n\n\n@profile\n# this function was a huge bottleneck so threw away box abstractions to optimize performance\n\n\n@profile\ndef _get_all_anchor_coords(conv_rows, conv_cols, anchor_dims, stride):\n \"\"\"\n Given the shape of a convolutional layer and the anchors to generate for each position, return all anchors.\n :param conv_rows: positive integer, height of this convolutional layer.\n :param conv_cols: positive integer, width of this convolutional layer.\n :param anchor_dims: list of lists of positive integers, one height and width pair for each anchor.\n :param stride: positive integer, cumulative stride of this anchor position in pixels.\n :return: 2-d numpy array with one row for each anchor box containing its [x1, y1, x2, y2] coordinates.\n \"\"\"\n num_boxes = conv_rows * conv_cols * len(anchor_dims)\n\n y, x, anchor_idxs = _num_boxes_to_conv_np(num_boxes, conv_cols, len(anchor_dims))\n x_center, y_center = _get_conv_center_np(x, y, stride)\n anchor_coords = np.zeros((num_boxes, 4), dtype=np.float32)\n anchor_height = anchor_dims[anchor_idxs, 0]\n anchor_width = anchor_dims[anchor_idxs, 1]\n\n anchor_coords[:, 0] = x_center - anchor_width // 2\n anchor_coords[:, 1] = y_center - anchor_height // 2\n anchor_coords[:, 2] = anchor_coords[:, 0] + anchor_width\n anchor_coords[:, 3] = anchor_coords[:, 1] + anchor_height\n\n return anchor_coords\n\n\n@profile\n\n\n\n\n@profile\ndef _apply_sampling(is_pos, can_use):\n \"\"\"\n Applies the sampling logic described in the Faster R-CNN paper to determine which anchors should be evaluated in the\n loss function.\n :param is_pos: 1-d numpy array of booleans for whether each anchor is a true positive for some object.\n :param can_use: 1-d numpy array of booleans for whether each anchor can be used at all in the loss function.\n :return: 1-d numpy array of booleans of which anchors were chosen to be used in the loss function.\n \"\"\"\n # extract [0] due to np.where returning a tuple\n pos_locs = np.where(np.logical_and(is_pos == 1, can_use == 1))[0]\n neg_locs = np.where(np.logical_and(is_pos == 0, can_use == 1))[0]\n\n num_pos = len(pos_locs)\n num_neg = len(neg_locs)\n\n # cap the number of positive samples per batch to no more than half the batch size\n if num_pos > MAX_POS_SAMPLES:\n locs_off = random.sample(range(num_pos), num_pos - MAX_POS_SAMPLES)\n can_use[pos_locs[locs_off]] = 0\n num_pos = MAX_POS_SAMPLES\n\n # fill remaining portion of the batch size with negative samples\n if num_neg + num_pos > SAMPLE_SIZE:\n locs_off = random.sample(range(num_neg), num_neg + num_pos - SAMPLE_SIZE)\n can_use[neg_locs[locs_off]] = 0\n\n return can_use\n"},"input_ids":{"kind":"list like","value":[11748,4738,198,6738,33829,1330,2039,388,198,198,11748,299,32152,355,45941,198,198,6738,2183,62,12501,273,2024,1330,7034,198,6738,15268,1330,8315,198,6738,4888,62,9979,1187,1330,12597,31553,62,44,16724,4061,31271,4877,11,5550,38865,62,1565,3398,20673,198,6738,7736,1330,42302,62,72,280,11,3272,62,699,11,651,62,2301,62,37266,11,651,62,65,3524,62,1073,3669,198,198,37997,62,41983,43,2969,796,657,13,22,198,45,7156,62,41983,43,2969,796,657,13,18,198,198,49302,16437,62,33489,796,17759,198,22921,62,37997,62,49302,6489,1546,796,13108,628,198,198,4871,371,21999,44357,13511,25,198,220,220,220,37227,198,220,220,220,14711,1686,15968,262,3307,286,15453,3047,17311,329,257,3814,6961,3127,329,257,1813,2939,13,198,220,220,220,37227,628,220,220,220,825,11593,15003,834,7,944,11,42302,62,42946,62,67,12078,11,33769,11,662,14681,62,20786,11,18021,62,67,12078,28,7206,38865,62,1565,3398,20673,2599,198,220,220,220,220,220,220,220,37227,198,220,220,220,220,220,220,220,1058,17143,42302,62,42946,62,67,12078,25,2163,326,18178,257,46545,286,262,2939,338,6001,290,9647,287,17848,290,5860,262,198,220,220,220,220,220,220,220,6001,290,9647,286,262,3063,2122,282,7679,3161,284,262,374,21999,11685,13,198,220,220,220,220,220,220,220,1058,17143,33769,25,3967,18253,11,262,23818,33769,379,262,3063,2122,282,7679,3161,284,262,374,21999,11685,13,198,220,220,220,220,220,220,220,1058,17143,662,14681,62,20786,25,2163,326,8991,262,976,13389,284,262,2939,338,17848,355,973,329,1846,11286,316,198,220,220,220,220,220,220,220,3047,13,15323,262,1846,11286,316,662,12,35311,19590,481,307,32691,14265,13,198,220,220,220,220,220,220,220,1058,17143,18021,62,67,12078,25,1351,286,8341,286,3967,37014,11,530,6001,290,9647,5166,329,1123,18021,13,198,220,220,220,220,220,220,220,37227,198,220,220,220,220,220,220,220,2116,13557,23870,796,23884,198,220,220,220,220,220,220,220,2116,13,9948,66,62,42946,62,67,12078,796,42302,62,42946,62,67,12078,198,220,220,220,220,220,220,220,2116,13,2536,485,796,33769,198,220,220,220,220,220,220,220,2116,13,3866,14681,62,20786,796,662,14681,62,20786,198,220,220,220,220,220,220,220,2116,13,3702,273,62,67,12078,796,18021,62,67,12078,628,220,220,220,2488,13317,198,220,220,220,825,7365,1740,62,9060,7,944,11,2939,2599,198,220,220,220,220,220,220,220,37227,198,220,220,220,220,220,220,220,16409,262,2939,1366,284,307,11672,656,262,3127,13,198,220,220,220,220,220,220,220,1058,17143,2939,25,15268,13,5159,2134,13,198,220,220,220,220,220,220,220,1058,7783,25,604,12,67,299,32152,7177,351,257,2060,15458,286,262,2939,11,815,460,307,973,355,257,17337,292,2746,5128,13,198,220,220,220,220,220,220,220,37227,198,220,220,220,220,220,220,220,1441,45941,13,11201,392,62,67,12078,7,944,13,3866,14681,62,20786,7,9060,13,7890,828,16488,28,15,8,628,220,220,220,2488,13317,628,220,220,220,2488,13317,198,220,220,220,825,374,21999,62,88,62,7942,7,944,11,2939,2599,198,220,220,220,220,220,220,220,37227,198,220,220,220,220,220,220,220,33687,281,2939,290,5860,262,17337,292,2746,17311,284,4512,351,13,198,220,220,220,220,220,220,220,1058,17143,2939,25,15268,13,5159,2134,284,7716,3047,17311,329,13,198,220,220,220,220,220,220,220,1058,7783,25,46545,810,262,717,5002,318,257,299,32152,7177,286,262,2323,3872,3127,5072,329,1771,1123,198,220,220,220,220,220,220,220,18021,12893,1686,351,281,2134,11,290,262,1218,5002,318,257,299,32152,7177,286,262,2323,3872,3127,5072,329,262,198,220,220,220,220,220,220,220,5421,278,3091,13389,10007,284,6121,1123,18021,656,281,2134,338,5421,278,3091,13,198,220,220,220,220,220,220,220,37227,198,220,220,220,220,220,220,220,705,7061,198,220,220,220,220,220,220,220,12642,10829,40918,532,2087,618,2116,13,14681,373,2263,657,13,19,82,284,1057,13,4619,788,11,23392,340,866,284,198,220,220,220,220,220,220,220,657,13,2999,82,15726,11,657,13,11245,82,319,3253,82,523,262,12940,2125,470,1165,4465,7471,13,198,220,220,220,220,220,220,220,705,7061,198,220,220,220,220,220,220,220,611,2939,13,23870,62,2539,407,287,2116,13557,23870,25,198,220,220,220,220,220,220,220,220,220,220,220,2116,13557,14681,7,9060,8,628,220,220,220,220,220,220,220,2482,796,2116,13557,23870,58,9060,13,23870,62,2539,60,198,220,220,220,220,220,220,220,1303,16926,46,25,1521,318,262,39986,1255,852,13140,30,7488,10055,1771,25646,340,19575,3047,640,13,198,220,220,220,220,220,220,220,1619,2116,13557,23870,58,9060,13,23870,62,2539,60,198,220,220,220,220,220,220,220,460,62,1904,796,4808,39014,62,37687,11347,7,43420,17816,271,62,1930,6,4357,2482,17816,5171,62,1904,6,12962,198,220,220,220,220,220,220,220,3063,62,8516,11,3063,62,4033,82,796,2116,13,9948,66,62,42946,62,67,12078,7,9060,13,17015,11,2939,13,10394,8,628,220,220,220,220,220,220,220,318,62,1930,796,45941,13,3447,1758,7,43420,17816,271,62,1930,6,4357,357,42946,62,8516,11,3063,62,4033,82,11,18896,7,944,13,3702,273,62,67,12078,22305,198,220,220,220,220,220,220,220,460,62,1904,796,45941,13,3447,1758,7,5171,62,1904,11,357,42946,62,8516,11,3063,62,4033,82,11,18896,7,944,13,3702,273,62,67,12078,22305,198,220,220,220,220,220,220,220,6163,62,271,62,1930,796,45941,13,6404,605,62,392,7,271,62,1930,11,460,62,1904,8,628,220,220,220,220,220,220,220,1303,12082,26515,351,1771,393,407,284,779,329,262,2994,2163,198,220,220,220,220,220,220,220,331,62,4871,796,45941,13,1102,9246,268,378,26933,5171,62,1904,11,318,62,1930,4357,16488,28,17,8,198,220,220,220,220,220,220,220,275,65,2301,62,5171,62,1904,796,45941,13,44754,7,34213,62,271,62,1930,11,604,11,16488,796,362,8,198,220,220,220,220,220,220,220,275,65,2301,62,83,853,1039,796,45941,13,3447,1758,7,43420,17816,11848,2301,62,83,853,1039,6,4357,357,42946,62,8516,11,3063,62,4033,82,11,604,1635,18896,7,944,13,3702,273,62,67,12078,22305,198,220,220,220,220,220,220,220,331,62,11848,2301,796,45941,13,1102,9246,268,378,26933,11848,2301,62,5171,62,1904,11,275,65,2301,62,83,853,1039,4357,16488,796,362,8,628,220,220,220,220,220,220,220,331,62,4871,796,45941,13,11201,392,62,67,12078,7,88,62,4871,11,16488,28,15,8,198,220,220,220,220,220,220,220,331,62,11848,2301,796,45941,13,11201,392,62,67,12078,7,88,62,11848,2301,11,16488,28,15,8,628,220,220,220,220,220,220,220,1441,331,62,4871,11,331,62,11848,2301,628,198,4299,4808,312,87,62,1462,62,42946,7,312,87,11,3063,62,10394,11,43360,62,525,62,17946,2599,198,220,220,220,37227,198,220,220,220,1482,24040,281,18021,3091,6376,287,257,352,12,67,299,32152,7177,284,663,11188,513,12,67,6376,10200,663,3063,2122,198,220,220,220,2292,290,18021,6376,13,198,220,220,220,1058,17143,4686,87,25,1729,12,31591,18253,11,262,2292,287,257,352,12,67,299,32152,7177,286,43360,13,198,220,220,220,1058,17143,3063,62,10394,25,262,1271,286,1744,16021,6116,262,3063,2122,282,7679,338,16628,460,22265,11,1312,13,68,13,198,220,220,220,1969,284,262,9647,287,17848,9086,416,262,23818,33769,379,326,7679,13,198,220,220,220,1058,17143,43360,62,525,62,17946,25,3967,18253,11,262,1271,286,43360,379,1123,3063,2122,282,8106,2292,13,198,220,220,220,1058,7783,25,46545,286,262,5752,11,5721,11,290,18021,6376,286,262,3063,2122,282,8106,2292,329,428,6376,13,198,220,220,220,37227,198,220,220,220,2659,271,273,796,3063,62,10394,1635,43360,62,525,62,17946,198,220,220,220,331,11,17675,796,4686,87,3373,2659,271,273,11,4686,87,4064,2659,271,273,198,220,220,220,2124,11,18021,62,312,87,796,17675,3373,43360,62,525,62,17946,11,17675,4064,43360,62,525,62,17946,198,220,220,220,1441,331,11,2124,11,18021,62,312,87,628,198,31,13317,628,198,4299,4808,1136,62,42946,62,16159,7,42946,62,87,11,3063,62,88,11,33769,2599,198,220,220,220,37227,198,220,220,220,9938,82,262,3641,286,428,3063,2122,2292,287,262,2939,338,2656,20435,2272,13,198,220,220,220,1058,17143,3063,62,87,25,1729,12,31591,18253,11,2124,20435,286,262,3063,2122,2292,13,198,220,220,220,1058,17143,3063,62,88,25,1729,12,31591,18253,11,331,20435,286,262,3063,2122,2292,13,198,220,220,220,1058,17143,33769,25,3967,18253,11,262,23818,33769,287,17848,379,428,7679,286,262,3127,13,198,220,220,220,1058,7783,25,46545,286,3967,37014,11,262,2124,290,331,22715,286,262,3641,286,262,3063,2122,2292,13,198,220,220,220,37227,198,220,220,220,2124,62,16159,796,33769,1635,357,42946,62,87,1343,657,13,20,8,198,220,220,220,331,62,16159,796,33769,1635,357,42946,62,88,1343,657,13,20,8,628,220,220,220,1441,493,7,87,62,16159,828,493,7,88,62,16159,8,628,198,31,13317,628,198,31,13317,628,198,31,13317,628,198,31,13317,198,2,428,2163,373,257,3236,49936,523,9617,1497,3091,12531,507,284,27183,2854,628,198,31,13317,198,4299,4808,1136,62,439,62,3702,273,62,1073,3669,7,42946,62,8516,11,3063,62,4033,82,11,18021,62,67,12078,11,33769,2599,198,220,220,220,37227,198,220,220,220,11259,262,5485,286,257,3063,2122,282,7679,290,262,43360,284,7716,329,1123,2292,11,1441,477,43360,13,198,220,220,220,1058,17143,3063,62,8516,25,3967,18253,11,6001,286,428,3063,2122,282,7679,13,198,220,220,220,1058,17143,3063,62,4033,82,25,3967,18253,11,9647,286,428,3063,2122,282,7679,13,198,220,220,220,1058,17143,18021,62,67,12078,25,1351,286,8341,286,3967,37014,11,530,6001,290,9647,5166,329,1123,18021,13,198,220,220,220,1058,17143,33769,25,3967,18253,11,23818,33769,286,428,18021,2292,287,17848,13,198,220,220,220,1058,7783,25,362,12,67,299,32152,7177,351,530,5752,329,1123,18021,3091,7268,663,685,87,16,11,331,16,11,2124,17,11,331,17,60,22715,13,198,220,220,220,37227,198,220,220,220,997,62,29305,796,3063,62,8516,1635,3063,62,4033,82,1635,18896,7,3702,273,62,67,12078,8,628,220,220,220,331,11,2124,11,18021,62,312,34223,796,4808,22510,62,29305,62,1462,62,42946,62,37659,7,22510,62,29305,11,3063,62,4033,82,11,18896,7,3702,273,62,67,12078,4008,198,220,220,220,2124,62,16159,11,331,62,16159,796,4808,1136,62,42946,62,16159,62,37659,7,87,11,331,11,33769,8,198,220,220,220,18021,62,1073,3669,796,45941,13,9107,418,19510,22510,62,29305,11,604,828,288,4906,28,37659,13,22468,2624,8,198,220,220,220,18021,62,17015,796,18021,62,67,12078,58,3702,273,62,312,34223,11,657,60,198,220,220,220,18021,62,10394,796,18021,62,67,12078,58,3702,273,62,312,34223,11,352,60,628,220,220,220,18021,62,1073,3669,58,45299,657,60,796,2124,62,16159,532,18021,62,10394,3373,362,198,220,220,220,18021,62,1073,3669,58,45299,352,60,796,331,62,16159,532,18021,62,17015,3373,362,198,220,220,220,18021,62,1073,3669,58,45299,362,60,796,18021,62,1073,3669,58,45299,657,60,1343,18021,62,10394,198,220,220,220,18021,62,1073,3669,58,45299,513,60,796,18021,62,1073,3669,58,45299,352,60,1343,18021,62,17015,628,220,220,220,1441,18021,62,1073,3669,628,198,31,13317,628,628,198,31,13317,198,4299,4808,39014,62,37687,11347,7,271,62,1930,11,460,62,1904,2599,198,220,220,220,37227,198,220,220,220,2034,13508,262,19232,9156,3417,287,262,38996,371,12,18474,3348,284,5004,543,43360,815,307,16726,287,262,198,220,220,220,2994,2163,13,198,220,220,220,1058,17143,318,62,1930,25,352,12,67,299,32152,7177,286,1489,2305,504,329,1771,1123,18021,318,257,2081,3967,329,617,2134,13,198,220,220,220,1058,17143,460,62,1904,25,352,12,67,299,32152,7177,286,1489,2305,504,329,1771,1123,18021,460,307,973,379,477,287,262,2994,2163,13,198,220,220,220,1058,7783,25,352,12,67,299,32152,7177,286,1489,2305,504,286,543,43360,547,7147,284,307,973,287,262,2994,2163,13,198,220,220,220,37227,198,220,220,220,1303,7925,685,15,60,2233,284,45941,13,3003,8024,257,46545,198,220,220,220,1426,62,17946,82,796,45941,13,3003,7,37659,13,6404,605,62,392,7,271,62,1930,6624,352,11,460,62,1904,6624,352,4008,58,15,60,198,220,220,220,2469,62,17946,82,796,45941,13,3003,7,37659,13,6404,605,62,392,7,271,62,1930,6624,657,11,460,62,1904,6624,352,4008,58,15,60,628,220,220,220,997,62,1930,796,18896,7,1930,62,17946,82,8,198,220,220,220,997,62,12480,796,18896,7,12480,62,17946,82,8,628,220,220,220,1303,1451,262,1271,286,3967,8405,583,15458,284,645,517,621,2063,262,15458,2546,198,220,220,220,611,997,62,1930,1875,25882,62,37997,62,49302,6489,1546,25,198,220,220,220,220,220,220,220,1179,82,62,2364,796,4738,13,39873,7,9521,7,22510,62,1930,828,997,62,1930,532,25882,62,37997,62,49302,6489,1546,8,198,220,220,220,220,220,220,220,460,62,1904,58,1930,62,17946,82,58,17946,82,62,2364,11907,796,657,198,220,220,220,220,220,220,220,997,62,1930,796,25882,62,37997,62,49302,6489,1546,628,220,220,220,1303,6070,5637,6903,286,262,15458,2546,351,4633,8405,198,220,220,220,611,997,62,12480,1343,997,62,1930,1875,28844,16437,62,33489,25,198,220,220,220,220,220,220,220,1179,82,62,2364,796,4738,13,39873,7,9521,7,22510,62,12480,828,997,62,12480,1343,997,62,1930,532,28844,16437,62,33489,8,198,220,220,220,220,220,220,220,460,62,1904,58,12480,62,17946,82,58,17946,82,62,2364,11907,796,657,628,220,220,220,1441,460,62,1904,198],"string":"[\n 11748,\n 4738,\n 198,\n 6738,\n 33829,\n 1330,\n 2039,\n 388,\n 198,\n 198,\n 11748,\n 299,\n 32152,\n 355,\n 45941,\n 198,\n 198,\n 6738,\n 2183,\n 62,\n 12501,\n 273,\n 2024,\n 1330,\n 7034,\n 198,\n 6738,\n 15268,\n 1330,\n 8315,\n 198,\n 6738,\n 4888,\n 62,\n 9979,\n 1187,\n 1330,\n 12597,\n 31553,\n 62,\n 44,\n 16724,\n 4061,\n 31271,\n 4877,\n 11,\n 5550,\n 38865,\n 62,\n 1565,\n 3398,\n 20673,\n 198,\n 6738,\n 7736,\n 1330,\n 42302,\n 62,\n 72,\n 280,\n 11,\n 3272,\n 62,\n 699,\n 11,\n 651,\n 62,\n 2301,\n 62,\n 37266,\n 11,\n 651,\n 62,\n 65,\n 3524,\n 62,\n 1073,\n 3669,\n 198,\n 198,\n 37997,\n 62,\n 41983,\n 43,\n 2969,\n 796,\n 657,\n 13,\n 22,\n 198,\n 45,\n 7156,\n 62,\n 41983,\n 43,\n 2969,\n 796,\n 657,\n 13,\n 18,\n 198,\n 198,\n 49302,\n 16437,\n 62,\n 33489,\n 796,\n 17759,\n 198,\n 22921,\n 62,\n 37997,\n 62,\n 49302,\n 6489,\n 1546,\n 796,\n 13108,\n 628,\n 198,\n 198,\n 4871,\n 371,\n 21999,\n 44357,\n 13511,\n 25,\n 198,\n 220,\n 220,\n 220,\n 37227,\n 198,\n 220,\n 220,\n 220,\n 14711,\n 1686,\n 15968,\n 262,\n 3307,\n 286,\n 15453,\n 3047,\n 17311,\n 329,\n 257,\n 3814,\n 6961,\n 3127,\n 329,\n 257,\n 1813,\n 2939,\n 13,\n 198,\n 220,\n 220,\n 220,\n 37227,\n 628,\n 220,\n 220,\n 220,\n 825,\n 11593,\n 15003,\n 834,\n 7,\n 944,\n 11,\n 42302,\n 62,\n 42946,\n 62,\n 67,\n 12078,\n 11,\n 33769,\n 11,\n 662,\n 14681,\n 62,\n 20786,\n 11,\n 18021,\n 62,\n 67,\n 12078,\n 28,\n 7206,\n 38865,\n 62,\n 1565,\n 3398,\n 20673,\n 2599,\n 198,\n 220,\n 220,\n 220,\n 220,\n 220,\n 220,\n 220,\n 37227,\n 198,\n 220,\n 220,\n 220,\n 220,\n 220,\n 220,\n 220,\n 1058,\n 17143,\n 42302,\n 62,\n 42946,\n 62,\n 67,\n 12078,\n 25,\n 2163,\n 326,\n 18178,\n 257,\n 46545,\n 286,\n 262,\n 2939,\n 338,\n 6001,\n 290,\n 9647,\n 287,\n 17848,\n 290,\n 5860,\n 262,\n 198,\n 220,\n 220,\n 220,\n 220,\n 220,\n 220,\n 220,\n 6001,\n 290,\n 9647,\n 286,\n 262,\n 3063,\n 2122,\n 282,\n 7679,\n 3161,\n 284,\n 262,\n 374,\n 21999,\n 11685,\n 13,\n 198,\n 220,\n 220,\n 220,\n 220,\n 220,\n 220,\n 220,\n 1058,\n 17143,\n 33769,\n 25,\n 3967,\n 18253,\n 11,\n 262,\n 23818,\n 33769,\n 379,\n 262,\n 3063,\n 2122,\n 282,\n 7679,\n 3161,\n 284,\n 262,\n 374,\n 21999,\n 11685,\n 13,\n 198,\n 220,\n 220,\n 220,\n 220,\n 220,\n 220,\n 220,\n 1058,\n 17143,\n 662,\n 14681,\n 62,\n 20786,\n 25,\n 2163,\n 326,\n 8991,\n 262,\n 976,\n 13389,\n 284,\n 262,\n 2939,\n 338,\n 17848,\n 355,\n 973,\n 329,\n 1846,\n 11286,\n 316,\n 198,\n 220,\n 220,\n 220,\n 220,\n 220,\n 220,\n 220,\n 3047,\n 13,\n 15323,\n 262,\n 1846,\n 11286,\n 316,\n 662,\n 12,\n 35311,\n 19590,\n 481,\n 307,\n 32691,\n 14265,\n 13,\n 198,\n 220,\n 220,\n 220,\n 220,\n 220,\n 220,\n 220,\n 1058,\n 17143,\n 18021,\n 62,\n 67,\n 12078,\n 25,\n 1351,\n 286,\n 8341,\n 286,\n 3967,\n 37014,\n 11,\n 530,\n 6001,\n 290,\n 9647,\n 5166,\n 329,\n 1123,\n 18021,\n 13,\n 198,\n 220,\n 220,\n 220,\n 220,\n 220,\n 220,\n 220,\n 37227,\n 198,\n 220,\n 220,\n 220,\n 220,\n 220,\n 220,\n 220,\n 2116,\n 13557,\n 23870,\n 796,\n 23884,\n 198,\n 220,\n 220,\n 220,\n 220,\n 220,\n 220,\n 220,\n 2116,\n 13,\n 9948,\n 66,\n 62,\n 42946,\n 62,\n 67,\n 12078,\n 796,\n 42302,\n 62,\n 42946,\n 62,\n 67,\n 12078,\n 198,\n 220,\n 220,\n 220,\n 220,\n 220,\n 220,\n 220,\n 2116,\n 13,\n 2536,\n 485,\n 796,\n 33769,\n 198,\n 220,\n 220,\n 220,\n 220,\n 220,\n 220,\n 220,\n 2116,\n 13,\n 3866,\n 14681,\n 62,\n 20786,\n 796,\n 662,\n 14681,\n 62,\n 20786,\n 198,\n 220,\n 220,\n 220,\n 220,\n 220,\n 220,\n 220,\n 2116,\n 13,\n 3702,\n 273,\n 62,\n 67,\n 12078,\n 796,\n 18021,\n 62,\n 67,\n 12078,\n 628,\n 220,\n 220,\n 220,\n 2488,\n 13317,\n 198,\n 220,\n 220,\n 220,\n 825,\n 7365,\n 1740,\n 62,\n 9060,\n 7,\n 944,\n 11,\n 2939,\n 2599,\n 198,\n 220,\n 220,\n 220,\n 220,\n 220,\n 220,\n 220,\n 37227,\n 198,\n 220,\n 220,\n 220,\n 220,\n 220,\n 220,\n 220,\n 16409,\n 262,\n 2939,\n 1366,\n 284,\n 307,\n 11672,\n 656,\n 262,\n 3127,\n 13,\n 198,\n 220,\n 220,\n 220,\n 220,\n 220,\n 220,\n 220,\n 1058,\n 17143,\n 2939,\n 25,\n 15268,\n 13,\n 5159,\n 2134,\n 13,\n 198,\n 220,\n 220,\n 220,\n 220,\n 220,\n 220,\n 220,\n 1058,\n 7783,\n 25,\n 604,\n 12,\n 67,\n 299,\n 32152,\n 7177,\n 351,\n 257,\n 2060,\n 15458,\n 286,\n 262,\n 2939,\n 11,\n 815,\n 460,\n 307,\n 973,\n 355,\n 257,\n 17337,\n 292,\n 2746,\n 5128,\n 13,\n 198,\n 220,\n 220,\n 220,\n 220,\n 220,\n 220,\n 220,\n 37227,\n 198,\n 220,\n 220,\n 220,\n 220,\n 220,\n 220,\n 220,\n 1441,\n 45941,\n 13,\n 11201,\n 392,\n 62,\n 67,\n 12078,\n 7,\n 944,\n 13,\n 3866,\n 14681,\n 62,\n 20786,\n 7,\n 9060,\n 13,\n 7890,\n 828,\n 16488,\n 28,\n 15,\n 8,\n 628,\n 220,\n 220,\n 220,\n 2488,\n 13317,\n 628,\n 220,\n 220,\n 220,\n 2488,\n 13317,\n 198,\n 220,\n 220,\n 220,\n 825,\n 374,\n 21999,\n 62,\n 88,\n 62,\n 7942,\n 7,\n 944,\n 11,\n 2939,\n 2599,\n 198,\n 220,\n 220,\n 220,\n 220,\n 220,\n 220,\n 220,\n 37227,\n 198,\n 220,\n 220,\n 220,\n 220,\n 220,\n 220,\n 220,\n 33687,\n 281,\n 2939,\n 290,\n 5860,\n 262,\n 17337,\n 292,\n 2746,\n 17311,\n 284,\n 4512,\n 351,\n 13,\n 198,\n 220,\n 220,\n 220,\n 220,\n 220,\n 220,\n 220,\n 1058,\n 17143,\n 2939,\n 25,\n 15268,\n 13,\n 5159,\n 2134,\n 284,\n 7716,\n 3047,\n 17311,\n 329,\n 13,\n 198,\n 220,\n 220,\n 220,\n 220,\n 220,\n 220,\n 220,\n 1058,\n 7783,\n 25,\n 46545,\n 810,\n 262,\n 717,\n 5002,\n 318,\n 257,\n 299,\n 32152,\n 7177,\n 286,\n 262,\n 2323,\n 3872,\n 3127,\n 5072,\n 329,\n 1771,\n 1123,\n 198,\n 220,\n 220,\n 220,\n 220,\n 220,\n 220,\n 220,\n 18021,\n 12893,\n 1686,\n 351,\n 281,\n 2134,\n 11,\n 290,\n 262,\n 1218,\n 5002,\n 318,\n 257,\n 299,\n 32152,\n 7177,\n 286,\n 262,\n 2323,\n 3872,\n 3127,\n 5072,\n 329,\n 262,\n 198,\n 220,\n 220,\n 220,\n 220,\n 220,\n 220,\n 220,\n 5421,\n 278,\n 3091,\n 13389,\n 10007,\n 284,\n 6121,\n 1123,\n 18021,\n 656,\n 281,\n 2134,\n 338,\n 5421,\n 278,\n 3091,\n 13,\n 198,\n 220,\n 220,\n 220,\n 220,\n 220,\n 220,\n 220,\n 37227,\n 198,\n 220,\n 220,\n 220,\n 220,\n 220,\n 220,\n 220,\n 705,\n 7061,\n 198,\n 220,\n 220,\n 220,\n 220,\n 220,\n 220,\n 220,\n 12642,\n 10829,\n 40918,\n 532,\n 2087,\n 618,\n 2116,\n 13,\n 14681,\n 373,\n 2263,\n 657,\n 13,\n 19,\n 82,\n 284,\n 1057,\n 13,\n 4619,\n 788,\n 11,\n 23392,\n 340,\n 866,\n 284,\n 198,\n 220,\n 220,\n 220,\n 220,\n 220,\n 220,\n 220,\n 657,\n 13,\n 2999,\n 82,\n 15726,\n 11,\n 657,\n 13,\n 11245,\n 82,\n 319,\n 3253,\n 82,\n 523,\n 262,\n 12940,\n 2125,\n 470,\n 1165,\n 4465,\n 7471,\n 13,\n 198,\n 220,\n 220,\n 220,\n 220,\n 220,\n 220,\n 220,\n 705,\n 7061,\n 198,\n 220,\n 220,\n 220,\n 220,\n 220,\n 220,\n 220,\n 611,\n 2939,\n 13,\n 23870,\n 62,\n 2539,\n 407,\n 287,\n 2116,\n 13557,\n 23870,\n 25,\n 198,\n 220,\n 220,\n 220,\n 220,\n 220,\n 220,\n 220,\n 220,\n 220,\n 220,\n 220,\n 2116,\n 13557,\n 14681,\n 7,\n 9060,\n 8,\n 628,\n 220,\n 220,\n 220,\n 220,\n 220,\n 220,\n 220,\n 2482,\n 796,\n 2116,\n 13557,\n 23870,\n 58,\n 9060,\n 13,\n 23870,\n 62,\n 2539,\n 60,\n 198,\n 220,\n 220,\n 220,\n 220,\n 220,\n 220,\n 220,\n 1303,\n 16926,\n 46,\n 25,\n 1521,\n 318,\n 262,\n 39986,\n 1255,\n 852,\n 13140,\n 30,\n 7488,\n 10055,\n 1771,\n 25646,\n 340,\n 19575,\n 3047,\n 640,\n 13,\n 198,\n 220,\n 220,\n 220,\n 220,\n 220,\n 220,\n 220,\n 1619,\n 2116,\n 13557,\n 23870,\n 58,\n 9060,\n 13,\n 23870,\n 62,\n 2539,\n 60,\n 198,\n 220,\n 220,\n 220,\n 220,\n 220,\n 220,\n 220,\n 460,\n 62,\n 1904,\n 796,\n 4808,\n 39014,\n 62,\n 37687,\n 11347,\n 7,\n 43420,\n 17816,\n 271,\n 62,\n 1930,\n 6,\n 4357,\n 2482,\n 17816,\n 5171,\n 62,\n 1904,\n 6,\n 12962,\n 198,\n 220,\n 220,\n 220,\n 220,\n 220,\n 220,\n 220,\n 3063,\n 62,\n 8516,\n 11,\n 3063,\n 62,\n 4033,\n 82,\n 796,\n 2116,\n 13,\n 9948,\n 66,\n 62,\n 42946,\n 62,\n 67,\n 12078,\n 7,\n 9060,\n 13,\n 17015,\n 11,\n 2939,\n 13,\n 10394,\n 8,\n 628,\n 220,\n 220,\n 220,\n 220,\n 220,\n 220,\n 220,\n 318,\n 62,\n 1930,\n 796,\n 45941,\n 13,\n 3447,\n 1758,\n 7,\n 43420,\n 17816,\n 271,\n 62,\n 1930,\n 6,\n 4357,\n 357,\n 42946,\n 62,\n 8516,\n 11,\n 3063,\n 62,\n 4033,\n 82,\n 11,\n 18896,\n 7,\n 944,\n 13,\n 3702,\n 273,\n 62,\n 67,\n 12078,\n 22305,\n 198,\n 220,\n 220,\n 220,\n 220,\n 220,\n 220,\n 220,\n 460,\n 62,\n 1904,\n 796,\n 45941,\n 13,\n 3447,\n 1758,\n 7,\n 5171,\n 62,\n 1904,\n 11,\n 357,\n 42946,\n 62,\n 8516,\n 11,\n 3063,\n 62,\n 4033,\n 82,\n 11,\n 18896,\n 7,\n 944,\n 13,\n 3702,\n 273,\n 62,\n 67,\n 12078,\n 22305,\n 198,\n 220,\n 220,\n 220,\n 220,\n 220,\n 220,\n 220,\n 6163,\n 62,\n 271,\n 62,\n 1930,\n 796,\n 45941,\n 13,\n 6404,\n 605,\n 62,\n 392,\n 7,\n 271,\n 62,\n 1930,\n 11,\n 460,\n 62,\n 1904,\n 8,\n 628,\n 220,\n 220,\n 220,\n 220,\n 220,\n 220,\n 220,\n 1303,\n 12082,\n 26515,\n 351,\n 1771,\n 393,\n 407,\n 284,\n 779,\n 329,\n 262,\n 2994,\n 2163,\n 198,\n 220,\n 220,\n 220,\n 220,\n 220,\n 220,\n 220,\n 331,\n 62,\n 4871,\n 796,\n 45941,\n 13,\n 1102,\n 9246,\n 268,\n 378,\n 26933,\n 5171,\n 62,\n 1904,\n 11,\n 318,\n 62,\n 1930,\n 4357,\n 16488,\n 28,\n 17,\n 8,\n 198,\n 220,\n 220,\n 220,\n 220,\n 220,\n 220,\n 220,\n 275,\n 65,\n 2301,\n 62,\n 5171,\n 62,\n 1904,\n 796,\n 45941,\n 13,\n 44754,\n 7,\n 34213,\n 62,\n 271,\n 62,\n 1930,\n 11,\n 604,\n 11,\n 16488,\n 796,\n 362,\n 8,\n 198,\n 220,\n 220,\n 220,\n 220,\n 220,\n 220,\n 220,\n 275,\n 65,\n 2301,\n 62,\n 83,\n 853,\n 1039,\n 796,\n 45941,\n 13,\n 3447,\n 1758,\n 7,\n 43420,\n 17816,\n 11848,\n 2301,\n 62,\n 83,\n 853,\n 1039,\n 6,\n 4357,\n 357,\n 42946,\n 62,\n 8516,\n 11,\n 3063,\n 62,\n 4033,\n 82,\n 11,\n 604,\n 1635,\n 18896,\n 7,\n 944,\n 13,\n 3702,\n 273,\n 62,\n 67,\n 12078,\n 22305,\n 198,\n 220,\n 220,\n 220,\n 220,\n 220,\n 220,\n 220,\n 331,\n 62,\n 11848,\n 2301,\n 796,\n 45941,\n 13,\n 1102,\n 9246,\n 268,\n 378,\n 26933,\n 11848,\n 2301,\n 62,\n 5171,\n 62,\n 1904,\n 11,\n 275,\n 65,\n 2301,\n 62,\n 83,\n 853,\n 1039,\n 4357,\n 16488,\n 796,\n 362,\n 8,\n 628,\n 220,\n 220,\n 220,\n 220,\n 220,\n 220,\n 220,\n 331,\n 62,\n 4871,\n 796,\n 45941,\n 13,\n 11201,\n 392,\n 62,\n 67,\n 12078,\n 7,\n 88,\n 62,\n 4871,\n 11,\n 16488,\n 28,\n 15,\n 8,\n 198,\n 220,\n 220,\n 220,\n 220,\n 220,\n 220,\n 220,\n 331,\n 62,\n 11848,\n 2301,\n 796,\n 45941,\n 13,\n 11201,\n 392,\n 62,\n 67,\n 12078,\n 7,\n 88,\n 62,\n 11848,\n 2301,\n 11,\n 16488,\n 28,\n 15,\n 8,\n 628,\n 220,\n 220,\n 220,\n 220,\n 220,\n 220,\n 220,\n 1441,\n 331,\n 62,\n 4871,\n 11,\n 331,\n 62,\n 11848,\n 2301,\n 628,\n 198,\n 4299,\n 4808,\n 312,\n 87,\n 62,\n 1462,\n 62,\n 42946,\n 7,\n 312,\n 87,\n 11,\n 3063,\n 62,\n 10394,\n 11,\n 43360,\n 62,\n 525,\n 62,\n 17946,\n 2599,\n 198,\n 220,\n 220,\n 220,\n 37227,\n 198,\n 220,\n 220,\n 220,\n 1482,\n 24040,\n 281,\n 18021,\n 3091,\n 6376,\n 287,\n 257,\n 352,\n 12,\n 67,\n 299,\n 32152,\n 7177,\n 284,\n 663,\n 11188,\n 513,\n 12,\n 67,\n 6376,\n 10200,\n 663,\n 3063,\n 2122,\n 198,\n 220,\n 220,\n 220,\n 2292,\n 290,\n 18021,\n 6376,\n 13,\n 198,\n 220,\n 220,\n 220,\n 1058,\n 17143,\n 4686,\n 87,\n 25,\n 1729,\n 12,\n 31591,\n 18253,\n 11,\n 262,\n 2292,\n 287,\n 257,\n 352,\n 12,\n 67,\n 299,\n 32152,\n 7177,\n 286,\n 43360,\n 13,\n 198,\n 220,\n 220,\n 220,\n 1058,\n 17143,\n 3063,\n 62,\n 10394,\n 25,\n 262,\n 1271,\n 286,\n 1744,\n 16021,\n 6116,\n 262,\n 3063,\n 2122,\n 282,\n 7679,\n 338,\n 16628,\n 460,\n 22265,\n 11,\n 1312,\n 13,\n 68,\n 13,\n 198,\n 220,\n 220,\n 220,\n 1969,\n 284,\n 262,\n 9647,\n 287,\n 17848,\n 9086,\n 416,\n 262,\n 23818,\n 33769,\n 379,\n 326,\n 7679,\n 13,\n 198,\n 220,\n 220,\n 220,\n 1058,\n 17143,\n 43360,\n 62,\n 525,\n 62,\n 17946,\n 25,\n 3967,\n 18253,\n 11,\n 262,\n 1271,\n 286,\n 43360,\n 379,\n 1123,\n 3063,\n 2122,\n 282,\n 8106,\n 2292,\n 13,\n 198,\n 220,\n 220,\n 220,\n 1058,\n 7783,\n 25,\n 46545,\n 286,\n 262,\n 5752,\n 11,\n 5721,\n 11,\n 290,\n 18021,\n 6376,\n 286,\n 262,\n 3063,\n 2122,\n 282,\n 8106,\n 2292,\n 329,\n 428,\n 6376,\n 13,\n 198,\n 220,\n 220,\n 220,\n 37227,\n 198,\n 220,\n 220,\n 220,\n 2659,\n 271,\n 273,\n 796,\n 3063,\n 62,\n 10394,\n 1635,\n 43360,\n 62,\n 525,\n 62,\n 17946,\n 198,\n 220,\n 220,\n 220,\n 331,\n 11,\n 17675,\n 796,\n 4686,\n 87,\n 3373,\n 2659,\n 271,\n 273,\n 11,\n 4686,\n 87,\n 4064,\n 2659,\n 271,\n 273,\n 198,\n 220,\n 220,\n 220,\n 2124,\n 11,\n 18021,\n 62,\n 312,\n 87,\n 796,\n 17675,\n 3373,\n 43360,\n 62,\n 525,\n 62,\n 17946,\n 11,\n 17675,\n 4064,\n 43360,\n 62,\n 525,\n 62,\n 17946,\n 198,\n 220,\n 220,\n 220,\n 1441,\n 331,\n 11,\n 2124,\n 11,\n 18021,\n 62,\n 312,\n 87,\n 628,\n 198,\n 31,\n 13317,\n 628,\n 198,\n 4299,\n 4808,\n 1136,\n 62,\n 42946,\n 62,\n 16159,\n 7,\n 42946,\n 62,\n 87,\n 11,\n 3063,\n 62,\n 88,\n 11,\n 33769,\n 2599,\n 198,\n 220,\n 220,\n 220,\n 37227,\n 198,\n 220,\n 220,\n 220,\n 9938,\n 82,\n 262,\n 3641,\n 286,\n 428,\n 3063,\n 2122,\n 2292,\n 287,\n 262,\n 2939,\n 338,\n 2656,\n 20435,\n 2272,\n 13,\n 198,\n 220,\n 220,\n 220,\n 1058,\n 17143,\n 3063,\n 62,\n 87,\n 25,\n 1729,\n 12,\n 31591,\n 18253,\n 11,\n 2124,\n 20435,\n 286,\n 262,\n 3063,\n 2122,\n 2292,\n 13,\n 198,\n 220,\n 220,\n 220,\n 1058,\n 17143,\n 3063,\n 62,\n 88,\n 25,\n 1729,\n 12,\n 31591,\n 18253,\n 11,\n 331,\n 20435,\n 286,\n 262,\n 3063,\n 2122,\n 2292,\n 13,\n 198,\n 220,\n 220,\n 220,\n 1058,\n 17143,\n 33769,\n 25,\n 3967,\n 18253,\n 11,\n 262,\n 23818,\n 33769,\n 287,\n 17848,\n 379,\n 428,\n 7679,\n 286,\n 262,\n 3127,\n 13,\n 198,\n 220,\n 220,\n 220,\n 1058,\n 7783,\n 25,\n 46545,\n 286,\n 3967,\n 37014,\n 11,\n 262,\n 2124,\n 290,\n 331,\n 22715,\n 286,\n 262,\n 3641,\n 286,\n 262,\n 3063,\n 2122,\n 2292,\n 13,\n 198,\n 220,\n 220,\n 220,\n 37227,\n 198,\n 220,\n 220,\n 220,\n 2124,\n 62,\n 16159,\n 796,\n 33769,\n 1635,\n 357,\n 42946,\n 62,\n 87,\n 1343,\n 657,\n 13,\n 20,\n 8,\n 198,\n 220,\n 220,\n 220,\n 331,\n 62,\n 16159,\n 796,\n 33769,\n 1635,\n 357,\n 42946,\n 62,\n 88,\n 1343,\n 657,\n 13,\n 20,\n 8,\n 628,\n 220,\n 220,\n 220,\n 1441,\n 493,\n 7,\n 87,\n 62,\n 16159,\n 828,\n 493,\n 7,\n 88,\n 62,\n 16159,\n 8,\n 628,\n 198,\n 31,\n 13317,\n 628,\n 198,\n 31,\n 13317,\n 628,\n 198,\n 31,\n 13317,\n 628,\n 198,\n 31,\n 13317,\n 198,\n 2,\n 428,\n 2163,\n 373,\n 257,\n 3236,\n 49936,\n 523,\n 9617,\n 1497,\n 3091,\n 12531,\n 507,\n 284,\n 27183,\n 2854,\n 628,\n 198,\n 31,\n 13317,\n 198,\n 4299,\n 4808,\n 1136,\n 62,\n 439,\n 62,\n 3702,\n 273,\n 62,\n 1073,\n 3669,\n 7,\n 42946,\n 62,\n 8516,\n 11,\n 3063,\n 62,\n 4033,\n 82,\n 11,\n 18021,\n 62,\n 67,\n 12078,\n 11,\n 33769,\n 2599,\n 198,\n 220,\n 220,\n 220,\n 37227,\n 198,\n 220,\n 220,\n 220,\n 11259,\n 262,\n 5485,\n 286,\n 257,\n 3063,\n 2122,\n 282,\n 7679,\n 290,\n 262,\n 43360,\n 284,\n 7716,\n 329,\n 1123,\n 2292,\n 11,\n 1441,\n 477,\n 43360,\n 13,\n 198,\n 220,\n 220,\n 220,\n 1058,\n 17143,\n 3063,\n 62,\n 8516,\n 25,\n 3967,\n 18253,\n 11,\n 6001,\n 286,\n 428,\n 3063,\n 2122,\n 282,\n 7679,\n 13,\n 198,\n 220,\n 220,\n 220,\n 1058,\n 17143,\n 3063,\n 62,\n 4033,\n 82,\n 25,\n 3967,\n 18253,\n 11,\n 9647,\n 286,\n 428,\n 3063,\n 2122,\n 282,\n 7679,\n 13,\n 198,\n 220,\n 220,\n 220,\n 1058,\n 17143,\n 18021,\n 62,\n 67,\n 12078,\n 25,\n 1351,\n 286,\n 8341,\n 286,\n 3967,\n 37014,\n 11,\n 530,\n 6001,\n 290,\n 9647,\n 5166,\n 329,\n 1123,\n 18021,\n 13,\n 198,\n 220,\n 220,\n 220,\n 1058,\n 17143,\n 33769,\n 25,\n 3967,\n 18253,\n 11,\n 23818,\n 33769,\n 286,\n 428,\n 18021,\n 2292,\n 287,\n 17848,\n 13,\n 198,\n 220,\n 220,\n 220,\n 1058,\n 7783,\n 25,\n 362,\n 12,\n 67,\n 299,\n 32152,\n 7177,\n 351,\n 530,\n 5752,\n 329,\n 1123,\n 18021,\n 3091,\n 7268,\n 663,\n 685,\n 87,\n 16,\n 11,\n 331,\n 16,\n 11,\n 2124,\n 17,\n 11,\n 331,\n 17,\n 60,\n 22715,\n 13,\n 198,\n 220,\n 220,\n 220,\n 37227,\n 198,\n 220,\n 220,\n 220,\n 997,\n 62,\n 29305,\n 796,\n 3063,\n 62,\n 8516,\n 1635,\n 3063,\n 62,\n 4033,\n 82,\n 1635,\n 18896,\n 7,\n 3702,\n 273,\n 62,\n 67,\n 12078,\n 8,\n 628,\n 220,\n 220,\n 220,\n 331,\n 11,\n 2124,\n 11,\n 18021,\n 62,\n 312,\n 34223,\n 796,\n 4808,\n 22510,\n 62,\n 29305,\n 62,\n 1462,\n 62,\n 42946,\n 62,\n 37659,\n 7,\n 22510,\n 62,\n 29305,\n 11,\n 3063,\n 62,\n 4033,\n 82,\n 11,\n 18896,\n 7,\n 3702,\n 273,\n 62,\n 67,\n 12078,\n 4008,\n 198,\n 220,\n 220,\n 220,\n 2124,\n 62,\n 16159,\n 11,\n 331,\n 62,\n 16159,\n 796,\n 4808,\n 1136,\n 62,\n 42946,\n 62,\n 16159,\n 62,\n 37659,\n 7,\n 87,\n 11,\n 331,\n 11,\n 33769,\n 8,\n 198,\n 220,\n 220,\n 220,\n 18021,\n 62,\n 1073,\n 3669,\n 796,\n 45941,\n 13,\n 9107,\n 418,\n 19510,\n 22510,\n 62,\n 29305,\n 11,\n 604,\n 828,\n 288,\n 4906,\n 28,\n 37659,\n 13,\n 22468,\n 2624,\n 8,\n 198,\n 220,\n 220,\n 220,\n 18021,\n 62,\n 17015,\n 796,\n 18021,\n 62,\n 67,\n 12078,\n 58,\n 3702,\n 273,\n 62,\n 312,\n 34223,\n 11,\n 657,\n 60,\n 198,\n 220,\n 220,\n 220,\n 18021,\n 62,\n 10394,\n 796,\n 18021,\n 62,\n 67,\n 12078,\n 58,\n 3702,\n 273,\n 62,\n 312,\n 34223,\n 11,\n 352,\n 60,\n 628,\n 220,\n 220,\n 220,\n 18021,\n 62,\n 1073,\n 3669,\n 58,\n 45299,\n 657,\n 60,\n 796,\n 2124,\n 62,\n 16159,\n 532,\n 18021,\n 62,\n 10394,\n 3373,\n 362,\n 198,\n 220,\n 220,\n 220,\n 18021,\n 62,\n 1073,\n 3669,\n 58,\n 45299,\n 352,\n 60,\n 796,\n 331,\n 62,\n 16159,\n 532,\n 18021,\n 62,\n 17015,\n 3373,\n 362,\n 198,\n 220,\n 220,\n 220,\n 18021,\n 62,\n 1073,\n 3669,\n 58,\n 45299,\n 362,\n 60,\n 796,\n 18021,\n 62,\n 1073,\n 3669,\n 58,\n 45299,\n 657,\n 60,\n 1343,\n 18021,\n 62,\n 10394,\n 198,\n 220,\n 220,\n 220,\n 18021,\n 62,\n 1073,\n 3669,\n 58,\n 45299,\n 513,\n 60,\n 796,\n 18021,\n 62,\n 1073,\n 3669,\n 58,\n 45299,\n 352,\n 60,\n 1343,\n 18021,\n 62,\n 17015,\n 628,\n 220,\n 220,\n 220,\n 1441,\n 18021,\n 62,\n 1073,\n 3669,\n 628,\n 198,\n 31,\n 13317,\n 628,\n 628,\n 198,\n 31,\n 13317,\n 198,\n 4299,\n 4808,\n 39014,\n 62,\n 37687,\n 11347,\n 7,\n 271,\n 62,\n 1930,\n 11,\n 460,\n 62,\n 1904,\n 2599,\n 198,\n 220,\n 220,\n 220,\n 37227,\n 198,\n 220,\n 220,\n 220,\n 2034,\n 13508,\n 262,\n 19232,\n 9156,\n 3417,\n 287,\n 262,\n 38996,\n 371,\n 12,\n 18474,\n 3348,\n 284,\n 5004,\n 543,\n 43360,\n 815,\n 307,\n 16726,\n 287,\n 262,\n 198,\n 220,\n 220,\n 220,\n 2994,\n 2163,\n 13,\n 198,\n 220,\n 220,\n 220,\n 1058,\n 17143,\n 318,\n 62,\n 1930,\n 25,\n 352,\n 12,\n 67,\n 299,\n 32152,\n 7177,\n 286,\n 1489,\n 2305,\n 504,\n 329,\n 1771,\n 1123,\n 18021,\n 318,\n 257,\n 2081,\n 3967,\n 329,\n 617,\n 2134,\n 13,\n 198,\n 220,\n 220,\n 220,\n 1058,\n 17143,\n 460,\n 62,\n 1904,\n 25,\n 352,\n 12,\n 67,\n 299,\n 32152,\n 7177,\n 286,\n 1489,\n 2305,\n 504,\n 329,\n 1771,\n 1123,\n 18021,\n 460,\n 307,\n 973,\n 379,\n 477,\n 287,\n 262,\n 2994,\n 2163,\n 13,\n 198,\n 220,\n 220,\n 220,\n 1058,\n 7783,\n 25,\n 352,\n 12,\n 67,\n 299,\n 32152,\n 7177,\n 286,\n 1489,\n 2305,\n 504,\n 286,\n 543,\n 43360,\n 547,\n 7147,\n 284,\n 307,\n 973,\n 287,\n 262,\n 2994,\n 2163,\n 13,\n 198,\n 220,\n 220,\n 220,\n 37227,\n 198,\n 220,\n 220,\n 220,\n 1303,\n 7925,\n 685,\n 15,\n 60,\n 2233,\n 284,\n 45941,\n 13,\n 3003,\n 8024,\n 257,\n 46545,\n 198,\n 220,\n 220,\n 220,\n 1426,\n 62,\n 17946,\n 82,\n 796,\n 45941,\n 13,\n 3003,\n 7,\n 37659,\n 13,\n 6404,\n 605,\n 62,\n 392,\n 7,\n 271,\n 62,\n 1930,\n 6624,\n 352,\n 11,\n 460,\n 62,\n 1904,\n 6624,\n 352,\n 4008,\n 58,\n 15,\n 60,\n 198,\n 220,\n 220,\n 220,\n 2469,\n 62,\n 17946,\n 82,\n 796,\n 45941,\n 13,\n 3003,\n 7,\n 37659,\n 13,\n 6404,\n 605,\n 62,\n 392,\n 7,\n 271,\n 62,\n 1930,\n 6624,\n 657,\n 11,\n 460,\n 62,\n 1904,\n 6624,\n 352,\n 4008,\n 58,\n 15,\n 60,\n 628,\n 220,\n 220,\n 220,\n 997,\n 62,\n 1930,\n 796,\n 18896,\n 7,\n 1930,\n 62,\n 17946,\n 82,\n 8,\n 198,\n 220,\n 220,\n 220,\n 997,\n 62,\n 12480,\n 796,\n 18896,\n 7,\n 12480,\n 62,\n 17946,\n 82,\n 8,\n 628,\n 220,\n 220,\n 220,\n 1303,\n 1451,\n 262,\n 1271,\n 286,\n 3967,\n 8405,\n 583,\n 15458,\n 284,\n 645,\n 517,\n 621,\n 2063,\n 262,\n 15458,\n 2546,\n 198,\n 220,\n 220,\n 220,\n 611,\n 997,\n 62,\n 1930,\n 1875,\n 25882,\n 62,\n 37997,\n 62,\n 49302,\n 6489,\n 1546,\n 25,\n 198,\n 220,\n 220,\n 220,\n 220,\n 220,\n 220,\n 220,\n 1179,\n 82,\n 62,\n 2364,\n 796,\n 4738,\n 13,\n 39873,\n 7,\n 9521,\n 7,\n 22510,\n 62,\n 1930,\n 828,\n 997,\n 62,\n 1930,\n 532,\n 25882,\n 62,\n 37997,\n 62,\n 49302,\n 6489,\n 1546,\n 8,\n 198,\n 220,\n 220,\n 220,\n 220,\n 220,\n 220,\n 220,\n 460,\n 62,\n 1904,\n 58,\n 1930,\n 62,\n 17946,\n 82,\n 58,\n 17946,\n 82,\n 62,\n 2364,\n 11907,\n 796,\n 657,\n 198,\n 220,\n 220,\n 220,\n 220,\n 220,\n 220,\n 220,\n 997,\n 62,\n 1930,\n 796,\n 25882,\n 62,\n 37997,\n 62,\n 49302,\n 6489,\n 1546,\n 628,\n 220,\n 220,\n 220,\n 1303,\n 6070,\n 5637,\n 6903,\n 286,\n 262,\n 15458,\n 2546,\n 351,\n 4633,\n 8405,\n 198,\n 220,\n 220,\n 220,\n 611,\n 997,\n 62,\n 12480,\n 1343,\n 997,\n 62,\n 1930,\n 1875,\n 28844,\n 16437,\n 62,\n 33489,\n 25,\n 198,\n 220,\n 220,\n 220,\n 220,\n 220,\n 220,\n 220,\n 1179,\n 82,\n 62,\n 2364,\n 796,\n 4738,\n 13,\n 39873,\n 7,\n 9521,\n 7,\n 22510,\n 62,\n 12480,\n 828,\n 997,\n 62,\n 12480,\n 1343,\n 997,\n 62,\n 1930,\n 532,\n 28844,\n 16437,\n 62,\n 33489,\n 8,\n 198,\n 220,\n 220,\n 220,\n 220,\n 220,\n 220,\n 220,\n 460,\n 62,\n 1904,\n 58,\n 12480,\n 62,\n 17946,\n 82,\n 58,\n 17946,\n 82,\n 62,\n 2364,\n 11907,\n 796,\n 657,\n 628,\n 220,\n 220,\n 220,\n 1441,\n 460,\n 62,\n 1904,\n 198\n]"},"ratio_char_token":{"kind":"number","value":2.777241379310345,"string":"2.777241"},"token_count":{"kind":"number","value":2900,"string":"2,900"}}},{"rowIdx":1296,"cells":{"content":{"kind":"string","value":"# coding: utf-8\n\n\"\"\"\n OpenAPI Petstore\n\n This spec is mainly for testing Petstore server and contains fake endpoints, models. Please do not use this for any other purpose. Special characters: \\\" \\\\ # noqa: E501\n\n The version of the OpenAPI document: 1.0.0\n Generated by: https://openapi-generator.tech\n\"\"\"\n\n\nimport pprint # noqa: F401\nimport re # noqa: F401\n\nimport six # noqa: F401\n\nfrom petstore_api.exceptions import ( # noqa: F401\n ApiKeyError,\n ApiTypeError,\n ApiValueError,\n)\nfrom petstore_api.model_utils import ( # noqa: F401\n ModelNormal,\n ModelSimple,\n check_allowed_values,\n check_validations,\n date,\n datetime,\n file_type,\n get_simple_class,\n int,\n model_to_dict,\n none_type,\n str,\n type_error_message,\n validate_and_convert_types\n)\n\n\nclass XmlItem(ModelNormal):\n \"\"\"NOTE: This class is auto generated by OpenAPI Generator.\n Ref: https://openapi-generator.tech\n\n Do not edit the class manually.\n\n Attributes:\n allowed_values (dict): The key is the tuple path to the attribute\n and the for var_name this is (var_name,). The value is a dict\n with a capitalized key describing the allowed value and an allowed\n value. These dicts store the allowed enum values.\n attribute_map (dict): The key is attribute name\n and the value is json key in definition.\n discriminator_value_class_map (dict): A dict to go from the discriminator\n variable value to the discriminator class name.\n openapi_types (dict): The key is attribute name\n and the value is attribute type.\n validations (dict): The key is the tuple path to the attribute\n and the for var_name this is (var_name,). The value is a dict\n that stores validations for max_length, min_length, max_items,\n min_items, exclusive_maximum, inclusive_maximum, exclusive_minimum,\n inclusive_minimum, and regex.\n additional_properties_type (tuple): A tuple of classes accepted\n as additional properties values.\n \"\"\"\n\n allowed_values = {\n }\n\n attribute_map = {\n 'attribute_string': 'attribute_string', # noqa: E501\n 'attribute_number': 'attribute_number', # noqa: E501\n 'attribute_integer': 'attribute_integer', # noqa: E501\n 'attribute_boolean': 'attribute_boolean', # noqa: E501\n 'wrapped_array': 'wrapped_array', # noqa: E501\n 'name_string': 'name_string', # noqa: E501\n 'name_number': 'name_number', # noqa: E501\n 'name_integer': 'name_integer', # noqa: E501\n 'name_boolean': 'name_boolean', # noqa: E501\n 'name_array': 'name_array', # noqa: E501\n 'name_wrapped_array': 'name_wrapped_array', # noqa: E501\n 'prefix_string': 'prefix_string', # noqa: E501\n 'prefix_number': 'prefix_number', # noqa: E501\n 'prefix_integer': 'prefix_integer', # noqa: E501\n 'prefix_boolean': 'prefix_boolean', # noqa: E501\n 'prefix_array': 'prefix_array', # noqa: E501\n 'prefix_wrapped_array': 'prefix_wrapped_array', # noqa: E501\n 'namespace_string': 'namespace_string', # noqa: E501\n 'namespace_number': 'namespace_number', # noqa: E501\n 'namespace_integer': 'namespace_integer', # noqa: E501\n 'namespace_boolean': 'namespace_boolean', # noqa: E501\n 'namespace_array': 'namespace_array', # noqa: E501\n 'namespace_wrapped_array': 'namespace_wrapped_array', # noqa: E501\n 'prefix_ns_string': 'prefix_ns_string', # noqa: E501\n 'prefix_ns_number': 'prefix_ns_number', # noqa: E501\n 'prefix_ns_integer': 'prefix_ns_integer', # noqa: E501\n 'prefix_ns_boolean': 'prefix_ns_boolean', # noqa: E501\n 'prefix_ns_array': 'prefix_ns_array', # noqa: E501\n 'prefix_ns_wrapped_array': 'prefix_ns_wrapped_array' # noqa: E501\n }\n\n openapi_types = {\n 'attribute_string': (str,), # noqa: E501\n 'attribute_number': (float,), # noqa: E501\n 'attribute_integer': (int,), # noqa: E501\n 'attribute_boolean': (bool,), # noqa: E501\n 'wrapped_array': ([int],), # noqa: E501\n 'name_string': (str,), # noqa: E501\n 'name_number': (float,), # noqa: E501\n 'name_integer': (int,), # noqa: E501\n 'name_boolean': (bool,), # noqa: E501\n 'name_array': ([int],), # noqa: E501\n 'name_wrapped_array': ([int],), # noqa: E501\n 'prefix_string': (str,), # noqa: E501\n 'prefix_number': (float,), # noqa: E501\n 'prefix_integer': (int,), # noqa: E501\n 'prefix_boolean': (bool,), # noqa: E501\n 'prefix_array': ([int],), # noqa: E501\n 'prefix_wrapped_array': ([int],), # noqa: E501\n 'namespace_string': (str,), # noqa: E501\n 'namespace_number': (float,), # noqa: E501\n 'namespace_integer': (int,), # noqa: E501\n 'namespace_boolean': (bool,), # noqa: E501\n 'namespace_array': ([int],), # noqa: E501\n 'namespace_wrapped_array': ([int],), # noqa: E501\n 'prefix_ns_string': (str,), # noqa: E501\n 'prefix_ns_number': (float,), # noqa: E501\n 'prefix_ns_integer': (int,), # noqa: E501\n 'prefix_ns_boolean': (bool,), # noqa: E501\n 'prefix_ns_array': ([int],), # noqa: E501\n 'prefix_ns_wrapped_array': ([int],), # noqa: E501\n }\n\n validations = {\n }\n\n additional_properties_type = None\n\n discriminator = None\n\n def __init__(self, _check_type=True, _from_server=False, _path_to_item=(), _configuration=None, **kwargs): # noqa: E501\n \"\"\"XmlItem - a model defined in OpenAPI\n\n\n Keyword Args:\n _check_type (bool): if True, values for parameters in openapi_types\n will be type checked and a TypeError will be\n raised if the wrong type is input.\n Defaults to True\n _path_to_item (tuple/list): This is a list of keys or values to\n drill down to the model in received_data\n when deserializing a response\n _from_server (bool): True if the data is from the server\n False if the data is from the client (default)\n _configuration (Configuration): the instance to use when\n deserializing a file_type parameter.\n If passed, type conversion is attempted\n If omitted no type conversion is done.\n attribute_string (str): [optional] # noqa: E501\n attribute_number (float): [optional] # noqa: E501\n attribute_integer (int): [optional] # noqa: E501\n attribute_boolean (bool): [optional] # noqa: E501\n wrapped_array ([int]): [optional] # noqa: E501\n name_string (str): [optional] # noqa: E501\n name_number (float): [optional] # noqa: E501\n name_integer (int): [optional] # noqa: E501\n name_boolean (bool): [optional] # noqa: E501\n name_array ([int]): [optional] # noqa: E501\n name_wrapped_array ([int]): [optional] # noqa: E501\n prefix_string (str): [optional] # noqa: E501\n prefix_number (float): [optional] # noqa: E501\n prefix_integer (int): [optional] # noqa: E501\n prefix_boolean (bool): [optional] # noqa: E501\n prefix_array ([int]): [optional] # noqa: E501\n prefix_wrapped_array ([int]): [optional] # noqa: E501\n namespace_string (str): [optional] # noqa: E501\n namespace_number (float): [optional] # noqa: E501\n namespace_integer (int): [optional] # noqa: E501\n namespace_boolean (bool): [optional] # noqa: E501\n namespace_array ([int]): [optional] # noqa: E501\n namespace_wrapped_array ([int]): [optional] # noqa: E501\n prefix_ns_string (str): [optional] # noqa: E501\n prefix_ns_number (float): [optional] # noqa: E501\n prefix_ns_integer (int): [optional] # noqa: E501\n prefix_ns_boolean (bool): [optional] # noqa: E501\n prefix_ns_array ([int]): [optional] # noqa: E501\n prefix_ns_wrapped_array ([int]): [optional] # noqa: E501\n \"\"\"\n self._data_store = {}\n self._check_type = _check_type\n self._from_server = _from_server\n self._path_to_item = _path_to_item\n self._configuration = _configuration\n\n for var_name, var_value in six.iteritems(kwargs):\n self.__set_item(var_name, var_value)\n\n def __setitem__(self, name, value):\n \"\"\"this allows us to set values with instance[field_name] = val\"\"\"\n self.__set_item(name, value)\n\n def __getitem__(self, name):\n \"\"\"this allows us to get a value with val = instance[field_name]\"\"\"\n return self.__get_item(name)\n\n @property\n def attribute_string(self):\n \"\"\"Gets the attribute_string of this XmlItem. # noqa: E501\n\n Returns:\n (str): The attribute_string of this XmlItem. # noqa: E501\n \"\"\"\n return self.__get_item('attribute_string')\n\n @attribute_string.setter\n def attribute_string(self, value):\n \"\"\"Sets the attribute_string of this XmlItem. # noqa: E501\n \"\"\"\n return self.__set_item('attribute_string', value)\n\n @property\n def attribute_number(self):\n \"\"\"Gets the attribute_number of this XmlItem. # noqa: E501\n\n Returns:\n (float): The attribute_number of this XmlItem. # noqa: E501\n \"\"\"\n return self.__get_item('attribute_number')\n\n @attribute_number.setter\n def attribute_number(self, value):\n \"\"\"Sets the attribute_number of this XmlItem. # noqa: E501\n \"\"\"\n return self.__set_item('attribute_number', value)\n\n @property\n def attribute_integer(self):\n \"\"\"Gets the attribute_integer of this XmlItem. # noqa: E501\n\n Returns:\n (int): The attribute_integer of this XmlItem. # noqa: E501\n \"\"\"\n return self.__get_item('attribute_integer')\n\n @attribute_integer.setter\n def attribute_integer(self, value):\n \"\"\"Sets the attribute_integer of this XmlItem. # noqa: E501\n \"\"\"\n return self.__set_item('attribute_integer', value)\n\n @property\n def attribute_boolean(self):\n \"\"\"Gets the attribute_boolean of this XmlItem. # noqa: E501\n\n Returns:\n (bool): The attribute_boolean of this XmlItem. # noqa: E501\n \"\"\"\n return self.__get_item('attribute_boolean')\n\n @attribute_boolean.setter\n def attribute_boolean(self, value):\n \"\"\"Sets the attribute_boolean of this XmlItem. # noqa: E501\n \"\"\"\n return self.__set_item('attribute_boolean', value)\n\n @property\n def wrapped_array(self):\n \"\"\"Gets the wrapped_array of this XmlItem. # noqa: E501\n\n Returns:\n ([int]): The wrapped_array of this XmlItem. # noqa: E501\n \"\"\"\n return self.__get_item('wrapped_array')\n\n @wrapped_array.setter\n def wrapped_array(self, value):\n \"\"\"Sets the wrapped_array of this XmlItem. # noqa: E501\n \"\"\"\n return self.__set_item('wrapped_array', value)\n\n @property\n def name_string(self):\n \"\"\"Gets the name_string of this XmlItem. # noqa: E501\n\n Returns:\n (str): The name_string of this XmlItem. # noqa: E501\n \"\"\"\n return self.__get_item('name_string')\n\n @name_string.setter\n def name_string(self, value):\n \"\"\"Sets the name_string of this XmlItem. # noqa: E501\n \"\"\"\n return self.__set_item('name_string', value)\n\n @property\n def name_number(self):\n \"\"\"Gets the name_number of this XmlItem. # noqa: E501\n\n Returns:\n (float): The name_number of this XmlItem. # noqa: E501\n \"\"\"\n return self.__get_item('name_number')\n\n @name_number.setter\n def name_number(self, value):\n \"\"\"Sets the name_number of this XmlItem. # noqa: E501\n \"\"\"\n return self.__set_item('name_number', value)\n\n @property\n def name_integer(self):\n \"\"\"Gets the name_integer of this XmlItem. # noqa: E501\n\n Returns:\n (int): The name_integer of this XmlItem. # noqa: E501\n \"\"\"\n return self.__get_item('name_integer')\n\n @name_integer.setter\n def name_integer(self, value):\n \"\"\"Sets the name_integer of this XmlItem. # noqa: E501\n \"\"\"\n return self.__set_item('name_integer', value)\n\n @property\n def name_boolean(self):\n \"\"\"Gets the name_boolean of this XmlItem. # noqa: E501\n\n Returns:\n (bool): The name_boolean of this XmlItem. # noqa: E501\n \"\"\"\n return self.__get_item('name_boolean')\n\n @name_boolean.setter\n def name_boolean(self, value):\n \"\"\"Sets the name_boolean of this XmlItem. # noqa: E501\n \"\"\"\n return self.__set_item('name_boolean', value)\n\n @property\n def name_array(self):\n \"\"\"Gets the name_array of this XmlItem. # noqa: E501\n\n Returns:\n ([int]): The name_array of this XmlItem. # noqa: E501\n \"\"\"\n return self.__get_item('name_array')\n\n @name_array.setter\n def name_array(self, value):\n \"\"\"Sets the name_array of this XmlItem. # noqa: E501\n \"\"\"\n return self.__set_item('name_array', value)\n\n @property\n def name_wrapped_array(self):\n \"\"\"Gets the name_wrapped_array of this XmlItem. # noqa: E501\n\n Returns:\n ([int]): The name_wrapped_array of this XmlItem. # noqa: E501\n \"\"\"\n return self.__get_item('name_wrapped_array')\n\n @name_wrapped_array.setter\n def name_wrapped_array(self, value):\n \"\"\"Sets the name_wrapped_array of this XmlItem. # noqa: E501\n \"\"\"\n return self.__set_item('name_wrapped_array', value)\n\n @property\n def prefix_string(self):\n \"\"\"Gets the prefix_string of this XmlItem. # noqa: E501\n\n Returns:\n (str): The prefix_string of this XmlItem. # noqa: E501\n \"\"\"\n return self.__get_item('prefix_string')\n\n @prefix_string.setter\n def prefix_string(self, value):\n \"\"\"Sets the prefix_string of this XmlItem. # noqa: E501\n \"\"\"\n return self.__set_item('prefix_string', value)\n\n @property\n def prefix_number(self):\n \"\"\"Gets the prefix_number of this XmlItem. # noqa: E501\n\n Returns:\n (float): The prefix_number of this XmlItem. # noqa: E501\n \"\"\"\n return self.__get_item('prefix_number')\n\n @prefix_number.setter\n def prefix_number(self, value):\n \"\"\"Sets the prefix_number of this XmlItem. # noqa: E501\n \"\"\"\n return self.__set_item('prefix_number', value)\n\n @property\n def prefix_integer(self):\n \"\"\"Gets the prefix_integer of this XmlItem. # noqa: E501\n\n Returns:\n (int): The prefix_integer of this XmlItem. # noqa: E501\n \"\"\"\n return self.__get_item('prefix_integer')\n\n @prefix_integer.setter\n def prefix_integer(self, value):\n \"\"\"Sets the prefix_integer of this XmlItem. # noqa: E501\n \"\"\"\n return self.__set_item('prefix_integer', value)\n\n @property\n def prefix_boolean(self):\n \"\"\"Gets the prefix_boolean of this XmlItem. # noqa: E501\n\n Returns:\n (bool): The prefix_boolean of this XmlItem. # noqa: E501\n \"\"\"\n return self.__get_item('prefix_boolean')\n\n @prefix_boolean.setter\n def prefix_boolean(self, value):\n \"\"\"Sets the prefix_boolean of this XmlItem. # noqa: E501\n \"\"\"\n return self.__set_item('prefix_boolean', value)\n\n @property\n def prefix_array(self):\n \"\"\"Gets the prefix_array of this XmlItem. # noqa: E501\n\n Returns:\n ([int]): The prefix_array of this XmlItem. # noqa: E501\n \"\"\"\n return self.__get_item('prefix_array')\n\n @prefix_array.setter\n def prefix_array(self, value):\n \"\"\"Sets the prefix_array of this XmlItem. # noqa: E501\n \"\"\"\n return self.__set_item('prefix_array', value)\n\n @property\n def prefix_wrapped_array(self):\n \"\"\"Gets the prefix_wrapped_array of this XmlItem. # noqa: E501\n\n Returns:\n ([int]): The prefix_wrapped_array of this XmlItem. # noqa: E501\n \"\"\"\n return self.__get_item('prefix_wrapped_array')\n\n @prefix_wrapped_array.setter\n def prefix_wrapped_array(self, value):\n \"\"\"Sets the prefix_wrapped_array of this XmlItem. # noqa: E501\n \"\"\"\n return self.__set_item('prefix_wrapped_array', value)\n\n @property\n def namespace_string(self):\n \"\"\"Gets the namespace_string of this XmlItem. # noqa: E501\n\n Returns:\n (str): The namespace_string of this XmlItem. # noqa: E501\n \"\"\"\n return self.__get_item('namespace_string')\n\n @namespace_string.setter\n def namespace_string(self, value):\n \"\"\"Sets the namespace_string of this XmlItem. # noqa: E501\n \"\"\"\n return self.__set_item('namespace_string', value)\n\n @property\n def namespace_number(self):\n \"\"\"Gets the namespace_number of this XmlItem. # noqa: E501\n\n Returns:\n (float): The namespace_number of this XmlItem. # noqa: E501\n \"\"\"\n return self.__get_item('namespace_number')\n\n @namespace_number.setter\n def namespace_number(self, value):\n \"\"\"Sets the namespace_number of this XmlItem. # noqa: E501\n \"\"\"\n return self.__set_item('namespace_number', value)\n\n @property\n def namespace_integer(self):\n \"\"\"Gets the namespace_integer of this XmlItem. # noqa: E501\n\n Returns:\n (int): The namespace_integer of this XmlItem. # noqa: E501\n \"\"\"\n return self.__get_item('namespace_integer')\n\n @namespace_integer.setter\n def namespace_integer(self, value):\n \"\"\"Sets the namespace_integer of this XmlItem. # noqa: E501\n \"\"\"\n return self.__set_item('namespace_integer', value)\n\n @property\n def namespace_boolean(self):\n \"\"\"Gets the namespace_boolean of this XmlItem. # noqa: E501\n\n Returns:\n (bool): The namespace_boolean of this XmlItem. # noqa: E501\n \"\"\"\n return self.__get_item('namespace_boolean')\n\n @namespace_boolean.setter\n def namespace_boolean(self, value):\n \"\"\"Sets the namespace_boolean of this XmlItem. # noqa: E501\n \"\"\"\n return self.__set_item('namespace_boolean', value)\n\n @property\n def namespace_array(self):\n \"\"\"Gets the namespace_array of this XmlItem. # noqa: E501\n\n Returns:\n ([int]): The namespace_array of this XmlItem. # noqa: E501\n \"\"\"\n return self.__get_item('namespace_array')\n\n @namespace_array.setter\n def namespace_array(self, value):\n \"\"\"Sets the namespace_array of this XmlItem. # noqa: E501\n \"\"\"\n return self.__set_item('namespace_array', value)\n\n @property\n def namespace_wrapped_array(self):\n \"\"\"Gets the namespace_wrapped_array of this XmlItem. # noqa: E501\n\n Returns:\n ([int]): The namespace_wrapped_array of this XmlItem. # noqa: E501\n \"\"\"\n return self.__get_item('namespace_wrapped_array')\n\n @namespace_wrapped_array.setter\n def namespace_wrapped_array(self, value):\n \"\"\"Sets the namespace_wrapped_array of this XmlItem. # noqa: E501\n \"\"\"\n return self.__set_item('namespace_wrapped_array', value)\n\n @property\n def prefix_ns_string(self):\n \"\"\"Gets the prefix_ns_string of this XmlItem. # noqa: E501\n\n Returns:\n (str): The prefix_ns_string of this XmlItem. # noqa: E501\n \"\"\"\n return self.__get_item('prefix_ns_string')\n\n @prefix_ns_string.setter\n def prefix_ns_string(self, value):\n \"\"\"Sets the prefix_ns_string of this XmlItem. # noqa: E501\n \"\"\"\n return self.__set_item('prefix_ns_string', value)\n\n @property\n def prefix_ns_number(self):\n \"\"\"Gets the prefix_ns_number of this XmlItem. # noqa: E501\n\n Returns:\n (float): The prefix_ns_number of this XmlItem. # noqa: E501\n \"\"\"\n return self.__get_item('prefix_ns_number')\n\n @prefix_ns_number.setter\n def prefix_ns_number(self, value):\n \"\"\"Sets the prefix_ns_number of this XmlItem. # noqa: E501\n \"\"\"\n return self.__set_item('prefix_ns_number', value)\n\n @property\n def prefix_ns_integer(self):\n \"\"\"Gets the prefix_ns_integer of this XmlItem. # noqa: E501\n\n Returns:\n (int): The prefix_ns_integer of this XmlItem. # noqa: E501\n \"\"\"\n return self.__get_item('prefix_ns_integer')\n\n @prefix_ns_integer.setter\n def prefix_ns_integer(self, value):\n \"\"\"Sets the prefix_ns_integer of this XmlItem. # noqa: E501\n \"\"\"\n return self.__set_item('prefix_ns_integer', value)\n\n @property\n def prefix_ns_boolean(self):\n \"\"\"Gets the prefix_ns_boolean of this XmlItem. # noqa: E501\n\n Returns:\n (bool): The prefix_ns_boolean of this XmlItem. # noqa: E501\n \"\"\"\n return self.__get_item('prefix_ns_boolean')\n\n @prefix_ns_boolean.setter\n def prefix_ns_boolean(self, value):\n \"\"\"Sets the prefix_ns_boolean of this XmlItem. # noqa: E501\n \"\"\"\n return self.__set_item('prefix_ns_boolean', value)\n\n @property\n def prefix_ns_array(self):\n \"\"\"Gets the prefix_ns_array of this XmlItem. # noqa: E501\n\n Returns:\n ([int]): The prefix_ns_array of this XmlItem. # noqa: E501\n \"\"\"\n return self.__get_item('prefix_ns_array')\n\n @prefix_ns_array.setter\n def prefix_ns_array(self, value):\n \"\"\"Sets the prefix_ns_array of this XmlItem. # noqa: E501\n \"\"\"\n return self.__set_item('prefix_ns_array', value)\n\n @property\n def prefix_ns_wrapped_array(self):\n \"\"\"Gets the prefix_ns_wrapped_array of this XmlItem. # noqa: E501\n\n Returns:\n ([int]): The prefix_ns_wrapped_array of this XmlItem. # noqa: E501\n \"\"\"\n return self.__get_item('prefix_ns_wrapped_array')\n\n @prefix_ns_wrapped_array.setter\n def prefix_ns_wrapped_array(self, value):\n \"\"\"Sets the prefix_ns_wrapped_array of this XmlItem. # noqa: E501\n \"\"\"\n return self.__set_item('prefix_ns_wrapped_array', value)\n\n def to_dict(self):\n \"\"\"Returns the model properties as a dict\"\"\"\n return model_to_dict(self, serialize=False)\n\n def to_str(self):\n \"\"\"Returns the string representation of the model\"\"\"\n return pprint.pformat(self.to_dict())\n\n def __repr__(self):\n \"\"\"For `print` and `pprint`\"\"\"\n return self.to_str()\n\n def __eq__(self, other):\n \"\"\"Returns true if both objects are equal\"\"\"\n if not isinstance(other, XmlItem):\n return False\n\n if not set(self._data_store.keys()) == set(other._data_store.keys()):\n return False\n for _var_name, this_val in six.iteritems(self._data_store):\n that_val = other._data_store[_var_name]\n types = set()\n types.add(this_val.__class__)\n types.add(that_val.__class__)\n vals_equal = this_val == that_val\n if (not six.PY3 and\n len(types) == 2 and unicode in types): # noqa: F821\n vals_equal = (\n this_val.encode('utf-8') == that_val.encode('utf-8')\n )\n if not vals_equal:\n return False\n return True\n\n def __ne__(self, other):\n \"\"\"Returns true if both objects are not equal\"\"\"\n return not self == other\n"},"input_ids":{"kind":"list like","value":[2,19617,25,3384,69,12,23,198,198,37811,198,220,220,220,4946,17614,4767,8095,628,220,220,220,770,1020,318,8384,329,4856,4767,8095,4382,290,4909,8390,886,13033,11,4981,13,4222,466,407,779,428,329,597,584,4007,13,6093,3435,25,19990,26867,220,1303,645,20402,25,412,33548,628,220,220,220,383,2196,286,262,4946,17614,3188,25,352,13,15,13,15,198,220,220,220,2980,515,416,25,3740,1378,9654,15042,12,8612,1352,13,13670,198,37811,628,198,11748,279,4798,220,1303,645,20402,25,376,21844,198,11748,302,220,1303,645,20402,25,376,21844,198,198,11748,2237,220,1303,645,20402,25,376,21844,198,198,6738,4273,8095,62,15042,13,1069,11755,1330,357,220,1303,645,20402,25,376,21844,198,220,220,220,5949,72,9218,12331,11,198,220,220,220,5949,72,6030,12331,11,198,220,220,220,5949,72,11395,12331,11,198,8,198,6738,4273,8095,62,15042,13,19849,62,26791,1330,357,220,1303,645,20402,25,376,21844,198,220,220,220,9104,26447,11,198,220,220,220,9104,26437,11,198,220,220,220,2198,62,40845,62,27160,11,198,220,220,220,2198,62,12102,602,11,198,220,220,220,3128,11,198,220,220,220,4818,8079,11,198,220,220,220,2393,62,4906,11,198,220,220,220,651,62,36439,62,4871,11,198,220,220,220,493,11,198,220,220,220,2746,62,1462,62,11600,11,198,220,220,220,4844,62,4906,11,198,220,220,220,965,11,198,220,220,220,2099,62,18224,62,20500,11,198,220,220,220,26571,62,392,62,1102,1851,62,19199,198,8,628,198,4871,1395,4029,7449,7,17633,26447,2599,198,220,220,220,37227,16580,25,770,1398,318,8295,7560,416,4946,17614,35986,13,198,220,220,220,6524,25,3740,1378,9654,15042,12,8612,1352,13,13670,628,220,220,220,2141,407,4370,262,1398,14500,13,628,220,220,220,49213,25,198,220,220,220,220,220,3142,62,27160,357,11600,2599,383,1994,318,262,46545,3108,284,262,11688,198,220,220,220,220,220,220,220,220,220,290,262,329,1401,62,3672,428,318,357,7785,62,3672,11,737,383,1988,318,257,8633,198,220,220,220,220,220,220,220,220,220,351,257,3139,1143,1994,12059,262,3142,1988,290,281,3142,198,220,220,220,220,220,220,220,220,220,1988,13,2312,8633,82,3650,262,3142,33829,3815,13,198,220,220,220,220,220,11688,62,8899,357,11600,2599,383,1994,318,11688,1438,198,220,220,220,220,220,220,220,220,220,290,262,1988,318,33918,1994,287,6770,13,198,220,220,220,220,220,6534,20900,62,8367,62,4871,62,8899,357,11600,2599,317,8633,284,467,422,262,6534,20900,198,220,220,220,220,220,220,220,220,220,7885,1988,284,262,6534,20900,1398,1438,13,198,220,220,220,220,220,1280,15042,62,19199,357,11600,2599,383,1994,318,11688,1438,198,220,220,220,220,220,220,220,220,220,290,262,1988,318,11688,2099,13,198,220,220,220,220,220,4938,602,357,11600,2599,383,1994,318,262,46545,3108,284,262,11688,198,220,220,220,220,220,220,220,220,220,290,262,329,1401,62,3672,428,318,357,7785,62,3672,11,737,383,1988,318,257,8633,198,220,220,220,220,220,220,220,220,220,326,7000,4938,602,329,3509,62,13664,11,949,62,13664,11,3509,62,23814,11,198,220,220,220,220,220,220,220,220,220,949,62,23814,11,8568,62,47033,11,19889,62,47033,11,8568,62,39504,11,198,220,220,220,220,220,220,220,220,220,19889,62,39504,11,290,40364,13,198,220,220,220,220,220,3224,62,48310,62,4906,357,83,29291,2599,317,46545,286,6097,6292,198,220,220,220,220,220,220,220,220,220,355,3224,6608,3815,13,198,220,220,220,37227,628,220,220,220,3142,62,27160,796,1391,198,220,220,220,1782,628,220,220,220,11688,62,8899,796,1391,198,220,220,220,220,220,220,220,705,42348,62,8841,10354,705,42348,62,8841,3256,220,1303,645,20402,25,412,33548,198,220,220,220,220,220,220,220,705,42348,62,17618,10354,705,42348,62,17618,3256,220,1303,645,20402,25,412,33548,198,220,220,220,220,220,220,220,705,42348,62,41433,10354,705,42348,62,41433,3256,220,1303,645,20402,25,412,33548,198,220,220,220,220,220,220,220,705,42348,62,2127,21052,10354,705,42348,62,2127,21052,3256,220,1303,645,20402,25,412,33548,198,220,220,220,220,220,220,220,705,29988,1496,62,18747,10354,705,29988,1496,62,18747,3256,220,1303,645,20402,25,412,33548,198,220,220,220,220,220,220,220,705,3672,62,8841,10354,705,3672,62,8841,3256,220,1303,645,20402,25,412,33548,198,220,220,220,220,220,220,220,705,3672,62,17618,10354,705,3672,62,17618,3256,220,1303,645,20402,25,412,33548,198,220,220,220,220,220,220,220,705,3672,62,41433,10354,705,3672,62,41433,3256,220,1303,645,20402,25,412,33548,198,220,220,220,220,220,220,220,705,3672,62,2127,21052,10354,705,3672,62,2127,21052,3256,220,1303,645,20402,25,412,33548,198,220,220,220,220,220,220,220,705,3672,62,18747,10354,705,3672,62,18747,3256,220,1303,645,20402,25,412,33548,198,220,220,220,220,220,220,220,705,3672,62,29988,1496,62,18747,10354,705,3672,62,29988,1496,62,18747,3256,220,1303,645,20402,25,412,33548,198,220,220,220,220,220,220,220,705,40290,62,8841,10354,705,40290,62,8841,3256,220,1303,645,20402,25,412,33548,198,220,220,220,220,220,220,220,705,40290,62,17618,10354,705,40290,62,17618,3256,220,1303,645,20402,25,412,33548,198,220,220,220,220,220,220,220,705,40290,62,41433,10354,705,40290,62,41433,3256,220,1303,645,20402,25,412,33548,198,220,220,220,220,220,220,220,705,40290,62,2127,21052,10354,705,40290,62,2127,21052,3256,220,1303,645,20402,25,412,33548,198,220,220,220,220,220,220,220,705,40290,62,18747,10354,705,40290,62,18747,3256,220,1303,645,20402,25,412,33548,198,220,220,220,220,220,220,220,705,40290,62,29988,1496,62,18747,10354,705,40290,62,29988,1496,62,18747,3256,220,1303,645,20402,25,412,33548,198,220,220,220,220,220,220,220,705,14933,10223,62,8841,10354,705,14933,10223,62,8841,3256,220,1303,645,20402,25,412,33548,198,220,220,220,220,220,220,220,705,14933,10223,62,17618,10354,705,14933,10223,62,17618,3256,220,1303,645,20402,25,412,33548,198,220,220,220,220,220,220,220,705,14933,10223,62,41433,10354,705,14933,10223,62,41433,3256,220,1303,645,20402,25,412,33548,198,220,220,220,220,220,220,220,705,14933,10223,62,2127,21052,10354,705,14933,10223,62,2127,21052,3256,220,1303,645,20402,25,412,33548,198,220,220,220,220,220,220,220,705,14933,10223,62,18747,10354,705,14933,10223,62,18747,3256,220,1303,645,20402,25,412,33548,198,220,220,220,220,220,220,220,705,14933,10223,62,29988,1496,62,18747,10354,705,14933,10223,62,29988,1496,62,18747,3256,220,1303,645,20402,25,412,33548,198,220,220,220,220,220,220,220,705,40290,62,5907,62,8841,10354,705,40290,62,5907,62,8841,3256,220,1303,645,20402,25,412,33548,198,220,220,220,220,220,220,220,705,40290,62,5907,62,17618,10354,705,40290,62,5907,62,17618,3256,220,1303,645,20402,25,412,33548,198,220,220,220,220,220,220,220,705,40290,62,5907,62,41433,10354,705,40290,62,5907,62,41433,3256,220,1303,645,20402,25,412,33548,198,220,220,220,220,220,220,220,705,40290,62,5907,62,2127,21052,10354,705,40290,62,5907,62,2127,21052,3256,220,1303,645,20402,25,412,33548,198,220,220,220,220,220,220,220,705,40290,62,5907,62,18747,10354,705,40290,62,5907,62,18747,3256,220,1303,645,20402,25,412,33548,198,220,220,220,220,220,220,220,705,40290,62,5907,62,29988,1496,62,18747,10354,705,40290,62,5907,62,29988,1496,62,18747,6,220,1303,645,20402,25,412,33548,198,220,220,220,1782,628,220,220,220,1280,15042,62,19199,796,1391,198,220,220,220,220,220,220,220,705,42348,62,8841,10354,357,2536,11,828,220,1303,645,20402,25,412,33548,198,220,220,220,220,220,220,220,705,42348,62,17618,10354,357,22468,11,828,220,1303,645,20402,25,412,33548,198,220,220,220,220,220,220,220,705,42348,62,41433,10354,357,600,11,828,220,1303,645,20402,25,412,33548,198,220,220,220,220,220,220,220,705,42348,62,2127,21052,10354,357,30388,11,828,220,1303,645,20402,25,412,33548,198,220,220,220,220,220,220,220,705,29988,1496,62,18747,10354,29565,600,4357,828,220,1303,645,20402,25,412,33548,198,220,220,220,220,220,220,220,705,3672,62,8841,10354,357,2536,11,828,220,1303,645,20402,25,412,33548,198,220,220,220,220,220,220,220,705,3672,62,17618,10354,357,22468,11,828,220,1303,645,20402,25,412,33548,198,220,220,220,220,220,220,220,705,3672,62,41433,10354,357,600,11,828,220,1303,645,20402,25,412,33548,198,220,220,220,220,220,220,220,705,3672,62,2127,21052,10354,357,30388,11,828,220,1303,645,20402,25,412,33548,198,220,220,220,220,220,220,220,705,3672,62,18747,10354,29565,600,4357,828,220,1303,645,20402,25,412,33548,198,220,220,220,220,220,220,220,705,3672,62,29988,1496,62,18747,10354,29565,600,4357,828,220,1303,645,20402,25,412,33548,198,220,220,220,220,220,220,220,705,40290,62,8841,10354,357,2536,11,828,220,1303,645,20402,25,412,33548,198,220,220,220,220,220,220,220,705,40290,62,17618,10354,357,22468,11,828,220,1303,645,20402,25,412,33548,198,220,220,220,220,220,220,220,705,40290,62,41433,10354,357,600,11,828,220,1303,645,20402,25,412,33548,198,220,220,220,220,220,220,220,705,40290,62,2127,21052,10354,357,30388,11,828,220,1303,645,20402,25,412,33548,198,220,220,220,220,220,220,220,705,40290,62,18747,10354,29565,600,4357,828,220,1303,645,20402,25,412,33548,198,220,220,220,220,220,220,220,705,40290,62,29988,1496,62,18747,10354,29565,600,4357,828,220,1303,645,20402,25,412,33548,198,220,220,220,220,220,220,220,705,14933,10223,62,8841,10354,357,2536,11,828,220,1303,645,20402,25,412,33548,198,220,220,220,220,220,220,220,705,14933,10223,62,17618,10354,357,22468,11,828,220,1303,645,20402,25,412,33548,198,220,220,220,220,220,220,220,705,14933,10223,62,41433,10354,357,600,11,828,220,1303,645,20402,25,412,33548,198,220,220,220,220,220,220,220,705,14933,10223,62,2127,21052,10354,357,30388,11,828,220,1303,645,20402,25,412,33548,198,220,220,220,220,220,220,220,705,14933,10223,62,18747,10354,29565,600,4357,828,220,1303,645,20402,25,412,33548,198,220,220,220,220,220,220,220,705,14933,10223,62,29988,1496,62,18747,10354,29565,600,4357,828,220,1303,645,20402,25,412,33548,198,220,220,220,220,220,220,220,705,40290,62,5907,62,8841,10354,357,2536,11,828,220,1303,645,20402,25,412,33548,198,220,220,220,220,220,220,220,705,40290,62,5907,62,17618,10354,357,22468,11,828,220,1303,645,20402,25,412,33548,198,220,220,220,220,220,220,220,705,40290,62,5907,62,41433,10354,357,600,11,828,220,1303,645,20402,25,412,33548,198,220,220,220,220,220,220,220,705,40290,62,5907,62,2127,21052,10354,357,30388,11,828,220,1303,645,20402,25,412,33548,198,220,220,220,220,220,220,220,705,40290,62,5907,62,18747,10354,29565,600,4357,828,220,1303,645,20402,25,412,33548,198,220,220,220,220,220,220,220,705,40290,62,5907,62,29988,1496,62,18747,10354,29565,600,4357,828,220,1303,645,20402,25,412,33548,198,220,220,220,1782,628,220,220,220,4938,602,796,1391,198,220,220,220,1782,628,220,220,220,3224,62,48310,62,4906,796,6045,628,220,220,220,6534,20900,796,6045,628,220,220,220,825,11593,15003,834,7,944,11,4808,9122,62,4906,28,17821,11,4808,6738,62,15388,28,25101,11,4808,6978,62,1462,62,9186,16193,828,4808,11250,3924,28,14202,11,12429,46265,22046,2599,220,1303,645,20402,25,412,33548,198,220,220,220,220,220,220,220,37227,55,4029,7449,532,257,2746,5447,287,4946,17614,628,198,220,220,220,220,220,220,220,7383,4775,943,14542,25,198,220,220,220,220,220,220,220,220,220,220,220,4808,9122,62,4906,357,30388,2599,611,6407,11,3815,329,10007,287,1280,15042,62,19199,198,220,220,220,220,220,220,220,220,220,220,220,220,220,220,220,220,220,220,220,220,220,220,220,220,220,220,220,220,220,220,220,481,307,2099,10667,290,257,5994,12331,481,307,198,220,220,220,220,220,220,220,220,220,220,220,220,220,220,220,220,220,220,220,220,220,220,220,220,220,220,220,220,220,220,220,4376,611,262,2642,2099,318,5128,13,198,220,220,220,220,220,220,220,220,220,220,220,220,220,220,220,220,220,220,220,220,220,220,220,220,220,220,220,220,220,220,220,2896,13185,284,6407,198,220,220,220,220,220,220,220,220,220,220,220,4808,6978,62,1462,62,9186,357,83,29291,14,4868,2599,770,318,257,1351,286,8251,393,3815,284,198,220,220,220,220,220,220,220,220,220,220,220,220,220,220,220,220,220,220,220,220,220,220,220,220,220,220,220,220,220,220,220,16007,866,284,262,2746,287,2722,62,7890,198,220,220,220,220,220,220,220,220,220,220,220,220,220,220,220,220,220,220,220,220,220,220,220,220,220,220,220,220,220,220,220,618,748,48499,2890,257,2882,198,220,220,220,220,220,220,220,220,220,220,220,4808,6738,62,15388,357,30388,2599,6407,611,262,1366,318,422,262,4382,198,220,220,220,220,220,220,220,220,220,220,220,220,220,220,220,220,220,220,220,220,220,220,220,220,220,220,220,220,220,220,220,10352,611,262,1366,318,422,262,5456,357,12286,8,198,220,220,220,220,220,220,220,220,220,220,220,4808,11250,3924,357,38149,2599,262,4554,284,779,618,198,220,220,220,220,220,220,220,220,220,220,220,220,220,220,220,220,220,220,220,220,220,220,220,220,220,220,220,220,220,220,220,748,48499,2890,257,2393,62,4906,11507,13,198,220,220,220,220,220,220,220,220,220,220,220,220,220,220,220,220,220,220,220,220,220,220,220,220,220,220,220,220,220,220,220,1002,3804,11,2099,11315,318,7482,198,220,220,220,220,220,220,220,220,220,220,220,220,220,220,220,220,220,220,220,220,220,220,220,220,220,220,220,220,220,220,220,1002,22532,645,2099,11315,318,1760,13,198,220,220,220,220,220,220,220,220,220,220,220,11688,62,8841,357,2536,2599,685,25968,60,220,1303,645,20402,25,412,33548,198,220,220,220,220,220,220,220,220,220,220,220,11688,62,17618,357,22468,2599,685,25968,60,220,1303,645,20402,25,412,33548,198,220,220,220,220,220,220,220,220,220,220,220,11688,62,41433,357,600,2599,685,25968,60,220,1303,645,20402,25,412,33548,198,220,220,220,220,220,220,220,220,220,220,220,11688,62,2127,21052,357,30388,2599,685,25968,60,220,1303,645,20402,25,412,33548,198,220,220,220,220,220,220,220,220,220,220,220,12908,62,18747,29565,600,60,2599,685,25968,60,220,1303,645,20402,25,412,33548,198,220,220,220,220,220,220,220,220,220,220,220,1438,62,8841,357,2536,2599,685,25968,60,220,1303,645,20402,25,412,33548,198,220,220,220,220,220,220,220,220,220,220,220,1438,62,17618,357,22468,2599,685,25968,60,220,1303,645,20402,25,412,33548,198,220,220,220,220,220,220,220,220,220,220,220,1438,62,41433,357,600,2599,685,25968,60,220,1303,645,20402,25,412,33548,198,220,220,220,220,220,220,220,220,220,220,220,1438,62,2127,21052,357,30388,2599,685,25968,60,220,1303,645,20402,25,412,33548,198,220,220,220,220,220,220,220,220,220,220,220,1438,62,18747,29565,600,60,2599,685,25968,60,220,1303,645,20402,25,412,33548,198,220,220,220,220,220,220,220,220,220,220,220,1438,62,29988,1496,62,18747,29565,600,60,2599,685,25968,60,220,1303,645,20402,25,412,33548,198,220,220,220,220,220,220,220,220,220,220,220,21231,62,8841,357,2536,2599,685,25968,60,220,1303,645,20402,25,412,33548,198,220,220,220,220,220,220,220,220,220,220,220,21231,62,17618,357,22468,2599,685,25968,60,220,1303,645,20402,25,412,33548,198,220,220,220,220,220,220,220,220,220,220,220,21231,62,41433,357,600,2599,685,25968,60,220,1303,645,20402,25,412,33548,198,220,220,220,220,220,220,220,220,220,220,220,21231,62,2127,21052,357,30388,2599,685,25968,60,220,1303,645,20402,25,412,33548,198,220,220,220,220,220,220,220,220,220,220,220,21231,62,18747,29565,600,60,2599,685,25968,60,220,1303,645,20402,25,412,33548,198,220,220,220,220,220,220,220,220,220,220,220,21231,62,29988,1496,62,18747,29565,600,60,2599,685,25968,60,220,1303,645,20402,25,412,33548,198,220,220,220,220,220,220,220,220,220,220,220,25745,62,8841,357,2536,2599,685,25968,60,220,1303,645,20402,25,412,33548,198,220,220,220,220,220,220,220,220,220,220,220,25745,62,17618,357,22468,2599,685,25968,60,220,1303,645,20402,25,412,33548,198,220,220,220,220,220,220,220,220,220,220,220,25745,62,41433,357,600,2599,685,25968,60,220,1303,645,20402,25,412,33548,198,220,220,220,220,220,220,220,220,220,220,220,25745,62,2127,21052,357,30388,2599,685,25968,60,220,1303,645,20402,25,412,33548,198,220,220,220,220,220,220,220,220,220,220,220,25745,62,18747,29565,600,60,2599,685,25968,60,220,1303,645,20402,25,412,33548,198,220,220,220,220,220,220,220,220,220,220,220,25745,62,29988,1496,62,18747,29565,600,60,2599,685,25968,60,220,1303,645,20402,25,412,33548,198,220,220,220,220,220,220,220,220,220,220,220,21231,62,5907,62,8841,357,2536,2599,685,25968,60,220,1303,645,20402,25,412,33548,198,220,220,220,220,220,220,220,220,220,220,220,21231,62,5907,62,17618,357,22468,2599,685,25968,60,220,1303,645,20402,25,412,33548,198,220,220,220,220,220,220,220,220,220,220,220,21231,62,5907,62,41433,357,600,2599,685,25968,60,220,1303,645,20402,25,412,33548,198,220,220,220,220,220,220,220,220,220,220,220,21231,62,5907,62,2127,21052,357,30388,2599,685,25968,60,220,1303,645,20402,25,412,33548,198,220,220,220,220,220,220,220,220,220,220,220,21231,62,5907,62,18747,29565,600,60,2599,685,25968,60,220,1303,645,20402,25,412,33548,198,220,220,220,220,220,220,220,220,220,220,220,21231,62,5907,62,29988,1496,62,18747,29565,600,60,2599,685,25968,60,220,1303,645,20402,25,412,33548,198,220,220,220,220,220,220,220,37227,198,220,220,220,220,220,220,220,2116,13557,7890,62,8095,796,23884,198,220,220,220,220,220,220,220,2116,13557,9122,62,4906,796,4808,9122,62,4906,198,220,220,220,220,220,220,220,2116,13557,6738,62,15388,796,4808,6738,62,15388,198,220,220,220,220,220,220,220,2116,13557,6978,62,1462,62,9186,796,4808,6978,62,1462,62,9186,198,220,220,220,220,220,220,220,2116,13557,11250,3924,796,4808,11250,3924,628,220,220,220,220,220,220,220,329,1401,62,3672,11,1401,62,8367,287,2237,13,2676,23814,7,46265,22046,2599,198,220,220,220,220,220,220,220,220,220,220,220,2116,13,834,2617,62,9186,7,7785,62,3672,11,1401,62,8367,8,628,220,220,220,825,11593,2617,9186,834,7,944,11,1438,11,1988,2599,198,220,220,220,220,220,220,220,37227,5661,3578,514,284,900,3815,351,4554,58,3245,62,3672,60,796,1188,37811,198,220,220,220,220,220,220,220,2116,13,834,2617,62,9186,7,3672,11,1988,8,628,220,220,220,825,11593,1136,9186,834,7,944,11,1438,2599,198,220,220,220,220,220,220,220,37227,5661,3578,514,284,651,257,1988,351,1188,796,4554,58,3245,62,3672,60,37811,198,220,220,220,220,220,220,220,1441,2116,13,834,1136,62,9186,7,3672,8,628,220,220,220,2488,26745,198,220,220,220,825,11688,62,8841,7,944,2599,198,220,220,220,220,220,220,220,37227,38,1039,262,11688,62,8841,286,428,1395,4029,7449,13,220,1303,645,20402,25,412,33548,628,220,220,220,220,220,220,220,16409,25,198,220,220,220,220,220,220,220,220,220,220,220,357,2536,2599,383,11688,62,8841,286,428,1395,4029,7449,13,220,1303,645,20402,25,412,33548,198,220,220,220,220,220,220,220,37227,198,220,220,220,220,220,220,220,1441,2116,13,834,1136,62,9186,10786,42348,62,8841,11537,628,220,220,220,2488,42348,62,8841,13,2617,353,198,220,220,220,825,11688,62,8841,7,944,11,1988,2599,198,220,220,220,220,220,220,220,37227,50,1039,262,11688,62,8841,286,428,1395,4029,7449,13,220,1303,645,20402,25,412,33548,198,220,220,220,220,220,220,220,37227,198,220,220,220,220,220,220,220,1441,2116,13,834,2617,62,9186,10786,42348,62,8841,3256,1988,8,628,220,220,220,2488,26745,198,220,220,220,825,11688,62,17618,7,944,2599,198,220,220,220,220,220,220,220,37227,38,1039,262,11688,62,17618,286,428,1395,4029,7449,13,220,1303,645,20402,25,412,33548,628,220,220,220,220,220,220,220,16409,25,198,220,220,220,220,220,220,220,220,220,220,220,357,22468,2599,383,11688,62,17618,286,428,1395,4029,7449,13,220,1303,645,20402,25,412,33548,198,220,220,220,220,220,220,220,37227,198,220,220,220,220,220,220,220,1441,2116,13,834,1136,62,9186,10786,42348,62,17618,11537,628,220,220,220,2488,42348,62,17618,13,2617,353,198,220,220,220,825,11688,62,17618,7,944,11,1988,2599,198,220,220,220,220,220,220,220,37227,50,1039,262,11688,62,17618,286,428,1395,4029,7449,13,220,1303,645,20402,25,412,33548,198,220,220,220,220,220,220,220,37227,198,220,220,220,220,220,220,220,1441,2116,13,834,2617,62,9186,10786,42348,62,17618,3256,1988,8,628,220,220,220,2488,26745,198,220,220,220,825,11688,62,41433,7,944,2599,198,220,220,220,220,220,220,220,37227,38,1039,262,11688,62,41433,286,428,1395,4029,7449,13,220,1303,645,20402,25,412,33548,628,220,220,220,220,220,220,220,16409,25,198,220,220,220,220,220,220,220,220,220,220,220,357,600,2599,383,11688,62,41433,286,428,1395,4029,7449,13,220,1303,645,20402,25,412,33548,198,220,220,220,220,220,220,220,37227,198,220,220,220,220,220,220,220,1441,2116,13,834,1136,62,9186,10786,42348,62,41433,11537,628,220,220,220,2488,42348,62,41433,13,2617,353,198,220,220,220,825,11688,62,41433,7,944,11,1988,2599,198,220,220,220,220,220,220,220,37227,50,1039,262,11688,62,41433,286,428,1395,4029,7449,13,220,1303,645,20402,25,412,33548,198,220,220,220,220,220,220,220,37227,198,220,220,220,220,220,220,220,1441,2116,13,834,2617,62,9186,10786,42348,62,41433,3256,1988,8,628,220,220,220,2488,26745,198,220,220,220,825,11688,62,2127,21052,7,944,2599,198,220,220,220,220,220,220,220,37227,38,1039,262,11688,62,2127,21052,286,428,1395,4029,7449,13,220,1303,645,20402,25,412,33548,628,220,220,220,220,220,220,220,16409,25,198,220,220,220,220,220,220,220,220,220,220,220,357,30388,2599,383,11688,62,2127,21052,286,428,1395,4029,7449,13,220,1303,645,20402,25,412,33548,198,220,220,220,220,220,220,220,37227,198,220,220,220,220,220,220,220,1441,2116,13,834,1136,62,9186,10786,42348,62,2127,21052,11537,628,220,220,220,2488,42348,62,2127,21052,13,2617,353,198,220,220,220,825,11688,62,2127,21052,7,944,11,1988,2599,198,220,220,220,220,220,220,220,37227,50,1039,262,11688,62,2127,21052,286,428,1395,4029,7449,13,220,1303,645,20402,25,412,33548,198,220,220,220,220,220,220,220,37227,198,220,220,220,220,220,220,220,1441,2116,13,834,2617,62,9186,10786,42348,62,2127,21052,3256,1988,8,628,220,220,220,2488,26745,198,220,220,220,825,12908,62,18747,7,944,2599,198,220,220,220,220,220,220,220,37227,38,1039,262,12908,62,18747,286,428,1395,4029,7449,13,220,1303,645,20402,25,412,33548,628,220,220,220,220,220,220,220,16409,25,198,220,220,220,220,220,220,220,220,220,220,220,29565,600,60,2599,383,12908,62,18747,286,428,1395,4029,7449,13,220,1303,645,20402,25,412,33548,198,220,220,220,220,220,220,220,37227,198,220,220,220,220,220,220,220,1441,2116,13,834,1136,62,9186,10786,29988,1496,62,18747,11537,628,220,220,220,2488,29988,1496,62,18747,13,2617,353,198,220,220,220,825,12908,62,18747,7,944,11,1988,2599,198,220,220,220,220,220,220,220,37227,50,1039,262,12908,62,18747,286,428,1395,4029,7449,13,220,1303,645,20402,25,412,33548,198,220,220,220,220,220,220,220,37227,198,220,220,220,220,220,220,220,1441,2116,13,834,2617,62,9186,10786,29988,1496,62,18747,3256,1988,8,628,220,220,220,2488,26745,198,220,220,220,825,1438,62,8841,7,944,2599,198,220,220,220,220,220,220,220,37227,38,1039,262,1438,62,8841,286,428,1395,4029,7449,13,220,1303,645,20402,25,412,33548,628,220,220,220,220,220,220,220,16409,25,198,220,220,220,220,220,220,220,220,220,220,220,357,2536,2599,383,1438,62,8841,286,428,1395,4029,7449,13,220,1303,645,20402,25,412,33548,198,220,220,220,220,220,220,220,37227,198,220,220,220,220,220,220,220,1441,2116,13,834,1136,62,9186,10786,3672,62,8841,11537,628,220,220,220,2488,3672,62,8841,13,2617,353,198,220,220,220,825,1438,62,8841,7,944,11,1988,2599,198,220,220,220,220,220,220,220,37227,50,1039,262,1438,62,8841,286,428,1395,4029,7449,13,220,1303,645,20402,25,412,33548,198,220,220,220,220,220,220,220,37227,198,220,220,220,220,220,220,220,1441,2116,13,834,2617,62,9186,10786,3672,62,8841,3256,1988,8,628,220,220,220,2488,26745,198,220,220,220,825,1438,62,17618,7,944,2599,198,220,220,220,220,220,220,220,37227,38,1039,262,1438,62,17618,286,428,1395,4029,7449,13,220,1303,645,20402,25,412,33548,628,220,220,220,220,220,220,220,16409,25,198,220,220,220,220,220,220,220,220,220,220,220,357,22468,2599,383,1438,62,17618,286,428,1395,4029,7449,13,220,1303,645,20402,25,412,33548,198,220,220,220,220,220,220,220,37227,198,220,220,220,220,220,220,220,1441,2116,13,834,1136,62,9186,10786,3672,62,17618,11537,628,220,220,220,2488,3672,62,17618,13,2617,353,198,220,220,220,825,1438,62,17618,7,944,11,1988,2599,198,220,220,220,220,220,220,220,37227,50,1039,262,1438,62,17618,286,428,1395,4029,7449,13,220,1303,645,20402,25,412,33548,198,220,220,220,220,220,220,220,37227,198,220,220,220,220,220,220,220,1441,2116,13,834,2617,62,9186,10786,3672,62,17618,3256,1988,8,628,220,220,220,2488,26745,198,220,220,220,825,1438,62,41433,7,944,2599,198,220,220,220,220,220,220,220,37227,38,1039,262,1438,62,41433,286,428,1395,4029,7449,13,220,1303,645,20402,25,412,33548,628,220,220,220,220,220,220,220,16409,25,198,220,220,220,220,220,220,220,220,220,220,220,357,600,2599,383,1438,62,41433,286,428,1395,4029,7449,13,220,1303,645,20402,25,412,33548,198,220,220,220,220,220,220,220,37227,198,220,220,220,220,220,220,220,1441,2116,13,834,1136,62,9186,10786,3672,62,41433,11537,628,220,220,220,2488,3672,62,41433,13,2617,353,198,220,220,220,825,1438,62,41433,7,944,11,1988,2599,198,220,220,220,220,220,220,220,37227,50,1039,262,1438,62,41433,286,428,1395,4029,7449,13,220,1303,645,20402,25,412,33548,198,220,220,220,220,220,220,220,37227,198,220,220,220,220,220,220,220,1441,2116,13,834,2617,62,9186,10786,3672,62,41433,3256,1988,8,628,220,220,220,2488,26745,198,220,220,220,825,1438,62,2127,21052,7,944,2599,198,220,220,220,220,220,220,220,37227,38,1039,262,1438,62,2127,21052,286,428,1395,4029,7449,13,220,1303,645,20402,25,412,33548,628,220,220,220,220,220,220,220,16409,25,198,220,220,220,220,220,220,220,220,220,220,220,357,30388,2599,383,1438,62,2127,21052,286,428,1395,4029,7449,13,220,1303,645,20402,25,412,33548,198,220,220,220,220,220,220,220,37227,198,220,220,220,220,220,220,220,1441,2116,13,834,1136,62,9186,10786,3672,62,2127,21052,11537,628,220,220,220,2488,3672,62,2127,21052,13,2617,353,198,220,220,220,825,1438,62,2127,21052,7,944,11,1988,2599,198,220,220,220,220,220,220,220,37227,50,1039,262,1438,62,2127,21052,286,428,1395,4029,7449,13,220,1303,645,20402,25,412,33548,198,220,220,220,220,220,220,220,37227,198,220,220,220,220,220,220,220,1441,2116,13,834,2617,62,9186,10786,3672,62,2127,21052,3256,1988,8,628,220,220,220,2488,26745,198,220,220,220,825,1438,62,18747,7,944,2599,198,220,220,220,220,220,220,220,37227,38,1039,262,1438,62,18747,286,428,1395,4029,7449,13,220,1303,645,20402,25,412,33548,628,220,220,220,220,220,220,220,16409,25,198,220,220,220,220,220,220,220,220,220,220,220,29565,600,60,2599,383,1438,62,18747,286,428,1395,4029,7449,13,220,1303,645,20402,25,412,33548,198,220,220,220,220,220,220,220,37227,198,220,220,220,220,220,220,220,1441,2116,13,834,1136,62,9186,10786,3672,62,18747,11537,628,220,220,220,2488,3672,62,18747,13,2617,353,198,220,220,220,825,1438,62,18747,7,944,11,1988,2599,198,220,220,220,220,220,220,220,37227,50,1039,262,1438,62,18747,286,428,1395,4029,7449,13,220,1303,645,20402,25,412,33548,198,220,220,220,220,220,220,220,37227,198,220,220,220,220,220,220,220,1441,2116,13,834,2617,62,9186,10786,3672,62,18747,3256,1988,8,628,220,220,220,2488,26745,198,220,220,220,825,1438,62,29988,1496,62,18747,7,944,2599,198,220,220,220,220,220,220,220,37227,38,1039,262,1438,62,29988,1496,62,18747,286,428,1395,4029,7449,13,220,1303,645,20402,25,412,33548,628,220,220,220,220,220,220,220,16409,25,198,220,220,220,220,220,220,220,220,220,220,220,29565,600,60,2599,383,1438,62,29988,1496,62,18747,286,428,1395,4029,7449,13,220,1303,645,20402,25,412,33548,198,220,220,220,220,220,220,220,37227,198,220,220,220,220,220,220,220,1441,2116,13,834,1136,62,9186,10786,3672,62,29988,1496,62,18747,11537,628,220,220,220,2488,3672,62,29988,1496,62,18747,13,2617,353,198,220,220,220,825,1438,62,29988,1496,62,18747,7,944,11,1988,2599,198,220,220,220,220,220,220,220,37227,50,1039,262,1438,62,29988,1496,62,18747,286,428,1395,4029,7449,13,220,1303,645,20402,25,412,33548,198,220,220,220,220,220,220,220,37227,198,220,220,220,220,220,220,220,1441,2116,13,834,2617,62,9186,10786,3672,62,29988,1496,62,18747,3256,1988,8,628,220,220,220,2488,26745,198,220,220,220,825,21231,62,8841,7,944,2599,198,220,220,220,220,220,220,220,37227,38,1039,262,21231,62,8841,286,428,1395,4029,7449,13,220,1303,645,20402,25,412,33548,628,220,220,220,220,220,220,220,16409,25,198,220,220,220,220,220,220,220,220,220,220,220,357,2536,2599,383,21231,62,8841,286,428,1395,4029,7449,13,220,1303,645,20402,25,412,33548,198,220,220,220,220,220,220,220,37227,198,220,220,220,220,220,220,220,1441,2116,13,834,1136,62,9186,10786,40290,62,8841,11537,628,220,220,220,2488,40290,62,8841,13,2617,353,198,220,220,220,825,21231,62,8841,7,944,11,1988,2599,198,220,220,220,220,220,220,220,37227,50,1039,262,21231,62,8841,286,428,1395,4029,7449,13,220,1303,645,20402,25,412,33548,198,220,220,220,220,220,220,220,37227,198,220,220,220,220,220,220,220,1441,2116,13,834,2617,62,9186,10786,40290,62,8841,3256,1988,8,628,220,220,220,2488,26745,198,220,220,220,825,21231,62,17618,7,944,2599,198,220,220,220,220,220,220,220,37227,38,1039,262,21231,62,17618,286,428,1395,4029,7449,13,220,1303,645,20402,25,412,33548,628,220,220,220,220,220,220,220,16409,25,198,220,220,220,220,220,220,220,220,220,220,220,357,22468,2599,383,21231,62,17618,286,428,1395,4029,7449,13,220,1303,645,20402,25,412,33548,198,220,220,220,220,220,220,220,37227,198,220,220,220,220,220,220,220,1441,2116,13,834,1136,62,9186,10786,40290,62,17618,11537,628,220,220,220,2488,40290,62,17618,13,2617,353,198,220,220,220,825,21231,62,17618,7,944,11,1988,2599,198,220,220,220,220,220,220,220,37227,50,1039,262,21231,62,17618,286,428,1395,4029,7449,13,220,1303,645,20402,25,412,33548,198,220,220,220,220,220,220,220,37227,198,220,220,220,220,220,220,220,1441,2116,13,834,2617,62,9186,10786,40290,62,17618,3256,1988,8,628,220,220,220,2488,26745,198,220,220,220,825,21231,62,41433,7,944,2599,198,220,220,220,220,220,220,220,37227,38,1039,262,21231,62,41433,286,428,1395,4029,7449,13,220,1303,645,20402,25,412,33548,628,220,220,220,220,220,220,220,16409,25,198,220,220,220,220,220,220,220,220,220,220,220,357,600,2599,383,21231,62,41433,286,428,1395,4029,7449,13,220,1303,645,20402,25,412,33548,198,220,220,220,220,220,220,220,37227,198,220,220,220,220,220,220,220,1441,2116,13,834,1136,62,9186,10786,40290,62,41433,11537,628,220,220,220,2488,40290,62,41433,13,2617,353,198,220,220,220,825,21231,62,41433,7,944,11,1988,2599,198,220,220,220,220,220,220,220,37227,50,1039,262,21231,62,41433,286,428,1395,4029,7449,13,220,1303,645,20402,25,412,33548,198,220,220,220,220,220,220,220,37227,198,220,220,220,220,220,220,220,1441,2116,13,834,2617,62,9186,10786,40290,62,41433,3256,1988,8,628,220,220,220,2488,26745,198,220,220,220,825,21231,62,2127,21052,7,944,2599,198,220,220,220,220,220,220,220,37227,38,1039,262,21231,62,2127,21052,286,428,1395,4029,7449,13,220,1303,645,20402,25,412,33548,628,220,220,220,220,220,220,220,16409,25,198,220,220,220,220,220,220,220,220,220,220,220,357,30388,2599,383,21231,62,2127,21052,286,428,1395,4029,7449,13,220,1303,645,20402,25,412,33548,198,220,220,220,220,220,220,220,37227,198,220,220,220,220,220,220,220,1441,2116,13,834,1136,62,9186,10786,40290,62,2127,21052,11537,628,220,220,220,2488,40290,62,2127,21052,13,2617,353,198,220,220,220,825,21231,62,2127,21052,7,944,11,1988,2599,198,220,220,220,220,220,220,220,37227,50,1039,262,21231,62,2127,21052,286,428,1395,4029,7449,13,220,1303,645,20402,25,412,33548,198,220,220,220,220,220,220,220,37227,198,220,220,220,220,220,220,220,1441,2116,13,834,2617,62,9186,10786,40290,62,2127,21052,3256,1988,8,628,220,220,220,2488,26745,198,220,220,220,825,21231,62,18747,7,944,2599,198,220,220,220,220,220,220,220,37227,38,1039,262,21231,62,18747,286,428,1395,4029,7449,13,220,1303,645,20402,25,412,33548,628,220,220,220,220,220,220,220,16409,25,198,220,220,220,220,220,220,220,220,220,220,220,29565,600,60,2599,383,21231,62,18747,286,428,1395,4029,7449,13,220,1303,645,20402,25,412,33548,198,220,220,220,220,220,220,220,37227,198,220,220,220,220,220,220,220,1441,2116,13,834,1136,62,9186,10786,40290,62,18747,11537,628,220,220,220,2488,40290,62,18747,13,2617,353,198,220,220,220,825,21231,62,18747,7,944,11,1988,2599,198,220,220,220,220,220,220,220,37227,50,1039,262,21231,62,18747,286,428,1395,4029,7449,13,220,1303,645,20402,25,412,33548,198,220,220,220,220,220,220,220,37227,198,220,220,220,220,220,220,220,1441,2116,13,834,2617,62,9186,10786,40290,62,18747,3256,1988,8,628,220,220,220,2488,26745,198,220,220,220,825,21231,62,29988,1496,62,18747,7,944,2599,198,220,220,220,220,220,220,220,37227,38,1039,262,21231,62,29988,1496,62,18747,286,428,1395,4029,7449,13,220,1303,645,20402,25,412,33548,628,220,220,220,220,220,220,220,16409,25,198,220,220,220,220,220,220,220,220,220,220,220,29565,600,60,2599,383,21231,62,29988,1496,62,18747,286,428,1395,4029,7449,13,220,1303,645,20402,25,412,33548,198,220,220,220,220,220,220,220,37227,198,220,220,220,220,220,220,220,1441,2116,13,834,1136,62,9186,10786,40290,62,29988,1496,62,18747,11537,628,220,220,220,2488,40290,62,29988,1496,62,18747,13,2617,353,198,220,220,220,825,21231,62,29988,1496,62,18747,7,944,11,1988,2599,198,220,220,220,220,220,220,220,37227,50,1039,262,21231,62,29988,1496,62,18747,286,428,1395,4029,7449,13,220,1303,645,20402,25,412,33548,198,220,220,220,220,220,220,220,37227,198,220,220,220,220,220,220,220,1441,2116,13,834,2617,62,9186,10786,40290,62,29988,1496,62,18747,3256,1988,8,628,220,220,220,2488,26745,198,220,220,220,825,25745,62,8841,7,944,2599,198,220,220,220,220,220,220,220,37227,38,1039,262,25745,62,8841,286,428,1395,4029,7449,13,220,1303,645,20402,25,412,33548,628,220,220,220,220,220,220,220,16409,25,198,220,220,220,220,220,220,220,220,220,220,220,357,2536,2599,383,25745,62,8841,286,428,1395,4029,7449,13,220,1303,645,20402,25,412,33548,198,220,220,220,220,220,220,220,37227,198,220,220,220,220,220,220,220,1441,2116,13,834,1136,62,9186,10786,14933,10223,62,8841,11537,628,220,220,220,2488,14933,10223,62,8841,13,2617,353,198,220,220,220,825,25745,62,8841,7,944,11,1988,2599,198,220,220,220,220,220,220,220,37227,50,1039,262,25745,62,8841,286,428,1395,4029,7449,13,220,1303,645,20402,25,412,33548,198,220,220,220,220,220,220,220,37227,198,220,220,220,220,220,220,220,1441,2116,13,834,2617,62,9186,10786,14933,10223,62,8841,3256,1988,8,628,220,220,220,2488,26745,198,220,220,220,825,25745,62,17618,7,944,2599,198,220,220,220,220,220,220,220,37227,38,1039,262,25745,62,17618,286,428,1395,4029,7449,13,220,1303,645,20402,25,412,33548,628,220,220,220,220,220,220,220,16409,25,198,220,220,220,220,220,220,220,220,220,220,220,357,22468,2599,383,25745,62,17618,286,428,1395,4029,7449,13,220,1303,645,20402,25,412,33548,198,220,220,220,220,220,220,220,37227,198,220,220,220,220,220,220,220,1441,2116,13,834,1136,62,9186,10786,14933,10223,62,17618,11537,628,220,220,220,2488,14933,10223,62,17618,13,2617,353,198,220,220,220,825,25745,62,17618,7,944,11,1988,2599,198,220,220,220,220,220,220,220,37227,50,1039,262,25745,62,17618,286,428,1395,4029,7449,13,220,1303,645,20402,25,412,33548,198,220,220,220,220,220,220,220,37227,198,220,220,220,220,220,220,220,1441,2116,13,834,2617,62,9186,10786,14933,10223,62,17618,3256,1988,8,628,220,220,220,2488,26745,198,220,220,220,825,25745,62,41433,7,944,2599,198,220,220,220,220,220,220,220,37227,38,1039,262,25745,62,41433,286,428,1395,4029,7449,13,220,1303,645,20402,25,412,33548,628,220,220,220,220,220,220,220,16409,25,198,220,220,220,220,220,220,220,220,220,220,220,357,600,2599,383,25745,62,41433,286,428,1395,4029,7449,13,220,1303,645,20402,25,412,33548,198,220,220,220,220,220,220,220,37227,198,220,220,220,220,220,220,220,1441,2116,13,834,1136,62,9186,10786,14933,10223,62,41433,11537,628,220,220,220,2488,14933,10223,62,41433,13,2617,353,198,220,220,220,825,25745,62,41433,7,944,11,1988,2599,198,220,220,220,220,220,220,220,37227,50,1039,262,25745,62,41433,286,428,1395,4029,7449,13,220,1303,645,20402,25,412,33548,198,220,220,220,220,220,220,220,37227,198,220,220,220,220,220,220,220,1441,2116,13,834,2617,62,9186,10786,14933,10223,62,41433,3256,1988,8,628,220,220,220,2488,26745,198,220,220,220,825,25745,62,2127,21052,7,944,2599,198,220,220,220,220,220,220,220,37227,38,1039,262,25745,62,2127,21052,286,428,1395,4029,7449,13,220,1303,645,20402,25,412,33548,628,220,220,220,220,220,220,220,16409,25,198,220,220,220,220,220,220,220,220,220,220,220,357,30388,2599,383,25745,62,2127,21052,286,428,1395,4029,7449,13,220,1303,645,20402,25,412,33548,198,220,220,220,220,220,220,220,37227,198,220,220,220,220,220,220,220,1441,2116,13,834,1136,62,9186,10786,14933,10223,62,2127,21052,11537,628,220,220,220,2488,14933,10223,62,2127,21052,13,2617,353,198,220,220,220,825,25745,62,2127,21052,7,944,11,1988,2599,198,220,220,220,220,220,220,220,37227,50,1039,262,25745,62,2127,21052,286,428,1395,4029,7449,13,220,1303,645,20402,25,412,33548,198,220,220,220,220,220,220,220,37227,198,220,220,220,220,220,220,220,1441,2116,13,834,2617,62,9186,10786,14933,10223,62,2127,21052,3256,1988,8,628,220,220,220,2488,26745,198,220,220,220,825,25745,62,18747,7,944,2599,198,220,220,220,220,220,220,220,37227,38,1039,262,25745,62,18747,286,428,1395,4029,7449,13,220,1303,645,20402,25,412,33548,628,220,220,220,220,220,220,220,16409,25,198,220,220,220,220,220,220,220,220,220,220,220,29565,600,60,2599,383,25745,62,18747,286,428,1395,4029,7449,13,220,1303,645,20402,25,412,33548,198,220,220,220,220,220,220,220,37227,198,220,220,220,220,220,220,220,1441,2116,13,834,1136,62,9186,10786,14933,10223,62,18747,11537,628,220,220,220,2488,14933,10223,62,18747,13,2617,353,198,220,220,220,825,25745,62,18747,7,944,11,1988,2599,198,220,220,220,220,220,220,220,37227,50,1039,262,25745,62,18747,286,428,1395,4029,7449,13,220,1303,645,20402,25,412,33548,198,220,220,220,220,220,220,220,37227,198,220,220,220,220,220,220,220,1441,2116,13,834,2617,62,9186,10786,14933,10223,62,18747,3256,1988,8,628,220,220,220,2488,26745,198,220,220,220,825,25745,62,29988,1496,62,18747,7,944,2599,198,220,220,220,220,220,220,220,37227,38,1039,262,25745,62,29988,1496,62,18747,286,428,1395,4029,7449,13,220,1303,645,20402,25,412,33548,628,220,220,220,220,220,220,220,16409,25,198,220,220,220,220,220,220,220,220,220,220,220,29565,600,60,2599,383,25745,62,29988,1496,62,18747,286,428,1395,4029,7449,13,220,1303,645,20402,25,412,33548,198,220,220,220,220,220,220,220,37227,198,220,220,220,220,220,220,220,1441,2116,13,834,1136,62,9186,10786,14933,10223,62,29988,1496,62,18747,11537,628,220,220,220,2488,14933,10223,62,29988,1496,62,18747,13,2617,353,198,220,220,220,825,25745,62,29988,1496,62,18747,7,944,11,1988,2599,198,220,220,220,220,220,220,220,37227,50,1039,262,25745,62,29988,1496,62,18747,286,428,1395,4029,7449,13,220,1303,645,20402,25,412,33548,198,220,220,220,220,220,220,220,37227,198,220,220,220,220,220,220,220,1441,2116,13,834,2617,62,9186,10786,14933,10223,62,29988,1496,62,18747,3256,1988,8,628,220,220,220,2488,26745,198,220,220,220,825,21231,62,5907,62,8841,7,944,2599,198,220,220,220,220,220,220,220,37227,38,1039,262,21231,62,5907,62,8841,286,428,1395,4029,7449,13,220,1303,645,20402,25,412,33548,628,220,220,220,220,220,220,220,16409,25,198,220,220,220,220,220,220,220,220,220,220,220,357,2536,2599,383,21231,62,5907,62,8841,286,428,1395,4029,7449,13,220,1303,645,20402,25,412,33548,198,220,220,220,220,220,220,220,37227,198,220,220,220,220,220,220,220,1441,2116,13,834,1136,62,9186,10786,40290,62,5907,62,8841,11537,628,220,220,220,2488,40290,62,5907,62,8841,13,2617,353,198,220,220,220,825,21231,62,5907,62,8841,7,944,11,1988,2599,198,220,220,220,220,220,220,220,37227,50,1039,262,21231,62,5907,62,8841,286,428,1395,4029,7449,13,220,1303,645,20402,25,412,33548,198,220,220,220,220,220,220,220,37227,198,220,220,220,220,220,220,220,1441,2116,13,834,2617,62,9186,10786,40290,62,5907,62,8841,3256,1988,8,628,220,220,220,2488,26745,198,220,220,220,825,21231,62,5907,62,17618,7,944,2599,198,220,220,220,220,220,220,220,37227,38,1039,262,21231,62,5907,62,17618,286,428,1395,4029,7449,13,220,1303,645,20402,25,412,33548,628,220,220,220,220,220,220,220,16409,25,198,220,220,220,220,220,220,220,220,220,220,220,357,22468,2599,383,21231,62,5907,62,17618,286,428,1395,4029,7449,13,220,1303,645,20402,25,412,33548,198,220,220,220,220,220,220,220,37227,198,220,220,220,220,220,220,220,1441,2116,13,834,1136,62,9186,10786,40290,62,5907,62,17618,11537,628,220,220,220,2488,40290,62,5907,62,17618,13,2617,353,198,220,220,220,825,21231,62,5907,62,17618,7,944,11,1988,2599,198,220,220,220,220,220,220,220,37227,50,1039,262,21231,62,5907,62,17618,286,428,1395,4029,7449,13,220,1303,645,20402,25,412,33548,198,220,220,220,220,220,220,220,37227,198,220,220,220,220,220,220,220,1441,2116,13,834,2617,62,9186,10786,40290,62,5907,62,17618,3256,1988,8,628,220,220,220,2488,26745,198,220,220,220,825,21231,62,5907,62,41433,7,944,2599,198,220,220,220,220,220,220,220,37227,38,1039,262,21231,62,5907,62,41433,286,428,1395,4029,7449,13,220,1303,645,20402,25,412,33548,628,220,220,220,220,220,220,220,16409,25,198,220,220,220,220,220,220,220,220,220,220,220,357,600,2599,383,21231,62,5907,62,41433,286,428,1395,4029,7449,13,220,1303,645,20402,25,412,33548,198,220,220,220,220,220,220,220,37227,198,220,220,220,220,220,220,220,1441,2116,13,834,1136,62,9186,10786,40290,62,5907,62,41433,11537,628,220,220,220,2488,40290,62,5907,62,41433,13,2617,353,198,220,220,220,825,21231,62,5907,62,41433,7,944,11,1988,2599,198,220,220,220,220,220,220,220,37227,50,1039,262,21231,62,5907,62,41433,286,428,1395,4029,7449,13,220,1303,645,20402,25,412,33548,198,220,220,220,220,220,220,220,37227,198,220,220,220,220,220,220,220,1441,2116,13,834,2617,62,9186,10786,40290,62,5907,62,41433,3256,1988,8,628,220,220,220,2488,26745,198,220,220,220,825,21231,62,5907,62,2127,21052,7,944,2599,198,220,220,220,220,220,220,220,37227,38,1039,262,21231,62,5907,62,2127,21052,286,428,1395,4029,7449,13,220,1303,645,20402,25,412,33548,628,220,220,220,220,220,220,220,16409,25,198,220,220,220,220,220,220,220,220,220,220,220,357,30388,2599,383,21231,62,5907,62,2127,21052,286,428,1395,4029,7449,13,220,1303,645,20402,25,412,33548,198,220,220,220,220,220,220,220,37227,198,220,220,220,220,220,220,220,1441,2116,13,834,1136,62,9186,10786,40290,62,5907,62,2127,21052,11537,628,220,220,220,2488,40290,62,5907,62,2127,21052,13,2617,353,198,220,220,220,825,21231,62,5907,62,2127,21052,7,944,11,1988,2599,198,220,220,220,220,220,220,220,37227,50,1039,262,21231,62,5907,62,2127,21052,286,428,1395,4029,7449,13,220,1303,645,20402,25,412,33548,198,220,220,220,220,220,220,220,37227,198,220,220,220,220,220,220,220,1441,2116,13,834,2617,62,9186,10786,40290,62,5907,62,2127,21052,3256,1988,8,628,220,220,220,2488,26745,198,220,220,220,825,21231,62,5907,62,18747,7,944,2599,198,220,220,220,220,220,220,220,37227,38,1039,262,21231,62,5907,62,18747,286,428,1395,4029,7449,13,220,1303,645,20402,25,412,33548,628,220,220,220,220,220,220,220,16409,25,198,220,220,220,220,220,220,220,220,220,220,220,29565,600,60,2599,383,21231,62,5907,62,18747,286,428,1395,4029,7449,13,220,1303,645,20402,25,412,33548,198,220,220,220,220,220,220,220,37227,198,220,220,220,220,220,220,220,1441,2116,13,834,1136,62,9186,10786,40290,62,5907,62,18747,11537,628,220,220,220,2488,40290,62,5907,62,18747,13,2617,353,198,220,220,220,825,21231,62,5907,62,18747,7,944,11,1988,2599,198,220,220,220,220,220,220,220,37227,50,1039,262,21231,62,5907,62,18747,286,428,1395,4029,7449,13,220,1303,645,20402,25,412,33548,198,220,220,220,220,220,220,220,37227,198,220,220,220,220,220,220,220,1441,2116,13,834,2617,62,9186,10786,40290,62,5907,62,18747,3256,1988,8,628,220,220,220,2488,26745,198,220,220,220,825,21231,62,5907,62,29988,1496,62,18747,7,944,2599,198,220,220,220,220,220,220,220,37227,38,1039,262,21231,62,5907,62,29988,1496,62,18747,286,428,1395,4029,7449,13,220,1303,645,20402,25,412,33548,628,220,220,220,220,220,220,220,16409,25,198,220,220,220,220,220,220,220,220,220,220,220,29565,600,60,2599,383,21231,62,5907,62,29988,1496,62,18747,286,428,1395,4029,7449,13,220,1303,645,20402,25,412,33548,198,220,220,220,220,220,220,220,37227,198,220,220,220,220,220,220,220,1441,2116,13,834,1136,62,9186,10786,40290,62,5907,62,29988,1496,62,18747,11537,628,220,220,220,2488,40290,62,5907,62,29988,1496,62,18747,13,2617,353,198,220,220,220,825,21231,62,5907,62,29988,1496,62,18747,7,944,11,1988,2599,198,220,220,220,220,220,220,220,37227,50,1039,262,21231,62,5907,62,29988,1496,62,18747,286,428,1395,4029,7449,13,220,1303,645,20402,25,412,33548,198,220,220,220,220,220,220,220,37227,198,220,220,220,220,220,220,220,1441,2116,13,834,2617,62,9186,10786,40290,62,5907,62,29988,1496,62,18747,3256,1988,8,628,220,220,220,825,284,62,11600,7,944,2599,198,220,220,220,220,220,220,220,37227,35561,262,2746,6608,355,257,8633,37811,198,220,220,220,220,220,220,220,1441,2746,62,1462,62,11600,7,944,11,11389,1096,28,25101,8,628,220,220,220,825,284,62,2536,7,944,2599,198,220,220,220,220,220,220,220,37227,35561,262,4731,10552,286,262,2746,37811,198,220,220,220,220,220,220,220,1441,279,4798,13,79,18982,7,944,13,1462,62,11600,28955,628,220,220,220,825,11593,260,1050,834,7,944,2599,198,220,220,220,220,220,220,220,37227,1890,4600,4798,63,290,4600,381,22272,63,37811,198,220,220,220,220,220,220,220,1441,2116,13,1462,62,2536,3419,628,220,220,220,825,11593,27363,834,7,944,11,584,2599,198,220,220,220,220,220,220,220,37227,35561,2081,611,1111,5563,389,4961,37811,198,220,220,220,220,220,220,220,611,407,318,39098,7,847,11,1395,4029,7449,2599,198,220,220,220,220,220,220,220,220,220,220,220,1441,10352,628,220,220,220,220,220,220,220,611,407,900,7,944,13557,7890,62,8095,13,13083,28955,6624,900,7,847,13557,7890,62,8095,13,13083,3419,2599,198,220,220,220,220,220,220,220,220,220,220,220,1441,10352,198,220,220,220,220,220,220,220,329,4808,7785,62,3672,11,428,62,2100,287,2237,13,2676,23814,7,944,13557,7890,62,8095,2599,198,220,220,220,220,220,220,220,220,220,220,220,326,62,2100,796,584,13557,7890,62,8095,29795,7785,62,3672,60,198,220,220,220,220,220,220,220,220,220,220,220,3858,796,900,3419,198,220,220,220,220,220,220,220,220,220,220,220,3858,13,2860,7,5661,62,2100,13,834,4871,834,8,198,220,220,220,220,220,220,220,220,220,220,220,3858,13,2860,7,5562,62,2100,13,834,4871,834,8,198,220,220,220,220,220,220,220,220,220,220,220,410,874,62,40496,796,428,62,2100,6624,326,62,2100,198,220,220,220,220,220,220,220,220,220,220,220,611,357,1662,2237,13,47,56,18,290,198,220,220,220,220,220,220,220,220,220,220,220,220,220,220,220,220,220,220,220,18896,7,19199,8,6624,362,290,28000,1098,287,3858,2599,220,1303,645,20402,25,376,23,2481,198,220,220,220,220,220,220,220,220,220,220,220,220,220,220,220,410,874,62,40496,796,357,198,220,220,220,220,220,220,220,220,220,220,220,220,220,220,220,220,220,220,220,428,62,2100,13,268,8189,10786,40477,12,23,11537,6624,326,62,2100,13,268,8189,10786,40477,12,23,11537,198,220,220,220,220,220,220,220,220,220,220,220,220,220,220,220,1267,198,220,220,220,220,220,220,220,220,220,220,220,611,407,410,874,62,40496,25,198,220,220,220,220,220,220,220,220,220,220,220,220,220,220,220,1441,10352,198,220,220,220,220,220,220,220,1441,6407,628,220,220,220,825,11593,710,834,7,944,11,584,2599,198,220,220,220,220,220,220,220,37227,35561,2081,611,1111,5563,389,407,4961,37811,198,220,220,220,220,220,220,220,1441,407,2116,6624,584,198],"string":"[\n 2,\n 19617,\n 25,\n 3384,\n 69,\n 12,\n 23,\n 198,\n 198,\n 37811,\n 198,\n 220,\n 220,\n 220,\n 4946,\n 17614,\n 4767,\n 8095,\n 628,\n 220,\n 220,\n 220,\n 770,\n 1020,\n 318,\n 8384,\n 329,\n 4856,\n 4767,\n 8095,\n 4382,\n 290,\n 4909,\n 8390,\n 886,\n 13033,\n 11,\n 4981,\n 13,\n 4222,\n 466,\n 407,\n 779,\n 428,\n 329,\n 597,\n 584,\n 4007,\n 13,\n 6093,\n 3435,\n 25,\n 19990,\n 26867,\n 220,\n 1303,\n 645,\n 20402,\n 25,\n 412,\n 33548,\n 628,\n 220,\n 220,\n 220,\n 383,\n 2196,\n 286,\n 262,\n 4946,\n 17614,\n 3188,\n 25,\n 352,\n 13,\n 15,\n 13,\n 15,\n 198,\n 220,\n 220,\n 220,\n 2980,\n 515,\n 416,\n 25,\n 3740,\n 1378,\n 9654,\n 15042,\n 12,\n 8612,\n 1352,\n 13,\n 13670,\n 198,\n 37811,\n 628,\n 198,\n 11748,\n 279,\n 4798,\n 220,\n 1303,\n 645,\n 20402,\n 25,\n 376,\n 21844,\n 198,\n 11748,\n 302,\n 220,\n 1303,\n 645,\n 20402,\n 25,\n 376,\n 21844,\n 198,\n 198,\n 11748,\n 2237,\n 220,\n 1303,\n 645,\n 20402,\n 25,\n 376,\n 21844,\n 198,\n 198,\n 6738,\n 4273,\n 8095,\n 62,\n 15042,\n 13,\n 1069,\n 11755,\n 1330,\n 357,\n 220,\n 1303,\n 645,\n 20402,\n 25,\n 376,\n 21844,\n 198,\n 220,\n 220,\n 220,\n 5949,\n 72,\n 9218,\n 12331,\n 11,\n 198,\n 220,\n 220,\n 220,\n 5949,\n 72,\n 6030,\n 12331,\n 11,\n 198,\n 220,\n 220,\n 220,\n 5949,\n 72,\n 11395,\n 12331,\n 11,\n 198,\n 8,\n 198,\n 6738,\n 4273,\n 8095,\n 62,\n 15042,\n 13,\n 19849,\n 62,\n 26791,\n 1330,\n 357,\n 220,\n 1303,\n 645,\n 20402,\n 25,\n 376,\n 21844,\n 198,\n 220,\n 220,\n 220,\n 9104,\n 26447,\n 11,\n 198,\n 220,\n 220,\n 220,\n 9104,\n 26437,\n 11,\n 198,\n 220,\n 220,\n 220,\n 2198,\n 62,\n 40845,\n 62,\n 27160,\n 11,\n 198,\n 220,\n 220,\n 220,\n 2198,\n 62,\n 12102,\n 602,\n 11,\n 198,\n 220,\n 220,\n 220,\n 3128,\n 11,\n 198,\n 220,\n 220,\n 220,\n 4818,\n 8079,\n 11,\n 198,\n 220,\n 220,\n 220,\n 2393,\n 62,\n 4906,\n 11,\n 198,\n 220,\n 220,\n 220,\n 651,\n 62,\n 36439,\n 62,\n 4871,\n 11,\n 198,\n 220,\n 220,\n 220,\n 493,\n 11,\n 198,\n 220,\n 220,\n 220,\n 2746,\n 62,\n 1462,\n 62,\n 11600,\n 11,\n 198,\n 220,\n 220,\n 220,\n 4844,\n 62,\n 4906,\n 11,\n 198,\n 220,\n 220,\n 220,\n 965,\n 11,\n 198,\n 220,\n 220,\n 220,\n 2099,\n 62,\n 18224,\n 62,\n 20500,\n 11,\n 198,\n 220,\n 220,\n 220,\n 26571,\n 62,\n 392,\n 62,\n 1102,\n 1851,\n 62,\n 19199,\n 198,\n 8,\n 628,\n 198,\n 4871,\n 1395,\n 4029,\n 7449,\n 7,\n 17633,\n 26447,\n 2599,\n 198,\n 220,\n 220,\n 220,\n 37227,\n 16580,\n 25,\n 770,\n 1398,\n 318,\n 8295,\n 7560,\n 416,\n 4946,\n 17614,\n 35986,\n 13,\n 198,\n 220,\n 220,\n 220,\n 6524,\n 25,\n 3740,\n 1378,\n 9654,\n 15042,\n 12,\n 8612,\n 1352,\n 13,\n 13670,\n 628,\n 220,\n 220,\n 220,\n 2141,\n 407,\n 4370,\n 262,\n 1398,\n 14500,\n 13,\n 628,\n 220,\n 220,\n 220,\n 49213,\n 25,\n 198,\n 220,\n 220,\n 220,\n 220,\n 220,\n 3142,\n 62,\n 27160,\n 357,\n 11600,\n 2599,\n 383,\n 1994,\n 318,\n 262,\n 46545,\n 3108,\n 284,\n 262,\n 11688,\n 198,\n 220,\n 220,\n 220,\n 220,\n 220,\n 220,\n 220,\n 220,\n 220,\n 290,\n 262,\n 329,\n 1401,\n 62,\n 3672,\n 428,\n 318,\n 357,\n 7785,\n 62,\n 3672,\n 11,\n 737,\n 383,\n 1988,\n 318,\n 257,\n 8633,\n 198,\n 220,\n 220,\n 220,\n 220,\n 220,\n 220,\n 220,\n 220,\n 220,\n 351,\n 257,\n 3139,\n 1143,\n 1994,\n 12059,\n 262,\n 3142,\n 1988,\n 290,\n 281,\n 3142,\n 198,\n 220,\n 220,\n 220,\n 220,\n 220,\n 220,\n 220,\n 220,\n 220,\n 1988,\n 13,\n 2312,\n 8633,\n 82,\n 3650,\n 262,\n 3142,\n 33829,\n 3815,\n 13,\n 198,\n 220,\n 220,\n 220,\n 220,\n 220,\n 11688,\n 62,\n 8899,\n 357,\n 11600,\n 2599,\n 383,\n 1994,\n 318,\n 11688,\n 1438,\n 198,\n 220,\n 220,\n 220,\n 220,\n 220,\n 220,\n 220,\n 220,\n 220,\n 290,\n 262,\n 1988,\n 318,\n 33918,\n 1994,\n 287,\n 6770,\n 13,\n 198,\n 220,\n 220,\n 220,\n 220,\n 220,\n 6534,\n 20900,\n 62,\n 8367,\n 62,\n 4871,\n 62,\n 8899,\n 357,\n 11600,\n 2599,\n 317,\n 8633,\n 284,\n 467,\n 422,\n 262,\n 6534,\n 20900,\n 198,\n 220,\n 220,\n 220,\n 220,\n 220,\n 220,\n 220,\n 220,\n 220,\n 7885,\n 1988,\n 284,\n 262,\n 6534,\n 20900,\n 1398,\n 1438,\n 13,\n 198,\n 220,\n 220,\n 220,\n 220,\n 220,\n 1280,\n 15042,\n 62,\n 19199,\n 357,\n 11600,\n 2599,\n 383,\n 1994,\n 318,\n 11688,\n 1438,\n 198,\n 220,\n 220,\n 220,\n 220,\n 220,\n 220,\n 220,\n 220,\n 220,\n 290,\n 262,\n 1988,\n 318,\n 11688,\n 2099,\n 13,\n 198,\n 220,\n 220,\n 220,\n 220,\n 220,\n 4938,\n 602,\n 357,\n 11600,\n 2599,\n 383,\n 1994,\n 318,\n 262,\n 46545,\n 3108,\n 284,\n 262,\n 11688,\n 198,\n 220,\n 220,\n 220,\n 220,\n 220,\n 220,\n 220,\n 220,\n 220,\n 290,\n 262,\n 329,\n 1401,\n 62,\n 3672,\n 428,\n 318,\n 357,\n 7785,\n 62,\n 3672,\n 11,\n 737,\n 383,\n 1988,\n 318,\n 257,\n 8633,\n 198,\n 220,\n 220,\n 220,\n 220,\n 220,\n 220,\n 220,\n 220,\n 220,\n 326,\n 7000,\n 4938,\n 602,\n 329,\n 3509,\n 62,\n 13664,\n 11,\n 949,\n 62,\n 13664,\n 11,\n 3509,\n 62,\n 23814,\n 11,\n 198,\n 220,\n 220,\n 220,\n 220,\n 220,\n 220,\n 220,\n 220,\n 220,\n 949,\n 62,\n 23814,\n 11,\n 8568,\n 62,\n 47033,\n 11,\n 19889,\n 62,\n 47033,\n 11,\n 8568,\n 62,\n 39504,\n 11,\n 198,\n 220,\n 220,\n 220,\n 220,\n 220,\n 220,\n 220,\n 220,\n 220,\n 19889,\n 62,\n 39504,\n 11,\n 290,\n 40364,\n 13,\n 198,\n 220,\n 220,\n 220,\n 220,\n 220,\n 3224,\n 62,\n 48310,\n 62,\n 4906,\n 357,\n 83,\n 29291,\n 2599,\n 317,\n 46545,\n 286,\n 6097,\n 6292,\n 198,\n 220,\n 220,\n 220,\n 220,\n 220,\n 220,\n 220,\n 220,\n 220,\n 355,\n 3224,\n 6608,\n 3815,\n 13,\n 198,\n 220,\n 220,\n 220,\n 37227,\n 628,\n 220,\n 220,\n 220,\n 3142,\n 62,\n 27160,\n 796,\n 1391,\n 198,\n 220,\n 220,\n 220,\n 1782,\n 628,\n 220,\n 220,\n 220,\n 11688,\n 62,\n 8899,\n 796,\n 1391,\n 198,\n 220,\n 220,\n 220,\n 220,\n 220,\n 220,\n 220,\n 705,\n 42348,\n 62,\n 8841,\n 10354,\n 705,\n 42348,\n 62,\n 8841,\n 3256,\n 220,\n 1303,\n 645,\n 20402,\n 25,\n 412,\n 33548,\n 198,\n 220,\n 220,\n 220,\n 220,\n 220,\n 220,\n 220,\n 705,\n 42348,\n 62,\n 17618,\n 10354,\n 705,\n 42348,\n 62,\n 17618,\n 3256,\n 220,\n 1303,\n 645,\n 20402,\n 25,\n 412,\n 33548,\n 198,\n 220,\n 220,\n 220,\n 220,\n 220,\n 220,\n 220,\n 705,\n 42348,\n 62,\n 41433,\n 10354,\n 705,\n 42348,\n 62,\n 41433,\n 3256,\n 220,\n 1303,\n 645,\n 20402,\n 25,\n 412,\n 33548,\n 198,\n 220,\n 220,\n 220,\n 220,\n 220,\n 220,\n 220,\n 705,\n 42348,\n 62,\n 2127,\n 21052,\n 10354,\n 705,\n 42348,\n 62,\n 2127,\n 21052,\n 3256,\n 220,\n 1303,\n 645,\n 20402,\n 25,\n 412,\n 33548,\n 198,\n 220,\n 220,\n 220,\n 220,\n 220,\n 220,\n 220,\n 705,\n 29988,\n 1496,\n 62,\n 18747,\n 10354,\n 705,\n 29988,\n 1496,\n 62,\n 18747,\n 3256,\n 220,\n 1303,\n 645,\n 20402,\n 25,\n 412,\n 33548,\n 198,\n 220,\n 220,\n 220,\n 220,\n 220,\n 220,\n 220,\n 705,\n 3672,\n 62,\n 8841,\n 10354,\n 705,\n 3672,\n 62,\n 8841,\n 3256,\n 220,\n 1303,\n 645,\n 20402,\n 25,\n 412,\n 33548,\n 198,\n 220,\n 220,\n 220,\n 220,\n 220,\n 220,\n 220,\n 705,\n 3672,\n 62,\n 17618,\n 10354,\n 705,\n 3672,\n 62,\n 17618,\n 3256,\n 220,\n 1303,\n 645,\n 20402,\n 25,\n 412,\n 33548,\n 198,\n 220,\n 220,\n 220,\n 220,\n 220,\n 220,\n 220,\n 705,\n 3672,\n 62,\n 41433,\n 10354,\n 705,\n 3672,\n 62,\n 41433,\n 3256,\n 220,\n 1303,\n 645,\n 20402,\n 25,\n 412,\n 33548,\n 198,\n 220,\n 220,\n 220,\n 220,\n 220,\n 220,\n 220,\n 705,\n 3672,\n 62,\n 2127,\n 21052,\n 10354,\n 705,\n 3672,\n 62,\n 2127,\n 21052,\n 3256,\n 220,\n 1303,\n 645,\n 20402,\n 25,\n 412,\n 33548,\n 198,\n 220,\n 220,\n 220,\n 220,\n 220,\n 220,\n 220,\n 705,\n 3672,\n 62,\n 18747,\n 10354,\n 705,\n 3672,\n 62,\n 18747,\n 3256,\n 220,\n 1303,\n 645,\n 20402,\n 25,\n 412,\n 33548,\n 198,\n 220,\n 220,\n 220,\n 220,\n 220,\n 220,\n 220,\n 705,\n 3672,\n 62,\n 29988,\n 1496,\n 62,\n 18747,\n 10354,\n 705,\n 3672,\n 62,\n 29988,\n 1496,\n 62,\n 18747,\n 3256,\n 220,\n 1303,\n 645,\n 20402,\n 25,\n 412,\n 33548,\n 198,\n 220,\n 220,\n 220,\n 220,\n 220,\n 220,\n 220,\n 705,\n 40290,\n 62,\n 8841,\n 10354,\n 705,\n 40290,\n 62,\n 8841,\n 3256,\n 220,\n 1303,\n 645,\n 20402,\n 25,\n 412,\n 33548,\n 198,\n 220,\n 220,\n 220,\n 220,\n 220,\n 220,\n 220,\n 705,\n 40290,\n 62,\n 17618,\n 10354,\n 705,\n 40290,\n 62,\n 17618,\n 3256,\n 220,\n 1303,\n 645,\n 20402,\n 25,\n 412,\n 33548,\n 198,\n 220,\n 220,\n 220,\n 220,\n 220,\n 220,\n 220,\n 705,\n 40290,\n 62,\n 41433,\n 10354,\n 705,\n 40290,\n 62,\n 41433,\n 3256,\n 220,\n 1303,\n 645,\n 20402,\n 25,\n 412,\n 33548,\n 198,\n 220,\n 220,\n 220,\n 220,\n 220,\n 220,\n 220,\n 705,\n 40290,\n 62,\n 2127,\n 21052,\n 10354,\n 705,\n 40290,\n 62,\n 2127,\n 21052,\n 3256,\n 220,\n 1303,\n 645,\n 20402,\n 25,\n 412,\n 33548,\n 198,\n 220,\n 220,\n 220,\n 220,\n 220,\n 220,\n 220,\n 705,\n 40290,\n 62,\n 18747,\n 10354,\n 705,\n 40290,\n 62,\n 18747,\n 3256,\n 220,\n 1303,\n 645,\n 20402,\n 25,\n 412,\n 33548,\n 198,\n 220,\n 220,\n 220,\n 220,\n 220,\n 220,\n 220,\n 705,\n 40290,\n 62,\n 29988,\n 1496,\n 62,\n 18747,\n 10354,\n 705,\n 40290,\n 62,\n 29988,\n 1496,\n 62,\n 18747,\n 3256,\n 220,\n 1303,\n 645,\n 20402,\n 25,\n 412,\n 33548,\n 198,\n 220,\n 220,\n 220,\n 220,\n 220,\n 220,\n 220,\n 705,\n 14933,\n 10223,\n 62,\n 8841,\n 10354,\n 705,\n 14933,\n 10223,\n 62,\n 8841,\n 3256,\n 220,\n 1303,\n 645,\n 20402,\n 25,\n 412,\n 33548,\n 198,\n 220,\n 220,\n 220,\n 220,\n 220,\n 220,\n 220,\n 705,\n 14933,\n 10223,\n 62,\n 17618,\n 10354,\n 705,\n 14933,\n 10223,\n 62,\n 17618,\n 3256,\n 220,\n 1303,\n 645,\n 20402,\n 25,\n 412,\n 33548,\n 198,\n 220,\n 220,\n 220,\n 220,\n 220,\n 220,\n 220,\n 705,\n 14933,\n 10223,\n 62,\n 41433,\n 10354,\n 705,\n 14933,\n 10223,\n 62,\n 41433,\n 3256,\n 220,\n 1303,\n 645,\n 20402,\n 25,\n 412,\n 33548,\n 198,\n 220,\n 220,\n 220,\n 220,\n 220,\n 220,\n 220,\n 705,\n 14933,\n 10223,\n 62,\n 2127,\n 21052,\n 10354,\n 705,\n 14933,\n 10223,\n 62,\n 2127,\n 21052,\n 3256,\n 220,\n 1303,\n 645,\n 20402,\n 25,\n 412,\n 33548,\n 198,\n 220,\n 220,\n 220,\n 220,\n 220,\n 220,\n 220,\n 705,\n 14933,\n 10223,\n 62,\n 18747,\n 10354,\n 705,\n 14933,\n 10223,\n 62,\n 18747,\n 3256,\n 220,\n 1303,\n 645,\n 20402,\n 25,\n 412,\n 33548,\n 198,\n 220,\n 220,\n 220,\n 220,\n 220,\n 220,\n 220,\n 705,\n 14933,\n 10223,\n 62,\n 29988,\n 1496,\n 62,\n 18747,\n 10354,\n 705,\n 14933,\n 10223,\n 62,\n 29988,\n 1496,\n 62,\n 18747,\n 3256,\n 220,\n 1303,\n 645,\n 20402,\n 25,\n 412,\n 33548,\n 198,\n 220,\n 220,\n 220,\n 220,\n 220,\n 220,\n 220,\n 705,\n 40290,\n 62,\n 5907,\n 62,\n 8841,\n 10354,\n 705,\n 40290,\n 62,\n 5907,\n 62,\n 8841,\n 3256,\n 220,\n 1303,\n 645,\n 20402,\n 25,\n 412,\n 33548,\n 198,\n 220,\n 220,\n 220,\n 220,\n 220,\n 220,\n 220,\n 705,\n 40290,\n 62,\n 5907,\n 62,\n 17618,\n 10354,\n 705,\n 40290,\n 62,\n 5907,\n 62,\n 17618,\n 3256,\n 220,\n 1303,\n 645,\n 20402,\n 25,\n 412,\n 33548,\n 198,\n 220,\n 220,\n 220,\n 220,\n 220,\n 220,\n 220,\n 705,\n 40290,\n 62,\n 5907,\n 62,\n 41433,\n 10354,\n 705,\n 40290,\n 62,\n 5907,\n 62,\n 41433,\n 3256,\n 220,\n 1303,\n 645,\n 20402,\n 25,\n 412,\n 33548,\n 198,\n 220,\n 220,\n 220,\n 220,\n 220,\n 220,\n 220,\n 705,\n 40290,\n 62,\n 5907,\n 62,\n 2127,\n 21052,\n 10354,\n 705,\n 40290,\n 62,\n 5907,\n 62,\n 2127,\n 21052,\n 3256,\n 220,\n 1303,\n 645,\n 20402,\n 25,\n 412,\n 33548,\n 198,\n 220,\n 220,\n 220,\n 220,\n 220,\n 220,\n 220,\n 705,\n 40290,\n 62,\n 5907,\n 62,\n 18747,\n 10354,\n 705,\n 40290,\n 62,\n 5907,\n 62,\n 18747,\n 3256,\n 220,\n 1303,\n 645,\n 20402,\n 25,\n 412,\n 33548,\n 198,\n 220,\n 220,\n 220,\n 220,\n 220,\n 220,\n 220,\n 705,\n 40290,\n 62,\n 5907,\n 62,\n 29988,\n 1496,\n 62,\n 18747,\n 10354,\n 705,\n 40290,\n 62,\n 5907,\n 62,\n 29988,\n 1496,\n 62,\n 18747,\n 6,\n 220,\n 1303,\n 645,\n 20402,\n 25,\n 412,\n 33548,\n 198,\n 220,\n 220,\n 220,\n 1782,\n 628,\n 220,\n 220,\n 220,\n 1280,\n 15042,\n 62,\n 19199,\n 796,\n 1391,\n 198,\n 220,\n 220,\n 220,\n 220,\n 220,\n 220,\n 220,\n 705,\n 42348,\n 62,\n 8841,\n 10354,\n 357,\n 2536,\n 11,\n 828,\n 220,\n 1303,\n 645,\n 20402,\n 25,\n 412,\n 33548,\n 198,\n 220,\n 220,\n 220,\n 220,\n 220,\n 220,\n 220,\n 705,\n 42348,\n 62,\n 17618,\n 10354,\n 357,\n 22468,\n 11,\n 828,\n 220,\n 1303,\n 645,\n 20402,\n 25,\n 412,\n 33548,\n 198,\n 220,\n 220,\n 220,\n 220,\n 220,\n 220,\n 220,\n 705,\n 42348,\n 62,\n 41433,\n 10354,\n 357,\n 600,\n 11,\n 828,\n 220,\n 1303,\n 645,\n 20402,\n 25,\n 412,\n 33548,\n 198,\n 220,\n 220,\n 220,\n 220,\n 220,\n 220,\n 220,\n 705,\n 42348,\n 62,\n 2127,\n 21052,\n 10354,\n 357,\n 30388,\n 11,\n 828,\n 220,\n 1303,\n 645,\n 20402,\n 25,\n 412,\n 33548,\n 198,\n 220,\n 220,\n 220,\n 220,\n 220,\n 220,\n 220,\n 705,\n 29988,\n 1496,\n 62,\n 18747,\n 10354,\n 29565,\n 600,\n 4357,\n 828,\n 220,\n 1303,\n 645,\n 20402,\n 25,\n 412,\n 33548,\n 198,\n 220,\n 220,\n 220,\n 220,\n 220,\n 220,\n 220,\n 705,\n 3672,\n 62,\n 8841,\n 10354,\n 357,\n 2536,\n 11,\n 828,\n 220,\n 1303,\n 645,\n 20402,\n 25,\n 412,\n 33548,\n 198,\n 220,\n 220,\n 220,\n 220,\n 220,\n 220,\n 220,\n 705,\n 3672,\n 62,\n 17618,\n 10354,\n 357,\n 22468,\n 11,\n 828,\n 220,\n 1303,\n 645,\n 20402,\n 25,\n 412,\n 33548,\n 198,\n 220,\n 220,\n 220,\n 220,\n 220,\n 220,\n 220,\n 705,\n 3672,\n 62,\n 41433,\n 10354,\n 357,\n 600,\n 11,\n 828,\n 220,\n 1303,\n 645,\n 20402,\n 25,\n 412,\n 33548,\n 198,\n 220,\n 220,\n 220,\n 220,\n 220,\n 220,\n 220,\n 705,\n 3672,\n 62,\n 2127,\n 21052,\n 10354,\n 357,\n 30388,\n 11,\n 828,\n 220,\n 1303,\n 645,\n 20402,\n 25,\n 412,\n 33548,\n 198,\n 220,\n 220,\n 220,\n 220,\n 220,\n 220,\n 220,\n 705,\n 3672,\n 62,\n 18747,\n 10354,\n 29565,\n 600,\n 4357,\n 828,\n 220,\n 1303,\n 645,\n 20402,\n 25,\n 412,\n 33548,\n 198,\n 220,\n 220,\n 220,\n 220,\n 220,\n 220,\n 220,\n 705,\n 3672,\n 62,\n 29988,\n 1496,\n 62,\n 18747,\n 10354,\n 29565,\n 600,\n 4357,\n 828,\n 220,\n 1303,\n 645,\n 20402,\n 25,\n 412,\n 33548,\n 198,\n 220,\n 220,\n 220,\n 220,\n 220,\n 220,\n 220,\n 705,\n 40290,\n 62,\n 8841,\n 10354,\n 357,\n 2536,\n 11,\n 828,\n 220,\n 1303,\n 645,\n 20402,\n 25,\n 412,\n 33548,\n 198,\n 220,\n 220,\n 220,\n 220,\n 220,\n 220,\n 220,\n 705,\n 40290,\n 62,\n 17618,\n 10354,\n 357,\n 22468,\n 11,\n 828,\n 220,\n 1303,\n 645,\n 20402,\n 25,\n 412,\n 33548,\n 198,\n 220,\n 220,\n 220,\n 220,\n 220,\n 220,\n 220,\n 705,\n 40290,\n 62,\n 41433,\n 10354,\n 357,\n 600,\n 11,\n 828,\n 220,\n 1303,\n 645,\n 20402,\n 25,\n 412,\n 33548,\n 198,\n 220,\n 220,\n 220,\n 220,\n 220,\n 220,\n 220,\n 705,\n 40290,\n 62,\n 2127,\n 21052,\n 10354,\n 357,\n 30388,\n 11,\n 828,\n 220,\n 1303,\n 645,\n 20402,\n 25,\n 412,\n 33548,\n 198,\n 220,\n 220,\n 220,\n 220,\n 220,\n 220,\n 220,\n 705,\n 40290,\n 62,\n 18747,\n 10354,\n 29565,\n 600,\n 4357,\n 828,\n 220,\n 1303,\n 645,\n 20402,\n 25,\n 412,\n 33548,\n 198,\n 220,\n 220,\n 220,\n 220,\n 220,\n 220,\n 220,\n 705,\n 40290,\n 62,\n 29988,\n 1496,\n 62,\n 18747,\n 10354,\n 29565,\n 600,\n 4357,\n 828,\n 220,\n 1303,\n 645,\n 20402,\n 25,\n 412,\n 33548,\n 198,\n 220,\n 220,\n 220,\n 220,\n 220,\n 220,\n 220,\n 705,\n 14933,\n 10223,\n 62,\n 8841,\n 10354,\n 357,\n 2536,\n 11,\n 828,\n 220,\n 1303,\n 645,\n 20402,\n 25,\n 412,\n 33548,\n 198,\n 220,\n 220,\n 220,\n 220,\n 220,\n 220,\n 220,\n 705,\n 14933,\n 10223,\n 62,\n 17618,\n 10354,\n 357,\n 22468,\n 11,\n 828,\n 220,\n 1303,\n 645,\n 20402,\n 25,\n 412,\n 33548,\n 198,\n 220,\n 220,\n 220,\n 220,\n 220,\n 220,\n 220,\n 705,\n 14933,\n 10223,\n 62,\n 41433,\n 10354,\n 357,\n 600,\n 11,\n 828,\n 220,\n 1303,\n 645,\n 20402,\n 25,\n 412,\n 33548,\n 198,\n 220,\n 220,\n 220,\n 220,\n 220,\n 220,\n 220,\n 705,\n 14933,\n 10223,\n 62,\n 2127,\n 21052,\n 10354,\n 357,\n 30388,\n 11,\n 828,\n 220,\n 1303,\n 645,\n 20402,\n 25,\n 412,\n 33548,\n 198,\n 220,\n 220,\n 220,\n 220,\n 220,\n 220,\n 220,\n 705,\n 14933,\n 10223,\n 62,\n 18747,\n 10354,\n 29565,\n 600,\n 4357,\n 828,\n 220,\n 1303,\n 645,\n 20402,\n 25,\n 412,\n 33548,\n 198,\n 220,\n 220,\n 220,\n 220,\n 220,\n 220,\n 220,\n 705,\n 14933,\n 10223,\n 62,\n 29988,\n 1496,\n 62,\n 18747,\n 10354,\n 29565,\n 600,\n 4357,\n 828,\n 220,\n 1303,\n 645,\n 20402,\n 25,\n 412,\n 33548,\n 198,\n 220,\n 220,\n 220,\n 220,\n 220,\n 220,\n 220,\n 705,\n 40290,\n 62,\n 5907,\n 62,\n 8841,\n 10354,\n 357,\n 2536,\n 11,\n 828,\n 220,\n 1303,\n 645,\n 20402,\n 25,\n 412,\n 33548,\n 198,\n 220,\n 220,\n 220,\n 220,\n 220,\n 220,\n 220,\n 705,\n 40290,\n 62,\n 5907,\n 62,\n 17618,\n 10354,\n 357,\n 22468,\n 11,\n 828,\n 220,\n 1303,\n 645,\n 20402,\n 25,\n 412,\n 33548,\n 198,\n 220,\n 220,\n 220,\n 220,\n 220,\n 220,\n 220,\n 705,\n 40290,\n 62,\n 5907,\n 62,\n 41433,\n 10354,\n 357,\n 600,\n 11,\n 828,\n 220,\n 1303,\n 645,\n 20402,\n 25,\n 412,\n 33548,\n 198,\n 220,\n 220,\n 220,\n 220,\n 220,\n 220,\n 220,\n 705,\n 40290,\n 62,\n 5907,\n 62,\n 2127,\n 21052,\n 10354,\n 357,\n 30388,\n 11,\n 828,\n 220,\n 1303,\n 645,\n 20402,\n 25,\n 412,\n 33548,\n 198,\n 220,\n 220,\n 220,\n 220,\n 220,\n 220,\n 220,\n 705,\n 40290,\n 62,\n 5907,\n 62,\n 18747,\n 10354,\n 29565,\n 600,\n 4357,\n 828,\n 220,\n 1303,\n 645,\n 20402,\n 25,\n 412,\n 33548,\n 198,\n 220,\n 220,\n 220,\n 220,\n 220,\n 220,\n 220,\n 705,\n 40290,\n 62,\n 5907,\n 62,\n 29988,\n 1496,\n 62,\n 18747,\n 10354,\n 29565,\n 600,\n 4357,\n 828,\n 220,\n 1303,\n 645,\n 20402,\n 25,\n 412,\n 33548,\n 198,\n 220,\n 220,\n 220,\n 1782,\n 628,\n 220,\n 220,\n 220,\n 4938,\n 602,\n 796,\n 1391,\n 198,\n 220,\n 220,\n 220,\n 1782,\n 628,\n 220,\n 220,\n 220,\n 3224,\n 62,\n 48310,\n 62,\n 4906,\n 796,\n 6045,\n 628,\n 220,\n 220,\n 220,\n 6534,\n 20900,\n 796,\n 6045,\n 628,\n 220,\n 220,\n 220,\n 825,\n 11593,\n 15003,\n 834,\n 7,\n 944,\n 11,\n 4808,\n 9122,\n 62,\n 4906,\n 28,\n 17821,\n 11,\n 4808,\n 6738,\n 62,\n 15388,\n 28,\n 25101,\n 11,\n 4808,\n 6978,\n 62,\n 1462,\n 62,\n 9186,\n 16193,\n 828,\n 4808,\n 11250,\n 3924,\n 28,\n 14202,\n 11,\n 12429,\n 46265,\n 22046,\n 2599,\n 220,\n 1303,\n 645,\n 20402,\n 25,\n 412,\n 33548,\n 198,\n 220,\n 220,\n 220,\n 220,\n 220,\n 220,\n 220,\n 37227,\n 55,\n 4029,\n 7449,\n 532,\n 257,\n 2746,\n 5447,\n 287,\n 4946,\n 17614,\n 628,\n 198,\n 220,\n 220,\n 220,\n 220,\n 220,\n 220,\n 220,\n 7383,\n 4775,\n 943,\n 14542,\n 25,\n 198,\n 220,\n 220,\n 220,\n 220,\n 220,\n 220,\n 220,\n 220,\n 220,\n 220,\n 220,\n 4808,\n 9122,\n 62,\n 4906,\n 357,\n 30388,\n 2599,\n 611,\n 6407,\n 11,\n 3815,\n 329,\n 10007,\n 287,\n 1280,\n 15042,\n 62,\n 19199,\n 198,\n 220,\n 220,\n 220,\n 220,\n 220,\n 220,\n 220,\n 220,\n 220,\n 220,\n 220,\n 220,\n 220,\n 220,\n 220,\n 220,\n 220,\n 220,\n 220,\n 220,\n 220,\n 220,\n 220,\n 220,\n 220,\n 220,\n 220,\n 220,\n 220,\n 220,\n 220,\n 481,\n 307,\n 2099,\n 10667,\n 290,\n 257,\n 5994,\n 12331,\n 481,\n 307,\n 198,\n 220,\n 220,\n 220,\n 220,\n 220,\n 220,\n 220,\n 220,\n 220,\n 220,\n 220,\n 220,\n 220,\n 220,\n 220,\n 220,\n 220,\n 220,\n 220,\n 220,\n 220,\n 220,\n 220,\n 220,\n 220,\n 220,\n 220,\n 220,\n 220,\n 220,\n 220,\n 4376,\n 611,\n 262,\n 2642,\n 2099,\n 318,\n 5128,\n 13,\n 198,\n 220,\n 220,\n 220,\n 220,\n 220,\n 220,\n 220,\n 220,\n 220,\n 220,\n 220,\n 220,\n 220,\n 220,\n 220,\n 220,\n 220,\n 220,\n 220,\n 220,\n 220,\n 220,\n 220,\n 220,\n 220,\n 220,\n 220,\n 220,\n 220,\n 220,\n 220,\n 2896,\n 13185,\n 284,\n 6407,\n 198,\n 220,\n 220,\n 220,\n 220,\n 220,\n 220,\n 220,\n 220,\n 220,\n 220,\n 220,\n 4808,\n 6978,\n 62,\n 1462,\n 62,\n 9186,\n 357,\n 83,\n 29291,\n 14,\n 4868,\n 2599,\n 770,\n 318,\n 257,\n 1351,\n 286,\n 8251,\n 393,\n 3815,\n 284,\n 198,\n 220,\n 220,\n 220,\n 220,\n 220,\n 220,\n 220,\n 220,\n 220,\n 220,\n 220,\n 220,\n 220,\n 220,\n 220,\n 220,\n 220,\n 220,\n 220,\n 220,\n 220,\n 220,\n 220,\n 220,\n 220,\n 220,\n 220,\n 220,\n 220,\n 220,\n 220,\n 16007,\n 866,\n 284,\n 262,\n 2746,\n 287,\n 2722,\n 62,\n 7890,\n 198,\n 220,\n 220,\n 220,\n 220,\n 220,\n 220,\n 220,\n 220,\n 220,\n 220,\n 220,\n 220,\n 220,\n 220,\n 220,\n 220,\n 220,\n 220,\n 220,\n 220,\n 220,\n 220,\n 220,\n 220,\n 220,\n 220,\n 220,\n 220,\n 220,\n 220,\n 220,\n 618,\n 748,\n 48499,\n 2890,\n 257,\n 2882,\n 198,\n 220,\n 220,\n 220,\n 220,\n 220,\n 220,\n 220,\n 220,\n 220,\n 220,\n 220,\n 4808,\n 6738,\n 62,\n 15388,\n 357,\n 30388,\n 2599,\n 6407,\n 611,\n 262,\n 1366,\n 318,\n 422,\n 262,\n 4382,\n 198,\n 220,\n 220,\n 220,\n 220,\n 220,\n 220,\n 220,\n 220,\n 220,\n 220,\n 220,\n 220,\n 220,\n 220,\n 220,\n 220,\n 220,\n 220,\n 220,\n 220,\n 220,\n 220,\n 220,\n 220,\n 220,\n 220,\n 220,\n 220,\n 220,\n 220,\n 220,\n 10352,\n 611,\n 262,\n 1366,\n 318,\n 422,\n 262,\n 5456,\n 357,\n 12286,\n 8,\n 198,\n 220,\n 220,\n 220,\n 220,\n 220,\n 220,\n 220,\n 220,\n 220,\n 220,\n 220,\n 4808,\n 11250,\n 3924,\n 357,\n 38149,\n 2599,\n 262,\n 4554,\n 284,\n 779,\n 618,\n 198,\n 220,\n 220,\n 220,\n 220,\n 220,\n 220,\n 220,\n 220,\n 220,\n 220,\n 220,\n 220,\n 220,\n 220,\n 220,\n 220,\n 220,\n 220,\n 220,\n 220,\n 220,\n 220,\n 220,\n 220,\n 220,\n 220,\n 220,\n 220,\n 220,\n 220,\n 220,\n 748,\n 48499,\n 2890,\n 257,\n 2393,\n 62,\n 4906,\n 11507,\n 13,\n 198,\n 220,\n 220,\n 220,\n 220,\n 220,\n 220,\n 220,\n 220,\n 220,\n 220,\n 220,\n 220,\n 220,\n 220,\n 220,\n 220,\n 220,\n 220,\n 220,\n 220,\n 220,\n 220,\n 220,\n 220,\n 220,\n 220,\n 220,\n 220,\n 220,\n 220,\n 220,\n 1002,\n 3804,\n 11,\n 2099,\n 11315,\n 318,\n 7482,\n 198,\n 220,\n 220,\n 220,\n 220,\n 220,\n 220,\n 220,\n 220,\n 220,\n 220,\n 220,\n 220,\n 220,\n 220,\n 220,\n 220,\n 220,\n 220,\n 220,\n 220,\n 220,\n 220,\n 220,\n 220,\n 220,\n 220,\n 220,\n 220,\n 220,\n 220,\n 220,\n 1002,\n 22532,\n 645,\n 2099,\n 11315,\n 318,\n 1760,\n 13,\n 198,\n 220,\n 220,\n 220,\n 220,\n 220,\n 220,\n 220,\n 220,\n 220,\n 220,\n 220,\n 11688,\n 62,\n 8841,\n 357,\n 2536,\n 2599,\n 685,\n 25968,\n 60,\n 220,\n 1303,\n 645,\n 20402,\n 25,\n 412,\n 33548,\n 198,\n 220,\n 220,\n 220,\n 220,\n 220,\n 220,\n 220,\n 220,\n 220,\n 220,\n 220,\n 11688,\n 62,\n 17618,\n 357,\n 22468,\n 2599,\n 685,\n 25968,\n 60,\n 220,\n 1303,\n 645,\n 20402,\n 25,\n 412,\n 33548,\n 198,\n 220,\n 220,\n 220,\n 220,\n 220,\n 220,\n 220,\n 220,\n 220,\n 220,\n 220,\n 11688,\n 62,\n 41433,\n 357,\n 600,\n 2599,\n 685,\n 25968,\n 60,\n 220,\n 1303,\n 645,\n 20402,\n 25,\n 412,\n 33548,\n 198,\n 220,\n 220,\n 220,\n 220,\n 220,\n 220,\n 220,\n 220,\n 220,\n 220,\n 220,\n 11688,\n 62,\n 2127,\n 21052,\n 357,\n 30388,\n 2599,\n 685,\n 25968,\n 60,\n 220,\n 1303,\n 645,\n 20402,\n 25,\n 412,\n 33548,\n 198,\n 220,\n 220,\n 220,\n 220,\n 220,\n 220,\n 220,\n 220,\n 220,\n 220,\n 220,\n 12908,\n 62,\n 18747,\n 29565,\n 600,\n 60,\n 2599,\n 685,\n 25968,\n 60,\n 220,\n 1303,\n 645,\n 20402,\n 25,\n 412,\n 33548,\n 198,\n 220,\n 220,\n 220,\n 220,\n 220,\n 220,\n 220,\n 220,\n 220,\n 220,\n 220,\n 1438,\n 62,\n 8841,\n 357,\n 2536,\n 2599,\n 685,\n 25968,\n 60,\n 220,\n 1303,\n 645,\n 20402,\n 25,\n 412,\n 33548,\n 198,\n 220,\n 220,\n 220,\n 220,\n 220,\n 220,\n 220,\n 220,\n 220,\n 220,\n 220,\n 1438,\n 62,\n 17618,\n 357,\n 22468,\n 2599,\n 685,\n 25968,\n 60,\n 220,\n 1303,\n 645,\n 20402,\n 25,\n 412,\n 33548,\n 198,\n 220,\n 220,\n 220,\n 220,\n 220,\n 220,\n 220,\n 220,\n 220,\n 220,\n 220,\n 1438,\n 62,\n 41433,\n 357,\n 600,\n 2599,\n 685,\n 25968,\n 60,\n 220,\n 1303,\n 645,\n 20402,\n 25,\n 412,\n 33548,\n 198,\n 220,\n 220,\n 220,\n 220,\n 220,\n 220,\n 220,\n 220,\n 220,\n 220,\n 220,\n 1438,\n 62,\n 2127,\n 21052,\n 357,\n 30388,\n 2599,\n 685,\n 25968,\n 60,\n 220,\n 1303,\n 645,\n 20402,\n 25,\n 412,\n 33548,\n 198,\n 220,\n 220,\n 220,\n 220,\n 220,\n 220,\n 220,\n 220,\n 220,\n 220,\n 220,\n 1438,\n 62,\n 18747,\n 29565,\n 600,\n 60,\n 2599,\n 685,\n 25968,\n 60,\n 220,\n 1303,\n 645,\n 20402,\n 25,\n 412,\n 33548,\n 198,\n 220,\n 220,\n 220,\n 220,\n 220,\n 220,\n 220,\n 220,\n 220,\n 220,\n 220,\n 1438,\n 62,\n 29988,\n 1496,\n 62,\n 18747,\n 29565,\n 600,\n 60,\n 2599,\n 685,\n 25968,\n 60,\n 220,\n 1303,\n 645,\n 20402,\n 25,\n 412,\n 33548,\n 198,\n 220,\n 220,\n 220,\n 220,\n 220,\n 220,\n 220,\n 220,\n 220,\n 220,\n 220,\n 21231,\n 62,\n 8841,\n 357,\n 2536,\n 2599,\n 685,\n 25968,\n 60,\n 220,\n 1303,\n 645,\n 20402,\n 25,\n 412,\n 33548,\n 198,\n 220,\n 220,\n 220,\n 220,\n 220,\n 220,\n 220,\n 220,\n 220,\n 220,\n 220,\n 21231,\n 62,\n 17618,\n 357,\n 22468,\n 2599,\n 685,\n 25968,\n 60,\n 220,\n 1303,\n 645,\n 20402,\n 25,\n 412,\n 33548,\n 198,\n 220,\n 220,\n 220,\n 220,\n 220,\n 220,\n 220,\n 220,\n 220,\n 220,\n 220,\n 21231,\n 62,\n 41433,\n 357,\n 600,\n 2599,\n 685,\n 25968,\n 60,\n 220,\n 1303,\n 645,\n 20402,\n 25,\n 412,\n 33548,\n 198,\n 220,\n 220,\n 220,\n 220,\n 220,\n 220,\n 220,\n 220,\n 220,\n 220,\n 220,\n 21231,\n 62,\n 2127,\n 21052,\n 357,\n 30388,\n 2599,\n 685,\n 25968,\n 60,\n 220,\n 1303,\n 645,\n 20402,\n 25,\n 412,\n 33548,\n 198,\n 220,\n 220,\n 220,\n 220,\n 220,\n 220,\n 220,\n 220,\n 220,\n 220,\n 220,\n 21231,\n 62,\n 18747,\n 29565,\n 600,\n 60,\n 2599,\n 685,\n 25968,\n 60,\n 220,\n 1303,\n 645,\n 20402,\n 25,\n 412,\n 33548,\n 198,\n 220,\n 220,\n 220,\n 220,\n 220,\n 220,\n 220,\n 220,\n 220,\n 220,\n 220,\n 21231,\n 62,\n 29988,\n 1496,\n 62,\n 18747,\n 29565,\n 600,\n 60,\n 2599,\n 685,\n 25968,\n 60,\n 220,\n 1303,\n 645,\n 20402,\n 25,\n 412,\n 33548,\n 198,\n 220,\n 220,\n 220,\n 220,\n 220,\n 220,\n 220,\n 220,\n 220,\n 220,\n 220,\n 25745,\n 62,\n 8841,\n 357,\n 2536,\n 2599,\n 685,\n 25968,\n 60,\n 220,\n 1303,\n 645,\n 20402,\n 25,\n 412,\n 33548,\n 198,\n 220,\n 220,\n 220,\n 220,\n 220,\n 220,\n 220,\n 220,\n 220,\n 220,\n 220,\n 25745,\n 62,\n 17618,\n 357,\n 22468,\n 2599,\n 685,\n 25968,\n 60,\n 220,\n 1303,\n 645,\n 20402,\n 25,\n 412,\n 33548,\n 198,\n 220,\n 220,\n 220,\n 220,\n 220,\n 220,\n 220,\n 220,\n 220,\n 220,\n 220,\n 25745,\n 62,\n 41433,\n 357,\n 600,\n 2599,\n 685,\n 25968,\n 60,\n 220,\n 1303,\n 645,\n 20402,\n 25,\n 412,\n 33548,\n 198,\n 220,\n 220,\n 220,\n 220,\n 220,\n 220,\n 220,\n 220,\n 220,\n 220,\n 220,\n 25745,\n 62,\n 2127,\n 21052,\n 357,\n 30388,\n 2599,\n 685,\n 25968,\n 60,\n 220,\n 1303,\n 645,\n 20402,\n 25,\n 412,\n 33548,\n 198,\n 220,\n 220,\n 220,\n 220,\n 220,\n 220,\n 220,\n 220,\n 220,\n 220,\n 220,\n 25745,\n 62,\n 18747,\n 29565,\n 600,\n 60,\n 2599,\n 685,\n 25968,\n 60,\n 220,\n 1303,\n 645,\n 20402,\n 25,\n 412,\n 33548,\n 198,\n 220,\n 220,\n 220,\n 220,\n 220,\n 220,\n 220,\n 220,\n 220,\n 220,\n 220,\n 25745,\n 62,\n 29988,\n 1496,\n 62,\n 18747,\n 29565,\n 600,\n 60,\n 2599,\n 685,\n 25968,\n 60,\n 220,\n 1303,\n 645,\n 20402,\n 25,\n 412,\n 33548,\n 198,\n 220,\n 220,\n 220,\n 220,\n 220,\n 220,\n 220,\n 220,\n 220,\n 220,\n 220,\n 21231,\n 62,\n 5907,\n 62,\n 8841,\n 357,\n 2536,\n 2599,\n 685,\n 25968,\n 60,\n 220,\n 1303,\n 645,\n 20402,\n 25,\n 412,\n 33548,\n 198,\n 220,\n 220,\n 220,\n 220,\n 220,\n 220,\n 220,\n 220,\n 220,\n 220,\n 220,\n 21231,\n 62,\n 5907,\n 62,\n 17618,\n 357,\n 22468,\n 2599,\n 685,\n 25968,\n 60,\n 220,\n 1303,\n 645,\n 20402,\n 25,\n 412,\n 33548,\n 198,\n 220,\n 220,\n 220,\n 220,\n 220,\n 220,\n 220,\n 220,\n 220,\n 220,\n 220,\n 21231,\n 62,\n 5907,\n 62,\n 41433,\n 357,\n 600,\n 2599,\n 685,\n 25968,\n 60,\n 220,\n 1303,\n 645,\n 20402,\n 25,\n 412,\n 33548,\n 198,\n 220,\n 220,\n 220,\n 220,\n 220,\n 220,\n 220,\n 220,\n 220,\n 220,\n 220,\n 21231,\n 62,\n 5907,\n 62,\n 2127,\n 21052,\n 357,\n 30388,\n 2599,\n 685,\n 25968,\n 60,\n 220,\n 1303,\n 645,\n 20402,\n 25,\n 412,\n 33548,\n 198,\n 220,\n 220,\n 220,\n 220,\n 220,\n 220,\n 220,\n 220,\n 220,\n 220,\n 220,\n 21231,\n 62,\n 5907,\n 62,\n 18747,\n 29565,\n 600,\n 60,\n 2599,\n 685,\n 25968,\n 60,\n 220,\n 1303,\n 645,\n 20402,\n 25,\n 412,\n 33548,\n 198,\n 220,\n 220,\n 220,\n 220,\n 220,\n 220,\n 220,\n 220,\n 220,\n 220,\n 220,\n 21231,\n 62,\n 5907,\n 62,\n 29988,\n 1496,\n 62,\n 18747,\n 29565,\n 600,\n 60,\n 2599,\n 685,\n 25968,\n 60,\n 220,\n 1303,\n 645,\n 20402,\n 25,\n 412,\n 33548,\n 198,\n 220,\n 220,\n 220,\n 220,\n 220,\n 220,\n 220,\n 37227,\n 198,\n 220,\n 220,\n 220,\n 220,\n 220,\n 220,\n 220,\n 2116,\n 13557,\n 7890,\n 62,\n 8095,\n 796,\n 23884,\n 198,\n 220,\n 220,\n 220,\n 220,\n 220,\n 220,\n 220,\n 2116,\n 13557,\n 9122,\n 62,\n 4906,\n 796,\n 4808,\n 9122,\n 62,\n 4906,\n 198,\n 220,\n 220,\n 220,\n 220,\n 220,\n 220,\n 220,\n 2116,\n 13557,\n 6738,\n 62,\n 15388,\n 796,\n 4808,\n 6738,\n 62,\n 15388,\n 198,\n 220,\n 220,\n 220,\n 220,\n 220,\n 220,\n 220,\n 2116,\n 13557,\n 6978,\n 62,\n 1462,\n 62,\n 9186,\n 796,\n 4808,\n 6978,\n 62,\n 1462,\n 62,\n 9186,\n 198,\n 220,\n 220,\n 220,\n 220,\n 220,\n 220,\n 220,\n 2116,\n 13557,\n 11250,\n 3924,\n 796,\n 4808,\n 11250,\n 3924,\n 628,\n 220,\n 220,\n 220,\n 220,\n 220,\n 220,\n 220,\n 329,\n 1401,\n 62,\n 3672,\n 11,\n 1401,\n 62,\n 8367,\n 287,\n 2237,\n 13,\n 2676,\n 23814,\n 7,\n 46265,\n 22046,\n 2599,\n 198,\n 220,\n 220,\n 220,\n 220,\n 220,\n 220,\n 220,\n 220,\n 220,\n 220,\n 220,\n 2116,\n 13,\n 834,\n 2617,\n 62,\n 9186,\n 7,\n 7785,\n 62,\n 3672,\n 11,\n 1401,\n 62,\n 8367,\n 8,\n 628,\n 220,\n 220,\n 220,\n 825,\n 11593,\n 2617,\n 9186,\n 834,\n 7,\n 944,\n 11,\n 1438,\n 11,\n 1988,\n 2599,\n 198,\n 220,\n 220,\n 220,\n 220,\n 220,\n 220,\n 220,\n 37227,\n 5661,\n 3578,\n 514,\n 284,\n 900,\n 3815,\n 351,\n 4554,\n 58,\n 3245,\n 62,\n 3672,\n 60,\n 796,\n 1188,\n 37811,\n 198,\n 220,\n 220,\n 220,\n 220,\n 220,\n 220,\n 220,\n 2116,\n 13,\n 834,\n 2617,\n 62,\n 9186,\n 7,\n 3672,\n 11,\n 1988,\n 8,\n 628,\n 220,\n 220,\n 220,\n 825,\n 11593,\n 1136,\n 9186,\n 834,\n 7,\n 944,\n 11,\n 1438,\n 2599,\n 198,\n 220,\n 220,\n 220,\n 220,\n 220,\n 220,\n 220,\n 37227,\n 5661,\n 3578,\n 514,\n 284,\n 651,\n 257,\n 1988,\n 351,\n 1188,\n 796,\n 4554,\n 58,\n 3245,\n 62,\n 3672,\n 60,\n 37811,\n 198,\n 220,\n 220,\n 220,\n 220,\n 220,\n 220,\n 220,\n 1441,\n 2116,\n 13,\n 834,\n 1136,\n 62,\n 9186,\n 7,\n 3672,\n 8,\n 628,\n 220,\n 220,\n 220,\n 2488,\n 26745,\n 198,\n 220,\n 220,\n 220,\n 825,\n 11688,\n 62,\n 8841,\n 7,\n 944,\n 2599,\n 198,\n 220,\n 220,\n 220,\n 220,\n 220,\n 220,\n 220,\n 37227,\n 38,\n 1039,\n 262,\n 11688,\n 62,\n 8841,\n 286,\n 428,\n 1395,\n 4029,\n 7449,\n 13,\n 220,\n 1303,\n 645,\n 20402,\n 25,\n 412,\n 33548,\n 628,\n 220,\n 220,\n 220,\n 220,\n 220,\n 220,\n 220,\n 16409,\n 25,\n 198,\n 220,\n 220,\n 220,\n 220,\n 220,\n 220,\n 220,\n 220,\n 220,\n 220,\n 220,\n 357,\n 2536,\n 2599,\n 383,\n 11688,\n 62,\n 8841,\n 286,\n 428,\n 1395,\n 4029,\n 7449,\n 13,\n 220,\n 1303,\n 645,\n 20402,\n 25,\n 412,\n 33548,\n 198,\n 220,\n 220,\n 220,\n 220,\n 220,\n 220,\n 220,\n 37227,\n 198,\n 220,\n 220,\n 220,\n 220,\n 220,\n 220,\n 220,\n 1441,\n 2116,\n 13,\n 834,\n 1136,\n 62,\n 9186,\n 10786,\n 42348,\n 62,\n 8841,\n 11537,\n 628,\n 220,\n 220,\n 220,\n 2488,\n 42348,\n 62,\n 8841,\n 13,\n 2617,\n 353,\n 198,\n 220,\n 220,\n 220,\n 825,\n 11688,\n 62,\n 8841,\n 7,\n 944,\n 11,\n 1988,\n 2599,\n 198,\n 220,\n 220,\n 220,\n 220,\n 220,\n 220,\n 220,\n 37227,\n 50,\n 1039,\n 262,\n 11688,\n 62,\n 8841,\n 286,\n 428,\n 1395,\n 4029,\n 7449,\n 13,\n 220,\n 1303,\n 645,\n 20402,\n 25,\n 412,\n 33548,\n 198,\n 220,\n 220,\n 220,\n 220,\n 220,\n 220,\n 220,\n 37227,\n 198,\n 220,\n 220,\n 220,\n 220,\n 220,\n 220,\n 220,\n 1441,\n 2116,\n 13,\n 834,\n 2617,\n 62,\n 9186,\n 10786,\n 42348,\n 62,\n 8841,\n 3256,\n 1988,\n 8,\n 628,\n 220,\n 220,\n 220,\n 2488,\n 26745,\n 198,\n 220,\n 220,\n 220,\n 825,\n 11688,\n 62,\n 17618,\n 7,\n 944,\n 2599,\n 198,\n 220,\n 220,\n 220,\n 220,\n 220,\n 220,\n 220,\n 37227,\n 38,\n 1039,\n 262,\n 11688,\n 62,\n 17618,\n 286,\n 428,\n 1395,\n 4029,\n 7449,\n 13,\n 220,\n 1303,\n 645,\n 20402,\n 25,\n 412,\n 33548,\n 628,\n 220,\n 220,\n 220,\n 220,\n 220,\n 220,\n 220,\n 16409,\n 25,\n 198,\n 220,\n 220,\n 220,\n 220,\n 220,\n 220,\n 220,\n 220,\n 220,\n 220,\n 220,\n 357,\n 22468,\n 2599,\n 383,\n 11688,\n 62,\n 17618,\n 286,\n 428,\n 1395,\n 4029,\n 7449,\n 13,\n 220,\n 1303,\n 645,\n 20402,\n 25,\n 412,\n 33548,\n 198,\n 220,\n 220,\n 220,\n 220,\n 220,\n 220,\n 220,\n 37227,\n 198,\n 220,\n 220,\n 220,\n 220,\n 220,\n 220,\n 220,\n 1441,\n 2116,\n 13,\n 834,\n 1136,\n 62,\n 9186,\n 10786,\n 42348,\n 62,\n 17618,\n 11537,\n 628,\n 220,\n 220,\n 220,\n 2488,\n 42348,\n 62,\n 17618,\n 13,\n 2617,\n 353,\n 198,\n 220,\n 220,\n 220,\n 825,\n 11688,\n 62,\n 17618,\n 7,\n 944,\n 11,\n 1988,\n 2599,\n 198,\n 220,\n 220,\n 220,\n 220,\n 220,\n 220,\n 220,\n 37227,\n 50,\n 1039,\n 262,\n 11688,\n 62,\n 17618,\n 286,\n 428,\n 1395,\n 4029,\n 7449,\n 13,\n 220,\n 1303,\n 645,\n 20402,\n 25,\n 412,\n 33548,\n 198,\n 220,\n 220,\n 220,\n 220,\n 220,\n 220,\n 220,\n 37227,\n 198,\n 220,\n 220,\n 220,\n 220,\n 220,\n 220,\n 220,\n 1441,\n 2116,\n 13,\n 834,\n 2617,\n 62,\n 9186,\n 10786,\n 42348,\n 62,\n 17618,\n 3256,\n 1988,\n 8,\n 628,\n 220,\n 220,\n 220,\n 2488,\n 26745,\n 198,\n 220,\n 220,\n 220,\n 825,\n 11688,\n 62,\n 41433,\n 7,\n 944,\n 2599,\n 198,\n 220,\n 220,\n 220,\n 220,\n 220,\n 220,\n 220,\n 37227,\n 38,\n 1039,\n 262,\n 11688,\n 62,\n 41433,\n 286,\n 428,\n 1395,\n 4029,\n 7449,\n 13,\n 220,\n 1303,\n 645,\n 20402,\n 25,\n 412,\n 33548,\n 628,\n 220,\n 220,\n 220,\n 220,\n 220,\n 220,\n 220,\n 16409,\n 25,\n 198,\n 220,\n 220,\n 220,\n 220,\n 220,\n 220,\n 220,\n 220,\n 220,\n 220,\n 220,\n 357,\n 600,\n 2599,\n 383,\n 11688,\n 62,\n 41433,\n 286,\n 428,\n 1395,\n 4029,\n 7449,\n 13,\n 220,\n 1303,\n 645,\n 20402,\n 25,\n 412,\n 33548,\n 198,\n 220,\n 220,\n 220,\n 220,\n 220,\n 220,\n 220,\n 37227,\n 198,\n 220,\n 220,\n 220,\n 220,\n 220,\n 220,\n 220,\n 1441,\n 2116,\n 13,\n 834,\n 1136,\n 62,\n 9186,\n 10786,\n 42348,\n 62,\n 41433,\n 11537,\n 628,\n 220,\n 220,\n 220,\n 2488,\n 42348,\n 62,\n 41433,\n 13,\n 2617,\n 353,\n 198,\n 220,\n 220,\n 220,\n 825,\n 11688,\n 62,\n 41433,\n 7,\n 944,\n 11,\n 1988,\n 2599,\n 198,\n 220,\n 220,\n 220,\n 220,\n 220,\n 220,\n 220,\n 37227,\n 50,\n 1039,\n 262,\n 11688,\n 62,\n 41433,\n 286,\n 428,\n 1395,\n 4029,\n 7449,\n 13,\n 220,\n 1303,\n 645,\n 20402,\n 25,\n 412,\n 33548,\n 198,\n 220,\n 220,\n 220,\n 220,\n 220,\n 220,\n 220,\n 37227,\n 198,\n 220,\n 220,\n 220,\n 220,\n 220,\n 220,\n 220,\n 1441,\n 2116,\n 13,\n 834,\n 2617,\n 62,\n 9186,\n 10786,\n 42348,\n 62,\n 41433,\n 3256,\n 1988,\n 8,\n 628,\n 220,\n 220,\n 220,\n 2488,\n 26745,\n 198,\n 220,\n 220,\n 220,\n 825,\n 11688,\n 62,\n 2127,\n 21052,\n 7,\n 944,\n 2599,\n 198,\n 220,\n 220,\n 220,\n 220,\n 220,\n 220,\n 220,\n 37227,\n 38,\n 1039,\n 262,\n 11688,\n 62,\n 2127,\n 21052,\n 286,\n 428,\n 1395,\n 4029,\n 7449,\n 13,\n 220,\n 1303,\n 645,\n 20402,\n 25,\n 412,\n 33548,\n 628,\n 220,\n 220,\n 220,\n 220,\n 220,\n 220,\n 220,\n 16409,\n 25,\n 198,\n 220,\n 220,\n 220,\n 220,\n 220,\n 220,\n 220,\n 220,\n 220,\n 220,\n 220,\n 357,\n 30388,\n 2599,\n 383,\n 11688,\n 62,\n 2127,\n 21052,\n 286,\n 428,\n 1395,\n 4029,\n 7449,\n 13,\n 220,\n 1303,\n 645,\n 20402,\n 25,\n 412,\n 33548,\n 198,\n 220,\n 220,\n 220,\n 220,\n 220,\n 220,\n 220,\n 37227,\n 198,\n 220,\n 220,\n 220,\n 220,\n 220,\n 220,\n 220,\n 1441,\n 2116,\n 13,\n 834,\n 1136,\n 62,\n 9186,\n 10786,\n 42348,\n 62,\n 2127,\n 21052,\n 11537,\n 628,\n 220,\n 220,\n 220,\n 2488,\n 42348,\n 62,\n 2127,\n 21052,\n 13,\n 2617,\n 353,\n 198,\n 220,\n 220,\n 220,\n 825,\n 11688,\n 62,\n 2127,\n 21052,\n 7,\n 944,\n 11,\n 1988,\n 2599,\n 198,\n 220,\n 220,\n 220,\n 220,\n 220,\n 220,\n 220,\n 37227,\n 50,\n 1039,\n 262,\n 11688,\n 62,\n 2127,\n 21052,\n 286,\n 428,\n 1395,\n 4029,\n 7449,\n 13,\n 220,\n 1303,\n 645,\n 20402,\n 25,\n 412,\n 33548,\n 198,\n 220,\n 220,\n 220,\n 220,\n 220,\n 220,\n 220,\n 37227,\n 198,\n 220,\n 220,\n 220,\n 220,\n 220,\n 220,\n 220,\n 1441,\n 2116,\n 13,\n 834,\n 2617,\n 62,\n 9186,\n 10786,\n 42348,\n 62,\n 2127,\n 21052,\n 3256,\n 1988,\n 8,\n 628,\n 220,\n 220,\n 220,\n 2488,\n 26745,\n 198,\n 220,\n 220,\n 220,\n 825,\n 12908,\n 62,\n 18747,\n 7,\n 944,\n 2599,\n 198,\n 220,\n 220,\n 220,\n 220,\n 220,\n 220,\n 220,\n 37227,\n 38,\n 1039,\n 262,\n 12908,\n 62,\n 18747,\n 286,\n 428,\n 1395,\n 4029,\n 7449,\n 13,\n 220,\n 1303,\n 645,\n 20402,\n 25,\n 412,\n 33548,\n 628,\n 220,\n 220,\n 220,\n 220,\n 220,\n 220,\n 220,\n 16409,\n 25,\n 198,\n 220,\n 220,\n 220,\n 220,\n 220,\n 220,\n 220,\n 220,\n 220,\n 220,\n 220,\n 29565,\n 600,\n 60,\n 2599,\n 383,\n 12908,\n 62,\n 18747,\n 286,\n 428,\n 1395,\n 4029,\n 7449,\n 13,\n 220,\n 1303,\n 645,\n 20402,\n 25,\n 412,\n 33548,\n 198,\n 220,\n 220,\n 220,\n 220,\n 220,\n 220,\n 220,\n 37227,\n 198,\n 220,\n 220,\n 220,\n 220,\n 220,\n 220,\n 220,\n 1441,\n 2116,\n 13,\n 834,\n 1136,\n 62,\n 9186,\n 10786,\n 29988,\n 1496,\n 62,\n 18747,\n 11537,\n 628,\n 220,\n 220,\n 220,\n 2488,\n 29988,\n 1496,\n 62,\n 18747,\n 13,\n 2617,\n 353,\n 198,\n 220,\n 220,\n 220,\n 825,\n 12908,\n 62,\n 18747,\n 7,\n 944,\n 11,\n 1988,\n 2599,\n 198,\n 220,\n 220,\n 220,\n 220,\n 220,\n 220,\n 220,\n 37227,\n 50,\n 1039,\n 262,\n 12908,\n 62,\n 18747,\n 286,\n 428,\n 1395,\n 4029,\n 7449,\n 13,\n 220,\n 1303,\n 645,\n 20402,\n 25,\n 412,\n 33548,\n 198,\n 220,\n 220,\n 220,\n 220,\n 220,\n 220,\n 220,\n 37227,\n 198,\n 220,\n 220,\n 220,\n 220,\n 220,\n 220,\n 220,\n 1441,\n 2116,\n 13,\n 834,\n 2617,\n 62,\n 9186,\n 10786,\n 29988,\n 1496,\n 62,\n 18747,\n 3256,\n 1988,\n 8,\n 628,\n 220,\n 220,\n 220,\n 2488,\n 26745,\n 198,\n 220,\n 220,\n 220,\n 825,\n 1438,\n 62,\n 8841,\n 7,\n 944,\n 2599,\n 198,\n 220,\n 220,\n 220,\n 220,\n 220,\n 220,\n 220,\n 37227,\n 38,\n 1039,\n 262,\n 1438,\n 62,\n 8841,\n 286,\n 428,\n 1395,\n 4029,\n 7449,\n 13,\n 220,\n 1303,\n 645,\n 20402,\n 25,\n 412,\n 33548,\n 628,\n 220,\n 220,\n 220,\n 220,\n 220,\n 220,\n 220,\n 16409,\n 25,\n 198,\n 220,\n 220,\n 220,\n 220,\n 220,\n 220,\n 220,\n 220,\n 220,\n 220,\n 220,\n 357,\n 2536,\n 2599,\n 383,\n 1438,\n 62,\n 8841,\n 286,\n 428,\n 1395,\n 4029,\n 7449,\n 13,\n 220,\n 1303,\n 645,\n 20402,\n 25,\n 412,\n 33548,\n 198,\n 220,\n 220,\n 220,\n 220,\n 220,\n 220,\n 220,\n 37227,\n 198,\n 220,\n 220,\n 220,\n 220,\n 220,\n 220,\n 220,\n 1441,\n 2116,\n 13,\n 834,\n 1136,\n 62,\n 9186,\n 10786,\n 3672,\n 62,\n 8841,\n 11537,\n 628,\n 220,\n 220,\n 220,\n 2488,\n 3672,\n 62,\n 8841,\n 13,\n 2617,\n 353,\n 198,\n 220,\n 220,\n 220,\n 825,\n 1438,\n 62,\n 8841,\n 7,\n 944,\n 11,\n 1988,\n 2599,\n 198,\n 220,\n 220,\n 220,\n 220,\n 220,\n 220,\n 220,\n 37227,\n 50,\n 1039,\n 262,\n 1438,\n 62,\n 8841,\n 286,\n 428,\n 1395,\n 4029,\n 7449,\n 13,\n 220,\n 1303,\n 645,\n 20402,\n 25,\n 412,\n 33548,\n 198,\n 220,\n 220,\n 220,\n 220,\n 220,\n 220,\n 220,\n 37227,\n 198,\n 220,\n 220,\n 220,\n 220,\n 220,\n 220,\n 220,\n 1441,\n 2116,\n 13,\n 834,\n 2617,\n 62,\n 9186,\n 10786,\n 3672,\n 62,\n 8841,\n 3256,\n 1988,\n 8,\n 628,\n 220,\n 220,\n 220,\n 2488,\n 26745,\n 198,\n 220,\n 220,\n 220,\n 825,\n 1438,\n 62,\n 17618,\n 7,\n 944,\n 2599,\n 198,\n 220,\n 220,\n 220,\n 220,\n 220,\n 220,\n 220,\n 37227,\n 38,\n 1039,\n 262,\n 1438,\n 62,\n 17618,\n 286,\n 428,\n 1395,\n 4029,\n 7449,\n 13,\n 220,\n 1303,\n 645,\n 20402,\n 25,\n 412,\n 33548,\n 628,\n 220,\n 220,\n 220,\n 220,\n 220,\n 220,\n 220,\n 16409,\n 25,\n 198,\n 220,\n 220,\n 220,\n 220,\n 220,\n 220,\n 220,\n 220,\n 220,\n 220,\n 220,\n 357,\n 22468,\n 2599,\n 383,\n 1438,\n 62,\n 17618,\n 286,\n 428,\n 1395,\n 4029,\n 7449,\n 13,\n 220,\n 1303,\n 645,\n 20402,\n 25,\n 412,\n 33548,\n 198,\n 220,\n 220,\n 220,\n 220,\n 220,\n 220,\n 220,\n 37227,\n 198,\n 220,\n 220,\n 220,\n 220,\n 220,\n 220,\n 220,\n 1441,\n 2116,\n 13,\n 834,\n 1136,\n 62,\n 9186,\n 10786,\n 3672,\n 62,\n 17618,\n 11537,\n 628,\n 220,\n 220,\n 220,\n 2488,\n 3672,\n 62,\n 17618,\n 13,\n 2617,\n 353,\n 198,\n 220,\n 220,\n 220,\n 825,\n 1438,\n 62,\n 17618,\n 7,\n 944,\n 11,\n 1988,\n 2599,\n 198,\n 220,\n 220,\n 220,\n 220,\n 220,\n 220,\n 220,\n 37227,\n 50,\n 1039,\n 262,\n 1438,\n 62,\n 17618,\n 286,\n 428,\n 1395,\n 4029,\n 7449,\n 13,\n 220,\n 1303,\n 645,\n 20402,\n 25,\n 412,\n 33548,\n 198,\n 220,\n 220,\n 220,\n 220,\n 220,\n 220,\n 220,\n 37227,\n 198,\n 220,\n 220,\n 220,\n 220,\n 220,\n 220,\n 220,\n 1441,\n 2116,\n 13,\n 834,\n 2617,\n 62,\n 9186,\n 10786,\n 3672,\n 62,\n 17618,\n 3256,\n 1988,\n 8,\n 628,\n 220,\n 220,\n 220,\n 2488,\n 26745,\n 198,\n 220,\n 220,\n 220,\n 825,\n 1438,\n 62,\n 41433,\n 7,\n 944,\n 2599,\n 198,\n 220,\n 220,\n 220,\n 220,\n 220,\n 220,\n 220,\n 37227,\n 38,\n 1039,\n 262,\n 1438,\n 62,\n 41433,\n 286,\n 428,\n 1395,\n 4029,\n 7449,\n 13,\n 220,\n 1303,\n 645,\n 20402,\n 25,\n 412,\n 33548,\n 628,\n 220,\n 220,\n 220,\n 220,\n 220,\n 220,\n 220,\n 16409,\n 25,\n 198,\n 220,\n 220,\n 220,\n 220,\n 220,\n 220,\n 220,\n 220,\n 220,\n 220,\n 220,\n 357,\n 600,\n 2599,\n 383,\n 1438,\n 62,\n 41433,\n 286,\n 428,\n 1395,\n 4029,\n 7449,\n 13,\n 220,\n 1303,\n 645,\n 20402,\n 25,\n 412,\n 33548,\n 198,\n 220,\n 220,\n 220,\n 220,\n 220,\n 220,\n 220,\n 37227,\n 198,\n 220,\n 220,\n 220,\n 220,\n 220,\n 220,\n 220,\n 1441,\n 2116,\n 13,\n 834,\n 1136,\n 62,\n 9186,\n 10786,\n 3672,\n 62,\n 41433,\n 11537,\n 628,\n 220,\n 220,\n 220,\n 2488,\n 3672,\n 62,\n 41433,\n 13,\n 2617,\n 353,\n 198,\n 220,\n 220,\n 220,\n 825,\n 1438,\n 62,\n 41433,\n 7,\n 944,\n 11,\n 1988,\n 2599,\n 198,\n 220,\n 220,\n 220,\n 220,\n 220,\n 220,\n 220,\n 37227,\n 50,\n 1039,\n 262,\n 1438,\n 62,\n 41433,\n 286,\n 428,\n 1395,\n 4029,\n 7449,\n 13,\n 220,\n 1303,\n 645,\n 20402,\n 25,\n 412,\n 33548,\n 198,\n 220,\n 220,\n 220,\n 220,\n 220,\n 220,\n 220,\n 37227,\n 198,\n 220,\n 220,\n 220,\n 220,\n 220,\n 220,\n 220,\n 1441,\n 2116,\n 13,\n 834,\n 2617,\n 62,\n 9186,\n 10786,\n 3672,\n 62,\n 41433,\n 3256,\n 1988,\n 8,\n 628,\n 220,\n 220,\n 220,\n 2488,\n 26745,\n 198,\n 220,\n 220,\n 220,\n 825,\n 1438,\n 62,\n 2127,\n 21052,\n 7,\n 944,\n 2599,\n 198,\n 220,\n 220,\n 220,\n 220,\n 220,\n 220,\n 220,\n 37227,\n 38,\n 1039,\n 262,\n 1438,\n 62,\n 2127,\n 21052,\n 286,\n 428,\n 1395,\n 4029,\n 7449,\n 13,\n 220,\n 1303,\n 645,\n 20402,\n 25,\n 412,\n 33548,\n 628,\n 220,\n 220,\n 220,\n 220,\n 220,\n 220,\n 220,\n 16409,\n 25,\n 198,\n 220,\n 220,\n 220,\n 220,\n 220,\n 220,\n 220,\n 220,\n 220,\n 220,\n 220,\n 357,\n 30388,\n 2599,\n 383,\n 1438,\n 62,\n 2127,\n 21052,\n 286,\n 428,\n 1395,\n 4029,\n 7449,\n 13,\n 220,\n 1303,\n 645,\n 20402,\n 25,\n 412,\n 33548,\n 198,\n 220,\n 220,\n 220,\n 220,\n 220,\n 220,\n 220,\n 37227,\n 198,\n 220,\n 220,\n 220,\n 220,\n 220,\n 220,\n 220,\n 1441,\n 2116,\n 13,\n 834,\n 1136,\n 62,\n 9186,\n 10786,\n 3672,\n 62,\n 2127,\n 21052,\n 11537,\n 628,\n 220,\n 220,\n 220,\n 2488,\n 3672,\n 62,\n 2127,\n 21052,\n 13,\n 2617,\n 353,\n 198,\n 220,\n 220,\n 220,\n 825,\n 1438,\n 62,\n 2127,\n 21052,\n 7,\n 944,\n 11,\n 1988,\n 2599,\n 198,\n 220,\n 220,\n 220,\n 220,\n 220,\n 220,\n 220,\n 37227,\n 50,\n 1039,\n 262,\n 1438,\n 62,\n 2127,\n 21052,\n 286,\n 428,\n 1395,\n 4029,\n 7449,\n 13,\n 220,\n 1303,\n 645,\n 20402,\n 25,\n 412,\n 33548,\n 198,\n 220,\n 220,\n 220,\n 220,\n 220,\n 220,\n 220,\n 37227,\n 198,\n 220,\n 220,\n 220,\n 220,\n 220,\n 220,\n 220,\n 1441,\n 2116,\n 13,\n 834,\n 2617,\n 62,\n 9186,\n 10786,\n 3672,\n 62,\n 2127,\n 21052,\n 3256,\n 1988,\n 8,\n 628,\n 220,\n 220,\n 220,\n 2488,\n 26745,\n 198,\n 220,\n 220,\n 220,\n 825,\n 1438,\n 62,\n 18747,\n 7,\n 944,\n 2599,\n 198,\n 220,\n 220,\n 220,\n 220,\n 220,\n 220,\n 220,\n 37227,\n 38,\n 1039,\n 262,\n 1438,\n 62,\n 18747,\n 286,\n 428,\n 1395,\n 4029,\n 7449,\n 13,\n 220,\n 1303,\n 645,\n 20402,\n 25,\n 412,\n 33548,\n 628,\n 220,\n 220,\n 220,\n 220,\n 220,\n 220,\n 220,\n 16409,\n 25,\n 198,\n 220,\n 220,\n 220,\n 220,\n 220,\n 220,\n 220,\n 220,\n 220,\n 220,\n 220,\n 29565,\n 600,\n 60,\n 2599,\n 383,\n 1438,\n 62,\n 18747,\n 286,\n 428,\n 1395,\n 4029,\n 7449,\n 13,\n 220,\n 1303,\n 645,\n 20402,\n 25,\n 412,\n 33548,\n 198,\n 220,\n 220,\n 220,\n 220,\n 220,\n 220,\n 220,\n 37227,\n 198,\n 220,\n 220,\n 220,\n 220,\n 220,\n 220,\n 220,\n 1441,\n 2116,\n 13,\n 834,\n 1136,\n 62,\n 9186,\n 10786,\n 3672,\n 62,\n 18747,\n 11537,\n 628,\n 220,\n 220,\n 220,\n 2488,\n 3672,\n 62,\n 18747,\n 13,\n 2617,\n 353,\n 198,\n 220,\n 220,\n 220,\n 825,\n 1438,\n 62,\n 18747,\n 7,\n 944,\n 11,\n 1988,\n 2599,\n 198,\n 220,\n 220,\n 220,\n 220,\n 220,\n 220,\n 220,\n 37227,\n 50,\n 1039,\n 262,\n 1438,\n 62,\n 18747,\n 286,\n 428,\n 1395,\n 4029,\n 7449,\n 13,\n 220,\n 1303,\n 645,\n 20402,\n 25,\n 412,\n 33548,\n 198,\n 220,\n 220,\n 220,\n 220,\n 220,\n 220,\n 220,\n 37227,\n 198,\n 220,\n 220,\n 220,\n 220,\n 220,\n 220,\n 220,\n 1441,\n 2116,\n 13,\n 834,\n 2617,\n 62,\n 9186,\n 10786,\n 3672,\n 62,\n 18747,\n 3256,\n 1988,\n 8,\n 628,\n 220,\n 220,\n 220,\n 2488,\n 26745,\n 198,\n 220,\n 220,\n 220,\n 825,\n 1438,\n 62,\n 29988,\n 1496,\n 62,\n 18747,\n 7,\n 944,\n 2599,\n 198,\n 220,\n 220,\n 220,\n 220,\n 220,\n 220,\n 220,\n 37227,\n 38,\n 1039,\n 262,\n 1438,\n 62,\n 29988,\n 1496,\n 62,\n 18747,\n 286,\n 428,\n 1395,\n 4029,\n 7449,\n 13,\n 220,\n 1303,\n 645,\n 20402,\n 25,\n 412,\n 33548,\n 628,\n 220,\n 220,\n 220,\n 220,\n 220,\n 220,\n 220,\n 16409,\n 25,\n 198,\n 220,\n 220,\n 220,\n 220,\n 220,\n 220,\n 220,\n 220,\n 220,\n 220,\n 220,\n 29565,\n 600,\n 60,\n 2599,\n 383,\n 1438,\n 62,\n 29988,\n 1496,\n 62,\n 18747,\n 286,\n 428,\n 1395,\n 4029,\n 7449,\n 13,\n 220,\n 1303,\n 645,\n 20402,\n 25,\n 412,\n 33548,\n 198,\n 220,\n 220,\n 220,\n 220,\n 220,\n 220,\n 220,\n 37227,\n 198,\n 220,\n 220,\n 220,\n 220,\n 220,\n 220,\n 220,\n 1441,\n 2116,\n 13,\n 834,\n 1136,\n 62,\n 9186,\n 10786,\n 3672,\n 62,\n 29988,\n 1496,\n 62,\n 18747,\n 11537,\n 628,\n 220,\n 220,\n 220,\n 2488,\n 3672,\n 62,\n 29988,\n 1496,\n 62,\n 18747,\n 13,\n 2617,\n 353,\n 198,\n 220,\n 220,\n 220,\n 825,\n 1438,\n 62,\n 29988,\n 1496,\n 62,\n 18747,\n 7,\n 944,\n 11,\n 1988,\n 2599,\n 198,\n 220,\n 220,\n 220,\n 220,\n 220,\n 220,\n 220,\n 37227,\n 50,\n 1039,\n 262,\n 1438,\n 62,\n 29988,\n 1496,\n 62,\n 18747,\n 286,\n 428,\n 1395,\n 4029,\n 7449,\n 13,\n 220,\n 1303,\n 645,\n 20402,\n 25,\n 412,\n 33548,\n 198,\n 220,\n 220,\n 220,\n 220,\n 220,\n 220,\n 220,\n 37227,\n 198,\n 220,\n 220,\n 220,\n 220,\n 220,\n 220,\n 220,\n 1441,\n 2116,\n 13,\n 834,\n 2617,\n 62,\n 9186,\n 10786,\n 3672,\n 62,\n 29988,\n 1496,\n 62,\n 18747,\n 3256,\n 1988,\n 8,\n 628,\n 220,\n 220,\n 220,\n 2488,\n 26745,\n 198,\n 220,\n 220,\n 220,\n 825,\n 21231,\n 62,\n 8841,\n 7,\n 944,\n 2599,\n 198,\n 220,\n 220,\n 220,\n 220,\n 220,\n 220,\n 220,\n 37227,\n 38,\n 1039,\n 262,\n 21231,\n 62,\n 8841,\n 286,\n 428,\n 1395,\n 4029,\n 7449,\n 13,\n 220,\n 1303,\n 645,\n 20402,\n 25,\n 412,\n 33548,\n 628,\n 220,\n 220,\n 220,\n 220,\n 220,\n 220,\n 220,\n 16409,\n 25,\n 198,\n 220,\n 220,\n 220,\n 220,\n 220,\n 220,\n 220,\n 220,\n 220,\n 220,\n 220,\n 357,\n 2536,\n 2599,\n 383,\n 21231,\n 62,\n 8841,\n 286,\n 428,\n 1395,\n 4029,\n 7449,\n 13,\n 220,\n 1303,\n 645,\n 20402,\n 25,\n 412,\n 33548,\n 198,\n 220,\n 220,\n 220,\n 220,\n 220,\n 220,\n 220,\n 37227,\n 198,\n 220,\n 220,\n 220,\n 220,\n 220,\n 220,\n 220,\n 1441,\n 2116,\n 13,\n 834,\n 1136,\n 62,\n 9186,\n 10786,\n 40290,\n 62,\n 8841,\n 11537,\n 628,\n 220,\n 220,\n 220,\n 2488,\n 40290,\n 62,\n 8841,\n 13,\n 2617,\n 353,\n 198,\n 220,\n 220,\n 220,\n 825,\n 21231,\n 62,\n 8841,\n 7,\n 944,\n 11,\n 1988,\n 2599,\n 198,\n 220,\n 220,\n 220,\n 220,\n 220,\n 220,\n 220,\n 37227,\n 50,\n 1039,\n 262,\n 21231,\n 62,\n 8841,\n 286,\n 428,\n 1395,\n 4029,\n 7449,\n 13,\n 220,\n 1303,\n 645,\n 20402,\n 25,\n 412,\n 33548,\n 198,\n 220,\n 220,\n 220,\n 220,\n 220,\n 220,\n 220,\n 37227,\n 198,\n 220,\n 220,\n 220,\n 220,\n 220,\n 220,\n 220,\n 1441,\n 2116,\n 13,\n 834,\n 2617,\n 62,\n 9186,\n 10786,\n 40290,\n 62,\n 8841,\n 3256,\n 1988,\n 8,\n 628,\n 220,\n 220,\n 220,\n 2488,\n 26745,\n 198,\n 220,\n 220,\n 220,\n 825,\n 21231,\n 62,\n 17618,\n 7,\n 944,\n 2599,\n 198,\n 220,\n 220,\n 220,\n 220,\n 220,\n 220,\n 220,\n 37227,\n 38,\n 1039,\n 262,\n 21231,\n 62,\n 17618,\n 286,\n 428,\n 1395,\n 4029,\n 7449,\n 13,\n 220,\n 1303,\n 645,\n 20402,\n 25,\n 412,\n 33548,\n 628,\n 220,\n 220,\n 220,\n 220,\n 220,\n 220,\n 220,\n 16409,\n 25,\n 198,\n 220,\n 220,\n 220,\n 220,\n 220,\n 220,\n 220,\n 220,\n 220,\n 220,\n 220,\n 357,\n 22468,\n 2599,\n 383,\n 21231,\n 62,\n 17618,\n 286,\n 428,\n 1395,\n 4029,\n 7449,\n 13,\n 220,\n 1303,\n 645,\n 20402,\n 25,\n 412,\n 33548,\n 198,\n 220,\n 220,\n 220,\n 220,\n 220,\n 220,\n 220,\n 37227,\n 198,\n 220,\n 220,\n 220,\n 220,\n 220,\n 220,\n 220,\n 1441,\n 2116,\n 13,\n 834,\n 1136,\n 62,\n 9186,\n 10786,\n 40290,\n 62,\n 17618,\n 11537,\n 628,\n 220,\n 220,\n 220,\n 2488,\n 40290,\n 62,\n 17618,\n 13,\n 2617,\n 353,\n 198,\n 220,\n 220,\n 220,\n 825,\n 21231,\n 62,\n 17618,\n 7,\n 944,\n 11,\n 1988,\n 2599,\n 198,\n 220,\n 220,\n 220,\n 220,\n 220,\n 220,\n 220,\n 37227,\n 50,\n 1039,\n 262,\n 21231,\n 62,\n 17618,\n 286,\n 428,\n 1395,\n 4029,\n 7449,\n 13,\n 220,\n 1303,\n 645,\n 20402,\n 25,\n 412,\n 33548,\n 198,\n 220,\n 220,\n 220,\n 220,\n 220,\n 220,\n 220,\n 37227,\n 198,\n 220,\n 220,\n 220,\n 220,\n 220,\n 220,\n 220,\n 1441,\n 2116,\n 13,\n 834,\n 2617,\n 62,\n 9186,\n 10786,\n 40290,\n 62,\n 17618,\n 3256,\n 1988,\n 8,\n 628,\n 220,\n 220,\n 220,\n 2488,\n 26745,\n 198,\n 220,\n 220,\n 220,\n 825,\n 21231,\n 62,\n 41433,\n 7,\n 944,\n 2599,\n 198,\n 220,\n 220,\n 220,\n 220,\n 220,\n 220,\n 220,\n 37227,\n 38,\n 1039,\n 262,\n 21231,\n 62,\n 41433,\n 286,\n 428,\n 1395,\n 4029,\n 7449,\n 13,\n 220,\n 1303,\n 645,\n 20402,\n 25,\n 412,\n 33548,\n 628,\n 220,\n 220,\n 220,\n 220,\n 220,\n 220,\n 220,\n 16409,\n 25,\n 198,\n 220,\n 220,\n 220,\n 220,\n 220,\n 220,\n 220,\n 220,\n 220,\n 220,\n 220,\n 357,\n 600,\n 2599,\n 383,\n 21231,\n 62,\n 41433,\n 286,\n 428,\n 1395,\n 4029,\n 7449,\n 13,\n 220,\n 1303,\n 645,\n 20402,\n 25,\n 412,\n 33548,\n 198,\n 220,\n 220,\n 220,\n 220,\n 220,\n 220,\n 220,\n 37227,\n 198,\n 220,\n 220,\n 220,\n 220,\n 220,\n 220,\n 220,\n 1441,\n 2116,\n 13,\n 834,\n 1136,\n 62,\n 9186,\n 10786,\n 40290,\n 62,\n 41433,\n 11537,\n 628,\n 220,\n 220,\n 220,\n 2488,\n 40290,\n 62,\n 41433,\n 13,\n 2617,\n 353,\n 198,\n 220,\n 220,\n 220,\n 825,\n 21231,\n 62,\n 41433,\n 7,\n 944,\n 11,\n 1988,\n 2599,\n 198,\n 220,\n 220,\n 220,\n 220,\n 220,\n 220,\n 220,\n 37227,\n 50,\n 1039,\n 262,\n 21231,\n 62,\n 41433,\n 286,\n 428,\n 1395,\n 4029,\n 7449,\n 13,\n 220,\n 1303,\n 645,\n 20402,\n 25,\n 412,\n 33548,\n 198,\n 220,\n 220,\n 220,\n 220,\n 220,\n 220,\n 220,\n 37227,\n 198,\n 220,\n 220,\n 220,\n 220,\n 220,\n 220,\n 220,\n 1441,\n 2116,\n 13,\n 834,\n 2617,\n 62,\n 9186,\n 10786,\n 40290,\n 62,\n 41433,\n 3256,\n 1988,\n 8,\n 628,\n 220,\n 220,\n 220,\n 2488,\n 26745,\n 198,\n 220,\n 220,\n 220,\n 825,\n 21231,\n 62,\n 2127,\n 21052,\n 7,\n 944,\n 2599,\n 198,\n 220,\n 220,\n 220,\n 220,\n 220,\n 220,\n 220,\n 37227,\n 38,\n 1039,\n 262,\n 21231,\n 62,\n 2127,\n 21052,\n 286,\n 428,\n 1395,\n 4029,\n 7449,\n 13,\n 220,\n 1303,\n 645,\n 20402,\n 25,\n 412,\n 33548,\n 628,\n 220,\n 220,\n 220,\n 220,\n 220,\n 220,\n 220,\n 16409,\n 25,\n 198,\n 220,\n 220,\n 220,\n 220,\n 220,\n 220,\n 220,\n 220,\n 220,\n 220,\n 220,\n 357,\n 30388,\n 2599,\n 383,\n 21231,\n 62,\n 2127,\n 21052,\n 286,\n 428,\n 1395,\n 4029,\n 7449,\n 13,\n 220,\n 1303,\n 645,\n 20402,\n 25,\n 412,\n 33548,\n 198,\n 220,\n 220,\n 220,\n 220,\n 220,\n 220,\n 220,\n 37227,\n 198,\n 220,\n 220,\n 220,\n 220,\n 220,\n 220,\n 220,\n 1441,\n 2116,\n 13,\n 834,\n 1136,\n 62,\n 9186,\n 10786,\n 40290,\n 62,\n 2127,\n 21052,\n 11537,\n 628,\n 220,\n 220,\n 220,\n 2488,\n 40290,\n 62,\n 2127,\n 21052,\n 13,\n 2617,\n 353,\n 198,\n 220,\n 220,\n 220,\n 825,\n 21231,\n 62,\n 2127,\n 21052,\n 7,\n 944,\n 11,\n 1988,\n 2599,\n 198,\n 220,\n 220,\n 220,\n 220,\n 220,\n 220,\n 220,\n 37227,\n 50,\n 1039,\n 262,\n 21231,\n 62,\n 2127,\n 21052,\n 286,\n 428,\n 1395,\n 4029,\n 7449,\n 13,\n 220,\n 1303,\n 645,\n 20402,\n 25,\n 412,\n 33548,\n 198,\n 220,\n 220,\n 220,\n 220,\n 220,\n 220,\n 220,\n 37227,\n 198,\n 220,\n 220,\n 220,\n 220,\n 220,\n 220,\n 220,\n 1441,\n 2116,\n 13,\n 834,\n 2617,\n 62,\n 9186,\n 10786,\n 40290,\n 62,\n 2127,\n 21052,\n 3256,\n 1988,\n 8,\n 628,\n 220,\n 220,\n 220,\n 2488,\n 26745,\n 198,\n 220,\n 220,\n 220,\n 825,\n 21231,\n 62,\n 18747,\n 7,\n 944,\n 2599,\n 198,\n 220,\n 220,\n 220,\n 220,\n 220,\n 220,\n 220,\n 37227,\n 38,\n 1039,\n 262,\n 21231,\n 62,\n 18747,\n 286,\n 428,\n 1395,\n 4029,\n 7449,\n 13,\n 220,\n 1303,\n 645,\n 20402,\n 25,\n 412,\n 33548,\n 628,\n 220,\n 220,\n 220,\n 220,\n 220,\n 220,\n 220,\n 16409,\n 25,\n 198,\n 220,\n 220,\n 220,\n 220,\n 220,\n 220,\n 220,\n 220,\n 220,\n 220,\n 220,\n 29565,\n 600,\n 60,\n 2599,\n 383,\n 21231,\n 62,\n 18747,\n 286,\n 428,\n 1395,\n 4029,\n 7449,\n 13,\n 220,\n 1303,\n 645,\n 20402,\n 25,\n 412,\n 33548,\n 198,\n 220,\n 220,\n 220,\n 220,\n 220,\n 220,\n 220,\n 37227,\n 198,\n 220,\n 220,\n 220,\n 220,\n 220,\n 220,\n 220,\n 1441,\n 2116,\n 13,\n 834,\n 1136,\n 62,\n 9186,\n 10786,\n 40290,\n 62,\n 18747,\n 11537,\n 628,\n 220,\n 220,\n 220,\n 2488,\n 40290,\n 62,\n 18747,\n 13,\n 2617,\n 353,\n 198,\n 220,\n 220,\n 220,\n 825,\n 21231,\n 62,\n 18747,\n 7,\n 944,\n 11,\n 1988,\n 2599,\n 198,\n 220,\n 220,\n 220,\n 220,\n 220,\n 220,\n 220,\n 37227,\n 50,\n 1039,\n 262,\n 21231,\n 62,\n 18747,\n 286,\n 428,\n 1395,\n 4029,\n 7449,\n 13,\n 220,\n 1303,\n 645,\n 20402,\n 25,\n 412,\n 33548,\n 198,\n 220,\n 220,\n 220,\n 220,\n 220,\n 220,\n 220,\n 37227,\n 198,\n 220,\n 220,\n 220,\n 220,\n 220,\n 220,\n 220,\n 1441,\n 2116,\n 13,\n 834,\n 2617,\n 62,\n 9186,\n 10786,\n 40290,\n 62,\n 18747,\n 3256,\n 1988,\n 8,\n 628,\n 220,\n 220,\n 220,\n 2488,\n 26745,\n 198,\n 220,\n 220,\n 220,\n 825,\n 21231,\n 62,\n 29988,\n 1496,\n 62,\n 18747,\n 7,\n 944,\n 2599,\n 198,\n 220,\n 220,\n 220,\n 220,\n 220,\n 220,\n 220,\n 37227,\n 38,\n 1039,\n 262,\n 21231,\n 62,\n 29988,\n 1496,\n 62,\n 18747,\n 286,\n 428,\n 1395,\n 4029,\n 7449,\n 13,\n 220,\n 1303,\n 645,\n 20402,\n 25,\n 412,\n 33548,\n 628,\n 220,\n 220,\n 220,\n 220,\n 220,\n 220,\n 220,\n 16409,\n 25,\n 198,\n 220,\n 220,\n 220,\n 220,\n 220,\n 220,\n 220,\n 220,\n 220,\n 220,\n 220,\n 29565,\n 600,\n 60,\n 2599,\n 383,\n 21231,\n 62,\n 29988,\n 1496,\n 62,\n 18747,\n 286,\n 428,\n 1395,\n 4029,\n 7449,\n 13,\n 220,\n 1303,\n 645,\n 20402,\n 25,\n 412,\n 33548,\n 198,\n 220,\n 220,\n 220,\n 220,\n 220,\n 220,\n 220,\n 37227,\n 198,\n 220,\n 220,\n 220,\n 220,\n 220,\n 220,\n 220,\n 1441,\n 2116,\n 13,\n 834,\n 1136,\n 62,\n 9186,\n 10786,\n 40290,\n 62,\n 29988,\n 1496,\n 62,\n 18747,\n 11537,\n 628,\n 220,\n 220,\n 220,\n 2488,\n 40290,\n 62,\n 29988,\n 1496,\n 62,\n 18747,\n 13,\n 2617,\n 353,\n 198,\n 220,\n 220,\n 220,\n 825,\n 21231,\n 62,\n 29988,\n 1496,\n 62,\n 18747,\n 7,\n 944,\n 11,\n 1988,\n 2599,\n 198,\n 220,\n 220,\n 220,\n 220,\n 220,\n 220,\n 220,\n 37227,\n 50,\n 1039,\n 262,\n 21231,\n 62,\n 29988,\n 1496,\n 62,\n 18747,\n 286,\n 428,\n 1395,\n 4029,\n 7449,\n 13,\n 220,\n 1303,\n 645,\n 20402,\n 25,\n 412,\n 33548,\n 198,\n 220,\n 220,\n 220,\n 220,\n 220,\n 220,\n 220,\n 37227,\n 198,\n 220,\n 220,\n 220,\n 220,\n 220,\n 220,\n 220,\n 1441,\n 2116,\n 13,\n 834,\n 2617,\n 62,\n 9186,\n 10786,\n 40290,\n 62,\n 29988,\n 1496,\n 62,\n 18747,\n 3256,\n 1988,\n 8,\n 628,\n 220,\n 220,\n 220,\n 2488,\n 26745,\n 198,\n 220,\n 220,\n 220,\n 825,\n 25745,\n 62,\n 8841,\n 7,\n 944,\n 2599,\n 198,\n 220,\n 220,\n 220,\n 220,\n 220,\n 220,\n 220,\n 37227,\n 38,\n 1039,\n 262,\n 25745,\n 62,\n 8841,\n 286,\n 428,\n 1395,\n 4029,\n 7449,\n 13,\n 220,\n 1303,\n 645,\n 20402,\n 25,\n 412,\n 33548,\n 628,\n 220,\n 220,\n 220,\n 220,\n 220,\n 220,\n 220,\n 16409,\n 25,\n 198,\n 220,\n 220,\n 220,\n 220,\n 220,\n 220,\n 220,\n 220,\n 220,\n 220,\n 220,\n 357,\n 2536,\n 2599,\n 383,\n 25745,\n 62,\n 8841,\n 286,\n 428,\n 1395,\n 4029,\n 7449,\n 13,\n 220,\n 1303,\n 645,\n 20402,\n 25,\n 412,\n 33548,\n 198,\n 220,\n 220,\n 220,\n 220,\n 220,\n 220,\n 220,\n 37227,\n 198,\n 220,\n 220,\n 220,\n 220,\n 220,\n 220,\n 220,\n 1441,\n 2116,\n 13,\n 834,\n 1136,\n 62,\n 9186,\n 10786,\n 14933,\n 10223,\n 62,\n 8841,\n 11537,\n 628,\n 220,\n 220,\n 220,\n 2488,\n 14933,\n 10223,\n 62,\n 8841,\n 13,\n 2617,\n 353,\n 198,\n 220,\n 220,\n 220,\n 825,\n 25745,\n 62,\n 8841,\n 7,\n 944,\n 11,\n 1988,\n 2599,\n 198,\n 220,\n 220,\n 220,\n 220,\n 220,\n 220,\n 220,\n 37227,\n 50,\n 1039,\n 262,\n 25745,\n 62,\n 8841,\n 286,\n 428,\n 1395,\n 4029,\n 7449,\n 13,\n 220,\n 1303,\n 645,\n 20402,\n 25,\n 412,\n 33548,\n 198,\n 220,\n 220,\n 220,\n 220,\n 220,\n 220,\n 220,\n 37227,\n 198,\n 220,\n 220,\n 220,\n 220,\n 220,\n 220,\n 220,\n 1441,\n 2116,\n 13,\n 834,\n 2617,\n 62,\n 9186,\n 10786,\n 14933,\n 10223,\n 62,\n 8841,\n 3256,\n 1988,\n 8,\n 628,\n 220,\n 220,\n 220,\n 2488,\n 26745,\n 198,\n 220,\n 220,\n 220,\n 825,\n 25745,\n 62,\n 17618,\n 7,\n 944,\n 2599,\n 198,\n 220,\n 220,\n 220,\n 220,\n 220,\n 220,\n 220,\n 37227,\n 38,\n 1039,\n 262,\n 25745,\n 62,\n 17618,\n 286,\n 428,\n 1395,\n 4029,\n 7449,\n 13,\n 220,\n 1303,\n 645,\n 20402,\n 25,\n 412,\n 33548,\n 628,\n 220,\n 220,\n 220,\n 220,\n 220,\n 220,\n 220,\n 16409,\n 25,\n 198,\n 220,\n 220,\n 220,\n 220,\n 220,\n 220,\n 220,\n 220,\n 220,\n 220,\n 220,\n 357,\n 22468,\n 2599,\n 383,\n 25745,\n 62,\n 17618,\n 286,\n 428,\n 1395,\n 4029,\n 7449,\n 13,\n 220,\n 1303,\n 645,\n 20402,\n 25,\n 412,\n 33548,\n 198,\n 220,\n 220,\n 220,\n 220,\n 220,\n 220,\n 220,\n 37227,\n 198,\n 220,\n 220,\n 220,\n 220,\n 220,\n 220,\n 220,\n 1441,\n 2116,\n 13,\n 834,\n 1136,\n 62,\n 9186,\n 10786,\n 14933,\n 10223,\n 62,\n 17618,\n 11537,\n 628,\n 220,\n 220,\n 220,\n 2488,\n 14933,\n 10223,\n 62,\n 17618,\n 13,\n 2617,\n 353,\n 198,\n 220,\n 220,\n 220,\n 825,\n 25745,\n 62,\n 17618,\n 7,\n 944,\n 11,\n 1988,\n 2599,\n 198,\n 220,\n 220,\n 220,\n 220,\n 220,\n 220,\n 220,\n 37227,\n 50,\n 1039,\n 262,\n 25745,\n 62,\n 17618,\n 286,\n 428,\n 1395,\n 4029,\n 7449,\n 13,\n 220,\n 1303,\n 645,\n 20402,\n 25,\n 412,\n 33548,\n 198,\n 220,\n 220,\n 220,\n 220,\n 220,\n 220,\n 220,\n 37227,\n 198,\n 220,\n 220,\n 220,\n 220,\n 220,\n 220,\n 220,\n 1441,\n 2116,\n 13,\n 834,\n 2617,\n 62,\n 9186,\n 10786,\n 14933,\n 10223,\n 62,\n 17618,\n 3256,\n 1988,\n 8,\n 628,\n 220,\n 220,\n 220,\n 2488,\n 26745,\n 198,\n 220,\n 220,\n 220,\n 825,\n 25745,\n 62,\n 41433,\n 7,\n 944,\n 2599,\n 198,\n 220,\n 220,\n 220,\n 220,\n 220,\n 220,\n 220,\n 37227,\n 38,\n 1039,\n 262,\n 25745,\n 62,\n 41433,\n 286,\n 428,\n 1395,\n 4029,\n 7449,\n 13,\n 220,\n 1303,\n 645,\n 20402,\n 25,\n 412,\n 33548,\n 628,\n 220,\n 220,\n 220,\n 220,\n 220,\n 220,\n 220,\n 16409,\n 25,\n 198,\n 220,\n 220,\n 220,\n 220,\n 220,\n 220,\n 220,\n 220,\n 220,\n 220,\n 220,\n 357,\n 600,\n 2599,\n 383,\n 25745,\n 62,\n 41433,\n 286,\n 428,\n 1395,\n 4029,\n 7449,\n 13,\n 220,\n 1303,\n 645,\n 20402,\n 25,\n 412,\n 33548,\n 198,\n 220,\n 220,\n 220,\n 220,\n 220,\n 220,\n 220,\n 37227,\n 198,\n 220,\n 220,\n 220,\n 220,\n 220,\n 220,\n 220,\n 1441,\n 2116,\n 13,\n 834,\n 1136,\n 62,\n 9186,\n 10786,\n 14933,\n 10223,\n 62,\n 41433,\n 11537,\n 628,\n 220,\n 220,\n 220,\n 2488,\n 14933,\n 10223,\n 62,\n 41433,\n 13,\n 2617,\n 353,\n 198,\n 220,\n 220,\n 220,\n 825,\n 25745,\n 62,\n 41433,\n 7,\n 944,\n 11,\n 1988,\n 2599,\n 198,\n 220,\n 220,\n 220,\n 220,\n 220,\n 220,\n 220,\n 37227,\n 50,\n 1039,\n 262,\n 25745,\n 62,\n 41433,\n 286,\n 428,\n 1395,\n 4029,\n 7449,\n 13,\n 220,\n 1303,\n 645,\n 20402,\n 25,\n 412,\n 33548,\n 198,\n 220,\n 220,\n 220,\n 220,\n 220,\n 220,\n 220,\n 37227,\n 198,\n 220,\n 220,\n 220,\n 220,\n 220,\n 220,\n 220,\n 1441,\n 2116,\n 13,\n 834,\n 2617,\n 62,\n 9186,\n 10786,\n 14933,\n 10223,\n 62,\n 41433,\n 3256,\n 1988,\n 8,\n 628,\n 220,\n 220,\n 220,\n 2488,\n 26745,\n 198,\n 220,\n 220,\n 220,\n 825,\n 25745,\n 62,\n 2127,\n 21052,\n 7,\n 944,\n 2599,\n 198,\n 220,\n 220,\n 220,\n 220,\n 220,\n 220,\n 220,\n 37227,\n 38,\n 1039,\n 262,\n 25745,\n 62,\n 2127,\n 21052,\n 286,\n 428,\n 1395,\n 4029,\n 7449,\n 13,\n 220,\n 1303,\n 645,\n 20402,\n 25,\n 412,\n 33548,\n 628,\n 220,\n 220,\n 220,\n 220,\n 220,\n 220,\n 220,\n 16409,\n 25,\n 198,\n 220,\n 220,\n 220,\n 220,\n 220,\n 220,\n 220,\n 220,\n 220,\n 220,\n 220,\n 357,\n 30388,\n 2599,\n 383,\n 25745,\n 62,\n 2127,\n 21052,\n 286,\n 428,\n 1395,\n 4029,\n 7449,\n 13,\n 220,\n 1303,\n 645,\n 20402,\n 25,\n 412,\n 33548,\n 198,\n 220,\n 220,\n 220,\n 220,\n 220,\n 220,\n 220,\n 37227,\n 198,\n 220,\n 220,\n 220,\n 220,\n 220,\n 220,\n 220,\n 1441,\n 2116,\n 13,\n 834,\n 1136,\n 62,\n 9186,\n 10786,\n 14933,\n 10223,\n 62,\n 2127,\n 21052,\n 11537,\n 628,\n 220,\n 220,\n 220,\n 2488,\n 14933,\n 10223,\n 62,\n 2127,\n 21052,\n 13,\n 2617,\n 353,\n 198,\n 220,\n 220,\n 220,\n 825,\n 25745,\n 62,\n 2127,\n 21052,\n 7,\n 944,\n 11,\n 1988,\n 2599,\n 198,\n 220,\n 220,\n 220,\n 220,\n 220,\n 220,\n 220,\n 37227,\n 50,\n 1039,\n 262,\n 25745,\n 62,\n 2127,\n 21052,\n 286,\n 428,\n 1395,\n 4029,\n 7449,\n 13,\n 220,\n 1303,\n 645,\n 20402,\n 25,\n 412,\n 33548,\n 198,\n 220,\n 220,\n 220,\n 220,\n 220,\n 220,\n 220,\n 37227,\n 198,\n 220,\n 220,\n 220,\n 220,\n 220,\n 220,\n 220,\n 1441,\n 2116,\n 13,\n 834,\n 2617,\n 62,\n 9186,\n 10786,\n 14933,\n 10223,\n 62,\n 2127,\n 21052,\n 3256,\n 1988,\n 8,\n 628,\n 220,\n 220,\n 220,\n 2488,\n 26745,\n 198,\n 220,\n 220,\n 220,\n 825,\n 25745,\n 62,\n 18747,\n 7,\n 944,\n 2599,\n 198,\n 220,\n 220,\n 220,\n 220,\n 220,\n 220,\n 220,\n 37227,\n 38,\n 1039,\n 262,\n 25745,\n 62,\n 18747,\n 286,\n 428,\n 1395,\n 4029,\n 7449,\n 13,\n 220,\n 1303,\n 645,\n 20402,\n 25,\n 412,\n 33548,\n 628,\n 220,\n 220,\n 220,\n 220,\n 220,\n 220,\n 220,\n 16409,\n 25,\n 198,\n 220,\n 220,\n 220,\n 220,\n 220,\n 220,\n 220,\n 220,\n 220,\n 220,\n 220,\n 29565,\n 600,\n 60,\n 2599,\n 383,\n 25745,\n 62,\n 18747,\n 286,\n 428,\n 1395,\n 4029,\n 7449,\n 13,\n 220,\n 1303,\n 645,\n 20402,\n 25,\n 412,\n 33548,\n 198,\n 220,\n 220,\n 220,\n 220,\n 220,\n 220,\n 220,\n 37227,\n 198,\n 220,\n 220,\n 220,\n 220,\n 220,\n 220,\n 220,\n 1441,\n 2116,\n 13,\n 834,\n 1136,\n 62,\n 9186,\n 10786,\n 14933,\n 10223,\n 62,\n 18747,\n 11537,\n 628,\n 220,\n 220,\n 220,\n 2488,\n 14933,\n 10223,\n 62,\n 18747,\n 13,\n 2617,\n 353,\n 198,\n 220,\n 220,\n 220,\n 825,\n 25745,\n 62,\n 18747,\n 7,\n 944,\n 11,\n 1988,\n 2599,\n 198,\n 220,\n 220,\n 220,\n 220,\n 220,\n 220,\n 220,\n 37227,\n 50,\n 1039,\n 262,\n 25745,\n 62,\n 18747,\n 286,\n 428,\n 1395,\n 4029,\n 7449,\n 13,\n 220,\n 1303,\n 645,\n 20402,\n 25,\n 412,\n 33548,\n 198,\n 220,\n 220,\n 220,\n 220,\n 220,\n 220,\n 220,\n 37227,\n 198,\n 220,\n 220,\n 220,\n 220,\n 220,\n 220,\n 220,\n 1441,\n 2116,\n 13,\n 834,\n 2617,\n 62,\n 9186,\n 10786,\n 14933,\n 10223,\n 62,\n 18747,\n 3256,\n 1988,\n 8,\n 628,\n 220,\n 220,\n 220,\n 2488,\n 26745,\n 198,\n 220,\n 220,\n 220,\n 825,\n 25745,\n 62,\n 29988,\n 1496,\n 62,\n 18747,\n 7,\n 944,\n 2599,\n 198,\n 220,\n 220,\n 220,\n 220,\n 220,\n 220,\n 220,\n 37227,\n 38,\n 1039,\n 262,\n 25745,\n 62,\n 29988,\n 1496,\n 62,\n 18747,\n 286,\n 428,\n 1395,\n 4029,\n 7449,\n 13,\n 220,\n 1303,\n 645,\n 20402,\n 25,\n 412,\n 33548,\n 628,\n 220,\n 220,\n 220,\n 220,\n 220,\n 220,\n 220,\n 16409,\n 25,\n 198,\n 220,\n 220,\n 220,\n 220,\n 220,\n 220,\n 220,\n 220,\n 220,\n 220,\n 220,\n 29565,\n 600,\n 60,\n 2599,\n 383,\n 25745,\n 62,\n 29988,\n 1496,\n 62,\n 18747,\n 286,\n 428,\n 1395,\n 4029,\n 7449,\n 13,\n 220,\n 1303,\n 645,\n 20402,\n 25,\n 412,\n 33548,\n 198,\n 220,\n 220,\n 220,\n 220,\n 220,\n 220,\n 220,\n 37227,\n 198,\n 220,\n 220,\n 220,\n 220,\n 220,\n 220,\n 220,\n 1441,\n 2116,\n 13,\n 834,\n 1136,\n 62,\n 9186,\n 10786,\n 14933,\n 10223,\n 62,\n 29988,\n 1496,\n 62,\n 18747,\n 11537,\n 628,\n 220,\n 220,\n 220,\n 2488,\n 14933,\n 10223,\n 62,\n 29988,\n 1496,\n 62,\n 18747,\n 13,\n 2617,\n 353,\n 198,\n 220,\n 220,\n 220,\n 825,\n 25745,\n 62,\n 29988,\n 1496,\n 62,\n 18747,\n 7,\n 944,\n 11,\n 1988,\n 2599,\n 198,\n 220,\n 220,\n 220,\n 220,\n 220,\n 220,\n 220,\n 37227,\n 50,\n 1039,\n 262,\n 25745,\n 62,\n 29988,\n 1496,\n 62,\n 18747,\n 286,\n 428,\n 1395,\n 4029,\n 7449,\n 13,\n 220,\n 1303,\n 645,\n 20402,\n 25,\n 412,\n 33548,\n 198,\n 220,\n 220,\n 220,\n 220,\n 220,\n 220,\n 220,\n 37227,\n 198,\n 220,\n 220,\n 220,\n 220,\n 220,\n 220,\n 220,\n 1441,\n 2116,\n 13,\n 834,\n 2617,\n 62,\n 9186,\n 10786,\n 14933,\n 10223,\n 62,\n 29988,\n 1496,\n 62,\n 18747,\n 3256,\n 1988,\n 8,\n 628,\n 220,\n 220,\n 220,\n 2488,\n 26745,\n 198,\n 220,\n 220,\n 220,\n 825,\n 21231,\n 62,\n 5907,\n 62,\n 8841,\n 7,\n 944,\n 2599,\n 198,\n 220,\n 220,\n 220,\n 220,\n 220,\n 220,\n 220,\n 37227,\n 38,\n 1039,\n 262,\n 21231,\n 62,\n 5907,\n 62,\n 8841,\n 286,\n 428,\n 1395,\n 4029,\n 7449,\n 13,\n 220,\n 1303,\n 645,\n 20402,\n 25,\n 412,\n 33548,\n 628,\n 220,\n 220,\n 220,\n 220,\n 220,\n 220,\n 220,\n 16409,\n 25,\n 198,\n 220,\n 220,\n 220,\n 220,\n 220,\n 220,\n 220,\n 220,\n 220,\n 220,\n 220,\n 357,\n 2536,\n 2599,\n 383,\n 21231,\n 62,\n 5907,\n 62,\n 8841,\n 286,\n 428,\n 1395,\n 4029,\n 7449,\n 13,\n 220,\n 1303,\n 645,\n 20402,\n 25,\n 412,\n 33548,\n 198,\n 220,\n 220,\n 220,\n 220,\n 220,\n 220,\n 220,\n 37227,\n 198,\n 220,\n 220,\n 220,\n 220,\n 220,\n 220,\n 220,\n 1441,\n 2116,\n 13,\n 834,\n 1136,\n 62,\n 9186,\n 10786,\n 40290,\n 62,\n 5907,\n 62,\n 8841,\n 11537,\n 628,\n 220,\n 220,\n 220,\n 2488,\n 40290,\n 62,\n 5907,\n 62,\n 8841,\n 13,\n 2617,\n 353,\n 198,\n 220,\n 220,\n 220,\n 825,\n 21231,\n 62,\n 5907,\n 62,\n 8841,\n 7,\n 944,\n 11,\n 1988,\n 2599,\n 198,\n 220,\n 220,\n 220,\n 220,\n 220,\n 220,\n 220,\n 37227,\n 50,\n 1039,\n 262,\n 21231,\n 62,\n 5907,\n 62,\n 8841,\n 286,\n 428,\n 1395,\n 4029,\n 7449,\n 13,\n 220,\n 1303,\n 645,\n 20402,\n 25,\n 412,\n 33548,\n 198,\n 220,\n 220,\n 220,\n 220,\n 220,\n 220,\n 220,\n 37227,\n 198,\n 220,\n 220,\n 220,\n 220,\n 220,\n 220,\n 220,\n 1441,\n 2116,\n 13,\n 834,\n 2617,\n 62,\n 9186,\n 10786,\n 40290,\n 62,\n 5907,\n 62,\n 8841,\n 3256,\n 1988,\n 8,\n 628,\n 220,\n 220,\n 220,\n 2488,\n 26745,\n 198,\n 220,\n 220,\n 220,\n 825,\n 21231,\n 62,\n 5907,\n 62,\n 17618,\n 7,\n 944,\n 2599,\n 198,\n 220,\n 220,\n 220,\n 220,\n 220,\n 220,\n 220,\n 37227,\n 38,\n 1039,\n 262,\n 21231,\n 62,\n 5907,\n 62,\n 17618,\n 286,\n 428,\n 1395,\n 4029,\n 7449,\n 13,\n 220,\n 1303,\n 645,\n 20402,\n 25,\n 412,\n 33548,\n 628,\n 220,\n 220,\n 220,\n 220,\n 220,\n 220,\n 220,\n 16409,\n 25,\n 198,\n 220,\n 220,\n 220,\n 220,\n 220,\n 220,\n 220,\n 220,\n 220,\n 220,\n 220,\n 357,\n 22468,\n 2599,\n 383,\n 21231,\n 62,\n 5907,\n 62,\n 17618,\n 286,\n 428,\n 1395,\n 4029,\n 7449,\n 13,\n 220,\n 1303,\n 645,\n 20402,\n 25,\n 412,\n 33548,\n 198,\n 220,\n 220,\n 220,\n 220,\n 220,\n 220,\n 220,\n 37227,\n 198,\n 220,\n 220,\n 220,\n 220,\n 220,\n 220,\n 220,\n 1441,\n 2116,\n 13,\n 834,\n 1136,\n 62,\n 9186,\n 10786,\n 40290,\n 62,\n 5907,\n 62,\n 17618,\n 11537,\n 628,\n 220,\n 220,\n 220,\n 2488,\n 40290,\n 62,\n 5907,\n 62,\n 17618,\n 13,\n 2617,\n 353,\n 198,\n 220,\n 220,\n 220,\n 825,\n 21231,\n 62,\n 5907,\n 62,\n 17618,\n 7,\n 944,\n 11,\n 1988,\n 2599,\n 198,\n 220,\n 220,\n 220,\n 220,\n 220,\n 220,\n 220,\n 37227,\n 50,\n 1039,\n 262,\n 21231,\n 62,\n 5907,\n 62,\n 17618,\n 286,\n 428,\n 1395,\n 4029,\n 7449,\n 13,\n 220,\n 1303,\n 645,\n 20402,\n 25,\n 412,\n 33548,\n 198,\n 220,\n 220,\n 220,\n 220,\n 220,\n 220,\n 220,\n 37227,\n 198,\n 220,\n 220,\n 220,\n 220,\n 220,\n 220,\n 220,\n 1441,\n 2116,\n 13,\n 834,\n 2617,\n 62,\n 9186,\n 10786,\n 40290,\n 62,\n 5907,\n 62,\n 17618,\n 3256,\n 1988,\n 8,\n 628,\n 220,\n 220,\n 220,\n 2488,\n 26745,\n 198,\n 220,\n 220,\n 220,\n 825,\n 21231,\n 62,\n 5907,\n 62,\n 41433,\n 7,\n 944,\n 2599,\n 198,\n 220,\n 220,\n 220,\n 220,\n 220,\n 220,\n 220,\n 37227,\n 38,\n 1039,\n 262,\n 21231,\n 62,\n 5907,\n 62,\n 41433,\n 286,\n 428,\n 1395,\n 4029,\n 7449,\n 13,\n 220,\n 1303,\n 645,\n 20402,\n 25,\n 412,\n 33548,\n 628,\n 220,\n 220,\n 220,\n 220,\n 220,\n 220,\n 220,\n 16409,\n 25,\n 198,\n 220,\n 220,\n 220,\n 220,\n 220,\n 220,\n 220,\n 220,\n 220,\n 220,\n 220,\n 357,\n 600,\n 2599,\n 383,\n 21231,\n 62,\n 5907,\n 62,\n 41433,\n 286,\n 428,\n 1395,\n 4029,\n 7449,\n 13,\n 220,\n 1303,\n 645,\n 20402,\n 25,\n 412,\n 33548,\n 198,\n 220,\n 220,\n 220,\n 220,\n 220,\n 220,\n 220,\n 37227,\n 198,\n 220,\n 220,\n 220,\n 220,\n 220,\n 220,\n 220,\n 1441,\n 2116,\n 13,\n 834,\n 1136,\n 62,\n 9186,\n 10786,\n 40290,\n 62,\n 5907,\n 62,\n 41433,\n 11537,\n 628,\n 220,\n 220,\n 220,\n 2488,\n 40290,\n 62,\n 5907,\n 62,\n 41433,\n 13,\n 2617,\n 353,\n 198,\n 220,\n 220,\n 220,\n 825,\n 21231,\n 62,\n 5907,\n 62,\n 41433,\n 7,\n 944,\n 11,\n 1988,\n 2599,\n 198,\n 220,\n 220,\n 220,\n 220,\n 220,\n 220,\n 220,\n 37227,\n 50,\n 1039,\n 262,\n 21231,\n 62,\n 5907,\n 62,\n 41433,\n 286,\n 428,\n 1395,\n 4029,\n 7449,\n 13,\n 220,\n 1303,\n 645,\n 20402,\n 25,\n 412,\n 33548,\n 198,\n 220,\n 220,\n 220,\n 220,\n 220,\n 220,\n 220,\n 37227,\n 198,\n 220,\n 220,\n 220,\n 220,\n 220,\n 220,\n 220,\n 1441,\n 2116,\n 13,\n 834,\n 2617,\n 62,\n 9186,\n 10786,\n 40290,\n 62,\n 5907,\n 62,\n 41433,\n 3256,\n 1988,\n 8,\n 628,\n 220,\n 220,\n 220,\n 2488,\n 26745,\n 198,\n 220,\n 220,\n 220,\n 825,\n 21231,\n 62,\n 5907,\n 62,\n 2127,\n 21052,\n 7,\n 944,\n 2599,\n 198,\n 220,\n 220,\n 220,\n 220,\n 220,\n 220,\n 220,\n 37227,\n 38,\n 1039,\n 262,\n 21231,\n 62,\n 5907,\n 62,\n 2127,\n 21052,\n 286,\n 428,\n 1395,\n 4029,\n 7449,\n 13,\n 220,\n 1303,\n 645,\n 20402,\n 25,\n 412,\n 33548,\n 628,\n 220,\n 220,\n 220,\n 220,\n 220,\n 220,\n 220,\n 16409,\n 25,\n 198,\n 220,\n 220,\n 220,\n 220,\n 220,\n 220,\n 220,\n 220,\n 220,\n 220,\n 220,\n 357,\n 30388,\n 2599,\n 383,\n 21231,\n 62,\n 5907,\n 62,\n 2127,\n 21052,\n 286,\n 428,\n 1395,\n 4029,\n 7449,\n 13,\n 220,\n 1303,\n 645,\n 20402,\n 25,\n 412,\n 33548,\n 198,\n 220,\n 220,\n 220,\n 220,\n 220,\n 220,\n 220,\n 37227,\n 198,\n 220,\n 220,\n 220,\n 220,\n 220,\n 220,\n 220,\n 1441,\n 2116,\n 13,\n 834,\n 1136,\n 62,\n 9186,\n 10786,\n 40290,\n 62,\n 5907,\n 62,\n 2127,\n 21052,\n 11537,\n 628,\n 220,\n 220,\n 220,\n 2488,\n 40290,\n 62,\n 5907,\n 62,\n 2127,\n 21052,\n 13,\n 2617,\n 353,\n 198,\n 220,\n 220,\n 220,\n 825,\n 21231,\n 62,\n 5907,\n 62,\n 2127,\n 21052,\n 7,\n 944,\n 11,\n 1988,\n 2599,\n 198,\n 220,\n 220,\n 220,\n 220,\n 220,\n 220,\n 220,\n 37227,\n 50,\n 1039,\n 262,\n 21231,\n 62,\n 5907,\n 62,\n 2127,\n 21052,\n 286,\n 428,\n 1395,\n 4029,\n 7449,\n 13,\n 220,\n 1303,\n 645,\n 20402,\n 25,\n 412,\n 33548,\n 198,\n 220,\n 220,\n 220,\n 220,\n 220,\n 220,\n 220,\n 37227,\n 198,\n 220,\n 220,\n 220,\n 220,\n 220,\n 220,\n 220,\n 1441,\n 2116,\n 13,\n 834,\n 2617,\n 62,\n 9186,\n 10786,\n 40290,\n 62,\n 5907,\n 62,\n 2127,\n 21052,\n 3256,\n 1988,\n 8,\n 628,\n 220,\n 220,\n 220,\n 2488,\n 26745,\n 198,\n 220,\n 220,\n 220,\n 825,\n 21231,\n 62,\n 5907,\n 62,\n 18747,\n 7,\n 944,\n 2599,\n 198,\n 220,\n 220,\n 220,\n 220,\n 220,\n 220,\n 220,\n 37227,\n 38,\n 1039,\n 262,\n 21231,\n 62,\n 5907,\n 62,\n 18747,\n 286,\n 428,\n 1395,\n 4029,\n 7449,\n 13,\n 220,\n 1303,\n 645,\n 20402,\n 25,\n 412,\n 33548,\n 628,\n 220,\n 220,\n 220,\n 220,\n 220,\n 220,\n 220,\n 16409,\n 25,\n 198,\n 220,\n 220,\n 220,\n 220,\n 220,\n 220,\n 220,\n 220,\n 220,\n 220,\n 220,\n 29565,\n 600,\n 60,\n 2599,\n 383,\n 21231,\n 62,\n 5907,\n 62,\n 18747,\n 286,\n 428,\n 1395,\n 4029,\n 7449,\n 13,\n 220,\n 1303,\n 645,\n 20402,\n 25,\n 412,\n 33548,\n 198,\n 220,\n 220,\n 220,\n 220,\n 220,\n 220,\n 220,\n 37227,\n 198,\n 220,\n 220,\n 220,\n 220,\n 220,\n 220,\n 220,\n 1441,\n 2116,\n 13,\n 834,\n 1136,\n 62,\n 9186,\n 10786,\n 40290,\n 62,\n 5907,\n 62,\n 18747,\n 11537,\n 628,\n 220,\n 220,\n 220,\n 2488,\n 40290,\n 62,\n 5907,\n 62,\n 18747,\n 13,\n 2617,\n 353,\n 198,\n 220,\n 220,\n 220,\n 825,\n 21231,\n 62,\n 5907,\n 62,\n 18747,\n 7,\n 944,\n 11,\n 1988,\n 2599,\n 198,\n 220,\n 220,\n 220,\n 220,\n 220,\n 220,\n 220,\n 37227,\n 50,\n 1039,\n 262,\n 21231,\n 62,\n 5907,\n 62,\n 18747,\n 286,\n 428,\n 1395,\n 4029,\n 7449,\n 13,\n 220,\n 1303,\n 645,\n 20402,\n 25,\n 412,\n 33548,\n 198,\n 220,\n 220,\n 220,\n 220,\n 220,\n 220,\n 220,\n 37227,\n 198,\n 220,\n 220,\n 220,\n 220,\n 220,\n 220,\n 220,\n 1441,\n 2116,\n 13,\n 834,\n 2617,\n 62,\n 9186,\n 10786,\n 40290,\n 62,\n 5907,\n 62,\n 18747,\n 3256,\n 1988,\n 8,\n 628,\n 220,\n 220,\n 220,\n 2488,\n 26745,\n 198,\n 220,\n 220,\n 220,\n 825,\n 21231,\n 62,\n 5907,\n 62,\n 29988,\n 1496,\n 62,\n 18747,\n 7,\n 944,\n 2599,\n 198,\n 220,\n 220,\n 220,\n 220,\n 220,\n 220,\n 220,\n 37227,\n 38,\n 1039,\n 262,\n 21231,\n 62,\n 5907,\n 62,\n 29988,\n 1496,\n 62,\n 18747,\n 286,\n 428,\n 1395,\n 4029,\n 7449,\n 13,\n 220,\n 1303,\n 645,\n 20402,\n 25,\n 412,\n 33548,\n 628,\n 220,\n 220,\n 220,\n 220,\n 220,\n 220,\n 220,\n 16409,\n 25,\n 198,\n 220,\n 220,\n 220,\n 220,\n 220,\n 220,\n 220,\n 220,\n 220,\n 220,\n 220,\n 29565,\n 600,\n 60,\n 2599,\n 383,\n 21231,\n 62,\n 5907,\n 62,\n 29988,\n 1496,\n 62,\n 18747,\n 286,\n 428,\n 1395,\n 4029,\n 7449,\n 13,\n 220,\n 1303,\n 645,\n 20402,\n 25,\n 412,\n 33548,\n 198,\n 220,\n 220,\n 220,\n 220,\n 220,\n 220,\n 220,\n 37227,\n 198,\n 220,\n 220,\n 220,\n 220,\n 220,\n 220,\n 220,\n 1441,\n 2116,\n 13,\n 834,\n 1136,\n 62,\n 9186,\n 10786,\n 40290,\n 62,\n 5907,\n 62,\n 29988,\n 1496,\n 62,\n 18747,\n 11537,\n 628,\n 220,\n 220,\n 220,\n 2488,\n 40290,\n 62,\n 5907,\n 62,\n 29988,\n 1496,\n 62,\n 18747,\n 13,\n 2617,\n 353,\n 198,\n 220,\n 220,\n 220,\n 825,\n 21231,\n 62,\n 5907,\n 62,\n 29988,\n 1496,\n 62,\n 18747,\n 7,\n 944,\n 11,\n 1988,\n 2599,\n 198,\n 220,\n 220,\n 220,\n 220,\n 220,\n 220,\n 220,\n 37227,\n 50,\n 1039,\n 262,\n 21231,\n 62,\n 5907,\n 62,\n 29988,\n 1496,\n 62,\n 18747,\n 286,\n 428,\n 1395,\n 4029,\n 7449,\n 13,\n 220,\n 1303,\n 645,\n 20402,\n 25,\n 412,\n 33548,\n 198,\n 220,\n 220,\n 220,\n 220,\n 220,\n 220,\n 220,\n 37227,\n 198,\n 220,\n 220,\n 220,\n 220,\n 220,\n 220,\n 220,\n 1441,\n 2116,\n 13,\n 834,\n 2617,\n 62,\n 9186,\n 10786,\n 40290,\n 62,\n 5907,\n 62,\n 29988,\n 1496,\n 62,\n 18747,\n 3256,\n 1988,\n 8,\n 628,\n 220,\n 220,\n 220,\n 825,\n 284,\n 62,\n 11600,\n 7,\n 944,\n 2599,\n 198,\n 220,\n 220,\n 220,\n 220,\n 220,\n 220,\n 220,\n 37227,\n 35561,\n 262,\n 2746,\n 6608,\n 355,\n 257,\n 8633,\n 37811,\n 198,\n 220,\n 220,\n 220,\n 220,\n 220,\n 220,\n 220,\n 1441,\n 2746,\n 62,\n 1462,\n 62,\n 11600,\n 7,\n 944,\n 11,\n 11389,\n 1096,\n 28,\n 25101,\n 8,\n 628,\n 220,\n 220,\n 220,\n 825,\n 284,\n 62,\n 2536,\n 7,\n 944,\n 2599,\n 198,\n 220,\n 220,\n 220,\n 220,\n 220,\n 220,\n 220,\n 37227,\n 35561,\n 262,\n 4731,\n 10552,\n 286,\n 262,\n 2746,\n 37811,\n 198,\n 220,\n 220,\n 220,\n 220,\n 220,\n 220,\n 220,\n 1441,\n 279,\n 4798,\n 13,\n 79,\n 18982,\n 7,\n 944,\n 13,\n 1462,\n 62,\n 11600,\n 28955,\n 628,\n 220,\n 220,\n 220,\n 825,\n 11593,\n 260,\n 1050,\n 834,\n 7,\n 944,\n 2599,\n 198,\n 220,\n 220,\n 220,\n 220,\n 220,\n 220,\n 220,\n 37227,\n 1890,\n 4600,\n 4798,\n 63,\n 290,\n 4600,\n 381,\n 22272,\n 63,\n 37811,\n 198,\n 220,\n 220,\n 220,\n 220,\n 220,\n 220,\n 220,\n 1441,\n 2116,\n 13,\n 1462,\n 62,\n 2536,\n 3419,\n 628,\n 220,\n 220,\n 220,\n 825,\n 11593,\n 27363,\n 834,\n 7,\n 944,\n 11,\n 584,\n 2599,\n 198,\n 220,\n 220,\n 220,\n 220,\n 220,\n 220,\n 220,\n 37227,\n 35561,\n 2081,\n 611,\n 1111,\n 5563,\n 389,\n 4961,\n 37811,\n 198,\n 220,\n 220,\n 220,\n 220,\n 220,\n 220,\n 220,\n 611,\n 407,\n 318,\n 39098,\n 7,\n 847,\n 11,\n 1395,\n 4029,\n 7449,\n 2599,\n 198,\n 220,\n 220,\n 220,\n 220,\n 220,\n 220,\n 220,\n 220,\n 220,\n 220,\n 220,\n 1441,\n 10352,\n 628,\n 220,\n 220,\n 220,\n 220,\n 220,\n 220,\n 220,\n 611,\n 407,\n 900,\n 7,\n 944,\n 13557,\n 7890,\n 62,\n 8095,\n 13,\n 13083,\n 28955,\n 6624,\n 900,\n 7,\n 847,\n 13557,\n 7890,\n 62,\n 8095,\n 13,\n 13083,\n 3419,\n 2599,\n 198,\n 220,\n 220,\n 220,\n 220,\n 220,\n 220,\n 220,\n 220,\n 220,\n 220,\n 220,\n 1441,\n 10352,\n 198,\n 220,\n 220,\n 220,\n 220,\n 220,\n 220,\n 220,\n 329,\n 4808,\n 7785,\n 62,\n 3672,\n 11,\n 428,\n 62,\n 2100,\n 287,\n 2237,\n 13,\n 2676,\n 23814,\n 7,\n 944,\n 13557,\n 7890,\n 62,\n 8095,\n 2599,\n 198,\n 220,\n 220,\n 220,\n 220,\n 220,\n 220,\n 220,\n 220,\n 220,\n 220,\n 220,\n 326,\n 62,\n 2100,\n 796,\n 584,\n 13557,\n 7890,\n 62,\n 8095,\n 29795,\n 7785,\n 62,\n 3672,\n 60,\n 198,\n 220,\n 220,\n 220,\n 220,\n 220,\n 220,\n 220,\n 220,\n 220,\n 220,\n 220,\n 3858,\n 796,\n 900,\n 3419,\n 198,\n 220,\n 220,\n 220,\n 220,\n 220,\n 220,\n 220,\n 220,\n 220,\n 220,\n 220,\n 3858,\n 13,\n 2860,\n 7,\n 5661,\n 62,\n 2100,\n 13,\n 834,\n 4871,\n 834,\n 8,\n 198,\n 220,\n 220,\n 220,\n 220,\n 220,\n 220,\n 220,\n 220,\n 220,\n 220,\n 220,\n 3858,\n 13,\n 2860,\n 7,\n 5562,\n 62,\n 2100,\n 13,\n 834,\n 4871,\n 834,\n 8,\n 198,\n 220,\n 220,\n 220,\n 220,\n 220,\n 220,\n 220,\n 220,\n 220,\n 220,\n 220,\n 410,\n 874,\n 62,\n 40496,\n 796,\n 428,\n 62,\n 2100,\n 6624,\n 326,\n 62,\n 2100,\n 198,\n 220,\n 220,\n 220,\n 220,\n 220,\n 220,\n 220,\n 220,\n 220,\n 220,\n 220,\n 611,\n 357,\n 1662,\n 2237,\n 13,\n 47,\n 56,\n 18,\n 290,\n 198,\n 220,\n 220,\n 220,\n 220,\n 220,\n 220,\n 220,\n 220,\n 220,\n 220,\n 220,\n 220,\n 220,\n 220,\n 220,\n 220,\n 220,\n 220,\n 220,\n 18896,\n 7,\n 19199,\n 8,\n 6624,\n 362,\n 290,\n 28000,\n 1098,\n 287,\n 3858,\n 2599,\n 220,\n 1303,\n 645,\n 20402,\n 25,\n 376,\n 23,\n 2481,\n 198,\n 220,\n 220,\n 220,\n 220,\n 220,\n 220,\n 220,\n 220,\n 220,\n 220,\n 220,\n 220,\n 220,\n 220,\n 220,\n 410,\n 874,\n 62,\n 40496,\n 796,\n 357,\n 198,\n 220,\n 220,\n 220,\n 220,\n 220,\n 220,\n 220,\n 220,\n 220,\n 220,\n 220,\n 220,\n 220,\n 220,\n 220,\n 220,\n 220,\n 220,\n 220,\n 428,\n 62,\n 2100,\n 13,\n 268,\n 8189,\n 10786,\n 40477,\n 12,\n 23,\n 11537,\n 6624,\n 326,\n 62,\n 2100,\n 13,\n 268,\n 8189,\n 10786,\n 40477,\n 12,\n 23,\n 11537,\n 198,\n 220,\n 220,\n 220,\n 220,\n 220,\n 220,\n 220,\n 220,\n 220,\n 220,\n 220,\n 220,\n 220,\n 220,\n 220,\n 1267,\n 198,\n 220,\n 220,\n 220,\n 220,\n 220,\n 220,\n 220,\n 220,\n 220,\n 220,\n 220,\n 611,\n 407,\n 410,\n 874,\n 62,\n 40496,\n 25,\n 198,\n 220,\n 220,\n 220,\n 220,\n 220,\n 220,\n 220,\n 220,\n 220,\n 220,\n 220,\n 220,\n 220,\n 220,\n 220,\n 1441,\n 10352,\n 198,\n 220,\n 220,\n 220,\n 220,\n 220,\n 220,\n 220,\n 1441,\n 6407,\n 628,\n 220,\n 220,\n 220,\n 825,\n 11593,\n 710,\n 834,\n 7,\n 944,\n 11,\n 584,\n 2599,\n 198,\n 220,\n 220,\n 220,\n 220,\n 220,\n 220,\n 220,\n 37227,\n 35561,\n 2081,\n 611,\n 1111,\n 5563,\n 389,\n 407,\n 4961,\n 37811,\n 198,\n 220,\n 220,\n 220,\n 220,\n 220,\n 220,\n 220,\n 1441,\n 407,\n 2116,\n 6624,\n 584,\n 198\n]"},"ratio_char_token":{"kind":"number","value":2.2418569824035943,"string":"2.241857"},"token_count":{"kind":"number","value":10684,"string":"10,684"}}},{"rowIdx":1297,"cells":{"content":{"kind":"string","value":"\"\"\"\nDie Modelle für Projektweite Daten: Nutzer/Profile\n\n\"\"\"\n\nfrom django.db import models\nfrom django.contrib.auth.models import AbstractUser\nfrom django.conf import settings\nfrom django.utils.translation import ugettext as _\nfrom userena.models import UserenaBaseProfile\nfrom django.core.validators import RegexValidator\nimport random, string\nfrom django.template.defaultfilters import slugify\nfrom django.urls import reverse\n\n\n\ndef knoepfe_kopf(user):\n \"\"\" gibt Knöpfe für Kopfleiste als Liste von Tupeln zurück \"\"\"\n anmelden = (reverse('userena_signin'), 'Anmelden')\n registrieren = (reverse('userena_signup'), 'Registrieren') \n abmelden = (reverse('userena_signout'), 'Abmelden')\n profil = lambda nutzer: (reverse('userena_profile_detail', \n kwargs={'username': nutzer.username}), 'Profil') \n spam = ('spam', 'spam') \n admin = ('/admin/', 'admin')\n \n if user.username == 'admin':\n liste = [abmelden, profil(user), spam] \n elif user.is_authenticated():\n liste = [abmelden, profil(user)]\n else:\n liste = [anmelden, registrieren]\n if user.is_staff and user.get_all_permissions():\n liste.append(admin)\n \n return liste\n\ndef knoepfe_menü(user):\n \"\"\" gibt Knöpfe für Menüleiste als Liste von Tupeln zurück \"\"\"\n alle = {\n 'index': ('/', 'Startseite'), \n 'olymp': (reverse('Wettbewerbe:index'), 'Wettbewerbe'), \n 'ehemalige': (reverse('Ehemalige:index'), 'Ehemalige'),\n 'impressum': (reverse('impressum'), 'Impressum'),\n 'db': ('https://olymp.piokg.de/static/db.pdf', 'Datenbanklayout'), # quick and very dirty :)\n 'todo': ('/todo/', 'ToDo-Liste'),\n }\n \n if user.username == 'admin':\n return [alle[name] for name in ('index', 'olymp', 'ehemalige', 'todo', 'db')]\n else:\n return [alle[name] for name in ('index', 'olymp', 'db', 'impressum')]\n \n\nclass Nutzer(AbstractUser):\n \"\"\" Nutzer-Klasse \"\"\"\n def knoepfe_kopf(nutzer):\n \"\"\" soll Liste von Paaren für Knöpfe der Kopfleiste ausgeben \n Nutzt im Moment die module-fkt gleichen Namens, könnte später vll\n die Gruppenzugehörigkeit heranziehen, etc, ist flexibel \"\"\"\n return knoepfe_kopf(nutzer)\n\n def knoepfe_menü(self):\n \"\"\" soll Liste von Paaren für Knöpfe der Menüleiste ausgeben \n Nutzt im Moment die module-fkt gleichen Namens, könnte später vll\n die Gruppenzugehörigkeit heranziehen, etc, ist flexibel \"\"\"\n return knoepfe_menü(self)\n \n \n"},"input_ids":{"kind":"list like","value":[37811,198,32423,9104,293,277,25151,1041,73,988,83,732,578,16092,268,25,11959,9107,14,37046,198,198,37811,198,198,6738,42625,14208,13,9945,1330,4981,198,6738,42625,14208,13,3642,822,13,18439,13,27530,1330,27741,12982,198,6738,42625,14208,13,10414,1330,6460,198,6738,42625,14208,13,26791,13,41519,1330,334,1136,5239,355,4808,198,6738,779,918,64,13,27530,1330,5765,918,64,14881,37046,198,6738,42625,14208,13,7295,13,12102,2024,1330,797,25636,47139,1352,198,11748,4738,11,4731,198,6738,42625,14208,13,28243,13,12286,10379,1010,1330,31065,1958,198,6738,42625,14208,13,6371,82,1330,9575,628,198,198,4299,638,78,538,5036,62,74,404,69,7,7220,2599,198,220,220,220,37227,46795,83,6102,9101,79,5036,277,25151,40500,27919,40833,435,82,7343,68,18042,49595,45542,1976,333,9116,694,37227,198,220,220,220,281,1326,335,268,796,357,50188,10786,1904,918,64,62,12683,259,33809,705,2025,1326,335,268,11537,198,220,220,220,4214,380,14226,796,357,50188,10786,1904,918,64,62,12683,929,33809,705,8081,396,380,14226,11537,220,198,220,220,220,450,1326,335,268,796,357,50188,10786,1904,918,64,62,12683,448,33809,705,4826,1326,335,268,11537,198,220,220,220,1534,346,796,37456,6701,9107,25,357,50188,10786,1904,918,64,62,13317,62,49170,3256,220,198,220,220,220,220,220,220,220,220,220,220,220,220,220,220,220,220,220,220,220,479,86,22046,34758,6,29460,10354,6701,9107,13,29460,92,828,705,2964,10379,11537,220,198,220,220,220,18084,796,19203,2777,321,3256,705,2777,321,11537,220,198,220,220,220,13169,796,19203,14,28482,14,3256,705,28482,11537,198,220,220,220,220,198,220,220,220,611,2836,13,29460,6624,705,28482,10354,198,220,220,220,220,220,220,220,1351,68,796,685,397,1326,335,268,11,1534,346,7,7220,828,18084,60,220,220,220,220,220,220,220,220,198,220,220,220,1288,361,2836,13,271,62,41299,3474,33529,198,220,220,220,220,220,220,220,1351,68,796,685,397,1326,335,268,11,1534,346,7,7220,15437,198,220,220,220,2073,25,198,220,220,220,220,220,220,220,1351,68,796,685,272,1326,335,268,11,4214,380,14226,60,198,220,220,220,611,2836,13,271,62,28120,290,2836,13,1136,62,439,62,525,8481,33529,198,220,220,220,220,220,220,220,1351,68,13,33295,7,28482,8,198,220,220,220,220,198,220,220,220,1441,1351,68,198,198,4299,638,78,538,5036,62,3653,9116,7,7220,2599,198,220,220,220,37227,46795,83,6102,9101,79,5036,277,25151,6065,9116,293,40833,435,82,7343,68,18042,49595,45542,1976,333,9116,694,37227,198,220,220,220,28654,796,1391,198,220,220,220,220,220,220,220,705,9630,10354,19203,14,3256,705,10434,325,578,33809,220,198,220,220,220,220,220,220,220,705,3366,3149,10354,357,50188,10786,54,3087,65,413,263,1350,25,9630,33809,705,54,3087,65,413,263,1350,33809,220,198,220,220,220,220,220,220,220,705,68,4411,282,10045,10354,357,50188,10786,36,4411,282,10045,25,9630,33809,705,36,4411,282,10045,33809,198,220,220,220,220,220,220,220,705,320,8439,388,10354,357,50188,10786,320,8439,388,33809,705,26950,601,388,33809,198,220,220,220,220,220,220,220,705,9945,10354,19203,5450,1378,3366,3149,13,14415,482,70,13,2934,14,12708,14,9945,13,12315,3256,705,27354,268,17796,39786,33809,1303,2068,290,845,11841,14373,198,220,220,220,220,220,220,220,705,83,24313,10354,19203,14,83,24313,14,3256,705,2514,5211,12,8053,68,33809,198,220,220,220,1782,198,220,220,220,220,198,220,220,220,611,2836,13,29460,6624,705,28482,10354,198,220,220,220,220,220,220,220,1441,685,6765,58,3672,60,329,1438,287,19203,9630,3256,705,3366,3149,3256,705,68,4411,282,10045,3256,705,83,24313,3256,705,9945,11537,60,198,220,220,220,2073,25,198,220,220,220,220,220,220,220,1441,685,6765,58,3672,60,329,1438,287,19203,9630,3256,705,3366,3149,3256,705,9945,3256,705,320,8439,388,11537,60,198,220,220,220,220,220,220,220,220,198,198,4871,11959,9107,7,23839,12982,2599,198,220,220,220,37227,11959,9107,12,42,75,21612,37227,198,220,220,220,825,638,78,538,5036,62,74,404,69,7,14930,9107,2599,198,220,220,220,220,220,220,220,37227,523,297,7343,68,18042,11243,5757,277,25151,6102,9101,79,5036,4587,40500,27919,40833,257,385,469,11722,220,198,220,220,220,220,220,220,220,11959,89,83,545,29278,4656,8265,12,69,21841,26852,41437,17871,641,11,479,48863,429,68,599,11033,353,410,297,198,220,220,220,220,220,220,220,4656,25665,381,19471,2217,71,9101,4359,365,270,607,35410,494,831,11,3503,11,318,83,7059,43837,37227,198,220,220,220,220,220,220,220,1441,638,78,538,5036,62,74,404,69,7,14930,9107,8,628,220,220,220,825,638,78,538,5036,62,3653,9116,7,944,2599,198,220,220,220,220,220,220,220,37227,523,297,7343,68,18042,11243,5757,277,25151,6102,9101,79,5036,4587,6065,9116,293,40833,257,385,469,11722,220,198,220,220,220,220,220,220,220,11959,89,83,545,29278,4656,8265,12,69,21841,26852,41437,17871,641,11,479,48863,429,68,599,11033,353,410,297,198,220,220,220,220,220,220,220,4656,25665,381,19471,2217,71,9101,4359,365,270,607,35410,494,831,11,3503,11,318,83,7059,43837,37227,198,220,220,220,220,220,220,220,1441,638,78,538,5036,62,3653,9116,7,944,8,198,220,220,220,220,198,220,220,220,220,198],"string":"[\n 37811,\n 198,\n 32423,\n 9104,\n 293,\n 277,\n 25151,\n 1041,\n 73,\n 988,\n 83,\n 732,\n 578,\n 16092,\n 268,\n 25,\n 11959,\n 9107,\n 14,\n 37046,\n 198,\n 198,\n 37811,\n 198,\n 198,\n 6738,\n 42625,\n 14208,\n 13,\n 9945,\n 1330,\n 4981,\n 198,\n 6738,\n 42625,\n 14208,\n 13,\n 3642,\n 822,\n 13,\n 18439,\n 13,\n 27530,\n 1330,\n 27741,\n 12982,\n 198,\n 6738,\n 42625,\n 14208,\n 13,\n 10414,\n 1330,\n 6460,\n 198,\n 6738,\n 42625,\n 14208,\n 13,\n 26791,\n 13,\n 41519,\n 1330,\n 334,\n 1136,\n 5239,\n 355,\n 4808,\n 198,\n 6738,\n 779,\n 918,\n 64,\n 13,\n 27530,\n 1330,\n 5765,\n 918,\n 64,\n 14881,\n 37046,\n 198,\n 6738,\n 42625,\n 14208,\n 13,\n 7295,\n 13,\n 12102,\n 2024,\n 1330,\n 797,\n 25636,\n 47139,\n 1352,\n 198,\n 11748,\n 4738,\n 11,\n 4731,\n 198,\n 6738,\n 42625,\n 14208,\n 13,\n 28243,\n 13,\n 12286,\n 10379,\n 1010,\n 1330,\n 31065,\n 1958,\n 198,\n 6738,\n 42625,\n 14208,\n 13,\n 6371,\n 82,\n 1330,\n 9575,\n 628,\n 198,\n 198,\n 4299,\n 638,\n 78,\n 538,\n 5036,\n 62,\n 74,\n 404,\n 69,\n 7,\n 7220,\n 2599,\n 198,\n 220,\n 220,\n 220,\n 37227,\n 46795,\n 83,\n 6102,\n 9101,\n 79,\n 5036,\n 277,\n 25151,\n 40500,\n 27919,\n 40833,\n 435,\n 82,\n 7343,\n 68,\n 18042,\n 49595,\n 45542,\n 1976,\n 333,\n 9116,\n 694,\n 37227,\n 198,\n 220,\n 220,\n 220,\n 281,\n 1326,\n 335,\n 268,\n 796,\n 357,\n 50188,\n 10786,\n 1904,\n 918,\n 64,\n 62,\n 12683,\n 259,\n 33809,\n 705,\n 2025,\n 1326,\n 335,\n 268,\n 11537,\n 198,\n 220,\n 220,\n 220,\n 4214,\n 380,\n 14226,\n 796,\n 357,\n 50188,\n 10786,\n 1904,\n 918,\n 64,\n 62,\n 12683,\n 929,\n 33809,\n 705,\n 8081,\n 396,\n 380,\n 14226,\n 11537,\n 220,\n 198,\n 220,\n 220,\n 220,\n 450,\n 1326,\n 335,\n 268,\n 796,\n 357,\n 50188,\n 10786,\n 1904,\n 918,\n 64,\n 62,\n 12683,\n 448,\n 33809,\n 705,\n 4826,\n 1326,\n 335,\n 268,\n 11537,\n 198,\n 220,\n 220,\n 220,\n 1534,\n 346,\n 796,\n 37456,\n 6701,\n 9107,\n 25,\n 357,\n 50188,\n 10786,\n 1904,\n 918,\n 64,\n 62,\n 13317,\n 62,\n 49170,\n 3256,\n 220,\n 198,\n 220,\n 220,\n 220,\n 220,\n 220,\n 220,\n 220,\n 220,\n 220,\n 220,\n 220,\n 220,\n 220,\n 220,\n 220,\n 220,\n 220,\n 220,\n 220,\n 479,\n 86,\n 22046,\n 34758,\n 6,\n 29460,\n 10354,\n 6701,\n 9107,\n 13,\n 29460,\n 92,\n 828,\n 705,\n 2964,\n 10379,\n 11537,\n 220,\n 198,\n 220,\n 220,\n 220,\n 18084,\n 796,\n 19203,\n 2777,\n 321,\n 3256,\n 705,\n 2777,\n 321,\n 11537,\n 220,\n 198,\n 220,\n 220,\n 220,\n 13169,\n 796,\n 19203,\n 14,\n 28482,\n 14,\n 3256,\n 705,\n 28482,\n 11537,\n 198,\n 220,\n 220,\n 220,\n 220,\n 198,\n 220,\n 220,\n 220,\n 611,\n 2836,\n 13,\n 29460,\n 6624,\n 705,\n 28482,\n 10354,\n 198,\n 220,\n 220,\n 220,\n 220,\n 220,\n 220,\n 220,\n 1351,\n 68,\n 796,\n 685,\n 397,\n 1326,\n 335,\n 268,\n 11,\n 1534,\n 346,\n 7,\n 7220,\n 828,\n 18084,\n 60,\n 220,\n 220,\n 220,\n 220,\n 220,\n 220,\n 220,\n 220,\n 198,\n 220,\n 220,\n 220,\n 1288,\n 361,\n 2836,\n 13,\n 271,\n 62,\n 41299,\n 3474,\n 33529,\n 198,\n 220,\n 220,\n 220,\n 220,\n 220,\n 220,\n 220,\n 1351,\n 68,\n 796,\n 685,\n 397,\n 1326,\n 335,\n 268,\n 11,\n 1534,\n 346,\n 7,\n 7220,\n 15437,\n 198,\n 220,\n 220,\n 220,\n 2073,\n 25,\n 198,\n 220,\n 220,\n 220,\n 220,\n 220,\n 220,\n 220,\n 1351,\n 68,\n 796,\n 685,\n 272,\n 1326,\n 335,\n 268,\n 11,\n 4214,\n 380,\n 14226,\n 60,\n 198,\n 220,\n 220,\n 220,\n 611,\n 2836,\n 13,\n 271,\n 62,\n 28120,\n 290,\n 2836,\n 13,\n 1136,\n 62,\n 439,\n 62,\n 525,\n 8481,\n 33529,\n 198,\n 220,\n 220,\n 220,\n 220,\n 220,\n 220,\n 220,\n 1351,\n 68,\n 13,\n 33295,\n 7,\n 28482,\n 8,\n 198,\n 220,\n 220,\n 220,\n 220,\n 198,\n 220,\n 220,\n 220,\n 1441,\n 1351,\n 68,\n 198,\n 198,\n 4299,\n 638,\n 78,\n 538,\n 5036,\n 62,\n 3653,\n 9116,\n 7,\n 7220,\n 2599,\n 198,\n 220,\n 220,\n 220,\n 37227,\n 46795,\n 83,\n 6102,\n 9101,\n 79,\n 5036,\n 277,\n 25151,\n 6065,\n 9116,\n 293,\n 40833,\n 435,\n 82,\n 7343,\n 68,\n 18042,\n 49595,\n 45542,\n 1976,\n 333,\n 9116,\n 694,\n 37227,\n 198,\n 220,\n 220,\n 220,\n 28654,\n 796,\n 1391,\n 198,\n 220,\n 220,\n 220,\n 220,\n 220,\n 220,\n 220,\n 705,\n 9630,\n 10354,\n 19203,\n 14,\n 3256,\n 705,\n 10434,\n 325,\n 578,\n 33809,\n 220,\n 198,\n 220,\n 220,\n 220,\n 220,\n 220,\n 220,\n 220,\n 705,\n 3366,\n 3149,\n 10354,\n 357,\n 50188,\n 10786,\n 54,\n 3087,\n 65,\n 413,\n 263,\n 1350,\n 25,\n 9630,\n 33809,\n 705,\n 54,\n 3087,\n 65,\n 413,\n 263,\n 1350,\n 33809,\n 220,\n 198,\n 220,\n 220,\n 220,\n 220,\n 220,\n 220,\n 220,\n 705,\n 68,\n 4411,\n 282,\n 10045,\n 10354,\n 357,\n 50188,\n 10786,\n 36,\n 4411,\n 282,\n 10045,\n 25,\n 9630,\n 33809,\n 705,\n 36,\n 4411,\n 282,\n 10045,\n 33809,\n 198,\n 220,\n 220,\n 220,\n 220,\n 220,\n 220,\n 220,\n 705,\n 320,\n 8439,\n 388,\n 10354,\n 357,\n 50188,\n 10786,\n 320,\n 8439,\n 388,\n 33809,\n 705,\n 26950,\n 601,\n 388,\n 33809,\n 198,\n 220,\n 220,\n 220,\n 220,\n 220,\n 220,\n 220,\n 705,\n 9945,\n 10354,\n 19203,\n 5450,\n 1378,\n 3366,\n 3149,\n 13,\n 14415,\n 482,\n 70,\n 13,\n 2934,\n 14,\n 12708,\n 14,\n 9945,\n 13,\n 12315,\n 3256,\n 705,\n 27354,\n 268,\n 17796,\n 39786,\n 33809,\n 1303,\n 2068,\n 290,\n 845,\n 11841,\n 14373,\n 198,\n 220,\n 220,\n 220,\n 220,\n 220,\n 220,\n 220,\n 705,\n 83,\n 24313,\n 10354,\n 19203,\n 14,\n 83,\n 24313,\n 14,\n 3256,\n 705,\n 2514,\n 5211,\n 12,\n 8053,\n 68,\n 33809,\n 198,\n 220,\n 220,\n 220,\n 1782,\n 198,\n 220,\n 220,\n 220,\n 220,\n 198,\n 220,\n 220,\n 220,\n 611,\n 2836,\n 13,\n 29460,\n 6624,\n 705,\n 28482,\n 10354,\n 198,\n 220,\n 220,\n 220,\n 220,\n 220,\n 220,\n 220,\n 1441,\n 685,\n 6765,\n 58,\n 3672,\n 60,\n 329,\n 1438,\n 287,\n 19203,\n 9630,\n 3256,\n 705,\n 3366,\n 3149,\n 3256,\n 705,\n 68,\n 4411,\n 282,\n 10045,\n 3256,\n 705,\n 83,\n 24313,\n 3256,\n 705,\n 9945,\n 11537,\n 60,\n 198,\n 220,\n 220,\n 220,\n 2073,\n 25,\n 198,\n 220,\n 220,\n 220,\n 220,\n 220,\n 220,\n 220,\n 1441,\n 685,\n 6765,\n 58,\n 3672,\n 60,\n 329,\n 1438,\n 287,\n 19203,\n 9630,\n 3256,\n 705,\n 3366,\n 3149,\n 3256,\n 705,\n 9945,\n 3256,\n 705,\n 320,\n 8439,\n 388,\n 11537,\n 60,\n 198,\n 220,\n 220,\n 220,\n 220,\n 220,\n 220,\n 220,\n 220,\n 198,\n 198,\n 4871,\n 11959,\n 9107,\n 7,\n 23839,\n 12982,\n 2599,\n 198,\n 220,\n 220,\n 220,\n 37227,\n 11959,\n 9107,\n 12,\n 42,\n 75,\n 21612,\n 37227,\n 198,\n 220,\n 220,\n 220,\n 825,\n 638,\n 78,\n 538,\n 5036,\n 62,\n 74,\n 404,\n 69,\n 7,\n 14930,\n 9107,\n 2599,\n 198,\n 220,\n 220,\n 220,\n 220,\n 220,\n 220,\n 220,\n 37227,\n 523,\n 297,\n 7343,\n 68,\n 18042,\n 11243,\n 5757,\n 277,\n 25151,\n 6102,\n 9101,\n 79,\n 5036,\n 4587,\n 40500,\n 27919,\n 40833,\n 257,\n 385,\n 469,\n 11722,\n 220,\n 198,\n 220,\n 220,\n 220,\n 220,\n 220,\n 220,\n 220,\n 11959,\n 89,\n 83,\n 545,\n 29278,\n 4656,\n 8265,\n 12,\n 69,\n 21841,\n 26852,\n 41437,\n 17871,\n 641,\n 11,\n 479,\n 48863,\n 429,\n 68,\n 599,\n 11033,\n 353,\n 410,\n 297,\n 198,\n 220,\n 220,\n 220,\n 220,\n 220,\n 220,\n 220,\n 4656,\n 25665,\n 381,\n 19471,\n 2217,\n 71,\n 9101,\n 4359,\n 365,\n 270,\n 607,\n 35410,\n 494,\n 831,\n 11,\n 3503,\n 11,\n 318,\n 83,\n 7059,\n 43837,\n 37227,\n 198,\n 220,\n 220,\n 220,\n 220,\n 220,\n 220,\n 220,\n 1441,\n 638,\n 78,\n 538,\n 5036,\n 62,\n 74,\n 404,\n 69,\n 7,\n 14930,\n 9107,\n 8,\n 628,\n 220,\n 220,\n 220,\n 825,\n 638,\n 78,\n 538,\n 5036,\n 62,\n 3653,\n 9116,\n 7,\n 944,\n 2599,\n 198,\n 220,\n 220,\n 220,\n 220,\n 220,\n 220,\n 220,\n 37227,\n 523,\n 297,\n 7343,\n 68,\n 18042,\n 11243,\n 5757,\n 277,\n 25151,\n 6102,\n 9101,\n 79,\n 5036,\n 4587,\n 6065,\n 9116,\n 293,\n 40833,\n 257,\n 385,\n 469,\n 11722,\n 220,\n 198,\n 220,\n 220,\n 220,\n 220,\n 220,\n 220,\n 220,\n 11959,\n 89,\n 83,\n 545,\n 29278,\n 4656,\n 8265,\n 12,\n 69,\n 21841,\n 26852,\n 41437,\n 17871,\n 641,\n 11,\n 479,\n 48863,\n 429,\n 68,\n 599,\n 11033,\n 353,\n 410,\n 297,\n 198,\n 220,\n 220,\n 220,\n 220,\n 220,\n 220,\n 220,\n 4656,\n 25665,\n 381,\n 19471,\n 2217,\n 71,\n 9101,\n 4359,\n 365,\n 270,\n 607,\n 35410,\n 494,\n 831,\n 11,\n 3503,\n 11,\n 318,\n 83,\n 7059,\n 43837,\n 37227,\n 198,\n 220,\n 220,\n 220,\n 220,\n 220,\n 220,\n 220,\n 1441,\n 638,\n 78,\n 538,\n 5036,\n 62,\n 3653,\n 9116,\n 7,\n 944,\n 8,\n 198,\n 220,\n 220,\n 220,\n 220,\n 198,\n 220,\n 220,\n 220,\n 220,\n 198\n]"},"ratio_char_token":{"kind":"number","value":2.281981981981982,"string":"2.281982"},"token_count":{"kind":"number","value":1110,"string":"1,110"}}},{"rowIdx":1298,"cells":{"content":{"kind":"string","value":"import numpy as np\nimport cv2\nimport sys\nimport torch\n\nsys.path.append('..')\n\nfrom torch.utils import data\nfrom torch.utils.data import DataLoader\n\n\n\n\n\n\n\n\n\n\n\n\n\n\nif __name__ == '__main__':\n file_list = './data/test_data/list.txt'\n wlfwdataset = WLFWDatasets(file_list)\n dataloader = DataLoader(wlfwdataset, batch_size=256, shuffle=True, num_workers=0, drop_last=False)\n for img, landmark, attribute, euler_angle in dataloader:\n print(\"img shape\", img.shape)\n print(\"landmark size\", landmark.size())\n print(\"attrbute size\", attribute)\n print(\"euler_angle\", euler_angle.size())\n"},"input_ids":{"kind":"list like","value":[11748,299,32152,355,45941,198,11748,269,85,17,198,11748,25064,198,11748,28034,198,198,17597,13,6978,13,33295,10786,492,11537,198,198,6738,28034,13,26791,1330,1366,198,6738,28034,13,26791,13,7890,1330,6060,17401,628,628,628,628,628,628,628,198,361,11593,3672,834,6624,705,834,12417,834,10354,198,220,220,220,2393,62,4868,796,705,19571,7890,14,9288,62,7890,14,4868,13,14116,6,198,220,220,220,266,1652,16993,265,292,316,796,370,43,37,22332,265,292,1039,7,7753,62,4868,8,198,220,220,220,4818,282,1170,263,796,6060,17401,7,86,1652,16993,265,292,316,11,15458,62,7857,28,11645,11,36273,28,17821,11,997,62,22896,28,15,11,4268,62,12957,28,25101,8,198,220,220,220,329,33705,11,20533,11,11688,11,304,18173,62,9248,287,4818,282,1170,263,25,198,220,220,220,220,220,220,220,3601,7203,9600,5485,1600,33705,13,43358,8,198,220,220,220,220,220,220,220,3601,7203,1044,4102,2546,1600,20533,13,7857,28955,198,220,220,220,220,220,220,220,3601,7203,1078,26145,1133,2546,1600,11688,8,198,220,220,220,220,220,220,220,3601,7203,68,18173,62,9248,1600,304,18173,62,9248,13,7857,28955,198],"string":"[\n 11748,\n 299,\n 32152,\n 355,\n 45941,\n 198,\n 11748,\n 269,\n 85,\n 17,\n 198,\n 11748,\n 25064,\n 198,\n 11748,\n 28034,\n 198,\n 198,\n 17597,\n 13,\n 6978,\n 13,\n 33295,\n 10786,\n 492,\n 11537,\n 198,\n 198,\n 6738,\n 28034,\n 13,\n 26791,\n 1330,\n 1366,\n 198,\n 6738,\n 28034,\n 13,\n 26791,\n 13,\n 7890,\n 1330,\n 6060,\n 17401,\n 628,\n 628,\n 628,\n 628,\n 628,\n 628,\n 628,\n 198,\n 361,\n 11593,\n 3672,\n 834,\n 6624,\n 705,\n 834,\n 12417,\n 834,\n 10354,\n 198,\n 220,\n 220,\n 220,\n 2393,\n 62,\n 4868,\n 796,\n 705,\n 19571,\n 7890,\n 14,\n 9288,\n 62,\n 7890,\n 14,\n 4868,\n 13,\n 14116,\n 6,\n 198,\n 220,\n 220,\n 220,\n 266,\n 1652,\n 16993,\n 265,\n 292,\n 316,\n 796,\n 370,\n 43,\n 37,\n 22332,\n 265,\n 292,\n 1039,\n 7,\n 7753,\n 62,\n 4868,\n 8,\n 198,\n 220,\n 220,\n 220,\n 4818,\n 282,\n 1170,\n 263,\n 796,\n 6060,\n 17401,\n 7,\n 86,\n 1652,\n 16993,\n 265,\n 292,\n 316,\n 11,\n 15458,\n 62,\n 7857,\n 28,\n 11645,\n 11,\n 36273,\n 28,\n 17821,\n 11,\n 997,\n 62,\n 22896,\n 28,\n 15,\n 11,\n 4268,\n 62,\n 12957,\n 28,\n 25101,\n 8,\n 198,\n 220,\n 220,\n 220,\n 329,\n 33705,\n 11,\n 20533,\n 11,\n 11688,\n 11,\n 304,\n 18173,\n 62,\n 9248,\n 287,\n 4818,\n 282,\n 1170,\n 263,\n 25,\n 198,\n 220,\n 220,\n 220,\n 220,\n 220,\n 220,\n 220,\n 3601,\n 7203,\n 9600,\n 5485,\n 1600,\n 33705,\n 13,\n 43358,\n 8,\n 198,\n 220,\n 220,\n 220,\n 220,\n 220,\n 220,\n 220,\n 3601,\n 7203,\n 1044,\n 4102,\n 2546,\n 1600,\n 20533,\n 13,\n 7857,\n 28955,\n 198,\n 220,\n 220,\n 220,\n 220,\n 220,\n 220,\n 220,\n 3601,\n 7203,\n 1078,\n 26145,\n 1133,\n 2546,\n 1600,\n 11688,\n 8,\n 198,\n 220,\n 220,\n 220,\n 220,\n 220,\n 220,\n 220,\n 3601,\n 7203,\n 68,\n 18173,\n 62,\n 9248,\n 1600,\n 304,\n 18173,\n 62,\n 9248,\n 13,\n 7857,\n 28955,\n 198\n]"},"ratio_char_token":{"kind":"number","value":2.541322314049587,"string":"2.541322"},"token_count":{"kind":"number","value":242,"string":"242"}}},{"rowIdx":1299,"cells":{"content":{"kind":"string","value":"import os\n\nimport numpy as np\nimport pytest\nfrom nexusformat.nexus.tree import NXfield, NXgroup, NXroot, nxload\n\n\n\n@pytest.mark.parametrize(\"save\", [\"False\", \"True\"])\n"},"input_ids":{"kind":"list like","value":[11748,28686,198,198,11748,299,32152,355,45941,198,11748,12972,9288,198,6738,45770,18982,13,44520,13,21048,1330,42482,3245,11,42482,8094,11,42482,15763,11,299,87,2220,628,198,198,31,9078,9288,13,4102,13,17143,316,380,2736,7203,21928,1600,14631,25101,1600,366,17821,8973,8,198],"string":"[\n 11748,\n 28686,\n 198,\n 198,\n 11748,\n 299,\n 32152,\n 355,\n 45941,\n 198,\n 11748,\n 12972,\n 9288,\n 198,\n 6738,\n 45770,\n 18982,\n 13,\n 44520,\n 13,\n 21048,\n 1330,\n 42482,\n 3245,\n 11,\n 42482,\n 8094,\n 11,\n 42482,\n 15763,\n 11,\n 299,\n 87,\n 2220,\n 628,\n 198,\n 198,\n 31,\n 9078,\n 9288,\n 13,\n 4102,\n 13,\n 17143,\n 316,\n 380,\n 2736,\n 7203,\n 21928,\n 1600,\n 14631,\n 25101,\n 1600,\n 366,\n 17821,\n 8973,\n 8,\n 198\n]"},"ratio_char_token":{"kind":"number","value":2.8793103448275863,"string":"2.87931"},"token_count":{"kind":"number","value":58,"string":"58"}}}],"truncated":false,"partial":false},"paginationData":{"pageIndex":12,"numItemsPerPage":100,"numTotalItems":12760182,"offset":1200,"length":100}},"jwt":"eyJhbGciOiJFZERTQSJ9.eyJyZWFkIjp0cnVlLCJwZXJtaXNzaW9ucyI6eyJyZXBvLmNvbnRlbnQucmVhZCI6dHJ1ZX0sImlhdCI6MTc1NjI2ODkyMCwic3ViIjoiL2RhdGFzZXRzL3l0emkvdGhlLXN0YWNrLWRlZHVwLXB5dGhvbi1maWx0ZXJlZC1kb2NzdHJpbmdzLWdwdDIiLCJleHAiOjE3NTYyNzI1MjAsImlzcyI6Imh0dHBzOi8vaHVnZ2luZ2ZhY2UuY28ifQ.auOqsRkDzmZbiLuiFCUx8yOmlyw7y-Bjv1gXlQUMNJes7gSEtrIV5pyCxoFRFpp0vDYPuHCyKc52GovLpkarCw","displayUrls":true},"discussionsStats":{"closed":0,"open":1,"total":1},"fullWidth":true,"hasGatedAccess":true,"hasFullAccess":true,"isEmbedded":false,"savedQueries":{"community":[],"user":[]}}">
content
stringlengths
1
1.04M
input_ids
listlengths
1
774k
ratio_char_token
float64
0.38
22.9
token_count
int64
1
774k
import re # Value selectors; aliases, tags, etc. def tag(*tags): """Select a (list of) tag(s).""" vtag = [t for t in tags] return {"tag": vtag} def tag_and(*tag_ands): """Select a (list of) tag_and(s).""" vtag_and = [t for t in tag_ands] return {"tag_and": vtag_and} def tag_not(*tag_nots): """Select a (list of) tag_not(s).""" vtag_not = [t for t in tag_nots] return {"tag_not": vtag_not} def alias(*alias): """Select a (list of) alias(es).""" valias = [t for t in alias] return {"alias": valias} def registration_id(*reg_ids): """Select a (list of) registration_id(s).""" vregistration_id = [t for t in reg_ids] return {"registration_id": vregistration_id} def segment(*segments): """Select a (list of) segment(s).""" vsegment = [t for t in segments] return {"segment": vsegment} def abtest(*abtests): """Select a (list of) abtest(s).""" vabtest = [t for t in abtests] return {"abtest": vabtest}
[ 11748, 302, 198, 198, 2, 11052, 2922, 669, 26, 47217, 11, 15940, 11, 3503, 13, 198, 198, 4299, 7621, 46491, 31499, 2599, 198, 220, 220, 220, 37227, 17563, 257, 357, 4868, 286, 8, 7621, 7, 82, 21387, 15931, 198, 220, 220, 220, 410, 12985, 796, 685, 83, 329, 256, 287, 15940, 60, 198, 220, 220, 220, 1441, 19779, 12985, 1298, 410, 12985, 92, 198, 198, 4299, 7621, 62, 392, 46491, 12985, 62, 1746, 2599, 198, 220, 220, 220, 37227, 17563, 257, 357, 4868, 286, 8, 7621, 62, 392, 7, 82, 21387, 15931, 198, 220, 220, 220, 410, 12985, 62, 392, 796, 685, 83, 329, 256, 287, 7621, 62, 1746, 60, 198, 220, 220, 220, 1441, 19779, 12985, 62, 392, 1298, 410, 12985, 62, 392, 92, 198, 198, 4299, 7621, 62, 1662, 46491, 12985, 62, 1662, 82, 2599, 198, 220, 220, 220, 37227, 17563, 257, 357, 4868, 286, 8, 7621, 62, 1662, 7, 82, 21387, 15931, 198, 220, 220, 220, 410, 12985, 62, 1662, 796, 685, 83, 329, 256, 287, 7621, 62, 1662, 82, 60, 198, 220, 220, 220, 1441, 19779, 12985, 62, 1662, 1298, 410, 12985, 62, 1662, 92, 198, 198, 4299, 16144, 46491, 26011, 2599, 198, 220, 220, 220, 37227, 17563, 257, 357, 4868, 286, 8, 16144, 7, 274, 21387, 15931, 198, 220, 220, 220, 1188, 4448, 796, 685, 83, 329, 256, 287, 16144, 60, 198, 220, 220, 220, 1441, 19779, 26011, 1298, 1188, 4448, 92, 198, 198, 4299, 9352, 62, 312, 46491, 2301, 62, 2340, 2599, 198, 220, 220, 220, 37227, 17563, 257, 357, 4868, 286, 8, 9352, 62, 312, 7, 82, 21387, 15931, 198, 220, 220, 220, 410, 2301, 33397, 62, 312, 796, 685, 83, 329, 256, 287, 842, 62, 2340, 60, 198, 220, 220, 220, 1441, 19779, 2301, 33397, 62, 312, 1298, 410, 2301, 33397, 62, 312, 92, 198, 198, 4299, 10618, 46491, 325, 11726, 2599, 198, 220, 220, 220, 37227, 17563, 257, 357, 4868, 286, 8, 10618, 7, 82, 21387, 15931, 198, 220, 220, 220, 410, 325, 5154, 796, 685, 83, 329, 256, 287, 17894, 60, 198, 220, 220, 220, 1441, 19779, 325, 5154, 1298, 410, 325, 5154, 92, 198, 198, 4299, 450, 9288, 46491, 397, 41989, 2599, 198, 220, 220, 220, 37227, 17563, 257, 357, 4868, 286, 8, 450, 9288, 7, 82, 21387, 15931, 198, 220, 220, 220, 410, 397, 9288, 796, 685, 83, 329, 256, 287, 450, 41989, 60, 198, 220, 220, 220, 1441, 19779, 397, 9288, 1298, 410, 397, 9288, 92, 198 ]
2.414634
410
# -*- coding: utf-8 -*- # Generated by Django 1.10.5 on 2018-07-30 14:11 from __future__ import unicode_literals from django.db import migrations, models
[ 2, 532, 9, 12, 19617, 25, 3384, 69, 12, 23, 532, 9, 12, 198, 2, 2980, 515, 416, 37770, 352, 13, 940, 13, 20, 319, 2864, 12, 2998, 12, 1270, 1478, 25, 1157, 198, 6738, 11593, 37443, 834, 1330, 28000, 1098, 62, 17201, 874, 198, 198, 6738, 42625, 14208, 13, 9945, 1330, 15720, 602, 11, 4981, 628 ]
2.736842
57
num_vezes = 0 soma_total = 0 maior_numero = None menor_numero = None while True: num = input("Digite um número ou \"sair\" para encerrar o programa: ") if num == "sair": break try: numero = int(num) num_vezes += 1 soma_total += numero if maior_numero is None or numero > maior_numero: maior_numero = numero if menor_numero is None or numero < menor_numero: menor_numero = numero except: print("Digite apenas números ou a palavra \"sair\", por favor.") if maior_numero == None or menor_numero == None: print("Você não digitou nenhum número. Portanto é impossível calcular o número de vezes, o somatório, o menor e o maior.") print("Obrigado por utilizar o meu programa!") else: print("Números foram digitados " + str(num_vezes) + " vezes.") print("A soma total dos números digitados é " + str(int(soma_total)) + ".") print("O menor número digitado foi o número " + str(int(menor_numero)) + ".") print("O maior número digitado foi o número " + str(int(maior_numero)) + ".") print("Obrigado por utilizar o meu programa!")
[ 22510, 62, 303, 12271, 796, 657, 198, 82, 6086, 62, 23350, 796, 657, 198, 2611, 1504, 62, 22510, 3529, 796, 6045, 198, 3653, 273, 62, 22510, 3529, 796, 6045, 198, 4514, 6407, 25, 198, 220, 220, 220, 997, 796, 5128, 7203, 19511, 578, 23781, 299, 21356, 647, 78, 267, 84, 19990, 82, 958, 7879, 31215, 551, 2189, 20040, 267, 1430, 64, 25, 366, 8, 198, 220, 220, 220, 611, 997, 6624, 366, 82, 958, 1298, 198, 220, 220, 220, 220, 220, 220, 220, 2270, 198, 220, 220, 220, 1949, 25, 198, 220, 220, 220, 220, 220, 220, 220, 997, 3529, 796, 493, 7, 22510, 8, 198, 220, 220, 220, 220, 220, 220, 220, 997, 62, 303, 12271, 15853, 352, 198, 220, 220, 220, 220, 220, 220, 220, 3870, 64, 62, 23350, 15853, 997, 3529, 198, 220, 220, 220, 220, 220, 220, 220, 611, 17266, 1504, 62, 22510, 3529, 318, 6045, 393, 997, 3529, 1875, 17266, 1504, 62, 22510, 3529, 25, 198, 220, 220, 220, 220, 220, 220, 220, 220, 220, 220, 220, 17266, 1504, 62, 22510, 3529, 796, 997, 3529, 198, 220, 220, 220, 220, 220, 220, 220, 611, 1450, 273, 62, 22510, 3529, 318, 6045, 393, 997, 3529, 1279, 1450, 273, 62, 22510, 3529, 25, 198, 220, 220, 220, 220, 220, 220, 220, 220, 220, 220, 220, 1450, 273, 62, 22510, 3529, 796, 997, 3529, 198, 220, 220, 220, 2845, 25, 198, 220, 220, 220, 220, 220, 220, 220, 3601, 7203, 19511, 578, 2471, 268, 292, 299, 21356, 647, 418, 267, 84, 257, 6340, 615, 430, 19990, 82, 958, 34607, 16964, 2661, 19570, 198, 361, 17266, 1504, 62, 22510, 3529, 6624, 6045, 393, 1450, 273, 62, 22510, 3529, 6624, 6045, 25, 198, 220, 220, 220, 3601, 7203, 53, 420, 25792, 299, 28749, 16839, 280, 299, 16550, 388, 299, 21356, 647, 78, 13, 4347, 14723, 38251, 848, 793, 8836, 626, 2386, 10440, 267, 299, 21356, 647, 78, 390, 1569, 12271, 11, 267, 3870, 265, 10205, 27250, 11, 267, 1450, 273, 304, 267, 17266, 1504, 19570, 198, 220, 220, 220, 3601, 7203, 46, 1671, 328, 4533, 16964, 7736, 528, 283, 267, 502, 84, 1430, 64, 2474, 8, 198, 17772, 25, 198, 220, 220, 220, 3601, 7203, 45, 21356, 647, 418, 329, 321, 16839, 22484, 366, 1343, 965, 7, 22510, 62, 303, 12271, 8, 1343, 366, 1569, 12271, 19570, 198, 220, 220, 220, 3601, 7203, 32, 3870, 64, 2472, 23430, 299, 21356, 647, 418, 16839, 22484, 38251, 366, 1343, 965, 7, 600, 7, 82, 6086, 62, 23350, 4008, 1343, 366, 19570, 198, 220, 220, 220, 3601, 7203, 46, 1450, 273, 299, 21356, 647, 78, 16839, 4533, 11511, 72, 267, 299, 21356, 647, 78, 366, 1343, 965, 7, 600, 7, 3653, 273, 62, 22510, 3529, 4008, 1343, 366, 19570, 198, 220, 220, 220, 3601, 7203, 46, 17266, 1504, 299, 21356, 647, 78, 16839, 4533, 11511, 72, 267, 299, 21356, 647, 78, 366, 1343, 965, 7, 600, 7, 2611, 1504, 62, 22510, 3529, 4008, 1343, 366, 19570, 198, 220, 220, 220, 3601, 7203, 46, 1671, 328, 4533, 16964, 7736, 528, 283, 267, 502, 84, 1430, 64, 2474, 8, 198 ]
2.219417
515
from selenium import webdriver import time
[ 6738, 384, 11925, 1505, 1330, 3992, 26230, 198, 11748, 640, 628 ]
4
11
""" Filter classes """ from . import etree from .base import CPIXComparableBase def encode_bool(value): """Encode booleans to produce valid XML""" if value: return "true" return "false" class KeyPeriodFilter(CPIXComparableBase): """ KeyPeriodFilter element Has single required attribute: periodId """ def element(self): """Returns XML element""" el = etree.Element("KeyPeriodFilter") el.set("periodId", str(self.period_id)) return el @staticmethod def parse(xml): """ Parse XML and return KeyPeriodFilter """ if isinstance(xml, (str, bytes)): xml = etree.fromstring(xml) period_id = xml.attrib["periodId"] return KeyPeriodFilter(period_id) class LabelFilter(CPIXComparableBase): """ LabelFilter element Not yet implemented """ class VideoFilter(CPIXComparableBase): """ VideoFilter element Has optional attributes: minPixels maxPixels hdr wcg minFps maxFps """ def element(self): """Returns XML element""" el = etree.Element("VideoFilter") if self.min_pixels is not None: el.set("minPixels", str(self.min_pixels)) if self.max_pixels is not None: el.set("maxPixels", str(self.max_pixels)) if self.hdr is not None: el.set("hdr", encode_bool(self.hdr)) if self.wcg is not None: el.set("wcg", encode_bool(self.wcg)) if self.min_fps is not None: el.set("minFps", str(self.min_fps)) if self.max_fps is not None: el.set("maxFps", str(self.max_fps)) return el @staticmethod def parse(xml): """ Parse XML and return VideoFilter """ if isinstance(xml, (str, bytes)): xml = etree.fromstring(xml) min_pixels = None max_pixels = None hdr = None wcg = None min_fps = None max_fps = None if "minPixels" in xml.attrib: min_pixels = xml.attrib["minPixels"] if "maxPixels" in xml.attrib: max_pixels = xml.attrib["maxPixels"] if "hdr" in xml.attrib: hdr = xml.attrib["hdr"] if "wcg" in xml.attrib: wcg = xml.attrib["wcg"] if "minFps" in xml.attrib: min_fps = xml.attrib["minFps"] if "maxFps" in xml.attrib: max_fps = xml.attrib["maxFps"] return VideoFilter(min_pixels, max_pixels, hdr, wcg, min_fps, max_fps) class AudioFilter(CPIXComparableBase): """ AudioFilter element Has optional attributes: minChannels maxChannels """ def element(self): """Returns XML element""" el = etree.Element("AudioFilter") if self.min_channels: el.set("minChannels", str(self.min_channels)) if self.max_channels: el.set("maxChannels", str(self.max_channels)) return el @staticmethod def parse(xml): """ Parse XML and return AudioFilter """ if isinstance(xml, (str, bytes)): xml = etree.fromstring(xml) min_channels = None max_channels = None if "minChannels" in xml.attrib: min_channels = xml.attrib["minChannels"] if "maxChannels" in xml.attrib: max_channels = xml.attrib["maxChannels"] return AudioFilter(min_channels, max_channels) class BitrateFilter(CPIXComparableBase): """ BitrateFilter element Has optional attributes: minBitrate maxBitrate """ def element(self): """Returns XML element""" el = etree.Element("BitrateFilter") if self.min_bitrate: el.set("minBitrate", str(self.min_bitrate)) if self.max_bitrate: el.set("maxBitrate", str(self.max_bitrate)) return el @staticmethod def parse(xml): """ Parse XML and return BitrateFilter """ if isinstance(xml, (str, bytes)): xml = etree.fromstring(xml) min_bitrate = None max_bitrate = None if "minBitrate" in xml.attrib: min_bitrate = xml.attrib["minBitrate"] if "maxBitrate" in xml.attrib: max_bitrate = xml.attrib["maxBitrate"] return BitrateFilter(min_bitrate, max_bitrate)
[ 37811, 198, 22417, 6097, 198, 37811, 198, 6738, 764, 1330, 2123, 631, 198, 6738, 764, 8692, 1330, 16932, 10426, 5377, 37064, 14881, 628, 198, 4299, 37773, 62, 30388, 7, 8367, 2599, 198, 220, 220, 220, 37227, 4834, 8189, 1489, 2305, 504, 284, 4439, 4938, 23735, 37811, 198, 220, 220, 220, 611, 1988, 25, 198, 220, 220, 220, 220, 220, 220, 220, 1441, 366, 7942, 1, 198, 220, 220, 220, 1441, 366, 9562, 1, 628, 198, 4871, 7383, 5990, 2101, 22417, 7, 8697, 10426, 5377, 37064, 14881, 2599, 198, 220, 220, 220, 37227, 198, 220, 220, 220, 7383, 5990, 2101, 22417, 5002, 198, 220, 220, 220, 7875, 2060, 2672, 11688, 25, 198, 220, 220, 220, 220, 220, 220, 220, 2278, 7390, 198, 220, 220, 220, 37227, 628, 220, 220, 220, 825, 5002, 7, 944, 2599, 198, 220, 220, 220, 220, 220, 220, 220, 37227, 35561, 23735, 5002, 37811, 198, 220, 220, 220, 220, 220, 220, 220, 1288, 796, 2123, 631, 13, 20180, 7203, 9218, 5990, 2101, 22417, 4943, 198, 220, 220, 220, 220, 220, 220, 220, 1288, 13, 2617, 7203, 41007, 7390, 1600, 965, 7, 944, 13, 41007, 62, 312, 4008, 198, 220, 220, 220, 220, 220, 220, 220, 1441, 1288, 628, 220, 220, 220, 2488, 12708, 24396, 198, 220, 220, 220, 825, 21136, 7, 19875, 2599, 198, 220, 220, 220, 220, 220, 220, 220, 37227, 198, 220, 220, 220, 220, 220, 220, 220, 2547, 325, 23735, 290, 1441, 7383, 5990, 2101, 22417, 198, 220, 220, 220, 220, 220, 220, 220, 37227, 198, 220, 220, 220, 220, 220, 220, 220, 611, 318, 39098, 7, 19875, 11, 357, 2536, 11, 9881, 8, 2599, 198, 220, 220, 220, 220, 220, 220, 220, 220, 220, 220, 220, 35555, 796, 2123, 631, 13, 6738, 8841, 7, 19875, 8, 628, 220, 220, 220, 220, 220, 220, 220, 2278, 62, 312, 796, 35555, 13, 1078, 822, 14692, 41007, 7390, 8973, 628, 220, 220, 220, 220, 220, 220, 220, 1441, 7383, 5990, 2101, 22417, 7, 41007, 62, 312, 8, 628, 198, 4871, 36052, 22417, 7, 8697, 10426, 5377, 37064, 14881, 2599, 198, 220, 220, 220, 37227, 198, 220, 220, 220, 36052, 22417, 5002, 198, 220, 220, 220, 1892, 1865, 9177, 198, 220, 220, 220, 37227, 628, 198, 4871, 7623, 22417, 7, 8697, 10426, 5377, 37064, 14881, 2599, 198, 220, 220, 220, 37227, 198, 220, 220, 220, 7623, 22417, 5002, 198, 220, 220, 220, 7875, 11902, 12608, 25, 198, 220, 220, 220, 220, 220, 220, 220, 949, 47, 14810, 198, 220, 220, 220, 220, 220, 220, 220, 3509, 47, 14810, 198, 220, 220, 220, 220, 220, 220, 220, 289, 7109, 198, 220, 220, 220, 220, 220, 220, 220, 266, 66, 70, 198, 220, 220, 220, 220, 220, 220, 220, 949, 37, 862, 198, 220, 220, 220, 220, 220, 220, 220, 3509, 37, 862, 198, 220, 220, 220, 37227, 628, 220, 220, 220, 825, 5002, 7, 944, 2599, 198, 220, 220, 220, 220, 220, 220, 220, 37227, 35561, 23735, 5002, 37811, 198, 220, 220, 220, 220, 220, 220, 220, 1288, 796, 2123, 631, 13, 20180, 7203, 10798, 22417, 4943, 198, 220, 220, 220, 220, 220, 220, 220, 611, 2116, 13, 1084, 62, 79, 14810, 318, 407, 6045, 25, 198, 220, 220, 220, 220, 220, 220, 220, 220, 220, 220, 220, 1288, 13, 2617, 7203, 1084, 47, 14810, 1600, 965, 7, 944, 13, 1084, 62, 79, 14810, 4008, 198, 220, 220, 220, 220, 220, 220, 220, 611, 2116, 13, 9806, 62, 79, 14810, 318, 407, 6045, 25, 198, 220, 220, 220, 220, 220, 220, 220, 220, 220, 220, 220, 1288, 13, 2617, 7203, 9806, 47, 14810, 1600, 965, 7, 944, 13, 9806, 62, 79, 14810, 4008, 198, 220, 220, 220, 220, 220, 220, 220, 611, 2116, 13, 71, 7109, 318, 407, 6045, 25, 198, 220, 220, 220, 220, 220, 220, 220, 220, 220, 220, 220, 1288, 13, 2617, 7203, 71, 7109, 1600, 37773, 62, 30388, 7, 944, 13, 71, 7109, 4008, 198, 220, 220, 220, 220, 220, 220, 220, 611, 2116, 13, 86, 66, 70, 318, 407, 6045, 25, 198, 220, 220, 220, 220, 220, 220, 220, 220, 220, 220, 220, 1288, 13, 2617, 7203, 86, 66, 70, 1600, 37773, 62, 30388, 7, 944, 13, 86, 66, 70, 4008, 198, 220, 220, 220, 220, 220, 220, 220, 611, 2116, 13, 1084, 62, 29647, 318, 407, 6045, 25, 198, 220, 220, 220, 220, 220, 220, 220, 220, 220, 220, 220, 1288, 13, 2617, 7203, 1084, 37, 862, 1600, 965, 7, 944, 13, 1084, 62, 29647, 4008, 198, 220, 220, 220, 220, 220, 220, 220, 611, 2116, 13, 9806, 62, 29647, 318, 407, 6045, 25, 198, 220, 220, 220, 220, 220, 220, 220, 220, 220, 220, 220, 1288, 13, 2617, 7203, 9806, 37, 862, 1600, 965, 7, 944, 13, 9806, 62, 29647, 4008, 198, 220, 220, 220, 220, 220, 220, 220, 1441, 1288, 628, 220, 220, 220, 2488, 12708, 24396, 198, 220, 220, 220, 825, 21136, 7, 19875, 2599, 198, 220, 220, 220, 220, 220, 220, 220, 37227, 198, 220, 220, 220, 220, 220, 220, 220, 2547, 325, 23735, 290, 1441, 7623, 22417, 198, 220, 220, 220, 220, 220, 220, 220, 37227, 198, 220, 220, 220, 220, 220, 220, 220, 611, 318, 39098, 7, 19875, 11, 357, 2536, 11, 9881, 8, 2599, 198, 220, 220, 220, 220, 220, 220, 220, 220, 220, 220, 220, 35555, 796, 2123, 631, 13, 6738, 8841, 7, 19875, 8, 628, 220, 220, 220, 220, 220, 220, 220, 949, 62, 79, 14810, 796, 6045, 198, 220, 220, 220, 220, 220, 220, 220, 3509, 62, 79, 14810, 796, 6045, 198, 220, 220, 220, 220, 220, 220, 220, 289, 7109, 796, 6045, 198, 220, 220, 220, 220, 220, 220, 220, 266, 66, 70, 796, 6045, 198, 220, 220, 220, 220, 220, 220, 220, 949, 62, 29647, 796, 6045, 198, 220, 220, 220, 220, 220, 220, 220, 3509, 62, 29647, 796, 6045, 628, 220, 220, 220, 220, 220, 220, 220, 611, 366, 1084, 47, 14810, 1, 287, 35555, 13, 1078, 822, 25, 198, 220, 220, 220, 220, 220, 220, 220, 220, 220, 220, 220, 949, 62, 79, 14810, 796, 35555, 13, 1078, 822, 14692, 1084, 47, 14810, 8973, 198, 220, 220, 220, 220, 220, 220, 220, 611, 366, 9806, 47, 14810, 1, 287, 35555, 13, 1078, 822, 25, 198, 220, 220, 220, 220, 220, 220, 220, 220, 220, 220, 220, 3509, 62, 79, 14810, 796, 35555, 13, 1078, 822, 14692, 9806, 47, 14810, 8973, 198, 220, 220, 220, 220, 220, 220, 220, 611, 366, 71, 7109, 1, 287, 35555, 13, 1078, 822, 25, 198, 220, 220, 220, 220, 220, 220, 220, 220, 220, 220, 220, 289, 7109, 796, 35555, 13, 1078, 822, 14692, 71, 7109, 8973, 198, 220, 220, 220, 220, 220, 220, 220, 611, 366, 86, 66, 70, 1, 287, 35555, 13, 1078, 822, 25, 198, 220, 220, 220, 220, 220, 220, 220, 220, 220, 220, 220, 266, 66, 70, 796, 35555, 13, 1078, 822, 14692, 86, 66, 70, 8973, 198, 220, 220, 220, 220, 220, 220, 220, 611, 366, 1084, 37, 862, 1, 287, 35555, 13, 1078, 822, 25, 198, 220, 220, 220, 220, 220, 220, 220, 220, 220, 220, 220, 949, 62, 29647, 796, 35555, 13, 1078, 822, 14692, 1084, 37, 862, 8973, 198, 220, 220, 220, 220, 220, 220, 220, 611, 366, 9806, 37, 862, 1, 287, 35555, 13, 1078, 822, 25, 198, 220, 220, 220, 220, 220, 220, 220, 220, 220, 220, 220, 3509, 62, 29647, 796, 35555, 13, 1078, 822, 14692, 9806, 37, 862, 8973, 628, 220, 220, 220, 220, 220, 220, 220, 1441, 7623, 22417, 7, 1084, 62, 79, 14810, 11, 3509, 62, 79, 14810, 11, 289, 7109, 11, 266, 66, 70, 11, 949, 62, 29647, 11, 3509, 62, 29647, 8, 628, 198, 4871, 13491, 22417, 7, 8697, 10426, 5377, 37064, 14881, 2599, 198, 220, 220, 220, 37227, 198, 220, 220, 220, 13491, 22417, 5002, 198, 220, 220, 220, 7875, 11902, 12608, 25, 198, 220, 220, 220, 220, 220, 220, 220, 949, 1925, 8961, 198, 220, 220, 220, 220, 220, 220, 220, 3509, 1925, 8961, 198, 220, 220, 220, 37227, 628, 220, 220, 220, 825, 5002, 7, 944, 2599, 198, 220, 220, 220, 220, 220, 220, 220, 37227, 35561, 23735, 5002, 37811, 198, 220, 220, 220, 220, 220, 220, 220, 1288, 796, 2123, 631, 13, 20180, 7203, 21206, 22417, 4943, 198, 220, 220, 220, 220, 220, 220, 220, 611, 2116, 13, 1084, 62, 354, 8961, 25, 198, 220, 220, 220, 220, 220, 220, 220, 220, 220, 220, 220, 1288, 13, 2617, 7203, 1084, 1925, 8961, 1600, 965, 7, 944, 13, 1084, 62, 354, 8961, 4008, 198, 220, 220, 220, 220, 220, 220, 220, 611, 2116, 13, 9806, 62, 354, 8961, 25, 198, 220, 220, 220, 220, 220, 220, 220, 220, 220, 220, 220, 1288, 13, 2617, 7203, 9806, 1925, 8961, 1600, 965, 7, 944, 13, 9806, 62, 354, 8961, 4008, 198, 220, 220, 220, 220, 220, 220, 220, 1441, 1288, 628, 220, 220, 220, 2488, 12708, 24396, 198, 220, 220, 220, 825, 21136, 7, 19875, 2599, 198, 220, 220, 220, 220, 220, 220, 220, 37227, 198, 220, 220, 220, 220, 220, 220, 220, 2547, 325, 23735, 290, 1441, 13491, 22417, 198, 220, 220, 220, 220, 220, 220, 220, 37227, 198, 220, 220, 220, 220, 220, 220, 220, 611, 318, 39098, 7, 19875, 11, 357, 2536, 11, 9881, 8, 2599, 198, 220, 220, 220, 220, 220, 220, 220, 220, 220, 220, 220, 35555, 796, 2123, 631, 13, 6738, 8841, 7, 19875, 8, 628, 220, 220, 220, 220, 220, 220, 220, 949, 62, 354, 8961, 796, 6045, 198, 220, 220, 220, 220, 220, 220, 220, 3509, 62, 354, 8961, 796, 6045, 628, 220, 220, 220, 220, 220, 220, 220, 611, 366, 1084, 1925, 8961, 1, 287, 35555, 13, 1078, 822, 25, 198, 220, 220, 220, 220, 220, 220, 220, 220, 220, 220, 220, 949, 62, 354, 8961, 796, 35555, 13, 1078, 822, 14692, 1084, 1925, 8961, 8973, 198, 220, 220, 220, 220, 220, 220, 220, 611, 366, 9806, 1925, 8961, 1, 287, 35555, 13, 1078, 822, 25, 198, 220, 220, 220, 220, 220, 220, 220, 220, 220, 220, 220, 3509, 62, 354, 8961, 796, 35555, 13, 1078, 822, 14692, 9806, 1925, 8961, 8973, 628, 220, 220, 220, 220, 220, 220, 220, 1441, 13491, 22417, 7, 1084, 62, 354, 8961, 11, 3509, 62, 354, 8961, 8, 628, 198, 4871, 4722, 4873, 22417, 7, 8697, 10426, 5377, 37064, 14881, 2599, 198, 220, 220, 220, 37227, 198, 220, 220, 220, 4722, 4873, 22417, 5002, 198, 220, 220, 220, 7875, 11902, 12608, 25, 198, 220, 220, 220, 220, 220, 220, 220, 949, 13128, 4873, 198, 220, 220, 220, 220, 220, 220, 220, 3509, 13128, 4873, 198, 220, 220, 220, 37227, 628, 220, 220, 220, 825, 5002, 7, 944, 2599, 198, 220, 220, 220, 220, 220, 220, 220, 37227, 35561, 23735, 5002, 37811, 198, 220, 220, 220, 220, 220, 220, 220, 1288, 796, 2123, 631, 13, 20180, 7203, 13128, 4873, 22417, 4943, 198, 220, 220, 220, 220, 220, 220, 220, 611, 2116, 13, 1084, 62, 2545, 4873, 25, 198, 220, 220, 220, 220, 220, 220, 220, 220, 220, 220, 220, 1288, 13, 2617, 7203, 1084, 13128, 4873, 1600, 965, 7, 944, 13, 1084, 62, 2545, 4873, 4008, 198, 220, 220, 220, 220, 220, 220, 220, 611, 2116, 13, 9806, 62, 2545, 4873, 25, 198, 220, 220, 220, 220, 220, 220, 220, 220, 220, 220, 220, 1288, 13, 2617, 7203, 9806, 13128, 4873, 1600, 965, 7, 944, 13, 9806, 62, 2545, 4873, 4008, 198, 220, 220, 220, 220, 220, 220, 220, 1441, 1288, 628, 220, 220, 220, 2488, 12708, 24396, 198, 220, 220, 220, 825, 21136, 7, 19875, 2599, 198, 220, 220, 220, 220, 220, 220, 220, 37227, 198, 220, 220, 220, 220, 220, 220, 220, 2547, 325, 23735, 290, 1441, 4722, 4873, 22417, 198, 220, 220, 220, 220, 220, 220, 220, 37227, 198, 220, 220, 220, 220, 220, 220, 220, 611, 318, 39098, 7, 19875, 11, 357, 2536, 11, 9881, 8, 2599, 198, 220, 220, 220, 220, 220, 220, 220, 220, 220, 220, 220, 35555, 796, 2123, 631, 13, 6738, 8841, 7, 19875, 8, 628, 220, 220, 220, 220, 220, 220, 220, 949, 62, 2545, 4873, 796, 6045, 198, 220, 220, 220, 220, 220, 220, 220, 3509, 62, 2545, 4873, 796, 6045, 628, 220, 220, 220, 220, 220, 220, 220, 611, 366, 1084, 13128, 4873, 1, 287, 35555, 13, 1078, 822, 25, 198, 220, 220, 220, 220, 220, 220, 220, 220, 220, 220, 220, 949, 62, 2545, 4873, 796, 35555, 13, 1078, 822, 14692, 1084, 13128, 4873, 8973, 198, 220, 220, 220, 220, 220, 220, 220, 611, 366, 9806, 13128, 4873, 1, 287, 35555, 13, 1078, 822, 25, 198, 220, 220, 220, 220, 220, 220, 220, 220, 220, 220, 220, 3509, 62, 2545, 4873, 796, 35555, 13, 1078, 822, 14692, 9806, 13128, 4873, 8973, 628, 220, 220, 220, 220, 220, 220, 220, 1441, 4722, 4873, 22417, 7, 1084, 62, 2545, 4873, 11, 3509, 62, 2545, 4873, 8, 198 ]
2.079683
2,146
import base64 import httplib2 from email.mime.text import MIMEText from apiclient.discovery import build from oauth2client.client import flow_from_clientsecrets from oauth2client.file import Storage from oauth2client.tools import run_flow from google_auth_oauthlib.flow import InstalledAppFlow permiso = ['https://www.googleapis.com/auth/gmail.send'] memoria = Storage('gmail.storage') IDOAuth = InstalledAppFlow.from_client_secrets_file("secreto_cliente_Gmail.json", scopes=permiso) http = httplib2.Http() credentials = memoria.get() if credentials is None or credentials.invalid: credentials = run_flow(IDOAuth, memoria, http=http) Servicio=build('gmail', 'v1', credentials=credentials) http = credentials.authorize(credentials) message = MIMEText("Message") message['to'] = "[email protected]" message['from'] = "[email protected]" message['subject'] = "Subject" body = {'raw': base64.b64encode(message.as_bytes())} Servicio.users().messages().send(userId="me",body=body).execute()
[ 11748, 2779, 2414, 198, 11748, 1841, 489, 571, 17, 198, 198, 6738, 3053, 13, 76, 524, 13, 5239, 1330, 337, 3955, 2767, 2302, 198, 198, 6738, 2471, 291, 75, 1153, 13, 67, 40821, 1330, 1382, 198, 6738, 267, 18439, 17, 16366, 13, 16366, 1330, 5202, 62, 6738, 62, 16366, 2363, 8004, 198, 6738, 267, 18439, 17, 16366, 13, 7753, 1330, 20514, 198, 6738, 267, 18439, 17, 16366, 13, 31391, 1330, 1057, 62, 11125, 198, 6738, 23645, 62, 18439, 62, 12162, 1071, 8019, 13, 11125, 1330, 2262, 4262, 4677, 37535, 198, 16321, 26786, 796, 37250, 5450, 1378, 2503, 13, 13297, 499, 271, 13, 785, 14, 18439, 14, 14816, 13, 21280, 20520, 198, 11883, 7661, 796, 20514, 10786, 14816, 13, 35350, 11537, 198, 2389, 23621, 1071, 796, 2262, 4262, 4677, 37535, 13, 6738, 62, 16366, 62, 2363, 8004, 62, 7753, 7203, 21078, 78, 62, 16366, 68, 62, 38, 4529, 13, 17752, 1600, 629, 13920, 28, 16321, 26786, 8, 198, 4023, 796, 1841, 489, 571, 17, 13, 43481, 3419, 198, 66, 445, 14817, 796, 1066, 7661, 13, 1136, 3419, 198, 361, 18031, 318, 6045, 393, 18031, 13, 259, 12102, 25, 198, 220, 18031, 796, 1057, 62, 11125, 7, 2389, 23621, 1071, 11, 1066, 7661, 11, 2638, 28, 4023, 8, 198, 198, 11838, 46441, 28, 11249, 10786, 14816, 3256, 705, 85, 16, 3256, 18031, 28, 66, 445, 14817, 8, 198, 4023, 796, 18031, 13, 9800, 1096, 7, 66, 445, 14817, 8, 198, 198, 20500, 796, 337, 3955, 2767, 2302, 7203, 12837, 4943, 198, 20500, 17816, 1462, 20520, 796, 366, 10215, 260, 516, 861, 65, 31, 14816, 13, 785, 1, 198, 20500, 17816, 6738, 20520, 796, 366, 395, 1192, 544, 929, 85, 31, 14816, 13, 785, 1, 198, 20500, 17816, 32796, 20520, 796, 366, 19776, 1, 198, 2618, 796, 1391, 6, 1831, 10354, 2779, 2414, 13, 65, 2414, 268, 8189, 7, 20500, 13, 292, 62, 33661, 28955, 92, 198, 198, 11838, 46441, 13, 18417, 22446, 37348, 1095, 22446, 21280, 7, 7220, 7390, 2625, 1326, 1600, 2618, 28, 2618, 737, 41049, 3419, 198 ]
2.970326
337
import os import shutil import traceback HOME_DIR = os.path.abspath(os.path.expanduser("~")) PATH_DEFAULT_OBS = os.path.join(HOME_DIR, "videos", "obs") DRY_RUN = False def _is_video_file(file_path: str) -> bool: """Returns True if the given file is a video file.""" _, ext = os.path.splitext(file_path.lower()) return ext in [".mp4", ".mkv"] def makedirs(new_dir: str, exist_ok: bool = False) -> None: """Make the given directory.""" print(f"make_dirs: {new_dir}") if DRY_RUN: return os.makedirs(new_dir, exist_ok=exist_ok) def movefile(src: str, dst: str) -> None: """Move the given file.""" print(f"movefile: {src} -> {dst}") if DRY_RUN: return shutil.move(src, dst) def organize(path: str = PATH_DEFAULT_OBS) -> None: """Organize the given path.""" paths = [os.path.join(path, p) for p in os.listdir(path) if _is_video_file(p)] for p in paths: try: name_ext = os.path.basename(p) name = os.path.splitext(name_ext)[0] ext = os.path.splitext(name_ext)[1] date_time = name.replace(" ", "_").split("_") new_dir = os.path.join(path, date_time[0]) new_path = os.path.join(new_dir, f"{date_time[1]}{ext}") makedirs(os.path.dirname(new_path), exist_ok=True) movefile(p, new_path) except Exception as e: traceback.print_exc() print(f"Could not process {p} because of {e}") def main() -> None: """Main entry point.""" reply = input( f"WARNING! This will organize all your videos in the obs path:\n {PATH_DEFAULT_OBS}\ncontinue? [y/n]: " ) if reply.lower() != "y": organize() if __name__ == "__main__": main()
[ 11748, 28686, 198, 11748, 4423, 346, 198, 11748, 12854, 1891, 198, 198, 39069, 62, 34720, 796, 28686, 13, 6978, 13, 397, 2777, 776, 7, 418, 13, 6978, 13, 11201, 392, 7220, 7203, 93, 48774, 198, 34219, 62, 7206, 38865, 62, 46, 4462, 796, 28686, 13, 6978, 13, 22179, 7, 39069, 62, 34720, 11, 366, 32861, 1600, 366, 8158, 4943, 198, 7707, 56, 62, 49, 4944, 796, 10352, 628, 198, 4299, 4808, 271, 62, 15588, 62, 7753, 7, 7753, 62, 6978, 25, 965, 8, 4613, 20512, 25, 198, 220, 220, 220, 37227, 35561, 6407, 611, 262, 1813, 2393, 318, 257, 2008, 2393, 526, 15931, 198, 220, 220, 220, 4808, 11, 1070, 796, 28686, 13, 6978, 13, 22018, 578, 742, 7, 7753, 62, 6978, 13, 21037, 28955, 198, 220, 220, 220, 1441, 1070, 287, 685, 1911, 3149, 19, 1600, 27071, 28015, 85, 8973, 628, 198, 4299, 285, 4335, 17062, 7, 3605, 62, 15908, 25, 965, 11, 2152, 62, 482, 25, 20512, 796, 10352, 8, 4613, 6045, 25, 198, 220, 220, 220, 37227, 12050, 262, 1813, 8619, 526, 15931, 198, 220, 220, 220, 3601, 7, 69, 1, 15883, 62, 15908, 82, 25, 1391, 3605, 62, 15908, 92, 4943, 198, 220, 220, 220, 611, 10560, 56, 62, 49, 4944, 25, 198, 220, 220, 220, 220, 220, 220, 220, 1441, 198, 220, 220, 220, 28686, 13, 76, 4335, 17062, 7, 3605, 62, 15908, 11, 2152, 62, 482, 28, 38476, 62, 482, 8, 628, 198, 4299, 1445, 7753, 7, 10677, 25, 965, 11, 29636, 25, 965, 8, 4613, 6045, 25, 198, 220, 220, 220, 37227, 21774, 262, 1813, 2393, 526, 15931, 198, 220, 220, 220, 3601, 7, 69, 1, 21084, 7753, 25, 1391, 10677, 92, 4613, 1391, 67, 301, 92, 4943, 198, 220, 220, 220, 611, 10560, 56, 62, 49, 4944, 25, 198, 220, 220, 220, 220, 220, 220, 220, 1441, 198, 220, 220, 220, 4423, 346, 13, 21084, 7, 10677, 11, 29636, 8, 628, 198, 4299, 16481, 7, 6978, 25, 965, 796, 46490, 62, 7206, 38865, 62, 46, 4462, 8, 4613, 6045, 25, 198, 220, 220, 220, 37227, 26121, 1096, 262, 1813, 3108, 526, 15931, 198, 220, 220, 220, 13532, 796, 685, 418, 13, 6978, 13, 22179, 7, 6978, 11, 279, 8, 329, 279, 287, 28686, 13, 4868, 15908, 7, 6978, 8, 611, 4808, 271, 62, 15588, 62, 7753, 7, 79, 15437, 198, 220, 220, 220, 329, 279, 287, 13532, 25, 198, 220, 220, 220, 220, 220, 220, 220, 1949, 25, 198, 220, 220, 220, 220, 220, 220, 220, 220, 220, 220, 220, 1438, 62, 2302, 796, 28686, 13, 6978, 13, 12093, 12453, 7, 79, 8, 198, 220, 220, 220, 220, 220, 220, 220, 220, 220, 220, 220, 1438, 796, 28686, 13, 6978, 13, 22018, 578, 742, 7, 3672, 62, 2302, 38381, 15, 60, 198, 220, 220, 220, 220, 220, 220, 220, 220, 220, 220, 220, 1070, 796, 28686, 13, 6978, 13, 22018, 578, 742, 7, 3672, 62, 2302, 38381, 16, 60, 198, 220, 220, 220, 220, 220, 220, 220, 220, 220, 220, 220, 3128, 62, 2435, 796, 1438, 13, 33491, 7203, 33172, 45434, 11074, 35312, 7203, 62, 4943, 198, 220, 220, 220, 220, 220, 220, 220, 220, 220, 220, 220, 649, 62, 15908, 796, 28686, 13, 6978, 13, 22179, 7, 6978, 11, 3128, 62, 2435, 58, 15, 12962, 198, 220, 220, 220, 220, 220, 220, 220, 220, 220, 220, 220, 649, 62, 6978, 796, 28686, 13, 6978, 13, 22179, 7, 3605, 62, 15908, 11, 277, 1, 90, 4475, 62, 2435, 58, 16, 60, 18477, 2302, 92, 4943, 198, 220, 220, 220, 220, 220, 220, 220, 220, 220, 220, 220, 285, 4335, 17062, 7, 418, 13, 6978, 13, 15908, 3672, 7, 3605, 62, 6978, 828, 2152, 62, 482, 28, 17821, 8, 198, 220, 220, 220, 220, 220, 220, 220, 220, 220, 220, 220, 1445, 7753, 7, 79, 11, 649, 62, 6978, 8, 198, 220, 220, 220, 220, 220, 220, 220, 2845, 35528, 355, 304, 25, 198, 220, 220, 220, 220, 220, 220, 220, 220, 220, 220, 220, 12854, 1891, 13, 4798, 62, 41194, 3419, 198, 220, 220, 220, 220, 220, 220, 220, 220, 220, 220, 220, 3601, 7, 69, 1, 23722, 407, 1429, 1391, 79, 92, 780, 286, 1391, 68, 92, 4943, 628, 198, 4299, 1388, 3419, 4613, 6045, 25, 198, 220, 220, 220, 37227, 13383, 5726, 966, 526, 15931, 198, 220, 220, 220, 10971, 796, 5128, 7, 198, 220, 220, 220, 220, 220, 220, 220, 277, 1, 31502, 0, 770, 481, 16481, 477, 534, 5861, 287, 262, 10201, 3108, 7479, 77, 220, 1391, 34219, 62, 7206, 38865, 62, 46, 4462, 32239, 77, 43043, 30, 685, 88, 14, 77, 5974, 366, 198, 220, 220, 220, 1267, 198, 220, 220, 220, 611, 10971, 13, 21037, 3419, 14512, 366, 88, 1298, 198, 220, 220, 220, 220, 220, 220, 220, 16481, 3419, 628, 198, 361, 11593, 3672, 834, 6624, 366, 834, 12417, 834, 1298, 198, 220, 220, 220, 1388, 3419, 198 ]
2.164822
813
import math x = float(input('Digite um ângulo: ')) tangente = math.tan(math.radians(x)) cos = math.acos(math.radians(x)) seno = math.asin(math.radians(x)) print(f'O cosseno de {x} é {cos:.2f}') print(f'O seno de {x} é {seno:.2f}') print(f'A tangente de {x} é {tangente:.2f}')
[ 11748, 10688, 198, 87, 796, 12178, 7, 15414, 10786, 19511, 578, 23781, 6184, 95, 782, 43348, 25, 705, 4008, 198, 83, 648, 21872, 796, 10688, 13, 38006, 7, 11018, 13, 6335, 1547, 7, 87, 4008, 198, 6966, 796, 10688, 13, 330, 418, 7, 11018, 13, 6335, 1547, 7, 87, 4008, 198, 6248, 78, 796, 10688, 13, 47337, 7, 11018, 13, 6335, 1547, 7, 87, 4008, 198, 4798, 7, 69, 6, 46, 269, 793, 23397, 390, 1391, 87, 92, 38251, 1391, 6966, 25, 13, 17, 69, 92, 11537, 198, 4798, 7, 69, 6, 46, 3308, 78, 390, 1391, 87, 92, 38251, 1391, 6248, 78, 25, 13, 17, 69, 92, 11537, 198, 4798, 7, 69, 6, 32, 13875, 21872, 390, 1391, 87, 92, 38251, 1391, 83, 648, 21872, 25, 13, 17, 69, 92, 11537, 220 ]
2.075188
133
#!/usr/local/bin/python """This demonstrates a minimal http upload cgi. This allows a user to upload up to three files at once. It is trivial to change the number of files uploaded. This script has security risks. A user could attempt to fill a disk partition with endless uploads. If you have a system open to the public you would obviously want to limit the size and number of files written to the disk. """ import cgi import cgitb; cgitb.enable() import os, sys try: # Windows needs stdio set for binary mode. import msvcrt msvcrt.setmode (0, os.O_BINARY) # stdin = 0 msvcrt.setmode (1, os.O_BINARY) # stdout = 1 except ImportError: pass UPLOAD_DIR = "/tmp" HTML_TEMPLATE = """<!DOCTYPE HTML PUBLIC "-//W3C//DTD HTML 4.01 Transitional//EN"> <html><head><title>File Upload</title> <meta http-equiv="Content-Type" content="text/html; charset=iso-8859-1"> </head><body><h1>File Upload</h1> <form action="%(SCRIPT_NAME)s" method="POST" enctype="multipart/form-data"> File name: <input name="file_1" type="file"><br> File name: <input name="file_2" type="file"><br> File name: <input name="file_3" type="file"><br> <input name="submit" type="submit"> </form> </body> </html>""" def print_html_form (): """This prints out the html form. Note that the action is set to the name of the script which makes this is a self-posting form. In other words, this cgi both displays a form and processes it. """ print "content-type: text/html\n" print HTML_TEMPLATE % {'SCRIPT_NAME':os.environ['SCRIPT_NAME']} def save_uploaded_file (form_field, upload_dir): """This saves a file uploaded by an HTML form. The form_field is the name of the file input field from the form. For example, the following form_field would be "file_1": <input name="file_1" type="file"> The upload_dir is the directory where the file will be written. If no file was uploaded or if the field does not exist then this does nothing. """ form = cgi.FieldStorage() if not form.has_key(form_field): return fileitem = form[form_field] if not fileitem.file: return fout = file (os.path.join(upload_dir, fileitem.filename), 'wb') while 1: chunk = fileitem.file.read(100000) if not chunk: break fout.write (chunk) fout.close() save_uploaded_file ("file_1", UPLOAD_DIR) save_uploaded_file ("file_2", UPLOAD_DIR) save_uploaded_file ("file_3", UPLOAD_DIR) print_html_form ()
[ 2, 48443, 14629, 14, 12001, 14, 8800, 14, 29412, 198, 37811, 1212, 15687, 257, 10926, 2638, 9516, 269, 12397, 13, 198, 1212, 3578, 257, 2836, 284, 9516, 510, 284, 1115, 3696, 379, 1752, 13, 198, 1026, 318, 20861, 284, 1487, 262, 1271, 286, 3696, 19144, 13, 198, 198, 1212, 4226, 468, 2324, 7476, 13, 317, 2836, 714, 2230, 284, 6070, 198, 64, 11898, 18398, 351, 13079, 9516, 82, 13, 220, 198, 1532, 345, 423, 257, 1080, 1280, 284, 262, 1171, 345, 561, 6189, 765, 198, 1462, 4179, 262, 2546, 290, 1271, 286, 3696, 3194, 284, 262, 11898, 13, 198, 37811, 198, 11748, 269, 12397, 198, 11748, 269, 18300, 65, 26, 269, 18300, 65, 13, 21633, 3419, 198, 11748, 28686, 11, 25064, 198, 28311, 25, 1303, 3964, 2476, 14367, 952, 900, 329, 13934, 4235, 13, 198, 220, 220, 220, 1330, 13845, 85, 6098, 83, 198, 220, 220, 220, 13845, 85, 6098, 83, 13, 2617, 14171, 357, 15, 11, 28686, 13, 46, 62, 33, 1268, 13153, 8, 1303, 14367, 259, 220, 796, 657, 198, 220, 220, 220, 13845, 85, 6098, 83, 13, 2617, 14171, 357, 16, 11, 28686, 13, 46, 62, 33, 1268, 13153, 8, 1303, 14367, 448, 796, 352, 198, 16341, 17267, 12331, 25, 198, 220, 220, 220, 1208, 198, 198, 52, 6489, 41048, 62, 34720, 796, 12813, 22065, 1, 198, 198, 28656, 62, 51, 3620, 6489, 6158, 796, 37227, 27, 0, 18227, 4177, 56, 11401, 11532, 44731, 27444, 1003, 54, 18, 34, 1003, 35, 21016, 11532, 604, 13, 486, 3602, 1859, 1003, 1677, 5320, 198, 27, 6494, 6927, 2256, 6927, 7839, 29, 8979, 36803, 3556, 7839, 29, 198, 27, 28961, 2638, 12, 4853, 452, 2625, 19746, 12, 6030, 1, 2695, 2625, 5239, 14, 6494, 26, 34534, 316, 28, 26786, 12, 3459, 3270, 12, 16, 5320, 198, 3556, 2256, 6927, 2618, 6927, 71, 16, 29, 8979, 36803, 3556, 71, 16, 29, 198, 27, 687, 2223, 2625, 4, 7, 6173, 46023, 62, 20608, 8, 82, 1, 2446, 2625, 32782, 1, 551, 310, 2981, 2625, 16680, 541, 433, 14, 687, 12, 7890, 5320, 198, 8979, 1438, 25, 1279, 15414, 1438, 2625, 7753, 62, 16, 1, 2099, 2625, 7753, 22039, 1671, 29, 198, 8979, 1438, 25, 1279, 15414, 1438, 2625, 7753, 62, 17, 1, 2099, 2625, 7753, 22039, 1671, 29, 198, 8979, 1438, 25, 1279, 15414, 1438, 2625, 7753, 62, 18, 1, 2099, 2625, 7753, 22039, 1671, 29, 198, 27, 15414, 1438, 2625, 46002, 1, 2099, 2625, 46002, 5320, 198, 3556, 687, 29, 198, 3556, 2618, 29, 198, 3556, 6494, 29, 37811, 198, 198, 4299, 3601, 62, 6494, 62, 687, 357, 2599, 198, 220, 220, 220, 37227, 1212, 20842, 503, 262, 27711, 1296, 13, 5740, 326, 262, 2223, 318, 900, 284, 198, 220, 220, 220, 220, 220, 262, 1438, 286, 262, 4226, 543, 1838, 428, 318, 257, 2116, 12, 7353, 278, 1296, 13, 198, 220, 220, 220, 220, 220, 554, 584, 2456, 11, 428, 269, 12397, 1111, 11298, 257, 1296, 290, 7767, 340, 13, 198, 220, 220, 220, 37227, 198, 220, 220, 220, 3601, 366, 11299, 12, 4906, 25, 2420, 14, 6494, 59, 77, 1, 198, 220, 220, 220, 3601, 11532, 62, 51, 3620, 6489, 6158, 4064, 1391, 6, 6173, 46023, 62, 20608, 10354, 418, 13, 268, 2268, 17816, 6173, 46023, 62, 20608, 20520, 92, 198, 198, 4299, 3613, 62, 25850, 276, 62, 7753, 357, 687, 62, 3245, 11, 9516, 62, 15908, 2599, 198, 220, 220, 220, 37227, 1212, 16031, 257, 2393, 19144, 416, 281, 11532, 1296, 13, 198, 220, 220, 220, 220, 220, 220, 383, 1296, 62, 3245, 318, 262, 1438, 286, 262, 2393, 5128, 2214, 422, 262, 1296, 13, 198, 220, 220, 220, 220, 220, 220, 1114, 1672, 11, 262, 1708, 1296, 62, 3245, 561, 307, 366, 7753, 62, 16, 1298, 198, 220, 220, 220, 220, 220, 220, 220, 220, 220, 220, 1279, 15414, 1438, 2625, 7753, 62, 16, 1, 2099, 2625, 7753, 5320, 198, 220, 220, 220, 220, 220, 220, 383, 9516, 62, 15908, 318, 262, 8619, 810, 262, 2393, 481, 307, 3194, 13, 198, 220, 220, 220, 220, 220, 220, 1002, 645, 2393, 373, 19144, 393, 611, 262, 2214, 857, 407, 2152, 788, 198, 220, 220, 220, 220, 220, 220, 428, 857, 2147, 13, 198, 220, 220, 220, 37227, 198, 220, 220, 220, 1296, 796, 269, 12397, 13, 15878, 31425, 3419, 198, 220, 220, 220, 611, 407, 1296, 13, 10134, 62, 2539, 7, 687, 62, 3245, 2599, 1441, 198, 220, 220, 220, 2393, 9186, 796, 1296, 58, 687, 62, 3245, 60, 198, 220, 220, 220, 611, 407, 2393, 9186, 13, 7753, 25, 1441, 198, 220, 220, 220, 277, 448, 796, 2393, 357, 418, 13, 6978, 13, 22179, 7, 25850, 62, 15908, 11, 2393, 9186, 13, 34345, 828, 705, 39346, 11537, 198, 220, 220, 220, 981, 352, 25, 198, 220, 220, 220, 220, 220, 220, 220, 16058, 796, 2393, 9186, 13, 7753, 13, 961, 7, 3064, 830, 8, 198, 220, 220, 220, 220, 220, 220, 220, 611, 407, 16058, 25, 2270, 198, 220, 220, 220, 220, 220, 220, 220, 277, 448, 13, 13564, 357, 354, 2954, 8, 198, 220, 220, 220, 277, 448, 13, 19836, 3419, 198, 198, 21928, 62, 25850, 276, 62, 7753, 5855, 7753, 62, 16, 1600, 471, 6489, 41048, 62, 34720, 8, 198, 21928, 62, 25850, 276, 62, 7753, 5855, 7753, 62, 17, 1600, 471, 6489, 41048, 62, 34720, 8, 198, 21928, 62, 25850, 276, 62, 7753, 5855, 7753, 62, 18, 1600, 471, 6489, 41048, 62, 34720, 8, 198, 198, 4798, 62, 6494, 62, 687, 7499, 198 ]
2.730473
909
import argparse import datetime import os import re import sys import unicodedata import libs.header import libs.unicode import libs.utf8 if __name__ == '__main__': parser = argparse.ArgumentParser(description='Parse Unicode codepoint database and write integration tests.') parser.add_argument( '-v', '--verbose', dest = 'verbose', action = 'store_true', help = 'verbose output') parser.add_argument( '--casemapping', dest = 'casemapping', action = 'store_true', help = 'write case mapping tests') parser.add_argument( '--normalization', dest = 'normalization', action = 'store_true', help = 'write normalization tests') parser.add_argument( '--is-normalized', dest = 'isnormalized', action = 'store_true', help = 'write is-normalized tests') parser.add_argument( '--casefolding', dest = 'casefolding', action = 'store_true', help = 'write casefolding tests') args = parser.parse_args() if not args.casemapping and not args.normalization and not args.isnormalized and not args.casefolding: all = True else: all = False db = unicodedata.Database() db.loadFromFiles(None) if all or args.casemapping: suite = CaseMappingIntegrationSuite(db) suite.execute() if all or args.normalization: suite = NormalizationIntegrationSuite(db) suite.execute() if all or args.isnormalized: suite = IsNormalizedIntegrationSuite(db) suite.execute() if all or args.casefolding: suite = CaseFoldingIntegrationSuite(db) suite.execute()
[ 11748, 1822, 29572, 201, 198, 11748, 4818, 8079, 201, 198, 11748, 28686, 201, 198, 11748, 302, 201, 198, 11748, 25064, 201, 198, 11748, 28000, 9043, 1045, 201, 198, 11748, 9195, 82, 13, 25677, 201, 198, 11748, 9195, 82, 13, 46903, 1098, 201, 198, 11748, 9195, 82, 13, 40477, 23, 201, 198, 201, 198, 361, 11593, 3672, 834, 6624, 705, 834, 12417, 834, 10354, 201, 198, 197, 48610, 796, 1822, 29572, 13, 28100, 1713, 46677, 7, 11213, 11639, 10044, 325, 34371, 14873, 538, 1563, 6831, 290, 3551, 11812, 5254, 2637, 8, 201, 198, 197, 48610, 13, 2860, 62, 49140, 7, 201, 198, 197, 197, 29001, 85, 3256, 705, 438, 19011, 577, 3256, 201, 198, 197, 197, 16520, 796, 705, 19011, 577, 3256, 201, 198, 197, 197, 2673, 796, 705, 8095, 62, 7942, 3256, 201, 198, 197, 197, 16794, 796, 705, 19011, 577, 5072, 11537, 201, 198, 197, 48610, 13, 2860, 62, 49140, 7, 201, 198, 197, 197, 6, 438, 34004, 368, 5912, 3256, 201, 198, 197, 197, 16520, 796, 705, 34004, 368, 5912, 3256, 201, 198, 197, 197, 2673, 796, 705, 8095, 62, 7942, 3256, 201, 198, 197, 197, 16794, 796, 705, 13564, 1339, 16855, 5254, 11537, 201, 198, 197, 48610, 13, 2860, 62, 49140, 7, 201, 198, 197, 197, 6, 438, 11265, 1634, 3256, 201, 198, 197, 197, 16520, 796, 705, 11265, 1634, 3256, 201, 198, 197, 197, 2673, 796, 705, 8095, 62, 7942, 3256, 201, 198, 197, 197, 16794, 796, 705, 13564, 3487, 1634, 5254, 11537, 201, 198, 197, 48610, 13, 2860, 62, 49140, 7, 201, 198, 197, 197, 6, 438, 271, 12, 11265, 1143, 3256, 201, 198, 197, 197, 16520, 796, 705, 271, 11265, 1143, 3256, 201, 198, 197, 197, 2673, 796, 705, 8095, 62, 7942, 3256, 201, 198, 197, 197, 16794, 796, 705, 13564, 318, 12, 11265, 1143, 5254, 11537, 201, 198, 197, 48610, 13, 2860, 62, 49140, 7, 201, 198, 197, 197, 6, 438, 7442, 11379, 278, 3256, 201, 198, 197, 197, 16520, 796, 705, 7442, 11379, 278, 3256, 201, 198, 197, 197, 2673, 796, 705, 8095, 62, 7942, 3256, 201, 198, 197, 197, 16794, 796, 705, 13564, 1339, 11379, 278, 5254, 11537, 201, 198, 197, 22046, 796, 30751, 13, 29572, 62, 22046, 3419, 201, 198, 197, 201, 198, 197, 361, 407, 26498, 13, 34004, 368, 5912, 290, 407, 26498, 13, 11265, 1634, 290, 407, 26498, 13, 271, 11265, 1143, 290, 407, 26498, 13, 7442, 11379, 278, 25, 201, 198, 197, 197, 439, 796, 6407, 201, 198, 197, 17772, 25, 201, 198, 197, 197, 439, 796, 10352, 201, 198, 197, 201, 198, 197, 9945, 796, 28000, 9043, 1045, 13, 38105, 3419, 201, 198, 197, 9945, 13, 2220, 4863, 25876, 7, 14202, 8, 201, 198, 197, 201, 198, 197, 361, 477, 393, 26498, 13, 34004, 368, 5912, 25, 201, 198, 197, 197, 2385, 578, 796, 8913, 44, 5912, 34500, 1358, 5606, 578, 7, 9945, 8, 201, 198, 197, 197, 2385, 578, 13, 41049, 3419, 201, 198, 197, 201, 198, 197, 361, 477, 393, 26498, 13, 11265, 1634, 25, 201, 198, 197, 197, 2385, 578, 796, 14435, 1634, 34500, 1358, 5606, 578, 7, 9945, 8, 201, 198, 197, 197, 2385, 578, 13, 41049, 3419, 201, 198, 197, 201, 198, 197, 361, 477, 393, 26498, 13, 271, 11265, 1143, 25, 201, 198, 197, 197, 2385, 578, 796, 1148, 26447, 1143, 34500, 1358, 5606, 578, 7, 9945, 8, 201, 198, 197, 197, 2385, 578, 13, 41049, 3419, 201, 198, 197, 201, 198, 197, 361, 477, 393, 26498, 13, 7442, 11379, 278, 25, 201, 198, 197, 197, 2385, 578, 796, 8913, 37, 33266, 34500, 1358, 5606, 578, 7, 9945, 8, 201, 198, 197, 197, 2385, 578, 13, 41049, 3419 ]
2.567434
608
try: from PyQt4.QtCore import QSettings except ImportError: from PyQt5.QtCore import QSettings
[ 28311, 25, 198, 220, 220, 220, 422, 9485, 48, 83, 19, 13, 48, 83, 14055, 1330, 1195, 26232, 198, 16341, 17267, 12331, 25, 198, 220, 220, 220, 422, 9485, 48, 83, 20, 13, 48, 83, 14055, 1330, 1195, 26232, 628, 220, 220, 220, 220 ]
2.454545
44
from re import search from typing import List, Optional, Pattern
[ 6738, 302, 1330, 2989, 198, 6738, 19720, 1330, 7343, 11, 32233, 11, 23939, 628 ]
4.714286
14
""" __________________________________________________________________________________________________ :project: SiLA2_python :details: Response data type in a SiLA Command, Property, Intermediate, ... :file: data_type_response.py :authors: Timm Severin :date: (creation) 20190820 :date: (last modification) 20190820 __________________________________________________________________________________________________ **Copyright**: This file is provided "AS IS" with NO WARRANTY OF ANY KIND, INCLUDING THE WARRANTIES OF DESIGN, MERCHANTABILITY AND FITNESS FOR A PARTICULAR PURPOSE. For further Information see LICENSE file that comes with this distribution. __________________________________________________________________________________________________ """ # import library packages from .data_type_parameter import ParameterDataType class ResponseDataType(ParameterDataType): """ The class for responses. This is essentially identical to a :class:`~.ParameterDataType`, however can be handled differently in the final application and thus exists as its own class/object. .. note:: When checking whether an object is a response or a parameter, note that :func:`isinstance(obj, ParameterDataType)` will also return true if the object is a :class:`ResponseDataType`, since they are derived from each other. Use ``type(obj) is ParameterDataType`` for a precise check. """
[ 37811, 198, 27193, 10221, 834, 198, 198, 25, 16302, 25, 15638, 13534, 17, 62, 29412, 198, 198, 25, 36604, 25, 18261, 1366, 2099, 287, 257, 15638, 13534, 9455, 11, 14161, 11, 42540, 11, 2644, 198, 198, 25, 7753, 25, 220, 220, 220, 1366, 62, 4906, 62, 26209, 13, 9078, 198, 25, 41617, 25, 5045, 76, 26434, 259, 198, 198, 25, 4475, 25, 357, 38793, 8, 220, 220, 220, 220, 220, 220, 220, 220, 220, 13130, 2919, 1238, 198, 25, 4475, 25, 357, 12957, 17613, 8, 13130, 2919, 1238, 198, 198, 27193, 10221, 834, 198, 198, 1174, 15269, 1174, 25, 198, 220, 770, 2393, 318, 2810, 366, 1921, 3180, 1, 351, 8005, 34764, 56, 3963, 15529, 509, 12115, 11, 198, 220, 47783, 2751, 3336, 34764, 11015, 3963, 22196, 16284, 11, 34482, 3398, 1565, 5603, 25382, 5357, 376, 46144, 7473, 317, 16652, 2149, 37232, 33079, 48933, 13, 628, 220, 1114, 2252, 6188, 766, 38559, 24290, 2393, 326, 2058, 351, 428, 6082, 13, 198, 27193, 10221, 834, 198, 37811, 198, 198, 2, 1330, 5888, 10392, 198, 6738, 764, 7890, 62, 4906, 62, 17143, 2357, 1330, 25139, 2357, 6601, 6030, 628, 198, 4871, 18261, 6601, 6030, 7, 36301, 6601, 6030, 2599, 198, 220, 220, 220, 37227, 198, 220, 220, 220, 383, 1398, 329, 9109, 13, 198, 220, 220, 220, 220, 220, 220, 220, 770, 318, 6986, 10411, 284, 257, 1058, 4871, 25, 63, 93, 13, 36301, 6601, 6030, 47671, 2158, 460, 307, 12118, 10338, 287, 262, 2457, 198, 220, 220, 220, 220, 220, 220, 220, 3586, 290, 4145, 7160, 355, 663, 898, 1398, 14, 15252, 13, 628, 220, 220, 220, 11485, 3465, 3712, 1649, 10627, 1771, 281, 2134, 318, 257, 2882, 393, 257, 11507, 11, 3465, 326, 198, 220, 220, 220, 220, 220, 220, 220, 220, 220, 220, 220, 220, 220, 1058, 20786, 25, 63, 271, 39098, 7, 26801, 11, 25139, 2357, 6601, 6030, 8, 63, 481, 635, 1441, 2081, 611, 262, 2134, 318, 257, 198, 220, 220, 220, 220, 220, 220, 220, 220, 220, 220, 220, 220, 220, 1058, 4871, 25, 63, 31077, 6601, 6030, 47671, 1201, 484, 389, 10944, 422, 1123, 584, 13, 5765, 7559, 4906, 7, 26801, 8, 318, 25139, 2357, 6601, 6030, 15506, 198, 220, 220, 220, 220, 220, 220, 220, 220, 220, 220, 220, 220, 220, 329, 257, 7141, 2198, 13, 198, 220, 220, 220, 37227, 198 ]
3.801546
388
# =============================================================== # Author: Rodolfo Ferro # Email: [email protected] # Twitter: @FerroRodolfo # # ABOUT COPYING OR USING PARTIAL INFORMATION: # This script was originally created by Rodolfo Ferro, for # his workshop in PythonDay Mexico 2018 at CUCEA in Gdl, Mx. # Any explicit usage of this script or its contents is granted # according to the license provided and its conditions. # =============================================================== # -*- coding: utf-8 -*- import requests import pprint import json def get_json(url, filename): """ Download JSON response url for testing. """ # Get response: response = requests.get(url) # If response's status is 200: if response.status_code == requests.codes.ok: # Pretty print response: pprint.pprint(response.json()) # Save response into a JSON file: with open(filename, 'wt') as output: output.write(response.text) return def get_prediction(url, filename): """ Download JSON response url for prediction. """ # Set metadata: headers = {'Content-type': 'application/json'} input_values = {'sepal_length': 6.4, 'sepal_width': 3.2, 'petal_length': 4.5, 'petal_width': 1.5} # Get response: response = requests.post(url, json=input_values, headers=headers) # If response's status is 200: if response.status_code == requests.codes.ok: # Pretty print response: pprint.pprint(response.json()) # Save response into a JSON file: with open(filename, 'wt') as output: output.write(response.text) return if __name__ == '__main__': # Try out our JSON response downloader: get_json('http://localhost:5000/api/v0.0', 'response.json') get_prediction('http://localhost:5000/api/v0.0/predict', 'response.json')
[ 2, 46111, 4770, 25609, 855, 198, 2, 6434, 25, 6882, 4024, 78, 12880, 305, 198, 2, 9570, 25, 11354, 305, 31, 66, 320, 265, 13, 36802, 198, 2, 3009, 25, 2488, 43362, 305, 27917, 4024, 78, 198, 2, 198, 2, 33478, 27975, 45761, 6375, 1294, 2751, 16652, 12576, 38044, 25, 198, 2, 770, 4226, 373, 6198, 2727, 416, 6882, 4024, 78, 12880, 305, 11, 329, 198, 2, 465, 20243, 287, 11361, 12393, 5828, 2864, 379, 29369, 5222, 32, 287, 402, 25404, 11, 337, 87, 13, 198, 2, 4377, 7952, 8748, 286, 428, 4226, 393, 663, 10154, 318, 7520, 198, 2, 1864, 284, 262, 5964, 2810, 290, 663, 3403, 13, 198, 2, 46111, 4770, 25609, 855, 198, 198, 2, 532, 9, 12, 19617, 25, 3384, 69, 12, 23, 532, 9, 12, 198, 198, 11748, 7007, 198, 11748, 279, 4798, 198, 11748, 33918, 628, 198, 4299, 651, 62, 17752, 7, 6371, 11, 29472, 2599, 198, 220, 220, 220, 37227, 198, 220, 220, 220, 10472, 19449, 2882, 19016, 329, 4856, 13, 198, 220, 220, 220, 37227, 628, 220, 220, 220, 1303, 3497, 2882, 25, 198, 220, 220, 220, 2882, 796, 7007, 13, 1136, 7, 6371, 8, 628, 220, 220, 220, 1303, 1002, 2882, 338, 3722, 318, 939, 25, 198, 220, 220, 220, 611, 2882, 13, 13376, 62, 8189, 6624, 7007, 13, 40148, 13, 482, 25, 198, 220, 220, 220, 220, 220, 220, 220, 1303, 20090, 3601, 2882, 25, 198, 220, 220, 220, 220, 220, 220, 220, 279, 4798, 13, 381, 22272, 7, 26209, 13, 17752, 28955, 628, 220, 220, 220, 220, 220, 220, 220, 1303, 12793, 2882, 656, 257, 19449, 2393, 25, 198, 220, 220, 220, 220, 220, 220, 220, 351, 1280, 7, 34345, 11, 705, 46569, 11537, 355, 5072, 25, 198, 220, 220, 220, 220, 220, 220, 220, 220, 220, 220, 220, 5072, 13, 13564, 7, 26209, 13, 5239, 8, 198, 220, 220, 220, 1441, 628, 198, 4299, 651, 62, 28764, 2867, 7, 6371, 11, 29472, 2599, 198, 220, 220, 220, 37227, 198, 220, 220, 220, 10472, 19449, 2882, 19016, 329, 17724, 13, 198, 220, 220, 220, 37227, 628, 220, 220, 220, 1303, 5345, 20150, 25, 198, 220, 220, 220, 24697, 796, 1391, 6, 19746, 12, 4906, 10354, 705, 31438, 14, 17752, 6, 92, 198, 220, 220, 220, 5128, 62, 27160, 796, 1391, 6, 325, 18596, 62, 13664, 10354, 718, 13, 19, 11, 198, 220, 220, 220, 220, 220, 220, 220, 220, 220, 220, 220, 220, 220, 220, 220, 220, 220, 220, 220, 705, 325, 18596, 62, 10394, 10354, 513, 13, 17, 11, 198, 220, 220, 220, 220, 220, 220, 220, 220, 220, 220, 220, 220, 220, 220, 220, 220, 220, 220, 220, 705, 6449, 282, 62, 13664, 10354, 604, 13, 20, 11, 198, 220, 220, 220, 220, 220, 220, 220, 220, 220, 220, 220, 220, 220, 220, 220, 220, 220, 220, 220, 705, 6449, 282, 62, 10394, 10354, 352, 13, 20, 92, 628, 220, 220, 220, 1303, 3497, 2882, 25, 198, 220, 220, 220, 2882, 796, 7007, 13, 7353, 7, 6371, 11, 33918, 28, 15414, 62, 27160, 11, 24697, 28, 50145, 8, 628, 220, 220, 220, 1303, 1002, 2882, 338, 3722, 318, 939, 25, 198, 220, 220, 220, 611, 2882, 13, 13376, 62, 8189, 6624, 7007, 13, 40148, 13, 482, 25, 198, 220, 220, 220, 220, 220, 220, 220, 1303, 20090, 3601, 2882, 25, 198, 220, 220, 220, 220, 220, 220, 220, 279, 4798, 13, 381, 22272, 7, 26209, 13, 17752, 28955, 628, 220, 220, 220, 220, 220, 220, 220, 1303, 12793, 2882, 656, 257, 19449, 2393, 25, 198, 220, 220, 220, 220, 220, 220, 220, 351, 1280, 7, 34345, 11, 705, 46569, 11537, 355, 5072, 25, 198, 220, 220, 220, 220, 220, 220, 220, 220, 220, 220, 220, 5072, 13, 13564, 7, 26209, 13, 5239, 8, 198, 220, 220, 220, 1441, 628, 198, 361, 11593, 3672, 834, 6624, 705, 834, 12417, 834, 10354, 198, 220, 220, 220, 1303, 9993, 503, 674, 19449, 2882, 4321, 263, 25, 198, 220, 220, 220, 651, 62, 17752, 10786, 4023, 1378, 36750, 25, 27641, 14, 15042, 14, 85, 15, 13, 15, 3256, 705, 26209, 13, 17752, 11537, 198, 220, 220, 220, 651, 62, 28764, 2867, 10786, 4023, 1378, 36750, 25, 27641, 14, 15042, 14, 85, 15, 13, 15, 14, 79, 17407, 3256, 705, 26209, 13, 17752, 11537, 198 ]
2.719495
713
import pybullet_envs from stable_baselines3 import SAC_LABER model = SAC_LABER('MlpPolicy', 'HalfCheetahBulletEnv-v0', verbose=1, tensorboard_log="results/long_SAC_LABER_HalfCheetahBullet/") model.learn(total_timesteps=3000000)
[ 11748, 12972, 15065, 1616, 62, 268, 14259, 198, 6738, 8245, 62, 12093, 20655, 18, 1330, 311, 2246, 62, 48780, 1137, 198, 198, 19849, 796, 311, 2246, 62, 48780, 1137, 10786, 44, 34431, 36727, 3256, 705, 31305, 7376, 316, 993, 33481, 1616, 4834, 85, 12, 85, 15, 3256, 15942, 577, 28, 16, 11, 11192, 273, 3526, 62, 6404, 2625, 43420, 14, 6511, 62, 50, 2246, 62, 48780, 1137, 62, 31305, 7376, 316, 993, 33481, 1616, 14, 4943, 198, 19849, 13, 35720, 7, 23350, 62, 16514, 395, 25386, 28, 18, 10535, 8, 198 ]
2.516484
91
# -*- coding: utf-8 -*- """ testapplehealthdata.py: tests for the applehealthdata.py Copyright (c) 2016 Nicholas J. Radcliffe Licence: MIT """ from __future__ import absolute_import from __future__ import division from __future__ import print_function from __future__ import unicode_literals import os import re import shutil import sys import unittest from collections import Counter from applehealthdata import (HealthDataExtractor, format_freqs, format_value, abbreviate, encode) CLEAN_UP = True VERBOSE = False def get_base_dir(): """ Return the directory containing this test file, which will (normally) be the applyhealthdata directory also containing the testdata dir. """ return os.path.split(os.path.abspath(__file__))[0] def get_testdata_dir(): """Return the full path to the testdata directory""" return os.path.join(get_base_dir(), 'testdata') def get_tmp_dir(): """Return the full path to the tmp directory""" return os.path.join(get_base_dir(), 'tmp') def remove_any_tmp_dir(): """ Remove the temporary directory if it exists. Returns its location either way. """ tmp_dir = get_tmp_dir() if os.path.exists(tmp_dir): shutil.rmtree(tmp_dir) return tmp_dir def make_tmp_dir(): """ Remove any existing tmp directory. Create empty tmp direcory. Return the location of the tmp dir. """ tmp_dir = remove_any_tmp_dir() os.mkdir(tmp_dir) return tmp_dir def copy_test_data(): """ Copy the test data export6s3sample.xml from testdata directory to tmp directory. """ tmp_dir = make_tmp_dir() name = 'export6s3sample.xml' in_xml_file = os.path.join(get_testdata_dir(), name) out_xml_file = os.path.join(get_tmp_dir(), name) shutil.copyfile(in_xml_file, out_xml_file) return out_xml_file if __name__ == '__main__': unittest.main()
[ 2, 532, 9, 12, 19617, 25, 3384, 69, 12, 23, 532, 9, 12, 198, 37811, 198, 9288, 18040, 13948, 7890, 13, 9078, 25, 5254, 329, 262, 17180, 13948, 7890, 13, 9078, 198, 198, 15269, 357, 66, 8, 1584, 20320, 449, 13, 5325, 33783, 198, 26656, 594, 25, 17168, 198, 37811, 198, 6738, 11593, 37443, 834, 1330, 4112, 62, 11748, 198, 6738, 11593, 37443, 834, 1330, 7297, 198, 6738, 11593, 37443, 834, 1330, 3601, 62, 8818, 198, 6738, 11593, 37443, 834, 1330, 28000, 1098, 62, 17201, 874, 198, 198, 11748, 28686, 198, 11748, 302, 198, 11748, 4423, 346, 198, 11748, 25064, 198, 11748, 555, 715, 395, 198, 198, 6738, 17268, 1330, 15034, 628, 198, 6738, 17180, 13948, 7890, 1330, 357, 18081, 6601, 11627, 40450, 11, 198, 220, 220, 220, 220, 220, 220, 220, 220, 220, 220, 220, 220, 220, 220, 220, 220, 220, 220, 220, 220, 220, 220, 220, 220, 220, 220, 220, 220, 5794, 62, 19503, 48382, 11, 5794, 62, 8367, 11, 198, 220, 220, 220, 220, 220, 220, 220, 220, 220, 220, 220, 220, 220, 220, 220, 220, 220, 220, 220, 220, 220, 220, 220, 220, 220, 220, 220, 220, 37640, 378, 11, 37773, 8, 198, 198, 29931, 1565, 62, 8577, 796, 6407, 198, 5959, 33, 14058, 796, 10352, 628, 198, 4299, 651, 62, 8692, 62, 15908, 33529, 198, 220, 220, 220, 37227, 198, 220, 220, 220, 8229, 262, 8619, 7268, 428, 1332, 2393, 11, 198, 220, 220, 220, 543, 481, 357, 27237, 453, 8, 307, 262, 4174, 13948, 7890, 8619, 198, 220, 220, 220, 635, 7268, 262, 1332, 7890, 26672, 13, 198, 220, 220, 220, 37227, 198, 220, 220, 220, 1441, 28686, 13, 6978, 13, 35312, 7, 418, 13, 6978, 13, 397, 2777, 776, 7, 834, 7753, 834, 4008, 58, 15, 60, 628, 198, 4299, 651, 62, 9288, 7890, 62, 15908, 33529, 198, 220, 220, 220, 37227, 13615, 262, 1336, 3108, 284, 262, 1332, 7890, 8619, 37811, 198, 220, 220, 220, 1441, 28686, 13, 6978, 13, 22179, 7, 1136, 62, 8692, 62, 15908, 22784, 705, 9288, 7890, 11537, 628, 198, 4299, 651, 62, 22065, 62, 15908, 33529, 198, 220, 220, 220, 37227, 13615, 262, 1336, 3108, 284, 262, 45218, 8619, 37811, 198, 220, 220, 220, 1441, 28686, 13, 6978, 13, 22179, 7, 1136, 62, 8692, 62, 15908, 22784, 705, 22065, 11537, 628, 198, 4299, 4781, 62, 1092, 62, 22065, 62, 15908, 33529, 198, 220, 220, 220, 37227, 198, 220, 220, 220, 17220, 262, 8584, 8619, 611, 340, 7160, 13, 198, 220, 220, 220, 16409, 663, 4067, 2035, 835, 13, 198, 220, 220, 220, 37227, 198, 220, 220, 220, 45218, 62, 15908, 796, 651, 62, 22065, 62, 15908, 3419, 198, 220, 220, 220, 611, 28686, 13, 6978, 13, 1069, 1023, 7, 22065, 62, 15908, 2599, 198, 220, 220, 220, 220, 220, 220, 220, 4423, 346, 13, 81, 16762, 631, 7, 22065, 62, 15908, 8, 198, 220, 220, 220, 1441, 45218, 62, 15908, 628, 198, 4299, 787, 62, 22065, 62, 15908, 33529, 198, 220, 220, 220, 37227, 198, 220, 220, 220, 17220, 597, 4683, 45218, 8619, 13, 198, 220, 220, 220, 13610, 6565, 45218, 19958, 66, 652, 13, 198, 220, 220, 220, 8229, 262, 4067, 286, 262, 45218, 26672, 13, 198, 220, 220, 220, 37227, 198, 220, 220, 220, 45218, 62, 15908, 796, 4781, 62, 1092, 62, 22065, 62, 15908, 3419, 198, 220, 220, 220, 28686, 13, 28015, 15908, 7, 22065, 62, 15908, 8, 198, 220, 220, 220, 1441, 45218, 62, 15908, 628, 198, 4299, 4866, 62, 9288, 62, 7890, 33529, 198, 220, 220, 220, 37227, 198, 220, 220, 220, 17393, 262, 1332, 1366, 10784, 21, 82, 18, 39873, 13, 19875, 422, 1332, 7890, 8619, 198, 220, 220, 220, 284, 45218, 8619, 13, 198, 220, 220, 220, 37227, 198, 220, 220, 220, 45218, 62, 15908, 796, 787, 62, 22065, 62, 15908, 3419, 198, 220, 220, 220, 1438, 796, 705, 39344, 21, 82, 18, 39873, 13, 19875, 6, 198, 220, 220, 220, 287, 62, 19875, 62, 7753, 796, 28686, 13, 6978, 13, 22179, 7, 1136, 62, 9288, 7890, 62, 15908, 22784, 1438, 8, 198, 220, 220, 220, 503, 62, 19875, 62, 7753, 796, 28686, 13, 6978, 13, 22179, 7, 1136, 62, 22065, 62, 15908, 22784, 1438, 8, 198, 220, 220, 220, 4423, 346, 13, 30073, 7753, 7, 259, 62, 19875, 62, 7753, 11, 503, 62, 19875, 62, 7753, 8, 198, 220, 220, 220, 1441, 503, 62, 19875, 62, 7753, 628, 628, 198, 361, 11593, 3672, 834, 6624, 705, 834, 12417, 834, 10354, 198, 220, 220, 220, 555, 715, 395, 13, 12417, 3419, 198 ]
2.610372
752
import unittest from datetime import date from controller.books import Book, BookRead if __name__ == "__main__": unittest.main()
[ 11748, 555, 715, 395, 198, 6738, 4818, 8079, 1330, 3128, 198, 198, 6738, 10444, 13, 12106, 1330, 4897, 11, 4897, 5569, 628, 628, 198, 361, 11593, 3672, 834, 6624, 366, 834, 12417, 834, 1298, 198, 220, 220, 220, 555, 715, 395, 13, 12417, 3419, 198 ]
3.066667
45
from ixnetwork_restpy.base import Base from ixnetwork_restpy.files import Files
[ 6738, 220, 844, 27349, 62, 2118, 9078, 13, 8692, 1330, 7308, 198, 6738, 220, 844, 27349, 62, 2118, 9078, 13, 16624, 1330, 13283, 628 ]
3.375
24
import pytest @pytest.yield_fixture(scope="module") @pytest.yield_fixture(scope="module") @pytest.yield_fixture(scope="module")
[ 11748, 12972, 9288, 628, 198, 31, 9078, 9288, 13, 88, 1164, 62, 69, 9602, 7, 29982, 2625, 21412, 4943, 628, 198, 31, 9078, 9288, 13, 88, 1164, 62, 69, 9602, 7, 29982, 2625, 21412, 4943, 628, 198, 31, 9078, 9288, 13, 88, 1164, 62, 69, 9602, 7, 29982, 2625, 21412, 4943, 198 ]
2.576923
52
import threading import os.path import time from blueThread import MainBlue # class myThread (threading.Thread): # def __init__(self, threadID, name, counter): # threading.Thread.__init__(self) # self.threadID = threadID # self.name = name # self.counter = counter # def run(self): # print("Starting " + self.name) # print_time(self.name, 5, self.counter) # print("Exiting " + self.name) run = True foo = [False] fileName = "" def LookForFile(strToFind, path): """ function repeatedly look for a file """ while run: MainBlue(foo) time.sleep(1) print("exiting file thread!") def LookForStop(strToFind, path): """ function repeatedly look for a file """ global run count = 0 filePath = path + strToFind while run: count += 1 if os.path.exists(filePath): run = False print("{0} FOUND {1} at {2} [{3}]".format(t2.getName(), strToFind, filePath, count)) else: print("{0} not found {1} at {2} [{3}]".format(t2.getName(), strToFind, filePath, count)) time.sleep(1) print("exiting stop thread!") if __name__ == "__main__": # creating thread t1 = threading.Thread(target=LookForFile, name="THREAD_Finder", args=("rain","../"), daemon=True) # t2 = threading.Thread(name="THREAD_Stopper", target=LookForStop, args=("stop","../"), daemon=True) # starting thread 1 t1.start() # starting thread 2 # t2.start() # while run: # print("doing nothing...") # time.sleep(10) input("Press Enter to flip foo") if foo[0]: foo[0] = False else: foo[0] = True input("Press Enter to exit") run = False # wait until thread 1 is completely executed t1.join() # wait until thread 2 is completely executed # t2.join() # both threads completely executed print("Done!")
[ 11748, 4704, 278, 201, 198, 11748, 28686, 13, 6978, 201, 198, 11748, 640, 201, 198, 6738, 4171, 16818, 1330, 8774, 14573, 201, 198, 201, 198, 220, 220, 201, 198, 2, 1398, 616, 16818, 357, 16663, 278, 13, 16818, 2599, 201, 198, 2, 220, 220, 825, 11593, 15003, 834, 7, 944, 11, 4704, 2389, 11, 1438, 11, 3753, 2599, 201, 198, 2, 220, 220, 220, 220, 4704, 278, 13, 16818, 13, 834, 15003, 834, 7, 944, 8, 201, 198, 2, 220, 220, 220, 220, 2116, 13, 16663, 2389, 796, 4704, 2389, 201, 198, 2, 220, 220, 220, 220, 2116, 13, 3672, 796, 1438, 201, 198, 2, 220, 220, 220, 220, 2116, 13, 24588, 796, 3753, 201, 198, 2, 220, 220, 825, 1057, 7, 944, 2599, 201, 198, 2, 220, 220, 220, 220, 3601, 7203, 22851, 366, 1343, 2116, 13, 3672, 8, 201, 198, 2, 220, 220, 220, 220, 3601, 62, 2435, 7, 944, 13, 3672, 11, 642, 11, 2116, 13, 24588, 8, 201, 198, 2, 220, 220, 220, 220, 3601, 7203, 3109, 1780, 366, 1343, 2116, 13, 3672, 8, 201, 198, 220, 220, 220, 220, 201, 198, 5143, 796, 6407, 201, 198, 21943, 796, 685, 25101, 60, 201, 198, 7753, 5376, 796, 13538, 201, 198, 4299, 6803, 1890, 8979, 7, 2536, 2514, 16742, 11, 3108, 2599, 201, 198, 220, 220, 220, 37227, 201, 198, 220, 220, 220, 2163, 7830, 804, 329, 257, 2393, 201, 198, 220, 220, 220, 37227, 201, 198, 220, 220, 220, 981, 1057, 25, 201, 198, 220, 220, 220, 220, 220, 8774, 14573, 7, 21943, 8, 201, 198, 220, 220, 220, 220, 220, 640, 13, 42832, 7, 16, 8, 201, 198, 220, 220, 220, 3601, 7203, 1069, 1780, 2393, 4704, 2474, 8, 201, 198, 201, 198, 4299, 6803, 1890, 19485, 7, 2536, 2514, 16742, 11, 3108, 2599, 201, 198, 220, 220, 220, 37227, 201, 198, 220, 220, 220, 2163, 7830, 804, 329, 257, 2393, 201, 198, 220, 220, 220, 37227, 201, 198, 220, 220, 220, 3298, 1057, 201, 198, 220, 220, 220, 954, 796, 657, 201, 198, 220, 220, 220, 2393, 15235, 796, 3108, 1343, 965, 2514, 16742, 201, 198, 220, 220, 220, 981, 1057, 25, 201, 198, 220, 220, 220, 220, 220, 954, 15853, 352, 201, 198, 220, 220, 220, 220, 220, 611, 28686, 13, 6978, 13, 1069, 1023, 7, 7753, 15235, 2599, 201, 198, 220, 220, 220, 220, 220, 220, 220, 1057, 796, 10352, 201, 198, 220, 220, 220, 220, 220, 220, 220, 3601, 7203, 90, 15, 92, 376, 15919, 1391, 16, 92, 379, 1391, 17, 92, 685, 90, 18, 92, 60, 1911, 18982, 7, 83, 17, 13, 1136, 5376, 22784, 965, 2514, 16742, 11, 2393, 15235, 11, 954, 4008, 201, 198, 220, 220, 220, 220, 220, 2073, 25, 201, 198, 220, 220, 220, 220, 220, 220, 220, 3601, 7203, 90, 15, 92, 407, 1043, 1391, 16, 92, 379, 1391, 17, 92, 685, 90, 18, 92, 60, 1911, 18982, 7, 83, 17, 13, 1136, 5376, 22784, 965, 2514, 16742, 11, 2393, 15235, 11, 954, 4008, 201, 198, 220, 220, 220, 220, 220, 640, 13, 42832, 7, 16, 8, 201, 198, 220, 220, 220, 3601, 7203, 1069, 1780, 2245, 4704, 2474, 8, 201, 198, 220, 220, 201, 198, 361, 11593, 3672, 834, 6624, 366, 834, 12417, 834, 1298, 201, 198, 201, 198, 220, 220, 220, 1303, 4441, 4704, 201, 198, 220, 220, 220, 256, 16, 796, 4704, 278, 13, 16818, 7, 16793, 28, 8567, 1890, 8979, 11, 1438, 2625, 4221, 15675, 62, 37, 5540, 1600, 26498, 28, 7203, 3201, 2430, 40720, 12340, 33386, 28, 17821, 8, 201, 198, 220, 220, 220, 1303, 256, 17, 796, 4704, 278, 13, 16818, 7, 3672, 2625, 4221, 15675, 62, 1273, 78, 2848, 1600, 2496, 28, 8567, 1890, 19485, 11, 26498, 28, 7203, 11338, 2430, 40720, 12340, 33386, 28, 17821, 8, 201, 198, 220, 220, 201, 198, 220, 220, 220, 1303, 3599, 4704, 352, 201, 198, 220, 220, 220, 256, 16, 13, 9688, 3419, 201, 198, 220, 220, 220, 1303, 3599, 4704, 362, 201, 198, 220, 220, 220, 1303, 256, 17, 13, 9688, 3419, 201, 198, 220, 220, 220, 1303, 981, 1057, 25, 201, 198, 220, 220, 220, 1303, 220, 220, 3601, 7203, 19631, 2147, 9313, 8, 201, 198, 220, 220, 220, 1303, 220, 220, 640, 13, 42832, 7, 940, 8, 201, 198, 220, 220, 220, 5128, 7203, 13800, 6062, 284, 14283, 22944, 4943, 201, 198, 220, 220, 220, 611, 22944, 58, 15, 5974, 201, 198, 220, 220, 220, 220, 220, 22944, 58, 15, 60, 796, 10352, 201, 198, 220, 220, 220, 2073, 25, 201, 198, 220, 220, 220, 220, 220, 22944, 58, 15, 60, 796, 6407, 201, 198, 220, 220, 220, 5128, 7203, 13800, 6062, 284, 8420, 4943, 201, 198, 220, 220, 220, 1057, 796, 10352, 201, 198, 201, 198, 220, 220, 220, 1303, 4043, 1566, 4704, 352, 318, 3190, 10945, 201, 198, 220, 220, 220, 256, 16, 13, 22179, 3419, 201, 198, 220, 220, 220, 1303, 4043, 1566, 4704, 362, 318, 3190, 10945, 201, 198, 220, 220, 220, 1303, 256, 17, 13, 22179, 3419, 201, 198, 220, 220, 201, 198, 220, 220, 220, 1303, 1111, 14390, 3190, 10945, 201, 198, 220, 220, 220, 3601, 7203, 45677, 2474, 8 ]
2.299534
858
import time from datetime import datetime from datetime import timedelta from uuid import uuid4 as uuid from activitystreams import parse from dino import environ from dino.auth.redis import AuthRedis from dino.cache.redis import CacheRedis from dino.config import ApiActions, RedisKeys from dino.config import ConfigKeys from dino.config import SessionKeys from dino.config import UserKeys from dino.db.rdbms.handler import DatabaseRdbms from dino.environ import ConfigDict from dino.environ import GNEnvironment from dino.exceptions import ChannelExistsException from dino.exceptions import ChannelNameExistsException from dino.exceptions import EmptyChannelNameException from dino.exceptions import EmptyRoomNameException from dino.exceptions import InvalidAclTypeException from dino.exceptions import InvalidApiActionException from dino.exceptions import NoSuchChannelException from dino.exceptions import NoSuchRoomException from dino.exceptions import NoSuchUserException from dino.exceptions import RoomExistsException from dino.exceptions import RoomNameExistsForChannelException from dino.exceptions import UserExistsException from dino.exceptions import ValidationException from dino.validation.acl import AclDisallowValidator from dino.validation.acl import AclIsAdminValidator from dino.validation.acl import AclIsSuperUserValidator from dino.validation.acl import AclRangeValidator from dino.validation.acl import AclSameChannelValidator from dino.validation.acl import AclSameRoomValidator from dino.validation.acl import AclStrInCsvValidator from test.base import BaseTest
[ 11748, 640, 198, 6738, 4818, 8079, 1330, 4818, 8079, 198, 6738, 4818, 8079, 1330, 28805, 12514, 198, 6738, 334, 27112, 1330, 334, 27112, 19, 355, 334, 27112, 198, 198, 6738, 3842, 5532, 82, 1330, 21136, 198, 198, 6738, 288, 2879, 1330, 551, 2268, 198, 6738, 288, 2879, 13, 18439, 13, 445, 271, 1330, 26828, 7738, 271, 198, 6738, 288, 2879, 13, 23870, 13, 445, 271, 1330, 34088, 7738, 271, 198, 6738, 288, 2879, 13, 11250, 1330, 5949, 72, 32, 2733, 11, 2297, 271, 40729, 198, 6738, 288, 2879, 13, 11250, 1330, 17056, 40729, 198, 6738, 288, 2879, 13, 11250, 1330, 23575, 40729, 198, 6738, 288, 2879, 13, 11250, 1330, 11787, 40729, 198, 6738, 288, 2879, 13, 9945, 13, 4372, 65, 907, 13, 30281, 1330, 24047, 49, 9945, 907, 198, 6738, 288, 2879, 13, 268, 2268, 1330, 17056, 35, 713, 198, 6738, 288, 2879, 13, 268, 2268, 1330, 15484, 31441, 198, 6738, 288, 2879, 13, 1069, 11755, 1330, 11102, 3109, 1023, 16922, 198, 6738, 288, 2879, 13, 1069, 11755, 1330, 11102, 5376, 3109, 1023, 16922, 198, 6738, 288, 2879, 13, 1069, 11755, 1330, 33523, 29239, 5376, 16922, 198, 6738, 288, 2879, 13, 1069, 11755, 1330, 33523, 41178, 5376, 16922, 198, 6738, 288, 2879, 13, 1069, 11755, 1330, 17665, 32, 565, 6030, 16922, 198, 6738, 288, 2879, 13, 1069, 11755, 1330, 17665, 32, 14415, 12502, 16922, 198, 6738, 288, 2879, 13, 1069, 11755, 1330, 1400, 16678, 29239, 16922, 198, 6738, 288, 2879, 13, 1069, 11755, 1330, 1400, 16678, 41178, 16922, 198, 6738, 288, 2879, 13, 1069, 11755, 1330, 1400, 16678, 12982, 16922, 198, 6738, 288, 2879, 13, 1069, 11755, 1330, 10096, 3109, 1023, 16922, 198, 6738, 288, 2879, 13, 1069, 11755, 1330, 10096, 5376, 3109, 1023, 1890, 29239, 16922, 198, 6738, 288, 2879, 13, 1069, 11755, 1330, 11787, 3109, 1023, 16922, 198, 6738, 288, 2879, 13, 1069, 11755, 1330, 3254, 24765, 16922, 198, 6738, 288, 2879, 13, 12102, 341, 13, 37779, 1330, 317, 565, 7279, 12154, 47139, 1352, 198, 6738, 288, 2879, 13, 12102, 341, 13, 37779, 1330, 317, 565, 3792, 46787, 47139, 1352, 198, 6738, 288, 2879, 13, 12102, 341, 13, 37779, 1330, 317, 565, 3792, 12442, 12982, 47139, 1352, 198, 6738, 288, 2879, 13, 12102, 341, 13, 37779, 1330, 317, 565, 17257, 47139, 1352, 198, 6738, 288, 2879, 13, 12102, 341, 13, 37779, 1330, 317, 565, 30556, 29239, 47139, 1352, 198, 6738, 288, 2879, 13, 12102, 341, 13, 37779, 1330, 317, 565, 30556, 41178, 47139, 1352, 198, 6738, 288, 2879, 13, 12102, 341, 13, 37779, 1330, 317, 565, 13290, 818, 34, 21370, 47139, 1352, 198, 6738, 1332, 13, 8692, 1330, 7308, 14402, 628 ]
3.674365
433
"""migrate workbench state enum Revision ID: cfd1c43b5d33 Revises: c8a7073deebb Create Date: 2020-11-17 16:42:32.511722+00:00 """ from alembic import op import sqlalchemy as sa # revision identifiers, used by Alembic. revision = 'cfd1c43b5d33' down_revision = 'c8a7073deebb' branch_labels = None depends_on = None
[ 37811, 76, 42175, 670, 26968, 1181, 33829, 198, 198, 18009, 1166, 4522, 25, 269, 16344, 16, 66, 3559, 65, 20, 67, 2091, 198, 18009, 2696, 25, 269, 23, 64, 2154, 4790, 67, 1453, 11848, 198, 16447, 7536, 25, 12131, 12, 1157, 12, 1558, 1467, 25, 3682, 25, 2624, 13, 20, 17657, 1828, 10, 405, 25, 405, 198, 198, 37811, 198, 6738, 31341, 2022, 291, 1330, 1034, 198, 11748, 44161, 282, 26599, 355, 473, 628, 198, 2, 18440, 42814, 11, 973, 416, 9300, 2022, 291, 13, 198, 260, 10178, 796, 705, 12993, 67, 16, 66, 3559, 65, 20, 67, 2091, 6, 198, 2902, 62, 260, 10178, 796, 705, 66, 23, 64, 2154, 4790, 67, 1453, 11848, 6, 198, 1671, 3702, 62, 23912, 1424, 796, 6045, 198, 10378, 2412, 62, 261, 796, 6045, 628, 198 ]
2.406015
133
import json fn = open('../static/alderman.js', 'w') #add alderman boundaries variable json_file = open('../maps/alderman.geojson') geo_json = json.load(json_file) fn.write('var alderman_boundaries = ') fn.write(json.dumps(geo_json)) fn.write(';\n\n') json_file.close()
[ 11748, 33918, 198, 198, 22184, 796, 1280, 10786, 40720, 12708, 14, 282, 1082, 805, 13, 8457, 3256, 705, 86, 11537, 198, 198, 2, 2860, 257, 335, 2224, 13215, 7885, 198, 17752, 62, 7753, 796, 1280, 10786, 40720, 31803, 14, 282, 1082, 805, 13, 469, 13210, 1559, 11537, 198, 469, 78, 62, 17752, 796, 33918, 13, 2220, 7, 17752, 62, 7753, 8, 198, 22184, 13, 13564, 10786, 7785, 257, 335, 2224, 62, 7784, 3166, 796, 705, 8, 198, 22184, 13, 13564, 7, 17752, 13, 67, 8142, 7, 469, 78, 62, 17752, 4008, 198, 22184, 13, 13564, 10786, 26, 59, 77, 59, 77, 11537, 198, 17752, 62, 7753, 13, 19836, 3419 ]
2.477064
109
# tables.py class MortalityTable: """mortalitytable is a matrix, by age and duration.""" class MortalityImprovementTable: """MortalityImprovementTable is a matrix, by age and year.""" class RangeTable: """range table"""
[ 2, 8893, 13, 9078, 201, 198, 201, 198, 201, 198, 201, 198, 4871, 10788, 1483, 10962, 25, 201, 198, 220, 220, 220, 37227, 76, 28337, 11487, 318, 257, 17593, 11, 416, 2479, 290, 9478, 526, 15931, 201, 198, 220, 220, 220, 220, 201, 198, 4871, 10788, 1483, 47531, 434, 10962, 25, 201, 198, 220, 220, 220, 37227, 44, 28337, 47531, 434, 10962, 318, 257, 17593, 11, 416, 2479, 290, 614, 526, 15931, 201, 198, 220, 220, 220, 220, 201, 198, 4871, 13667, 10962, 25, 201, 198, 220, 220, 220, 37227, 9521, 3084, 37811, 201, 198, 201, 198 ]
2.670103
97
"""Mathematical helper functions.""" def normalize(array): """Normalize the array. Set all the values betwwen 0 and 1. 0 corresponds to the min value and 1 the max. If the normalization cannot occur, will return the array. """ min_ = min(array) max_ = max(array) return ( (array - min_) / (max_ - min_) # Normalize if min_ != max_ else array / (max_ if max_ > 0 else 1) # Avoid divide by 0 )
[ 37811, 19044, 10024, 605, 31904, 5499, 526, 15931, 628, 198, 4299, 3487, 1096, 7, 18747, 2599, 198, 220, 220, 220, 37227, 26447, 1096, 262, 7177, 13, 628, 220, 220, 220, 5345, 477, 262, 3815, 731, 1383, 268, 657, 290, 352, 13, 198, 220, 220, 220, 657, 24866, 284, 262, 949, 1988, 290, 352, 262, 3509, 13, 198, 220, 220, 220, 1002, 262, 3487, 1634, 2314, 3051, 11, 481, 1441, 262, 7177, 13, 198, 220, 220, 220, 37227, 198, 220, 220, 220, 949, 62, 796, 949, 7, 18747, 8, 198, 220, 220, 220, 3509, 62, 796, 3509, 7, 18747, 8, 198, 220, 220, 220, 1441, 357, 198, 220, 220, 220, 220, 220, 220, 220, 357, 18747, 532, 949, 62, 8, 1220, 357, 9806, 62, 532, 949, 62, 8, 220, 1303, 14435, 1096, 198, 220, 220, 220, 220, 220, 220, 220, 611, 949, 62, 14512, 3509, 62, 2073, 198, 220, 220, 220, 220, 220, 220, 220, 7177, 1220, 357, 9806, 62, 611, 3509, 62, 1875, 657, 2073, 352, 8, 220, 1303, 24390, 14083, 416, 657, 198, 220, 220, 220, 1267, 198 ]
2.553073
179
nome = input('Insira nome completo: ').strip() print('Possui "Silva"?', 'silva' in nome.lower()) input()
[ 77, 462, 796, 5128, 10786, 20376, 8704, 299, 462, 1224, 1462, 25, 705, 737, 36311, 3419, 198, 4798, 10786, 47, 793, 9019, 366, 15086, 6862, 13984, 3256, 705, 18217, 6862, 6, 287, 299, 462, 13, 21037, 28955, 198, 15414, 3419, 198 ]
2.560976
41
import torch import torch.nn as nn __all__ = ['ResNet', 'resnet18', 'resnet34', 'resnet50', 'resnet101', 'resnet152'] def conv3x3(in_planes, out_planes, **kwargs): """3x3 convolution with padding""" kwargs['kernel_size'] = 3 kwargs['padding'] = 1 kwargs['bias'] = False return nn.Conv2d(in_planes, out_planes, **kwargs) def conv1x1(in_planes, out_planes, **kwargs): """1x1 convolution""" kwargs['kernel_size'] = 1 kwargs['bias'] = False return nn.Conv2d(in_planes, out_planes, **kwargs) class BasicBlock(nn.Module): """BasicBlock""" expansion = 1 class Bottleneck(nn.Module): """Bottleneck""" expansion = 4 class ResNet(nn.Module): """ResNet""" def resnet18(num_classes=1000, **kwargs): """resnet18""" return ResNet([2, 2, 2, 2], num_classes, BasicBlock) def resnet34(num_classes=1000, **kwargs): """resnet34""" return ResNet([3, 4, 6, 3], num_classes, BasicBlock) def resnet50(num_classes=1000, **kwargs): """resnet50""" return ResNet([3, 4, 6, 3], num_classes, Bottleneck) def resnet101(num_classes=1000, **kwargs): """resnet101""" return ResNet([3, 4, 23, 3], num_classes, Bottleneck) def resnet152(num_classes=1000, **kwargs): """resnet152""" return ResNet([3, 8, 36, 3], num_classes, Bottleneck)
[ 11748, 28034, 198, 11748, 28034, 13, 20471, 355, 299, 77, 198, 198, 834, 439, 834, 796, 37250, 4965, 7934, 3256, 705, 411, 3262, 1507, 3256, 705, 411, 3262, 2682, 3256, 705, 411, 3262, 1120, 3256, 705, 411, 3262, 8784, 3256, 705, 411, 3262, 17827, 20520, 198, 198, 4299, 3063, 18, 87, 18, 7, 259, 62, 22587, 11, 503, 62, 22587, 11, 12429, 46265, 22046, 2599, 198, 220, 220, 220, 37227, 18, 87, 18, 3063, 2122, 351, 24511, 37811, 198, 220, 220, 220, 479, 86, 22046, 17816, 33885, 62, 7857, 20520, 796, 513, 198, 220, 220, 220, 479, 86, 22046, 17816, 39231, 20520, 796, 352, 198, 220, 220, 220, 479, 86, 22046, 17816, 65, 4448, 20520, 796, 10352, 198, 220, 220, 220, 1441, 299, 77, 13, 3103, 85, 17, 67, 7, 259, 62, 22587, 11, 503, 62, 22587, 11, 12429, 46265, 22046, 8, 198, 198, 4299, 3063, 16, 87, 16, 7, 259, 62, 22587, 11, 503, 62, 22587, 11, 12429, 46265, 22046, 2599, 198, 220, 220, 220, 37227, 16, 87, 16, 3063, 2122, 37811, 198, 220, 220, 220, 479, 86, 22046, 17816, 33885, 62, 7857, 20520, 796, 352, 198, 220, 220, 220, 479, 86, 22046, 17816, 65, 4448, 20520, 796, 10352, 198, 220, 220, 220, 1441, 299, 77, 13, 3103, 85, 17, 67, 7, 259, 62, 22587, 11, 503, 62, 22587, 11, 12429, 46265, 22046, 8, 198, 198, 4871, 14392, 12235, 7, 20471, 13, 26796, 2599, 198, 220, 220, 220, 37227, 26416, 12235, 37811, 198, 220, 220, 220, 7118, 796, 352, 198, 220, 220, 220, 220, 198, 4871, 14835, 43163, 7, 20471, 13, 26796, 2599, 198, 220, 220, 220, 37227, 28653, 43163, 37811, 198, 220, 220, 220, 7118, 796, 604, 198, 220, 220, 220, 220, 198, 4871, 1874, 7934, 7, 20471, 13, 26796, 2599, 198, 220, 220, 220, 37227, 4965, 7934, 37811, 198, 220, 220, 220, 220, 198, 4299, 581, 3262, 1507, 7, 22510, 62, 37724, 28, 12825, 11, 12429, 46265, 22046, 2599, 198, 220, 220, 220, 37227, 411, 3262, 1507, 37811, 198, 220, 220, 220, 1441, 1874, 7934, 26933, 17, 11, 362, 11, 362, 11, 362, 4357, 997, 62, 37724, 11, 14392, 12235, 8, 198, 198, 4299, 581, 3262, 2682, 7, 22510, 62, 37724, 28, 12825, 11, 12429, 46265, 22046, 2599, 198, 220, 220, 220, 37227, 411, 3262, 2682, 37811, 198, 220, 220, 220, 1441, 1874, 7934, 26933, 18, 11, 604, 11, 718, 11, 513, 4357, 997, 62, 37724, 11, 14392, 12235, 8, 198, 198, 4299, 581, 3262, 1120, 7, 22510, 62, 37724, 28, 12825, 11, 12429, 46265, 22046, 2599, 198, 220, 220, 220, 37227, 411, 3262, 1120, 37811, 198, 220, 220, 220, 1441, 1874, 7934, 26933, 18, 11, 604, 11, 718, 11, 513, 4357, 997, 62, 37724, 11, 14835, 43163, 8, 198, 198, 4299, 581, 3262, 8784, 7, 22510, 62, 37724, 28, 12825, 11, 12429, 46265, 22046, 2599, 198, 220, 220, 220, 37227, 411, 3262, 8784, 37811, 198, 220, 220, 220, 1441, 1874, 7934, 26933, 18, 11, 604, 11, 2242, 11, 513, 4357, 997, 62, 37724, 11, 14835, 43163, 8, 198, 198, 4299, 581, 3262, 17827, 7, 22510, 62, 37724, 28, 12825, 11, 12429, 46265, 22046, 2599, 198, 220, 220, 220, 37227, 411, 3262, 17827, 37811, 198, 220, 220, 220, 1441, 1874, 7934, 26933, 18, 11, 807, 11, 4570, 11, 513, 4357, 997, 62, 37724, 11, 14835, 43163, 8 ]
2.398182
550
from modelon.impact.client import ( SimpleFMUExperimentDefinition, SimpleModelicaExperimentDefinition, Range, Choices, SimpleExperimentExtension, ) import pytest from modelon.impact.client import exceptions from tests.impact.client.fixtures import *
[ 6738, 2746, 261, 13, 48240, 13, 16366, 1330, 357, 198, 220, 220, 220, 17427, 23264, 52, 20468, 3681, 36621, 11, 198, 220, 220, 220, 17427, 17633, 3970, 20468, 3681, 36621, 11, 198, 220, 220, 220, 13667, 11, 198, 220, 220, 220, 10031, 1063, 11, 198, 220, 220, 220, 17427, 20468, 3681, 11627, 3004, 11, 198, 8, 198, 11748, 12972, 9288, 198, 6738, 2746, 261, 13, 48240, 13, 16366, 1330, 13269, 198, 198, 6738, 5254, 13, 48240, 13, 16366, 13, 69, 25506, 1330, 1635, 628, 628 ]
3.223529
85
#coding:utf-8 import pymongo import records
[ 2, 66, 7656, 25, 40477, 12, 23, 198, 11748, 279, 4948, 25162, 198, 11748, 4406, 628 ]
2.8125
16
# ou-tm351 - `nb_pub_utils` #GOTCHA - Python on Mac logging in to Github: https://stackoverflow.com/a/42098127/454773 import click import os import shutil import zipfile import humanize import datetime import github from tabulate import tabulate from shlex import quote import subprocess def listify(item): ''' If presented with a string and a list is required, make a list... ''' item = [] if item is None else item #We may be passed a tuple - in which case, listify... item = list(item) if isinstance(item,(list,tuple)) else [item] return item def exclude_hidden_items(itemlist, exclude_hidden=True): ''' Exclude hidden items from ziplist ''' if exclude_hidden: rmlist=[] for x in itemlist: if x.startswith('.'): rmlist.append(x) for x in rmlist: itemlist.remove(x) def exclude_items(itemlist, excludes, exclude_hidden=True, ipynb_only=False): ''' Exclude items from ziplist ''' for xd in set(itemlist).intersection(excludes): itemlist.remove(xd) if ipynb_only: for i in [_i for _i in itemlist if not _i.endswith("ipynb")]: itemlist.remove(i) if exclude_hidden: exclude_hidden_items(itemlist) def notebookTest(path=None, filename=None, dir_excludes=None, file_excludes=None): ''' Run notebook tests over explicitly named files and directories. ''' #Could probably define this recursively to handle mulitple paths/filenames... sanitiser = """[regex1] regex: <graphviz.files.Source at [^>]*> replace: <graphviz.files.Source> [regex2] regex: CPU times: .* replace: CPU times: CPUTIME [regex3] regex: Wall time: .* replace: Wall time: WALLTIME [regex4] regex: .* per loop \(mean ± std. dev. of .* runs, .* loops each\) replace: TIMEIT_REPORT """ #tmp_fn = "_sanitise_cfg.cfg" #with open(tmp_fn, "w") as f: # f.write(sanitiser) #cmd=f'py.test --nbval-sanitize-with {tmp_fn} ' cmd=f'py.test ' file_excludes = listify(file_excludes) for d in listify(dir_excludes): cmd = cmd + ' --ignore={} '.format(quote(d)) print("*Not testing in directory: {}*".format(d)) cmd = cmd+' --nbval ' ## WARNING - TO DO - if we are running this from a notebook, also exclude path=='.' if path is None and filename is None: #Process current directory return cli_command(cmd) elif filename: #Process file(s) in directory if isinstance(filename, list): for _filename in filename: cmd = '{cmd} {filename}'.format(cmd=cmd, filename=pathmaker(path, quote(_filename))) resp=cli_command(cmd) else: cmd = '{cmd} {filename}'.format(cmd=cmd, filename=pathmaker(path, quote(filename))) resp=cli_command(cmd) return resp else: #Process files in path #If we pass a directory name in then the test will be run over all files in the directory #py.test accumulates the test responses resps = [] for singlepath in listify(path): for dirname, subdirs, files in os.walk(singlepath): exclude_items(subdirs, dir_excludes) exclude_items(files, file_excludes, ipynb_only=True) print('Processing directory: {}'.format(dirname)) with click.progressbar(files) as bar: for filename in bar: filepathname=os.path.join(dirname, filename) cmd = '{cmd} {path}'.format(cmd=cmd, path=quote(filepathname)) resps.append( cli_command(cmd) ) #for singlepath in listify(path): # print("\nTesting in directory: {}".format(singlepath)) # if singlepath=='.': # print('**DO NOT test in current directory from a notebook**') # cmd = '{cmd} {path}'.format(cmd=cmd, path=quote(singlepath)) # resps.append( cli_command(cmd) ) os.unlink(tmp_fn) return resps def notebookProcessor(notebook, mode=None, outpath=None, outfile=None, inplace=True): ''' Clear notebook output cells. Process a single notebook, clearing cell outputs running cells until a warning, or running all cells despite warnings. Processed notebooks can be written to a specified directory or rendered inplace. ''' if mode is None: return (-1, 'Mode not specified.') if outpath is not None and not os.path.exists(outpath): os.makedirs(outpath) if outfile is not None: outpath = '/'.join([outpath,outfile]) if outpath is not None else outfile cmd='jupyter nbconvert --to notebook' if mode in ['clearOutput', 'clearOutputTest' ]: cmd = '{cmd} --ClearOutputPreprocessor.enabled=True'.format(cmd=cmd) elif mode == 'run': cmd = '{cmd} --execute'.format(cmd=cmd) elif mode == 'runWithErrors': cmd = '{cmd} --ExecutePreprocessor.allow_errors=True --execute'.format(cmd=cmd) else: return (-1, 'Mode not specified correctly.') if outpath is None and inplace: cmd='{cmd} --inplace'.format(cmd=cmd) #Select file cmd='{cmd} {notebook}'.format(cmd=cmd,notebook=quote(notebook)) #If output path not set, and --inplace is not set, # nbformat will create a new file with same name ending: .nbformat.ipynb if outpath is not None: cmd ='{cmd} --output-dir {outpath}'.format(cmd=cmd, outpath=quote(outpath)) return cli_command(cmd) def directoryProcessor(path, mode=None, outpath=None, inplace=True, include_hidden=False, dir_excludes=None, file_excludes=None, rmdir=False, currdir=False, subdirs=True, reportlevel=1, logfile=None): ''' Process all the notebooks in one or more directories and (optionally) in associated subdirectories. Processed notebooks can be written to a specified directory or rendered inplace. Path hierarchies to notebooks in multiple directories or subdirectories are respected when writing to a specified output directory. ''' def _process(outpath): ''' Process files associated with a particular directory ''' processfiles=[f for f in files if f.endswith('.ipynb')] if subdirs: print(dirname) if outpath is not None: outpath='/'.join([outpath, dirname]) if not os.path.exists(outpath): os.makedirs(outpath) if not mode == 'tests': #print('About to process {}'.format(processfiles)) with click.progressbar(processfiles) as bar: for filename in bar: if not currdir and dirname=='.': continue if reportlevel>1: print("Processing >{}<".format('/'.join([dirname,filename]))) resp = notebookProcessor('/'.join([dirname,filename]), mode=mode, outpath=outpath, inplace=inplace ) if reportlevel>0 and resp and resp[0]!=0: print("Error with {}".format('/'.join([dirname,filename]))) if logfile: with open(logfile, "a") as out: out.write(resp[1]) #if mode in ['tests', 'clearOutputTest']: # #Tests need to run in original dir in case of file dependencies # testreport = notebookTest(path=dirname,dir_excludes=dir_excludes) # print('tested:',dirname) # print(testreport[1]) #if mode == 'clearOutputTest': # #If we are testing for warnings, need to test in original directory # # in case there are file dependencies # outpath=None # inplace=True if mode is None: return if isinstance(path, list): if rmdir: shutil.rmtree(outpath, ignore_errors=True) #Make sure we only delete the directory on the way in... rmdir=False for _path in path: #When provided with multiple directories, process each one separately #Note that subdirs for each directory can be handled automatically directoryProcessor(_path, mode, '/'.join([outpath, _path]), inplace, include_hidden, dir_excludes, file_excludes, rmdir, currdir, subdirs, reportlevel, logfile) return #TO DO - simplify this so we just pass one exclusion type then detect if file or dir? file_excludes = listify(file_excludes) dir_excludes = listify(dir_excludes) if outpath is not None and os.path.exists(outpath): if rmdir: print('\n***Deleting directory `{}` and all its contents....***\n\n'.format(outpath)) shutil.rmtree(outpath, ignore_errors=True) else: print('\nOutput directory `{}` already exists. Remove it first by setting: rmdir=True\n'.format(outpath)) #dir_excludes = [] if dir_excludes is None else dir_excludes #file_excludes = [] if file_excludes is None else file_excludes if os.path.isfile(path): notebookProcessor(path, mode=mode, outpath=outpath, inplace=inplace ) elif subdirs: for dirname, subdirs, files in os.walk(path): exclude_items(subdirs, dir_excludes, not include_hidden) exclude_items(files, file_excludes, not include_hidden) _process(outpath) # if passed a single file rather than directory path else: files=os.listdir(path) exclude_items(files, file_excludes, not include_hidden) dirname=path _process(outpath) #Running zipper with a file_processor will change the cell state in current dir #That is, notebooks are processed in place then zipped #The notebooks as seen in the dir will reflect those in the zipfile #We could modify this behaviour so it does not affect original notebooks? def zipper(dirtozip, zipfilename, include_hidden=False, dir_excludes=None, file_excludes=None, file_processor=None, reportlevel=1, rmdir=False, zip_append=False): ''' Zip the contents of a directory and its subdirectories ''' file_excludes = listify(file_excludes) dir_excludes = listify(dir_excludes) zip_permission = "a" if zip_append else "w" #Create a new/replacement zip file, rather than append if zipfile already exists zf = zipfile.ZipFile(zipfilename, zip_permission, compression=zipfile.ZIP_DEFLATED) #Don't zip files of same name as the zip file we are creating file_excludes.append(zipfilename) # if we have just a single file to zip and not a dir, zip that if os.path.isfile(dirtozip): zf.write(dirtozip) elif os.path.isdir(dirtozip): #https://stackoverflow.com/a/31779538/454773 for dirname, subdirs, files in os.walk(dirtozip): exclude_items(subdirs, dir_excludes, not include_hidden) exclude_items(files, file_excludes, not include_hidden) print('Processing directory: {}'.format(dirname)) zf.write(dirname) with click.progressbar(files) as bar: for filename in bar: if reportlevel>1:print(filename) filepathname=os.path.join(dirname, filename) #There is no point using 'run': if there is an error, nbconvert will fail if file_processor in ['clearOutput', 'runWithErrors'] and filename.endswith('.ipynb'): #This introduces side effects - notebooks are processed in current path #Should we do this in a tmpfile? notebookProcessor(filepathname, mode=file_processor, inplace=True) zf.write(filepathname) zf.close() #Is this too risky?! #if rmdir: shutil.rmtree(dirtozip, ignore_errors=True) return zipfilename def insideZip(zfn, report=True): ''' Look inside a zip file. The report contains four columns: file_size, file compressed size, datetime and filename. Setting report=True returns a pretty printed report. ''' if not os.path.isfile(zfn): print("\nHmm... {} doesn't seem to be a file?\n".format(zfn)) return print('\nLooking inside zipfile: {}\n'.format(zfn)) fz=zipfile.ZipFile(zfn) txt=[] for fn in fz.infolist(): txt.append( [fn.file_size, fn.compress_size, datetime.datetime(*fn.date_time).isoformat(), fn.filename] ) print('{}, {}, {}, {}'.format(fn.file_size, fn.compress_size, datetime.datetime(*fn.date_time).isoformat(), fn.filename)) tabulate(txt, headers=['Full','Zip','Datetime','Path'],tablefmt="simple") return txt @click.command() @click.option('--file-processor','-r', type=click.Choice(['clearOutput', 'runWithErrors'])) @click.option('--include-hiddenfiles', '-H', is_flag=True, help='Include hidden files') @click.option('--exclude-dir', '-X', multiple=True, type=click.Path(resolve_path=False), help='Exclude specified directory') @click.option('--exclude-file','-x', multiple=True,type=click.Path(resolve_path=False), help='Exclude specified file') @click.option('--zip_append','-a', is_flag=True, help='Add to existing zip file') @click.argument('path', type=click.Path(resolve_path=False)) #@click.argument('zipfile', type=click.File('wb')) @click.argument('zipfile', type=click.Path()) def cli_zip(file_processor, include_hiddenfiles, exclude_dir, exclude_file, zip_append, path, zipfile): """Create a zip file from the contents of a specified directory. The zipper can optionally run a notebook processor on notebooks before zipping them to check that all cells are run or all cells are cleared. """ print('You must be crazy using this...') if not zip_append: print(f"\nOverwriting any previous {zipfile} file\n") else: print(f"\nAppending zipped files to: {zipfile}\n") fn = zipper(path, zipfile, include_hidden=include_hiddenfiles, dir_excludes=exclude_dir, file_excludes=exclude_file, file_processor=file_processor, zip_append=zip_append) print(f"\nZip file: {fn}\n") @click.command() @click.option('--quiet', '-q', is_flag=True, help='Suppress the report.') @click.option('--warnings', '-w', is_flag=True, help='Display warnings') @click.argument('filename', type=click.Path(resolve_path=True),nargs=-1) def cli_zipview(filename, warnings, quiet): """List the contents of one or more specified zipfiles. """ zip_contents = [] for f in listify(filename): zip_contents.append((f, insideZip(f))) if warnings and zip_contents: for (zn, item) in zip_contents: print(f"\n\n====== Zip file quality report: {zn} ======\n") for record in item: if record[1] > 1e6: print(f"WARNING: \"{record[3]}\" looks quite large file ({humanize.naturalsize(record[0])} unzipped, {humanize.naturalsize(record[1])} compressed)") for _path in record[3].split('/'): if len(_path) > 50: print(f"ERROR: the filepath element \"{_path}\" in \"{record[3]}\" is too long (max. 50 chars)") if _path.startswith("."): print(f"WARNING: \"{record[3]}\" is a hidden file/directory (do you really need it in the zip file?)") print("\n===========================\n\n") @click.command() @click.option('--exclude-dir','-X', multiple=True,type=click.Path(resolve_path=False), help='Do not recurse through specified directory when assembling tests.') @click.option('--exclude-file','-x', multiple=True,type=click.Path(resolve_path=False), help='Exclude specified file') @click.option('--outfile','-o', type=click.Path(resolve_path=False), help='Output report file. Leave this blank to display report on command line.') @click.argument('testitems', type=click.Path(resolve_path=False),nargs=-1) def cli_nbtest( exclude_dir, exclude_file, outfile, testitems): """Test specified notebooks and/or the notebooks in a specified directory or directories (`TESTITEMS`) using the `nbdime` plugin for `py.test`. Running `tm351nbtest` without any specified directory or file will assemble tests recursively from the current directory down.""" testitems = testitems or '.' _notebookTest(testitems, outfile, exclude_dir, exclude_file) @click.command() @click.option('--file-processor','-r', type=click.Choice(['clearOutput', 'runWithErrors']), help='File processor actions that can be applied to notebooks using `nbconvert`') @click.option('--outpath', '-O', type=click.Path(resolve_path=False), help='path to output directory') @click.option('--inplace/--no-inplace',default=True, help='Run processors on notebooks inplace') @click.option('--exclude-dir', '-X', multiple=True, type=click.Path(resolve_path=False), help='Exclude specified directory') @click.option('--exclude-file','-x', multiple=True,type=click.Path(resolve_path=False), help='Exclude specified file') @click.option('--include-hidden/--no-include-hidden',default=False, help='Include hidden files') @click.option('--rmdir/--no-rmdir',default=False, help='Check the output directory is empty before we use it') @click.option('--currdir/--no-currdir',default=False, help='Process files in current directory') @click.option('--subdirs/--no-subdirs',default=True, help='Process files in subdirectories') @click.option('--reportlevel', default=1, help='Reporting level') @click.argument('path',type=click.Path(resolve_path=False)) def cli_nbrun(file_processor, outpath, inplace, exclude_dir, exclude_file, include_hidden, rmdir, currdir, subdirs, reportlevel, path): """Directory processor for notebooks - allows the user to run nbconvert operations on notebooks, such as running all cells or clearing all cells. To run tests, use: tm351nbtest To zip folders (with the option or running notebook processors on zipped files), use: tm351zip """ directoryProcessor(path, mode=file_processor, outpath=outpath, inplace=inplace, include_hidden=include_hidden, dir_excludes=exclude_dir, file_excludes=exclude_file, rmdir=rmdir, currdir=currdir, subdirs=subdirs,reportlevel=reportlevel) from github import Github import getpass import base64 import logging from github.GithubException import GithubException def get_sha_for_tag(repository, tag): """ Returns a commit PyGithub object for the specified repository and tag. """ branches = repository.get_branches() matched_branches = [match for match in branches if match.name == tag] if matched_branches: return matched_branches[0].commit.sha tags = repository.get_tags() matched_tags = [match for match in tags if match.name == tag] if not matched_tags: raise ValueError('No Tag or Branch exists with that name') return matched_tags[0].commit.sha def download_directory(repository, sha, server_path, outpath='gh_downloads', file_processor=None): """ Download all contents at server_path with commit tag sha in the repository. """ contents = repository.get_dir_contents(server_path, ref=sha) if not os.path.exists(outpath): os.makedirs(outpath) for content in contents: print("Downloading: %s" % content.path) if content.type == 'dir': download_directory(repository, sha, content.path, '/'.join([outpath,content.name])) else: try: path = content.path file_content = repository.get_contents(path, ref=sha) file_data = base64.b64decode(file_content.content) outpathfile='/'.join([outpath,content.name]) file_out = open(outpathfile, "wb") file_out.write(file_data) file_out.close() except (IOError, github.GithubException) as exc: #If we fail over because of a large blog, use the data api for the download ret,error=exc.args if 'message' in error and error['message']=='Not Found': print('Hmm... file not found? {}'.format(path)) elif 'errors' in error and error['errors'][0]['code']=='too_large': #print('...large file, trying blob download instead...') file_content = repository.get_git_blob(content.sha) file_data = base64.b64decode(file_content.content) file_out = open('/'.join([outpath,content.name]), "wb") file_out.write(file_data) file_out.close() #logging.error('Error processing %s: %s', content.path, exc) #if content.name.endswith('.ipynb') and file_processor in ['clearOutput', 'clearOutputTest','runWithErrors' ]: # notebookProcessor(outpathfile, file_processor) DEFAULT_REPO='undercertainty/tm351' @click.command() @click.option('--github-user', '-u', help="Your Github username.") @click.option('--password', hide_input=True, confirmation_prompt=False) @click.option('--repo','-r', prompt='Repository ({})'.format(DEFAULT_REPO), help='Repository name') @click.option('--branch','-b',help='Branch or tag to download') @click.option('--directory', help='Directory to download (or: all)') @click.option('--savedir',type=click.Path(resolve_path=False), help='Directory to download repo / repo dir into; default is dir name') @click.option('--file-processor', type=click.Choice(['clearOutput', 'runWithErrors']), help='Optionally specify a file processor to be run against downloaded notebooks.') @click.option('--zip/--no-zip', default=False, help='Optionally create a zip file of the downloaded repository/directory with the same name as the repository/directory.') @click.option('--auth/--no-auth', default=True, help="By default, run with auth (prompt for credentials)") @click.option('--with-tests','-t',is_flag=True, help="Run tests on notebooks after download") @click.option('--logfile',type=click.Path(resolve_path=False), help='Path to logfile') def cli_gitrepos(github_user, password, repo, branch, directory, savedir, file_processor, zip, auth, with_tests, logfile): """Download files from a specified branch in a particular git repository. The download can also be limited to just the contents of a specified directory. Don't worry that there look to be a lot of arguments - you will be prompted for them if you just run: tm351gitrepos """ if auth or github_user: if not github_user: github_user = click.prompt('\nGithub username') if not password: password = click.prompt('\nGithub password', hide_input=True) github = Github(github_user, password) #Show we're keeping no password... password = None auth = True else: github = Github() if auth: user = github.get_user() #organisations = github.get_user().get_orgs() print('Logging into git as {} ({})'.format(github_user, user.name)) repo = repo or DEFAULT_REPO repository = github.get_repo(repo) if not branch: print('\nBranches available:\n\t{}'.format('\n\t'.join(github_repo_branches(repository)) )) branch = click.prompt('\nWhich branch? (master)') branch_or_tag_to_download = branch or 'master' sha = get_sha_for_tag(repository, branch_or_tag_to_download) another = '' while another!='-': if not directory: if branch!='master': contents = repository.get_dir_contents('.', ref=sha) else: contents = repository.get_dir_contents('.') print('\nYou can download all directories from this repo (all) or select one:\n\t{}'.format('\n\t'.join(github_repo_topdirs(contents)))) directory = click.prompt('Which directory? (all)') directory_to_download = '.' if (not directory or directory=='all') else directory outpath = savedir or directory_to_download if outpath == '.' and savedir !='.': outpath=repo.replace('/','_')+'_files' msg='\nOkay... downloading {}/{}'.format(repo,directory_to_download ) if file_processor is not None: msg = msg + ' using notebook processor: {}'.format(file_processor) else: msg = msg + ' with no notebook processing' print(msg) download_directory(repository, sha, directory_to_download, outpath,file_processor ) if file_processor in ['clearOutput', 'clearOutputTest','runWithErrors' ]: click.echo('\nRunning notebook processor: {}'.format(file_processor)) directoryProcessor(outpath, mode=file_processor, subdirs=True, reportlevel=1, logfile=logfile) if logfile: click.echo('\nLog written to {}'.format(logfile)) if with_tests: click.echo('\nRunning notebook tests over: {}'.format(outpath)) if not logfile: logfile = 'tests.log' _notebookTest(outpath, logfile ) click.echo('\nLog written to {}'.format(logfile)) if zip: print('\nZipping into: {}/nYou may also want to delete the working directory ({}).'.format(repository, outpath) ) zipper(outpath,repository) else: print('\n\nTo zip the downloaded directory, run something like: {}'.format('tm351zip {o} {z}\n\nTo run a notebook processor (OPTIONS: runWithErrors, clearOutput) while zipping: tm351zip "{o}" {z} --file-processor OPTION\n'.format(o=outpath,z=repository.name))) directory='' another = click.prompt('\Download another directory from this branch? (To quit: -)') #TODO #print('\n\nTo run this command again: {}'.format())
[ 2, 267, 84, 12, 17209, 35273, 532, 4600, 46803, 62, 12984, 62, 26791, 63, 198, 198, 2, 38, 2394, 49285, 532, 11361, 319, 4100, 18931, 287, 284, 38994, 25, 3740, 1378, 25558, 2502, 11125, 13, 785, 14, 64, 14, 27211, 4089, 16799, 14, 2231, 2857, 4790, 198, 198, 11748, 3904, 198, 198, 11748, 28686, 198, 11748, 4423, 346, 198, 11748, 19974, 7753, 198, 11748, 1692, 1096, 198, 11748, 4818, 8079, 198, 11748, 33084, 198, 6738, 7400, 5039, 1330, 7400, 5039, 198, 6738, 427, 2588, 1330, 9577, 628, 198, 11748, 850, 14681, 198, 198, 4299, 1351, 1958, 7, 9186, 2599, 198, 220, 220, 220, 705, 7061, 1002, 5545, 351, 257, 4731, 290, 257, 1351, 318, 2672, 11, 787, 257, 1351, 986, 705, 7061, 198, 220, 220, 220, 2378, 796, 17635, 611, 2378, 318, 6045, 2073, 2378, 198, 220, 220, 220, 1303, 1135, 743, 307, 3804, 257, 46545, 532, 287, 543, 1339, 11, 1351, 1958, 986, 198, 220, 220, 220, 2378, 796, 1351, 7, 9186, 8, 611, 318, 39098, 7, 9186, 11, 7, 4868, 11, 83, 29291, 4008, 2073, 685, 9186, 60, 198, 220, 220, 220, 1441, 2378, 198, 220, 220, 220, 220, 198, 4299, 19607, 62, 30342, 62, 23814, 7, 9186, 4868, 11, 19607, 62, 30342, 28, 17821, 2599, 198, 220, 220, 220, 705, 7061, 1475, 9152, 7104, 3709, 422, 1976, 24705, 396, 705, 7061, 198, 220, 220, 220, 611, 19607, 62, 30342, 25, 198, 220, 220, 220, 220, 220, 220, 220, 374, 4029, 396, 28, 21737, 198, 220, 220, 220, 220, 220, 220, 220, 329, 2124, 287, 2378, 4868, 25, 198, 220, 220, 220, 220, 220, 220, 220, 220, 220, 220, 220, 611, 2124, 13, 9688, 2032, 342, 10786, 2637, 2599, 198, 220, 220, 220, 220, 220, 220, 220, 220, 220, 220, 220, 220, 220, 220, 220, 374, 4029, 396, 13, 33295, 7, 87, 8, 198, 220, 220, 220, 220, 220, 220, 220, 329, 2124, 287, 374, 4029, 396, 25, 198, 220, 220, 220, 220, 220, 220, 220, 220, 220, 220, 220, 2378, 4868, 13, 28956, 7, 87, 8, 198, 220, 220, 220, 220, 220, 220, 220, 220, 220, 220, 220, 220, 198, 4299, 19607, 62, 23814, 7, 9186, 4868, 11, 36833, 11, 19607, 62, 30342, 28, 17821, 11, 20966, 2047, 65, 62, 8807, 28, 25101, 2599, 198, 220, 220, 220, 705, 7061, 1475, 9152, 3709, 422, 1976, 24705, 396, 705, 7061, 628, 220, 220, 220, 329, 2124, 67, 287, 900, 7, 9186, 4868, 737, 3849, 5458, 7, 1069, 13955, 2599, 198, 220, 220, 220, 220, 220, 220, 220, 2378, 4868, 13, 28956, 7, 24954, 8, 628, 220, 220, 220, 611, 20966, 2047, 65, 62, 8807, 25, 198, 220, 220, 220, 220, 220, 220, 220, 329, 1312, 287, 685, 62, 72, 329, 4808, 72, 287, 2378, 4868, 611, 407, 4808, 72, 13, 437, 2032, 342, 7203, 541, 2047, 65, 4943, 5974, 198, 220, 220, 220, 220, 220, 220, 220, 220, 220, 220, 220, 220, 220, 220, 220, 2378, 4868, 13, 28956, 7, 72, 8, 198, 220, 220, 220, 220, 220, 220, 220, 220, 198, 220, 220, 220, 611, 19607, 62, 30342, 25, 19607, 62, 30342, 62, 23814, 7, 9186, 4868, 8, 198, 220, 220, 220, 220, 198, 220, 220, 220, 220, 198, 198, 4299, 20922, 14402, 7, 6978, 28, 14202, 11, 29472, 28, 14202, 11, 26672, 62, 1069, 13955, 28, 14202, 11, 2393, 62, 1069, 13955, 28, 14202, 2599, 198, 220, 220, 220, 705, 7061, 5660, 20922, 5254, 625, 11777, 3706, 3696, 290, 29196, 13, 198, 220, 220, 220, 705, 7061, 198, 220, 220, 220, 220, 198, 220, 220, 220, 1303, 23722, 2192, 8160, 428, 664, 1834, 2280, 284, 5412, 35971, 270, 1154, 13532, 14, 10379, 268, 1047, 986, 198, 220, 220, 220, 220, 198, 220, 220, 220, 5336, 270, 5847, 796, 13538, 17912, 260, 25636, 16, 60, 198, 260, 25636, 25, 1279, 34960, 85, 528, 13, 16624, 13, 7416, 379, 685, 61, 37981, 9, 29, 198, 33491, 25, 1279, 34960, 85, 528, 13, 16624, 13, 7416, 29, 198, 198, 58, 260, 25636, 17, 60, 198, 260, 25636, 25, 9135, 1661, 25, 764, 9, 198, 33491, 25, 9135, 1661, 25, 16932, 3843, 12789, 198, 198, 58, 260, 25636, 18, 60, 198, 260, 25636, 25, 5007, 640, 25, 764, 9, 198, 33491, 25, 5007, 640, 25, 370, 7036, 34694, 198, 198, 58, 260, 25636, 19, 60, 198, 260, 25636, 25, 764, 9, 583, 9052, 16792, 32604, 6354, 14367, 13, 1614, 13, 286, 764, 9, 4539, 11, 764, 9, 23607, 1123, 22725, 198, 33491, 25, 20460, 2043, 62, 2200, 15490, 198, 37811, 198, 220, 220, 220, 1303, 22065, 62, 22184, 796, 45434, 12807, 270, 786, 62, 37581, 13, 37581, 1, 198, 220, 220, 220, 1303, 4480, 1280, 7, 22065, 62, 22184, 11, 366, 86, 4943, 355, 277, 25, 198, 220, 220, 220, 1303, 220, 220, 220, 277, 13, 13564, 7, 12807, 270, 5847, 8, 628, 220, 220, 220, 1303, 28758, 28, 69, 6, 9078, 13, 9288, 1377, 46803, 2100, 12, 12807, 270, 1096, 12, 4480, 1391, 22065, 62, 22184, 92, 705, 198, 220, 220, 220, 23991, 28, 69, 6, 9078, 13, 9288, 705, 628, 220, 220, 220, 2393, 62, 1069, 13955, 796, 1351, 1958, 7, 7753, 62, 1069, 13955, 8, 628, 220, 220, 220, 329, 288, 287, 1351, 1958, 7, 15908, 62, 1069, 13955, 2599, 198, 220, 220, 220, 220, 220, 220, 220, 23991, 796, 23991, 1343, 705, 1377, 46430, 34758, 92, 45302, 18982, 7, 22708, 7, 67, 4008, 198, 220, 220, 220, 220, 220, 220, 220, 3601, 7203, 9, 3673, 4856, 287, 8619, 25, 23884, 9, 1911, 18982, 7, 67, 4008, 628, 220, 220, 220, 23991, 796, 23991, 10, 6, 1377, 46803, 2100, 705, 198, 220, 220, 220, 22492, 39410, 532, 5390, 8410, 532, 611, 356, 389, 2491, 428, 422, 257, 20922, 11, 635, 19607, 3108, 855, 6, 2637, 198, 220, 220, 220, 611, 3108, 318, 6045, 290, 29472, 318, 6045, 25, 198, 220, 220, 220, 220, 220, 220, 220, 1303, 18709, 1459, 8619, 198, 220, 220, 220, 220, 220, 220, 220, 1441, 537, 72, 62, 21812, 7, 28758, 8, 198, 220, 220, 220, 1288, 361, 29472, 25, 198, 220, 220, 220, 220, 220, 220, 220, 1303, 18709, 2393, 7, 82, 8, 287, 8619, 198, 220, 220, 220, 220, 220, 220, 220, 611, 318, 39098, 7, 34345, 11, 1351, 2599, 198, 220, 220, 220, 220, 220, 220, 220, 220, 220, 220, 220, 329, 4808, 34345, 287, 29472, 25, 198, 220, 220, 220, 220, 220, 220, 220, 220, 220, 220, 220, 220, 220, 220, 220, 23991, 796, 705, 90, 28758, 92, 1391, 34345, 92, 4458, 18982, 7, 28758, 28, 28758, 11, 29472, 28, 6978, 10297, 7, 6978, 11, 9577, 28264, 34345, 22305, 198, 220, 220, 220, 220, 220, 220, 220, 220, 220, 220, 220, 220, 220, 220, 220, 1217, 28, 44506, 62, 21812, 7, 28758, 8, 198, 220, 220, 220, 220, 220, 220, 220, 2073, 25, 198, 220, 220, 220, 220, 220, 220, 220, 220, 220, 220, 220, 23991, 796, 705, 90, 28758, 92, 1391, 34345, 92, 4458, 18982, 7, 28758, 28, 28758, 11, 29472, 28, 6978, 10297, 7, 6978, 11, 9577, 7, 34345, 22305, 198, 220, 220, 220, 220, 220, 220, 220, 220, 220, 220, 220, 1217, 28, 44506, 62, 21812, 7, 28758, 8, 198, 220, 220, 220, 220, 220, 220, 220, 1441, 1217, 198, 220, 220, 220, 2073, 25, 198, 220, 220, 220, 220, 220, 220, 220, 1303, 18709, 3696, 287, 3108, 198, 220, 220, 220, 220, 220, 220, 220, 1303, 1532, 356, 1208, 257, 8619, 1438, 287, 788, 262, 1332, 481, 307, 1057, 625, 477, 3696, 287, 262, 8619, 198, 220, 220, 220, 220, 220, 220, 220, 1303, 9078, 13, 9288, 10507, 15968, 262, 1332, 9109, 198, 220, 220, 220, 220, 220, 220, 220, 581, 862, 796, 17635, 198, 220, 220, 220, 220, 220, 220, 220, 329, 2060, 6978, 287, 1351, 1958, 7, 6978, 2599, 198, 220, 220, 220, 220, 220, 220, 220, 220, 220, 220, 220, 329, 26672, 3672, 11, 850, 15908, 82, 11, 3696, 287, 28686, 13, 11152, 7, 29762, 6978, 2599, 198, 220, 220, 220, 220, 220, 220, 220, 220, 220, 220, 220, 220, 220, 220, 220, 19607, 62, 23814, 7, 7266, 15908, 82, 11, 26672, 62, 1069, 13955, 8, 198, 220, 220, 220, 220, 220, 220, 220, 220, 220, 220, 220, 220, 220, 220, 220, 19607, 62, 23814, 7, 16624, 11, 2393, 62, 1069, 13955, 11, 20966, 2047, 65, 62, 8807, 28, 17821, 8, 198, 220, 220, 220, 220, 220, 220, 220, 220, 220, 220, 220, 220, 220, 220, 220, 3601, 10786, 18709, 278, 8619, 25, 23884, 4458, 18982, 7, 15908, 3672, 4008, 198, 220, 220, 220, 220, 220, 220, 220, 220, 220, 220, 220, 220, 220, 220, 220, 351, 3904, 13, 33723, 5657, 7, 16624, 8, 355, 2318, 25, 198, 220, 220, 220, 220, 220, 220, 220, 220, 220, 220, 220, 220, 220, 220, 220, 220, 220, 220, 220, 329, 29472, 287, 2318, 25, 198, 220, 220, 220, 220, 220, 220, 220, 220, 220, 220, 220, 220, 220, 220, 220, 220, 220, 220, 220, 220, 220, 220, 220, 2393, 6978, 3672, 28, 418, 13, 6978, 13, 22179, 7, 15908, 3672, 11, 29472, 8, 198, 220, 220, 220, 220, 220, 220, 220, 220, 220, 220, 220, 220, 220, 220, 220, 220, 220, 220, 220, 220, 220, 220, 220, 23991, 796, 705, 90, 28758, 92, 1391, 6978, 92, 4458, 18982, 7, 28758, 28, 28758, 11, 3108, 28, 22708, 7, 7753, 6978, 3672, 4008, 198, 220, 220, 220, 220, 220, 220, 220, 220, 220, 220, 220, 220, 220, 220, 220, 220, 220, 220, 220, 220, 220, 220, 220, 581, 862, 13, 33295, 7, 537, 72, 62, 21812, 7, 28758, 8, 1267, 198, 220, 220, 220, 220, 220, 220, 220, 1303, 1640, 2060, 6978, 287, 1351, 1958, 7, 6978, 2599, 198, 220, 220, 220, 220, 220, 220, 220, 1303, 220, 220, 220, 3601, 7203, 59, 77, 44154, 287, 8619, 25, 23884, 1911, 18982, 7, 29762, 6978, 4008, 198, 220, 220, 220, 220, 220, 220, 220, 1303, 220, 220, 220, 611, 2060, 6978, 855, 6, 2637, 25, 198, 220, 220, 220, 220, 220, 220, 220, 1303, 220, 220, 220, 220, 220, 220, 220, 3601, 10786, 1174, 18227, 5626, 1332, 287, 1459, 8619, 422, 257, 20922, 1174, 11537, 198, 220, 220, 220, 220, 220, 220, 220, 1303, 220, 220, 220, 23991, 796, 705, 90, 28758, 92, 1391, 6978, 92, 4458, 18982, 7, 28758, 28, 28758, 11, 3108, 28, 22708, 7, 29762, 6978, 4008, 198, 220, 220, 220, 220, 220, 220, 220, 1303, 220, 220, 220, 581, 862, 13, 33295, 7, 537, 72, 62, 21812, 7, 28758, 8, 1267, 198, 220, 220, 220, 220, 220, 220, 220, 220, 198, 220, 220, 220, 220, 220, 220, 220, 28686, 13, 403, 8726, 7, 22065, 62, 22184, 8, 198, 220, 220, 220, 220, 220, 220, 220, 1441, 581, 862, 198, 220, 220, 220, 220, 220, 220, 220, 220, 198, 4299, 20922, 18709, 273, 7, 11295, 2070, 11, 4235, 28, 14202, 11, 503, 6978, 28, 14202, 11, 503, 7753, 28, 14202, 11, 287, 5372, 28, 17821, 2599, 198, 220, 220, 220, 705, 7061, 11459, 20922, 5072, 4778, 13, 198, 220, 220, 220, 220, 198, 220, 220, 220, 220, 220, 220, 220, 10854, 257, 2060, 20922, 11, 17304, 2685, 23862, 2491, 4778, 1566, 198, 220, 220, 220, 220, 220, 220, 220, 257, 6509, 11, 393, 2491, 477, 4778, 3805, 14601, 13, 198, 220, 220, 220, 220, 220, 220, 220, 220, 198, 220, 220, 220, 220, 220, 220, 220, 10854, 276, 43935, 460, 307, 3194, 284, 257, 7368, 8619, 393, 15111, 287, 5372, 13, 198, 220, 220, 220, 705, 7061, 198, 220, 220, 220, 220, 198, 220, 220, 220, 611, 4235, 318, 6045, 25, 1441, 13841, 16, 11, 705, 19076, 407, 7368, 2637, 8, 198, 220, 220, 220, 220, 198, 220, 220, 220, 611, 503, 6978, 318, 407, 6045, 290, 407, 28686, 13, 6978, 13, 1069, 1023, 7, 448, 6978, 2599, 198, 220, 220, 220, 220, 220, 220, 220, 28686, 13, 76, 4335, 17062, 7, 448, 6978, 8, 198, 220, 220, 220, 220, 198, 220, 220, 220, 611, 503, 7753, 318, 407, 6045, 25, 198, 220, 220, 220, 220, 220, 220, 220, 503, 6978, 796, 31051, 4458, 22179, 26933, 448, 6978, 11, 448, 7753, 12962, 611, 503, 6978, 318, 407, 6045, 2073, 503, 7753, 198, 220, 220, 220, 220, 198, 220, 220, 220, 23991, 11639, 73, 929, 88, 353, 299, 65, 1102, 1851, 1377, 1462, 20922, 6, 628, 220, 220, 220, 611, 4235, 287, 37250, 20063, 26410, 3256, 705, 20063, 26410, 14402, 6, 2361, 25, 198, 220, 220, 220, 220, 220, 220, 220, 23991, 796, 705, 90, 28758, 92, 1377, 19856, 26410, 6719, 41341, 13, 25616, 28, 17821, 4458, 18982, 7, 28758, 28, 28758, 8, 198, 220, 220, 220, 1288, 361, 4235, 6624, 705, 5143, 10354, 198, 220, 220, 220, 220, 220, 220, 220, 23991, 796, 705, 90, 28758, 92, 1377, 41049, 4458, 18982, 7, 28758, 28, 28758, 8, 198, 220, 220, 220, 1288, 361, 4235, 6624, 705, 5143, 3152, 9139, 5965, 10354, 198, 220, 220, 220, 220, 220, 220, 220, 23991, 796, 705, 90, 28758, 92, 1377, 23002, 1133, 6719, 41341, 13, 12154, 62, 48277, 28, 17821, 1377, 41049, 4458, 18982, 7, 28758, 28, 28758, 8, 198, 220, 220, 220, 2073, 25, 1441, 13841, 16, 11, 705, 19076, 407, 7368, 9380, 2637, 8, 198, 220, 220, 220, 220, 198, 220, 220, 220, 611, 503, 6978, 318, 6045, 290, 287, 5372, 25, 198, 220, 220, 220, 220, 220, 220, 220, 23991, 11639, 90, 28758, 92, 1377, 259, 5372, 4458, 18982, 7, 28758, 28, 28758, 8, 628, 220, 220, 220, 1303, 17563, 2393, 198, 220, 220, 220, 23991, 11639, 90, 28758, 92, 1391, 11295, 2070, 92, 4458, 18982, 7, 28758, 28, 28758, 11, 11295, 2070, 28, 22708, 7, 11295, 2070, 4008, 198, 220, 220, 220, 220, 198, 220, 220, 220, 1303, 1532, 5072, 3108, 407, 900, 11, 290, 1377, 259, 5372, 318, 407, 900, 11, 198, 220, 220, 220, 1303, 220, 299, 65, 18982, 481, 2251, 257, 649, 2393, 351, 976, 1438, 7464, 25, 764, 46803, 18982, 13, 541, 2047, 65, 198, 220, 220, 220, 611, 503, 6978, 318, 407, 6045, 25, 198, 220, 220, 220, 220, 220, 220, 220, 23991, 796, 6, 90, 28758, 92, 1377, 22915, 12, 15908, 1391, 448, 6978, 92, 4458, 18982, 7, 28758, 28, 28758, 11, 503, 6978, 28, 22708, 7, 448, 6978, 4008, 198, 220, 220, 220, 220, 220, 220, 220, 220, 198, 220, 220, 220, 1441, 537, 72, 62, 21812, 7, 28758, 8, 198, 198, 4299, 8619, 18709, 273, 7, 6978, 11, 198, 220, 220, 220, 220, 220, 220, 220, 220, 220, 220, 220, 220, 220, 220, 220, 220, 220, 220, 220, 220, 220, 220, 4235, 28, 14202, 11, 503, 6978, 28, 14202, 11, 287, 5372, 28, 17821, 11, 198, 220, 220, 220, 220, 220, 220, 220, 220, 220, 220, 220, 220, 220, 220, 220, 220, 220, 220, 220, 220, 220, 220, 2291, 62, 30342, 28, 25101, 11, 198, 220, 220, 220, 220, 220, 220, 220, 220, 220, 220, 220, 220, 220, 220, 220, 220, 220, 220, 220, 220, 220, 220, 26672, 62, 1069, 13955, 28, 14202, 11, 198, 220, 220, 220, 220, 220, 220, 220, 220, 220, 220, 220, 220, 220, 220, 220, 220, 220, 220, 220, 220, 220, 220, 2393, 62, 1069, 13955, 28, 14202, 11, 374, 9132, 343, 28, 25101, 11, 1090, 4372, 343, 28, 25101, 11, 850, 15908, 82, 28, 17821, 11, 198, 220, 220, 220, 220, 220, 220, 220, 220, 220, 220, 220, 220, 220, 220, 220, 220, 220, 220, 220, 220, 220, 220, 989, 5715, 28, 16, 11, 2604, 7753, 28, 14202, 2599, 198, 220, 220, 220, 705, 7061, 10854, 477, 262, 43935, 287, 530, 393, 517, 29196, 290, 198, 220, 220, 220, 220, 220, 220, 220, 357, 18076, 453, 8, 287, 3917, 850, 12942, 1749, 13, 198, 220, 220, 220, 220, 198, 220, 220, 220, 220, 220, 220, 220, 10854, 276, 43935, 460, 307, 3194, 284, 257, 7368, 8619, 393, 15111, 287, 5372, 13, 198, 220, 220, 220, 220, 220, 220, 220, 220, 220, 220, 220, 220, 198, 220, 220, 220, 220, 220, 220, 220, 10644, 28398, 444, 284, 43935, 287, 3294, 29196, 393, 850, 12942, 1749, 389, 198, 220, 220, 220, 220, 220, 220, 220, 14462, 618, 3597, 284, 257, 7368, 5072, 8619, 13, 198, 220, 220, 220, 705, 7061, 198, 220, 220, 220, 220, 198, 220, 220, 220, 825, 4808, 14681, 7, 448, 6978, 2599, 198, 220, 220, 220, 220, 220, 220, 220, 705, 7061, 10854, 3696, 3917, 351, 257, 1948, 8619, 705, 7061, 198, 220, 220, 220, 220, 220, 220, 220, 1429, 16624, 41888, 69, 329, 277, 287, 3696, 611, 277, 13, 437, 2032, 342, 7, 4458, 541, 2047, 65, 11537, 60, 198, 220, 220, 220, 220, 220, 220, 220, 220, 198, 220, 220, 220, 220, 220, 220, 220, 611, 850, 15908, 82, 25, 198, 220, 220, 220, 220, 220, 220, 220, 220, 220, 220, 220, 3601, 7, 15908, 3672, 8, 198, 220, 220, 220, 220, 220, 220, 220, 220, 220, 220, 220, 611, 503, 6978, 318, 407, 6045, 25, 198, 220, 220, 220, 220, 220, 220, 220, 220, 220, 220, 220, 220, 220, 220, 220, 503, 6978, 11639, 14, 4458, 22179, 26933, 448, 6978, 11, 26672, 3672, 12962, 198, 220, 220, 220, 220, 220, 220, 220, 220, 220, 220, 220, 220, 220, 220, 220, 611, 407, 28686, 13, 6978, 13, 1069, 1023, 7, 448, 6978, 2599, 198, 220, 220, 220, 220, 220, 220, 220, 220, 220, 220, 220, 220, 220, 220, 220, 220, 220, 220, 220, 28686, 13, 76, 4335, 17062, 7, 448, 6978, 8, 198, 220, 220, 220, 220, 220, 220, 220, 611, 407, 4235, 6624, 705, 41989, 10354, 198, 220, 220, 220, 220, 220, 220, 220, 220, 220, 220, 220, 1303, 4798, 10786, 8585, 284, 1429, 23884, 4458, 18982, 7, 14681, 16624, 4008, 198, 220, 220, 220, 220, 220, 220, 220, 220, 220, 220, 220, 351, 3904, 13, 33723, 5657, 7, 14681, 16624, 8, 355, 2318, 25, 198, 220, 220, 220, 220, 220, 220, 220, 220, 220, 220, 220, 220, 220, 220, 220, 329, 29472, 287, 2318, 25, 198, 220, 220, 220, 220, 220, 220, 220, 220, 220, 220, 220, 220, 220, 220, 220, 220, 220, 220, 220, 611, 407, 1090, 4372, 343, 290, 26672, 3672, 855, 6, 2637, 25, 2555, 198, 220, 220, 220, 220, 220, 220, 220, 220, 220, 220, 220, 220, 220, 220, 220, 220, 220, 220, 220, 611, 989, 5715, 29, 16, 25, 198, 220, 220, 220, 220, 220, 220, 220, 220, 220, 220, 220, 220, 220, 220, 220, 220, 220, 220, 220, 220, 220, 220, 220, 3601, 7203, 18709, 278, 1875, 90, 92, 27, 1911, 18982, 10786, 14, 4458, 22179, 26933, 15908, 3672, 11, 34345, 60, 22305, 198, 220, 220, 220, 220, 220, 220, 220, 220, 220, 220, 220, 220, 220, 220, 220, 220, 220, 220, 220, 1217, 796, 20922, 18709, 273, 10786, 14, 4458, 22179, 26933, 15908, 3672, 11, 34345, 46570, 4235, 28, 14171, 11, 503, 6978, 28, 448, 6978, 11, 287, 5372, 28, 259, 5372, 1267, 198, 220, 220, 220, 220, 220, 220, 220, 220, 220, 220, 220, 220, 220, 220, 220, 220, 220, 220, 220, 611, 989, 5715, 29, 15, 290, 1217, 290, 1217, 58, 15, 60, 0, 28, 15, 25, 198, 220, 220, 220, 220, 220, 220, 220, 220, 220, 220, 220, 220, 220, 220, 220, 220, 220, 220, 220, 220, 220, 220, 220, 3601, 7203, 12331, 351, 23884, 1911, 18982, 10786, 14, 4458, 22179, 26933, 15908, 3672, 11, 34345, 60, 22305, 198, 220, 220, 220, 220, 220, 220, 220, 220, 220, 220, 220, 220, 220, 220, 220, 220, 220, 220, 220, 611, 2604, 7753, 25, 198, 220, 220, 220, 220, 220, 220, 220, 220, 220, 220, 220, 220, 220, 220, 220, 220, 220, 220, 220, 220, 220, 220, 220, 351, 1280, 7, 6404, 7753, 11, 366, 64, 4943, 355, 503, 25, 198, 220, 220, 220, 220, 220, 220, 220, 220, 220, 220, 220, 220, 220, 220, 220, 220, 220, 220, 220, 220, 220, 220, 220, 220, 220, 220, 220, 503, 13, 13564, 7, 4363, 58, 16, 12962, 628, 220, 220, 220, 220, 220, 220, 220, 1303, 361, 4235, 287, 37250, 41989, 3256, 705, 20063, 26410, 14402, 6, 5974, 198, 220, 220, 220, 220, 220, 220, 220, 1303, 220, 220, 220, 1303, 51, 3558, 761, 284, 1057, 287, 2656, 26672, 287, 1339, 286, 2393, 20086, 198, 220, 220, 220, 220, 220, 220, 220, 1303, 220, 220, 220, 1332, 13116, 796, 20922, 14402, 7, 6978, 28, 15908, 3672, 11, 15908, 62, 1069, 13955, 28, 15908, 62, 1069, 13955, 8, 198, 220, 220, 220, 220, 220, 220, 220, 1303, 220, 220, 220, 3601, 10786, 39612, 25, 3256, 15908, 3672, 8, 198, 220, 220, 220, 220, 220, 220, 220, 1303, 220, 220, 220, 3601, 7, 9288, 13116, 58, 16, 12962, 198, 220, 220, 220, 220, 198, 220, 220, 220, 1303, 361, 4235, 6624, 705, 20063, 26410, 14402, 10354, 198, 220, 220, 220, 1303, 220, 220, 220, 1303, 1532, 356, 389, 4856, 329, 14601, 11, 761, 284, 1332, 287, 2656, 8619, 198, 220, 220, 220, 1303, 220, 220, 220, 1303, 220, 287, 1339, 612, 389, 2393, 20086, 198, 220, 220, 220, 1303, 220, 220, 220, 503, 6978, 28, 14202, 198, 220, 220, 220, 1303, 220, 220, 220, 287, 5372, 28, 17821, 198, 220, 220, 220, 220, 198, 220, 220, 220, 611, 4235, 318, 6045, 25, 1441, 198, 220, 220, 220, 220, 198, 220, 220, 220, 611, 318, 39098, 7, 6978, 11, 1351, 2599, 198, 220, 220, 220, 220, 220, 220, 220, 611, 374, 9132, 343, 25, 198, 220, 220, 220, 220, 220, 220, 220, 220, 220, 220, 220, 4423, 346, 13, 81, 16762, 631, 7, 448, 6978, 11, 8856, 62, 48277, 28, 17821, 8, 198, 220, 220, 220, 220, 220, 220, 220, 220, 220, 220, 220, 1303, 12050, 1654, 356, 691, 12233, 262, 8619, 319, 262, 835, 287, 986, 198, 220, 220, 220, 220, 220, 220, 220, 220, 220, 220, 220, 374, 9132, 343, 28, 25101, 198, 220, 220, 220, 220, 220, 220, 220, 220, 220, 220, 220, 220, 198, 220, 220, 220, 220, 220, 220, 220, 329, 4808, 6978, 287, 3108, 25, 198, 220, 220, 220, 220, 220, 220, 220, 220, 220, 220, 220, 1303, 2215, 2810, 351, 3294, 29196, 11, 1429, 1123, 530, 13869, 198, 220, 220, 220, 220, 220, 220, 220, 220, 220, 220, 220, 1303, 6425, 326, 850, 15908, 82, 329, 1123, 8619, 460, 307, 12118, 6338, 198, 220, 220, 220, 220, 220, 220, 220, 220, 220, 220, 220, 8619, 18709, 273, 28264, 6978, 11, 4235, 11, 31051, 4458, 22179, 26933, 448, 6978, 11, 4808, 6978, 46570, 287, 5372, 11, 198, 220, 220, 220, 220, 220, 220, 220, 220, 220, 220, 220, 220, 220, 220, 220, 220, 220, 220, 220, 220, 220, 220, 220, 220, 220, 220, 220, 220, 220, 220, 2291, 62, 30342, 11, 26672, 62, 1069, 13955, 11, 2393, 62, 1069, 13955, 11, 198, 220, 220, 220, 220, 220, 220, 220, 220, 220, 220, 220, 220, 220, 220, 220, 220, 220, 220, 220, 220, 220, 220, 220, 220, 220, 220, 220, 220, 220, 220, 374, 9132, 343, 11, 1090, 4372, 343, 11, 850, 15908, 82, 11, 989, 5715, 11, 2604, 7753, 8, 198, 220, 220, 220, 220, 220, 220, 220, 1441, 628, 220, 220, 220, 1303, 10468, 8410, 532, 30276, 428, 523, 356, 655, 1208, 530, 19328, 2099, 788, 4886, 611, 2393, 393, 26672, 30, 198, 220, 220, 220, 2393, 62, 1069, 13955, 796, 1351, 1958, 7, 7753, 62, 1069, 13955, 8, 198, 220, 220, 220, 26672, 62, 1069, 13955, 796, 1351, 1958, 7, 15908, 62, 1069, 13955, 8, 198, 220, 220, 220, 220, 198, 220, 220, 220, 611, 503, 6978, 318, 407, 6045, 290, 28686, 13, 6978, 13, 1069, 1023, 7, 448, 6978, 2599, 198, 220, 220, 220, 220, 220, 220, 220, 611, 374, 9132, 343, 25, 198, 220, 220, 220, 220, 220, 220, 220, 220, 220, 220, 220, 3601, 10786, 59, 77, 8162, 5005, 293, 889, 8619, 4600, 90, 92, 63, 290, 477, 663, 10154, 1106, 8162, 59, 77, 59, 77, 4458, 18982, 7, 448, 6978, 4008, 198, 220, 220, 220, 220, 220, 220, 220, 220, 220, 220, 220, 4423, 346, 13, 81, 16762, 631, 7, 448, 6978, 11, 8856, 62, 48277, 28, 17821, 8, 198, 220, 220, 220, 220, 220, 220, 220, 2073, 25, 198, 220, 220, 220, 220, 220, 220, 220, 220, 220, 220, 220, 3601, 10786, 59, 77, 26410, 8619, 4600, 90, 92, 63, 1541, 7160, 13, 17220, 340, 717, 416, 4634, 25, 374, 9132, 343, 28, 17821, 59, 77, 4458, 18982, 7, 448, 6978, 4008, 198, 220, 220, 220, 220, 220, 220, 220, 220, 198, 220, 220, 220, 1303, 15908, 62, 1069, 13955, 796, 17635, 611, 26672, 62, 1069, 13955, 318, 6045, 2073, 26672, 62, 1069, 13955, 220, 198, 220, 220, 220, 1303, 7753, 62, 1069, 13955, 796, 17635, 611, 2393, 62, 1069, 13955, 318, 6045, 2073, 2393, 62, 1069, 13955, 198, 220, 220, 220, 611, 28686, 13, 6978, 13, 4468, 576, 7, 6978, 2599, 198, 220, 220, 220, 220, 220, 220, 220, 20922, 18709, 273, 7, 6978, 11, 4235, 28, 14171, 11, 503, 6978, 28, 448, 6978, 11, 287, 5372, 28, 259, 5372, 1267, 198, 220, 220, 220, 1288, 361, 850, 15908, 82, 25, 198, 220, 220, 220, 220, 220, 220, 220, 329, 26672, 3672, 11, 850, 15908, 82, 11, 3696, 287, 28686, 13, 11152, 7, 6978, 2599, 198, 220, 220, 220, 220, 220, 220, 220, 220, 220, 220, 220, 19607, 62, 23814, 7, 7266, 15908, 82, 11, 26672, 62, 1069, 13955, 11, 407, 2291, 62, 30342, 8, 198, 220, 220, 220, 220, 220, 220, 220, 220, 220, 220, 220, 19607, 62, 23814, 7, 16624, 11, 2393, 62, 1069, 13955, 11, 407, 2291, 62, 30342, 8, 198, 220, 220, 220, 220, 220, 220, 220, 220, 220, 220, 220, 4808, 14681, 7, 448, 6978, 8, 198, 220, 220, 220, 1303, 611, 3804, 257, 2060, 2393, 2138, 621, 8619, 3108, 198, 220, 220, 220, 2073, 25, 198, 220, 220, 220, 220, 220, 220, 220, 3696, 28, 418, 13, 4868, 15908, 7, 6978, 8, 198, 220, 220, 220, 220, 220, 220, 220, 19607, 62, 23814, 7, 16624, 11, 2393, 62, 1069, 13955, 11, 407, 2291, 62, 30342, 8, 198, 220, 220, 220, 220, 220, 220, 220, 26672, 3672, 28, 6978, 198, 220, 220, 220, 220, 220, 220, 220, 4808, 14681, 7, 448, 6978, 8, 198, 220, 220, 220, 220, 220, 220, 220, 220, 198, 2, 28768, 48992, 351, 257, 2393, 62, 41341, 481, 1487, 262, 2685, 1181, 287, 1459, 26672, 198, 2, 2504, 318, 11, 43935, 389, 13686, 287, 1295, 788, 1976, 3949, 198, 2, 464, 43935, 355, 1775, 287, 262, 26672, 481, 4079, 883, 287, 262, 19974, 7753, 198, 2, 1135, 714, 13096, 428, 9172, 523, 340, 857, 407, 2689, 2656, 43935, 30, 198, 4299, 48992, 7, 15908, 1462, 13344, 11, 19974, 34345, 11, 198, 220, 220, 220, 220, 220, 220, 220, 220, 220, 220, 2291, 62, 30342, 28, 25101, 11, 198, 220, 220, 220, 220, 220, 220, 220, 220, 220, 220, 26672, 62, 1069, 13955, 28, 14202, 11, 198, 220, 220, 220, 220, 220, 220, 220, 220, 220, 220, 2393, 62, 1069, 13955, 28, 14202, 11, 220, 198, 220, 220, 220, 220, 220, 220, 220, 220, 220, 220, 2393, 62, 41341, 28, 14202, 11, 198, 220, 220, 220, 220, 220, 220, 220, 220, 220, 220, 989, 5715, 28, 16, 11, 374, 9132, 343, 28, 25101, 11, 220, 198, 220, 220, 220, 220, 220, 220, 220, 220, 220, 220, 19974, 62, 33295, 28, 25101, 2599, 198, 220, 220, 220, 705, 7061, 38636, 262, 10154, 286, 257, 8619, 290, 663, 850, 12942, 1749, 705, 7061, 198, 220, 220, 220, 220, 220, 198, 220, 220, 220, 2393, 62, 1069, 13955, 796, 1351, 1958, 7, 7753, 62, 1069, 13955, 8, 198, 220, 220, 220, 26672, 62, 1069, 13955, 796, 1351, 1958, 7, 15908, 62, 1069, 13955, 8, 628, 220, 220, 220, 19974, 62, 525, 3411, 796, 366, 64, 1, 611, 19974, 62, 33295, 2073, 366, 86, 1, 198, 220, 220, 220, 1303, 16447, 257, 649, 14, 35666, 5592, 19974, 2393, 11, 2138, 621, 24443, 611, 19974, 7753, 1541, 7160, 198, 220, 220, 220, 1976, 69, 796, 19974, 7753, 13, 41729, 8979, 7, 13344, 34345, 11, 19974, 62, 525, 3411, 11, 19794, 28, 13344, 7753, 13, 57, 4061, 62, 7206, 3697, 11617, 8, 198, 220, 220, 220, 220, 198, 220, 220, 220, 1303, 3987, 470, 19974, 3696, 286, 976, 1438, 355, 262, 19974, 2393, 356, 389, 4441, 198, 220, 220, 220, 2393, 62, 1069, 13955, 13, 33295, 7, 13344, 34345, 8, 628, 220, 220, 220, 1303, 611, 356, 423, 655, 257, 2060, 2393, 284, 19974, 290, 407, 257, 26672, 11, 19974, 326, 198, 220, 220, 220, 611, 28686, 13, 6978, 13, 4468, 576, 7, 15908, 1462, 13344, 2599, 198, 220, 220, 220, 220, 220, 220, 220, 1976, 69, 13, 13564, 7, 15908, 1462, 13344, 8, 198, 220, 220, 220, 1288, 361, 28686, 13, 6978, 13, 9409, 343, 7, 15908, 1462, 13344, 2599, 198, 220, 220, 220, 220, 220, 220, 220, 1303, 5450, 1378, 25558, 2502, 11125, 13, 785, 14, 64, 14, 34125, 41544, 2548, 14, 2231, 2857, 4790, 198, 220, 220, 220, 220, 220, 220, 220, 329, 26672, 3672, 11, 850, 15908, 82, 11, 3696, 287, 28686, 13, 11152, 7, 15908, 1462, 13344, 2599, 198, 220, 220, 220, 220, 220, 220, 220, 220, 220, 220, 220, 19607, 62, 23814, 7, 7266, 15908, 82, 11, 26672, 62, 1069, 13955, 11, 407, 2291, 62, 30342, 8, 198, 220, 220, 220, 220, 220, 220, 220, 220, 220, 220, 220, 19607, 62, 23814, 7, 16624, 11, 2393, 62, 1069, 13955, 11, 407, 2291, 62, 30342, 8, 198, 220, 220, 220, 220, 220, 220, 220, 220, 220, 220, 220, 3601, 10786, 18709, 278, 8619, 25, 23884, 4458, 18982, 7, 15908, 3672, 4008, 198, 220, 220, 220, 220, 220, 220, 220, 220, 220, 220, 220, 1976, 69, 13, 13564, 7, 15908, 3672, 8, 198, 220, 220, 220, 220, 220, 220, 220, 220, 220, 220, 220, 351, 3904, 13, 33723, 5657, 7, 16624, 8, 355, 2318, 25, 198, 220, 220, 220, 220, 220, 220, 220, 220, 220, 220, 220, 220, 220, 220, 220, 329, 29472, 287, 2318, 25, 198, 220, 220, 220, 220, 220, 220, 220, 220, 220, 220, 220, 220, 220, 220, 220, 220, 220, 220, 220, 611, 989, 5715, 29, 16, 25, 4798, 7, 34345, 8, 198, 220, 220, 220, 220, 220, 220, 220, 220, 220, 220, 220, 220, 220, 220, 220, 220, 220, 220, 220, 2393, 6978, 3672, 28, 418, 13, 6978, 13, 22179, 7, 15908, 3672, 11, 29472, 8, 198, 220, 220, 220, 220, 220, 220, 220, 220, 220, 220, 220, 220, 220, 220, 220, 220, 220, 220, 220, 1303, 1858, 318, 645, 966, 1262, 705, 5143, 10354, 611, 612, 318, 281, 4049, 11, 299, 65, 1102, 1851, 481, 2038, 198, 220, 220, 220, 220, 220, 220, 220, 220, 220, 220, 220, 220, 220, 220, 220, 220, 220, 220, 220, 611, 2393, 62, 41341, 287, 37250, 20063, 26410, 3256, 705, 5143, 3152, 9139, 5965, 20520, 290, 29472, 13, 437, 2032, 342, 7, 4458, 541, 2047, 65, 6, 2599, 198, 220, 220, 220, 220, 220, 220, 220, 220, 220, 220, 220, 220, 220, 220, 220, 220, 220, 220, 220, 220, 220, 220, 220, 1303, 1212, 20718, 1735, 3048, 532, 43935, 389, 13686, 287, 1459, 3108, 198, 220, 220, 220, 220, 220, 220, 220, 220, 220, 220, 220, 220, 220, 220, 220, 220, 220, 220, 220, 220, 220, 220, 220, 1303, 19926, 356, 466, 428, 287, 257, 45218, 7753, 30, 198, 220, 220, 220, 220, 220, 220, 220, 220, 220, 220, 220, 220, 220, 220, 220, 220, 220, 220, 220, 220, 220, 220, 220, 20922, 18709, 273, 7, 7753, 6978, 3672, 11, 4235, 28, 7753, 62, 41341, 11, 287, 5372, 28, 17821, 8, 198, 220, 220, 220, 220, 220, 220, 220, 220, 220, 220, 220, 220, 220, 220, 220, 220, 220, 220, 220, 1976, 69, 13, 13564, 7, 7753, 6978, 3672, 8, 198, 220, 220, 220, 1976, 69, 13, 19836, 3419, 198, 220, 220, 220, 220, 198, 220, 220, 220, 1303, 3792, 428, 1165, 17564, 12248, 198, 220, 220, 220, 1303, 361, 374, 9132, 343, 25, 4423, 346, 13, 81, 16762, 631, 7, 15908, 1462, 13344, 11, 8856, 62, 48277, 28, 17821, 8, 198, 220, 220, 220, 1441, 19974, 34345, 198, 220, 220, 220, 220, 198, 4299, 2641, 41729, 7, 89, 22184, 11, 989, 28, 17821, 2599, 198, 220, 220, 220, 705, 7061, 6803, 2641, 257, 19974, 2393, 13, 198, 220, 220, 220, 220, 220, 220, 220, 383, 989, 4909, 1440, 15180, 25, 2393, 62, 7857, 11, 2393, 25388, 2546, 11, 4818, 8079, 290, 29472, 13, 198, 220, 220, 220, 220, 220, 220, 220, 25700, 989, 28, 17821, 5860, 257, 2495, 10398, 989, 13, 705, 7061, 198, 220, 220, 220, 611, 407, 28686, 13, 6978, 13, 4468, 576, 7, 89, 22184, 2599, 198, 220, 220, 220, 220, 220, 220, 220, 3601, 7203, 59, 77, 44217, 986, 23884, 1595, 470, 1283, 284, 307, 257, 2393, 30, 59, 77, 1911, 18982, 7, 89, 22184, 4008, 198, 220, 220, 220, 220, 220, 220, 220, 1441, 198, 220, 220, 220, 3601, 10786, 59, 77, 15784, 2641, 19974, 7753, 25, 23884, 59, 77, 4458, 18982, 7, 89, 22184, 4008, 198, 220, 220, 220, 277, 89, 28, 13344, 7753, 13, 41729, 8979, 7, 89, 22184, 8, 198, 220, 220, 220, 220, 198, 220, 220, 220, 256, 742, 28, 21737, 198, 220, 220, 220, 329, 24714, 287, 277, 89, 13, 259, 9062, 396, 33529, 198, 220, 220, 220, 220, 220, 220, 220, 256, 742, 13, 33295, 7, 685, 22184, 13, 7753, 62, 7857, 11, 198, 220, 220, 220, 220, 220, 220, 220, 220, 220, 220, 220, 220, 220, 220, 220, 220, 220, 220, 220, 220, 24714, 13, 5589, 601, 62, 7857, 11, 198, 220, 220, 220, 220, 220, 220, 220, 220, 220, 220, 220, 220, 220, 220, 220, 220, 220, 220, 220, 220, 4818, 8079, 13, 19608, 8079, 46491, 22184, 13, 4475, 62, 2435, 737, 26786, 18982, 22784, 198, 220, 220, 220, 220, 220, 220, 220, 220, 220, 220, 220, 220, 220, 220, 220, 220, 220, 220, 220, 220, 24714, 13, 34345, 60, 1267, 198, 220, 220, 220, 220, 220, 220, 220, 3601, 10786, 90, 5512, 1391, 5512, 1391, 5512, 23884, 4458, 18982, 7, 22184, 13, 7753, 62, 7857, 11, 198, 220, 220, 220, 220, 220, 220, 220, 220, 220, 220, 220, 220, 220, 220, 220, 220, 220, 220, 220, 220, 24714, 13, 5589, 601, 62, 7857, 11, 198, 220, 220, 220, 220, 220, 220, 220, 220, 220, 220, 220, 220, 220, 220, 220, 220, 220, 220, 220, 220, 4818, 8079, 13, 19608, 8079, 46491, 22184, 13, 4475, 62, 2435, 737, 26786, 18982, 22784, 198, 220, 220, 220, 220, 220, 220, 220, 220, 220, 220, 220, 220, 220, 220, 220, 220, 220, 220, 220, 220, 24714, 13, 34345, 4008, 198, 220, 220, 220, 7400, 5039, 7, 14116, 11, 24697, 28, 17816, 13295, 41707, 41729, 41707, 27354, 8079, 41707, 15235, 6, 4357, 11487, 69, 16762, 2625, 36439, 4943, 198, 220, 220, 220, 1441, 256, 742, 220, 220, 198, 198, 31, 12976, 13, 21812, 3419, 198, 31, 12976, 13, 18076, 10786, 438, 7753, 12, 41341, 3256, 29001, 81, 3256, 2099, 28, 12976, 13, 46770, 7, 17816, 20063, 26410, 3256, 705, 5143, 3152, 9139, 5965, 20520, 4008, 198, 31, 12976, 13, 18076, 10786, 438, 17256, 12, 30342, 16624, 3256, 705, 12, 39, 3256, 318, 62, 32109, 28, 17821, 11, 1037, 11639, 818, 9152, 7104, 3696, 11537, 198, 31, 12976, 13, 18076, 10786, 438, 1069, 9152, 12, 15908, 3256, 705, 12, 55, 3256, 3294, 28, 17821, 11, 2099, 28, 12976, 13, 15235, 7, 411, 6442, 62, 6978, 28, 25101, 828, 1037, 11639, 3109, 9152, 7368, 8619, 11537, 198, 31, 12976, 13, 18076, 10786, 438, 1069, 9152, 12, 7753, 3256, 29001, 87, 3256, 3294, 28, 17821, 11, 4906, 28, 12976, 13, 15235, 7, 411, 6442, 62, 6978, 28, 25101, 828, 1037, 11639, 3109, 9152, 7368, 2393, 11537, 198, 31, 12976, 13, 18076, 10786, 438, 13344, 62, 33295, 3256, 29001, 64, 3256, 318, 62, 32109, 28, 17821, 11, 1037, 11639, 4550, 284, 4683, 19974, 2393, 11537, 198, 31, 12976, 13, 49140, 10786, 6978, 3256, 2099, 28, 12976, 13, 15235, 7, 411, 6442, 62, 6978, 28, 25101, 4008, 198, 2, 31, 12976, 13, 49140, 10786, 13344, 7753, 3256, 2099, 28, 12976, 13, 8979, 10786, 39346, 6, 4008, 198, 31, 12976, 13, 49140, 10786, 13344, 7753, 3256, 2099, 28, 12976, 13, 15235, 28955, 198, 4299, 537, 72, 62, 13344, 7, 7753, 62, 41341, 11, 2291, 62, 30342, 16624, 11, 19607, 62, 15908, 11, 19607, 62, 7753, 11, 19974, 62, 33295, 11, 3108, 11, 19974, 7753, 2599, 198, 220, 220, 220, 37227, 16447, 257, 19974, 2393, 422, 262, 10154, 286, 257, 7368, 8619, 13, 198, 220, 220, 220, 220, 198, 220, 220, 220, 383, 48992, 460, 42976, 1057, 257, 20922, 12649, 319, 43935, 878, 1976, 4501, 606, 284, 2198, 326, 477, 4778, 389, 1057, 393, 477, 4778, 389, 12539, 13, 198, 220, 220, 220, 37227, 198, 220, 220, 220, 3601, 10786, 1639, 1276, 307, 7165, 1262, 428, 986, 11537, 628, 220, 220, 220, 611, 407, 19974, 62, 33295, 25, 198, 220, 220, 220, 220, 220, 220, 220, 3601, 7, 69, 1, 59, 77, 5886, 16502, 597, 2180, 1391, 13344, 7753, 92, 2393, 59, 77, 4943, 198, 220, 220, 220, 2073, 25, 198, 220, 220, 220, 220, 220, 220, 220, 3601, 7, 69, 1, 59, 77, 4677, 1571, 1976, 3949, 3696, 284, 25, 1391, 13344, 7753, 32239, 77, 4943, 628, 220, 220, 220, 24714, 796, 48992, 7, 6978, 11, 19974, 7753, 11, 198, 220, 220, 220, 220, 220, 220, 220, 220, 220, 220, 220, 220, 220, 220, 220, 2291, 62, 30342, 28, 17256, 62, 30342, 16624, 11, 198, 220, 220, 220, 220, 220, 220, 220, 220, 220, 220, 220, 220, 220, 220, 220, 26672, 62, 1069, 13955, 28, 1069, 9152, 62, 15908, 11, 198, 220, 220, 220, 220, 220, 220, 220, 220, 220, 220, 220, 220, 220, 220, 220, 2393, 62, 1069, 13955, 28, 1069, 9152, 62, 7753, 11, 220, 198, 220, 220, 220, 220, 220, 220, 220, 220, 220, 220, 220, 220, 220, 220, 220, 2393, 62, 41341, 28, 7753, 62, 41341, 11, 198, 220, 220, 220, 220, 220, 220, 220, 220, 220, 220, 220, 220, 220, 220, 220, 19974, 62, 33295, 28, 13344, 62, 33295, 8, 628, 220, 220, 220, 3601, 7, 69, 1, 59, 77, 41729, 2393, 25, 1391, 22184, 32239, 77, 4943, 198, 198, 31, 12976, 13, 21812, 3419, 198, 31, 12976, 13, 18076, 10786, 438, 39624, 3256, 705, 12, 80, 3256, 318, 62, 32109, 28, 17821, 11, 1037, 11639, 15979, 601, 262, 989, 2637, 8, 198, 31, 12976, 13, 18076, 10786, 438, 40539, 654, 3256, 705, 12, 86, 3256, 318, 62, 32109, 28, 17821, 11, 1037, 11639, 23114, 14601, 11537, 198, 31, 12976, 13, 49140, 10786, 34345, 3256, 2099, 28, 12976, 13, 15235, 7, 411, 6442, 62, 6978, 28, 17821, 828, 77, 22046, 10779, 16, 8, 198, 4299, 537, 72, 62, 13344, 1177, 7, 34345, 11, 14601, 11, 5897, 2599, 198, 220, 220, 220, 37227, 8053, 262, 10154, 286, 530, 393, 517, 7368, 19974, 16624, 13, 198, 220, 220, 220, 37227, 198, 220, 220, 220, 19974, 62, 3642, 658, 796, 17635, 198, 220, 220, 220, 329, 277, 287, 1351, 1958, 7, 34345, 2599, 198, 220, 220, 220, 220, 220, 220, 220, 19974, 62, 3642, 658, 13, 33295, 19510, 69, 11, 2641, 41729, 7, 69, 22305, 628, 220, 220, 220, 611, 14601, 290, 19974, 62, 3642, 658, 25, 198, 220, 220, 220, 220, 220, 220, 220, 329, 357, 47347, 11, 2378, 8, 287, 19974, 62, 3642, 658, 25, 198, 220, 220, 220, 220, 220, 220, 220, 220, 220, 220, 220, 3601, 7, 69, 1, 59, 77, 59, 77, 50155, 38636, 2393, 3081, 989, 25, 1391, 47347, 92, 29335, 28, 59, 77, 4943, 198, 220, 220, 220, 220, 220, 220, 220, 220, 220, 220, 220, 329, 1700, 287, 2378, 25, 198, 220, 220, 220, 220, 220, 220, 220, 220, 220, 220, 220, 220, 220, 220, 220, 611, 1700, 58, 16, 60, 1875, 352, 68, 21, 25, 198, 220, 220, 220, 220, 220, 220, 220, 220, 220, 220, 220, 220, 220, 220, 220, 220, 220, 220, 220, 3601, 7, 69, 1, 31502, 25, 19990, 90, 22105, 58, 18, 48999, 7879, 3073, 2407, 1588, 2393, 37913, 10734, 1096, 13, 77, 2541, 874, 1096, 7, 22105, 58, 15, 12962, 92, 555, 89, 3949, 11, 1391, 10734, 1096, 13, 77, 2541, 874, 1096, 7, 22105, 58, 16, 12962, 92, 25388, 8, 4943, 198, 220, 220, 220, 220, 220, 220, 220, 220, 220, 220, 220, 220, 220, 220, 220, 329, 4808, 6978, 287, 1700, 58, 18, 4083, 35312, 10786, 14, 6, 2599, 198, 220, 220, 220, 220, 220, 220, 220, 220, 220, 220, 220, 220, 220, 220, 220, 220, 220, 220, 220, 611, 18896, 28264, 6978, 8, 1875, 2026, 25, 198, 220, 220, 220, 220, 220, 220, 220, 220, 220, 220, 220, 220, 220, 220, 220, 220, 220, 220, 220, 220, 220, 220, 220, 3601, 7, 69, 1, 24908, 25, 262, 2393, 6978, 5002, 19990, 90, 62, 6978, 92, 7879, 287, 19990, 90, 22105, 58, 18, 48999, 7879, 318, 1165, 890, 357, 9806, 13, 2026, 34534, 8, 4943, 198, 220, 220, 220, 220, 220, 220, 220, 220, 220, 220, 220, 220, 220, 220, 220, 220, 220, 220, 220, 611, 4808, 6978, 13, 9688, 2032, 342, 7203, 526, 2599, 198, 220, 220, 220, 220, 220, 220, 220, 220, 220, 220, 220, 220, 220, 220, 220, 220, 220, 220, 220, 220, 220, 220, 220, 3601, 7, 69, 1, 31502, 25, 19990, 90, 22105, 58, 18, 48999, 7879, 318, 257, 7104, 2393, 14, 34945, 357, 4598, 345, 1107, 761, 340, 287, 262, 19974, 2393, 10091, 4943, 198, 220, 220, 220, 220, 220, 220, 220, 3601, 7203, 59, 77, 4770, 2559, 18604, 59, 77, 59, 77, 4943, 628, 198, 31, 12976, 13, 21812, 3419, 198, 31, 12976, 13, 18076, 10786, 438, 1069, 9152, 12, 15908, 3256, 29001, 55, 3256, 3294, 28, 17821, 11, 4906, 28, 12976, 13, 15235, 7, 411, 6442, 62, 6978, 28, 25101, 828, 1037, 11639, 5211, 407, 664, 12321, 832, 7368, 8619, 618, 40525, 5254, 2637, 8, 198, 31, 12976, 13, 18076, 10786, 438, 1069, 9152, 12, 7753, 3256, 29001, 87, 3256, 3294, 28, 17821, 11, 4906, 28, 12976, 13, 15235, 7, 411, 6442, 62, 6978, 28, 25101, 828, 1037, 11639, 3109, 9152, 7368, 2393, 11537, 198, 31, 12976, 13, 18076, 10786, 438, 448, 7753, 3256, 29001, 78, 3256, 2099, 28, 12976, 13, 15235, 7, 411, 6442, 62, 6978, 28, 25101, 828, 1037, 11639, 26410, 989, 2393, 13, 17446, 428, 9178, 284, 3359, 989, 319, 3141, 1627, 2637, 8, 198, 31, 12976, 13, 49140, 10786, 9288, 23814, 3256, 2099, 28, 12976, 13, 15235, 7, 411, 6442, 62, 6978, 28, 25101, 828, 77, 22046, 10779, 16, 8, 198, 4299, 537, 72, 62, 46803, 9288, 7, 19607, 62, 15908, 11, 19607, 62, 7753, 11, 503, 7753, 11, 1332, 23814, 2599, 198, 220, 220, 220, 37227, 14402, 7368, 43935, 290, 14, 273, 262, 43935, 287, 257, 7368, 8619, 393, 29196, 357, 63, 51, 6465, 2043, 39201, 63, 8, 1262, 262, 4600, 77, 17457, 524, 63, 13877, 329, 4600, 9078, 13, 9288, 44646, 198, 220, 220, 220, 220, 198, 220, 220, 220, 18162, 4600, 17209, 35273, 46803, 9288, 63, 1231, 597, 7368, 8619, 393, 2393, 481, 25432, 5254, 664, 1834, 2280, 422, 262, 1459, 8619, 866, 526, 15931, 198, 220, 220, 220, 1332, 23814, 796, 1332, 23814, 393, 705, 2637, 198, 220, 220, 220, 4808, 11295, 2070, 14402, 7, 9288, 23814, 11, 503, 7753, 11, 19607, 62, 15908, 11, 19607, 62, 7753, 8, 628, 198, 31, 12976, 13, 21812, 3419, 198, 31, 12976, 13, 18076, 10786, 438, 7753, 12, 41341, 3256, 29001, 81, 3256, 2099, 28, 12976, 13, 46770, 7, 17816, 20063, 26410, 3256, 705, 5143, 3152, 9139, 5965, 20520, 828, 1037, 11639, 8979, 12649, 4028, 326, 460, 307, 5625, 284, 43935, 1262, 4600, 46803, 1102, 1851, 63, 11537, 198, 31, 12976, 13, 18076, 10786, 438, 448, 6978, 3256, 705, 12, 46, 3256, 2099, 28, 12976, 13, 15235, 7, 411, 6442, 62, 6978, 28, 25101, 828, 1037, 11639, 6978, 284, 5072, 8619, 11537, 198, 31, 12976, 13, 18076, 10786, 438, 259, 5372, 14, 438, 3919, 12, 259, 5372, 3256, 12286, 28, 17821, 11, 1037, 11639, 10987, 20399, 319, 43935, 287, 5372, 11537, 198, 31, 12976, 13, 18076, 10786, 438, 1069, 9152, 12, 15908, 3256, 705, 12, 55, 3256, 3294, 28, 17821, 11, 2099, 28, 12976, 13, 15235, 7, 411, 6442, 62, 6978, 28, 25101, 828, 1037, 11639, 3109, 9152, 7368, 8619, 11537, 198, 31, 12976, 13, 18076, 10786, 438, 1069, 9152, 12, 7753, 3256, 29001, 87, 3256, 3294, 28, 17821, 11, 4906, 28, 12976, 13, 15235, 7, 411, 6442, 62, 6978, 28, 25101, 828, 1037, 11639, 3109, 9152, 7368, 2393, 11537, 198, 31, 12976, 13, 18076, 10786, 438, 17256, 12, 30342, 14, 438, 3919, 12, 17256, 12, 30342, 3256, 12286, 28, 25101, 11, 1037, 11639, 818, 9152, 7104, 3696, 11537, 198, 31, 12976, 13, 18076, 10786, 438, 81, 9132, 343, 14, 438, 3919, 12, 81, 9132, 343, 3256, 12286, 28, 25101, 11, 1037, 11639, 9787, 262, 5072, 8619, 318, 6565, 878, 356, 779, 340, 11537, 198, 31, 12976, 13, 18076, 10786, 438, 22019, 4372, 343, 14, 438, 3919, 12, 22019, 4372, 343, 3256, 12286, 28, 25101, 11, 1037, 11639, 18709, 3696, 287, 1459, 8619, 11537, 198, 31, 12976, 13, 18076, 10786, 438, 7266, 15908, 82, 14, 438, 3919, 12, 7266, 15908, 82, 3256, 12286, 28, 17821, 11, 1037, 11639, 18709, 3696, 287, 850, 12942, 1749, 11537, 198, 31, 12976, 13, 18076, 10786, 438, 13116, 5715, 3256, 4277, 28, 16, 11, 1037, 11639, 42159, 1241, 11537, 198, 31, 12976, 13, 49140, 10786, 6978, 3256, 4906, 28, 12976, 13, 15235, 7, 411, 6442, 62, 6978, 28, 25101, 4008, 198, 4299, 537, 72, 62, 77, 1671, 403, 7, 7753, 62, 41341, 11, 503, 6978, 11, 287, 5372, 11, 19607, 62, 15908, 11, 19607, 62, 7753, 11, 2291, 62, 30342, 11, 374, 9132, 343, 11, 1090, 4372, 343, 11, 850, 15908, 82, 11, 989, 5715, 11, 3108, 2599, 198, 220, 220, 220, 37227, 43055, 12649, 329, 43935, 532, 3578, 262, 2836, 284, 1057, 299, 65, 1102, 1851, 4560, 319, 43935, 11, 884, 355, 2491, 477, 4778, 393, 17304, 477, 4778, 13, 198, 220, 220, 220, 220, 198, 220, 220, 220, 1675, 1057, 5254, 11, 779, 25, 256, 76, 35273, 46803, 9288, 198, 220, 220, 220, 220, 198, 220, 220, 220, 1675, 19974, 24512, 357, 4480, 262, 3038, 393, 2491, 20922, 20399, 319, 1976, 3949, 3696, 828, 779, 25, 256, 76, 35273, 13344, 198, 220, 220, 220, 37227, 198, 220, 220, 220, 8619, 18709, 273, 7, 6978, 11, 198, 220, 220, 220, 220, 220, 220, 220, 220, 220, 220, 220, 220, 220, 220, 220, 220, 220, 220, 220, 220, 220, 220, 4235, 28, 7753, 62, 41341, 11, 503, 6978, 28, 448, 6978, 11, 287, 5372, 28, 259, 5372, 11, 198, 220, 220, 220, 220, 220, 220, 220, 220, 220, 220, 220, 220, 220, 220, 220, 220, 220, 220, 220, 220, 220, 220, 2291, 62, 30342, 28, 17256, 62, 30342, 11, 198, 220, 220, 220, 220, 220, 220, 220, 220, 220, 220, 220, 220, 220, 220, 220, 220, 220, 220, 220, 220, 220, 220, 26672, 62, 1069, 13955, 28, 1069, 9152, 62, 15908, 11, 198, 220, 220, 220, 220, 220, 220, 220, 220, 220, 220, 220, 220, 220, 220, 220, 220, 220, 220, 220, 220, 220, 220, 2393, 62, 1069, 13955, 28, 1069, 9152, 62, 7753, 11, 374, 9132, 343, 28, 81, 9132, 343, 11, 1090, 4372, 343, 28, 22019, 4372, 343, 11, 198, 220, 220, 220, 220, 220, 220, 220, 220, 220, 220, 220, 220, 220, 220, 220, 220, 220, 220, 220, 220, 220, 220, 850, 15908, 82, 28, 7266, 15908, 82, 11, 13116, 5715, 28, 13116, 5715, 8, 628, 628, 198, 6738, 33084, 1330, 38994, 198, 11748, 651, 6603, 198, 198, 11748, 2779, 2414, 198, 11748, 18931, 198, 6738, 33084, 13, 38, 10060, 16922, 1330, 38994, 16922, 198, 198, 4299, 651, 62, 26270, 62, 1640, 62, 12985, 7, 260, 1930, 37765, 11, 7621, 2599, 198, 220, 220, 220, 37227, 198, 220, 220, 220, 16409, 257, 4589, 9485, 38, 10060, 2134, 329, 262, 7368, 16099, 290, 7621, 13, 198, 220, 220, 220, 37227, 198, 220, 220, 220, 13737, 796, 16099, 13, 1136, 62, 1671, 12140, 3419, 198, 220, 220, 220, 14451, 62, 1671, 12140, 796, 685, 15699, 329, 2872, 287, 13737, 611, 2872, 13, 3672, 6624, 7621, 60, 198, 220, 220, 220, 611, 14451, 62, 1671, 12140, 25, 198, 220, 220, 220, 220, 220, 220, 220, 1441, 14451, 62, 1671, 12140, 58, 15, 4083, 41509, 13, 26270, 628, 220, 220, 220, 15940, 796, 16099, 13, 1136, 62, 31499, 3419, 198, 220, 220, 220, 14451, 62, 31499, 796, 685, 15699, 329, 2872, 287, 15940, 611, 2872, 13, 3672, 6624, 7621, 60, 198, 220, 220, 220, 611, 407, 14451, 62, 31499, 25, 198, 220, 220, 220, 220, 220, 220, 220, 5298, 11052, 12331, 10786, 2949, 17467, 393, 20551, 7160, 351, 326, 1438, 11537, 198, 220, 220, 220, 1441, 14451, 62, 31499, 58, 15, 4083, 41509, 13, 26270, 198, 198, 4299, 4321, 62, 34945, 7, 260, 1930, 37765, 11, 427, 64, 11, 4382, 62, 6978, 11, 503, 6978, 11639, 456, 62, 15002, 82, 3256, 2393, 62, 41341, 28, 14202, 2599, 198, 220, 220, 220, 37227, 198, 220, 220, 220, 10472, 477, 10154, 379, 4382, 62, 6978, 351, 4589, 7621, 427, 64, 287, 198, 220, 220, 220, 262, 16099, 13, 198, 220, 220, 220, 37227, 198, 220, 220, 220, 10154, 796, 16099, 13, 1136, 62, 15908, 62, 3642, 658, 7, 15388, 62, 6978, 11, 1006, 28, 26270, 8, 198, 220, 220, 220, 611, 407, 28686, 13, 6978, 13, 1069, 1023, 7, 448, 6978, 2599, 198, 220, 220, 220, 220, 220, 220, 220, 28686, 13, 76, 4335, 17062, 7, 448, 6978, 8, 198, 220, 220, 220, 220, 220, 220, 220, 220, 220, 220, 220, 220, 198, 220, 220, 220, 329, 2695, 287, 10154, 25, 198, 220, 220, 220, 220, 220, 220, 220, 3601, 7203, 10002, 278, 25, 4064, 82, 1, 4064, 2695, 13, 6978, 8, 198, 220, 220, 220, 220, 220, 220, 220, 611, 2695, 13, 4906, 6624, 705, 15908, 10354, 198, 220, 220, 220, 220, 220, 220, 220, 220, 220, 220, 220, 4321, 62, 34945, 7, 260, 1930, 37765, 11, 427, 64, 11, 2695, 13, 6978, 11, 31051, 4458, 22179, 26933, 448, 6978, 11, 11299, 13, 3672, 60, 4008, 198, 220, 220, 220, 220, 220, 220, 220, 2073, 25, 198, 220, 220, 220, 220, 220, 220, 220, 220, 220, 220, 220, 1949, 25, 198, 220, 220, 220, 220, 220, 220, 220, 220, 220, 220, 220, 220, 220, 220, 220, 3108, 796, 2695, 13, 6978, 198, 220, 220, 220, 220, 220, 220, 220, 220, 220, 220, 220, 220, 220, 220, 220, 2393, 62, 11299, 796, 16099, 13, 1136, 62, 3642, 658, 7, 6978, 11, 1006, 28, 26270, 8, 198, 220, 220, 220, 220, 220, 220, 220, 220, 220, 220, 220, 220, 220, 220, 220, 2393, 62, 7890, 796, 2779, 2414, 13, 65, 2414, 12501, 1098, 7, 7753, 62, 11299, 13, 11299, 8, 198, 220, 220, 220, 220, 220, 220, 220, 220, 220, 220, 220, 220, 220, 220, 220, 503, 6978, 7753, 11639, 14, 4458, 22179, 26933, 448, 6978, 11, 11299, 13, 3672, 12962, 198, 220, 220, 220, 220, 220, 220, 220, 220, 220, 220, 220, 220, 220, 220, 220, 2393, 62, 448, 796, 1280, 7, 448, 6978, 7753, 11, 366, 39346, 4943, 198, 220, 220, 220, 220, 220, 220, 220, 220, 220, 220, 220, 220, 220, 220, 220, 2393, 62, 448, 13, 13564, 7, 7753, 62, 7890, 8, 198, 220, 220, 220, 220, 220, 220, 220, 220, 220, 220, 220, 220, 220, 220, 220, 2393, 62, 448, 13, 19836, 3419, 198, 220, 220, 220, 220, 220, 220, 220, 220, 220, 220, 220, 2845, 357, 9399, 12331, 11, 33084, 13, 38, 10060, 16922, 8, 355, 2859, 25, 198, 220, 220, 220, 220, 220, 220, 220, 220, 220, 220, 220, 220, 220, 220, 220, 1303, 1532, 356, 2038, 625, 780, 286, 257, 1588, 4130, 11, 779, 262, 1366, 40391, 329, 262, 4321, 198, 220, 220, 220, 220, 220, 220, 220, 220, 220, 220, 220, 220, 220, 220, 220, 1005, 11, 18224, 28, 41194, 13, 22046, 198, 220, 220, 220, 220, 220, 220, 220, 220, 220, 220, 220, 220, 220, 220, 220, 611, 705, 20500, 6, 287, 4049, 290, 4049, 17816, 20500, 20520, 855, 6, 3673, 4062, 10354, 198, 220, 220, 220, 220, 220, 220, 220, 220, 220, 220, 220, 220, 220, 220, 220, 220, 220, 220, 220, 3601, 10786, 44217, 986, 2393, 407, 1043, 30, 23884, 4458, 18982, 7, 6978, 4008, 198, 220, 220, 220, 220, 220, 220, 220, 220, 220, 220, 220, 220, 220, 220, 220, 1288, 361, 705, 48277, 6, 287, 4049, 290, 4049, 17816, 48277, 6, 7131, 15, 7131, 6, 8189, 20520, 855, 6, 18820, 62, 11664, 10354, 198, 220, 220, 220, 220, 220, 220, 220, 220, 220, 220, 220, 220, 220, 220, 220, 220, 220, 220, 220, 1303, 4798, 10786, 986, 11664, 2393, 11, 2111, 44812, 4321, 2427, 986, 11537, 198, 220, 220, 220, 220, 220, 220, 220, 220, 220, 220, 220, 220, 220, 220, 220, 220, 220, 220, 220, 2393, 62, 11299, 796, 16099, 13, 1136, 62, 18300, 62, 2436, 672, 7, 11299, 13, 26270, 8, 198, 220, 220, 220, 220, 220, 220, 220, 220, 220, 220, 220, 220, 220, 220, 220, 220, 220, 220, 220, 2393, 62, 7890, 796, 2779, 2414, 13, 65, 2414, 12501, 1098, 7, 7753, 62, 11299, 13, 11299, 8, 198, 220, 220, 220, 220, 220, 220, 220, 220, 220, 220, 220, 220, 220, 220, 220, 220, 220, 220, 220, 2393, 62, 448, 796, 1280, 10786, 14, 4458, 22179, 26933, 448, 6978, 11, 11299, 13, 3672, 46570, 366, 39346, 4943, 198, 220, 220, 220, 220, 220, 220, 220, 220, 220, 220, 220, 220, 220, 220, 220, 220, 220, 220, 220, 2393, 62, 448, 13, 13564, 7, 7753, 62, 7890, 8, 198, 220, 220, 220, 220, 220, 220, 220, 220, 220, 220, 220, 220, 220, 220, 220, 220, 220, 220, 220, 2393, 62, 448, 13, 19836, 3419, 198, 220, 220, 220, 220, 220, 220, 220, 220, 220, 220, 220, 220, 220, 220, 220, 1303, 6404, 2667, 13, 18224, 10786, 12331, 7587, 4064, 82, 25, 4064, 82, 3256, 2695, 13, 6978, 11, 2859, 8, 198, 220, 220, 220, 220, 220, 220, 220, 220, 220, 220, 220, 1303, 361, 2695, 13, 3672, 13, 437, 2032, 342, 7, 4458, 541, 2047, 65, 11537, 290, 2393, 62, 41341, 287, 37250, 20063, 26410, 3256, 705, 20063, 26410, 14402, 41707, 5143, 3152, 9139, 5965, 6, 2361, 25, 198, 220, 220, 220, 220, 220, 220, 220, 220, 220, 220, 220, 1303, 220, 220, 220, 220, 220, 220, 220, 20922, 18709, 273, 7, 448, 6978, 7753, 11, 2393, 62, 41341, 8, 628, 198, 7206, 38865, 62, 2200, 16402, 11639, 4625, 39239, 774, 14, 17209, 35273, 6, 198, 198, 31, 12976, 13, 21812, 3419, 198, 31, 12976, 13, 18076, 10786, 438, 12567, 12, 7220, 3256, 705, 12, 84, 3256, 220, 1037, 2625, 7120, 38994, 20579, 19570, 198, 31, 12976, 13, 18076, 10786, 438, 28712, 3256, 7808, 62, 15414, 28, 17821, 11, 198, 220, 220, 220, 220, 220, 220, 220, 220, 220, 220, 220, 220, 220, 12641, 62, 16963, 457, 28, 25101, 8, 198, 31, 12976, 13, 18076, 10786, 438, 260, 7501, 3256, 29001, 81, 3256, 6152, 11639, 6207, 13264, 37913, 30072, 4458, 18982, 7, 7206, 38865, 62, 2200, 16402, 828, 198, 220, 220, 220, 220, 220, 220, 220, 220, 220, 220, 220, 220, 220, 1037, 11639, 6207, 13264, 1438, 11537, 198, 31, 12976, 13, 18076, 10786, 438, 1671, 3702, 3256, 29001, 65, 3256, 16794, 11639, 33, 25642, 393, 7621, 284, 4321, 11537, 198, 31, 12976, 13, 18076, 10786, 438, 34945, 3256, 1037, 11639, 43055, 284, 4321, 357, 273, 25, 477, 8, 11537, 198, 31, 12976, 13, 18076, 10786, 438, 82, 9586, 343, 3256, 4906, 28, 12976, 13, 15235, 7, 411, 6442, 62, 6978, 28, 25101, 828, 198, 220, 220, 220, 220, 220, 220, 220, 220, 220, 220, 220, 220, 220, 1037, 11639, 43055, 284, 4321, 29924, 1220, 29924, 26672, 656, 26, 4277, 318, 26672, 1438, 11537, 198, 31, 12976, 13, 18076, 10786, 438, 7753, 12, 41341, 3256, 2099, 28, 12976, 13, 46770, 7, 17816, 20063, 26410, 3256, 705, 5143, 3152, 9139, 5965, 20520, 828, 1037, 11639, 19722, 453, 11986, 257, 2393, 12649, 284, 307, 1057, 1028, 15680, 43935, 2637, 8, 198, 31, 12976, 13, 18076, 10786, 438, 13344, 14, 438, 3919, 12, 13344, 3256, 4277, 28, 25101, 11, 1037, 11639, 19722, 453, 2251, 257, 19974, 2393, 286, 262, 15680, 16099, 14, 34945, 351, 262, 976, 1438, 355, 262, 16099, 14, 34945, 2637, 8, 198, 31, 12976, 13, 18076, 10786, 438, 18439, 14, 438, 3919, 12, 18439, 3256, 4277, 28, 17821, 11, 1037, 2625, 3886, 4277, 11, 1057, 351, 6284, 357, 16963, 457, 329, 18031, 8, 4943, 198, 31, 12976, 13, 18076, 10786, 438, 4480, 12, 41989, 3256, 29001, 83, 3256, 271, 62, 32109, 28, 17821, 11, 1037, 2625, 10987, 5254, 319, 43935, 706, 4321, 4943, 198, 31, 12976, 13, 18076, 10786, 438, 6404, 7753, 3256, 4906, 28, 12976, 13, 15235, 7, 411, 6442, 62, 6978, 28, 25101, 828, 1037, 11639, 15235, 284, 2604, 7753, 11537, 198, 4299, 537, 72, 62, 18300, 260, 1930, 7, 12567, 62, 7220, 11, 9206, 11, 29924, 11, 8478, 11, 8619, 11, 7448, 343, 11, 2393, 62, 41341, 11, 19974, 11, 6284, 11, 351, 62, 41989, 11, 2604, 7753, 2599, 198, 220, 220, 220, 37227, 10002, 3696, 422, 257, 7368, 8478, 287, 257, 1948, 17606, 16099, 13, 198, 220, 220, 220, 220, 198, 220, 220, 220, 383, 4321, 460, 635, 307, 3614, 284, 655, 262, 10154, 286, 257, 7368, 8619, 13, 198, 220, 220, 220, 220, 198, 220, 220, 220, 2094, 470, 5490, 326, 612, 804, 284, 307, 257, 1256, 286, 7159, 532, 345, 481, 307, 12053, 329, 606, 611, 345, 655, 1057, 25, 256, 76, 35273, 18300, 260, 1930, 198, 220, 220, 220, 37227, 198, 220, 220, 220, 220, 198, 220, 220, 220, 611, 6284, 393, 33084, 62, 7220, 25, 198, 220, 220, 220, 220, 220, 220, 220, 611, 407, 33084, 62, 7220, 25, 33084, 62, 7220, 796, 3904, 13, 16963, 457, 10786, 59, 77, 38, 10060, 20579, 11537, 198, 220, 220, 220, 220, 220, 220, 220, 611, 407, 9206, 25, 9206, 796, 3904, 13, 16963, 457, 10786, 59, 77, 38, 10060, 9206, 3256, 7808, 62, 15414, 28, 17821, 8, 198, 220, 220, 220, 220, 220, 220, 220, 33084, 796, 38994, 7, 12567, 62, 7220, 11, 9206, 8, 198, 220, 220, 220, 220, 220, 220, 220, 1303, 15307, 356, 821, 5291, 645, 9206, 986, 198, 220, 220, 220, 220, 220, 220, 220, 9206, 796, 6045, 198, 220, 220, 220, 220, 220, 220, 220, 6284, 796, 6407, 198, 220, 220, 220, 2073, 25, 33084, 796, 38994, 3419, 628, 198, 220, 220, 220, 611, 6284, 25, 198, 220, 220, 220, 220, 220, 220, 220, 2836, 796, 33084, 13, 1136, 62, 7220, 3419, 198, 220, 220, 220, 220, 220, 220, 220, 1303, 9971, 38189, 796, 33084, 13, 1136, 62, 7220, 22446, 1136, 62, 2398, 82, 3419, 198, 220, 220, 220, 220, 220, 220, 220, 3601, 10786, 11187, 2667, 656, 17606, 355, 23884, 37913, 30072, 4458, 18982, 7, 12567, 62, 7220, 11, 2836, 13, 3672, 4008, 198, 220, 220, 220, 220, 198, 220, 220, 220, 29924, 796, 29924, 393, 5550, 38865, 62, 2200, 16402, 198, 220, 220, 220, 16099, 796, 33084, 13, 1136, 62, 260, 7501, 7, 260, 7501, 8, 628, 220, 220, 220, 611, 407, 8478, 25, 198, 220, 220, 220, 220, 220, 220, 220, 3601, 10786, 59, 77, 9414, 12140, 1695, 7479, 77, 59, 83, 90, 92, 4458, 18982, 10786, 59, 77, 59, 83, 4458, 22179, 7, 12567, 62, 260, 7501, 62, 1671, 12140, 7, 260, 1930, 37765, 4008, 15306, 198, 220, 220, 220, 220, 220, 220, 220, 8478, 796, 3904, 13, 16963, 457, 10786, 59, 77, 13828, 8478, 30, 357, 9866, 8, 11537, 628, 220, 220, 220, 8478, 62, 273, 62, 12985, 62, 1462, 62, 15002, 796, 8478, 393, 705, 9866, 6, 198, 220, 220, 220, 427, 64, 796, 651, 62, 26270, 62, 1640, 62, 12985, 7, 260, 1930, 37765, 11, 8478, 62, 273, 62, 12985, 62, 1462, 62, 15002, 8, 198, 220, 220, 220, 220, 198, 220, 220, 220, 1194, 796, 10148, 198, 220, 220, 220, 981, 1194, 0, 11639, 12, 10354, 198, 220, 220, 220, 220, 220, 220, 220, 611, 407, 8619, 25, 198, 220, 220, 220, 220, 220, 220, 220, 220, 220, 220, 220, 611, 8478, 0, 11639, 9866, 10354, 198, 220, 220, 220, 220, 220, 220, 220, 220, 220, 220, 220, 220, 220, 220, 220, 10154, 796, 16099, 13, 1136, 62, 15908, 62, 3642, 658, 10786, 2637, 11, 1006, 28, 26270, 8, 198, 220, 220, 220, 220, 220, 220, 220, 220, 220, 220, 220, 2073, 25, 198, 220, 220, 220, 220, 220, 220, 220, 220, 220, 220, 220, 220, 220, 220, 220, 10154, 796, 16099, 13, 1136, 62, 15908, 62, 3642, 658, 10786, 2637, 8, 198, 220, 220, 220, 220, 220, 220, 220, 220, 220, 220, 220, 3601, 10786, 59, 77, 1639, 460, 4321, 477, 29196, 422, 428, 29924, 357, 439, 8, 393, 2922, 530, 7479, 77, 59, 83, 90, 92, 4458, 18982, 10786, 59, 77, 59, 83, 4458, 22179, 7, 12567, 62, 260, 7501, 62, 4852, 15908, 82, 7, 3642, 658, 35514, 198, 220, 220, 220, 220, 220, 220, 220, 220, 220, 220, 220, 8619, 796, 3904, 13, 16963, 457, 10786, 13828, 8619, 30, 357, 439, 8, 11537, 628, 220, 220, 220, 220, 220, 220, 220, 8619, 62, 1462, 62, 15002, 796, 705, 2637, 611, 357, 1662, 8619, 393, 8619, 855, 6, 439, 11537, 2073, 8619, 198, 220, 220, 220, 220, 220, 220, 220, 503, 6978, 796, 7448, 343, 393, 8619, 62, 1462, 62, 15002, 198, 220, 220, 220, 220, 220, 220, 220, 611, 503, 6978, 6624, 705, 2637, 290, 7448, 343, 5145, 11639, 2637, 25, 503, 6978, 28, 260, 7501, 13, 33491, 10786, 14, 41707, 62, 11537, 10, 6, 62, 16624, 6, 198, 220, 220, 220, 220, 220, 220, 220, 220, 198, 220, 220, 220, 220, 220, 220, 220, 31456, 11639, 59, 77, 16454, 986, 22023, 23884, 14, 90, 92, 4458, 18982, 7, 260, 7501, 11, 34945, 62, 1462, 62, 15002, 1267, 220, 198, 220, 220, 220, 220, 220, 220, 220, 611, 2393, 62, 41341, 318, 407, 6045, 25, 198, 220, 220, 220, 220, 220, 220, 220, 220, 220, 220, 220, 31456, 796, 31456, 1343, 705, 1262, 20922, 12649, 25, 23884, 4458, 18982, 7, 7753, 62, 41341, 8, 198, 220, 220, 220, 220, 220, 220, 220, 2073, 25, 31456, 796, 31456, 1343, 705, 351, 645, 20922, 7587, 6, 198, 220, 220, 220, 220, 220, 220, 220, 3601, 7, 19662, 8, 198, 220, 220, 220, 220, 220, 220, 220, 4321, 62, 34945, 7, 260, 1930, 37765, 11, 427, 64, 11, 8619, 62, 1462, 62, 15002, 11, 503, 6978, 11, 7753, 62, 41341, 1267, 628, 220, 220, 220, 220, 220, 220, 220, 611, 2393, 62, 41341, 287, 37250, 20063, 26410, 3256, 705, 20063, 26410, 14402, 41707, 5143, 3152, 9139, 5965, 6, 2361, 25, 198, 220, 220, 220, 220, 220, 220, 220, 220, 220, 220, 220, 3904, 13, 30328, 10786, 59, 77, 28768, 20922, 12649, 25, 23884, 4458, 18982, 7, 7753, 62, 41341, 4008, 198, 220, 220, 220, 220, 220, 220, 220, 220, 220, 220, 220, 8619, 18709, 273, 7, 448, 6978, 11, 4235, 28, 7753, 62, 41341, 11, 850, 15908, 82, 28, 17821, 11, 198, 220, 220, 220, 220, 220, 220, 220, 220, 220, 220, 220, 220, 220, 220, 220, 220, 220, 220, 220, 220, 220, 220, 220, 220, 220, 220, 220, 220, 220, 220, 220, 989, 5715, 28, 16, 11, 2604, 7753, 28, 6404, 7753, 8, 198, 220, 220, 220, 220, 220, 220, 220, 220, 220, 220, 220, 611, 2604, 7753, 25, 198, 220, 220, 220, 220, 220, 220, 220, 220, 220, 220, 220, 220, 220, 220, 220, 3904, 13, 30328, 10786, 59, 77, 11187, 3194, 284, 23884, 4458, 18982, 7, 6404, 7753, 4008, 628, 220, 220, 220, 220, 220, 220, 220, 611, 351, 62, 41989, 25, 198, 220, 220, 220, 220, 220, 220, 220, 220, 220, 220, 220, 3904, 13, 30328, 10786, 59, 77, 28768, 20922, 5254, 625, 25, 23884, 4458, 18982, 7, 448, 6978, 4008, 198, 220, 220, 220, 220, 220, 220, 220, 220, 220, 220, 220, 611, 407, 2604, 7753, 25, 2604, 7753, 796, 705, 41989, 13, 6404, 6, 198, 220, 220, 220, 220, 220, 220, 220, 220, 220, 220, 220, 4808, 11295, 2070, 14402, 7, 448, 6978, 11, 2604, 7753, 1267, 198, 220, 220, 220, 220, 220, 220, 220, 220, 220, 220, 220, 3904, 13, 30328, 10786, 59, 77, 11187, 3194, 284, 23884, 4458, 18982, 7, 6404, 7753, 4008, 198, 220, 220, 220, 220, 220, 220, 220, 220, 220, 220, 220, 220, 198, 220, 220, 220, 220, 220, 220, 220, 611, 19974, 25, 198, 220, 220, 220, 220, 220, 220, 220, 220, 220, 220, 220, 3601, 10786, 59, 77, 57, 4501, 656, 25, 23884, 14, 77, 1639, 743, 635, 765, 284, 12233, 262, 1762, 8619, 37913, 92, 737, 4458, 18982, 7, 260, 1930, 37765, 11, 503, 6978, 8, 1267, 198, 220, 220, 220, 220, 220, 220, 220, 220, 220, 220, 220, 48992, 7, 448, 6978, 11, 260, 1930, 37765, 8, 198, 220, 220, 220, 220, 220, 220, 220, 2073, 25, 198, 220, 220, 220, 220, 220, 220, 220, 220, 220, 220, 220, 3601, 10786, 59, 77, 59, 77, 2514, 19974, 262, 15680, 8619, 11, 1057, 1223, 588, 25, 23884, 4458, 18982, 10786, 17209, 35273, 13344, 1391, 78, 92, 1391, 89, 32239, 77, 59, 77, 2514, 1057, 257, 20922, 12649, 357, 3185, 51, 11053, 25, 1057, 3152, 9139, 5965, 11, 1598, 26410, 8, 981, 1976, 4501, 25, 256, 76, 35273, 13344, 45144, 78, 36786, 1391, 89, 92, 1377, 7753, 12, 41341, 39852, 2849, 59, 77, 4458, 18982, 7, 78, 28, 448, 6978, 11, 89, 28, 260, 1930, 37765, 13, 3672, 22305, 628, 220, 220, 220, 220, 220, 220, 220, 8619, 28, 7061, 198, 220, 220, 220, 220, 220, 220, 220, 1194, 796, 3904, 13, 16963, 457, 10786, 59, 10002, 1194, 8619, 422, 428, 8478, 30, 357, 2514, 11238, 25, 532, 8, 11537, 628, 220, 220, 220, 220, 1303, 51, 3727, 46, 198, 220, 220, 220, 220, 1303, 4798, 10786, 59, 77, 59, 77, 2514, 1057, 428, 3141, 757, 25, 23884, 4458, 18982, 28955, 198 ]
2.404883
11,018
#!/usr/bin/env """ class definitions for standard 1 variable plots class definitions for standard 2 variable plots class definitions for standard 3 variable plots History: -------- 2019-05-21: error in calculation used corrected udata to correct vdata """ # System Stack import datetime # science stack import numpy as np # Visual Stack import matplotlib as mpl mpl.use("Agg") import matplotlib.pyplot as plt from matplotlib.dates import ( YearLocator, WeekdayLocator, MonthLocator, DayLocator, HourLocator, DateFormatter, ) import matplotlib.ticker as ticker class TimeseriesPorpertyPropertyPlot(object): """ class to plot property vs property plots with density iso-contours""" mpl.rcParams["svg.fonttype"] = "none" mpl.rcParams["ps.fonttype"] = 42 mpl.rcParams["pdf.fonttype"] = 42 def __init__( self, fontsize=10, labelsize=10, plotstyle="k-.", stylesheet="seaborn-whitegrid" ): """Initialize the timeseries with items that do not change. This sets up the axes and station locations. The `fontsize` and `spacing` are also specified here to ensure that they are consistent between individual station elements. Parameters ---------- fontsize : int The fontsize to use for drawing text labelsize : int The fontsize to use for labels stylesheet : str Choose a mpl stylesheet [u'seaborn-darkgrid', u'seaborn-notebook', u'classic', u'seaborn-ticks', u'grayscale', u'bmh', u'seaborn-talk', u'dark_background', u'ggplot', u'fivethirtyeight', u'seaborn-colorblind', u'seaborn-deep', u'seaborn-whitegrid', u'seaborn-bright', u'seaborn-poster', u'seaborn-muted', u'seaborn-paper', u'seaborn-white', u'seaborn-pastel', u'seaborn-dark', u'seaborn-dark-palette'] """ self.fontsize = fontsize self.labelsize = labelsize self.plotstyle = plotstyle plt.style.use(stylesheet) @staticmethod def add_title(mooringid="", lat=-99.9, lon=-99.9, depth=9999, instrument=""): """Pass parameters to annotate the title of the plot This sets the standard plot title using common meta information from PMEL/EPIC style netcdf files Parameters ---------- mooringid : str Mooring Identifier lat : float The latitude of the mooring lon : float The longitude of the mooring depth : int Nominal depth of the instrument instrument : str Name/identifier of the instrument plotted """ ptitle = ( "Plotted on: {time:%Y/%m/%d %H:%M} \n from {mooringid} Lat: {latitude:3.3f} Lon: {longitude:3.3f}" " Depth: {depth}\n : {instrument}" ).format( time=datetime.datetime.now(), mooringid=mooringid, latitude=lat, longitude=lon, depth=depth, instrument=instrument, ) return ptitle @staticmethod
[ 2, 48443, 14629, 14, 8800, 14, 24330, 198, 198, 37811, 198, 4871, 17336, 329, 3210, 352, 7885, 21528, 198, 4871, 17336, 329, 3210, 362, 7885, 21528, 198, 4871, 17336, 329, 3210, 513, 7885, 21528, 628, 7443, 25, 198, 24200, 198, 13130, 12, 2713, 12, 2481, 25, 4049, 287, 17952, 973, 19267, 334, 7890, 284, 3376, 410, 7890, 220, 198, 198, 37811, 198, 198, 2, 4482, 23881, 198, 11748, 4818, 8079, 198, 198, 2, 3783, 8931, 198, 11748, 299, 32152, 355, 45941, 198, 198, 2, 15612, 23881, 198, 198, 11748, 2603, 29487, 8019, 355, 285, 489, 198, 198, 76, 489, 13, 1904, 7203, 46384, 4943, 198, 11748, 2603, 29487, 8019, 13, 9078, 29487, 355, 458, 83, 198, 6738, 2603, 29487, 8019, 13, 19581, 1330, 357, 198, 220, 220, 220, 6280, 33711, 1352, 11, 198, 220, 220, 220, 6119, 820, 33711, 1352, 11, 198, 220, 220, 220, 16061, 33711, 1352, 11, 198, 220, 220, 220, 3596, 33711, 1352, 11, 198, 220, 220, 220, 19123, 33711, 1352, 11, 198, 220, 220, 220, 7536, 8479, 1436, 11, 198, 8, 198, 11748, 2603, 29487, 8019, 13, 83, 15799, 355, 4378, 263, 628, 628, 628, 628, 628, 198, 4871, 3782, 10640, 47, 273, 9287, 21746, 43328, 7, 15252, 2599, 198, 220, 220, 220, 37227, 1398, 284, 7110, 3119, 3691, 3119, 21528, 351, 12109, 47279, 12, 3642, 4662, 37811, 628, 220, 220, 220, 285, 489, 13, 6015, 10044, 4105, 14692, 21370, 70, 13, 10331, 4906, 8973, 796, 366, 23108, 1, 198, 220, 220, 220, 285, 489, 13, 6015, 10044, 4105, 14692, 862, 13, 10331, 4906, 8973, 796, 5433, 198, 220, 220, 220, 285, 489, 13, 6015, 10044, 4105, 14692, 12315, 13, 10331, 4906, 8973, 796, 5433, 628, 220, 220, 220, 825, 11593, 15003, 834, 7, 198, 220, 220, 220, 220, 220, 220, 220, 2116, 11, 10369, 7857, 28, 940, 11, 14722, 1096, 28, 940, 11, 7110, 7635, 2625, 74, 12, 33283, 12186, 25473, 2625, 325, 397, 1211, 12, 11186, 25928, 1, 198, 220, 220, 220, 15179, 198, 220, 220, 220, 220, 220, 220, 220, 37227, 24243, 1096, 262, 1661, 10640, 351, 3709, 326, 466, 407, 1487, 13, 628, 220, 220, 220, 220, 220, 220, 220, 770, 5621, 510, 262, 34197, 290, 4429, 7064, 13, 383, 4600, 10331, 7857, 63, 290, 4600, 2777, 4092, 63, 198, 220, 220, 220, 220, 220, 220, 220, 389, 635, 7368, 994, 284, 4155, 326, 484, 389, 6414, 1022, 1981, 198, 220, 220, 220, 220, 220, 220, 220, 4429, 4847, 13, 628, 220, 220, 220, 220, 220, 220, 220, 40117, 198, 220, 220, 220, 220, 220, 220, 220, 24200, 438, 198, 220, 220, 220, 220, 220, 220, 220, 10369, 7857, 1058, 493, 198, 220, 220, 220, 220, 220, 220, 220, 220, 220, 220, 220, 383, 10369, 7857, 284, 779, 329, 8263, 2420, 198, 220, 220, 220, 220, 220, 220, 220, 14722, 1096, 1058, 493, 198, 220, 220, 220, 220, 220, 220, 220, 220, 220, 383, 10369, 7857, 284, 779, 329, 14722, 198, 220, 220, 220, 220, 220, 220, 220, 12186, 25473, 1058, 965, 198, 220, 220, 220, 220, 220, 220, 220, 220, 220, 17489, 257, 285, 489, 12186, 25473, 685, 84, 338, 68, 397, 1211, 12, 21953, 25928, 3256, 220, 198, 220, 220, 220, 220, 220, 220, 220, 220, 220, 334, 338, 68, 397, 1211, 12, 11295, 2070, 3256, 334, 6, 49421, 3256, 334, 338, 68, 397, 1211, 12, 83, 3378, 3256, 220, 198, 220, 220, 220, 220, 220, 220, 220, 220, 220, 334, 6, 2164, 592, 38765, 3256, 334, 6, 20475, 71, 3256, 334, 338, 68, 397, 1211, 12, 16620, 3256, 334, 1549, 668, 62, 25249, 3256, 220, 198, 220, 220, 220, 220, 220, 220, 220, 220, 220, 334, 6, 1130, 29487, 3256, 334, 6, 13261, 400, 5893, 26022, 3256, 334, 338, 68, 397, 1211, 12, 8043, 27461, 3256, 220, 198, 220, 220, 220, 220, 220, 220, 220, 220, 220, 334, 338, 68, 397, 1211, 12, 22089, 3256, 334, 338, 68, 397, 1211, 12, 11186, 25928, 3256, 334, 338, 68, 397, 1211, 12, 29199, 3256, 220, 198, 220, 220, 220, 220, 220, 220, 220, 220, 220, 334, 338, 68, 397, 1211, 12, 79, 6197, 3256, 334, 338, 68, 397, 1211, 12, 76, 7241, 3256, 334, 338, 68, 397, 1211, 12, 20189, 3256, 220, 198, 220, 220, 220, 220, 220, 220, 220, 220, 220, 334, 338, 68, 397, 1211, 12, 11186, 3256, 334, 338, 68, 397, 1211, 12, 30119, 417, 3256, 334, 338, 68, 397, 1211, 12, 21953, 3256, 220, 198, 220, 220, 220, 220, 220, 220, 220, 220, 220, 334, 338, 68, 397, 1211, 12, 21953, 12, 18596, 5857, 20520, 198, 220, 220, 220, 220, 220, 220, 220, 37227, 628, 220, 220, 220, 220, 220, 220, 220, 2116, 13, 10331, 7857, 796, 10369, 7857, 198, 220, 220, 220, 220, 220, 220, 220, 2116, 13, 23912, 1424, 1096, 796, 14722, 1096, 198, 220, 220, 220, 220, 220, 220, 220, 2116, 13, 29487, 7635, 796, 7110, 7635, 198, 220, 220, 220, 220, 220, 220, 220, 458, 83, 13, 7635, 13, 1904, 7, 47720, 25473, 8, 628, 220, 220, 220, 2488, 12708, 24396, 198, 220, 220, 220, 825, 751, 62, 7839, 7, 76, 2675, 278, 312, 2625, 1600, 3042, 10779, 2079, 13, 24, 11, 300, 261, 10779, 2079, 13, 24, 11, 6795, 28, 24214, 11, 8875, 33151, 2599, 198, 220, 220, 220, 220, 220, 220, 220, 37227, 14478, 10007, 284, 24708, 378, 262, 3670, 286, 262, 7110, 628, 220, 220, 220, 220, 220, 770, 5621, 262, 3210, 7110, 3670, 1262, 2219, 13634, 1321, 422, 3122, 3698, 14, 8905, 2149, 3918, 2010, 66, 7568, 3696, 628, 220, 220, 220, 220, 220, 40117, 198, 220, 220, 220, 220, 220, 24200, 438, 198, 220, 220, 220, 220, 220, 285, 2675, 278, 312, 1058, 965, 198, 220, 220, 220, 220, 220, 220, 220, 31451, 278, 11440, 7483, 198, 220, 220, 220, 220, 220, 3042, 1058, 12178, 198, 220, 220, 220, 220, 220, 220, 220, 383, 32477, 286, 262, 285, 2675, 278, 198, 220, 220, 220, 220, 220, 300, 261, 1058, 12178, 198, 220, 220, 220, 220, 220, 220, 220, 383, 890, 3984, 286, 262, 285, 2675, 278, 198, 220, 220, 220, 220, 220, 6795, 1058, 493, 198, 220, 220, 220, 220, 220, 220, 220, 21198, 1292, 6795, 286, 262, 8875, 198, 220, 220, 220, 220, 220, 8875, 1058, 965, 198, 220, 220, 220, 220, 220, 220, 220, 6530, 14, 738, 7483, 286, 262, 8875, 37515, 198, 220, 220, 220, 220, 220, 37227, 628, 220, 220, 220, 220, 220, 220, 220, 279, 7839, 796, 357, 198, 220, 220, 220, 220, 220, 220, 220, 220, 220, 220, 220, 366, 3646, 8426, 319, 25, 1391, 2435, 25, 4, 56, 14, 4, 76, 14, 4, 67, 4064, 39, 25, 4, 44, 92, 3467, 77, 422, 1391, 76, 2675, 278, 312, 92, 5476, 25, 1391, 15460, 3984, 25, 18, 13, 18, 69, 92, 220, 39295, 25, 1391, 6511, 3984, 25, 18, 13, 18, 69, 36786, 198, 220, 220, 220, 220, 220, 220, 220, 220, 220, 220, 220, 366, 36350, 25, 1391, 18053, 32239, 77, 1058, 1391, 259, 43872, 36786, 198, 220, 220, 220, 220, 220, 220, 220, 6739, 18982, 7, 198, 220, 220, 220, 220, 220, 220, 220, 220, 220, 220, 220, 640, 28, 19608, 8079, 13, 19608, 8079, 13, 2197, 22784, 198, 220, 220, 220, 220, 220, 220, 220, 220, 220, 220, 220, 285, 2675, 278, 312, 28, 76, 2675, 278, 312, 11, 198, 220, 220, 220, 220, 220, 220, 220, 220, 220, 220, 220, 32477, 28, 15460, 11, 198, 220, 220, 220, 220, 220, 220, 220, 220, 220, 220, 220, 890, 3984, 28, 14995, 11, 198, 220, 220, 220, 220, 220, 220, 220, 220, 220, 220, 220, 6795, 28, 18053, 11, 198, 220, 220, 220, 220, 220, 220, 220, 220, 220, 220, 220, 8875, 28, 259, 43872, 11, 198, 220, 220, 220, 220, 220, 220, 220, 1267, 628, 220, 220, 220, 220, 220, 220, 220, 1441, 279, 7839, 628, 220, 220, 220, 2488, 12708, 24396, 198 ]
2.362253
1,314
""" The tests for omit interaction feature """ import os import sys from collections import namedtuple from pyplif_hippos import ParseConfig, hippos, similarity def test_configuration_single_omit_interaction(tmpdir): """Test configuration for omitting specific interaction""" # Arrange config_file = tmpdir.mkdir("sub").join("config.txt") config_file.write( """ docking_method plants # plants or vina docking_conf plants-003.conf similarity_coef tanimoto mcconnaughey full_ref 00000100000000000000000000000000000100000000000001000000000000010000001000000000000000000001000000000000000000000000000000101000000000000000000101000000000010000 00010101000000000000000000000000000100000000000001010000000000010000001000000000000010000000000000000000000001011000001000001000000000000000000101000000000000000 00010101000000100000000000000000000100000000000001010100100000010000001000000000000010000001000000000000010000000000100000101010000000000000000001000000000000000 residue_name ARG116 GLU117 LEU132 LYS148 ASP149 ARG150 ARG154 TRP177 SER178 ILE221 ARG223 THR224 GLU226 ALA245 HIS273 GLU275 GLU276 ARG292 ASP294 GLY347 ARG374 TRP408 TYR409 residue_number 40 41 56 72 73 74 78 101 102 145 147 148 150 169 197 199 200 216 218 271 298 332 333 omit_interaction hydrophobic ARG223 full_outfile plants_full_ifp.csv sim_outfile plants_similarity.csv logfile plants.log """ ) arg = os.path.join(config_file.dirname, config_file.basename) if len(sys.argv) > 1: sys.argv[1] = arg else: sys.argv.append(arg) # Act hippos_config = ParseConfig() hippos_config.parse_config() omit_interaction = hippos_config.omit_interaction[0] # Assert assert omit_interaction.interaction_type == "hydrophobic" assert omit_interaction.res_name == ["ARG223"] def test_configuration_omit_multiple_residue_interaction(tmpdir): """Test configuration for omitting multiple residue interaction""" # Arrange config_file = tmpdir.mkdir("sub").join("config.txt") config_file.write( """ docking_method plants # plants or vina docking_conf plants-003.conf similarity_coef tanimoto mcconnaughey full_ref 00000100000000000000000000000000000100000000000001000000000000010000001000000000000000000001000000000000000000000000000000101000000000000000000101000000000010000 00010101000000000000000000000000000100000000000001010000000000010000001000000000000010000000000000000000000001011000001000001000000000000000000101000000000000000 00010101000000100000000000000000000100000000000001010100100000010000001000000000000010000001000000000000010000000000100000101010000000000000000001000000000000000 residue_name ARG116 GLU117 LEU132 LYS148 ASP149 ARG150 ARG154 TRP177 SER178 ILE221 ARG223 THR224 GLU226 ALA245 HIS273 GLU275 GLU276 ARG292 ASP294 GLY347 ARG374 TRP408 TYR409 residue_number 40 41 56 72 73 74 78 101 102 145 147 148 150 169 197 199 200 216 218 271 298 332 333 omit_interaction hydrophobic ARG150 TRP177 ARG223 full_outfile plants_full_ifp.csv sim_outfile plants_similarity.csv logfile plants.log """ ) arg = os.path.join(config_file.dirname, config_file.basename) if len(sys.argv) > 1: sys.argv[1] = arg else: sys.argv.append(arg) # Act hippos_config = ParseConfig() hippos_config.parse_config() omit_interaction = hippos_config.omit_interaction[0] # Assert assert omit_interaction.interaction_type == "hydrophobic" assert omit_interaction.res_name == ["ARG150", "TRP177", "ARG223"] def test_configuration_omit_multiple_interaction_type(tmpdir): """Test configuration for omitting multiple interaction type""" # Arrange config_file = tmpdir.mkdir("sub").join("config.txt") config_file.write( """ docking_method plants # plants or vina docking_conf plants-003.conf similarity_coef tanimoto mcconnaughey full_ref 00000100000000000000000000000000000100000000000001000000000000010000001000000000000000000001000000000000000000000000000000101000000000000000000101000000000010000 00010101000000000000000000000000000100000000000001010000000000010000001000000000000010000000000000000000000001011000001000001000000000000000000101000000000000000 00010101000000100000000000000000000100000000000001010100100000010000001000000000000010000001000000000000010000000000100000101010000000000000000001000000000000000 residue_name ARG116 GLU117 LEU132 LYS148 ASP149 ARG150 ARG154 TRP177 SER178 ILE221 ARG223 THR224 GLU226 ALA245 HIS273 GLU275 GLU276 ARG292 ASP294 GLY347 ARG374 TRP408 TYR409 residue_number 40 41 56 72 73 74 78 101 102 145 147 148 150 169 197 199 200 216 218 271 298 332 333 omit_interaction hydrophobic ARG223 omit_interaction h_bond ARG292 full_outfile plants_full_ifp.csv sim_outfile plants_similarity.csv logfile plants.log """ ) arg = os.path.join(config_file.dirname, config_file.basename) if len(sys.argv) > 1: sys.argv[1] = arg else: sys.argv.append(arg) # Act hippos_config = ParseConfig() hippos_config.parse_config() omit_interaction_1 = hippos_config.omit_interaction[0] omit_interaction_2 = hippos_config.omit_interaction[1] # Assert assert omit_interaction_1.interaction_type == "hydrophobic" assert omit_interaction_1.res_name == ["ARG223"] assert omit_interaction_2.interaction_type == "h_bond" assert omit_interaction_2.res_name == ["ARG292"] def test_configuration_long_interaction_type(tmpdir): """Test configuration checking all long interaction_type""" # Arrange config_file = tmpdir.mkdir("sub").join("config.txt") config_file.write( """ docking_method plants # plants or vina docking_conf plants-003.conf similarity_coef tanimoto mcconnaughey full_ref 00000100000000000000000000000000000100000000000001000000000000010000001000000000000000000001000000000000000000000000000000101000000000000000000101000000000010000 00010101000000000000000000000000000100000000000001010000000000010000001000000000000010000000000000000000000001011000001000001000000000000000000101000000000000000 00010101000000100000000000000000000100000000000001010100100000010000001000000000000010000001000000000000010000000000100000101010000000000000000001000000000000000 residue_name ARG116 GLU117 LEU132 LYS148 ASP149 ARG150 ARG154 TRP177 SER178 ILE221 ARG223 THR224 GLU226 ALA245 HIS273 GLU275 GLU276 ARG292 ASP294 GLY347 ARG374 TRP408 TYR409 residue_number 40 41 56 72 73 74 78 101 102 145 147 148 150 169 197 199 200 216 218 271 298 332 333 omit_interaction hydrophobic ARG116 omit_interaction aromatic GLU117 omit_interaction h_bond LEU132 omit_interaction electrostatic LYS148 omit_interaction h_bond_donor ASP149 omit_interaction h_bond_acceptor ARG150 omit_interaction electrostatic_positive ARG154 omit_interaction electrostatic_negative TRP177 omit_interaction aromatic_facetoface SER178 omit_interaction aromatic_edgetoface ILE221 full_outfile plants_full_ifp.csv sim_outfile plants_similarity.csv logfile plants.log """ ) arg = os.path.join(config_file.dirname, config_file.basename) if len(sys.argv) > 1: sys.argv[1] = arg else: sys.argv.append(arg) # Act hippos_config = ParseConfig() hippos_config.parse_config() omit_interaction_1 = hippos_config.omit_interaction[0] omit_interaction_2 = hippos_config.omit_interaction[1] omit_interaction_3 = hippos_config.omit_interaction[2] omit_interaction_4 = hippos_config.omit_interaction[3] omit_interaction_5 = hippos_config.omit_interaction[4] omit_interaction_6 = hippos_config.omit_interaction[5] omit_interaction_7 = hippos_config.omit_interaction[6] omit_interaction_8 = hippos_config.omit_interaction[7] omit_interaction_9 = hippos_config.omit_interaction[8] omit_interaction_10 = hippos_config.omit_interaction[9] # Assert assert omit_interaction_1.interaction_type == "hydrophobic" assert omit_interaction_1.res_name == ["ARG116"] assert omit_interaction_2.interaction_type == "aromatic" assert omit_interaction_2.res_name == ["GLU117"] assert omit_interaction_3.interaction_type == "h_bond" assert omit_interaction_3.res_name == ["LEU132"] assert omit_interaction_4.interaction_type == "electrostatic" assert omit_interaction_4.res_name == ["LYS148"] assert omit_interaction_5.interaction_type == "h_bond_donor" assert omit_interaction_5.res_name == ["ASP149"] assert omit_interaction_6.interaction_type == "h_bond_acceptor" assert omit_interaction_6.res_name == ["ARG150"] assert omit_interaction_7.interaction_type == "electrostatic_positive" assert omit_interaction_7.res_name == ["ARG154"] assert omit_interaction_8.interaction_type == "electrostatic_negative" assert omit_interaction_8.res_name == ["TRP177"] assert omit_interaction_9.interaction_type == "aromatic_facetoface" assert omit_interaction_9.res_name == ["SER178"] assert omit_interaction_10.interaction_type == "aromatic_edgetoface" assert omit_interaction_10.res_name == ["ILE221"] def test_configuration_short_interaction_type(tmpdir): """Test configuration checking all short interaction_type""" # Arrange config_file = tmpdir.mkdir("sub").join("config.txt") config_file.write( """ docking_method plants # plants or vina docking_conf plants-003.conf similarity_coef tanimoto mcconnaughey full_ref 00000100000000000000000000000000000100000000000001000000000000010000001000000000000000000001000000000000000000000000000000101000000000000000000101000000000010000 00010101000000000000000000000000000100000000000001010000000000010000001000000000000010000000000000000000000001011000001000001000000000000000000101000000000000000 00010101000000100000000000000000000100000000000001010100100000010000001000000000000010000001000000000000010000000000100000101010000000000000000001000000000000000 residue_name ARG116 GLU117 LEU132 LYS148 ASP149 ARG150 ARG154 TRP177 SER178 ILE221 ARG223 THR224 GLU226 ALA245 HIS273 GLU275 GLU276 ARG292 ASP294 GLY347 ARG374 TRP408 TYR409 residue_number 40 41 56 72 73 74 78 101 102 145 147 148 150 169 197 199 200 216 218 271 298 332 333 omit_interaction HPB ARG116 omit_interaction ARM GLU117 omit_interaction HBD LEU132 omit_interaction ELE LYS148 omit_interaction HBD_DON ASP149 omit_interaction HBD_ACC ARG150 omit_interaction ELE_POS ARG154 omit_interaction ELE_NEG TRP177 omit_interaction ARM_F2F SER178 omit_interaction ARM_E2F ILE221 full_outfile plants_full_ifp.csv sim_outfile plants_similarity.csv logfile plants.log """ ) arg = os.path.join(config_file.dirname, config_file.basename) if len(sys.argv) > 1: sys.argv[1] = arg else: sys.argv.append(arg) # Act hippos_config = ParseConfig() hippos_config.parse_config() omit_interaction_1 = hippos_config.omit_interaction[0] omit_interaction_2 = hippos_config.omit_interaction[1] omit_interaction_3 = hippos_config.omit_interaction[2] omit_interaction_4 = hippos_config.omit_interaction[3] omit_interaction_5 = hippos_config.omit_interaction[4] omit_interaction_6 = hippos_config.omit_interaction[5] omit_interaction_7 = hippos_config.omit_interaction[6] omit_interaction_8 = hippos_config.omit_interaction[7] omit_interaction_9 = hippos_config.omit_interaction[8] omit_interaction_10 = hippos_config.omit_interaction[9] # Assert assert omit_interaction_1.interaction_type == "hydrophobic" assert omit_interaction_1.res_name == ["ARG116"] assert omit_interaction_2.interaction_type == "aromatic" assert omit_interaction_2.res_name == ["GLU117"] assert omit_interaction_3.interaction_type == "h_bond" assert omit_interaction_3.res_name == ["LEU132"] assert omit_interaction_4.interaction_type == "electrostatic" assert omit_interaction_4.res_name == ["LYS148"] assert omit_interaction_5.interaction_type == "h_bond_donor" assert omit_interaction_5.res_name == ["ASP149"] assert omit_interaction_6.interaction_type == "h_bond_acceptor" assert omit_interaction_6.res_name == ["ARG150"] assert omit_interaction_7.interaction_type == "electrostatic_positive" assert omit_interaction_7.res_name == ["ARG154"] assert omit_interaction_8.interaction_type == "electrostatic_negative" assert omit_interaction_8.res_name == ["TRP177"] assert omit_interaction_9.interaction_type == "aromatic_facetoface" assert omit_interaction_9.res_name == ["SER178"] assert omit_interaction_10.interaction_type == "aromatic_edgetoface" assert omit_interaction_10.res_name == ["ILE221"] def test_replace_bit_char(): """Test bit replacement function for omitted residue""" # Arrange bitstring = "1000001" omit_hydrophobic = [1, 0, 0, 0, 0, 0, 0] omit_aromatic = [0, 1, 1, 0, 0, 0, 0] omit_h_bond = [0, 0, 0, 1, 1, 0, 0] omit_electrostatic = [0, 0, 0, 0, 0, 1, 1] omit_h_bond_donor = [0, 0, 0, 1, 0, 0, 0] omit_h_bond_acceptor = [0, 0, 0, 0, 1, 0, 0] omit_electrostatic_positive = [0, 0, 0, 0, 0, 1, 0] omit_electrostatic_negative = [0, 0, 0, 0, 0, 0, 1] omit_aromatic_facetoface = [0, 1, 0, 0, 0, 0, 0] omit_aromatic_edgetoface = [0, 0, 1, 0, 0, 0, 0] # Act bitstring_1 = hippos.replace_bit_char(bitstring, omit_hydrophobic) bitstring_2 = hippos.replace_bit_char(bitstring, omit_aromatic) bitstring_3 = hippos.replace_bit_char(bitstring, omit_h_bond) bitstring_4 = hippos.replace_bit_char(bitstring, omit_electrostatic) bitstring_5 = hippos.replace_bit_char(bitstring, omit_h_bond_donor) bitstring_6 = hippos.replace_bit_char(bitstring, omit_h_bond_acceptor) bitstring_7 = hippos.replace_bit_char(bitstring, omit_electrostatic_positive) bitstring_8 = hippos.replace_bit_char(bitstring, omit_electrostatic_negative) bitstring_9 = hippos.replace_bit_char(bitstring, omit_aromatic_facetoface) bitstring_10 = hippos.replace_bit_char(bitstring, omit_aromatic_edgetoface) # Assert assert bitstring_1 == "n000001" assert bitstring_2 == "1nn0001" assert bitstring_3 == "100nn01" assert bitstring_4 == "10000nn" assert bitstring_5 == "100n001" assert bitstring_6 == "1000n01" assert bitstring_7 == "10000n1" assert bitstring_8 == "100000n" assert bitstring_9 == "1n00001" assert bitstring_10 == "10n0001" def test_cleanup_omitted_interaction(): """Test for bitstring preparation prior to similarity calculation""" # Arrange refbit = "000001000101" tgtbit = "11n00n000011" # Act clean_refbit, clean_tgtbit = similarity.clean_omitted_interactions(refbit, tgtbit) # Assert assert clean_refbit == "0000000101" assert clean_tgtbit == "1100000011"
[ 37811, 198, 464, 5254, 329, 42848, 10375, 3895, 198, 37811, 198, 198, 11748, 28686, 198, 11748, 25064, 198, 198, 6738, 17268, 1330, 3706, 83, 29291, 198, 198, 6738, 12972, 489, 361, 62, 71, 3974, 418, 1330, 2547, 325, 16934, 11, 18568, 418, 11, 26789, 628, 198, 4299, 1332, 62, 11250, 3924, 62, 29762, 62, 296, 270, 62, 3849, 2673, 7, 22065, 15908, 2599, 198, 220, 220, 220, 37227, 14402, 8398, 329, 267, 16138, 2176, 10375, 37811, 628, 220, 220, 220, 1303, 943, 9521, 628, 220, 220, 220, 4566, 62, 7753, 796, 45218, 15908, 13, 28015, 15908, 7203, 7266, 11074, 22179, 7203, 11250, 13, 14116, 4943, 198, 220, 220, 220, 4566, 62, 7753, 13, 13564, 7, 198, 220, 220, 220, 220, 220, 220, 220, 37227, 198, 67, 8629, 62, 24396, 220, 220, 220, 6134, 220, 220, 220, 1303, 6134, 393, 410, 1437, 198, 67, 8629, 62, 10414, 220, 220, 220, 220, 220, 6134, 12, 11245, 13, 10414, 198, 198, 38610, 414, 62, 1073, 891, 220, 220, 256, 11227, 2069, 285, 535, 261, 77, 7493, 20342, 198, 198, 12853, 62, 5420, 220, 17643, 486, 25645, 8269, 2388, 486, 8269, 2388, 486, 8269, 2388, 486, 2388, 8298, 25645, 2388, 16, 25645, 8269, 2388, 8298, 486, 25645, 8298, 486, 8269, 8298, 2388, 3571, 486, 486, 486, 25645, 8269, 18005, 8269, 2388, 486, 486, 8269, 18005, 2388, 8298, 8269, 2388, 486, 25645, 8269, 8784, 49388, 486, 2388, 486, 25645, 8298, 486, 8269, 24598, 3571, 486, 486, 486, 2388, 8298, 25645, 2388, 16, 8269, 2388, 486, 486, 486, 8298, 2388, 8298, 2388, 8298, 8269, 2388, 486, 2388, 8298, 8269, 2388, 486, 8269, 8298, 2388, 486, 486, 486, 25645, 8298, 8269, 24598, 198, 198, 411, 312, 518, 62, 3672, 5923, 38, 18298, 10188, 52, 17657, 12509, 52, 19924, 406, 16309, 18294, 34658, 19442, 5923, 38, 8628, 5923, 38, 21526, 7579, 47, 22413, 18871, 23188, 314, 2538, 26115, 5923, 38, 22047, 35383, 24137, 10188, 52, 24909, 8355, 32, 22995, 33700, 27367, 10188, 52, 23195, 10188, 52, 27988, 5923, 38, 32759, 34658, 27696, 10188, 56, 30995, 5923, 38, 31020, 7579, 47, 26200, 24412, 49, 29416, 198, 411, 312, 518, 62, 17618, 2319, 6073, 7265, 7724, 8854, 8915, 8699, 8949, 15143, 20299, 22909, 22613, 6640, 27191, 29903, 1594, 939, 26881, 29217, 33797, 37576, 41423, 23460, 198, 198, 296, 270, 62, 3849, 2673, 220, 7409, 10051, 20803, 220, 5923, 38, 22047, 198, 198, 12853, 62, 448, 7753, 6134, 62, 12853, 62, 361, 79, 13, 40664, 198, 14323, 62, 448, 7753, 6134, 62, 38610, 414, 13, 40664, 198, 6404, 7753, 6134, 13, 6404, 198, 37811, 198, 220, 220, 220, 1267, 628, 220, 220, 220, 1822, 796, 28686, 13, 6978, 13, 22179, 7, 11250, 62, 7753, 13, 15908, 3672, 11, 4566, 62, 7753, 13, 12093, 12453, 8, 628, 220, 220, 220, 611, 18896, 7, 17597, 13, 853, 85, 8, 1875, 352, 25, 198, 220, 220, 220, 220, 220, 220, 220, 25064, 13, 853, 85, 58, 16, 60, 796, 1822, 198, 220, 220, 220, 2073, 25, 198, 220, 220, 220, 220, 220, 220, 220, 25064, 13, 853, 85, 13, 33295, 7, 853, 8, 628, 220, 220, 220, 1303, 2191, 628, 220, 220, 220, 18568, 418, 62, 11250, 796, 2547, 325, 16934, 3419, 198, 220, 220, 220, 18568, 418, 62, 11250, 13, 29572, 62, 11250, 3419, 198, 220, 220, 220, 42848, 62, 3849, 2673, 796, 18568, 418, 62, 11250, 13, 296, 270, 62, 3849, 2673, 58, 15, 60, 628, 220, 220, 220, 1303, 2195, 861, 628, 220, 220, 220, 6818, 42848, 62, 3849, 2673, 13, 3849, 2673, 62, 4906, 6624, 366, 15511, 10051, 20803, 1, 198, 220, 220, 220, 6818, 42848, 62, 3849, 2673, 13, 411, 62, 3672, 6624, 14631, 1503, 38, 22047, 8973, 628, 198, 4299, 1332, 62, 11250, 3924, 62, 296, 270, 62, 48101, 62, 411, 312, 518, 62, 3849, 2673, 7, 22065, 15908, 2599, 198, 220, 220, 220, 37227, 14402, 8398, 329, 267, 16138, 3294, 35186, 10375, 37811, 628, 220, 220, 220, 1303, 943, 9521, 628, 220, 220, 220, 4566, 62, 7753, 796, 45218, 15908, 13, 28015, 15908, 7203, 7266, 11074, 22179, 7203, 11250, 13, 14116, 4943, 198, 220, 220, 220, 4566, 62, 7753, 13, 13564, 7, 198, 220, 220, 220, 220, 220, 220, 220, 37227, 198, 67, 8629, 62, 24396, 220, 220, 220, 6134, 220, 220, 220, 1303, 6134, 393, 410, 1437, 198, 67, 8629, 62, 10414, 220, 220, 220, 220, 220, 6134, 12, 11245, 13, 10414, 198, 198, 38610, 414, 62, 1073, 891, 220, 220, 256, 11227, 2069, 285, 535, 261, 77, 7493, 20342, 198, 198, 12853, 62, 5420, 220, 17643, 486, 25645, 8269, 2388, 486, 8269, 2388, 486, 8269, 2388, 486, 2388, 8298, 25645, 2388, 16, 25645, 8269, 2388, 8298, 486, 25645, 8298, 486, 8269, 8298, 2388, 3571, 486, 486, 486, 25645, 8269, 18005, 8269, 2388, 486, 486, 8269, 18005, 2388, 8298, 8269, 2388, 486, 25645, 8269, 8784, 49388, 486, 2388, 486, 25645, 8298, 486, 8269, 24598, 3571, 486, 486, 486, 2388, 8298, 25645, 2388, 16, 8269, 2388, 486, 486, 486, 8298, 2388, 8298, 2388, 8298, 8269, 2388, 486, 2388, 8298, 8269, 2388, 486, 8269, 8298, 2388, 486, 486, 486, 25645, 8298, 8269, 24598, 198, 198, 411, 312, 518, 62, 3672, 5923, 38, 18298, 10188, 52, 17657, 12509, 52, 19924, 406, 16309, 18294, 34658, 19442, 5923, 38, 8628, 5923, 38, 21526, 7579, 47, 22413, 18871, 23188, 314, 2538, 26115, 5923, 38, 22047, 35383, 24137, 10188, 52, 24909, 8355, 32, 22995, 33700, 27367, 10188, 52, 23195, 10188, 52, 27988, 5923, 38, 32759, 34658, 27696, 10188, 56, 30995, 5923, 38, 31020, 7579, 47, 26200, 24412, 49, 29416, 198, 411, 312, 518, 62, 17618, 2319, 6073, 7265, 7724, 8854, 8915, 8699, 8949, 15143, 20299, 22909, 22613, 6640, 27191, 29903, 1594, 939, 26881, 29217, 33797, 37576, 41423, 23460, 198, 198, 296, 270, 62, 3849, 2673, 220, 7409, 10051, 20803, 220, 5923, 38, 8628, 7579, 47, 22413, 5923, 38, 22047, 198, 198, 12853, 62, 448, 7753, 6134, 62, 12853, 62, 361, 79, 13, 40664, 198, 14323, 62, 448, 7753, 6134, 62, 38610, 414, 13, 40664, 198, 6404, 7753, 6134, 13, 6404, 198, 37811, 198, 220, 220, 220, 1267, 628, 220, 220, 220, 1822, 796, 28686, 13, 6978, 13, 22179, 7, 11250, 62, 7753, 13, 15908, 3672, 11, 4566, 62, 7753, 13, 12093, 12453, 8, 628, 220, 220, 220, 611, 18896, 7, 17597, 13, 853, 85, 8, 1875, 352, 25, 198, 220, 220, 220, 220, 220, 220, 220, 25064, 13, 853, 85, 58, 16, 60, 796, 1822, 198, 220, 220, 220, 2073, 25, 198, 220, 220, 220, 220, 220, 220, 220, 25064, 13, 853, 85, 13, 33295, 7, 853, 8, 628, 220, 220, 220, 1303, 2191, 628, 220, 220, 220, 18568, 418, 62, 11250, 796, 2547, 325, 16934, 3419, 198, 220, 220, 220, 18568, 418, 62, 11250, 13, 29572, 62, 11250, 3419, 198, 220, 220, 220, 42848, 62, 3849, 2673, 796, 18568, 418, 62, 11250, 13, 296, 270, 62, 3849, 2673, 58, 15, 60, 628, 220, 220, 220, 1303, 2195, 861, 628, 220, 220, 220, 6818, 42848, 62, 3849, 2673, 13, 3849, 2673, 62, 4906, 6624, 366, 15511, 10051, 20803, 1, 198, 220, 220, 220, 6818, 42848, 62, 3849, 2673, 13, 411, 62, 3672, 6624, 14631, 1503, 38, 8628, 1600, 366, 5446, 47, 22413, 1600, 366, 1503, 38, 22047, 8973, 628, 198, 4299, 1332, 62, 11250, 3924, 62, 296, 270, 62, 48101, 62, 3849, 2673, 62, 4906, 7, 22065, 15908, 2599, 198, 220, 220, 220, 37227, 14402, 8398, 329, 267, 16138, 3294, 10375, 2099, 37811, 628, 220, 220, 220, 1303, 943, 9521, 628, 220, 220, 220, 4566, 62, 7753, 796, 45218, 15908, 13, 28015, 15908, 7203, 7266, 11074, 22179, 7203, 11250, 13, 14116, 4943, 198, 220, 220, 220, 4566, 62, 7753, 13, 13564, 7, 198, 220, 220, 220, 220, 220, 220, 220, 37227, 198, 67, 8629, 62, 24396, 220, 220, 220, 6134, 220, 220, 220, 1303, 6134, 393, 410, 1437, 198, 67, 8629, 62, 10414, 220, 220, 220, 220, 220, 6134, 12, 11245, 13, 10414, 198, 198, 38610, 414, 62, 1073, 891, 220, 220, 256, 11227, 2069, 285, 535, 261, 77, 7493, 20342, 198, 198, 12853, 62, 5420, 220, 17643, 486, 25645, 8269, 2388, 486, 8269, 2388, 486, 8269, 2388, 486, 2388, 8298, 25645, 2388, 16, 25645, 8269, 2388, 8298, 486, 25645, 8298, 486, 8269, 8298, 2388, 3571, 486, 486, 486, 25645, 8269, 18005, 8269, 2388, 486, 486, 8269, 18005, 2388, 8298, 8269, 2388, 486, 25645, 8269, 8784, 49388, 486, 2388, 486, 25645, 8298, 486, 8269, 24598, 3571, 486, 486, 486, 2388, 8298, 25645, 2388, 16, 8269, 2388, 486, 486, 486, 8298, 2388, 8298, 2388, 8298, 8269, 2388, 486, 2388, 8298, 8269, 2388, 486, 8269, 8298, 2388, 486, 486, 486, 25645, 8298, 8269, 24598, 198, 198, 411, 312, 518, 62, 3672, 5923, 38, 18298, 10188, 52, 17657, 12509, 52, 19924, 406, 16309, 18294, 34658, 19442, 5923, 38, 8628, 5923, 38, 21526, 7579, 47, 22413, 18871, 23188, 314, 2538, 26115, 5923, 38, 22047, 35383, 24137, 10188, 52, 24909, 8355, 32, 22995, 33700, 27367, 10188, 52, 23195, 10188, 52, 27988, 5923, 38, 32759, 34658, 27696, 10188, 56, 30995, 5923, 38, 31020, 7579, 47, 26200, 24412, 49, 29416, 198, 411, 312, 518, 62, 17618, 2319, 6073, 7265, 7724, 8854, 8915, 8699, 8949, 15143, 20299, 22909, 22613, 6640, 27191, 29903, 1594, 939, 26881, 29217, 33797, 37576, 41423, 23460, 198, 198, 296, 270, 62, 3849, 2673, 220, 7409, 10051, 20803, 220, 5923, 38, 22047, 198, 296, 270, 62, 3849, 2673, 220, 289, 62, 65, 623, 220, 5923, 38, 32759, 198, 198, 12853, 62, 448, 7753, 6134, 62, 12853, 62, 361, 79, 13, 40664, 198, 14323, 62, 448, 7753, 6134, 62, 38610, 414, 13, 40664, 198, 6404, 7753, 6134, 13, 6404, 198, 37811, 198, 220, 220, 220, 1267, 628, 220, 220, 220, 1822, 796, 28686, 13, 6978, 13, 22179, 7, 11250, 62, 7753, 13, 15908, 3672, 11, 4566, 62, 7753, 13, 12093, 12453, 8, 628, 220, 220, 220, 611, 18896, 7, 17597, 13, 853, 85, 8, 1875, 352, 25, 198, 220, 220, 220, 220, 220, 220, 220, 25064, 13, 853, 85, 58, 16, 60, 796, 1822, 198, 220, 220, 220, 2073, 25, 198, 220, 220, 220, 220, 220, 220, 220, 25064, 13, 853, 85, 13, 33295, 7, 853, 8, 628, 220, 220, 220, 1303, 2191, 628, 220, 220, 220, 18568, 418, 62, 11250, 796, 2547, 325, 16934, 3419, 198, 220, 220, 220, 18568, 418, 62, 11250, 13, 29572, 62, 11250, 3419, 198, 220, 220, 220, 42848, 62, 3849, 2673, 62, 16, 796, 18568, 418, 62, 11250, 13, 296, 270, 62, 3849, 2673, 58, 15, 60, 198, 220, 220, 220, 42848, 62, 3849, 2673, 62, 17, 796, 18568, 418, 62, 11250, 13, 296, 270, 62, 3849, 2673, 58, 16, 60, 628, 220, 220, 220, 1303, 2195, 861, 628, 220, 220, 220, 6818, 42848, 62, 3849, 2673, 62, 16, 13, 3849, 2673, 62, 4906, 6624, 366, 15511, 10051, 20803, 1, 198, 220, 220, 220, 6818, 42848, 62, 3849, 2673, 62, 16, 13, 411, 62, 3672, 6624, 14631, 1503, 38, 22047, 8973, 628, 220, 220, 220, 6818, 42848, 62, 3849, 2673, 62, 17, 13, 3849, 2673, 62, 4906, 6624, 366, 71, 62, 65, 623, 1, 198, 220, 220, 220, 6818, 42848, 62, 3849, 2673, 62, 17, 13, 411, 62, 3672, 6624, 14631, 1503, 38, 32759, 8973, 628, 198, 4299, 1332, 62, 11250, 3924, 62, 6511, 62, 3849, 2673, 62, 4906, 7, 22065, 15908, 2599, 198, 220, 220, 220, 37227, 14402, 8398, 10627, 477, 890, 10375, 62, 4906, 37811, 628, 220, 220, 220, 1303, 943, 9521, 628, 220, 220, 220, 4566, 62, 7753, 796, 45218, 15908, 13, 28015, 15908, 7203, 7266, 11074, 22179, 7203, 11250, 13, 14116, 4943, 198, 220, 220, 220, 4566, 62, 7753, 13, 13564, 7, 198, 220, 220, 220, 220, 220, 220, 220, 37227, 198, 67, 8629, 62, 24396, 220, 220, 220, 6134, 220, 220, 220, 1303, 6134, 393, 410, 1437, 198, 67, 8629, 62, 10414, 220, 220, 220, 220, 220, 6134, 12, 11245, 13, 10414, 198, 198, 38610, 414, 62, 1073, 891, 220, 220, 256, 11227, 2069, 285, 535, 261, 77, 7493, 20342, 198, 198, 12853, 62, 5420, 220, 17643, 486, 25645, 8269, 2388, 486, 8269, 2388, 486, 8269, 2388, 486, 2388, 8298, 25645, 2388, 16, 25645, 8269, 2388, 8298, 486, 25645, 8298, 486, 8269, 8298, 2388, 3571, 486, 486, 486, 25645, 8269, 18005, 8269, 2388, 486, 486, 8269, 18005, 2388, 8298, 8269, 2388, 486, 25645, 8269, 8784, 49388, 486, 2388, 486, 25645, 8298, 486, 8269, 24598, 3571, 486, 486, 486, 2388, 8298, 25645, 2388, 16, 8269, 2388, 486, 486, 486, 8298, 2388, 8298, 2388, 8298, 8269, 2388, 486, 2388, 8298, 8269, 2388, 486, 8269, 8298, 2388, 486, 486, 486, 25645, 8298, 8269, 24598, 198, 198, 411, 312, 518, 62, 3672, 5923, 38, 18298, 10188, 52, 17657, 12509, 52, 19924, 406, 16309, 18294, 34658, 19442, 5923, 38, 8628, 5923, 38, 21526, 7579, 47, 22413, 18871, 23188, 314, 2538, 26115, 5923, 38, 22047, 35383, 24137, 10188, 52, 24909, 8355, 32, 22995, 33700, 27367, 10188, 52, 23195, 10188, 52, 27988, 5923, 38, 32759, 34658, 27696, 10188, 56, 30995, 5923, 38, 31020, 7579, 47, 26200, 24412, 49, 29416, 198, 411, 312, 518, 62, 17618, 2319, 6073, 7265, 7724, 8854, 8915, 8699, 8949, 15143, 20299, 22909, 22613, 6640, 27191, 29903, 1594, 939, 26881, 29217, 33797, 37576, 41423, 23460, 198, 198, 296, 270, 62, 3849, 2673, 220, 7409, 10051, 20803, 220, 5923, 38, 18298, 198, 296, 270, 62, 3849, 2673, 220, 48440, 220, 10188, 52, 17657, 198, 296, 270, 62, 3849, 2673, 220, 289, 62, 65, 623, 220, 220, 12509, 52, 19924, 198, 296, 270, 62, 3849, 2673, 220, 15206, 12708, 220, 406, 16309, 18294, 198, 296, 270, 62, 3849, 2673, 220, 289, 62, 65, 623, 62, 9099, 273, 220, 34658, 19442, 198, 296, 270, 62, 3849, 2673, 220, 289, 62, 65, 623, 62, 13635, 273, 220, 5923, 38, 8628, 198, 296, 270, 62, 3849, 2673, 220, 15206, 12708, 62, 24561, 220, 5923, 38, 21526, 198, 296, 270, 62, 3849, 2673, 220, 15206, 12708, 62, 31591, 220, 7579, 47, 22413, 198, 296, 270, 62, 3849, 2673, 220, 48440, 62, 69, 23253, 1659, 558, 220, 18871, 23188, 198, 296, 270, 62, 3849, 2673, 220, 48440, 62, 276, 1136, 1659, 558, 220, 314, 2538, 26115, 198, 198, 12853, 62, 448, 7753, 6134, 62, 12853, 62, 361, 79, 13, 40664, 198, 14323, 62, 448, 7753, 6134, 62, 38610, 414, 13, 40664, 198, 6404, 7753, 6134, 13, 6404, 198, 37811, 198, 220, 220, 220, 1267, 628, 220, 220, 220, 1822, 796, 28686, 13, 6978, 13, 22179, 7, 11250, 62, 7753, 13, 15908, 3672, 11, 4566, 62, 7753, 13, 12093, 12453, 8, 628, 220, 220, 220, 611, 18896, 7, 17597, 13, 853, 85, 8, 1875, 352, 25, 198, 220, 220, 220, 220, 220, 220, 220, 25064, 13, 853, 85, 58, 16, 60, 796, 1822, 198, 220, 220, 220, 2073, 25, 198, 220, 220, 220, 220, 220, 220, 220, 25064, 13, 853, 85, 13, 33295, 7, 853, 8, 628, 220, 220, 220, 1303, 2191, 628, 220, 220, 220, 18568, 418, 62, 11250, 796, 2547, 325, 16934, 3419, 198, 220, 220, 220, 18568, 418, 62, 11250, 13, 29572, 62, 11250, 3419, 198, 220, 220, 220, 42848, 62, 3849, 2673, 62, 16, 796, 18568, 418, 62, 11250, 13, 296, 270, 62, 3849, 2673, 58, 15, 60, 198, 220, 220, 220, 42848, 62, 3849, 2673, 62, 17, 796, 18568, 418, 62, 11250, 13, 296, 270, 62, 3849, 2673, 58, 16, 60, 198, 220, 220, 220, 42848, 62, 3849, 2673, 62, 18, 796, 18568, 418, 62, 11250, 13, 296, 270, 62, 3849, 2673, 58, 17, 60, 198, 220, 220, 220, 42848, 62, 3849, 2673, 62, 19, 796, 18568, 418, 62, 11250, 13, 296, 270, 62, 3849, 2673, 58, 18, 60, 198, 220, 220, 220, 42848, 62, 3849, 2673, 62, 20, 796, 18568, 418, 62, 11250, 13, 296, 270, 62, 3849, 2673, 58, 19, 60, 198, 220, 220, 220, 42848, 62, 3849, 2673, 62, 21, 796, 18568, 418, 62, 11250, 13, 296, 270, 62, 3849, 2673, 58, 20, 60, 198, 220, 220, 220, 42848, 62, 3849, 2673, 62, 22, 796, 18568, 418, 62, 11250, 13, 296, 270, 62, 3849, 2673, 58, 21, 60, 198, 220, 220, 220, 42848, 62, 3849, 2673, 62, 23, 796, 18568, 418, 62, 11250, 13, 296, 270, 62, 3849, 2673, 58, 22, 60, 198, 220, 220, 220, 42848, 62, 3849, 2673, 62, 24, 796, 18568, 418, 62, 11250, 13, 296, 270, 62, 3849, 2673, 58, 23, 60, 198, 220, 220, 220, 42848, 62, 3849, 2673, 62, 940, 796, 18568, 418, 62, 11250, 13, 296, 270, 62, 3849, 2673, 58, 24, 60, 628, 220, 220, 220, 1303, 2195, 861, 628, 220, 220, 220, 6818, 42848, 62, 3849, 2673, 62, 16, 13, 3849, 2673, 62, 4906, 6624, 366, 15511, 10051, 20803, 1, 198, 220, 220, 220, 6818, 42848, 62, 3849, 2673, 62, 16, 13, 411, 62, 3672, 6624, 14631, 1503, 38, 18298, 8973, 198, 220, 220, 220, 6818, 42848, 62, 3849, 2673, 62, 17, 13, 3849, 2673, 62, 4906, 6624, 366, 283, 13730, 1, 198, 220, 220, 220, 6818, 42848, 62, 3849, 2673, 62, 17, 13, 411, 62, 3672, 6624, 14631, 8763, 52, 17657, 8973, 198, 220, 220, 220, 6818, 42848, 62, 3849, 2673, 62, 18, 13, 3849, 2673, 62, 4906, 6624, 366, 71, 62, 65, 623, 1, 198, 220, 220, 220, 6818, 42848, 62, 3849, 2673, 62, 18, 13, 411, 62, 3672, 6624, 14631, 2538, 52, 19924, 8973, 198, 220, 220, 220, 6818, 42848, 62, 3849, 2673, 62, 19, 13, 3849, 2673, 62, 4906, 6624, 366, 9509, 305, 12708, 1, 198, 220, 220, 220, 6818, 42848, 62, 3849, 2673, 62, 19, 13, 411, 62, 3672, 6624, 14631, 11319, 50, 18294, 8973, 198, 220, 220, 220, 6818, 42848, 62, 3849, 2673, 62, 20, 13, 3849, 2673, 62, 4906, 6624, 366, 71, 62, 65, 623, 62, 9099, 273, 1, 198, 220, 220, 220, 6818, 42848, 62, 3849, 2673, 62, 20, 13, 411, 62, 3672, 6624, 14631, 1921, 47, 19442, 8973, 198, 220, 220, 220, 6818, 42848, 62, 3849, 2673, 62, 21, 13, 3849, 2673, 62, 4906, 6624, 366, 71, 62, 65, 623, 62, 13635, 273, 1, 198, 220, 220, 220, 6818, 42848, 62, 3849, 2673, 62, 21, 13, 411, 62, 3672, 6624, 14631, 1503, 38, 8628, 8973, 198, 220, 220, 220, 6818, 42848, 62, 3849, 2673, 62, 22, 13, 3849, 2673, 62, 4906, 6624, 366, 9509, 305, 12708, 62, 24561, 1, 198, 220, 220, 220, 6818, 42848, 62, 3849, 2673, 62, 22, 13, 411, 62, 3672, 6624, 14631, 1503, 38, 21526, 8973, 198, 220, 220, 220, 6818, 42848, 62, 3849, 2673, 62, 23, 13, 3849, 2673, 62, 4906, 6624, 366, 9509, 305, 12708, 62, 31591, 1, 198, 220, 220, 220, 6818, 42848, 62, 3849, 2673, 62, 23, 13, 411, 62, 3672, 6624, 14631, 5446, 47, 22413, 8973, 198, 220, 220, 220, 6818, 42848, 62, 3849, 2673, 62, 24, 13, 3849, 2673, 62, 4906, 6624, 366, 283, 13730, 62, 69, 23253, 1659, 558, 1, 198, 220, 220, 220, 6818, 42848, 62, 3849, 2673, 62, 24, 13, 411, 62, 3672, 6624, 14631, 35009, 23188, 8973, 198, 220, 220, 220, 6818, 42848, 62, 3849, 2673, 62, 940, 13, 3849, 2673, 62, 4906, 6624, 366, 283, 13730, 62, 276, 1136, 1659, 558, 1, 198, 220, 220, 220, 6818, 42848, 62, 3849, 2673, 62, 940, 13, 411, 62, 3672, 6624, 14631, 41119, 26115, 8973, 628, 198, 4299, 1332, 62, 11250, 3924, 62, 19509, 62, 3849, 2673, 62, 4906, 7, 22065, 15908, 2599, 198, 220, 220, 220, 37227, 14402, 8398, 10627, 477, 1790, 10375, 62, 4906, 37811, 628, 220, 220, 220, 1303, 943, 9521, 628, 220, 220, 220, 4566, 62, 7753, 796, 45218, 15908, 13, 28015, 15908, 7203, 7266, 11074, 22179, 7203, 11250, 13, 14116, 4943, 198, 220, 220, 220, 4566, 62, 7753, 13, 13564, 7, 198, 220, 220, 220, 220, 220, 220, 220, 37227, 198, 67, 8629, 62, 24396, 220, 220, 220, 6134, 220, 220, 220, 1303, 6134, 393, 410, 1437, 198, 67, 8629, 62, 10414, 220, 220, 220, 220, 220, 6134, 12, 11245, 13, 10414, 198, 198, 38610, 414, 62, 1073, 891, 220, 220, 256, 11227, 2069, 285, 535, 261, 77, 7493, 20342, 198, 198, 12853, 62, 5420, 220, 17643, 486, 25645, 8269, 2388, 486, 8269, 2388, 486, 8269, 2388, 486, 2388, 8298, 25645, 2388, 16, 25645, 8269, 2388, 8298, 486, 25645, 8298, 486, 8269, 8298, 2388, 3571, 486, 486, 486, 25645, 8269, 18005, 8269, 2388, 486, 486, 8269, 18005, 2388, 8298, 8269, 2388, 486, 25645, 8269, 8784, 49388, 486, 2388, 486, 25645, 8298, 486, 8269, 24598, 3571, 486, 486, 486, 2388, 8298, 25645, 2388, 16, 8269, 2388, 486, 486, 486, 8298, 2388, 8298, 2388, 8298, 8269, 2388, 486, 2388, 8298, 8269, 2388, 486, 8269, 8298, 2388, 486, 486, 486, 25645, 8298, 8269, 24598, 198, 198, 411, 312, 518, 62, 3672, 5923, 38, 18298, 10188, 52, 17657, 12509, 52, 19924, 406, 16309, 18294, 34658, 19442, 5923, 38, 8628, 5923, 38, 21526, 7579, 47, 22413, 18871, 23188, 314, 2538, 26115, 5923, 38, 22047, 35383, 24137, 10188, 52, 24909, 8355, 32, 22995, 33700, 27367, 10188, 52, 23195, 10188, 52, 27988, 5923, 38, 32759, 34658, 27696, 10188, 56, 30995, 5923, 38, 31020, 7579, 47, 26200, 24412, 49, 29416, 198, 411, 312, 518, 62, 17618, 2319, 6073, 7265, 7724, 8854, 8915, 8699, 8949, 15143, 20299, 22909, 22613, 6640, 27191, 29903, 1594, 939, 26881, 29217, 33797, 37576, 41423, 23460, 198, 198, 296, 270, 62, 3849, 2673, 220, 6574, 33, 220, 5923, 38, 18298, 198, 296, 270, 62, 3849, 2673, 220, 20359, 220, 10188, 52, 17657, 198, 296, 270, 62, 3849, 2673, 220, 367, 14529, 220, 220, 12509, 52, 19924, 198, 296, 270, 62, 3849, 2673, 220, 40342, 220, 406, 16309, 18294, 198, 296, 270, 62, 3849, 2673, 220, 367, 14529, 62, 41173, 220, 34658, 19442, 198, 296, 270, 62, 3849, 2673, 220, 367, 14529, 62, 26861, 220, 5923, 38, 8628, 198, 296, 270, 62, 3849, 2673, 220, 40342, 62, 37997, 220, 5923, 38, 21526, 198, 296, 270, 62, 3849, 2673, 220, 40342, 62, 45, 7156, 220, 7579, 47, 22413, 198, 296, 270, 62, 3849, 2673, 220, 20359, 62, 37, 17, 37, 220, 18871, 23188, 198, 296, 270, 62, 3849, 2673, 220, 20359, 62, 36, 17, 37, 220, 314, 2538, 26115, 198, 198, 12853, 62, 448, 7753, 6134, 62, 12853, 62, 361, 79, 13, 40664, 198, 14323, 62, 448, 7753, 6134, 62, 38610, 414, 13, 40664, 198, 6404, 7753, 6134, 13, 6404, 198, 37811, 198, 220, 220, 220, 1267, 628, 220, 220, 220, 1822, 796, 28686, 13, 6978, 13, 22179, 7, 11250, 62, 7753, 13, 15908, 3672, 11, 4566, 62, 7753, 13, 12093, 12453, 8, 628, 220, 220, 220, 611, 18896, 7, 17597, 13, 853, 85, 8, 1875, 352, 25, 198, 220, 220, 220, 220, 220, 220, 220, 25064, 13, 853, 85, 58, 16, 60, 796, 1822, 198, 220, 220, 220, 2073, 25, 198, 220, 220, 220, 220, 220, 220, 220, 25064, 13, 853, 85, 13, 33295, 7, 853, 8, 628, 220, 220, 220, 1303, 2191, 628, 220, 220, 220, 18568, 418, 62, 11250, 796, 2547, 325, 16934, 3419, 198, 220, 220, 220, 18568, 418, 62, 11250, 13, 29572, 62, 11250, 3419, 198, 220, 220, 220, 42848, 62, 3849, 2673, 62, 16, 796, 18568, 418, 62, 11250, 13, 296, 270, 62, 3849, 2673, 58, 15, 60, 198, 220, 220, 220, 42848, 62, 3849, 2673, 62, 17, 796, 18568, 418, 62, 11250, 13, 296, 270, 62, 3849, 2673, 58, 16, 60, 198, 220, 220, 220, 42848, 62, 3849, 2673, 62, 18, 796, 18568, 418, 62, 11250, 13, 296, 270, 62, 3849, 2673, 58, 17, 60, 198, 220, 220, 220, 42848, 62, 3849, 2673, 62, 19, 796, 18568, 418, 62, 11250, 13, 296, 270, 62, 3849, 2673, 58, 18, 60, 198, 220, 220, 220, 42848, 62, 3849, 2673, 62, 20, 796, 18568, 418, 62, 11250, 13, 296, 270, 62, 3849, 2673, 58, 19, 60, 198, 220, 220, 220, 42848, 62, 3849, 2673, 62, 21, 796, 18568, 418, 62, 11250, 13, 296, 270, 62, 3849, 2673, 58, 20, 60, 198, 220, 220, 220, 42848, 62, 3849, 2673, 62, 22, 796, 18568, 418, 62, 11250, 13, 296, 270, 62, 3849, 2673, 58, 21, 60, 198, 220, 220, 220, 42848, 62, 3849, 2673, 62, 23, 796, 18568, 418, 62, 11250, 13, 296, 270, 62, 3849, 2673, 58, 22, 60, 198, 220, 220, 220, 42848, 62, 3849, 2673, 62, 24, 796, 18568, 418, 62, 11250, 13, 296, 270, 62, 3849, 2673, 58, 23, 60, 198, 220, 220, 220, 42848, 62, 3849, 2673, 62, 940, 796, 18568, 418, 62, 11250, 13, 296, 270, 62, 3849, 2673, 58, 24, 60, 628, 220, 220, 220, 1303, 2195, 861, 628, 220, 220, 220, 6818, 42848, 62, 3849, 2673, 62, 16, 13, 3849, 2673, 62, 4906, 6624, 366, 15511, 10051, 20803, 1, 198, 220, 220, 220, 6818, 42848, 62, 3849, 2673, 62, 16, 13, 411, 62, 3672, 6624, 14631, 1503, 38, 18298, 8973, 198, 220, 220, 220, 6818, 42848, 62, 3849, 2673, 62, 17, 13, 3849, 2673, 62, 4906, 6624, 366, 283, 13730, 1, 198, 220, 220, 220, 6818, 42848, 62, 3849, 2673, 62, 17, 13, 411, 62, 3672, 6624, 14631, 8763, 52, 17657, 8973, 198, 220, 220, 220, 6818, 42848, 62, 3849, 2673, 62, 18, 13, 3849, 2673, 62, 4906, 6624, 366, 71, 62, 65, 623, 1, 198, 220, 220, 220, 6818, 42848, 62, 3849, 2673, 62, 18, 13, 411, 62, 3672, 6624, 14631, 2538, 52, 19924, 8973, 198, 220, 220, 220, 6818, 42848, 62, 3849, 2673, 62, 19, 13, 3849, 2673, 62, 4906, 6624, 366, 9509, 305, 12708, 1, 198, 220, 220, 220, 6818, 42848, 62, 3849, 2673, 62, 19, 13, 411, 62, 3672, 6624, 14631, 11319, 50, 18294, 8973, 198, 220, 220, 220, 6818, 42848, 62, 3849, 2673, 62, 20, 13, 3849, 2673, 62, 4906, 6624, 366, 71, 62, 65, 623, 62, 9099, 273, 1, 198, 220, 220, 220, 6818, 42848, 62, 3849, 2673, 62, 20, 13, 411, 62, 3672, 6624, 14631, 1921, 47, 19442, 8973, 198, 220, 220, 220, 6818, 42848, 62, 3849, 2673, 62, 21, 13, 3849, 2673, 62, 4906, 6624, 366, 71, 62, 65, 623, 62, 13635, 273, 1, 198, 220, 220, 220, 6818, 42848, 62, 3849, 2673, 62, 21, 13, 411, 62, 3672, 6624, 14631, 1503, 38, 8628, 8973, 198, 220, 220, 220, 6818, 42848, 62, 3849, 2673, 62, 22, 13, 3849, 2673, 62, 4906, 6624, 366, 9509, 305, 12708, 62, 24561, 1, 198, 220, 220, 220, 6818, 42848, 62, 3849, 2673, 62, 22, 13, 411, 62, 3672, 6624, 14631, 1503, 38, 21526, 8973, 198, 220, 220, 220, 6818, 42848, 62, 3849, 2673, 62, 23, 13, 3849, 2673, 62, 4906, 6624, 366, 9509, 305, 12708, 62, 31591, 1, 198, 220, 220, 220, 6818, 42848, 62, 3849, 2673, 62, 23, 13, 411, 62, 3672, 6624, 14631, 5446, 47, 22413, 8973, 198, 220, 220, 220, 6818, 42848, 62, 3849, 2673, 62, 24, 13, 3849, 2673, 62, 4906, 6624, 366, 283, 13730, 62, 69, 23253, 1659, 558, 1, 198, 220, 220, 220, 6818, 42848, 62, 3849, 2673, 62, 24, 13, 411, 62, 3672, 6624, 14631, 35009, 23188, 8973, 198, 220, 220, 220, 6818, 42848, 62, 3849, 2673, 62, 940, 13, 3849, 2673, 62, 4906, 6624, 366, 283, 13730, 62, 276, 1136, 1659, 558, 1, 198, 220, 220, 220, 6818, 42848, 62, 3849, 2673, 62, 940, 13, 411, 62, 3672, 6624, 14631, 41119, 26115, 8973, 628, 198, 4299, 1332, 62, 33491, 62, 2545, 62, 10641, 33529, 198, 220, 220, 220, 37227, 14402, 1643, 9014, 2163, 329, 22532, 35186, 37811, 628, 220, 220, 220, 1303, 943, 9521, 628, 220, 220, 220, 1643, 8841, 796, 366, 49388, 486, 1, 628, 220, 220, 220, 42848, 62, 15511, 10051, 20803, 796, 685, 16, 11, 657, 11, 657, 11, 657, 11, 657, 11, 657, 11, 657, 60, 198, 220, 220, 220, 42848, 62, 283, 13730, 796, 685, 15, 11, 352, 11, 352, 11, 657, 11, 657, 11, 657, 11, 657, 60, 198, 220, 220, 220, 42848, 62, 71, 62, 65, 623, 796, 685, 15, 11, 657, 11, 657, 11, 352, 11, 352, 11, 657, 11, 657, 60, 198, 220, 220, 220, 42848, 62, 9509, 305, 12708, 796, 685, 15, 11, 657, 11, 657, 11, 657, 11, 657, 11, 352, 11, 352, 60, 198, 220, 220, 220, 42848, 62, 71, 62, 65, 623, 62, 9099, 273, 796, 685, 15, 11, 657, 11, 657, 11, 352, 11, 657, 11, 657, 11, 657, 60, 198, 220, 220, 220, 42848, 62, 71, 62, 65, 623, 62, 13635, 273, 796, 685, 15, 11, 657, 11, 657, 11, 657, 11, 352, 11, 657, 11, 657, 60, 198, 220, 220, 220, 42848, 62, 9509, 305, 12708, 62, 24561, 796, 685, 15, 11, 657, 11, 657, 11, 657, 11, 657, 11, 352, 11, 657, 60, 198, 220, 220, 220, 42848, 62, 9509, 305, 12708, 62, 31591, 796, 685, 15, 11, 657, 11, 657, 11, 657, 11, 657, 11, 657, 11, 352, 60, 198, 220, 220, 220, 42848, 62, 283, 13730, 62, 69, 23253, 1659, 558, 796, 685, 15, 11, 352, 11, 657, 11, 657, 11, 657, 11, 657, 11, 657, 60, 198, 220, 220, 220, 42848, 62, 283, 13730, 62, 276, 1136, 1659, 558, 796, 685, 15, 11, 657, 11, 352, 11, 657, 11, 657, 11, 657, 11, 657, 60, 628, 220, 220, 220, 1303, 2191, 628, 220, 220, 220, 1643, 8841, 62, 16, 796, 18568, 418, 13, 33491, 62, 2545, 62, 10641, 7, 2545, 8841, 11, 42848, 62, 15511, 10051, 20803, 8, 198, 220, 220, 220, 1643, 8841, 62, 17, 796, 18568, 418, 13, 33491, 62, 2545, 62, 10641, 7, 2545, 8841, 11, 42848, 62, 283, 13730, 8, 198, 220, 220, 220, 1643, 8841, 62, 18, 796, 18568, 418, 13, 33491, 62, 2545, 62, 10641, 7, 2545, 8841, 11, 42848, 62, 71, 62, 65, 623, 8, 198, 220, 220, 220, 1643, 8841, 62, 19, 796, 18568, 418, 13, 33491, 62, 2545, 62, 10641, 7, 2545, 8841, 11, 42848, 62, 9509, 305, 12708, 8, 198, 220, 220, 220, 1643, 8841, 62, 20, 796, 18568, 418, 13, 33491, 62, 2545, 62, 10641, 7, 2545, 8841, 11, 42848, 62, 71, 62, 65, 623, 62, 9099, 273, 8, 198, 220, 220, 220, 1643, 8841, 62, 21, 796, 18568, 418, 13, 33491, 62, 2545, 62, 10641, 7, 2545, 8841, 11, 42848, 62, 71, 62, 65, 623, 62, 13635, 273, 8, 198, 220, 220, 220, 1643, 8841, 62, 22, 796, 18568, 418, 13, 33491, 62, 2545, 62, 10641, 7, 2545, 8841, 11, 42848, 62, 9509, 305, 12708, 62, 24561, 8, 198, 220, 220, 220, 1643, 8841, 62, 23, 796, 18568, 418, 13, 33491, 62, 2545, 62, 10641, 7, 2545, 8841, 11, 42848, 62, 9509, 305, 12708, 62, 31591, 8, 198, 220, 220, 220, 1643, 8841, 62, 24, 796, 18568, 418, 13, 33491, 62, 2545, 62, 10641, 7, 2545, 8841, 11, 42848, 62, 283, 13730, 62, 69, 23253, 1659, 558, 8, 198, 220, 220, 220, 1643, 8841, 62, 940, 796, 18568, 418, 13, 33491, 62, 2545, 62, 10641, 7, 2545, 8841, 11, 42848, 62, 283, 13730, 62, 276, 1136, 1659, 558, 8, 628, 220, 220, 220, 1303, 2195, 861, 628, 220, 220, 220, 6818, 1643, 8841, 62, 16, 6624, 366, 77, 2388, 486, 1, 198, 220, 220, 220, 6818, 1643, 8841, 62, 17, 6624, 366, 16, 20471, 18005, 1, 198, 220, 220, 220, 6818, 1643, 8841, 62, 18, 6624, 366, 3064, 20471, 486, 1, 198, 220, 220, 220, 6818, 1643, 8841, 62, 19, 6624, 366, 49388, 20471, 1, 198, 220, 220, 220, 6818, 1643, 8841, 62, 20, 6624, 366, 3064, 77, 8298, 1, 198, 220, 220, 220, 6818, 1643, 8841, 62, 21, 6624, 366, 12825, 77, 486, 1, 198, 220, 220, 220, 6818, 1643, 8841, 62, 22, 6624, 366, 49388, 77, 16, 1, 198, 220, 220, 220, 6818, 1643, 8841, 62, 23, 6624, 366, 3064, 830, 77, 1, 198, 220, 220, 220, 6818, 1643, 8841, 62, 24, 6624, 366, 16, 77, 2388, 16, 1, 198, 220, 220, 220, 6818, 1643, 8841, 62, 940, 6624, 366, 940, 77, 18005, 1, 628, 198, 4299, 1332, 62, 27773, 929, 62, 296, 2175, 62, 3849, 2673, 33529, 198, 220, 220, 220, 37227, 14402, 329, 1643, 8841, 11824, 3161, 284, 26789, 17952, 37811, 628, 220, 220, 220, 1303, 943, 9521, 628, 220, 220, 220, 1006, 2545, 796, 366, 2388, 486, 18005, 486, 1, 198, 220, 220, 220, 256, 13655, 2545, 796, 366, 1157, 77, 405, 77, 2388, 1157, 1, 628, 220, 220, 220, 1303, 2191, 628, 220, 220, 220, 3424, 62, 5420, 2545, 11, 3424, 62, 83, 13655, 2545, 796, 26789, 13, 27773, 62, 296, 2175, 62, 3849, 4658, 7, 5420, 2545, 11, 256, 13655, 2545, 8, 628, 220, 220, 220, 1303, 2195, 861, 628, 220, 220, 220, 6818, 3424, 62, 5420, 2545, 6624, 366, 10535, 486, 486, 1, 198, 220, 220, 220, 6818, 3424, 62, 83, 13655, 2545, 6624, 366, 1157, 10535, 1157, 1, 198 ]
2.755917
5,408
#!/usr/bin/python3 import sys from lib.demucs import demucs from lib.demucs.demucs import model from lib.demucs.demucs.audio import AudioFile from lib.demucs.demucs.utils import apply_model, load_model from pathlib import Path from scipy.io import wavfile # within the demucs directory sys.modules['demucs.model'] = model sys.modules['demucs'] = demucs class DemucsService(): """ def encode_mp3(wav, path, bitrate=320, verbose=False): try: import lameenc except ImportError: print("Failed to call lame encoder. Maybe it is not installed? " "On windows, run `python.exe -m pip install -U lameenc`, " "on OSX/Linux, run `python3 -m pip install -U lameenc`, " "then try again.", file=sys.stderr) sys.exit(1) encoder = lameenc.Encoder() encoder.set_bit_rate(bitrate) encoder.set_in_sample_rate(44100) encoder.set_channels(2) encoder.set_quality(2) # 2-highest, 7-fastest if not verbose: encoder.silence() mp3_data = encoder.encode(wav.tostring()) mp3_data += encoder.flush() with open(path, "wb") as f: f.write(mp3_data) """
[ 2, 48443, 14629, 14, 8800, 14, 29412, 18, 198, 198, 11748, 25064, 198, 198, 6738, 9195, 13, 9536, 1229, 82, 1330, 1357, 1229, 82, 198, 6738, 9195, 13, 9536, 1229, 82, 13, 9536, 1229, 82, 1330, 2746, 198, 6738, 9195, 13, 9536, 1229, 82, 13, 9536, 1229, 82, 13, 24051, 1330, 13491, 8979, 198, 6738, 9195, 13, 9536, 1229, 82, 13, 9536, 1229, 82, 13, 26791, 1330, 4174, 62, 19849, 11, 3440, 62, 19849, 198, 6738, 3108, 8019, 1330, 10644, 198, 6738, 629, 541, 88, 13, 952, 1330, 266, 615, 7753, 628, 198, 2, 1626, 262, 1357, 1229, 82, 8619, 198, 17597, 13, 18170, 17816, 9536, 1229, 82, 13, 19849, 20520, 796, 2746, 198, 17597, 13, 18170, 17816, 9536, 1229, 82, 20520, 796, 1357, 1229, 82, 628, 198, 4871, 1897, 1229, 82, 16177, 33529, 628, 220, 220, 220, 37227, 198, 220, 220, 220, 825, 37773, 62, 3149, 18, 7, 45137, 11, 3108, 11, 1643, 4873, 28, 19504, 11, 15942, 577, 28, 25101, 2599, 198, 220, 220, 220, 220, 220, 220, 220, 1949, 25, 198, 220, 220, 220, 220, 220, 220, 220, 220, 220, 220, 220, 1330, 30248, 12685, 198, 220, 220, 220, 220, 220, 220, 220, 2845, 17267, 12331, 25, 198, 220, 220, 220, 220, 220, 220, 220, 220, 220, 220, 220, 3601, 7203, 37, 6255, 284, 869, 30248, 2207, 12342, 13, 6674, 340, 318, 407, 6589, 30, 366, 198, 220, 220, 220, 220, 220, 220, 220, 220, 220, 220, 220, 220, 220, 220, 220, 366, 2202, 9168, 11, 1057, 4600, 29412, 13, 13499, 532, 76, 7347, 2721, 532, 52, 30248, 12685, 47671, 366, 198, 220, 220, 220, 220, 220, 220, 220, 220, 220, 220, 220, 220, 220, 220, 220, 366, 261, 7294, 55, 14, 19314, 11, 1057, 4600, 29412, 18, 532, 76, 7347, 2721, 532, 52, 30248, 12685, 47671, 366, 198, 220, 220, 220, 220, 220, 220, 220, 220, 220, 220, 220, 220, 220, 220, 220, 366, 8524, 1949, 757, 33283, 2393, 28, 17597, 13, 301, 1082, 81, 8, 198, 220, 220, 220, 220, 220, 220, 220, 220, 220, 220, 220, 25064, 13, 37023, 7, 16, 8, 198, 220, 220, 220, 220, 220, 220, 220, 2207, 12342, 796, 30248, 12685, 13, 27195, 12342, 3419, 198, 220, 220, 220, 220, 220, 220, 220, 2207, 12342, 13, 2617, 62, 2545, 62, 4873, 7, 2545, 4873, 8, 198, 220, 220, 220, 220, 220, 220, 220, 2207, 12342, 13, 2617, 62, 259, 62, 39873, 62, 4873, 7, 2598, 3064, 8, 198, 220, 220, 220, 220, 220, 220, 220, 2207, 12342, 13, 2617, 62, 354, 8961, 7, 17, 8, 198, 220, 220, 220, 220, 220, 220, 220, 2207, 12342, 13, 2617, 62, 13237, 7, 17, 8, 220, 1303, 362, 12, 35323, 11, 767, 12, 7217, 395, 198, 220, 220, 220, 220, 220, 220, 220, 611, 407, 15942, 577, 25, 198, 220, 220, 220, 220, 220, 220, 220, 220, 220, 220, 220, 2207, 12342, 13, 18217, 594, 3419, 198, 220, 220, 220, 220, 220, 220, 220, 29034, 18, 62, 7890, 796, 2207, 12342, 13, 268, 8189, 7, 45137, 13, 83, 455, 1806, 28955, 198, 220, 220, 220, 220, 220, 220, 220, 29034, 18, 62, 7890, 15853, 2207, 12342, 13, 25925, 3419, 198, 220, 220, 220, 220, 220, 220, 220, 351, 1280, 7, 6978, 11, 366, 39346, 4943, 355, 277, 25, 198, 220, 220, 220, 220, 220, 220, 220, 220, 220, 220, 220, 277, 13, 13564, 7, 3149, 18, 62, 7890, 8, 198, 220, 220, 220, 37227, 198 ]
2.162587
572
import pymysql conn = pymysql.Connection( host = '192.168.160.33', port = 3306, user = 'develop', password='xs_dev', database='test', charset='utf8' ) cursor = conn.cursor() sql = """ select * from user1 """ try: cursor.execute(sql) res = cursor.fetchall() for row in res: id = row[0] fname=row[1] lname=row[2] age =row[3] sex=row[4] income=row[5] print("id=%s,fname=%s,lname=%s,age=%s,sex=%s,income=%s" % (id, fname, lname, age, sex, income)) except Exception as e: print(e) # 关闭连接 conn.close()
[ 11748, 279, 4948, 893, 13976, 198, 198, 37043, 796, 279, 4948, 893, 13976, 13, 32048, 7, 198, 220, 220, 220, 2583, 796, 705, 17477, 13, 14656, 13, 14198, 13, 2091, 3256, 198, 220, 220, 220, 2493, 796, 513, 20548, 11, 198, 220, 220, 220, 2836, 796, 705, 16244, 3256, 198, 220, 220, 220, 9206, 11639, 34223, 62, 7959, 3256, 198, 220, 220, 220, 6831, 11639, 9288, 3256, 198, 220, 220, 220, 34534, 316, 11639, 40477, 23, 6, 198, 8, 198, 198, 66, 21471, 796, 48260, 13, 66, 21471, 3419, 198, 198, 25410, 796, 37227, 198, 19738, 1635, 422, 2836, 16, 198, 37811, 198, 198, 28311, 25, 198, 220, 220, 220, 23493, 13, 41049, 7, 25410, 8, 198, 220, 220, 220, 581, 796, 23493, 13, 69, 7569, 439, 3419, 198, 220, 220, 220, 329, 5752, 287, 581, 25, 198, 220, 220, 220, 220, 220, 220, 220, 4686, 796, 5752, 58, 15, 60, 198, 220, 220, 220, 220, 220, 220, 220, 277, 3672, 28, 808, 58, 16, 60, 198, 220, 220, 220, 220, 220, 220, 220, 300, 3672, 28, 808, 58, 17, 60, 198, 220, 220, 220, 220, 220, 220, 220, 2479, 796, 808, 58, 18, 60, 198, 220, 220, 220, 220, 220, 220, 220, 1714, 28, 808, 58, 19, 60, 198, 220, 220, 220, 220, 220, 220, 220, 3739, 28, 808, 58, 20, 60, 198, 220, 220, 220, 220, 220, 220, 220, 3601, 7203, 312, 28, 4, 82, 11, 69, 3672, 28, 4, 82, 11, 75, 3672, 28, 4, 82, 11, 496, 28, 4, 82, 11, 8044, 28, 4, 82, 11, 12519, 28, 4, 82, 1, 4064, 357, 312, 11, 277, 3672, 11, 300, 3672, 11, 2479, 11, 1714, 11, 3739, 4008, 198, 16341, 35528, 355, 304, 25, 198, 220, 220, 220, 3601, 7, 68, 8, 198, 198, 2, 10263, 227, 111, 29785, 255, 32573, 252, 162, 236, 98, 198, 37043, 13, 19836, 3419 ]
1.904153
313
from nfmanagementapi.models import ServiceObject from nfmanagementapi.schemata import ServiceObjectSchema from marshmallow.exceptions import ValidationError from .BaseResource import BaseResource from flask import request from app import db from uuid import uuid4 path = 'service_objects' endpoint = 'service_objects'
[ 6738, 299, 69, 27604, 15042, 13, 27530, 1330, 4809, 10267, 198, 6738, 299, 69, 27604, 15042, 13, 1416, 4411, 1045, 1330, 4809, 10267, 27054, 2611, 198, 6738, 22397, 42725, 13, 1069, 11755, 1330, 3254, 24765, 12331, 198, 6738, 764, 14881, 26198, 1330, 7308, 26198, 198, 6738, 42903, 1330, 2581, 198, 6738, 598, 1330, 20613, 198, 6738, 334, 27112, 1330, 334, 27112, 19, 198, 198, 6978, 796, 705, 15271, 62, 48205, 6, 198, 437, 4122, 796, 705, 15271, 62, 48205, 6, 198 ]
3.938272
81
# Generated by Django 3.1.6 on 2021-02-12 00:15 from django.db import migrations, models import django.db.models.deletion
[ 2, 2980, 515, 416, 37770, 513, 13, 16, 13, 21, 319, 33448, 12, 2999, 12, 1065, 3571, 25, 1314, 198, 198, 6738, 42625, 14208, 13, 9945, 1330, 15720, 602, 11, 4981, 198, 11748, 42625, 14208, 13, 9945, 13, 27530, 13, 2934, 1616, 295, 628 ]
2.818182
44
config = { "frequency": 440.0, "duration": 20.0, "sampling_rate": 44100, "filename": "test_v1.wav", "overtones": [ [ 440.0, 1.0 ], [ 12447.350408741928, 0.1098108639573242 ], [ 12465.3571923053, 0.843727285302496 ], [ 21539.57505590213, 0.17496422223017305 ], [ 14675.669378957353, 0.013028474684831037 ], [ 20577.216573422433, 0.23529784971612777 ], [ 21425.497754119715, 0.6436550795219932 ], [ 11410.89145988607, 0.011826877382886125 ] ], "amp_ctrl_points": [ [ 0.0, 0.0 ], [ 20.0, 100.0 ], [ 33.0, 20.0 ], [ 47.0, 88.0 ], [ 56.0, 45.0 ], [ 76.0, 80.0 ], [ 90.0, 5.0 ], [ 100.0, 20.0 ] ] }
[ 11250, 796, 1391, 201, 198, 220, 220, 220, 366, 35324, 1298, 33879, 13, 15, 11, 201, 198, 220, 220, 220, 366, 32257, 1298, 1160, 13, 15, 11, 201, 198, 220, 220, 220, 366, 37687, 11347, 62, 4873, 1298, 5846, 3064, 11, 201, 198, 220, 220, 220, 366, 34345, 1298, 366, 9288, 62, 85, 16, 13, 45137, 1600, 201, 198, 220, 220, 220, 366, 2502, 36257, 1298, 685, 201, 198, 220, 220, 220, 220, 220, 220, 220, 685, 201, 198, 220, 220, 220, 220, 220, 220, 220, 220, 220, 220, 220, 33879, 13, 15, 11, 201, 198, 220, 220, 220, 220, 220, 220, 220, 220, 220, 220, 220, 352, 13, 15, 201, 198, 220, 220, 220, 220, 220, 220, 220, 16589, 201, 198, 220, 220, 220, 220, 220, 220, 220, 685, 201, 198, 220, 220, 220, 220, 220, 220, 220, 220, 220, 220, 220, 1105, 34825, 13, 14877, 26200, 4524, 1129, 2078, 11, 201, 198, 220, 220, 220, 220, 220, 220, 220, 220, 220, 220, 220, 657, 13, 940, 4089, 940, 4521, 2670, 48638, 27877, 201, 198, 220, 220, 220, 220, 220, 220, 220, 16589, 201, 198, 220, 220, 220, 220, 220, 220, 220, 685, 201, 198, 220, 220, 220, 220, 220, 220, 220, 220, 220, 220, 220, 19755, 2996, 13, 27277, 17477, 1270, 4310, 11, 201, 198, 220, 220, 220, 220, 220, 220, 220, 220, 220, 220, 220, 657, 13, 5705, 2718, 1983, 26279, 1270, 1731, 4846, 201, 198, 220, 220, 220, 220, 220, 220, 220, 16589, 201, 198, 220, 220, 220, 220, 220, 220, 220, 685, 201, 198, 220, 220, 220, 220, 220, 220, 220, 220, 220, 220, 220, 22951, 2670, 13, 3553, 1120, 38605, 2999, 1485, 11, 201, 198, 220, 220, 220, 220, 220, 220, 220, 220, 220, 220, 220, 657, 13, 1558, 2920, 2414, 1828, 1828, 18938, 22, 22515, 201, 198, 220, 220, 220, 220, 220, 220, 220, 16589, 201, 198, 220, 220, 220, 220, 220, 220, 220, 685, 201, 198, 220, 220, 220, 220, 220, 220, 220, 220, 220, 220, 220, 22986, 2425, 13, 36657, 2718, 4531, 3553, 33319, 11, 201, 198, 220, 220, 220, 220, 220, 220, 220, 220, 220, 220, 220, 657, 13, 486, 1270, 2078, 2857, 38472, 2780, 26717, 2718, 201, 198, 220, 220, 220, 220, 220, 220, 220, 16589, 201, 198, 220, 220, 220, 220, 220, 220, 220, 685, 201, 198, 220, 220, 220, 220, 220, 220, 220, 220, 220, 220, 220, 22538, 3324, 13, 20666, 3553, 2682, 24137, 2091, 11, 201, 198, 220, 220, 220, 220, 220, 220, 220, 220, 220, 220, 220, 657, 13, 22370, 1959, 3695, 38073, 1433, 1065, 29331, 201, 198, 220, 220, 220, 220, 220, 220, 220, 16589, 201, 198, 220, 220, 220, 220, 220, 220, 220, 685, 201, 198, 220, 220, 220, 220, 220, 220, 220, 220, 220, 220, 220, 28277, 1495, 13, 2920, 34483, 3901, 24991, 1314, 11, 201, 198, 220, 220, 220, 220, 220, 220, 220, 220, 220, 220, 220, 657, 13, 2414, 2623, 22730, 3720, 4309, 19104, 2624, 201, 198, 220, 220, 220, 220, 220, 220, 220, 16589, 201, 198, 220, 220, 220, 220, 220, 220, 220, 685, 201, 198, 220, 220, 220, 220, 220, 220, 220, 220, 220, 220, 220, 17342, 940, 13, 4531, 1415, 3270, 3459, 31980, 11, 201, 198, 220, 220, 220, 220, 220, 220, 220, 220, 220, 220, 220, 657, 13, 486, 1507, 25022, 3324, 2548, 2078, 4521, 11623, 201, 198, 220, 220, 220, 220, 220, 220, 220, 2361, 201, 198, 220, 220, 220, 16589, 201, 198, 220, 220, 220, 366, 696, 62, 44755, 62, 13033, 1298, 685, 201, 198, 220, 220, 220, 220, 220, 220, 220, 685, 201, 198, 220, 220, 220, 220, 220, 220, 220, 220, 220, 220, 220, 657, 13, 15, 11, 201, 198, 220, 220, 220, 220, 220, 220, 220, 220, 220, 220, 220, 657, 13, 15, 201, 198, 220, 220, 220, 220, 220, 220, 220, 16589, 201, 198, 220, 220, 220, 220, 220, 220, 220, 685, 201, 198, 220, 220, 220, 220, 220, 220, 220, 220, 220, 220, 220, 1160, 13, 15, 11, 201, 198, 220, 220, 220, 220, 220, 220, 220, 220, 220, 220, 220, 1802, 13, 15, 201, 198, 220, 220, 220, 220, 220, 220, 220, 16589, 201, 198, 220, 220, 220, 220, 220, 220, 220, 685, 201, 198, 220, 220, 220, 220, 220, 220, 220, 220, 220, 220, 220, 4747, 13, 15, 11, 201, 198, 220, 220, 220, 220, 220, 220, 220, 220, 220, 220, 220, 1160, 13, 15, 201, 198, 220, 220, 220, 220, 220, 220, 220, 16589, 201, 198, 220, 220, 220, 220, 220, 220, 220, 685, 201, 198, 220, 220, 220, 220, 220, 220, 220, 220, 220, 220, 220, 6298, 13, 15, 11, 201, 198, 220, 220, 220, 220, 220, 220, 220, 220, 220, 220, 220, 9193, 13, 15, 201, 198, 220, 220, 220, 220, 220, 220, 220, 16589, 201, 198, 220, 220, 220, 220, 220, 220, 220, 685, 201, 198, 220, 220, 220, 220, 220, 220, 220, 220, 220, 220, 220, 7265, 13, 15, 11, 201, 198, 220, 220, 220, 220, 220, 220, 220, 220, 220, 220, 220, 4153, 13, 15, 201, 198, 220, 220, 220, 220, 220, 220, 220, 16589, 201, 198, 220, 220, 220, 220, 220, 220, 220, 685, 201, 198, 220, 220, 220, 220, 220, 220, 220, 220, 220, 220, 220, 8684, 13, 15, 11, 201, 198, 220, 220, 220, 220, 220, 220, 220, 220, 220, 220, 220, 4019, 13, 15, 201, 198, 220, 220, 220, 220, 220, 220, 220, 16589, 201, 198, 220, 220, 220, 220, 220, 220, 220, 685, 201, 198, 220, 220, 220, 220, 220, 220, 220, 220, 220, 220, 220, 4101, 13, 15, 11, 201, 198, 220, 220, 220, 220, 220, 220, 220, 220, 220, 220, 220, 642, 13, 15, 201, 198, 220, 220, 220, 220, 220, 220, 220, 16589, 201, 198, 220, 220, 220, 220, 220, 220, 220, 685, 201, 198, 220, 220, 220, 220, 220, 220, 220, 220, 220, 220, 220, 1802, 13, 15, 11, 201, 198, 220, 220, 220, 220, 220, 220, 220, 220, 220, 220, 220, 1160, 13, 15, 201, 198, 220, 220, 220, 220, 220, 220, 220, 2361, 201, 198, 220, 220, 220, 2361, 201, 198, 92, 201, 198 ]
1.307617
1,024
import datetime import re import os import struct from dataclasses import dataclass, field from itertools import combinations, product from typing import List, Dict import pandas as pd import numpy as np import peakutils from matplotlib import pyplot as plt from scipy import signal as spsig import plotly.graph_objs as go from tqdm.autonotebook import tqdm import networkx as nx from ipywidgets import interactive, VBox, HBox from lmfit.models import LinearModel from pyspectools import routines from pyspectools import figurefactory as ff from pyspectools import fitting from pyspectools.spectra import analysis from pyspectools import parsers def parse_spectrum(filename, threshold=20.0): """ Function to read in a blackchirp or QtFTM spectrum from file """ dataframe = pd.read_csv( filename, delimiter="\t", names=["Frequency", "Intensity"], skiprows=1 ) return dataframe[dataframe["Intensity"] <= threshold] def center_cavity(dataframe, thres=0.3, verbose=True): """ Finds the center frequency of a Doppler pair in cavity FTM measurements and provides a column of offset frequencies. Sometimes the peak finding threshold has to be tweaked to get the center frequency correctly. """ # Find the peak intensities center_indexes = peakutils.indexes(dataframe["Intensity"], thres=thres) peak_frequencies = dataframe.iloc[center_indexes]["Frequency"] # Calculate the center frequency as the average center = np.average(peak_frequencies) if verbose is True: print("Center frequency at " + str(center)) dataframe["Offset Frequency"] = dataframe["Frequency"] - center @dataclass @dataclass class Scan: """ DataClass for a Scan. Holds all of the relevant information that describes a FT scan, such as the ID, what machine it was collected on, and the experimental settings. Has a few class methods that will make look ups easily such as the date the scan was collected and the gases used. """ id: int machine: str fid: np.array date: datetime.datetime shots: int = 0 cavity_voltage: int = 0 cavity_atten: int = 0 cavity_frequency: float = 0.0 dr_frequency: float = 0.0 dr_power: int = 0 fid_points: int = 0 fid_spacing: float = 0.0 discharge: bool = False magnet: bool = False gases: Dict = field(default_factory=dict) filter: List = field(default_factory=list) exp: float = 0.0 zeropad: bool = False window: str = "" def __post_init__(self): """ Functions called after __init__ is called. """ # Perform FFT self.process_fid() def __deepcopy__(self): """ Dunder method to produce a deep copy - this will be used when manipulating multiple Scan objects. :return: A deep copy of the current Scan object """ new_scan = Empty() new_scan.__class__ = self.__class__ new_scan.__dict__.update(self.__dict__) return new_scan def average(self, others): """ Dunder method to co-average two or more Scans in the time domain. :param other: Scan object, or tuple/list :return: A new Scan object with the co-added FID """ new_scan = self.__deepcopy__() try: new_scan.fid = np.average(others.extend(new_scan.fid), axis=0) new_scan.average_ids = [scan.id for scan in others] # If there is no extend method, then assume we're working with a # single Scan except AttributeError: new_scan.fid = np.average([new_scan.fid, others.fid], axis=0) new_scan.average_ids = [others.id] new_scan.process_fid() return new_scan def __add__(self, other): """ Dunder method to co-add two or more Scans in the time domain. :param other: Scan object, or tuple/list :return: A new Scan object with the co-added FID """ new_scan = self.__deepcopy__() new_scan.fid = np.sum([new_scan.fid, other.fid], axis=0) new_scan.process_fid() return new_scan def __sub__(self, other): """ Dunder method to subtract another Scan from the current Scan in the time domain. i.e. this scan - other scan :param other: Scan object, or tuple/list :return: A new Scan object with the subtracted FID """ new_scan = self.__deepcopy__() new_scan.fid = np.subtract(new_scan.fid, other.fid) new_scan.process_fid() return new_scan def subtract_frequency(self, other): """ Method to subtract another Scan from the current in the frequency domain. :param other: Scan object to subtract with :return: A new Scan object with the subtracted spectrum """ new_scan = self.__deepcopy__() new_scan.spectrum["Intensity"] = ( new_scan.spectrum["Intensity"] - other.spectrum["Intensity"] ) new_scan.subtracted = other.id return new_scan def add_frequency(self, other): """ Method to add another Scan from the current in the frequency domain. :param other: Scan object to add with :return: A new Scan object with the co-added spectrum """ new_scan = self.__deepcopy__() new_scan.spectrum["Intensity"] = ( new_scan.spectrum["Intensity"] + other.spectrum["Intensity"] ) new_scan.subtracted = other.id return new_scan @classmethod def from_dict(cls, data_dict): """ Function to initialize a Scan object from a dictionary of FT scan data collected from `parse_scan`. :param data_dict: dict containing parsed data from FT :return: Scan object """ scan_obj = cls(**data_dict) return scan_obj @classmethod def from_qtftm(cls, filepath): """ Method to initialize a Scan object from a FT scan file. Will load the lines into memory and parse the data into a dictionary, which then gets passed into a Scan object. :param filepath: str path to FID file :return: Scan object """ with open(filepath) as read_file: data_dict = parse_scan(read_file.readlines()) scan_obj = cls(**data_dict) return scan_obj @classmethod def from_pickle(cls, filepath): """ Method to create a Scan object from a previously pickled Scan. :param filepath: path to the Scan pickle :return: instance of the Scan object """ scan_obj = routines.read_obj(filepath) if isinstance(scan_obj, Scan) is False: raise Exception("File is not a Scan object; {}".format(type(scan_obj))) else: return scan_obj @classmethod def from_remote(cls, remote_path, ssh_obj=None): """ Method to initialize a Scan object from a remote server. Has the option to pass an instance of a paramiko SSHClient, which would be useful in a Batch. If none is supplied, an instance will be created. :param remote_path: str remote path to the file :param ssh_obj: optional argument to supply a paramiko SSHClient object :return: Scan object from remote QtFTM file """ if ssh_obj is None: default_keypath = os.path.join(os.path.expanduser("~"), ".ssh/id_rsa.pub") hostname = input("Please provide remote hostname: ") username = input("Please provide login: ") ssh_settings = {"hostname": hostname, "username": username} if os.path.isfile(default_keypath) is True: ssh_settings["key_filename"] = default_keypath else: password = input("Please provide password: ") ssh_settings["password"] = password ssh_obj = routines.RemoteClient(**ssh_settings) # Parse the scan data from remote file data_dict = parse_scan(ssh_obj.open_remote(remote_path)) scan_obj = cls(**data_dict) return scan_obj def to_file(self, filepath, format="yaml"): """ Method to dump data to YAML format. Extensions are automatically decided, but can also be supplied. parameters: -------------------- :param filepath - str path to yaml file :param format - str denoting the syntax used for dumping. Defaults to YAML. """ if "." not in filepath: if format == "json": filepath += ".json" else: filepath += ".yml" if format == "json": writer = routines.dump_json else: writer = routines.dump_yaml writer(filepath, self.__dict__) def to_pickle(self, filepath=None, **kwargs): """ Pickles the Scan object with the joblib wrapper implemented in routines. :param filepath: optional argument to pickle to. Defaults to the id.pkl :param kwargs: additional settings for the pickle operation """ if filepath is None: filepath = "{}.pkl".format(self.id) routines.save_obj(self, filepath, **kwargs) def process_fid(self, **kwargs): """ Perform an FFT on the FID to yield the frequency domain spectrum. Kwargs are passed into the FID processing, which will override the Scan attributes. :param kwargs: Optional keyword arguments for processing the FID """ # Calculate the frequency bins frequencies = np.linspace( self.cavity_frequency, self.cavity_frequency + 1.0, len(self.fid) ) # Calculate the time bins time = np.linspace(0.0, self.fid_spacing * self.fid_points, self.fid_points) process_list = ["window", "filter", "exp", "zeropad"] process_dict = { key: value for key, value in self.__dict__.items() if key in process_list } # Override with user settings process_dict.update(**kwargs) temp_fid = np.copy(self.fid) self.spectrum = fid2fft( temp_fid, 1.0 / self.fid_spacing, frequencies, **process_dict ) self.fid_df = pd.DataFrame({"Time (us)": time * 1e6, "FID": temp_fid}) def within_time(self, date_range): """ Function for determining of the scan was taken between a specified date range in month/day/year, in the format 04/09/08 for April 9th, 2008. :param date_range: list containing the beginning and end date strings :return: bool - True if within range, False otherwise """ try: early = datetime.datetime.strptime(date_range[0], "%m/%d/%y") except: early = datetime.datetime(1, 1, 1) try: late = datetime.datetime.strptime(date_range[1], "%m/%d/%y") except: late = datetime.datetime(9999, 1, 1) return early <= self.date <= late def is_depleted(self, ref, roi=None, depletion=None): """ Function for determining if the signal in this Scan is less than that of another scan. This is done by a simple comparison of the average of 10 largest intensities in the two spectra. If the current scan is less intense than the reference by the expected depletion percentage, then it is "depleted". This function can be used to determine if a scan if depleted in DR/magnet/discharge assays. TODO - implement a chi squared test of sorts to determine if a depletion is statistically significant :param ref: second Scan object for comparison :param depletion: percentage of depletion expected of the reference :return: bool - True if signal in this Scan is less intense than the reference """ y_ref = ref.spectrum["Intensity"].values y_obs = self.spectrum["Intensity"].values self.ref_freq = ref.fit.frequency self.ref_id = ref.id if roi: y_ref = y_ref[roi] y_obs = y_obs[roi] # This doesn't work, or is not particularly discriminating. # chisq, p_value = chisquare( # y_obs, y_ref # ) if depletion is None: sigma = np.std(y_obs, axis=0) * 16.0 else: sigma = depletion expected = np.sum(y_ref, axis=0) - sigma return np.sum(y_obs, axis=0) <= expected def scatter_trace(self): """ Create a Plotly Scattergl trace. Called by the Batch function, although performance-wise it takes forever to plot up ~3000 scans. :return trace: Scattergl object """ text = "Scan ID: {}<br>Cavity: {}<br>DR: {}<br>Magnet: {}<br>Attn: {}".format( self.id, self.cavity_frequency, self.dr_frequency, self.magnet, self.cavity_atten, ) trace = go.Scattergl( x=np.linspace(self.id, self.id + 1, len(self.spectrum["Intensity"])), y=self.spectrum["Intensity"], text=text, marker={"color": "rgb(43,140,190)"}, hoverinfo="text", ) return trace def fit_cavity(self, plot=True, verbose=False): """ Perform a fit to the cavity spectrum. Uses a paired Gaussian model that minimizes the number of fitting parameters. :param plot: bool specify whether a Plotly figure is made :return: Model Fit result """ y = self.spectrum["Intensity"].dropna().values x = self.spectrum["Frequency (MHz)"].dropna().values model = fitting.PairGaussianModel() result = model.fit_pair(x, y, verbose=verbose) self.spectrum["Fit"] = result.best_fit self.fit = result self.fit.frequency = self.fit.best_values["x0"] if plot is True: fig = go.FigureWidget() fig.layout["xaxis"]["title"] = "Frequency (MHz)" fig.layout["xaxis"]["tickformat"] = ".2f" fig.add_scatter(x=x, y=y, name="Observed") fig.add_scatter(x=x, y=result.best_fit, name="Fit") return result, fig else: return result def parse_scan(filecontents): """ Function for extracting the FID data from an FT scan. The data is returned as a dictionary, which can be used to initialize a Scan object. :param filecontents: list of lines from an FID file :return: dict containing parsed data from FID """ data = {"gases": dict()} # FID regex fid_regex = re.compile(r"^fid\d*", re.M) # Regex to find gas channels gas_regex = re.compile(r"^#Gas \d name", re.M) flow_regex = re.compile(r"^#Gas \d flow", re.M) # Regex to detect which channel is set to the discharge dc_regex = re.compile(r"^#Pulse ch \d name\s*DC", re.M) dc_channel = None for index, line in enumerate(filecontents): if "#Scan" in line: split_line = line.split() data["id"] = int(split_line[1]) try: data["machine"] = split_line[2] except IndexError: data["machine"] = "FT1" if "#Probe freq" in line: data["cavity_frequency"] = float(line.split()[2]) if "#Shots" in line: data["shots"] = int(line.split()[-1]) if "#Date" in line: strip_targets = ["#Date", "\t", "\n"] data["date"] = datetime.datetime.strptime( re.sub("|".join(strip_targets), "", line), "%a %b %d %H:%M:%S %Y" ) if "#Cavity Voltage" in line: data["cavity_voltage"] = int(line.split()[2]) if "#Attenuation" in line: data["cavity_atten"] = int(line.split()[1]) if "#DR freq" in line: data["dr_frequency"] = float(line.split()[2]) if "#DR power" in line: data["dr_power"] = int(line.split()[2]) if "#FID spacing" in line: data["fid_spacing"] = float(re.findall(r"\de[+-]?\d\d", line)[0]) if "#FID points" in line: data["fid_points"] = int(line.split()[-1]) # Get the name of the gas if gas_regex.match(line): split_line = line.split() # Only bother parsing if the channel is used gas_index = int(split_line[1]) try: data["gases"][gas_index] = {"gas": " ".join(split_line[3:])} except IndexError: data["gases"][gas_index] = {"gas": ""} # Get the flow rate for channel if flow_regex.match(line): split_line = line.split() gas_index = int(split_line[1]) data["gases"][gas_index]["flow"] = float(split_line[3]) if "#Magnet enabled" in line: data["magnet"] = bool(int(line.split()[2])) # Find the channel the discharge is set to and compile a regex # to look for the channel if dc_regex.match(line): dc_index = line.split()[2] dc_channel = re.compile(r"^#Pulse ch {} enabled".format(dc_index), re.M) # Once the discharge channel index is known, start searching for it if dc_channel: if dc_channel.match(line): data["discharge"] = bool(int(line.split()[-1])) # Find when the FID lines start popping up if fid_regex.match(line): fid = filecontents[index + 1 :] fid = [float(value) for value in fid] data["fid"] = np.array(fid) return data def perform_fft(fid, spacing, start=0, stop=-1, window="boxcar"): """ Perform an FFT on an FID to get the frequency domain spectrum. All of the arguments are optional, and provide control over how the FFT is performed, as well as post-processing parameters like window functions and zero-padding. This is based on the FFT code by Kyle Crabtree, with modifications to fit this dataclass. Parameters ---------- fid - Numpy 1D array Array holding the values of the FID spacing - float Time spacing between FID points in microseconds start - int, optional Starting index for the FID array to perform the FFT stop - int, optional End index for the FID array to perform the FFT zpf - int, optional Pad the FID with zeros to nth nearest power of 2 window - str Specify the window function used to process the FID. Defaults to boxcar, which is effectively no filtering. The names of the window functions available can be found at: https://docs.scipy.org/doc/scipy/reference/signal.windows.html Returns ------- """ fid = np.copy(fid) if window is not None and window in spsig.windows.__all__: window_f = spsig.windows.get_window(window, fid.size) fid *= window_f else: raise Exception("Specified window function is not implemented in SciPy!") # Set values to zero up to starting index fid[:start] = 0.0 if stop < 0: # If we're using negative indexes fid[fid.size + stop :] = 0.0 else: # Otherwise, index with a positive number fid[stop:] = 0.0 # Perform the FFT fft = np.fft.rfft(fid) read_length = len(fid) // 2 + 1 df = 1.0 / fid.size / spacing # Generate the frequency array frequency = np.linspace(0.0, self.header["sideband"] * df, read_length) frequency += self.header["probe_freq"] fft[(frequency >= f_max) & (frequency <= f_min)] = 0.0 fft *= 1000.0 return frequency, fft def fid2fft(fid, rate, frequencies, **kwargs): """ Process an FID by performing an FFT to yield the frequency domain information. Kwargs are passed as additional processing options, and are implemented as some case statements to ensure the settings are valid (e.g. conforms to sampling rate, etc.) :param fid: np.array corresponding to the FID intensity :param rate: sampling rate in Hz :param frequencies: np.array corresponding to the frequency bins :param kwargs: signal processing options: delay - delays the FID processing by setting the start of the FID to zero zeropad - Toggles whether or not the number of sampled points is doubled to get artificially higher resolution in the FFT window - Various window functions provided by `scipy.signal` exp - Specifies an exponential filter filter - 2-tuple specifying the frequency cutoffs for a band pass filter :return: freq_df - pandas dataframe with the FFT spectrum """ # Remove DC new_fid = fid - np.average(fid) if "delay" in kwargs: delay = int(kwargs["delay"] / (1.0 / rate) / 1e6) new_fid[:delay] = 0.0 # Zero-pad the FID if "zeropad" in kwargs: if kwargs["zeropad"] is True: # Pad the FID with zeros to get higher resolution fid = np.append(new_fid, np.zeros(len(new_fid))) # Since we've padded with zeros, we'll have to update the # frequency array frequencies = spsig.resample(frequencies, len(frequencies) * 2) # Apply a window function to the FID if "window" in kwargs: if kwargs["window"] in spsig.windows.__all__: new_fid *= spsig.get_window(kwargs["window"], new_fid.size) # Apply an exponential filter on the FID if "exp" in kwargs: if kwargs["exp"] > 0.0: new_fid *= spsig.exponential(len(new_fid), tau=kwargs["exp"]) # Apply a bandpass filter on the FID if ("filter" in kwargs) and (len(kwargs["filter"]) == 2): low, high = sorted(kwargs["filter"]) if low < high: new_fid = apply_butter_filter(new_fid, low, high, rate) # Perform the FFT fft = np.fft.rfft(new_fid) # Get the real part of the FFT, and only the non-duplicated side real_fft = np.abs(fft[: int(len(new_fid) / 2)]) / len(new_fid) * 1e3 frequencies = spsig.resample(frequencies, real_fft.size) # For some reason, resampling screws up the frequency ordering... real_fft = real_fft[np.argsort(frequencies)] frequencies = np.sort(frequencies) # Package into a pandas dataframe freq_df = pd.DataFrame({"Frequency (MHz)": frequencies, "Intensity": real_fft}) return freq_df def butter_bandpass(low, high, rate, order=1): """ A modified version of the Butterworth bandpass filter described here, adapted for use with the FID signal. http://scipy-cookbook.readthedocs.io/items/ButterworthBandpass.html The arguments are: :param low The low frequency cut-off, given in kHz. :param high The high frequency cut-off, given in kHz. :param rate The sampling rate, given in Hz. From the FIDs, this means that the inverse of the FID spacing is used. :return bandpass window """ # Calculate the Nyquist frequency nyq = 0.5 * (rate / (2.0 * np.pi)) low = (low * 1e3) / nyq high = (high * 1e3) / nyq if high > 1.0: raise Exception("High frequency cut-off exceeds the Nyquist frequency.") b, a = spsig.butter(order, [low, high], btype="band", analog=False) return b, a def apply_butter_filter(data, low, high, rate, order=1): """ A modified Butterworth bandpass filter, adapted from the Scipy cookbook. The argument data supplies the FID, which then uses the scipy signal processing function to apply the digital filter, and returns the filtered FID. See the `butter_bandpass` function for additional arguments. """ b, a = butter_bandpass(low, high, rate, order=order) y = spsig.lfilter(b, a, data) return y def generate_ftb_line(frequency, shots, **kwargs): """ Function that generates an FTB file for a list of frequencies, plus categorization tests. kwargs are passed as additional options for the ftb batch. Keywords are: magnet: bool dipole: float atten: int skiptune: bool drfreq: float drpower: int cal parameters: --------------- :param frequency: float for frequency in MHz :param shots: int number of shots to integrate for returns: --------------- :return ftbline: str """ line = "ftm:{:.4f} shots:{}".format(frequency, shots) for key, value in kwargs.items(): line += " {}:{}".format(key, value) line += "\n" return line def neu_categorize_frequencies(frequencies, intensities=None, nshots=50, **kwargs): """ Routine to generate an FTB batch file for performing a series of tests on frequencies. """ ftb_string = "" if intensities: norm_int = intensities / np.max(intensities) shotcounts = np.round(nshots / norm_int).astype(int) else: shotcounts = np.full(len(frequencies), nshots, dtype=int) # default settings for all stuff param_dict = { "dipole": 1.0, "magnet": "false", "drpower": "10", "skiptune": "false", } param_dict.update(kwargs) for freq, shot in zip(frequencies, shotcounts): ftb_string += generate_ftb_str(freq, shot, **param_dict) if "magnet" in kwargs: param_dict["magnet"] = "true" ftb_string += generate_ftb_str(freq, shot, **param_dict) def categorize_frequencies( frequencies, nshots=50, intensities=None, power=None, attn_list=None, dipole=None, attn=None, magnet=False, dr=False, discharge=False, ): """ Function that will format an FT batch file to perform categorization tests, with some flexibility on how certain tests are performed. """ ftb_str = "" if intensities is None: shots = np.full(len(frequencies), nshots, dtype=int) else: shots = np.sqrt(nshots / intensities).astype(int) if dipole: if attn is None: # If dipole test requested, but no attenuation # supplied do the default sweep dipole_test = [0.01, 0.1, 1.0, 3.0, 5.0] dipole_flag = "dipole" else: # Otherwise run specific attenuations dipole_test = attn_list dipole_flag = "atten" if dr is True: freq_list = combinations(frequencies, 2) print(list(freq_list)) else: freq_list = frequencies # loop over each frequency and number of shots for value, shotcount in zip(freq_list, shots): if dr is True: freq, dr_freq = value else: freq = value # Generate normal observation try: freq = float(freq) shotcount = int(shotcount) if dr is True: dr_freq = float(dr_freq) ftb_str += generate_ftb_line(freq, shotcount, **{"skiptune": "false"}) if dr is True: ftb_str += generate_ftb_line( freq, shotcount, **{"skiptune": "true", "drfreq": dr_freq} ) if dipole is True: for dipole_value in dipole_test: ftb_str += generate_ftb_line( freq, shotcount, **{dipole_flag: dipole_value} ) if magnet is True: ftb_str += generate_ftb_line(freq, shotcount, **{"magnet": "true"}) if discharge is True: # Toggle the discharge stack on and off ftb_str += generate_ftb_line( freq, shotcount, **{"pulse,1,enabled": "false"} ) ftb_str += generate_ftb_line( freq, shotcount, **{"pulse,1,enabled": "true"} ) except ValueError: print("Error with " + str(value)) return ftb_str def calculate_integration_times(intensity, nshots=50): """ Method for calculating the expected integration time in shot counts based on the intensity; either theoretical line strengths or SNR. parameters: --------------- intensity - array of intensity metric; e.g. SNR nshots - optional int number of shots used for the strongest line returns: --------------- shot_counts - array of shot counts for each frequency """ norm_int = intensity / np.max(intensity) shot_counts = np.round(nshots / norm_int).astype(int) return shot_counts @dataclass @dataclass
[ 11748, 4818, 8079, 198, 11748, 302, 198, 11748, 28686, 198, 11748, 2878, 198, 6738, 4818, 330, 28958, 1330, 4818, 330, 31172, 11, 2214, 198, 6738, 340, 861, 10141, 1330, 17790, 11, 1720, 198, 6738, 19720, 1330, 7343, 11, 360, 713, 198, 198, 11748, 19798, 292, 355, 279, 67, 198, 11748, 299, 32152, 355, 45941, 198, 11748, 9103, 26791, 198, 6738, 2603, 29487, 8019, 1330, 12972, 29487, 355, 458, 83, 198, 6738, 629, 541, 88, 1330, 6737, 355, 599, 82, 328, 198, 11748, 7110, 306, 13, 34960, 62, 672, 8457, 355, 467, 198, 6738, 256, 80, 36020, 13, 2306, 261, 1258, 2070, 1330, 256, 80, 36020, 198, 11748, 3127, 87, 355, 299, 87, 198, 6738, 20966, 88, 28029, 11407, 1330, 14333, 11, 569, 14253, 11, 367, 14253, 198, 6738, 300, 76, 11147, 13, 27530, 1330, 44800, 17633, 198, 198, 6738, 279, 893, 806, 10141, 1330, 31878, 198, 6738, 279, 893, 806, 10141, 1330, 3785, 69, 9548, 355, 31246, 198, 6738, 279, 893, 806, 10141, 1330, 15830, 198, 6738, 279, 893, 806, 10141, 13, 4443, 430, 1330, 3781, 198, 6738, 279, 893, 806, 10141, 1330, 13544, 364, 628, 198, 198, 4299, 21136, 62, 4443, 6582, 7, 34345, 11, 11387, 28, 1238, 13, 15, 2599, 198, 220, 220, 220, 37227, 15553, 284, 1100, 287, 257, 2042, 354, 343, 79, 393, 33734, 9792, 44, 10958, 422, 2393, 37227, 198, 220, 220, 220, 1366, 14535, 796, 279, 67, 13, 961, 62, 40664, 7, 198, 220, 220, 220, 220, 220, 220, 220, 29472, 11, 46728, 2676, 2625, 59, 83, 1600, 3891, 28, 14692, 37, 28707, 1600, 366, 5317, 6377, 33116, 14267, 8516, 28, 16, 198, 220, 220, 220, 1267, 198, 220, 220, 220, 1441, 1366, 14535, 58, 7890, 14535, 14692, 5317, 6377, 8973, 19841, 11387, 60, 628, 198, 4299, 3641, 62, 66, 615, 414, 7, 7890, 14535, 11, 294, 411, 28, 15, 13, 18, 11, 15942, 577, 28, 17821, 2599, 198, 220, 220, 220, 37227, 9938, 82, 262, 3641, 8373, 286, 257, 2141, 381, 1754, 5166, 287, 31643, 376, 15972, 13871, 198, 220, 220, 220, 220, 220, 220, 220, 290, 3769, 257, 5721, 286, 11677, 19998, 13, 628, 220, 220, 220, 220, 220, 220, 220, 8975, 262, 9103, 4917, 11387, 468, 284, 307, 38304, 284, 651, 262, 3641, 198, 220, 220, 220, 220, 220, 220, 220, 8373, 9380, 13, 198, 220, 220, 220, 37227, 198, 220, 220, 220, 1303, 9938, 262, 9103, 17509, 871, 198, 220, 220, 220, 3641, 62, 9630, 274, 796, 9103, 26791, 13, 9630, 274, 7, 7890, 14535, 14692, 5317, 6377, 33116, 294, 411, 28, 400, 411, 8, 198, 220, 220, 220, 9103, 62, 69, 8897, 3976, 796, 1366, 14535, 13, 346, 420, 58, 16159, 62, 9630, 274, 7131, 1, 37, 28707, 8973, 198, 220, 220, 220, 1303, 27131, 378, 262, 3641, 8373, 355, 262, 2811, 198, 220, 220, 220, 3641, 796, 45941, 13, 23913, 7, 36729, 62, 69, 8897, 3976, 8, 198, 220, 220, 220, 611, 15942, 577, 318, 6407, 25, 198, 220, 220, 220, 220, 220, 220, 220, 3601, 7203, 23656, 8373, 379, 366, 1343, 965, 7, 16159, 4008, 198, 220, 220, 220, 1366, 14535, 14692, 34519, 31902, 8973, 796, 1366, 14535, 14692, 37, 28707, 8973, 532, 3641, 628, 198, 31, 19608, 330, 31172, 628, 198, 31, 19608, 330, 31172, 198, 4871, 20937, 25, 198, 220, 220, 220, 37227, 198, 220, 220, 220, 6060, 9487, 329, 257, 20937, 13, 9340, 82, 477, 286, 262, 5981, 1321, 326, 198, 220, 220, 220, 8477, 257, 19446, 9367, 11, 884, 355, 262, 4522, 11, 644, 4572, 340, 373, 7723, 198, 220, 220, 220, 319, 11, 290, 262, 11992, 6460, 13, 628, 220, 220, 220, 7875, 257, 1178, 1398, 5050, 326, 481, 787, 804, 19649, 3538, 884, 355, 198, 220, 220, 220, 262, 3128, 262, 9367, 373, 7723, 290, 262, 21678, 973, 13, 198, 220, 220, 220, 37227, 628, 220, 220, 220, 4686, 25, 493, 198, 220, 220, 220, 4572, 25, 965, 198, 220, 220, 220, 49909, 25, 45941, 13, 18747, 198, 220, 220, 220, 3128, 25, 4818, 8079, 13, 19608, 8079, 198, 220, 220, 220, 6934, 25, 493, 796, 657, 198, 220, 220, 220, 31643, 62, 37764, 496, 25, 493, 796, 657, 198, 220, 220, 220, 31643, 62, 41769, 25, 493, 796, 657, 198, 220, 220, 220, 31643, 62, 35324, 25, 12178, 796, 657, 13, 15, 198, 220, 220, 220, 1553, 62, 35324, 25, 12178, 796, 657, 13, 15, 198, 220, 220, 220, 1553, 62, 6477, 25, 493, 796, 657, 198, 220, 220, 220, 49909, 62, 13033, 25, 493, 796, 657, 198, 220, 220, 220, 49909, 62, 2777, 4092, 25, 12178, 796, 657, 13, 15, 198, 220, 220, 220, 17655, 25, 20512, 796, 10352, 198, 220, 220, 220, 19972, 25, 20512, 796, 10352, 198, 220, 220, 220, 21678, 25, 360, 713, 796, 2214, 7, 12286, 62, 69, 9548, 28, 11600, 8, 198, 220, 220, 220, 8106, 25, 7343, 796, 2214, 7, 12286, 62, 69, 9548, 28, 4868, 8, 198, 220, 220, 220, 1033, 25, 12178, 796, 657, 13, 15, 198, 220, 220, 220, 1976, 263, 404, 324, 25, 20512, 796, 10352, 198, 220, 220, 220, 4324, 25, 965, 796, 13538, 628, 220, 220, 220, 825, 11593, 7353, 62, 15003, 834, 7, 944, 2599, 198, 220, 220, 220, 220, 220, 220, 220, 37227, 198, 220, 220, 220, 220, 220, 220, 220, 40480, 1444, 706, 11593, 15003, 834, 318, 1444, 13, 198, 220, 220, 220, 220, 220, 220, 220, 37227, 198, 220, 220, 220, 220, 220, 220, 220, 1303, 35006, 376, 9792, 198, 220, 220, 220, 220, 220, 220, 220, 2116, 13, 14681, 62, 69, 312, 3419, 628, 220, 220, 220, 825, 11593, 22089, 30073, 834, 7, 944, 2599, 198, 220, 220, 220, 220, 220, 220, 220, 37227, 198, 220, 220, 220, 220, 220, 220, 220, 360, 4625, 2446, 284, 4439, 257, 2769, 4866, 532, 428, 481, 307, 973, 618, 198, 220, 220, 220, 220, 220, 220, 220, 29349, 3294, 20937, 5563, 13, 198, 220, 220, 220, 220, 220, 220, 220, 1058, 7783, 25, 317, 2769, 4866, 286, 262, 1459, 20937, 2134, 198, 220, 220, 220, 220, 220, 220, 220, 37227, 628, 220, 220, 220, 220, 220, 220, 220, 649, 62, 35836, 796, 33523, 3419, 198, 220, 220, 220, 220, 220, 220, 220, 649, 62, 35836, 13, 834, 4871, 834, 796, 2116, 13, 834, 4871, 834, 198, 220, 220, 220, 220, 220, 220, 220, 649, 62, 35836, 13, 834, 11600, 834, 13, 19119, 7, 944, 13, 834, 11600, 834, 8, 198, 220, 220, 220, 220, 220, 220, 220, 1441, 649, 62, 35836, 628, 220, 220, 220, 825, 2811, 7, 944, 11, 1854, 2599, 198, 220, 220, 220, 220, 220, 220, 220, 37227, 198, 220, 220, 220, 220, 220, 220, 220, 360, 4625, 2446, 284, 763, 12, 23913, 734, 393, 517, 1446, 504, 287, 262, 640, 7386, 13, 198, 220, 220, 220, 220, 220, 220, 220, 1058, 17143, 584, 25, 20937, 2134, 11, 393, 46545, 14, 4868, 198, 220, 220, 220, 220, 220, 220, 220, 1058, 7783, 25, 317, 649, 20937, 2134, 351, 262, 763, 12, 29373, 376, 2389, 198, 220, 220, 220, 220, 220, 220, 220, 37227, 198, 220, 220, 220, 220, 220, 220, 220, 649, 62, 35836, 796, 2116, 13, 834, 22089, 30073, 834, 3419, 198, 220, 220, 220, 220, 220, 220, 220, 1949, 25, 198, 220, 220, 220, 220, 220, 220, 220, 220, 220, 220, 220, 649, 62, 35836, 13, 69, 312, 796, 45941, 13, 23913, 7, 847, 82, 13, 2302, 437, 7, 3605, 62, 35836, 13, 69, 312, 828, 16488, 28, 15, 8, 198, 220, 220, 220, 220, 220, 220, 220, 220, 220, 220, 220, 649, 62, 35836, 13, 23913, 62, 2340, 796, 685, 35836, 13, 312, 329, 9367, 287, 1854, 60, 198, 220, 220, 220, 220, 220, 220, 220, 1303, 1002, 612, 318, 645, 9117, 2446, 11, 788, 7048, 356, 821, 1762, 351, 257, 198, 220, 220, 220, 220, 220, 220, 220, 1303, 2060, 20937, 198, 220, 220, 220, 220, 220, 220, 220, 2845, 3460, 4163, 12331, 25, 198, 220, 220, 220, 220, 220, 220, 220, 220, 220, 220, 220, 649, 62, 35836, 13, 69, 312, 796, 45941, 13, 23913, 26933, 3605, 62, 35836, 13, 69, 312, 11, 1854, 13, 69, 312, 4357, 16488, 28, 15, 8, 198, 220, 220, 220, 220, 220, 220, 220, 220, 220, 220, 220, 649, 62, 35836, 13, 23913, 62, 2340, 796, 685, 847, 82, 13, 312, 60, 198, 220, 220, 220, 220, 220, 220, 220, 649, 62, 35836, 13, 14681, 62, 69, 312, 3419, 198, 220, 220, 220, 220, 220, 220, 220, 1441, 649, 62, 35836, 628, 220, 220, 220, 825, 11593, 2860, 834, 7, 944, 11, 584, 2599, 198, 220, 220, 220, 220, 220, 220, 220, 37227, 198, 220, 220, 220, 220, 220, 220, 220, 360, 4625, 2446, 284, 763, 12, 2860, 734, 393, 517, 1446, 504, 287, 262, 640, 7386, 13, 198, 220, 220, 220, 220, 220, 220, 220, 1058, 17143, 584, 25, 20937, 2134, 11, 393, 46545, 14, 4868, 198, 220, 220, 220, 220, 220, 220, 220, 1058, 7783, 25, 317, 649, 20937, 2134, 351, 262, 763, 12, 29373, 376, 2389, 198, 220, 220, 220, 220, 220, 220, 220, 37227, 198, 220, 220, 220, 220, 220, 220, 220, 649, 62, 35836, 796, 2116, 13, 834, 22089, 30073, 834, 3419, 198, 220, 220, 220, 220, 220, 220, 220, 649, 62, 35836, 13, 69, 312, 796, 45941, 13, 16345, 26933, 3605, 62, 35836, 13, 69, 312, 11, 584, 13, 69, 312, 4357, 16488, 28, 15, 8, 198, 220, 220, 220, 220, 220, 220, 220, 649, 62, 35836, 13, 14681, 62, 69, 312, 3419, 198, 220, 220, 220, 220, 220, 220, 220, 1441, 649, 62, 35836, 628, 220, 220, 220, 825, 11593, 7266, 834, 7, 944, 11, 584, 2599, 198, 220, 220, 220, 220, 220, 220, 220, 37227, 198, 220, 220, 220, 220, 220, 220, 220, 360, 4625, 2446, 284, 34128, 1194, 20937, 422, 262, 1459, 20937, 287, 262, 640, 7386, 13, 198, 220, 220, 220, 220, 220, 220, 220, 1312, 13, 68, 13, 428, 9367, 532, 584, 9367, 198, 220, 220, 220, 220, 220, 220, 220, 1058, 17143, 584, 25, 20937, 2134, 11, 393, 46545, 14, 4868, 198, 220, 220, 220, 220, 220, 220, 220, 1058, 7783, 25, 317, 649, 20937, 2134, 351, 262, 13284, 20216, 376, 2389, 198, 220, 220, 220, 220, 220, 220, 220, 37227, 198, 220, 220, 220, 220, 220, 220, 220, 649, 62, 35836, 796, 2116, 13, 834, 22089, 30073, 834, 3419, 198, 220, 220, 220, 220, 220, 220, 220, 649, 62, 35836, 13, 69, 312, 796, 45941, 13, 7266, 83, 974, 7, 3605, 62, 35836, 13, 69, 312, 11, 584, 13, 69, 312, 8, 198, 220, 220, 220, 220, 220, 220, 220, 649, 62, 35836, 13, 14681, 62, 69, 312, 3419, 198, 220, 220, 220, 220, 220, 220, 220, 1441, 649, 62, 35836, 628, 220, 220, 220, 825, 34128, 62, 35324, 7, 944, 11, 584, 2599, 198, 220, 220, 220, 220, 220, 220, 220, 37227, 198, 220, 220, 220, 220, 220, 220, 220, 11789, 284, 34128, 1194, 20937, 422, 262, 1459, 287, 262, 8373, 7386, 13, 198, 220, 220, 220, 220, 220, 220, 220, 1058, 17143, 584, 25, 20937, 2134, 284, 34128, 351, 198, 220, 220, 220, 220, 220, 220, 220, 1058, 7783, 25, 317, 649, 20937, 2134, 351, 262, 13284, 20216, 10958, 198, 220, 220, 220, 220, 220, 220, 220, 37227, 198, 220, 220, 220, 220, 220, 220, 220, 649, 62, 35836, 796, 2116, 13, 834, 22089, 30073, 834, 3419, 198, 220, 220, 220, 220, 220, 220, 220, 649, 62, 35836, 13, 4443, 6582, 14692, 5317, 6377, 8973, 796, 357, 198, 220, 220, 220, 220, 220, 220, 220, 220, 220, 220, 220, 649, 62, 35836, 13, 4443, 6582, 14692, 5317, 6377, 8973, 532, 584, 13, 4443, 6582, 14692, 5317, 6377, 8973, 198, 220, 220, 220, 220, 220, 220, 220, 1267, 198, 220, 220, 220, 220, 220, 220, 220, 649, 62, 35836, 13, 7266, 83, 20216, 796, 584, 13, 312, 198, 220, 220, 220, 220, 220, 220, 220, 1441, 649, 62, 35836, 628, 220, 220, 220, 825, 751, 62, 35324, 7, 944, 11, 584, 2599, 198, 220, 220, 220, 220, 220, 220, 220, 37227, 198, 220, 220, 220, 220, 220, 220, 220, 11789, 284, 751, 1194, 20937, 422, 262, 1459, 287, 262, 8373, 7386, 13, 198, 220, 220, 220, 220, 220, 220, 220, 1058, 17143, 584, 25, 20937, 2134, 284, 751, 351, 198, 220, 220, 220, 220, 220, 220, 220, 1058, 7783, 25, 317, 649, 20937, 2134, 351, 262, 763, 12, 29373, 10958, 198, 220, 220, 220, 220, 220, 220, 220, 37227, 198, 220, 220, 220, 220, 220, 220, 220, 649, 62, 35836, 796, 2116, 13, 834, 22089, 30073, 834, 3419, 198, 220, 220, 220, 220, 220, 220, 220, 649, 62, 35836, 13, 4443, 6582, 14692, 5317, 6377, 8973, 796, 357, 198, 220, 220, 220, 220, 220, 220, 220, 220, 220, 220, 220, 649, 62, 35836, 13, 4443, 6582, 14692, 5317, 6377, 8973, 1343, 584, 13, 4443, 6582, 14692, 5317, 6377, 8973, 198, 220, 220, 220, 220, 220, 220, 220, 1267, 198, 220, 220, 220, 220, 220, 220, 220, 649, 62, 35836, 13, 7266, 83, 20216, 796, 584, 13, 312, 198, 220, 220, 220, 220, 220, 220, 220, 1441, 649, 62, 35836, 628, 220, 220, 220, 2488, 4871, 24396, 198, 220, 220, 220, 825, 422, 62, 11600, 7, 565, 82, 11, 1366, 62, 11600, 2599, 198, 220, 220, 220, 220, 220, 220, 220, 37227, 198, 220, 220, 220, 220, 220, 220, 220, 15553, 284, 41216, 257, 20937, 2134, 422, 257, 22155, 198, 220, 220, 220, 220, 220, 220, 220, 286, 19446, 9367, 1366, 7723, 422, 4600, 29572, 62, 35836, 44646, 198, 220, 220, 220, 220, 220, 220, 220, 1058, 17143, 1366, 62, 11600, 25, 8633, 7268, 44267, 1366, 422, 19446, 198, 220, 220, 220, 220, 220, 220, 220, 1058, 7783, 25, 20937, 2134, 198, 220, 220, 220, 220, 220, 220, 220, 37227, 198, 220, 220, 220, 220, 220, 220, 220, 9367, 62, 26801, 796, 537, 82, 7, 1174, 7890, 62, 11600, 8, 198, 220, 220, 220, 220, 220, 220, 220, 1441, 9367, 62, 26801, 628, 220, 220, 220, 2488, 4871, 24396, 198, 220, 220, 220, 825, 422, 62, 39568, 701, 76, 7, 565, 82, 11, 2393, 6978, 2599, 198, 220, 220, 220, 220, 220, 220, 220, 37227, 198, 220, 220, 220, 220, 220, 220, 220, 11789, 284, 41216, 257, 20937, 2134, 422, 257, 19446, 9367, 2393, 13, 198, 220, 220, 220, 220, 220, 220, 220, 2561, 3440, 262, 3951, 656, 4088, 290, 21136, 262, 1366, 656, 198, 220, 220, 220, 220, 220, 220, 220, 257, 22155, 11, 543, 788, 3011, 3804, 656, 257, 20937, 2134, 13, 198, 220, 220, 220, 220, 220, 220, 220, 1058, 17143, 2393, 6978, 25, 965, 3108, 284, 376, 2389, 2393, 198, 220, 220, 220, 220, 220, 220, 220, 1058, 7783, 25, 20937, 2134, 198, 220, 220, 220, 220, 220, 220, 220, 37227, 198, 220, 220, 220, 220, 220, 220, 220, 351, 1280, 7, 7753, 6978, 8, 355, 1100, 62, 7753, 25, 198, 220, 220, 220, 220, 220, 220, 220, 220, 220, 220, 220, 1366, 62, 11600, 796, 21136, 62, 35836, 7, 961, 62, 7753, 13, 961, 6615, 28955, 198, 220, 220, 220, 220, 220, 220, 220, 9367, 62, 26801, 796, 537, 82, 7, 1174, 7890, 62, 11600, 8, 198, 220, 220, 220, 220, 220, 220, 220, 1441, 9367, 62, 26801, 628, 220, 220, 220, 2488, 4871, 24396, 198, 220, 220, 220, 825, 422, 62, 27729, 293, 7, 565, 82, 11, 2393, 6978, 2599, 198, 220, 220, 220, 220, 220, 220, 220, 37227, 198, 220, 220, 220, 220, 220, 220, 220, 11789, 284, 2251, 257, 20937, 2134, 422, 257, 4271, 2298, 992, 198, 220, 220, 220, 220, 220, 220, 220, 20937, 13, 198, 220, 220, 220, 220, 220, 220, 220, 1058, 17143, 2393, 6978, 25, 3108, 284, 262, 20937, 2298, 293, 198, 220, 220, 220, 220, 220, 220, 220, 1058, 7783, 25, 4554, 286, 262, 20937, 2134, 198, 220, 220, 220, 220, 220, 220, 220, 37227, 198, 220, 220, 220, 220, 220, 220, 220, 9367, 62, 26801, 796, 31878, 13, 961, 62, 26801, 7, 7753, 6978, 8, 198, 220, 220, 220, 220, 220, 220, 220, 611, 318, 39098, 7, 35836, 62, 26801, 11, 20937, 8, 318, 10352, 25, 198, 220, 220, 220, 220, 220, 220, 220, 220, 220, 220, 220, 5298, 35528, 7203, 8979, 318, 407, 257, 20937, 2134, 26, 23884, 1911, 18982, 7, 4906, 7, 35836, 62, 26801, 22305, 198, 220, 220, 220, 220, 220, 220, 220, 2073, 25, 198, 220, 220, 220, 220, 220, 220, 220, 220, 220, 220, 220, 1441, 9367, 62, 26801, 628, 220, 220, 220, 2488, 4871, 24396, 198, 220, 220, 220, 825, 422, 62, 47960, 7, 565, 82, 11, 6569, 62, 6978, 11, 26678, 62, 26801, 28, 14202, 2599, 198, 220, 220, 220, 220, 220, 220, 220, 37227, 198, 220, 220, 220, 220, 220, 220, 220, 11789, 284, 41216, 257, 20937, 2134, 422, 257, 6569, 4382, 13, 198, 220, 220, 220, 220, 220, 220, 220, 7875, 262, 3038, 284, 1208, 281, 4554, 286, 257, 5772, 12125, 33825, 11792, 11, 543, 561, 307, 198, 220, 220, 220, 220, 220, 220, 220, 4465, 287, 257, 347, 963, 13, 1002, 4844, 318, 14275, 11, 281, 4554, 481, 307, 2727, 13, 628, 220, 220, 220, 220, 220, 220, 220, 1058, 17143, 6569, 62, 6978, 25, 965, 6569, 3108, 284, 262, 2393, 198, 220, 220, 220, 220, 220, 220, 220, 1058, 17143, 26678, 62, 26801, 25, 11902, 4578, 284, 5127, 257, 5772, 12125, 33825, 11792, 2134, 198, 220, 220, 220, 220, 220, 220, 220, 1058, 7783, 25, 20937, 2134, 422, 6569, 33734, 9792, 44, 2393, 198, 220, 220, 220, 220, 220, 220, 220, 37227, 198, 220, 220, 220, 220, 220, 220, 220, 611, 26678, 62, 26801, 318, 6045, 25, 198, 220, 220, 220, 220, 220, 220, 220, 220, 220, 220, 220, 4277, 62, 2539, 6978, 796, 28686, 13, 6978, 13, 22179, 7, 418, 13, 6978, 13, 11201, 392, 7220, 7203, 93, 12340, 27071, 45824, 14, 312, 62, 3808, 64, 13, 12984, 4943, 198, 220, 220, 220, 220, 220, 220, 220, 220, 220, 220, 220, 2583, 3672, 796, 5128, 7203, 5492, 2148, 6569, 2583, 3672, 25, 220, 220, 220, 366, 8, 198, 220, 220, 220, 220, 220, 220, 220, 220, 220, 220, 220, 20579, 796, 5128, 7203, 5492, 2148, 17594, 25, 220, 220, 220, 220, 220, 220, 220, 220, 220, 220, 220, 220, 220, 366, 8, 198, 220, 220, 220, 220, 220, 220, 220, 220, 220, 220, 220, 26678, 62, 33692, 796, 19779, 4774, 3672, 1298, 2583, 3672, 11, 366, 29460, 1298, 20579, 92, 198, 220, 220, 220, 220, 220, 220, 220, 220, 220, 220, 220, 611, 28686, 13, 6978, 13, 4468, 576, 7, 12286, 62, 2539, 6978, 8, 318, 6407, 25, 198, 220, 220, 220, 220, 220, 220, 220, 220, 220, 220, 220, 220, 220, 220, 220, 26678, 62, 33692, 14692, 2539, 62, 34345, 8973, 796, 4277, 62, 2539, 6978, 198, 220, 220, 220, 220, 220, 220, 220, 220, 220, 220, 220, 2073, 25, 198, 220, 220, 220, 220, 220, 220, 220, 220, 220, 220, 220, 220, 220, 220, 220, 9206, 796, 5128, 7203, 5492, 2148, 9206, 25, 220, 220, 220, 220, 220, 220, 220, 220, 220, 220, 220, 220, 220, 366, 8, 198, 220, 220, 220, 220, 220, 220, 220, 220, 220, 220, 220, 220, 220, 220, 220, 26678, 62, 33692, 14692, 28712, 8973, 796, 9206, 198, 220, 220, 220, 220, 220, 220, 220, 220, 220, 220, 220, 26678, 62, 26801, 796, 31878, 13, 36510, 11792, 7, 1174, 45824, 62, 33692, 8, 198, 220, 220, 220, 220, 220, 220, 220, 1303, 2547, 325, 262, 9367, 1366, 422, 6569, 2393, 198, 220, 220, 220, 220, 220, 220, 220, 1366, 62, 11600, 796, 21136, 62, 35836, 7, 45824, 62, 26801, 13, 9654, 62, 47960, 7, 47960, 62, 6978, 4008, 198, 220, 220, 220, 220, 220, 220, 220, 9367, 62, 26801, 796, 537, 82, 7, 1174, 7890, 62, 11600, 8, 198, 220, 220, 220, 220, 220, 220, 220, 1441, 9367, 62, 26801, 628, 220, 220, 220, 825, 284, 62, 7753, 7, 944, 11, 2393, 6978, 11, 5794, 2625, 88, 43695, 1, 2599, 198, 220, 220, 220, 220, 220, 220, 220, 37227, 11789, 284, 10285, 1366, 284, 575, 2390, 43, 5794, 13, 198, 220, 220, 220, 220, 220, 220, 220, 220, 220, 220, 220, 49751, 389, 6338, 3066, 11, 475, 198, 220, 220, 220, 220, 220, 220, 220, 220, 220, 220, 220, 460, 635, 307, 14275, 13, 628, 220, 220, 220, 220, 220, 220, 220, 220, 220, 220, 220, 10007, 25, 198, 220, 220, 220, 220, 220, 220, 220, 220, 220, 220, 220, 41436, 198, 220, 220, 220, 220, 220, 220, 220, 220, 220, 220, 220, 1058, 17143, 2393, 6978, 532, 965, 3108, 284, 331, 43695, 2393, 198, 220, 220, 220, 220, 220, 220, 220, 220, 220, 220, 220, 1058, 17143, 5794, 532, 965, 2853, 10720, 262, 15582, 973, 329, 30231, 13, 2896, 13185, 284, 575, 2390, 43, 13, 198, 220, 220, 220, 220, 220, 220, 220, 37227, 198, 220, 220, 220, 220, 220, 220, 220, 611, 366, 526, 407, 287, 2393, 6978, 25, 198, 220, 220, 220, 220, 220, 220, 220, 220, 220, 220, 220, 611, 5794, 6624, 366, 17752, 1298, 198, 220, 220, 220, 220, 220, 220, 220, 220, 220, 220, 220, 220, 220, 220, 220, 2393, 6978, 15853, 27071, 17752, 1, 198, 220, 220, 220, 220, 220, 220, 220, 220, 220, 220, 220, 2073, 25, 198, 220, 220, 220, 220, 220, 220, 220, 220, 220, 220, 220, 220, 220, 220, 220, 2393, 6978, 15853, 27071, 88, 4029, 1, 198, 220, 220, 220, 220, 220, 220, 220, 611, 5794, 6624, 366, 17752, 1298, 198, 220, 220, 220, 220, 220, 220, 220, 220, 220, 220, 220, 6260, 796, 31878, 13, 39455, 62, 17752, 198, 220, 220, 220, 220, 220, 220, 220, 2073, 25, 198, 220, 220, 220, 220, 220, 220, 220, 220, 220, 220, 220, 6260, 796, 31878, 13, 39455, 62, 88, 43695, 198, 220, 220, 220, 220, 220, 220, 220, 6260, 7, 7753, 6978, 11, 2116, 13, 834, 11600, 834, 8, 628, 220, 220, 220, 825, 284, 62, 27729, 293, 7, 944, 11, 2393, 6978, 28, 14202, 11, 12429, 46265, 22046, 2599, 198, 220, 220, 220, 220, 220, 220, 220, 37227, 198, 220, 220, 220, 220, 220, 220, 220, 12346, 829, 262, 20937, 2134, 351, 262, 1693, 8019, 29908, 9177, 198, 220, 220, 220, 220, 220, 220, 220, 287, 31878, 13, 198, 220, 220, 220, 220, 220, 220, 220, 1058, 17143, 2393, 6978, 25, 11902, 4578, 284, 2298, 293, 284, 13, 2896, 13185, 284, 262, 4686, 13, 79, 41582, 198, 220, 220, 220, 220, 220, 220, 220, 1058, 17143, 479, 86, 22046, 25, 3224, 6460, 329, 262, 2298, 293, 4905, 198, 220, 220, 220, 220, 220, 220, 220, 37227, 198, 220, 220, 220, 220, 220, 220, 220, 611, 2393, 6978, 318, 6045, 25, 198, 220, 220, 220, 220, 220, 220, 220, 220, 220, 220, 220, 2393, 6978, 796, 45144, 27422, 79, 41582, 1911, 18982, 7, 944, 13, 312, 8, 198, 220, 220, 220, 220, 220, 220, 220, 31878, 13, 21928, 62, 26801, 7, 944, 11, 2393, 6978, 11, 12429, 46265, 22046, 8, 628, 220, 220, 220, 825, 1429, 62, 69, 312, 7, 944, 11, 12429, 46265, 22046, 2599, 198, 220, 220, 220, 220, 220, 220, 220, 37227, 198, 220, 220, 220, 220, 220, 220, 220, 35006, 281, 376, 9792, 319, 262, 376, 2389, 284, 7800, 262, 8373, 7386, 10958, 13, 198, 220, 220, 220, 220, 220, 220, 220, 31767, 22046, 389, 3804, 656, 262, 376, 2389, 7587, 11, 543, 481, 20957, 262, 198, 220, 220, 220, 220, 220, 220, 220, 20937, 12608, 13, 198, 220, 220, 220, 220, 220, 220, 220, 1058, 17143, 479, 86, 22046, 25, 32233, 21179, 7159, 329, 7587, 262, 376, 2389, 198, 220, 220, 220, 220, 220, 220, 220, 37227, 198, 220, 220, 220, 220, 220, 220, 220, 1303, 27131, 378, 262, 8373, 41701, 198, 220, 220, 220, 220, 220, 220, 220, 19998, 796, 45941, 13, 21602, 10223, 7, 198, 220, 220, 220, 220, 220, 220, 220, 220, 220, 220, 220, 2116, 13, 66, 615, 414, 62, 35324, 11, 2116, 13, 66, 615, 414, 62, 35324, 1343, 352, 13, 15, 11, 18896, 7, 944, 13, 69, 312, 8, 198, 220, 220, 220, 220, 220, 220, 220, 1267, 198, 220, 220, 220, 220, 220, 220, 220, 1303, 27131, 378, 262, 640, 41701, 198, 220, 220, 220, 220, 220, 220, 220, 640, 796, 45941, 13, 21602, 10223, 7, 15, 13, 15, 11, 2116, 13, 69, 312, 62, 2777, 4092, 1635, 2116, 13, 69, 312, 62, 13033, 11, 2116, 13, 69, 312, 62, 13033, 8, 198, 220, 220, 220, 220, 220, 220, 220, 1429, 62, 4868, 796, 14631, 17497, 1600, 366, 24455, 1600, 366, 11201, 1600, 366, 9107, 404, 324, 8973, 198, 220, 220, 220, 220, 220, 220, 220, 1429, 62, 11600, 796, 1391, 198, 220, 220, 220, 220, 220, 220, 220, 220, 220, 220, 220, 1994, 25, 1988, 329, 1994, 11, 1988, 287, 2116, 13, 834, 11600, 834, 13, 23814, 3419, 611, 1994, 287, 1429, 62, 4868, 198, 220, 220, 220, 220, 220, 220, 220, 1782, 198, 220, 220, 220, 220, 220, 220, 220, 1303, 3827, 13154, 351, 2836, 6460, 198, 220, 220, 220, 220, 220, 220, 220, 1429, 62, 11600, 13, 19119, 7, 1174, 46265, 22046, 8, 198, 220, 220, 220, 220, 220, 220, 220, 20218, 62, 69, 312, 796, 45941, 13, 30073, 7, 944, 13, 69, 312, 8, 198, 220, 220, 220, 220, 220, 220, 220, 2116, 13, 4443, 6582, 796, 49909, 17, 487, 83, 7, 198, 220, 220, 220, 220, 220, 220, 220, 220, 220, 220, 220, 20218, 62, 69, 312, 11, 352, 13, 15, 1220, 2116, 13, 69, 312, 62, 2777, 4092, 11, 19998, 11, 12429, 14681, 62, 11600, 198, 220, 220, 220, 220, 220, 220, 220, 1267, 198, 220, 220, 220, 220, 220, 220, 220, 2116, 13, 69, 312, 62, 7568, 796, 279, 67, 13, 6601, 19778, 7, 4895, 7575, 357, 385, 8, 1298, 640, 1635, 352, 68, 21, 11, 366, 37, 2389, 1298, 20218, 62, 69, 312, 30072, 628, 220, 220, 220, 825, 1626, 62, 2435, 7, 944, 11, 3128, 62, 9521, 2599, 198, 220, 220, 220, 220, 220, 220, 220, 37227, 198, 220, 220, 220, 220, 220, 220, 220, 15553, 329, 13213, 286, 262, 9367, 373, 2077, 1022, 198, 220, 220, 220, 220, 220, 220, 220, 257, 7368, 3128, 2837, 287, 1227, 14, 820, 14, 1941, 11, 287, 262, 5794, 198, 220, 220, 220, 220, 220, 220, 220, 8702, 14, 2931, 14, 2919, 329, 3035, 860, 400, 11, 3648, 13, 198, 220, 220, 220, 220, 220, 220, 220, 1058, 17143, 3128, 62, 9521, 25, 1351, 7268, 262, 3726, 290, 886, 3128, 13042, 198, 220, 220, 220, 220, 220, 220, 220, 1058, 7783, 25, 20512, 532, 6407, 611, 1626, 2837, 11, 10352, 4306, 198, 220, 220, 220, 220, 220, 220, 220, 37227, 198, 220, 220, 220, 220, 220, 220, 220, 1949, 25, 198, 220, 220, 220, 220, 220, 220, 220, 220, 220, 220, 220, 1903, 796, 4818, 8079, 13, 19608, 8079, 13, 2536, 457, 524, 7, 4475, 62, 9521, 58, 15, 4357, 36521, 76, 14, 4, 67, 14, 4, 88, 4943, 198, 220, 220, 220, 220, 220, 220, 220, 2845, 25, 198, 220, 220, 220, 220, 220, 220, 220, 220, 220, 220, 220, 1903, 796, 4818, 8079, 13, 19608, 8079, 7, 16, 11, 352, 11, 352, 8, 198, 220, 220, 220, 220, 220, 220, 220, 1949, 25, 198, 220, 220, 220, 220, 220, 220, 220, 220, 220, 220, 220, 2739, 796, 4818, 8079, 13, 19608, 8079, 13, 2536, 457, 524, 7, 4475, 62, 9521, 58, 16, 4357, 36521, 76, 14, 4, 67, 14, 4, 88, 4943, 198, 220, 220, 220, 220, 220, 220, 220, 2845, 25, 198, 220, 220, 220, 220, 220, 220, 220, 220, 220, 220, 220, 2739, 796, 4818, 8079, 13, 19608, 8079, 7, 24214, 11, 352, 11, 352, 8, 198, 220, 220, 220, 220, 220, 220, 220, 1441, 1903, 19841, 2116, 13, 4475, 19841, 2739, 628, 220, 220, 220, 825, 318, 62, 10378, 33342, 7, 944, 11, 1006, 11, 686, 72, 28, 14202, 11, 42435, 28, 14202, 2599, 198, 220, 220, 220, 220, 220, 220, 220, 37227, 198, 220, 220, 220, 220, 220, 220, 220, 15553, 329, 13213, 611, 262, 6737, 287, 428, 20937, 318, 1342, 198, 220, 220, 220, 220, 220, 220, 220, 621, 326, 286, 1194, 9367, 13, 770, 318, 1760, 416, 257, 2829, 7208, 198, 220, 220, 220, 220, 220, 220, 220, 286, 262, 2811, 286, 838, 4387, 17509, 871, 287, 262, 734, 5444, 430, 13, 1002, 198, 220, 220, 220, 220, 220, 220, 220, 262, 1459, 9367, 318, 1342, 8157, 621, 262, 4941, 416, 262, 198, 220, 220, 220, 220, 220, 220, 220, 2938, 42435, 5873, 11, 788, 340, 318, 366, 10378, 33342, 1911, 628, 220, 220, 220, 220, 220, 220, 220, 770, 2163, 460, 307, 973, 284, 5004, 611, 257, 9367, 611, 34069, 198, 220, 220, 220, 220, 220, 220, 220, 287, 10560, 14, 19726, 3262, 14, 6381, 10136, 840, 592, 13, 628, 220, 220, 220, 220, 220, 220, 220, 16926, 46, 532, 3494, 257, 33166, 44345, 1332, 286, 10524, 284, 5004, 611, 257, 198, 220, 220, 220, 220, 220, 220, 220, 220, 220, 220, 220, 220, 220, 220, 42435, 318, 19941, 2383, 628, 220, 220, 220, 220, 220, 220, 220, 1058, 17143, 1006, 25, 1218, 20937, 2134, 329, 7208, 198, 220, 220, 220, 220, 220, 220, 220, 1058, 17143, 42435, 25, 5873, 286, 42435, 2938, 286, 262, 4941, 198, 220, 220, 220, 220, 220, 220, 220, 1058, 7783, 25, 20512, 532, 6407, 611, 6737, 287, 428, 20937, 318, 1342, 8157, 621, 262, 4941, 198, 220, 220, 220, 220, 220, 220, 220, 37227, 198, 220, 220, 220, 220, 220, 220, 220, 331, 62, 5420, 796, 1006, 13, 4443, 6582, 14692, 5317, 6377, 1, 4083, 27160, 198, 220, 220, 220, 220, 220, 220, 220, 331, 62, 8158, 796, 2116, 13, 4443, 6582, 14692, 5317, 6377, 1, 4083, 27160, 198, 220, 220, 220, 220, 220, 220, 220, 2116, 13, 5420, 62, 19503, 80, 796, 1006, 13, 11147, 13, 35324, 198, 220, 220, 220, 220, 220, 220, 220, 2116, 13, 5420, 62, 312, 796, 1006, 13, 312, 198, 220, 220, 220, 220, 220, 220, 220, 611, 686, 72, 25, 198, 220, 220, 220, 220, 220, 220, 220, 220, 220, 220, 220, 331, 62, 5420, 796, 331, 62, 5420, 58, 305, 72, 60, 198, 220, 220, 220, 220, 220, 220, 220, 220, 220, 220, 220, 331, 62, 8158, 796, 331, 62, 8158, 58, 305, 72, 60, 198, 220, 220, 220, 220, 220, 220, 220, 1303, 770, 1595, 470, 670, 11, 393, 318, 407, 3573, 48212, 13, 198, 220, 220, 220, 220, 220, 220, 220, 1303, 442, 271, 80, 11, 279, 62, 8367, 796, 442, 271, 421, 533, 7, 198, 220, 220, 220, 220, 220, 220, 220, 1303, 220, 220, 220, 331, 62, 8158, 11, 331, 62, 5420, 198, 220, 220, 220, 220, 220, 220, 220, 1303, 1267, 198, 220, 220, 220, 220, 220, 220, 220, 611, 42435, 318, 6045, 25, 198, 220, 220, 220, 220, 220, 220, 220, 220, 220, 220, 220, 264, 13495, 796, 45941, 13, 19282, 7, 88, 62, 8158, 11, 16488, 28, 15, 8, 1635, 1467, 13, 15, 198, 220, 220, 220, 220, 220, 220, 220, 2073, 25, 198, 220, 220, 220, 220, 220, 220, 220, 220, 220, 220, 220, 264, 13495, 796, 42435, 198, 220, 220, 220, 220, 220, 220, 220, 2938, 796, 45941, 13, 16345, 7, 88, 62, 5420, 11, 16488, 28, 15, 8, 532, 264, 13495, 198, 220, 220, 220, 220, 220, 220, 220, 1441, 45941, 13, 16345, 7, 88, 62, 8158, 11, 16488, 28, 15, 8, 19841, 2938, 628, 220, 220, 220, 825, 41058, 62, 40546, 7, 944, 2599, 198, 220, 220, 220, 220, 220, 220, 220, 37227, 198, 220, 220, 220, 220, 220, 220, 220, 13610, 257, 28114, 306, 1446, 1436, 4743, 12854, 13, 34099, 416, 262, 347, 963, 2163, 11, 3584, 198, 220, 220, 220, 220, 220, 220, 220, 2854, 12, 3083, 340, 2753, 8097, 284, 7110, 510, 5299, 23924, 23824, 13, 198, 220, 220, 220, 220, 220, 220, 220, 1058, 7783, 12854, 25, 1446, 1436, 4743, 2134, 198, 220, 220, 220, 220, 220, 220, 220, 37227, 198, 220, 220, 220, 220, 220, 220, 220, 2420, 796, 366, 33351, 4522, 25, 23884, 27, 1671, 29, 34, 615, 414, 25, 23884, 27, 1671, 29, 7707, 25, 23884, 27, 1671, 29, 13436, 3262, 25, 23884, 27, 1671, 29, 8086, 77, 25, 23884, 1911, 18982, 7, 198, 220, 220, 220, 220, 220, 220, 220, 220, 220, 220, 220, 2116, 13, 312, 11, 198, 220, 220, 220, 220, 220, 220, 220, 220, 220, 220, 220, 2116, 13, 66, 615, 414, 62, 35324, 11, 198, 220, 220, 220, 220, 220, 220, 220, 220, 220, 220, 220, 2116, 13, 7109, 62, 35324, 11, 198, 220, 220, 220, 220, 220, 220, 220, 220, 220, 220, 220, 2116, 13, 19726, 3262, 11, 198, 220, 220, 220, 220, 220, 220, 220, 220, 220, 220, 220, 2116, 13, 66, 615, 414, 62, 41769, 11, 198, 220, 220, 220, 220, 220, 220, 220, 1267, 198, 220, 220, 220, 220, 220, 220, 220, 12854, 796, 467, 13, 3351, 1436, 4743, 7, 198, 220, 220, 220, 220, 220, 220, 220, 220, 220, 220, 220, 2124, 28, 37659, 13, 21602, 10223, 7, 944, 13, 312, 11, 2116, 13, 312, 1343, 352, 11, 18896, 7, 944, 13, 4443, 6582, 14692, 5317, 6377, 8973, 36911, 198, 220, 220, 220, 220, 220, 220, 220, 220, 220, 220, 220, 331, 28, 944, 13, 4443, 6582, 14692, 5317, 6377, 33116, 198, 220, 220, 220, 220, 220, 220, 220, 220, 220, 220, 220, 2420, 28, 5239, 11, 198, 220, 220, 220, 220, 220, 220, 220, 220, 220, 220, 220, 18364, 28, 4895, 8043, 1298, 366, 81, 22296, 7, 3559, 11, 15187, 11, 19782, 16725, 5512, 198, 220, 220, 220, 220, 220, 220, 220, 220, 220, 220, 220, 20599, 10951, 2625, 5239, 1600, 198, 220, 220, 220, 220, 220, 220, 220, 1267, 198, 220, 220, 220, 220, 220, 220, 220, 1441, 12854, 628, 220, 220, 220, 825, 4197, 62, 66, 615, 414, 7, 944, 11, 7110, 28, 17821, 11, 15942, 577, 28, 25101, 2599, 198, 220, 220, 220, 220, 220, 220, 220, 37227, 198, 220, 220, 220, 220, 220, 220, 220, 35006, 257, 4197, 284, 262, 31643, 10958, 13, 36965, 257, 20312, 12822, 31562, 2746, 198, 220, 220, 220, 220, 220, 220, 220, 326, 10356, 4340, 262, 1271, 286, 15830, 10007, 13, 198, 220, 220, 220, 220, 220, 220, 220, 1058, 17143, 7110, 25, 20512, 11986, 1771, 257, 28114, 306, 3785, 318, 925, 198, 220, 220, 220, 220, 220, 220, 220, 1058, 7783, 25, 9104, 25048, 1255, 198, 220, 220, 220, 220, 220, 220, 220, 37227, 198, 220, 220, 220, 220, 220, 220, 220, 331, 796, 2116, 13, 4443, 6582, 14692, 5317, 6377, 1, 4083, 14781, 2616, 22446, 27160, 198, 220, 220, 220, 220, 220, 220, 220, 2124, 796, 2116, 13, 4443, 6582, 14692, 37, 28707, 357, 25983, 16725, 4083, 14781, 2616, 22446, 27160, 198, 220, 220, 220, 220, 220, 220, 220, 2746, 796, 15830, 13, 47, 958, 35389, 31562, 17633, 3419, 198, 220, 220, 220, 220, 220, 220, 220, 1255, 796, 2746, 13, 11147, 62, 24874, 7, 87, 11, 331, 11, 15942, 577, 28, 19011, 577, 8, 198, 220, 220, 220, 220, 220, 220, 220, 2116, 13, 4443, 6582, 14692, 31805, 8973, 796, 1255, 13, 13466, 62, 11147, 198, 220, 220, 220, 220, 220, 220, 220, 2116, 13, 11147, 796, 1255, 198, 220, 220, 220, 220, 220, 220, 220, 2116, 13, 11147, 13, 35324, 796, 2116, 13, 11147, 13, 13466, 62, 27160, 14692, 87, 15, 8973, 198, 220, 220, 220, 220, 220, 220, 220, 611, 7110, 318, 6407, 25, 198, 220, 220, 220, 220, 220, 220, 220, 220, 220, 220, 220, 2336, 796, 467, 13, 11337, 38300, 3419, 198, 220, 220, 220, 220, 220, 220, 220, 220, 220, 220, 220, 2336, 13, 39786, 14692, 87, 22704, 1, 7131, 1, 7839, 8973, 796, 366, 37, 28707, 357, 25983, 16725, 198, 220, 220, 220, 220, 220, 220, 220, 220, 220, 220, 220, 2336, 13, 39786, 14692, 87, 22704, 1, 7131, 1, 42298, 18982, 8973, 796, 27071, 17, 69, 1, 198, 220, 220, 220, 220, 220, 220, 220, 220, 220, 220, 220, 2336, 13, 2860, 62, 1416, 1436, 7, 87, 28, 87, 11, 331, 28, 88, 11, 1438, 2625, 31310, 8520, 4943, 198, 220, 220, 220, 220, 220, 220, 220, 220, 220, 220, 220, 2336, 13, 2860, 62, 1416, 1436, 7, 87, 28, 87, 11, 331, 28, 20274, 13, 13466, 62, 11147, 11, 1438, 2625, 31805, 4943, 198, 220, 220, 220, 220, 220, 220, 220, 220, 220, 220, 220, 1441, 1255, 11, 2336, 198, 220, 220, 220, 220, 220, 220, 220, 2073, 25, 198, 220, 220, 220, 220, 220, 220, 220, 220, 220, 220, 220, 1441, 1255, 628, 198, 4299, 21136, 62, 35836, 7, 7753, 3642, 658, 2599, 198, 220, 220, 220, 37227, 198, 220, 220, 220, 15553, 329, 37895, 262, 376, 2389, 1366, 422, 281, 19446, 9367, 13, 383, 1366, 198, 220, 220, 220, 318, 4504, 355, 257, 22155, 11, 543, 460, 307, 973, 284, 41216, 257, 198, 220, 220, 220, 20937, 2134, 13, 198, 220, 220, 220, 1058, 17143, 2393, 3642, 658, 25, 1351, 286, 3951, 422, 281, 376, 2389, 2393, 198, 220, 220, 220, 1058, 7783, 25, 8633, 7268, 44267, 1366, 422, 376, 2389, 198, 220, 220, 220, 37227, 198, 220, 220, 220, 1366, 796, 19779, 70, 1386, 1298, 8633, 3419, 92, 198, 220, 220, 220, 1303, 376, 2389, 40364, 198, 220, 220, 220, 49909, 62, 260, 25636, 796, 302, 13, 5589, 576, 7, 81, 1, 61, 69, 312, 59, 67, 9, 1600, 302, 13, 44, 8, 198, 220, 220, 220, 1303, 797, 25636, 284, 1064, 3623, 9619, 198, 220, 220, 220, 3623, 62, 260, 25636, 796, 302, 13, 5589, 576, 7, 81, 1, 61, 2, 39699, 3467, 67, 1438, 1600, 302, 13, 44, 8, 198, 220, 220, 220, 5202, 62, 260, 25636, 796, 302, 13, 5589, 576, 7, 81, 1, 61, 2, 39699, 3467, 67, 5202, 1600, 302, 13, 44, 8, 198, 220, 220, 220, 1303, 797, 25636, 284, 4886, 543, 6518, 318, 900, 284, 262, 17655, 198, 220, 220, 220, 30736, 62, 260, 25636, 796, 302, 13, 5589, 576, 7, 81, 1, 61, 2, 47, 9615, 442, 3467, 67, 1438, 59, 82, 9, 9697, 1600, 302, 13, 44, 8, 198, 220, 220, 220, 30736, 62, 17620, 796, 6045, 198, 220, 220, 220, 329, 6376, 11, 1627, 287, 27056, 378, 7, 7753, 3642, 658, 2599, 198, 220, 220, 220, 220, 220, 220, 220, 611, 25113, 33351, 1, 287, 1627, 25, 198, 220, 220, 220, 220, 220, 220, 220, 220, 220, 220, 220, 6626, 62, 1370, 796, 1627, 13, 35312, 3419, 198, 220, 220, 220, 220, 220, 220, 220, 220, 220, 220, 220, 1366, 14692, 312, 8973, 796, 493, 7, 35312, 62, 1370, 58, 16, 12962, 198, 220, 220, 220, 220, 220, 220, 220, 220, 220, 220, 220, 1949, 25, 198, 220, 220, 220, 220, 220, 220, 220, 220, 220, 220, 220, 220, 220, 220, 220, 1366, 14692, 30243, 8973, 796, 6626, 62, 1370, 58, 17, 60, 198, 220, 220, 220, 220, 220, 220, 220, 220, 220, 220, 220, 2845, 12901, 12331, 25, 198, 220, 220, 220, 220, 220, 220, 220, 220, 220, 220, 220, 220, 220, 220, 220, 1366, 14692, 30243, 8973, 796, 366, 9792, 16, 1, 198, 220, 220, 220, 220, 220, 220, 220, 611, 25113, 2964, 1350, 2030, 80, 1, 287, 1627, 25, 198, 220, 220, 220, 220, 220, 220, 220, 220, 220, 220, 220, 1366, 14692, 66, 615, 414, 62, 35324, 8973, 796, 12178, 7, 1370, 13, 35312, 3419, 58, 17, 12962, 198, 220, 220, 220, 220, 220, 220, 220, 611, 25113, 2484, 1747, 1, 287, 1627, 25, 198, 220, 220, 220, 220, 220, 220, 220, 220, 220, 220, 220, 1366, 14692, 20910, 8973, 796, 493, 7, 1370, 13, 35312, 3419, 58, 12, 16, 12962, 198, 220, 220, 220, 220, 220, 220, 220, 611, 25113, 10430, 1, 287, 1627, 25, 198, 220, 220, 220, 220, 220, 220, 220, 220, 220, 220, 220, 10283, 62, 83, 853, 1039, 796, 14631, 2, 10430, 1600, 37082, 83, 1600, 37082, 77, 8973, 198, 220, 220, 220, 220, 220, 220, 220, 220, 220, 220, 220, 1366, 14692, 4475, 8973, 796, 4818, 8079, 13, 19608, 8079, 13, 2536, 457, 524, 7, 198, 220, 220, 220, 220, 220, 220, 220, 220, 220, 220, 220, 220, 220, 220, 220, 302, 13, 7266, 7203, 91, 1911, 22179, 7, 36311, 62, 83, 853, 1039, 828, 366, 1600, 1627, 828, 36521, 64, 4064, 65, 4064, 67, 4064, 39, 25, 4, 44, 25, 4, 50, 4064, 56, 1, 198, 220, 220, 220, 220, 220, 220, 220, 220, 220, 220, 220, 1267, 198, 220, 220, 220, 220, 220, 220, 220, 611, 25113, 34, 615, 414, 45444, 1, 287, 1627, 25, 198, 220, 220, 220, 220, 220, 220, 220, 220, 220, 220, 220, 1366, 14692, 66, 615, 414, 62, 37764, 496, 8973, 796, 493, 7, 1370, 13, 35312, 3419, 58, 17, 12962, 198, 220, 220, 220, 220, 220, 220, 220, 611, 25113, 8086, 268, 2288, 1, 287, 1627, 25, 198, 220, 220, 220, 220, 220, 220, 220, 220, 220, 220, 220, 1366, 14692, 66, 615, 414, 62, 41769, 8973, 796, 493, 7, 1370, 13, 35312, 3419, 58, 16, 12962, 198, 220, 220, 220, 220, 220, 220, 220, 611, 25113, 7707, 2030, 80, 1, 287, 1627, 25, 198, 220, 220, 220, 220, 220, 220, 220, 220, 220, 220, 220, 1366, 14692, 7109, 62, 35324, 8973, 796, 12178, 7, 1370, 13, 35312, 3419, 58, 17, 12962, 198, 220, 220, 220, 220, 220, 220, 220, 611, 25113, 7707, 1176, 1, 287, 1627, 25, 198, 220, 220, 220, 220, 220, 220, 220, 220, 220, 220, 220, 1366, 14692, 7109, 62, 6477, 8973, 796, 493, 7, 1370, 13, 35312, 3419, 58, 17, 12962, 198, 220, 220, 220, 220, 220, 220, 220, 611, 25113, 37, 2389, 31050, 1, 287, 1627, 25, 198, 220, 220, 220, 220, 220, 220, 220, 220, 220, 220, 220, 1366, 14692, 69, 312, 62, 2777, 4092, 8973, 796, 12178, 7, 260, 13, 19796, 439, 7, 81, 1, 59, 2934, 58, 10, 12, 60, 30, 59, 67, 59, 67, 1600, 1627, 38381, 15, 12962, 198, 220, 220, 220, 220, 220, 220, 220, 611, 25113, 37, 2389, 2173, 1, 287, 1627, 25, 198, 220, 220, 220, 220, 220, 220, 220, 220, 220, 220, 220, 1366, 14692, 69, 312, 62, 13033, 8973, 796, 493, 7, 1370, 13, 35312, 3419, 58, 12, 16, 12962, 198, 220, 220, 220, 220, 220, 220, 220, 1303, 3497, 262, 1438, 286, 262, 3623, 198, 220, 220, 220, 220, 220, 220, 220, 611, 3623, 62, 260, 25636, 13, 15699, 7, 1370, 2599, 198, 220, 220, 220, 220, 220, 220, 220, 220, 220, 220, 220, 6626, 62, 1370, 796, 1627, 13, 35312, 3419, 198, 220, 220, 220, 220, 220, 220, 220, 220, 220, 220, 220, 1303, 5514, 11393, 32096, 611, 262, 6518, 318, 973, 198, 220, 220, 220, 220, 220, 220, 220, 220, 220, 220, 220, 3623, 62, 9630, 796, 493, 7, 35312, 62, 1370, 58, 16, 12962, 198, 220, 220, 220, 220, 220, 220, 220, 220, 220, 220, 220, 1949, 25, 198, 220, 220, 220, 220, 220, 220, 220, 220, 220, 220, 220, 220, 220, 220, 220, 1366, 14692, 70, 1386, 1, 7131, 22649, 62, 9630, 60, 796, 19779, 22649, 1298, 366, 27071, 22179, 7, 35312, 62, 1370, 58, 18, 25, 12962, 92, 198, 220, 220, 220, 220, 220, 220, 220, 220, 220, 220, 220, 2845, 12901, 12331, 25, 198, 220, 220, 220, 220, 220, 220, 220, 220, 220, 220, 220, 220, 220, 220, 220, 1366, 14692, 70, 1386, 1, 7131, 22649, 62, 9630, 60, 796, 19779, 22649, 1298, 13538, 92, 198, 220, 220, 220, 220, 220, 220, 220, 1303, 3497, 262, 5202, 2494, 329, 6518, 198, 220, 220, 220, 220, 220, 220, 220, 611, 5202, 62, 260, 25636, 13, 15699, 7, 1370, 2599, 198, 220, 220, 220, 220, 220, 220, 220, 220, 220, 220, 220, 6626, 62, 1370, 796, 1627, 13, 35312, 3419, 198, 220, 220, 220, 220, 220, 220, 220, 220, 220, 220, 220, 3623, 62, 9630, 796, 493, 7, 35312, 62, 1370, 58, 16, 12962, 198, 220, 220, 220, 220, 220, 220, 220, 220, 220, 220, 220, 1366, 14692, 70, 1386, 1, 7131, 22649, 62, 9630, 7131, 1, 11125, 8973, 796, 12178, 7, 35312, 62, 1370, 58, 18, 12962, 198, 220, 220, 220, 220, 220, 220, 220, 611, 25113, 13436, 3262, 9343, 1, 287, 1627, 25, 198, 220, 220, 220, 220, 220, 220, 220, 220, 220, 220, 220, 1366, 14692, 19726, 3262, 8973, 796, 20512, 7, 600, 7, 1370, 13, 35312, 3419, 58, 17, 60, 4008, 198, 220, 220, 220, 220, 220, 220, 220, 1303, 9938, 262, 6518, 262, 17655, 318, 900, 284, 290, 17632, 257, 40364, 198, 220, 220, 220, 220, 220, 220, 220, 1303, 284, 804, 329, 262, 6518, 198, 220, 220, 220, 220, 220, 220, 220, 611, 30736, 62, 260, 25636, 13, 15699, 7, 1370, 2599, 198, 220, 220, 220, 220, 220, 220, 220, 220, 220, 220, 220, 30736, 62, 9630, 796, 1627, 13, 35312, 3419, 58, 17, 60, 198, 220, 220, 220, 220, 220, 220, 220, 220, 220, 220, 220, 30736, 62, 17620, 796, 302, 13, 5589, 576, 7, 81, 1, 61, 2, 47, 9615, 442, 23884, 9343, 1911, 18982, 7, 17896, 62, 9630, 828, 302, 13, 44, 8, 198, 220, 220, 220, 220, 220, 220, 220, 1303, 4874, 262, 17655, 6518, 6376, 318, 1900, 11, 923, 10342, 329, 340, 198, 220, 220, 220, 220, 220, 220, 220, 611, 30736, 62, 17620, 25, 198, 220, 220, 220, 220, 220, 220, 220, 220, 220, 220, 220, 611, 30736, 62, 17620, 13, 15699, 7, 1370, 2599, 198, 220, 220, 220, 220, 220, 220, 220, 220, 220, 220, 220, 220, 220, 220, 220, 1366, 14692, 6381, 10136, 8973, 796, 20512, 7, 600, 7, 1370, 13, 35312, 3419, 58, 12, 16, 60, 4008, 198, 220, 220, 220, 220, 220, 220, 220, 1303, 9938, 618, 262, 376, 2389, 3951, 923, 26324, 510, 198, 220, 220, 220, 220, 220, 220, 220, 611, 49909, 62, 260, 25636, 13, 15699, 7, 1370, 2599, 198, 220, 220, 220, 220, 220, 220, 220, 220, 220, 220, 220, 49909, 796, 2393, 3642, 658, 58, 9630, 1343, 352, 1058, 60, 198, 220, 220, 220, 220, 220, 220, 220, 220, 220, 220, 220, 49909, 796, 685, 22468, 7, 8367, 8, 329, 1988, 287, 49909, 60, 198, 220, 220, 220, 220, 220, 220, 220, 220, 220, 220, 220, 1366, 14692, 69, 312, 8973, 796, 45941, 13, 18747, 7, 69, 312, 8, 198, 220, 220, 220, 1441, 1366, 628, 198, 4299, 1620, 62, 487, 83, 7, 69, 312, 11, 31050, 11, 923, 28, 15, 11, 2245, 10779, 16, 11, 4324, 2625, 3524, 7718, 1, 2599, 198, 220, 220, 220, 37227, 198, 220, 220, 220, 35006, 281, 376, 9792, 319, 281, 376, 2389, 284, 651, 262, 8373, 7386, 10958, 13, 198, 220, 220, 220, 1439, 286, 262, 7159, 389, 11902, 11, 290, 2148, 1630, 625, 703, 262, 376, 9792, 318, 6157, 11, 355, 880, 355, 1281, 12, 36948, 198, 220, 220, 220, 10007, 588, 4324, 5499, 290, 6632, 12, 39231, 13, 628, 220, 220, 220, 770, 318, 1912, 319, 262, 376, 9792, 2438, 416, 14316, 32379, 21048, 11, 351, 19008, 284, 4197, 428, 4818, 330, 31172, 13, 628, 220, 220, 220, 40117, 198, 220, 220, 220, 24200, 438, 198, 220, 220, 220, 49909, 532, 399, 32152, 352, 35, 7177, 198, 220, 220, 220, 220, 220, 220, 220, 15690, 4769, 262, 3815, 286, 262, 376, 2389, 198, 220, 220, 220, 31050, 532, 12178, 198, 220, 220, 220, 220, 220, 220, 220, 3862, 31050, 1022, 376, 2389, 2173, 287, 4580, 43012, 198, 220, 220, 220, 923, 532, 493, 11, 11902, 198, 220, 220, 220, 220, 220, 220, 220, 17962, 6376, 329, 262, 376, 2389, 7177, 284, 1620, 262, 376, 9792, 198, 220, 220, 220, 2245, 532, 493, 11, 11902, 198, 220, 220, 220, 220, 220, 220, 220, 5268, 6376, 329, 262, 376, 2389, 7177, 284, 1620, 262, 376, 9792, 198, 220, 220, 220, 1976, 79, 69, 532, 493, 11, 11902, 198, 220, 220, 220, 220, 220, 220, 220, 15744, 262, 376, 2389, 351, 1976, 27498, 284, 299, 400, 16936, 1176, 286, 362, 198, 220, 220, 220, 4324, 532, 965, 198, 220, 220, 220, 220, 220, 220, 220, 18291, 1958, 262, 4324, 2163, 973, 284, 1429, 262, 376, 2389, 13, 2896, 13185, 284, 3091, 7718, 11, 543, 318, 6840, 645, 25431, 13, 198, 220, 220, 220, 220, 220, 220, 220, 383, 3891, 286, 262, 4324, 5499, 1695, 460, 307, 1043, 379, 25, 198, 220, 220, 220, 220, 220, 220, 220, 3740, 1378, 31628, 13, 1416, 541, 88, 13, 2398, 14, 15390, 14, 1416, 541, 88, 14, 35790, 14, 12683, 282, 13, 28457, 13, 6494, 628, 220, 220, 220, 16409, 198, 220, 220, 220, 35656, 198, 220, 220, 220, 37227, 198, 220, 220, 220, 49909, 796, 45941, 13, 30073, 7, 69, 312, 8, 198, 220, 220, 220, 611, 4324, 318, 407, 6045, 290, 4324, 287, 599, 82, 328, 13, 28457, 13, 834, 439, 834, 25, 198, 220, 220, 220, 220, 220, 220, 220, 4324, 62, 69, 796, 599, 82, 328, 13, 28457, 13, 1136, 62, 17497, 7, 17497, 11, 49909, 13, 7857, 8, 198, 220, 220, 220, 220, 220, 220, 220, 49909, 1635, 28, 4324, 62, 69, 198, 220, 220, 220, 2073, 25, 198, 220, 220, 220, 220, 220, 220, 220, 5298, 35528, 7203, 22882, 1431, 4324, 2163, 318, 407, 9177, 287, 10286, 20519, 2474, 8, 198, 220, 220, 220, 1303, 5345, 3815, 284, 6632, 510, 284, 3599, 6376, 198, 220, 220, 220, 49909, 58, 25, 9688, 60, 796, 657, 13, 15, 198, 220, 220, 220, 611, 2245, 1279, 657, 25, 198, 220, 220, 220, 220, 220, 220, 220, 1303, 1002, 356, 821, 1262, 4633, 39199, 198, 220, 220, 220, 220, 220, 220, 220, 49909, 58, 69, 312, 13, 7857, 1343, 2245, 1058, 60, 796, 657, 13, 15, 198, 220, 220, 220, 2073, 25, 198, 220, 220, 220, 220, 220, 220, 220, 1303, 15323, 11, 6376, 351, 257, 3967, 1271, 198, 220, 220, 220, 220, 220, 220, 220, 49909, 58, 11338, 47715, 796, 657, 13, 15, 198, 220, 220, 220, 1303, 35006, 262, 376, 9792, 198, 220, 220, 220, 277, 701, 796, 45941, 13, 487, 83, 13, 81, 487, 83, 7, 69, 312, 8, 198, 220, 220, 220, 1100, 62, 13664, 796, 18896, 7, 69, 312, 8, 3373, 362, 1343, 352, 198, 220, 220, 220, 47764, 796, 352, 13, 15, 1220, 49909, 13, 7857, 1220, 31050, 198, 220, 220, 220, 1303, 2980, 378, 262, 8373, 7177, 198, 220, 220, 220, 8373, 796, 45941, 13, 21602, 10223, 7, 15, 13, 15, 11, 2116, 13, 25677, 14692, 1589, 3903, 8973, 1635, 47764, 11, 1100, 62, 13664, 8, 198, 220, 220, 220, 8373, 15853, 2116, 13, 25677, 14692, 1676, 1350, 62, 19503, 80, 8973, 198, 220, 220, 220, 277, 701, 58, 7, 35324, 18189, 277, 62, 9806, 8, 1222, 357, 35324, 19841, 277, 62, 1084, 15437, 796, 657, 13, 15, 198, 220, 220, 220, 277, 701, 1635, 28, 8576, 13, 15, 198, 220, 220, 220, 1441, 8373, 11, 277, 701, 628, 198, 4299, 49909, 17, 487, 83, 7, 69, 312, 11, 2494, 11, 19998, 11, 12429, 46265, 22046, 2599, 198, 220, 220, 220, 37227, 198, 220, 220, 220, 10854, 281, 376, 2389, 416, 9489, 281, 376, 9792, 284, 7800, 262, 8373, 7386, 198, 220, 220, 220, 1321, 13, 31767, 22046, 389, 3804, 355, 3224, 7587, 3689, 11, 198, 220, 220, 220, 290, 389, 9177, 355, 617, 1339, 6299, 284, 4155, 262, 6460, 198, 220, 220, 220, 389, 4938, 357, 68, 13, 70, 13, 17216, 82, 284, 19232, 2494, 11, 3503, 2014, 628, 220, 220, 220, 1058, 17143, 49909, 25, 45941, 13, 18747, 11188, 284, 262, 376, 2389, 12245, 198, 220, 220, 220, 1058, 17143, 2494, 25, 19232, 2494, 287, 26109, 198, 220, 220, 220, 1058, 17143, 19998, 25, 45941, 13, 18747, 11188, 284, 262, 8373, 41701, 198, 220, 220, 220, 1058, 17143, 479, 86, 22046, 25, 6737, 7587, 3689, 25, 198, 220, 220, 220, 220, 220, 220, 220, 220, 220, 220, 220, 220, 220, 220, 220, 220, 220, 220, 220, 5711, 532, 16119, 262, 376, 2389, 7587, 416, 4634, 262, 923, 198, 220, 220, 220, 220, 220, 220, 220, 220, 220, 220, 220, 220, 220, 220, 220, 220, 220, 220, 220, 220, 220, 220, 220, 220, 220, 220, 220, 286, 262, 376, 2389, 284, 6632, 198, 220, 220, 220, 220, 220, 220, 220, 220, 220, 220, 220, 220, 220, 220, 220, 220, 220, 220, 220, 1976, 263, 404, 324, 532, 309, 48549, 1771, 393, 407, 262, 1271, 286, 35846, 198, 220, 220, 220, 220, 220, 220, 220, 220, 220, 220, 220, 220, 220, 220, 220, 220, 220, 220, 220, 220, 220, 220, 220, 220, 220, 220, 220, 220, 220, 2173, 318, 15229, 284, 651, 32455, 2440, 198, 220, 220, 220, 220, 220, 220, 220, 220, 220, 220, 220, 220, 220, 220, 220, 220, 220, 220, 220, 220, 220, 220, 220, 220, 220, 220, 220, 220, 220, 6323, 287, 262, 376, 9792, 198, 220, 220, 220, 220, 220, 220, 220, 220, 220, 220, 220, 220, 220, 220, 220, 220, 220, 220, 220, 4324, 532, 26386, 4324, 5499, 2810, 416, 4600, 1416, 541, 88, 13, 12683, 282, 63, 198, 220, 220, 220, 220, 220, 220, 220, 220, 220, 220, 220, 220, 220, 220, 220, 220, 220, 220, 220, 1033, 532, 18291, 6945, 281, 39682, 8106, 198, 220, 220, 220, 220, 220, 220, 220, 220, 220, 220, 220, 220, 220, 220, 220, 220, 220, 220, 220, 8106, 532, 362, 12, 83, 29291, 31577, 262, 8373, 2005, 8210, 329, 257, 198, 220, 220, 220, 220, 220, 220, 220, 220, 220, 220, 220, 220, 220, 220, 220, 220, 220, 220, 220, 220, 220, 220, 220, 220, 220, 220, 220, 220, 4097, 1208, 8106, 198, 220, 220, 220, 1058, 7783, 25, 2030, 80, 62, 7568, 532, 19798, 292, 1366, 14535, 351, 262, 376, 9792, 10958, 198, 220, 220, 220, 37227, 198, 220, 220, 220, 1303, 17220, 6257, 198, 220, 220, 220, 649, 62, 69, 312, 796, 49909, 532, 45941, 13, 23913, 7, 69, 312, 8, 198, 220, 220, 220, 611, 366, 40850, 1, 287, 479, 86, 22046, 25, 198, 220, 220, 220, 220, 220, 220, 220, 5711, 796, 493, 7, 46265, 22046, 14692, 40850, 8973, 1220, 357, 16, 13, 15, 1220, 2494, 8, 1220, 352, 68, 21, 8, 198, 220, 220, 220, 220, 220, 220, 220, 649, 62, 69, 312, 58, 25, 40850, 60, 796, 657, 13, 15, 198, 220, 220, 220, 1303, 12169, 12, 15636, 262, 376, 2389, 198, 220, 220, 220, 611, 366, 9107, 404, 324, 1, 287, 479, 86, 22046, 25, 198, 220, 220, 220, 220, 220, 220, 220, 611, 479, 86, 22046, 14692, 9107, 404, 324, 8973, 318, 6407, 25, 198, 220, 220, 220, 220, 220, 220, 220, 220, 220, 220, 220, 1303, 15744, 262, 376, 2389, 351, 1976, 27498, 284, 651, 2440, 6323, 198, 220, 220, 220, 220, 220, 220, 220, 220, 220, 220, 220, 49909, 796, 45941, 13, 33295, 7, 3605, 62, 69, 312, 11, 45941, 13, 9107, 418, 7, 11925, 7, 3605, 62, 69, 312, 22305, 198, 220, 220, 220, 220, 220, 220, 220, 220, 220, 220, 220, 1303, 4619, 356, 1053, 44582, 351, 1976, 27498, 11, 356, 1183, 423, 284, 4296, 262, 198, 220, 220, 220, 220, 220, 220, 220, 220, 220, 220, 220, 1303, 8373, 7177, 198, 220, 220, 220, 220, 220, 220, 220, 220, 220, 220, 220, 19998, 796, 599, 82, 328, 13, 411, 1403, 7, 69, 8897, 3976, 11, 18896, 7, 69, 8897, 3976, 8, 1635, 362, 8, 198, 220, 220, 220, 1303, 27967, 257, 4324, 2163, 284, 262, 376, 2389, 198, 220, 220, 220, 611, 366, 17497, 1, 287, 479, 86, 22046, 25, 198, 220, 220, 220, 220, 220, 220, 220, 611, 479, 86, 22046, 14692, 17497, 8973, 287, 599, 82, 328, 13, 28457, 13, 834, 439, 834, 25, 198, 220, 220, 220, 220, 220, 220, 220, 220, 220, 220, 220, 649, 62, 69, 312, 1635, 28, 599, 82, 328, 13, 1136, 62, 17497, 7, 46265, 22046, 14692, 17497, 33116, 649, 62, 69, 312, 13, 7857, 8, 198, 220, 220, 220, 1303, 27967, 281, 39682, 8106, 319, 262, 376, 2389, 198, 220, 220, 220, 611, 366, 11201, 1, 287, 479, 86, 22046, 25, 198, 220, 220, 220, 220, 220, 220, 220, 611, 479, 86, 22046, 14692, 11201, 8973, 1875, 657, 13, 15, 25, 198, 220, 220, 220, 220, 220, 220, 220, 220, 220, 220, 220, 649, 62, 69, 312, 1635, 28, 599, 82, 328, 13, 11201, 35470, 7, 11925, 7, 3605, 62, 69, 312, 828, 256, 559, 28, 46265, 22046, 14692, 11201, 8973, 8, 198, 220, 220, 220, 1303, 27967, 257, 4097, 6603, 8106, 319, 262, 376, 2389, 198, 220, 220, 220, 611, 5855, 24455, 1, 287, 479, 86, 22046, 8, 290, 357, 11925, 7, 46265, 22046, 14692, 24455, 8973, 8, 6624, 362, 2599, 198, 220, 220, 220, 220, 220, 220, 220, 1877, 11, 1029, 796, 23243, 7, 46265, 22046, 14692, 24455, 8973, 8, 198, 220, 220, 220, 220, 220, 220, 220, 611, 1877, 1279, 1029, 25, 198, 220, 220, 220, 220, 220, 220, 220, 220, 220, 220, 220, 649, 62, 69, 312, 796, 4174, 62, 4360, 353, 62, 24455, 7, 3605, 62, 69, 312, 11, 1877, 11, 1029, 11, 2494, 8, 198, 220, 220, 220, 1303, 35006, 262, 376, 9792, 198, 220, 220, 220, 277, 701, 796, 45941, 13, 487, 83, 13, 81, 487, 83, 7, 3605, 62, 69, 312, 8, 198, 220, 220, 220, 1303, 3497, 262, 1103, 636, 286, 262, 376, 9792, 11, 290, 691, 262, 1729, 12, 646, 489, 3474, 1735, 198, 220, 220, 220, 1103, 62, 487, 83, 796, 45941, 13, 8937, 7, 487, 83, 58, 25, 493, 7, 11925, 7, 3605, 62, 69, 312, 8, 1220, 362, 8, 12962, 1220, 18896, 7, 3605, 62, 69, 312, 8, 1635, 352, 68, 18, 198, 220, 220, 220, 19998, 796, 599, 82, 328, 13, 411, 1403, 7, 69, 8897, 3976, 11, 1103, 62, 487, 83, 13, 7857, 8, 198, 220, 220, 220, 1303, 1114, 617, 1738, 11, 581, 321, 11347, 23742, 510, 262, 8373, 16216, 986, 198, 220, 220, 220, 1103, 62, 487, 83, 796, 1103, 62, 487, 83, 58, 37659, 13, 22046, 419, 7, 69, 8897, 3976, 15437, 198, 220, 220, 220, 19998, 796, 45941, 13, 30619, 7, 69, 8897, 3976, 8, 198, 220, 220, 220, 1303, 15717, 656, 257, 19798, 292, 1366, 14535, 198, 220, 220, 220, 2030, 80, 62, 7568, 796, 279, 67, 13, 6601, 19778, 7, 4895, 37, 28707, 357, 25983, 8, 1298, 19998, 11, 366, 5317, 6377, 1298, 1103, 62, 487, 83, 30072, 198, 220, 220, 220, 1441, 2030, 80, 62, 7568, 628, 198, 4299, 9215, 62, 3903, 6603, 7, 9319, 11, 1029, 11, 2494, 11, 1502, 28, 16, 2599, 198, 220, 220, 220, 37227, 198, 220, 220, 220, 220, 220, 220, 220, 317, 9518, 2196, 286, 262, 18971, 9268, 4097, 6603, 8106, 3417, 994, 11, 198, 220, 220, 220, 220, 220, 220, 220, 16573, 329, 779, 351, 262, 376, 2389, 6737, 13, 198, 220, 220, 220, 220, 220, 220, 220, 2638, 1378, 1416, 541, 88, 12, 27916, 2070, 13, 961, 83, 704, 420, 82, 13, 952, 14, 23814, 14, 1537, 353, 9268, 31407, 6603, 13, 6494, 198, 220, 220, 220, 220, 220, 220, 220, 383, 7159, 389, 25, 628, 220, 220, 220, 220, 220, 220, 220, 1058, 17143, 1877, 383, 1877, 8373, 2005, 12, 2364, 11, 1813, 287, 37597, 13, 198, 220, 220, 220, 220, 220, 220, 220, 1058, 17143, 1029, 383, 1029, 8373, 2005, 12, 2364, 11, 1813, 287, 37597, 13, 198, 220, 220, 220, 220, 220, 220, 220, 1058, 17143, 2494, 383, 19232, 2494, 11, 1813, 287, 26109, 13, 3574, 262, 376, 47954, 11, 428, 1724, 326, 198, 220, 220, 220, 220, 220, 220, 220, 220, 220, 220, 220, 220, 220, 220, 220, 220, 220, 220, 220, 262, 34062, 286, 262, 376, 2389, 31050, 318, 973, 13, 198, 220, 220, 220, 220, 220, 220, 220, 1058, 7783, 4097, 6603, 4324, 198, 220, 220, 220, 37227, 198, 220, 220, 220, 1303, 27131, 378, 262, 17735, 30062, 8373, 198, 220, 220, 220, 299, 88, 80, 796, 657, 13, 20, 1635, 357, 4873, 1220, 357, 17, 13, 15, 1635, 45941, 13, 14415, 4008, 198, 220, 220, 220, 1877, 796, 357, 9319, 1635, 352, 68, 18, 8, 1220, 299, 88, 80, 198, 220, 220, 220, 1029, 796, 357, 8929, 1635, 352, 68, 18, 8, 1220, 299, 88, 80, 198, 220, 220, 220, 611, 1029, 1875, 352, 13, 15, 25, 198, 220, 220, 220, 220, 220, 220, 220, 5298, 35528, 7203, 11922, 8373, 2005, 12, 2364, 21695, 262, 17735, 30062, 8373, 19570, 198, 220, 220, 220, 275, 11, 257, 796, 599, 82, 328, 13, 4360, 353, 7, 2875, 11, 685, 9319, 11, 1029, 4357, 275, 4906, 2625, 3903, 1600, 15075, 28, 25101, 8, 198, 220, 220, 220, 1441, 275, 11, 257, 628, 198, 4299, 4174, 62, 4360, 353, 62, 24455, 7, 7890, 11, 1877, 11, 1029, 11, 2494, 11, 1502, 28, 16, 2599, 198, 220, 220, 220, 37227, 198, 220, 220, 220, 220, 220, 220, 220, 317, 9518, 18971, 9268, 4097, 6603, 8106, 11, 16573, 422, 262, 1446, 541, 88, 4255, 2070, 13, 628, 220, 220, 220, 220, 220, 220, 220, 383, 4578, 1366, 9416, 262, 376, 2389, 11, 543, 788, 3544, 262, 629, 541, 88, 6737, 198, 220, 220, 220, 220, 220, 220, 220, 7587, 2163, 284, 4174, 262, 4875, 8106, 11, 290, 5860, 262, 29083, 198, 220, 220, 220, 220, 220, 220, 220, 376, 2389, 13, 628, 220, 220, 220, 220, 220, 220, 220, 4091, 262, 4600, 4360, 353, 62, 3903, 6603, 63, 2163, 329, 3224, 7159, 13, 198, 220, 220, 220, 37227, 198, 220, 220, 220, 275, 11, 257, 796, 9215, 62, 3903, 6603, 7, 9319, 11, 1029, 11, 2494, 11, 1502, 28, 2875, 8, 198, 220, 220, 220, 331, 796, 599, 82, 328, 13, 1652, 346, 353, 7, 65, 11, 257, 11, 1366, 8, 198, 220, 220, 220, 1441, 331, 628, 198, 198, 4299, 7716, 62, 701, 65, 62, 1370, 7, 35324, 11, 6934, 11, 12429, 46265, 22046, 2599, 198, 220, 220, 220, 37227, 15553, 326, 18616, 281, 19446, 33, 2393, 329, 257, 1351, 286, 198, 220, 220, 220, 220, 220, 220, 220, 19998, 11, 5556, 17851, 1634, 5254, 13, 628, 220, 220, 220, 220, 220, 220, 220, 479, 86, 22046, 389, 3804, 355, 3224, 3689, 329, 262, 10117, 65, 198, 220, 220, 220, 220, 220, 220, 220, 15458, 13, 7383, 10879, 389, 25, 628, 220, 220, 220, 220, 220, 220, 220, 19972, 25, 20512, 198, 220, 220, 220, 220, 220, 220, 220, 19550, 2305, 25, 12178, 198, 220, 220, 220, 220, 220, 220, 220, 31919, 25, 493, 198, 220, 220, 220, 220, 220, 220, 220, 1341, 10257, 1726, 25, 20512, 198, 220, 220, 220, 220, 220, 220, 220, 1553, 19503, 80, 25, 12178, 198, 220, 220, 220, 220, 220, 220, 220, 1553, 6477, 25, 493, 198, 220, 220, 220, 220, 220, 220, 220, 2386, 628, 220, 220, 220, 220, 220, 220, 220, 10007, 25, 198, 220, 220, 220, 220, 220, 220, 220, 220, 24305, 198, 220, 220, 220, 220, 220, 220, 220, 1058, 17143, 8373, 25, 12178, 329, 8373, 287, 19805, 198, 220, 220, 220, 220, 220, 220, 220, 1058, 17143, 6934, 25, 493, 1271, 286, 6934, 284, 19386, 329, 628, 220, 220, 220, 220, 220, 220, 220, 5860, 25, 198, 220, 220, 220, 220, 220, 220, 220, 220, 24305, 198, 220, 220, 220, 220, 220, 220, 220, 1058, 7783, 10117, 65, 1370, 25, 965, 198, 220, 220, 220, 37227, 198, 220, 220, 220, 1627, 796, 366, 701, 76, 29164, 25, 13, 19, 69, 92, 6934, 29164, 92, 1911, 18982, 7, 35324, 11, 6934, 8, 198, 220, 220, 220, 329, 1994, 11, 1988, 287, 479, 86, 22046, 13, 23814, 33529, 198, 220, 220, 220, 220, 220, 220, 220, 1627, 15853, 366, 23884, 29164, 92, 1911, 18982, 7, 2539, 11, 1988, 8, 198, 220, 220, 220, 1627, 15853, 37082, 77, 1, 198, 220, 220, 220, 1441, 1627, 628, 198, 4299, 497, 84, 62, 66, 47467, 1096, 62, 69, 8897, 3976, 7, 69, 8897, 3976, 11, 17509, 871, 28, 14202, 11, 299, 20910, 28, 1120, 11, 12429, 46265, 22046, 2599, 198, 220, 220, 220, 37227, 198, 220, 220, 220, 220, 220, 220, 220, 371, 28399, 284, 7716, 281, 19446, 33, 15458, 2393, 329, 9489, 257, 2168, 286, 5254, 198, 220, 220, 220, 220, 220, 220, 220, 319, 19998, 13, 198, 220, 220, 220, 37227, 198, 220, 220, 220, 10117, 65, 62, 8841, 796, 13538, 198, 220, 220, 220, 611, 17509, 871, 25, 198, 220, 220, 220, 220, 220, 220, 220, 2593, 62, 600, 796, 17509, 871, 1220, 45941, 13, 9806, 7, 600, 641, 871, 8, 198, 220, 220, 220, 220, 220, 220, 220, 2823, 9127, 82, 796, 45941, 13, 744, 7, 77, 20910, 1220, 2593, 62, 600, 737, 459, 2981, 7, 600, 8, 198, 220, 220, 220, 2073, 25, 198, 220, 220, 220, 220, 220, 220, 220, 2823, 9127, 82, 796, 45941, 13, 12853, 7, 11925, 7, 69, 8897, 3976, 828, 299, 20910, 11, 288, 4906, 28, 600, 8, 628, 220, 220, 220, 1303, 4277, 6460, 329, 477, 3404, 198, 220, 220, 220, 5772, 62, 11600, 796, 1391, 198, 220, 220, 220, 220, 220, 220, 220, 366, 67, 541, 2305, 1298, 352, 13, 15, 11, 198, 220, 220, 220, 220, 220, 220, 220, 366, 19726, 3262, 1298, 366, 9562, 1600, 198, 220, 220, 220, 220, 220, 220, 220, 366, 7109, 6477, 1298, 366, 940, 1600, 198, 220, 220, 220, 220, 220, 220, 220, 366, 20545, 457, 1726, 1298, 366, 9562, 1600, 198, 220, 220, 220, 1782, 628, 220, 220, 220, 5772, 62, 11600, 13, 19119, 7, 46265, 22046, 8, 198, 220, 220, 220, 329, 2030, 80, 11, 2823, 287, 19974, 7, 69, 8897, 3976, 11, 2823, 9127, 82, 2599, 198, 220, 220, 220, 220, 220, 220, 220, 10117, 65, 62, 8841, 15853, 7716, 62, 701, 65, 62, 2536, 7, 19503, 80, 11, 2823, 11, 12429, 17143, 62, 11600, 8, 198, 220, 220, 220, 220, 220, 220, 220, 611, 366, 19726, 3262, 1, 287, 479, 86, 22046, 25, 198, 220, 220, 220, 220, 220, 220, 220, 220, 220, 220, 220, 5772, 62, 11600, 14692, 19726, 3262, 8973, 796, 366, 7942, 1, 198, 220, 220, 220, 220, 220, 220, 220, 220, 220, 220, 220, 10117, 65, 62, 8841, 15853, 7716, 62, 701, 65, 62, 2536, 7, 19503, 80, 11, 2823, 11, 12429, 17143, 62, 11600, 8, 628, 198, 4299, 17851, 1096, 62, 69, 8897, 3976, 7, 198, 220, 220, 220, 19998, 11, 198, 220, 220, 220, 299, 20910, 28, 1120, 11, 198, 220, 220, 220, 17509, 871, 28, 14202, 11, 198, 220, 220, 220, 1176, 28, 14202, 11, 198, 220, 220, 220, 708, 77, 62, 4868, 28, 14202, 11, 198, 220, 220, 220, 19550, 2305, 28, 14202, 11, 198, 220, 220, 220, 708, 77, 28, 14202, 11, 198, 220, 220, 220, 19972, 28, 25101, 11, 198, 220, 220, 220, 1553, 28, 25101, 11, 198, 220, 220, 220, 17655, 28, 25101, 11, 198, 2599, 198, 220, 220, 220, 37227, 198, 220, 220, 220, 220, 220, 220, 220, 15553, 326, 481, 5794, 281, 19446, 15458, 2393, 284, 1620, 17851, 1634, 198, 220, 220, 220, 220, 220, 220, 220, 5254, 11, 351, 617, 13688, 319, 703, 1728, 5254, 389, 6157, 13, 198, 220, 220, 220, 37227, 198, 220, 220, 220, 10117, 65, 62, 2536, 796, 13538, 198, 220, 220, 220, 611, 17509, 871, 318, 6045, 25, 198, 220, 220, 220, 220, 220, 220, 220, 6934, 796, 45941, 13, 12853, 7, 11925, 7, 69, 8897, 3976, 828, 299, 20910, 11, 288, 4906, 28, 600, 8, 198, 220, 220, 220, 2073, 25, 198, 220, 220, 220, 220, 220, 220, 220, 6934, 796, 45941, 13, 31166, 17034, 7, 77, 20910, 1220, 17509, 871, 737, 459, 2981, 7, 600, 8, 628, 220, 220, 220, 611, 19550, 2305, 25, 198, 220, 220, 220, 220, 220, 220, 220, 611, 708, 77, 318, 6045, 25, 198, 220, 220, 220, 220, 220, 220, 220, 220, 220, 220, 220, 1303, 1002, 19550, 2305, 1332, 9167, 11, 475, 645, 31919, 2288, 198, 220, 220, 220, 220, 220, 220, 220, 220, 220, 220, 220, 1303, 14275, 466, 262, 4277, 16085, 198, 220, 220, 220, 220, 220, 220, 220, 220, 220, 220, 220, 19550, 2305, 62, 9288, 796, 685, 15, 13, 486, 11, 657, 13, 16, 11, 352, 13, 15, 11, 513, 13, 15, 11, 642, 13, 15, 60, 198, 220, 220, 220, 220, 220, 220, 220, 220, 220, 220, 220, 19550, 2305, 62, 32109, 796, 366, 67, 541, 2305, 1, 198, 220, 220, 220, 220, 220, 220, 220, 2073, 25, 198, 220, 220, 220, 220, 220, 220, 220, 220, 220, 220, 220, 1303, 15323, 1057, 2176, 31919, 6055, 198, 220, 220, 220, 220, 220, 220, 220, 220, 220, 220, 220, 19550, 2305, 62, 9288, 796, 708, 77, 62, 4868, 198, 220, 220, 220, 220, 220, 220, 220, 220, 220, 220, 220, 19550, 2305, 62, 32109, 796, 366, 41769, 1, 628, 220, 220, 220, 611, 1553, 318, 6407, 25, 198, 220, 220, 220, 220, 220, 220, 220, 2030, 80, 62, 4868, 796, 17790, 7, 69, 8897, 3976, 11, 362, 8, 198, 220, 220, 220, 220, 220, 220, 220, 3601, 7, 4868, 7, 19503, 80, 62, 4868, 4008, 198, 220, 220, 220, 2073, 25, 198, 220, 220, 220, 220, 220, 220, 220, 2030, 80, 62, 4868, 796, 19998, 628, 220, 220, 220, 1303, 9052, 625, 1123, 8373, 290, 1271, 286, 6934, 198, 220, 220, 220, 329, 1988, 11, 2823, 9127, 287, 19974, 7, 19503, 80, 62, 4868, 11, 6934, 2599, 198, 220, 220, 220, 220, 220, 220, 220, 611, 1553, 318, 6407, 25, 198, 220, 220, 220, 220, 220, 220, 220, 220, 220, 220, 220, 2030, 80, 11, 1553, 62, 19503, 80, 796, 1988, 198, 220, 220, 220, 220, 220, 220, 220, 2073, 25, 198, 220, 220, 220, 220, 220, 220, 220, 220, 220, 220, 220, 2030, 80, 796, 1988, 198, 220, 220, 220, 220, 220, 220, 220, 220, 220, 220, 220, 1303, 2980, 378, 3487, 13432, 198, 220, 220, 220, 220, 220, 220, 220, 1949, 25, 198, 220, 220, 220, 220, 220, 220, 220, 220, 220, 220, 220, 2030, 80, 796, 12178, 7, 19503, 80, 8, 198, 220, 220, 220, 220, 220, 220, 220, 220, 220, 220, 220, 2823, 9127, 796, 493, 7, 9442, 9127, 8, 198, 220, 220, 220, 220, 220, 220, 220, 220, 220, 220, 220, 611, 1553, 318, 6407, 25, 198, 220, 220, 220, 220, 220, 220, 220, 220, 220, 220, 220, 220, 220, 220, 220, 1553, 62, 19503, 80, 796, 12178, 7, 7109, 62, 19503, 80, 8, 628, 220, 220, 220, 220, 220, 220, 220, 220, 220, 220, 220, 10117, 65, 62, 2536, 15853, 7716, 62, 701, 65, 62, 1370, 7, 19503, 80, 11, 2823, 9127, 11, 12429, 4895, 20545, 457, 1726, 1298, 366, 9562, 20662, 8, 628, 220, 220, 220, 220, 220, 220, 220, 220, 220, 220, 220, 611, 1553, 318, 6407, 25, 198, 220, 220, 220, 220, 220, 220, 220, 220, 220, 220, 220, 220, 220, 220, 220, 10117, 65, 62, 2536, 15853, 7716, 62, 701, 65, 62, 1370, 7, 198, 220, 220, 220, 220, 220, 220, 220, 220, 220, 220, 220, 220, 220, 220, 220, 220, 220, 220, 220, 2030, 80, 11, 2823, 9127, 11, 12429, 4895, 20545, 457, 1726, 1298, 366, 7942, 1600, 366, 7109, 19503, 80, 1298, 1553, 62, 19503, 80, 92, 198, 220, 220, 220, 220, 220, 220, 220, 220, 220, 220, 220, 220, 220, 220, 220, 1267, 628, 220, 220, 220, 220, 220, 220, 220, 220, 220, 220, 220, 611, 19550, 2305, 318, 6407, 25, 198, 220, 220, 220, 220, 220, 220, 220, 220, 220, 220, 220, 220, 220, 220, 220, 329, 19550, 2305, 62, 8367, 287, 19550, 2305, 62, 9288, 25, 198, 220, 220, 220, 220, 220, 220, 220, 220, 220, 220, 220, 220, 220, 220, 220, 220, 220, 220, 220, 10117, 65, 62, 2536, 15853, 7716, 62, 701, 65, 62, 1370, 7, 198, 220, 220, 220, 220, 220, 220, 220, 220, 220, 220, 220, 220, 220, 220, 220, 220, 220, 220, 220, 220, 220, 220, 220, 2030, 80, 11, 2823, 9127, 11, 12429, 90, 67, 541, 2305, 62, 32109, 25, 19550, 2305, 62, 8367, 92, 198, 220, 220, 220, 220, 220, 220, 220, 220, 220, 220, 220, 220, 220, 220, 220, 220, 220, 220, 220, 1267, 628, 220, 220, 220, 220, 220, 220, 220, 220, 220, 220, 220, 611, 19972, 318, 6407, 25, 198, 220, 220, 220, 220, 220, 220, 220, 220, 220, 220, 220, 220, 220, 220, 220, 10117, 65, 62, 2536, 15853, 7716, 62, 701, 65, 62, 1370, 7, 19503, 80, 11, 2823, 9127, 11, 12429, 4895, 19726, 3262, 1298, 366, 7942, 20662, 8, 628, 220, 220, 220, 220, 220, 220, 220, 220, 220, 220, 220, 611, 17655, 318, 6407, 25, 198, 220, 220, 220, 220, 220, 220, 220, 220, 220, 220, 220, 220, 220, 220, 220, 1303, 34098, 262, 17655, 8931, 319, 290, 572, 198, 220, 220, 220, 220, 220, 220, 220, 220, 220, 220, 220, 220, 220, 220, 220, 10117, 65, 62, 2536, 15853, 7716, 62, 701, 65, 62, 1370, 7, 198, 220, 220, 220, 220, 220, 220, 220, 220, 220, 220, 220, 220, 220, 220, 220, 220, 220, 220, 220, 2030, 80, 11, 2823, 9127, 11, 12429, 4895, 79, 9615, 11, 16, 11, 25616, 1298, 366, 9562, 20662, 198, 220, 220, 220, 220, 220, 220, 220, 220, 220, 220, 220, 220, 220, 220, 220, 1267, 198, 220, 220, 220, 220, 220, 220, 220, 220, 220, 220, 220, 220, 220, 220, 220, 10117, 65, 62, 2536, 15853, 7716, 62, 701, 65, 62, 1370, 7, 198, 220, 220, 220, 220, 220, 220, 220, 220, 220, 220, 220, 220, 220, 220, 220, 220, 220, 220, 220, 2030, 80, 11, 2823, 9127, 11, 12429, 4895, 79, 9615, 11, 16, 11, 25616, 1298, 366, 7942, 20662, 198, 220, 220, 220, 220, 220, 220, 220, 220, 220, 220, 220, 220, 220, 220, 220, 1267, 198, 220, 220, 220, 220, 220, 220, 220, 2845, 11052, 12331, 25, 198, 220, 220, 220, 220, 220, 220, 220, 220, 220, 220, 220, 3601, 7203, 12331, 351, 366, 1343, 965, 7, 8367, 4008, 628, 220, 220, 220, 1441, 10117, 65, 62, 2536, 628, 198, 4299, 15284, 62, 18908, 1358, 62, 22355, 7, 47799, 11, 299, 20910, 28, 1120, 2599, 198, 220, 220, 220, 37227, 198, 220, 220, 220, 220, 220, 220, 220, 11789, 329, 26019, 262, 2938, 11812, 640, 198, 220, 220, 220, 220, 220, 220, 220, 287, 2823, 9853, 1912, 319, 262, 12245, 26, 2035, 16200, 198, 220, 220, 220, 220, 220, 220, 220, 1627, 18929, 393, 11346, 49, 13, 628, 220, 220, 220, 220, 220, 220, 220, 10007, 25, 198, 220, 220, 220, 220, 220, 220, 220, 220, 24305, 198, 220, 220, 220, 220, 220, 220, 220, 12245, 532, 7177, 286, 12245, 18663, 26, 304, 13, 70, 13, 11346, 49, 198, 220, 220, 220, 220, 220, 220, 220, 299, 20910, 532, 11902, 493, 1271, 286, 6934, 973, 329, 262, 12841, 1627, 628, 220, 220, 220, 220, 220, 220, 220, 5860, 25, 198, 220, 220, 220, 220, 220, 220, 220, 220, 24305, 198, 220, 220, 220, 220, 220, 220, 220, 2823, 62, 9127, 82, 532, 7177, 286, 2823, 9853, 329, 1123, 8373, 198, 220, 220, 220, 37227, 198, 220, 220, 220, 2593, 62, 600, 796, 12245, 1220, 45941, 13, 9806, 7, 47799, 8, 198, 220, 220, 220, 2823, 62, 9127, 82, 796, 45941, 13, 744, 7, 77, 20910, 1220, 2593, 62, 600, 737, 459, 2981, 7, 600, 8, 198, 220, 220, 220, 1441, 2823, 62, 9127, 82, 628, 628, 198, 31, 19608, 330, 31172, 628, 198, 31, 19608, 330, 31172, 198 ]
2.307527
12,555
import json from dataclasses import dataclass import omitempty from dnsimple.struct import Struct class DomainRenewRequest(dict): """DomainRenewRequest represents the attributes you can pass to a renew API request.""" @dataclass class DomainRenewal(Struct): """Represents the result of a domain renewal call.""" id = None """The domain registration ID in DNSimple""" domain_id = None """The associated domain ID""" state = None """The state of the renewal""" period = None """The number of years the domain was registered for""" created_at = None """When the domain renewal was created in DNSimple""" updated_at = None """When the domain renewal was last updated in DNSimple"""
[ 11748, 33918, 198, 6738, 4818, 330, 28958, 1330, 4818, 330, 31172, 198, 198, 11748, 42848, 28920, 198, 198, 6738, 288, 5907, 320, 1154, 13, 7249, 1330, 32112, 628, 198, 4871, 20021, 26764, 413, 18453, 7, 11600, 2599, 198, 220, 220, 220, 37227, 43961, 26764, 413, 18453, 6870, 262, 12608, 345, 460, 1208, 284, 257, 6931, 7824, 2581, 526, 15931, 628, 198, 31, 19608, 330, 31172, 198, 4871, 20021, 26764, 413, 282, 7, 44909, 2599, 628, 220, 220, 220, 37227, 6207, 6629, 262, 1255, 286, 257, 7386, 22901, 869, 526, 15931, 198, 220, 220, 220, 4686, 796, 6045, 198, 220, 220, 220, 37227, 464, 7386, 9352, 4522, 287, 18538, 320, 1154, 37811, 198, 220, 220, 220, 7386, 62, 312, 796, 6045, 198, 220, 220, 220, 37227, 464, 3917, 7386, 4522, 37811, 198, 220, 220, 220, 1181, 796, 6045, 198, 220, 220, 220, 37227, 464, 1181, 286, 262, 22901, 37811, 198, 220, 220, 220, 2278, 796, 6045, 198, 220, 220, 220, 37227, 464, 1271, 286, 812, 262, 7386, 373, 6823, 329, 37811, 198, 220, 220, 220, 2727, 62, 265, 796, 6045, 198, 220, 220, 220, 37227, 2215, 262, 7386, 22901, 373, 2727, 287, 18538, 320, 1154, 37811, 198, 220, 220, 220, 6153, 62, 265, 796, 6045, 198, 220, 220, 220, 37227, 2215, 262, 7386, 22901, 373, 938, 6153, 287, 18538, 320, 1154, 37811, 198 ]
3.337838
222
class RequestAdapter(object): """ RequestAdapters bridge transmute's representation of a request, with the framework's implementation. implement the unimplemented methods. """ @property def body(self): """ return the request body. """ raise NotImplementedError() def _get_framework_args(self): """ often, a framework provides specific variables that are passed into the handler function (e.g. the request object in aiohttp). return a dictionary of these arguments, which will be added to the function arguments if they appear. """ raise NotImplementedError()
[ 4871, 19390, 47307, 7, 15252, 2599, 198, 220, 220, 220, 37227, 198, 220, 220, 220, 19390, 2782, 12126, 7696, 21595, 1133, 338, 198, 220, 220, 220, 10552, 286, 257, 2581, 11, 351, 262, 9355, 338, 198, 220, 220, 220, 7822, 13, 628, 220, 220, 220, 3494, 262, 28418, 1154, 12061, 5050, 13, 198, 220, 220, 220, 37227, 628, 220, 220, 220, 2488, 26745, 198, 220, 220, 220, 825, 1767, 7, 944, 2599, 198, 220, 220, 220, 220, 220, 220, 220, 37227, 1441, 262, 2581, 1767, 13, 37227, 198, 220, 220, 220, 220, 220, 220, 220, 5298, 1892, 3546, 1154, 12061, 12331, 3419, 628, 220, 220, 220, 825, 4808, 1136, 62, 30604, 62, 22046, 7, 944, 2599, 198, 220, 220, 220, 220, 220, 220, 220, 37227, 198, 220, 220, 220, 220, 220, 220, 220, 1690, 11, 257, 9355, 3769, 2176, 9633, 326, 389, 3804, 198, 220, 220, 220, 220, 220, 220, 220, 656, 262, 21360, 2163, 357, 68, 13, 70, 13, 262, 2581, 2134, 287, 198, 220, 220, 220, 220, 220, 220, 220, 257, 952, 4023, 737, 1441, 257, 22155, 286, 777, 7159, 11, 543, 481, 307, 198, 220, 220, 220, 220, 220, 220, 220, 2087, 284, 262, 2163, 7159, 611, 484, 1656, 13, 198, 220, 220, 220, 220, 220, 220, 220, 37227, 198, 220, 220, 220, 220, 220, 220, 220, 5298, 1892, 3546, 1154, 12061, 12331, 3419, 198 ]
2.938596
228
# python3 """ Task: Count the number of inversions of a given sequence """ tot_count = 0 n = int ( input () ) seq = [ int ( i ) for i in input ().split () ] mergesort ( seq ) print ( tot_count )
[ 2, 21015, 18, 198, 198, 37811, 15941, 25, 2764, 262, 1271, 286, 287, 47178, 286, 257, 1813, 8379, 37227, 628, 628, 198, 83, 313, 62, 9127, 796, 657, 198, 77, 796, 493, 357, 5128, 7499, 1267, 198, 41068, 796, 685, 493, 357, 1312, 1267, 329, 1312, 287, 5128, 27972, 35312, 7499, 2361, 198, 647, 3212, 419, 357, 33756, 1267, 198, 4798, 357, 2006, 62, 9127, 1267, 198 ]
2.985075
67
import numpy as np import scipy.misc import os import time # from PIL import Image DATA_DIR = '/home/ubuntu/lsun/bedrooms/' NEW_DATA_DIR = '/home/ubuntu/lsun/bedrooms_128/' # with open(DATA_DIR+'files.txt', 'r') as f: # files = [l[:-1] for l in f] # # images = np.zeros((batch_size, 3, 256, 256), dtype='int32') # random_state = np.random.RandomState(42) # random_state.shuffle(files) # z = 1729468 # for i, path in enumerate(files): # if i < 1729500: # continue # try: # image = scipy.misc.imread( # os.path.normpath(os.path.join(DATA_DIR, path)) # ) # # try: # # image = image.transpose(2,0,1) # offset_y = (image.shape[0]-256)/2 # offset_x = (image.shape[1]-256)/2 # image = image[offset_y:offset_y+256, offset_x:offset_x+256] # image = image[::2,::2]+image[1::2,::2]+image[::2,1::2]+image[1::2,1::2] # image = image / 4 # # image = image.astype('int32') # # im = Image.fromarray(image) # # p = os.path.normpath(os.path.join(NEW_DATA_DIR, path)) # # try: # # os.makedirs(os.path.dirname(p)) # # except: # # pass # scipy.misc.imsave(NEW_DATA_DIR+'{}.jpg'.format(z), image) # # im.save(p[:-4]+'jpg') # if z % 100 == 0: # print z # z += 1 # except: # print "skip" # # if i > 0 and i % batch_size == 0: # # if downscale: # # downscaled_images = images[:,:,::2,::2] + images[:,:,1::2,::2] + images[:,:,::2,1::2] + images[:,:,1::2,1::2] # # downscaled_images = downscaled_images / 4. # # yield (downscaled_images.astype('int32'),) # # else: # # yield (images,) # # except Exception as ex: # # print ex # # print "warning data preprocess failed for path {}".format(path) if __name__ == '__main__': train_gen = load(64) t0 = time.time() for i, batch in enumerate(train_gen(), start=1): print "{}\t{}".format(str(time.time() - t0), batch[0][0,0,0,0]) if i == 1000: break t0 = time.time()
[ 11748, 299, 32152, 355, 45941, 198, 11748, 629, 541, 88, 13, 44374, 198, 11748, 28686, 198, 11748, 640, 198, 2, 422, 350, 4146, 1330, 7412, 198, 198, 26947, 62, 34720, 796, 31051, 11195, 14, 32230, 14, 7278, 403, 14, 3077, 9649, 14, 6, 198, 13965, 62, 26947, 62, 34720, 796, 31051, 11195, 14, 32230, 14, 7278, 403, 14, 3077, 9649, 62, 12762, 14, 6, 198, 198, 2, 351, 1280, 7, 26947, 62, 34720, 10, 6, 16624, 13, 14116, 3256, 705, 81, 11537, 355, 277, 25, 198, 2, 220, 220, 220, 220, 3696, 796, 685, 75, 58, 21912, 16, 60, 329, 300, 287, 277, 60, 198, 2, 1303, 4263, 796, 45941, 13, 9107, 418, 19510, 43501, 62, 7857, 11, 513, 11, 17759, 11, 17759, 828, 288, 4906, 11639, 600, 2624, 11537, 198, 2, 4738, 62, 5219, 796, 45941, 13, 25120, 13, 29531, 9012, 7, 3682, 8, 198, 2, 4738, 62, 5219, 13, 1477, 18137, 7, 16624, 8, 198, 198, 2, 1976, 796, 1596, 27696, 3104, 198, 2, 329, 1312, 11, 3108, 287, 27056, 378, 7, 16624, 2599, 198, 2, 220, 220, 220, 220, 611, 1312, 1279, 1596, 1959, 4059, 25, 198, 2, 220, 220, 220, 220, 220, 220, 220, 220, 2555, 198, 2, 220, 220, 220, 220, 1949, 25, 198, 2, 220, 220, 220, 220, 220, 220, 220, 220, 2939, 796, 629, 541, 88, 13, 44374, 13, 320, 961, 7, 198, 2, 220, 220, 220, 220, 220, 220, 220, 220, 220, 220, 220, 220, 28686, 13, 6978, 13, 27237, 6978, 7, 418, 13, 6978, 13, 22179, 7, 26947, 62, 34720, 11, 3108, 4008, 198, 2, 220, 220, 220, 220, 220, 220, 220, 220, 1267, 198, 198, 2, 220, 220, 220, 220, 220, 220, 220, 220, 1303, 1949, 25, 220, 220, 220, 220, 220, 220, 220, 220, 220, 220, 220, 220, 220, 220, 220, 220, 198, 2, 220, 220, 220, 220, 220, 220, 220, 220, 1303, 2939, 796, 2939, 13, 7645, 3455, 7, 17, 11, 15, 11, 16, 8, 198, 2, 220, 220, 220, 220, 220, 220, 220, 220, 11677, 62, 88, 796, 357, 9060, 13, 43358, 58, 15, 45297, 11645, 20679, 17, 198, 2, 220, 220, 220, 220, 220, 220, 220, 220, 11677, 62, 87, 796, 357, 9060, 13, 43358, 58, 16, 45297, 11645, 20679, 17, 198, 2, 220, 220, 220, 220, 220, 220, 220, 220, 2939, 796, 2939, 58, 28968, 62, 88, 25, 28968, 62, 88, 10, 11645, 11, 11677, 62, 87, 25, 28968, 62, 87, 10, 11645, 60, 198, 2, 220, 220, 220, 220, 220, 220, 220, 220, 2939, 796, 2939, 58, 3712, 17, 11, 3712, 17, 48688, 9060, 58, 16, 3712, 17, 11, 3712, 17, 48688, 9060, 58, 3712, 17, 11, 16, 3712, 17, 48688, 9060, 58, 16, 3712, 17, 11, 16, 3712, 17, 60, 198, 2, 220, 220, 220, 220, 220, 220, 220, 220, 2939, 796, 2939, 1220, 604, 198, 2, 220, 220, 220, 220, 220, 220, 220, 220, 1303, 2939, 796, 2939, 13, 459, 2981, 10786, 600, 2624, 11537, 198, 2, 220, 220, 220, 220, 220, 220, 220, 220, 1303, 545, 796, 7412, 13, 6738, 18747, 7, 9060, 8, 198, 2, 220, 220, 220, 220, 220, 220, 220, 220, 1303, 279, 796, 28686, 13, 6978, 13, 27237, 6978, 7, 418, 13, 6978, 13, 22179, 7, 13965, 62, 26947, 62, 34720, 11, 3108, 4008, 198, 2, 220, 220, 220, 220, 220, 220, 220, 220, 1303, 1949, 25, 198, 2, 220, 220, 220, 220, 220, 220, 220, 220, 1303, 220, 220, 220, 220, 28686, 13, 76, 4335, 17062, 7, 418, 13, 6978, 13, 15908, 3672, 7, 79, 4008, 198, 2, 220, 220, 220, 220, 220, 220, 220, 220, 1303, 2845, 25, 198, 2, 220, 220, 220, 220, 220, 220, 220, 220, 1303, 220, 220, 220, 220, 1208, 198, 2, 220, 220, 220, 220, 220, 220, 220, 220, 629, 541, 88, 13, 44374, 13, 12078, 1015, 7, 13965, 62, 26947, 62, 34720, 10, 6, 90, 27422, 9479, 4458, 18982, 7, 89, 828, 2939, 8, 198, 2, 220, 220, 220, 220, 220, 220, 220, 220, 1303, 545, 13, 21928, 7, 79, 58, 21912, 19, 48688, 6, 9479, 11537, 198, 2, 220, 220, 220, 220, 220, 220, 220, 220, 611, 1976, 4064, 1802, 6624, 657, 25, 198, 2, 220, 220, 220, 220, 220, 220, 220, 220, 220, 220, 220, 220, 3601, 1976, 198, 2, 220, 220, 220, 220, 220, 220, 220, 220, 1976, 15853, 352, 198, 2, 220, 220, 220, 220, 2845, 25, 198, 2, 220, 220, 220, 220, 220, 220, 220, 220, 3601, 366, 48267, 1, 198, 198, 2, 220, 220, 220, 220, 1303, 611, 1312, 1875, 657, 290, 1312, 4064, 15458, 62, 7857, 6624, 657, 25, 198, 2, 220, 220, 220, 220, 1303, 220, 220, 220, 220, 611, 866, 9888, 25, 198, 2, 220, 220, 220, 220, 1303, 220, 220, 220, 220, 220, 220, 220, 220, 866, 1416, 3021, 62, 17566, 796, 4263, 58, 45299, 45299, 3712, 17, 11, 3712, 17, 60, 1343, 4263, 58, 45299, 45299, 16, 3712, 17, 11, 3712, 17, 60, 1343, 4263, 58, 45299, 45299, 3712, 17, 11, 16, 3712, 17, 60, 1343, 4263, 58, 45299, 45299, 16, 3712, 17, 11, 16, 3712, 17, 60, 198, 2, 220, 220, 220, 220, 1303, 220, 220, 220, 220, 220, 220, 220, 220, 866, 1416, 3021, 62, 17566, 796, 866, 1416, 3021, 62, 17566, 1220, 604, 13, 198, 2, 220, 220, 220, 220, 1303, 220, 220, 220, 220, 220, 220, 220, 220, 7800, 357, 2902, 1416, 3021, 62, 17566, 13, 459, 2981, 10786, 600, 2624, 33809, 8, 198, 2, 220, 220, 220, 220, 1303, 220, 220, 220, 220, 2073, 25, 198, 2, 220, 220, 220, 220, 1303, 220, 220, 220, 220, 220, 220, 220, 220, 7800, 357, 17566, 35751, 198, 2, 220, 220, 220, 220, 1303, 2845, 35528, 355, 409, 25, 198, 2, 220, 220, 220, 220, 1303, 220, 220, 220, 220, 3601, 409, 198, 2, 220, 220, 220, 220, 1303, 220, 220, 220, 220, 3601, 366, 43917, 1366, 662, 14681, 4054, 329, 3108, 23884, 1911, 18982, 7, 6978, 8, 628, 198, 361, 11593, 3672, 834, 6624, 705, 834, 12417, 834, 10354, 198, 220, 220, 220, 4512, 62, 5235, 796, 3440, 7, 2414, 8, 198, 220, 220, 220, 256, 15, 796, 640, 13, 2435, 3419, 198, 220, 220, 220, 329, 1312, 11, 15458, 287, 27056, 378, 7, 27432, 62, 5235, 22784, 923, 28, 16, 2599, 198, 220, 220, 220, 220, 220, 220, 220, 3601, 45144, 32239, 83, 90, 92, 1911, 18982, 7, 2536, 7, 2435, 13, 2435, 3419, 532, 256, 15, 828, 15458, 58, 15, 7131, 15, 11, 15, 11, 15, 11, 15, 12962, 198, 220, 220, 220, 220, 220, 220, 220, 611, 1312, 6624, 8576, 25, 198, 220, 220, 220, 220, 220, 220, 220, 220, 220, 220, 220, 2270, 198, 220, 220, 220, 220, 220, 220, 220, 256, 15, 796, 640, 13, 2435, 3419, 198 ]
1.919326
1,128
from django.db.utils import IntegrityError from django.db.models import Q from rest_framework import serializers from core.models import FavoriteThing from core.models import Category from .helper import reorder_rankings, reorder_rankings_subtract
[ 6738, 42625, 14208, 13, 9945, 13, 26791, 1330, 39348, 12331, 198, 6738, 42625, 14208, 13, 9945, 13, 27530, 1330, 1195, 198, 6738, 1334, 62, 30604, 1330, 11389, 11341, 198, 6738, 4755, 13, 27530, 1330, 33992, 51, 722, 198, 6738, 4755, 13, 27530, 1330, 21743, 198, 6738, 764, 2978, 525, 1330, 302, 2875, 62, 43027, 654, 11, 302, 2875, 62, 43027, 654, 62, 7266, 83, 974, 628 ]
3.772727
66
# Tests for the Genomics Data Quality Pipeline import mock, datetime, pytz from rdr_service import clock from rdr_service.api_util import open_cloud_file from rdr_service.genomic_enums import GenomicJob, GenomicSubProcessStatus, GenomicSubProcessResult, \ GenomicManifestTypes, GenomicIncidentCode from tests.helpers.unittest_base import BaseTestCase from rdr_service.genomic.genomic_job_controller import DataQualityJobController from rdr_service.genomic.genomic_data_quality_components import ReportingComponent
[ 2, 30307, 329, 262, 5215, 31994, 6060, 14156, 37709, 198, 11748, 15290, 11, 4818, 8079, 11, 12972, 22877, 198, 198, 6738, 374, 7109, 62, 15271, 1330, 8801, 198, 6738, 374, 7109, 62, 15271, 13, 15042, 62, 22602, 1330, 1280, 62, 17721, 62, 7753, 198, 6738, 374, 7109, 62, 15271, 13, 5235, 10179, 62, 268, 5700, 1330, 5215, 10179, 33308, 11, 5215, 10179, 7004, 18709, 19580, 11, 5215, 10179, 7004, 18709, 23004, 11, 3467, 198, 220, 220, 220, 5215, 10179, 5124, 8409, 31431, 11, 5215, 10179, 25517, 738, 10669, 198, 6738, 5254, 13, 16794, 364, 13, 403, 715, 395, 62, 8692, 1330, 7308, 14402, 20448, 198, 6738, 374, 7109, 62, 15271, 13, 5235, 10179, 13, 5235, 10179, 62, 21858, 62, 36500, 1330, 6060, 35013, 33308, 22130, 198, 6738, 374, 7109, 62, 15271, 13, 5235, 10179, 13, 5235, 10179, 62, 7890, 62, 13237, 62, 5589, 3906, 1330, 29595, 21950, 628, 628 ]
3.503356
149
# Time limit exceeded while True: try: A = input() B = input() lA = len(A) lB = len(B) biggest = "" shortest = "" lshortest = 0 if max(lA, lB) == lA: biggest, shortest = A, B lbiggest = lA lshortest = lB else: biggest, shortest = B, A lbiggest = lB lshortest = lA bSub = 0 currentSub = 0 for k in range(lshortest): for w in range(lbiggest): if shortest[k] == biggest[w]: currentSub = 1 q = w+1 for p in range(k+1,lshortest): if q >= lbiggest: break if shortest[p] == biggest[q]: currentSub += 1 q += 1 else: break if currentSub >= bSub: bSub = currentSub print(bSub) except: break
[ 2, 3862, 4179, 20672, 198, 198, 4514, 6407, 25, 198, 197, 28311, 25, 198, 197, 197, 32, 796, 5128, 3419, 198, 197, 197, 33, 796, 5128, 3419, 628, 197, 197, 75, 32, 796, 18896, 7, 32, 8, 198, 197, 197, 75, 33, 796, 18896, 7, 33, 8, 628, 197, 197, 14261, 3495, 796, 13538, 198, 197, 197, 19509, 395, 796, 13538, 198, 197, 197, 75, 19509, 395, 796, 657, 198, 197, 197, 361, 3509, 7, 75, 32, 11, 300, 33, 8, 6624, 300, 32, 25, 198, 197, 197, 197, 14261, 3495, 11, 35581, 796, 317, 11, 347, 198, 197, 197, 197, 75, 14261, 3495, 796, 300, 32, 198, 197, 197, 197, 75, 19509, 395, 796, 300, 33, 198, 197, 197, 17772, 25, 198, 197, 197, 197, 14261, 3495, 11, 35581, 796, 347, 11, 317, 198, 197, 197, 197, 75, 14261, 3495, 796, 300, 33, 198, 197, 197, 197, 75, 19509, 395, 796, 300, 32, 628, 198, 197, 197, 65, 7004, 796, 657, 198, 197, 197, 14421, 7004, 796, 657, 198, 197, 197, 1640, 479, 287, 2837, 7, 75, 19509, 395, 2599, 198, 197, 197, 197, 1640, 266, 287, 2837, 7, 75, 14261, 3495, 2599, 198, 197, 197, 197, 197, 361, 35581, 58, 74, 60, 6624, 4094, 58, 86, 5974, 198, 197, 197, 197, 197, 197, 14421, 7004, 796, 352, 628, 197, 197, 197, 197, 197, 80, 796, 266, 10, 16, 628, 197, 197, 197, 197, 197, 1640, 279, 287, 2837, 7, 74, 10, 16, 11, 75, 19509, 395, 2599, 198, 197, 197, 197, 197, 197, 197, 361, 10662, 18189, 300, 14261, 3495, 25, 198, 197, 197, 197, 197, 197, 197, 197, 9032, 198, 197, 197, 197, 197, 197, 197, 361, 35581, 58, 79, 60, 6624, 4094, 58, 80, 5974, 198, 197, 197, 197, 197, 197, 197, 197, 14421, 7004, 15853, 352, 198, 197, 197, 197, 197, 197, 197, 197, 80, 15853, 352, 198, 197, 197, 197, 197, 197, 197, 17772, 25, 198, 197, 197, 197, 197, 197, 197, 197, 9032, 628, 197, 197, 197, 197, 361, 1459, 7004, 18189, 275, 7004, 25, 198, 197, 197, 197, 197, 197, 65, 7004, 796, 1459, 7004, 628, 197, 197, 4798, 7, 65, 7004, 8, 198, 197, 198, 197, 16341, 25, 198, 197, 197, 9032 ]
1.929919
371
import os, urllib, requests, json priority = 1
[ 11748, 28686, 11, 2956, 297, 571, 11, 7007, 11, 33918, 198, 49336, 796, 352, 198 ]
3.133333
15
list1 = [1, 4, 8, 2, 9] print len(list1) print max(list1), min(list1) print list1[-2] print list1[-5:3] print list1[-3:]
[ 198, 4868, 16, 796, 685, 16, 11, 604, 11, 807, 11, 362, 11, 860, 60, 198, 198, 4798, 18896, 7, 4868, 16, 8, 198, 4798, 3509, 7, 4868, 16, 828, 949, 7, 4868, 16, 8, 198, 4798, 1351, 16, 58, 12, 17, 60, 198, 4798, 1351, 16, 58, 12, 20, 25, 18, 60, 198, 4798, 1351, 16, 58, 12, 18, 47715, 628 ]
2
62
from matplotlib import pyplot as plt from script import sales_times1 from script import sales_times2 # normed=True This command divides the height of each column by # a constant such that the total shaded area of the histogram sums # to 1 plt.hist(sales_times1, bins=20, alpha=0.4, normed=True) plt.hist(sales_times2, bins=20, alpha=0.4, normed=True) plt.show() #%% from matplotlib import pyplot as plt exam_scores1 = [62.58, 67.63, 81.37, 52.53, 62.98, 72.15, 59.05, 73.85, 97.24, 76.81, 89.34, 74.44, 68.52, 85.13, 90.75, 70.29, 75.62, 85.38, 77.82, 98.31, 79.08, 61.72, 71.33, 80.77, 80.31, 78.16, 61.15, 64.99, 72.67, 78.94] exam_scores2 = [72.38, 71.28, 79.24, 83.86, 84.42, 79.38, 75.51, 76.63, 81.48,78.81,79.23,74.38,79.27,81.07,75.42,90.35,82.93,86.74,81.33,95.1,86.57,83.66,85.58,81.87,92.14,72.15,91.64,74.21,89.04,76.54,81.9,96.5,80.05,74.77,72.26,73.23,92.6,66.22,70.09,77.2] # Make your plot here plt.figure(figsize=(10,8)) plt.hist(exam_scores1,bins=12,normed=True, histtype='step',linewidth=2) plt.hist(exam_scores2,bins=12,normed=True, histtype='step',linewidth=2) legends=["1st Yr Teaching","2nd Yr Teaching"] plt.legend(legends) plt.title("Final Exam Score Distribution") plt.xlabel("Percentage") plt.ylabel("Frequency") plt.savefig("my_histogram.png") #%% import numpy as np import pandas as pd # Import matplotlib pyplot from matplotlib import pyplot as plt # Read in transactions data greatest_books = pd.read_csv("top-hundred-books.csv") # Save transaction times to a separate numpy array author_ages = greatest_books['Ages'] # Use numpy to calculate the average age of the top 100 authors average_age = np.average(author_ages) print("The average age of the 100 greatest authors, according to Le Monde is: " + str(average_age)) # Plot the figure plt.hist(author_ages, range=(10, 80), bins=14, edgecolor='black') plt.title("Age of Top 100 Novel Authors at Publication") plt.xlabel("Publication Age") plt.ylabel("Count") plt.axvline(average_age, color='r', linestyle='solid', linewidth=2, label="Mean") plt.legend() plt.show()
[ 6738, 2603, 29487, 8019, 1330, 12972, 29487, 355, 458, 83, 198, 6738, 4226, 1330, 4200, 62, 22355, 16, 198, 6738, 4226, 1330, 4200, 62, 22355, 17, 198, 2, 2593, 276, 28, 17821, 770, 3141, 36319, 262, 6001, 286, 1123, 5721, 416, 198, 2, 257, 6937, 884, 326, 262, 2472, 427, 5286, 1989, 286, 262, 1554, 21857, 21784, 198, 2, 284, 352, 220, 198, 489, 83, 13, 10034, 7, 82, 2040, 62, 22355, 16, 11, 41701, 28, 1238, 11, 17130, 28, 15, 13, 19, 11, 2593, 276, 28, 17821, 8, 198, 489, 83, 13, 10034, 7, 82, 2040, 62, 22355, 17, 11, 41701, 28, 1238, 11, 17130, 28, 15, 13, 19, 11, 2593, 276, 28, 17821, 8, 198, 198, 489, 83, 13, 12860, 3419, 198, 2, 16626, 198, 6738, 2603, 29487, 8019, 1330, 12972, 29487, 355, 458, 83, 198, 198, 1069, 321, 62, 1416, 2850, 16, 796, 685, 5237, 13, 3365, 11, 8275, 13, 5066, 11, 9773, 13, 2718, 11, 6740, 13, 4310, 11, 8190, 13, 4089, 11, 7724, 13, 1314, 11, 7863, 13, 2713, 11, 8854, 13, 5332, 11, 10111, 13, 1731, 11, 8684, 13, 6659, 11, 9919, 13, 2682, 11, 8915, 13, 2598, 11, 8257, 13, 4309, 11, 7600, 13, 1485, 11, 4101, 13, 2425, 11, 4317, 13, 1959, 11, 5441, 13, 5237, 11, 7600, 13, 2548, 11, 8541, 13, 6469, 11, 9661, 13, 3132, 11, 9225, 13, 2919, 11, 8454, 13, 4761, 11, 9166, 13, 2091, 11, 4019, 13, 3324, 11, 4019, 13, 3132, 11, 8699, 13, 1433, 11, 8454, 13, 1314, 11, 5598, 13, 2079, 11, 7724, 13, 3134, 11, 8699, 13, 5824, 60, 198, 1069, 321, 62, 1416, 2850, 17, 796, 685, 4761, 13, 2548, 11, 9166, 13, 2078, 11, 9225, 13, 1731, 11, 9698, 13, 4521, 11, 9508, 13, 3682, 11, 9225, 13, 2548, 11, 5441, 13, 4349, 11, 8684, 13, 5066, 11, 9773, 13, 2780, 11, 3695, 13, 6659, 11, 3720, 13, 1954, 11, 4524, 13, 2548, 11, 3720, 13, 1983, 11, 6659, 13, 2998, 11, 2425, 13, 3682, 11, 3829, 13, 2327, 11, 6469, 13, 6052, 11, 4521, 13, 4524, 11, 6659, 13, 2091, 11, 3865, 13, 16, 11, 4521, 13, 3553, 11, 5999, 13, 2791, 11, 5332, 13, 3365, 11, 6659, 13, 5774, 11, 5892, 13, 1415, 11, 4761, 13, 1314, 11, 6420, 13, 2414, 11, 4524, 13, 2481, 11, 4531, 13, 3023, 11, 4304, 13, 4051, 11, 6659, 13, 24, 11, 4846, 13, 20, 11, 1795, 13, 2713, 11, 4524, 13, 3324, 11, 4761, 13, 2075, 11, 4790, 13, 1954, 11, 5892, 13, 21, 11, 2791, 13, 1828, 11, 2154, 13, 2931, 11, 3324, 13, 17, 60, 198, 198, 2, 6889, 534, 7110, 994, 198, 489, 83, 13, 26875, 7, 5647, 7857, 16193, 940, 11, 23, 4008, 198, 489, 83, 13, 10034, 7, 1069, 321, 62, 1416, 2850, 16, 11, 65, 1040, 28, 1065, 11, 27237, 276, 28, 17821, 11, 198, 220, 220, 220, 220, 220, 220, 220, 220, 1554, 4906, 11639, 9662, 3256, 2815, 413, 5649, 28, 17, 8, 198, 489, 83, 13, 10034, 7, 1069, 321, 62, 1416, 2850, 17, 11, 65, 1040, 28, 1065, 11, 27237, 276, 28, 17821, 11, 198, 220, 220, 220, 220, 220, 220, 220, 220, 1554, 4906, 11639, 9662, 3256, 2815, 413, 5649, 28, 17, 8, 198, 1455, 2412, 28, 14692, 16, 301, 575, 81, 38094, 2430, 17, 358, 575, 81, 38094, 8973, 198, 489, 83, 13, 1455, 437, 7, 1455, 2412, 8, 198, 489, 83, 13, 7839, 7203, 19006, 35909, 15178, 27484, 4943, 198, 489, 83, 13, 87, 18242, 7203, 31905, 496, 4943, 198, 489, 83, 13, 2645, 9608, 7203, 37, 28707, 4943, 198, 198, 489, 83, 13, 21928, 5647, 7203, 1820, 62, 10034, 21857, 13, 11134, 4943, 198, 2, 16626, 198, 11748, 299, 32152, 355, 45941, 198, 11748, 19798, 292, 355, 279, 67, 198, 198, 2, 17267, 2603, 29487, 8019, 12972, 29487, 198, 6738, 2603, 29487, 8019, 1330, 12972, 29487, 355, 458, 83, 198, 198, 2, 4149, 287, 8945, 1366, 198, 18223, 395, 62, 12106, 796, 279, 67, 13, 961, 62, 40664, 7203, 4852, 12, 71, 3229, 12, 12106, 13, 40664, 4943, 198, 198, 2, 12793, 8611, 1661, 284, 257, 4553, 299, 32152, 7177, 198, 9800, 62, 1095, 796, 6000, 62, 12106, 17816, 32, 3212, 20520, 198, 198, 2, 5765, 299, 32152, 284, 15284, 262, 2811, 2479, 286, 262, 1353, 1802, 7035, 198, 23913, 62, 496, 796, 45941, 13, 23913, 7, 9800, 62, 1095, 8, 198, 198, 4798, 7203, 464, 2811, 2479, 286, 262, 1802, 6000, 7035, 11, 1864, 284, 1004, 337, 14378, 318, 25, 366, 1343, 965, 7, 23913, 62, 496, 4008, 198, 198, 2, 28114, 262, 3785, 198, 489, 83, 13, 10034, 7, 9800, 62, 1095, 11, 2837, 16193, 940, 11, 4019, 828, 41701, 28, 1415, 11, 220, 5743, 8043, 11639, 13424, 11537, 198, 489, 83, 13, 7839, 7203, 23396, 286, 5849, 1802, 24467, 46665, 379, 45065, 4943, 198, 489, 83, 13, 87, 18242, 7203, 15202, 341, 7129, 4943, 198, 489, 83, 13, 2645, 9608, 7203, 12332, 4943, 198, 489, 83, 13, 897, 85, 1370, 7, 23913, 62, 496, 11, 3124, 11639, 81, 3256, 9493, 10992, 11639, 39390, 3256, 9493, 413, 5649, 28, 17, 11, 6167, 2625, 5308, 272, 4943, 198, 489, 83, 13, 1455, 437, 3419, 198, 198, 489, 83, 13, 12860, 3419, 198 ]
2.376
875
# print(123456) # print('Kaic', 'Pierre', 'Outra Coisa') # print('Kaic', 'Pierre', sep='-', end='') # print('Testando', 'Outras', 'Coisas', sep='-', end='') print('428', '330', '048', sep='.', end='-') print('93')
[ 2, 3601, 7, 10163, 29228, 8, 198, 2, 3601, 10786, 42, 18452, 3256, 705, 36910, 3256, 705, 7975, 430, 1766, 9160, 11537, 198, 2, 3601, 10786, 42, 18452, 3256, 705, 36910, 3256, 41767, 11639, 12, 3256, 886, 28, 7061, 8, 198, 2, 3601, 10786, 14402, 25440, 3256, 705, 7975, 8847, 3256, 705, 7222, 271, 292, 3256, 41767, 11639, 12, 3256, 886, 28, 7061, 8, 198, 4798, 10786, 40173, 3256, 705, 26073, 3256, 705, 47202, 3256, 41767, 11639, 2637, 11, 886, 11639, 12, 11537, 198, 4798, 10786, 6052, 11537, 198 ]
2.404494
89
import sys sys.path.append("../") # KoBERT 모델 import config import pandas as pd import numpy as np from sklearn.preprocessing import OneHotEncoder import torch from torch import nn import torch.nn.functional as F import torch.optim as optim from torch.utils.data import Dataset, DataLoader import gluonnlp as nlp from tqdm import tqdm, tqdm_notebook from KoBERT.kobert.utils import get_tokenizer from KoBERT.kobert.pytorch_kobert import get_pytorch_kobert_model from transformers import AdamW # from transformers.optimization import WarmupLinearSchedule from transformers import get_linear_schedule_with_warmup device = torch.device('cuda' if torch.cuda.is_available() else 'cpu') bertmodel, vocab = get_pytorch_kobert_model() # 토크나이저 메서드를 tokenizer에 호출 # 코퍼스를 토큰으로 만드는 과정을 수행, 이 때 토크나이저는 kobert 패키지에 있는 get_tokenizer()를 사용하고, # 토큰화를 위해 필요한 단어 사전은 kobert의 vocab을 사용함. # uncased로 투입해야 하므로 lower = False tokenizer = get_tokenizer() tok = nlp.data.BERTSPTokenizer(tokenizer, vocab, lower = False) print(f'device using: {device}') model_config=config.model_config class EarlyStopping: """Early stops the training if validation loss doesn't improve after a given patience.""" def __init__(self, patience=7, verbose=False, delta=0, path='checkpoint.pt', trace_func=print): """ Args: patience (int): How long to wait after last time validation loss improved. Default: 7 verbose (bool): If True, prints a message for each validation loss improvement. Default: False delta (float): Minimum change in the monitored quantity to qualify as an improvement. Default: 0 path (str): Path for the checkpoint to be saved to. Default: 'checkpoint.pt' trace_func (function): trace print function. Default: print """ self.patience = patience self.verbose = verbose self.counter = 0 self.best_score = None self.early_stop = False self.val_loss_min = np.Inf self.delta = delta self.path = path self.trace_func = trace_func def save_checkpoint(self, val_loss, model): '''Saves model when validation loss decrease.''' if self.verbose: self.trace_func(f'Validation loss decreased ({self.val_loss_min:.6f} --> {val_loss:.6f}). Saving model ...') torch.save(model.state_dict(), self.path) self.val_loss_min = val_loss
[ 11748, 25064, 198, 17597, 13, 6978, 13, 33295, 7203, 40720, 4943, 198, 198, 2, 17634, 13246, 51, 31619, 103, 101, 167, 235, 116, 198, 198, 11748, 4566, 198, 198, 11748, 19798, 292, 355, 279, 67, 198, 11748, 299, 32152, 355, 45941, 198, 6738, 1341, 35720, 13, 3866, 36948, 1330, 1881, 21352, 27195, 12342, 198, 198, 11748, 28034, 198, 6738, 28034, 1330, 299, 77, 198, 11748, 28034, 13, 20471, 13, 45124, 355, 376, 198, 11748, 28034, 13, 40085, 355, 6436, 198, 6738, 28034, 13, 26791, 13, 7890, 1330, 16092, 292, 316, 11, 6060, 17401, 198, 11748, 1278, 84, 261, 21283, 79, 355, 299, 34431, 198, 6738, 256, 80, 36020, 1330, 256, 80, 36020, 11, 256, 80, 36020, 62, 11295, 2070, 628, 198, 198, 6738, 17634, 13246, 51, 13, 74, 2023, 83, 13, 26791, 1330, 651, 62, 30001, 7509, 198, 6738, 17634, 13246, 51, 13, 74, 2023, 83, 13, 9078, 13165, 354, 62, 74, 2023, 83, 1330, 651, 62, 9078, 13165, 354, 62, 74, 2023, 83, 62, 19849, 198, 198, 6738, 6121, 364, 1330, 7244, 54, 198, 2, 422, 6121, 364, 13, 40085, 1634, 1330, 25692, 929, 14993, 451, 27054, 5950, 198, 198, 6738, 6121, 364, 1330, 651, 62, 29127, 62, 15952, 5950, 62, 4480, 62, 31975, 929, 198, 198, 25202, 796, 28034, 13, 25202, 10786, 66, 15339, 6, 611, 28034, 13, 66, 15339, 13, 271, 62, 15182, 3419, 2073, 705, 36166, 11537, 198, 198, 4835, 19849, 11, 12776, 397, 796, 651, 62, 9078, 13165, 354, 62, 74, 2023, 83, 62, 19849, 3419, 198, 198, 2, 220, 169, 228, 254, 169, 223, 105, 167, 224, 246, 35975, 112, 168, 254, 222, 31619, 102, 242, 168, 226, 250, 167, 241, 250, 167, 98, 120, 11241, 7509, 168, 245, 238, 220, 169, 246, 116, 168, 114, 250, 198, 2, 23821, 121, 242, 169, 235, 120, 168, 232, 97, 167, 98, 120, 220, 169, 228, 254, 169, 223, 108, 168, 250, 120, 167, 94, 250, 31619, 100, 234, 167, 241, 250, 167, 232, 242, 220, 166, 111, 120, 168, 254, 243, 35975, 226, 23821, 230, 246, 169, 244, 231, 11, 23821, 251, 112, 31619, 243, 234, 220, 169, 228, 254, 169, 223, 105, 167, 224, 246, 35975, 112, 168, 254, 222, 167, 232, 242, 479, 2023, 83, 220, 169, 234, 101, 169, 224, 97, 168, 100, 222, 168, 245, 238, 23821, 252, 230, 167, 232, 242, 651, 62, 30001, 7509, 3419, 167, 98, 120, 23821, 8955, 168, 248, 102, 47991, 246, 166, 111, 254, 11, 198, 2, 220, 169, 228, 254, 169, 223, 108, 169, 247, 242, 167, 98, 120, 23821, 250, 226, 47991, 112, 220, 47991, 226, 168, 248, 242, 47991, 250, 31619, 233, 101, 168, 244, 112, 23821, 8955, 168, 254, 226, 35975, 222, 479, 2023, 83, 35975, 246, 12776, 397, 35975, 226, 23821, 8955, 168, 248, 102, 47991, 101, 13, 198, 2, 4591, 839, 167, 94, 250, 220, 169, 230, 105, 168, 252, 227, 47991, 112, 168, 243, 120, 220, 47991, 246, 167, 107, 222, 167, 94, 250, 2793, 796, 10352, 198, 198, 30001, 7509, 796, 651, 62, 30001, 7509, 3419, 198, 83, 482, 796, 299, 34431, 13, 7890, 13, 13246, 51, 4303, 30642, 7509, 7, 30001, 7509, 11, 12776, 397, 11, 2793, 796, 10352, 8, 198, 4798, 7, 69, 1549, 1990, 501, 1262, 25, 1391, 25202, 92, 11537, 628, 198, 19849, 62, 11250, 28, 11250, 13, 19849, 62, 11250, 628, 198, 220, 220, 220, 220, 198, 198, 4871, 12556, 1273, 33307, 25, 198, 220, 220, 220, 37227, 20457, 9911, 262, 3047, 611, 21201, 2994, 1595, 470, 2987, 706, 257, 1813, 16336, 526, 15931, 198, 220, 220, 220, 825, 11593, 15003, 834, 7, 944, 11, 16336, 28, 22, 11, 15942, 577, 28, 25101, 11, 25979, 28, 15, 11, 3108, 11639, 9122, 4122, 13, 457, 3256, 12854, 62, 20786, 28, 4798, 2599, 198, 220, 220, 220, 220, 220, 220, 220, 37227, 198, 220, 220, 220, 220, 220, 220, 220, 943, 14542, 25, 198, 220, 220, 220, 220, 220, 220, 220, 220, 220, 220, 220, 16336, 357, 600, 2599, 1374, 890, 284, 4043, 706, 938, 640, 21201, 2994, 6596, 13, 198, 220, 220, 220, 220, 220, 220, 220, 220, 220, 220, 220, 220, 220, 220, 220, 220, 220, 220, 220, 220, 220, 220, 220, 220, 220, 220, 220, 15161, 25, 767, 198, 220, 220, 220, 220, 220, 220, 220, 220, 220, 220, 220, 15942, 577, 357, 30388, 2599, 1002, 6407, 11, 20842, 257, 3275, 329, 1123, 21201, 2994, 9025, 13, 220, 198, 220, 220, 220, 220, 220, 220, 220, 220, 220, 220, 220, 220, 220, 220, 220, 220, 220, 220, 220, 220, 220, 220, 220, 220, 220, 220, 220, 15161, 25, 10352, 198, 220, 220, 220, 220, 220, 220, 220, 220, 220, 220, 220, 25979, 357, 22468, 2599, 26265, 1487, 287, 262, 20738, 12040, 284, 12780, 355, 281, 9025, 13, 198, 220, 220, 220, 220, 220, 220, 220, 220, 220, 220, 220, 220, 220, 220, 220, 220, 220, 220, 220, 220, 220, 220, 220, 220, 220, 220, 220, 15161, 25, 657, 198, 220, 220, 220, 220, 220, 220, 220, 220, 220, 220, 220, 3108, 357, 2536, 2599, 10644, 329, 262, 26954, 284, 307, 7448, 284, 13, 198, 220, 220, 220, 220, 220, 220, 220, 220, 220, 220, 220, 220, 220, 220, 220, 220, 220, 220, 220, 220, 220, 220, 220, 220, 220, 220, 220, 15161, 25, 705, 9122, 4122, 13, 457, 6, 198, 220, 220, 220, 220, 220, 220, 220, 220, 220, 220, 220, 12854, 62, 20786, 357, 8818, 2599, 12854, 3601, 2163, 13, 198, 220, 220, 220, 220, 220, 220, 220, 220, 220, 220, 220, 220, 220, 220, 220, 220, 220, 220, 220, 220, 220, 220, 220, 220, 220, 220, 220, 15161, 25, 3601, 220, 220, 220, 220, 220, 220, 220, 220, 220, 220, 220, 220, 198, 220, 220, 220, 220, 220, 220, 220, 37227, 198, 220, 220, 220, 220, 220, 220, 220, 2116, 13, 8071, 1240, 796, 16336, 198, 220, 220, 220, 220, 220, 220, 220, 2116, 13, 19011, 577, 796, 15942, 577, 198, 220, 220, 220, 220, 220, 220, 220, 2116, 13, 24588, 796, 657, 198, 220, 220, 220, 220, 220, 220, 220, 2116, 13, 13466, 62, 26675, 796, 6045, 198, 220, 220, 220, 220, 220, 220, 220, 2116, 13, 11458, 62, 11338, 796, 10352, 198, 220, 220, 220, 220, 220, 220, 220, 2116, 13, 2100, 62, 22462, 62, 1084, 796, 45941, 13, 18943, 198, 220, 220, 220, 220, 220, 220, 220, 2116, 13, 67, 12514, 796, 25979, 198, 220, 220, 220, 220, 220, 220, 220, 2116, 13, 6978, 796, 3108, 198, 220, 220, 220, 220, 220, 220, 220, 2116, 13, 40546, 62, 20786, 796, 12854, 62, 20786, 628, 220, 220, 220, 825, 3613, 62, 9122, 4122, 7, 944, 11, 1188, 62, 22462, 11, 2746, 2599, 198, 220, 220, 220, 220, 220, 220, 220, 705, 7061, 50, 3080, 2746, 618, 21201, 2994, 10070, 2637, 7061, 198, 220, 220, 220, 220, 220, 220, 220, 611, 2116, 13, 19011, 577, 25, 198, 220, 220, 220, 220, 220, 220, 220, 220, 220, 220, 220, 2116, 13, 40546, 62, 20786, 7, 69, 6, 7762, 24765, 2994, 11832, 37913, 944, 13, 2100, 62, 22462, 62, 1084, 25, 13, 21, 69, 92, 14610, 1391, 2100, 62, 22462, 25, 13, 21, 69, 92, 737, 220, 34689, 2746, 2644, 11537, 198, 220, 220, 220, 220, 220, 220, 220, 28034, 13, 21928, 7, 19849, 13, 5219, 62, 11600, 22784, 2116, 13, 6978, 8, 198, 220, 220, 220, 220, 220, 220, 220, 2116, 13, 2100, 62, 22462, 62, 1084, 796, 1188, 62, 22462, 198 ]
2.075623
1,243
import urllib.parse from .saucenao import get_saucenao_detail, SauceNAOError
[ 11748, 2956, 297, 571, 13, 29572, 198, 198, 6738, 764, 82, 14272, 268, 5488, 1330, 651, 62, 82, 14272, 268, 5488, 62, 49170, 11, 37618, 4535, 46, 12331, 628 ]
2.724138
29
A = True B = False print(A and B) print(A or B)
[ 32, 796, 6407, 198, 33, 796, 10352, 198, 4798, 7, 32, 290, 347, 8, 198, 4798, 7, 32, 393, 347, 8, 198 ]
2.181818
22
#!/usr/bin/env python # Author : Pierre Schnizer """ Collection of Callbacks systems for pygsl. They follow the GSL definitions as close as possible. Instead os a struct python classes are used. All solvers accept a C void pointer, which is passed to the callback. In Pygsl this is an abitrary python object. See the doc strings of the various classes for further detail. """ from . import _callback class gsl_function(_gsl_function): """ This class defines the callbacks known as gsl_function to gsl. e.g to supply the function f: def f(x, params): a = params[0] b = parmas[1] c = params[3] return a * x ** 2 + b * x + c to some solver, use function = gsl_function(f, params) """ initfunc = _callback.gsl_function_init freefunc = _callback.gsl_function_free class gsl_function_fdf(_gsl_function_fdf): """ This class defines the callbacks known as gsl_function_fdf to gsl. e.g to supply the function f: def f(x, None): return exp(2 * x) def df(x, None): return 2 * exp(2 * x) def fdf(x, None): myf = f(x, None) mydf = df(x, None) return myf, mydf to some solver, accepting gsl_function_fdf, use function = gsl_function_fdf(f, df, fdf, params) """ initfunc = _callback.gsl_function_init_fdf freefunc = _callback.gsl_function_free_fdf class gsl_multiroot_function(_gsl_function): """ This class defines the callbacks for gsl_multiroot_function. To supply the function rosenbrock define the function: def rosenbrock_f(x, params): a = params[0] b = params[1] y = copy.copy(x) y[0] = a * (1 - x[0]) y[1] = b * (x[1] - x[0] * x[0]) return y sys = multiroots.gsl_multiroot_function(rosenbrock_f, params, 2) """ initfunc = _callback.gsl_multiroot_function_init freefunc = _callback.gsl_multiroot_function_free class gsl_multiroot_function_fdf(_gsl_function_fdf): """ This class defines the callbacks for gsl_multiroot_function. To supply the function rosenbrock define the functions: def rosenbrock_f(x, params): a = params[0] b = params[1] y = copy.copy(x) y[0] = a * (1 - x[0]) y[1] = b * (x[1] - x[0] * x[0]) return y def rosenbrock_df(x, params): a = params[0] b = params[1] df = Numeric.zeros((x.shape[0], x.shape[0]), Numeric.Float) df[0,0] = -a df[0,1] = 0 df[1,0] = -2 * b * x[0] df[1,1] = b return df def rosenbrock_fdf(x, params): f = rosenbrock_f(x, params) df = rosenbrock_df(x, params) return f, df # dimension of x size = 2 sys = multiroots.gsl_multiroot_function(rosenbrock_f, rosenbrock_df, rosenbrock_fdf, params, size) """ initfunc = _callback.gsl_multiroot_function_init_fdf freefunc = _callback.gsl_multiroot_function_free_fdf class gsl_multifit_function(_gsl_function): """ This class defines the callbacks for gsl_multimin_function. To fit a exponential function to data write the following function: def exp_f(x, params): A = x[0] lambda_ = x[1] b = x[2] t= params[0] yi = params[1] sigma = params[2] Yi = A * exp(-lambda_ * t) + b f = yi - Yi / sigma return f # Number of data samples n = len(data) # Number of paramters p = 3 multifit_nlin.gsl_multifit_function(exp_f, data, n, p) """ initfunc = _callback.gsl_multifit_function_init freefunc = _callback.gsl_multifit_function_free class gsl_multifit_function_fdf(_gsl_function_fdf): """ This class defines the callbacks for gsl_multimin_function. def exp_f(x, params): A = x[0] lambda_ = x[1] b = x[2] t= params[0] yi = params[1] sigma = params[2] Yi = A * exp(-lambda_ * t) + b f = yi - Yi / sigma return f def exp_df(x, params): A = x[0] lambda_ = x[1] b = x[2] t= params[0] yi = params[1] sigma = params[2] e = exp(-lambda_ * t) e_s = e/sigma df = Numeric.array((e_s, -t * A * e_s, 1/sigma)) df = Numeric.transpose(df) print df.shape return df def exp_fdf(x, params): f = exp_f(x, params) df = exp_df(x, params) return f, df # Number of data samples n = len(data) # Number of paramters p = 3 multifit_nlin.gsl_multifit_function_fdf(exp_f, exp_df, exp_fdf, data, n, p) """ initfunc = _callback.gsl_multifit_function_init_fdf freefunc = _callback.gsl_multifit_function_free_fdf class gsl_multimin_function(gsl_multiroot_function): """ This class defines the callbacks for gsl_multimin_function. The following example function defines a simple paraboloid with two parameters. To supply the system define the function: def my_f(v, params): x = v[0] y = v[1] dp = params t1 = (x - dp[0]) t2 = (y - dp[1]) f = 10.0 * t1 * t1 + 20.0 * t2 * t2 + 30.0 return f # dimension of x size = 2 sys = multimin.gsl_multifit_function(my_f, params, 2) """ initfunc = _callback.gsl_multimin_function_init freefunc = _callback.gsl_multimin_function_free class gsl_multimin_function_fdf(gsl_multiroot_function_fdf): """ This class defines the callbacks for gsl_multimin_function_fdf. The following example function defines a simple paraboloid with two parameters. To supply the system define the function: def my_f(v, params): x = v[0] y = v[1] dp = params t1 = (x - dp[0]) t2 = (y - dp[1]) f = 10.0 * t1 * t1 + 20.0 * t2 * t2 + 30.0 return f def my_df(v, params): x = v[0] y = v[1] df = Numeric.zeros(v.shape, Numeric.Float) dp = params df[0] = 20. * (x - dp[0]) df[1] = 40. * (y - dp[1]) return df def my_fdf(v, params): f = my_f(v, params) df = my_df(v,params) return f, df # dimension of x size = 2 sys = multimin.gsl_multifit_function(my_f, my_df, my_fdf, params, size) """ initfunc = _callback.gsl_multimin_function_init_fdf freefunc = _callback.gsl_multimin_function_free_fdf class gsl_monte_function(gsl_multiroot_function): """ This class defines the callbacks for gsl_monte_function. """ initfunc = _callback.gsl_monte_function_init freefunc = _callback.gsl_monte_function_free
[ 2, 48443, 14629, 14, 8800, 14, 24330, 21015, 198, 2, 6434, 1058, 21204, 45606, 7509, 220, 198, 37811, 198, 36307, 286, 4889, 10146, 3341, 329, 220, 12972, 70, 6649, 13, 1119, 1061, 262, 46326, 17336, 355, 198, 19836, 355, 1744, 13, 5455, 28686, 257, 2878, 21015, 6097, 389, 973, 13, 198, 198, 3237, 1540, 690, 2453, 257, 327, 7951, 17562, 11, 543, 318, 3804, 284, 262, 23838, 13, 554, 9485, 70, 6649, 198, 5661, 318, 281, 450, 270, 11619, 21015, 2134, 13, 220, 4091, 262, 2205, 13042, 286, 262, 2972, 6097, 198, 1640, 2252, 3703, 13, 198, 198, 37811, 198, 6738, 764, 1330, 4808, 47423, 628, 198, 4871, 308, 6649, 62, 8818, 28264, 70, 6649, 62, 8818, 2599, 198, 220, 220, 220, 37227, 198, 220, 220, 220, 770, 1398, 15738, 262, 869, 10146, 1900, 355, 308, 6649, 62, 8818, 284, 198, 220, 220, 220, 308, 6649, 13, 628, 220, 220, 220, 304, 13, 70, 284, 5127, 262, 2163, 277, 25, 198, 220, 220, 220, 220, 198, 220, 220, 220, 825, 277, 7, 87, 11, 42287, 2599, 198, 220, 220, 220, 220, 220, 220, 220, 257, 796, 42287, 58, 15, 60, 198, 220, 220, 220, 220, 220, 220, 220, 275, 796, 1582, 5356, 58, 16, 60, 198, 220, 220, 220, 220, 220, 220, 220, 269, 796, 42287, 58, 18, 60, 198, 220, 220, 220, 220, 220, 220, 220, 1441, 257, 1635, 2124, 12429, 362, 1343, 275, 1635, 2124, 1343, 269, 628, 220, 220, 220, 284, 617, 1540, 332, 11, 779, 628, 220, 220, 220, 2163, 796, 308, 6649, 62, 8818, 7, 69, 11, 42287, 8, 198, 220, 220, 220, 37227, 628, 220, 220, 220, 2315, 20786, 796, 220, 4808, 47423, 13, 70, 6649, 62, 8818, 62, 15003, 198, 220, 220, 220, 1479, 20786, 796, 220, 4808, 47423, 13, 70, 6649, 62, 8818, 62, 5787, 198, 220, 220, 220, 220, 198, 4871, 308, 6649, 62, 8818, 62, 69, 7568, 28264, 70, 6649, 62, 8818, 62, 69, 7568, 2599, 198, 220, 220, 220, 37227, 198, 220, 220, 220, 770, 1398, 15738, 262, 869, 10146, 1900, 355, 308, 6649, 62, 8818, 62, 69, 7568, 284, 198, 220, 220, 220, 308, 6649, 13, 628, 220, 220, 220, 304, 13, 70, 284, 5127, 262, 2163, 277, 25, 198, 220, 220, 220, 220, 198, 220, 220, 220, 825, 277, 7, 87, 11, 6045, 2599, 198, 220, 220, 220, 220, 220, 220, 220, 1441, 1033, 7, 17, 1635, 2124, 8, 628, 220, 220, 220, 825, 47764, 7, 87, 11, 6045, 2599, 198, 220, 220, 220, 220, 220, 220, 220, 1441, 362, 1635, 1033, 7, 17, 1635, 2124, 8, 628, 220, 220, 220, 825, 277, 7568, 7, 87, 11, 6045, 2599, 198, 220, 220, 220, 220, 220, 220, 220, 616, 69, 220, 796, 220, 277, 7, 87, 11, 6045, 8, 198, 220, 220, 220, 220, 220, 220, 220, 616, 7568, 796, 47764, 7, 87, 11, 6045, 8, 198, 220, 220, 220, 220, 220, 220, 220, 1441, 616, 69, 11, 616, 7568, 628, 198, 220, 220, 220, 284, 617, 1540, 332, 11, 12598, 308, 6649, 62, 8818, 62, 69, 7568, 11, 779, 628, 220, 220, 220, 2163, 796, 308, 6649, 62, 8818, 62, 69, 7568, 7, 69, 11, 47764, 11, 277, 7568, 11, 42287, 8, 198, 220, 220, 220, 37227, 198, 220, 220, 220, 2315, 20786, 796, 220, 4808, 47423, 13, 70, 6649, 62, 8818, 62, 15003, 62, 69, 7568, 198, 220, 220, 220, 1479, 20786, 796, 220, 4808, 47423, 13, 70, 6649, 62, 8818, 62, 5787, 62, 69, 7568, 628, 198, 198, 4871, 308, 6649, 62, 16680, 7058, 313, 62, 8818, 28264, 70, 6649, 62, 8818, 2599, 198, 220, 220, 220, 37227, 198, 220, 220, 220, 770, 1398, 15738, 262, 869, 10146, 329, 308, 6649, 62, 16680, 7058, 313, 62, 8818, 13, 628, 220, 220, 220, 1675, 5127, 262, 2163, 686, 6248, 7957, 694, 8160, 262, 2163, 25, 198, 220, 220, 220, 220, 220, 220, 220, 220, 198, 220, 220, 220, 825, 686, 6248, 7957, 694, 62, 69, 7, 87, 11, 42287, 2599, 198, 220, 220, 220, 220, 220, 220, 220, 257, 796, 42287, 58, 15, 60, 198, 220, 220, 220, 220, 220, 220, 220, 275, 796, 42287, 58, 16, 60, 198, 220, 220, 220, 220, 220, 220, 220, 331, 796, 4866, 13, 30073, 7, 87, 8, 198, 220, 220, 220, 220, 220, 220, 220, 331, 58, 15, 60, 796, 257, 1635, 357, 16, 532, 2124, 58, 15, 12962, 198, 220, 220, 220, 220, 220, 220, 220, 331, 58, 16, 60, 796, 275, 1635, 357, 87, 58, 16, 60, 532, 2124, 58, 15, 60, 1635, 2124, 58, 15, 12962, 198, 220, 220, 220, 220, 220, 220, 220, 1441, 331, 628, 220, 220, 220, 25064, 796, 5021, 19150, 13, 70, 6649, 62, 16680, 7058, 313, 62, 8818, 7, 4951, 268, 7957, 694, 62, 69, 11, 42287, 11, 362, 8, 198, 220, 220, 220, 37227, 198, 220, 220, 220, 2315, 20786, 796, 220, 4808, 47423, 13, 70, 6649, 62, 16680, 7058, 313, 62, 8818, 62, 15003, 198, 220, 220, 220, 1479, 20786, 796, 220, 4808, 47423, 13, 70, 6649, 62, 16680, 7058, 313, 62, 8818, 62, 5787, 628, 198, 198, 4871, 308, 6649, 62, 16680, 7058, 313, 62, 8818, 62, 69, 7568, 28264, 70, 6649, 62, 8818, 62, 69, 7568, 2599, 198, 220, 220, 220, 37227, 198, 220, 220, 220, 770, 1398, 15738, 262, 869, 10146, 329, 308, 6649, 62, 16680, 7058, 313, 62, 8818, 13, 198, 220, 220, 220, 220, 198, 220, 220, 220, 1675, 5127, 262, 2163, 686, 6248, 7957, 694, 8160, 262, 5499, 25, 198, 220, 220, 220, 220, 198, 220, 220, 220, 825, 686, 6248, 7957, 694, 62, 69, 7, 87, 11, 42287, 2599, 198, 220, 220, 220, 220, 220, 220, 220, 257, 796, 42287, 58, 15, 60, 198, 220, 220, 220, 220, 220, 220, 220, 275, 796, 42287, 58, 16, 60, 198, 220, 220, 220, 220, 220, 220, 220, 331, 796, 4866, 13, 30073, 7, 87, 8, 198, 220, 220, 220, 220, 220, 220, 220, 331, 58, 15, 60, 796, 257, 1635, 357, 16, 532, 2124, 58, 15, 12962, 198, 220, 220, 220, 220, 220, 220, 220, 331, 58, 16, 60, 796, 275, 1635, 357, 87, 58, 16, 60, 532, 2124, 58, 15, 60, 1635, 2124, 58, 15, 12962, 198, 220, 220, 220, 220, 220, 220, 220, 1441, 331, 198, 220, 220, 220, 220, 198, 220, 220, 220, 825, 686, 6248, 7957, 694, 62, 7568, 7, 87, 11, 42287, 2599, 198, 220, 220, 220, 220, 220, 220, 220, 257, 796, 42287, 58, 15, 60, 198, 220, 220, 220, 220, 220, 220, 220, 275, 796, 42287, 58, 16, 60, 198, 220, 220, 220, 220, 220, 220, 220, 47764, 796, 399, 39223, 13, 9107, 418, 19510, 87, 13, 43358, 58, 15, 4357, 2124, 13, 43358, 58, 15, 46570, 399, 39223, 13, 43879, 8, 198, 220, 220, 220, 220, 220, 220, 220, 47764, 58, 15, 11, 15, 60, 796, 532, 64, 198, 220, 220, 220, 220, 220, 220, 220, 47764, 58, 15, 11, 16, 60, 796, 657, 198, 220, 220, 220, 220, 220, 220, 220, 47764, 58, 16, 11, 15, 60, 796, 532, 17, 1635, 275, 1635, 2124, 58, 15, 60, 198, 220, 220, 220, 220, 220, 220, 220, 47764, 58, 16, 11, 16, 60, 796, 275, 198, 220, 220, 220, 220, 220, 220, 220, 1441, 47764, 198, 220, 220, 220, 220, 198, 220, 220, 220, 825, 686, 6248, 7957, 694, 62, 69, 7568, 7, 87, 11, 42287, 2599, 198, 220, 220, 220, 220, 220, 220, 220, 277, 796, 686, 6248, 7957, 694, 62, 69, 7, 87, 11, 42287, 8, 198, 220, 220, 220, 220, 220, 220, 220, 47764, 796, 686, 6248, 7957, 694, 62, 7568, 7, 87, 11, 42287, 8, 198, 220, 220, 220, 220, 220, 220, 220, 1441, 277, 11, 47764, 628, 220, 220, 220, 1303, 15793, 286, 2124, 198, 220, 220, 220, 2546, 796, 362, 198, 220, 220, 220, 25064, 796, 5021, 19150, 13, 70, 6649, 62, 16680, 7058, 313, 62, 8818, 7, 4951, 268, 7957, 694, 62, 69, 11, 686, 6248, 7957, 694, 62, 7568, 11, 198, 220, 220, 220, 220, 220, 220, 220, 220, 220, 220, 220, 220, 220, 220, 220, 220, 220, 220, 220, 220, 220, 220, 220, 220, 220, 220, 220, 220, 220, 220, 220, 220, 220, 220, 220, 220, 220, 220, 220, 220, 220, 220, 220, 686, 6248, 7957, 694, 62, 69, 7568, 11, 42287, 11, 2546, 8, 198, 220, 220, 220, 37227, 198, 220, 220, 220, 2315, 20786, 796, 220, 4808, 47423, 13, 70, 6649, 62, 16680, 7058, 313, 62, 8818, 62, 15003, 62, 69, 7568, 198, 220, 220, 220, 1479, 20786, 796, 220, 4808, 47423, 13, 70, 6649, 62, 16680, 7058, 313, 62, 8818, 62, 5787, 62, 69, 7568, 628, 198, 4871, 308, 6649, 62, 16680, 361, 270, 62, 8818, 28264, 70, 6649, 62, 8818, 2599, 198, 220, 220, 220, 37227, 198, 220, 220, 220, 770, 1398, 15738, 262, 869, 10146, 329, 308, 6649, 62, 16680, 320, 259, 62, 8818, 13, 628, 220, 220, 220, 1675, 4197, 257, 39682, 2163, 284, 1366, 3551, 262, 1708, 2163, 25, 198, 220, 220, 220, 220, 198, 220, 220, 220, 825, 1033, 62, 69, 7, 87, 11, 42287, 2599, 198, 220, 220, 220, 220, 220, 220, 220, 317, 796, 2124, 58, 15, 60, 198, 220, 220, 220, 220, 220, 220, 220, 37456, 62, 796, 2124, 58, 16, 60, 198, 220, 220, 220, 220, 220, 220, 220, 275, 796, 2124, 58, 17, 60, 198, 220, 220, 220, 220, 220, 220, 220, 256, 28, 42287, 58, 15, 60, 198, 220, 220, 220, 220, 220, 220, 220, 331, 72, 796, 42287, 58, 16, 60, 198, 220, 220, 220, 220, 220, 220, 220, 264, 13495, 796, 42287, 58, 17, 60, 198, 220, 220, 220, 220, 220, 220, 220, 26463, 796, 317, 1635, 1033, 32590, 50033, 62, 1635, 256, 8, 1343, 275, 198, 220, 220, 220, 220, 220, 220, 220, 277, 796, 331, 72, 532, 26463, 1220, 264, 13495, 198, 220, 220, 220, 220, 220, 220, 220, 1441, 277, 628, 220, 220, 220, 1303, 7913, 286, 1366, 8405, 198, 220, 220, 220, 299, 796, 18896, 7, 7890, 8, 198, 220, 220, 220, 1303, 7913, 286, 5772, 1010, 198, 220, 220, 220, 279, 220, 796, 513, 198, 220, 220, 220, 43543, 270, 62, 77, 2815, 13, 70, 6649, 62, 16680, 361, 270, 62, 8818, 7, 11201, 62, 69, 11, 1366, 11, 299, 11, 279, 8, 198, 220, 220, 220, 37227, 628, 220, 220, 220, 2315, 20786, 796, 220, 4808, 47423, 13, 70, 6649, 62, 16680, 361, 270, 62, 8818, 62, 15003, 198, 220, 220, 220, 1479, 20786, 796, 220, 4808, 47423, 13, 70, 6649, 62, 16680, 361, 270, 62, 8818, 62, 5787, 628, 220, 220, 220, 220, 198, 4871, 308, 6649, 62, 16680, 361, 270, 62, 8818, 62, 69, 7568, 28264, 70, 6649, 62, 8818, 62, 69, 7568, 2599, 198, 220, 220, 220, 37227, 198, 220, 220, 220, 770, 1398, 15738, 262, 869, 10146, 329, 308, 6649, 62, 16680, 320, 259, 62, 8818, 13, 198, 220, 220, 220, 825, 1033, 62, 69, 7, 87, 11, 42287, 2599, 198, 220, 220, 220, 220, 220, 220, 220, 317, 796, 2124, 58, 15, 60, 198, 220, 220, 220, 220, 220, 220, 220, 37456, 62, 796, 2124, 58, 16, 60, 198, 220, 220, 220, 220, 220, 220, 220, 275, 796, 2124, 58, 17, 60, 198, 220, 220, 220, 220, 220, 220, 220, 256, 28, 42287, 58, 15, 60, 198, 220, 220, 220, 220, 220, 220, 220, 331, 72, 796, 42287, 58, 16, 60, 198, 220, 220, 220, 220, 220, 220, 220, 264, 13495, 796, 42287, 58, 17, 60, 198, 220, 220, 220, 220, 220, 220, 220, 26463, 796, 317, 1635, 1033, 32590, 50033, 62, 1635, 256, 8, 1343, 275, 198, 220, 220, 220, 220, 220, 220, 220, 277, 796, 331, 72, 532, 26463, 1220, 264, 13495, 198, 220, 220, 220, 220, 220, 220, 220, 1441, 277, 628, 220, 220, 220, 825, 1033, 62, 7568, 7, 87, 11, 42287, 2599, 198, 220, 220, 220, 220, 220, 220, 220, 317, 796, 2124, 58, 15, 60, 198, 220, 220, 220, 220, 220, 220, 220, 37456, 62, 796, 2124, 58, 16, 60, 198, 220, 220, 220, 220, 220, 220, 220, 275, 796, 2124, 58, 17, 60, 198, 220, 220, 220, 220, 220, 220, 220, 256, 28, 42287, 58, 15, 60, 198, 220, 220, 220, 220, 220, 220, 220, 331, 72, 796, 42287, 58, 16, 60, 198, 220, 220, 220, 220, 220, 220, 220, 264, 13495, 796, 42287, 58, 17, 60, 198, 220, 220, 220, 220, 220, 220, 220, 304, 796, 1033, 32590, 50033, 62, 1635, 256, 8, 198, 220, 220, 220, 220, 220, 220, 220, 304, 62, 82, 796, 304, 14, 82, 13495, 198, 220, 220, 220, 220, 220, 220, 220, 47764, 796, 399, 39223, 13, 18747, 19510, 68, 62, 82, 11, 532, 83, 1635, 317, 1635, 304, 62, 82, 11, 352, 14, 82, 13495, 4008, 198, 220, 220, 220, 220, 220, 220, 220, 47764, 796, 399, 39223, 13, 7645, 3455, 7, 7568, 8, 198, 220, 220, 220, 220, 220, 220, 220, 3601, 47764, 13, 43358, 198, 220, 220, 220, 220, 220, 220, 220, 1441, 47764, 628, 220, 220, 220, 825, 1033, 62, 69, 7568, 7, 87, 11, 42287, 2599, 198, 220, 220, 220, 220, 220, 220, 220, 277, 796, 1033, 62, 69, 7, 87, 11, 42287, 8, 198, 220, 220, 220, 220, 220, 220, 220, 47764, 796, 1033, 62, 7568, 7, 87, 11, 42287, 8, 198, 220, 220, 220, 220, 220, 220, 220, 1441, 277, 11, 47764, 628, 220, 220, 220, 1303, 7913, 286, 1366, 8405, 198, 220, 220, 220, 299, 796, 18896, 7, 7890, 8, 198, 220, 220, 220, 1303, 7913, 286, 5772, 1010, 198, 220, 220, 220, 279, 220, 796, 513, 198, 220, 220, 220, 43543, 270, 62, 77, 2815, 13, 70, 6649, 62, 16680, 361, 270, 62, 8818, 62, 69, 7568, 7, 11201, 62, 69, 11, 1033, 62, 7568, 11, 1033, 62, 69, 7568, 11, 1366, 11, 299, 11, 279, 8, 628, 220, 220, 220, 37227, 198, 220, 220, 220, 2315, 20786, 796, 220, 4808, 47423, 13, 70, 6649, 62, 16680, 361, 270, 62, 8818, 62, 15003, 62, 69, 7568, 198, 220, 220, 220, 1479, 20786, 796, 220, 4808, 47423, 13, 70, 6649, 62, 16680, 361, 270, 62, 8818, 62, 5787, 62, 69, 7568, 198, 198, 4871, 308, 6649, 62, 16680, 320, 259, 62, 8818, 7, 70, 6649, 62, 16680, 7058, 313, 62, 8818, 2599, 220, 220, 220, 220, 198, 220, 220, 220, 37227, 198, 220, 220, 220, 770, 1398, 15738, 262, 869, 10146, 329, 308, 6649, 62, 16680, 320, 259, 62, 8818, 13, 628, 220, 220, 220, 383, 1708, 1672, 2163, 15738, 257, 2829, 1582, 28426, 1868, 351, 734, 198, 220, 220, 220, 10007, 13, 628, 220, 220, 220, 1675, 5127, 220, 262, 1080, 8160, 262, 2163, 25, 198, 220, 220, 220, 825, 616, 62, 69, 7, 85, 11, 42287, 2599, 198, 220, 220, 220, 220, 220, 220, 220, 2124, 796, 410, 58, 15, 60, 198, 220, 220, 220, 220, 220, 220, 220, 331, 796, 410, 58, 16, 60, 198, 220, 220, 220, 220, 198, 220, 220, 220, 220, 220, 220, 220, 288, 79, 796, 42287, 198, 220, 220, 220, 220, 220, 220, 220, 256, 16, 220, 796, 357, 87, 532, 288, 79, 58, 15, 12962, 198, 220, 220, 220, 220, 220, 220, 220, 256, 17, 220, 796, 357, 88, 532, 288, 79, 58, 16, 12962, 198, 220, 220, 220, 220, 220, 220, 220, 277, 796, 838, 13, 15, 1635, 256, 16, 1635, 256, 16, 1343, 1160, 13, 15, 1635, 256, 17, 1635, 256, 17, 1343, 1542, 13, 15, 198, 220, 220, 220, 220, 220, 220, 220, 1441, 277, 220, 198, 220, 220, 220, 220, 198, 220, 220, 220, 1303, 15793, 286, 2124, 198, 220, 220, 220, 2546, 796, 362, 628, 220, 220, 220, 25064, 796, 43104, 259, 13, 70, 6649, 62, 16680, 361, 270, 62, 8818, 7, 1820, 62, 69, 11, 42287, 11, 362, 8, 198, 220, 220, 220, 37227, 628, 220, 220, 220, 2315, 20786, 796, 220, 4808, 47423, 13, 70, 6649, 62, 16680, 320, 259, 62, 8818, 62, 15003, 198, 220, 220, 220, 1479, 20786, 796, 220, 4808, 47423, 13, 70, 6649, 62, 16680, 320, 259, 62, 8818, 62, 5787, 198, 198, 4871, 308, 6649, 62, 16680, 320, 259, 62, 8818, 62, 69, 7568, 7, 70, 6649, 62, 16680, 7058, 313, 62, 8818, 62, 69, 7568, 2599, 198, 220, 220, 220, 37227, 198, 220, 220, 220, 770, 1398, 15738, 262, 869, 10146, 329, 308, 6649, 62, 16680, 320, 259, 62, 8818, 62, 69, 7568, 13, 628, 220, 220, 220, 383, 1708, 1672, 2163, 15738, 257, 2829, 1582, 28426, 1868, 351, 734, 198, 220, 220, 220, 10007, 13, 628, 220, 220, 220, 1675, 5127, 220, 262, 1080, 8160, 262, 2163, 25, 198, 220, 220, 220, 825, 616, 62, 69, 7, 85, 11, 42287, 2599, 198, 220, 220, 220, 220, 220, 220, 220, 2124, 796, 410, 58, 15, 60, 198, 220, 220, 220, 220, 220, 220, 220, 331, 796, 410, 58, 16, 60, 198, 220, 220, 220, 220, 198, 220, 220, 220, 220, 220, 220, 220, 288, 79, 796, 42287, 198, 220, 220, 220, 220, 220, 220, 220, 256, 16, 220, 796, 357, 87, 532, 288, 79, 58, 15, 12962, 198, 220, 220, 220, 220, 220, 220, 220, 256, 17, 220, 796, 357, 88, 532, 288, 79, 58, 16, 12962, 198, 220, 220, 220, 220, 220, 220, 220, 277, 796, 838, 13, 15, 1635, 256, 16, 1635, 256, 16, 1343, 1160, 13, 15, 1635, 256, 17, 1635, 256, 17, 1343, 1542, 13, 15, 198, 220, 220, 220, 220, 220, 220, 220, 1441, 277, 198, 220, 220, 220, 825, 616, 62, 7568, 7, 85, 11, 42287, 2599, 198, 220, 220, 220, 220, 220, 220, 220, 2124, 796, 410, 58, 15, 60, 198, 220, 220, 220, 220, 220, 220, 220, 331, 796, 410, 58, 16, 60, 198, 220, 220, 220, 220, 220, 220, 220, 47764, 796, 399, 39223, 13, 9107, 418, 7, 85, 13, 43358, 11, 399, 39223, 13, 43879, 8, 198, 220, 220, 220, 220, 220, 220, 220, 288, 79, 796, 42287, 198, 220, 220, 220, 220, 220, 220, 220, 47764, 58, 15, 60, 796, 1160, 13, 1635, 357, 87, 532, 288, 79, 58, 15, 12962, 198, 220, 220, 220, 220, 220, 220, 220, 47764, 58, 16, 60, 796, 2319, 13, 1635, 357, 88, 532, 288, 79, 58, 16, 12962, 198, 220, 220, 220, 220, 220, 220, 220, 1441, 47764, 628, 220, 220, 220, 825, 616, 62, 69, 7568, 7, 85, 11, 42287, 2599, 198, 220, 220, 220, 220, 220, 220, 220, 277, 796, 616, 62, 69, 7, 85, 11, 42287, 8, 198, 220, 220, 220, 220, 220, 220, 220, 47764, 796, 616, 62, 7568, 7, 85, 11, 37266, 8, 198, 220, 220, 220, 220, 220, 220, 220, 1441, 277, 11, 47764, 628, 220, 220, 220, 220, 198, 220, 220, 220, 1303, 15793, 286, 2124, 198, 220, 220, 220, 2546, 796, 362, 198, 220, 220, 220, 25064, 796, 43104, 259, 13, 70, 6649, 62, 16680, 361, 270, 62, 8818, 7, 1820, 62, 69, 11, 616, 62, 7568, 11, 616, 62, 69, 7568, 11, 42287, 11, 2546, 8, 198, 220, 220, 220, 37227, 628, 220, 220, 220, 2315, 20786, 796, 220, 4808, 47423, 13, 70, 6649, 62, 16680, 320, 259, 62, 8818, 62, 15003, 62, 69, 7568, 198, 220, 220, 220, 1479, 20786, 796, 220, 4808, 47423, 13, 70, 6649, 62, 16680, 320, 259, 62, 8818, 62, 5787, 62, 69, 7568, 198, 198, 4871, 308, 6649, 62, 2144, 660, 62, 8818, 7, 70, 6649, 62, 16680, 7058, 313, 62, 8818, 2599, 220, 220, 220, 220, 198, 220, 220, 220, 37227, 198, 220, 220, 220, 770, 1398, 15738, 262, 869, 10146, 329, 308, 6649, 62, 2144, 660, 62, 8818, 13, 628, 220, 220, 220, 37227, 628, 220, 220, 220, 2315, 20786, 796, 220, 4808, 47423, 13, 70, 6649, 62, 2144, 660, 62, 8818, 62, 15003, 198, 220, 220, 220, 1479, 20786, 796, 220, 4808, 47423, 13, 70, 6649, 62, 2144, 660, 62, 8818, 62, 5787, 198 ]
2.066425
3,312
import argparse if __name__ == "__main__": main()
[ 11748, 1822, 29572, 628, 198, 198, 361, 11593, 3672, 834, 6624, 366, 834, 12417, 834, 1298, 198, 220, 220, 220, 1388, 3419 ]
2.545455
22
from collections import Counter def partial_digest(distances): '''Returns a set whose positive pairwise differences generate 'distances'.''' # Initialize variables. X = {0} width = max(distances) # Create lambda functions for multiset operations. new_dist = lambda y, S: Counter(abs(y-s) for s in S) containment = lambda a, b: all(a[x] <= b[x] for x in a) # Create the multiset which generates 'distances'. while len(distances) > 0: y = max(distances) if containment(new_dist(y, X), distances): X |= {y} distances -= new_dist(y, X) else: X |= {width - y} distances -= new_dist(width - y, X) return X def main(): '''Main call. Reads, runs, and saves problem specific data.''' # Read the input data. with open('data/data.dat') as input_data: distances = Counter(map(int,input_data.read().strip().split())) # Get the partial digest. X = sorted(list(partial_digest(distances))) # Print and save the answer. print ' '.join(map(str, X)) if __name__ == '__main__': main()
[ 6738, 17268, 1330, 15034, 628, 198, 4299, 13027, 62, 12894, 395, 7, 17080, 1817, 2599, 198, 220, 220, 220, 705, 7061, 35561, 257, 900, 3025, 3967, 5166, 3083, 5400, 7716, 705, 17080, 1817, 6, 2637, 7061, 198, 220, 220, 220, 1303, 20768, 1096, 9633, 13, 198, 220, 220, 220, 1395, 796, 1391, 15, 92, 198, 220, 220, 220, 9647, 796, 3509, 7, 17080, 1817, 8, 628, 220, 220, 220, 1303, 13610, 37456, 5499, 329, 1963, 271, 316, 4560, 13, 198, 220, 220, 220, 649, 62, 17080, 796, 37456, 331, 11, 311, 25, 15034, 7, 8937, 7, 88, 12, 82, 8, 329, 264, 287, 311, 8, 198, 220, 220, 220, 37149, 796, 37456, 257, 11, 275, 25, 477, 7, 64, 58, 87, 60, 19841, 275, 58, 87, 60, 329, 2124, 287, 257, 8, 628, 220, 220, 220, 1303, 13610, 262, 1963, 271, 316, 543, 18616, 705, 17080, 1817, 4458, 198, 220, 220, 220, 981, 18896, 7, 17080, 1817, 8, 1875, 657, 25, 198, 220, 220, 220, 220, 220, 220, 220, 331, 796, 3509, 7, 17080, 1817, 8, 198, 220, 220, 220, 220, 220, 220, 220, 611, 37149, 7, 3605, 62, 17080, 7, 88, 11, 1395, 828, 18868, 2599, 198, 220, 220, 220, 220, 220, 220, 220, 220, 220, 220, 220, 1395, 930, 28, 1391, 88, 92, 198, 220, 220, 220, 220, 220, 220, 220, 220, 220, 220, 220, 18868, 48185, 649, 62, 17080, 7, 88, 11, 1395, 8, 198, 220, 220, 220, 220, 220, 220, 220, 2073, 25, 198, 220, 220, 220, 220, 220, 220, 220, 220, 220, 220, 220, 1395, 930, 28, 1391, 10394, 532, 331, 92, 198, 220, 220, 220, 220, 220, 220, 220, 220, 220, 220, 220, 18868, 48185, 649, 62, 17080, 7, 10394, 532, 331, 11, 1395, 8, 628, 220, 220, 220, 1441, 1395, 628, 198, 4299, 1388, 33529, 198, 220, 220, 220, 705, 7061, 13383, 869, 13, 4149, 82, 11, 4539, 11, 290, 16031, 1917, 2176, 1366, 2637, 7061, 198, 220, 220, 220, 1303, 4149, 262, 5128, 1366, 13, 198, 220, 220, 220, 351, 1280, 10786, 7890, 14, 7890, 13, 19608, 11537, 355, 5128, 62, 7890, 25, 198, 220, 220, 220, 220, 220, 220, 220, 18868, 796, 15034, 7, 8899, 7, 600, 11, 15414, 62, 7890, 13, 961, 22446, 36311, 22446, 35312, 3419, 4008, 628, 220, 220, 220, 1303, 3497, 262, 13027, 16274, 13, 198, 220, 220, 220, 1395, 796, 23243, 7, 4868, 7, 47172, 62, 12894, 395, 7, 17080, 1817, 22305, 628, 220, 220, 220, 1303, 12578, 290, 3613, 262, 3280, 13, 198, 220, 220, 220, 3601, 705, 45302, 22179, 7, 8899, 7, 2536, 11, 1395, 4008, 628, 198, 198, 361, 11593, 3672, 834, 6624, 705, 834, 12417, 834, 10354, 198, 220, 220, 220, 1388, 3419 ]
2.501109
451
if __name__ == '__main__': text = input("Give words: ") print(pig_latin(text))
[ 198, 198, 361, 11593, 3672, 834, 6624, 705, 834, 12417, 834, 10354, 198, 220, 220, 220, 2420, 796, 5128, 7203, 23318, 2456, 25, 366, 8, 198, 220, 220, 220, 3601, 7, 79, 328, 62, 75, 10680, 7, 5239, 4008, 198 ]
2.225
40
# -*- coding: utf-8 -*- """ Created on Wed Aug 15 13:35:23 2018 @author: Victor Onink Here we create a figure that has the 24h, and the 3h flow field densities for the North Pacific """ import numpy as np from mpl_toolkits.basemap import Basemap import matplotlib.pyplot as plt from scipy import io import pandas as pd # cbar=my_map.colorbar(density) # cbar.ax.tick_params(labelsize=12) # cbar.set_label("Plastic Counts ($10^{-3}$ # km$^{-2}$)", rotation=90,fontsize=12) #%% location='D:\Desktop\Thesis\ParcelsFigData\Data\North Pacific\OutputFiles\Onink et al\Densities/' File=['NorthPacificTotalDensity24h','NorthPacificStokesTotalDensity24h', 'NorthPacificTotalDensity3h','NorthPacificStokesTotalDensity3h'] axeslabelsize=14 textsize=12 fig,axes=plt.subplots(nrows=2, ncols=1,figsize=(10*2,8*1)) for i in range(len(File)): density=np.load(location+File[i]) density[np.isnan(density)]=0 meanFinalYear=np.sum(density[-183:,:,:]/density[-183:,:,:].shape[0],axis=0) meanFinalYear[meanFinalYear==0]=np.nan latD=np.linspace(-80,80,160) lonD=np.linspace(0,359,360) plt.subplot(2,2,i+1) density=plotDensity(i,lonD,latD,meanFinalYear) fig.subplots_adjust(right=0.9) cbar_ax = fig.add_axes([0.93, 0.12, 0.02, 0.74]) cbar=fig.colorbar(density,cax=cbar_ax) cbar.ax.tick_params(labelsize=textsize) cbar.set_label("Plastic Counts ($10^{-3}$ # km$^{-2}$)", rotation=90,fontsize=axeslabelsize) cbar.ax.set_yticklabels(['<0.1','0.3','0.5','0.7','0.9','1.1','1.3','1.5','1.7','1.9<']) plt.subplots_adjust(wspace=0.06) plt.savefig('D:\Desktop\Thesis\ParcelsFigData\Data\North Pacific\Figures\NorthPacificTimeStepDensities.jpg', bbox_inches='tight')
[ 2, 532, 9, 12, 19617, 25, 3384, 69, 12, 23, 532, 9, 12, 198, 37811, 198, 41972, 319, 3300, 2447, 1315, 1511, 25, 2327, 25, 1954, 2864, 198, 198, 31, 9800, 25, 12622, 1550, 676, 198, 4342, 356, 2251, 257, 3785, 326, 468, 262, 1987, 71, 11, 290, 262, 513, 71, 5202, 2214, 29509, 871, 198, 1640, 262, 2258, 8211, 198, 37811, 198, 198, 11748, 299, 32152, 355, 45941, 198, 6738, 285, 489, 62, 25981, 74, 896, 13, 12093, 368, 499, 1330, 6455, 368, 499, 198, 11748, 2603, 29487, 8019, 13, 9078, 29487, 355, 458, 83, 198, 6738, 629, 541, 88, 1330, 33245, 198, 11748, 19798, 292, 355, 279, 67, 198, 2, 220, 220, 220, 269, 5657, 28, 1820, 62, 8899, 13, 8043, 5657, 7, 43337, 8, 198, 2, 220, 220, 220, 269, 5657, 13, 897, 13, 42298, 62, 37266, 7, 23912, 1424, 1096, 28, 1065, 8, 198, 2, 220, 220, 220, 269, 5657, 13, 2617, 62, 18242, 7203, 3646, 3477, 2764, 82, 7198, 940, 36796, 12, 18, 92, 3, 1303, 10571, 3, 36796, 12, 17, 92, 3, 42501, 13179, 28, 3829, 11, 10331, 7857, 28, 1065, 8, 198, 198, 2, 16626, 220, 220, 220, 220, 220, 220, 220, 220, 220, 220, 220, 220, 220, 220, 220, 220, 220, 220, 220, 220, 220, 220, 220, 220, 220, 220, 220, 220, 220, 220, 220, 220, 220, 220, 220, 220, 198, 24886, 11639, 35, 7479, 36881, 59, 464, 13429, 59, 10044, 5276, 82, 14989, 6601, 59, 6601, 59, 14157, 8211, 59, 26410, 25876, 59, 2202, 676, 2123, 435, 59, 35, 641, 871, 14, 6, 198, 8979, 28, 17816, 14157, 22933, 14957, 35, 6377, 1731, 71, 41707, 14157, 22933, 1273, 3369, 14957, 35, 6377, 1731, 71, 3256, 198, 220, 220, 220, 220, 220, 705, 14157, 22933, 14957, 35, 6377, 18, 71, 41707, 14157, 22933, 1273, 3369, 14957, 35, 6377, 18, 71, 20520, 198, 897, 274, 23912, 1424, 1096, 28, 1415, 198, 5239, 7857, 28, 1065, 198, 5647, 11, 897, 274, 28, 489, 83, 13, 7266, 489, 1747, 7, 77, 8516, 28, 17, 11, 299, 4033, 82, 28, 16, 11, 5647, 7857, 16193, 940, 9, 17, 11, 23, 9, 16, 4008, 198, 1640, 1312, 287, 2837, 7, 11925, 7, 8979, 8, 2599, 198, 220, 220, 220, 12109, 28, 37659, 13, 2220, 7, 24886, 10, 8979, 58, 72, 12962, 198, 220, 220, 220, 12109, 58, 37659, 13, 271, 12647, 7, 43337, 15437, 28, 15, 198, 220, 220, 220, 1612, 19006, 17688, 28, 37659, 13, 16345, 7, 43337, 58, 12, 24839, 45299, 45299, 47715, 14, 43337, 58, 12, 24839, 45299, 45299, 25, 4083, 43358, 58, 15, 4357, 22704, 28, 15, 8, 198, 220, 220, 220, 1612, 19006, 17688, 58, 32604, 19006, 17688, 855, 15, 22241, 37659, 13, 12647, 198, 220, 220, 220, 3042, 35, 28, 37659, 13, 21602, 10223, 32590, 1795, 11, 1795, 11, 14198, 8, 198, 220, 220, 220, 300, 261, 35, 28, 37659, 13, 21602, 10223, 7, 15, 11, 30743, 11, 15277, 8, 198, 220, 220, 220, 458, 83, 13, 7266, 29487, 7, 17, 11, 17, 11, 72, 10, 16, 8, 198, 220, 220, 220, 12109, 28, 29487, 35, 6377, 7, 72, 11, 14995, 35, 11, 15460, 35, 11, 32604, 19006, 17688, 8, 198, 5647, 13, 7266, 489, 1747, 62, 23032, 7, 3506, 28, 15, 13, 24, 8, 198, 66, 5657, 62, 897, 796, 2336, 13, 2860, 62, 897, 274, 26933, 15, 13, 6052, 11, 657, 13, 1065, 11, 657, 13, 2999, 11, 657, 13, 4524, 12962, 198, 66, 5657, 28, 5647, 13, 8043, 5657, 7, 43337, 11, 66, 897, 28, 66, 5657, 62, 897, 8, 198, 66, 5657, 13, 897, 13, 42298, 62, 37266, 7, 23912, 1424, 1096, 28, 5239, 7857, 8, 198, 66, 5657, 13, 2617, 62, 18242, 7203, 3646, 3477, 2764, 82, 7198, 940, 36796, 12, 18, 92, 3, 1303, 10571, 3, 36796, 12, 17, 92, 3, 42501, 13179, 28, 3829, 11, 10331, 7857, 28, 897, 274, 23912, 1424, 1096, 8, 198, 66, 5657, 13, 897, 13, 2617, 62, 20760, 624, 23912, 1424, 7, 17816, 27, 15, 13, 16, 41707, 15, 13, 18, 41707, 15, 13, 20, 41707, 15, 13, 22, 41707, 15, 13, 24, 41707, 16, 13, 16, 41707, 16, 13, 18, 41707, 16, 13, 20, 41707, 16, 13, 22, 41707, 16, 13, 24, 27, 6, 12962, 198, 489, 83, 13, 7266, 489, 1747, 62, 23032, 7, 86, 13200, 28, 15, 13, 3312, 8, 198, 489, 83, 13, 21928, 5647, 10786, 35, 7479, 36881, 59, 464, 13429, 59, 10044, 5276, 82, 14989, 6601, 59, 6601, 59, 14157, 8211, 59, 14989, 942, 59, 14157, 22933, 7575, 8600, 35, 641, 871, 13, 9479, 3256, 198, 220, 220, 220, 220, 220, 220, 220, 220, 220, 220, 220, 275, 3524, 62, 45457, 11639, 33464, 11537, 220, 198 ]
2.212005
783
from settings import * BASE_URL = os.getenv('OPENDUTY_BASE_URL', "http://localhost") XMPP_SETTINGS = { 'user': os.getenv('OPENDUTY_XMPP_USER'), 'password': os.getenv('OPENDUTY_XMPP_PASS'), 'server': os.getenv('OPENDUTY_XMPP_SERVER', 'xmpp'), 'port': os.getenv('OPENDUTY_XMPP_PORT', 5222), } EMAIL_SETTINGS = { 'user': os.getenv('OPENDUTY_EMAIL_USER'), 'password': os.getenv('OPENDUTY_EMAIL_PASS'), } ''' TWILIO_SETTINGS = { 'SID': "TWILIO_ACCOUNT_SID", 'token': "TWILIO_ACCOUNT_TOKEN", 'phone_number': "your_twilio_phone_number", 'sms_number': "your_twilio_sms_number", 'twiml_url': "http://www.website.org/voice.xml" } ''' SLACK_SETTINGS = { 'apikey': os.getenv('OPENDUTY_SLACK_APIKEY', "YOUR_SLACK_API_KEY") } ''' PROWL_SETTINGS = { 'priority': 0 'application': 'openduty' } ''' DATABASES = { 'default': { 'ENGINE': os.getenv('OPENDUTY_DATABASE_ENGINE', 'django.db.backends.mysql'), 'NAME': os.getenv('OPENDUTY_DATABASE_NAME', 'openduty'), 'USER': os.getenv('OPENDUTY_DATABASE_USER', 'openduty'), 'PASSWORD': os.getenv('OPENDUTY_DATABASE_PASS', 'dutyfree'), 'HOST': os.getenv('OPENDUTY_DATABASE_HOST', 'db'), 'PORT': os.getenv('OPENDUTY_DATABASE_PORT', '3306') } } # SECURITY WARNING: keep the secret key used in production secret! SECRET_KEY = os.getenv('OPENDUTY_SECRET_KEY', 'yoursecretkey') ALLOWED_HOSTS = ['your.dutyfree.host'] DEBUG = os.getenv('OPENDUTY_DEBUG', False) TEMPLATE_DEBUG = os.getenv('OPENDUTY_TEMPLATE_DEBUG', False)
[ 6738, 6460, 1330, 1635, 628, 198, 33, 11159, 62, 21886, 796, 28686, 13, 1136, 24330, 10786, 3185, 10619, 3843, 56, 62, 33, 11159, 62, 21886, 3256, 366, 4023, 1378, 36750, 4943, 198, 198, 55, 7378, 47, 62, 28480, 51, 20754, 796, 1391, 198, 220, 220, 220, 705, 7220, 10354, 28686, 13, 1136, 24330, 10786, 3185, 10619, 3843, 56, 62, 55, 7378, 47, 62, 29904, 33809, 198, 220, 220, 220, 705, 28712, 10354, 28686, 13, 1136, 24330, 10786, 3185, 10619, 3843, 56, 62, 55, 7378, 47, 62, 47924, 33809, 198, 220, 220, 220, 705, 15388, 10354, 28686, 13, 1136, 24330, 10786, 3185, 10619, 3843, 56, 62, 55, 7378, 47, 62, 35009, 5959, 3256, 705, 87, 76, 381, 33809, 198, 220, 220, 220, 705, 634, 10354, 28686, 13, 1136, 24330, 10786, 3185, 10619, 3843, 56, 62, 55, 7378, 47, 62, 15490, 3256, 642, 23148, 828, 198, 92, 198, 198, 27630, 4146, 62, 28480, 51, 20754, 796, 1391, 198, 220, 220, 220, 705, 7220, 10354, 28686, 13, 1136, 24330, 10786, 3185, 10619, 3843, 56, 62, 27630, 4146, 62, 29904, 33809, 198, 220, 220, 220, 705, 28712, 10354, 28686, 13, 1136, 24330, 10786, 3185, 10619, 3843, 56, 62, 27630, 4146, 62, 47924, 33809, 198, 92, 198, 198, 7061, 6, 198, 34551, 4146, 9399, 62, 28480, 51, 20754, 796, 1391, 198, 220, 220, 220, 705, 50, 2389, 10354, 366, 34551, 4146, 9399, 62, 26861, 28270, 62, 50, 2389, 1600, 198, 220, 220, 220, 705, 30001, 10354, 366, 34551, 4146, 9399, 62, 26861, 28270, 62, 10468, 43959, 1600, 198, 220, 220, 220, 705, 4862, 62, 17618, 10354, 366, 14108, 62, 4246, 346, 952, 62, 4862, 62, 17618, 1600, 198, 220, 220, 220, 705, 82, 907, 62, 17618, 10354, 366, 14108, 62, 4246, 346, 952, 62, 82, 907, 62, 17618, 1600, 198, 220, 220, 220, 705, 4246, 320, 75, 62, 6371, 10354, 366, 4023, 1378, 2503, 13, 732, 12485, 13, 2398, 14, 38888, 13, 19875, 1, 198, 92, 198, 7061, 6, 198, 198, 8634, 8120, 62, 28480, 51, 20754, 796, 1391, 198, 220, 220, 220, 705, 499, 522, 88, 10354, 28686, 13, 1136, 24330, 10786, 3185, 10619, 3843, 56, 62, 8634, 8120, 62, 17614, 20373, 3256, 366, 56, 11698, 62, 8634, 8120, 62, 17614, 62, 20373, 4943, 198, 92, 198, 198, 7061, 6, 198, 4805, 3913, 43, 62, 28480, 51, 20754, 796, 1391, 198, 220, 220, 220, 705, 49336, 10354, 657, 198, 220, 220, 220, 705, 31438, 10354, 705, 404, 437, 3935, 6, 198, 92, 198, 7061, 6, 198, 198, 35, 1404, 6242, 1921, 1546, 796, 1391, 198, 220, 220, 220, 705, 12286, 10354, 1391, 198, 220, 220, 220, 220, 220, 220, 220, 705, 26808, 8881, 10354, 28686, 13, 1136, 24330, 10786, 3185, 10619, 3843, 56, 62, 35, 1404, 6242, 11159, 62, 26808, 8881, 3256, 705, 28241, 14208, 13, 9945, 13, 1891, 2412, 13, 28744, 13976, 33809, 198, 220, 220, 220, 220, 220, 220, 220, 705, 20608, 10354, 28686, 13, 1136, 24330, 10786, 3185, 10619, 3843, 56, 62, 35, 1404, 6242, 11159, 62, 20608, 3256, 705, 404, 437, 3935, 33809, 198, 220, 220, 220, 220, 220, 220, 220, 705, 29904, 10354, 28686, 13, 1136, 24330, 10786, 3185, 10619, 3843, 56, 62, 35, 1404, 6242, 11159, 62, 29904, 3256, 705, 404, 437, 3935, 33809, 198, 220, 220, 220, 220, 220, 220, 220, 705, 47924, 54, 12532, 10354, 28686, 13, 1136, 24330, 10786, 3185, 10619, 3843, 56, 62, 35, 1404, 6242, 11159, 62, 47924, 3256, 705, 26278, 5787, 33809, 198, 220, 220, 220, 220, 220, 220, 220, 705, 39, 10892, 10354, 28686, 13, 1136, 24330, 10786, 3185, 10619, 3843, 56, 62, 35, 1404, 6242, 11159, 62, 39, 10892, 3256, 705, 9945, 33809, 198, 220, 220, 220, 220, 220, 220, 220, 705, 15490, 10354, 28686, 13, 1136, 24330, 10786, 3185, 10619, 3843, 56, 62, 35, 1404, 6242, 11159, 62, 15490, 3256, 705, 18, 20548, 11537, 198, 220, 220, 220, 1782, 198, 92, 198, 198, 2, 10729, 4261, 9050, 39410, 25, 1394, 262, 3200, 1994, 973, 287, 3227, 3200, 0, 198, 23683, 26087, 62, 20373, 796, 28686, 13, 1136, 24330, 10786, 3185, 10619, 3843, 56, 62, 23683, 26087, 62, 20373, 3256, 705, 14108, 21078, 2539, 11537, 198, 198, 7036, 3913, 1961, 62, 39, 10892, 50, 796, 37250, 14108, 13, 26278, 5787, 13, 4774, 20520, 198, 198, 30531, 796, 28686, 13, 1136, 24330, 10786, 3185, 10619, 3843, 56, 62, 30531, 3256, 10352, 8, 198, 51, 3620, 6489, 6158, 62, 30531, 796, 28686, 13, 1136, 24330, 10786, 3185, 10619, 3843, 56, 62, 51, 3620, 6489, 6158, 62, 30531, 3256, 10352, 8, 198 ]
2.086782
749
# Conventional Machine Learning Algorithms # Test Script for Class of "NaiveBayes". # Author: Qixun Qu # Create on: 2018/04/24 # Modify on: 2018/04/25 # ,,, ,,, # ;" '; ;' ", # ; @.ss$$$$$$s.@ ; # `s$$$$$$$$$$$$$$$' # $$$$$$$$$$$$$$$$$$ # $$$$P""Y$$$Y""W$$$$$ # $$$$ p"$$$"q $$$$$ # $$$$ .$$$$$. $$$$' # $$$DaU$$O$$DaU$$$' # '$$$$'.^.'$$$$' # '&$$$$$&' from __future__ import division from __future__ import print_function from utils import * from NaiveBayes import * from sklearn.datasets import make_hastie_10_2 # Basic settings random_state = 9527 n_samples = 10000 test_size = 0.2 # Generate Dataset for training and testing # Obtain all samples X, y = make_hastie_10_2(n_samples=n_samples, random_state=random_state) # Split dataset X_train, y_train, X_test, y_test = split_dataset(X, y, test_size, random_state) # Normalize dataset X_train_scaled, X_test_scaled = scale_dataset(X_train, X_test) # Train Gaussian Naive Bayes Classifier nb = NaiveBayes(alpha=1) nb.fit(X_train_scaled, y_train, cont_feat_idx="all") # Predict test set and evaluate results y_pred = nb.predict(X_test_scaled) print("Accuracy of test set:", accuracy(y_pred, y_test)) # Accuracy can reach 0.9765.
[ 2, 1482, 20405, 10850, 18252, 978, 7727, 907, 198, 2, 6208, 12327, 329, 5016, 286, 366, 26705, 425, 15262, 274, 1911, 198, 2, 6434, 25, 1195, 844, 403, 2264, 198, 2, 13610, 319, 25, 2864, 14, 3023, 14, 1731, 198, 2, 3401, 1958, 319, 25, 2864, 14, 3023, 14, 1495, 198, 198, 2, 220, 220, 220, 220, 837, 9832, 220, 220, 220, 220, 220, 220, 220, 220, 837, 9832, 198, 2, 220, 220, 2162, 1, 220, 220, 705, 26, 220, 220, 220, 220, 2162, 6, 220, 220, 33172, 198, 2, 220, 220, 2162, 220, 2488, 13, 824, 36737, 13702, 82, 13, 31, 220, 2162, 198, 2, 220, 220, 4600, 82, 36737, 36737, 36737, 13702, 3, 6, 198, 2, 220, 220, 720, 36737, 36737, 36737, 36737, 3, 198, 2, 220, 720, 13702, 3, 47, 15931, 56, 13702, 3, 56, 15931, 54, 36737, 3, 198, 2, 220, 720, 13702, 3, 220, 279, 1, 13702, 3, 1, 80, 220, 720, 36737, 198, 2, 220, 720, 13702, 3, 220, 764, 36737, 35307, 220, 720, 13702, 3, 6, 198, 2, 220, 220, 720, 13702, 26531, 52, 13702, 46, 13702, 26531, 52, 13702, 3, 6, 198, 2, 220, 220, 220, 705, 36737, 4458, 61, 2637, 36737, 6, 198, 2, 220, 220, 220, 220, 220, 220, 705, 5, 36737, 3, 5, 6, 628, 198, 6738, 11593, 37443, 834, 1330, 7297, 198, 6738, 11593, 37443, 834, 1330, 3601, 62, 8818, 628, 198, 6738, 3384, 4487, 1330, 1635, 198, 6738, 11013, 425, 15262, 274, 1330, 1635, 198, 6738, 1341, 35720, 13, 19608, 292, 1039, 1330, 787, 62, 71, 459, 494, 62, 940, 62, 17, 628, 198, 2, 14392, 6460, 198, 25120, 62, 5219, 796, 6957, 1983, 198, 77, 62, 82, 12629, 796, 33028, 198, 9288, 62, 7857, 796, 657, 13, 17, 628, 198, 2, 2980, 378, 16092, 292, 316, 329, 3047, 290, 4856, 198, 2, 1835, 3153, 477, 8405, 198, 55, 11, 331, 796, 787, 62, 71, 459, 494, 62, 940, 62, 17, 7, 77, 62, 82, 12629, 28, 77, 62, 82, 12629, 11, 198, 220, 220, 220, 220, 220, 220, 220, 220, 220, 220, 220, 220, 220, 220, 220, 220, 220, 220, 220, 220, 220, 220, 220, 4738, 62, 5219, 28, 25120, 62, 5219, 8, 198, 2, 27758, 27039, 198, 55, 62, 27432, 11, 331, 62, 27432, 11, 1395, 62, 9288, 11, 331, 62, 9288, 796, 6626, 62, 19608, 292, 316, 7, 55, 11, 331, 11, 1332, 62, 7857, 11, 198, 220, 220, 220, 220, 220, 220, 220, 220, 220, 220, 220, 220, 220, 220, 220, 220, 220, 220, 220, 220, 220, 220, 220, 220, 220, 220, 220, 220, 220, 220, 220, 220, 220, 220, 220, 220, 220, 220, 220, 220, 220, 220, 220, 220, 220, 220, 220, 220, 4738, 62, 5219, 8, 198, 2, 14435, 1096, 27039, 198, 55, 62, 27432, 62, 1416, 3021, 11, 1395, 62, 9288, 62, 1416, 3021, 796, 5046, 62, 19608, 292, 316, 7, 55, 62, 27432, 11, 1395, 62, 9288, 8, 628, 198, 2, 16835, 12822, 31562, 11013, 425, 4696, 274, 5016, 7483, 198, 46803, 796, 11013, 425, 15262, 274, 7, 26591, 28, 16, 8, 198, 46803, 13, 11147, 7, 55, 62, 27432, 62, 1416, 3021, 11, 331, 62, 27432, 11, 542, 62, 27594, 62, 312, 87, 2625, 439, 4943, 198, 198, 2, 49461, 1332, 900, 290, 13446, 2482, 198, 88, 62, 28764, 796, 299, 65, 13, 79, 17407, 7, 55, 62, 9288, 62, 1416, 3021, 8, 198, 4798, 7203, 17320, 23843, 286, 1332, 900, 25, 1600, 9922, 7, 88, 62, 28764, 11, 331, 62, 9288, 4008, 198, 2, 33222, 460, 3151, 657, 13, 5607, 2996, 13, 198 ]
2.20302
596
from Bridge import Proxy2Server import os from DataTypes import Packet, A_Packet_Class from DataTypes import VarInt, Output_Streamer, Bytes_Streamer, Socket_Streamer import time output = Output_Streamer() input = Bytes_Streamer() login_packets = A_Packet_Class() SOCK = Socket_Streamer('connect.2b2t.org', 25565, login_packets) handshake = Packet(login_packets) handshake.set(['VarInt', 'VarInt', 'String', 'Ushort', 'VarInt']) status = Packet(login_packets) status.set(['VarInt', 'String']) request = Packet(login_packets) request.set(['VarInt']) ping_pong = Packet(login_packets) ping_pong.set(['VarInt', 'Long']) encryption_req = Packet(login_packets) encryption_req.set(['VarInt', 'String', 'String', 'String']) encryption_res = Packet(login_packets) encryption_res.set(['VarInt', 'String', 'String']) login_success = Packet(login_packets) login_success.set(['VarInt', 'String', 'String']) set_compression = Packet(login_packets) set_compression.set(['VarInt', 'VarInt']) login_packets.map_pack(pack_0) login_packets.map_unpack(unpack_0) # data = handshake.pack([0x00, 340, b'2b2t.org', 25565, 1]) # server_sock.write(data) # data = request.pack([0x00]) # server_sock.write(data) # status.unpack(server_sock, output) input.write(handshake.pack([0x00, 340, b'2b2t.org', 25565, 2])) SOCK.write(input) input.write(status.pack([0x00, b'ThBlitz'])) SOCK.write(input) SOCK.read(input) encryption_req.unpack(input, output) print(f'encryption_req : {output.getvalue()}') data = output.getvalue() login_packets.server_id = data[1] login_packets.server_public_key = data[2] login_packets.verification_token = data[3] import secrets login_packets.aes_key = secrets.randbits(128).to_bytes(16, 'big') hash , ver_token , shared_secret = login_packets.get_hash() import mojang_api uuid , name , token , login_data = mojang_api.login_through_microsoft() res = mojang_api.join_server(token, uuid, hash) print(f'response from mojang : {res}') input.reset() input.write(encryption_res.pack([0x01, shared_secret, ver_token])) SOCK.write(input) login_packets.encryption_enabled = True SOCK.read(input) set_compression.unpack(input, output) login_packets.compression_threshold = output.getvalue()[1] login_packets.compression_enabled = True print(f'compression_packet : {output.getvalue()}') SOCK.read(input) login_success.unpack(input, output) print(f'login_success : {output.getvalue()}') SOCK.read(input) status.unpack(input, output) print(input.getvalue()) while True: SOCK.read(input) print(hex(VarInt.unpack(input))) print(input.read()) time.sleep(1) # t
[ 6738, 10290, 1330, 38027, 17, 10697, 198, 11748, 28686, 198, 6738, 6060, 31431, 1330, 6400, 316, 11, 317, 62, 47, 8317, 62, 9487, 198, 6738, 6060, 31431, 1330, 12372, 5317, 11, 25235, 62, 28696, 11, 2750, 4879, 62, 28696, 11, 47068, 62, 28696, 198, 11748, 640, 628, 198, 22915, 796, 25235, 62, 28696, 3419, 198, 198, 15414, 796, 2750, 4879, 62, 28696, 3419, 198, 198, 38235, 62, 8002, 1039, 796, 317, 62, 47, 8317, 62, 9487, 3419, 198, 198, 50, 11290, 796, 47068, 62, 28696, 10786, 8443, 13, 17, 65, 17, 83, 13, 2398, 3256, 14280, 2996, 11, 17594, 62, 8002, 1039, 8, 198, 198, 4993, 32431, 796, 6400, 316, 7, 38235, 62, 8002, 1039, 8, 198, 4993, 32431, 13, 2617, 7, 17816, 19852, 5317, 3256, 705, 19852, 5317, 3256, 705, 10100, 3256, 705, 52, 19509, 3256, 705, 19852, 5317, 6, 12962, 198, 198, 13376, 796, 6400, 316, 7, 38235, 62, 8002, 1039, 8, 198, 13376, 13, 2617, 7, 17816, 19852, 5317, 3256, 705, 10100, 6, 12962, 198, 198, 25927, 796, 6400, 316, 7, 38235, 62, 8002, 1039, 8, 198, 25927, 13, 2617, 7, 17816, 19852, 5317, 6, 12962, 198, 198, 13886, 62, 79, 506, 796, 6400, 316, 7, 38235, 62, 8002, 1039, 8, 198, 13886, 62, 79, 506, 13, 2617, 7, 17816, 19852, 5317, 3256, 705, 14617, 6, 12962, 198, 198, 12685, 13168, 62, 42180, 796, 6400, 316, 7, 38235, 62, 8002, 1039, 8, 198, 12685, 13168, 62, 42180, 13, 2617, 7, 17816, 19852, 5317, 3256, 705, 10100, 3256, 705, 10100, 3256, 705, 10100, 6, 12962, 198, 198, 12685, 13168, 62, 411, 796, 6400, 316, 7, 38235, 62, 8002, 1039, 8, 198, 12685, 13168, 62, 411, 13, 2617, 7, 17816, 19852, 5317, 3256, 705, 10100, 3256, 705, 10100, 6, 12962, 198, 198, 38235, 62, 13138, 796, 6400, 316, 7, 38235, 62, 8002, 1039, 8, 198, 38235, 62, 13138, 13, 2617, 7, 17816, 19852, 5317, 3256, 705, 10100, 3256, 705, 10100, 6, 12962, 198, 198, 2617, 62, 5589, 2234, 796, 6400, 316, 7, 38235, 62, 8002, 1039, 8, 198, 2617, 62, 5589, 2234, 13, 2617, 7, 17816, 19852, 5317, 3256, 705, 19852, 5317, 6, 12962, 198, 198, 38235, 62, 8002, 1039, 13, 8899, 62, 8002, 7, 8002, 62, 15, 8, 198, 38235, 62, 8002, 1039, 13, 8899, 62, 403, 8002, 7, 403, 8002, 62, 15, 8, 628, 628, 198, 2, 1366, 796, 42231, 13, 8002, 26933, 15, 87, 405, 11, 28560, 11, 275, 6, 17, 65, 17, 83, 13, 2398, 3256, 14280, 2996, 11, 352, 12962, 198, 2, 4382, 62, 82, 735, 13, 13564, 7, 7890, 8, 198, 2, 1366, 796, 2581, 13, 8002, 26933, 15, 87, 405, 12962, 198, 2, 4382, 62, 82, 735, 13, 13564, 7, 7890, 8, 198, 198, 2, 3722, 13, 403, 8002, 7, 15388, 62, 82, 735, 11, 5072, 8, 198, 198, 15414, 13, 13564, 7, 4993, 32431, 13, 8002, 26933, 15, 87, 405, 11, 28560, 11, 275, 6, 17, 65, 17, 83, 13, 2398, 3256, 14280, 2996, 11, 362, 60, 4008, 198, 198, 50, 11290, 13, 13564, 7, 15414, 8, 198, 198, 15414, 13, 13564, 7, 13376, 13, 8002, 26933, 15, 87, 405, 11, 275, 6, 817, 3629, 4224, 20520, 4008, 198, 198, 50, 11290, 13, 13564, 7, 15414, 8, 198, 198, 50, 11290, 13, 961, 7, 15414, 8, 198, 198, 12685, 13168, 62, 42180, 13, 403, 8002, 7, 15414, 11, 5072, 8, 198, 198, 4798, 7, 69, 6, 12685, 13168, 62, 42180, 1058, 1391, 22915, 13, 1136, 8367, 3419, 92, 11537, 198, 198, 7890, 796, 5072, 13, 1136, 8367, 3419, 198, 38235, 62, 8002, 1039, 13, 15388, 62, 312, 796, 1366, 58, 16, 60, 198, 38235, 62, 8002, 1039, 13, 15388, 62, 11377, 62, 2539, 796, 1366, 58, 17, 60, 198, 38235, 62, 8002, 1039, 13, 332, 2649, 62, 30001, 796, 1366, 58, 18, 60, 198, 198, 11748, 13141, 198, 38235, 62, 8002, 1039, 13, 64, 274, 62, 2539, 796, 13141, 13, 25192, 9895, 7, 12762, 737, 1462, 62, 33661, 7, 1433, 11, 705, 14261, 11537, 198, 198, 17831, 837, 3326, 62, 30001, 837, 4888, 62, 21078, 796, 17594, 62, 8002, 1039, 13, 1136, 62, 17831, 3419, 198, 198, 11748, 6941, 73, 648, 62, 15042, 198, 12303, 312, 837, 1438, 837, 11241, 837, 17594, 62, 7890, 796, 6941, 73, 648, 62, 15042, 13, 38235, 62, 9579, 62, 40485, 3419, 198, 411, 796, 6941, 73, 648, 62, 15042, 13, 22179, 62, 15388, 7, 30001, 11, 334, 27112, 11, 12234, 8, 198, 4798, 7, 69, 821, 2777, 2591, 422, 6941, 73, 648, 1058, 1391, 411, 92, 11537, 198, 198, 15414, 13, 42503, 3419, 198, 15414, 13, 13564, 7, 12685, 13168, 62, 411, 13, 8002, 26933, 15, 87, 486, 11, 4888, 62, 21078, 11, 3326, 62, 30001, 60, 4008, 198, 198, 50, 11290, 13, 13564, 7, 15414, 8, 198, 198, 38235, 62, 8002, 1039, 13, 12685, 13168, 62, 25616, 796, 6407, 198, 198, 50, 11290, 13, 961, 7, 15414, 8, 198, 198, 2617, 62, 5589, 2234, 13, 403, 8002, 7, 15414, 11, 5072, 8, 198, 198, 38235, 62, 8002, 1039, 13, 5589, 2234, 62, 400, 10126, 796, 5072, 13, 1136, 8367, 3419, 58, 16, 60, 198, 38235, 62, 8002, 1039, 13, 5589, 2234, 62, 25616, 796, 6407, 198, 198, 4798, 7, 69, 6, 5589, 2234, 62, 8002, 316, 1058, 1391, 22915, 13, 1136, 8367, 3419, 92, 11537, 198, 198, 50, 11290, 13, 961, 7, 15414, 8, 198, 198, 38235, 62, 13138, 13, 403, 8002, 7, 15414, 11, 5072, 8, 198, 198, 4798, 7, 69, 6, 38235, 62, 13138, 1058, 1391, 22915, 13, 1136, 8367, 3419, 92, 11537, 198, 198, 50, 11290, 13, 961, 7, 15414, 8, 198, 198, 13376, 13, 403, 8002, 7, 15414, 11, 5072, 8, 198, 4798, 7, 15414, 13, 1136, 8367, 28955, 198, 198, 4514, 6407, 25, 198, 220, 220, 220, 311, 11290, 13, 961, 7, 15414, 8, 198, 220, 220, 220, 3601, 7, 33095, 7, 19852, 5317, 13, 403, 8002, 7, 15414, 22305, 198, 220, 220, 220, 3601, 7, 15414, 13, 961, 28955, 198, 220, 220, 220, 640, 13, 42832, 7, 16, 8, 628, 628, 628, 628, 198, 198, 2, 256, 198 ]
2.585149
1,010
# -*- coding: utf-8 -*- """ Created on Wed Mar 17 13:35:39 2021 @author: ejgen ------ What is this file? ------ This script targets the files goodreads_reviews_cleaned.csv and review_sentences_analyzed.csv, calculating summary statistics such as review length and sentiment score. This script targets the following files: ../../data/cleaned/goodreads_reviews_cleaned.csv ../../data/analysis_results/review_sentences_analyzed.csv The resulting csv file is located at: ../../data/analysis_results/goodreads_reviews_analyzed.csv """ #%% --- Import required packages --- import os from pathlib import Path # To wrap around filepaths import pandas as pd #%% --- Set proper directory to assure integration with doit --- abspath = os.path.abspath(__file__) dname = os.path.dirname(abspath) os.chdir(dname) #%% --- Import data --- #goodreads_reviews_cleaned import_fp = Path("../../data/cleaned/goodreads_reviews_cleaned.csv") goodreads_reviews = pd.read_csv(import_fp, encoding = "utf-8", index_col = False) #review_sentences_analyzed import_fp = Path("../../data/analysis_results/review_sentences_analyzed.csv") sentences_analyzed = pd.read_csv(import_fp, encoding = "utf-8") #%% --- Prepare data --- sentences_analyzed = sentences_analyzed.loc[:,["review_id", "sentence_id", "sent_mentions_original", "sent_mentions_trans", "length_in_words", "VADER_score_compound"]] # Take a subset of goodreads reviews to include only reviews whose review no # appear in sentences_analyzed. rid_mask = goodreads_reviews["review_id"].isin(sentences_analyzed["review_id"]) goodreads_reviews = goodreads_reviews.loc[rid_mask, :] #%% --- Analyze: review length in sentences and words. --- length_per_review = (sentences_analyzed .groupby("review_id") ["length_in_words"] .agg(["sum","count"]) .rename({"sum" : "total_length_in_words", "count" : "total_length_in_sentences"}, axis = 1)) goodreads_reviews = (goodreads_reviews .merge(length_per_review, how = "left", on = "review_id")) #%% --- Analyze: mention ratios for explicit translation/author mentions orig_mention_mask = sentences_analyzed["sent_mentions_original"] == True trans_mention_mask = sentences_analyzed["sent_mentions_trans"] == True only_orig_mention_mask = (orig_mention_mask & ~trans_mention_mask) only_trans_mention_mask = (~orig_mention_mask & trans_mention_mask) both_mention_mask = (orig_mention_mask & trans_mention_mask) masks = {"share_of_only_trans_mentions" : only_trans_mention_mask, "share_of_trans_mentions" : trans_mention_mask, "share_of_only_orig_mentions": only_orig_mention_mask, "share_of_orig_mentions": orig_mention_mask} for prefix, mask in masks.items(): calc = (sentences_analyzed[mask]. groupby("review_id") ["length_in_words"] .agg(["count"]) .rename({"count": prefix}, axis = 1) .reset_index()) goodreads_reviews = (goodreads_reviews.merge(calc, how = "left", on = "review_id") .fillna(value = 0, axis = 0)) goodreads_reviews[prefix] = ((goodreads_reviews[prefix] / goodreads_reviews["total_length_in_sentences"]) * 100) #%% --- Analyze: VADER score for the whole review --- VADER_score_per_review = (sentences_analyzed .groupby("review_id") ["VADER_score_compound"] .agg(["sum","count"]) .reset_index()) VADER_score_per_review["avg_VADER_score"] = (VADER_score_per_review["sum"] / VADER_score_per_review["count"]) VADER_score_per_review = VADER_score_per_review.drop(labels = ["sum","count"], axis = "columns") goodreads_reviews = goodreads_reviews.merge(VADER_score_per_review, how = "left", on = "review_id") #%% --- Export data --- export_fp = Path("../../data/analysis_results/goodreads_reviews_analyzed.csv") goodreads_reviews.to_csv(export_fp, encoding = "utf-8", index = False)
[ 2, 532, 9, 12, 19617, 25, 3384, 69, 12, 23, 532, 9, 12, 198, 37811, 198, 41972, 319, 3300, 1526, 1596, 1511, 25, 2327, 25, 2670, 33448, 198, 198, 31, 9800, 25, 304, 73, 5235, 198, 198, 23031, 1867, 318, 428, 2393, 30, 40103, 198, 198, 1212, 4226, 6670, 262, 3696, 922, 40779, 62, 19023, 82, 62, 2375, 22739, 13, 40664, 290, 198, 19023, 62, 34086, 3007, 62, 38200, 8863, 13, 40664, 11, 26019, 10638, 7869, 884, 355, 198, 19023, 4129, 290, 15598, 4776, 13, 198, 198, 1212, 4226, 6670, 262, 1708, 3696, 25, 198, 220, 220, 220, 11485, 14, 40720, 7890, 14, 2375, 22739, 14, 11274, 40779, 62, 19023, 82, 62, 2375, 22739, 13, 40664, 198, 220, 220, 220, 11485, 14, 40720, 7890, 14, 20930, 62, 43420, 14, 19023, 62, 34086, 3007, 62, 38200, 8863, 13, 40664, 198, 220, 220, 220, 220, 198, 464, 7186, 269, 21370, 2393, 318, 5140, 379, 25, 198, 220, 220, 220, 11485, 14, 40720, 7890, 14, 20930, 62, 43420, 14, 11274, 40779, 62, 19023, 82, 62, 38200, 8863, 13, 40664, 198, 220, 220, 220, 220, 220, 220, 220, 220, 198, 37811, 198, 2, 16626, 11420, 17267, 2672, 10392, 11420, 198, 198, 11748, 28686, 198, 198, 6738, 3108, 8019, 1330, 10644, 1303, 1675, 14441, 1088, 2393, 6978, 82, 198, 11748, 19798, 292, 355, 279, 67, 198, 198, 2, 16626, 11420, 5345, 1774, 8619, 284, 19832, 11812, 351, 466, 270, 11420, 198, 198, 397, 2777, 776, 796, 28686, 13, 6978, 13, 397, 2777, 776, 7, 834, 7753, 834, 8, 198, 67, 3672, 796, 28686, 13, 6978, 13, 15908, 3672, 7, 397, 2777, 776, 8, 198, 418, 13, 354, 15908, 7, 67, 3672, 8, 198, 198, 2, 16626, 11420, 17267, 1366, 11420, 198, 198, 2, 11274, 40779, 62, 19023, 82, 62, 2375, 22739, 198, 11748, 62, 46428, 796, 10644, 7203, 40720, 40720, 7890, 14, 2375, 22739, 14, 11274, 40779, 62, 19023, 82, 62, 2375, 22739, 13, 40664, 4943, 198, 11274, 40779, 62, 19023, 82, 796, 279, 67, 13, 961, 62, 40664, 7, 11748, 62, 46428, 11, 21004, 796, 366, 40477, 12, 23, 1600, 6376, 62, 4033, 796, 10352, 8, 198, 198, 2, 19023, 62, 34086, 3007, 62, 38200, 8863, 198, 11748, 62, 46428, 796, 10644, 7203, 40720, 40720, 7890, 14, 20930, 62, 43420, 14, 19023, 62, 34086, 3007, 62, 38200, 8863, 13, 40664, 4943, 198, 34086, 3007, 62, 38200, 8863, 796, 279, 67, 13, 961, 62, 40664, 7, 11748, 62, 46428, 11, 21004, 796, 366, 40477, 12, 23, 4943, 198, 198, 2, 16626, 11420, 43426, 1366, 11420, 198, 198, 34086, 3007, 62, 38200, 8863, 796, 13439, 62, 38200, 8863, 13, 17946, 58, 45299, 14692, 19023, 62, 312, 1600, 198, 220, 220, 220, 220, 220, 220, 220, 220, 220, 220, 220, 220, 220, 220, 220, 220, 220, 220, 220, 220, 220, 220, 220, 220, 220, 220, 220, 220, 220, 220, 220, 220, 220, 220, 220, 220, 220, 220, 220, 220, 220, 220, 220, 220, 220, 220, 220, 366, 34086, 594, 62, 312, 1600, 198, 220, 220, 220, 220, 220, 220, 220, 220, 220, 220, 220, 220, 220, 220, 220, 220, 220, 220, 220, 220, 220, 220, 220, 220, 220, 220, 220, 220, 220, 220, 220, 220, 220, 220, 220, 220, 220, 220, 220, 220, 220, 220, 220, 220, 220, 220, 220, 366, 34086, 62, 434, 507, 62, 14986, 1600, 198, 220, 220, 220, 220, 220, 220, 220, 220, 220, 220, 220, 220, 220, 220, 220, 220, 220, 220, 220, 220, 220, 220, 220, 220, 220, 220, 220, 220, 220, 220, 220, 220, 220, 220, 220, 220, 220, 220, 220, 220, 220, 220, 220, 220, 220, 220, 220, 366, 34086, 62, 434, 507, 62, 7645, 1600, 198, 220, 220, 220, 220, 220, 220, 220, 220, 220, 220, 220, 220, 220, 220, 220, 220, 220, 220, 220, 220, 220, 220, 220, 220, 220, 220, 220, 220, 220, 220, 220, 220, 220, 220, 220, 220, 220, 220, 220, 220, 220, 220, 220, 220, 220, 220, 220, 366, 13664, 62, 259, 62, 10879, 1600, 198, 220, 220, 220, 220, 220, 220, 220, 220, 220, 220, 220, 220, 220, 220, 220, 220, 220, 220, 220, 220, 220, 220, 220, 220, 220, 220, 220, 220, 220, 220, 220, 220, 220, 220, 220, 220, 220, 220, 220, 220, 220, 220, 220, 220, 220, 220, 220, 366, 53, 2885, 1137, 62, 26675, 62, 5589, 633, 8973, 60, 198, 198, 2, 7214, 257, 24637, 286, 922, 40779, 8088, 284, 2291, 691, 8088, 3025, 2423, 645, 198, 2, 1656, 287, 13439, 62, 38200, 8863, 13, 198, 198, 6058, 62, 27932, 796, 922, 40779, 62, 19023, 82, 14692, 19023, 62, 312, 1, 4083, 45763, 7, 34086, 3007, 62, 38200, 8863, 14692, 19023, 62, 312, 8973, 8, 198, 11274, 40779, 62, 19023, 82, 796, 922, 40779, 62, 19023, 82, 13, 17946, 58, 6058, 62, 27932, 11, 1058, 60, 198, 2, 16626, 11420, 16213, 2736, 25, 2423, 4129, 287, 13439, 290, 2456, 13, 11420, 198, 198, 13664, 62, 525, 62, 19023, 796, 357, 34086, 3007, 62, 38200, 8863, 198, 220, 220, 220, 220, 220, 220, 220, 220, 220, 220, 220, 220, 220, 220, 220, 220, 220, 220, 220, 220, 220, 220, 220, 764, 8094, 1525, 7203, 19023, 62, 312, 4943, 198, 220, 220, 220, 220, 220, 220, 220, 220, 220, 220, 220, 220, 220, 220, 220, 220, 220, 220, 220, 220, 220, 220, 220, 14631, 13664, 62, 259, 62, 10879, 8973, 198, 220, 220, 220, 220, 220, 220, 220, 220, 220, 220, 220, 220, 220, 220, 220, 220, 220, 220, 220, 220, 220, 220, 220, 764, 9460, 7, 14692, 16345, 2430, 9127, 8973, 8, 198, 220, 220, 220, 220, 220, 220, 220, 220, 220, 220, 220, 220, 220, 220, 220, 220, 220, 220, 220, 220, 220, 220, 220, 764, 918, 480, 7, 4895, 16345, 1, 1058, 366, 23350, 62, 13664, 62, 259, 62, 10879, 1600, 198, 220, 220, 220, 220, 220, 220, 220, 220, 220, 220, 220, 220, 220, 220, 220, 220, 220, 220, 220, 220, 220, 220, 220, 220, 220, 220, 220, 220, 220, 220, 220, 220, 220, 366, 9127, 1, 1058, 366, 23350, 62, 13664, 62, 259, 62, 34086, 3007, 25719, 198, 220, 220, 220, 220, 220, 220, 220, 220, 220, 220, 220, 220, 220, 220, 220, 220, 220, 220, 220, 220, 220, 220, 220, 220, 220, 220, 220, 220, 220, 220, 220, 16488, 796, 352, 4008, 198, 198, 11274, 40779, 62, 19023, 82, 796, 357, 11274, 40779, 62, 19023, 82, 198, 220, 220, 220, 220, 220, 220, 220, 220, 220, 220, 220, 220, 220, 220, 220, 220, 220, 220, 220, 220, 220, 764, 647, 469, 7, 13664, 62, 525, 62, 19023, 11, 198, 220, 220, 220, 220, 220, 220, 220, 220, 220, 220, 220, 220, 220, 220, 220, 220, 220, 220, 220, 220, 220, 220, 220, 220, 220, 220, 220, 703, 796, 366, 9464, 1600, 198, 220, 220, 220, 220, 220, 220, 220, 220, 220, 220, 220, 220, 220, 220, 220, 220, 220, 220, 220, 220, 220, 220, 220, 220, 220, 220, 220, 319, 796, 366, 19023, 62, 312, 48774, 198, 198, 2, 16626, 11420, 16213, 2736, 25, 3068, 22423, 329, 7952, 11059, 14, 9800, 15802, 198, 198, 11612, 62, 434, 295, 62, 27932, 796, 13439, 62, 38200, 8863, 14692, 34086, 62, 434, 507, 62, 14986, 8973, 6624, 6407, 198, 7645, 62, 434, 295, 62, 27932, 796, 13439, 62, 38200, 8863, 14692, 34086, 62, 434, 507, 62, 7645, 8973, 6624, 6407, 198, 8807, 62, 11612, 62, 434, 295, 62, 27932, 796, 357, 11612, 62, 434, 295, 62, 27932, 1222, 5299, 7645, 62, 434, 295, 62, 27932, 8, 198, 8807, 62, 7645, 62, 434, 295, 62, 27932, 796, 31034, 11612, 62, 434, 295, 62, 27932, 1222, 1007, 62, 434, 295, 62, 27932, 8, 198, 16885, 62, 434, 295, 62, 27932, 796, 357, 11612, 62, 434, 295, 62, 27932, 1222, 1007, 62, 434, 295, 62, 27932, 8, 198, 198, 5356, 591, 796, 19779, 20077, 62, 1659, 62, 8807, 62, 7645, 62, 434, 507, 1, 1058, 691, 62, 7645, 62, 434, 295, 62, 27932, 11, 198, 220, 220, 220, 220, 220, 220, 220, 220, 366, 20077, 62, 1659, 62, 7645, 62, 434, 507, 1, 1058, 1007, 62, 434, 295, 62, 27932, 11, 198, 220, 220, 220, 220, 220, 220, 220, 220, 366, 20077, 62, 1659, 62, 8807, 62, 11612, 62, 434, 507, 1298, 691, 62, 11612, 62, 434, 295, 62, 27932, 11, 198, 220, 220, 220, 220, 220, 220, 220, 220, 366, 20077, 62, 1659, 62, 11612, 62, 434, 507, 1298, 1796, 62, 434, 295, 62, 27932, 92, 198, 198, 1640, 21231, 11, 9335, 287, 20680, 13, 23814, 33529, 198, 220, 220, 220, 42302, 796, 357, 34086, 3007, 62, 38200, 8863, 58, 27932, 4083, 198, 220, 220, 220, 220, 220, 220, 220, 220, 220, 220, 220, 1448, 1525, 7203, 19023, 62, 312, 4943, 198, 220, 220, 220, 220, 220, 220, 220, 220, 220, 220, 220, 14631, 13664, 62, 259, 62, 10879, 8973, 198, 220, 220, 220, 220, 220, 220, 220, 220, 220, 220, 220, 764, 9460, 7, 14692, 9127, 8973, 8, 198, 220, 220, 220, 220, 220, 220, 220, 220, 220, 220, 220, 764, 918, 480, 7, 4895, 9127, 1298, 21231, 5512, 198, 220, 220, 220, 220, 220, 220, 220, 220, 220, 220, 220, 220, 220, 220, 220, 220, 220, 220, 220, 16488, 796, 352, 8, 198, 220, 220, 220, 220, 220, 220, 220, 220, 220, 220, 220, 764, 42503, 62, 9630, 28955, 198, 220, 220, 220, 220, 198, 220, 220, 220, 922, 40779, 62, 19023, 82, 796, 357, 11274, 40779, 62, 19023, 82, 13, 647, 469, 7, 9948, 66, 11, 198, 220, 220, 220, 220, 220, 220, 220, 220, 220, 220, 220, 220, 220, 220, 220, 220, 220, 220, 220, 220, 220, 220, 220, 220, 220, 220, 220, 220, 220, 220, 220, 220, 220, 220, 220, 220, 220, 220, 220, 220, 220, 220, 220, 220, 220, 220, 220, 220, 703, 796, 366, 9464, 1600, 198, 220, 220, 220, 220, 220, 220, 220, 220, 220, 220, 220, 220, 220, 220, 220, 220, 220, 220, 220, 220, 220, 220, 220, 220, 220, 220, 220, 220, 220, 220, 220, 220, 220, 220, 220, 220, 220, 220, 220, 220, 220, 220, 220, 220, 220, 220, 220, 220, 319, 796, 366, 19023, 62, 312, 4943, 198, 220, 220, 220, 220, 220, 220, 220, 220, 220, 220, 220, 220, 220, 220, 220, 220, 220, 220, 220, 220, 220, 220, 220, 220, 764, 20797, 2616, 7, 8367, 796, 657, 11, 198, 220, 220, 220, 220, 220, 220, 220, 220, 220, 220, 220, 220, 220, 220, 220, 220, 220, 220, 220, 220, 220, 220, 220, 220, 220, 220, 220, 220, 220, 220, 220, 220, 16488, 796, 657, 4008, 198, 220, 220, 220, 220, 198, 220, 220, 220, 922, 40779, 62, 19023, 82, 58, 40290, 60, 796, 14808, 11274, 40779, 62, 19023, 82, 58, 40290, 60, 198, 220, 220, 220, 220, 220, 220, 220, 220, 220, 220, 220, 220, 220, 220, 220, 220, 220, 220, 220, 220, 220, 220, 220, 220, 220, 220, 220, 220, 220, 220, 1220, 922, 40779, 62, 19023, 82, 14692, 23350, 62, 13664, 62, 259, 62, 34086, 3007, 8973, 8, 198, 220, 220, 220, 220, 220, 220, 220, 220, 220, 220, 220, 220, 220, 220, 220, 220, 220, 220, 220, 220, 220, 220, 220, 220, 220, 220, 220, 220, 220, 220, 1635, 1802, 8, 198, 220, 220, 220, 220, 198, 2, 16626, 11420, 16213, 2736, 25, 569, 2885, 1137, 4776, 329, 262, 2187, 2423, 11420, 198, 198, 53, 2885, 1137, 62, 26675, 62, 525, 62, 19023, 796, 357, 34086, 3007, 62, 38200, 8863, 198, 220, 220, 220, 220, 220, 220, 220, 220, 220, 220, 220, 220, 220, 220, 220, 220, 220, 220, 220, 220, 220, 220, 220, 220, 220, 764, 8094, 1525, 7203, 19023, 62, 312, 4943, 198, 220, 220, 220, 220, 220, 220, 220, 220, 220, 220, 220, 220, 220, 220, 220, 220, 220, 220, 220, 220, 220, 220, 220, 220, 220, 14631, 53, 2885, 1137, 62, 26675, 62, 5589, 633, 8973, 198, 220, 220, 220, 220, 220, 220, 220, 220, 220, 220, 220, 220, 220, 220, 220, 220, 220, 220, 220, 220, 220, 220, 220, 220, 220, 764, 9460, 7, 14692, 16345, 2430, 9127, 8973, 8, 198, 220, 220, 220, 220, 220, 220, 220, 220, 220, 220, 220, 220, 220, 220, 220, 220, 220, 220, 220, 220, 220, 220, 220, 220, 220, 764, 42503, 62, 9630, 28955, 198, 198, 53, 2885, 1137, 62, 26675, 62, 525, 62, 19023, 14692, 615, 70, 62, 53, 2885, 1137, 62, 26675, 8973, 796, 357, 53, 2885, 1137, 62, 26675, 62, 525, 62, 19023, 14692, 16345, 8973, 198, 220, 220, 220, 220, 220, 220, 220, 220, 220, 220, 220, 220, 220, 220, 220, 220, 220, 220, 220, 220, 220, 220, 220, 220, 220, 220, 220, 220, 220, 220, 220, 220, 220, 220, 220, 220, 220, 220, 220, 220, 220, 220, 220, 220, 220, 1220, 569, 2885, 1137, 62, 26675, 62, 525, 62, 19023, 14692, 9127, 8973, 8, 198, 198, 53, 2885, 1137, 62, 26675, 62, 525, 62, 19023, 796, 569, 2885, 1137, 62, 26675, 62, 525, 62, 19023, 13, 14781, 7, 23912, 1424, 796, 14631, 16345, 2430, 9127, 33116, 198, 220, 220, 220, 220, 220, 220, 220, 220, 220, 220, 220, 220, 220, 220, 220, 220, 220, 220, 220, 220, 220, 220, 220, 220, 220, 220, 220, 220, 220, 220, 220, 220, 220, 220, 220, 220, 220, 220, 220, 220, 220, 220, 220, 220, 220, 220, 220, 220, 220, 220, 220, 220, 220, 16488, 796, 366, 28665, 82, 4943, 198, 198, 11274, 40779, 62, 19023, 82, 796, 922, 40779, 62, 19023, 82, 13, 647, 469, 7, 53, 2885, 1137, 62, 26675, 62, 525, 62, 19023, 11, 198, 220, 220, 220, 220, 220, 220, 220, 220, 220, 220, 220, 220, 220, 220, 220, 220, 220, 220, 220, 220, 220, 220, 220, 220, 220, 220, 220, 220, 220, 220, 220, 220, 220, 220, 220, 220, 220, 220, 220, 220, 220, 220, 220, 703, 796, 366, 9464, 1600, 198, 220, 220, 220, 220, 220, 220, 220, 220, 220, 220, 220, 220, 220, 220, 220, 220, 220, 220, 220, 220, 220, 220, 220, 220, 220, 220, 220, 220, 220, 220, 220, 220, 220, 220, 220, 220, 220, 220, 220, 220, 220, 220, 220, 319, 796, 366, 19023, 62, 312, 4943, 198, 198, 2, 16626, 11420, 36472, 1366, 11420, 198, 198, 39344, 62, 46428, 796, 10644, 7203, 40720, 40720, 7890, 14, 20930, 62, 43420, 14, 11274, 40779, 62, 19023, 82, 62, 38200, 8863, 13, 40664, 4943, 198, 11274, 40779, 62, 19023, 82, 13, 1462, 62, 40664, 7, 39344, 62, 46428, 11, 21004, 796, 366, 40477, 12, 23, 1600, 6376, 796, 10352, 8, 198 ]
1.998347
2,420
import cv2, json, sys, datetime import tensorflow as tf import numpy as np from face_filter import c_face_filter from mtcnn_detect import c_MTCNNDetect from face_attr import c_face_attr_reader standard_face_size = 160 # 160(weight) * 160(height) detect_resolution = 80 # 80(weight) * 80(height) the_face_attrs_reader = c_face_attr_reader(standard_face_size) the_filter = c_face_filter() face_detect = c_MTCNNDetect(tf.Graph(), scale_factor=2) #scale_factor, rescales image for faster detection vs = cv2.VideoCapture(0) ret = 0 while ret >= 0: ret = record_single_face()
[ 11748, 269, 85, 17, 11, 33918, 11, 25064, 11, 4818, 8079, 198, 11748, 11192, 273, 11125, 355, 48700, 198, 11748, 299, 32152, 355, 45941, 198, 198, 6738, 1986, 62, 24455, 1330, 269, 62, 2550, 62, 24455, 198, 6738, 285, 23047, 20471, 62, 15255, 478, 1330, 269, 62, 44, 4825, 6144, 47504, 198, 6738, 1986, 62, 35226, 1330, 269, 62, 2550, 62, 35226, 62, 46862, 198, 198, 20307, 62, 2550, 62, 7857, 796, 13454, 1303, 13454, 7, 6551, 8, 1635, 13454, 7, 17015, 8, 198, 15255, 478, 62, 29268, 796, 4019, 1303, 4019, 7, 6551, 8, 1635, 4019, 7, 17015, 8, 198, 198, 1169, 62, 2550, 62, 1078, 3808, 62, 46862, 796, 269, 62, 2550, 62, 35226, 62, 46862, 7, 20307, 62, 2550, 62, 7857, 8, 198, 1169, 62, 24455, 796, 269, 62, 2550, 62, 24455, 3419, 198, 2550, 62, 15255, 478, 796, 269, 62, 44, 4825, 6144, 47504, 7, 27110, 13, 37065, 22784, 5046, 62, 31412, 28, 17, 8, 1303, 9888, 62, 31412, 11, 6811, 2040, 2939, 329, 5443, 13326, 198, 14259, 796, 269, 85, 17, 13, 10798, 49630, 7, 15, 8, 198, 198, 1186, 796, 657, 198, 4514, 1005, 18189, 657, 25, 198, 220, 220, 220, 1005, 796, 1700, 62, 29762, 62, 2550, 3419 ]
2.814634
205
from pandac import PandaModules as PM from direct.directnotify import DirectNotifyGlobal from direct.showbase.PythonUtil import list2dict, uniqueElements import string import LevelConstants import types if __dev__: import os
[ 6738, 19798, 330, 1330, 41112, 5841, 5028, 355, 3122, 198, 6738, 1277, 13, 12942, 1662, 1958, 1330, 4128, 3673, 1958, 22289, 198, 6738, 1277, 13, 12860, 8692, 13, 37906, 18274, 346, 1330, 1351, 17, 11600, 11, 3748, 36, 3639, 198, 11748, 4731, 198, 11748, 5684, 34184, 1187, 198, 11748, 3858, 198, 361, 11593, 7959, 834, 25, 198, 220, 220, 220, 1330, 28686, 198 ]
3.634921
63
#!/usr/bin/env python # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # Copyright (c) 2017 Jamf. All rights reserved. # # Redistribution and use in source and binary forms, with or without # modification, are permitted provided that the following conditions are met: # * Redistributions of source code must retain the above copyright # notice, this list of conditions and the following disclaimer. # * Redistributions in binary form must reproduce the above copyright # notice, this list of conditions and the following disclaimer in the # documentation and/or other materials provided with the distribution. # * Neither the name of the Jamf nor the names of its contributors may be # used to endorse or promote products derived from this software without # specific prior written permission. # # THIS SOFTWARE IS PROVIDED BY JAMF SOFTWARE, LLC "AS IS" AND ANY # EXPRESS OR IMPLIED WARRANTIES, INCLUDING, BUT NOT LIMITED TO, THE IMPLIED # WARRANTIES OF MERCHANTABILITY AND FITNESS FOR A PARTICULAR PURPOSE ARE # DISCLAIMED. IN NO EVENT SHALL JAMF SOFTWARE, LLC BE LIABLE FOR ANY # DIRECT, INDIRECT, INCIDENTAL, SPECIAL, EXEMPLARY, OR CONSEQUENTIAL DAMAGES # (INCLUDING, BUT NOT LIMITED TO, PROCUREMENT OF SUBSTITUTE GOODS OR SERVICES; # LOSS OF USE, DATA, OR PROFITS; OR BUSINESS INTERRUPTION) HOWEVER CAUSED AND # ON ANY THEORY OF LIABILITY, WHETHER IN CONTRACT, STRICT LIABILITY, OR TORT # (INCLUDING NEGLIGENCE OR OTHERWISE) ARISING IN ANY WAY OUT OF THE USE OF THIS # SOFTWARE, EVEN IF ADVISED OF THE POSSIBILITY OF SUCH DAMAGE. # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # This script was modified from Andrina Kelly's version presented at JNUC2013 for allowing # a user to elevate their privelages to administrator once per day for 60 minutes. After # the 60 minutes if a user created a new admin account that account will have admin rights # also revoked. # # To accomplish this the following will be performed: # - A launch daemon will be put in place in order to remove admin rights # - Log will be written to tempAdmin.log # - This policy in Jamf will be set to only be allowed once per day # # REQUIREMENTS: # - Jamf Pro # - Policy for enabling tempAdmin via Self Service # - Policy to remove tempAdmin via custom trigger # - tempAdmin.sh & removeTempAdmin.sh Scripts # # # Written by: Joshua Roskos | Professional Services Engineer | Jamf # # Created On: June 20th, 2017 # Updated On: July 26th, 2017 # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # IMPORTS # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # import os, plistlib, pwd, grp, subprocess, sys from SystemConfiguration import SCDynamicStoreCopyConsoleUser from datetime import datetime # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # VARIABLES # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # userName = (SCDynamicStoreCopyConsoleUser(None, None, None) or [None])[0] # get the logged in user's name workingDir = '/usr/local/jamfps/' # working directory for script launchdFile = 'com.jamfps.adminremove.plist' # launch daemon file name launchdLabel = launchdFile.replace('.plist', '') # launch daemon label plistFile = 'MakeMeAdmin.plist' # settings file name tempAdminLog = 'tempAdmin.log' # script log file adminTimer = 3600 # how long should they have admin rights for (in seconds) policyCustomTrigger = 'adminremove' # custom trigger specified for removeTempAdmin.py policy # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # LAUNCH DAEMON # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # place launchd plist to call JSS policy to remove admin rights. print 'Creating LaunchDaemon...' launchDaemon = { 'Label':launchdLabel, 'LaunchOnlyOnce':True, 'ProgramArguments':['/usr/local/jamf/bin/jamf', 'policy', '-trigger', policyCustomTrigger], 'StartInterval':adminTimer, 'UserName':'root', } plistlib.writePlist(launchDaemon, '/Library/LaunchDaemons/' + launchdFile) # set the permission on the file just made. userID = pwd.getpwnam("root").pw_uid groupID = grp.getgrnam("wheel").gr_gid os.chown('/Library/LaunchDaemons/' + launchdFile, userID, groupID) os.chmod('/Library/LaunchDaemons/' + launchdFile, 0644) # load the removal plist timer. print 'Loading LaunchDaemon...' subprocess.call(["launchctl", "load", "-w", '/Library/LaunchDaemons/' + launchdFile]) # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # APPLICATION # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # build log files if not os.path.exists(workingDir): os.makedirs(workingDir) # record user that will need to have admin rights removed # record current existing admins print 'Retrieving List of Current Admins...' currentAdmins = grp.getgrnam('admin').gr_mem print 'Updating Plist...' plist = { 'User2Remove':userName, 'CurrentAdminUsers':currentAdmins} plistlib.writePlist(plist, workingDir + plistFile) # give current logged user admin rights subprocess.call(["dseditgroup", "-o", "edit", "-a", userName, "-t", "user", "admin"]) # add log entry log = open(workingDir + tempAdminLog, "a+") log.write("{} - MakeMeAdmin Granted Admin Rights for {}\r\n".format(datetime.now(), userName)) log.close() print 'Granted Admin Right to ' + userName
[ 2, 48443, 14629, 14, 8800, 14, 24330, 21015, 198, 198, 2, 1303, 1303, 1303, 1303, 1303, 1303, 1303, 1303, 1303, 1303, 1303, 1303, 1303, 1303, 1303, 1303, 1303, 1303, 1303, 1303, 1303, 1303, 1303, 1303, 1303, 1303, 1303, 1303, 1303, 1303, 1303, 1303, 1303, 1303, 1303, 1303, 1303, 1303, 1303, 1303, 1303, 1303, 1303, 1303, 1303, 220, 198, 2, 198, 2, 15069, 357, 66, 8, 2177, 9986, 69, 13, 220, 1439, 2489, 10395, 13, 198, 2, 198, 2, 220, 220, 220, 220, 220, 220, 2297, 396, 3890, 290, 779, 287, 2723, 290, 13934, 5107, 11, 351, 393, 1231, 198, 2, 220, 220, 220, 220, 220, 220, 17613, 11, 389, 10431, 2810, 326, 262, 1708, 3403, 389, 1138, 25, 198, 2, 220, 220, 220, 220, 220, 220, 220, 220, 220, 220, 220, 220, 220, 220, 1635, 2297, 396, 2455, 507, 286, 2723, 2438, 1276, 12377, 262, 2029, 6634, 198, 2, 220, 220, 220, 220, 220, 220, 220, 220, 220, 220, 220, 220, 220, 220, 220, 220, 4003, 11, 428, 1351, 286, 3403, 290, 262, 1708, 37592, 13, 198, 2, 220, 220, 220, 220, 220, 220, 220, 220, 220, 220, 220, 220, 220, 220, 1635, 2297, 396, 2455, 507, 287, 13934, 1296, 1276, 22919, 262, 2029, 6634, 198, 2, 220, 220, 220, 220, 220, 220, 220, 220, 220, 220, 220, 220, 220, 220, 220, 220, 4003, 11, 428, 1351, 286, 3403, 290, 262, 1708, 37592, 287, 262, 198, 2, 220, 220, 220, 220, 220, 220, 220, 220, 220, 220, 220, 220, 220, 220, 220, 220, 10314, 290, 14, 273, 584, 5696, 2810, 351, 262, 6082, 13, 198, 2, 220, 220, 220, 220, 220, 220, 220, 220, 220, 220, 220, 220, 220, 220, 1635, 16126, 262, 1438, 286, 262, 9986, 69, 4249, 262, 3891, 286, 663, 20420, 743, 307, 198, 2, 220, 220, 220, 220, 220, 220, 220, 220, 220, 220, 220, 220, 220, 220, 220, 220, 973, 284, 11438, 393, 7719, 3186, 10944, 422, 428, 3788, 1231, 220, 198, 2, 220, 220, 220, 220, 220, 220, 220, 220, 220, 220, 220, 220, 220, 220, 220, 220, 2176, 3161, 3194, 7170, 13, 198, 2, 198, 2, 220, 220, 220, 220, 220, 220, 12680, 47466, 3180, 36592, 2389, 1961, 11050, 449, 2390, 37, 47466, 11, 11419, 366, 1921, 3180, 1, 5357, 15529, 198, 2, 220, 220, 220, 220, 220, 220, 7788, 32761, 6375, 8959, 49094, 34764, 11015, 11, 47783, 2751, 11, 21728, 5626, 40880, 5390, 11, 3336, 8959, 49094, 198, 2, 220, 220, 220, 220, 220, 220, 34764, 11015, 3963, 34482, 3398, 1565, 5603, 25382, 5357, 376, 46144, 7473, 317, 16652, 2149, 37232, 33079, 48933, 15986, 198, 2, 220, 220, 220, 220, 220, 220, 13954, 48778, 1961, 13, 3268, 8005, 49261, 50163, 449, 2390, 37, 47466, 11, 11419, 9348, 43031, 19146, 7473, 15529, 198, 2, 220, 220, 220, 220, 220, 220, 42242, 11, 3268, 17931, 23988, 11, 19387, 25256, 1847, 11, 38846, 11, 7788, 3620, 6489, 13153, 11, 6375, 7102, 5188, 10917, 3525, 12576, 29506, 25552, 198, 2, 220, 220, 220, 220, 220, 220, 357, 1268, 39149, 2751, 11, 21728, 5626, 40880, 5390, 11, 41755, 11335, 10979, 3963, 28932, 2257, 2043, 37780, 21090, 50, 6375, 49254, 26, 198, 2, 220, 220, 220, 220, 220, 220, 406, 18420, 3963, 23210, 11, 42865, 11, 6375, 4810, 19238, 29722, 26, 6375, 43949, 44180, 23255, 49, 8577, 24131, 8, 29630, 36, 5959, 7257, 2937, 1961, 5357, 198, 2, 220, 220, 220, 220, 220, 220, 6177, 15529, 3336, 15513, 3963, 43031, 25382, 11, 7655, 2767, 16879, 3268, 27342, 10659, 11, 19269, 18379, 43031, 25382, 11, 6375, 309, 9863, 198, 2, 220, 220, 220, 220, 220, 220, 357, 1268, 39149, 2751, 399, 7156, 43, 3528, 18310, 6375, 25401, 54, 24352, 8, 5923, 1797, 2751, 3268, 15529, 34882, 16289, 3963, 3336, 23210, 3963, 12680, 198, 2, 220, 220, 220, 220, 220, 220, 47466, 11, 45886, 16876, 5984, 29817, 1961, 3963, 3336, 28069, 11584, 25382, 3963, 13558, 3398, 29506, 11879, 13, 198, 2, 198, 2, 1303, 1303, 1303, 1303, 1303, 1303, 1303, 1303, 1303, 1303, 1303, 1303, 1303, 1303, 1303, 1303, 1303, 1303, 1303, 1303, 1303, 1303, 1303, 1303, 1303, 1303, 1303, 1303, 1303, 1303, 1303, 1303, 1303, 1303, 1303, 1303, 1303, 1303, 1303, 1303, 1303, 1303, 1303, 1303, 1303, 220, 198, 198, 2, 1303, 1303, 1303, 1303, 1303, 1303, 1303, 1303, 1303, 1303, 1303, 1303, 1303, 1303, 1303, 1303, 1303, 1303, 1303, 1303, 1303, 1303, 1303, 1303, 1303, 1303, 1303, 1303, 1303, 1303, 1303, 1303, 1303, 1303, 1303, 1303, 1303, 1303, 1303, 1303, 1303, 1303, 1303, 1303, 1303, 220, 198, 2, 220, 198, 2, 770, 4226, 373, 9518, 422, 843, 22267, 9077, 338, 2196, 5545, 379, 449, 45, 9598, 6390, 329, 5086, 198, 2, 257, 2836, 284, 36830, 511, 1293, 626, 1095, 284, 18382, 1752, 583, 1110, 329, 3126, 2431, 13, 2293, 220, 198, 2, 262, 3126, 2431, 611, 257, 2836, 2727, 257, 649, 13169, 1848, 326, 1848, 481, 423, 13169, 2489, 198, 2, 635, 30809, 13, 198, 2, 198, 2, 1675, 9989, 428, 262, 1708, 481, 307, 6157, 25, 198, 2, 197, 197, 197, 12, 317, 4219, 33386, 481, 307, 1234, 287, 1295, 287, 1502, 284, 4781, 13169, 2489, 198, 2, 197, 197, 197, 12, 5972, 481, 307, 3194, 284, 20218, 46787, 13, 6404, 198, 2, 197, 197, 197, 12, 770, 2450, 287, 9986, 69, 481, 307, 900, 284, 691, 307, 3142, 1752, 583, 1110, 198, 2, 198, 2, 4526, 49128, 28957, 25, 198, 2, 197, 197, 197, 12, 9986, 69, 1041, 198, 2, 197, 197, 197, 12, 7820, 329, 15882, 20218, 46787, 2884, 12189, 4809, 198, 2, 197, 197, 197, 12, 7820, 284, 4781, 20218, 46787, 2884, 2183, 7616, 198, 2, 197, 197, 197, 12, 20218, 46787, 13, 1477, 1222, 4781, 30782, 46787, 13, 1477, 12327, 82, 198, 2, 198, 2, 198, 2, 22503, 416, 25, 20700, 10018, 46150, 930, 18612, 6168, 23164, 930, 9986, 69, 198, 2, 198, 2, 15622, 1550, 25, 2795, 1160, 400, 11, 2177, 198, 2, 19433, 1550, 25, 2901, 2608, 400, 11, 2177, 198, 2, 220, 198, 2, 1303, 1303, 1303, 1303, 1303, 1303, 1303, 1303, 1303, 1303, 1303, 1303, 1303, 1303, 1303, 1303, 1303, 1303, 1303, 1303, 1303, 1303, 1303, 1303, 1303, 1303, 1303, 1303, 1303, 1303, 1303, 1303, 1303, 1303, 1303, 1303, 1303, 1303, 1303, 1303, 1303, 1303, 1303, 1303, 1303, 220, 198, 198, 2, 1303, 1303, 1303, 1303, 1303, 1303, 1303, 1303, 1303, 1303, 1303, 1303, 1303, 1303, 1303, 1303, 1303, 1303, 1303, 1303, 1303, 1303, 1303, 1303, 1303, 1303, 1303, 1303, 1303, 1303, 1303, 1303, 1303, 1303, 1303, 1303, 1303, 1303, 1303, 1303, 1303, 1303, 1303, 1303, 1303, 220, 198, 2, 30023, 33002, 198, 2, 1303, 1303, 1303, 1303, 1303, 1303, 1303, 1303, 1303, 1303, 1303, 1303, 1303, 1303, 1303, 1303, 1303, 1303, 1303, 1303, 1303, 1303, 1303, 1303, 1303, 1303, 1303, 1303, 1303, 1303, 1303, 1303, 1303, 1303, 1303, 1303, 1303, 1303, 1303, 1303, 1303, 1303, 1303, 1303, 1303, 220, 198, 198, 11748, 28686, 11, 458, 396, 8019, 11, 279, 16993, 11, 1036, 79, 11, 850, 14681, 11, 25064, 198, 6738, 4482, 38149, 1330, 6374, 44090, 22658, 29881, 47581, 12982, 198, 6738, 4818, 8079, 1330, 4818, 8079, 628, 198, 2, 1303, 1303, 1303, 1303, 1303, 1303, 1303, 1303, 1303, 1303, 1303, 1303, 1303, 1303, 1303, 1303, 1303, 1303, 1303, 1303, 1303, 1303, 1303, 1303, 1303, 1303, 1303, 1303, 1303, 1303, 1303, 1303, 1303, 1303, 1303, 1303, 1303, 1303, 1303, 1303, 1303, 1303, 1303, 1303, 1303, 220, 198, 2, 569, 1503, 3539, 9148, 1546, 198, 2, 1303, 1303, 1303, 1303, 1303, 1303, 1303, 1303, 1303, 1303, 1303, 1303, 1303, 1303, 1303, 1303, 1303, 1303, 1303, 1303, 1303, 1303, 1303, 1303, 1303, 1303, 1303, 1303, 1303, 1303, 1303, 1303, 1303, 1303, 1303, 1303, 1303, 1303, 1303, 1303, 1303, 1303, 1303, 1303, 1303, 220, 198, 198, 7220, 5376, 796, 357, 6173, 44090, 22658, 29881, 47581, 12982, 7, 14202, 11, 6045, 11, 6045, 8, 393, 685, 14202, 12962, 58, 15, 60, 220, 220, 1303, 651, 262, 18832, 287, 2836, 338, 1438, 198, 16090, 35277, 796, 31051, 14629, 14, 12001, 14, 39159, 29647, 14, 6, 220, 220, 220, 220, 220, 220, 220, 220, 220, 220, 220, 220, 220, 220, 220, 220, 220, 220, 220, 220, 220, 220, 220, 220, 220, 220, 220, 220, 220, 220, 220, 220, 220, 220, 220, 220, 220, 220, 220, 220, 220, 220, 1303, 1762, 8619, 329, 4226, 198, 35681, 67, 8979, 796, 705, 785, 13, 39159, 29647, 13, 28482, 28956, 13, 489, 396, 6, 220, 220, 220, 220, 220, 220, 220, 220, 220, 220, 220, 220, 220, 220, 220, 220, 220, 220, 220, 220, 220, 220, 220, 220, 220, 220, 220, 220, 220, 220, 220, 1303, 4219, 33386, 2393, 1438, 198, 35681, 67, 33986, 796, 4219, 67, 8979, 13, 33491, 7, 4458, 489, 396, 3256, 10148, 8, 220, 220, 220, 220, 220, 220, 220, 220, 220, 220, 220, 220, 220, 220, 220, 220, 220, 220, 220, 220, 220, 220, 220, 220, 220, 220, 220, 1303, 4219, 33386, 6167, 198, 489, 396, 8979, 796, 705, 12050, 5308, 46787, 13, 489, 396, 6, 220, 220, 220, 220, 220, 220, 220, 220, 220, 220, 220, 220, 220, 220, 220, 220, 220, 220, 220, 220, 220, 220, 220, 220, 220, 220, 220, 220, 220, 220, 220, 220, 220, 220, 220, 220, 220, 220, 220, 220, 220, 220, 220, 220, 1303, 6460, 2393, 1438, 198, 29510, 46787, 11187, 796, 705, 29510, 46787, 13, 6404, 6, 220, 220, 220, 220, 220, 220, 220, 220, 220, 220, 220, 220, 220, 220, 220, 220, 220, 220, 220, 220, 220, 220, 220, 220, 220, 220, 220, 220, 220, 220, 220, 220, 220, 220, 220, 220, 220, 220, 220, 220, 220, 220, 220, 220, 220, 1303, 4226, 2604, 2393, 198, 28482, 48801, 796, 4570, 405, 220, 220, 220, 220, 220, 220, 220, 220, 220, 220, 220, 220, 220, 220, 220, 220, 220, 220, 220, 220, 220, 220, 220, 220, 220, 220, 220, 220, 220, 220, 220, 220, 220, 220, 220, 220, 220, 220, 220, 220, 220, 220, 220, 220, 220, 220, 220, 220, 220, 220, 220, 220, 220, 220, 220, 220, 220, 220, 1303, 703, 890, 815, 484, 423, 13169, 2489, 329, 357, 259, 4201, 8, 198, 30586, 15022, 48344, 796, 705, 28482, 28956, 6, 220, 220, 220, 220, 220, 220, 220, 220, 220, 220, 220, 220, 220, 220, 220, 220, 220, 220, 220, 220, 220, 220, 220, 220, 220, 220, 220, 220, 220, 220, 220, 220, 220, 220, 220, 220, 220, 220, 220, 220, 1303, 2183, 7616, 7368, 329, 4781, 30782, 46787, 13, 9078, 2450, 198, 198, 2, 1303, 1303, 1303, 1303, 1303, 1303, 1303, 1303, 1303, 1303, 1303, 1303, 1303, 1303, 1303, 1303, 1303, 1303, 1303, 1303, 1303, 1303, 1303, 1303, 1303, 1303, 1303, 1303, 1303, 1303, 1303, 1303, 1303, 1303, 1303, 1303, 1303, 1303, 1303, 1303, 1303, 1303, 1303, 1303, 1303, 220, 198, 2, 9131, 47461, 17051, 3620, 1340, 198, 2, 1303, 1303, 1303, 1303, 1303, 1303, 1303, 1303, 1303, 1303, 1303, 1303, 1303, 1303, 1303, 1303, 1303, 1303, 1303, 1303, 1303, 1303, 1303, 1303, 1303, 1303, 1303, 1303, 1303, 1303, 1303, 1303, 1303, 1303, 1303, 1303, 1303, 1303, 1303, 1303, 1303, 1303, 1303, 1303, 1303, 220, 198, 198, 2, 1295, 4219, 67, 458, 396, 284, 869, 449, 5432, 2450, 284, 4781, 13169, 2489, 13, 198, 4798, 705, 32071, 21225, 26531, 7966, 986, 6, 198, 35681, 26531, 7966, 796, 1391, 705, 33986, 10354, 35681, 67, 33986, 11, 198, 220, 220, 220, 220, 220, 220, 220, 220, 220, 220, 220, 220, 220, 220, 220, 220, 705, 38296, 10049, 7454, 10354, 17821, 11, 198, 220, 220, 220, 220, 220, 220, 220, 220, 220, 220, 220, 220, 220, 220, 220, 220, 705, 15167, 28100, 2886, 10354, 17816, 14, 14629, 14, 12001, 14, 39159, 69, 14, 8800, 14, 39159, 69, 3256, 705, 30586, 3256, 705, 12, 46284, 3256, 2450, 15022, 48344, 4357, 198, 220, 220, 220, 220, 220, 220, 220, 220, 220, 220, 220, 220, 220, 220, 220, 220, 705, 10434, 9492, 2100, 10354, 28482, 48801, 11, 198, 220, 220, 220, 220, 220, 220, 220, 220, 220, 220, 220, 220, 220, 220, 220, 220, 705, 12982, 5376, 10354, 6, 15763, 3256, 198, 220, 220, 220, 220, 220, 220, 220, 220, 220, 220, 220, 220, 220, 220, 220, 220, 1782, 198, 489, 396, 8019, 13, 13564, 3646, 396, 7, 35681, 26531, 7966, 11, 31051, 23377, 14, 38296, 26531, 368, 684, 14, 6, 1343, 4219, 67, 8979, 8, 198, 198, 2, 900, 262, 7170, 319, 262, 2393, 655, 925, 13, 198, 7220, 2389, 796, 279, 16993, 13, 1136, 79, 675, 321, 7203, 15763, 11074, 79, 86, 62, 27112, 198, 8094, 2389, 796, 1036, 79, 13, 1136, 2164, 7402, 7203, 22001, 11074, 2164, 62, 70, 312, 198, 418, 13, 354, 593, 10786, 14, 23377, 14, 38296, 26531, 368, 684, 14, 6, 1343, 4219, 67, 8979, 11, 2836, 2389, 11, 1448, 2389, 8, 198, 418, 13, 354, 4666, 10786, 14, 23377, 14, 38296, 26531, 368, 684, 14, 6, 1343, 4219, 67, 8979, 11, 657, 29173, 8, 198, 198, 2, 3440, 262, 9934, 458, 396, 19781, 13, 220, 198, 4798, 705, 19031, 21225, 26531, 7966, 986, 6, 198, 7266, 14681, 13, 13345, 7, 14692, 35681, 34168, 1600, 366, 2220, 1600, 27444, 86, 1600, 31051, 23377, 14, 38296, 26531, 368, 684, 14, 6, 1343, 4219, 67, 8979, 12962, 198, 198, 2, 1303, 1303, 1303, 1303, 1303, 1303, 1303, 1303, 1303, 1303, 1303, 1303, 1303, 1303, 1303, 1303, 1303, 1303, 1303, 1303, 1303, 1303, 1303, 1303, 1303, 1303, 1303, 1303, 1303, 1303, 1303, 1303, 1303, 1303, 1303, 1303, 1303, 1303, 1303, 1303, 1303, 1303, 1303, 1303, 1303, 220, 198, 2, 39421, 6234, 198, 2, 1303, 1303, 1303, 1303, 1303, 1303, 1303, 1303, 1303, 1303, 1303, 1303, 1303, 1303, 1303, 1303, 1303, 1303, 1303, 1303, 1303, 1303, 1303, 1303, 1303, 1303, 1303, 1303, 1303, 1303, 1303, 1303, 1303, 1303, 1303, 1303, 1303, 1303, 1303, 1303, 1303, 1303, 1303, 1303, 1303, 220, 198, 198, 2, 1382, 2604, 3696, 198, 361, 407, 28686, 13, 6978, 13, 1069, 1023, 7, 16090, 35277, 2599, 198, 220, 220, 220, 28686, 13, 76, 4335, 17062, 7, 16090, 35277, 8, 198, 198, 2, 1700, 2836, 326, 481, 761, 284, 423, 13169, 2489, 4615, 198, 2, 1700, 1459, 4683, 44563, 198, 4798, 705, 9781, 37418, 7343, 286, 9236, 1215, 42951, 986, 6, 198, 14421, 2782, 42951, 796, 1036, 79, 13, 1136, 2164, 7402, 10786, 28482, 27691, 2164, 62, 11883, 198, 4798, 705, 4933, 38734, 1345, 396, 986, 6, 198, 489, 396, 796, 1391, 705, 12982, 17, 27914, 10354, 7220, 5376, 11, 198, 220, 220, 220, 220, 220, 220, 220, 220, 220, 705, 11297, 46787, 14490, 10354, 14421, 2782, 42951, 92, 198, 489, 396, 8019, 13, 13564, 3646, 396, 7, 489, 396, 11, 1762, 35277, 1343, 458, 396, 8979, 8, 198, 198, 2, 1577, 1459, 18832, 2836, 13169, 2489, 198, 7266, 14681, 13, 13345, 7, 14692, 9310, 19312, 8094, 1600, 27444, 78, 1600, 366, 19312, 1600, 27444, 64, 1600, 2836, 5376, 11, 27444, 83, 1600, 366, 7220, 1600, 366, 28482, 8973, 8, 198, 198, 2, 751, 2604, 5726, 198, 6404, 796, 1280, 7, 16090, 35277, 1343, 20218, 46787, 11187, 11, 366, 64, 10, 4943, 198, 6404, 13, 13564, 7203, 90, 92, 532, 6889, 5308, 46787, 38842, 32053, 6923, 329, 23884, 59, 81, 59, 77, 1911, 18982, 7, 19608, 8079, 13, 2197, 22784, 2836, 5376, 4008, 198, 6404, 13, 19836, 3419, 198, 198, 4798, 705, 8642, 4126, 32053, 6498, 284, 705, 1343, 2836, 5376, 198 ]
2.492737
2,547
import hashlib message = input() print(hashlib.sha256(message.encode()).hexdigest())
[ 11748, 12234, 8019, 198, 198, 20500, 796, 5128, 3419, 198, 198, 4798, 7, 17831, 8019, 13, 26270, 11645, 7, 20500, 13, 268, 8189, 3419, 737, 33095, 12894, 395, 28955 ]
2.965517
29
# Generated by Django 3.1.6 on 2021-04-17 11:19 import django.contrib.postgres.fields from django.db import migrations, models
[ 2, 2980, 515, 416, 37770, 513, 13, 16, 13, 21, 319, 33448, 12, 3023, 12, 1558, 1367, 25, 1129, 198, 198, 11748, 42625, 14208, 13, 3642, 822, 13, 7353, 34239, 13, 25747, 198, 6738, 42625, 14208, 13, 9945, 1330, 15720, 602, 11, 4981, 628 ]
2.931818
44
# ------------------------------------------------------------------------------------------ # Copyright (c) Microsoft Corporation. All rights reserved. # Licensed under the MIT License (MIT). See LICENSE in the repo root for license information. # ------------------------------------------------------------------------------------------ from enum import Enum from typing import Any, Dict, List, Optional, Tuple import param import pytest from abex.common.generic_parsing import GenericConfig, IntTuple def test_overridable_parameter() -> None: """ Test to check overridable parameters are correctly identified. """ param_dict = ParamClass.get_overridable_parameters() assert "name" in param_dict assert "flag" in param_dict assert "seed" in param_dict assert "number" in param_dict assert "integers" in param_dict assert "optional_int" in param_dict assert "optional_float" in param_dict assert "tuple1" in param_dict assert "int_tuple" in param_dict assert "enum" in param_dict assert "readonly" not in param_dict assert "_non_override" not in param_dict assert "constant" not in param_dict def test_create_parser() -> None: """ Check that parse_args works as expected, with both non default and default values. """ check(["--name=foo"], "name", "foo") check(["--seed", "42"], "seed", 42) check(["--seed", ""], "seed", 42) check(["--number", "2.17"], "number", 2.17) check(["--number", ""], "number", 3.14) check(["--integers", "1,2,3"], "integers", [1, 2, 3]) check(["--optional_int", ""], "optional_int", None) check(["--optional_int", "2"], "optional_int", 2) check(["--optional_float", ""], "optional_float", None) check(["--optional_float", "3.14"], "optional_float", 3.14) check(["--tuple1", "1,2"], "tuple1", (1, 2.0)) check(["--int_tuple", "1,2,3"], "int_tuple", (1, 2, 3)) check(["--enum=2"], "enum", ParamEnum.EnumValue2) check(["--floats=1,2,3.14"], "floats", [1.0, 2.0, 3.14]) check(["--integers=1,2,3"], "integers", [1, 2, 3]) check(["--flag"], "flag", True) # Check that default values are created as expected, and that the non-overridable parameters # are omitted. defaults = vars(ParamClass.create_argparser().parse_args([])) assert defaults["seed"] == 42 assert defaults["tuple1"] == (1, 2.3) assert defaults["int_tuple"] == (1, 1, 1) assert defaults["enum"] == ParamEnum.EnumValue1 assert "readonly" not in defaults assert "constant" not in defaults assert "_non_override" not in defaults # We can't test if all invalid cases are handled because argparse call sys.exit # upon errors. def test_apply_overrides() -> None: """ Test that overrides are applied correctly, ond only to overridable parameters, """ m = ParamClass() overrides = {"name": "newName", "int_tuple": (0, 1, 2)} actual_overrides = m.apply_overrides(overrides) assert actual_overrides == overrides assert all([x == i and isinstance(x, int) for i, x in enumerate(m.int_tuple)]) assert m.name == "newName" # Attempt to change seed and constant, but the latter should be ignored. change_seed: Dict[str, Any] = {"seed": 123} old_constant = m.constant changes2 = m.apply_overrides({**change_seed, "constant": "Nothing"}) assert changes2 == change_seed assert m.seed == 123 assert m.constant == old_constant @pytest.mark.parametrize("value_idx_0", [1.0, 1]) @pytest.mark.parametrize("value_idx_1", [2.0, 2]) @pytest.mark.parametrize("value_idx_2", [3.0, 3]) def test_int_tuple_validation(value_idx_0: Any, value_idx_1: Any, value_idx_2: Any) -> None: """ Test integer tuple parameter is validated correctly. """ m = ParamClass() val = (value_idx_0, value_idx_1, value_idx_2) if not all([isinstance(x, int) for x in val]): with pytest.raises(ValueError): m.int_tuple = (value_idx_0, value_idx_1, value_idx_2) else: m.int_tuple = (value_idx_0, value_idx_1, value_idx_2)
[ 2, 220, 16529, 22369, 438, 198, 2, 220, 15069, 357, 66, 8, 5413, 10501, 13, 1439, 2489, 10395, 13, 198, 2, 220, 49962, 739, 262, 17168, 13789, 357, 36393, 737, 4091, 38559, 24290, 287, 262, 29924, 6808, 329, 5964, 1321, 13, 198, 2, 220, 16529, 22369, 438, 198, 6738, 33829, 1330, 2039, 388, 198, 6738, 19720, 1330, 4377, 11, 360, 713, 11, 7343, 11, 32233, 11, 309, 29291, 198, 198, 11748, 5772, 198, 11748, 12972, 9288, 198, 6738, 450, 1069, 13, 11321, 13, 41357, 62, 79, 945, 278, 1330, 42044, 16934, 11, 2558, 51, 29291, 628, 628, 198, 4299, 1332, 62, 2502, 6058, 540, 62, 17143, 2357, 3419, 4613, 6045, 25, 198, 220, 220, 220, 37227, 198, 220, 220, 220, 6208, 284, 2198, 625, 6058, 540, 10007, 389, 9380, 5174, 13, 198, 220, 220, 220, 37227, 198, 220, 220, 220, 5772, 62, 11600, 796, 25139, 9487, 13, 1136, 62, 2502, 6058, 540, 62, 17143, 7307, 3419, 198, 220, 220, 220, 6818, 366, 3672, 1, 287, 5772, 62, 11600, 198, 220, 220, 220, 6818, 366, 32109, 1, 287, 5772, 62, 11600, 198, 220, 220, 220, 6818, 366, 28826, 1, 287, 5772, 62, 11600, 198, 220, 220, 220, 6818, 366, 17618, 1, 287, 5772, 62, 11600, 198, 220, 220, 220, 6818, 366, 18908, 364, 1, 287, 5772, 62, 11600, 198, 220, 220, 220, 6818, 366, 25968, 62, 600, 1, 287, 5772, 62, 11600, 198, 220, 220, 220, 6818, 366, 25968, 62, 22468, 1, 287, 5772, 62, 11600, 198, 220, 220, 220, 6818, 366, 83, 29291, 16, 1, 287, 5772, 62, 11600, 198, 220, 220, 220, 6818, 366, 600, 62, 83, 29291, 1, 287, 5772, 62, 11600, 198, 220, 220, 220, 6818, 366, 44709, 1, 287, 5772, 62, 11600, 198, 220, 220, 220, 6818, 366, 961, 8807, 1, 407, 287, 5772, 62, 11600, 198, 220, 220, 220, 6818, 45434, 13159, 62, 2502, 13154, 1, 407, 287, 5772, 62, 11600, 198, 220, 220, 220, 6818, 366, 9979, 415, 1, 407, 287, 5772, 62, 11600, 628, 198, 4299, 1332, 62, 17953, 62, 48610, 3419, 4613, 6045, 25, 198, 220, 220, 220, 37227, 198, 220, 220, 220, 6822, 326, 21136, 62, 22046, 2499, 355, 2938, 11, 351, 1111, 1729, 4277, 290, 4277, 3815, 13, 198, 220, 220, 220, 37227, 628, 220, 220, 220, 2198, 7, 14692, 438, 3672, 28, 21943, 33116, 366, 3672, 1600, 366, 21943, 4943, 198, 220, 220, 220, 2198, 7, 14692, 438, 28826, 1600, 366, 3682, 33116, 366, 28826, 1600, 5433, 8, 198, 220, 220, 220, 2198, 7, 14692, 438, 28826, 1600, 13538, 4357, 366, 28826, 1600, 5433, 8, 198, 220, 220, 220, 2198, 7, 14692, 438, 17618, 1600, 366, 17, 13, 1558, 33116, 366, 17618, 1600, 362, 13, 1558, 8, 198, 220, 220, 220, 2198, 7, 14692, 438, 17618, 1600, 13538, 4357, 366, 17618, 1600, 513, 13, 1415, 8, 198, 220, 220, 220, 2198, 7, 14692, 438, 18908, 364, 1600, 366, 16, 11, 17, 11, 18, 33116, 366, 18908, 364, 1600, 685, 16, 11, 362, 11, 513, 12962, 198, 220, 220, 220, 2198, 7, 14692, 438, 25968, 62, 600, 1600, 13538, 4357, 366, 25968, 62, 600, 1600, 6045, 8, 198, 220, 220, 220, 2198, 7, 14692, 438, 25968, 62, 600, 1600, 366, 17, 33116, 366, 25968, 62, 600, 1600, 362, 8, 198, 220, 220, 220, 2198, 7, 14692, 438, 25968, 62, 22468, 1600, 13538, 4357, 366, 25968, 62, 22468, 1600, 6045, 8, 198, 220, 220, 220, 2198, 7, 14692, 438, 25968, 62, 22468, 1600, 366, 18, 13, 1415, 33116, 366, 25968, 62, 22468, 1600, 513, 13, 1415, 8, 198, 220, 220, 220, 2198, 7, 14692, 438, 83, 29291, 16, 1600, 366, 16, 11, 17, 33116, 366, 83, 29291, 16, 1600, 357, 16, 11, 362, 13, 15, 4008, 198, 220, 220, 220, 2198, 7, 14692, 438, 600, 62, 83, 29291, 1600, 366, 16, 11, 17, 11, 18, 33116, 366, 600, 62, 83, 29291, 1600, 357, 16, 11, 362, 11, 513, 4008, 198, 220, 220, 220, 2198, 7, 14692, 438, 44709, 28, 17, 33116, 366, 44709, 1600, 25139, 4834, 388, 13, 4834, 388, 11395, 17, 8, 198, 220, 220, 220, 2198, 7, 14692, 438, 48679, 1381, 28, 16, 11, 17, 11, 18, 13, 1415, 33116, 366, 48679, 1381, 1600, 685, 16, 13, 15, 11, 362, 13, 15, 11, 513, 13, 1415, 12962, 198, 220, 220, 220, 2198, 7, 14692, 438, 18908, 364, 28, 16, 11, 17, 11, 18, 33116, 366, 18908, 364, 1600, 685, 16, 11, 362, 11, 513, 12962, 198, 220, 220, 220, 2198, 7, 14692, 438, 32109, 33116, 366, 32109, 1600, 6407, 8, 198, 220, 220, 220, 1303, 6822, 326, 4277, 3815, 389, 2727, 355, 2938, 11, 290, 326, 262, 1729, 12, 2502, 6058, 540, 10007, 198, 220, 220, 220, 1303, 389, 22532, 13, 198, 220, 220, 220, 26235, 796, 410, 945, 7, 22973, 9487, 13, 17953, 62, 853, 48610, 22446, 29572, 62, 22046, 7, 21737, 4008, 198, 220, 220, 220, 6818, 26235, 14692, 28826, 8973, 6624, 5433, 198, 220, 220, 220, 6818, 26235, 14692, 83, 29291, 16, 8973, 6624, 357, 16, 11, 362, 13, 18, 8, 198, 220, 220, 220, 6818, 26235, 14692, 600, 62, 83, 29291, 8973, 6624, 357, 16, 11, 352, 11, 352, 8, 198, 220, 220, 220, 6818, 26235, 14692, 44709, 8973, 6624, 25139, 4834, 388, 13, 4834, 388, 11395, 16, 198, 220, 220, 220, 6818, 366, 961, 8807, 1, 407, 287, 26235, 198, 220, 220, 220, 6818, 366, 9979, 415, 1, 407, 287, 26235, 198, 220, 220, 220, 6818, 45434, 13159, 62, 2502, 13154, 1, 407, 287, 26235, 198, 220, 220, 220, 1303, 775, 460, 470, 1332, 611, 477, 12515, 2663, 389, 12118, 780, 1822, 29572, 869, 25064, 13, 37023, 198, 220, 220, 220, 1303, 2402, 8563, 13, 628, 198, 4299, 1332, 62, 39014, 62, 2502, 81, 1460, 3419, 4613, 6045, 25, 198, 220, 220, 220, 37227, 198, 220, 220, 220, 6208, 326, 23170, 1460, 389, 5625, 9380, 11, 319, 67, 691, 284, 625, 6058, 540, 10007, 11, 198, 220, 220, 220, 37227, 198, 220, 220, 220, 285, 796, 25139, 9487, 3419, 198, 220, 220, 220, 23170, 1460, 796, 19779, 3672, 1298, 366, 3605, 5376, 1600, 366, 600, 62, 83, 29291, 1298, 357, 15, 11, 352, 11, 362, 38165, 198, 220, 220, 220, 4036, 62, 2502, 81, 1460, 796, 285, 13, 39014, 62, 2502, 81, 1460, 7, 2502, 81, 1460, 8, 198, 220, 220, 220, 6818, 4036, 62, 2502, 81, 1460, 6624, 23170, 1460, 198, 220, 220, 220, 6818, 477, 26933, 87, 6624, 1312, 290, 318, 39098, 7, 87, 11, 493, 8, 329, 1312, 11, 2124, 287, 27056, 378, 7, 76, 13, 600, 62, 83, 29291, 8, 12962, 198, 220, 220, 220, 6818, 285, 13, 3672, 6624, 366, 3605, 5376, 1, 198, 220, 220, 220, 1303, 25770, 284, 1487, 9403, 290, 6937, 11, 475, 262, 6846, 815, 307, 9514, 13, 198, 220, 220, 220, 1487, 62, 28826, 25, 360, 713, 58, 2536, 11, 4377, 60, 796, 19779, 28826, 1298, 17031, 92, 198, 220, 220, 220, 1468, 62, 9979, 415, 796, 285, 13, 9979, 415, 198, 220, 220, 220, 2458, 17, 796, 285, 13, 39014, 62, 2502, 81, 1460, 15090, 1174, 3803, 62, 28826, 11, 366, 9979, 415, 1298, 366, 18465, 20662, 8, 198, 220, 220, 220, 6818, 2458, 17, 6624, 1487, 62, 28826, 198, 220, 220, 220, 6818, 285, 13, 28826, 6624, 17031, 198, 220, 220, 220, 6818, 285, 13, 9979, 415, 6624, 1468, 62, 9979, 415, 628, 198, 31, 9078, 9288, 13, 4102, 13, 17143, 316, 380, 2736, 7203, 8367, 62, 312, 87, 62, 15, 1600, 685, 16, 13, 15, 11, 352, 12962, 198, 31, 9078, 9288, 13, 4102, 13, 17143, 316, 380, 2736, 7203, 8367, 62, 312, 87, 62, 16, 1600, 685, 17, 13, 15, 11, 362, 12962, 198, 31, 9078, 9288, 13, 4102, 13, 17143, 316, 380, 2736, 7203, 8367, 62, 312, 87, 62, 17, 1600, 685, 18, 13, 15, 11, 513, 12962, 198, 4299, 1332, 62, 600, 62, 83, 29291, 62, 12102, 341, 7, 8367, 62, 312, 87, 62, 15, 25, 4377, 11, 1988, 62, 312, 87, 62, 16, 25, 4377, 11, 1988, 62, 312, 87, 62, 17, 25, 4377, 8, 4613, 6045, 25, 198, 220, 220, 220, 37227, 198, 220, 220, 220, 6208, 18253, 46545, 11507, 318, 31031, 9380, 13, 198, 220, 220, 220, 37227, 198, 220, 220, 220, 285, 796, 25139, 9487, 3419, 198, 220, 220, 220, 1188, 796, 357, 8367, 62, 312, 87, 62, 15, 11, 1988, 62, 312, 87, 62, 16, 11, 1988, 62, 312, 87, 62, 17, 8, 198, 220, 220, 220, 611, 407, 477, 26933, 271, 39098, 7, 87, 11, 493, 8, 329, 2124, 287, 1188, 60, 2599, 198, 220, 220, 220, 220, 220, 220, 220, 351, 12972, 9288, 13, 430, 2696, 7, 11395, 12331, 2599, 198, 220, 220, 220, 220, 220, 220, 220, 220, 220, 220, 220, 285, 13, 600, 62, 83, 29291, 796, 357, 8367, 62, 312, 87, 62, 15, 11, 1988, 62, 312, 87, 62, 16, 11, 1988, 62, 312, 87, 62, 17, 8, 198, 220, 220, 220, 2073, 25, 198, 220, 220, 220, 220, 220, 220, 220, 285, 13, 600, 62, 83, 29291, 796, 357, 8367, 62, 312, 87, 62, 15, 11, 1988, 62, 312, 87, 62, 16, 11, 1988, 62, 312, 87, 62, 17, 8, 198 ]
2.676509
1,524
# coding=utf-8 # -------------------------------------------------------------------------- # Copyright (c) Microsoft Corporation. All rights reserved. # Licensed under the MIT License. See License.txt in the project root for # license information. # # Code generated by Microsoft (R) AutoRest Code Generator. # Changes may cause incorrect behavior and will be lost if the code is # regenerated. # -------------------------------------------------------------------------- from msrest.serialization import Model class VirtualNetworkConfiguration(Model): """Configuration of a virtual network to which API Management service is deployed. Variables are only populated by the server, and will be ignored when sending a request. :ivar vnetid: The virtual network ID. This is typically a GUID. Expect a null GUID by default. :vartype vnetid: str :ivar subnetname: The name of the subnet. :vartype subnetname: str :param subnet_resource_id: The full resource ID of a subnet in a virtual network to deploy the API Management service in. :type subnet_resource_id: str """ _validation = { 'vnetid': {'readonly': True}, 'subnetname': {'readonly': True}, 'subnet_resource_id': {'pattern': r'^/subscriptions/[^/]*/resourceGroups/[^/]*/providers/Microsoft.(ClassicNetwork|Network)/virtualNetworks/[^/]*/subnets/[^/]*$'}, } _attribute_map = { 'vnetid': {'key': 'vnetid', 'type': 'str'}, 'subnetname': {'key': 'subnetname', 'type': 'str'}, 'subnet_resource_id': {'key': 'subnetResourceId', 'type': 'str'}, }
[ 2, 19617, 28, 40477, 12, 23, 198, 2, 16529, 35937, 198, 2, 15069, 357, 66, 8, 5413, 10501, 13, 1439, 2489, 10395, 13, 198, 2, 49962, 739, 262, 17168, 13789, 13, 4091, 13789, 13, 14116, 287, 262, 1628, 6808, 329, 198, 2, 5964, 1321, 13, 198, 2, 198, 2, 6127, 7560, 416, 5413, 357, 49, 8, 11160, 19452, 6127, 35986, 13, 198, 2, 19179, 743, 2728, 11491, 4069, 290, 481, 307, 2626, 611, 262, 2438, 318, 198, 2, 16935, 515, 13, 198, 2, 16529, 35937, 198, 198, 6738, 13845, 2118, 13, 46911, 1634, 1330, 9104, 628, 198, 4871, 15595, 26245, 38149, 7, 17633, 2599, 198, 220, 220, 220, 37227, 38149, 286, 257, 7166, 3127, 284, 543, 7824, 8549, 2139, 318, 198, 220, 220, 220, 12380, 13, 628, 220, 220, 220, 15965, 2977, 389, 691, 22331, 416, 262, 4382, 11, 290, 481, 307, 9514, 618, 198, 220, 220, 220, 7216, 257, 2581, 13, 628, 220, 220, 220, 1058, 452, 283, 410, 3262, 312, 25, 383, 7166, 3127, 4522, 13, 770, 318, 6032, 257, 19348, 2389, 13, 23600, 257, 198, 220, 220, 220, 220, 9242, 19348, 2389, 416, 4277, 13, 198, 220, 220, 220, 1058, 85, 433, 2981, 410, 3262, 312, 25, 965, 198, 220, 220, 220, 1058, 452, 283, 850, 3262, 3672, 25, 383, 1438, 286, 262, 850, 3262, 13, 198, 220, 220, 220, 1058, 85, 433, 2981, 850, 3262, 3672, 25, 965, 198, 220, 220, 220, 1058, 17143, 850, 3262, 62, 31092, 62, 312, 25, 383, 1336, 8271, 4522, 286, 257, 850, 3262, 287, 257, 7166, 198, 220, 220, 220, 220, 3127, 284, 6061, 262, 7824, 8549, 2139, 287, 13, 198, 220, 220, 220, 1058, 4906, 850, 3262, 62, 31092, 62, 312, 25, 965, 198, 220, 220, 220, 37227, 628, 220, 220, 220, 4808, 12102, 341, 796, 1391, 198, 220, 220, 220, 220, 220, 220, 220, 705, 85, 3262, 312, 10354, 1391, 6, 961, 8807, 10354, 6407, 5512, 198, 220, 220, 220, 220, 220, 220, 220, 705, 7266, 3262, 3672, 10354, 1391, 6, 961, 8807, 10354, 6407, 5512, 198, 220, 220, 220, 220, 220, 220, 220, 705, 7266, 3262, 62, 31092, 62, 312, 10354, 1391, 6, 33279, 10354, 374, 6, 61, 14, 7266, 12048, 507, 14, 58, 61, 14, 60, 16208, 31092, 38, 14459, 14, 58, 61, 14, 60, 16208, 15234, 4157, 14, 15905, 12195, 39914, 26245, 91, 26245, 20679, 32844, 7934, 5225, 14, 58, 61, 14, 60, 16208, 7266, 45938, 14, 58, 61, 14, 60, 9, 3, 6, 5512, 198, 220, 220, 220, 1782, 628, 220, 220, 220, 4808, 42348, 62, 8899, 796, 1391, 198, 220, 220, 220, 220, 220, 220, 220, 705, 85, 3262, 312, 10354, 1391, 6, 2539, 10354, 705, 85, 3262, 312, 3256, 705, 4906, 10354, 705, 2536, 6, 5512, 198, 220, 220, 220, 220, 220, 220, 220, 705, 7266, 3262, 3672, 10354, 1391, 6, 2539, 10354, 705, 7266, 3262, 3672, 3256, 705, 4906, 10354, 705, 2536, 6, 5512, 198, 220, 220, 220, 220, 220, 220, 220, 705, 7266, 3262, 62, 31092, 62, 312, 10354, 1391, 6, 2539, 10354, 705, 7266, 3262, 26198, 7390, 3256, 705, 4906, 10354, 705, 2536, 6, 5512, 198, 220, 220, 220, 1782, 198 ]
3.099617
522
import django.shortcuts def main(request): """ request handler for '/'. """ return django.shortcuts.render(request, 'app_website/index.html', {}) # ~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ # global error handlers for app_website # ~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ def error_400(request, exception): """ request handler for a 400 error. """ context = { 'err': '[400 Bad Request] Path: ' + request.path, } return django.shortcuts.render(request, 'app_website/error.html', context) def error_403(request, exception): """ request handler for a 403 error. """ context = { 'err': '[403 Permission Denied] Path: ' + request.path, } return django.shortcuts.render(request, 'app_website/error.html', context) def error_404(request, exception): """ request handler for a 404 error. """ context = { 'err': '[404 Page Not Found] Path: ' + request.path, } return django.shortcuts.render(request, 'app_website/error.html', context) def error_500(request): """ request handler for a 500 error. """ context = { 'err': '[500 Server Error] Path: ' + request.path, } return django.shortcuts.render(request, 'app_website/error.html', context)
[ 11748, 42625, 14208, 13, 19509, 23779, 628, 198, 4299, 1388, 7, 25927, 2599, 198, 220, 37227, 198, 220, 2581, 21360, 329, 31051, 4458, 198, 220, 37227, 198, 220, 1441, 42625, 14208, 13, 19509, 23779, 13, 13287, 7, 25927, 11, 705, 1324, 62, 732, 12485, 14, 9630, 13, 6494, 3256, 23884, 8, 628, 198, 2, 220, 27156, 27156, 27156, 27156, 15116, 8728, 93, 198, 2, 3298, 4049, 32847, 329, 598, 62, 732, 12485, 198, 2, 220, 27156, 27156, 27156, 27156, 15116, 8728, 93, 628, 198, 4299, 4049, 62, 7029, 7, 25927, 11, 6631, 2599, 198, 220, 37227, 198, 220, 2581, 21360, 329, 257, 7337, 4049, 13, 198, 220, 37227, 198, 220, 4732, 796, 1391, 198, 220, 220, 220, 705, 8056, 10354, 44438, 7029, 7772, 19390, 60, 10644, 25, 705, 1343, 2581, 13, 6978, 11, 198, 220, 1782, 198, 220, 1441, 42625, 14208, 13, 19509, 23779, 13, 13287, 7, 25927, 11, 705, 1324, 62, 732, 12485, 14, 18224, 13, 6494, 3256, 4732, 8, 628, 198, 4299, 4049, 62, 31552, 7, 25927, 11, 6631, 2599, 198, 220, 37227, 198, 220, 2581, 21360, 329, 257, 38210, 4049, 13, 198, 220, 37227, 198, 220, 4732, 796, 1391, 198, 220, 220, 220, 705, 8056, 10354, 44438, 31552, 2448, 3411, 5601, 798, 60, 10644, 25, 705, 1343, 2581, 13, 6978, 11, 198, 220, 1782, 198, 220, 1441, 42625, 14208, 13, 19509, 23779, 13, 13287, 7, 25927, 11, 705, 1324, 62, 732, 12485, 14, 18224, 13, 6494, 3256, 4732, 8, 628, 198, 4299, 4049, 62, 26429, 7, 25927, 11, 6631, 2599, 198, 220, 37227, 198, 220, 2581, 21360, 329, 257, 32320, 4049, 13, 198, 220, 37227, 198, 220, 4732, 796, 1391, 198, 220, 220, 220, 705, 8056, 10354, 44438, 26429, 7873, 1892, 4062, 60, 10644, 25, 705, 1343, 2581, 13, 6978, 11, 198, 220, 1782, 198, 220, 1441, 42625, 14208, 13, 19509, 23779, 13, 13287, 7, 25927, 11, 705, 1324, 62, 732, 12485, 14, 18224, 13, 6494, 3256, 4732, 8, 628, 198, 4299, 4049, 62, 4059, 7, 25927, 2599, 198, 220, 37227, 198, 220, 2581, 21360, 329, 257, 5323, 4049, 13, 198, 220, 37227, 198, 220, 4732, 796, 1391, 198, 220, 220, 220, 705, 8056, 10354, 44438, 4059, 9652, 13047, 60, 10644, 25, 705, 1343, 2581, 13, 6978, 11, 198, 220, 1782, 198, 220, 1441, 42625, 14208, 13, 19509, 23779, 13, 13287, 7, 25927, 11, 705, 1324, 62, 732, 12485, 14, 18224, 13, 6494, 3256, 4732, 8, 198 ]
3.2225
400
from .SculptASequenceView import SculptASequenceView
[ 6738, 764, 50, 3129, 457, 1921, 4853, 594, 7680, 1330, 1446, 13327, 1921, 4853, 594, 7680, 198 ]
3.117647
17
# This code is part of Ansible, but is an independent component. # This particular file snippet, and this file snippet only, is BSD licensed. # Modules you write using this snippet, which is embedded dynamically by Ansible # still belong to the author of the module, and may assign their own license # to the complete work. # # Copyright (c) 2015 Peter Sprygada, <[email protected]> # # Redistribution and use in source and binary forms, with or without modification, # are permitted provided that the following conditions are met: # # * Redistributions of source code must retain the above copyright # notice, this list of conditions and the following disclaimer. # * Redistributions in binary form must reproduce the above copyright notice, # this list of conditions and the following disclaimer in the documentation # and/or other materials provided with the distribution. # # THIS SOFTWARE IS PROVIDED BY THE COPYRIGHT HOLDERS AND CONTRIBUTORS "AS IS" AND # ANY EXPRESS OR IMPLIED WARRANTIES, INCLUDING, BUT NOT LIMITED TO, THE IMPLIED # WARRANTIES OF MERCHANTABILITY AND FITNESS FOR A PARTICULAR PURPOSE ARE DISCLAIMED. # IN NO EVENT SHALL THE COPYRIGHT HOLDER OR CONTRIBUTORS BE LIABLE FOR ANY DIRECT, INDIRECT, # INCIDENTAL, SPECIAL, EXEMPLARY, OR CONSEQUENTIAL DAMAGES (INCLUDING, BUT NOT LIMITED TO, # PROCUREMENT OF SUBSTITUTE GOODS OR SERVICES; LOSS OF USE, DATA, OR PROFITS; OR BUSINESS # INTERRUPTION) HOWEVER CAUSED AND ON ANY THEORY OF LIABILITY, WHETHER IN CONTRACT, STRICT # LIABILITY, OR TORT (INCLUDING NEGLIGENCE OR OTHERWISE) ARISING IN ANY WAY OUT OF THE # USE OF THIS SOFTWARE, EVEN IF ADVISED OF THE POSSIBILITY OF SUCH DAMAGE. # import itertools import re from ansible.module_utils.six import string_types from ansible.module_utils.six.moves import zip, zip_longest DEFAULT_COMMENT_TOKENS = ['#', '!', '/*', '*/']
[ 2, 770, 2438, 318, 636, 286, 28038, 856, 11, 475, 318, 281, 4795, 7515, 13, 198, 2, 770, 1948, 2393, 39442, 11, 290, 428, 2393, 39442, 691, 11, 318, 347, 10305, 11971, 13, 198, 2, 3401, 5028, 345, 3551, 1262, 428, 39442, 11, 543, 318, 14553, 32366, 416, 28038, 856, 198, 2, 991, 5594, 284, 262, 1772, 286, 262, 8265, 11, 290, 743, 8333, 511, 898, 5964, 198, 2, 284, 262, 1844, 670, 13, 198, 2, 198, 2, 15069, 357, 66, 8, 1853, 5613, 1338, 563, 70, 4763, 11, 1279, 862, 79, 563, 70, 4763, 31, 504, 856, 13, 785, 29, 198, 2, 198, 2, 2297, 396, 3890, 290, 779, 287, 2723, 290, 13934, 5107, 11, 351, 393, 1231, 17613, 11, 198, 2, 389, 10431, 2810, 326, 262, 1708, 3403, 389, 1138, 25, 198, 2, 198, 2, 220, 220, 220, 1635, 2297, 396, 2455, 507, 286, 2723, 2438, 1276, 12377, 262, 2029, 6634, 198, 2, 220, 220, 220, 220, 220, 4003, 11, 428, 1351, 286, 3403, 290, 262, 1708, 37592, 13, 198, 2, 220, 220, 220, 1635, 2297, 396, 2455, 507, 287, 13934, 1296, 1276, 22919, 262, 2029, 6634, 4003, 11, 198, 2, 220, 220, 220, 220, 220, 428, 1351, 286, 3403, 290, 262, 1708, 37592, 287, 262, 10314, 198, 2, 220, 220, 220, 220, 220, 290, 14, 273, 584, 5696, 2810, 351, 262, 6082, 13, 198, 2, 198, 2, 12680, 47466, 3180, 36592, 2389, 1961, 11050, 3336, 27975, 38162, 9947, 367, 15173, 4877, 5357, 27342, 9865, 3843, 20673, 366, 1921, 3180, 1, 5357, 198, 2, 15529, 7788, 32761, 6375, 8959, 49094, 34764, 11015, 11, 47783, 2751, 11, 21728, 5626, 40880, 5390, 11, 3336, 8959, 49094, 198, 2, 34764, 11015, 3963, 34482, 3398, 1565, 5603, 25382, 5357, 376, 46144, 7473, 317, 16652, 2149, 37232, 33079, 48933, 15986, 13954, 48778, 1961, 13, 198, 2, 3268, 8005, 49261, 50163, 3336, 27975, 38162, 9947, 49707, 14418, 6375, 27342, 9865, 3843, 20673, 9348, 43031, 19146, 7473, 15529, 42242, 11, 3268, 17931, 23988, 11, 198, 2, 19387, 25256, 1847, 11, 38846, 11, 7788, 3620, 6489, 13153, 11, 6375, 7102, 5188, 10917, 3525, 12576, 29506, 25552, 357, 1268, 39149, 2751, 11, 21728, 5626, 40880, 5390, 11, 198, 2, 41755, 11335, 10979, 3963, 28932, 2257, 2043, 37780, 21090, 50, 6375, 49254, 26, 406, 18420, 3963, 23210, 11, 42865, 11, 6375, 4810, 19238, 29722, 26, 6375, 43949, 44180, 198, 2, 23255, 49, 8577, 24131, 8, 29630, 36, 5959, 7257, 2937, 1961, 5357, 6177, 15529, 3336, 15513, 3963, 43031, 25382, 11, 7655, 2767, 16879, 3268, 27342, 10659, 11, 19269, 18379, 198, 2, 43031, 25382, 11, 6375, 309, 9863, 357, 1268, 39149, 2751, 399, 7156, 43, 3528, 18310, 6375, 25401, 54, 24352, 8, 5923, 1797, 2751, 3268, 15529, 34882, 16289, 3963, 3336, 198, 2, 23210, 3963, 12680, 47466, 11, 45886, 16876, 5984, 29817, 1961, 3963, 3336, 28069, 11584, 25382, 3963, 13558, 3398, 29506, 11879, 13, 198, 2, 198, 198, 11748, 340, 861, 10141, 198, 11748, 302, 198, 198, 6738, 9093, 856, 13, 21412, 62, 26791, 13, 19412, 1330, 4731, 62, 19199, 198, 6738, 9093, 856, 13, 21412, 62, 26791, 13, 19412, 13, 76, 5241, 1330, 19974, 11, 19974, 62, 6511, 395, 198, 198, 7206, 38865, 62, 9858, 10979, 62, 10468, 42, 16938, 796, 37250, 2, 3256, 705, 0, 3256, 705, 15211, 3256, 705, 16208, 20520, 628, 198 ]
3.416819
547
import os import pytest from dvc.ignore import DvcIgnore from dvc.main import main @pytest.mark.parametrize( "file,ret,output", [("ignored", 0, True), ("not_ignored", 1, False)] ) @pytest.mark.parametrize( "file,ret,output", [ ("file", 0, "{}:1:f*\tfile\n".format(DvcIgnore.DVCIGNORE_FILE)), ("foo", 0, "{}:2:!foo\tfoo\n".format(DvcIgnore.DVCIGNORE_FILE)), ( os.path.join("dir", "foobar"), 0, "{}:1:foobar\t{}\n".format( os.path.join("dir", DvcIgnore.DVCIGNORE_FILE), os.path.join("dir", "foobar"), ), ), ], ) @pytest.mark.parametrize("non_matching", [True, False]) @pytest.mark.parametrize( "args", [ ["-n", "file"], ["-a", "file"], ["-q", "-d", "file"], ["--stdin", "file"], [], ], ) @pytest.mark.parametrize("path,ret", [({"dir": {}}, 0), ({"dir": "files"}, 1)]) @pytest.mark.parametrize( "file,ret,output", [("ignored", 0, True), ("not_ignored", 1, False)] )
[ 11748, 28686, 198, 198, 11748, 12972, 9288, 198, 198, 6738, 288, 28435, 13, 46430, 1330, 360, 28435, 32916, 382, 198, 6738, 288, 28435, 13, 12417, 1330, 1388, 628, 198, 31, 9078, 9288, 13, 4102, 13, 17143, 316, 380, 2736, 7, 198, 220, 220, 220, 366, 7753, 11, 1186, 11, 22915, 1600, 685, 7203, 570, 1850, 1600, 657, 11, 6407, 828, 5855, 1662, 62, 570, 1850, 1600, 352, 11, 10352, 15437, 198, 8, 628, 198, 31, 9078, 9288, 13, 4102, 13, 17143, 316, 380, 2736, 7, 198, 220, 220, 220, 366, 7753, 11, 1186, 11, 22915, 1600, 198, 220, 220, 220, 685, 198, 220, 220, 220, 220, 220, 220, 220, 5855, 7753, 1600, 657, 11, 45144, 38362, 16, 25, 69, 9, 59, 83, 7753, 59, 77, 1911, 18982, 7, 35, 28435, 32916, 382, 13, 35, 15922, 16284, 6965, 62, 25664, 36911, 198, 220, 220, 220, 220, 220, 220, 220, 5855, 21943, 1600, 657, 11, 45144, 38362, 17, 25, 0, 21943, 59, 83, 21943, 59, 77, 1911, 18982, 7, 35, 28435, 32916, 382, 13, 35, 15922, 16284, 6965, 62, 25664, 36911, 198, 220, 220, 220, 220, 220, 220, 220, 357, 198, 220, 220, 220, 220, 220, 220, 220, 220, 220, 220, 220, 28686, 13, 6978, 13, 22179, 7203, 15908, 1600, 366, 6513, 30973, 12340, 198, 220, 220, 220, 220, 220, 220, 220, 220, 220, 220, 220, 657, 11, 198, 220, 220, 220, 220, 220, 220, 220, 220, 220, 220, 220, 45144, 38362, 16, 25, 6513, 30973, 59, 83, 90, 32239, 77, 1911, 18982, 7, 198, 220, 220, 220, 220, 220, 220, 220, 220, 220, 220, 220, 220, 220, 220, 220, 28686, 13, 6978, 13, 22179, 7203, 15908, 1600, 360, 28435, 32916, 382, 13, 35, 15922, 16284, 6965, 62, 25664, 828, 198, 220, 220, 220, 220, 220, 220, 220, 220, 220, 220, 220, 220, 220, 220, 220, 28686, 13, 6978, 13, 22179, 7203, 15908, 1600, 366, 6513, 30973, 12340, 198, 220, 220, 220, 220, 220, 220, 220, 220, 220, 220, 220, 10612, 198, 220, 220, 220, 220, 220, 220, 220, 10612, 198, 220, 220, 220, 16589, 198, 8, 628, 198, 31, 9078, 9288, 13, 4102, 13, 17143, 316, 380, 2736, 7203, 13159, 62, 15699, 278, 1600, 685, 17821, 11, 10352, 12962, 628, 198, 31, 9078, 9288, 13, 4102, 13, 17143, 316, 380, 2736, 7, 198, 220, 220, 220, 366, 22046, 1600, 198, 220, 220, 220, 685, 198, 220, 220, 220, 220, 220, 220, 220, 14631, 12, 77, 1600, 366, 7753, 33116, 198, 220, 220, 220, 220, 220, 220, 220, 14631, 12, 64, 1600, 366, 7753, 33116, 198, 220, 220, 220, 220, 220, 220, 220, 14631, 12, 80, 1600, 27444, 67, 1600, 366, 7753, 33116, 198, 220, 220, 220, 220, 220, 220, 220, 14631, 438, 19282, 259, 1600, 366, 7753, 33116, 198, 220, 220, 220, 220, 220, 220, 220, 685, 4357, 198, 220, 220, 220, 16589, 198, 8, 628, 198, 31, 9078, 9288, 13, 4102, 13, 17143, 316, 380, 2736, 7203, 6978, 11, 1186, 1600, 47527, 4895, 15908, 1298, 23884, 5512, 657, 828, 357, 4895, 15908, 1298, 366, 16624, 25719, 352, 8, 12962, 628, 628, 628, 198, 198, 31, 9078, 9288, 13, 4102, 13, 17143, 316, 380, 2736, 7, 198, 220, 220, 220, 366, 7753, 11, 1186, 11, 22915, 1600, 685, 7203, 570, 1850, 1600, 657, 11, 6407, 828, 5855, 1662, 62, 570, 1850, 1600, 352, 11, 10352, 15437, 198, 8, 198 ]
1.910394
558
import os import threading import time from networktables import NetworkTables from PIL import Image from PIL.ImageColor import getcolor, getrgb from PIL.ImageOps import grayscale from StreamDeck.DeviceManager import DeviceManager from StreamDeck.ImageHelpers import PILHelper ASSETS_PATH = os.path.join(os.path.dirname(__file__), "assets") ASSETS_PATH = os.path.join(os.path.dirname(__file__), "icons") # As a client to connect to a robot NetworkTables.initialize(server="10.11.89.2") # NetworkTables.initialize(server="127.0.0.1") time.sleep(3) sd = NetworkTables.getTable("StreamDeck/0") # a = [ # "default", # "default", # "default", # "default", # "default", # "default", # "default", # "default", # "default", # "default", # "default", # "default", # "default", # "default", # "default", # ] # sd.putStringArray("Icons", a) buttons = [] for i in range(0, 15): sd.putBoolean(f"Action/{i}", False) sd.putBoolean(f"Status/{i}", False) button = Button(i) buttons.append(button) deck = DeviceManager().enumerate()[0] deck.open() deck.reset() print( "Opened '{}' device (serial number: '{}')".format( deck.deck_type(), deck.get_serial_number() ) ) # Set initial screen brightness to 30%. deck.set_brightness(30) # Set initial key images. # for key in range(deck.key_count()): # update_key_image(deck, key, False) # Register callback function for when a key state changes. deck.set_key_callback(key_change_callback) while True: for button in buttons: button.update(deck) # Wait until all application threads have terminated (for this example, # this is when all deck handles are closed). for t in threading.enumerate(): if t is threading.currentThread(): continue if t.is_alive(): t.join()
[ 11748, 28686, 198, 11748, 4704, 278, 198, 11748, 640, 198, 198, 6738, 3127, 83, 2977, 1330, 7311, 51, 2977, 198, 6738, 350, 4146, 1330, 7412, 198, 6738, 350, 4146, 13, 5159, 10258, 1330, 651, 8043, 11, 651, 81, 22296, 198, 6738, 350, 4146, 13, 5159, 41472, 1330, 1036, 592, 38765, 198, 198, 6738, 13860, 5005, 694, 13, 24728, 13511, 1330, 16232, 13511, 198, 6738, 13860, 5005, 694, 13, 5159, 12621, 19276, 1330, 350, 4146, 47429, 198, 198, 10705, 32716, 62, 34219, 796, 28686, 13, 6978, 13, 22179, 7, 418, 13, 6978, 13, 15908, 3672, 7, 834, 7753, 834, 828, 366, 19668, 4943, 628, 198, 198, 10705, 32716, 62, 34219, 796, 28686, 13, 6978, 13, 22179, 7, 418, 13, 6978, 13, 15908, 3672, 7, 834, 7753, 834, 828, 366, 34280, 4943, 628, 628, 198, 198, 2, 1081, 257, 5456, 284, 2018, 284, 257, 9379, 198, 26245, 51, 2977, 13, 36733, 1096, 7, 15388, 2625, 940, 13, 1157, 13, 4531, 13, 17, 4943, 198, 2, 7311, 51, 2977, 13, 36733, 1096, 7, 15388, 2625, 16799, 13, 15, 13, 15, 13, 16, 4943, 198, 2435, 13, 42832, 7, 18, 8, 628, 198, 21282, 796, 7311, 51, 2977, 13, 1136, 10962, 7203, 12124, 5005, 694, 14, 15, 4943, 198, 2, 257, 796, 685, 198, 2, 220, 220, 220, 220, 366, 12286, 1600, 198, 2, 220, 220, 220, 220, 366, 12286, 1600, 198, 2, 220, 220, 220, 220, 366, 12286, 1600, 198, 2, 220, 220, 220, 220, 366, 12286, 1600, 198, 2, 220, 220, 220, 220, 366, 12286, 1600, 198, 2, 220, 220, 220, 220, 366, 12286, 1600, 198, 2, 220, 220, 220, 220, 366, 12286, 1600, 198, 2, 220, 220, 220, 220, 366, 12286, 1600, 198, 2, 220, 220, 220, 220, 366, 12286, 1600, 198, 2, 220, 220, 220, 220, 366, 12286, 1600, 198, 2, 220, 220, 220, 220, 366, 12286, 1600, 198, 2, 220, 220, 220, 220, 366, 12286, 1600, 198, 2, 220, 220, 220, 220, 366, 12286, 1600, 198, 2, 220, 220, 220, 220, 366, 12286, 1600, 198, 2, 220, 220, 220, 220, 366, 12286, 1600, 198, 2, 2361, 198, 2, 45647, 13, 1996, 10100, 19182, 7203, 40, 5936, 1600, 257, 8, 198, 198, 4360, 27288, 796, 17635, 198, 198, 1640, 1312, 287, 2837, 7, 15, 11, 1315, 2599, 198, 220, 220, 220, 45647, 13, 1996, 46120, 13087, 7, 69, 1, 12502, 14, 90, 72, 92, 1600, 10352, 8, 198, 220, 220, 220, 45647, 13, 1996, 46120, 13087, 7, 69, 1, 19580, 14, 90, 72, 92, 1600, 10352, 8, 198, 220, 220, 220, 4936, 796, 20969, 7, 72, 8, 198, 220, 220, 220, 12163, 13, 33295, 7, 16539, 8, 198, 198, 35875, 796, 16232, 13511, 22446, 268, 6975, 378, 3419, 58, 15, 60, 198, 35875, 13, 9654, 3419, 198, 35875, 13, 42503, 3419, 198, 4798, 7, 198, 220, 220, 220, 366, 18257, 2945, 705, 90, 92, 6, 3335, 357, 46911, 1271, 25, 705, 90, 92, 11537, 1911, 18982, 7, 198, 220, 220, 220, 220, 220, 220, 220, 6203, 13, 35875, 62, 4906, 22784, 6203, 13, 1136, 62, 46911, 62, 17618, 3419, 198, 220, 220, 220, 1267, 198, 8, 198, 198, 2, 5345, 4238, 3159, 22204, 284, 1542, 7225, 198, 35875, 13, 2617, 62, 29199, 1108, 7, 1270, 8, 198, 2, 5345, 4238, 1994, 4263, 13, 198, 2, 329, 1994, 287, 2837, 7, 35875, 13, 2539, 62, 9127, 3419, 2599, 198, 2, 220, 220, 220, 4296, 62, 2539, 62, 9060, 7, 35875, 11, 1994, 11, 10352, 8, 198, 198, 2, 17296, 23838, 2163, 329, 618, 257, 1994, 1181, 2458, 13, 198, 35875, 13, 2617, 62, 2539, 62, 47423, 7, 2539, 62, 3803, 62, 47423, 8, 198, 198, 4514, 6407, 25, 198, 220, 220, 220, 329, 4936, 287, 12163, 25, 198, 220, 220, 220, 220, 220, 220, 220, 4936, 13, 19119, 7, 35875, 8, 198, 198, 2, 16314, 1566, 477, 3586, 14390, 423, 23083, 357, 1640, 428, 1672, 11, 198, 2, 428, 318, 618, 477, 6203, 17105, 389, 4838, 737, 198, 1640, 256, 287, 4704, 278, 13, 268, 6975, 378, 33529, 198, 220, 220, 220, 611, 256, 318, 4704, 278, 13, 14421, 16818, 33529, 198, 220, 220, 220, 220, 220, 220, 220, 2555, 198, 220, 220, 220, 611, 256, 13, 271, 62, 282, 425, 33529, 198, 220, 220, 220, 220, 220, 220, 220, 256, 13, 22179, 3419, 198 ]
2.577031
714
from dragonfly import (Grammar, CompoundRule, Text, MappingRule, Dictation, Function, Choice) from macro_utilities import (replace_in_text, comment_choice, execute_with_dictation) from vim.rules.letter import (camel_case, proper) comparison_choice_map = { "equal": "==", "not equal": "/=", "less or equal": "<=", "greater or equal": ">=", "less": "<", "greater": ">", } stack_command_choice_map = { "build fast": "build --fast", "build": "build", "shell": "repl", "shall": "repl", "test": "test", "test fast": "test --fast", "run": "run", "install": "install", } # The main Curry grammar rules are activated here curryBootstrap = Grammar("curry bootstrap") curryBootstrap.add_rule(CurryEnabler()) curryBootstrap.load() curryGrammar = Grammar("curry grammar") curryGrammar.add_rule(CurryUtilities()) curryGrammar.add_rule(CurryDisabler()) curryGrammar.load() curryGrammar.disable()
[ 6738, 10441, 12254, 1330, 357, 38, 859, 3876, 11, 3082, 633, 31929, 11, 8255, 11, 337, 5912, 31929, 11, 360, 713, 341, 11, 15553, 11, 18502, 8, 198, 6738, 15021, 62, 315, 2410, 1330, 357, 33491, 62, 259, 62, 5239, 11, 2912, 62, 25541, 11, 12260, 62, 4480, 62, 11600, 341, 8, 198, 6738, 43907, 13, 38785, 13, 9291, 1330, 357, 66, 17983, 62, 7442, 11, 1774, 8, 628, 628, 628, 628, 198, 785, 1845, 1653, 62, 25541, 62, 8899, 796, 1391, 198, 220, 220, 220, 366, 40496, 1298, 366, 855, 1600, 198, 220, 220, 220, 366, 1662, 4961, 1298, 12813, 28, 1600, 198, 220, 220, 220, 366, 1203, 393, 4961, 1298, 33490, 28, 1600, 198, 220, 220, 220, 366, 18223, 263, 393, 4961, 1298, 366, 29, 28, 1600, 198, 220, 220, 220, 366, 1203, 1298, 33490, 1600, 198, 220, 220, 220, 366, 18223, 263, 1298, 366, 29, 1600, 198, 92, 628, 628, 628, 628, 628, 628, 628, 628, 628, 628, 198, 25558, 62, 21812, 62, 25541, 62, 8899, 796, 1391, 198, 220, 220, 220, 366, 11249, 3049, 1298, 366, 11249, 1377, 7217, 1600, 198, 220, 220, 220, 366, 11249, 1298, 366, 11249, 1600, 198, 220, 220, 220, 366, 29149, 1298, 366, 35666, 1600, 198, 220, 220, 220, 366, 49271, 1298, 366, 35666, 1600, 198, 220, 220, 220, 366, 9288, 1298, 366, 9288, 1600, 198, 220, 220, 220, 366, 9288, 3049, 1298, 366, 9288, 1377, 7217, 1600, 198, 220, 220, 220, 366, 5143, 1298, 366, 5143, 1600, 198, 220, 220, 220, 366, 17350, 1298, 366, 17350, 1600, 198, 92, 628, 628, 198, 198, 2, 383, 1388, 20920, 23491, 3173, 389, 13906, 994, 198, 66, 16682, 36476, 26418, 796, 20159, 3876, 7203, 66, 16682, 6297, 26418, 4943, 198, 66, 16682, 36476, 26418, 13, 2860, 62, 25135, 7, 34, 16682, 4834, 397, 1754, 28955, 198, 66, 16682, 36476, 26418, 13, 2220, 3419, 198, 198, 66, 16682, 38, 859, 3876, 796, 20159, 3876, 7203, 66, 16682, 23491, 4943, 198, 66, 16682, 38, 859, 3876, 13, 2860, 62, 25135, 7, 34, 16682, 18274, 2410, 28955, 198, 66, 16682, 38, 859, 3876, 13, 2860, 62, 25135, 7, 34, 16682, 7279, 397, 1754, 28955, 198, 66, 16682, 38, 859, 3876, 13, 2220, 3419, 198, 66, 16682, 38, 859, 3876, 13, 40223, 3419, 628 ]
2.578249
377
from deluge.plugins.init import PluginInitBase VERSION = (0, 1, 8)
[ 6738, 1619, 2217, 13, 37390, 13, 15003, 1330, 42636, 31768, 14881, 628, 198, 43717, 796, 357, 15, 11, 352, 11, 807, 8, 628, 628 ]
3
24
from django.shortcuts import reverse from django.views.generic import UpdateView from applications.users.forms.profile import ProfileForm from applications.users.layouts.profile import ProfileLayout from applications.users.mixins.authenticated import AuthenticatedMixin from applications.common.mixins.add_message import AddMessageMixin from applications.common.mixins.add_request_to_form import AddRequestToFormMixin Profile = ProfileCBV.as_view()
[ 6738, 42625, 14208, 13, 19509, 23779, 1330, 9575, 198, 6738, 42625, 14208, 13, 33571, 13, 41357, 1330, 10133, 7680, 198, 198, 6738, 5479, 13, 18417, 13, 23914, 13, 13317, 1330, 13118, 8479, 198, 6738, 5479, 13, 18417, 13, 10724, 5269, 13, 13317, 1330, 13118, 32517, 198, 6738, 5479, 13, 18417, 13, 19816, 1040, 13, 41299, 3474, 1330, 31885, 3474, 35608, 259, 198, 6738, 5479, 13, 11321, 13, 19816, 1040, 13, 2860, 62, 20500, 1330, 3060, 12837, 35608, 259, 198, 6738, 5479, 13, 11321, 13, 19816, 1040, 13, 2860, 62, 25927, 62, 1462, 62, 687, 1330, 3060, 18453, 2514, 8479, 35608, 259, 628, 198, 198, 37046, 796, 13118, 23199, 53, 13, 292, 62, 1177, 3419, 198 ]
3.93913
115
# -*- coding: utf-8 -*- import csv import os import cv2 import numpy as np from flask import render_template, request, redirect, url_for from flask import jsonify from app.main import main from app.utils.frame.frame import base64_to_png from app.utils.frame.site import Site from app.utils.frame.sub import PictureSub from config import Config import json @main.route('/') @main.route('/picture/', methods=['GET', 'POST']) # INFO 2019/12/25 15:18 liliangbin 背景图片设置 @main.route('/background/', methods=['GET', 'POST']) # TODO 2020/1/4 15:13 liliangbin 返回的地址应该是画框的位置(视频名字和时间位置)通过前端设置了 @main.route('/site/', methods=['GET', 'POST']) # TODO 2020/6/12 15:50 liliangbin 代码可以优化一波 @main.route('/change_datas/', methods=['GET', 'POST']) # INFO 2020/6/12 15:51 liliangbin 获取用户 @main.route("/site_get/", methods=['GET', 'POST']) @main.route('/video_location/', methods=['POST'])
[ 2, 532, 9, 12, 19617, 25, 3384, 69, 12, 23, 532, 9, 12, 198, 198, 11748, 269, 21370, 198, 11748, 28686, 198, 198, 11748, 269, 85, 17, 198, 11748, 299, 32152, 355, 45941, 198, 6738, 42903, 1330, 8543, 62, 28243, 11, 2581, 11, 18941, 11, 19016, 62, 1640, 198, 6738, 42903, 1330, 33918, 1958, 198, 6738, 598, 13, 12417, 1330, 1388, 198, 6738, 598, 13, 26791, 13, 14535, 13, 14535, 1330, 2779, 2414, 62, 1462, 62, 11134, 198, 6738, 598, 13, 26791, 13, 14535, 13, 15654, 1330, 14413, 198, 6738, 598, 13, 26791, 13, 14535, 13, 7266, 1330, 17741, 7004, 198, 6738, 4566, 1330, 17056, 198, 11748, 33918, 628, 198, 31, 12417, 13, 38629, 10786, 14, 11537, 628, 198, 31, 12417, 13, 38629, 10786, 14, 34053, 14, 3256, 5050, 28, 17816, 18851, 3256, 705, 32782, 6, 12962, 628, 198, 2, 24890, 13130, 14, 1065, 14, 1495, 1315, 25, 1507, 300, 2403, 648, 8800, 220, 5525, 225, 234, 162, 247, 107, 32368, 122, 31965, 229, 164, 106, 122, 163, 121, 106, 198, 31, 12417, 13, 38629, 10786, 14, 25249, 14, 3256, 5050, 28, 17816, 18851, 3256, 705, 32782, 6, 12962, 628, 198, 2, 16926, 46, 12131, 14, 16, 14, 19, 1315, 25, 1485, 300, 2403, 648, 8800, 5525, 123, 242, 32368, 252, 21410, 28839, 108, 161, 251, 222, 41753, 242, 46237, 98, 42468, 18796, 119, 162, 94, 228, 21410, 19526, 235, 163, 121, 106, 171, 120, 230, 164, 100, 228, 165, 95, 239, 28938, 235, 27764, 245, 161, 240, 234, 33768, 114, 29785, 112, 19526, 235, 163, 121, 106, 171, 120, 231, 34460, 248, 32573, 229, 30298, 235, 44165, 107, 164, 106, 122, 163, 121, 106, 12859, 228, 198, 31, 12417, 13, 38629, 10786, 14, 15654, 14, 3256, 5050, 28, 17816, 18851, 3256, 705, 32782, 6, 12962, 628, 198, 2, 16926, 46, 12131, 14, 21, 14, 1065, 1315, 25, 1120, 300, 2403, 648, 8800, 220, 47987, 163, 254, 223, 20998, 107, 20015, 98, 27670, 246, 44293, 244, 31660, 37345, 95, 198, 31, 12417, 13, 38629, 10786, 14, 3803, 62, 19608, 292, 14, 3256, 5050, 28, 17816, 18851, 3256, 705, 32782, 6, 12962, 628, 198, 2, 24890, 12131, 14, 21, 14, 1065, 1315, 25, 4349, 300, 2403, 648, 8800, 220, 5525, 236, 115, 20998, 244, 18796, 101, 22755, 115, 198, 31, 12417, 13, 38629, 7203, 14, 15654, 62, 1136, 14, 1600, 5050, 28, 17816, 18851, 3256, 705, 32782, 6, 12962, 628, 198, 31, 12417, 13, 38629, 10786, 14, 15588, 62, 24886, 14, 3256, 5050, 28, 17816, 32782, 6, 12962, 198 ]
2.119617
418
# django imports from django.forms import ModelForm # lfs imports from lfs.discounts.models import Discount class DiscountForm(ModelForm): """ Form to manage discount data. """
[ 2, 42625, 14208, 17944, 198, 6738, 42625, 14208, 13, 23914, 1330, 9104, 8479, 198, 198, 2, 300, 9501, 17944, 198, 6738, 300, 9501, 13, 15410, 608, 82, 13, 27530, 1330, 43474, 628, 198, 4871, 43474, 8479, 7, 17633, 8479, 2599, 198, 220, 220, 220, 37227, 198, 220, 220, 220, 5178, 284, 6687, 9780, 1366, 13, 198, 220, 220, 220, 37227, 198 ]
3.147541
61
# MIT License # # Copyright (c) 2020 SCL team at Red Hat # # Permission is hereby granted, free of charge, to any person obtaining a copy # of this software and associated documentation files (the "Software"), to deal # in the Software without restriction, including without limitation the rights # to use, copy, modify, merge, publish, distribute, sublicense, and/or sell # copies of the Software, and to permit persons to whom the Software is # furnished to do so, subject to the following conditions: # # The above copyright notice and this permission notice shall be included in all # copies or substantial portions of the Software. # # THE SOFTWARE IS PROVIDED "AS IS", WITHOUT WARRANTY OF ANY KIND, EXPRESS OR # IMPLIED, INCLUDING BUT NOT LIMITED TO THE WARRANTIES OF MERCHANTABILITY, # FITNESS FOR A PARTICULAR PURPOSE AND NONINFRINGEMENT. IN NO EVENT SHALL THE # AUTHORS OR COPYRIGHT HOLDERS BE LIABLE FOR ANY CLAIM, DAMAGES OR OTHER # LIABILITY, WHETHER IN AN ACTION OF CONTRACT, TORT OR OTHERWISE, ARISING FROM, # OUT OF OR IN CONNECTION WITH THE SOFTWARE OR THE USE OR OTHER DEALINGS IN THE # SOFTWARE. from contextlib import contextmanager import logging import shutil import os import json import jinja2 import subprocess from pathlib import Path from betka.constants import HOME logger = logging.getLogger(__name__) def run_cmd(cmd, return_output=False, ignore_error=False, shell=False, **kwargs): """ Run provided command on host system using the same user as invoked this code. Raises subprocess.CalledProcessError if it fails. :param cmd: list or str :param return_output: bool, return output of the command :param ignore_error: bool, do not fail in case nonzero return code :param shell: bool, run command in shell :param kwargs: pass keyword arguments to subprocess.check_* functions; for more info, please check `help(subprocess.Popen)` :return: None or str """ logger.debug("command: %r", cmd) try: if return_output: return subprocess.check_output( cmd, stderr=subprocess.STDOUT, universal_newlines=True, shell=shell, **kwargs, ) else: return subprocess.check_call(cmd, shell=shell, **kwargs) except subprocess.CalledProcessError as cpe: if ignore_error: if return_output: return cpe.output else: return cpe.returncode else: logger.error(f"failed with code {cpe.returncode} and output:\n{cpe.output}") raise cpe def text_from_template(template_dir, template_filename, template_data): """ Create text based on template in path template_dir/template_filename :param template_dir: string, directory containing templates :param template_filename: template for text in jinja :param template_data: dict, data for substitution in template :return: string """ if not os.path.exists(os.path.join(template_dir, template_filename)): raise FileNotFoundError("Path to template not found.") template_loader = jinja2.FileSystemLoader(searchpath=template_dir) template_env = jinja2.Environment(loader=template_loader) template = template_env.get_template(template_filename) output_text = template.render(template_data=template_data) logger.debug("Text from template created:") logger.debug(output_text) return output_text def copy_upstream2downstream(src_parent: Path, dest_parent: Path): """Copies content from upstream repo to downstream repo Copies all files/dirs/symlinks from upstream source to dist-git one by one, while removing previous if exists. :param src_parent: path to source directory :param dest_parent: path to destination directory """ for f in src_parent.iterdir(): if f.name.startswith(".git"): continue dest = dest_parent / f.name src = src_parent / f.name logger.debug(f"Copying {str(src)} to {str(dest)}.") # First remove the dest only if it is not symlink. if dest.is_dir() and not dest.is_symlink(): logger.debug("rmtree %s", dest) shutil.rmtree(dest) else: if dest.exists(): dest.unlink() # Now copy the src to dest if src.is_symlink() or not src.is_dir(): logger.debug("cp %s %s", src, dest) shutil.copy2(src, dest, follow_symlinks=False) else: logger.debug("cp -r %s %s", src, dest) shutil.copytree(src, dest, symlinks=True) def clean_directory(path: Path): """ Function cleans directory except itself :param path: directory path which is cleaned """ for d in path.iterdir(): src = path / d if src.is_dir(): logger.debug("rmtree %s", str(src)) shutil.rmtree(src) else: src.unlink() def list_dir_content(dir_name: Path): """ Lists all content of dir_name :param dir_name: Directory for showing files """ logger.info("Look for a content in '%s' directory", str(dir_name)) for f in dir_name.rglob("*"): if str(f).startswith(".git"): continue logger.debug(f"{f.parent / f.name}") @contextmanager def cwd(path): """ Switch to Path directory and once action is done returns back :param path: :return: """ prev_cwd = Path.cwd() os.chdir(path) try: yield finally: os.chdir(prev_cwd)
[ 2, 17168, 13789, 198, 2, 198, 2, 15069, 357, 66, 8, 12131, 311, 5097, 1074, 379, 2297, 10983, 198, 2, 198, 2, 2448, 3411, 318, 29376, 7520, 11, 1479, 286, 3877, 11, 284, 597, 1048, 16727, 257, 4866, 198, 2, 286, 428, 3788, 290, 3917, 10314, 3696, 357, 1169, 366, 25423, 12340, 284, 1730, 198, 2, 287, 262, 10442, 1231, 17504, 11, 1390, 1231, 17385, 262, 2489, 198, 2, 284, 779, 11, 4866, 11, 13096, 11, 20121, 11, 7715, 11, 14983, 11, 850, 43085, 11, 290, 14, 273, 3677, 198, 2, 9088, 286, 262, 10442, 11, 290, 284, 8749, 6506, 284, 4150, 262, 10442, 318, 198, 2, 30760, 284, 466, 523, 11, 2426, 284, 262, 1708, 3403, 25, 198, 2, 198, 2, 383, 2029, 6634, 4003, 290, 428, 7170, 4003, 2236, 307, 3017, 287, 477, 198, 2, 9088, 393, 8904, 16690, 286, 262, 10442, 13, 198, 2, 198, 2, 3336, 47466, 3180, 36592, 2389, 1961, 366, 1921, 3180, 1600, 42881, 34764, 56, 3963, 15529, 509, 12115, 11, 7788, 32761, 6375, 198, 2, 8959, 49094, 11, 47783, 2751, 21728, 5626, 40880, 5390, 3336, 34764, 11015, 3963, 34482, 3398, 1565, 5603, 25382, 11, 198, 2, 376, 46144, 7473, 317, 16652, 2149, 37232, 33079, 48933, 5357, 44521, 1268, 10913, 2751, 12529, 13, 3268, 8005, 49261, 50163, 3336, 198, 2, 37195, 20673, 6375, 27975, 38162, 9947, 367, 15173, 4877, 9348, 43031, 19146, 7473, 15529, 47666, 3955, 11, 29506, 25552, 6375, 25401, 198, 2, 43031, 25382, 11, 7655, 2767, 16879, 3268, 3537, 40282, 3963, 27342, 10659, 11, 309, 9863, 6375, 25401, 54, 24352, 11, 5923, 1797, 2751, 16034, 11, 198, 2, 16289, 3963, 6375, 3268, 7102, 45, 24565, 13315, 3336, 47466, 6375, 3336, 23210, 6375, 25401, 5550, 1847, 20754, 3268, 3336, 198, 2, 47466, 13, 628, 198, 6738, 4732, 8019, 1330, 4732, 37153, 198, 11748, 18931, 198, 11748, 4423, 346, 198, 11748, 28686, 198, 11748, 33918, 198, 198, 11748, 474, 259, 6592, 17, 198, 11748, 850, 14681, 198, 198, 6738, 3108, 8019, 1330, 10644, 198, 6738, 731, 4914, 13, 9979, 1187, 1330, 41779, 198, 198, 6404, 1362, 796, 18931, 13, 1136, 11187, 1362, 7, 834, 3672, 834, 8, 628, 198, 4299, 1057, 62, 28758, 7, 28758, 11, 1441, 62, 22915, 28, 25101, 11, 8856, 62, 18224, 28, 25101, 11, 7582, 28, 25101, 11, 12429, 46265, 22046, 2599, 198, 220, 220, 220, 37227, 198, 220, 220, 220, 5660, 2810, 3141, 319, 2583, 1080, 1262, 262, 976, 2836, 355, 24399, 428, 2438, 13, 198, 220, 220, 220, 7567, 2696, 850, 14681, 13, 34, 4262, 18709, 12331, 611, 340, 10143, 13, 628, 220, 220, 220, 1058, 17143, 23991, 25, 1351, 393, 965, 198, 220, 220, 220, 1058, 17143, 1441, 62, 22915, 25, 20512, 11, 1441, 5072, 286, 262, 3141, 198, 220, 220, 220, 1058, 17143, 8856, 62, 18224, 25, 20512, 11, 466, 407, 2038, 287, 1339, 1729, 22570, 1441, 2438, 198, 220, 220, 220, 1058, 17143, 7582, 25, 20512, 11, 1057, 3141, 287, 7582, 198, 220, 220, 220, 1058, 17143, 479, 86, 22046, 25, 1208, 21179, 7159, 284, 850, 14681, 13, 9122, 62, 9, 5499, 26, 329, 517, 7508, 11, 198, 220, 220, 220, 220, 220, 220, 220, 220, 220, 220, 220, 3387, 2198, 4600, 16794, 7, 7266, 14681, 13, 47, 9654, 8, 63, 198, 220, 220, 220, 1058, 7783, 25, 6045, 393, 965, 198, 220, 220, 220, 37227, 198, 220, 220, 220, 49706, 13, 24442, 7203, 21812, 25, 4064, 81, 1600, 23991, 8, 198, 220, 220, 220, 1949, 25, 198, 220, 220, 220, 220, 220, 220, 220, 611, 1441, 62, 22915, 25, 198, 220, 220, 220, 220, 220, 220, 220, 220, 220, 220, 220, 1441, 850, 14681, 13, 9122, 62, 22915, 7, 198, 220, 220, 220, 220, 220, 220, 220, 220, 220, 220, 220, 220, 220, 220, 220, 23991, 11, 198, 220, 220, 220, 220, 220, 220, 220, 220, 220, 220, 220, 220, 220, 220, 220, 336, 1082, 81, 28, 7266, 14681, 13, 36886, 11, 198, 220, 220, 220, 220, 220, 220, 220, 220, 220, 220, 220, 220, 220, 220, 220, 10112, 62, 3605, 6615, 28, 17821, 11, 198, 220, 220, 220, 220, 220, 220, 220, 220, 220, 220, 220, 220, 220, 220, 220, 7582, 28, 29149, 11, 198, 220, 220, 220, 220, 220, 220, 220, 220, 220, 220, 220, 220, 220, 220, 220, 12429, 46265, 22046, 11, 198, 220, 220, 220, 220, 220, 220, 220, 220, 220, 220, 220, 1267, 198, 220, 220, 220, 220, 220, 220, 220, 2073, 25, 198, 220, 220, 220, 220, 220, 220, 220, 220, 220, 220, 220, 1441, 850, 14681, 13, 9122, 62, 13345, 7, 28758, 11, 7582, 28, 29149, 11, 12429, 46265, 22046, 8, 198, 220, 220, 220, 2845, 850, 14681, 13, 34, 4262, 18709, 12331, 355, 269, 431, 25, 198, 220, 220, 220, 220, 220, 220, 220, 611, 8856, 62, 18224, 25, 198, 220, 220, 220, 220, 220, 220, 220, 220, 220, 220, 220, 611, 1441, 62, 22915, 25, 198, 220, 220, 220, 220, 220, 220, 220, 220, 220, 220, 220, 220, 220, 220, 220, 1441, 269, 431, 13, 22915, 198, 220, 220, 220, 220, 220, 220, 220, 220, 220, 220, 220, 2073, 25, 198, 220, 220, 220, 220, 220, 220, 220, 220, 220, 220, 220, 220, 220, 220, 220, 1441, 269, 431, 13, 7783, 8189, 198, 220, 220, 220, 220, 220, 220, 220, 2073, 25, 198, 220, 220, 220, 220, 220, 220, 220, 220, 220, 220, 220, 49706, 13, 18224, 7, 69, 1, 47904, 351, 2438, 1391, 66, 431, 13, 7783, 8189, 92, 290, 5072, 7479, 77, 90, 66, 431, 13, 22915, 92, 4943, 198, 220, 220, 220, 220, 220, 220, 220, 220, 220, 220, 220, 5298, 269, 431, 628, 198, 4299, 2420, 62, 6738, 62, 28243, 7, 28243, 62, 15908, 11, 11055, 62, 34345, 11, 11055, 62, 7890, 2599, 198, 220, 220, 220, 37227, 198, 220, 220, 220, 13610, 2420, 1912, 319, 11055, 287, 3108, 11055, 62, 15908, 14, 28243, 62, 34345, 198, 220, 220, 220, 1058, 17143, 11055, 62, 15908, 25, 4731, 11, 8619, 7268, 24019, 198, 220, 220, 220, 1058, 17143, 11055, 62, 34345, 25, 11055, 329, 2420, 287, 474, 259, 6592, 198, 220, 220, 220, 1058, 17143, 11055, 62, 7890, 25, 8633, 11, 1366, 329, 32097, 287, 11055, 198, 220, 220, 220, 1058, 7783, 25, 4731, 198, 220, 220, 220, 37227, 628, 220, 220, 220, 611, 407, 28686, 13, 6978, 13, 1069, 1023, 7, 418, 13, 6978, 13, 22179, 7, 28243, 62, 15908, 11, 11055, 62, 34345, 8, 2599, 198, 220, 220, 220, 220, 220, 220, 220, 5298, 9220, 3673, 21077, 12331, 7203, 15235, 284, 11055, 407, 1043, 19570, 628, 220, 220, 220, 11055, 62, 29356, 796, 474, 259, 6592, 17, 13, 8979, 11964, 17401, 7, 12947, 6978, 28, 28243, 62, 15908, 8, 198, 220, 220, 220, 11055, 62, 24330, 796, 474, 259, 6592, 17, 13, 31441, 7, 29356, 28, 28243, 62, 29356, 8, 198, 220, 220, 220, 11055, 796, 11055, 62, 24330, 13, 1136, 62, 28243, 7, 28243, 62, 34345, 8, 198, 220, 220, 220, 5072, 62, 5239, 796, 11055, 13, 13287, 7, 28243, 62, 7890, 28, 28243, 62, 7890, 8, 198, 220, 220, 220, 49706, 13, 24442, 7203, 8206, 422, 11055, 2727, 25, 4943, 198, 220, 220, 220, 49706, 13, 24442, 7, 22915, 62, 5239, 8, 628, 220, 220, 220, 1441, 5072, 62, 5239, 628, 198, 4299, 4866, 62, 929, 5532, 17, 2902, 5532, 7, 10677, 62, 8000, 25, 10644, 11, 2244, 62, 8000, 25, 10644, 2599, 198, 220, 220, 220, 37227, 13379, 444, 2695, 422, 28717, 29924, 284, 33218, 29924, 628, 220, 220, 220, 220, 6955, 444, 477, 3696, 14, 15908, 82, 14, 37047, 28751, 422, 28717, 2723, 284, 1233, 12, 18300, 530, 416, 530, 11, 198, 220, 220, 220, 220, 981, 10829, 2180, 611, 7160, 13, 628, 220, 220, 220, 220, 1058, 17143, 12351, 62, 8000, 25, 3108, 284, 2723, 8619, 198, 220, 220, 220, 220, 1058, 17143, 2244, 62, 8000, 25, 3108, 284, 10965, 8619, 198, 220, 220, 220, 220, 37227, 198, 220, 220, 220, 329, 277, 287, 12351, 62, 8000, 13, 2676, 15908, 33529, 198, 220, 220, 220, 220, 220, 220, 220, 611, 277, 13, 3672, 13, 9688, 2032, 342, 7, 1911, 18300, 1, 2599, 198, 220, 220, 220, 220, 220, 220, 220, 220, 220, 220, 220, 2555, 198, 220, 220, 220, 220, 220, 220, 220, 2244, 796, 2244, 62, 8000, 1220, 277, 13, 3672, 198, 220, 220, 220, 220, 220, 220, 220, 12351, 796, 12351, 62, 8000, 1220, 277, 13, 3672, 198, 220, 220, 220, 220, 220, 220, 220, 49706, 13, 24442, 7, 69, 1, 13379, 1112, 1391, 2536, 7, 10677, 38165, 284, 1391, 2536, 7, 16520, 38165, 19570, 198, 220, 220, 220, 220, 220, 220, 220, 1303, 3274, 4781, 262, 2244, 691, 611, 340, 318, 407, 827, 4029, 676, 13, 198, 220, 220, 220, 220, 220, 220, 220, 611, 2244, 13, 271, 62, 15908, 3419, 290, 407, 2244, 13, 271, 62, 1837, 4029, 676, 33529, 198, 220, 220, 220, 220, 220, 220, 220, 220, 220, 220, 220, 49706, 13, 24442, 7203, 81, 16762, 631, 4064, 82, 1600, 2244, 8, 198, 220, 220, 220, 220, 220, 220, 220, 220, 220, 220, 220, 4423, 346, 13, 81, 16762, 631, 7, 16520, 8, 198, 220, 220, 220, 220, 220, 220, 220, 2073, 25, 198, 220, 220, 220, 220, 220, 220, 220, 220, 220, 220, 220, 611, 2244, 13, 1069, 1023, 33529, 198, 220, 220, 220, 220, 220, 220, 220, 220, 220, 220, 220, 220, 220, 220, 220, 2244, 13, 403, 8726, 3419, 628, 220, 220, 220, 220, 220, 220, 220, 1303, 2735, 4866, 262, 12351, 284, 2244, 198, 220, 220, 220, 220, 220, 220, 220, 611, 12351, 13, 271, 62, 1837, 4029, 676, 3419, 393, 407, 12351, 13, 271, 62, 15908, 33529, 198, 220, 220, 220, 220, 220, 220, 220, 220, 220, 220, 220, 49706, 13, 24442, 7203, 13155, 4064, 82, 4064, 82, 1600, 12351, 11, 2244, 8, 198, 220, 220, 220, 220, 220, 220, 220, 220, 220, 220, 220, 4423, 346, 13, 30073, 17, 7, 10677, 11, 2244, 11, 1061, 62, 37047, 28751, 28, 25101, 8, 198, 220, 220, 220, 220, 220, 220, 220, 2073, 25, 198, 220, 220, 220, 220, 220, 220, 220, 220, 220, 220, 220, 49706, 13, 24442, 7203, 13155, 532, 81, 4064, 82, 4064, 82, 1600, 12351, 11, 2244, 8, 198, 220, 220, 220, 220, 220, 220, 220, 220, 220, 220, 220, 4423, 346, 13, 30073, 21048, 7, 10677, 11, 2244, 11, 5659, 28751, 28, 17821, 8, 628, 198, 4299, 3424, 62, 34945, 7, 6978, 25, 10644, 2599, 198, 220, 220, 220, 37227, 198, 220, 220, 220, 15553, 20658, 8619, 2845, 2346, 198, 220, 220, 220, 1058, 17143, 3108, 25, 8619, 3108, 543, 318, 20750, 198, 220, 220, 220, 37227, 198, 220, 220, 220, 329, 288, 287, 3108, 13, 2676, 15908, 33529, 198, 220, 220, 220, 220, 220, 220, 220, 12351, 796, 3108, 1220, 288, 198, 220, 220, 220, 220, 220, 220, 220, 611, 12351, 13, 271, 62, 15908, 33529, 198, 220, 220, 220, 220, 220, 220, 220, 220, 220, 220, 220, 49706, 13, 24442, 7203, 81, 16762, 631, 4064, 82, 1600, 965, 7, 10677, 4008, 198, 220, 220, 220, 220, 220, 220, 220, 220, 220, 220, 220, 4423, 346, 13, 81, 16762, 631, 7, 10677, 8, 198, 220, 220, 220, 220, 220, 220, 220, 2073, 25, 198, 220, 220, 220, 220, 220, 220, 220, 220, 220, 220, 220, 12351, 13, 403, 8726, 3419, 628, 198, 4299, 1351, 62, 15908, 62, 11299, 7, 15908, 62, 3672, 25, 10644, 2599, 198, 220, 220, 220, 37227, 198, 220, 220, 220, 44968, 477, 2695, 286, 26672, 62, 3672, 198, 220, 220, 220, 1058, 17143, 26672, 62, 3672, 25, 27387, 329, 4478, 3696, 198, 220, 220, 220, 37227, 198, 220, 220, 220, 49706, 13, 10951, 7203, 8567, 329, 257, 2695, 287, 705, 4, 82, 6, 8619, 1600, 965, 7, 15908, 62, 3672, 4008, 198, 220, 220, 220, 329, 277, 287, 26672, 62, 3672, 13, 81, 4743, 672, 7203, 9, 1, 2599, 198, 220, 220, 220, 220, 220, 220, 220, 611, 965, 7, 69, 737, 9688, 2032, 342, 7, 1911, 18300, 1, 2599, 198, 220, 220, 220, 220, 220, 220, 220, 220, 220, 220, 220, 2555, 198, 220, 220, 220, 220, 220, 220, 220, 49706, 13, 24442, 7, 69, 1, 90, 69, 13, 8000, 1220, 277, 13, 3672, 92, 4943, 628, 198, 198, 31, 22866, 37153, 198, 4299, 269, 16993, 7, 6978, 2599, 198, 220, 220, 220, 37227, 198, 220, 220, 220, 14645, 284, 10644, 8619, 290, 1752, 2223, 318, 1760, 198, 220, 220, 220, 5860, 736, 198, 220, 220, 220, 1058, 17143, 3108, 25, 198, 220, 220, 220, 1058, 7783, 25, 198, 220, 220, 220, 37227, 198, 220, 220, 220, 8654, 62, 66, 16993, 796, 10644, 13, 66, 16993, 3419, 198, 220, 220, 220, 28686, 13, 354, 15908, 7, 6978, 8, 198, 220, 220, 220, 1949, 25, 198, 220, 220, 220, 220, 220, 220, 220, 7800, 198, 220, 220, 220, 3443, 25, 198, 220, 220, 220, 220, 220, 220, 220, 28686, 13, 354, 15908, 7, 47050, 62, 66, 16993, 8, 198 ]
2.603809
2,153
# Copyright (c) 2021 PaddlePaddle Authors. All Rights Reserved. # # Licensed under the Apache License, Version 2.0 (the "License"); # you may not use this file except in compliance with the License. # You may obtain a copy of the License at # # http://www.apache.org/licenses/LICENSE-2.0 # # Unless required by applicable law or agreed to in writing, software # distributed under the License is distributed on an "AS IS" BASIS, # WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied. # See the License for the specific language governing permissions and # limitations under the License. import numpy as np from deepspeech.frontend.utility import IGNORE_ID from deepspeech.io.utility import pad_sequence from deepspeech.utils.log import Log __all__ = ["SpeechCollator"] logger = Log(__name__).getlog()
[ 2, 15069, 357, 66, 8, 33448, 350, 37382, 47, 37382, 46665, 13, 1439, 6923, 33876, 13, 198, 2, 198, 2, 49962, 739, 262, 24843, 13789, 11, 10628, 362, 13, 15, 357, 1169, 366, 34156, 15341, 198, 2, 345, 743, 407, 779, 428, 2393, 2845, 287, 11846, 351, 262, 13789, 13, 198, 2, 921, 743, 7330, 257, 4866, 286, 262, 13789, 379, 198, 2, 198, 2, 220, 220, 220, 220, 2638, 1378, 2503, 13, 43073, 13, 2398, 14, 677, 4541, 14, 43, 2149, 24290, 12, 17, 13, 15, 198, 2, 198, 2, 17486, 2672, 416, 9723, 1099, 393, 4987, 284, 287, 3597, 11, 3788, 198, 2, 9387, 739, 262, 13789, 318, 9387, 319, 281, 366, 1921, 3180, 1, 29809, 1797, 11, 198, 2, 42881, 34764, 11015, 6375, 7102, 49828, 11053, 3963, 15529, 509, 12115, 11, 2035, 4911, 393, 17142, 13, 198, 2, 4091, 262, 13789, 329, 262, 2176, 3303, 15030, 21627, 290, 198, 2, 11247, 739, 262, 13789, 13, 198, 11748, 299, 32152, 355, 45941, 198, 198, 6738, 2769, 45862, 13, 8534, 437, 13, 315, 879, 1330, 28730, 6965, 62, 2389, 198, 6738, 2769, 45862, 13, 952, 13, 315, 879, 1330, 14841, 62, 43167, 198, 6738, 2769, 45862, 13, 26791, 13, 6404, 1330, 5972, 198, 198, 834, 439, 834, 796, 14631, 5248, 3055, 22667, 1352, 8973, 198, 198, 6404, 1362, 796, 5972, 7, 834, 3672, 834, 737, 1136, 6404, 3419, 628 ]
3.6
230
# -*-python-*- # # Copyright (C) 1999-2018 The ViewCVS Group. All Rights Reserved. # # By using this file, you agree to the terms and conditions set forth in # the LICENSE.html file which can be found at the top level of the ViewVC # distribution or at http://viewvc.org/license-1.html. # # For more information, visit http://viewvc.org/ # # ----------------------------------------------------------------------- "Version Control lib driver for remotely accessible Subversion repositories." import vclib import sys import os import re import tempfile import time import urllib from svn_repos import Revision, SVNChangedPath, _datestr_to_date, \ _compare_paths, _path_parts, _cleanup_path, \ _rev2optrev, _fix_subversion_exception, \ _split_revprops, _canonicalize_path from svn import core, delta, client, wc, ra ### Require Subversion 1.3.1 or better. (for svn_ra_get_locations support) if (core.SVN_VER_MAJOR, core.SVN_VER_MINOR, core.SVN_VER_PATCH) < (1, 3, 1): raise Exception, "Version requirement not met (needs 1.3.1 or better)" ### BEGIN COMPATABILITY CODE ### try: SVN_INVALID_REVNUM = core.SVN_INVALID_REVNUM except AttributeError: # The 1.4.x bindings are missing core.SVN_INVALID_REVNUM SVN_INVALID_REVNUM = -1 ### END COMPATABILITY CODE ### def cat_to_tempfile(svnrepos, path, rev): """Check out file revision to temporary file""" temp = tempfile.mktemp() stream = core.svn_stream_from_aprfile(temp) url = svnrepos._geturl(path) client.svn_client_cat(core.Stream(stream), url, _rev2optrev(rev), svnrepos.ctx) core.svn_stream_close(stream) return temp
[ 2, 532, 9, 12, 29412, 12, 9, 12, 198, 2, 198, 2, 15069, 357, 34, 8, 7358, 12, 7908, 383, 3582, 34, 20304, 4912, 13, 1439, 6923, 33876, 13, 198, 2, 198, 2, 2750, 1262, 428, 2393, 11, 345, 4236, 284, 262, 2846, 290, 3403, 900, 6071, 287, 198, 2, 262, 38559, 24290, 13, 6494, 2393, 543, 460, 307, 1043, 379, 262, 1353, 1241, 286, 262, 3582, 15922, 198, 2, 6082, 393, 379, 2638, 1378, 1177, 28435, 13, 2398, 14, 43085, 12, 16, 13, 6494, 13, 198, 2, 198, 2, 1114, 517, 1321, 11, 3187, 2638, 1378, 1177, 28435, 13, 2398, 14, 198, 2, 198, 2, 16529, 26866, 198, 198, 1, 14815, 6779, 9195, 4639, 329, 19863, 9857, 3834, 9641, 38072, 526, 198, 198, 11748, 410, 565, 571, 198, 11748, 25064, 198, 11748, 28686, 198, 11748, 302, 198, 11748, 20218, 7753, 198, 11748, 640, 198, 11748, 2956, 297, 571, 198, 6738, 38487, 77, 62, 260, 1930, 1330, 46604, 11, 20546, 45, 31813, 15235, 11, 4808, 19608, 395, 81, 62, 1462, 62, 4475, 11, 3467, 198, 220, 220, 220, 220, 220, 220, 220, 220, 220, 220, 220, 220, 220, 220, 220, 220, 220, 220, 220, 220, 220, 4808, 5589, 533, 62, 6978, 82, 11, 4808, 6978, 62, 42632, 11, 4808, 27773, 929, 62, 6978, 11, 3467, 198, 220, 220, 220, 220, 220, 220, 220, 220, 220, 220, 220, 220, 220, 220, 220, 220, 220, 220, 220, 220, 220, 4808, 18218, 17, 8738, 18218, 11, 4808, 13049, 62, 7266, 9641, 62, 1069, 4516, 11, 3467, 198, 220, 220, 220, 220, 220, 220, 220, 220, 220, 220, 220, 220, 220, 220, 220, 220, 220, 220, 220, 220, 220, 4808, 35312, 62, 18218, 1676, 862, 11, 4808, 49883, 605, 1096, 62, 6978, 198, 6738, 38487, 77, 1330, 4755, 11, 25979, 11, 5456, 11, 266, 66, 11, 2179, 628, 198, 21017, 9394, 557, 3834, 9641, 352, 13, 18, 13, 16, 393, 1365, 13, 357, 1640, 38487, 77, 62, 430, 62, 1136, 62, 17946, 602, 1104, 8, 198, 361, 357, 7295, 13, 50, 53, 45, 62, 5959, 62, 5673, 41, 1581, 11, 4755, 13, 50, 53, 45, 62, 5959, 62, 23678, 1581, 11, 4755, 13, 50, 53, 45, 62, 5959, 62, 47, 11417, 8, 1279, 357, 16, 11, 513, 11, 352, 2599, 198, 220, 5298, 35528, 11, 366, 14815, 9079, 407, 1138, 357, 50032, 352, 13, 18, 13, 16, 393, 1365, 16725, 628, 198, 21017, 347, 43312, 24301, 13563, 25382, 42714, 44386, 198, 198, 28311, 25, 198, 220, 20546, 45, 62, 1268, 23428, 2389, 62, 2200, 53, 41359, 796, 4755, 13, 50, 53, 45, 62, 1268, 23428, 2389, 62, 2200, 53, 41359, 198, 16341, 3460, 4163, 12331, 25, 1303, 383, 352, 13, 19, 13, 87, 34111, 389, 4814, 4755, 13, 50, 53, 45, 62, 1268, 23428, 2389, 62, 2200, 53, 41359, 198, 220, 20546, 45, 62, 1268, 23428, 2389, 62, 2200, 53, 41359, 796, 532, 16, 628, 198, 21017, 23578, 24301, 13563, 25382, 42714, 44386, 628, 220, 220, 220, 220, 198, 4299, 3797, 62, 1462, 62, 29510, 7753, 7, 21370, 77, 260, 1930, 11, 3108, 11, 2710, 2599, 198, 220, 37227, 9787, 503, 2393, 18440, 284, 8584, 2393, 37811, 198, 220, 20218, 796, 20218, 7753, 13, 28015, 29510, 3419, 198, 220, 4269, 796, 4755, 13, 21370, 77, 62, 5532, 62, 6738, 62, 499, 81, 7753, 7, 29510, 8, 198, 220, 19016, 796, 38487, 77, 260, 1930, 13557, 1136, 6371, 7, 6978, 8, 198, 220, 5456, 13, 21370, 77, 62, 16366, 62, 9246, 7, 7295, 13, 12124, 7, 5532, 828, 19016, 11, 4808, 18218, 17, 8738, 18218, 7, 18218, 828, 198, 220, 220, 220, 220, 220, 220, 220, 220, 220, 220, 220, 220, 220, 220, 220, 220, 220, 220, 220, 220, 220, 220, 220, 38487, 77, 260, 1930, 13, 49464, 8, 198, 220, 4755, 13, 21370, 77, 62, 5532, 62, 19836, 7, 5532, 8, 198, 220, 1441, 20218, 628, 198 ]
2.631415
643
#!/usr/bin/env python3 # -*- coding: utf-8 -*- import io import pathlib import sys import tempfile from multiprocessing import Pool, cpu_count import PyPDF2 as PyPDF2 import click import pdfminer.pdftypes as pdftypes import pdfminer.settings from fpdf import FPDF from pdfminer.converter import TextConverter from pdfminer.layout import LAParams, LTAnno, LTContainer, LTText, LTTextBox from pdfminer.pdfdocument import PDFDocument, PDFNoOutlines from pdfminer.pdfinterp import PDFPageInterpreter, PDFResourceManager from pdfminer.pdfpage import PDFPage from pdfminer.pdfparser import PDFParser from pdfminer.psparser import PSLiteral, PSLiteralTable from tqdm import tqdm pdfminer.settings.STRICT = False SUBSTITUTIONS = { u'ff': 'ff', u'fi': 'fi', u'fl': 'fl', u'’': "'", } ANNOT_SUBTYPES = set(['Text', 'Highlight', 'Squiggly', 'StrikeOut', 'Underline']) DEBUG_BOXHIT = False OUTDIR = "" @click.command() @click.option('--outdir', default="", help='Specify output directory') @click.argument('files', nargs=-1) if __name__ == "__main__": main()
[ 2, 48443, 14629, 14, 8800, 14, 24330, 21015, 18, 198, 2, 532, 9, 12, 19617, 25, 3384, 69, 12, 23, 532, 9, 12, 628, 198, 11748, 33245, 198, 11748, 3108, 8019, 198, 11748, 25064, 198, 11748, 20218, 7753, 198, 6738, 18540, 305, 919, 278, 1330, 19850, 11, 42804, 62, 9127, 198, 198, 11748, 9485, 20456, 17, 355, 9485, 20456, 17, 198, 11748, 3904, 198, 11748, 37124, 1084, 263, 13, 30094, 701, 9497, 355, 279, 67, 701, 9497, 198, 11748, 37124, 1084, 263, 13, 33692, 198, 6738, 277, 12315, 1330, 376, 20456, 198, 6738, 37124, 1084, 263, 13, 1102, 332, 353, 1330, 8255, 3103, 332, 353, 198, 6738, 37124, 1084, 263, 13, 39786, 1330, 406, 2969, 283, 4105, 11, 34146, 2025, 3919, 11, 34146, 29869, 11, 34146, 8206, 11, 34146, 8206, 14253, 198, 6738, 37124, 1084, 263, 13, 12315, 22897, 1330, 12960, 24941, 11, 12960, 2949, 7975, 6615, 198, 6738, 37124, 1084, 263, 13, 12315, 3849, 79, 1330, 14340, 5837, 496, 9492, 3866, 353, 11, 12960, 26198, 13511, 198, 6738, 37124, 1084, 263, 13, 12315, 7700, 1330, 14340, 5837, 496, 198, 6738, 37124, 1084, 263, 13, 12315, 48610, 1330, 14340, 5837, 28198, 198, 6738, 37124, 1084, 263, 13, 862, 48610, 1330, 6599, 43, 270, 1691, 11, 6599, 43, 270, 1691, 10962, 198, 6738, 256, 80, 36020, 1330, 256, 80, 36020, 198, 198, 12315, 1084, 263, 13, 33692, 13, 18601, 18379, 796, 10352, 198, 198, 50, 10526, 2257, 2043, 3843, 11053, 796, 1391, 198, 220, 220, 220, 334, 6, 171, 105, 222, 10354, 705, 487, 3256, 198, 220, 220, 220, 334, 6, 171, 105, 223, 10354, 705, 12463, 3256, 198, 220, 220, 220, 334, 6, 171, 105, 224, 10354, 705, 2704, 3256, 198, 220, 220, 220, 334, 6, 447, 247, 10354, 24018, 1600, 198, 92, 198, 198, 1565, 11929, 62, 50, 10526, 9936, 47, 1546, 796, 900, 7, 17816, 8206, 3256, 705, 11922, 2971, 3256, 705, 22266, 6950, 306, 3256, 705, 31584, 7975, 3256, 705, 9203, 1370, 6, 12962, 198, 198, 30531, 62, 39758, 39, 2043, 796, 10352, 198, 198, 12425, 34720, 796, 13538, 628, 628, 628, 628, 628, 628, 628, 628, 198, 31, 12976, 13, 21812, 3419, 198, 31, 12976, 13, 18076, 10786, 438, 448, 15908, 3256, 4277, 2625, 1600, 1037, 11639, 22882, 1958, 5072, 8619, 11537, 198, 31, 12976, 13, 49140, 10786, 16624, 3256, 299, 22046, 10779, 16, 8, 628, 198, 361, 11593, 3672, 834, 6624, 366, 834, 12417, 834, 1298, 198, 220, 220, 220, 1388, 3419, 198 ]
2.671569
408
import torch def heatmap_focal_loss(preds, gt_heatmap, alpha, gamma, eps=1e-3): """ Params: preds: Tensor[num_classes, height, width] gt_heatmap: Tensor[num_classes, height, width] alpha: gamma: how much you want to reduce penalty around the ground truth locations eps: add small number to prevent inf error Returns: loss: Tensor[] """ # See CornerNet paper for detail https://arxiv.org/abs/1808.01244 loss = -torch.where( gt_heatmap == 1, (1 - preds)**alpha * torch.log(preds + eps), # Loss for positive locations (1 - gt_heatmap) ** gamma * (preds)**alpha * torch.log(1 - preds - eps) # loss for negative locations ).sum() return loss def dice_loss(inputs, targets, smooth=1.0): """ Params: inputs: arbitrary size of Tensor targets: arbitrary size of Tensor smooth: smoothing factor Returns: loss: Tensor[] """ inputs = inputs.view(-1) targets = targets.view(-1) # Squred denominator version of Dice loss dice = (2 * (inputs*targets).sum() + smooth) / ((inputs**2).sum() + (targets**2).sum() + smooth) return 1 - dice
[ 11748, 28034, 198, 198, 4299, 4894, 8899, 62, 69, 4374, 62, 22462, 7, 28764, 82, 11, 308, 83, 62, 25080, 8899, 11, 17130, 11, 34236, 11, 304, 862, 28, 16, 68, 12, 18, 2599, 198, 220, 220, 220, 37227, 198, 220, 220, 220, 2547, 4105, 25, 198, 220, 220, 220, 220, 220, 220, 220, 2747, 82, 25, 309, 22854, 58, 22510, 62, 37724, 11, 6001, 11, 9647, 60, 198, 220, 220, 220, 220, 220, 220, 220, 308, 83, 62, 25080, 8899, 25, 309, 22854, 58, 22510, 62, 37724, 11, 6001, 11, 9647, 60, 198, 220, 220, 220, 220, 220, 220, 220, 17130, 25, 198, 220, 220, 220, 220, 220, 220, 220, 34236, 25, 703, 881, 345, 765, 284, 4646, 7389, 1088, 262, 2323, 3872, 7064, 198, 220, 220, 220, 220, 220, 220, 220, 304, 862, 25, 751, 1402, 1271, 284, 2948, 1167, 4049, 198, 220, 220, 220, 16409, 25, 198, 220, 220, 220, 220, 220, 220, 220, 2994, 25, 309, 22854, 21737, 198, 220, 220, 220, 37227, 198, 220, 220, 220, 1303, 4091, 26212, 7934, 3348, 329, 3703, 3740, 1378, 283, 87, 452, 13, 2398, 14, 8937, 14, 1507, 2919, 13, 486, 25707, 198, 220, 220, 220, 2994, 796, 532, 13165, 354, 13, 3003, 7, 198, 220, 220, 220, 220, 220, 220, 220, 308, 83, 62, 25080, 8899, 6624, 352, 11, 198, 220, 220, 220, 220, 220, 220, 220, 357, 16, 532, 2747, 82, 8, 1174, 26591, 1635, 28034, 13, 6404, 7, 28764, 82, 1343, 304, 862, 828, 1303, 22014, 329, 3967, 7064, 198, 220, 220, 220, 220, 220, 220, 220, 357, 16, 532, 308, 83, 62, 25080, 8899, 8, 12429, 34236, 1635, 357, 28764, 82, 8, 1174, 26591, 1635, 28034, 13, 6404, 7, 16, 532, 2747, 82, 532, 304, 862, 8, 1303, 2994, 329, 4633, 7064, 198, 220, 220, 220, 6739, 16345, 3419, 198, 220, 220, 220, 1441, 2994, 198, 198, 4299, 17963, 62, 22462, 7, 15414, 82, 11, 6670, 11, 7209, 28, 16, 13, 15, 2599, 198, 220, 220, 220, 37227, 198, 220, 220, 220, 2547, 4105, 25, 198, 220, 220, 220, 220, 220, 220, 220, 17311, 25, 14977, 2546, 286, 309, 22854, 198, 220, 220, 220, 220, 220, 220, 220, 6670, 25, 14977, 2546, 286, 309, 22854, 198, 220, 220, 220, 220, 220, 220, 220, 7209, 25, 32746, 722, 5766, 198, 220, 220, 220, 16409, 25, 198, 220, 220, 220, 220, 220, 220, 220, 2994, 25, 309, 22854, 21737, 198, 220, 220, 220, 37227, 198, 220, 220, 220, 17311, 796, 17311, 13, 1177, 32590, 16, 8, 198, 220, 220, 220, 6670, 796, 6670, 13, 1177, 32590, 16, 8, 628, 220, 220, 220, 1303, 5056, 445, 31457, 1352, 2196, 286, 34381, 2994, 198, 220, 220, 220, 17963, 796, 357, 17, 1635, 357, 15414, 82, 9, 83, 853, 1039, 737, 16345, 3419, 1343, 7209, 8, 1220, 14808, 15414, 82, 1174, 17, 737, 16345, 3419, 1343, 357, 83, 853, 1039, 1174, 17, 737, 16345, 3419, 1343, 7209, 8, 628, 220, 220, 220, 1441, 352, 532, 17963, 198 ]
2.406439
497
import pygments.lexers.hdl as lexers from multiprocessing import Process import helpers.common as common tokenizer = lexers.VerilogLexer()
[ 11748, 12972, 11726, 13, 2588, 364, 13, 71, 25404, 355, 31191, 364, 198, 6738, 18540, 305, 919, 278, 1330, 10854, 198, 11748, 49385, 13, 11321, 355, 2219, 198, 30001, 7509, 796, 31191, 364, 13, 13414, 346, 519, 45117, 263, 3419, 628 ]
3.414634
41
""" .. module:: dj-stripe.tests.test_event_handlers :synopsis: dj-stripe Event Handler Tests. .. moduleauthor:: Alex Kavanaugh (@kavdev) .. moduleauthor:: Lee Skillen (@lskillen) """ from copy import deepcopy import decimal from django.contrib.auth import get_user_model from django.test import TestCase from mock import patch from djstripe.models import Event, Charge, Transfer, Account, Plan, Customer, InvoiceItem, Invoice, Card, Subscription from tests import (FAKE_CARD, FAKE_CHARGE, FAKE_CHARGE_II, FAKE_CUSTOMER, FAKE_CUSTOMER_II, FAKE_EVENT_CHARGE_SUCCEEDED, FAKE_EVENT_CUSTOMER_CREATED, FAKE_EVENT_CUSTOMER_DELETED, FAKE_EVENT_CUSTOMER_SOURCE_CREATED, FAKE_EVENT_CUSTOMER_SOURCE_DELETED, FAKE_EVENT_CUSTOMER_SOURCE_DELETED_DUPE, FAKE_EVENT_CUSTOMER_SUBSCRIPTION_CREATED, FAKE_EVENT_CUSTOMER_SUBSCRIPTION_DELETED, FAKE_EVENT_INVOICE_CREATED, FAKE_EVENT_INVOICE_DELETED, FAKE_EVENT_INVOICEITEM_CREATED, FAKE_EVENT_INVOICEITEM_DELETED, FAKE_EVENT_PLAN_CREATED, FAKE_EVENT_PLAN_DELETED, FAKE_EVENT_TRANSFER_CREATED, FAKE_EVENT_TRANSFER_DELETED, FAKE_INVOICE, FAKE_INVOICE_II, FAKE_INVOICEITEM, FAKE_PLAN, FAKE_SUBSCRIPTION, FAKE_SUBSCRIPTION_III, FAKE_TRANSFER)
[ 37811, 198, 492, 8265, 3712, 42625, 12, 33565, 431, 13, 41989, 13, 9288, 62, 15596, 62, 4993, 8116, 198, 220, 220, 1058, 28869, 24608, 25, 42625, 12, 33565, 431, 8558, 32412, 30307, 13, 198, 198, 492, 8265, 9800, 3712, 4422, 21195, 4275, 74, 615, 7959, 8, 198, 492, 8265, 9800, 3712, 5741, 16023, 268, 4275, 7278, 12728, 268, 8, 198, 198, 37811, 198, 198, 6738, 4866, 1330, 2769, 30073, 198, 11748, 32465, 198, 198, 6738, 42625, 14208, 13, 3642, 822, 13, 18439, 1330, 651, 62, 7220, 62, 19849, 198, 6738, 42625, 14208, 13, 9288, 1330, 6208, 20448, 198, 6738, 15290, 1330, 8529, 198, 198, 6738, 42625, 33565, 431, 13, 27530, 1330, 8558, 11, 20260, 11, 20558, 11, 10781, 11, 5224, 11, 22092, 11, 10001, 2942, 7449, 11, 10001, 2942, 11, 5172, 11, 3834, 33584, 198, 6738, 5254, 1330, 357, 7708, 7336, 62, 34, 9795, 11, 9677, 7336, 62, 38019, 8264, 11, 9677, 7336, 62, 38019, 8264, 62, 3978, 11, 9677, 7336, 62, 34, 7759, 2662, 1137, 11, 9677, 7336, 62, 34, 7759, 2662, 1137, 62, 3978, 11, 198, 220, 220, 220, 220, 220, 220, 220, 220, 220, 220, 220, 220, 220, 220, 220, 220, 220, 220, 9677, 7336, 62, 20114, 3525, 62, 38019, 8264, 62, 12564, 4093, 41841, 1961, 11, 9677, 7336, 62, 20114, 3525, 62, 34, 7759, 2662, 1137, 62, 43387, 11617, 11, 198, 220, 220, 220, 220, 220, 220, 220, 220, 220, 220, 220, 220, 220, 220, 220, 220, 220, 220, 9677, 7336, 62, 20114, 3525, 62, 34, 7759, 2662, 1137, 62, 7206, 28882, 1961, 11, 9677, 7336, 62, 20114, 3525, 62, 34, 7759, 2662, 1137, 62, 47690, 62, 43387, 11617, 11, 198, 220, 220, 220, 220, 220, 220, 220, 220, 220, 220, 220, 220, 220, 220, 220, 220, 220, 220, 9677, 7336, 62, 20114, 3525, 62, 34, 7759, 2662, 1137, 62, 47690, 62, 7206, 28882, 1961, 11, 9677, 7336, 62, 20114, 3525, 62, 34, 7759, 2662, 1137, 62, 47690, 62, 7206, 28882, 1961, 62, 35, 8577, 36, 11, 198, 220, 220, 220, 220, 220, 220, 220, 220, 220, 220, 220, 220, 220, 220, 220, 220, 220, 220, 9677, 7336, 62, 20114, 3525, 62, 34, 7759, 2662, 1137, 62, 12564, 4462, 40165, 62, 43387, 11617, 11, 9677, 7336, 62, 20114, 3525, 62, 34, 7759, 2662, 1137, 62, 12564, 4462, 40165, 62, 7206, 28882, 1961, 11, 198, 220, 220, 220, 220, 220, 220, 220, 220, 220, 220, 220, 220, 220, 220, 220, 220, 220, 220, 9677, 7336, 62, 20114, 3525, 62, 1268, 29516, 8476, 62, 43387, 11617, 11, 9677, 7336, 62, 20114, 3525, 62, 1268, 29516, 8476, 62, 7206, 28882, 1961, 11, 9677, 7336, 62, 20114, 3525, 62, 1268, 29516, 8476, 2043, 3620, 62, 43387, 11617, 11, 198, 220, 220, 220, 220, 220, 220, 220, 220, 220, 220, 220, 220, 220, 220, 220, 220, 220, 220, 9677, 7336, 62, 20114, 3525, 62, 1268, 29516, 8476, 2043, 3620, 62, 7206, 28882, 1961, 11, 9677, 7336, 62, 20114, 3525, 62, 6489, 1565, 62, 43387, 11617, 11, 9677, 7336, 62, 20114, 3525, 62, 6489, 1565, 62, 7206, 28882, 1961, 11, 198, 220, 220, 220, 220, 220, 220, 220, 220, 220, 220, 220, 220, 220, 220, 220, 220, 220, 220, 9677, 7336, 62, 20114, 3525, 62, 5446, 15037, 24302, 62, 43387, 11617, 11, 9677, 7336, 62, 20114, 3525, 62, 5446, 15037, 24302, 62, 7206, 28882, 1961, 11, 9677, 7336, 62, 1268, 29516, 8476, 11, 9677, 7336, 62, 1268, 29516, 8476, 62, 3978, 11, 198, 220, 220, 220, 220, 220, 220, 220, 220, 220, 220, 220, 220, 220, 220, 220, 220, 220, 220, 9677, 7336, 62, 1268, 29516, 8476, 2043, 3620, 11, 9677, 7336, 62, 6489, 1565, 11, 9677, 7336, 62, 12564, 4462, 40165, 11, 9677, 7336, 62, 12564, 4462, 40165, 62, 10855, 11, 9677, 7336, 62, 5446, 15037, 24302, 8, 628, 628, 628, 628 ]
2.114105
631
import common import json import logging import os import subprocess import time from dateutil import parser head_vault_hosts = 'OLD_IFS=${IFS};IFS=\',\' read -r -a VAULT_HOSTS <<< \"$STRING_VAULT_HOST\";IFS=${OLD_IFS};' source_kms_utils = '. /usr/sbin/kms_utils.sh;' global vault_token global vault_accessor global MAX_PERCENTAGE_EXPIRATION vault_token = os.getenv('VAULT_TOKEN', '') vault_accessor = os.getenv('ACCESSOR_TOKEN','') MIN_PERCENTAGE_EXPIRATION = 0.2 logger = None
[ 11748, 2219, 198, 11748, 33918, 198, 11748, 18931, 198, 11748, 28686, 198, 11748, 850, 14681, 198, 11748, 640, 198, 198, 6738, 3128, 22602, 1330, 30751, 198, 198, 2256, 62, 85, 1721, 62, 4774, 82, 796, 705, 15173, 62, 5064, 50, 28, 38892, 5064, 50, 19629, 5064, 50, 28, 59, 3256, 43054, 1100, 532, 81, 532, 64, 13753, 16724, 62, 39, 10892, 50, 9959, 27, 19990, 3, 18601, 2751, 62, 11731, 16724, 62, 39, 10892, 7879, 26, 5064, 50, 28, 38892, 15173, 62, 5064, 50, 19629, 6, 198, 10459, 62, 74, 907, 62, 26791, 796, 45302, 1220, 14629, 14, 82, 8800, 14, 74, 907, 62, 26791, 13, 1477, 26, 6, 198, 198, 20541, 22563, 62, 30001, 198, 20541, 22563, 62, 15526, 273, 198, 20541, 25882, 62, 18973, 43960, 11879, 62, 49864, 4663, 6234, 198, 198, 85, 1721, 62, 30001, 796, 28686, 13, 1136, 24330, 10786, 11731, 16724, 62, 10468, 43959, 3256, 10148, 8, 198, 85, 1721, 62, 15526, 273, 796, 28686, 13, 1136, 24330, 10786, 26861, 7597, 1581, 62, 10468, 43959, 3256, 7061, 8, 198, 23678, 62, 18973, 43960, 11879, 62, 49864, 4663, 6234, 796, 657, 13, 17, 198, 198, 6404, 1362, 796, 6045, 628 ]
2.5
194
"Introducing the sys Module" import sys print(sys.platform) print(sys.maxsize) print(sys.version) if sys.platform[:3] == 'win': print('hello windows')
[ 1, 15005, 2259, 262, 25064, 19937, 1, 198, 11748, 25064, 220, 198, 4798, 7, 17597, 13, 24254, 8, 198, 4798, 7, 17597, 13, 9806, 7857, 8, 198, 4798, 7, 17597, 13, 9641, 8, 628, 198, 361, 25064, 13, 24254, 58, 25, 18, 60, 6624, 705, 5404, 10354, 3601, 10786, 31373, 9168, 11537, 198 ]
2.90566
53
from .orion import parse_orion
[ 6738, 764, 273, 295, 1330, 21136, 62, 273, 295, 198 ]
3.1
10
with open("./day09.input") as file: data = [int(line.strip()) for line in file.readlines()] p1 = get_first_not_matching(25) print(p1) p2 = get_contiguous_ns_that_add_to(p1) print(p2)
[ 4480, 1280, 7, 1911, 14, 820, 2931, 13, 15414, 4943, 355, 2393, 25, 198, 197, 7890, 796, 685, 600, 7, 1370, 13, 36311, 28955, 329, 1627, 287, 2393, 13, 961, 6615, 3419, 60, 628, 198, 198, 79, 16, 796, 651, 62, 11085, 62, 1662, 62, 15699, 278, 7, 1495, 8, 198, 4798, 7, 79, 16, 8, 198, 198, 79, 17, 796, 651, 62, 3642, 29709, 62, 5907, 62, 5562, 62, 2860, 62, 1462, 7, 79, 16, 8, 198, 4798, 7, 79, 17, 8 ]
2.253012
83
import json import os import nibabel as nib import numpy as np import pandas as pd ROOT = "./" DATA = os.path.join(ROOT, "data/")
[ 11748, 33918, 198, 11748, 28686, 198, 198, 11748, 33272, 9608, 355, 33272, 198, 11748, 299, 32152, 355, 45941, 198, 11748, 19798, 292, 355, 279, 67, 198, 198, 13252, 2394, 796, 366, 19571, 1, 198, 26947, 796, 28686, 13, 6978, 13, 22179, 7, 13252, 2394, 11, 366, 7890, 14, 4943, 198 ]
2.64
50
import matplotlib import random import operator import csv import drunkframework import matplotlib.animation import matplotlib.pyplot """WARNING!!!!!""" """This code was tested using Spyder 5.0.4, should any problems be encountered using older models please try """ #creates a new empty list for what will be the csv environment data, see https://docs.python.org/3/library/csv.html for more environment = [] #drunks adapted from agents from GUI's practical replacing "agents" drunks = [] #density is an empty list which will track agent movement independent of the movement process density= [] #specifies number of drunks/agents num_of_drunks = 25 #outlines the number of iterations the line 64-78 code will undergo num_of_iterations = 100 #sets the dimensions for the matplotlib plots fig = matplotlib.pyplot.figure(figsize=(7, 7)) ax = fig.add_axes([0, 0, 1, 1]) f = open('drunk.txt', newline='') #Note that the correct directory must be navigated to in the terminal else the full file path will be needed reader = csv.reader(f, quoting=csv.QUOTE_NONNUMERIC) #Used for testing purposes to ascertain the lay of the environment #matplotlib.pyplot.xlim(0, 300) #matplotlib.pyplot.ylim(0, 300) #matplotlib.pyplot.imshow(environment) for row in reader: rowlist =[] for value in row: rowlist.append(value) environment.append(rowlist) f.close() #print (rowlist) Used this to check list structure #Code on lines 46-50 appends the density list output to a 300x300 grid, this code is needed #to prevent the error "IndexError: list index out of range" for i in range(300): rowlist = [] for j in range(300): rowlist.append(0) density.append(rowlist) #matplotlib.pyplot.imshow(environment) run this in isolation to check the environment is #correct ## Make drunks and assign them with an identification number. for i in range(num_of_drunks): identification = ((1+i)*10) # print(identification) #this should print 10-250 giving each of the drunks an identification number, later to be matched up with houses drunks.append(drunkframework.Drunk(environment, drunks, identification)) #This is is supposed to work whereby if the co-ordinates of stilldrunk match their identification number they are home #In the prototype density of the environment changed throughout the iterations, as such the drunks would #often stop in areas which were not their home. The work around this was seperating the process of track #and move through the creation of the density list. Track is left in but commented. for i in range (num_of_drunks): stilldrunk = drunks[i] for j in range(num_of_iterations): while environment [stilldrunk._y][stilldrunk._x] != stilldrunk.identification: density[drunks[i]._y][drunks[i]._x]+=1 drunks[i].move() #drunks[i].track() omitted from the final iteration of the application #saves density list (see lines 68 to 73) with open('density.txt', 'w', newline='') as f: csvwriter = csv.writer(f, delimiter=',', quoting=csv.QUOTE_NONNUMERIC) for row in density: csvwriter.writerow(row) #lines 79 to 90 serve the purpose of display the density and drunks in relation #to their finishing position within the environment matplotlib.pyplot.xlim(0, 300) matplotlib.pyplot.ylim(0, 300) matplotlib.pyplot.imshow(density) matplotlib.pyplot.xlim(0, 300) matplotlib.pyplot.ylim(0, 300) matplotlib.pyplot.show(drunks) matplotlib.pyplot.xlim(0, 300) matplotlib.pyplot.ylim(0, 300) matplotlib.pyplot.imshow(environment) #Code below just prints we're home for each of the 25 agents following a resolution of #the code for i in range(num_of_drunks): matplotlib.pyplot.scatter(drunks[i]._x, drunks[i]._y) print("we're home!")
[ 11748, 2603, 29487, 8019, 201, 198, 11748, 4738, 201, 198, 11748, 10088, 201, 198, 11748, 269, 21370, 201, 198, 11748, 10785, 30604, 201, 198, 11748, 2603, 29487, 8019, 13, 11227, 341, 220, 201, 198, 11748, 2603, 29487, 8019, 13, 9078, 29487, 201, 198, 201, 198, 201, 198, 201, 198, 201, 198, 37811, 31502, 13896, 2474, 15931, 201, 198, 37811, 1212, 2438, 373, 6789, 1262, 23688, 1082, 642, 13, 15, 13, 19, 11, 815, 597, 2761, 307, 12956, 1262, 4697, 201, 198, 27530, 3387, 1949, 37227, 201, 198, 201, 198, 2, 20123, 274, 257, 649, 6565, 1351, 329, 644, 481, 307, 262, 269, 21370, 2858, 1366, 11, 766, 3740, 1378, 31628, 13, 29412, 13, 2398, 14, 18, 14, 32016, 14, 40664, 13, 6494, 329, 517, 201, 198, 38986, 796, 17635, 201, 198, 2, 67, 5143, 591, 16573, 422, 6554, 422, 25757, 338, 8472, 13586, 366, 49638, 1, 201, 198, 67, 5143, 591, 796, 17635, 201, 198, 2, 43337, 318, 281, 6565, 1351, 543, 481, 2610, 5797, 3356, 4795, 286, 262, 3356, 1429, 201, 198, 43337, 28, 17635, 201, 198, 2, 16684, 6945, 1271, 286, 1553, 14125, 14, 49638, 201, 198, 22510, 62, 1659, 62, 67, 5143, 591, 796, 1679, 201, 198, 2, 448, 6615, 262, 1271, 286, 34820, 262, 1627, 5598, 12, 3695, 2438, 481, 17777, 201, 198, 22510, 62, 1659, 62, 2676, 602, 796, 1802, 201, 198, 201, 198, 201, 198, 2, 28709, 262, 15225, 329, 262, 2603, 29487, 8019, 21528, 201, 198, 5647, 796, 2603, 29487, 8019, 13, 9078, 29487, 13, 26875, 7, 5647, 7857, 16193, 22, 11, 767, 4008, 201, 198, 897, 796, 2336, 13, 2860, 62, 897, 274, 26933, 15, 11, 657, 11, 352, 11, 352, 12962, 201, 198, 201, 198, 201, 198, 201, 198, 69, 796, 1280, 10786, 7109, 2954, 13, 14116, 3256, 649, 1370, 28, 7061, 8, 201, 198, 2, 6425, 326, 262, 3376, 8619, 1276, 307, 20436, 515, 284, 287, 262, 12094, 2073, 262, 1336, 2393, 3108, 481, 307, 2622, 201, 198, 46862, 796, 269, 21370, 13, 46862, 7, 69, 11, 28411, 28, 40664, 13, 10917, 23051, 62, 45, 1340, 41359, 1137, 2149, 8, 201, 198, 201, 198, 2, 38052, 329, 4856, 4959, 284, 35520, 262, 3830, 286, 262, 2858, 201, 198, 2, 6759, 29487, 8019, 13, 9078, 29487, 13, 87, 2475, 7, 15, 11, 5867, 8, 201, 198, 2, 6759, 29487, 8019, 13, 9078, 29487, 13, 88, 2475, 7, 15, 11, 5867, 8, 201, 198, 2, 6759, 29487, 8019, 13, 9078, 29487, 13, 320, 12860, 7, 38986, 8, 201, 198, 201, 198, 1640, 5752, 287, 9173, 25, 201, 198, 220, 220, 220, 5752, 4868, 796, 21737, 201, 198, 220, 220, 220, 329, 1988, 287, 5752, 25, 201, 198, 220, 220, 220, 220, 220, 220, 220, 5752, 4868, 13, 33295, 7, 8367, 8, 201, 198, 220, 220, 220, 2858, 13, 33295, 7, 808, 4868, 8, 201, 198, 69, 13, 19836, 3419, 201, 198, 2, 4798, 357, 808, 4868, 8, 16718, 428, 284, 2198, 1351, 4645, 201, 198, 201, 198, 2, 10669, 319, 3951, 6337, 12, 1120, 598, 2412, 262, 12109, 1351, 5072, 284, 257, 5867, 87, 6200, 10706, 11, 428, 2438, 318, 2622, 220, 201, 198, 2, 1462, 2948, 262, 4049, 366, 15732, 12331, 25, 1351, 6376, 503, 286, 2837, 1, 220, 220, 220, 220, 220, 220, 220, 220, 220, 220, 220, 220, 220, 220, 220, 220, 220, 220, 220, 220, 220, 220, 220, 220, 220, 220, 220, 220, 220, 220, 220, 220, 201, 198, 1640, 1312, 287, 2837, 7, 6200, 2599, 201, 198, 220, 220, 220, 5752, 4868, 796, 17635, 201, 198, 220, 220, 220, 329, 474, 287, 2837, 7, 6200, 2599, 201, 198, 220, 220, 220, 220, 220, 220, 220, 5752, 4868, 13, 33295, 7, 15, 8, 201, 198, 220, 220, 220, 12109, 13, 33295, 7, 808, 4868, 8, 201, 198, 2, 6759, 29487, 8019, 13, 9078, 29487, 13, 320, 12860, 7, 38986, 8, 1057, 428, 287, 15133, 284, 2198, 262, 2858, 318, 201, 198, 2, 30283, 201, 198, 201, 198, 201, 198, 2235, 6889, 1553, 14125, 290, 8333, 606, 351, 281, 11795, 1271, 13, 201, 198, 1640, 1312, 287, 2837, 7, 22510, 62, 1659, 62, 67, 5143, 591, 2599, 201, 198, 220, 220, 220, 11795, 796, 14808, 16, 10, 72, 27493, 940, 8, 220, 201, 198, 220, 220, 1303, 3601, 7, 738, 2649, 8, 1303, 5661, 815, 3601, 838, 12, 9031, 3501, 1123, 286, 262, 1553, 14125, 281, 11795, 1271, 11, 1568, 284, 307, 14451, 510, 351, 7777, 201, 198, 220, 220, 220, 1553, 14125, 13, 33295, 7, 7109, 2954, 30604, 13, 6187, 2954, 7, 38986, 11, 1553, 14125, 11, 11795, 4008, 201, 198, 220, 220, 220, 220, 201, 198, 201, 198, 201, 198, 2, 1212, 318, 318, 4385, 284, 670, 23482, 611, 262, 763, 12, 585, 17540, 286, 991, 7109, 2954, 2872, 511, 11795, 1271, 484, 389, 1363, 220, 201, 198, 2, 818, 262, 14879, 12109, 286, 262, 2858, 3421, 3690, 262, 34820, 11, 355, 884, 262, 1553, 14125, 561, 201, 198, 2, 28950, 2245, 287, 3006, 543, 547, 407, 511, 1363, 13, 383, 670, 1088, 428, 373, 384, 525, 803, 262, 1429, 286, 2610, 201, 198, 2, 392, 1445, 832, 262, 6282, 286, 262, 12109, 1351, 13, 17762, 318, 1364, 287, 475, 16476, 13, 201, 198, 1640, 1312, 287, 2837, 357, 22510, 62, 1659, 62, 67, 5143, 591, 2599, 201, 198, 220, 220, 220, 991, 7109, 2954, 796, 1553, 14125, 58, 72, 60, 201, 198, 220, 220, 220, 329, 474, 287, 2837, 7, 22510, 62, 1659, 62, 2676, 602, 2599, 201, 198, 220, 220, 220, 220, 220, 220, 220, 220, 981, 2858, 685, 24219, 7109, 2954, 13557, 88, 7131, 24219, 7109, 2954, 13557, 87, 60, 14512, 991, 7109, 2954, 13, 738, 2649, 25, 201, 198, 220, 220, 220, 220, 220, 220, 220, 220, 220, 220, 220, 220, 220, 220, 220, 12109, 58, 67, 5143, 591, 58, 72, 4083, 62, 88, 7131, 67, 5143, 591, 58, 72, 4083, 62, 87, 60, 47932, 16, 201, 198, 220, 220, 220, 220, 220, 220, 220, 220, 220, 220, 220, 220, 220, 220, 220, 1553, 14125, 58, 72, 4083, 21084, 3419, 201, 198, 220, 220, 220, 220, 220, 220, 220, 220, 220, 220, 220, 220, 220, 220, 220, 1303, 67, 5143, 591, 58, 72, 4083, 11659, 3419, 22532, 422, 262, 2457, 24415, 286, 262, 3586, 201, 198, 201, 198, 2, 82, 3080, 12109, 1351, 357, 3826, 3951, 8257, 284, 8854, 8, 201, 198, 4480, 1280, 10786, 43337, 13, 14116, 3256, 705, 86, 3256, 649, 1370, 28, 7061, 8, 355, 277, 25, 201, 198, 220, 220, 220, 269, 21370, 16002, 796, 269, 21370, 13, 16002, 7, 69, 11, 46728, 2676, 28, 3256, 3256, 28411, 28, 40664, 13, 10917, 23051, 62, 45, 1340, 41359, 1137, 2149, 8, 201, 198, 220, 220, 220, 329, 5752, 287, 12109, 25, 201, 198, 220, 220, 220, 220, 220, 220, 220, 269, 21370, 16002, 13, 16002, 322, 7, 808, 8, 220, 220, 220, 220, 220, 220, 220, 220, 220, 220, 220, 220, 220, 220, 220, 220, 201, 198, 220, 220, 201, 198, 2, 6615, 9225, 284, 4101, 4691, 262, 4007, 286, 3359, 262, 12109, 290, 1553, 14125, 287, 8695, 201, 198, 2, 1462, 511, 12848, 2292, 1626, 262, 2858, 201, 198, 220, 220, 220, 220, 220, 220, 220, 220, 220, 220, 220, 220, 220, 220, 220, 220, 220, 220, 220, 220, 220, 220, 220, 220, 220, 220, 220, 220, 220, 220, 201, 198, 6759, 29487, 8019, 13, 9078, 29487, 13, 87, 2475, 7, 15, 11, 5867, 8, 201, 198, 6759, 29487, 8019, 13, 9078, 29487, 13, 88, 2475, 7, 15, 11, 5867, 8, 201, 198, 6759, 29487, 8019, 13, 9078, 29487, 13, 320, 12860, 7, 43337, 8, 201, 198, 201, 198, 6759, 29487, 8019, 13, 9078, 29487, 13, 87, 2475, 7, 15, 11, 5867, 8, 201, 198, 6759, 29487, 8019, 13, 9078, 29487, 13, 88, 2475, 7, 15, 11, 5867, 8, 201, 198, 6759, 29487, 8019, 13, 9078, 29487, 13, 12860, 7, 67, 5143, 591, 8, 201, 198, 201, 198, 201, 198, 6759, 29487, 8019, 13, 9078, 29487, 13, 87, 2475, 7, 15, 11, 5867, 8, 201, 198, 6759, 29487, 8019, 13, 9078, 29487, 13, 88, 2475, 7, 15, 11, 5867, 8, 201, 198, 6759, 29487, 8019, 13, 9078, 29487, 13, 320, 12860, 7, 38986, 8, 201, 198, 201, 198, 2, 10669, 2174, 655, 20842, 356, 821, 1363, 329, 1123, 286, 262, 1679, 6554, 1708, 257, 6323, 286, 201, 198, 2, 1169, 2438, 201, 198, 201, 198, 1640, 1312, 287, 2837, 7, 22510, 62, 1659, 62, 67, 5143, 591, 2599, 201, 198, 220, 220, 220, 220, 220, 220, 220, 2603, 29487, 8019, 13, 9078, 29487, 13, 1416, 1436, 7, 67, 5143, 591, 58, 72, 4083, 62, 87, 11, 1553, 14125, 58, 72, 4083, 62, 88, 8, 201, 198, 220, 220, 220, 220, 220, 220, 220, 3601, 7203, 732, 821, 1363, 2474, 8, 220, 220, 220, 220, 201, 198 ]
2.713701
1,467
"""Loading a .caffemodel and figure out the encoding. Author: Yuhuang Hu Email : [email protected] """ from __future__ import absolute_import from __future__ import print_function import os # from keras.utils.visualize_util import plot from keras.datasets import mnist as dataset from keras.utils import np_utils import transcaffe as tc batch_size = 128 nb_classes = 10 nb_epoch = 40 # input image dimensions img_rows, img_cols = 28, 28 # number of convolutional filters to use nb_filters = 32 # size of pooling area for max pooling nb_pool = 2 # convolution kernel size nb_conv = 3 # color channels chnls = 1 # the data, shuffled and split between train and test sets (X_train, y_train), (X_test, y_test) = dataset.load_data() X_train = X_train.reshape(X_train.shape[0], chnls, img_rows, img_cols) X_test = X_test.reshape(X_test.shape[0], chnls, img_rows, img_cols) X_train = X_train.astype("float32") X_test = X_test.astype("float32") X_train /= 255 X_test /= 255 # convert class vectors to binary class matrices Y_train = np_utils.to_categorical(y_train, nb_classes) Y_test = np_utils.to_categorical(y_test, nb_classes) print('X_train shape:', X_train.shape) print(X_train.shape[0], 'train samples') print(X_test.shape[0], 'test samples') # define model for testing data_path = os.environ["TRANSCAFFE_DATA"] # model_str = os.path.join(data_path, # "VGG_ILSVRC_16_layers_deploy.prototxt.txt") model_str = os.path.join(data_path, "lenet.prototxt.txt") model_bin = os.path.join(data_path, "lenet_iter_10000.caffemodel") model = tc.load(model_str, model_bin, target_lib="keras") model.compile(loss='categorical_crossentropy', optimizer='adadelta', metrics=['accuracy']) score = model.evaluate(X_test, Y_test, verbose=0) print('Test score:', score[0]) print('Test accuracy:', score[1])
[ 37811, 19031, 257, 764, 66, 2001, 368, 375, 417, 290, 3785, 503, 262, 21004, 13, 198, 198, 13838, 25, 575, 7456, 84, 648, 11256, 198, 15333, 1058, 18735, 4669, 518, 3064, 31, 14816, 13, 785, 198, 37811, 198, 198, 6738, 11593, 37443, 834, 1330, 4112, 62, 11748, 198, 6738, 11593, 37443, 834, 1330, 3601, 62, 8818, 198, 11748, 28686, 198, 2, 422, 41927, 292, 13, 26791, 13, 41464, 1096, 62, 22602, 1330, 7110, 198, 198, 6738, 41927, 292, 13, 19608, 292, 1039, 1330, 285, 77, 396, 355, 27039, 198, 6738, 41927, 292, 13, 26791, 1330, 45941, 62, 26791, 198, 198, 11748, 23589, 21223, 355, 37096, 198, 198, 43501, 62, 7857, 796, 13108, 198, 46803, 62, 37724, 796, 838, 198, 46803, 62, 538, 5374, 796, 2319, 198, 198, 2, 5128, 2939, 15225, 198, 9600, 62, 8516, 11, 33705, 62, 4033, 82, 796, 2579, 11, 2579, 198, 2, 1271, 286, 3063, 2122, 282, 16628, 284, 779, 198, 46803, 62, 10379, 1010, 796, 3933, 198, 2, 2546, 286, 5933, 278, 1989, 329, 3509, 5933, 278, 198, 46803, 62, 7742, 796, 362, 198, 2, 3063, 2122, 9720, 2546, 198, 46803, 62, 42946, 796, 513, 198, 2, 3124, 9619, 198, 1349, 7278, 796, 352, 198, 198, 2, 262, 1366, 11, 32299, 992, 290, 6626, 1022, 4512, 290, 1332, 5621, 198, 7, 55, 62, 27432, 11, 331, 62, 27432, 828, 357, 55, 62, 9288, 11, 331, 62, 9288, 8, 796, 27039, 13, 2220, 62, 7890, 3419, 198, 198, 55, 62, 27432, 796, 1395, 62, 27432, 13, 3447, 1758, 7, 55, 62, 27432, 13, 43358, 58, 15, 4357, 442, 77, 7278, 11, 33705, 62, 8516, 11, 33705, 62, 4033, 82, 8, 198, 55, 62, 9288, 796, 1395, 62, 9288, 13, 3447, 1758, 7, 55, 62, 9288, 13, 43358, 58, 15, 4357, 442, 77, 7278, 11, 33705, 62, 8516, 11, 33705, 62, 4033, 82, 8, 198, 55, 62, 27432, 796, 1395, 62, 27432, 13, 459, 2981, 7203, 22468, 2624, 4943, 198, 55, 62, 9288, 796, 1395, 62, 9288, 13, 459, 2981, 7203, 22468, 2624, 4943, 198, 55, 62, 27432, 1220, 28, 14280, 198, 55, 62, 9288, 1220, 28, 14280, 198, 198, 2, 10385, 1398, 30104, 284, 13934, 1398, 2603, 45977, 198, 56, 62, 27432, 796, 45941, 62, 26791, 13, 1462, 62, 66, 2397, 12409, 7, 88, 62, 27432, 11, 299, 65, 62, 37724, 8, 198, 56, 62, 9288, 796, 45941, 62, 26791, 13, 1462, 62, 66, 2397, 12409, 7, 88, 62, 9288, 11, 299, 65, 62, 37724, 8, 198, 198, 4798, 10786, 55, 62, 27432, 5485, 25, 3256, 1395, 62, 27432, 13, 43358, 8, 198, 4798, 7, 55, 62, 27432, 13, 43358, 58, 15, 4357, 705, 27432, 8405, 11537, 198, 4798, 7, 55, 62, 9288, 13, 43358, 58, 15, 4357, 705, 9288, 8405, 11537, 628, 198, 2, 8160, 2746, 329, 4856, 198, 7890, 62, 6978, 796, 28686, 13, 268, 2268, 14692, 5446, 1565, 6173, 32, 5777, 36, 62, 26947, 8973, 198, 198, 2, 2746, 62, 2536, 796, 28686, 13, 6978, 13, 22179, 7, 7890, 62, 6978, 11, 198, 2, 220, 220, 220, 220, 220, 220, 220, 220, 220, 220, 220, 220, 220, 220, 220, 220, 220, 220, 220, 220, 220, 220, 220, 220, 220, 366, 53, 11190, 62, 45484, 53, 7397, 62, 1433, 62, 75, 6962, 62, 2934, 1420, 13, 11235, 313, 742, 13, 14116, 4943, 198, 19849, 62, 2536, 796, 28686, 13, 6978, 13, 22179, 7, 7890, 62, 6978, 11, 366, 11925, 316, 13, 11235, 313, 742, 13, 14116, 4943, 198, 19849, 62, 8800, 796, 28686, 13, 6978, 13, 22179, 7, 7890, 62, 6978, 11, 366, 11925, 316, 62, 2676, 62, 49388, 13, 66, 2001, 368, 375, 417, 4943, 198, 198, 19849, 796, 37096, 13, 2220, 7, 19849, 62, 2536, 11, 2746, 62, 8800, 11, 2496, 62, 8019, 2625, 6122, 292, 4943, 198, 198, 19849, 13, 5589, 576, 7, 22462, 11639, 66, 2397, 12409, 62, 19692, 298, 28338, 3256, 6436, 7509, 11639, 324, 324, 12514, 3256, 198, 220, 220, 220, 220, 220, 220, 220, 220, 220, 220, 220, 220, 220, 20731, 28, 17816, 4134, 23843, 6, 12962, 198, 26675, 796, 2746, 13, 49786, 7, 55, 62, 9288, 11, 575, 62, 9288, 11, 15942, 577, 28, 15, 8, 198, 4798, 10786, 14402, 4776, 25, 3256, 4776, 58, 15, 12962, 198, 4798, 10786, 14402, 9922, 25, 3256, 4776, 58, 16, 12962, 198 ]
2.582048
713
from typing import Dict, List, Optional from kubernetes import client from tlaunch.lp_k8s.resource import Resource from tlaunch.lp_k8s.util import map_opt DEFAULT_PORT = 8001 DEFAULT_NAME = 'launchpad' REVERB_IMAGE = 'reg.real-ai.cn/launchpad/reverb' DEFAULT_COMMAND = ['python3', '-u', '-mlaunchpad_kubernetes.process_entry']
[ 6738, 19720, 1330, 360, 713, 11, 7343, 11, 32233, 198, 198, 6738, 479, 18478, 3262, 274, 1330, 5456, 198, 198, 6738, 256, 35681, 13, 34431, 62, 74, 23, 82, 13, 31092, 1330, 20857, 198, 6738, 256, 35681, 13, 34431, 62, 74, 23, 82, 13, 22602, 1330, 3975, 62, 8738, 198, 198, 7206, 38865, 62, 15490, 796, 807, 8298, 198, 7206, 38865, 62, 20608, 796, 705, 35681, 15636, 6, 198, 2200, 5959, 33, 62, 3955, 11879, 796, 705, 2301, 13, 5305, 12, 1872, 13, 31522, 14, 35681, 15636, 14, 260, 19011, 6, 198, 7206, 38865, 62, 9858, 44, 6981, 796, 37250, 29412, 18, 3256, 705, 12, 84, 3256, 705, 12, 4029, 11429, 15636, 62, 74, 18478, 3262, 274, 13, 14681, 62, 13000, 20520, 628, 628 ]
2.685484
124
"""Retry downloading files that caused errors in http_downloader. We can find files to try downloading again by parsing the err.txt file for error messages. Error log lines we are interested in look like: 09-04-2017 12:45:17..Error_http_downloader 'exports/CalStateTEACH Term 1/grios/Schedule/Mentor Info.docx', 'https://ourdomain.instructure.com/files/8080/download?download_frd=1&verifier=zVZdnkpTmmJIGYAg2U0PaDqESrJBFLi0Xsm73Eldu' A regex string that captures the file name & URL looks like: [0-9][0-9]-[0-9][0-9]-[0-9][0-9][0-9][0-9] [0-9][0-9]:[0-9][0-9]:[0-9][0-9]\.\.Error_http_downloader '(.*)', '(.*)'$ 09.04.2017 tps Created. 09.17.2018 tps Change bad global Null reference to None. """ import script_logging import http_downloader import os import re import shutil ######### Constants ######### # Regex pattern for extracting file download details from error log. REGEX_PATTERN = "[0-9][0-9]-[0-9][0-9]-[0-9][0-9][0-9][0-9] [0-9][0-9]:[0-9][0-9]:[0-9][0-9]\.\.Error_http_downloader '(.*)', '(.*)'$" def make_cp_file_name(): """Create a unique file that looks like "retry000.txt", "retry001.txt", "retry002.txt", etc. """ cp_file_name = None # Function return variable n = 0 while True: cp_file_name = 'retry%03d.txt' % n if (not os.path.exists(cp_file_name)): break else: n = n + 1 continue return cp_file_name ######### Stand-Alone Execution ######### if __name__ == "__main__": load_errors()
[ 37811, 9781, 563, 22023, 3696, 326, 4073, 8563, 287, 2638, 62, 15002, 263, 13, 198, 1135, 460, 1064, 3696, 284, 1949, 22023, 757, 416, 32096, 262, 11454, 13, 14116, 2393, 329, 4049, 6218, 13, 198, 12331, 2604, 3951, 356, 389, 4609, 287, 804, 588, 25, 198, 198, 2931, 12, 3023, 12, 5539, 1105, 25, 2231, 25, 1558, 492, 12331, 62, 4023, 62, 15002, 263, 705, 1069, 3742, 14, 9771, 9012, 9328, 16219, 35118, 352, 14, 70, 380, 418, 14, 27054, 5950, 14, 44, 298, 273, 14151, 13, 15390, 87, 3256, 705, 5450, 1378, 454, 27830, 13, 8625, 5620, 13, 785, 14, 16624, 14, 1795, 1795, 14, 15002, 30, 15002, 62, 69, 4372, 28, 16, 5, 332, 7483, 28, 89, 53, 57, 32656, 74, 79, 51, 3020, 41, 3528, 56, 10262, 17, 52, 15, 28875, 35, 80, 1546, 81, 47858, 3697, 72, 15, 55, 5796, 4790, 36, 335, 84, 6, 198, 198, 32, 40364, 4731, 326, 23007, 262, 2393, 1438, 1222, 10289, 3073, 588, 25, 198, 198, 58, 15, 12, 24, 7131, 15, 12, 24, 45297, 58, 15, 12, 24, 7131, 15, 12, 24, 45297, 58, 15, 12, 24, 7131, 15, 12, 24, 7131, 15, 12, 24, 7131, 15, 12, 24, 60, 685, 15, 12, 24, 7131, 15, 12, 24, 5974, 58, 15, 12, 24, 7131, 15, 12, 24, 5974, 58, 15, 12, 24, 7131, 15, 12, 24, 60, 17405, 17405, 12331, 62, 4023, 62, 15002, 263, 29513, 15885, 8, 3256, 29513, 15885, 33047, 3, 198, 198, 2931, 13, 3023, 13, 5539, 256, 862, 15622, 13, 198, 2931, 13, 1558, 13, 7908, 256, 862, 9794, 2089, 3298, 35886, 4941, 284, 6045, 13, 198, 37811, 198, 11748, 4226, 62, 6404, 2667, 198, 11748, 2638, 62, 15002, 263, 198, 11748, 28686, 198, 11748, 302, 198, 11748, 4423, 346, 628, 198, 7804, 2, 4757, 1187, 1303, 7804, 198, 198, 2, 797, 25636, 3912, 329, 37895, 2393, 4321, 3307, 422, 4049, 2604, 13, 198, 31553, 6369, 62, 47, 1404, 31800, 796, 12878, 15, 12, 24, 7131, 15, 12, 24, 45297, 58, 15, 12, 24, 7131, 15, 12, 24, 45297, 58, 15, 12, 24, 7131, 15, 12, 24, 7131, 15, 12, 24, 7131, 15, 12, 24, 60, 685, 15, 12, 24, 7131, 15, 12, 24, 5974, 58, 15, 12, 24, 7131, 15, 12, 24, 5974, 58, 15, 12, 24, 7131, 15, 12, 24, 60, 17405, 17405, 12331, 62, 4023, 62, 15002, 263, 29513, 15885, 8, 3256, 29513, 15885, 33047, 3, 1, 198, 220, 198, 198, 4299, 787, 62, 13155, 62, 7753, 62, 3672, 33529, 198, 220, 220, 220, 37227, 16447, 257, 3748, 2393, 326, 3073, 588, 366, 1186, 563, 830, 13, 14116, 1600, 366, 1186, 563, 8298, 13, 14116, 1600, 220, 198, 220, 220, 220, 366, 1186, 563, 21601, 13, 14116, 1600, 3503, 13, 198, 220, 220, 220, 37227, 628, 220, 220, 220, 31396, 62, 7753, 62, 3672, 796, 6045, 220, 1303, 15553, 1441, 7885, 198, 220, 220, 220, 299, 796, 657, 198, 220, 220, 220, 981, 6407, 25, 198, 220, 220, 220, 220, 220, 220, 220, 31396, 62, 7753, 62, 3672, 796, 705, 1186, 563, 4, 3070, 67, 13, 14116, 6, 4064, 299, 198, 220, 220, 220, 220, 220, 220, 220, 611, 357, 1662, 28686, 13, 6978, 13, 1069, 1023, 7, 13155, 62, 7753, 62, 3672, 8, 2599, 198, 220, 220, 220, 220, 220, 220, 220, 220, 220, 220, 220, 2270, 220, 198, 220, 220, 220, 220, 220, 220, 220, 2073, 25, 198, 220, 220, 220, 220, 220, 220, 220, 220, 220, 220, 220, 299, 796, 299, 1343, 352, 198, 220, 220, 220, 220, 220, 220, 220, 220, 220, 220, 220, 2555, 628, 220, 220, 220, 1441, 31396, 62, 7753, 62, 3672, 628, 628, 198, 7804, 2, 5751, 12, 2348, 505, 37497, 1303, 7804, 198, 198, 361, 11593, 3672, 834, 6624, 366, 834, 12417, 834, 1298, 198, 220, 220, 220, 3440, 62, 48277, 3419, 198 ]
2.370313
640
from nltk import RegexpTokenizer # Common stopwords in french and english # Clean text or sentence, removing stopwords # return list
[ 6738, 299, 2528, 74, 1330, 797, 25636, 79, 30642, 7509, 198, 198, 2, 8070, 2245, 10879, 287, 48718, 290, 46932, 198, 198, 2, 5985, 2420, 393, 6827, 11, 10829, 2245, 10879, 198, 2, 1441, 1351, 198 ]
3.75
36
import random from enum import Enum import numpy as np from custom_decorators import profile from shapes import Box from shared_constants import BBREG_MULTIPLIERS, DEFAULT_ANCHORS from util import calc_iou, cross_ious, get_reg_params, get_bbox_coords POS_OVERLAP = 0.7 NEG_OVERLAP = 0.3 SAMPLE_SIZE = 256 MAX_POS_SAMPLES = 128 class RpnTrainingManager: """ Encapsulates the details of generating training inputs for a region proposal network for a given image. """ def __init__(self, calc_conv_dims, stride, preprocess_func, anchor_dims=DEFAULT_ANCHORS): """ :param calc_conv_dims: function that accepts a tuple of the image's height and width in pixels and returns the height and width of the convolutional layer prior to the rpn layers. :param stride: positive integer, the cumulative stride at the convolutional layer prior to the rpn layers. :param preprocess_func: function that applies the same transformation to the image's pixels as used for Imagenet training. Otherwise the Imagenet pre-trained weights will be mismatched. :param anchor_dims: list of lists of positive integers, one height and width pair for each anchor. """ self._cache = {} self.calc_conv_dims = calc_conv_dims self.stride = stride self.preprocess_func = preprocess_func self.anchor_dims = anchor_dims @profile def batched_image(self, image): """ Returns the image data to be fed into the network. :param image: shapes.Image object. :return: 4-d numpy array with a single batch of the image, should can be used as a Keras model input. """ return np.expand_dims(self.preprocess_func(image.data), axis=0) @profile @profile def rpn_y_true(self, image): """ Takes an image and returns the Keras model inputs to train with. :param image: shapes.Image object to generate training inputs for. :return: tuple where the first element is a numpy array of the ground truth network output for whether each anchor overlaps with an object, and the second element is a numpy array of the ground truth network output for the bounding box transformation parameters to transform each anchor into an object's bounding box. """ ''' Consider removing caching - added when self.process was taking 0.4s to run. Since then, optimized it down to 0.02s locally, 0.003s on aws so the cache isn't too useful anymore. ''' if image.cache_key not in self._cache: self._process(image) results = self._cache[image.cache_key] # TODO: why is the cached result being deleted? Investigate whether restoring it improves training time. del self._cache[image.cache_key] can_use = _apply_sampling(results['is_pos'], results['can_use']) conv_rows, conv_cols = self.calc_conv_dims(image.height, image.width) is_pos = np.reshape(results['is_pos'], (conv_rows, conv_cols, len(self.anchor_dims))) can_use = np.reshape(can_use, (conv_rows, conv_cols, len(self.anchor_dims))) selected_is_pos = np.logical_and(is_pos, can_use) # combine arrays with whether or not to use for the loss function y_class = np.concatenate([can_use, is_pos], axis=2) bbreg_can_use = np.repeat(selected_is_pos, 4, axis = 2) bbreg_targets = np.reshape(results['bbreg_targets'], (conv_rows, conv_cols, 4 * len(self.anchor_dims))) y_bbreg = np.concatenate([bbreg_can_use, bbreg_targets], axis = 2) y_class = np.expand_dims(y_class, axis=0) y_bbreg = np.expand_dims(y_bbreg, axis=0) return y_class, y_bbreg def _idx_to_conv(idx, conv_width, anchors_per_loc): """ Converts an anchor box index in a 1-d numpy array to its corresponding 3-d index representing its convolution position and anchor index. :param idx: non-negative integer, the position in a 1-d numpy array of anchors. :param conv_width: the number of possible horizontal positions the convolutional layer's filters can occupy, i.e. close to the width in pixels divided by the cumulative stride at that layer. :param anchors_per_loc: positive integer, the number of anchors at each convolutional filter position. :return: tuple of the row, column, and anchor index of the convolutional filter position for this index. """ divisor = conv_width * anchors_per_loc y, remainder = idx // divisor, idx % divisor x, anchor_idx = remainder // anchors_per_loc, remainder % anchors_per_loc return y, x, anchor_idx @profile def _get_conv_center(conv_x, conv_y, stride): """ Finds the center of this convolution position in the image's original coordinate space. :param conv_x: non-negative integer, x coordinate of the convolution position. :param conv_y: non-negative integer, y coordinate of the convolution position. :param stride: positive integer, the cumulative stride in pixels at this layer of the network. :return: tuple of positive integers, the x and y coordinates of the center of the convolution position. """ x_center = stride * (conv_x + 0.5) y_center = stride * (conv_y + 0.5) return int(x_center), int(y_center) @profile @profile @profile @profile # this function was a huge bottleneck so threw away box abstractions to optimize performance @profile def _get_all_anchor_coords(conv_rows, conv_cols, anchor_dims, stride): """ Given the shape of a convolutional layer and the anchors to generate for each position, return all anchors. :param conv_rows: positive integer, height of this convolutional layer. :param conv_cols: positive integer, width of this convolutional layer. :param anchor_dims: list of lists of positive integers, one height and width pair for each anchor. :param stride: positive integer, cumulative stride of this anchor position in pixels. :return: 2-d numpy array with one row for each anchor box containing its [x1, y1, x2, y2] coordinates. """ num_boxes = conv_rows * conv_cols * len(anchor_dims) y, x, anchor_idxs = _num_boxes_to_conv_np(num_boxes, conv_cols, len(anchor_dims)) x_center, y_center = _get_conv_center_np(x, y, stride) anchor_coords = np.zeros((num_boxes, 4), dtype=np.float32) anchor_height = anchor_dims[anchor_idxs, 0] anchor_width = anchor_dims[anchor_idxs, 1] anchor_coords[:, 0] = x_center - anchor_width // 2 anchor_coords[:, 1] = y_center - anchor_height // 2 anchor_coords[:, 2] = anchor_coords[:, 0] + anchor_width anchor_coords[:, 3] = anchor_coords[:, 1] + anchor_height return anchor_coords @profile @profile def _apply_sampling(is_pos, can_use): """ Applies the sampling logic described in the Faster R-CNN paper to determine which anchors should be evaluated in the loss function. :param is_pos: 1-d numpy array of booleans for whether each anchor is a true positive for some object. :param can_use: 1-d numpy array of booleans for whether each anchor can be used at all in the loss function. :return: 1-d numpy array of booleans of which anchors were chosen to be used in the loss function. """ # extract [0] due to np.where returning a tuple pos_locs = np.where(np.logical_and(is_pos == 1, can_use == 1))[0] neg_locs = np.where(np.logical_and(is_pos == 0, can_use == 1))[0] num_pos = len(pos_locs) num_neg = len(neg_locs) # cap the number of positive samples per batch to no more than half the batch size if num_pos > MAX_POS_SAMPLES: locs_off = random.sample(range(num_pos), num_pos - MAX_POS_SAMPLES) can_use[pos_locs[locs_off]] = 0 num_pos = MAX_POS_SAMPLES # fill remaining portion of the batch size with negative samples if num_neg + num_pos > SAMPLE_SIZE: locs_off = random.sample(range(num_neg), num_neg + num_pos - SAMPLE_SIZE) can_use[neg_locs[locs_off]] = 0 return can_use
[ 11748, 4738, 198, 6738, 33829, 1330, 2039, 388, 198, 198, 11748, 299, 32152, 355, 45941, 198, 198, 6738, 2183, 62, 12501, 273, 2024, 1330, 7034, 198, 6738, 15268, 1330, 8315, 198, 6738, 4888, 62, 9979, 1187, 1330, 12597, 31553, 62, 44, 16724, 4061, 31271, 4877, 11, 5550, 38865, 62, 1565, 3398, 20673, 198, 6738, 7736, 1330, 42302, 62, 72, 280, 11, 3272, 62, 699, 11, 651, 62, 2301, 62, 37266, 11, 651, 62, 65, 3524, 62, 1073, 3669, 198, 198, 37997, 62, 41983, 43, 2969, 796, 657, 13, 22, 198, 45, 7156, 62, 41983, 43, 2969, 796, 657, 13, 18, 198, 198, 49302, 16437, 62, 33489, 796, 17759, 198, 22921, 62, 37997, 62, 49302, 6489, 1546, 796, 13108, 628, 198, 198, 4871, 371, 21999, 44357, 13511, 25, 198, 220, 220, 220, 37227, 198, 220, 220, 220, 14711, 1686, 15968, 262, 3307, 286, 15453, 3047, 17311, 329, 257, 3814, 6961, 3127, 329, 257, 1813, 2939, 13, 198, 220, 220, 220, 37227, 628, 220, 220, 220, 825, 11593, 15003, 834, 7, 944, 11, 42302, 62, 42946, 62, 67, 12078, 11, 33769, 11, 662, 14681, 62, 20786, 11, 18021, 62, 67, 12078, 28, 7206, 38865, 62, 1565, 3398, 20673, 2599, 198, 220, 220, 220, 220, 220, 220, 220, 37227, 198, 220, 220, 220, 220, 220, 220, 220, 1058, 17143, 42302, 62, 42946, 62, 67, 12078, 25, 2163, 326, 18178, 257, 46545, 286, 262, 2939, 338, 6001, 290, 9647, 287, 17848, 290, 5860, 262, 198, 220, 220, 220, 220, 220, 220, 220, 6001, 290, 9647, 286, 262, 3063, 2122, 282, 7679, 3161, 284, 262, 374, 21999, 11685, 13, 198, 220, 220, 220, 220, 220, 220, 220, 1058, 17143, 33769, 25, 3967, 18253, 11, 262, 23818, 33769, 379, 262, 3063, 2122, 282, 7679, 3161, 284, 262, 374, 21999, 11685, 13, 198, 220, 220, 220, 220, 220, 220, 220, 1058, 17143, 662, 14681, 62, 20786, 25, 2163, 326, 8991, 262, 976, 13389, 284, 262, 2939, 338, 17848, 355, 973, 329, 1846, 11286, 316, 198, 220, 220, 220, 220, 220, 220, 220, 3047, 13, 15323, 262, 1846, 11286, 316, 662, 12, 35311, 19590, 481, 307, 32691, 14265, 13, 198, 220, 220, 220, 220, 220, 220, 220, 1058, 17143, 18021, 62, 67, 12078, 25, 1351, 286, 8341, 286, 3967, 37014, 11, 530, 6001, 290, 9647, 5166, 329, 1123, 18021, 13, 198, 220, 220, 220, 220, 220, 220, 220, 37227, 198, 220, 220, 220, 220, 220, 220, 220, 2116, 13557, 23870, 796, 23884, 198, 220, 220, 220, 220, 220, 220, 220, 2116, 13, 9948, 66, 62, 42946, 62, 67, 12078, 796, 42302, 62, 42946, 62, 67, 12078, 198, 220, 220, 220, 220, 220, 220, 220, 2116, 13, 2536, 485, 796, 33769, 198, 220, 220, 220, 220, 220, 220, 220, 2116, 13, 3866, 14681, 62, 20786, 796, 662, 14681, 62, 20786, 198, 220, 220, 220, 220, 220, 220, 220, 2116, 13, 3702, 273, 62, 67, 12078, 796, 18021, 62, 67, 12078, 628, 220, 220, 220, 2488, 13317, 198, 220, 220, 220, 825, 7365, 1740, 62, 9060, 7, 944, 11, 2939, 2599, 198, 220, 220, 220, 220, 220, 220, 220, 37227, 198, 220, 220, 220, 220, 220, 220, 220, 16409, 262, 2939, 1366, 284, 307, 11672, 656, 262, 3127, 13, 198, 220, 220, 220, 220, 220, 220, 220, 1058, 17143, 2939, 25, 15268, 13, 5159, 2134, 13, 198, 220, 220, 220, 220, 220, 220, 220, 1058, 7783, 25, 604, 12, 67, 299, 32152, 7177, 351, 257, 2060, 15458, 286, 262, 2939, 11, 815, 460, 307, 973, 355, 257, 17337, 292, 2746, 5128, 13, 198, 220, 220, 220, 220, 220, 220, 220, 37227, 198, 220, 220, 220, 220, 220, 220, 220, 1441, 45941, 13, 11201, 392, 62, 67, 12078, 7, 944, 13, 3866, 14681, 62, 20786, 7, 9060, 13, 7890, 828, 16488, 28, 15, 8, 628, 220, 220, 220, 2488, 13317, 628, 220, 220, 220, 2488, 13317, 198, 220, 220, 220, 825, 374, 21999, 62, 88, 62, 7942, 7, 944, 11, 2939, 2599, 198, 220, 220, 220, 220, 220, 220, 220, 37227, 198, 220, 220, 220, 220, 220, 220, 220, 33687, 281, 2939, 290, 5860, 262, 17337, 292, 2746, 17311, 284, 4512, 351, 13, 198, 220, 220, 220, 220, 220, 220, 220, 1058, 17143, 2939, 25, 15268, 13, 5159, 2134, 284, 7716, 3047, 17311, 329, 13, 198, 220, 220, 220, 220, 220, 220, 220, 1058, 7783, 25, 46545, 810, 262, 717, 5002, 318, 257, 299, 32152, 7177, 286, 262, 2323, 3872, 3127, 5072, 329, 1771, 1123, 198, 220, 220, 220, 220, 220, 220, 220, 18021, 12893, 1686, 351, 281, 2134, 11, 290, 262, 1218, 5002, 318, 257, 299, 32152, 7177, 286, 262, 2323, 3872, 3127, 5072, 329, 262, 198, 220, 220, 220, 220, 220, 220, 220, 5421, 278, 3091, 13389, 10007, 284, 6121, 1123, 18021, 656, 281, 2134, 338, 5421, 278, 3091, 13, 198, 220, 220, 220, 220, 220, 220, 220, 37227, 198, 220, 220, 220, 220, 220, 220, 220, 705, 7061, 198, 220, 220, 220, 220, 220, 220, 220, 12642, 10829, 40918, 532, 2087, 618, 2116, 13, 14681, 373, 2263, 657, 13, 19, 82, 284, 1057, 13, 4619, 788, 11, 23392, 340, 866, 284, 198, 220, 220, 220, 220, 220, 220, 220, 657, 13, 2999, 82, 15726, 11, 657, 13, 11245, 82, 319, 3253, 82, 523, 262, 12940, 2125, 470, 1165, 4465, 7471, 13, 198, 220, 220, 220, 220, 220, 220, 220, 705, 7061, 198, 220, 220, 220, 220, 220, 220, 220, 611, 2939, 13, 23870, 62, 2539, 407, 287, 2116, 13557, 23870, 25, 198, 220, 220, 220, 220, 220, 220, 220, 220, 220, 220, 220, 2116, 13557, 14681, 7, 9060, 8, 628, 220, 220, 220, 220, 220, 220, 220, 2482, 796, 2116, 13557, 23870, 58, 9060, 13, 23870, 62, 2539, 60, 198, 220, 220, 220, 220, 220, 220, 220, 1303, 16926, 46, 25, 1521, 318, 262, 39986, 1255, 852, 13140, 30, 7488, 10055, 1771, 25646, 340, 19575, 3047, 640, 13, 198, 220, 220, 220, 220, 220, 220, 220, 1619, 2116, 13557, 23870, 58, 9060, 13, 23870, 62, 2539, 60, 198, 220, 220, 220, 220, 220, 220, 220, 460, 62, 1904, 796, 4808, 39014, 62, 37687, 11347, 7, 43420, 17816, 271, 62, 1930, 6, 4357, 2482, 17816, 5171, 62, 1904, 6, 12962, 198, 220, 220, 220, 220, 220, 220, 220, 3063, 62, 8516, 11, 3063, 62, 4033, 82, 796, 2116, 13, 9948, 66, 62, 42946, 62, 67, 12078, 7, 9060, 13, 17015, 11, 2939, 13, 10394, 8, 628, 220, 220, 220, 220, 220, 220, 220, 318, 62, 1930, 796, 45941, 13, 3447, 1758, 7, 43420, 17816, 271, 62, 1930, 6, 4357, 357, 42946, 62, 8516, 11, 3063, 62, 4033, 82, 11, 18896, 7, 944, 13, 3702, 273, 62, 67, 12078, 22305, 198, 220, 220, 220, 220, 220, 220, 220, 460, 62, 1904, 796, 45941, 13, 3447, 1758, 7, 5171, 62, 1904, 11, 357, 42946, 62, 8516, 11, 3063, 62, 4033, 82, 11, 18896, 7, 944, 13, 3702, 273, 62, 67, 12078, 22305, 198, 220, 220, 220, 220, 220, 220, 220, 6163, 62, 271, 62, 1930, 796, 45941, 13, 6404, 605, 62, 392, 7, 271, 62, 1930, 11, 460, 62, 1904, 8, 628, 220, 220, 220, 220, 220, 220, 220, 1303, 12082, 26515, 351, 1771, 393, 407, 284, 779, 329, 262, 2994, 2163, 198, 220, 220, 220, 220, 220, 220, 220, 331, 62, 4871, 796, 45941, 13, 1102, 9246, 268, 378, 26933, 5171, 62, 1904, 11, 318, 62, 1930, 4357, 16488, 28, 17, 8, 198, 220, 220, 220, 220, 220, 220, 220, 275, 65, 2301, 62, 5171, 62, 1904, 796, 45941, 13, 44754, 7, 34213, 62, 271, 62, 1930, 11, 604, 11, 16488, 796, 362, 8, 198, 220, 220, 220, 220, 220, 220, 220, 275, 65, 2301, 62, 83, 853, 1039, 796, 45941, 13, 3447, 1758, 7, 43420, 17816, 11848, 2301, 62, 83, 853, 1039, 6, 4357, 357, 42946, 62, 8516, 11, 3063, 62, 4033, 82, 11, 604, 1635, 18896, 7, 944, 13, 3702, 273, 62, 67, 12078, 22305, 198, 220, 220, 220, 220, 220, 220, 220, 331, 62, 11848, 2301, 796, 45941, 13, 1102, 9246, 268, 378, 26933, 11848, 2301, 62, 5171, 62, 1904, 11, 275, 65, 2301, 62, 83, 853, 1039, 4357, 16488, 796, 362, 8, 628, 220, 220, 220, 220, 220, 220, 220, 331, 62, 4871, 796, 45941, 13, 11201, 392, 62, 67, 12078, 7, 88, 62, 4871, 11, 16488, 28, 15, 8, 198, 220, 220, 220, 220, 220, 220, 220, 331, 62, 11848, 2301, 796, 45941, 13, 11201, 392, 62, 67, 12078, 7, 88, 62, 11848, 2301, 11, 16488, 28, 15, 8, 628, 220, 220, 220, 220, 220, 220, 220, 1441, 331, 62, 4871, 11, 331, 62, 11848, 2301, 628, 198, 4299, 4808, 312, 87, 62, 1462, 62, 42946, 7, 312, 87, 11, 3063, 62, 10394, 11, 43360, 62, 525, 62, 17946, 2599, 198, 220, 220, 220, 37227, 198, 220, 220, 220, 1482, 24040, 281, 18021, 3091, 6376, 287, 257, 352, 12, 67, 299, 32152, 7177, 284, 663, 11188, 513, 12, 67, 6376, 10200, 663, 3063, 2122, 198, 220, 220, 220, 2292, 290, 18021, 6376, 13, 198, 220, 220, 220, 1058, 17143, 4686, 87, 25, 1729, 12, 31591, 18253, 11, 262, 2292, 287, 257, 352, 12, 67, 299, 32152, 7177, 286, 43360, 13, 198, 220, 220, 220, 1058, 17143, 3063, 62, 10394, 25, 262, 1271, 286, 1744, 16021, 6116, 262, 3063, 2122, 282, 7679, 338, 16628, 460, 22265, 11, 1312, 13, 68, 13, 198, 220, 220, 220, 1969, 284, 262, 9647, 287, 17848, 9086, 416, 262, 23818, 33769, 379, 326, 7679, 13, 198, 220, 220, 220, 1058, 17143, 43360, 62, 525, 62, 17946, 25, 3967, 18253, 11, 262, 1271, 286, 43360, 379, 1123, 3063, 2122, 282, 8106, 2292, 13, 198, 220, 220, 220, 1058, 7783, 25, 46545, 286, 262, 5752, 11, 5721, 11, 290, 18021, 6376, 286, 262, 3063, 2122, 282, 8106, 2292, 329, 428, 6376, 13, 198, 220, 220, 220, 37227, 198, 220, 220, 220, 2659, 271, 273, 796, 3063, 62, 10394, 1635, 43360, 62, 525, 62, 17946, 198, 220, 220, 220, 331, 11, 17675, 796, 4686, 87, 3373, 2659, 271, 273, 11, 4686, 87, 4064, 2659, 271, 273, 198, 220, 220, 220, 2124, 11, 18021, 62, 312, 87, 796, 17675, 3373, 43360, 62, 525, 62, 17946, 11, 17675, 4064, 43360, 62, 525, 62, 17946, 198, 220, 220, 220, 1441, 331, 11, 2124, 11, 18021, 62, 312, 87, 628, 198, 31, 13317, 628, 198, 4299, 4808, 1136, 62, 42946, 62, 16159, 7, 42946, 62, 87, 11, 3063, 62, 88, 11, 33769, 2599, 198, 220, 220, 220, 37227, 198, 220, 220, 220, 9938, 82, 262, 3641, 286, 428, 3063, 2122, 2292, 287, 262, 2939, 338, 2656, 20435, 2272, 13, 198, 220, 220, 220, 1058, 17143, 3063, 62, 87, 25, 1729, 12, 31591, 18253, 11, 2124, 20435, 286, 262, 3063, 2122, 2292, 13, 198, 220, 220, 220, 1058, 17143, 3063, 62, 88, 25, 1729, 12, 31591, 18253, 11, 331, 20435, 286, 262, 3063, 2122, 2292, 13, 198, 220, 220, 220, 1058, 17143, 33769, 25, 3967, 18253, 11, 262, 23818, 33769, 287, 17848, 379, 428, 7679, 286, 262, 3127, 13, 198, 220, 220, 220, 1058, 7783, 25, 46545, 286, 3967, 37014, 11, 262, 2124, 290, 331, 22715, 286, 262, 3641, 286, 262, 3063, 2122, 2292, 13, 198, 220, 220, 220, 37227, 198, 220, 220, 220, 2124, 62, 16159, 796, 33769, 1635, 357, 42946, 62, 87, 1343, 657, 13, 20, 8, 198, 220, 220, 220, 331, 62, 16159, 796, 33769, 1635, 357, 42946, 62, 88, 1343, 657, 13, 20, 8, 628, 220, 220, 220, 1441, 493, 7, 87, 62, 16159, 828, 493, 7, 88, 62, 16159, 8, 628, 198, 31, 13317, 628, 198, 31, 13317, 628, 198, 31, 13317, 628, 198, 31, 13317, 198, 2, 428, 2163, 373, 257, 3236, 49936, 523, 9617, 1497, 3091, 12531, 507, 284, 27183, 2854, 628, 198, 31, 13317, 198, 4299, 4808, 1136, 62, 439, 62, 3702, 273, 62, 1073, 3669, 7, 42946, 62, 8516, 11, 3063, 62, 4033, 82, 11, 18021, 62, 67, 12078, 11, 33769, 2599, 198, 220, 220, 220, 37227, 198, 220, 220, 220, 11259, 262, 5485, 286, 257, 3063, 2122, 282, 7679, 290, 262, 43360, 284, 7716, 329, 1123, 2292, 11, 1441, 477, 43360, 13, 198, 220, 220, 220, 1058, 17143, 3063, 62, 8516, 25, 3967, 18253, 11, 6001, 286, 428, 3063, 2122, 282, 7679, 13, 198, 220, 220, 220, 1058, 17143, 3063, 62, 4033, 82, 25, 3967, 18253, 11, 9647, 286, 428, 3063, 2122, 282, 7679, 13, 198, 220, 220, 220, 1058, 17143, 18021, 62, 67, 12078, 25, 1351, 286, 8341, 286, 3967, 37014, 11, 530, 6001, 290, 9647, 5166, 329, 1123, 18021, 13, 198, 220, 220, 220, 1058, 17143, 33769, 25, 3967, 18253, 11, 23818, 33769, 286, 428, 18021, 2292, 287, 17848, 13, 198, 220, 220, 220, 1058, 7783, 25, 362, 12, 67, 299, 32152, 7177, 351, 530, 5752, 329, 1123, 18021, 3091, 7268, 663, 685, 87, 16, 11, 331, 16, 11, 2124, 17, 11, 331, 17, 60, 22715, 13, 198, 220, 220, 220, 37227, 198, 220, 220, 220, 997, 62, 29305, 796, 3063, 62, 8516, 1635, 3063, 62, 4033, 82, 1635, 18896, 7, 3702, 273, 62, 67, 12078, 8, 628, 220, 220, 220, 331, 11, 2124, 11, 18021, 62, 312, 34223, 796, 4808, 22510, 62, 29305, 62, 1462, 62, 42946, 62, 37659, 7, 22510, 62, 29305, 11, 3063, 62, 4033, 82, 11, 18896, 7, 3702, 273, 62, 67, 12078, 4008, 198, 220, 220, 220, 2124, 62, 16159, 11, 331, 62, 16159, 796, 4808, 1136, 62, 42946, 62, 16159, 62, 37659, 7, 87, 11, 331, 11, 33769, 8, 198, 220, 220, 220, 18021, 62, 1073, 3669, 796, 45941, 13, 9107, 418, 19510, 22510, 62, 29305, 11, 604, 828, 288, 4906, 28, 37659, 13, 22468, 2624, 8, 198, 220, 220, 220, 18021, 62, 17015, 796, 18021, 62, 67, 12078, 58, 3702, 273, 62, 312, 34223, 11, 657, 60, 198, 220, 220, 220, 18021, 62, 10394, 796, 18021, 62, 67, 12078, 58, 3702, 273, 62, 312, 34223, 11, 352, 60, 628, 220, 220, 220, 18021, 62, 1073, 3669, 58, 45299, 657, 60, 796, 2124, 62, 16159, 532, 18021, 62, 10394, 3373, 362, 198, 220, 220, 220, 18021, 62, 1073, 3669, 58, 45299, 352, 60, 796, 331, 62, 16159, 532, 18021, 62, 17015, 3373, 362, 198, 220, 220, 220, 18021, 62, 1073, 3669, 58, 45299, 362, 60, 796, 18021, 62, 1073, 3669, 58, 45299, 657, 60, 1343, 18021, 62, 10394, 198, 220, 220, 220, 18021, 62, 1073, 3669, 58, 45299, 513, 60, 796, 18021, 62, 1073, 3669, 58, 45299, 352, 60, 1343, 18021, 62, 17015, 628, 220, 220, 220, 1441, 18021, 62, 1073, 3669, 628, 198, 31, 13317, 628, 628, 198, 31, 13317, 198, 4299, 4808, 39014, 62, 37687, 11347, 7, 271, 62, 1930, 11, 460, 62, 1904, 2599, 198, 220, 220, 220, 37227, 198, 220, 220, 220, 2034, 13508, 262, 19232, 9156, 3417, 287, 262, 38996, 371, 12, 18474, 3348, 284, 5004, 543, 43360, 815, 307, 16726, 287, 262, 198, 220, 220, 220, 2994, 2163, 13, 198, 220, 220, 220, 1058, 17143, 318, 62, 1930, 25, 352, 12, 67, 299, 32152, 7177, 286, 1489, 2305, 504, 329, 1771, 1123, 18021, 318, 257, 2081, 3967, 329, 617, 2134, 13, 198, 220, 220, 220, 1058, 17143, 460, 62, 1904, 25, 352, 12, 67, 299, 32152, 7177, 286, 1489, 2305, 504, 329, 1771, 1123, 18021, 460, 307, 973, 379, 477, 287, 262, 2994, 2163, 13, 198, 220, 220, 220, 1058, 7783, 25, 352, 12, 67, 299, 32152, 7177, 286, 1489, 2305, 504, 286, 543, 43360, 547, 7147, 284, 307, 973, 287, 262, 2994, 2163, 13, 198, 220, 220, 220, 37227, 198, 220, 220, 220, 1303, 7925, 685, 15, 60, 2233, 284, 45941, 13, 3003, 8024, 257, 46545, 198, 220, 220, 220, 1426, 62, 17946, 82, 796, 45941, 13, 3003, 7, 37659, 13, 6404, 605, 62, 392, 7, 271, 62, 1930, 6624, 352, 11, 460, 62, 1904, 6624, 352, 4008, 58, 15, 60, 198, 220, 220, 220, 2469, 62, 17946, 82, 796, 45941, 13, 3003, 7, 37659, 13, 6404, 605, 62, 392, 7, 271, 62, 1930, 6624, 657, 11, 460, 62, 1904, 6624, 352, 4008, 58, 15, 60, 628, 220, 220, 220, 997, 62, 1930, 796, 18896, 7, 1930, 62, 17946, 82, 8, 198, 220, 220, 220, 997, 62, 12480, 796, 18896, 7, 12480, 62, 17946, 82, 8, 628, 220, 220, 220, 1303, 1451, 262, 1271, 286, 3967, 8405, 583, 15458, 284, 645, 517, 621, 2063, 262, 15458, 2546, 198, 220, 220, 220, 611, 997, 62, 1930, 1875, 25882, 62, 37997, 62, 49302, 6489, 1546, 25, 198, 220, 220, 220, 220, 220, 220, 220, 1179, 82, 62, 2364, 796, 4738, 13, 39873, 7, 9521, 7, 22510, 62, 1930, 828, 997, 62, 1930, 532, 25882, 62, 37997, 62, 49302, 6489, 1546, 8, 198, 220, 220, 220, 220, 220, 220, 220, 460, 62, 1904, 58, 1930, 62, 17946, 82, 58, 17946, 82, 62, 2364, 11907, 796, 657, 198, 220, 220, 220, 220, 220, 220, 220, 997, 62, 1930, 796, 25882, 62, 37997, 62, 49302, 6489, 1546, 628, 220, 220, 220, 1303, 6070, 5637, 6903, 286, 262, 15458, 2546, 351, 4633, 8405, 198, 220, 220, 220, 611, 997, 62, 12480, 1343, 997, 62, 1930, 1875, 28844, 16437, 62, 33489, 25, 198, 220, 220, 220, 220, 220, 220, 220, 1179, 82, 62, 2364, 796, 4738, 13, 39873, 7, 9521, 7, 22510, 62, 12480, 828, 997, 62, 12480, 1343, 997, 62, 1930, 532, 28844, 16437, 62, 33489, 8, 198, 220, 220, 220, 220, 220, 220, 220, 460, 62, 1904, 58, 12480, 62, 17946, 82, 58, 17946, 82, 62, 2364, 11907, 796, 657, 628, 220, 220, 220, 1441, 460, 62, 1904, 198 ]
2.777241
2,900
# coding: utf-8 """ OpenAPI Petstore This spec is mainly for testing Petstore server and contains fake endpoints, models. Please do not use this for any other purpose. Special characters: \" \\ # noqa: E501 The version of the OpenAPI document: 1.0.0 Generated by: https://openapi-generator.tech """ import pprint # noqa: F401 import re # noqa: F401 import six # noqa: F401 from petstore_api.exceptions import ( # noqa: F401 ApiKeyError, ApiTypeError, ApiValueError, ) from petstore_api.model_utils import ( # noqa: F401 ModelNormal, ModelSimple, check_allowed_values, check_validations, date, datetime, file_type, get_simple_class, int, model_to_dict, none_type, str, type_error_message, validate_and_convert_types ) class XmlItem(ModelNormal): """NOTE: This class is auto generated by OpenAPI Generator. Ref: https://openapi-generator.tech Do not edit the class manually. Attributes: allowed_values (dict): The key is the tuple path to the attribute and the for var_name this is (var_name,). The value is a dict with a capitalized key describing the allowed value and an allowed value. These dicts store the allowed enum values. attribute_map (dict): The key is attribute name and the value is json key in definition. discriminator_value_class_map (dict): A dict to go from the discriminator variable value to the discriminator class name. openapi_types (dict): The key is attribute name and the value is attribute type. validations (dict): The key is the tuple path to the attribute and the for var_name this is (var_name,). The value is a dict that stores validations for max_length, min_length, max_items, min_items, exclusive_maximum, inclusive_maximum, exclusive_minimum, inclusive_minimum, and regex. additional_properties_type (tuple): A tuple of classes accepted as additional properties values. """ allowed_values = { } attribute_map = { 'attribute_string': 'attribute_string', # noqa: E501 'attribute_number': 'attribute_number', # noqa: E501 'attribute_integer': 'attribute_integer', # noqa: E501 'attribute_boolean': 'attribute_boolean', # noqa: E501 'wrapped_array': 'wrapped_array', # noqa: E501 'name_string': 'name_string', # noqa: E501 'name_number': 'name_number', # noqa: E501 'name_integer': 'name_integer', # noqa: E501 'name_boolean': 'name_boolean', # noqa: E501 'name_array': 'name_array', # noqa: E501 'name_wrapped_array': 'name_wrapped_array', # noqa: E501 'prefix_string': 'prefix_string', # noqa: E501 'prefix_number': 'prefix_number', # noqa: E501 'prefix_integer': 'prefix_integer', # noqa: E501 'prefix_boolean': 'prefix_boolean', # noqa: E501 'prefix_array': 'prefix_array', # noqa: E501 'prefix_wrapped_array': 'prefix_wrapped_array', # noqa: E501 'namespace_string': 'namespace_string', # noqa: E501 'namespace_number': 'namespace_number', # noqa: E501 'namespace_integer': 'namespace_integer', # noqa: E501 'namespace_boolean': 'namespace_boolean', # noqa: E501 'namespace_array': 'namespace_array', # noqa: E501 'namespace_wrapped_array': 'namespace_wrapped_array', # noqa: E501 'prefix_ns_string': 'prefix_ns_string', # noqa: E501 'prefix_ns_number': 'prefix_ns_number', # noqa: E501 'prefix_ns_integer': 'prefix_ns_integer', # noqa: E501 'prefix_ns_boolean': 'prefix_ns_boolean', # noqa: E501 'prefix_ns_array': 'prefix_ns_array', # noqa: E501 'prefix_ns_wrapped_array': 'prefix_ns_wrapped_array' # noqa: E501 } openapi_types = { 'attribute_string': (str,), # noqa: E501 'attribute_number': (float,), # noqa: E501 'attribute_integer': (int,), # noqa: E501 'attribute_boolean': (bool,), # noqa: E501 'wrapped_array': ([int],), # noqa: E501 'name_string': (str,), # noqa: E501 'name_number': (float,), # noqa: E501 'name_integer': (int,), # noqa: E501 'name_boolean': (bool,), # noqa: E501 'name_array': ([int],), # noqa: E501 'name_wrapped_array': ([int],), # noqa: E501 'prefix_string': (str,), # noqa: E501 'prefix_number': (float,), # noqa: E501 'prefix_integer': (int,), # noqa: E501 'prefix_boolean': (bool,), # noqa: E501 'prefix_array': ([int],), # noqa: E501 'prefix_wrapped_array': ([int],), # noqa: E501 'namespace_string': (str,), # noqa: E501 'namespace_number': (float,), # noqa: E501 'namespace_integer': (int,), # noqa: E501 'namespace_boolean': (bool,), # noqa: E501 'namespace_array': ([int],), # noqa: E501 'namespace_wrapped_array': ([int],), # noqa: E501 'prefix_ns_string': (str,), # noqa: E501 'prefix_ns_number': (float,), # noqa: E501 'prefix_ns_integer': (int,), # noqa: E501 'prefix_ns_boolean': (bool,), # noqa: E501 'prefix_ns_array': ([int],), # noqa: E501 'prefix_ns_wrapped_array': ([int],), # noqa: E501 } validations = { } additional_properties_type = None discriminator = None def __init__(self, _check_type=True, _from_server=False, _path_to_item=(), _configuration=None, **kwargs): # noqa: E501 """XmlItem - a model defined in OpenAPI Keyword Args: _check_type (bool): if True, values for parameters in openapi_types will be type checked and a TypeError will be raised if the wrong type is input. Defaults to True _path_to_item (tuple/list): This is a list of keys or values to drill down to the model in received_data when deserializing a response _from_server (bool): True if the data is from the server False if the data is from the client (default) _configuration (Configuration): the instance to use when deserializing a file_type parameter. If passed, type conversion is attempted If omitted no type conversion is done. attribute_string (str): [optional] # noqa: E501 attribute_number (float): [optional] # noqa: E501 attribute_integer (int): [optional] # noqa: E501 attribute_boolean (bool): [optional] # noqa: E501 wrapped_array ([int]): [optional] # noqa: E501 name_string (str): [optional] # noqa: E501 name_number (float): [optional] # noqa: E501 name_integer (int): [optional] # noqa: E501 name_boolean (bool): [optional] # noqa: E501 name_array ([int]): [optional] # noqa: E501 name_wrapped_array ([int]): [optional] # noqa: E501 prefix_string (str): [optional] # noqa: E501 prefix_number (float): [optional] # noqa: E501 prefix_integer (int): [optional] # noqa: E501 prefix_boolean (bool): [optional] # noqa: E501 prefix_array ([int]): [optional] # noqa: E501 prefix_wrapped_array ([int]): [optional] # noqa: E501 namespace_string (str): [optional] # noqa: E501 namespace_number (float): [optional] # noqa: E501 namespace_integer (int): [optional] # noqa: E501 namespace_boolean (bool): [optional] # noqa: E501 namespace_array ([int]): [optional] # noqa: E501 namespace_wrapped_array ([int]): [optional] # noqa: E501 prefix_ns_string (str): [optional] # noqa: E501 prefix_ns_number (float): [optional] # noqa: E501 prefix_ns_integer (int): [optional] # noqa: E501 prefix_ns_boolean (bool): [optional] # noqa: E501 prefix_ns_array ([int]): [optional] # noqa: E501 prefix_ns_wrapped_array ([int]): [optional] # noqa: E501 """ self._data_store = {} self._check_type = _check_type self._from_server = _from_server self._path_to_item = _path_to_item self._configuration = _configuration for var_name, var_value in six.iteritems(kwargs): self.__set_item(var_name, var_value) def __setitem__(self, name, value): """this allows us to set values with instance[field_name] = val""" self.__set_item(name, value) def __getitem__(self, name): """this allows us to get a value with val = instance[field_name]""" return self.__get_item(name) @property def attribute_string(self): """Gets the attribute_string of this XmlItem. # noqa: E501 Returns: (str): The attribute_string of this XmlItem. # noqa: E501 """ return self.__get_item('attribute_string') @attribute_string.setter def attribute_string(self, value): """Sets the attribute_string of this XmlItem. # noqa: E501 """ return self.__set_item('attribute_string', value) @property def attribute_number(self): """Gets the attribute_number of this XmlItem. # noqa: E501 Returns: (float): The attribute_number of this XmlItem. # noqa: E501 """ return self.__get_item('attribute_number') @attribute_number.setter def attribute_number(self, value): """Sets the attribute_number of this XmlItem. # noqa: E501 """ return self.__set_item('attribute_number', value) @property def attribute_integer(self): """Gets the attribute_integer of this XmlItem. # noqa: E501 Returns: (int): The attribute_integer of this XmlItem. # noqa: E501 """ return self.__get_item('attribute_integer') @attribute_integer.setter def attribute_integer(self, value): """Sets the attribute_integer of this XmlItem. # noqa: E501 """ return self.__set_item('attribute_integer', value) @property def attribute_boolean(self): """Gets the attribute_boolean of this XmlItem. # noqa: E501 Returns: (bool): The attribute_boolean of this XmlItem. # noqa: E501 """ return self.__get_item('attribute_boolean') @attribute_boolean.setter def attribute_boolean(self, value): """Sets the attribute_boolean of this XmlItem. # noqa: E501 """ return self.__set_item('attribute_boolean', value) @property def wrapped_array(self): """Gets the wrapped_array of this XmlItem. # noqa: E501 Returns: ([int]): The wrapped_array of this XmlItem. # noqa: E501 """ return self.__get_item('wrapped_array') @wrapped_array.setter def wrapped_array(self, value): """Sets the wrapped_array of this XmlItem. # noqa: E501 """ return self.__set_item('wrapped_array', value) @property def name_string(self): """Gets the name_string of this XmlItem. # noqa: E501 Returns: (str): The name_string of this XmlItem. # noqa: E501 """ return self.__get_item('name_string') @name_string.setter def name_string(self, value): """Sets the name_string of this XmlItem. # noqa: E501 """ return self.__set_item('name_string', value) @property def name_number(self): """Gets the name_number of this XmlItem. # noqa: E501 Returns: (float): The name_number of this XmlItem. # noqa: E501 """ return self.__get_item('name_number') @name_number.setter def name_number(self, value): """Sets the name_number of this XmlItem. # noqa: E501 """ return self.__set_item('name_number', value) @property def name_integer(self): """Gets the name_integer of this XmlItem. # noqa: E501 Returns: (int): The name_integer of this XmlItem. # noqa: E501 """ return self.__get_item('name_integer') @name_integer.setter def name_integer(self, value): """Sets the name_integer of this XmlItem. # noqa: E501 """ return self.__set_item('name_integer', value) @property def name_boolean(self): """Gets the name_boolean of this XmlItem. # noqa: E501 Returns: (bool): The name_boolean of this XmlItem. # noqa: E501 """ return self.__get_item('name_boolean') @name_boolean.setter def name_boolean(self, value): """Sets the name_boolean of this XmlItem. # noqa: E501 """ return self.__set_item('name_boolean', value) @property def name_array(self): """Gets the name_array of this XmlItem. # noqa: E501 Returns: ([int]): The name_array of this XmlItem. # noqa: E501 """ return self.__get_item('name_array') @name_array.setter def name_array(self, value): """Sets the name_array of this XmlItem. # noqa: E501 """ return self.__set_item('name_array', value) @property def name_wrapped_array(self): """Gets the name_wrapped_array of this XmlItem. # noqa: E501 Returns: ([int]): The name_wrapped_array of this XmlItem. # noqa: E501 """ return self.__get_item('name_wrapped_array') @name_wrapped_array.setter def name_wrapped_array(self, value): """Sets the name_wrapped_array of this XmlItem. # noqa: E501 """ return self.__set_item('name_wrapped_array', value) @property def prefix_string(self): """Gets the prefix_string of this XmlItem. # noqa: E501 Returns: (str): The prefix_string of this XmlItem. # noqa: E501 """ return self.__get_item('prefix_string') @prefix_string.setter def prefix_string(self, value): """Sets the prefix_string of this XmlItem. # noqa: E501 """ return self.__set_item('prefix_string', value) @property def prefix_number(self): """Gets the prefix_number of this XmlItem. # noqa: E501 Returns: (float): The prefix_number of this XmlItem. # noqa: E501 """ return self.__get_item('prefix_number') @prefix_number.setter def prefix_number(self, value): """Sets the prefix_number of this XmlItem. # noqa: E501 """ return self.__set_item('prefix_number', value) @property def prefix_integer(self): """Gets the prefix_integer of this XmlItem. # noqa: E501 Returns: (int): The prefix_integer of this XmlItem. # noqa: E501 """ return self.__get_item('prefix_integer') @prefix_integer.setter def prefix_integer(self, value): """Sets the prefix_integer of this XmlItem. # noqa: E501 """ return self.__set_item('prefix_integer', value) @property def prefix_boolean(self): """Gets the prefix_boolean of this XmlItem. # noqa: E501 Returns: (bool): The prefix_boolean of this XmlItem. # noqa: E501 """ return self.__get_item('prefix_boolean') @prefix_boolean.setter def prefix_boolean(self, value): """Sets the prefix_boolean of this XmlItem. # noqa: E501 """ return self.__set_item('prefix_boolean', value) @property def prefix_array(self): """Gets the prefix_array of this XmlItem. # noqa: E501 Returns: ([int]): The prefix_array of this XmlItem. # noqa: E501 """ return self.__get_item('prefix_array') @prefix_array.setter def prefix_array(self, value): """Sets the prefix_array of this XmlItem. # noqa: E501 """ return self.__set_item('prefix_array', value) @property def prefix_wrapped_array(self): """Gets the prefix_wrapped_array of this XmlItem. # noqa: E501 Returns: ([int]): The prefix_wrapped_array of this XmlItem. # noqa: E501 """ return self.__get_item('prefix_wrapped_array') @prefix_wrapped_array.setter def prefix_wrapped_array(self, value): """Sets the prefix_wrapped_array of this XmlItem. # noqa: E501 """ return self.__set_item('prefix_wrapped_array', value) @property def namespace_string(self): """Gets the namespace_string of this XmlItem. # noqa: E501 Returns: (str): The namespace_string of this XmlItem. # noqa: E501 """ return self.__get_item('namespace_string') @namespace_string.setter def namespace_string(self, value): """Sets the namespace_string of this XmlItem. # noqa: E501 """ return self.__set_item('namespace_string', value) @property def namespace_number(self): """Gets the namespace_number of this XmlItem. # noqa: E501 Returns: (float): The namespace_number of this XmlItem. # noqa: E501 """ return self.__get_item('namespace_number') @namespace_number.setter def namespace_number(self, value): """Sets the namespace_number of this XmlItem. # noqa: E501 """ return self.__set_item('namespace_number', value) @property def namespace_integer(self): """Gets the namespace_integer of this XmlItem. # noqa: E501 Returns: (int): The namespace_integer of this XmlItem. # noqa: E501 """ return self.__get_item('namespace_integer') @namespace_integer.setter def namespace_integer(self, value): """Sets the namespace_integer of this XmlItem. # noqa: E501 """ return self.__set_item('namespace_integer', value) @property def namespace_boolean(self): """Gets the namespace_boolean of this XmlItem. # noqa: E501 Returns: (bool): The namespace_boolean of this XmlItem. # noqa: E501 """ return self.__get_item('namespace_boolean') @namespace_boolean.setter def namespace_boolean(self, value): """Sets the namespace_boolean of this XmlItem. # noqa: E501 """ return self.__set_item('namespace_boolean', value) @property def namespace_array(self): """Gets the namespace_array of this XmlItem. # noqa: E501 Returns: ([int]): The namespace_array of this XmlItem. # noqa: E501 """ return self.__get_item('namespace_array') @namespace_array.setter def namespace_array(self, value): """Sets the namespace_array of this XmlItem. # noqa: E501 """ return self.__set_item('namespace_array', value) @property def namespace_wrapped_array(self): """Gets the namespace_wrapped_array of this XmlItem. # noqa: E501 Returns: ([int]): The namespace_wrapped_array of this XmlItem. # noqa: E501 """ return self.__get_item('namespace_wrapped_array') @namespace_wrapped_array.setter def namespace_wrapped_array(self, value): """Sets the namespace_wrapped_array of this XmlItem. # noqa: E501 """ return self.__set_item('namespace_wrapped_array', value) @property def prefix_ns_string(self): """Gets the prefix_ns_string of this XmlItem. # noqa: E501 Returns: (str): The prefix_ns_string of this XmlItem. # noqa: E501 """ return self.__get_item('prefix_ns_string') @prefix_ns_string.setter def prefix_ns_string(self, value): """Sets the prefix_ns_string of this XmlItem. # noqa: E501 """ return self.__set_item('prefix_ns_string', value) @property def prefix_ns_number(self): """Gets the prefix_ns_number of this XmlItem. # noqa: E501 Returns: (float): The prefix_ns_number of this XmlItem. # noqa: E501 """ return self.__get_item('prefix_ns_number') @prefix_ns_number.setter def prefix_ns_number(self, value): """Sets the prefix_ns_number of this XmlItem. # noqa: E501 """ return self.__set_item('prefix_ns_number', value) @property def prefix_ns_integer(self): """Gets the prefix_ns_integer of this XmlItem. # noqa: E501 Returns: (int): The prefix_ns_integer of this XmlItem. # noqa: E501 """ return self.__get_item('prefix_ns_integer') @prefix_ns_integer.setter def prefix_ns_integer(self, value): """Sets the prefix_ns_integer of this XmlItem. # noqa: E501 """ return self.__set_item('prefix_ns_integer', value) @property def prefix_ns_boolean(self): """Gets the prefix_ns_boolean of this XmlItem. # noqa: E501 Returns: (bool): The prefix_ns_boolean of this XmlItem. # noqa: E501 """ return self.__get_item('prefix_ns_boolean') @prefix_ns_boolean.setter def prefix_ns_boolean(self, value): """Sets the prefix_ns_boolean of this XmlItem. # noqa: E501 """ return self.__set_item('prefix_ns_boolean', value) @property def prefix_ns_array(self): """Gets the prefix_ns_array of this XmlItem. # noqa: E501 Returns: ([int]): The prefix_ns_array of this XmlItem. # noqa: E501 """ return self.__get_item('prefix_ns_array') @prefix_ns_array.setter def prefix_ns_array(self, value): """Sets the prefix_ns_array of this XmlItem. # noqa: E501 """ return self.__set_item('prefix_ns_array', value) @property def prefix_ns_wrapped_array(self): """Gets the prefix_ns_wrapped_array of this XmlItem. # noqa: E501 Returns: ([int]): The prefix_ns_wrapped_array of this XmlItem. # noqa: E501 """ return self.__get_item('prefix_ns_wrapped_array') @prefix_ns_wrapped_array.setter def prefix_ns_wrapped_array(self, value): """Sets the prefix_ns_wrapped_array of this XmlItem. # noqa: E501 """ return self.__set_item('prefix_ns_wrapped_array', value) def to_dict(self): """Returns the model properties as a dict""" return model_to_dict(self, serialize=False) def to_str(self): """Returns the string representation of the model""" return pprint.pformat(self.to_dict()) def __repr__(self): """For `print` and `pprint`""" return self.to_str() def __eq__(self, other): """Returns true if both objects are equal""" if not isinstance(other, XmlItem): return False if not set(self._data_store.keys()) == set(other._data_store.keys()): return False for _var_name, this_val in six.iteritems(self._data_store): that_val = other._data_store[_var_name] types = set() types.add(this_val.__class__) types.add(that_val.__class__) vals_equal = this_val == that_val if (not six.PY3 and len(types) == 2 and unicode in types): # noqa: F821 vals_equal = ( this_val.encode('utf-8') == that_val.encode('utf-8') ) if not vals_equal: return False return True def __ne__(self, other): """Returns true if both objects are not equal""" return not self == other
[ 2, 19617, 25, 3384, 69, 12, 23, 198, 198, 37811, 198, 220, 220, 220, 4946, 17614, 4767, 8095, 628, 220, 220, 220, 770, 1020, 318, 8384, 329, 4856, 4767, 8095, 4382, 290, 4909, 8390, 886, 13033, 11, 4981, 13, 4222, 466, 407, 779, 428, 329, 597, 584, 4007, 13, 6093, 3435, 25, 19990, 26867, 220, 1303, 645, 20402, 25, 412, 33548, 628, 220, 220, 220, 383, 2196, 286, 262, 4946, 17614, 3188, 25, 352, 13, 15, 13, 15, 198, 220, 220, 220, 2980, 515, 416, 25, 3740, 1378, 9654, 15042, 12, 8612, 1352, 13, 13670, 198, 37811, 628, 198, 11748, 279, 4798, 220, 1303, 645, 20402, 25, 376, 21844, 198, 11748, 302, 220, 1303, 645, 20402, 25, 376, 21844, 198, 198, 11748, 2237, 220, 1303, 645, 20402, 25, 376, 21844, 198, 198, 6738, 4273, 8095, 62, 15042, 13, 1069, 11755, 1330, 357, 220, 1303, 645, 20402, 25, 376, 21844, 198, 220, 220, 220, 5949, 72, 9218, 12331, 11, 198, 220, 220, 220, 5949, 72, 6030, 12331, 11, 198, 220, 220, 220, 5949, 72, 11395, 12331, 11, 198, 8, 198, 6738, 4273, 8095, 62, 15042, 13, 19849, 62, 26791, 1330, 357, 220, 1303, 645, 20402, 25, 376, 21844, 198, 220, 220, 220, 9104, 26447, 11, 198, 220, 220, 220, 9104, 26437, 11, 198, 220, 220, 220, 2198, 62, 40845, 62, 27160, 11, 198, 220, 220, 220, 2198, 62, 12102, 602, 11, 198, 220, 220, 220, 3128, 11, 198, 220, 220, 220, 4818, 8079, 11, 198, 220, 220, 220, 2393, 62, 4906, 11, 198, 220, 220, 220, 651, 62, 36439, 62, 4871, 11, 198, 220, 220, 220, 493, 11, 198, 220, 220, 220, 2746, 62, 1462, 62, 11600, 11, 198, 220, 220, 220, 4844, 62, 4906, 11, 198, 220, 220, 220, 965, 11, 198, 220, 220, 220, 2099, 62, 18224, 62, 20500, 11, 198, 220, 220, 220, 26571, 62, 392, 62, 1102, 1851, 62, 19199, 198, 8, 628, 198, 4871, 1395, 4029, 7449, 7, 17633, 26447, 2599, 198, 220, 220, 220, 37227, 16580, 25, 770, 1398, 318, 8295, 7560, 416, 4946, 17614, 35986, 13, 198, 220, 220, 220, 6524, 25, 3740, 1378, 9654, 15042, 12, 8612, 1352, 13, 13670, 628, 220, 220, 220, 2141, 407, 4370, 262, 1398, 14500, 13, 628, 220, 220, 220, 49213, 25, 198, 220, 220, 220, 220, 220, 3142, 62, 27160, 357, 11600, 2599, 383, 1994, 318, 262, 46545, 3108, 284, 262, 11688, 198, 220, 220, 220, 220, 220, 220, 220, 220, 220, 290, 262, 329, 1401, 62, 3672, 428, 318, 357, 7785, 62, 3672, 11, 737, 383, 1988, 318, 257, 8633, 198, 220, 220, 220, 220, 220, 220, 220, 220, 220, 351, 257, 3139, 1143, 1994, 12059, 262, 3142, 1988, 290, 281, 3142, 198, 220, 220, 220, 220, 220, 220, 220, 220, 220, 1988, 13, 2312, 8633, 82, 3650, 262, 3142, 33829, 3815, 13, 198, 220, 220, 220, 220, 220, 11688, 62, 8899, 357, 11600, 2599, 383, 1994, 318, 11688, 1438, 198, 220, 220, 220, 220, 220, 220, 220, 220, 220, 290, 262, 1988, 318, 33918, 1994, 287, 6770, 13, 198, 220, 220, 220, 220, 220, 6534, 20900, 62, 8367, 62, 4871, 62, 8899, 357, 11600, 2599, 317, 8633, 284, 467, 422, 262, 6534, 20900, 198, 220, 220, 220, 220, 220, 220, 220, 220, 220, 7885, 1988, 284, 262, 6534, 20900, 1398, 1438, 13, 198, 220, 220, 220, 220, 220, 1280, 15042, 62, 19199, 357, 11600, 2599, 383, 1994, 318, 11688, 1438, 198, 220, 220, 220, 220, 220, 220, 220, 220, 220, 290, 262, 1988, 318, 11688, 2099, 13, 198, 220, 220, 220, 220, 220, 4938, 602, 357, 11600, 2599, 383, 1994, 318, 262, 46545, 3108, 284, 262, 11688, 198, 220, 220, 220, 220, 220, 220, 220, 220, 220, 290, 262, 329, 1401, 62, 3672, 428, 318, 357, 7785, 62, 3672, 11, 737, 383, 1988, 318, 257, 8633, 198, 220, 220, 220, 220, 220, 220, 220, 220, 220, 326, 7000, 4938, 602, 329, 3509, 62, 13664, 11, 949, 62, 13664, 11, 3509, 62, 23814, 11, 198, 220, 220, 220, 220, 220, 220, 220, 220, 220, 949, 62, 23814, 11, 8568, 62, 47033, 11, 19889, 62, 47033, 11, 8568, 62, 39504, 11, 198, 220, 220, 220, 220, 220, 220, 220, 220, 220, 19889, 62, 39504, 11, 290, 40364, 13, 198, 220, 220, 220, 220, 220, 3224, 62, 48310, 62, 4906, 357, 83, 29291, 2599, 317, 46545, 286, 6097, 6292, 198, 220, 220, 220, 220, 220, 220, 220, 220, 220, 355, 3224, 6608, 3815, 13, 198, 220, 220, 220, 37227, 628, 220, 220, 220, 3142, 62, 27160, 796, 1391, 198, 220, 220, 220, 1782, 628, 220, 220, 220, 11688, 62, 8899, 796, 1391, 198, 220, 220, 220, 220, 220, 220, 220, 705, 42348, 62, 8841, 10354, 705, 42348, 62, 8841, 3256, 220, 1303, 645, 20402, 25, 412, 33548, 198, 220, 220, 220, 220, 220, 220, 220, 705, 42348, 62, 17618, 10354, 705, 42348, 62, 17618, 3256, 220, 1303, 645, 20402, 25, 412, 33548, 198, 220, 220, 220, 220, 220, 220, 220, 705, 42348, 62, 41433, 10354, 705, 42348, 62, 41433, 3256, 220, 1303, 645, 20402, 25, 412, 33548, 198, 220, 220, 220, 220, 220, 220, 220, 705, 42348, 62, 2127, 21052, 10354, 705, 42348, 62, 2127, 21052, 3256, 220, 1303, 645, 20402, 25, 412, 33548, 198, 220, 220, 220, 220, 220, 220, 220, 705, 29988, 1496, 62, 18747, 10354, 705, 29988, 1496, 62, 18747, 3256, 220, 1303, 645, 20402, 25, 412, 33548, 198, 220, 220, 220, 220, 220, 220, 220, 705, 3672, 62, 8841, 10354, 705, 3672, 62, 8841, 3256, 220, 1303, 645, 20402, 25, 412, 33548, 198, 220, 220, 220, 220, 220, 220, 220, 705, 3672, 62, 17618, 10354, 705, 3672, 62, 17618, 3256, 220, 1303, 645, 20402, 25, 412, 33548, 198, 220, 220, 220, 220, 220, 220, 220, 705, 3672, 62, 41433, 10354, 705, 3672, 62, 41433, 3256, 220, 1303, 645, 20402, 25, 412, 33548, 198, 220, 220, 220, 220, 220, 220, 220, 705, 3672, 62, 2127, 21052, 10354, 705, 3672, 62, 2127, 21052, 3256, 220, 1303, 645, 20402, 25, 412, 33548, 198, 220, 220, 220, 220, 220, 220, 220, 705, 3672, 62, 18747, 10354, 705, 3672, 62, 18747, 3256, 220, 1303, 645, 20402, 25, 412, 33548, 198, 220, 220, 220, 220, 220, 220, 220, 705, 3672, 62, 29988, 1496, 62, 18747, 10354, 705, 3672, 62, 29988, 1496, 62, 18747, 3256, 220, 1303, 645, 20402, 25, 412, 33548, 198, 220, 220, 220, 220, 220, 220, 220, 705, 40290, 62, 8841, 10354, 705, 40290, 62, 8841, 3256, 220, 1303, 645, 20402, 25, 412, 33548, 198, 220, 220, 220, 220, 220, 220, 220, 705, 40290, 62, 17618, 10354, 705, 40290, 62, 17618, 3256, 220, 1303, 645, 20402, 25, 412, 33548, 198, 220, 220, 220, 220, 220, 220, 220, 705, 40290, 62, 41433, 10354, 705, 40290, 62, 41433, 3256, 220, 1303, 645, 20402, 25, 412, 33548, 198, 220, 220, 220, 220, 220, 220, 220, 705, 40290, 62, 2127, 21052, 10354, 705, 40290, 62, 2127, 21052, 3256, 220, 1303, 645, 20402, 25, 412, 33548, 198, 220, 220, 220, 220, 220, 220, 220, 705, 40290, 62, 18747, 10354, 705, 40290, 62, 18747, 3256, 220, 1303, 645, 20402, 25, 412, 33548, 198, 220, 220, 220, 220, 220, 220, 220, 705, 40290, 62, 29988, 1496, 62, 18747, 10354, 705, 40290, 62, 29988, 1496, 62, 18747, 3256, 220, 1303, 645, 20402, 25, 412, 33548, 198, 220, 220, 220, 220, 220, 220, 220, 705, 14933, 10223, 62, 8841, 10354, 705, 14933, 10223, 62, 8841, 3256, 220, 1303, 645, 20402, 25, 412, 33548, 198, 220, 220, 220, 220, 220, 220, 220, 705, 14933, 10223, 62, 17618, 10354, 705, 14933, 10223, 62, 17618, 3256, 220, 1303, 645, 20402, 25, 412, 33548, 198, 220, 220, 220, 220, 220, 220, 220, 705, 14933, 10223, 62, 41433, 10354, 705, 14933, 10223, 62, 41433, 3256, 220, 1303, 645, 20402, 25, 412, 33548, 198, 220, 220, 220, 220, 220, 220, 220, 705, 14933, 10223, 62, 2127, 21052, 10354, 705, 14933, 10223, 62, 2127, 21052, 3256, 220, 1303, 645, 20402, 25, 412, 33548, 198, 220, 220, 220, 220, 220, 220, 220, 705, 14933, 10223, 62, 18747, 10354, 705, 14933, 10223, 62, 18747, 3256, 220, 1303, 645, 20402, 25, 412, 33548, 198, 220, 220, 220, 220, 220, 220, 220, 705, 14933, 10223, 62, 29988, 1496, 62, 18747, 10354, 705, 14933, 10223, 62, 29988, 1496, 62, 18747, 3256, 220, 1303, 645, 20402, 25, 412, 33548, 198, 220, 220, 220, 220, 220, 220, 220, 705, 40290, 62, 5907, 62, 8841, 10354, 705, 40290, 62, 5907, 62, 8841, 3256, 220, 1303, 645, 20402, 25, 412, 33548, 198, 220, 220, 220, 220, 220, 220, 220, 705, 40290, 62, 5907, 62, 17618, 10354, 705, 40290, 62, 5907, 62, 17618, 3256, 220, 1303, 645, 20402, 25, 412, 33548, 198, 220, 220, 220, 220, 220, 220, 220, 705, 40290, 62, 5907, 62, 41433, 10354, 705, 40290, 62, 5907, 62, 41433, 3256, 220, 1303, 645, 20402, 25, 412, 33548, 198, 220, 220, 220, 220, 220, 220, 220, 705, 40290, 62, 5907, 62, 2127, 21052, 10354, 705, 40290, 62, 5907, 62, 2127, 21052, 3256, 220, 1303, 645, 20402, 25, 412, 33548, 198, 220, 220, 220, 220, 220, 220, 220, 705, 40290, 62, 5907, 62, 18747, 10354, 705, 40290, 62, 5907, 62, 18747, 3256, 220, 1303, 645, 20402, 25, 412, 33548, 198, 220, 220, 220, 220, 220, 220, 220, 705, 40290, 62, 5907, 62, 29988, 1496, 62, 18747, 10354, 705, 40290, 62, 5907, 62, 29988, 1496, 62, 18747, 6, 220, 1303, 645, 20402, 25, 412, 33548, 198, 220, 220, 220, 1782, 628, 220, 220, 220, 1280, 15042, 62, 19199, 796, 1391, 198, 220, 220, 220, 220, 220, 220, 220, 705, 42348, 62, 8841, 10354, 357, 2536, 11, 828, 220, 1303, 645, 20402, 25, 412, 33548, 198, 220, 220, 220, 220, 220, 220, 220, 705, 42348, 62, 17618, 10354, 357, 22468, 11, 828, 220, 1303, 645, 20402, 25, 412, 33548, 198, 220, 220, 220, 220, 220, 220, 220, 705, 42348, 62, 41433, 10354, 357, 600, 11, 828, 220, 1303, 645, 20402, 25, 412, 33548, 198, 220, 220, 220, 220, 220, 220, 220, 705, 42348, 62, 2127, 21052, 10354, 357, 30388, 11, 828, 220, 1303, 645, 20402, 25, 412, 33548, 198, 220, 220, 220, 220, 220, 220, 220, 705, 29988, 1496, 62, 18747, 10354, 29565, 600, 4357, 828, 220, 1303, 645, 20402, 25, 412, 33548, 198, 220, 220, 220, 220, 220, 220, 220, 705, 3672, 62, 8841, 10354, 357, 2536, 11, 828, 220, 1303, 645, 20402, 25, 412, 33548, 198, 220, 220, 220, 220, 220, 220, 220, 705, 3672, 62, 17618, 10354, 357, 22468, 11, 828, 220, 1303, 645, 20402, 25, 412, 33548, 198, 220, 220, 220, 220, 220, 220, 220, 705, 3672, 62, 41433, 10354, 357, 600, 11, 828, 220, 1303, 645, 20402, 25, 412, 33548, 198, 220, 220, 220, 220, 220, 220, 220, 705, 3672, 62, 2127, 21052, 10354, 357, 30388, 11, 828, 220, 1303, 645, 20402, 25, 412, 33548, 198, 220, 220, 220, 220, 220, 220, 220, 705, 3672, 62, 18747, 10354, 29565, 600, 4357, 828, 220, 1303, 645, 20402, 25, 412, 33548, 198, 220, 220, 220, 220, 220, 220, 220, 705, 3672, 62, 29988, 1496, 62, 18747, 10354, 29565, 600, 4357, 828, 220, 1303, 645, 20402, 25, 412, 33548, 198, 220, 220, 220, 220, 220, 220, 220, 705, 40290, 62, 8841, 10354, 357, 2536, 11, 828, 220, 1303, 645, 20402, 25, 412, 33548, 198, 220, 220, 220, 220, 220, 220, 220, 705, 40290, 62, 17618, 10354, 357, 22468, 11, 828, 220, 1303, 645, 20402, 25, 412, 33548, 198, 220, 220, 220, 220, 220, 220, 220, 705, 40290, 62, 41433, 10354, 357, 600, 11, 828, 220, 1303, 645, 20402, 25, 412, 33548, 198, 220, 220, 220, 220, 220, 220, 220, 705, 40290, 62, 2127, 21052, 10354, 357, 30388, 11, 828, 220, 1303, 645, 20402, 25, 412, 33548, 198, 220, 220, 220, 220, 220, 220, 220, 705, 40290, 62, 18747, 10354, 29565, 600, 4357, 828, 220, 1303, 645, 20402, 25, 412, 33548, 198, 220, 220, 220, 220, 220, 220, 220, 705, 40290, 62, 29988, 1496, 62, 18747, 10354, 29565, 600, 4357, 828, 220, 1303, 645, 20402, 25, 412, 33548, 198, 220, 220, 220, 220, 220, 220, 220, 705, 14933, 10223, 62, 8841, 10354, 357, 2536, 11, 828, 220, 1303, 645, 20402, 25, 412, 33548, 198, 220, 220, 220, 220, 220, 220, 220, 705, 14933, 10223, 62, 17618, 10354, 357, 22468, 11, 828, 220, 1303, 645, 20402, 25, 412, 33548, 198, 220, 220, 220, 220, 220, 220, 220, 705, 14933, 10223, 62, 41433, 10354, 357, 600, 11, 828, 220, 1303, 645, 20402, 25, 412, 33548, 198, 220, 220, 220, 220, 220, 220, 220, 705, 14933, 10223, 62, 2127, 21052, 10354, 357, 30388, 11, 828, 220, 1303, 645, 20402, 25, 412, 33548, 198, 220, 220, 220, 220, 220, 220, 220, 705, 14933, 10223, 62, 18747, 10354, 29565, 600, 4357, 828, 220, 1303, 645, 20402, 25, 412, 33548, 198, 220, 220, 220, 220, 220, 220, 220, 705, 14933, 10223, 62, 29988, 1496, 62, 18747, 10354, 29565, 600, 4357, 828, 220, 1303, 645, 20402, 25, 412, 33548, 198, 220, 220, 220, 220, 220, 220, 220, 705, 40290, 62, 5907, 62, 8841, 10354, 357, 2536, 11, 828, 220, 1303, 645, 20402, 25, 412, 33548, 198, 220, 220, 220, 220, 220, 220, 220, 705, 40290, 62, 5907, 62, 17618, 10354, 357, 22468, 11, 828, 220, 1303, 645, 20402, 25, 412, 33548, 198, 220, 220, 220, 220, 220, 220, 220, 705, 40290, 62, 5907, 62, 41433, 10354, 357, 600, 11, 828, 220, 1303, 645, 20402, 25, 412, 33548, 198, 220, 220, 220, 220, 220, 220, 220, 705, 40290, 62, 5907, 62, 2127, 21052, 10354, 357, 30388, 11, 828, 220, 1303, 645, 20402, 25, 412, 33548, 198, 220, 220, 220, 220, 220, 220, 220, 705, 40290, 62, 5907, 62, 18747, 10354, 29565, 600, 4357, 828, 220, 1303, 645, 20402, 25, 412, 33548, 198, 220, 220, 220, 220, 220, 220, 220, 705, 40290, 62, 5907, 62, 29988, 1496, 62, 18747, 10354, 29565, 600, 4357, 828, 220, 1303, 645, 20402, 25, 412, 33548, 198, 220, 220, 220, 1782, 628, 220, 220, 220, 4938, 602, 796, 1391, 198, 220, 220, 220, 1782, 628, 220, 220, 220, 3224, 62, 48310, 62, 4906, 796, 6045, 628, 220, 220, 220, 6534, 20900, 796, 6045, 628, 220, 220, 220, 825, 11593, 15003, 834, 7, 944, 11, 4808, 9122, 62, 4906, 28, 17821, 11, 4808, 6738, 62, 15388, 28, 25101, 11, 4808, 6978, 62, 1462, 62, 9186, 16193, 828, 4808, 11250, 3924, 28, 14202, 11, 12429, 46265, 22046, 2599, 220, 1303, 645, 20402, 25, 412, 33548, 198, 220, 220, 220, 220, 220, 220, 220, 37227, 55, 4029, 7449, 532, 257, 2746, 5447, 287, 4946, 17614, 628, 198, 220, 220, 220, 220, 220, 220, 220, 7383, 4775, 943, 14542, 25, 198, 220, 220, 220, 220, 220, 220, 220, 220, 220, 220, 220, 4808, 9122, 62, 4906, 357, 30388, 2599, 611, 6407, 11, 3815, 329, 10007, 287, 1280, 15042, 62, 19199, 198, 220, 220, 220, 220, 220, 220, 220, 220, 220, 220, 220, 220, 220, 220, 220, 220, 220, 220, 220, 220, 220, 220, 220, 220, 220, 220, 220, 220, 220, 220, 220, 481, 307, 2099, 10667, 290, 257, 5994, 12331, 481, 307, 198, 220, 220, 220, 220, 220, 220, 220, 220, 220, 220, 220, 220, 220, 220, 220, 220, 220, 220, 220, 220, 220, 220, 220, 220, 220, 220, 220, 220, 220, 220, 220, 4376, 611, 262, 2642, 2099, 318, 5128, 13, 198, 220, 220, 220, 220, 220, 220, 220, 220, 220, 220, 220, 220, 220, 220, 220, 220, 220, 220, 220, 220, 220, 220, 220, 220, 220, 220, 220, 220, 220, 220, 220, 2896, 13185, 284, 6407, 198, 220, 220, 220, 220, 220, 220, 220, 220, 220, 220, 220, 4808, 6978, 62, 1462, 62, 9186, 357, 83, 29291, 14, 4868, 2599, 770, 318, 257, 1351, 286, 8251, 393, 3815, 284, 198, 220, 220, 220, 220, 220, 220, 220, 220, 220, 220, 220, 220, 220, 220, 220, 220, 220, 220, 220, 220, 220, 220, 220, 220, 220, 220, 220, 220, 220, 220, 220, 16007, 866, 284, 262, 2746, 287, 2722, 62, 7890, 198, 220, 220, 220, 220, 220, 220, 220, 220, 220, 220, 220, 220, 220, 220, 220, 220, 220, 220, 220, 220, 220, 220, 220, 220, 220, 220, 220, 220, 220, 220, 220, 618, 748, 48499, 2890, 257, 2882, 198, 220, 220, 220, 220, 220, 220, 220, 220, 220, 220, 220, 4808, 6738, 62, 15388, 357, 30388, 2599, 6407, 611, 262, 1366, 318, 422, 262, 4382, 198, 220, 220, 220, 220, 220, 220, 220, 220, 220, 220, 220, 220, 220, 220, 220, 220, 220, 220, 220, 220, 220, 220, 220, 220, 220, 220, 220, 220, 220, 220, 220, 10352, 611, 262, 1366, 318, 422, 262, 5456, 357, 12286, 8, 198, 220, 220, 220, 220, 220, 220, 220, 220, 220, 220, 220, 4808, 11250, 3924, 357, 38149, 2599, 262, 4554, 284, 779, 618, 198, 220, 220, 220, 220, 220, 220, 220, 220, 220, 220, 220, 220, 220, 220, 220, 220, 220, 220, 220, 220, 220, 220, 220, 220, 220, 220, 220, 220, 220, 220, 220, 748, 48499, 2890, 257, 2393, 62, 4906, 11507, 13, 198, 220, 220, 220, 220, 220, 220, 220, 220, 220, 220, 220, 220, 220, 220, 220, 220, 220, 220, 220, 220, 220, 220, 220, 220, 220, 220, 220, 220, 220, 220, 220, 1002, 3804, 11, 2099, 11315, 318, 7482, 198, 220, 220, 220, 220, 220, 220, 220, 220, 220, 220, 220, 220, 220, 220, 220, 220, 220, 220, 220, 220, 220, 220, 220, 220, 220, 220, 220, 220, 220, 220, 220, 1002, 22532, 645, 2099, 11315, 318, 1760, 13, 198, 220, 220, 220, 220, 220, 220, 220, 220, 220, 220, 220, 11688, 62, 8841, 357, 2536, 2599, 685, 25968, 60, 220, 1303, 645, 20402, 25, 412, 33548, 198, 220, 220, 220, 220, 220, 220, 220, 220, 220, 220, 220, 11688, 62, 17618, 357, 22468, 2599, 685, 25968, 60, 220, 1303, 645, 20402, 25, 412, 33548, 198, 220, 220, 220, 220, 220, 220, 220, 220, 220, 220, 220, 11688, 62, 41433, 357, 600, 2599, 685, 25968, 60, 220, 1303, 645, 20402, 25, 412, 33548, 198, 220, 220, 220, 220, 220, 220, 220, 220, 220, 220, 220, 11688, 62, 2127, 21052, 357, 30388, 2599, 685, 25968, 60, 220, 1303, 645, 20402, 25, 412, 33548, 198, 220, 220, 220, 220, 220, 220, 220, 220, 220, 220, 220, 12908, 62, 18747, 29565, 600, 60, 2599, 685, 25968, 60, 220, 1303, 645, 20402, 25, 412, 33548, 198, 220, 220, 220, 220, 220, 220, 220, 220, 220, 220, 220, 1438, 62, 8841, 357, 2536, 2599, 685, 25968, 60, 220, 1303, 645, 20402, 25, 412, 33548, 198, 220, 220, 220, 220, 220, 220, 220, 220, 220, 220, 220, 1438, 62, 17618, 357, 22468, 2599, 685, 25968, 60, 220, 1303, 645, 20402, 25, 412, 33548, 198, 220, 220, 220, 220, 220, 220, 220, 220, 220, 220, 220, 1438, 62, 41433, 357, 600, 2599, 685, 25968, 60, 220, 1303, 645, 20402, 25, 412, 33548, 198, 220, 220, 220, 220, 220, 220, 220, 220, 220, 220, 220, 1438, 62, 2127, 21052, 357, 30388, 2599, 685, 25968, 60, 220, 1303, 645, 20402, 25, 412, 33548, 198, 220, 220, 220, 220, 220, 220, 220, 220, 220, 220, 220, 1438, 62, 18747, 29565, 600, 60, 2599, 685, 25968, 60, 220, 1303, 645, 20402, 25, 412, 33548, 198, 220, 220, 220, 220, 220, 220, 220, 220, 220, 220, 220, 1438, 62, 29988, 1496, 62, 18747, 29565, 600, 60, 2599, 685, 25968, 60, 220, 1303, 645, 20402, 25, 412, 33548, 198, 220, 220, 220, 220, 220, 220, 220, 220, 220, 220, 220, 21231, 62, 8841, 357, 2536, 2599, 685, 25968, 60, 220, 1303, 645, 20402, 25, 412, 33548, 198, 220, 220, 220, 220, 220, 220, 220, 220, 220, 220, 220, 21231, 62, 17618, 357, 22468, 2599, 685, 25968, 60, 220, 1303, 645, 20402, 25, 412, 33548, 198, 220, 220, 220, 220, 220, 220, 220, 220, 220, 220, 220, 21231, 62, 41433, 357, 600, 2599, 685, 25968, 60, 220, 1303, 645, 20402, 25, 412, 33548, 198, 220, 220, 220, 220, 220, 220, 220, 220, 220, 220, 220, 21231, 62, 2127, 21052, 357, 30388, 2599, 685, 25968, 60, 220, 1303, 645, 20402, 25, 412, 33548, 198, 220, 220, 220, 220, 220, 220, 220, 220, 220, 220, 220, 21231, 62, 18747, 29565, 600, 60, 2599, 685, 25968, 60, 220, 1303, 645, 20402, 25, 412, 33548, 198, 220, 220, 220, 220, 220, 220, 220, 220, 220, 220, 220, 21231, 62, 29988, 1496, 62, 18747, 29565, 600, 60, 2599, 685, 25968, 60, 220, 1303, 645, 20402, 25, 412, 33548, 198, 220, 220, 220, 220, 220, 220, 220, 220, 220, 220, 220, 25745, 62, 8841, 357, 2536, 2599, 685, 25968, 60, 220, 1303, 645, 20402, 25, 412, 33548, 198, 220, 220, 220, 220, 220, 220, 220, 220, 220, 220, 220, 25745, 62, 17618, 357, 22468, 2599, 685, 25968, 60, 220, 1303, 645, 20402, 25, 412, 33548, 198, 220, 220, 220, 220, 220, 220, 220, 220, 220, 220, 220, 25745, 62, 41433, 357, 600, 2599, 685, 25968, 60, 220, 1303, 645, 20402, 25, 412, 33548, 198, 220, 220, 220, 220, 220, 220, 220, 220, 220, 220, 220, 25745, 62, 2127, 21052, 357, 30388, 2599, 685, 25968, 60, 220, 1303, 645, 20402, 25, 412, 33548, 198, 220, 220, 220, 220, 220, 220, 220, 220, 220, 220, 220, 25745, 62, 18747, 29565, 600, 60, 2599, 685, 25968, 60, 220, 1303, 645, 20402, 25, 412, 33548, 198, 220, 220, 220, 220, 220, 220, 220, 220, 220, 220, 220, 25745, 62, 29988, 1496, 62, 18747, 29565, 600, 60, 2599, 685, 25968, 60, 220, 1303, 645, 20402, 25, 412, 33548, 198, 220, 220, 220, 220, 220, 220, 220, 220, 220, 220, 220, 21231, 62, 5907, 62, 8841, 357, 2536, 2599, 685, 25968, 60, 220, 1303, 645, 20402, 25, 412, 33548, 198, 220, 220, 220, 220, 220, 220, 220, 220, 220, 220, 220, 21231, 62, 5907, 62, 17618, 357, 22468, 2599, 685, 25968, 60, 220, 1303, 645, 20402, 25, 412, 33548, 198, 220, 220, 220, 220, 220, 220, 220, 220, 220, 220, 220, 21231, 62, 5907, 62, 41433, 357, 600, 2599, 685, 25968, 60, 220, 1303, 645, 20402, 25, 412, 33548, 198, 220, 220, 220, 220, 220, 220, 220, 220, 220, 220, 220, 21231, 62, 5907, 62, 2127, 21052, 357, 30388, 2599, 685, 25968, 60, 220, 1303, 645, 20402, 25, 412, 33548, 198, 220, 220, 220, 220, 220, 220, 220, 220, 220, 220, 220, 21231, 62, 5907, 62, 18747, 29565, 600, 60, 2599, 685, 25968, 60, 220, 1303, 645, 20402, 25, 412, 33548, 198, 220, 220, 220, 220, 220, 220, 220, 220, 220, 220, 220, 21231, 62, 5907, 62, 29988, 1496, 62, 18747, 29565, 600, 60, 2599, 685, 25968, 60, 220, 1303, 645, 20402, 25, 412, 33548, 198, 220, 220, 220, 220, 220, 220, 220, 37227, 198, 220, 220, 220, 220, 220, 220, 220, 2116, 13557, 7890, 62, 8095, 796, 23884, 198, 220, 220, 220, 220, 220, 220, 220, 2116, 13557, 9122, 62, 4906, 796, 4808, 9122, 62, 4906, 198, 220, 220, 220, 220, 220, 220, 220, 2116, 13557, 6738, 62, 15388, 796, 4808, 6738, 62, 15388, 198, 220, 220, 220, 220, 220, 220, 220, 2116, 13557, 6978, 62, 1462, 62, 9186, 796, 4808, 6978, 62, 1462, 62, 9186, 198, 220, 220, 220, 220, 220, 220, 220, 2116, 13557, 11250, 3924, 796, 4808, 11250, 3924, 628, 220, 220, 220, 220, 220, 220, 220, 329, 1401, 62, 3672, 11, 1401, 62, 8367, 287, 2237, 13, 2676, 23814, 7, 46265, 22046, 2599, 198, 220, 220, 220, 220, 220, 220, 220, 220, 220, 220, 220, 2116, 13, 834, 2617, 62, 9186, 7, 7785, 62, 3672, 11, 1401, 62, 8367, 8, 628, 220, 220, 220, 825, 11593, 2617, 9186, 834, 7, 944, 11, 1438, 11, 1988, 2599, 198, 220, 220, 220, 220, 220, 220, 220, 37227, 5661, 3578, 514, 284, 900, 3815, 351, 4554, 58, 3245, 62, 3672, 60, 796, 1188, 37811, 198, 220, 220, 220, 220, 220, 220, 220, 2116, 13, 834, 2617, 62, 9186, 7, 3672, 11, 1988, 8, 628, 220, 220, 220, 825, 11593, 1136, 9186, 834, 7, 944, 11, 1438, 2599, 198, 220, 220, 220, 220, 220, 220, 220, 37227, 5661, 3578, 514, 284, 651, 257, 1988, 351, 1188, 796, 4554, 58, 3245, 62, 3672, 60, 37811, 198, 220, 220, 220, 220, 220, 220, 220, 1441, 2116, 13, 834, 1136, 62, 9186, 7, 3672, 8, 628, 220, 220, 220, 2488, 26745, 198, 220, 220, 220, 825, 11688, 62, 8841, 7, 944, 2599, 198, 220, 220, 220, 220, 220, 220, 220, 37227, 38, 1039, 262, 11688, 62, 8841, 286, 428, 1395, 4029, 7449, 13, 220, 1303, 645, 20402, 25, 412, 33548, 628, 220, 220, 220, 220, 220, 220, 220, 16409, 25, 198, 220, 220, 220, 220, 220, 220, 220, 220, 220, 220, 220, 357, 2536, 2599, 383, 11688, 62, 8841, 286, 428, 1395, 4029, 7449, 13, 220, 1303, 645, 20402, 25, 412, 33548, 198, 220, 220, 220, 220, 220, 220, 220, 37227, 198, 220, 220, 220, 220, 220, 220, 220, 1441, 2116, 13, 834, 1136, 62, 9186, 10786, 42348, 62, 8841, 11537, 628, 220, 220, 220, 2488, 42348, 62, 8841, 13, 2617, 353, 198, 220, 220, 220, 825, 11688, 62, 8841, 7, 944, 11, 1988, 2599, 198, 220, 220, 220, 220, 220, 220, 220, 37227, 50, 1039, 262, 11688, 62, 8841, 286, 428, 1395, 4029, 7449, 13, 220, 1303, 645, 20402, 25, 412, 33548, 198, 220, 220, 220, 220, 220, 220, 220, 37227, 198, 220, 220, 220, 220, 220, 220, 220, 1441, 2116, 13, 834, 2617, 62, 9186, 10786, 42348, 62, 8841, 3256, 1988, 8, 628, 220, 220, 220, 2488, 26745, 198, 220, 220, 220, 825, 11688, 62, 17618, 7, 944, 2599, 198, 220, 220, 220, 220, 220, 220, 220, 37227, 38, 1039, 262, 11688, 62, 17618, 286, 428, 1395, 4029, 7449, 13, 220, 1303, 645, 20402, 25, 412, 33548, 628, 220, 220, 220, 220, 220, 220, 220, 16409, 25, 198, 220, 220, 220, 220, 220, 220, 220, 220, 220, 220, 220, 357, 22468, 2599, 383, 11688, 62, 17618, 286, 428, 1395, 4029, 7449, 13, 220, 1303, 645, 20402, 25, 412, 33548, 198, 220, 220, 220, 220, 220, 220, 220, 37227, 198, 220, 220, 220, 220, 220, 220, 220, 1441, 2116, 13, 834, 1136, 62, 9186, 10786, 42348, 62, 17618, 11537, 628, 220, 220, 220, 2488, 42348, 62, 17618, 13, 2617, 353, 198, 220, 220, 220, 825, 11688, 62, 17618, 7, 944, 11, 1988, 2599, 198, 220, 220, 220, 220, 220, 220, 220, 37227, 50, 1039, 262, 11688, 62, 17618, 286, 428, 1395, 4029, 7449, 13, 220, 1303, 645, 20402, 25, 412, 33548, 198, 220, 220, 220, 220, 220, 220, 220, 37227, 198, 220, 220, 220, 220, 220, 220, 220, 1441, 2116, 13, 834, 2617, 62, 9186, 10786, 42348, 62, 17618, 3256, 1988, 8, 628, 220, 220, 220, 2488, 26745, 198, 220, 220, 220, 825, 11688, 62, 41433, 7, 944, 2599, 198, 220, 220, 220, 220, 220, 220, 220, 37227, 38, 1039, 262, 11688, 62, 41433, 286, 428, 1395, 4029, 7449, 13, 220, 1303, 645, 20402, 25, 412, 33548, 628, 220, 220, 220, 220, 220, 220, 220, 16409, 25, 198, 220, 220, 220, 220, 220, 220, 220, 220, 220, 220, 220, 357, 600, 2599, 383, 11688, 62, 41433, 286, 428, 1395, 4029, 7449, 13, 220, 1303, 645, 20402, 25, 412, 33548, 198, 220, 220, 220, 220, 220, 220, 220, 37227, 198, 220, 220, 220, 220, 220, 220, 220, 1441, 2116, 13, 834, 1136, 62, 9186, 10786, 42348, 62, 41433, 11537, 628, 220, 220, 220, 2488, 42348, 62, 41433, 13, 2617, 353, 198, 220, 220, 220, 825, 11688, 62, 41433, 7, 944, 11, 1988, 2599, 198, 220, 220, 220, 220, 220, 220, 220, 37227, 50, 1039, 262, 11688, 62, 41433, 286, 428, 1395, 4029, 7449, 13, 220, 1303, 645, 20402, 25, 412, 33548, 198, 220, 220, 220, 220, 220, 220, 220, 37227, 198, 220, 220, 220, 220, 220, 220, 220, 1441, 2116, 13, 834, 2617, 62, 9186, 10786, 42348, 62, 41433, 3256, 1988, 8, 628, 220, 220, 220, 2488, 26745, 198, 220, 220, 220, 825, 11688, 62, 2127, 21052, 7, 944, 2599, 198, 220, 220, 220, 220, 220, 220, 220, 37227, 38, 1039, 262, 11688, 62, 2127, 21052, 286, 428, 1395, 4029, 7449, 13, 220, 1303, 645, 20402, 25, 412, 33548, 628, 220, 220, 220, 220, 220, 220, 220, 16409, 25, 198, 220, 220, 220, 220, 220, 220, 220, 220, 220, 220, 220, 357, 30388, 2599, 383, 11688, 62, 2127, 21052, 286, 428, 1395, 4029, 7449, 13, 220, 1303, 645, 20402, 25, 412, 33548, 198, 220, 220, 220, 220, 220, 220, 220, 37227, 198, 220, 220, 220, 220, 220, 220, 220, 1441, 2116, 13, 834, 1136, 62, 9186, 10786, 42348, 62, 2127, 21052, 11537, 628, 220, 220, 220, 2488, 42348, 62, 2127, 21052, 13, 2617, 353, 198, 220, 220, 220, 825, 11688, 62, 2127, 21052, 7, 944, 11, 1988, 2599, 198, 220, 220, 220, 220, 220, 220, 220, 37227, 50, 1039, 262, 11688, 62, 2127, 21052, 286, 428, 1395, 4029, 7449, 13, 220, 1303, 645, 20402, 25, 412, 33548, 198, 220, 220, 220, 220, 220, 220, 220, 37227, 198, 220, 220, 220, 220, 220, 220, 220, 1441, 2116, 13, 834, 2617, 62, 9186, 10786, 42348, 62, 2127, 21052, 3256, 1988, 8, 628, 220, 220, 220, 2488, 26745, 198, 220, 220, 220, 825, 12908, 62, 18747, 7, 944, 2599, 198, 220, 220, 220, 220, 220, 220, 220, 37227, 38, 1039, 262, 12908, 62, 18747, 286, 428, 1395, 4029, 7449, 13, 220, 1303, 645, 20402, 25, 412, 33548, 628, 220, 220, 220, 220, 220, 220, 220, 16409, 25, 198, 220, 220, 220, 220, 220, 220, 220, 220, 220, 220, 220, 29565, 600, 60, 2599, 383, 12908, 62, 18747, 286, 428, 1395, 4029, 7449, 13, 220, 1303, 645, 20402, 25, 412, 33548, 198, 220, 220, 220, 220, 220, 220, 220, 37227, 198, 220, 220, 220, 220, 220, 220, 220, 1441, 2116, 13, 834, 1136, 62, 9186, 10786, 29988, 1496, 62, 18747, 11537, 628, 220, 220, 220, 2488, 29988, 1496, 62, 18747, 13, 2617, 353, 198, 220, 220, 220, 825, 12908, 62, 18747, 7, 944, 11, 1988, 2599, 198, 220, 220, 220, 220, 220, 220, 220, 37227, 50, 1039, 262, 12908, 62, 18747, 286, 428, 1395, 4029, 7449, 13, 220, 1303, 645, 20402, 25, 412, 33548, 198, 220, 220, 220, 220, 220, 220, 220, 37227, 198, 220, 220, 220, 220, 220, 220, 220, 1441, 2116, 13, 834, 2617, 62, 9186, 10786, 29988, 1496, 62, 18747, 3256, 1988, 8, 628, 220, 220, 220, 2488, 26745, 198, 220, 220, 220, 825, 1438, 62, 8841, 7, 944, 2599, 198, 220, 220, 220, 220, 220, 220, 220, 37227, 38, 1039, 262, 1438, 62, 8841, 286, 428, 1395, 4029, 7449, 13, 220, 1303, 645, 20402, 25, 412, 33548, 628, 220, 220, 220, 220, 220, 220, 220, 16409, 25, 198, 220, 220, 220, 220, 220, 220, 220, 220, 220, 220, 220, 357, 2536, 2599, 383, 1438, 62, 8841, 286, 428, 1395, 4029, 7449, 13, 220, 1303, 645, 20402, 25, 412, 33548, 198, 220, 220, 220, 220, 220, 220, 220, 37227, 198, 220, 220, 220, 220, 220, 220, 220, 1441, 2116, 13, 834, 1136, 62, 9186, 10786, 3672, 62, 8841, 11537, 628, 220, 220, 220, 2488, 3672, 62, 8841, 13, 2617, 353, 198, 220, 220, 220, 825, 1438, 62, 8841, 7, 944, 11, 1988, 2599, 198, 220, 220, 220, 220, 220, 220, 220, 37227, 50, 1039, 262, 1438, 62, 8841, 286, 428, 1395, 4029, 7449, 13, 220, 1303, 645, 20402, 25, 412, 33548, 198, 220, 220, 220, 220, 220, 220, 220, 37227, 198, 220, 220, 220, 220, 220, 220, 220, 1441, 2116, 13, 834, 2617, 62, 9186, 10786, 3672, 62, 8841, 3256, 1988, 8, 628, 220, 220, 220, 2488, 26745, 198, 220, 220, 220, 825, 1438, 62, 17618, 7, 944, 2599, 198, 220, 220, 220, 220, 220, 220, 220, 37227, 38, 1039, 262, 1438, 62, 17618, 286, 428, 1395, 4029, 7449, 13, 220, 1303, 645, 20402, 25, 412, 33548, 628, 220, 220, 220, 220, 220, 220, 220, 16409, 25, 198, 220, 220, 220, 220, 220, 220, 220, 220, 220, 220, 220, 357, 22468, 2599, 383, 1438, 62, 17618, 286, 428, 1395, 4029, 7449, 13, 220, 1303, 645, 20402, 25, 412, 33548, 198, 220, 220, 220, 220, 220, 220, 220, 37227, 198, 220, 220, 220, 220, 220, 220, 220, 1441, 2116, 13, 834, 1136, 62, 9186, 10786, 3672, 62, 17618, 11537, 628, 220, 220, 220, 2488, 3672, 62, 17618, 13, 2617, 353, 198, 220, 220, 220, 825, 1438, 62, 17618, 7, 944, 11, 1988, 2599, 198, 220, 220, 220, 220, 220, 220, 220, 37227, 50, 1039, 262, 1438, 62, 17618, 286, 428, 1395, 4029, 7449, 13, 220, 1303, 645, 20402, 25, 412, 33548, 198, 220, 220, 220, 220, 220, 220, 220, 37227, 198, 220, 220, 220, 220, 220, 220, 220, 1441, 2116, 13, 834, 2617, 62, 9186, 10786, 3672, 62, 17618, 3256, 1988, 8, 628, 220, 220, 220, 2488, 26745, 198, 220, 220, 220, 825, 1438, 62, 41433, 7, 944, 2599, 198, 220, 220, 220, 220, 220, 220, 220, 37227, 38, 1039, 262, 1438, 62, 41433, 286, 428, 1395, 4029, 7449, 13, 220, 1303, 645, 20402, 25, 412, 33548, 628, 220, 220, 220, 220, 220, 220, 220, 16409, 25, 198, 220, 220, 220, 220, 220, 220, 220, 220, 220, 220, 220, 357, 600, 2599, 383, 1438, 62, 41433, 286, 428, 1395, 4029, 7449, 13, 220, 1303, 645, 20402, 25, 412, 33548, 198, 220, 220, 220, 220, 220, 220, 220, 37227, 198, 220, 220, 220, 220, 220, 220, 220, 1441, 2116, 13, 834, 1136, 62, 9186, 10786, 3672, 62, 41433, 11537, 628, 220, 220, 220, 2488, 3672, 62, 41433, 13, 2617, 353, 198, 220, 220, 220, 825, 1438, 62, 41433, 7, 944, 11, 1988, 2599, 198, 220, 220, 220, 220, 220, 220, 220, 37227, 50, 1039, 262, 1438, 62, 41433, 286, 428, 1395, 4029, 7449, 13, 220, 1303, 645, 20402, 25, 412, 33548, 198, 220, 220, 220, 220, 220, 220, 220, 37227, 198, 220, 220, 220, 220, 220, 220, 220, 1441, 2116, 13, 834, 2617, 62, 9186, 10786, 3672, 62, 41433, 3256, 1988, 8, 628, 220, 220, 220, 2488, 26745, 198, 220, 220, 220, 825, 1438, 62, 2127, 21052, 7, 944, 2599, 198, 220, 220, 220, 220, 220, 220, 220, 37227, 38, 1039, 262, 1438, 62, 2127, 21052, 286, 428, 1395, 4029, 7449, 13, 220, 1303, 645, 20402, 25, 412, 33548, 628, 220, 220, 220, 220, 220, 220, 220, 16409, 25, 198, 220, 220, 220, 220, 220, 220, 220, 220, 220, 220, 220, 357, 30388, 2599, 383, 1438, 62, 2127, 21052, 286, 428, 1395, 4029, 7449, 13, 220, 1303, 645, 20402, 25, 412, 33548, 198, 220, 220, 220, 220, 220, 220, 220, 37227, 198, 220, 220, 220, 220, 220, 220, 220, 1441, 2116, 13, 834, 1136, 62, 9186, 10786, 3672, 62, 2127, 21052, 11537, 628, 220, 220, 220, 2488, 3672, 62, 2127, 21052, 13, 2617, 353, 198, 220, 220, 220, 825, 1438, 62, 2127, 21052, 7, 944, 11, 1988, 2599, 198, 220, 220, 220, 220, 220, 220, 220, 37227, 50, 1039, 262, 1438, 62, 2127, 21052, 286, 428, 1395, 4029, 7449, 13, 220, 1303, 645, 20402, 25, 412, 33548, 198, 220, 220, 220, 220, 220, 220, 220, 37227, 198, 220, 220, 220, 220, 220, 220, 220, 1441, 2116, 13, 834, 2617, 62, 9186, 10786, 3672, 62, 2127, 21052, 3256, 1988, 8, 628, 220, 220, 220, 2488, 26745, 198, 220, 220, 220, 825, 1438, 62, 18747, 7, 944, 2599, 198, 220, 220, 220, 220, 220, 220, 220, 37227, 38, 1039, 262, 1438, 62, 18747, 286, 428, 1395, 4029, 7449, 13, 220, 1303, 645, 20402, 25, 412, 33548, 628, 220, 220, 220, 220, 220, 220, 220, 16409, 25, 198, 220, 220, 220, 220, 220, 220, 220, 220, 220, 220, 220, 29565, 600, 60, 2599, 383, 1438, 62, 18747, 286, 428, 1395, 4029, 7449, 13, 220, 1303, 645, 20402, 25, 412, 33548, 198, 220, 220, 220, 220, 220, 220, 220, 37227, 198, 220, 220, 220, 220, 220, 220, 220, 1441, 2116, 13, 834, 1136, 62, 9186, 10786, 3672, 62, 18747, 11537, 628, 220, 220, 220, 2488, 3672, 62, 18747, 13, 2617, 353, 198, 220, 220, 220, 825, 1438, 62, 18747, 7, 944, 11, 1988, 2599, 198, 220, 220, 220, 220, 220, 220, 220, 37227, 50, 1039, 262, 1438, 62, 18747, 286, 428, 1395, 4029, 7449, 13, 220, 1303, 645, 20402, 25, 412, 33548, 198, 220, 220, 220, 220, 220, 220, 220, 37227, 198, 220, 220, 220, 220, 220, 220, 220, 1441, 2116, 13, 834, 2617, 62, 9186, 10786, 3672, 62, 18747, 3256, 1988, 8, 628, 220, 220, 220, 2488, 26745, 198, 220, 220, 220, 825, 1438, 62, 29988, 1496, 62, 18747, 7, 944, 2599, 198, 220, 220, 220, 220, 220, 220, 220, 37227, 38, 1039, 262, 1438, 62, 29988, 1496, 62, 18747, 286, 428, 1395, 4029, 7449, 13, 220, 1303, 645, 20402, 25, 412, 33548, 628, 220, 220, 220, 220, 220, 220, 220, 16409, 25, 198, 220, 220, 220, 220, 220, 220, 220, 220, 220, 220, 220, 29565, 600, 60, 2599, 383, 1438, 62, 29988, 1496, 62, 18747, 286, 428, 1395, 4029, 7449, 13, 220, 1303, 645, 20402, 25, 412, 33548, 198, 220, 220, 220, 220, 220, 220, 220, 37227, 198, 220, 220, 220, 220, 220, 220, 220, 1441, 2116, 13, 834, 1136, 62, 9186, 10786, 3672, 62, 29988, 1496, 62, 18747, 11537, 628, 220, 220, 220, 2488, 3672, 62, 29988, 1496, 62, 18747, 13, 2617, 353, 198, 220, 220, 220, 825, 1438, 62, 29988, 1496, 62, 18747, 7, 944, 11, 1988, 2599, 198, 220, 220, 220, 220, 220, 220, 220, 37227, 50, 1039, 262, 1438, 62, 29988, 1496, 62, 18747, 286, 428, 1395, 4029, 7449, 13, 220, 1303, 645, 20402, 25, 412, 33548, 198, 220, 220, 220, 220, 220, 220, 220, 37227, 198, 220, 220, 220, 220, 220, 220, 220, 1441, 2116, 13, 834, 2617, 62, 9186, 10786, 3672, 62, 29988, 1496, 62, 18747, 3256, 1988, 8, 628, 220, 220, 220, 2488, 26745, 198, 220, 220, 220, 825, 21231, 62, 8841, 7, 944, 2599, 198, 220, 220, 220, 220, 220, 220, 220, 37227, 38, 1039, 262, 21231, 62, 8841, 286, 428, 1395, 4029, 7449, 13, 220, 1303, 645, 20402, 25, 412, 33548, 628, 220, 220, 220, 220, 220, 220, 220, 16409, 25, 198, 220, 220, 220, 220, 220, 220, 220, 220, 220, 220, 220, 357, 2536, 2599, 383, 21231, 62, 8841, 286, 428, 1395, 4029, 7449, 13, 220, 1303, 645, 20402, 25, 412, 33548, 198, 220, 220, 220, 220, 220, 220, 220, 37227, 198, 220, 220, 220, 220, 220, 220, 220, 1441, 2116, 13, 834, 1136, 62, 9186, 10786, 40290, 62, 8841, 11537, 628, 220, 220, 220, 2488, 40290, 62, 8841, 13, 2617, 353, 198, 220, 220, 220, 825, 21231, 62, 8841, 7, 944, 11, 1988, 2599, 198, 220, 220, 220, 220, 220, 220, 220, 37227, 50, 1039, 262, 21231, 62, 8841, 286, 428, 1395, 4029, 7449, 13, 220, 1303, 645, 20402, 25, 412, 33548, 198, 220, 220, 220, 220, 220, 220, 220, 37227, 198, 220, 220, 220, 220, 220, 220, 220, 1441, 2116, 13, 834, 2617, 62, 9186, 10786, 40290, 62, 8841, 3256, 1988, 8, 628, 220, 220, 220, 2488, 26745, 198, 220, 220, 220, 825, 21231, 62, 17618, 7, 944, 2599, 198, 220, 220, 220, 220, 220, 220, 220, 37227, 38, 1039, 262, 21231, 62, 17618, 286, 428, 1395, 4029, 7449, 13, 220, 1303, 645, 20402, 25, 412, 33548, 628, 220, 220, 220, 220, 220, 220, 220, 16409, 25, 198, 220, 220, 220, 220, 220, 220, 220, 220, 220, 220, 220, 357, 22468, 2599, 383, 21231, 62, 17618, 286, 428, 1395, 4029, 7449, 13, 220, 1303, 645, 20402, 25, 412, 33548, 198, 220, 220, 220, 220, 220, 220, 220, 37227, 198, 220, 220, 220, 220, 220, 220, 220, 1441, 2116, 13, 834, 1136, 62, 9186, 10786, 40290, 62, 17618, 11537, 628, 220, 220, 220, 2488, 40290, 62, 17618, 13, 2617, 353, 198, 220, 220, 220, 825, 21231, 62, 17618, 7, 944, 11, 1988, 2599, 198, 220, 220, 220, 220, 220, 220, 220, 37227, 50, 1039, 262, 21231, 62, 17618, 286, 428, 1395, 4029, 7449, 13, 220, 1303, 645, 20402, 25, 412, 33548, 198, 220, 220, 220, 220, 220, 220, 220, 37227, 198, 220, 220, 220, 220, 220, 220, 220, 1441, 2116, 13, 834, 2617, 62, 9186, 10786, 40290, 62, 17618, 3256, 1988, 8, 628, 220, 220, 220, 2488, 26745, 198, 220, 220, 220, 825, 21231, 62, 41433, 7, 944, 2599, 198, 220, 220, 220, 220, 220, 220, 220, 37227, 38, 1039, 262, 21231, 62, 41433, 286, 428, 1395, 4029, 7449, 13, 220, 1303, 645, 20402, 25, 412, 33548, 628, 220, 220, 220, 220, 220, 220, 220, 16409, 25, 198, 220, 220, 220, 220, 220, 220, 220, 220, 220, 220, 220, 357, 600, 2599, 383, 21231, 62, 41433, 286, 428, 1395, 4029, 7449, 13, 220, 1303, 645, 20402, 25, 412, 33548, 198, 220, 220, 220, 220, 220, 220, 220, 37227, 198, 220, 220, 220, 220, 220, 220, 220, 1441, 2116, 13, 834, 1136, 62, 9186, 10786, 40290, 62, 41433, 11537, 628, 220, 220, 220, 2488, 40290, 62, 41433, 13, 2617, 353, 198, 220, 220, 220, 825, 21231, 62, 41433, 7, 944, 11, 1988, 2599, 198, 220, 220, 220, 220, 220, 220, 220, 37227, 50, 1039, 262, 21231, 62, 41433, 286, 428, 1395, 4029, 7449, 13, 220, 1303, 645, 20402, 25, 412, 33548, 198, 220, 220, 220, 220, 220, 220, 220, 37227, 198, 220, 220, 220, 220, 220, 220, 220, 1441, 2116, 13, 834, 2617, 62, 9186, 10786, 40290, 62, 41433, 3256, 1988, 8, 628, 220, 220, 220, 2488, 26745, 198, 220, 220, 220, 825, 21231, 62, 2127, 21052, 7, 944, 2599, 198, 220, 220, 220, 220, 220, 220, 220, 37227, 38, 1039, 262, 21231, 62, 2127, 21052, 286, 428, 1395, 4029, 7449, 13, 220, 1303, 645, 20402, 25, 412, 33548, 628, 220, 220, 220, 220, 220, 220, 220, 16409, 25, 198, 220, 220, 220, 220, 220, 220, 220, 220, 220, 220, 220, 357, 30388, 2599, 383, 21231, 62, 2127, 21052, 286, 428, 1395, 4029, 7449, 13, 220, 1303, 645, 20402, 25, 412, 33548, 198, 220, 220, 220, 220, 220, 220, 220, 37227, 198, 220, 220, 220, 220, 220, 220, 220, 1441, 2116, 13, 834, 1136, 62, 9186, 10786, 40290, 62, 2127, 21052, 11537, 628, 220, 220, 220, 2488, 40290, 62, 2127, 21052, 13, 2617, 353, 198, 220, 220, 220, 825, 21231, 62, 2127, 21052, 7, 944, 11, 1988, 2599, 198, 220, 220, 220, 220, 220, 220, 220, 37227, 50, 1039, 262, 21231, 62, 2127, 21052, 286, 428, 1395, 4029, 7449, 13, 220, 1303, 645, 20402, 25, 412, 33548, 198, 220, 220, 220, 220, 220, 220, 220, 37227, 198, 220, 220, 220, 220, 220, 220, 220, 1441, 2116, 13, 834, 2617, 62, 9186, 10786, 40290, 62, 2127, 21052, 3256, 1988, 8, 628, 220, 220, 220, 2488, 26745, 198, 220, 220, 220, 825, 21231, 62, 18747, 7, 944, 2599, 198, 220, 220, 220, 220, 220, 220, 220, 37227, 38, 1039, 262, 21231, 62, 18747, 286, 428, 1395, 4029, 7449, 13, 220, 1303, 645, 20402, 25, 412, 33548, 628, 220, 220, 220, 220, 220, 220, 220, 16409, 25, 198, 220, 220, 220, 220, 220, 220, 220, 220, 220, 220, 220, 29565, 600, 60, 2599, 383, 21231, 62, 18747, 286, 428, 1395, 4029, 7449, 13, 220, 1303, 645, 20402, 25, 412, 33548, 198, 220, 220, 220, 220, 220, 220, 220, 37227, 198, 220, 220, 220, 220, 220, 220, 220, 1441, 2116, 13, 834, 1136, 62, 9186, 10786, 40290, 62, 18747, 11537, 628, 220, 220, 220, 2488, 40290, 62, 18747, 13, 2617, 353, 198, 220, 220, 220, 825, 21231, 62, 18747, 7, 944, 11, 1988, 2599, 198, 220, 220, 220, 220, 220, 220, 220, 37227, 50, 1039, 262, 21231, 62, 18747, 286, 428, 1395, 4029, 7449, 13, 220, 1303, 645, 20402, 25, 412, 33548, 198, 220, 220, 220, 220, 220, 220, 220, 37227, 198, 220, 220, 220, 220, 220, 220, 220, 1441, 2116, 13, 834, 2617, 62, 9186, 10786, 40290, 62, 18747, 3256, 1988, 8, 628, 220, 220, 220, 2488, 26745, 198, 220, 220, 220, 825, 21231, 62, 29988, 1496, 62, 18747, 7, 944, 2599, 198, 220, 220, 220, 220, 220, 220, 220, 37227, 38, 1039, 262, 21231, 62, 29988, 1496, 62, 18747, 286, 428, 1395, 4029, 7449, 13, 220, 1303, 645, 20402, 25, 412, 33548, 628, 220, 220, 220, 220, 220, 220, 220, 16409, 25, 198, 220, 220, 220, 220, 220, 220, 220, 220, 220, 220, 220, 29565, 600, 60, 2599, 383, 21231, 62, 29988, 1496, 62, 18747, 286, 428, 1395, 4029, 7449, 13, 220, 1303, 645, 20402, 25, 412, 33548, 198, 220, 220, 220, 220, 220, 220, 220, 37227, 198, 220, 220, 220, 220, 220, 220, 220, 1441, 2116, 13, 834, 1136, 62, 9186, 10786, 40290, 62, 29988, 1496, 62, 18747, 11537, 628, 220, 220, 220, 2488, 40290, 62, 29988, 1496, 62, 18747, 13, 2617, 353, 198, 220, 220, 220, 825, 21231, 62, 29988, 1496, 62, 18747, 7, 944, 11, 1988, 2599, 198, 220, 220, 220, 220, 220, 220, 220, 37227, 50, 1039, 262, 21231, 62, 29988, 1496, 62, 18747, 286, 428, 1395, 4029, 7449, 13, 220, 1303, 645, 20402, 25, 412, 33548, 198, 220, 220, 220, 220, 220, 220, 220, 37227, 198, 220, 220, 220, 220, 220, 220, 220, 1441, 2116, 13, 834, 2617, 62, 9186, 10786, 40290, 62, 29988, 1496, 62, 18747, 3256, 1988, 8, 628, 220, 220, 220, 2488, 26745, 198, 220, 220, 220, 825, 25745, 62, 8841, 7, 944, 2599, 198, 220, 220, 220, 220, 220, 220, 220, 37227, 38, 1039, 262, 25745, 62, 8841, 286, 428, 1395, 4029, 7449, 13, 220, 1303, 645, 20402, 25, 412, 33548, 628, 220, 220, 220, 220, 220, 220, 220, 16409, 25, 198, 220, 220, 220, 220, 220, 220, 220, 220, 220, 220, 220, 357, 2536, 2599, 383, 25745, 62, 8841, 286, 428, 1395, 4029, 7449, 13, 220, 1303, 645, 20402, 25, 412, 33548, 198, 220, 220, 220, 220, 220, 220, 220, 37227, 198, 220, 220, 220, 220, 220, 220, 220, 1441, 2116, 13, 834, 1136, 62, 9186, 10786, 14933, 10223, 62, 8841, 11537, 628, 220, 220, 220, 2488, 14933, 10223, 62, 8841, 13, 2617, 353, 198, 220, 220, 220, 825, 25745, 62, 8841, 7, 944, 11, 1988, 2599, 198, 220, 220, 220, 220, 220, 220, 220, 37227, 50, 1039, 262, 25745, 62, 8841, 286, 428, 1395, 4029, 7449, 13, 220, 1303, 645, 20402, 25, 412, 33548, 198, 220, 220, 220, 220, 220, 220, 220, 37227, 198, 220, 220, 220, 220, 220, 220, 220, 1441, 2116, 13, 834, 2617, 62, 9186, 10786, 14933, 10223, 62, 8841, 3256, 1988, 8, 628, 220, 220, 220, 2488, 26745, 198, 220, 220, 220, 825, 25745, 62, 17618, 7, 944, 2599, 198, 220, 220, 220, 220, 220, 220, 220, 37227, 38, 1039, 262, 25745, 62, 17618, 286, 428, 1395, 4029, 7449, 13, 220, 1303, 645, 20402, 25, 412, 33548, 628, 220, 220, 220, 220, 220, 220, 220, 16409, 25, 198, 220, 220, 220, 220, 220, 220, 220, 220, 220, 220, 220, 357, 22468, 2599, 383, 25745, 62, 17618, 286, 428, 1395, 4029, 7449, 13, 220, 1303, 645, 20402, 25, 412, 33548, 198, 220, 220, 220, 220, 220, 220, 220, 37227, 198, 220, 220, 220, 220, 220, 220, 220, 1441, 2116, 13, 834, 1136, 62, 9186, 10786, 14933, 10223, 62, 17618, 11537, 628, 220, 220, 220, 2488, 14933, 10223, 62, 17618, 13, 2617, 353, 198, 220, 220, 220, 825, 25745, 62, 17618, 7, 944, 11, 1988, 2599, 198, 220, 220, 220, 220, 220, 220, 220, 37227, 50, 1039, 262, 25745, 62, 17618, 286, 428, 1395, 4029, 7449, 13, 220, 1303, 645, 20402, 25, 412, 33548, 198, 220, 220, 220, 220, 220, 220, 220, 37227, 198, 220, 220, 220, 220, 220, 220, 220, 1441, 2116, 13, 834, 2617, 62, 9186, 10786, 14933, 10223, 62, 17618, 3256, 1988, 8, 628, 220, 220, 220, 2488, 26745, 198, 220, 220, 220, 825, 25745, 62, 41433, 7, 944, 2599, 198, 220, 220, 220, 220, 220, 220, 220, 37227, 38, 1039, 262, 25745, 62, 41433, 286, 428, 1395, 4029, 7449, 13, 220, 1303, 645, 20402, 25, 412, 33548, 628, 220, 220, 220, 220, 220, 220, 220, 16409, 25, 198, 220, 220, 220, 220, 220, 220, 220, 220, 220, 220, 220, 357, 600, 2599, 383, 25745, 62, 41433, 286, 428, 1395, 4029, 7449, 13, 220, 1303, 645, 20402, 25, 412, 33548, 198, 220, 220, 220, 220, 220, 220, 220, 37227, 198, 220, 220, 220, 220, 220, 220, 220, 1441, 2116, 13, 834, 1136, 62, 9186, 10786, 14933, 10223, 62, 41433, 11537, 628, 220, 220, 220, 2488, 14933, 10223, 62, 41433, 13, 2617, 353, 198, 220, 220, 220, 825, 25745, 62, 41433, 7, 944, 11, 1988, 2599, 198, 220, 220, 220, 220, 220, 220, 220, 37227, 50, 1039, 262, 25745, 62, 41433, 286, 428, 1395, 4029, 7449, 13, 220, 1303, 645, 20402, 25, 412, 33548, 198, 220, 220, 220, 220, 220, 220, 220, 37227, 198, 220, 220, 220, 220, 220, 220, 220, 1441, 2116, 13, 834, 2617, 62, 9186, 10786, 14933, 10223, 62, 41433, 3256, 1988, 8, 628, 220, 220, 220, 2488, 26745, 198, 220, 220, 220, 825, 25745, 62, 2127, 21052, 7, 944, 2599, 198, 220, 220, 220, 220, 220, 220, 220, 37227, 38, 1039, 262, 25745, 62, 2127, 21052, 286, 428, 1395, 4029, 7449, 13, 220, 1303, 645, 20402, 25, 412, 33548, 628, 220, 220, 220, 220, 220, 220, 220, 16409, 25, 198, 220, 220, 220, 220, 220, 220, 220, 220, 220, 220, 220, 357, 30388, 2599, 383, 25745, 62, 2127, 21052, 286, 428, 1395, 4029, 7449, 13, 220, 1303, 645, 20402, 25, 412, 33548, 198, 220, 220, 220, 220, 220, 220, 220, 37227, 198, 220, 220, 220, 220, 220, 220, 220, 1441, 2116, 13, 834, 1136, 62, 9186, 10786, 14933, 10223, 62, 2127, 21052, 11537, 628, 220, 220, 220, 2488, 14933, 10223, 62, 2127, 21052, 13, 2617, 353, 198, 220, 220, 220, 825, 25745, 62, 2127, 21052, 7, 944, 11, 1988, 2599, 198, 220, 220, 220, 220, 220, 220, 220, 37227, 50, 1039, 262, 25745, 62, 2127, 21052, 286, 428, 1395, 4029, 7449, 13, 220, 1303, 645, 20402, 25, 412, 33548, 198, 220, 220, 220, 220, 220, 220, 220, 37227, 198, 220, 220, 220, 220, 220, 220, 220, 1441, 2116, 13, 834, 2617, 62, 9186, 10786, 14933, 10223, 62, 2127, 21052, 3256, 1988, 8, 628, 220, 220, 220, 2488, 26745, 198, 220, 220, 220, 825, 25745, 62, 18747, 7, 944, 2599, 198, 220, 220, 220, 220, 220, 220, 220, 37227, 38, 1039, 262, 25745, 62, 18747, 286, 428, 1395, 4029, 7449, 13, 220, 1303, 645, 20402, 25, 412, 33548, 628, 220, 220, 220, 220, 220, 220, 220, 16409, 25, 198, 220, 220, 220, 220, 220, 220, 220, 220, 220, 220, 220, 29565, 600, 60, 2599, 383, 25745, 62, 18747, 286, 428, 1395, 4029, 7449, 13, 220, 1303, 645, 20402, 25, 412, 33548, 198, 220, 220, 220, 220, 220, 220, 220, 37227, 198, 220, 220, 220, 220, 220, 220, 220, 1441, 2116, 13, 834, 1136, 62, 9186, 10786, 14933, 10223, 62, 18747, 11537, 628, 220, 220, 220, 2488, 14933, 10223, 62, 18747, 13, 2617, 353, 198, 220, 220, 220, 825, 25745, 62, 18747, 7, 944, 11, 1988, 2599, 198, 220, 220, 220, 220, 220, 220, 220, 37227, 50, 1039, 262, 25745, 62, 18747, 286, 428, 1395, 4029, 7449, 13, 220, 1303, 645, 20402, 25, 412, 33548, 198, 220, 220, 220, 220, 220, 220, 220, 37227, 198, 220, 220, 220, 220, 220, 220, 220, 1441, 2116, 13, 834, 2617, 62, 9186, 10786, 14933, 10223, 62, 18747, 3256, 1988, 8, 628, 220, 220, 220, 2488, 26745, 198, 220, 220, 220, 825, 25745, 62, 29988, 1496, 62, 18747, 7, 944, 2599, 198, 220, 220, 220, 220, 220, 220, 220, 37227, 38, 1039, 262, 25745, 62, 29988, 1496, 62, 18747, 286, 428, 1395, 4029, 7449, 13, 220, 1303, 645, 20402, 25, 412, 33548, 628, 220, 220, 220, 220, 220, 220, 220, 16409, 25, 198, 220, 220, 220, 220, 220, 220, 220, 220, 220, 220, 220, 29565, 600, 60, 2599, 383, 25745, 62, 29988, 1496, 62, 18747, 286, 428, 1395, 4029, 7449, 13, 220, 1303, 645, 20402, 25, 412, 33548, 198, 220, 220, 220, 220, 220, 220, 220, 37227, 198, 220, 220, 220, 220, 220, 220, 220, 1441, 2116, 13, 834, 1136, 62, 9186, 10786, 14933, 10223, 62, 29988, 1496, 62, 18747, 11537, 628, 220, 220, 220, 2488, 14933, 10223, 62, 29988, 1496, 62, 18747, 13, 2617, 353, 198, 220, 220, 220, 825, 25745, 62, 29988, 1496, 62, 18747, 7, 944, 11, 1988, 2599, 198, 220, 220, 220, 220, 220, 220, 220, 37227, 50, 1039, 262, 25745, 62, 29988, 1496, 62, 18747, 286, 428, 1395, 4029, 7449, 13, 220, 1303, 645, 20402, 25, 412, 33548, 198, 220, 220, 220, 220, 220, 220, 220, 37227, 198, 220, 220, 220, 220, 220, 220, 220, 1441, 2116, 13, 834, 2617, 62, 9186, 10786, 14933, 10223, 62, 29988, 1496, 62, 18747, 3256, 1988, 8, 628, 220, 220, 220, 2488, 26745, 198, 220, 220, 220, 825, 21231, 62, 5907, 62, 8841, 7, 944, 2599, 198, 220, 220, 220, 220, 220, 220, 220, 37227, 38, 1039, 262, 21231, 62, 5907, 62, 8841, 286, 428, 1395, 4029, 7449, 13, 220, 1303, 645, 20402, 25, 412, 33548, 628, 220, 220, 220, 220, 220, 220, 220, 16409, 25, 198, 220, 220, 220, 220, 220, 220, 220, 220, 220, 220, 220, 357, 2536, 2599, 383, 21231, 62, 5907, 62, 8841, 286, 428, 1395, 4029, 7449, 13, 220, 1303, 645, 20402, 25, 412, 33548, 198, 220, 220, 220, 220, 220, 220, 220, 37227, 198, 220, 220, 220, 220, 220, 220, 220, 1441, 2116, 13, 834, 1136, 62, 9186, 10786, 40290, 62, 5907, 62, 8841, 11537, 628, 220, 220, 220, 2488, 40290, 62, 5907, 62, 8841, 13, 2617, 353, 198, 220, 220, 220, 825, 21231, 62, 5907, 62, 8841, 7, 944, 11, 1988, 2599, 198, 220, 220, 220, 220, 220, 220, 220, 37227, 50, 1039, 262, 21231, 62, 5907, 62, 8841, 286, 428, 1395, 4029, 7449, 13, 220, 1303, 645, 20402, 25, 412, 33548, 198, 220, 220, 220, 220, 220, 220, 220, 37227, 198, 220, 220, 220, 220, 220, 220, 220, 1441, 2116, 13, 834, 2617, 62, 9186, 10786, 40290, 62, 5907, 62, 8841, 3256, 1988, 8, 628, 220, 220, 220, 2488, 26745, 198, 220, 220, 220, 825, 21231, 62, 5907, 62, 17618, 7, 944, 2599, 198, 220, 220, 220, 220, 220, 220, 220, 37227, 38, 1039, 262, 21231, 62, 5907, 62, 17618, 286, 428, 1395, 4029, 7449, 13, 220, 1303, 645, 20402, 25, 412, 33548, 628, 220, 220, 220, 220, 220, 220, 220, 16409, 25, 198, 220, 220, 220, 220, 220, 220, 220, 220, 220, 220, 220, 357, 22468, 2599, 383, 21231, 62, 5907, 62, 17618, 286, 428, 1395, 4029, 7449, 13, 220, 1303, 645, 20402, 25, 412, 33548, 198, 220, 220, 220, 220, 220, 220, 220, 37227, 198, 220, 220, 220, 220, 220, 220, 220, 1441, 2116, 13, 834, 1136, 62, 9186, 10786, 40290, 62, 5907, 62, 17618, 11537, 628, 220, 220, 220, 2488, 40290, 62, 5907, 62, 17618, 13, 2617, 353, 198, 220, 220, 220, 825, 21231, 62, 5907, 62, 17618, 7, 944, 11, 1988, 2599, 198, 220, 220, 220, 220, 220, 220, 220, 37227, 50, 1039, 262, 21231, 62, 5907, 62, 17618, 286, 428, 1395, 4029, 7449, 13, 220, 1303, 645, 20402, 25, 412, 33548, 198, 220, 220, 220, 220, 220, 220, 220, 37227, 198, 220, 220, 220, 220, 220, 220, 220, 1441, 2116, 13, 834, 2617, 62, 9186, 10786, 40290, 62, 5907, 62, 17618, 3256, 1988, 8, 628, 220, 220, 220, 2488, 26745, 198, 220, 220, 220, 825, 21231, 62, 5907, 62, 41433, 7, 944, 2599, 198, 220, 220, 220, 220, 220, 220, 220, 37227, 38, 1039, 262, 21231, 62, 5907, 62, 41433, 286, 428, 1395, 4029, 7449, 13, 220, 1303, 645, 20402, 25, 412, 33548, 628, 220, 220, 220, 220, 220, 220, 220, 16409, 25, 198, 220, 220, 220, 220, 220, 220, 220, 220, 220, 220, 220, 357, 600, 2599, 383, 21231, 62, 5907, 62, 41433, 286, 428, 1395, 4029, 7449, 13, 220, 1303, 645, 20402, 25, 412, 33548, 198, 220, 220, 220, 220, 220, 220, 220, 37227, 198, 220, 220, 220, 220, 220, 220, 220, 1441, 2116, 13, 834, 1136, 62, 9186, 10786, 40290, 62, 5907, 62, 41433, 11537, 628, 220, 220, 220, 2488, 40290, 62, 5907, 62, 41433, 13, 2617, 353, 198, 220, 220, 220, 825, 21231, 62, 5907, 62, 41433, 7, 944, 11, 1988, 2599, 198, 220, 220, 220, 220, 220, 220, 220, 37227, 50, 1039, 262, 21231, 62, 5907, 62, 41433, 286, 428, 1395, 4029, 7449, 13, 220, 1303, 645, 20402, 25, 412, 33548, 198, 220, 220, 220, 220, 220, 220, 220, 37227, 198, 220, 220, 220, 220, 220, 220, 220, 1441, 2116, 13, 834, 2617, 62, 9186, 10786, 40290, 62, 5907, 62, 41433, 3256, 1988, 8, 628, 220, 220, 220, 2488, 26745, 198, 220, 220, 220, 825, 21231, 62, 5907, 62, 2127, 21052, 7, 944, 2599, 198, 220, 220, 220, 220, 220, 220, 220, 37227, 38, 1039, 262, 21231, 62, 5907, 62, 2127, 21052, 286, 428, 1395, 4029, 7449, 13, 220, 1303, 645, 20402, 25, 412, 33548, 628, 220, 220, 220, 220, 220, 220, 220, 16409, 25, 198, 220, 220, 220, 220, 220, 220, 220, 220, 220, 220, 220, 357, 30388, 2599, 383, 21231, 62, 5907, 62, 2127, 21052, 286, 428, 1395, 4029, 7449, 13, 220, 1303, 645, 20402, 25, 412, 33548, 198, 220, 220, 220, 220, 220, 220, 220, 37227, 198, 220, 220, 220, 220, 220, 220, 220, 1441, 2116, 13, 834, 1136, 62, 9186, 10786, 40290, 62, 5907, 62, 2127, 21052, 11537, 628, 220, 220, 220, 2488, 40290, 62, 5907, 62, 2127, 21052, 13, 2617, 353, 198, 220, 220, 220, 825, 21231, 62, 5907, 62, 2127, 21052, 7, 944, 11, 1988, 2599, 198, 220, 220, 220, 220, 220, 220, 220, 37227, 50, 1039, 262, 21231, 62, 5907, 62, 2127, 21052, 286, 428, 1395, 4029, 7449, 13, 220, 1303, 645, 20402, 25, 412, 33548, 198, 220, 220, 220, 220, 220, 220, 220, 37227, 198, 220, 220, 220, 220, 220, 220, 220, 1441, 2116, 13, 834, 2617, 62, 9186, 10786, 40290, 62, 5907, 62, 2127, 21052, 3256, 1988, 8, 628, 220, 220, 220, 2488, 26745, 198, 220, 220, 220, 825, 21231, 62, 5907, 62, 18747, 7, 944, 2599, 198, 220, 220, 220, 220, 220, 220, 220, 37227, 38, 1039, 262, 21231, 62, 5907, 62, 18747, 286, 428, 1395, 4029, 7449, 13, 220, 1303, 645, 20402, 25, 412, 33548, 628, 220, 220, 220, 220, 220, 220, 220, 16409, 25, 198, 220, 220, 220, 220, 220, 220, 220, 220, 220, 220, 220, 29565, 600, 60, 2599, 383, 21231, 62, 5907, 62, 18747, 286, 428, 1395, 4029, 7449, 13, 220, 1303, 645, 20402, 25, 412, 33548, 198, 220, 220, 220, 220, 220, 220, 220, 37227, 198, 220, 220, 220, 220, 220, 220, 220, 1441, 2116, 13, 834, 1136, 62, 9186, 10786, 40290, 62, 5907, 62, 18747, 11537, 628, 220, 220, 220, 2488, 40290, 62, 5907, 62, 18747, 13, 2617, 353, 198, 220, 220, 220, 825, 21231, 62, 5907, 62, 18747, 7, 944, 11, 1988, 2599, 198, 220, 220, 220, 220, 220, 220, 220, 37227, 50, 1039, 262, 21231, 62, 5907, 62, 18747, 286, 428, 1395, 4029, 7449, 13, 220, 1303, 645, 20402, 25, 412, 33548, 198, 220, 220, 220, 220, 220, 220, 220, 37227, 198, 220, 220, 220, 220, 220, 220, 220, 1441, 2116, 13, 834, 2617, 62, 9186, 10786, 40290, 62, 5907, 62, 18747, 3256, 1988, 8, 628, 220, 220, 220, 2488, 26745, 198, 220, 220, 220, 825, 21231, 62, 5907, 62, 29988, 1496, 62, 18747, 7, 944, 2599, 198, 220, 220, 220, 220, 220, 220, 220, 37227, 38, 1039, 262, 21231, 62, 5907, 62, 29988, 1496, 62, 18747, 286, 428, 1395, 4029, 7449, 13, 220, 1303, 645, 20402, 25, 412, 33548, 628, 220, 220, 220, 220, 220, 220, 220, 16409, 25, 198, 220, 220, 220, 220, 220, 220, 220, 220, 220, 220, 220, 29565, 600, 60, 2599, 383, 21231, 62, 5907, 62, 29988, 1496, 62, 18747, 286, 428, 1395, 4029, 7449, 13, 220, 1303, 645, 20402, 25, 412, 33548, 198, 220, 220, 220, 220, 220, 220, 220, 37227, 198, 220, 220, 220, 220, 220, 220, 220, 1441, 2116, 13, 834, 1136, 62, 9186, 10786, 40290, 62, 5907, 62, 29988, 1496, 62, 18747, 11537, 628, 220, 220, 220, 2488, 40290, 62, 5907, 62, 29988, 1496, 62, 18747, 13, 2617, 353, 198, 220, 220, 220, 825, 21231, 62, 5907, 62, 29988, 1496, 62, 18747, 7, 944, 11, 1988, 2599, 198, 220, 220, 220, 220, 220, 220, 220, 37227, 50, 1039, 262, 21231, 62, 5907, 62, 29988, 1496, 62, 18747, 286, 428, 1395, 4029, 7449, 13, 220, 1303, 645, 20402, 25, 412, 33548, 198, 220, 220, 220, 220, 220, 220, 220, 37227, 198, 220, 220, 220, 220, 220, 220, 220, 1441, 2116, 13, 834, 2617, 62, 9186, 10786, 40290, 62, 5907, 62, 29988, 1496, 62, 18747, 3256, 1988, 8, 628, 220, 220, 220, 825, 284, 62, 11600, 7, 944, 2599, 198, 220, 220, 220, 220, 220, 220, 220, 37227, 35561, 262, 2746, 6608, 355, 257, 8633, 37811, 198, 220, 220, 220, 220, 220, 220, 220, 1441, 2746, 62, 1462, 62, 11600, 7, 944, 11, 11389, 1096, 28, 25101, 8, 628, 220, 220, 220, 825, 284, 62, 2536, 7, 944, 2599, 198, 220, 220, 220, 220, 220, 220, 220, 37227, 35561, 262, 4731, 10552, 286, 262, 2746, 37811, 198, 220, 220, 220, 220, 220, 220, 220, 1441, 279, 4798, 13, 79, 18982, 7, 944, 13, 1462, 62, 11600, 28955, 628, 220, 220, 220, 825, 11593, 260, 1050, 834, 7, 944, 2599, 198, 220, 220, 220, 220, 220, 220, 220, 37227, 1890, 4600, 4798, 63, 290, 4600, 381, 22272, 63, 37811, 198, 220, 220, 220, 220, 220, 220, 220, 1441, 2116, 13, 1462, 62, 2536, 3419, 628, 220, 220, 220, 825, 11593, 27363, 834, 7, 944, 11, 584, 2599, 198, 220, 220, 220, 220, 220, 220, 220, 37227, 35561, 2081, 611, 1111, 5563, 389, 4961, 37811, 198, 220, 220, 220, 220, 220, 220, 220, 611, 407, 318, 39098, 7, 847, 11, 1395, 4029, 7449, 2599, 198, 220, 220, 220, 220, 220, 220, 220, 220, 220, 220, 220, 1441, 10352, 628, 220, 220, 220, 220, 220, 220, 220, 611, 407, 900, 7, 944, 13557, 7890, 62, 8095, 13, 13083, 28955, 6624, 900, 7, 847, 13557, 7890, 62, 8095, 13, 13083, 3419, 2599, 198, 220, 220, 220, 220, 220, 220, 220, 220, 220, 220, 220, 1441, 10352, 198, 220, 220, 220, 220, 220, 220, 220, 329, 4808, 7785, 62, 3672, 11, 428, 62, 2100, 287, 2237, 13, 2676, 23814, 7, 944, 13557, 7890, 62, 8095, 2599, 198, 220, 220, 220, 220, 220, 220, 220, 220, 220, 220, 220, 326, 62, 2100, 796, 584, 13557, 7890, 62, 8095, 29795, 7785, 62, 3672, 60, 198, 220, 220, 220, 220, 220, 220, 220, 220, 220, 220, 220, 3858, 796, 900, 3419, 198, 220, 220, 220, 220, 220, 220, 220, 220, 220, 220, 220, 3858, 13, 2860, 7, 5661, 62, 2100, 13, 834, 4871, 834, 8, 198, 220, 220, 220, 220, 220, 220, 220, 220, 220, 220, 220, 3858, 13, 2860, 7, 5562, 62, 2100, 13, 834, 4871, 834, 8, 198, 220, 220, 220, 220, 220, 220, 220, 220, 220, 220, 220, 410, 874, 62, 40496, 796, 428, 62, 2100, 6624, 326, 62, 2100, 198, 220, 220, 220, 220, 220, 220, 220, 220, 220, 220, 220, 611, 357, 1662, 2237, 13, 47, 56, 18, 290, 198, 220, 220, 220, 220, 220, 220, 220, 220, 220, 220, 220, 220, 220, 220, 220, 220, 220, 220, 220, 18896, 7, 19199, 8, 6624, 362, 290, 28000, 1098, 287, 3858, 2599, 220, 1303, 645, 20402, 25, 376, 23, 2481, 198, 220, 220, 220, 220, 220, 220, 220, 220, 220, 220, 220, 220, 220, 220, 220, 410, 874, 62, 40496, 796, 357, 198, 220, 220, 220, 220, 220, 220, 220, 220, 220, 220, 220, 220, 220, 220, 220, 220, 220, 220, 220, 428, 62, 2100, 13, 268, 8189, 10786, 40477, 12, 23, 11537, 6624, 326, 62, 2100, 13, 268, 8189, 10786, 40477, 12, 23, 11537, 198, 220, 220, 220, 220, 220, 220, 220, 220, 220, 220, 220, 220, 220, 220, 220, 1267, 198, 220, 220, 220, 220, 220, 220, 220, 220, 220, 220, 220, 611, 407, 410, 874, 62, 40496, 25, 198, 220, 220, 220, 220, 220, 220, 220, 220, 220, 220, 220, 220, 220, 220, 220, 1441, 10352, 198, 220, 220, 220, 220, 220, 220, 220, 1441, 6407, 628, 220, 220, 220, 825, 11593, 710, 834, 7, 944, 11, 584, 2599, 198, 220, 220, 220, 220, 220, 220, 220, 37227, 35561, 2081, 611, 1111, 5563, 389, 407, 4961, 37811, 198, 220, 220, 220, 220, 220, 220, 220, 1441, 407, 2116, 6624, 584, 198 ]
2.241857
10,684
""" Die Modelle für Projektweite Daten: Nutzer/Profile """ from django.db import models from django.contrib.auth.models import AbstractUser from django.conf import settings from django.utils.translation import ugettext as _ from userena.models import UserenaBaseProfile from django.core.validators import RegexValidator import random, string from django.template.defaultfilters import slugify from django.urls import reverse def knoepfe_kopf(user): """ gibt Knöpfe für Kopfleiste als Liste von Tupeln zurück """ anmelden = (reverse('userena_signin'), 'Anmelden') registrieren = (reverse('userena_signup'), 'Registrieren') abmelden = (reverse('userena_signout'), 'Abmelden') profil = lambda nutzer: (reverse('userena_profile_detail', kwargs={'username': nutzer.username}), 'Profil') spam = ('spam', 'spam') admin = ('/admin/', 'admin') if user.username == 'admin': liste = [abmelden, profil(user), spam] elif user.is_authenticated(): liste = [abmelden, profil(user)] else: liste = [anmelden, registrieren] if user.is_staff and user.get_all_permissions(): liste.append(admin) return liste def knoepfe_menü(user): """ gibt Knöpfe für Menüleiste als Liste von Tupeln zurück """ alle = { 'index': ('/', 'Startseite'), 'olymp': (reverse('Wettbewerbe:index'), 'Wettbewerbe'), 'ehemalige': (reverse('Ehemalige:index'), 'Ehemalige'), 'impressum': (reverse('impressum'), 'Impressum'), 'db': ('https://olymp.piokg.de/static/db.pdf', 'Datenbanklayout'), # quick and very dirty :) 'todo': ('/todo/', 'ToDo-Liste'), } if user.username == 'admin': return [alle[name] for name in ('index', 'olymp', 'ehemalige', 'todo', 'db')] else: return [alle[name] for name in ('index', 'olymp', 'db', 'impressum')] class Nutzer(AbstractUser): """ Nutzer-Klasse """ def knoepfe_kopf(nutzer): """ soll Liste von Paaren für Knöpfe der Kopfleiste ausgeben Nutzt im Moment die module-fkt gleichen Namens, könnte später vll die Gruppenzugehörigkeit heranziehen, etc, ist flexibel """ return knoepfe_kopf(nutzer) def knoepfe_menü(self): """ soll Liste von Paaren für Knöpfe der Menüleiste ausgeben Nutzt im Moment die module-fkt gleichen Namens, könnte später vll die Gruppenzugehörigkeit heranziehen, etc, ist flexibel """ return knoepfe_menü(self)
[ 37811, 198, 32423, 9104, 293, 277, 25151, 1041, 73, 988, 83, 732, 578, 16092, 268, 25, 11959, 9107, 14, 37046, 198, 198, 37811, 198, 198, 6738, 42625, 14208, 13, 9945, 1330, 4981, 198, 6738, 42625, 14208, 13, 3642, 822, 13, 18439, 13, 27530, 1330, 27741, 12982, 198, 6738, 42625, 14208, 13, 10414, 1330, 6460, 198, 6738, 42625, 14208, 13, 26791, 13, 41519, 1330, 334, 1136, 5239, 355, 4808, 198, 6738, 779, 918, 64, 13, 27530, 1330, 5765, 918, 64, 14881, 37046, 198, 6738, 42625, 14208, 13, 7295, 13, 12102, 2024, 1330, 797, 25636, 47139, 1352, 198, 11748, 4738, 11, 4731, 198, 6738, 42625, 14208, 13, 28243, 13, 12286, 10379, 1010, 1330, 31065, 1958, 198, 6738, 42625, 14208, 13, 6371, 82, 1330, 9575, 628, 198, 198, 4299, 638, 78, 538, 5036, 62, 74, 404, 69, 7, 7220, 2599, 198, 220, 220, 220, 37227, 46795, 83, 6102, 9101, 79, 5036, 277, 25151, 40500, 27919, 40833, 435, 82, 7343, 68, 18042, 49595, 45542, 1976, 333, 9116, 694, 37227, 198, 220, 220, 220, 281, 1326, 335, 268, 796, 357, 50188, 10786, 1904, 918, 64, 62, 12683, 259, 33809, 705, 2025, 1326, 335, 268, 11537, 198, 220, 220, 220, 4214, 380, 14226, 796, 357, 50188, 10786, 1904, 918, 64, 62, 12683, 929, 33809, 705, 8081, 396, 380, 14226, 11537, 220, 198, 220, 220, 220, 450, 1326, 335, 268, 796, 357, 50188, 10786, 1904, 918, 64, 62, 12683, 448, 33809, 705, 4826, 1326, 335, 268, 11537, 198, 220, 220, 220, 1534, 346, 796, 37456, 6701, 9107, 25, 357, 50188, 10786, 1904, 918, 64, 62, 13317, 62, 49170, 3256, 220, 198, 220, 220, 220, 220, 220, 220, 220, 220, 220, 220, 220, 220, 220, 220, 220, 220, 220, 220, 220, 479, 86, 22046, 34758, 6, 29460, 10354, 6701, 9107, 13, 29460, 92, 828, 705, 2964, 10379, 11537, 220, 198, 220, 220, 220, 18084, 796, 19203, 2777, 321, 3256, 705, 2777, 321, 11537, 220, 198, 220, 220, 220, 13169, 796, 19203, 14, 28482, 14, 3256, 705, 28482, 11537, 198, 220, 220, 220, 220, 198, 220, 220, 220, 611, 2836, 13, 29460, 6624, 705, 28482, 10354, 198, 220, 220, 220, 220, 220, 220, 220, 1351, 68, 796, 685, 397, 1326, 335, 268, 11, 1534, 346, 7, 7220, 828, 18084, 60, 220, 220, 220, 220, 220, 220, 220, 220, 198, 220, 220, 220, 1288, 361, 2836, 13, 271, 62, 41299, 3474, 33529, 198, 220, 220, 220, 220, 220, 220, 220, 1351, 68, 796, 685, 397, 1326, 335, 268, 11, 1534, 346, 7, 7220, 15437, 198, 220, 220, 220, 2073, 25, 198, 220, 220, 220, 220, 220, 220, 220, 1351, 68, 796, 685, 272, 1326, 335, 268, 11, 4214, 380, 14226, 60, 198, 220, 220, 220, 611, 2836, 13, 271, 62, 28120, 290, 2836, 13, 1136, 62, 439, 62, 525, 8481, 33529, 198, 220, 220, 220, 220, 220, 220, 220, 1351, 68, 13, 33295, 7, 28482, 8, 198, 220, 220, 220, 220, 198, 220, 220, 220, 1441, 1351, 68, 198, 198, 4299, 638, 78, 538, 5036, 62, 3653, 9116, 7, 7220, 2599, 198, 220, 220, 220, 37227, 46795, 83, 6102, 9101, 79, 5036, 277, 25151, 6065, 9116, 293, 40833, 435, 82, 7343, 68, 18042, 49595, 45542, 1976, 333, 9116, 694, 37227, 198, 220, 220, 220, 28654, 796, 1391, 198, 220, 220, 220, 220, 220, 220, 220, 705, 9630, 10354, 19203, 14, 3256, 705, 10434, 325, 578, 33809, 220, 198, 220, 220, 220, 220, 220, 220, 220, 705, 3366, 3149, 10354, 357, 50188, 10786, 54, 3087, 65, 413, 263, 1350, 25, 9630, 33809, 705, 54, 3087, 65, 413, 263, 1350, 33809, 220, 198, 220, 220, 220, 220, 220, 220, 220, 705, 68, 4411, 282, 10045, 10354, 357, 50188, 10786, 36, 4411, 282, 10045, 25, 9630, 33809, 705, 36, 4411, 282, 10045, 33809, 198, 220, 220, 220, 220, 220, 220, 220, 705, 320, 8439, 388, 10354, 357, 50188, 10786, 320, 8439, 388, 33809, 705, 26950, 601, 388, 33809, 198, 220, 220, 220, 220, 220, 220, 220, 705, 9945, 10354, 19203, 5450, 1378, 3366, 3149, 13, 14415, 482, 70, 13, 2934, 14, 12708, 14, 9945, 13, 12315, 3256, 705, 27354, 268, 17796, 39786, 33809, 1303, 2068, 290, 845, 11841, 14373, 198, 220, 220, 220, 220, 220, 220, 220, 705, 83, 24313, 10354, 19203, 14, 83, 24313, 14, 3256, 705, 2514, 5211, 12, 8053, 68, 33809, 198, 220, 220, 220, 1782, 198, 220, 220, 220, 220, 198, 220, 220, 220, 611, 2836, 13, 29460, 6624, 705, 28482, 10354, 198, 220, 220, 220, 220, 220, 220, 220, 1441, 685, 6765, 58, 3672, 60, 329, 1438, 287, 19203, 9630, 3256, 705, 3366, 3149, 3256, 705, 68, 4411, 282, 10045, 3256, 705, 83, 24313, 3256, 705, 9945, 11537, 60, 198, 220, 220, 220, 2073, 25, 198, 220, 220, 220, 220, 220, 220, 220, 1441, 685, 6765, 58, 3672, 60, 329, 1438, 287, 19203, 9630, 3256, 705, 3366, 3149, 3256, 705, 9945, 3256, 705, 320, 8439, 388, 11537, 60, 198, 220, 220, 220, 220, 220, 220, 220, 220, 198, 198, 4871, 11959, 9107, 7, 23839, 12982, 2599, 198, 220, 220, 220, 37227, 11959, 9107, 12, 42, 75, 21612, 37227, 198, 220, 220, 220, 825, 638, 78, 538, 5036, 62, 74, 404, 69, 7, 14930, 9107, 2599, 198, 220, 220, 220, 220, 220, 220, 220, 37227, 523, 297, 7343, 68, 18042, 11243, 5757, 277, 25151, 6102, 9101, 79, 5036, 4587, 40500, 27919, 40833, 257, 385, 469, 11722, 220, 198, 220, 220, 220, 220, 220, 220, 220, 11959, 89, 83, 545, 29278, 4656, 8265, 12, 69, 21841, 26852, 41437, 17871, 641, 11, 479, 48863, 429, 68, 599, 11033, 353, 410, 297, 198, 220, 220, 220, 220, 220, 220, 220, 4656, 25665, 381, 19471, 2217, 71, 9101, 4359, 365, 270, 607, 35410, 494, 831, 11, 3503, 11, 318, 83, 7059, 43837, 37227, 198, 220, 220, 220, 220, 220, 220, 220, 1441, 638, 78, 538, 5036, 62, 74, 404, 69, 7, 14930, 9107, 8, 628, 220, 220, 220, 825, 638, 78, 538, 5036, 62, 3653, 9116, 7, 944, 2599, 198, 220, 220, 220, 220, 220, 220, 220, 37227, 523, 297, 7343, 68, 18042, 11243, 5757, 277, 25151, 6102, 9101, 79, 5036, 4587, 6065, 9116, 293, 40833, 257, 385, 469, 11722, 220, 198, 220, 220, 220, 220, 220, 220, 220, 11959, 89, 83, 545, 29278, 4656, 8265, 12, 69, 21841, 26852, 41437, 17871, 641, 11, 479, 48863, 429, 68, 599, 11033, 353, 410, 297, 198, 220, 220, 220, 220, 220, 220, 220, 4656, 25665, 381, 19471, 2217, 71, 9101, 4359, 365, 270, 607, 35410, 494, 831, 11, 3503, 11, 318, 83, 7059, 43837, 37227, 198, 220, 220, 220, 220, 220, 220, 220, 1441, 638, 78, 538, 5036, 62, 3653, 9116, 7, 944, 8, 198, 220, 220, 220, 220, 198, 220, 220, 220, 220, 198 ]
2.281982
1,110
import numpy as np import cv2 import sys import torch sys.path.append('..') from torch.utils import data from torch.utils.data import DataLoader if __name__ == '__main__': file_list = './data/test_data/list.txt' wlfwdataset = WLFWDatasets(file_list) dataloader = DataLoader(wlfwdataset, batch_size=256, shuffle=True, num_workers=0, drop_last=False) for img, landmark, attribute, euler_angle in dataloader: print("img shape", img.shape) print("landmark size", landmark.size()) print("attrbute size", attribute) print("euler_angle", euler_angle.size())
[ 11748, 299, 32152, 355, 45941, 198, 11748, 269, 85, 17, 198, 11748, 25064, 198, 11748, 28034, 198, 198, 17597, 13, 6978, 13, 33295, 10786, 492, 11537, 198, 198, 6738, 28034, 13, 26791, 1330, 1366, 198, 6738, 28034, 13, 26791, 13, 7890, 1330, 6060, 17401, 628, 628, 628, 628, 628, 628, 628, 198, 361, 11593, 3672, 834, 6624, 705, 834, 12417, 834, 10354, 198, 220, 220, 220, 2393, 62, 4868, 796, 705, 19571, 7890, 14, 9288, 62, 7890, 14, 4868, 13, 14116, 6, 198, 220, 220, 220, 266, 1652, 16993, 265, 292, 316, 796, 370, 43, 37, 22332, 265, 292, 1039, 7, 7753, 62, 4868, 8, 198, 220, 220, 220, 4818, 282, 1170, 263, 796, 6060, 17401, 7, 86, 1652, 16993, 265, 292, 316, 11, 15458, 62, 7857, 28, 11645, 11, 36273, 28, 17821, 11, 997, 62, 22896, 28, 15, 11, 4268, 62, 12957, 28, 25101, 8, 198, 220, 220, 220, 329, 33705, 11, 20533, 11, 11688, 11, 304, 18173, 62, 9248, 287, 4818, 282, 1170, 263, 25, 198, 220, 220, 220, 220, 220, 220, 220, 3601, 7203, 9600, 5485, 1600, 33705, 13, 43358, 8, 198, 220, 220, 220, 220, 220, 220, 220, 3601, 7203, 1044, 4102, 2546, 1600, 20533, 13, 7857, 28955, 198, 220, 220, 220, 220, 220, 220, 220, 3601, 7203, 1078, 26145, 1133, 2546, 1600, 11688, 8, 198, 220, 220, 220, 220, 220, 220, 220, 3601, 7203, 68, 18173, 62, 9248, 1600, 304, 18173, 62, 9248, 13, 7857, 28955, 198 ]
2.541322
242
import os import numpy as np import pytest from nexusformat.nexus.tree import NXfield, NXgroup, NXroot, nxload @pytest.mark.parametrize("save", ["False", "True"])
[ 11748, 28686, 198, 198, 11748, 299, 32152, 355, 45941, 198, 11748, 12972, 9288, 198, 6738, 45770, 18982, 13, 44520, 13, 21048, 1330, 42482, 3245, 11, 42482, 8094, 11, 42482, 15763, 11, 299, 87, 2220, 628, 198, 198, 31, 9078, 9288, 13, 4102, 13, 17143, 316, 380, 2736, 7203, 21928, 1600, 14631, 25101, 1600, 366, 17821, 8973, 8, 198 ]
2.87931
58