



'''simple docstring'''




import argparse
import json
import re
import string
import sys

import numpy as np


a  :     Any       =       0.5



def  __lowerCamelCase    (   _lowercase      ,							_lowercase						) ->     str:
							UpperCAmelCase	:						Optional[Any]					=						[""".""", """,""", """;""", """:"""]

							for token in remove_tokens:
														UpperCAmelCase	:						List[Any]					=						ground_truth.replace(_lowercase      ,							""""""						)
														UpperCAmelCase	:						List[str]					=						prediction.replace(_lowercase      ,							""""""						)

							UpperCAmelCase	,	UpperCAmelCase	:						Union[str, Any]					=						ground_truth.lower(), prediction.lower()
							UpperCAmelCase	,	UpperCAmelCase	:						Tuple					=						ground_truth.replace("""/"""      ,							""" """						), prediction.replace("""/"""      ,							""" """						)
							UpperCAmelCase	,	UpperCAmelCase	:						List[str]					=						set(ground_truth.split(""" """						)						), set(prediction.split(""" """						)						)

							UpperCAmelCase	:						Optional[Any]					=						ground_truth.intersection(_lowercase						)
							UpperCAmelCase	:						List[str]					=						ground_truth.union(_lowercase						)
							UpperCAmelCase	:						int					=						len(_lowercase						) / len(_lowercase						)
							return jaccard



def  __lowerCamelCase    (   _lowercase						) ->     Any:

							def remove_articles(_lowercase						):
														return re.sub(R"""\b(a|an|the)\b"""      ,							""" """      ,							_lowercase						)

							def white_space_fix(_lowercase						):
														return " ".join(text.split()						)

							def remove_punc(_lowercase						):
														UpperCAmelCase	:						Dict					=						set(string.punctuation						)
														return "".join(ch for ch in text if ch not in exclude						)

							def lower(_lowercase						):
														return text.lower()

							return white_space_fix(remove_articles(remove_punc(lower(_lowercase						)						)						)						)



def  __lowerCamelCase    (   _lowercase      ,							_lowercase      ,							_lowercase						) ->     Optional[int]:
							UpperCAmelCase	,	UpperCAmelCase	,	UpperCAmelCase	:						List[str]					=						0, 0, 0

							UpperCAmelCase	:						Dict					=						"""Parties""" in qa_id

							# first check if ground truth is empty
							if len(_lowercase						) == 0:
														if len(_lowercase						) > 0:
																					fp += len(_lowercase						)  # false positive for each one
							else:
														for ground_truth in ground_truths:
																					assert len(_lowercase						) > 0
																					# check if there is a match
																					UpperCAmelCase	:						Any					=						False
																					for pred in predictions:
																												if substr_ok:
																																			UpperCAmelCase	:						Dict					=						get_jaccard(_lowercase      ,							_lowercase						) >= IOU_THRESH or ground_truth in pred
																												else:
																																			UpperCAmelCase	:						Tuple					=						get_jaccard(_lowercase      ,							_lowercase						) >= IOU_THRESH
																												if is_match:
																																			UpperCAmelCase	:						int					=						True

																					if match_found:
																												tp += 1
																					else:
																												fn += 1

        # now also get any fps by looping through preds
														for pred in predictions:
																					# Check if there's a match. if so, don't count (don't want to double count based on the above)
																					# but if there's no match, then this is a false positive.
																					# (Note: we get the true positives in the above loop instead of this loop so that we don't double count
																					# multiple predictions that are matched with the same answer.)
																					UpperCAmelCase	:						Optional[Any]					=						False
																					for ground_truth in ground_truths:
																												assert len(_lowercase						) > 0
																												if substr_ok:
																																			UpperCAmelCase	:						Union[str, Any]					=						get_jaccard(_lowercase      ,							_lowercase						) >= IOU_THRESH or ground_truth in pred
																												else:
																																			UpperCAmelCase	:						str					=						get_jaccard(_lowercase      ,							_lowercase						) >= IOU_THRESH
																												if is_match:
																																			UpperCAmelCase	:						Optional[Any]					=						True

																					if not match_found:
																												fp += 1

							UpperCAmelCase	:						int					=						tp / (tp + fp) if tp + fp > 0 else np.nan
							UpperCAmelCase	:						int					=						tp / (tp + fn) if tp + fn > 0 else np.nan

							return precision, recall



def  __lowerCamelCase    (   _lowercase						) ->     Optional[int]:
							UpperCAmelCase	:						Union[str, Any]					=						precisions[::-1]
							for i in range(1      ,							len(_lowercase						)						):
														UpperCAmelCase	:						Optional[int]					=						max(precision_best[i - 1]      ,							precision_best[i]						)
							UpperCAmelCase	:						str					=						precision_best[::-1]
							return precisions



def  __lowerCamelCase    (   _lowercase      ,							_lowercase						) ->     Union[str, Any]:
							UpperCAmelCase	:						List[Any]					=						process_precisions(_lowercase						)
							UpperCAmelCase	:						Tuple					=						np.trapz(_lowercase      ,							_lowercase						)
							if np.isnan(_lowercase						):
														return 0
							return aupr



def  __lowerCamelCase    (   _lowercase      ,							_lowercase      ,							_lowercase						) ->     List[Any]:
							UpperCAmelCase	:						List[str]					=						process_precisions(_lowercase						)
							UpperCAmelCase	:						Optional[Any]					=						0
							for prec, recall in zip(_lowercase      ,							_lowercase						):
														if recall >= recall_thresh:
																					UpperCAmelCase	:						List[str]					=						prec
																					break
							return prec_at_recall



def  __lowerCamelCase    (   _lowercase      ,							_lowercase						) ->     List[Any]:
							return normalize_answer(_lowercase						) == normalize_answer(_lowercase						)



def  __lowerCamelCase    (   _lowercase      ,							_lowercase      ,							_lowercase						) ->     int:
							UpperCAmelCase	:						int					=						0
							for pred in predictions:
														for ground_truth in ground_truths:
																					UpperCAmelCase	:						Optional[int]					=						metric_fn(_lowercase      ,							_lowercase						)
																					if score == 1:  # break the loop when one prediction matches the ground truth
																												break
														if score == 1:
																					break
							return score



def  __lowerCamelCase    (   _lowercase      ,							_lowercase						) ->     Dict:
							UpperCAmelCase	:						Optional[int]					=						0
							UpperCAmelCase	:						Union[str, Any]					=						[]
							UpperCAmelCase	:						List[Any]					=						[]
							for article in dataset:
														for paragraph in article["paragraphs"]:
																					for qa in paragraph["qas"]:
																												total += 1
																												if qa["id"] not in predictions:
																																			UpperCAmelCase	:						str					=						"""Unanswered question """ + qa["""id"""] + """ will receive score 0."""
																																			print(_lowercase      ,							file=sys.stderr						)
																																			continue
																												UpperCAmelCase	:						str					=						[x["""text"""] for x in qa["""answers"""]]
																												UpperCAmelCase	:						Optional[Any]					=						predictions[qa["""id"""]]
																												UpperCAmelCase	,	UpperCAmelCase	:						int					=						compute_precision_recall(_lowercase      ,							_lowercase      ,							qa["""id"""]						)

																												precisions.append(_lowercase						)
																												recalls.append(_lowercase						)

																												if precision == 0 and recall == 0:
																																			fa += 0
																												else:
																																			fa += 2 * (precision * recall) / (precision + recall)

																												exact_match += metric_max_over_ground_truths(_lowercase      ,							_lowercase      ,							_lowercase						)

							UpperCAmelCase	:						int					=						[x for _, x in sorted(zip(_lowercase      ,							_lowercase						)						)]
							recalls.sort()

							UpperCAmelCase	:						int					=						100.0 * fa / total
							UpperCAmelCase	:						Optional[int]					=						100.0 * exact_match / total
							UpperCAmelCase	:						List[Any]					=						get_aupr(_lowercase      ,							_lowercase						)

							UpperCAmelCase	:						Dict					=						get_prec_at_recall(_lowercase      ,							_lowercase      ,							recall_thresh=0.9						)
							UpperCAmelCase	:						Union[str, Any]					=						get_prec_at_recall(_lowercase      ,							_lowercase      ,							recall_thresh=0.8						)

							return {
							    "exact_match": exact_match,
							    "f1": fa,
							    "aupr": aupr,
							    "prec_at_80_recall": prec_at_aa_recall,
							    "prec_at_90_recall": prec_at_aa_recall,
							}


if __name__ == "__main__":
							a  :     List[Any]       =       argparse.ArgumentParser(description="""Evaluation for CUAD""")
							parser.add_argument("""dataset_file""", help="""Dataset file""")
							parser.add_argument("""prediction_file""", help="""Prediction File""")
							a  :     List[Any]       =       parser.parse_args()
							with open(args.dataset_file) as dataset_file:
														a  :     Optional[int]       =       json.load(dataset_file)
														a  :     Dict       =       dataset_json["""data"""]
							with open(args.prediction_file) as prediction_file:
														a  :     List[Any]       =       json.load(prediction_file)
							print(json.dumps(evaluate(dataset, predictions)))






'''simple docstring'''




import sys



def  __lowerCamelCase    (   _lowercase      ,							_lowercase						) ->     int:
							if not numbers:
														return 0
							if target == 0 and target in numbers:
														return 0
							if not isinstance(_lowercase      ,							(list, tuple)						) or not all(
							    isinstance(_lowercase      ,							_lowercase						) for number in numbers						):
														raise ValueError("""numbers must be an iterable of integers"""						)

							UpperCAmelCase	:						Optional[Any]					=						0
							UpperCAmelCase	:						List[str]					=						sys.maxsize

							while right < len(_lowercase						):
														curr_sum += numbers[right]
														while curr_sum >= target and left <= right:
																					UpperCAmelCase	:						Optional[Any]					=						min(_lowercase      ,							right - left + 1						)
																					curr_sum -= numbers[left]
																					left += 1
														right += 1

							return 0 if min_len == sys.maxsize else min_len

