





'''simple docstring'''


import numpy as np




def    __a (     UpperCAmelCase       ,			UpperCAmelCase       ,			UpperCAmelCase    )      ->List[Any]:



	"""simple docstring"""







	A							  =      n_draws * class_counts / class_counts.sum()
	# floored means we don't overshoot n_samples, but probably undershoot
	A							  =      np.floor(UpperCAmelCase    )
	# we add samples according to how much "left over" probability
	# they had, until we arrive at n_samples
	A							  =      int(n_draws - floored.sum()    )
	if need_to_add > 0:
		A							  =      continuous - floored
		A							  =      np.sort(np.unique(UpperCAmelCase    )    )[::-1]
		# add according to remainder, but break ties
		# randomly to avoid biases
		for value in values:
			((A)  ,    )							  =      np.where(remainder == value    )
			# if we need_to_add less than what's in inds
			# we draw randomly from them.
			# if we need to add more, we add them all and
			# go to the next value
			A							  =      min(len(UpperCAmelCase    )       ,			UpperCAmelCase    )
			A							  =      rng.choice(UpperCAmelCase       ,			size=UpperCAmelCase       ,			replace=UpperCAmelCase    )
			floored[inds] += 1
			need_to_add -= add_now
			if need_to_add == 0:
				break
	return floored.astype(np.intaa    )




def    __a (     UpperCAmelCase       ,			UpperCAmelCase       ,			UpperCAmelCase       ,			UpperCAmelCase       ,			UpperCAmelCase=10    )      ->List[Any]:



	"""simple docstring"""







	A  ,    A							  =      np.unique(UpperCAmelCase       ,			return_inverse=UpperCAmelCase    )
	A							  =      classes.shape[0]
	A							  =      np.bincount(UpperCAmelCase    )
	if np.min(UpperCAmelCase    ) < 2:
		raise ValueError("""Minimum class count error"""    )
	if n_train < n_classes:
		raise ValueError(
		    """The train_size = %d should be greater or """ """equal to the number of classes = %d""" % (n_train, n_classes)    )
	if n_test < n_classes:
		raise ValueError(
		    """The test_size = %d should be greater or """ """equal to the number of classes = %d""" % (n_test, n_classes)    )
	A							  =      np.split(np.argsort(UpperCAmelCase       ,			kind="""mergesort"""    )       ,			np.cumsum(UpperCAmelCase    )[:-1]    )
	for _ in range(UpperCAmelCase    ):
		A							  =      approximate_mode(UpperCAmelCase       ,			UpperCAmelCase       ,			UpperCAmelCase    )
		A							  =      class_counts - n_i
		A							  =      approximate_mode(UpperCAmelCase       ,			UpperCAmelCase       ,			UpperCAmelCase    )

		A							  =      []
		A							  =      []

		for i in range(UpperCAmelCase    ):
			A							  =      rng.permutation(class_counts[i]    )
			A							  =      class_indices[i].take(UpperCAmelCase       ,			mode="""clip"""    )
			train.extend(perm_indices_class_i[: n_i[i]]    )
			test.extend(perm_indices_class_i[n_i[i] : n_i[i] + t_i[i]]    )
		A							  =      rng.permutation(UpperCAmelCase    )
		A							  =      rng.permutation(UpperCAmelCase    )

		yield train, test








'''simple docstring'''


import hashlib
import importlib.util
import json
import os
import pathlib
from types import ModuleType

import pytest
import requests

_lowerCamelCase				:	Optional[Any]				    =       pathlib.Path.cwd().joinpath('project_euler')
_lowerCamelCase				:	Optional[int]				    =       pathlib.Path.cwd().joinpath(
    'scripts', 'project_euler_answers.json'
)

with open(PROJECT_EULER_ANSWERS_PATH) as file_handle:
				_lowerCamelCase				:	dict[str, str]				    =       json.load(file_handle)




def    __a (     UpperCAmelCase    )      ->ModuleType:



	"""simple docstring"""







	A							  =      importlib.util.spec_from_file_location(file_path.name       ,			str(UpperCAmelCase    )    )
	A							  =      importlib.util.module_from_spec(UpperCAmelCase    )  # type: ignore
	spec.loader.exec_module(UpperCAmelCase    )  # type: ignore
	return module




def    __a (     )      ->list[pathlib.Path]:



	"""simple docstring"""







	A							  =      []
	for problem_dir_path in PROJECT_EULER_DIR_PATH.iterdir():
		if problem_dir_path.is_file() or problem_dir_path.name.startswith("""_"""    ):
			continue
		for file_path in problem_dir_path.iterdir():
			if file_path.suffix != ".py" or file_path.name.startswith(("""_""", """test""")    ):
				continue
			solution_file_paths.append(UpperCAmelCase    )
	return solution_file_paths




def    __a (     )      ->str:



	"""simple docstring"""







	with open(os.environ["""GITHUB_EVENT_PATH"""]    ) as file:
		A							  =      json.load(UpperCAmelCase    )
	return event["pull_request"]["url"] + "/files"




def    __a (     )      ->list[pathlib.Path]:



	"""simple docstring"""







	A							  =      []
	A							  =      {
	    """Accept""": """application/vnd.github.v3+json""",
	    """Authorization""": """token """ + os.environ["""GITHUB_TOKEN"""],
	}
	A							  =      requests.get(get_files_url()       ,			headers=UpperCAmelCase    ).json()
	for file in files:
		A							  =      pathlib.Path.cwd().joinpath(file["""filename"""]    )
		if (
		    filepath.suffix != ".py"
		    or filepath.name.startswith(("""_""", """test""")    )
		    or not filepath.name.startswith("""sol"""    )
		):
			continue
		solution_file_paths.append(UpperCAmelCase    )
	return solution_file_paths




def    __a (     )      ->list[pathlib.Path]:



	"""simple docstring"""







	if os.environ.get("""CI"""    ) and os.environ.get("""GITHUB_EVENT_NAME"""    ) == "pull_request":
		# Return only if there are any, otherwise default to all solutions
		if filepaths := added_solution_file_path():
			return filepaths
	return all_solution_file_paths()




@pytest.mark.parametrize(
    """solution_path"""       ,			collect_solution_file_paths()       ,			ids=lambda UpperCAmelCase    : f"""{path.parent.name}/{path.name}"""       ,			)
def    __a (     UpperCAmelCase    )      ->None:



	"""simple docstring"""







	A							  =      solution_path.parent.name[8:].zfill(3    )
	A							  =      PROBLEM_ANSWERS[problem_number]
	A							  =      convert_path_to_module(UpperCAmelCase    )
	A							  =      str(solution_module.solution()    )  # type: ignore
	A							  =      hashlib.shaaaa(answer.encode()    ).hexdigest()
	assert (
	    answer == expected
	), f"""Expected solution to {problem_number} to have hash {expected}, got {answer}"""

