


from __future__ import annotations

from collections.abc import Iterable

class 			lowerCamelCase_					:





							def __init__(							self			,       _SCREAMING_SNAKE_CASE			,       _SCREAMING_SNAKE_CASE    ):
								a_			, a_     			=   float(UpperCamelCase_    ), float(UpperCamelCase_    )





							def __eq__(							self			,       _SCREAMING_SNAKE_CASE    ):
								return self.x == other.x and self.y == other.y





							def __ne__(							self			,       _SCREAMING_SNAKE_CASE    ):
								return not self == other





							def __gt__(							self			,       _SCREAMING_SNAKE_CASE    ):
								if self.x > other.x:
									return True
								elif self.x == other.x:
									return self.y > other.y
								return False





							def __lt__(							self			,       _SCREAMING_SNAKE_CASE    ):
								return not self > other





							def __ge__(							self			,       _SCREAMING_SNAKE_CASE    ):
								if self.x > other.x:
									return True
								elif self.x == other.x:
									return self.y >= other.y
								return False





							def __le__(							self			,       _SCREAMING_SNAKE_CASE    ):
								if self.x < other.x:
									return True
								elif self.x == other.x:
									return self.y <= other.y
								return False





							def __repr__(							self    ):
								return f"""({self.x}, {self.y})"""





							def __hash__(							self    ):
								return hash(self.x    )







def 			__SCREAMING_SNAKE_CASE		(		UpperCamelCase		:      list[Point] | list[list[float]] | Iterable[list[float]]     ,					)     ->	Any:



	"""simple docstring"""






	a_     			=   []
	if list_of_tuples:
		for p in list_of_tuples:
			if isinstance(A__     ,					A__	):
				points.append(A__	)
			else:
				try:
					points.append(Point(p[0]     ,					p[1]	)	)
				except (IndexError, TypeError):
					print(
					    F"""Ignoring deformed point {p}. All points"""
					    """ must have at least 2 coordinates."""	)
	return points

def 			__SCREAMING_SNAKE_CASE		(		UpperCamelCase		:      list[Point] | list[list[float]]	)     ->	List[str]:



	"""simple docstring"""






	if not hasattr(A__     ,					"""__iter__"""	):
		a_     			=   F"""Expecting an iterable object but got an non-iterable type {points}"""
		raise ValueError(A__	)

	if not points:
		a_     			=   F"""Expecting a list of points but got {points}"""
		raise ValueError(A__	)

	return _construct_points(A__	)

def 			__SCREAMING_SNAKE_CASE		(		UpperCamelCase		:      Point     ,					UpperCamelCase		:      Point     ,					UpperCamelCase		:      Point	)     ->	str:



	"""simple docstring"""






	a_     			=   (a.x * b.y + b.x * c.y + c.x * a.y) - (a.y * b.x + b.y * c.x + c.y * a.x)
	return det

def 			__SCREAMING_SNAKE_CASE		(		UpperCamelCase		:      list[Point]	)     ->	Optional[int]:



	"""simple docstring"""






	a_     			=   sorted(_validate_input(A__	)	)
	a_     			=   len(A__	)
	a_     			=   set()

	for i in range(n - 1	):
		for j in range(i + 1     ,					A__	):
			a_     			=   a_     			=   False
			a_     			=   True
			for k in range(A__	):
				if k != i and k != j:
					a_     			=   _det(points[i]     ,					points[j]     ,					points[k]	)

					if det_k > 0:
						a_     			=   True
					elif det_k < 0:
						a_     			=   True
					else:
						# point[i], point[j], point[k] all lie on a straight line
						# if point[k] is to the left of point[i] or it's to the
						# right of point[j], then point[i], point[j] cannot be
						# part of the convex hull of A
						if points[k] < points[i] or points[k] > points[j]:
							a_     			=   False
							break

				if points_left_of_ij and points_right_of_ij:
					a_     			=   False
					break

			if ij_part_of_convex_hull:
				convex_set.update([points[i], points[j]]	)

	return sorted(A__	)

def 			__SCREAMING_SNAKE_CASE		(		UpperCamelCase		:      list[Point]	)     ->	List[Any]:



	"""simple docstring"""






	a_     			=   sorted(_validate_input(A__	)	)
	a_     			=   len(A__	)

	# divide all the points into an upper hull and a lower hull
	# the left most point and the right most point are definitely
	# members of the convex hull by definition.
	# use these two anchors to divide all the points into two hulls,
	# an upper hull and a lower hull.

	# all points to the left (above) the line joining the extreme points belong to the
	# upper hull
	# all points to the right (below) the line joining the extreme points below to the
	# lower hull
	# ignore all points on the line joining the extreme points since they cannot be
	# part of the convex hull

	a_     			=   points[0]
	a_     			=   points[n - 1]

	a_     			=   {left_most_point, right_most_point}
	a_     			=   []
	a_     			=   []

	for i in range(1     ,					n - 1	):
		a_     			=   _det(A__     ,					A__     ,					points[i]	)

		if det > 0:
			upper_hull.append(points[i]	)
		elif det < 0:
			lower_hull.append(points[i]	)

	_construct_hull(A__     ,					A__     ,					A__     ,					A__	)
	_construct_hull(A__     ,					A__     ,					A__     ,					A__	)

	return sorted(A__	)

def 			__SCREAMING_SNAKE_CASE		(		UpperCamelCase		:      list[Point]     ,					UpperCamelCase		:      Point     ,					UpperCamelCase		:      Point     ,					UpperCamelCase		:      set[Point]	)     ->	Optional[Any]:



	"""simple docstring"""






	if points:
		a_     			=   None
		a_     			=   float("""-inf"""	)
		a_     			=   []

		for p in points:
			a_     			=   _det(A__     ,					A__     ,					A__	)

			if det > 0:
				candidate_points.append(A__	)

				if det > extreme_point_distance:
					a_     			=   det
					a_     			=   p

		if extreme_point:
			_construct_hull(A__     ,					A__     ,					A__     ,					A__	)
			convex_set.add(A__	)
			_construct_hull(A__     ,					A__     ,					A__     ,					A__	)

def 			__SCREAMING_SNAKE_CASE		(		UpperCamelCase		:      list[Point]	)     ->	Any:



	"""simple docstring"""






	a_     			=   sorted(_validate_input(A__	)	)
	a_     			=   len(A__	)

	a_     			=   points[:2]
	for i in range(2     ,					A__	):
		a_     			=   _det(convex_hull[1]     ,					convex_hull[0]     ,					points[i]	)
		if det > 0:
			convex_hull.insert(0     ,					points[i]	)
			break
		elif det < 0:
			convex_hull.append(points[i]	)
			break
		else:
			a_     			=   points[i]
	i += 1

	for j in range(A__     ,					A__	):
		if (
		    _det(convex_hull[0]     ,					convex_hull[-1]     ,					points[j]	) > 0
		    and _det(convex_hull[-1]     ,					convex_hull[0]     ,					points[1]	) < 0
		):
			# The point lies within the convex hull
			continue

		convex_hull.insert(0     ,					points[j]	)
		convex_hull.append(points[j]	)
		while _det(convex_hull[0]     ,					convex_hull[1]     ,					convex_hull[2]	) >= 0:
			del convex_hull[1]
		while _det(convex_hull[-1]     ,					convex_hull[-2]     ,					convex_hull[-3]	) <= 0:
			del convex_hull[-2]

    # `convex_hull` is contains the convex hull in circular order
	return sorted(convex_hull[1:] if len(A__	) > 3 else convex_hull	)

def 			__SCREAMING_SNAKE_CASE		(		)     ->	Union[str, Any]:



	"""simple docstring"""






	a_     			=   [
	    (0, 3),
	    (2, 2),
	    (1, 1),
	    (2, 1),
	    (3, 0),
	    (0, 0),
	    (3, 3),
	    (2, -1),
	    (2, -4),
	    (1, -3),
	]
	# the convex set of points is
	# [(0, 0), (0, 3), (1, -3), (2, -4), (3, 0), (3, 3)]
	a_     			=   convex_hull_bf(A__	)

	a_     			=   convex_hull_recursive(A__	)
	assert results_bf == results_recursive

	a_     			=   convex_hull_melkman(A__	)
	assert results_bf == results_melkman

	print(A__	)


if __name__ == "__main__":
			main()





import argparse
import json
import re
import string
import sys

import numpy as np


UpperCAmelCase_   							=      0.5




def    lowerCamelCase__			(		A__			:   Optional[Any]    ,     A__			:   Union[str, Any]      ):





       '''simple docstring'''



       __lowerCamelCase  =		[""".""", """,""", """;""", """:"""]

       for token in remove_tokens:
              __lowerCamelCase  =		ground_truth.replace(A__    ,     """"""      )
              __lowerCamelCase  =		prediction.replace(A__    ,     """"""      )

       __lowerCamelCase,  __lowerCamelCase  =		ground_truth.lower(), prediction.lower()
       __lowerCamelCase,  __lowerCamelCase  =		ground_truth.replace("""/"""    ,     """ """      ), prediction.replace("""/"""    ,     """ """      )
       __lowerCamelCase,  __lowerCamelCase  =		set(ground_truth.split(""" """      )      ), set(prediction.split(""" """      )      )

       __lowerCamelCase  =		ground_truth.intersection(A__      )
       __lowerCamelCase  =		ground_truth.union(A__      )
       __lowerCamelCase  =		len(A__      ) / len(A__      )
       return jaccard




def    lowerCamelCase__			(		A__			:   Optional[Any]      ):





       '''simple docstring'''



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

       def white_space_fix(A__			:   Optional[Any]      ):
              return " ".join(text.split()      )

       def remove_punc(A__			:   Optional[Any]      ):
              __lowerCamelCase  =		set(string.punctuation      )
              return "".join(ch for ch in text if ch not in exclude      )

       def lower(A__			:   Tuple      ):
              return text.lower()

       return white_space_fix(remove_articles(remove_punc(lower(A__      )      )      )      )




def    lowerCamelCase__			(		A__			:   Any    ,     A__			:   Optional[Any]    ,     A__			:   Optional[Any]      ):





       '''simple docstring'''



       __lowerCamelCase,  __lowerCamelCase,  __lowerCamelCase  =		0, 0, 0

       __lowerCamelCase  =		"""Parties""" in qa_id

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

                     if not match_found:
                            fp += 1

       __lowerCamelCase  =		tp / (tp + fp) if tp + fp > 0 else np.nan
       __lowerCamelCase  =		tp / (tp + fn) if tp + fn > 0 else np.nan

       return precision, recall




def    lowerCamelCase__			(		A__			:   int      ):





       '''simple docstring'''



       __lowerCamelCase  =		precisions[::-1]
       for i in range(1    ,     len(A__      )      ):
              __lowerCamelCase  =		max(precision_best[i - 1]    ,     precision_best[i]      )
       __lowerCamelCase  =		precision_best[::-1]
       return precisions




def    lowerCamelCase__			(		A__			:   str    ,     A__			:   Union[str, Any]      ):





       '''simple docstring'''



       __lowerCamelCase  =		process_precisions(A__      )
       __lowerCamelCase  =		np.trapz(A__    ,     A__      )
       if np.isnan(A__      ):
              return 0
       return aupr




def    lowerCamelCase__			(		A__			:   Optional[Any]    ,     A__			:   List[str]    ,     A__			:   int      ):





       '''simple docstring'''



       __lowerCamelCase  =		process_precisions(A__      )
       __lowerCamelCase  =		0
       for prec, recall in zip(A__    ,     A__      ):
              if recall >= recall_thresh:
                     __lowerCamelCase  =		prec
                     break
       return prec_at_recall




def    lowerCamelCase__			(		A__			:   Optional[Any]    ,     A__			:   List[Any]      ):





       '''simple docstring'''



       return normalize_answer(A__      ) == normalize_answer(A__      )




def    lowerCamelCase__			(		A__			:   Tuple    ,     A__			:   int    ,     A__			:   Dict      ):





       '''simple docstring'''



       __lowerCamelCase  =		0
       for pred in predictions:
              for ground_truth in ground_truths:
                     __lowerCamelCase  =		metric_fn(A__    ,     A__      )
                     if score == 1:  # break the loop when one prediction matches the ground truth
                            break
              if score == 1:
                     break
       return score




def    lowerCamelCase__			(		A__			:   Union[str, Any]    ,     A__			:   Optional[Any]      ):





       '''simple docstring'''



       __lowerCamelCase  =		__lowerCamelCase  =		__lowerCamelCase  =		0
       __lowerCamelCase  =		[]
       __lowerCamelCase  =		[]
       for article in dataset:
              for paragraph in article["paragraphs"]:
                     for qa in paragraph["qas"]:
                            total += 1
                            if qa["id"] not in predictions:
                                   __lowerCamelCase  =		"""Unanswered question """ + qa["""id"""] + """ will receive score 0."""
                                   print(A__    ,     file=sys.stderr      )
                                   continue
                            __lowerCamelCase  =		[x["""text"""] for x in qa["""answers"""]]
                            __lowerCamelCase  =		predictions[qa["""id"""]]
                            __lowerCamelCase,  __lowerCamelCase  =		compute_precision_recall(A__    ,     A__    ,     qa["""id"""]      )

                            precisions.append(A__      )
                            recalls.append(A__      )

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

                            exact_match += metric_max_over_ground_truths(A__    ,     A__    ,     A__      )

       __lowerCamelCase  =		[x for _, x in sorted(zip(A__    ,     A__      )      )]
       recalls.sort()

       __lowerCamelCase  =		100.0 * fa / total
       __lowerCamelCase  =		100.0 * exact_match / total
       __lowerCamelCase  =		get_aupr(A__    ,     A__      )

       __lowerCamelCase  =		get_prec_at_recall(A__    ,     A__    ,     recall_thresh=0.9      )
       __lowerCamelCase  =		get_prec_at_recall(A__    ,     A__    ,     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__":
       UpperCAmelCase_   							=      argparse.ArgumentParser(description='Evaluation for CUAD')
       parser.add_argument('dataset_file', help='Dataset file')
       parser.add_argument('prediction_file', help='Prediction File')
       UpperCAmelCase_   							=      parser.parse_args()
       with open(args.dataset_file) as dataset_file:
              UpperCAmelCase_   							=      json.load(dataset_file)
              UpperCAmelCase_   							=      dataset_json['data']
       with open(args.prediction_file) as prediction_file:
              UpperCAmelCase_   							=      json.load(prediction_file)
       print(json.dumps(evaluate(dataset, predictions)))

