
"""simple docstring"""




import importlib
from typing import List, Optional, Union

from seqeval.metrics import accuracy_score, classification_report

import datasets


__lowerCAmelCase							:  List[Any] 				=		'''\\n@inproceedings{ramshaw-marcus-1995-text,\n    title = "Text Chunking using Transformation-Based Learning",\n    author = "Ramshaw, Lance  and\n      Marcus, Mitch",\n    booktitle = "Third Workshop on Very Large Corpora",\n    year = "1995",\n    url = "https://www.aclweb.org/anthology/W95-0107",\n}\n@misc{seqeval,\n  title={{seqeval}: A Python framework for sequence labeling evaluation},\n  url={https://github.com/chakki-works/seqeval},\n  note={Software available from https://github.com/chakki-works/seqeval},\n  author={Hiroki Nakayama},\n  year={2018},\n}\n'''

__lowerCAmelCase							:  Optional[Any] 				=		'''\\nseqeval is a Python framework for sequence labeling evaluation.\nseqeval can evaluate the performance of chunking tasks such as named-entity recognition, part-of-speech tagging, semantic role labeling and so on.\n\nThis is well-tested by using the Perl script conlleval, which can be used for\nmeasuring the performance of a system that has processed the CoNLL-2000 shared task data.\n\nseqeval supports following formats:\nIOB1\nIOB2\nIOE1\nIOE2\nIOBES\n\nSee the [README.md] file at https://github.com/chakki-works/seqeval for more information.\n'''

__lowerCAmelCase							:  Union[str, Any] 				=		'''\nProduces labelling scores along with its sufficient statistics\nfrom a source against one or more references.\n\nArgs:\n    predictions: List of List of predicted labels (Estimated targets as returned by a tagger)\n    references: List of List of reference labels (Ground truth (correct) target values)\n    suffix: True if the IOB prefix is after type, False otherwise. default: False\n    scheme: Specify target tagging scheme. Should be one of ["IOB1", "IOB2", "IOE1", "IOE2", "IOBES", "BILOU"].\n        default: None\n    mode: Whether to count correct entity labels with incorrect I/B tags as true positives or not.\n        If you want to only count exact matches, pass mode="strict". default: None.\n    sample_weight: Array-like of shape (n_samples,), weights for individual samples. default: None\n    zero_division: Which value to substitute as a metric value when encountering zero division. Should be on of 0, 1,\n        "warn". "warn" acts as 0, but the warning is raised.\n\nReturns:\n    \'scores\': dict. Summary of the scores for overall and per type\n        Overall:\n            \'accuracy\': accuracy,\n            \'precision\': precision,\n            \'recall\': recall,\n            \'f1\': F1 score, also known as balanced F-score or F-measure,\n        Per type:\n            \'precision\': precision,\n            \'recall\': recall,\n            \'f1\': F1 score, also known as balanced F-score or F-measure\nExamples:\n\n    >>> predictions = [[\'O\', \'O\', \'B-MISC\', \'I-MISC\', \'I-MISC\', \'I-MISC\', \'O\'], [\'B-PER\', \'I-PER\', \'O\']]\n    >>> references = [[\'O\', \'O\', \'O\', \'B-MISC\', \'I-MISC\', \'I-MISC\', \'O\'], [\'B-PER\', \'I-PER\', \'O\']]\n    >>> seqeval = datasets.load_metric("seqeval")\n    >>> results = seqeval.compute(predictions=predictions, references=references)\n    >>> print(list(results.keys()))\n    [\'MISC\', \'PER\', \'overall_precision\', \'overall_recall\', \'overall_f1\', \'overall_accuracy\']\n    >>> print(results["overall_f1"])\n    0.5\n    >>> print(results["PER"]["f1"])\n    1.0\n'''
@datasets.utils.file_utils.add_start_docstrings(_DESCRIPTION					,   _KWARGS_DESCRIPTION					)
class SCREAMING_SNAKE_CASE       (      datasets.Metric					):






	'''simple docstring'''







	def    _UpperCamelCase							(  self :str			)			->   int:

			'''simple docstring'''






			return datasets.MetricInfo(
			    description=_DESCRIPTION       ,    citation=_CITATION       ,    homepage='''https://github.com/chakki-works/seqeval'''       ,    inputs_description=_KWARGS_DESCRIPTION       ,    features=datasets.Features(
			        {
			            '''predictions''': datasets.Sequence(datasets.Value('''string'''       ,    id='''label'''			)       ,    id='''sequence'''			),
			            '''references''': datasets.Sequence(datasets.Value('''string'''       ,    id='''label'''			)       ,    id='''sequence'''			),
			        }			)       ,    codebase_urls=['''https://github.com/chakki-works/seqeval''']       ,    reference_urls=['''https://github.com/chakki-works/seqeval''']       ,    )






	def    _UpperCamelCase							(  self :Tuple       ,    __magic_name__ :Dict       ,    __magic_name__ :List[str]       ,    __magic_name__ :str = False       ,    __magic_name__ :List[Any] = None       ,    __magic_name__ :Tuple = None       ,    __magic_name__ :int = None       ,    __magic_name__ :Optional[int] = "warn"       ,    )			->   Any:

			'''simple docstring'''






			if scheme is not None:
					try:
							a__   		=     importlib.import_module('''seqeval.scheme'''			)
							a__   		=     getattr(lowercase__       ,    lowercase__			)
					except AttributeError:
							raise ValueError(F"Scheme should be one of [IOB1, IOB2, IOE1, IOE2, IOBES, BILOU], got {scheme}"			)
			a__   		=     classification_report(
			    y_true=lowercase__       ,    y_pred=lowercase__       ,    suffix=lowercase__       ,    output_dict=lowercase__       ,    scheme=lowercase__       ,    mode=lowercase__       ,    sample_weight=lowercase__       ,    zero_division=lowercase__       ,    )
			report.pop('''macro avg'''			)
			report.pop('''weighted avg'''			)
			a__   		=     report.pop('''micro avg'''			)

			a__   		=     {
			    type_name: {
			        '''precision''': score['''precision'''],
			        '''recall''': score['''recall'''],
			        '''f1''': score['''f1-score'''],
			        '''number''': score['''support'''],
			    }
			    for type_name, score in report.items()
			}
			a__   		=     overall_score['''precision''']
			a__   		=     overall_score['''recall''']
			a__   		=     overall_score['''f1-score''']
			a__   		=     accuracy_score(y_true=lowercase__       ,    y_pred=lowercase__			)

			return scores






"""simple docstring"""




from __future__ import annotations

from math import pi, pow

def     UpperCamelCase_    (						SCREAMING_SNAKE_CASE_     ):
					if side_length < 0:
										raise ValueError('vol_cube() only accepts non-negative values'     )
					return pow(SCREAMING_SNAKE_CASE_,	3     )

def     UpperCamelCase_    (						SCREAMING_SNAKE_CASE_,	SCREAMING_SNAKE_CASE_     ):
					if height < 0 or radius < 0:
										raise ValueError('vol_spherical_cap() only accepts non-negative values'     )
					# Volume is 1/3 pi * height squared * (3 * radius - height)
					return 1 / 3 * pi * pow(SCREAMING_SNAKE_CASE_,	2     ) * (3 * radius - height)

def     UpperCamelCase_    (						SCREAMING_SNAKE_CASE_,	SCREAMING_SNAKE_CASE_,	SCREAMING_SNAKE_CASE_     ):
					if radius_a < 0 or radius_a < 0 or centers_distance < 0:
										raise ValueError('vol_spheres_intersect() only accepts non-negative values'     )
					if centers_distance == 0:
										return vol_sphere(min(SCREAMING_SNAKE_CASE_,	SCREAMING_SNAKE_CASE_     )     )

					SCREAMING_SNAKE_CASE           =      (
					    (radius_a - radius_a + centers_distance)
					    * (radius_a + radius_a - centers_distance)
					    / (2 * centers_distance)
					)
					SCREAMING_SNAKE_CASE           =      (
					    (radius_a - radius_a + centers_distance)
					    * (radius_a + radius_a - centers_distance)
					    / (2 * centers_distance)
					)

					return vol_spherical_cap(SCREAMING_SNAKE_CASE_,	SCREAMING_SNAKE_CASE_     ) + vol_spherical_cap(SCREAMING_SNAKE_CASE_,	SCREAMING_SNAKE_CASE_     )

def     UpperCamelCase_    (						SCREAMING_SNAKE_CASE_,	SCREAMING_SNAKE_CASE_,	SCREAMING_SNAKE_CASE_     ):

					if radius_a <= 0 or radius_a <= 0 or centers_distance < 0:
										raise ValueError(
										    'vol_spheres_union() only accepts non-negative values, non-zero radius'     )

					if centers_distance == 0:
										return vol_sphere(max(SCREAMING_SNAKE_CASE_,	SCREAMING_SNAKE_CASE_     )     )

					return (
					    vol_sphere(SCREAMING_SNAKE_CASE_     )
					    + vol_sphere(SCREAMING_SNAKE_CASE_     )
					    - vol_spheres_intersect(SCREAMING_SNAKE_CASE_,	SCREAMING_SNAKE_CASE_,	SCREAMING_SNAKE_CASE_     )
					)

def     UpperCamelCase_    (						SCREAMING_SNAKE_CASE_,	SCREAMING_SNAKE_CASE_,	SCREAMING_SNAKE_CASE_     ):
					if width < 0 or height < 0 or length < 0:
										raise ValueError('vol_cuboid() only accepts non-negative values'     )
					return float(width * height * length     )

def     UpperCamelCase_    (						SCREAMING_SNAKE_CASE_,	SCREAMING_SNAKE_CASE_     ):
					if height < 0 or area_of_base < 0:
										raise ValueError('vol_cone() only accepts non-negative values'     )
					return area_of_base * height / 3.0

def     UpperCamelCase_    (						SCREAMING_SNAKE_CASE_,	SCREAMING_SNAKE_CASE_     ):
					if height < 0 or radius < 0:
										raise ValueError('vol_right_circ_cone() only accepts non-negative values'     )
					return pi * pow(SCREAMING_SNAKE_CASE_,	2     ) * height / 3.0

def     UpperCamelCase_    (						SCREAMING_SNAKE_CASE_,	SCREAMING_SNAKE_CASE_     ):
					if height < 0 or area_of_base < 0:
										raise ValueError('vol_prism() only accepts non-negative values'     )
					return float(area_of_base * height     )

def     UpperCamelCase_    (						SCREAMING_SNAKE_CASE_,	SCREAMING_SNAKE_CASE_     ):
					if height < 0 or area_of_base < 0:
										raise ValueError('vol_pyramid() only accepts non-negative values'     )
					return area_of_base * height / 3.0

def     UpperCamelCase_    (						SCREAMING_SNAKE_CASE_     ):
					if radius < 0:
										raise ValueError('vol_sphere() only accepts non-negative values'     )
					# Volume is 4/3 * pi * radius cubed
					return 4 / 3 * pi * pow(SCREAMING_SNAKE_CASE_,	3     )

def     UpperCamelCase_    (						SCREAMING_SNAKE_CASE_     ):
					if radius < 0:
										raise ValueError('vol_hemisphere() only accepts non-negative values'     )
					# Volume is radius cubed * pi * 2/3
					return pow(SCREAMING_SNAKE_CASE_,	3     ) * pi * 2 / 3

def     UpperCamelCase_    (						SCREAMING_SNAKE_CASE_,	SCREAMING_SNAKE_CASE_     ):
					if height < 0 or radius < 0:
										raise ValueError('vol_circular_cylinder() only accepts non-negative values'     )
					# Volume is radius squared * height * pi
					return pow(SCREAMING_SNAKE_CASE_,	2     ) * height * pi

def     UpperCamelCase_    (						SCREAMING_SNAKE_CASE_,	SCREAMING_SNAKE_CASE_,	SCREAMING_SNAKE_CASE_     ):
					# Volume - (outer_radius squared - inner_radius squared) * pi * height
					if inner_radius < 0 or outer_radius < 0 or height < 0:
										raise ValueError(
										    'vol_hollow_circular_cylinder() only accepts non-negative values'     )
					if outer_radius <= inner_radius:
										raise ValueError('outer_radius must be greater than inner_radius'     )
					return pi * (pow(SCREAMING_SNAKE_CASE_,	2     ) - pow(SCREAMING_SNAKE_CASE_,	2     )) * height

def     UpperCamelCase_    (						SCREAMING_SNAKE_CASE_,	SCREAMING_SNAKE_CASE_,	SCREAMING_SNAKE_CASE_     ):
					# Volume is 1/3 * pi * height *
					#           (radius_1 squared + radius_2 squared + radius_1 * radius_2)
					if radius_a < 0 or radius_a < 0 or height < 0:
										raise ValueError('vol_conical_frustum() only accepts non-negative values'     )
					return (
					    1
					    / 3
					    * pi
					    * height
					    * (pow(SCREAMING_SNAKE_CASE_,	2     ) + pow(SCREAMING_SNAKE_CASE_,	2     ) + radius_a * radius_a)
					)

def     UpperCamelCase_    (						SCREAMING_SNAKE_CASE_,	SCREAMING_SNAKE_CASE_     ):
					if torus_radius < 0 or tube_radius < 0:
										raise ValueError('vol_torus() only accepts non-negative values'     )
					return 2 * pow(SCREAMING_SNAKE_CASE_,	2     ) * torus_radius * pow(SCREAMING_SNAKE_CASE_,	2     )

def     UpperCamelCase_    (						):
					print('Volumes:'     )
					print(f'''Cube: {vol_cube(2     ) = }'''     )  # = 8
					print(f'''Cuboid: {vol_cuboid(2,	2,	2     ) = }'''     )  # = 8
					print(f'''Cone: {vol_cone(2,	2     ) = }'''     )  # ~= 1.33
					print(f'''Right Circular Cone: {vol_right_circ_cone(2,	2     ) = }'''     )  # ~= 8.38
					print(f'''Prism: {vol_prism(2,	2     ) = }'''     )  # = 4
					print(f'''Pyramid: {vol_pyramid(2,	2     ) = }'''     )  # ~= 1.33
					print(f'''Sphere: {vol_sphere(2     ) = }'''     )  # ~= 33.5
					print(f'''Hemisphere: {vol_hemisphere(2     ) = }'''     )  # ~= 16.75
					print(f'''Circular Cylinder: {vol_circular_cylinder(2,	2     ) = }'''     )  # ~= 25.1
					print(f'''Torus: {vol_torus(2,	2     ) = }'''     )  # ~= 157.9
					print(f'''Conical Frustum: {vol_conical_frustum(2,	2,	4     ) = }'''     )  # ~= 58.6
					print(f'''Spherical cap: {vol_spherical_cap(1,	2     ) = }'''     )  # ~= 5.24
					print(f'''Spheres intersetion: {vol_spheres_intersect(2,	2,	1     ) = }'''     )  # ~= 21.21
					print(f'''Spheres union: {vol_spheres_union(2,	2,	1     ) = }'''     )  # ~= 45.81
					print(
					    f'''Hollow Circular Cylinder: {vol_hollow_circular_cylinder(1,	2,	3     ) = }'''     )  # ~= 28.3


if __name__ == "__main__":
	main()
