


"""simple docstring"""







from __future__ import annotations




class 			UpperCamelCase_     :

	"""simple docstring"""





	def __init__(			self      :    List[Any]      ,      UpperCAmelCase__      :    str      ,      UpperCAmelCase__      :    str       )	->     Optional[int]:
						__SCREAMING_SNAKE_CASE       ,  __SCREAMING_SNAKE_CASE						       =    text, pattern
						__SCREAMING_SNAKE_CASE       ,  __SCREAMING_SNAKE_CASE						       =    len(UpperCAmelCase__       ), len(UpperCAmelCase__       )




	def   UpperCAmelCase_				(			self      :    List[Any]      ,      UpperCAmelCase__      :    str       )	->     int:

						for i in range(self.patLen - 1      ,      -1      ,      -1       ):
											if char == self.pattern[i]:
																return i
						return -1




	def   UpperCAmelCase_				(			self      :    Any      ,      UpperCAmelCase__      :    int       )	->     int:

						for i in range(self.patLen - 1      ,      -1      ,      -1       ):
											if self.pattern[i] != self.text[current_pos + i]:
																return current_pos + i
						return -1




	def   UpperCAmelCase_				(			self      :    Optional[int]       )	->     list[int]:
						# searches pattern in text and returns index positions
						__SCREAMING_SNAKE_CASE						       =    []
						for i in range(self.textLen - self.patLen + 1       ):
											__SCREAMING_SNAKE_CASE						       =    self.mismatch_in_text(UpperCAmelCase__       )
											if mismatch_index == -1:
																positions.append(UpperCAmelCase__       )
											else:
																__SCREAMING_SNAKE_CASE						       =    self.match_in_pattern(self.text[mismatch_index]       )
																__SCREAMING_SNAKE_CASE						       =    (
																    mismatch_index - match_index
																)  # shifting index lgtm [py/multiple-definition]
						return positions


a__    :							Tuple            =					'''ABAABA'''
a__    :							List[str]            =					'''AB'''
a__    :							List[str]            =					BoyerMooreSearch(text, pattern)
a__    :							int            =					bms.bad_character_heuristic()

if len(positions) == 0:
		print('''No match found''')
else:
		print('''Pattern found in following positions: ''')
		print(positions)




"""simple docstring"""







from __future__ import annotations

import math

import numpy as np
from numpy.linalg import norm




def        UpperCAmelCase__	(lowerCAmelCase_  ,						lowerCAmelCase_       ):




					'''simple docstring'''


					return math.sqrt(sum(pow(a - b  ,						2       ) for a, b in zip(lowerCAmelCase_  ,						lowerCAmelCase_       )       )       )




def        UpperCAmelCase__	(lowerCAmelCase_  ,						lowerCAmelCase_       ):




					'''simple docstring'''


					if dataset.ndim != value_array.ndim:
										__SCREAMING_SNAKE_CASE						       =    (
										    "Wrong input data's dimensions... "
										    f"""dataset : {dataset.ndim}, value_array : {value_array.ndim}"""
										)
										raise ValueError(lowerCAmelCase_       )

					try:
										if dataset.shape[1] != value_array.shape[1]:
															__SCREAMING_SNAKE_CASE						       =    (
															    "Wrong input data's shape... "
															    f"""dataset : {dataset.shape[1]}, value_array : {value_array.shape[1]}"""
															)
															raise ValueError(lowerCAmelCase_       )
					except IndexError:
										if dataset.ndim != value_array.ndim:
															raise TypeError("Wrong shape"       )

					if dataset.dtype != value_array.dtype:
										__SCREAMING_SNAKE_CASE						       =    (
										    "Input data have different datatype... "
										    f"""dataset : {dataset.dtype}, value_array : {value_array.dtype}"""
										)
										raise TypeError(lowerCAmelCase_       )

					__SCREAMING_SNAKE_CASE						       =    []

					for value in value_array:
										__SCREAMING_SNAKE_CASE						       =    euclidean(lowerCAmelCase_  ,						dataset[0]       )
										__SCREAMING_SNAKE_CASE						       =    dataset[0].tolist()

										for dataset_value in dataset[1:]:
															__SCREAMING_SNAKE_CASE						       =    euclidean(lowerCAmelCase_  ,						lowerCAmelCase_       )

															if dist > temp_dist:
																				__SCREAMING_SNAKE_CASE						       =    temp_dist
																				__SCREAMING_SNAKE_CASE						       =    dataset_value.tolist()

										answer.append([vector, dist]       )

					return answer




def        UpperCAmelCase__	(lowerCAmelCase_  ,						lowerCAmelCase_       ):




					'''simple docstring'''


					return np.dot(lowerCAmelCase_  ,						lowerCAmelCase_       ) / (norm(lowerCAmelCase_       ) * norm(lowerCAmelCase_       ))


if __name__ == "__main__":
		import doctest

		doctest.testmod()
