

import doctest
from collections import deque

import numpy as np



class   __lowercase    :




			"""simple docstring"""







			def __init__(			self  :					Union[str, Any]):
									SCREAMING_SNAKE_CASE_:			int  		=	[2, 1, 2, -1]
									SCREAMING_SNAKE_CASE_:			Optional[Any]  		=	[1, 2, 3, 4]




			def 	_SCREAMING_SNAKE_CASE      (			self  :					Tuple):
									SCREAMING_SNAKE_CASE_:			Any  		=	len(self.first_signal)
									SCREAMING_SNAKE_CASE_:			Dict  		=	len(self.second_signal)

									SCREAMING_SNAKE_CASE_:			Union[str, Any]  		=	max(lowerCAmelCase__       ,						lowerCAmelCase__)

									# create a zero matrix of max_length x max_length
									SCREAMING_SNAKE_CASE_:			List[Any]  		=	[[0] * max_length for i in range(lowerCAmelCase__)]

									# fills the smaller signal with zeros to make both signals of same length
									if length_first_signal < length_second_signal:
															self.first_signal += [0] * (max_length - length_first_signal)
									elif length_first_signal > length_second_signal:
															self.second_signal += [0] * (max_length - length_second_signal)
									for i in range(lowerCAmelCase__):
															SCREAMING_SNAKE_CASE_:			Tuple  		=	deque(self.second_signal)
															rotated_signal.rotate(lowerCAmelCase__)
															for j, item in enumerate(lowerCAmelCase__):
																					matrix[i][j] += item

        # multiply the matrix with the first signal
									SCREAMING_SNAKE_CASE_:			Optional[Any]  		=	np.matmul(np.transpose(lowerCAmelCase__)       ,						np.transpose(self.first_signal))

									# rounding-off to two decimal places
									return [round(lowerCAmelCase__       ,						2) for i in final_signal]


if __name__ == "__main__":
						doctest.testmod()









from __future__ import annotations

from collections import deque
from collections.abc import Iterator
from dataclasses import dataclass



@dataclass
class   __lowercase    :




			"""simple docstring"""







			_UpperCAmelCase       :							int
			_UpperCAmelCase       :							int







class   __lowercase    :




			"""simple docstring"""







			def __init__(			self  :					Any       ,						lowerCAmelCase__  :					int):
									SCREAMING_SNAKE_CASE_:			list[list[Edge]]  		=	[[] for _ in range(lowerCAmelCase__)]
									SCREAMING_SNAKE_CASE_:			Dict  		=	size



			def __getitem__(			self  :					Dict       ,						lowerCAmelCase__  :					int):
									return iter(self._graph[vertex])



			@property
			def 	_SCREAMING_SNAKE_CASE      (			self  :					Tuple):
									return self._size



			def 	_SCREAMING_SNAKE_CASE      (			self  :					Dict       ,						lowerCAmelCase__  :					int       ,						lowerCAmelCase__  :					int       ,						lowerCAmelCase__  :					int):
									if weight not in (0, 1):
															raise ValueError("Edge weight must be either 0 or 1.")

									if to_vertex < 0 or to_vertex >= self.size:
															raise ValueError("Vertex indexes must be in [0; size).")

									self._graph[from_vertex].append(Edge(lowerCAmelCase__       ,						lowerCAmelCase__))




			def 	_SCREAMING_SNAKE_CASE      (			self  :					List[Any]       ,						lowerCAmelCase__  :					int       ,						lowerCAmelCase__  :					int):
									SCREAMING_SNAKE_CASE_:			Optional[int]  		=	deque([start_vertex])
									SCREAMING_SNAKE_CASE_:			list[int | None]  		=	[None] * self.size
									SCREAMING_SNAKE_CASE_:			List[Any]  		=	0

									while queue:
															SCREAMING_SNAKE_CASE_:			int  		=	queue.popleft()
															SCREAMING_SNAKE_CASE_:			str  		=	distances[current_vertex]
															if current_distance is None:
																					continue

															for edge in self[current_vertex]:
																					SCREAMING_SNAKE_CASE_:			Optional[int]  		=	current_distance + edge.weight
																					SCREAMING_SNAKE_CASE_:			str  		=	distances[edge.destination_vertex]
																					if (
																					    isinstance(lowerCAmelCase__       ,						lowerCAmelCase__)
																					    and new_distance >= dest_vertex_distance
																					):
																											continue
																					SCREAMING_SNAKE_CASE_:			Any  		=	new_distance
																					if edge.weight == 0:
																											queue.appendleft(edge.destination_vertex)
																					else:
																											queue.append(edge.destination_vertex)

									if distances[finish_vertex] is None:
															raise ValueError("No path from start_vertex to finish_vertex.")

									return distances[finish_vertex]


if __name__ == "__main__":
						import doctest

						doctest.testmod()






