



from queue import PriorityQueue
from typing import Any

import numpy as np

def        __a			(   __lowerCAmelCase      ,	__lowerCAmelCase      ,	__lowerCAmelCase      ,	__lowerCAmelCase      ,	__lowerCAmelCase      ,	__lowerCAmelCase      ,	__lowerCAmelCase      ,	__lowerCAmelCase      ,	__lowerCAmelCase      ,	)     ->     float | int:
					for nxt, d in graph[v]:
										if nxt in visited_forward:
															continue
										SCREAMING_SNAKE_CASE							:     List[str]						=				cst_fwd.get(__lowerCAmelCase      ,	np.inf   )
										SCREAMING_SNAKE_CASE							:     List[str]						=				cst_fwd[v] + d
										if new_cost_f < old_cost_f:
															queue.put((new_cost_f, nxt)   )
															SCREAMING_SNAKE_CASE							:     List[Any]						=				new_cost_f
															SCREAMING_SNAKE_CASE							:     str						=				v
										if nxt in visited_backward:
															if cst_fwd[v] + d + cst_bwd[nxt] < shortest_distance:
																				SCREAMING_SNAKE_CASE							:     Optional[int]						=				cst_fwd[v] + d + cst_bwd[nxt]
					return shortest_distance

def        __a			(   __lowerCAmelCase      ,	__lowerCAmelCase      ,	__lowerCAmelCase      ,	__lowerCAmelCase   )     ->     int:
					SCREAMING_SNAKE_CASE							:     List[Any]						=				-1

					SCREAMING_SNAKE_CASE							:     Tuple						=				set()
					SCREAMING_SNAKE_CASE							:     Any						=				set()
					SCREAMING_SNAKE_CASE							:     str						=				{source: 0}
					SCREAMING_SNAKE_CASE							:     Union[str, Any]						=				{destination: 0}
					SCREAMING_SNAKE_CASE							:     Dict						=				{source: None}
					SCREAMING_SNAKE_CASE							:     Optional[int]						=				{destination: None}
					SCREAMING_SNAKE_CASE							:     PriorityQueue[Any]						=				PriorityQueue()
					SCREAMING_SNAKE_CASE							:     PriorityQueue[Any]						=				PriorityQueue()

					SCREAMING_SNAKE_CASE							:     int						=				np.inf

					queue_forward.put((0, source)   )
					queue_backward.put((0, destination)   )

					if source == destination:
										return 0

					while not queue_forward.empty() and not queue_backward.empty():
										SCREAMING_SNAKE_CASE					,  SCREAMING_SNAKE_CASE							:     Any						=				queue_forward.get()
										visited_forward.add(__lowerCAmelCase   )

										SCREAMING_SNAKE_CASE					,  SCREAMING_SNAKE_CASE							:     Optional[int]						=				queue_backward.get()
										visited_backward.add(__lowerCAmelCase   )

										SCREAMING_SNAKE_CASE							:     List[Any]						=				pass_and_relaxation(
										    __lowerCAmelCase      ,	__lowerCAmelCase      ,	__lowerCAmelCase      ,	__lowerCAmelCase      ,	__lowerCAmelCase      ,	__lowerCAmelCase      ,	__lowerCAmelCase      ,	__lowerCAmelCase      ,	__lowerCAmelCase      ,	)

										SCREAMING_SNAKE_CASE							:     List[Any]						=				pass_and_relaxation(
										    __lowerCAmelCase      ,	__lowerCAmelCase      ,	__lowerCAmelCase      ,	__lowerCAmelCase      ,	__lowerCAmelCase      ,	__lowerCAmelCase      ,	__lowerCAmelCase      ,	__lowerCAmelCase      ,	__lowerCAmelCase      ,	)

										if cst_fwd[v_fwd] + cst_bwd[v_bwd] >= shortest_distance:
															break

					if shortest_distance != np.inf:
										SCREAMING_SNAKE_CASE							:     Optional[Any]						=				shortest_distance
					return shortest_path_distance


_lowerCamelCase    :		Dict		      =    {
    """B""": [["""C""", 1]],
    """C""": [["""D""", 1]],
    """D""": [["""F""", 1]],
    """E""": [["""B""", 1], ["""G""", 2]],
    """F""": [],
    """G""": [["""F""", 1]],
}
_lowerCamelCase    :		Optional[int]		      =    {
    """B""": [["""E""", 1]],
    """C""": [["""B""", 1]],
    """D""": [["""C""", 1]],
    """F""": [["""D""", 1], ["""G""", 1]],
    """E""": [[None, np.inf]],
    """G""": [["""E""", 2]],
}

if __name__ == "__main__":
			import doctest

			doctest.testmod()




def        __a			(   __lowerCAmelCase   )     ->     list[list[float]]:
					SCREAMING_SNAKE_CASE							:     list[list[float]]						=				[]
					for data in source_data:
										for i, el in enumerate(__lowerCAmelCase   ):
															if len(__lowerCAmelCase   ) < i + 1:
																				data_lists.append([]   )
															data_lists[i].append(float(__lowerCAmelCase   )   )
					return data_lists

def        __a			(   __lowerCAmelCase      ,	__lowerCAmelCase   )     ->     list[list[float]]:
					SCREAMING_SNAKE_CASE							:     list[list[float]]						=				[]
					for dlist, weight in zip(__lowerCAmelCase      ,	__lowerCAmelCase   ):
										SCREAMING_SNAKE_CASE							:     str						=				min(__lowerCAmelCase   )
										SCREAMING_SNAKE_CASE							:     int						=				max(__lowerCAmelCase   )

										SCREAMING_SNAKE_CASE							:     list[float]						=				[]
										# for weight 0 score is 1 - actual score
										if weight == 0:
															for item in dlist:
																				try:
																									score.append(1 - ((item - mind) / (maxd - mind))   )
																				except ZeroDivisionError:
																									score.append(1   )

										elif weight == 1:
															for item in dlist:
																				try:
																									score.append((item - mind) / (maxd - mind)   )
																				except ZeroDivisionError:
																									score.append(0   )

        # weight not 0 or 1
										else:
															SCREAMING_SNAKE_CASE							:     Union[str, Any]						=				F'''Invalid weight of {weight:f} provided'''
															raise ValueError(__lowerCAmelCase   )

										score_lists.append(__lowerCAmelCase   )

					return score_lists

def        __a			(   __lowerCAmelCase   )     ->     list[float]:
					SCREAMING_SNAKE_CASE							:     list[float]						=				[0 for i in range(len(score_lists[0]   )   )]

					for slist in score_lists:
										for j, ele in enumerate(__lowerCAmelCase   ):
															SCREAMING_SNAKE_CASE							:     str						=				final_scores[j] + ele

					return final_scores



def        __a			(   __lowerCAmelCase      ,	__lowerCAmelCase   )     ->     list[list[float]]:
					SCREAMING_SNAKE_CASE							:     Tuple						=				get_data(__lowerCAmelCase   )
					SCREAMING_SNAKE_CASE							:     List[str]						=				calculate_each_score(__lowerCAmelCase      ,	__lowerCAmelCase   )
					SCREAMING_SNAKE_CASE							:     str						=				generate_final_scores(__lowerCAmelCase   )

					# append scores to source data
					for i, ele in enumerate(__lowerCAmelCase   ):
										source_data[i].append(__lowerCAmelCase   )

					return source_data