Fix multi heuristic astar algo (TheAlgorithms#4612)

Author: mhihasan

graphs/multi_heuristic_astar.py

@@ -2,6 +2,8 @@
 
 import numpy as np
 
+TPos = tuple[int, int]
+
 
 class PriorityQueue:
  def __init__(self):
@@ -53,24 +55,24 @@ def get(self):
  return (priority, item)
 
 
-def consistent_heuristic(P, goal):
+def consistent_heuristic(P: TPos, goal: TPos):
  # euclidean distance
  a = np.array(P)
  b = np.array(goal)
  return np.linalg.norm(a - b)
 
 
-def heuristic_2(P, goal):
+def heuristic_2(P: TPos, goal: TPos):
  # integer division by time variable
  return consistent_heuristic(P, goal) // t
 
 
-def heuristic_1(P, goal):
+def heuristic_1(P: TPos, goal: TPos):
  # manhattan distance
  return abs(P[0] - goal[0]) + abs(P[1] - goal[1])
 
 
-def key(start, i, goal, g_function):
+def key(start: TPos, i: int, goal: TPos, g_function: dict[TPos, float]):
  ans = g_function[start] + W1 * heuristics[i](start, goal)
  return ans
 
@@ -117,7 +119,7 @@ def do_something(back_pointer, goal, start):
  quit()
 
 
-def valid(p):
+def valid(p: TPos):
  if p[0] < 0 or p[0] > n - 1:
  return False
  if p[1] < 0 or p[1] > n - 1:
@@ -215,7 +217,6 @@ def make_common_ground():
  (18, 1),
  (19, 1),
 ]
-blocks_no = []
 blocks_all = make_common_ground()
 
 
@@ -233,7 +234,7 @@ def make_common_ground():
 t = 1
 
 
-def multi_a_star(start, goal, n_heuristic):
+def multi_a_star(start: TPos, goal: TPos, n_heuristic: int):
  g_function = {start: 0, goal: float("inf")}
  back_pointer = {start: -1, goal: -1}
  open_list = []
@@ -243,8 +244,8 @@ def multi_a_star(start, goal, n_heuristic):
  open_list.append(PriorityQueue())
  open_list[i].put(start, key(start, i, goal, g_function))
 
- close_list_anchor = []
- close_list_inad = []
+ close_list_anchor: list[int] = []
+ close_list_inad: list[int] = []
  while open_list[0].minkey() < float("inf"):
  for i in range(1, n_heuristic):
  # print(open_list[0].minkey(), open_list[i].minkey())