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from collections import deque class Graph: # example of adjacency list (or rather map) # adjacency_list = { # 'A': [('B', 1), ('C', 3), ('D', 7)], # 'B': [('D', 5)], # 'C': [('D', 12)] # } def __init__(self, adjacency_list): self.adjacency_list = adjacency_list def get_neighbors(self, v): return self.adjacency_list[v] # heuristic function with equal values for all nodes def h(self, n): H = { 'A': 1, 'B': 1, 'C': 1, 'D': 1 } return H[n] def a_star_algorithm(self, start_node, stop_node): # open_list is a list of nodes which have been visited, but who's neighbors # haven't all been inspected, starts off with the start node # closed_list is a list of nodes which have been visited # and who's neighbors have been inspected open_list = set([start_node]) closed_list = set([]) # g contains current distances from start_node to all other nodes # the default value (if it's not found in the map) is +infinity g = {} g[start_node] = 0 # parents contains an adjacency map of all nodes parents = {} parents[start_node] = start_node while len(open_list) > 0: n = None # find a node with the lowest value of f() - evaluation function for v in open_list: if n == None or g[v] + self.h(v) < g[n] + self.h(n): n = v; if n == None: print('Path does not exist!') return None # if the current node is the stop_node # then we begin reconstructin the path from it to the start_node if n == stop_node: reconst_path = [] while parents[n] != n: reconst_path.append(n) n = parents[n] reconst_path.append(start_node) reconst_path.reverse() print('Path found: {}'.format(reconst_path)) return reconst_path # for all neighbors of the current node do for (m, weight) in self.get_neighbors(n): # if the current node isn't in both open_list and closed_list # add it to open_list and note n as it's parent if m not in open_list and m not in closed_list: open_list.add(m) parents[m] = n g[m] = g[n] + weight # otherwise, check if it's quicker to first visit n, then m # and if it is, update parent data and g data # and if the node was in the closed_list, move it to open_list else: if g[m] > g[n] + weight: g[m] = g[n] + weight parents[m] = n if m in closed_list: closed_list.remove(m) open_list.add(m) # remove n from the open_list, and add it to closed_list # because all of his neighbors were inspected open_list.remove(n) closed_list.add(n) print('Path does not exist!') return None adjacency_list = { 'A': [('B', 1), ('C', 3), ('D', 7)], 'B': [('D', 5)], 'C': [('D', 12)] } graph1 = Graph(adjacency_list) graph1.a_star_algorithm('A', 'D')

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