Added handing of directed graphs to a_star and dijkstra as well as to reading graphs from file.
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@ -2,7 +2,7 @@ def heuristic_cost(start, goal, graph):
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return 0
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def a_star_algorithm(graph, point_set, start, goal, h=heuristic_cost):
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def a_star_algorithm(graph, start, goal, h=heuristic_cost, is_directed=False):
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def return_path_and_weight(c_f, c, s):
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current_node = c_f[c]
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shortest_path = [c, current_node]
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@ -12,15 +12,24 @@ def a_star_algorithm(graph, point_set, start, goal, h=heuristic_cost):
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weight = 0
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shortest_path.reverse()
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for k in range(len(shortest_path) - 1):
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if shortest_path[k] > shortest_path[k+1]:
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weight += graph[(shortest_path[k], shortest_path[k+1])]
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if not is_directed:
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if shortest_path[k] > shortest_path[k+1]:
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weight += graph[(shortest_path[k], shortest_path[k+1])]
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else:
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weight += graph[(shortest_path[k + 1], shortest_path[k])]
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else:
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weight += graph[(shortest_path[k + 1], shortest_path[k])]
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weight += graph[(shortest_path[k], shortest_path[k + 1])]
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return shortest_path, weight
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for edge in graph.keys():
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point_set[edge[0]].append(edge[1])
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point_set[edge[1]].append(edge[0])
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point_set = dict()
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for arc in g.keys():
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point_set[arc[0]] = []
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point_set[arc[1]] = []
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for arc in graph.keys():
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point_set[arc[0]].append(arc[1])
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if not is_directed:
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point_set[arc[1]].append(arc[0])
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open_set = set()
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open_set.add(start)
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@ -43,10 +52,13 @@ def a_star_algorithm(graph, point_set, start, goal, h=heuristic_cost):
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open_set.remove(current)
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for neighbor in point_set[current]:
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tentative_g_score = g_score[current]
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if current > neighbor:
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tentative_g_score += graph[(current, neighbor)]
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if not is_directed:
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if current > neighbor:
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tentative_g_score += graph[(current, neighbor)]
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else:
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tentative_g_score += graph[(neighbor, current)]
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else:
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tentative_g_score += graph[(neighbor, current)]
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tentative_g_score += graph[(current, neighbor)]
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if tentative_g_score < g_score[neighbor]:
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came_from[neighbor] = current
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g_score[neighbor] = tentative_g_score
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@ -72,9 +84,15 @@ if __name__ == "__main__":
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(9, 1): 8
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}
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v = dict()
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for i in g.keys():
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v[i[0]] = []
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v[i[1]] = []
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g2 = {
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(4, 1): 6,
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(1, 3): 4,
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(1, 2): 2,
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(2, 4): 5,
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(3, 4): 1,
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(5, 3): 1
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}
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print(a_star_algorithm(g, v, 7, 10, heuristic_cost))
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print(a_star_algorithm(g, 7, 10, heuristic_cost))
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print(a_star_algorithm(g2, 1, 4, heuristic_cost, is_directed=True))
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print(a_star_algorithm(g2, 1, 5, heuristic_cost, is_directed=True))
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@ -3,7 +3,7 @@ import heapq as heap
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# function which takes graph, vertex set, start and goal, uses djikstra algorithm to establish shortest paths from start
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# every other vertex in graph and returns shortest path between start and goal
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def dijkstra_algorithm(graph, point_set, start, goal):
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def dijkstra_algorithm(graph, start, goal, is_directed=False):
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# dictionary which will store for every vertex it's distance to start
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dist = dict()
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@ -16,10 +16,16 @@ def dijkstra_algorithm(graph, point_set, start, goal):
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# list which is used to keep priority queue with vertexes to be explored by the algorithm
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queue = []
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point_set = dict()
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for arc in graph.keys():
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point_set[arc[0]] = []
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point_set[arc[1]] = []
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# creating dictionary which for every vertex keeps all it's neighbors
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for edge in graph.keys():
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point_set[edge[0]].append(edge[1])
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point_set[edge[1]].append(edge[0])
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for arc in graph.keys():
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point_set[arc[0]].append(arc[1])
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if not is_directed:
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point_set[arc[1]].append(arc[0])
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for vertex in point_set:
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dist[vertex] = float('inf')
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@ -34,11 +40,13 @@ def dijkstra_algorithm(graph, point_set, start, goal):
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current = heap.heappop(queue)
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for neighbor in point_set[current[1]]:
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new_dist = 0
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if neighbor > current[1]:
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new_dist = dist[current[1]] + graph[(neighbor, current[1])]
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if not is_directed:
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if neighbor > current[1]:
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new_dist = dist[current[1]] + graph[(neighbor, current[1])]
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else:
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new_dist = dist[current[1]] + graph[(current[1], neighbor)]
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else:
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new_dist = dist[current[1]] + graph[(current[1], neighbor)]
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if new_dist < dist[neighbor]:
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dist[neighbor] = new_dist
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for k in range(len(queue)):
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@ -76,9 +84,15 @@ if __name__ == "__main__":
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(9, 1): 8
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}
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v = dict()
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for i in g.keys():
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v[i[0]] = []
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v[i[1]] = []
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g2 = {
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(4, 1): 6,
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(1, 3): 4,
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(1, 2): 2,
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(2, 4): 5,
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(3, 4): 1,
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(5, 3): 1
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}
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print(dijkstra_algorithm(g, v, 7, 10))
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print('')
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print(dijkstra_algorithm(g, 7, 10))
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print(dijkstra_algorithm(g2, 1, 5, is_directed=True))
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@ -15,10 +15,10 @@ def read_graph_from_file(path, separator=",", read_first_line=False, is_directed
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if not is_directed:
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if node1 < node2:
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node1, node2 = node2, node1
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if not has_weight:
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edges[(node1, node2)] = 1
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else:
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edges[(node1, node2)] = int(split[2])
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if not has_weight:
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edges[(node1, node2)] = 1
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else:
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edges[(node1, node2)] = int(split[2])
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else:
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read_line = True
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line = file.readline()
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