019f8fd211
git-subtree-dir: users/wpcarro git-subtree-mainline:464bbcb15cgit-subtree-split:24f5a642afChange-Id: I6105b3762b79126b3488359c95978cadb3efa789
38 lines
1.1 KiB
Python
38 lines
1.1 KiB
Python
from heapq import heappush, heappop
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import random
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# Dijkstra's algorithm will traverse a directed graph with weighted edges. If
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# the edges aren't weighted, we can pretend that each edges weighs 1. The
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# algorithm will find the shortest path between points A and B.
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def dijkstra(a, b, graph):
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h = []
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seen = set()
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heappush(h, (0, a, [a], []))
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while h:
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km, x, path, steps = heappop(h)
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if x == b:
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for a, b, d in steps:
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print("{} -> {} => {}".format(a, b, d))
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return path, km
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seen.add(x)
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for c, dist in graph[x]:
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if c not in seen:
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heappush(h, (km + dist, c, path + [c], steps + [(x, c, dist)]))
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return [], float('inf')
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graph = {
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1: [(3, 9), (2, 7), (6, 14)],
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2: [(1, 7), (3, 10), (4, 15)],
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3: [(1, 9), (6, 2), (4, 11), (2, 10)],
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4: [(5, 6), (2, 15), (3, 11)],
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5: [(4, 6), (6, 9)],
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6: [(5, 9), (3, 2), (1, 14)],
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}
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beg = random.choice(list(graph.keys()))
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end = random.choice(list(graph.keys()))
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print("Searching for the shortest path from {} -> {}".format(beg, end))
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print(dijkstra(beg, end, graph))
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