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Create graphs/dijkstra_alternate.py (#7405)
* Update dijkstra.py * [pre-commit.ci] auto fixes from pre-commit.com hooks for more information, see https://pre-commit.ci * Update dijkstra.py * Update graphs/dijkstra.py Co-authored-by: Christian Clauss <cclauss@me.com> * Update graphs/dijkstra.py Co-authored-by: Christian Clauss <cclauss@me.com> * Update graphs/dijkstra.py Co-authored-by: Christian Clauss <cclauss@me.com> * Update dijkstra.py * [pre-commit.ci] auto fixes from pre-commit.com hooks for more information, see https://pre-commit.ci * Update dijkstra.py * Apply suggestions from code review * Create dijkstra_alternate.py * Update dijkstra.py * [pre-commit.ci] auto fixes from pre-commit.com hooks for more information, see https://pre-commit.ci * int(1e7) * Update dijkstra_alternate.py * Update graphs/dijkstra_alternate.py * sptset --> visited Co-authored-by: pre-commit-ci[bot] <66853113+pre-commit-ci[bot]@users.noreply.github.com> Co-authored-by: Christian Clauss <cclauss@me.com>
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graphs/dijkstra_alternate.py
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graphs/dijkstra_alternate.py
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from __future__ import annotations
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class Graph:
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def __init__(self, vertices: int) -> None:
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"""
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>>> graph = Graph(2)
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>>> graph.vertices
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2
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>>> len(graph.graph)
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2
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>>> len(graph.graph[0])
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2
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"""
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self.vertices = vertices
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self.graph = [[0] * vertices for _ in range(vertices)]
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def print_solution(self, distances_from_source: list[int]) -> None:
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"""
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>>> Graph(0).print_solution([]) # doctest: +NORMALIZE_WHITESPACE
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Vertex Distance from Source
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"""
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print("Vertex \t Distance from Source")
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for vertex in range(self.vertices):
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print(vertex, "\t\t", distances_from_source[vertex])
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def minimum_distance(
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self, distances_from_source: list[int], visited: list[bool]
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) -> int:
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"""
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A utility function to find the vertex with minimum distance value, from the set
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of vertices not yet included in shortest path tree.
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>>> Graph(3).minimum_distance([1, 2, 3], [False, False, True])
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0
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"""
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# Initialize minimum distance for next node
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minimum = 1e7
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min_index = 0
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# Search not nearest vertex not in the shortest path tree
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for vertex in range(self.vertices):
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if distances_from_source[vertex] < minimum and visited[vertex] is False:
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minimum = distances_from_source[vertex]
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min_index = vertex
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return min_index
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def dijkstra(self, source: int) -> None:
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"""
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Function that implements Dijkstra's single source shortest path algorithm for a
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graph represented using adjacency matrix representation.
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>>> Graph(4).dijkstra(1) # doctest: +NORMALIZE_WHITESPACE
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Vertex Distance from Source
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0 10000000
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1 0
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2 10000000
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3 10000000
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"""
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distances = [int(1e7)] * self.vertices # distances from the source
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distances[source] = 0
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visited = [False] * self.vertices
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for _ in range(self.vertices):
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u = self.minimum_distance(distances, visited)
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visited[u] = True
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# Update dist value of the adjacent vertices
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# of the picked vertex only if the current
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# distance is greater than new distance and
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# the vertex in not in the shortest path tree
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for v in range(self.vertices):
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if (
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self.graph[u][v] > 0
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and visited[v] is False
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and distances[v] > distances[u] + self.graph[u][v]
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):
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distances[v] = distances[u] + self.graph[u][v]
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self.print_solution(distances)
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if __name__ == "__main__":
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graph = Graph(9)
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graph.graph = [
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[0, 4, 0, 0, 0, 0, 0, 8, 0],
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[4, 0, 8, 0, 0, 0, 0, 11, 0],
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[0, 8, 0, 7, 0, 4, 0, 0, 2],
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[0, 0, 7, 0, 9, 14, 0, 0, 0],
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[0, 0, 0, 9, 0, 10, 0, 0, 0],
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[0, 0, 4, 14, 10, 0, 2, 0, 0],
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[0, 0, 0, 0, 0, 2, 0, 1, 6],
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[8, 11, 0, 0, 0, 0, 1, 0, 7],
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[0, 0, 2, 0, 0, 0, 6, 7, 0],
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]
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graph.dijkstra(0)
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