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* Revised the book * Update the book with the second revised edition * Revise base on the manuscript of the first edition
57 lines
1.6 KiB
Python
57 lines
1.6 KiB
Python
"""
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File: graph_dfs.py
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Created Time: 2023-02-23
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Author: Krahets (krahets@163.com)
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"""
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import sys
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from pathlib import Path
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sys.path.append(str(Path(__file__).parent.parent))
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from modules import Vertex, vets_to_vals, vals_to_vets
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from graph_adjacency_list import GraphAdjList
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def dfs(graph: GraphAdjList, visited: set[Vertex], res: list[Vertex], vet: Vertex):
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"""深度优先遍历辅助函数"""
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res.append(vet) # 记录访问顶点
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visited.add(vet) # 标记该顶点已被访问
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# 遍历该顶点的所有邻接顶点
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for adjVet in graph.adj_list[vet]:
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if adjVet in visited:
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continue # 跳过已被访问的顶点
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# 递归访问邻接顶点
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dfs(graph, visited, res, adjVet)
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def graph_dfs(graph: GraphAdjList, start_vet: Vertex) -> list[Vertex]:
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"""深度优先遍历"""
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# 使用邻接表来表示图，以便获取指定顶点的所有邻接顶点
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# 顶点遍历序列
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res = []
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# 哈希表，用于记录已被访问过的顶点
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visited = set[Vertex]()
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dfs(graph, visited, res, start_vet)
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return res
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"""Driver Code"""
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if __name__ == "__main__":
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# 初始化无向图
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v = vals_to_vets([0, 1, 2, 3, 4, 5, 6])
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edges = [
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[v[0], v[1]],
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[v[0], v[3]],
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[v[1], v[2]],
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[v[2], v[5]],
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[v[4], v[5]],
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[v[5], v[6]],
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]
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graph = GraphAdjList(edges)
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print("\n初始化后，图为")
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graph.print()
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# 深度优先遍历
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res = graph_dfs(graph, v[0])
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print("\n深度优先遍历（DFS）顶点序列为")
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print(vets_to_vals(res))
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