{"id":1131197,"date":"2025-01-08T20:46:35","date_gmt":"2025-01-08T12:46:35","guid":{"rendered":"https:\/\/docs.pingcode.com\/ask\/ask-ask\/1131197.html"},"modified":"2025-01-08T20:46:38","modified_gmt":"2025-01-08T12:46:38","slug":"%e5%a6%82%e4%bd%95%e5%88%a9%e7%94%a8python%e7%bc%96%e5%86%990-1%e9%82%bb%e6%8e%a5%e7%9f%a9%e9%98%b5","status":"publish","type":"post","link":"https:\/\/docs.pingcode.com\/ask\/1131197.html","title":{"rendered":"\u5982\u4f55\u5229\u7528Python\u7f16\u51990-1\u90bb\u63a5\u77e9\u9635"},"content":{"rendered":"<p style=\"text-align:center;\" ><img decoding=\"async\" src=\"https:\/\/cdn-kb.worktile.com\/kb\/wp-content\/uploads\/2024\/04\/25101036\/f19b40b3-844f-447a-892a-59fd73582682.webp\" alt=\"\u5982\u4f55\u5229\u7528Python\u7f16\u51990-1\u90bb\u63a5\u77e9\u9635\" \/><\/p>\n<p><p> <strong>\u5982\u4f55\u5229\u7528Python\u7f16\u51990-1\u90bb\u63a5\u77e9\u9635<\/strong><\/p>\n<\/p>\n<p><p><strong>\u5229\u7528Python\u7f16\u51990-1\u90bb\u63a5\u77e9\u9635\u7684\u6838\u5fc3\u6b65\u9aa4\u5305\u62ec\uff1a\u5b9a\u4e49\u8282\u70b9\u548c\u8fb9\u3001\u4f7f\u7528\u5217\u8868\u6216NumPy\u6570\u7ec4\u521b\u5efa\u77e9\u9635\u3001\u586b\u5145\u77e9\u9635<\/strong>\u3002\u672c\u6587\u5c06\u8be6\u7ec6\u4ecb\u7ecd\u8fd9\u51e0\u4e2a\u6b65\u9aa4\u53ca\u5176\u5b9e\u73b0\u65b9\u6cd5\uff0c\u5e76\u63d0\u4f9b\u4e00\u4e9b\u5b9e\u7528\u7684\u4ee3\u7801\u793a\u4f8b\u6765\u8bf4\u660e\u5982\u4f55\u4f7f\u7528Python\u7f16\u51990-1\u90bb\u63a5\u77e9\u9635\u3002\u6211\u4eec\u7279\u522b\u4f1a\u8be6\u7ec6\u63cf\u8ff0\u5982\u4f55\u4f7f\u7528NumPy\u6570\u7ec4\u6765\u521b\u5efa\u548c\u64cd\u4f5c\u90bb\u63a5\u77e9\u9635\uff0c\u56e0\u4e3aNumPy\u6570\u7ec4\u5728\u5904\u7406\u77e9\u9635\u64cd\u4f5c\u65f6\u975e\u5e38\u9ad8\u6548\u3002<\/p>\n<\/p>\n<p><h3>\u4e00\u3001\u5b9a\u4e49\u8282\u70b9\u548c\u8fb9<\/h3>\n<\/p>\n<p><p>\u5728\u56fe\u8bba\u4e2d\uff0c\u90bb\u63a5\u77e9\u9635\u662f\u4e00\u79cd\u8868\u793a\u56fe\u7684\u6709\u6548\u65b9\u5f0f\u30020-1\u90bb\u63a5\u77e9\u9635\u75280\u548c1\u8868\u793a\u8282\u70b9\u4e4b\u95f4\u662f\u5426\u5b58\u5728\u8fb9\u3002\u9996\u5148\uff0c\u6211\u4eec\u9700\u8981\u5b9a\u4e49\u56fe\u7684\u8282\u70b9\u548c\u8fb9\u3002<\/p>\n<\/p>\n<p><h4>1. \u8282\u70b9\u5b9a\u4e49<\/h4>\n<\/p>\n<p><p>\u8282\u70b9\u662f\u56fe\u7684\u57fa\u672c\u7ec4\u6210\u90e8\u5206\u3002\u53ef\u4ee5\u7528\u4e00\u4e2a\u7b80\u5355\u7684\u5217\u8868\u6765\u5b9a\u4e49\u8282\u70b9\uff0c\u4f8b\u5982\uff1a<\/p>\n<\/p>\n<p><pre><code class=\"language-python\">nodes = [&#39;A&#39;, &#39;B&#39;, &#39;C&#39;, &#39;D&#39;]<\/p>\n<p><\/code><\/pre>\n<\/p>\n<p><p>\u5728\u8fd9\u4e2a\u5217\u8868\u4e2d\uff0c<code>&#39;A&#39;<\/code>\u3001<code>&#39;B&#39;<\/code>\u3001<code>&#39;C&#39;<\/code> \u548c <code>&#39;D&#39;<\/code> \u662f\u56fe\u7684\u8282\u70b9\u3002<\/p>\n<\/p>\n<p><h4>2. \u8fb9\u5b9a\u4e49<\/h4>\n<\/p>\n<p><p>\u8fb9\u662f\u8fde\u63a5\u4e24\u4e2a\u8282\u70b9\u7684\u7ebf\u3002\u53ef\u4ee5\u7528\u4e00\u4e2a\u5143\u7ec4\u5217\u8868\u6765\u5b9a\u4e49\u8fb9\uff0c\u4f8b\u5982\uff1a<\/p>\n<\/p>\n<p><pre><code class=\"language-python\">edges = [(&#39;A&#39;, &#39;B&#39;), (&#39;A&#39;, &#39;C&#39;), (&#39;B&#39;, &#39;D&#39;)]<\/p>\n<p><\/code><\/pre>\n<\/p>\n<p><p>\u8fd9\u91cc\uff0c<code>(&#39;A&#39;, &#39;B&#39;)<\/code> \u8868\u793a\u8282\u70b9 <code>A<\/code> \u548c\u8282\u70b9 <code>B<\/code> \u4e4b\u95f4\u5b58\u5728\u4e00\u6761\u8fb9\u3002<\/p>\n<\/p>\n<p><h3>\u4e8c\u3001\u4f7f\u7528\u5217\u8868\u521b\u5efa\u90bb\u63a5\u77e9\u9635<\/h3>\n<\/p>\n<p><p>\u90bb\u63a5\u77e9\u9635\u53ef\u4ee5\u4f7f\u7528\u5d4c\u5957\u5217\u8868\u6765\u8868\u793a\u3002\u9996\u5148\uff0c\u6211\u4eec\u521b\u5efa\u4e00\u4e2a <code>n x n<\/code> \u7684\u77e9\u9635\uff0c\u5176\u4e2d <code>n<\/code> \u662f\u8282\u70b9\u7684\u6570\u91cf\u3002\u7136\u540e\uff0c\u6839\u636e\u8fb9\u7684\u4fe1\u606f\u586b\u5145\u77e9\u9635\u3002<\/p>\n<\/p>\n<p><h4>1. \u521d\u59cb\u5316\u77e9\u9635<\/h4>\n<\/p>\n<p><p>\u9996\u5148\uff0c\u6211\u4eec\u521d\u59cb\u5316\u4e00\u4e2a\u5168\u4e3a0\u7684\u77e9\u9635\uff1a<\/p>\n<\/p>\n<p><pre><code class=\"language-python\">n = len(nodes)<\/p>\n<p>adj_matrix = [[0] * n for _ in range(n)]<\/p>\n<p><\/code><\/pre>\n<\/p>\n<p><p>\u8fd9\u4e2a\u4ee3\u7801\u521b\u5efa\u4e86\u4e00\u4e2a <code>n x n<\/code> \u7684\u5168\u96f6\u77e9\u9635\u3002<\/p>\n<\/p>\n<p><h4>2. \u586b\u5145\u77e9\u9635<\/h4>\n<\/p>\n<p><p>\u63a5\u4e0b\u6765\uff0c\u6211\u4eec\u6839\u636e\u8fb9\u7684\u4fe1\u606f\u5c06\u77e9\u9635\u586b\u5145\u4e3a0-1\u77e9\u9635\uff1a<\/p>\n<\/p>\n<p><pre><code class=\"language-python\">node_index = {node: i for i, node in enumerate(nodes)}<\/p>\n<p>for edge in edges:<\/p>\n<p>    i, j = node_index[edge[0]], node_index[edge[1]]<\/p>\n<p>    adj_matrix[i][j] = 1<\/p>\n<p>    adj_matrix[j][i] = 1  # \u5982\u679c\u662f\u65e0\u5411\u56fe<\/p>\n<p><\/code><\/pre>\n<\/p>\n<p><h3>\u4e09\u3001\u4f7f\u7528NumPy\u6570\u7ec4\u521b\u5efa\u90bb\u63a5\u77e9\u9635<\/h3>\n<\/p>\n<p><p>NumPy\u662fPython\u4e2d\u5904\u7406\u77e9\u9635\u548c\u6570\u7ec4\u64cd\u4f5c\u7684\u5f3a\u5927\u5e93\u3002\u4f7f\u7528NumPy\u6570\u7ec4\u4e0d\u4ec5\u53ef\u4ee5\u7b80\u5316\u4ee3\u7801\uff0c\u8fd8\u80fd\u63d0\u9ad8\u6548\u7387\u3002<\/p>\n<\/p>\n<p><h4>1. \u5b89\u88c5NumPy<\/h4>\n<\/p>\n<p><p>\u9996\u5148\uff0c\u786e\u4fdd\u4f60\u5df2\u7ecf\u5b89\u88c5\u4e86NumPy\u5e93\u3002\u5982\u679c\u6ca1\u6709\u5b89\u88c5\uff0c\u53ef\u4ee5\u4f7f\u7528\u4ee5\u4e0b\u547d\u4ee4\u8fdb\u884c\u5b89\u88c5\uff1a<\/p>\n<\/p>\n<p><pre><code class=\"language-bash\">pip install numpy<\/p>\n<p><\/code><\/pre>\n<\/p>\n<p><h4>2. \u521d\u59cb\u5316NumPy\u6570\u7ec4<\/h4>\n<\/p>\n<p><p>\u4e0e\u4f7f\u7528\u5217\u8868\u7c7b\u4f3c\uff0c\u9996\u5148\u6211\u4eec\u521d\u59cb\u5316\u4e00\u4e2a\u5168\u4e3a0\u7684NumPy\u6570\u7ec4\uff1a<\/p>\n<\/p>\n<p><pre><code class=\"language-python\">import numpy as np<\/p>\n<p>n = len(nodes)<\/p>\n<p>adj_matrix = np.zeros((n, n), dtype=int)<\/p>\n<p><\/code><\/pre>\n<\/p>\n<p><h4>3. \u586b\u5145NumPy\u6570\u7ec4<\/h4>\n<\/p>\n<p><p>\u7136\u540e\uff0c\u6211\u4eec\u6839\u636e\u8fb9\u7684\u4fe1\u606f\u586b\u5145NumPy\u6570\u7ec4\uff1a<\/p>\n<\/p>\n<p><pre><code class=\"language-python\">for edge in edges:<\/p>\n<p>    i, j = node_index[edge[0]], node_index[edge[1]]<\/p>\n<p>    adj_matrix[i][j] = 1<\/p>\n<p>    adj_matrix[j][i] = 1  # \u5982\u679c\u662f\u65e0\u5411\u56fe<\/p>\n<p><\/code><\/pre>\n<\/p>\n<p><h3>\u56db\u3001\u5b8c\u6574\u4ee3\u7801\u793a\u4f8b<\/h3>\n<\/p>\n<p><p>\u4ee5\u4e0b\u662f\u4e00\u4e2a\u5b8c\u6574\u7684\u4ee3\u7801\u793a\u4f8b\uff0c\u5c55\u793a\u5982\u4f55\u4f7f\u7528Python\u548cNumPy\u6765\u521b\u5efa0-1\u90bb\u63a5\u77e9\u9635\uff1a<\/p>\n<\/p>\n<p><pre><code class=\"language-python\">import numpy as np<\/p>\n<h2><strong>\u5b9a\u4e49\u8282\u70b9<\/strong><\/h2>\n<p>nodes = [&#39;A&#39;, &#39;B&#39;, &#39;C&#39;, &#39;D&#39;]<\/p>\n<h2><strong>\u5b9a\u4e49\u8fb9<\/strong><\/h2>\n<p>edges = [(&#39;A&#39;, &#39;B&#39;), (&#39;A&#39;, &#39;C&#39;), (&#39;B&#39;, &#39;D&#39;)]<\/p>\n<h2><strong>\u521b\u5efa\u8282\u70b9\u7d22\u5f15<\/strong><\/h2>\n<p>node_index = {node: i for i, node in enumerate(nodes)}<\/p>\n<h2><strong>\u521d\u59cb\u5316NumPy\u6570\u7ec4<\/strong><\/h2>\n<p>n = len(nodes)<\/p>\n<p>adj_matrix = np.zeros((n, n), dtype=int)<\/p>\n<h2><strong>\u586b\u5145NumPy\u6570\u7ec4<\/strong><\/h2>\n<p>for edge in edges:<\/p>\n<p>    i, j = node_index[edge[0]], node_index[edge[1]]<\/p>\n<p>    adj_matrix[i][j] = 1<\/p>\n<p>    adj_matrix[j][i] = 1  # \u5982\u679c\u662f\u65e0\u5411\u56fe<\/p>\n<p>print(adj_matrix)<\/p>\n<p><\/code><\/pre>\n<\/p>\n<p><h3>\u4e94\u3001\u90bb\u63a5\u77e9\u9635\u7684\u5e94\u7528<\/h3>\n<\/p>\n<p><p>\u90bb\u63a5\u77e9\u9635\u5728\u56fe\u8bba\u548c\u7f51\u7edc\u5206\u6790\u4e2d\u6709\u5e7f\u6cdb\u7684\u5e94\u7528\u3002\u4ee5\u4e0b\u662f\u4e00\u4e9b\u5e38\u89c1\u7684\u5e94\u7528\u573a\u666f\uff1a<\/p>\n<\/p>\n<p><h4>1. \u8def\u5f84\u67e5\u627e<\/h4>\n<\/p>\n<p><p>\u90bb\u63a5\u77e9\u9635\u53ef\u4ee5\u7528\u4e8e\u56fe\u4e2d\u7684\u8def\u5f84\u67e5\u627e\u7b97\u6cd5\uff0c\u5982\u6df1\u5ea6\u4f18\u5148\u641c\u7d22\uff08DFS\uff09\u548c\u5e7f\u5ea6\u4f18\u5148\u641c\u7d22\uff08BFS\uff09\u3002<\/p>\n<\/p>\n<p><pre><code class=\"language-python\">def dfs(graph, start):<\/p>\n<p>    visited, stack = set(), [start]<\/p>\n<p>    while stack:<\/p>\n<p>        vertex = stack.pop()<\/p>\n<p>        if vertex not in visited:<\/p>\n<p>            visited.add(vertex)<\/p>\n<p>            stack.extend(set(graph[vertex]) - visited)<\/p>\n<p>    return visited<\/p>\n<p><\/code><\/pre>\n<\/p>\n<p><h4>2. \u6700\u77ed\u8def\u5f84<\/h4>\n<\/p>\n<p><p>\u90bb\u63a5\u77e9\u9635\u53ef\u4ee5\u7528\u4e8e\u8ba1\u7b97\u56fe\u4e2d\u7684\u6700\u77ed\u8def\u5f84\uff0c\u5982Dijkstra\u7b97\u6cd5\u548cFloyd-Warshall\u7b97\u6cd5\u3002<\/p>\n<\/p>\n<p><pre><code class=\"language-python\">def floyd_warshall(graph):<\/p>\n<p>    dist = dict(graph)  # \u521d\u59cb\u5316\u8ddd\u79bb<\/p>\n<p>    for k in graph:<\/p>\n<p>        for i in graph:<\/p>\n<p>            for j in graph:<\/p>\n<p>                if dist[i][j] &gt; dist[i][k] + dist[k][j]:<\/p>\n<p>                    dist[i][j] = dist[i][k] + dist[k][j]<\/p>\n<p>    return dist<\/p>\n<p><\/code><\/pre>\n<\/p>\n<p><h4>3. \u793e\u4ea4\u7f51\u7edc\u5206\u6790<\/h4>\n<\/p>\n<p><p>\u5728\u793e\u4ea4\u7f51\u7edc\u5206\u6790\u4e2d\uff0c\u90bb\u63a5\u77e9\u9635\u53ef\u4ee5\u7528\u4e8e\u8ba1\u7b97\u7f51\u7edc\u7684\u5ea6\u4e2d\u5fc3\u6027\u3001\u63a5\u8fd1\u4e2d\u5fc3\u6027\u548c\u4e2d\u4ecb\u4e2d\u5fc3\u6027\u7b49\u6307\u6807\u3002<\/p>\n<\/p>\n<p><pre><code class=\"language-python\">import networkx as nx<\/p>\n<p>G = nx.from_numpy_matrix(adj_matrix)<\/p>\n<p>degree_centrality = nx.degree_centrality(G)<\/p>\n<p>closeness_centrality = nx.closeness_centrality(G)<\/p>\n<p>betweenness_centrality = nx.betweenness_centrality(G)<\/p>\n<p><\/code><\/pre>\n<\/p>\n<p><h3>\u516d\u3001\u4f18\u5316\u548c\u6ce8\u610f\u4e8b\u9879<\/h3>\n<\/p>\n<p><p>\u5728\u7f16\u5199\u548c\u4f7f\u7528\u90bb\u63a5\u77e9\u9635\u65f6\uff0c\u6709\u4e00\u4e9b\u4f18\u5316\u548c\u6ce8\u610f\u4e8b\u9879\uff1a<\/p>\n<\/p>\n<p><h4>1. \u7a00\u758f\u77e9\u9635<\/h4>\n<\/p>\n<p><p>\u5bf9\u4e8e\u5927\u89c4\u6a21\u7a00\u758f\u56fe\uff0c\u4f7f\u7528\u7a00\u758f\u77e9\u9635\uff08\u4f8b\u5982SciPy\u4e2d\u7684\u7a00\u758f\u77e9\u9635\uff09\u53ef\u4ee5\u8282\u7701\u5185\u5b58\u548c\u8ba1\u7b97\u65f6\u95f4\u3002<\/p>\n<\/p>\n<p><pre><code class=\"language-python\">from scipy.sparse import csr_matrix<\/p>\n<p>sparse_adj_matrix = csr_matrix(adj_matrix)<\/p>\n<p><\/code><\/pre>\n<\/p>\n<p><h4>2. \u6709\u5411\u56fe<\/h4>\n<\/p>\n<p><p>\u5bf9\u4e8e\u6709\u5411\u56fe\uff0c\u53ea\u9700\u5728\u586b\u5145\u77e9\u9635\u65f6\u5c06\u5355\u5411\u8fb9\u7684\u503c\u8bbe\u4e3a1\u5373\u53ef\uff0c\u65e0\u9700\u5bf9\u79f0\u586b\u5145\u3002<\/p>\n<\/p>\n<p><pre><code class=\"language-python\">for edge in edges:<\/p>\n<p>    i, j = node_index[edge[0]], node_index[edge[1]]<\/p>\n<p>    adj_matrix[i][j] = 1<\/p>\n<p><\/code><\/pre>\n<\/p>\n<p><h4>3. \u6743\u91cd\u56fe<\/h4>\n<\/p>\n<p><p>\u5bf9\u4e8e\u5e26\u6743\u91cd\u7684\u56fe\uff0c\u53ef\u4ee5\u5728\u77e9\u9635\u4e2d\u5b58\u50a8\u6743\u91cd\u503c\u800c\u4e0d\u662f0\u548c1\u3002<\/p>\n<\/p>\n<p><pre><code class=\"language-python\">edges = [(&#39;A&#39;, &#39;B&#39;, 2), (&#39;A&#39;, &#39;C&#39;, 3), (&#39;B&#39;, &#39;D&#39;, 4)]<\/p>\n<p>for edge in edges:<\/p>\n<p>    i, j = node_index[edge[0]], node_index[edge[1]]<\/p>\n<p>    adj_matrix[i][j] = edge[2]<\/p>\n<p>    adj_matrix[j][i] = edge[2]  # \u5982\u679c\u662f\u65e0\u5411\u56fe<\/p>\n<p><\/code><\/pre>\n<\/p>\n<p><h3>\u4e03\u3001\u603b\u7ed3<\/h3>\n<\/p>\n<p><p><strong>\u5229\u7528Python\u7f16\u51990-1\u90bb\u63a5\u77e9\u9635\u7684\u5173\u952e\u6b65\u9aa4\u5305\u62ec\uff1a\u5b9a\u4e49\u8282\u70b9\u548c\u8fb9\u3001\u4f7f\u7528\u5217\u8868\u6216NumPy\u6570\u7ec4\u521b\u5efa\u77e9\u9635\u3001\u586b\u5145\u77e9\u9635<\/strong>\u3002\u65e0\u8bba\u662f\u4f7f\u7528\u5d4c\u5957\u5217\u8868\u8fd8\u662fNumPy\u6570\u7ec4\uff0c\u90fd\u53ef\u4ee5\u6709\u6548\u5730\u521b\u5efa\u548c\u64cd\u4f5c\u90bb\u63a5\u77e9\u9635\u3002\u6b64\u5916\uff0c\u90bb\u63a5\u77e9\u9635\u5728\u8def\u5f84\u67e5\u627e\u3001\u6700\u77ed\u8def\u5f84\u8ba1\u7b97\u548c\u793e\u4ea4\u7f51\u7edc\u5206\u6790\u7b49\u9886\u57df\u6709\u5e7f\u6cdb\u7684\u5e94\u7528\u3002\u5728\u5b9e\u9645\u5e94\u7528\u4e2d\uff0c\u9009\u62e9\u5408\u9002\u7684\u6570\u636e\u7ed3\u6784\u548c\u4f18\u5316\u65b9\u6cd5\u53ef\u4ee5\u663e\u8457\u63d0\u9ad8\u7a0b\u5e8f\u7684\u6027\u80fd\u548c\u6548\u7387\u3002<\/p>\n<\/p>\n<h2><strong>\u76f8\u5173\u95ee\u7b54FAQs\uff1a<\/strong><\/h2>\n<p> <strong>\u5982\u4f55\u5728Python\u4e2d\u521b\u5efa\u4e00\u4e2a0-1\u90bb\u63a5\u77e9\u9635\uff1f<\/strong><br \/>\u53ef\u4ee5\u4f7f\u7528NumPy\u5e93\u6765\u8f7b\u677e\u521b\u5efa0-1\u90bb\u63a5\u77e9\u9635\u3002\u9996\u5148\uff0c\u60a8\u9700\u8981\u5b89\u88c5NumPy\u5e93\uff08\u5982\u679c\u5c1a\u672a\u5b89\u88c5\uff09\uff0c\u7136\u540e\u53ef\u4ee5\u4f7f\u7528<code>numpy.zeros<\/code>\u521b\u5efa\u4e00\u4e2a\u77e9\u9635\uff0c\u5e76\u901a\u8fc7\u6307\u5b9a\u8fb9\u7684\u8fde\u63a5\u6765\u586b\u51451\u3002\u4f8b\u5982\uff0c\u53ef\u4ee5\u4f7f\u7528\u4ee5\u4e0b\u4ee3\u7801\u793a\u4f8b\uff1a<\/p>\n<pre><code class=\"language-python\">import numpy as np\n\n# \u5047\u8bbe\u67095\u4e2a\u8282\u70b9\nn = 5\nadj_matrix = np.zeros((n, n))\n\n# \u6dfb\u52a0\u8fb9\nadj_matrix[0][1] = 1\nadj_matrix[1][2] = 1\nadj_matrix[3][4] = 1\n\nprint(adj_matrix)\n<\/code><\/pre>\n<p>\u8fd9\u6837\u5c31\u80fd\u751f\u6210\u4e00\u4e2a\u5305\u542b5\u4e2a\u8282\u70b9\u7684\u90bb\u63a5\u77e9\u9635\u3002<\/p>\n<p><strong>\u90bb\u63a5\u77e9\u9635\u4e0e\u90bb\u63a5\u8868\u6709\u4ec0\u4e48\u533a\u522b\uff1f<\/strong><br \/>\u90bb\u63a5\u77e9\u9635\u548c\u90bb\u63a5\u8868\u662f\u4e24\u79cd\u8868\u793a\u56fe\u7684\u65b9\u5f0f\u3002\u90bb\u63a5\u77e9\u9635\u4f7f\u7528\u4e00\u4e2a\u4e8c\u7ef4\u6570\u7ec4\u6765\u8868\u793a\u56fe\u4e2d\u8282\u70b9\u4e4b\u95f4\u7684\u8fde\u63a5\uff0c\u9002\u5408\u4e8e\u7a20\u5bc6\u56fe\u3002\u6bcf\u4e2a\u5143\u7d20\u4e3a1\u8868\u793a\u5b58\u5728\u8fb9\uff0c\u4e3a0\u8868\u793a\u4e0d\u5b58\u5728\u8fb9\u3002\u90bb\u63a5\u8868\u5219\u4f7f\u7528\u94fe\u8868\u6216\u6570\u7ec4\u6765\u5b58\u50a8\u6bcf\u4e2a\u8282\u70b9\u7684\u90bb\u63a5\u8282\u70b9\uff0c\u66f4\u9002\u5408\u7a00\u758f\u56fe\uff0c\u8282\u7701\u7a7a\u95f4\u3002\u9009\u62e9\u54ea\u79cd\u65b9\u5f0f\u53d6\u51b3\u4e8e\u5177\u4f53\u5e94\u7528\u548c\u56fe\u7684\u7279\u6027\u3002<\/p>\n<p><strong>\u5982\u4f55\u5c06\u90bb\u63a5\u77e9\u9635\u8f6c\u6362\u4e3a\u5176\u4ed6\u56fe\u8868\u793a\u5f62\u5f0f\uff1f<\/strong><br \/>\u53ef\u4ee5\u5c06\u90bb\u63a5\u77e9\u9635\u8f6c\u6362\u4e3a\u90bb\u63a5\u8868\u6216\u8fb9\u5217\u8868\u3002\u5bf9\u4e8e\u90bb\u63a5\u8868\uff0c\u53ef\u4ee5\u904d\u5386\u77e9\u9635\u7684\u6bcf\u4e00\u884c\uff0c\u8bb0\u5f55\u6bcf\u4e2a\u8282\u70b9\u8fde\u63a5\u7684\u5176\u4ed6\u8282\u70b9\u3002\u5bf9\u4e8e\u8fb9\u5217\u8868\uff0c\u53ef\u4ee5\u904d\u5386\u6574\u4e2a\u77e9\u9635\uff0c\u8bb0\u5f55\u6240\u6709\u5b58\u5728\u7684\u8fb9\u3002\u4e0b\u9762\u662f\u4e00\u4e2a\u7b80\u5355\u7684\u793a\u4f8b\uff0c\u5c06\u90bb\u63a5\u77e9\u9635\u8f6c\u6362\u4e3a\u8fb9\u5217\u8868\uff1a<\/p>\n<pre><code class=\"language-python\">edges = []\nfor i in range(n):\n    for j in range(n):\n        if adj_matrix[i][j] == 1:\n            edges.append((i, j))\n\nprint(edges)\n<\/code><\/pre>\n<p>\u8fd9\u6837\u5c31\u80fd\u5f97\u5230\u56fe\u4e2d\u6240\u6709\u7684\u8fb9\u3002<\/p>\n","protected":false},"excerpt":{"rendered":"\u5982\u4f55\u5229\u7528Python\u7f16\u51990-1\u90bb\u63a5\u77e9\u9635 \u5229\u7528Python\u7f16\u51990-1\u90bb\u63a5\u77e9\u9635\u7684\u6838\u5fc3\u6b65\u9aa4\u5305\u62ec\uff1a\u5b9a\u4e49\u8282\u70b9\u548c\u8fb9\u3001\u4f7f\u7528\u5217 [&hellip;]","protected":false},"author":3,"featured_media":1131211,"comment_status":"closed","ping_status":"","sticky":false,"template":"","format":"standard","meta":{"_acf_changed":false,"footnotes":""},"categories":[37],"tags":[],"acf":[],"_links":{"self":[{"href":"https:\/\/docs.pingcode.com\/wp-json\/wp\/v2\/posts\/1131197"}],"collection":[{"href":"https:\/\/docs.pingcode.com\/wp-json\/wp\/v2\/posts"}],"about":[{"href":"https:\/\/docs.pingcode.com\/wp-json\/wp\/v2\/types\/post"}],"author":[{"embeddable":true,"href":"https:\/\/docs.pingcode.com\/wp-json\/wp\/v2\/users\/3"}],"replies":[{"embeddable":true,"href":"https:\/\/docs.pingcode.com\/wp-json\/wp\/v2\/comments?post=1131197"}],"version-history":[{"count":"1","href":"https:\/\/docs.pingcode.com\/wp-json\/wp\/v2\/posts\/1131197\/revisions"}],"predecessor-version":[{"id":1131214,"href":"https:\/\/docs.pingcode.com\/wp-json\/wp\/v2\/posts\/1131197\/revisions\/1131214"}],"wp:featuredmedia":[{"embeddable":true,"href":"https:\/\/docs.pingcode.com\/wp-json\/wp\/v2\/media\/1131211"}],"wp:attachment":[{"href":"https:\/\/docs.pingcode.com\/wp-json\/wp\/v2\/media?parent=1131197"}],"wp:term":[{"taxonomy":"category","embeddable":true,"href":"https:\/\/docs.pingcode.com\/wp-json\/wp\/v2\/categories?post=1131197"},{"taxonomy":"post_tag","embeddable":true,"href":"https:\/\/docs.pingcode.com\/wp-json\/wp\/v2\/tags?post=1131197"}],"curies":[{"name":"wp","href":"https:\/\/api.w.org\/{rel}","templated":true}]}}