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1. 算法实现
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<p><img alt="图的广度优先遍历" src="../graph_traversal.assets/graph_bfs.png" /></p>
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<p align="center"> 图:图的广度优先遍历 </p>
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<h3 id="_1">算法实现<a class="headerlink" href="#_1" title="Permanent link">¶</a></h3>
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<h3 id="1">1. 算法实现<a class="headerlink" href="#1" title="Permanent link">¶</a></h3>
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<p>BFS 通常借助「队列」来实现。队列具有“先入先出”的性质,这与 BFS 的“由近及远”的思想异曲同工。</p>
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<li>将遍历起始顶点 <code>startVet</code> 加入队列,并开启循环。</li>
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<p class="admonition-title">广度优先遍历的序列是否唯一?</p>
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<p>不唯一。广度优先遍历只要求按“由近及远”的顺序遍历,<strong>而多个相同距离的顶点的遍历顺序是允许被任意打乱的</strong>。以上图为例,顶点 <span class="arithmatex">\(1\)</span> , <span class="arithmatex">\(3\)</span> 的访问顺序可以交换、顶点 <span class="arithmatex">\(2\)</span> , <span class="arithmatex">\(4\)</span> , <span class="arithmatex">\(6\)</span> 的访问顺序也可以任意交换。</p>
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<h3 id="_2">复杂度分析<a class="headerlink" href="#_2" title="Permanent link">¶</a></h3>
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<h3 id="2">2. 复杂度分析<a class="headerlink" href="#2" title="Permanent link">¶</a></h3>
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<p><strong>时间复杂度:</strong> 所有顶点都会入队并出队一次,使用 <span class="arithmatex">\(O(|V|)\)</span> 时间;在遍历邻接顶点的过程中,由于是无向图,因此所有边都会被访问 <span class="arithmatex">\(2\)</span> 次,使用 <span class="arithmatex">\(O(2|E|)\)</span> 时间;总体使用 <span class="arithmatex">\(O(|V| + |E|)\)</span> 时间。</p>
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<p><strong>空间复杂度:</strong> 列表 <code>res</code> ,哈希表 <code>visited</code> ,队列 <code>que</code> 中的顶点数量最多为 <span class="arithmatex">\(|V|\)</span> ,使用 <span class="arithmatex">\(O(|V|)\)</span> 空间。</p>
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<h2 id="932">9.3.2 深度优先遍历<a class="headerlink" href="#932" title="Permanent link">¶</a></h2>
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<p><img alt="图的深度优先遍历" src="../graph_traversal.assets/graph_dfs.png" /></p>
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<p align="center"> 图:图的深度优先遍历 </p>
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<h3 id="_3">算法实现<a class="headerlink" href="#_3" title="Permanent link">¶</a></h3>
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<h3 id="1_1">1. 算法实现<a class="headerlink" href="#1_1" title="Permanent link">¶</a></h3>
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<p>这种“走到尽头 + 回溯”的算法形式通常基于递归来实现。与 BFS 类似,在 DFS 中我们也需要借助一个哈希表 <code>visited</code> 来记录已被访问的顶点,以避免重复访问顶点。</p>
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<p>与广度优先遍历类似,深度优先遍历序列的顺序也不是唯一的。给定某顶点,先往哪个方向探索都可以,即邻接顶点的顺序可以任意打乱,都是深度优先遍历。</p>
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<p>以树的遍历为例,“根 <span class="arithmatex">\(\rightarrow\)</span> 左 <span class="arithmatex">\(\rightarrow\)</span> 右”、“左 <span class="arithmatex">\(\rightarrow\)</span> 根 <span class="arithmatex">\(\rightarrow\)</span> 右”、“左 <span class="arithmatex">\(\rightarrow\)</span> 右 <span class="arithmatex">\(\rightarrow\)</span> 根”分别对应前序、中序、后序遍历,它们展示了三种不同的遍历优先级,然而这三者都属于深度优先遍历。</p>
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<h3 id="_4">复杂度分析<a class="headerlink" href="#_4" title="Permanent link">¶</a></h3>
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<h3 id="2_1">2. 复杂度分析<a class="headerlink" href="#2_1" title="Permanent link">¶</a></h3>
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<p><strong>时间复杂度:</strong> 所有顶点都会被访问 <span class="arithmatex">\(1\)</span> 次,使用 <span class="arithmatex">\(O(|V|)\)</span> 时间;所有边都会被访问 <span class="arithmatex">\(2\)</span> 次,使用 <span class="arithmatex">\(O(2|E|)\)</span> 时间;总体使用 <span class="arithmatex">\(O(|V| + |E|)\)</span> 时间。</p>
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<p><strong>空间复杂度:</strong> 列表 <code>res</code> ,哈希表 <code>visited</code> 顶点数量最多为 <span class="arithmatex">\(|V|\)</span> ,递归深度最大为 <span class="arithmatex">\(|V|\)</span> ,因此使用 <span class="arithmatex">\(O(|V|)\)</span> 空间。</p>
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