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chapter_sorting/radix_sort/index.html
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<h1 id="118">11.8. &nbsp; 基数排序<a class="headerlink" href="#118" title="Permanent link">&para;</a></h1>
<p>上一节我们介绍了计数排序，它适用于数据量 <span class="arithmatex">\(n\)</span> 较大但数据范围 <span class="arithmatex">\(m\)</span> 较小的情况。假设我们需要对 <span class="arithmatex">\(n = 10^6\)</span> 个学号进行排序，而学号是一个 <span class="arithmatex">\(8\)</span> 位数字，这意味着数据范围 <span class="arithmatex">\(m = 10^8\)</span> 非常大，使用计数排序需要分配大量内存空间，而基数排序可以避免这种情况。</p>
<p>「基数排序 Radix Sort」的核心思想与计数排序一致，也通过统计个数来实现排序。在此基础上，基数排序利用数字各位之间的递进关系，依次对每一位进行排序**，从而得到最终的排序结果。</p>
<p>「基数排序 Radix Sort」的核心思想与计数排序一致，也通过统计个数来实现排序。在此基础上，基数排序利用数字各位之间的递进关系，依次对每一位进行排序，从而得到最终的排序结果。</p>
<h2 id="1181">11.8.1. &nbsp; 算法流程<a class="headerlink" href="#1181" title="Permanent link">&para;</a></h2>
<p>以学号数据为例，假设数字的最低位是第 <span class="arithmatex">\(1\)</span> 位，最高位是第 <span class="arithmatex">\(8\)</span> 位，基数排序的步骤如下：</p>
<ol>

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<li>完美二叉树是理想情况，可以充分发挥二叉树“分治”的优势；</li>
<li>链表则是另一个极端，各项操作都变为线性操作，时间复杂度退化至 <span class="arithmatex">\(O(n)\)</span> ；</li>
</ul>
<p><img alt="二叉树的最佳与最二叉树的最佳和最差结构差情况" src="../binary_tree.assets/binary_tree_corner_cases.png" /></p>
<p align="center"> Fig. 二叉树的最佳与最二叉树的最佳和最差结构差情况 </p>
<p><img alt="二叉树的最佳与最差结构" src="../binary_tree.assets/binary_tree_corner_cases.png" /></p>
<p align="center"> Fig. 二叉树的最佳与最差结构 </p>
<p>如下表所示，在最佳和最差结构下，二叉树的叶节点数量、节点总数、高度等达到极大或极小值。</p>
<div class="center-table">

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