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---
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comments: true
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---
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# 11.2. 选择排序
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「选择排序 Selection Sort」的工作原理非常直接:开启一个循环,每轮从未排序区间选择最小的元素,将其放到已排序区间的末尾。
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设数组的长度为 $n$ ,选择排序的算法流程如下:
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1. 初始状态下,所有元素未排序,即未排序(索引)区间为 $[0, n-1]$ 。
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2. 选取区间 $[0, n-1]$ 中的最小元素,将其与索引 $0$ 处元素交换。完成后,数组前 1 个元素已排序。
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3. 选取区间 $[1, n-1]$ 中的最小元素,将其与索引 $1$ 处元素交换。完成后,数组前 2 个元素已排序。
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4. 以此类推。经过 $n - 1$ 轮选择与交换后,数组前 $n - 1$ 个元素已排序。
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5. 仅剩的一个元素必定是最大元素,无需排序,因此数组排序完成。
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=== "<1>"
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![选择排序步骤](selection_sort.assets/selection_sort_step1.png)
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=== "<2>"
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![selection_sort_step2](selection_sort.assets/selection_sort_step2.png)
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=== "<3>"
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![selection_sort_step3](selection_sort.assets/selection_sort_step3.png)
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=== "<4>"
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![selection_sort_step4](selection_sort.assets/selection_sort_step4.png)
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=== "<5>"
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![selection_sort_step5](selection_sort.assets/selection_sort_step5.png)
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=== "<6>"
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![selection_sort_step6](selection_sort.assets/selection_sort_step6.png)
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=== "<7>"
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![selection_sort_step7](selection_sort.assets/selection_sort_step7.png)
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=== "<8>"
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![selection_sort_step8](selection_sort.assets/selection_sort_step8.png)
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=== "<9>"
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![selection_sort_step9](selection_sort.assets/selection_sort_step9.png)
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=== "<10>"
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![selection_sort_step10](selection_sort.assets/selection_sort_step10.png)
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=== "<11>"
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![selection_sort_step11](selection_sort.assets/selection_sort_step11.png)
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在代码中,我们用 $k$ 来记录未排序区间内的最小元素。
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=== "Java"
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```java title="selection_sort.java"
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/* 选择排序 */
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void selectionSort(int[] nums) {
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int n = nums.length;
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// 外循环:未排序区间为 [i, n-1]
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for (int i = 0; i < n - 1; i++) {
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// 内循环:找到未排序区间内的最小元素
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int k = i;
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for (int j = i + 1; j < n; j++) {
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if (nums[j] < nums[k])
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k = j; // 记录最小元素的索引
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}
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// 将该最小元素与未排序区间的首个元素交换
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int temp = nums[i];
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nums[i] = nums[k];
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nums[k] = temp;
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}
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}
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```
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=== "C++"
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```cpp title="selection_sort.cpp"
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/* 选择排序 */
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void selectionSort(vector<int> &nums) {
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int n = nums.size();
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// 外循环:未排序区间为 [i, n-1]
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for (int i = 0; i < n - 1; i++) {
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// 内循环:找到未排序区间内的最小元素
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int k = i;
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for (int j = i + 1; j < n; j++) {
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if (nums[j] < nums[k])
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k = j; // 记录最小元素的索引
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}
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// 将该最小元素与未排序区间的首个元素交换
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swap(nums[i], nums[k]);
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}
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}
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```
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=== "Python"
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```python title="selection_sort.py"
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def selection_sort(nums: list[int]):
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"""选择排序"""
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n = len(nums)
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# 外循环:未排序区间为 [i, n-1]
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for i in range(n - 1):
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# 内循环:找到未排序区间内的最小元素
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k = i
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for j in range(i + 1, n):
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if nums[j] < nums[k]:
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k = j # 记录最小元素的索引
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# 将该最小元素与未排序区间的首个元素交换
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nums[i], nums[k] = nums[k], nums[i]
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```
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=== "Go"
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```go title="selection_sort.go"
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/* 选择排序 */
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func selectionSort(nums []int) {
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n := len(nums)
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// 外循环:未排序区间为 [i, n-1]
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for i := 0; i < n-1; i++ {
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// 内循环:找到未排序区间内的最小元素
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k := i
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for j := i + 1; j < n; j++ {
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if nums[j] < nums[k] {
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// 记录最小元素的索引
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k = j
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}
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}
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// 将该最小元素与未排序区间的首个元素交换
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nums[i], nums[k] = nums[k], nums[i]
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}
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}
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```
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=== "JS"
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```javascript title="selection_sort.js"
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/* 选择排序 */
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function selectionSort(nums) {
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let n = nums.length;
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// 外循环:未排序区间为 [i, n-1]
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for (let i = 0; i < n - 1; i++) {
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// 内循环:找到未排序区间内的最小元素
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let k = i;
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for (let j = i + 1; j < n; j++) {
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if (nums[j] < nums[k]) {
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k = j; // 记录最小元素的索引
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}
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}
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// 将该最小元素与未排序区间的首个元素交换
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[nums[i], nums[k]] = [nums[k], nums[i]];
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}
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}
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```
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=== "TS"
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```typescript title="selection_sort.ts"
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/* 选择排序 */
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function selectionSort(nums: number[]): void {
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let n = nums.length;
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// 外循环:未排序区间为 [i, n-1]
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for (let i = 0; i < n - 1; i++) {
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// 内循环:找到未排序区间内的最小元素
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let k = i;
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for (let j = i + 1; j < n; j++) {
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if (nums[j] < nums[k]) {
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k = j; // 记录最小元素的索引
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}
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}
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// 将该最小元素与未排序区间的首个元素交换
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[nums[i], nums[k]] = [nums[k], nums[i]];
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}
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}
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```
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=== "C"
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```c title="selection_sort.c"
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/* 选择排序 */
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void selectionSort(int nums[], int n) {
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// 外循环:未排序区间为 [i, n-1]
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for (int i = 0; i < n - 1; i++) {
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// 内循环:找到未排序区间内的最小元素
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int k = i;
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for (int j = i + 1; j < n; j++) {
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if (nums[j] < nums[k])
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k = j; // 记录最小元素的索引
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}
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// 将该最小元素与未排序区间的首个元素交换
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int temp = nums[i];
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nums[i] = nums[k];
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nums[k] = temp;
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}
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}
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```
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=== "C#"
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```csharp title="selection_sort.cs"
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/* 选择排序 */
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void selectionSort(int[] nums) {
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int n = nums.Length;
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// 外循环:未排序区间为 [i, n-1]
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for (int i = 0; i < n - 1; i++) {
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// 内循环:找到未排序区间内的最小元素
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int k = i;
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for (int j = i + 1; j < n; j++) {
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if (nums[j] < nums[k])
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k = j; // 记录最小元素的索引
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}
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// 将该最小元素与未排序区间的首个元素交换
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(nums[k], nums[i]) = (nums[i], nums[k]);
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}
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}
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```
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=== "Swift"
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```swift title="selection_sort.swift"
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/* 选择排序 */
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func selectionSort(nums: inout [Int]) {
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// 外循环:未排序区间为 [i, n-1]
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for i in nums.indices.dropLast() {
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// 内循环:找到未排序区间内的最小元素
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var k = i
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for j in nums.indices.dropFirst(i + 1) {
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if nums[j] < nums[k] {
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k = j // 记录最小元素的索引
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}
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}
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// 将该最小元素与未排序区间的首个元素交换
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nums.swapAt(i, k)
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}
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}
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```
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=== "Zig"
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```zig title="selection_sort.zig"
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[class]{}-[func]{selectionSort}
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```
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=== "Dart"
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```dart title="selection_sort.dart"
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/* 选择排序 */
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void selectionSort(List<int> nums) {
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int n = nums.length;
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// 外循环:未排序区间为 [i, n-1]
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for (int i = 0; i < n - 1; i++) {
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// 内循环:找到未排序区间内的最小元素
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int k = i;
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for (int j = i + 1; j < n; j++) {
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if (nums[j] < nums[k]) k = j; // 记录最小元素的索引
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}
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// 将该最小元素与未排序区间的首个元素交换
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int temp = nums[i];
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nums[i] = nums[k];
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nums[k] = temp;
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}
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}
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```
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=== "Rust"
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```rust title="selection_sort.rs"
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/* 选择排序 */
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fn selection_sort(nums: &mut [i32]) {
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let n = nums.len();
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// 外循环:未排序区间为 [i, n-1]
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for i in 0..n-1 {
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// 内循环:找到未排序区间内的最小元素
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let mut k = i;
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for j in i+1..n {
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if nums[j] < nums[k] {
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k = j; // 记录最小元素的索引
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}
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}
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// 将该最小元素与未排序区间的首个元素交换
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nums.swap(i, k);
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}
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}
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```
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## 11.2.1. 算法特性
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- **时间复杂度为 $O(n^2)$ 、非自适应排序**:外循环共 $n - 1$ 轮,第一轮的未排序区间长度为 $n$ ,最后一轮的未排序区间长度为 $2$ ,即各轮外循环分别包含 $n$ , $n - 1$ , $\cdots$ , $2$ 轮内循环,求和为 $\frac{(n - 1)(n + 2)}{2}$ 。
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- **空间复杂度 $O(1)$ 、原地排序**:指针 $i$ , $j$ 使用常数大小的额外空间。
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- **非稳定排序**:在交换元素时,有可能将 `nums[i]` 交换至其相等元素的右边,导致两者的相对顺序发生改变。
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![选择排序非稳定示例](selection_sort.assets/selection_sort_instability.png)
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<p align="center"> Fig. 选择排序非稳定示例 </p>
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