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// File: quick_sort_test.go
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// Created Time: 2022-12-13
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// Author: msk397 (machangxinq@gmail.com)
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package time_complexity
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/* 常数阶 */
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func constant(n int) int {
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count := 0
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size := 100000
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for i := 0; i < size; i++ {
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count++
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}
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return count
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}
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/* 线性阶 */
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func linear(n int) int {
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count := 0
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for i := 0; i < n; i++ {
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count++
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}
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return count
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}
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/* 线性阶(遍历数组) */
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func arrayTraversal(nums []int) int {
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count := 0
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// 循环次数与数组长度成正比
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for range nums {
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count++
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}
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return count
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}
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/* 平方阶 */
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func quadratic(n int) int {
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count := 0
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// 循环次数与数组长度成平方关系
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for i := 0; i < n; i++ {
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for j := 0; j < n; j++ {
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count++
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}
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}
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return count
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}
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/* 平方阶(冒泡排序) */
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func bubbleSort(nums []int) int {
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count := 0 // 计数器
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// 外循环:待排序元素数量为 n-1, n-2, ..., 1
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for i := len(nums) - 1; i > 0; i-- {
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// 内循环:冒泡操作
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for j := 0; j < i; j++ {
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if nums[j] > nums[j+1] {
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// 交换 nums[j] 与 nums[j + 1]
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tmp := nums[j]
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nums[j] = nums[j+1]
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nums[j+1] = tmp
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count += 3 // 元素交换包含 3 个单元操作
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}
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}
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}
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return count
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}
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/* 指数阶(循环实现)*/
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func exponential(n int) int {
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count, base := 0, 1
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// cell 每轮一分为二,形成数列 1, 2, 4, 8, ..., 2^(n-1)
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for i := 0; i < n; i++ {
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for j := 0; j < base; j++ {
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count++
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}
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base *= 2
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}
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// count = 1 + 2 + 4 + 8 + .. + 2^(n-1) = 2^n - 1
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return count
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}
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/* 指数阶(递归实现)*/
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func expRecur(n int) int {
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if n == 1 {
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return 1
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}
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return expRecur(n-1) + expRecur(n-1) + 1
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}
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/* 对数阶(循环实现)*/
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func logarithmic(n float64) int {
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count := 0
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for n > 1 {
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n = n / 2
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count++
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}
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return count
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}
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/* 对数阶(递归实现)*/
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func logRecur(n float64) int {
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if n <= 1 {
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return 0
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}
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return logRecur(n/2) + 1
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}
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/* 线性对数阶 */
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func linearLogRecur(n float64) int {
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if n <= 1 {
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return 1
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}
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count := linearLogRecur(n/2) +
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linearLogRecur(n/2)
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for i := 0.0; i < n; i++ {
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count++
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}
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return count
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}
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/* 阶乘阶(递归实现) */
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func factorialRecur(n int) int {
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if n == 0 {
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return 1
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}
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count := 0
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// 从 1 个分裂出 n 个
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for i := 0; i < n; i++ {
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count += factorialRecur(n - 1)
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}
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return count
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}
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// File: quick_sort_test.go
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// Created Time: 2022-12-13
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// Author: msk397 (machangxinq@gmail.com)
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package time_complexity
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import (
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"fmt"
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"testing"
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)
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func TestTimeComplexity(t *testing.T) {
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n := 8
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fmt.Println("输入数据大小 n =", n)
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count := constant(n)
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fmt.Println("常数阶的计算操作数量 =", count)
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count = linear(n)
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fmt.Println("线性阶的计算操作数量 =", count)
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count = arrayTraversal(make([]int, n))
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fmt.Println("线性阶(遍历数组)的计算操作数量 =", count)
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count = quadratic(n)
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fmt.Println("平方阶的计算操作数量 =", count)
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nums := make([]int, n)
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for i := 0; i < n; i++ {
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nums[i] = n - i
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}
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count = bubbleSort(nums)
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fmt.Println("平方阶(冒泡排序)的计算操作数量 =", count)
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count = exponential(n)
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fmt.Println("指数阶(循环实现)的计算操作数量 =", count)
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count = expRecur(n)
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fmt.Println("指数阶(递归实现)的计算操作数量 =", count)
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count = logarithmic(float64(n))
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fmt.Println("对数阶(循环实现)的计算操作数量 =", count)
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count = logRecur(float64(n))
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fmt.Println("对数阶(递归实现)的计算操作数量 =", count)
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count = linearLogRecur(float64(n))
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fmt.Println("线性对数阶(递归实现)的计算操作数量 =", count)
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count = factorialRecur(n)
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fmt.Println("阶乘阶(递归实现)的计算操作数量 =", count)
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}
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@ -0,0 +1,45 @@
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// File: worst_best_time_complexity.go
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// Created Time: 2022-12-13
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// Author: msk397 (machangxinq@gmail.com)
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package time_complexity
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import (
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"fmt"
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"math/rand"
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)
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/* 生成一个数组,元素为 { 1, 2, ..., n },顺序被打乱 */
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func randomNumbers(n int) []int {
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nums := make([]int, n)
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// 生成数组 nums = { 1, 2, 3, ..., n }
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for i := 0; i < n; i++ {
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nums[i] = i + 1
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}
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// 随机打乱数组元素
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rand.Shuffle(len(nums), func(i, j int) {
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nums[i], nums[j] = nums[j], nums[i]
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})
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return nums
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}
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/* 查找数组 nums 中数字 1 所在索引 */
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func findOne(nums []int) int {
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for i := 0; i < len(nums); i++ {
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if nums[i] == 1 {
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return i
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}
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}
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return -1
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}
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/* Driver Code */
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func main() {
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for i := 0; i < 10; i++ {
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n := 100
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nums := randomNumbers(n)
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index := findOne(nums)
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fmt.Println("\n数组 [ 1, 2, ..., n ] 被打乱后 =", nums)
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fmt.Println("数字 1 的索引为", index)
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}
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}
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package merge_sort
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// File: merge_sort.go
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// Created Time: 2022-12-13
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// Author: msk397 (machangxinq@gmail.com)
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/*
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合并左子数组和右子数组
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左子数组区间 [left, mid]
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右子数组区间 [mid + 1, right]
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*/
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func merge(nums []int, left, mid, right int) {
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// 初始化辅助数组 借助 copy模块
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tmp := make([]int, right-left+1)
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for i := left; i <= right; i++ {
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tmp[i-left] = nums[i]
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}
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// 左子数组的起始索引和结束索引
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left_start, left_end := left-left, mid-left
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// 右子数组的起始索引和结束索引
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right_start, right_end := mid+1-left, right-left
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// i, j 分别指向左子数组、右子数组的首元素
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i, j := left_start, right_start
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// 通过覆盖原数组 nums 来合并左子数组和右子数组
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for k := left; k <= right; k++ {
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// 若 “左子数组已全部合并完”,则选取右子数组元素,并且 j++
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if i > left_end {
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nums[k] = tmp[j]
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j++
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// 否则,若 “右子数组已全部合并完” 或 “左子数组元素 < 右子数组元素”,则选取左子数组元素,并且 i++
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} else if j > right_end || tmp[i] <= tmp[j] {
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nums[k] = tmp[i]
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i++
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// 否则,若 “左子数组元素 > 右子数组元素”,则选取右子数组元素,并且 j++
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} else {
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nums[k] = tmp[j]
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j++
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}
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}
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}
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func mergeSort(nums []int, left, right int) {
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// 终止条件
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if left >= right {
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return
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}
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// 划分阶段
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mid := (left + right) / 2
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mergeSort(nums, left, mid)
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mergeSort(nums, mid+1, right)
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// 合并阶段
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merge(nums, left, mid, right)
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}
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@ -0,0 +1,15 @@
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package merge_sort
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// File: merge_sort_test.go
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// Created Time: 2022-12-13
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// Author: msk397 (machangxinq@gmail.com)
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import (
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"fmt"
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"testing"
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)
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func TestMergeSort(t *testing.T) {
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nums := []int{7, 3, 2, 6, 0, 1, 5, 4}
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mergeSort(nums, 0, len(nums)-1)
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fmt.Println("归并排序完成后 nums = ", nums)
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}
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Loading…
Reference in new issue