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3ea91bda99
* Use int instead of float for the example code of log time complexity * Bug fixes * Bug fixes
48 lines
1.3 KiB
Go
48 lines
1.3 KiB
Go
// File: time_complexity_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 chapter_computational_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("常数阶的操作数量 =", count)
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count = linear(n)
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fmt.Println("线性阶的操作数量 =", count)
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count = arrayTraversal(make([]int, n))
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fmt.Println("线性阶(遍历数组)的操作数量 =", count)
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count = quadratic(n)
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fmt.Println("平方阶的操作数量 =", 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)的操作数量 =", count)
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count = logarithmic(n)
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fmt.Println("对数阶(循环实现)的操作数量 =", count)
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count = logRecur(n)
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fmt.Println("对数阶(递归实现)的操作数量 =", count)
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count = linearLogRecur(n)
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fmt.Println("线性对数阶(递归实现)的操作数量 =", count)
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count = factorialRecur(n)
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fmt.Println("阶乘阶(递归实现)的操作数量 =", count)
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}
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