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https://github.com/krahets/hello-algo.git
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2655a2f66a
* Add kotlin code block for chapter_hashing * Add kotlin code block for chapter_heap. * Add kotlin code block for chapter_stack_and_queue and chapter_tree * fix indentation * Update binary_tree.md * style(kotlin): simplify code and improve readability. * simplify kt code for chapter_computational_complexity. * style(kotlin): replace ArrayList with MutableList. * Update subset_sum_i.kt Use kotlin api instead of java. * Update subset_sum_ii.kt use kotlin api instead of java * style(kotlin): replace ArrayList with mutablelist. --------- Co-authored-by: Yudong Jin <krahets@163.com>
167 lines
No EOL
3.9 KiB
Kotlin
167 lines
No EOL
3.9 KiB
Kotlin
/**
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* File: time_complexity.kt
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* Created Time: 2024-01-25
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* Author: curtishd (1023632660@qq.com)
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*/
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package chapter_computational_complexity.time_complexity
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/* 常数阶 */
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fun constant(n: Int): Int {
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var count = 0
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val size = 100000
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for (i in 0..<size)
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count++
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return count
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}
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/* 线性阶 */
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fun linear(n: Int): Int {
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var count = 0
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// 循环次数与数组长度成正比
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for (i in 0..<n)
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count++
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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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fun arrayTraversal(nums: IntArray): Int {
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var count = 0
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// 循环次数与数组长度成正比
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for (num in 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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fun quadratic(n: Int): Int {
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var count = 0
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// 循环次数与数据大小 n 成平方关系
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for (i in 0..<n) {
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for (j in 0..<n) {
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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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fun bubbleSort(nums: IntArray): Int {
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var count = 0 // 计数器
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// 外循环:未排序区间为 [0, i]
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for (i in nums.size - 1 downTo 1) {
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// 内循环:将未排序区间 [0, i] 中的最大元素交换至该区间的最右端
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for (j in 0..<i) {
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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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nums[j] = nums[j + 1].also { nums[j + 1] = nums[j] }
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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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fun exponential(n: Int): Int {
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var count = 0
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// 细胞每轮一分为二,形成数列 1, 2, 4, 8, ..., 2^(n-1)
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var base = 1
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for (i in 0..<n) {
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for (j in 0..<base) {
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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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fun 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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fun logarithmic(n: Int): Int {
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var n1 = n
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var count = 0
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while (n1 > 1) {
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n1 /= 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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fun logRecur(n: Int): Int {
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if (n <= 1)
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return 0
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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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fun linearLogRecur(n: Int): Int {
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if (n <= 1)
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return 1
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var count = linearLogRecur(n / 2) + linearLogRecur(n / 2)
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for (i in 0..<n) {
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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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fun factorialRecur(n: Int): Int {
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if (n == 0)
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return 1
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var count = 0
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// 从 1 个分裂出 n 个
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for (i in 0..<n) {
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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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/* Driver Code */
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fun main() {
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// 可以修改 n 运行,体会一下各种复杂度的操作数量变化趋势
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val n = 8
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println("输入数据大小 n = $n")
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var count = constant(n)
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println("常数阶的操作数量 = $count")
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count = linear(n)
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println("线性阶的操作数量 = $count")
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count = arrayTraversal(IntArray(n))
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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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println("平方阶的操作数量 = $count")
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val nums = IntArray(n)
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for (i in 0..<n)
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nums[i] = n - i // [n,n-1,...,2,1]
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count = bubbleSort(nums)
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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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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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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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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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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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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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println("阶乘阶(递归实现)的操作数量 = $count")
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} |