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Add kotlin code for the chapter of heap (#1115)
* feat(kotlin): add kotlin code for dynamic programming. * Update knapsack.kt * feat(kotlin): add kotlin codes for graph. * style(kotlin): reformatted the codes. * feat(kotlin): add kotlin codes for the chapter of greedy. * Update max_product_cutting.kt * feat(kotlin): add kotlin code for chapter of hashing. * style(kotlin): modified some comment * Update array_hash_map.kt * Update hash_map_chaining.kt * Update hash_map_chaining.kt * feat(kotlin): add kotlin codes for the chapter of heap. * Update my_heap.kt
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66
codes/kotlin/chapter_heap/heap.kt
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66
codes/kotlin/chapter_heap/heap.kt
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/**
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* File: heap.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_heap
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import utils.printHeap
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import java.util.*
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fun testPush(heap: Queue<Int>, value: Int) {
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heap.offer(value) // 元素入堆
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print("\n元素 $value 入堆后\n")
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printHeap(heap)
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}
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fun testPop(heap: Queue<Int>) {
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val value = heap.poll() // 堆顶元素出堆
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print("\n堆顶元素 $value 出堆后\n")
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printHeap(heap)
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}
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/* Driver Code */
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fun main() {
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/* 初始化堆 */
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// 初始化小顶堆
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val minHeap: PriorityQueue<Int>
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// 初始化大顶堆(使用 lambda 表达式修改 Comparator 即可)
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val maxHeap = PriorityQueue { a: Int, b: Int -> b - a }
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println("\n以下测试样例为大顶堆")
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/* 元素入堆 */
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testPush(maxHeap, 1)
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testPush(maxHeap, 3)
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testPush(maxHeap, 2)
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testPush(maxHeap, 5)
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testPush(maxHeap, 4)
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/* 获取堆顶元素 */
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val peek = maxHeap.peek()
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print("\n堆顶元素为 $peek\n")
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/* 堆顶元素出堆 */
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testPop(maxHeap)
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testPop(maxHeap)
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testPop(maxHeap)
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testPop(maxHeap)
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testPop(maxHeap)
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/* 获取堆大小 */
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val size = maxHeap.size
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print("\n堆元素数量为 $size\n")
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/* 判断堆是否为空 */
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val isEmpty = maxHeap.isEmpty()
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print("\n堆是否为空 $isEmpty\n")
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/* 输入列表并建堆 */
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// 时间复杂度为 O(n) ,而非 O(nlogn)
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minHeap = PriorityQueue(mutableListOf<Int?>(1, 3, 2, 5, 4))
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println("\n输入列表并建立小顶堆后")
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printHeap(minHeap)
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}
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157
codes/kotlin/chapter_heap/my_heap.kt
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codes/kotlin/chapter_heap/my_heap.kt
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/**
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* File: my_heap.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_heap
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import utils.printHeap
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import java.util.*
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/* 大顶堆 */
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class MaxHeap(nums: List<Int>?) {
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// 使用列表而非数组,这样无须考虑扩容问题
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// 将列表元素原封不动添加进堆
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private val maxHeap = ArrayList(nums!!)
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/* 构造函数,根据输入列表建堆 */
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init {
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// 堆化除叶节点以外的其他所有节点
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for (i in parent(size() - 1) downTo 0) {
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siftDown(i)
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}
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}
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/* 获取左子节点的索引 */
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private fun left(i: Int): Int {
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return 2 * i + 1
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}
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/* 获取右子节点的索引 */
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private fun right(i: Int): Int {
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return 2 * i + 2
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}
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/* 获取父节点的索引 */
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private fun parent(i: Int): Int {
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return (i - 1) / 2 // 向下整除
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}
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/* 交换元素 */
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private fun swap(i: Int, j: Int) {
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maxHeap[i] = maxHeap[j].also { maxHeap[j] = maxHeap[i] }
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}
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/* 获取堆大小 */
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fun size(): Int {
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return maxHeap.size
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}
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/* 判断堆是否为空 */
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fun isEmpty(): Boolean {
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/* 判断堆是否为空 */
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return size() == 0
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}
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/* 访问堆顶元素 */
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fun peek(): Int {
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return maxHeap[0]
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}
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/* 元素入堆 */
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fun push(value: Int) {
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// 添加节点
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maxHeap.add(value)
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// 从底至顶堆化
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siftUp(size() - 1)
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}
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/* 从节点 i 开始,从底至顶堆化 */
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private fun siftUp(it: Int) {
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// Kotlin的函数参数不可变,因此创建临时变量
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var i = it
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while (true) {
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// 获取节点 i 的父节点
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val p = parent(i)
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// 当“越过根节点”或“节点无须修复”时,结束堆化
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if (p < 0 || maxHeap[i] <= maxHeap[p]) break
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// 交换两节点
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swap(i, p)
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// 循环向上堆化
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i = p
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}
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}
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/* 元素出堆 */
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fun pop(): Int {
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// 判空处理
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if (isEmpty()) throw IndexOutOfBoundsException()
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// 交换根节点与最右叶节点(交换首元素与尾元素)
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swap(0, size() - 1)
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// 删除节点
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val value = maxHeap.removeAt(size() - 1)
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// 从顶至底堆化
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siftDown(0)
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// 返回堆顶元素
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return value
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}
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/* 从节点 i 开始,从顶至底堆化 */
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private fun siftDown(it: Int) {
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// Kotlin的函数参数不可变,因此创建临时变量
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var i = it
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while (true) {
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// 判断节点 i, l, r 中值最大的节点,记为 ma
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val l = left(i)
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val r = right(i)
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var ma = i
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if (l < size() && maxHeap[l] > maxHeap[ma]) ma = l
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if (r < size() && maxHeap[r] > maxHeap[ma]) ma = r
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// 若节点 i 最大或索引 l, r 越界,则无须继续堆化,跳出
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if (ma == i) break
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// 交换两节点
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swap(i, ma)
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// 循环向下堆化
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i = ma
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}
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}
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/* 打印堆(二叉树) */
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fun print() {
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val queue = PriorityQueue { a: Int, b: Int -> b - a }
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queue.addAll(maxHeap)
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printHeap(queue)
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}
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}
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/* Driver Code */
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fun main() {
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/* 初始化大顶堆 */
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val maxHeap = MaxHeap(mutableListOf(9, 8, 6, 6, 7, 5, 2, 1, 4, 3, 6, 2))
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println("\n输入列表并建堆后")
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maxHeap.print()
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/* 获取堆顶元素 */
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var peek = maxHeap.peek()
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print("\n堆顶元素为 $peek\n")
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/* 元素入堆 */
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val value = 7
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maxHeap.push(value)
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print("\n元素 $value 入堆后\n")
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maxHeap.print()
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/* 堆顶元素出堆 */
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peek = maxHeap.pop()
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print("\n堆顶元素 $peek 出堆后\n")
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maxHeap.print()
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/* 获取堆大小 */
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val size = maxHeap.size()
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print("\n堆元素数量为 $size\n")
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/* 判断堆是否为空 */
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val isEmpty = maxHeap.isEmpty()
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print("\n堆是否为空 $isEmpty\n")
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}
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38
codes/kotlin/chapter_heap/top_k.kt
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38
codes/kotlin/chapter_heap/top_k.kt
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/**
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* File: top_k.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_heap
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import utils.printHeap
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import java.util.*
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/* 基于堆查找数组中最大的 k 个元素 */
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fun topKHeap(nums: IntArray, k: Int): Queue<Int> {
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// 初始化小顶堆
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val heap = PriorityQueue<Int>()
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// 将数组的前 k 个元素入堆
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for (i in 0..<k) {
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heap.offer(nums[i])
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}
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// 从第 k+1 个元素开始,保持堆的长度为 k
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for (i in k..<nums.size) {
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// 若当前元素大于堆顶元素,则将堆顶元素出堆、当前元素入堆
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if (nums[i] > heap.peek()) {
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heap.poll()
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heap.offer(nums[i])
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}
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}
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return heap
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}
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/* Driver Code */
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fun main() {
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val nums = intArrayOf(1, 7, 6, 3, 2)
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val k = 3
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val res = topKHeap(nums, k)
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println("最大的 $k 个元素为")
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printHeap(res)
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}
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