hello-algo/codes/kotlin/chapter_heap/top_k.kt
curtishd a05192ea0f
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
2024-03-15 01:12:00 +08:00

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914 B
Kotlin

/**
* File: top_k.kt
* Created Time: 2024-01-25
* Author: curtishd (1023632660@qq.com)
*/
package chapter_heap
import utils.printHeap
import java.util.*
/* 基于堆查找数组中最大的 k 个元素 */
fun topKHeap(nums: IntArray, k: Int): Queue<Int> {
// 初始化小顶堆
val heap = PriorityQueue<Int>()
// 将数组的前 k 个元素入堆
for (i in 0..<k) {
heap.offer(nums[i])
}
// 从第 k+1 个元素开始,保持堆的长度为 k
for (i in k..<nums.size) {
// 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
if (nums[i] > heap.peek()) {
heap.poll()
heap.offer(nums[i])
}
}
return heap
}
/* Driver Code */
fun main() {
val nums = intArrayOf(1, 7, 6, 3, 2)
val k = 3
val res = topKHeap(nums, k)
println("最大的 $k 个元素为")
printHeap(res)
}