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feature(swift): Reimplement merge_sort and top_k (#898)
* feat: Add swift-collections * fix: use heap * refactor: merge * fix: import HeapModule
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4 changed files with 52 additions and 33 deletions
14
codes/swift/Package.resolved
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14
codes/swift/Package.resolved
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@ -0,0 +1,14 @@
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{
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"pins" : [
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{
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"identity" : "swift-collections",
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"kind" : "remoteSourceControl",
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"location" : "https://github.com/apple/swift-collections",
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"state" : {
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"branch" : "release/1.1",
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"revision" : "4a1d92ba85027010d2c528c05576cde9a362254b"
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}
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}
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],
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"version" : 2
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}
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@ -99,6 +99,9 @@ let package = Package(
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.executable(name: "max_capacity", targets: ["max_capacity"]),
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.executable(name: "max_product_cutting", targets: ["max_product_cutting"]),
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],
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dependencies: [
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.package(url: "https://github.com/apple/swift-collections", branch: "release/1.1"),
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],
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targets: [
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// helper
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.target(name: "utils", path: "utils"),
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@ -141,7 +144,7 @@ let package = Package(
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.executableTarget(name: "avl_tree", dependencies: ["utils"], path: "chapter_tree", sources: ["avl_tree.swift"]),
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// chapter_heap
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.executableTarget(name: "my_heap", dependencies: ["utils"], path: "chapter_heap", sources: ["my_heap.swift"]),
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.executableTarget(name: "top_k", dependencies: ["utils"], path: "chapter_heap", sources: ["top_k.swift"]),
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.executableTarget(name: "top_k", dependencies: ["utils", .product(name: "HeapModule", package: "swift-collections")], path: "chapter_heap", sources: ["top_k.swift"]),
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// chapter_graph
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.executableTarget(name: "graph_adjacency_matrix", dependencies: ["utils"], path: "chapter_graph", sources: ["graph_adjacency_matrix.swift"]),
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.executableTarget(name: "graph_adjacency_list", dependencies: ["utils"], path: "chapter_graph", sources: ["graph_adjacency_list.swift"]),
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@ -4,21 +4,22 @@
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* Author: nuomi1 (nuomi1@qq.com)
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*/
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import HeapModule
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import utils
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/* 基于堆查找数组中最大的 k 个元素 */
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func topKHeap(nums: [Int], k: Int) -> [Int] {
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// 将数组的前 k 个元素入堆
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var heap = Array(nums.prefix(k))
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var heap = Heap(nums.prefix(k))
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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 stride(from: k, to: nums.count, by: 1) {
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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.first! {
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heap.removeFirst()
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heap.insert(nums[i], at: 0)
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if nums[i] > heap.min()! {
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_ = heap.removeMin()
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heap.insert(nums[i])
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}
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}
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return heap
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return heap.unordered
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}
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@main
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@ -5,38 +5,39 @@
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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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func merge(nums: inout [Int], left: Int, mid: Int, right: Int) {
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// 初始化辅助数组
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let tmp = Array(nums[left ..< (right + 1)])
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// 左子数组的起始索引和结束索引
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let leftStart = left - left
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let leftEnd = mid - left
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// 右子数组的起始索引和结束索引
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let rightStart = mid + 1 - left
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let rightEnd = 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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var i = leftStart
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var j = rightStart
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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 in left ... right {
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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 > leftEnd {
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nums[k] = tmp[j]
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j += 1
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}
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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 > rightEnd || tmp[i] <= tmp[j] {
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nums[k] = tmp[i]
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// 左子数组区间 [left, mid], 右子数组区间 [mid+1, right]
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// 创建一个临时数组 tmp ,用于存放合并后的结果
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var tmp = Array(repeating: 0, count: right - left + 1)
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// 初始化左子数组和右子数组的起始索引
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var i = left, j = mid + 1, k = 0
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// 当左右子数组都还有元素时,比较并将较小的元素复制到临时数组中
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while i <= mid, j <= right {
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if nums[i] <= nums[j] {
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tmp[k] = nums[i]
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i += 1
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}
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// 否则,若“左右子数组都未全部合并完”且“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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k += 1
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} else {
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tmp[k] = nums[j]
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j += 1
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k += 1
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}
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}
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// 将左子数组和右子数组的剩余元素复制到临时数组中
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while i <= mid {
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tmp[k] = nums[i]
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i += 1
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k += 1
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}
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while j <= right {
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tmp[k] = nums[j]
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j += 1
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k += 1
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}
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// 将临时数组 tmp 中的元素复制回原数组 nums 的对应区间
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for k in tmp.indices {
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nums[left + k] = tmp[k]
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}
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}
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/* 归并排序 */
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