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add zig codes for Section 'Hash Map', 'Binary Tree', 'Linear Search'
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2 changed files with 0 additions and 99 deletions
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@ -188,20 +188,6 @@ pub fn build(b: *std.build.Builder) void {
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const run_step_binary_tree= b.step("run_binary_tree", "Run binary_tree");
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run_step_binary_tree.dependOn(&run_cmd_binary_tree.step);
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// Section: "Heap"
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// Source File: "chapter_heap/heap.zig"
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// Run Command: zig build run_heap
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const exe_heap = b.addExecutable("heap", "chapter_heap/heap.zig");
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exe_heap.addPackagePath("include", "include/include.zig");
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exe_heap.setTarget(target);
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exe_heap.setBuildMode(mode);
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exe_heap.install();
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const run_cmd_heap = exe_heap.run();
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run_cmd_heap.step.dependOn(b.getInstallStep());
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if (b.args) |args| run_cmd_heap.addArgs(args);
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const run_step_heap = b.step("run_heap", "Run heap");
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run_step_heap.dependOn(&run_cmd_heap.step);
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// Section: "Linear Search"
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// Source File: "chapter_searching/linear_search.zig"
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// Run Command: zig build run_linear_search
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@ -1,85 +0,0 @@
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// File: heap.zig
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// Created Time: 2023-01-14
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// Author: sjinzh (sjinzh@gmail.com)
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const std = @import("std");
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const inc = @import("include");
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fn lessThan(context: void, a: i32, b: i32) std.math.Order {
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_ = context;
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return std.math.order(a, b);
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}
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fn greaterThan(context: void, a: i32, b: i32) std.math.Order {
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return lessThan(context, a, b).invert();
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}
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fn testPush(comptime T: type, mem_allocator: std.mem.Allocator, heap_push: anytype, val: T) !void {
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var heap = heap_push;
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try heap.add(val); //元素入堆
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std.debug.print("\n元素 {} 入堆后\n", .{val});
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try inc.PrintUtil.printHeap(T, mem_allocator, heap);
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}
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fn testPop(comptime T: type, mem_allocator: std.mem.Allocator, heap_pop: anytype) !void {
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var val = heap_pop.remove(); //堆顶元素出堆
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std.debug.print("\n堆顶元素 {} 出堆后\n", .{val});
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try inc.PrintUtil.printHeap(T, mem_allocator, heap_pop);
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}
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// Driver Code
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pub fn main() !void {
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// 初始化内存分配器
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var mem_arena = std.heap.ArenaAllocator.init(std.heap.page_allocator);
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// 延迟释放内存
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defer mem_arena.deinit();
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const mem_allocator = mem_arena.allocator();
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// 初始化堆
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// 初始化小顶堆
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const PQlt = std.PriorityQueue(i32, void, lessThan);
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var minHeap = PQlt.init(std.heap.page_allocator, {});
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defer minHeap.deinit();
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// 初始化大顶堆
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const PQgt = std.PriorityQueue(i32, void, greaterThan);
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var maxHeap = PQgt.init(std.heap.page_allocator, {});
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defer maxHeap.deinit();
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std.debug.print("\n以下测试样例为大顶堆", .{});
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// 元素入堆
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try testPush(i32, mem_allocator, &maxHeap, 1);
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try testPush(i32, mem_allocator, &maxHeap, 3);
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try testPush(i32, mem_allocator, &maxHeap, 2);
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try testPush(i32, mem_allocator, &maxHeap, 5);
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try testPush(i32, mem_allocator, &maxHeap, 4);
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// 获取堆顶元素
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var peek = maxHeap.peek().?;
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std.debug.print("\n堆顶元素为 {}\n", .{peek});
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// 堆顶元素出堆
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try testPop(i32, mem_allocator, &maxHeap);
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try testPop(i32, mem_allocator, &maxHeap);
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try testPop(i32, mem_allocator, &maxHeap);
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try testPop(i32, mem_allocator, &maxHeap);
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try testPop(i32, mem_allocator, &maxHeap);
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// 获取堆的大小
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var size = maxHeap.len;
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std.debug.print("\n堆元素数量为 {}", .{size});
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// 判断堆是否为空
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var isEmpty = if (maxHeap.len == 0) true else false;
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std.debug.print("\n堆是否为空 {}\n", .{isEmpty});
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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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try minHeap.addSlice(&[_]i32{ 1, 3, 2, 5, 4 });
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std.debug.print("\n输入列表并建立小顶堆后\n", .{});
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try inc.PrintUtil.printHeap(i32, mem_allocator, minHeap);
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const getchar = try std.io.getStdIn().reader().readByte();
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_ = getchar;
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}
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