xmengnet/hello-algo
1
0
Fork 0
mirror of https://github.com/krahets/hello-algo.git synced 2024-12-25 13:26:30 +08:00
Code Issues Projects Releases Packages Wiki Activity Actions

add zig codes for Section 'Hash Map', 'Binary Tree', 'Linear Search'

Browse source
This commit is contained in:
sjinzh 2023-01-14 18:03:32 +08:00
parent de2c9c352d
commit 3782296de3
2 changed files with 0 additions and 99 deletions
Show stats Download patch file Download diff file Expand all files Collapse all files

14
codes/zig/build.zig
View file

@ -188,20 +188,6 @@ pub fn build(b: *std.build.Builder) void {
const run_step_binary_tree= b.step("run_binary_tree", "Run binary_tree"); const run_step_binary_tree= b.step("run_binary_tree", "Run binary_tree");
run_step_binary_tree.dependOn(&run_cmd_binary_tree.step); run_step_binary_tree.dependOn(&run_cmd_binary_tree.step);
// Section: "Heap"
// Source File: "chapter_heap/heap.zig"
// Run Command: zig build run_heap
const exe_heap = b.addExecutable("heap", "chapter_heap/heap.zig");
exe_heap.addPackagePath("include", "include/include.zig");
exe_heap.setTarget(target);
exe_heap.setBuildMode(mode);
exe_heap.install();
const run_cmd_heap = exe_heap.run();
run_cmd_heap.step.dependOn(b.getInstallStep());
if (b.args) |args| run_cmd_heap.addArgs(args);
const run_step_heap = b.step("run_heap", "Run heap");
run_step_heap.dependOn(&run_cmd_heap.step);
// Section: "Linear Search" // Section: "Linear Search"
// Source File: "chapter_searching/linear_search.zig" // Source File: "chapter_searching/linear_search.zig"
// Run Command: zig build run_linear_search // Run Command: zig build run_linear_search

85
codes/zig/chapter_heap/heap.zig
View file

@ -1,85 +0,0 @@
// File: heap.zig
// Created Time: 2023-01-14
// Author: sjinzh (sjinzh@gmail.com)
const std = @import("std");
const inc = @import("include");
fn lessThan(context: void, a: i32, b: i32) std.math.Order {
_ = context;
return std.math.order(a, b);
}
fn greaterThan(context: void, a: i32, b: i32) std.math.Order {
return lessThan(context, a, b).invert();
}
fn testPush(comptime T: type, mem_allocator: std.mem.Allocator, heap_push: anytype, val: T) !void {
var heap = heap_push;
try heap.add(val); //元素入堆
std.debug.print("\n元素 {} 入堆后\n", .{val});
try inc.PrintUtil.printHeap(T, mem_allocator, heap);
}
fn testPop(comptime T: type, mem_allocator: std.mem.Allocator, heap_pop: anytype) !void {
var val = heap_pop.remove(); //堆顶元素出堆
std.debug.print("\n堆顶元素 {} 出堆后\n", .{val});
try inc.PrintUtil.printHeap(T, mem_allocator, heap_pop);
}
// Driver Code
pub fn main() !void {
// 初始化内存分配器
var mem_arena = std.heap.ArenaAllocator.init(std.heap.page_allocator);
// 延迟释放内存
defer mem_arena.deinit();
const mem_allocator = mem_arena.allocator();
// 初始化堆
// 初始化小顶堆
const PQlt = std.PriorityQueue(i32, void, lessThan);
var minHeap = PQlt.init(std.heap.page_allocator, {});
defer minHeap.deinit();
// 初始化大顶堆
const PQgt = std.PriorityQueue(i32, void, greaterThan);
var maxHeap = PQgt.init(std.heap.page_allocator, {});
defer maxHeap.deinit();
std.debug.print("\n以下测试样例为大顶堆", .{});
// 元素入堆
try testPush(i32, mem_allocator, &maxHeap, 1);
try testPush(i32, mem_allocator, &maxHeap, 3);
try testPush(i32, mem_allocator, &maxHeap, 2);
try testPush(i32, mem_allocator, &maxHeap, 5);
try testPush(i32, mem_allocator, &maxHeap, 4);
// 获取堆顶元素
var peek = maxHeap.peek().?;
std.debug.print("\n堆顶元素为 {}\n", .{peek});
// 堆顶元素出堆
try testPop(i32, mem_allocator, &maxHeap);
try testPop(i32, mem_allocator, &maxHeap);
try testPop(i32, mem_allocator, &maxHeap);
try testPop(i32, mem_allocator, &maxHeap);
try testPop(i32, mem_allocator, &maxHeap);
// 获取堆的大小
var size = maxHeap.len;
std.debug.print("\n堆元素数量为 {}", .{size});
// 判断堆是否为空
var isEmpty = if (maxHeap.len == 0) true else false;
std.debug.print("\n堆是否为空 {}\n", .{isEmpty});
// 输入列表并建堆
// 时间复杂度为 O(n) ，而非 O(nlogn)
try minHeap.addSlice(&[_]i32{ 1, 3, 2, 5, 4 });
std.debug.print("\n输入列表并建立小顶堆后\n", .{});
try inc.PrintUtil.printHeap(i32, mem_allocator, minHeap);
const getchar = try std.io.getStdIn().reader().readByte();
_ = getchar;
}