归并,插入和stl排序的速度比较

原创于 2022-03-25 09:50:20 发布 · 796 阅读

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#其他 #c++ #算法

本文通过实验对比了STL排序、归并排序及插入排序三种排序算法的性能，并针对不同数据规模进行了测试。实验结果显示，当数据量较小时，归并排序采用插入排序作为子程序能有效提高效率。

//#pragma region
#include <bits/stdc++.h>
#include <time.h>
using namespace std;  // clang-format off
#define redir(i, o) { if (i) freopen("a.in", "r", stdin);if (o)freopen("a.out", "w", stdout);}
#define repr(i,a,b) for(int i = a;i < b;++i)
#define DEBUG "L= "<< setw(2)<< __LINE__ << ":  "
#ifdef DEBUG
#define print(a) cout<<DEBUG<<#a << ": " <<(a)<<endl
#define prin2(a, b) cout <<DEBUG<<":  "<< #a<<": "<< (a)<<" "<<#b<< ": "<<(b)<<endl
#define prinl(a) do{cout<<DEBUG<<endl;int s=min((int)a.size(),16);for(int i=0;i<s;i++)cout<<setw(4)<<i<<" \n"[i==s-1];int num=0;for(auto i:a){cout<<setw(4)<<i<<"\n "[bool(++num%s)];}cout<<endl;}while(0)
#define prinSq(a) do{cout<<"X:    ";for(auto i=0;i<a.size();i++){cout<<setw(4)<<i<<" ";}cout<<endl;for(auto i=0;i<a.size();i++){cout<<"Y="<<setw(2)<<i<<": ";for(auto i : a[i])cout<<setw(4)<<i<<" ";cout<<endl;}}while(0)
#define pTime(a) do{cout<<"\n\n";auto t=clock();a;cout<<DEBUG<<"测试结束,消耗"<<clock()-t<<"微秒\n";}while(0)
#else
#define endl "\n"
#define print(a)
#define prin2(a, b)
#define printL(a)
#define prinSq(a)
#define pTime(a) a;
#endif  // clang-format on
template<typename T>vector<vector<T>>makeSq(int y, int x, T *init) {
	auto ans = vector<vector<T>>(y, vector<T>(x, *init)); delete init; return ans;
}


void quick_sort(int arr[], int le, int ri) {
	int index = partition(int arr[], left, right);
	quick_sort(arr, le, index - 1);
	quick_sort(arr, index + 1, right);
}

int partition(int arr[], int left, int right) {
	int i = left;
	int j = right + 1;
	int target = arr[left];

	while (1) {
		while (arr[++i] < target)
			if (i == right) break;

		while (arr[--j] > target)
			if (j == left) break;

		if (i >= j)
			break;

		swap(arr[i], arr[j]);
	}
	swap(arr[left], j);

	return j;
}

void Isort(vector<int> &x) {
	unsigned siz = x.size();
	for (unsigned i = 1; i < siz; i++) {
		int key = x[i];
		unsigned j = i - 1;
		while (j != (unsigned)0 - 1 && key < x[j]) {
			x[j + 1] = x[j];
			--j;
		}
		x[++j] = key;
	}
	return;
}

void Gsort(vector<int> &x) {
	if (x.size() < 90) {
		Isort(x);
		return;
	}
	// if (x.size() == 1) return;

	unsigned mid = x.size() / 2;

	vector<int> l(mid), r(x.size() - mid);
	for (unsigned i = 0; i < mid; i++) l[i] = x[i];
	Gsort(l);
	for (unsigned i = mid; i < x.size(); i++) r[i - mid] = x[i];
	Gsort(r);

	l.emplace_back(INT_MAX);
	r.emplace_back(INT_MAX);
	for (unsigned ll = 0, rr = 0, i = 0; i < x.size(); i++) {
		if (l[ll] < r[rr]) {
			x[i] = l[ll++];
		} else {
			x[i] = r[rr++];
		}
	}
	return;
}


void test(int N) {
	vector<int> now, t1;
	repr(i, 0, N) now.emplace_back(rand());

	t1 = now;
	pTime(sort(t1.begin(), t1.end())); print("stl排序");
	prinl(t1);

	t1 = now;
	pTime(Gsort(t1)); print("归并排序");
	prinl(t1);

	if (N >= (int)9 * 1e4)return;
	t1 = now;
	pTime(Isort(t1)); print("插入排序");

}



int main() {
	srand(time(0));
	print("1e2");
	test(1e2);
	print("1e4");
	test(1e4);
	print("1e5");
	test(1e5);
	print("1e6");
	test(1e6);
	return 0;
}

归并排序在元素数量小于100时直接进行插入排序, 可以加快排序速度, 达到接近stl排序的效果

执行结果:

Active code page: 65001
L= 119:  "\n\n1e2":

1e2


L= 102:  测试结束,消耗0微秒
L= 102:  "stl排序": stl排序


L= 106:  测试结束,消耗0微秒
L= 106:  "归并排序": 归并排序


L= 111:  测试结束,消耗0微秒
L= 111:  "插入排序": 插入排序
L= 121:  "\n\n1e4":

1e4


L= 102:  测试结束,消耗3微秒
L= 102:  "stl排序": stl排序


L= 106:  测试结束,消耗4微秒
L= 106:  "归并排序": 归并排序


L= 111:  测试结束,消耗175微秒
L= 111:  "插入排序": 插入排序
L= 123:  "\n\n1e5":

1e5


L= 102:  测试结束,消耗31微秒
L= 102:  "stl排序": stl排序


L= 106:  测试结束,消耗43微秒
L= 106:  "归并排序": 归并排序
L= 125:  "\n\n1e6":

1e6


L= 102:  测试结束,消耗314微秒
L= 102:  "stl排序": stl排序


L= 106:  测试结束,消耗463微秒
L= 106:  "归并排序": 归并排序

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