- B1: 前缀和与差分
- B2: 快速组合
- B3: 二分查找
- B4: 高精度加法
- B4: 高精度除法
- B4: 高精度乘法
- B4: 高精度减法
- D1: 单调栈
- D2: 单调队列
- D3: Spare Table
- D4: 字典树
- D5: 并查集
- D6: 树状数组-限定区间计数
- D6: 树状数组-单点更新区间求和
- D7: 线段树-基础
- G1: 二分图-判定
- G2: 二分图-最大匹配
- G3: Astar k短路 on matrix
- G4: 拓扑排序
- G5: 连通无环无向图的重心
- G6: MST-Kruskal
- G7: MST-Prim
- G8: ShortestPath-BellmanFord
- G9: ShortestPath-Dijkstra
- G9: ShortestPath-Dijkstra Heap OPT
- G10: ShortestPath-SPFA
- G11: ShortestPath-Floyd
- M1: 快速幂与龟速乘
- M2: 欧几里得-最大公约数
- M2: EX欧几里得-翡蜀定理
- M2: EX欧几里得-线性同余方程
- M2: EX欧几里得-乘法逆元
- M3: 费马小定理-乘法逆元
- M4: 分解质因数
- M4: 分解质因数-欧拉函数
- M4: 分解质因数-多数乘积约数计数
- M4: 分解质因数-多数乘积约数求和
- M5: 欧拉筛
- M5: 欧拉筛-质数筛
- M6: 埃氏筛-质数筛
- M7: Stein算法-最大公约数
- M8: 矩阵乘法与快速幂
- O1: 快速排序
- O2: 并归排序
- S1: KMP
- S2: 字符串哈希
This doc has been marked needs-review. Following information are in upcoming update plan.
int ar[maxn];
template< class type, class Comp >
void merge_sort(type *v, int l, int r, Comp cmp) {
static int i, j, pos;
static type bak[maxn];
if (l >= r - 1) return ;
const int mid = (l + r) >> 1u;
msort(v, l, mid, cmp);
msort(v, mid, r, cmp);
i = l, j = mid, pos = l;
while (i < mid && j < r) {
if (cmp(v[i], v[j])) bak[pos++] = v[i++];
else bak[pos++] = v[j++];
}
while (i < mid) bak[pos++] = v[i++];
while (j < r) bak[pos++] = v[j++];
while (--pos >= l) v[pos] = bak[pos];
}
Usage
如果不是自定义比较函数, 一般cmp只能是less_equal<>()和greater_equal<>().
并归排序的运用
计算逆序对的数量
typedef unsigned long long ullong;
int ar[maxn];
template< class type, class Comp >
ullong cpa(type *v, int l, int r, Comp cmp) {
static int i, j, pos;
static type bak[maxn];
if (l >= r - 1) return 0;
const int mid = (l + r) >> 1u;
ullong ret = 0;
ret += cpa(v, l, mid, cmp);
ret += cpa(v, mid, r, cmp);
i = l, j = mid, pos = l;
while (i < mid && j < r) {
if (cmp(v[i], v[j])) bak[pos++] = v[i++];
else bak[pos++] = v[j++], ret += mid - i;
}
while (i < mid) bak[pos++] = v[i++];
while (j < r) bak[pos++] = v[j++];
while (--pos >= l) v[pos] = bak[pos];
return ret;
}
计算正序对的数量同理.