A summary of rank finding's questions is as follows:
In a group of discrete points, check if the x and Y values are less than its points for each point, and if so, the rank of the point is the number of points less than it.
The thought of divide and conquer law:
Recursively divides the target area into two parts, based on the median of x values in all points on the interface, until the points in each region are below one, and for each small area, check the Y value of the point in its left child area and the Y value of the point in the right child area to The rank of the points in the child is counted.
This method eliminates the point of non-conforming horizontal position and effectively reduces the number of statistics.
The code examples are as follows:
#include <algorithm>#include<iostream>#include<vector>#include<cstring>Const intMax_n = +;structpoint{intx; inty;};BOOLcmpx (Point A, point B) {returnA.x <b.x;}BOOLCmpy (Point A, point B) {returnA.y <b.y;}intRank[max_n][max_n]; Point S[max_n];//Point set, start point, end +1voidRankfinding (Point s[],int from,intTo ) { intn = to- from; if(N <=0) { return; } if(n = =1) {rank[s[ from].x][s[ from].Y] =0; return; } std::sort (S+ from, S + to, cmpx);//n*log (n) intL = (to + from) /2; Rankfinding (S), from, l);//2*t (N/2)rankfinding (S, L, to); Std::sort (S+ from, S + L, cmpy);//(N/2) *log (N/2)Std::sort (S + L, S +to, Cmpy); for(inti = l; I < to; ++i) { for(intj = from; J < L; ++j) {if(S[i].y >s[j].y) {RANK[S[I].X][S[I].Y]++; } } }}intMain () {memset (rank,-1,sizeof(rank)); memset (S),0,sizeof(S)); s[0] = {1,1 }; s[1] = {1,3 }; s[2] = {2,5 }; s[3] = {6,2 }; s[4] = {9,3 }; s[5] = {4,8 }; s[6] = {7,6 }; s[7] = {5,5 }; s[8] = {2,3 }; Rankfinding (S),0,9); for(inti =0; i < max_n; ++i) { for(intj =0; J < Max_n; ++j) {if(Rank[i][j]! =-1) {Std::cout<< I <<' '<< J <<' '<< Rank[i][j] <<Std::endl; } } }}
tags in code, complexity
T (n) =2*t (N/2) +n*log (n) +2* (N/2) * (log (N/2))
=2*t (N/2) +n* (2*log (n)-1) =2* (T (N/2) +n*log (n)-N)
T (2^k) =2* (t (2^ (K-1)) + (k-1) * (2^k))) =2^ (k-1) * (t (1)) + (2^k) * (k-1) ^2= (2^k) * (t (1)/2+ (k-1) ^2)
T (n) =n* (t (1)/2+ (log (n)) ^2)
So the complexity is O (n (^2))
The strategy of rank-finding (maxium rank finding) based on divide-and-conquer method