Submission #425315

#TimeUsernameProblemLanguageResultExecution timeMemory
425315frodakcinArt Class (IOI13_artclass)C++17
34 / 100
3874 ms8156 KiB
#include "artclass.h" #include <random> #include <chrono> #include <vector> #include <algorithm> std::mt19937 rng(std::chrono::high_resolution_clock::now().time_since_epoch().count()); int style(int H, int W, int R[500][500], int G[500][500], int B[500][500]) { auto dist=[&](int a, int b, int x, int y)->double { double d2=0; d2 += (R[a][b]-R[x][y])*(R[a][b]-R[x][y]); d2 += (G[a][b]-G[x][y])*(G[a][b]-G[x][y]); d2 += (B[a][b]-B[x][y])*(B[a][b]-B[x][y]); return sqrt(d2); }; auto logistic=[&](double x)->double { const double x0 = 0; const double rt = 0.2; return 1/(1+exp((x-x0)*rt)); }; // differentiate between 1/4 and 2/3 double wtdif = 0; for(int i=0;i+1<H;++i) for(int j=0;j<W;++j) wtdif += logistic(dist(i, j, i+1, j)); wtdif /= (H-1)*W; // return (int)(wtdif*10000); // CUT: 1800 if(wtdif < 0.18) { // styles 2 or 3 /* double green_factor = 0; for(int i=0;i<H;++i) for(int j=0;j<W;++j) green_factor += (double)G[i][j]/(R[i][j]+G[i][j]+B[i][j]+1); green_factor /= H*W; */ std::vector<double> vars; int L = ((H+W)/2)/20; for(int i=L;i+L<=H;++i) for(int j=L;j+L<=W;++j) { auto var_col = [&](int col[500][500])->double { double mean = 0; for(int u=i-L;u<i+L;++u) for(int v=j-L;v<j+L;++v) mean += col[u][v]; mean /= L*L*4; double var = 0; for(int u=i-L;u<i+L;++u) for(int v=j-L;v<j+L;++v) var += (col[u][v]-mean)*(col[u][v]-mean); var /= L*L*4; return var; }; double var_cur=0; var_cur += var_col(R); var_cur += var_col(G); var_cur += var_col(B); vars.push_back(var_cur); } std::sort(vars.begin(), vars.end()); //return (int)(vars[vars.size()/4]); //return (int)(green_factor*1000); if(vars[vars.size()/4] < 3200) return 2; else return 3; } else { // styles 1 or 4 double variance = 0; auto var_col = [&](int col[500][500])->double { double mean = 0; for(int u=0;u<H;++u) for(int v=0;v<W;++v) mean += col[u][v]; mean /= H*W; double var = 0; for(int u=0;u<H;++u) for(int v=0;v<W;++v) var += (col[u][v]-mean)*(col[u][v]-mean); var /= H*W; return var; }; variance += var_col(R); variance += var_col(G); variance += var_col(B); if(variance < 10000) return 1; else return 4; } return -1; }
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