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  1. #include <iostream>
  2. #include <math.h>
  3. using namespace std;
  4. void correlate(int ny, int nx, const float* data, float* result) 
  5. {
  6. 	float* inter = new float[ny*nx];
  7. 	for (int y = 0; y < ny; ++y) 
  8. 	{
  9. 		double mean = 0.0;
  10. 		double sd = 0.0;
  11. 		double temp;
  12. 		//Finding the mean
  13. 		for (int x = 0; x < nx; ++x) 
  14. 		{
  15. 			mean += data[x + y*nx];
  16. 		}
  17. 		mean = mean/nx;
  18. 		//cout<<mean<<endl;
  19. 		//Finding the Standard Deviation
  20. 		for (int x = 0; x < nx; ++x) 
  21. 		{
  22. 			temp = data[x + y*nx] - mean;
  23. 			inter[x + y*nx] = temp;
  24. 			sd += (temp)*(temp);
  25. 		}
  26. 		sd= sqrt(sd/(nx-1));
  27. 		//cout<<nx<<" "<<sd<<endl;
  28. 		//Finding zero mean and unit variance
  29. 		for (int x = 0; x < nx; ++x) 
  30. 		{
  31. 			inter[x + y*nx] = inter[x + y*nx] / sd;
  32. 		}
  33.     }
  34. 	for (int i = 0; i < ny; i++) 
  35. 	{
  36.         for (int j = 0; j < ny; j++) 
  37. 		{
  38.             float sum = 0.0;
  39.            	for (int k = 0; k < nx; k++)
  40.                 sum = sum + inter[i * nx + k] * inter[j * nx + k];
  41.             result[i * ny + j] = sum;
  42.         }
  43.     }
  44.  
  45. }
  46.  
  47.  
  48. int main() {
  49.     float xarr[] = { 0, 2, 4, 6, 8 ,10};
  50.     int nx = 3;
  51.     int ny = 2;
  52.     float *result = new float[ny*ny];
  53.     correlate(2,3,xarr,result);
  54.     for(int i = 0;i<ny*ny;i++)
  55.     	cout<< result[i] <<" ";
  56. 	return 0;
  57. }
Success #stdin #stdout 0.01s 5300KB
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https://ideone.com/2u8owy
language:
C++ (gcc 8.3)
created:
10 days ago
visibility:
public

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