TYPE * genRandomImage(int xsize, int ysize, int zsize){
int i,j,k;
int row,col,slide;
TYPE *image;
image=(TYPE *)malloc(sizeof(TYPE)*xsize*ysize*zsize);
srand(time(NULL));
//srand(1);
for(k=0;k<zsize;k++){
for(i=0;i<xsize;i++){
for(j=0;j<ysize;j++){
image[k*(xsize*ysize) + i*ysize + j]= generateGaussianNoise(); // N(0,1) random
//image[k*(xsize*ysize) + i*ysize + j]= (TYPE)( 2.0*((TYPE)rand())/((TYPE)RAND_MAX) - 1.0 ); // uniform [0,1] random
//image[k*(xsize*ysize) + i*ysize + j]= (TYPE)(((TYPE)rand())/((TYPE)RAND_MAX)); // uniform [0,1] random
//image[k*(xsize*ysize) + i*ysize + j]= (TYPE)(rand()%2); // {0,1} random
//image[k*(xsize*ysize) + i*ysize + j]= (TYPE)((i*j+k)%2); // non random
//printf("image[%d]=%f\n",k*(xsize*ysize) + i*ysize + j,image[k*(xsize*ysize) + i*ysize + j]);
}
}
}
return image;
}
void FillMatrix(double *A,int n)
{
double temp;
srand(time(NULL));
for (int i=0; i<n; i++)
{
for (int j=i; j<n; j++)
{
temp=generateGaussianNoise(0.2);
A[i*n+j]=temp;
A[j*n+i]=temp;
}
}
}
int generateGaussianInt(const int &variance, const int &avg){
return (int)(variance*generateGaussianNoise())+avg;
}
double generatePositiveGaussianNoise(const double &variance, const double &avg){
return (variance*abs(generateGaussianNoise()))+avg;
}
double generateGaussianNoise(const double &variance, const double &avg)
{
return (variance*generateGaussianNoise())+avg;
}
