Commit 02194d4b authored by Claudio Gheller's avatar Claudio Gheller
Browse files

Tabulated gaussian kernel with increased precision added (only CPU version)

parent 7205d63d

Makefile

+2 −0
Original line number Original line Diff line number Diff line
@@ -40,6 +40,8 @@ OPT += -DWRITE_IMAGE 
#OPT += -DPARALLELIO

#OPT += -DPARALLELIO

# Normalize uvw in case it is not done in the binMS

# Normalize uvw in case it is not done in the binMS

OPT += -DNORMALIZE_UVW

OPT += -DNORMALIZE_UVW

# Gridding kernel: GAUSS, GAUSS_HI_PRECISION

OPT += -DGAUSS_HI_PRECISION





ifeq (FITSIO,$(findstring FITSIO,$(OPT)))

ifeq (FITSIO,$(findstring FITSIO,$(OPT)))

	LIBS += -L$(FITSIO_LIB) -lcfitsio

	LIBS += -L$(FITSIO_LIB) -lcfitsio

w-stacking.cu

+12 −7
Original line number Original line Diff line number Diff line
@@ -24,11 +24,12 @@ gauss_kernel_norm(double norm, double std22, double u_dist, double v_dist) 




void makeGaussKernel(double * kernel,

void makeGaussKernel(double * kernel,

		     int KernelLen,

		     int KernelLen,

		     int increaseprecision,

		     double std22)

		     double std22)

{

{





  double norm = std22/PI;

  double norm = std22/PI;

  int n = KernelLen, mid = n / 2;

  int n = increaseprecision*KernelLen, mid = n / 2;

  for (int i = 0; i != mid + 1; i++) {

  for (int i = 0; i != mid + 1; i++) {

      double term = (double)i / mid;

      double term = (double)i / mid;

      kernel[mid + i] = sqrt(norm) * exp(-(term*term)*std22);

      kernel[mid + i] = sqrt(norm) * exp(-(term*term)*std22);
@@ -201,11 +202,12 @@ void wstack( 
    // initialize the convolution kernel

    // initialize the convolution kernel

    // gaussian:

    // gaussian:

    int KernelLen = (w_support-1)/2;

    int KernelLen = (w_support-1)/2;

    int increaseprecision = 21; // this number must be odd: increaseprecison*w_support must be odd (w_support must be odd)

    double std = 1.0;

    double std = 1.0;

    double std22 = 1.0/(2.0*std*std);

    double std22 = 1.0/(2.0*std*std);

    double norm = std22/PI;

    double norm = std22/PI;

    double * convkernel = malloc(w_support*sizeof(*convkernel));

    double * convkernel = malloc(increaseprecision*w_support*sizeof(*convkernel));

    makeGaussKernel(convkernel,w_support,std22);

    makeGaussKernel(convkernel,w_support,increaseprecision,std22);

    

    

    // Loop over visibilities.

    // Loop over visibilities.

// Switch between CUDA and GPU versions

// Switch between CUDA and GPU versions
@@ -327,14 +329,17 @@ void wstack( 




            for (j = jmin; j <= jmax; j++)

            for (j = jmin; j <= jmax; j++)

            {

            {

		int jKer = (int)j-pos_u+KernelLen;

		int kKer = (int)k-pos_v+KernelLen;

                double u_dist = (double)j+0.5 - pos_u;

                double u_dist = (double)j+0.5 - pos_u;

		long iKer = 2 * (j + k*grid_size_x + grid_w*grid_size_x*grid_size_y);

		long iKer = 2 * (j + k*grid_size_x + grid_w*grid_size_x*grid_size_y);

                int jKer = (int)(increaseprecision*u_dist) + KernelLen;

                int kKer = (int)(increaseprecision*v_dist) + KernelLen;







                #ifdef GAUSS_HI_PRECISION 

		//double conv_weight = gauss_kernel_norm(norm,std22,u_dist,v_dist);

		double conv_weight = gauss_kernel_norm(norm,std22,u_dist,v_dist);

                #endif

                #ifdef GAUSS

		double conv_weight = convkernel[jKer]*convkernel[kKer];

		double conv_weight = convkernel[jKer]*convkernel[kKer];

                #endif

		// Loops over frequencies and polarizations

		// Loops over frequencies and polarizations

		double add_term_real = 0.0;

		double add_term_real = 0.0;

		double add_term_img = 0.0;

		double add_term_img = 0.0;