Commit 1db60710 authored by Claudio Gheller's avatar Claudio Gheller
Browse files

Kaiser-Bessel and tabulated Gaussian available on CPU. Bug fixed in uvw normalization

parent 02194d4b

Makefile

+1 −1
Original line number Original line Diff line number Diff line
@@ -40,7 +40,7 @@ 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

# Gridding kernel: GAUSS, GAUSS_HI_PRECISION, KAISERBESSEL

OPT += -DGAUSS_HI_PRECISION

OPT += -DGAUSS_HI_PRECISION





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

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

w-stacking-fftw.c

+4 −4
Original line number Original line Diff line number Diff line
@@ -354,12 +354,12 @@ if(rank == 0){ 
	maxv_all = maxv;

	maxv_all = maxv;

	maxw_all = maxw;

	maxw_all = maxw;

        #endif

        #endif

	double offset = 0.0;

	double offset = 0.001;

	double ming = MIN(minu_all,minv_all);

	double ming = MAX(abs(minu_all),abs(minv_all));

	double maxg = MAX(maxu_all,maxv_all);

	double maxg = MAX(abs(maxu_all),abs(maxv_all));

	maxg = MAX(maxg,ming);

	minw = minw_all;

	minw = minw_all;

	maxw = maxw_all;

	maxw = maxw_all;

        ming = ming-offset*ming;

        maxg = maxg+offset*maxg;

        maxg = maxg+offset*maxg;

        for (long inorm=0; inorm<Nmeasures; inorm++)

        for (long inorm=0; inorm<Nmeasures; inorm++)

	    {

	    {

w-stacking.cu

+29 −9
Original line number Original line Diff line number Diff line
@@ -31,11 +31,12 @@ void makeGaussKernel(double * kernel, 
  double norm = std22/PI;

  double norm = std22/PI;

  int n = increaseprecision*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/(double)increaseprecision;

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

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

  }

  }





  for (int i = 0; i != mid; i++) kernel[i] = kernel[n - 1 - i];

  for (int i = 0; i != mid; i++) kernel[i] = kernel[n - 1 - i];

//  for (int i = 0; i < n; i++) printf("%f\n",kernel[i]);





}

}
@@ -53,10 +54,11 @@ double bessel0(double x, double precision) { 
}

}

void makeKaiserBesselKernel(double * kernel,

void makeKaiserBesselKernel(double * kernel,

		            int KernelLen,

		            int KernelLen,

			    int increaseprecision,

                            double alpha,

                            double alpha,

                            double overSamplingFactor,

                            double overSamplingFactor,

                            int withSinc) {

                            int withSinc) {

  int n = KernelLen, mid = n / 2;

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

  double * sincKernel = malloc((mid + 1)*sizeof(*sincKernel));

  double * sincKernel = malloc((mid + 1)*sizeof(*sincKernel));

  const double filterRatio = 1.0 / overSamplingFactor;

  const double filterRatio = 1.0 / overSamplingFactor;

  sincKernel[0] = filterRatio;

  sincKernel[0] = filterRatio;
@@ -73,6 +75,7 @@ void makeKaiserBesselKernel(double * kernel, 
                normFactor;

                normFactor;

  }

  }

  for (int i = 0; i != mid; i++) kernel[i] = kernel[n - 1 - i];

  for (int i = 0; i != mid; i++) kernel[i] = kernel[n - 1 - i];

  //for (int i = 0; i < n; i++) printf("%f\n",kernel[i]);

}

}
@@ -202,12 +205,21 @@ 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)

    int increaseprecision = 5; // 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(increaseprecision*w_support*sizeof(*convkernel));

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

    double overSamplingFactor = 1.0;

    int withSinc = 0;

    double alpha = 8.6;

    #ifdef GAUSS

    makeGaussKernel(convkernel,w_support,increaseprecision,std22);

    makeGaussKernel(convkernel,w_support,increaseprecision,std22);

    #endif

    #ifdef KAISERBESSEL

    makeKaiserBesselKernel(convkernel, w_support, increaseprecision, alpha, overSamplingFactor, withSinc);

    #endif



    

    

    // Loop over visibilities.

    // Loop over visibilities.

// Switch between CUDA and GPU versions

// Switch between CUDA and GPU versions
@@ -325,20 +337,28 @@ void wstack( 
        for (k = kmin; k <= kmax; k++)

        for (k = kmin; k <= kmax; k++)

        {

        {





            double v_dist = (double)k+0.5 - pos_v;

            //double v_dist = (double)k+0.5 - pos_v;

            double v_dist = (double)k - pos_v;





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

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

            {

            {

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

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

                double u_dist = (double)j - 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 jKer = (int)(increaseprecision * (fabs(u_dist+(double)KernelLen)));

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

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





                #ifdef GAUSS_HI_PRECISION 

                #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

                #endif

                #ifdef GAUSS

                #ifdef GAUSS

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

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

		//if(jKer < 0 || jKer >= 35 || kKer < 0 || kKer >= 35)

		//	printf("%f %d %f %d\n",fabs(u_dist+(double)KernelLen),jKer,fabs(v_dist+(double)KernelLen),kKer);

		//printf("%d %d %d %d %f %f %f %f %f\n",jKer, j, kKer, k, pos_u, pos_v, u_dist,v_dist,conv_weight);

                #endif

                #ifdef KAISERBESSEL

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

	        #endif	

	        #endif	

		// Loops over frequencies and polarizations

		// Loops over frequencies and polarizations

		double add_term_real = 0.0;

		double add_term_real = 0.0;