mirror of
https://github.com/cosmo-sims/MUSIC.git
synced 2024-09-19 17:03:46 +02:00
a few fixes.
This commit is contained in:
Oliver Hahn
parent
df94ef9fac
commit
35046923eb
5 changed files with 86 additions and 164 deletions
2
Makefile
2
Makefile
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@ -10,7 +10,7 @@ BOXLIB_HOME = ${HOME}/nyx_tot_sterben/BoxLib
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##############################################################################
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### compiler and path settings
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CC = g++
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OPT = -Wall -Wno-unknown-pragmas -O3 -g -mtune=native
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OPT = -Wall -Wno-unknown-pragmas -O0 -g -mtune=native
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CFLAGS =
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LFLAGS = -lgsl -lgslcblas
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CPATHS = -I. -I$(HOME)/local/include -I/opt/local/include -I/usr/local/include
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@ -216,11 +216,12 @@ namespace convolution{
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template void perform<double>( kernel* pk, void *pd, bool shift );
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template void perform<float>( kernel* pk, void *pd, bool shift );
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/*****************************************************************************************\
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*** SPECIFIC KERNEL IMPLEMENTATIONS *********************************************
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\*****************************************************************************************/
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/*****************************************************************************************/
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/*** SPECIFIC KERNEL IMPLEMENTATIONS *********************************************/
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/*****************************************************************************************/
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template< typename real_t >
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class kernel_k_new : public kernel
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class kernel_k : public kernel
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{
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protected:
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/**/
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@ -228,7 +229,7 @@ namespace convolution{
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TransferFunction_k *tfk_;
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public:
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kernel_k_new( config_file& cf, transfer_function* ptf, refinement_hierarchy& refh, tf_type type )
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kernel_k( config_file& cf, transfer_function* ptf, refinement_hierarchy& refh, tf_type type )
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: kernel( cf, ptf, refh, type )
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{
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boxlength_ = pcf_->getValue<double>("setup","boxlength");
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@ -283,7 +284,6 @@ namespace convolution{
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return this;
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}
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void *get_ptr() { return NULL; }
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bool is_ksampled() { return true; }
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@ -293,14 +293,11 @@ namespace convolution{
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for( size_t i=0; i<len; ++i )
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{
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double kk = kfac_ * in_k[i];
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/*if( kk > kmax_ )
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out_Tk[i] = 0.0;
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else*/
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out_Tk[i] = volfac_ * tfk_->compute( kk );
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}
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}
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~kernel_k_new() { delete tfk_; }
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~kernel_k() { delete tfk_; }
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void deallocate() { }
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@ -309,107 +306,6 @@ namespace convolution{
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template< typename real_t >
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class kernel_k : public kernel
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{
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protected:
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std::vector<real_t> kdata_;
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void compute_kernel( tf_type type );
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public:
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kernel_k( config_file& cf, transfer_function* ptf, refinement_hierarchy& refh, tf_type type )
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: kernel( cf, ptf, refh, type )
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{ }
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kernel* fetch_kernel( int ilevel, bool isolated=false );
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void *get_ptr()
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{ return reinterpret_cast<void*> (&kdata_[0]); }
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bool is_ksampled()
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{ return false; }
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void at_k( size_t, const double*, double * ) { }
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~kernel_k()
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{ deallocate(); }
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void deallocate()
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{ std::vector<real_t>().swap( kdata_ ); }
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};
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template< typename real_t >
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kernel* kernel_k<real_t>::fetch_kernel( int ilevel, bool isolated )
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{
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double
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boxlength = pcf_->getValue<double>("setup","boxlength"),
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nspec = pcf_->getValue<double>("cosmology","nspec"),
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pnorm = pcf_->getValue<double>("cosmology","pnorm"),
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fac = pow(boxlength,3)/pow(2.0*M_PI,3);
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TransferFunction_k *tfk = new TransferFunction_k(type_,ptf_,nspec,pnorm);
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int
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nx = prefh_->size(prefh_->levelmax(),0),
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ny = prefh_->size(prefh_->levelmax(),1),
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nz = prefh_->size(prefh_->levelmax(),2);
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cparam_.nx = nx;
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cparam_.ny = ny;
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cparam_.nz = nz;
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cparam_.lx = boxlength;
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cparam_.ly = boxlength;
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cparam_.lz = boxlength;
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cparam_.pcf = pcf_;
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kdata_.assign( (size_t)nx*(size_t)ny*(size_t)(nz+2), 0.0 );
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fftw_complex *kdata = reinterpret_cast<fftw_complex*> ( this->get_ptr() );
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unsigned nzp = (nz/2+1);
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fac =1.0;
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double kfac = 2.0*M_PI/boxlength, ksum = 0.0;
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size_t kcount = 0;
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#pragma omp parallel for reduction(+:ksum,kcount)
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for( int i=0; i<nx; ++i )
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for( int j=0; j<ny; ++j )
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for( int k=0; k<nz/2+1; ++k )
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{
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double kx,ky,kz;
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kx = (double)i;
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ky = (double)j;
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kz = (double)k;
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if( kx > nx/2 ) kx -= nx;
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if( ky > ny/2 ) ky -= ny;
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size_t q = ((size_t)i*ny+(size_t)j)*nzp+(size_t)k;
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RE(kdata[q]) = fac*tfk->compute(kfac*sqrt(kx*kx+ky*ky+kz*kz));
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IM(kdata[q]) = 0.0;
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if( k==0 || k==nz/2 )
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{
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ksum += RE(kdata[q]);
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kcount++;
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}else{
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ksum += 2.0*(RE(kdata[q]));
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kcount+=2;
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}
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}
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delete tfk;
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return this;
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}
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////////////////////////////////////////////////////////////////////////////
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template< typename real_t >
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@ -662,12 +558,14 @@ namespace convolution{
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LOGUSER("Computing fine kernel (level %d)...", levelmax);
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#ifdef OLD_KERNEL_SAMPLING
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int ref_fac = (deconv&&kspacepoisson)? 2 : 0;
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const int ql = -ref_fac/2+1, qr = ql+ref_fac;
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const double rf8 = pow(ref_fac,3);
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const double dx05 = 0.5*dx, dx025 = 0.25*dx;
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std::cerr << ">>>>>>>>>>>> " << ref_fac << " <<<<<<<<<<<<<<<<" << std::endl;
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#endif
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if( bperiodic )
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{
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@ -1282,11 +1180,9 @@ namespace
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{
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convolution::kernel_creator_concrete< convolution::kernel_real_cached<double> > creator_d("tf_kernel_real_double");
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convolution::kernel_creator_concrete< convolution::kernel_real_cached<float> > creator_f("tf_kernel_real_float");
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convolution::kernel_creator_concrete< convolution::kernel_k<double> > creator_kd("tf_kernel_k_double");
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convolution::kernel_creator_concrete< convolution::kernel_k<float> > creator_kf("tf_kernel_k_float");
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convolution::kernel_creator_concrete< convolution::kernel_k_new<double> > creator_knd("tf_kernel_k_new_double");
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convolution::kernel_creator_concrete< convolution::kernel_k_new<float> > creator_knf("tf_kernel_k_new_float");
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}
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38
densities.cc
38
densities.cc
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@ -18,6 +18,8 @@
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#define DEF_RAN_CUBE_SIZE 32
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//#define NO_COARSE_OVERLAP
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template< typename m1, typename m2 >
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void fft_interpolate( m1& V, m2& v, bool from_basegrid=false )
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{
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@ -27,9 +29,21 @@ void fft_interpolate( m1& V, m2& v, bool from_basegrid=false )
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if( !from_basegrid )
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{
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#ifdef NO_COARSE_OVERLAP
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oxf += nxF/4;
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oyf += nyF/4;
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ozf += nzF/4;
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#else
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oxf += nxF/4 - nxf/8;
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oyf += nyF/4 - nyf/8;
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ozf += nzF/4 - nzf/8;
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}else{
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oxf -= nxf/8;
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oyf -= nyf/8;
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ozf -= nzf/8;
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#endif
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}
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LOGUSER("FFT interpolate: offset=%d,%d,%d size=%d,%d,%d",oxf,oyf,ozf,nxf,nyf,nzf);
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@ -47,6 +61,8 @@ void fft_interpolate( m1& V, m2& v, bool from_basegrid=false )
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// copy coarse data to rcoarse[.]
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memset( rcoarse, 0, sizeof(fftw_real) * nxc*nyc*nzcp );
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#ifdef NO_COARSE_OVERLAP
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#pragma omp parallel for
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for( int i=0; i<(int)nxc/2; ++i )
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for( int j=0; j<(int)nyc/2; ++j )
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@ -58,6 +74,20 @@ void fft_interpolate( m1& V, m2& v, bool from_basegrid=false )
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size_t q = ((size_t)ii*nyc+(size_t)jj)*nzcp+(size_t)kk;
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rcoarse[q] = V( oxf+i, oyf+j, ozf+k );
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}
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#else
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#pragma omp parallel for
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for( int i=0; i<(int)nxc; ++i )
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for( int j=0; j<(int)nyc; ++j )
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for( int k=0; k<(int)nzc; ++k )
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{
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int ii(i);
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int jj(j);
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int kk(k);
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size_t q = ((size_t)ii*nyc+(size_t)jj)*nzcp+(size_t)kk;
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rcoarse[q] = V( oxf+i, oyf+j, ozf+k );
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}
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#endif
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#pragma omp parallel for
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for( int i=0; i<(int)nxf; ++i )
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@ -276,9 +306,9 @@ void GenerateDensityUnigrid( config_file& cf, transfer_function *ptf, tf_type ty
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LOGUSER("Using k-space transfer function kernel.");
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#ifdef SINGLE_PRECISION
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the_kernel_creator = convolution::get_kernel_map()[ "tf_kernel_k_new_float" ];
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the_kernel_creator = convolution::get_kernel_map()[ "tf_kernel_k_float" ];
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#else
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the_kernel_creator = convolution::get_kernel_map()[ "tf_kernel_k_new_double" ];
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the_kernel_creator = convolution::get_kernel_map()[ "tf_kernel_k_double" ];
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#endif
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}
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else
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@ -363,9 +393,9 @@ void GenerateDensityHierarchy( config_file& cf, transfer_function *ptf, tf_type
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LOGUSER("Using k-space transfer function kernel.");
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#ifdef SINGLE_PRECISION
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the_kernel_creator = convolution::get_kernel_map()[ "tf_kernel_k_new_float" ];
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the_kernel_creator = convolution::get_kernel_map()[ "tf_kernel_k_float" ];
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#else
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the_kernel_creator = convolution::get_kernel_map()[ "tf_kernel_k_new_double" ];
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the_kernel_creator = convolution::get_kernel_map()[ "tf_kernel_k_double" ];
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#endif
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}
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else
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11
mesh.hh
11
mesh.hh
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@ -775,17 +775,12 @@ public:
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*/
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bool is_refined( unsigned ilevel, int i, int j, int k ) const
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{
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if( ilevel == levelmax() )
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return false;
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if( bhave_refmask )
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return !(*m_ref_masks[ilevel-1])(offset(ilevel,0)+i/2,offset(ilevel,1)+j/2,offset(ilevel,2)+k/2);
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/*if( ilevel == levelmax() ){
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if( !bhave_refmask ) return false;
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else if( ref_mask(offset(levelmax(),0)+i/2,offset(levelmax(),1)+j/2,offset(levelmax(),2)+k/2) )
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return false;
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else
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return true;
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}*/
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if( ilevel == levelmax()-1 && bhave_refmask )
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return (*m_ref_masks[ilevel])(i,j,k);
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@ -800,8 +800,9 @@ struct HDFHyperslabWriter3Ds
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hid_t memspace = H5Screate_simple(4, counts, NULL);
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H5Sselect_hyperslab( filespace, H5S_SELECT_SET, offsets, NULL, counts, NULL );
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herr_t status;
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status = H5Dwrite(dset_id_, type_id_, memspace, filespace, H5P_DEFAULT, reinterpret_cast<void*>(data));
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//herr_t status;
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//status =
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H5Dwrite(dset_id_, type_id_, memspace, filespace, H5P_DEFAULT, reinterpret_cast<void*>(data));
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H5Sclose(filespace);
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H5Sclose(memspace);
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}
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