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MUSIC/random.cc
Oliver Hahn 2236b9f29b fixed some code causing compiler warnings
2012-11-20 16:02:32 +01:00

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/*
random.cc - This file is part of MUSIC -
a code to generate multi-scale initial conditions
for cosmological simulations
Copyright (C) 2010 Oliver Hahn
*/
#include "random.hh"
// TODO: move all this into a plugin!!!
template< typename T >
random_numbers<T>::random_numbers( unsigned res, unsigned cubesize, long baseseed, int *x0, int *lx )
: res_( res ), cubesize_( cubesize ), ncubes_( 1 ), baseseed_( baseseed )
{
LOGINFO("Generating random numbers (1) with seed %ld", baseseed);
initialize();
fill_subvolume( x0, lx );
}
template< typename T >
random_numbers<T>::random_numbers( unsigned res, unsigned cubesize, long baseseed, bool zeromean )
: res_( res ), cubesize_( cubesize ), ncubes_( 1 ), baseseed_( baseseed )
{
LOGINFO("Generating random numbers (2) with seed %ld", baseseed);
double mean = 0.0;
initialize();
mean = fill_all();
if( zeromean )
{
mean = 0.0;
#pragma omp parallel for reduction(+:mean)
for(int i=0; i<(int)res_; ++i )
for( unsigned j=0; j<res_; ++j )
for( unsigned k=0; k<res_; ++k )
mean += (*this)(i,j,k);
mean *= 1.0/(res_*res_*res_);
#pragma omp parallel for
for(int i=0; i<(int)res_; ++i )
for( unsigned j=0; j<res_; ++j )
for( unsigned k=0; k<res_; ++k )
(*this)(i,j,k) = (*this)(i,j,k) - mean;
}
}
template< typename T >
random_numbers<T>::random_numbers( unsigned res, std::string randfname, bool randsign )
: res_( res ), cubesize_( res ), ncubes_(1)
{
rnums_.push_back( new Meshvar<T>( res, 0, 0, 0 ) );
cubemap_[0] = 0; // create dummy map index
std::ifstream ifs(randfname.c_str(), std::ios::binary);
if( !ifs )
{
LOGERR("Could not open random number file \'%s\'!",randfname.c_str());
throw std::runtime_error(std::string("Could not open random number file \'")+randfname+std::string("\'!"));
}
unsigned vartype;
unsigned nx,ny,nz,blksz32;
size_t blksz64;
int iseed;
//long seed;
float sign4 = -1.0f;
double sign8 = -1.0;
int addrtype = 32;
if( randsign ) // use grafic2 sign convention
{
sign4 = 1.0f;
sign8 = 1.0;
}
//... read header and check if 32bit or 64bit block size .../
ifs.read( reinterpret_cast<char*> (&blksz32), sizeof(int) );
ifs.read( reinterpret_cast<char*> (&nx), sizeof(unsigned) );
if( blksz32 != 4*sizeof(int) || nx != res_ )
{
addrtype = 64;
ifs.seekg( 0 );
ifs.read( reinterpret_cast<char*> (&blksz64), sizeof(size_t) );
ifs.read( reinterpret_cast<char*> (&nx), sizeof(unsigned) );
if( blksz64 != 4*sizeof(int) || nx != res_ )
addrtype = -1;
}
ifs.seekg( 0 );
if( addrtype < 0 )
throw std::runtime_error("corrupt random number file");
if( addrtype == 32 )
ifs.read( reinterpret_cast<char*> (&blksz32), sizeof(int) );
else
ifs.read( reinterpret_cast<char*> (&blksz64), sizeof(size_t) );
ifs.read( reinterpret_cast<char*> (&nx), sizeof(unsigned) );
ifs.read( reinterpret_cast<char*> (&ny), sizeof(unsigned) );
ifs.read( reinterpret_cast<char*> (&nz), sizeof(unsigned) );
ifs.read( reinterpret_cast<char*> (&iseed), sizeof(int) );
//seed = (long)iseed;
if( nx!=res_ || ny!=res_ || nz!=res_ )
{
char errmsg[128];
sprintf(errmsg,"White noise file dimensions do not match level dimensions: %ux%ux%u vs. %u**3",nx,ny,nz,res_);
throw std::runtime_error(errmsg);
}
if( addrtype == 32 )
ifs.read( reinterpret_cast<char*> (&blksz32), sizeof(int) );
else
ifs.read( reinterpret_cast<char*> (&blksz64), sizeof(size_t) );
//... read data ...//
//check whether random numbers are single or double precision numbers
if( addrtype == 32 )
{
ifs.read( reinterpret_cast<char*> (&blksz32), sizeof(int) );
if( blksz32 == nx*ny*sizeof(float) )
vartype = 4;
else if( blksz32 == nx*ny*sizeof(double) )
vartype = 8;
else
throw std::runtime_error("corrupt random number file");
}else{
ifs.read( reinterpret_cast<char*> (&blksz64), sizeof(size_t) );
if( blksz64 == nx*ny*sizeof(float) )
vartype = 4;
else if( blksz64 == nx*ny*sizeof(double) )
vartype = 8;
else
throw std::runtime_error("corrupt random number file");
}
//rewind to beginning of block
if( addrtype == 32 )
ifs.seekg(-sizeof(int),std::ios::cur);
else
ifs.seekg(-sizeof(size_t),std::ios::cur);
std::vector<float> in_float;
std::vector<double> in_double;
LOGINFO("Random number file \'%s\'\n contains %ld numbers. Reading...",randfname.c_str(),nx*ny*nz);
double sum = 0.0, sum2 = 0.0;
unsigned count = 0;
//perform actual reading
if( vartype == 4 )
{
for( int ii=0; ii<(int)nz; ++ii )
{
if( addrtype == 32 )
{
ifs.read( reinterpret_cast<char*> (&blksz32), sizeof(int) );
if( blksz32 != nx*ny*sizeof(float) )
throw std::runtime_error("corrupt random number file");
}
else
{
ifs.read( reinterpret_cast<char*> (&blksz64), sizeof(size_t) );
if( blksz64 != nx*ny*sizeof(float) )
throw std::runtime_error("corrupt random number file");
}
in_float.assign(nx*ny,0.0f);
ifs.read( (char*)&in_float[0], nx*ny*sizeof(float) );
for( int jj=0,q=0; jj<(int)ny; ++jj )
for( int kk=0; kk<(int)nx; ++kk ){
sum += in_float[q];
sum2 += in_float[q]*in_float[q];
++count;
(*rnums_[0])(kk,jj,ii) = sign4 * in_float[q++];
}
if( addrtype == 32 )
{
ifs.read( reinterpret_cast<char*> (&blksz32), sizeof(int) );
if( blksz32 != nx*ny*sizeof(float) )
throw std::runtime_error("corrupt random number file");
}
else
{
ifs.read( reinterpret_cast<char*> (&blksz64), sizeof(size_t) );
if( blksz64 != nx*ny*sizeof(float) )
throw std::runtime_error("corrupt random number file");
}
}
}
else if( vartype == 8 )
{
for( int ii=0; ii<(int)nz; ++ii )
{
if( addrtype == 32 )
{
ifs.read( reinterpret_cast<char*> (&blksz32), sizeof(int) );
if( blksz32 != nx*ny*sizeof(double) )
throw std::runtime_error("corrupt random number file");
}
else
{
ifs.read( reinterpret_cast<char*> (&blksz64), sizeof(size_t) );
if( blksz64 != nx*ny*sizeof(double) )
throw std::runtime_error("corrupt random number file");
}
in_double.assign(nx*ny,0.0f);
ifs.read( (char*)&in_double[0], nx*ny*sizeof(double) );
for( int jj=0,q=0; jj<(int)ny; ++jj )
for( int kk=0; kk<(int)nx; ++kk )
{
sum += in_double[q];
sum2 += in_double[q]*in_double[q];
++count;
(*rnums_[0])(kk,jj,ii) = sign8 * in_double[q++];
}
if( addrtype == 32 )
{
ifs.read( reinterpret_cast<char*> (&blksz32), sizeof(int) );
if( blksz32 != nx*ny*sizeof(double) )
throw std::runtime_error("corrupt random number file");
}
else
{
ifs.read( reinterpret_cast<char*> (&blksz64), sizeof(size_t) );
if( blksz64 != nx*ny*sizeof(double) )
throw std::runtime_error("corrupt random number file");
}
}
}
double mean, var;
mean = sum/count;
var = sum2/count-mean*mean;
LOGINFO("Random numbers in file have \n mean = %f and var = %f", mean, var);
}
//... copy construct by averaging down
template< typename T >
random_numbers<T>::random_numbers( /*const*/ random_numbers <T>& rc, bool kdegrade )
{
//if( res > rc.m_res || (res/rc.m_res)%2 != 0 )
// throw std::runtime_error("Invalid restriction in random number container copy constructor.");
double sum = 0.0, sum2 = 0.0;
unsigned count = 0;
if( kdegrade )
{
LOGINFO("Generating a coarse white noise field by k-space degrading");
//... initialize properties of container
res_ = rc.res_/2;
cubesize_ = res_;
ncubes_ = 1;
baseseed_ = -2;
if( sizeof(fftw_real)!=sizeof(T) )
{
LOGERR("type mismatch with fftw_real in k-space averaging");
throw std::runtime_error("type mismatch with fftw_real in k-space averaging");
}
fftw_real
*rfine = new fftw_real[(size_t)rc.res_*(size_t)rc.res_*2*((size_t)rc.res_/2+1)],
*rcoarse = new fftw_real[(size_t)res_*(size_t)res_*2*((size_t)res_/2+1)];
fftw_complex
*ccoarse = reinterpret_cast<fftw_complex*> (rcoarse),
*cfine = reinterpret_cast<fftw_complex*> (rfine);
int nx(rc.res_), ny(rc.res_), nz(rc.res_), nxc(res_), nyc(res_), nzc(res_);
#ifdef FFTW3
#ifdef SINGLE_PRECISION
fftwf_plan
pf = fftwf_plan_dft_r2c_3d(nx, ny, nz, rfine, cfine, FFTW_ESTIMATE),
ipc= fftwf_plan_dft_c2r_3d(nxc, nyc, nzc, ccoarse, rcoarse, FFTW_ESTIMATE);
#else
fftw_plan
pf = fftw_plan_dft_r2c_3d(nx, ny, nz, rfine, cfine, FFTW_ESTIMATE),
ipc= fftw_plan_dft_c2r_3d(nxc, nyc, nzc, ccoarse, rcoarse, FFTW_ESTIMATE);
#endif
#else
rfftwnd_plan
pf = rfftw3d_create_plan( nx, ny, nz, FFTW_REAL_TO_COMPLEX, FFTW_ESTIMATE|FFTW_IN_PLACE),
ipc = rfftw3d_create_plan( nxc, nyc, nzc, FFTW_COMPLEX_TO_REAL, FFTW_ESTIMATE|FFTW_IN_PLACE);
#endif
#pragma omp parallel for
for( int i=0; i<nx; i++ )
for( int j=0; j<ny; j++ )
for( int k=0; k<nz; k++ )
{
size_t q = ((size_t)i*ny+(size_t)j)*(nz+2)+(size_t)k;
rfine[q] = rc(i,j,k);
}
#ifdef FFTW3
#ifdef SINGLE_PRECISION
fftwf_execute( pf );
#else
fftw_execute( pf );
#endif
#else
#ifndef SINGLETHREAD_FFTW
rfftwnd_threads_one_real_to_complex( omp_get_max_threads(), pf, rfine, NULL );
#else
rfftwnd_one_real_to_complex( pf, rfine, NULL );
#endif
#endif
double fftnorm = 1.0/((double)nxc*(double)nyc*(double)nzc);
#pragma omp parallel for
for( int i=0; i<nxc; i++ )
for( int j=0; j<nyc; j++ )
for( int k=0; k<nzc/2+1; k++ )
{
int ii(i),jj(j),kk(k);
if( i > nxc/2 ) ii += nx/2;
if( j > nyc/2 ) jj += ny/2;
size_t qc,qf;
qc = ((size_t)i*nyc+(size_t)j)*(nzc/2+1)+(size_t)k;
qf = ((size_t)ii*ny+(size_t)jj)*(nz/2+1)+(size_t)kk;
RE(ccoarse[qc]) = 1.0/sqrt(8.0)*RE(cfine[qf])*fftnorm;
IM(ccoarse[qc]) = 1.0/sqrt(8.0)*IM(cfine[qf])*fftnorm;
}
delete[] rfine;
#ifdef FFTW3
#ifdef SINGLE_PRECISION
fftwf_execute( ipc );
#else
fftw_execute( ipc );
#endif
#else
#ifndef SINGLETHREAD_FFTW
rfftwnd_threads_one_complex_to_real( omp_get_max_threads(), ipc, ccoarse, NULL );
#else
rfftwnd_one_complex_to_real( ipc, ccoarse, NULL );
#endif
#endif
rnums_.push_back( new Meshvar<T>( res_, 0, 0, 0 ) );
cubemap_[0] = 0; // map all to single array
#pragma omp parallel for reduction(+:sum,sum2,count)
for( int i=0; i<nxc; i++ )
for( int j=0; j<nyc; j++ )
for( int k=0; k<nzc; k++ )
{
size_t q = ((size_t)i*nyc+(size_t)j)*(nzc+2)+(size_t)k;
(*rnums_[0])(i,j,k) = rcoarse[q];
sum += (*rnums_[0])(i,j,k);
sum2+= (*rnums_[0])(i,j,k) * (*rnums_[0])(i,j,k);
++count;
}
delete[] rcoarse;
#ifdef FFTW3
#ifdef SINGLE_PRECISION
fftwf_destroy_plan(pf);
fftwf_destroy_plan(ipc);
#else
fftw_destroy_plan(pf);
fftw_destroy_plan(ipc);
#endif
#else
rfftwnd_destroy_plan(pf);
rfftwnd_destroy_plan(ipc);
#endif
}
else
{
LOGINFO("Generating a coarse white noise field by averaging");
if( rc.rnums_.size() == 1 )
{
//... initialize properties of container
res_ = rc.res_/2;
cubesize_ = res_;
ncubes_ = 1;
baseseed_ = -2;
//... use restriction to get consistent random numbers on coarser grid
mg_straight gop;
rnums_.push_back( new Meshvar<T>( res_, 0, 0, 0 ) );
cubemap_[0] = 0; // map all to single array
gop.restrict( *rc.rnums_[0], *rnums_[0] );
#pragma omp parallel for reduction(+:sum,sum2,count)
for( int i=0; i< (int)rnums_[0]->size(0); ++i )
for( unsigned j=0; j< rnums_[0]->size(1); ++j )
for( unsigned k=0; k< rnums_[0]->size(2); ++k )
{
(*rnums_[0])(i,j,k) *= sqrt(8); //.. maintain that var(delta)=1
sum += (*rnums_[0])(i,j,k);
sum2+= (*rnums_[0])(i,j,k) * (*rnums_[0])(i,j,k);
++count;
}
}
else
{
//... initialize properties of container
res_ = rc.res_/2;
cubesize_ = res_;
ncubes_ = 1;
baseseed_ = -2;
rnums_.push_back( new Meshvar<T>( res_, 0, 0, 0 ) );
cubemap_[0] = 0;
double fac = 1.0/sqrt(8);
#pragma omp parallel for reduction(+:sum,sum2,count)
for( int ii=0; ii<(int)rc.res_/2; ++ii )
{
unsigned i=2*ii;
for( unsigned j=0,jj=0; j<rc.res_; j+=2,++jj )
for( unsigned k=0,kk=0; k<rc.res_; k+=2,++kk )
{
(*rnums_[0])(ii,jj,kk) = fac *
( rc(i,j,k)+rc(i+1,j,k)+rc(i,j+1,k)+rc(i,j,k+1)+
rc(i+1,j+1,k)+rc(i+1,j,k+1)+rc(i,j+1,k+1)+rc(i+1,j+1,k+1));
sum += (*rnums_[0])(ii,jj,kk);
sum2+= (*rnums_[0])(ii,jj,kk) * (*rnums_[0])(ii,jj,kk);
++count;
}
}
}
}
double rmean, rvar;
rmean = sum/count;
rvar = sum2/count-rmean*rmean;
LOGINFO("Restricted random numbers have\n mean = %f, var = %f", rmean, rvar);
}
template< typename T >
random_numbers<T>::random_numbers( random_numbers<T>& rc, unsigned cubesize, long baseseed,
bool kspace, int *x0_, int *lx_, bool zeromean )
: res_( 2*rc.res_ ), cubesize_( cubesize ), ncubes_( 1 ), baseseed_( baseseed )
{
initialize();
int x0[3],lx[3];
if( x0_==NULL || lx_==NULL )
{
for(int i=0;i<3;++i ){
x0[i]=0;
lx[i]=res_;
}
fill_all();
}
else
{
for(int i=0;i<3;++i ){
x0[i]=x0_[i];
lx[i]=lx_[i];
}
fill_subvolume( x0, lx );
}
if( kspace )
{
LOGINFO("Generating a constrained random number set with seed %ld\n using coarse mode replacement...",baseseed);
size_t nx=lx[0], ny=lx[1], nz=lx[2],
nxc=lx[0]/2, nyc=lx[1]/2, nzc=lx[2]/2;
fftw_real *rfine = new fftw_real[nx*ny*(nz+2l)];
fftw_complex *cfine = reinterpret_cast<fftw_complex*> (rfine);
#ifdef FFTW3
#ifdef SINGLE_PRECISION
fftwf_plan
pf = fftwf_plan_dft_r2c_3d( nx, ny, nz, rfine, cfine, FFTW_ESTIMATE),
ipf = fftwf_plan_dft_c2r_3d( nx, ny, nz, cfine, rfine, FFTW_ESTIMATE);
#else
fftw_plan
pf = fftw_plan_dft_r2c_3d( nx, ny, nz, rfine, cfine, FFTW_ESTIMATE),
ipf = fftw_plan_dft_c2r_3d( nx, ny, nz, cfine, rfine, FFTW_ESTIMATE);
#endif
#else
rfftwnd_plan
pf = rfftw3d_create_plan( nx, ny, nz, FFTW_REAL_TO_COMPLEX, FFTW_ESTIMATE|FFTW_IN_PLACE),
ipf = rfftw3d_create_plan( nx, ny, nz, FFTW_COMPLEX_TO_REAL, FFTW_ESTIMATE|FFTW_IN_PLACE);
#endif
#pragma omp parallel for
for( int i=0; i<(int)nx; i++ )
for( int j=0; j<(int)ny; j++ )
for( int k=0; k<(int)nz; k++ )
{
size_t q = ((size_t)i*(size_t)ny+(size_t)j)*(size_t)(nz+2)+(size_t)k;
rfine[q] = (*this)(x0[0]+i,x0[1]+j,x0[2]+k);
}
//this->free_all_mem(); // temporarily free memory, allocate again later
fftw_real *rcoarse = new fftw_real[nxc*nyc*(nzc+2)];
fftw_complex *ccoarse = reinterpret_cast<fftw_complex*> (rcoarse);
#ifdef FFTW3
#ifdef SINGLE_PRECISION
fftwf_plan pc = fftwf_plan_dft_r2c_3d( nxc, nyc, nzc, rcoarse, ccoarse, FFTW_ESTIMATE);
#else
fftw_plan pc = fftw_plan_dft_r2c_3d( nxc, nyc, nzc, rcoarse, ccoarse, FFTW_ESTIMATE);
#endif
#else
rfftwnd_plan pc = rfftw3d_create_plan( nxc, nyc, nzc, FFTW_REAL_TO_COMPLEX, FFTW_ESTIMATE|FFTW_IN_PLACE);
#endif
#pragma omp parallel for
for( int i=0; i<(int)nxc; i++ )
for( int j=0; j<(int)nyc; j++ )
for( int k=0; k<(int)nzc; k++ )
{
size_t q = ((size_t)i*(size_t)nyc+(size_t)j)*(size_t)(nzc+2)+(size_t)k;
rcoarse[q] = rc(x0[0]/2+i,x0[1]/2+j,x0[2]/2+k);
}
#ifdef FFTW3
#ifdef SINGLE_PRECISION
fftwf_execute( pc );
fftwf_execute( pf );
#else
fftw_execute( pc );
fftw_execute( pf );
#endif
#else
#ifndef SINGLETHREAD_FFTW
rfftwnd_threads_one_real_to_complex( omp_get_max_threads(), pc, rcoarse, NULL );
rfftwnd_threads_one_real_to_complex( omp_get_max_threads(), pf, rfine, NULL );
#else
rfftwnd_one_real_to_complex( pc, rcoarse, NULL );
rfftwnd_one_real_to_complex( pf, rfine, NULL );
#endif
#endif
double fftnorm = 1.0/((double)nx*(double)ny*(double)nz);
#pragma omp parallel for
for( int i=0; i<(int)nxc; i++ )
for( int j=0; j<(int)nyc; j++ )
for( int k=0; k<(int)nzc/2+1; k++ )
{
int ii(i),jj(j),kk(k);
if( i > (int)nxc/2 ) ii += nx/2;
if( j > (int)nyc/2 ) jj += ny/2;
size_t qc,qf;
qc = ((size_t)i*(size_t)nyc+(size_t)j)*(nzc/2+1)+(size_t)k;
qf = ((size_t)ii*(size_t)ny+(size_t)jj)*(nz/2+1)+(size_t)kk;
RE(cfine[qf]) = sqrt(8.0)*RE(ccoarse[qc]);
IM(cfine[qf]) = sqrt(8.0)*IM(ccoarse[qc]);
}
delete[] rcoarse;
#pragma omp parallel for
for( int i=0; i<(int)nx; i++ )
for( int j=0; j<(int)ny; j++ )
for( int k=0; k<(int)nz/2+1; k++ )
{
size_t q = ((size_t)i*ny+(size_t)j)*(nz/2+1)+(size_t)k;
RE(cfine[q]) *= fftnorm;
IM(cfine[q]) *= fftnorm;
}
#ifdef FFTW3
#ifdef SINGLE_PRECISION
fftwf_execute( ipf );
#else
fftw_execute( ipf );
#endif
#else
#ifndef SINGLETHREAD_FFTW
rfftwnd_threads_one_complex_to_real( omp_get_max_threads(), ipf, cfine, NULL );
#else
rfftwnd_one_complex_to_real( ipf, cfine, NULL );
#endif
#endif
#pragma omp parallel for
for( int i=0; i<(int)nx; i++ )
for( int j=0; j<(int)ny; j++ )
for( int k=0; k<(int)nz; k++ )
{
size_t q = ((size_t)i*ny+(size_t)j)*(nz+2)+(size_t)k;
(*this)(x0[0]+i,x0[1]+j,x0[2]+k,false) = rfine[q];
}
delete[] rfine;
#ifdef FFTW3
#ifdef SINGLE_PRECISION
fftwf_destroy_plan(pf);
fftwf_destroy_plan(pc);
fftwf_destroy_plan(ipf);
#else
fftw_destroy_plan(pf);
fftw_destroy_plan(pc);
fftw_destroy_plan(ipf);
#endif
#else
fftwnd_destroy_plan(pf);
fftwnd_destroy_plan(pc);
fftwnd_destroy_plan(ipf);
#endif
}
else
{
LOGINFO("Generating a constrained random number set with seed %ld\n using Hoffman-Ribak constraints...", baseseed);
double fac = 1./sqrt(8.0);
for( int i=x0[0],ii=x0[0]/2; ii<lx[0]; i+=2,++ii )
for( int j=x0[1],jj=x0[1]/2; jj<lx[1]; j+=2,++jj )
for( int k=x0[2],kk=x0[2]/2; kk<lx[2]; k+=2,++kk )
{
double topval = rc(ii,jj,kk);
double locmean = 0.125*((*this)(i,j,k)+(*this)(i+1,j,k)+(*this)(i,j+1,k)+(*this)(i,j,k+1)+
(*this)(i+1,j+1,k)+(*this)(i+1,j,k+1)+(*this)(i,j+1,k+1)+(*this)(i+1,j+1,k+1));
double dif = fac*topval-locmean;
(*this)(i,j,k) += dif;
(*this)(i+1,j,k) += dif;
(*this)(i,j+1,k) += dif;
(*this)(i,j,k+1) += dif;
(*this)(i+1,j+1,k) += dif;
(*this)(i+1,j,k+1) += dif;
(*this)(i,j+1,k+1) += dif;
(*this)(i+1,j+1,k+1) += dif;
}
}
}
template< typename T >
void random_numbers<T>::register_cube( int i, int j, int k)
{
i = (i+ncubes_)%ncubes_;
j = (j+ncubes_)%ncubes_;
k = (k+ncubes_)%ncubes_;
size_t icube = ((size_t)i*ncubes_+(size_t)j)*ncubes_+(size_t)k;
cubemap_iterator it = cubemap_.find( icube );
if( it == cubemap_.end() )
{
rnums_.push_back( NULL );
cubemap_[icube] = rnums_.size()-1;
#ifdef DEBUG
LOGDEBUG("registering new cube %d,%d,%d . ID = %ld, memloc = %ld",i,j,k,icube,cubemap_[icube]);
#endif
}
}
template< typename T >
double random_numbers<T>::fill_cube( int i, int j, int k)
{
gsl_rng *RNG = gsl_rng_alloc( gsl_rng_mt19937 );
i = (i+ncubes_)%ncubes_;
j = (j+ncubes_)%ncubes_;
k = (k+ncubes_)%ncubes_;
size_t icube = ((size_t)i*ncubes_+(size_t)j)*ncubes_+(size_t)k;
long cubeseed = baseseed_+icube; //... each cube gets its unique seed
gsl_rng_set( RNG, cubeseed );
cubemap_iterator it = cubemap_.find( icube );
if( it == cubemap_.end() )
{
LOGERR("Attempt to access non-registered random number cube!");
throw std::runtime_error("Attempt to access non-registered random number cube!");
}
size_t cubeidx = it->second;
if( rnums_[cubeidx] == NULL )
rnums_[cubeidx] = new Meshvar<T>( cubesize_, 0, 0, 0 );
double mean = 0.0;
for( int ii=0; ii<(int)cubesize_; ++ii )
for( int jj=0; jj<(int)cubesize_; ++jj )
for( int kk=0; kk<(int)cubesize_; ++kk )
{
(*rnums_[cubeidx])(ii,jj,kk) = gsl_ran_ugaussian_ratio_method( RNG );
mean += (*rnums_[cubeidx])(ii,jj,kk);
}
gsl_rng_free( RNG );
return mean/(cubesize_*cubesize_*cubesize_);
}
template< typename T >
void random_numbers<T>::subtract_from_cube( int i, int j, int k, double val )
{
i = (i+ncubes_)%ncubes_;
j = (j+ncubes_)%ncubes_;
k = (k+ncubes_)%ncubes_;
size_t icube = ((size_t)i*ncubes_+(size_t)j)*ncubes_+(size_t)k;
cubemap_iterator it = cubemap_.find( icube );
if( it == cubemap_.end() )
{
LOGERR("Attempt to access unallocated RND cube %d,%d,%d in random_numbers::subtract_from_cube",i,j,k);
throw std::runtime_error("Attempt to access unallocated RND cube in random_numbers::subtract_from_cube");
}
size_t cubeidx = it->second;
for( int ii=0; ii<(int)cubesize_; ++ii )
for( int jj=0; jj<(int)cubesize_; ++jj )
for( int kk=0; kk<(int)cubesize_; ++kk )
(*rnums_[cubeidx])(ii,jj,kk) -= val;
}
template< typename T >
void random_numbers<T>::free_cube( int i, int j, int k )
{
i = (i+ncubes_)%ncubes_;
j = (j+ncubes_)%ncubes_;
k = (k+ncubes_)%ncubes_;
size_t icube = ((size_t)i*(size_t)ncubes_+(size_t)j)*(size_t)ncubes_+(size_t)k;
cubemap_iterator it = cubemap_.find( icube );
if( it == cubemap_.end() )
{
LOGERR("Attempt to access unallocated RND cube %d,%d,%d in random_numbers::free_cube",i,j,k);
throw std::runtime_error("Attempt to access unallocated RND cube in random_numbers::free_cube");
}
size_t cubeidx = it->second;
if( rnums_[cubeidx] != NULL )
{
delete rnums_[cubeidx];
rnums_[cubeidx] = NULL;
}
}
template< typename T >
void random_numbers<T>::initialize( void )
{
ncubes_ = std::max((int)((double)res_/cubesize_),1);
if( res_ < cubesize_ )
{
ncubes_ = 1;
cubesize_ = res_;
}
LOGINFO("Generating random numbers w/ sample cube size of %d", cubesize_ );
}
template< typename T >
double random_numbers<T>::fill_subvolume( int *i0, int *n )
{
int i0cube[3], ncube[3];
i0cube[0] = (int)((double)(res_+i0[0])/cubesize_);
i0cube[1] = (int)((double)(res_+i0[1])/cubesize_);
i0cube[2] = (int)((double)(res_+i0[2])/cubesize_);
ncube[0] = (int)(n[0]/cubesize_) + 2;
ncube[1] = (int)(n[1]/cubesize_) + 2;
ncube[2] = (int)(n[2]/cubesize_) + 2;
#ifdef DEBUG
LOGDEBUG("random numbers needed for region %d,%d,%d ..+ %d,%d,%d",i0[0],i0[1],i0[2],n[0],n[1],n[2]);
LOGDEBUG("filling cubes %d,%d,%d ..+ %d,%d,%d",i0cube[0],i0cube[1],i0cube[2],ncube[0],ncube[1],ncube[2]);
#endif
double mean = 0.0;
for( int i=i0cube[0]; i<i0cube[0]+ncube[0]; ++i )
for( int j=i0cube[1]; j<i0cube[1]+ncube[1]; ++j )
for( int k=i0cube[2]; k<i0cube[2]+ncube[2]; ++k )
{
int ii(i),jj(j),kk(k);
ii = (ii+ncubes_)%ncubes_;
jj = (jj+ncubes_)%ncubes_;
kk = (kk+ncubes_)%ncubes_;
register_cube( ii,jj,kk );
}
#pragma omp parallel for reduction(+:mean)
for( int i=i0cube[0]; i<i0cube[0]+ncube[0]; ++i )
for( int j=i0cube[1]; j<i0cube[1]+ncube[1]; ++j )
for( int k=i0cube[2]; k<i0cube[2]+ncube[2]; ++k )
{
int ii(i),jj(j),kk(k);
ii = (ii+ncubes_)%ncubes_;
jj = (jj+ncubes_)%ncubes_;
kk = (kk+ncubes_)%ncubes_;
mean += fill_cube(ii, jj, kk);
}
return mean/(ncube[0]*ncube[1]*ncube[2]);
}
template< typename T >
double random_numbers<T>::fill_all( void )
{
double sum = 0.0;
for( int i=0; i<(int)ncubes_; ++i )
for( int j=0; j<(int)ncubes_; ++j )
for( int k=0; k<(int)ncubes_; ++k )
{
int ii(i),jj(j),kk(k);
ii = (ii+ncubes_)%ncubes_;
jj = (jj+ncubes_)%ncubes_;
kk = (kk+ncubes_)%ncubes_;
register_cube(ii,jj,kk);
}
#pragma omp parallel for reduction(+:sum)
for( int i=0; i<(int)ncubes_; ++i )
for( int j=0; j<(int)ncubes_; ++j )
for( int k=0; k<(int)ncubes_; ++k )
{
int ii(i),jj(j),kk(k);
ii = (ii+ncubes_)%ncubes_;
jj = (jj+ncubes_)%ncubes_;
kk = (kk+ncubes_)%ncubes_;
sum+=fill_cube(ii, jj, kk);
}
//... subtract mean
#pragma omp parallel for reduction(+:sum)
for( int i=0; i<(int)ncubes_; ++i )
for( int j=0; j<(int)ncubes_; ++j )
for( int k=0; k<(int)ncubes_; ++k )
{
int ii(i),jj(j),kk(k);
ii = (ii+ncubes_)%ncubes_;
jj = (jj+ncubes_)%ncubes_;
kk = (kk+ncubes_)%ncubes_;
subtract_from_cube(ii,jj,kk,sum/(ncubes_*ncubes_*ncubes_));
}
return sum/(ncubes_*ncubes_*ncubes_);
}
template< typename T >
void random_numbers<T>:: print_allocated( void )
{
unsigned ncount = 0, ntot = rnums_.size();
for( size_t i=0; i<rnums_.size(); ++i )
if( rnums_[i]!=NULL ) ncount++;
LOGINFO(" -> %d of %d random number cubes currently allocated",ncount,ntot);
}
//////////////////////////////////////////////////////////////////////////////////////////////////////////
//////////////////////////////////////////////////////////////////////////////////////////////////////////
#pragma mark -
//////////////////////////////////////////////////////////////////////////////////////////////////////////
//////////////////////////////////////////////////////////////////////////////////////////////////////////
template< typename rng, typename T >
random_number_generator<rng,T>::random_number_generator( config_file& cf, refinement_hierarchy& refh, transfer_function *ptf )
: pcf_( &cf ), prefh_( &refh ), constraints( cf, ptf )
{
levelmin_ = prefh_->levelmin();
levelmax_ = prefh_->levelmax();
ran_cube_size_ = pcf_->getValueSafe<unsigned>("random","cubesize",DEF_RAN_CUBE_SIZE);
disk_cached_ = pcf_->getValueSafe<bool>("random","disk_cached",true);
restart_ = pcf_->getValueSafe<bool>("random","restart",false);
mem_cache_.assign(levelmax_-levelmin_+1, (std::vector<T>*)NULL);
if( restart_ && !disk_cached_ )
{
LOGERR("Cannot restart from mem cached random numbers.");
throw std::runtime_error("Cannot restart from mem cached random numbers.");
}
////disk_cached_ = false;
//... determine seed/white noise file data to be applied
parse_rand_parameters();
if( !restart_ )
{
//... compute the actual random numbers
compute_random_numbers();
}
}
template< typename rng, typename T >
random_number_generator<rng,T>::~random_number_generator()
{
//... clear memory caches
for( unsigned i=0; i<mem_cache_.size(); ++i )
if( mem_cache_[i] != NULL )
delete mem_cache_[i];
//... clear disk caches
if( disk_cached_ )
{
for( int ilevel=levelmin_; ilevel<=levelmax_; ++ilevel )
{
char fname[128];
sprintf(fname,"wnoise_%04d.bin",ilevel);
// unlink(fname);
}
}
}
template< typename rng, typename T >
bool random_number_generator<rng,T>::is_number(const std::string& s)
{
for (size_t i = 0; i < s.length(); i++)
if (!std::isdigit(s[i])&&s[i]!='-' )
return false;
return true;
}
template< typename rng, typename T >
void random_number_generator<rng,T>::parse_rand_parameters( void )
{
//... parse random number options
for( int i=0; i<=100; ++i )
{
char seedstr[128];
std::string tempstr;
sprintf(seedstr,"seed[%d]",i);
if( pcf_->containsKey( "random", seedstr ) )
tempstr = pcf_->getValue<std::string>( "random", seedstr );
else
// "-2" means that no seed entry was found for that level
tempstr = std::string("-2");
if( is_number( tempstr ) )
{
long ltemp;
pcf_->convert( tempstr, ltemp );
rngfnames_.push_back( "" );
if( ltemp < 0 )
//... generate some dummy seed which only depends on the level, negative so we know it's not
//... an actual seed and thus should not be used as a constraint for coarse levels
//rngseeds_.push_back( -abs((unsigned)(ltemp-i)%123+(unsigned)(ltemp+827342523521*i)%123456789) );
rngseeds_.push_back( -abs((long)(ltemp-i)%123+(long)(ltemp+7342523521*i)%123456789) );
else
rngseeds_.push_back( ltemp );
}else{
rngfnames_.push_back( tempstr );
rngseeds_.push_back(-1);
LOGINFO("Random numbers for level %3d will be read from file.",i);
}
}
//.. determine for which levels random seeds/random number files are given
levelmin_seed_ = -1;
for( unsigned ilevel = 0; ilevel < rngseeds_.size(); ++ilevel )
{
if( levelmin_seed_ < 0 && (rngfnames_[ilevel].size() > 0 || rngseeds_[ilevel] > 0) )
levelmin_seed_ = ilevel;
}
}
template< typename rng, typename T >
void random_number_generator<rng,T>::correct_avg( int icoarse, int ifine )
{
int shift[3], levelmin_poisson;
shift[0] = pcf_->getValue<int>("setup","shift_x");
shift[1] = pcf_->getValue<int>("setup","shift_y");
shift[2] = pcf_->getValue<int>("setup","shift_z");
levelmin_poisson = pcf_->getValue<unsigned>("setup","levelmin");
int lfacc = 1<<(icoarse-levelmin_poisson);
int nc[3], i0c[3], nf[3], i0f[3];
if( icoarse != levelmin_ )
{
nc[0] = 2*prefh_->size(icoarse, 0);
nc[1] = 2*prefh_->size(icoarse, 1);
nc[2] = 2*prefh_->size(icoarse, 2);
i0c[0] = prefh_->offset_abs(icoarse, 0) - lfacc*shift[0] - nc[0]/4;
i0c[1] = prefh_->offset_abs(icoarse, 1) - lfacc*shift[1] - nc[1]/4;
i0c[2] = prefh_->offset_abs(icoarse, 2) - lfacc*shift[2] - nc[2]/4;
}
else
{
nc[0] = prefh_->size(icoarse, 0);
nc[1] = prefh_->size(icoarse, 1);
nc[2] = prefh_->size(icoarse, 2);
i0c[0] = - lfacc*shift[0];
i0c[1] = - lfacc*shift[1];
i0c[2] = - lfacc*shift[2];
}
nf[0] = 2*prefh_->size(ifine, 0);
nf[1] = 2*prefh_->size(ifine, 1);
nf[2] = 2*prefh_->size(ifine, 2);
i0f[0] = prefh_->offset_abs(ifine, 0) - 2*lfacc*shift[0] - nf[0]/4;
i0f[1] = prefh_->offset_abs(ifine, 1) - 2*lfacc*shift[1] - nf[1]/4;
i0f[2] = prefh_->offset_abs(ifine, 2) - 2*lfacc*shift[2] - nf[2]/4;
//.................................
if( disk_cached_ )
{
char fncoarse[128], fnfine[128];
sprintf(fncoarse,"wnoise_%04d.bin",icoarse);
sprintf(fnfine,"wnoise_%04d.bin",ifine);
std::ifstream
iffine( fnfine, std::ios::binary ),
ifcoarse( fncoarse, std::ios::binary );
int nxc,nyc,nzc,nxf,nyf,nzf;
iffine.read( reinterpret_cast<char*> (&nxf), sizeof(unsigned) );
iffine.read( reinterpret_cast<char*> (&nyf), sizeof(unsigned) );
iffine.read( reinterpret_cast<char*> (&nzf), sizeof(unsigned) );
ifcoarse.read( reinterpret_cast<char*> (&nxc), sizeof(unsigned) );
ifcoarse.read( reinterpret_cast<char*> (&nyc), sizeof(unsigned) );
ifcoarse.read( reinterpret_cast<char*> (&nzc), sizeof(unsigned) );
if( nxf!=nf[0] || nyf!=nf[1] || nzf!=nf[2] || nxc!=nc[0] || nyc!=nc[1] || nzc!=nc[2] )
{
LOGERR("White noise file mismatch. This should not happen. Notify a developer!");
throw std::runtime_error("White noise file mismatch. This should not happen. Notify a developer!");
}
int nxd(nxf/2),nyd(nyf/2),nzd(nzf/2);
std::vector<T> deg_rand( (size_t)nxd*(size_t)nyd*(size_t)nzd, 0.0 );
double fac = 1.0/sqrt(8.0);
for( int i=0, ic=0; i<nxf; i+=2, ic++ )
{
std::vector<T> fine_rand( 2*nyf*nzf, 0.0 );
iffine.read( reinterpret_cast<char*> (&fine_rand[0]), 2*nyf*nzf*sizeof(T) );
#pragma omp parallel for
for( int j=0; j<nyf; j+=2 )
for( int k=0; k<nzf; k+=2 )
{
int jc = j/2, kc = k/2;
//size_t qc = (((size_t)i/2)*(size_t)nyd+((size_t)j/2))*(size_t)nzd+((size_t)k/2);
size_t qc = ((size_t)(ic*nyd+jc))*(size_t)nzd+(size_t)kc;
size_t qf[8];
qf[0] = (0*(size_t)nyf+(size_t)j+0)*(size_t)nzf+(size_t)k+0;
qf[1] = (0*(size_t)nyf+(size_t)j+0)*(size_t)nzf+(size_t)k+1;
qf[2] = (0*(size_t)nyf+(size_t)j+1)*(size_t)nzf+(size_t)k+0;
qf[3] = (0*(size_t)nyf+(size_t)j+1)*(size_t)nzf+(size_t)k+1;
qf[4] = (1*(size_t)nyf+(size_t)j+0)*(size_t)nzf+(size_t)k+0;
qf[5] = (1*(size_t)nyf+(size_t)j+0)*(size_t)nzf+(size_t)k+1;
qf[6] = (1*(size_t)nyf+(size_t)j+1)*(size_t)nzf+(size_t)k+0;
qf[7] = (1*(size_t)nyf+(size_t)j+1)*(size_t)nzf+(size_t)k+1;
double d = 0.0;
for( int q=0; q<8; ++q )
d += fac*fine_rand[qf[q]];
//deg_rand[qc] += d;
deg_rand[qc] = d;
}
}
//... now deg_rand holds the oct-averaged fine field, store this in the coarse field
std::vector<T> coarse_rand(nxc*nyc*nzc,0.0);
ifcoarse.read( reinterpret_cast<char*> (&coarse_rand[0]), nxc*nyc*nzc*sizeof(T) );
int di,dj,dk;
di = i0f[0]/2-i0c[0];
dj = i0f[1]/2-i0c[1];
dk = i0f[2]/2-i0c[2];
#pragma omp parallel for
for( int i=0; i<nxd; i++ )
for( int j=0; j<nyd; j++ )
for( int k=0; k<nzd; k++ )
{
//unsigned qc = (((i+di+nxc)%nxc)*nyc+(((j+dj+nyc)%nyc)))*nzc+((k+dk+nzc)%nzc);
if( i+di < 0 || i+di >= nxc || j+dj < 0 || j+dj >= nyc || k+dk < 0 || k+dk >= nzc )
continue;
size_t qc = (((size_t)i+(size_t)di)*(size_t)nyc+((size_t)j+(size_t)dj))*(size_t)nzc+(size_t)(k+dk);
size_t qcd = (size_t)(i*nyd+j)*(size_t)nzd+(size_t)k;
coarse_rand[qc] = deg_rand[qcd];
}
deg_rand.clear();
ifcoarse.close();
std::ofstream ofcoarse( fncoarse, std::ios::binary|std::ios::trunc );
ofcoarse.write( reinterpret_cast<char*> (&nxc), sizeof(unsigned) );
ofcoarse.write( reinterpret_cast<char*> (&nyc), sizeof(unsigned) );
ofcoarse.write( reinterpret_cast<char*> (&nzc), sizeof(unsigned) );
ofcoarse.write( reinterpret_cast<char*> (&coarse_rand[0]), nxc*nyc*nzc*sizeof(T) );
ofcoarse.close();
}
else
{
int nxc,nyc,nzc,nxf,nyf,nzf;
nxc = nc[0]; nyc = nc[1]; nzc = nc[2];
nxf = nf[0]; nyf = nf[1]; nzf = nf[2];
int nxd(nxf/2),nyd(nyf/2),nzd(nzf/2);
int di,dj,dk;
di = i0f[0]/2-i0c[0];
dj = i0f[1]/2-i0c[1];
dk = i0f[2]/2-i0c[2];
double fac = 1.0/sqrt(8.0);
#pragma omp parallel for
for( int i=0; i<nxd; i++ )
for( int j=0; j<nyd; j++ )
for( int k=0; k<nzd; k++ )
{
if( i+di < 0 || i+di >= nxc || j+dj < 0 || j+dj >= nyc || k+dk < 0 || k+dk >= nzc )
continue;
size_t qf[8];
qf[0] = (size_t)((2*i+0)*nyf+2*j+0)*(size_t)nzf+(size_t)(2*k+0);
qf[1] = (size_t)((2*i+0)*nyf+2*j+0)*(size_t)nzf+(size_t)(2*k+1);
qf[2] = (size_t)((2*i+0)*nyf+2*j+1)*(size_t)nzf+(size_t)(2*k+0);
qf[3] = (size_t)((2*i+0)*nyf+2*j+1)*(size_t)nzf+(size_t)(2*k+1);
qf[4] = (size_t)((2*i+1)*nyf+2*j+0)*(size_t)nzf+(size_t)(2*k+0);
qf[5] = (size_t)((2*i+1)*nyf+2*j+0)*(size_t)nzf+(size_t)(2*k+1);
qf[6] = (size_t)((2*i+1)*nyf+2*j+1)*(size_t)nzf+(size_t)(2*k+0);
qf[7] = (size_t)((2*i+1)*nyf+2*j+1)*(size_t)nzf+(size_t)(2*k+1);
double finesum = 0.0;
for( int q=0; q<8; ++q )
finesum += fac*(*mem_cache_[ifine-levelmin_])[qf[q]];
size_t qc = ((size_t)(i+di)*nyc+(size_t)(j+dj))*(size_t)nzc+(size_t)(k+dk);
(*mem_cache_[icoarse-levelmin_])[qc] = finesum;
}
}
}
template< typename rng, typename T >
void random_number_generator<rng,T>::compute_random_numbers( void )
{
bool kavg = pcf_->getValueSafe<bool>("random","kaveraging",true);
bool rndsign = pcf_->getValueSafe<bool>("random","grafic_sign",false);
std::vector< rng* > randc(std::max(levelmax_,levelmin_seed_)+1,(rng*)NULL);
//--- FILL ALL WHITE NOISE ARRAYS FOR WHICH WE NEED THE FULL FIELD ---//
//... seeds are given for a level coarser than levelmin
if( levelmin_seed_ < levelmin_ )
{
if( rngfnames_[levelmin_seed_].size() > 0 )
randc[levelmin_seed_]
= new rng( 1<<levelmin_seed_, rngfnames_[levelmin_seed_], rndsign );
else
randc[levelmin_seed_]
= new rng( 1<<levelmin_seed_, ran_cube_size_, rngseeds_[levelmin_seed_], true );
for( int i=levelmin_seed_+1; i<=levelmin_; ++i )
{
//#warning add possibility to read noise from file also here!
if( rngfnames_[i].size() > 0 )
LOGINFO("Warning: Cannot use filenames for higher levels currently! Ignoring!");
randc[i] = new rng( *randc[i-1], ran_cube_size_, rngseeds_[i], kavg );
delete randc[i-1];
randc[i-1] = NULL;
}
}
//... seeds are given for a level finer than levelmin, obtain by averaging
if( levelmin_seed_ > levelmin_ )
{
if( rngfnames_[levelmin_seed_].size() > 0 )
randc[levelmin_seed_] = new rng( 1<<levelmin_seed_, rngfnames_[levelmin_seed_], rndsign );
else
randc[levelmin_seed_] = new rng( 1<<levelmin_seed_, ran_cube_size_, rngseeds_[levelmin_seed_], true );//, x0, lx );
for( int ilevel = levelmin_seed_-1; ilevel >= (int)levelmin_; --ilevel ){
if( rngseeds_[ilevel-levelmin_] > 0 )
LOGINFO("Warning: random seed for level %d will be ignored.\n" \
" consistency requires that it is obtained by restriction from level %d", ilevel, levelmin_seed_ );
if( ilevel >= levelmax_ )
randc[ilevel] = new rng( *randc[ilevel+1], kavg );
else
randc[ilevel] = new rng( *randc[ilevel+1], false );
if( ilevel+1 > levelmax_ )
{
delete randc[ilevel+1];
randc[ilevel+1] = NULL;
}
}
}
//--- GENERATE AND STORE ALL LEVELS, INCLUDING REFINEMENTS ---//
//... levelmin
if( randc[levelmin_] == NULL )
{
if( rngfnames_[levelmin_].size() > 0 )
randc[levelmin_] = new rng( 1<<levelmin_, rngfnames_[levelmin_], rndsign );
else
randc[levelmin_] = new rng( 1<<levelmin_, ran_cube_size_, rngseeds_[levelmin_], true );
}
//if( levelmax_ == levelmin_ )
{
//... apply constraints to coarse grid
//... if no constraints are specified, or not for this level
//... constraints.apply will return without doing anything
int x0[3] = { 0, 0, 0 };
int lx[3] = { 1<<levelmin_, 1<<levelmin_, 1<<levelmin_ };
constraints.apply( levelmin_, x0, lx, randc[levelmin_] );
}
store_rnd( levelmin_, randc[levelmin_] );
//... refinement levels
for( int ilevel=levelmin_+1; ilevel<=levelmax_; ++ilevel )
{
int lx[3], x0[3];
int shift[3], levelmin_poisson;
shift[0] = pcf_->getValue<int>("setup","shift_x");
shift[1] = pcf_->getValue<int>("setup","shift_y");
shift[2] = pcf_->getValue<int>("setup","shift_z");
levelmin_poisson = pcf_->getValue<unsigned>("setup","levelmin");
int lfac = 1<<(ilevel-levelmin_poisson);
lx[0] = 2*prefh_->size(ilevel, 0);
lx[1] = 2*prefh_->size(ilevel, 1);
lx[2] = 2*prefh_->size(ilevel, 2);
x0[0] = prefh_->offset_abs(ilevel, 0) - lfac*shift[0] - lx[0]/4;
x0[1] = prefh_->offset_abs(ilevel, 1) - lfac*shift[1] - lx[1]/4;
x0[2] = prefh_->offset_abs(ilevel, 2) - lfac*shift[2] - lx[2]/4;
if( randc[ilevel] == NULL )
randc[ilevel] = new rng( *randc[ilevel-1], ran_cube_size_, rngseeds_[ilevel], kavg, x0, lx );
delete randc[ilevel-1];
randc[ilevel-1] = NULL;
//... apply constraints to this level, if any
//if( ilevel == levelmax_ )
constraints.apply( ilevel, x0, lx, randc[ilevel] );
//... store numbers
store_rnd( ilevel, randc[ilevel] );
}
delete randc[levelmax_];
randc[levelmax_] = NULL;
//... make sure that the coarse grid contains oct averages where it overlaps with a fine grid
//... this also ensures that constraints enforced on fine grids are carried to the coarser grids
for( int ilevel=levelmax_; ilevel>levelmin_; --ilevel )
correct_avg( ilevel-1, ilevel );
//.. we do not have random numbers for a coarse level, generate them
/*if( levelmax_rand_ >= (int)levelmin_ )
{
std::cerr << "lmaxread >= (int)levelmin\n";
randc[levelmax_rand_] = new rng( (unsigned)pow(2,levelmax_rand_), rngfnames_[levelmax_rand_] );
for( int ilevel = levelmax_rand_-1; ilevel >= (int)levelmin_; --ilevel )
randc[ilevel] = new rng( *randc[ilevel+1] );
}*/
}
template< typename rng, typename T >
void random_number_generator<rng,T>:: store_rnd( int ilevel, rng* prng )
{
int shift[3], levelmin_poisson;
shift[0] = pcf_->getValue<int>("setup","shift_x");
shift[1] = pcf_->getValue<int>("setup","shift_y");
shift[2] = pcf_->getValue<int>("setup","shift_z");
levelmin_poisson = pcf_->getValue<unsigned>("setup","levelmin");
int lfac = 1<<(ilevel-levelmin_poisson);
bool grafic_out = false;
if( grafic_out )
{
std::vector<float> data;
if( ilevel == levelmin_ )
{
int N = 1<<levelmin_;
int i0,j0,k0;
i0 = -lfac*shift[0];
j0 = -lfac*shift[1];
k0 = -lfac*shift[2];
char fname[128];
sprintf(fname,"grafic_wnoise_%04d.bin",ilevel);
LOGUSER("Storing white noise field for grafic in file \'%s\'...", fname );
std::ofstream ofs(fname,std::ios::binary|std::ios::trunc);
data.assign( N*N, 0.0 );
int blksize = 4*sizeof(int);
int iseed = 0;
ofs.write(reinterpret_cast<char*> (&blksize), sizeof(int) );
ofs.write(reinterpret_cast<char*> (&N), sizeof(int) );
ofs.write(reinterpret_cast<char*> (&N), sizeof(int) );
ofs.write(reinterpret_cast<char*> (&N), sizeof(int) );
ofs.write(reinterpret_cast<char*> (&iseed), sizeof(int) );
ofs.write(reinterpret_cast<char*> (&blksize), sizeof(int) );
for( int k=0; k<N; ++k )
{
#pragma omp parallel for
for( int j=0; j<N; ++j )
for( int i=0; i<N; ++i )
data[j*N+i] = -(*prng)(i+i0,j+j0,k+k0);
blksize = N*N*sizeof(float);
ofs.write(reinterpret_cast<char*> (&blksize), sizeof(int) );
ofs.write(reinterpret_cast<char*> (&data[0]), N*N*sizeof(float) );
ofs.write(reinterpret_cast<char*> (&blksize), sizeof(int) );
}
ofs.close();
}
else {
int nx,ny,nz;
int i0,j0,k0;
nx = prefh_->size(ilevel, 0);
ny = prefh_->size(ilevel, 1);
nz = prefh_->size(ilevel, 2);
i0 = prefh_->offset_abs(ilevel, 0) - lfac*shift[0];
j0 = prefh_->offset_abs(ilevel, 1) - lfac*shift[1];
k0 = prefh_->offset_abs(ilevel, 2) - lfac*shift[2];
char fname[128];
sprintf(fname,"grafic_wnoise_%04d.bin",ilevel);
LOGUSER("Storing white noise field for grafic in file \'%s\'...", fname );
LOGDEBUG("(%d,%d,%d) -- (%d,%d,%d) -- lfac = %d",nx,ny,nz,i0,j0,k0,lfac);
std::ofstream ofs(fname,std::ios::binary|std::ios::trunc);
data.assign( nx*ny, 0.0 );
int blksize = 4*sizeof(int);
int iseed = 0;
ofs.write(reinterpret_cast<char*> (&blksize), sizeof(int) );
ofs.write( reinterpret_cast<char*> (&nz), sizeof(unsigned) );
ofs.write( reinterpret_cast<char*> (&ny), sizeof(unsigned) );
ofs.write( reinterpret_cast<char*> (&nx), sizeof(unsigned) );
ofs.write(reinterpret_cast<char*> (&iseed), sizeof(int) );
ofs.write(reinterpret_cast<char*> (&blksize), sizeof(int) );
for( int k=0; k<nz; ++k )
{
#pragma omp parallel for
for( int j=0; j<ny; ++j )
for( int i=0; i<nx; ++i )
data[j*nx+i] = -(*prng)(i+i0,j+j0,k+k0);
blksize = nx*ny*sizeof(float);
ofs.write(reinterpret_cast<char*> (&blksize), sizeof(int) );
ofs.write(reinterpret_cast<char*> (&data[0]), nx*ny*sizeof(float) );
ofs.write(reinterpret_cast<char*> (&blksize), sizeof(int) );
}
ofs.close();
}
}
if( disk_cached_ )
{
std::vector<T> data;
if( ilevel == levelmin_ )
{
int N = 1<<levelmin_;
int i0,j0,k0;
i0 = -lfac*shift[0];
j0 = -lfac*shift[1];
k0 = -lfac*shift[2];
char fname[128];
sprintf(fname,"wnoise_%04d.bin",ilevel);
LOGUSER("Storing white noise field in file \'%s\'...", fname );
std::ofstream ofs(fname,std::ios::binary|std::ios::trunc);
ofs.write( reinterpret_cast<char*> (&N), sizeof(unsigned) );
ofs.write( reinterpret_cast<char*> (&N), sizeof(unsigned) );
ofs.write( reinterpret_cast<char*> (&N), sizeof(unsigned) );
data.assign( N*N, 0.0 );
for( int i=0; i<N; ++i )
{
#pragma omp parallel for
for( int j=0; j<N; ++j )
for( int k=0; k<N; ++k )
data[j*N+k] = (*prng)(i+i0,j+j0,k+k0);
ofs.write(reinterpret_cast<char*> (&data[0]), N*N*sizeof(T) );
}
ofs.close();
}
else
{
int nx,ny,nz;
int i0,j0,k0;
nx = 2*prefh_->size(ilevel, 0);
ny = 2*prefh_->size(ilevel, 1);
nz = 2*prefh_->size(ilevel, 2);
i0 = prefh_->offset_abs(ilevel, 0) - lfac*shift[0] - nx/4;
j0 = prefh_->offset_abs(ilevel, 1) - lfac*shift[1] - ny/4; // was nx/4
k0 = prefh_->offset_abs(ilevel, 2) - lfac*shift[2] - nz/4; // was nx/4
char fname[128];
sprintf(fname,"wnoise_%04d.bin",ilevel);
LOGUSER("Storing white noise field in file \'%s\'...", fname );
std::ofstream ofs(fname,std::ios::binary|std::ios::trunc);
ofs.write( reinterpret_cast<char*> (&nx), sizeof(unsigned) );
ofs.write( reinterpret_cast<char*> (&ny), sizeof(unsigned) );
ofs.write( reinterpret_cast<char*> (&nz), sizeof(unsigned) );
data.assign( ny*nz, 0.0 );
for( int i=0; i<nx; ++i )
{
#pragma omp parallel for
for( int j=0; j<ny; ++j )
for( int k=0; k<nz; ++k )
data[j*nz+k] = (*prng)(i+i0,j+j0,k+k0);
ofs.write(reinterpret_cast<char*> (&data[0]), ny*nz*sizeof(T) );
}
ofs.close();
}
}
else
{
int nx,ny,nz;
int i0,j0,k0;
if( ilevel == levelmin_ )
{
i0 = -lfac*shift[0];
j0 = -lfac*shift[1];
k0 = -lfac*shift[2];
nx = ny = nz = 1<<levelmin_;
}
else
{
nx = 2*prefh_->size(ilevel, 0);
ny = 2*prefh_->size(ilevel, 1);
nz = 2*prefh_->size(ilevel, 2);
i0 = prefh_->offset_abs(ilevel, 0) - lfac*shift[0] - nx/4;
j0 = prefh_->offset_abs(ilevel, 1) - lfac*shift[1] - ny/4; // was nx/4
k0 = prefh_->offset_abs(ilevel, 2) - lfac*shift[2] - nz/4; // was nx/4
}
mem_cache_[ilevel-levelmin_] = new std::vector<T>(nx*ny*nz,0.0);
LOGUSER("Copying white noise to mem cache...");
#pragma omp parallel for
for( int i=0; i<nx; ++i )
for( int j=0; j<ny; ++j )
for( int k=0; k<nz; ++k )
(*mem_cache_[ilevel-levelmin_])[((size_t)i*ny+(size_t)j)*nz+(size_t)k] = (*prng)(i+i0,j+j0,k+k0);
}
}
//////////////////////////////////////////////////////////////////////////////////////////////////////////
//////////////////////////////////////////////////////////////////////////////////////////////////////////
#pragma mark -
//////////////////////////////////////////////////////////////////////////////////////////////////////////
//////////////////////////////////////////////////////////////////////////////////////////////////////////
template class random_numbers<float>;
template class random_numbers<double>;
template class random_number_generator< random_numbers<float>, float >;
template class random_number_generator< random_numbers<double>, double >;
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