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fixes to the noise interpolation, improves stability of large-scale modes substantially

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Oliver Hahn 2013-08-27 21:50:51 -07:00
parent 7db63aba4a
commit 5d84806257
3 changed files with 71 additions and 23 deletions
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2
Makefile
View file

@ -3,7 +3,7 @@
FFTW3 = yes
MULTITHREADFFTW = yes
SINGLEPRECISION = no
HAVEHDF5 = no
HAVEHDF5 = yes
HAVEBOXLIB = no
BOXLIB_HOME = ${HOME}/nyx_tot_sterben/BoxLib

2
main.cc
View file

@ -37,7 +37,7 @@
#include "transfer_function.hh"
#define THE_CODE_NAME "music!"
#define THE_CODE_VERSION "1.3b"
#define THE_CODE_VERSION "1.4b"
namespace music

90
random.cc
View file

@ -499,7 +499,7 @@ random_numbers<T>::random_numbers( random_numbers<T>& rc, unsigned cubesize, lon
{
LOGINFO("Generating a constrained random number set with seed %ld\n using coarse mode replacement...",baseseed);
assert(lx[0]%2==0 && lx[1]%2==0 && lx[2]%2==0);
size_t nx=lx[0], ny=lx[1], nz=lx[2],
nxc=lx[0]/2, nyc=lx[1]/2, nzc=lx[2]/2;
@ -575,25 +575,73 @@ random_numbers<T>::random_numbers( random_numbers<T>& rc, unsigned cubesize, lon
#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++ )
double sqrt8 = sqrt(8.0);
// embedding
// 0 0
#pragma omp parallel for
for( int i=0; i<(int)nxc/2+1; i++ )
for( int j=0; j<(int)nyc/2+1; 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;
{
int ii(i),jj(j),kk(k);
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]);
}
RE(cfine[qf]) = sqrt8*RE(ccoarse[qc]);
IM(cfine[qf]) = sqrt8*IM(ccoarse[qc]);
}
// 1 0
#pragma omp parallel for
for( int i=nxc/2; i<(int)nxc; i++ )
for( int j=0; j<(int)nyc/2+1; j++ )
for( int k=0; k<(int)nzc/2+1; k++ )
{
int ii(i+nx/2),jj(j),kk(k);
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]) = sqrt8*RE(ccoarse[qc]);
IM(cfine[qf]) = sqrt8*IM(ccoarse[qc]);
if( i==(int)nxc/2 || j==(int)nyc/2 )
IM(cfine[qf]) *= -1.0;
}
// 0 1
#pragma omp parallel for
for( int i=0; i<(int)nxc/2+1; i++ )
for( int j=nyc/2; j<(int)nyc; j++ )
for( int k=0; k<(int)nzc/2+1; k++ )
{
int ii(i),jj(j+ny/2),kk(k);
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]) = sqrt8*RE(ccoarse[qc]);
IM(cfine[qf]) = sqrt8*IM(ccoarse[qc]);
if( i==(int)nxc/2 || j==(int)nyc/2 )
IM(cfine[qf]) *= -1.0;
}
// 1 1
#pragma omp parallel for
for( int i=nxc/2; i<(int)nxc; i++ )
for( int j=nyc/2; j<(int)nyc; j++ )
for( int k=0; k<(int)nzc/2+1; k++ )
{
int ii(i+nx/2),jj(j+ny/2),kk(k);
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]) = sqrt8*RE(ccoarse[qc]);
IM(cfine[qf]) = sqrt8*IM(ccoarse[qc]);
}
delete[] rcoarse;
#pragma omp parallel for
@ -655,11 +703,11 @@ random_numbers<T>::random_numbers( random_numbers<T>& rc, unsigned cubesize, lon
{
LOGINFO("Generating a constrained random number set with seed %ld\n using Hoffman-Ribak constraints...", baseseed);
double fac = 1./sqrt(8.0);
double fac = 1.0/sqrt(8.0);//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 )
for( int i=x0[0],ii=x0[0]/2; i<x0[0]+lx[0]; i+=2,++ii )
for( int j=x0[1],jj=x0[1]/2; j<x0[1]+lx[1]; j+=2,++jj )
for( int k=x0[2],kk=x0[2]/2; k<x0[2]+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)+