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o_run_bayes.c
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Sun, Jan 5, 02:42

o_run_bayes.c
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#include<stdio.h>
#include<signal.h>
#include<stdlib.h>
#include<string.h>
#include<math.h>
#include<fonction.h>
#include<constant.h>
#include<dimension.h>
#include<structure.h>
#include "bayesys3.h"
#include "userstr.h"
#include "lt.h"
/****************************************************************/
/* nom: o_run_bayes */
/* auteur: Eric Jullo */
/* date: 01/06 */
/* place: ESO, Chile */
/****************************************************************
* Optimise the potential parameters using the bayesys3 algorithm.
*
*/
typedef void (*sighandler_t)(int);
static void signalReset(int);
int optInterrupt; // Global variable read in bayesapp.c/UserMonitor()
double *tmpCube; // temporary Cube to be used in UserBuild()
double **zbitstmp1;
int *ibitstmp;
// Mutex functions implemented in bayesapp.c
void init_mutex();
void destroy_mutex();
double o_run_bayes()
{
extern struct g_mode M;
extern struct g_image I;
extern struct g_grille G;
// Addressing
CommonStr Common[1];
ObjectStr *Objects;
UserCommonStr UserCommon[1];
int nDim;
long int i, j;
FILE *burnin;
// Get the number of free parameters, and write header of bayes.dat
nDim = bayesHeader();
#ifdef DEBUG
burnin = fopen( "burnin.dbg.dat", "w" );
#else
burnin = fopen( "burnin.dat", "w" );
#endif
fclose(burnin);
//Common Bayesys parameters
Common->Ndata = 0;
Common->ENSEMBLE = 10; // # objects in ensemble
if ( M.minchi0 > 10 )
Common->ENSEMBLE = (int)ceil(M.minchi0);
Common->Method = -1; // Algorithm method
Common->Rate = M.rate; // Speed of calculation (dimensionless)
Common->Iseed = -4321; // Random seed, -ve is time seed
#if defined(DEBUG) || defined(__CONSTANT_SEED__)
Common->Iseed = 4321; // Reproductible samples
#endif
Objects = (ObjectStr *)malloc((unsigned int) Common->ENSEMBLE * sizeof(ObjectStr));
// Initialize Bayesys for MassInf. WL only with a Grid
if( G.nmsgrid != G.nlens )
{
if( I.stat == 8 || I.n_mult != 0 )
{
extern long int narclet;
extern struct g_pot P[NPOTFILE];
extern struct galaxie arclet[];
extern struct galaxie multi[NFMAX][NIMAX];
extern struct g_frame F;
double gam1, gam2;
struct matrix grad2;
struct point grad;
long int ilens;
double e;
int k;
int Ndata = narclet;
for ( i = 0; i < I.n_mult; i++ )
Ndata += I.mult[i];
int nmult = Ndata - narclet;
Ndata = 2 * Ndata;
double *Data = (double *)malloc((unsigned int)(Ndata * sizeof(double)));
double *Acc = (double *)malloc((unsigned int)(Ndata * sizeof(double)));
double *zbitstmp0 = (double *)calloc(Ndata, sizeof(double));
zbitstmp1 = alloc_square_double(G.nlens - G.nmsgrid + 2 * I.n_mult, Ndata);
ibitstmp = (int *)calloc(Ndata, sizeof(int));
// Contribution from the grid potentials
for( ilens = 0; ilens < G.nlens - G.nmsgrid; ilens++ )
{
int nimage = 0;
for ( i = 0; i < I.n_mult; i++ )
for ( j = 0; j < I.mult[i]; j++ )
{
zbitstmp1[ilens][nimage] = multi[i][j].np_grad[ilens].x * multi[i][j].dr;
zbitstmp1[ilens][nmult + nimage] = multi[i][j].np_grad[ilens].y * multi[i][j].dr;
nimage++;
}
for( i = 0; i < narclet; i++ )
{
gam1 = 0.5 * (arclet[i].np_grad2a[ilens] - arclet[i].np_grad2c[ilens]) / arclet[i].dos;
gam2 = arclet[i].np_grad2b[ilens] / arclet[i].dos;
zbitstmp1[ilens][2 * nmult + i] = 2. * gam1; // e1 defined as (a^2 - b^2) / (a^2 + b^2) and kap <<1
zbitstmp1[ilens][2 * nmult + narclet + i] = 2. * gam2; // g2 (see B&S01 Eq 4.6)
}
}
// Contribution from the fixed potentials
int nimage = 0;
for( ilens = G.no_lens; ilens < G.nplens[0]; ilens++ )
{
nimage = 0;
for ( i = 0; i < I.n_mult; i++ )
for ( j = 0; j < I.mult[i]; j++ )
{
grad = e_grad_pot(&multi[i][j].C, ilens);
zbitstmp0[nimage] += grad.x * multi[i][j].dr;
zbitstmp0[nmult + nimage] += grad.y * multi[i][j].dr;
nimage++;
}
for( i = 0; i < narclet; i++ )
{
grad2 = e_grad2_pot(&arclet[i].C, ilens);
zbitstmp0[2 * nmult + i] += (grad2.a - grad2.c) * arclet[i].dr;
zbitstmp0[2 * nmult + narclet + i] += 2. * grad2.b * arclet[i].dr;
}
}
// Contribution from the potfile, if it is fixed
for( k = 0; k < G.npot; k++ )
if( P[k].isigma == 0 && P[k].ircut == 0 )
for( ilens = G.nplens[k]; ilens < G.nplens[k+1]; ilens++ )
{
nimage = 0;
for ( i = 0; i < I.n_mult; i++ )
for ( j = 0; j < I.mult[i]; j++ )
{
grad = e_grad_pot(&multi[i][j].C, ilens);
zbitstmp0[nimage] += grad.x * multi[i][j].dr;
zbitstmp0[nmult + nimage] += grad.y * multi[i][j].dr;
nimage++;
}
for( i = 0; i < narclet; i++ )
{
grad2 = e_grad2_pot(&arclet[i].C, ilens);
zbitstmp0[2 * nmult + i] += (grad2.a - grad2.c) * arclet[i].dr;
zbitstmp0[2 * nmult + narclet + i] += 2. * grad2.b * arclet[i].dr;
}
}
// Shift source positions to (F.xmin, F.ymin)
// nimage = 0;
// double xmin = 1000.;
// double ymin = 1000.;
// for( i = 0; i < I.n_mult; i++ )
// for( j = 0; j < I.mult[i]; j++ )
// {
// if( multi[i][j].C.x < xmin ) xmin = multi[i][j].C.x;
// if( multi[i][j].C.y < ymin ) ymin = multi[i][j].C.y;
// }
//
// for( i = 0; i < I.n_mult; i++ )
// for( j = 0; j < I.mult[i]; j++ )
// {
// zbitstmp0[nimage] += xmin;
// zbitstmp0[nmult + nimage] += ymin;
// nimage++;
// }
// Indexes for the source positions
nimage = 0;
for ( i = 0; i < I.n_mult; i++ )
for ( j = 0; j < I.mult[i]; j++ )
{
zbitstmp1[G.nlens - G.nmsgrid + i][nimage] = 1.;
zbitstmp1[G.nlens - G.nmsgrid + I.n_mult + i][nmult + nimage] = 1.;
nimage++;
}
// Data
nimage = 0;
for ( i = 0; i < I.n_mult; i++ )
for ( j = 0; j < I.mult[i]; j++ )
{
Data[nimage] = multi[i][j].C.x - zbitstmp0[nimage];
Data[nmult + nimage] = multi[i][j].C.y - zbitstmp0[nmult + nimage];
Acc[nimage] = 1. / multi[i][j].E.a / multi[i][j].mu; // cos(multi[i][j].E.theta);
Acc[nmult + nimage] = 1. / multi[i][j].E.b / multi[i][j].mu; // cos(multi[i][j].E.theta);;
ibitstmp[nimage] = nimage;
ibitstmp[nmult + nimage] = nmult + nimage;
nimage++;
}
for( i = 0; i < narclet; i++ )
{
e = (arclet[i].E.a * arclet[i].E.a - arclet[i].E.b * arclet[i].E.b) / (arclet[i].E.a * arclet[i].E.a + arclet[i].E.b * arclet[i].E.b);
Data[2 * nmult + i] = e * cos(2. * arclet[i].E.theta) - zbitstmp0[2 * nmult + i]; // gamma1
Data[2 * nmult + narclet + i] = e * sin(2. * arclet[i].E.theta) - zbitstmp0[2 * nmult + narclet + i]; // gamma2
Acc[2 * nmult + i] = 1. / sqrt(arclet[i].var1 + I.sig2ell);
Acc[2 * nmult + narclet + i] = 1. / sqrt(arclet[i].var2 + I.sig2ell);
ibitstmp[2 * nmult + i] = 2 * nmult + i;
ibitstmp[2 * nmult + narclet + i] = 2 * nmult + narclet + i;
}
free(zbitstmp0);
Common->Ndata = Ndata;
Common->Data = Data;
Common->Acc = Acc;
// UserBuild uses mock data
for( i = 0; i < Common->ENSEMBLE; i++ )
Objects[i].Mock = (double*)malloc(Ndata * sizeof(double));
}
// Number of Atoms free
Common->MinAtoms = 1; // >= 1
Common->MaxAtoms = 0; // >= MinAtoms, or 0 = infinity(not implemented)
Common->Alpha = -0.02 * (G.nlens - G.nmsgrid) - 2 * I.n_mult - 1; // +ve for Poisson, -ve for geometric
if( nDim < G.nlens )
{
// MassInf parameters
Common->Ndim = 1; // Coordinate in the grid
Common->Valency = 1; // On/off switch for MassInf/Grid optim (Default: off)
Common->MassInf = 1; // Positive prior on the flux
if( I.n_mult > 0 && G.no_lens > 0 )
{
Common->Valency = 3; // Add 2 valencies for the SL source positions X and Y
Common->Method = -3; // Remove lifeStory2 algorithm for conflict of atom valencies
Common->MassInf = 2; // Positive/Negative prior on the flux
}
Common->ProbON = 0.7;
Common->FluxUnit0 = -10.; // 1 for pmass, 10 for b0
nDim = G.nlens - G.nmsgrid; // To initialize statistics arrays err, tmpCube and avg
}
else
{
// Normal optimization but with Natoms (see UserBuild)
Common->Ndim = nDim; // Number of parameters of the optimized clumps
Common->Valency = 0; // On/off switch for MassInf/Grid optim (Default: off)
}
}
else
{
// Number of Atoms = 1
Common->MinAtoms = 1; // >= 1
Common->MaxAtoms = 1; // >= MinAtoms, or 0 = infinity(not implemented)
Common->Alpha = -1.; // +ve for Poisson, -ve for geometric
Common->Ndim = nDim; // Number of parameters of the optimized clumps
Common->Valency = 0; // On/off switch for MassInf/Grid optim (Default: off)
}
// Initialize some statistics
Common->UserCommon = (void*)UserCommon;
UserCommon->Nsample = 0;
UserCommon->atoms = 0.0;
UserCommon->Nchi2 = 0;
UserCommon->sum = 0.;
UserCommon->Ndim = nDim;
tmpCube = (double *)malloc((unsigned int) nDim * sizeof(double));
UserCommon->err = (double *)malloc((unsigned int) nDim * sizeof(double));
UserCommon->avg = (double *)malloc((unsigned int) nDim * sizeof(double));
for ( i = 0; i < nDim; i++ )
{
UserCommon->err[i] = 0.;
UserCommon->avg[i] = 0.;
}
// Handle CTRL-C to interrupt the optimisation but not lenstool
signal(SIGINT, signalReset);
optInterrupt = 0;
// Initialize mutex for nchi2 counts
init_mutex();
//Run bayesys
int code = BayeSys3(Common, Objects);
printf("\nBayeSys3 return code %d\n", code);
// Destroy mutex
destroy_mutex();
// Reset the SIGINT signal to its default behavior
signal(SIGINT, SIG_DFL);
fprintf(stdout, "\n");
/*Set the lens parameters that give the best model
* and the Gaussian prior at 3sigma limits*/
o_set_lens_bayes(-4, 3, 3.);
NPRINTF( stderr, "log(Evidence) = %lf\n", Common->Evidence );
NPRINTF( stderr, "Information = -Entropy = %lf\n", Common->Information );
NPRINTF( stderr, "Calls to chi2() function = %ld\n", UserCommon->Nchi2 );
/*Free the structures*/
if( I.stat == 8 && G.nlens != G.nmsgrid )
{
free_square_double(zbitstmp1, G.nlens-G.nmsgrid);
free( ibitstmp );
free( Common->Data );
free( Common->Acc );
free( Objects->Mock );
}
free( Objects );
free( UserCommon->err );
free( UserCommon->avg );
free( tmpCube );
return( Common->Evidence );
}
/* Write the header of the bayes.dat file.
* Return the number of free parameters/dimensions.
*/
int bayesHeader()
{
extern struct g_mode M;
extern struct g_grille G;
extern struct g_image I;
extern struct g_pot P[NPOTFILE];
extern struct pot lens[];
extern struct z_lim zlim[];
extern struct z_lim zalim;
extern struct galaxie multi[NFMAX][NIMAX];
extern int block[][NPAMAX];
extern int cblock[NPAMAX];
extern int vfblock[NPAMAX];
extern struct sigposStr sigposAs;
int nDim = 0; //# of parameters
int ipx; //index of the current parameter in the Param
int i; //index of the clump in the lens[] global variable
int k; //index of the z_m_limit images to optimise
int nimages;
char limages[ZMBOUND][IDSIZE];
FILE *bayes;
char name[60];
// Clean the results files
#ifdef DEBUG
bayes = fopen( "bayes.dbg.dat" , "w" );
#else
bayes = fopen( "bayes.dat" , "w" );
#endif
fprintf( bayes, "#Nsample\n");
//if ( sigposAs.bk != 0 || I.dsigell != -1 ||
// (I.stat == 6 && I.statmode == 1) )
fprintf( bayes, "#ln(Lhood)\n");
//else
// fprintf( bayes, "#Chi2\n");
// fprintf( bayes, "#Evidence\n");
// Number of lens parameters in the atom
for ( i = 0; i < G.no_lens; i++ )
{
int nDim_old = nDim;
for ( ipx = CX; ipx <= PMASS; ipx++ )
if ( block[i][ipx] != 0 )
{
nDim++;
fprintf( bayes, "#%s : %s\n", lens[i].n, getParName(ipx, name, lens[i].type) );
}
// check against optimized potential without free parameters
if( nDim_old == nDim )
{
fprintf(stderr, "ERROR: Individually optimized potential %s without free parameter.\n", lens[i].n);
exit(1);
}
}
// multiscale grid clumps
for ( i = G.nmsgrid; i < G.nlens; i++ )
{
fprintf( bayes, "#%s : %s\n", lens[i].n, getParName(B0, name, lens[i].type) );
if( block[i][B0] != 0 )
nDim++;
}
// source positions of multiple images with grid optimization
if( G.nmsgrid != G.nlens && nDim < G.nlens - G.nmsgrid )
{
for ( i = 0; i < I.n_mult; i++ )
fprintf( bayes, "#X src %s\n", multi[i][0].n );
for ( i = 0; i < I.n_mult; i++ )
fprintf( bayes, "#Y src %s\n", multi[i][0].n );
}
// source positions for image reconstruction
if( M.iclean == 2 )
{
extern int sblock[NFMAX][NPAMAX];
extern struct galaxie source[NFMAX];
extern struct g_source S;
for ( i = 0; i < S.ns; i++ )
for ( ipx = SCX; ipx <= SFLUX; ipx++ )
if ( sblock[i][ipx] != 0 )
{
nDim++;
fprintf( bayes, "#src %s : %s\n", source[i].n, getParName(ipx, name, 0));
}
}
// Number of cosmological parameters in the atom
for ( ipx = OMEGAM; ipx <= WA; ipx++ )
if ( cblock[ipx] != 0 )
{
nDim++;
fprintf( bayes, "#%s\n", getParName(ipx, name, 0) );
}
// Number of redshifts to optimise
for ( k = 0; k < I.nzlim; k++ )
if ( zlim[k].bk != 0 )
{
nimages = splitzmlimit( zlim[k].n, limages );
i = 0;
while ( indexCmp( multi[i][0].n, limages[0] ) ) i++;
fprintf( bayes, "#Redshift of %s\n", multi[i][0].n );
nDim++;
}
// redshift of the arclets
if ( zalim.bk != 0 )
{
fprintf( bayes, "#Redshift of arclets\n");
nDim++;
}
// Velocity field parameters to optimise
for ( ipx = VFCX; ipx <= VFSIGMA; ipx++ )
if ( vfblock[ipx] != 0 )
{
nDim++;
fprintf( bayes, "#%s\n", getParName(ipx, name, 0) );
}
// Potfile parameters to optimise
for ( i = 0; i < G.npot; i++ )
if ( P[i].ftype != 0 )
{
if ( P[i].ircut != 0 )
{
nDim++;
fprintf( bayes, "#Pot%d rcut (arcsec)\n", i);
}
if ( P[i].isigma != 0 )
{
nDim++;
fprintf( bayes, "#Pot%d sigma (km/s)\n", i);
}
if ( P[i].islope != 0 )
{
nDim++;
if ( P[i].ftype == 62 )
fprintf( bayes, "#Pot%d m200slope\n", i);
else
fprintf( bayes, "#Pot%d rcut_slope\n", i);
}
if ( P[i].ivdslope != 0 )
{
nDim++;
if ( P[i].ftype == 62 )
fprintf( bayes, "#Pot%d c200slope\n", i);
else
fprintf( bayes, "#Pot%d sigma_slope\n", i);
}
if ( P[i].ivdscat != 0 )
{
nDim++;
fprintf( bayes, "#Pot%d vdscatter\n", i);
}
if ( P[i].ircutscat != 0 )
{
nDim++;
fprintf( bayes, "#Pot%d rcutscatter\n", i);
}
if ( P[i].ia != 0 )
{
nDim++;
if ( P[i].ftype == 62 )
fprintf( bayes, "#Pot%d m200\n", i);
else
fprintf( bayes, "#Pot%d a\n", i);
}
if ( P[i].ib != 0 )
{
nDim++;
if ( P[i].ftype == 62 )
fprintf( bayes, "#Pot%d c200\n", i);
else
fprintf( bayes, "#Pot%d b\n", i);
}
}
// The noise
if ( sigposAs.bk != 0 )
{
for ( i = 0; i < I.n_mult; i++ )
for ( k = 0; k < I.mult[i]; k++)
{
fprintf( bayes, "#SigposArsec %s (arcsec)\n", multi[i][k].n);
nDim++;
}
}
if ( I.dsigell != -1. )
{
nDim++;
fprintf( bayes, "#Sigell (arcsec)\n");
}
//add Chi2 as last column
fprintf( bayes, "#Chi2\n");
fclose(bayes);
return(nDim);
}
static void signalReset(int param)
{
signal(SIGINT, SIG_DFL);
optInterrupt = 1;
fprintf( stderr, "INFO: Optimisation interrupted by CTRL-C\r");
}

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