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Commit 3492911e authored by Moises Fernandez's avatar Moises Fernandez
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Pass some parameters to FIT instead of read from options to do it more general... 

Pass some parameters to FIT instead of read from options to do it more general and use it in RUBIX. Delete unnecessary params in Samples Save
parent 5b8c2f28
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with 48 additions and 67 deletions
CUDA/xfibres_gpu.cu
+ 48
− 67
View file @ 3492911e
......@@ -89,7 +89,7 @@ void xfibres_gpu( //INPUT
fit(datam_vec,bvecs_vec,bvals_vec,datam_host,bvecs_host,bvals_host,datam_gpu,bvecs_gpu,bvals_gpu,ndirections,gpu_log,params_gpu,vox_repeat,nrepeat);
if(opts.rician.value()){
calculate_tau(datam_gpu,params_gpu,bvecs_gpu,bvals_gpu,vox_repeat,nrepeat, ndirections, gpu_log, tau_host);
calculate_tau(datam_gpu,params_gpu,bvecs_gpu,bvals_gpu,vox_repeat,nrepeat,ndirections,nfib,opts.modelnum.value(),opts.f0.value(),opts.nonlin.value(),gpu_log,tau_host);
}
bvecs_gpu.clear(); //free bvecs_gpu
......@@ -116,15 +116,14 @@ void xfibres_gpu( //INPUT
runmcmc_burnin(datam_gpu, bvals_gpu, alpha_gpu, beta_gpu, ndirections, rand(), gpu_log, fibres_gpu,multifibres_gpu, signals_gpu, isosignals_gpu);
thrust::device_vector<int> multirecords_gpu;
thrust::device_vector<float> rf0_gpu, rtau_gpu, rs0_gpu, rd_gpu, rdstd_gpu, rth_gpu, rph_gpu, rf_gpu, rlikelihood_energy_gpu;
thrust::device_vector<float> rf0_gpu,rtau_gpu,rs0_gpu,rd_gpu,rdstd_gpu,rth_gpu,rph_gpu,rf_gpu;
prepare_data_gpu_MCMC_record(nvox, multirecords_gpu, rf0_gpu, rtau_gpu, rs0_gpu, rd_gpu, rdstd_gpu, rth_gpu, rph_gpu, rf_gpu, rlikelihood_energy_gpu);
prepare_data_gpu_MCMC_record(nvox,rf0_gpu,rtau_gpu,rs0_gpu,rd_gpu,rdstd_gpu,rth_gpu,rph_gpu,rf_gpu);
runmcmc_record(datam_gpu, bvals_gpu, alpha_gpu,beta_gpu, fibres_gpu, multifibres_gpu, signals_gpu, isosignals_gpu, ndirections, rand(), gpu_log, multirecords_gpu, rf0_gpu, rtau_gpu, rs0_gpu, rd_gpu, rdstd_gpu, rth_gpu, rph_gpu, rf_gpu, rlikelihood_energy_gpu);
runmcmc_record(datam_gpu, bvals_gpu, alpha_gpu,beta_gpu, fibres_gpu, multifibres_gpu, signals_gpu, isosignals_gpu, ndirections, rand(), gpu_log, rf0_gpu, rtau_gpu, rs0_gpu, rd_gpu, rdstd_gpu, rth_gpu, rph_gpu, rf_gpu);
/////// FINISH ALL VOXELS ///////
record_finish_voxels(multirecords_gpu, rf0_gpu, rtau_gpu, rs0_gpu, rd_gpu, rdstd_gpu, rth_gpu, rph_gpu, rf_gpu, rlikelihood_energy_gpu, nvox, ndirections, idSubpart);
record_finish_voxels(rf0_gpu,rtau_gpu,rs0_gpu,rd_gpu,rdstd_gpu,rth_gpu,rph_gpu,rf_gpu,nvox,idSubpart);
}else{
/////// FINISH EMPTY SLICE ///////
Samples samples(nvox,ndirections);
......@@ -191,7 +190,7 @@ void fit( //INPUT
if(opts.modelnum.value()==1){
if(opts.nonlin.value()){
fit_PVM_single(datam_vec,bvecs_vec,bvals_vec,datam_gpu,bvecs_gpu,bvals_gpu,ndirections,opts.f0.value(),output_file,params_gpu);
fit_PVM_single(datam_vec,bvecs_vec,bvals_vec,datam_gpu,bvecs_gpu,bvals_gpu,ndirections,nfib,opts.f0.value(),output_file,params_gpu);
if (opts.f0.value()){
float md,mf,f0;
......@@ -224,14 +223,14 @@ void fit( //INPUT
thrust::device_vector<double> bvals_repeat_gpu=bvals_repeat_host;
thrust::device_vector<double> params_repeat_gpu=params_repeat_host;
fit_PVM_single(datam_repeat_vec,bvecs_repeat_vec,bvals_repeat_vec,datam_repeat_gpu,bvecs_repeat_gpu,bvals_repeat_gpu,ndirections,false,output_file,params_repeat_gpu);
fit_PVM_single(datam_repeat_vec,bvecs_repeat_vec,bvals_repeat_vec,datam_repeat_gpu,bvecs_repeat_gpu,bvals_repeat_gpu,ndirections,nfib,false,output_file,params_repeat_gpu);
thrust::copy(params_repeat_gpu.begin(), params_repeat_gpu.end(), params_repeat_host.begin());
//mix all the parameteres: repeated and not repeated
mix_params(params_repeat_host,vox_repeat, nrepeat, nvox, params_gpu);
}
}
}else{
fit_PVM_single_c(datam_vec,bvecs_vec,bvals_vec,datam_gpu,bvecs_gpu,bvals_gpu,ndirections,opts.f0.value(),output_file,params_gpu);
fit_PVM_single_c(datam_vec,bvecs_vec,bvals_vec,datam_gpu,bvecs_gpu,bvals_gpu,ndirections,nfib,opts.f0.value(),output_file,params_gpu);
if (opts.f0.value()){
float md,mf,f0;
......@@ -264,7 +263,7 @@ void fit( //INPUT
thrust::device_vector<double> bvals_repeat_gpu=bvals_repeat_host;
thrust::device_vector<double> params_repeat_gpu=params_repeat_host;
fit_PVM_single_c(datam_repeat_vec,bvecs_repeat_vec,bvals_repeat_vec,datam_repeat_gpu,bvecs_repeat_gpu,bvals_repeat_gpu,ndirections,false,output_file,params_repeat_gpu);
fit_PVM_single_c(datam_repeat_vec,bvecs_repeat_vec,bvals_repeat_vec,datam_repeat_gpu,bvecs_repeat_gpu,bvals_repeat_gpu,ndirections,nfib,false,output_file,params_repeat_gpu);
thrust::copy(params_repeat_gpu.begin(), params_repeat_gpu.end(), params_repeat_host.begin());
//mix all the parameteres: repeated and not repeated
......@@ -274,9 +273,9 @@ void fit( //INPUT
}
}else{
//model 2 : non-mono-exponential
fit_PVM_single_c(datam_vec,bvecs_vec,bvals_vec,datam_gpu,bvecs_gpu,bvals_gpu,ndirections,opts.f0.value(),output_file,params_gpu);
fit_PVM_single_c(datam_vec,bvecs_vec,bvals_vec,datam_gpu,bvecs_gpu,bvals_gpu,ndirections,nfib,opts.f0.value(),output_file,params_gpu);
fit_PVM_multi(datam_gpu,bvecs_gpu,bvals_gpu,nvox,ndirections,opts.f0.value(),output_file,params_gpu);
fit_PVM_multi(datam_gpu,bvecs_gpu,bvals_gpu,nvox,ndirections,nfib,opts.f0.value(),output_file,params_gpu);
if (opts.f0.value()){
float md,mf,f0;
......@@ -309,9 +308,9 @@ void fit( //INPUT
thrust::device_vector<double> bvals_repeat_gpu=bvals_repeat_host;
thrust::device_vector<double> params_repeat_gpu=params_repeat_host;
fit_PVM_single_c(datam_repeat_vec,bvecs_repeat_vec,bvals_repeat_vec,datam_repeat_gpu,bvecs_repeat_gpu,bvals_repeat_gpu,ndirections,false,output_file,params_repeat_gpu);
fit_PVM_single_c(datam_repeat_vec,bvecs_repeat_vec,bvals_repeat_vec,datam_repeat_gpu,bvecs_repeat_gpu,bvals_repeat_gpu,ndirections,nfib,false,output_file,params_repeat_gpu);
fit_PVM_multi(datam_repeat_gpu,bvecs_repeat_gpu,bvals_repeat_gpu,nrepeat,ndirections,false,output_file,params_repeat_gpu);
fit_PVM_multi(datam_repeat_gpu,bvecs_repeat_gpu,bvals_repeat_gpu,nrepeat,ndirections,nfib,false,output_file,params_repeat_gpu);
thrust::copy(params_repeat_gpu.begin(), params_repeat_gpu.end(), params_repeat_host.begin());
//mix all the parameteres: repeated and not repeated
......@@ -518,7 +517,6 @@ void prepare_data_gpu_MCMC( //INPUT
void prepare_data_gpu_MCMC_record( //INPUT
int nvox,
//OUTPUT
thrust::device_vector<int>& multirecords_gpu,
thrust::device_vector<float>& rf0_gpu,
thrust::device_vector<float>& rtau_gpu,
thrust::device_vector<float>& rs0_gpu,
......@@ -526,28 +524,24 @@ void prepare_data_gpu_MCMC_record( //INPUT
thrust::device_vector<float>& rdstd_gpu,
thrust::device_vector<float>& rth_gpu,
thrust::device_vector<float>& rph_gpu,
thrust::device_vector<float>& rf_gpu,
thrust::device_vector<float>& rlikelihood_energy_gpu)
thrust::device_vector<float>& rf_gpu)
{
xfibresOptions& opts = xfibresOptions::getInstance();
int nfib = opts.nfibres.value();
int nrecords = (opts.njumps.value()/opts.sampleevery.value());
int nsamples = (opts.njumps.value()/opts.sampleevery.value());
multirecords_gpu.resize(nvox*nrecords);
if(opts.f0.value()) rf0_gpu.resize(nvox*nrecords);
if(opts.rician.value()) rtau_gpu.resize(nvox*nrecords);
rs0_gpu.resize(nvox*nrecords);
rd_gpu.resize(nvox*nrecords);
if(opts.modelnum.value()==2) rdstd_gpu.resize(nvox*nrecords);
rth_gpu.resize(nvox*nrecords*nfib);
rph_gpu.resize(nvox*nrecords*nfib);
rf_gpu.resize(nvox*nrecords*nfib);
rlikelihood_energy_gpu.resize(nvox*nrecords);
if(opts.f0.value()) rf0_gpu.resize(nvox*nsamples);
if(opts.rician.value()) rtau_gpu.resize(nvox*nsamples);
rs0_gpu.resize(nvox*nsamples);
rd_gpu.resize(nvox*nsamples);
if(opts.modelnum.value()==2) rdstd_gpu.resize(nvox*nsamples);
rth_gpu.resize(nvox*nsamples*nfib);
rph_gpu.resize(nvox*nsamples*nfib);
rf_gpu.resize(nvox*nsamples*nfib);
}
void record_finish_voxels( //INPUT
thrust::device_vector<int>& multirecords_gpu,
thrust::device_vector<float>& rf0_gpu,
thrust::device_vector<float>& rtau_gpu,
thrust::device_vector<float>& rs0_gpu,
......@@ -556,31 +550,25 @@ void record_finish_voxels( //INPUT
thrust::device_vector<float>& rth_gpu,
thrust::device_vector<float>& rph_gpu,
thrust::device_vector<float>& rf_gpu,
thrust::device_vector<float>& rlikelihood_energy_gpu,
int nvox,
int ndirections,
int idpart)
{
xfibresOptions& opts = xfibresOptions::getInstance();
int nfib = opts.nfibres.value();
int nrecords = (opts.njumps.value()/opts.sampleevery.value());
thrust::host_vector<int> multirecords_host;
thrust::host_vector<float> rf0_host,rtau_host,rs0_host,rd_host,rdstd_host,rth_host,rph_host,rf_host,rlikelihood_energy_host;
multirecords_host.resize(nvox*nrecords);
rf0_host.resize(nvox*nrecords);
rtau_host.resize(nvox*nrecords);
rs0_host.resize(nvox*nrecords);
rd_host.resize(nvox*nrecords);
rdstd_host.resize(nvox*nrecords);
rth_host.resize(nvox*nfib*nrecords);
rph_host.resize(nvox*nfib*nrecords);
rf_host.resize(nvox*nfib*nrecords);
rlikelihood_energy_host.resize(nvox*nrecords);
thrust::copy(multirecords_gpu.begin(), multirecords_gpu.end(), multirecords_host.begin());
int nsamples = (opts.njumps.value()/opts.sampleevery.value());
thrust::host_vector<float> rf0_host,rtau_host,rs0_host,rd_host,rdstd_host,rth_host,rph_host,rf_host;
rf0_host.resize(nvox*nsamples);
rtau_host.resize(nvox*nsamples);
rs0_host.resize(nvox*nsamples);
rd_host.resize(nvox*nsamples);
rdstd_host.resize(nvox*nsamples);
rth_host.resize(nvox*nfib*nsamples);
rph_host.resize(nvox*nfib*nsamples);
rf_host.resize(nvox*nfib*nsamples);
if(opts.f0.value()) thrust::copy(rf0_gpu.begin(), rf0_gpu.end(), rf0_host.begin());
if(opts.rician.value()) thrust::copy(rtau_gpu.begin(), rtau_gpu.end(), rtau_host.begin());
thrust::copy(rs0_gpu.begin(), rs0_gpu.end(), rs0_host.begin());
......@@ -589,48 +577,41 @@ void record_finish_voxels( //INPUT
thrust::copy(rth_gpu.begin(), rth_gpu.end(), rth_host.begin());
thrust::copy(rph_gpu.begin(), rph_gpu.end(), rph_host.begin());
thrust::copy(rf_gpu.begin(), rf_gpu.end(), rf_host.begin());
thrust::copy(rlikelihood_energy_gpu.begin(), rlikelihood_energy_gpu.end(), rlikelihood_energy_host.begin());
Samples samples(nvox,ndirections);
Samples samples(nvox,nsamples);
float ard,arf0,artau,ardstd,ars0,arlikelihood_energy;
float ard,arf0,artau,ardstd,ars0;
float *arth = new float[nfib];
float *arph = new float[nfib];
float *arf = new float[nfib];
int samp;
for(int vox=0;vox<nvox;vox++){
for(int rec=0;rec<nrecords;rec++){
ard=rd_host[(vox*nrecords)+rec];
for(int rec=0;rec<nsamples;rec++){
ard=rd_host[(vox*nsamples)+rec];
if(opts.f0.value()){
arf0=rf0_host[(vox*nrecords)+rec];
arf0=rf0_host[(vox*nsamples)+rec];
}
if(opts.rician.value()){
artau=rtau_host[(vox*nrecords)+rec];
artau=rtau_host[(vox*nsamples)+rec];
}
if(opts.modelnum.value()==2){
ardstd=rdstd_host[(vox*nrecords)+rec];
ardstd=rdstd_host[(vox*nsamples)+rec];
}
ars0=rs0_host[(vox*nrecords)+rec];
arlikelihood_energy=rlikelihood_energy_host[(vox*nrecords)+rec];
ars0=rs0_host[(vox*nsamples)+rec];
for(int j=0;j<nfib;j++){
arth[j]=rth_host[(vox*nfib*nrecords)+(j*nrecords)+rec];
arph[j]=rph_host[(vox*nfib*nrecords)+(j*nrecords)+rec];
arf[j]=rf_host[(vox*nfib*nrecords)+(j*nrecords)+rec];
arth[j]=rth_host[(vox*nfib*nsamples)+(j*nsamples)+rec];
arph[j]=rph_host[(vox*nfib*nsamples)+(j*nsamples)+rec];
arf[j]=rf_host[(vox*nfib*nsamples)+(j*nsamples)+rec];
}
samp=multirecords_host[(vox*nrecords)+rec];
samples.record(ard,arf0,artau,ardstd,ars0,arlikelihood_energy,arth,arph,arf,vox+1,samp);
samples.record(ard,arf0,artau,ardstd,ars0,arth,arph,arf,vox+1,rec+1);
}
samples.finish_voxel(vox+1);
}
samples.save(idpart);
}
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