void GridPrintingBase::update(){
if( getStep()==0 || getStride()==0 ) return ;
OFile ofile; ofile.link(*this);
ofile.setBackupString("analysis");
ofile.open( filename ); printGrid( ofile ); ofile.close();
}
void CoeffsBase::writeIterationCounterAndTimeToFile(OFile& ofile) const {
if(time_md>=0.0) {
ofile.fmtField("%f");
ofile.addConstantField(field_time_).printField(field_time_,time_md);
ofile.fmtField();
}
ofile.addConstantField(field_iteration_).printField(field_iteration_,(int) iteration_opt);
}
void CoeffsBase::writeCoeffsInfoToFile(OFile& ofile) const {
ofile.addConstantField(field_type_).printField(field_type_,getTypeStr());
ofile.addConstantField(field_ndimensions_).printField(field_ndimensions_,(int) numberOfDimensions());
ofile.addConstantField(field_ncoeffs_total_).printField(field_ncoeffs_total_,(int) numberOfCoeffs());
for(unsigned int k=0; k<numberOfDimensions(); k++) {
ofile.addConstantField(field_shape_prefix_+getDimensionLabel(k));
ofile.printField(field_shape_prefix_+getDimensionLabel(k),(int) shapeOfIndices(k));
}
}
void GridPrintingBase::runFinalJobs() {
if( !output_for_all_replicas ) {
bool found=false; unsigned myrep=plumed.multi_sim_comm.Get_rank();
for(unsigned i=0; i<preps.size(); ++i) {
if( myrep==preps[i] ) { found=true; break; }
}
if( !found ) return;
}
if( getStride()>0 ) return;
OFile ofile; ofile.link(*this);
ofile.open( filename ); printGrid( ofile );
}
void ReferenceAtoms::printAtoms( OFile& ofile, const double& lunits ) const {
plumed_assert( indices.size()==reference_atoms.size() && align.size()==reference_atoms.size() && displace.size()==reference_atoms.size() );
for(unsigned i=0;i<reference_atoms.size();++i){
ofile.printf("ATOM %4d X RES %4u %8.3f%8.3f%8.3f%6.2f%6.2f\n",
indices[i].serial(), i,
lunits*reference_atoms[i][0], lunits*reference_atoms[i][1], lunits*reference_atoms[i][2],
align[i], displace[i] );
}
}
void PointWiseMapping::print( const std::string& method, const double & time, OFile& afile, const std::string& fmt ){
std::string descr2, descr="DESCRIPTION: results from %s analysis performed at time " + fmt +"\n";
afile.printf(descr.c_str(), method.c_str(), time );
if(fmt.find("-")!=std::string::npos){
descr="REMARK WEIGHT=" + fmt + " %s=" + fmt + " "; descr2="%s=" + fmt;
} else {
// This ensures numbers are left justified (i.e. next to the equals sign
std::size_t psign=fmt.find("%");
plumed_assert( psign!=std::string::npos );
descr="REMARK WEIGHT=%-" + fmt.substr(psign+1) + " %s=%-" + fmt.substr(psign+1) + " ";
descr2="%s=%-" + fmt.substr(psign+1);
}
for(unsigned i=0;i<frames.size();++i){
afile.printf(descr.c_str(), frames[i]->getWeight(), property[0].c_str(), low_dim[i][0] );
for(unsigned j=1;j<property.size();++j) afile.printf(descr2.c_str(), property[j].c_str(), low_dim[i][j]);
afile.printf("\n");
frames[i]->print( afile, fmt );
}
}
void MetaD::writeGaussian(const Gaussian& hill, OFile&file){
unsigned ncv=getNumberOfArguments();
file.printField("time",getTimeStep()*getStep());
for(unsigned i=0;i<ncv;++i){
file.printField(getPntrToArgument(i),hill.center[i]);
}
if(hill.multivariate){
hillsOfile_.printField("multivariate","true");
Matrix<double> mymatrix(ncv,ncv);
unsigned k=0;
for(unsigned i=0;i<ncv;i++){
for(unsigned j=i;j<ncv;j++){
mymatrix(i,j)=mymatrix(j,i)=hill.sigma[k]; // recompose the full inverse matrix
k++;
}
}
// invert it
Matrix<double> invmatrix(ncv,ncv);
Invert(mymatrix,invmatrix);
// enforce symmetry
for(unsigned i=0;i<ncv;i++){
for(unsigned j=i;j<ncv;j++){
invmatrix(i,j)=invmatrix(j,i);
}
}
// do cholesky so to have a "sigma like" number
Matrix<double> lower(ncv,ncv);
cholesky(invmatrix,lower); // now this , in band form , is similar to the sigmas
// loop in band form
for (unsigned i=0;i<ncv;i++){
for (unsigned j=0;j<ncv-i;j++){
file.printField("sigma_"+getPntrToArgument(j+i)->getName()+"_"+getPntrToArgument(j)->getName(),lower(j+i,j));
}
}
} else {
hillsOfile_.printField("multivariate","false");
for(unsigned i=0;i<ncv;++i)
file.printField("sigma_"+getPntrToArgument(i)->getName(),hill.sigma[i]);
}
double height=hill.height;
if(welltemp_){height*=biasf_/(biasf_-1.0);}
file.printField("height",height).printField("biasf",biasf_);
if(mw_n_>1) file.printField("clock",int(time(0)));
file.printField();
}
void MaxEnt::WriteLagrangians(vector<double> &lagmult,OFile &file) {
if(printFirstStep) {
unsigned ncv=getNumberOfArguments();
file.printField("time",getTimeStep()*getStep());
for(unsigned i=0; i<ncv; ++i)
file.printField(getPntrToArgument(i)->getName()+"_coupling",lagmult[i]);
file.printField();
} else {
if(!isFirstStep) {
unsigned ncv=getNumberOfArguments();
file.printField("time",getTimeStep()*getStep());
for(unsigned i=0; i<ncv; ++i)
file.printField(getPntrToArgument(i)->getName()+"_coupling",lagmult[i]);
file.printField();
}
}
}
FuncSumHills::FuncSumHills(const ActionOptions&ao):
Action(ao),
Function(ao),
initstride(-1),
iscltool(false),
integratehills(false),
integratehisto(false),
parallelread(false),
negativebias(false),
nohistory(false),
beta(-1.),
fmt("%14.9f")
{
// format
parse("FMT",fmt);
log<<" Output format is "<<fmt<<"\n";
// here read
// Grid Stuff
vector<std::string> gmin;
parseVector("GRID_MIN",gmin);
if(gmin.size()!=getNumberOfArguments() && gmin.size()!=0) error("not enough values for GRID_MIN");
plumed_massert(gmin.size()==getNumberOfArguments() || gmin.size()==0,"need GRID_MIN argument for this") ;
vector<std::string> gmax;
parseVector("GRID_MAX",gmax);
if(gmax.size()!=getNumberOfArguments() && gmax.size()!=0) error("not enough values for GRID_MAX");
plumed_massert(gmax.size()==getNumberOfArguments() || gmax.size()==0,"need GRID_MAX argument for this") ;
vector<unsigned> gbin;
parseVector("GRID_BIN",gbin);
plumed_massert(gbin.size()==getNumberOfArguments() || gbin.size()==0,"need GRID_BIN argument for this");
if(gbin.size()!=getNumberOfArguments() && gbin.size()!=0) error("not enough values for GRID_BIN");
//plumed_assert(getNumberOfArguments()==gbin.size());
// hills file:
parseVector("HILLSFILES",hillsFiles);
if(hillsFiles.size()==0){
integratehills=false; // default behaviour
}else{
integratehills=true;
for(unsigned i=0;i<hillsFiles.size();i++) log<<" hillsfile : "<<hillsFiles[i]<<"\n";
}
// histo file:
parseVector("HISTOFILES",histoFiles);
if(histoFiles.size()==0){
integratehisto=false;
}else{
integratehisto=true;
for(unsigned i=0;i<histoFiles.size();i++) log<<" histofile : "<<histoFiles[i]<<"\n";
}
vector<double> histoSigma;
if(integratehisto){
parseVector("HISTOSIGMA",histoSigma);
plumed_massert(histoSigma.size()==getNumberOfArguments()," The number of sigmas must be the same of the number of arguments ");
for(unsigned i=0;i<histoSigma.size();i++) log<<" histosigma : "<<histoSigma[i]<<"\n";
}
// add some automatic hills width: not in case stride is defined
// since when you start from zero the automatic size will be zero!
if(gmin.size()==0 || gmax.size()==0){
log<<" \n";
log<<" No boundaries defined: need to do a prescreening of hills \n";
std::vector<Value*> tmpvalues;
for(unsigned i=0;i<getNumberOfArguments();i++)tmpvalues.push_back( getPntrToArgument(i) );
if(integratehills) {
FilesHandler *hillsHandler;
hillsHandler=new FilesHandler(hillsFiles,parallelread,*this, log);
vector<double> vmin,vmax;
vector<unsigned> vbin;
hillsHandler->getMinMaxBin(tmpvalues,comm,vmin,vmax,vbin);
log<<" found boundaries from hillsfile: \n";
gmin.resize(vmin.size());
gmax.resize(vmax.size());
if(gbin.size()==0){
gbin=vbin;
}else{
log<<" found nbins in input, this overrides the automatic choice \n";
}
for(unsigned i=0;i<getNumberOfArguments();i++){
Tools::convert(vmin[i],gmin[i]);
Tools::convert(vmax[i],gmax[i]);
log<<" variable "<< getPntrToArgument(i)->getName()<<" min: "<<gmin[i]<<" max: "<<gmax[i]<<" nbin: "<<gbin[i]<<"\n";
}
}
// if at this stage bins are not there then do it with histo
if(gmin.size()==0){
FilesHandler *histoHandler;
histoHandler=new FilesHandler(histoFiles,parallelread,*this, log);
vector<double> vmin,vmax;
vector<unsigned> vbin;
histoHandler->getMinMaxBin(tmpvalues,comm,vmin,vmax,vbin,histoSigma);
log<<" found boundaries from histofile: \n";
gmin.resize(vmin.size());
gmax.resize(vmax.size());
if(gbin.size()==0){
gbin=vbin;
}else{
log<<" found nbins in input, this overrides the automatic choice \n";
}
for(unsigned i=0;i<getNumberOfArguments();i++){
Tools::convert(vmin[i],gmin[i]);
Tools::convert(vmax[i],gmax[i]);
log<<" variable "<< getPntrToArgument(i)->getName()<<" min: "<<gmin[i]<<" max: "<<gmax[i]<<" nbin: "<<gbin[i]<<"\n";
}
}
log<<" done!\n";
log<<" \n";
}
// needs a projection?
proj.clear();
parseVector("PROJ",proj);
plumed_massert(proj.size()<getNumberOfArguments()," The number of projection must be less than the full list of arguments ");
if( proj.size() != 0 || integratehisto==true ) {
parse("KT",beta);
for(unsigned i=0;i<proj.size();i++) log<<" projection "<<i<<" : "<<proj[i]<<"\n";
plumed_massert(beta>0.,"if you make a projection or a histogram correction then you need KT flag!");
beta=1./beta;
log<<" beta is "<<beta<<"\n";
}
// is a cltool: then you start and then die
parseFlag("ISCLTOOL",iscltool);
//
parseFlag("NEGBIAS",negativebias);
//
parseFlag("PARALLELREAD",parallelread);
// stride
parse("INITSTRIDE",initstride);
// output suffix or names
if(initstride<0){ log<<" Doing only one integration: no stride \n";
outhills="fes.dat";outhisto="correction.dat";}
else{outhills="fes_";outhisto="correction_";
log<<" Doing integration slices every "<<initstride<<" kernels\n";
parseFlag("NOHISTORY",nohistory);
if(nohistory)log<<" nohistory: each stride block has no memory of the previous block\n";
}
//what might it be this?
// here start
// want something right now?? do it and return
// your argument is a set of cvs
// then you need: a hills / a colvar-like file (to do a histogram)
// create a bias representation for this
if(iscltool){
std::vector<Value*> tmpvalues;
for(unsigned i=0;i<getNumberOfArguments();i++){
// allocate a new value from the old one: no deriv here
tmpvalues.push_back( getPntrToArgument(i) );
}
// check if the files exists
if(integratehills){
checkFilesAreExisting(hillsFiles);
biasrep=new BiasRepresentation(tmpvalues,comm, gmin, gmax, gbin);
if(negativebias){
biasrep->setRescaledToBias(true);
log<<" required the -bias instead of the free energy \n";
if(initstride<0){outhills="negativebias.dat";}
else{outhills="negativebias_";}
}
}
parse("OUTHILLS",outhills);
parse("OUTHISTO",outhisto);
if(integratehills)log<<" output file for fes/bias is : "<<outhills<<"\n";
if(integratehisto)log<<" output file for correction is : "<<outhisto<<"\n";
checkRead();
log<<"\n";
log<<" Now calculating...\n";
log<<"\n";
if(integratehisto){
checkFilesAreExisting(histoFiles);
historep=new BiasRepresentation(tmpvalues,comm,gmin,gmax,gbin,histoSigma);
}
// decide how to source hills ( serial/parallel )
// here below the input control
// say how many hills and it will read them from the
// bunch of files provided, will update the representation
// of hills (i.e. a list of hills and the associated grid)
// decide how to source colvars ( serial parallel )
FilesHandler *hillsHandler;
FilesHandler *histoHandler;
if(integratehills) hillsHandler=new FilesHandler(hillsFiles,parallelread,*this, log);
if(integratehisto) histoHandler=new FilesHandler(histoFiles,parallelread,*this, log);
// read a number of hills and put in the bias representation
int nfiles=0;
bool ibias=integratehills; bool ihisto=integratehisto;
while(true){
if( integratehills && ibias ){
if(nohistory){biasrep->clear();log<<" clearing history before reading a new block\n";};
log<<" reading hills: \n";
ibias=hillsHandler->readBunch(biasrep,initstride) ; log<<"\n";
}
if( integratehisto && ihisto ){
if(nohistory){historep->clear();log<<" clearing history before reading a new block\n";};
log<<" reading histogram: \n";
ihisto=histoHandler->readBunch(historep,initstride) ; log<<"\n";
}
// dump: need to project?
if(proj.size()!=0){
if(integratehills){
log<<" Bias: Projecting on subgrid... \n";
BiasWeight *Bw=new BiasWeight(beta);
Grid biasGrid=*(biasrep->getGridPtr());
Grid smallGrid=biasGrid.project(proj,Bw);
OFile gridfile; gridfile.link(*this);
std::ostringstream ostr;ostr<<nfiles;
string myout;
if(initstride>0){ myout=outhills+ostr.str()+".dat" ;}else{myout=outhills;}
log<<" Bias: Writing subgrid on file "<<myout<<" \n";
gridfile.open(myout);
smallGrid.setOutputFmt(fmt);
smallGrid.writeToFile(gridfile);
gridfile.close();
if(!ibias)integratehills=false;// once you get to the final bunch just give up
}
if(integratehisto){
log<<" Histo: Projecting on subgrid... \n";
ProbWeight *Pw=new ProbWeight(beta);
Grid histoGrid=*(historep->getGridPtr());
Grid smallGrid=histoGrid.project(proj,Pw);
OFile gridfile; gridfile.link(*this);
std::ostringstream ostr;ostr<<nfiles;
string myout;
if(initstride>0){ myout=outhisto+ostr.str()+".dat" ;}else{myout=outhisto;}
log<<" Histo: Writing subgrid on file "<<myout<<" \n";
gridfile.open(myout);
smallGrid.setOutputFmt(fmt);
smallGrid.writeToFile(gridfile);
gridfile.close();
if(!ihisto)integratehisto=false;// once you get to the final bunch just give up
}
}else{
if(integratehills){
Grid biasGrid=*(biasrep->getGridPtr());
biasGrid.scaleAllValuesAndDerivatives(-1.);
OFile gridfile; gridfile.link(*this);
std::ostringstream ostr;ostr<<nfiles;
string myout;
if(initstride>0){ myout=outhills+ostr.str()+".dat" ;}else{myout=outhills;}
log<<" Writing full grid on file "<<myout<<" \n";
gridfile.open(myout);
biasGrid.setOutputFmt(fmt);
biasGrid.writeToFile(gridfile);
gridfile.close();
// rescale back prior to accumulate
if(!ibias)integratehills=false;// once you get to the final bunch just give up
}
if(integratehisto){
Grid histoGrid=*(historep->getGridPtr());
histoGrid.applyFunctionAllValuesAndDerivatives(&mylog,&mylogder);
histoGrid.scaleAllValuesAndDerivatives(-1./beta);
OFile gridfile; gridfile.link(*this);
std::ostringstream ostr;ostr<<nfiles;
string myout;
if(initstride>0){ myout=outhisto+ostr.str()+".dat" ;}else{myout=outhisto;}
log<<" Writing full grid on file "<<myout<<" \n";
gridfile.open(myout);
histoGrid.setOutputFmt(fmt);
histoGrid.writeToFile(gridfile);
gridfile.close();
if(!ihisto)integratehisto=false;// once you get to the final bunch just give up
}
}
if ( !ibias && !ihisto) break; //when both are over then just quit
nfiles++;
}
return;
}
// just an initialization but you need to do something on the fly?: need to connect with a metad run and its grid representation
// your argument is a metad run
// if the grid does not exist crash and say that you need some data
// otherwise just link with it
}
FuncSumHills::FuncSumHills(const ActionOptions&ao):
Action(ao),
Function(ao),
initstride(-1),
iscltool(false),
integratehills(false),
integratehisto(false),
parallelread(false),
negativebias(false),
nohistory(false),
minTOzero(false),
doInt(false),
lowI_(-1.),
uppI_(-1.),
beta(-1.),
fmt("%14.9f"),
biasrep(NULL),
historep(NULL)
{
// format
parse("FMT",fmt);
log<<" Output format is "<<fmt<<"\n";
// here read
// Grid Stuff
vector<std::string> gmin;
parseVector("GRID_MIN",gmin);
if(gmin.size()!=getNumberOfArguments() && gmin.size()!=0) error("not enough values for GRID_MIN");
plumed_massert(gmin.size()==getNumberOfArguments() || gmin.size()==0,"need GRID_MIN argument for this") ;
vector<std::string> gmax;
parseVector("GRID_MAX",gmax);
if(gmax.size()!=getNumberOfArguments() && gmax.size()!=0) error("not enough values for GRID_MAX");
plumed_massert(gmax.size()==getNumberOfArguments() || gmax.size()==0,"need GRID_MAX argument for this") ;
vector<unsigned> gbin;
vector<double> gspacing;
parseVector("GRID_BIN",gbin);
plumed_massert(gbin.size()==getNumberOfArguments() || gbin.size()==0,"need GRID_BIN argument for this") ;
if(gbin.size()!=getNumberOfArguments() && gbin.size()!=0) error("not enough values for GRID_BIN");
parseVector("GRID_SPACING",gspacing);
plumed_massert(gspacing.size()==getNumberOfArguments() || gspacing.size()==0,"need GRID_SPACING argument for this") ;
if(gspacing.size()!=getNumberOfArguments() && gspacing.size()!=0) error("not enough values for GRID_SPACING");
if(gspacing.size()!=0 && gbin.size()==0){
log<<" The number of bins will be estimated from GRID_SPACING\n";
} else if(gspacing.size()!=0 && gbin.size()!=0){
log<<" You specified both GRID_BIN and GRID_SPACING\n";
log<<" The more conservative (highest) number of bins will be used for each variable\n";
}
if(gspacing.size()!=0) for(unsigned i=0;i<getNumberOfArguments();i++){
if(gbin.size()==0) gbin.assign(getNumberOfArguments(),1);
double a,b;
Tools::convert(gmin[i],a);
Tools::convert(gmax[i],b);
unsigned n=((b-a)/gspacing[i])+1;
if(gbin[i]<n) gbin[i]=n;
}
// Inteval keyword
vector<double> tmpI(2);
parseVector("INTERVAL",tmpI);
if(tmpI.size()!=2&&tmpI.size()!=0) error("both a lower and an upper limits must be provided with INTERVAL");
else if(tmpI.size()==2) {
lowI_=tmpI.at(0);
uppI_=tmpI.at(1);
if(getNumberOfArguments()!=1) error("INTERVAL limits correction works only for monodimensional metadynamics!");
if(uppI_<lowI_) error("The Upper limit must be greater than the Lower limit!");
doInt=true;
}
if(doInt) log << " Upper and Lower limits boundaries for the bias are activated at " << lowI_ << " - " << uppI_<<"\n";
// hills file:
parseVector("HILLSFILES",hillsFiles);
if(hillsFiles.size()==0){
integratehills=false; // default behaviour
}else{
integratehills=true;
for(unsigned i=0;i<hillsFiles.size();i++) log<<" hillsfile : "<<hillsFiles[i]<<"\n";
}
// histo file:
parseVector("HISTOFILES",histoFiles);
if(histoFiles.size()==0){
integratehisto=false;
}else{
integratehisto=true;
for(unsigned i=0;i<histoFiles.size();i++) log<<" histofile : "<<histoFiles[i]<<"\n";
}
vector<double> histoSigma;
if(integratehisto){
parseVector("HISTOSIGMA",histoSigma);
for(unsigned i=0;i<histoSigma.size();i++) log<<" histosigma : "<<histoSigma[i]<<"\n";
}
// needs a projection?
proj.clear();
parseVector("PROJ",proj);
if(integratehills) {
plumed_massert(proj.size()<getNumberOfArguments()," The number of projection must be less than the full list of arguments ");
}
if(integratehisto) {
plumed_massert(proj.size()<=getNumberOfArguments()," The number of projection must be less or equal to the full list of arguments ");
}
if(integratehisto&&proj.size()==0) {
for(unsigned i=0;i<getNumberOfArguments();i++) proj.push_back(getPntrToArgument(i)->getName());
}
// add some automatic hills width: not in case stride is defined
// since when you start from zero the automatic size will be zero!
if(gmin.size()==0 || gmax.size()==0){
log<<" \n";
log<<" No boundaries defined: need to do a prescreening of hills \n";
std::vector<Value*> tmphillsvalues, tmphistovalues;
if(integratehills) {
for(unsigned i=0;i<getNumberOfArguments();i++)tmphillsvalues.push_back( getPntrToArgument(i) );
}
if(integratehisto) {
for(unsigned i=0;i<getNumberOfArguments();i++) {
std::string ss = getPntrToArgument(i)->getName();
for(unsigned j=0;j<proj.size();j++) {
if(proj[j]==ss) tmphistovalues.push_back( getPntrToArgument(i) );
}
}
}
if(integratehills) {
FilesHandler *hillsHandler;
hillsHandler=new FilesHandler(hillsFiles,parallelread,*this, log);
vector<double> vmin,vmax;
vector<unsigned> vbin;
hillsHandler->getMinMaxBin(tmphillsvalues,comm,vmin,vmax,vbin);
log<<" found boundaries from hillsfile: \n";
gmin.resize(vmin.size());
gmax.resize(vmax.size());
if(gbin.size()==0){
gbin=vbin;
}else{
log<<" found nbins in input, this overrides the automatic choice \n";
}
for(unsigned i=0;i<getNumberOfArguments();i++){
Tools::convert(vmin[i],gmin[i]);
Tools::convert(vmax[i],gmax[i]);
log<<" variable "<< getPntrToArgument(i)->getName()<<" min: "<<gmin[i]<<" max: "<<gmax[i]<<" nbin: "<<gbin[i]<<"\n";
}
delete hillsHandler;
}
// if at this stage bins are not there then do it with histo
if(gmin.size()==0){
FilesHandler *histoHandler;
histoHandler=new FilesHandler(histoFiles,parallelread,*this, log);
vector<double> vmin,vmax;
vector<unsigned> vbin;
histoHandler->getMinMaxBin(tmphistovalues,comm,vmin,vmax,vbin,histoSigma);
log<<" found boundaries from histofile: \n";
gmin.resize(vmin.size());
gmax.resize(vmax.size());
if(gbin.size()==0){
gbin=vbin;
}else{
log<<" found nbins in input, this overrides the automatic choice \n";
}
for(unsigned i=0;i<proj.size();i++){
Tools::convert(vmin[i],gmin[i]);
Tools::convert(vmax[i],gmax[i]);
log<<" variable "<< proj[i] <<" min: "<<gmin[i]<<" max: "<<gmax[i]<<" nbin: "<<gbin[i]<<"\n";
}
delete histoHandler;
}
log<<" done!\n";
log<<" \n";
}
if( proj.size() != 0 || integratehisto==true ) {
parse("KT",beta);
for(unsigned i=0;i<proj.size();i++) log<<" projection "<<i<<" : "<<proj[i]<<"\n";
// this should be only for projection or free energy from histograms
plumed_massert(beta>0.,"if you make a projection or a histogram correction then you need KT flag!");
beta=1./beta;
log<<" beta is "<<beta<<"\n";
}
// is a cltool: then you start and then die
parseFlag("ISCLTOOL",iscltool);
//
parseFlag("NEGBIAS",negativebias);
//
parseFlag("PARALLELREAD",parallelread);
// stride
parse("INITSTRIDE",initstride);
// output suffix or names
if(initstride<0){ log<<" Doing only one integration: no stride \n";
outhills="fes.dat";outhisto="histo.dat";}
else{outhills="fes_";outhisto="histo_";
log<<" Doing integration slices every "<<initstride<<" kernels\n";
parseFlag("NOHISTORY",nohistory);
if(nohistory)log<<" nohistory: each stride block has no memory of the previous block\n";
}
parseFlag("MINTOZERO",minTOzero);
if(minTOzero)log<<" mintozero: bias/histogram will be translated to have the minimum value equal to zero\n";
//what might it be this?
// here start
// want something right now?? do it and return
// your argument is a set of cvs
// then you need: a hills / a colvar-like file (to do a histogram)
// create a bias representation for this
if(iscltool){
std::vector<Value*> tmphillsvalues, tmphistovalues;
if(integratehills) {
for(unsigned i=0;i<getNumberOfArguments();i++){
// allocate a new value from the old one: no deriv here
// if we are summing hills then all the arguments are needed
tmphillsvalues.push_back( getPntrToArgument(i) );
}
}
if(integratehisto) {
for(unsigned i=0;i<getNumberOfArguments();i++) {
std::string ss = getPntrToArgument(i)->getName();
for(unsigned j=0;j<proj.size();j++) {
if(proj[j]==ss) tmphistovalues.push_back( getPntrToArgument(i) );
}
}
}
// check if the files exists
if(integratehills){
checkFilesAreExisting(hillsFiles);
biasrep=new BiasRepresentation(tmphillsvalues,comm, gmin, gmax, gbin, doInt, lowI_, uppI_);
if(negativebias){
biasrep->setRescaledToBias(true);
log<<" required the -bias instead of the free energy \n";
if(initstride<0){outhills="negativebias.dat";}
else{outhills="negativebias_";}
}
}
parse("OUTHILLS",outhills);
parse("OUTHISTO",outhisto);
if(integratehills)log<<" output file for fes/bias is : "<<outhills<<"\n";
if(integratehisto)log<<" output file for histogram is : "<<outhisto<<"\n";
checkRead();
log<<"\n";
log<<" Now calculating...\n";
log<<"\n";
// here it defines the column to be histogrammed, tmpvalues should be only
// the list of the collective variable one want to consider
if(integratehisto){
checkFilesAreExisting(histoFiles);
historep=new BiasRepresentation(tmphistovalues,comm,gmin,gmax,gbin,histoSigma);
}
// decide how to source hills ( serial/parallel )
// here below the input control
// say how many hills and it will read them from the
// bunch of files provided, will update the representation
// of hills (i.e. a list of hills and the associated grid)
// decide how to source colvars ( serial parallel )
FilesHandler *hillsHandler;
FilesHandler *histoHandler;
hillsHandler=NULL;
histoHandler=NULL;
if(integratehills) hillsHandler=new FilesHandler(hillsFiles,parallelread,*this, log);
if(integratehisto) histoHandler=new FilesHandler(histoFiles,parallelread,*this, log);
// read a number of hills and put in the bias representation
int nfiles=0;
bool ibias=integratehills; bool ihisto=integratehisto;
while(true){
if( integratehills && ibias ){
if(nohistory){biasrep->clear();log<<" clearing history before reading a new block\n";};
log<<" reading hills: \n";
ibias=hillsHandler->readBunch(biasrep,initstride) ; log<<"\n";
}
if( integratehisto && ihisto ){
if(nohistory){historep->clear();log<<" clearing history before reading a new block\n";};
log<<" reading histogram: \n";
ihisto=histoHandler->readBunch(historep,initstride) ; log<<"\n";
}
// dump: need to project?
if(proj.size()!=0){
if(integratehills){
log<<" Bias: Projecting on subgrid... \n";
BiasWeight *Bw=new BiasWeight(beta);
Grid biasGrid=*(biasrep->getGridPtr());
Grid smallGrid=biasGrid.project(proj,Bw);
OFile gridfile; gridfile.link(*this);
std::ostringstream ostr;ostr<<nfiles;
string myout;
if(initstride>0){ myout=outhills+ostr.str()+".dat" ;}else{myout=outhills;}
log<<" Bias: Writing subgrid on file "<<myout<<" \n";
gridfile.open(myout);
if(minTOzero) smallGrid.setMinToZero();
smallGrid.setOutputFmt(fmt);
smallGrid.writeToFile(gridfile);
gridfile.close();
if(!ibias)integratehills=false;// once you get to the final bunch just give up
delete Bw;
}
// this should be removed
if(integratehisto){
log<<" Histo: Projecting on subgrid... \n";
Grid histoGrid=*(historep->getGridPtr());
OFile gridfile; gridfile.link(*this);
std::ostringstream ostr;ostr<<nfiles;
string myout;
if(initstride>0){ myout=outhisto+ostr.str()+".dat" ;}else{myout=outhisto;}
log<<" Histo: Writing subgrid on file "<<myout<<" \n";
gridfile.open(myout);
histoGrid.applyFunctionAllValuesAndDerivatives(&mylog,&mylogder);
histoGrid.scaleAllValuesAndDerivatives(-1./beta);
if(minTOzero) histoGrid.setMinToZero();
histoGrid.setOutputFmt(fmt);
histoGrid.writeToFile(gridfile);
gridfile.close();
if(!ihisto)integratehisto=false;// once you get to the final bunch just give up
}
}else{
if(integratehills){
Grid biasGrid=*(biasrep->getGridPtr());
biasGrid.scaleAllValuesAndDerivatives(-1.);
OFile gridfile; gridfile.link(*this);
std::ostringstream ostr;ostr<<nfiles;
string myout;
if(initstride>0){ myout=outhills+ostr.str()+".dat" ;}else{myout=outhills;}
log<<" Writing full grid on file "<<myout<<" \n";
gridfile.open(myout);
if(minTOzero) biasGrid.setMinToZero();
biasGrid.setOutputFmt(fmt);
biasGrid.writeToFile(gridfile);
gridfile.close();
// rescale back prior to accumulate
if(!ibias)integratehills=false;// once you get to the final bunch just give up
}
if(integratehisto){
Grid histoGrid=*(historep->getGridPtr());
// do this if you want a free energy from a grid, otherwise do not
histoGrid.applyFunctionAllValuesAndDerivatives(&mylog,&mylogder);
histoGrid.scaleAllValuesAndDerivatives(-1./beta);
OFile gridfile; gridfile.link(*this);
std::ostringstream ostr;ostr<<nfiles;
string myout;
if(initstride>0){ myout=outhisto+ostr.str()+".dat" ;}else{myout=outhisto;}
log<<" Writing full grid on file "<<myout<<" \n";
gridfile.open(myout);
// also this is usefull only for free energy
if(minTOzero) histoGrid.setMinToZero();
histoGrid.setOutputFmt(fmt);
histoGrid.writeToFile(gridfile);
gridfile.close();
if(!ihisto)integratehisto=false; // once you get to the final bunch just give up
}
}
if ( !ibias && !ihisto) break; //when both are over then just quit
nfiles++;
}
if(hillsHandler) delete hillsHandler;
if(histoHandler) delete histoHandler;
return;
}
// just an initialization but you need to do something on the fly?: need to connect with a metad run and its grid representation
// your argument is a metad run
// if the grid does not exist crash and say that you need some data
// otherwise just link with it
}
void GridPrintingBase::runFinalJobs(){
if( getStride()>0 ) return;
OFile ofile; ofile.link(*this);
ofile.open( filename ); printGrid( ofile ); ofile.close();
}