ReweightWham.cpp

/* +++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++
   Copyright (c) 2011-2016 The plumed team
   (see the PEOPLE file at the root of the distribution for a list of names)

   See http://www.plumed.org for more information.

   This file is part of plumed, version 2.

   plumed is free software: you can redistribute it and/or modify
   it under the terms of the GNU Lesser General Public License as published by
   the Free Software Foundation, either version 3 of the License, or
   (at your option) any later version.

   plumed is distributed in the hope that it will be useful,
   but WITHOUT ANY WARRANTY; without even the implied warranty of
   MERCHANTABILITY or FITNESS FOR A PARTICULAR PURPOSE.  See the
   GNU Lesser General Public License for more details.

   You should have received a copy of the GNU Lesser General Public License
   along with plumed.  If not, see <http://www.gnu.org/licenses/>.
+++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++ */
#include "ReweightWham.h"
#include "core/ActionRegister.h"

//+PLUMEDOC REWEIGHTING REWEIGHT_WHAM
/*

\par Examples

*/
//+ENDPLUMEDOC

namespace PLMD {
namespace bias {

PLUMED_REGISTER_ACTION(ReweightWham,"REWEIGHT_WHAM")

void ReweightWham::registerKeywords(Keywords& keys ) {
  ReweightBase::registerKeywords( keys ); keys.use("ARG");
  keys.add("compulsory","MAXITER","1000","maximum number of iterations for WHAM algorithm");
  keys.add("compulsory","WHAMTOL","1e-10","threshold for convergence of WHAM algorithm");
}

ReweightWham::ReweightWham(const ActionOptions&ao):
  Action(ao),
  ReweightBase(ao),
  weightsCalculated(false)
{
  std::vector<Value*> targ, fagr;
  unsigned nbias = 0; wlists.push_back( 0 );
  for(unsigned i=1;; i++) {
    if( !parseArgumentList("ARG",i,targ ) ) break;
    log.printf("  bias number %d involves :");
    for(unsigned j=0; j<targ.size(); ++j) {
      log.printf("%s ",targ[j]->getName().c_str() );
      fagr.push_back( targ[j] );
    }
    log.printf("\n"); targ.resize(0);
    wlists.push_back( fagr.size() );
    nbias++;
  }
  plumed_assert( wlists.size()==(nbias+1) ); requestArguments( fagr );
  parse("MAXITER",maxiter); parse("WHAMTOL",thresh);
}

double ReweightWham::getLogWeight() {
  if( getStep()==0 ) return 1.0;  // This is here as first step is ignored in all analyses
  weightsCalculated=false;
  for(unsigned i=0; i<wlists.size()-1; ++i) {
    double total_bias=0;
    for(unsigned j=wlists[i]; j<wlists[i+1]; ++j) total_bias+=getArgument(j);
    stored_biases.push_back( total_bias );
  }
  return 1.0;
}

void ReweightWham::clearData() {
  stored_biases.resize(0);
}

void ReweightWham::calculateWeights( const unsigned& nframes ) {
  if( stored_biases.size()!=(wlists.size()-1)*nframes ) error("wrong number of weights stored");
  // Get the minimum value of the bias
  double minv = *min_element(std::begin(stored_biases), std::end(stored_biases));
  // Resize final weights array
  plumed_assert( stored_biases.size()%(wlists.size()-1)==0 );
  final_weights.resize( stored_biases.size() / (wlists.size()-1), 1.0 );
  // Offset and exponential of the bias
  std::vector<double> expv( stored_biases.size() );
  for(unsigned i=0; i<expv.size(); ++i) expv[i] = exp( (-stored_biases[i]+minv) / simtemp );
  // Initialize Z
  std::vector<double> Z( wlists.size()-1, 1.0 ), oldZ( wlists.size()-1 );
  // Now the iterative loop to calculate the WHAM weights
  for(unsigned iter=0; iter<maxiter; ++iter) {
    // Store Z
    for(unsigned j=0; j<Z.size(); ++j) oldZ[j]=Z[j];
    // Recompute weights
    double norm=0;
    for(unsigned j=0; j<final_weights.size(); ++j) {
      double ew=0;
      for(unsigned k=0; k<Z.size(); ++k) ew += expv[j*Z.size()+k]  / Z[k];
      final_weights[j] = 1.0 / ew; norm += final_weights[j];
    }
    // Normalize weights
    for(unsigned j=0; j<final_weights.size(); ++j) final_weights[j] /= norm;
    // Recompute Z
    for(unsigned j=0; j<Z.size(); ++j) Z[j] = 0.0;
    for(unsigned j=0; j<final_weights.size(); ++j) {
      for(unsigned k=0; k<Z.size(); ++k) Z[k] += final_weights[j]*expv[j*Z.size()+k];
    }
    // Normalize Z and compute change in Z
    double change=0; norm=0; for(unsigned k=0; k<Z.size(); ++k) norm+=Z[k];
    for(unsigned k=0; k<Z.size(); ++k) {
      Z[k] /= norm; double d = std::log( Z[k] / oldZ[k] ); change += d*d;
    }
    if( change<thresh ) { weightsCalculated=true; return; }
  }
  error("Too many iterations in WHAM" );
}

}
}