source: src/Actions/FragmentationAction/FitPotentialAction.cpp@ 48d20d

/*
 * Project: MoleCuilder
 * Description: creates and alters molecular systems
 * Copyright (C)  2013 University of Bonn. All rights reserved.
 * 
 *
 *   This file is part of MoleCuilder.
 *
 *    MoleCuilder is free software: you can redistribute it and/or modify
 *    it under the terms of the GNU General Public License as published by
 *    the Free Software Foundation, either version 2 of the License, or
 *    (at your option) any later version.
 *
 *    MoleCuilder 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 General Public License for more details.
 *
 *    You should have received a copy of the GNU General Public License
 *    along with MoleCuilder.  If not, see <http://www.gnu.org/licenses/>.
 */

/*
 * FitPotentialAction.cpp
 *
 *  Created on: Apr 09, 2013
 *      Author: heber
 */

// include config.h
#ifdef HAVE_CONFIG_H
#include <config.h>
#endif

// needs to come before MemDebug due to placement new
#include <boost/archive/text_iarchive.hpp>

#include "CodePatterns/MemDebug.hpp"

#include <algorithm>
#include <boost/bind.hpp>
#include <boost/filesystem.hpp>
#include <boost/foreach.hpp>
#include <map>
#include <string>
#include <sstream>

#include "Actions/FragmentationAction/FitPotentialAction.hpp"

#include "CodePatterns/Log.hpp"

#include "Element/element.hpp"
#include "Fragmentation/Homology/HomologyContainer.hpp"
#include "Fragmentation/Homology/HomologyGraph.hpp"
#include "Fragmentation/Summation/SetValues/Fragment.hpp"
#include "FunctionApproximation/Extractors.hpp"
#include "FunctionApproximation/FunctionApproximation.hpp"
#include "FunctionApproximation/FunctionModel.hpp"
#include "FunctionApproximation/TrainingData.hpp"
#include "FunctionApproximation/writeDistanceEnergyTable.hpp"
#include "Potentials/PotentialFactory.hpp"
#include "Potentials/SerializablePotential.hpp"

using namespace MoleCuilder;

// and construct the stuff
#include "FitPotentialAction.def"
#include "Action_impl_pre.hpp"
/** =========== define the function ====================== */

HomologyGraph getFirstGraphwithSpecifiedElements(
    const HomologyContainer &homologies,
    const SerializablePotential::ParticleTypes_t &types)
{
  ASSERT( !types.empty(),
      "getFirstGraphwithSpecifiedElements() - charges is empty?");
  // create charges
  Fragment::charges_t charges;
  charges.resize(types.size());
  std::transform(types.begin(), types.end(),
      charges.begin(), boost::lambda::_1);
  // convert into count map
  Extractors::elementcounts_t counts_per_charge =
      Extractors::_detail::getElementCounts(charges);
  ASSERT( !counts_per_charge.empty(),
      "getFirstGraphwithSpecifiedElements() - charge counts are empty?");
  LOG(2, "DEBUG: counts_per_charge is " << counts_per_charge << ".");
  // we want to check each (unique) key only once
  HomologyContainer::const_key_iterator olditer = homologies.key_end();
  for (HomologyContainer::const_key_iterator iter =
      homologies.key_begin(); iter != homologies.key_end(); olditer = iter++) {
    // if it's the same as the old one, skip it
    if (*olditer == *iter)
      continue;
    // if it's a new key, check if every element has the right number of counts
    Extractors::elementcounts_t::const_iterator countiter = counts_per_charge.begin();
    for (; countiter != counts_per_charge.end(); ++countiter)
      if (!(*iter).hasTimesAtomicNumber(countiter->first,countiter->second))
        break;
    if( countiter == counts_per_charge.end())
      return *iter;
  }
  return HomologyGraph();
}

Action::state_ptr FragmentationFitPotentialAction::performCall() {
  // charges specify the potential type
  SerializablePotential::ParticleTypes_t chargenumbers;
  {
    const std::vector<const element *> &charges = params.charges.get();
    std::transform(charges.begin(), charges.end(), std::back_inserter(chargenumbers),
        boost::bind(&element::getAtomicNumber, _1));
  }
  // fragment specifies the homology fragment to use
  SerializablePotential::ParticleTypes_t fragmentnumbers;
  {
    const std::vector<const element *> &fragment = params.fragment.get();
    std::transform(fragment.begin(), fragment.end(), std::back_inserter(fragmentnumbers),
        boost::bind(&element::getAtomicNumber, _1));
  }

  // parse homologies into container
  HomologyContainer homologies;
  if (boost::filesystem::exists(params.homology_file.get())) {
    std::ifstream returnstream(params.homology_file.get().string().c_str());
    if (returnstream.good()) {
      boost::archive::text_iarchive ia(returnstream);
      ia >> homologies;
    } else {
      ELOG(0, "Failed to parse from " << params.homology_file.get().string() << ".");
      return Action::failure;
    }
    returnstream.close();
  } else {
    ELOG(0, params.homology_file.get() << " does not exist.");
    return Action::failure;
  }

  // first we try to look into the HomologyContainer
  LOG(1, "INFO: Listing all present homologies ...");
  for (HomologyContainer::container_t::const_iterator iter =
      homologies.begin(); iter != homologies.end(); ++iter) {
    LOG(1, "INFO: graph " << iter->first << " has Fragment " << iter->second.first
        << " and associated energy " << iter->second.second << ".");
  }

  LOG(0, "STATUS: I'm training now a " << params.potentialtype.get() << " potential on charges "
      << chargenumbers << " on data from " << params.homology_file.get() << ".");

  /******************** TRAINING ********************/
  // fit potential
  FunctionModel *model =
      PotentialFactory::getInstance().createInstance(
          params.potentialtype.get(),
          chargenumbers);
  ASSERT( model != NULL,
      "main() - model returned from PotentialFactory is NULL.");
  FunctionModel::parameters_t bestparams(model->getParameterDimension(), 0.);
  {
    // then we ought to pick the right HomologyGraph ...
    const HomologyGraph graph = getFirstGraphwithSpecifiedElements(homologies,fragmentnumbers);
    if (graph != HomologyGraph()) {
      LOG(1, "First representative graph containing fragment "
          << fragmentnumbers << " is " << graph << ".");

      // Afterwards we go through all of this type and gather the distance and the energy value
      TrainingData data(model->getFragmentSpecificExtractor());
      data(homologies.getHomologousGraphs(graph));

      // print distances and energies if desired for debugging
      if (!data.getTrainingInputs().empty()) {
        // print which distance is which
        size_t counter=1;
        if (DoLog(3)) {
          const FunctionModel::arguments_t &inputs = data.getTrainingInputs()[0];
          for (FunctionModel::arguments_t::const_iterator iter = inputs.begin();
              iter != inputs.end(); ++iter) {
            const argument_t &arg = *iter;
            LOG(3, "DEBUG: distance " << counter++ << " is between (#"
                << arg.indices.first << "c" << arg.types.first << ","
                << arg.indices.second << "c" << arg.types.second << ").");
          }
        }

        // print table
        LOG(3, "DEBUG: I gathered the following training data:\n" <<
            _detail::writeDistanceEnergyTable(data.getDistanceEnergyTable()));
      }

      // now perform the function approximation by optimizing the model function
      FunctionApproximation approximator(data, *model);
      if (model->isBoxConstraint() && approximator.checkParameterDerivatives()) {
        double l2error = std::numeric_limits<double>::infinity();
        // seed with current time
        srand((unsigned)time(0));
        for (unsigned int runs=0; runs < params.best_of_howmany.get(); ++runs) {
          // generate new random initial parameter values
          model->setParametersToRandomInitialValues(data);
          LOG(1, "INFO: Initial parameters of run " << runs << " are "
              << model->getParameters() << ".");
          approximator(FunctionApproximation::ParameterDerivative);
          LOG(1, "INFO: Final parameters of run " << runs << " are "
              << model->getParameters() << ".");
          const double new_l2error = data.getL2Error(*model);
          if (new_l2error < l2error) {
            // store currently best parameters
            l2error = new_l2error;
            bestparams = model->getParameters();
            LOG(1, "STATUS: New fit from run " << runs
                << " has better error of " << l2error << ".");
          }
        }
        // reset parameters from best fit
        model->setParameters(bestparams);
        LOG(1, "INFO: Best parameters with L2 error of "
            << l2error << " are " << model->getParameters() << ".");
      } else {
        ELOG(0, "We require parameter derivatives for a box constraint minimization.");
        return Action::failure;
      }

      // create a map of each fragment with error.
      typedef std::multimap< double, size_t > WorseFragmentMap_t;
      WorseFragmentMap_t WorseFragmentMap;
      HomologyContainer::range_t fragmentrange = homologies.getHomologousGraphs(graph);
      // fragments make it into the container in reversed order, hence count from top down
      size_t index= std::distance(fragmentrange.first, fragmentrange.second)-1;
      for (HomologyContainer::const_iterator iter = fragmentrange.first;
          iter != fragmentrange.second;
          ++iter) {
        const Fragment& fragment = iter->second.first;
        const double &energy = iter->second.second;

        // create arguments from the fragment
        FunctionModel::extractor_t extractor = model->getFragmentSpecificExtractor();
        FunctionModel::arguments_t args = extractor(fragment, 1);

        // calculate value from potential
        const double fitvalue = (*model)(args)[0];

        // insert difference into map
        const double error = fabs(energy - fitvalue);
        WorseFragmentMap.insert( std::make_pair( error, index-- ) );

        {
          // give only the distances in the debugging text
          std::stringstream streamargs;
          BOOST_FOREACH (argument_t arg, args) {
            streamargs << " " << arg.distance*AtomicLengthToAngstroem;
          }
          LOG(2, "DEBUG: frag.#" << index+1 << "'s error is |" << energy << " - " << fitvalue
              << "| = " << error << " for args " << streamargs.str() << ".");
        }
      }
      LOG(0, "RESULT: WorstFragmentMap " << WorseFragmentMap << ".");

      SerializablePotential *potential = dynamic_cast<SerializablePotential *>(model);
      if (potential != NULL) {
        LOG(1, "STATUS: Resulting parameters are " << std::endl << *potential);
      } else {
        LOG(1, "INFO: FunctionModel is no serializable potential.");
      }
    }
  }
  delete model;

  return Action::success;
}

Action::state_ptr FragmentationFitPotentialAction::performUndo(Action::state_ptr _state) {
  return Action::success;
}

Action::state_ptr FragmentationFitPotentialAction::performRedo(Action::state_ptr _state){
  return Action::success;
}

bool FragmentationFitPotentialAction::canUndo() {
  return false;
}

bool FragmentationFitPotentialAction::shouldUndo() {
  return false;
}
/** =========== end of function ====================== */