src/gromacs/awh/bias.cpp

   1 /*
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   5  * Mark Abraham, David van der Spoel, Berk Hess, and Erik Lindahl,
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  35
  36 /*! \internal \file
  37  * \brief
  38  * Implements the Bias class.
  39  *
  40  * \author Viveca Lindahl
  41  * \author Berk Hess <hess@kth.se>
  42  * \ingroup module_awh
  43  */
  44
  45 #include "gmxpre.h"
  46
  47 #include "bias.h"
  48
  49 #include <assert.h>
  50
  51 #include <cmath>
  52 #include <cstdio>
  53 #include <cstdlib>
  54 #include <cstring>
  55
  56 #include <algorithm>
  57
  58 #include "gromacs/fileio/gmxfio.h"
  59 #include "gromacs/gmxlib/network.h"
  60 #include "gromacs/math/utilities.h"
  61 #include "gromacs/mdtypes/awh-history.h"
  62 #include "gromacs/mdtypes/awh-params.h"
  63 #include "gromacs/mdtypes/commrec.h"
  64 #include "gromacs/utility/exceptions.h"
  65 #include "gromacs/utility/gmxassert.h"
  66 #include "gromacs/utility/stringutil.h"
  67
  68 #include "pointstate.h"
  69
  70 namespace gmx
  71 {
  72
  73 void Bias::warnForHistogramAnomalies(double t, gmx_int64_t step, FILE *fplog)
  74 {
  75     const int    maxNumWarningsInCheck = 1;   /* The maximum number of warnings to print per check */
  76     const int    maxNumWarningsInRun   = 10;  /* The maximum number of warnings to print in a run */
  77
  78     if (fplog == nullptr || numWarningsIssued_ >= maxNumWarningsInRun || state_.inInitialStage() ||
  79         !params_.isCheckStep(state_.points().size(), step))
  80     {
  81         return;
  82     }
  83
  84     numWarningsIssued_ +=
  85         state_.warnForHistogramAnomalies(grid_, biasIndex(), t, fplog,
  86                                          maxNumWarningsInCheck);
  87
  88     if (numWarningsIssued_ >= maxNumWarningsInRun)
  89     {
  90         fprintf(fplog, "\nawh%d: suppressing future AWH warnings.\n", biasIndex() + 1);
  91     }
  92 }
  93
  94 void Bias::doSkippedUpdatesForAllPoints()
  95 {
  96     state_.doSkippedUpdatesForAllPoints(params_);
  97 }
  98
  99 void Bias::calcForceAndUpdateBias(const awh_dvec        coordValue,
 100                                   awh_dvec              biasForce,
 101                                   double               *awhPotential,
 102                                   double               *potentialJump,
 103                                   const gmx_multisim_t *ms,
 104                                   double                t,
 105                                   gmx_int64_t           step,
 106                                   gmx_int64_t           seed,
 107                                   FILE                 *fplog)
 108 {
 109     if (step < 0)
 110     {
 111         GMX_THROW(InvalidInputError("The step number is negative which is not supported by the AWH code."));
 112     }
 113
 114     state_.setCoordValue(grid_, coordValue);
 115
 116     std::vector < double, AlignedAllocator < double>> &probWeightNeighbor = alignedTempWorkSpace_;
 117
 118     /* If the convolved force is needed or this is a sampling step,
 119      * the bias in the current neighborhood needs to be up-to-date
 120      * and the probablity weights need to be calculated.
 121      */
 122     const bool sampleCoord   = params_.isSampleCoordStep(step);
 123     const bool moveUmbrella  = (sampleCoord || step == 0);
 124     double     convolvedBias = 0;
 125     if (params_.convolveForce || moveUmbrella || sampleCoord)
 126     {
 127         if (params_.skipUpdates())
 128         {
 129             state_.doSkippedUpdatesInNeighborhood(params_, grid_);
 130         }
 131
 132         convolvedBias = state_.updateProbabilityWeightsAndConvolvedBias(dimParams_, grid_, &probWeightNeighbor);
 133
 134         if (sampleCoord)
 135         {
 136             state_.sampleCoordAndPmf(grid_, probWeightNeighbor, convolvedBias);
 137         }
 138     }
 139
 140     const CoordState &coordState = state_.coordState();
 141
 142     /* Set the bias force and get the potential contribution from this bias.
 143      * The potential jump occurs at different times depending on how
 144      * the force is applied (and how the potential is normalized).
 145      * For the convolved force it happens when the bias is updated,
 146      * for the umbrella when the umbrella is moved.
 147      */
 148     *potentialJump = 0;
 149     double potential;
 150     if (params_.convolveForce)
 151     {
 152         state_.calcConvolvedForce(dimParams_, grid_, probWeightNeighbor,
 153                                   biasForce);
 154
 155         potential = -convolvedBias*params_.invBeta;
 156     }
 157     else
 158     {
 159         /* Umbrella force */
 160         GMX_RELEASE_ASSERT(state_.points()[coordState.umbrellaGridpoint()].inTargetRegion(),
 161                            "AWH bias grid point for the umbrella reference value is outside of the target region.");
 162         potential =
 163             state_.calcUmbrellaForceAndPotential(dimParams_, grid_, coordState.umbrellaGridpoint(), biasForce);
 164
 165         /* Moving the umbrella results in a force correction and
 166          * a new potential. The umbrella center is sampled as often as
 167          * the coordinate so we know the probability weights needed
 168          * for moving the umbrella are up-to-date.
 169          */
 170         if (moveUmbrella)
 171         {
 172             double newPotential = state_.moveUmbrella(dimParams_, grid_, probWeightNeighbor, biasForce, step, seed, params_.biasIndex);
 173             *potentialJump      = newPotential - potential;
 174         }
 175     }
 176
 177     /* Update the free energy estimates and bias and other history dependent method parameters */
 178     if (params_.isUpdateFreeEnergyStep(step))
 179     {
 180         state_.updateFreeEnergyAndAddSamplesToHistogram(dimParams_, grid_,
 181                                                         params_,
 182                                                         ms, t, step, fplog,
 183                                                         &updateList_);
 184
 185         if (params_.convolveForce)
 186         {
 187             /* The update results in a potential jump, so we need the new convolved potential. */
 188             double newPotential = -calcConvolvedBias(coordState.coordValue())*params_.invBeta;
 189             *potentialJump      = newPotential - potential;
 190         }
 191     }
 192
 193     /* Return the potential. */
 194     *awhPotential = potential;
 195
 196     /* Check the sampled histograms and potentially warn user if something is suspicious */
 197     warnForHistogramAnomalies(t, step, fplog);
 198 }
 199
 200 void Bias::restoreStateFromHistory(const AwhBiasHistory *biasHistory,
 201                                    const t_commrec      *cr)
 202 {
 203     GMX_RELEASE_ASSERT(thisRankDoesIO_ == MASTER(cr), "The master rank should do I/O, the other ranks should not");
 204
 205     if (MASTER(cr))
 206     {
 207         GMX_RELEASE_ASSERT(biasHistory != nullptr, "On the master rank we need a valid history object to restore from");
 208         state_.restoreFromHistory(*biasHistory, grid_);
 209     }
 210
 211     if (PAR(cr))
 212     {
 213         state_.broadcast(cr);
 214     }
 215 }
 216
 217 void Bias::initHistoryFromState(AwhBiasHistory *biasHistory) const
 218 {
 219     GMX_RELEASE_ASSERT(biasHistory != nullptr, "Need a valid biasHistory");
 220
 221     state_.initHistoryFromState(biasHistory);
 222 }
 223
 224 void Bias::updateHistory(AwhBiasHistory *biasHistory) const
 225 {
 226     GMX_RELEASE_ASSERT(biasHistory != nullptr, "Need a valid biasHistory");
 227
 228     state_.updateHistory(biasHistory, grid_);
 229 }
 230
 231 Bias::Bias(int                             biasIndexInCollection,
 232            const AwhParams                &awhParams,
 233            const AwhBiasParams            &awhBiasParams,
 234            const std::vector<DimParams>   &dimParamsInit,
 235            double                          beta,
 236            double                          mdTimeStep,
 237            int                             numSharingSimulations,
 238            const std::string              &biasInitFilename,
 239            ThisRankWillDoIO                thisRankWillDoIO,
 240            BiasParams::DisableUpdateSkips  disableUpdateSkips) :
 241     dimParams_(dimParamsInit),
 242     grid_(dimParamsInit, awhBiasParams.dimParams),
 243     params_(awhParams, awhBiasParams, dimParams_, beta, mdTimeStep, disableUpdateSkips, numSharingSimulations, grid_.axis(), biasIndexInCollection),
 244     state_(awhBiasParams, params_.initialHistogramSize, dimParams_, grid_),
 245     thisRankDoesIO_(thisRankWillDoIO == ThisRankWillDoIO::Yes),
 246     alignedTempWorkSpace_(),
 247     numWarningsIssued_(0)
 248 {
 249     /* For a global update updateList covers all points, so reserve that */
 250     updateList_.reserve(grid_.numPoints());
 251
 252     state_.initGridPointState(awhBiasParams, dimParams_, grid_, params_, biasInitFilename, awhParams.numBias);
 253 }
 254
 255 } // namespace gmx