src/gromacs/awh/bias.cpp

   1 /*
   2  * This file is part of the GROMACS molecular simulation package.
   3  *
   4  * Copyright (c) 2015,2016,2017,2018, by the GROMACS development team, led by
   5  * Mark Abraham, David van der Spoel, Berk Hess, and Erik Lindahl,
   6  * and including many others, as listed in the AUTHORS file in the
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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 <cassert>
  50 #include <cinttypes>
  51 #include <cmath>
  52 #include <cstdio>
  53 #include <cstdlib>
  54 #include <cstring>
  55
  56 #include <algorithm>
  57
  58 #include "gromacs/compat/make_unique.h"
  59 #include "gromacs/fileio/gmxfio.h"
  60 #include "gromacs/gmxlib/network.h"
  61 #include "gromacs/math/functions.h"
  62 #include "gromacs/math/utilities.h"
  63 #include "gromacs/mdtypes/awh-history.h"
  64 #include "gromacs/mdtypes/awh-params.h"
  65 #include "gromacs/mdtypes/commrec.h"
  66 #include "gromacs/utility/exceptions.h"
  67 #include "gromacs/utility/gmxassert.h"
  68 #include "gromacs/utility/stringutil.h"
  69
  70 #include "correlationgrid.h"
  71 #include "correlationhistory.h"
  72 #include "pointstate.h"
  73
  74 namespace gmx
  75 {
  76
  77 void Bias::warnForHistogramAnomalies(double t, int64_t step, FILE *fplog)
  78 {
  79     const int    maxNumWarningsInCheck = 1;   /* The maximum number of warnings to print per check */
  80     const int    maxNumWarningsInRun   = 10;  /* The maximum number of warnings to print in a run */
  81
  82     if (fplog == nullptr || numWarningsIssued_ >= maxNumWarningsInRun || state_.inInitialStage() ||
  83         !params_.isCheckHistogramForAnomaliesStep(step))
  84     {
  85         return;
  86     }
  87
  88     numWarningsIssued_ +=
  89         state_.warnForHistogramAnomalies(grid_, biasIndex(), t, fplog,
  90                                          maxNumWarningsInCheck);
  91
  92     if (numWarningsIssued_ >= maxNumWarningsInRun)
  93     {
  94         fprintf(fplog, "\nawh%d: suppressing future AWH warnings.\n", biasIndex() + 1);
  95     }
  96 }
  97
  98 void Bias::doSkippedUpdatesForAllPoints()
  99 {
 100     if (params_.skipUpdates())
 101     {
 102         state_.doSkippedUpdatesForAllPoints(params_);
 103     }
 104 }
 105
 106 gmx::ArrayRef<const double>
 107 Bias::calcForceAndUpdateBias(const awh_dvec        coordValue,
 108                              double               *awhPotential,
 109                              double               *potentialJump,
 110                              const t_commrec      *commRecord,
 111                              const gmx_multisim_t *ms,
 112                              double                t,
 113                              int64_t               step,
 114                              int64_t               seed,
 115                              FILE                 *fplog)
 116 {
 117     if (step < 0)
 118     {
 119         GMX_THROW(InvalidInputError("The step number is negative which is not supported by the AWH code."));
 120     }
 121
 122     state_.setCoordValue(grid_, coordValue);
 123
 124     std::vector < double, AlignedAllocator < double>> &probWeightNeighbor = alignedTempWorkSpace_;
 125
 126     /* If the convolved force is needed or this is a sampling step,
 127      * the bias in the current neighborhood needs to be up-to-date
 128      * and the probablity weights need to be calculated.
 129      */
 130     const bool sampleCoord   = params_.isSampleCoordStep(step);
 131     const bool moveUmbrella  = (sampleCoord || step == 0);
 132     double     convolvedBias = 0;
 133     if (params_.convolveForce || moveUmbrella || sampleCoord)
 134     {
 135         if (params_.skipUpdates())
 136         {
 137             state_.doSkippedUpdatesInNeighborhood(params_, grid_);
 138         }
 139
 140         convolvedBias = state_.updateProbabilityWeightsAndConvolvedBias(dimParams_, grid_, &probWeightNeighbor);
 141
 142         if (sampleCoord)
 143         {
 144             updateForceCorrelationGrid(probWeightNeighbor, t);
 145
 146             state_.sampleCoordAndPmf(grid_, probWeightNeighbor, convolvedBias);
 147         }
 148     }
 149
 150     const CoordState &coordState = state_.coordState();
 151
 152     /* Set the bias force and get the potential contribution from this bias.
 153      * The potential jump occurs at different times depending on how
 154      * the force is applied (and how the potential is normalized).
 155      * For the convolved force it happens when the bias is updated,
 156      * for the umbrella when the umbrella is moved.
 157      */
 158     *potentialJump = 0;
 159     double potential;
 160     if (params_.convolveForce)
 161     {
 162         state_.calcConvolvedForce(dimParams_, grid_, probWeightNeighbor,
 163                                   tempForce_, biasForce_);
 164
 165         potential = -convolvedBias*params_.invBeta;
 166     }
 167     else
 168     {
 169         /* Umbrella force */
 170         GMX_RELEASE_ASSERT(state_.points()[coordState.umbrellaGridpoint()].inTargetRegion(),
 171                            "AWH bias grid point for the umbrella reference value is outside of the target region.");
 172         potential =
 173             state_.calcUmbrellaForceAndPotential(dimParams_, grid_, coordState.umbrellaGridpoint(), biasForce_);
 174
 175         /* Moving the umbrella results in a force correction and
 176          * a new potential. The umbrella center is sampled as often as
 177          * the coordinate so we know the probability weights needed
 178          * for moving the umbrella are up-to-date.
 179          */
 180         if (moveUmbrella)
 181         {
 182             double newPotential = state_.moveUmbrella(dimParams_, grid_, probWeightNeighbor, biasForce_, step, seed, params_.biasIndex);
 183             *potentialJump      = newPotential - potential;
 184         }
 185     }
 186
 187     /* Update the free energy estimates and bias and other history dependent method parameters */
 188     if (params_.isUpdateFreeEnergyStep(step))
 189     {
 190         state_.updateFreeEnergyAndAddSamplesToHistogram(dimParams_, grid_,
 191                                                         params_,
 192                                                         commRecord, ms,
 193                                                         t, step, fplog,
 194                                                         &updateList_);
 195
 196         if (params_.convolveForce)
 197         {
 198             /* The update results in a potential jump, so we need the new convolved potential. */
 199             double newPotential = -calcConvolvedBias(coordState.coordValue())*params_.invBeta;
 200             *potentialJump      = newPotential - potential;
 201         }
 202     }
 203
 204     /* Return the potential. */
 205     *awhPotential = potential;
 206
 207     /* Check the sampled histograms and potentially warn user if something is suspicious */
 208     warnForHistogramAnomalies(t, step, fplog);
 209
 210     return biasForce_;
 211 }
 212
 213 /*! \brief
 214  * Count the total number of samples / sample weight over all grid points.
 215  *
 216  * \param[in] pointState  The state of the points in a bias.
 217  * \returns the total sample count.
 218  */
 219 static int64_t countSamples(const std::vector<PointState> &pointState)
 220 {
 221     double numSamples = 0;
 222     for (const PointState &point : pointState)
 223     {
 224         numSamples += point.weightSumTot();
 225     }
 226
 227     return gmx::roundToInt64(numSamples);
 228 }
 229
 230 /*! \brief
 231  * Check if the state (loaded from checkpoint) and the run are consistent.
 232  *
 233  * When the state and the run setup are inconsistent, an exception is thrown.
 234  *
 235  * \param[in] params  The parameters of the bias.
 236  * \param[in] state   The state of the bias.
 237  */
 238 static void ensureStateAndRunConsistency(const BiasParams &params,
 239                                          const BiasState  &state)
 240 {
 241     int64_t numSamples            = countSamples(state.points());
 242     int64_t numUpdatesFromSamples = numSamples/(params.numSamplesUpdateFreeEnergy_*params.numSharedUpdate);
 243     int64_t numUpdatesExpected    = state.histogramSize().numUpdates();
 244     if (numUpdatesFromSamples != numUpdatesExpected)
 245     {
 246         std::string mesg = gmx::formatString("The number of AWH updates in the checkpoint file (%" PRId64 ") does not match the total number of AWH samples divided by the number of samples per update for %d sharing AWH bias(es) (%" PRId64 "/%d=%" PRId64 ")",
 247                                              numUpdatesExpected,
 248                                              params.numSharedUpdate,
 249                                              numSamples,
 250                                              params.numSamplesUpdateFreeEnergy_*params.numSharedUpdate,
 251                                              numUpdatesFromSamples);
 252         mesg += " Maybe you changed AWH parameters.";
 253         /* Unfortunately we currently do not store the number of simulations
 254          * sharing the bias or the state to checkpoint. But we can hint at
 255          * a mismatch in the number of sharing simulations.
 256          */
 257         if (numUpdatesFromSamples % state.histogramSize().numUpdates() == 0)
 258         {
 259             mesg += gmx::formatString(" Or the run you continued from used %" PRId64 " sharing simulations, whereas you now specified %d sharing simulations.",
 260                                       numUpdatesFromSamples/state.histogramSize().numUpdates(),
 261                                       params.numSharedUpdate);
 262         }
 263         GMX_THROW(InvalidInputError(mesg));
 264     }
 265 }
 266
 267 void Bias::restoreStateFromHistory(const AwhBiasHistory *biasHistory,
 268                                    const t_commrec      *cr)
 269 {
 270     GMX_RELEASE_ASSERT(thisRankDoesIO_ == MASTER(cr), "The master rank should do I/O, the other ranks should not");
 271
 272     if (MASTER(cr))
 273     {
 274         GMX_RELEASE_ASSERT(biasHistory != nullptr, "On the master rank we need a valid history object to restore from");
 275         state_.restoreFromHistory(*biasHistory, grid_);
 276
 277         /* Ensure that the state is consistent with our current run setup,
 278          * since the user can have changed AWH parameters or the number
 279          * of simulations sharing the bias.
 280          */
 281         ensureStateAndRunConsistency(params_, state_);
 282
 283         if (forceCorrelationGrid_ != nullptr)
 284         {
 285             forceCorrelationGrid_->restoreStateFromHistory(biasHistory->forceCorrelationGrid);
 286         }
 287     }
 288
 289     if (PAR(cr))
 290     {
 291         state_.broadcast(cr);
 292     }
 293 }
 294
 295 void Bias::initHistoryFromState(AwhBiasHistory *biasHistory) const
 296 {
 297     GMX_RELEASE_ASSERT(biasHistory != nullptr, "Need a valid biasHistory");
 298
 299     state_.initHistoryFromState(biasHistory);
 300
 301     if (forceCorrelationGrid_ != nullptr)
 302     {
 303         biasHistory->forceCorrelationGrid = initCorrelationGridHistoryFromState(forceCorrelationGrid());
 304     }
 305 }
 306
 307 void Bias::updateHistory(AwhBiasHistory *biasHistory) const
 308 {
 309     GMX_RELEASE_ASSERT(biasHistory != nullptr, "Need a valid biasHistory");
 310
 311     state_.updateHistory(biasHistory, grid_);
 312
 313     if (forceCorrelationGrid_ != nullptr)
 314     {
 315         updateCorrelationGridHistory(&biasHistory->forceCorrelationGrid, forceCorrelationGrid());
 316     }
 317 }
 318
 319 Bias::Bias(int                             biasIndexInCollection,
 320            const AwhParams                &awhParams,
 321            const AwhBiasParams            &awhBiasParams,
 322            const std::vector<DimParams>   &dimParamsInit,
 323            double                          beta,
 324            double                          mdTimeStep,
 325            int                             numSharingSimulations,
 326            const std::string              &biasInitFilename,
 327            ThisRankWillDoIO                thisRankWillDoIO,
 328            BiasParams::DisableUpdateSkips  disableUpdateSkips) :
 329     dimParams_(dimParamsInit),
 330     grid_(dimParamsInit, awhBiasParams.dimParams),
 331     params_(awhParams, awhBiasParams, dimParams_, beta, mdTimeStep, disableUpdateSkips, numSharingSimulations, grid_.axis(), biasIndexInCollection),
 332     state_(awhBiasParams, params_.initialHistogramSize, dimParams_, grid_),
 333     thisRankDoesIO_(thisRankWillDoIO == ThisRankWillDoIO::Yes),
 334     biasForce_(ndim()),
 335
 336     tempForce_(ndim()),
 337     numWarningsIssued_(0)
 338 {
 339     /* For a global update updateList covers all points, so reserve that */
 340     updateList_.reserve(grid_.numPoints());
 341
 342     state_.initGridPointState(awhBiasParams, dimParams_, grid_, params_, biasInitFilename, awhParams.numBias);
 343
 344     if (thisRankDoesIO_)
 345     {
 346         /* Set up the force correlation object. */
 347
 348         /* We let the correlation init function set its parameters
 349          * to something useful for now.
 350          */
 351         double blockLength = 0;
 352         /* Construct the force correlation object. */
 353         forceCorrelationGrid_ =
 354             compat::make_unique<CorrelationGrid>(state_.points().size(), ndim(),
 355                                                  blockLength, CorrelationGrid::BlockLengthMeasure::Time,
 356                                                  awhParams.nstSampleCoord*mdTimeStep);
 357
 358         writer_ = compat::make_unique<BiasWriter>(*this);
 359     }
 360 }
 361
 362 void Bias::printInitializationToLog(FILE *fplog) const
 363 {
 364     if (fplog != nullptr && forceCorrelationGrid_ != nullptr)
 365     {
 366         std::string prefix =
 367             gmx::formatString("\nawh%d:", params_.biasIndex + 1);
 368
 369         fprintf(fplog,
 370                 "%s initial force correlation block length = %g %s"
 371                 "%s force correlation number of blocks = %d",
 372                 prefix.c_str(), forceCorrelationGrid().getBlockLength(),
 373                 forceCorrelationGrid().blockLengthMeasure == CorrelationGrid::BlockLengthMeasure::Weight ? "" : "ps",
 374                 prefix.c_str(), forceCorrelationGrid().getNumBlocks());
 375     }
 376 }
 377
 378 void Bias::updateForceCorrelationGrid(gmx::ArrayRef<const double> probWeightNeighbor,
 379                                       double                      t)
 380 {
 381     if (forceCorrelationGrid_ == nullptr)
 382     {
 383         return;
 384     }
 385
 386     const std::vector<int> &neighbor = grid_.point(state_.coordState().gridpointIndex()).neighbor;
 387
 388     gmx::ArrayRef<double>   forceFromNeighbor = tempForce_;
 389     for (size_t n = 0; n < neighbor.size(); n++)
 390     {
 391         double weightNeighbor = probWeightNeighbor[n];
 392         int    indexNeighbor  = neighbor[n];
 393
 394         /* Add the force data of this neighbor point. Note: the sum of these forces is the convolved force.
 395
 396            We actually add the force normalized by beta which has the units of 1/length. This means that the
 397            resulting correlation time integral is directly in units of friction time/length^2 which is really what
 398            we're interested in. */
 399         state_.calcUmbrellaForceAndPotential(dimParams_, grid_, indexNeighbor, forceFromNeighbor);
 400
 401         /* Note: we might want to give a whole list of data to add instead and have this loop in the data adding function */
 402         forceCorrelationGrid_->addData(indexNeighbor, weightNeighbor, forceFromNeighbor, t);
 403     }
 404 }
 405
 406 /* Return the number of data blocks that have been prepared for writing. */
 407 int Bias::numEnergySubblocksToWrite() const
 408 {
 409     GMX_RELEASE_ASSERT(writer_ != nullptr, "Should only request data from an initialized writer");
 410
 411     return writer_->numBlocks();
 412 }
 413
 414 /* Write bias data blocks to energy subblocks. */
 415 int Bias::writeToEnergySubblocks(t_enxsubblock *subblock) const
 416 {
 417     GMX_RELEASE_ASSERT(writer_ != nullptr, "Should only request data from an initialized writer");
 418
 419     return writer_->writeToEnergySubblocks(*this, subblock);
 420 }
 421
 422 } // namespace gmx