src/gromacs/awh/coordstate.cpp

   1 /*
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  35
  36 /*! \internal \file
  37  * \brief
  38  * Implements the CoordState 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 "coordstate.h"
  48
  49 #include <algorithm>
  50
  51 #include "gromacs/math/utilities.h"
  52 #include "gromacs/mdtypes/awh-history.h"
  53 #include "gromacs/mdtypes/awh-params.h"
  54 #include "gromacs/random/threefry.h"
  55 #include "gromacs/random/uniformrealdistribution.h"
  56 #include "gromacs/utility/arrayref.h"
  57 #include "gromacs/utility/gmxassert.h"
  58
  59 #include "grid.h"
  60
  61 namespace gmx
  62 {
  63
  64 CoordState::CoordState(const AwhBiasParams          &awhBiasParams,
  65                        const std::vector<DimParams> &dimParams,
  66                        const Grid                   &grid)
  67 {
  68     for (size_t d = 0; d < dimParams.size(); d++)
  69     {
  70         coordValue_[d] = dimParams[d].scaleUserInputToInternal(awhBiasParams.dimParams[d].coordValueInit);
  71     }
  72
  73     /* The grid-point index is always the nearest point to the coordinate.
  74      * We initialize the umbrella location to the same nearest point.
  75      * More correctly one would sample from the biased distribution,
  76      * but it doesn't really matter, as this will happen after a few steps.
  77      */
  78     gridpointIndex_    = grid.nearestIndex(coordValue_);
  79     umbrellaGridpoint_ = gridpointIndex_;
  80 }
  81
  82 namespace
  83 {
  84
  85 /*! \brief Generate a sample from a discrete probability distribution defined on [0, distr.size() - 1].
  86  *
  87  * The pair (indexSeed0,indexSeed1) should be different for every invocation.
  88  *
  89  * \param[in] distr       Normalized probability distribution to generate a sample from.
  90  * \param[in] seed        Random seed for initializing the random number generator.
  91  * \param[in] indexSeed0  Random seed needed by the random number generator.
  92  * \param[in] indexSeed1  Random seed needed by the random number generator.
  93  * \returns a sample index in [0, distr.size() - 1]
  94  */
  95 int getSampleFromDistribution(ArrayRef<const double> distr,
  96                               gmx_int64_t            seed,
  97                               gmx_int64_t            indexSeed0,
  98                               gmx_int64_t            indexSeed1)
  99 {
 100     gmx::ThreeFry2x64<0>               rng(seed, gmx::RandomDomain::AwhBiasing);
 101     gmx::UniformRealDistribution<real> uniformRealDistr;
 102
 103     GMX_RELEASE_ASSERT(distr.size() > 0, "We need a non-zero length distribution to sample from");
 104
 105     /* Generate the cumulative probability distribution function */
 106     std::vector<double> cumulativeDistribution(distr.size());
 107
 108     cumulativeDistribution[0] = distr[0];
 109
 110     for (size_t i = 1; i < distr.size(); i++)
 111     {
 112         cumulativeDistribution[i] = cumulativeDistribution[i - 1] + distr[i];
 113     }
 114
 115     GMX_RELEASE_ASSERT(gmx_within_tol(cumulativeDistribution.back(), 1.0, 0.01), "Attempt to get sample from non-normalized/zero distribution");
 116
 117     /* Use binary search to convert the real value to an integer in [0, ndistr - 1] distributed according to distr. */
 118     rng.restart(indexSeed0, indexSeed1);
 119
 120     double value  = uniformRealDistr(rng);
 121     int    sample = std::upper_bound(cumulativeDistribution.begin(), cumulativeDistribution.end() - 1, value) - cumulativeDistribution.begin();
 122
 123     return sample;
 124 }
 125
 126 }   // namespace
 127
 128 void
 129 CoordState::sampleUmbrellaGridpoint(const Grid                  &grid,
 130                                     int                          gridpointIndex,
 131                                     gmx::ArrayRef<const double>  probWeightNeighbor,
 132                                     gmx_int64_t                  step,
 133                                     gmx_int64_t                  seed,
 134                                     int                          indexSeed)
 135 {
 136     /* Sample new umbrella reference value from the probability distribution
 137      * which is defined for the neighboring points of the current coordinate.
 138      */
 139     const std::vector<int> &neighbor = grid.point(gridpointIndex).neighbor;
 140
 141     /* In order to use the same seed for all AWH biases and get independent
 142        samples we use the index of the bias. */
 143     int localIndex     = getSampleFromDistribution(probWeightNeighbor,
 144                                                    seed, step, indexSeed);
 145
 146     umbrellaGridpoint_ = neighbor[localIndex];
 147 }
 148
 149 void CoordState::setCoordValue(const Grid     &grid,
 150                                const awh_dvec  coordValue)
 151 {
 152     for (int dim = 0; dim < grid.numDimensions(); dim++)
 153     {
 154         coordValue_[dim] = coordValue[dim];
 155     }
 156
 157     /* The grid point closest to the coordinate value defines the current
 158      * neighborhood of points. Besides at steps when global updates and/or
 159      * checks are performed, only the neighborhood will be touched.
 160      */
 161     gridpointIndex_ = grid.nearestIndex(coordValue_);
 162 }
 163
 164 void
 165 CoordState::restoreFromHistory(const AwhBiasStateHistory &stateHistory)
 166 {
 167     umbrellaGridpoint_ = stateHistory.umbrellaGridpoint;
 168 }
 169
 170 } // namespace gmx