src/gromacs/applied_forces/awh/tests/bias.cpp

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   4  * Copyright (c) 2017,2018,2019,2020,2021, by the GROMACS development team, led by
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  35 #include "gmxpre.h"
  36
  37 #include "gromacs/applied_forces/awh/bias.h"
  38
  39 #include <cmath>
  40
  41 #include <memory>
  42 #include <tuple>
  43 #include <vector>
  44
  45 #include <gmock/gmock.h>
  46 #include <gmock/gmock-matchers.h>
  47 #include <gtest/gtest.h>
  48
  49 #include "gromacs/applied_forces/awh/correlationgrid.h"
  50 #include "gromacs/applied_forces/awh/pointstate.h"
  51 #include "gromacs/mdtypes/awh_params.h"
  52 #include "gromacs/utility/inmemoryserializer.h"
  53 #include "gromacs/utility/stringutil.h"
  54
  55 #include "gromacs/applied_forces/awh/tests/awh_setup.h"
  56 #include "testutils/refdata.h"
  57 #include "testutils/testasserts.h"
  58
  59 namespace gmx
  60 {
  61
  62 namespace test
  63 {
  64
  65 //! Database of 21 test coordinates that represent a trajectory */
  66 constexpr double g_coords[] = { 0.62, 0.70, 0.68, 0.80, 0.93, 0.87, 1.16, 1.14, 0.95, 0.89, 0.91,
  67                                 0.86, 0.88, 0.79, 0.75, 0.82, 0.74, 0.70, 0.68, 0.71, 0.73 };
  68
  69 //! Convenience typedef: growth type enum, potential type enum, disable update skips
  70 typedef std::tuple<AwhHistogramGrowthType, AwhPotentialType, BiasParams::DisableUpdateSkips> BiasTestParameters;
  71
  72 /*! \brief Test fixture for testing Bias updates
  73  */
  74 class BiasTest : public ::testing::TestWithParam<BiasTestParameters>
  75 {
  76 private:
  77     //! Storage for test parameters.
  78     std::unique_ptr<AwhTestParameters> params_;
  79
  80 public:
  81     //! Random seed for AWH MC sampling
  82     int64_t seed_;
  83     //! Coordinates representing a trajectory in time
  84     std::vector<double> coordinates_;
  85     //! The awh Bias
  86     std::unique_ptr<Bias> bias_;
  87
  88     BiasTest() : coordinates_(std::begin(g_coords), std::end(g_coords))
  89     {
  90         /* We test all combinations of:
  91          *   eawhgrowth:
  92          *     eawhgrowthLINEAR:     final, normal update phase
  93          *     ewahgrowthEXP_LINEAR: intial phase, updated size is constant
  94          *   eawhpotential (should only affect the force output):
  95          *     eawhpotentialUMBRELLA:  MC on lambda (umbrella potential location)
  96          *     eawhpotentialCONVOLVED: MD on a convolved potential landscape
  97          *   disableUpdateSkips (should not affect the results):
  98          *     BiasParams::DisableUpdateSkips::yes: update the point state for every sample
  99          *     BiasParams::DisableUpdateSkips::no:  update the point state at an interval > 1 sample
 100          *
 101          * Note: It would be nice to explicitly check that eawhpotential
 102          *       and disableUpdateSkips do not affect the point state.
 103          *       But the reference data will also ensure this.
 104          */
 105         AwhHistogramGrowthType         eawhgrowth;
 106         AwhPotentialType               eawhpotential;
 107         BiasParams::DisableUpdateSkips disableUpdateSkips;
 108         std::tie(eawhgrowth, eawhpotential, disableUpdateSkips) = GetParam();
 109
 110         /* Set up a basic AWH setup with a single, 1D bias with parameters
 111          * such that we can measure the effects of different parameters.
 112          * The idea is to, among other things, have part of the interval
 113          * not covered by samples.
 114          */
 115         auto awhDimBuffer   = awhDimParamSerialized();
 116         auto awhDimArrayRef = gmx::arrayRefFromArray(&awhDimBuffer, 1);
 117         params_             = std::make_unique<AwhTestParameters>(getAwhTestParameters(
 118                 eawhgrowth, eawhpotential, awhDimArrayRef, false, 0.4, false, 0.5, 0));
 119
 120         seed_ = params_->awhParams.seed();
 121
 122         constexpr double mdTimeStep = 0.1;
 123
 124         int numSamples = coordinates_.size() - 1; // No sample taken at step 0
 125         GMX_RELEASE_ASSERT(numSamples % params_->awhParams.numSamplesUpdateFreeEnergy() == 0,
 126                            "This test is intended to reproduce the situation when the might need "
 127                            "to write output during a normal AWH run, therefore the number of "
 128                            "samples should be a multiple of the free-energy update interval (but "
 129                            "the test should also runs fine without this condition).");
 130
 131         bias_ = std::make_unique<Bias>(-1,
 132                                        params_->awhParams,
 133                                        params_->awhParams.awhBiasParams()[0],
 134                                        params_->dimParams,
 135                                        params_->beta,
 136                                        mdTimeStep,
 137                                        1,
 138                                        "",
 139                                        Bias::ThisRankWillDoIO::No,
 140                                        disableUpdateSkips);
 141     }
 142 };
 143
 144 TEST_P(BiasTest, ForcesBiasPmf)
 145 {
 146     gmx::test::TestReferenceData    data;
 147     gmx::test::TestReferenceChecker checker(data.rootChecker());
 148
 149     Bias& bias = *bias_;
 150
 151     /* Make strings with the properties we expect to be different in the tests.
 152      * These also helps to interpret the reference data.
 153      */
 154     std::vector<std::string> props;
 155     props.push_back(formatString("stage:           %s", bias.state().inInitialStage() ? "initial" : "final"));
 156     props.push_back(formatString("convolve forces: %s", bias.params().convolveForce ? "yes" : "no"));
 157     props.push_back(formatString("skip updates:    %s", bias.params().skipUpdates() ? "yes" : "no"));
 158
 159     SCOPED_TRACE(gmx::formatString("%s, %s, %s", props[0].c_str(), props[1].c_str(), props[2].c_str()));
 160
 161     std::vector<double> force, pot, potJump;
 162
 163     double  coordMaxValue = 0;
 164     double  potentialJump = 0;
 165     int64_t step          = 0;
 166     for (auto& coord : coordinates_)
 167     {
 168         coordMaxValue = std::max(coordMaxValue, std::abs(coord));
 169
 170         awh_dvec                    coordValue = { coord, 0, 0, 0 };
 171         double                      potential  = 0;
 172         gmx::ArrayRef<const double> biasForce  = bias.calcForceAndUpdateBias(
 173                 coordValue, {}, {}, &potential, &potentialJump, nullptr, nullptr, step, step, seed_, nullptr);
 174
 175         force.push_back(biasForce[0]);
 176         pot.push_back(potential);
 177         potJump.push_back(potentialJump);
 178
 179         step++;
 180     }
 181
 182     /* When skipping updates, ensure all skipped updates are performed here.
 183      * This should result in the same bias state as at output in a normal run.
 184      */
 185     if (bias.params().skipUpdates())
 186     {
 187         bias.doSkippedUpdatesForAllPoints();
 188     }
 189
 190     std::vector<double> pointBias, logPmfsum;
 191     for (const auto& point : bias.state().points())
 192     {
 193         pointBias.push_back(point.bias());
 194         logPmfsum.push_back(point.logPmfSum());
 195     }
 196
 197     /* The umbrella force is computed from the coordinate deviation.
 198      * In taking this deviation we lose a lot of precision, so we should
 199      * compare against k*max(coord) instead of the instantaneous force.
 200      */
 201     const double kCoordMax = bias.dimParams()[0].pullDimParams().k * coordMaxValue;
 202
 203     constexpr int ulpTol = 10;
 204
 205     checker.checkSequence(props.begin(), props.end(), "Properties");
 206     checker.setDefaultTolerance(absoluteTolerance(kCoordMax * GMX_DOUBLE_EPS * ulpTol));
 207     checker.checkSequence(force.begin(), force.end(), "Force");
 208     checker.checkSequence(pot.begin(), pot.end(), "Potential");
 209     checker.checkSequence(potJump.begin(), potJump.end(), "PotentialJump");
 210     checker.setDefaultTolerance(relativeToleranceAsUlp(1.0, ulpTol));
 211     checker.checkSequence(pointBias.begin(), pointBias.end(), "PointBias");
 212     checker.checkSequence(logPmfsum.begin(), logPmfsum.end(), "PointLogPmfsum");
 213 }
 214
 215 /* Scan initial/final phase, MC/convolved force and update skip (not) allowed
 216  * Both the convolving and skipping should not affect the bias and PMF.
 217  * It would be nice if the test would explicitly check for this.
 218  * Currently this is tested through identical reference data.
 219  */
 220 INSTANTIATE_TEST_CASE_P(WithParameters,
 221                         BiasTest,
 222                         ::testing::Combine(::testing::Values(AwhHistogramGrowthType::Linear,
 223                                                              AwhHistogramGrowthType::ExponentialLinear),
 224                                            ::testing::Values(AwhPotentialType::Umbrella,
 225                                                              AwhPotentialType::Convolved),
 226                                            ::testing::Values(BiasParams::DisableUpdateSkips::yes,
 227                                                              BiasParams::DisableUpdateSkips::no)));
 228
 229 // Test that we detect coverings and exit the initial stage at the correct step
 230 TEST(BiasTest, DetectsCovering)
 231 {
 232     const std::vector<char> serializedAwhParametersPerDim = awhDimParamSerialized();
 233     auto awhDimArrayRef            = gmx::arrayRefFromArray(&serializedAwhParametersPerDim, 1);
 234     const AwhTestParameters params = getAwhTestParameters(AwhHistogramGrowthType::ExponentialLinear,
 235                                                           AwhPotentialType::Convolved,
 236                                                           awhDimArrayRef,
 237                                                           false,
 238                                                           0.4,
 239                                                           false,
 240                                                           0.5,
 241                                                           0);
 242     const AwhDimParams&     awhDimParams = params.awhParams.awhBiasParams()[0].dimParams()[0];
 243
 244     constexpr double mdTimeStep = 0.1;
 245
 246     Bias bias(-1,
 247               params.awhParams,
 248               params.awhParams.awhBiasParams()[0],
 249               params.dimParams,
 250               params.beta,
 251               mdTimeStep,
 252               1,
 253               "",
 254               Bias::ThisRankWillDoIO::No);
 255
 256     /* We use a trajectory of the sum of two sines to cover the reaction
 257      * coordinate range in a semi-realistic way. The period is 4*pi=12.57.
 258      * We get out of the initial stage after 4 coverings at step 300.
 259      */
 260     constexpr int64_t exitStepRef = 300;
 261     const double      midPoint    = 0.5 * (awhDimParams.end() + awhDimParams.origin());
 262     const double      halfWidth   = 0.5 * (awhDimParams.end() - awhDimParams.origin());
 263
 264     bool inInitialStage = bias.state().inInitialStage();
 265     /* Normally this loop exits at exitStepRef, but we extend with failure */
 266     int64_t step;
 267     for (step = 0; step <= 2 * exitStepRef; step++)
 268     {
 269         double t     = step * mdTimeStep;
 270         double coord = midPoint + halfWidth * (0.5 * std::sin(t) + 0.55 * std::sin(1.5 * t));
 271
 272         awh_dvec coordValue    = { coord, 0, 0, 0 };
 273         double   potential     = 0;
 274         double   potentialJump = 0;
 275         bias.calcForceAndUpdateBias(coordValue,
 276                                     {},
 277                                     {},
 278                                     &potential,
 279                                     &potentialJump,
 280                                     nullptr,
 281                                     nullptr,
 282                                     step,
 283                                     step,
 284                                     params.awhParams.seed(),
 285                                     nullptr);
 286
 287         inInitialStage = bias.state().inInitialStage();
 288         if (!inInitialStage)
 289         {
 290             break;
 291         }
 292     }
 293
 294     EXPECT_EQ(false, inInitialStage);
 295     if (!inInitialStage)
 296     {
 297         EXPECT_EQ(exitStepRef, step);
 298     }
 299 }
 300
 301 } // namespace test
 302 } // namespace gmx