SparsePcaaQuery.cpp

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#include "storm/modelchecker/multiobjective/pcaa/SparsePcaaQuery.h"
 
#include "storm/adapters/RationalNumberAdapter.h"
#include "storm/environment/modelchecker/MultiObjectiveModelCheckerEnvironment.h"
#include "storm/io/export.h"
#include "storm/modelchecker/multiobjective/MultiObjectivePostprocessing.h"
#include "storm/modelchecker/multiobjective/Objective.h"
#include "storm/models/sparse/MarkovAutomaton.h"
#include "storm/models/sparse/Mdp.h"
#include "storm/models/sparse/StandardRewardModel.h"
#include "storm/settings/SettingsManager.h"
#include "storm/settings/modules/CoreSettings.h"
#include "storm/storage/geometry/Hyperrectangle.h"
#include "storm/utility/constants.h"
#include "storm/utility/vector.h"
 
#include "storm/exceptions/UnexpectedException.h"
 
namespace storm {
namespace modelchecker {
namespace multiobjective {
 
template<class SparseModelType, typename GeometryValueType>
SparsePcaaQuery<SparseModelType, GeometryValueType>::~SparsePcaaQuery() {
    if (storm::settings::getModule<storm::settings::modules::CoreSettings>().isShowStatisticsSet()) {
        STORM_PRINT_AND_LOG("Pareto Curve Approximation Algorithm terminated after " << this->refinementSteps.size() << " refinement steps.\n");
    }
}
 
template<class SparseModelType, typename GeometryValueType>
SparsePcaaQuery<SparseModelType, GeometryValueType>::SparsePcaaQuery(preprocessing::SparseMultiObjectivePreprocessorResult<SparseModelType>& preprocessorResult)
    : originalModel(preprocessorResult.originalModel), originalFormula(preprocessorResult.originalFormula), objectives(preprocessorResult.objectives) {
    this->weightVectorChecker = WeightVectorCheckerFactory<SparseModelType>::create(preprocessorResult);
 
    this->diracWeightVectorsToBeChecked = storm::storage::BitVector(this->objectives.size(), true);
    this->overApproximation = storm::storage::geometry::Polytope<GeometryValueType>::createUniversalPolytope();
    this->underApproximation = storm::storage::geometry::Polytope<GeometryValueType>::createEmptyPolytope();
}
 
template<class SparseModelType, typename GeometryValueType>
typename SparsePcaaQuery<SparseModelType, GeometryValueType>::WeightVector SparsePcaaQuery<SparseModelType, GeometryValueType>::findSeparatingVector(
    Point const& pointToBeSeparated) {
    STORM_LOG_DEBUG("Searching a weight vector to seperate the point given by "
                    << storm::utility::vector::toString(storm::utility::vector::convertNumericVector<double>(pointToBeSeparated)) << ".");
 
    if (underApproximation->isEmpty()) {
        // In this case, every weight vector is separating
        uint_fast64_t objIndex = diracWeightVectorsToBeChecked.getNextSetIndex(0) % pointToBeSeparated.size();
        WeightVector result(pointToBeSeparated.size(), storm::utility::zero<GeometryValueType>());
        result[objIndex] = storm::utility::one<GeometryValueType>();
        diracWeightVectorsToBeChecked.set(objIndex, false);
        return result;
    }
 
    // Reaching this point means that the underApproximation contains halfspaces. The seperating vector has to be the normal vector of one of these halfspaces.
    // We pick one with maximal distance to the given point. However, Dirac weight vectors that only assign a non-zero weight to a single objective take
    // precedence.
    STORM_LOG_ASSERT(!underApproximation->contains(pointToBeSeparated),
                     "Tried to find a separating point but the point is already contained in the underApproximation");
    std::vector<storm::storage::geometry::Halfspace<GeometryValueType>> halfspaces = underApproximation->getHalfspaces();
    uint_fast64_t farestHalfspaceIndex = halfspaces.size();
    GeometryValueType farestDistance = -storm::utility::one<GeometryValueType>();
    bool foundSeparatingDiracVector = false;
    for (uint_fast64_t halfspaceIndex = 0; halfspaceIndex < halfspaces.size(); ++halfspaceIndex) {
        GeometryValueType distance = halfspaces[halfspaceIndex].euclideanDistance(pointToBeSeparated);
        if (!storm::utility::isZero(distance)) {
            storm::storage::BitVector nonZeroVectorEntries = ~storm::utility::vector::filterZero<GeometryValueType>(halfspaces[halfspaceIndex].normalVector());
            bool isSingleObjectiveVector =
                nonZeroVectorEntries.getNumberOfSetBits() == 1 && diracWeightVectorsToBeChecked.get(nonZeroVectorEntries.getNextSetIndex(0));
            // Check if this halfspace is a better candidate than the current one
            if ((!foundSeparatingDiracVector && isSingleObjectiveVector) ||
                (foundSeparatingDiracVector == isSingleObjectiveVector && distance > farestDistance)) {
                foundSeparatingDiracVector = foundSeparatingDiracVector || isSingleObjectiveVector;
                farestHalfspaceIndex = halfspaceIndex;
                farestDistance = distance;
            }
        }
    }
    if (foundSeparatingDiracVector) {
        diracWeightVectorsToBeChecked &= storm::utility::vector::filterZero<GeometryValueType>(halfspaces[farestHalfspaceIndex].normalVector());
    }
 
    STORM_LOG_THROW(farestHalfspaceIndex < halfspaces.size(), storm::exceptions::UnexpectedException, "There is no seperating vector.");
    STORM_LOG_DEBUG("Found separating weight vector: "
                    << storm::utility::vector::toString(storm::utility::vector::convertNumericVector<double>(halfspaces[farestHalfspaceIndex].normalVector()))
                    << ".");
    return halfspaces[farestHalfspaceIndex].normalVector();
}
 
template<class SparseModelType, typename GeometryValueType>
void SparsePcaaQuery<SparseModelType, GeometryValueType>::performRefinementStep(Environment const& env, WeightVector&& direction, bool produceScheduler) {
    // Normalize the direction vector so that the entries sum up to one
    storm::utility::vector::scaleVectorInPlace(
        direction, storm::utility::one<GeometryValueType>() / std::accumulate(direction.begin(), direction.end(), storm::utility::zero<GeometryValueType>()));
    weightVectorChecker->check(env, storm::utility::vector::convertNumericVector<typename SparseModelType::ValueType>(direction));
    STORM_LOG_DEBUG("weighted objectives checker result (under approximation) is " << storm::utility::vector::toString(
                        storm::utility::vector::convertNumericVector<double>(weightVectorChecker->getUnderApproximationOfInitialStateResults())));
    RefinementStep step;
    step.weightVector = direction;
    step.lowerBoundPoint = storm::utility::vector::convertNumericVector<GeometryValueType>(weightVectorChecker->getUnderApproximationOfInitialStateResults());
    step.upperBoundPoint = storm::utility::vector::convertNumericVector<GeometryValueType>(weightVectorChecker->getOverApproximationOfInitialStateResults());
    // For the minimizing objectives, we need to scale the corresponding entries with -1 as we want to consider the downward closure
    for (uint_fast64_t objIndex = 0; objIndex < this->objectives.size(); ++objIndex) {
        if (storm::solver::minimize(this->objectives[objIndex].formula->getOptimalityType())) {
            step.lowerBoundPoint[objIndex] *= -storm::utility::one<GeometryValueType>();
            step.upperBoundPoint[objIndex] *= -storm::utility::one<GeometryValueType>();
        }
    }
    if (produceScheduler) {
        step.scheduler = weightVectorChecker->computeScheduler();
    }
    refinementSteps.push_back(std::move(step));
 
    updateOverApproximation();
    updateUnderApproximation();
}
 
template<class SparseModelType, typename GeometryValueType>
void SparsePcaaQuery<SparseModelType, GeometryValueType>::updateOverApproximation() {
    storm::storage::geometry::Halfspace<GeometryValueType> h(
        refinementSteps.back().weightVector, storm::utility::vector::dotProduct(refinementSteps.back().weightVector, refinementSteps.back().upperBoundPoint));
 
    // Due to numerical issues, it might be the case that the updated overapproximation does not contain the underapproximation,
    // e.g., when the new point is strictly contained in the underapproximation. Check if this is the case.
    GeometryValueType maximumOffset = h.offset();
    for (auto const& step : refinementSteps) {
        maximumOffset = std::max(maximumOffset, storm::utility::vector::dotProduct(h.normalVector(), step.lowerBoundPoint));
    }
    if (maximumOffset > h.offset()) {
        // We correct the issue by shifting the halfspace such that it contains the underapproximation
        h.offset() = maximumOffset;
        STORM_LOG_WARN("Numerical issues: The overapproximation would not contain the underapproximation. Hence, a halfspace is shifted by "
                       << storm::utility::convertNumber<double>(h.invert().euclideanDistance(refinementSteps.back().upperBoundPoint)) << ".");
    }
    overApproximation = overApproximation->intersection(h);
    STORM_LOG_DEBUG("Updated OverApproximation to " << overApproximation->toString(true));
}
 
template<class SparseModelType, typename GeometryValueType>
void SparsePcaaQuery<SparseModelType, GeometryValueType>::updateUnderApproximation() {
    std::vector<Point> paretoPoints;
    paretoPoints.reserve(refinementSteps.size());
    for (auto const& step : refinementSteps) {
        paretoPoints.push_back(step.lowerBoundPoint);
    }
    underApproximation = storm::storage::geometry::Polytope<GeometryValueType>::createDownwardClosure(paretoPoints);
    STORM_LOG_DEBUG("Updated UnderApproximation to " << underApproximation->toString(true));
}
 
template<class SparseModelType, typename GeometryValueType>
bool SparsePcaaQuery<SparseModelType, GeometryValueType>::maxStepsPerformed(Environment const& env) const {
    return env.modelchecker().multi().isMaxStepsSet() && this->refinementSteps.size() >= env.modelchecker().multi().getMaxSteps();
}
 
template<typename SparseModelType, typename GeometryValueType>
void SparsePcaaQuery<SparseModelType, GeometryValueType>::exportPlotOfCurrentApproximation(Environment const& env) const {
    STORM_LOG_ERROR_COND(objectives.size() == 2, "Exporting plot requested but this is only implemented for the two-dimensional case.");
 
    auto transformedUnderApprox = transformObjectivePolytopeToOriginal(this->objectives, underApproximation);
    auto transformedOverApprox = transformObjectivePolytopeToOriginal(this->objectives, overApproximation);
 
    // Get pareto points as well as a hyperrectangle that is used to guarantee that the resulting polytopes are bounded.
    storm::storage::geometry::Hyperrectangle<GeometryValueType> boundaries(
        std::vector<GeometryValueType>(objectives.size(), storm::utility::zero<GeometryValueType>()),
        std::vector<GeometryValueType>(objectives.size(), storm::utility::zero<GeometryValueType>()));
    std::vector<std::vector<GeometryValueType>> paretoPoints;
    paretoPoints.reserve(refinementSteps.size());
    for (auto const& step : refinementSteps) {
        paretoPoints.push_back(transformObjectiveValuesToOriginal(this->objectives, step.lowerBoundPoint));
        boundaries.enlarge(paretoPoints.back());
    }
    auto underApproxVertices = transformedUnderApprox->getVertices();
    for (auto const& v : underApproxVertices) {
        boundaries.enlarge(v);
    }
    auto overApproxVertices = transformedOverApprox->getVertices();
    for (auto const& v : overApproxVertices) {
        boundaries.enlarge(v);
    }
 
    // Further enlarge the boundaries a little
    storm::utility::vector::scaleVectorInPlace(boundaries.lowerBounds(), GeometryValueType(15) / GeometryValueType(10));
    storm::utility::vector::scaleVectorInPlace(boundaries.upperBounds(), GeometryValueType(15) / GeometryValueType(10));
 
    auto boundariesAsPolytope = boundaries.asPolytope();
    std::vector<std::string> columnHeaders = {"x", "y"};
 
    std::vector<std::vector<double>> pointsForPlotting;
    if (env.modelchecker().multi().getPlotPathUnderApproximation()) {
        underApproxVertices = transformedUnderApprox->intersection(boundariesAsPolytope)->getVerticesInClockwiseOrder();
        pointsForPlotting.reserve(underApproxVertices.size());
        for (auto const& v : underApproxVertices) {
            pointsForPlotting.push_back(storm::utility::vector::convertNumericVector<double>(v));
        }
        storm::io::exportDataToCSVFile<double, std::string>(env.modelchecker().multi().getPlotPathUnderApproximation().get(), pointsForPlotting, columnHeaders);
    }
 
    if (env.modelchecker().multi().getPlotPathOverApproximation()) {
        pointsForPlotting.clear();
        overApproxVertices = transformedOverApprox->intersection(boundariesAsPolytope)->getVerticesInClockwiseOrder();
        pointsForPlotting.reserve(overApproxVertices.size());
        for (auto const& v : overApproxVertices) {
            pointsForPlotting.push_back(storm::utility::vector::convertNumericVector<double>(v));
        }
        storm::io::exportDataToCSVFile<double, std::string>(env.modelchecker().multi().getPlotPathOverApproximation().get(), pointsForPlotting, columnHeaders);
    }
 
    if (env.modelchecker().multi().getPlotPathParetoPoints()) {
        pointsForPlotting.clear();
        pointsForPlotting.reserve(paretoPoints.size());
        for (auto const& v : paretoPoints) {
            pointsForPlotting.push_back(storm::utility::vector::convertNumericVector<double>(v));
        }
        storm::io::exportDataToCSVFile<double, std::string>(env.modelchecker().multi().getPlotPathParetoPoints().get(), pointsForPlotting, columnHeaders);
    }
}
 
#ifdef STORM_HAVE_CARL
template class SparsePcaaQuery<storm::models::sparse::Mdp<double>, storm::RationalNumber>;
template class SparsePcaaQuery<storm::models::sparse::MarkovAutomaton<double>, storm::RationalNumber>;
 
template class SparsePcaaQuery<storm::models::sparse::Mdp<storm::RationalNumber>, storm::RationalNumber>;
template class SparsePcaaQuery<storm::models::sparse::MarkovAutomaton<storm::RationalNumber>, storm::RationalNumber>;
#endif
}  // namespace multiobjective
}  // namespace modelchecker
}  // namespace storm