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ModelInstantiator + test

Former-commit-id: f3c9980067
tempestpy_adaptions
TimQu 9 years ago
parent
commit
6e8602413e
  1. 2
      src/models/sparse/StochasticTwoPlayerGame.cpp
  2. 161
      src/utility/ModelInstantiator.cpp
  3. 158
      src/utility/ModelInstantiator.h
  4. 266
      test/functional/utility/ModelInstantiatorTest.cpp
  5. 146
      test/functional/utility/brp16_2.pm
  6. 56
      test/functional/utility/coin2_2.pm

2
src/models/sparse/StochasticTwoPlayerGame.cpp

@ -65,7 +65,7 @@ namespace storm {
// template class StochasticTwoPlayerGame<float>;
#ifdef STORM_HAVE_CARL
// template class StochasticTwoPlayerGame<storm::RationalFunction>;
template class StochasticTwoPlayerGame<storm::RationalFunction>;
#endif
} // namespace sparse

161
src/utility/ModelInstantiator.cpp

@ -0,0 +1,161 @@
/*
* File: ModelInstantiator.cpp
* Author: Tim Quatmann
*
* Created on February 23, 2016
*/
#include "src/utility/ModelInstantiator.h"
#include "src/models/sparse/StandardRewardModel.h"
namespace storm {
namespace utility {
template<typename ParametricSparseModelType, typename ConstantSparseModelType>
ModelInstantiator<ParametricSparseModelType, ConstantSparseModelType>::ModelInstantiator(ParametricSparseModelType const& parametricModel){
//Now pre-compute the information for the equation system.
initializeModelSpecificData(parametricModel);
initializeMatrixMapping(this->instantiatedModel->getTransitionMatrix(), this->functions, this->matrixMapping, parametricModel.getTransitionMatrix());
for(auto& rewModel : this->instantiatedModel->getRewardModels()) {
if(rewModel.second.hasStateRewards()){
initializeVectorMapping(rewModel.second.getStateRewardVector(), this->functions, this->vectorMapping, parametricModel.getRewardModel(rewModel.first).getStateRewardVector());
}
if(rewModel.second.hasStateActionRewards()){
initializeVectorMapping(rewModel.second.getStateActionRewardVector(), this->functions, this->vectorMapping, parametricModel.getRewardModel(rewModel.first).getStateActionRewardVector());
}
if(rewModel.second.hasTransitionRewards()){
initializeMatrixMapping(rewModel.second.getTransitionRewardMatrix(), this->functions, this->matrixMapping, parametricModel.getRewardModel(rewModel.first).getTransitionRewardMatrix());
}
}
}
template<typename ParametricSparseModelType, typename ConstantType>
ModelInstantiator<ParametricSparseModelType, ConstantType>::~ModelInstantiator() {
//Intentionally left empty
}
template<typename ParametricSparseModelType, typename ConstantSparseModelType>
storm::storage::SparseMatrix<typename ConstantSparseModelType::ValueType> ModelInstantiator<ParametricSparseModelType, ConstantSparseModelType>::buildDummyMatrix(storm::storage::SparseMatrix<ParametricType> const& parametricMatrix) const{
storm::storage::SparseMatrixBuilder<ConstantType> matrixBuilder(parametricMatrix.getRowCount(),
parametricMatrix.getColumnCount(),
parametricMatrix.getEntryCount(),
true, // no force dimensions
true, //Custom row grouping
parametricMatrix.getRowGroupCount());
for(std::size_t rowGroup = 0; rowGroup < parametricMatrix.getRowGroupCount(); ++rowGroup){
matrixBuilder.newRowGroup(parametricMatrix.getRowGroupIndices()[rowGroup]);
for(std::size_t row = parametricMatrix.getRowGroupIndices()[rowGroup]; row < parametricMatrix.getRowGroupIndices()[rowGroup+1]; ++row){
ConstantType dummyValue = storm::utility::one<ConstantType>();
for(auto const& paramEntry : parametricMatrix.getRow(row)){
matrixBuilder.addNextValue(row, paramEntry.getColumn(), dummyValue);
dummyValue = storm::utility::zero<ConstantType>();
}
}
}
return matrixBuilder.build();
}
template<typename ParametricSparseModelType, typename ConstantSparseModelType>
std::unordered_map<std::string, typename ConstantSparseModelType::RewardModelType> ModelInstantiator<ParametricSparseModelType, ConstantSparseModelType>::buildDummyRewardModels(std::unordered_map<std::string, typename ParametricSparseModelType::RewardModelType> const& parametricRewardModel) const {
std::unordered_map<std::string, typename ConstantSparseModelType::RewardModelType> result;
for(auto const& paramRewardModel : parametricRewardModel){
auto const& rewModel = paramRewardModel.second;
boost::optional<std::vector<ConstantType>> optionalStateRewardVector;
if(rewModel.hasStateRewards()) {
optionalStateRewardVector = std::vector<ConstantType>(rewModel.getStateRewardVector().size());
}
boost::optional<std::vector<ConstantType>> optionalStateActionRewardVector;
if(rewModel.hasStateActionRewards()) {
optionalStateActionRewardVector = std::vector<ConstantType>(rewModel.getStateActionRewardVector().size());
}
boost::optional<storm::storage::SparseMatrix<ConstantType>> optionalTransitionRewardMatrix;
if(rewModel.hasTransitionRewards()) {
optionalTransitionRewardMatrix = buildDummyMatrix(rewModel.getTransitionRewardMatrix());
}
result.insert(std::make_pair(paramRewardModel.first,
storm::models::sparse::StandardRewardModel<ConstantType>(std::move(optionalStateRewardVector), std::move(optionalStateActionRewardVector), std::move(optionalTransitionRewardMatrix))
));
}
return result;
}
template<typename ParametricSparseModelType, typename ConstantSparseModelType>
void ModelInstantiator<ParametricSparseModelType, ConstantSparseModelType>::initializeMatrixMapping(storm::storage::SparseMatrix<ConstantType>& constantMatrix,
std::unordered_map<ParametricType, ConstantType>& functions,
std::vector<std::pair<typename storm::storage::SparseMatrix<ConstantType>::iterator, ConstantType*>>& mapping,
storm::storage::SparseMatrix<ParametricType> const& parametricMatrix) const{
ConstantType dummyValue = storm::utility::one<ConstantType>();
auto constantEntryIt = constantMatrix.begin();
auto parametricEntryIt = parametricMatrix.begin();
while(parametricEntryIt != parametricMatrix.end()){
STORM_LOG_ASSERT(parametricEntryIt->getColumn() == constantEntryIt->getColumn(), "Entries of parametric and constant matrix are not at the same position");
if(storm::utility::isConstant(parametricEntryIt->getValue())){
//Constant entries can be inserted directly
constantEntryIt->setValue(storm::utility::convertNumber<ConstantType>(storm::utility::parametric::getConstantPart(parametricEntryIt->getValue())));
} else {
//insert the new function and store that the current constantMatrix entry needs to be set to the value of this function
auto functionsIt = functions.insert(std::make_pair(parametricEntryIt->getValue(), dummyValue)).first;
mapping.emplace_back(std::make_pair(constantEntryIt, &(functionsIt->second)));
//Note that references to elements of an unordered map remain valid after calling unordered_map::insert.
}
++constantEntryIt;
++parametricEntryIt;
}
STORM_LOG_ASSERT(constantEntryIt == constantMatrix.end(), "Parametric matrix seems to have more or less entries then the constant matrix");
//TODO: is this necessary?
constantMatrix.updateNonzeroEntryCount();
}
template<typename ParametricSparseModelType, typename ConstantSparseModelType>
void ModelInstantiator<ParametricSparseModelType, ConstantSparseModelType>::initializeVectorMapping(std::vector<ConstantType>& constantVector,
std::unordered_map<ParametricType, ConstantType>& functions,
std::vector<std::pair<typename std::vector<ConstantType>::iterator, ConstantType*>>& mapping,
std::vector<ParametricType> const& parametricVector) const{
ConstantType dummyValue = storm::utility::one<ConstantType>();
auto constantEntryIt = constantVector.begin();
auto parametricEntryIt = parametricVector.begin();
while(parametricEntryIt != parametricVector.end()){
if(storm::utility::isConstant(storm::utility::simplify(*parametricEntryIt))){
//Constant entries can be inserted directly
*constantEntryIt = storm::utility::convertNumber<ConstantType>(storm::utility::parametric::getConstantPart(*parametricEntryIt));
} else {
//insert the new function and store that the current constantVector entry needs to be set to the value of this function
auto functionsIt = functions.insert(std::make_pair(*parametricEntryIt, dummyValue)).first;
mapping.emplace_back(std::make_pair(constantEntryIt, &(functionsIt->second)));
//Note that references to elements of an unordered map remain valid after calling unordered_map::insert.
}
++constantEntryIt;
++parametricEntryIt;
}
STORM_LOG_ASSERT(constantEntryIt == constantVector.end(), "Parametric vector seems to have more or less entries then the constant vector");
}
template<typename ParametricSparseModelType, typename ConstantSparseModelType>
ConstantSparseModelType const& ModelInstantiator<ParametricSparseModelType, ConstantSparseModelType>::instantiate(std::map<VariableType, CoefficientType>const& valuation){
//Write results into the placeholders
for(auto& functionResult : this->functions){
functionResult.second=storm::utility::convertNumber<ConstantType>(
storm::utility::parametric::evaluate(functionResult.first, valuation));
}
//Write the instantiated values to the matrices and vectors according to the stored mappings
for(auto& entryValuePair : this->matrixMapping){
entryValuePair.first->setValue(*(entryValuePair.second));
}
for(auto& entryValuePair : this->vectorMapping){
*(entryValuePair.first)=*(entryValuePair.second);
}
return *this->instantiatedModel;
}
#ifdef STORM_HAVE_CARL
template class ModelInstantiator<storm::models::sparse::Dtmc<storm::RationalFunction>, storm::models::sparse::Dtmc<double>>;
template class ModelInstantiator<storm::models::sparse::Mdp<storm::RationalFunction>, storm::models::sparse::Mdp<double>>;
template class ModelInstantiator<storm::models::sparse::Ctmc<storm::RationalFunction>, storm::models::sparse::Ctmc<double>>;
template class ModelInstantiator<storm::models::sparse::MarkovAutomaton<storm::RationalFunction>, storm::models::sparse::MarkovAutomaton<double>>;
template class ModelInstantiator<storm::models::sparse::StochasticTwoPlayerGame<storm::RationalFunction>, storm::models::sparse::StochasticTwoPlayerGame<double>>;
#endif
} //namespace utility
} //namespace storm

158
src/utility/ModelInstantiator.h

@ -0,0 +1,158 @@
/*
* File: ModelInstantiator.h
* Author: Tim Quatmann
*
* Created on February 23, 2016
*/
#ifndef STORM_UTILITY_MODELINSTANTIATOR_H
#define STORM_UTILITY_MODELINSTANTIATOR_H
#include <unordered_map>
#include <memory>
#include <type_traits>
#include "src/models/sparse/Dtmc.h"
#include "src/models/sparse/Mdp.h"
#include "src/models/sparse/Ctmc.h"
#include "src/models/sparse/MarkovAutomaton.h"
#include "src/models/sparse/StochasticTwoPlayerGame.h"
#include "src/utility/parametric.h"
#include "src/utility/constants.h"
namespace storm {
namespace utility{
/*!
* This class allows efficient instantiation of the given parametric model.
* The key to efficiency is to evaluate every distinct transition- (or reward-) function only once
* instead of evaluating the same function for each occurrence in the model.
*/
template<typename ParametricSparseModelType, typename ConstantSparseModelType>
class ModelInstantiator {
public:
typedef typename ParametricSparseModelType::ValueType ParametricType;
typedef typename storm::utility::parametric::VariableType<ParametricType>::type VariableType;
typedef typename storm::utility::parametric::CoefficientType<ParametricType>::type CoefficientType;
typedef typename ConstantSparseModelType::ValueType ConstantType;
/*!
* Constructs a ModelInstantiator
* @param parametricModel The model that is to be instantiated
*/
ModelInstantiator(ParametricSparseModelType const& parametricModel);
/*!
* Destructs the ModelInstantiator
*/
virtual ~ModelInstantiator();
/*!
* Evaluates the occurring parametric functions and retrieves the instantiated model
* @param valuation Maps each occurring variables to the value with which it should be substituted
* @return The instantiated model
*/
ConstantSparseModelType const& instantiate(std::map<VariableType, CoefficientType>const& valuation);
private:
/*!
* Initializes the instantiatedModel with dummy data by considering the model-specific ingredients.
* Also initializes other model-specific data, e.g., the exitRate vector of a markov automaton
*/
template<typename PMT = ParametricSparseModelType>
typename std::enable_if<
std::is_same<PMT,storm::models::sparse::Dtmc<typename ParametricSparseModelType::ValueType>>::value ||
std::is_same<PMT,storm::models::sparse::Mdp<typename ParametricSparseModelType::ValueType>>::value ||
std::is_same<PMT,storm::models::sparse::Ctmc<typename ParametricSparseModelType::ValueType>>::value
>::type
initializeModelSpecificData(PMT const& parametricModel) {
auto stateLabelingCopy = parametricModel.getStateLabeling();
auto choiceLabelingCopy = parametricModel.getOptionalChoiceLabeling();
this->instantiatedModel = std::make_shared<ConstantSparseModelType>(buildDummyMatrix(parametricModel.getTransitionMatrix()), std::move(stateLabelingCopy), buildDummyRewardModels(parametricModel.getRewardModels()), std::move(choiceLabelingCopy));
}
template<typename PMT = ParametricSparseModelType>
typename std::enable_if<
std::is_same<PMT,storm::models::sparse::MarkovAutomaton<typename ParametricSparseModelType::ValueType>>::value
>::type
initializeModelSpecificData(PMT const& parametricModel) {
auto stateLabelingCopy = parametricModel.getStateLabeling();
auto markovianStatesCopy = parametricModel.getMarkovianStates();
auto choiceLabelingCopy = parametricModel.getOptionalChoiceLabeling();
std::vector<ConstantType> exitRates(parametricModel.getExitRates().size(), storm::utility::one<ConstantType>());
this->instantiatedModel = std::make_shared<ConstantSparseModelType>(buildDummyMatrix(parametricModel.getTransitionMatrix()), std::move(stateLabelingCopy), std::move(markovianStatesCopy), std::move(exitRates), buildDummyRewardModels(parametricModel.getRewardModels()), std::move(choiceLabelingCopy));
initializeVectorMapping(this->instantiatedModel->getExitRates(), this->functions, this->vectorMapping, parametricModel.getExitRates());
}
template<typename PMT = ParametricSparseModelType>
typename std::enable_if<
std::is_same<PMT,storm::models::sparse::StochasticTwoPlayerGame<typename ParametricSparseModelType::ValueType>>::value
>::type
initializeModelSpecificData(PMT const& parametricModel) {
auto player1MatrixCopy = parametricModel.getPlayer1Matrix();
auto stateLabelingCopy = parametricModel.getStateLabeling();
boost::optional<std::vector<typename storm::models::sparse::LabelSet>> player1ChoiceLabeling, player2ChoiceLabeling;
if(parametricModel.hasPlayer1ChoiceLabeling()) player1ChoiceLabeling = parametricModel.getPlayer1ChoiceLabeling();
if(parametricModel.hasPlayer2ChoiceLabeling()) player2ChoiceLabeling = parametricModel.getPlayer2ChoiceLabeling();
this->instantiatedModel = std::make_shared<ConstantSparseModelType>(std::move(player1MatrixCopy), buildDummyMatrix(parametricModel.getTransitionMatrix()), std::move(stateLabelingCopy), buildDummyRewardModels(parametricModel.getRewardModels()), std::move(player1ChoiceLabeling), std::move(player2ChoiceLabeling));
}
/*!
* Creates a matrix that has entries at the same position as the given matrix.
* The returned matrix is a stochastic matrix, i.e., the rows sum up to one.
*/
storm::storage::SparseMatrix<ConstantType> buildDummyMatrix(storm::storage::SparseMatrix<ParametricType> const& parametricMatrix) const;
/*!
* Creates a copy of the given reward models with the same names and with state(action)rewards / transitionrewards having the same entry-count and entry-positions.
*/
std::unordered_map<std::string, typename ConstantSparseModelType::RewardModelType> buildDummyRewardModels(std::unordered_map<std::string, typename ParametricSparseModelType::RewardModelType> const& parametricRewardModel) const;
/*!
* Connects the occurring functions with the corresponding matrix entries
*
* @note constantMatrix and parametricMatrix should have entries at the same positions
*
* @param constantMatrix The matrix to which the evaluation results are written
* @param functions Occurring functions are inserted in this map
* @param mapping The connections of functions to matrix entries are push_backed into this
* @param parametricMatrix the source matrix with the functions to consider.
*/
void initializeMatrixMapping(storm::storage::SparseMatrix<ConstantType>& constantMatrix,
std::unordered_map<ParametricType, ConstantType>& functions,
std::vector<std::pair<typename storm::storage::SparseMatrix<ConstantType>::iterator, ConstantType*>>& mapping,
storm::storage::SparseMatrix<ParametricType> const& parametricMatrix) const;
/*!
* Connects the occurring functions with the corresponding vector entries
*
* @note constantVector and parametricVector should have the same size
*
* @param constantVector The vector to which the evaluation results are written
* @param functions Occurring functions with their placeholders are inserted in this map
* @param mapping The connections of functions to vector entries are push_backed into this
* @param parametricVector the source vector with the functions to consider.
*/
void initializeVectorMapping(std::vector<ConstantType>& constantVector,
std::unordered_map<ParametricType, ConstantType>& functions,
std::vector<std::pair<typename std::vector<ConstantType>::iterator, ConstantType*>>& mapping,
std::vector<ParametricType> const& parametricVector) const;
/// The resulting model
std::shared_ptr<ConstantSparseModelType> instantiatedModel;
/// the occurring functions together with the corresponding placeholders for their evaluated result
std::unordered_map<ParametricType, ConstantType> functions;
/// Connection of matrix entries with placeholders
std::vector<std::pair<typename storm::storage::SparseMatrix<ConstantType>::iterator, ConstantType*>> matrixMapping;
/// Connection of Vector entries with placeholders
std::vector<std::pair<typename std::vector<ConstantType>::iterator, ConstantType*>> vectorMapping;
};
}//Namespace utility
} //namespace storm
#endif /* STORM_UTILITY_MODELINSTANTIATOR_H */

266
test/functional/utility/ModelInstantiatorTest.cpp

@ -0,0 +1,266 @@
#include "gtest/gtest.h"
#include "storm-config.h"
#ifdef STORM_HAVE_CARL
#include "src/adapters/CarlAdapter.h"
#include<carl/numbers/numbers.h>
#include<carl/core/VariablePool.h>
#include "src/settings/SettingsManager.h"
#include "src/settings/modules/GeneralSettings.h"
#include "utility/storm.h"
#include "utility/ModelInstantiator.h"
#include "src/models/sparse/Model.h"
#include "src/models/sparse/Dtmc.h"
#include "src/models/sparse/Mdp.h"
TEST(ModelInstantiatorTest, Brp_Prob) {
carl::VariablePool::getInstance().clear();
std::string const& programFile = STORM_CPP_TESTS_BASE_PATH "/functional/utility/brp16_2.pm";
std::string const& formulaAsString = "P=? [F s=5 ]";
std::string const& constantsAsString = ""; //e.g. pL=0.9,TOACK=0.5
// Program and formula
storm::prism::Program program = storm::parseProgram(programFile);
program.checkValidity();
std::vector<std::shared_ptr<storm::logic::Formula>> formulas = storm::parseFormulasForProgram(formulaAsString, program);
ASSERT_TRUE(formulas.size()==1);
// Parametric model
typename storm::builder::ExplicitPrismModelBuilder<storm::RationalFunction>::Options options = storm::builder::ExplicitPrismModelBuilder<storm::RationalFunction>::Options(*formulas[0]);
options.addConstantDefinitionsFromString(program, constantsAsString);
options.preserveFormula(*formulas[0]);
std::shared_ptr<storm::models::sparse::Dtmc<storm::RationalFunction>> dtmc = storm::builder::ExplicitPrismModelBuilder<storm::RationalFunction>().translateProgram(program, options)->as<storm::models::sparse::Dtmc<storm::RationalFunction>>();
storm::utility::ModelInstantiator<storm::models::sparse::Dtmc<storm::RationalFunction>, storm::models::sparse::Dtmc<double>> modelInstantiator(*dtmc);
EXPECT_FALSE(dtmc->hasRewardModel());
{
std::map<storm::Variable, storm::RationalNumber> valuation;
storm::Variable const& pL = carl::VariablePool::getInstance().findVariableWithName("pL");
ASSERT_NE(pL, carl::Variable::NO_VARIABLE);
storm::Variable const& pK = carl::VariablePool::getInstance().findVariableWithName("pK");
ASSERT_NE(pK, carl::Variable::NO_VARIABLE);
valuation.insert(std::make_pair(pL,carl::rationalize<storm::RationalNumber>(0.8)));
valuation.insert(std::make_pair(pK,carl::rationalize<storm::RationalNumber>(0.9)));
storm::models::sparse::Dtmc<double> const& instantiated(modelInstantiator.instantiate(valuation));
ASSERT_EQ(dtmc->getTransitionMatrix().getRowGroupIndices(), instantiated.getTransitionMatrix().getRowGroupIndices());
for(std::size_t rowGroup = 0; rowGroup < dtmc->getTransitionMatrix().getRowGroupCount(); ++rowGroup){
for(std::size_t row = dtmc->getTransitionMatrix().getRowGroupIndices()[rowGroup]; row < dtmc->getTransitionMatrix().getRowGroupIndices()[rowGroup+1]; ++row){
auto instantiatedEntry = instantiated.getTransitionMatrix().getRow(row).begin();
for(auto const& paramEntry : dtmc->getTransitionMatrix().getRow(row)){
EXPECT_EQ(paramEntry.getColumn(), instantiatedEntry->getColumn());
double evaluatedValue = carl::toDouble(paramEntry.getValue().evaluate(valuation));
EXPECT_EQ(evaluatedValue, instantiatedEntry->getValue());
++instantiatedEntry;
}
EXPECT_EQ(instantiated.getTransitionMatrix().getRow(row).end(),instantiatedEntry);
}
}
EXPECT_EQ(dtmc->getStateLabeling(), instantiated.getStateLabeling());
EXPECT_EQ(dtmc->getOptionalChoiceLabeling(), instantiated.getOptionalChoiceLabeling());
storm::modelchecker::SparseDtmcPrctlModelChecker<storm::models::sparse::Dtmc<double>> modelchecker(instantiated);
std::unique_ptr<storm::modelchecker::CheckResult> chkResult = modelchecker.check(*formulas[0]);
storm::modelchecker::ExplicitQuantitativeCheckResult<double>& quantitativeChkResult = chkResult->asExplicitQuantitativeCheckResult<double>();
EXPECT_NEAR(0.2989278941, quantitativeChkResult[*instantiated.getInitialStates().begin()], storm::settings::generalSettings().getPrecision());
}
{
std::map<storm::Variable, storm::RationalNumber> valuation;
storm::Variable const& pL = carl::VariablePool::getInstance().findVariableWithName("pL");
ASSERT_NE(pL, carl::Variable::NO_VARIABLE);
storm::Variable const& pK = carl::VariablePool::getInstance().findVariableWithName("pK");
ASSERT_NE(pK, carl::Variable::NO_VARIABLE);
valuation.insert(std::make_pair(pL,carl::rationalize<storm::RationalNumber>(1)));
valuation.insert(std::make_pair(pK,carl::rationalize<storm::RationalNumber>(1)));
storm::models::sparse::Dtmc<double> const& instantiated(modelInstantiator.instantiate(valuation));
ASSERT_EQ(dtmc->getTransitionMatrix().getRowGroupIndices(), instantiated.getTransitionMatrix().getRowGroupIndices());
for(std::size_t rowGroup = 0; rowGroup < dtmc->getTransitionMatrix().getRowGroupCount(); ++rowGroup){
for(std::size_t row = dtmc->getTransitionMatrix().getRowGroupIndices()[rowGroup]; row < dtmc->getTransitionMatrix().getRowGroupIndices()[rowGroup+1]; ++row){
auto instantiatedEntry = instantiated.getTransitionMatrix().getRow(row).begin();
for(auto const& paramEntry : dtmc->getTransitionMatrix().getRow(row)){
EXPECT_EQ(paramEntry.getColumn(), instantiatedEntry->getColumn());
double evaluatedValue = carl::toDouble(paramEntry.getValue().evaluate(valuation));
EXPECT_EQ(evaluatedValue, instantiatedEntry->getValue());
++instantiatedEntry;
}
EXPECT_EQ(instantiated.getTransitionMatrix().getRow(row).end(),instantiatedEntry);
}
}
EXPECT_EQ(dtmc->getStateLabeling(), instantiated.getStateLabeling());
EXPECT_EQ(dtmc->getOptionalChoiceLabeling(), instantiated.getOptionalChoiceLabeling());
storm::modelchecker::SparseDtmcPrctlModelChecker<storm::models::sparse::Dtmc<double>> modelchecker(instantiated);
std::unique_ptr<storm::modelchecker::CheckResult> chkResult = modelchecker.check(*formulas[0]);
storm::modelchecker::ExplicitQuantitativeCheckResult<double>& quantitativeChkResult = chkResult->asExplicitQuantitativeCheckResult<double>();
EXPECT_EQ(0.0 , quantitativeChkResult[*instantiated.getInitialStates().begin()]);
}
{
std::map<storm::Variable, storm::RationalNumber> valuation;
storm::Variable const& pL = carl::VariablePool::getInstance().findVariableWithName("pL");
ASSERT_NE(pL, carl::Variable::NO_VARIABLE);
storm::Variable const& pK = carl::VariablePool::getInstance().findVariableWithName("pK");
ASSERT_NE(pK, carl::Variable::NO_VARIABLE);
valuation.insert(std::make_pair(pL,carl::rationalize<storm::RationalNumber>(1)));
valuation.insert(std::make_pair(pK,carl::rationalize<storm::RationalNumber>(0.9)));
storm::models::sparse::Dtmc<double> const& instantiated(modelInstantiator.instantiate(valuation));
ASSERT_EQ(dtmc->getTransitionMatrix().getRowGroupIndices(), instantiated.getTransitionMatrix().getRowGroupIndices());
for(std::size_t rowGroup = 0; rowGroup < dtmc->getTransitionMatrix().getRowGroupCount(); ++rowGroup){
for(std::size_t row = dtmc->getTransitionMatrix().getRowGroupIndices()[rowGroup]; row < dtmc->getTransitionMatrix().getRowGroupIndices()[rowGroup+1]; ++row){
auto instantiatedEntry = instantiated.getTransitionMatrix().getRow(row).begin();
for(auto const& paramEntry : dtmc->getTransitionMatrix().getRow(row)){
EXPECT_EQ(paramEntry.getColumn(), instantiatedEntry->getColumn());
double evaluatedValue = carl::toDouble(paramEntry.getValue().evaluate(valuation));
EXPECT_EQ(evaluatedValue, instantiatedEntry->getValue());
++instantiatedEntry;
}
EXPECT_EQ(instantiated.getTransitionMatrix().getRow(row).end(),instantiatedEntry);
}
}
EXPECT_EQ(dtmc->getStateLabeling(), instantiated.getStateLabeling());
EXPECT_EQ(dtmc->getOptionalChoiceLabeling(), instantiated.getOptionalChoiceLabeling());
storm::modelchecker::SparseDtmcPrctlModelChecker<storm::models::sparse::Dtmc<double>> modelchecker(instantiated);
std::unique_ptr<storm::modelchecker::CheckResult> chkResult = modelchecker.check(*formulas[0]);
storm::modelchecker::ExplicitQuantitativeCheckResult<double>& quantitativeChkResult = chkResult->asExplicitQuantitativeCheckResult<double>();
EXPECT_NEAR(0.01588055832, quantitativeChkResult[*instantiated.getInitialStates().begin()], storm::settings::generalSettings().getPrecision());
}
}
TEST(ModelInstantiatorTest, Brp_Rew) {
carl::VariablePool::getInstance().clear();
std::string const& programFile = STORM_CPP_TESTS_BASE_PATH "/functional/utility/brp16_2.pm";
std::string const& formulaAsString = "R=? [F ((s=5) | (s=0&srep=3)) ]";
std::string const& constantsAsString = ""; //e.g. pL=0.9,TOACK=0.5
// Program and formula
storm::prism::Program program = storm::parseProgram(programFile);
program.checkValidity();
std::vector<std::shared_ptr<storm::logic::Formula>> formulas = storm::parseFormulasForProgram(formulaAsString, program);
ASSERT_TRUE(formulas.size()==1);
// Parametric model
typename storm::builder::ExplicitPrismModelBuilder<storm::RationalFunction>::Options options = storm::builder::ExplicitPrismModelBuilder<storm::RationalFunction>::Options(*formulas[0]);
options.addConstantDefinitionsFromString(program, constantsAsString);
options.preserveFormula(*formulas[0]);
std::shared_ptr<storm::models::sparse::Dtmc<storm::RationalFunction>> dtmc = storm::builder::ExplicitPrismModelBuilder<storm::RationalFunction>().translateProgram(program, options)->as<storm::models::sparse::Dtmc<storm::RationalFunction>>();
storm::utility::ModelInstantiator<storm::models::sparse::Dtmc<storm::RationalFunction>, storm::models::sparse::Dtmc<double>> modelInstantiator(*dtmc);
{
std::map<storm::Variable, storm::RationalNumber> valuation;
storm::Variable const& pL = carl::VariablePool::getInstance().findVariableWithName("pL");
ASSERT_NE(pL, carl::Variable::NO_VARIABLE);
storm::Variable const& pK = carl::VariablePool::getInstance().findVariableWithName("pK");
ASSERT_NE(pK, carl::Variable::NO_VARIABLE);
storm::Variable const& TOMsg = carl::VariablePool::getInstance().findVariableWithName("TOMsg");
ASSERT_NE(pK, carl::Variable::NO_VARIABLE);
storm::Variable const& TOAck = carl::VariablePool::getInstance().findVariableWithName("TOAck");
ASSERT_NE(pK, carl::Variable::NO_VARIABLE);
valuation.insert(std::make_pair(pL,carl::rationalize<storm::RationalNumber>(0.9)));
valuation.insert(std::make_pair(pK,carl::rationalize<storm::RationalNumber>(0.3)));
valuation.insert(std::make_pair(TOMsg,carl::rationalize<storm::RationalNumber>(0.3)));
valuation.insert(std::make_pair(TOAck,carl::rationalize<storm::RationalNumber>(0.5)));
storm::models::sparse::Dtmc<double> const& instantiated(modelInstantiator.instantiate(valuation));
ASSERT_EQ(dtmc->getTransitionMatrix().getRowGroupIndices(), instantiated.getTransitionMatrix().getRowGroupIndices());
for(std::size_t rowGroup = 0; rowGroup < dtmc->getTransitionMatrix().getRowGroupCount(); ++rowGroup){
for(std::size_t row = dtmc->getTransitionMatrix().getRowGroupIndices()[rowGroup]; row < dtmc->getTransitionMatrix().getRowGroupIndices()[rowGroup+1]; ++row){
auto instantiatedEntry = instantiated.getTransitionMatrix().getRow(row).begin();
for(auto const& paramEntry : dtmc->getTransitionMatrix().getRow(row)){
EXPECT_EQ(paramEntry.getColumn(), instantiatedEntry->getColumn());
double evaluatedValue = carl::toDouble(paramEntry.getValue().evaluate(valuation));
EXPECT_EQ(evaluatedValue, instantiatedEntry->getValue());
++instantiatedEntry;
}
EXPECT_EQ(instantiated.getTransitionMatrix().getRow(row).end(),instantiatedEntry);
}
}
ASSERT_TRUE(instantiated.hasUniqueRewardModel());
EXPECT_FALSE(instantiated.getUniqueRewardModel()->second.hasStateRewards());
EXPECT_FALSE(instantiated.getUniqueRewardModel()->second.hasTransitionRewards());
EXPECT_TRUE(instantiated.getUniqueRewardModel()->second.hasStateActionRewards());
ASSERT_TRUE(dtmc->getUniqueRewardModel()->second.hasStateActionRewards());
std::size_t stateActionEntries = dtmc->getUniqueRewardModel()->second.getStateActionRewardVector().size();
ASSERT_EQ(stateActionEntries, instantiated.getUniqueRewardModel()->second.getStateActionRewardVector().size());
for(std::size_t i =0; i<stateActionEntries; ++i){
double evaluatedValue = carl::toDouble(dtmc->getUniqueRewardModel()->second.getStateActionRewardVector()[i].evaluate(valuation));
EXPECT_EQ(evaluatedValue, instantiated.getUniqueRewardModel()->second.getStateActionRewardVector()[i]);
}
EXPECT_EQ(dtmc->getStateLabeling(), instantiated.getStateLabeling());
EXPECT_EQ(dtmc->getOptionalChoiceLabeling(), instantiated.getOptionalChoiceLabeling());
storm::modelchecker::SparseDtmcPrctlModelChecker<storm::models::sparse::Dtmc<double>> modelchecker(instantiated);
std::unique_ptr<storm::modelchecker::CheckResult> chkResult = modelchecker.check(*formulas[0]);
storm::modelchecker::ExplicitQuantitativeCheckResult<double>& quantitativeChkResult = chkResult->asExplicitQuantitativeCheckResult<double>();
EXPECT_NEAR(1.308324495, quantitativeChkResult[*instantiated.getInitialStates().begin()], storm::settings::generalSettings().getPrecision());
}
}
TEST(ModelInstantiatorTest, consensus) {
carl::VariablePool::getInstance().clear();
std::string const& programFile = STORM_CPP_TESTS_BASE_PATH "/functional/utility/coin2_2.pm";
std::string const& formulaAsString = "Pmin=? [F \"finished\"&\"all_coins_equal_1\" ]";
std::string const& constantsAsString = ""; //e.g. pL=0.9,TOACK=0.5
// Program and formula
storm::prism::Program program = storm::parseProgram(programFile);
program.checkValidity();
std::vector<std::shared_ptr<storm::logic::Formula>> formulas = storm::parseFormulasForProgram(formulaAsString, program);
ASSERT_TRUE(formulas.size()==1);
// Parametric model
typename storm::builder::ExplicitPrismModelBuilder<storm::RationalFunction>::Options options = storm::builder::ExplicitPrismModelBuilder<storm::RationalFunction>::Options(*formulas[0]);
options.addConstantDefinitionsFromString(program, constantsAsString);
options.preserveFormula(*formulas[0]);
std::shared_ptr<storm::models::sparse::Mdp<storm::RationalFunction>> mdp = storm::builder::ExplicitPrismModelBuilder<storm::RationalFunction>().translateProgram(program, options)->as<storm::models::sparse::Mdp<storm::RationalFunction>>();
storm::utility::ModelInstantiator<storm::models::sparse::Mdp<storm::RationalFunction>, storm::models::sparse::Mdp<double>> modelInstantiator(*mdp);
std::map<storm::Variable, storm::RationalNumber> valuation;
storm::Variable const& p1 = carl::VariablePool::getInstance().findVariableWithName("p1");
ASSERT_NE(p1, carl::Variable::NO_VARIABLE);
storm::Variable const& p2 = carl::VariablePool::getInstance().findVariableWithName("p2");
ASSERT_NE(p2, carl::Variable::NO_VARIABLE);
valuation.insert(std::make_pair(p1,carl::rationalize<storm::RationalNumber>(0.51)));
valuation.insert(std::make_pair(p2,carl::rationalize<storm::RationalNumber>(0.49)));
storm::models::sparse::Mdp<double> const& instantiated(modelInstantiator.instantiate(valuation));
ASSERT_EQ(mdp->getTransitionMatrix().getRowGroupIndices(), instantiated.getTransitionMatrix().getRowGroupIndices());
for(std::size_t rowGroup = 0; rowGroup < mdp->getTransitionMatrix().getRowGroupCount(); ++rowGroup){
for(std::size_t row = mdp->getTransitionMatrix().getRowGroupIndices()[rowGroup]; row < mdp->getTransitionMatrix().getRowGroupIndices()[rowGroup+1]; ++row){
auto instantiatedEntry = instantiated.getTransitionMatrix().getRow(row).begin();
for(auto const& paramEntry : mdp->getTransitionMatrix().getRow(row)){
EXPECT_EQ(paramEntry.getColumn(), instantiatedEntry->getColumn());
double evaluatedValue = carl::toDouble(paramEntry.getValue().evaluate(valuation));
EXPECT_EQ(evaluatedValue, instantiatedEntry->getValue());
++instantiatedEntry;
}
EXPECT_EQ(instantiated.getTransitionMatrix().getRow(row).end(),instantiatedEntry);
}
}
EXPECT_EQ(mdp->getStateLabeling(), instantiated.getStateLabeling());
EXPECT_EQ(mdp->getOptionalChoiceLabeling(), instantiated.getOptionalChoiceLabeling());
storm::modelchecker::SparseMdpPrctlModelChecker<storm::models::sparse::Mdp<double>> modelchecker(instantiated);
std::unique_ptr<storm::modelchecker::CheckResult> chkResult = modelchecker.check(*formulas[0]);
storm::modelchecker::ExplicitQuantitativeCheckResult<double>& quantitativeChkResult = chkResult->asExplicitQuantitativeCheckResult<double>();
EXPECT_NEAR(0.3526577219, quantitativeChkResult[*instantiated.getInitialStates().begin()], storm::settings::generalSettings().getPrecision());
}
#endif

146
test/functional/utility/brp16_2.pm

@ -0,0 +1,146 @@
// bounded retransmission protocol [D'AJJL01]
// gxn/dxp 23/05/2001
dtmc
// number of chunks
const int N = 16;
// maximum number of retransmissions
const int MAX = 2;
// reliability of channels
const double pL;
const double pK;
// timeouts
const double TOMsg;
const double TOAck;
module sender
s : [0..6];
// 0 idle
// 1 next_frame
// 2 wait_ack
// 3 retransmit
// 4 success
// 5 error
// 6 wait sync
srep : [0..3];
// 0 bottom
// 1 not ok (nok)
// 2 do not know (dk)
// 3 ok (ok)
nrtr : [0..MAX];
i : [0..N];
bs : bool;
s_ab : bool;
fs : bool;
ls : bool;
// idle
[NewFile] (s=0) -> (s'=1) & (i'=1) & (srep'=0);
// next_frame
[aF] (s=1) -> (s'=2) & (fs'=(i=1)) & (ls'=(i=N)) & (bs'=s_ab) & (nrtr'=0);
// wait_ack
[aB] (s=2) -> (s'=4) & (s_ab'=!s_ab);
[TO_Msg] (s=2) -> (s'=3);
[TO_Ack] (s=2) -> (s'=3);
// retransmit
[aF] (s=3) & (nrtr<MAX) -> (s'=2) & (fs'=(i=1)) & (ls'=(i=N)) & (bs'=s_ab) & (nrtr'=nrtr+1);
[] (s=3) & (nrtr=MAX) & (i<N) -> (s'=5) & (srep'=1);
[] (s=3) & (nrtr=MAX) & (i=N) -> (s'=5) & (srep'=2);
// success
[] (s=4) & (i<N) -> (s'=1) & (i'=i+1);
[] (s=4) & (i=N) -> (s'=0) & (srep'=3);
// error
[SyncWait] (s=5) -> (s'=6);
// wait sync
[SyncWait] (s=6) -> (s'=0) & (s_ab'=false);
endmodule
module receiver
r : [0..5];
// 0 new_file
// 1 fst_safe
// 2 frame_received
// 3 frame_reported
// 4 idle
// 5 resync
rrep : [0..4];
// 0 bottom
// 1 fst
// 2 inc
// 3 ok
// 4 nok
fr : bool;
lr : bool;
br : bool;
r_ab : bool;
recv : bool;
// new_file
[SyncWait] (r=0) -> (r'=0);
[aG] (r=0) -> (r'=1) & (fr'=fs) & (lr'=ls) & (br'=bs) & (recv'=T);
// fst_safe_frame
[] (r=1) -> (r'=2) & (r_ab'=br);
// frame_received
[] (r=2) & (r_ab=br) & (fr=true) & (lr=false) -> (r'=3) & (rrep'=1);
[] (r=2) & (r_ab=br) & (fr=false) & (lr=false) -> (r'=3) & (rrep'=2);
[] (r=2) & (r_ab=br) & (fr=false) & (lr=true) -> (r'=3) & (rrep'=3);
[aA] (r=2) & !(r_ab=br) -> (r'=4);
// frame_reported
[aA] (r=3) -> (r'=4) & (r_ab'=!r_ab);
// idle
[aG] (r=4) -> (r'=2) & (fr'=fs) & (lr'=ls) & (br'=bs) & (recv'=T);
[SyncWait] (r=4) & (ls=true) -> (r'=5);
[SyncWait] (r=4) & (ls=false) -> (r'=5) & (rrep'=4);
// resync
[SyncWait] (r=5) -> (r'=0) & (rrep'=0);
endmodule
// prevents more than one file being sent
module tester
T : bool;
[NewFile] (T=false) -> (T'=true);
endmodule
module channelK
k : [0..2];
// idle
[aF] (k=0) -> pK : (k'=1) + 1-pK : (k'=2);
// sending
[aG] (k=1) -> (k'=0);
// lost
[TO_Msg] (k=2) -> (k'=0);
endmodule
module channelL
l : [0..2];
// idle
[aA] (l=0) -> pL : (l'=1) + 1-pL : (l'=2);
// sending
[aB] (l=1) -> (l'=0);
// lost
[TO_Ack] (l=2) -> (l'=0);
endmodule
rewards
[TO_Msg] true : TOMsg;
[TO_Ack] true : TOAck;
endrewards

56
test/functional/utility/coin2_2.pm

@ -0,0 +1,56 @@
//Randomised Consensus Protocol
mdp
const double p1; // in [0.2 , 0.8]
const double p2; // in [0.2 , 0.8]
const int N=2;
const int K=2;
const int range = 2*(K+1)*N;
const int counter_init = (K+1)*N;
const int left = N;
const int right = 2*(K+1)*N - N;
// shared coin
global counter : [0..range] init counter_init;
module process1
// program counter
pc1 : [0..3];
// 0 - flip
// 1 - write
// 2 - check
// 3 - finished
// local coin
coin1 : [0..1];
// flip coin
[] (pc1=0) -> p1 : (coin1'=0) & (pc1'=1) + 1 - p1 : (coin1'=1) & (pc1'=1);
// write tails -1 (reset coin to add regularity)
[] (pc1=1) & (coin1=0) & (counter>0) -> (counter'=counter-1) & (pc1'=2) & (coin1'=0);
// write heads +1 (reset coin to add regularity)
[] (pc1=1) & (coin1=1) & (counter<range) -> (counter'=counter+1) & (pc1'=2) & (coin1'=0);
// check
// decide tails
[] (pc1=2) & (counter<=left) -> (pc1'=3) & (coin1'=0);
// decide heads
[] (pc1=2) & (counter>=right) -> (pc1'=3) & (coin1'=1);
// flip again
[] (pc1=2) & (counter>left) & (counter<right) -> (pc1'=0);
// loop (all loop together when done)
[done] (pc1=3) -> (pc1'=3);
endmodule
module process2 = process1[pc1=pc2,coin1=coin2,p1=p2] endmodule
label "finished" = pc1=3 &pc2=3 ;
label "all_coins_equal_1" = coin1=1 &coin2=1 ;
rewards "steps"
true : 1;
endrewards
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