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first version of UnifPlus for MA

tempestpy_adaptions
Timo Philipp Gros 7 years ago
parent
ace351bd71
commit
54ab1c114e
2 changed files with 357 additions and 3 deletions
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  1. 298
      src/storm/modelchecker/csl/helper/SparseMarkovAutomatonCslHelper.cpp
  2. 62
      src/storm/modelchecker/csl/helper/SparseMarkovAutomatonCslHelper.h

298
src/storm/modelchecker/csl/helper/SparseMarkovAutomatonCslHelper.cpp
View File

@ -133,10 +133,304 @@ namespace storm {
void SparseMarkovAutomatonCslHelper::computeBoundedReachabilityProbabilities(OptimizationDirection dir, storm::storage::SparseMatrix<ValueType> const& transitionMatrix, std::vector<ValueType> const& exitRates, storm::storage::BitVector const& goalStates, storm::storage::BitVector const& markovianNonGoalStates, storm::storage::BitVector const& probabilisticNonGoalStates, std::vector<ValueType>& markovianNonGoalValues, std::vector<ValueType>& probabilisticNonGoalValues, ValueType delta, uint64_t numberOfSteps, storm::solver::MinMaxLinearEquationSolverFactory<ValueType> const& minMaxLinearEquationSolverFactory) {
STORM_LOG_THROW(false, storm::exceptions::InvalidOperationException, "Computing bounded reachability probabilities is unsupported for this value type.");
}
template <typename ValueType, typename std::enable_if<storm::NumberTraits<ValueType>::SupportsExponential, int>::type=0>
void SparseMarkovAutomatonCslHelper::printTransitions(std::vector<ValueType> const& exitRateVector, storm::storage::SparseMatrix<ValueType> const& fullTransitionMatrix, storm::storage::BitVector const& markovianStates, std::vector<std::vector<ValueType>>& vd, std::vector<std::vector<ValueType>>& vu, std::vector<std::vector<ValueType>>& wu){
std::ofstream logfile("U+logfile.txt", std::ios::app);
auto rowGroupIndices = fullTransitionMatrix.getRowGroupIndices();
auto numberOfStates = fullTransitionMatrix.getRowGroupCount();
logfile << "number of states = num of row group count " << numberOfStates << "\n";
for (int i = 0; i < fullTransitionMatrix.getRowGroupCount(); i++) {
logfile << " from node " << i << " ";
auto from = rowGroupIndices[i];
auto to = rowGroupIndices[i+1];
for (auto j = from ; j< to; j++){
for (auto &v : fullTransitionMatrix.getRow(j)) {
if (markovianStates[i]){
logfile << v.getValue() *exitRateVector[i] << " -> "<< v.getColumn() << "\t";
} else {
logfile << v.getValue() << " -> "<< v.getColumn() << "\t";
}
}
logfile << "\n";
}
}
logfile << "\n";
logfile << "vd: \n";
for (int i =0 ; i<vd.size(); i++){
for(int j=0; j<fullTransitionMatrix.getRowGroupCount(); j++){
logfile << vd[i][j] << "\t" ;
}
logfile << "\n";
}
logfile << "\nvu:\n";
for (int i =0 ; i<vu.size(); i++){
for(int j=0; j<fullTransitionMatrix.getRowGroupCount(); j++){
logfile << vu[i][j] << "\t" ;
}
logfile << "\n";
}
logfile << "\nwu\n";
for (int i =0 ; i<wu.size(); i++){
for(int j=0; j<fullTransitionMatrix.getRowGroupCount(); j++){
logfile << wu[i][j] << "\t" ;
}
logfile << "\n";
}
logfile.close();
}
template<typename ValueType>
ValueType SparseMarkovAutomatonCslHelper::poisson(ValueType lambda, uint64_t i) {
ValueType res = pow(lambda, i);
ValueType fac = 1;
for (long j = i ; j>0 ; j--){
fac = fac *j;
}
res = res / fac ;
res = res * exp(-lambda);
return res;
}
template <typename ValueType, typename std::enable_if<storm::NumberTraits<ValueType>::SupportsExponential, int>::type=0>
void SparseMarkovAutomatonCslHelper::calculateVu(uint64_t k, uint64_t node, ValueType lambda, std::vector<std::vector<ValueType>>& vu, std::vector<std::vector<ValueType>>& wu, storm::storage::SparseMatrix<ValueType> const& fullTransitionMatrix, storm::storage::BitVector const& markovianStates, storm::storage::BitVector const& psiStates){
if (vu[k][node]!=-1){return;} //dynamic programming. avoiding multiple calculation.
uint64_t N = vu.size()-1;
auto rowGroupIndices = fullTransitionMatrix.getRowGroupIndices();
ValueType res =0;
for (long i = k ; i < N ; i++ ){
if (wu[N-1-(i-k)][node]==-1){
calculateWu((N-1-(i-k)),node,lambda,wu,fullTransitionMatrix,markovianStates,psiStates);
}
res+=poisson(lambda, i)*wu[N-1-(i-k)][node];
}
vu[k][node]=res;
}
template <typename ValueType, typename std::enable_if<storm::NumberTraits<ValueType>::SupportsExponential, int>::type=0>
void SparseMarkovAutomatonCslHelper::calculateWu(uint64_t k, uint64_t node, ValueType lambda, std::vector<std::vector<ValueType>>& wu, storm::storage::SparseMatrix<ValueType> const& fullTransitionMatrix, storm::storage::BitVector const& markovianStates, storm::storage::BitVector const& psiStates){
if (wu[k][node]!=-1){return;} //dynamic programming. avoiding multiple calculation.
uint64_t N = wu.size()-1;
auto rowGroupIndices = fullTransitionMatrix.getRowGroupIndices();
ValueType res;
if (k==N){
wu[k][node]=0;
return;
}
if (psiStates[node]){
wu[k][node]=1;
return;
}
if (markovianStates[node]){
res = 0;
auto line = fullTransitionMatrix.getRow(rowGroupIndices[node]);
for (auto &element : line){
uint64_t to = element.getColumn();
if (wu[k+1][to]==-1){
calculateWu(k+1,to,lambda,wu,fullTransitionMatrix,markovianStates,psiStates);
}
res+=element.getValue()*wu[k+1][to];
}
} else {
res = 0;
uint64_t rowStart = rowGroupIndices[node];
uint64_t rowEnd = rowGroupIndices[node+1];
for (uint64_t i = rowStart; i< rowEnd; i++){
auto line = fullTransitionMatrix.getRow(i);
ValueType between = 0;
for (auto& element: line){
uint64_t to = element.getColumn();
if (to==node){
continue;
}
if (wu[k][to]==-1){
calculateWu(k,to,lambda,wu,fullTransitionMatrix,markovianStates,psiStates);
}
between+=element.getValue()*wu[k][to];
}
if (between > res){
res = between;
}
}
} // end no goal-prob state
wu[k][node]=res;
}
template <typename ValueType, typename std::enable_if<storm::NumberTraits<ValueType>::SupportsExponential, int>::type=0>
void SparseMarkovAutomatonCslHelper::calculateVd(uint64_t k, uint64_t node, ValueType lambda, std::vector<std::vector<ValueType>>& vd, storm::storage::SparseMatrix<ValueType> const& fullTransitionMatrix, storm::storage::BitVector const& markovianStates, storm::storage::BitVector const& psiStates){
std::ofstream logfile("U+logfile.txt", std::ios::app);
if (vd[k][node]!=-1){return;} //dynamic programming. avoiding multiple calculation.
logfile << "calculating vd for k = " << k << " node "<< node << " \t";
uint64_t N = vd.size()-1;
auto rowGroupIndices = fullTransitionMatrix.getRowGroupIndices();
ValueType res;
if (k==N){
logfile << "k == N! res = 0\n";
vd[k][node]=0;
return;
}
//goal state
if (psiStates[node]){
res = 0;
for (uint64_t i = k ; i<N ; i++){
res+=poisson(lambda,i);
}
vd[k][node]=res;
logfile << "goal state node " << node << " res = " << res << "\n";
return;
}
// no-goal markovian state
if (markovianStates[node]){
logfile << "markovian state: ";
res = 0;
auto line = fullTransitionMatrix.getRow(rowGroupIndices[node]);
for (auto &element : line){
uint64_t to = element.getColumn();
if (vd[k+1][to]==-1){
calculateVd(k+1,to,lambda,vd, fullTransitionMatrix, markovianStates,psiStates);
}
res+=element.getValue()*vd[k+1][to];
}
} else { //no-goal prob state
logfile << "prob state: ";
res = 0;
uint64_t rowStart = rowGroupIndices[node];
uint64_t rowEnd = rowGroupIndices[node+1];
for (uint64_t i = rowStart; i< rowEnd; i++){
auto line = fullTransitionMatrix.getRow(i);
ValueType between = 0;
for (auto& element: line){
uint64_t to = element.getColumn();
if (to==node){
logfile << "ignoring self loops for now";
continue;
}
if (vd[k][to]==-1){
calculateVd(k,to,lambda,vd, fullTransitionMatrix, markovianStates,psiStates);
}
between+=element.getValue()*vd[k][to];
}
if (between > res){
res = between;
}
}
}
vd[k][node]=res;
logfile << " res = " << res << "\n";
}
template <typename ValueType, typename std::enable_if<storm::NumberTraits<ValueType>::SupportsExponential, int>::type>
std::vector<ValueType> SparseMarkovAutomatonCslHelper::computeBoundedUntilProbabilities(OptimizationDirection dir, storm::storage::SparseMatrix<ValueType> const& transitionMatrix, std::vector<ValueType> const& exitRateVector, storm::storage::BitVector const& markovianStates, storm::storage::BitVector const& psiStates, std::pair<double, double> const& boundsPair, storm::solver::MinMaxLinearEquationSolverFactory<ValueType> const& minMaxLinearEquationSolverFactory) {
std::vector<ValueType> SparseMarkovAutomatonCslHelper::unifPlus( std::pair<double, double> const& boundsPair, std::vector<ValueType> const& exitRateVector, storm::storage::SparseMatrix<ValueType> const& transitionMatrix, storm::storage::BitVector const& markovianStates, storm::storage::BitVector const& psiStates){
std::ofstream logfile("U+logfile.txt", std::ios::app);
ValueType maxNorm = 0;
//bitvectors to identify different kind of states
storm::storage::BitVector const &markovianNonGoalStates = markovianStates & ~psiStates;
storm::storage::BitVector const &probabilisticNonGoalStates = ~markovianStates & ~psiStates;
storm::storage::BitVector const &allStates = markovianStates | ~markovianStates;
//vectors to save calculation
std::vector<std::vector<ValueType>> vd,vu,wu;
//transition matrix with diagonal entries. The values can be changed during uniformisation
typename storm::storage::SparseMatrix<ValueType> fullTransitionMatrix = transitionMatrix.getSubmatrix(true, allStates , allStates , true);
auto rowGroupIndices = fullTransitionMatrix.getRowGroupIndices();
std::vector<ValueType> exitRate{exitRateVector};
//(1) define horizon, epsilon, kappa , N, lambda,
double T = boundsPair.second;
ValueType kappa = storm::utility::one<ValueType>() /10; // would be better as option-parameter
uint64_t numberOfStates = fullTransitionMatrix.getRowGroupCount();
ValueType epsilon = storm::settings::getModule<storm::settings::modules::GeneralSettings>().getPrecision();
ValueType lambda = exitRateVector[0];
for (ValueType act: exitRateVector) {
lambda = std::max(act, lambda);
}
uint64_t N;
// while not close enough to precision:
do {
// (2) update parameter
N = ceil(lambda*T*exp(2)-log(kappa*epsilon));
// (3) uniform - just applied to markovian states
for (int i = 0; i < fullTransitionMatrix.getRowGroupCount(); i++) {
if (!markovianStates[i]) {
continue;
}
uint64_t from = rowGroupIndices[i]; //markovian state -> no Nondeterminism -> only one row
if (exitRate[i] == lambda) {
continue; //already unified
}
auto line = fullTransitionMatrix.getRow(from);
ValueType exitOld = exitRate[i];
ValueType exitNew = lambda;
for (auto &v : line) {
if (v.getColumn() == i) { //diagonal element
ValueType newSelfLoop = exitNew - exitOld + v.getValue();
ValueType newRate = newSelfLoop / exitNew;
v.setValue(newRate);
} else { //modify probability
ValueType propOld = v.getValue();
ValueType propNew = propOld * exitOld / exitNew;
v.setValue(propNew);
}
}
exitRate[i] = exitNew;
}
// (4) define vectors/matrices
std::vector<ValueType> init(numberOfStates, -1);
vd = std::vector<std::vector<ValueType>> (N + 1, init);
vu = std::vector<std::vector<ValueType>> (N + 1, init);
wu = std::vector<std::vector<ValueType>> (N + 1, init);
printTransitions(exitRate, fullTransitionMatrix, markovianStates,vd,vu,wu); // TODO: delete when develepmont is finished
// (5) calculate vectors and maxNorm
for (uint64_t i = 0; i < numberOfStates; i++) {
for (uint64_t k = N; k <= N; k--) {
calculateVd(k, i, T*lambda, vd, fullTransitionMatrix, markovianStates, psiStates);
calculateWu(k, i, T*lambda, wu, fullTransitionMatrix, markovianStates, psiStates);
calculateVu(k, i, T*lambda, vu, wu, fullTransitionMatrix, markovianStates, psiStates);
//also use iteration to keep maxNorm of vd and vu up to date, so the loop-condition is easy to prove
ValueType diff = std::abs(vd[k][i]-vu[k][i]);
maxNorm = std::max(maxNorm, diff);
}
}
printTransitions(exitRate, fullTransitionMatrix, markovianStates,vd,vu,wu); // TODO: delete when development is finished
// (6) double lambda
lambda=2*lambda;
} while (maxNorm>epsilon*(1-kappa));
return vd[0];
}
template <typename ValueType, typename std::enable_if<storm::NumberTraits<ValueType>::SupportsExponential, int>::type>
std::vector<ValueType> SparseMarkovAutomatonCslHelper::computeBoundedUntilProbabilities(OptimizationDirection dir, storm::storage::SparseMatrix<ValueType> const& transitionMatrix, std::vector<ValueType> const& exitRateVector, storm::storage::BitVector const& markovianStates, storm::storage::BitVector const& psiStates, std::pair<double, double> const& boundsPair, storm::solver::MinMaxLinearEquationSolverFactory<ValueType> const& minMaxLinearEquationSolverFactory) {
return unifPlus(boundsPair, exitRateVector, transitionMatrix, markovianStates, psiStates);
/*
uint64_t numberOfStates = transitionMatrix.getRowGroupCount();
// 'Unpack' the bounds to make them more easily accessible.
@ -195,7 +489,7 @@ namespace storm {
storm::utility::vector::setVectorValues(result, probabilisticNonGoalStates, vProbabilistic);
storm::utility::vector::setVectorValues(result, markovianNonGoalStates, vMarkovian);
return result;
}
}*/
}
template <typename ValueType, typename std::enable_if<!storm::NumberTraits<ValueType>::SupportsExponential, int>::type>

62
src/storm/modelchecker/csl/helper/SparseMarkovAutomatonCslHelper.h
View File

@ -14,7 +14,22 @@ namespace storm {
class SparseMarkovAutomatonCslHelper {
public:
/*!
* Computes TBU according to the UnifPlus algorithm
*
* @param boundsPair With precondition that the first component is 0, the second one gives the time bound
* @param exitRateVector the exit-rates of the given MA
* @param transitionMatrix the transitions of the given MA
* @param markovianStates bitvector refering to the markovian states
* @param psiStates bitvector refering to the goal states
*
* @return the probability vector
*
*/
template <typename ValueType, typename std::enable_if<storm::NumberTraits<ValueType>::SupportsExponential, int>::type=0>
static std::vector<ValueType> unifPlus( std::pair<double, double> const& boundsPair, std::vector<ValueType> const& exitRateVector, storm::storage::SparseMatrix<ValueType> const& transitionMatrix, storm::storage::BitVector const& markovianStates, storm::storage::BitVector const& psiStates);
template <typename ValueType, typename std::enable_if<storm::NumberTraits<ValueType>::SupportsExponential, int>::type = 0>
static std::vector<ValueType> computeBoundedUntilProbabilities(OptimizationDirection dir, storm::storage::SparseMatrix<ValueType> const& transitionMatrix, std::vector<ValueType> const& exitRateVector, storm::storage::BitVector const& markovianStates, storm::storage::BitVector const& psiStates, std::pair<double, double> const& boundsPair, storm::solver::MinMaxLinearEquationSolverFactory<ValueType> const& minMaxLinearEquationSolverFactory);
@ -38,6 +53,51 @@ namespace storm {
static std::vector<ValueType> computeReachabilityTimes(OptimizationDirection dir, storm::storage::SparseMatrix<ValueType> const& transitionMatrix, storm::storage::SparseMatrix<ValueType> const& backwardTransitions, std::vector<ValueType> const& exitRateVector, storm::storage::BitVector const& markovianStates, storm::storage::BitVector const& psiStates, storm::solver::MinMaxLinearEquationSolverFactory<ValueType> const& minMaxLinearEquationSolverFactory);
private:
/*!
* Computes the poission-distribution
*
*
* @param parameter lambda to use
* @param point i
* TODO: replace with Fox-Lynn
* @return the probability
*/
template <typename ValueType>
static ValueType poisson(ValueType lambda, uint64_t i);
/*!
* Computes vd vector according to UnifPlus
*
*/
template <typename ValueType, typename std::enable_if<storm::NumberTraits<ValueType>::SupportsExponential, int>::type=0>
static void calculateVd(uint64_t k, uint64_t node, ValueType lambda, std::vector<std::vector<ValueType>>& vd, storm::storage::SparseMatrix<ValueType> const& fullTransitionMatrix, storm::storage::BitVector const& markovianStates, storm::storage::BitVector const& psiStates);
/*!
* Computes vu vector according to UnifPlus
*
*/
template <typename ValueType, typename std::enable_if<storm::NumberTraits<ValueType>::SupportsExponential, int>::type=0>
static void calculateVu(uint64_t k, uint64_t node, ValueType lambda, std::vector<std::vector<ValueType>>& vu, std::vector<std::vector<ValueType>>& wu, storm::storage::SparseMatrix<ValueType> const& fullTransitionMatrix, storm::storage::BitVector const& markovianStates, storm::storage::BitVector const& psiStates);
/*!
* Computes wu vector according to UnifPlus
*
*/
template <typename ValueType, typename std::enable_if<storm::NumberTraits<ValueType>::SupportsExponential, int>::type=0>
static void calculateWu(uint64_t k, uint64_t node, ValueType lambda, std::vector<std::vector<ValueType>>& wu, storm::storage::SparseMatrix<ValueType> const& fullTransitionMatrix, storm::storage::BitVector const& markovianStates, storm::storage::BitVector const& psiStates);
/*!
* Prints the TransitionMatrix and the vectors vd, vu, wu to the logfile
* TODO: delete when development is finished
*
*/
template <typename ValueType, typename std::enable_if<storm::NumberTraits<ValueType>::SupportsExponential, int>::type=0>
static void printTransitions(std::vector<ValueType> const& exitRateVector, storm::storage::SparseMatrix<ValueType> const& fullTransitionMatrix, storm::storage::BitVector const& markovianStates,std::vector<std::vector<ValueType>>& vd, std::vector<std::vector<ValueType>>& vu, std::vector<std::vector<ValueType>>& wu);
template <typename ValueType, typename std::enable_if<storm::NumberTraits<ValueType>::SupportsExponential, int>::type = 0>
static void computeBoundedReachabilityProbabilities(OptimizationDirection dir, storm::storage::SparseMatrix<ValueType> const& transitionMatrix, std::vector<ValueType> const& exitRates, storm::storage::BitVector const& goalStates, storm::storage::BitVector const& markovianNonGoalStates, storm::storage::BitVector const& probabilisticNonGoalStates, std::vector<ValueType>& markovianNonGoalValues, std::vector<ValueType>& probabilisticNonGoalValues, ValueType delta, uint64_t numberOfSteps, storm::solver::MinMaxLinearEquationSolverFactory<ValueType> const& minMaxLinearEquationSolverFactory);

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