sp
/
tempest
1
0
Fork 0
Code Issues Pull Requests Projects Releases Wiki Activity
Browse Source

Merge branch 'unifplus_refactor'

tempestpy_adaptions
Matthias Volk 6 years ago
parent
fceaeed557 99808240bf
commit
3e2da7eba1
2 changed files with 123 additions and 77 deletions
Whitespace
Show all changes Ignore whitespace when comparing lines Ignore changes in amount of whitespace Ignore changes in whitespace at EOL
Split View
Diff Options
Show Stats Download Patch File Download Diff File
  1. 1
      CHANGELOG.md
  2. 193
      src/storm/modelchecker/csl/helper/SparseMarkovAutomatonCslHelper.cpp

1
CHANGELOG.md
View File

@ -18,6 +18,7 @@ Version 1.3.x
- New binary `storm-conv` that handles conversions between model files
- New binary `storm-pomdp` that handles the translation of POMDPs to pMCs.
- Maximal progress assumption is now applied while building Markov Automata (sparse engine).
- Improved Unif+ implementation for Markov Automata, significantly reduced memory consumption.
- Added support for expected time properties for discrete time models
- Bug fix in the parser for DRN (MDPs and MAs might have been affected).
- `storm-gspn`: Improved .pnpro parser

193
src/storm/modelchecker/csl/helper/SparseMarkovAutomatonCslHelper.cpp
View File

@ -35,55 +35,95 @@ namespace storm {
namespace modelchecker {
namespace helper {
/**
* Data structure holding result vectors (vLower, vUpper, wUpper) for Unif+.
*/
template<typename ValueType>
void calculateUnifPlusVector(Environment const& env, uint64_t k, uint64_t state, uint64_t const kind, ValueType lambda, uint64_t numberOfProbabilisticChoices, std::vector<std::vector<ValueType>> const & relativeReachability, OptimizationDirection dir, std::vector<std::vector<std::vector<ValueType>>>& unifVectors, storm::storage::SparseMatrix<ValueType> const& fullTransitionMatrix, storm::storage::BitVector const& markovianStates, storm::storage::BitVector const& psiStates, std::unique_ptr<storm::solver::MinMaxLinearEquationSolver<ValueType>> const& solver, storm::utility::numerical::FoxGlynnResult<ValueType> const& poisson, bool cycleFree) {
struct UnifPlusVectors {
UnifPlusVectors() {
// Intentionally empty
}
/**
* Initialize results vectors. vLowerOld, vUpperOld and wUpper[k=N] are initialized with zeros.
*/
UnifPlusVectors(uint64_t steps, uint64_t noStates) : numberOfStates(noStates), steps(steps), resLowerOld(numberOfStates, storm::utility::zero<ValueType>()), resLowerNew(numberOfStates, -1), resUpper(numberOfStates, storm::utility::zero<ValueType>()), wUpperOld(numberOfStates, storm::utility::zero<ValueType>()), wUpperNew(numberOfStates, -1) {
// Intentionally left empty
}
/**
* Prepare new iteration by setting the new result vectors as old result vectors, and initializing the new result vectors with -1 again.
*/
void prepareNewIteration() {
resLowerOld.swap(resLowerNew);
std::fill(resLowerNew.begin(), resLowerNew.end(), -1);
wUpperOld.swap(wUpperNew);
std::fill(wUpperNew.begin(), wUpperNew.end(), -1);
}
if (unifVectors[kind][k][state] != -1) {
uint64_t numberOfStates;
uint64_t steps;
std::vector<ValueType> resLowerOld;
std::vector<ValueType> resLowerNew;
std::vector<ValueType> resUpper;
std::vector<ValueType> wUpperOld;
std::vector<ValueType> wUpperNew;
};
template<typename ValueType>
void calculateUnifPlusVector(Environment const& env, uint64_t k, uint64_t state, bool calcLower, ValueType lambda, uint64_t numberOfProbabilisticChoices, std::vector<std::vector<ValueType>> const & relativeReachability, OptimizationDirection dir, UnifPlusVectors<ValueType>& unifVectors, storm::storage::SparseMatrix<ValueType> const& fullTransitionMatrix, storm::storage::BitVector const& markovianStates, storm::storage::BitVector const& psiStates, std::unique_ptr<storm::solver::MinMaxLinearEquationSolver<ValueType>> const& solver, storm::utility::numerical::FoxGlynnResult<ValueType> const& poisson, bool cycleFree) {
// Set reference to acutal vector
std::vector<ValueType>& resVectorOld = calcLower ? unifVectors.resLowerOld : unifVectors.wUpperOld;
std::vector<ValueType>& resVectorNew = calcLower ? unifVectors.resLowerNew : unifVectors.wUpperNew;
if (resVectorNew[state] != -1) {
// Result already calculated.
return;
}
auto numberOfStates = fullTransitionMatrix.getRowGroupCount();
uint64_t N = unifVectors[kind].size() - 1;
uint64_t N = unifVectors.steps;
auto const& rowGroupIndices = fullTransitionMatrix.getRowGroupIndices();
ValueType res;
// First case, k==N, independent from kind of state.
if (k == N) {
unifVectors[kind][k][state] = storm::utility::zero<ValueType>();
STORM_LOG_ASSERT(false, "Result for k=N was already calculated.");
resVectorNew[state] = storm::utility::zero<ValueType>();
return;
}
// Goal state, independent from kind of state.
if (psiStates[state]) {
if (kind == 0) {
// Vd
if (calcLower) {
// v lower
res = storm::utility::zero<ValueType>();
for (uint64_t i = k; i < N; ++i){
if (i >= poisson.left && i <= poisson.right) {
ValueType between = poisson.weights[i - poisson.left];
res += between;
res += poisson.weights[i - poisson.left];
}
}
unifVectors[kind][k][state] = res;
resVectorNew[state] = res;
} else {
// WU
unifVectors[kind][k][state] = storm::utility::one<ValueType>();
// w upper
resVectorNew[state] = storm::utility::one<ValueType>();
}
return;
}
// Markovian non-goal state.
if (markovianStates[state]) {
res = storm::utility::zero<ValueType>();
for (auto const& element : fullTransitionMatrix.getRow(rowGroupIndices[state])) {
uint64_t to = element.getColumn();
if (unifVectors[kind][k+1][to] == -1) {
calculateUnifPlusVector(env, k+1, to, kind, lambda, numberOfProbabilisticChoices, relativeReachability, dir, unifVectors, fullTransitionMatrix, markovianStates, psiStates, solver, poisson, cycleFree);
uint64_t successor = element.getColumn();
if (resVectorOld[successor] == -1) {
STORM_LOG_ASSERT(false, "Need to calculate previous result.");
calculateUnifPlusVector(env, k+1, successor, calcLower, lambda, numberOfProbabilisticChoices, relativeReachability, dir, unifVectors, fullTransitionMatrix, markovianStates, psiStates, solver, poisson, cycleFree);
}
res += element.getValue()*unifVectors[kind][k+1][to];
res += element.getValue() * resVectorOld[successor];
}
unifVectors[kind][k][state]=res;
resVectorNew[state]=res;
return;
}
@ -93,7 +133,7 @@ namespace storm {
res = -1;
for (uint64_t i = rowGroupIndices[state]; i < rowGroupIndices[state + 1]; ++i) {
auto row = fullTransitionMatrix.getRow(i);
ValueType between = 0;
ValueType between = storm::utility::zero<ValueType>();
for (auto const& element : row) {
uint64_t successor = element.getColumn();
@ -102,10 +142,10 @@ namespace storm {
continue;
}
if (unifVectors[kind][k][successor] == -1) {
calculateUnifPlusVector(env, k, successor, kind, lambda, numberOfProbabilisticChoices, relativeReachability, dir, unifVectors, fullTransitionMatrix, markovianStates, psiStates, solver, poisson, cycleFree);
if (resVectorNew[successor] == -1) {
calculateUnifPlusVector(env, k, successor, calcLower, lambda, numberOfProbabilisticChoices, relativeReachability, dir, unifVectors, fullTransitionMatrix, markovianStates, psiStates, solver, poisson, cycleFree);
}
between += element.getValue() * unifVectors[kind][k][successor];
between += element.getValue() * resVectorNew[successor];
}
if (maximize(dir)) {
res = storm::utility::max(res, between);
@ -117,11 +157,11 @@ namespace storm {
}
}
}
unifVectors[kind][k][state] = res;
resVectorNew[state] = res;
return;
}
// If we arrived at this point, the model is not cycle free. Use the solver to solve the unterlying equation system.
// If we arrived at this point, the model is not cycle free. Use the solver to solve the underlying equation system.
uint64_t numberOfProbabilisticStates = numberOfStates - markovianStates.getNumberOfSetBits();
std::vector<ValueType> b(numberOfProbabilisticChoices, storm::utility::zero<ValueType>());
std::vector<ValueType> x(numberOfProbabilisticStates, storm::utility::zero<ValueType>());
@ -142,10 +182,10 @@ namespace storm {
continue;
}
if (unifVectors[kind][k][successor] == -1) {
calculateUnifPlusVector(env, k, successor, kind, lambda, numberOfProbabilisticStates, relativeReachability, dir, unifVectors, fullTransitionMatrix, markovianStates, psiStates, solver, poisson, cycleFree);
if (resVectorNew[successor] == -1) {
calculateUnifPlusVector(env, k, successor, calcLower, lambda, numberOfProbabilisticStates, relativeReachability, dir, unifVectors, fullTransitionMatrix, markovianStates, psiStates, solver, poisson, cycleFree);
}
res = res + relativeReachability[j][stateCount] * unifVectors[kind][k][successor];
res += relativeReachability[j][stateCount] * resVectorNew[successor];
++stateCount;
}
@ -158,28 +198,7 @@ namespace storm {
solver->solveEquations(env, dir, x, b);
// Expand the solution for the probabilistic states to all states.
storm::utility::vector::setVectorValues(unifVectors[kind][k], ~markovianStates, x);
}
template <typename ValueType>
void calculateVu(Environment const& env, std::vector<std::vector<ValueType>> const& relativeReachability, OptimizationDirection dir, uint64_t k, uint64_t state, uint64_t const kind, ValueType lambda, uint64_t numberOfProbabilisticStates, std::vector<std::vector<std::vector<ValueType>>>& unifVectors, storm::storage::SparseMatrix<ValueType> const& fullTransitionMatrix, storm::storage::BitVector const& markovianStates, storm::storage::BitVector const& psiStates, std::unique_ptr<storm::solver::MinMaxLinearEquationSolver<ValueType>> const& solver, storm::utility::numerical::FoxGlynnResult<ValueType> const & poisson, bool cycleFree) {
// Avoiding multiple computation of the same value.
if (unifVectors[1][k][state] != -1) {
return;
}
uint64_t N = unifVectors[1].size() - 1;
ValueType res = storm::utility::zero<ValueType>();
for (uint64_t i = k; i < N; ++i) {
if (unifVectors[2][N-1-(i-k)][state] == -1) {
calculateUnifPlusVector(env, N-1-(i-k), state, 2, lambda, numberOfProbabilisticStates, relativeReachability, dir, unifVectors, fullTransitionMatrix, markovianStates, psiStates, solver, poisson, cycleFree);
}
if (i >= poisson.left && i <= poisson.right) {
res += poisson.weights[i - poisson.left] * unifVectors[2][N-1-(i-k)][state];
}
}
unifVectors[1][k][state] = res;
storm::utility::vector::setVectorValues(resVectorNew, ~markovianStates, x);
}
template <typename ValueType>
@ -229,7 +248,7 @@ namespace storm {
bool cycleFree = sccDecomposition.empty();
// Vectors to store computed vectors.
std::vector<std::vector<std::vector<ValueType>>> unifVectors(3);
UnifPlusVectors<ValueType> unifVectors;
// Transitions from goal states will be ignored. However, we mark them as non-probabilistic to make sure
// we do not apply the MDP algorithm to them.
@ -255,17 +274,22 @@ namespace storm {
// (1) define/declare horizon, epsilon, kappa, N, lambda, maxNorm
uint64_t numberOfStates = fullTransitionMatrix.getRowGroupCount();
double T = boundsPair.second;
// 'Unpack' the bounds to make them more easily accessible.
double lowerBound = boundsPair.first;
double upperBound = boundsPair.second;
// Lower bound > 0 is not implemented!
STORM_LOG_THROW(lowerBound == 0, storm::exceptions::NotImplementedException, "Support for lower bound > 0 not implemented in Unif+.");
// Truncation error
// TODO: make kappa a parameter.
ValueType kappa = storm::utility::one<ValueType>() / 10;
// Approximation error
ValueType epsilon = storm::settings::getModule<storm::settings::modules::GeneralSettings>().getPrecision();
// Lambda is largest exit rate
ValueType lambda = exitRateVector[0];
for (ValueType const& rate : exitRateVector) {
lambda = std::max(rate, lambda);
}
STORM_LOG_TRACE("Initial lambda is " << lambda << ".");
uint64_t N;
ValueType maxNorm = storm::utility::zero<ValueType>();
STORM_LOG_DEBUG("Initial lambda is " << lambda << ".");
// Compute the relative reachability vectors and create solver for models with SCCs.
std::vector<std::vector<ValueType>> relativeReachabilities(transitionMatrix.getRowCount());
@ -300,16 +324,19 @@ namespace storm {
}
}
ValueType maxNorm = storm::utility::zero<ValueType>();
// Maximal step size
uint64_t N;
storm::utility::ProgressMeasurement progressIterations("iterations");
size_t iteration = 0;
progressIterations.startNewMeasurement(iteration);
// Loop until result is within precision bound.
std::vector<ValueType> init(numberOfStates, -1);
do {
maxNorm = storm::utility::zero<ValueType>();
// (2) update parameter
N = storm::utility::ceil(lambda * T * std::exp(2) - storm::utility::log(kappa * epsilon));
N = storm::utility::ceil(lambda * upperBound * std::exp(2) - storm::utility::log(kappa * epsilon));
// (3) uniform - just applied to Markovian states.
for (uint64_t i = 0; i < fullTransitionMatrix.getRowGroupCount(); i++) {
for (uint64_t i = 0; i < numberOfStates; i++) {
if (!markovianAndGoalStates[i] || psiStates[i]) {
continue;
}
@ -340,7 +367,7 @@ namespace storm {
}
// Compute poisson distribution.
storm::utility::numerical::FoxGlynnResult<ValueType> foxGlynnResult = storm::utility::numerical::foxGlynn(lambda * T, epsilon * kappa / 100);
storm::utility::numerical::FoxGlynnResult<ValueType> foxGlynnResult = storm::utility::numerical::foxGlynn(lambda * upperBound, epsilon * kappa / 100);
// Scale the weights so they sum to one.
for (auto& element : foxGlynnResult.weights) {
@ -348,35 +375,48 @@ namespace storm {
}
// (4) Define vectors/matrices.
std::vector<std::vector<ValueType>> v = std::vector<std::vector<ValueType>>(N + 1, init);
unifVectors[0] = v;
unifVectors[1] = v;
unifVectors[2] = v;
// Initialize result vectors and already insert zeros for iteration N
unifVectors = UnifPlusVectors<ValueType>(N, numberOfStates);
// Define 0=vd, 1=vu, 2=wu.
// (5) Compute vectors and maxNorm.
for (uint64_t i = 0; i < numberOfStates; ++i) {
for (uint64_t k = N; k <= N; --k) {
calculateUnifPlusVector(env, k, i, 0, lambda, numberOfProbabilisticChoices, relativeReachabilities, dir, unifVectors, fullTransitionMatrix, markovianAndGoalStates, psiStates, solver, foxGlynnResult, cycleFree);
calculateUnifPlusVector(env, k, i, 2, lambda, numberOfProbabilisticChoices, relativeReachabilities, dir, unifVectors, fullTransitionMatrix, markovianAndGoalStates, psiStates, solver, foxGlynnResult, cycleFree);
calculateVu(env, relativeReachabilities, dir, k, i, 1, lambda, numberOfProbabilisticChoices, unifVectors, fullTransitionMatrix, markovianAndGoalStates, psiStates, solver, foxGlynnResult, cycleFree);
// Iteration k = N was already performed by initializing with zeros.
// Iterations k < N
storm::utility::ProgressMeasurement progressSteps("steps in iteration " + std::to_string(iteration));
progressSteps.setMaxCount(N);
progressSteps.startNewMeasurement(0);
for (int64_t k = N-1; k >= 0; --k) {
if (k < (int64_t)(N-1)) {
unifVectors.prepareNewIteration();
}
for (uint64_t state = 0; state < numberOfStates; ++state) {
// Calculate results for lower bound and wUpper
calculateUnifPlusVector(env, k, state, true, lambda, numberOfProbabilisticChoices, relativeReachabilities, dir, unifVectors, fullTransitionMatrix, markovianAndGoalStates, psiStates, solver, foxGlynnResult, cycleFree);
calculateUnifPlusVector(env, k, state, false, lambda, numberOfProbabilisticChoices, relativeReachabilities, dir, unifVectors, fullTransitionMatrix, markovianAndGoalStates, psiStates, solver, foxGlynnResult, cycleFree);
// Calculate result for upper bound
uint64_t index = N-1-k;
if (index >= foxGlynnResult.left && index <= foxGlynnResult.right) {
STORM_LOG_ASSERT(unifVectors.wUpperNew[state] != -1, "wUpper was not computed before.");
unifVectors.resUpper[state] += foxGlynnResult.weights[index - foxGlynnResult.left] * unifVectors.wUpperNew[state];
}
}
progressSteps.updateProgress(N-k);
}
// Only iterate over result vector, as the results can only get more precise.
maxNorm = storm::utility::zero<ValueType>();
for (uint64_t i = 0; i < numberOfStates; i++){
ValueType diff = storm::utility::abs(unifVectors[0][0][i] - unifVectors[1][0][i]);
ValueType diff = storm::utility::abs(unifVectors.resUpper[i] - unifVectors.resLowerNew[i]);
maxNorm = std::max(maxNorm, diff);
}
// (6) Double lambda.
lambda *= 2;
STORM_LOG_TRACE("Increased lambda to " << lambda << ", max diff is " << maxNorm << ".");
STORM_LOG_DEBUG("Increased lambda to " << lambda << ", max diff is " << maxNorm << ".");
progressIterations.updateProgress(++iteration);
} while (maxNorm > epsilon * (1 - kappa));
return unifVectors[0][0];
return unifVectors.resLowerNew;
}
template <typename ValueType>
@ -569,7 +609,12 @@ namespace storm {
return computeBoundedUntilProbabilitiesImca(env, dir, transitionMatrix, exitRateVector, markovianStates, psiStates, boundsPair);
} else {
STORM_LOG_ASSERT(settings.getMarkovAutomatonBoundedReachabilityMethod() == storm::settings::modules::MinMaxEquationSolverSettings::MarkovAutomatonBoundedReachabilityMethod::UnifPlus, "Unknown solution method.");
return computeBoundedUntilProbabilitiesUnifPlus(env, dir, transitionMatrix, exitRateVector, markovianStates, psiStates, boundsPair);
if (!storm::utility::isZero(boundsPair.first)) {
STORM_LOG_WARN("Using IMCA method because Unif+ does not support a lower bound > 0.");
return computeBoundedUntilProbabilitiesImca(env, dir, transitionMatrix, exitRateVector, markovianStates, psiStates, boundsPair);
} else {
return computeBoundedUntilProbabilitiesUnifPlus(env, dir, transitionMatrix, exitRateVector, markovianStates, psiStates, boundsPair);
}
}
}

Write Preview
Loading…
Cancel
Save