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Small simplifications

tempestpy_adaptions
Matthias Volk 6 years ago
parent
f9fb90499d
commit
6220b114b5
1 changed files with 44 additions and 37 deletions
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  1. 81
      src/storm/modelchecker/csl/helper/SparseMarkovAutomatonCslHelper.cpp

81
src/storm/modelchecker/csl/helper/SparseMarkovAutomatonCslHelper.cpp
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@ -35,11 +35,23 @@ namespace storm {
namespace modelchecker {
namespace helper {
/**
* Data structure holding result vectors (vLower, vUpper, wUpper) for Unif+.
*/
template<typename ValueType>
struct UnifPlusVectors {
UnifPlusVectors(uint64_t steps, uint64_t noStates) : numberOfStates(noStates), resLowerOld(numberOfStates, -1), resLowerNew(numberOfStates, -1), resUpperOld(numberOfStates, -1), resUpperNew(numberOfStates, -1) {
// Intentionally empty.
wUpper = std::vector<std::vector<ValueType>>(steps, std::vector<ValueType>(numberOfStates, -1));
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), resLowerOld(numberOfStates, storm::utility::zero<ValueType>()), resLowerNew(numberOfStates, -1), resUpperOld(numberOfStates, storm::utility::zero<ValueType>()), resUpperNew(numberOfStates, storm::utility::zero<ValueType>()) {
// For wUpper we have to keep track of all previous results
wUpper = std::vector<std::vector<ValueType>>(steps+1, std::vector<ValueType>(numberOfStates, -1));
// Initialize entries for step N with zeros
std::fill(wUpper[steps].begin(), wUpper[steps].end(), storm::utility::zero<ValueType>());
}
/**
@ -49,7 +61,7 @@ namespace storm {
resLowerOld.swap(resLowerNew);
std::fill(resLowerNew.begin(), resLowerNew.end(), -1);
resUpperOld.swap(resUpperNew);
std::fill(resUpperNew.begin(), resUpperNew.end(), -1);
std::fill(resUpperNew.begin(), resUpperNew.end(), storm::utility::zero<ValueType>());
}
uint64_t numberOfStates;
@ -62,6 +74,7 @@ namespace storm {
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.wUpper[k+1];
std::vector<ValueType>& resVectorNew = calcLower ? unifVectors.resLowerNew : unifVectors.wUpper[k];
@ -188,29 +201,6 @@ namespace storm {
// Expand the solution for the probabilistic states to all states.
storm::utility::vector::setVectorValues(resVectorNew, ~markovianStates, x);
}
template <typename ValueType>
void calculateResUpper(Environment const& env, std::vector<std::vector<ValueType>> const& relativeReachability, OptimizationDirection dir, uint64_t k, uint64_t state, ValueType lambda, uint64_t numberOfProbabilisticStates, 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) {
// Avoiding multiple computation of the same value.
if (unifVectors.resUpperNew[state] != -1) {
STORM_LOG_ASSERT(false, "Result was already calculated.");
return;
}
uint64_t N = unifVectors.wUpper.size() - 1;
ValueType res = storm::utility::zero<ValueType>();
for (uint64_t i = k; i < N; ++i) {
if (unifVectors.wUpper[N-1-(i-k)][state] == -1) {
STORM_LOG_ASSERT(false, "Need to calculate previous result.");
calculateUnifPlusVector(env, N-1-(i-k), state, false, 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.wUpper[N-1-(i-k)][state];
}
}
unifVectors.resUpperNew[state] = res;
}
template <typename ValueType>
void eliminateProbabilisticSelfLoops(storm::storage::SparseMatrix<ValueType>& transitionMatrix, storm::storage::BitVector const& markovianStates) {
@ -259,7 +249,7 @@ namespace storm {
bool cycleFree = sccDecomposition.empty();
// Vectors to store computed vectors.
UnifPlusVectors<ValueType> unifVectors(0, 0);
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.
@ -383,22 +373,39 @@ namespace storm {
}
// (4) Define vectors/matrices.
unifVectors = UnifPlusVectors<ValueType>(N+1, numberOfStates);
// Initialize result vectors and already insert zeros for iteration N
unifVectors = UnifPlusVectors<ValueType>(N, numberOfStates);
// (5) Compute vectors and maxNorm.
for (int64_t k = N; k >= 0; --k) {
for (uint64_t i = 0; i < numberOfStates; ++i) {
calculateUnifPlusVector(env, k, i, true, lambda, numberOfProbabilisticChoices, relativeReachabilities, dir, unifVectors, fullTransitionMatrix, markovianAndGoalStates, psiStates, solver, foxGlynnResult, cycleFree);
calculateUnifPlusVector(env, k, i, false, lambda, numberOfProbabilisticChoices, relativeReachabilities, dir, unifVectors, fullTransitionMatrix, markovianAndGoalStates, psiStates, solver, foxGlynnResult, cycleFree);
calculateResUpper(env, relativeReachabilities, dir, k, i, lambda, numberOfProbabilisticChoices, unifVectors, fullTransitionMatrix, markovianAndGoalStates, psiStates, solver, foxGlynnResult, cycleFree);
// Iteration k = N was already performed by initializing with zeros.
// Iterations k < N
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
// resUpperNew was already initialized with zeros
uint64_t left = std::max(foxGlynnResult.left, (uint64_t)(k));
uint64_t right = std::min(foxGlynnResult.right, N-1);
for (uint64_t state = 0; state < numberOfStates; ++state) {
for (uint64_t i = left; i <= right; ++i) {
STORM_LOG_ASSERT(unifVectors.wUpper[N-1-(i-k)][state] != -1, "wUpper was not computed before.");
unifVectors.resUpperNew[state] += foxGlynnResult.weights[i - foxGlynnResult.left] * unifVectors.wUpper[N-1-(i-k)][state];
}
}
unifVectors.prepareNewIteration();
}
// 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.resUpperOld[i] - unifVectors.resLowerOld[i]);
ValueType diff = storm::utility::abs(unifVectors.resUpperNew[i] - unifVectors.resLowerNew[i]);
maxNorm = std::max(maxNorm, diff);
}
@ -408,7 +415,7 @@ namespace storm {
} while (maxNorm > epsilon * (1 - kappa));
return unifVectors.resLowerOld;
return unifVectors.resLowerNew;
}
template <typename ValueType>

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