TimQu
7 years ago
27 changed files with 596 additions and 228 deletions
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24CHANGELOG.md
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36doc/checklist_new_release.md
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7resources/3rdparty/CMakeLists.txt
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2resources/3rdparty/carl/CMakeLists.txt
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2resources/3rdparty/sylvan/CMakeLists.txt
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2src/storm/adapters/Smt2ExpressionAdapter.h
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159src/storm/counterexamples/SMTMinimalLabelSetGenerator.h
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57src/storm/logic/ComparisonType.h
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24src/storm/modelchecker/csl/helper/SparseCtmcCslHelper.cpp
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30src/storm/modelchecker/prctl/helper/SparseDtmcPrctlHelper.cpp
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5src/storm/modelchecker/prctl/helper/SparseDtmcPrctlHelper.h
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5src/storm/solver/AbstractEquationSolver.cpp
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5src/storm/solver/AbstractEquationSolver.h
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4src/storm/solver/NativeLinearEquationSolver.cpp
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2src/storm/solver/SmtlibSmtSolver.cpp
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8src/storm/solver/SymbolicMinMaxLinearEquationSolver.cpp
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10src/storm/solver/SymbolicNativeLinearEquationSolver.cpp
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6src/storm/storage/dd/Add.cpp
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7src/storm/storage/dd/cudd/InternalCuddAdd.cpp
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5src/storm/storage/dd/cudd/InternalCuddAdd.h
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7src/storm/storage/dd/sylvan/InternalSylvanAdd.cpp
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2src/storm/storage/dd/sylvan/InternalSylvanAdd.h
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2src/storm/storage/sparse/PrismChoiceOrigins.cpp
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2src/storm/storage/sparse/PrismChoiceOrigins.h
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275src/storm/utility/numerical.cpp
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134src/storm/utility/numerical.h
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2version.cmake
@ -0,0 +1,36 @@ |
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The following steps should be performed before releasing a new storm version. |
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Note that in most case a simultaneous release of [carl](https://github.com/smtrat/carl), [storm](https://github.com/moves-rwth/storm), [pycarl](https://github.com/moves-rwth/pycarl/) and [stormpy](https://github.com/moves-rwth/stormpy/) is preferred. |
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1. Update `CHANGELOG.md` |
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To get all the commits from an author since the last tag execute: |
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```console |
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git log last_tag..HEAD --author "author_name" |
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``` |
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2. Update used carl version: |
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* Update `GIT_TAG` in `resources/3rdparty/carl/CMakeLists.txt` |
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* Maybe update `CARL_MINVERSION` in `resources/3rdparty/CMakeLists.txt` |
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3. Check that storm builds without errors and all tests are successful |
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* [Travis](https://travis-ci.org/moves-rwth/storm) should run successfully |
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4. Set new storm version: |
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* Set new storm version in `version.cmake` |
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5. Set new tag in git |
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```console |
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git tag -a new_version |
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git push origin new_version |
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``` |
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Next we push the tag to GitHub. This step requires the GitHub repo to to be configured as a remote. |
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```console |
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git remote add github https://github.com/moves-rwth/storm.git |
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git push github new_version |
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``` |
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The new tag should now be visible on [GitHub](https://github.com/moves-rwth/storm/tags) |
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6. [Add new release](https://github.com/moves-rwth/storm/releases/new) in GitHub |
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7. Update [Homebrew formula](https://github.com/moves-rwth/homebrew-storm) |
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8. Announce new storm version on [website](http://www.stormchecker.org/news.html) |
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@ -0,0 +1,275 @@ |
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#include "storm/utility/numerical.h"
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#include <cmath>
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#include <boost/math/constants/constants.hpp>
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#include "storm/utility/macros.h"
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#include "storm/utility/constants.h"
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#include "storm/exceptions/InvalidArgumentException.h"
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#include "storm/exceptions/PrecisionExceededException.h"
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namespace storm { |
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namespace utility { |
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namespace numerical { |
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template<typename ValueType> |
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FoxGlynnResult<ValueType>::FoxGlynnResult() : left(0), right(0), totalWeight(storm::utility::zero<ValueType>()) { |
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// Intentionally left empty.
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} |
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/*!
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* The following implementation of Fox and Glynn's algorithm is taken from David Jansen's patched version |
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* in MRMC, which is based on his paper: |
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* |
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* https://pms.cs.ru.nl/iris-diglib/src/getContent.php?id=2011-Jansen-UnderstandingFoxGlynn
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* |
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* We have only adapted the code to match more of C++'s and our coding guidelines. |
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*/ |
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template<typename ValueType> |
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FoxGlynnResult<ValueType> foxGlynnFinder(ValueType lambda, ValueType epsilon) { |
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ValueType tau = std::numeric_limits<ValueType>::min(); |
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ValueType omega = std::numeric_limits<ValueType>::max(); |
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ValueType const sqrt_2_pi = boost::math::constants::root_two_pi<ValueType>(); |
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ValueType const log10_e = std::log10(boost::math::constants::e<ValueType>()); |
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uint64_t m = static_cast<uint64_t>(lambda); |
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int64_t left = 0; |
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int64_t right = 0; |
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// tau is only used in underflow checks, which we are going to do in the logarithm domain.
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tau = log(tau); |
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// In error bound comparisons, we always compare with epsilon*sqrt_2_pi.
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epsilon *= sqrt_2_pi; |
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// Compute left truncation point.
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if (m < 25) { |
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// For lambda below 25 the exponential can be smaller than tau. If that is the case we expect
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// underflows and warn the user.
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if (-lambda <= tau) { |
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STORM_LOG_WARN("Fox-Glynn: 0 < lambda < 25, underflow near Poi(" << lambda << ", 0) = " << std::exp(-lambda) << ". The results are unreliable."); |
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} |
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// Zero is used as left truncation point for lambda <= 25.
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left = 0; |
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} else { |
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// Compute the left truncation point for lambda >= 25 (for lambda < 25 we use zero as left truncation point).
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ValueType const bl = (1 + 1 / lambda) * std::exp((1/lambda) * 0.125); |
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ValueType const sqrt_lambda = std::sqrt(lambda); |
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int64_t k; |
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// Start looking for the left truncation point:
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// * start search at k=4 (taken from original Fox-Glynn paper)
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// * increase the left truncation point until we fulfil the error condition
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for (k = 4;; ++k) { |
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ValueType max_err; |
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left = m - static_cast<int64_t>(std::ceil(k*sqrt_lambda + 0.5)); |
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// For small lambda the above calculation can yield negative truncation points, crop them here.
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if (left <= 0) { |
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left = 0; |
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break; |
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} |
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// Note that Propositions 2-4 in Fox--Glynn mix up notation: they write Phi where they mean
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// 1 - Phi. (In Corollaries 1 and 2, phi is used correctly again.)
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max_err = bl * exp(-0.5 * (k*k)) / k; |
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if (max_err * 2 <= epsilon) { |
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// If the error on the left hand side is smaller, we can be more lenient on the right hand
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// side. To this end, we now set epsilon to the part of the error that has not yet been eaten
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// up by the left-hand truncation.
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epsilon -= max_err; |
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break; |
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} |
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} |
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// Finally the left truncation point is found.
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} |
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// Compute right truncation point.
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{ |
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ValueType lambda_max; |
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int64_t m_max, k; |
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// According to Fox-Glynn, if lambda < 400 we should take lambda = 400, otherwise use the original
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// value. This is for computing the right truncation point.
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if (m < 400) { |
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lambda_max = 400; |
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m_max = 400; |
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epsilon *= 0.662608824988162441697980; |
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/* i.e. al = (1+1/400) * exp(1/16) * sqrt_2; epsilon /= al; */ |
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} else { |
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lambda_max = lambda; |
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m_max = m; |
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epsilon *= (1 - 1 / (lambda + 1)) * 0.664265347050632847802225; |
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/* i.e. al = (1+1/lambda) * exp(1/16) * sqrt_2; epsilon /= al; */ |
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} |
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// Find right truncation point.
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// This loop is a modification to the original Fox-Glynn paper.
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// The search for the right truncation point is only terminated by the error condition and not by
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// the stop index from the FG paper. This can yield more accurate results if necessary.
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for (k = 4;; ++k) { |
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// dkl_inv is between 1 - 1e-33 and 1 if lambda_max >= 400 and k >= 4; this will always be
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// rounded to 1.0. We therefore leave the factor out.
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// double dkl_inv=1 - exp(-266/401.0 * (k*sqrt(2*lambda_max) + 1.5));
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// actually: "k * (dkl_inv*epsilon/al) >= exp(-0.5 * k^2)", but epsilon has been changed appropriately.
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if (k * epsilon >= exp(-0.5*(k*k))) { |
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break; |
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} |
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} |
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right = m_max + static_cast<int64_t>(std::ceil(k * std::sqrt(2 * lambda_max) + 0.5)); |
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if (right > m_max + static_cast<int64_t>(std::ceil((lambda_max + 1) * 0.5))) { |
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STORM_LOG_WARN("Fox-Glynn: right = " << right << " >> lambda = " << lambda_max << ", cannot bound the right tail. The results are unreliable."); |
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} |
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} |
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// Time to set the initial value for weights.
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FoxGlynnResult<ValueType> fgresult; |
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fgresult.left = static_cast<uint64_t>(left); |
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fgresult.right = static_cast<uint64_t>(right); |
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fgresult.weights.resize(fgresult.right - fgresult.left + 1); |
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fgresult.weights[m - left] = omega / (1.0e+10 * (right - left)); |
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if (m >= 25) { |
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// Perform underflow check.
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ValueType result, log_c_m_inf; |
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int64_t i; |
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// we are going to compare with tau - log(w[m]).
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tau -= std::log(fgresult.weights[m - left]); |
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// We take the c_m_inf = 0.14627 / sqrt( m ), as for lambda >= 25
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// c_m = 1 / ( sqrt( 2.0 * pi * m ) ) * exp( m - lambda - 1 / ( 12.0 * m ) ) => c_m_inf.
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// Note that m-lambda is in the interval (-1,0], and -1/(12*m) is in [-1/(12*25),0).
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// So, exp(m-lambda - 1/(12*m)) is in (exp(-1-1/(12*25)),exp(0)).
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// Therefore, we can improve the lower bound on c_m to exp(-1-1/(12*25)) / sqrt(2*pi) = ~0.14627.
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// Its logarithm is -1 - 1/(12*25) - log(2*pi) * 0.5 = ~ -1.922272 (rounded towards -infinity).
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log_c_m_inf = -1.922272 - log((double) m) * 0.5; |
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// We use FG's Proposition 6 directly (and not Corollary 4 i and ii), as k_prime may be too large
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// if pFG->left == 0.
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i = m - left; |
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// Equivalent to 2*i <= m, equivalent to i <= lambda/2.
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if (i <= left) { |
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// Use Proposition 6 (i). Note that Fox--Glynn are off by one in the proof of this proposition;
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// they sum up to i-1, but should have summed up to i. */
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result = log_c_m_inf |
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- i * (i+1) * (0.5 + (2*i+1)/(6*lambda)) / lambda; |
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} else { |
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// Use Corollary 4 (iii). Note that k_prime <= sqrt(m+1)/m is a misprint for k_prime <= m/sqrt(m+1),
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// which is equivalent to left >= 0, which holds trivially.
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result = -lambda; |
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if (left != 0) { |
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// Also use Proposition 6 (ii).
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double result_1 = log_c_m_inf + i * log(1 - i/(double) (m+1)); |
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// Take the maximum.
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if (result_1 > result) { |
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result = result_1; |
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} |
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} |
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} |
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if (result <= tau) { |
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int64_t const log10_result = static_cast<int64_t>(std::floor(result * log10_e)); |
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STORM_LOG_WARN("Fox-Glynn: lambda >= 25, underflow near Poi(" << lambda << "," << left << ") <= " << std::exp(result - log10_result/log10_e) << log10_result << ". The results are unreliable."); |
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} |
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// We still have to perform an underflow check for the right truncation point when lambda >= 400.
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if (m >= 400) { |
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// Use Proposition 5 of Fox--Glynn.
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i = right - m; |
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result = log_c_m_inf - i * (i + 1) / (2 * lambda); |
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if (result <= tau) { |
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int64_t const log10_result = static_cast<int64_t>(std::floor(result * log10_e)); |
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STORM_LOG_WARN("Fox-Glynn: lambda >= 25, underflow near Poi(" << lambda << "," << right << ") <= " << std::exp(result - log10_result/log10_e) << log10_result << ". The results are unreliable."); |
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} |
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} |
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} |
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return fgresult; |
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} |
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template<typename ValueType> |
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FoxGlynnResult<ValueType> foxGlynnWeighter(ValueType lambda, ValueType epsilon) { |
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ValueType tau = std::numeric_limits<ValueType>::min(); |
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// The magic m point.
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uint64_t m = static_cast<uint64_t>(lambda); |
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int64_t j, t; |
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FoxGlynnResult<ValueType> result = foxGlynnFinder(lambda, epsilon); |
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// Fill the left side of the array.
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for (j = m - result.left; j > 0; --j) { |
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result.weights[j - 1] = (j + result.left) / lambda * result.weights[j]; |
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} |
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t = result.right - result.left; |
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// Fill the right side of the array, have two cases lambda < 400 & lambda >= 400.
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if (m < 400) { |
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// Perform the underflow check, according to Fox-Glynn.
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STORM_LOG_THROW(result.right <= 600, storm::exceptions::PrecisionExceededException, "Fox-Glynn: " << result.right << " > 600, underflow is possible."); |
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// Compute weights.
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for (j = m - result.left; j < t; ++j) { |
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ValueType q = lambda / (j + 1 + result.left); |
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if (result.weights[j] > tau / q) { |
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result.weights[j + 1] = q * result.weights[j]; |
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} else { |
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t = j; |
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result.right = j + result.left; |
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// It's time to compute W.
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break; |
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} |
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} |
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} else { |
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// Compute weights.
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for (j = m - result.left; j < t; ++j) { |
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result.weights[j + 1] = lambda / (j + 1 + result.left) * result.weights[j]; |
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} |
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} |
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// It is time to compute the normalization weight W.
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result.totalWeight = storm::utility::zero<ValueType>(); |
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j = 0; |
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// t was set above.
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while(j < t) { |
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if (result.weights[j] <= result.weights[t]) { |
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result.totalWeight += result.weights[j]; |
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j++; |
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} else { |
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result.totalWeight += result.weights[t]; |
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t--; |
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} |
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} |
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result.totalWeight += result.weights[j]; |
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STORM_LOG_TRACE("Fox-Glynn: ltp = " << result.left << ", rtp = " << result.right << ", w = " << result.totalWeight << "."); |
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return result; |
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} |
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template<typename ValueType> |
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FoxGlynnResult<ValueType> foxGlynn(ValueType lambda, ValueType epsilon) { |
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STORM_LOG_THROW(lambda > 0, storm::exceptions::InvalidArgumentException, "Fox-Glynn requires positive lambda."); |
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return foxGlynnWeighter(lambda, epsilon); |
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} |
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template FoxGlynnResult<double> foxGlynn(double lambda, double epsilon); |
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} |
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} |
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} |
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@ -1,131 +1,23 @@ |
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#include <vector> |
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#include <tuple> |
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#include <cmath> |
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#include "storm/utility/macros.h" |
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#include "storm/utility/constants.h" |
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#include "storm/exceptions/InvalidArgumentException.h" |
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#include "storm/exceptions/OutOfRangeException.h" |
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#include <cstdint> |
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namespace storm { |
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namespace utility { |
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namespace numerical { |
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template<typename ValueType> |
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struct FoxGlynnResult { |
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FoxGlynnResult(); |
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uint64_t left; |
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uint64_t right; |
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ValueType totalWeight; |
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std::vector<ValueType> weights; |
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}; |
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template<typename ValueType> |
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std::tuple<uint_fast64_t, uint_fast64_t, ValueType, std::vector<ValueType>> getFoxGlynnCutoff(ValueType lambda, ValueType overflow, ValueType accuracy) { |
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STORM_LOG_THROW(lambda != storm::utility::zero<ValueType>(), storm::exceptions::InvalidArgumentException, "Error in Fox-Glynn algorithm: lambda must not be zero."); |
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FoxGlynnResult<ValueType> foxGlynn(ValueType lambda, ValueType epsilon); |
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// This code is a modified version of the one in PRISM. According to their implementation, for lambda |
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// smaller than 400, we compute the result using the naive method. |
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if (lambda < 400) { |
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ValueType eToPowerMinusLambda = std::exp(-lambda); |
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ValueType targetValue = (1 - accuracy) / eToPowerMinusLambda; |
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std::vector<ValueType> weights; |
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ValueType exactlyKEvents = 1; |
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ValueType atMostKEvents = exactlyKEvents; |
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weights.push_back(exactlyKEvents * eToPowerMinusLambda); |
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uint_fast64_t k = 1; |
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do { |
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exactlyKEvents *= lambda / k; |
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atMostKEvents += exactlyKEvents; |
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weights.push_back(exactlyKEvents * eToPowerMinusLambda); |
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++k; |
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} while (atMostKEvents < targetValue); |
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return std::make_tuple(0, k - 1, 1.0, weights); |
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} else { |
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STORM_LOG_THROW(accuracy >= 1e-10, storm::exceptions::InvalidArgumentException, "Error in Fox-Glynn algorithm: the accuracy must not be below 1e-10."); |
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// Factor from Fox&Glynn's paper. The paper does not explain where it comes from. |
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ValueType factor = 1e+10; |
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// Now start the Finder algorithm to find the truncation points. |
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ValueType m = std::floor(lambda); |
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uint_fast64_t leftTruncationPoint = 0, rightTruncationPoint = 0; |
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{ |
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// Factors used by the corollaries explained in Fox & Glynns paper. |
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// Square root of pi. |
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ValueType sqrtpi = 1.77245385090551602729; |
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// Square root of 2. |
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ValueType sqrt2 = 1.41421356237309504880; |
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// Set up a_\lambda, b_\lambda, and the square root of lambda. |
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ValueType aLambda = 0, bLambda = 0, sqrtLambda = 0; |
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if (m < 400) { |
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sqrtLambda = std::sqrt(400.0); |
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aLambda = (1.0 + 1.0 / 400.0) * std::exp(0.0625) * sqrt2; |
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bLambda = (1.0 + 1.0 / 400.0) * std::exp(0.125 / 400.0); |
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} else { |
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sqrtLambda = std::sqrt(lambda); |
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aLambda = (1.0 + 1.0 / lambda) * std::exp(0.0625) * sqrt2; |
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bLambda = (1.0 + 1.0 / lambda) * std::exp(0.125 / lambda); |
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} |
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// Use Corollary 1 from the paper to find the right truncation point. |
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uint_fast64_t k = 4; |
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ValueType dkl = 1.0 / (1 - std::exp(-(2.0 / 9.0) * (k * sqrt2 * sqrtLambda + 1.5))); |
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// According to David Jansen the upper bound can be ignored to achieve more accurate results. |
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// Right hand side of the equation in Corollary 1. |
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while ((accuracy / 2.0) < (aLambda * dkl * std::exp(-(k*k / 2.0)) / (k * sqrt2 * sqrtpi))) { |
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++k; |
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// d(k,Lambda) from the paper. |
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dkl = 1.0 / (1 - std::exp(-(2.0 / 9.0)*(k * sqrt2 * sqrtLambda + 1.5))); |
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} |
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// Left hand side of the equation in Corollary 1. |
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rightTruncationPoint = static_cast<uint_fast64_t>(std::ceil((m + k * sqrt2 * sqrtLambda + 1.5))); |
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// Use Corollary 2 to find left truncation point. |
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k = 4; |
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// Right hand side of the equation in Corollary 2. |
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while ((accuracy / 2.0) < ((bLambda * std::exp(-(k*k / 2.0))) / (k * sqrt2 * sqrtpi))) { |
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++k; |
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} |
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|
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// Left hand side of the equation in Corollary 2. |
|||
leftTruncationPoint = static_cast<uint_fast64_t>(std::max(std::trunc(m - k * sqrtLambda - 1.5), storm::utility::zero<ValueType>())); |
|||
|
|||
// Check for underflow. |
|||
STORM_LOG_THROW(std::trunc((m - k * sqrtLambda - 1.5)) >= 0, storm::exceptions::OutOfRangeException, "Error in Fox-Glynn algorithm: Underflow of left truncation point."); |
|||
} |
|||
|
|||
std::vector<ValueType> weights(rightTruncationPoint - leftTruncationPoint + 1); |
|||
weights[m - leftTruncationPoint] = overflow / (factor * (rightTruncationPoint - leftTruncationPoint)); |
|||
for (uint_fast64_t j = m; j > leftTruncationPoint; --j) { |
|||
weights[j - 1 - leftTruncationPoint] = (j / lambda) * weights[j - leftTruncationPoint]; |
|||
} |
|||
|
|||
for (uint_fast64_t j = m; j < rightTruncationPoint; ++j) { |
|||
weights[j + 1 - leftTruncationPoint] = (lambda / (j + 1)) * weights[j - leftTruncationPoint]; |
|||
} |
|||
|
|||
|
|||
// Compute the total weight and start with smallest to avoid roundoff errors. |
|||
ValueType totalWeight = storm::utility::zero<ValueType>(); |
|||
|
|||
uint_fast64_t s = leftTruncationPoint; |
|||
uint_fast64_t t = rightTruncationPoint; |
|||
while (s < t) { |
|||
if (weights[s - leftTruncationPoint] <= weights[t - leftTruncationPoint]) { |
|||
totalWeight += weights[s - leftTruncationPoint]; |
|||
++s; |
|||
} else { |
|||
totalWeight += weights[t - leftTruncationPoint]; |
|||
--t; |
|||
} |
|||
} |
|||
|
|||
totalWeight += weights[s - leftTruncationPoint]; |
|||
|
|||
return std::make_tuple(leftTruncationPoint, rightTruncationPoint, totalWeight, weights); |
|||
} |
|||
} |
|||
} |
|||
} |
|||
} |
|||
@ -1,4 +1,4 @@ |
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set(STORM_VERSION_MAJOR 1) |
|||
set(STORM_VERSION_MINOR 1) |
|||
set(STORM_VERSION_MINOR 2) |
|||
set(STORM_VERSION_PATCH 0) |
|||
|
|||
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