[opengm] 203/386: fixed minor bugs in examples
Ghislain Vaillant
ghisvail-guest at moszumanska.debian.org
Wed Aug 31 08:37:41 UTC 2016
This is an automated email from the git hooks/post-receive script.
ghisvail-guest pushed a commit to branch debian/master
in repository opengm.
commit aad5300e6057c18d6bc2171d5aca2952406a7df6
Author: DerThorsten <thorsten.beier at iwr.uni-heidelberg.de>
Date: Wed Jan 7 10:45:09 2015 +0100
fixed minor bugs in examples
---
src/examples/unsorted-examples/inference_types.cxx | 9 +++++----
src/tutorials/c++/basics/doMinSumInference.cxx | 2 +-
src/tutorials/c++/basics/doSumProdInference.cxx | 2 +-
src/unittest/inference/test_messagepassing.cxx | 20 ++++++++++----------
4 files changed, 17 insertions(+), 16 deletions(-)
diff --git a/src/examples/unsorted-examples/inference_types.cxx b/src/examples/unsorted-examples/inference_types.cxx
index 3ae18e5..dcc4b98 100644
--- a/src/examples/unsorted-examples/inference_types.cxx
+++ b/src/examples/unsorted-examples/inference_types.cxx
@@ -34,19 +34,20 @@ int main() {
// ....
// assume starting point is filled with labels
OptimizerMinimizerParameterType minimizerParameter(
- OptimizerMinimizerType::SINGLE_VARIABLE, // flip a single variable (FACTOR for flip all var. a factor depends on)
- startingPoint
+ OptimizerMinimizerType::SINGLE_VARIABLE // flip a single variable (FACTOR for flip all var. a factor depends on)
);
// without starting point
OptimizerMaximizerParameterType maximizerParameter(
- OptimizerMaximizerType::FACTOR, // flip a single variable (FACTOR for flip all var. a factor depends on)
- startingPoint
+ OptimizerMaximizerType::FACTOR // flip a single variable (FACTOR for flip all var. a factor depends on)
);
// construct optimizers ( minimizer and maximizer )
OptimizerMinimizerType optimizerMinimizer(gm,minimizerParameter);
OptimizerMaximizerType optimizerMaximizer(gm,maximizerParameter);
+ optimizerMinimizer.setStartingPoint(startingPoint.begin());
+ optimizerMaximizer.setStartingPoint(startingPoint.begin());
+
// optimize the models ( minimizer and maximize )
optimizerMinimizer.infer();
optimizerMaximizer.infer();
diff --git a/src/tutorials/c++/basics/doMinSumInference.cxx b/src/tutorials/c++/basics/doMinSumInference.cxx
index bc8a11e..1aa00a0 100644
--- a/src/tutorials/c++/basics/doMinSumInference.cxx
+++ b/src/tutorials/c++/basics/doMinSumInference.cxx
@@ -123,7 +123,7 @@ int main(int argc, char** argv) {
// Infer with TRWSI
std::cout << "Start TRWSi inference ... " <<std::endl;
typedef opengm::TRWSi<Model,opengm::Minimizer> TRWSi;
- TRWSi::Parameter para(100);
+ TRWSi::Parameter para(size_t(100));
para.precision_=1e-12;
TRWSi trws(gm,para);
trws.infer();
diff --git a/src/tutorials/c++/basics/doSumProdInference.cxx b/src/tutorials/c++/basics/doSumProdInference.cxx
index 2cad7da..e4a792b 100644
--- a/src/tutorials/c++/basics/doSumProdInference.cxx
+++ b/src/tutorials/c++/basics/doSumProdInference.cxx
@@ -126,7 +126,7 @@ void inferBP(const Model& gm, bool normalization = true){
typedef opengm::BeliefPropagationUpdateRules<Model, opengm::Integrator> UpdateRules;
typedef opengm::MessagePassing<Model, opengm::Integrator, UpdateRules, opengm::MaxDistance> LBP;
- LBP::Parameter parameter(100); //maximal number of iterations=0
+ LBP::Parameter parameter(size_t(100)); //maximal number of iterations=0
parameter.useNormalization_ = normalization;
LBP lbp(gm, parameter);
diff --git a/src/unittest/inference/test_messagepassing.cxx b/src/unittest/inference/test_messagepassing.cxx
index a065942..9bed1b0 100644
--- a/src/unittest/inference/test_messagepassing.cxx
+++ b/src/unittest/inference/test_messagepassing.cxx
@@ -167,7 +167,7 @@ int main() {
typedef opengm::GraphicalModel<double, opengm::Adder> GraphicalModelType;
typedef opengm::BeliefPropagationUpdateRules<GraphicalModelType,opengm::Minimizer> UpdateRulesType;
typedef opengm::MessagePassing<GraphicalModelType, opengm::Minimizer,UpdateRulesType, opengm::MaxDistance> BP;
- BP::Parameter para(10);
+ BP::Parameter para(size_t(10));
sumTester.test<BP>(para);
std::cout << " ... parallel ... ";
para.isAcyclic_=opengm::Tribool::False;
@@ -179,7 +179,7 @@ int main() {
typedef opengm::GraphicalModel<double, opengm::Adder> GraphicalModelType;
typedef opengm::BeliefPropagationUpdateRules<GraphicalModelType,opengm::Minimizer> UpdateRulesType;
typedef opengm::MessagePassing<GraphicalModelType, opengm::Minimizer,UpdateRulesType, opengm::MaxDistance> BP;
- BP::Parameter para(100);
+ BP::Parameter para(size_t(100));
para.isAcyclic_ = false;
sumTester.test<BP>(para);
std::cout << " OK!"<<std::endl;
@@ -198,7 +198,7 @@ int main() {
typedef opengm::GraphicalModel<double,opengm::Adder> GraphicalModelType;
typedef opengm::BeliefPropagationUpdateRules<GraphicalModelType,opengm::Maximizer> UpdateRulesType;
typedef opengm::MessagePassing<GraphicalModelType, opengm::Maximizer,UpdateRulesType, opengm::MaxDistance> BP;
- BP::Parameter para(10);
+ BP::Parameter para(size_t(10));
sumTester.test<BP>(para);
std::cout << " OK!"<<std::endl;
}
@@ -207,7 +207,7 @@ int main() {
typedef opengm::GraphicalModel<double,opengm::Multiplier > GraphicalModelType;
typedef opengm::BeliefPropagationUpdateRules<GraphicalModelType,opengm::Maximizer> UpdateRulesType;
typedef opengm::MessagePassing<GraphicalModelType, opengm::Maximizer,UpdateRulesType, opengm::MaxDistance> BP;
- BP::Parameter para(10);
+ BP::Parameter para(size_t(10));
prodTester.test<BP>(para);
std::cout << " OK!"<<std::endl;
}
@@ -290,7 +290,7 @@ int main() {
typedef opengm::GraphicalModel<double,opengm::Adder > GraphicalModelType;
typedef opengm::TrbpUpdateRules<GraphicalModelType,opengm::Minimizer> UpdateRulesType;
typedef opengm::MessagePassing<GraphicalModelType, opengm::Minimizer,UpdateRulesType, opengm::MaxDistance> BP;
- BP::Parameter para(10);
+ BP::Parameter para(size_t(100));
sumTester.test<BP>(para);
std::cout << " ... parallel ... ";
para.isAcyclic_=opengm::Tribool::False;
@@ -323,7 +323,7 @@ int main() {
typedef opengm::GraphicalModel<double,opengm::Adder> GraphicalModelType;
typedef opengm::TrbpUpdateRules<GraphicalModelType,opengm::Maximizer> UpdateRulesType;
typedef opengm::MessagePassing<GraphicalModelType, opengm::Maximizer, UpdateRulesType,opengm::MaxDistance> BP;
- BP::Parameter para(10);
+ BP::Parameter para(size_t(10));
sumTester.test<BP>(para);
std::cout << " OK!"<<std::endl;
}
@@ -332,7 +332,7 @@ int main() {
typedef opengm::GraphicalModel<double,opengm::Multiplier > GraphicalModelType;
typedef opengm::TrbpUpdateRules<GraphicalModelType,opengm::Maximizer> UpdateRulesType;
typedef opengm::MessagePassing<GraphicalModelType, opengm::Maximizer, UpdateRulesType,opengm::MaxDistance> BP;
- BP::Parameter para(10);
+ BP::Parameter para(size_t(10));
prodTester.test<BP>(para);
std::cout << " OK!"<<std::endl;
}
@@ -341,7 +341,7 @@ int main() {
typedef opengm::GraphicalModel<double,opengm::Multiplier > GraphicalModelType;
typedef opengm::TrbpUpdateRules<GraphicalModelType,opengm::Maximizer> UpdateRulesType;
typedef opengm::MessagePassing<GraphicalModelType, opengm::Maximizer, UpdateRulesType, opengm::MaxDistance> BP;
- BP::Parameter para(10);
+ BP::Parameter para(size_t(10));
prodTester.test<BP>(para);
std::cout << " OK!"<<std::endl;
}
@@ -359,7 +359,7 @@ int main() {
typedef opengm::GraphicalModel<double,opengm::Adder > GraphicalModelType;
typedef opengm::TrbpUpdateRules<GraphicalModelType,opengm::Integrator> UpdateRulesType;
typedef opengm::MessagePassing<GraphicalModelType, opengm::Integrator,UpdateRulesType, opengm::MaxDistance> BP;
- BP::Parameter para(10);
+ BP::Parameter para(size_t(10));
sumTester.test<BP>(para);
std::cout << " OK!"<<std::endl;
}
@@ -368,7 +368,7 @@ int main() {
typedef opengm::GraphicalModel<double,opengm::Multiplier > GraphicalModelType;
typedef opengm::TrbpUpdateRules<GraphicalModelType,opengm::Integrator> UpdateRulesType;
typedef opengm::MessagePassing<GraphicalModelType, opengm::Integrator,UpdateRulesType, opengm::MaxDistance> BP;
- BP::Parameter para(10);
+ BP::Parameter para(size_t(10));
prodTester.test<BP>(para);
std::cout << " OK!"<<std::endl;
}
--
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