Renabled BLAS using ATLAS for Linux, fixed a variety of annoying warnings
Alex Cunningham
parent
fa954ab55e
commit
e8979dafad
17
.cproject
17
.cproject
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@ -317,6 +317,7 @@
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</target>
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<target name="clean" path="wrap" targetID="org.eclipse.cdt.build.MakeTargetBuilder">
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<buildCommand>make</buildCommand>
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<buildArguments/>
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<buildTarget>clean</buildTarget>
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<stopOnError>true</stopOnError>
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<useDefaultCommand>true</useDefaultCommand>
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@ -476,7 +477,6 @@
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</target>
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<target name="testBayesTree.run" path="cpp" targetID="org.eclipse.cdt.build.MakeTargetBuilder">
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<buildCommand>make</buildCommand>
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<buildArguments/>
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<buildTarget>testBayesTree.run</buildTarget>
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<stopOnError>true</stopOnError>
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<useDefaultCommand>false</useDefaultCommand>
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@ -484,6 +484,7 @@
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</target>
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<target name="testSymbolicBayesNet.run" path="cpp" targetID="org.eclipse.cdt.build.MakeTargetBuilder">
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<buildCommand>make</buildCommand>
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<buildArguments/>
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<buildTarget>testSymbolicBayesNet.run</buildTarget>
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<stopOnError>true</stopOnError>
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<useDefaultCommand>false</useDefaultCommand>
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@ -491,7 +492,6 @@
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</target>
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<target name="testSymbolicFactorGraph.run" path="cpp" targetID="org.eclipse.cdt.build.MakeTargetBuilder">
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<buildCommand>make</buildCommand>
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<buildArguments/>
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<buildTarget>testSymbolicFactorGraph.run</buildTarget>
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<stopOnError>true</stopOnError>
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<useDefaultCommand>false</useDefaultCommand>
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@ -683,7 +683,6 @@
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</target>
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<target name="testGraph.run" path="cpp" targetID="org.eclipse.cdt.build.MakeTargetBuilder">
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<buildCommand>make</buildCommand>
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<buildArguments/>
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<buildTarget>testGraph.run</buildTarget>
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<stopOnError>true</stopOnError>
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<useDefaultCommand>false</useDefaultCommand>
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@ -739,6 +738,7 @@
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</target>
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<target name="testSimulated2D.run" path="cpp" targetID="org.eclipse.cdt.build.MakeTargetBuilder">
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<buildCommand>make</buildCommand>
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<buildArguments/>
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<buildTarget>testSimulated2D.run</buildTarget>
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<stopOnError>true</stopOnError>
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<useDefaultCommand>false</useDefaultCommand>
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@ -786,7 +786,6 @@
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</target>
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<target name="testErrors.run" path="cpp" targetID="org.eclipse.cdt.build.MakeTargetBuilder">
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<buildCommand>make</buildCommand>
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<buildArguments/>
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<buildTarget>testErrors.run</buildTarget>
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<stopOnError>true</stopOnError>
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<useDefaultCommand>false</useDefaultCommand>
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@ -794,7 +793,6 @@
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</target>
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<target name="testDSF.run" path="cpp" targetID="org.eclipse.cdt.build.MakeTargetBuilder">
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<buildCommand>make</buildCommand>
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<buildArguments/>
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<buildTarget>testDSF.run</buildTarget>
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<stopOnError>true</stopOnError>
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<useDefaultCommand>true</useDefaultCommand>
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@ -810,12 +808,19 @@
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</target>
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<target name="testConstraintOptimizer.run" path="cpp" targetID="org.eclipse.cdt.build.MakeTargetBuilder">
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<buildCommand>make</buildCommand>
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<buildArguments/>
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<buildTarget>testConstraintOptimizer.run</buildTarget>
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<stopOnError>true</stopOnError>
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<useDefaultCommand>true</useDefaultCommand>
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<runAllBuilders>true</runAllBuilders>
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</target>
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<target name="testBTree.run" path="cpp" targetID="org.eclipse.cdt.build.MakeTargetBuilder">
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<buildCommand>make</buildCommand>
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<buildArguments/>
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<buildTarget>testBTree.run</buildTarget>
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<stopOnError>true</stopOnError>
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<useDefaultCommand>true</useDefaultCommand>
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<runAllBuilders>true</runAllBuilders>
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</target>
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<target name="install" path="" targetID="org.eclipse.cdt.build.MakeTargetBuilder">
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<buildCommand>make</buildCommand>
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<buildArguments>-j2</buildArguments>
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@ -41,15 +41,15 @@ namespace gtsam {
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* leaf node with height 1
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*/
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Node(const value_type& keyValue) :
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keyValue_(keyValue), height_(1) {
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height_(1), keyValue_(keyValue) {
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}
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/**
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* Create a node from two subtrees and a key value pair
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*/
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Node(const BTree& l, const value_type& keyValue, const BTree& r) :
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left(l), keyValue_(keyValue), right(r),
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height_(l.height() >= r.height() ? l.height() + 1 : r.height() + 1) {
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height_(l.height() >= r.height() ? l.height() + 1 : r.height() + 1),
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keyValue_(keyValue), left(l), right(r) {
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}
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inline const Key& key() const { return keyValue_.first;}
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@ -56,7 +56,7 @@ namespace gtsam {
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BinaryConditional(const Symbol& key, const Symbol& parent, const std::vector<double>& cpt) :
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Conditional(key) {
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parents_.push_back(parent);
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for( int i = 0 ; i < cpt.size() ; i++ )
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for( size_t i = 0 ; i < cpt.size() ; i++ )
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cpt_.push_back(1-cpt[i]); // p(!x|parents)
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cpt_.insert(cpt_.end(),cpt.begin(),cpt.end()); // p(x|parents)
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}
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@ -105,7 +105,7 @@ void FactorGraph<Factor>::push_back(const FactorGraph<Factor>& factors) {
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/* ************************************************************************* */
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template<class Factor>
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void FactorGraph<Factor>::replace(int index, sharedFactor factor) {
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void FactorGraph<Factor>::replace(size_t index, sharedFactor factor) {
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if(index >= factors_.size())
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throw invalid_argument(boost::str(boost::format(
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"Factor graph does not contain a factor with index %d.") % index));
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@ -321,7 +321,7 @@ template<class Factor> void FactorGraph<Factor>::checkGraphConsistency() const {
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// Make sure each factor listed for a variable actually involves that variable
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BOOST_FOREACH(const SymbolMap<list<int> >::value_type& var, indices_) {
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BOOST_FOREACH(int i, var.second) {
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BOOST_FOREACH(size_t i, var.second) {
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if(i >= factors_.size()) {
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cout << "*** Factor graph inconsistency: " << (string)var.first << " lists factor " <<
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i << " but the graph does not contain this many factors." << endl;
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@ -380,8 +380,8 @@ void FactorGraph<Factor>::split(const PredecessorMap<Key>& tree, FactorGraph<Fac
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Key key1 = factor2->key1();
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Key key2 = factor2->key2();
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// if the tree contains the key
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if (tree.find(key1) != tree.end() && tree.find(key1)->second.compare(key2) == 0 ||
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tree.find(key2) != tree.end() && tree.find(key2)->second.compare(key1) == 0)
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if ((tree.find(key1) != tree.end() && tree.find(key1)->second.compare(key2) == 0) ||
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(tree.find(key2) != tree.end() && tree.find(key2)->second.compare(key1) == 0))
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Ab1.push_back(factor2);
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else
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Ab2.push_back(factor2);
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@ -87,7 +87,7 @@ namespace gtsam {
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void push_back(const FactorGraph<Factor>& factors);
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/** replace a factor by index */
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void replace(int index, sharedFactor factor);
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void replace(size_t index, sharedFactor factor);
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/** return keys in some random order */
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Ordering keys() const;
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@ -59,7 +59,6 @@ namespace gtsam {
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for ( rit=bayesNet.rbegin(); rit != bayesNet.rend(); ++rit )
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this->insert(*rit, index);
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int count = 0;
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// add orphans to the bottom of the new tree
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BOOST_FOREACH(sharedClique orphan, orphans) {
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@ -306,8 +306,8 @@ AM_LDFLAGS = -L../CppUnitLite -lCppUnitLite $(BOOST_LDFLAGS) $(boost_serializati
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if USE_BLAS_LINUX
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AM_CXXFLAGS += -DGT_USE_CBLAS
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libgtsam_la_CPPFLAGS += -DGT_USE_CBLAS
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AM_LDFLAGS += $(BLAS_LIBS) $(LIBS) $(FLIBS)
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libgtsam_la_LDFLAGS += $(BLAS_LIBS) $(LIBS) $(FLIBS)
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AM_LDFLAGS += -lcblas -latlas # If getting from script: $(BLAS_LIBS) $(LIBS) $(FLIBS)
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libgtsam_la_LDFLAGS += -lcblas -latlas # $(BLAS_LIBS) $(LIBS) $(FLIBS)
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endif
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if USE_BLAS_MACOS
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@ -268,10 +268,10 @@ void transposeMultiplyAdd(double alpha, const Matrix& A, const Vector& e, SubVec
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// ublas x += prod(trans(A),e) is terribly slow
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// TODO: use BLAS
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size_t m = A.size1(), n = A.size2();
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for (int j = 0; j < n; j++) {
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for (size_t j = 0; j < n; j++) {
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const double * ei = e.data().begin();
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const double * aij = A.data().begin() + j;
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for (int i = 0; i < m; i++, aij+=n, ei++)
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for (size_t i = 0; i < m; i++, aij+=n, ei++)
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x(j) += alpha * (*aij) * (*ei);
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}
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}
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@ -293,13 +293,6 @@ Vector column_(const Matrix& A, size_t j) {
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// throw invalid_argument("Column index out of bounds!");
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return column(A,j); // real boost version
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// TODO: improve this
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// size_t m = A.size1();
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// Vector a(m);
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// for (size_t i=0; i<m; ++i)
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// a(i) = A(i,j);
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// return a;
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}
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/* ************************************************************************* */
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@ -348,7 +341,7 @@ Matrix sub(const Matrix& A, size_t i1, size_t i2, size_t j1, size_t j2) {
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/* ************************************************************************* */
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void insertSub(Matrix& big, const Matrix& small, size_t i, size_t j) {
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// direct pointer method
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size_t ib = big.size1(), jb = big.size2(),
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size_t jb = big.size2(),
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is = small.size1(), js = small.size2();
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// pointer to start of window in big
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@ -472,13 +465,13 @@ inline void householder_update_manual(Matrix &A, int j, double beta, const Vecto
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}
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void householder_update(Matrix &A, int j, double beta, const Vector& vjm) {
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const size_t m = A.size1(), n = A.size2();
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#if defined GT_USE_CBLAS
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// CBLAS version not working, using manual approach
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householder_update_manual(A,j,beta,vjm);
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// // straight atlas version
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// const size_t m = A.size1(), n = A.size2();
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// const size_t mj = m-j;
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//
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// // find pointers to the data
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@ -659,8 +652,9 @@ void householder(Matrix &A, size_t k) {
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/* ************************************************************************* */
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Vector backSubstituteUpper(const Matrix& U, const Vector& b, bool unit) {
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size_t m = U.size1(), n = U.size2();
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size_t n = U.size2();
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#ifndef NDEBUG
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size_t m = U.size1();
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if (m!=n)
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throw invalid_argument("backSubstituteUpper: U must be square");
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#endif
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@ -679,8 +673,9 @@ Vector backSubstituteUpper(const Matrix& U, const Vector& b, bool unit) {
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/* ************************************************************************* */
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Vector backSubstituteUpper(const Vector& b, const Matrix& U, bool unit) {
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size_t m = U.size1(), n = U.size2();
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size_t n = U.size2();
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#ifndef NDEBUG
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size_t m = U.size1();
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if (m!=n)
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throw invalid_argument("backSubstituteUpper: U must be square");
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#endif
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@ -699,8 +694,9 @@ Vector backSubstituteUpper(const Vector& b, const Matrix& U, bool unit) {
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/* ************************************************************************* */
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Vector backSubstituteLower(const Matrix& L, const Vector& b, bool unit) {
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size_t m = L.size1(), n = L.size2();
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size_t n = L.size2();
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#ifndef NDEBUG
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size_t m = U.size1();
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if (m!=n)
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throw invalid_argument("backSubstituteLower: L must be square");
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#endif
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@ -750,11 +746,12 @@ Matrix collect(const std::vector<const Matrix *>& matrices, size_t m, size_t n)
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// if we have known and constant dimensions, use them
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size_t dimA1 = m;
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size_t dimA2 = n*matrices.size();
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if (!m && !n)
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if (!m && !n) {
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BOOST_FOREACH(const Matrix* M, matrices) {
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dimA1 = M->size1(); // TODO: should check if all the same !
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dimA2 += M->size2();
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}
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}
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// memcpy version
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Matrix A(dimA1, dimA2);
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@ -896,11 +893,11 @@ Matrix RtR(const Matrix &A)
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/* ************************************************************************* */
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Vector solve_ldl(const Matrix& M, const Vector& rhs) {
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int N = M.size1(); // size of the matrix
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unsigned int N = M.size1(); // size of the matrix
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// count the nonzero entries above diagonal
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double thresh = 1e-9;
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size_t nrANZ = 0; // # of nonzeros on diagonal and upper triangular part of A
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unsigned int nrANZ = 0; // # of nonzeros on diagonal and upper triangular part of A
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for (size_t i=0; i<N; ++i) // rows
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for (size_t j=i; j<N; ++j) // columns
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if (fabs(M(i,j)) > thresh)
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@ -950,7 +947,7 @@ Vector solve_ldl(const Matrix& M, const Vector& rhs) {
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double * Lx = new double[nrLNZ];
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int * Li = new int [nrLNZ];
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int d = LDL_numeric (N, Ap, Ai, Ax, Lp, Parent, Lnz, Li, Lx, D, Y, Pattern,
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size_t d = LDL_numeric (N, Ap, Ai, Ax, Lp, Parent, Lnz, Li, Lx, D, Y, Pattern,
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Flag, NULL, NULL);
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if (d == N) {
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@ -49,7 +49,7 @@ NonlinearConstraint1<Config, Key, X>::NonlinearConstraint1(
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const LagrangeKey& lagrange_key,
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bool isEquality) :
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NonlinearConstraint<Config>(lagrange_key, dim_constraint, isEquality),
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g_(boost::bind(g, _1)), G_(boost::bind(gradG, _1)), key_(key)
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G_(boost::bind(gradG, _1)), g_(boost::bind(g, _1)), key_(key)
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{
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this->keys_.push_back(key);
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}
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@ -64,7 +64,7 @@ NonlinearConstraint1<Config, Key, X>::NonlinearConstraint1(
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const LagrangeKey& lagrange_key,
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bool isEquality) :
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NonlinearConstraint<Config>(lagrange_key, dim_constraint, isEquality),
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g_(g), G_(gradG), key_(key)
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G_(gradG), g_(g), key_(key)
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{
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this->keys_.push_back(key);
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}
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@ -144,7 +144,7 @@ NonlinearConstraint2<Config, Key1, X1, Key2, X2>::NonlinearConstraint2(
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const LagrangeKey& lagrange_key,
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bool isEquality) :
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NonlinearConstraint<Config>(lagrange_key, dim_constraint, isEquality),
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g_(boost::bind(g, _1)), G1_(boost::bind(G1, _1)), G2_(boost::bind(G2, _1)),
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G1_(boost::bind(G1, _1)), G2_(boost::bind(G2, _1)), g_(boost::bind(g, _1)),
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key1_(key1), key2_(key2)
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{
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this->keys_.push_back(key1);
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@ -163,7 +163,7 @@ NonlinearConstraint2<Config, Key1, X1, Key2, X2>::NonlinearConstraint2(
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const LagrangeKey& lagrange_key,
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bool isEquality) :
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NonlinearConstraint<Config>(lagrange_key, dim_constraint, isEquality),
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g_(g), G1_(G1), G2_(G2),
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G1_(G1), G2_(G2), g_(g),
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key1_(key1), key2_(key2)
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{
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this->keys_.push_back(key1);
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@ -67,9 +67,8 @@ namespace simulated3D {
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Simulated3DMeasurement(const Vector& z,
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const SharedGaussian& model, PoseKey& j1, PointKey j2) :
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z_(z),
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NonlinearFactor2<VectorConfig, PoseKey, Vector, PointKey, Vector> (
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model, j1, j2) {
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model, j1, j2), z_(z) {
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}
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Vector evaluateError(const Vector& x1, const Vector& x2, boost::optional<
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@ -22,7 +22,6 @@ namespace gtsam {
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*/
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template<class X>
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Vector numericalGradient(double (*h)(const X&), const X& x, double delta=1e-5) {
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double hx = h(x);
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double factor = 1.0/(2.0*delta);
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const size_t n = x.dim();
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Vector d(n,0.0), g(n,0.0);
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@ -78,7 +78,7 @@ namespace gtsam {
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GenericOdometry(const Point2& z, const SharedGaussian& model,
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const Key& i1, const Key& i2) :
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z_(z), NonlinearFactor2<Cfg, Key, Point2, Key, Point2> (model, i1, i2) {
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NonlinearFactor2<Cfg, Key, Point2, Key, Point2> (model, i1, i2), z_(z) {
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}
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Vector evaluateError(const Point2& x1, const Point2& x2, boost::optional<
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@ -100,7 +100,7 @@ namespace gtsam {
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GenericMeasurement(const Point2& z, const SharedGaussian& model,
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const XKey& i, const LKey& j) :
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z_(z), NonlinearFactor2<Cfg, XKey, Point2, LKey, Point2> (model, i, j) {
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NonlinearFactor2<Cfg, XKey, Point2, LKey, Point2> (model, i, j), z_(z) {
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}
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Vector evaluateError(const Point2& x1, const Point2& x2, boost::optional<
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@ -460,8 +460,8 @@ TEST( GaussianFactorGraph, combine)
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GaussianFactorGraph fg2 = createGaussianFactorGraph();
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|
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// get sizes
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int size1 = fg1.size();
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int size2 = fg2.size();
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size_t size1 = fg1.size();
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size_t size2 = fg2.size();
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// combine them
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fg1.combine(fg2);
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||||
|
|
@ -479,8 +479,8 @@ TEST( GaussianFactorGraph, combine2)
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GaussianFactorGraph fg2 = createGaussianFactorGraph();
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|
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// get sizes
|
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int size1 = fg1.size();
|
||||
int size2 = fg2.size();
|
||||
size_t size1 = fg1.size();
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||||
size_t size2 = fg2.size();
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||||
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||||
// combine them
|
||||
GaussianFactorGraph fg3 = GaussianFactorGraph::combine2(fg1, fg2);
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|
|
@ -491,7 +491,7 @@ TEST( GaussianFactorGraph, combine2)
|
|||
/* ************************************************************************* */
|
||||
// print a vector of ints if needed for debugging
|
||||
void print(vector<int> v) {
|
||||
for (int k = 0; k < v.size(); k++)
|
||||
for (size_t k = 0; k < v.size(); k++)
|
||||
cout << v[k] << " ";
|
||||
cout << endl;
|
||||
}
|
||||
|
|
|
|||
|
|
@ -795,19 +795,19 @@ TEST( matrix, svd_sort )
|
|||
// update A, b
|
||||
// A' \define A_{S}-ar and b'\define b-ad
|
||||
// __attribute__ ((noinline)) // uncomment to prevent inlining when profiling
|
||||
static void updateAb(Matrix& A, Vector& b, int j, const Vector& a,
|
||||
const Vector& r, double d) {
|
||||
const size_t m = A.size1(), n = A.size2();
|
||||
for (int i = 0; i < m; i++) { // update all rows
|
||||
double ai = a(i);
|
||||
b(i) -= ai * d;
|
||||
double *Aij = A.data().begin() + i * n + j + 1;
|
||||
const double *rptr = r.data().begin() + j + 1;
|
||||
// A(i,j+1:end) -= ai*r(j+1:end)
|
||||
for (int j2 = j + 1; j2 < n; j2++, Aij++, rptr++)
|
||||
*Aij -= ai * (*rptr);
|
||||
}
|
||||
}
|
||||
//static void updateAb(Matrix& A, Vector& b, int j, const Vector& a,
|
||||
// const Vector& r, double d) {
|
||||
// const size_t m = A.size1(), n = A.size2();
|
||||
// for (int i = 0; i < m; i++) { // update all rows
|
||||
// double ai = a(i);
|
||||
// b(i) -= ai * d;
|
||||
// double *Aij = A.data().begin() + i * n + j + 1;
|
||||
// const double *rptr = r.data().begin() + j + 1;
|
||||
// // A(i,j+1:end) -= ai*r(j+1:end)
|
||||
// for (int j2 = j + 1; j2 < n; j2++, Aij++, rptr++)
|
||||
// *Aij -= ai * (*rptr);
|
||||
// }
|
||||
//}
|
||||
|
||||
/* ************************************************************************* */
|
||||
TEST( matrix, weighted_elimination )
|
||||
|
|
|
|||
|
|
@ -53,7 +53,6 @@ TEST(NoiseModel, constructors)
|
|||
m.push_back(Isotropic::Precision(3, prc));
|
||||
|
||||
// test whiten
|
||||
int i=0;
|
||||
BOOST_FOREACH(Gaussian::shared_ptr mi, m)
|
||||
CHECK(assert_equal(whitened,mi->whiten(unwhitened)));
|
||||
|
||||
|
|
|
|||
|
|
@ -139,7 +139,6 @@ namespace test2 {
|
|||
|
||||
/** jacobian for y, jacobianG(x,y) in y: -1 */
|
||||
Matrix G2(const VecConfig& config, const list<Key>& keys) {
|
||||
double x = config[keys.back()](0);
|
||||
return Matrix_(1, 1, -1.0);
|
||||
}
|
||||
|
||||
|
|
|
|||
|
|
@ -78,7 +78,6 @@ TEST( Pose2Graph, linearization )
|
|||
0.0, 2.0, 0.0,
|
||||
0.0, 0.0, 10.0);
|
||||
|
||||
double sigma = 1;
|
||||
Vector b = Vector_(3,-0.1/sx,0.1/sy,0.0);
|
||||
SharedDiagonal probModel1 = noiseModel::Unit::Create(3);
|
||||
lfg_expected.add("x1", A1, "x2", A2, b, probModel1);
|
||||
|
|
|
|||
|
|
@ -915,7 +915,6 @@ boost::shared_ptr<Graph2D> linearMapWarpGraph() {
|
|||
|
||||
/* ********************************************************************* */
|
||||
TEST ( SQPOptimizer, map_warp_initLam ) {
|
||||
bool verbose = false;
|
||||
// get a graph
|
||||
boost::shared_ptr<Graph2D> graph = linearMapWarpGraph();
|
||||
|
||||
|
|
|
|||
|
|
@ -65,7 +65,7 @@ namespace gtsam { namespace visualSLAM {
|
|||
GenericProjectionFactor(const Point2& z,
|
||||
const SharedGaussian& model, PosK j_pose,
|
||||
LmK j_landmark, const shared_ptrK& K) :
|
||||
z_(z), K_(K), Base(model, j_pose, j_landmark) {
|
||||
Base(model, j_pose, j_landmark), z_(z), K_(K) {
|
||||
}
|
||||
|
||||
/**
|
||||
|
|
|
|||
Loading…
Reference in New Issue