Replaced BOOSE_FOREACH with for in tests folder. Tested the changed code locally: successful.
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20b02d3f4d
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a464769ce1
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@ -26,7 +26,6 @@
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#include <CppUnitLite/TestHarness.h>
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#include <boost/foreach.hpp>
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#include <boost/assign/std/list.hpp> // for operator +=
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using namespace boost::assign;
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@ -220,7 +219,7 @@ TEST( GaussianBayesTree, balanced_smoother_shortcuts )
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// Permutation toFront(Permutation::PullToFront(C3->keys(), varIndex.size()));
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// Permutation toFrontInverse(*toFront.inverse());
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// varIndex.permute(toFront);
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// BOOST_FOREACH(const GaussianFactor::shared_ptr& factor, marginal) {
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// for(const GaussianFactor::shared_ptr& factor: marginal) {
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// factor->permuteWithInverse(toFrontInverse); }
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// GaussianBayesNet actual = *inference::EliminateUntil(marginal, C3->keys().size(), varIndex);
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// actual.permuteWithInverse(toFront);
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@ -26,7 +26,6 @@
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#include <CppUnitLite/TestHarness.h>
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#include <boost/foreach.hpp>
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#include <boost/tuple/tuple.hpp>
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#include <boost/assign/std/list.hpp> // for operator +=
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#include <boost/assign/std/set.hpp> // for operator +=
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@ -585,7 +584,7 @@ TEST( GaussianFactorGraph, conditional_sigma_failure) {
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GaussianBayesTree actBT = *lfg.eliminateMultifrontal();
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// Check that all sigmas in an unconstrained bayes tree are set to one
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BOOST_FOREACH(const GaussianBayesTree::sharedClique& clique, actBT.nodes() | br::map_values) {
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for(const GaussianBayesTree::sharedClique& clique: actBT.nodes() | br::map_values) {
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GaussianConditional::shared_ptr conditional = clique->conditional();
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//size_t dim = conditional->rows();
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//EXPECT(assert_equal(gtsam::Vector::Ones(dim), conditional->get_model()->sigmas(), tol));
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@ -22,7 +22,6 @@
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#include <gtsam/linear/GaussianISAM.h>
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#include <gtsam/inference/Ordering.h>
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#include <boost/foreach.hpp>
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#include <boost/assign/std/list.hpp> // for operator +=
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using namespace boost::assign;
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#include <boost/range/adaptor/map.hpp>
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@ -46,7 +45,7 @@ TEST( ISAM, iSAM_smoother )
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// run iSAM for every factor
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GaussianISAM actual;
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BOOST_FOREACH(boost::shared_ptr<GaussianFactor> factor, smoother) {
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for(boost::shared_ptr<GaussianFactor> factor: smoother) {
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GaussianFactorGraph factorGraph;
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factorGraph.push_back(factor);
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actual.update(factorGraph);
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@ -56,7 +55,7 @@ TEST( ISAM, iSAM_smoother )
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GaussianBayesTree expected = *smoother.eliminateMultifrontal(ordering);
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// Verify sigmas in the bayes tree
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BOOST_FOREACH(const GaussianBayesTree::sharedClique& clique, expected.nodes() | br::map_values) {
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for(const GaussianBayesTree::sharedClique& clique: expected.nodes() | br::map_values) {
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GaussianConditional::shared_ptr conditional = clique->conditional();
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EXPECT(!conditional->get_model());
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}
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@ -23,7 +23,6 @@
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#include <gtsam/base/debug.h>
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#include <gtsam/base/TestableAssertions.h>
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#include <gtsam/base/treeTraversal-inst.h>
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#include <boost/foreach.hpp>
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#include <boost/assign/list_of.hpp>
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#include <gtsam/base/deprecated/LieScalar.h>
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using namespace boost::assign;
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@ -212,7 +211,7 @@ struct ConsistencyVisitor
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if(find(node->parent()->children.begin(), node->parent()->children.end(), node) == node->parent()->children.end())
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consistent = false;
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}
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BOOST_FOREACH(Key j, node->conditional()->frontals())
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for(Key j: node->conditional()->frontals())
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{
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if(isam.nodes().at(j).get() != node.get())
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consistent = false;
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@ -251,7 +250,7 @@ bool isam_check(const NonlinearFactorGraph& fullgraph, const Values& fullinit, c
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// Check gradient at each node
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bool nodeGradientsOk = true;
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typedef ISAM2::sharedClique sharedClique;
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BOOST_FOREACH(const sharedClique& clique, isam.nodes() | br::map_values) {
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for(const sharedClique& clique: isam.nodes() | br::map_values) {
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// Compute expected gradient
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GaussianFactorGraph jfg;
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jfg += clique->conditional();
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@ -483,7 +482,7 @@ TEST(ISAM2, swapFactors)
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// Check gradient at each node
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typedef ISAM2::sharedClique sharedClique;
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BOOST_FOREACH(const sharedClique& clique, isam.nodes() | br::map_values) {
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for(const sharedClique& clique: isam.nodes() | br::map_values) {
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// Compute expected gradient
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GaussianFactorGraph jfg;
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jfg += clique->conditional();
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@ -608,7 +607,7 @@ TEST(ISAM2, constrained_ordering)
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// Check gradient at each node
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typedef ISAM2::sharedClique sharedClique;
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BOOST_FOREACH(const sharedClique& clique, isam.nodes() | br::map_values) {
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for(const sharedClique& clique: isam.nodes() | br::map_values) {
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// Compute expected gradient
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GaussianFactorGraph jfg;
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jfg += clique->conditional();
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@ -650,7 +649,7 @@ namespace {
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bool checkMarginalizeLeaves(ISAM2& isam, const FastList<Key>& leafKeys) {
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Matrix expectedAugmentedHessian, expected3AugmentedHessian;
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vector<Key> toKeep;
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BOOST_FOREACH(Key j, isam.getDelta() | br::map_keys)
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for(Key j: isam.getDelta() | br::map_keys)
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if(find(leafKeys.begin(), leafKeys.end(), j) == leafKeys.end())
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toKeep.push_back(j);
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@ -29,7 +29,6 @@
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#include <CppUnitLite/Test.h>
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#include <CppUnitLite/TestRegistry.h>
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#include <CppUnitLite/TestResult.h>
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#include <boost/foreach.hpp>
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#include <stddef.h>
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#include <stdexcept>
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#include <string>
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@ -51,7 +50,7 @@ TEST(PinholeCamera, BAL) {
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NonlinearFactorGraph graph;
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for (size_t j = 0; j < db.number_tracks(); j++) {
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BOOST_FOREACH (const SfM_Measurement& m, db.tracks[j].measurements)
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for (const SfM_Measurement& m: db.tracks[j].measurements)
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graph.push_back(sfmFactor(m.second, unit2, m.first, P(j)));
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}
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@ -57,7 +57,7 @@ TEST( SubgraphPreconditioner, planarOrdering ) {
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/** unnormalized error */
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static double error(const GaussianFactorGraph& fg, const VectorValues& x) {
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double total_error = 0.;
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BOOST_FOREACH(const GaussianFactor::shared_ptr& factor, fg)
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for(const GaussianFactor::shared_ptr& factor: fg)
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total_error += factor->error(x);
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return total_error;
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}
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@ -28,7 +28,6 @@
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#include <gtsam/inference/Ordering.h>
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#include <gtsam/base/numericalDerivative.h>
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#include <boost/foreach.hpp>
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#include <boost/tuple/tuple.hpp>
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#include <boost/assign/std/list.hpp>
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using namespace boost::assign;
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@ -41,7 +40,7 @@ using namespace example;
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/** unnormalized error */
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static double error(const GaussianFactorGraph& fg, const VectorValues& x) {
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double total_error = 0.;
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BOOST_FOREACH(const GaussianFactor::shared_ptr& factor, fg)
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for(const GaussianFactor::shared_ptr& factor: fg)
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total_error += factor->error(x);
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return total_error;
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}
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