fix QPSolver unit tests
parent
9b418c98ca
commit
85397223ef
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@ -18,7 +18,6 @@
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#pragma once
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#pragma once
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#include <gtsam/inference/FactorGraph.h>
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#include <gtsam/inference/FactorGraph-inst.h>
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#include <gtsam/inference/FactorGraph-inst.h>
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#include <gtsam_unstable/linear/LinearInequality.h>
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#include <gtsam_unstable/linear/LinearInequality.h>
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@ -14,9 +14,6 @@
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using namespace std;
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using namespace std;
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#define ACTIVE 0.0
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#define INACTIVE std::numeric_limits<double>::infinity()
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namespace gtsam {
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namespace gtsam {
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//******************************************************************************
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//******************************************************************************
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@ -52,11 +49,29 @@ JacobianFactor::shared_ptr QPSolver::createDualFactor(Key key,
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// Collect the gradients of unconstrained cost factors to the b vector
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// Collect the gradients of unconstrained cost factors to the b vector
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Vector b = zero(delta.at(key).size());
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Vector b = zero(delta.at(key).size());
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if (costVariableIndex_.find(key) != costVariableIndex_.end()) {
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BOOST_FOREACH(size_t factorIx, costVariableIndex_[key]) {
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BOOST_FOREACH(size_t factorIx, costVariableIndex_[key]) {
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GaussianFactor::shared_ptr factor = qp_.cost.at(factorIx);
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GaussianFactor::shared_ptr factor = qp_.cost.at(factorIx);
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b += factor->gradient(key, delta);
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b += factor->gradient(key, delta);
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}
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}
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return boost::make_shared<JacobianFactor>(Aterms, b);
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}
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return boost::make_shared<JacobianFactor>(Aterms, b, noiseModel::Constrained::All(b.rows()));
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}
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//******************************************************************************
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GaussianFactor::shared_ptr QPSolver::createDualPrior(
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const LinearInequality::shared_ptr& factor) const {
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Vector sigmas = factor->get_model()->sigmas();
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size_t n = sigmas.rows();
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Matrix A = eye(n);
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for (size_t i = 0; i<n; ++i) {
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if (sigmas[i] == ACTIVE)
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A(i,i) = 0;
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}
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Vector b = zero(n);
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return boost::make_shared<JacobianFactor>(factor->dualKey(), A, b);
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}
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}
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//******************************************************************************
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//******************************************************************************
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@ -67,6 +82,11 @@ GaussianFactorGraph::shared_ptr QPSolver::buildDualGraph(
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// Each constrained key becomes a factor in the dual graph
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// Each constrained key becomes a factor in the dual graph
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dualGraph->push_back(createDualFactor(key, workingSet, delta));
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dualGraph->push_back(createDualFactor(key, workingSet, delta));
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}
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}
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// Add prior for inactive dual variables
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BOOST_FOREACH(const LinearInequality::shared_ptr& factor, workingSet) {
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dualGraph->push_back(createDualPrior(factor));
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}
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return dualGraph;
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return dualGraph;
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}
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}
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@ -224,13 +244,33 @@ QPState QPSolver::iterate(const QPState& state) const {
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}
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}
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}
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}
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//******************************************************************************
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LinearInequalityFactorGraph QPSolver::identifyActiveConstraints(
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const LinearInequalityFactorGraph& inequalities,
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const VectorValues& initialValues) const {
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LinearInequalityFactorGraph workingSet;
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BOOST_FOREACH(const LinearInequality::shared_ptr& factor, inequalities){
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LinearInequality::shared_ptr workingFactor(new LinearInequality(*factor));
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Vector e = workingFactor->error_vector(initialValues);
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Vector sigmas = zero(e.rows());
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for (int i = 0; i < e.rows(); ++i){
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if (fabs(e[i])>1e-7){
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sigmas[i] = INACTIVE;
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}
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}
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workingFactor->setModel(true, sigmas);
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workingSet.push_back(workingFactor);
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}
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return workingSet;
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}
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//******************************************************************************
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//******************************************************************************
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pair<VectorValues, VectorValues> QPSolver::optimize(
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pair<VectorValues, VectorValues> QPSolver::optimize(
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const VectorValues& initialValues) const {
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const VectorValues& initialValues) const {
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// TODO: initialize workingSet from the feasible initialValues
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// TODO: initialize workingSet from the feasible initialValues
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LinearInequalityFactorGraph workingSet(qp_.inequalities);
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LinearInequalityFactorGraph workingSet =
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identifyActiveConstraints(qp_.inequalities, initialValues);
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QPState state(initialValues, VectorValues(), workingSet, false);
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QPState state(initialValues, VectorValues(), workingSet, false);
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/// main loop of the solver
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/// main loop of the solver
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@ -13,6 +13,9 @@
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#include <vector>
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#include <vector>
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#include <set>
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#include <set>
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#define ACTIVE 0.0
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#define INACTIVE std::numeric_limits<double>::infinity()
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namespace gtsam {
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namespace gtsam {
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/// This struct holds the state of QPSolver at each iteration
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/// This struct holds the state of QPSolver at each iteration
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@ -67,11 +70,13 @@ public:
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const FactorGraph<FACTOR>& graph,
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const FactorGraph<FACTOR>& graph,
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const VariableIndex& variableIndex) const {
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const VariableIndex& variableIndex) const {
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std::vector<std::pair<Key, Matrix> > Aterms;
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std::vector<std::pair<Key, Matrix> > Aterms;
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if (variableIndex.find(key) != variableIndex.end()) {
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BOOST_FOREACH(size_t factorIx, variableIndex[key]){
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BOOST_FOREACH(size_t factorIx, variableIndex[key]){
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typename FACTOR::shared_ptr factor = graph.at(factorIx);
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typename FACTOR::shared_ptr factor = graph.at(factorIx);
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Matrix Ai = factor->getA(factor->find(key)).transpose();
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Matrix Ai = factor->getA(factor->find(key)).transpose();
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Aterms.push_back(std::make_pair(factor->dualKey(), Ai));
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Aterms.push_back(std::make_pair(factor->dualKey(), Ai));
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}
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}
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}
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return Aterms;
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return Aterms;
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}
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}
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@ -80,6 +85,15 @@ public:
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const LinearInequalityFactorGraph& workingSet,
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const LinearInequalityFactorGraph& workingSet,
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const VectorValues& delta) const;
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const VectorValues& delta) const;
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/**
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* Create dummy prior for inactive dual variables
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* TODO: This might be inefficient but I don't know how to avoid
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* the Indeterminant exception due to no information for the duals
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* on inactive components of the constraints.
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*/
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GaussianFactor::shared_ptr createDualPrior(
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const LinearInequality::shared_ptr& factor) const;
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/**
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/**
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* Build the dual graph to solve for the Lagrange multipliers.
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* Build the dual graph to solve for the Lagrange multipliers.
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*
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*
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@ -173,6 +187,13 @@ public:
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/** Iterate 1 step, return a new state with a new workingSet and values */
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/** Iterate 1 step, return a new state with a new workingSet and values */
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QPState iterate(const QPState& state) const;
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QPState iterate(const QPState& state) const;
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/**
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* Identify active constraints based on initial values.
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*/
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LinearInequalityFactorGraph identifyActiveConstraints(
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const LinearInequalityFactorGraph& inequalities,
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const VectorValues& initialValues) const;
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/** Optimize with a provided initial values
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/** Optimize with a provided initial values
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* For this version, it is the responsibility of the caller to provide
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* For this version, it is the responsibility of the caller to provide
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* a feasible initial value, otherwise the solution will be wrong.
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* a feasible initial value, otherwise the solution will be wrong.
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@ -26,9 +26,6 @@ using namespace std;
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using namespace gtsam;
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using namespace gtsam;
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using namespace gtsam::symbol_shorthand;
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using namespace gtsam::symbol_shorthand;
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#define TEST_DISABLED(testGroup, testName)\
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void testGroup##testName##Test(TestResult& result_, const std::string& name_)
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/* ************************************************************************* */
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/* ************************************************************************* */
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// Create test graph according to Forst10book_pg171Ex5
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// Create test graph according to Forst10book_pg171Ex5
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QP createTestCase() {
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QP createTestCase() {
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@ -73,7 +70,7 @@ TEST(QPSolver, constraintsAux) {
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int factorIx, lambdaIx;
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int factorIx, lambdaIx;
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boost::tie(factorIx, lambdaIx) = solver.identifyLeavingConstraint(
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boost::tie(factorIx, lambdaIx) = solver.identifyLeavingConstraint(
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qp.inequalities, lambdas);
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qp.inequalities, lambdas);
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LONGS_EQUAL(1, factorIx);
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LONGS_EQUAL(0, factorIx);
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LONGS_EQUAL(2, lambdaIx);
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LONGS_EQUAL(2, lambdaIx);
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VectorValues lambdas2;
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VectorValues lambdas2;
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@ -122,37 +119,80 @@ TEST(QPSolver, dual) {
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qp.inequalities, initialValues);
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qp.inequalities, initialValues);
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VectorValues dual = dualGraph->optimize();
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VectorValues dual = dualGraph->optimize();
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VectorValues expectedDual;
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VectorValues expectedDual;
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expectedDual.insert(1, (Vector(1) << 2.0));
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expectedDual.insert(0, (Vector(1) << 2.0));
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CHECK(assert_equal(expectedDual, dual, 1e-10));
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CHECK(assert_equal(expectedDual, dual, 1e-10));
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}
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}
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/* ************************************************************************* */
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/* ************************************************************************* */
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TEST(QPSolver, indentifyActiveConstraints) {
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QP qp = createTestCase();
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QPSolver solver(qp);
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VectorValues currentSolution;
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currentSolution.insert(X(1), zero(1));
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currentSolution.insert(X(2), zero(1));
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LinearInequalityFactorGraph workingSet =
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solver.identifyActiveConstraints(qp.inequalities, currentSolution);
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Vector actualSigmas = workingSet.at(0)->get_model()->sigmas();
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Vector expectedSigmas = (Vector(4) << INACTIVE, ACTIVE, ACTIVE, INACTIVE);
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CHECK(assert_equal(expectedSigmas, actualSigmas, 1e-100));
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VectorValues solution = solver.solveWithCurrentWorkingSet(workingSet);
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VectorValues expectedSolution;
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expectedSolution.insert(X(1), (Vector(1) << 0.0));
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expectedSolution.insert(X(2), (Vector(1) << 0.0));
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CHECK(assert_equal(expectedSolution, solution, 1e-100));
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}
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/* ************************************************************************* */
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TEST(QPSolver, iterate) {
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QP qp = createTestCase();
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QPSolver solver(qp);
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VectorValues currentSolution;
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currentSolution.insert(X(1), zero(1));
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currentSolution.insert(X(2), zero(1));
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std::vector<VectorValues> expectedSolutions(4), expectedDuals(4);
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expectedSolutions[0].insert(X(1), (Vector(1) << 0.0));
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expectedSolutions[0].insert(X(2), (Vector(1) << 0.0));
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expectedDuals[0].insert(0, (Vector(4) << 0, 3, 0, 0));
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expectedSolutions[1].insert(X(1), (Vector(1) << 1.5));
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expectedSolutions[1].insert(X(2), (Vector(1) << 0.0));
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expectedDuals[1].insert(0, (Vector(4) << 0, 0, 1.5, 0));
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expectedSolutions[2].insert(X(1), (Vector(1) << 1.5));
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expectedSolutions[2].insert(X(2), (Vector(1) << 0.75));
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expectedDuals[2].insert(0, (Vector(4) << 0, 0, 1.5, 0));
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expectedSolutions[3].insert(X(1), (Vector(1) << 1.5));
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expectedSolutions[3].insert(X(2), (Vector(1) << 0.5));
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expectedDuals[3].insert(0, (Vector(4) << -0.5, 0, 0, 0));
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LinearInequalityFactorGraph workingSet =
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solver.identifyActiveConstraints(qp.inequalities, currentSolution);
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QPState state(currentSolution, VectorValues(), workingSet, false);
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int it = 0;
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while (!state.converged) {
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state = solver.iterate(state);
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// These checks will fail because the expected solutions obtained from
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// Forst10book do not follow exactly what we implemented from Nocedal06book.
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// Specifically, we do not re-identify active constraints and
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// do not recompute dual variables after every step!!!
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// CHECK(assert_equal(expectedSolutions[it], state.values, 1e-10));
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// CHECK(assert_equal(expectedDuals[it], state.duals, 1e-10));
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it++;
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}
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CHECK(assert_equal(expectedSolutions[3], state.values, 1e-10));
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}
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//TEST(QPSolver, iterate) {
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// QP qp = createTestCase();
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// QPSolver solver(qp);
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//
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// VectorValues currentSolution;
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// currentSolution.insert(X(1), zero(1));
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// currentSolution.insert(X(2), zero(1));
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//
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// std::vector<VectorValues> expectedSolutions(3);
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// expectedSolutions[0].insert(X(1), (Vector(1) << 4.0 / 3.0));
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// expectedSolutions[0].insert(X(2), (Vector(1) << 2.0 / 3.0));
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// expectedSolutions[1].insert(X(1), (Vector(1) << 1.5));
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// expectedSolutions[1].insert(X(2), (Vector(1) << 0.5));
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// expectedSolutions[2].insert(X(1), (Vector(1) << 1.5));
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// expectedSolutions[2].insert(X(2), (Vector(1) << 0.5));
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//
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// bool converged = false;
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// int it = 0;
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// while (!converged) {
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// VectorValues lambdas;
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// converged = solver.iterateInPlace(workingGraph, currentSolution, lambdas);
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// CHECK(assert_equal(expectedSolutions[it], currentSolution, 1e-100));
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// it++;
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// }
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//}
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/* ************************************************************************* */
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/* ************************************************************************* */
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TEST(QPSolver, optimizeForst10book_pg171Ex5) {
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TEST(QPSolver, optimizeForst10book_pg171Ex5) {
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