[REFACTOR] Changed Vector(..).finished for VectorN(...)
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@ -9,7 +9,6 @@
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#include <gtsam_unstable/linear/LPState.h>
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#include <gtsam_unstable/linear/LP.h>
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namespace gtsam {
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typedef std::map<Key, size_t> KeyDimMap;
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typedef std::vector<std::pair<Key, Matrix> > TermsContainer;
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@ -47,17 +47,17 @@ using namespace gtsam::symbol_shorthand;
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*/
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LP simpleLP1() {
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LP lp;
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lp.cost = LinearCost(1, (Vector(2) << -1., -1.).finished()); // min -x1-x2 (max x1+x2)
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lp.cost = LinearCost(1, Vector2( -1., -1.)); // min -x1-x2 (max x1+x2)
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lp.inequalities.push_back(
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LinearInequality(1, (Vector(2) << -1, 0).finished(), 0, 1)); // x1 >= 0
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LinearInequality(1, Vector2( -1, 0), 0, 1)); // x1 >= 0
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lp.inequalities.push_back(
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LinearInequality(1, (Vector(2) << 0, -1).finished(), 0, 2)); // x2 >= 0
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LinearInequality(1, Vector2( 0, -1), 0, 2)); // x2 >= 0
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lp.inequalities.push_back(
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LinearInequality(1, (Vector(2) << 1, 2).finished(), 4, 3)); // x1 + 2*x2 <= 4
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LinearInequality(1, Vector2( 1, 2), 4, 3)); // x1 + 2*x2 <= 4
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lp.inequalities.push_back(
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LinearInequality(1, (Vector(2) << 4, 2).finished(), 12, 4)); // 4x1 + 2x2 <= 12
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LinearInequality(1, Vector2( 4, 2), 12, 4)); // 4x1 + 2x2 <= 12
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lp.inequalities.push_back(
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LinearInequality(1, (Vector(2) << -1, 1).finished(), 1, 5)); // -x1 + x2 <= 1
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LinearInequality(1, Vector2( -1, 1), 1, 5)); // -x1 + x2 <= 1
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return lp;
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}
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@ -83,15 +83,15 @@ TEST(LPInitSolverMatlab, initialization) {
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LP expectedInitLP;
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expectedInitLP.cost = LinearCost(yKey, ones(1));
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expectedInitLP.inequalities.push_back(
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LinearInequality(1, (Vector(2) << -1, 0).finished(), 2, Vector::Constant(1, -1), 0, 1)); // -x1 - y <= 0
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LinearInequality(1, Vector2( -1, 0), 2, Vector::Constant(1, -1), 0, 1)); // -x1 - y <= 0
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expectedInitLP.inequalities.push_back(
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LinearInequality(1, (Vector(2) << 0, -1).finished(), 2, Vector::Constant(1, -1), 0, 2)); // -x2 - y <= 0
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LinearInequality(1, Vector2( 0, -1), 2, Vector::Constant(1, -1), 0, 2)); // -x2 - y <= 0
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expectedInitLP.inequalities.push_back(
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LinearInequality(1, (Vector(2) << 1, 2).finished(), 2, Vector::Constant(1, -1), 4, 3)); // x1 + 2*x2 - y <= 4
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LinearInequality(1, Vector2( 1, 2), 2, Vector::Constant(1, -1), 4, 3)); // x1 + 2*x2 - y <= 4
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expectedInitLP.inequalities.push_back(
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LinearInequality(1, (Vector(2) << 4, 2).finished(), 2, Vector::Constant(1, -1), 12, 4)); // 4x1 + 2x2 - y <= 12
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LinearInequality(1, Vector2( 4, 2), 2, Vector::Constant(1, -1), 12, 4)); // 4x1 + 2x2 - y <= 12
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expectedInitLP.inequalities.push_back(
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LinearInequality(1, (Vector(2) << -1, 1).finished(), 2, Vector::Constant(1, -1), 1, 5)); // -x1 + x2 - y <= 1
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LinearInequality(1, Vector2( -1, 1), 2, Vector::Constant(1, -1), 1, 5)); // -x1 + x2 - y <= 1
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CHECK(assert_equal(expectedInitLP, *initLP, 1e-10));
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LPSolver lpSolveInit(*initLP);
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@ -99,7 +99,7 @@ TEST(LPInitSolverMatlab, initialization) {
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xy0.insert(yKey, Vector::Constant(1, y0));
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VectorValues xyInit = lpSolveInit.optimize(xy0).first;
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VectorValues expected_init;
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expected_init.insert(1, (Vector(2) << 1, 1).finished());
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expected_init.insert(1, Vector2( 1, 1));
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expected_init.insert(2, Vector::Constant(1, -1));
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CHECK(assert_equal(expected_init, xyInit, 1e-10));
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@ -117,9 +117,9 @@ TEST(LPInitSolverMatlab, initialization) {
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*/
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TEST(LPSolver, overConstrainedLinearSystem) {
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GaussianFactorGraph graph;
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Matrix A1 = (Matrix(3,1) <<1,1,1).finished();
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Matrix A2 = (Matrix(3,1) <<1,-1,2).finished();
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Vector b = (Vector(3) << 1, 5, 6).finished();
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Matrix A1 = Vector3(1,1,1);
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Matrix A2 = Vector3(1,-1,2);
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Vector b = Vector3( 1, 5, 6);
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JacobianFactor factor(1, A1, 2, A2, b, noiseModel::Constrained::All(3));
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graph.push_back(factor);
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@ -149,13 +149,13 @@ TEST(LPSolver, simpleTest1) {
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VectorValues x1 = lpSolver.solveWithCurrentWorkingSet(init,
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InequalityFactorGraph());
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VectorValues expected_x1;
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expected_x1.insert(1, (Vector(2) << 1, 1).finished());
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expected_x1.insert(1, Vector2( 1, 1));
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CHECK(assert_equal(expected_x1, x1, 1e-10));
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VectorValues result, duals;
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boost::tie(result, duals) = lpSolver.optimize(init);
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VectorValues expectedResult;
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expectedResult.insert(1, (Vector(2)<<8./3., 2./3.).finished());
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expectedResult.insert(1, Vector2(8./3., 2./3.));
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CHECK(assert_equal(expectedResult, result, 1e-10));
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}
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@ -167,9 +167,9 @@ TEST(LPSolver, simpleTest1) {
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*/
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/* ************************************************************************* */
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TEST(LPSolver, LinearCost) {
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LinearCost cost(1, (Vector(3) << 2., 4., 6.).finished());
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LinearCost cost(1, Vector3( 2., 4., 6.));
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VectorValues x;
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x.insert(1, (Vector(3) << 1., 3., 5.).finished());
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x.insert(1, Vector3( 1., 3., 5.));
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double error = cost.error(x);
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double expectedError = 44.0;
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DOUBLES_EQUAL(expectedError, error, 1e-100);
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