/** * @file testNonlinearConstraint.cpp * @brief Tests for nonlinear constraints handled via SQP * @author Alex Cunningham */ #include #include #include #include // for operator += #define GTSAM_MAGIC_KEY #include #include #include #include using namespace std; using namespace gtsam; using namespace boost::assign; typedef TypedSymbol Key; typedef TupleConfig2< LieConfig, LieConfig > VecConfig; typedef NonlinearConstraint1 NLC1; typedef NonlinearConstraint2 NLC2; /* ************************************************************************* */ // unary functions with scalar variables /* ************************************************************************* */ namespace test1 { /** p = 1, g(x) = x^2-5 = 0 */ Vector g(const VecConfig& config, const list& keys) { double x = config[keys.front()](0); return Vector_(1, x * x - 5); } /** p = 1, jacobianG(x) = 2x */ Matrix G(const VecConfig& config, const list& keys) { double x = config[keys.front()](0); return Matrix_(1, 1, 2 * x); } } // \namespace test1 /* ************************************************************************* */ TEST( NonlinearConstraint1, unary_scalar_construction ) { // construct a constraint on x // the lagrange multipliers will be expected on L_x1 // and there is only one multiplier size_t p = 1; Key x1(1); list keys; keys += x1; LagrangeKey L1(1); NLC1 c1(boost::bind(test1::g, _1, keys), x1, boost::bind(test1::G, _1, keys), p, L1); // get a configuration to use for finding the error VecConfig config; config.insert(x1, Vector_(1, 1.0)); // calculate the error Vector actualVec = c1.unwhitenedError(config); Vector expectedVec = Vector_(1, -4.0); CHECK(assert_equal(actualVec, expectedVec, 1e-5)); double actError = c1.error(config); double expError = 8.0; DOUBLES_EQUAL(expError, actError, 1e-5); } /* ************************************************************************* */ TEST( NonlinearConstraint1, unary_scalar_linearize ) { size_t p = 1; Key x1(1); list keys; keys += x1; LagrangeKey L1(1); NLC1 c1(boost::bind(test1::g, _1, keys), x1, boost::bind(test1::G, _1, keys), p, L1); // get a configuration to use for linearization (with lagrange multipliers) VecConfig realconfig; realconfig.insert(x1, Vector_(1, 1.0)); realconfig.insert(L1, Vector_(1, 3.0)); // linearize the system GaussianFactor::shared_ptr linfactor = c1.linearize(realconfig); // verify - probabilistic component goes on top Vector sigmas = Vector_(2, 1.0, 0.0); SharedDiagonal mixedModel = noiseModel::Constrained::MixedSigmas(sigmas); // stack the matrices to combine Matrix Ax1 = Matrix_(2,1, 6.0, 2.0), AL1 = Matrix_(2,1, 1.0, 0.0); Vector rhs = Vector_(2, 0.0, 4.0); GaussianFactor expectedFactor(x1, Ax1, L1, AL1, rhs, mixedModel); CHECK(assert_equal(*linfactor, expectedFactor)); } /* ************************************************************************* */ TEST( NonlinearConstraint1, unary_scalar_equal ) { Key x(0), y(1); list keys1, keys2; keys1 += x; keys2 += y; LagrangeKey L1(1); NLC1 c1(boost::bind(test1::g, _1, keys1), x, boost::bind(test1::G, _1, keys1), 1, L1, true), c2(boost::bind(test1::g, _1, keys1), x, boost::bind(test1::G, _1, keys1), 1, L1), c3(boost::bind(test1::g, _1, keys1), x, boost::bind(test1::G, _1, keys1), 2, L1), c4(boost::bind(test1::g, _1, keys2), y, boost::bind(test1::G, _1, keys2), 1, L1); CHECK(assert_equal(c1, c2)); CHECK(assert_equal(c2, c1)); CHECK(!c1.equals(c3)); CHECK(!c1.equals(c4)); } /* ************************************************************************* */ // binary functions with scalar variables /* ************************************************************************* */ namespace test2 { /** p = 1, g(x) = x^2-5 -y = 0 */ Vector g(const VecConfig& config, const list& keys) { double x = config[keys.front()](0); double y = config[keys.back()](0); return Vector_(1, x * x - 5.0 - y); } /** jacobian for x, jacobianG(x,y) in x: 2x*/ Matrix G1(const VecConfig& config, const list& keys) { double x = config[keys.front()](0); return Matrix_(1, 1, 2.0 * x); } /** jacobian for y, jacobianG(x,y) in y: -1 */ Matrix G2(const VecConfig& config, const list& keys) { return Matrix_(1, 1, -1.0); } } // \namespace test2 /* ************************************************************************* */ TEST( NonlinearConstraint2, binary_scalar_construction ) { // construct a constraint on x and y // the lagrange multipliers will be expected on L_xy // and there is only one multiplier size_t p = 1; Key x0(0), x1(1); list keys; keys += x0, x1; LagrangeKey L1(1); NLC2 c1( boost::bind(test2::g, _1, keys), x0, boost::bind(test2::G1, _1, keys), x1, boost::bind(test2::G1, _1, keys), p, L1); // get a configuration to use for finding the error VecConfig config; config.insert(x0, Vector_(1, 1.0)); config.insert(x1, Vector_(1, 2.0)); // calculate the error Vector actual = c1.unwhitenedError(config); Vector expected = Vector_(1.0, -6.0); CHECK(assert_equal(actual, expected, 1e-5)); } /* ************************************************************************* */ TEST( NonlinearConstraint2, binary_scalar_linearize ) { // create a constraint size_t p = 1; Key x0(0), x1(1); list keys; keys += x0, x1; LagrangeKey L1(1); NLC2 c1( boost::bind(test2::g, _1, keys), x0, boost::bind(test2::G1, _1, keys), x1, boost::bind(test2::G2, _1, keys), p, L1); // get a configuration to use for finding the error VecConfig realconfig; realconfig.insert(x0, Vector_(1, 1.0)); realconfig.insert(x1, Vector_(1, 2.0)); realconfig.insert(L1, Vector_(1, 3.0)); // linearize the system GaussianFactor::shared_ptr actualFactor = c1.linearize(realconfig); // verify - probabilistic component goes on top Matrix Ax0 = Matrix_(2,1, 6.0, 2.0), Ax1 = Matrix_(2,1,-3.0,-1.0), AL = Matrix_(2,1, 1.0, 0.0); Vector rhs = Vector_(2, 0.0, 6.0), sigmas = Vector_(2, 1.0, 0.0); SharedDiagonal expModel = noiseModel::Constrained::MixedSigmas(sigmas); GaussianFactor expFactor(x0,Ax0, x1, Ax1,L1, AL, rhs, expModel); CHECK(assert_equal(expFactor, *actualFactor)); } /* ************************************************************************* */ TEST( NonlinearConstraint2, binary_scalar_equal ) { list keys1, keys2, keys3; Key x0(0), x1(1), x2(2); keys1 += x0, x1; keys2 += x1, x0; keys3 += x0; LagrangeKey L1(1); NLC2 c1(boost::bind(test2::g, _1, keys1), x0, boost::bind(test2::G1, _1, keys1), x1, boost::bind(test2::G2, _1, keys1), 1, L1), c2(boost::bind(test2::g, _1, keys1), x0, boost::bind(test2::G1, _1, keys1), x1, boost::bind(test2::G2, _1, keys1), 1, L1), c3(boost::bind(test2::g, _1, keys2), x1, boost::bind(test2::G1, _1, keys2), x0, boost::bind(test2::G2, _1, keys2), 1, L1), c4(boost::bind(test2::g, _1, keys3), x0, boost::bind(test2::G1, _1, keys3), x2, boost::bind(test2::G2, _1, keys3), 3, L1); CHECK(assert_equal(c1, c2)); CHECK(assert_equal(c2, c1)); CHECK(!c1.equals(c3)); CHECK(!c1.equals(c4)); } /* ************************************************************************* */ // Inequality tests /* ************************************************************************* */ namespace inequality1 { /** p = 1, g(x) x^2 - 5 > 0 */ Vector g(const VecConfig& config, const Key& key) { double x = config[key](0); double g = x * x - 5; return Vector_(1, g); // return the actual cost } /** p = 1, jacobianG(x) = 2*x */ Matrix G(const VecConfig& config, const Key& key) { double x = config[key](0); return Matrix_(1, 1, 2 * x); } } // \namespace inequality1 /* ************************************************************************* */ TEST( NonlinearConstraint1, unary_inequality ) { size_t p = 1; Key x0(0); LagrangeKey L1(1); NLC1 c1(boost::bind(inequality1::g, _1, x0), x0, boost::bind(inequality1::G, _1, x0), p, L1, false); // inequality constraint // get configurations to use for evaluation VecConfig config1, config2; config1.insert(x0, Vector_(1, 10.0)); // should be inactive config2.insert(x0, Vector_(1, 1.0)); // should have nonzero error // check error CHECK(!c1.active(config1)); Vector actualError2 = c1.unwhitenedError(config2); CHECK(assert_equal(actualError2, Vector_(1, -4.0, 1e-9))); CHECK(c1.active(config2)); } /* ************************************************************************* */ TEST( NonlinearConstraint1, unary_inequality_linearize ) { size_t p = 1; Key x0(0); LagrangeKey L1(1); NLC1 c1(boost::bind(inequality1::g, _1, x0), x0, boost::bind(inequality1::G, _1, x0), p, L1, false); // inequality constraint // get configurations to use for linearization VecConfig config1, config2; config1.insert(x0, Vector_(1, 10.0)); // should have zero error config2.insert(x0, Vector_(1, 1.0)); // should have nonzero error config1.insert(L1, Vector_(1, 3.0)); config2.insert(L1, Vector_(1, 3.0)); // linearize for inactive constraint GaussianFactor::shared_ptr actualFactor1 = c1.linearize(config1); // check if the factor is active CHECK(!c1.active(config1)); // linearize for active constraint GaussianFactor::shared_ptr actualFactor2 = c1.linearize(config2); CHECK(c1.active(config2)); // verify Vector sigmas = Vector_(2, 1.0, 0.0); SharedDiagonal model = noiseModel::Constrained::MixedSigmas(sigmas); GaussianFactor expectedFactor(x0, Matrix_(2,1, 6.0, 2.0), L1, Matrix_(2,1, 1.0, 0.0), Vector_(2, 0.0, 4.0), model); CHECK(assert_equal(*actualFactor2, expectedFactor)); } /* ************************************************************************* */ // Binding arbitrary functions /* ************************************************************************* */ namespace binding1 { /** p = 1, g(x) x^2 - r > 0 */ Vector g(double r, const VecConfig& config, const Key& key) { double x = config[key](0); double g = x * x - r; return Vector_(1, g); // return the actual cost } /** p = 1, jacobianG(x) = 2*x */ Matrix G(double coeff, const VecConfig& config, const Key& key) { double x = config[key](0); return Matrix_(1, 1, coeff * x); } } // \namespace binding1 /* ************************************************************************* */ TEST( NonlinearConstraint1, unary_binding ) { size_t p = 1; double coeff = 2; double radius = 5; Key x0(0); LagrangeKey L1(1); NLC1 c1(boost::bind(binding1::g, radius, _1, x0), x0, boost::bind(binding1::G, coeff, _1, x0), p, L1, false); // inequality constraint // get configurations to use for evaluation VecConfig config1, config2; config1.insert(x0, Vector_(1, 10.0)); // should have zero error config2.insert(x0, Vector_(1, 1.0)); // should have nonzero error // check error CHECK(!c1.active(config1)); Vector actualError2 = c1.unwhitenedError(config2); CHECK(assert_equal(actualError2, Vector_(1, -4.0, 1e-9))); CHECK(c1.active(config2)); } /* ************************************************************************* */ namespace binding2 { /** p = 1, g(x) = x^2-5 -y = 0 */ Vector g(double r, const VecConfig& config, const Key& k1, const Key& k2) { double x = config[k1](0); double y = config[k2](0); return Vector_(1, x * x - r - y); } /** jacobian for x, jacobianG(x,y) in x: 2x*/ Matrix G1(double c, const VecConfig& config, const Key& key) { double x = config[key](0); return Matrix_(1, 1, c * x); } /** jacobian for y, jacobianG(x,y) in y: -1 */ Matrix G2(double c, const VecConfig& config) { return Matrix_(1, 1, -1.0 * c); } } // \namespace binding2 /* ************************************************************************* */ TEST( NonlinearConstraint2, binary_binding ) { // construct a constraint on x and y // the lagrange multipliers will be expected on L_xy // and there is only one multiplier size_t p = 1; double a = 2.0; double b = 1.0; double r = 5.0; Key x0(0), x1(1); LagrangeKey L1(1); NLC2 c1(boost::bind(binding2::g, r, _1, x0, x1), x0, boost::bind(binding2::G1, a, _1, x0), x1, boost::bind(binding2::G2, b, _1), p, L1); // get a configuration to use for finding the error VecConfig config; config.insert(x0, Vector_(1, 1.0)); config.insert(x1, Vector_(1, 2.0)); // calculate the error Vector actual = c1.unwhitenedError(config); Vector expected = Vector_(1.0, -6.0); CHECK(assert_equal(actual, expected, 1e-5)); } /* ************************************************************************* */ int main() { TestResult tr; return TestRegistry::runAllTests(tr); } /* ************************************************************************* */