void CompositeOFTest::get_hessians( MsqHessian& LP1_hess, MsqHessian& LP2_hess, ObjectiveFunction& OF, MsqHessian& OF_hess ) { MsqPrintError err(cout); PatchData pd; create_twelve_hex_patch( pd, err ); ASSERT_NO_ERROR( err ); LP1_hess.initialize( pd, err ); ASSERT_NO_ERROR(err); LP2_hess.initialize( pd, err ); ASSERT_NO_ERROR(err); OF_hess .initialize( pd, err ); ASSERT_NO_ERROR(err); std::vector<Vector3D> grad; bool rval; double value; rval = LP1.evaluate_with_Hessian( ObjectiveFunction::CALCULATE, pd, value, grad, LP1_hess, err ); ASSERT_NO_ERROR(err); CPPUNIT_ASSERT(rval); rval = LP2.evaluate_with_Hessian( ObjectiveFunction::CALCULATE, pd, value, grad, LP2_hess, err ); ASSERT_NO_ERROR(err); CPPUNIT_ASSERT(rval); rval = OF .evaluate_with_Hessian( ObjectiveFunction::CALCULATE, pd, value, grad, OF_hess , err ); ASSERT_NO_ERROR(err); CPPUNIT_ASSERT(rval); }
/** Internal helper function for test_eval_type */ double ObjectiveFunctionTests::evaluate_internal( ObjectiveFunction::EvalType type, OFTestMode test_mode, ObjectiveFunction* of ) { MsqPrintError err(cout); vector<Vector3D> grad; vector<SymMatrix3D> diag; MsqHessian hess; bool valid = false; double result; switch (test_mode) { case EVAL: valid = of->evaluate( type, patch(), result, OF_FREE_EVALS_ONLY, err ); break; case GRAD: valid = of->evaluate_with_gradient( type, patch(), result, grad, err ); break; case DIAG: valid = of->evaluate_with_Hessian_diagonal( type, patch(), result, grad, diag, err ); break; case HESS: hess.initialize( patch(), err ); ASSERT_NO_ERROR( err ); valid = of->evaluate_with_Hessian( type, patch(), result, grad, hess, err ); break; default: CPPUNIT_ASSERT(false); } ASSERT_NO_ERROR( err ); CPPUNIT_ASSERT(valid); return result; }
void ObjectiveFunctionTests::compare_hessian_diagonal( ObjectiveFunction* of ) { MsqPrintError err(std::cout); PatchData pd; create_twelve_hex_patch( pd, err ); ASSERT_NO_ERROR( err ); std::vector<Vector3D> diag_grad, hess_grad; std::vector<SymMatrix3D> diag; MsqHessian hess; double diag_val, hess_val; bool valid; valid = of->evaluate_with_Hessian_diagonal( ObjectiveFunction::CALCULATE, pd, diag_val, diag_grad, diag, err ); ASSERT_NO_ERROR( err ); CPPUNIT_ASSERT(valid); CPPUNIT_ASSERT_EQUAL( pd.num_free_vertices(), diag_grad.size() ); CPPUNIT_ASSERT_EQUAL( pd.num_free_vertices(), diag.size() ); hess.initialize( pd, err ); ASSERT_NO_ERROR( err ); valid = of->evaluate_with_Hessian( ObjectiveFunction::CALCULATE, pd, hess_val, hess_grad, hess, err ); ASSERT_NO_ERROR( err ); CPPUNIT_ASSERT(valid); CPPUNIT_ASSERT_EQUAL( pd.num_free_vertices(), hess_grad.size() ); CPPUNIT_ASSERT_EQUAL( pd.num_free_vertices(), hess.size() ); CPPUNIT_ASSERT_DOUBLES_EQUAL( hess_val, diag_val, 1e-6 ); for (size_t i = 0; i < pd.num_free_vertices(); ++i) { CPPUNIT_ASSERT_VECTORS_EQUAL( hess_grad[i], diag_grad[i], 1e-6 ); CPPUNIT_ASSERT_MATRICES_EQUAL( *hess.get_block(i,i), diag[i], 1e-6 ); } }
void ObjectiveFunctionTests::compare_hessian_gradient( ObjectiveFunction* of ) { MsqPrintError err(std::cout); PatchData pd; create_twelve_hex_patch( pd, err ); ASSERT_NO_ERROR( err ); std::vector<Vector3D> grad, hess_grad; MsqHessian hess; double grad_val, hess_val; bool valid; valid = of->evaluate_with_gradient( ObjectiveFunction::CALCULATE, pd, grad_val, grad, err ); ASSERT_NO_ERROR( err ); CPPUNIT_ASSERT(valid); CPPUNIT_ASSERT_EQUAL( pd.num_free_vertices(), grad.size() ); hess.initialize( pd, err ); ASSERT_NO_ERROR( err ); valid = of->evaluate_with_Hessian( ObjectiveFunction::CALCULATE, pd, hess_val, hess_grad, hess, err ); ASSERT_NO_ERROR( err ); CPPUNIT_ASSERT(valid); CPPUNIT_ASSERT_EQUAL( pd.num_free_vertices(), hess_grad.size() ); CPPUNIT_ASSERT_DOUBLES_EQUAL( grad_val, hess_val, 1e-6 ); for (size_t i = 0; i < pd.num_free_vertices(); ++i) { CPPUNIT_ASSERT_VECTORS_EQUAL( grad[i], hess_grad[i], 1e-6 ); } }
void StdDevTemplateTest::test_hessian_fails_sqr() { MsqError err; double value; bool rval; vector<Vector3D> grad; MsqHessian Hess; Hess.initialize( patch(), err ); CPPUNIT_ASSERT(!MSQ_CHKERR(err)); OFTestQM metric( &value, 1 ); VarianceTemplate func( &metric ); rval = func.evaluate_with_Hessian( ObjectiveFunction::CALCULATE, patch(), value, grad, Hess, err ); CPPUNIT_ASSERT(err); }
bool ObjectiveFunction::evaluate_with_Hessian_diagonal( EvalType type, PatchData& pd, double& value_out, std::vector<Vector3D>& grad_out, std::vector<SymMatrix3D>& hess_diag_out, MsqError& err ) { MsqHessian hess; hess.initialize( pd, err ); MSQ_ERRZERO(err); bool val = evaluate_with_Hessian( type, pd, value_out, grad_out, hess, err ); MSQ_ERRZERO(err); hess_diag_out.resize( hess.size() ); for (size_t i = 0; i < hess.size(); ++i) hess_diag_out[i] = hess.get_block(i,i)->upper(); return val; }
void CompositeOFTest::test_multiply_hessian() { MsqError err; PatchData pd; create_twelve_hex_patch( pd, err ); ASSERT_NO_ERROR( err ); // this should always fail because the Hessian is not sparse CompositeOFMultiply OF( &LP1, &LP2 ); double value; MsqHessian hess; hess.initialize( pd, err ); ASSERT_NO_ERROR(err); std::vector<Vector3D> grad; OF.evaluate_with_Hessian( ObjectiveFunction::CALCULATE, pd, value, grad, hess, err ); CPPUNIT_ASSERT(err); }
void ObjectiveFunctionTest::test_compute_ana_hessian_tet_scaled() { MsqPrintError err(cout); PatchData tetPatch; create_qm_two_tet_patch(tetPatch,err); ASSERT_NO_ERROR(err); // creates a mean ratio quality metric ... IdealWeightInverseMeanRatio* mean_ratio = new IdealWeightInverseMeanRatio(err); CPPUNIT_ASSERT(!err); mean_ratio->set_averaging_method(QualityMetric::SUM); // ... and builds an objective function with it LPtoPTemplate LP2(mean_ratio, 2, err); LP2.set_dividing_by_n(true); MsqHessian H; std::vector<Vector3D> g; double dummy; H.initialize(tetPatch, err); CPPUNIT_ASSERT(!err); LP2.evaluate_with_Hessian(ObjectiveFunction::CALCULATE, tetPatch, dummy, g, H, err); CPPUNIT_ASSERT(!err); CPPUNIT_ASSERT_EQUAL( tetPatch.num_free_vertices(), g.size() ); Matrix3D mat00(" 2.44444 0.2566 0.181444 " " 0.2566 2.14815 0.104757 " " 0.181444 0.104757 2.07407 "); mat00*=.5; Matrix3D mat13(" 5.47514 3.16659 9.83479 " " -1.11704 -5.29718 -3.67406 " " 10.3635 -13.5358 -15.5638 "); mat13*=.5; CPPUNIT_ASSERT_MATRICES_EQUAL( mat00, *H.get_block(0,0), 1e-4 ); CPPUNIT_ASSERT_MATRICES_EQUAL( mat13, *H.get_block(1,3), 1e-4 ); // cout << H <<endl; delete mean_ratio; }
void ObjectiveFunctionTests::test_handles_qm_error( OFTestMode test_mode, ObjectiveFunctionTemplate* of ) { OFTestBadQM metric(true); of->set_quality_metric( &metric ); MsqError err; vector<Vector3D> grad; vector<SymMatrix3D> diag; MsqHessian hess; double result; bool valid; switch (test_mode) { case EVAL: valid = of->evaluate( ObjectiveFunction::CALCULATE, patch(), result, OF_FREE_EVALS_ONLY, err ); break; case GRAD: valid = of->evaluate_with_gradient( ObjectiveFunction::CALCULATE, patch(), result, grad, err ); break; case DIAG: valid = of->evaluate_with_Hessian_diagonal( ObjectiveFunction::CALCULATE, patch(), result, grad, diag, err ); break; case HESS: hess.initialize( patch(), err ); ASSERT_NO_ERROR( err ); valid = of->evaluate_with_Hessian( ObjectiveFunction::CALCULATE, patch(), result, grad, hess, err ); break; default: CPPUNIT_ASSERT(false); } CPPUNIT_ASSERT(err); }
void ObjectiveFunctionTests::compare_numerical_hessian( ObjectiveFunction* of, bool diagonal_only ) { const double delta = 0.0001; MsqPrintError err(std::cout); PatchData pd; create_qm_two_tet_patch( pd, err ); ASSERT_NO_ERROR( err ); CPPUNIT_ASSERT( pd.num_free_vertices() != 0 ); // get analytical Hessian from objective function std::vector<Vector3D> grad; std::vector<SymMatrix3D> diag; MsqHessian hess; hess.initialize( pd, err ); ASSERT_NO_ERROR( err ); double value; bool valid; if (diagonal_only) valid = of->evaluate_with_Hessian_diagonal( ObjectiveFunction::CALCULATE, pd, value, grad, diag, err ); else valid = of->evaluate_with_Hessian( ObjectiveFunction::CALCULATE, pd, value, grad, hess, err ); ASSERT_NO_ERROR(err); CPPUNIT_ASSERT(valid); // do numerical approximation of each block and compare to analytical value for (size_t i = 0; i < pd.num_free_vertices(); ++i) { const size_t j_end = diagonal_only ? i+1 : pd.num_free_vertices(); for (size_t j = i; j < j_end; ++j) { // do numerical approximation for block corresponding to // coorindates for ith and jth vertices. Matrix3D block; for (int k = 0; k < 3; ++k) { for (int m = 0; m < 3; ++m) { double dk, dm, dkm; Vector3D ik = pd.vertex_by_index(i); Vector3D im = pd.vertex_by_index(j); Vector3D delta_k(0.0); delta_k[k] = delta; pd.move_vertex( delta_k, i, err ); ASSERT_NO_ERROR(err); valid = of->evaluate( ObjectiveFunction::CALCULATE, pd, dk, true, err ); ASSERT_NO_ERROR(err); CPPUNIT_ASSERT(valid); Vector3D delta_m(0.0); delta_m[m] = delta; pd.move_vertex( delta_m, j, err ); ASSERT_NO_ERROR(err); valid = of->evaluate( ObjectiveFunction::CALCULATE, pd, dkm, true, err ); ASSERT_NO_ERROR(err); CPPUNIT_ASSERT(valid); // be careful here that we do the right thing if i==j pd.set_vertex_coordinates( ik, i, err ); ASSERT_NO_ERROR(err); pd.set_vertex_coordinates( im, j, err ); ASSERT_NO_ERROR(err); pd.move_vertex( delta_m, j, err ); ASSERT_NO_ERROR(err); valid = of->evaluate( ObjectiveFunction::CALCULATE, pd, dm, true, err ); ASSERT_NO_ERROR(err); CPPUNIT_ASSERT(valid); pd.set_vertex_coordinates( ik, i, err ); ASSERT_NO_ERROR(err); pd.set_vertex_coordinates( im, j, err ); ASSERT_NO_ERROR(err); block[k][m] = (dkm - dk - dm + value)/(delta*delta); } } // compare to analytical value if (diagonal_only) { CPPUNIT_ASSERT(i == j); // see j_end above CPPUNIT_ASSERT(i < diag.size()); CHECK_EQUAL_MATRICES( block, Matrix3D(diag[i]) ); } else { Matrix3D* m = hess.get_block( i, j ); Matrix3D* mt = hess.get_block( j, i ); if (NULL != m) { CHECK_EQUAL_MATRICES( block, *m ); } if (NULL != mt) { CHECK_EQUAL_MATRICES( transpose(block), *m ); } if (NULL == mt && NULL == m) { CHECK_EQUAL_MATRICES( Matrix3D(0.0), block ); } } } } }