| /external/ceres-solver/internal/ceres/ |
| dynamic_compressed_row_finalizer.h | 42 DynamicCompressedRowSparseMatrix* jacobian = local
44 jacobian->Finalize(num_parameters);
|
| evaluator_test_utils.h | 44 const double jacobian[200]; member in struct:ceres::internal::ExpectedEvaluation
|
| normal_prior_test.cc | 70 double * jacobian = new double[num_rows * num_cols]; local
74 prior.Evaluate(&x, residuals.data(), &jacobian);
82 MatrixRef J(jacobian, num_rows, num_cols);
87 delete []jacobian;
|
| corrector_test.cc | 60 double jacobian = 10.0; local
74 // The jacobian in this case will be
75 // sqrt(kRho[1]) * (1 - kAlpha) * jacobian.
76 const double kExpectedJacobian = sqrt(kRho[1]) * (1 - kAlpha) * jacobian;
79 c.CorrectJacobian(1.0, 1.0, &residuals, &jacobian);
83 ASSERT_NEAR(kExpectedJacobian, jacobian, 1e-6);
88 double jacobian = 10.0; local
102 // The jacobian in this case will be
103 // sqrt(kRho[1]) * jacobian.
104 const double kExpectedJacobian = sqrt(kRho[1]) * jacobian;
116 double jacobian = 10.0; local
147 double jacobian[2 * 3]; local
215 double jacobian[2 * 3]; local
[all...] |
| dynamic_compressed_row_jacobian_writer.cc | 48 // Initialize `jacobian` with zero number of `max_num_nonzeros`.
52 DynamicCompressedRowSparseMatrix* jacobian = local
58 program_, jacobian);
60 return jacobian;
67 DynamicCompressedRowSparseMatrix* jacobian = local
79 // `residual_offset` is the residual row in the global jacobian.
80 // Empty the jacobian rows.
81 jacobian->ClearRows(residual_offset, num_residuals);
98 jacobian->InsertEntry(
|
| autodiff_local_parameterization_test.cc | 64 double jacobian[9]; local
65 parameterization.ComputeJacobian(x, jacobian);
69 EXPECT_EQ(jacobian[k], (i == j) ? 1.0 : 0.0);
105 double jacobian[9]; local
106 parameterization.ComputeJacobian(x, jacobian);
110 EXPECT_NEAR(jacobian[k], (i == j) ? 1.2345 : 0.0, kTolerance);
157 double jacobian[12]; local
160 parameterization.ComputeJacobian(x, jacobian);
175 EXPECT_TRUE(IsFinite(jacobian[i]));
176 EXPECT_NEAR(jacobian[i], jacobian_ref[i], kTolerance
[all...] |
| block_jacobian_writer.cc | 47 // per-parameter jacobian goes where in the overall program jacobian.
63 // are there. This will determine where the F blocks start in the jacobian
64 // matrix. Also compute the number of jacobian blocks.
135 // Create evaluate prepareres that point directly into the final jacobian. This
206 BlockSparseMatrix* jacobian = new BlockSparseMatrix(bs); local
207 CHECK_NOTNULL(jacobian);
208 return jacobian;
|
| dogleg_strategy_test.cc | 77 Matrix jacobian = sqrtD * basis; local
78 jacobian_.reset(new DenseSparseMatrix(jacobian));
82 residual_ = -jacobian * minimum;
105 Matrix jacobian = Ddiag.asDiagonal(); local
106 jacobian_.reset(new DenseSparseMatrix(jacobian));
110 residual_ = -jacobian * minimum;
|
| local_parameterization_test.cc | 55 double jacobian[9]; local
56 parameterization.ComputeJacobian(x, jacobian);
60 EXPECT_EQ(jacobian[k], (i == j) ? 1.0 : 0.0);
106 double jacobian[4 * 3]; local
107 parameterization.ComputeJacobian(x, jacobian);
113 EXPECT_EQ(jacobian[jacobian_cursor], delta_cursor == k ? 1.0 : 0.0);
118 EXPECT_EQ(jacobian[jacobian_cursor], 0.0);
184 // Autodiff jacobian at delta_x = 0.
188 double jacobian[12]; local
189 param.ComputeJacobian(x, jacobian);
[all...] |
| residual_block_utils_test.cc | 62 double jacobian; local
63 double* jacobians[] = { &jacobian };
|
| compressed_row_jacobian_writer.cc | 44 const Program* program, CompressedRowSparseMatrix* jacobian) {
47 vector<int>& col_blocks = *(jacobian->mutable_col_blocks());
55 vector<int>& row_blocks = *(jacobian->mutable_row_blocks());
88 // Count the number of jacobian nonzeros.
102 // Allocate storage for the jacobian with some extra space at the end.
103 // Allocate more space than needed to store the jacobian so that when the LM
106 CompressedRowSparseMatrix* jacobian = local
114 int* rows = jacobian->mutable_rows();
115 int* cols = jacobian->mutable_cols();
150 // parameter vector. This code mirrors that in Write(), where jacobian
182 CompressedRowSparseMatrix* jacobian = local
[all...] |
| dynamic_numeric_diff_cost_function_test.cc | 120 // Prepare the jacobian.
124 vector<double*> jacobian; local
125 jacobian.push_back(jacobian_vect[0].data());
126 jacobian.push_back(jacobian_vect[1].data());
128 // Test jacobian computation.
131 jacobian.data()));
139 // Check "A" Jacobian.
141 // Check "B" Jacobian.
147 // Check "C" Jacobian for first parameter block.
156 // Check "C" Jacobian for second parameter block
191 vector<double*> jacobian; local
241 vector<double*> jacobian; local
444 vector<double*> jacobian; local
474 vector<double*> jacobian; local
496 vector<double*> jacobian; local
[all...] |
| covariance_test.cc | 129 const double* jacobian)
130 : jacobian_(jacobian, jacobian + num_residuals * parameter_block_size) {
214 virtual bool ComputeJacobian(const double* x, double* jacobian) const {
215 jacobian[0] = x[0];
216 jacobian[1] = x[1];
239 double jacobian[] = { 1.0, 0.0, 0.0, 1.0}; local
240 problem_.AddResidualBlock(new UnaryCostFunction(2, 2, jacobian), NULL, x);
244 double jacobian[] = { 2.0, 0.0, 0.0, 0.0, 2.0, 0.0, 0.0, 0.0, 2.0 }; local
245 problem_.AddResidualBlock(new UnaryCostFunction(3, 3, jacobian), NULL, y)
249 double jacobian = 5.0; local
629 double jacobian[] = { 1.0, 0.0, 0.0, 1.0}; local
634 double jacobian[] = { 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0 }; local
639 double jacobian = 5.0; local
[all...] |
| dynamic_autodiff_cost_function_test.cc | 119 // Prepare the jacobian.
123 vector<double*> jacobian; local
124 jacobian.push_back(jacobian_vect[0].data());
125 jacobian.push_back(jacobian_vect[1].data());
127 // Test jacobian computation.
130 jacobian.data()));
138 // Check "A" Jacobian.
140 // Check "B" Jacobian.
146 // Check "C" Jacobian for first parameter block.
155 // Check "C" Jacobian for second parameter block
190 vector<double*> jacobian; local
240 vector<double*> jacobian; local
443 vector<double*> jacobian; local
473 vector<double*> jacobian; local
495 vector<double*> jacobian; local
687 vector<double*> jacobian; local
713 vector<double*> jacobian; local
744 vector<double*> jacobian; local
[all...] |
| evaluator_test.cc | 70 // evaluator into the "local" jacobian. In the tests, the "subset
72 // from these jacobians. Put values in the jacobian that make this
82 MatrixRef jacobian(jacobians[k],
86 jacobian.col(j).setConstant(kFactor * (j + 1));
155 scoped_ptr<SparseMatrix> jacobian(evaluator->CreateJacobian());
159 ASSERT_EQ(expected_num_rows, jacobian->num_rows());
160 ASSERT_EQ(expected_num_cols, jacobian->num_cols());
169 expected_jacobian != NULL ? jacobian.get() : NULL));
173 jacobian->ToDenseMatrix(&actual_jacobian);
197 (i & 4) ? expected.jacobian : NULL)
578 double* jacobian = jacobians[0]; local
[all...] |
| minimizer.h | 113 jacobian = NULL;
168 // Jacobian matrix. The Options struct does not own this pointer.
176 // Object holding the Jacobian matrix. It is assumed that the
180 SparseMatrix* jacobian; member in struct:ceres::internal::Minimizer::Options
|
| trust_region_minimizer.cc | 109 // of the Jacobian.
110 void TrustRegionMinimizer::EstimateScale(const SparseMatrix& jacobian,
112 jacobian.SquaredColumnNorm(scale);
113 for (int i = 0; i < jacobian.num_cols(); ++i) {
132 SparseMatrix* jacobian = CHECK_NOTNULL(options_.jacobian); local
196 // Do initial cost and Jacobian evaluation.
202 jacobian)) {
203 summary->message = "Residual and Jacobian evaluation failed.";
236 EstimateScale(*jacobian, scale.data())
[all...] |
| covariance_impl.cc | 411 CRSMatrix jacobian; local
412 problem_->Evaluate(evaluate_options_, NULL, NULL, NULL, &jacobian);
415 // Construct a compressed column form of the Jacobian.
416 const int num_rows = jacobian.num_rows;
417 const int num_cols = jacobian.num_cols;
418 const int num_nonzeros = jacobian.values.size();
425 transpose_rows[jacobian.cols[idx] + 1] += 1;
433 for (int idx = jacobian.rows[r]; idx < jacobian.rows[r + 1]; ++idx) {
434 const int c = jacobian.cols[idx]
574 CRSMatrix jacobian; local
663 CRSMatrix jacobian; local
[all...] |
| problem_test.cc | 1097 CRSMatrix jacobian; local
[all...] |
| /external/eigen/unsupported/Eigen/src/AutoDiff/ |
| AutoDiffVector.h | 73 : m_values(other.values()), m_jacobian(other.jacobian())
77 : m_values(other.values()), m_jacobian(other.jacobian())
84 m_jacobian = other.jacobian();
91 m_jacobian = other.jacobian();
98 inline const JacobianType& jacobian() const { return m_jacobian; } function in class:Eigen::AutoDiffVector
99 inline JacobianType& jacobian() { return m_jacobian; } function in class:Eigen::AutoDiffVector
111 m_jacobian + other.jacobian());
119 m_jacobian += other.jacobian();
133 m_jacobian - other.jacobian());
141 m_jacobian -= other.jacobian();
[all...] |
| /external/eigen/unsupported/Eigen/src/LevenbergMarquardt/ |
| LevenbergMarquardt.h | 177 /** \returns a reference to the diagonal of the jacobian */
186 /** \returns the number of jacobian evaluation */
202 /** \returns a reference to the matrix where the current Jacobian matrix is stored
204 JacobianType& jacobian() {return m_fjac; } function in class:Eigen::LevenbergMarquardt
206 /** \returns a reference to the triangular matrix R from the QR of the jacobian matrix.
207 * \sa jacobian()
231 JacobianType m_rfactor; // The triangular matrix R from the QR of the jacobian matrix m_fjac
283 //FIXME Sparse Case : Allocate space for the jacobian
|
