/external/apache-commons-math/src/main/java/org/apache/commons/math/analysis/ |
DifferentiableMultivariateVectorialFunction.java | 31 * Returns the jacobian function. 32 * @return the jacobian function 34 MultivariateMatrixFunction jacobian(); method in interface:DifferentiableMultivariateVectorialFunction
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/external/ceres-solver/internal/ceres/ |
dynamic_compressed_row_finalizer.h | 42 DynamicCompressedRowSparseMatrix* jacobian = local 44 jacobian->Finalize(num_parameters);
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evaluator_test_utils.h | 44 const double jacobian[200]; member in struct:ceres::internal::ExpectedEvaluation
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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;
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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(
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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;
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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;
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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 };
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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
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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/apache-commons-math/src/main/java/org/apache/commons/math/optimization/fitting/ |
CurveFitter.java | 163 public MultivariateMatrixFunction jacobian() { method in class:CurveFitter.TheoreticalValuesFunction 168 final double[][] jacobian = new double[observations.size()][]; 172 jacobian[i++] = f.gradient(observed.getX(), point); 175 return jacobian;
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/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/apache-commons-math/src/main/java/org/apache/commons/math/estimation/ |
AbstractEstimator.java | 32 * settings, jacobian and error estimation.</p> 52 * Jacobian matrix. 58 protected double[] jacobian; field in class:AbstractEstimator 60 /** Number of columns of the jacobian matrix. */ 63 /** Number of rows of the jacobian matrix. */ 83 /** Number of jacobian evaluations. */ 115 * Get the number of jacobian evaluations. 117 * @return number of jacobian evaluations 124 * Update the jacobian matrix. 128 Arrays.fill(jacobian, 0) [all...] |
/external/apache-commons-math/src/main/java/org/apache/commons/math/optimization/general/ |
AbstractLeastSquaresOptimizer.java | 40 * settings, jacobian and error estimation.</p> 54 * Jacobian matrix. 60 protected double[][] jacobian; field in class:AbstractLeastSquaresOptimizer 62 /** Number of columns of the jacobian matrix. */ 65 /** Number of rows of the jacobian matrix. */ 89 /** Weighted Jacobian */ 110 /** Number of jacobian evaluations. */ 186 * Update the jacobian matrix. 187 * @exception FunctionEvaluationException if the function jacobian 192 jacobian = jF.value(point) [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
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