| /external/ceres-solver/internal/ceres/ |
| D | corrector_test.cc | 151 MatrixRef jac(jacobian, 3, 2); in TEST() local
191 g_jac = sqrt(rho[1]) * (jac - kAlpha / sq_norm * in TEST()
192 res * res.transpose() * jac); in TEST()
194 g_grad = rho[1] * jac.transpose() * res; in TEST()
195 g_hess = rho[1] * jac.transpose() * jac + in TEST()
196 2.0 * rho[2] * jac.transpose() * res * res.transpose() * jac; in TEST()
203 c_grad = jac.transpose() * res; in TEST()
204 c_hess = jac.transpose() * jac; in TEST()
207 ASSERT_NEAR((g_jac - jac).norm(), 0.0, 1e-10); in TEST()
219 MatrixRef jac(jacobian, 3, 2); in TEST() local
[all …]
|
| D | conditioned_cost_function_test.cc | 72 jac[kTestCostFunctionSize * kTestCostFunctionSize], in TEST() local
80 jac[i * 2] = i * i; in TEST()
106 jacs[0] = jac; in TEST()
115 double actual = jac[i * kTestCostFunctionSize + j]; in TEST()
|
| D | autodiff_test.cc | 57 T jac[M * N]) { // row-major. in SymmetricDiff()
89 RowMajorAccess(jac, M, N, i, j) = in SymmetricDiff()
|
| /external/eigen/unsupported/Eigen/src/AutoDiff/ |
| D | AutoDiffJacobian.h | 57 JacobianType& jac = *_jac; in operator() local
60 ActiveValue av(jac.rows()); in operator()
63 for (Index j=0; j<jac.rows(); j++) in operator()
66 for (Index i=0; i<jac.cols(); i++) in operator()
71 for (Index i=0; i<jac.rows(); i++) in operator()
74 jac.row(i) = av[i].derivatives(); in operator()
|
| D | AutoDiffVector.h | 67 inline AutoDiffVector(const ValueType& values, const JacobianType& jac) in AutoDiffVector() argument
68 : m_values(values), m_jacobian(jac) in AutoDiffVector()
|
| /external/eigen/unsupported/test/ |
| D | NumericalDiff.cpp | 73 MatrixXd jac(15,3); in test_forward() local
85 numDiff.df(x, jac); in test_forward()
88 VERIFY_IS_APPROX(jac, actual_jac); in test_forward()
94 MatrixXd jac(15,3); in test_central() local
105 numDiff.df(x, jac); in test_central()
107 VERIFY_IS_APPROX(jac, actual_jac); in test_central()
|
| /external/eigen/unsupported/Eigen/ |
| D | AdolcForward | 130 JacobianType& jac = *_jac;
133 ActiveValue av(jac.rows());
135 for (int j=0; j<jac.cols(); j++)
136 for (int i=0; i<jac.cols(); i++)
141 for (int i=0; i<jac.rows(); i++)
144 for (int j=0; j<jac.cols(); j++)
145 jac.coeffRef(i,j) = av[i].getADValue(j);
|
| /external/eigen/unsupported/Eigen/src/NumericalDiff/ |
| D | NumericalDiff.h | 64 int df(const InputType& _x, JacobianType &jac) const in df() argument
104 jac.col(j) = (val2-val1)/h; in df()
112 jac.col(j) = (val2-val1)/(2*h); in df()
|
| /external/opencv3/modules/stitching/include/opencv2/stitching/detail/ |
| D | motion_estimators.hpp | 170 virtual void calcJacobian(Mat &jac) = 0;
213 void calcJacobian(Mat &jac);
233 void calcJacobian(Mat &jac);
|
| /external/opencv3/modules/stitching/src/ |
| D | motion_estimators.cpp | 213 Mat err, jac; in estimate() local
233 calcJacobian(jac); in estimate()
234 CvMat tmp = jac; in estimate()
397 void BundleAdjusterReproj::calcJacobian(Mat &jac) in calcJacobian() argument
399 jac.create(total_num_matches_ * 2, num_images_ * 7, CV_64F); in calcJacobian()
400 jac.setTo(0); in calcJacobian()
414 calcDeriv(err1_, err2_, 2 * step, jac.col(i * 7)); in calcJacobian()
424 calcDeriv(err1_, err2_, 2 * step, jac.col(i * 7 + 1)); in calcJacobian()
434 calcDeriv(err1_, err2_, 2 * step, jac.col(i * 7 + 2)); in calcJacobian()
444 calcDeriv(err1_, err2_, 2 * step, jac.col(i * 7 + 3)); in calcJacobian()
[all …]
|
| /external/opencv3/modules/calib3d/test/ |
| D | test_precomp.hpp | 20 void Rodrigues(const Mat& src, Mat& dst, Mat* jac=0);
|
| D | test_fundam.cpp | 351 void cvtest::Rodrigues(const Mat& src, Mat& dst, Mat* jac) in Rodrigues() argument
354 if( jac ) in Rodrigues()
355 _jac = *jac; in Rodrigues()
356 cvTsRodrigues(&_src, &_dst, jac ? &_jac : 0); in Rodrigues()
|
| /external/opencv3/doc/py_tutorials/py_calib3d/py_pose/ |
| D | py_pose.markdown | 76 imgpts, jac = cv2.projectPoints(axis, rvecs, tvecs, mtx, dist)
|
| /external/hyphenation-patterns/en-GB/ |
| D | hyph-en-gb.pat.txt | 3904 3jac
|