| /external/ceres-solver/internal/ceres/ |
| covariance.cc | 31 #include "ceres/covariance.h"
41 Covariance::Covariance(const Covariance::Options& options) {
45 Covariance::~Covariance() {
48 bool Covariance::Compute(
54 bool Covariance::GetCovarianceBlock(const double* parameter_block1,
|
| covariance_impl.cc | 43 #include "ceres/covariance.h"
92 CovarianceImpl::CovarianceImpl(const Covariance::Options& options)
118 << "Covariance::GetCovarianceBlock called before Covariance::Compute";
120 << "Covariance::GetCovarianceBlock called when Covariance::Compute "
124 // covariance block is also zero.
148 // Find where in the covariance matrix the block is located.
160 // covariance block begin.
167 LOG(WARNING) << "Unable to find covariance block for
[all...] |
| covariance_impl.h | 38 #include "ceres/covariance.h"
51 explicit CovarianceImpl(const Covariance::Options& options);
77 Covariance::Options options_;
|
| covariance_test.cc | 31 #include "ceres/covariance.h"
96 Covariance::Options options;
285 void ComputeAndCompareCovarianceBlocks(const Covariance::Options& options,
288 // covariance computation is correct.
315 Covariance covariance(options);
316 EXPECT_TRUE(covariance.Compute(covariance_blocks, &problem_));
322 GetCovarianceBlockAndCompare(block1, block2, covariance, expected_covariance);
324 GetCovarianceBlockAndCompare(block2, block1, covariance, expected_covariance);
331 const Covariance& covariance
[all...] |
| CMakeLists.txt | 53 covariance.cc
241 CERES_TEST(covariance)
|
| /external/ceres-solver/include/ceres/ |
| covariance.h | 55 // This class allows the user to evaluate the covariance for a
62 // non-linear least squares solve is to analyze the covariance of the
70 // independent variable x with mean f(x) and identity covariance. Then
76 // And the covariance of x* is given by
83 // If J(x*) is rank deficient, then the covariance matrix C(x*) is
88 // Note that in the above, we assumed that the covariance
94 // Where S is a positive semi-definite matrix denoting the covariance
99 // and the corresponding covariance estimate of x* is given by
104 // covariance matrix not equal to identity, then it is the user's
108 // is the inverse square root of the covariance matrix S
[all...] |
| normal_prior.h | 52 // where, mu is a vector and S is a covariance matrix, then, A =
54 // covariance, also known as the stiffness matrix. There are however
56 // which would be the case if the covariance matrix S is rank
|
| ceres.h | 44 #include "ceres/covariance.h"
|
| /external/eigen/unsupported/Eigen/src/NonLinearOptimization/ |
| covar.h | 45 /* form the full lower triangle of the covariance matrix */
62 /* symmetrize the covariance matrix in r. */
|
| /frameworks/native/services/sensorservice/ |
| Fusion.h | 40 * the predicated covariance matrix is made of 4 3x3 sub-matrices and it is
52 * the process noise covariance matrix
|
| /external/ceres-solver/docs/source/ |
| solving.rst | [all...] |
| /external/srec/srec/include/ |
| hmm_desc.h | 39 #define DIAG (1<<4) /* Diagonal covariance model */
40 #define FULL (2<<4) /* Full covariance model */
|
| hmm_type.h | 39 typedef double covdata; /* covariance data */
|
| all_defs.h | 50 #define EIGEN 1 /* for full covariance probability calc. */
60 #define ITEM_WEIGHT 1 // item weighting for covariance calc.
|
| pre_desc.h | 70 prdata grand_mod_cov; /* grand covariance modulus */
71 prdata grand_mod_cov_gaussian; /* grand covariance modulus */
|
| /external/chromium_org/third_party/protobuf/java/src/main/java/com/google/protobuf/ |
| Message.java | 53 // (From MessageLite, re-declared here only for return type covariance.)
98 // (From MessageLite, re-declared here only for return type covariance.)
107 // covariance.)
129 // covariance.)
213 // covariance.)
|
| MessageOrBuilder.java | 44 // (From MessageLite, re-declared here only for return type covariance.)
|
| /external/protobuf/java/src/main/java/com/google/protobuf/ |
| Message.java | 61 // (From MessageLite, re-declared here only for return type covariance.)
154 // (From MessageLite, re-declared here only for return type covariance.)
163 // covariance.)
185 // covariance.)
201 // covariance.)
281 // covariance.)
|
| /external/eigen/Eigen/src/Eigen2Support/ |
| LeastSquares.h | 122 * 2 - compute the covariance matrix
123 * 3 - pick the eigenvector corresponding to the smallest eigenvalue of the covariance matrix
148 // compute the covariance matrix
|
| /external/opencv/cv/include/ |
| cvtypes.h | 300 CvMat* process_noise_cov; /* process noise covariance matrix (Q) */
301 CvMat* measurement_noise_cov; /* measurement noise covariance matrix (R) */
302 CvMat* error_cov_pre; /* priori error estimate covariance matrix (P'(k)):
306 CvMat* error_cov_post; /* posteriori error estimate covariance matrix (P(k)):
|
| /external/clang/test/ARCMT/ |
| checking.m | 199 - (id) init03; // covariance
200 - (id) init04; // covariance
218 - (Test8_super*) init30; // id exception to covariance
222 - (Test8_super*) init34; // covariance
225 - (Test8*) init40; // id exception to covariance
|
| /external/chromium_org/ui/gfx/ |
| color_analysis.cc | 407 gfx::Matrix3F covariance = gfx::Matrix3F::Zeros(); local
409 return covariance;
444 // Covariance (not normalized) is E(X*X.t) - m * m.t and this is how it
449 covariance.set(
468 return covariance;
554 gfx::Matrix3F covariance = ComputeColorCovariance(source_bitmap); local
556 gfx::Vector3dF eigenvals = covariance.SolveEigenproblem(&eigenvectors);
|
| color_analysis.h | 102 // Compute color covariance matrix for the input bitmap.
|
| color_analysis_unittest.cc | 292 gfx::Matrix3F covariance = color_utils::ComputeColorCovariance(bitmap); local
294 EXPECT_TRUE(covariance == gfx::Matrix3F::Zeros());
309 gfx::Matrix3F covariance = color_utils::ComputeColorCovariance(bitmap); local
315 EXPECT_EQ(expected_covariance, covariance);
|
| /external/eigen/Eigen/src/Geometry/ |
| Umeyama.h | 70 * The algorithm is based on the analysis of the covariance matrix
75 * though the actual computational effort lies in the covariance
|
