| /external/ceres-solver/internal/ceres/ |
| suitesparse.h | 172 // Given a Cholesky factorization of a matrix A = LL^T, solve the
173 // linear system Ax = b, and return the result. If the Solve fails
175 cholmod_dense* Solve(cholmod_factor* L, cholmod_dense* b);
177 // Combine the calls to Cholesky and Solve into a single call. If
178 // the cholesky factorization or the solve fails, return
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| dogleg_strategy.cc | 116 // regularize the Gauss-Newton solve and that defines the
373 // For any given y, we can solve (2) for x as
444 return -B_i.partialPivLu().solve(subspace_g_);
453 // This function attempts to solve the boundary-constrained subspace problem
526 // If the solve fails, the multiplier to the diagonal is increased
532 // multiplier starts out from the last successful solve.
540 // that we need to solve the normal equations more or less
557 // As in the LevenbergMarquardtStrategy, solve Jy = r instead
561 linear_solver_summary = linear_solver_->Solve(jacobian,
618 // to doing a pure Gauss-Newton solve
[all...] |
| coordinate_descent_minimizer.cc | 181 Solve(&inner_program,
202 // Solve the optimization problem for one parameter block.
203 void CoordinateDescentMinimizer::Solve(Program* program,
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| schur_eliminator_test.cc | 116 .solve(Matrix::Identity(block_size, block_size));
124 sol_expected = H.llt().solve(g);
164 .solve(rhs);
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| solver.cc | 66 void Solver::Solve(const Solver::Options& options,
72 internal::SolverImpl::Solve(options, problem_impl, summary);
77 void Solve(const Solver::Options& options,
81 solver.Solve(options, problem, summary);
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| implicit_schur_complement.h | 67 // Now if we wish to solve Ax = b in the least squares sense, one way
68 // is to form this Schur complement system and solve it using
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| implicit_schur_complement_test.cc | 112 schur_solution = lhs->selfadjointView<Eigen::Upper>().llt().solve(*rhs);
159 lhs.selfadjointView<Eigen::Upper>().llt().solve(rhs);
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| levenberg_marquardt_strategy.cc | 103 // Instead of solving Jx = -r, solve Jy = r.
107 linear_solver_->Solve(jacobian, residuals, solve_options, step);
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| unsymmetric_linear_solver_test.cc | 89 solver->Solve(transformed_A.get(),
97 solver->Solve(transformed_A.get(),
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| /external/eigen/doc/ |
| C06_TutorialLinearAlgebra.dox | 9 This tutorial explains how to solve linear systems, compute various decompositions such as LU,
44 Vector3f x = dec.solve(b);
110 All of these decompositions offer a solve() method that works as in the above example.
162 advantageously replaced by solve() operations, and the determinant is often \em not a good way of checking if a matrix
182 The best way to do least squares solving is with a SVD decomposition. Eigen provides one as the JacobiSVD class, and its solve()
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| I11_Aliasing.dox | 49 explains how to solve this problem by calling \link DenseBase::eval() eval()\endlink.
82 If you understand the cause of the aliasing issue, then it is obvious what must happen to solve it: Eigen has
122 <tr> <td> LDLT::solve() </td> <td> LDLT::solveInPlace() </td> </tr>
123 <tr class="alt"> <td> LLT::solve() </td> <td> LLT::solveInPlace() </td> </tr>
124 <tr> <td> TriangularView::solve() </td> <td> TriangularView::solveInPlace() </td> </tr>
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| C09_TutorialSparse.dox | 29 <tr><td>\link SparseCholesky_Module SparseCholesky \endlink</td><td>\code#include <Eigen/SparseCholesky>\endcode</td><td>Direct sparse LLT and LDLT Cholesky factorization to solve sparse self-adjoint positive definite problems</td></tr>
30 <tr><td>\link IterativeLinearSolvers_Module IterativeLinearSolvers \endlink</td><td>\code#include <Eigen/IterativeLinearSolvers>\endcode</td><td>Iterative solvers to solve large general linear square problems (including self-adjoint positive definite problems)</td></tr>
291 // solve Ax = b
298 x = solver.solve(b);
303 // solve for another right hand side:
304 x1 = solver.solve(b1);
313 x = solver.compute(A).solve(b);
322 x1 = solver.solve(b1);
323 x2 = solver.solve(b2);
327 x1 = solver.solve(b1)
[all...] |
| /external/eigen/test/ |
| sparse_solver.h | 19 DenseRhs refX = dA.lu().solve(db);
31 x = solver.solve(b);
51 x = solver.solve(b);
66 x.block(0,0,x.rows(),x.cols()) = solver.solve(b.block(0,0,b.rows(),b.cols()));
88 x = solver.solve(b);
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| /external/chromium_org/third_party/opus/src/silk/float/ |
| solve_LS_FLP.c | 48 * Function to solve linear equation Ax = b, when A is a MxM lower
59 * Function to solve linear equation (A^T)x = b, when A is a MxM lower
70 * Function to solve linear equation Ax = b, when A is a MxM
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| levinsondurbin_FLP.c | 34 /* Solve the normal equations using the Levinson-Durbin recursion */
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| /external/llvm/include/llvm/Analysis/ |
| SparsePropagation.h | 143 /// Solve - Solve for constants and executable blocks.
145 void Solve(Function &F);
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| /external/ceres-solver/examples/ |
| bundle_adjuster.cc | 98 "accuracy of each linear solve of the truncated newton step. "
99 "Changing this parameter can affect solve performance.");
103 DEFINE_double(max_solver_time, 1e32, "Maximum solve time in seconds.");
326 Solve(options, &problem, &summary);
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| powell.cc | 56 using ceres::Solve;
145 Solve(options, &problem, &summary);
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| /external/chromium_org/remoting/client/plugin/ |
| mac_key_event_processor.h | 5 // MacKeyEventProcessor is designed to solve the problem of missing keyup
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| /external/eigen/Eigen/src/Cholesky/ |
| LDLT.h | 161 * This function also supports in-place solves using the syntax <tt>x = decompositionObject.solve(x)</tt> .
176 solve(const MatrixBase<Rhs>& b) const function in class:Eigen::LDLT
180 && "LDLT::solve(): invalid number of rows of the right hand side matrix b");
186 bool solve(const MatrixBase<OtherDerived>& b, ResultType *result) const function in class:Eigen::LDLT
188 *result = this->solve(b);
519 /** \internal use x = ldlt_object.solve(x);
521 * This is the \em in-place version of solve().
530 * \sa LDLT::solve(), MatrixBase::ldlt()
540 bAndX = this->solve(bAndX);
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| /external/eigen/unsupported/Eigen/src/MatrixFunctions/ |
| MatrixLogarithm.h | 254 .template triangularView<Upper>().solve(TminusI);
270 .template triangularView<Upper>().solve(TminusI);
288 .template triangularView<Upper>().solve(TminusI);
306 .template triangularView<Upper>().solve(TminusI);
326 .template triangularView<Upper>().solve(TminusI);
346 .template triangularView<Upper>().solve(TminusI);
368 .template triangularView<Upper>().solve(TminusI);
390 .template triangularView<Upper>().solve(TminusI);
414 .template triangularView<Upper>().solve(TminusI);
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| /external/llvm/lib/Support/ |
| SearchForAddressOfSpecialSymbol.cpp | 24 // If this is darwin, it has some funky issues, try to solve them here. Some
|
| /external/llvm/test/Transforms/CodeExtractor/ |
| 2004-03-13-LoopExtractorCrash.ll | 3 define void @solve() {
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| /frameworks/base/core/tests/coretests/src/android/util/ |
| TouchModeFlexibleAsserts.java | 28 * tap) until we can find a way to solve the flakiness.
|
| /external/chromium_org/third_party/WebKit/Source/core/rendering/ |
| RenderBox.cpp | [all...] |
