| /external/eigen/Eigen/src/Eigenvalues/ |
| ComplexSchur.h | 40 * Call the function compute() to compute the Schur decomposition of
88 * intends to perform decompositions via compute(). The \p size
92 * \sa compute() for an example.
108 * This constructor calls compute() to compute the Schur decomposition.
121 compute(matrix.derived(), computeU);
130 * member function compute(const MatrixType& matrix, bool computeU)
131 * has been called before to compute the Schur decomposition of a
151 * member function compute(const MatrixType& matrix, bool computeU
319 ComplexSchur<MatrixType>& ComplexSchur<MatrixType>::compute(const EigenBase<InputType>& matrix, bool computeU) function in class:Eigen::ComplexSchur
[all...] |
| EigenSolver.h | 46 * Call the function compute() to compute the eigenvalues and eigenvectors of
109 * perform decompositions via EigenSolver::compute(const MatrixType&, bool).
111 * \sa compute() for an example.
138 * This constructor calls compute() to compute the eigenvalues
144 * \sa compute()
156 compute(matrix.derived(), computeEigenvectors);
165 * compute(const MatrixType&, bool) has been called before, and
187 * compute(const MatrixType&, bool) has been called before, an
379 EigenSolver<MatrixType>::compute(const EigenBase<InputType>& matrix, bool computeEigenvectors) function in class:Eigen::EigenSolver
[all...] |
| GeneralizedEigenSolver.h | 45 * Call the function compute() to compute the generalized eigenvalues and eigenvectors of
114 * perform decompositions via EigenSolver::compute(const MatrixType&, bool).
116 * \sa compute() for an example.
150 * This constructor calls compute() to compute the generalized eigenvalues
153 * \sa compute()
164 compute(A, B, computeEigenvectors);
174 * compute(const MatrixType&, const MatrixType& bool) has been called before, and
194 * compute(const MatrixType&,const MatrixType&,bool) has been called before
287 GeneralizedEigenSolver<MatrixType>::compute(const MatrixType& A, const MatrixType& B, bool computeEigenvectors) function in class:Eigen::GeneralizedEigenSolver
[all...] |
| RealSchur.h | 36 * A, and thus the real Schur decomposition is used in EigenSolver to compute
39 * Call the function compute() to compute the real Schur decomposition of a
77 * perform decompositions via compute(). The \p size parameter is only
81 * \sa compute() for an example.
98 * This constructor calls compute() to compute the Schur decomposition.
113 compute(matrix.derived(), computeU);
121 * member function compute(const MatrixType&, bool) has been called before
122 * to compute the Schur decomposition of a matrix, and \p computeU was se
249 RealSchur<MatrixType>& RealSchur<MatrixType>::compute(const EigenBase<InputType>& matrix, bool computeU) function in class:Eigen::RealSchur
[all...] |
| Tridiagonalization.h | 48 * decomposition. This class is used in SelfAdjointEigenSolver to compute the
51 * Call the function compute() to compute the tridiagonal decomposition of a
107 * perform decompositions via compute(). The \p size parameter is only
111 * \sa compute() for an example.
124 * This constructor calls compute() to compute the tridiagonal decomposition.
157 Tridiagonalization& compute(const EigenBase<InputType>& matrix) function in class:Eigen::Tridiagonalization
171 * the member function compute(const MatrixType&) has been called before
172 * to compute the tridiagonal decomposition of a matrix
[all...] |
| /external/eigen/Eigen/src/IterativeLinearSolvers/ |
| IncompleteCholesky.h | 75 * You must call compute() or the pair analyzePattern()/factorize() to make it valid.
86 compute(matrix);
99 * or a call to compute() or analyzePattern().
132 * The method analyzePattern() or compute() must have been called beforehand
135 * \sa compute(), analyzePattern()
147 void compute(const MatrixType& mat) function in class:Eigen::IncompleteCholesky
251 // Scale and compute the shift for the matrix
|
| IncompleteLUT.h | 20 * Compute a quick-sort split of a vector
130 compute(mat);
155 * Compute an incomplete LU factorization with dual threshold on the matrix mat
160 IncompleteLUT& compute(const MatrixType& amat) function in class:Eigen::IncompleteLUT
213 * \param fillfactor This is used to compute the number @p fill_in of largest elements to keep on each row.
225 // Compute the Fill-reducing permutation
|
| IterativeSolverBase.h | 174 * by a call to compute().
178 * this class becomes invalid. Call compute() to update it with the new
186 compute(matrix());
213 * this class becomes invalid. Call compute() to update it with the new
234 * this class becomes invalid. Call compute() to update it with the new
238 Derived& compute(const EigenBase<MatrixDerived>& A) function in class:Eigen::IterativeSolverBase
241 m_preconditioner.compute(matrix());
314 * \sa solve(), compute()
|
| /external/eigen/Eigen/src/PaStiXSupport/ |
| PaStiXSupport.h | 223 // Compute the ordering and the symbolic factorization
226 // Compute the numerical factorization
239 void compute(ColSpMatrix& mat);
295 void PastixBase<Derived>::compute(ColSpMatrix& mat) function in class:Eigen::PastixBase
429 compute(matrix);
431 /** Compute the LU supernodal factorization of \p matrix.
436 void compute (const MatrixType& matrix) function in class:Eigen::PastixLU
441 Base::compute(temp);
443 /** Compute the LU symbolic factorization of \p matrix using its sparsity pattern.
456 /** Compute the LU supernodal factorization of \p matri
547 void compute (const MatrixType& matrix) function in class:Eigen::PastixLLT
631 void compute (const MatrixType& matrix) function in class:Eigen::PastixLDLT
[all...] |
| /external/eigen/Eigen/src/QR/ |
| CompleteOrthogonalDecomposition.h | 83 * \c CompleteOrthogonalDecomposition::compute(const* MatrixType&).
100 * matrix \a matrix by calling the method compute(). The default
107 * cod.compute(matrix);
110 * \sa compute()
118 compute(matrix.derived());
184 CompleteOrthogonalDecomposition& compute(const EigenBase<InputType>& matrix) { function in class:Eigen::CompleteOrthogonalDecomposition
185 // Compute the column pivoted QR factorization A P = Q R.
186 m_cpqr.compute(matrix);
273 * \warning: Do not compute \c this->pseudoInverse()*rhs to solve a linear systems.
300 * Most be called before calling compute()
[all...] |
| HouseholderQR.h | 68 * perform decompositions via HouseholderQR::compute(const MatrixType&).
87 * the method compute(). It is a short cut for:
91 * qr.compute(matrix);
94 * \sa compute()
103 compute(matrix.derived());
170 HouseholderQR& compute(const EigenBase<InputType>& matrix) { function in class:Eigen::HouseholderQR
|
| /external/eigen/Eigen/src/SVD/ |
| JacobiSVD.h | 90 m_qr.compute(matrix);
138 m_qr.compute(m_adjoint);
174 m_qr.compute(matrix);
230 m_qr.compute(m_adjoint);
273 m_qr.compute(matrix);
326 m_qr.compute(m_adjoint);
519 * perform decompositions via JacobiSVD::compute(const MatrixType&).
548 compute(matrix, computationOptions);
561 JacobiSVD& compute(const MatrixType& matrix, unsigned int computationOptions);
567 * This method uses the current \a computationOptions, as already passed to the constructor or to compute(const MatrixType&, unsigned int)
569 JacobiSVD& compute(const MatrixType& matrix) function in class:Eigen::JacobiSVD
663 JacobiSVD<MatrixType, QRPreconditioner>::compute(const MatrixType& matrix, unsigned int computationOptions) function in class:Eigen::JacobiSVD
[all...] |
| UpperBidiagonalization.h | 52 * perform decompositions via Bidiagonalization::compute(const MatrixType&).
61 compute(matrix);
64 UpperBidiagonalization& compute(const MatrixType& matrix);
199 // 3 - Compute y_k^T = tau_v * ( A^T*v_k - Y_k-1*V_k-1^T*v_k - U_k-1*X_k-1^T*v_k )
228 // 6 - Compute x_k = tau_u * ( A*u_k - X_k-1*U_k-1^T*u_k - V_k*Y_k^T*u_k )
379 UpperBidiagonalization<_MatrixType>& UpperBidiagonalization<_MatrixType>::compute(const _MatrixType& matrix) function in class:Eigen::internal::UpperBidiagonalization
|
| /external/eigen/unsupported/Eigen/src/Eigenvalues/ |
| ArpackSelfAdjointEigenSolver.h | 67 * perform decompositions via compute().
85 * \param[in] nbrEigenvalues The number of eigenvalues / eigenvectors to compute.
96 * This constructor calls compute(const MatrixType&, const MatrixType&, Index, string, int, RealScalar)
97 * to compute the eigenvalues of the matrix \p A with respect to \p B. The eigenvectors are computed if
111 compute(A, B, nbrEigenvalues, eigs_sigma, options, tol);
119 * \param[in] nbrEigenvalues The number of eigenvalues / eigenvectors to compute.
130 * This constructor calls compute(const MatrixType&, Index, string, int, RealScalar)
131 * to compute the eigenvalues of the matrix \p A. The eigenvectors are computed if
146 compute(A, nbrEigenvalues, eigs_sigma, options, tol);
154 * \param[in] nbrEigenvalues The number of eigenvalues / eigenvectors to compute
335 ::compute(const MatrixType& A, Index nbrEigenvalues, function in class:Eigen::ArpackGeneralizedSelfAdjointEigenSolver
348 ::compute(const MatrixType& A, const MatrixType& B, Index nbrEigenvalues, function in class:Eigen::ArpackGeneralizedSelfAdjointEigenSolver
[all...] |
| /external/eigen/unsupported/Eigen/src/MatrixFunctions/ |
| MatrixLogarithm.h | 35 /** \brief Compute logarithm of 2x2 triangular matrix. */
130 /* \brief Compute Pade approximation to matrix logarithm */
221 /** \brief Compute logarithm of triangular matrices with size > 2.
272 /** \brief Compute matrix logarithm of atomic matrix
276 MatrixType compute(const MatrixType& A);
280 MatrixType MatrixLogarithmAtomic<MatrixType>::compute(const MatrixType& A) function in class:Eigen::internal::MatrixLogarithmAtomic
325 /** \brief Compute the matrix logarithm.
|
| MatrixPower.h | 55 * \brief Compute the matrix power.
61 { m_pow.compute(res, m_p); }
127 * \brief Compute the matrix power.
132 void compute(ResultType& res) const;
144 void MatrixPowerAtomic<MatrixType>::compute(ResultType& res) const function in class:Eigen::MatrixPowerAtomic
329 * Therefore, if you want to compute multiple (>= 2) matrix powers
372 * \brief Compute the matrix power.
379 void compute(ResultType& res, RealScalar p);
450 void MatrixPower<MatrixType>::compute(ResultType& res, RealScalar p) function in class:Eigen::MatrixPower
559 MatrixPowerAtomic<ComplexMatrix>(m_T.topLeftCorner(m_rank, m_rank), p).compute(blockTp)
[all...] |
| /external/guava/guava/src/com/google/common/collect/ |
| ComputingConcurrentHashMap.java | 151 return compute(key, hash, e, computingValueReference);
171 V compute(K key, int hash, ReferenceEntry<K, V> e, method in class:ComputingConcurrentHashMap.ComputingSegment
182 value = computingValueReference.compute(key, hash);
353 V compute(K key, int hash) throws ExecutionException { method in class:ComputingConcurrentHashMap.ComputingValueReference
|
| /frameworks/rs/ |
| rsElement.cpp | 172 void Element::compute() { function in class:android::renderscript::Element
260 e->compute();
341 e->compute();
|
| rsType.cpp | 74 void Type::compute() { function in class:android::renderscript::Type
287 nt->compute();
|
| /hardware/qcom/display/msm8084/liboverlay/ |
| overlayUtils.cpp | 303 static inline int compute(const uint32_t& x, const uint32_t& y, function in namespace:overlay::utils
310 srcCrop.x = compute(whf.w, srcCrop.x, srcCrop.w);
313 srcCrop.y = compute(whf.h, srcCrop.y, srcCrop.h);
317 srcCrop.x = compute(whf.h,
|
| /hardware/qcom/display/msm8960/liboverlay/ |
| overlayUtils.cpp | 223 static inline int compute(const uint32_t& x, const uint32_t& y, function in namespace:overlay::utils
233 srcCrop.x = compute(whf.w, srcCrop.x, srcCrop.w);
236 srcCrop.y = compute(whf.h, srcCrop.y, srcCrop.h);
240 srcCrop.x = compute(whf.h,
|
| /libcore/ojluni/src/main/java/java/util/ |
| ArrayPrefixHelpers.java | 74 * main phase bit. When false, segments compute only their sum.
87 * To better exploit locality and reduce overhead, the compute
136 public final void compute() { method in class:ArrayPrefixHelpers.CumulateTask
288 public final void compute() { method in class:ArrayPrefixHelpers.LongCumulateTask
438 public final void compute() { method in class:ArrayPrefixHelpers.DoubleCumulateTask
588 public final void compute() { method in class:ArrayPrefixHelpers.IntCumulateTask
[all...] |
| /libcore/ojluni/src/main/java/java/util/concurrent/ |
| CountedCompleter.java | 71 * #compute}, that should in most cases (as illustrated below), invoke
99 * exceptional completion of method {@code compute}. Upon any
150 * public void compute() { // version 1
173 * public void compute() { // version 2
178 * new ForEach(this, array, op, lo, mid).compute(); // direct invoke
197 * public void compute() { // version 3
237 * public void compute() { // similar to ForEach version 3
295 * public void compute() {
304 * left.compute(); // directly execute left
367 * public void compute() {
454 public abstract void compute(); method in class:CountedCompleter
732 compute(); method
[all...] |
| /libcore/ojluni/src/main/java/java/util/stream/ |
| AbstractTask.java | 48 * <p>Splitting and setting up the child task links is done by {@code compute()}
49 * for internal nodes. At {@code compute()} time for leaf nodes, it is
172 * {@code compute()} and the result passed to @{code setLocalResult()}
248 * {@link #compute} has been called on this node). If the node is not a
278 * Decides whether or not to split a task further or compute it
291 public void compute() { method in class:AbstractTask
|
| ForEachOps.java | 279 public void compute() { method in class:ForEachOps.ForEachTask
399 public final void compute() { method in class:ForEachOps.ForEachOrderedTask
|
