| /external/eigen/unsupported/test/ |
| minres.cpp | 21 // Diagonal preconditioner
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| /external/eigen/unsupported/Eigen/src/Polynomials/ |
| Companion.h | 225 //First row, first column excluding the diagonal
237 //Middle rows and columns excluding the diagonal
241 // column norm, excluding the diagonal
244 // row norm, excluding the diagonal
256 //Last row, last column excluding the diagonal
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| /external/eigen/Eigen/src/Cholesky/ |
| LDLT.h | 37 * is lower triangular with a unit diagonal and D is a diagonal matrix.
162 /** \returns the coefficients of the diagonal matrix D */
163 inline Diagonal<const MatrixType> vectorD() const
166 return m_matrix.diagonal();
275 * part correspond to the coefficients of L (its diagonal is equal to 1 and
276 * is not stored), and the diagonal entries correspond to D.
316 // Find largest diagonal element
318 mat.diagonal().tail(size-k).cwiseAbs().maxCoeff(&index_of_biggest_in_corner);
351 temp.head(k) = mat.diagonal().real().head(k).asDiagonal() * A10.adjoint()
[all...] |
| /external/apache-commons-math/src/main/java/org/apache/commons/math/linear/ |
| MatrixUtils.java | 195 * Returns a diagonal matrix with specified elements.
197 * @param diagonal diagonal elements of the matrix (the array elements
199 * @return diagonal matrix
202 public static RealMatrix createRealDiagonalMatrix(final double[] diagonal) {
203 final RealMatrix m = createRealMatrix(diagonal.length, diagonal.length);
204 for (int i = 0; i < diagonal.length; ++i) {
205 m.setEntry(i, i, diagonal[i]);
211 * Returns a diagonal matrix with specified elements
[all...] |
| CholeskyDecompositionImpl.java | 38 /** Default threshold above which off-diagonal elements are considered too different
42 /** Default threshold below which diagonal elements are considered null
83 * @param relativeSymmetryThreshold threshold above which off-diagonal
85 * @param absolutePositivityThreshold threshold below which diagonal
116 // check off-diagonal elements (and reset them to 0)
135 // check diagonal element
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| QRDecompositionImpl.java | 47 * <p>The elements BELOW the diagonal are the elements of the UPPER triangular
48 * matrix R, and the rows ABOVE the diagonal are the Householder reflector vectors
53 /** The diagonal elements of R. */
158 // copy the diagonal from rDiag and the upper triangle of qr
256 * <p>The elements BELOW the diagonal are the elements of the UPPER triangular
257 * matrix R, and the rows ABOVE the diagonal are the Householder reflector vectors
262 /** The diagonal elements of R. */
268 * @param rDiag diagonal elements of R
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| EigenDecomposition.java | 58 * Returns the block diagonal matrix D of the decomposition.
59 * <p>D is a block diagonal matrix.</p>
60 * <p>Real eigenvalues are on the diagonal while complex values are on
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| /external/eigen/test/ |
| sparse_basic.cpp | 499 // test diagonal
504 VERIFY_IS_APPROX(m2.diagonal(), refMat2.diagonal().eval());
505 DenseVector d = m2.diagonal();
506 VERIFY_IS_APPROX(d, refMat2.diagonal().eval());
507 d = m2.diagonal().array();
508 VERIFY_IS_APPROX(d, refMat2.diagonal().eval());
509 VERIFY_IS_APPROX(const_cast<const SparseMatrixType&>(m2).diagonal(), refMat2.diagonal().eval());
512 m2.diagonal() += refMat2.diagonal()
[all...] |
| product_mmtr.cpp | 23 ref3.diagonal() = DEST.diagonal(); \
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| miscmatrices.cpp | 34 square.diagonal() = VectorType::Ones(rows);
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| geo_alignedbox.cpp | 127 VERIFY_IS_APPROX( 53.0f, box.diagonal().squaredNorm() );
128 VERIFY_IS_APPROX( std::sqrt( 53.0f ), box.diagonal().norm() );
154 VERIFY_IS_APPROX( 62, box.diagonal().squaredNorm() );
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| evaluators.cpp | 373 // test Diagonal
374 VERIFY_IS_APPROX_EVALUATOR(vec1, mat1.diagonal());
376 VERIFY_IS_APPROX_EVALUATOR(vec1, mat1.diagonal(1));
377 VERIFY_IS_APPROX_EVALUATOR(vec1, mat1.diagonal<-1>());
381 copy_using_evaluator(mat1.diagonal(1), vec1);
382 mat2.diagonal(1) = vec1;
385 copy_using_evaluator(mat1.diagonal<-1>(), mat1.diagonal(1));
386 mat2.diagonal<-1>() = mat2.diagonal(1)
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| /external/eigen/bench/ |
| eig33.cpp | 94 scaledMat.diagonal().array() -= shift;
123 // tmp.diagonal().array() -= evals(0);
127 // tmp.diagonal().array() -= evals(1);
131 // tmp.diagonal().array() -= evals(2);
143 tmp.diagonal ().array () -= evals (2);
147 tmp.diagonal ().array () -= evals (1);
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| /external/eigen/Eigen/src/Core/products/ |
| TriangularMatrixMatrix.h | 143 triangularBuffer.diagonal().setZero();
145 triangularBuffer.diagonal().setOnes();
169 // 2 - the diagonal block => special kernel
170 // 3 - the dense panel below (lower case) or above (upper case) the diagonal block => GEPP
172 // the block diagonal, if any:
212 // the part below (lower case) or above (upper case) the diagonal => GEPP
290 triangularBuffer.diagonal().setZero();
292 triangularBuffer.diagonal().setOnes();
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| /external/eigen/Eigen/src/Eigenvalues/ |
| GeneralizedEigenSolver.h | 32 * \f$ D \f$ is a diagonal matrix with the eigenvalues on the diagonal, and
324 m_alphas.coeffRef(i) = mS.diagonal().coeff(i);
325 m_betas.coeffRef(i) = mT.diagonal().coeff(i);
362 // We need to extract the generalized eigenvalues of the pair of a general 2x2 block S and a positive diagonal 2x2 block T
367 RealScalar a = mT.diagonal().coeff(i),
368 b = mT.diagonal().coeff(i+1);
371 // ^^ NOTE: using diagonal()(i) instead of coeff(i,i) workarounds a MSVC bug.
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| ComplexEigenSolver.h | 32 * \f$. If \f$ D \f$ is a diagonal matrix with the eigenvalues on
33 * the diagonal, and \f$ V \f$ is a matrix with the eigenvectors as
269 // The eigenvalues are on the diagonal of T.
274 m_eivalues = m_schur.matrixT().diagonal();
293 // Compute X such that T = X D X^(-1), where D is the diagonal of T.
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| /external/bison/lib/ |
| bitsetv.h | 50 the same as transitive closure but with all bits on the diagonal
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| /external/eigen/Eigen/ |
| IterativeLinearSolvers | 27 * - DiagonalPreconditioner - also called Jacobi preconditioner, work very well on diagonal dominant matrices.
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| /external/libopus/silk/fixed/ |
| regularize_correlations_FIX.c | 34 /* Add noise to matrix diagonal */
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| /external/libopus/silk/float/ |
| regularize_correlations_FLP.c | 34 /* Add noise to matrix diagonal */
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| /external/eigen/Eigen/src/SparseCore/ |
| SparseDiagonalProduct.h | 15 // The product of a diagonal matrix with a sparse matrix can be easily
45 explicit product_evaluator(const XprType& xpr) : Base(xpr.rhs(), xpr.lhs().diagonal()) {}
56 explicit product_evaluator(const XprType& xpr) : Base(xpr.lhs(), xpr.rhs().diagonal().transpose()) {}
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| /external/eigen/unsupported/Eigen/src/IterativeSolvers/ |
| Scaling.h | 67 * Compute the left and right diagonal matrices to scale the input matrix @p mat
69 * FIXME This algorithm will be modified such that the diagonal elements are permuted on the diagonal.
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| /sdk/files/ |
| devices.xml | 12 <d:diagonal-length>3.7</d:diagonal-length>
87 <d:diagonal-length>4</d:diagonal-length>
200 <d:diagonal-length>4.65</d:diagonal-length> <!-- In inches -->
331 <d:diagonal-length>7.27</d:diagonal-length>
410 <d:diagonal-length>4.7</d:diagonal-length
[all...] |
| /external/eigen/Eigen/src/Core/ |
| SelfAdjointView.h | 222 /** \returns a const expression of the main diagonal of the matrix \c *this
224 * This method simply returns the diagonal of the nested expression, thus by-passing the SelfAdjointView decorator.
226 * \sa MatrixBase::diagonal(), class Diagonal */
228 typename MatrixType::ConstDiagonalReturnType diagonal() const function in class:Eigen::SelfAdjointView
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| /external/gemmlowp/internal/ |
| kernel.h | 73 // There is also a third possibility, "diagonal order",
123 enum class CellOrder { DepthMajor, WidthMajor, Diagonal };
175 case CellOrder::Diagonal:
176 return "Diagonal";
191 case CellOrder::Diagonal:
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