| /external/eigen/Eigen/src/Eigenvalues/ |
| D | GeneralizedSelfAdjointEigenSolver.h | 106 GeneralizedSelfAdjointEigenSolver(const MatrixType& matA, const MatrixType& matB,
108 : Base(matA.cols())
110 compute(matA, matB, options);
153 GeneralizedSelfAdjointEigenSolver& compute(const MatrixType& matA, const MatrixType& matB,
163 compute(const MatrixType& matA, const MatrixType& matB, int options) in compute() argument
165 eigen_assert(matA.cols()==matA.rows() && matB.rows()==matA.rows() && matB.cols()==matB.rows()); in compute()
184 MatrixType matC = matA.template selfadjointView<Lower>(); in compute()
197 MatrixType matC = matA.template selfadjointView<Lower>(); in compute()
210 MatrixType matC = matA.template selfadjointView<Lower>(); in compute()
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| D | HessenbergDecomposition.h | 272 static void _compute(MatrixType& matA, CoeffVectorType& hCoeffs, VectorType& temp);
294 void HessenbergDecomposition<MatrixType>::_compute(MatrixType& matA, CoeffVectorType& hCoeffs, Vect…
296 eigen_assert(matA.rows()==matA.cols());
297 Index n = matA.rows();
305 matA.col(i).tail(remainingSize).makeHouseholderInPlace(h, beta);
306 matA.col(i).coeffRef(i+1) = beta;
313 matA.bottomRightCorner(remainingSize, remainingSize)
314 .applyHouseholderOnTheLeft(matA.col(i).tail(remainingSize-1), h, &temp.coeffRef(0));
317 matA.rightCols(remainingSize)
318 ….applyHouseholderOnTheRight(matA.col(i).tail(remainingSize-1).conjugate(), numext::conj(h), &temp.…
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| D | Tridiagonalization.h | 28 void tridiagonalization_inplace(MatrixType& matA, CoeffVectorType& hCoeffs);
347 void tridiagonalization_inplace(MatrixType& matA, CoeffVectorType& hCoeffs)
352 Index n = matA.rows();
353 eigen_assert(n==matA.cols());
361 matA.col(i).tail(remainingSize).makeHouseholderInPlace(h, beta);
365 matA.col(i).coeffRef(i+1) = 1;
367 …hCoeffs.tail(n-i-1).noalias() = (matA.bottomRightCorner(remainingSize,remainingSize).template self…
368 * (conj(h) * matA.col(i).tail(remainingSize)));
370 …nj(h)*RealScalar(-0.5)*(hCoeffs.tail(remainingSize).dot(matA.col(i).tail(remainingSize)))) * matA.…
372 matA.bottomRightCorner(remainingSize, remainingSize).template selfadjointView<Lower>()
[all …]
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| /external/eigen/doc/snippets/ |
| D | TopicAliasing_mult1.cpp | 1 MatrixXf matA(2,2); variable
2 matA << 2, 0, 0, 2;
3 matA = matA * matA;
4 cout << matA;
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| D | TopicAliasing_mult3.cpp | 1 MatrixXf matA(2,2); variable
2 matA << 2, 0, 0, 2;
3 matA.noalias() = matA * matA;
4 cout << matA;
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| D | Tutorial_AdvancedInitialization_Block.cpp | 1 MatrixXf matA(2, 2); variable
2 matA << 1, 2, 3, 4;
4 matB << matA, matA/10, matA/10, matA;
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| D | TopicAliasing_mult2.cpp | 1 MatrixXf matA(2,2), matB(2,2); variable
2 matA << 2, 0, 0, 2;
5 matB = matA * matA;
9 matB.noalias() = matA * matA;
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| /external/eigen/doc/ |
| D | TopicAliasing.dox | 158 Thus, if \c matA is a \b squared matrix, then the statement <tt>matA = matA * matA;</tt> is safe.
171 However, this comes at a price. When executing the expression <tt>matA = matA * matA</tt>, %Eigen e…
172 product in a temporary matrix which is assigned to \c matA after the computation. This is fine. But…
173 the same when the product is assigned to a different matrix (e.g., <tt>matB = matA * matA</tt>). In…
178 aliasing, as follows: <tt>matB.noalias() = matA * matA</tt>. This allows %Eigen to evaluate the mat…
179 <tt>matA * matA</tt> directly into \c matB.
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| /external/neven/Embedded/common/src/b_TensorEm/ |
| D | Int32Mat.h | 115 const int32* matA,
129 int32* matA,
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| D | Int32Mat.c | 210 const int32* matA, in bts_Int32Mat_solve() argument
218 bbs_memcpy32( tmpMatA, matA, ( matWidthA * matWidthA ) * bbs_SIZEOF32( int32 ) ); in bts_Int32Mat_solve()
232 int32* matA, in bts_Int32Mat_solve2() argument
246 int32* matL = matA; in bts_Int32Mat_solve2()
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| /external/skia/src/effects/ |
| D | SkColorMatrix.cpp | 132 void SkColorMatrix::setConcat(const SkColorMatrix& matA, const SkColorMatrix& matB) { in setConcat() argument
133 SetConcat(fMat, matA.fMat, matB.fMat); in setConcat()
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| /external/eigen/test/ |
| D | cholesky.cpp | 353 MatrixType matA; in cholesky_bug241() local
354 matA << 1, 1, 1, 1; in cholesky_bug241()
357 VectorType vecX = matA.ldlt().solve(vecB); in cholesky_bug241()
358 VERIFY_IS_APPROX(matA * vecX, vecB); in cholesky_bug241()
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| /external/eigen/blas/ |
| D | level3_impl.h | 322 Matrix<Scalar,Dynamic,Dynamic,ColMajor> matA(size,size); in EIGEN_BLAS_FUNC()
325 matA.triangularView<Upper>() = matrix(a,size,size,*lda); in EIGEN_BLAS_FUNC()
326 matA.triangularView<Lower>() = matrix(a,size,size,*lda).transpose(); in EIGEN_BLAS_FUNC()
330 matA.triangularView<Lower>() = matrix(a,size,size,*lda); in EIGEN_BLAS_FUNC()
331 matA.triangularView<Upper>() = matrix(a,size,size,*lda).transpose(); in EIGEN_BLAS_FUNC()
334 matrix(c, *m, *n, *ldc) += alpha * matA * matrix(b, *m, *n, *ldb); in EIGEN_BLAS_FUNC()
336 matrix(c, *m, *n, *ldc) += alpha * matrix(b, *m, *n, *ldb) * matA; in EIGEN_BLAS_FUNC()
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