| /external/eigen/Eigen/src/Eigenvalues/ |
| ComplexSchur.h | 28 * \brief Performs a complex Schur decomposition of a real or complex square matrix
30 * \tparam _MatrixType the type of the matrix of which we are
32 * instantiation of the Matrix class template.
34 * Given a real or complex square matrix A, this class computes the
36 * complex matrix, and T is a complex upper triangular matrix. The
37 * diagonal of the matrix T corresponds to the eigenvalues of the
38 * matrix A.
41 * a given matrix. Alternatively, you can use the
78 * This is a square matrix with entries of type #ComplexScalar.
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| Tridiagonalization.h | 36 * \brief Tridiagonal decomposition of a selfadjoint matrix
38 * \tparam _MatrixType the type of the matrix of which we are computing the
40 * Matrix class template.
42 * This class performs a tridiagonal decomposition of a selfadjoint matrix \f$ A \f$ such that:
43 * \f$ A = Q T Q^* \f$ where \f$ Q \f$ is unitary and \f$ T \f$ a real symmetric tridiagonal matrix.
45 * A tridiagonal matrix is a matrix which has nonzero elements only on the
47 * decomposition of a selfadjoint matrix is in fact a tridiagonal
49 * eigenvalues and eigenvectors of a selfadjoint matrix.
52 * given matrix. Alternatively, you can use the Tridiagonalization(const MatrixType&
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| EigenSolver.h | 25 * \tparam _MatrixType the type of the matrix of which we are computing the
26 * eigendecomposition; this is expected to be an instantiation of the Matrix
29 * The eigenvalues and eigenvectors of a matrix \f$ A \f$ are scalars
31 * \f$ D \f$ is a diagonal matrix with the eigenvalues on the diagonal, and
32 * \f$ V \f$ is a matrix with the eigenvectors as its columns, then \f$ A V =
33 * V D \f$. The matrix \f$ V \f$ is almost always invertible, in which case we
36 * The eigenvalues and eigenvectors of a matrix may be complex, even when the
37 * matrix is real. However, we can choose real matrices \f$ V \f$ and \f$ D
39 * matrix \f$ D \f$ is not required to be diagonal, but if it is allowed to
47 * a given matrix. Alternatively, you can use the
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| /external/eigen/bench/ |
| quat_slerp.cpp | 157 Matrix<RefScalar,Dynamic,1> maxerr(7);
160 Matrix<RefScalar,Dynamic,1> avgerr(7);
|
| /external/eigen/unsupported/Eigen/src/KroneckerProduct/ |
| KroneckerTensorProduct.h | 78 * \tparam Lhs Type of the left-hand side, a matrix expression.
79 * \tparam Rhs Type of the rignt-hand side, a matrix expression.
104 * If at least one of the operands is a sparse matrix expression,
105 * then this class is returned and evaluates into a sparse matrix.
111 * \tparam Lhs Type of the left-hand side, a matrix expression.
112 * \tparam Rhs Type of the rignt-hand side, a matrix expression.
178 Matrix<int,Dynamic,Dynamic,ColMajor> nnzAB = nnzB * nnzA.transpose();
216 typedef Matrix<Scalar,Rows,Cols> ReturnType;
256 * \warning If you want to replace a matrix by its Kronecker product
257 * with some matrix, do \b NOT do this
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| /external/eigen/unsupported/test/ |
| kronecker_product.cpp | 88 // DM = dense matrix; SM = sparse matrix
90 Matrix<double, 2, 3> DM_a;
111 Matrix<double, 6, 6> DM_fix_ab = kroneckerProduct(DM_a.topLeftCorner<2,3>(),DM_b);
|
| /frameworks/base/media/mca/filterpacks/java/android/filterpacks/videosrc/ |
| CameraSource.java | 32 import android.opengl.Matrix;
188 Matrix.multiplyMM(mMappedCoords, 0,
|
| /frameworks/layoutlib/bridge/src/android/view/ |
| RenderNode_Delegate.java | 22 import android.graphics.Matrix;
172 /*package*/ static void getMatrix(RenderNode renderNode, Matrix outMatrix) {
|
| /frameworks/support/v17/leanback/src/android/support/v17/leanback/widget/ |
| DetailsOverviewSharedElementHelper.java | 17 import android.graphics.Matrix;
69 private Matrix mSavedMatrix;
80 mSavedMatrix = mSavedScaleType == ScaleType.MATRIX ? imageView.getMatrix() : null;
88 // enforcing imageView to update its internal bounds/matrix immediately
103 if (snapshotImageView.getScaleType() == ScaleType.MATRIX) {
116 if (mSavedScaleType == ScaleType.MATRIX) {
|
| /external/eigen/unsupported/Eigen/src/SparseExtra/ |
| BlockSparseMatrix.h | 19 * \brief A versatile sparse matrix representation where each element is a block
30 * Here, bmat is a b_rows x b_cols block sparse matrix
31 * where each coefficient is a 3x3 dense matrix.
41 * It is thus required in this case to describe the layout of the matrix by calling
44 * In any of the previous case, the matrix can be filled by calling setFromTriplets().
45 * A regular sparse matrix can be converted to a block sparse matrix and vice versa.
80 typedef Ref<Matrix<typename BlockSparseMatrixT::Scalar, BlockSparseMatrixT::BlockSize, BlockSparseMatrixT::BlockSize> > Scalar;
81 typedef Ref<Matrix<typename BlockSparseMatrixT::RealScalar, BlockSparseMatrixT::BlockSize, BlockSparseMatrixT::BlockSize> > RealScalar;
100 /* Proxy to view the block sparse matrix as a regular sparse matrix *
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| /frameworks/base/graphics/java/android/graphics/drawable/ |
| BitmapDrawable.java | 31 import android.graphics.Matrix;
104 // Mirroring matrix for using with Shaders
105 private Matrix mMirrorMatrix;
549 * Updates the {@code paint}'s shader matrix to be consistent with the
563 final Matrix matrix = getOrCreateMirrorMatrix(); local
564 matrix.reset();
568 matrix.setTranslate(dx, 0);
569 matrix.setScale(-1, 1);
574 matrix.postScale(densityScale, densityScale)
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| RippleDrawable.java | 35 import android.graphics.Matrix;
134 private Matrix mMaskMatrix;
785 mMaskMatrix = new Matrix();
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| /packages/apps/Messaging/src/com/android/messaging/util/ |
| ImageUtils.java | 26 import android.graphics.Matrix;
136 final Matrix matrix = new Matrix(); local
139 matrix.setRectToRect(source, dest, Matrix.ScaleToFit.CENTER);
141 shader.setLocalMatrix(matrix);
397 // Matrix to undo orientation and scale at the same time
398 private final Matrix mMatrix;
445 mMatrix = new Matrix();
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| /external/eigen/Eigen/src/SVD/ |
| JacobiSVD.h | 25 *** Their role is to reduce the problem of computing the SVD to the case of a square matrix.
74 typedef Matrix<Scalar, 1, RowsAtCompileTime, RowMajor, 1, MaxRowsAtCompileTime> WorkspaceType;
86 bool run(JacobiSVD<MatrixType, FullPivHouseholderQRPreconditioner>& svd, const MatrixType& matrix)
88 if(matrix.rows() > matrix.cols())
90 m_qr.compute(matrix);
91 svd.m_workMatrix = m_qr.matrixQR().block(0,0,matrix.cols(),matrix.cols()).template triangularView<Upper>();
119 typedef Matrix<Scalar, ColsAtCompileTime, RowsAtCompileTime, TrOptions, MaxColsAtCompileTime, MaxRowsAtCompileTime>
133 bool run(JacobiSVD<MatrixType, FullPivHouseholderQRPreconditioner>& svd, const MatrixType& matrix)
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| /external/eigen/test/ |
| sparse_product.cpp | 41 typedef Matrix<Scalar,Dynamic,Dynamic> DenseMatrix;
42 typedef Matrix<Scalar,Dynamic,1> DenseVector;
43 typedef Matrix<Scalar,1,Dynamic> RowDenseVector;
50 // test matrix-matrix product
134 // sparse * dense matrix
209 // sparse matrix * sparse vector
225 // test matrix - diagonal product
255 // evaluate to a dense matrix to check the .row() and .col() iterator functions
354 typedef Matrix<Scalar, Dynamic, 1> Vector
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| sparse_block.cpp | 37 typedef Matrix<Scalar,Dynamic,Dynamic,SparseMatrixType::IsRowMajor?RowMajor:ColMajor> DenseMatrix;
38 typedef Matrix<Scalar,Dynamic,1> DenseVector;
39 typedef Matrix<Scalar,1,Dynamic> RowDenseVector;
|
| /frameworks/ex/camera2/portability/src/com/android/ex/camera2/portability/ |
| AndroidCamera2AgentImpl.java | 22 import android.graphics.Matrix;
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| /packages/apps/Gallery/src/com/android/camera/ |
| CropImage.java | 30 import android.graphics.Matrix;
289 croppedImage = Util.transform(new Matrix(), croppedImage,
419 Matrix mImageMatrix;
508 Matrix matrix = new Matrix();
509 matrix.setScale(mScale, mScale);
511 .getWidth(), mBitmap.getHeight(), matrix, true);
|
| /cts/apps/CtsVerifier/src/com/android/cts/verifier/camera/video/ |
| CameraVideoActivity.java | 20 import android.graphics.Matrix;
698 Matrix transform = new Matrix();
|
| /external/eigen/Eigen/src/LU/ |
| FullPivLU.h | 30 * \brief LU decomposition of a matrix with complete pivoting, and related features
32 * \tparam _MatrixType the type of the matrix of which we are computing the LU decomposition
34 * This class represents a LU decomposition of any matrix, with complete pivoting: the matrix A is
44 * decomposition is inherently more stable and/or flexible. For example, when computing the kernel of a matrix,
45 * working with the SVD allows to select the smallest singular values of the matrix, something that
51 * As an exemple, here is how the original matrix can be retrieved:
96 * \param matrix the matrix of which to compute the LU decomposition.
100 explicit FullPivLU(const EigenBase<InputType>& matrix);
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| /external/eigen/Eigen/src/PaStiXSupport/ |
| PaStiXSupport.h | 27 * The matrix can be either real or complex, symmetric or not.
95 // Convert the matrix to Fortran-style Numbering
142 typedef Matrix<Scalar,Dynamic,1> Vector;
208 * \c InvalidInput if the input matrix is invalid
220 // Initialize the Pastix data structure, check the matrix
249 mutable Matrix<StorageIndex,Dynamic,1> m_perm; // Permutation vector
250 mutable Matrix<StorageIndex,Dynamic,1> m_invp; // Inverse permutation vector
251 mutable int m_size; // Size of the matrix
297 eigen_assert(mat.rows() == mat.cols() && "The input matrix should be squared");
369 eigen_assert(m_isInitialized && "The matrix should be factorized first")
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| /external/eigen/Eigen/src/QR/ |
| FullPivHouseholderQR.h | 38 * \brief Householder rank-revealing QR decomposition of a matrix with full pivoting
40 * \tparam _MatrixType the type of the matrix of which we are computing the QR decomposition
42 * This class performs a rank-revealing QR decomposition of a matrix \b A into matrices \b P, \b P', \b Q and \b R
47 * by using Householder transformations. Here, \b P and \b P' are permutation matrices, \b Q a unitary matrix
48 * and \b R an upper triangular matrix.
74 typedef Matrix<StorageIndex, 1,
113 /** \brief Constructs a QR factorization from a given matrix
115 * This constructor computes the QR factorization of the matrix \a matrix by calling
119 * FullPivHouseholderQR<MatrixType> qr(matrix.rows(), matrix.cols())
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| /external/eigen/Eigen/src/SparseQR/ |
| SparseQR.h | 54 * Q is the orthogonal matrix represented as products of Householder reflectors.
58 * R is the sparse triangular or trapezoidal matrix. The later occurs when A is rank-deficient.
61 * \tparam _MatrixType The type of the sparse matrix A, must be a column-major SparseMatrix<>
67 * \warning The input sparse matrix A must be in compressed mode (see SparseMatrix::makeCompressed()).
84 typedef Matrix<StorageIndex, Dynamic, 1> IndexVector;
85 typedef Matrix<Scalar, Dynamic, 1> ScalarVector;
97 /** Construct a QR factorization of the matrix \a mat.
99 * \warning The matrix \a mat must be in compressed mode (see SparseMatrix::makeCompressed()).
108 /** Computes the QR factorization of the sparse matrix \a mat.
110 * \warning The matrix \a mat must be in compressed mode (see SparseMatrix::makeCompressed())
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| /external/eigen/unsupported/Eigen/src/NonLinearOptimization/ |
| HybridNonLinearSolver.h | 66 typedef Matrix< Scalar, Dynamic, 1 > FVectorType;
67 typedef Matrix< Scalar, Dynamic, Dynamic > JacobianType;
69 typedef Matrix< Scalar, Dynamic, Dynamic > UpperTriangularType;
197 /* calculate the jacobian matrix. */
440 /* calculate the jacobian matrix. */
|
| /external/llvm/include/llvm/CodeGen/PBQP/ |
| Graph.h | 55 typedef typename SolverT::Matrix Matrix;
413 /// @param Costs Cost matrix for new edge.
419 "Matrix dimensions mismatch.");
420 // Get cost matrix from the problem domain.
431 /// @param Costs Cost matrix for new edge.
445 "Matrix dimensions mismatch.");
446 // Get cost matrix from the problem domain.
511 /// @brief Update an edge's cost matrix.
513 /// @param Costs New cost matrix
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