| /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 | 34 * \brief Tridiagonal decomposition of a selfadjoint matrix
36 * \tparam _MatrixType the type of the matrix of which we are computing the
38 * Matrix class template.
40 * This class performs a tridiagonal decomposition of a selfadjoint matrix \f$ A \f$ such that:
41 * \f$ A = Q T Q^* \f$ where \f$ Q \f$ is unitary and \f$ T \f$ a real symmetric tridiagonal matrix.
43 * A tridiagonal matrix is a matrix which has nonzero elements only on the
45 * decomposition of a selfadjoint matrix is in fact a tridiagonal
47 * eigenvalues and eigenvectors of a selfadjoint matrix.
50 * 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/Eigen/src/SparseCore/ |
| ConservativeSparseSparseProduct.h | 29 Matrix<Scalar,Dynamic,1> values(rows);
30 Matrix<Index,Dynamic,1> indices(rows);
|
| SparseMatrix.h | 19 * \brief A versatible sparse matrix representation
27 * A call to the function makeCompressed() turns the matrix into the standard \em compressed format
110 Eigen::Map<Matrix<Index,Dynamic,1> > innerNonZeros() { return Eigen::Map<Matrix<Index,Dynamic,1> >(m_innerNonZeros, m_innerNonZeros?m_outerSize:0); }
111 const Eigen::Map<const Matrix<Index,Dynamic,1> > innerNonZeros() const { return Eigen::Map<const Matrix<Index,Dynamic,1> >(m_innerNonZeros, m_innerNonZeros?m_outerSize:0); }
118 /** \returns the number of rows of the matrix */
120 /** \returns the number of columns of the matrix */
123 /** \returns the number of rows (resp. columns) of the matrix if the storage order column major (resp. row major) */
125 /** \returns the number of columns (resp. rows) of the matrix if the storage order column major (resp. row major) *
[all...] |
| /external/eigen/bench/ |
| quat_slerp.cpp | 157 Matrix<RefScalar,Dynamic,1> maxerr(7);
160 Matrix<RefScalar,Dynamic,1> avgerr(7);
|
| /external/eigen/test/eigen2/ |
| eigen2_sparse_basic.cpp | 54 typedef Matrix<Scalar,Dynamic,Dynamic> DenseMatrix;
55 typedef Matrix<Scalar,Dynamic,1> DenseVector;
|
| eigen2_geometry.cpp | 21 typedef Matrix<Scalar,2,2> Matrix2;
22 typedef Matrix<Scalar,3,3> Matrix3;
23 typedef Matrix<Scalar,4,4> Matrix4;
24 typedef Matrix<Scalar,2,1> Vector2;
25 typedef Matrix<Scalar,3,1> Vector3;
26 typedef Matrix<Scalar,4,1> Vector4;
90 // rotation matrix conversion
141 VERIFY_IS_APPROX(t0.matrix(), Transform3::MatrixType::Identity());
142 t0.matrix().setZero();
144 VERIFY_IS_APPROX(t0.matrix(), Transform3::MatrixType::Identity())
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| eigen2_geometry_with_eigen2_prefix.cpp | 23 typedef Matrix<Scalar,2,2> Matrix2;
24 typedef Matrix<Scalar,3,3> Matrix3;
25 typedef Matrix<Scalar,4,4> Matrix4;
26 typedef Matrix<Scalar,2,1> Vector2;
27 typedef Matrix<Scalar,3,1> Vector3;
28 typedef Matrix<Scalar,4,1> Vector4;
92 // rotation matrix conversion
143 VERIFY_IS_APPROX(t0.matrix(), Transform3::MatrixType::Identity());
144 t0.matrix().setZero();
146 VERIFY_IS_APPROX(t0.matrix(), Transform3::MatrixType::Identity())
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| /external/eigen/test/ |
| sparse_permutations.cpp | 21 typedef Matrix<Scalar,Dynamic,Dynamic> DenseMatrix;
22 typedef Matrix<Index,Dynamic,1> VectorI;
|
| main.h | 305 /** Creates a random Partial Isometry matrix of given rank.
307 * A partial isometry is a matrix all of whose singular values are either 0 or 1.
317 typedef Matrix<Scalar, Dynamic, 1> VectorType;
318 typedef Matrix<Scalar, Rows, Rows> MatrixAType;
319 typedef Matrix<Scalar, Cols, Cols> MatrixBType;
|
| /frameworks/base/media/mca/filterpacks/java/android/filterpacks/videosrc/ |
| CameraSource.java | 38 import android.opengl.Matrix;
195 Matrix.multiplyMM(mMappedCoords, 0,
|
| /external/ceres-solver/internal/ceres/ |
| schur_eliminator_impl.h | 37 // Eigen has an internal threshold switching between different matrix
40 // matrix matrix product algorithm that has a higher setup cost. For
41 // matrix sizes close to this threshold, especially when the matrices
104 // matrix should already have been ordered so that all rows
200 += diag.array().square().matrix();
208 // Gaussian elimination to them. The matrix ete stores the normal
209 // matrix corresponding to the block being eliminated and array
233 typename EigenTypes<kEBlockSize, kEBlockSize>::Matrix
239 ete = diag.array().square().matrix().asDiagonal()
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| /external/eigen/Eigen/src/Eigen2Support/Geometry/ |
| Transform.h | 34 * The homography is internally represented and stored as a (Dim+1)^2 matrix which
35 * is available through the matrix() method.
40 * \sa class Matrix, class Quaternion
53 /** type of the matrix used to represent the transformation */
54 typedef Matrix<Scalar,HDim,HDim> MatrixType;
55 /** type of the matrix used to represent the linear part of the transformation */
56 typedef Matrix<Scalar,Dim,Dim> LinearMatrixType;
62 typedef Matrix<Scalar,Dim,1> VectorType;
99 transform->matrix() = other;
109 transform->matrix()(Dim,Dim) = Scalar(1)
143 inline const MatrixType& matrix() const { return m_matrix; } function in class:Eigen::Transform
145 inline MatrixType& matrix() { return m_matrix; } function in class:Eigen::Transform
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| /external/eigen/Eigen/src/SparseCholesky/ |
| SimplicialCholesky.h | 68 * such that the factorized matrix is P A P^-1.
70 * \tparam _MatrixType the type of the sparse matrix A, it must be a SparseMatrix<>
85 typedef Matrix<Scalar,Dynamic,1> VectorType;
94 SimplicialCholeskyBase(const MatrixType& matrix)
97 derived().compute(matrix);
113 * \c NumericalIssue if the matrix.appears to be negative.
131 && "SimplicialCholeskyBase::solve(): invalid number of rows of the right hand side matrix b");
145 && "SimplicialCholesky::solve(): invalid number of rows of the right hand side matrix b");
225 // we process the sparse rhs per block of NbColsAtOnce columns temporarily stored into a dense matrix.
229 Eigen::Matrix<DestScalar,Dynamic,Dynamic> tmp(size,rhsCols)
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| /frameworks/base/core/java/com/android/internal/widget/ |
| LockPatternView.java | 26 import android.graphics.Matrix;
128 private final Matrix mArrowMatrix = new Matrix();
129 private final Matrix mCircleMatrix = new Matrix();
132 * Represents a cell in the 3 X 3 matrix of the unlock pattern view.
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| /frameworks/base/packages/SystemUI/src/com/android/systemui/screenshot/ |
| GlobalScreenshot.java | 37 import android.graphics.Matrix;
141 Matrix matrix = new Matrix();
142 matrix.postTranslate((shortSide - mImageWidth) / 2,
144 c.drawBitmap(data.image, matrix, paint);
328 private Matrix mDisplayMatrix;
357 mDisplayMatrix = new Matrix();
|
| /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/formats/ |
| CameraFormatsActivity.java | 28 import android.graphics.Matrix;
401 Matrix transform = new Matrix();
|
| /cts/apps/CtsVerifier/src/com/android/cts/verifier/camera/video/ |
| CameraVideoActivity.java | 20 import android.graphics.Matrix;
695 Matrix transform = new Matrix();
|
| /cts/tests/tests/widget/src/android/widget/cts/ |
| ImageViewTest.java | 33 import android.graphics.Matrix;
290 imageView.setScaleType(ImageView.ScaleType.MATRIX);
291 assertEquals(ImageView.ScaleType.MATRIX, imageView.getScaleType());
312 final Matrix matrix = new Matrix(); local
313 imageView.setImageMatrix(matrix);
314 assertEquals(matrix, imageView.getImageMatrix());
|
| /external/eigen/Eigen/src/LU/ |
| FullPivLU.h | 19 * \brief LU decomposition of a matrix with complete pivoting, and related features
21 * \param MatrixType the type of the matrix of which we are computing the LU decomposition
23 * This class represents a LU decomposition of any matrix, with complete pivoting: the matrix A
32 * decomposition is inherently more stable and/or flexible. For example, when computing the kernel of a matrix,
33 * working with the SVD allows to select the smallest singular values of the matrix, something that
39 * As an exemple, here is how the original matrix can be retrieved:
83 * \param matrix the matrix of which to compute the LU decomposition.
86 FullPivLU(const MatrixType& matrix);
[all...] |
| /external/eigen/Eigen/src/QR/ |
| FullPivHouseholderQR.h | 32 * \brief Householder rank-revealing QR decomposition of a matrix with full pivoting
34 * \param MatrixType the type of the matrix of which we are computing the QR decomposition
36 * This class performs a rank-revealing QR decomposition of a matrix \b A into matrices \b P, \b Q and \b R
41 * by using Householder transformations. Here, \b P is a permutation matrix, \b Q a unitary matrix and \b R an
42 * upper triangular matrix.
66 typedef Matrix<Index, 1, ColsAtCompileTime, RowMajor, 1, MaxColsAtCompileTime> IntRowVectorType;
103 FullPivHouseholderQR(const MatrixType& matrix)
104 : m_qr(matrix.rows(), matrix.cols())
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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;
195 /* calculate the jacobian matrix. */
435 /* calculate the jacobian matrix. */
|
| /frameworks/base/media/tests/MediaDump/src/com/android/mediadump/ |
| VideoDumpView.java | 48 import android.opengl.Matrix;
357 Matrix.setIdentityM(mSTMatrix, 0);
417 Matrix.setIdentityM(mMVPMatrix, 0);
|
