| /external/ceres-solver/internal/ceres/ |
| D | incomplete_lq_factorization_test.cc | 58 CompressedRowSparseMatrix matrix(1, 1, 1); in TEST() local
59 matrix.mutable_rows()[0] = 0; in TEST()
60 matrix.mutable_rows()[1] = 1; in TEST()
61 matrix.mutable_cols()[0] = 0; in TEST()
62 matrix.mutable_values()[0] = 2; in TEST()
65 IncompleteLQFactorization(matrix, 1, 0.0, 1, 0.0)); in TEST()
66 ExpectMatricesAreEqual(matrix, *l, 1e-16); in TEST()
83 CompressedRowSparseMatrix matrix(10, 10, 100); in TEST() local
84 int* rows = matrix.mutable_rows(); in TEST()
85 int* cols = matrix.mutable_cols(); in TEST()
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| /external/deqp/framework/common/ |
| D | tcuMatrix.hpp | 23 * \brief Templatized matrix class.
33 // Templated matrix class.
35 class Matrix class
48 Matrix (void);
49 explicit Matrix (const T& src);
50 explicit Matrix (const T src[Rows*Cols]);
51 Matrix (const Vector<T, Rows>& src);
52 Matrix (const Matrix<T, Rows, Cols>& src);
53 ~Matrix (void);
55 Matrix<T, Rows, Cols>& operator= (const Matrix<T, Rows, Cols>& src);
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| /external/eigen/test/ |
| D | geo_transformations.cpp | 20 typedef Matrix<Scalar,3,1> Vector3; in non_projective_only()
39 VERIFY_IS_APPROX(t0.matrix(), Transform3::MatrixType::Identity()); in non_projective_only()
58 VERIFY((t0 * t1).matrix().isIdentity(test_precision<Scalar>())); in non_projective_only()
61 VERIFY_IS_APPROX(t1.matrix(), t0.matrix()); in non_projective_only()
82 typedef Matrix<Scalar,3,3> Matrix3; in transformations()
83 typedef Matrix<Scalar,4,4> Matrix4; in transformations()
84 typedef Matrix<Scalar,2,1> Vector2; in transformations()
85 typedef Matrix<Scalar,3,1> Vector3; in transformations()
86 typedef Matrix<Scalar,4,1> Vector4; in transformations()
122 // rotation matrix conversion in transformations()
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| D | corners.cpp | 13 VERIFY_IS_EQUAL(matrix.A, matrix.B); \
25 MatrixType matrix = MatrixType::Random(rows,cols); in corners() local
48 MatrixType matrix = MatrixType::Random(); in corners_fixedsize() local
60 VERIFY_IS_EQUAL((matrix.template topLeftCorner<r,c>()), (matrix.template block<r,c>(0,0))); in corners_fixedsize()
61 VERIFY_IS_EQUAL((matrix.template topRightCorner<r,c>()), (matrix.template block<r,c>(0,cols-c))); in corners_fixedsize()
62 …VERIFY_IS_EQUAL((matrix.template bottomLeftCorner<r,c>()), (matrix.template block<r,c>(rows-r,0))); in corners_fixedsize()
63 …VERIFY_IS_EQUAL((matrix.template bottomRightCorner<r,c>()), (matrix.template block<r,c>(rows-r,col… in corners_fixedsize()
65 …VERIFY_IS_EQUAL((matrix.template topLeftCorner<r,c>()), (matrix.template topLeftCorner<r,Dynamic>(… in corners_fixedsize()
66 …VERIFY_IS_EQUAL((matrix.template topRightCorner<r,c>()), (matrix.template topRightCorner<r,Dynamic… in corners_fixedsize()
67 …VERIFY_IS_EQUAL((matrix.template bottomLeftCorner<r,c>()), (matrix.template bottomLeftCorner<r,Dyn… in corners_fixedsize()
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| /external/eigen/Eigen/src/LU/ |
| D | Inverse.h | 24 static inline void run(const MatrixType& matrix, ResultType& result) in run()
26 result = matrix.partialPivLu().inverse(); in run()
40 static inline void run(const MatrixType& matrix, ResultType& result)
43 result.coeffRef(0,0) = Scalar(1) / matrix.coeff(0,0);
51 const MatrixType& matrix,
59 determinant = matrix.coeff(0,0);
71 const MatrixType& matrix, const typename ResultType::Scalar& invdet,
74 result.coeffRef(0,0) = matrix.coeff(1,1) * invdet;
75 result.coeffRef(1,0) = -matrix.coeff(1,0) * invdet;
76 result.coeffRef(0,1) = -matrix.coeff(0,1) * invdet;
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| /external/eigen/unsupported/Eigen/ |
| D | MatrixFunctions | 24 * \defgroup MatrixFunctions_Module Matrix functions module
26 * matrix functions.
35 * - \ref matrixbase_cos "MatrixBase::cos()", for computing the matrix cosine
36 * - \ref matrixbase_cosh "MatrixBase::cosh()", for computing the matrix hyperbolic cosine
37 * - \ref matrixbase_exp "MatrixBase::exp()", for computing the matrix exponential
38 * - \ref matrixbase_log "MatrixBase::log()", for computing the matrix logarithm
39 * - \ref matrixbase_pow "MatrixBase::pow()", for computing the matrix power
40 …* - \ref matrixbase_matrixfunction "MatrixBase::matrixFunction()", for computing general matrix f…
41 * - \ref matrixbase_sin "MatrixBase::sin()", for computing the matrix sine
42 * - \ref matrixbase_sinh "MatrixBase::sinh()", for computing the matrix hyperbolic sine
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| /external/eigen/unsupported/test/ |
| D | bdcsvd.cpp | 107 // test of Dynamic defined Matrix (42, 42) of float in test_bdcsvd()
108 CALL_SUBTEST_11(( bdcsvd_verify_assert<Matrix<float,Dynamic,Dynamic> > in test_bdcsvd()
109 (Matrix<float,Dynamic,Dynamic>(42,42)) )); in test_bdcsvd()
110 CALL_SUBTEST_11(( compare_bdc_jacobi<Matrix<float,Dynamic,Dynamic> > in test_bdcsvd()
111 (Matrix<float,Dynamic,Dynamic>(42,42), 0) )); in test_bdcsvd()
112 CALL_SUBTEST_11(( bdcsvd<Matrix<float,Dynamic,Dynamic> > in test_bdcsvd()
113 (Matrix<float,Dynamic,Dynamic>(42,42)) )); in test_bdcsvd()
115 // test of Dynamic defined Matrix (50, 50) of double in test_bdcsvd()
116 CALL_SUBTEST_13(( bdcsvd_verify_assert<Matrix<double,Dynamic,Dynamic> > in test_bdcsvd()
117 (Matrix<double,Dynamic,Dynamic>(50,50)) )); in test_bdcsvd()
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| /external/eigen/Eigen/src/Eigenvalues/ |
| D | HessenbergDecomposition.h | 32 * \brief Reduces a square matrix to Hessenberg form by an orthogonal similarity transformation
34 …* \tparam _MatrixType the type of the matrix of which we are computing the Hessenberg decomposition
36 * This class performs an Hessenberg decomposition of a matrix \f$ A \f$. In
38 * matrix \f$ Q \f$ and a Hessenberg matrix \f$ H \f$ such that \f$ A = Q H
39 * Q^T \f$. An orthogonal matrix is a matrix whose inverse equals its
40 * transpose (\f$ Q^{-1} = Q^T \f$). A Hessenberg matrix has zeros below the
42 * of a complex matrix is \f$ A = Q H Q^* \f$ with \f$ Q \f$ unitary (that is,
46 * given matrix. Alternatively, you can use the
82 … typedef Matrix<Scalar, SizeMinusOne, 1, Options & ~RowMajor, MaxSizeMinusOne, 1> CoeffVectorType;
91 * \param [in] size The size of the matrix whose Hessenberg decomposition will be computed.
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| D | 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.
81 …typedef Matrix<ComplexScalar, RowsAtCompileTime, ColsAtCompileTime, Options, MaxRowsAtCompileTime,…
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| D | 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&)
80 … typedef Matrix<Scalar, SizeMinusOne, 1, Options & ~RowMajor, MaxSizeMinusOne, 1> CoeffVectorType;
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| D | ComplexEigenSolver.h | 26 * \tparam _MatrixType the type of the matrix of which we are
28 * instantiation of the Matrix class template.
30 * The eigenvalues and eigenvectors of a matrix \f$ A \f$ are scalars
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
34 * its columns, then \f$ A V = V D \f$. The matrix \f$ V \f$ is
78 …typedef Matrix<ComplexScalar, ColsAtCompileTime, 1, Options&(~RowMajor), MaxColsAtCompileTime, 1> …
80 /** \brief Type for matrix of eigenvectors as returned by eigenvectors().
82 * This is a square matrix with entries of type #ComplexScalar.
85 …typedef Matrix<ComplexScalar, RowsAtCompileTime, ColsAtCompileTime, Options, MaxRowsAtCompileTime,…
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| /external/opencv/cxcore/include/ |
| D | cxcore.hpp | 213 CvMatrix() : matrix(0) {} in CvMatrix()
215 { matrix = cvCreateMat( rows, cols, type ); } in CvMatrix()
219 { matrix = cvInitMatHeader( hdr, rows, cols, type, data, step ); } in CvMatrix()
224 { matrix = cvCreateMatHeader( rows, cols, type ); in CvMatrix()
225 cvSetData( matrix, data, step ); } in CvMatrix()
228 { matrix = m; } in CvMatrix()
232 matrix = m.matrix; in CvMatrix()
236 CvMatrix( const char* filename, const char* matname=0, int color=-1 ) : matrix(0) in CvMatrix()
239 CvMatrix( CvFileStorage* fs, const char* mapname, const char* matname ) : matrix(0) in CvMatrix()
242 CvMatrix( CvFileStorage* fs, const char* seqname, int idx ) : matrix(0) in CvMatrix()
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| /external/llvm/include/llvm/CodeGen/PBQP/ |
| D | Math.h | 1 //===------ Math.h - PBQP Vector and Matrix classes -------------*- C++ -*-===//
162 /// \brief PBQP Matrix class
163 class Matrix {
165 friend hash_code hash_value(const Matrix &);
168 /// \brief Construct a PBQP Matrix with the given dimensions.
169 Matrix(unsigned Rows, unsigned Cols) : in Matrix() function
173 /// \brief Construct a PBQP Matrix with the given dimensions and initial
175 Matrix(unsigned Rows, unsigned Cols, PBQPNum InitVal) in Matrix() function
180 /// \brief Copy construct a PBQP matrix.
181 Matrix(const Matrix &M) in Matrix() function
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| /external/jmonkeyengine/engine/src/core/com/jme3/math/ |
| D | Matrix3f.java | 42 * <code>Matrix3f</code> defines a 3x3 matrix. Matrix data is maintained
44 * are used for matrix operations as well as generating a matrix from a given
63 * initial values for the matrix is that of the identity matrix.
71 * constructs a matrix with the given values.
74 * 0x0 in the matrix.
76 * 0x1 in the matrix.
78 * 0x2 in the matrix.
80 * 1x0 in the matrix.
82 * 1x1 in the matrix.
84 * 1x2 in the matrix.
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| D | Matrix4f.java | 42 * <code>Matrix4f</code> defines and maintains a 4x4 matrix in row major order.
43 * This matrix is intended for use in a translation and rotational capacity.
44 * It provides convenience methods for creating the matrix from a multitude
69 * Constructor instantiates a new <code>Matrix</code> that is set to the
70 * identity matrix.
78 * constructs a matrix with the given values.
114 * Constructor instantiates a new <code>Matrix</code> that is set to the
115 * provided matrix. This constructor copies a given Matrix. If the provided
116 * matrix is null, the constructor sets the matrix to the identity.
119 * the matrix to copy.
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| /external/apache-commons-math/src/main/java/org/apache/commons/math/stat/correlation/ |
| D | Covariance.java | 27 * Computes covariances for pairs of arrays or columns of a matrix.
48 /** covariance matrix */
52 * Create an empty covariance matrix.
67 * Create a Covariance matrix from a rectangular array
86 * Create a Covariance matrix from a rectangular array
101 * Create a covariance matrix from a matrix whose columns
107 * <p>The matrix must have at least two columns and two rows</p>
109 * @param matrix matrix with columns representing covariates
111 * @throws IllegalArgumentException if the input matrix does not have
114 public Covariance(RealMatrix matrix, boolean biasCorrected) { in Covariance() argument
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| D | PearsonsCorrelation.java | 33 * or columns of a matrix.
48 /** correlation matrix */
79 * @param matrix matrix with columns representing variables to correlate
81 public PearsonsCorrelation(RealMatrix matrix) { in PearsonsCorrelation() argument
82 checkSufficientData(matrix); in PearsonsCorrelation()
83 nObs = matrix.getRowDimension(); in PearsonsCorrelation()
84 correlationMatrix = computeCorrelationMatrix(matrix); in PearsonsCorrelation()
89 * matrix is computed by scaling the Covariance's covariance matrix.
90 * The Covariance instance must have been created from a data matrix with
105 * Create a PearsonsCorrelation from a covariance matrix. The correlation
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| D | SpearmansCorrelation.java | 52 * Create a SpearmansCorrelation with the given input data matrix
55 * @param dataMatrix matrix of data with columns representing
67 * Create a SpearmansCorrelation from the given data matrix.
69 * @param dataMatrix matrix of data with columns representing
86 * Calculate the Spearman Rank Correlation Matrix.
88 * @return Spearman Rank Correlation Matrix
97 * <code>new SpearmansCorrelation(matrix).getRankCorrelation()</code>
99 * <code>new PearsonsCorrelation(rankTransform(matrix))</code> where
100 * <code>rankTransform(matrix)</code> is the result of applying the
102 * <code>matrix.</code>
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| /external/eigen/Eigen/src/Core/ |
| D | Matrix.h | 16 /** \class Matrix
19 * \brief The matrix class, also used for vectors and row-vectors
21 …* The %Matrix class is the work-horse for all \em dense (\ref dense "note") matrices and vectors w…
24 …* The %Matrix class encompasses \em both fixed-size and dynamic-size objects (\ref fixedsize "note…
42 * \li \c Matrix2d is a 2x2 square matrix of doubles (\c Matrix<double, 2, 2>)
43 * \li \c Vector4f is a vector of 4 floats (\c Matrix<float, 4, 1>)
44 * \li \c RowVector3i is a row-vector of 3 ints (\c Matrix<int, 1, 3>)
46 * \li \c MatrixXf is a dynamic-size matrix of floats (\c Matrix<float, Dynamic, Dynamic>)
47 * \li \c VectorXf is a dynamic-size vector of floats (\c Matrix<float, Dynamic, 1>)
49 …* \li \c Matrix2Xf is a partially fixed-size (dynamic-size) matrix of floats (\c Matrix<float, 2, …
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| /external/eigen/test/eigen2/ |
| D | eigen2_geometry.cpp | 21 typedef Matrix<Scalar,2,2> Matrix2; in geometry()
22 typedef Matrix<Scalar,3,3> Matrix3; in geometry()
23 typedef Matrix<Scalar,4,4> Matrix4; in geometry()
24 typedef Matrix<Scalar,2,1> Vector2; in geometry()
25 typedef Matrix<Scalar,3,1> Vector3; in geometry()
26 typedef Matrix<Scalar,4,1> Vector4; in geometry()
90 // rotation matrix conversion in geometry()
141 VERIFY_IS_APPROX(t0.matrix(), Transform3::MatrixType::Identity()); in geometry()
142 t0.matrix().setZero(); in geometry()
144 VERIFY_IS_APPROX(t0.matrix(), Transform3::MatrixType::Identity()); in geometry()
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| D | eigen2_geometry_with_eigen2_prefix.cpp | 23 typedef Matrix<Scalar,2,2> Matrix2; in geometry()
24 typedef Matrix<Scalar,3,3> Matrix3; in geometry()
25 typedef Matrix<Scalar,4,4> Matrix4; in geometry()
26 typedef Matrix<Scalar,2,1> Vector2; in geometry()
27 typedef Matrix<Scalar,3,1> Vector3; in geometry()
28 typedef Matrix<Scalar,4,1> Vector4; in geometry()
92 // rotation matrix conversion in geometry()
143 VERIFY_IS_APPROX(t0.matrix(), Transform3::MatrixType::Identity()); in geometry()
144 t0.matrix().setZero(); in geometry()
146 VERIFY_IS_APPROX(t0.matrix(), Transform3::MatrixType::Identity()); in geometry()
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| /external/eigen/bench/btl/data/ |
| D | action_settings.txt | 1 aat ; "{/*1.5 A x A^T}" ; "matrix size" ; 4:3000
2 ata ; "{/*1.5 A^T x A}" ; "matrix size" ; 4:3000
3 atv ; "{/*1.5 matrix^T x vector}" ; "matrix size" ; 4:3000
6 matrix_matrix ; "{/*1.5 matrix matrix product}" ; "matrix size" ; 4:3000
7 matrix_vector ; "{/*1.5 matrix vector product}" ; "matrix size" ; 4:3000
8 trmm ; "{/*1.5 triangular matrix matrix product}" ; "matrix size" ; 4:3000
10 trisolve_matrix ; "{/*1.5 triangular solver - matrix (M = inv(L) M)}" ; "size" ; 4:3000
11 cholesky ; "{/*1.5 Cholesky decomposition}" ; "matrix size" ; 4:3000
12 complete_lu_decomp ; "{/*1.5 Complete LU decomposition}" ; "matrix size" ; 4:3000
13 partial_lu_decomp ; "{/*1.5 Partial LU decomposition}" ; "matrix size" ; 4:3000
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| /external/apache-commons-math/src/main/java/org/apache/commons/math/linear/ |
| D | SingularValueDecomposition.java | 24 * Singular Value Decomposition of a real matrix.
26 * The Singular Value Decomposition of matrix A is a set of three matrices: U,
28 * a m × n matrix, then U is a m × p orthogonal matrix, Σ is a
29 * p × p diagonal matrix with positive or null elements, V is a p ×
30 * n orthogonal matrix (hence V<sup>T</sup> is also orthogonal) where
56 * Returns the matrix U of the decomposition.
57 * <p>U is an orthogonal matrix, i.e. its transpose is also its inverse.</p>
58 * @return the U matrix
64 * Returns the transpose of the matrix U of the decomposition.
65 * <p>U is an orthogonal matrix, i.e. its transpose is also its inverse.</p>
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| /external/eigen/doc/ |
| D | ClassHierarchy.dox | 17 the derived class (for instance, \c Matrix) inherits the base class with the derived class itself a…
18 template argument (in this case, \c Matrix inherits from \c MatrixBase<Matrix>). This allows …
31 …- Matrix means plain dense matrix. If \c m is a \c %Matrix, then, for instance, \c m+m is no longe…
32 \c %Matrix, it is a "matrix expression".
33 …- MatrixBase means dense matrix expression. This means that a \c %MatrixBase is something that can…
34 …added, matrix-multiplied, LU-decomposed, QR-decomposed... All matrix expression classes, including
35 \c %Matrix itself, inherit \c %MatrixBase.
41 …- DenseBase means dense (matrix or array) expression. Both \c %ArrayBase and \c %MatrixBase inherit
43 …whether they are matrix or array expressions. For example, the \link DenseBase::block() block(...)…
51 …- PlainObjectBase means dense (matrix or array) plain object, i.e. something that stores its own d…
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| /external/eigen/Eigen/src/PaStiXSupport/ |
| D | PaStiXSupport.h | 19 * The matrix can be either real or complex, symmetric or not.
87 // Convert the matrix to Fortran-style Numbering
128 typedef Matrix<Scalar,Dynamic,1> Vector;
153 && "PastixBase::solve(): invalid number of rows of the right hand side matrix b");
213 * \c InvalidInput if the input matrix is invalid
233 && "PastixBase::solve(): invalid number of rows of the right hand side matrix b");
239 // Initialize the Pastix data structure, check the matrix
267 mutable Matrix<int,IPARM_SIZE,1> m_iparm; // integer vector for the input parameters
268 mutable Matrix<double,DPARM_SIZE,1> m_dparm; // Scalar vector for the input parameters
269 mutable Matrix<Index,Dynamic,1> m_perm; // Permutation vector
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