| /external/eigen/ |
| eigen3.pc.in | 2 Description: A C++ template library for linear algebra: vectors, matrices, and related algorithms
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| README.android | 4 Eigen is a C++ template library for linear algebra: matrices, vectors,
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| /external/chromium_org/third_party/skia/gm/ |
| shadertext2.cpp | 62 SkTDArray<LabeledMatrix> matrices; local
63 matrices.append()->fMatrix.reset();
64 matrices.top().fLabel = "Identity";
65 matrices.append()->fMatrix.setScale(1.2f, 0.8f);
66 matrices.top().fLabel = "Scale";
67 matrices.append()->fMatrix.setRotate(10.f);
68 matrices.top().fLabel = "Rotate";
69 matrices.append()->fMatrix.reset();
70 matrices.top().fMatrix.setPerspX(-0.0015f);
71 matrices.top().fMatrix.setPerspY(+0.0015f)
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| /external/skia/gm/ |
| shadertext2.cpp | 62 SkTDArray<LabeledMatrix> matrices; local
63 matrices.append()->fMatrix.reset();
64 matrices.top().fLabel = "Identity";
65 matrices.append()->fMatrix.setScale(1.2f, 0.8f);
66 matrices.top().fLabel = "Scale";
67 matrices.append()->fMatrix.setRotate(10.f);
68 matrices.top().fLabel = "Rotate";
69 matrices.append()->fMatrix.reset();
70 matrices.top().fMatrix.setPerspX(-0.0015f);
71 matrices.top().fMatrix.setPerspY(+0.0015f)
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| /external/opencv/cvaux/src/ |
| cvtexture.cpp | 60 double*** matrices; member in struct:CvGLCM
140 newGLCM->matrices = 0;
233 if( (flag == CV_GLCM_GLCM || flag == CV_GLCM_ALL) && (*GLCM)->matrices )
237 if( (*GLCM)->matrices[ matrixLoop ] )
239 cvFree( (*GLCM)->matrices[matrixLoop] );
240 cvFree( (*GLCM)->matrices + matrixLoop );
244 cvFree( &((*GLCM)->matrices) );
283 double*** matrices = 0; local
285 // allocate memory to the matrices
286 CV_CALL( destGLCM->matrices = (double***)cvAlloc( sizeof(matrices[0])*numSteps ))
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| /external/eigen/Eigen/ |
| IterativeLinearSolvers | 14 * - ConjugateGradient for selfadjoint (hermitian) matrices,
15 * - BiCGSTAB for general square matrices.
19 * - DiagonalPreconditioner - also called JAcobi preconditioner, work very well on diagonal dominant matrices.
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| Cholesky | 12 * This module provides two variants of the Cholesky decomposition for selfadjoint (hermitian) matrices.
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| SVD | 14 * This module provides SVD decomposition for matrices (both real and complex).
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| SparseQR | 9 * \brief Provides QR decomposition for sparse matrices
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| /external/eigen/bench/spbench/ |
| spbenchsolver.cpp | 7 cout<< " The matrices for the benchmark should be collected in a folder specified with an environment variable EIGEN_MATRIXDIR \n";
8 cout<< " The matrices are stored using the matrix market coordinate format \n";
31 // Get the location of the test matrices
36 std::cerr << "Please, specify the location of the matrices with -d mat_folder or the environment variable EIGEN_MATRIXDIR \n";
70 // Test the real-arithmetics matrices
73 // Test the complex-arithmetics matrices
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| /external/eigen/unsupported/Eigen/src/SVD/ |
| TODOBdcsvd.txt | 6 - support static matrices
7 - return a error at compilation time when using integer matrices (int, long, std::complex<int>, ...)
27 6) multiply naiveU and naiveV to the right by the matrices found, only naiveU when CompV is set to
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| doneInBDCSVD.txt | 14 The implemented has trouble with fixed size matrices.
16 In the actual implementation, it returns matrices of zero when ask to do a svd on an int matrix.
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| /external/ceres-solver/data/ |
| README.foe | 7 matrices from the MATLAB files and performing matrix multiplication.
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| /external/eigen/Eigen/src/Core/ |
| Matrix.h | 21 * The %Matrix class is the work-horse for all \em dense (\ref dense "note") matrices and vectors within Eigen.
22 * Vectors are matrices with one column, and row-vectors are matrices with one row.
36 * for vectorization. It defaults to aligning matrices except for fixed sizes that aren't a multiple of the packet size.
54 * You can access elements of vectors and matrices using normal subscripting:
76 * <dd>This %Matrix class handles dense, not sparse matrices and vectors. For sparse matrices and vectors, see the Sparse module.
78 * Dense matrices and vectors are plain usual arrays of coefficients. All the coefficients are stored, in an ordinary contiguous array.
79 * This is unlike Sparse matrices and vectors where the coefficients are stored as a list of nonzero coefficients.</dd>
83 * of coefficients as a fixed-size array, as a class member. This makes sense for very small matrices, typically up to 4x4, sometimes u
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| /external/eigen/doc/snippets/ |
| RealQZ_compute.cpp | 3 RealQZ<MatrixXf> qz(4); // preallocate space for 4x4 matrices
6 // print original matrices and result of decomposition
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| /external/eigen/test/ |
| pastix_support.cpp | 30 // There is no support for selfadjoint matrices with PaStiX.
31 // Complex symmetric matrices should pass though
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| sparselu.cpp | 26 // SparseLU solve does not accept column major matrices for the destination.
28 // rhs and destination matrices when compiled with EIGEN_DEFAULT_TO_ROW_MAJOR
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| /external/eigen/doc/ |
| TutorialArrayClass.dox | 59 The parenthesis operator is overloaded to provide write and read access to the coefficients of an array, just as with matrices.
76 Adding and subtracting two arrays is the same as for matrices.
94 First of all, of course you can multiply an array by a scalar, this works in the same way as matrices. Where arrays
95 are fundamentally different from matrices, is when you multiply two together. Matrices interpret
133 apply Matrix operations on arrays, or Array operations on matrices. Thus, if you need to do linear algebraic
134 operations such as matrix multiplication, then you should use matrices; if you need to do coefficient-wise
137 access to all operations regardless of the choice of declaring objects as arrays or as matrices.
147 Mixing matrices and arrays in an expression is forbidden with Eigen. For instance, you cannot add a matrix and
148 array directly; the operands of a \c + operator should either both be matrices or both be arrays. However
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| StorageOrders.dox | 5 There are two different storage orders for matrices and two-dimensional arrays: column-major and row-major.
63 Matrices and arrays using one storage order can be assigned to matrices and arrays using the other storage
65 the entries automatically. More generally, row-major and column-major matrices can be mixed in an expression
79 matrices. It may be worthwhile to experiment a bit to find out what is faster for your particular
82 is thus done with column-major matrices. This means that, even though we aim to support column-major and
83 row-major storage orders transparently, the Eigen library may well work best with column-major matrices.
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| /external/chromium_org/third_party/mesa/src/src/glsl/ |
| TODO | 5 also trivial for arrays, matrices, and vectors that are accessed with
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| /external/chromium_org/third_party/skia/src/gpu/gl/ |
| GrGLUniformManager.h | 65 // matrices are column-major, the first three upload a single matrix, the latter three upload
66 // arrayCount matrices into a uniform array.
69 void setMatrix3fv(UniformHandle, int arrayCount, const GrGLfloat matrices[]) const;
70 void setMatrix4fv(UniformHandle, int arrayCount, const GrGLfloat matrices[]) const;
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| /external/eigen/unsupported/Eigen/ |
| SVD | 14 * This module provides SVD decomposition for matrices (both real and complex).
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| /external/mesa3d/src/glsl/ |
| TODO | 5 also trivial for arrays, matrices, and vectors that are accessed with
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| /external/skia/src/gpu/gl/ |
| GrGLUniformManager.h | 65 // matrices are column-major, the first three upload a single matrix, the latter three upload
66 // arrayCount matrices into a uniform array.
69 void setMatrix3fv(UniformHandle, int arrayCount, const GrGLfloat matrices[]) const;
70 void setMatrix4fv(UniformHandle, int arrayCount, const GrGLfloat matrices[]) const;
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| /external/eigen/unsupported/test/ |
| matrix_functions.h | 16 // for real matrices, make sure none of the eigenvalues are negative
33 // for complex matrices, any matrix is fine
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