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  2. NumPy - Wikipedia

    en.wikipedia.org/wiki/NumPy

    NumPy. NumPy (pronounced / ˈnʌmpaɪ / NUM-py) is a library for the Python programming language, adding support for large, multi-dimensional arrays and matrices, along with a large collection of high-level mathematical functions to operate on these arrays. [ 3] The predecessor of NumPy, Numeric, was originally created by Jim Hugunin with ...

  3. Transpose - Wikipedia

    en.wikipedia.org/wiki/Transpose

    If A is an m × n matrix and A T is its transpose, then the result of matrix multiplication with these two matrices gives two square matrices: A A T is m × m and A T A is n × n. Furthermore, these products are symmetric matrices. Indeed, the matrix product A A T has entries that are the inner product of a row of A with a column of A T.

  4. Row- and column-major order - Wikipedia

    en.wikipedia.org/wiki/Row-_and_column-major_order

    In computing, row-major order and column-major order are methods for storing multidimensional arrays in linear storage such as random access memory . The difference between the orders lies in which elements of an array are contiguous in memory. In row-major order, the consecutive elements of a row reside next to each other, whereas the same ...

  5. Adjugate matrix - Wikipedia

    en.wikipedia.org/wiki/Adjugate_matrix

    Definition. The adjugate of A is the transpose of the cofactor matrix C of A , In more detail, suppose R is a unital commutative ring and A is an n × n matrix with entries from R. The (i, j) - minor of A, denoted Mij, is the determinant of the (n − 1) × (n − 1) matrix that results from deleting row i and column j of A.

  6. Moore–Penrose inverse - Wikipedia

    en.wikipedia.org/wiki/Moore–Penrose_inverse

    Moore–Penrose inverse. In mathematics, and in particular linear algebra, the Moore–Penrose inverse ⁠ ⁠ of a matrix ⁠ ⁠, often called the pseudoinverse, is the most widely known generalization of the inverse matrix. [ 1] It was independently described by E. H. Moore in 1920, [ 2] Arne Bjerhammar in 1951, [ 3] and Roger Penrose in ...

  7. In-place matrix transposition - Wikipedia

    en.wikipedia.org/wiki/In-place_matrix_transposition

    In-place matrix transposition. In-place matrix transposition, also called in-situ matrix transposition, is the problem of transposing an N × M matrix in-place in computer memory, ideally with O (1) (bounded) additional storage, or at most with additional storage much less than NM. Typically, the matrix is assumed to be stored in row-major or ...

  8. Vectorization (mathematics) - Wikipedia

    en.wikipedia.org/wiki/Vectorization_(mathematics)

    Vectorization (mathematics) In mathematics, especially in linear algebra and matrix theory, the vectorization of a matrix is a linear transformation which converts the matrix into a vector. Specifically, the vectorization of a m × n matrix A, denoted vec ( A ), is the mn × 1 column vector obtained by stacking the columns of the matrix A on ...

  9. Comparison of linear algebra libraries - Wikipedia

    en.wikipedia.org/wiki/Comparison_of_linear...

    uBLAS is a C++ template class library that provides BLAS level 1, 2, 3 functionality for dense, packed and sparse matrices. Eigen is a C++ template library for linear algebra: matrices, vectors, numerical solvers, and related algorithms. Fastor is a high performance tensor (fixed multi-dimensional array) library for modern C++.