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cpmech / gosl

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Go scientific library for machine learning, linear algebra, FFT, Bessel, elliptic, orthogonal polys, geometry, NURBS, numerical quadrature, 3D transfinite interpolation, random numbers, Mersenne twister, probability distributions, optimisation, graph, plotting, visualisation, tensors, eigenvalues, differential equations, more.

visualization machine-learning optimization linear-algebra sparse-systems linear-programming artificial-intelligence scientific-computing fast-fourier-transform graph-theory computational-geometry plotting differential-equations eigenvectors tensor-algebra hacktoberfest eigenvalues parallel-computations mkl hacktoberfest2019
  • Updated May 13, 2020
  • Go

ocramz / sparse-linear-algebra

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Sparse matrix multiplication incorrect documentation

GregorySchwartz
GregorySchwartz commented May 4, 2020

(#~#^) should be A B^T and vice versa for (#~^#). The documentation and function is above anb below the wrong type signature in each one respectively. Solution is to swap type signatures.

Wrong:

-- | Sparsifying A^T B
(#~#^) :: (MatrixRing (SpMatrix a), Epsilon a) =>
     SpMatrix a -> SpMatrix a -> SpMatrix a
a #~^# b = transpose a #~# b


-- | Sparsifying A B^T
(#~^#) :: (M
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hosseinmoein / Matrix

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C++ Matrix -- High performance and accurate (e.g. edge cases) matrix math library with expression template arithmetic operators

data-science cpp matrix metaprogramming matrix-factorization statistical-analysis eigenvectors matrix-calculations eigenvalues numerical-analysis lu-decomposition qr-decomposition matrix-decompositions financial-engineering tridiagonal matrix-math-library determinant-calculation hessenberg-reduction single-value-decomposition schur-decomposition
  • Updated Apr 5, 2020
  • C++

cpmech / gosl-examples

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Go scientific library for machine learning, linear algebra, FFT, Bessel, elliptic, orthogonal polys, geometry, NURBS, numerical quadrature, 3D transfinite interpolation, random numbers, Mersenne twister, probability distributions, optimisation, graph, plotting, visualisation, tensors, eigenvalues, differential equations, more.

visualization machine-learning optimization linear-algebra sparse-systems linear-programming artificial-intelligence scientific-computing fast-fourier-transform graph-theory computational-geometry plotting differential-equations eigenvectors tensor-algebra hacktoberfest eigenvalues parallel-computations mkl
  • Updated May 13, 2020
  • Go

Agha-Muqarib / NumPy-Basics-Arrays-And-Vectorized-Computation

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It includes the basic and advance numpy array manipulations. The topics like indexing, slicing, fast element array-wise functions, mathematical and statistical methods, filing, linear algebra functions, pseudo-random numbers, reshaping, splitting, concatenating,tiles, repeating, where( ) function & numpy advanced array manipulation are implemented.

python numpy matrix indexing matrix-functions arrays eigenvectors array-methods eigenvalues filing numpy-tutorial slicing array-manipulations numpy-exercises numpy-arrays matrix-computations arraylists numpy-matrix linear-algebra-functions
  • Updated Apr 21, 2020
  • Jupyter Notebook

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