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Analyzed 7 days ago
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NumPy is the fundamental package for scientific computing with Python. It contains among other things:
a powerful N-dimensional array object
sophisticated (broadcasting) functions
tools for integrating C/C++ and Fortran code
useful linear algebra, Fourier transform, and random number

Licenses:
No declared licenses

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Analyzed 7 days ago
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Eigen is a C++ template library for linear algebra: matrices, vectors, numerical solvers, and related algorithms.
* It supports tiny & large dense, and sparse matrices, fully integrated with one another.
* It has no dependency and no binary to compile or link-to.
* It takes full advantage of

Licenses:
lgpl3, mozilla_p...

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Analyzed 7 days ago
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(from the scilab homepage...)
Scilab is a scientific software package for numerical computations providing a powerful open computing environment for engineering and scientific applications.
Scilab is an open source software. Since 1994 it has been distributed freely along with the source code

Licenses:
No declared licenses

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Analyzed 10 minutes ago
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Armadillo is a C++ linear algebra library (matrix maths) aiming towards a good balance between speed and ease of use. Integer, floating point and complex numbers are supported, as well as a subset of trigonometric and statistics functions. Various matrix decompositions are provided through optional

Mostly written in language not available

Licenses:
mozilla_p...

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Claimed by
Code Lutin
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Analyzed about 3 hours ago
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Java library to provide multi-dimensional matrix functionalities.

*No analysis available*

The BLAS (Basic Linear Algebra Subprograms) are routines that provide standard building blocks for performing basic vector and matrix operations. The Level 1 BLAS perform scalar, vector and vector-vector operations, the Level 2 BLAS perform matrix-vector operations, and the Level 3 BLAS perform

Mostly written in language not available

Licenses:
blas

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Analyzed about 11 hours ago
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jblas is a fast linear algebra library for Java. jblas is based on BLAS and LAPACK, the de-facto industry standard for matrix computations, and uses state-of-the-art implementations like ATLAS for all its computational routines, making jBLAS very fast.
jblas can is essentially a light-wight