Search Results for "numpy-mkl"
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Showing 5 open source projects for "numpy-mkl"
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segyio
Fast Python library for SEGY files
Segyio is a small LGPL-licensed C library for easy interaction with SEG-Y and Seismic Unix formatted seismic data, with language bindings for Python and Matlab. Segyio is an attempt to create an easy-to-use, embeddable, community-oriented library for seismic applications. Features are added as they are needed; suggestions and contributions of all kinds are very welcome. -
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Peroxide
Rust numeric library with high performance and friendly syntax
...This means that Peroxide can guarantee excellent performance for linear algebraic computations by leveraging the optimized routines provided by BLAS. For users familiar with numerical computing libraries like NumPy, MATLAB, or R, Rust's syntax might seem unfamiliar at first. This can make it more challenging to learn and use Rust libraries that heavily rely on Rust's unique features and syntax. -
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Armadillo
fast C++ library for linear algebra & scientific computing
* Fast C++ library for linear algebra (matrix maths) and scientific computing * Easy to use functions and syntax, deliberately similar to Matlab / Octave * Uses template meta-programming techniques to increase efficiency * Provides user-friendly wrappers for OpenBLAS, Intel MKL, LAPACK, ATLAS, ARPACK, SuperLU and FFTW libraries * Useful for machine learning, pattern recognition, signal processing, bioinformatics, statistics, finance, etc. * Downloads: http://arma.sourceforge.net/download.html * Documentation: http://arma.sourceforge.net/docs.html * Bug reports: http://arma.sourceforge.net/faq.html * Git repo: https://gitlab.com/conradsnicta/armadillo-code -
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math lib for .NET. n-dim arrays, complex numbers, linear algebra, FFT, sorting, cells- and logical arrays as well as 3D plotting classes help developing algorithms on every platform supporting .NET. Sources from SVN, binaries: http://ilnumerics.net
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Quick reference for switching between mathematical computation environments for computer algebra, numeric processing and data visualisation. Examples are Matlab, IDL, SPlus, and their open-source counterparts Octave, Scilab, Python+NumPy and R.
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