gnu: Add python-pyfit-sne.

* gnu/packages/bioinformatics.scm (python-pyfit-sne): New variable.
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Ricardo Wurmus 2019-02-15 11:02:41 +01:00
parent a37bdf4289
commit 9846ec0bea
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@ -14497,3 +14497,33 @@ designed for use with hybrid capture, including both whole-exome and custom
target panels, and short-read sequencing platforms such as Illumina and Ion target panels, and short-read sequencing platforms such as Illumina and Ion
Torrent.") Torrent.")
(license license:asl2.0))) (license license:asl2.0)))
(define-public python-pyfit-sne
(package
(name "python-pyfit-sne")
(version "1.0.1")
(source
(origin
(method git-fetch)
(uri (git-reference
(url "https://github.com/KlugerLab/pyFIt-SNE.git")
(commit version)))
(file-name (git-file-name name version))
(sha256
(base32 "13wh3qkzs56azmmgnxib6xfr29g7xh09sxylzjpni5j0pp0rc5qw"))))
(build-system python-build-system)
(propagated-inputs
`(("python-numpy" ,python-numpy)))
(inputs
`(("fftw" ,fftw)))
(native-inputs
`(("python-cython" ,python-cython)))
(home-page "https://github.com/KlugerLab/pyFIt-SNE")
(synopsis "FFT-accelerated Interpolation-based t-SNE")
(description
"t-Stochastic Neighborhood Embedding (t-SNE) is a highly successful
method for dimensionality reduction and visualization of high dimensional
datasets. A popular implementation of t-SNE uses the Barnes-Hut algorithm to
approximate the gradient at each iteration of gradient descent. This package
is a Cython wrapper for FIt-SNE.")
(license license:bsd-4)))