gnu: Add r-swne.

* gnu/packages/statistics.scm (r-swne): New variable.
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Ricardo Wurmus 2022-02-08 23:55:38 +01:00
parent 98a4da8a13
commit 61d1d4a3c5
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@ -6106,6 +6106,60 @@ (define-public r-nnlm
regularizations.")
(license license:bsd-2))))
(define-public r-swne
(let ((commit "05fc3ee4e09b2c34d99c69d3b97cece4c1c34143")
(revision "1"))
(package
(name "r-swne")
(version (git-version "0.6.20" revision commit))
(source
(origin
(method git-fetch)
(uri (git-reference
(url "https://github.com/yanwu2014/swne")
(commit commit)))
(file-name (git-file-name name version))
(sha256
(base32 "0crlpg9kclbv4v8250p3086a3lk6f2hcq79psqkdylc1qnrx3kfx"))))
(properties `((upstream-name . "swne")))
(build-system r-build-system)
(propagated-inputs
(list r-fnn
r-ggplot2
r-ggrepel
r-hash
r-ica
r-igraph
r-irlba
r-jsonlite
r-liger
r-mass
r-matrix
r-mgcv
r-nnlm ;not listed but required at install time
r-plyr
r-proxy
r-rcolorbrewer
r-rcpp
r-rcpparmadillo
r-rcppeigen
r-reshape
r-reshape2
r-snow
r-umap
r-usedist))
(home-page "https://github.com/yanwu2014/swne")
(synopsis "Visualize high dimensional datasets")
(description
"@dfn{Similarity Weighted Nonnegative Embedding} (SWNE) is a method for
visualizing high dimensional datasets. SWNE uses Nonnegative Matrix
Factorization to decompose datasets into latent factors, projects those
factors onto 2 dimensions, and embeds samples and key features in 2 dimensions
relative to the factors. SWNE can capture both the local and global dataset
structure, and allows relevant features to be embedded directly onto the
visualization, facilitating interpretation of the data.")
(license license:gpl2))))
(define-public python-rpy2
(package
(name "python-rpy2")