345 lines
14 KiB
Scheme
345 lines
14 KiB
Scheme
;;; GNU Guix --- Functional package management for GNU
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;;; Copyright © 2015 Ricardo Wurmus <rekado@elephly.net>
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;;;
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;;; This file is part of GNU Guix.
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;;;
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;;; GNU Guix is free software; you can redistribute it and/or modify it
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;;; under the terms of the GNU General Public License as published by
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;;; the Free Software Foundation; either version 3 of the License, or (at
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;;; your option) any later version.
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;;;
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;;; GNU Guix is distributed in the hope that it will be useful, but
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;;; WITHOUT ANY WARRANTY; without even the implied warranty of
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;;; MERCHANTABILITY or FITNESS FOR A PARTICULAR PURPOSE. See the
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;;; GNU General Public License for more details.
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;;;
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;;; You should have received a copy of the GNU General Public License
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;;; along with GNU Guix. If not, see <http://www.gnu.org/licenses/>.
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(define-module (gnu packages machine-learning)
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#:use-module ((guix licenses) #:prefix license:)
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#:use-module (guix packages)
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#:use-module (guix utils)
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#:use-module (guix download)
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#:use-module (guix build-system cmake)
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#:use-module (guix build-system gnu)
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#:use-module (guix build-system r)
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#:use-module (gnu packages)
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#:use-module (gnu packages boost)
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#:use-module (gnu packages compression)
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#:use-module (gnu packages gcc)
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#:use-module (gnu packages maths)
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#:use-module (gnu packages pkg-config)
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#:use-module (gnu packages python)
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#:use-module (gnu packages statistics)
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#:use-module (gnu packages swig)
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#:use-module (gnu packages xml))
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(define-public libsvm
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(package
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(name "libsvm")
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(version "3.20")
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(source
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(origin
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(method url-fetch)
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(uri (string-append
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"https://github.com/cjlin1/libsvm/archive/v"
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(string-delete #\. version) ".tar.gz"))
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(file-name (string-append name "-" version ".tar.gz"))
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(sha256
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(base32
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"1jpjlql3frjza7zxzrqqr2firh44fjb8fqsdmvz6bjz7sb47zgp4"))))
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(build-system gnu-build-system)
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(arguments
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`(#:tests? #f ;no "check" target
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#:phases (modify-phases %standard-phases
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(delete 'configure)
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(replace
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'install
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(lambda* (#:key outputs #:allow-other-keys)
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(let* ((out (assoc-ref outputs "out"))
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(bin (string-append out "/bin/")))
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(mkdir-p bin)
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(for-each (lambda (file)
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(copy-file file (string-append bin file)))
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'("svm-train"
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"svm-predict"
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"svm-scale")))
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#t)))))
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(home-page "http://www.csie.ntu.edu.tw/~cjlin/libsvm/")
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(synopsis "Library for Support Vector Machines")
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(description
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"LIBSVM is a machine learning library for support vector
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classification, (C-SVC, nu-SVC), regression (epsilon-SVR, nu-SVR) and
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distribution estimation (one-class SVM). It supports multi-class
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classification.")
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(license license:bsd-3)))
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(define-public python-libsvm
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(package (inherit libsvm)
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(name "python-libsvm")
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(build-system gnu-build-system)
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(arguments
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`(#:tests? #f ;no "check" target
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#:make-flags '("-C" "python")
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#:phases
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(modify-phases %standard-phases
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(delete 'configure)
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(replace
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'install
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(lambda* (#:key inputs outputs #:allow-other-keys)
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(let ((site (string-append (assoc-ref outputs "out")
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"/lib/python"
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(string-take
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(string-take-right
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(assoc-ref inputs "python") 5) 3)
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"/site-packages/")))
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(substitute* "python/svm.py"
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(("../libsvm.so.2") "libsvm.so.2"))
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(mkdir-p site)
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(for-each (lambda (file)
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(copy-file file (string-append site (basename file))))
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(find-files "python" "\\.py"))
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(copy-file "libsvm.so.2"
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(string-append site "libsvm.so.2")))
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#t)))))
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(inputs
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`(("python" ,python)))
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(synopsis "Python bindings of libSVM")))
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(define-public randomjungle
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(package
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(name "randomjungle")
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(version "2.1.0")
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(source
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(origin
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(method url-fetch)
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(uri (string-append
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"http://www.imbs-luebeck.de/imbs/sites/default/files/u59/"
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"randomjungle-" version ".tar_.gz"))
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(sha256
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(base32
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"12c8rf30cla71swx2mf4ww9mfd8jbdw5lnxd7dxhyw1ygrvg6y4w"))))
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(build-system gnu-build-system)
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(arguments
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`(#:configure-flags
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(list (string-append "--with-boost="
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(assoc-ref %build-inputs "boost")))
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#:phases
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(modify-phases %standard-phases
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(add-before
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'configure 'set-CXXFLAGS
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(lambda _
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(setenv "CXXFLAGS" "-fpermissive ")
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#t)))))
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(inputs
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`(("boost" ,boost)
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("gsl" ,gsl)
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("libxml2" ,libxml2)
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("zlib" ,zlib)))
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(native-inputs
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`(("gfortran" ,gfortran)))
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(home-page "http://www.imbs-luebeck.de/imbs/de/node/227/")
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(synopsis "Implementation of the Random Forests machine learning method")
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(description
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"Random Jungle is an implementation of Random Forests. It is supposed to
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analyse high dimensional data. In genetics, it can be used for analysing big
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Genome Wide Association (GWA) data. Random Forests is a powerful machine
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learning method. Most interesting features are variable selection, missing
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value imputation, classifier creation, generalization error estimation and
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sample proximities between pairs of cases.")
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(license license:gpl3+)))
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(define-public shogun
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(package
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(name "shogun")
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(version "4.0.0")
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(source
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(origin
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(method url-fetch)
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(uri (string-append
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"ftp://shogun-toolbox.org/shogun/releases/"
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(version-major+minor version)
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"/sources/shogun-" version ".tar.bz2"))
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(sha256
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(base32
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"159nlijnb7mnrv9za80wnm1shwvy45hgrqzn51hxy7gw4z6d6fdb"))
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(modules '((guix build utils)
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(ice-9 rdelim)))
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(snippet
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'(begin
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;; Remove non-free sources and files referencing them
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(for-each delete-file
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(find-files "src/shogun/classifier/svm/"
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"SVMLight\\.(cpp|h)"))
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(for-each delete-file
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(find-files "examples/undocumented/libshogun/"
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(string-append
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"(classifier_.*svmlight.*|"
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"evaluation_cross_validation_locked_comparison).cpp")))
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;; Remove non-free functions.
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(define (delete-ifdefs file)
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(with-atomic-file-replacement file
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(lambda (in out)
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(let loop ((line (read-line in 'concat))
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(skipping? #f))
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(if (eof-object? line)
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#t
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(let ((skip-next?
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(or (and skipping?
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(not (string-prefix?
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"#endif //USE_SVMLIGHT" line)))
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(string-prefix?
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"#ifdef USE_SVMLIGHT" line))))
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(when (or (not skipping?)
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(and skipping? (not skip-next?)))
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(display line out))
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(loop (read-line in 'concat) skip-next?)))))))
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(for-each delete-ifdefs (find-files "src/shogun/kernel/"
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"^Kernel\\.(cpp|h)"))))))
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(build-system cmake-build-system)
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(arguments
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'(#:tests? #f ;no check target
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#:phases
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(alist-cons-after
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'unpack 'delete-broken-symlinks
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(lambda _
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(for-each delete-file '("applications/arts/data"
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"applications/asp/data"
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"applications/easysvm/data"
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"applications/msplicer/data"
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"applications/ocr/data"
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"examples/documented/data"
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"examples/documented/matlab_static"
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"examples/documented/octave_static"
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"examples/undocumented/data"
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"examples/undocumented/matlab_static"
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"examples/undocumented/octave_static"
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"tests/integration/data"
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"tests/integration/matlab_static"
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"tests/integration/octave_static"
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"tests/integration/python_modular/tests"))
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#t)
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(alist-cons-after
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'unpack 'change-R-target-path
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(lambda* (#:key outputs #:allow-other-keys)
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(substitute* '("src/interfaces/r_modular/CMakeLists.txt"
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"src/interfaces/r_static/CMakeLists.txt"
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"examples/undocumented/r_modular/CMakeLists.txt")
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(("\\$\\{R_COMPONENT_LIB_PATH\\}")
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(string-append (assoc-ref outputs "out")
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"/lib/R/library/")))
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#t)
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(alist-cons-after
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'unpack 'fix-octave-modules
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(lambda* (#:key outputs #:allow-other-keys)
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(substitute* '("src/interfaces/octave_modular/CMakeLists.txt"
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"src/interfaces/octave_static/CMakeLists.txt")
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(("^include_directories\\(\\$\\{OCTAVE_INCLUDE_DIRS\\}")
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"include_directories(${OCTAVE_INCLUDE_DIRS} ${OCTAVE_INCLUDE_DIRS}/octave"))
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;; change target directory
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(substitute* "src/interfaces/octave_modular/CMakeLists.txt"
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(("\\$\\{OCTAVE_OCT_LOCAL_API_FILE_DIR\\}")
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(string-append (assoc-ref outputs "out")
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"/share/octave/packages")))
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#t)
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(alist-cons-before
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'build 'set-HOME
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;; $HOME needs to be set at some point during the build phase
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(lambda _ (setenv "HOME" "/tmp") #t)
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%standard-phases))))
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#:configure-flags
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(list "-DCMAKE_BUILD_WITH_INSTALL_RPATH=TRUE"
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"-DUSE_SVMLIGHT=OFF" ;disable proprietary SVMLIGHT
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;;"-DJavaModular=ON" ;requires unpackaged jblas
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;;"-DRubyModular=ON" ;requires unpackaged ruby-narray
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;;"-DPerlModular=ON" ;"FindPerlLibs" does not exist
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;;"-DLuaModular=ON" ;fails because lua doesn't build pkgconfig file
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"-DOctaveModular=ON"
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"-DOctaveStatic=ON"
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"-DPythonModular=ON"
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"-DPythonStatic=ON"
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"-DRModular=ON"
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"-DRStatic=ON"
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"-DCmdLineStatic=ON")))
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(inputs
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`(("python" ,python)
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("numpy" ,python-numpy)
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("r" ,r)
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("octave" ,octave)
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("swig" ,swig)
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("hdf5" ,hdf5)
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("atlas" ,atlas)
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("arpack" ,arpack-ng)
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("lapack" ,lapack)
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("glpk" ,glpk)
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("libxml2" ,libxml2)
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("lzo" ,lzo)
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("zlib" ,zlib)))
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(native-inputs
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`(("pkg-config" ,pkg-config)))
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;; Non-portable SSE instructions are used so building fails on platforms
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;; other than x86_64.
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(supported-systems '("x86_64-linux"))
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(home-page "http://shogun-toolbox.org/")
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(synopsis "Machine learning toolbox")
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(description
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"The Shogun Machine learning toolbox provides a wide range of unified and
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efficient Machine Learning (ML) methods. The toolbox seamlessly allows to
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combine multiple data representations, algorithm classes, and general purpose
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tools. This enables both rapid prototyping of data pipelines and extensibility
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in terms of new algorithms.")
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(license license:gpl3+)))
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(define-public r-adaptivesparsity
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(package
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(name "r-adaptivesparsity")
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(version "1.4")
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(source (origin
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(method url-fetch)
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(uri (cran-uri "AdaptiveSparsity" version))
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(sha256
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(base32
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"1az7isvalf3kmdiycrfl6s9k9xqk22k1mc6rh8v0jmcz402qyq8z"))))
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(properties
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`((upstream-name . "AdaptiveSparsity")))
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(build-system r-build-system)
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(arguments
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`(#:phases
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(modify-phases %standard-phases
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(add-after 'unpack 'link-against-armadillo
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(lambda _
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(substitute* "src/Makevars"
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(("PKG_LIBS=" prefix)
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(string-append prefix "-larmadillo"))))))))
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(propagated-inputs
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`(("r-rcpp" ,r-rcpp)
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("r-rcpparmadillo" ,r-rcpparmadillo)))
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(home-page "http://cran.r-project.org/web/packages/AdaptiveSparsity")
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(synopsis "Adaptive sparsity models")
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(description
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"This package implements the Figueiredo machine learning algorithm for
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adaptive sparsity and the Wong algorithm for adaptively sparse gaussian
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geometric models.")
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(license license:lgpl3+)))
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(define-public r-nnet
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(package
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(name "r-nnet")
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(version "7.3-12")
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(source
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(origin
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(method url-fetch)
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(uri (cran-uri "nnet" version))
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(sha256
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(base32
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"17amqnw9dpap2w8ivx53hxha2xrm0drwfnj32li0xk41hlz548r7"))))
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(build-system r-build-system)
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(home-page "http://www.stats.ox.ac.uk/pub/MASS4/")
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(synopsis "Feed-forward neural networks and multinomial log-linear models")
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(description
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"This package provides functions for feed-forward neural networks with a
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single hidden layer, and for multinomial log-linear models.")
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(license (list license:gpl2+ license:gpl3+))))
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