;;; GNU Guix --- Functional package management for GNU
;;; Copyright © 2015 Ricardo Wurmus <rekado@elephly.net>
;;;
;;; This file is part of GNU Guix.
;;;
;;; GNU Guix is free software; you can redistribute it and/or modify it
;;; under the terms of the GNU General Public License as published by
;;; the Free Software Foundation; either version 3 of the License, or (at
;;; your option) any later version.
;;;
;;; GNU Guix is distributed in the hope that it will be useful, but
;;; WITHOUT ANY WARRANTY; without even the implied warranty of
;;; MERCHANTABILITY or FITNESS FOR A PARTICULAR PURPOSE.  See the
;;; GNU General Public License for more details.
;;;
;;; You should have received a copy of the GNU General Public License
;;; along with GNU Guix.  If not, see <http://www.gnu.org/licenses/>.

(define-module (gnu packages machine-learning)
  #:use-module ((guix licenses) #:prefix license:)
  #:use-module (guix packages)
  #:use-module (guix utils)
  #:use-module (guix download)
  #:use-module (guix build-system cmake)
  #:use-module (guix build-system gnu)
  #:use-module (guix build-system r)
  #:use-module (gnu packages)
  #:use-module (gnu packages boost)
  #:use-module (gnu packages compression)
  #:use-module (gnu packages gcc)
  #:use-module (gnu packages maths)
  #:use-module (gnu packages pkg-config)
  #:use-module (gnu packages python)
  #:use-module (gnu packages statistics)
  #:use-module (gnu packages swig)
  #:use-module (gnu packages xml))

(define-public libsvm
  (package
    (name "libsvm")
    (version "3.20")
    (source
     (origin
       (method url-fetch)
       (uri (string-append
             "https://github.com/cjlin1/libsvm/archive/v"
             (string-delete #\. version) ".tar.gz"))
       (file-name (string-append name "-" version ".tar.gz"))
       (sha256
        (base32
         "1jpjlql3frjza7zxzrqqr2firh44fjb8fqsdmvz6bjz7sb47zgp4"))))
    (build-system gnu-build-system)
    (arguments
     `(#:tests? #f ;no "check" target
       #:phases (modify-phases %standard-phases
                  (delete 'configure)
                  (replace
                   'install
                   (lambda* (#:key outputs #:allow-other-keys)
                     (let* ((out (assoc-ref outputs "out"))
                            (bin (string-append out "/bin/")))
                       (mkdir-p bin)
                       (for-each (lambda (file)
                                   (copy-file file (string-append bin file)))
                                 '("svm-train"
                                   "svm-predict"
                                   "svm-scale")))
                     #t)))))
    (home-page "http://www.csie.ntu.edu.tw/~cjlin/libsvm/")
    (synopsis "Library for Support Vector Machines")
    (description
     "LIBSVM is a machine learning library for support vector
classification, (C-SVC, nu-SVC), regression (epsilon-SVR, nu-SVR) and
distribution estimation (one-class SVM).  It supports multi-class
classification.")
    (license license:bsd-3)))

(define-public python-libsvm
  (package (inherit libsvm)
    (name "python-libsvm")
    (build-system gnu-build-system)
    (arguments
     `(#:tests? #f ;no "check" target
       #:make-flags '("-C" "python")
       #:phases
       (modify-phases %standard-phases
         (delete 'configure)
         (replace
          'install
          (lambda* (#:key inputs outputs #:allow-other-keys)
            (let ((site (string-append (assoc-ref outputs "out")
                                       "/lib/python"
                                       (string-take
                                        (string-take-right
                                         (assoc-ref inputs "python") 5) 3)
                                       "/site-packages/")))
              (substitute* "python/svm.py"
                (("../libsvm.so.2") "libsvm.so.2"))
              (mkdir-p site)
              (for-each (lambda (file)
                          (copy-file file (string-append site (basename file))))
                        (find-files "python" "\\.py"))
              (copy-file "libsvm.so.2"
                         (string-append site "libsvm.so.2")))
            #t)))))
    (inputs
     `(("python" ,python)))
    (synopsis "Python bindings of libSVM")))

(define-public randomjungle
  (package
    (name "randomjungle")
    (version "2.1.0")
    (source
     (origin
       (method url-fetch)
       (uri (string-append
             "http://www.imbs-luebeck.de/imbs/sites/default/files/u59/"
             "randomjungle-" version ".tar_.gz"))
       (sha256
        (base32
         "12c8rf30cla71swx2mf4ww9mfd8jbdw5lnxd7dxhyw1ygrvg6y4w"))))
    (build-system gnu-build-system)
    (arguments
     `(#:configure-flags
       (list (string-append "--with-boost="
                            (assoc-ref %build-inputs "boost")))
       #:phases
       (modify-phases %standard-phases
         (add-before
          'configure 'set-CXXFLAGS
          (lambda _
            (setenv "CXXFLAGS" "-fpermissive ")
            #t)))))
    (inputs
     `(("boost" ,boost)
       ("gsl" ,gsl)
       ("libxml2" ,libxml2)
       ("zlib" ,zlib)))
    (native-inputs
     `(("gfortran" ,gfortran)))
    (home-page "http://www.imbs-luebeck.de/imbs/de/node/227/")
    (synopsis "Implementation of the Random Forests machine learning method")
    (description
     "Random Jungle is an implementation of Random Forests.  It is supposed to
analyse high dimensional data.  In genetics, it can be used for analysing big
Genome Wide Association (GWA) data.  Random Forests is a powerful machine
learning method.  Most interesting features are variable selection, missing
value imputation, classifier creation, generalization error estimation and
sample proximities between pairs of cases.")
    (license license:gpl3+)))

(define-public shogun
  (package
    (name "shogun")
    (version "4.0.0")
    (source
     (origin
       (method url-fetch)
       (uri (string-append
             "ftp://shogun-toolbox.org/shogun/releases/"
             (version-major+minor version)
             "/sources/shogun-" version ".tar.bz2"))
       (sha256
        (base32
         "159nlijnb7mnrv9za80wnm1shwvy45hgrqzn51hxy7gw4z6d6fdb"))
       (modules '((guix build utils)
                  (ice-9 rdelim)))
       (snippet
        '(begin
           ;; Remove non-free sources and files referencing them
           (for-each delete-file
                     (find-files "src/shogun/classifier/svm/"
                                 "SVMLight\\.(cpp|h)"))
           (for-each delete-file
                     (find-files "examples/undocumented/libshogun/"
                                 (string-append
                                  "(classifier_.*svmlight.*|"
                                  "evaluation_cross_validation_locked_comparison).cpp")))
           ;; Remove non-free functions.
           (define (delete-ifdefs file)
             (with-atomic-file-replacement file
               (lambda (in out)
                 (let loop ((line (read-line in 'concat))
                            (skipping? #f))
                   (if (eof-object? line)
                       #t
                       (let ((skip-next?
                              (or (and skipping?
                                       (not (string-prefix?
                                             "#endif //USE_SVMLIGHT" line)))
                                  (string-prefix?
                                   "#ifdef USE_SVMLIGHT" line))))
                         (when (or (not skipping?)
                                   (and skipping? (not skip-next?)))
                           (display line out))
                         (loop (read-line in 'concat) skip-next?)))))))
           (for-each delete-ifdefs (find-files "src/shogun/kernel/"
                                               "^Kernel\\.(cpp|h)"))))))
    (build-system cmake-build-system)
    (arguments
     '(#:tests? #f ;no check target
       #:phases
       (alist-cons-after
        'unpack 'delete-broken-symlinks
        (lambda _
          (for-each delete-file '("applications/arts/data"
                                  "applications/asp/data"
                                  "applications/easysvm/data"
                                  "applications/msplicer/data"
                                  "applications/ocr/data"
                                  "examples/documented/data"
                                  "examples/documented/matlab_static"
                                  "examples/documented/octave_static"
                                  "examples/undocumented/data"
                                  "examples/undocumented/matlab_static"
                                  "examples/undocumented/octave_static"
                                  "tests/integration/data"
                                  "tests/integration/matlab_static"
                                  "tests/integration/octave_static"
                                  "tests/integration/python_modular/tests"))
          #t)
        (alist-cons-after
         'unpack 'change-R-target-path
         (lambda* (#:key outputs #:allow-other-keys)
           (substitute* '("src/interfaces/r_modular/CMakeLists.txt"
                          "src/interfaces/r_static/CMakeLists.txt"
                          "examples/undocumented/r_modular/CMakeLists.txt")
             (("\\$\\{R_COMPONENT_LIB_PATH\\}")
              (string-append (assoc-ref outputs "out")
                             "/lib/R/library/")))
           #t)
         (alist-cons-after
          'unpack 'fix-octave-modules
          (lambda* (#:key outputs #:allow-other-keys)
            (substitute* '("src/interfaces/octave_modular/CMakeLists.txt"
                           "src/interfaces/octave_static/CMakeLists.txt")
              (("^include_directories\\(\\$\\{OCTAVE_INCLUDE_DIRS\\}")
               "include_directories(${OCTAVE_INCLUDE_DIRS} ${OCTAVE_INCLUDE_DIRS}/octave"))

            ;; change target directory
            (substitute* "src/interfaces/octave_modular/CMakeLists.txt"
              (("\\$\\{OCTAVE_OCT_LOCAL_API_FILE_DIR\\}")
               (string-append (assoc-ref outputs "out")
                              "/share/octave/packages")))
            #t)
          (alist-cons-before
           'build 'set-HOME
           ;; $HOME needs to be set at some point during the build phase
           (lambda _ (setenv "HOME" "/tmp") #t)
           %standard-phases))))
       #:configure-flags
       (list "-DCMAKE_BUILD_WITH_INSTALL_RPATH=TRUE"
             "-DUSE_SVMLIGHT=OFF" ;disable proprietary SVMLIGHT
             ;;"-DJavaModular=ON" ;requires unpackaged jblas
             ;;"-DRubyModular=ON" ;requires unpackaged ruby-narray
             ;;"-DPerlModular=ON" ;"FindPerlLibs" does not exist
             ;;"-DLuaModular=ON"  ;fails because lua doesn't build pkgconfig file
             "-DOctaveModular=ON"
             "-DOctaveStatic=ON"
             "-DPythonModular=ON"
             "-DPythonStatic=ON"
             "-DRModular=ON"
             "-DRStatic=ON"
             "-DCmdLineStatic=ON")))
    (inputs
     `(("python" ,python)
       ("numpy" ,python-numpy)
       ("r" ,r)
       ("octave" ,octave)
       ("swig" ,swig)
       ("hdf5" ,hdf5)
       ("atlas" ,atlas)
       ("arpack" ,arpack-ng)
       ("lapack" ,lapack)
       ("glpk" ,glpk)
       ("libxml2" ,libxml2)
       ("lzo" ,lzo)
       ("zlib" ,zlib)))
    (native-inputs
     `(("pkg-config" ,pkg-config)))
    ;; Non-portable SSE instructions are used so building fails on platforms
    ;; other than x86_64.
    (supported-systems '("x86_64-linux"))
    (home-page "http://shogun-toolbox.org/")
    (synopsis "Machine learning toolbox")
    (description
     "The Shogun Machine learning toolbox provides a wide range of unified and
efficient Machine Learning (ML) methods.  The toolbox seamlessly allows to
combine multiple data representations, algorithm classes, and general purpose
tools.  This enables both rapid prototyping of data pipelines and extensibility
in terms of new algorithms.")
    (license license:gpl3+)))

(define-public r-adaptivesparsity
  (package
    (name "r-adaptivesparsity")
    (version "1.4")
    (source (origin
              (method url-fetch)
              (uri (cran-uri "AdaptiveSparsity" version))
              (sha256
               (base32
                "1az7isvalf3kmdiycrfl6s9k9xqk22k1mc6rh8v0jmcz402qyq8z"))))
    (properties
     `((upstream-name . "AdaptiveSparsity")))
    (build-system r-build-system)
    (arguments
     `(#:phases
       (modify-phases %standard-phases
         (add-after 'unpack 'link-against-armadillo
           (lambda _
             (substitute* "src/Makevars"
               (("PKG_LIBS=" prefix)
                (string-append prefix "-larmadillo"))))))))
    (propagated-inputs
     `(("r-rcpp" ,r-rcpp)
       ("r-rcpparmadillo" ,r-rcpparmadillo)))
    (home-page "http://cran.r-project.org/web/packages/AdaptiveSparsity")
    (synopsis "Adaptive sparsity models")
    (description
     "This package implements the Figueiredo machine learning algorithm for
adaptive sparsity and the Wong algorithm for adaptively sparse gaussian
geometric models.")
    (license license:lgpl3+)))

(define-public r-nnet
  (package
    (name "r-nnet")
    (version "7.3-12")
    (source
     (origin
       (method url-fetch)
       (uri (cran-uri "nnet" version))
       (sha256
        (base32
         "17amqnw9dpap2w8ivx53hxha2xrm0drwfnj32li0xk41hlz548r7"))))
    (build-system r-build-system)
    (home-page "http://www.stats.ox.ac.uk/pub/MASS4/")
    (synopsis "Feed-forward neural networks and multinomial log-linear models")
    (description
     "This package provides functions for feed-forward neural networks with a
single hidden layer, and for multinomial log-linear models.")
    (license (list license:gpl2+ license:gpl3+))))
