;;; GNU Guix --- Functional package management for GNU
-;;; Copyright © 2015, 2016, 2017 Ricardo Wurmus <rekado@elephly.net>
+;;; Copyright © 2015, 2016, 2017, 2018 Ricardo Wurmus <rekado@elephly.net>
;;; Copyright © 2016 Efraim Flashner <efraim@flashner.co.il>
;;; Copyright © 2016, 2017 Marius Bakke <mbakke@fastmail.com>
;;; Copyright © 2016 Hartmut Goebel <h.goebel@crazy-compilers.com>
+;;; Copyright © 2018 Tobias Geerinckx-Rice <me@tobias.gr>
+;;; Copyright © 2018 Kei Kebreau <kkebreau@posteo.net>
+;;; Copyright © 2018 Mark Meyer <mark@ofosos.org>
+;;; Copyright © 2018 Ben Woodcroft <donttrustben@gmail.com>
+;;; Copyright © 2018 Fis Trivial <ybbs.daans@hotmail.com>
+;;; Copyright © 2018 Julien Lepiller <julien@lepiller.eu>
+;;; Copyright © 2018 Björn Höfling <bjoern.hoefling@bjoernhoefling.de>
;;;
;;; This file is part of GNU Guix.
;;;
#:use-module (guix build-system ocaml)
#:use-module (guix build-system python)
#:use-module (guix build-system r)
+ #:use-module (guix git-download)
#:use-module (gnu packages)
+ #:use-module (gnu packages algebra)
#:use-module (gnu packages autotools)
#:use-module (gnu packages boost)
#:use-module (gnu packages check)
#:use-module (gnu packages gcc)
#:use-module (gnu packages image)
#:use-module (gnu packages maths)
+ #:use-module (gnu packages mpi)
#:use-module (gnu packages ocaml)
+ #:use-module (gnu packages onc-rpc)
#:use-module (gnu packages perl)
#:use-module (gnu packages pkg-config)
#:use-module (gnu packages python)
+ #:use-module (gnu packages python-xyz)
#:use-module (gnu packages statistics)
#:use-module (gnu packages swig)
#:use-module (gnu packages xml)
#:use-module (gnu packages xorg))
+(define-public fann
+ ;; The last release is >100 commits behind, so we package from git.
+ (let ((commit "d71d54788bee56ba4cf7522801270152da5209d7"))
+ (package
+ (name "fann")
+ (version (string-append "2.2.0-1." (string-take commit 8)))
+ (source (origin
+ (method git-fetch)
+ (uri (git-reference
+ (url "https://github.com/libfann/fann.git")
+ (commit commit)))
+ (file-name (string-append name "-" version "-checkout"))
+ (sha256
+ (base32
+ "0ibwpfrjs6q2lijs8slxjgzb2llcl6rk3v2ski4r6215g5jjhg3x"))))
+ (build-system cmake-build-system)
+ (arguments
+ `(#:phases
+ (modify-phases %standard-phases
+ (replace 'check
+ (lambda* (#:key outputs #:allow-other-keys)
+ (let* ((out (assoc-ref outputs "out")))
+ (with-directory-excursion (string-append (getcwd) "/tests")
+ (invoke "./fann_tests"))))))))
+ (home-page "http://leenissen.dk/fann/wp/")
+ (synopsis "Fast Artificial Neural Network")
+ (description
+ "FANN is a free open source neural network library, which implements
+multilayer artificial neural networks in C with support for both fully
+connected and sparsely connected networks.")
+ (license license:lgpl2.1))))
+
(define-public libsvm
(package
(name "libsvm")
- (version "3.20")
+ (version "3.22")
(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"))
+ (uri (string-append "https://www.csie.ntu.edu.tw/~cjlin/libsvm/"
+ name "-" version ".tar.gz"))
(sha256
(base32
- "1jpjlql3frjza7zxzrqqr2firh44fjb8fqsdmvz6bjz7sb47zgp4"))))
+ "0zd7s19y5vb7agczl6456bn45cj1y64739sslaskw1qk7dywd0bd"))))
(build-system gnu-build-system)
(arguments
`(#:tests? #f ;no "check" target
#:phases (modify-phases %standard-phases
(delete 'configure)
(replace
- 'install
+ 'install ; no ‘install’ target
(lambda* (#:key outputs #:allow-other-keys)
(let* ((out (assoc-ref outputs "out"))
(bin (string-append out "/bin/")))
(modify-phases %standard-phases
(delete 'configure)
(replace
- 'install
+ 'install ; no ‘install’ target
(lambda* (#:key inputs outputs #:allow-other-keys)
(let ((site (string-append (assoc-ref outputs "out")
"/lib/python"
#t))
(add-after 'disable-broken-tests 'autogen
(lambda _
- (zero? (system* "bash" "autogen.sh")))))))
+ (invoke "bash" "autogen.sh"))))))
(inputs
`(("python" ,python-2) ; only Python 2 is supported
("libxml2" ,libxml2)))
"1l5jbhwjpsj38x8b9698hfpkv75h8hn3kj0gihjhn8ym2cwwv110"))))
(build-system ocaml-build-system)
(arguments
- `(#:phases
+ `(#:ocaml ,ocaml-4.02
+ #:findlib ,ocaml4.02-findlib
+ #:phases
(modify-phases %standard-phases
(add-before 'configure 'patch-paths
(lambda _
(origin
(method url-fetch)
(uri (string-append
- "http://www.imbs-luebeck.de/imbs/sites/default/files/u59/"
- "randomjungle-" version ".tar_.gz"))
+ "https://www.imbs.uni-luebeck.de/fileadmin/files/Software"
+ "/randomjungle/randomjungle-" version ".tar_.gz"))
+ (patches (search-patches "randomjungle-disable-static-build.patch"))
(sha256
(base32
"12c8rf30cla71swx2mf4ww9mfd8jbdw5lnxd7dxhyw1ygrvg6y4w"))))
(build-system gnu-build-system)
(arguments
`(#:configure-flags
- (list (string-append "--with-boost="
+ (list "--disable-static"
+ (string-append "--with-boost="
(assoc-ref %build-inputs "boost")))
#:phases
(modify-phases %standard-phases
;; Non-portable assembly instructions are used so building fails on
;; platforms other than x86_64 or i686.
(supported-systems '("x86_64-linux" "i686-linux"))
- (home-page "http://www.imbs-luebeck.de/imbs/de/node/227/")
+ (home-page "https://www.imbs.uni-luebeck.de/forschung/software/details.html#c224")
(synopsis "Implementation of the Random Forests machine learning method")
(description
"Random Jungle is an implementation of Random Forests. It is supposed to
(define-public shogun
(package
(name "shogun")
- (version "4.0.0")
+ (version "6.1.3")
(source
(origin
(method url-fetch)
"/sources/shogun-" version ".tar.bz2"))
(sha256
(base32
- "159nlijnb7mnrv9za80wnm1shwvy45hgrqzn51hxy7gw4z6d6fdb"))
+ "1rn9skm3nw6hr7mr3lgp2gfqhi7ii0lyxck7qmqnf8avq349s5jp"))
(modules '((guix build utils)
(ice-9 rdelim)))
(snippet
(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)"))))))
+ (for-each delete-ifdefs
+ (append
+ (find-files "src/shogun/classifier/mkl"
+ "^MKLClassification\\.cpp")
+ (find-files "src/shogun/classifier/svm"
+ "^SVMLightOneClass\\.(cpp|h)")
+ (find-files "src/shogun/multiclass"
+ "^ScatterSVM\\.(cpp|h)")
+ (find-files "src/shogun/kernel/"
+ "^(Kernel|CombinedKernel|ProductKernel)\\.(cpp|h)")
+ (find-files "src/shogun/regression/svr"
+ "^(MKLRegression|SVRLight)\\.(cpp|h)")
+ (find-files "src/shogun/transfer/domain_adaptation"
+ "^DomainAdaptationSVM\\.(cpp|h)")))
+ #t))))
(build-system cmake-build-system)
(arguments
'(#:tests? #f ;no check target
"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"))
+ "examples/meta/data"
+ "examples/undocumented/data"))
#t))
(add-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")
+ (substitute* '("src/interfaces/r/CMakeLists.txt"
+ "examples/meta/r/CMakeLists.txt")
(("\\$\\{R_COMPONENT_LIB_PATH\\}")
(string-append (assoc-ref outputs "out")
"/lib/R/library/")))
#t))
(add-after 'unpack 'fix-octave-modules
(lambda* (#:key outputs #:allow-other-keys)
- (substitute* '("src/interfaces/octave_modular/CMakeLists.txt"
- "src/interfaces/octave_static/CMakeLists.txt")
+ (substitute* "src/interfaces/octave/CMakeLists.txt"
(("^include_directories\\(\\$\\{OCTAVE_INCLUDE_DIRS\\}")
- "include_directories(${OCTAVE_INCLUDE_DIRS} ${OCTAVE_INCLUDE_DIRS}/octave"))
-
- ;; change target directory
- (substitute* "src/interfaces/octave_modular/CMakeLists.txt"
+ "include_directories(${OCTAVE_INCLUDE_DIRS} ${OCTAVE_INCLUDE_DIRS}/octave")
+ ;; change target directory
(("\\$\\{OCTAVE_OCT_LOCAL_API_FILE_DIR\\}")
(string-append (assoc-ref outputs "out")
"/share/octave/packages")))
+ (substitute* '("src/interfaces/octave/swig_typemaps.i"
+ "src/interfaces/octave/sg_print_functions.cpp")
+ ;; "octave/config.h" and "octave/oct-obj.h" deprecated in Octave.
+ (("octave/config\\.h") "octave/octave-config.h")
+ (("octave/oct-obj.h") "octave/ovl.h"))
#t))
+ (add-after 'unpack 'move-rxcpp
+ (lambda* (#:key inputs #:allow-other-keys)
+ (let ((rxcpp-dir "shogun/third-party/rxcpp"))
+ (mkdir-p rxcpp-dir)
+ (install-file (assoc-ref inputs "rxcpp") rxcpp-dir)
+ #t)))
(add-before 'build 'set-HOME
;; $HOME needs to be set at some point during the build phase
(lambda _ (setenv "HOME" "/tmp") #t)))
#: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")))
+ "-DBUILD_META_EXAMPLES=OFF" ;requires unpackaged ctags
+ ;;"-DINTERFACE_JAVA=ON" ;requires unpackaged jblas
+ ;;"-DINTERFACE_RUBY=ON" ;requires unpackaged ruby-narray
+ ;;"-DINTERFACE_PERL=ON" ;"FindPerlLibs" does not exist
+ ;;"-DINTERFACE_LUA=ON" ;fails because lua doesn't build pkgconfig file
+ "-DINTERFACE_OCTAVE=ON"
+ "-DINTERFACE_PYTHON=ON"
+ "-DINTERFACE_R=ON")))
(inputs
`(("python" ,python)
("numpy" ,python-numpy)
("r-minimal" ,r-minimal)
- ("octave" ,octave)
+ ("octave" ,octave-cli)
("swig" ,swig)
+ ("eigen" ,eigen)
("hdf5" ,hdf5)
("atlas" ,atlas)
("arpack" ,arpack-ng)
("lzo" ,lzo)
("zlib" ,zlib)))
(native-inputs
- `(("pkg-config" ,pkg-config)))
+ `(("pkg-config" ,pkg-config)
+ ("rxcpp" ,rxcpp)))
;; Non-portable SSE instructions are used so building fails on platforms
;; other than x86_64.
(supported-systems '("x86_64-linux"))
in terms of new algorithms.")
(license license:gpl3+)))
+(define-public rxcpp
+ (package
+ (name "rxcpp")
+ (version "4.0.0")
+ (source
+ (origin
+ (method url-fetch)
+ (uri (string-append "https://github.com/ReactiveX/RxCpp/archive/v"
+ version ".tar.gz"))
+ (sha256
+ (base32
+ "0y2isr8dy2n1yjr9c5570kpc9lvdlch6jv0jvw000amwn5d3krsh"))
+ (file-name (string-append name "-" version ".tar.gz"))))
+ (build-system cmake-build-system)
+ (arguments
+ `(#:phases
+ (modify-phases %standard-phases
+ (add-after 'unpack 'remove-werror
+ (lambda _
+ (substitute* (find-files ".")
+ (("-Werror") ""))
+ #t))
+ (replace 'check
+ (lambda _
+ (invoke "ctest"))))))
+ (native-inputs
+ `(("catch" ,catch-framework)))
+ (home-page "http://reactivex.io/")
+ (synopsis "Reactive Extensions for C++")
+ (description
+ "The Reactive Extensions for C++ (RxCpp) is a library of algorithms for
+values-distributed-in-time. ReactiveX is a library for composing asynchronous
+and event-based programs by using observable sequences.
+
+It extends the observer pattern to support sequences of data and/or events and
+adds operators that allow you to compose sequences together declaratively while
+abstracting away concerns about things like low-level threading,
+synchronization, thread-safety, concurrent data structures, and non-blocking
+I/O.")
+ (license license:asl2.0)))
+
(define-public r-adaptivesparsity
(package
(name "r-adaptivesparsity")
- (version "1.4")
+ (version "1.6")
(source (origin
(method url-fetch)
(uri (cran-uri "AdaptiveSparsity" version))
(sha256
(base32
- "1az7isvalf3kmdiycrfl6s9k9xqk22k1mc6rh8v0jmcz402qyq8z"))))
+ "0imr5m8mll9j6n4icsv6z9rl5kbnwsp9wvzrg7n90nnmcxq2cz91"))))
(properties
`((upstream-name . "AdaptiveSparsity")))
(build-system r-build-system)
(("PKG_LIBS=" prefix)
(string-append prefix "-larmadillo"))))))))
(propagated-inputs
- `(("r-rcpp" ,r-rcpp)
+ `(("r-mass" ,r-mass)
+ ("r-matrix" ,r-matrix)
+ ("r-rcpp" ,r-rcpp)
("r-rcpparmadillo" ,r-rcpparmadillo)))
(inputs
`(("armadillo" ,armadillo)))
- (home-page "http://cran.r-project.org/web/packages/AdaptiveSparsity")
+ (home-page "https://cran.r-project.org/web/packages/AdaptiveSparsity")
(synopsis "Adaptive sparsity models")
(description
"This package implements the Figueiredo machine learning algorithm for
(define-public r-kernlab
(package
(name "r-kernlab")
- (version "0.9-25")
+ (version "0.9-27")
(source
(origin
(method url-fetch)
(uri (cran-uri "kernlab" version))
(sha256
(base32
- "0qnaq9x3j2xc6jrmmd98wc6hkzch487s4p3a9lnc00xvahkhgpmr"))))
+ "1m0xqf6gyvwayz7w3c83y32ayvnlz0jicj8ijk808zq9sh7dbbgn"))))
(build-system r-build-system)
- (home-page "http://cran.r-project.org/web/packages/kernlab")
+ (home-page "https://cran.r-project.org/web/packages/kernlab")
(synopsis "Kernel-based machine learning tools")
(description
"This package provides kernel-based machine learning methods for
#t))))
(build-system cmake-build-system)
(arguments
- ;; Recent releases defaults to "lib64" on 64bit.
- `(#:configure-flags (list (string-append "-DCMAKE_INSTALL_LIBDIR="
- (assoc-ref %outputs "out")
- "/lib"))
- #:phases
+ `(#:phases
(modify-phases %standard-phases
(add-after 'unpack 'disable-asserts
(lambda _
;; No test target, so we build and run the unit tests here.
(let ((test-dir (string-append "../dlib-" ,version "/dlib/test")))
(with-directory-excursion test-dir
- (and (zero? (system* "make" "-j" (number->string (parallel-job-count))))
- (zero? (system* "./dtest" "--runall")))))))
+ (invoke "make" "-j" (number->string (parallel-job-count)))
+ (invoke "./dtest" "--runall"))
+ #t)))
(add-after 'install 'delete-static-library
(lambda* (#:key outputs #:allow-other-keys)
(delete-file (string-append (assoc-ref outputs "out")
"/lib/libdlib.a"))
#t)))))
(native-inputs
- `(("pkg-config" ,pkg-config)))
+ `(("pkg-config" ,pkg-config)
+ ;; For tests.
+ ("libnsl" ,libnsl)))
(inputs
`(("giflib" ,giflib)
("lapack" ,lapack)
(define-public python-scikit-learn
(package
(name "python-scikit-learn")
- (version "0.19.1")
+ (version "0.20.1")
(source
(origin
- (method url-fetch)
- (uri (string-append
- "https://github.com/scikit-learn/scikit-learn/archive/"
- version ".tar.gz"))
- (file-name (string-append name "-" version ".tar.gz"))
+ (method git-fetch)
+ (uri (git-reference
+ (url "https://github.com/scikit-learn/scikit-learn.git")
+ (commit version)))
+ (file-name (git-file-name name version))
(sha256
(base32
- "18n8775kyfwbvcjjjzda9c5sqy4737c0hrmj6qj1ps2jmlqzair9"))))
+ "0fkhwg3xn1s7ln9q1szq6kwc4jhwvjh8w4kmv9wcrqy7cq3lbv0d"))))
(build-system python-build-system)
(arguments
`(#:phases
(modify-phases %standard-phases
- (delete 'check)
- (add-after 'install 'check
- ;; Running tests from the source directory requires
- ;; an "inplace" build with paths relative to CWD.
- ;; http://scikit-learn.org/stable/developers/advanced_installation.html#testing
- ;; Use the installed version instead.
- (lambda* (#:key inputs outputs #:allow-other-keys)
- (add-installed-pythonpath inputs outputs)
- ;; some tests require access to "$HOME"
+ (add-after 'build 'build-ext
+ (lambda _ (invoke "python" "setup.py" "build_ext" "--inplace") #t))
+ (replace 'check
+ (lambda _
+ ;; Restrict OpenBLAS threads to prevent segfaults while testing!
+ (setenv "OPENBLAS_NUM_THREADS" "1")
+
+ ;; Some tests require write access to $HOME.
(setenv "HOME" "/tmp")
- ;; Step out of the source directory just to be sure.
- (chdir "..")
- (zero? (system* "nosetests" "-v" "sklearn")))))))
+
+ (invoke "pytest" "sklearn" "-m" "not network")))
+ ;; FIXME: This fails with permission denied
+ (delete 'reset-gzip-timestamps))))
(inputs
`(("openblas" ,openblas)))
(native-inputs
- `(("python-nose" ,python-nose)
+ `(("python-pytest" ,python-pytest)
+ ("python-pandas" ,python-pandas) ;for tests
("python-cython" ,python-cython)))
(propagated-inputs
`(("python-numpy" ,python-numpy)
(home-page "http://scikit-learn.org/")
(synopsis "Machine Learning in Python")
(description
- "Scikit-learn provides simple and efficient tools for data
-mining and data analysis.")
+ "Scikit-learn provides simple and efficient tools for data mining and
+data analysis.")
(license license:bsd-3)))
(define-public python2-scikit-learn
(package-with-python2 python-scikit-learn))
+
+(define-public python-autograd
+ (let* ((commit "442205dfefe407beffb33550846434baa90c4de7")
+ (revision "0")
+ (version (git-version "0.0.0" revision commit)))
+ (package
+ (name "python-autograd")
+ (home-page "https://github.com/HIPS/autograd")
+ (source (origin
+ (method git-fetch)
+ (uri (git-reference
+ (url home-page)
+ (commit commit)))
+ (sha256
+ (base32
+ "189sv2xb0mwnjawa9z7mrgdglc1miaq93pnck26r28fi1jdwg0z4"))
+ (file-name (git-file-name name version))))
+ (version version)
+ (build-system python-build-system)
+ (native-inputs
+ `(("python-nose" ,python-nose)
+ ("python-pytest" ,python-pytest)))
+ (propagated-inputs
+ `(("python-future" ,python-future)
+ ("python-numpy" ,python-numpy)))
+ (arguments
+ `(#:phases (modify-phases %standard-phases
+ (replace 'check
+ (lambda _
+ (invoke "py.test" "-v"))))))
+ (synopsis "Efficiently computes derivatives of NumPy code")
+ (description "Autograd can automatically differentiate native Python and
+NumPy code. It can handle a large subset of Python's features, including loops,
+ifs, recursion and closures, and it can even take derivatives of derivatives
+of derivatives. It supports reverse-mode differentiation
+(a.k.a. backpropagation), which means it can efficiently take gradients of
+scalar-valued functions with respect to array-valued arguments, as well as
+forward-mode differentiation, and the two can be composed arbitrarily. The
+main intended application of Autograd is gradient-based optimization.")
+ (license license:expat))))
+
+(define-public python2-autograd
+ (package-with-python2 python-autograd))
+
+(define-public lightgbm
+ (package
+ (name "lightgbm")
+ (version "2.0.12")
+ (source (origin
+ (method url-fetch)
+ (uri (string-append
+ "https://github.com/Microsoft/LightGBM/archive/v"
+ version ".tar.gz"))
+ (sha256
+ (base32
+ "132zf0yk0545mg72hyzxm102g3hpb6ixx9hnf8zd2k55gas6cjj1"))
+ (file-name (string-append name "-" version ".tar.gz"))))
+ (native-inputs
+ `(("python-pytest" ,python-pytest)
+ ("python-nose" ,python-nose)))
+ (inputs
+ `(("openmpi" ,openmpi)))
+ (propagated-inputs
+ `(("python-numpy" ,python-numpy)
+ ("python-scipy" ,python-scipy)))
+ (arguments
+ `(#:configure-flags
+ '("-DUSE_MPI=ON")
+ #:phases
+ (modify-phases %standard-phases
+ (replace 'check
+ (lambda* (#:key outputs #:allow-other-keys)
+ (with-directory-excursion ,(string-append "../LightGBM-" version)
+ (invoke "pytest" "tests/c_api_test/test_.py")))))))
+ (build-system cmake-build-system)
+ (home-page "https://github.com/Microsoft/LightGBM")
+ (synopsis "Gradient boosting framework based on decision tree algorithms")
+ (description "LightGBM is a gradient boosting framework that uses tree
+based learning algorithms. It is designed to be distributed and efficient with
+the following advantages:
+
+@itemize
+@item Faster training speed and higher efficiency
+@item Lower memory usage
+@item Better accuracy
+@item Parallel and GPU learning supported (not enabled in this package)
+@item Capable of handling large-scale data
+@end itemize\n")
+ (license license:expat)))
+
+(define-public vowpal-wabbit
+ ;; Language bindings not included.
+ (package
+ (name "vowpal-wabbit")
+ (version "8.5.0")
+ (source (origin
+ (method url-fetch)
+ (uri (string-append
+ "https://github.com/JohnLangford/vowpal_wabbit/archive/"
+ version ".tar.gz"))
+ (sha256
+ (base32
+ "0clp2kb7rk5sckhllxjr5a651awf4s8dgzg4659yh4hf5cqnf0gr"))
+ (file-name (string-append name "-" version ".tar.gz"))))
+ (inputs
+ `(("boost" ,boost)
+ ("zlib" ,zlib)))
+ (arguments
+ `(#:configure-flags
+ (list (string-append "--with-boost="
+ (assoc-ref %build-inputs "boost")))))
+ (build-system gnu-build-system)
+ (home-page "https://github.com/JohnLangford/vowpal_wabbit")
+ (synopsis "Fast machine learning library for online learning")
+ (description "Vowpal Wabbit is a machine learning system with techniques
+such as online, hashing, allreduce, reductions, learning2search, active, and
+interactive learning.")
+ (license license:bsd-3)))
+
+(define-public python2-fastlmm
+ (package
+ (name "python2-fastlmm")
+ (version "0.2.21")
+ (source
+ (origin
+ (method url-fetch)
+ (uri (pypi-uri "fastlmm" version ".zip"))
+ (sha256
+ (base32
+ "1q8c34rpmwkfy3r4d5172pzdkpfryj561897z9r3x22gq7813x1m"))))
+ (build-system python-build-system)
+ (arguments
+ `(#:python ,python-2)) ; only Python 2.7 is supported
+ (propagated-inputs
+ `(("python2-numpy" ,python2-numpy)
+ ("python2-scipy" ,python2-scipy)
+ ("python2-matplotlib" ,python2-matplotlib)
+ ("python2-pandas" ,python2-pandas)
+ ("python2-scikit-learn" ,python2-scikit-learn)
+ ("python2-pysnptools" ,python2-pysnptools)))
+ (native-inputs
+ `(("unzip" ,unzip)
+ ("python2-cython" ,python2-cython)
+ ("python2-mock" ,python2-mock)
+ ("python2-nose" ,python2-nose)))
+ (home-page "http://research.microsoft.com/en-us/um/redmond/projects/mscompbio/fastlmm/")
+ (synopsis "Perform genome-wide association studies on large data sets")
+ (description
+ "FaST-LMM, which stands for Factored Spectrally Transformed Linear Mixed
+Models, is a program for performing both single-SNP and SNP-set genome-wide
+association studies (GWAS) on extremely large data sets.")
+ (license license:asl2.0)))
HCoop / jackhill / guix / guix.git / blobdiff