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-rw-r--r-- | var/spack/repos/builtin/packages/r-xgboost/package.py | 54 |
1 files changed, 54 insertions, 0 deletions
diff --git a/var/spack/repos/builtin/packages/r-xgboost/package.py b/var/spack/repos/builtin/packages/r-xgboost/package.py new file mode 100644 index 0000000000..458045ff74 --- /dev/null +++ b/var/spack/repos/builtin/packages/r-xgboost/package.py @@ -0,0 +1,54 @@ +############################################################################## +# Copyright (c) 2013-2016, Lawrence Livermore National Security, LLC. +# Produced at the Lawrence Livermore National Laboratory. +# +# This file is part of Spack. +# Created by Todd Gamblin, tgamblin@llnl.gov, All rights reserved. +# LLNL-CODE-647188 +# +# For details, see https://github.com/llnl/spack +# Please also see the LICENSE file for our notice and the LGPL. +# +# This program is free software; you can redistribute it and/or modify +# it under the terms of the GNU Lesser General Public License (as +# published by the Free Software Foundation) version 2.1, February 1999. +# +# This program 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 terms and +# conditions of the GNU Lesser General Public License for more details. +# +# You should have received a copy of the GNU Lesser General Public +# License along with this program; if not, write to the Free Software +# Foundation, Inc., 59 Temple Place, Suite 330, Boston, MA 02111-1307 USA +############################################################################## + +from spack import * + + +class RXgboost(Package): + """Extreme Gradient Boosting, which is an efficient implementation of + gradient boosting framework. This package is its R interface. The package + includes efficient linear model solver and tree learning algorithms. The + package can automatically do parallel computation on a single machine which + could be more than 10 times faster than existing gradient boosting + packages. It supports various objective functions, including regression, + classification and ranking. The package is made to be extensible, so that + users are also allowed to define their own objectives easily.""" + + homepage = "https://github.com/dmlc/xgboost" + url = "https://cran.r-project.org/src/contrib/xgboost_0.4-4.tar.gz" + list_url = "https://cran.r-project.org/src/contrib/Archive/xgboost" + + version('0.4-4', 'c24d3076058101a71de4b8af8806697c') + + extends('R') + + depends_on('r-matrix', type=nolink) + depends_on('r-datatable', type=nolink) + depends_on('r-magrittr', type=nolink) + depends_on('r-stringr', type=nolink) + + def install(self, spec, prefix): + R('CMD', 'INSTALL', '--library={0}'.format(self.module.r_lib_dir), + self.stage.source_path) |