0c0a1fdedc
* Add several new R packages * Add a few more R packages * Update more versions * Convert Package to RPackage * Add a few more packages * Add missing dependencies
56 lines
2.6 KiB
Python
56 lines
2.6 KiB
Python
##############################################################################
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# Copyright (c) 2013-2016, Lawrence Livermore National Security, LLC.
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# Produced at the Lawrence Livermore National Laboratory.
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#
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# This file is part of Spack.
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# Created by Todd Gamblin, tgamblin@llnl.gov, All rights reserved.
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# LLNL-CODE-647188
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#
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# For details, see https://github.com/llnl/spack
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# Please also see the LICENSE file for our notice and the LGPL.
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#
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# This program is free software; you can redistribute it and/or modify
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# it under the terms of the GNU Lesser General Public License (as
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# published by the Free Software Foundation) version 2.1, February 1999.
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#
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# This program 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 terms and
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# conditions of the GNU Lesser General Public License for more details.
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#
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# You should have received a copy of the GNU Lesser General Public
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# License along with this program; if not, write to the Free Software
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# Foundation, Inc., 59 Temple Place, Suite 330, Boston, MA 02111-1307 USA
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##############################################################################
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from spack import *
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class RXgboost(RPackage):
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"""Extreme Gradient Boosting, which is an efficient implementation of
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gradient boosting framework. This package is its R interface. The package
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includes efficient linear model solver and tree learning algorithms. The
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package can automatically do parallel computation on a single machine which
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could be more than 10 times faster than existing gradient boosting
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packages. It supports various objective functions, including regression,
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classification and ranking. The package is made to be extensible, so that
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users are also allowed to define their own objectives easily."""
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homepage = "https://github.com/dmlc/xgboost"
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url = "https://cran.r-project.org/src/contrib/xgboost_0.6-4.tar.gz"
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list_url = "https://cran.r-project.org/src/contrib/Archive/xgboost"
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version('0.6-4', '86e517e3ce39f8a01de796920f6b425e')
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version('0.4-4', 'c24d3076058101a71de4b8af8806697c')
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depends_on('r@3.3.0:')
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depends_on('r-matrix@1.1-0:', type=('build', 'run'))
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depends_on('r-data-table@1.9.6:', type=('build', 'run'))
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depends_on('r-magrittr@1.5:', type=('build', 'run'))
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depends_on('r-stringi@0.5.2:', type=('build', 'run'))
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# This is not listed as required, but installation fails without it
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# ERROR: dependency 'stringr' is not available for package 'xgboost'
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depends_on('r-stringr', type=('build', 'run'))
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