New package - RStan

This PR creates the RStan package and its dependencies.

var/spack/repos/builtin/packages/r-stanheaders/package.py

@@ -0,0 +1,55 @@
+##############################################################################
+# 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 RStanheaders(Package):
+    """The C++ header files of the Stan project are provided by this package,
+    but it contains no R code, vignettes, or function documentation. There is a
+    shared object containing part of the CVODES library, but it is not
+    accessible from R. StanHeaders is only useful for developers who want to
+    utilize the LinkingTo directive of their package's DESCRIPTION file to
+    build on the Stan library without incurring unnecessary dependencies. The
+    Stan project develops a probabilistic programming language that implements
+    full or approximate Bayesian statistical inference via Markov Chain Monte
+    Carlo or variational methods and implements (optionally penalized) maximum
+    likelihood estimation via optimization. The Stan library includes an
+    advanced automatic differentiation scheme, templated statistical and linear
+    algebra functions that can handle the automatically differentiable scalar
+    types (and doubles, ints, etc.), and a parser for the Stan language. The
+    'rstan' package provides user-facing R functions to parse, compile, test,
+    estimate, and analyze Stan models."""
+
+    homepage = "http://mc-stan.org/"
+    url      = "https://cran.r-project.org/src/contrib/StanHeaders_2.10.0-2.tar.gz"
+    list_url = "https://cran.r-project.org/src/contrib/Archive/StanHeaders"
+
+    version('2.10.0-2', '9d09b1e9278f08768f7a988ad9082d57')
+
+    extends('R')
+
+    def install(self, spec, prefix):
+        R('CMD', 'INSTALL', '--library={0}'.format(self.module.r_lib_dir),
+          self.stage.source_path)