old_contents: # Copyright 2013-2021 Lawrence Livermore National Security, LLC and other
  # Spack Project Developers. See the top-level COPYRIGHT file for details.
  #
  # SPDX-License-Identifier: (Apache-2.0 OR MIT)
  
  from spack import *
  
  
  class RGlmnet(RPackage):
      """Extremely efficient procedures for fitting the entire lasso or
      elastic-net regularization path for linear regression, logistic and
      multinomial regression models, Poisson regression and the Cox model. Two
      recent additions are the multiple-response Gaussian, and the grouped
      multinomial. The algorithm uses cyclical coordinate descent in a path-wise
      fashion, as described in the paper linked to via the URL below."""
  
      homepage = "https://cloud.r-project.org/package=glmnet"
      url      = "https://cloud.r-project.org/src/contrib/glmnet_2.0-13.tar.gz"
      list_url = "https://cloud.r-project.org/src/contrib/Archive/glmnet"
  
      version('2.0-18', sha256='e8dce9d7b8105f9cc18ba981d420de64a53b09abee219660d3612915d554256b')
      version('2.0-13', sha256='f3288dcaddb2f7014d42b755bede6563f73c17bc87f8292c2ef7776cb9b9b8fd')
      version('2.0-5', sha256='2ca95352c8fbd93aa7800f3d972ee6c1a5fcfeabc6be8c10deee0cb457fd77b1')
  
      depends_on('r-matrix@1.0-6:', type=('build', 'run'))
      depends_on('r-foreach', type=('build', 'run'))
  
new_contents: # Copyright 2013-2021 Lawrence Livermore National Security, LLC and other
  # Spack Project Developers. See the top-level COPYRIGHT file for details.
  #
  # SPDX-License-Identifier: (Apache-2.0 OR MIT)
  
  from spack import *
  
  
  class RGlmnet(RPackage):
      """Lasso and Elastic-Net Regularized Generalized Linear Models
  
      Extremely efficient procedures for fitting the entire lasso or
      elastic-net regularization path for linear regression, logistic and
      multinomial regression models, Poisson regression and the Cox model. Two
      recent additions are the multiple-response Gaussian, and the grouped
      multinomial. The algorithm uses cyclical coordinate descent in a path-wise
      fashion, as described in the paper linked to via the URL below."""
  
      homepage = "https://cloud.r-project.org/package=glmnet"
      url      = "https://cloud.r-project.org/src/contrib/glmnet_2.0-13.tar.gz"
      list_url = "https://cloud.r-project.org/src/contrib/Archive/glmnet"
  
      version('4.1', sha256='8f0af50919f488789ecf261f6e0907f367d89fca812baa2f814054fb2d0e40cb')
      version('2.0-18', sha256='e8dce9d7b8105f9cc18ba981d420de64a53b09abee219660d3612915d554256b')
      version('2.0-13', sha256='f3288dcaddb2f7014d42b755bede6563f73c17bc87f8292c2ef7776cb9b9b8fd')
      version('2.0-5', sha256='2ca95352c8fbd93aa7800f3d972ee6c1a5fcfeabc6be8c10deee0cb457fd77b1')
  
      depends_on('r@3.6.0:', when='@4.1:', type=('build', 'run'))
      depends_on('r-matrix@1.0-6:', type=('build', 'run'))
      depends_on('r-foreach', type=('build', 'run'))
      depends_on('r-shape', when='@4.1:', type=('build', 'run'))
      depends_on('r-survival', when='@4.1:', type=('build', 'run'))
  
subject: add version 4.1 to r-glmnet (#21025)