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authorGlenn Johnson <glenn-johnson@uiowa.edu>2021-01-17 13:47:11 -0600
committerGitHub <noreply@github.com>2021-01-17 13:47:11 -0600
commitc8e52aaa9c7925f8913087e277f200a9f3d33ba2 (patch)
tree144a272a6feb908fcec29d202812e3fbe3f54544
parentc204b94927000f6124d3ddf66bd932be70ecd1fe (diff)
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add version 4.1 to r-glmnet (#21025)
-rw-r--r--var/spack/repos/builtin/packages/r-glmnet/package.py8
1 files changed, 7 insertions, 1 deletions
diff --git a/var/spack/repos/builtin/packages/r-glmnet/package.py b/var/spack/repos/builtin/packages/r-glmnet/package.py
index 1a7e958ddf..c0a33c48a7 100644
--- a/var/spack/repos/builtin/packages/r-glmnet/package.py
+++ b/var/spack/repos/builtin/packages/r-glmnet/package.py
@@ -7,7 +7,9 @@ from spack import *
class RGlmnet(RPackage):
- """Extremely efficient procedures for fitting the entire lasso or
+ """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
@@ -18,9 +20,13 @@ class RGlmnet(RPackage):
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'))