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authorGlenn Johnson <glenn-johnson@uiowa.edu>2021-01-16 08:16:35 -0600
committerGitHub <noreply@github.com>2021-01-16 15:16:35 +0100
commit7c5ea8d3b458c28396d74e126329117862b367e1 (patch)
tree23c6cd58fd7e8f8a666a467b3b97a96fc8eabcf3
parent47a4727ac54950548b03fa2db0859eedf21f796c (diff)
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add version 2.4 to r-factominer (#20943)
-rw-r--r--var/spack/repos/builtin/packages/r-factominer/package.py16
1 files changed, 15 insertions, 1 deletions
diff --git a/var/spack/repos/builtin/packages/r-factominer/package.py b/var/spack/repos/builtin/packages/r-factominer/package.py
index a1071fcddf..4ec3de8676 100644
--- a/var/spack/repos/builtin/packages/r-factominer/package.py
+++ b/var/spack/repos/builtin/packages/r-factominer/package.py
@@ -7,12 +7,22 @@ from spack import *
class RFactominer(RPackage):
- """FactoMineR: Multivariate Exploratory Data Analysis and Data Mining"""
+ """Multivariate Exploratory Data Analysis and Data Mining
+
+ Exploratory data analysis methods to summarize, visualize and describe
+ datasets. The main principal component methods are available, those with
+ the largest potential in terms of applications: principal component
+ analysis (PCA) when variables are quantitative, correspondence analysis
+ (CA) and multiple correspondence analysis (MCA) when variables are
+ categorical, Multiple Factor Analysis when variables are structured in
+ groups, etc. and hierarchical cluster analysis. F. Husson, S. Le and J.
+ Pages (2017)."""
homepage = "http://factominer.free.fr"
url = "https://cloud.r-project.org/src/contrib/FactoMineR_1.35.tar.gz"
list_url = "https://cloud.r-project.org/src/contrib/Archive/FactoMineR"
+ version('2.4', sha256='b9e3adce9a66b4daccc85fa67cb0769d6be230beeb126921b386ccde5db2e851')
version('1.42', sha256='4cd9efb3681767c3bd48ddc3504ebead1493fcbbc0a9f759a00955b16c3481fa')
version('1.41', sha256='a9889d69e298b8a01e8d0a5a54260730e742c95681e367d759829aad9a8740c0')
version('1.40', sha256='68cb778fe7581b55666a5ae4aa7a5e7fa3ecbd133ae8cff1b2371a737b6d95e8')
@@ -22,11 +32,15 @@ class RFactominer(RPackage):
version('1.35', sha256='afe176fe561d1d16c5965ecb2b80ec90a56d0fbcd75c43ec8025a401a5b715a9')
depends_on('r@3.0.0:', type=('build', 'run'))
+ depends_on('r@3.5.0:', when='@2.4:', type=('build', 'run'))
depends_on('r-car', type=('build', 'run'))
depends_on('r-cluster', type=('build', 'run'))
+ depends_on('r-dt', when='@2.4:', type=('build', 'run'))
depends_on('r-ellipse', type=('build', 'run'))
depends_on('r-flashclust', type=('build', 'run'))
depends_on('r-lattice', type=('build', 'run'))
depends_on('r-leaps', type=('build', 'run'))
depends_on('r-mass', type=('build', 'run'))
depends_on('r-scatterplot3d', type=('build', 'run'))
+ depends_on('r-ggplot2', when='@2.4:', type=('build', 'run'))
+ depends_on('r-ggrepel', when='@2.4:', type=('build', 'run'))