File R-bestNormalize.spec of Package R-bestNormalize

# Automatically generated by CRAN2OBS
# 
# Spec file for package bestNormalize 
# This file is auto-generated using information in the package source, 
# esp. Description and Summary. Improvements in that area should be 
# discussed with upstream. 
# 
# Copyright (c) 2026 SUSE LINUX GmbH, Nuernberg, Germany. 
# 
# All modifications and additions to the file contributed by third parties 
# remain the property of their copyright owners, unless otherwise agreed 
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# license that conforms to the Open Source Definition (Version 1.9) 
# published by the Open Source Initiative. 
#  
# Please submit bugfixes or comments via http://bugs.opensuse.org/ 
# 
 
%global packname  bestNormalize 
%global rlibdir   %{_libdir}/R/library 
 
Name:           R-%{packname} 
Version:        1.9.2 
Release:        0 
Summary:        Normalizing Transformation Functions 
Group:          Development/Libraries/Other 
License:        GPL-3 
URL:            http://cran.r-project.org/web/packages/%{packname} 
Source:         bestNormalize_1.9.2.tar.gz 
Requires:       R-base 
Requires:	R-LambertW
Requires:	R-nortest
Requires:	R-dplyr
Requires:	R-doParallel
Requires:	R-foreach
Requires:	R-doRNG
Requires:	R-recipes
Requires:	R-tibble
Requires:	R-butcher
Requires:	R-purrr
Requires:	R-progress
Requires:	R-generics
Requires:	R-cli
Requires:	R-lobstr
Requires:	R-rlang
Requires:	R-vctrs
Requires:	R-iterators
Requires:	R-rngtools
Requires:	R-glue
Requires:	R-lifecycle
Requires:	R-magrittr
Requires:	R-pillar
Requires:	R-R6
Requires:	R-tidyselect
Requires:	R-ggplot2
Requires:	R-lamW
Requires:	R-RColorBrewer
Requires:	R-reshape2
Requires:	R-Rcpp
Requires:	R-crayon
Requires:	R-hms
Requires:	R-prettyunits
Requires:	R-clock
Requires:	R-gower
Requires:	R-hardhat
Requires:	R-ipred
Requires:	R-lubridate
Requires:	R-sparsevctrs
Requires:	R-tidyr
Requires:	R-timeDate
Requires:	R-withr
Requires:	R-pkgconfig
Requires:	R-tzdb
Requires:	R-cpp11
Requires:	R-gtable
Requires:	R-isoband
Requires:	R-S7
Requires:	R-scales
Requires:	R-prodlim
Requires:	R-RcppParallel
Requires:	R-timechange
Requires:	R-utf8
Requires:	R-plyr
Requires:	R-stringr
Requires:	R-digest
Requires:	R-data.table
Requires:	R-diagram
Requires:	R-lava
Requires:	R-farver
Requires:	R-labeling
Requires:	R-viridisLite
Requires:	R-stringi
Requires:	R-shape
Requires:	R-future.apply
Requires:	R-numDeriv
Requires:	R-progressr
Requires:	R-SQUAREM
Requires:	R-future
Requires:	R-globals
Requires:	R-listenv
Requires:	R-parallelly
 
# %%if 0%%{?sle_version} > 120400 || 0%%{?is_opensuse} 
# # Three others commonly needed 
# BuildRequires:  tex(ae.sty) 
# BuildRequires:  tex(fancyvrb.sty) 
# BuildRequires:  tex(inconsolata.sty) 
# BuildRequires:  tex(natbib.sty) 
# %else 
# BuildRequires:  texlive 
# %endif 
# BuildRequires:  texinfo 
BuildRequires:  fdupes 
BuildRequires:  R-base 
BuildRequires: 	R-LambertW
BuildRequires: 	R-nortest
BuildRequires: 	R-dplyr
BuildRequires: 	R-doParallel
BuildRequires: 	R-foreach
BuildRequires: 	R-doRNG
BuildRequires: 	R-recipes
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BuildRequires: 	R-purrr
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BuildRequires: 	R-iterators
BuildRequires: 	R-rngtools
BuildRequires: 	R-glue
BuildRequires: 	R-lifecycle
BuildRequires: 	R-magrittr
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BuildRequires: 	R-R6
BuildRequires: 	R-tidyselect
BuildRequires: 	R-ggplot2
BuildRequires: 	R-lamW
BuildRequires: 	R-RColorBrewer
BuildRequires: 	R-reshape2
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BuildRequires: 	R-crayon
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BuildRequires: 	R-prettyunits
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BuildRequires: 	R-progressr
BuildRequires: 	R-SQUAREM
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BuildRequires: 	R-globals
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BuildRequires: 	R-parallelly
 
Suggests:	R-knitr
Suggests:	R-rmarkdown
Suggests:	R-testthat
Suggests:	R-ggplot2
Suggests:	R-scales
Suggests:	R-rlang
Suggests:	R-covr
%description 
Estimate a suite of normalizing transformations, including a new 
adaptation of a technique based on ranks which can guarantee normally 
distributed transformed data if there are no ties: ordered quantile 
normalization (ORQ). ORQ normalization combines a rank-mapping approach 
with a shifted logit approximation that allows the transformation to 
work on data outside the original domain. It is also able to handle new 
data within the original domain via linear interpolation. The package 
is built to estimate the best normalizing transformation for a vector 
consistently and accurately. It implements the Box-Cox transformation, 
the Yeo-Johnson transformation, three types of Lambert WxF 
transformations, and the ordered quantile normalization transformation. 
It estimates the normalization efficacy of other commonly used 
transformations, and it allows users to specify custom transformations 
or normalization statistics. Finally, functionality can be integrated 
into a machine learning workflow via recipes. 
 
%prep 
%setup -q -c -n %{packname} 
# the next line is needed, because we build without --clean in between two packages 
rm -rf ~/.R  
 
 
%build 
 
%install 
mkdir -p %{buildroot}%{rlibdir} 
%{_bindir}/R CMD INSTALL -l %{buildroot}%{rlibdir} %{packname} 
test -d %{packname}/src && (cd %{packname}/src; rm -f *.o *.so) 
rm -f %{buildroot}%{rlibdir}/R.css 
%fdupes -s %{buildroot}%{rlibdir} 
 
#%%check 
#%%{_bindir}/R CMD check %%{packname} 
 
%files 
%dir %{rlibdir}/%{packname} 
%{rlibdir}/%{packname}/CITATION
%doc %{rlibdir}/%{packname}/DESCRIPTION
%{rlibdir}/%{packname}/INDEX
%{rlibdir}/%{packname}/Meta
%{rlibdir}/%{packname}/NAMESPACE
%doc %{rlibdir}/%{packname}/NEWS.md
%{rlibdir}/%{packname}/R
%{rlibdir}/%{packname}/data
%{rlibdir}/%{packname}/doc
%doc %{rlibdir}/%{packname}/help
%doc %{rlibdir}/%{packname}/html
 
%changelog