File R-rmweather.spec of Package R-rmweather

# Automatically generated by CRAN2OBS
# 
# Spec file for package rmweather 
# 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) 2025 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 
# upon. The license for this file, and modifications and additions to the 
# file, is the same license as for the pristine package itself (unless the 
# license for the pristine package is not an Open Source License, in which 
# case the license is the MIT License). An "Open Source License" is a 
# 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  rmweather 
%global rlibdir   %{_libdir}/R/library 
 
Name:           R-%{packname} 
Version:        0.2.63 
Release:        0 
Summary:        Tools to Conduct Meteorological Normalisation and Counterfactual Modelling for Air Quality Data 
Group:          Development/Libraries/Other 
License:        GPL-3 | file LICENSE 
URL:            http://cran.r-project.org/web/packages/%{packname} 
Source:         rmweather_0.2.63.tar.gz 
Requires:       R-base 
Requires:	R-dplyr
Requires:	R-ggplot2
Requires:	R-lubridate
Requires:	R-magrittr
Requires:	R-pdp
Requires:	R-purrr
Requires:	R-ranger
Requires:	R-stringr
Requires:	R-strucchange
Requires:	R-tibble
Requires:	R-viridis
Requires:	R-tidyr
Requires:	R-cli
Requires:	R-generics
Requires:	R-glue
Requires:	R-lifecycle
Requires:	R-pillar
Requires:	R-R6
Requires:	R-rlang
Requires:	R-tidyselect
Requires:	R-vctrs
Requires:	R-gtable
Requires:	R-isoband
Requires:	R-S7
Requires:	R-scales
Requires:	R-withr
Requires:	R-timechange
Requires:	R-foreach
Requires:	R-Rcpp
Requires:	R-RcppEigen
Requires:	R-stringi
Requires:	R-zoo
Requires:	R-sandwich
Requires:	R-pkgconfig
Requires:	R-cpp11
Requires:	R-viridisLite
Requires:	R-gridExtra
Requires:	R-iterators
Requires:	R-utf8
Requires:	R-farver
Requires:	R-labeling
Requires:	R-RColorBrewer
 
# %%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-dplyr
BuildRequires: 	R-ggplot2
BuildRequires: 	R-lubridate
BuildRequires: 	R-magrittr
BuildRequires: 	R-pdp
BuildRequires: 	R-purrr
BuildRequires: 	R-ranger
BuildRequires: 	R-stringr
BuildRequires: 	R-strucchange
BuildRequires: 	R-tibble
BuildRequires: 	R-viridis
BuildRequires: 	R-tidyr
BuildRequires: 	R-cli
BuildRequires: 	R-generics
BuildRequires: 	R-glue
BuildRequires: 	R-lifecycle
BuildRequires: 	R-pillar
BuildRequires: 	R-R6
BuildRequires: 	R-rlang
BuildRequires: 	R-tidyselect
BuildRequires: 	R-vctrs
BuildRequires: 	R-gtable
BuildRequires: 	R-isoband
BuildRequires: 	R-S7
BuildRequires: 	R-scales
BuildRequires: 	R-withr
BuildRequires: 	R-timechange
BuildRequires: 	R-foreach
BuildRequires: 	R-Rcpp-devel
BuildRequires: 	R-RcppEigen-devel
BuildRequires: 	R-stringi
BuildRequires: 	R-zoo
BuildRequires: 	R-sandwich
BuildRequires: 	R-pkgconfig
BuildRequires: 	R-cpp11-devel
BuildRequires: 	R-viridisLite
BuildRequires: 	R-gridExtra
BuildRequires: 	R-iterators
BuildRequires: 	R-utf8
BuildRequires: 	R-farver
BuildRequires: 	R-labeling
BuildRequires: 	R-RColorBrewer
 
Suggests:	R-testthat
Suggests:	R-openair
%description 
An integrated set of tools to allow data users to conduct 
meteorological normalisation and counterfactual modelling for air 
quality data. The meteorological normalisation technique uses 
predictive random forest models to remove variation of pollutant 
concentrations so trends and interventions can be explored in a robust 
way. For examples, see Grange et al. (2018) 
<doi:10.5194/acp-18-6223-2018> and Grange and Carslaw (2019) 
<doi:10.1016/j.scitotenv.2018.10.344>. The random forest models can 
also be used for counterfactual or business as usual (BAU) modelling by 
using the models to predict, from the model's perspective, the future. 
For an example, see Grange et al. (2021) <doi:10.5194/acp-2020-1171>. 
 
%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
%license %{rlibdir}/%{packname}/LICENSE
%{rlibdir}/%{packname}/Meta
%{rlibdir}/%{packname}/NAMESPACE
%{rlibdir}/%{packname}/R
%{rlibdir}/%{packname}/data
%doc %{rlibdir}/%{packname}/help
%doc %{rlibdir}/%{packname}/html
 
%changelog