File R-diffval.spec of Package R-diffval
# Automatically generated by CRAN2OBS
#
# Spec file for package diffval
# 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.
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# Please submit bugfixes or comments via http://bugs.opensuse.org/
#
%global packname diffval
%global rlibdir %{_libdir}/R/library
Name: R-%{packname}
Version: 1.2.0
Release: 0
Summary: Vegetation Patterns
Group: Development/Libraries/Other
License: GPL (>= 3)
URL: http://cran.r-project.org/web/packages/%{packname}
Source: diffval_1.2.0.tar.gz
Requires: R-base
# %%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
Suggests: R-gurobi
%description
Find, visualize and explore patterns of differential taxa in vegetation
data (namely in a phytosociological table), using the Differential
Value (DiffVal). Patterns are searched through mathematical
optimization algorithms. Ultimately, Total Differential Value (TDV)
optimization aims at obtaining classifications of vegetation data based
on differential taxa, as in the traditional geobotanical approach
(Monteiro-Henriques 2025, <doi:10.3897/VCS.140466>). The Gurobi
optimizer, as well as the R package 'gurobi', can be installed from
<https://www.gurobi.com/products/gurobi-optimizer/>. The useful
vignette Gurobi Installation Guide, from package 'prioritizr', can be
found here:
<https://prioritizr.net/articles/gurobi_installation_guide.html>.
%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}
%doc %{rlibdir}/%{packname}/DESCRIPTION
%{rlibdir}/%{packname}/INDEX
%{rlibdir}/%{packname}/Meta
%{rlibdir}/%{packname}/NAMESPACE
%doc %{rlibdir}/%{packname}/NEWS.md
%{rlibdir}/%{packname}/R
%{rlibdir}/%{packname}/data
%doc %{rlibdir}/%{packname}/help
%doc %{rlibdir}/%{packname}/html
%changelog