File R-douconca.spec of Package R-douconca
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# Spec file for package douconca
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%global packname douconca
%global rlibdir %{_libdir}/R/library
Name: R-%{packname}
Version: 1.2.5
Release: 0
Summary: Double Constrained Correspondence Analysis for Trait-Environment Analysis in Ecology
Group: Development/Libraries/Other
License: GPL-3
URL: http://cran.r-project.org/web/packages/%{packname}
Source: douconca_1.2.5.tar.gz
Requires: R-base
Requires: R-ggplot2
Requires: R-ggrepel
Requires: R-gridExtra
Requires: R-permute
Requires: R-rlang
Requires: R-vegan
Requires: R-cli
Requires: R-gtable
Requires: R-isoband
Requires: R-lifecycle
Requires: R-S7
Requires: R-scales
Requires: R-vctrs
Requires: R-withr
Requires: R-Rcpp
Requires: R-glue
Requires: R-cpp11
Requires: R-farver
Requires: R-labeling
Requires: R-R6
Requires: R-RColorBrewer
Requires: R-viridisLite
# %%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-ggplot2
BuildRequires: R-ggrepel
BuildRequires: R-gridExtra
BuildRequires: R-permute
BuildRequires: R-rlang
BuildRequires: R-vegan
BuildRequires: R-cli
BuildRequires: R-gtable
BuildRequires: R-isoband
BuildRequires: R-lifecycle
BuildRequires: R-S7
BuildRequires: R-scales
BuildRequires: R-vctrs
BuildRequires: R-withr
BuildRequires: R-Rcpp-devel
BuildRequires: R-glue
BuildRequires: R-cpp11-devel
BuildRequires: R-farver
BuildRequires: R-labeling
BuildRequires: R-R6
BuildRequires: R-RColorBrewer
BuildRequires: R-viridisLite
Suggests: R-rmarkdown
Suggests: R-knitr
Suggests: R-tinytest
%description
Double constrained correspondence analysis (dc-CA) analyzes
(multi-)trait (multi-)environment ecological data by using the 'vegan'
package and native R code. Throughout the two step algorithm of ter
Braak et al. (2018) is used. This algorithm combines and extends
community- (sample-) and species-level analyses, i.e. the usual
community weighted means (CWM)-based regression analysis and the
species-level analysis of species-niche centroids (SNC)-based
regression analysis. The two steps use canonical correspondence
analysis to regress the abundance data on to the traits and (weighted)
redundancy analysis to regress the CWM of the orthonormalized traits on
to the environmental predictors. The function dc_CA() has an option to
divide the abundance data of a site by the site total, giving equal
site weights. This division has the advantage that the multivariate
analysis corresponds with an unweighted (multi-trait) community-level
analysis, instead of being weighted. The first step of the algorithm
uses vegan::cca(). The second step uses wrda() but vegan::rda() if the
site weights are equal. This version has a predict() function. For
details see ter Braak et al. 2018 <doi:10.1007/s10651-017-0395-x>. and
ter Braak & van Rossum 2025 <doi:10.1016/j.ecoinf.2025.103143>.
%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
%{rlibdir}/%{packname}/demo
%{rlibdir}/%{packname}/doc
%doc %{rlibdir}/%{packname}/help
%doc %{rlibdir}/%{packname}/html
%{rlibdir}/%{packname}/tinytest
%changelog
