%global __brp_check_rpaths %{nil}
%global __requires_exclude ^libmpi
%global packname  bRacatus
%global packver   2.0.0
%global rlibdir   /usr/local/lib/R/library

Name:             R-CRAN-%{packname}
Version:          2.0.0
Release:          1%{?dist}%{?buildtag}
Summary:          A Method to Estimate the Accuracy and Biogeographical Status of Georeferenced Biological Data

License:          GPL (>= 2)
URL:              https://cran.r-project.org/package=%{packname}
Source0:          %{url}&version=%{packver}#/%{packname}_%{packver}.tar.gz


BuildRequires:    R-devel >= 3.5.0
Requires:         R-core >= 3.5.0
BuildArch:        noarch
BuildRequires:    R-CRAN-data.table 
BuildRequires:    R-CRAN-geojsonio 
BuildRequires:    R-graphics 
BuildRequires:    R-grDevices 
BuildRequires:    R-CRAN-jsonlite 
BuildRequires:    R-methods 
BuildRequires:    R-CRAN-plotfunctions 
BuildRequires:    R-CRAN-raster 
BuildRequires:    R-CRAN-rgbif 
BuildRequires:    R-CRAN-rnaturalearth 
BuildRequires:    R-CRAN-sf 
BuildRequires:    R-CRAN-sp 
BuildRequires:    R-stats 
Requires:         R-CRAN-data.table 
Requires:         R-CRAN-geojsonio 
Requires:         R-graphics 
Requires:         R-grDevices 
Requires:         R-CRAN-jsonlite 
Requires:         R-methods 
Requires:         R-CRAN-plotfunctions 
Requires:         R-CRAN-raster 
Requires:         R-CRAN-rgbif 
Requires:         R-CRAN-rnaturalearth 
Requires:         R-CRAN-sf 
Requires:         R-CRAN-sp 
Requires:         R-stats 

%description
Automated assessment of accuracy and geographical status of georeferenced
biological data. The methods rely on reference regions, namely checklists
and range maps. Includes functions to obtain data from the Global
Biodiversity Information Facility <https://www.gbif.org/> and from the
Global Inventory of Floras and Traits
<https://gift.uni-goettingen.de/home>. Alternatively, the user can input
their own data. Furthermore, provides easy visualisation of the data and
the results through the plotting functions. Especially suited for large
datasets. The reference for the methodology is: Arlé et al. (under
review).

%prep
%setup -q -c -n %{packname}

# fix end of executable files
find -type f -executable -exec grep -Iq . {} \; -exec sed -i -e '$a\' {} \;
# prevent binary stripping
[ -d %{packname}/src ] && find %{packname}/src -type f -exec \
  sed -i 's@/usr/bin/strip@/usr/bin/true@g' {} \; || true
[ -d %{packname}/src ] && find %{packname}/src/Make* -type f -exec \
  sed -i 's@-g0@@g' {} \; || true
# don't allow local prefix in executable scripts
find -type f -executable -exec sed -Ei 's@#!( )*/usr/local/bin@#!/usr/bin@g' {} \;

%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
# remove buildroot from installed files
find %{buildroot}%{rlibdir} -type f -exec sed -i "s@%{buildroot}@@g" {} \;

%files
%{rlibdir}/%{packname}