%global __brp_check_rpaths %{nil}
%global __requires_exclude ^libmpi
%global packname  ForecastingEnsembles
%global packver   0.5.0
%global rlibdir   /usr/local/lib/R/library

Name:             R-CRAN-%{packname}
Version:          0.5.0
Release:          1%{?dist}%{?buildtag}
Summary:          Time Series Forecasting Using 23 Individual Models

License:          MIT + file LICENSE
URL:              https://cran.r-project.org/package=%{packname}
Source0:          %{url}&version=%{packver}#/%{packname}_%{packver}.tar.gz


BuildRequires:    R-devel >= 2.10
Requires:         R-core >= 2.10
BuildArch:        noarch
BuildRequires:    R-CRAN-doParallel 
BuildRequires:    R-CRAN-dplyr 
BuildRequires:    R-CRAN-fable 
BuildRequires:    R-CRAN-fabletools 
BuildRequires:    R-CRAN-fable.prophet 
BuildRequires:    R-CRAN-feasts 
BuildRequires:    R-CRAN-fracdiff 
BuildRequires:    R-CRAN-ggplot2 
BuildRequires:    R-CRAN-gt 
BuildRequires:    R-CRAN-magrittr 
BuildRequires:    R-parallel 
BuildRequires:    R-CRAN-readr 
BuildRequires:    R-stats 
BuildRequires:    R-CRAN-tibble 
BuildRequires:    R-CRAN-tidyr 
BuildRequires:    R-CRAN-tsibble 
BuildRequires:    R-CRAN-urca 
BuildRequires:    R-utils 
Requires:         R-CRAN-doParallel 
Requires:         R-CRAN-dplyr 
Requires:         R-CRAN-fable 
Requires:         R-CRAN-fabletools 
Requires:         R-CRAN-fable.prophet 
Requires:         R-CRAN-feasts 
Requires:         R-CRAN-fracdiff 
Requires:         R-CRAN-ggplot2 
Requires:         R-CRAN-gt 
Requires:         R-CRAN-magrittr 
Requires:         R-parallel 
Requires:         R-CRAN-readr 
Requires:         R-stats 
Requires:         R-CRAN-tibble 
Requires:         R-CRAN-tidyr 
Requires:         R-CRAN-tsibble 
Requires:         R-CRAN-urca 
Requires:         R-utils 

%description
Runs multiple individual time series models, and combines them into an
ensembles of time series models. This is mainly used to predict the
results of the monthly labor market report from the United States Bureau
of Labor Statistics for virtually any part of the economy reported by the
Bureau of Labor Statistics, but it can be easily modified to work with
other types of time series data. For example, the package was used to
predict the winning men's and women's time for the 2024 London Marathon.

%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}