%global __brp_check_rpaths %{nil}
%global __requires_exclude ^libmpi
%global packname  sdtmval
%global packver   0.4.1
%global rlibdir   /usr/local/lib/R/library

Name:             R-CRAN-%{packname}
Version:          0.4.1
Release:          1%{?dist}%{?buildtag}
Summary:          Validate SDTM Domains

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-dplyr 
BuildRequires:    R-CRAN-glue 
BuildRequires:    R-CRAN-haven 
BuildRequires:    R-CRAN-knitr 
BuildRequires:    R-CRAN-lubridate 
BuildRequires:    R-CRAN-magrittr 
BuildRequires:    R-CRAN-purrr 
BuildRequires:    R-CRAN-readxl 
BuildRequires:    R-CRAN-rlang 
BuildRequires:    R-stats 
BuildRequires:    R-CRAN-stringr 
BuildRequires:    R-CRAN-tidyr 
BuildRequires:    R-CRAN-tidyselect 
BuildRequires:    R-utils 
Requires:         R-CRAN-dplyr 
Requires:         R-CRAN-glue 
Requires:         R-CRAN-haven 
Requires:         R-CRAN-knitr 
Requires:         R-CRAN-lubridate 
Requires:         R-CRAN-magrittr 
Requires:         R-CRAN-purrr 
Requires:         R-CRAN-readxl 
Requires:         R-CRAN-rlang 
Requires:         R-stats 
Requires:         R-CRAN-stringr 
Requires:         R-CRAN-tidyr 
Requires:         R-CRAN-tidyselect 
Requires:         R-utils 

%description
Provides a set of tools to assist statistical programmers in validating
Study Data Tabulation Model (SDTM) domain data sets. Statistical
programmers are required to validate that a SDTM data set domain has been
programmed correctly, per the SDTM Implementation Guide (SDTMIG) by
'CDISC' (<https://www.cdisc.org/standards/foundational/sdtmig>), study
specification, and study protocol using a process called double
programming. Double programming involves two different programmers
independently converting the raw electronic data cut (EDC) data into a
SDTM domain data table and comparing their results to ensure accurate
standardization of the data. One of these attempts is termed 'production'
and the other 'validation'. Generally, production runs are the official
programs for submittals and these are written in 'SAS'. Validation runs
can be programmed in another language, in this case 'R'.

%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}