%global __brp_check_rpaths %{nil}
%global __requires_exclude ^libmpi
%global packname  MBNMAdose
%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:          Dose-Response MBNMA Models

License:          GPL-3
URL:              https://cran.r-project.org/package=%{packname}
Source0:          %{url}&version=%{packver}#/%{packname}_%{packver}.tar.gz


BuildRequires:    R-devel >= 3.0.2
Requires:         R-core >= 3.0.2
BuildArch:        noarch
BuildRequires:    R-CRAN-rjags >= 4.8
BuildRequires:    R-CRAN-ggplot2 >= 2.2.1
BuildRequires:    R-CRAN-igraph >= 2.0.1.1
BuildRequires:    R-CRAN-checkmate >= 1.8.5
BuildRequires:    R-CRAN-magrittr >= 1.5
BuildRequires:    R-CRAN-reshape2 >= 1.4.3
BuildRequires:    R-CRAN-dplyr >= 0.7.4
BuildRequires:    R-CRAN-R2jags >= 0.5.7
BuildRequires:    R-CRAN-Rdpack >= 0.11.0
BuildRequires:    R-grDevices 
BuildRequires:    R-stats 
BuildRequires:    R-graphics 
BuildRequires:    R-utils 
BuildRequires:    R-CRAN-scales 
Requires:         R-CRAN-rjags >= 4.8
Requires:         R-CRAN-ggplot2 >= 2.2.1
Requires:         R-CRAN-igraph >= 2.0.1.1
Requires:         R-CRAN-checkmate >= 1.8.5
Requires:         R-CRAN-magrittr >= 1.5
Requires:         R-CRAN-reshape2 >= 1.4.3
Requires:         R-CRAN-dplyr >= 0.7.4
Requires:         R-CRAN-R2jags >= 0.5.7
Requires:         R-CRAN-Rdpack >= 0.11.0
Requires:         R-grDevices 
Requires:         R-stats 
Requires:         R-graphics 
Requires:         R-utils 
Requires:         R-CRAN-scales 

%description
Fits Bayesian dose-response model-based network meta-analysis (MBNMA) that
incorporate multiple doses within an agent by modelling different
dose-response functions, as described by Mawdsley et al. (2016)
<doi:10.1002/psp4.12091>. By modelling dose-response relationships this
can connect networks of evidence that might otherwise be disconnected, and
can improve precision on treatment estimates. Several common dose-response
functions are provided; others may be added by the user. Various
characteristics and assumptions can be flexibly added to the models, such
as shared class effects. The consistency of direct and indirect evidence
in the network can be assessed using unrelated mean effects models and/or
by node-splitting at the treatment level.

%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}