%global __brp_check_rpaths %{nil} %global packname glamlasso %global packver 3.0.1 %global rlibdir /usr/local/lib/R/library Name: R-CRAN-%{packname} Version: 3.0.1 Release: 1%{?dist}%{?buildtag} Summary: Penalization in Large Scale Generalized Linear Array Models License: GPL-3 URL: https://cran.r-project.org/package=%{packname} Source0: %{url}&version=%{packver}#/%{packname}_%{packver}.tar.gz BuildRequires: R-devel Requires: R-core BuildRequires: R-CRAN-Rcpp >= 0.11.2 BuildRequires: R-CRAN-RcppArmadillo Requires: R-CRAN-Rcpp >= 0.11.2 %description Efficient design matrix free lasso penalized estimation in large scale 2 and 3-dimensional generalized linear array model framework. The procedure is based on the gdpg algorithm from Lund et al. (2017) . Currently Lasso or Smoothly Clipped Absolute Deviation (SCAD) penalized estimation is possible for the following models: The Gaussian model with identity link, the Binomial model with logit link, the Poisson model with log link and the Gamma model with log link. It is also possible to include a component in the model with non-tensor design e.g an intercept. Also provided are functions, glamlassoRR() and glamlassoS(), fitting special cases of GLAMs. %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 # 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}