%global __brp_check_rpaths %{nil} %global __requires_exclude ^libmpi %global packname alookr %global packver 0.3.9 %global rlibdir /usr/local/lib/R/library Name: R-CRAN-%{packname} Version: 0.3.9 Release: 1%{?dist}%{?buildtag} Summary: Model Classifier for Binary Classification License: GPL-2 URL: https://cran.r-project.org/package=%{packname} Source0: %{url}&version=%{packver}#/%{packname}_%{packver}.tar.gz BuildRequires: R-devel >= 3.2.0 Requires: R-core >= 3.2.0 BuildArch: noarch BuildRequires: R-CRAN-ggplot2 >= 3.0.0 BuildRequires: R-CRAN-cli >= 1.1.0 BuildRequires: R-CRAN-dplyr >= 0.7.6 BuildRequires: R-CRAN-randomForest BuildRequires: R-CRAN-caTools BuildRequires: R-CRAN-dlookr BuildRequires: R-CRAN-future BuildRequires: R-CRAN-ggmosaic BuildRequires: R-CRAN-MASS BuildRequires: R-CRAN-MLmetrics BuildRequires: R-methods BuildRequires: R-CRAN-parallelly BuildRequires: R-CRAN-party BuildRequires: R-CRAN-purrr BuildRequires: R-CRAN-ROCR BuildRequires: R-CRAN-ranger BuildRequires: R-CRAN-rlang BuildRequires: R-CRAN-rpart BuildRequires: R-stats BuildRequires: R-CRAN-tibble BuildRequires: R-CRAN-tidyr BuildRequires: R-CRAN-tidyselect BuildRequires: R-CRAN-xgboost BuildRequires: R-CRAN-glmnet Requires: R-CRAN-ggplot2 >= 3.0.0 Requires: R-CRAN-cli >= 1.1.0 Requires: R-CRAN-dplyr >= 0.7.6 Requires: R-CRAN-randomForest Requires: R-CRAN-caTools Requires: R-CRAN-dlookr Requires: R-CRAN-future Requires: R-CRAN-ggmosaic Requires: R-CRAN-MASS Requires: R-CRAN-MLmetrics Requires: R-methods Requires: R-CRAN-parallelly Requires: R-CRAN-party Requires: R-CRAN-purrr Requires: R-CRAN-ROCR Requires: R-CRAN-ranger Requires: R-CRAN-rlang Requires: R-CRAN-rpart Requires: R-stats Requires: R-CRAN-tibble Requires: R-CRAN-tidyr Requires: R-CRAN-tidyselect Requires: R-CRAN-xgboost Requires: R-CRAN-glmnet %description A collection of tools that support data splitting, predictive modeling, and model evaluation. A typical function is to split a dataset into a training dataset and a test dataset. Then compare the data distribution of the two datasets. Another feature is to support the development of predictive models and to compare the performance of several predictive models, helping to select the best model. %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}