%global __brp_check_rpaths %{nil} %global packname LDAShiny %global packver 0.9.3 %global rlibdir /usr/local/lib/R/library Name: R-CRAN-%{packname} Version: 0.9.3 Release: 1%{?dist}%{?buildtag} Summary: User-Friendly Interface for Review of Scientific Literature 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 BuildArch: noarch BuildRequires: R-CRAN-DT >= 0.15 BuildRequires: R-CRAN-beepr BuildRequires: R-CRAN-broom BuildRequires: R-CRAN-chinese.misc BuildRequires: R-CRAN-dplyr BuildRequires: R-CRAN-highcharter BuildRequires: R-CRAN-htmlwidgets BuildRequires: R-CRAN-ldatuning BuildRequires: R-parallel BuildRequires: R-CRAN-plotly BuildRequires: R-CRAN-purrr BuildRequires: R-CRAN-quanteda BuildRequires: R-CRAN-shiny BuildRequires: R-CRAN-shinyalert BuildRequires: R-CRAN-shinyBS BuildRequires: R-CRAN-shinycssloaders BuildRequires: R-CRAN-shinydashboard BuildRequires: R-CRAN-shinyjs BuildRequires: R-CRAN-shinyWidgets BuildRequires: R-CRAN-SnowballC BuildRequires: R-CRAN-stringr BuildRequires: R-CRAN-textmineR BuildRequires: R-CRAN-tidyr BuildRequires: R-CRAN-tidytext BuildRequires: R-CRAN-tm BuildRequires: R-CRAN-topicmodels Requires: R-CRAN-DT >= 0.15 Requires: R-CRAN-beepr Requires: R-CRAN-broom Requires: R-CRAN-chinese.misc Requires: R-CRAN-dplyr Requires: R-CRAN-highcharter Requires: R-CRAN-htmlwidgets Requires: R-CRAN-ldatuning Requires: R-parallel Requires: R-CRAN-plotly Requires: R-CRAN-purrr Requires: R-CRAN-quanteda Requires: R-CRAN-shiny Requires: R-CRAN-shinyalert Requires: R-CRAN-shinyBS Requires: R-CRAN-shinycssloaders Requires: R-CRAN-shinydashboard Requires: R-CRAN-shinyjs Requires: R-CRAN-shinyWidgets Requires: R-CRAN-SnowballC Requires: R-CRAN-stringr Requires: R-CRAN-textmineR Requires: R-CRAN-tidyr Requires: R-CRAN-tidytext Requires: R-CRAN-tm Requires: R-CRAN-topicmodels %description Contains the development of a tool that provides a web-based graphical user interface (GUI) to perform a review of the scientific literature under the Bayesian approach of Latent Dirichlet Allocation (LDA)and machine learning algorithms. The application methodology is framed by the well known procedures in topic modelling on how to clean and process data. Contains methods described by Blei, David M., Andrew Y. Ng, and Michael I. Jordan (2003) Allocation"; Thomas L. Griffiths and Mark Steyvers (2004) ; Xiong Hui, et al (2019) . %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}