%global __brp_check_rpaths %{nil} %global __requires_exclude ^libmpi %global packname Xplortext %global packver 1.5.5 %global rlibdir /usr/local/lib/R/library Name: R-CRAN-%{packname} Version: 1.5.5 Release: 1%{?dist}%{?buildtag} Summary: Statistical Analysis of Textual Data License: GPL (>= 2.0) URL: https://cran.r-project.org/package=%{packname} Source0: %{url}&version=%{packver}#/%{packname}_%{packver}.tar.gz BuildRequires: R-devel >= 4.4 Requires: R-core >= 4.4 BuildArch: noarch BuildRequires: R-CRAN-ggplot2 >= 3.5.1 BuildRequires: R-CRAN-FactoMineR >= 2.11 BuildRequires: R-CRAN-tm >= 0.7.14 BuildRequires: R-CRAN-ape BuildRequires: R-CRAN-cluster BuildRequires: R-CRAN-dendextend BuildRequires: R-CRAN-flexclust BuildRequires: R-CRAN-flashClust BuildRequires: R-CRAN-ggdendro BuildRequires: R-CRAN-ggforce BuildRequires: R-CRAN-ggpubr BuildRequires: R-CRAN-ggrepel BuildRequires: R-graphics BuildRequires: R-CRAN-gridExtra BuildRequires: R-CRAN-MASS BuildRequires: R-methods BuildRequires: R-CRAN-patchwork BuildRequires: R-CRAN-plotly BuildRequires: R-CRAN-stringi BuildRequires: R-CRAN-stringr BuildRequires: R-CRAN-slam BuildRequires: R-stats BuildRequires: R-utils BuildRequires: R-CRAN-vegan Requires: R-CRAN-ggplot2 >= 3.5.1 Requires: R-CRAN-FactoMineR >= 2.11 Requires: R-CRAN-tm >= 0.7.14 Requires: R-CRAN-ape Requires: R-CRAN-cluster Requires: R-CRAN-dendextend Requires: R-CRAN-flexclust Requires: R-CRAN-flashClust Requires: R-CRAN-ggdendro Requires: R-CRAN-ggforce Requires: R-CRAN-ggpubr Requires: R-CRAN-ggrepel Requires: R-graphics Requires: R-CRAN-gridExtra Requires: R-CRAN-MASS Requires: R-methods Requires: R-CRAN-patchwork Requires: R-CRAN-plotly Requires: R-CRAN-stringi Requires: R-CRAN-stringr Requires: R-CRAN-slam Requires: R-stats Requires: R-utils Requires: R-CRAN-vegan %description Provides a set of functions devoted to multivariate exploratory statistics on textual data. Classical methods such as correspondence analysis and agglomerative hierarchical clustering are available. Chronologically constrained agglomerative hierarchical clustering enriched with labelled-by-words trees is offered. Given a division of the corpus into parts, their characteristic words and documents are identified. Further, accessing to 'FactoMineR' functions is very easy. Two of them are relevant in textual domain. MFA() addresses multiple lexical table allowing applications such as dealing with multilingual corpora as well as simultaneously analyzing both open-ended and closed questions in surveys. See for examples. %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}