%global __brp_check_rpaths %{nil} %global __requires_exclude ^libmpi %global packname MetricGraph %global packver 1.4.0 %global rlibdir /usr/local/lib/R/library Name: R-CRAN-%{packname} Version: 1.4.0 Release: 1%{?dist}%{?buildtag} Summary: Random Fields on Metric Graphs License: GPL (>= 2) URL: https://cran.r-project.org/package=%{packname} Source0: %{url}&version=%{packver}#/%{packname}_%{packver}.tar.gz BuildRequires: R-devel >= 3.5.0 Requires: R-core >= 3.5.0 BuildRequires: R-CRAN-rSPDE >= 2.3.3 BuildRequires: R-CRAN-Rcpp >= 1.0.5 BuildRequires: R-stats BuildRequires: R-CRAN-RANN BuildRequires: R-CRAN-ggplot2 BuildRequires: R-CRAN-igraph BuildRequires: R-CRAN-sf BuildRequires: R-CRAN-Matrix BuildRequires: R-methods BuildRequires: R-CRAN-R6 BuildRequires: R-CRAN-lifecycle BuildRequires: R-CRAN-sp BuildRequires: R-CRAN-dplyr BuildRequires: R-CRAN-tidyr BuildRequires: R-CRAN-magrittr BuildRequires: R-CRAN-broom BuildRequires: R-CRAN-zoo BuildRequires: R-CRAN-ggnewscale BuildRequires: R-CRAN-RcppEigen Requires: R-CRAN-rSPDE >= 2.3.3 Requires: R-CRAN-Rcpp >= 1.0.5 Requires: R-stats Requires: R-CRAN-RANN Requires: R-CRAN-ggplot2 Requires: R-CRAN-igraph Requires: R-CRAN-sf Requires: R-CRAN-Matrix Requires: R-methods Requires: R-CRAN-R6 Requires: R-CRAN-lifecycle Requires: R-CRAN-sp Requires: R-CRAN-dplyr Requires: R-CRAN-tidyr Requires: R-CRAN-magrittr Requires: R-CRAN-broom Requires: R-CRAN-zoo Requires: R-CRAN-ggnewscale %description Facilitates creation and manipulation of metric graphs, such as street or river networks. Further facilitates operations and visualizations of data on metric graphs, and the creation of a large class of random fields and stochastic partial differential equations on such spaces. These random fields can be used for simulation, prediction and inference. In particular, linear mixed effects models including random field components can be fitted to data based on computationally efficient sparse matrix representations. Interfaces to the R packages 'INLA' and 'inlabru' are also provided, which facilitate working with Bayesian statistical models on metric graphs. The main references for the methods are Bolin, Simas and Wallin (2024) , Bolin, Kovacs, Kumar and Simas (2023) and Bolin, Simas and Wallin (2023) and . %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}