%global __brp_check_rpaths %{nil} %global packname postGGIR %global packver 2.4.0.2 %global rlibdir /usr/local/lib/R/library Name: R-CRAN-%{packname} Version: 2.4.0.2 Release: 1%{?dist}%{?buildtag} Summary: Data Processing after Running 'GGIR' for Accelerometer Data License: GPL-3 URL: https://cran.r-project.org/package=%{packname} Source0: %{url}&version=%{packver}#/%{packname}_%{packver}.tar.gz BuildRequires: R-devel >= 3.6.0 Requires: R-core >= 3.6.0 BuildArch: noarch BuildRequires: R-CRAN-refund BuildRequires: R-CRAN-denseFLMM BuildRequires: R-CRAN-dplyr BuildRequires: R-CRAN-xlsx BuildRequires: R-CRAN-survival BuildRequires: R-stats BuildRequires: R-CRAN-tidyr BuildRequires: R-CRAN-zoo BuildRequires: R-CRAN-ineq BuildRequires: R-CRAN-cosinor BuildRequires: R-CRAN-cosinor2 BuildRequires: R-CRAN-abind BuildRequires: R-CRAN-accelerometry BuildRequires: R-CRAN-ActCR BuildRequires: R-CRAN-ActFrag BuildRequires: R-CRAN-minpack.lm BuildRequires: R-CRAN-kableExtra BuildRequires: R-CRAN-GGIR Requires: R-CRAN-refund Requires: R-CRAN-denseFLMM Requires: R-CRAN-dplyr Requires: R-CRAN-xlsx Requires: R-CRAN-survival Requires: R-stats Requires: R-CRAN-tidyr Requires: R-CRAN-zoo Requires: R-CRAN-ineq Requires: R-CRAN-cosinor Requires: R-CRAN-cosinor2 Requires: R-CRAN-abind Requires: R-CRAN-accelerometry Requires: R-CRAN-ActCR Requires: R-CRAN-ActFrag Requires: R-CRAN-minpack.lm Requires: R-CRAN-kableExtra Requires: R-CRAN-GGIR %description Generate all necessary R/Rmd/shell files for data processing after running 'GGIR' (v2.4.0) for accelerometer data. In part 1, all csv files in the GGIR output directory were read, transformed and then merged. In part 2, the GGIR output files were checked and summarized in one excel sheet. In part 3, the merged data was cleaned according to the number of valid hours on each night and the number of valid days for each subject. In part 4, the cleaned activity data was imputed by the average Euclidean norm minus one (ENMO) over all the valid days for each subject. Finally, a comprehensive report of data processing was created using Rmarkdown, and the report includes few exploratory plots and multiple commonly used features extracted from minute level actigraphy data. %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}