Overview

File R-TCIU.spec of Package R-TCIU

# Automatically generated by CRAN2OBS
# 
# Spec file for package TCIU 
# This file is auto-generated using information in the package source, 
# esp. Description and Summary. Improvements in that area should be 
# discussed with upstream. 
# 
# Copyright (c) 2025 SUSE LINUX GmbH, Nuernberg, Germany. 
# 
# All modifications and additions to the file contributed by third parties 
# remain the property of their copyright owners, unless otherwise agreed 
# upon. The license for this file, and modifications and additions to the 
# file, is the same license as for the pristine package itself (unless the 
# license for the pristine package is not an Open Source License, in which 
# case the license is the MIT License). An "Open Source License" is a 
# license that conforms to the Open Source Definition (Version 1.9) 
# published by the Open Source Initiative. 
#  
# Please submit bugfixes or comments via http://bugs.opensuse.org/ 
# 
 
%global packname  TCIU 
%global rlibdir   %{_libdir}/R/library 
 
Name:           R-%{packname} 
Version:        1.2.7 
Release:        0 
Summary:        Spacekime Analytics, Time Complexity and Inferential Uncertainty 
Group:          Development/Libraries/Other 
License:        GPL-3 
URL:            http://cran.r-project.org/web/packages/%{packname} 
Source:         TCIU_1.2.7.tar.gz 
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%description 
Provide the core functionality to transform longitudinal data to 
complex-time (kime) data using analytic and numerical techniques, 
visualize the original time-series and reconstructed kime-surfaces, 
perform model based (e.g., tensor-linear regression) and model-free 
classification and clustering methods in the book Dinov, ID and Velev, 
MV. (2021) "Data Science: Time Complexity, Inferential Uncertainty, and 
Spacekime Analytics", De Gruyter STEM Series, ISBN 978-3-11-069780-3. 
<https://www.degruyter.com/view/title/576646>. The package includes 18 
core functions which can be separated into three groups. 1) draw 
longitudinal data, such as Functional magnetic resonance imaging(fMRI) 
time-series, and forecast or transform the time-series data. 2) 
simulate real-valued time-series data, e.g., fMRI time-courses, detect 
the activated areas, report the corresponding p-values, and visualize 
the p-values in the 3D brain space. 3) Laplace transform and 
kimesurface reconstructions of the fMRI data. 
 
%prep 
%setup -q -c -n %{packname} 
# the next line is needed, because we build without --clean in between two packages 
rm -rf ~/.R  
 
 
%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 
%fdupes -s %{buildroot}%{rlibdir} 
 
#%%check 
#%%{_bindir}/R CMD check %%{packname} 
 
%files 
%dir %{rlibdir}/%{packname} 
%doc %{rlibdir}/%{packname}/DESCRIPTION
%{rlibdir}/%{packname}/INDEX
%{rlibdir}/%{packname}/Meta
%{rlibdir}/%{packname}/NAMESPACE
%{rlibdir}/%{packname}/R
%{rlibdir}/%{packname}/data
%{rlibdir}/%{packname}/demo
%doc %{rlibdir}/%{packname}/doc
%doc %{rlibdir}/%{packname}/help
%doc %{rlibdir}/%{packname}/html
%{rlibdir}/%{packname}/libs
 
%changelog
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