File R-ANN2.spec of Package R-ANN2

# Automatically generated by CRAN2OBS
# 
# Spec file for package ANN2 
# 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) 2026 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  ANN2 
%global rlibdir   %{_libdir}/R/library 
 
Name:           R-%{packname} 
Version:        2.4.0 
Release:        0 
Summary:        Artificial Neural Networks for Anomaly Detection 
Group:          Development/Libraries/Other 
License:        GPL (>= 3) | file LICENSE 
URL:            http://cran.r-project.org/web/packages/%{packname} 
Source:         ANN2_2.4.0.tar.gz 

Requires:       R-%{packname}-devel
Requires:       R-base 
Requires:	R-Rcpp
Requires:	R-reshape2
Requires:	R-ggplot2
Requires:	R-viridisLite
Requires:	R-rlang
Requires:	R-RcppArmadillo
Requires:	R-testthat
Requires:	R-cli
Requires:	R-gtable
Requires:	R-isoband
Requires:	R-lifecycle
Requires:	R-S7
Requires:	R-scales
Requires:	R-vctrs
Requires:	R-withr
Requires:	R-plyr
Requires:	R-stringr
Requires:	R-brio
Requires:	R-callr
Requires:	R-desc
Requires:	R-evaluate
Requires:	R-jsonlite
Requires:	R-magrittr
Requires:	R-pkgload
Requires:	R-praise
Requires:	R-processx
Requires:	R-ps
Requires:	R-R6
Requires:	R-waldo
Requires:	R-glue
Requires:	R-cpp11
Requires:	R-fs
Requires:	R-pkgbuild
Requires:	R-rprojroot
Requires:	R-farver
Requires:	R-labeling
Requires:	R-RColorBrewer
Requires:	R-stringi
Requires:	R-diffobj
Requires:	R-crayon
 
# %%if 0%%{?sle_version} > 120400 || 0%%{?is_opensuse} 
# # Three others commonly needed 
# BuildRequires:  tex(ae.sty) 
# BuildRequires:  tex(fancyvrb.sty) 
# BuildRequires:  tex(inconsolata.sty) 
# BuildRequires:  tex(natbib.sty) 
# %else 
# BuildRequires:  texlive 
# %endif 
# BuildRequires:  texinfo 
BuildRequires:  fdupes 
BuildRequires:  R-base 
BuildRequires: 	R-Rcpp-devel
BuildRequires: 	R-reshape2
BuildRequires: 	R-ggplot2
BuildRequires: 	R-viridisLite
BuildRequires: 	R-rlang
BuildRequires: 	R-RcppArmadillo-devel
BuildRequires: 	R-testthat
BuildRequires: 	R-cli
BuildRequires: 	R-gtable
BuildRequires: 	R-isoband
BuildRequires: 	R-lifecycle
BuildRequires: 	R-S7
BuildRequires: 	R-scales
BuildRequires: 	R-vctrs
BuildRequires: 	R-withr
BuildRequires: 	R-plyr
BuildRequires: 	R-stringr
BuildRequires: 	R-brio
BuildRequires: 	R-callr
BuildRequires: 	R-desc
BuildRequires: 	R-evaluate
BuildRequires: 	R-jsonlite
BuildRequires: 	R-magrittr
BuildRequires: 	R-pkgload
BuildRequires: 	R-praise
BuildRequires: 	R-processx
BuildRequires: 	R-ps
BuildRequires: 	R-R6
BuildRequires: 	R-waldo
BuildRequires: 	R-glue
BuildRequires: 	R-cpp11-devel
BuildRequires: 	R-fs
BuildRequires: 	R-pkgbuild
BuildRequires: 	R-rprojroot
BuildRequires: 	R-farver
BuildRequires: 	R-labeling
BuildRequires: 	R-RColorBrewer
BuildRequires: 	R-stringi
BuildRequires: 	R-diffobj
BuildRequires: 	R-crayon
BuildRequires:  gcc gcc-c++ gcc-fortran
 
Suggests:	R-testthat

%package        devel
Summary:        Development files for %{packname}
Requires:       %{name} = %{version}
Requires:       R-base-devel

%description 
Training of neural networks for classification and regression tasks 
using mini-batch gradient descent. Special features include a function 
for training autoencoders, which can be used to detect anomalies, and 
some related plotting functions. Multiple activation functions are 
supported, including tanh, relu, step and ramp. For the use of the step 
and ramp activation functions in detecting anomalies using 
autoencoders, see Hawkins et al. (2002) <doi:10.1007/3-540-46145-0_17>. 
Furthermore, several loss functions are supported, including robust 
ones such as Huber and pseudo-Huber loss, as well as L1 and L2 
regularization. The possible options for optimization algorithms are 
RMSprop, Adam and SGD with momentum. The package contains a vectorized 
C++ implementation that facilitates fast training through mini-batch 
learning. 
 
%description     devel
Development files and header needed to build packages using %{packname}

%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
%license %{rlibdir}/%{packname}/LICENSE
%{rlibdir}/%{packname}/Meta
%{rlibdir}/%{packname}/NAMESPACE
%{rlibdir}/%{packname}/R
%doc %{rlibdir}/%{packname}/help
%doc %{rlibdir}/%{packname}/html
%{rlibdir}/%{packname}/libs

%files devel
%{rlibdir}/%{packname}/cereal

%changelog