%global __brp_check_rpaths %{nil}
%global packname  kpeaks
%global packver   1.1.0
%global rlibdir   /usr/local/lib/R/library

Name:             R-CRAN-%{packname}
Version:          1.1.0
Release:          3%{?dist}%{?buildtag}
Summary:          Determination of K Using Peak Counts of Features for Clustering

License:          GPL (>= 2)
URL:              https://cran.r-project.org/package=%{packname}
Source0:          %{url}&version=%{packver}#/%{packname}_%{packver}.tar.gz


BuildRequires:    R-devel >= 3.3.0
Requires:         R-core >= 3.3.0
BuildArch:        noarch
BuildRequires:    R-graphics 
BuildRequires:    R-stats 
BuildRequires:    R-utils 
BuildRequires:    R-methods 
Requires:         R-graphics 
Requires:         R-stats 
Requires:         R-utils 
Requires:         R-methods 

%description
The number of clusters (k) is needed to start all the partitioning
clustering algorithms. An optimal value of this input argument is widely
determined by using some internal validity indices. Since most of the
existing internal indices suggest a k value which is computed from the
clustering results after several runs of a clustering algorithm they are
computationally expensive. On the contrary, the package 'kpeaks' enables
to estimate k before running any clustering algorithm. It is based on a
simple novel technique using the descriptive statistics of peak counts of
the features in a data set.

%prep
%setup -q -c -n %{packname}

find -type f -executable -exec grep -Iq . {} \; -exec sed -i -e '$a\' {} \;

%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

%files
%{rlibdir}/%{packname}