##
##  liblinear.spec -- OpenPKG RPM Package Specification
##  Copyright (c) 2000-2025 OpenPKG Project <http://openpkg.org/>
##
##  Permission to use, copy, modify, and distribute this software for
##  any purpose with or without fee is hereby granted, provided that
##  the above copyright notice and this permission notice appear in all
##  copies.
##
##  THIS SOFTWARE IS PROVIDED ``AS IS'' AND ANY EXPRESSED OR IMPLIED
##  WARRANTIES, INCLUDING, BUT NOT LIMITED TO, THE IMPLIED WARRANTIES OF
##  MERCHANTABILITY AND FITNESS FOR A PARTICULAR PURPOSE ARE DISCLAIMED.
##  IN NO EVENT SHALL THE AUTHORS AND COPYRIGHT HOLDERS AND THEIR
##  CONTRIBUTORS BE LIABLE FOR ANY DIRECT, INDIRECT, INCIDENTAL,
##  SPECIAL, EXEMPLARY, OR CONSEQUENTIAL DAMAGES (INCLUDING, BUT NOT
##  LIMITED TO, PROCUREMENT OF SUBSTITUTE GOODS OR SERVICES; LOSS OF
##  USE, DATA, OR PROFITS; OR BUSINESS INTERRUPTION) HOWEVER CAUSED AND
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##  OR TORT (INCLUDING NEGLIGENCE OR OTHERWISE) ARISING IN ANY WAY OUT
##  OF THE USE OF THIS SOFTWARE, EVEN IF ADVISED OF THE POSSIBILITY OF
##  SUCH DAMAGE.
##

#   package version
%define       V_opkg  2.43
%define       V_dist  243

#   package information
Name:         liblinear
Summary:      Support Vector Machine (SVM) Library
URL:          https://www.csie.ntu.edu.tw/~cjlin/liblinear/
Vendor:       Chih-Chung Chang, Chih-Jen Lin
Packager:     OpenPKG Project
Distribution: OpenPKG Community
Class:        EVAL
Group:        Algorithm
License:      BSD
Version:      %{V_opkg}
Release:      20210225

#   list of sources
Source0:      https://github.com/cjlin1/liblinear/archive/v%{V_dist}.tar.gz

#   build information
BuildPreReq:  OpenPKG, openpkg >= 20160101, gcc, gcc::with_cxx = yes
PreReq:       OpenPKG, openpkg >= 20160101

%description
    LIBLINEAR is a linear classifier for data with millions of instances
    and features. It supports L2-regularized classifiers; L2-loss
    linear SVM, L1-loss linear SVM, and logistic regression (LR);
    L1-regularized classifiers; L2-loss linear SVM and logistic
    regression (LR); L2-regularized support vector regression and
    L2-loss linear SVR and L1-loss linear SVR.

%track
    prog liblinear = {
        version   = %{V_dist}
        url       = https://github.com/cjlin1/liblinear/releases
        regex     = v(__VER__)\.tar\.gz
    }

%prep
    %setup -q -n liblinear-%{V_dist}

%build
    %{l_make} %{l_mflags -O} \
        CXX="%{l_cxx}" \
        CFLAGS="%{l_cxxflags -O}"
    ar cr liblinear.a linear.o newton.o blas/blas.a
    ranlib liblinear.a

%install
    %{l_shtool} mkdir -f -p -m 755 \
        $RPM_BUILD_ROOT%{l_prefix}/bin \
        $RPM_BUILD_ROOT%{l_prefix}/include \
        $RPM_BUILD_ROOT%{l_prefix}/lib
    %{l_shtool} install -c -s -m 755 \
        train $RPM_BUILD_ROOT%{l_prefix}/bin/linear-train
    %{l_shtool} install -c -s -m 755 \
        predict $RPM_BUILD_ROOT%{l_prefix}/bin/linear-predict
    %{l_shtool} install -c -m 644 \
        linear.h $RPM_BUILD_ROOT%{l_prefix}/include/
    %{l_shtool} install -c -m 644 \
        liblinear.a $RPM_BUILD_ROOT%{l_prefix}/lib/
    %{l_rpmtool} files -v -ofiles -r$RPM_BUILD_ROOT %{l_files_std}

%files -f files

%clean

