automatic version update by autodist [release 3.24-1mamba;Tue Feb 09 2021]
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# libsvm
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# libsvm
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Libsvm is a simple, easy-to-use, and efficient software for SVM classification and regression.
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It solves C-SVM classification, nu-SVM classification, one-class-SVM, epsilon-SVM regression, and nu-SVM regression.
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It also provides an automatic model selection tool for C-SVM classification.
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47
libsvm-3.20-Makefile.patch
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47
libsvm-3.20-Makefile.patch
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--- libsvm-3.20/Makefile 2015-03-22 12:55:35.000000000 +0100
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+++ libsvm-3.20/Makefile.linux 2015-03-22 14:00:24.234436503 +0100
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@@ -1,25 +1,28 @@
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CXX ?= g++
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-CFLAGS = -Wall -Wconversion -O3 -fPIC
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+MAKE = make
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+CFLAGS_ADD = -Wall -Wconversion -O3 -fPIC
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SHVER = 2
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-OS = $(shell uname)
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+SHARED_LIB_FLAGS= -shared -Wl,-soname,liblinear.so.$(SHVER)
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+LIBS= -L. -lsvm
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all: svm-train svm-predict svm-scale
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lib: svm.o
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- if [ "$(OS)" = "Darwin" ]; then \
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- SHARED_LIB_FLAG="-dynamiclib -Wl,-install_name,libsvm.so.$(SHVER)"; \
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- else \
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- SHARED_LIB_FLAG="-shared -Wl,-soname,libsvm.so.$(SHVER)"; \
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- fi; \
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- $(CXX) $${SHARED_LIB_FLAG} svm.o -o libsvm.so.$(SHVER)
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-
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-svm-predict: svm-predict.c svm.o
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- $(CXX) $(CFLAGS) svm-predict.c svm.o -o svm-predict -lm
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-svm-train: svm-train.c svm.o
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- $(CXX) $(CFLAGS) svm-train.c svm.o -o svm-train -lm
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+ $(CXX) $(SHARED_LIB_FLAGS) $(LDFLAGS) svm.o -o libsvm.so.$(SHVER)
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+ ln -fs libsvm.so.$(SHVER) libsvm.so
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+
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+svm-predict: lib svm-predict.c
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+ $(CXX) $(CFLAGS_ADD) svm-predict.c $(LIBS) -o svm-predict -lm
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+
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+svm-train: lib svm-train.c
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+ $(CXX) $(CFLAGS_ADD) svm-train.c $(LIBS) -o svm-train -lm
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+
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svm-scale: svm-scale.c
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- $(CXX) $(CFLAGS) svm-scale.c -o svm-scale
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+ $(CXX) $(CFLAGS_ADD) svm-scale.c -o svm-scale
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+
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svm.o: svm.cpp svm.h
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- $(CXX) $(CFLAGS) -c svm.cpp
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+ $(CXX) $(CFLAGS_ADD) $(CFLAGS) -c -o svm.o svm.cpp
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+
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clean:
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- rm -f *~ svm.o svm-train svm-predict svm-scale libsvm.so.$(SHVER)
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+ rm -f *~ svm.o svm-train svm-predict svm-scale libsvm.so*
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+ ${MAKE} -C python clean
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128
libsvm.spec
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libsvm.spec
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Name: libsvm
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Version: 3.24
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Release: 1mamba
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Summary: A simple, easy-to-use, and efficient software for SVM classification and regression
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Group: Development/Libraries
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Vendor: openmamba
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Distribution: openmamba
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Packager: Davide Madrisan <davide.madrisan@gmail.com>
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URL: https://www.csie.ntu.edu.tw/~cjlin/libsvm
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## GITSOURCE https://github.com/cjlin1/libsvm.git v320
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Source: https://github.com/cjlin1/libsvm.git/v320/libsvm-%{version}.tar.bz2
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Patch0: libsvm-3.20-Makefile.patch
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License: BSD
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## AUTOBUILDREQ-BEGIN
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BuildRequires: glibc-devel
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BuildRequires: libgcc
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#BuildRequires: libpython-devel
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BuildRequires: libstdc++6-devel
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## AUTOBUILDREQ-END
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BuildRequires: gcc-c++
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BuildRoot: %{_tmppath}/%{name}-%{version}-root
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# FIXME
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# build the java bindings, svm-toy-gtk, and svm-toy-qt
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%description
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Libsvm is a simple, easy-to-use, and efficient software for SVM classification and regression.
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It solves C-SVM classification, nu-SVM classification, one-class-SVM, epsilon-SVM regression, and nu-SVM regression.
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It also provides an automatic model selection tool for C-SVM classification.
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%package devel
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Group: Development/Libraries
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Summary: Development files for %{name}
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Requires: %{name} = %{?epoch:%epoch:}%{version}-%{release}
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Requires: pkg-config
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%description devel
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This package contains libraries and header files for developing applications that use %{name}.
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%package -n python-%{name}
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Group: Development/Libraries/Python
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Summary: Python bindings for %{name}
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Requires: %{name} = %{?epoch:%epoch:}%{version}-%{release}
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Requires: python
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%description -n python-%{name}
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%{summary}.
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%prep
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%setup -q
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%patch0 -p1
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# add pkg-config file
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cat << _EOF >> %{name}.pc
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Name: %{name}
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Description: Library for SVM classification and regression
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URL: %{url}
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Version: 3.24
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prefix=%{_prefix}
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includedir=%{_includedir}
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Cflags: -I\${includedir}/libsvm
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Libs: -lsvm
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_EOF
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%build
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CFLAGS="%optflags -O3"; export CFLAGS
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%make all
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python -m compileall -l python
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python -m compileall -l tools
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%install
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[ "%{buildroot}" != / ] && rm -rf "%{buildroot}"
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mkdir -p %{buildroot}%{_bindir}
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install -m 0755 svm-train %{buildroot}%{_bindir}/
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install -m 0755 svm-predict %{buildroot}%{_bindir}/
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install -m 0755 svm-scale %{buildroot}%{_bindir}/
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mkdir -p %{buildroot}%{_libdir}
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install libsvm.so* %{buildroot}%{_libdir}/
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mkdir -p %{buildroot}%{_libdir}/pkgconfig
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install -m 0644 %{name}.pc %{buildroot}%{_libdir}/pkgconfig/
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mkdir -p %{buildroot}%{_includedir}/%{name}
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install -m 0644 svm.h %{buildroot}%{_includedir}/%{name}/
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mkdir -p %{buildroot}%{python_sitearch}/%{name}
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install -m 0644 python/*.py* tools/*.py* %{buildroot}%{python_sitearch}/%{name}/
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> %{buildroot}%{python_sitearch}/%{name}/__init__.py
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for f in python/*.py tools/*.py; do
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ln -s %{python_sitearch}/%{name}/${f/*\/} %{buildroot}%{_bindir}/svm-${f/*\/}
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done
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%clean
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[ "%{buildroot}" != / ] && rm -rf "%{buildroot}"
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%post -p /sbin/ldconfig
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%postun -p /sbin/ldconfig
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%files
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%defattr(-,root,root)
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%{_bindir}/svm-predict
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%{_bindir}/svm-scale
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%{_bindir}/svm-train
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%{_libdir}/*.so.*
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%files devel
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%defattr(-,root,root)
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%{_includedir}/%{name}
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%{_libdir}/*.so
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%{_libdir}/pkgconfig/*.pc
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%doc README
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%files -n python-%{name}
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%defattr(-,root,root)
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%{_bindir}/svm-*.py
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%{python_sitearch}/%{name}
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%changelog
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* Tue Feb 09 2021 Automatic Build System <autodist@mambasoft.it> 3.24-1mamba
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- automatic version update by autodist
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* Sun Mar 22 2015 Davide Madrisan <davide.madrisan@gmail.com> 3.20-1mamba
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- package created by autospec
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