libsvm, bump version (#11257)

sci-libs/libsvm/libsvm-3.35.recipe

@@ -0,0 +1,98 @@
+SUMMARY="Library for Support Vector Machines"
+DESCRIPTION="Libsvm is a simple, easy-to-use, and efficient software for SVM \
+classification and regression. It solves C-SVM classification, nu-SVM \
+classification, one-class-SVM, epsilon-SVM regression, and nu-SVM \
+regression. It also provides an automatic model selection tool for \
+C-SVM classification."
+HOMEPAGE="https://www.csie.ntu.edu.tw/~cjlin/libsvm/"
+COPYRIGHT="2000-2024 Chih-Chung Chang and Chih-Jen Lin"
+LICENSE="BSD (3-clause)"
+REVISION="1"
+SOURCE_URI="https://www.csie.ntu.edu.tw/~cjlin/libsvm/libsvm-$portVersion.tar.gz"
+CHECKSUM_SHA256="ea5633fc84b1c2fa58aa4c44b62e437573020297a1dfbe73bf1531ec817a8478"
+SOURCE_FILENAME="libsvm-$portVersion.tar.gz"
+SOURCE_URI_2="https://www.csie.ntu.edu.tw/~cjlin/papers/guide/guide.pdf#noarchive"
+CHECKSUM_SHA256_2="d04e2f21a849a6476a98abf3e2bafe379974b573eabf52ed95b9bb5163c91033"
+PATCHES="libsvm-$portVersion.patchset"
+
+ARCHITECTURES="all !x86_gcc2"
+SECONDARY_ARCHITECTURES="x86"
+
+PROVIDES="
+	libsvm$secondaryArchSuffix = $portVersion
+	lib:libsvm$secondaryArchSuffix
+	"
+REQUIRES="
+	haiku$secondaryArchSuffix
+	"
+
+PROVIDES_devel="
+	libsvm_${secondaryArchSuffix}devel = $portVersion
+	devel:libsvm$secondaryArchSuffix
+	"
+REQUIRES_devel="
+	libsvm$secondaryArchSuffix == $portVersion base
+	"
+
+PROVIDES_tools="
+	libsvm_${secondaryArchSuffix}tools = $portVersion
+	cmd:svm_checkdata
+	cmd:svm_easy
+	cmd:svm_grid
+	cmd:svm_predict
+	cmd:svm_scale
+	cmd:svm_subset
+	cmd:svm_train
+	"
+REQUIRES_tools="
+	haiku$secondaryArchSuffix
+	cmd:python3
+	"
+
+BUILD_REQUIRES="
+	haiku${secondaryArchSuffix}_devel
+	"
+BUILD_PREREQUIRES="
+	cmd:g++$secondaryArchSuffix
+	cmd:gcc$secondaryArchSuffix
+	cmd:make
+	cmd:sed
+	"
+
+BUILD()
+{
+	make lib all $jobArgs
+}
+
+INSTALL()
+{
+	mkdir -p $prefix/bin $developDocDir $libDir $includeDir
+
+	# tools
+	cp svm-train			$prefix/bin/svm-train
+	cp svm-predict			$prefix/bin/svm-predict
+	cp svm-scale			$prefix/bin/svm-scale
+	cp tools/checkdata.py	$prefix/bin/svm-checkdata
+	cp tools/subset.py		$prefix/bin/svm-subset
+	cp tools/easy.py		$prefix/bin/svm-easy
+	cp tools/grid.py		$prefix/bin/svm-grid
+
+	# documentation
+	cp $sourceDir2/guide.pdf $developDocDir
+
+	# library
+	cp libsvm.so.4 $libDir
+	ln -s $libDir/libsvm.so.4 $libDir/libsvm.so
+
+	#header
+	cp svm.h $includeDir
+
+	prepareInstalledDevelLib \
+		libsvm
+
+	packageEntries tools \
+		$prefix/bin
+
+	packageEntries devel \
+		$developDir
+}

sci-libs/libsvm/libsvm-v323.recipe

@@ -1,86 +0,0 @@
-SUMMARY="Library for Support Vector Machines"
-DESCRIPTION="Libsvm is a simple, easy-to-use, and efficient software for SVM \
-classification and regression. It solves C-SVM classification, nu-SVM \
-classification, one-class-SVM, epsilon-SVM regression, and nu-SVM \
-regression. It also provides an automatic model selection tool for \
-C-SVM classification."
-HOMEPAGE="https://www.csie.ntu.edu.tw/~cjlin/libsvm/"
-COPYRIGHT="2000-2018 Chih-Chung Chang and Chih-Jen Lin"
-LICENSE="BSD (3-clause)"
-REVISION="2"
-SOURCE_URI="https://github.com/cjlin1/libsvm/archive/$portVersion.tar.gz"
-CHECKSUM_SHA256="7a466f90f327a98f8ed1cb217570547bcb00077933d1619f3cb9e73518f38196"
-SOURCE_FILENAME="libsvm-$portVersion.tar.gz"
-SOURCE_DIR="libsvm-323"
-PATCHES="libsvm-$portVersion.patchset"
-
-ARCHITECTURES="all"
-
-PROVIDES="
-	libsvm = $portVersion
-	lib:libsvm
-	"
-REQUIRES="
-	haiku
-	"
-
-PROVIDES_devel="
-	libsvm_devel = $portVersion
-	devel:libsvm
-	"
-REQUIRES_devel="
-	libsvm == $portVersion base
-	"
-
-PROVIDES_tools="
-	libsvm_tools = $portVersion
-	cmd:svm_checkdata
-	cmd:svm_easy
-	cmd:svm_grid
-	cmd:svm_predict
-	cmd:svm_scale
-	cmd:svm_subset
-	cmd:svm_train
-	"
-REQUIRES_tools="
-	haiku
-	cmd:python3
-	"
-
-BUILD_REQUIRES="
-	haiku_devel
-	"
-BUILD_PREREQUIRES="
-	haiku
-	cmd:g++
-	cmd:gcc
-	cmd:make
-	cmd:sed
-	"
-
-BUILD()
-{
-	make lib $jobArgs
-	make $jobArgs
-}
-
-INSTALL()
-{
-	mkdir -p $binDir
-	mkdir -p $libDir
-	mkdir -p $includeDir
-
-	cp svm-train			$binDir/svm-train
-	cp svm-predict			$binDir/svm-predict
-	cp svm-scale			$binDir/svm-scale
-	cp tools/checkdata.py	$binDir/svm-checkdata
-	cp tools/subset.py		$binDir/svm-subset
-	cp tools/easy.py		$binDir/svm-easy
-	cp tools/grid.py		$binDir/svm-grid
-	packageEntries tools $binDir
-
-	cp libsvm.so.2 $libDir
-	cp svm.h $includeDir
-	prepareInstalledDevelLib libsvm
-	packageEntries devel $developDir
-}