45 lines
1.7 KiB
Ruby
45 lines
1.7 KiB
Ruby
class Libsvm < Formula
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desc "Library for support vector machines"
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homepage "https://www.csie.ntu.edu.tw/~cjlin/libsvm/"
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url "https://www.csie.ntu.edu.tw/~cjlin/libsvm/libsvm-3.22.tar.gz"
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mirror "https://dl.bintray.com/homebrew/mirror/libsvm-3.22.tar.gz"
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sha256 "6d81c67d3b13073eb5a25aa77188f141b242ec328518fad95367ede253d0a77d"
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bottle do
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cellar :any
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sha256 "6fae589e624777638a8a5bc1c8b03e3bb48f88a61380b608273b44bd2d25aec4" => :high_sierra
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sha256 "39f3552e425be4bcb6e42d917b508bf94904520526c49ec52712c017680583fd" => :sierra
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sha256 "67867d2ddde33efd85da4c1a03757af0e3dcf591186552140876ddd11916d5df" => :el_capitan
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sha256 "3ee2001f87f2a58e698aeb0bfc413baa820184dba1caa2b3ec0a5a593a80d651" => :yosemite
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end
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def install
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system "make", "CFLAGS=#{ENV.cflags}"
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system "make", "lib"
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bin.install "svm-scale", "svm-train", "svm-predict"
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lib.install "libsvm.so.2" => "libsvm.2.dylib"
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lib.install_symlink "libsvm.2.dylib" => "libsvm.dylib"
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MachO::Tools.change_dylib_id("#{lib}/libsvm.2.dylib", "#{lib}/libsvm.2.dylib")
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include.install "svm.h"
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end
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test do
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(testpath/"train_classification.txt").write <<~EOS
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+1 201:1.2 3148:1.8 3983:1 4882:1
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-1 874:0.3 3652:1.1 3963:1 6179:1
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+1 1168:1.2 3318:1.2 3938:1.8 4481:1
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+1 350:1 3082:1.5 3965:1 6122:0.2
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-1 99:1 3057:1 3957:1 5838:0.3
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EOS
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(testpath/"train_regression.txt").write <<~EOS
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0.23 201:1.2 3148:1.8 3983:1 4882:1
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0.33 874:0.3 3652:1.1 3963:1 6179:1
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-0.12 1168:1.2 3318:1.2 3938:1.8 4481:1
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EOS
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system "#{bin}/svm-train", "-s", "0", "train_classification.txt"
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system "#{bin}/svm-train", "-s", "3", "train_regression.txt"
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end
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end
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