48 lines
1.5 KiB
Ruby
48 lines
1.5 KiB
Ruby
class Rgf < Formula
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desc "Regularized Greedy Forest library"
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homepage "https://github.com/RGF-team/rgf"
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url "https://github.com/RGF-team/rgf/archive/3.10.0.tar.gz"
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sha256 "e2cd1f0c8e3a23a4b5a06e0cf7dade27b0d390a4682c67f450877b945126aebc"
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license "MIT"
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livecheck do
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url :stable
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strategy :github_latest
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end
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bottle do
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sha256 cellar: :any_skip_relocation, arm64_big_sur: "521b1290a8f4c1df387d6a5154ee17cfeb4135b0bc29daffc8233b5d6e050e4c"
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sha256 cellar: :any_skip_relocation, big_sur: "88ea31516318953101add3d40fee31904651b93b27b1050650b9ce234ed7c867"
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sha256 cellar: :any_skip_relocation, catalina: "8183722939081f3a0fc2d55ced41d873fb77e0fb00573713c9aac0e935e952c8"
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sha256 cellar: :any_skip_relocation, mojave: "157d6024686c5333c2789b0f40fe3aa7bbaf5341b39c9ee8fe0654db45543a74"
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end
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depends_on "cmake" => :build
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def install
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cd "RGF" do
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mkdir "build" do
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system "cmake", *std_cmake_args, ".."
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system "make"
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system "make", "install" # installs to bin/rgf
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end
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bin.install "bin/rgf"
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pkgshare.install "examples"
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end
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end
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test do
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cp_r (pkgshare/"examples/sample/."), testpath
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parameters = %w[
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algorithm=RGF
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train_x_fn=train.data.x
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train_y_fn=train.data.y
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test_x_fn=test.data.x
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reg_L2=1
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model_fn_prefix=rgf.model
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]
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output = shell_output("#{bin}/rgf train_predict #{parameters.join(",")}")
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assert_match "Generated 20 model file(s)", output
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end
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end
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