100 lines
4.5 KiB
Ruby
100 lines
4.5 KiB
Ruby
class Pythran < Formula
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include Language::Python::Virtualenv
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desc "Ahead of Time compiler for numeric kernels"
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homepage "https://pythran.readthedocs.io/"
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url "https://files.pythonhosted.org/packages/99/e0/ed0e81de05cfa4ecbcbceec6603d175387d8bc7a6332cbfd155d09958ccf/pythran-0.12.0.tar.gz"
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sha256 "eff3dd0d3eebe57372f0d14f82985525e9bcdfb5b1d1010e1932cf9207060f9f"
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license "BSD-3-Clause"
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revision 1
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head "https://github.com/serge-sans-paille/pythran.git", branch: "master"
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bottle do
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sha256 cellar: :any_skip_relocation, arm64_ventura: "e5bf394a94b7af4cd5144c55e796a3de7a30e82f7966d6b2b5dc1aa03a1091f8"
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sha256 cellar: :any_skip_relocation, arm64_monterey: "e5bf394a94b7af4cd5144c55e796a3de7a30e82f7966d6b2b5dc1aa03a1091f8"
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sha256 cellar: :any_skip_relocation, arm64_big_sur: "e5bf394a94b7af4cd5144c55e796a3de7a30e82f7966d6b2b5dc1aa03a1091f8"
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sha256 cellar: :any_skip_relocation, ventura: "ea51ad415eb3da7ed5e1dea09bd6a2caa7a6bd8c1ff24e9091f73c6295d0215f"
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sha256 cellar: :any_skip_relocation, monterey: "ea51ad415eb3da7ed5e1dea09bd6a2caa7a6bd8c1ff24e9091f73c6295d0215f"
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sha256 cellar: :any_skip_relocation, big_sur: "ea51ad415eb3da7ed5e1dea09bd6a2caa7a6bd8c1ff24e9091f73c6295d0215f"
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sha256 cellar: :any_skip_relocation, catalina: "ea51ad415eb3da7ed5e1dea09bd6a2caa7a6bd8c1ff24e9091f73c6295d0215f"
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sha256 cellar: :any_skip_relocation, x86_64_linux: "f30eb8b8aaafff3f6cfa3bd473f3d8b9d63239f5e3ce2630797855a331a230ec"
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end
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depends_on "gcc" # for OpenMP
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depends_on "numpy"
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depends_on "openblas"
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depends_on "python@3.11"
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depends_on "six"
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resource "beniget" do
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url "https://files.pythonhosted.org/packages/14/e7/50cbac38f77eca8efd39516be6651fdb9f3c4c0fab8cf2cf05f612578737/beniget-0.4.1.tar.gz"
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sha256 "75554b3b8ad0553ce2f607627dad3d95c60c441189875b98e097528f8e23ac0c"
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end
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resource "gast" do
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url "https://files.pythonhosted.org/packages/48/a3/0bd844c54ae8141642088b7ae09dd38fec2ec7faa9b7d25bb6a23c1f266f/gast-0.5.3.tar.gz"
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sha256 "cfbea25820e653af9c7d1807f659ce0a0a9c64f2439421a7bba4f0983f532dea"
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end
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resource "ply" do
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url "https://files.pythonhosted.org/packages/e5/69/882ee5c9d017149285cab114ebeab373308ef0f874fcdac9beb90e0ac4da/ply-3.11.tar.gz"
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sha256 "00c7c1aaa88358b9c765b6d3000c6eec0ba42abca5351b095321aef446081da3"
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end
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def install
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if OS.mac?
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gcc_major_ver = Formula["gcc"].any_installed_version.major
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inreplace "pythran/pythran-darwin.cfg" do |s|
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s.gsub!(/^include_dirs=/, "include_dirs=#{Formula["openblas"].opt_include}")
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s.gsub!(/^library_dirs=/, "library_dirs=#{Formula["openblas"].opt_lib}")
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s.gsub!(/^blas=.*/, "blas=openblas")
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s.gsub!(/^CC=.*/, "CC=#{Formula["gcc"].opt_bin}/gcc-#{gcc_major_ver}")
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s.gsub!(/^CXX=.*/, "CXX=#{Formula["gcc"].opt_bin}/g++-#{gcc_major_ver}")
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end
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end
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virtualenv_install_with_resources
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end
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test do
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pythran = Formula["pythran"].opt_bin/"pythran"
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python = Formula["python@3.11"].opt_libexec/"bin/python"
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(testpath/"dprod.py").write <<~EOS
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#pythran export dprod(int list, int list)
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def dprod(arr0, arr1):
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return sum([x*y for x,y in zip(arr0, arr1)])
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EOS
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system pythran, testpath/"dprod.py"
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rm_f testpath/"dprod.py"
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assert_equal "11", shell_output("#{python} -c 'import dprod; print(dprod.dprod([1,2], [3,4]))'").chomp
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(testpath/"arc_distance.py").write <<~EOS
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#pythran export arc_distance(float[], float[], float[], float[])
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import numpy as np
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def arc_distance(theta_1, phi_1, theta_2, phi_2):
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"""
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Calculates the pairwise arc distance between all points in vector a and b.
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"""
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temp = np.sin((theta_2-theta_1)/2)**2 + np.cos(theta_1)*np.cos(theta_2)*np.sin((phi_2-phi_1)/2)**2
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distance_matrix = 2 * np.arctan2(np.sqrt(temp), np.sqrt(1-temp))
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return distance_matrix
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EOS
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# Test with configured gcc to detect breakages from gcc major versions and for OpenMP support
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with_env(CC: nil, CXX: nil) do
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system pythran, "-DUSE_XSIMD", "-fopenmp", "-march=native", testpath/"arc_distance.py"
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end
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rm_f testpath/"arc_distance.py"
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system python, "-c", <<~EOS
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import numpy as np
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import arc_distance
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d = arc_distance.arc_distance(
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np.array([12.4,0.5,-5.6,12.34,9.21]), np.array([-5.6,3.4,2.3,-23.31,12.6]),
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np.array([3.45,1.5,55.4,567.0,43.2]), np.array([56.1,3.4,1.34,-56.9,-3.4]),
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)
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assert ([1.927, 1., 1.975, 1.83, 1.032] == np.round(d, 3)).all()
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EOS
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end
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end
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