38 lines
1.5 KiB
Python
38 lines
1.5 KiB
Python
# Copyright 2013-2022 Lawrence Livermore National Security, LLC and other
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# Spack Project Developers. See the top-level COPYRIGHT file for details.
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#
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# SPDX-License-Identifier: (Apache-2.0 OR MIT)
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from spack.package import *
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class PyScikitOptimize(PythonPackage):
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"""Scikit-Optimize, or skopt, is a simple and efficient library to
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minimize (very) expensive and noisy black-box functions. It implements
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several methods for sequential model-based optimization. skopt aims to
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be accessible and easy to use in many contexts.
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The library is built on top of NumPy, SciPy and Scikit-Learn."""
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homepage = "https://scikit-optimize.github.io"
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pypi = "scikit-optimize/scikit-optimize-0.5.2.tar.gz"
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git = "https://github.com/scikit-optimize/scikit-optimize.git"
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maintainers = ["liuyangzhuan"]
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version("master", branch="master")
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version("0.5.2", sha256="1d7657a4b8ef9aa6d81e49b369c677c584e83269f11710557741d3b3f8fa0a75")
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variant("plots", default=True, description="Build with plot support from py-matplotlib")
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variant("gptune", default=False, description="Build with patches for GPTune")
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depends_on("py-setuptools", type="build")
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depends_on("py-numpy", type=("build", "run"))
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depends_on("py-scipy@0.14.0:", type=("build", "run"))
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depends_on("py-scikit-learn@0.19.1:", type=("build", "run"))
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depends_on("py-pyyaml", when="+gptune", type=("build", "run"))
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depends_on("py-matplotlib", when="+plots")
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patch("space.patch", when="+gptune")
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