33 lines
1.6 KiB
Python
33 lines
1.6 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 RPtw(RPackage):
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"""Parametric Time Warping.
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Parametric Time Warping aligns patterns, i.e. it aims to put corresponding
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features at the same locations. The algorithm searches for an optimal
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polynomial describing the warping. It is possible to align one sample to a
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reference, several samples to the same reference, or several samples to
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several references. One can choose between calculating individual warpings,
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or one global warping for a set of samples and one reference. Two
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optimization criteria are implemented: RMS (Root Mean Square error) and WCC
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(Weighted Cross Correlation). Both warping of peak profiles and of peak
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lists are supported. A vignette for the latter is contained in the inst/doc
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directory of the source package - the vignette source can be found on the
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package github site."""
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cran = "ptw"
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version("1.9-16", sha256="7e87c34b9eeaeabe3bfb937162e6cda4dd48d6bd6a97b9db8bb8303d131caa66")
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version("1.9-15", sha256="22fa003f280bc000f46bca88d69bf332b29bc68435115ba8044533b70bfb7b46")
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version("1.9-13", sha256="7855e74a167db3d3eba9df9d9c3daa25d7cf487cbcfe8b095f16d96eba862f46")
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version("1.9-12", sha256="cdb1752e04e661e379f11867b0a17e2177e9ee647c54bbcc37d39d6b8c062b84")
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depends_on("r-nloptr", type=("build", "run"))
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depends_on("r-rcppde", type=("build", "run"), when="@1.9-16:")
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