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Closed
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WVM issue in scaling.py #1208

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jranalli
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@jranalli jranalli commented Apr 9, 2021

  • Closes Bug within scaling.py wavelet calculation methodology #1206
  • I am familiar with the contributing guidelines
  • Tests added
  • Updates entries to docs/sphinx/source/api.rst for API changes.
  • Adds description and name entries in the appropriate "what's new" file in docs/sphinx/source/whatsnew for all changes. Includes link to the GitHub Issue with :issue:`num` or this Pull Request with :pull:`num`. Includes contributor name and/or GitHub username (link with :ghuser:`user`).
  • New code is fully documented. Includes numpydoc compliant docstrings, examples, and comments where necessary.
  • Pull request is nearly complete and ready for detailed review.
  • Maintainer: Appropriate GitHub Labels and Milestone are assigned to the Pull Request and linked Issue.

I fixed what I believe is the issue by changing the way the approximation and detail coefficients are calculated. I may be a bit confused about the wavelets because I'm not an expert at this, I'm reading it as a Haar wavelet because it's being calculated using the rolling average. Creating the pull request at this stage so someone can take a look and see if I've gone down the right path here.

jranalli added 3 commits April 9, 2021 16:54
…the original signal.

(cherry picked from commit 942cf0f)
…wing the revised algorithm. Note that there's no independent theoretical verification for these values.

(cherry picked from commit e86ad55)
…tch their intended levels.

(cherry picked from commit 01fe853)
@jranalli jranalli closed this Apr 22, 2021
@jranalli jranalli deleted the wvm-fix branch April 22, 2021 17:06
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Closed following offline discussion with the author of WVM Matlab. Will resubmit pull request based on the decision.

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Bug within scaling.py wavelet calculation methodology
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