HERA-Team / hera_qm

HERA Data Quality Metrics
MIT License
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Add auto_shape_checker to classify antennas based on their (dis)similarity to the average good autocorrelation #435

Closed jsdillon closed 1 year ago

jsdillon commented 1 year ago

This PR creates a new absolute bounds checker that looks for autocorrelations that have different shapes from the average unflagged autocorrelation, excluding flagged channels.

Once a per-polarization reference auto is calcuated, the euclidian distance is calculated between it and each auto (ignoring flagged channels) after normalizing both to have a mean of 1 (so overall power level shouldn't matter). Bounds can be thought of as a relative difference of normalized bandpasses.

codecov[bot] commented 1 year ago

Codecov Report

Base: 97.04% // Head: 97.05% // Increases project coverage by +0.01% :tada:

Coverage data is based on head (1a4eb31) compared to base (a57f874). Patch coverage: 100.00% of modified lines in pull request are covered.

Additional details and impacted files ```diff @@ Coverage Diff @@ ## main #435 +/- ## ========================================== + Coverage 97.04% 97.05% +0.01% ========================================== Files 9 9 Lines 3550 3563 +13 ========================================== + Hits 3445 3458 +13 Misses 105 105 ``` | [Impacted Files](https://codecov.io/gh/HERA-Team/hera_qm/pull/435?src=pr&el=tree&utm_medium=referral&utm_source=github&utm_content=comment&utm_campaign=pr+comments&utm_term=HERA-Team) | Coverage Δ | | |---|---|---| | [hera\_qm/ant\_class.py](https://codecov.io/gh/HERA-Team/hera_qm/pull/435/diff?src=pr&el=tree&utm_medium=referral&utm_source=github&utm_content=comment&utm_campaign=pr+comments&utm_term=HERA-Team#diff-aGVyYV9xbS9hbnRfY2xhc3MucHk=) | `97.59% <100.00%> (+0.16%)` | :arrow_up: | Help us with your feedback. Take ten seconds to tell us [how you rate us](https://about.codecov.io/nps?utm_medium=referral&utm_source=github&utm_content=comment&utm_campaign=pr+comments&utm_term=HERA-Team). Have a feature suggestion? [Share it here.](https://app.codecov.io/gh/feedback/?utm_medium=referral&utm_source=github&utm_content=comment&utm_campaign=pr+comments&utm_term=HERA-Team)

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