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Support use of Google Film for temporal interpolation #2270
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…pecific plugin and addition of a Google Film option to the temporal interpolation plugin and CLI.
…he situation where a range of forecast periods are available, but within this range there are gaps to be filled. This class also checks an attribute, which contains information about the forecast source at each forecast period. Forecast periods at which there is a transition from one forecast source to another will be the target for the interpolation.
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bayliffe
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A nice round 30 comments for you.
* upstream/master: BUG: gh actions coverage report (metoppv#2269) Bump actions/checkout from 5 to 6 (metoppv#2272) Bump actions/github-script from 7 to 8 (metoppv#2271) Fix acceptance tests that were relying on a warning being raised (metoppv#2268) Merge CLI and application UI improvements (metoppv#2222) OrographicEnhancement CLI -> MetaOrographicEnhancement application (metoppv#2221)
… batched approach used for Google Film interpolation.
…parallel backend available using the joblib package.
bayliffe
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I believe you will need to modify the improver_production environment in the long term, but for now the improver_tests/acceptance/test_temporal_interpolate.py test fails when running the acceptance tests as the tensorflow_hub module is not found. You need to extend your pytest.skip test to include not only the availability of the google film model but also the tensorflow_hub module.
bayliffe
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Thanks Gavin. Automated tests failing, but ready for second review.
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Thanks @gavinevans. I've added some comments.
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Note that some functions in this PR are deliberately not covered by unit tests e.g. |
maxwhitemet
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Thanks @gavinevans. I'm happy with the changes made. Approved 👍
Addresses https://github.com/metoppv/mo-blue-team/issues/763
improver_test_data PR: metoppv/improver_test_data#118
Description
This PR adds two pieces of functionality:
File breakdown:
temporal-interpolateCLI but is intended to take a collection of validity times for a forecast from a fixed forecast reference time and fill gaps, or smooth across transitions between forecast sources.Testing: