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[New Check]: TimeSeries with empty dataset #403

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@alessandratrapani alessandratrapani commented Sep 18, 2023

Related to Issue #324
add check function for empty dataset

  • add check function
  • add unit tests
  • add check function documentation
  • update CHANGELOG.md

@alessandratrapani alessandratrapani marked this pull request as draft September 18, 2023 09:22
@alessandratrapani alessandratrapani changed the title add check function for empty dataset [New Check]: TimeSeries with empty dataset Sep 18, 2023
@alessandratrapani alessandratrapani added the category: new check a new best practices check to apply to all NWBFiles and their contents label Sep 18, 2023
@alessandratrapani alessandratrapani self-assigned this Sep 18, 2023
@CodyCBakerPhD
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CodyCBakerPhD commented Sep 18, 2023

@alessandratrapani Very minor thing, but it seems as if GitHub is not smart enough to recognize the keyphrase 'Related to Issue #...' when automatically adding the development issue link

I always do 'fix #...', I think I've seen 'resolve #...' work for others

No worries, though - it's easy to add it afterward through the web interface

@CodyCBakerPhD CodyCBakerPhD linked an issue Sep 18, 2023 that may be closed by this pull request
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Comment on lines +34 to +40
def is_empty_data(data):
if isinstance(data, ndarray):
return data.size == 0
elif isinstance(data, (list, tuple)):
return all(is_empty_data(item) for item in data)
else:
return not bool(data)
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I wouldn't mind if this were moved to the common utils to be used by any other check (or anyone else) going forward 😃

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I want to say the basic structure looks good for checking the data field; there are perhaps some other cases we must consider

The best way to tell will be to add several tests (cases where it should pass without raising a message, cases where it should catch 'emptiness', skips on certain edge cases such as ImageSeries)

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[Add Check]: Datasets are not empty
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