Numpy JSON serialization #160
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force-serialize numpy dtypes
| self.data.add(Observation(time=time, | ||
| duration=duration, | ||
| self.data.add(Observation(time=float(time), | ||
| duration=float(duration), | ||
| value=value, | ||
| confidence=confidence)) |
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I know confidence can be None, but might we want a similar coercion here too?
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Confidence is not typed in the schema. Technically it can be anything, just like value, so we can't coerce here.
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Yup. The reasoning here is confidence is namespace-dependent; sometimes it's required (tempo), sometimes it's optional (msd_tagtraum).
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| # And that it says the right thing (roughly) | |||
| assert 'deprecated' in str(out[0].message).lower() | |||
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| def test_numpy_serialize(): | |||
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This looks good for JObject, which I guess is testing serialize_object under the hood ... I'm wondering if it's worth checking the float casting for the observation data in Annotation?
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Exactly. I just pushed up a second test for Annotation, working on observation fields. I think that should cover it for now.
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LGTM 👍 |
This PR fixes #159 by doing explicit type coercion on numpy scalars when converting to JSON.
It's a bit of a stop-gap solution for now. I think we should at some point re-structure how
serialize_objis implemented and used, so that it applies transparently throughout all__json__calls. That's probably out of scope for this fix though, so this PR should be ready to go.