Adding type hints for cleanlab/filter #598
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## master #598 +/- ##
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Coverage 96.23% 96.23%
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Files 60 60
Lines 4705 4707 +2
Branches 817 817
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+ Hits 4528 4530 +2
Misses 91 91
Partials 86 86
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Adding the types for variables within the functions. type cheatsheet: 1. np array of float type: npt.NDArray["np.floating[T]"] 2. np array of int type: npt.NDArray[np.int_] 3. np array of bool type: npt.NDArray[np.bool_] 4. np.array of either bool or int: npt.NDArray[Union[np.bool_, np.int_]]
cleanlab/filter.py
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| @@ -298,16 +298,16 @@ class 0, 1, ..., K-1. | |||
| # Create `prune_count_matrix` with the number of examples to remove in each class and | |||
| # leave at least min_examples_per_class examples per class. | |||
| # `prune_count_matrix` is transposed relative to the confident_joint. | |||
| prune_count_matrix = _keep_at_least_n_per_class( | |||
| prune_count_matrix:npt.NDArray[np.int_] = _keep_at_least_n_per_class( | |||
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The prune_count_matrix changes the data type (from an array of int to float). Should I declare it as a float? Although the function here returns int explicitly.
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I'll have to take a better look later today.
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@elisno did you have a chance to look at this?
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I don't see where the datatype should change in this function. I think this annotation is fine for now.
cleanlab/filter.py
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| confident_joint: Optional[np.ndarray] = None, | ||
| n_jobs: Optional[int] = None, | ||
| verbose: bool = False, | ||
| ) -> np.ndarray: | ||
| ) -> npt.NDArray[Union[np.bool_, np.int_]]: | ||
| #TODO: add docstring in the same format as other functions with args and returns |
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Can I add to-dos wherever the doc doesn't have the same format as the other functions?
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Are you referring to the "shape"-format?
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The format of doc itself.
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Ohh right, now I see what you mean! Thank you for pointing this out!
That's not related to this PR, so you shouldn't add this particular to-do in this PR.
Feel free to open an issue!
If you find other instances, you can add them to the same issue.
We want to address these kinds of docstrings in a separate PR.
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I've updated some of the type-hints to pass more of the strict checks (not 100% just yet). CI is now failing on "Test without optional dependencies and with minimum compatible versions of dependencies", where numpy.typing is not recognized. |
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