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feature/mypy-types-cleanlab-internal-utils#608
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feature/mypy-types-cleanlab-internal-utils#608
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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_]]
functions added for:1. remove_noise_from_class2. clip_noise_rates3. clip_values4. value_counts
functions added for:1. remove_noise_from_class2. clip_noise_rates3. clip_values4. value_counts
…m:unna97/cleanlab into feature/mypy-types-cleanlab-internal-util
Codecov ReportAll modified and coverable lines are covered by tests ✅
Additional details and impacted files@@ Coverage Diff @@## master #608 +/- ##======================================= Coverage 96.23% 96.23% ======================================= Files 60 60 Lines 4705 4707 +2 Branches 817 817 =======================================+ Hits 4528 4530 +2 Misses 91 91 Partials 86 86 ☔ View full report in Codecov by Sentry. |
Thanks for the PR! The internal utils module is quite large, so how about we work on those in smaller segments (say 5-10 functions/methods)? I think we can just focus on the functions you've annotated up to this point:
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In Note that the It's outside of our control, so we should ignore the specific warning associated with that function call. - x = np.copy(noise_matrix)+ x: npt.NDArray["np.floating[T]"] = np.copy(noise_matrix) # type: ignore[no-untyped-call] We assume that the copied variable should have the same type as the input ( |
Sure@elisno, do you mean with a separate PR for the above functions? |
You should use this PR for those functions. |
Yes, for bigger files I am using one PR. while for other segments as you have mentioned before. |
- value_counts_fill_missing_classes- get_missing_classes- round_preserving_sum- estimate_pu_f1- confusion_matrix- print_square_matrix- print_noise_matrix- print_inverse_noise_matrix- print_joint_matrix- compress_int_array- subset_X_y- subset_labels- num_unique_classes- get_unique_classes- format_labels- smart_display_dataframe
@elisno sorry for doing so much in a single commit. I did add type hints for functions other than those you mentioned. There are specific errors in outputs that I am unsure about. |
@elisno Did you have a chance to review this? |
@elisno I was waiting for suggestions before making any further changes. Will you still be reviewing this branch? |
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