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Adding support for numpy 2 #132

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merged 5 commits into from
Jul 15, 2024
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prsabahrami
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Adhering to NEP 50, np.can_cast no longer applies any value-based logic for 0-D arrays and NumPy scalars.

Using np.min_scalar_type(value), the data type with the smallest size and smallest scalar kind that can hold value is checked against dtype.

However, there is still another issue due to the below schema of numpy 2.0.0's promotion rules:
image

For example, in the case of casting np.int64(5) to np.int8 , np.min_scalar_type(np.int64(5)) returns np.uint8, and according to the diagram, np.uint8 can not be casted to np.int8. I have manually checked if value is of kind uint and dtype is of kind np.signedinteger and if the casting can safely happen.

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Thanks!

pyproject.toml Outdated Show resolved Hide resolved
@pavelzw pavelzw added the enhancement New feature or request label Jul 14, 2024
Co-authored-by: Pavel Zwerschke <[email protected]>
@pavelzw pavelzw merged commit 576680c into Quantco:main Jul 15, 2024
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@prsabahrami
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My pleasure!

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2 participants