ENH: Adding __array_ufunc__ capability to MaskedArrays (again) #22914
Commits on Jan 3, 2023
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ENH: Adding __array_ufunc__ capability to MaskedArrays.
This enables any ufunc numpy operations that are called on a MaskedArray to use the masked version of that function automatically without needing to resort to np.ma.func() calls.
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BUG: fix ma.minimum.reduce with axis keyword
Fixes the problem reported at numpy#21977 (comment) The reduce method here effectively calls itself with an unmasked MaskedArray (mask=nomask) and then expects either a MaskedArray or a scalar. This change ensures that an ordinary ndarray is converted to a MaskedArray, following the pattern already used in mean and var in this module.
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TST: add a test for ma.minimum.reduce with axis keyword
Adapted from the problem reported at numpy#21977 (comment)
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ENH: Remove masked ufunc power restriction
Now we are calling np.power() in std() which goes through the ufunc machinery, so we don't want to pass any additional unsafe casting kwargs that aren't allowed within the masked implementation.
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FIX: Rearrange handling of ndarray-like ufuncs
Move the np-ufunc check to the top of the routine so we immediately go to super() when necessary. Before we were returning NotImplemented if an arg wasn't able to be handled. Update the arg instance check to defer for everything but another class that has implemented __array_ufunc__
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FIX: view should return the type(self) rather than MaskedArray
This allows for subclasses to be handled correctly
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MAINT: Remove unused delegate_binop code
This is handled in the C code now within the ufunc machinery.
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