ENH: stats: end-to-end array-API support for NHSTs with chi-squared null distribution #20782
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mdhaber
commented
May 24, 2024
| array_args = [np.asarray(arg) for arg in array_args] | ||
| out = _f(*array_args, *other_args, **kwargs) | ||
| return _xp.asarray(out) | ||
| _f = _generic_implementations[f_name](xp=xp, spx=spx) |
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I reworked _generic_implementations so we have more flexibility. Previously, _generic_implementations contained functions that had to work for any backend; now, _generic_implementations contains functions that return a function if possible/desired or None otherwise.
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I've checked locally and all tests pass with CuPy now except So this is ready for review, but there are minor things to change before merge even if CI passes. Update: CI failure is unrelated. |
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Oops, yes, all done. Thanks! |
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Reference issue
Toward gh-20544
Follow-up to gh-20777
What does this implement/fix?
Similar to gh-20777 but for hypothesis tests with a chi-squared null distribution.
Additional information
Technically I should probably be passing
symmetric=Falsein all these calls to_get_pvalue, butalternative='greater'is specified explicitly, so it doesn't really matter.