[BUG] `np.average` with weights fails

[dlakaplan]

import numpy_quaddtype
x=numpy_quaddtype.QuadPrecision([1,2,3])
y=numpy_quaddtype.QuadPrecision([2,2.5,2.3])
np.average(x,weights=1/y)

fails:

File ~/miniforge3/envs/pintdev_arm/lib/python3.14/site-packages/numpy/lib/_function_base_impl.py:587, in average(a, axis, weights, returned, keepdims)
    584 else:
    585     result_dtype = np.result_type(a.dtype, wgt.dtype)
--> 587 scl = wgt.sum(axis=axis, dtype=result_dtype, **keepdims_kw)
    588 if np.any(scl == 0.0):
    589     raise ZeroDivisionError(
    590         "Weights sum to zero, can't be normalized")

File ~/miniforge3/envs/pintdev_arm/lib/python3.14/site-packages/numpy/_core/_methods.py:49, in _sum(a, axis, dtype, out, keepdims, initial, where)
     47 def _sum(a, axis=None, dtype=None, out=None, keepdims=False,
     48          initial=_NoValue, where=True):
---> 49     return umr_sum(a, axis, dtype, out, keepdims, initial, where)

TypeError: Cannot pass a new user DType instance to the `dtype` or `signature` arguments of ufuncs. Pass the DType class instead.

Without the weights argument this works OK.

[SwayamInSync]

Thanks @dlakaplan seems the issue from NumPy side

TypeError: Cannot pass a new user DType instance to the dtype or signature arguments of ufuncs. Pass the DType class instead.

The error message is same as numpy/numpy#31447

I guess we need to change that line in numpy?

- return umr_sum(a, axis, dtype, out, keepdims, initial, where)
+ return umr_sum(a, axis, type(dtype), out, keepdims, initial, where)

Will check and drop the PR

[dlakaplan]

Thanks. Note that I am seeing similar errors with np.histogram()

[SwayamInSync]

Yes that'll too get resolve in the next release!!

Thanks. Note that I am seeing similar errors with np.histogram()