Fist off, a word of caution. float128 depends on your system and maps to whatever longdouble is (IIRC) or may not even exist. So I hope you don't expect IEEE 128 bit floats, if you are unsure, maybe check `np.finfo`.
If speed does not matter
```
res = np.zeros(np.max(b), dtype=np.longdouble)
np.add.at(res, b, a)
```
will work, but do not expect it to be fast.
- Sebastian
On Do, 2016-12-01 at 05:54 +0800, Wei, Huayi wrote:
> Hi, There,
>
> Here is a sample code using `numpy.bincount`
>
> import numpy as np
> a = np.array([1.0, 2.0, 3.0], dtype=np.float128)
> b = np.array([1, 2, 0], dtype=np.int)
> c = np.bincount(b, weights=a)
>
> If run it, I get the following error report:
>
> ----> 1 c = np.bincount(b, weights=a)
> TypeError: Cannot cast array data from dtype('float128') to
> dtype('float64') according to the rule 'safe'
>
> Is it a bug of `np.bincount`? Does there exist any similar function
> which I can use to do the similar thing with numpy.float128 type
> weights?
>
> Best
>
> Huayi
>
>
>
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