[Numpy-discussion] Does numpy.bincount support numpy.float128 type weights?

Julian Taylor jtaylor.debian at googlemail.com
Wed Nov 30 17:16:29 EST 2016


Also note that float128 is rarely what you want.
It is not a quad precision value, it maps to C long double which is 80
bit on x86 and less on stuff like arm.

On 30.11.2016 22:59, Nathan Goldbaum wrote:
> I think this is a deficiency in the current implementation of bincount,
> which always casts the weights to float64. This WIP pull request should
> probably fix it:
> 
> https://github.com/numpy/numpy/pull/7464
> 
> On Wed, Nov 30, 2016 at 3:54 PM, Wei, Huayi <weihuayi at xtu.edu.cn
> <mailto:weihuayi at xtu.edu.cn>> 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 <http://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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