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

[Wei, Huayi]

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

[Nathan Goldbaum]

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

[Julian Taylor]

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

[Sebastian Berg]

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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> 

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