[Numpy-discussion] Upgrade to 1.6.x: frompyfunc() ufunc casting issue
Aditya Sethi
ady.sethi at gmail.com
Mon Sep 19 19:18:29 EDT 2011
Hi Stefan,
The problem arises when you try to use methods of the ufunc.
So for the custom universal function previously defined, uadd:
uadd([1,2,3],[1,2,3]) works fine.
But uadd.accumulate(..) or uadd.reduce(..) fail with error:
ValueError: could not find a matching type for add (vectorized).accumulate
( or (vectorized).reduce )
Apologies, I should have been more clear before.
Thanks,
Aditya
2011/9/19 Stéfan van der Walt <stefan at sun.ac.za>
> Hi,
>
> On Mon, Sep 19, 2011 at 2:38 PM, Aditya Sethi <ady.sethi at gmail.com> wrote:
> > I am facing an issue upgrading numpy from 1.5.1 to 1.6.1.
> > In numPy 1.6, the casting behaviour for ufunc has changed and has become
> > stricter.
> > Can someone advise how to implement the below simple example which worked
> in
> > 1.5.1 but fails in 1.6.1?
> >>>> import numpy as np
> >>>> def add(a,b):
> > ... return (a+b)
> >>>> uadd = np.frompyfunc(add,2,1)
> >>>> uadd
> > <ufunc 'add (vectorized)'>
> >>>> uadd.accumulate([1,2,3])
> > Traceback (most recent call last):
> > File "<stdin>", line 1, in <module>
> > ValueError: could not find a matching type for add
> (vectorized).accumulate,
> > requested type has type code 'l'
>
> Seems to work ok on the latest version:
>
> In [12]: uadd([1,2,3],[1,2,3])
> Out[12]: array([2, 4, 6], dtype=object)
>
> In [13]: np.__version__
> Out[13]: '2.0.0.dev-af22fc4'
>
> Cheers
> Stéfan
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