Hi everyone, A long time ago, Aditya Sethi <ady.sethi@gmail... 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'
Here's the workaround I found to that problem:
uadd.accumulate([1,2,3], dtype='object') array([1, 3, 6], dtype=object)
It seems like "accumulate" infers that 'l' is the required output dtype, but does not have the appropriate implementation:
uadd.types ['OO->O']
Forcing the output dtype to be 'object' (the only supported dtype) seems to do the trick. Hope this helps, -- Pascal