This strikes me as a bug-- haven't checked NumPy 1.6 yet but this
happens in 1.5.1. Here's a toy example:
class MyNdarray(np.ndarray):
def __new__(cls, data):
subarr = np.array(data, dtype=np.float64).view(cls)
return subarr
def __radd__(self, other):
print 'hello
Hi,
I am pleased to announce the availability of the third release candidate of
NumPy 1.6.0.
Compared to the second release candidate, two issues in f2py and one in
loadtxt were fixed. If no new problems are reported, the final release will
be in one week.
Sources and binaries can be found at
ht
On Fri, May 6, 2011 at 12:57 PM, Derek Homeier <
de...@astro.physik.uni-goettingen.de> wrote:
>
> On 6 May 2011, at 07:53, Ralf Gommers wrote:
>
> >
> > >> Looks okay, and I agree that it's better to fix it now. The timing
> > >> is a bit unfortunate though, just after RC2. I'll have closer look
>
Hello,
I'm trying to use apply_along_axis with a function that returns 2 arrays,
but I always get different error messages.
For example, here is a test:
>>> from numpy import *
>>> def f(x):
... a = array([1, 2, 3], dtype=float)
... b = array([4, 5, 6], dtype=float)
... return (a, b)
