On 2. juli 2012, at 22.40, Nathaniel Smith wrote:
> On Mon, Jul 2, 2012 at 6:54 PM, Sveinung Gundersen wrote:
>> [snip]
>>
>>
>>
>> Your actual memory usage may not have increased as much as you think,
>> since memmap objects don't necessarily
rray.item()
>else:
> return scalar_or_0d_array
> # works on both numpy 1.5 and numpy 1.6:
> total = scalarify(a.sum())
Thank you for this! However, such a solution would have to be scattered
throughout the code (probably over 100 places), and I would rather not do that.
I g
k (most recent call last):
File "", line 1, in
AttributeError: 'numpy.int64' object has no attribute '__iter__'
>>> len(a.sum())
Traceback (most recent call last):
File "", line 1, in
TypeError: object of type 'numpy.int64' h
