On Wed, Apr 20, 2011 at 2:19 PM, Daniel Lepage wrote:
> You can also insert new axes when you slice an array via np.newaxis, fwiw:
>
import numpy as np
x = np.random.random((3,4,5))
y = x.mean(axis=1)
y.shape
> (3, 5)
y[:,np.newaxis,:].shape
> (3, 1, 5)
That's convenient
On 04/20/2011 12:24 PM, Yannick Copin wrote:
> gmail.com> writes:
>> I also proposed this already once.
>>
>> However there is already function in numpy (where I have often
>> problems remembering the name):
>>
>> numpy.expand_dims(a, axis)
> Ah, thanks for the tip, I didn't know this one. Th
You can also insert new axes when you slice an array via np.newaxis, fwiw:
>>> import numpy as np
>>> x = np.random.random((3,4,5))
>>> y = x.mean(axis=1)
>>> y.shape
(3, 5)
>>> y[:,np.newaxis,:].shape
(3, 1, 5)
--
Dan Lepage
On Wed, Apr 20, 2011 at 1:24 PM, Yannick Copin
wrote:
> gmail.com>
gmail.com> writes:
> I also proposed this already once.
>
> However there is already function in numpy (where I have often
> problems remembering the name):
>
> numpy.expand_dims(a, axis)
Ah, thanks for the tip, I didn't know this one. The name is unfortunate
indeed...
Cheers,
Yannick
_
On Wed, Apr 20, 2011 at 6:27 AM, Yannick Copin wrote:
> Hi,
>
> I'm a very frequent user of the following "unsqueeze" function, which I
> initially copied from scipy/stats/models/robust/scale.py and which seems to be
> also present in scikits.statsmodels.tools.unsqueeze. Would it be possible to
>
Hi,
I'm a very frequent user of the following "unsqueeze" function, which I
initially copied from scipy/stats/models/robust/scale.py and which seems to be
also present in scikits.statsmodels.tools.unsqueeze. Would it be possible to
include it natively to numpy?
def unsqueeze(data, axis, oldsha
