[Numpy-discussion] add axis to results of reduction (mean, min, ...)
Keith Goodman
kwgoodman@gmail....
Thu Aug 6 11:03:46 CDT 2009
On Thu, Aug 6, 2009 at 8:55 AM, <josef.pktd@gmail.com> wrote:
> What's the best way of getting back the correct shape to be able to
> broadcast, mean, min,.. to the original array, that works for
> arbitrary dimension and axis?
>
> I thought I have seen some helper functions, but I don't find them anymore?
>
> Josef
>
>>>> a
> array([[1, 2, 3, 3, 0],
> [2, 2, 3, 2, 1]])
>>>> a-a.max(0)
> array([[-1, 0, 0, 0, -1],
> [ 0, 0, 0, -1, 0]])
>>>> a-a.max(1)
> Traceback (most recent call last):
> File "<pyshell#135>", line 1, in <module>
> a-a.max(1)
> ValueError: shape mismatch: objects cannot be broadcast to a single shape
>>>> a-a.max(1)[:,None]
> array([[-2, -1, 0, 0, -3],
> [-1, -1, 0, -1, -2]])
Would this do it?
>> pylab.demean??
Type: function
Base Class: <type 'function'>
String Form: <function demean at 0x3c5c050>
Namespace: Interactive
File: /usr/lib/python2.6/dist-packages/matplotlib/mlab.py
Definition: pylab.demean(x, axis=0)
Source:
def demean(x, axis=0):
"Return x minus its mean along the specified axis"
x = np.asarray(x)
if axis:
ind = [slice(None)] * axis
ind.append(np.newaxis)
return x - x.mean(axis)[ind]
return x - x.mean(axis)
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