[Numpy-discussion] add axis to results of reduction (mean, min, ...)

[Keith Goodman]

On Thu, Aug 6, 2009 at 8:55 AM, <josef.pktd at 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)