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

Robert Kern robert.kern@gmail....
Thu Aug 6 11:07:14 CDT 2009


On Thu, Aug 6, 2009 at 11:03, Keith Goodman<kwgoodman@gmail.com> wrote:
> 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)

Ouch! That doesn't handle axis=-1.

if axis != 0:
    ind = [slice(None)] * x.ndim
    ind[axis] = np.newaxis

-- 
Robert Kern

"I have come to believe that the whole world is an enigma, a harmless
enigma that is made terrible by our own mad attempt to interpret it as
though it had an underlying truth."
  -- Umberto Eco


More information about the NumPy-Discussion mailing list