[Numpy-discussion] inplace operations

Christopher Barker Chris.Barker at noaa.gov
Fri Jan 26 17:35:08 CST 2007


BBands wrote:
> If I have a NumPy array like so:
> 
> [[1, 12],
>  [2, 13],
>  [3, 14],
>  [4, 15],
>  [5, 16],
>  [6, 15],
>  [7, 14]]
> 
> How can I do an inplace diff, ending up with this?
> 
> [[1, 0],
>  [2, 1],
>  [3, 1],
>  [4, 1],
>  [5, 1],
>  [6, -1],
>  [7, -1]]

 >>> import numpy as N
 >>> a = N.array([[1, 12],
...  [2, 13],
...  [3, 14],
...  [4, 15],
...  [5, 16],
...  [6, 15],
...  [7, 14]])
 >>>
 >>> a
array([[ 1, 12],
        [ 2, 13],
        [ 3, 14],
        [ 4, 15],
        [ 5, 16],
        [ 6, 15],
        [ 7, 14]])
 >>> a[1:,1] = a[1:,1] - a[:-1,1]
 >>> a
array([[ 1, 12],
        [ 2,  1],
        [ 3,  1],
        [ 4,  1],
        [ 5,  1],
        [ 6, -1],
        [ 7, -1]])
 >>> a[0,1] = 0


 > Also, can I covert to natural logs in place?

 >>> a
array([[  1.,  12.],
        [  2.,  13.],
        [  3.,  14.],
        [  4.,  15.],
        [  5.,  16.],
        [  6.,  15.],
        [  7.,  14.]])
 >>> N.log(a[:,1], a[:,1])
array([ 2.48490665,  2.56494936,  2.63905733,  2.7080502 ,  2.77258872,
         2.7080502 ,  2.63905733])
 >>> a
array([[ 1.        ,  2.48490665],
        [ 2.        ,  2.56494936],
        [ 3.        ,  2.63905733],
        [ 4.        ,  2.7080502 ],
        [ 5.        ,  2.77258872],
        [ 6.        ,  2.7080502 ],
        [ 7.        ,  2.63905733]])

All ufuncs (like log() ) take an optional parameter that is the array 
you want the output to go to. If you pass in the same array, the 
operation happens in place.

By the way, it looks like your first column is an index number. As The 
array structure keeps track of that for you, you might just as well 
store just the data in a single (N,) shaped array.

-Chris


-- 
Christopher Barker, Ph.D.
Oceanographer

Emergency Response Division
NOAA/NOS/OR&R            (206) 526-6959   voice
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Chris.Barker at noaa.gov


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