Hi,
You can try masked_array module:
x = np.array([[0,1,2],[3,4,5],[6,7,8]])
I3 np.ma.masked_where(x<1, x)
O3
masked_array(data =
[[-- 1 2]
[3 4 5]
[6 7 8]],
mask =
[[ True False False]
[False False False]
[False False False]],
fill_value = 999999)
There might be a smarter solution than this, since ma tends to get slower
when you deal with big data arrays. But you retain the 2D information
instead of getting a flattened np.array.
On Wed, Mar 14, 2012 at 5:35 PM, jonasr <[email protected]> wrote:
>
> Hello,
>
> my problem is that i want to remove some small numbers of an 2d array,
> for example if i want to sort out all numbers smaller then 1 of an array i
> get
>
> x=[[0,1,2],[3,4,5][6,7,8]]
>
> c=x>=1
>
> In [213]: c
> Out[213]:
> array([[False, True, True],
> [ True, True, True],
> [ True, True, True]], dtype=bool)
>
> In [214]: x[c]
> Out[214]: array([1, 2, 3, 4, 5, 6, 7, 8])
>
> the problem ist that i now have a 1d array, is there any possibility to
> keep the 2d structure ?
>
> greets jonas
> --
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--
Gökhan
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