Re: [Numpy-discussion] Multi-dimensional array of splitted array

[Ibrahim EL MEREHBI]

As an object, will it change how numpy operates?

Sincerely Yours,
Bob

On 23/03/2016 15:22, Sebastian Berg wrote:

On Mi, 2016-03-23 at 10:02 -0400, Joseph Fox-Rabinovitz wrote:

On Wed, Mar 23, 2016 at 9:37 AM, Ibrahim EL MEREHBI
<bobmerh...@gmail.com> wrote:

Thanks Eric. I already checked that. It's not what I want. I think
I wasn't
clear about what I wanted.

I want to split each column but I want to do it for each column and
end up
with an array. Here's the result I wish to have:

array([[[0], [1, 2, 3, 4], [5, 6, 7], [8, 9]],
        [[10], [11, 12, 13, 14], [15, 16, 17], [18, 19]],
        [[20], [21, 21, 23, 24], [25, 26, 27], [28, 29]]],
dtype=object)

Apply [`np.stack`](http://docs.scipy.org/doc/numpy-1.10.0/reference/g
enerated/numpy.stack.html#numpy.stack)
to the result. It will merge the arrays the way you want.

Oh sorry, nvm. As an object array, it works of course....

     -Joe

Sincerely Yours,
Bob



On 23/03/2016 14:17, Eric Moore wrote:

Try just calling np.array_split on the full 2D array.  It splits
along a
particular axis, which is selected using the axis argument of
np.array_split.  The axis to split along defaults to the first so
the two
calls to np.array_split below are exactly equivalent.

In [16]: a = np.c_[:10,10:20,20:30]


In [17]: np.array_split(a, [2,5,8])

Out[17]:

[array([[ 0, 10, 20],

[ 1, 11, 21]]), array([[ 2, 12, 22],

[ 3, 13, 23],

[ 4, 14, 24]]), array([[ 5, 15, 25],

[ 6, 16, 26],

[ 7, 17, 27]]), array([[ 8, 18, 28],

[ 9, 19, 29]])]


In [18]: np.array_split(a, [2,5,8], 0)

Out[18]:

[array([[ 0, 10, 20],

[ 1, 11, 21]]), array([[ 2, 12, 22],

[ 3, 13, 23],

[ 4, 14, 24]]), array([[ 5, 15, 25],

[ 6, 16, 26],

[ 7, 17, 27]]), array([[ 8, 18, 28],

[ 9, 19, 29]])]


Eric



On Wed, Mar 23, 2016 at 9:06 AM, Ibrahim EL MEREHBI <
bobmerh...@gmail.com>
wrote:

Hello,

I have a multi-diensional array that I would like to split its
columns.

For example consider,

dat = np.array([np.arange(10),np.arange(10,20),
np.arange(20,30)]).T

array([[ 0, 10, 20],
        [ 1, 11, 21],
        [ 2, 12, 22],
        [ 3, 13, 23],
        [ 4, 14, 24],
        [ 5, 15, 25],
        [ 6, 16, 26],
        [ 7, 17, 27],
        [ 8, 18, 28],
        [ 9, 19, 29]])


I already can split one column at a time:

np.array_split(dat[:,0], [2,5,8])

[array([0, 1]), array([2, 3, 4]), array([5, 6, 7]), array([8,
9])]


How can I extend this for all columns and (overwrite or) have a
new
multi-dimensional array?

Thank you,
Bob


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