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

Ibrahim EL MEREHBI bobmerhebi at gmail.com
Wed Mar 23 10:38:53 EDT 2016

```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
>> <bobmerhebi at 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 <
>>> bobmerhebi at 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
>>>>
>>>>
>>>> _______________________________________________
>>>> NumPy-Discussion mailing list
>>>> NumPy-Discussion at scipy.org
>>>> https://mail.scipy.org/mailman/listinfo/numpy-discussion
>>>>
>>>
>>>
>>> _______________________________________________
>>> NumPy-Discussion mailing list
>>> NumPy-Discussion at scipy.org
>>> https://mail.scipy.org/mailman/listinfo/numpy-discussion
>>>
>>>
>>>
>>>
>>> _______________________________________________
>>> NumPy-Discussion mailing list
>>> NumPy-Discussion at scipy.org
>>> https://mail.scipy.org/mailman/listinfo/numpy-discussion
>>>
>> _______________________________________________
>> NumPy-Discussion mailing list
>> NumPy-Discussion at scipy.org
>> https://mail.scipy.org/mailman/listinfo/numpy-discussion
>>
>>
>> _______________________________________________
>> NumPy-Discussion mailing list
>> NumPy-Discussion at scipy.org
>> https://mail.scipy.org/mailman/listinfo/numpy-discussion

-------------- next part --------------
An HTML attachment was scrubbed...
URL: <http://mail.python.org/pipermail/numpy-discussion/attachments/20160323/ff44cb94/attachment.html>
```