- xorbits.numpy.split(ary, indices_or_sections, axis=0)#
Split an array into multiple sub-arrays as views into ary.
ary (ndarray) – Array to be divided into sub-arrays.
indices_or_sections (int or 1-D array) –
If indices_or_sections is an integer, N, the array will be divided into N equal arrays along axis. If such a split is not possible, an error is raised.
If indices_or_sections is a 1-D array of sorted integers, the entries indicate where along axis the array is split. For example,
[2, 3]would, for
axis=0, result in
If an index exceeds the dimension of the array along axis, an empty sub-array is returned correspondingly.
axis (int, optional) – The axis along which to split, default is 0.
sub-arrays – A list of sub-arrays as views into ary.
- Return type
list of ndarrays
ValueError – If indices_or_sections is given as an integer, but a split does not result in equal division.
Split an array into multiple sub-arrays of equal or near-equal size. Does not raise an exception if an equal division cannot be made.
Split array into multiple sub-arrays horizontally (column-wise).
Split array into multiple sub-arrays vertically (row wise).
Split array into multiple sub-arrays along the 3rd axis (depth).
Join a sequence of arrays along an existing axis.
Join a sequence of arrays along a new axis.
Stack arrays in sequence horizontally (column wise).
Stack arrays in sequence vertically (row wise).
Stack arrays in sequence depth wise (along third dimension).
>>> x = np.arange(9.0) >>> np.split(x, 3) [array([0., 1., 2.]), array([3., 4., 5.]), array([6., 7., 8.])]
>>> x = np.arange(8.0) >>> np.split(x, [3, 5, 6, 10]) [array([0., 1., 2.]), array([3., 4.]), array([5.]), array([6., 7.]), array(, dtype=float64)]
This docstring was copied from numpy.