dpnp.split

dpnp.split(ary, indices_or_sections, axis=0)

Split an array into multiple sub-arrays as views into ary.

For full documentation refer to numpy.split.

Parameters:

• ary ({dpnp.ndarray, usm_ndarray}) -- Array to be divided into sub-arrays.

• indices_or_sections ({int, sequence of ints}) --

  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 sequence of sorted integers, the entries indicate where along axis the array is split. For example, [2, 3] would, for axis=0, result in

  • ary[:2]

  • ary[2:3]

  • ary[3:]

  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: 0.

Returns:

sub-arrays -- A list of sub arrays. Each array is a view of the corresponding input array.

Return type:

list of dpnp.ndarray

Raises:

ValueError -- If indices_or_sections is given as an integer, but a split does not result in equal division.

See also

dpnp.array_split

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.

dpnp.hsplit

Split array into multiple sub-arrays horizontally (column-wise).

dpnp.vsplit

Split array into multiple sub-arrays vertically (row wise).

dpnp.dsplit

Split array into multiple sub-arrays along the 3rd axis (depth).

dpnp.concatenate

Join a sequence of arrays along an existing axis.

dpnp.stack

Join a sequence of arrays along a new axis.

dpnp.hstack

Stack arrays in sequence horizontally (column wise).

dpnp.vstack

Stack arrays in sequence vertically (row wise).

dpnp.dstack

Stack arrays in sequence depth wise (along third dimension).

Examples

>>> import dpnp as np
>>> 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([])]