numpy.split — NumPy v1.13 Manual (original) (raw)
numpy. split(ary, indices_or_sections, axis=0)[source]¶
Split an array into multiple sub-arrays.
| Parameters: | 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 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 is 0. |
|---|---|
| Returns: | sub-arrays : list of ndarrays A list of sub-arrays. |
| Raises: | ValueError If indices_or_sections is given as an integer, but a split does not result in equal division. |
See also
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).
Examples
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)]