numpy.split
-
numpy.split(ary, indices_or_sections, axis=0)
[source] -
Split an array into multiple sub-arrays as views into
ary
.- Parameters
-
-
aryndarray
-
Array to be divided into sub-arrays.
-
indices_or_sectionsint or 1-D array
-
If
indices_or_sections
is an integer, N, the array will be divided into N equal arrays alongaxis
. 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 alongaxis
the array is split. For example,[2, 3]
would, foraxis=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. -
axisint, optional
-
The axis along which to split, default is 0.
-
- Returns
-
-
sub-arrayslist of ndarrays
-
A list of sub-arrays as views into
ary
.
-
- Raises
-
- ValueError
-
If
indices_or_sections
is given as an integer, but a split does not result in equal division.
See also
-
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.
-
hsplit
-
Split array into multiple sub-arrays horizontally (column-wise).
-
vsplit
-
Split array into multiple sub-arrays vertically (row wise).
-
dsplit
-
Split array into multiple sub-arrays along the 3rd axis (depth).
-
concatenate
-
Join a sequence of arrays along an existing axis.
-
stack
-
Join a sequence of arrays along a new axis.
-
hstack
-
Stack arrays in sequence horizontally (column wise).
-
vstack
-
Stack arrays in sequence vertically (row wise).
-
dstack
-
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)]
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Licensed under the 3-clause BSD License.
https://numpy.org/doc/1.19/reference/generated/numpy.split.html