MCPcopy Index your code
hub / github.com/numpy/numpy / split

Function split

numpy/lib/_shape_base_impl.py:781–856  ·  view source on GitHub ↗

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

(ary, indices_or_sections, axis=0)

Source from the content-addressed store, hash-verified

779
780@array_function_dispatch(_split_dispatcher)
781def split(ary, indices_or_sections, axis=0):
782 """
783 Split an array into multiple sub-arrays as views into `ary`.
784
785 Parameters
786 ----------
787 ary : ndarray
788 Array to be divided into sub-arrays.
789 indices_or_sections : int or 1-D array
790 If `indices_or_sections` is an integer, N, the array will be divided
791 into N equal arrays along `axis`. If such a split is not possible,
792 an error is raised.
793
794 If `indices_or_sections` is a 1-D array of sorted integers, the entries
795 indicate where along `axis` the array is split. For example,
796 ``[2, 3]`` would, for ``axis=0``, result in
797
798 - ary[:2]
799 - ary[2:3]
800 - ary[3:]
801
802 If an index exceeds the dimension of the array along `axis`,
803 an empty sub-array is returned correspondingly.
804 axis : int, optional
805 The axis along which to split, default is 0.
806
807 Returns
808 -------
809 sub-arrays : list of ndarrays
810 A list of sub-arrays as views into `ary`.
811
812 Raises
813 ------
814 ValueError
815 If `indices_or_sections` is given as an integer, but
816 a split does not result in equal division.
817
818 See Also
819 --------
820 array_split : Split an array into multiple sub-arrays of equal or
821 near-equal size. Does not raise an exception if
822 an equal division cannot be made.
823 hsplit : Split array into multiple sub-arrays horizontally (column-wise).
824 vsplit : Split array into multiple sub-arrays vertically (row wise).
825 dsplit : Split array into multiple sub-arrays along the 3rd axis (depth).
826 concatenate : Join a sequence of arrays along an existing axis.
827 stack : Join a sequence of arrays along a new axis.
828 hstack : Stack arrays in sequence horizontally (column wise).
829 vstack : Stack arrays in sequence vertically (row wise).
830 dstack : Stack arrays in sequence depth wise (along third dimension).
831
832 Examples
833 --------
834 >>> import numpy as np
835 >>> x = np.arange(9.0)
836 >>> np.split(x, 3)
837 [array([0., 1., 2.]), array([3., 4., 5.]), array([6., 7., 8.])]
838

Callers 5

test_equal_splitMethod · 0.90
splitMethod · 0.85
hsplitFunction · 0.85
vsplitFunction · 0.85
dsplitFunction · 0.85

Calls 1

array_splitFunction · 0.85

Tested by 1

test_equal_splitMethod · 0.72

Used in the wild real call sites across dependent graphs

searching dependent graphs…