numpy.split()
numpy.split
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, 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.
- 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.
第一个参数array:输入序列
第二个参数indices_or_sections:分割参考
- 若是整型,则会将序列均分(下标超出等不可能实现的情况会报错
- 若是有序序列,会按照序列的数值为截点依次分割
第三个参数axis:0为水平1为竖直
>>> 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)]
>>> x = np.arange(8.0) >>> np.split(x, (3,)) [array([0., 1., 2.]), array([3., 4.,5.,6., 7.])]