mxnet.np.vsplit¶
-
vsplit
(ary, indices_or_sections)¶ Split an array into multiple sub-arrays vertically (row-wise).
vsplit
is equivalent tosplit
with axis=0 (default): the array is always split along the first axis regardless of the array dimension.- Parameters
ary (ndarray) – Array to be divided into sub-arrays.
indices_or_sections (int or 1 - D Python tuple, list or set.) –
If indices_or_sections is an integer, N, the array will be divided into N equal arrays along axis 0. 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 0 the array is split. For example,
[2, 3]
would result inary[:2]
ary[2:3]
ary[3:]
If an index exceeds the dimension of the array along axis 0, an error will be thrown.
- Returns
sub-arrays – A list of sub-arrays.
- Return type
list of ndarrays
See also
split()
Split an array into multiple sub-arrays of equal size.
()
This function differs from the original numpy.vsplit in the following aspects: * Currently parameter
indices_or_sections
does not support ndarray, but supports scalar, tuple and list. * Inindices_or_sections
, if an index exceeds the dimension of the array along axis 0, an error will be thrown.
Examples
>>> x = np.arange(16.0).reshape(4, 4) >>> x array([[ 0., 1., 2., 3.], [ 4., 5., 6., 7.], [ 8., 9., 10., 11.], [ 12., 13., 14., 15.]]) >>> np.vsplit(x, 2) [array([[0., 1., 2., 3.], [4., 5., 6., 7.]]), array([[ 8., 9., 10., 11.], [12., 13., 14., 15.]])]
>>> # With a higher dimensional array the split is still along the first axis. >>> x = np.arange(8.0).reshape(2, 2, 2) >>> x array([[[ 0., 1.], [ 2., 3.]], [[ 4., 5.], [ 6., 7.]]]) >>> np.vsplit(x, 2) [array([[[0., 1.], [2., 3.]]]), array([[[4., 5.], [6., 7.]]])]