vsplit(ary, indices_or_sections)
Please refer to the split
documentation. vsplit
is equivalent to split
with :None:None:`axis=0` (default), the array is always split along the first axis regardless of the array dimension.
Split an array into multiple sub-arrays vertically (row-wise).
split
Split an array into multiple sub-arrays of equal size.
>>> 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.]])]
>>> np.vsplit(x, np.array([3, 6])) [array([[ 0., 1., 2., 3.], [ 4., 5., 6., 7.], [ 8., 9., 10., 11.]]), array([[12., 13., 14., 15.]]), array([], shape=(0, 4), dtype=float64)]
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.]]])]See :
The following pages refer to to this document either explicitly or contain code examples using this.
numpy.block
numpy.concatenate
numpy.core._multiarray_umath.concatenate
numpy.vstack
numpy.split
numpy.ma.extras.vstack
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