hsplit(*args, **kwargs)
Please refer to the split
documentation. hsplit
is equivalent to split
with axis=1
, the array is always split along the second axis regardless of the array dimension.
The function is applied to both the _data and the _mask, if any.
Split an array into multiple sub-arrays horizontally (column-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.hsplit(x, 2) [array([[ 0., 1.], [ 4., 5.], [ 8., 9.], [12., 13.]]), array([[ 2., 3.], [ 6., 7.], [10., 11.], [14., 15.]])]
>>> np.hsplit(x, np.array([3, 6])) [array([[ 0., 1., 2.], [ 4., 5., 6.], [ 8., 9., 10.], [12., 13., 14.]]), array([[ 3.], [ 7.], [11.], [15.]]), array([], shape=(4, 0), dtype=float64)]
With a higher dimensional array the split is still along the second axis.
>>> x = np.arange(8.0).reshape(2, 2, 2)
... x array([[[0., 1.], [2., 3.]], [[4., 5.], [6., 7.]]])
>>> np.hsplit(x, 2) [array([[[0., 1.]], [[4., 5.]]]), array([[[2., 3.]], [[6., 7.]]])]See :
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