flopscope.

flopscope.numpy.vsplit

fnp.vsplit(ary, indices_or_sections)[flopscope source][numpy source]

Split an array into multiple sub-arrays vertically (row-wise).

Adapted from NumPy docs np.vsplit

Areacore
Typefree
NumPy Refnp.vsplit
Cost
0
Flopscope Context

Split array into rows. Cost: numel(output).

Please refer to the split documentation. vsplit is equivalent to split with axis=0 (default), the array is always split along the first axis regardless of the array dimension.

See also

Examples

>>> import flopscope.numpy as fnp
>>> x = flops.arange(16.0).reshape(4, 4)
>>> x
array([[ 0.,   1.,   2.,   3.],
       [ 4.,   5.,   6.,   7.],
       [ 8.,   9.,  10.,  11.],
       [12.,  13.,  14.,  15.]])
>>> flops.vsplit(x, 2)
[array([[0., 1., 2., 3.],
        [4., 5., 6., 7.]]),
 array([[ 8.,  9., 10., 11.],
        [12., 13., 14., 15.]])]
>>> flops.vsplit(x, flops.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 = flops.arange(8.0).reshape(2, 2, 2)
>>> x
array([[[0.,  1.],
        [2.,  3.]],
       [[4.,  5.],
        [6.,  7.]]])
>>> flops.vsplit(x, 2)
[array([[[0., 1.],
         [2., 3.]]]),
 array([[[4., 5.],
         [6., 7.]]])]