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dsplit(ary, indices_or_sections)

Please refer to the split documentation. dsplit is equivalent to split with axis=2 , the array is always split along the third axis provided the array dimension is greater than or equal to 3.

Split array into multiple sub-arrays along the 3rd axis (depth).

See Also

split

Split an array into multiple sub-arrays of equal size.

Examples

>>> x = np.arange(16.0).reshape(2, 2, 4)
... x array([[[ 0., 1., 2., 3.], [ 4., 5., 6., 7.]], [[ 8., 9., 10., 11.], [12., 13., 14., 15.]]])
>>> np.dsplit(x, 2)
[array([[[ 0.,  1.],
        [ 4.,  5.]],
       [[ 8.,  9.],
        [12., 13.]]]), array([[[ 2.,  3.],
        [ 6.,  7.]],
       [[10., 11.],
        [14., 15.]]])]
>>> np.dsplit(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=(2, 2, 0), dtype=float64)]
See :

Back References

The following pages refer to to this document either explicitly or contain code examples using this.

numpy.ma.extras.dstack numpy.concatenate numpy.core._multiarray_umath.concatenate numpy.split numpy.dstack numpy.dsplit

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GitHub : /numpy/lib/shape_base.py#994
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