dask.array.Array.vindex

dask.array.Array.vindex¶

property Array.vindex¶

Vectorized indexing with broadcasting.

This is equivalent to numpy’s advanced indexing, using arrays that are broadcast against each other. This allows for pointwise indexing:

>>> import dask.array as da
>>> x = np.array([[1, 2, 3], [4, 5, 6], [7, 8, 9]])
>>> x = da.from_array(x, chunks=2)
>>> x.vindex[[0, 1, 2], [0, 1, 2]].compute()
array([1, 5, 9])

Mixed basic/advanced indexing with slices/arrays is also supported. The order of dimensions in the result follows those proposed for ndarray.vindex: the subspace spanned by arrays is followed by all slices.

Note: vindex provides more general functionality than standard indexing, but it also has fewer optimizations and can be significantly slower.

dask.array.Array.view

dask.array.Array.visualize