Class BlockView

dask/array/core.py:6172–6271

An array-like interface to the blocks of an array. ``BlockView`` provides an array-like interface to the blocks of a dask array. Numpy-style indexing of a ``BlockView`` returns a selection of blocks as a new dask array. You can index ``BlockView`` like a numpy array of shape

class BlockView:
    """An array-like interface to the blocks of an array.

    ``BlockView`` provides an array-like interface
    to the blocks of a dask array.  Numpy-style indexing of a
     ``BlockView`` returns a selection of blocks as a new dask array.

    You can index ``BlockView`` like a numpy array of shape
    equal to the number of blocks in each dimension, (available as
    array.blocks.size).  The dimensionality of the output array matches
    the dimension of this array, even if integer indices are passed.
    Slicing with ``np.newaxis`` or multiple lists is not supported.

    Examples
    --------
    >>> import dask.array as da
    >>> from dask.array.core import BlockView
    >>> x = da.arange(8, chunks=2)
    >>> bv = BlockView(x)
    >>> bv.shape # aliases x.numblocks
    (4,)
    >>> bv.size
    4
    >>> bv[0].compute()
    array([0, 1])
    >>> bv[:3].compute()
    array([0, 1, 2, 3, 4, 5])
    >>> bv[::2].compute()
    array([0, 1, 4, 5])
    >>> bv[[-1, 0]].compute()
    array([6, 7, 0, 1])
    >>> bv.ravel()  # doctest: +NORMALIZE_WHITESPACE
    [dask.array<blocks, shape=(2,), dtype=int64, chunksize=(2,), chunktype=numpy.ndarray>,
     dask.array<blocks, shape=(2,), dtype=int64, chunksize=(2,), chunktype=numpy.ndarray>,
     dask.array<blocks, shape=(2,), dtype=int64, chunksize=(2,), chunktype=numpy.ndarray>,
     dask.array<blocks, shape=(2,), dtype=int64, chunksize=(2,), chunktype=numpy.ndarray>]

    Returns
    -------
    An instance of ``da.array.Blockview``
    """

    def __init__(self, array: Array):
        self._array = array

    def __getitem__(self, index: Any) -> Array:
        from dask.array.slicing import normalize_index

        if not isinstance(index, tuple):
            index = (index,)
        if sum(isinstance(ind, (np.ndarray, list)) for ind in index) > 1:
            raise ValueError("Can only slice with a single list")
        if any(ind is None for ind in index):
            raise ValueError("Slicing with np.newaxis or None is not supported")
        index = normalize_index(index, self._array.numblocks)
        index = tuple(
            slice(k, k + 1) if isinstance(k, Number) else k  # type: ignore[operator]
            for k in index