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Method blocks

dask/array/core.py:2103–2140  ·  view source on GitHub ↗

An array-like interface to the blocks of an array. This returns a ``Blockview`` object that provides an array-like interface to the blocks of a dask array. Numpy-style indexing of a ``Blockview`` object returns a selection of blocks as a new dask array. You can ind

(self)

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2101
2102 @property
2103 def blocks(self):
2104 """An array-like interface to the blocks of an array.
2105
2106 This returns a ``Blockview`` object that provides an array-like interface
2107 to the blocks of a dask array. Numpy-style indexing of a ``Blockview`` object
2108 returns a selection of blocks as a new dask array.
2109
2110 You can index ``array.blocks`` like a numpy array of shape
2111 equal to the number of blocks in each dimension, (available as
2112 array.blocks.size). The dimensionality of the output array matches
2113 the dimension of this array, even if integer indices are passed.
2114 Slicing with ``np.newaxis`` or multiple lists is not supported.
2115
2116 Examples
2117 --------
2118 >>> import dask.array as da
2119 >>> x = da.arange(8, chunks=2)
2120 >>> x.blocks.shape # aliases x.numblocks
2121 (4,)
2122 >>> x.blocks[0].compute()
2123 array([0, 1])
2124 >>> x.blocks[:3].compute()
2125 array([0, 1, 2, 3, 4, 5])
2126 >>> x.blocks[::2].compute()
2127 array([0, 1, 4, 5])
2128 >>> x.blocks[[-1, 0]].compute()
2129 array([6, 7, 0, 1])
2130 >>> x.blocks.ravel() # doctest: +NORMALIZE_WHITESPACE
2131 [dask.array<blocks, shape=(2,), dtype=int64, chunksize=(2,), chunktype=numpy.ndarray>,
2132 dask.array<blocks, shape=(2,), dtype=int64, chunksize=(2,), chunktype=numpy.ndarray>,
2133 dask.array<blocks, shape=(2,), dtype=int64, chunksize=(2,), chunktype=numpy.ndarray>,
2134 dask.array<blocks, shape=(2,), dtype=int64, chunksize=(2,), chunktype=numpy.ndarray>]
2135
2136 Returns
2137 -------
2138 An instance of ``dask.array.Blockview``
2139 """
2140 return BlockView(self)
2141
2142 @property
2143 def partitions(self):

Callers

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Calls 1

BlockViewClass · 0.85

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