Function from_delayed

dask/array/core.py:4191–4235

Create a dask array from a dask delayed value This routine is useful for constructing dask arrays in an ad-hoc fashion using dask delayed, particularly when combined with stack and concatenate. The dask array will consist of a single chunk. Examples -------- >>> import das

(value, shape, dtype=None, meta=None, name=None)

def from_delayed(value, shape, dtype=None, meta=None, name=None):
    """Create a dask array from a dask delayed value

    This routine is useful for constructing dask arrays in an ad-hoc fashion
    using dask delayed, particularly when combined with stack and concatenate.

    The dask array will consist of a single chunk.

    Examples
    --------
    >>> import dask
    >>> import dask.array as da
    >>> import numpy as np
    >>> value = dask.delayed(np.ones)(5)
    >>> array = da.from_delayed(value, (5,), dtype=float)
    >>> array
    dask.array<from-value, shape=(5,), dtype=float64, chunksize=(5,), chunktype=numpy.ndarray>
    >>> array.compute()
    array([1., 1., 1., 1., 1.])
    """
    from dask.delayed import Delayed, delayed

    is_future = False
    name = name or "from-value-" + tokenize(value, shape, dtype, meta)
    if isinstance(value, TaskRef):
        is_future = True
    elif not isinstance(value, Delayed) and hasattr(value, "key"):
        value = delayed(value)
    task = Alias(
        key=(name,) + (0,) * len(shape),
        target=value.key,
    )

    dsk = {task.key: task}

    if is_future:
        dsk[value.key] = value
        dependencies = []
    else:
        dependencies = [value]
    chunks = tuple((d,) for d in shape)
    # TODO: value._key may not be the name of the layer in value.dask
    # This should be fixed after we build full expression graphs
    graph = HighLevelGraph.from_collections(name, dsk, dependencies=dependencies)
    return Array(graph, name, chunks, dtype=dtype, meta=meta)


def from_func(func, shape, dtype=None, name=None, args=(), kwargs=None):