Function asarray

dask/array/_array_expr/_collection.py:1205–1280

Convert the input to a dask array. Parameters ---------- a : array-like Input data, in any form that can be converted to a dask array. This includes lists, lists of tuples, tuples, tuples of tuples, tuples of lists and ndarrays. allow_unknown_chunksizes: bool

(
    a, allow_unknown_chunksizes=False, dtype=None, order=None, *, like=None, **kwargs
)

def asarray(
    a, allow_unknown_chunksizes=False, dtype=None, order=None, *, like=None, **kwargs
):
    """Convert the input to a dask array.

    Parameters
    ----------
    a : array-like
        Input data, in any form that can be converted to a dask array. This
        includes lists, lists of tuples, tuples, tuples of tuples, tuples of
        lists and ndarrays.
    allow_unknown_chunksizes: bool
        Allow unknown chunksizes, such as come from converting from dask
        dataframes.  Dask.array is unable to verify that chunks line up.  If
        data comes from differently aligned sources then this can cause
        unexpected results.
    dtype : data-type, optional
        By default, the data-type is inferred from the input data.
    order : {‘C’, ‘F’, ‘A’, ‘K’}, optional
        Memory layout. ‘A’ and ‘K’ depend on the order of input array a.
        ‘C’ row-major (C-style), ‘F’ column-major (Fortran-style) memory
        representation. ‘A’ (any) means ‘F’ if a is Fortran contiguous, ‘C’
        otherwise ‘K’ (keep) preserve input order. Defaults to ‘C’.
    like: array-like
        Reference object to allow the creation of Dask arrays with chunks
        that are not NumPy arrays. If an array-like passed in as ``like``
        supports the ``__array_function__`` protocol, the chunk type of the
        resulting array will be defined by it. In this case, it ensures the
        creation of a Dask array compatible with that passed in via this
        argument. If ``like`` is a Dask array, the chunk type of the
        resulting array will be defined by the chunk type of ``like``.
        Requires NumPy 1.20.0 or higher.

    Returns
    -------
    out : dask array
        Dask array interpretation of a.

    Examples
    --------
    >>> import dask.array as da
    >>> import numpy as np
    >>> x = np.arange(3)
    >>> da.asarray(x)
    dask.array<array, shape=(3,), dtype=int64, chunksize=(3,), chunktype=numpy.ndarray>

    >>> y = [[1, 2, 3], [4, 5, 6]]
    >>> da.asarray(y)
    dask.array<array, shape=(2, 3), dtype=int64, chunksize=(2, 3), chunktype=numpy.ndarray>

    .. warning::
        `order` is ignored if `a` is an `Array`, has the attribute ``to_dask_array``,
        or is a list or tuple of `Array`&#x27;s.
    """
    if like is None:
        if isinstance(a, Array):
            return _as_dtype(a, dtype)
        elif hasattr(a, "to_dask_array"):