asarray(a, allow_unknown_chunksizes=False, dtype=None, order=None, *, like=None, **kwargs)
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, 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.
By default, the data-type is inferred from the input data.
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’.
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 definde 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.
Dask array interpretation of a.
Convert the input to a dask array.
>>> import dask.array as daThis example is valid syntax, but we were not able to check execution
... 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]]See :
... da.asarray(y) dask.array<array, shape=(2, 3), dtype=int64, chunksize=(2, 3), chunktype=numpy.ndarray>
The following pages refer to to this document either explicitly or contain code examples using this.
dask.array.core.asarray
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