/
ak_from_numpy.py
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/
ak_from_numpy.py
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# BSD 3-Clause License; see https://github.com/scikit-hep/awkward/blob/main/LICENSE
from __future__ import annotations
from awkward._dispatch import high_level_function
from awkward._layout import from_arraylib, wrap_layout
__all__ = ("from_numpy",)
@high_level_function()
def from_numpy(
array,
*,
regulararray=False,
recordarray=True,
highlevel=True,
behavior=None,
attrs=None,
):
"""
Args:
array (np.ndarray): The NumPy array to convert into an Awkward Array.
This array can be a np.ma.MaskedArray.
regulararray (bool): If True and the array is multidimensional,
the dimensions are represented by nested #ak.contents.RegularArray
nodes; if False and the array is multidimensional, the dimensions
are represented by a multivalued #ak.contents.NumpyArray.shape.
If the array is one-dimensional, this has no effect.
recordarray (bool): If True and the array is a NumPy structured array
(dtype.names is not None), the fields are represented by an
#ak.contents.RecordArray; if False and the array is a structured
array, the structure is left in the #ak.contents.NumpyArray `format`,
which some functions do not recognize.
highlevel (bool): If True, return an #ak.Array; otherwise, return
a low-level #ak.contents.Content subclass.
behavior (None or dict): Custom #ak.behavior for the output array, if
high-level.
attrs (None or dict): Custom attributes for the output array, if
high-level.
Converts a NumPy array into an Awkward Array.
The resulting layout can only involve the following #ak.contents.Content types:
* #ak.contents.NumpyArray
* #ak.contents.ByteMaskedArray or #ak.contents.UnmaskedArray if the
`array` is an np.ma.MaskedArray.
* #ak.contents.RegularArray if `regulararray=True`.
* #ak.contents.RecordArray if `recordarray=True`.
See also #ak.to_numpy and #ak.from_cupy.
"""
return wrap_layout(
from_arraylib(array, regulararray, recordarray),
highlevel=highlevel,
behavior=behavior,
)