ak.to_numpy#
Defined in awkward.operations.ak_to_numpy on line 13.
- ak.to_numpy(array, *, allow_missing=True)#
- Parameters:
array – Array-like data (anything
ak.to_layoutrecognizes).allow_missing (bool) – allow missing (None) values.
Converts array (many types supported, including all Awkward Arrays and
Records) into a NumPy array, if possible.
If the data are numerical and regular (nested lists have equal lengths
in each dimension, as described by the ak.Array.type), they can be losslessly
converted to a NumPy array and this function returns without an error.
Otherwise, the function raises an error. It does not create a NumPy
array with dtype "O" for np.object_ (see the
note on object_ type)
since silent conversions to dtype "O" arrays would not only be a
significant performance hit, but would also break functionality, since
nested lists in a NumPy "O" array are severed from the array and
cannot be sliced as dimensions.
If array is not an Awkward Array, then this function is equivalent
to calling np.asarray on it.
If allow_missing is True; NumPy
masked arrays
are a possible result; otherwise, missing values (None) cause this
function to raise an error.
See also ak.from_numpy and ak.to_cupy.