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_layout recognizes).

  • 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.