ak.to_regular#

Defined in awkward.operations.ak_to_regular on line 9.

ak.to_regular(array, axis=1, *, highlevel=True, behavior=None)#
Parameters
  • array – Array-like data (anything ak.to_layout recognizes).

  • axis (int or None) – The dimension at which this operation is applied. The outermost dimension is 0, followed by 1, etc., and negative values count backward from the innermost: -1 is the innermost dimension, -2 is the next level up, etc. If None, convert all variable dimensions into regular ones or raise a ValueError if that is not possible.

  • 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.

Converts a variable-length axis into a regular one, if possible.

>>> irregular = ak.from_iter(np.arange(2*3*5).reshape(2, 3, 5))
>>> irregular.type.show()
2 * var * var * int64
>>> ak.to_regular(irregular).type.show()
2 * 3 * var * int64
>>> ak.to_regular(irregular, axis=2).type.show()
2 * var * 5 * int64
>>> ak.to_regular(irregular, axis=-1).type.show()
2 * var * 5 * int64

But truly irregular data cannot be converted.

>>> ak.to_regular(ak.Array([[1, 2, 3], [], [4, 5]]))
ValueError: while calling
    ak.to_regular(
        array = <Array [[1, 2, 3], [], [4, 5]] type='3 * var * int64'>
        axis = 1
        highlevel = True
        behavior = None
    )
Error details: cannot convert to RegularArray because subarray lengths are not regular

See also ak.from_regular.