Function add

numpy/core/defchararray.py:302–337

Return element-wise string concatenation for two arrays of str or unicode. Arrays `x1` and `x2` must have the same shape. Parameters ---------- x1 : array_like of str or unicode Input array. x2 : array_like of str or unicode Input array. Returns --

(x1, x2)

@array_function_dispatch(_binary_op_dispatcher)
def add(x1, x2):
    """
    Return element-wise string concatenation for two arrays of str or unicode.

    Arrays `x1` and `x2` must have the same shape.

    Parameters
    ----------
    x1 : array_like of str or unicode
        Input array.
    x2 : array_like of str or unicode
        Input array.

    Returns
    -------
    add : ndarray
        Output array of `bytes_` or `str_`, depending on input types
        of the same shape as `x1` and `x2`.

    """
    arr1 = numpy.asarray(x1)
    arr2 = numpy.asarray(x2)
    out_size = _get_num_chars(arr1) + _get_num_chars(arr2)

    if type(arr1.dtype) != type(arr2.dtype):
        # Enforce this for now.  The solution to it will be implement add
        # as a ufunc.  It never worked right on Python 3: bytes + unicode gave
        # nonsense unicode + bytes errored, and unicode + object used the
        # object dtype itemsize as num chars (worked on short strings).
        # bytes + void worked but promoting void->bytes is dubious also.
        raise TypeError(
            "np.char.add() requires both arrays of the same dtype kind, but "
            f"got dtypes: '{arr1.dtype}' and '{arr2.dtype}' (the few cases "
            "where this used to work often lead to incorrect results).")

    return _vec_string(arr1, type(arr1.dtype)(out_size), '__add__', (arr2,))

def _multiply_dispatcher(a, i):
    return (a,)