Make x and new_x float.
    This is particulary useful for datetime dtype.
    x, new_x: tuple of np.ndarray

def _floatize_x(x, new_x):
    """ Make x and new_x float.
    This is particulary useful for datetime dtype.
    x, new_x: tuple of np.ndarray
    """
    x = list(x)
    new_x = list(new_x)
    for i in range(len(x)):
        if _contains_datetime_like_objects(x[i]):
            # Scipy casts coordinates to np.float64, which is not accurate
            # enough for datetime64 (uses 64bit integer).
            # We assume that the most of the bits are used to represent the
            # offset (min(x)) and the variation (x - min(x)) can be
            # represented by float.
            xmin = x[i].values.min()
            x[i] = x[i]._to_numeric(offset=xmin, dtype=np.float64)
            new_x[i] = new_x[i]._to_numeric(offset=xmin, dtype=np.float64)
    return x, new_x