docs: 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