docs: def masked(a, b):
      """Return a numpy array with values from a where elements in b are
      not False. Populate with numpy.nan where b is False. When plotting,
      those elements look like missing, which can be a desired result.
  
      """
  
      if np.any([a.dtype.kind.startswith(c) for c in ['i', 'u', 'f', 'c']]):
          n = np.array([np.nan for i in range(len(a))])
      else:
          n = np.array([None for i in range(len(a))])
          # a = a.astype(object)
      return np.where(b, a, n)