code: def transition_uniform(n_states: int) -> np.ndarray:
      """Construct a uniform transition matrix over ``n_states``.
  
      Parameters
      ----------
      n_states : int > 0
          The number of states
  
      Returns
      -------
      transition : np.ndarray [shape=(n_states, n_states)]
          ``transition[i, j] = 1./n_states``
  
      Examples
      --------
      >>> librosa.sequence.transition_uniform(3)
      array([[0.333, 0.333, 0.333],
             [0.333, 0.333, 0.333],
             [0.333, 0.333, 0.333]])
      """
      if not is_positive_int(n_states):
          raise ParameterError(
              f"n_states={n_states} must be a positive integer"
          )
  
      transition = np.empty((n_states, n_states), dtype=np.float64)
      transition.fill(1.0 / n_states)
      return transition
  
imports: from __future__ import annotations
  import numpy
  from scipy.spatial.distance import cdist
  from numba import jit
  from .util import pad_center, fill_off_diagonal, is_positive_int, tiny, expand_to
  from .util.exceptions import ParameterError
  from .filters import get_window
  from typing import Any, Iterable, List, Optional, Tuple, Union, overload
  from typing_extensions import Literal
  from ._typing import _WindowSpec, _IntLike_co
label_desc: Use image node_id 31 for calling a global function with example usage: transition_uniform(n_states) and returns: transition