code: def plot_interval(ax, interval_df, ix=None):
      cov = interval_df.columns.levels[1][0]
      var_name = interval_df.columns.levels[0][0]
      x_ix = np.argwhere(ix.isin(interval_df.index)).ravel()
      x_ix = np.array(x_ix)
  
      ax.fill_between(
          x_ix,
          interval_df[var_name][cov]["lower"]
          .astype("float64")
          .to_numpy(),
          interval_df[var_name][cov]["upper"]
          .astype("float64")
          .to_numpy(),
          alpha=0.2,
          color=ax.get_lines()[-1].get_c(),
          label=f"{int(cov * 100)}% prediction interval",
      )
      ax.legend()
      return ax
  
file_path: sktime/sktime/utils/plotting.py
imports: import math
  from warnings import simplefilter, warn
  import numpy
  import pandas
  from sktime.datatypes import convert_to
  from sktime.utils.validation._dependencies import _check_soft_dependencies
  from sktime.utils.validation.forecasting import check_interval_df, check_y
  from sktime.utils.validation.series import check_consistent_index_type
label_desc: Use image node_id 2 for calling a global function with example usage: plot_interval(ax, interval_df, ix) and returns: ax