code: def Add_one_line(
      x_time_array: list,
      y_twod_budget: List[List],
      namespace: str,
      index,
      ax,
  ):
      # training-based
      x_ = x_time_array
      y_ = y_twod_budget
  
      if all(isinstance(item, list) for item in x_):
          expx = np.array(x_)
          x_m = np.quantile(expx, 0.5, axis=0)
      else:
          x_m = x_
  
      exp = np.array(y_)
      exp = np.where(exp > 10, exp, exp * 100)
  
      y_h = np.quantile(exp, 0.75, axis=0)
      y_m = np.quantile(exp, 0.5, axis=0)
      y_l = np.quantile(exp, 0.25, axis=0)
  
      ax.plot(
          x_m,
          y_m,
          mark_list[int(index % len(mark_list))]
          + line_shape_list[int(index % len(line_shape_list))],
          label=namespace,
          markersize=mark_size_list[int(index % len(mark_list))],
          linewidth=3,
      )
  
      ax.fill_between(x_m, y_l, y_h, alpha=shade_degree)
      return x_m
  
file_path: singa/examples/model_selection/TRAILS-Database-Native-Model-Selection/internal/ml/model_selection/exps/draw_tab_lib.py
imports: from typing import List
  import numpy
  from matplotlib import pyplot
  from matplotlib.ticker import MaxNLocator
  import warnings
  import matplotlib.cbook
  import seaborn
  import matplotlib.pyplot
label_desc: Use image node_id 1 for calling a global function with example usage: Add_one_line(x_time_array, y_twod_budget, namespace, index, ax) and returns: x_m