code: def show_linear_weight(exp):
      coef_df = {}
      for r in exp.list_recorders("list"):
          t = r.load_object("task")
          if None in t["dataset"]["kwargs"]["segments"]["test"]:
              continue
          m = r.load_object("params.pkl")
          coef_df[
              t["dataset"]["kwargs"]["segments"]["test"]
          ] = pd.Series(m.coef_)
  
      coef_df = pd.concat(coef_df)
  
      coef_df.index.names = ["test_start", "test_end", "coef_idx"]
  
      coef_df = coef_df.droplevel("test_end").unstack("coef_idx").T
  
      plt.figure(figsize=(40, 20))
      sns.heatmap(coef_df)
      plt.show()
  
file_path: qlib/examples/benchmarks_dynamic/DDG-DA/vis_data.py
imports: import pickle
  import numpy
  import pandas
  import matplotlib.pyplot
  import seaborn
  from tqdm.auto import tqdm
  from qlib import auto_init
  from qlib.workflow import R
label_desc: Use image node_id 1 for calling a global function with example usage: show_linear_weight(exp) without return types