code: def measure_temporal_complexity():
      from tsfresh.examples.robot_execution_failures import (
          download_robot_execution_failures,
          load_robot_execution_failures,
      )
  
      download_robot_execution_failures()
      df, y = load_robot_execution_failures()
  
      commit_hash = (
          check_output(["git", "log", '--format="%H"', "-1"])
          .decode("ascii")
          .strip()
          .replace('"', "")
      )
  
      lengths_to_test = [1, 5, 10, 60, 100, 400, 600, 1000, 2000]
      results = []
  
      for length in lengths_to_test:
          results.append(simulate_with_length(length, df))
          results.append(simulate_with_length(length, df))
          results.append(simulate_with_length(length, df))
  
      results = pd.DataFrame(results)
      results.to_csv("{hash}.dat".format(hash=commit_hash))
  
imports: import time
  from glob import glob
  from subprocess import check_output
  import pandas
label_desc: Use image node_id 3 for calling a global function with example usage: measure_temporal_complexity() without return types