code: def get_multi_run_analyzer(opt) -> MultiRunAcuteAnalyzer:
      """
      Return an object to analyze the results of multiple runs simultaneously.
  
      Load HITs from each run into a separate dataframe, and then pass all dataframes into
      a separate analyzer class that will concatenate them.
      """
  
      run_ids = opt["run_ids"].split(",")
  
      # Define paths
      assert (
          opt["outdir"] is not None
      ), "--outdir must be specified when combining results of multiple runs!"
      timestamp = datetime.now().strftime("%Y%m%d_%H%M%S")
      opt["outdir"] = os.path.join(
          opt["outdir"], f"combined_runs_{timestamp}"
      )
      os.makedirs(opt["outdir"], exist_ok=True)
      run_id_list_path = os.path.join(opt["outdir"], "run_ids.txt")
  
      # Save a simple list of all run IDs stitched together
      with open(run_id_list_path, "w") as f:
          for run_id in run_ids:
              f.write(run_id + "\n")
  
      # Loop loading HITs over all run ids into dataframes
      dataframes = {}
      for run_id in run_ids:
          print(f"\nStarting to load HITs for run ID {run_id}.")
          opt_copy = deepcopy(opt)
          opt_copy["run_ids"] = run_id
          dataframes[run_id] = AcuteAnalyzer(opt_copy).dataframe
  
      return MultiRunAcuteAnalyzer(opt=opt, dataframes=dataframes)
  
imports: import hashlib
  import json
  import os
  from copy import deepcopy
  from datetime import datetime
  from typing import Dict, Any, List, Optional
  import numpy
  import pandas
  from IPython.core.display import HTML
  from mephisto.tools.data_browser import DataBrowser
  from mephisto.abstractions.databases.local_database import LocalMephistoDB
  from mephisto.data_model.unit import Unit
  from mephisto.data_model.worker import Worker
  from scipy.stats import binom_test
  from parlai.core.params import ParlaiParser
  from parlai.crowdsourcing.tasks.acute_eval.acute_eval_blueprint import BLUEPRINT_TYPE
  from parlai.crowdsourcing.tasks.acute_eval.fast_acute_blueprint import FAST_ACUTE_BLUEPRINT_TYPE
  from parlai.crowdsourcing.tasks.acute_eval.util import get_hashed_combo_path
label_desc: Use image node_id 2 for calling a global function with example usage: get_multi_run_analyzer(opt) and returns: MultiRunAcuteAnalyzer