code: def analyzeParameters(expName, suite):
    
    print("\n================",expName,"=====================")
    try:
      expParams = suite.get_params(expName)
      pprint.pprint(expParams)
  
      for p in ["boost_strength", "k", "learning_rate", "weight_sparsity",
                "k_inference_factor", "boost_strength_factor",
                "c1_out_channels", "c1_k", "learning_rate_factor",
                "batches_in_epoch",
                ]:
        if p in expParams and type(expParams[p]) == list:
          print("\n",p)
          for v1 in expParams[p]:
            # Retrieve the last totalCorrect from each experiment
            # Print them sorted from best to worst
            values, params = suite.get_values_fix_params(
              expName, 0, "testerror", "last", **{p:v1})
            v = np.array(values)
            try:
              print("Average/min/max for", p, v1, "=", v.mean(), v.min(), v.max())
              # sortedIndices = v.argsort()
              # for i in sortedIndices[::-1]:
              #   print(v[i],params[i]["name"])
            except:
              print("Can't compute stats for",p)
  
    except:
      print("Couldn't load experiment",expName)
docs: Analyze the impact of each list parameter in this experiment