code: def findOptimalResults(expName, suite, outFile):
    
    writer = csv.writer(outFile)
    headers = ["testAccuracy", "bgAccuracy", "maxTotalAccuracy", "experiment path"]
    writer.writerow(headers)
    info = []
    print("\n================",expName,"=====================")
    try:
      # 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")
      for p in params:
        expPath = p["name"]
        if not "results" in expPath:
          expPath = os.path.join("results", expPath)
        maxTestAccuracy, maxValidationAccuracy, maxBGAccuracy, maxIter, maxTotalAccuracy = bestScore(expPath, suite)
        row = [maxTestAccuracy, maxBGAccuracy, maxTotalAccuracy, expPath]
        info.append(row)
        writer.writerow(row)
  
      print(tabulate(info, headers=headers, tablefmt="grid"))
    except:
      print("Couldn't analyze experiment",expName)
docs: Go through every experiment in the specified folder. For each experiment, find
    the iteration with the best validation score, and return the metrics
    associated with that iteration.