code: def configureNoisePlot(suite, experiments, labels, linestyles,
                         marker, filter=None):
    
    formats = dict()
    results = []
    for i in xrange(len(experiments)):
      path = suite.get_exp(experiments[i])[0]
      data = suite.get_exps(path=path)
      if filter is not None:
        data = filterResults(data, filter)
  
      # Format Linear Noise curve
      if len(data) > 1:
        format = {exp: {
          "label": "{},{}".format(labels[i], basename(exp)),
          "linestyle": "{}".format(linestyles[i]),
          "marker": "{}".format(marker[i])
        } for exp in data}
      else:
        format = {data[0]: {
          "label": "{}".format(labels[i]),
          "linestyle": "{}".format(linestyles[i]),
          "marker": "{}".format(marker[i])
        }}
  
      formats.update(format)
      results.extend(data)
  
    return (results, formats)
docs: Load experiment results anc configure the "Noise curve" Plot
    :param suite: The configured experiment suite. Must call `parse_opt` and `
                  parse_cfg` before calling this functions
    :param experiments: list containing the experiments to load
    :param experiments: list containing the experiments to load
    :param labels: list containing the plot labels for each experiment
    :param linestyles: list containing the plot linestyle for each experiment
    :param filter: list containing the specific parameters to filter
    :return: tuple containing the experiment results and plot formats to be passed
             to `plotNoiseCurve` function