code: def main():
      import argparse
  
      parser = argparse.ArgumentParser()
      parser.add_argument("logdir", nargs="*")
      parser.add_argument("--legend", "-l", nargs="*")
      parser.add_argument("--xaxis", "-x", default="TotalEnvInteracts")
      parser.add_argument(
          "--value", "-y", default="Performance", nargs="*"
      )
      parser.add_argument("--count", action="store_true")
      parser.add_argument("--smooth", "-s", type=int, default=1)
      parser.add_argument("--select", nargs="*")
      parser.add_argument("--exclude", nargs="*")
      parser.add_argument("--est", default="mean")
      args = parser.parse_args()
      """
  
      Args: 
          logdir (strings): As many log directories (or prefixes to log 
              directories, which the plotter will autocomplete internally) as 
              you'd like to plot from.
  
          legend (strings): Optional way to specify legend for the plot. The 
              plotter legend will automatically use the ``exp_name`` from the
              config.json file, unless you tell it otherwise through this flag.
              This only works if you provide a name for each directory that
              will get plotted. (Note: this may not be the same as the number
              of logdir args you provide! Recall that the plotter looks for
              autocompletes of the logdir args: there may be more than one 
              match for a given logdir prefix, and you will need to provide a 
              legend string for each one of those matches---unless you have 
              removed some of them as candidates via selection or exclusion 
              rules (below).)
  
          xaxis (string): Pick what column from data is used for the x-axis.
               Defaults to ``TotalEnvInteracts``.
  
          value (strings): Pick what columns from data to graph on the y-axis. 
              Submitting multiple values will produce multiple graphs. Defaults
              to ``Performance``, which is not an actual output of any algorithm.
              Instead, ``Performance`` refers to either ``AverageEpRet``, the 
              correct performance measure for the on-policy algorithms, or
              ``AverageTestEpRet``, the correct performance measure for the 
              off-policy algorithms. The plotter will automatically figure out 
              which of ``AverageEpRet`` or ``AverageTestEpRet`` to report for 
              each separate logdir.
  
          count: Optional flag. By default, the plotter shows y-values which
              are averaged across all results that share an ``exp_name``, 
              which is typically a set of identical experiments that only vary
              in random seed. But if you'd like to see all of those curves 
              separately, use the ``--count`` flag.
  
          smooth (int): Smooth data by averaging it over a fixed window. This 
              parameter says how wide the averaging window will be.
  
          select (strings): Optional selection rule: the plotter will only show
              curves from logdirs that contain all of these substrings.
  
          exclude (strings): Optional exclusion rule: plotter will only show 
              curves from logdirs that do not contain these substrings.
  
      """
  
      make_plots(
          args.logdir,
          args.legend,
          args.xaxis,
          args.value,
          args.count,
          smooth=args.smooth,
          select=args.select,
          exclude=args.exclude,
          estimator=args.est,
      )
  
file_path: spinningup/spinup/utils/plot.py
imports: import seaborn
  import pandas
  import matplotlib.pyplot
  import json
  import os
  import os.path
  import numpy
label_desc: Use image node_id 5 for calling a global function with example usage: main() without return types