def main():
parser = argparse.ArgumentParser(
description='Plots an experiment in terminal')
parser.add_argument('glob', help='directory of experiment to plot')
parser.add_argument('--window',
help='smoothing window',
type=int,
default=100)
parser.add_argument('--width', help='smoothing window', type=int)
parser.add_argument('--height', help='smoothing window', type=int)
parser.add_argument('-x', help='x axis', default='frames')
parser.add_argument('-y', help='y axis', default='mean_win_rate')
args = parser.parse_args()
exps_and_logs = Experiment.discover_logs(args.glob, JSONLogger())
print('loaded {} experiments'.format(len(exps_and_logs)))
fig = plotille.Figure()
kwargs = {}
for exp, log in exps_and_logs:
if log:
df = pd.DataFrame(log)
fig.plot(X=df[args.x],
Y=df[args.y].rolling(args.window, min_periods=1).mean(),
label=exp.name,
**kwargs)
fig.x_label = args.x
fig.y_label = args.y
if args.height:
fig.height = args.height
if args.width:
fig.width = args.width
print(fig.show(legend=True))
exp = Experiment(
config=dict(seed=seed,
type=t,
name=name,
logdir=os.path.join(args.logdir, 'seeded')),
loggers=loggers).start(delete_existing=args.delete_existing)
for i in range(100):
if t == 'linear':
score = i + random.uniform(-noise, noise)
elif t == 'quadratic':
score = (i / 10)**2 + random.uniform(-noise * 2, noise * 2)
exp.log(dict(score=score))
exp.finish()
exps_and_logs = Experiment.discover_logs(glob_path=os.path.join(
args.logdir, 'seeded', '*'),
logger=JSONLogger())
if args.wandb:
WandbLogger.upload_logs(exps_and_logs, project='seeded_upload')
plotter = LinePlotter()
fig, ax = plt.subplots(figsize=(5, 5))
plotter.plot(exps_and_logs,
x='step',
y='score',
group='type',
xpid='name',
read_every=2,
smooth_window=10,
ax=ax)