f"{yKey}@16%",
x_key=f"{xKey}@mean",
path="**/metrics.pkl",
num_bins=bins,
dropna=dropna)
plt.plot(step, avg, color=color, label=label)
plt.fill_between(step, bottom, top, alpha=0.15, color=color)
with doc @ "Step 2: Plot", doc.table().figure_row() as r:
colors = ['#49b8ff', '#444444', '#ff7575', '#66c56c', '#f4b247']
for method in ['curl', 'rad', 'pad']:
plt.figure()
with loader.Prefix(method):
group(yKey="episode_reward/mean",
bins=None,
dropna=True,
color=colors[0],
label="Eval")
group(yKey="train/episode_reward/mean",
color=colors[1],
label="Train")
plt.gca().xaxis.set_major_formatter(
ticker.FuncFormatter(lambda x, _: f"{int(x / 1000)}k"
if x else "0"))
plt.legend(frameon=False)
plt.ylim(0, 1000)
r.savefig(f"figures/{method}/train_vs_eval.png",
plt.plot(step, avg, color=color, label=label)
plt.fill_between(step, bottom, top, alpha=0.15, color=color)
with doc @ "Step 2: Plot":
title = "CURL"
colors = ['#49b8ff', '#444444', '#ff7575', '#66c56c', '#f4b247']
for domain in [
'walker-walk', 'cartpole-swingup', 'ball_in_cup-catch',
'finger-spin'
]:
name, task = domain.split("-")
doc(name.replace('_', ' ').title(), f"[{task}]")
with loader.Prefix(domain), doc.table().figure_row() as r:
for method in ['curl', 'rad', 'pad']:
with loader.Prefix(method):
group(yKey="episode_reward/mean",
bins=None,
dropna=True,
color=colors[0],
label="Eval")
group(yKey="train/episode_reward/mean",
color=colors[1],
label="Train")
plt.legend(frameon=False)
plt.ylim(0, 1000)
plt.gca().xaxis.set_major_formatter(
ticker.FuncFormatter(lambda x, _: f"{int(x / 1000)}k"