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"