}
set_figure_params(serif=True, fontsize=12)
fig, axes = plt.subplots(ncols=4, nrows=2, sharey=True)
fig.set_size_inches(6.75, 2)
for i, (environment, max_value) in enumerate(ENVIRONMENTS.items()):
row, col = i // 4, i % 4
df = pd.read_pickle(f"{environment}/{environment}_results.pkl")
df = df[df.name != "DQN-delayed"]
df = df[df.name != "REINFORCE"]
plot_df_key(
df=df,
axes=axes[row, col],
key="value_evaluation" if environment != "cart_pole" else "train_return",
get_color=get_color,
get_linestyle=get_linestyle,
max_value=max_value,
)
if environment == "two_state_deterministic":
title = "Two State D"
elif environment == "two_state_stochastic":
title = "Two State S"
elif environment == "windy_grid_world":
title = "Grid World"
else:
title = " ".join(environment.split("_")).title()
axes[row, col].set_title(title, fontsize=11)
for col in range(4):
"""Python Script Template."""
import pandas as pd
import matplotlib.pyplot as plt
from exps.plotting import plot_df_key, set_figure_params
from exps.environments.utilities import get_color, get_linestyle
df = pd.read_pickle("two_state_deterministic_results.pkl")
set_figure_params(serif=True)
fig, axes = plt.subplots(ncols=1, nrows=1)
plot_df_key(
df=df,
axes=axes,
key="value_evaluation",
get_color=get_color,
get_linestyle=get_linestyle,
)
plt.xlabel("Episode")
plt.ylabel("Reward")
plt.title(f"Two-State-Deterministic")
# plt.legend(loc="best", frameon=False)
plt.legend(bbox_to_anchor=(0.52, 0.3), loc="lower left", frameon=False, ncol=2)
plt.savefig("two_state_deterministic_results.pdf", bbox_inches="tight")
"""Python Script Template."""
import pandas as pd
import matplotlib.pyplot as plt
from exps.plotting import plot_df_key, set_figure_params
from exps.environments.utilities import get_color, get_linestyle
df = pd.read_pickle("cart_pole_results.pkl")
df = df[df.time < 25]
# set_figure_params(serif=True)
fig, axes = plt.subplots(ncols=1, nrows=1)
plot_df_key(
df=df,
axes=axes,
key="train_return",
get_color=get_color,
get_linestyle=get_linestyle,
)
plt.xlabel("Episode")
plt.ylabel("Reward")
plt.title(f"Cart-Pole")
plt.legend(loc="best", frameon=False)
# plt.legend(bbox_to_anchor=(0.7, 0.32), loc="lower left", frameon=False)
plt.savefig("cart_pole_results.pdf", bbox_inches="tight")