plot_variance.py

import json
import matplotlib.pyplot as plt
import numpy as np

rollout_nums = [4, 8, 16, 32, 64, 128]

trace_var_bl_true = []
trace_var_bl_false = []

for nr in rollout_nums:
    with open(f"results_bs16_nr{nr}_nb4_r5_blTrue.json") as f:
        data = json.load(f)
        trace_var_bl_true.append(data["averaged"]["trace_variance"]["mean"])

    with open(f"results_bs16_nr{nr}_nb4_r5_blFalse.json") as f:
        data = json.load(f)
        trace_var_bl_false.append(data["averaged"]["trace_variance"]["mean"])

fig, ax = plt.subplots(figsize=(7, 5))

ax.plot(rollout_nums, trace_var_bl_true, marker='o', label='MaxRL')
ax.plot(rollout_nums, trace_var_bl_false, marker='s', label='MaxRL (w/o baseline)')

ax.set_xscale('log', base=2)
ax.set_xticks(rollout_nums)
ax.set_xticklabels(rollout_nums)
ax.set_xlabel('Rollout', fontsize=14)
ax.set_ylabel('Gradient Variance', fontsize=14)
ax.legend(fontsize=12)
ax.grid(True, alpha=0.3)

plt.tight_layout()
plt.savefig("variance_plot.pdf", dpi=300)
plt.savefig("variance_plot.png", dpi=300)
print("Saved variance_plot.pdf and variance_plot.png")

print("\nData:")
for nr, v_t, v_f in zip(rollout_nums, trace_var_bl_true, trace_var_bl_false):
    print(f"  nr={nr}: blTrue={v_t:.4f}, blFalse={v_f:.4f}")