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#!/usr/bin/env python
"""
Plot FPR vs Bit Rate comparison across multiple models.
"""
import argparse
import pickle
import matplotlib.pyplot as plt
from pathlib import Path
from datetime import datetime
def load_fpr_bitrate_data(results_dir):
"""Load precomputed FPR vs Bit Rate data from results directory."""
data_file = Path(results_dir) / "fpr_vs_bitrate.pkl"
if not data_file.exists():
print(f"Warning: {data_file} not found")
return None
with open(data_file, 'rb') as f:
mean_bits_by_sigma = pickle.load(f)
return mean_bits_by_sigma
def plot_multi_model_comparison(sweep_dir, sigmas=[0.01, 0.05]):
"""Create comparison plots for all models in sweep directory."""
sweep_dir = Path(sweep_dir)
# Find all model directories
model_dirs = []
for subdir in sweep_dir.iterdir():
if subdir.is_dir():
# Look for results folder
results_dir = None
if (subdir / "results").exists():
results_dir = subdir / "results"
else:
# Try to find gumbel_cgs_analysis_results subfolder
gumbel_dirs = list((subdir / "gumbel_cgs_analysis_results").glob("*"))
if gumbel_dirs:
results_dir = sorted(gumbel_dirs)[-1] # Most recent
if results_dir and (results_dir / "all_prompts.pkl").exists():
model_name = subdir.name.replace('_', '/')
model_dirs.append((model_name, results_dir))
if not model_dirs:
print(f"Error: No valid model results found in {sweep_dir}")
return
print(f"Found {len(model_dirs)} models:")
for model_name, _ in model_dirs:
print(f" - {model_name}")
# Define colors and markers for different models
colors = ['#1f77b4', '#ff7f0e', '#2ca02c', '#d62728', '#9467bd', '#8c564b']
markers = ['o', 's', '^', 'v', 'D', 'P']
# Create plots for each sigma
for sigma in sigmas:
plt.figure(figsize=(12, 8))
for idx, (model_name, results_dir) in enumerate(model_dirs):
print(f"\nProcessing {model_name} for sigma={sigma}...")
mean_bits_by_sigma = load_fpr_bitrate_data(results_dir)
if mean_bits_by_sigma is None:
continue
# Check if this sigma was computed
if sigma not in mean_bits_by_sigma:
print(f" ✗ Sigma {sigma} not found in precomputed data")
continue
try:
# Extract FPR and bit rate values for this sigma
fpr_bitrate_dict = mean_bits_by_sigma[sigma]
fpr_values = sorted(fpr_bitrate_dict.keys())
bitrate_values = [fpr_bitrate_dict[fpr] for fpr in fpr_values]
# Plot
color = colors[idx % len(colors)]
marker = markers[idx % len(markers)]
# Simplify model name for legend
if 'Llama' in model_name:
label = 'Llama-' + model_name.split('-')[3] # e.g., "Llama-8B" or "Llama-3B"
elif 'Qwen' in model_name:
label = 'Qwen-' + model_name.split('-')[1] # e.g., "Qwen-30B"
elif 'Mixtral' in model_name:
label = 'Mixtral-8x7B'
else:
label = model_name
plt.plot(fpr_values, bitrate_values,
marker=marker, markersize=4, markevery=10,
color=color, linewidth=2, label=label, alpha=0.8)
print(f" ✓ Plotted {model_name}")
except Exception as e:
print(f" ✗ Failed to process {model_name}: {e}")
plt.xlabel("False Positive Rate (%)", fontsize=18)
plt.ylabel("Extractable Information (%)", fontsize=18)
plt.xscale("log")
plt.yscale("log")
plt.title(f"FPR vs Bit Rate Comparison (σ={sigma})", fontsize=20, fontweight='bold')
plt.tick_params(axis='both', which='major', labelsize=14)
plt.legend(fontsize=14, loc='best')
plt.grid(True, alpha=0.3)
plt.tight_layout()
# Save plot
datestring = datetime.now().strftime("%Y%m%d_%H%M%S")
output_file = sweep_dir / f"multi_model_comparison_sigma{sigma}_{datestring}"
plt.savefig(f"{output_file}.png", dpi=150, bbox_inches='tight')
plt.savefig(f"{output_file}.pdf", dpi=150, bbox_inches='tight')
plt.close()
print(f"\n✓ Saved comparison plot to {output_file}.png/.pdf")
print(f"\n{'='*80}")
print("All comparison plots created successfully!")
print(f"{'='*80}")
def main():
parser = argparse.ArgumentParser(description="Create multi-model comparison plots")
parser.add_argument("--sweep-dir", type=str, required=True,
help="Directory containing model experiment results")
parser.add_argument("--sigmas", type=str, default="0.01,0.05",
help="Comma-separated list of sigma values to plot (default: 0.01,0.05)")
args = parser.parse_args()
sigmas = [float(s.strip()) for s in args.sigmas.split(',')]
plot_multi_model_comparison(args.sweep_dir, sigmas)
if __name__ == "__main__":
main()
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