Initial commit: organized project structure for student handoff

Reorganized flat 41-file directory into structured layout with:
- scripts/ for Python analysis code with shared config.py
- notebooks/ for Jupyter analysis notebooks
- data/ split into raw/, metadata/, processed/
- docs/ with analysis summary, experimental design, and bimodal hypothesis tutorial
- tasks/ with todo checklist and lessons learned
- Comprehensive README, PLANNING.md, and .gitignore

Co-Authored-By: Claude Opus 4.6 <noreply@anthropic.com>

scripts/plot_avg_distance_first_200s.py

@@ -0,0 +1,51 @@
+import pandas as pd
+import matplotlib.pyplot as plt
+import numpy as np
+
+from config import DATA_PROCESSED, FIGURES
+
+# Load data
+trained_distances = pd.read_csv(DATA_PROCESSED / 'trained_distances.csv')
+untrained_distances = pd.read_csv(DATA_PROCESSED / 'untrained_distances.csv')
+
+# Remove NaN distances and filter for first 200 seconds
+trained_clean = trained_distances.dropna(subset=['distance'])
+untrained_clean = untrained_distances.dropna(subset=['distance'])
+
+trained_filtered = trained_clean[trained_clean['t'] <= 200000]
+untrained_filtered = untrained_clean[untrained_clean['t'] <= 200000]
+
+# Calculate average distance over time
+trained_avg = trained_filtered.groupby('t')['distance'].mean()
+untrained_avg = untrained_filtered.groupby('t')['distance'].mean()
+
+# Apply smoothing
+window_size = 50
+trained_smooth = trained_avg.rolling(window=window_size, center=True).mean()
+untrained_smooth = untrained_avg.rolling(window=window_size, center=True).mean()
+
+# Create the plot
+plt.figure(figsize=(12, 6))
+
+plt.plot(trained_smooth.index/1000, trained_smooth.values,
+         label='Trained (smoothed)', color='blue', linewidth=2)
+plt.plot(untrained_smooth.index/1000, untrained_smooth.values,
+         label='Untrained (smoothed)', color='red', linewidth=2)
+
+plt.xlabel('Time (seconds)')
+plt.ylabel('Average Distance')
+plt.title('Average Distance Between Flies Over Time (First 200 Seconds)')
+plt.legend()
+plt.grid(True, alpha=0.3)
+
+plt.tight_layout()
+plt.savefig(FIGURES / 'avg_distance_over_time_first_200s.png', dpi=300, bbox_inches='tight')
+plt.show()
+
+print("Trained flies (first 200 seconds):")
+print(f"  Mean distance: {trained_filtered['distance'].mean():.2f}")
+print(f"  Std distance: {trained_filtered['distance'].std():.2f}")
+
+print("\nUntrained flies (first 200 seconds):")
+print(f"  Mean distance: {untrained_filtered['distance'].mean():.2f}")
+print(f"  Std distance: {untrained_filtered['distance'].std():.2f}")