Giorgio
e7e4db264d
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>
51 lines
1.9 KiB
Python
51 lines
1.9 KiB
Python
import pandas as pd
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import matplotlib.pyplot as plt
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import numpy as np
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from config import DATA_PROCESSED, FIGURES
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# Load data
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trained_distances = pd.read_csv(DATA_PROCESSED / 'trained_distances.csv')
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untrained_distances = pd.read_csv(DATA_PROCESSED / 'untrained_distances.csv')
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# Remove NaN distances and filter for first 200 seconds
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trained_clean = trained_distances.dropna(subset=['distance'])
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untrained_clean = untrained_distances.dropna(subset=['distance'])
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trained_filtered = trained_clean[trained_clean['t'] <= 200000]
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untrained_filtered = untrained_clean[untrained_clean['t'] <= 200000]
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# Calculate average distance over time
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trained_avg = trained_filtered.groupby('t')['distance'].mean()
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untrained_avg = untrained_filtered.groupby('t')['distance'].mean()
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# Apply smoothing
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window_size = 50
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trained_smooth = trained_avg.rolling(window=window_size, center=True).mean()
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untrained_smooth = untrained_avg.rolling(window=window_size, center=True).mean()
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# Create the plot
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plt.figure(figsize=(12, 6))
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plt.plot(trained_smooth.index/1000, trained_smooth.values,
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label='Trained (smoothed)', color='blue', linewidth=2)
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plt.plot(untrained_smooth.index/1000, untrained_smooth.values,
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label='Untrained (smoothed)', color='red', linewidth=2)
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plt.xlabel('Time (seconds)')
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plt.ylabel('Average Distance')
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plt.title('Average Distance Between Flies Over Time (First 200 Seconds)')
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plt.legend()
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plt.grid(True, alpha=0.3)
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plt.tight_layout()
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plt.savefig(FIGURES / 'avg_distance_over_time_first_200s.png', dpi=300, bbox_inches='tight')
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plt.show()
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print("Trained flies (first 200 seconds):")
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print(f" Mean distance: {trained_filtered['distance'].mean():.2f}")
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print(f" Std distance: {trained_filtered['distance'].std():.2f}")
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print("\nUntrained flies (first 200 seconds):")
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print(f" Mean distance: {untrained_filtered['distance'].mean():.2f}")
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print(f" Std distance: {untrained_filtered['distance'].std():.2f}")
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