demo.py

#!/usr/bin/env python3
"""
Demo Script for Functional Connectivity Analyzer

This script demonstrates the basic functionality of the Functional Connectivity Analyzer
using synthetic fMRI data.
"""

import numpy as np
import matplotlib.pyplot as plt
from connectivity_analyzer import FunctionalConnectivityAnalyzer
from utils import create_synthetic_data, create_roi_labels, print_analysis_summary


def main():
    """Run the demo."""
    print("🚀 FUNCTIONAL CONNECTIVITY ANALYZER DEMO")
    print("=" * 50)
    
    # Create synthetic fMRI data
    print("\n📊 Creating synthetic fMRI data...")
    n_timepoints = 150
    n_rois = 8
    sampling_rate = 1.0
    
    time_series, true_connectivity = create_synthetic_data(
        n_timepoints=n_timepoints,
        n_rois=n_rois,
        sampling_rate=sampling_rate,
        noise_level=0.1,
        connectivity_strength=0.6
    )
    
    roi_labels = create_roi_labels(n_rois, atlas_type="custom")
    
    print(f"   ✅ Created time series: {time_series.shape}")
    print(f"   ✅ Number of ROIs: {n_rois}")
    print(f"   ✅ Time points: {n_timepoints}")
    
    # Initialize analyzer
    print("\n🔧 Initializing analyzer...")
    analyzer = FunctionalConnectivityAnalyzer(
        sampling_rate=sampling_rate,
        detrend=True,
        normalize=True,
        verbose=True
    )
    
    # Set data
    analyzer.roi_signals = time_series
    analyzer.roi_labels = roi_labels
    
    # Compute connectivity metrics
    print("\n🧮 Computing connectivity metrics...")
    methods = ['coherence', 'plv', 'pearson_correlation']
    
    for method in methods:
        print(f"   Computing {method}...")
        matrix = analyzer.compute_connectivity(
            method=method,
            frequency_band=(0.01, 0.1)  # Slow-5 frequency band
        )
        print(f"   ✅ {method} computed successfully")
    
    # Visualize results
    print("\n📈 Creating visualizations...")
    
    for method in methods:
        matrix = analyzer.connectivity_matrices[method]
        
        # Plot connectivity matrix
        analyzer.plot_connectivity_matrix(
            matrix,
            roi_labels=roi_labels,
            title=f"{method.upper()} Connectivity Matrix"
        )
        
        # Plot network graph
        analyzer.plot_network_graph(
            matrix,
            roi_labels=roi_labels,
            threshold=0.3
        )
    
    # Network analysis
    print("\n🌐 Analyzing network properties...")
    
    for method in methods:
        matrix = analyzer.connectivity_matrices[method]
        network_props = analyzer.analyze_network_properties(matrix, threshold=0.3)
        
        print(f"\n   {method.upper()} Network Properties:")
        print(f"     • Nodes: {network_props['n_nodes']}")
        print(f"     • Edges: {network_props['n_edges']}")
        print(f"     • Density: {network_props['density']:.3f}")
        print(f"     • Clustering: {network_props['average_clustering']:.3f}")
        print(f"     • Modularity: {network_props['modularity']:.3f}")
    
    # Statistical analysis
    print("\n📊 Performing statistical analysis...")
    
    for method in methods:
        matrix = analyzer.connectivity_matrices[method]
        stats_results = analyzer.statistical_analysis(
            matrix,
            method='fdr',
            threshold=0.05
        )
        
        n_significant = np.sum(stats_results['significant_connections'])
        print(f"   {method}: {n_significant} significant connections")
    
    # Save results
    print("\n💾 Saving results...")
    analyzer.save_results(
        output_dir="demo_results",
        prefix="demo"
    )
    
    # Print summary
    print("\n📋 Analysis Summary:")
    summary = analyzer.get_summary()
    print_analysis_summary(summary)
    
    # Compare with true connectivity
    print("\n🔍 Comparing with true connectivity...")
    for method in methods:
        matrix = analyzer.connectivity_matrices[method]
        from utils import compute_matrix_similarity
        similarity = compute_matrix_similarity(matrix, true_connectivity, method='correlation')
        print(f"   {method} similarity: {similarity:.3f}")
    
    print("\n" + "=" * 50)
    print("🎉 DEMO COMPLETED SUCCESSFULLY!")
    print("=" * 50)
    print("\n📁 Results saved in 'demo_results/' directory")
    print("📊 Check the generated plots for visualizations")
    print("📄 CSV files contain the connectivity matrices")
    print("\n🔗 Next steps:")
    print("   • Try the examples/ directory for more advanced usage")
    print("   • Run tests with: python -m tests.test_connectivity_analyzer")
    print("   • Check the README.md for detailed documentation")


if __name__ == "__main__":
    main()