Avian Mortality Analytics System

class CollisionAnalyzer:
    def __init__(self, min_samples=5, eps=0.1):
        self.min_samples = min_samples
        self.eps = eps
        
    def analyze_collision_patterns(self, incidents):
        # Convert incidents to numpy array for processing
        coordinates = np.array([[i['lat'], i['lng']] for i in incidents])
        
        # Perform DBSCAN clustering
        clustering = DBSCAN(
            eps=self.eps, 
            min_samples=self.min_samples,
            metric='haversine'
        ).fit(coordinates)
        
        # Process clusters and calculate risk metrics
        clusters = self._process_clusters(coordinates, clustering.labels_)
        
        # Calculate kernel density estimation for risk heatmap
        kde = self._calculate_density(coordinates)
        
        return {
            'clusters': clusters,
            'density': kde,
            'risk_zones': self._identify_risk_zones(clusters, kde)
        }
    
    def _process_clusters(self, coordinates, labels):
        clusters = []
        unique_labels = set(labels)
        
        for label in unique_labels:
            if label == -1:
                continue
                
            mask = labels == label
            cluster_points = coordinates[mask]
            
            clusters.append({
                'center': cluster_points.mean(axis=0),
                'size': len(cluster_points),
                'density': len(cluster_points) / self._calculate_area(cluster_points),
                'points': cluster_points.tolist(),
                'risk_score': self._calculate_risk_score(cluster_points)
            })
        
        return clusters
    
    def _calculate_risk_score(self, cluster_points):
        density = len(cluster_points) / self._calculate_area(cluster_points)
        temporal_factor = self._analyze_temporal_patterns(cluster_points)
        environmental_risk = self._assess_environmental_factors(cluster_points)
        
        return (density * 0.4 + temporal_factor * 0.3 + environmental_risk * 0.3)