Updates

ETB-API/analytics_predictive_insights/management/commands/run_anomaly_detection.py

@@ -0,0 +1,63 @@
+"""
+Management command to run anomaly detection
+"""
+from django.core.management.base import BaseCommand, CommandError
+from analytics_predictive_insights.models import PredictiveModel
+from analytics_predictive_insights.ml.anomaly_detection import AnomalyDetectionService
+
+
+class Command(BaseCommand):
+    """Run anomaly detection using active models"""
+    
+    help = 'Run anomaly detection using all active anomaly detection models'
+    
+    def add_arguments(self, parser):
+        parser.add_argument(
+            '--model-id',
+            type=str,
+            help='Run anomaly detection for a specific model ID only'
+        )
+        parser.add_argument(
+            '--time-window',
+            type=int,
+            default=24,
+            help='Time window in hours for anomaly detection (default: 24)'
+        )
+    
+    def handle(self, *args, **options):
+        """Handle the command execution"""
+        model_id = options.get('model_id')
+        time_window = options.get('time_window', 24)
+        
+        try:
+            # Initialize anomaly detection service
+            anomaly_service = AnomalyDetectionService()
+            
+            self.stdout.write('Starting anomaly detection...')
+            
+            # Run anomaly detection
+            total_anomalies = anomaly_service.run_anomaly_detection(model_id)
+            
+            if total_anomalies > 0:
+                self.stdout.write(
+                    self.style.SUCCESS(f'✓ Detected {total_anomalies} anomalies')
+                )
+            else:
+                self.stdout.write(
+                    self.style.WARNING('⚠ No anomalies detected')
+                )
+            
+            # Get summary
+            summary = anomaly_service.get_anomaly_summary(time_window)
+            
+            self.stdout.write('\nAnomaly Summary:')
+            self.stdout.write(f'  Total anomalies: {summary["total_anomalies"]}')
+            self.stdout.write(f'  Critical: {summary["critical_anomalies"]}')
+            self.stdout.write(f'  High: {summary["high_anomalies"]}')
+            self.stdout.write(f'  Medium: {summary["medium_anomalies"]}')
+            self.stdout.write(f'  Low: {summary["low_anomalies"]}')
+            self.stdout.write(f'  Unresolved: {summary["unresolved_anomalies"]}')
+            self.stdout.write(f'  False positive rate: {summary["false_positive_rate"]:.2f}%')
+            
+        except Exception as e:
+            raise CommandError(f'Error running anomaly detection: {str(e)}')