Starter Code

MidasHMM/hmm/main.py

@@ -0,0 +1,63 @@
+# main.py
+import yaml
+import logging
+from pathlib import Path
+from midas.data_processor import DataProcessor
+from midas.feature_engineer import FeatureEngineer
+from midas.hmm_trainer import HMMTrainer
+from midas.analysis import MarketRegimeAnalysis
+
+def main():
+    # Setup logging
+    logging.basicConfig(
+        level=logging.INFO,
+        format='%(asctime)s - %(name)s - %(levelname)s - %(message)s',
+        handlers=[
+            logging.FileHandler("midas.log"),
+            logging.StreamHandler()
+        ]
+    )
+    
+    try:
+        # Load config
+        with open('config/params.yaml') as f:
+            config = yaml.safe_load(f)
+            
+        # Create output directory
+        output_dir = Path(config['output_dir'])
+        output_dir.mkdir(parents=True, exist_ok=True)
+        
+        # Process data
+        processor = DataProcessor(config)
+        raw_data = processor.process_tickers()
+        
+        # Engineer features
+        engineer = FeatureEngineer(config)
+        features = engineer.calculate_features(raw_data)
+        
+        # Train HMM
+        trainer = HMMTrainer(config)
+        model = trainer.train(features)
+        trainer.save_model(output_dir / "hmm_model.pkl")
+        
+        # Generate analysis
+        analysis = MarketRegimeAnalysis(model, features)
+        
+        # Save plots
+        analysis.plot_regimes(pd.concat([d['close'] for d in raw_data.values]))
+        plt.savefig(output_dir / "combined_regimes.png")
+        
+        analysis.plot_transition_matrix()
+        plt.savefig(output_dir / "transition_matrix.png")
+        
+        analysis.plot_state_durations()
+        plt.savefig(output_dir / "state_durations.png")
+        
+        logging.info("Process completed successfully")
+        
+    except Exception as e:
+        logging.error(f"Main process failed: {str(e)}", exc_info=True)
+        raise
+
+if __name__ == "__main__":
+    main()