ampel360_integrated_demo.py

#!/usr/bin/env python3
"""
AMPEL360-H₂-BWB-Q Integrated Framework Demonstration
Complete showcase of the next-generation aerospace framework capabilities
"""

import os
import sys
import json
import time
import logging
import asyncio
from typing import Dict, Any

# Add framework paths
sys.path.append(os.path.join(os.path.dirname(__file__), 'OPTIM-FRAMEWORK', 'T-TECHNOLOGICAL', 'AQUA-OS'))
sys.path.append(os.path.join(os.path.dirname(__file__), 'OPTIM-FRAMEWORK', 'I-INTELLIGENT', 'quantum-ml'))
sys.path.append(os.path.join(os.path.dirname(__file__), 'OPTIM-FRAMEWORK', 'T-TECHNOLOGICAL', 'ATOMIC-DESIGN'))
sys.path.append(os.path.join(os.path.dirname(__file__), 'OPTIM-FRAMEWORK', 'M-MACHINE', 'digital-twin-sync'))

# Import framework components
try:
    from aqua_os_core import AQUAOSCore
    AQUA_OS_AVAILABLE = True
except ImportError:
    AQUA_OS_AVAILABLE = False

try:
    from quantum_ml_pipeline import AerospaceMLPipeline, TrainingConfig, ModelType, FeatureType
    ML_PIPELINE_AVAILABLE = True
except ImportError:
    ML_PIPELINE_AVAILABLE = False

try:
    from atomic_design_system import ComponentLibrary, create_bwb_component_library
    ATOMIC_DESIGN_AVAILABLE = True
except ImportError:
    ATOMIC_DESIGN_AVAILABLE = False

try:
    from digital_twin_sync import BWBDigitalTwin
    DIGITAL_TWIN_AVAILABLE = True
except ImportError:
    DIGITAL_TWIN_AVAILABLE = False


class AMPEL360Framework:
    """
    Integrated AMPEL360-H₂-BWB-Q Framework
    Orchestrates all quantum-enhanced aerospace design capabilities
    """
    
    def __init__(self):
        self.logger = logging.getLogger(__name__)
        
        # Initialize framework components
        self.aqua_os = None
        self.ml_pipeline = None
        self.component_library = None
        self.digital_twin = None
        
        # Framework status
        self.initialized_components = []
        self.performance_metrics = {}
        
    def initialize(self) -> Dict[str, Any]:
        """Initialize all framework components"""
        self.logger.info("Initializing AMPEL360-H₂-BWB-Q Framework...")
        
        initialization_results = {
            "aqua_os": self._initialize_aqua_os(),
            "ml_pipeline": self._initialize_ml_pipeline(),
            "atomic_design": self._initialize_atomic_design(),
            "digital_twin": self._initialize_digital_twin()
        }
        
        # Count successfully initialized components
        success_count = sum(1 for result in initialization_results.values() if result["success"])
        total_count = len(initialization_results)
        
        self.logger.info(f"Framework initialization: {success_count}/{total_count} components ready")
        
        return {
            "overall_success": success_count == total_count,
            "component_results": initialization_results,
            "initialized_components": self.initialized_components,
            "framework_status": "operational" if success_count >= 2 else "degraded"
        }
    
    def _initialize_aqua_os(self) -> Dict[str, Any]:
        """Initialize AQUA-OS quantum operating system"""
        if not AQUA_OS_AVAILABLE:
            return {"success": False, "error": "AQUA-OS module not available"}
        
        try:
            self.aqua_os = AQUAOSCore()
            if self.aqua_os.initialize():
                self.initialized_components.append("AQUA-OS")
                return {
                    "success": True,
                    "status": self.aqua_os.get_system_status(),
                    "description": "Quantum computing infrastructure ready"
                }
            else:
                return {"success": False, "error": "AQUA-OS initialization failed"}
        except Exception as e:
            return {"success": False, "error": f"AQUA-OS error: {e}"}
    
    def _initialize_ml_pipeline(self) -> Dict[str, Any]:
        """Initialize quantum-enhanced ML pipeline"""
        if not ML_PIPELINE_AVAILABLE:
            return {"success": False, "error": "ML pipeline module not available"}
        
        try:
            config = TrainingConfig(
                model_type=ModelType.HYBRID_ENSEMBLE,
                feature_type=FeatureType.HYBRID,
                quantum_feature_dimension=8,
                max_training_time=60  # Reduced for demo
            )
            
            self.ml_pipeline = AerospaceMLPipeline(config)
            self.initialized_components.append("Quantum-ML")
            
            return {
                "success": True,
                "configuration": {
                    "model_type": config.model_type.value,
                    "feature_type": config.feature_type.value,
                    "quantum_dimension": config.quantum_feature_dimension
                },
                "description": "Quantum-enhanced machine learning ready"
            }
        except Exception as e:
            return {"success": False, "error": f"ML pipeline error: {e}"}
    
    def _initialize_atomic_design(self) -> Dict[str, Any]:
        """Initialize atomic design system"""
        if not ATOMIC_DESIGN_AVAILABLE:
            return {"success": False, "error": "Atomic design module not available"}
        
        try:
            self.component_library = create_bwb_component_library()
            self.initialized_components.append("Atomic-Design")
            
            component_count = len(self.component_library.components)
            
            return {
                "success": True,
                "component_count": component_count,
                "component_types": list(self.component_library.component_types.keys()),
                "description": f"Component library with {component_count} BWB components ready"
            }
        except Exception as e:
            return {"success": False, "error": f"Atomic design error: {e}"}
    
    def _initialize_digital_twin(self) -> Dict[str, Any]:
        """Initialize digital twin synchronization"""
        if not DIGITAL_TWIN_AVAILABLE:
            return {"success": False, "error": "Digital twin module not available"}
        
        try:
            self.digital_twin = BWBDigitalTwin()
            self.digital_twin.synchronizer.start_synchronization()
            self.initialized_components.append("Digital-Twin")
            
            return {
                "success": True,
                "sync_mode": "real_time",
                "description": "Digital twin synchronization active"
            }
        except Exception as e:
            return {"success": False, "error": f"Digital twin error: {e}"}
    
    async def run_integrated_demonstration(self) -> Dict[str, Any]:
        """Run comprehensive integrated demonstration"""
        self.logger.info("Starting integrated AMPEL360 demonstration...")
        
        demonstration_results = {}
        
        # Phase 1: Quantum-Enhanced Design Optimization
        if self.ml_pipeline:
            self.logger.info("Phase 1: Quantum-Enhanced Design Optimization")
            ml_results = await self._demonstrate_ml_optimization()
            demonstration_results["quantum_optimization"] = ml_results
        
        # Phase 2: Component-Based Design
        if self.component_library:
            self.logger.info("Phase 2: Component-Based Design")
            atomic_results = self._demonstrate_atomic_design()
            demonstration_results["atomic_design"] = atomic_results
        
        # Phase 3: Digital Twin Simulation
        if self.digital_twin:
            self.logger.info("Phase 3: Digital Twin Simulation") 
            twin_results = await self._demonstrate_digital_twin()
            demonstration_results["digital_twin"] = twin_results
        
        # Phase 4: Quantum Computing Infrastructure
        if self.aqua_os:
            self.logger.info("Phase 4: Quantum Computing Infrastructure")
            quantum_results = self._demonstrate_quantum_capabilities()
            demonstration_results["quantum_infrastructure"] = quantum_results
        
        # Calculate overall performance
        overall_performance = self._calculate_framework_performance(demonstration_results)
        
        return {
            "demonstration_results": demonstration_results,
            "performance_metrics": overall_performance,
            "framework_capabilities": self._summarize_capabilities()
        }
    
    async def _demonstrate_ml_optimization(self) -> Dict[str, Any]:
        """Demonstrate quantum-enhanced ML optimization"""
        start_time = time.time()
        
        # Train ML pipeline
        performance = self.ml_pipeline.train_pipeline()
        
        # Test design optimization
        optimal_design = self.ml_pipeline.optimize_design()
        
        # Test prediction
        test_design = {
            'wingspan': 60.0,
            'chord_root': 15.0,
            'chord_tip': 4.0,
            'sweep_angle': 25.0,
            'twist': 0.0,
            'thickness_ratio': 0.14,
            'aspect_ratio': 6.3
        }
        
        prediction = self.ml_pipeline.predict_design_performance(test_design)
        
        execution_time = time.time() - start_time
        
        return {
            "training_performance": performance,
            "optimal_design": optimal_design,
            "test_prediction": prediction,
            "execution_time": execution_time,
            "quantum_advantage": performance.get("quantum_advantage", 0)
        }
    
    def _demonstrate_atomic_design(self) -> Dict[str, Any]:
        """Demonstrate atomic design system"""
        start_time = time.time()
        
        # Validate all components
        validation_results = {}
        for comp_id, component in self.component_library.components.items():
            validation = component.validate()
            validation_results[comp_id] = validation
        
        # Test assembly optimization
        component_ids = list(self.component_library.components.keys())
        assembly_optimization = self.component_library.optimize_assembly(
            component_ids=component_ids,
            objectives=["weight", "cost"],
            constraints={"max_weight": 10000, "max_cost": 3000000}
        )
        
        execution_time = time.time() - start_time
        
        return {
            "component_validation": validation_results,
            "assembly_optimization": assembly_optimization,
            "execution_time": execution_time,
            "component_hierarchy": self._analyze_component_hierarchy()
        }
    
    async def _demonstrate_digital_twin(self) -> Dict[str, Any]:
        """Demonstrate digital twin capabilities"""
        start_time = time.time()
        
        # Run short simulation
        await self.digital_twin.simulate_flight_test(duration=10.0)
        
        # Get twin status
        twin_status = self.digital_twin.get_twin_status()
        
        execution_time = time.time() - start_time
        
        return {
            "simulation_duration": 10.0,
            "twin_status": twin_status,
            "execution_time": execution_time,
            "sync_performance": twin_status.get("sync_statistics", {})
        }
    
    def _demonstrate_quantum_capabilities(self) -> Dict[str, Any]:
        """Demonstrate quantum computing capabilities"""
        if not self.aqua_os:
            return {"error": "AQUA-OS not available"}
        
        system_status = self.aqua_os.get_system_status()
        
        # Simulate quantum job submission
        backend_info = {}
        for backend_name in self.aqua_os.backend_manager.get_available_backends():
            try:
                info = self.aqua_os.backend_manager.get_backend_info(backend_name)
                backend_info[backend_name] = info
            except:
                pass
        
        return {
            "system_status": system_status,
            "available_backends": backend_info,
            "quantum_readiness": system_status["status"] == "operational"
        }
    
    def _analyze_component_hierarchy(self) -> Dict[str, Any]:
        """Analyze component hierarchy in atomic design"""
        hierarchy = {"atoms": 0, "molecules": 0, "organisms": 0, "templates": 0, "pages": 0}
        
        for component in self.component_library.components.values():
            level = component.level.value
            if level in hierarchy:
                hierarchy[level] += 1
        
        return hierarchy
    
    def _calculate_framework_performance(self, results: Dict[str, Any]) -> Dict[str, Any]:
        """Calculate overall framework performance metrics"""
        performance = {
            "execution_times": {},
            "success_rates": {},
            "capabilities_demonstrated": len(results),
            "overall_score": 0.0
        }
        
        # Collect execution times
        for phase, result in results.items():
            if "execution_time" in result:
                performance["execution_times"][phase] = result["execution_time"]
        
        # Calculate success rates
        for phase, result in results.items():
            if "error" not in result:
                performance["success_rates"][phase] = 1.0
            else:
                performance["success_rates"][phase] = 0.0
        
        # Overall score (0-100)
        if performance["success_rates"]:
            avg_success = sum(performance["success_rates"].values()) / len(performance["success_rates"])
            performance["overall_score"] = avg_success * 100
        
        return performance
    
    def _summarize_capabilities(self) -> Dict[str, Any]:
        """Summarize demonstrated framework capabilities"""
        capabilities = {
            "quantum_computing": "AQUA-OS" in self.initialized_components,
            "machine_learning": "Quantum-ML" in self.initialized_components,
            "atomic_design": "Atomic-Design" in self.initialized_components,
            "digital_twin": "Digital-Twin" in self.initialized_components,
            "optimization": True,  # Always available through basic systems
            "simulation": True,    # Always available through basic systems
            "integration": len(self.initialized_components) > 1
        }
        
        # Advanced capabilities
        advanced_capabilities = []
        if capabilities["quantum_computing"] and capabilities["machine_learning"]:
            advanced_capabilities.append("Quantum-Enhanced ML")
        if capabilities["atomic_design"] and capabilities["optimization"]:
            advanced_capabilities.append("Component-Based Optimization")
        if capabilities["digital_twin"] and capabilities["simulation"]:
            advanced_capabilities.append("Real-Time Twin Synchronization")
        if len(self.initialized_components) >= 3:
            advanced_capabilities.append("Integrated Multi-Domain Design")
        
        capabilities["advanced_features"] = advanced_capabilities
        
        return capabilities
    
    def shutdown(self):
        """Shutdown framework components"""
        self.logger.info("Shutting down AMPEL360 framework...")
        
        if self.digital_twin:
            self.digital_twin.synchronizer.stop_synchronization()
        
        # Additional cleanup as needed
        self.logger.info("Framework shutdown complete")


async def main():
    """Main demonstration function"""
    print("🚁" * 30)
    print("🚁 AMPEL360-H₂-BWB-Q INTEGRATED FRAMEWORK DEMONSTRATION 🚁")
    print("🚁" * 30)
    print()
    print("Next-Generation Aerospace Framework Showcase")
    print("Quantum-Powered Development • Onboard Quantum Systems • Advanced Optimization")
    print("Built on Amedeo Pelliccia Methodology • Digital Twins • MBSE • CQEA")
    print()
    print("=" * 80)
    
    # Configure logging
    logging.basicConfig(
        level=logging.INFO,
        format='%(asctime)s - %(name)s - %(levelname)s - %(message)s'
    )
    
    # Initialize framework
    framework = AMPEL360Framework()
    
    print("🔧 Initializing AMPEL360 Framework Components...")
    init_results = framework.initialize()
    
    print(f"   Framework Status: {init_results['framework_status'].upper()}")
    print(f"   Components Ready: {len(init_results['initialized_components'])}/4")
    
    for component, result in init_results['component_results'].items():
        status = "✅" if result['success'] else "❌"
        description = result.get('description', result.get('error', 'Unknown'))
        print(f"   {status} {component.replace('_', '-').title()}: {description}")
    
    print("\n" + "=" * 80)
    
    if init_results['overall_success'] or len(init_results['initialized_components']) >= 2:
        print("🚀 Running Integrated Demonstration...")
        print()
        
        # Run comprehensive demonstration
        demo_results = await framework.run_integrated_demonstration()
        
        print("\n" + "=" * 80)
        print("📊 DEMONSTRATION RESULTS")
        print("=" * 80)
        
        # Display results for each phase
        for phase, results in demo_results['demonstration_results'].items():
            print(f"\n🎯 {phase.replace('_', ' ').title()}:")
            
            if 'execution_time' in results:
                print(f"   ⏱️  Execution Time: {results['execution_time']:.2f} seconds")
            
            if phase == 'quantum_optimization':
                if 'optimal_design' in results:
                    opt_perf = results['optimal_design']['optimal_performance']
                    print(f"   🎯 Optimal Performance: {opt_perf:.2f}")
                if 'quantum_advantage' in results:
                    qa = results['quantum_advantage']
                    print(f"   ⚡ Quantum Advantage: {qa:.1f}%")
            
            elif phase == 'atomic_design':
                if 'assembly_optimization' in results:
                    assembly = results['assembly_optimization']['system_performance']
                    print(f"   🏗️  Assembly Mass: {assembly['total_mass']:.0f} kg")
                    print(f"   💰 Assembly Cost: ${assembly['total_cost']:,.0f}")
            
            elif phase == 'digital_twin':
                if 'twin_status' in results:
                    updates = results['twin_status']['update_count']
                    confidence = results['twin_status']['current_state']['confidence_scores']['overall']
                    print(f"   🔄 Data Updates: {updates}")
                    print(f"   🎯 Confidence: {confidence:.1%}")
            
            elif phase == 'quantum_infrastructure':
                if 'system_status' in results:
                    backends = results['system_status']['available_backends']
                    print(f"   🔧 Available Backends: {backends}")
        
        # Overall performance summary
        performance = demo_results['performance_metrics']
        print(f"\n🏆 OVERALL PERFORMANCE")
        print(f"   Success Rate: {performance['overall_score']:.1f}%")
        print(f"   Capabilities Demonstrated: {performance['capabilities_demonstrated']}")
        
        # Framework capabilities
        capabilities = demo_results['framework_capabilities']
        print(f"\n🚀 FRAMEWORK CAPABILITIES")
        
        basic_caps = [k.replace('_', ' ').title() for k, v in capabilities.items() 
                     if isinstance(v, bool) and v and k != 'integration']
        print(f"   Core: {', '.join(basic_caps)}")
        
        if capabilities.get('advanced_features'):
            print(f"   Advanced: {', '.join(capabilities['advanced_features'])}")
        
        print("\n" + "=" * 80)
        print("🎉 DEMONSTRATION COMPLETE")
        print("=" * 80)
        print()
        print("✅ AMPEL360-H₂-BWB-Q Framework Successfully Demonstrated!")
        print("   • Quantum-Enhanced Optimization ⚡")
        print("   • Component-Based Design 🏗️")
        print("   • Real-Time Digital Twin 🌐")
        print("   • Integrated Multi-Domain Workflow 🔄")
        print()
        print("🎯 Next-Generation Aerospace Framework Ready for Production!")
        
    else:
        print("❌ Insufficient components initialized for full demonstration")
        print("   Minimum 2 components required for integrated demo")
    
    # Shutdown
    framework.shutdown()
    print("\n👋 Framework demonstration complete!")


if __name__ == "__main__":
    # Run the demonstration
    asyncio.run(main())