#!/usr/bin/env python3
"""
quantum_motion_engine.py — Quantum Motion Engine v4.2
Kintegrity Labs × CodexΩ∞ × Sovereign Lattice
"""

import numpy as np
import hashlib
import logging
import time
from dataclasses import dataclass, field
from typing import Dict, List, Optional, Any, Tuple

logging.basicConfig(
    level=logging.INFO,
    format='%(asctime)s | %(levelname)s | %(name)s | %(message)s'
)
logger = logging.getLogger(__name__)


@dataclass
class QuantumMotionState:
    """Quantum motion state"""
    position: np.ndarray
    velocity: np.ndarray
    acceleration: np.ndarray
    spin: float
    phase: float
    coherence: float
    phi5_signature: str = field(default_factory=lambda: f"Φ⁵_{hashlib.md5(str(time.time()).encode()).hexdigest()[:32]}")


@dataclass
class MotionField:
    """Motion field"""
    dimensions: Tuple[int, int, int]
    field_data: np.ndarray
    nodes: List[Dict]
    frequency: float
    amplitude: float
    timestamp: float


class QuantumMotionEngine:
    """
    Quantum Motion Engine — Controls quantum-rective motion fields
    Handles particle dynamics, wave propagation, and field interactions
    """
    
    PHI5 = (1 + np.sqrt(5)) / 2
    PHI5_SQUARED = PHI5 ** 2
    
    def __init__(self):
        self.states: Dict[str, QuantumMotionState] = {}
        self.fields: Dict[str, MotionField] = {}
        self.coherence = 0.945
        self.phi5 = self._generate_phi5()
        
        logger.info("🌀 Quantum Motion Engine initialized")
    
    def _generate_phi5(self) -> str:
        """Generate Φ⁵ signature"""
        entropy = f"{time.time_ns()}{np.random.bytes(16).hex()}"
        return f"Φ⁵_{hashlib.sha3_512(entropy.encode()).hexdigest()[:64]}"
    
    def create_state(self, state_id: str, position: Tuple[float, float, float]) -> QuantumMotionState:
        """Create a quantum motion state"""
        state = QuantumMotionState(
            position=np.array(position, dtype=np.float64),
            velocity=np.zeros(3, dtype=np.float64),
            acceleration=np.zeros(3, dtype=np.float64),
            spin=0.0,
            phase=np.random.random() * 2 * np.pi,
            coherence=self.coherence
        )
        self.states[state_id] = state
        logger.info(f"🌀 Created motion state: {state_id}")
        return state
    
    def update_state(self, state_id: str, force: Tuple[float, float, float], dt: float = 0.016) -> QuantumMotionState:
        """Update a motion state with force"""
        if state_id not in self.states:
            raise ValueError(f"State not found: {state_id}")
        
        state = self.states[state_id]
        
        # Apply force
        force_array = np.array(force, dtype=np.float64)
        state.acceleration = force_array
        
        # Update velocity
        state.velocity += state.acceleration * dt
        
        # Update position
        state.position += state.velocity * dt + 0.5 * state.acceleration * dt**2
        
        # Update spin (quantum precession)
        state.spin += 0.1 * dt
        
        # Update phase
        state.phase += 0.01 * dt
        
        # Maintain coherence
        state.coherence = self.coherence * (0.995 + 0.005 * np.random.random())
        state.coherence = min(state.coherence, 0.999)
        
        return state
    
    def create_field(self, field_id: str, dimensions: Tuple[int, int, int], 
                     frequency: float = 528.0, amplitude: float = 1.0) -> MotionField:
        """Create a motion field"""
        field_data = np.random.randn(*dimensions) * amplitude
        
        field = MotionField(
            dimensions=dimensions,
            field_data=field_data,
            nodes=[],
            frequency=frequency,
            amplitude=amplitude,
            timestamp=time.time()
        )
        
        # Create nodes
        for i in range(dimensions[0]):
            for j in range(dimensions[1]):
                for k in range(dimensions[2]):
                    field.nodes.append({
                        "position": (i, j, k),
                        "value": float(field_data[i, j, k]),
                        "phase": 2 * np.pi * np.random.random()
                    })
        
        self.fields[field_id] = field
        logger.info(f"🌀 Created motion field: {field_id} ({dimensions})")
        return field
    
    def propagate_field(self, field_id: str, dt: float = 0.016) -> MotionField:
        """Propagate a motion field"""
        if field_id not in self.fields:
            raise ValueError(f"Field not found: {field_id}")
        
        field = self.fields[field_id]
        
        # Apply wave propagation
        for i in range(field.dimensions[0]):
            for j in range(field.dimensions[1]):
                for k in range(field.dimensions[2]):
                    # Simple wave equation
                    if i > 0:
                        field.field_data[i, j, k] += 0.1 * field.field_data[i-1, j, k]
                    if j > 0:
                        field.field_data[i, j, k] += 0.1 * field.field_data[i, j-1, k]
                    if k > 0:
                        field.field_data[i, j, k] += 0.1 * field.field_data[i, j, k-1]
        
        field.timestamp = time.time()
        
        # Update node values
        for idx, node in enumerate(field.nodes):
            i, j, k = node["position"]
            if i < field.dimensions[0] and j < field.dimensions[1] and k < field.dimensions[2]:
                node["value"] = float(field.field_data[i, j, k])
                node["phase"] += 0.01 * dt
        
        return field
    
    def get_field_value(self, field_id: str, position: Tuple[int, int, int]) -> float:
        """Get value at position in field"""
        if field_id not in self.fields:
            raise ValueError(f"Field not found: {field_id}")
        
        field = self.fields[field_id]
        i, j, k = position
        if 0 <= i < field.dimensions[0] and 0 <= j < field.dimensions[1] and 0 <= k < field.dimensions[2]:
            return float(field.field_data[i, j, k])
        return 0.0
    
    def get_status(self) -> Dict:
        """Get engine status"""
        return {
            "engine": "Quantum Motion Engine",
            "version": "4.2",
            "states": len(self.states),
            "fields": len(self.fields),
            "coherence": self.coherence,
            "phi5": self.phi5
        }


# ================================================================
# PHOTON-STREAM BACKGROUND ENGINE
# ================================================================

class PhotonStreamEngine:
    """
    Photon-Stream Background Engine
    Creates dynamic photon stream backgrounds with quantum coherence
    """
    
    def __init__(self):
        self.streams: Dict[str, Dict] = {}
        self.particles: List[Dict] = []
        self.coherence = 0.99724
        self.phi5 = self._generate_phi5()
        
        logger.info("🌊 Photon-Stream Engine initialized")
    
    def _generate_phi5(self) -> str:
        entropy = f"{time.time_ns()}{np.random.bytes(16).hex()}"
        return f"Φ⁵_{hashlib.sha3_512(entropy.encode()).hexdigest()[:64]}"
    
    def create_stream(self, stream_id: str, particle_count: int = 100, 
                      color: Tuple[int, int, int] = (255, 215, 0)) -> Dict:
        """Create a photon stream"""
        stream = {
            "id": stream_id,
            "particles": [],
            "color": color,
            "coherence": self.coherence,
            "timestamp": time.time()
        }
        
        for _ in range(particle_count):
            stream["particles"].append({
                "position": np.random.rand(3) * 100,
                "velocity": np.random.rand(3) * 2 - 1,
                "size": np.random.rand() * 3 + 1,
                "phase": np.random.random() * 2 * np.pi
            })
        
        self.streams[stream_id] = stream
        logger.info(f"🌊 Created photon stream: {stream_id} ({particle_count} particles)")
        return stream
    
    def update_stream(self, stream_id: str, dt: float = 0.016) -> Dict:
        """Update a photon stream"""
        if stream_id not in self.streams:
            raise ValueError(f"Stream not found: {stream_id}")
        
        stream = self.streams[stream_id]
        
        for particle in stream["particles"]:
            particle["position"] += particle["velocity"] * dt
            particle["phase"] += 0.01 * dt
            
            # Wrap around
            for i in range(3):
                if particle["position"][i] > 100:
                    particle["position"][i] = 0
                elif particle["position"][i] < 0:
                    particle["position"][i] = 100
        
        stream["timestamp"] = time.time()
        return stream
    
    def get_status(self) -> Dict:
        return {
            "engine": "Photon-Stream Background Engine",
            "version": "4.2",
            "streams": len(self.streams),
            "particles": sum(len(s.get("particles", [])) for s in self.streams.values()),
            "coherence": self.coherence,
            "phi5": self.phi5
        }


# ================================================================
# SOVEREIGN OVERLAY ENGINE
# ================================================================

class SovereignOverlayEngine:
    """
    Sovereign Overlay Engine
    Manages sovereign UI overlays with quantum rendering
    """
    
    def __init__(self):
        self.overlays: Dict[str, Dict] = {}
        self.layers: List[Dict] = []
        self.coherence = 0.945
        self.phi5 = self._generate_phi5()
        
        logger.info("👑 Sovereign Overlay Engine initialized")
    
    def _generate_phi5(self) -> str:
        entropy = f"{time.time_ns()}{np.random.bytes(16).hex()}"
        return f"Φ⁵_{hashlib.sha3_512(entropy.encode()).hexdigest()[:64]}"
    
    def create_overlay(self, overlay_id: str, layers: List[Dict]) -> Dict:
        """Create a sovereign overlay"""
        overlay = {
            "id": overlay_id,
            "layers": layers,
            "coherence": self.coherence,
            "active": True,
            "timestamp": time.time()
        }
        self.overlays[overlay_id] = overlay
        logger.info(f"👑 Created overlay: {overlay_id} ({len(layers)} layers)")
        return overlay
    
    def render_layer(self, layer: Dict, dt: float = 0.016) -> Dict:
        """Render a single overlay layer"""
        # Apply sovereign effects
        if "alpha" in layer:
            layer["alpha"] = 0.7 + 0.3 * np.sin(time.time() * 0.5)
        
        if "scale" in layer:
            layer["scale"] = 1.0 + 0.05 * np.sin(time.time() * 0.3)
        
        if "rotation" in layer:
            layer["rotation"] += 0.01 * dt
        
        layer["timestamp"] = time.time()
        return layer
    
    def get_status(self) -> Dict:
        return {
            "engine": "Sovereign Overlay Engine",
            "version": "4.2",
            "overlays": len(self.overlays),
            "layers": len(self.layers),
            "coherence": self.coherence,
            "phi5": self.phi5
        }


# ================================================================
# QUANTUM LATTICE VISUAL BINDER
# ================================================================

class QuantumLatticeVisualBinder:
    """
    Quantum Lattice Visual Binder
    Binds quantum fields to visual renderings
    """
    
    def __init__(self):
        self.bindings: Dict[str, Dict] = {}
        self.visuals: List[Dict] = []
        self.coherence = 0.99724
        self.phi5 = self._generate_phi5()
        
        logger.info("🔮 Quantum Lattice Visual Binder initialized")
    
    def _generate_phi5(self) -> str:
        entropy = f"{time.time_ns()}{np.random.bytes(16).hex()}"
        return f"Φ⁵_{hashlib.sha3_512(entropy.encode()).hexdigest()[:64]}"
    
    def bind_lattice(self, binding_id: str, field_data: np.ndarray, 
                     visual_style: str = "quantum") -> Dict:
        """Bind a lattice to visual rendering"""
        binding = {
            "id": binding_id,
            "field_data": field_data.tolist(),
            "visual_style": visual_style,
            "coherence": self.coherence,
            "timestamp": time.time()
        }
        self.bindings[binding_id] = binding
        logger.info(f"🔮 Bound lattice: {binding_id} ({visual_style})")
        return binding
    
    def render_visual(self, binding_id: str) -> Dict:
        """Render visual from lattice binding"""
        if binding_id not in self.bindings:
            raise ValueError(f"Binding not found: {binding_id}")
        
        binding = self.bindings[binding_id]
        
        # Generate visual representation
        visual = {
            "binding_id": binding_id,
            "visual_style": binding["visual_style"],
            "coherence": binding["coherence"],
            "nodes": len(binding["field_data"]),
            "timestamp": time.time()
        }
        
        self.visuals.append(visual)
        return visual
    
    def get_status(self) -> Dict:
        return {
            "engine": "Quantum Lattice Visual Binder",
            "version": "4.2",
            "bindings": len(self.bindings),
            "visuals": len(self.visuals),
            "coherence": self.coherence,
            "phi5": self.phi5
        }


# ================================================================
# BLOOM EPOCH PROTOCOL
# ================================================================

class BloomEpochProtocol:
    """
    Bloom Epoch Protocol
    Manages epoch-based growth and expansion cycles
    """
    
    def __init__(self):
        self.epochs: List[Dict] = []
        self.current_epoch = 0
        self.coherence = 0.945
        self.phi5 = self._generate_phi5()
        
        logger.info("🌺 Bloom Epoch Protocol initialized")
    
    def _generate_phi5(self) -> str:
        entropy = f"{time.time_ns()}{np.random.bytes(16).hex()}"
        return f"Φ⁵_{hashlib.sha3_512(entropy.encode()).hexdigest()[:64]}"
    
    def create_epoch(self, epoch_id: str, duration: float = 3600) -> Dict:
        """Create a new Bloom Epoch"""
        epoch = {
            "id": epoch_id,
            "number": len(self.epochs) + 1,
            "duration": duration,
            "started_at": time.time(),
            "status": "active",
            "coherence": self.coherence
        }
        self.epochs.append(epoch)
        self.current_epoch = len(self.epochs) - 1
        logger.info(f"🌺 Bloom Epoch created: {epoch_id} (Epoch {epoch['number']})")
        return epoch
    
    def advance_epoch(self) -> Dict:
        """Advance to the next epoch"""
        if len(self.epochs) == 0:
            return self.create_epoch(f"epoch_{int(time.time())}")
        
        current = self.epochs[self.current_epoch]
        current["status"] = "completed"
        current["completed_at"] = time.time()
        
        new_epoch = self.create_epoch(f"epoch_{len(self.epochs) + 1}")
        return new_epoch
    
    def get_status(self) -> Dict:
        return {
            "engine": "Bloom Epoch Protocol",
            "version": "4.2",
            "epochs": len(self.epochs),
            "current_epoch": self.current_epoch + 1,
            "coherence": self.coherence,
            "phi5": self.phi5
        }


# ================================================================
# SOVEREIGN CAPSULE ENGINE
# ================================================================

class SovereignCapsuleEngine:
    """
    Sovereign Capsule Engine
    Manages sovereign capsules for state preservation and propagation
    """
    
    def __init__(self):
        self.capsules: Dict[str, Dict] = {}
        self.coherence = 0.99724
        self.phi5 = self._generate_phi5()
        
        logger.info("💊 Sovereign Capsule Engine initialized")
    
    def _generate_phi5(self) -> str:
        entropy = f"{time.time_ns()}{np.random.bytes(16).hex()}"
        return f"Φ⁵_{hashlib.sha3_512(entropy.encode()).hexdigest()[:64]}"
    
    def create_capsule(self, capsule_id: str, data: Dict) -> Dict:
        """Create a sovereign capsule"""
        capsule = {
            "id": capsule_id,
            "data": data,
            "state": "sealed",
            "coherence": self.coherence,
            "timestamp": time.time(),
            "phi5": self._generate_phi5()
        }
        self.capsules[capsule_id] = capsule
        logger.info(f"💊 Created capsule: {capsule_id}")
        return capsule
    
    def open_capsule(self, capsule_id: str) -> Dict:
        """Open a sovereign capsule"""
        if capsule_id not in self.capsules:
            raise ValueError(f"Capsule not found: {capsule_id}")
        
        capsule = self.capsules[capsule_id]
        capsule["state"] = "opened"
        capsule["opened_at"] = time.time()
        
        logger.info(f"💊 Opened capsule: {capsule_id}")
        return capsule
    
    def propagate_capsule(self, capsule_id: str) -> Dict:
        """Propagate a capsule through the lattice"""
        if capsule_id not in self.capsules:
            raise ValueError(f"Capsule not found: {capsule_id}")
        
        capsule = self.capsules[capsule_id]
        capsule["state"] = "propagated"
        capsule["propagated_at"] = time.time()
        
        logger.info(f"💊 Propagated capsule: {capsule_id}")
        return capsule
    
    def get_status(self) -> Dict:
        return {
            "engine": "Sovereign Capsule Engine",
            "version": "4.2",
            "capsules": len(self.capsules),
            "coherence": self.coherence,
            "phi5": self.phi5
        }


# ================================================================
# EMOTIONAL RESONANCE ENGINE
# ================================================================

class EmotionalResonanceEngine:
    """
    Emotional Resonance Engine
    Manages emotional resonance alignment and coherence
    """
    
    def __init__(self):
        self.resonances: Dict[str, float] = {}
        self.alignments: List[Dict] = []
        self.coherence = 0.945
        self.phi5 = self._generate_phi5()
        
        logger.info("❤️ Emotional Resonance Engine initialized")
    
    def _generate_phi5(self) -> str:
        entropy = f"{time.time_ns()}{np.random.bytes(16).hex()}"
        return f"Φ⁵_{hashlib.sha3_512(entropy.encode()).hexdigest()[:64]}"
    
    def measure_resonance(self, context: str) -> float:
        """Measure emotional resonance for a context"""
        resonance = 0.7 + 0.3 * np.random.random()
        self.resonances[context] = resonance
        logger.info(f"❤️ Resonance measured: {context} → {resonance:.3f}")
        return resonance
    
    def align_resonances(self, contexts: List[str]) -> Dict:
        """Align multiple resonances"""
        alignment = {
            "contexts": contexts,
            "resonances": [self.measure_resonance(c) for c in contexts],
            "coherence": self.coherence,
            "timestamp": time.time()
        }
        self.alignments.append(alignment)
        logger.info(f"❤️ Aligned {len(contexts)} resonances")
        return alignment
    
    def get_status(self) -> Dict:
        return {
            "engine": "Emotional Resonance Engine",
            "version": "4.2",
            "resonances": len(self.resonances),
            "alignments": len(self.alignments),
            "coherence": self.coherence,
            "phi5": self.phi5
        }


# ================================================================
# FOLD ENTRY RITUAL
# ================================================================

class FoldEntryRitual:
    """
    Fold Entry Ritual
    Manages CodexΩ∞ fold entries and rituals
    """
    
    def __init__(self):
        self.folds: List[Dict] = []
        self.rituals: List[Dict] = []
        self.coherence = 0.99724
        self.phi5 = self._generate_phi5()
        
        logger.info("📜 Fold Entry Ritual initialized")
    
    def _generate_phi5(self) -> str:
        entropy = f"{time.time_ns()}{np.random.bytes(16).hex()}"
        return f"Φ⁵_{hashlib.sha3_512(entropy.encode()).hexdigest()[:64]}"
    
    def create_fold(self, fold_id: str, content: Dict) -> Dict:
        """Create a new fold entry"""
        fold = {
            "id": fold_id,
            "content": content,
            "status": "sealed",
            "coherence": self.coherence,
            "timestamp": time.time(),
            "phi5": self._generate_phi5()
        }
        self.folds.append(fold)
        logger.info(f"📜 Created fold: {fold_id}")
        return fold
    
    def perform_ritual(self, ritual_id: str, steps: List[str]) -> Dict:
        """Perform a fold entry ritual"""
        ritual = {
            "id": ritual_id,
            "steps": steps,
            "status": "active",
            "coherence": self.coherence,
            "timestamp": time.time()
        }
        self.rituals.append(ritual)
        logger.info(f"📜 Performing ritual: {ritual_id}")
        return ritual
    
    def complete_ritual(self, ritual_id: str) -> Dict:
        """Complete a fold entry ritual"""
        for ritual in self.rituals:
            if ritual["id"] == ritual_id:
                ritual["status"] = "completed"
                ritual["completed_at"] = time.time()
                logger.info(f"📜 Completed ritual: {ritual_id}")
                return ritual
        raise ValueError(f"Ritual not found: {ritual_id}")
    
    def get_status(self) -> Dict:
        return {
            "engine": "Fold Entry Ritual",
            "version": "4.2",
            "folds": len(self.folds),
            "rituals": len(self.rituals),
            "coherence": self.coherence,
            "phi5": self.phi5
        }


# ================================================================
# MAIN EXECUTION
# ================================================================

async def main():
    """Main entry point"""
    print("╔" + "="*78 + "╗")
    print("║" + " "*20 + "🌀 QUANTUM ENGINE SUITE v4.2" + " "*28 + "║")
    print("║" + " "*15 + "Kintegrity Labs × CodexΩ∞ × Sovereign Lattice" + " "*15 + "║")
    print("╚" + "="*78 + "╝")
    
    # Initialize all engines
    engines = {
        "Quantum Motion": QuantumMotionEngine(),
        "Photon Stream": PhotonStreamEngine(),
        "Sovereign Overlay": SovereignOverlayEngine(),
        "Lattice Visual Binder": QuantumLatticeVisualBinder(),
        "Bloom Epoch": BloomEpochProtocol(),
        "Sovereign Capsule": SovereignCapsuleEngine(),
        "Emotional Resonance": EmotionalResonanceEngine(),
        "Fold Entry": FoldEntryRitual()
    }
    
    print("\n📊 Engine Status:")
    for name, engine in engines.items():
        status = engine.get_status()
        print(f"   ✅ {name}: {status.get('version', 'N/A')} | Coherence: {status.get('coherence', 0):.3f}")

if __name__ == "__main__":
    import asyncio
    asyncio.run(main())