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quantum_motion_engine.py

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+#!/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())