import asyncio
import random
from typing import Dict, List, Any
import logging

class BCIConnector:
    """
    Connecteur pour interfaces cerveau-machine
    Simulation de lecture et d'interprétation de signaux cérébraux
    """
    
    def __init__(self):
        self.logger = logging.getLogger("bci_connector")
        self.signal_quality = 0.0
        self.mental_states = {}
        self.brain_patterns = {}
        
    async def initialize(self):
        """Initialise l'interface BCI"""
        self.logger.info("🧠 Initialisation de l'interface cerveau-machine...")
        
        try:
            await self._calibrate_sensors()
            await self._setup_pattern_recognition()
            
            self.signal_quality = 0.85
            self.logger.info("✅ Interface BCI initialisée")
            return True
            
        except Exception as e:
            self.logger.error(f"❌ Erreur d'initialisation BCI: {e}")
            return False
    
    async def read_brain_signals(self) -> Dict[str, Any]:
        """Lit les signaux cérébraux en temps réel"""
        try:
            # Simulation de signaux cérébraux
            signals = {
                "eeg": {
                    "delta": random.uniform(0.1, 0.5),
                    "theta": random.uniform(0.1, 0.4),
                    "alpha": random.uniform(0.1, 0.6),
                    "beta": random.uniform(0.1, 0.8),
                    "gamma": random.uniform(0.1, 0.3)
                },
                "focus_level": random.uniform(0.3, 0.9),
                "mental_workload": random.uniform(0.2, 0.8),
                "emotional_state": random.choice(["calme", "concentré", "créatif", "attentif"]),
                "signal_quality": self.signal_quality
            }
            
            return signals
            
        except Exception as e:
            self.logger.error(f"Erreur de lecture BCI: {e}")
            return {"error": str(e)}
    
    async def detect_mental_commands(self) -> List[Dict[str, Any]]:
        """Détecte les commandes mentales"""
        commands = [
            {"type": "focus", "intensity": random.uniform(0.5, 0.95), "confidence": 0.8},
            {"type": "imagine", "content": "mouvement", "confidence": 0.7},
            {"type": "emotion", "value": random.choice(["positive", "negative", "neutral"]), "confidence": 0.6}
        ]
        
        return random.sample(commands, random.randint(1, 3))
    
    async def send_neuro_feedback(self, feedback: Dict[str, Any]) -> bool:
        """Envoie un feedback neuro-cognitif"""
        self.logger.info(f"📤 Envoi de feedback neuro: {feedback.get('type', 'inconnu')}")
        return True
    
    async def _calibrate_sensors(self):
        """Calibre les capteurs BCI"""
        self.logger.info("🎯 Calibration des capteurs cérébraux...")
        await asyncio.sleep(0.8)
        
        self.signal_quality = random.uniform(0.7, 0.95)
        self.logger.info(f"📊 Qualité du signal: {self.signal_quality:.3f}")
    
    async def _setup_pattern_recognition(self):
        """Configure la reconnaissance de patterns cérébraux"""
        self.brain_patterns = {
            "focus_patterns": ["concentration_intense", "attention_soutenue"],
            "creative_patterns": ["pensee_laterale", "association_libre"],
            "relaxation_patterns": ["meditation", "detente_profonde"]
        }