"""
Multi-Objective Optimization Pipeline for AbirQu
Copyright 2026 Abir Maheshwari

Pipeline for optimizing multiple objectives (depth, gates, error).
"""
from typing import List, Dict, Callable, Tuple, Any
from abirqu.circuit import Circuit

class MultiObjectivePipeline:
    """Pipeline for optimizing multiple objectives (depth, gates, error)."""
    
    def __init__(self):
        self.objectives: List[Tuple[str, Callable, float]] = []  # (name, func, weight)
        self.weights: Dict[str, float] = {}
        self.history: List[Dict] = []
        
    def add_objective(self, name: str, func: Callable[[Circuit], float], weight: float = 1.0):
        """Add an optimization objective."""
        self.objectives.append((name, func, weight))
        self.weights[name] = weight
        
    def optimize(self, circuit: Circuit) -> 'PipelineResult':
        """Run multi-objective optimization."""
        # Evaluate current circuit
        scores = self._evaluate(circuit)
        initial_score = self._weighted_score(scores)
        
        # Apply optimizations (simplified - would use proper optimization algorithm)
        optimized = self._optimize_circuit(circuit)
        
        # Evaluate optimized circuit
        final_scores = self._evaluate(optimized)
        final_score = self._weighted_score(final_scores)
        
        # Record in history
        self.history.append({
            'initial': scores,
            'final': final_scores,
            'improvement': final_score - initial_score
        })
        
        return PipelineResult(circuit, optimized, self.objectives, self.history[-1])
        
    def _evaluate(self, circuit: Circuit) -> Dict[str, float]:
        """Evaluate circuit on all objectives."""
        scores = {}
        for name, func, weight in self.objectives:
            try:
                scores[name] = func(circuit)
            except:
                scores[name] = 0.0
        return scores
        
    def _weighted_score(self, scores: Dict[str, float]) -> float:
        """Calculate weighted score."""
        total = 0.0
        total_weight = 0.0
        for name, func, weight in self.objectives:
            if name in scores:
                total += scores[name] * weight
                total_weight += weight
        return total / max(total_weight, 1.0)
        
    def _optimize_circuit(self, circuit: Circuit) -> Circuit:
        """Apply optimization passes using CircuitSimplifier."""
        from abirqu.optimize.circuit_simplifier import CircuitSimplifier
        simplifier = CircuitSimplifier()
        return simplifier.optimize(circuit)
        
    def get_score(self, circuit: Circuit) -> float:
        """Calculate weighted objective score."""
        scores = self._evaluate(circuit)
        return self._weighted_score(scores)
        
    def get_pareto_front(self, circuits: List[Circuit]) -> List[Circuit]:
        """Get Pareto-optimal circuits."""
        # Simplified: return all circuits
        return circuits
        
    def clear_history(self):
        self.history = []

class PipelineResult:
    def __init__(self, original: Circuit, optimized: Circuit, 
                 objectives: List[Tuple], history_entry: Dict):
        self.original = original
        self.optimized = optimized
        self.objectives = objectives
        self.scores = history_entry
        
    def __repr__(self):
        return f"PipelineResult(original={len(self.original.gates)} gates, optimized={len(self.optimized.gates)} gates)"
