import numpy as np
from typing import Optional, Dict, Any, List
from quantum_topology import ChernSimonsTopology
from quantum_gates import QuantumGate

class QuantumCircuit:
    def __init__(self, topology: ChernSimonsTopology):
        self.topology = topology
        self.gates: List[QuantumGate] = []
        self.initialize_gates()
        
    def initialize_gates(self):
        """Initialize quantum gates based on topology"""
        self.gates = [
            QuantumGate("H"),
            QuantumGate("CNOT"),
            QuantumGate("Phase"),
            QuantumGate("X"),
            QuantumGate("Z")
        ]
        
    def prepare_input(self, data: str) -> np.ndarray:
        """Convert classical input to quantum state"""
        state = np.zeros(self.topology.dimension, dtype=np.complex128)
        state[0] = 1.0  # Initialize to |0...0⟩
        
        for i, char in enumerate(data):
            if i >= self.topology.depth:
                break
            if ord(char) % 2:
                h_gate = QuantumGate("H")
                state = h_gate.apply(state, self.topology)
        
        state /= np.sqrt(np.sum(np.abs(state) ** 2))
        return state
        
    def evolve(
        self,
        state: np.ndarray,
        params: Optional[Dict[str, Any]] = None
    ) -> np.ndarray:
        current_state = state.copy()
        
        if params and "gates" in params:
            for gate_name in params["gates"]:
                gate = QuantumGate(gate_name)
                current_state = gate.apply(current_state, self.topology)
        else:
            for gate in self.gates:
                current_state = gate.apply(current_state, self.topology)
                
        for i in range(self.topology.depth - 1):
            for j in range(i + 1, self.topology.depth):
                braiding = self.topology.calculate_braiding(i, j)
                current_state = np.dot(current_state.reshape(-1, 4), braiding.T).flatten()
        
        current_state /= np.sqrt(np.sum(np.abs(current_state) ** 2))
        return current_state