"""
Module: quantum_simulation.py
This module contains functions for quantum simulation logic extracted from qio_module.py.

Extensive Notation:
- Placeholder function simulate_quantum_system uses minimal logic to simulate a quantum system.
- Future updates will include detailed simulation algorithms and parameter validation.
"""

from qiskit import QuantumCircuit, transpile
from qiskit_aer import AerSimulator
from qiskit_ibm_runtime import QiskitRuntimeService, Sampler, Options, Session
from qiskit.circuit.library import RealAmplitudes, EfficientSU2
from qiskit_aer.primitives import Sampler as LocalSampler
import logging
import numpy as np
from typing import Dict, List, Optional, Union, Tuple
from qiskit.circuit.library import QFT

logger = logging.getLogger(__name__)

def create_bell_state():
    """
    Creates a Bell state quantum circuit.
    
    Returns:
        QuantumCircuit: Quantum circuit representing the Bell state.
    """
    # Create a quantum circuit with 2 qubits and 2 classical bits for measurement
    qc = QuantumCircuit(2, 2)
    
    # Apply Hadamard gate to the first qubit to create superposition
    qc.h(0)
    
    # Apply CNOT gate with control qubit 0 and target qubit 1 to entangle qubits
    qc.cx(0, 1)
    
    # Measure both qubits to collapse the state
    qc.measure([0, 1], [0, 1])
    
    return qc

def run_circuit(circuit, shots=1000):
    """
    Run a quantum circuit using Qiskit 2.0 compatible API.
    
    Args:
        circuit (QuantumCircuit): The quantum circuit to run
        shots (int): Number of shots for the simulation
        
    Returns:
        dict: Counts of measurement outcomes
    """
    try:
        # Use Aer's simulator backend with Qiskit 2.0 API
        simulator = AerSimulator()
        
        # Execute the circuit with the new API
        job = simulator.run(circuit, shots=shots)
        
        # Get the result
        result = job.result()
        
        # Get the counts
        counts = result.get_counts(circuit)
        
        return counts
    except Exception as e:
        logger.error(f"Error running quantum circuit: {str(e)}")
        raise

def quantum_fourier_transform(n_qubits):
    """
    Creates a Quantum Fourier Transform circuit.
    
    Args:
        n_qubits (int): Number of qubits for the QFT
        
    Returns:
        QuantumCircuit: QFT circuit
    """
    qc = QuantumCircuit(n_qubits)
    
    # Implement QFT
    for i in range(n_qubits):
        qc.h(i)
        for j in range(i+1, n_qubits):
            qc.cp(2*3.14159265359/2**(j-i), j, i)
    
    # Swap qubits
    for i in range(n_qubits//2):
        qc.swap(i, n_qubits-i-1)
        
    return qc

def run_qft_simulation(n_qubits, shots=1000):
    """
    Executes a Quantum Fourier Transform (QFT) simulation.
    
    Args:
        n_qubits (int): Number of qubits in the QFT circuit.
        shots (int): Number of simulation runs.
    
    Returns:
        dict: Measurement counts from the QFT simulation.
    """
    qft_circuit = quantum_fourier_transform(n_qubits)
    
    # Add measurement to all qubits to observe the QFT output
    qft_circuit.measure_all()
    
    # Run the circuit with the updated API
    return run_circuit(qft_circuit, shots=shots)

def simulate_quantum_system(params):
    """Simulate a quantum system using provided parameters.
    
    Parameters:
        params (dict): Dictionary of simulation parameters.
        
    Returns:
        dict: Simulation result containing a status and the input parameters.
    """
    # TODO: Implement advanced quantum simulation logic
    return {"result": "Quantum simulation complete", "params": params}

def build_quantum_circuit(num_qubits: int, num_layers: int, rotation_params: list, entanglement_fn=None):
    """
    Stub function to simulate building a quantum circuit.

    :param num_qubits: Number of qubits to use in the circuit.
    :param num_layers: Number of layers in the circuit.
    :param rotation_params: List of rotation parameters for the circuit's gates.
    :param entanglement_fn: Function to generate entanglement between qubits.
    :return: A dummy representation of a quantum circuit (e.g., a dictionary).
    """
    # Consolidated dynamic circuit generator - delegate to the implementation in src/dynamic_circuit.py
    from src import dynamic_circuit
    return dynamic_circuit.build_quantum_circuit(num_qubits, num_layers, rotation_params, entanglement_fn)

class QuantumSimulator:
    """Quantum simulator for financial time series modeling"""
    
    def __init__(self, qubits: int = 4, shots: int = 1024, backend_name: Optional[str] = None):
        """
        Initialize the quantum simulator
        
        Args:
            qubits: Number of qubits to use in simulation
            shots: Number of measurement shots
            backend_name: Optional IBM Quantum backend name
        """
        self.qubits = qubits
        self.shots = shots
        self.backend_name = backend_name
        
        # Initialize sampler based on whether we're using IBM Quantum or local
        if backend_name:
            try:
                self.service = QiskitRuntimeService()
                options = {"backend_name": backend_name}
                self.sampler = Sampler(options=options)
            except Exception as e:
                print(f"Error initializing IBM Quantum backend: {str(e)}")
                print("Falling back to local simulator")
                self.sampler = LocalSampler()
        else:
            # Use local simulator
            self.sampler = LocalSampler()
    
    def execute_circuit(self, circuit: QuantumCircuit) -> Dict[str, int]:
        """
        Execute a quantum circuit and return measurement results
        
        Args:
            circuit: The quantum circuit to execute
            
        Returns:
            Measurement results as counts
        """
        try:
            # Ensure circuit has measurements
            if not circuit.num_clbits:
                circuit.measure_all()
                
            # Execute the circuit
            job = self.sampler.run([circuit], shots=self.shots)
            result = job.result()
            
            # Process results based on primitive type
            if hasattr(result, 'quasi_dists'):
                # V2 primitive results
                quasi_dists = result.quasi_dists
                counts = {}
                for bitstring, prob in quasi_dists[0].items():
                    bin_str = format(bitstring, f'0{circuit.num_qubits}b')
                    counts[bin_str] = int(prob * self.shots)
                return counts
            else:
                # V1 primitive results (only for backward compatibility)
                counts = result[0].data.meas.get_counts()
                return counts
        except Exception as e:
            print(f"Circuit execution error: {str(e)}")
            print("Using fallback execution method")
            # Fallback to V1 primitive if available
            return self._fallback_execution(circuit)
    
    def _fallback_execution(self, circuit: QuantumCircuit) -> Dict[str, int]:
        """Fallback execution method using local simulator"""
        from qiskit import Aer
        backend = Aer.get_backend('aer_simulator')
        result = backend.run(circuit, shots=self.shots).result()
        return result.get_counts() 