"""Quantum microscopy algorithm implementation."""

import logging
from functools import lru_cache
from typing import Any, Dict, List, Optional, Tuple

import numpy as np
from qiskit import ClassicalRegister, QuantumCircuit, QuantumRegister
from qiskit.circuit.library import QFT
from qiskit.result import Result

from ..config import Config
from ..exceptions import QuantumCircuitError, ValidationError
from .base import BaseQuantumAlgorithm

logger = logging.getLogger(__name__)


class QuantumMicroscopy(BaseQuantumAlgorithm):
    """Quantum microscopy algorithm with enhanced capabilities."""

    def __init__(self, config: Config):
        """Initialize quantum microscopy algorithm."""
        super().__init__(config)
        self.resolution_cache: Dict[tuple, np.ndarray] = {}

    def validate_parameters(self, **kwargs) -> None:
        """Validate microscopy-specific parameters."""
        required_params = ["num_qubits", "target_function"]
        for param in required_params:
            if param not in kwargs:
                raise ValidationError(f"Missing required parameter: {param}")

        num_qubits = kwargs["num_qubits"]
        if not isinstance(num_qubits, int) or num_qubits <= 0:
            raise ValidationError("num_qubits must be a positive integer")

        if num_qubits > self.config.quantum.max_qubits:
            raise ValidationError(
                f"num_qubits exceeds maximum: {self.config.quantum.max_qubits}"
            )

    def build_circuit(self, **kwargs) -> QuantumCircuit:
        """Build quantum microscopy circuit."""
        try:
            # Validate and extract parameters
            self.validate_parameters(**kwargs)
            num_qubits = kwargs["num_qubits"]
            target_function = kwargs["target_function"]

            # Create quantum and classical registers
            qreg = QuantumRegister(num_qubits, "q")
            creg = ClassicalRegister(num_qubits, "c")
            circuit = QuantumCircuit(qreg, creg)

            # Initialize superposition
            circuit.h(qreg)

            # Apply target function oracle
            self._apply_oracle(circuit, qreg, target_function)

            # Apply Quantum Fourier Transform
            circuit.append(QFT(num_qubits), qreg)

            # Measure all qubits
            circuit.measure(qreg, creg)

            return circuit

        except (ValidationError, KeyError) as e:
            logger.error(f"Parameter error building quantum microscopy circuit: {e}")
            raise QuantumCircuitError(f"Failed to build circuit: {e}")
        except Exception as e:
            logger.error(f"Error building quantum microscopy circuit: {e}")
            raise QuantumCircuitError(f"Failed to build circuit: {e}")

    def _apply_oracle(
        self, circuit: QuantumCircuit, qreg: QuantumRegister, target_function: callable
    ) -> None:
        """Apply oracle function to the circuit."""
        # Implementation depends on the specific target function
        # This is a simplified example
        for i in range(len(qreg)):
            if target_function(i):
                circuit.z(qreg[i])

    @lru_cache(maxsize=100)
    def _compute_resolution_matrix(self, num_qubits: int, shots: int) -> np.ndarray:
        """Compute resolution matrix with caching."""
        # Simplified resolution matrix computation
        resolution = np.zeros((2**num_qubits, 2**num_qubits))
        for i in range(2**num_qubits):
            for j in range(2**num_qubits):
                resolution[i, j] = np.exp(-0.5 * (i - j) ** 2 / shots)
        return resolution

    def analyze_results(self, results: Result) -> Dict[str, Any]:
        """Analyze quantum microscopy results."""
        try:
            counts = results.get_counts()

            # Convert counts to probability distribution
            total_shots = sum(counts.values())
            probabilities = {
                state: count / total_shots for state, count in counts.items()
            }

            # Compute fidelity and other metrics
            analysis = {
                "counts": counts,
                "probabilities": probabilities,
                "total_shots": total_shots,
                "fidelity": self._compute_fidelity(probabilities),
                "entropy": self._compute_entropy(probabilities),
                "execution_time": results.time_taken,
            }

            return analysis

        except Exception as e:
            logger.error(f"Error analyzing results: {e}")
            raise QuantumCircuitError(f"Failed to analyze results: {e}")

    def _compute_fidelity(self, probabilities: Dict[str, float]) -> float:
        """Compute quantum state fidelity."""
        # Simplified fidelity calculation
        max_prob = max(probabilities.values()) if probabilities else 0
        return max_prob

    def _compute_entropy(self, probabilities: Dict[str, float]) -> float:
        """Compute von Neumann entropy."""
        entropy = 0
        for prob in probabilities.values():
            if prob > 0:
                entropy -= prob * np.log2(prob)
        return entropy

    def get_resolution_enhancement(self, **kwargs) -> float:
        """Calculate resolution enhancement factor."""
        num_qubits = kwargs.get("num_qubits", 1)
        classical_resolution = 1.0
        quantum_resolution = 1.0 / (2**num_qubits)
        return classical_resolution / quantum_resolution
