"""Neuroimaging preprocessing module"""

import logging
from pathlib import Path
from typing import Optional, Dict, Any, Union
import numpy as np

logger = logging.getLogger(__name__)


class MRIPreprocessor:
    """Preprocessor for MRI data"""
    
    def __init__(self, config: Optional[Dict[str, Any]] = None):
        """
        Initialize MRI preprocessor
        
        Args:
            config: Preprocessing configuration
        """
        self.config = config or self._default_config()
        logger.info("Initialized MRI preprocessor")
    
    def _default_config(self) -> Dict[str, Any]:
        """Get default preprocessing configuration"""
        return {
            "normalize": True,
            "skull_strip": True,
            "registration_template": "MNI152",
            "resolution": [1, 1, 1],  # mm
        }
    
    def load(self, filepath: Union[str, Path]) -> np.ndarray:
        """
        Load MRI data from file
        
        Args:
            filepath: Path to MRI file (NIfTI format expected)
            
        Returns:
            Loaded MRI data as numpy array
        """
        # Placeholder implementation
        logger.info(f"Loading MRI from {filepath}")
        # TODO: Implement actual loading with nibabel
        return np.zeros((182, 218, 182))  # Standard MNI dimensions
    
    def preprocess(self, data: np.ndarray) -> np.ndarray:
        """
        Apply preprocessing pipeline
        
        Args:
            data: Raw MRI data
            
        Returns:
            Preprocessed MRI data
        """
        logger.info("Starting preprocessing pipeline")
        
        if self.config["normalize"]:
            data = self._normalize(data)
        
        if self.config["skull_strip"]:
            data = self._skull_strip(data)
        
        # TODO: Add more preprocessing steps
        
        logger.info("Preprocessing complete")
        return data
    
    def _normalize(self, data: np.ndarray) -> np.ndarray:
        """Normalize intensity values"""
        # Placeholder implementation
        logger.debug("Normalizing intensities")
        return data / (data.max() + 1e-8)
    
    def _skull_strip(self, data: np.ndarray) -> np.ndarray:
        """Remove skull from brain MRI"""
        # Placeholder implementation
        logger.debug("Performing skull stripping")
        return data
