"""
Simple evaluation functions for BioBatchNet
Note: Full evaluation requires scib package (optional dependency)
"""
import numpy as np

def evaluate_nn(adata_dict, fraction=1.0, seed=42):
    """
    Simplified evaluation function for neural network methods.
    For full evaluation metrics, install scib package.
    
    Args:
        adata_dict: Dictionary of AnnData objects with method names as keys
        fraction: Fraction of data to use for evaluation
        seed: Random seed for subsampling
        
    Returns:
        Dictionary with evaluation results (placeholder in this version)
    """
    results = {}
    
    # This is a simplified version without scib dependency
    # Returns basic metrics that can be computed without additional packages
    
    for key, adata in adata_dict.items():
        # Basic evaluation placeholder
        results[key] = {
            'processed': True,
            'n_cells': adata.shape[0],
            'n_features': adata.shape[1],
            'note': 'Full metrics require scib package'
        }
        
        # If BioBatchNet, check if embedding exists
        if key == 'BioBatchNet' and 'X_biobatchnet' in adata.obsm:
            results[key]['embedding_dim'] = adata.obsm['X_biobatchnet'].shape[1]
    
    return results