src/preprocessing/clinical_encoder.py

import pandas as pd
import numpy as np

class ClinicalEncoder:
    def __init__(self, continuous=None, categorical=None):
        self.continuous = continuous or []
        self.categorical = categorical or []
        self.preprocessor = None
        self.feature_dim = 0

    def transform(self, df):
        if self.preprocessor is None:
            # Fallback if preprocessor didn't load (shouldn't happen with pickle)
            return np.zeros((len(df), self.feature_dim))
        
        # Ensure input is DataFrame
        if not isinstance(df, pd.DataFrame):
            df = pd.DataFrame([df])
            
        return self.preprocessor.transform(df)