import logging
import numpy as np

# Configure logging
logging.basicConfig(
    level=logging.INFO,
    format="%(asctime)s [%(levelname)s] %(name)s - %(message)s",
)
logger = logging.getLogger(__name__)


def post_processing(df):

    try:
        df['hd_score_m1'] = np.round(
            np.minimum(df['prediction'] * 100 + 0.00001, 1) * 85 +
            np.maximum(np.log2(df['prediction'] * 100 + 0.000001) * 185, 0),
            0
        )
        logging.info(f"hd_score_m1 calculated: {df['hd_score_m1'].iloc[0]}")
    except Exception as e:
        logging.error(f"Error processing hd_score_m1 calculations: {e}")


    return df[['application_key', 'application_timestamp', 'deviceid', 'fuzzydeviceid', 'application_email_address', 'hd_score_m1']].iloc[0].to_dict()