import numpy as np
import pandas as pd


TRAILING_HIGH_WINDOW = 60
COMPRESSION_WINDOW = 20
VOLUME_WINDOW = 20


def breakout_after_compression_score(
    close: pd.DataFrame,
    high: pd.DataFrame,
    low: pd.DataFrame,
    volume: pd.DataFrame,
) -> pd.DataFrame:
    """Score breakout setups and shift the result so it is tradable next day."""
    close = close.sort_index()
    high = high.reindex(index=close.index, columns=close.columns).sort_index()
    low = low.reindex(index=close.index, columns=close.columns).sort_index()
    volume = volume.reindex(index=close.index, columns=close.columns).sort_index()

    trailing_high = close.rolling(TRAILING_HIGH_WINDOW, min_periods=TRAILING_HIGH_WINDOW).max()
    proximity_to_high = close / trailing_high.replace(0, np.nan)

    recent_high = high.rolling(COMPRESSION_WINDOW, min_periods=COMPRESSION_WINDOW).max()
    recent_low = low.rolling(COMPRESSION_WINDOW, min_periods=COMPRESSION_WINDOW).min()
    recent_mid = (recent_high + recent_low) / 2
    compressed_range = -((recent_high - recent_low) / recent_mid.replace(0, np.nan))

    median_volume = volume.rolling(VOLUME_WINDOW, min_periods=VOLUME_WINDOW).median()
    abnormal_volume = volume / median_volume.replace(0, np.nan)

    score = proximity_to_high + compressed_range + abnormal_volume
    return score.shift(1)