import numpy as np
from typing import Dict, Any
from config import (
    MAX_RISK_PER_TRADE,
    HIGH_VOLATILITY_THRESHOLD,
    REDUCED_RISK_FACTOR,
)


def compute_stop_distance(atr: float, multiplier: float = 2.0) -> float:
    return atr * multiplier


def compute_position_size(
    account_equity: float,
    entry_price: float,
    stop_distance: float,
    risk_fraction: float = MAX_RISK_PER_TRADE,
) -> float:
    if stop_distance <= 0 or entry_price <= 0:
        return 0.0
    dollar_risk = account_equity * risk_fraction
    units = dollar_risk / stop_distance
    notional = units * entry_price
    return notional


def compute_risk_fraction(
    vol_ratio: float,
    regime_score: float,
    base_risk: float = MAX_RISK_PER_TRADE,
) -> float:
    risk = base_risk

    if vol_ratio > HIGH_VOLATILITY_THRESHOLD:
        risk *= REDUCED_RISK_FACTOR

    if regime_score < 0.4:
        risk *= REDUCED_RISK_FACTOR
    elif regime_score < 0.6:
        risk *= 0.75

    return float(np.clip(risk, 0.001, base_risk))


def evaluate_risk(
    df_last_close: float,
    atr: float,
    atr_pct: float,
    regime_score: float,
    vol_ratio: float,
    account_equity: float = 10000.0,
    stop_multiplier: float = 2.0,
) -> Dict[str, Any]:
    stop_distance = compute_stop_distance(atr, stop_multiplier)
    risk_fraction = compute_risk_fraction(vol_ratio, regime_score)
    position_notional = compute_position_size(
        account_equity, df_last_close, stop_distance, risk_fraction
    )

    stop_price_long = df_last_close - stop_distance
    stop_price_short = df_last_close + stop_distance
    risk_reward_target = stop_distance * 2.0

    target_long = df_last_close + risk_reward_target
    target_short = df_last_close - risk_reward_target

    return {
        "entry_price": df_last_close,
        "atr": atr,
        "atr_pct": atr_pct,
        "stop_distance": stop_distance,
        "stop_price_long": stop_price_long,
        "stop_price_short": stop_price_short,
        "target_long": target_long,
        "target_short": target_short,
        "risk_fraction": risk_fraction,
        "position_notional": position_notional,
        "vol_ratio": vol_ratio,
        "regime_score": regime_score,
    }