"""Technische Indikatoren (reine pandas/numpy, ohne TA-Lib)."""

from __future__ import annotations

import numpy as np
import pandas as pd


def ema(series: pd.Series, period: int) -> pd.Series:
    return series.ewm(span=period, adjust=False).mean()


def rsi(close: pd.Series, period: int = 14) -> pd.Series:
    delta = close.diff()
    gain = delta.clip(lower=0.0)
    loss = -delta.clip(upper=0.0)
    avg_gain = gain.ewm(alpha=1 / period, adjust=False).mean()
    avg_loss = loss.ewm(alpha=1 / period, adjust=False).mean()
    rs = avg_gain / avg_loss.replace(0.0, np.nan)
    out = 100 - (100 / (1 + rs))
    return out.fillna(50.0)


def atr(df: pd.DataFrame, period: int = 14) -> pd.Series:
    high, low, close = df["high"], df["low"], df["close"]
    prev_close = close.shift(1)
    tr = pd.concat(
        [(high - low), (high - prev_close).abs(), (low - prev_close).abs()], axis=1
    ).max(axis=1)
    return tr.ewm(alpha=1 / period, adjust=False).mean()


def crossover(a: pd.Series, b: pd.Series) -> pd.Series:
    return (a > b) & (a.shift(1) <= b.shift(1))


def crossunder(a: pd.Series, b: pd.Series) -> pd.Series:
    return (a < b) & (a.shift(1) >= b.shift(1))