import numpy as np
import pandas as pd
import pytest

from multi_swarm.metrics.basic import max_drawdown, sharpe_ratio, total_return


def test_sharpe_zero_returns():
    r = pd.Series([0.0] * 100)
    assert sharpe_ratio(r, periods_per_year=8760) == 0.0


def test_sharpe_positive_returns():
    np.random.seed(42)
    r = pd.Series(np.random.normal(0.001, 0.01, 1000))
    s = sharpe_ratio(r, periods_per_year=8760)
    assert s > 0


def test_sharpe_negative_returns():
    np.random.seed(42)
    r = pd.Series(np.random.normal(-0.001, 0.01, 1000))
    s = sharpe_ratio(r, periods_per_year=8760)
    assert s < 0


def test_max_drawdown_monotonic_up():
    eq = pd.Series([100.0, 105.0, 110.0, 115.0, 120.0])
    assert max_drawdown(eq) == pytest.approx(0.0)


def test_max_drawdown_known_curve():
    eq = pd.Series([100.0, 110.0, 90.0, 95.0, 105.0])
    # peak 110, trough 90, drawdown = (110-90)/110 ≈ 0.1818
    assert max_drawdown(eq) == pytest.approx(20.0 / 110.0)


def test_total_return():
    eq = pd.Series([100.0, 110.0, 105.0, 120.0])
    assert total_return(eq) == pytest.approx(0.20)