import numpy as np
import pandas as pd

from multi_swarm.metrics.dsr import deflated_sharpe_ratio, expected_max_sharpe


def test_expected_max_sharpe_grows_with_n_trials():
    e1 = expected_max_sharpe(n_trials=1, sharpe_var=1.0)
    e10 = expected_max_sharpe(n_trials=10, sharpe_var=1.0)
    e100 = expected_max_sharpe(n_trials=100, sharpe_var=1.0)
    assert e1 < e10 < e100


def test_dsr_zero_when_sharpe_equals_expected_max():
    np.random.seed(0)
    returns = pd.Series(np.random.normal(0, 0.01, 500))
    _dsr, p = deflated_sharpe_ratio(
        returns, n_trials=10, periods_per_year=8760, sharpe_var=0.0
    )
    # Con sharpe_var=0 e Sharpe stimato vicino a 0, p-value deve essere alto.
    assert 0.0 <= p <= 1.0


def test_dsr_significant_for_strong_sharpe():
    np.random.seed(42)
    returns = pd.Series(np.random.normal(0.005, 0.005, 1000))
    dsr, p = deflated_sharpe_ratio(
        returns, n_trials=5, periods_per_year=8760, sharpe_var=1.0
    )
    # Sharpe atteso > 0 e p-value basso
    assert dsr > 0
    assert p < 0.5