"""Test del gate weights_tilt_null (lezione 2026-07-01: EW-STR refutato come best-of-k).

Dati SINTETICI deterministici: 3 sleeve a date d'inizio diverse, di cui uno ("C") con
Sharpe gonfiato SOLO nell'hold-out — il tilt verso C deve risultare sospetto (percentile
alto fra i tilt casuali, delta_insample ~<=0), mentre un tilt nullo deve essere innocuo.
"""
import sys
from pathlib import Path

import numpy as np
import pandas as pd
import pytest

sys.path.insert(0, str(Path(__file__).resolve().parents[1]))

from src.portfolio.portfolio import HOLDOUT, StrategyPortfolio, Sleeve, combine_outer, weights_tilt_null


def _mk_daily(start: str, n: int, mu: float, sigma: float, seed: int,
              mu_holdout: float | None = None) -> pd.Series:
    rng = np.random.default_rng(seed)
    idx = pd.date_range(start, periods=n, freq="1D", tz="UTC")
    r = rng.normal(mu, sigma, n)
    if mu_holdout is not None:
        m = idx >= HOLDOUT
        r[m] = rng.normal(mu_holdout, sigma, int(m.sum()))
    return pd.Series(r, index=idx)


@pytest.fixture(scope="module")
def cols() -> dict:
    n = 2600  # ~2019-07 -> 2026-08: copre pre e post hold-out
    return {
        "A": _mk_daily("2019-07-01", n, 8e-4, 0.010, seed=1),
        "B": _mk_daily("2021-01-01", n - 550, 6e-4, 0.012, seed=2),
        # C: rumore pre-holdout, forte SOLO nell'hold-out (imita lo sleeve selezionato sull'OOS)
        "C": _mk_daily("2019-07-01", n, 0.0, 0.011, seed=3, mu_holdout=18e-4),
    }


def test_combine_outer_equivale_a_combined_daily(cols):
    sleeves = [Sleeve(nm, w, daily_fn=(lambda s=cols[nm]: s))
               for nm, w in [("A", 0.5), ("B", 0.3), ("C", 0.2)]]
    port = StrategyPortfolio(sleeves)
    a = port.combined_daily()
    b = combine_outer(cols, {"A": 0.5, "B": 0.3, "C": 0.2})
    assert np.allclose(a.values, b.values) and a.index.equals(b.index)


def test_tilt_identico_e_neutro(cols):
    w = {"A": 0.5, "B": 0.3, "C": 0.2}
    rep = weights_tilt_null(cols, w, w, n=100, seed=7)
    assert rep["delta_hold"] == 0.0 and rep["delta_full"] == 0.0 and rep["delta_insample"] == 0.0
    assert rep["n_samples"] == 100
    assert 0.0 <= rep["frac_random_beat_hold"] <= 1.0


def test_vincoli_floor_caps_rispettati(cols):
    rep = weights_tilt_null(cols, {"A": 0.5, "B": 0.3, "C": 0.2}, {"A": 0.4, "B": 0.3, "C": 0.3},
                            caps={"B": 0.35}, floor=0.05, n=150, seed=11)
    S = rep["samples"]
    assert (S >= 0.05 - 1e-12).all() and (S[:, 1] <= 0.35 + 1e-12).all()
    assert np.allclose(S.sum(axis=1), 1.0)


def test_tilt_verso_sleeve_holdout_only_e_sospetto(cols):
    """Tilt verso C (edge solo hold-out): delta_hold>0 ma insample<=~0 -> gate_pass False."""
    w_cur = {"A": 0.5, "B": 0.3, "C": 0.2}
    w_pro = {"A": 0.30, "B": 0.25, "C": 0.45}
    rep = weights_tilt_null(cols, w_cur, w_pro, n=300, seed=13, k_seen=15)
    assert rep["delta_hold"] > 0            # sull'hold-out "vince" (per costruzione)
    assert rep["delta_insample"] <= 0.05    # ma pre-holdout non c'e' edge
    assert rep["bestofk_pctl"] == pytest.approx(100 * 15 / 16)
    assert not rep["gate_pass"]


def test_determinismo(cols):
    w_cur = {"A": 0.5, "B": 0.3, "C": 0.2}
    w_pro = {"A": 0.4, "B": 0.3, "C": 0.3}
    r1 = weights_tilt_null(cols, w_cur, w_pro, n=80, seed=42)
    r2 = weights_tilt_null(cols, w_cur, w_pro, n=80, seed=42)
    assert r1["pctl_hold"] == r2["pctl_hold"] and np.allclose(r1["samples"], r2["samples"])