"""Test minimale per scripts/research/signal_inout_1leg.py:
  - la costruzione del segnale MACD e' CAUSALE (no look-ahead): causality_ok ok, tail-diff ~0;
  - una cella esegue end-to-end (study_weights ritorna un verdetto valido).
Veloce: solo BTC a 1d, una cella.
"""
import sys

import numpy as np

sys.path.insert(0, "/opt/docker/PythagorasGoal/scripts/research/alt")
sys.path.insert(0, "/opt/docker/PythagorasGoal/scripts/research")
import altlib as al  # noqa: E402
import signal_inout_1leg as sig  # noqa: E402


def test_macd_target_is_causal():
    """Un target MACD costruito con EMA(adjust=False) non deve guardare al futuro."""
    fn = sig.make_macd("LF")(tf="1d", fast=12, slow=26, sig=9)
    c = al.causality_ok(fn, tf="1d")
    assert c["ok"], c
    assert c["max_tail_diff"] <= 1e-6, c


def test_macd_position_values_and_hold():
    """Long-flat in {0,1}; long-short in {-1,1}; nessun NaN."""
    df = al.get("BTC", "1d")
    lf = sig.make_macd("LF")(tf="1d", fast=12, slow=26, sig=9)(df)
    ls = sig.make_macd("LS")(tf="1d", fast=12, slow=26, sig=9)(df)
    assert len(lf) == len(df) and len(ls) == len(df)
    assert set(np.unique(lf)).issubset({0.0, 1.0})
    assert set(np.unique(ls)).issubset({-1.0, 1.0})
    assert np.isfinite(lf).all() and np.isfinite(ls).all()


def test_one_cell_executes_end_to_end():
    """study_weights su una cella MACD-LF deve produrre un verdetto valido."""
    fn = sig.make_macd("LF")(tf="1d", fast=12, slow=26, sig=9)
    rep = al.study_weights("MACD-LF-test", fn, tfs=("1d",))
    assert rep["verdict"]["grade"] in ("PASS", "WEAK", "FAIL")
    assert rep["cells"] and rep["cells"][0]["per_asset"]


def test_supertrend_and_rsi_targets_run():
    """Supertrend (stateful) e RSI (mean-rev) producono posizioni causali eseguibili."""
    df = al.get("BTC", "1d")
    st = sig.make_supertrend("LF")(tf="1d", atr_win=14, mult=2.5)(df)
    rs = sig.make_rsi()(tf="1d", win=14, oversold=30, overbought=65)(df)
    assert len(st) == len(df) and len(rs) == len(df)
    assert np.isfinite(st).all() and np.isfinite(rs).all()
    assert al.causality_ok(sig.make_supertrend("LF")(tf="1d", atr_win=14, mult=2.5), tf="1d")["ok"]