"""Report accuracy per ANNO × MERCATO delle strategie migliori.

Esegue ogni strategia vincente su BTC e ETH e produce tabella
accuracy/trades per ogni anno. Permette di vedere robustezza temporale
e differenze tra mercati.
"""
from __future__ import annotations
import sys
sys.path.insert(0, ".")

import importlib.util
from pathlib import Path

STRATEGIES_DIR = Path("scripts/strategies")


def load_class(module_file, class_name):
    path = STRATEGIES_DIR / f"{module_file}.py"
    spec = importlib.util.spec_from_file_location(module_file, path)
    mod = importlib.util.module_from_spec(spec)
    spec.loader.exec_module(mod)
    return getattr(mod, class_name)


# (label, module, class, params, hold)
STRATEGIES = [
    ("SQ02 antifake+vol", "SQ02_squeeze_antifake_vol", "SqueezeAntifakeVol", {}, 3),
    ("MT01 ema20+vol",    "MT01_squeeze_mtf_momentum", "SqueezeMTFMomentum",
     {"ema_period": 20, "min_slope": 0.001, "vol_filter": True}, 3),
    ("PD01 vtb3 vm1.3",   "PD01_price_volume_divergence", "PriceVolumeDivergence",
     {}, 3),
    ("CM01 cb6+vol",      "CM01_cross_market_momentum", "CrossMarketMomentum",
     {"cross_bars": 6, "mom_min": 0.001, "use_vol": True}, 3),
    ("AD01 lt.65 ht.95",  "AD01_adaptive_squeeze", "AdaptiveSqueeze",
     {"low_thr": 0.65, "high_thr": 0.95, "use_vol": True}, 3),
]

ASSETS = ["BTC", "ETH"]
TF = "15m"
ALL_YEARS = list(range(2018, 2027))


def run():
    results = {}  # (label, asset) -> BacktestResult

    for label, module, cls_name, params, hold in STRATEGIES:
        try:
            cls = load_class(module, cls_name)
        except Exception as e:
            print(f"SKIP {label}: {e}")
            continue
        strat = cls()
        for asset in ASSETS:
            try:
                r = strat.backtest(asset, TF, hold=hold, **params)
                if r:
                    results[(label, asset)] = r
            except Exception as e:
                print(f"  errore {label} {asset}: {e}")

    # ── Tabella ACCURACY per anno × mercato ──────────────────────────
    print(f"\n{'=' * 140}")
    print(f"  ACCURACY PER ANNO × MERCATO — {TF} (fee 0.2% RT, leva 3x, pos 15%)")
    print(f"{'=' * 140}")

    header = f"  {'Strategia':<22s} {'Mkt':>3s}"
    for y in ALL_YEARS:
        header += f" {y:>7d}"
    header += f" │ {'TOT':>6s} {'DD%':>5s} {'Worst':>10s}"
    print(header)
    print(f"  {'─' * 136}")

    for label, module, cls_name, params, hold in STRATEGIES:
        for asset in ASSETS:
            r = results.get((label, asset))
            if not r:
                continue
            yd = {ys.year: ys for ys in r.yearly}
            line = f"  {label:<22s} {asset:>3s}"
            for y in ALL_YEARS:
                if y in yd:
                    line += f" {yd[y].accuracy:>5.0f}%↑" if yd[y].accuracy >= 80 else f" {yd[y].accuracy:>5.0f}% "
                else:
                    line += f" {'—':>7s}"
            worst = r.worst_year
            worst_str = f"{worst.year}({worst.accuracy:.0f}%)" if worst else "N/A"
            line += f" │ {r.accuracy:>5.1f}% {r.max_dd:>4.1f}% {worst_str:>10s}"
            print(line)
        print(f"  {'·' * 136}")

    # ── Tabella TRADES per anno × mercato ────────────────────────────
    print(f"\n{'=' * 140}")
    print(f"  NUMERO TRADES PER ANNO × MERCATO")
    print(f"{'=' * 140}")

    header = f"  {'Strategia':<22s} {'Mkt':>3s}"
    for y in ALL_YEARS:
        header += f" {y:>7d}"
    header += f" │ {'TOT':>6s} {'€/day':>6s}"
    print(header)
    print(f"  {'─' * 130}")

    for label, module, cls_name, params, hold in STRATEGIES:
        for asset in ASSETS:
            r = results.get((label, asset))
            if not r:
                continue
            yd = {ys.year: ys for ys in r.yearly}
            line = f"  {label:<22s} {asset:>3s}"
            for y in ALL_YEARS:
                if y in yd:
                    line += f" {yd[y].trades:>7d}"
                else:
                    line += f" {'—':>7s}"
            line += f" │ {r.trades:>6d} {r.daily_pnl:>+6.2f}"
            print(line)
        print(f"  {'·' * 130}")

    # ── Tabella PnL per anno × mercato ──────────────────────────────
    print(f"\n{'=' * 140}")
    print(f"  PnL € PER ANNO × MERCATO (su €1000, no compounding tra anni)")
    print(f"{'=' * 140}")

    header = f"  {'Strategia':<22s} {'Mkt':>3s}"
    for y in ALL_YEARS:
        header += f" {y:>7d}"
    header += f" │ {'TOT€':>8s}"
    print(header)
    print(f"  {'─' * 132}")

    for label, module, cls_name, params, hold in STRATEGIES:
        for asset in ASSETS:
            r = results.get((label, asset))
            if not r:
                continue
            yd = {ys.year: ys for ys in r.yearly}
            line = f"  {label:<22s} {asset:>3s}"
            for y in ALL_YEARS:
                if y in yd:
                    line += f" {yd[y].pnl:>+7.0f}"
                else:
                    line += f" {'—':>7s}"
            line += f" │ {r.pnl:>+8.0f}"
            print(line)
        print(f"  {'·' * 132}")

    # ── Sintesi: media per anno (tutte le strategie) ────────────────
    print(f"\n{'=' * 140}")
    print(f"  SINTESI — Accuracy media per anno (tutte le strategie, BTC+ETH)")
    print(f"{'=' * 140}")
    year_acc = {y: [] for y in ALL_YEARS}
    for (label, asset), r in results.items():
        for ys in r.yearly:
            if ys.trades >= 10:
                year_acc[ys.year].append(ys.accuracy)

    line_y = f"  {'Anno':<22s}    "
    line_a = f"  {'Acc media':<22s}    "
    for y in ALL_YEARS:
        accs = year_acc[y]
        avg = sum(accs) / len(accs) if accs else 0
        line_y += f" {y:>7d}"
        line_a += f" {avg:>6.1f}%"
    print(line_y)
    print(line_a)


if __name__ == "__main__":
    run()