initial: import DOLPHIN baseline 2026-04-21 from dolphinng5_predict working tree

Includes core prod + GREEN/BLUE subsystems:
- prod/ (BLUE harness, configs, scripts, docs)
- nautilus_dolphin/ (GREEN Nautilus-native impl + dvae/ preserved)
- adaptive_exit/ (AEM engine + models/bucket_assignments.pkl)
- Observability/ (EsoF advisor, TUI, dashboards)
- external_factors/ (EsoF producer)
- mc_forewarning_qlabs_fork/ (MC regime/envelope)

Excludes runtime caches, logs, backups, and reproducible artifacts per .gitignore.

prod/diagnose_nautilus.py

@@ -0,0 +1,103 @@
+"""
+Diagnose hanging backtest engine.
+Feed only 500 rows of day 1, with extensive logging.
+"""
+import sys, time
+sys.path.insert(0, '.')
+sys.path.insert(0, 'nautilus_dolphin')
+
+from nautilus_dolphin.nautilus.dolphin_actor import DolphinActor
+from prod.nautilus_native_backtest import get_parquet_files, _make_instrument
+import pandas as pd
+import numpy as np
+from nautilus_trader.model.identifiers import Venue
+from nautilus_trader.backtest.engine import BacktestEngine, BacktestEngineConfig
+from nautilus_trader.model.enums import OmsType, AccountType
+from nautilus_trader.model.objects import Money, Currency
+from nautilus_trader.model.data import BarType, Bar
+import prod.nautilus_native_backtest as _nbt_mod
+
+files = get_parquet_files()
+df0 = pd.read_parquet(files[0])
+df0 = df0.iloc[:500]  # JUST 500 ROWS!
+
+SKIP_COLS = {
+    'timestamp', 'scan_number', 'v50_lambda_max_velocity', 'v150_lambda_max_velocity',
+    'v300_lambda_max_velocity', 'v750_lambda_max_velocity', 'vel_div',
+    'instability_50', 'instability_150'
+}
+asset_cols = [c for c in df0.columns if c not in SKIP_COLS]
+
+NV = Venue('BINANCE')
+instruments = {}
+for sym in asset_cols:
+    try: instruments[sym] = _make_instrument(sym, NV)
+    except: pass
+
+print("Building features and bars...")
+_nbt_mod._FEATURE_STORE.clear()
+all_bars = []
+import datetime
+
+# Midnight nanoseconds
+day_dt = datetime.datetime.strptime(files[0].stem, '%Y-%m-%d').replace(tzinfo=datetime.timezone.utc)
+day_start_ns = int(day_dt.timestamp() * 1e9)
+
+for ri in range(len(df0)):
+    row = df0.iloc[ri]
+    ts_ns = int(day_start_ns + ri * 5 * 1_000_000_000)
+    
+    _nbt_mod._FEATURE_STORE[ts_ns] = {
+        'vel_div': float(row.get('vel_div', 0.0)),
+        'v50': float(row.get('v50_lambda_max_velocity', 0.0)),
+        'v750': float(row.get('v750_lambda_max_velocity', 0.0)),
+        'inst50': float(row.get('instability_50', 0.0)),
+        'vol_ok': True,
+        'row_i': ri,
+    }
+    
+    for sym in asset_cols:
+        px = row.get(sym)
+        if px and np.isfinite(float(px)) and float(px)>0:
+            bt = BarType.from_str(f"{sym}.BINANCE-5-SECOND-LAST-EXTERNAL")
+            bar = _nbt_mod._make_bar(bt, float(px), ts_ns)
+            all_bars.append(bar)
+
+print(f"Created {len(all_bars)} bars.")
+
+# Build engine
+be_cfg = BacktestEngineConfig(trader_id='TEST-DIAGNOSE-01')
+bt_engine = BacktestEngine(config=be_cfg)
+usdt = Currency.from_str('USDT')
+bt_engine.add_venue(venue=NV, oms_type=OmsType.HEDGING, account_type=AccountType.MARGIN, base_currency=usdt, starting_balances=[Money('25000', usdt)])
+
+for sym, instr in instruments.items():
+    bt_engine.add_instrument(instr)
+
+actor_cfg = {
+    'engine': dict(_nbt_mod.CHAMPION_ENGINE_CFG),
+    'paper_trade': {'initial_capital': 25000.0},
+    'posture_override': 'APEX',
+    'live_mode': False,
+    'native_mode': True,
+    'run_date': files[0].stem,
+    'bar_type': 'BTCUSDT.BINANCE-5-SECOND-LAST-EXTERNAL',
+    'mc_models_dir': _nbt_mod.MC_MODELS_DIR,
+    'mc_base_cfg': _nbt_mod.MC_BASE_CFG,
+    'venue': 'BINANCE',
+    'vol_p60': 0.0002,
+    'acb_preload_dates': [f.stem for f in files],
+    'assets': asset_cols,
+    'parquet_dir': 'vbt_cache',
+    'registered_assets': asset_cols,
+}
+actor_cfg['engine']['initial_capital'] = 25000.0
+
+actor = DolphinActor(config=actor_cfg)
+bt_engine.add_strategy(actor)
+bt_engine.add_data(all_bars)
+
+print("Starting BacktestEngine run...")
+t0 = time.time()
+bt_engine.run()
+print(f"Done in {time.time()-t0:.2f}s")