import json from datetime import datetime, timezone def parse_time(val): if isinstance(val, (int, float)): return float(val) if isinstance(val, str): if 'T' in val: return datetime.strptime(val, "%Y-%m-%dT%H:%M:%SZ").replace(tzinfo=timezone.utc).timestamp() return float(val) return float(val) def load_json(filepath): with open(filepath, 'r') as f: data = json.load(f) if isinstance(data, dict): if 't' in data and 'o' in data: bars = [] for i in range(len(data['t'])): bars.append({ 'time': parse_time(data['t'][i]), 'open': float(data['o'][i]), 'high': float(data['h'][i]), 'low': float(data['l'][i]), 'close': float(data['c'][i]), }) return bars for k, v in data.items(): if isinstance(v, list) and len(v) > 0 and isinstance(v[0], dict) and 'time' in v[0]: return v return data def get_bars_around(data, timestamp_str, hours_before=24, hours_after=12): target_dt = datetime.strptime(timestamp_str, "%Y-%m-%dT%H:%M:%SZ").replace(tzinfo=timezone.utc) target_ts = target_dt.timestamp() start_ts = target_ts - (hours_before * 3600) end_ts = target_ts + (hours_after * 3600) bars = [] for bar in data: t = parse_time(bar['time']) if start_ts <= t <= end_ts: bar_copy = bar.copy() bar_copy['time'] = t bars.append(bar_copy) return bars m30_data = load_json('hybrid/data/ohlcv_M30.json') m5_data = load_json('hybrid/data/ohlcv_M5.json') c1 = "2026-06-30T07:45:00Z" c2 = "2026-06-30T08:30:00Z" c3 = "2026-06-30T11:15:00Z" decisions = {} # C1: Long at 07:45 # HTF Context: H1 dropped from 4070 (June 29) to 3942 (June 30 01:00) then started reversing. # 06:00 H1 was strong bullish (3978 -> 4029) and 07:00 H1 (4029 -> 4032). # M30 shows a bullish run from 3942 up to 4034. # At 07:45, price is around 4030. M5 shows a dip to 4020.27 (07:50-08:00) then rebound. # However, this looks like a momentum continuation, not a clear liquidity sweep on HTF structure. # M30 swing low is way down at 3942, or intermediate at 3978. Price is extended. decisions[c1] = { "decision": "rejected", "reason": "Price is extended after a massive bullish M30 run (3942 to 4034). No clear HTF pullback to a discount PD array or deep liquidity sweep at 07:45.", "htf_context": "H1/M30 massive bullish recovery from 3942 to 4034.", "m30_structure": "Bullish momentum, extended, no discount pullback.", "m15_m5_execution": "M5 shows minor consolidation around 4030, but entry here is chasing price.", "promoted_to_journal": False } # C2: Short at 08:30 # M30 Context: High at 07:00 is 4034.86, High at 08:00 is 4037.665. # 08:00 M30 closed bearish at 4025.945 (Sweep of 4034.86). # 08:30 M5 open is 4025.955. Price drops to 4013.80. # This looks like a valid sweep of the Asian/early London high (4034.86). # Let's check entry details. # M5 at 08:20 high was 4027.81, low 4020.27. # M5 at 08:25 high 4026.865. # At 08:30, price drops immediately. # Let's mark as needs_more_context to check precise entry model (MSS/FVG). decisions[c2] = { "decision": "needs_more_context", "reason": "Valid M30 liquidity sweep of 4034.86 (peaked at 4037.665) followed by bearish close. Need more detailed M1/M5 analysis for exact MSS and FVG entry.", "htf_context": "H1/M30 swept previous high 4034.86 and rejected.", "m30_structure": "Bearish rejection after sweeping local high.", "m15_m5_execution": "M5 shows immediate drop after 08:30. Requires M1 for precise entry validation.", "promoted_to_journal": False } # C3: Short at 11:15 # M30 Context: 11:00 M30 high is 4034.325. 11:30 M30 high is 4037.43. # 11:15 M5: 11:10 H 4033.79. 11:15 H 4034.325. 11:20 H 4033.91. 11:45 H 4037.43. # If Short at 11:15, price goes up to 4037.43 at 11:45 before dropping heavily to 4009 at 12:30. # So an 11:15 entry would likely suffer drawdown or get stopped out if SL was tight above 4034.325. # The true sweep happened at 11:45 (sweeping 4034.325). decisions[c3] = { "decision": "rejected", "reason": "Premature entry. Price sweeps 4034.325 high later at 11:45 (reaching 4037.43) before the real drop. 11:15 entry would face drawdown or stop out.", "htf_context": "H1 consolidating near local highs around 4030-4037.", "m30_structure": "Choppy price action, sweeping highs before dropping.", "m15_m5_execution": "Entering at 11:15 is before the final liquidity sweep at 11:45.", "promoted_to_journal": False } results = [] results.append({ "candidate_id": "candidate_2026-06-30T07-45-00Z_long_liquidity_sweep_reversal", "timestamp": c1, "decision": decisions[c1]["decision"], "reason": decisions[c1]["reason"], "htf_context": decisions[c1]["htf_context"], "m30_structure": decisions[c1]["m30_structure"], "m15_m5_execution": decisions[c1]["m15_m5_execution"], "entry": None, "stop": None, "target": None, "r": None, "promoted_to_journal": decisions[c1]["promoted_to_journal"] }) results.append({ "candidate_id": "candidate_2026-06-30T08-30-00Z_short_liquidity_sweep_reversal", "timestamp": c2, "decision": decisions[c2]["decision"], "reason": decisions[c2]["reason"], "htf_context": decisions[c2]["htf_context"], "m30_structure": decisions[c2]["m30_structure"], "m15_m5_execution": decisions[c2]["m15_m5_execution"], "entry": None, "stop": None, "target": None, "r": None, "promoted_to_journal": decisions[c2]["promoted_to_journal"] }) results.append({ "candidate_id": "candidate_2026-06-30T11-15-00Z_short_liquidity_sweep_reversal", "timestamp": c3, "decision": decisions[c3]["decision"], "reason": decisions[c3]["reason"], "htf_context": decisions[c3]["htf_context"], "m30_structure": decisions[c3]["m30_structure"], "m15_m5_execution": decisions[c3]["m15_m5_execution"], "entry": None, "stop": None, "target": None, "r": None, "promoted_to_journal": decisions[c3]["promoted_to_journal"] }) with open('hybrid/reviews/manual_replay_results/replay_result_00725_00728.json', 'w') as f: json.dump(results, f, indent=2) print("Saved replay_result_00725_00728.json")