54 lines
2.1 KiB
Python
54 lines
2.1 KiB
Python
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# -*- coding: utf-8 -*-
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"""P3-S.3 diagnostic: runtime-training pivot parity (strict vs equal-allowed) utk CHoCH."""
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import os
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import sys
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import numpy as np
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HERE = os.path.dirname(os.path.abspath(__file__))
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REPO_ML = os.path.normpath(os.path.join(HERE, "..", "..", "..", "ml"))
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REPO_P3 = os.path.normpath(os.path.join(REPO_ML, "p3"))
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REPO_PARITY = os.path.normpath(os.path.join(REPO_ML, "parity"))
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sys.path.insert(0, HERE)
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sys.path.insert(0, REPO_ML)
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sys.path.insert(0, REPO_P3)
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sys.path.insert(0, REPO_PARITY)
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import p3_common as P3
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P3.DATA = r"D:\TradingTerminal\HFM Metatrader 5\MQL5\Files\AlgoForge\Data"
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import smc_semantic_common as SC
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import train_model as TM
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import build_features_p2 as BFP
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def main():
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t, o, h, l, c, v, htf = SC.load_data()
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n = len(c)
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sw_at = np.zeros(n, dtype=int)
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sw_s = TM.build_structure(o, h, l, c, SC.SWING_LEN, False, sw_at, begin=100)
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inn_s = TM.build_structure(o, h, l, c, SC.INTERNAL_LEN, True,
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sw_s["trend"].copy(), begin=100)
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sw_e = BFP.build_structure_fast(o, h, l, c, SC.SWING_LEN, False, sw_at, begin=100)
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inn_e = BFP.build_structure_fast(o, h, l, c, SC.INTERNAL_LEN, True,
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sw_e["trend"].copy(), begin=100)
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cd_s, cd_e = inn_s["choch_dir"], inn_e["choch_dir"]
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cb_s, cb_e = inn_s["choch_bar"], inn_e["choch_bar"]
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out = {
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"n_bars": int(n),
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"choch_dir_mismatch": int((cd_s != cd_e).sum()),
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"choch_dir_mismatch_pct": round(float((cd_s != cd_e).sum()) / n * 100.0, 4),
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"choch_bar_mismatch": int((cb_s != cb_e).sum()),
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"onsets_strict": int((cb_s == np.arange(n)).sum()),
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"onsets_equal_allowed": int((cb_e == np.arange(n)).sum()),
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"note": "strict = train_model.build_structure (equal TIDAK allowed); "
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"equal = build_features_p2.build_structure_fast / EA IsPivotHigh (equal allowed)",
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}
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print(out)
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with open(os.path.join(HERE, "output", "parity_choch_pivot_strict_vs_equal.json"),
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"w", encoding="utf-8") as f:
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import json
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json.dump(out, f, indent=2, default=str)
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if __name__ == "__main__":
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main()
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