forked from mnbvc188199/Warrior_EA
e9c562b39f
- Introduced `FeatureScale.mqh` with `FeatSquash` function for stateless feature scaling. - Added `RegimeMath.mqh` class for regime arithmetic, including efficiency and variance calculations. - Documented the Mind trading logic in `MIND.md`, detailing the trading process and modes. - Created `VOLNORM_PLAN.md` and `VOLNORM_RESULTS.md` for tick-volume normalization testing. - Implemented `read_book.py` for analyzing trade book data and correlations. - Developed `volnorm.py` for testing tick-volume normalization with new and old methods.
64 lines
3.3 KiB
Python
64 lines
3.3 KiB
Python
"""Write tester .ini files into the fleet terminal's data dir, every input pinned.
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python mql5/make_inis.py warrior <tag> SYM [SYM ...] [key=value ...]
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python mql5/make_inis.py dipz <tag> SYM [SYM ...] [key=value ...]
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The tester INHERITS any input an .ini leaves out from the last run, so both
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templates list every input the EA declares; key=value overrides one of them
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(or a [Tester] key such as FromDate / Model).
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"""
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from __future__ import annotations
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import sys
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DATA = r"C:\Users\admin\AppData\Roaming\MetaQuotes\Terminal\10CE948A1DFC9A8C27E56E827008EBD4"
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TESTER = dict(Period="H4", Model="1", FromDate="2022.01.01", ToDate="2026.09.01",
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ForwardMode="0", ForwardDate="2026.09.01", Deposit="100000", Currency="USD",
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Leverage="1:100", Optimization="0", Visual="0", ReplaceReport="1")
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WARRIOR = dict(
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Magic="20260911", EveryTick="false", ThresholdOpen="15", ThresholdClose="50", Direction="1",
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FadeCrowd="0", MoneyMode="0", Risk="25", FixedLots="0.01", StopMode="3", TargetMode="0",
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TrailMode="0", BreakevenAt="0", ManagementCut="0", MaxOpenRiskPct="0.75", KillSwitchDD="4.5",
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FridayFlatMin="170", TradeLog="true",
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**{w: "100" for w in ["W_MA", "W_RSI", "W_MACD", "W_CCI", "W_Stoch", "W_WPR", "W_RVI", "W_SAR",
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"W_AO", "W_AC", "W_Ichimoku", "W_WyckoffEv", "W_WyckoffSt", "W_Neural",
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"W_Regime", "W_DipBuy"]},
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UseClassics="false", UseWyckoff="false", UseRegime="false", UseDipBuy="true", DipEntry="1",
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DipZ="1.5", DipExitMA="20", DipTrendMA="0", DipMaxBars="10", DipVolGate="true",
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DipVolPct="0.5", DipMetaCut="50", DipMetaRefit="500", UseNeural="false", NeuralCut="50",
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UseDatabase="false", DB_RankingFeedsWeights="false", AtrPeriod="14",
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MindMode="1", MindWyckoff="true", MindPeers="SP500,NAS100,US30,DAX40", MindMinTrades="40",
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MindShrink="20", MindMinScale="0.5", MindTrials="50")
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DIPZ = dict(InpTF="16388", InpZPeriod="20", InpZEntry="-1.5", InpMaxBars="10", InpStopATR="3.0",
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InpATRPeriod="14", InpRiskPct="0.25", InpVolGate="true", InpVolPct="0.5",
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InpVolWindow="30", InpVolWarm="250", InpMaxOpenRiskPct="0.75", InpMaxDDPct="4.5",
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InpFridayFlatMin="170", InpMagic="20260922", InpJournal="true", InpEquityLog="false")
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EXPERT = {"warrior": r"Warrior\Warrior_EA", "dipz": r"Warrior\WarriorDipZ"}
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if __name__ == "__main__":
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kind, tag, rest = sys.argv[1], sys.argv[2], sys.argv[3:]
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syms = [a for a in rest if "=" not in a]
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over = dict(a.split("=", 1) for a in rest if "=" in a)
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inputs = dict(WARRIOR if kind == "warrior" else DIPZ)
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tester = dict(TESTER)
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for k, v in over.items():
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if k in tester:
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tester[k] = v
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elif k in inputs:
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inputs[k] = v
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else:
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if k != "Expert":
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sys.exit(f"unknown key {k}")
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expert = over.pop("Expert", EXPERT[kind])
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for sym in syms:
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name = f"claude_{tag}_{sym}"
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lines = ["[Tester]", f"Expert={expert}", f"Symbol={sym}"]
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lines += [f"{k}={v}" for k, v in tester.items()]
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lines += [f"Report={name}", "", "[TesterInputs]"]
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lines += [f"{k}={v}" for k, v in inputs.items()]
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with open(rf"{DATA}\{name}.ini", "w", encoding="ascii", newline="\n") as f:
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f.write("\n".join(lines) + "\n")
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print(name)
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