Add Entry opportunity training diagnostics

This commit is contained in:
Codex
2026-06-28 09:27:59 +08:00
parent e8420f76fe
commit 6be4bb976a
5 changed files with 468 additions and 10 deletions
@@ -0,0 +1,26 @@
from __future__ import annotations
import argparse
import _bootstrap # noqa: F401
from trader_training.good_trade_structure import diagnose_good_trade_structure
from trader_training.io_utils import add_common_args, setup_logging
def _float_tuple(value: str) -> tuple[float, ...]:
return tuple(float(item.strip()) for item in value.split(",") if item.strip())
def main() -> None:
parser = argparse.ArgumentParser(description="Diagnose whether existing features separate good and bad Entry trades.")
add_common_args(parser)
parser.add_argument("--min-good-edge-bps", type=float, default=3.0)
parser.add_argument("--bad-edge-bps", type=float, default=-3.0)
parser.add_argument("--top-fractions", type=_float_tuple, default=(0.01, 0.05, 0.10))
args = parser.parse_args()
setup_logging()
diagnose_good_trade_structure(args)
if __name__ == "__main__":
main()