gahusb
ace0339d33
- git mv stock-lab/ → stock/ - docker-compose.yml: 서비스 키 + container_name + build.context + frontend.depends_on + agent-office STOCK_LAB_URL → STOCK_URL - agent-office/app: config.py, service_proxy.py, agents/stock.py, tests/ STOCK_LAB_URL → STOCK_URL - nginx/default.conf: proxy_pass http://stock-lab → http://stock (3 lines) - CLAUDE.md / README.md / STATUS.md / scripts/ 문구 갱신 - stock/ 내부 자기 참조 갱신 lab 네이밍 정책 (feedback_lab_naming.md) graduation. API URL / Python import / DB 파일명 변경 없음.
41 lines
1.3 KiB
Python
41 lines
1.3 KiB
Python
"""거래량 급증 — log1p(recent/baseline)."""
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import numpy as np
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import pandas as pd
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from .base import ScoreNode, percentile_rank
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class VolumeSurge(ScoreNode):
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name = "volume_surge"
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label = "거래량 급증"
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default_params = {"baseline_days": 20, "eval_days": 3}
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param_schema = {
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"type": "object",
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"properties": {
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"baseline_days": {"type": "integer", "minimum": 5, "maximum": 60, "default": 20},
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"eval_days": {"type": "integer", "minimum": 1, "maximum": 10, "default": 3},
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},
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}
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def compute(self, ctx, params: dict) -> pd.Series:
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baseline = int(params.get("baseline_days", 20))
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eval_d = int(params.get("eval_days", 3))
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prices = ctx.prices
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if prices.empty:
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return pd.Series(dtype=float)
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ordered = prices.sort_values("date")
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last_recent = ordered.groupby("ticker").tail(eval_d).groupby("ticker")["volume"].mean()
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last_baseline = (
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ordered.groupby("ticker")
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.tail(baseline + eval_d)
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.groupby("ticker")
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.head(baseline)
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.groupby("ticker")["volume"]
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.mean()
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)
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ratio = last_recent / last_baseline.replace(0, pd.NA)
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raw = np.log1p(ratio.astype(float))
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return percentile_rank(raw).fillna(50.0)
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