HC900-Crawler/scripts/analysis/c6111_startup.py

"""
② START-UP 절차 학습 (few-shot).

형제 컬럼 호환: --data, --prefix CLI 인자.
"""
import argparse
import numpy as np
import pandas as pd
import matplotlib
matplotlib.use("Agg")
import matplotlib.pyplot as plt

BASE = "/home/windpacer/projects/hc900_ax/scripts/analysis/"


def detect_cutins(df):
    """★제품 컷인★ 이벤트: product 0→>100 상향, 직전 30분 라인아웃(product<50)이고 hot(reb>75)."""
    prod = df["product"].values
    reb = df["reb_temp"].values
    outs = []
    i = 60
    n = len(df)
    while i < n:
        if prod[i] > 100 and prod[i-1] <= 100:
            pre = prod[max(0, i-60):i]          # 직전 30분
            if np.nanmedian(pre) < 50 and reb[i] > 75:   # 라인아웃(제품off)+hot
                outs.append(i)
                i += 720
                continue
        i += 1
    return outs


def milestones(df, ci):
    """제품 컷인 인덱스 ci 기준 절차 추출."""
    tc = df["dtat"].iloc[ci]
    # 역방향: 스팀투입(steam_op>10 연속 시작) — 컷인 직전 steam off→on
    back = df.iloc[max(0, ci-1200):ci]
    off = back[back["steam_op"] <= 10]
    i_steam = off.index[-1] + 1 if len(off) else back.index[0]
    # 리플럭스 확립(스팀투입 이후 reflux>100 첫)
    aft = df.iloc[i_steam:ci]
    r_on = aft[aft["reflux"] > 100]
    i_refl = r_on.index[0] if len(r_on) else None
    # 풀로드(컷인 이후 feed>250 첫)
    fwd = df.iloc[ci:ci+1200]
    f_on = fwd[fwd["feed"] > 250]
    i_full = f_on.index[0] if len(f_on) else None

    def mins(i):
        return None if i is None else (df["dtat"].iloc[i]-tc).total_seconds()/60
    r = df.iloc[ci]
    return dict(cutin_time=tc,
                steam_to_cutin=-mins(i_steam),
                reflux_to_cutin=(-mins(i_refl) if i_refl is not None else None),
                cutin_to_full=mins(i_full),
                cutin_rebA=r["reb_temp"], cutin_TC=r["T_C"], cutin_TD=r["T_D"],
                cutin_dT_AD=r["reb_temp"]-r["T_D"])


def main():
    parser = argparse.ArgumentParser()
    parser.add_argument("--data", default=BASE + "C-6111_data.pkl")
    parser.add_argument("--prefix", default="C-6111")
    args = parser.parse_args()
    df = pd.read_pickle(args.data).sort_values("dtat").reset_index(drop=True)
    cutins = detect_cutins(df)
    print(f"탐지된 ★제품 컷인★(진짜 startup) 이벤트: {len(cutins)}개")

    rows, windows = [], []
    for ci in cutins:
        w = df.iloc[max(0, ci-360):min(len(df), ci+360)].copy()   # 컷인 ±3h
        w["rel_min"] = (w["dtat"] - df["dtat"].iloc[ci]).dt.total_seconds()/60
        windows.append(w)
        rows.append(milestones(df, ci))
    M = pd.DataFrame(rows)
    pd.set_option("display.width", 220)
    print("\n=== 제품컷인 기준 절차(분) + 컷인 시점 컬럼상태 ===")
    cols = ["cutin_time", "steam_to_cutin", "reflux_to_cutin", "cutin_to_full",
            "cutin_rebA", "cutin_TC", "cutin_dT_AD"]
    show = M[cols].copy()
    show["cutin_time"] = show["cutin_time"].dt.strftime("%m-%d %H:%M")
    print(show.round(1).to_string(index=False))
    print("\n=== 절차 레시피(중앙값) ===")
    print(f"  스팀투입→제품컷인(전환류 라인아웃 길이): {M.steam_to_cutin.median():.0f}분")
    print(f"  리플럭스확립→제품컷인               : {M.reflux_to_cutin.median():.0f}분")
    print(f"  제품컷인→풀로드                     : {M.cutin_to_full.median():.0f}분")
    print(f"  ★제품컷인 트리거(컬럼상태): reb-A={M.cutin_rebA.median():.1f}±{M.cutin_rebA.std():.1f}℃, "
          f"T_C={M.cutin_TC.median():.1f}±{M.cutin_TC.std():.2f}℃, ΔT(A-D)={M.cutin_dT_AD.median():.1f}℃")

    fig, ax = plt.subplots(4, 1, figsize=(13, 11), sharex=True)
    for k, w in enumerate(windows):
        c = plt.cm.tab10(k)
        ax[0].plot(w.rel_min, w.reb_temp, color=c, lw=.9, label=f"ep{k+1} {w.dtat.iloc[len(w)//2]:%m-%d}")
        ax[0].plot(w.rel_min, w["T_D"], color=c, lw=.6, ls=":")
        ax[1].plot(w.rel_min, w.steam_flow, color=c, lw=.9)
        ax[2].plot(w.rel_min, w.reflux, color=c, lw=.9)
        ax[2].plot(w.rel_min, w["product"], color=c, lw=.9, ls="--")
        ax[3].plot(w.rel_min, w.feed, color=c, lw=.9)
    ax[0].set_ylabel("reb_temp/T_D(:)"); ax[0].legend(fontsize=7)
    ax[0].set_title("STARTUP aligned at PRODUCT CUT-IN (rel=0)")
    ax[1].set_ylabel("steam flow"); ax[2].set_ylabel("reflux/product(--)")
    ax[3].set_ylabel("feed"); ax[3].set_xlabel("minutes from product cut-in")
    for a in ax:
        a.axvline(0, c="k", lw=.5)
    fig.tight_layout(); fig.savefig(BASE + f"{args.prefix}_startup.png", dpi=95)
    print(f"\n플롯 저장: {BASE}{args.prefix}_startup.png")


if __name__ == "__main__":
    main()