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@@ -597,3 +597,139 @@ def fleet(win: str = '2026年') -> dict[str, Any]:
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`TypeError: fleet_view() missing 1 required positional argument: 'win'`（算法服务 500）。
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"""
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return fleet_view(win)
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+from src import paths as _P # 路径唯一真源 (与 cwd 无关)
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+from src.windscada import taxonomy
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+from src.windscada.subsys import temp_nbm, hydraulic, yaw as yawmod, pitch as pitchmod
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+import hashlib, time
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+import numpy as np, pandas as pd
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+import threading as _thr
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+
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+# ── curves 视图所需（同法逐字搬） ──
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+LENSES = [('wsb', 'grd_wtc_ActPower_mean', 'L1 功率曲线 (风速-功率)', '风速 m/s (机舱风)', 'kW'),
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+ ('wsb', 'cp', 'L6 风能利用系数 Cp (风速-Cp)', '风速 m/s', 'Cp'),
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+ ('wsb', 'lam', 'L5 叶尖速比 λ (风速-λ)', '风速 m/s', 'λ'),
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+ ('grb', 'tq', 'L4 转矩-转速 (发电机侧)', '发电机转速 rpm', 'kNm'),
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+ ('pwb', 'tur_wtc_PitcPosA_mean', 'L2 功率-桨距 (控制律/削峰)', '功率 kW', '°'),
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+ ('pwb', 'tur_wtc_GenRpm_mean', 'L3 功率-发电机转速 (饱和点)', '功率 kW', 'rpm'),
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+ ('pwb', 'p3', 'L2b 三叶桨距极差 (集距/不平衡)', '功率 kW', '°'),
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+ ('pwb', 'ratio', 'L7 转速比 gen/rot (传动链)', '功率 kW', '—')]
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+
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+CFG = farm(); ST = pathlib.Path(CFG['store'])
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+
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+_WIN_BUSY: dict = {'sysmx': set(), 'curves': set(), 'm9': set()}
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+
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+_WIN_CACHE: dict = {'sysmx': {}, 'curves': {}, 'm9': {}}
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+
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+_WIN_ERR: dict = {'sysmx': {}, 'curves': {}, 'm9': {}}
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+
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+
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+
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+def curves_of(win):
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+ """→ (七镜头分箱件 或 None, pending)。按窗重算（干净窗就是正式产物本身）。"""
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+ from src.windscada.perf import curves as _cv
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+ a, b = span_of(win)
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+ if (a, b) == (_cv.WIN[0], '2025-12-31'): # 与正式产物的判别窗一致 ⇒ 直接用产物, 不重算
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+ import pandas as _pd
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+ return _pd.read_parquet(ST / 'curve_lenses.parquet'), False
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+ st = _win_get('curves', win, lambda: _cv.build_store(CFG, span=(a, b), write=False))
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+ return st, st is None
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+
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+
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+def curve_view(win='2025H2'):
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+ """特性曲线多镜头 (SOP §4.6c): fleet 中位+四分位带 + 过绝对锚的离群台曲线.
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+
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+ ★2026-09-21 用户令「发电性能随时间窗变化」: 七镜头**按所选时间窗重算**（首次后台算，先回 pending），
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+ 7 张月度时序图按所选窗的月份过滤。原口径（2025H2 干净判别窗）仍可作为窗之一被选中，
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+ 选到它时直接用正式产物，不重算。
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+ """
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+ import pandas as pd
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+ from src.windscada.perf import curves as cv
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+ a, b = span_of(win)
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+ ms = months_of(win)
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+ store, pending = curves_of(win)
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+ if pending:
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+ return dict(building=True, win=win, span=[a, b], months=ms,
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+ note=f'正在按所选时间窗 {a} ~ {b} 重算七镜头曲线（首次约 10~45 秒），完成后自动刷新。'
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+ f'期间下方月度时序图已按所选窗过滤，可直接看。')
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+ wlabel = f'{a} ~ {b}'
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+ figs = []
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+ for xc, yc, title, xlab, unit in LENSES:
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+ r = cv.lens(xc, yc, store_df=store, win_label=wlabel)
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+ if not r: continue
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+ outs = sorted(r['离群'].items(), key=lambda kv: -abs(kv[1]['z']))[:3]
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+ a = r['anchor']
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+ series = [dict(name='全场中位', vals=r['fleet'])]
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+ series += [dict(name=f"{t.replace('WTG','')}# {v['resid']:+.4g}{a['单位']}", vals=r['per_t'][t]) for t, v in outs]
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+ figs.append(dict(kind='multiline', title=title, unit=unit, months=[f"{x:g}" for x in r['x']],
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+ series=series, xlab=xlab,
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+ note=(f"显著门 |残差|≥{a['门']}{a['单位']} ({a['说明']}) ∧ |z|≥3 → 离群 "
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+ f"{'/'.join(t.replace('WTG','')+'#' for t,_ in outs) if outs else '无'}"
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+ f" ｜ 灰域=全场四分位, 逐档中位聚合, 已剥限电(只正常发电态)"
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+ f" ｜ 样本 {r['n_total']:,} 个10min点 / {r['n_turbines']} 台 / 最小档 {r['n_min_bin']:,}"
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+ f" ｜ 时间窗 {r['win']}（随所选时间窗）"),
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+ band=dict(q1=r['q1'], q3=r['q3'])))
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+ # 残差视图 (§4.6c④ per机必算同型残差): 绝对量尺度上四分位带只有几个像素, 残差面才看得见
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+ if outs:
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+ rs = [dict(name=f"{t.replace('WTG','')}# {v['resid']:+.4g}{a['单位']}",
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+ vals=[None if (r['per_t'][t][i] is None or r['fleet'][i] is None) else round(r['per_t'][t][i] - r['fleet'][i], 4)
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+ for i in range(len(r['x']))]) for t, v in outs]
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+ q1d = [round(r['q1'][i] - r['fleet'][i], 4) for i in range(len(r['x']))]
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+ q3d = [round(r['q3'][i] - r['fleet'][i], 4) for i in range(len(r['x']))]
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+ figs.append(dict(kind='multiline', title=title.split(' (')[0] + ' · 同型机群残差 (本台−全场中位)', unit=unit,
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+ months=[f"{x:g}" for x in r['x']], series=rs, xlab=xlab,
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+ thresholds=[dict(v=a['门'], label=f"显著门 +{a['门']}{a['单位']}"), dict(v=-a['门'], label='')],
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+ band=dict(q1=q1d, q3=q3d),
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+ note=(f"虚线=物理绝对锚 ±{a['门']}{a['单位']} ({a['说明']}); 灰域=全场四分位残差带; 出带且过锚才算离群"
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+ f" ｜ 样本 {r['n_total']:,} 点 / {r['n_turbines']} 台 ｜ 时间窗 {r['win']}")))
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+ # ---- 时序件: 控制参数月度 (M9b) + 偏航动态月度 (M12) ----
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+ def _ts(path, val, title, unit, xlab, picks=None, note='', thr=None):
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+ f = ST / path
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+ if not f.exists(): return None
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+ d = pd.read_parquet(f)
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+ if val not in d.columns: return None
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+ piv = d.pivot_table(index='month', columns='turbine', values=val)
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+ # ★2026-09-21 用户令: 月度时序图按**所选时间窗**的月份过滤（月度件无法按日切，如实写"按月取整"）
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+ if ms:
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+ piv = piv.reindex([m for m in [str(x) for x in piv.index] if m in set(ms)])
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+ if not len(piv): return None
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+ msx = [str(x) for x in piv.index]
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+ med = piv.median(axis=1)
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+ dev = (piv.sub(med, axis=0)).abs().mean()
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+ picks = picks or list(dev.sort_values(ascending=False).head(3).index)
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+ series = [dict(name='全场中位', vals=[None if v != v else round(float(v), 3) for v in med])]
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+ series += [dict(name=t.replace('WTG', '') + '#', vals=[None if v != v else round(float(v), 3) for v in piv[t]])
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+ for t in picks if t in piv.columns]
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+ # 样本量与窗随图走 (2026-08-28 门禁 F1): 7 张时序图原来只有结论没有依据规模,
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+ # 违反第一性原理②"Sample size declared"。逐月×台的非空格数即样本量。
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+ _n = int(piv.notna().to_numpy().sum())
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+ _nt = int(piv.shape[1])
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+ note2 = (note + f" ｜ 样本 {_n:,} 个月×台 / {_nt} 台 / {len(msx)} 个月"
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+ f" ｜ 时间窗 {msx[0]}~{msx[-1]}（月度聚合，随所选时间窗·按月取整）") if msx else note
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+ return dict(kind='multiline', title=title, unit=unit, months=msx, series=series, xlab=xlab,
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+ note=note2, thresholds=thr or [],
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+ band=dict(q1=[None if v != v else round(float(v), 3) for v in piv.quantile(0.25, axis=1)],
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+ q3=[None if v != v else round(float(v), 3) for v in piv.quantile(0.75, axis=1)]))
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+ for args in (
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+ ('control_monthly.parquet', 'p_cap', '时序① 满发功率封顶 月度 (取每月高位稳定值; 阶跃=配置变更)', 'kW', '月', None,
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+ '灰域=全场四分位; 参数级分组见发电性能页 (4175/4200/4225 三组); 阶跃=配置变更, 平移=工况'),
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+ ('control_monthly.parquet', 'w_cap', '时序② 转速封顶 月度 (取每月高位稳定值)', 'rpm', '月', None, '两轴独立分组 (1672/1680)'),
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+ ('control_monthly.parquet', 'pitch_rated', '时序③ 额定段桨距角 月度 (标定漂移)', '°', '月',
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+ ['WTG03', 'WTG34', 'WTG19'], '离群台=桨距调度同档差 top3'),
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+ ('yaw_dynamic_monthly.parquet', 'err_sd', '时序④ 对风散布 σ 月度 (原始, 未清洗)', '°', '月',
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+ ['WTG08', 'WTG16', 'WTG04'], '三台19个月全程高 → 非发作型; 清洗后降至5-7°, 判为机舱位置通道拖偏(A类数据质量)非对风故障'),
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+ ('yaw_dynamic_monthly.parquet', 'travel_day', '时序⑤ 偏航行程 月度 (抗采样物理量)', '°/日', '月', None,
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+ '行程=活动量代理, 非真磨损量; 与状态位次数互核'),
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+ ('yaw_dynamic_monthly.parquet', 'twist_span', '时序⑥ 扭缆角月跨度 (ScYawPos 累计位置)', '°', '月', None, '解缆动作后回零'),
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+ ('yaw_dynamic_monthly.parquet', 'pump_med', '时序⑦ 偏航泵压 月度 (小站泵压)', 'bar', '月', None, '全场极齐 → 无泵压异常'),
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+ ):
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+ f = _ts(*args)
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+ if f: figs.append(f)
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+ return dict(figs=figs, physics=cv.physics_check(),
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+ note=('镜头口径 (SOP §4.6c): X轴优先功率(直测干净量); 机舱风 self-ref → 只判形状/相对, '
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+ '绝对达成率须现场测风; per机异常必算同型机群残差(禁眼估); 工况段筛选=剔除0kW与低转速混合态档'))
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+
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+
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+
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+def curves(win: str = '2026年') -> dict[str, Any]:
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+ """详情层口径的薄包装（`curve_view(q.get('win') or '2026年')`）。"""
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+ return curve_view(win)
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