feat(ECR-009): Crypto Wyckoff Screener 独立页（D/W/M）
移植 A_Share_DP 引擎；本地缓存与 60s tip；月线由日线 UTC 聚合；不碰主站 analyze/缠论叠层。 Co-authored-by: Cursor <cursoragent@cursor.com>
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jackyu66git
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"""Walk-forward Wyckoff phase/event annotations for chart overlay."""
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from __future__ import annotations
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from datetime import date
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from crypto_wyckoff.domain_models import OHLCVFrame, WyckoffCycle, WyckoffEvent, WyckoffPhase
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from crypto_wyckoff.cycle import CycleEngine
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from crypto_wyckoff.event import EventEngine
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from crypto_wyckoff.features import FeatureEngine
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from crypto_wyckoff.phase import PhaseEngine
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_MIN_BARS = {"1d": 40, "1w": 26, "1M": 18}
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_NOTABLE_EVENTS = {
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WyckoffEvent.PS.value,
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WyckoffEvent.SC.value,
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WyckoffEvent.AR.value,
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WyckoffEvent.ST.value,
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WyckoffEvent.SPRING.value,
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WyckoffEvent.TEST.value,
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WyckoffEvent.SOS.value,
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WyckoffEvent.LPS.value,
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WyckoffEvent.JUMP.value,
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WyckoffEvent.BACKUP.value,
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WyckoffEvent.BC.value,
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WyckoffEvent.UTAD.value,
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WyckoffEvent.SOW.value,
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WyckoffEvent.LPSY.value,
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}
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def _slice_frame(frame: OHLCVFrame, end_idx: int) -> OHLCVFrame:
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n = end_idx + 1
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return OHLCVFrame(
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ts_code=frame.ts_code,
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timeframe=frame.timeframe,
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trade_dates=frame.trade_dates[:n],
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open=frame.open[:n],
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high=frame.high[:n],
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low=frame.low[:n],
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close=frame.close[:n],
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volume=frame.volume[:n],
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amount=frame.amount[:n] if frame.amount else [],
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)
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def _compress_phases(points: list[tuple[str, str]]) -> list[dict]:
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"""points: [(date_iso, phase), ...] → segments."""
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if not points:
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return []
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segs: list[dict] = []
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start, phase = points[0]
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prev = start
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for d, p in points[1:]:
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if p != phase:
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segs.append({"start": start, "end": prev, "phase": phase})
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start, phase = d, p
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prev = d
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segs.append({"start": start, "end": prev, "phase": phase})
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return segs
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def annotate_frame(frame: OHLCVFrame, step: int | None = None) -> dict:
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"""Pure annotation: phase bands + event markers + latest levels.
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``step`` defaults by timeframe to keep interactive charts snappy.
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"""
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tf = frame.timeframe
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min_bars = _MIN_BARS.get(tf, 30)
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if step is None:
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step = {"1d": 2, "1w": 1, "1M": 1}.get(tf, 2)
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empty = {
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"phases": [],
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"events": [],
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"levels": {},
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"bars": len(frame),
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"timeframe": tf,
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}
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if frame.empty or len(frame) < min_bars:
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return empty
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feat_eng = FeatureEngine()
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cycle_eng = CycleEngine()
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phase_eng = PhaseEngine()
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event_eng = EventEngine()
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phase_points: list[tuple[str, str]] = []
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events: list[dict] = []
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last_event: str | None = None
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levels: dict = {}
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# Ensure last bar is always evaluated
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indices = list(range(min_bars - 1, len(frame), step))
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if indices[-1] != len(frame) - 1:
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indices.append(len(frame) - 1)
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for i in indices:
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sub = _slice_frame(frame, i)
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f = feat_eng.run(sub, tf)
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c = cycle_eng.run(f, tf)
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p = phase_eng.run(c, f, tf)
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e = event_eng.run(c, p, f, tf)
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d = str(frame.trade_dates[i])[:10]
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phase = p.payload.get("phase") or WyckoffPhase.NONE.value
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phase_points.append((d, phase))
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cur = e.payload.get("current_event") or WyckoffEvent.NONE.value
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if cur in _NOTABLE_EVENTS and cur != last_event:
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events.append({
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"date": d,
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"event": cur,
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"price": float(frame.close[i]),
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"low": float(frame.low[i]),
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"high": float(frame.high[i]),
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})
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last_event = cur
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elif cur == WyckoffEvent.NONE.value:
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last_event = None
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if i == len(frame) - 1 and not f.payload.get("insufficient"):
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levels = {
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k: f.payload.get(k)
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for k in (
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"range_high", "range_low", "ma20", "ma60",
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"swing_high", "swing_low", "close",
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)
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if f.payload.get(k) is not None
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}
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levels["phase"] = phase
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levels["cycle"] = c.payload.get("cycle")
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levels["current_event"] = cur
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return {
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"phases": _compress_phases(phase_points),
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"events": events,
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"levels": levels,
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"bars": len(frame),
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"timeframe": tf,
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}
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_RANGE_CYCLES = {
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WyckoffCycle.ACCUMULATION.value,
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WyckoffCycle.RE_ACCUMULATION.value,
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WyckoffCycle.DISTRIBUTION.value,
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WyckoffCycle.RE_DISTRIBUTION.value,
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}
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def _build_range_zones(
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price_frame: OHLCVFrame,
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cycle_segs: list[dict],
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levels: dict | None = None,
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) -> list[dict]:
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"""Build price boxes (high/low × date span) for accum/distrib ranges."""
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if price_frame.empty:
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return []
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dates = [str(d)[:10] for d in price_frame.trade_dates]
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highs = price_frame.high
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lows = price_frame.low
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zones: list[dict] = []
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for seg in cycle_segs or []:
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cy = seg.get("cycle")
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if cy not in _RANGE_CYCLES:
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continue
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start, end = seg["start"], seg["end"]
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idxs = [i for i, d in enumerate(dates) if start <= d <= end]
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if not idxs:
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# weekly bar date may sit between daily bars — take nearest window
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i0 = next((i for i, d in enumerate(dates) if d >= start), None)
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if i0 is None:
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continue
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i1 = next((i for i, d in enumerate(dates) if d > end), len(dates)) - 1
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idxs = list(range(i0, max(i0, i1) + 1))
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if not idxs:
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continue
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# pad short weekly hits to at least ~1 week of dailies for visibility
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if len(idxs) < 5 and idxs[-1] + 1 < len(dates):
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extra = min(5 - len(idxs), len(dates) - 1 - idxs[-1])
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idxs = list(range(idxs[0], idxs[-1] + 1 + max(0, extra)))
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hi = max(highs[i] for i in idxs)
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lo = min(lows[i] for i in idxs)
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if hi <= lo:
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continue
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zones.append({
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"kind": cy,
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"start": dates[idxs[0]],
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"end": dates[idxs[-1]],
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"high": float(hi),
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"low": float(lo),
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"current": False,
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})
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# Always expose the latest trading-range box from feature snapshot
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levels = levels or {}
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rh, rl = levels.get("range_high"), levels.get("range_low")
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if rh is not None and rl is not None and float(rh) > float(rl):
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look = min(60, len(dates))
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cy = levels.get("cycle") or "Unknown"
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if cy not in _RANGE_CYCLES:
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# Phase B/C in a range → treat as accumulation-style TR for display
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ph = levels.get("phase") or ""
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if ph in ("A", "B", "C"):
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cy = WyckoffCycle.ACCUMULATION.value
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elif ph in ("D", "E") and float(levels.get("close") or 0) < float(rh):
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cy = WyckoffCycle.ACCUMULATION.value
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else:
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cy = "Range"
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zones.append({
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"kind": cy,
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"start": dates[-look],
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"end": dates[-1],
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"high": float(rh),
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"low": float(rl),
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"current": True,
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})
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return zones
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def annotate_symbol(
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ts_code: str,
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freq: str,
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end_date: date | None = None,
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lookback: int = 180,
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) -> dict:
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"""IO + annotate for one symbol (used by API).
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For daily charts, phase bands come from **weekly** structure (Wyckoff
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primary timeframe), while event markers / levels come from daily.
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"""
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from crypto_wyckoff.io import latest_daily_trade_date, load_frames_batch
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if freq not in ("1d", "1w", "1M"):
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raise ValueError(f"unsupported freq: {freq}")
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ed = end_date or latest_daily_trade_date()
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empty = {
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"ts_code": ts_code,
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"freq": freq,
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"phases": [],
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"events": [],
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"levels": {},
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"zones": [],
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"bars": 0,
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"phase_source": freq,
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}
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if ed is None:
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return empty
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if freq == "1d":
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daily_frames = load_frames_batch("1d", ed, lookback, ts_codes=[ts_code])
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weekly_frames = load_frames_batch("1w", ed, max(60, lookback // 3), ts_codes=[ts_code])
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daily = daily_frames.get(ts_code)
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weekly = weekly_frames.get(ts_code)
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if daily is None:
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return empty
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d_ann = annotate_frame(daily)
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w_ann = annotate_frame(weekly) if weekly is not None else {"phases": []}
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cycles = _cycle_segments(weekly) if weekly is not None else []
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levels = d_ann.get("levels") or {}
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# Prefer weekly cycle on the latest levels for zone labeling
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if cycles:
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levels = {**levels, "cycle": cycles[-1].get("cycle") or levels.get("cycle")}
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# latest non-None weekly phase
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for p in reversed(w_ann.get("phases") or []):
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if p.get("phase") not in (None, "None"):
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levels = {**levels, "phase": p["phase"]}
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break
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return {
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"ts_code": ts_code,
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"freq": freq,
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"end_date": ed.isoformat(),
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"phases": w_ann.get("phases") or [],
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"events": d_ann.get("events") or [],
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"levels": d_ann.get("levels") or {},
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"zones": _build_range_zones(daily, cycles, levels),
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"bars": d_ann.get("bars", 0),
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"phase_source": "1w",
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"cycles": cycles,
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}
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frames = load_frames_batch(freq, ed, lookback, ts_codes=[ts_code])
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frame = frames.get(ts_code)
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if frame is None:
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return empty
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out = annotate_frame(frame)
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out["ts_code"] = ts_code
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out["freq"] = freq
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out["end_date"] = ed.isoformat()
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out["phase_source"] = freq
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out["cycles"] = _cycle_segments(frame)
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out["zones"] = _build_range_zones(frame, out["cycles"], out.get("levels") or {})
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if freq == "1M":
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# Monthly chart: cycle bands are more meaningful than phase
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if not any(p.get("phase") not in (None, "None") for p in out["phases"]):
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out["phases"] = [
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{"start": c["start"], "end": c["end"], "phase": c["cycle"]}
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for c in out["cycles"]
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if c.get("cycle") and c["cycle"] != "Unknown"
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]
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return out
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def _cycle_segments(frame: OHLCVFrame, step: int | None = None) -> list[dict]:
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"""Walk-forward cycle labels compressed to segments."""
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tf = frame.timeframe
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min_bars = _MIN_BARS.get(tf, 30)
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if step is None:
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step = {"1d": 3, "1w": 1, "1M": 1}.get(tf, 2)
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if frame.empty or len(frame) < min_bars:
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return []
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feat_eng = FeatureEngine()
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cycle_eng = CycleEngine()
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points: list[tuple[str, str]] = []
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indices = list(range(min_bars - 1, len(frame), step))
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if indices[-1] != len(frame) - 1:
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indices.append(len(frame) - 1)
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for i in indices:
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sub = _slice_frame(frame, i)
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f = feat_eng.run(sub, tf)
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c = cycle_eng.run(f, tf)
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points.append((str(frame.trade_dates[i])[:10], c.payload.get("cycle") or "Unknown"))
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segs = _compress_phases(points)
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return [{"start": s["start"], "end": s["end"], "cycle": s["phase"]} for s in segs]
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