fix(web): 自动刷新保留 K 线视窗；威科夫与图表增量更新

自动刷新改用 tail update 与 scrollToPosition 恢复视窗，避免 setData 后跳到最右；拆分 chart_tv 模块并扩展 analyze/recent API。同步威科夫分析、pipeline 增量构建及相关策略与配置。

Co-authored-by: Cursor <cursoragent@cursor.com>

crypto_wyckoff/rules/cycle_rules.py

@@ -0,0 +1,126 @@
+"""Cycle classification rules (monthly / weekly)."""
+
+from __future__ import annotations
+
+from typing import Any
+
+from crypto_wyckoff.domain_models import WyckoffCycle
+from crypto_wyckoff.rules.base import RuleHit, WyckoffRule
+
+
+def _f(ctx: dict[str, Any], key: str, default: float = 0.0) -> float:
+    v = ctx.get("features", {}).get(key, default)
+    try:
+        return float(v) if v is not None else default
+    except (TypeError, ValueError):
+        return default
+
+
+class MarkupCycleRule(WyckoffRule):
+    rule_id = "cycle_markup"
+    category = "cycle"
+    timeframes = ("1M", "1w")
+
+    def evaluate(self, context: dict[str, Any]) -> RuleHit | None:
+        close = _f(context, "close")
+        ma20 = _f(context, "ma20")
+        ma60 = _f(context, "ma60")
+        ma120 = _f(context, "ma120")
+        adx = _f(context, "adx")
+        slope = _f(context, "ma60_slope")
+        if close > ma20 > ma60 and (ma60 >= ma120 or slope > 0) and adx >= 18:
+            conf = min(95.0, 55 + adx + (10 if close > ma120 else 0))
+            return RuleHit(
+                rule_id=self.rule_id,
+                cycle=WyckoffCycle.MARKUP.value,
+                confidence=conf,
+                score=conf,
+                reasons=["价格位于均线多头排列", f"ADX={adx:.1f}"],
+                metrics={"adx": adx, "slope": slope},
+            )
+        return None
+
+
+class MarkdownCycleRule(WyckoffRule):
+    rule_id = "cycle_markdown"
+    category = "cycle"
+    timeframes = ("1M", "1w")
+
+    def evaluate(self, context: dict[str, Any]) -> RuleHit | None:
+        close = _f(context, "close")
+        ma20 = _f(context, "ma20")
+        ma60 = _f(context, "ma60")
+        ma120 = _f(context, "ma120")
+        adx = _f(context, "adx")
+        slope = _f(context, "ma60_slope")
+        if close < ma20 < ma60 and (ma60 <= ma120 or slope < 0) and adx >= 18:
+            conf = min(95.0, 55 + adx + (10 if close < ma120 else 0))
+            return RuleHit(
+                rule_id=self.rule_id,
+                cycle=WyckoffCycle.MARKDOWN.value,
+                confidence=conf,
+                score=conf,
+                reasons=["价格位于均线空头排列", f"ADX={adx:.1f}"],
+                metrics={"adx": adx},
+            )
+        return None
+
+
+class AccumulationCycleRule(WyckoffRule):
+    rule_id = "cycle_accumulation"
+    category = "cycle"
+    timeframes = ("1M", "1w")
+
+    def evaluate(self, context: dict[str, Any]) -> RuleHit | None:
+        adx = _f(context, "adx")
+        range_pct = _f(context, "range_pct_60")
+        close = _f(context, "close")
+        ma120 = _f(context, "ma120")
+        vol_trend = _f(context, "volume_trend")
+        # Range-bound after decline: strictly at/below MA120 (mutually exclusive vs Distribution)
+        if adx < 22 and range_pct < 0.28 and close <= ma120:
+            conf = 60 + (10 if vol_trend > 0 else 0) + (10 if close < ma120 else 0)
+            return RuleHit(
+                rule_id=self.rule_id,
+                cycle=WyckoffCycle.ACCUMULATION.value,
+                confidence=min(90.0, conf),
+                score=min(90.0, conf),
+                reasons=["低趋势强度区间震荡", "疑似吸筹区间"],
+                metrics={"adx": adx, "range_pct_60": range_pct},
+            )
+        return None
+
+
+class DistributionCycleRule(WyckoffRule):
+    rule_id = "cycle_distribution"
+    category = "cycle"
+    timeframes = ("1M", "1w")
+
+    def evaluate(self, context: dict[str, Any]) -> RuleHit | None:
+        adx = _f(context, "adx")
+        range_pct = _f(context, "range_pct_60")
+        close = _f(context, "close")
+        ma120 = _f(context, "ma120")
+        vol_trend = _f(context, "volume_trend")
+        # Range-bound near highs: strictly above MA120 (mutually exclusive vs Accumulation)
+        if adx < 22 and range_pct < 0.28 and close > ma120:
+            conf = 60 + (10 if vol_trend < 0 else 0) + (10 if close > ma120 else 0)
+            return RuleHit(
+                rule_id=self.rule_id,
+                cycle=WyckoffCycle.DISTRIBUTION.value,
+                confidence=min(90.0, conf),
+                score=min(90.0, conf),
+                reasons=["高位低趋势震荡", "疑似派发区间"],
+                metrics={"adx": adx, "range_pct_60": range_pct},
+            )
+        return None
+
+
+def build_rules() -> list[WyckoffRule]:
+    # Order: trend cycles first (more decisive), then range cycles
+    return [
+        MarkupCycleRule(),
+        MarkdownCycleRule(),
+        AccumulationCycleRule(),
+        DistributionCycleRule(),
+    ]