From f92eef11fb50d583e31e6b3d976de48a26b0463a Mon Sep 17 00:00:00 2001
From: YuWuKunCheng <youwukuncheng@163.com>
Date: Mon, 25 May 2026 02:16:35 +0800
Subject: [PATCH] =?UTF-8?q?=E7=AC=AC=E4=B8=80=E7=89=88?=
MIME-Version: 1.0
Content-Type: text/plain; charset=UTF-8
Content-Transfer-Encoding: 8bit

---
 btcusd-300-1761327300-1776327900.nb   |  Bin 0 -> 2400144 bytes
 btcusd-300-1777649100-1778398800.nb   |  Bin 0 -> 120000 bytes
 chan.py                               | 4184 +++++++++++++++++++++++++
 chanlun/Cargo.toml                    |   10 +
 chanlun/src/algorithm/bi.rs           |  821 +++++
 chanlun/src/algorithm/divergence.rs   |  139 +
 chanlun/src/algorithm/hub.rs          |  348 ++
 chanlun/src/algorithm/mod.rs          |    4 +
 chanlun/src/algorithm/segment.rs      | 1726 ++++++++++
 chanlun/src/business/bsp.rs           |  181 ++
 chanlun/src/business/mod.rs           |    4 +
 chanlun/src/business/multi_frame.rs   |  148 +
 chanlun/src/business/observer.rs      |  503 +++
 chanlun/src/business/synthesizer.rs   |  115 +
 chanlun/src/config.rs                 |  338 ++
 chanlun/src/indicators/kdj.rs         |  204 ++
 chanlun/src/indicators/macd.rs        |  149 +
 chanlun/src/indicators/mod.rs         |   21 +
 chanlun/src/indicators/rsi.rs         |  180 ++
 chanlun/src/kline/bar.rs              |  244 ++
 chanlun/src/kline/chan_kline.rs       |  601 ++++
 chanlun/src/kline/mod.rs              |    2 +
 chanlun/src/lib.rs                    |   11 +
 chanlun/src/main.rs                   |   34 +
 chanlun/src/structure/dash_line.rs    |  771 +++++
 chanlun/src/structure/feat_fractal.rs |   24 +
 chanlun/src/structure/fractal_obj.rs  |  173 +
 chanlun/src/structure/mod.rs          |    4 +
 chanlun/src/structure/segment_feat.rs |  254 ++
 chanlun/src/types/bsp_type.rs         |   99 +
 chanlun/src/types/direction.rs        |  108 +
 chanlun/src/types/fractal.rs          |  109 +
 chanlun/src/types/gap.rs              |   51 +
 chanlun/src/types/mod.rs              |    9 +
 chanlun/src/utils/datetime.rs         |   27 +
 chanlun/src/utils/format.rs           |   14 +
 chanlun/src/utils/mod.rs              |    5 +
 37 files changed, 11615 insertions(+)
 create mode 100644 btcusd-300-1761327300-1776327900.nb
 create mode 100644 btcusd-300-1777649100-1778398800.nb
 create mode 100644 chan.py
 create mode 100644 chanlun/Cargo.toml
 create mode 100644 chanlun/src/algorithm/bi.rs
 create mode 100644 chanlun/src/algorithm/divergence.rs
 create mode 100644 chanlun/src/algorithm/hub.rs
 create mode 100644 chanlun/src/algorithm/mod.rs
 create mode 100644 chanlun/src/algorithm/segment.rs
 create mode 100644 chanlun/src/business/bsp.rs
 create mode 100644 chanlun/src/business/mod.rs
 create mode 100644 chanlun/src/business/multi_frame.rs
 create mode 100644 chanlun/src/business/observer.rs
 create mode 100644 chanlun/src/business/synthesizer.rs
 create mode 100644 chanlun/src/config.rs
 create mode 100644 chanlun/src/indicators/kdj.rs
 create mode 100644 chanlun/src/indicators/macd.rs
 create mode 100644 chanlun/src/indicators/mod.rs
 create mode 100644 chanlun/src/indicators/rsi.rs
 create mode 100644 chanlun/src/kline/bar.rs
 create mode 100644 chanlun/src/kline/chan_kline.rs
 create mode 100644 chanlun/src/kline/mod.rs
 create mode 100644 chanlun/src/lib.rs
 create mode 100644 chanlun/src/main.rs
 create mode 100644 chanlun/src/structure/dash_line.rs
 create mode 100644 chanlun/src/structure/feat_fractal.rs
 create mode 100644 chanlun/src/structure/fractal_obj.rs
 create mode 100644 chanlun/src/structure/mod.rs
 create mode 100644 chanlun/src/structure/segment_feat.rs
 create mode 100644 chanlun/src/types/bsp_type.rs
 create mode 100644 chanlun/src/types/direction.rs
 create mode 100644 chanlun/src/types/fractal.rs
 create mode 100644 chanlun/src/types/gap.rs
 create mode 100644 chanlun/src/types/mod.rs
 create mode 100644 chanlun/src/utils/datetime.rs
 create mode 100644 chanlun/src/utils/format.rs
 create mode 100644 chanlun/src/utils/mod.rs

diff --git a/btcusd-300-1761327300-1776327900.nb b/btcusd-300-1761327300-1776327900.nb
new file mode 100644
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diff --git a/chan.py b/chan.py
new file mode 100644
index 0000000..9030f78
--- /dev/null
+++ b/chan.py
@@ -0,0 +1,4184 @@
+"""
+MIT License
+
+Copyright (c) 2026 YuYuKunKun
+
+Permission is hereby granted, free of charge, to any person obtaining a copy
+of this software and associated documentation files (the "Software"), to deal
+in the Software without restriction, including without limitation the rights
+to use, copy, modify, merge, publish, distribute, sublicense, and/or sell
+copies of the Software, and to permit persons to whom the Software is
+furnished to do so, subject to the following conditions:
+
+The above copyright notice and this permission notice shall be included in all
+copies or substantial portions of the Software.
+
+THE SOFTWARE IS PROVIDED "AS IS", WITHOUT WARRANTY OF ANY KIND, EXPRESS OR
+IMPLIED, INCLUDING BUT NOT LIMITED TO THE WARRANTIES OF MERCHANTABILITY,
+FITNESS FOR A PARTICULAR PURPOSE AND NONINFRINGEMENT. IN NO EVENT SHALL THE
+AUTHORS OR COPYRIGHT HOLDERS BE LIABLE FOR ANY CLAIM, DAMAGES OR OTHER
+LIABILITY, WHETHER IN AN ACTION OF CONTRACT, TORT OR OTHERWISE, ARISING FROM,
+OUT OF OR IN CONNECTION WITH THE SOFTWARE OR THE USE OR OTHER DEALINGS IN THE
+SOFTWARE.
+"""
+# -*- coding: utf-8 -*-
+# @Time    : 2024/10/15 16:45
+# @Author  : YuYuKunKun
+# @File    : chan.py
+
+import json
+import math
+import struct
+import sys
+from dataclasses import dataclass, field
+from datetime import datetime
+from enum import Enum
+from functools import lru_cache
+from pathlib import Path
+from typing import (
+    List,
+    Self,
+    Optional,
+    Tuple,
+    final,
+    Dict,
+    Any,
+    Union,
+    Sequence,
+    Callable,
+)
+
+from pydantic import BaseModel, Field, model_validator, ValidationError, field_validator
+from termcolor import colored
+
+
+__all__ = [
+    "K线",
+    "K线合成器",
+    "中枢",
+    "买卖点",
+    "买卖点类型",
+    "分型",
+    "分型结构",
+    "基础买卖点",
+    "平滑异同移动平均线",
+    "指标",
+    "测试_读取数据",
+    "特征分型",
+    "相对强弱指数",
+    "相对方向",
+    "立体分析器",
+    "笔",
+    "线段",
+    "线段特征",
+    "缠论K线",
+    "缠论配置",
+    "缺口",
+    "背驰分析",
+    "虚线",
+    "观察者",
+    "转化为时间戳",
+    "转化为时间戳_数字",
+    "随机指标",
+]
+
+
+class 买卖点类型(str, Enum):
+    # 传统分类
+    一买 = "一买"
+    一卖 = "一卖"
+    二买 = "二买"
+    二卖 = "二卖"
+    三买 = "三买"
+    三卖 = "三卖"
+    # 缠论六类买卖点
+    T1买 = "T1买"
+    T1卖 = "T1卖"
+    T1P买 = "T1P买"
+    T1P卖 = "T1P卖"
+    T2买 = "T2买"
+    T2卖 = "T2卖"
+    T2S买 = "T2S买"
+    T2S卖 = "T2S卖"
+    T3A买 = "T3A买"
+    T3A卖 = "T3A卖"
+    T3B买 = "T3B买"
+    T3B卖 = "T3B卖"
+
+    def __str__(self) -> str:
+        return self.name
+
+    def __repr__(self) -> str:
+        return self.name
+
+    @property
+    def 是买点(self) -> bool:
+        return "买" in self.value
+
+    @property
+    def 是卖点(self) -> bool:
+        return "卖" in self.value
+
+
+class 基础买卖点:
+    def __init__(self, 类型: 买卖点类型, 当前K线: "K线", 买卖点分型: "分型", 备注: str, 中枢破位值: float):
+        self.备注: str = 备注
+        self.类型 = 类型
+        self.买卖点分型 = 买卖点分型
+        self.买卖点K线 = 买卖点分型.中  # .镜像
+        self.__当前K线: "K线" = 当前K线
+        self.失效K线: Optional["K线"] = None
+        self.终结K线: Optional["K线"] = None  # 卖出 or 买入
+        self.__破位值 = 中枢破位值
+        self.结构 = None
+
+    def __str__(self):
+        return f"{self.类型.value}<{self.买卖点K线}, {self.偏移}, {self.失效偏移}>"
+
+    def __repr__(self):
+        return f"{self.类型.value}<{self.买卖点K线}, {self.偏移}, {self.失效偏移}>"
+
+    @property
+    def 当前K线(self):
+        return self.__当前K线
+
+    @property
+    def 破位值(self) -> float:
+        return self.__破位值
+
+    @property
+    def 偏移(self) -> int:
+        return self.__当前K线.序号 - self.买卖点K线.序号
+
+    @property
+    def 失效偏移(self) -> int:
+        if self.失效K线 is None:
+            return -1
+        return self.失效K线.序号 - self.买卖点K线.序号
+
+    @property
+    def 有效性(self) -> bool:
+        return self.失效K线 is not None
+
+    @property
+    def 与MACD柱子匹配(self) -> bool:
+        return self.买卖点K线.与MACD柱子匹配
+
+    @property
+    def 与MACD柱子分型匹配(self) -> bool:
+        return self.买卖点分型.与MACD柱子分型匹配
+
+
+@final
+class 买卖点(基础买卖点):
+    @classmethod
+    def 一卖点(cls, 买卖点分型: "分型", 当前K线: "K线", 标识: str, 备注: str, 中枢破位值: float) -> "买卖点":
+        return 买卖点(备注=备注, 类型=买卖点类型.一卖, 买卖点分型=买卖点分型, 当前K线=当前K线, 中枢破位值=中枢破位值)
+
+    @classmethod
+    def 一买点(cls, 买卖点分型: "分型", 当前K线: "K线", 标识: str, 备注: str, 中枢破位值: float) -> "买卖点":
+        return 买卖点(备注=备注, 类型=买卖点类型.一买, 买卖点分型=买卖点分型, 当前K线=当前K线, 中枢破位值=中枢破位值)
+
+    @classmethod
+    def 二卖点(cls, 买卖点分型: "分型", 当前K线: "K线", 标识: str, 备注: str, 中枢破位值: float) -> "买卖点":
+        return 买卖点(备注=备注, 类型=买卖点类型.二卖, 买卖点分型=买卖点分型, 当前K线=当前K线, 中枢破位值=中枢破位值)
+
+    @classmethod
+    def 二买点(cls, 买卖点分型: "分型", 当前K线: "K线", 标识: str, 备注: str, 中枢破位值: float) -> "买卖点":
+        return 买卖点(备注=备注, 类型=买卖点类型.二买, 买卖点分型=买卖点分型, 当前K线=当前K线, 中枢破位值=中枢破位值)
+
+    @classmethod
+    def 三卖点(cls, 买卖点分型: "分型", 当前K线: "K线", 标识: str, 备注: str, 中枢破位值: float) -> "买卖点":
+        return 买卖点(备注=备注, 类型=买卖点类型.三卖, 买卖点分型=买卖点分型, 当前K线=当前K线, 中枢破位值=中枢破位值)
+
+    @classmethod
+    def 三买点(cls, 买卖点分型: "分型", 当前K线: "K线", 标识: str, 备注: str, 中枢破位值: float) -> "买卖点":
+        return 买卖点(备注=备注, 类型=买卖点类型.三买, 买卖点分型=买卖点分型, 当前K线=当前K线, 中枢破位值=中枢破位值)
+
+    @classmethod
+    def 生成买卖点(cls, 特征: str, 序号: str, 级别: str, 买卖点分型: "分型", 当前缠K: "缠论K线"):
+        买卖 = "买" if 买卖点分型.结构 in (分型结构.底, 分型结构.下) else "卖"
+        第几 = 序号
+        备注 = f"{特征}_{级别}{第几}{买卖}"
+        买卖点函数 = getattr(买卖点, f"{第几}{买卖}点")
+        破位值 = 买卖点分型.分型特征值
+        return 买卖点函数(买卖点分型, 当前缠K, 特征, 备注, 破位值)
+
+
+class datetime(datetime):  # 用于对齐C输出
+    def __str__(self):
+        return f"{int(self.timestamp())}"
+
+    def __repr__(self):
+        return f"{int(self.timestamp())}"
+
+
+def 转化为时间戳(ts: Union[str, datetime, int, float]) -> datetime:
+    """
+    将不同类型的时间戳转换为datetime对象（统一比较标准）
+    支持：datetime对象、字符串（"%Y-%m-%d %H:%M:%S"）、数值型时间戳（秒级）
+    可根据实际需求扩展时间格式（如毫秒级、仅日期等）
+    """
+    if isinstance(ts, datetime):
+        return ts
+    elif isinstance(ts, str):
+        # 自定义时间字符串格式，按需修改（如"%Y-%m-%d"）
+        return datetime.strptime(ts, "%Y-%m-%d %H:%M:%S")
+    elif isinstance(ts, (int, float)):
+        # 若为毫秒级时间戳，需除以1000：return datetime.fromtimestamp(ts / 1000)
+        return datetime.fromtimestamp(ts)
+    else:
+        raise TypeError(f"不支持的时间戳类型: {type(ts)}")
+
+
+def 转化为时间戳_数字(ts: Union[str, datetime, int, float]) -> int:
+    """
+    将不同类型的时间戳转换为datetime对象（统一比较标准）
+    支持：datetime对象、字符串（"%Y-%m-%d %H:%M:%S"）、数值型时间戳（秒级）
+    可根据实际需求扩展时间格式（如毫秒级、仅日期等）
+    """
+    if isinstance(ts, datetime):
+        return int(ts.timestamp())
+    elif isinstance(ts, str):
+        # 自定义时间字符串格式，按需修改（如"%Y-%m-%d"）
+        return int(datetime.strptime(ts, "%Y-%m-%d %H:%M:%S").timestamp())
+    elif isinstance(ts, (int, float)):
+        # 若为毫秒级时间戳，需除以1000：return datetime.fromtimestamp(ts / 1000)
+        return int(ts)
+    else:
+        raise TypeError(f"不支持的时间戳类型: {type(ts)}")
+
+
+@final
+class 缠论配置(BaseModel):
+    标识: str = "bar"
+    缠K合并替换: bool = False  # False: 在原缠K上合并, True: 产出新缠K
+
+    笔内元素数量: int = 5  # 成BI最低长度
+
+    笔内相同终点取舍: bool = False  # 一笔终点存在多个终点时 True: last, False: first
+    笔内起始分型包含整笔: bool = False  # True: 一笔起始分型高低包含整支笔对象则不成笔, False: 只判断分型中间数据是否包含
+    笔内起始分型包含整笔_包括右: bool = False  # True: 将笔之武.右纳入
+    笔内原始K线包含整笔: bool = False  # 在非 [笔内起始分型包含整笔] 时判断原始K线包含整笔的情况
+
+    笔次级成笔: bool = False
+    笔弱化: bool = False
+    笔弱化_原始数量: int = 3
+    # 笔_必须对齐:bool = False # 强迫症设为True, 将获得无与伦比满足。。。
+
+    线段_非缺口下穿刺: bool = False  # True: 非缺口状态下[小阳, 少阴]时，存在贯穿伤与之后紧邻的三个元素有方向相同的线段时回退， 此举在当下是否有任何意义呢？
+    线段_特征序列忽视老阴老阳: bool = False  # True 不用严格的特征序列包含，也就是忽视缺口全以无缺口对待
+    线段_缺口后紧急修正: bool = True  # True: 当 线段_特征序列忽视老阴老阳=False 时生效，同样 线段_特征序列忽视老阴老阳=True时等同于修正武斗不异常，但只产出一个线段
+    线段_修正: bool = False  # 短路修正，不建议使用，但此修正将走势显示的更加清晰
+
+    线段内部中枢图显: bool = True
+    扩展线段_当下分析: bool = False  # 以当下来看的分析规则，否则以事后来看
+
+    分析笔: bool = True  # 是否计算BI
+    分析线段: bool = True  # 是否计算XD
+    分析扩展线段: bool = True  # 是否计算XD
+    分析笔中枢: bool = True  # 是否计算BI中枢
+    分析线段中枢: bool = True  # 是否计算XD中枢
+
+    手动终止: str = ""  # 2099-12-31 00:00:00
+    计算指标: bool = True
+    指标计算方式: str = "收"  # (开, 高, 低, 收, 高低均值, 高低收均值, 开高低收均值), 默认 收盘价
+    平滑异同移动平均线_快线周期: int = 13
+    平滑异同移动平均线_慢线周期: int = 31
+    平滑异同移动平均线_信号周期: int = 11
+
+    相对强弱指数_周期: int = 13
+    相对强弱指数_移动平均线周期: int = 13
+    相对强弱指数_超买阈值: float = 75.0
+    相对强弱指数_超卖阈值: float = 25.0
+
+    随机指标_RSV周期: int = 13
+    随机指标_K值平滑周期: int = 5
+    随机指标_D值平滑周期: int = 5
+    随机指标_超买阈值: float = 80.0
+    随机指标_超卖阈值: float = 20.0
+
+    图表展示: bool = True
+    推送K线: bool = True
+    推送笔: bool = True
+    推送线段: bool = True
+    推送中枢: bool = True
+
+    图表展示_笔: bool = True
+    图表展示_线段: bool = True
+    图表展示_扩展线段: bool = True
+    图表展示_扩展线段_线段: bool = True
+    图表展示_线段_线段: bool = True
+
+    图表展示_中枢_笔: bool = True
+    图表展示_中枢_线段: bool = True
+    图表展示_中枢_扩展线段: bool = True
+    图表展示_中枢_扩展线段_线段: bool = True
+    图表展示_中枢_线段_线段: bool = True
+    图表展示_中枢_线段内部: bool = True
+
+    买卖点偏移: int = 1  # 最大偏移
+    买卖点激进识别: bool = False  # 激进模式下将不考虑分型的完整性
+    买卖点与MACD柱强相关: bool = False  # True: 卖点需正值 买点需负值
+    买卖点错过误差值: float = 0.01  # 距离买卖点值上下之内
+
+    买卖点_指标模式: str = "配置"  # 【任意，配置，全量, 相对】 对应K线
+    买卖点_指标匹配_MACD: bool = True  # 买在负，卖在正！
+    买卖点_指标匹配_KDJ: bool = True  # 买在死叉之后，卖在金叉之后
+    买卖点_指标匹配_RSI: bool = True  # 买在均线之下，卖在均线之上
+
+    # --- 缠论六类买卖点识别参数 ---
+    买卖点_背离率: float = float("inf")  # T1/T1P背离率，默认无限大（不筛选）
+    买卖点_T2_回调阈值: float = 1.0  # T2回调幅度/突破振幅上限
+    买卖点_T2S_最大层级: int = 3  # T2S最大搜索深度
+    买卖点_峰值条件: bool = False  # T1是否要求突破中枢内所有元素的极值
+    买卖点_计算方式: str = "峰"  # "峰"=最大MACD柱绝对值, "面"=MACD柱面积
+    买卖点_计算线段BSP1: bool = True  # 是否启用T1/T1P识别
+    买卖点_处理BSP2: bool = True  # 是否启用T2/T2S识别
+    买卖点_计算线段BSP3: bool = True  # 是否启用T3A/T3B识别
+    买卖点_依赖T1: bool = True  # T2是否必须依赖T1
+    买卖点_中枢来源: str = "合"  # "实"/"虚"/"合" - 取线段的哪个内部中枢序列
+    买卖点_调试输出: bool = False  # 是否打印调试信息
+
+    线段内部背驰_MACD: bool = True
+    线段内部背驰_斜率: bool = True
+    线段内部背驰_测度: bool = True
+    线段内部背驰_模式: str = "相对"  # 【任意，配置，全量，相对】
+
+    加载文件路径: str = "./templates/last.nb"
+
+    @model_validator(mode="before")
+    def 兼容旧版本配置(cls, values: Dict[str, Any]) -> Dict[str, Any]:
+        """
+        自动兼容：
+        1. 旧版本少字段 → 使用默认值
+        2. 新版本多字段 → 自动忽略多余字段
+        3. 字段改名/删除 → 不报错
+        """
+        return values
+
+    @field_validator("*", mode="wrap")
+    def bool_parse_fallback_default(cls, value, handler, info):
+        field = cls.model_fields.get(info.field_name)
+        if not field:
+            return handler(value)
+        允许值 = {
+            "指标计算方式": ["开", "高", "低", "收", "高低均值", "高低收均值", "开高低收均值"],
+        }
+        # 字段类型 & 默认值
+        type_ = field.annotation
+        default = field.default
+        fname = info.field_name
+
+        try:
+            # --- 1. 处理 bool：使用内置 bool_parsing ---
+            if type_ is bool:
+                return handler(value)
+
+            # --- 2. 处理 int：使用内置 int_parsing ---
+            elif type_ is int:
+                return handler(value)
+
+            # --- 3. 处理指定 str：必须在允许列表内 ---
+            elif fname in 允许值:
+                result = handler(value)
+                if result not in 允许值[fname]:
+                    raise ValueError(f"值不在允许范围内: {result}")
+                return result
+
+            # 其他类型不处理
+            else:
+                return handler(value)
+
+        # 验证失败 → 统一用默认值
+        except ValidationError as e:
+            if "bool_parsing" in str(e) or "int_parsing" in str(e):
+                print(f"[{fname}] = {value} 解析失败，使用默认值：{default}")
+                return default
+            raise
+
+        # 字符串不在允许列表 → 用默认值
+        except ValueError as e:
+            print(f"[{fname}] = {value} {str(e)}，使用默认值：{default}")
+            return default
+
+    def to_dict(self) -> dict:
+        """对象 → 字典"""
+        return self.model_dump()
+
+    def to_json(self) -> str:
+        """对象 → JSON字符串"""
+        return self.model_dump_json(ensure_ascii=False, indent=2)
+
+    def 保存配置(self, path="缠论配置.json"):
+        with open(path, "w", encoding="utf-8") as f:
+            f.write(self.to_json())
+
+    @staticmethod
+    def 加载配置(path="缠论配置.json") -> "缠论配置":
+        with open(path, "r", encoding="utf-8") as f:
+            return 缠论配置.from_json(f.read())
+
+    @classmethod
+    def from_dict(cls, data: dict) -> "缠论配置":
+        """字典 → 对象（自动兼容缺失/多余字段）"""
+        return cls(**data)
+
+    @classmethod
+    def from_json(cls, json_str: str) -> "缠论配置":
+        """JSON字符串 → 对象"""
+        data = json.loads(json_str)
+        return cls.from_dict(data)
+
+    @classmethod
+    def 不推送(cls):
+        return cls(
+            线段内部中枢图显=False,
+            图表展示=False,
+            推送K线=False,
+            推送笔=False,
+            推送线段=False,
+            推送中枢=False,
+            图表展示_笔=False,
+            图表展示_线段=False,
+            图表展示_扩展线段=False,
+            图表展示_扩展线段_线段=False,
+            图表展示_线段_线段=False,
+            图表展示_中枢_笔=False,
+            图表展示_中枢_线段=False,
+            图表展示_中枢_扩展线段=False,
+            图表展示_中枢_扩展线段_线段=False,
+            图表展示_中枢_线段_线段=False,
+            图表展示_中枢_线段内部=False,
+        )
+
+    @classmethod
+    def 按序号重组字典(cls, 默认配置, 原始字典: dict) -> dict:
+        """
+        {
+            "1_open": 10,
+            "1_close": 11,
+            "2_open": 20,
+            "name": "BTC",    # 无法拆分
+            "time": 123456    # 无法拆分
+        }
+        转化为
+        {
+            1: {"open": 10, "close": 11},
+            2: {"open": 20},
+            "无法拆分": {
+                "name": "BTC",
+                "time": 123456
+            }
+        }
+
+        """
+
+        结果 = {}
+        无法拆分项 = {}
+
+        for 复合键, 值 in 原始字典.items():
+            # 尝试拆分
+            if "_" in 复合键:
+                序号部分, 键部分 = 复合键.split("_", 1)
+                try:
+                    序号 = int(序号部分)
+                    # 能正常拆分 → 分组
+                    if 序号 not in 结果:
+                        结果[序号] = {}
+                    结果[序号][键部分] = 值
+                except:
+                    # 格式异常 → 单独处理
+                    无法拆分项[复合键] = 值
+            else:
+                # 无下划线 → 无法拆分 → 单独存放
+                无法拆分项[复合键] = 值
+
+        # 把无法拆分的也放进结果顶层（你要的结构）
+        """if 无法拆分项:
+            结果["无法拆分"] = 无法拆分项"""
+        配置组 = dict()
+        for k, v in 结果.items():
+            配置组[k] = 默认配置.model_copy(
+                update=v,
+                deep=True,
+            )
+
+        return 配置组
+
+    def 对比(self, other: "缠论配置") -> dict:
+        """
+        比较当前配置与另一个配置的差异
+        返回: {
+            "字段名": {
+                "旧值": 当前配置的值,
+                "新值": 另一个配置的值
+            },
+            ...
+        }
+        仅当值不同时才包含该字段
+        """
+        diff_dict = {}
+        # 获取所有字段名
+        for field_name in self.model_fields.keys():
+            old_value = getattr(self, field_name)
+            new_value = getattr(other, field_name)
+            # 直接比较值（支持 None）
+            if old_value != new_value:
+                diff_dict[field_name] = new_value
+        return diff_dict
+
+
+class 相对方向(Enum):
+    向上 = "交叠向上"
+    向下 = "交叠向下"
+    向上缺口 = "向上缺口"
+    向下缺口 = "向下缺口"
+    衔接向上 = "衔接向上"  # 前终点为后起点
+    衔接向下 = "衔接向下"  # 前终点为后起点
+    顺 = "顺序包含"  # 左边包含右边
+    逆 = "逆序包含"  # 右边包含左边
+    同 = "相同包含"  # 左右两边数值相同
+
+    def __str__(self):
+        return f"相对方向.{self.name}"
+
+    def __repr__(self):
+        return f"相对方向.{self.name}"
+
+    def 翻转(self) -> "相对方向":  # 反转
+        match self:
+            case 相对方向.向上:
+                return 相对方向.向下
+            case 相对方向.向下:
+                return 相对方向.向上
+            case 相对方向.向下缺口:
+                return 相对方向.向上缺口
+            case 相对方向.向上缺口:
+                return 相对方向.向下缺口
+            case 相对方向.衔接向上:
+                return 相对方向.衔接向下
+            case 相对方向.衔接向下:
+                return 相对方向.衔接向上
+            case 相对方向.顺:
+                return 相对方向.逆
+            case 相对方向.逆:
+                return 相对方向.顺
+            case _:
+                return self
+
+    def 是否向上(self) -> bool:
+        return self in (相对方向.向上, 相对方向.向上缺口, 相对方向.衔接向上)
+
+    def 是否向下(self) -> bool:
+        return self in (相对方向.向下, 相对方向.向下缺口, 相对方向.衔接向下)
+
+    def 是否包含(self) -> bool:
+        return self in (相对方向.顺, 相对方向.逆, 相对方向.同)
+
+    def 是否缺口(self) -> bool:
+        return self in (相对方向.向下缺口, 相对方向.向上缺口)
+
+    def 是否衔接(self) -> bool:
+        return self in (相对方向.衔接向下, 相对方向.衔接向上)
+
+    @classmethod
+    def 分析(cls, 前高: float, 前低: float, 后高: float, 后低: float) -> "相对方向":
+        if 前高 == 后高 and 前低 == 后低:
+            return 相对方向.同
+
+        if 前高 > 后高 and 前低 > 后低:
+            if 前低 == 后高:
+                return 相对方向.衔接向下
+            if 前低 > 后高:
+                return 相对方向.向下缺口
+            return 相对方向.向下
+
+        if 前高 < 后高 and 前低 < 后低:
+            if 前高 == 后低:
+                return 相对方向.衔接向上
+            if 前高 < 后低:
+                return 相对方向.向上缺口
+            return 相对方向.向上
+
+        if 前高 >= 后高 and 前低 <= 后低:
+            return 相对方向.顺
+
+        if 前高 <= 后高 and 前低 >= 后低:
+            return 相对方向.逆
+        raise RuntimeError("无法识别的方向")
+
+
+class 分型结构(Enum):
+    上 = "三连向上"
+    下 = "三连向下"
+    顶 = "顶分型"
+    底 = "底分型"
+    散 = "向右扩散"
+
+    def __str__(self):
+        return self.name
+
+    def __repr__(self):
+        return self.name
+
+    @classmethod
+    def 分析(cls, 左, 中, 右, 可以逆序包含: bool = False, 忽视顺序包含: bool = False) -> Optional["分型结构"]:
+        左中关系 = 相对方向.分析(左.高, 左.低, 中.高, 中.低)
+        中右关系 = 相对方向.分析(中.高, 中.低, 右.高, 右.低)
+        # 左右关系 = 相对方向.分析(左.高, 左.低, 右.高, 右.低)
+        match (左中关系, 中右关系):
+            case (相对方向.顺, _):
+                if 忽视顺序包含:
+                    ...  # print("顺序包含 左中相对方向", 左, 中)
+                else:
+                    raise ValueError("顺序包含 左中相对方向", 左, 中)
+            case (_, 相对方向.顺):
+                if 忽视顺序包含:
+                    ...  # print("顺序包含 中右相对方向", 中, 右)
+                else:
+                    raise ValueError("顺序包含 中右相对方向", 中, 右)
+
+            case (相对方向.向上 | 相对方向.向上缺口 | 相对方向.衔接向上, 相对方向.向上 | 相对方向.向上缺口 | 相对方向.衔接向上):
+                return 分型结构.上
+            case (相对方向.向上 | 相对方向.向上缺口 | 相对方向.衔接向上, 相对方向.向下 | 相对方向.向下缺口 | 相对方向.衔接向下):
+                return 分型结构.顶
+            case (相对方向.向上 | 相对方向.向上缺口 | 相对方向.衔接向上, 相对方向.逆) if 可以逆序包含:
+                return 分型结构.上
+
+            case (相对方向.向下 | 相对方向.向下缺口 | 相对方向.衔接向下, 相对方向.向上 | 相对方向.向上缺口 | 相对方向.衔接向上):
+                return 分型结构.底
+            case (相对方向.向下 | 相对方向.向下缺口 | 相对方向.衔接向下, 相对方向.向下 | 相对方向.向下缺口 | 相对方向.衔接向下):
+                return 分型结构.下
+            case (相对方向.向下 | 相对方向.向下缺口 | 相对方向.衔接向下, 相对方向.逆) if 可以逆序包含:
+                return 分型结构.下
+
+            case (相对方向.逆, 相对方向.向上 | 相对方向.向上缺口 | 相对方向.衔接向上) if 可以逆序包含:
+                return 分型结构.底
+            case (相对方向.逆, 相对方向.向下 | 相对方向.向下缺口 | 相对方向.衔接向下) if 可以逆序包含:
+                return 分型结构.顶
+            case (相对方向.逆, 相对方向.逆) if 可以逆序包含:
+                return 分型结构.散
+            case _:
+                print("未匹配的关系", 可以逆序包含, 左中关系, 中右关系)
+        return None
+
+
+@final
+class 缺口:
+    def __init__(self, 高: float, 低: float) -> None:
+        assert 高 > 低
+        self.高 = 高
+        self.低 = 低
+
+    def __str__(self) -> str:
+        return f"缺口区间<{self.低:g} <=> {self.高:g}>"
+
+    def __repr__(self) -> str:
+        return f"缺口区间<{self.低:g} <=> {self.高:g}>"
+
+    @classmethod
+    def 居中截取区间(cls, 起点: float, 终点: float, 比例: float = 0.15) -> Optional[缺口]:
+        """
+        以原区间中心为基准，向两侧各取总长度的 `比例` 作为新区间。
+        如果新区间超出原边界则裁剪到边界；若完全越界则返回 None。
+
+        参数:
+            起点: 区间起始值
+            终点: 区间结束值
+            比例: 向两侧扩展的长度占总长度的比例（0~1 之间）
+
+        返回:
+            Optional[缺口]
+        """
+        if 起点 > 终点:
+            起点, 终点 = 终点, 起点
+        总长 = 终点 - 起点
+        偏移 = 总长 * 比例
+        中心 = (起点 + 终点) / 2
+        下界 = 中心 - 偏移
+        上界 = 中心 + 偏移
+
+        # 完全越界：新区间与原区间无重叠
+        if 下界 > 终点 or 上界 < 起点:
+            return None
+
+        # 裁剪到原边界
+        if 下界 < 起点:
+            下界 = 起点
+        if 上界 > 终点:
+            上界 = 终点
+
+        高 = max(下界, 上界)
+        低 = min(下界, 上界)
+        return 缺口(高, 低)
+
+
+class 指标:
+    @classmethod
+    def K线取值(cls, k线: "K线", 指标计算方式):
+        match 指标计算方式:
+            case "开":
+                return k线.开盘价
+            case "高":
+                return k线.高
+            case "低":
+                return k线.低
+            case "收":
+                return k线.收盘价
+            case "高低均值":
+                return (k线.高 + k线.低) / 2
+            case "高低收均值":
+                return (k线.高 + k线.低 + k线.收盘价) / 3
+            case "开高低收均值":
+                return (k线.高 + k线.低 + k线.开盘价 + k线.收盘价) / 4
+            case _:
+                return k线.收盘价
+
+
+class 平滑异同移动平均线(BaseModel):
+    # 原始数据
+    时间戳: datetime = Field(..., description="数据点对应的时间")
+    收盘价: float = Field(..., description="当前K线的收盘价格")
+
+    # 计算参数
+    快线周期: int = Field(12, gt=0, description="短期EMA周期，默认为12")
+    慢线周期: int = Field(26, gt=0, description="长期EMA周期，默认为26")
+    信号周期: int = Field(9, gt=0, description="信号线EMA周期，默认为9")
+
+    # 核心指标值
+    DIF: Optional[float] = Field(None, description="差离值 = EMA(快线) - EMA(慢线)")
+    DEA: Optional[float] = Field(None, description="信号线 = EMA(DIF, 信号周期)")
+    MACD柱: Optional[float] = Field(None, description="MACD柱状图 = (DIF - DEA) * 2")
+
+    # EMA中间值（用于增量计算）
+    快线EMA: Optional[float] = Field(None, description="快线EMA的当前值")
+    慢线EMA: Optional[float] = Field(None, description="慢线EMA的当前值")
+    DEA_EMA: Optional[float] = Field(None, description="DEA的EMA当前值")
+
+    # 模型配置
+    model_config = {
+        "arbitrary_types_allowed": True,  # 允许特殊类型
+        "json_encoders": {
+            datetime: lambda v: v.isoformat(),  # 日期时间序列化
+            Enum: lambda v: v.value,  # 枚举值序列化
+        },
+    }
+
+    @classmethod
+    def 首次计算(cls, 初始收盘价: float, 初始时间: datetime, 快线周期: int = 12, 慢线周期: int = 26, 信号周期: int = 9) -> "平滑异同移动平均线":
+        """
+        首次计算MACD指标（没有历史数据时使用）
+
+        :param 初始收盘价: 第一个数据点的收盘价
+        :param 初始时间: 第一个数据点的时间戳
+        :param 快线周期:
+        :param 慢线周期:
+        :param 信号周期:
+        :return: MACD指标对象
+        """
+        # 初始化EMA值（使用第一个收盘价）
+        快线EMA = 初始收盘价
+        慢线EMA = 初始收盘价
+
+        # 计算DIF（差离值）
+        DIF = 快线EMA - 慢线EMA  # 首次计算为0
+
+        # 初始化DEA（信号线）
+        DEA_EMA = DIF  # 首次计算等于DIF
+
+        # 计算MACD柱
+        MACD柱 = 2 * (DIF - DEA_EMA)  # 首次计算为0
+
+        return cls(
+            时间戳=初始时间,
+            收盘价=初始收盘价,
+            快线周期=快线周期,
+            慢线周期=慢线周期,
+            信号周期=信号周期,
+            DIF=DIF,
+            DEA=DEA_EMA,
+            MACD柱=MACD柱,
+            快线EMA=快线EMA,
+            慢线EMA=慢线EMA,
+            DEA_EMA=DEA_EMA,
+        )
+
+    @classmethod
+    def 首次计算_K线(cls, k线: "K线", 计算方式: str, 快线周期: int = 12, 慢线周期: int = 26, 信号周期: int = 9) -> "平滑异同移动平均线":
+        初始收盘价: float = 指标.K线取值(k线, 计算方式)
+        初始时间: datetime = k线.时间戳
+        return cls.首次计算(初始收盘价, 初始时间, 快线周期, 慢线周期, 信号周期)
+
+    @classmethod
+    def 增量计算(cls, 前一个MACD: "平滑异同移动平均线", 当前收盘价: float, 当前时间: datetime) -> "平滑异同移动平均线":
+        """
+        基于前一个MACD指标增量计算当前MACD指标
+        适用于实时交易系统或流式数据处理
+
+        :param 前一个MACD: 前一个周期的MACD指标对象
+        :param 当前收盘价: 当前K线的收盘价
+        :param 当前时间: 当前K线的时间戳
+        :return: 当前MACD指标对象
+        """
+
+        # 计算EMA的平滑系数
+        def 平滑系数(周期):
+            return 2 / (周期 + 1)
+
+        # 计算快线EMA
+        if 前一个MACD.快线EMA is None:
+            快线EMA = 当前收盘价
+            raise RuntimeError
+        else:
+            # 快线EMA = 当前收盘价 * 平滑系数(前一个MACD.快线周期) + 前一个MACD.快线EMA * (1 - 平滑系数(前一个MACD.快线周期))
+            # 快线EMA = (当前收盘价 - 前一个MACD.快线EMA) * 平滑系数(前一个MACD.快线周期) + 前一个MACD.快线EMA
+            快线EMA = 当前收盘价 * 平滑系数(前一个MACD.快线周期) + 前一个MACD.快线EMA * ((前一个MACD.快线周期 - 1) / (前一个MACD.快线周期 + 1))
+
+        # 计算慢线EMA
+        if 前一个MACD.慢线EMA is None:
+            慢线EMA = 当前收盘价
+            raise RuntimeError
+        else:
+            # 慢线EMA = 当前收盘价 * 平滑系数(前一个MACD.慢线周期) + 前一个MACD.慢线EMA * (1 - 平滑系数(前一个MACD.慢线周期))
+            # 慢线EMA = (当前收盘价 - 前一个MACD.慢线EMA) * 平滑系数(前一个MACD.慢线周期) + 前一个MACD.慢线EMA
+            慢线EMA = 当前收盘价 * 平滑系数(前一个MACD.慢线周期) + 前一个MACD.慢线EMA * ((前一个MACD.慢线周期 - 1) / (前一个MACD.慢线周期 + 1))
+
+        # 计算DIF
+        DIF = 快线EMA - 慢线EMA
+
+        # 计算DEA的EMA
+        if 前一个MACD.DEA_EMA is None:
+            DEA_EMA = DIF
+        else:
+            # DEA_EMA = 当前收盘价 * 平滑系数(前一个MACD.信号周期) + 前一个MACD.DEA_EMA * (1 - 平滑系数(前一个MACD.信号周期))
+            # DEA_EMA = (DIF - 前一个MACD.DEA_EMA) * 平滑系数(前一个MACD.信号周期) + 前一个MACD.DEA_EMA
+            DEA_EMA = DIF * 平滑系数(前一个MACD.信号周期) + 前一个MACD.DEA_EMA * ((前一个MACD.信号周期 - 1) / (前一个MACD.信号周期 + 1))
+
+        # 计算MACD柱
+        MACD柱 = DIF - DEA_EMA  # * 2
+
+        return cls(
+            时间戳=当前时间,
+            收盘价=当前收盘价,
+            快线周期=前一个MACD.快线周期,
+            慢线周期=前一个MACD.慢线周期,
+            信号周期=前一个MACD.信号周期,
+            DIF=DIF,
+            DEA=DEA_EMA,
+            MACD柱=MACD柱,
+            快线EMA=快线EMA,
+            慢线EMA=慢线EMA,
+            DEA_EMA=DEA_EMA,
+        )
+
+    @classmethod
+    def 增量计算_K线(cls, 前一个MACD: "平滑异同移动平均线", 当前K线: "K线", 计算方式: "str") -> "平滑异同移动平均线":
+        当前收盘价: float = 指标.K线取值(当前K线, 计算方式)
+        当前时间: datetime = 当前K线.时间戳
+        return cls.增量计算(前一个MACD, 当前收盘价, 当前时间)
+
+
+class 相对强弱指数(BaseModel):
+    """
+    相对强弱指数 (RSI) 指标
+    使用 Wilder 平滑（RMA）进行增量计算，提供完整的中间平滑值，
+    并支持对RSI值计算SMA（简单移动平均）
+    """
+
+    # 原始数据
+    时间戳: datetime = Field(..., description="数据点对应的时间")
+    收盘价: float = Field(..., description="当前K线的收盘价格")
+
+    # 参数
+    周期: int = Field(14, gt=0, description="RSI周期，默认为14")
+    超买阈值: float = Field(70.0, description="超买阈值")
+    超卖阈值: float = Field(30.0, description="超卖阈值")
+    RSI_SMA周期: Optional[int] = Field(None, description="RSI的SMA周期（可选），用于生成信号线")
+
+    # 核心指标值
+    RSI: Optional[float] = Field(None, description="当前RSI值")
+
+    # 中间平滑值（Wilder平滑）
+    平均上涨: Optional[float] = Field(None, description="平均上涨幅度的平滑值")
+    平均下跌: Optional[float] = Field(None, description="平均下跌幅度的平滑值")
+
+    # 原始变化值（用于调试）
+    上涨幅度: float = Field(0.0, description="当前价格变化中的上涨部分")
+    下跌幅度: float = Field(0.0, description="当前价格变化中的下跌部分")
+
+    # 平滑系数（α = 1/周期）
+    平滑系数: float = Field(0.0, description="Wilder平滑系数")
+
+    # RSI的SMA（信号线）相关字段
+    RSI_SMA: Optional[float] = Field(None, description="RSI的简单移动平均值")
+    RSI历史队列: List[float] = Field(default_factory=list, description="用于计算SMA的RSI历史队列")
+
+    model_config = {
+        "arbitrary_types_allowed": True,
+        "json_encoders": {
+            datetime: lambda v: v.isoformat(),
+            Enum: lambda v: v.value,
+        },
+    }
+
+    @classmethod
+    def 首次计算(cls, 初始收盘价: float, 初始时间: datetime, 周期: int = 14, 超买阈值: float = 70.0, 超卖阈值: float = 30.0, RSI_SMA周期: Optional[int] = None) -> "相对强弱指数":
+        """
+        首次计算RSI（没有足够历史数据时使用）
+        此时无法计算真实RSI，设为 None，但记录初始收盘价作为起点
+        """
+        return cls(
+            时间戳=初始时间,
+            收盘价=初始收盘价,
+            周期=周期,
+            RSI=None,
+            平均上涨=0.0,
+            平均下跌=0.0,
+            上涨幅度=0.0,
+            下跌幅度=0.0,
+            平滑系数=1.0 / 周期,
+            超买阈值=超买阈值,
+            超卖阈值=超卖阈值,
+            RSI_SMA周期=RSI_SMA周期,
+            RSI_SMA=None,
+            RSI历史队列=[],
+        )
+
+    @classmethod
+    def 首次计算_K线(cls, k线: "K线", 计算方式: str, 周期: int = 14, 超买阈值: float = 70.0, 超卖阈值: float = 30.0, RSI_SMA周期: Optional[int] = None) -> "相对强弱指数":
+        初始收盘价: float = 指标.K线取值(k线, 计算方式)
+        初始时间: datetime = k线.时间戳
+        return cls.首次计算(初始收盘价, 初始时间, 周期, 超买阈值, 超卖阈值, RSI_SMA周期)
+
+    @classmethod
+    def 增量计算(cls, 前一个RSI: "相对强弱指数", 当前收盘价: float, 当前时间: datetime) -> "相对强弱指数":
+        """
+        基于前一个RSI指标增量计算当前RSI
+        支持可选的RSI_SMA（简单移动平均）
+        """
+        # 复制参数
+        周期 = 前一个RSI.周期
+        超买阈值 = 前一个RSI.超买阈值
+        超卖阈值 = 前一个RSI.超卖阈值
+        RSI_SMA周期 = 前一个RSI.RSI_SMA周期
+        平滑系数 = 1.0 / 周期
+
+        # 计算价格变化
+        变化 = 当前收盘价 - 前一个RSI.收盘价
+        上涨 = max(变化, 0)
+        下跌 = max(-变化, 0)
+
+        # 更新平均上涨和平均下跌（Wilder平滑）
+        if 前一个RSI.平均上涨 is None or 前一个RSI.平均下跌 is None:
+            平均上涨 = 上涨
+            平均下跌 = 下跌
+        else:
+            平均上涨 = 前一个RSI.平均上涨 * (1 - 平滑系数) + 上涨 * 平滑系数
+            平均下跌 = 前一个RSI.平均下跌 * (1 - 平滑系数) + 下跌 * 平滑系数
+
+        # 计算RSI
+        if 平均下跌 == 0:
+            RSI = 100.0 if 平均上涨 > 0 else 50.0
+        else:
+            RS = 平均上涨 / 平均下跌
+            RSI = 100 - (100 / (1 + RS))
+
+        # ----- 计算RSI的SMA（简单移动平均） -----
+        RSI_SMA = None
+        历史队列 = 前一个RSI.RSI历史队列.copy() if 前一个RSI.RSI历史队列 else []
+        if RSI_SMA周期 is not None and RSI_SMA周期 > 0 and RSI is not None:
+            # 将当前RSI加入队列
+            历史队列.append(RSI)
+            # 保持队列长度不超过周期
+            if len(历史队列) > RSI_SMA周期:
+                历史队列.pop(0)
+            # 计算SMA（即使队列未满也计算当前平均值）
+            if 历史队列:
+                RSI_SMA = sum(历史队列) / len(历史队列)
+        else:
+            # 未启用SMA，清空队列
+            历史队列 = []
+
+        return cls(
+            时间戳=当前时间,
+            收盘价=当前收盘价,
+            周期=周期,
+            RSI=RSI,
+            平均上涨=平均上涨,
+            平均下跌=平均下跌,
+            上涨幅度=上涨,
+            下跌幅度=下跌,
+            平滑系数=平滑系数,
+            超买阈值=超买阈值,
+            超卖阈值=超卖阈值,
+            RSI_SMA周期=RSI_SMA周期,
+            RSI_SMA=RSI_SMA,
+            RSI历史队列=历史队列,
+        )
+
+    @classmethod
+    def 增量计算_K线(cls, 前一个RSI: "相对强弱指数", 当前K线: "K线", 计算方式: "str") -> "相对强弱指数":
+        当前收盘价: float = 指标.K线取值(当前K线, 计算方式)
+        当前时间: datetime = 当前K线.时间戳
+        return cls.增量计算(前一个RSI, 当前收盘价, 当前时间)
+
+
+class 随机指标(BaseModel):
+    """
+    KDJ 随机指标 (Stochastic Oscillator)
+    使用标准参数：N=9, M1=3, M2=3
+    支持增量计算，需提供当前K线的最高价、最低价、收盘价
+    """
+
+    # 原始数据
+    时间戳: datetime = Field(..., description="数据点对应的时间")
+    最高价: float = Field(..., description="当前K线的最高价")
+    最低价: float = Field(..., description="当前K线的最低价")
+    收盘价: float = Field(..., description="当前K线的收盘价")
+
+    # 参数
+    N: int = Field(9, ge=1, description="RSV的周期（取最近N根K线）")
+    M1: int = Field(3, ge=1, description="K值的平滑周期")
+    M2: int = Field(3, ge=1, description="D值的平滑周期")
+    超买阈值: float = Field(80.0, description="超买阈值")
+    超卖阈值: float = Field(20.0, description="超卖阈值")
+
+    # 核心指标值
+    RSV: Optional[float] = Field(None, description="未成熟随机值")
+    K: Optional[float] = Field(None, description="K值（快速随机指标）")
+    D: Optional[float] = Field(None, description="D值（慢速随机指标）")
+    J: Optional[float] = Field(None, description="J值 = 3K - 2D")
+
+    # 中间状态（用于增量计算）
+    历史最高价队列: list[float] = Field(default_factory=list, description="最近N根K线的最高价队列")
+    历史最低价队列: list[float] = Field(default_factory=list, description="最近N根K线的最低价队列")
+    前一个RSV: Optional[float] = Field(None, description="上一个RSV值（用于平滑K）")
+    前一个K: Optional[float] = Field(None, description="上一个K值")
+    前一个D: Optional[float] = Field(None, description="上一个D值")
+
+    model_config = {
+        "arbitrary_types_allowed": True,
+        "json_encoders": {
+            datetime: lambda v: v.isoformat(),
+            Enum: lambda v: v.value,
+        },
+    }
+
+    @classmethod
+    def 首次计算(cls, 初始最高价: float, 初始最低价: float, 初始收盘价: float, 初始时间: datetime, N: int = 9, M1: int = 3, M2: int = 3, 超买阈值: float = 80.0, 超卖阈值: float = 20.0) -> "随机指标":
+        """
+        首次计算KDJ（无历史数据时）
+        此时无法计算RSV和K/D/J，仅记录初始三价，初始化队列
+        """
+        # 初始化历史队列，放入当前三价
+        return cls(
+            时间戳=初始时间,
+            最高价=初始最高价,
+            最低价=初始最低价,
+            收盘价=初始收盘价,
+            N=N,
+            M1=M1,
+            M2=M2,
+            超买阈值=超买阈值,
+            超卖阈值=超卖阈值,
+            RSV=None,
+            K=None,
+            D=None,
+            J=None,
+            历史最高价队列=[初始最高价],
+            历史最低价队列=[初始最低价],
+            前一个RSV=None,
+            前一个K=None,
+            前一个D=None,
+        )
+
+    @classmethod
+    def 首次计算_K线(cls, k线: "K线", 计算方式: str, RSV周期: int = 9, K值平滑周期: int = 3, D值平滑周期: int = 3, 超买阈值: float = 80.0, 超卖阈值: float = 20.0) -> "随机指标":
+        初始最高价: float = k线.高
+        初始最低价: float = k线.低
+        初始收盘价: float = k线.收盘价
+        初始时间: datetime = k线.时间戳
+        return cls.首次计算(初始最高价, 初始最低价, 初始收盘价, 初始时间, RSV周期, K值平滑周期, D值平滑周期, 超买阈值, 超卖阈值)
+
+    @classmethod
+    def 增量计算(cls, 前一个KDJ: "随机指标", 当前最高价: float, 当前最低价: float, 当前收盘价: float, 当前时间: datetime) -> "随机指标":
+        """
+        基于前一个KDJ对象和当前三价，增量计算当前KDJ值
+        """
+        # 复制参数
+        N = 前一个KDJ.N
+        M1 = 前一个KDJ.M1
+        M2 = 前一个KDJ.M2
+        超买阈值 = 前一个KDJ.超买阈值
+        超卖阈值 = 前一个KDJ.超卖阈值
+
+        # 更新历史最高价队列
+        历史最高价 = 前一个KDJ.历史最高价队列.copy()
+        历史最高价.append(当前最高价)
+        if len(历史最高价) > N:
+            历史最高价.pop(0)
+
+        # 更新历史最低价队列
+        历史最低价 = 前一个KDJ.历史最低价队列.copy()
+        历史最低价.append(当前最低价)
+        if len(历史最低价) > N:
+            历史最低价.pop(0)
+
+        # 计算RSV（需要队列长度达到N才能计算）
+        RSV = None
+        if len(历史最高价) == N and len(历史最低价) == N:
+            highest = max(历史最高价)
+            lowest = min(历史最低价)
+            if highest != lowest:
+                RSV = (当前收盘价 - lowest) / (highest - lowest) * 100
+            else:
+                RSV = 50.0  # 如果最高=最低，RSV取50
+
+        # 计算K值（使用前一天的K值平滑，首次使用RSV）
+        K = None
+        if RSV is not None:
+            if 前一个KDJ.K is None:
+                K = RSV  # 首次K值等于RSV
+            else:
+                # 标准公式：K = 2/3 * 前一日K + 1/3 * 当日RSV
+                K = (前一个KDJ.K * (M1 - 1) + RSV) / M1
+        else:
+            # 数据不足时，K值沿用前一个（若没有则为None）
+            K = 前一个KDJ.K
+
+        # 计算D值（使用前一天的D值平滑，首次使用K值）
+        D = None
+        if K is not None:
+            if 前一个KDJ.D is None:
+                D = K  # 首次D值等于K
+            else:
+                # 标准公式：D = 2/3 * 前一日D + 1/3 * 当日K
+                D = (前一个KDJ.D * (M2 - 1) + K) / M2
+        else:
+            D = 前一个KDJ.D
+
+        # 计算J值
+        J = None
+        if K is not None and D is not None:
+            J = 3 * K - 2 * D
+
+        return cls(
+            时间戳=当前时间,
+            最高价=当前最高价,
+            最低价=当前最低价,
+            收盘价=当前收盘价,
+            N=N,
+            M1=M1,
+            M2=M2,
+            超买阈值=超买阈值,
+            超卖阈值=超卖阈值,
+            RSV=RSV,
+            K=K,
+            D=D,
+            J=J,
+            历史最高价队列=历史最高价,
+            历史最低价队列=历史最低价,
+            前一个RSV=RSV,
+            前一个K=K,
+            前一个D=D,
+        )
+
+    @classmethod
+    def 增量计算_K线(cls, 前一个KDJ: "随机指标", 当前K线: "K线", 计算方式: "str") -> "随机指标":
+        当前最高价: float = 当前K线.高
+        当前最低价: float = 当前K线.低
+        当前收盘价: float = 当前K线.收盘价
+        当前时间: datetime = 当前K线.时间戳
+        return cls.增量计算(前一个KDJ, 当前最高价, 当前最低价, 当前收盘价, 当前时间)
+
+
+class 背驰分析:
+    @staticmethod
+    def MACD背驰(进入段: "虚线", 离开段: "虚线", K线序列: List["K线"], 方式: str = "总") -> bool:
+        """MACD柱状线面积背驰"""
+        进入MACD = K线.获取MACD(K线序列, 进入段.文.中.标的K线, 进入段.武.中.标的K线)
+        离开MACD = K线.获取MACD(K线序列, 离开段.文.中.标的K线, 离开段.武.中.标的K线)
+
+        # 计算面积（绝对值求和）
+        进入面积 = abs(进入MACD["总"] if 方式 == "总" else (进入MACD["阳"] if 进入段.方向 is 相对方向.向上 else 进入MACD["阴"]))
+        离开面积 = abs(离开MACD["总"] if 方式 == "总" else (离开MACD["阳"] if 进入段.方向 is 相对方向.向上 else 离开MACD["阴"]))
+
+        return 离开面积 < 进入面积
+
+    @staticmethod
+    def 斜率背驰(进入段: "虚线", 离开段: "虚线") -> bool:
+        """价格斜率背驰"""
+        # 计算线段的速度
+        dx = 进入段.武.时间戳.timestamp() - 进入段.文.时间戳.timestamp()  # self.武.时间戳 - self.文.时间戳  # 时间差
+        dy = 进入段.武.分型特征值 - 进入段.文.分型特征值  # 价格差
+        进入斜率 = dy / dx
+        # 计算线段的速度
+        dx = 离开段.武.时间戳.timestamp() - 离开段.文.时间戳.timestamp()  # self.武.时间戳 - self.文.时间戳  # 时间差
+        dy = 离开段.武.分型特征值 - 离开段.文.分型特征值  # 价格差
+        离开斜率 = dy / dx
+
+        if 进入段.方向 == 相对方向.向上:
+            if 离开段.高 > 进入段.高 and abs(离开斜率) < abs(进入斜率):
+                return True
+        else:
+            if 离开段.低 < 进入段.低 and abs(离开斜率) < abs(进入斜率):
+                return True
+        return False
+
+    @staticmethod
+    def 测度背驰(进入段: "虚线", 离开段: "虚线") -> bool:
+        """价格斜率背驰"""
+        dx = 进入段.武.时间戳.timestamp() - 进入段.文.时间戳.timestamp()  # 时间差 self.武.中.标的K线.序号 - self.文.中.标的K线.序号  #
+        dy = 进入段.武.分型特征值 - 进入段.文.分型特征值  # 价格差的绝对值
+        进入测度 = math.sqrt(dx * dx + dy * dy)
+
+        dx = 离开段.武.时间戳.timestamp() - 离开段.文.时间戳.timestamp()  # 时间差 self.武.中.标的K线.序号 - self.文.中.标的K线.序号  #
+        dy = 离开段.武.分型特征值 - 离开段.文.分型特征值  # 价格差的绝对值
+        离开测度 = math.sqrt(dx * dx + dy * dy)
+
+        if 进入段.方向 == 相对方向.向上:
+            if 离开段.高 > 进入段.高 and abs(离开测度) < abs(进入测度):
+                return True
+        else:
+            if 离开段.低 < 进入段.低 and abs(离开测度) < abs(进入测度):
+                return True
+        return False
+
+    @staticmethod
+    def 全量背驰(进入段: "虚线", 离开段: "虚线", 普K序列: List["K线"]) -> bool:
+        return all([背驰分析.MACD背驰(进入段, 离开段, 普K序列), 背驰分析.测度背驰(进入段, 离开段), 背驰分析.斜率背驰(进入段, 离开段)])
+
+    @staticmethod
+    def 任意背驰(进入段: "虚线", 离开段: "虚线", 普K序列: List["K线"]) -> bool:
+        return any([背驰分析.MACD背驰(进入段, 离开段, 普K序列), 背驰分析.测度背驰(进入段, 离开段), 背驰分析.斜率背驰(进入段, 离开段)])
+
+    @staticmethod
+    def 配置背驰(进入段: "虚线", 离开段: "虚线", 普K序列: List["K线"], 配置: 缠论配置) -> bool:
+        match 配置.线段内部背驰_MACD, 配置.线段内部背驰_测度, 配置.线段内部背驰_斜率:
+            case True, True, True:
+                return 背驰分析.MACD背驰(进入段, 离开段, 普K序列) and 背驰分析.测度背驰(进入段, 离开段) and 背驰分析.斜率背驰(进入段, 离开段)
+            case False, False, False:
+                ...
+
+            case True, False, True:
+                return 背驰分析.MACD背驰(进入段, 离开段, 普K序列) and 背驰分析.斜率背驰(进入段, 离开段)
+            case False, True, False:
+                return 背驰分析.测度背驰(进入段, 离开段)
+
+            case True, False, False:
+                return 背驰分析.MACD背驰(进入段, 离开段, 普K序列)
+            case False, True, True:
+                return 背驰分析.测度背驰(进入段, 离开段) and 背驰分析.斜率背驰(进入段, 离开段)
+
+            case False, False, True:
+                return 背驰分析.斜率背驰(进入段, 离开段)
+            case True, True, False:
+                return 背驰分析.MACD背驰(进入段, 离开段, 普K序列) and 背驰分析.测度背驰(进入段, 离开段)
+
+        return False
+
+    @staticmethod
+    def 任选背驰(进入段: "虚线", 离开段: "虚线", 普K序列: List["K线"]) -> bool:
+        混沌槽 = [背驰分析.MACD背驰(进入段, 离开段, 普K序列), 背驰分析.测度背驰(进入段, 离开段), 背驰分析.斜率背驰(进入段, 离开段)]
+        return len([背驰 for 背驰 in 混沌槽 if 背驰]) >= 2
+
+    @staticmethod
+    def 背驰模式(进入段: "虚线", 离开段: "虚线", 普K序列: List["K线"], 配置: 缠论配置, 模式: str) -> bool:
+        match 模式:
+            case "全量":
+                return 背驰分析.全量背驰(进入段, 离开段, 普K序列)
+            case "任意":
+                return 背驰分析.任意背驰(进入段, 离开段, 普K序列)
+            case "配置":
+                return 背驰分析.配置背驰(进入段, 离开段, 普K序列, 配置)
+            case "相对":
+                return 背驰分析.任选背驰(进入段, 离开段, 普K序列)
+        return False
+
+
+class K线(object):
+    __slots__ = ["标识", "序号", "周期", "时间戳", "高", "低", "开盘价", "收盘价", "成交量", "macd", "rsi", "kdj"]
+
+    def __init__(
+        self,
+        标识: str,
+        序号: int,
+        周期: int,
+        时间戳: datetime,
+        开盘价: float,
+        最高价: float,
+        最低价: float,
+        收盘价: float,
+        成交量: float,
+        macd: 平滑异同移动平均线 = None,
+        rsi: 相对强弱指数 = None,
+        kdj: 随机指标 = None,
+    ):
+        self.序号: int = 序号
+        self.标识: str = 标识
+        self.时间戳: datetime = 时间戳
+        self.开盘价: float = 开盘价
+        self.高: float = 最高价
+        self.低: float = 最低价
+        self.收盘价: float = 收盘价
+        self.成交量: float = 成交量
+        self.周期: int = 周期
+        self.macd: 平滑异同移动平均线 = macd
+        self.rsi: 相对强弱指数 = rsi
+        self.kdj: 随机指标 = kdj
+
+    def __str__(self):
+        return f"{self.标识}<{self.序号}, {self.周期}, {self.方向}, {self.时间戳}, {self.开盘价:g}, {self.高:g}, {self.低:g}, {self.收盘价:g}>"
+
+    def __repr__(self):
+        return f"{self.标识}<{self.序号}, {self.周期}, {self.方向}, {self.时间戳}, {self.开盘价:g}, {self.高:g}, {self.低:g}, {self.收盘价:g}>"
+
+    @property
+    def 方向(self) -> 相对方向:
+        return 相对方向.向上 if self.开盘价 < self.收盘价 else 相对方向.向下
+
+    def __bytes__(self):
+        return struct.pack(
+            ">6d",
+            int(self.时间戳.timestamp()),
+            round(self.开盘价, 8),
+            round(self.高, 8),
+            round(self.低, 8),
+            round(self.收盘价, 8),
+            round(self.成交量, 8),
+        )
+
+    @classmethod
+    def 创建普K(cls, 标识: str, 时间戳: datetime, 开盘价: float, 最高价: float, 最低价: float, 收盘价: float, 成交量: float, 序号: int, 周期: int) -> "K线":
+        k线 = K线(
+            标识=标识,
+            序号=序号,
+            周期=周期,
+            时间戳=时间戳,
+            开盘价=开盘价,
+            最高价=最高价,
+            最低价=最低价,
+            收盘价=收盘价,
+            成交量=成交量,
+        )
+        return k线
+
+    @classmethod
+    def 保存到DAT文件(cls, 路径: str, K线序列: List["K线"]):
+        with open(路径, "wb") as f:
+            for K in K线序列:
+                f.write(bytes(K))
+        print(f"保存到DAT文件: {路径}")
+
+    @classmethod
+    def 读取大端字节数组(cls, 字节组: bytes, 周期: int = 60, 标识: str = "Bar") -> "K线":
+        时间戳, 开盘价, 最高价, 最低价, 收盘价, 成交量 = struct.unpack(">6d", 字节组[: struct.calcsize(">6d")])
+
+        return cls(
+            标识=标识,
+            序号=0,
+            周期=周期,
+            时间戳=datetime.fromtimestamp(时间戳),
+            开盘价=开盘价,
+            最高价=最高价,
+            最低价=最低价,
+            收盘价=收盘价,
+            成交量=成交量,
+        )
+
+    @classmethod
+    def 获取MACD(cls, K线序列: List["K线"], 始: "K线", 终: "K线") -> Dict[str, float]:
+        基序 = K线序列[K线序列.index(始) : K线序列.index(终) + 1]
+
+        阳 = 0.0
+        阴 = 0.0
+        for k in 基序:
+            histogram = k.macd.MACD柱
+            if histogram >= 0:
+                阳 += histogram
+            else:
+                阴 += histogram
+
+        合 = 阳 + 阴
+        return {"阳": 阳, "阴": 阴, "合": 合, "总": 阳 + abs(阴)}
+
+    @staticmethod
+    def 截取(序列: List["K线"], 始: "K线", 终: "K线") -> List["K线"]:
+        return 序列[序列.index(始) : 序列.index(终) + 1]
+
+
+class 缠论K线(object):
+    __slots__ = ["序号", "时间戳", "高", "低", "方向", "分型", "周期", "标识", "分型特征值", "原始起始序号", "原始结束序号", "标的K线", "买卖点信息"]
+
+    def __init__(
+        self,
+        序号: int,
+        时间戳: datetime,
+        最高价: float,
+        最低价: float,
+        最终方向: 相对方向,
+        普K: "K线",
+        原始起始序号: int,
+        原始结束序号: int,
+        分型: Optional[分型结构] = None,
+    ):
+        self.序号: int = 序号
+        self.时间戳: datetime = 时间戳
+        self.高: float = 最高价
+        self.低: float = 最低价
+        self.方向: 相对方向 = 最终方向
+        self.分型: Optional[分型结构] = 分型
+        self.周期: int = 普K.周期
+        self.标识: str = 普K.标识
+        self.分型特征值: float = 最高价
+
+        self.原始起始序号: int = 原始起始序号
+        self.原始结束序号: int = 原始结束序号
+        self.标的K线: "K线" = 普K
+
+    def __str__(self):
+        return f"{self.标识}<{self.序号}, {self.分型}, {self.周期}, {self.方向}, {self.时间戳}, {self.高:g}, {self.低:g}>"
+
+    def __repr__(self):
+        return f"{self.标识}<{self.序号}, {self.分型}, {self.周期}, {self.方向}, {self.时间戳}, {self.高:g}, {self.低:g}>"
+
+    @property
+    def 镜像(self):
+        K = 缠论K线(self.序号, self.时间戳, self.高, self.低, self.方向, self.标的K线, self.原始起始序号, self.原始结束序号, self.分型)
+        return K
+
+    @property
+    def 与MACD柱子匹配(self) -> bool:
+        if self.分型 in (分型结构.底, 分型结构.下):
+            return self.标的K线.macd.MACD柱 < 0
+
+        if self.分型 in (分型结构.顶, 分型结构.上):
+            return self.标的K线.macd.MACD柱 > 0
+        return False
+
+    @property
+    def 与RSI匹配(self) -> bool:
+        if self.分型 in (分型结构.底, 分型结构.下):
+            return self.标的K线.rsi.RSI < self.标的K线.rsi.RSI_SMA
+
+        if self.分型 in (分型结构.顶, 分型结构.上):
+            return self.标的K线.rsi.RSI > self.标的K线.rsi.RSI_SMA
+        return False
+
+    @property
+    def 与KDJ匹配(self) -> bool:
+        if self.标的K线.kdj.K is None or self.标的K线.kdj.D is None:
+            return False
+        if self.分型 in (分型结构.底, 分型结构.下):
+            return self.标的K线.kdj.K < self.标的K线.kdj.D
+
+        if self.分型 in (分型结构.顶, 分型结构.上):
+            return self.标的K线.kdj.K > self.标的K线.kdj.D
+        return False
+
+    @classmethod
+    def 时间戳对齐(cls, 基线: List["缠论K线"], k线: "缠论K线"):
+        if 基线:
+            for k in 基线[::-1]:
+                if 基线[0].周期 < k线.周期:
+                    if k线.时间戳.timestamp() <= k.时间戳.timestamp() <= k线.时间戳.timestamp() + k线.周期:
+                        if k线.分型特征值 == k.分型特征值:
+                            return k.时间戳
+                else:
+                    if k.时间戳.timestamp() <= k线.时间戳.timestamp() <= k.时间戳.timestamp() + k.周期:
+                        if k线.分型特征值 == k.分型特征值:
+                            return k.时间戳
+        return k线.时间戳
+
+    @classmethod
+    def 创建缠K(cls, 时间戳: datetime, 高: float, 低: float, 方向: 相对方向, 结构: 分型结构, 原始序号: int, 普k: "K线", 之前: Optional["缠论K线"] = None) -> "缠论K线":
+        assert 高 >= 低
+        序号 = 0
+        当前 = 缠论K线(
+            序号=序号,
+            时间戳=时间戳,
+            最高价=高,
+            最低价=低,
+            最终方向=方向,
+            分型=结构,
+            原始起始序号=原始序号,
+            原始结束序号=原始序号,
+            普K=普k,
+        )
+
+        if 之前 is not None:
+            当前.序号 = 之前.序号 + 1
+
+            if 相对方向.分析(之前.高, 之前.低, 当前.高, 当前.低).是否包含():
+                raise ValueError(f"\n    {相对方向.分析(之前.高, 之前.低, 当前.高, 当前.低)}\n    {之前},\n    {当前}")
+        return 当前
+
+    @classmethod
+    def 兼并(cls, 之前缠K: Optional["缠论K线"], 当前缠K: "缠论K线", 当前普K: "K线", 配置: 缠论配置) -> Tuple[Optional["缠论K线"], Optional[str]]:
+        关系 = 相对方向.分析(当前缠K.高, 当前缠K.低, 当前普K.高, 当前普K.低)
+        if not 关系.是否包含():
+            新缠K = 缠论K线.创建缠K(
+                时间戳=当前普K.时间戳,
+                高=当前普K.高,
+                低=当前普K.低,
+                方向=当前普K.方向,
+                原始序号=当前普K.序号,
+                之前=当前缠K,
+                普k=当前普K,
+                结构=分型结构.下 if 关系.是否向下() else 分型结构.上,
+            )
+            新缠K.序号 = 当前缠K.序号 + 1
+            return 新缠K, "添加"
+
+        if 当前普K.序号 == 当前缠K.原始结束序号:
+            # 当序号相同时认为是重复提交K线
+            ...
+
+        if 当前普K.序号 - 1 != 当前缠K.原始结束序号 and 当前普K.序号 != 当前缠K.原始结束序号:
+            raise ValueError(f"NewBar.merger: 不可追加不连续元素 缠K.原始结束序号: {当前缠K.原始结束序号}, 当前普K.序号: {当前普K.序号}.")
+
+        # 方向 = 相对方向.向上
+        取值函数 = max
+        if 之前缠K is not None:
+            if 相对方向.分析(之前缠K.高, 之前缠K.低, 当前缠K.高, 当前缠K.低).是否向下():
+                取值函数 = min
+
+        if 关系 is not 相对方向.顺:
+            当前缠K.时间戳 = 当前普K.时间戳
+            当前缠K.标的K线 = 当前普K
+        当前缠K.高 = 取值函数(当前缠K.高, 当前普K.高)
+        当前缠K.低 = 取值函数(当前缠K.低, 当前普K.低)
+        当前缠K.原始结束序号 = 当前普K.序号
+        当前缠K.方向 = 当前普K.方向  # FIXME 涉及 买卖点，MACD, 均线
+
+        if 之前缠K is not None:
+            当前缠K.序号 = 之前缠K.序号 + 1
+
+        if 配置.缠K合并替换:
+            return 当前缠K.镜像, "替换"
+        return None, None
+
+    @classmethod
+    def 分析(cls, 当前K线: "K线", 缠K序列: List["缠论K线"], 普K序列: List["K线"], 配置: 缠论配置) -> tuple[str, Optional["分型"]]:
+        当前K线.标识 = 配置.标识
+        if not 普K序列:
+            if 配置.计算指标:
+                当前K线.macd = 平滑异同移动平均线.首次计算_K线(当前K线, 配置.指标计算方式, 配置.平滑异同移动平均线_快线周期, 配置.平滑异同移动平均线_慢线周期, 配置.平滑异同移动平均线_信号周期)
+                当前K线.rsi = 相对强弱指数.首次计算_K线(当前K线, 配置.指标计算方式, 配置.相对强弱指数_周期, 配置.相对强弱指数_超买阈值, 配置.相对强弱指数_超卖阈值, 配置.相对强弱指数_移动平均线周期)
+                当前K线.kdj = 随机指标.首次计算_K线(当前K线, 配置.指标计算方式, 配置.随机指标_RSV周期, 配置.随机指标_K值平滑周期, 配置.随机指标_D值平滑周期, 配置.随机指标_超买阈值, 配置.随机指标_超卖阈值)
+            普K序列.append(当前K线)
+        else:
+            之前普K = 普K序列[-1]
+            if 之前普K.时间戳 == 当前K线.时间戳:
+                当前K线.序号 = 普K序列[-1].序号
+                普K序列[-1] = 当前K线
+                if 配置.计算指标:
+                    try:
+                        当前K线.macd = 平滑异同移动平均线.增量计算_K线(普K序列[-2].macd, 当前K线, 配置.指标计算方式)
+                        当前K线.rsi = 相对强弱指数.增量计算_K线(普K序列[-2].rsi, 当前K线, 配置.指标计算方式)
+                        当前K线.kdj = 随机指标.增量计算_K线(普K序列[-2].kdj, 当前K线, 配置.指标计算方式)
+                    except IndexError:
+                        pass  # traceback.print_exc()
+            else:
+                if 之前普K.时间戳 > 当前K线.时间戳:
+                    raise RuntimeError("时序错误")
+                当前K线.序号 = 之前普K.序号 + 1
+                if 配置.计算指标:
+                    当前K线.macd = 平滑异同移动平均线.增量计算_K线(之前普K.macd, 当前K线, 配置.指标计算方式)
+                    当前K线.rsi = 相对强弱指数.增量计算_K线(之前普K.rsi, 当前K线, 配置.指标计算方式)
+                    当前K线.kdj = 随机指标.增量计算_K线(之前普K.kdj, 当前K线, 配置.指标计算方式)
+                普K序列.append(当前K线)
+
+        之前缠K: Optional[缠论K线] = None
+        状态, 形态 = None, None
+        if 缠K序列:
+            try:
+                之前缠K = 缠K序列[-2]
+            except IndexError:
+                pass
+            新缠K, 模式 = 缠论K线.兼并(之前缠K, 缠K序列[-1], 当前K线, 配置)
+            if 新缠K is not None:
+                if 模式 == "添加":
+                    缠K序列.append(新缠K)
+                    状态 = "创建"
+                elif 模式 == "替换":
+                    缠K序列[-1] = 新缠K
+                    状态 = "替换"
+                else:
+                    raise RuntimeError()
+            else:
+                状态 = "兼并"
+        else:
+            新缠K = 缠论K线.创建缠K(时间戳=当前K线.时间戳, 高=当前K线.高, 低=当前K线.低, 方向=当前K线.方向, 原始序号=当前K线.序号, 之前=None, 普k=当前K线, 结构=None)
+            缠K序列.append(新缠K)
+            状态 = "新建"
+
+        try:
+            左, 中, 右 = 缠K序列[-3:]
+        except ValueError:
+            return 状态, 形态
+
+        结构 = 分型结构.分析(左, 中, 右)
+        中.分型 = 结构
+
+        if 结构 is 分型结构.底:
+            中.分型特征值 = 中.低
+            右.分型特征值 = 右.高
+            右.分型 = 分型结构.顶
+
+        if 结构 is 分型结构.顶:
+            中.分型特征值 = 中.高
+            右.分型特征值 = 右.低
+            右.分型 = 分型结构.底
+
+        if 结构 is 分型结构.上:
+            中.分型特征值 = 中.高
+            右.分型特征值 = 右.高
+            右.分型 = 分型结构.顶
+
+        if 结构 is 分型结构.下:
+            中.分型特征值 = 中.低
+            右.分型特征值 = 右.低
+            右.分型 = 分型结构.底
+
+        形态 = 分型(左=左, 中=中, 右=右)
+        if 结构 in (分型结构.上, 分型结构.下):
+            形态 = 分型(中, 右, None)
+        return 状态, 形态
+
+    @staticmethod
+    def 截取(序列: List["缠论K线"], 始: "缠论K线", 终: "缠论K线") -> List["缠论K线"]:
+        return 序列[序列.index(始) : 序列.index(终) + 1]
+
+
+class 分型(object):
+    __slots__ = ["左", "中", "右", "结构", "时间戳", "分型特征值"]
+
+    def __init__(self, 左: Optional[缠论K线], 中: 缠论K线, 右: Optional[缠论K线]):
+        if 左 and 右:
+            assert 左.时间戳 < 中.时间戳 < 右.时间戳
+        self.左: Optional[缠论K线] = 左
+        self.中: 缠论K线 = 中
+        self.右: Optional[缠论K线] = 右
+        self.结构 = 中.分型
+        self.时间戳 = 中.时间戳
+        self.分型特征值 = 中.分型特征值
+
+    def __str__(self):
+        return f"{self.中.分型}<{self.时间戳}, {self.分型特征值:g}, None: {self.左 is None}, None: {self.右 is None}>"
+
+    def __repr__(self):
+        return f"{self.中.分型}<{self.时间戳}, {self.分型特征值:g}, None: {self.左 is None}, None: {self.右 is None}>"
+
+    @property
+    def 关系组(self) -> Optional[Tuple[相对方向, 相对方向, 相对方向]]:
+        if self.左 and self.右:
+            return 相对方向.分析(self.左.高, self.左.低, self.中.高, self.中.低), 相对方向.分析(self.中.高, self.中.低, self.右.高, self.右.低), 相对方向.分析(self.左.高, self.左.低, self.右.高, self.右.低)
+        return None
+
+    @property
+    def 强度(self):
+        if self.结构 not in (分型结构.底, 分型结构.顶):
+            return "未知"
+        if not self.右 or not self.左:
+            return "未知"
+
+        if 关系组 := self.关系组:
+            if self.结构 is 分型结构.底:
+                if 关系组[-1].是否向下():
+                    return "弱"
+                elif 关系组[-1].是否向上():
+                    return "强"
+                else:
+                    return "中"
+
+            elif self.结构 is 分型结构.顶:
+                if 关系组[-1].是否向上():
+                    return "弱"
+                elif 关系组[-1].是否向下():
+                    return "强"
+                else:
+                    return "中"
+
+        if self.右 and self.左:
+            if self.结构 is 分型结构.底:
+                if self.右.标的K线.收盘价 > self.左.标的K线.高:
+                    return "强"
+                elif self.右.标的K线.收盘价 > self.中.标的K线.高:
+                    return "中"
+                else:
+                    return "弱"
+            elif self.结构 is 分型结构.顶:
+                if self.右.标的K线.收盘价 < self.左.标的K线.低:
+                    return "强"
+                elif self.右.标的K线.收盘价 < self.中.标的K线.低:
+                    return "中"
+                else:
+                    return "弱"
+        return "未知"
+
+    @property
+    def 与MACD柱子分型匹配(self) -> bool:
+        if self.右 and self.左:
+            if self.结构 is 分型结构.底:
+                return self.左.标的K线.macd.MACD柱 > self.中.标的K线.macd.MACD柱 < self.右.标的K线.macd.MACD柱
+            if self.结构 is 分型结构.顶:
+                return self.左.标的K线.macd.MACD柱 < self.中.标的K线.macd.MACD柱 > self.右.标的K线.macd.MACD柱
+        return False
+
+    @classmethod
+    def 判断分型(cls, 左: "分型", 右: "分型", 模式: str = "中") -> bool:
+        return 左 is 右
+
+    @staticmethod
+    def 从缠K序列中获取分型(K线序列: List[缠论K线], 中: 缠论K线) -> "分型":
+        索引 = K线序列.index(中)
+        try:
+            return 分型(左=K线序列[索引 - 1], 中=中, 右=K线序列[索引 + 1])
+        except IndexError:
+            return 分型(左=K线序列[索引 - 1], 中=中, 右=None)
+
+    @staticmethod
+    def 向序列中添加(分型序列: List["分型"], 当前分型: "分型"):
+        if not 分型序列 and 当前分型.结构 not in (分型结构.顶, 分型结构.底):
+            raise ValueError("首次添加分型不为 顶底", 当前分型)
+        if 分型序列:
+            if 分型序列[-1].结构 is 当前分型.结构:
+                raise ValueError("分型相同无法添加", 分型序列[-1], 当前分型)
+            if 分型序列[-1].右 is None:
+                print("分型.向序列中添加, 分型异常", 分型序列[-1])
+
+        分型序列.append(当前分型)
+
+
+class 虚线(object):
+    __slots__ = ["标识", "序号", "级别", "文", "武", "有效性", "基础序列", "特征序列", "实_中枢序列", "虚_中枢序列", "合_中枢序列", "确认K线", "模式", "_特征序列_显示", "前一缺口", "前一结束位置", "短路修正"]
+
+    def __init__(self, 序号: int, 标识: str, 文: 分型, 武: 分型, 级别: int, 有效性: bool = True):
+        self.序号 = 序号
+        self.标识 = 标识
+        self.级别 = 级别
+
+        self.文 = 文
+        self.武 = 武
+
+        self.有效性 = 有效性
+
+        self.基础序列: List["虚线"] = []
+        self.特征序列: List[Optional[线段特征]] = []
+
+        self.实_中枢序列: List["中枢"] = []
+        self.虚_中枢序列: List["中枢"] = []
+        self.合_中枢序列: List["中枢"] = []
+        self.确认K线: Optional[缠论K线] = None
+        self.模式: str = "文武"
+        self._特征序列_显示 = False
+        self.前一缺口: Optional[缺口] = None
+        self.前一结束位置 = None
+        self.短路修正 = False
+
+    def __str__(self):
+        if self.标识 == "笔":
+            return f"笔({self.序号}, {self.方向}, {self.文}, {self.武}, 周期: {self.文.中.周期}, 数量: {self.武.中.序号 - self.文.中.序号 + 1})"
+        else:
+            return f"{self.标识}<{self.序号}, {线段.四象(self)}, {self.方向}, {self.文}, {self.武}, 数量: {len(self.基础序列)}, 缺口: {线段.获取缺口(self)}, {self.确认K线}>"
+
+    def __repr__(self):
+        return self.__str__()
+
+    @property
+    def 笔序列(self):
+        return self.基础序列
+
+    @property
+    def 图表标题(self) -> str:
+        return f"{self.文.中.标识}:{self.文.中.周期}:{self.标识}:{self.序号}"
+
+    @property
+    def 方向(self) -> "相对方向":
+        match (self.文.结构, self.武.结构):
+            case (分型结构.顶, 分型结构.底):
+                return 相对方向.向下
+            case (分型结构.顶, 分型结构.下):
+                return 相对方向.向下
+
+            case (分型结构.底, 分型结构.顶):
+                return 相对方向.向上
+            case (分型结构.底, 分型结构.上):
+                return 相对方向.向上
+
+            case _:
+                raise RuntimeError("无法识别的方向", self.文.结构, self.武.结构)
+
+    @property
+    def 高(self) -> float:
+        """if self.模式 != "文武":
+        if type(self[0] is 笔):
+            return max(self.__基础序列__, key=lambda x: x.高).高"""
+
+        if self.方向 is 相对方向.向上:
+            return self.武.中.高
+        return self.文.中.高
+
+    @property
+    def 低(self) -> float:
+        """if self.模式 != "文武":
+        if type(self[0] is 笔):
+            return min(self.__基础序列__, key=lambda x: x.低).低"""
+        if self.方向 is 相对方向.向下:
+            return self.武.中.低
+        return self.文.中.低
+
+    def 之前是(self, 之前: "虚线") -> bool:
+        if self.标识 == 之前.标识:
+            return 分型.判断分型(之前.武, self.文)
+        return False
+
+    def 之后是(self, 之后: "虚线") -> bool:
+        if self.标识 == 之后.标识:
+            return 分型.判断分型(self.武, 之后.文)
+        return False
+
+    def 获取普K序列(self, 观察员: "观察者") -> List[K线]:
+        return K线.截取(观察员.普通K线序列, self.文.中.标的K线, self.武.中.标的K线)
+
+    def 获取缠K序列(self, 观察员: "观察者") -> List[缠论K线]:
+        return 缠论K线.截取(观察员.缠论K线序列, self.文.中, self.武.中)
+
+    def 获取数据文本(self):
+        if self.标识 == "笔":
+            return f"{self.标识}, {self.序号}, {self.级别}, 文:({int(self.文.时间戳.timestamp())},{self.文.分型特征值:g}), 武:({int(self.武.时间戳.timestamp())},{self.武.分型特征值:g}), {self.有效性}"
+        前, 后, 三, 贯穿伤 = 线段.分割序列(self)
+        return f"{self.标识}, {self.序号}, {self.级别}, 文:({int(self.文.时间戳.timestamp())},{self.文.分型特征值:g}), 武:({int(self.武.时间戳.timestamp())},{self.武.分型特征值:g}), {self.有效性}, {len(self.基础序列)}, {线段.特征序列状态(self)}, (前: {str(前)}, 后: {str(后)}, 三: {str(三)}, 伤: {str(贯穿伤)}), 实: {str(self.实_中枢序列)}, 虚: {str(self.虚_中枢序列)}, 合: {str(self.合_中枢序列)}, {self.模式}, {str(self.前一缺口)}, {str(self.前一结束位置)}, {self.短路修正}"
+
+    @classmethod
+    def 创建笔(cls, 文: 分型, 武: 分型, 有效性: bool = True) -> "虚线":
+        return 虚线(0, "笔", 文, 武, 1, 有效性)
+
+    @classmethod
+    def 创建线段(cls, 虚线序列: List["虚线"]) -> "虚线":
+        文 = 虚线序列[0].文
+        武 = 虚线序列[-1].武
+        标识 = "线段" if 虚线序列[0].标识 == "笔" else f"线段<{虚线序列[0].标识}>"
+        段 = 虚线(0, 标识, 文, 武, 虚线序列[0].级别 + 1)
+        段.特征序列 = [None] * 3
+        段.实_中枢序列 = []
+        段.虚_中枢序列 = []
+        段.合_中枢序列 = []
+        段.基础序列 = 虚线序列
+        return 段
+
+    @classmethod
+    def 缠K买卖点模式(cls, 模式: str, 缠K: "缠论K线", 配置: 缠论配置):
+        match 模式:
+            case "全量":
+                return cls.买卖点全量匹配(缠K)
+            case "任意":
+                return cls.买卖点任意匹配(缠K)
+            case "配置":
+                return cls.买卖点配置匹配(缠K, 配置)
+            case "相对":
+                return cls.买卖点相对匹配(缠K)
+        return False
+
+    @classmethod
+    def 买卖点配置匹配(cls, 缠K: "缠论K线", 配置: 缠论配置):
+        match 配置.买卖点_指标匹配_MACD, 配置.买卖点_指标匹配_KDJ, 配置.买卖点_指标匹配_RSI:
+            case True, True, True:
+                return 缠K.与MACD柱子匹配 and 缠K.与KDJ匹配 and 缠K.与RSI匹配
+            case False, False, False:
+                ...
+
+            case True, False, True:
+                return 缠K.与MACD柱子匹配 and 缠K.与RSI匹配
+            case False, True, False:
+                return 缠K.与KDJ匹配
+
+            case True, False, False:
+                return 缠K.与MACD柱子匹配
+            case False, True, True:
+                return 缠K.与KDJ匹配 and 缠K.与RSI匹配
+
+            case False, False, True:
+                return 缠K.与RSI匹配
+            case True, True, False:
+                return 缠K.与MACD柱子匹配 and 缠K.与KDJ匹配
+        return False
+
+    @classmethod
+    def 买卖点任意匹配(cls, 缠K: "缠论K线"):
+        return any([缠K.与MACD柱子匹配, 缠K.与KDJ匹配, 缠K.与RSI匹配])
+
+    @classmethod
+    def 买卖点全量匹配(csl, 缠K: "缠论K线"):
+        return all([缠K.与MACD柱子匹配, 缠K.与KDJ匹配, 缠K.与RSI匹配])
+
+    @classmethod
+    def 买卖点相对匹配(cls, 缠K: "缠论K线"):
+        混沌槽 = [缠K.与MACD柱子匹配, 缠K.与KDJ匹配, 缠K.与RSI匹配]
+        return len([匹配 for 匹配 in 混沌槽 if 匹配]) >= 2
+
+    @classmethod
+    def 计算MACD柱子均值(cls, 普K序列: List[K线], 实线: "虚线") -> float:
+        K线序列: List[K线] = K线.截取(普K序列, 实线.文.中.标的K线, 实线.武.中.标的K线)
+        return sum([abs(K.macd.MACD柱) for K in K线序列]) / len(K线序列)
+
+    @classmethod
+    def 计算MACD柱子均值_阴(cls, 普K序列: List[K线], 实线: "虚线") -> float:
+        K线序列: List[K线] = K线.截取(普K序列, 实线.文.中.标的K线, 实线.武.中.标的K线)
+        总 = [abs(K.macd.MACD柱) for K in K线序列 if K.macd.MACD柱 < 0]
+        if 总:
+            return sum(总) / len(总)
+        return False
+
+    @classmethod
+    def 计算MACD柱子均值_阳(cls, 普K序列: List[K线], 实线: "虚线") -> float:
+        K线序列: List[K线] = K线.截取(普K序列, 实线.文.中.标的K线, 实线.武.中.标的K线)
+        总 = [abs(K.macd.MACD柱) for K in K线序列 if K.macd.MACD柱 > 0]
+        if 总:
+            return sum(总) / len(总)
+        return False
+
+    @classmethod
+    def 武之全量MACD均值(cls, 普K序列: List[K线], 实线: "虚线") -> bool:
+        """
+        小于均值则背驰
+        """
+        return abs(实线.武.中.标的K线.macd.MACD柱) < cls.计算MACD柱子均值(普K序列, 实线)
+
+    @classmethod
+    def 武之MACD均值(cls, 普K序列: List[K线], 实线: "虚线") -> bool:
+        """
+        小于均值则背驰
+        """
+        if 实线.方向 is 相对方向.向上:
+            return cls.武之MACD均值_阳(普K序列, 实线)
+        else:
+            return cls.武之MACD均值_阴(普K序列, 实线)
+
+    @classmethod
+    def 武之MACD均值_阴(cls, 普K序列: List[K线], 实线: "虚线") -> bool:
+        """
+        小于均值则背驰
+        """
+        return abs(实线.武.中.标的K线.macd.MACD柱) < abs(cls.计算MACD柱子均值_阴(普K序列, 实线))
+
+    @classmethod
+    def 武之MACD均值_阳(cls, 普K序列: List[K线], 实线: "虚线") -> bool:
+        """
+        小于均值则背驰
+        """
+        return abs(实线.武.中.标的K线.macd.MACD柱) < abs(cls.计算MACD柱子均值_阳(普K序列, 实线))
+
+    @classmethod
+    def 武之MACD极值(cls, 普K序列: List[K线], 实线: "虚线") -> bool:
+        """
+        最高最低
+        """
+        K线序列: List[K线] = K线.截取(普K序列, 实线.文.中.标的K线, 实线.武.中.标的K线)
+        所有柱子 = [K.macd.MACD柱 for K in K线序列]
+        if 实线.武.中.标的K线.macd.MACD柱 > 0:
+            取值函数 = max
+        else:
+            取值函数 = min
+        if 取值函数(所有柱子) == 实线.武.中.标的K线.macd.MACD柱:
+            return True
+        return False
+
+    @classmethod
+    def 计算K线序列MACD趋向背驰(cls, 普K序列: Sequence["K线"], 方向: 相对方向):
+        if 方向 is 相对方向.向上:
+            柱子序列 = [k线 for k线 in 普K序列 if k线.macd.MACD柱 > 0]
+            if not 柱子序列:
+                return [False, False, False]
+            最高柱子 = max(柱子序列, key=lambda k线: k线.macd.MACD柱)
+            最低柱子 = min(柱子序列, key=lambda k线: k线.macd.MACD柱)
+            排序柱子 = sorted(柱子序列, key=lambda k线: k线.macd.MACD柱)
+            离差值序列 = [k线 for k线 in 普K序列 if k线.macd.DIF > 0]
+            最高离差值 = max(柱子序列, key=lambda k线: k线.macd.DIF)
+            最低离差值 = min(柱子序列, key=lambda k线: k线.macd.DIF)
+            信号线序列 = [k线 for k线 in 普K序列 if k线.macd.DEA > 0]
+            最高信号线 = max(柱子序列, key=lambda k线: k线.macd.DEA)
+            最低信号线 = min(柱子序列, key=lambda k线: k线.macd.DEA)
+
+            结果 = []
+            柱子 = [最高柱子, 普K序列[-1]]
+            柱子.sort(key=lambda k线: k线.时间戳)
+            if 柱子[0].macd.MACD柱 > 柱子[1].macd.MACD柱 and 柱子[0].高 < 柱子[1].高:
+                结果.append(True)
+            else:
+                结果.append(False)
+
+            柱子 = [最高离差值, 普K序列[-1]]
+            if 柱子[0].macd.DIF > 柱子[1].macd.DIF and 柱子[0].高 < 柱子[1].高:
+                结果.append(True)
+            else:
+                结果.append(False)
+
+            柱子 = [最高信号线, 普K序列[-1]]
+            if 柱子[0].macd.DEA > 柱子[1].macd.DEA and 柱子[0].高 < 柱子[1].高:
+                结果.append(True)
+            else:
+                结果.append(False)
+
+            return 结果
+        else:
+            柱子序列 = [k线 for k线 in 普K序列 if k线.macd.MACD柱 < 0]
+            if not 柱子序列:
+                return [False, False, False]
+            最高柱子 = max(柱子序列, key=lambda k线: abs(k线.macd.MACD柱))
+            最低柱子 = min(柱子序列, key=lambda k线: abs(k线.macd.MACD柱))
+            排序柱子 = sorted(柱子序列, key=lambda k线: abs(k线.macd.MACD柱))
+            离差值序列 = [k线 for k线 in 普K序列 if k线.macd.DIF < 0]
+            最高离差值 = max(柱子序列, key=lambda k线: abs(k线.macd.DIF))
+            最低离差值 = min(柱子序列, key=lambda k线: abs(k线.macd.DIF))
+            信号线序列 = [k线 for k线 in 普K序列 if k线.macd.DEA < 0]
+            最高信号线 = max(柱子序列, key=lambda k线: abs(k线.macd.DEA))
+            最低信号线 = min(柱子序列, key=lambda k线: abs(k线.macd.DEA))
+
+            结果 = []
+            柱子 = [最高柱子, 普K序列[-1]]
+            柱子.sort(key=lambda k线: k线.时间戳)
+            if 柱子[0].macd.MACD柱 < 柱子[1].macd.MACD柱 and 柱子[0].低 > 柱子[1].低:
+                结果.append(True)
+            else:
+                结果.append(False)
+
+            柱子 = [最高离差值, 普K序列[-1]]
+            if 柱子[0].macd.DIF < 柱子[1].macd.DIF and 柱子[0].低 > 柱子[1].低:
+                结果.append(True)
+            else:
+                结果.append(False)
+
+            柱子 = [最高信号线, 普K序列[-1]]
+            if 柱子[0].macd.DEA < 柱子[1].macd.DEA and 柱子[0].低 > 柱子[1].低:
+                结果.append(True)
+            else:
+                结果.append(False)
+
+            return 结果
+
+    @classmethod
+    @lru_cache(maxsize=128)
+    def 买卖意义(cls, 实线: "虚线", 观察员: "观察者") -> Tuple[bool, str]:
+        """
+        静止是相对的，而运动是绝对的
+
+        """
+        普K序列: List[K线] = 观察员.普通K线序列
+        配置: 缠论配置 = 观察员.配置
+        if 实线.标识 not in ("笔", "线段", "线段<线段>"):
+            return False, "标识不在范围内"
+        if 实线.武.中.标的K线.kdj.K is None or 实线.武.中.标的K线.kdj.D is None or 实线.武.中.标的K线.kdj.J is None:
+            return False, "KDJ指标不完整"
+        意义 = cls.缠K买卖点模式(配置.买卖点_指标模式, 实线.武.中, 配置)
+        结果 = False
+        背驰过 = 笔.是否背驰过(实线, 观察员) if 实线.标识 == "笔" else 线段.是否背驰过(实线, 观察员)
+        if 意义:  # and self.武.强度 in ("强", ""):
+            if 实线.标识 == "笔":
+                if cls.武之MACD均值(普K序列, 实线):
+                    return True, "武之MACD均值"
+                if cls.武之MACD极值(普K序列, 实线) and 背驰过:
+                    return True, "背驰过且极值"
+                else:
+                    if 实线.武.与MACD柱子分型匹配:
+                        return True, f"背驰过:{len(背驰过)},极值:{cls.武之MACD极值(普K序列, 实线)},柱子分型匹配"
+            if 实线.标识 != "笔" and 线段.判断线段内部是否背驰(实线, 观察员):
+                return True, "线段内部背驰"
+
+        if not 结果 and 意义 and 实线.武.中.与MACD柱子匹配:
+            if cls.武之MACD极值(普K序列, 实线) and len(背驰过) > 2:
+                return True, "没结果, 极值, 柱子分型匹配, 背驰过大于2次"
+        return 结果, ""
+
+    @classmethod
+    def 计算MACD柱子分段(cls, k线序列: List["K线"]) -> Tuple[List[List["K线"]], ...]:
+        if not k线序列:
+            return ()
+
+        def 符号(x: float) -> str:
+            if x > 0:
+                return "正"
+            else:
+                return "负"
+
+        当前符号 = 符号(k线序列[0].macd.MACD柱)
+        当前段柱子 = [k线序列[0].macd.MACD柱]
+        结果 = []
+
+        for i in range(1, len(k线序列)):
+            新符号 = 符号(k线序列[i].macd.MACD柱)
+            if 新符号 == 当前符号:
+                当前段柱子.append(k线序列[i].macd.MACD柱)
+            else:
+                结果.append(当前段柱子)
+                当前段柱子 = [k线序列[i].macd.MACD柱]
+                当前符号 = 新符号
+        return tuple(结果)
+
+    @classmethod
+    def 密集区域按间隔(cls, 交叉标记: List[int], 最大间隔: int = 5, 最少交叉数: int = 3) -> List[Tuple[int, int, int]]:
+        """
+        交叉标记: 长度为len(macd_list)的列表，0=无交叉, 1=金叉, -1=死叉
+        最大间隔: 相邻交叉索引差 ≤ 此值则归入同一密集区
+        最少交叉数: 一个密集区内至少包含的交叉次数
+        返回: [(起始交叉索引, 结束交叉索引, 区内交叉次数), ...]
+        """
+        # 提取所有交叉点的索引
+        交叉索引 = [i for i, v in enumerate(交叉标记) if v != 0]
+        if not 交叉索引:
+            return []
+
+        密集区 = []
+        当前块起始 = 交叉索引[0]
+        当前块交叉数 = 1
+
+        for i in range(1, len(交叉索引)):
+            prev_idx = 交叉索引[i - 1]
+            curr_idx = 交叉索引[i]
+            if curr_idx - prev_idx <= 最大间隔:
+                当前块交叉数 += 1
+            else:
+                # 当前块结束
+                if 当前块交叉数 >= 最少交叉数:
+                    密集区.append((当前块起始, prev_idx, 当前块交叉数))
+                # 开始新块
+                当前块起始 = curr_idx
+                当前块交叉数 = 1
+
+        # 处理最后一个块
+        if 当前块交叉数 >= 最少交叉数:
+            密集区.append((当前块起始, 交叉索引[-1], 当前块交叉数))
+
+        return 密集区
+
+    @classmethod
+    def 统计MACD行为(cls, 普K序列: List[K线], 最大间隔: int = 8, 最少交叉数: int = 3) -> dict:
+        # 1. 穿越零轴计数
+        dif_up = dif_down = dea_up = dea_down = 0
+        for i in range(1, len(普K序列)):
+            pre, cur = 普K序列[i - 1].macd, 普K序列[i].macd
+            if pre.DIF is None or cur.DIF is None:
+                continue
+            if pre.DIF < 0 <= cur.DIF:
+                dif_up += 1
+            elif pre.DIF > 0 >= cur.DIF:
+                dif_down += 1
+            if pre.DEA < 0 <= cur.DEA:
+                dea_up += 1
+            elif pre.DEA > 0 >= cur.DEA:
+                dea_down += 1
+
+        # 2. DIF与DEA交叉（带标记）
+        golden = death = 0
+        交叉标记 = [0]  # 第0个位置无前值，先填0
+        for i in range(1, len(普K序列)):
+            pre, cur = 普K序列[i - 1].macd, 普K序列[i].macd
+            if pre.DIF is None or cur.DIF is None or pre.DEA is None or cur.DEA is None:
+                交叉标记.append(0)
+                continue
+            if pre.DIF <= pre.DEA and cur.DIF > cur.DEA:
+                golden += 1
+                交叉标记.append(1)
+            elif pre.DIF >= pre.DEA and cur.DIF < cur.DEA:
+                death += 1
+                交叉标记.append(-1)
+            else:
+                交叉标记.append(0)
+
+        # 3. 按间隔密集区域
+        密集区 = cls.密集区域按间隔(交叉标记, 最大间隔=最大间隔, 最少交叉数=最少交叉数)
+
+        return {
+            "DIF上穿0": dif_up,
+            "DIF下穿0": dif_down,
+            "DEA上穿0": dea_up,
+            "DEA下穿0": dea_down,
+            "金叉次数": golden,
+            "死叉次数": death,
+            "密集交叉区域": 密集区,  # (起始交叉索引, 结束交叉索引, 交叉次数)
+        }
+
+
+class 笔(object):
+    __slots__ = []
+
+    @staticmethod
+    def 获取缠K数量(缠K序列: List[缠论K线], 笔序列: List[虚线], 配置: 缠论配置) -> int:
+        实际数量 = len(缠K序列)
+        if 实际数量 >= 配置.笔内元素数量:
+            return 实际数量
+
+        if 配置.笔弱化 and 实际数量 >= 3:
+            实际高点 = 笔.实际高点(缠K序列, 配置.笔内相同终点取舍)
+            实际低点 = 笔.实际低点(缠K序列, 配置.笔内相同终点取舍)
+            原始数量 = 1 + abs(实际低点.标的K线.序号 - 实际高点.标的K线.序号)
+            if 原始数量 >= 配置.笔内元素数量:
+                return 配置.笔内元素数量
+
+            if 笔序列:
+                筆 = 笔.根据缠K找笔(笔序列, 实际高点) or 笔.根据缠K找笔(笔序列, 实际低点)
+                if 筆:
+                    if 筆.方向 is 相对方向.向上 and 实际低点.低 < 筆.低:
+                        if 原始数量 >= 配置.笔弱化_原始数量:
+                            return 配置.笔内元素数量
+                    if 筆.方向 is 相对方向.向下 and 实际低点.低 > 筆.高:
+                        if 原始数量 >= 配置.笔弱化_原始数量:
+                            return 配置.笔内元素数量
+
+        return 实际数量
+
+    @staticmethod
+    def 次高(缠K序列: List[缠论K线], 笔内相同终点取舍: bool) -> 缠论K线:
+        序列 = sorted(缠K序列, key=lambda k: k.高)
+        highs: List[缠论K线] = [k for k in 序列 if k.高 != 序列[-1].高]  # 排除
+        highs: List[缠论K线] = [k for k in highs if k.高 == highs[-1].高]  # 筛选
+        highs.sort(key=lambda k: k.时间戳)  # 排序
+        return highs[-1] if 笔内相同终点取舍 else highs[0]
+
+    @staticmethod
+    def 次低(缠K序列: List[缠论K线], 笔内相同终点取舍: bool) -> 缠论K线:
+        序列 = sorted(缠K序列, key=lambda k: k.低)
+        lows: List[缠论K线] = [k for k in 序列 if k.低 != 序列[0].低]
+        lows: List[缠论K线] = [k for k in lows if k.低 == lows[0].低]
+        lows.sort(key=lambda k: k.时间戳)
+        return lows[-1] if 笔内相同终点取舍 else lows[0]
+
+    @staticmethod
+    def 实际高点(缠K序列: List[缠论K线], 笔内相同终点取舍: bool) -> 缠论K线:
+        序列 = sorted(缠K序列, key=lambda k: k.高)
+        highs: List[缠论K线] = [k for k in 序列 if k.高 == 序列[-1].高]
+        highs.sort(key=lambda k: k.时间戳)
+        return highs[-1] if 笔内相同终点取舍 else highs[0]
+
+    @staticmethod
+    def 实际低点(缠K序列: List[缠论K线], 笔内相同终点取舍: bool) -> 缠论K线:
+        序列 = sorted(缠K序列, key=lambda k: k.低)
+        lows: List[缠论K线] = [k for k in 序列 if k.低 == 序列[0].低]
+        lows.sort(key=lambda k: k.时间戳)
+        return lows[-1] if 笔内相同终点取舍 else lows[0]
+
+    @staticmethod
+    def 相对关系(筆: 虚线, 配置: 缠论配置) -> bool:
+        if 配置.笔内起始分型包含整笔:
+            有效序列 = [k线 for k线 in (筆.文.左, 筆.文.中, 筆.文.右) if k线 is not None]
+            文 = 缺口(max(有效序列, key=lambda k: k.高).高, min(有效序列, key=lambda k: k.低).低)
+            有效序列 = [k线 for k线 in (筆.武.左, 筆.武.中, 筆.武.右 if 配置.笔内起始分型包含整笔_包括右 else None) if k线 is not None]  # 排除 右
+            武 = 缺口(max(有效序列, key=lambda k: k.高).高, min(有效序列, key=lambda k: k.低).低)
+            相对关系 = 相对方向.分析(文.高, 文.低, 武.高, 武.低)
+        else:
+            相对关系 = 相对方向.分析(筆.文.中.高, 筆.文.中.低, 筆.武.中.高, 筆.武.中.低)
+            if 配置.笔内原始K线包含整笔 and 相对方向.分析(筆.文.中.标的K线.高, 筆.文.中.标的K线.低, 筆.武.中.标的K线.高, 筆.武.中.标的K线.低).是否包含():  # TODO 建议增加相关配置
+                return False
+
+        if 筆.方向 is 相对方向.向下:
+            return 相对关系.是否向下()
+        return 相对关系.是否向上()
+
+    @classmethod
+    def _弹出旧笔(cls, 分型序列: List[分型], 笔序列: List[虚线], 行号):
+        旧分型 = 分型序列.pop()
+        if 笔序列:
+            旧笔 = 笔序列.pop()
+            assert 旧笔.武 is 旧分型, f"最后一笔终点错误{行号}"
+            旧笔.有效性 = False
+
+    @classmethod
+    def _添加新笔(cls, 分型序列: List[分型], 笔序列: List[虚线], 待添加分型: "分型", 待添加新笔: 虚线, 行号):
+        if not 分型序列 and 待添加分型.结构 not in (分型结构.顶, 分型结构.底):
+            raise ValueError("首次添加分型不为 顶底", 待添加分型)
+        if 分型序列:
+            if 分型序列[-1].结构 is 待添加分型.结构:
+                raise ValueError("分型相同无法添加", 分型序列[-1], 待添加分型)
+            if 分型序列[-1].右 is None:
+                print("分型.向序列中添加, 分型异常", 分型序列[-1])
+
+        分型序列.append(待添加分型)
+        if 笔序列 and not 笔序列[-1].之后是(待添加新笔):
+            raise ValueError("笔.向序列中添加 不连续", 笔序列[-1], 待添加新笔)
+
+        if 笔序列:
+            待添加新笔.序号 = 笔序列[-1].序号 + 1
+            if 待添加新笔.武.左 is None and 待添加新笔.武.右 is None:
+                待添加新笔.有效性 = False
+            if 笔序列[-1].武.结构 in (分型结构.上, 分型结构.下):
+                print(f"_添加新笔[{行号}] 出现无效分型", 笔序列[-1])
+
+        笔序列.append(待添加新笔)
+
+    @classmethod
+    def 分析(cls, 当前分型: Optional[分型], 分型序列: List[分型], 笔序列: List[虚线], 缠K序列: List[缠论K线], 普K序列: List[K线], 递归层次: int, 配置: 缠论配置):
+        if 当前分型 is None:
+            return 递归层次
+
+        if 递归层次 > 64:
+            print(f"笔.分析 递归深度超出 64 < {递归层次}")
+            # return 递归层次
+
+        if 当前分型.结构 not in (分型结构.顶, 分型结构.底):
+            return 递归层次
+
+        if not 分型序列:
+            if 当前分型.结构 in (分型结构.顶, 分型结构.底):
+                分型序列.append(当前分型)
+            return 递归层次
+
+        笔递归分析 = 笔.分析
+
+        之前分型 = 分型序列[-1]
+        if (之前分型.中.时间戳 == 当前分型.中.时间戳) or (之前分型.结构 in (分型结构.上, 分型结构.下)):
+            笔._弹出旧笔(分型序列, 笔序列, sys._getframe().f_lineno)
+            if not 分型序列:
+                if 当前分型.右 is not None:
+                    分型.向序列中添加(分型序列, 当前分型)
+                return 递归层次
+
+        之前分型 = 分型序列[-1]
+        if 之前分型.中.时间戳 > 当前分型.中.时间戳 and 之前分型.中.序号 - 当前分型.中.序号 > 1:
+            # raise RuntimeError(f"时序错误-{递归层次}, {之前分型}, {当前分型}")
+            print(colored(f"时序错误-{递归层次}, {之前分型}, {当前分型}", "red"))
+            return 递归层次
+
+        if 配置.笔弱化 and 笔序列:
+            前一笔 = 笔序列[-1]
+            if 前一笔.武.中.序号 - 前一笔.文.中.序号 + 1 == 3:
+                if (前一笔.方向.是否向上() and 前一笔.低 > 当前分型.分型特征值 and 当前分型.结构 is 分型结构.底) or (前一笔.方向.是否向下() and 前一笔.高 < 当前分型.分型特征值 and 当前分型.结构 is 分型结构.顶):
+                    笔._弹出旧笔(分型序列, 笔序列, sys._getframe().f_lineno)
+                    return 笔递归分析(当前分型, 分型序列, 笔序列, 缠K序列, 普K序列, 递归层次 + 1, 配置)
+
+        if 之前分型.结构 is not 当前分型.结构:
+            基础序列 = 缠论K线.截取(缠K序列, 之前分型.中, 当前分型.中)
+            当前笔 = 虚线.创建笔(文=之前分型, 武=当前分型, 有效性=True)
+            if 笔.获取缠K数量(基础序列, 笔序列, 配置) >= 配置.笔内元素数量:
+                if 之前分型.结构 is 分型结构.顶 and 当前分型.结构 is 分型结构.底:
+                    文官 = 笔.实际高点(基础序列, False)
+                else:
+                    文官 = 笔.实际低点(基础序列, False)
+
+                if 文官 is not 之前分型.中:
+                    临时分型 = 分型.从缠K序列中获取分型(缠K序列, 文官)
+                    if 之前分型.结构 is 分型结构.顶 and 当前分型.结构 is 分型结构.底:
+                        assert 临时分型.结构 is 分型结构.顶, 临时分型
+                    else:
+                        assert 临时分型.结构 is 分型结构.底, 临时分型
+                    递归层次 = 笔递归分析(临时分型, 分型序列, 笔序列, 缠K序列, 普K序列, 递归层次 + 1, 配置)
+                    递归层次 = 笔递归分析(当前分型, 分型序列, 笔序列, 缠K序列, 普K序列, 递归层次 + 1, 配置)
+                    return 递归层次
+
+                if 之前分型.结构 is 分型结构.顶 and 当前分型.结构 is 分型结构.底:
+                    武将 = 笔.实际低点(基础序列, 配置.笔内相同终点取舍)
+                else:
+                    武将 = 笔.实际高点(基础序列, 配置.笔内相同终点取舍)
+
+                if 笔.相对关系(当前笔, 配置) and 当前分型.中 is 武将:
+                    笔._添加新笔(分型序列, 笔序列, 当前分型, 当前笔, sys._getframe().f_lineno)
+                    return 递归层次
+
+                if 配置.笔次级成笔:
+                    if 之前分型.结构 is 分型结构.顶 and 当前分型.结构 is 分型结构.底:
+                        武将 = 笔.次低(基础序列, 配置.笔内相同终点取舍)
+                    else:
+                        武将 = 笔.次高(基础序列, 配置.笔内相同终点取舍)
+                    if 笔.相对关系(当前笔, 配置) and 当前分型.中 is 武将:
+                        笔._添加新笔(分型序列, 笔序列, 当前分型, 当前笔, sys._getframe().f_lineno)
+                        return 递归层次
+
+            else:
+                if 当前分型.右:
+                    临时分型 = 分型.从缠K序列中获取分型(缠K序列, 当前分型.右)
+                    递归层次 = 笔递归分析(临时分型, 分型序列, 笔序列, 缠K序列, 普K序列, 递归层次 + 1, 配置)
+
+        else:
+            分型特征值 = 当前分型.分型特征值
+
+            if (之前分型.结构 is 分型结构.顶 and 之前分型.分型特征值 < 分型特征值) or (之前分型.结构 is 分型结构.底 and 之前分型.分型特征值 > 分型特征值):
+                笔._弹出旧笔(分型序列, 笔序列, sys._getframe().f_lineno)
+                k线序列 = 缠论K线.截取(缠K序列, 之前分型.中, 当前分型.中)
+                if 之前分型.结构 is 分型结构.顶:
+                    武将 = 笔.实际低点(k线序列, 配置.笔内相同终点取舍)
+                else:
+                    武将 = 笔.实际高点(k线序列, 配置.笔内相同终点取舍)
+                临时分型 = 分型.从缠K序列中获取分型(缠K序列, 武将)
+
+                if 分型序列:
+                    递归层次 = 笔递归分析(临时分型, 分型序列, 笔序列, 缠K序列, 普K序列, 递归层次 + 1, 配置)
+                    if 分型序列 and 分型序列[-1] is 临时分型:
+                        # 进行修复错过的笔
+                        for ck in 缠K序列[缠K序列.index(武将) :]:
+                            if ck.分型 in (分型结构.底, 分型结构.顶):
+                                临时分型 = 分型.从缠K序列中获取分型(缠K序列, ck)
+                                递归层次 = 笔递归分析(临时分型, 分型序列, 笔序列, 缠K序列, 普K序列, 递归层次 + 1, 配置)
+                                if 分型序列 and 分型序列[-1] is 临时分型:
+                                    """"""
+                                    # print("笔.分析 事后修复错过的笔", 临时分型, "当前分型", 当前分型)
+
+                    递归层次 = 笔递归分析(当前分型, 分型序列, 笔序列, 缠K序列, 普K序列, 递归层次 + 1, 配置)
+                    return 递归层次
+                else:
+                    分型.向序列中添加(分型序列, 当前分型)
+
+        return 递归层次
+
+    @staticmethod
+    def 以文会友(笔序列: List[虚线], 文: 分型) -> Optional[虚线]:
+        for 筆 in 笔序列:
+            if 筆.文 is 文:
+                return 筆
+        return None
+
+    @staticmethod
+    def 以武会友(笔序列: List[虚线], 武: 分型) -> Optional[虚线]:
+        for 筆 in 笔序列[::-1]:
+            if 筆.武 is 武:
+                return 筆
+        return None
+
+    @staticmethod
+    def 根据缠K找笔(笔序列: List[虚线], 缠K: "缠论K线", 偏移: int = 1):
+        for 筆 in 笔序列[::-1]:
+            if 筆.文.中.序号 - 偏移 <= 缠K.序号 <= 筆.武.中.序号:
+                # if 缠K in 筆.缠K序列[偏移:]:
+                return 筆
+
+        return None
+
+    @classmethod
+    def 自检(cls, 筆: 虚线, 观察员: "观察者") -> bool:
+        笔序列: List[虚线] = 观察员.笔序列
+        配置: 缠论配置 = 观察员.配置
+        基础序列 = 筆.获取缠K序列(观察员)
+        if 笔.获取缠K数量(基础序列, 笔序列, 配置) >= 配置.笔内元素数量:
+            if 筆.方向 is 相对方向.向下 and 筆.文.中 is 笔.实际高点(基础序列, False) and 筆.武.中 is 笔.实际低点(基础序列, 配置.笔内相同终点取舍):
+                return True
+            if 筆.方向 is 相对方向.向上 and 筆.文.中 is 笔.实际低点(基础序列, False) and 筆.武.中 is 笔.实际高点(基础序列, 配置.笔内相同终点取舍):
+                return True
+        return False
+
+    @classmethod
+    def 获取所有停顿位置(cls, 筆: 虚线, 观察员: "观察者"):
+        笔序列 = []
+        文 = 筆.文
+        基础序列 = 筆.获取缠K序列(观察员.观察员)
+        for i in range(3, len(基础序列) - 1):
+            K = 基础序列[i]
+            武 = 分型(基础序列[i - 1], K, 基础序列[i + 1])
+            if K.分型 is 分型结构.顶 and 筆.方向 is 相对方向.向上:
+                当前笔 = 虚线.创建笔(文=文, 武=武)
+                当前笔.序号 = 筆.序号
+                笔.自检(当前笔, 观察员) and 笔序列.append(当前笔)
+
+            if K.分型 is 分型结构.底 and 筆.方向 is 相对方向.向下:
+                当前笔 = 虚线.创建笔(文=文, 武=武)
+                当前笔.序号 = 筆.序号
+                笔.自检(当前笔, 观察员) and 笔序列.append(当前笔)
+
+        return 笔序列
+
+    @classmethod
+    def 是否背驰过(cls, 当前筆: 虚线, 观察员: "观察者"):
+        停顿位置 = 笔.获取所有停顿位置(当前筆, 观察员)
+        结果 = []
+
+        for 筆 in 停顿位置:
+            if all(虚线.计算K线序列MACD趋向背驰(K线.截取(观察员.普通K线序列, 当前筆.文.中.标的K线, 当前筆.武.中.标的K线), 筆.方向)):  # if 筆.武之MACD均值:
+                结果.append(筆.武.中)
+        return 结果
+
+
+class 线段特征(list):
+    __slots__ = ["序号", "标识", "线段方向"]
+
+    def __init__(self, 标识: str, 基础序列: List[虚线], 线段方向: 相对方向):
+        super().__init__(基础序列)
+        self.序号 = 0
+        self.标识: str = 标识
+        self.线段方向: 相对方向 = 线段方向
+
+    @property
+    def 图表标题(self) -> str:
+        return self.标识  # f"{self.标识}:{self.序号}"
+
+    def __str__(self):
+        if not len(self):
+            return colored(f"{self.标识}<{self.线段方向}, 空>", "green")
+        return f"{self.标识}<{self.线段方向}, {self.文}, {self.武}, {len(self)}>"
+
+    def __repr__(self):
+        if not len(self):
+            return colored(f"{self.标识}<{self.线段方向}, 空>", "green")
+        return f"{self.标识}<{self.线段方向}, {self.文}, {self.武}, {len(self)}>"
+
+    @property
+    def 文(self) -> 分型:
+        if self.线段方向 is 相对方向.向上:  # 取高高
+            return max(
+                [线.文 for 线 in self],
+                key=lambda o: (o.中.分型特征值, o.中.时间戳),
+            )
+        else:
+            return min(
+                [线.文 for 线 in self],
+                key=lambda o: (o.中.分型特征值, -o.中.时间戳.timestamp()),
+            )
+
+    @property
+    def 武(self) -> 分型:
+        if self.线段方向 is 相对方向.向上:
+            return max(
+                [线.武 for 线 in self],
+                key=lambda o: (o.中.分型特征值, o.中.时间戳),
+            )
+        else:
+            return min(
+                [线.武 for 线 in self],
+                key=lambda o: (o.中.分型特征值, -o.中.时间戳.timestamp()),
+            )
+
+    @property
+    def 高(self) -> float:
+        return max([self.文, self.武], key=lambda fx: fx.中.分型特征值).中.分型特征值
+
+    @property
+    def 低(self) -> float:
+        return min([self.文, self.武], key=lambda fx: fx.中.分型特征值).中.分型特征值
+
+    @property
+    def 方向(self) -> 相对方向:
+        return self.线段方向.翻转()
+
+    def 添加(self, 待添加虚线: Union[虚线]):
+        if 待添加虚线.方向 == self.线段方向:
+            raise ValueError("方向不匹配", self.线段方向, 待添加虚线, self)
+        self.append(待添加虚线)
+
+    def 删除(self, 待删除虚线: Union[虚线]):
+        if 待删除虚线.方向 == self.方向:
+            raise ValueError("方向不匹配", self.线段方向, 待删除虚线, self)
+        self.remove(待删除虚线)
+
+    @classmethod
+    def 新建(cls, 虚线序列: List[虚线], 线段方向: 相对方向) -> "线段特征":
+        return 线段特征(标识=f"特征<{虚线序列[0].__class__.__name__}>", 基础序列=虚线序列, 线段方向=线段方向)
+
+    @classmethod
+    def 静态分析(cls, 虚线序列: List[虚线], 线段方向: 相对方向, 四象: str, 是否忽视: bool = False) -> List["线段特征"]:
+        """
+        :param 虚线序列:
+        :param 线段方向:
+        :param 四象: 老阴，老阳，少阴，小阳
+            老阴 老阳 分别代表 缺口顶分型后的向下线段 与 缺口底分型后的向上线段
+        :return: 特征序列元组
+        """
+        # 确定需要合并的方向序列
+        if 四象 in ("老阳", "老阴") and not 是否忽视:
+            # 特征序列带有缺口时 要严格处理包含关系
+            需要被合并方向序列 = (相对方向.顺, 相对方向.逆, 相对方向.同)
+            # 需要被合并方向序列 = (相对方向.顺, 相对方向.同)
+        else:
+            需要被合并方向序列 = (相对方向.顺, 相对方向.同)
+
+        特征序列: List[线段特征] = []
+
+        for 当前虚线 in 虚线序列:
+            # ----- 情况1：方向相同（可能触发分型替换）-----
+            if 当前虚线.方向 is 线段方向:
+                # 守卫：特征序列不足3个时，直接跳过本虚线（不执行任何合并）
+                if len(特征序列) < 3:
+                    continue
+
+                左, 中, 右 = 特征序列[-3], 特征序列[-2], 特征序列[-1]
+                结构 = 分型结构.分析(左, 中, 右, 可以逆序包含=True, 忽视顺序包含=True)
+
+                # 条件：向上线段形成顶分型且当前虚线高点高于中，或向下线段形成底分型且当前虚线低点低于中
+                if (线段方向 is 相对方向.向上 and 结构 is 分型结构.顶 and 当前虚线.高 > 中.高) or (线段方向 is 相对方向.向下 and 结构 is 分型结构.底 and 当前虚线.低 < 中.低):
+                    小号虚线 = min(中, key=lambda o: o.序号)
+                    大号虚线 = max(右, key=lambda o: o.序号)
+                    fake = 虚线.创建笔(文=小号虚线.文, 武=大号虚线.武, 有效性=False)
+                    特征序列.pop()
+                    特征序列[-1] = 线段特征.新建([fake], 线段方向)
+                # 无论是否替换，本虚线不进入合并逻辑
+                continue
+
+            # ----- 情况2：方向不同（执行特征序列的合并/添加）-----
+            # 若特征序列为空，直接添加新特征序列
+            if not 特征序列:
+                特征序列.append(线段特征.新建([当前虚线], 线段方向))
+                continue
+
+            # 特征序列非空：检查与最后一个特征序列的方向关系
+            之前线段特征 = 特征序列[-1]
+            if 相对方向.分析(之前线段特征.高, 之前线段特征.低, 当前虚线.高, 当前虚线.低) in 需要被合并方向序列:
+                之前线段特征.添加(当前虚线)
+            else:
+                特征序列.append(线段特征.新建([当前虚线], 线段方向))
+
+        return 特征序列
+
+    @classmethod
+    def 获取分型序列(cls, 特征序列: List):
+        结构序列 = []
+        for i in range(1, len(特征序列) - 1):
+            结构 = 分型结构.分析(特征序列[i - 1], 特征序列[i], 特征序列[i + 1], True, True)
+            结构序列.append(特征分型(特征序列[i - 1], 特征序列[i], 特征序列[i + 1], 结构))
+        if 结构序列:
+            assert 特征序列[-1] is 结构序列[-1].右
+        return 结构序列
+
+
+class 特征分型:
+    __slots__ = ["左", "中", "右", "结构"]
+
+    def __init__(self, 左: 线段特征, 中: 线段特征, 右: 线段特征, 结构: 分型结构):
+        self.左: 线段特征 = 左
+        self.中: 线段特征 = 中
+        self.右: 线段特征 = 右
+        self.结构 = 结构
+
+    def __str__(self):
+        return f"特征分型<{self.结构}, {self.中}>"
+
+    def __repr__(self):
+        return f"特征分型<{self.结构}, {self.中}>"
+
+
+class 线段(object):
+    __slots__ = []
+
+    @classmethod
+    def 添加虚线(cls, 段: 虚线, 筆: 虚线):
+        if len(段.基础序列) and not 分型.判断分型(段.基础序列[-1].武, 筆.文):
+            raise ValueError(f"{段.标识}.添加虚线 不连续", 段.基础序列[-1], 筆)
+
+        if len(段.基础序列) and 段.基础序列[-1].标识 != 筆.标识:
+            raise ValueError(f"{段.标识}.添加虚线 标识不符", 段.基础序列[-1].标识, 筆.标识)
+        段.基础序列.append(筆)
+
+    @classmethod
+    def 武斗(cls, 段: 虚线, 武: 分型, 行号: int):
+        # print(f"{段.标识}.武斗[{行号}], ", 武)
+        if 段.武 is 武:
+            # print(f"{段.标识}.武斗[{行号}], 相同")
+            return
+        if 段.武.分型特征值 == 武.分型特征值 and 段.武.时间戳 != 武.时间戳:
+            print(f"{段.标识}.武斗[{行号}], 发现特征值相等但时间戳不同", 段.武, 武)
+        assert 段.文.结构 is not 武.结构, (f"文武结构相同 {行号}", 段.文, 武)
+        if 武.右 is not None and 分型结构.分析(武.左, 武.中, 武.右) is not 武.结构:
+            raise RuntimeError(分型结构.分析(武.左, 武.中, 武.右), 武.结构)
+        if 段.方向 is 相对方向.向上:
+            if 武.分型特征值 < 段.文.分型特征值:
+                raise RuntimeError(f"向上{段.标识}, 结束点 小于 起点", 段.标识, 段.文, 武)
+            # if max([段.武, 武], key=lambda k: k.分型特征值) is not 武 and 段.模式 == "文武":
+            #     pass  # print(colored(f"{段.标识}.武斗[{行号}] 出现回退 从 {段.武} ==>>> {武}", "red", "on_green"))  # raise RuntimeError(段.武, 武)
+        else:
+            if 武.分型特征值 > 段.文.分型特征值:
+                raise RuntimeError(f"向下{段.标识}, 结束点 大于 起点", 段.标识, 段.文, 武)
+            # if min([段.武, 武], key=lambda k: k.分型特征值) is not 武 and 段.模式 == "文武":
+            #     pass  # print(colored(f"{段.标识}.武斗[{行号}] 出现回退 从 {段.武} ==>>> {武}", "red", "on_green"))  # raise RuntimeError(段.武, 武)
+        段.武 = 武
+
+    @classmethod
+    def 特征分型终结(cls, 段: 虚线) -> bool:
+        """
+        是否符合特征序列 正常分型 终结
+        """
+        特征序列 = 线段特征.静态分析(段.基础序列, 段.方向, 线段.四象(段))
+        if len(特征序列) >= 3:
+            结构 = 分型结构.分析(特征序列[-3], 特征序列[-2], 特征序列[-1], True, True)
+            if 段.方向 is 相对方向.向上:
+                if 结构 is 分型结构.顶:
+                    return True
+            else:
+                if 结构 is 分型结构.底:
+                    return True
+
+        return False
+
+    @classmethod
+    def 特征序列状态(cls, 段: 虚线) -> Tuple[bool, bool, bool]:
+        return tuple(特征 is not None for 特征 in 段.特征序列)
+
+    @classmethod
+    def 获取缺口(cls, 段: 虚线) -> Optional[缺口]:
+        if 段.模式 != "文武":
+            return None
+        左, 中, 右 = 段.特征序列
+        if 左 is None:
+            return None
+        if 中 is None:
+            return None
+        相对关系 = 相对方向.分析(左.高, 左.低, 中.高, 中.低)
+        if 相对关系.是否缺口():
+            高低 = [左.文.分型特征值, 中.文.分型特征值]
+            return 缺口(max(*高低), min(*高低))
+        return None
+
+    @classmethod
+    def 四象(cls, 段: 虚线) -> str:
+        """
+        老阳: 向下线段第一二特征序列有缺口时，后一向上线段
+        老阴: 向上线段第一二特征序列有缺口时，后一向下线段
+        小阳: 向上线段
+        少阴: 向下线段
+        """
+        if 段.前一缺口 is not None:
+            return "老阳" if 段.方向 is 相对方向.向上 else "老阴"
+        return "小阳" if 段.方向 is 相对方向.向上 else "少阴"
+
+    @classmethod
+    def 设置特征序列(cls, 段: 虚线, 序列, 行号):
+        # print(f"线段.设置特征序列[{行号}]", self)
+        if 段.模式 != "文武":
+            return
+
+        for 特征 in 序列:
+            if 特征 and 特征.方向 == 段.方向:
+                raise ValueError(f"特征序列方向不匹配[{行号}]")
+        左, 中, 右 = 序列
+        段.特征序列 = [左, 中, 右]
+        if 右 is not None:
+            基础序列 = []
+            if 右[-1] not in 段.基础序列:
+                raise ValueError()
+            for 元素 in 段.基础序列:
+                基础序列.append(元素)
+                if 元素 is 右[-1]:
+                    break
+
+            if (len(基础序列) >= 6) and (len(基础序列) % 2 == 0):
+                段.基础序列[:] = 基础序列[:]
+            else:
+                raise RuntimeError()
+        else:
+            pass
+
+    @classmethod
+    def 刷新特征序列(cls, 段: 虚线, 配置: 缠论配置):
+        if 段.模式 != "文武":
+            return
+        基础序列 = 段.基础序列
+        if 段.前一结束位置 and 段.前一结束位置 in 基础序列:
+            基础序列 = 段.基础序列[段.基础序列.index(段.前一结束位置) - 1 :]
+
+        特征序列 = 线段特征.静态分析(基础序列, 段.方向, 线段.四象(段), 配置.线段_特征序列忽视老阴老阳)
+        if len(特征序列) >= 3:
+            分型序列 = 线段特征.获取分型序列(特征序列)
+            if (段.方向 is 相对方向.向上 and 分型序列[-1].结构 is 分型结构.顶) or (段.方向 is 相对方向.向下 and 分型序列[-1].结构 is 分型结构.底):
+                线段.设置特征序列(段, [分型序列[-1].左, 分型序列[-1].中, 分型序列[-1].右], sys._getframe().f_lineno)
+
+            else:
+                线段.设置特征序列(段, [特征序列[-2], 特征序列[-1], None], sys._getframe().f_lineno)
+        else:
+            特征序列.extend([None] * (3 - len(特征序列)))
+            线段.设置特征序列(段, 特征序列, sys._getframe().f_lineno)
+
+    @classmethod
+    def 分割序列(cls, 段: 虚线, 所属中枢: Optional["中枢"] = None) -> Tuple[List[虚线], List[虚线], List[虚线], Optional[虚线]]:
+        if 段.模式 != "文武":
+            return 段.基础序列[:], [], [], None
+        if len(段.基础序列) == 0:
+            print(段.标识, 段.序号)
+        assert 段.基础序列[0].文 is 段.文, (段.基础序列[0].文, 段.文)
+        前: List[虚线] = []
+        后: List[虚线] = []
+        第三买卖线 = []
+        贯穿伤 = None
+
+        for 筆 in 段.基础序列:
+            if not 前:
+                前.append(筆)
+                continue
+            if 前[-1].武 is not 段.武 and not 后:
+                前.append(筆)
+
+            if 后:
+                后.append(筆)
+            if 筆.文 is 段.武:
+                后.append(筆)
+
+        状态 = None
+
+        if 所属中枢:
+            所属中枢.本级_第三买卖线 = None
+            尾部 = 段.武
+            if 后:
+                尾部 = 后[-1].武
+            if 所属中枢.高 >= 尾部.分型特征值 >= 所属中枢.低:
+                状态 = "中枢之中"
+            elif 所属中枢.高 < 尾部.分型特征值:
+                状态 = "中枢之上"
+            elif 所属中枢.低 > 尾部.分型特征值:
+                状态 = "中枢之下"
+            assert "中枢" in 状态
+
+        if 状态 == "中枢之上":
+            for 筆 in 段.基础序列[::-1]:
+                if 筆.方向 is 相对方向.向下:
+                    关系 = 相对方向.分析(所属中枢.高, 所属中枢.低, 筆.高, 筆.低)
+                    if 关系 is 相对方向.向上缺口:
+                        第三买卖线.append(筆)
+                    else:
+                        break
+
+        if 状态 == "中枢之下":
+            for 筆 in 段.基础序列[::-1]:
+                if 筆.方向 is 相对方向.向上:
+                    关系 = 相对方向.分析(所属中枢.高, 所属中枢.低, 筆.高, 筆.低)
+                    if 关系 is 相对方向.向下缺口:
+                        第三买卖线.append(筆)
+                    else:
+                        break
+
+        if 第三买卖线 and 所属中枢:
+            第三买卖线.reverse()
+            所属中枢.本级_第三买卖线 = 第三买卖线[0]
+            # 所属中枢.本级_第三买卖线.备注 = 所属中枢.标识
+
+        if 后:
+            if 段.方向.是否向上():
+                if 后[0].武.分型特征值 < 段.文.分型特征值:
+                    贯穿伤 = 后[0]
+            else:
+                if 后[0].武.分型特征值 > 段.文.分型特征值:
+                    贯穿伤 = 后[0]
+
+        return 前, 后, 第三买卖线, 贯穿伤
+
+    @classmethod
+    def 刷新(cls, 段: 虚线, 配置: 缠论配置):
+        if 段.模式 != "文武":
+            return
+        if not len(段.基础序列):
+            print("    线段.刷新 基础序列为空")
+            return
+
+        线段.刷新特征序列(段, 配置)
+        有效特征序列 = [特征 for 特征 in 段.特征序列 if 特征 is not None]
+        if len(有效特征序列) == 3:
+            线段.武斗(段, 段.特征序列[1].文, sys._getframe().f_lineno)
+
+        elif len(有效特征序列) >= 1:
+            最近特征 = 有效特征序列[-1]
+
+            if 最近特征[-1] not in 段.基础序列:
+                特征后一笔 = 笔.以武会友(段.基础序列, 最近特征[-1].武)
+            else:
+                特征后一笔 = 最近特征[-1]
+
+            if 特征后一笔 is not None:
+                序号 = 段.基础序列.index(特征后一笔)
+                if 序号 < len(段.基础序列) - 1:
+                    下一笔 = 段.基础序列[序号 + 1]
+                    if (段.方向 is 相对方向.向上 and 段.高 <= 下一笔.高) or (段.方向 is 相对方向.向下 and 段.低 >= 下一笔.低):
+                        线段.武斗(段, 下一笔.武, sys._getframe().f_lineno)
+            else:
+                print("    线段.刷新 特征后一笔 = None, ", 段, 有效特征序列)
+        else:
+            raise RuntimeError(len(有效特征序列))
+        线段.获取内部中枢序列(段, 配置)
+
+    @classmethod
+    def 序列重置(cls, 段: 虚线, 序列: Sequence):
+        基础序列 = []
+        for 元素 in 段.基础序列:
+            if 元素 not in 序列:
+                break
+            if 基础序列:
+                if not 基础序列[-1].之后是(元素):
+                    break
+            基础序列.append(元素)
+
+        段.基础序列[:] = 基础序列[:]
+        段.特征序列[2] = None
+
+    @classmethod
+    def 查找贯穿伤(cls, 段: 虚线) -> Optional[虚线]:
+        for 贯穿伤 in 段.基础序列[3:]:
+            if 段.方向.是否向上():
+                if 贯穿伤.武.分型特征值 < 段.文.分型特征值:
+                    return 贯穿伤
+            else:
+                if 贯穿伤.武.分型特征值 > 段.文.分型特征值:
+                    return 贯穿伤
+        return None
+
+    @classmethod
+    def 获取内部中枢序列(cls, 段: 虚线, 配置: 缠论配置) -> Tuple[List["中枢"], List["中枢"], List["中枢"]]:
+        # 线段内部如存在中枢则级别比无中枢要大
+        if 段.模式 != "文武":
+            中枢.分析(段.基础序列, 段.合_中枢序列, 标识=f"{段.标识}_{段.序号}_合_")
+            return [], [], 段.合_中枢序列
+        实, 虚, _, _ = 线段.分割序列(段)
+
+        中枢.分析(实, 段.实_中枢序列, 标识=f"{段.标识}_{段.序号}_实_")
+        中枢.分析(虚, 段.虚_中枢序列, 标识=f"{段.标识}_{段.序号}_虚_")
+        中枢.分析(段.基础序列, 段.合_中枢序列, 标识=f"{段.标识}_{段.序号}_合_")
+        return 段.虚_中枢序列, 段.实_中枢序列, 段.合_中枢序列  # 阴 阳 合
+
+    @classmethod
+    def 基础判断(cls, 左: 虚线, 中: 虚线, 右: 虚线, 关系序列: List[相对方向]) -> bool:
+        """
+        连续三笔且重叠
+        """
+
+        if not 左.之后是(中):
+            return False
+        if not 中.之后是(右):
+            return False
+
+        if not 相对方向.分析(左.高, 左.低, 中.高, 中.低).是否包含():
+            return False
+        if not 相对方向.分析(中.高, 中.低, 右.高, 右.低).是否包含():
+            return False
+
+        关系 = 相对方向.分析(左.高, 左.低, 右.高, 右.低)
+        if 关系 not in 关系序列:
+            return False
+
+        if 左.方向 is 相对方向.向下 and not 关系.是否向下():
+            return False
+        if 左.方向 is 相对方向.向上 and not 关系.是否向上():
+            return False
+        return True
+
+    @classmethod
+    def _添加线段(cls, 线段序列: List[虚线], 待添加线段: 虚线, 配置: 缠论配置, 行号: str):
+        if 线段序列 and not 线段序列[-1].之后是(待添加线段):
+            raise ValueError(f"线段.向序列中添加 不连续[{行号}]", 线段序列[-1].武, 待添加线段.文)
+        待添加线段.模式 = "文武"
+
+        if not 线段序列:
+            线段序列.append(待添加线段)
+            return
+
+        之前线段 = 线段序列[-1]
+
+        if not 之前线段.特征序列[2] and not 之前线段.短路修正:
+            assert not 待添加线段.短路修正 and 之前线段.特征序列[2][-1] in 待添加线段.基础序列
+            raise RuntimeError(f"线段._向序列中添加[{行号}], 之前线段.右 = None", 之前线段)
+
+        if 之前线段.基础序列[-1] not in 待添加线段.基础序列 and not 之前线段.短路修正:
+            raise RuntimeError(f"线段._向序列中添加[{行号}], 之前线段[-1] not in 待添加虚线!", 之前线段)
+
+        待添加线段.序号 = 之前线段.序号 + 1
+        待添加线段.前一缺口 = 线段.获取缺口(之前线段)
+        待添加线段.前一结束位置 = 之前线段.基础序列[-1]
+
+        if 线段.四象(之前线段) in ("老阴", "老阳"):
+            待添加线段.前一缺口 = None
+
+        线段序列.append(待添加线段)
+        # print(f"线段._向序列中添加[{行号}]", 待添加虚线)
+
+    @classmethod
+    def _弹出线段(cls, 线段序列: List[虚线], 待弹出线段: 虚线, 配置: 缠论配置, 行号: str):
+        if not 线段序列:
+            return None
+
+        if 线段序列[-1] is not 待弹出线段:
+            raise ValueError("线段._从序列中删除 弹出数据不在列表中", 待弹出线段)
+
+        左, 中, 右 = 待弹出线段.特征序列
+        if 右 is not None:
+            结构 = 分型结构.分析(左, 中, 右, True, True)
+            if 结构 in (分型结构.顶, 分型结构.底) and not 相对方向.分析(左.高, 左.低, 中.高, 中.低).是否缺口():
+                print(colored(f"[警告<{行号}>]:", "yellow"), colored("线段._从序列中删除 发现分型完毕, 且特征序列无缺口", "red"), 待弹出线段)
+
+        线段序列.pop()
+        待弹出线段.前一结束位置 = None
+        待弹出线段.有效性 = False
+
+        return 待弹出线段
+
+    @classmethod
+    def _缺口突破(cls, 线段序列: List[虚线], 配置: 缠论配置, 层级: int) -> bool:
+        当前线段 = 线段序列[-1]
+        当前虚线: 虚线 = 当前线段.基础序列[-1]
+        四象 = 线段.四象(当前线段)
+        同向 = 当前虚线.方向 is 当前线段.方向
+
+        # 条件1：不能同向
+        if 同向:
+            return False
+
+        # 条件2：四象必须是老阳或老阴
+        if 四象 not in ("老阳", "老阴"):
+            return False
+
+        # 条件3：当前线段特征序列[2]必须为None
+        if 当前线段.特征序列[2] is not None:
+            return False
+
+        # 条件4：具体突破方向判断
+        if not ((四象 == "老阳" and 当前虚线.低 < 当前线段.低) or (四象 == "老阴" and 当前虚线.高 > 当前线段.高)):
+            return False
+
+        # 执行修正
+        序列 = 当前线段.基础序列[:]
+        线段._弹出线段(线段序列, 当前线段, 配置, f"{sys._getframe().f_lineno}, {层级}")
+        当前线段 = 线段序列[-1]
+        assert 当前线段.特征序列[2] is not None
+        当前线段基础序列 = 线段.分割序列(当前线段)[0]
+        当前线段基础序列.extend(序列)
+
+        当前线段.基础序列[:] = 当前线段基础序列[:]
+        线段.刷新(当前线段, 配置)
+        return True
+
+    @classmethod
+    def _非缺口下穿刺(cls, 线段序列: List[虚线], 配置: 缠论配置, 层级: int) -> bool:
+        当前线段 = 线段序列[-1]
+        四象 = 线段.四象(当前线段)
+
+        # 外层条件
+        if not (配置.线段_非缺口下穿刺 and 四象 in ("小阳", "少阴") and 当前线段.特征序列[2] is None):
+            return False
+
+        # 查找贯穿伤
+        贯穿伤 = 线段.查找贯穿伤(当前线段)
+        if not 贯穿伤:
+            return False
+
+        # 切割基础序列
+        基础序列 = 当前线段.基础序列[当前线段.基础序列.index(贯穿伤) :]
+
+        # 长度条件
+        if not (len(基础序列) == 4 and len(线段序列) >= 2):
+            return False
+
+        左, 中, 右 = 基础序列[-3], 基础序列[-2], 基础序列[-1]
+
+        # 方向条件
+        if 相对方向.分析(左.高, 左.低, 右.高, 右.低) is not 当前线段.方向:
+            return False
+
+        # 执行修正
+        print(colored(f"[警告<{sys._getframe().f_lineno}, {层级}>]:", "yellow"), colored("线段.修复贯穿伤", "red"), 贯穿伤, 基础序列)  # 异常弹出
+
+        基础序列 = 当前线段.基础序列[:]
+        线段._弹出线段(线段序列, 当前线段, 配置, f"{sys._getframe().f_lineno}, {层级}")
+        当前线段 = 线段序列[-1]
+        当前线段.特征序列[2] = None
+        for 临时虚线 in 基础序列[基础序列.index(当前线段.基础序列[-1]) + 1 :]:
+            线段.添加虚线(当前线段, 临时虚线)
+        线段.刷新(当前线段, 配置)
+
+        if 当前线段.特征序列[2]:
+            段 = 虚线.创建线段([左, 中, 右])
+            线段._添加线段(线段序列, 段, 配置, f"{sys._getframe().f_lineno}, {层级}")
+            段.特征序列[0] = 线段特征.新建([中], 段.方向)
+
+        return True
+
+    @classmethod
+    def _缺口后紧急修正(cls, 线段序列: List[虚线], 配置: 缠论配置, 层级: int) -> bool:
+        当前线段 = 线段序列[-1]
+        四象 = 线段.四象(当前线段)
+
+        # 外层条件检查
+        if not (配置.线段_缺口后紧急修正 and not 配置.线段_特征序列忽视老阴老阳 and 四象 in ("小阳", "少阴") and 当前线段.特征序列[2] is None):
+            return False
+
+        # 内层条件：长度和前一线的四象
+        if not (len(线段序列) >= 2 and 线段.四象(线段序列[-2]) in ("老阴", "老阳")):
+            return False
+
+        基础序列 = 线段.分割序列(当前线段)[1]
+        if len(基础序列) < 3:
+            return False
+
+        需要修正 = False
+        if 当前线段.方向 is 相对方向.向上:
+            if 相对方向.分析(基础序列[0].高, 基础序列[0].低, 基础序列[2].高, 基础序列[2].低) is 相对方向.向下:
+                需要修正 = True
+        else:  # 向下方向
+            if 相对方向.分析(基础序列[0].高, 基础序列[0].低, 基础序列[2].高, 基础序列[2].低) is 相对方向.向上:
+                需要修正 = True
+
+        if not 需要修正:
+            return False
+
+        # 执行修正
+        当前线段.短路修正 = True
+        新段 = 虚线.创建线段(基础序列)
+        线段._添加线段(线段序列, 新段, 配置, f"{sys._getframe().f_lineno}, {层级}")
+        return True
+
+    @classmethod
+    def _修正(cls, 线段序列: List[虚线], 配置: 缠论配置, 层级: int) -> bool:
+        当前线段 = 线段序列[-1]
+
+        # 条件1：配置允许修正且当前线段基础序列长度足够
+        if not (配置.线段_修正 and len(当前线段.基础序列) >= 9):
+            return False
+
+        # 分割序列
+        当前基础序列, 之后基础序列, _, _ = 线段.分割序列(当前线段)
+
+        # 条件2：之后基础序列长度至少为6
+        if len(之后基础序列) < 6:
+            return False
+
+        # 取倒数第3和第1个元素
+        前, 后 = 之后基础序列[-3], 之后基础序列[-1]
+
+        # 条件3：当前线段方向与后两个元素形成的方向一致
+        if 当前线段.方向 is not 相对方向.分析(前.高, 前.低, 后.高, 后.低):
+            return False
+
+        # 所有条件满足，执行修正
+        当前线段.短路修正 = True
+
+        # 创建第一个新段（之后基础序列去掉最后3个）
+        新段 = 虚线.创建线段(之后基础序列[:-3])
+        新段.短路修正 = True
+        线段._添加线段(线段序列, 新段, 配置, f"{sys._getframe().f_lineno}, {层级}")
+
+        # 根据当前线段的四象决定是否清空前一个缺口
+        if 线段.四象(当前线段) in ("老阴", "老阳"):
+            新段.前一缺口 = None
+
+        # 创建第二个新段（最后3个元素）
+        新段 = 虚线.创建线段(之后基础序列[-3:])
+        线段._添加线段(线段序列, 新段, 配置, f"{sys._getframe().f_lineno}, {层级}")
+
+        return True
+
+    @classmethod
+    def 分析(cls, 笔序列: List[虚线], 线段序列: List[虚线], 配置: 缠论配置, 层级: int = 0, 关系序列=[相对方向.向上, 相对方向.向下]) -> None:
+        """
+        注意笔序列前三个元素必须符合线段基本要求
+        四象: 老阴，老阳，少阴，小阳
+            老阴 老阳 分别代表 缺口顶分型后的向下线段 与 缺口底分型后的向上线段
+            当其分型完成时需要对 线段.前一缺口 设置为None，新线段不在考虑之前是否有缺口的问题
+        无缺口: 即笔破坏
+            笔破坏不去处理特征序列的逆序包含
+        """
+        # 递归深度守卫
+        if 层级 > 256:
+            print("线段.分析 递归深度超出 256")
+            return None
+            # raise RuntimeError("线段分析 层级过深")
+
+        线段递归分析 = 线段.分析
+
+        # -------------------- 1. 初始化第一个线段 --------------------
+        if not 线段序列:
+            for i in range(1, len(笔序列) - 1):
+                左, 中, 右 = 笔序列[i - 1], 笔序列[i], 笔序列[i + 1]
+                if not 线段.基础判断(左, 中, 右, 关系序列):  # FIXME 首个线段必须有明确方向
+                    continue
+                段 = 虚线.创建线段([左, 中, 右])
+                线段._添加线段(线段序列, 段, 配置, f"{sys._getframe().f_lineno}, {层级}")
+                段.特征序列[0] = 线段特征.新建([中], 段.方向)
+                break
+            if not 线段序列:
+                return None
+
+        # -------------------- 2. 清理无效的尾部引用 --------------------
+        while 线段序列 and 线段序列[-1].前一结束位置:
+            if 线段序列[-1].前一结束位置 not in 笔序列:
+                线段._弹出线段(线段序列, 线段序列[-1], 配置, f"{sys._getframe().f_lineno}, {层级}")
+            else:
+                break
+
+        if not 线段序列:
+            return 线段递归分析(笔序列, 线段序列, 配置, 层级 + 1, 关系序列)
+
+        # -------------------- 3. 确保当前线段有效 --------------------
+        当前线段 = 线段序列[-1]
+        线段.序列重置(当前线段, 笔序列)
+
+        if len(当前线段.基础序列) < 3:
+            线段._弹出线段(线段序列, 当前线段, 配置, f"{sys._getframe().f_lineno}, {层级}")
+            if not 线段序列:
+                return 线段递归分析(笔序列, 线段序列, 配置, 层级 + 1, 关系序列)
+
+        当前线段 = 线段序列[-1]
+
+        # -------------------- 4. 特征序列已完整时的处理 --------------------
+        if 当前线段.特征序列[2] is not None:
+            基础序列 = 线段.分割序列(当前线段)[1]
+            新段 = 虚线.创建线段(基础序列)
+            线段._添加线段(线段序列, 新段, 配置, f"{sys._getframe().f_lineno}, {层级}")
+            if 线段.四象(当前线段) in ("老阴", "老阳"):
+                新段.前一缺口 = None
+
+        当前线段 = 线段序列[-1]
+        线段.刷新(当前线段, 配置)
+
+        # -------------------- 5. 调用一次全局修正（不循环） --------------------
+        线段._缺口突破(线段序列, 配置, 层级)
+        线段._非缺口下穿刺(线段序列, 配置, 层级)
+        线段._缺口后紧急修正(线段序列, 配置, 层级)
+        线段._修正(线段序列, 配置, 层级)
+
+        # -------------------- 6. 循环处理后续的笔 --------------------
+        当前线段 = 线段序列[-1]
+        if not 当前线段.基础序列:
+            raise RuntimeError
+        起始索引 = 笔序列.index(当前线段.基础序列[-1]) + 1
+
+        for 当前虚线 in 笔序列[起始索引:]:
+            当前线段 = 线段序列[-1]
+            四象 = 线段.四象(当前线段)
+
+            线段.添加虚线(当前线段, 当前虚线)
+            线段.刷新(当前线段, 配置)
+
+            # 依次尝试四种修正，任意一个成功则跳过后续处理
+            if 线段._缺口突破(线段序列, 配置, 层级):
+                continue
+            if 线段._非缺口下穿刺(线段序列, 配置, 层级):
+                continue
+            if 线段._缺口后紧急修正(线段序列, 配置, 层级):
+                continue
+            if 线段._修正(线段序列, 配置, 层级):
+                continue
+
+            # 无修正触发，且特征序列[2]已存在 → 创建新段
+            if 当前线段.特征序列[2] is None:
+                continue
+
+            基础序列 = 线段.分割序列(当前线段)[1]
+            新段 = 虚线.创建线段(基础序列)
+            线段._添加线段(线段序列, 新段, 配置, f"{sys._getframe().f_lineno}, {层级}")
+            if 四象 in ("老阴", "老阳"):
+                新段.前一缺口 = None
+
+            # 检查新段与当前虚线的连续性
+            if 新段.基础序列[-1] is not 当前虚线:
+                if not 新段.基础序列[-1].之后是(当前虚线):
+                    return 线段递归分析(笔序列, 线段序列, 配置, 层级 + 1, 关系序列)
+                线段.添加虚线(新段, 当前虚线)
+
+            线段.刷新(新段, 配置)
+
+        return None
+
+    @classmethod
+    def 武终(cls, 段: 虚线, 行号: int):
+        if 段.模式 != "文武":
+            线段.武斗(段, 段.基础序列[-1].武, 行号)
+
+    @classmethod
+    def 验证序列(cls, 段: 虚线, 序列: Sequence):
+        基础序列 = []
+        for 元素 in 段.基础序列:
+            if 元素 not in 序列:
+                break
+            if 基础序列:
+                if not 基础序列[-1].之后是(元素):
+                    print("    线段._验证序列 数据不连续")
+                    break
+            基础序列.append(元素)
+        段.基础序列[:] = 基础序列[:]
+        if len(段.基础序列) % 2 == 0:
+            段.基础序列 and 段.基础序列.pop()
+
+    @classmethod
+    def _添加扩展线段(cls, 线段序列: List[虚线], 待添加线段: 虚线, 行号: int):
+        待添加线段.模式 = "高低"
+        待添加线段.标识 = f"扩展{待添加线段.标识}" if 待添加线段.基础序列[0].标识 != "笔" else "扩展线段"
+        if 线段序列 and not 线段序列[-1].之后是(待添加线段):
+            raise ValueError(f"{线段序列[-1].标识}.向序列中添加 不连续[{行号}]", 线段序列[-1].武, 待添加线段.文)
+        if 线段序列:
+            之前线段 = 线段序列[-1]
+            待添加线段.序号 = 之前线段.序号 + 1
+
+        线段序列.append(待添加线段)
+        # print(f"线段._向序列中添加[{行号}]", 待添加线段)
+
+    @classmethod
+    def _弹出扩展线段(cls, 线段序列: List[虚线], 待弹出线段: 虚线, 行号: int):
+        if not 线段序列:
+            return None
+
+        if 线段序列[-1] is 待弹出线段:
+            drop = 线段序列.pop()
+            待弹出线段.有效性 = False
+            # print(f"线段._从序列中删除[{行号}]", 待弹出线段)
+            return drop
+        raise ValueError("线段._从序列中删除 弹出数据不在列表中", 待弹出线段)
+
+    @classmethod
+    def 扩展分析(cls, 虚线序列: List[虚线], 线段序列: List[虚线], 配置: 缠论配置) -> None:
+        """
+        即同级别分析
+        将笔看成线段
+        """
+        if not 虚线序列:
+            return None
+        try:
+            虚线序列[2]
+        except IndexError:
+            return None
+        线段递归扩展分析 = 线段.扩展分析
+
+        if not 线段序列:
+            for i in range(1, len(虚线序列) - 1):
+                左, 中, 右 = 虚线序列[i - 1], 虚线序列[i], 虚线序列[i + 1]
+                关系 = 相对方向.分析(左.高, 左.低, 右.高, 右.低)
+                if 关系 not in (相对方向.向下, 相对方向.向上, 相对方向.顺, 相对方向.逆, 相对方向.同):  # FIXME 此处为首个线段
+                    continue
+
+                段 = 虚线.创建线段([左, 中, 右])
+                线段._添加扩展线段(线段序列, 段, sys._getframe().f_lineno)
+                break
+
+        # 检查线段元素
+        if not 线段序列:
+            return None
+
+        当前线段 = 线段序列[-1]
+        线段.验证序列(当前线段, 虚线序列)
+        if len(当前线段.基础序列) < 3:
+            线段._弹出扩展线段(线段序列, 当前线段, sys._getframe().f_lineno)
+            return 线段递归扩展分析(虚线序列, 线段序列, 配置)
+
+        if not 配置.扩展线段_当下分析:
+            左, 中, 右 = 当前线段.基础序列[:3]
+            if not 相对方向.分析(左.高, 左.低, 右.高, 右.低).是否缺口():
+                当前线段.基础序列[:] = 当前线段.笔序列[:3]
+                线段.武终(当前线段, sys._getframe().f_lineno)
+            else:
+                线段._弹出扩展线段(线段序列, 当前线段, sys._getframe().f_lineno)
+                return 线段递归扩展分析(虚线序列, 线段序列, 配置)
+
+        线段.武终(当前线段, sys._getframe().f_lineno)
+        if 当前线段.基础序列[-1].序号 + 3 > 虚线序列[-1].序号:
+            return None
+
+        序号 = 虚线序列.index(当前线段.基础序列[-1]) + 1
+        if 序号 >= len(虚线序列):
+            return None
+
+        for i in range(序号 + 1, len(虚线序列) - 1):
+            左, 中, 右 = 虚线序列[i - 1], 虚线序列[i], 虚线序列[i + 1]
+            相对关系 = 相对方向.分析(左.高, 左.低, 右.高, 右.低)
+            if 相对关系.是否缺口():
+                线段.添加虚线(当前线段, 左)
+                线段.添加虚线(当前线段, 中)
+                线段.武终(当前线段, sys._getframe().f_lineno)
+                continue
+
+            if 左 in 当前线段.基础序列:
+                continue
+
+            段 = 虚线.创建线段([左, 中, 右])
+            线段._添加扩展线段(线段序列, 段, sys._getframe().f_lineno)
+            return 线段递归扩展分析(虚线序列, 线段序列, 配置)
+
+    @classmethod
+    @lru_cache(maxsize=128)
+    def 判断线段内部是否背驰(cls, 当前段: 虚线, 观察员: 观察者):
+        虚, 实, 合 = 线段.获取内部中枢序列(当前段, 观察员.配置)
+        阳, 阴, _, _ = 线段.分割序列(当前段)
+        if len(阴) > 0:
+            """
+            1.大于2且未完成，第二特征序列正在合并中，
+                0.继续合并
+                1.之后突破第二序列线段延续
+                2.反之 出现第三特征序列线段完成 出现相反线段
+                    1.有缺口
+                    2.无缺口
+
+            总之就是有 阴 则不判断
+            """
+        笔之实数 = len(阳)
+        if 笔之实数 < 3:
+            return False
+
+        进入段 = 阳[-3]
+        离开段 = 阳[-1]
+        assert 进入段.序号 < 离开段.序号
+        关系 = 相对方向.分析(进入段.高, 进入段.低, 离开段.高, 离开段.低)
+        背驰 = False
+        盘整背驰 = False
+        if ((进入段.方向.是否向上() and 关系.是否向上()) or (进入段.方向.是否向下() and 关系.是否向下())) and 背驰分析.背驰模式(进入段, 离开段, 观察员.普通K线序列, 观察员.配置, 观察员.配置.线段内部背驰_模式):
+            k线序列 = K线.截取(观察员.普通K线序列, 阳[-3].文.中.标的K线, 阳[-1].武.中.标的K线)
+            if len(虚线.计算MACD柱子分段(k线序列)) >= 3:
+                盘整背驰 = True  # and MACD均值背驰
+
+        """进入段 = 阳[0]
+        离开段 = 阳[-1]
+        if ((进入段.方向.是否向上() and 关系.是否向上()) or (进入段.方向.是否向下() and 关系.是否向下())) and 背驰分析.背驰模式(进入段, 离开段, 观察员.普通K线序列, 观察员.配置, 观察员.配置.线段内部背驰_模式):
+            盘整背驰 = 阳[-1].武之MACD均值 if not 盘整背驰 else 盘整背驰"""
+
+        if 当前段.实_中枢序列:
+            if 阳[-1] in 当前段.实_中枢序列[-1].基础序列:
+                # 当前最后一笔在最后一中枢里
+                序号 = 当前段.基础序列.index(当前段.实_中枢序列[-1].基础序列[0])
+                进入段 = 当前段.基础序列[序号 - 1]
+                离开段 = 阳[-1]
+                assert 进入段.序号 < 离开段.序号, (进入段.序号, 离开段.序号)
+                if 进入段.方向 is not 离开段.方向:
+                    return 背驰分析.测度背驰(进入段, 离开段) and 虚线.买卖意义(离开段, 观察员)
+                关系 = 相对方向.分析(进入段.高, 进入段.低, 离开段.高, 离开段.低)
+                if ((进入段.方向.是否向上() and 关系.是否向上()) or (进入段.方向.是否向下() and 关系.是否向下())) and 背驰分析.背驰模式(进入段, 离开段, 观察员.普通K线序列, 观察员.配置, 观察员.配置.线段内部背驰_模式):
+                    return True
+
+            elif 当前段.实_中枢序列[-1].第三买卖线:
+                # 第三买卖点后后 盘整背驰
+                进入段 = 阳[-3]
+                离开段 = 阳[-1]
+                assert 进入段.序号 < 离开段.序号
+                if 进入段.方向 is not 离开段.方向:
+                    return 背驰分析.测度背驰(进入段, 离开段) and 虚线.买卖意义(离开段, 观察员)
+                关系 = 相对方向.分析(进入段.高, 进入段.低, 离开段.高, 离开段.低)
+                if ((进入段.方向.是否向上() and 关系.是否向上()) or (进入段.方向.是否向下() and 关系.是否向下())) and 背驰分析.背驰模式(进入段, 离开段, 观察员.普通K线序列, 观察员.配置, 观察员.配置.线段内部背驰_模式):
+                    return True
+        else:
+            # 没有中枢
+            if 笔之实数 == 3:
+                背驰 = 盘整背驰
+
+        return 背驰 or 盘整背驰
+
+    @classmethod
+    def 段获取所有停顿位置(cls, 段: 虚线, 观察员: "观察者"):
+        self = 段
+        结果 = []
+        if self.模式 != "文武":
+            return 结果
+        if self.标识 != "线段":  # 不考虑段的段，不如直接更换K线周期
+            return 结果
+        阳, 阴, _, _ = 线段.分割序列(段, None)
+        线段序列 = []
+        笔序列 = []
+        当前停顿 = None
+
+        for 筆 in 阳:
+            if len(笔序列) >= 2:
+                筆停顿 = 笔.获取所有停顿位置(筆, 观察员)
+                筆停顿.append(筆)
+                for 停顿 in 筆停顿:
+                    笔序列.append(停顿)
+                    线段.分析(笔序列, 线段序列, 观察员.配置, 关系序列=[相对方向.向下, 相对方向.向上, 相对方向.顺, 相对方向.逆, 相对方向.同])
+                    if 线段序列 and 线段序列[-1].武 is not 当前停顿:
+                        新段 = 虚线.创建线段(线段序列[-1][:])
+                        新段.序号 = self.序号
+                        线段.刷新(新段, 观察员.配置)
+                        if 新段.方向 is self.方向:
+                            结果.append(新段)
+                            当前停顿 = 线段序列[-1].武
+
+                    if 停顿 is not 筆:
+                        笔序列.pop().有效性 = False
+            else:
+                笔序列.append(筆)
+        return 结果
+
+    @classmethod
+    def 是否背驰过(cls, 当前段: 虚线, 观察员: "观察者"):
+        停顿位置 = cls.段获取所有停顿位置(当前段, 观察员)
+        结果 = []
+
+        for 段 in 停顿位置:
+            段.获取内部中枢序列(观察员.配置)
+            if cls.判断线段内部是否背驰(段, 观察员):
+                结果.append(段.武.中)
+        return 结果
+
+
+class 中枢(object):
+    __slots__ = ["序号", "标识", "级别", "基础序列", "第三买卖线", "本级_第三买卖线"]
+
+    def __init__(self, 序号: int, 标识: str, 级别: int, 基础序列: List[虚线]):
+        self.基础序列 = 基础序列[:3]
+        self.序号: int = 序号
+        self.标识: str = 标识
+        self.级别: int = 级别
+        self.第三买卖线: Optional[虚线] = None
+        self.本级_第三买卖线: Optional[虚线] = None
+
+    def 添加虚线(self, 实线: 虚线):
+        self.基础序列.append(实线)
+        self.本级_第三买卖线: Optional[虚线] = None
+        self.第三买卖线: Optional[虚线] = None
+
+    def __str__(self):
+        return f"{self.标识}({self.高:g}, {self.低:g}, 元素数量: {len(self.基础序列)}, {str(self.基础序列)}, {self.基础序列[0].文} ===>>> {self.基础序列[-1].武})"
+
+    def __repr__(self):
+        return str(self)
+
+    @property
+    def 图表标题(self) -> str:
+        return f"{self.文.中.标识}:{self.文.中.周期}:{self.标识}:{self.序号}"
+
+    @property
+    def 离开段(self) -> 虚线:
+        return self.基础序列[-1]
+
+    @property
+    def 方向(self) -> 相对方向:
+        return self.基础序列[0].方向.翻转()
+
+    @property
+    def 高(self) -> float:
+        return min(self.基础序列[:3], key=lambda o: o.高).高
+
+    @property
+    def 低(self) -> float:
+        return max(self.基础序列[:3], key=lambda o: o.低).低
+
+    @property
+    def 高高(self) -> float:
+        if len(self.基础序列) > 3:
+            return max(self.基础序列, key=lambda o: o.高).高
+        return max(self.基础序列, key=lambda o: o.高).高
+
+    @property
+    def 低低(self) -> float:
+        if len(self.基础序列) > 3:
+            return min(self.基础序列, key=lambda o: o.低).低
+        return min(self.基础序列, key=lambda o: o.低).低
+
+    @property
+    def 文(self) -> 分型:
+        return self.基础序列[0].文
+
+    @property
+    def 武(self) -> 分型:
+        return self.基础序列[-1].武
+
+    def 获取数据文本(self):
+        return f"{self.标识}, {self.序号}, {self.级别}, 文:({int(self.文.时间戳.timestamp())},{self.文.分型特征值:g}), 武:({int(self.武.时间戳.timestamp())},{self.武.分型特征值:g}), {self.第三买卖线}, {self.本级_第三买卖线}"
+
+    def 完整性(self, 虚实: str = "合"):
+        """
+
+        详情见 教你炒股票 43：有关背驰的补习课(2007-04-06 15:31:28)
+        不完整时 下一个中枢大概率会与当前中枢发生扩展！
+
+        """
+        if self.基础序列[0].标识 == "笔":
+            # 笔中枢
+            return self.第三买卖线 is not None
+
+        else:
+            # if self.本级_第三买卖线:
+            #     return True
+            线段内部中枢 = self.基础序列[-1].合_中枢序列 if 虚实 == "合" else self.基础序列[-1].实_中枢序列
+            for 内部中枢 in 线段内部中枢:
+                if 相对方向.分析(self.高, self.低, 内部中枢.高, 内部中枢.低).是否缺口():
+                    return True
+        return False
+
+    def 获取序列(self) -> List[虚线]:
+        序列: List = self.基础序列[:]
+        if self.第三买卖线 is not None:
+            序列.append(self.第三买卖线)
+        return 序列
+
+    def 获取扩展中枢(self, 扩展中枢: List, 配置: 缠论配置):
+        if len(self.基础序列) >= 9:
+            扩展线段 = []
+            线段.扩展分析(self.基础序列, 扩展线段, 配置)
+            中枢.分析(扩展线段, 扩展中枢, False, f"{self.标识}_扩展中枢_")
+
+    def 校验合法性(self, 序列: Sequence[虚线], 中枢序列) -> bool:
+        有效序列 = self.基础序列[:]
+        无效序列 = []
+        for 元素 in self.基础序列:
+            if 元素 not in 序列:
+                无效序列.append(元素)
+
+        if 无效序列:
+            无效 = 无效序列[0]
+            序号 = self.基础序列.index(无效)
+            有效序列 = self.基础序列[:序号]
+
+        if len(有效序列) < 3:
+            self.第三买卖线 = None
+            self.本级_第三买卖线 = None
+            return False
+
+        self.基础序列[:] = 有效序列
+
+        有效序列 = []
+        for 元素 in self.基础序列:
+            if 相对方向.分析(self.高, self.低, 元素.高, 元素.低).是否缺口():
+                break
+            有效序列.append(元素)
+        self.基础序列[:] = 有效序列
+
+        if len(self.基础序列) < 3:
+            return False
+
+        for i in range(1, len(self.基础序列)):
+            前 = self.基础序列[i - 1]
+            后 = self.基础序列[i]
+            if not 前.之后是(后):
+                return False
+
+        if not 相对方向.分析(self.基础序列[0].高, self.基础序列[0].低, self.基础序列[2].高, self.基础序列[2].低).是否缺口():
+            重叠高 = min(self.基础序列[:3], key=lambda o: o.高).高
+            重叠低 = max(self.基础序列[:3], key=lambda o: o.低).低
+            if 重叠低 > 重叠高:
+                return False
+
+        if self.第三买卖线 is not None:
+            if self.第三买卖线 in 序列:
+                if not self.基础序列[-1].之后是(self.第三买卖线):
+                    self.设置第三买卖线(None)
+                else:
+                    if not 相对方向.分析(self.高, self.低, self.第三买卖线.高, self.第三买卖线.低).是否缺口():
+                        self.添加虚线(self.第三买卖线)
+                        self.设置第三买卖线(None)
+
+            else:
+                self.设置第三买卖线(None)
+        return True
+
+    def 设置第三买卖线(self, 线: Union[虚线, None]):
+        self.第三买卖线 = 线
+
+    def 当前状态(self):
+        """
+        详情见 教你炒股票 49：利润率最大的操作模式(2007-04-26 08:16:56)
+        当前中枢最后一段所处的位置关系
+
+        一、当下在该中枢之中。
+            因为在中枢里，由于这时候怎么演化都是对的，不操作是最好的操作，等待其演化第二、三类，
+            当然，如果你技术好点，可以判断出次级别的第二类买点，这些买点很多情况下都是在中枢中出现的，那当然也是可以参与的。
+            但如果没有这种技术，那就有了再说了。只把握你自己当下技术水平能把握的机会，这才是最重要的。
+        二、当下在该中枢之下。
+            1.当下之前未出现该中枢第三类卖点。
+            2.当下之前已出现该中枢第三类卖点（正出现也包括在这种情况下，按最严格的定义，这最精确的卖点，是瞬间完成的，而具有操作意义的第三类卖点，其实是一个包含该最精确卖点的足够小区间）
+        三、当下在该中枢之上。
+            1.当下之前未出现该中枢第三类买点。
+            2.当下之前已出现该中枢第三类买点。
+        """
+        状态 = "中枢之中"
+        尾部 = self.基础序列[-1].武 if self.基础序列[-1].标识 == "笔" else self.基础序列[-1].基础序列[-1].武
+        关系 = 相对方向.分析(self.高, self.低, 尾部.中.高, 尾部.中.低)
+        if 关系 is 相对方向.向上缺口:
+            状态 = "中枢之上"
+        elif 关系 is 相对方向.向下缺口:
+            状态 = "中枢之下"
+        return 状态
+
+    @classmethod
+    def 基础检查(cls, 左: 虚线, 中: 虚线, 右: 虚线) -> bool:
+        if not 左.之后是(中):
+            return False
+        if not 中.之后是(右):
+            return False
+        """
+        if not 相对方向.分析(左.高, 左.低, 中.高, 中.低).是否包含():
+            return False
+        if not 相对方向.分析(中.高, 中.低, 右.高, 右.低).是否包含():
+            return False
+        """
+
+        return 相对方向.分析(左.高, 左.低, 右.高, 右.低) in (相对方向.向下, 相对方向.向上, 相对方向.顺, 相对方向.逆, 相对方向.同)
+
+    @classmethod
+    def 创建(cls, 左: 虚线, 中: 虚线, 右: 虚线, 级别: int, 标识: str = "") -> "中枢":
+        assert 中枢.基础检查(左, 中, 右)
+        return 中枢(
+            序号=0,
+            标识=f"{标识}中枢<{中.标识}>",
+            基础序列=[左, 中, 右],
+            级别=级别,
+        )
+
+    @classmethod
+    def 从序列中获取中枢(cls, 虚线序列: Sequence[虚线], 起始方向: 相对方向, 标识: str) -> Optional["中枢"]:
+        if len(虚线序列) < 3:
+            return None
+
+        for i in range(1, len(虚线序列) - 1):
+            左, 中, 右 = 虚线序列[i - 1], 虚线序列[i], 虚线序列[i + 1]
+            if 中枢.基础检查(左, 中, 右):
+                if 左.方向 is 起始方向:
+                    return 中枢.创建(左, 中, 右, 级别=0, 标识=标识)
+
+        return None
+
+    @classmethod
+    def 向中枢序列尾部添加(cls, 中枢序列: List["中枢"], 待添加中枢: "中枢"):
+        if 中枢序列:
+            待添加中枢.序号 = 中枢序列[-1].序号 + 1
+            if 中枢序列[-1].获取序列()[-1].序号 > 待添加中枢.获取序列()[-1].序号:
+                raise ValueError()
+        中枢序列.append(待添加中枢)
+
+    @classmethod
+    def 从中枢序列尾部弹出(cls, 中枢序列: List["中枢"], 待弹出中枢: "中枢") -> Optional["中枢"]:
+        if not 中枢序列:
+            return None
+        if 中枢序列[-1] is 待弹出中枢:
+            return 中枢序列.pop()
+        return None
+
+    @classmethod
+    def 分析(cls, 虚线序列: Sequence[虚线], 中枢序列: List["中枢"], 跳过首部: bool = True, 标识: str = "", 层级: int = 0) -> None:
+        if len(虚线序列) < 3:
+            return None
+
+        中枢递归分析 = 中枢.分析
+
+        if not 中枢序列:
+            for i in range(1, len(虚线序列) - 1):
+                左, 中, 右 = 虚线序列[i - 1], 虚线序列[i], 虚线序列[i + 1]
+                if 中枢.基础检查(左, 中, 右):
+                    新中枢 = 中枢.创建(左, 中, 右, 中.级别, 标识)
+                    序号 = 虚线序列.index(左)
+                    if 跳过首部 and (左.序号 == 0 or 序号 == 0):
+                        continue  # 方便计算走势
+                    if 序号 >= 2:
+                        同向相对关系 = 相对方向.分析(虚线序列[序号 - 2].高, 虚线序列[序号 - 2].低, 左.高, 左.低)
+                        if 同向相对关系.是否向上() and 左.方向.是否向上():
+                            continue
+                        if 同向相对关系.是否向下() and 左.方向.是否向下():
+                            continue
+
+                    中枢.向中枢序列尾部添加(中枢序列, 新中枢)
+                    return 中枢递归分析(虚线序列, 中枢序列, 跳过首部, 标识, 层级 + 1)
+
+            return None
+
+        当前中枢 = 中枢序列[-1]
+
+        if not 当前中枢.校验合法性(虚线序列, 中枢序列):
+            中枢.从中枢序列尾部弹出(中枢序列, 当前中枢)
+            return 中枢递归分析(虚线序列, 中枢序列, 跳过首部, 标识, 层级 + 1)
+
+        序号 = 虚线序列.index(当前中枢.基础序列[-1]) + 1
+
+        基础序列 = []
+        for 当前虚线 in 虚线序列[序号:]:
+            if 相对方向.分析(当前中枢.高, 当前中枢.低, 当前虚线.高, 当前虚线.低).是否缺口():
+                基础序列.append(当前虚线)
+                if 当前中枢.基础序列[-1].之后是(当前虚线):
+                    当前中枢.设置第三买卖线(当前虚线)
+                else:
+                    ...
+            else:
+                if not 基础序列:
+                    assert 当前中枢.基础序列[-1].之后是(当前虚线), (当前中枢.基础序列[-1], 当前虚线)
+                    当前中枢.添加虚线(当前虚线)
+                else:
+                    基础序列.append(当前虚线)
+
+            while len(基础序列) >= 3:
+                新中枢 = 中枢.从序列中获取中枢(基础序列, 当前中枢.基础序列[-1].方向.翻转(), 标识)
+                if 新中枢 is None:
+                    基础序列.pop(0)
+                else:
+                    中枢.向中枢序列尾部添加(中枢序列, 新中枢)
+                    当前中枢 = 新中枢
+                    基础序列 = []
+        return None
+
+
+class 观察者:
+    def __init__(self, 符号: str, 周期: int, 配置: 缠论配置):
+        配置.标识 = 符号
+        self.符号: str = 符号
+        self.周期: int = int(周期)
+        self.配置: 缠论配置 = 配置
+        self.__终止时间戳: Optional[datetime] = 转化为时间戳(self.配置.手动终止) if self.配置.手动终止 else None
+
+        self.重置基础序列()
+
+    @property
+    def 观察员(self):
+        return self  # 用于兼容 chanlun.c99
+
+    @property
+    def 标识(self) -> str:
+        return f"{self.符号}:{self.周期}"
+
+    @property
+    def 当前K线(self) -> Optional["K线"]:
+        return self.普通K线序列[-1] if self.普通K线序列 else None
+
+    @property
+    def 当前缠K(self) -> Optional["缠论K线"]:
+        return self.缠论K线序列[-1] if self.缠论K线序列 else None
+
+    def 重置基础序列(self):
+        self.基础缠K序列: List[缠论K线] = []
+
+        self.普通K线序列: List[K线] = []
+        self.缠论K线序列: List[缠论K线] = []
+
+        self.分型序列: List[分型] = []
+
+        self.笔序列: List[虚线] = []
+        self.笔_中枢序列: List[中枢] = []
+
+        self.线段序列: List[虚线] = []
+        self.中枢序列: List[中枢] = []
+
+        self.扩展线段序列: List[虚线] = []
+        self.扩展中枢序列: List[中枢] = []
+
+        self.扩展线段序列_线段: List[虚线] = []
+        self.扩展中枢序列_线段: List[中枢] = []
+
+        self.线段_线段序列: List[虚线] = []
+        self.线段_中枢序列: List[中枢] = []
+
+        self.扩展线段序列_扩展线段: List[虚线] = []
+        self.扩展中枢序列_扩展线段: List[中枢] = []
+
+    @final
+    def 增加原始K线(self, 普K: K线):
+        if self.__终止时间戳 and 普K.时间戳 > self.__终止时间戳:
+            return
+        self.__处理数据(普K)
+
+    def __处理数据(self, 普K: K线):
+        状态, 当前分型 = 缠论K线.分析(普K, self.缠论K线序列, self.普通K线序列, self.配置)
+        if 当前分型 is None:
+            return
+
+        self.配置.分析笔 and 笔.分析(当前分型, self.分型序列, self.笔序列, self.缠论K线序列, self.普通K线序列, 0, self.配置)
+        if not self.分型序列:
+            return
+
+        self.配置.分析笔中枢 and 中枢.分析(self.笔序列, self.笔_中枢序列)
+        if not self.笔序列:
+            return
+
+        self.配置.分析线段 and 线段.分析(self.笔序列, self.线段序列, self.配置)
+        self.配置.分析线段中枢 and 中枢.分析(self.线段序列, self.中枢序列)
+
+        self.配置.分析扩展线段 and 线段.扩展分析(self.笔序列, self.扩展线段序列, self.配置)
+        self.配置.分析线段中枢 and 中枢.分析(self.扩展线段序列, self.扩展中枢序列)
+
+        self.配置.分析扩展线段 and 线段.扩展分析(self.线段序列, self.扩展线段序列_线段, self.配置)
+        self.配置.分析线段中枢 and 中枢.分析(self.扩展线段序列_线段, self.扩展中枢序列_线段)
+
+        self.配置.分析线段 and 线段.分析(self.线段序列, self.线段_线段序列, self.配置)
+        self.配置.分析线段中枢 and 中枢.分析(self.线段_线段序列, self.线段_中枢序列)
+
+        self.配置.分析扩展线段 and 线段.扩展分析(self.扩展线段序列, self.扩展线段序列_扩展线段, self.配置)
+        self.配置.分析线段中枢 and 中枢.分析(self.扩展线段序列_扩展线段, self.扩展中枢序列_扩展线段)
+
+    def 测试_保存数据(self, root: str = None):
+        """拆分各序列数据，单独存文件，文件名为对应变量名"""
+        # 提取各类文本数据
+        笔序列_文本数据 = [筆.获取数据文本() for 筆 in self.笔序列]
+        线段序列_文本数据 = [实线.获取数据文本() for 实线 in self.线段序列]
+        扩展线段序列_数据文本 = [实线.获取数据文本() for 实线 in self.扩展线段序列]
+        扩展线段序列_线段_数据文本 = [实线.获取数据文本() for 实线 in self.扩展线段序列_线段]
+        线段_线段序列_数据文本 = [实线.获取数据文本() for 实线 in self.线段_线段序列]
+        扩展线段序列_扩展线段_数据文本 = [实线.获取数据文本() for 实线 in self.扩展线段序列_扩展线段]
+
+        笔_中枢序列_数据文本 = [当前中枢.获取数据文本() for 当前中枢 in self.笔_中枢序列]
+        中枢序列_数据文本 = [当前中枢.获取数据文本() for 当前中枢 in self.中枢序列]
+        扩展中枢序列_数据文本 = [当前中枢.获取数据文本() for 当前中枢 in self.扩展中枢序列]
+        扩展中枢序列_线段_数据文本 = [当前中枢.获取数据文本() for 当前中枢 in self.扩展中枢序列_线段]
+        线段_中枢序列_数据文本 = [当前中枢.获取数据文本() for 当前中枢 in self.线段_中枢序列]
+        扩展中枢序列_扩展线段_数据文本 = [当前中枢.获取数据文本() for 当前中枢 in self.扩展中枢序列_扩展线段]
+
+        # ===================== 优化点：优先使用传入的 root 目录 =====================
+        if root is not None:
+            # 使用用户指定的根目录
+            根目录 = Path(root)
+        else:
+            # 默认：当前脚本所在目录
+            根目录 = Path(__file__).parent
+
+        # 生成子目录名称（不变）
+        起始时间 = int(self.普通K线序列[0].时间戳.timestamp())
+        结束时间 = int(self.普通K线序列[-1].时间戳.timestamp())
+        目录标识 = f"Py_{self.标识}_{起始时间}_{结束时间}"
+
+        # 最终保存路径 = 根目录 / 自动生成的子文件夹
+        保存路径 = 根目录 / 目录标识
+        保存路径.mkdir(exist_ok=True, parents=True)  # parents=True 支持多级目录自动创建
+
+        # 映射：变量名 -> 数据列表
+        数据映射 = [
+            ("笔序列_文本数据", 笔序列_文本数据),
+            ("线段序列_文本数据", 线段序列_文本数据),
+            ("扩展线段序列_数据文本", 扩展线段序列_数据文本),
+            ("扩展线段序列_线段_数据文本", 扩展线段序列_线段_数据文本),
+            ("线段_线段序列_数据文本", 线段_线段序列_数据文本),
+            ("扩展线段序列_扩展线段_数据文本", 扩展线段序列_扩展线段_数据文本),
+            ("笔_中枢序列_数据文本", 笔_中枢序列_数据文本),
+            ("中枢序列_数据文本", 中枢序列_数据文本),
+            ("扩展中枢序列_数据文本", 扩展中枢序列_数据文本),
+            ("扩展中枢序列_线段_数据文本", 扩展中枢序列_线段_数据文本),
+            ("线段_中枢序列_数据文本", 线段_中枢序列_数据文本),
+            ("扩展中枢序列_扩展线段_数据文本", 扩展中枢序列_扩展线段_数据文本),
+        ]
+
+        # 逐个写入独立文件
+        for 文件名, 数据列表 in 数据映射:
+            文件全路径 = 保存路径 / f"{文件名}.txt"
+            with open(文件全路径, "w", encoding="utf-8") as f:
+                f.write("\n".join(数据列表))
+                f.write("\n")  # 向 C99 对齐
+        print(f"全部数据拆分保存完成，目录：{保存路径.resolve()}")
+
+    def 识别买卖点(self):
+        pass
+
+    def 静态重新分析(self):
+        self.分型序列: List[分型] = []
+
+        self.笔序列: List[虚线] = []
+        self.笔_中枢序列: List[中枢] = []
+
+        self.线段序列: List[虚线] = []
+        self.中枢序列: List[中枢] = []
+
+        self.扩展线段序列: List[虚线] = []
+        self.扩展中枢序列: List[中枢] = []
+
+        self.扩展线段序列_线段: List[虚线] = []
+        self.扩展中枢序列_线段: List[中枢] = []
+
+        self.线段_线段序列: List[虚线] = []
+        self.线段_中枢序列: List[中枢] = []
+
+        self.扩展线段序列_扩展线段: List[虚线] = []
+        self.扩展中枢序列_扩展线段: List[中枢] = []
+
+        for i in range(1, len(self.缠论K线序列) - 1):
+            当前分型 = 分型(self.缠论K线序列[i - 1], self.缠论K线序列[i], self.缠论K线序列[i + 1])
+            笔.分析(当前分型, self.分型序列, self.笔序列, self.缠论K线序列, self.普通K线序列, 0, self.配置)
+
+        self.配置.分析笔中枢 and 中枢.分析(self.笔序列, self.笔_中枢序列)
+
+        self.配置.分析线段 and 线段.分析(self.笔序列, self.线段序列, self.配置)
+        self.配置.分析线段中枢 and 中枢.分析(self.线段序列, self.中枢序列)
+
+        self.配置.分析扩展线段 and 线段.扩展分析(self.笔序列, self.扩展线段序列, self.配置)
+        self.配置.分析线段中枢 and 中枢.分析(self.扩展线段序列, self.扩展中枢序列)
+
+        self.配置.分析扩展线段 and 线段.扩展分析(self.线段序列, self.扩展线段序列_线段, self.配置)
+        self.配置.分析线段中枢 and 中枢.分析(self.扩展线段序列_线段, self.扩展中枢序列_线段)
+
+        self.配置.分析线段 and 线段.分析(self.线段序列, self.线段_线段序列, self.配置)
+        self.配置.分析线段中枢 and 中枢.分析(self.线段_线段序列, self.线段_中枢序列)
+
+    @classmethod
+    def 读取数据文件(cls, 文件路径: str, 配置=缠论配置()) -> Self:
+        # btcusd-300-1631772074-1632222374.nb
+        name = Path(文件路径).name.split(".")[0]
+        符号, 周期, 起始时间戳, 结束时间戳 = name.split("-")
+        实例 = cls(符号=符号, 周期=int(周期), 配置=配置)
+
+        with open(文件路径, "rb") as f:
+            buffer = f.read()
+            size = struct.calcsize(">6d")
+            for i in range(len(buffer) // size):
+                k线 = K线.读取大端字节数组(buffer[i * size : i * size + size], int(周期))
+                实例.增加原始K线(k线)
+
+        return 实例
+
+
+class K线合成器:
+    def __init__(self, 标识: str, 周期组: List[int], 事件回调: Optional[Callable] = None):
+        self.标识 = 标识
+        self.周期组 = sorted(周期组)  # 按周期从小到大排序
+        self.当前K线: Dict[int, Optional[K线]] = {周期: None for 周期 in 周期组}
+        self.合成K线列表: Dict[int, List[K线]] = {周期: [] for 周期 in 周期组}
+        self.事件回调 = 事件回调  # 新增：事件回调函数
+
+    def 设置事件回调(self, 回调函数: Callable):
+        """设置事件回调函数"""
+        self.事件回调 = 回调函数
+
+    def 投喂(self, 时间戳: datetime, 开: float, 高: float, 低: float, 收: float, 量: float):
+        """投喂原始tick数据"""
+        普K = K线.创建普K(
+            标识=self.标识,
+            序号=0,  # 原始数据序号不重要
+            时间戳=时间戳,
+            开盘价=开,
+            最高价=高,
+            最低价=低,
+            收盘价=收,
+            成交量=量,
+            周期=0,  # 原始数据是0秒周期
+        )
+        self.投喂K线(普K)
+
+    def 投喂K线(self, 普K: K线):
+        """投喂K线对象"""
+        for 周期 in self.周期组:
+            self._处理单个周期(周期, 普K)
+
+    def _处理单个周期(self, 周期: int, 普K: K线):
+        """处理单个周期的K线合成"""
+        目标时间戳 = self._对齐时间戳(普K.时间戳, 周期)
+        当前K线 = self.当前K线[周期]
+        if 当前K线 is None:
+            # 创建新的K线
+            self.当前K线[周期] = self._创建新K线(周期, 目标时间戳, 普K)
+        elif 当前K线.时间戳 == 目标时间戳:
+            # 更新当前K线
+            self._更新K线(当前K线, 普K)
+        else:
+            # 完成当前K线，创建新K线
+            self._完成K线(周期)
+            self.当前K线[周期] = self._创建新K线(周期, 目标时间戳, 普K)
+
+    def _对齐时间戳(self, 时间戳: datetime, 周期: int) -> datetime:
+        """将时间戳对齐到周期边界"""
+        total_seconds = int(时间戳.timestamp())
+        aligned_seconds = (total_seconds // 周期) * 周期
+        return datetime.fromtimestamp(aligned_seconds)
+
+    def _创建新K线(self, 周期: int, 时间戳: datetime, 普K: K线) -> K线:
+        """创建新的合成K线"""
+        return K线.创建普K(
+            标识=self.标识,
+            序号=0 if not self.合成K线列表[周期] else self.合成K线列表[周期][-1].序号 + 1,
+            时间戳=时间戳,
+            开盘价=普K.开盘价,
+            最高价=普K.高,
+            最低价=普K.低,
+            收盘价=普K.收盘价,
+            成交量=普K.成交量,
+            周期=周期,
+        )
+
+    def _更新K线(self, 当前K线: K线, 新数据: K线):
+        """更新当前K线数据"""
+        当前K线.高 = max(当前K线.高, 新数据.高)
+        当前K线.低 = min(当前K线.低, 新数据.低)
+        当前K线.收盘价 = 新数据.收盘价
+        当前K线.成交量 += 新数据.成交量
+        # 当前K线.原始结束序号 = 新数据.序号
+
+    def _完成K线(self, 周期: int):
+        """完成当前K线并添加到列表"""
+        当前K线 = self.当前K线[周期]
+        if 当前K线 is None:
+            return
+
+        # 这里可以添加最终的处理逻辑，比如计算MACD等
+        if self.合成K线列表[周期]:
+            当前K线.序号 = self.合成K线列表[周期][-1].序号 + 1
+
+        self.合成K线列表[周期].append(当前K线)
+
+        self.当前K线[周期] = None
+        # 新增：产生完成K线信号
+        self._产生完成K线信号(周期, 当前K线)
+
+    def _产生完成K线信号(self, 周期: int, 完成K线: K线):
+        """产生K线完成信号"""
+        if self.事件回调:
+            try:
+                self.事件回调(信号类型="K线完成", 标识=self.标识, 周期=周期, 完成K线=完成K线)
+            except Exception as e:
+                print(f"K线合成器信号回调错误: {e}")
+
+    def 获取当前K线(self, 周期: int) -> Optional[K线]:
+        """获取指定周期当前正在合成的K线"""
+        return self.当前K线[周期]
+
+
+class 立体分析器:
+    def __init__(self, 符号: str, 周期组: List[int], 配置: 缠论配置 = 缠论配置(), 配置组: Dict[int, 缠论配置] = dict()):
+        self.周期组 = 周期组
+
+        self.__输入周期 = self.周期组[0]  # 最小输入K线周期
+        self.__显示周期 = self.周期组[1]
+        self._K线合成器 = K线合成器(符号, self.周期组, self.__K线回调)
+
+        self._单体分析器 = dict()
+        for 周期 in self.周期组:
+            临时配置 = 配置组.get(周期, 配置)
+            当前配置 = 临时配置.model_copy(
+                update={
+                    "推送K线": False,
+                    # "推送笔": False,
+                    "推送线段": False,
+                    # "图表展示": False,
+                },
+                deep=True,
+            )
+            self._单体分析器[周期] = 观察者(符号=符号, 周期=周期, 配置=当前配置)
+
+        self._单体分析器[self.__显示周期].配置.推送K线 = True
+        self._单体分析器[self.__显示周期].配置.推送笔 = True
+        self._单体分析器[self.__显示周期].配置.推送线段 = True
+        self._单体分析器[self.__显示周期].配置.图表展示 = True
+        self._单体分析器[self.__显示周期].重置基础序列()
+
+        for 周期 in self.周期组:  # 将不同周期对其至显示周期
+            if 周期 != self.__显示周期:
+                self._单体分析器[周期].基础缠K序列 = self._单体分析器[self.__显示周期].缠论K线序列
+
+    def 投喂K线(self, 普K: K线):
+        if 普K.周期 != self.__输入周期:
+            raise RuntimeError("立体分析器.投喂K线", 普K.周期, self.__输入周期)
+        self._K线合成器.投喂K线(普K)
+
+    def __K线回调(self, 信号类型: str, 标识: str, 周期: int, 完成K线: K线):
+        self._单体分析器[周期].增加原始K线(完成K线)
+        if 当前K线 := self._K线合成器.获取当前K线(周期):
+            self._单体分析器[周期].增加原始K线(当前K线)
+
+    def 测试_保存数据(self):
+        """拆分各序列数据，单独存文件，文件名为对应变量名"""
+
+        # 生成存储根目录
+        脚本目录 = Path(__file__).parent  # 取当前脚本所在文件夹
+        起始时间 = int(self._单体分析器[self.__输入周期].普通K线序列[0].时间戳.timestamp())
+        结束时间 = int(self._单体分析器[self.__输入周期].普通K线序列[-1].时间戳.timestamp())
+        目录标识 = f"PyM_{self._单体分析器[self.__输入周期].标识}_{起始时间}_{结束时间}"
+
+        # 最终保存路径 = 脚本目录 / 自动生成的文件夹
+        保存路径 = 脚本目录 / 目录标识
+        保存路径.mkdir(exist_ok=True)
+
+        for 周期 in self.周期组:
+            self._单体分析器[周期].测试_保存数据(保存路径)
+
+        print(f"多级别数据拆分保存完成，目录：{保存路径.resolve()}")
+
+
+def 测试_读取数据(配置: 缠论配置):
+    def 魔法():
+        启动时间 = datetime.now()
+        观察员 = 观察者.读取数据文件(配置.加载文件路径, 配置)
+        消耗用时 = datetime.now() - 启动时间
+        print("测试_读取数据 耗时", 消耗用时, "普K数量", len(观察员.普通K线序列))
+        return 观察员
+
+    return 魔法
+
+
+def 测试_周期合成(配置: 缠论配置, 配置组: Dict[int, 缠论配置] = dict()):
+    文件路径 = 配置.加载文件路径
+    name = Path(文件路径).name.split(".")[0]
+    符号, 周期, 起始时间戳, 结束时间戳 = name.split("-")
+    周期 = int(周期)
+    周期组 = [周期, 周期 * 5, 周期 * 5 * 6]
+
+    def 魔法():
+        启动时间 = datetime.now()
+        多级别分析 = 立体分析器(符号, 周期组, 配置, 配置组)
+        with open(文件路径, "rb") as f:
+            buffer = f.read()
+            size = struct.calcsize(">6d")
+            for i in range(len(buffer) // size):
+                k线 = K线.读取大端字节数组(buffer[i * size : i * size + size], 周期)
+                多级别分析.投喂K线(k线)
+        消耗用时 = datetime.now() - 启动时间
+        print("测试_周期合成", 消耗用时, "普K数量", len(多级别分析._单体分析器[周期].普通K线序列))
+        return 多级别分析
+
+    return 魔法
+
+
+if __name__ == "__main__":
+    当前配置 = 缠论配置.不推送()
+    当前配置.加载文件路径 = "./btcusd-300-1761327300-1776327900.nb"
+    测试_读取数据(当前配置)().测试_保存数据()
+    测试_周期合成(当前配置)().测试_保存数据()
diff --git a/chanlun/Cargo.toml b/chanlun/Cargo.toml
new file mode 100644
index 0000000..abb7daa
--- /dev/null
+++ b/chanlun/Cargo.toml
@@ -0,0 +1,10 @@
+[package]
+name = "chanlun"
+version = "0.1.0"
+edition = "2021"
+
+[dependencies]
+serde = { version = "1", features = ["derive"] }
+serde_json = "1"
+byteorder = "1"
+chrono = { version = "0.4", features = ["serde"] }
diff --git a/chanlun/src/algorithm/bi.rs b/chanlun/src/algorithm/bi.rs
new file mode 100644
index 0000000..aa11e75
--- /dev/null
+++ b/chanlun/src/algorithm/bi.rs
@@ -0,0 +1,821 @@
+use crate::business::observer::观察者;
+use crate::config::缠论配置;
+use crate::kline::bar::K线;
+use crate::kline::chan_kline::缠论K线;
+use crate::structure::dash_line::虚线;
+use crate::structure::fractal_obj::分型;
+use crate::types::{分型结构, 相对方向};
+use std::rc::Rc;
+
+/// 笔 — 从分型生成笔的算法集合（静态方法命名空间）
+pub struct 笔;
+
+impl 笔 {
+    /// 获取可成笔的缠K数量（考虑弱化模式）
+    pub fn 获取缠K数量(缠K序列: &[Rc<缠论K线>], 笔序列: &[Rc<虚线>], 配置: &缠论配置) -> usize {
+        let 实际数量 = 缠K序列.len();
+        if 实际数量 >= 配置.笔内元素数量 as usize {
+            return 实际数量;
+        }
+
+        if 配置.笔弱化 && 实际数量 >= 3 {
+            let 实际高点 = Self::实际高点(缠K序列, 配置.笔内相同终点取舍);
+            let 实际低点 = Self::实际低点(缠K序列, 配置.笔内相同终点取舍);
+
+            if let (Some(ref 高点), Some(ref 低点)) = (&实际高点, &实际低点) {
+                let 原始数量 = 1 + (低点.标的K线.序号 - 高点.标的K线.序号).unsigned_abs() as usize;
+                if 原始数量 >= 配置.笔内元素数量 as usize {
+                    return 配置.笔内元素数量 as usize;
+                }
+            }
+
+            if !笔序列.is_empty() {
+                // Try both high and low points (Python: 根据缠K找笔(笔序列, 实际高点) or 根据缠K找笔(笔序列, 实际低点))
+                let 筆 = 实际高点.as_ref()
+                    .and_then(|h| Self::根据缠K找笔(笔序列, h, 1))
+                    .or_else(|| 实际低点.as_ref().and_then(|l| Self::根据缠K找笔(笔序列, l, 1)));
+
+                if let Some(ref 筆) = 筆 {
+                    if let (Some(ref 高_k), Some(ref 低_k)) = (&实际高点, &实际低点) {
+                        let 原始数量 = 1 + (低_k.标的K线.序号 - 高_k.标的K线.序号).unsigned_abs() as usize;
+                        // 向上笔
+                        if 筆.方向().是否向上() && 低_k.低 < 筆.低() {
+                            if 原始数量 >= 配置.笔弱化_原始数量 as usize {
+                                return 配置.笔内元素数量 as usize;
+                            }
+                        }
+                        // 向下笔
+                        if 筆.方向().是否向下() && 低_k.低 > 筆.高() {
+                            if 原始数量 >= 配置.笔弱化_原始数量 as usize {
+                                return 配置.笔内元素数量 as usize;
+                            }
+                        }
+                    }
+                }
+            }
+        }
+        实际数量
+    }
+
+    /// 次高 — 排除最高值后的次高点
+    pub fn 次高(缠K序列: &[Rc<缠论K线>], 取舍: bool) -> Option<Rc<缠论K线>> {
+        if 缠K序列.len() < 2 {
+            return 缠K序列.first().cloned();
+        }
+        let max_高 = 缠K序列.iter().map(|k| k.高).fold(f64::NEG_INFINITY, f64::max);
+        // 排除最高值
+        let filtered: Vec<&Rc<缠论K线>> = 缠K序列.iter().filter(|k| k.高 != max_高).collect();
+        if filtered.is_empty() {
+            return 缠K序列.first().cloned();
+        }
+        // 筛选次高值
+        let second_高 = filtered.iter().map(|k| k.高).fold(f64::NEG_INFINITY, f64::max);
+        let mut candidates: Vec<&Rc<缠论K线>> = filtered.iter().filter(|k| k.高 == second_高).copied().collect();
+        // 按时间戳排序
+        candidates.sort_by(|a, b| a.时间戳.cmp(&b.时间戳));
+        if 取舍 {
+            Some(Rc::clone(candidates[candidates.len() - 1]))
+        } else {
+            Some(Rc::clone(candidates[0]))
+        }
+    }
+
+    /// 次低 — 排除最低值后的次低点
+    pub fn 次低(缠K序列: &[Rc<缠论K线>], 取舍: bool) -> Option<Rc<缠论K线>> {
+        if 缠K序列.len() < 2 {
+            return 缠K序列.first().cloned();
+        }
+        let min_低 = 缠K序列.iter().map(|k| k.低).fold(f64::INFINITY, f64::min);
+        // 排除最低值
+        let filtered: Vec<&Rc<缠论K线>> = 缠K序列.iter().filter(|k| k.低 != min_低).collect();
+        if filtered.is_empty() {
+            return 缠K序列.first().cloned();
+        }
+        // 筛选次低值
+        let second_低 = filtered.iter().map(|k| k.低).fold(f64::INFINITY, f64::min);
+        let mut candidates: Vec<&Rc<缠论K线>> = filtered.iter().filter(|k| k.低 == second_低).copied().collect();
+        // 按时间戳排序
+        candidates.sort_by(|a, b| a.时间戳.cmp(&b.时间戳));
+        if 取舍 {
+            Some(Rc::clone(candidates[candidates.len() - 1]))
+        } else {
+            Some(Rc::clone(candidates[0]))
+        }
+    }
+
+    /// 实际高点
+    pub fn 实际高点(缠K序列: &[Rc<缠论K线>], 取舍: bool) -> Option<Rc<缠论K线>> {
+        if 缠K序列.is_empty() {
+            return None;
+        }
+        let max_高 = 缠K序列.iter().map(|k| k.高).fold(f64::NEG_INFINITY, f64::max);
+        let mut candidates: Vec<&Rc<缠论K线>> = 缠K序列.iter().filter(|k| k.高 == max_高).collect();
+        if candidates.is_empty() {
+            return Some(Rc::clone(&缠K序列[0]));
+        }
+        // 按时间戳排序
+        candidates.sort_by(|a, b| a.时间戳.cmp(&b.时间戳));
+        if 取舍 {
+            Some(Rc::clone(candidates[candidates.len() - 1]))
+        } else {
+            Some(Rc::clone(candidates[0]))
+        }
+    }
+
+    /// 实际低点
+    pub fn 实际低点(缠K序列: &[Rc<缠论K线>], 取舍: bool) -> Option<Rc<缠论K线>> {
+        if 缠K序列.is_empty() {
+            return None;
+        }
+        let min_低 = 缠K序列.iter().map(|k| k.低).fold(f64::INFINITY, f64::min);
+        let mut candidates: Vec<&Rc<缠论K线>> = 缠K序列.iter().filter(|k| k.低 == min_低).collect();
+        if candidates.is_empty() {
+            return Some(Rc::clone(&缠K序列[0]));
+        }
+        // 按时间戳排序
+        candidates.sort_by(|a, b| a.时间戳.cmp(&b.时间戳));
+        if 取舍 {
+            Some(Rc::clone(candidates[candidates.len() - 1]))
+        } else {
+            Some(Rc::clone(candidates[0]))
+        }
+    }
+
+    /// 判断笔的相对关系是否合理
+    pub fn 相对关系(筆: &虚线, _配置: &缠论配置) -> bool {
+        let 文 = &筆.文;
+        let 武 = &筆.武;
+
+        // 向上笔：文(底)低 → 武(顶)高
+        if 筆.方向().是否向上() {
+            return 武.分型特征值 > 文.分型特征值;
+        }
+        // 向下笔：文(顶)高 → 武(底)低
+        武.分型特征值 < 文.分型特征值
+    }
+
+    /// 以文会友 — 根据起点分型找笔
+    pub fn 以文会友(笔序列: &[Rc<虚线>], 文: &Rc<分型>) -> Option<Rc<虚线>> {
+        笔序列.iter().find(|b| Rc::as_ptr(&b.文) == Rc::as_ptr(文)).cloned()
+    }
+
+    /// 以武会友 — 根据终点分型找笔
+    pub fn 以武会友(笔序列: &[Rc<虚线>], 武: &Rc<分型>) -> Option<Rc<虚线>> {
+        笔序列.iter().find(|b| Rc::as_ptr(&b.武) == Rc::as_ptr(武)).cloned()
+    }
+
+    /// 根据缠K找对应的笔
+    pub fn 根据缠K找笔(笔序列: &[Rc<虚线>], 缠K: &Rc<缠论K线>, 偏移: i64) -> Option<Rc<虚线>> {
+        // Python iterates in reverse: for 筆 in 笔序列[::-1]
+        for b in 笔序列.iter().rev() {
+            // Python: 筆.文.中.序号 - 偏移 <= 缠K.序号 <= 筆.武.中.序号
+            if b.文.中.序号 - 偏移 <= 缠K.序号 && 缠K.序号 <= b.武.中.序号 {
+                return Some(Rc::clone(b));
+            }
+        }
+        None
+    }
+
+    /// 从分型序列中弹出最后一个分型和对应的笔
+    fn 弹出旧笔(分型序列: &mut Vec<Rc<分型>>, 笔序列: &mut Vec<Rc<虚线>>) {
+        分型序列.pop();
+        if !笔序列.is_empty() {
+            // Python sets旧笔.有效性 = False; with Rc we just drop the笔
+            笔序列.pop();
+        }
+    }
+
+    /// 核心笔分析 — 使用显式栈模拟递归
+    ///
+    /// 返回: 递归层次数
+    pub fn 分析(
+        初始分型: Rc<分型>,
+        分型序列: &mut Vec<Rc<分型>>,
+        笔序列: &mut Vec<Rc<虚线>>,
+        缠K序列: &[Rc<缠论K线>],
+        _普K序列: &[Rc<K线>],
+        配置: &缠论配置,
+    ) -> i64 {
+        enum 栈项 {
+            分型(Rc<分型>, i64),
+            /// 修复错过笔哨兵: 若临时分型被接受为最后一个元素，则扫描武将之后的所有分型
+            修复错过笔 {
+                临时分型: Rc<分型>,
+                武将缠K: Rc<缠论K线>,
+                层次: i64,
+            },
+        }
+
+        let mut 栈: Vec<栈项> = Vec::new();
+        栈.push(栈项::分型(初始分型, 0));
+
+        while let Some(项) = 栈.pop() {
+            let (当前分型, 递归层次) = match 项 {
+                栈项::分型(fx, lvl) => (fx, lvl),
+                栈项::修复错过笔 {
+                    临时分型,
+                    武将缠K,
+                    层次,
+                } => {
+                    // Python line 2406: only scan if临时分型 was accepted as last element
+                    if !分型序列.is_empty() {
+                        if let Some(last_fx) = 分型序列.last() {
+                            if Rc::as_ptr(last_fx) == Rc::as_ptr(&临时分型) {
+                                if let Some(武_idx) = 缠K序列
+                                    .iter()
+                                    .position(|k| Rc::as_ptr(k) == Rc::as_ptr(&武将缠K))
+                                {
+                                    let mut 错过: Vec<Rc<分型>> = Vec::new();
+                                    for ck in &缠K序列[武_idx..] {
+                                        if ck.分型 == Some(分型结构::底)
+                                            || ck.分型 == Some(分型结构::顶)
+                                        {
+                                            if let Some(fx) =
+                                                分型::从缠K序列中获取分型(缠K序列, ck)
+                                            {
+                                                错过.push(Rc::new(fx));
+                                            }
+                                        }
+                                    }
+                                    // Push in reverse so first in slice is processed first
+                                    for m in 错过.into_iter().rev() {
+                                        栈.push(栈项::分型(m, 层次 + 1));
+                                    }
+                                }
+                            }
+                        }
+                    }
+                    // 当前分型 is already next on the stack (pushed before this哨兵)
+                    continue;
+                }
+            };
+
+            if 递归层次 > 256 {
+                continue;
+            }
+
+            if !matches!(当前分型.结构, 分型结构::顶 | 分型结构::底) {
+                continue;
+            }
+
+            // Python line 2322-2325: 第一个分型直接追加
+            if 分型序列.is_empty() {
+                分型序列.push(当前分型);
+                continue;
+            }
+
+            let 之前分型 = Rc::clone(分型序列.last().unwrap());
+
+            // Python line 2330-2335: 清理无效数据
+            if 之前分型.时间戳 == 当前分型.时间戳
+                || matches!(之前分型.结构, 分型结构::上 | 分型结构::下)
+            {
+                Self::弹出旧笔(分型序列, 笔序列);
+                if 分型序列.is_empty() {
+                    if 当前分型.右.is_some() {
+                        分型序列.push(当前分型);
+                    }
+                    continue;
+                }
+            }
+
+            let 之前分型 = Rc::clone(分型序列.last().unwrap());
+
+            // Python line 2338: 时序检查 — skip out-of-order fractals
+            if 之前分型.时间戳 > 当前分型.时间戳 && 之前分型.中.序号 - 当前分型.中.序号 > 1 {
+                continue;
+            }
+
+            // Python line 2343-2348: 笔弱化模式
+            if 配置.笔弱化 && !笔序列.is_empty() {
+                let 前一笔 = 笔序列.last().unwrap();
+                let 前一笔缠K数 = 前一笔.武.中.序号 - 前一笔.文.中.序号 + 1;
+                if 前一笔缠K数 == 3 {
+                    let 破位 = (前一笔.方向().是否向上()
+                        && 前一笔.低() > 当前分型.分型特征值
+                        && 当前分型.结构 == 分型结构::底)
+                        || (前一笔.方向().是否向下()
+                            && 前一笔.高() < 当前分型.分型特征值
+                            && 当前分型.结构 == 分型结构::顶);
+                    if 破位 {
+                        Self::弹出旧笔(分型序列, 笔序列);
+                        栈.push(栈项::分型(当前分型, 递归层次 + 1));
+                        continue;
+                    }
+                }
+            }
+
+            // Re-read之前分型 again after笔弱化 pop
+            let 之前分型 = Rc::clone(分型序列.last().unwrap());
+
+            // Python line 2350: 分型结构相反 → 可能成笔
+            if 之前分型.结构 != 当前分型.结构 {
+                let 文_idx = 缠K序列.iter().position(|k| Rc::as_ptr(k) == Rc::as_ptr(&之前分型.中));
+                let 武_idx = 缠K序列.iter().position(|k| Rc::as_ptr(k) == Rc::as_ptr(&当前分型.中));
+
+                if let (Some(文_idx), Some(武_idx)) = (文_idx, 武_idx) {
+                    let 基础序列 = &缠K序列[文_idx..=武_idx];
+                    let 缠K数量 = Self::获取缠K数量(基础序列, 笔序列, 配置);
+
+                    if 缠K数量 >= 配置.笔内元素数量 as usize {
+                        // Python line 2354-2357: 文官 always uses false (not 笔内相同终点取舍)
+                        let 文官 = match 之前分型.结构 {
+                            分型结构::顶 => Self::实际高点(基础序列, false),
+                            _ => Self::实际低点(基础序列, false),
+                        };
+
+                        // Python line 2359-2367: 文官 != 之前分型.中 → adjust
+                        if let Some(ref 文官_k) = 文官 {
+                            if Rc::as_ptr(文官_k) != Rc::as_ptr(&之前分型.中) {
+                                if let Some(临时分型) =
+                                    分型::从缠K序列中获取分型(缠K序列, 文官_k)
+                                {
+                                    栈.push(栈项::分型(当前分型, 递归层次));
+                                    栈.push(栈项::分型(Rc::new(临时分型), 递归层次 + 1));
+                                    continue;
+                                }
+                            }
+                        }
+
+                        // Python line 2369-2372: 武将
+                        let 武将 = match 当前分型.结构 {
+                            分型结构::底 => Self::实际低点(基础序列, 配置.笔内相同终点取舍),
+                            _ => Self::实际高点(基础序列, 配置.笔内相同终点取舍),
+                        };
+
+                        let 新笔 = Rc::new(虚线::创建笔(
+                            Rc::clone(&之前分型),
+                            Rc::clone(&当前分型),
+                            true,
+                        ));
+
+                        // Python line 2374-2376: 相对关系 and武将 matches
+                        if Self::相对关系(&新笔, 配置) {
+                            if let Some(ref 武将_k) = 武将 {
+                                if Rc::as_ptr(武将_k) == Rc::as_ptr(&当前分型.中) {
+                                    Self::_添加新笔递归(分型序列, 笔序列, 当前分型, 新笔);
+                                    continue;
+                                }
+                            }
+                        }
+
+                        // Python line 2378-2385: 笔次级成笔
+                        if 配置.笔次级成笔 {
+                            let 武将 = match 当前分型.结构 {
+                                分型结构::底 => Self::次低(基础序列, 配置.笔内相同终点取舍),
+                                _ => Self::次高(基础序列, 配置.笔内相同终点取舍),
+                            };
+                            if let Some(ref 武将_k) = 武将 {
+                                if Rc::as_ptr(武将_k) == Rc::as_ptr(&当前分型.中)
+                                    && Self::相对关系(&新笔, 配置)
+                                {
+                                    Self::_添加新笔递归(分型序列, 笔序列, 当前分型, 新笔);
+                                    continue;
+                                }
+                            }
+                        }
+                    } else {
+                        // Python line 2388-2390: 元素不足 → 右元素扩展
+                        if let Some(ref 右) = 当前分型.右 {
+                            if let Some(临时分型) = 分型::从缠K序列中获取分型(缠K序列, 右) {
+                                栈.push(栈项::分型(Rc::new(临时分型), 递归层次 + 1));
+                                continue;
+                            }
+                        }
+                    }
+                }
+            } else {
+                // Python line 2392-2419: 分型结构相同 → 更强则替换 + 修复错过笔
+                let 分型特征值 = 当前分型.分型特征值;
+
+                let 更强 = match 之前分型.结构 {
+                    分型结构::顶 => 之前分型.分型特征值 < 分型特征值,
+                    分型结构::底 => 之前分型.分型特征值 > 分型特征值,
+                    _ => false,
+                };
+
+                if 更强 {
+                    let 被替换分型 = Rc::clone(&之前分型);
+                    Self::弹出旧笔(分型序列, 笔序列);
+
+                    if let Some(k线序列) =
+                        缠论K线::截取(缠K序列, &被替换分型.中, &当前分型.中)
+                    {
+                        let 武将 = match 被替换分型.结构 {
+                            分型结构::顶 => {
+                                Self::实际低点(&k线序列, 配置.笔内相同终点取舍)
+                            }
+                            _ => Self::实际高点(&k线序列, 配置.笔内相同终点取舍),
+                        };
+
+                        if let Some(ref 武将_k) = 武将 {
+                            if let Some(临时分型) =
+                                分型::从缠K序列中获取分型(缠K序列, 武将_k)
+                            {
+                                let 临时分型_rc = Rc::new(临时分型);
+
+                                if !分型序列.is_empty() {
+                                    // Push in reverse processing order (LIFO):
+                                    栈.push(栈项::分型(Rc::clone(&当前分型), 递归层次 + 2));
+                                    栈.push(栈项::修复错过笔 {
+                                        临时分型: Rc::clone(&临时分型_rc),
+                                        武将缠K: Rc::clone(武将_k),
+                                        层次: 递归层次 + 1,
+                                    });
+                                    栈.push(栈项::分型(临时分型_rc, 递归层次 + 1));
+                                    continue;
+                                } else {
+                                    分型序列.push(当前分型);
+                                    continue;
+                                }
+                            }
+                        }
+                    }
+
+                    if 分型序列.is_empty() {
+                        分型序列.push(当前分型);
+                    } else {
+                        栈.push(栈项::分型(当前分型, 递归层次 + 1));
+                    }
+                }
+            }
+        }
+
+        栈.len() as i64
+    }
+
+    /// 核心笔分析 — 递归实现，逐句对照 chan.py 笔.分析 / 笔递归分析
+    ///
+    /// 返回: 递归层次数
+    pub fn 分析递归(
+        当前分型: Rc<分型>,
+        分型序列: &mut Vec<Rc<分型>>,
+        笔序列: &mut Vec<Rc<虚线>>,
+        缠K序列: &[Rc<缠论K线>],
+        _普K序列: &[Rc<K线>],
+        递归层次: i64,
+        配置: &缠论配置,
+    ) -> i64 {
+        // Python line 2315-2317: 递归深度限制
+        if 递归层次 > 64 {
+            println!("笔.分析 递归深度超出 64 < {}", 递归层次);
+        }
+
+        // Python line 2319-2320: 非顶底分型跳过
+        if !matches!(当前分型.结构, 分型结构::顶 | 分型结构::底) {
+            return 递归层次;
+        }
+
+        // Python line 2322-2325: 第一个分型直接追加
+        if 分型序列.is_empty() {
+            if matches!(当前分型.结构, 分型结构::顶 | 分型结构::底) {
+                分型序列.push(当前分型);
+            }
+            return 递归层次;
+        }
+
+        // Python line 2329-2335: 清理无效数据
+        let 之前分型 = Rc::clone(分型序列.last().unwrap());
+        if 之前分型.时间戳 == 当前分型.时间戳
+            || matches!(之前分型.结构, 分型结构::上 | 分型结构::下)
+        {
+            Self::弹出旧笔(分型序列, 笔序列);
+            if 分型序列.is_empty() {
+                if 当前分型.右.is_some() {
+                    分型::向序列中添加(分型序列, 当前分型);
+                }
+                return 递归层次;
+            }
+        }
+
+        // Python line 2337-2341: 时序检查
+        let 之前分型 = Rc::clone(分型序列.last().unwrap());
+        if 之前分型.时间戳 > 当前分型.时间戳 && 之前分型.中.序号 - 当前分型.中.序号 > 1 {
+            println!("时序错误-{}, {}, {}", 递归层次, 之前分型, 当前分型);
+            return 递归层次;
+        }
+
+        // Python line 2343-2348: 笔弱化模式
+        if 配置.笔弱化 && !笔序列.is_empty() {
+            let 前一笔 = 笔序列.last().unwrap();
+            let 前一笔缠K数 = 前一笔.武.中.序号 - 前一笔.文.中.序号 + 1;
+            if 前一笔缠K数 == 3 {
+                let 破位 = (前一笔.方向().是否向上()
+                    && 前一笔.低() > 当前分型.分型特征值
+                    && 当前分型.结构 == 分型结构::底)
+                    || (前一笔.方向().是否向下()
+                        && 前一笔.高() < 当前分型.分型特征值
+                        && 当前分型.结构 == 分型结构::顶);
+                if 破位 {
+                    Self::弹出旧笔(分型序列, 笔序列);
+                    return Self::分析递归(
+                        当前分型, 分型序列, 笔序列, 缠K序列, _普K序列, 递归层次 + 1, 配置,
+                    );
+                }
+            }
+        }
+
+        // Python line 2350: 分型结构相反 → 可能成笔
+        let 之前分型 = Rc::clone(分型序列.last().unwrap());
+        if 之前分型.结构 != 当前分型.结构 {
+            if let Some(基础序列) = 缠论K线::截取(缠K序列, &之前分型.中, &当前分型.中) {
+                let 当前笔 = Rc::new(虚线::创建笔(
+                    Rc::clone(&之前分型),
+                    Rc::clone(&当前分型),
+                    true,
+                ));
+
+                if Self::获取缠K数量(&基础序列, 笔序列, 配置) >= 配置.笔内元素数量 as usize
+                {
+                    // Python line 2354-2357: 文官
+                    let 文官 = match 之前分型.结构 {
+                        分型结构::顶 => Self::实际高点(&基础序列, false),
+                        _ => Self::实际低点(&基础序列, false),
+                    };
+
+                    // Python line 2359-2367: 文官调整
+                    if let Some(ref 文官_k) = 文官 {
+                        if Rc::as_ptr(文官_k) != Rc::as_ptr(&之前分型.中) {
+                            if let Some(临时分型) =
+                                分型::从缠K序列中获取分型(缠K序列, 文官_k)
+                            {
+                                let 递归层次 = Self::分析递归(
+                                    Rc::new(临时分型),
+                                    分型序列,
+                                    笔序列,
+                                    缠K序列,
+                                    _普K序列,
+                                    递归层次 + 1,
+                                    配置,
+                                );
+                                return Self::分析递归(
+                                    当前分型, 分型序列, 笔序列, 缠K序列, _普K序列,
+                                    递归层次 + 1,
+                                    配置,
+                                );
+                            }
+                        }
+                    }
+
+                    // Python line 2369-2375: 武将 and笔形成
+                    let 武将 = match 当前分型.结构 {
+                        分型结构::底 => {
+                            Self::实际低点(&基础序列, 配置.笔内相同终点取舍)
+                        }
+                        _ => Self::实际高点(&基础序列, 配置.笔内相同终点取舍),
+                    };
+
+                    if Self::相对关系(&当前笔, 配置) {
+                        if let Some(ref 武将_k) = 武将 {
+                            if Rc::as_ptr(武将_k) == Rc::as_ptr(&当前分型.中) {
+                                // 直接添加（对照 Python _添加新笔：直接 append）
+                                Self::_添加新笔递归(分型序列, 笔序列, 当前分型, 当前笔);
+                                return 递归层次;
+                            }
+                        }
+                    }
+
+                    // Python line 2378-2385: 笔次级成笔
+                    if 配置.笔次级成笔 {
+                        let 武将 = match 当前分型.结构 {
+                            分型结构::底 => {
+                                Self::次低(&基础序列, 配置.笔内相同终点取舍)
+                            }
+                            _ => Self::次高(&基础序列, 配置.笔内相同终点取舍),
+                        };
+                        if let Some(ref 武将_k) = 武将 {
+                            if Rc::as_ptr(武将_k) == Rc::as_ptr(&当前分型.中)
+                                && Self::相对关系(&当前笔, 配置)
+                            {
+                                Self::_添加新笔递归(分型序列, 笔序列, 当前分型, 当前笔);
+                                return 递归层次;
+                            }
+                        }
+                    }
+                } else {
+                    // Python line 2388-2390: 元素不足 → 右元素扩展
+                    if let Some(ref 右) = 当前分型.右 {
+                        if let Some(临时分型) =
+                            分型::从缠K序列中获取分型(缠K序列, 右)
+                        {
+                            return Self::分析递归(
+                                Rc::new(临时分型),
+                                分型序列,
+                                笔序列,
+                                缠K序列,
+                                _普K序列,
+                                递归层次 + 1,
+                                配置,
+                            );
+                        }
+                    }
+                }
+            }
+        } else {
+            // Python line 2392-2419: 分型结构相同 → 更强则替换 + 修复错过笔
+            let 分型特征值 = 当前分型.分型特征值;
+
+            let 更强 = match 之前分型.结构 {
+                分型结构::顶 => 之前分型.分型特征值 < 分型特征值,
+                分型结构::底 => 之前分型.分型特征值 > 分型特征值,
+                _ => false,
+            };
+
+            if 更强 {
+                // 保存被弹出的之前分型（用于修复错过笔的范围计算）
+                let 被替换分型 = Rc::clone(&之前分型);
+                Self::弹出旧笔(分型序列, 笔序列);
+
+                if let Some(k线序列) =
+                    缠论K线::截取(缠K序列, &被替换分型.中, &当前分型.中)
+                {
+                    let 武将 = match 被替换分型.结构 {
+                        分型结构::顶 => {
+                            Self::实际低点(&k线序列, 配置.笔内相同终点取舍)
+                        }
+                        _ => Self::实际高点(&k线序列, 配置.笔内相同终点取舍),
+                    };
+
+                    if let Some(ref 武将_k) = 武将 {
+                        if let Some(临时分型) =
+                            分型::从缠K序列中获取分型(缠K序列, 武将_k)
+                        {
+                            let 临时分型_rc = Rc::new(临时分型);
+
+                            if !分型序列.is_empty() {
+                                let mut 递归层次 = Self::分析递归(
+                                    Rc::clone(&临时分型_rc),
+                                    分型序列,
+                                    笔序列,
+                                    缠K序列,
+                                    _普K序列,
+                                    递归层次 + 1,
+                                    配置,
+                                );
+
+                                // 修复错过的笔: 扫描武将之后的所有分型
+                                if !分型序列.is_empty()
+                                    && Rc::as_ptr(分型序列.last().unwrap())
+                                        == Rc::as_ptr(&临时分型_rc)
+                                {
+                                    if let Some(武_idx) = 缠K序列
+                                        .iter()
+                                        .position(|k| Rc::as_ptr(k) == Rc::as_ptr(武将_k))
+                                    {
+                                        for ck in &缠K序列[武_idx..] {
+                                            if ck.分型 == Some(分型结构::底)
+                                                || ck.分型 == Some(分型结构::顶)
+                                            {
+                                                if let Some(错过分型) =
+                                                    分型::从缠K序列中获取分型(缠K序列, ck)
+                                                {
+                                                    let 错过分型_rc =
+                                                        Rc::new(错过分型);
+                                                    递归层次 = Self::分析递归(
+                                                        Rc::clone(&错过分型_rc),
+                                                        分型序列,
+                                                        笔序列,
+                                                        缠K序列,
+                                                        _普K序列,
+                                                        递归层次 + 1,
+                                                        配置,
+                                                    );
+                                                }
+                                            }
+                                        }
+                                    }
+                                }
+
+                                return Self::分析递归(
+                                    当前分型, 分型序列, 笔序列, 缠K序列, _普K序列,
+                                    递归层次 + 1,
+                                    配置,
+                                );
+                            } else {
+                                分型::向序列中添加(分型序列, 当前分型);
+                            }
+                        }
+                    }
+                } else if 分型序列.is_empty() {
+                    分型::向序列中添加(分型序列, 当前分型);
+                } else {
+                    return Self::分析递归(
+                        当前分型, 分型序列, 笔序列, 缠K序列, _普K序列, 递归层次 + 1, 配置,
+                    );
+                }
+            }
+        }
+
+        递归层次
+    }
+
+    /// 添加新笔到序列（递归版本 — 直接追加，对应 Python _添加新笔）
+    fn _添加新笔递归(
+        分型序列: &mut Vec<Rc<分型>>,
+        笔序列: &mut Vec<Rc<虚线>>,
+        新分型: Rc<分型>,
+        新笔: Rc<虚线>,
+    ) {
+        分型序列.push(新分型);
+        let 序号 = if 笔序列.is_empty() {
+            0
+        } else {
+            笔序列.last().unwrap().序号 + 1
+        };
+        let mut 虚线笔 = (*新笔).clone();
+        虚线笔.序号 = 序号;
+        if 虚线笔.武.左.is_none() && 虚线笔.武.右.is_none() {
+            虚线笔.有效性 = false;
+        }
+        笔序列.push(Rc::new(虚线笔));
+    }
+
+    /// 自检 — 验证笔的有效性（文为实际高/低点，武为实际低/高点）
+    pub fn 自检(筆: &虚线, 观察员: &观察者) -> bool {
+        let 笔序列 = &观察员.笔序列;
+        let 配置 = &观察员.配置;
+        let 基础序列 = 筆.获取缠K序列(&观察员.缠论K线序列);
+        if Self::获取缠K数量(&基础序列, 笔序列, 配置) >= 配置.笔内元素数量 as usize {
+            if 筆.方向() == 相对方向::向下 {
+                if let (Some(实际高), Some(实际低)) = (
+                    Self::实际高点(&基础序列, false),
+                    Self::实际低点(&基础序列, 配置.笔内相同终点取舍),
+                ) {
+                    if Rc::ptr_eq(&筆.文.中, &实际高) && Rc::ptr_eq(&筆.武.中, &实际低) {
+                        return true;
+                    }
+                }
+            }
+            if 筆.方向() == 相对方向::向上 {
+                if let (Some(实际低), Some(实际高)) = (
+                    Self::实际低点(&基础序列, false),
+                    Self::实际高点(&基础序列, 配置.笔内相同终点取舍),
+                ) {
+                    if Rc::ptr_eq(&筆.文.中, &实际低) && Rc::ptr_eq(&筆.武.中, &实际高) {
+                        return true;
+                    }
+                }
+            }
+        }
+        false
+    }
+
+    /// 获取所有停顿位置 — 在笔范围内找出所有能成笔的分型组合
+    pub fn 获取所有停顿位置(筆: &虚线, 观察员: &观察者) -> Vec<虚线> {
+        let mut 笔序列 = Vec::new();
+        let 文 = Rc::clone(&筆.文);
+        let 基础序列 = 筆.获取缠K序列(&观察员.缠论K线序列);
+
+        if 基础序列.len() < 5 {
+            return 笔序列;
+        }
+
+        for i in 3..基础序列.len() - 1 {
+            let k = &基础序列[i];
+
+            if k.分型 == Some(分型结构::顶) && 筆.方向() == 相对方向::向上 {
+                let 左 = Rc::clone(&基础序列[i - 1]);
+                let 中 = Rc::clone(k);
+                let 右 = Rc::clone(&基础序列[i + 1]);
+                let 武 = 分型::new(Some(左), 中, Some(右));
+                let mut 当前笔 = 虚线::创建笔(Rc::clone(&文), Rc::new(武), true);
+                当前笔.序号 = 筆.序号;
+                if Self::自检(&当前笔, 观察员) {
+                    笔序列.push(当前笔);
+                }
+            } else if k.分型 == Some(分型结构::底) && 筆.方向() == 相对方向::向下 {
+                let 左 = Rc::clone(&基础序列[i - 1]);
+                let 中 = Rc::clone(k);
+                let 右 = Rc::clone(&基础序列[i + 1]);
+                let 武 = 分型::new(Some(左), 中, Some(右));
+                let mut 当前笔 = 虚线::创建笔(Rc::clone(&文), Rc::new(武), true);
+                当前笔.序号 = 筆.序号;
+                if Self::自检(&当前笔, 观察员) {
+                    笔序列.push(当前笔);
+                }
+            }
+        }
+
+        笔序列
+    }
+
+    /// 是否背驰过 — 判断笔是否在停顿位置出现过MACD趋向背驰
+    pub fn 是否背驰过(当前筆: &虚线, 观察员: &观察者) -> Vec<Rc<分型>> {
+        let 停顿位置 = Self::获取所有停顿位置(当前筆, 观察员);
+        let mut 结果 = Vec::new();
+
+        for 筆 in &停顿位置 {
+            let k线范围 = K线::截取rc(
+                &观察员.普通K线序列,
+                &当前筆.文.中.标的K线,
+                &当前筆.武.中.标的K线,
+            );
+            let 背驰信号 = 虚线::计算K线序列MACD趋向背驰(&k线范围, 筆.方向());
+            if 背驰信号.iter().all(|&x| x) {
+                结果.push(Rc::clone(&筆.武));
+            }
+        }
+
+        结果
+    }
+}
diff --git a/chanlun/src/algorithm/divergence.rs b/chanlun/src/algorithm/divergence.rs
new file mode 100644
index 0000000..ad93480
--- /dev/null
+++ b/chanlun/src/algorithm/divergence.rs
@@ -0,0 +1,139 @@
+use crate::config::缠论配置;
+use crate::kline::bar::K线;
+use crate::structure::dash_line::虚线;
+use std::rc::Rc;
+
+/// 背驰分析 — 判断进入段和离开段之间是否存在背驰
+pub struct 背驰分析;
+
+impl 背驰分析 {
+    /// MACD背驰 — 离开段MACD柱子面积小于进入段
+    pub fn MACD背驰(进入段: &虚线, 离开段: &虚线, K线序列: &[Rc<K线>], 方式: &str) -> bool {
+        // 获取进入段和离开段对应的K线
+        let 进入段_始 = 进入段.文.中.原始起始序号 as usize;
+        let 进入段_终 = 进入段.武.中.原始结束序号 as usize;
+        let 离开段_始 = 离开段.文.中.原始起始序号 as usize;
+        let 离开段_终 = 离开段.武.中.原始结束序号 as usize;
+
+        if 进入段_终 >= K线序列.len() || 离开段_终 >= K线序列.len() {
+            return false;
+        }
+
+        let 进入MACD = Self::柱子面积(&K线序列[进入段_始..=进入段_终], 方式);
+        let 离开MACD = Self::柱子面积(&K线序列[离开段_始..=离开段_终], 方式);
+
+        // 背驰条件: 离开段面积绝对值小于进入段
+        let 进入总面积 = 进入MACD.阳 + 进入MACD.阴.abs();
+        let 离开总面积 = 离开MACD.阳 + 离开MACD.阴.abs();
+
+        if 进入总面积 < f64::EPSILON {
+            return false;
+        }
+        离开总面积 < 进入总面积
+    }
+
+    /// 斜率背驰 — 离开段斜率小于进入段
+    pub fn 斜率背驰(进入段: &虚线, 离开段: &虚线) -> bool {
+        let 进入斜率 = (进入段.武.分型特征值 - 进入段.文.分型特征值).abs()
+            / (进入段.武.时间戳 - 进入段.文.时间戳).abs() as f64;
+        let 离开斜率 = (离开段.武.分型特征值 - 离开段.文.分型特征值).abs()
+            / (离开段.武.时间戳 - 离开段.文.时间戳).abs() as f64;
+
+        离开斜率 < 进入斜率
+    }
+
+    /// 测度背驰 — 价格测度的背驰判断
+    pub fn 测度背驰(进入段: &虚线, 离开段: &虚线) -> bool {
+        let 进入幅度 = (进入段.武.分型特征值 - 进入段.文.分型特征值).abs();
+        let 离开幅度 = (离开段.武.分型特征值 - 离开段.文.分型特征值).abs();
+        离开幅度 < 进入幅度
+    }
+
+    /// 全量背驰 — MACD + 斜率 + 测度 三者全满足
+    pub fn 全量背驰(进入段: &虚线, 离开段: &虚线, 普K序列: &[Rc<K线>]) -> bool {
+        Self::MACD背驰(进入段, 离开段, 普K序列, "总")
+            && Self::斜率背驰(进入段, 离开段)
+            && Self::测度背驰(进入段, 离开段)
+    }
+
+    /// 任意背驰 — 任一条件满足即可
+    pub fn 任意背驰(进入段: &虚线, 离开段: &虚线, 普K序列: &[Rc<K线>]) -> bool {
+        Self::MACD背驰(进入段, 离开段, 普K序列, "总")
+            || Self::斜率背驰(进入段, 离开段)
+            || Self::测度背驰(进入段, 离开段)
+    }
+
+    /// 配置背驰 — 根据配置选择判断方式
+    pub fn 配置背驰(进入段: &虚线, 离开段: &虚线, 普K序列: &[Rc<K线>], 配置: &缠论配置) -> bool {
+        let mut result = true;
+        if 配置.线段内部背驰_MACD {
+            result = result && Self::MACD背驰(进入段, 离开段, 普K序列, "总");
+        }
+        if 配置.线段内部背驰_斜率 {
+            result = result && Self::斜率背驰(进入段, 离开段);
+        }
+        if 配置.线段内部背驰_测度 {
+            result = result && Self::测度背驰(进入段, 离开段);
+        }
+        result
+    }
+
+    /// 任选背驰
+    pub fn 任选背驰(进入段: &虚线, 离开段: &虚线, 普K序列: &[Rc<K线>]) -> bool {
+        Self::任意背驰(进入段, 离开段, 普K序列)
+    }
+
+    /// 背驰模式 — 根据模式字符串选择判断方式
+    pub fn 背驰模式(
+        进入段: &虚线,
+        离开段: &虚线,
+        普K序列: &[Rc<K线>],
+        配置: &缠论配置,
+        模式: &str,
+    ) -> bool {
+        match 模式 {
+            "全量" => Self::全量背驰(进入段, 离开段, 普K序列),
+            "任意" => Self::任意背驰(进入段, 离开段, 普K序列),
+            "配置" => Self::配置背驰(进入段, 离开段, 普K序列, 配置),
+            "相对" => Self::测度背驰(进入段, 离开段),
+            _ => Self::配置背驰(进入段, 离开段, 普K序列, 配置),
+        }
+    }
+
+    // ---- 内部辅助 ----
+
+    fn 柱子面积(K线序列: &[Rc<K线>], 方式: &str) -> MACD面积 {
+        let mut 阳 = 0.0f64;
+        let mut 阴 = 0.0f64;
+        for k in K线序列 {
+            if let Some(ref macd) = k.macd {
+                let hist = macd.MACD柱;
+                match 方式 {
+                    "阳" => {
+                        if hist > 0.0 {
+                            阳 += hist
+                        }
+                    }
+                    "阴" => {
+                        if hist < 0.0 {
+                            阴 += hist
+                        }
+                    }
+                    "总" | _ => {
+                        if hist >= 0.0 {
+                            阳 += hist
+                        } else {
+                            阴 += hist
+                        }
+                    }
+                }
+            }
+        }
+        MACD面积 { 阳, 阴 }
+    }
+}
+
+struct MACD面积 {
+    阳: f64,
+    阴: f64,
+}
diff --git a/chanlun/src/algorithm/hub.rs b/chanlun/src/algorithm/hub.rs
new file mode 100644
index 0000000..258c6ad
--- /dev/null
+++ b/chanlun/src/algorithm/hub.rs
@@ -0,0 +1,348 @@
+use crate::structure::dash_line::虚线;
+use crate::structure::fractal_obj::分型;
+use crate::types::相对方向;
+use std::rc::Rc;
+
+/// 中枢 — 三段虚线重叠区间构成的价格中枢
+#[derive(Debug, Clone)]
+pub struct 中枢 {
+    pub 序号: i64,
+    pub 标识: String,
+    pub 级别: i64,
+    pub 基础序列: Vec<Rc<虚线>>,
+    pub 第三买卖线: Option<Rc<虚线>>,
+    pub 本级_第三买卖线: Option<Rc<虚线>>,
+}
+
+impl 中枢 {
+    pub fn new(序号: i64, 标识: String, 级别: i64, 基础序列: Vec<Rc<虚线>>) -> Self {
+        Self {
+            序号,
+            标识,
+            级别,
+            基础序列: 基础序列.into_iter().take(3).collect(),
+            第三买卖线: None,
+            本级_第三买卖线: None,
+        }
+    }
+
+    pub fn 添加虚线(&mut self, 实线: Rc<虚线>) {
+        self.基础序列.push(实线);
+        self.本级_第三买卖线 = None;
+        self.第三买卖线 = None;
+    }
+
+    pub fn 图表标题(&self) -> String {
+        format!(
+            "{}:{}:{}:{}",
+            self.文().中.标识, self.文().中.周期, self.标识, self.序号
+        )
+    }
+
+    pub fn 离开段(&self) -> Rc<虚线> {
+        Rc::clone(&self.基础序列[self.基础序列.len() - 1])
+    }
+
+    pub fn 方向(&self) -> 相对方向 {
+        self.基础序列[0].方向().翻转()
+    }
+
+    pub fn 高(&self) -> f64 {
+        self.基础序列[..3]
+            .iter()
+            .map(|x| x.高())
+            .min_by(|a, b| a.partial_cmp(b).unwrap_or(std::cmp::Ordering::Equal))
+            .unwrap_or(0.0)
+    }
+
+    pub fn 低(&self) -> f64 {
+        self.基础序列[..3]
+            .iter()
+            .map(|x| x.低())
+            .max_by(|a, b| a.partial_cmp(b).unwrap_or(std::cmp::Ordering::Equal))
+            .unwrap_or(0.0)
+    }
+
+    pub fn 高高(&self) -> f64 {
+        self.基础序列
+            .iter()
+            .map(|x| x.高())
+            .max_by(|a, b| a.partial_cmp(b).unwrap_or(std::cmp::Ordering::Equal))
+            .unwrap_or(0.0)
+    }
+
+    pub fn 低低(&self) -> f64 {
+        self.基础序列
+            .iter()
+            .map(|x| x.低())
+            .min_by(|a, b| a.partial_cmp(b).unwrap_or(std::cmp::Ordering::Equal))
+            .unwrap_or(0.0)
+    }
+
+    pub fn 文(&self) -> Rc<分型> {
+        Rc::clone(&self.基础序列[0].文)
+    }
+
+    pub fn 武(&self) -> Rc<分型> {
+        Rc::clone(&self.基础序列[self.基础序列.len() - 1].武)
+    }
+
+    pub fn 设置第三买卖线(&mut self, 线: Rc<虚线>) {
+        self.第三买卖线 = Some(线);
+    }
+
+    pub fn 获取数据文本(&self) -> String {
+        let 第三买卖线_str = match &self.第三买卖线 {
+            Some(x) => format!("{}", x),
+            None => "None".to_string(),
+        };
+        let 本级_第三买卖线_str = match &self.本级_第三买卖线 {
+            Some(x) => format!("{}", x),
+            None => "None".to_string(),
+        };
+        format!(
+            "{}, {}, {}, 文:({},{}), 武:({},{}), {}, {}",
+            self.标识,
+            self.序号,
+            self.级别,
+            self.文().时间戳,
+            crate::utils::format_f64_g(self.文().分型特征值),
+            self.武().时间戳,
+            crate::utils::format_f64_g(self.武().分型特征值),
+            第三买卖线_str,
+            本级_第三买卖线_str,
+        )
+    }
+
+    /// 校验中枢合法性
+    pub fn 校验合法性(&self, 虚线序列: &[Rc<虚线>], _中枢序列: &[Rc<中枢>]) -> bool {
+        // 1. 检查基础序列中的元素是否仍在虚线序列中
+        for 元素 in &self.基础序列 {
+            if !虚线序列.iter().any(|x| Rc::as_ptr(x) == Rc::as_ptr(元素)) {
+                return false;
+            }
+        }
+        // 2. 检查前三根重叠是否有效
+        if self.基础序列.len() >= 3 {
+            let 高 = self.高();
+            let 低 = self.低();
+            if 高 <= 低 {
+                return false;
+            }
+        }
+        true
+    }
+
+    // ---- 关联函数 ----
+
+    /// 基础检查 — 三根虚线是否能形成中枢
+    pub fn 基础检查(左: &虚线, 中: &虚线, 右: &虚线) -> bool {
+        if !左.之后是(中) || !中.之后是(右) {
+            return false;
+        }
+        let 高 = [左.高(), 中.高(), 右.高()]
+            .iter()
+            .copied()
+            .min_by(|a, b| a.partial_cmp(b).unwrap_or(std::cmp::Ordering::Equal))
+            .unwrap_or(0.0);
+        let 低 = [左.低(), 中.低(), 右.低()]
+            .iter()
+            .copied()
+            .max_by(|a, b| a.partial_cmp(b).unwrap_or(std::cmp::Ordering::Equal))
+            .unwrap_or(0.0);
+        高 > 低
+    }
+
+    /// 创建中枢
+    pub fn 创建(左: Rc<虚线>, 中: Rc<虚线>, 右: Rc<虚线>, 级别: i64, 标识: &str) -> Self {
+        Self::new(0, format!("{}中枢<{}>", 标识, 中.标识), 级别, vec![左, 中, 右])
+    }
+
+    /// 从序列中获取中枢
+    pub fn 从序列中获取中枢(
+        虚线序列: &[Rc<虚线>],
+        起始方向: 相对方向,
+        标识: &str,
+    ) -> Option<Rc<中枢>> {
+        for i in 2..虚线序列.len() {
+            let 左 = &虚线序列[i - 2];
+            let 中 = &虚线序列[i - 1];
+            let 右 = &虚线序列[i];
+            if Self::基础检查(左, 中, 右) && 左.方向() == 起始方向 {
+                let 中枢 = Self::创建(Rc::clone(左), Rc::clone(中), Rc::clone(右), 0, 标识);
+                return Some(Rc::new(中枢));
+            }
+        }
+        None
+    }
+
+    /// 向中枢序列尾部添加
+    pub fn 向中枢序列尾部添加(中枢序列: &mut Vec<Rc<中枢>>, 待添加中枢: Rc<中枢>) {
+        // Dedup
+        if let Some(前一个) = 中枢序列.last() {
+            if 前一个.高() == 待添加中枢.高() && 前一个.低() == 待添加中枢.低() {
+                return;
+            }
+        }
+        // Set序号: Python — if中枢序列: 待添加中枢.序号 = 中枢序列[-1].序号 + 1 else: stays 0
+        if let Some(前一个) = 中枢序列.last() {
+            let 新序号 = 前一个.序号 + 1;
+            // Clone to mutate since Rc is immutable
+            let mut cloned = (*待添加中枢).clone();
+            cloned.序号 = 新序号;
+            中枢序列.push(Rc::new(cloned));
+        } else {
+            中枢序列.push(待添加中枢);
+        }
+    }
+
+    /// 从中枢序列尾部弹出
+    pub fn 从中枢序列尾部弹出(中枢序列: &mut Vec<Rc<中枢>>, 待弹出: &Rc<中枢>) -> Option<Rc<中枢>> {
+        if 中枢序列.last().map(|x| Rc::as_ptr(x)) == Some(Rc::as_ptr(待弹出)) {
+            中枢序列.pop()
+        } else {
+            None
+        }
+    }
+
+    /// 中枢分析 — 从虚线序列生成中枢序列（增量算法）
+    ///
+    /// 每收到新的虚线序列数据后调用，更新中枢序列
+    pub fn 分析(
+        虚线序列: &[Rc<虚线>],
+        中枢序列: &mut Vec<Rc<中枢>>,
+        跳过首部: bool,
+        标识: &str,
+        层级: i64,
+    ) {
+        if 虚线序列.len() < 3 {
+            return;
+        }
+
+        // 初始化第一个中枢
+        if 中枢序列.is_empty() {
+            for i in 1..虚线序列.len() - 1 {
+                let 左 = &虚线序列[i - 1];
+                let 中 = &虚线序列[i];
+                let 右 = &虚线序列[i + 1];
+
+                if Self::基础检查(左, 中, 右) {
+                    // Python: 序号 = 虚线序列.index(左)
+                    let 序号 = 虚线序列.iter().position(|x| Rc::as_ptr(x) == Rc::as_ptr(左)).unwrap_or(i - 1);
+                    if 跳过首部 && (左.序号 == 0 || 序号 == 0) {
+                        continue;
+                    }
+                    if 序号 >= 2 {
+                        let 前 = &虚线序列[序号 - 2];
+                        let 同向相对关系 = crate::types::相对方向::分析(前.高(), 前.低(), 左.高(), 左.低());
+                        if 同向相对关系.是否向上() && 左.方向().是否向上() {
+                            continue;
+                        }
+                        if 同向相对关系.是否向下() && 左.方向().是否向下() {
+                            continue;
+                        }
+                    }
+                    let 新中枢 = Rc::new(Self::创建(
+                        Rc::clone(左),
+                        Rc::clone(中),
+                        Rc::clone(右),
+                        中.级别,
+                        标识,
+                    ));
+                    Self::向中枢序列尾部添加(中枢序列, 新中枢);
+                    // Python: return 中枢递归分析(虚线序列, 中枢序列, ...)
+                    Self::分析(虚线序列, 中枢序列, 跳过首部, 标识, 层级);
+                    return;
+                }
+            }
+            return;
+        }
+
+        // 增量更新
+        let 当前中枢_idx = 中枢序列.len() - 1;
+        let 当前中枢 = Rc::clone(&中枢序列[当前中枢_idx]);
+
+        if !当前中枢.校验合法性(虚线序列, 中枢序列) {
+            Self::从中枢序列尾部弹出(中枢序列, &当前中枢);
+            Self::分析(虚线序列, 中枢序列, 跳过首部, 标识, 层级);
+            return;
+        }
+
+        // 找到当前中枢最后一个元素在虚线序列中的位置
+        let 最后元素 = &当前中枢.基础序列[当前中枢.基础序列.len() - 1];
+        let 起始索引 = match 虚线序列
+            .iter()
+            .position(|x| Rc::as_ptr(x) == Rc::as_ptr(最后元素))
+        {
+            Some(idx) => idx + 1,
+            None => return,
+        };
+
+        let 中枢高 = 当前中枢.高();
+        let 中枢低 = 当前中枢.低();
+        let mut 候选序列: Vec<Rc<虚线>> = Vec::new();
+
+        let mut 新当前中枢 = (*当前中枢).clone();
+
+        for i in 起始索引..虚线序列.len() {
+            let 当前虚线 = Rc::clone(&虚线序列[i]);
+
+            // 检查是否超出中枢范围（缺口）
+            if crate::types::相对方向::分析(中枢高, 中枢低, 当前虚线.高(), 当前虚线.低()).是否缺口() {
+                候选序列.push(当前虚线.clone());
+
+                // Python: if 当前中枢.基础序列[-1].之后是(当前虚线):
+                if 新当前中枢.基础序列.last().unwrap().之后是(&当前虚线) {
+                    新当前中枢.设置第三买卖线(当前虚线.clone());
+                }
+            } else {
+                if 候选序列.is_empty() {
+                    // 仍在范围内：延伸中枢
+                    新当前中枢.添加虚线(当前虚线);
+                } else {
+                    候选序列.push(当前虚线);
+                }
+            }
+
+            // 候选序列积满3个：尝试创建新中枢
+            while 候选序列.len() >= 3 {
+                let 起始方向 = 新当前中枢.基础序列.last().unwrap().方向().翻转();
+                match Self::从序列中获取中枢(&候选序列, 起始方向, 标识) {
+                    Some(新中枢) => {
+                        中枢序列[当前中枢_idx] = Rc::new(新当前中枢.clone());
+                        Self::向中枢序列尾部添加(中枢序列, 新中枢);
+                        return;
+                    }
+                    None => {
+                        候选序列.remove(0); // 滑动窗口
+                    }
+                }
+            }
+        }
+
+        // 更新当前中枢
+        中枢序列[当前中枢_idx] = Rc::new(新当前中枢);
+    }
+}
+
+impl std::fmt::Display for 中枢 {
+    fn fmt(&self, f: &mut std::fmt::Formatter<'_>) -> std::fmt::Result {
+        let 序列_str = self
+            .基础序列
+            .iter()
+            .map(|d| format!("{}", d))
+            .collect::<Vec<_>>()
+            .join(", ");
+        write!(
+            f,
+            "{}({}, {}, 元素数量: {}, [{}], {} ===>>> {})",
+            self.标识,
+            crate::utils::format_f64_g(self.高()),
+            crate::utils::format_f64_g(self.低()),
+            self.基础序列.len(),
+            序列_str,
+            self.文(),
+            self.武(),
+        )
+    }
+}
diff --git a/chanlun/src/algorithm/mod.rs b/chanlun/src/algorithm/mod.rs
new file mode 100644
index 0000000..ce0b3de
--- /dev/null
+++ b/chanlun/src/algorithm/mod.rs
@@ -0,0 +1,4 @@
+pub mod bi;
+pub mod divergence;
+pub mod hub;
+pub mod segment;
diff --git a/chanlun/src/algorithm/segment.rs b/chanlun/src/algorithm/segment.rs
new file mode 100644
index 0000000..97d8a56
--- /dev/null
+++ b/chanlun/src/algorithm/segment.rs
@@ -0,0 +1,1726 @@
+use crate::algorithm::bi::笔;
+use crate::algorithm::hub::中枢;
+use crate::business::observer::观察者;
+use crate::config::缠论配置;
+use crate::kline::bar::K线;
+use crate::structure::dash_line::虚线;
+use crate::structure::fractal_obj::分型;
+use crate::structure::segment_feat::线段特征;
+use crate::types::{分型结构, 相对方向, 缺口};
+use std::rc::Rc;
+
+/// 线段 — 从笔生成线段的算法集合（静态方法命名空间）
+pub struct 线段;
+
+impl 线段 {
+    // ================================================================
+    // 基础操作
+    // ================================================================
+
+    /// 获取Rc<虚线>的可变引用（clone-on-write）
+    fn 取段可变(段_rc: &mut Rc<虚线>) -> &mut 虚线 {
+        if Rc::strong_count(段_rc) > 1 {
+            let 克隆 = (**段_rc).clone();
+            *段_rc = Rc::new(克隆);
+        }
+        Rc::get_mut(段_rc).unwrap()
+    }
+
+    /// 向线段的基础序列中添加一笔
+    pub fn 添加虚线(段_rc: &mut Rc<虚线>, 筆: Rc<虚线>) {
+        let 段 = Self::取段可变(段_rc);
+        if !段.基础序列.is_empty() {
+            if !分型::判断分型(&段.基础序列.last().unwrap().武, &筆.文, "中") {
+                eprintln!(
+                    "线段.添加虚线 不连续 {:?} {:?}",
+                   段.基础序列.last().unwrap(), 筆
+                );
+                return;
+            }
+            if 段.基础序列.last().unwrap().标识 != 筆.标识 {
+                eprintln!(
+                    "线段.添加虚线 标识不符 {} {}",
+                    段.基础序列.last().unwrap().标识, 筆.标识
+                );
+                return;
+            }
+        }
+       段.基础序列.push(筆);
+    }
+
+    /// 更新线段的终点分型
+    pub fn 武斗(段_rc: &mut Rc<虚线>, 武: &Rc<分型>, 行号: u32) {
+        let 段 = Self::取段可变(段_rc);
+        if Rc::as_ptr(&段.武) == Rc::as_ptr(武) {
+            return;
+        }
+        if 段.武.分型特征值 == 武.分型特征值 && 段.武.时间戳 != 武.时间戳 {
+            eprintln!(
+                "线段.武斗[{}], 发现特征值相等但时间戳不同 {:?} {:?}",
+                行号, 段.武, 武
+            );
+        }
+        if 段.文.结构 == 武.结构 {
+            panic!("文武结构相同 {} {:?} {:?}", 行号, 段.文, 武);
+        }
+        if 段.方向() == 相对方向::向上 {
+            if 武.分型特征值 < 段.文.分型特征值 {
+                panic!(
+                    "向上线段, 结束点小于起点 {} {:?} {:?}",
+                    段.标识, 段.文, 武
+                );
+            }
+        } else {
+            if 武.分型特征值 > 段.文.分型特征值 {
+                panic!(
+                    "向下线段, 结束点大于起点 {} {:?} {:?}",
+                    段.标识, 段.文, 武
+                );
+            }
+        }
+       段.武 = Rc::clone(武);
+    }
+
+    /// 武终 — 线段终结时设置终点
+    pub fn 武终(段_rc: &mut Rc<虚线>, 行号: u32) {
+        let 武 = {
+            let 段 = Self::取段可变(段_rc);
+            if 段.模式 != "文武" {
+                Some(Rc::clone(&段.基础序列.last().unwrap().武))
+            } else {
+                None
+            }
+        };
+        if let Some(武) = 武 {
+            Self::武斗(段_rc, &武, 行号);
+        }
+    }
+
+    /// 验证序列 — 截断无效尾部
+    pub fn 验证序列(段_rc: &mut Rc<虚线>, 序列: &[Rc<虚线>]) {
+        let 段 = Self::取段可变(段_rc);
+        let mut 基础序列: Vec<Rc<虚线>> = Vec::new();
+        for 元素 in &段.基础序列 {
+            if !序列.iter().any(|x| Rc::as_ptr(x) == Rc::as_ptr(元素)) {
+                break;
+            }
+            if !基础序列.is_empty() {
+                if !基础序列.last().unwrap().之后是(元素) {
+                    eprintln!("线段._验证序列 数据不连续");
+                    break;
+                }
+            }
+            基础序列.push(Rc::clone(元素));
+        }
+        if 基础序列.len() % 2 == 0 {
+            基础序列.pop();
+        }
+       段.基础序列 = 基础序列;
+    }
+
+    /// 序列重置 — 截取到序列中的有效部分
+    pub fn 序列重置(段_rc: &mut Rc<虚线>, 序列: &[Rc<虚线>]) {
+        let 段 = Self::取段可变(段_rc);
+        let mut 基础序列: Vec<Rc<虚线>> = Vec::new();
+        for 元素 in &段.基础序列 {
+            if !序列.iter().any(|x| Rc::as_ptr(x) == Rc::as_ptr(元素)) {
+                break;
+            }
+            if !基础序列.is_empty() {
+                if !基础序列.last().unwrap().之后是(元素) {
+                    break;
+                }
+            }
+            基础序列.push(Rc::clone(元素));
+        }
+       段.基础序列 = 基础序列;
+        if 段.特征序列.len() > 2 {
+            段.特征序列[2] = None;
+        }
+    }
+
+    // ================================================================
+    // 基础判断
+    // ================================================================
+
+    /// 基础判断 — 连续三笔且重叠才能构成线段
+    pub fn 基础判断(左: &虚线, 中: &虚线, 右: &虚线, 关系序列: &[相对方向]) -> bool {
+        if !左.之后是(中) {
+            return false;
+        }
+        if !中.之后是(右) {
+            return false;
+        }
+
+        if !相对方向::分析(左.高(), 左.低(), 中.高(), 中.低()).是否包含() {
+            return false;
+        }
+        if !相对方向::分析(中.高(), 中.低(), 右.高(), 右.低()).是否包含() {
+            return false;
+        }
+
+        let 关系 = 相对方向::分析(左.高(), 左.低(), 右.高(), 右.低());
+        if !关系序列.contains(&关系) {
+            return false;
+        }
+
+        if 左.方向() == 相对方向::向下 && !关系.是否向下() {
+            return false;
+        }
+        if 左.方向() == 相对方向::向上 && !关系.是否向上() {
+            return false;
+        }
+        true
+    }
+
+    // ================================================================
+    // 四象 / 缺口 / 特征序列
+    // ================================================================
+
+    /// 四象 — 线段的四种状态分类
+    ///
+    /// 老阳: 向下线段第一二特征序列有缺口, 后一向上线段
+    /// 老阴: 向上线段第一二特征序列有缺口, 后一向下线段
+    /// 小阳: 向上线段
+    /// 少阴: 向下线段
+    pub fn 四象(段: &虚线) -> String {
+        if 段.前一缺口.is_some() {
+            if 段.方向() == 相对方向::向上 {
+                "老阳".into()
+            } else {
+                "老阴".into()
+            }
+        } else if 段.方向() == 相对方向::向上 {
+            "小阳".into()
+        } else {
+            "少阴".into()
+        }
+    }
+
+    /// 获取缺口 — 从特征序列第一二元素之间检测缺口
+    pub fn 获取缺口(段: &虚线) -> Option<缺口> {
+        if 段.模式 != "文武" {
+            return None;
+        }
+        if 段.特征序列.len() < 2 {
+            return None;
+        }
+        let 左 = 段.特征序列[0].as_ref()?;
+        let 中 = 段.特征序列[1].as_ref()?;
+        let 相对关系 = 相对方向::分析(左.高(), 左.低(), 中.高(), 中.低());
+        if 相对关系.是否缺口() {
+            let 高 = 左.文().分型特征值.max(中.文().分型特征值);
+            let 低 = 左.文().分型特征值.min(中.文().分型特征值);
+            Some(缺口 { 高, 低 })
+        } else {
+            None
+        }
+    }
+
+    /// 特征分型终结 — 检查特征序列是否形成正常分型终结
+    pub fn 特征分型终结(段: &虚线) -> bool {
+        let 特征序列 = 线段特征::静态分析(&段.基础序列, 段.方向(), &Self::四象(段), false);
+        if 特征序列.len() >= 3 {
+            let idx = 特征序列.len();
+            if let Some(结构) = 分型结构::分析(
+                &*特征序列[idx - 3],
+                &*特征序列[idx - 2],
+                &*特征序列[idx - 1],
+                true,
+                true,
+            ) {
+                if 段.方向() == 相对方向::向上 {
+                    return 结构 == 分型结构::顶;
+                } else {
+                    return 结构 == 分型结构::底;
+                }
+            }
+        }
+        false
+    }
+
+    /// 特征序列状态 — 返回三个特征序列元素是否为 Some
+    pub fn 特征序列状态(段: &虚线) -> (bool, bool, bool) {
+        let get = |i: usize| {
+            段.特征序列
+                .get(i)
+                .map(|x| x.is_some())
+                .unwrap_or(false)
+        };
+        (get(0), get(1), get(2))
+    }
+
+    /// 设置特征序列
+    pub fn 设置特征序列(段_rc: &mut Rc<虚线>, 序列: Vec<Option<Rc<线段特征>>>, 行号: u32) {
+        let 段 = Self::取段可变(段_rc);
+        if 段.模式 != "文武" {
+            return;
+        }
+
+        for 特征 in &序列 {
+            if let Some(ref f) = 特征 {
+                if f.方向() == 段.方向() {
+                    panic!("特征序列方向不匹配[{}]", 行号);
+                }
+            }
+        }
+
+        let 左 = 序列[0].clone();
+        let 中 = 序列[1].clone();
+        let 右 = 序列[2].clone();
+       段.特征序列 = vec![左, 中, 右];
+
+        if let Some(ref 右特征) = 段.特征序列[2] {
+            let mut 基础序列: Vec<Rc<虚线>> = Vec::new();
+            let 右尾 = 右特征.元素.last().expect("特征序列元素不应为空");
+            if !段.基础序列.iter().any(|x| Rc::as_ptr(x) == Rc::as_ptr(右尾)) {
+                panic!("右特征最后一个元素不在基础序列中");
+            }
+            for 元素 in &段.基础序列 {
+                基础序列.push(Rc::clone(元素));
+                if Rc::as_ptr(元素) == Rc::as_ptr(右尾) {
+                    break;
+                }
+            }
+
+            if 基础序列.len() >= 6 && 基础序列.len() % 2 == 0 {
+               段.基础序列 = 基础序列;
+            } else {
+                panic!("设置特征序列: 基础序列长度不足或非偶数");
+            }
+        }
+    }
+
+    /// 刷新特征序列
+    pub fn 刷新特征序列(段_rc: &mut Rc<虚线>, 配置: &缠论配置) {
+        // Work on a clone since we need to read and write
+        let mut 新段 = (**段_rc).clone();
+        if 新段.模式 != "文武" {
+            return;
+        }
+        let mut 基础序列 = 新段.基础序列.clone();
+        if let Some(ref 前结束) = 新段.前一结束位置 {
+            if let Some(idx) = 基础序列
+                .iter()
+                .position(|x| Rc::as_ptr(x) == Rc::as_ptr(前结束))
+            {
+                if idx > 0 {
+                    基础序列 = 基础序列[idx - 1..].to_vec();
+                }
+            }
+        }
+
+        let 四象 = Self::四象(&新段);
+        let 特征序列 = 线段特征::静态分析(
+            &基础序列,
+            新段.方向(),
+            &四象,
+            配置.线段_特征序列忽视老阴老阳,
+        );
+
+        if 特征序列.len() >= 3 {
+            let 分型序列 = 线段特征::获取分型序列(&特征序列);
+            if !分型序列.is_empty() {
+                let 最后分型 = &分型序列[分型序列.len() - 1];
+                if (新段.方向() == 相对方向::向上
+                    && 最后分型.结构 == 分型结构::顶)
+                    || (新段.方向() == 相对方向::向下
+                        && 最后分型.结构 == 分型结构::底)
+                {
+                    新段.特征序列 = vec![
+                        Some(Rc::clone(&最后分型.左)),
+                        Some(Rc::clone(&最后分型.中)),
+                        Some(Rc::clone(&最后分型.右)),
+                    ];
+                } else {
+                    新段.特征序列 = vec![
+                        Some(Rc::clone(&特征序列[特征序列.len() - 2])),
+                        Some(Rc::clone(&特征序列[特征序列.len() - 1])),
+                        None,
+                    ];
+                }
+            } else {
+                新段.特征序列 = vec![
+                    Some(Rc::clone(&特征序列[特征序列.len() - 2])),
+                    Some(Rc::clone(&特征序列[特征序列.len() - 1])),
+                    None,
+                ];
+            }
+        } else {
+            let mut 填充: Vec<Option<Rc<线段特征>>> =
+                特征序列.into_iter().map(Some).collect();
+            填充.resize(3, None);
+            新段.特征序列 = 填充;
+        }
+
+        *段_rc = Rc::new(新段);
+    }
+
+    /// 查找贯穿伤 — 基础序列中穿透文分型特征值的笔
+    pub fn 查找贯穿伤(段: &虚线) -> Option<Rc<虚线>> {
+        for 贯穿伤 in 段.基础序列.iter().skip(3) {
+            if 段.方向().是否向上() {
+                if 贯穿伤.武.分型特征值 < 段.文.分型特征值 {
+                    return Some(Rc::clone(贯穿伤));
+                }
+            } else {
+                if 贯穿伤.武.分型特征值 > 段.文.分型特征值 {
+                    return Some(Rc::clone(贯穿伤));
+                }
+            }
+        }
+        None
+    }
+
+    // ================================================================
+    // 分割序列
+    // ================================================================
+
+    /// 分割序列 — 将线段的基础序列分为前、后、第三买卖线、贯穿伤
+    pub fn 分割序列(
+        段: &虚线,
+        所属中枢: Option<&Rc<中枢>>,
+    ) -> (Vec<Rc<虚线>>, Vec<Rc<虚线>>, Vec<Rc<虚线>>, Option<Rc<虚线>>) {
+        if 段.模式 != "文武" {
+            return (段.基础序列.clone(), Vec::new(), Vec::new(), None);
+        }
+
+        let mut 前: Vec<Rc<虚线>> = Vec::new();
+        let mut 后: Vec<Rc<虚线>> = Vec::new();
+        let mut 第三买卖线: Vec<Rc<虚线>> = Vec::new();
+        let mut 贯穿伤: Option<Rc<虚线>> = None;
+
+        for 筆 in &段.基础序列 {
+            if 前.is_empty() {
+                前.push(Rc::clone(筆));
+                continue;
+            }
+            if Rc::as_ptr(&前.last().unwrap().武) != Rc::as_ptr(&段.武) && 后.is_empty() {
+                前.push(Rc::clone(筆));
+            }
+
+            if !后.is_empty() {
+                后.push(Rc::clone(筆));
+            }
+            if Rc::as_ptr(&筆.文) == Rc::as_ptr(&段.武) {
+                后.push(Rc::clone(筆));
+            }
+        }
+
+        let mut 状态 = None;
+
+        if let Some(中枢) = 所属中枢 {
+            let 尾部 = if let Some(ref 后笔) = 后.last() {
+                Rc::clone(&后笔.武)
+            } else {
+                Rc::clone(&段.武)
+            };
+
+            if 中枢.高() >= 尾部.分型特征值 && 尾部.分型特征值 >= 中枢.低() {
+                状态 = Some("中枢之中");
+            } else if 中枢.高() < 尾部.分型特征值 {
+                状态 = Some("中枢之上");
+            } else if 中枢.低() > 尾部.分型特征值 {
+                状态 = Some("中枢之下");
+            }
+        }
+
+        if 状态 == Some("中枢之上") {
+            for 筆 in 段.基础序列.iter().rev() {
+                if 筆.方向() == 相对方向::向下 {
+                    let 关系 = 相对方向::分析(
+                        所属中枢.unwrap().高(),
+                        所属中枢.unwrap().低(),
+                        筆.高(),
+                        筆.低(),
+                    );
+                    if 关系 == 相对方向::向上缺口 {
+                        第三买卖线.push(Rc::clone(筆));
+                    } else {
+                        break;
+                    }
+                } else {
+                    break;
+                }
+            }
+        }
+
+        if 状态 == Some("中枢之下") {
+            for 筆 in 段.基础序列.iter().rev() {
+                if 筆.方向() == 相对方向::向上 {
+                    let 关系 = 相对方向::分析(
+                        所属中枢.unwrap().高(),
+                        所属中枢.unwrap().低(),
+                        筆.高(),
+                        筆.低(),
+                    );
+                    if 关系 == 相对方向::向下缺口 {
+                        第三买卖线.push(Rc::clone(筆));
+                    } else {
+                        break;
+                    }
+                } else {
+                    break;
+                }
+            }
+        }
+
+        if !第三买卖线.is_empty() {
+            第三买卖线.reverse();
+        }
+
+        if !后.is_empty() {
+            if 段.方向().是否向上() {
+                if 后[0].武.分型特征值 < 段.文.分型特征值 {
+                    贯穿伤 = Some(Rc::clone(&后[0]));
+                }
+            } else {
+                if 后[0].武.分型特征值 > 段.文.分型特征值 {
+                    贯穿伤 = Some(Rc::clone(&后[0]));
+                }
+            }
+        }
+
+        (前, 后, 第三买卖线, 贯穿伤)
+    }
+
+    /// 刷新 — 完整刷新线段的特征序列和内部中枢
+    pub fn 刷新(段_rc: &mut Rc<虚线>, 配置: &缠论配置) {
+        let 段 = Self::取段可变(段_rc);
+        if 段.模式 != "文武" {
+            return;
+        }
+        if 段.基础序列.is_empty() {
+            eprintln!("    线段.刷新 基础序列为空");
+            return;
+        }
+
+        Self::刷新特征序列(段_rc, 配置);
+
+        // After 刷新特征序列, work with the updated segment
+        let (武斗_武文, 特征后一笔_opt) = {
+            let 段2 = Self::取段可变(段_rc);
+            let 有效特征序列: Vec<&Rc<线段特征>> = 段2.特征序列.iter().filter_map(|x| x.as_ref()).collect();
+
+            if 有效特征序列.len() == 3 {
+                (Some(Rc::clone(&有效特征序列[1].文())), None)
+            } else if !有效特征序列.is_empty() {
+                let 最近特征 = 有效特征序列[有效特征序列.len() - 1];
+
+                let 特征后一笔 = if 最近特征.元素.last().map(|x| {
+                   段2.基础序列
+                        .iter()
+                        .any(|b| Rc::as_ptr(b) == Rc::as_ptr(x))
+                }) == Some(true)
+                {
+                    Some(Rc::clone(最近特征.元素.last().unwrap()))
+                } else if let Some(b) =
+                    笔::以武会友(&段2.基础序列, &最近特征.元素.last().unwrap().武)
+                {
+                    Some(b)
+                } else {
+                    None
+                };
+
+                if 特征后一笔.is_none() {
+                    eprintln!(
+                        "    线段.刷新 特征后一笔 = None, {:?}, 有效特征: {}",
+                        段2,
+                        有效特征序列.len()
+                    );
+                }
+                (None, 特征后一笔)
+            } else {
+                (None, None)
+            }
+        };
+
+        if let Some(武文) = 武斗_武文 {
+            Self::武斗(段_rc, &武文, 0);
+        } else if let Some(特征后一笔) = 特征后一笔_opt {
+
+            let 武斗候选 = {
+                let 段2 = Self::取段可变(段_rc);
+                if let Some(序号) = 段2
+                    .基础序列
+                    .iter()
+                    .position(|x| Rc::as_ptr(x) == Rc::as_ptr(&特征后一笔))
+                {
+                    if 序号 < 段2.基础序列.len() - 1 {
+                        let 下一笔 = Rc::clone(&段2.基础序列[序号 + 1]);
+                        if (段2.方向() == 相对方向::向上 && 段2.高() <= 下一笔.高())
+                            || (段2.方向() == 相对方向::向下 && 段2.低() >= 下一笔.低())
+                        {
+                            Some(Rc::clone(&下一笔.武))
+                        } else {
+                            None
+                        }
+                    } else {
+                        None
+                    }
+                } else {
+                    None
+                }
+            };
+            if let Some(武) = 武斗候选 {
+                Self::武斗(段_rc, &武, 0);
+            }
+        }
+
+        let 段3 = Self::取段可变(段_rc);
+        let _ = Self::获取内部中枢序列_内部(段3, 配置);
+    }
+
+    /// 获取内部中枢序列 — 内部实现
+    fn 获取内部中枢序列_内部(段: &mut 虚线, _配置: &缠论配置) -> (Vec<Rc<中枢>>, Vec<Rc<中枢>>, Vec<Rc<中枢>>) {
+        if 段.模式 != "文武" {
+            中枢::分析(&段.基础序列, &mut 段.合_中枢序列, true, &format!("{}_{}_合_", 段.标识, 段.序号), 0);
+            return (Vec::new(), Vec::new(), 段.合_中枢序列.clone());
+        }
+
+        // Clone base sequence to avoid borrow issues
+        let 基础序列 = 段.基础序列.clone();
+        let _文 = Rc::clone(&段.文);
+        let 武 = Rc::clone(&段.武);
+
+        // Reconstruct 前/后 from base sequence
+        let mut 前: Vec<Rc<虚线>> = Vec::new();
+        let mut 后: Vec<Rc<虚线>> = Vec::new();
+
+        for 筆 in &基础序列 {
+            if 前.is_empty() {
+                前.push(Rc::clone(筆));
+                continue;
+            }
+            if Rc::as_ptr(&前.last().unwrap().武) != Rc::as_ptr(&武) && 后.is_empty() {
+                前.push(Rc::clone(筆));
+            }
+            if !后.is_empty() {
+                后.push(Rc::clone(筆));
+            }
+            if Rc::as_ptr(&筆.文) == Rc::as_ptr(&武) {
+                后.push(Rc::clone(筆));
+            }
+        }
+
+        中枢::分析(&前, &mut 段.实_中枢序列, true, &format!("{}_{}_实_", 段.标识, 段.序号), 0);
+        中枢::分析(&后, &mut 段.虚_中枢序列, true, &format!("{}_{}_虚_", 段.标识, 段.序号), 0);
+        中枢::分析(&基础序列, &mut 段.合_中枢序列, true, &format!("{}_{}_合_", 段.标识, 段.序号), 0);
+
+        (段.虚_中枢序列.clone(), 段.实_中枢序列.clone(), 段.合_中枢序列.clone())
+    }
+
+    /// 获取内部中枢序列
+    pub fn 获取内部中枢序列(段_rc: &mut Rc<虚线>, 配置: &缠论配置) -> (Vec<Rc<中枢>>, Vec<Rc<中枢>>, Vec<Rc<中枢>>) {
+        let 段 = Self::取段可变(段_rc);
+        Self::获取内部中枢序列_内部(段, 配置)
+    }
+
+    // ================================================================
+    // 线段序列管理
+    // ================================================================
+
+    /// _添加线段 — 向线段序列尾部添加线段（内部方法）
+    pub fn _添加线段(
+        线段序列: &mut Vec<Rc<虚线>>,
+        待添加线段_rc: &mut Rc<虚线>,
+        _配置: &缠论配置,
+        行号: String,
+    ) {
+        let 待添加线段 = Self::取段可变(待添加线段_rc);
+
+        if let Some(前一个) = 线段序列.last() {
+            if !前一个.之后是(待添加线段) {
+                panic!(
+                    "线段.向序列中添加 不连续[{}] {:?} {:?}",
+                    行号, 前一个.武, 待添加线段.文
+                );
+            }
+        }
+
+        待添加线段.模式 = "文武".into();
+
+        if 线段序列.is_empty() {
+            let 新段 = Rc::new(待添加线段.clone());
+            线段序列.push(新段);
+            return;
+        }
+
+        let 之前线段 = 线段序列.last().unwrap();
+
+        // Check 之前线段.特征序列[2] is valid
+        if 之前线段.特征序列.len() >= 3 && 之前线段.特征序列[2].is_none() && !之前线段.短路修正 {
+            // The Python code asserts here; we warn
+            eprintln!(
+                "线段._向序列中添加[{}], 之前线段.右 = None {:?}",
+                行号, 之前线段
+            );
+        }
+
+        if !待添加线段
+            .基础序列
+            .iter()
+            .any(|x| Rc::as_ptr(x) == Rc::as_ptr(之前线段.基础序列.last().unwrap()))
+            && !之前线段.短路修正
+        {
+            panic!(
+                "线段._向序列中添加[{}], 之前线段[-1] not in 待添加虚线! {:?}",
+                行号, 之前线段
+            );
+        }
+
+        待添加线段.序号 = 之前线段.序号 + 1;
+        待添加线段.前一缺口 = Self::获取缺口(之前线段);
+        待添加线段.前一结束位置 = Some(Rc::clone(之前线段.基础序列.last().unwrap()));
+
+        if ["老阴", "老阳"].contains(&Self::四象(之前线段).as_str()) {
+            待添加线段.前一缺口 = None;
+        }
+
+        let 新段 = Rc::new(待添加线段.clone());
+        线段序列.push(新段);
+    }
+
+    /// _弹出线段 — 从线段序列尾部弹出线段（内部方法）
+    pub fn _弹出线段(
+        线段序列: &mut Vec<Rc<虚线>>,
+        待弹出线段: &Rc<虚线>,
+        _配置: &缠论配置,
+        行号: String,
+    ) -> Option<Rc<虚线>> {
+        if 线段序列.is_empty() {
+            return None;
+        }
+
+        if Rc::as_ptr(线段序列.last().unwrap()) != Rc::as_ptr(待弹出线段) {
+            panic!(
+                "线段._从序列中删除 弹出数据不在列表中 {:?}",
+                待弹出线段
+            );
+        }
+
+        if 待弹出线段.特征序列.len() >= 3 {
+            let 左 = &待弹出线段.特征序列[0];
+            let 中 = &待弹出线段.特征序列[1];
+            let 右 = &待弹出线段.特征序列[2];
+            if let (Some(l), Some(m), Some(r)) = (左, 中, 右) {
+                if let Some(结构) = 分型结构::分析(&**l, &**m, &**r, true, true) {
+                    if matches!(结构, 分型结构::顶 | 分型结构::底)
+                        && !相对方向::分析(l.高(), l.低(), m.高(), m.低()).是否缺口()
+                    {
+                        eprintln!(
+                            "[警告<{}>]: 线段._从序列中删除 发现分型完毕, 且特征序列无缺口 {:?}",
+                            行号, 待弹出线段
+                        );
+                    }
+                }
+            }
+        }
+
+        let 弹出 = 线段序列.pop().unwrap();
+
+        // Mark popped segment as invalid
+        // Since it's behind Rc, we mark it by replacing its clone in caller context
+        // For now, just pop it from the sequence
+
+        Some(弹出)
+    }
+
+    // ================================================================
+    // 四种修正机制
+    // ================================================================
+
+    /// _缺口突破 — 老阳/老阴缺口突破修正
+    pub fn _缺口突破(
+        线段序列: &mut Vec<Rc<虚线>>,
+        配置: &缠论配置,
+        层级: i64,
+    ) -> bool {
+        if 线段序列.is_empty() {
+            return false;
+        }
+
+        let 当前线段 = Rc::clone(线段序列.last().unwrap());
+        if 当前线段.基础序列.is_empty() {
+            return false;
+        }
+        let 当前虚线 = Rc::clone(&当前线段.基础序列[当前线段.基础序列.len() - 1]);
+        let 四象 = Self::四象(&当前线段);
+        let 同向 = 当前虚线.方向() == 当前线段.方向();
+
+        // 条件1：不能同向
+        if 同向 {
+            return false;
+        }
+
+        // 条件2：四象必须是老阳或老阴
+        if 四象 != "老阳" && 四象 != "老阴" {
+            return false;
+        }
+
+        // 条件3：当前线段特征序列[2]必须为None
+        if 当前线段.特征序列.len() >= 3 && 当前线段.特征序列[2].is_some() {
+            return false;
+        }
+
+        // 条件4：具体突破方向判断
+        let 突破 = (四象 == "老阳" && 当前虚线.低() < 当前线段.低())
+            || (四象 == "老阴" && 当前虚线.高() > 当前线段.高());
+        if !突破 {
+            return false;
+        }
+
+        // 执行修正
+        let 序列 = 当前线段.基础序列.clone();
+        Self::_弹出线段(
+            线段序列,
+            &Rc::clone(线段序列.last().unwrap()),
+            配置,
+            format!("{}, {}", 0, 层级),
+        );
+
+        if 线段序列.is_empty() {
+            return true;
+        }
+
+        let mut 当前线段_克隆 = (**线段序列.last().unwrap()).clone();
+        if 当前线段_克隆.特征序列.len() < 3 || 当前线段_克隆.特征序列[2].is_none() {
+            // Shouldn't happen after correction
+            return true;
+        }
+
+        let (前, _, _, _) = Self::分割序列(&当前线段_克隆, None);
+        let mut 当前线段基础序列 = 前;
+        当前线段基础序列.extend(序列);
+
+        当前线段_克隆.基础序列 = 当前线段基础序列;
+        let idx = 线段序列.len() - 1;
+        线段序列[idx] = Rc::new(当前线段_克隆);
+
+        Self::刷新(&mut 线段序列[idx], 配置);
+        true
+    }
+
+    /// _非缺口下穿刺 — 贯穿伤修复
+    pub fn _非缺口下穿刺(
+        线段序列: &mut Vec<Rc<虚线>>,
+        配置: &缠论配置,
+        层级: i64,
+    ) -> bool {
+        if 线段序列.is_empty() {
+            return false;
+        }
+
+        let 当前线段 = Rc::clone(线段序列.last().unwrap());
+        let 四象 = Self::四象(&当前线段);
+
+        // 外层条件
+        if !(配置.线段_非缺口下穿刺
+            && (四象 == "小阳" || 四象 == "少阴")
+            && 当前线段.特征序列.len() >= 3
+            && 当前线段.特征序列[2].is_none())
+        {
+            return false;
+        }
+
+        // 查找贯穿伤
+        let 贯穿伤 = Self::查找贯穿伤(&当前线段);
+        if 贯穿伤.is_none() {
+            return false;
+        }
+        let 贯穿伤 = 贯穿伤.unwrap();
+
+        // 切割基础序列
+        let 贯穿伤_idx = 当前线段
+            .基础序列
+            .iter()
+            .position(|x| Rc::as_ptr(x) == Rc::as_ptr(&贯穿伤));
+
+        if 贯穿伤_idx.is_none() {
+            return false;
+        }
+        let 基础序列: Vec<Rc<虚线>> = 当前线段.基础序列[贯穿伤_idx.unwrap()..].to_vec();
+
+        // 长度条件
+        if !(基础序列.len() == 4 && 线段序列.len() >= 2) {
+            return false;
+        }
+
+        let 左 = Rc::clone(&基础序列[基础序列.len() - 3]);
+        let 右 = Rc::clone(&基础序列[基础序列.len() - 1]);
+
+        // 方向条件
+        if 相对方向::分析(左.高(), 左.低(), 右.高(), 右.低()) != 当前线段.方向() {
+            return false;
+        }
+
+        // 执行修正
+        eprintln!(
+            "[警告<{}, {}>]: 线段.修复贯穿伤 {:?}",
+            层级, 层级, 贯穿伤
+        );
+
+        let 原始基础序列 = 当前线段.基础序列.clone();
+        Self::_弹出线段(
+            线段序列,
+            &Rc::clone(线段序列.last().unwrap()),
+            配置,
+            format!("{}, {}", 0, 层级),
+        );
+
+        if 线段序列.is_empty() {
+            return true;
+        }
+
+        let mut 当前线段_克隆 = (**线段序列.last().unwrap()).clone();
+        if 当前线段_克隆.特征序列.len() >= 3 {
+            当前线段_克隆.特征序列[2] = None;
+        }
+
+        let 开始笔 = Rc::clone(当前线段_克隆.基础序列.last().unwrap());
+        let 开始序号 = 原始基础序列
+            .iter()
+            .position(|x| Rc::as_ptr(x) == Rc::as_ptr(&开始笔));
+
+        if let Some(开始序号) = 开始序号 {
+            for 临时虚线 in &原始基础序列[开始序号 + 1..] {
+                当前线段_克隆.基础序列.push(Rc::clone(临时虚线));
+            }
+        }
+
+        let idx = 线段序列.len() - 1;
+        线段序列[idx] = Rc::new(当前线段_克隆);
+
+        Self::刷新(&mut 线段序列[idx], 配置);
+
+        let 当前线段 = Rc::clone(&线段序列[idx]);
+        if 当前线段.特征序列.len() >= 3 && 当前线段.特征序列[2].is_some() {
+            let 段 = 虚线::创建线段(&[
+                Rc::clone(&基础序列[基础序列.len() - 3]),
+                Rc::clone(&基础序列[基础序列.len() - 2]),
+                Rc::clone(&基础序列[基础序列.len() - 1]),
+            ]);
+            let mut 段_rc = Rc::new(段);
+            Self::_添加线段(线段序列, &mut 段_rc, 配置, format!("{}, {}", 0, 层级));
+
+            // Set feature sequence [0]
+            let 新段 = Self::取段可变(线段序列.last_mut().unwrap());
+            if 新段.特征序列.is_empty() {
+                新段.特征序列.push(None);
+            }
+            let 中笔 = Rc::clone(&基础序列[基础序列.len() - 2]);
+            新段.特征序列[0] = Some(Rc::new(线段特征::新建(
+                vec![中笔],
+                新段.方向(),
+            )));
+        }
+
+        true
+    }
+
+    /// _缺口后紧急修正 — 老阴/老阳后的紧急修正
+    pub fn _缺口后紧急修正(
+        线段序列: &mut Vec<Rc<虚线>>,
+        配置: &缠论配置,
+        层级: i64,
+    ) -> bool {
+        if 线段序列.is_empty() {
+            return false;
+        }
+
+        let 当前线段 = Rc::clone(线段序列.last().unwrap());
+        let 四象 = Self::四象(&当前线段);
+
+        // 外层条件
+        if !(配置.线段_缺口后紧急修正
+            && !配置.线段_特征序列忽视老阴老阳
+            && (四象 == "小阳" || 四象 == "少阴")
+            && 当前线段.特征序列.len() >= 3
+            && 当前线段.特征序列[2].is_none())
+        {
+            return false;
+        }
+
+        // 内层条件
+        if 线段序列.len() < 2 {
+            return false;
+        }
+        let 前一线段_idx = 线段序列.len() - 2;
+        if !["老阴", "老阳"].contains(&Self::四象(&线段序列[前一线段_idx]).as_str())
+        {
+            return false;
+        }
+
+        let (_, 基础序列, _, _) = Self::分割序列(&当前线段, None);
+        if 基础序列.len() < 3 {
+            return false;
+        }
+
+        let mut 需要修正 = false;
+        if 当前线段.方向() == 相对方向::向上 {
+            if 相对方向::分析(
+                基础序列[0].高(),
+                基础序列[0].低(),
+                基础序列[2].高(),
+                基础序列[2].低(),
+            ) == 相对方向::向下
+            {
+                需要修正 = true;
+            }
+        } else {
+            if 相对方向::分析(
+                基础序列[0].高(),
+                基础序列[0].低(),
+                基础序列[2].高(),
+                基础序列[2].低(),
+            ) == 相对方向::向上
+            {
+                需要修正 = true;
+            }
+        }
+
+        if !需要修正 {
+            return false;
+        }
+
+        // 执行修正 — set 短路修正 and create new segment
+        let idx = 线段序列.len() - 1;
+        let mut 当前线段_克隆 = (*线段序列[idx]).clone();
+        当前线段_克隆.短路修正 = true;
+        线段序列[idx] = Rc::new(当前线段_克隆);
+
+        let 新段 = 虚线::创建线段(&基础序列);
+        let mut 新段_rc = Rc::new(新段);
+        Self::_添加线段(线段序列, &mut 新段_rc, 配置, format!("{}, {}", 0, 层级));
+        true
+    }
+
+    /// _修正 — 通用线段修正（后段足够长时拆分）
+    pub fn _修正(
+        线段序列: &mut Vec<Rc<虚线>>,
+        配置: &缠论配置,
+        层级: i64,
+    ) -> bool {
+        if 线段序列.is_empty() {
+            return false;
+        }
+
+        let 当前线段 = Rc::clone(线段序列.last().unwrap());
+
+        // 条件1
+        if !(配置.线段_修正 && 当前线段.基础序列.len() >= 9) {
+            return false;
+        }
+
+        let (_, 之后基础序列, _, _) = Self::分割序列(&当前线段, None);
+
+        // 条件2
+        if 之后基础序列.len() < 6 {
+            return false;
+        }
+
+        let 前 = Rc::clone(&之后基础序列[之后基础序列.len() - 3]);
+        let 后 = Rc::clone(&之后基础序列[之后基础序列.len() - 1]);
+
+        // 条件3
+        if 当前线段.方向() != 相对方向::分析(前.高(), 前.低(), 后.高(), 后.低()) {
+            return false;
+        }
+
+        // 执行修正
+        let idx = 线段序列.len() - 1;
+        let mut 当前线段_克隆 = (*线段序列[idx]).clone();
+        当前线段_克隆.短路修正 = true;
+        线段序列[idx] = Rc::new(当前线段_克隆);
+
+        // 第一个新段
+        let 新段1 = 虚线::创建线段(&之后基础序列[..之后基础序列.len() - 3]);
+        let mut 新段1_rc = Rc::new(新段1);
+        // Set 短路修正
+        Self::取段可变(&mut 新段1_rc).短路修正 = true;
+        Self::_添加线段(线段序列, &mut 新段1_rc, 配置, format!("{}, {}", 0, 层级));
+
+        if ["老阴", "老阳"].contains(&Self::四象(&当前线段).as_str()) {
+            Self::取段可变(线段序列.last_mut().unwrap()).前一缺口 = None;
+        }
+
+        // 第二个新段
+        let start = 之后基础序列.len() - 3;
+        let 新段2 = 虚线::创建线段(&之后基础序列[start..]);
+        let mut 新段2_rc = Rc::new(新段2);
+        Self::_添加线段(线段序列, &mut 新段2_rc, 配置, format!("{}, {}", 0, 层级));
+
+        true
+    }
+
+    // ================================================================
+    // 核心分析 — 使用显式栈（loop）模拟递归
+    // ================================================================
+
+    /// 分析 — 从笔序列生成线段序列
+    ///
+    /// 使用显式栈（loop + continue）模拟 Python 的递归调用，避免栈溢出。
+    pub fn 分析(
+        笔序列: &[Rc<虚线>],
+        线段序列: &mut Vec<Rc<虚线>>,
+        配置: &缠论配置,
+        层级: i64,
+        关系序列: &[相对方向],
+    ) {
+        let mut 当前层级 = 层级;
+
+        loop {
+            if 当前层级 > 256 {
+                eprintln!("线段.分析 递归深度超出 256");
+                return;
+            }
+
+            if 笔序列.len() < 3 {
+                return;
+            }
+
+            // ---- 1. 初始化第一个线段 ----
+            if 线段序列.is_empty() {
+                for i in 1..笔序列.len() - 1 {
+                    let 左 = &笔序列[i - 1];
+                    let 中 = &笔序列[i];
+                    let 右 = &笔序列[i + 1];
+
+                    if !Self::基础判断(左, 中, 右, 关系序列) {
+                        continue;
+                    }
+                    let 段 = 虚线::创建线段(&[
+                        Rc::clone(左),
+                        Rc::clone(中),
+                        Rc::clone(右),
+                    ]);
+                    let mut 段_rc = Rc::new(段);
+                    Self::_添加线段(
+                        线段序列,
+                        &mut 段_rc,
+                        配置,
+                        format!("{}, {}", 0, 当前层级),
+                    );
+
+                    // 段.特征序列[0] = 线段特征.新建([中], 段.方向)
+                    let 段 = Self::取段可变(线段序列.last_mut().unwrap());
+                    if 段.特征序列.is_empty() {
+                        段.特征序列.push(None);
+                    }
+                    段.特征序列[0] = Some(Rc::new(线段特征::新建(
+                        vec![Rc::clone(中)],
+                        段.方向(),
+                    )));
+                    break;
+                }
+                if 线段序列.is_empty() {
+                    return;
+                }
+            }
+
+            // ---- 2. 清理无效的尾部引用 ----
+            while !线段序列.is_empty()
+                && 线段序列.last().unwrap().前一结束位置.is_some()
+            {
+                let 前一结束 = Rc::clone(
+                    线段序列.last().unwrap().前一结束位置.as_ref().unwrap(),
+                );
+                if !笔序列
+                    .iter()
+                    .any(|x| Rc::as_ptr(x) == Rc::as_ptr(&前一结束))
+                {
+                    let 当前 = Rc::clone(线段序列.last().unwrap());
+                    Self::_弹出线段(
+                        线段序列,
+                        &当前,
+                        配置,
+                        format!("{}, {}", 0, 当前层级),
+                    );
+                } else {
+                    break;
+                }
+            }
+
+            if 线段序列.is_empty() {
+                当前层级 += 1;
+                continue;
+            }
+
+            // ---- 3. 确保当前线段有效 ----
+            let mut 当前线段_rc = Rc::clone(线段序列.last().unwrap());
+            Self::序列重置(&mut 当前线段_rc, 笔序列);
+            let seg_idx = 线段序列.len() - 1;
+            线段序列[seg_idx] = 当前线段_rc;
+
+            if 线段序列.last().unwrap().基础序列.len() < 3 {
+                let 当前 = Rc::clone(线段序列.last().unwrap());
+                Self::_弹出线段(线段序列, &当前, 配置, format!("{}, {}", 0, 当前层级));
+                if 线段序列.is_empty() {
+                    当前层级 += 1;
+                    continue;
+                }
+            }
+
+            // ---- 4. 特征序列已完整时的处理 ----
+            {
+                let 当前线段 = Rc::clone(线段序列.last().unwrap());
+                if 当前线段.特征序列.len() >= 3 && 当前线段.特征序列[2].is_some() {
+                    let (_, 基础序列, _, _) = Self::分割序列(&当前线段, None);
+                    let 新段 = 虚线::创建线段(&基础序列);
+                    let mut 新段_rc = Rc::new(新段);
+                    Self::_添加线段(
+                        线段序列,
+                        &mut 新段_rc,
+                        配置,
+                        format!("{}, {}", 0, 当前层级),
+                    );
+                    if ["老阴", "老阳"].contains(&Self::四象(&当前线段).as_str()) {
+                        let last_idx = 线段序列.len() - 1;
+                        let mut 克隆 = (**线段序列.last().unwrap()).clone();
+                        克隆.前一缺口 = None;
+                        线段序列[last_idx] = Rc::new(克隆);
+                    }
+                }
+            }
+
+            // Refresh current segment
+            let idx = 线段序列.len() - 1;
+            Self::刷新(&mut 线段序列[idx], 配置);
+
+            // ---- 5. 调用一次全局修正 ----
+            Self::_缺口突破(线段序列, 配置, 当前层级);
+            Self::_非缺口下穿刺(线段序列, 配置, 当前层级);
+            Self::_缺口后紧急修正(线段序列, 配置, 当前层级);
+            Self::_修正(线段序列, 配置, 当前层级);
+
+            // ---- 6. 循环处理后续的笔 ----
+            let 当前线段 = Rc::clone(线段序列.last().unwrap());
+            if 当前线段.基础序列.is_empty() {
+                panic!("线段.分析: 基础序列为空");
+            }
+            let 最后笔 = Rc::clone(当前线段.基础序列.last().unwrap());
+            let 起始索引 = match 笔序列
+                .iter()
+                .position(|x| Rc::as_ptr(x) == Rc::as_ptr(&最后笔))
+            {
+                Some(idx) => idx + 1,
+                None => {
+                    // Last笔 not in 笔序列 — restart
+                    当前层级 += 1;
+                    continue;
+                }
+            };
+
+            let mut 需要递归 = false;
+
+            for i in 起始索引..笔序列.len() {
+                let 当前虚线 = Rc::clone(&笔序列[i]);
+                let 当前线段 = Rc::clone(线段序列.last().unwrap());
+                let 四象 = Self::四象(&当前线段);
+
+                // 向当前线段添加笔
+                let mut 线段_rc = Rc::clone(线段序列.last().unwrap());
+                Self::添加虚线(&mut 线段_rc, Rc::clone(&当前虚线));
+                let seg_idx = 线段序列.len() - 1;
+                线段序列[seg_idx] = 线段_rc;
+
+                // 刷新
+                let idx = 线段序列.len() - 1;
+                Self::刷新(&mut 线段序列[idx], 配置);
+
+                // 依次尝试四种修正
+                if Self::_缺口突破(线段序列, 配置, 当前层级) {
+                    continue;
+                }
+                if Self::_非缺口下穿刺(线段序列, 配置, 当前层级) {
+                    continue;
+                }
+                if Self::_缺口后紧急修正(线段序列, 配置, 当前层级) {
+                    continue;
+                }
+                if Self::_修正(线段序列, 配置, 当前层级) {
+                    continue;
+                }
+
+                // 无修正触发，检查特征序列
+                let 当前线段 = Rc::clone(线段序列.last().unwrap());
+                if 当前线段.特征序列.len() < 3 || 当前线段.特征序列[2].is_none() {
+                    continue;
+                }
+
+                // 特征序列[2]存在 → 创建新段
+                let (_, 基础序列, _, _) = Self::分割序列(&当前线段, None);
+                let 新段 = 虚线::创建线段(&基础序列);
+                let mut 新段_rc = Rc::new(新段);
+                Self::_添加线段(
+                    线段序列,
+                    &mut 新段_rc,
+                    配置,
+                    format!("{}, {}", 0, 当前层级),
+                );
+
+                if ["老阴", "老阳"].contains(&四象.as_str()) {
+                    let last_idx = 线段序列.len() - 1;
+                    let mut 克隆 = (**线段序列.last().unwrap()).clone();
+                    克隆.前一缺口 = None;
+                    线段序列[last_idx] = Rc::new(克隆);
+                }
+
+                // 检查新段与当前虚线的连续性
+                let 新段 = Rc::clone(线段序列.last().unwrap());
+                if Rc::as_ptr(新段.基础序列.last().unwrap()) != Rc::as_ptr(&当前虚线) {
+                    if !新段.基础序列.last().unwrap().之后是(&当前虚线) {
+                        需要递归 = true;
+                        break;
+                    }
+                    // 向新段添加当前虚线
+                    let mut 新段_rc = Rc::clone(线段序列.last().unwrap());
+                    Self::添加虚线(&mut 新段_rc, Rc::clone(&当前虚线));
+                    let seg_idx = 线段序列.len() - 1;
+                    线段序列[seg_idx] = 新段_rc;
+                }
+
+                let idx = 线段序列.len() - 1;
+                Self::刷新(&mut 线段序列[idx], 配置);
+            }
+
+            if 需要递归 {
+                当前层级 += 1;
+                continue;
+            }
+
+            break;
+        }
+    }
+
+    // ================================================================
+    // 扩展线段
+    // ================================================================
+
+    /// _添加扩展线段
+    pub fn _添加扩展线段(
+        线段序列: &mut Vec<Rc<虚线>>,
+        待添加线段_rc: &mut Rc<虚线>,
+        行号: u32,
+    ) {
+        let 待添加线段 = Self::取段可变(待添加线段_rc);
+        待添加线段.模式 = "高低".into();
+        待添加线段.标识 = if 待添加线段.基础序列[0].标识 != "笔" {
+            format!("扩展{}", 待添加线段.标识)
+        } else {
+            "扩展线段".into()
+        };
+
+        if let Some(前一个) = 线段序列.last() {
+            if !前一个.之后是(待添加线段) {
+                panic!(
+                    "线段.向序列中添加 不连续[{}] {:?} {:?}",
+                    行号, 前一个.武, 待添加线段.文
+                );
+            }
+            let 之前线段 = 线段序列.last().unwrap();
+            待添加线段.序号 = 之前线段.序号 + 1;
+        }
+
+        let 新段 = Rc::new(待添加线段.clone());
+        线段序列.push(新段);
+    }
+
+    /// _弹出扩展线段
+    pub fn _弹出扩展线段(
+        线段序列: &mut Vec<Rc<虚线>>,
+        待弹出线段: &Rc<虚线>,
+        _行号: u32,
+    ) -> Option<Rc<虚线>> {
+        if 线段序列.is_empty() {
+            return None;
+        }
+
+        if Rc::as_ptr(线段序列.last().unwrap()) == Rc::as_ptr(待弹出线段) {
+            Some(线段序列.pop().unwrap())
+        } else {
+            panic!(
+                "线段._从序列中删除 弹出数据不在列表中 {:?}",
+                待弹出线段
+            );
+        }
+    }
+
+    /// 扩展分析 — 将笔视为线段进行同级别分析
+    pub fn 扩展分析(
+        虚线序列: &[Rc<虚线>],
+        线段序列: &mut Vec<Rc<虚线>>,
+        配置: &缠论配置,
+    ) {
+        if 虚线序列.len() < 3 {
+            return;
+        }
+
+        let mut 当前层级 = 0i64;
+
+        loop {
+            if 当前层级 > 256 {
+                eprintln!("线段.扩展分析 递归深度超出 256");
+                return;
+            }
+
+            // 初始化第一个扩展线段
+            if 线段序列.is_empty() {
+                for i in 1..虚线序列.len() - 1 {
+                    let 左 = &虚线序列[i - 1];
+                    let 中 = &虚线序列[i];
+                    let 右 = &虚线序列[i + 1];
+                    let 关系 = 相对方向::分析(左.高(), 左.低(), 右.高(), 右.低());
+                    if !matches!(
+                        关系,
+                        相对方向::向下
+                            | 相对方向::向上
+                            | 相对方向::顺
+                            | 相对方向::逆
+                            | 相对方向::同
+                    ) {
+                        continue;
+                    }
+
+                    let 段 = 虚线::创建线段(&[
+                        Rc::clone(左),
+                        Rc::clone(中),
+                        Rc::clone(右),
+                    ]);
+                    let mut 段_rc = Rc::new(段);
+                    Self::_添加扩展线段(线段序列, &mut 段_rc, 0);
+                    break;
+                }
+
+                if 线段序列.is_empty() {
+                    return;
+                }
+            }
+
+            // 验证当前线段
+            let mut 当前线段_rc = Rc::clone(线段序列.last().unwrap());
+            Self::验证序列(&mut 当前线段_rc, 虚线序列);
+            let seg_idx = 线段序列.len() - 1;
+            线段序列[seg_idx] = 当前线段_rc;
+
+            if 线段序列.last().unwrap().基础序列.len() < 3 {
+                let 当前 = Rc::clone(线段序列.last().unwrap());
+                Self::_弹出扩展线段(线段序列, &当前, 0);
+                当前层级 += 1;
+                continue;
+            }
+
+            if !配置.扩展线段_当下分析 {
+                let 当前线段 = Rc::clone(线段序列.last().unwrap());
+                let 左 = Rc::clone(&当前线段.基础序列[0]);
+                let 右 = Rc::clone(&当前线段.基础序列[2]);
+
+                if !相对方向::分析(左.高(), 左.低(), 右.高(), 右.低()).是否缺口() {
+                    let mut 克隆 = (**线段序列.last().unwrap()).clone();
+                    克隆.基础序列 = 克隆.基础序列[..3].to_vec();
+                    let mut 段_rc = Rc::new(克隆);
+                    Self::武终(&mut 段_rc, 0);
+                    let seg_idx = 线段序列.len() - 1;
+                    线段序列[seg_idx] = 段_rc;
+                } else {
+                    let 当前 = Rc::clone(线段序列.last().unwrap());
+                    Self::_弹出扩展线段(线段序列, &当前, 0);
+                    当前层级 += 1;
+                    continue;
+                }
+            }
+
+            // 武终
+            let idx = 线段序列.len() - 1;
+            Self::武终(&mut 线段序列[idx], 0);
+
+            let 当前线段 = Rc::clone(线段序列.last().unwrap());
+            if 当前线段.基础序列.last().unwrap().序号 + 3 > 虚线序列.last().unwrap().序号 {
+                return;
+            }
+
+            let 最后笔 = Rc::clone(当前线段.基础序列.last().unwrap());
+            let 序号 = match 虚线序列
+                .iter()
+                .position(|x| Rc::as_ptr(x) == Rc::as_ptr(&最后笔))
+            {
+                Some(idx) => idx + 1,
+                None => return,
+            };
+
+            if 序号 >= 虚线序列.len() {
+                return;
+            }
+
+            let mut 需要递归 = false;
+
+            for i in 序号 + 1..虚线序列.len() - 1 {
+                let 左 = &虚线序列[i - 1];
+                let 中 = &虚线序列[i];
+                let 右 = &虚线序列[i + 1];
+                let 相对关系 = 相对方向::分析(左.高(), 左.低(), 右.高(), 右.低());
+
+                if 相对关系.是否缺口() {
+                    let mut 段_rc = Rc::clone(线段序列.last().unwrap());
+                    Self::添加虚线(&mut 段_rc, Rc::clone(左));
+                    let seg_idx = 线段序列.len() - 1;
+                    线段序列[seg_idx] = 段_rc;
+
+                    let mut 段_rc = Rc::clone(线段序列.last().unwrap());
+                    Self::添加虚线(&mut 段_rc, Rc::clone(中));
+                    let seg_idx = 线段序列.len() - 1;
+                    线段序列[seg_idx] = 段_rc;
+
+                    let seg_idx = 线段序列.len() - 1;
+                    Self::武终(&mut 线段序列[seg_idx], 0);
+                    continue;
+                }
+
+                if 线段序列
+                    .last()
+                    .unwrap()
+                    .基础序列
+                    .iter()
+                    .any(|x| Rc::as_ptr(x) == Rc::as_ptr(左))
+                {
+                    continue;
+                }
+
+                let 段 = 虚线::创建线段(&[
+                    Rc::clone(左),
+                    Rc::clone(中),
+                    Rc::clone(右),
+                ]);
+                let mut 段_rc = Rc::new(段);
+                Self::_添加扩展线段(线段序列, &mut 段_rc, 0);
+                需要递归 = true;
+                break;
+            }
+
+            if 需要递归 {
+                当前层级 += 1;
+                continue;
+            }
+
+            break;
+        }
+    }
+
+    // ================================================================
+    // 背驰相关
+    // ================================================================
+
+    /// 判断线段内部是否背驰
+    ///
+    /// 分析线段的内部中枢和MACD柱分段，判断是否发生内部背驰
+    pub fn 判断线段内部是否背驰(当前段: &虚线, 观察员: &观察者) -> bool {
+        let _虚 = &当前段.虚_中枢序列;
+        let 实 = &当前段.实_中枢序列;
+        let 阳: Vec<&Rc<虚线>> = 当前段
+            .基础序列
+            .iter()
+            .filter(|b| b.方向() == 相对方向::向上)
+            .collect();
+        let 阴: Vec<&Rc<虚线>> = 当前段
+            .基础序列
+            .iter()
+            .filter(|b| b.方向() == 相对方向::向下)
+            .collect();
+
+        if !阴.is_empty() {
+            // 阴不为空表示特征序列仍在合并中，不判断
+        }
+        let 笔之实数 = 阳.len();
+        if 笔之实数 < 3 {
+            return false;
+        }
+
+        let 进入段 = 阳[阳.len() - 3];
+        let 离开段 = 阳[阳.len() - 1];
+        if 进入段.序号 >= 离开段.序号 {
+            return false;
+        }
+        let 关系 = 相对方向::分析(进入段.高(), 进入段.低(), 离开段.高(), 离开段.低());
+        let mut 背驰 = false;
+        let mut 盘整背驰 = false;
+
+        if ((进入段.方向().是否向上() && 关系.是否向上())
+            || (进入段.方向().是否向下() && 关系.是否向下()))
+            && crate::algorithm::divergence::背驰分析::背驰模式(
+                进入段,
+                离开段,
+                &观察员.普通K线序列,
+                &观察员.配置,
+                &观察员.配置.线段内部背驰_模式,
+            )
+        {
+            let k线序列 = K线::截取rc(
+                &观察员.普通K线序列,
+                &阳[阳.len() - 3].文.中.标的K线,
+                &阳[阳.len() - 1].武.中.标的K线,
+            );
+            if 虚线::计算MACD柱子分段(&k线序列).len() >= 3 {
+                盘整背驰 = true;
+            }
+        }
+
+        if !实.is_empty() {
+            let 最后中枢 = &实[实.len() - 1];
+            if 最后中枢.基础序列.iter().any(|b| Rc::ptr_eq(b, 阳[阳.len() - 1])) {
+                // 最后一笔在最后一个中枢内
+                if let Some(序号) = 当前段.基础序列.iter().position(|b| {
+                    Rc::ptr_eq(b, &最后中枢.基础序列[0])
+                }) {
+                    if 序号 > 0 {
+                        let 进入段 = &当前段.基础序列[序号 - 1];
+                        let 离开段 = 阳[阳.len() - 1];
+                        if 进入段.序号 < 离开段.序号 {
+                            if 进入段.方向() != 离开段.方向() {
+                                return crate::algorithm::divergence::背驰分析::测度背驰(进入段, 离开段)
+                                    && 虚线::买卖意义(离开段, 观察员).0;
+                            }
+                            let 关系 = 相对方向::分析(
+                                进入段.高(),
+                                进入段.低(),
+                                离开段.高(),
+                                离开段.低(),
+                            );
+                            if ((进入段.方向().是否向上() && 关系.是否向上())
+                                || (进入段.方向().是否向下() && 关系.是否向下()))
+                                && crate::algorithm::divergence::背驰分析::背驰模式(
+                                    进入段,
+                                    离开段,
+                                    &观察员.普通K线序列,
+                                    &观察员.配置,
+                                    &观察员.配置.线段内部背驰_模式,
+                                )
+                            {
+                                return true;
+                            }
+                        }
+                    }
+                }
+            } else if 最后中枢.第三买卖线.is_some() {
+                // 第三买卖点后盘整背驰
+                let 进入段 = 阳[阳.len() - 3];
+                let 离开段 = 阳[阳.len() - 1];
+                if 进入段.序号 < 离开段.序号 {
+                    if 进入段.方向() != 离开段.方向() {
+                        return crate::algorithm::divergence::背驰分析::测度背驰(进入段, 离开段)
+                            && 虚线::买卖意义(离开段, 观察员).0;
+                    }
+                    let 关系 =
+                        相对方向::分析(进入段.高(), 进入段.低(), 离开段.高(), 离开段.低());
+                    if ((进入段.方向().是否向上() && 关系.是否向上())
+                        || (进入段.方向().是否向下() && 关系.是否向下()))
+                        && crate::algorithm::divergence::背驰分析::背驰模式(
+                            进入段,
+                            离开段,
+                            &观察员.普通K线序列,
+                            &观察员.配置,
+                            &观察员.配置.线段内部背驰_模式,
+                        )
+                    {
+                        return true;
+                    }
+                }
+            }
+        } else {
+            // 没有中枢
+            if 笔之实数 == 3 {
+                背驰 = 盘整背驰;
+            }
+        }
+
+        背驰 || 盘整背驰
+    }
+
+    /// 段获取所有停顿位置 — 在线段范围内找出所有停顿位置
+    pub fn 段获取所有停顿位置(段: &虚线, 观察员: &观察者) -> Vec<虚线> {
+        let mut 结果 = Vec::new();
+        if 段.模式 != "文武" || 段.标识 != "线段" {
+            return 结果;
+        }
+
+        let 阳: Vec<Rc<虚线>> = 段
+            .基础序列
+            .iter()
+            .filter(|b| b.方向() == 相对方向::向上)
+            .cloned()
+            .collect();
+        if 阳.len() < 3 {
+            return 结果;
+        }
+
+        // Simplified: only handle the basic case (笔停顿 + 线段停顿)
+        // Full implementation requires complex sequence management
+        let mut 笔序列: Vec<Rc<虚线>> = Vec::new();
+
+        for 筆 in &阳 {
+            if 笔序列.len() >= 2 {
+                let 筆停顿 = 笔::获取所有停顿位置(筆, 观察员);
+                let mut 停顿列表: Vec<虚线> = 筆停顿;
+                停顿列表.push((**筆).clone());
+
+                for 停顿 in 停顿列表 {
+                    笔序列.push(Rc::new(停顿.clone()));
+                    // 线段.分析 with the accumulated 笔序列
+                    let mut 线段序列: Vec<Rc<虚线>> = Vec::new();
+                    let 笔序列_slice: Vec<Rc<虚线>> = 笔序列.iter().map(|b| Rc::clone(b)).collect();
+                    Self::分析(
+                        &笔序列_slice,
+                        &mut 线段序列,
+                        &观察员.配置,
+                        0,
+                        &[
+                            相对方向::向下,
+                            相对方向::向上,
+                            相对方向::顺,
+                            相对方向::逆,
+                            相对方向::同,
+                        ],
+                    );
+
+                    let 重复 = match (线段序列.last(), 结果.last()) {
+                        (Some(a), Some(b)) => Rc::ptr_eq(&a.武, &b.武),
+                        _ => false,
+                    };
+                    if !重复 {
+                        if let Some(最后线段) = 线段序列.last() {
+                            let 新段 = 虚线::创建线段(&最后线段.基础序列);
+                            if 新段.方向() == 段.方向() {
+                                结果.push(新段);
+                            }
+                        }
+                    }
+
+                    // If this 停顿 is not the original 筆, pop it
+                    let 停顿_ptr: *const 虚线 = &停顿;
+                    let 筆_ptr: *const 虚线 = 筆.as_ref();
+                    if 停顿_ptr != 筆_ptr {
+                        笔序列.pop();
+                    }
+                }
+            } else {
+                笔序列.push(Rc::clone(筆));
+            }
+        }
+        结果
+    }
+
+    /// 是否背驰过 — 判断线段是否在停顿位置出现过背驰
+    pub fn 是否背驰过(当前段: &虚线, 观察员: &观察者) -> Vec<Rc<分型>> {
+        let 停顿位置 = Self::段获取所有停顿位置(当前段, 观察员);
+        let mut 结果 = Vec::new();
+
+        for 段 in 停顿位置 {
+            let mut 段_rc = Rc::new(段);
+            Self::获取内部中枢序列(&mut 段_rc, &观察员.配置);
+            if Self::判断线段内部是否背驰(&段_rc, 观察员) {
+                结果.push(Rc::clone(&段_rc.武));
+            }
+        }
+
+        结果
+    }
+}
diff --git a/chanlun/src/business/bsp.rs b/chanlun/src/business/bsp.rs
new file mode 100644
index 0000000..ca11643
--- /dev/null
+++ b/chanlun/src/business/bsp.rs
@@ -0,0 +1,181 @@
+use crate::kline::bar::K线;
+use crate::kline::chan_kline::缠论K线;
+use crate::structure::fractal_obj::分型;
+use crate::types::bsp_type::买卖点类型;
+use crate::types::分型结构;
+use std::rc::Rc;
+
+/// 基础买卖点 — 买卖点的基础数据结构
+#[derive(Debug, Clone)]
+pub struct 基础买卖点 {
+    pub 备注: String,
+    pub 类型: 买卖点类型,
+    pub 买卖点分型: Rc<分型>,
+    pub 买卖点K线: Rc<缠论K线>,
+    pub 当前K线: Rc<K线>,
+    pub 失效K线: Option<Rc<K线>>,
+    pub 终结K线: Option<Rc<K线>>,
+    pub 破位值: f64,
+    pub 结构: Option<分型结构>,
+}
+
+impl 基础买卖点 {
+    pub fn new(
+        类型: 买卖点类型,
+        当前K线: Rc<K线>,
+        买卖点分型: Rc<分型>,
+        备注: String,
+        中枢破位值: f64,
+    ) -> Self {
+        let 买卖点K线 = Rc::clone(&买卖点分型.中);
+        Self {
+            备注,
+            类型,
+            买卖点分型,
+            买卖点K线,
+            当前K线,
+            失效K线: None,
+            终结K线: None,
+            破位值: 中枢破位值,
+            结构: None,
+        }
+    }
+
+    /// 偏移 — 当前K线与买卖点K线的序号差
+    pub fn 偏移(&self) -> i64 {
+        self.当前K线.序号 - self.买卖点K线.序号
+    }
+
+    /// 失效偏移
+    pub fn 失效偏移(&self) -> i64 {
+        match &self.失效K线 {
+            Some(k) => k.序号 - self.买卖点K线.序号,
+            None => -1,
+        }
+    }
+
+    /// 有效性 — 失效K线是否存在
+    pub fn 有效性(&self) -> bool {
+        self.失效K线.is_some()
+    }
+
+    /// 与MACD柱子匹配
+    pub fn 与MACD柱子匹配(&self) -> bool {
+        self.买卖点K线.与MACD柱子匹配()
+    }
+
+    /// 与MACD柱子分型匹配
+    pub fn 与MACD柱子分型匹配(&self) -> bool {
+        self.买卖点分型.与MACD柱子分型匹配()
+    }
+}
+
+impl std::fmt::Display for 基础买卖点 {
+    fn fmt(&self, f: &mut std::fmt::Formatter<'_>) -> std::fmt::Result {
+        write!(
+            f,
+            "{}<{}, {}, {}>",
+            self.类型,
+            self.买卖点K线.as_ref(),
+            self.偏移(),
+            self.失效偏移(),
+        )
+    }
+}
+
+/// 买卖点 — 包含一二三类买卖点的工厂方法
+pub struct 买卖点;
+
+impl 买卖点 {
+    pub fn 一卖点(
+        买卖点分型: Rc<分型>,
+        当前K线: Rc<K线>,
+        _标识: &str,
+        备注: String,
+        中枢破位值: f64,
+    ) -> 基础买卖点 {
+        基础买卖点::new(买卖点类型::一卖, 当前K线, 买卖点分型, 备注, 中枢破位值)
+    }
+
+    pub fn 一买点(
+        买卖点分型: Rc<分型>,
+        当前K线: Rc<K线>,
+        _标识: &str,
+        备注: String,
+        中枢破位值: f64,
+    ) -> 基础买卖点 {
+        基础买卖点::new(买卖点类型::一买, 当前K线, 买卖点分型, 备注, 中枢破位值)
+    }
+
+    pub fn 二卖点(
+        买卖点分型: Rc<分型>,
+        当前K线: Rc<K线>,
+        _标识: &str,
+        备注: String,
+        中枢破位值: f64,
+    ) -> 基础买卖点 {
+        基础买卖点::new(买卖点类型::二卖, 当前K线, 买卖点分型, 备注, 中枢破位值)
+    }
+
+    pub fn 二买点(
+        买卖点分型: Rc<分型>,
+        当前K线: Rc<K线>,
+        _标识: &str,
+        备注: String,
+        中枢破位值: f64,
+    ) -> 基础买卖点 {
+        基础买卖点::new(买卖点类型::二买, 当前K线, 买卖点分型, 备注, 中枢破位值)
+    }
+
+    pub fn 三卖点(
+        买卖点分型: Rc<分型>,
+        当前K线: Rc<K线>,
+        _标识: &str,
+        备注: String,
+        中枢破位值: f64,
+    ) -> 基础买卖点 {
+        基础买卖点::new(买卖点类型::三卖, 当前K线, 买卖点分型, 备注, 中枢破位值)
+    }
+
+    pub fn 三买点(
+        买卖点分型: Rc<分型>,
+        当前K线: Rc<K线>,
+        _标识: &str,
+        备注: String,
+        中枢破位值: f64,
+    ) -> 基础买卖点 {
+        基础买卖点::new(买卖点类型::三买, 当前K线, 买卖点分型, 备注, 中枢破位值)
+    }
+
+    /// 生成买卖点 — 根据参数自动选择类型
+    pub fn 生成买卖点(
+        特征: &str,
+        序号: &str,
+        级别: &str,
+        买卖点分型: Rc<分型>,
+        当前缠K: Rc<缠论K线>,
+    ) -> 基础买卖点 {
+        let 买卖 = if matches!(买卖点分型.结构, 分型结构::底 | 分型结构::下) {
+            "买"
+        } else {
+            "卖"
+        };
+        let 备注 = format!("{}_{}{}{}", 特征, 级别, 序号, 买卖);
+        let 破位值 = 买卖点分型.分型特征值;
+
+        // 当前K线 — 从缠K获取其标的K线
+        let 当前K线 = Rc::clone(&当前缠K.标的K线);
+
+        let 类型 = match (序号, 买卖) {
+            ("一", "买") => 买卖点类型::一买,
+            ("一", "卖") => 买卖点类型::一卖,
+            ("二", "买") => 买卖点类型::二买,
+            ("二", "卖") => 买卖点类型::二卖,
+            ("三", "买") => 买卖点类型::三买,
+            ("三", "卖") => 买卖点类型::三卖,
+            _ => 买卖点类型::一买, // fallback
+        };
+
+        基础买卖点::new(类型, 当前K线, 买卖点分型, 备注, 破位值)
+    }
+}
diff --git a/chanlun/src/business/mod.rs b/chanlun/src/business/mod.rs
new file mode 100644
index 0000000..e27f29c
--- /dev/null
+++ b/chanlun/src/business/mod.rs
@@ -0,0 +1,4 @@
+pub mod bsp;
+pub mod multi_frame;
+pub mod observer;
+pub mod synthesizer;
diff --git a/chanlun/src/business/multi_frame.rs b/chanlun/src/business/multi_frame.rs
new file mode 100644
index 0000000..a2a0e75
--- /dev/null
+++ b/chanlun/src/business/multi_frame.rs
@@ -0,0 +1,148 @@
+use crate::business::observer::观察者;
+use crate::business::synthesizer::K线合成器;
+use crate::config::缠论配置;
+use crate::kline::bar::K线;
+use std::collections::HashMap;
+
+/// 立体分析器 — 多周期协调器
+///
+/// 包含一个K线合成器和每周期一个观察者。
+/// 输入最小周期K线，合成大周期后分发到对应观察者。
+pub struct 立体分析器 {
+    pub 周期组: Vec<i64>,
+    输入周期: i64,
+    显示周期: i64,
+    K线合成器: K线合成器,
+    单体分析器: HashMap<i64, 观察者>,
+    合成K线计数: HashMap<i64, usize>,
+}
+
+impl 立体分析器 {
+    pub fn new(
+        符号: String,
+        周期组: Vec<i64>,
+        配置: Option<缠论配置>,
+        配置组: Option<HashMap<i64, 缠论配置>>,
+    ) -> Self {
+        let mut 周期组 = 周期组;
+        周期组.sort();
+        let 输入周期 = 周期组[0];
+        let 显示周期 = if 周期组.len() > 1 {
+            周期组[1]
+        } else {
+            周期组[0]
+        };
+
+        let 默认配置 = 配置.unwrap_or_default();
+        let 配置组 = 配置组.unwrap_or_default();
+
+        let K线合成器 = K线合成器::new(符号.clone(), 周期组.clone());
+
+        let mut 单体分析器 = HashMap::new();
+        for &周期 in &周期组 {
+            let mut 当前配置 = 配置组.get(&周期).cloned().unwrap_or_else(|| 默认配置.clone());
+            当前配置.推送K线 = false;
+            当前配置.推送线段 = false;
+            // Set 标识 to match 符号
+            当前配置.标识 = 符号.clone();
+
+            let 观察员 = 观察者::new(符号.clone(), 周期, 当前配置);
+            单体分析器.insert(周期, 观察员);
+        }
+
+        // Configure display period
+        if let Some(显示观察员) = 单体分析器.get_mut(&显示周期) {
+            显示观察员.配置.推送K线 = true;
+            显示观察员.配置.推送笔 = true;
+            显示观察员.配置.推送线段 = true;
+            显示观察员.配置.图表展示 = true;
+            显示观察员.重置基础序列();
+        }
+
+        // Align other periods to display period's 缠K序列
+        // (in practice, this is done during data loading)
+        for &周期 in &周期组 {
+            if 周期 != 显示周期 {
+                // Other periods will reference display period's 缠论K线序列
+                // This is done during the K-line callback flow
+            }
+        }
+
+        let mut 合成K线计数 = HashMap::new();
+        for &周期 in &周期组 {
+            合成K线计数.insert(周期, 0);
+        }
+
+        Self {
+            周期组,
+            输入周期,
+            显示周期,
+            K线合成器,
+            单体分析器,
+            合成K线计数,
+        }
+    }
+
+    /// 投喂K线 — 统一入口，接收最小周期K线
+    pub fn 投喂K线(&mut self, 普K: K线) {
+        if 普K.周期 != self.输入周期 {
+            eprintln!(
+                "立体分析器.投喂K线 周期不匹配 {} != {}",
+                普K.周期, self.输入周期
+            );
+            return;
+        }
+
+        // Record current K-line counts before feeding
+        let mut 之前计数 = HashMap::new();
+        for &周期 in &self.周期组 {
+            之前计数.insert(周期, self.K线合成器.合成K线列表.get(&周期).map(|v| v.len()).unwrap_or(0));
+        }
+
+        // Feed to synthesizer
+        self.K线合成器.投喂K线(普K);
+
+        // Dispatch new K-lines to observers
+        for &周期 in &self.周期组 {
+            let 新K线列表 = self.K线合成器.合成K线列表.get(&周期);
+            let 之前计数 = 之前计数[&周期];
+            if let Some(列表) = 新K线列表 {
+                for k线 in 列表.iter().skip(之前计数) {
+                    // Clone the K-line for feeding to observer
+                    let 完成K线 = k线.clone();
+                    if let Some(观察员) = self.单体分析器.get_mut(&周期) {
+                        观察员.增加原始K线(完成K线);
+                    }
+                }
+            }
+
+            // Also feed the current in-progress K-line (if any)
+            if let Some(Some(当前K线)) = self.K线合成器.当前K线.get(&周期).cloned() {
+                if let Some(观察员) = self.单体分析器.get_mut(&周期) {
+                    // Feed a clone of current in-progress K-line for real-time updates
+                    // Note: this may cause duplicate data, matching Python behavior
+                    观察员.增加原始K线(当前K线);
+                }
+            }
+        }
+    }
+
+    /// 获取指定周期的观察者
+    pub fn 获取观察者(&self, 周期: i64) -> Option<&观察者> {
+        self.单体分析器.get(&周期)
+    }
+
+    /// 获取指定周期的观察者（可变）
+    pub fn 获取观察者_mut(&mut self, 周期: i64) -> Option<&mut 观察者> {
+        self.单体分析器.get_mut(&周期)
+    }
+
+    /// 测试_保存数据
+    pub fn 测试_保存数据(&self) {
+        for 周期 in &self.周期组 {
+            if let Some(观察员) = self.单体分析器.get(周期) {
+                观察员.测试_保存数据(None);
+            }
+        }
+    }
+}
diff --git a/chanlun/src/business/observer.rs b/chanlun/src/business/observer.rs
new file mode 100644
index 0000000..c21d95c
--- /dev/null
+++ b/chanlun/src/business/observer.rs
@@ -0,0 +1,503 @@
+use crate::algorithm::bi::笔;
+use crate::algorithm::hub::中枢;
+use crate::algorithm::segment::线段;
+use crate::config::缠论配置;
+use crate::kline::bar::K线;
+use crate::kline::chan_kline::缠论K线;
+use crate::structure::dash_line::虚线;
+use crate::structure::fractal_obj::分型;
+use crate::types::相对方向;
+use crate::utils::datetime;
+use std::rc::Rc;
+
+/// 观察者 — 单周期分析器，持有所有层级序列，接收K线流式输入后逐层计算
+pub struct 观察者 {
+    pub 符号: String,
+    pub 周期: i64,
+    pub 配置: 缠论配置,
+
+    // K线序列
+    pub 普通K线序列: Vec<Rc<K线>>,
+    pub 缠论K线序列: Vec<Rc<缠论K线>>,
+
+    // 分型与笔
+    pub 分型序列: Vec<Rc<分型>>,
+    pub 笔序列: Vec<Rc<虚线>>,
+    pub 笔_中枢序列: Vec<Rc<中枢>>,
+
+    // 线段
+    pub 线段序列: Vec<Rc<虚线>>,
+    pub 中枢序列: Vec<Rc<中枢>>,
+
+    // 扩展线段（笔级）
+    pub 扩展线段序列: Vec<Rc<虚线>>,
+    pub 扩展中枢序列: Vec<Rc<中枢>>,
+
+    // 扩展线段（线段级）
+    pub 扩展线段序列_线段: Vec<Rc<虚线>>,
+    pub 扩展中枢序列_线段: Vec<Rc<中枢>>,
+
+    // 线段之线段
+    pub 线段_线段序列: Vec<Rc<虚线>>,
+    pub 线段_中枢序列: Vec<Rc<中枢>>,
+
+    // 扩展线段之扩展线段
+    pub 扩展线段序列_扩展线段: Vec<Rc<虚线>>,
+    pub 扩展中枢序列_扩展线段: Vec<Rc<中枢>>,
+
+    // 终止时间戳
+    终止时间戳: Option<i64>,
+}
+
+impl 观察者 {
+    pub fn new(符号: String, 周期: i64, 配置: 缠论配置) -> Self {
+        let 终止时间戳 = if 配置.手动终止 != "1970-01-01 00:00:00"
+            && !配置.手动终止.is_empty()
+        {
+            datetime::转化为时间戳(&配置.手动终止)
+        } else {
+            None
+        };
+
+        let mut instance = Self {
+            符号: 符号.clone(),
+            周期,
+            配置,
+            普通K线序列: Vec::new(),
+            缠论K线序列: Vec::new(),
+            分型序列: Vec::new(),
+            笔序列: Vec::new(),
+            笔_中枢序列: Vec::new(),
+            线段序列: Vec::new(),
+            中枢序列: Vec::new(),
+            扩展线段序列: Vec::new(),
+            扩展中枢序列: Vec::new(),
+            扩展线段序列_线段: Vec::new(),
+            扩展中枢序列_线段: Vec::new(),
+            线段_线段序列: Vec::new(),
+            线段_中枢序列: Vec::new(),
+            扩展线段序列_扩展线段: Vec::new(),
+            扩展中枢序列_扩展线段: Vec::new(),
+            终止时间戳,
+        };
+        instance.配置.标识 = 符号;
+        instance
+    }
+
+    /// 标识
+    pub fn 标识(&self) -> String {
+        format!("{}:{}", self.符号, self.周期)
+    }
+
+    /// 当前K线
+    pub fn 当前K线(&self) -> Option<&Rc<K线>> {
+        self.普通K线序列.last()
+    }
+
+    /// 当前缠K
+    pub fn 当前缠K(&self) -> Option<&Rc<缠论K线>> {
+        self.缠论K线序列.last()
+    }
+
+    /// 重置基础序列
+    pub fn 重置基础序列(&mut self) {
+        self.普通K线序列.clear();
+        self.缠论K线序列.clear();
+        self.分型序列.clear();
+        self.笔序列.clear();
+        self.笔_中枢序列.clear();
+        self.线段序列.clear();
+        self.中枢序列.clear();
+        self.扩展线段序列.clear();
+        self.扩展中枢序列.clear();
+        self.扩展线段序列_线段.clear();
+        self.扩展中枢序列_线段.clear();
+        self.线段_线段序列.clear();
+        self.线段_中枢序列.clear();
+        self.扩展线段序列_扩展线段.clear();
+        self.扩展中枢序列_扩展线段.clear();
+    }
+
+    /// 增加原始K线 — 单根K线投喂入口
+    pub fn 增加原始K线(&mut self, 普K: K线) {
+        if let Some(终止) = self.终止时间戳 {
+            if 普K.时间戳 > 终止 {
+                return;
+            }
+        }
+        self.__处理数据(普K);
+    }
+
+    /// 核心数据处理管道
+    fn __处理数据(&mut self, mut 普K: K线) {
+        // Step 1: 缠论K线分析 (普K is consumed by 分析 as &mut)
+        let (_, 当前分型) = 缠论K线::分析(
+            &mut 普K,
+            &mut self.缠论K线序列,
+            &mut self.普通K线序列,
+            &self.配置,
+        );
+        let 当前分型 = match 当前分型 {
+            Some(fx) => fx,
+            None => return,
+        };
+
+        // Step 2: 笔分析
+        if self.配置.分析笔 {
+            笔::分析(
+                当前分型,
+                &mut self.分型序列,
+                &mut self.笔序列,
+                &self.缠论K线序列,
+                &self.普通K线序列,
+                &self.配置,
+            );
+        }
+        if self.分型序列.is_empty() {
+            return;
+        }
+
+        // Step 3: 笔中枢分析
+        if self.配置.分析笔中枢 {
+            中枢::分析(&self.笔序列, &mut self.笔_中枢序列, true, "", 0);
+        }
+        if self.笔序列.is_empty() {
+            return;
+        }
+
+        // Step 4: 线段分析
+        if self.配置.分析线段 {
+            线段::分析(
+                &self.笔序列,
+                &mut self.线段序列,
+                &self.配置,
+                0,
+                &[相对方向::向上, 相对方向::向下],
+            );
+        }
+        // Clone to avoid borrow issues
+        let 线段序列_克隆 = self.线段序列.clone();
+        if self.配置.分析线段中枢 {
+            中枢::分析(&线段序列_克隆, &mut self.中枢序列, true, "", 0);
+        }
+
+        // Step 5: 扩展线段（笔级）
+        let 笔序列_克隆 = self.笔序列.clone();
+        if self.配置.分析扩展线段 {
+            线段::扩展分析(&笔序列_克隆, &mut self.扩展线段序列, &self.配置);
+        }
+        let 扩展线段序列_克隆 = self.扩展线段序列.clone();
+        if self.配置.分析线段中枢 {
+            中枢::分析(&扩展线段序列_克隆, &mut self.扩展中枢序列, true, "", 0);
+        }
+
+        // Step 6: 扩展线段（线段级）
+        let 线段序列_克隆2 = self.线段序列.clone();
+        if self.配置.分析扩展线段 {
+            线段::扩展分析(&线段序列_克隆2, &mut self.扩展线段序列_线段, &self.配置);
+        }
+        let 扩展线段_线段_克隆 = self.扩展线段序列_线段.clone();
+        if self.配置.分析线段中枢 {
+            中枢::分析(
+                &扩展线段_线段_克隆,
+                &mut self.扩展中枢序列_线段,
+                true,
+                "",
+                0,
+            );
+        }
+
+        // Step 7: 线段之线段
+        let 线段序列_克隆3 = self.线段序列.clone();
+        if self.配置.分析线段 {
+            线段::分析(
+                &线段序列_克隆3,
+                &mut self.线段_线段序列,
+                &self.配置,
+                0,
+                &[
+                    相对方向::向下,
+                    相对方向::向上,
+                    相对方向::顺,
+                    相对方向::逆,
+                    相对方向::同,
+                ],
+            );
+        }
+        let 线段_线段_克隆 = self.线段_线段序列.clone();
+        if self.配置.分析线段中枢 {
+            中枢::分析(
+                &线段_线段_克隆,
+                &mut self.线段_中枢序列,
+                true,
+                "",
+                0,
+            );
+        }
+
+        // Step 8: 扩展线段之扩展线段
+        let 扩展线段序列_克隆2 = self.扩展线段序列.clone();
+        if self.配置.分析扩展线段 {
+            线段::扩展分析(
+                &扩展线段序列_克隆2,
+                &mut self.扩展线段序列_扩展线段,
+                &self.配置,
+            );
+        }
+        let 扩展线段_扩展线段_克隆 = self.扩展线段序列_扩展线段.clone();
+        if self.配置.分析线段中枢 {
+            中枢::分析(
+                &扩展线段_扩展线段_克隆,
+                &mut self.扩展中枢序列_扩展线段,
+                true,
+                "",
+                0,
+            );
+        }
+    }
+
+    /// 静态重新分析 — 遍历所有缠K重新生成分型/笔/线段
+    pub fn 静态重新分析(&mut self) {
+        self.分型序列.clear();
+        self.笔序列.clear();
+        self.笔_中枢序列.clear();
+        self.线段序列.clear();
+        self.中枢序列.clear();
+        self.扩展线段序列.clear();
+        self.扩展中枢序列.clear();
+        self.扩展线段序列_线段.clear();
+        self.扩展中枢序列_线段.clear();
+        self.线段_线段序列.clear();
+        self.线段_中枢序列.clear();
+        self.扩展线段序列_扩展线段.clear();
+        self.扩展中枢序列_扩展线段.clear();
+
+        let 缠K克隆 = self.缠论K线序列.clone();
+        let 普K克隆 = self.普通K线序列.clone();
+
+        for i in 1..缠K克隆.len() - 1 {
+            let 当前分型 = 分型::new(
+                Some(Rc::clone(&缠K克隆[i - 1])),
+                Rc::clone(&缠K克隆[i]),
+                Some(Rc::clone(&缠K克隆[i + 1])),
+            );
+            笔::分析(
+                Rc::new(当前分型),
+                &mut self.分型序列,
+                &mut self.笔序列,
+                &缠K克隆,
+                &普K克隆,
+                &self.配置,
+            );
+        }
+
+        if self.配置.分析笔中枢 {
+            中枢::分析(&self.笔序列, &mut self.笔_中枢序列, true, "", 0);
+        }
+
+        let 笔克隆 = self.笔序列.clone();
+        if self.配置.分析线段 {
+            线段::分析(
+                &笔克隆,
+                &mut self.线段序列,
+                &self.配置,
+                0,
+                &[相对方向::向上, 相对方向::向下],
+            );
+        }
+        let 线段克隆 = self.线段序列.clone();
+        if self.配置.分析线段中枢 {
+            中枢::分析(&线段克隆, &mut self.中枢序列, true, "", 0);
+        }
+
+        let 笔克隆2 = self.笔序列.clone();
+        if self.配置.分析扩展线段 {
+            线段::扩展分析(&笔克隆2, &mut self.扩展线段序列, &self.配置);
+        }
+        let 扩展线段克隆 = self.扩展线段序列.clone();
+        if self.配置.分析线段中枢 {
+            中枢::分析(&扩展线段克隆, &mut self.扩展中枢序列, true, "", 0);
+        }
+
+        let 线段克隆2 = self.线段序列.clone();
+        if self.配置.分析扩展线段 {
+            线段::扩展分析(&线段克隆2, &mut self.扩展线段序列_线段, &self.配置);
+        }
+        let 扩展线段_线段_克隆 = self.扩展线段序列_线段.clone();
+        if self.配置.分析线段中枢 {
+            中枢::分析(
+                &扩展线段_线段_克隆,
+                &mut self.扩展中枢序列_线段,
+                true,
+                "",
+                0,
+            );
+        }
+
+        let 线段克隆3 = self.线段序列.clone();
+        if self.配置.分析线段 {
+            线段::分析(
+                &线段克隆3,
+                &mut self.线段_线段序列,
+                &self.配置,
+                0,
+                &[
+                    相对方向::向下,
+                    相对方向::向上,
+                    相对方向::顺,
+                    相对方向::逆,
+                    相对方向::同,
+                ],
+            );
+        }
+        let 线段_线段_克隆 = self.线段_线段序列.clone();
+        if self.配置.分析线段中枢 {
+            中枢::分析(
+                &线段_线段_克隆,
+                &mut self.线段_中枢序列,
+                true,
+                "",
+                0,
+            );
+        }
+    }
+
+    /// 测试_保存数据 — 输出各序列数据文本到文件
+    pub fn 测试_保存数据(&self, root: Option<&str>) {
+
+        let 笔序列_文本数据: Vec<String> = self
+            .笔序列
+            .iter()
+            .map(|b| b.获取数据文本())
+            .collect();
+        let 线段序列_文本数据: Vec<String> = self
+            .线段序列
+            .iter()
+            .map(|s| s.获取数据文本())
+            .collect();
+        let 扩展线段序列_数据文本: Vec<String> = self
+            .扩展线段序列
+            .iter()
+            .map(|s| s.获取数据文本())
+            .collect();
+        let 扩展线段序列_线段_数据文本: Vec<String> = self
+            .扩展线段序列_线段
+            .iter()
+            .map(|s| s.获取数据文本())
+            .collect();
+        let 线段_线段序列_数据文本: Vec<String> = self
+            .线段_线段序列
+            .iter()
+            .map(|s| s.获取数据文本())
+            .collect();
+        let 扩展线段序列_扩展线段_数据文本: Vec<String> = self
+            .扩展线段序列_扩展线段
+            .iter()
+            .map(|s| s.获取数据文本())
+            .collect();
+
+        let 笔_中枢序列_数据文本: Vec<String> = self
+            .笔_中枢序列
+            .iter()
+            .map(|h| h.获取数据文本())
+            .collect();
+        let 中枢序列_数据文本: Vec<String> = self
+            .中枢序列
+            .iter()
+            .map(|h| h.获取数据文本())
+            .collect();
+        let 扩展中枢序列_数据文本: Vec<String> = self
+            .扩展中枢序列
+            .iter()
+            .map(|h| h.获取数据文本())
+            .collect();
+        let 扩展中枢序列_线段_数据文本: Vec<String> = self
+            .扩展中枢序列_线段
+            .iter()
+            .map(|h| h.获取数据文本())
+            .collect();
+        let 线段_中枢序列_数据文本: Vec<String> = self
+            .线段_中枢序列
+            .iter()
+            .map(|h| h.获取数据文本())
+            .collect();
+        let 扩展中枢序列_扩展线段_数据文本: Vec<String> = self
+            .扩展中枢序列_扩展线段
+            .iter()
+            .map(|h| h.获取数据文本())
+            .collect();
+
+        // 确定根目录
+        let 根目录 = match root {
+            Some(r) => std::path::PathBuf::from(r),
+            None => std::env::current_dir().unwrap_or_default(),
+        };
+
+        // 生成子目录名称
+        let 起始时间 = self.普通K线序列.first().map(|k| k.时间戳).unwrap_or(0);
+        let 结束时间 = self.普通K线序列.last().map(|k| k.时间戳).unwrap_or(0);
+        let 目录标识 = format!("Rust_{}_{}_{}", self.符号, 起始时间, 结束时间);
+
+        let 保存路径 = 根目录.join(&目录标识);
+        if let Err(e) = std::fs::create_dir_all(&保存路径) {
+            eprintln!("创建目录失败: {} -> {}", 保存路径.display(), e);
+            return;
+        }
+
+        let 数据映射: Vec<(&str, &[String])> = vec![
+            ("笔序列_文本数据", &笔序列_文本数据),
+            ("线段序列_文本数据", &线段序列_文本数据),
+            ("扩展线段序列_数据文本", &扩展线段序列_数据文本),
+            ("扩展线段序列_线段_数据文本", &扩展线段序列_线段_数据文本),
+            ("线段_线段序列_数据文本", &线段_线段序列_数据文本),
+            ("扩展线段序列_扩展线段_数据文本", &扩展线段序列_扩展线段_数据文本),
+            ("笔_中枢序列_数据文本", &笔_中枢序列_数据文本),
+            ("中枢序列_数据文本", &中枢序列_数据文本),
+            ("扩展中枢序列_数据文本", &扩展中枢序列_数据文本),
+            ("扩展中枢序列_线段_数据文本", &扩展中枢序列_线段_数据文本),
+            ("线段_中枢序列_数据文本", &线段_中枢序列_数据文本),
+            ("扩展中枢序列_扩展线段_数据文本", &扩展中枢序列_扩展线段_数据文本),
+        ];
+
+        for (文件名, 数据列表) in &数据映射 {
+            let 文件路径 = 保存路径.join(format!("{}.txt", 文件名));
+            let 内容 = 数据列表.join("\n") + "\n";
+            if let Err(e) = std::fs::write(&文件路径, &内容) {
+                eprintln!("写入文件失败: {} -> {}", 文件路径.display(), e);
+            }
+        }
+
+        println!("全部数据拆分保存完成，目录：{}", 保存路径.display());
+    }
+
+    /// 读取数据文件 — 从 .nb 文件加载数据
+    pub fn 读取数据文件(文件路径: &str, 配置: Option<缠论配置>) -> Result<Self, String> {
+        let 配置 = 配置.unwrap_or_default();
+
+        // Parse filename: btcusd-300-1631772074-1632222374.nb
+        let path = std::path::Path::new(文件路径);
+        let name = path
+            .file_stem()
+            .and_then(|n| n.to_str())
+            .ok_or("invalid filename")?;
+        let parts: Vec<&str> = name.split('-').collect();
+        if parts.len() < 4 {
+            return Err(format!("invalid filename format: {}", name));
+        }
+        let 符号 = parts[0].to_string();
+        let 周期: i64 = parts[1].parse().map_err(|e| format!("parse period: {}", e))?;
+
+        let mut 实例 = Self::new(符号, 周期, 配置);
+
+        let data = std::fs::read(文件路径).map_err(|e| format!("read file: {}", e))?;
+        let size = 48; // 6 × 8 bytes (big-endian double)
+        for i in 0..data.len() / size {
+            let offset = i * size;
+            if let Some(k线) = K线::from_bytes(&data[offset..offset + size], 周期, "nb") {
+                实例.增加原始K线(k线);
+            }
+        }
+
+        Ok(实例)
+    }
+}
diff --git a/chanlun/src/business/synthesizer.rs b/chanlun/src/business/synthesizer.rs
new file mode 100644
index 0000000..31a7780
--- /dev/null
+++ b/chanlun/src/business/synthesizer.rs
@@ -0,0 +1,115 @@
+use crate::kline::bar::K线;
+use std::collections::HashMap;
+
+/// K线合成器 — 将小周期K线合成为大周期K线
+pub struct K线合成器 {
+    pub 标识: String,
+    pub 周期组: Vec<i64>,
+    pub 当前K线: HashMap<i64, Option<K线>>,
+    pub 合成K线列表: HashMap<i64, Vec<K线>>,
+}
+
+impl K线合成器 {
+    pub fn new(标识: String, 周期组: Vec<i64>) -> Self {
+        let mut 周期组 = 周期组;
+        周期组.sort();
+
+        let mut 当前K线 = HashMap::new();
+        let mut 合成K线列表 = HashMap::new();
+        for &周期 in &周期组 {
+            当前K线.insert(周期, None);
+            合成K线列表.insert(周期, Vec::new());
+        }
+
+        Self {
+            标识,
+            周期组,
+            当前K线,
+            合成K线列表,
+        }
+    }
+
+    /// 投喂K线 — 输入最小周期K线，合成为所有目标周期
+    pub fn 投喂K线(&mut self, 普K: K线) {
+        let 周期组 = self.周期组.clone();
+        for 周期 in 周期组 {
+            self._处理单个周期(周期, &普K);
+        }
+    }
+
+    fn _处理单个周期(&mut self, 周期: i64, 普K: &K线) {
+        let 目标时间戳 = self._对齐时间戳(普K.时间戳, 周期);
+        let 当前K线 = self.当前K线.get(&周期).unwrap().clone();
+
+        if 当前K线.is_none() {
+            // 创建新K线
+            let 新K线 = self._创建新K线(周期, 目标时间戳, 普K);
+            *self.当前K线.get_mut(&周期).unwrap() = Some(新K线);
+        } else if 当前K线.as_ref().unwrap().时间戳 == 目标时间戳 {
+            // 更新当前K线
+            let mut k线 = 当前K线.unwrap();
+            self._更新K线(&mut k线, 普K);
+            *self.当前K线.get_mut(&周期).unwrap() = Some(k线);
+        } else {
+            // 完成当前K线，创建新K线
+            self._完成K线(周期);
+            let 新K线 = self._创建新K线(周期, 目标时间戳, 普K);
+            *self.当前K线.get_mut(&周期).unwrap() = Some(新K线);
+        }
+    }
+
+    fn _对齐时间戳(&self, 时间戳: i64, 周期: i64) -> i64 {
+        if 周期 == 0 {
+            return 时间戳;
+        }
+        (时间戳 / 周期) * 周期
+    }
+
+    fn _创建新K线(&self, 周期: i64, 时间戳: i64, 普K: &K线) -> K线 {
+        let 序号 = self
+            .合成K线列表
+            .get(&周期)
+            .and_then(|list| list.last())
+            .map(|k| k.序号 + 1)
+            .unwrap_or(0);
+
+        K线::创建普K(
+            &self.标识,
+            时间戳,
+            普K.开盘价,
+            普K.高,
+            普K.低,
+            普K.收盘价,
+            普K.成交量,
+            序号,
+            周期,
+        )
+    }
+
+    fn _更新K线(&self, 当前K线: &mut K线, 新数据: &K线) {
+        当前K线.高 = 当前K线.高.max(新数据.高);
+        当前K线.低 = 当前K线.低.min(新数据.低);
+        当前K线.收盘价 = 新数据.收盘价;
+        当前K线.成交量 += 新数据.成交量;
+    }
+
+    fn _完成K线(&mut self, 周期: i64) {
+        let 当前K线 = self.当前K线.get(&周期).and_then(|k| k.clone());
+        if let Some(mut k线) = 当前K线 {
+            k线.序号 = self
+                .合成K线列表
+                .get(&周期)
+                .and_then(|list| list.last())
+                .map(|k| k.序号 + 1)
+                .unwrap_or(0);
+
+            self.合成K线列表.get_mut(&周期).unwrap().push(k线);
+            *self.当前K线.get_mut(&周期).unwrap() = None;
+        }
+    }
+
+    /// 获取指定周期当前正在合成的K线
+    pub fn 获取当前K线(&self, 周期: i64) -> Option<&K线> {
+        self.当前K线.get(&周期).and_then(|k| k.as_ref())
+    }
+}
diff --git a/chanlun/src/config.rs b/chanlun/src/config.rs
new file mode 100644
index 0000000..5911544
--- /dev/null
+++ b/chanlun/src/config.rs
@@ -0,0 +1,338 @@
+use serde::{Deserialize, Serialize};
+
+fn is_infinite_f64(v: &f64) -> bool {
+    v.is_infinite()
+}
+
+/// 缠论配置 —— 控制所有分析阶段的行为
+///
+/// 所有字段带默认值，使用 `#[serde(default)]` 实现缺失字段容错
+#[derive(Debug, Clone, Serialize, Deserialize)]
+#[serde(default)]
+pub struct 缠论配置 {
+    // ---- 基础 ----
+    pub 标识: String,
+
+    // ---- 缠K ----
+    pub 缠K合并替换: bool,
+
+    // ---- 笔 ----
+    pub 笔内元素数量: i64,
+    pub 笔内相同终点取舍: bool,
+    pub 笔内起始分型包含整笔: bool,
+    pub 笔内起始分型包含整笔_包括右: bool,
+    pub 笔内原始K线包含整笔: bool,
+    pub 笔次级成笔: bool,
+    pub 笔弱化: bool,
+    pub 笔弱化_原始数量: i64,
+
+    // ---- 线段 ----
+    pub 线段_非缺口下穿刺: bool,
+    pub 线段_特征序列忽视老阴老阳: bool,
+    pub 线段_缺口后紧急修正: bool,
+    pub 线段_修正: bool,
+    pub 线段内部中枢图显: bool,
+    pub 扩展线段_当下分析: bool,
+
+    // ---- 分析开关 ----
+    pub 分析笔: bool,
+    pub 分析线段: bool,
+    pub 分析扩展线段: bool,
+    pub 分析笔中枢: bool,
+    pub 分析线段中枢: bool,
+
+    // ---- 终止 ----
+    pub 手动终止: String,
+
+    // ---- 指标 ----
+    pub 计算指标: bool,
+    pub 指标计算方式: String,
+
+    // ---- MACD ----
+    pub 平滑异同移动平均线_快线周期: i64,
+    pub 平滑异同移动平均线_慢线周期: i64,
+    pub 平滑异同移动平均线_信号周期: i64,
+
+    // ---- RSI ----
+    pub 相对强弱指数_周期: i64,
+    pub 相对强弱指数_移动平均线周期: i64,
+    pub 相对强弱指数_超买阈值: f64,
+    pub 相对强弱指数_超卖阈值: f64,
+
+    // ---- KDJ ----
+    pub 随机指标_RSV周期: i64,
+    pub 随机指标_K值平滑周期: i64,
+    pub 随机指标_D值平滑周期: i64,
+    pub 随机指标_超买阈值: f64,
+    pub 随机指标_超卖阈值: f64,
+
+    // ---- 推送/显示 ----
+    pub 图表展示: bool,
+    pub 推送K线: bool,
+    pub 推送笔: bool,
+    pub 推送线段: bool,
+    pub 推送中枢: bool,
+
+    // ---- 图表展示细分 ----
+    pub 图表展示_笔: bool,
+    pub 图表展示_线段: bool,
+    pub 图表展示_扩展线段: bool,
+    pub 图表展示_扩展线段_线段: bool,
+    pub 图表展示_线段_线段: bool,
+    pub 图表展示_中枢_笔: bool,
+    pub 图表展示_中枢_线段: bool,
+    pub 图表展示_中枢_扩展线段: bool,
+    pub 图表展示_中枢_扩展线段_线段: bool,
+    pub 图表展示_中枢_线段_线段: bool,
+    pub 图表展示_中枢_线段内部: bool,
+
+    // ---- 买卖点 ----
+    pub 买卖点偏移: i64,
+    pub 买卖点激进识别: bool,
+    pub 买卖点与MACD柱强相关: bool,
+    pub 买卖点错过误差值: f64,
+    pub 买卖点_指标模式: String,
+    pub 买卖点_指标匹配_MACD: bool,
+    pub 买卖点_指标匹配_KDJ: bool,
+    pub 买卖点_指标匹配_RSI: bool,
+    #[serde(skip_serializing_if = "is_infinite_f64")]
+    pub 买卖点_背离率: f64,
+    pub 买卖点_T2_回调阈值: f64,
+    pub 买卖点_T2S_最大层级: i64,
+    pub 买卖点_峰值条件: bool,
+    pub 买卖点_计算方式: String,
+    pub 买卖点_计算线段BSP1: bool,
+    pub 买卖点_处理BSP2: bool,
+    pub 买卖点_计算线段BSP3: bool,
+    pub 买卖点_依赖T1: bool,
+    pub 买卖点_中枢来源: String,
+    pub 买卖点_调试输出: bool,
+
+    // ---- 背驰 ----
+    pub 线段内部背驰_MACD: bool,
+    pub 线段内部背驰_斜率: bool,
+    pub 线段内部背驰_测度: bool,
+    pub 线段内部背驰_模式: String,
+
+    // ---- 文件 ----
+    pub 加载文件路径: String,
+}
+
+impl Default for 缠论配置 {
+    fn default() -> Self {
+        Self {
+            标识: "bar".into(),
+            缠K合并替换: false,
+            笔内元素数量: 5,
+            笔内相同终点取舍: false,
+            笔内起始分型包含整笔: false,
+            笔内起始分型包含整笔_包括右: false,
+            笔内原始K线包含整笔: false,
+            笔次级成笔: false,
+            笔弱化: false,
+            笔弱化_原始数量: 3,
+            线段_非缺口下穿刺: false,
+            线段_特征序列忽视老阴老阳: false,
+            线段_缺口后紧急修正: true,
+            线段_修正: false,
+            线段内部中枢图显: true,
+            扩展线段_当下分析: false,
+            分析笔: true,
+            分析线段: true,
+            分析扩展线段: true,
+            分析笔中枢: true,
+            分析线段中枢: true,
+            手动终止: String::new(),
+            计算指标: true,
+            指标计算方式: "收".into(),
+            平滑异同移动平均线_快线周期: 13,
+            平滑异同移动平均线_慢线周期: 31,
+            平滑异同移动平均线_信号周期: 11,
+            相对强弱指数_周期: 13,
+            相对强弱指数_移动平均线周期: 13,
+            相对强弱指数_超买阈值: 75.0,
+            相对强弱指数_超卖阈值: 25.0,
+            随机指标_RSV周期: 13,
+            随机指标_K值平滑周期: 5,
+            随机指标_D值平滑周期: 5,
+            随机指标_超买阈值: 80.0,
+            随机指标_超卖阈值: 20.0,
+            图表展示: true,
+            推送K线: true,
+            推送笔: true,
+            推送线段: true,
+            推送中枢: true,
+            图表展示_笔: true,
+            图表展示_线段: true,
+            图表展示_扩展线段: true,
+            图表展示_扩展线段_线段: true,
+            图表展示_线段_线段: true,
+            图表展示_中枢_笔: true,
+            图表展示_中枢_线段: true,
+            图表展示_中枢_扩展线段: true,
+            图表展示_中枢_扩展线段_线段: true,
+            图表展示_中枢_线段_线段: true,
+            图表展示_中枢_线段内部: true,
+            买卖点偏移: 1,
+            买卖点激进识别: false,
+            买卖点与MACD柱强相关: false,
+            买卖点错过误差值: 0.01,
+            买卖点_指标模式: "配置".into(),
+            买卖点_指标匹配_MACD: true,
+            买卖点_指标匹配_KDJ: true,
+            买卖点_指标匹配_RSI: true,
+            买卖点_背离率: f64::INFINITY,
+            买卖点_T2_回调阈值: 1.0,
+            买卖点_T2S_最大层级: 3,
+            买卖点_峰值条件: false,
+            买卖点_计算方式: "峰".into(),
+            买卖点_计算线段BSP1: true,
+            买卖点_处理BSP2: true,
+            买卖点_计算线段BSP3: true,
+            买卖点_依赖T1: true,
+            买卖点_中枢来源: "合".into(),
+            买卖点_调试输出: false,
+            线段内部背驰_MACD: true,
+            线段内部背驰_斜率: true,
+            线段内部背驰_测度: true,
+            线段内部背驰_模式: "相对".into(),
+            加载文件路径: "./templates/last.nb".into(),
+        }
+    }
+}
+
+impl 缠论配置 {
+    pub fn to_json(&self) -> String {
+        serde_json::to_string_pretty(self).unwrap_or_default()
+    }
+
+    pub fn from_json(json_str: &str) -> Result<Self, serde_json::Error> {
+        serde_json::from_str(json_str)
+    }
+
+    pub fn 保存配置(&self, path: &str) -> std::io::Result<()> {
+        std::fs::write(path, self.to_json())
+    }
+
+    pub fn 加载配置(path: &str) -> Result<Self, Box<dyn std::error::Error>> {
+        let content = std::fs::read_to_string(path)?;
+        let config = Self::from_json(&content)?;
+        Ok(config)
+    }
+
+    /// 返回一个关闭所有推送/显示的新配置
+    pub fn 不推送(&self) -> Self {
+        Self {
+            图表展示: false,
+            推送K线: false,
+            推送笔: false,
+            推送线段: false,
+            推送中枢: false,
+            图表展示_笔: false,
+            图表展示_线段: false,
+            图表展示_扩展线段: false,
+            图表展示_扩展线段_线段: false,
+            图表展示_线段_线段: false,
+            图表展示_中枢_笔: false,
+            图表展示_中枢_线段: false,
+            图表展示_中枢_扩展线段: false,
+            图表展示_中枢_扩展线段_线段: false,
+            图表展示_中枢_线段_线段: false,
+            图表展示_中枢_线段内部: false,
+            ..self.clone()
+        }
+    }
+
+    /// 按序号重组字典 — 兼容旧版配置的复合key格式
+    pub fn 按序号重组字典(默认配置: &Self, 原始字典: &serde_json::Value) -> Vec<(i64, Self)> {
+        let mut result = Vec::new();
+        if let serde_json::Value::Object(map) = 原始字典 {
+            // 按数字前缀分组: "1_open" → group 1 key "open"
+            let mut groups: std::collections::BTreeMap<i64, serde_json::Map<String, serde_json::Value>> =
+                std::collections::BTreeMap::new();
+            for (key, value) in map {
+                if let Some(pos) = key.find('_') {
+                    if let Ok(num) = key[..pos].parse::<i64>() {
+                        let field = key[pos + 1..].to_string();
+                        groups
+                            .entry(num)
+                            .or_default()
+                            .insert(field, value.clone());
+                    }
+                }
+            }
+            for (num, fields) in groups {
+                let mut config = 默认配置.clone();
+                if let Ok(partial) = serde_json::from_value::<缠论配置>(serde_json::Value::Object(fields)) {
+                    // merge partial into config (override matching fields)
+                    config = partial;
+                }
+                result.push((num, config));
+            }
+        }
+        result
+    }
+
+    /// 对比两个配置，返回差异字段
+    pub fn 对比(&self, other: &Self) -> Vec<String> {
+        let mut diffs = Vec::new();
+        let self_json = serde_json::to_value(self).unwrap();
+        let other_json = serde_json::to_value(other).unwrap();
+        if let (serde_json::Value::Object(self_map), serde_json::Value::Object(other_map)) =
+            (&self_json, &other_json)
+        {
+            for (key, self_val) in self_map {
+                if let Some(other_val) = other_map.get(key) {
+                    if self_val != other_val {
+                        diffs.push(key.clone());
+                    }
+                }
+            }
+        }
+        diffs
+    }
+}
+
+#[cfg(test)]
+mod tests {
+    use super::*;
+
+    #[test]
+    fn test_default_config_roundtrip() {
+        let config = 缠论配置::default();
+        let json = config.to_json();
+        let parsed: 缠论配置 = 缠论配置::from_json(&json).unwrap();
+        let json2 = parsed.to_json();
+        assert_eq!(json, json2);
+    }
+
+    #[test]
+    fn test_default_values() {
+        let config = 缠论配置::default();
+        assert_eq!(config.标识, "bar");
+        assert_eq!(config.笔内元素数量, 5);
+        assert!(config.买卖点_背离率.is_infinite());
+        assert_eq!(config.指标计算方式, "收");
+    }
+
+    #[test]
+    fn test_partial_deserialize() {
+        let json = r#"{"标识": "custom", "笔内元素数量": 7}"#;
+        let config: 缠论配置 = serde_json::from_str(json).unwrap();
+        assert_eq!(config.标识, "custom");
+        assert_eq!(config.笔内元素数量, 7);
+        // 未指定字段使用默认值
+        assert_eq!(config.买卖点偏移, 1);
+    }
+
+    #[test]
+    fn test_不推送() {
+        let config = 缠论配置::default();
+        let muted = config.不推送();
+        assert!(!muted.推送K线);
+        assert!(!muted.推送笔);
+        assert!(!muted.图表展示);
+        // 其他字段不变
+        assert_eq!(muted.笔内元素数量, 5);
+    }
+}
diff --git a/chanlun/src/indicators/kdj.rs b/chanlun/src/indicators/kdj.rs
new file mode 100644
index 0000000..470a560
--- /dev/null
+++ b/chanlun/src/indicators/kdj.rs
@@ -0,0 +1,204 @@
+use serde::{Deserialize, Serialize};
+
+/// 随机指标 (KDJ)
+///
+/// 使用滑动窗口 + 逐值平滑进行增量计算
+#[derive(Debug, Clone, Serialize, Deserialize)]
+#[serde(default)]
+pub struct 随机指标 {
+    pub 时间戳: i64,
+    pub 最高价: f64,
+    pub 最低价: f64,
+    pub 收盘价: f64,
+    pub N: i64,
+    pub M1: i64,
+    pub M2: i64,
+    pub 超买阈值: f64,
+    pub 超卖阈值: f64,
+    pub RSV: Option<f64>,
+    pub K: Option<f64>,
+    pub D: Option<f64>,
+    pub J: Option<f64>,
+    pub 历史最高价队列: Vec<f64>,
+    pub 历史最低价队列: Vec<f64>,
+    pub 前一个RSV: Option<f64>,
+    pub 前一个K: Option<f64>,
+    pub 前一个D: Option<f64>,
+}
+
+impl Default for 随机指标 {
+    fn default() -> Self {
+        Self {
+            时间戳: 0,
+            最高价: 0.0,
+            最低价: 0.0,
+            收盘价: 0.0,
+            N: 9,
+            M1: 3,
+            M2: 3,
+            超买阈值: 80.0,
+            超卖阈值: 20.0,
+            RSV: None,
+            K: None,
+            D: None,
+            J: None,
+            历史最高价队列: Vec::new(),
+            历史最低价队列: Vec::new(),
+            前一个RSV: None,
+            前一个K: None,
+            前一个D: None,
+        }
+    }
+}
+
+impl 随机指标 {
+    /// 首次计算 KDJ（无历史数据时）
+    pub fn 首次计算(
+        初始最高价: f64,
+        初始最低价: f64,
+        初始收盘价: f64,
+        初始时间: i64,
+        N: i64,
+        M1: i64,
+        M2: i64,
+        超买阈值: f64,
+        超卖阈值: f64,
+    ) -> Self {
+        Self {
+            时间戳: 初始时间,
+            最高价: 初始最高价,
+            最低价: 初始最低价,
+            收盘价: 初始收盘价,
+            N,
+            M1,
+            M2,
+            超买阈值,
+            超卖阈值,
+            RSV: None,
+            K: None,
+            D: None,
+            J: None,
+            历史最高价队列: vec![初始最高价],
+            历史最低价队列: vec![初始最低价],
+            前一个RSV: None,
+            前一个K: None,
+            前一个D: None,
+        }
+    }
+
+    /// 基于前一个 KDJ 增量计算当前 KDJ
+    pub fn 增量计算(前一个KDJ: &Self, 当前最高价: f64, 当前最低价: f64, 当前收盘价: f64, 当前时间: i64) -> Self {
+        let N = 前一个KDJ.N;
+        let M1 = 前一个KDJ.M1;
+        let M2 = 前一个KDJ.M2;
+        let 超买阈值 = 前一个KDJ.超买阈值;
+        let 超卖阈值 = 前一个KDJ.超卖阈值;
+
+        // 更新历史最高价队列
+        let mut 历史最高价 = 前一个KDJ.历史最高价队列.clone();
+        历史最高价.push(当前最高价);
+        if 历史最高价.len() > N as usize {
+            历史最高价.remove(0);
+        }
+
+        // 更新历史最低价队列
+        let mut 历史最低价 = 前一个KDJ.历史最低价队列.clone();
+        历史最低价.push(当前最低价);
+        if 历史最低价.len() > N as usize {
+            历史最低价.remove(0);
+        }
+
+        // RSV
+        let RSV = if 历史最高价.len() == N as usize && 历史最低价.len() == N as usize {
+            let highest = 历史最高价.iter().cloned().fold(f64::NEG_INFINITY, f64::max);
+            let lowest = 历史最低价.iter().cloned().fold(f64::INFINITY, f64::min);
+            if (highest - lowest).abs() > f64::EPSILON {
+                Some((当前收盘价 - lowest) / (highest - lowest) * 100.0)
+            } else {
+                Some(50.0)
+            }
+        } else {
+            None
+        };
+
+        // K值
+        let K = match RSV {
+            Some(rsv) => match 前一个KDJ.K {
+                None => Some(rsv),
+                Some(prev_k) => Some((prev_k * (M1 - 1) as f64 + rsv) / M1 as f64),
+            },
+            None => 前一个KDJ.K,
+        };
+
+        // D值
+        let D = match K {
+            Some(k) => match 前一个KDJ.D {
+                None => Some(k),
+                Some(prev_d) => Some((prev_d * (M2 - 1) as f64 + k) / M2 as f64),
+            },
+            None => 前一个KDJ.D,
+        };
+
+        // J值
+        let J = match (K, D) {
+            (Some(k), Some(d)) => Some(3.0 * k - 2.0 * d),
+            _ => None,
+        };
+
+        Self {
+            时间戳: 当前时间,
+            最高价: 当前最高价,
+            最低价: 当前最低价,
+            收盘价: 当前收盘价,
+            N,
+            M1,
+            M2,
+            超买阈值,
+            超卖阈值,
+            RSV,
+            K,
+            D,
+            J,
+            历史最高价队列: 历史最高价,
+            历史最低价队列: 历史最低价,
+            前一个RSV: RSV,
+            前一个K: K,
+            前一个D: D,
+        }
+    }
+}
+
+#[cfg(test)]
+mod tests {
+    use super::*;
+
+    #[test]
+    fn test_first_calc() {
+        let kdj = 随机指标::首次计算(110.0, 90.0, 100.0, 1000, 9, 3, 3, 80.0, 20.0);
+        assert_eq!(kdj.历史最高价队列, vec![110.0]);
+        assert_eq!(kdj.历史最低价队列, vec![90.0]);
+        assert_eq!(kdj.K, None);
+    }
+
+    #[test]
+    fn test_incremental_after_n_bars() {
+        let mut kdj = 随机指标::首次计算(110.0, 90.0, 100.0, 1000, 5, 3, 3, 80.0, 20.0);
+
+        // 喂入足够数据填充窗口
+        let data = [
+            (112.0, 91.0, 105.0),
+            (115.0, 93.0, 110.0),
+            (113.0, 95.0, 108.0),
+            (116.0, 98.0, 112.0),
+            (118.0, 100.0, 115.0),
+        ];
+        for (i, (高, 低, 收)) in data.iter().enumerate() {
+            kdj = 随机指标::增量计算(&kdj, *高, *低, *收, 1001 + i as i64);
+        }
+
+        // 窗口填满后 KDJ 应有值
+        assert!(kdj.K.is_some());
+        assert!(kdj.D.is_some());
+        assert!(kdj.J.is_some());
+    }
+}
diff --git a/chanlun/src/indicators/macd.rs b/chanlun/src/indicators/macd.rs
new file mode 100644
index 0000000..0883b8c
--- /dev/null
+++ b/chanlun/src/indicators/macd.rs
@@ -0,0 +1,149 @@
+use serde::{Deserialize, Serialize};
+
+/// 平滑异同移动平均线 (MACD)
+///
+/// 使用 EMA 递推算法进行增量计算
+#[derive(Debug, Clone, Serialize, Deserialize)]
+#[serde(default)]
+pub struct 平滑异同移动平均线 {
+    pub 时间戳: i64,
+    pub 收盘价: f64,
+    pub 快线周期: i64,
+    pub 慢线周期: i64,
+    pub 信号周期: i64,
+    pub DIF: Option<f64>,
+    pub DEA: Option<f64>,
+    #[serde(rename = "MACD柱")]
+    #[serde(default)]
+    pub MACD柱: f64,
+    pub 快线EMA: Option<f64>,
+    pub 慢线EMA: Option<f64>,
+    pub DEA_EMA: Option<f64>,
+}
+
+impl Default for 平滑异同移动平均线 {
+    fn default() -> Self {
+        Self {
+            时间戳: 0,
+            收盘价: 0.0,
+            快线周期: 12,
+            慢线周期: 26,
+            信号周期: 9,
+            DIF: None,
+            DEA: None,
+            MACD柱: 0.0,
+            快线EMA: None,
+            慢线EMA: None,
+            DEA_EMA: None,
+        }
+    }
+}
+
+fn 平滑系数(周期: i64) -> f64 {
+    2.0 / (周期 as f64 + 1.0)
+}
+
+impl 平滑异同移动平均线 {
+    /// 首次计算 MACD 指标（无历史数据时使用）
+    pub fn 首次计算(初始收盘价: f64, 初始时间: i64, 快线周期: i64, 慢线周期: i64, 信号周期: i64) -> Self {
+        let 快线EMA = 初始收盘价;
+        let 慢线EMA = 初始收盘价;
+        let DIF = 快线EMA - 慢线EMA;
+        let DEA_EMA = DIF;
+        let MACD柱 = DIF - DEA_EMA;
+
+        Self {
+            时间戳: 初始时间,
+            收盘价: 初始收盘价,
+            快线周期,
+            慢线周期,
+            信号周期,
+            DIF: Some(DIF),
+            DEA: Some(DEA_EMA),
+            MACD柱,
+            快线EMA: Some(快线EMA),
+            慢线EMA: Some(慢线EMA),
+            DEA_EMA: Some(DEA_EMA),
+        }
+    }
+
+    /// 基于前一个 MACD 指标增量计算当前 MACD
+    pub fn 增量计算(前一个MACD: &Self, 当前收盘价: f64, 当前时间: i64) -> Self {
+        // 快线 EMA
+        let 快线EMA = match 前一个MACD.快线EMA {
+            Some(prev) => {
+                当前收盘价 * 平滑系数(前一个MACD.快线周期)
+                    + prev * ((前一个MACD.快线周期 - 1) as f64 / (前一个MACD.快线周期 + 1) as f64)
+            }
+            None => 当前收盘价,
+        };
+
+        // 慢线 EMA
+        let 慢线EMA = match 前一个MACD.慢线EMA {
+            Some(prev) => {
+                当前收盘价 * 平滑系数(前一个MACD.慢线周期)
+                    + prev * ((前一个MACD.慢线周期 - 1) as f64 / (前一个MACD.慢线周期 + 1) as f64)
+            }
+            None => 当前收盘价,
+        };
+
+        // DIF
+        let DIF = 快线EMA - 慢线EMA;
+
+        // DEA_EMA
+        let DEA_EMA = match 前一个MACD.DEA_EMA {
+            Some(prev) => {
+                DIF * 平滑系数(前一个MACD.信号周期)
+                    + prev * ((前一个MACD.信号周期 - 1) as f64 / (前一个MACD.信号周期 + 1) as f64)
+            }
+            None => DIF,
+        };
+
+        // MACD 柱 (注意: Python 版没有 ×2)
+        let MACD柱 = DIF - DEA_EMA;
+
+        Self {
+            时间戳: 当前时间,
+            收盘价: 当前收盘价,
+            快线周期: 前一个MACD.快线周期,
+            慢线周期: 前一个MACD.慢线周期,
+            信号周期: 前一个MACD.信号周期,
+            DIF: Some(DIF),
+            DEA: Some(DEA_EMA),
+            MACD柱,
+            快线EMA: Some(快线EMA),
+            慢线EMA: Some(慢线EMA),
+            DEA_EMA: Some(DEA_EMA),
+        }
+    }
+}
+
+#[cfg(test)]
+mod tests {
+    use super::*;
+
+    #[test]
+    fn test_first_calc() {
+        let macd = 平滑异同移动平均线::首次计算(100.0, 1000, 12, 26, 9);
+        assert_eq!(macd.DIF, Some(0.0));
+        assert_eq!(macd.MACD柱, 0.0);
+        assert_eq!(macd.快线EMA, Some(100.0));
+        assert_eq!(macd.慢线EMA, Some(100.0));
+    }
+
+    #[test]
+    fn test_incremental_calc() {
+        let first = 平滑异同移动平均线::首次计算(100.0, 1000, 12, 26, 9);
+
+        // 价格上升
+        let second = 平滑异同移动平均线::增量计算(&first, 102.0, 1001);
+        assert!(second.DIF.unwrap() > 0.0);
+        // 快线EMA 应该比慢线EMA 变化更快
+        assert!(second.快线EMA.unwrap() > second.慢线EMA.unwrap());
+
+        // 价格下降
+        let third = 平滑异同移动平均线::增量计算(&second, 98.0, 1002);
+        // DIF 应该变小
+        assert!(third.DIF.unwrap() < second.DIF.unwrap());
+    }
+}
diff --git a/chanlun/src/indicators/mod.rs b/chanlun/src/indicators/mod.rs
new file mode 100644
index 0000000..f1258ab
--- /dev/null
+++ b/chanlun/src/indicators/mod.rs
@@ -0,0 +1,21 @@
+pub mod macd;
+pub mod kdj;
+pub mod rsi;
+
+pub use macd::平滑异同移动平均线;
+pub use kdj::随机指标;
+pub use rsi::相对强弱指数;
+
+/// K线取值 —— 根据计算方式从K线提取对应的价格
+pub fn K线取值(开盘价: f64, 高: f64, 低: f64, 收盘价: f64, 计算方式: &str) -> f64 {
+    match 计算方式 {
+        "开" => 开盘价,
+        "高" => 高,
+        "低" => 低,
+        "收" => 收盘价,
+        "高低均值" => (高 + 低) / 2.0,
+        "高低收均值" => (高 + 低 + 收盘价) / 3.0,
+        "开高低收均值" => (高 + 低 + 开盘价 + 收盘价) / 4.0,
+        _ => 收盘价,
+    }
+}
diff --git a/chanlun/src/indicators/rsi.rs b/chanlun/src/indicators/rsi.rs
new file mode 100644
index 0000000..a65210c
--- /dev/null
+++ b/chanlun/src/indicators/rsi.rs
@@ -0,0 +1,180 @@
+use serde::{Deserialize, Serialize};
+
+/// 相对强弱指数 (RSI)
+///
+/// 使用 Wilder 平滑（RMA）进行增量计算
+#[derive(Debug, Clone, Serialize, Deserialize)]
+#[serde(default)]
+pub struct 相对强弱指数 {
+    pub 时间戳: i64,
+    pub 收盘价: f64,
+    pub 周期: i64,
+    pub 超买阈值: f64,
+    pub 超卖阈值: f64,
+    pub RSI_SMA周期: Option<i64>,
+    pub RSI: Option<f64>,
+    pub 平均上涨: Option<f64>,
+    pub 平均下跌: Option<f64>,
+    pub 上涨幅度: f64,
+    pub 下跌幅度: f64,
+    pub 平滑系数: f64,
+    pub RSI_SMA: Option<f64>,
+    pub RSI历史队列: Vec<f64>,
+}
+
+impl Default for 相对强弱指数 {
+    fn default() -> Self {
+        Self {
+            时间戳: 0,
+            收盘价: 0.0,
+            周期: 14,
+            超买阈值: 70.0,
+            超卖阈值: 30.0,
+            RSI_SMA周期: None,
+            RSI: None,
+            平均上涨: None,
+            平均下跌: None,
+            上涨幅度: 0.0,
+            下跌幅度: 0.0,
+            平滑系数: 0.0,
+            RSI_SMA: None,
+            RSI历史队列: Vec::new(),
+        }
+    }
+}
+
+impl 相对强弱指数 {
+    /// 首次计算 RSI（历史数据不足时）
+    pub fn 首次计算(
+        初始收盘价: f64,
+        初始时间: i64,
+        周期: i64,
+        超买阈值: f64,
+        超卖阈值: f64,
+        RSI_SMA周期: Option<i64>,
+    ) -> Self {
+        Self {
+            时间戳: 初始时间,
+            收盘价: 初始收盘价,
+            周期,
+            超买阈值,
+            超卖阈值,
+            RSI_SMA周期,
+            RSI: None,
+            平均上涨: Some(0.0),
+            平均下跌: Some(0.0),
+            上涨幅度: 0.0,
+            下跌幅度: 0.0,
+            平滑系数: 1.0 / 周期 as f64,
+            RSI_SMA: None,
+            RSI历史队列: Vec::new(),
+        }
+    }
+
+    /// 基于前一个 RSI 增量计算当前 RSI
+    pub fn 增量计算(前一个RSI: &Self, 当前收盘价: f64, 当前时间: i64) -> Self {
+        let 周期 = 前一个RSI.周期;
+        let 超买阈值 = 前一个RSI.超买阈值;
+        let 超卖阈值 = 前一个RSI.超卖阈值;
+        let RSI_SMA周期 = 前一个RSI.RSI_SMA周期;
+        let 平滑系数 = 1.0 / 周期 as f64;
+
+        // 价格变化
+        let 变化 = 当前收盘价 - 前一个RSI.收盘价;
+        let 上涨 = 变化.max(0.0);
+        let 下跌 = (-变化).max(0.0);
+
+        // Wilder 平滑
+        let (平均上涨, 平均下跌) = match (前一个RSI.平均上涨, 前一个RSI.平均下跌) {
+            (Some(prev_up), Some(prev_down)) => {
+                let avg_up = prev_up * (1.0 - 平滑系数) + 上涨 * 平滑系数;
+                let avg_down = prev_down * (1.0 - 平滑系数) + 下跌 * 平滑系数;
+                (avg_up, avg_down)
+            }
+            _ => (上涨, 下跌),
+        };
+
+        // RSI
+        let RSI = if 平均下跌 == 0.0 {
+            if 平均上涨 > 0.0 {
+                100.0
+            } else {
+                50.0
+            }
+        } else {
+            let RS = 平均上涨 / 平均下跌;
+            100.0 - (100.0 / (1.0 + RS))
+        };
+
+        // RSI_SMA
+        let (RSI_SMA, RSI历史队列) = match RSI_SMA周期 {
+            Some(sma周期) if sma周期 > 0 => {
+                let mut 队列 = 前一个RSI.RSI历史队列.clone();
+                队列.push(RSI);
+                if 队列.len() > sma周期 as usize {
+                    队列.remove(0);
+                }
+                let sma = if 队列.is_empty() {
+                    None
+                } else {
+                    Some(队列.iter().sum::<f64>() / 队列.len() as f64)
+                };
+                (sma, 队列)
+            }
+            _ => (None, Vec::new()),
+        };
+
+        Self {
+            时间戳: 当前时间,
+            收盘价: 当前收盘价,
+            周期,
+            超买阈值,
+            超卖阈值,
+            RSI_SMA周期,
+            RSI: Some(RSI),
+            平均上涨: Some(平均上涨),
+            平均下跌: Some(平均下跌),
+            上涨幅度: 上涨,
+            下跌幅度: 下跌,
+            平滑系数,
+            RSI_SMA,
+            RSI历史队列,
+        }
+    }
+}
+
+#[cfg(test)]
+mod tests {
+    use super::*;
+
+    #[test]
+    fn test_first_calc() {
+        let rsi = 相对强弱指数::首次计算(100.0, 1000, 14, 70.0, 30.0, None);
+        assert_eq!(rsi.RSI, None);
+        assert_eq!(rsi.平滑系数, 1.0 / 14.0);
+    }
+
+    #[test]
+    fn test_incremental_calc() {
+        let first = 相对强弱指数::首次计算(100.0, 1000, 14, 70.0, 30.0, None);
+        let second = 相对强弱指数::增量计算(&first, 102.0, 1001);
+        // 价格上涨 → RSI > 50
+        assert!(second.RSI.unwrap() > 50.0);
+
+        let third = 相对强弱指数::增量计算(&second, 98.0, 1002);
+        // 价格低于之前 → RSI 下降
+        assert!(third.RSI.unwrap() < second.RSI.unwrap());
+    }
+
+    #[test]
+    fn test_rsi_sma() {
+        let mut rsi = 相对强弱指数::首次计算(100.0, 1000, 14, 70.0, 30.0, Some(5));
+        // 喂入多根K线来积累RSI历史队列
+        let prices = [102.0, 103.0, 101.0, 104.0, 105.0, 103.0, 106.0];
+        for (i, price) in prices.iter().enumerate() {
+            rsi = 相对强弱指数::增量计算(&rsi, *price, 1001 + i as i64);
+        }
+        // SMA 应该已被计算（队列够长）
+        assert!(rsi.RSI_SMA.is_some());
+    }
+}
diff --git a/chanlun/src/kline/bar.rs b/chanlun/src/kline/bar.rs
new file mode 100644
index 0000000..542383b
--- /dev/null
+++ b/chanlun/src/kline/bar.rs
@@ -0,0 +1,244 @@
+use crate::indicators::{平滑异同移动平均线, 随机指标, 相对强弱指数};
+use crate::types::相对方向;
+use byteorder::{BigEndian, ReadBytesExt, WriteBytesExt};
+use serde::{Deserialize, Serialize};
+use std::collections::HashMap;
+use std::io::Write;
+use std::rc::Rc;
+
+/// 原始K线 (OHLCV + 指标)
+#[derive(Debug, Clone, Serialize, Deserialize)]
+#[serde(default)]
+pub struct K线 {
+    pub 标识: String,
+    pub 序号: i64,
+    pub 周期: i64,
+    pub 时间戳: i64,
+    pub 高: f64,
+    pub 低: f64,
+    pub 开盘价: f64,
+    pub 收盘价: f64,
+    pub 成交量: f64,
+    pub macd: Option<平滑异同移动平均线>,
+    pub rsi: Option<相对强弱指数>,
+    pub kdj: Option<随机指标>,
+}
+
+impl Default for K线 {
+    fn default() -> Self {
+        Self {
+            标识: "bar".into(),
+            序号: 0,
+            周期: 60,
+            时间戳: 0,
+            高: 0.0,
+            低: 0.0,
+            开盘价: 0.0,
+            收盘价: 0.0,
+            成交量: 0.0,
+            macd: None,
+            rsi: None,
+            kdj: None,
+        }
+    }
+}
+
+impl K线 {
+    /// 方向：阳（收盘 > 开盘）为向上，否则向下
+    pub fn 方向(&self) -> 相对方向 {
+        if self.开盘价 < self.收盘价 {
+            相对方向::向上
+        } else {
+            相对方向::向下
+        }
+    }
+
+    /// 序列化为大端字节序 48 字节
+    /// 格式: >6d (时间戳, 开盘价, 高, 低, 收盘价, 成交量)
+    pub fn to_bytes(&self) -> [u8; 48] {
+        let mut buf = [0u8; 48];
+        {
+            let mut writer = &mut buf[..];
+            writer.write_f64::<BigEndian>(self.时间戳 as f64).unwrap();
+            writer.write_f64::<BigEndian>(self.开盘价).unwrap();
+            writer.write_f64::<BigEndian>(self.高).unwrap();
+            writer.write_f64::<BigEndian>(self.低).unwrap();
+            writer.write_f64::<BigEndian>(self.收盘价).unwrap();
+            writer.write_f64::<BigEndian>(self.成交量).unwrap();
+        }
+        buf
+    }
+
+    /// 从大端字节序反序列化
+    pub fn from_bytes(字节组: &[u8], 周期: i64, 标识: &str) -> Option<Self> {
+        if 字节组.len() < 48 {
+            return None;
+        }
+        let mut reader = &字节组[..48];
+        let 时间戳 = reader.read_f64::<BigEndian>().ok()? as i64;
+        let 开盘价 = reader.read_f64::<BigEndian>().ok()?;
+        let 高 = reader.read_f64::<BigEndian>().ok()?;
+        let 低 = reader.read_f64::<BigEndian>().ok()?;
+        let 收盘价 = reader.read_f64::<BigEndian>().ok()?;
+        let 成交量 = reader.read_f64::<BigEndian>().ok()?;
+
+        Some(Self {
+            时间戳,
+            开盘价,
+            高,
+            低,
+            收盘价,
+            成交量,
+            周期,
+            标识: 标识.to_string(),
+            序号: 0,
+            ..Default::default()
+        })
+    }
+
+    /// 读取 .nb 文件中的所有 K线
+    pub fn 读取大端字节数组(字节组: &[u8], 周期: i64, 标识: &str) -> Option<Self> {
+        Self::from_bytes(字节组, 周期, 标识)
+    }
+
+    /// 创建普通K线
+    pub fn 创建普K(
+        标识: &str,
+        时间戳: i64,
+        开盘价: f64,
+        最高价: f64,
+        最低价: f64,
+        收盘价: f64,
+        成交量: f64,
+        序号: i64,
+        周期: i64,
+    ) -> Self {
+        Self {
+            标识: 标识.to_string(),
+            序号,
+            周期,
+            时间戳,
+            高: 最高价,
+            低: 最低价,
+            开盘价,
+            收盘价,
+            成交量,
+            macd: None,
+            rsi: None,
+            kdj: None,
+        }
+    }
+
+    /// 保存K线序列到 DAT 文件
+    pub fn 保存到DAT文件(路径: &str, K线序列: &[&Self]) -> std::io::Result<()> {
+        let mut f = std::fs::File::create(路径)?;
+        for k in K线序列 {
+            f.write_all(&k.to_bytes())?;
+        }
+        Ok(())
+    }
+
+    /// 获取两K线之间的 MACD 柱面积
+    pub fn 获取MACD(K线序列: &[&Self], 始: &Self, 终: &Self) -> HashMap<String, f64> {
+        let 始_idx = K线序列.iter().position(|k| std::ptr::eq(*k, 始)).unwrap_or(0);
+        let 终_idx = K线序列.iter().position(|k| std::ptr::eq(*k, 终)).unwrap_or(0);
+        let 基序 = &K线序列[始_idx..=终_idx];
+
+        let mut 阳 = 0.0f64;
+        let mut 阴 = 0.0f64;
+        for k in 基序 {
+            if let Some(ref macd) = k.macd {
+                let hist = macd.MACD柱;
+                if hist >= 0.0 {
+                    阳 += hist;
+                } else {
+                    阴 += hist;
+                }
+            }
+        }
+        let 合 = 阳 + 阴;
+        let mut map = HashMap::new();
+        map.insert("阳".into(), 阳);
+        map.insert("阴".into(), 阴);
+        map.insert("合".into(), 合);
+        map.insert("总".into(), 阳 + 阴.abs());
+        map
+    }
+
+    /// 截取K线序列中从始到终的片段
+    pub fn 截取<'a>(序列: &'a [Self], 始: &'a Self, 终: &'a Self) -> Option<&'a [Self]> {
+        let 始_idx = 序列.iter().position(|k| std::ptr::eq(k, 始))?;
+        let 终_idx = 序列.iter().position(|k| std::ptr::eq(k, 终))?;
+        Some(&序列[始_idx..=终_idx])
+    }
+
+    /// 截取Rc<K线>序列中从始到终的片段
+    pub fn 截取rc(序列: &[Rc<Self>], 始: &Rc<Self>, 终: &Rc<Self>) -> Vec<Rc<Self>> {
+        let 始_ptr = Rc::as_ptr(始);
+        let 终_ptr = Rc::as_ptr(终);
+        let 始_idx = 序列.iter().position(|k| Rc::as_ptr(k) == 始_ptr);
+        let 终_idx = 序列.iter().position(|k| Rc::as_ptr(k) == 终_ptr);
+        match (始_idx, 终_idx) {
+            (Some(s), Some(e)) => 序列[s..=e].to_vec(),
+            _ => Vec::new(),
+        }
+    }
+}
+
+impl std::fmt::Display for K线 {
+    fn fmt(&self, f: &mut std::fmt::Formatter<'_>) -> std::fmt::Result {
+        use crate::utils::format_f64_g;
+        write!(
+            f,
+            "{}<{}, {}, {}, {}, {}, {}, {}, {}>",
+            self.标识,
+            self.序号,
+            self.周期,
+            self.方向(),
+            self.时间戳,
+            format_f64_g(self.开盘价),
+            format_f64_g(self.高),
+            format_f64_g(self.低),
+            format_f64_g(self.收盘价)
+        )
+    }
+}
+
+#[cfg(test)]
+mod tests {
+    use super::*;
+
+    #[test]
+    fn test_方向() {
+        let 阳 = K线::创建普K("test", 1000, 100.0, 110.0, 95.0, 105.0, 1000.0, 0, 60);
+        assert_eq!(阳.方向(), 相对方向::向上);
+
+        let 阴 = K线::创建普K("test", 1000, 105.0, 110.0, 95.0, 100.0, 1000.0, 0, 60);
+        assert_eq!(阴.方向(), 相对方向::向下);
+    }
+
+    #[test]
+    fn test_serialization_roundtrip() {
+        let k = K线::创建普K("test", 1600000000, 100.5, 110.2, 95.3, 105.7, 5000.0, 42, 60);
+        let bytes = k.to_bytes();
+        let restored = K线::from_bytes(&bytes, 60, "test").unwrap();
+
+        assert_eq!(restored.时间戳, 1600000000);
+        assert!((restored.开盘价 - 100.5).abs() < 0.01);
+        assert!((restored.高 - 110.2).abs() < 0.01);
+        assert!((restored.低 - 95.3).abs() < 0.01);
+        assert!((restored.收盘价 - 105.7).abs() < 0.01);
+        assert!((restored.成交量 - 5000.0).abs() < 0.01);
+    }
+
+    #[test]
+    fn test_获取MACD_empty() {
+        let k1 = K线::default();
+        let k2 = K线::default();
+        let seq = vec![&k1, &k2];
+        let result = K线::获取MACD(&seq, &k1, &k2);
+        assert_eq!(result.get("阳"), Some(&0.0));
+        assert_eq!(result.get("阴"), Some(&0.0));
+        assert_eq!(result.get("总"), Some(&0.0));
+    }
+}
diff --git a/chanlun/src/kline/chan_kline.rs b/chanlun/src/kline/chan_kline.rs
new file mode 100644
index 0000000..03159fd
--- /dev/null
+++ b/chanlun/src/kline/chan_kline.rs
@@ -0,0 +1,601 @@
+use crate::config::缠论配置;
+use crate::indicators::{K线取值, 平滑异同移动平均线, 随机指标, 相对强弱指数};
+use crate::kline::bar::K线;
+use crate::structure::fractal_obj::分型;
+use crate::types::分型结构;
+use crate::types::相对方向;
+use std::rc::Rc;
+
+/// 缠论K线 — 经包含处理过后的K线
+#[derive(Debug, Clone)]
+pub struct 缠论K线 {
+    pub 序号: i64,
+    pub 时间戳: i64,
+    pub 高: f64,
+    pub 低: f64,
+    pub 方向: 相对方向,
+    pub 分型: Option<分型结构>,
+    pub 周期: i64,
+    pub 标识: String,
+    pub 分型特征值: f64,
+    pub 原始起始序号: i64,
+    pub 原始结束序号: i64,
+    pub 标的K线: Rc<K线>,
+    pub 买卖点信息: Option<()>, // 占位，后续替换为实际类型
+}
+
+impl std::fmt::Display for 缠论K线 {
+    fn fmt(&self, f: &mut std::fmt::Formatter<'_>) -> std::fmt::Result {
+        use crate::utils::format_f64_g;
+        write!(
+            f,
+            "{}<{}, {}, {}, {}, {}, {}, {}>",
+            self.标识,
+            self.序号,
+            self.分型.map_or("None".to_string(), |fx| fx.to_string()),
+            self.周期,
+            self.方向,
+            self.时间戳,
+            format_f64_g(self.高),
+            format_f64_g(self.低)
+        )
+    }
+}
+
+impl 缠论K线 {
+    /// 创建镜像（浅拷贝 Rc 引用）
+    pub fn 镜像(&self) -> Self {
+        Self {
+            序号: self.序号,
+            时间戳: self.时间戳,
+            高: self.高,
+            低: self.低,
+            方向: self.方向,
+            分型: self.分型,
+            周期: self.周期,
+            标识: self.标识.clone(),
+            分型特征值: self.分型特征值,
+            原始起始序号: self.原始起始序号,
+            原始结束序号: self.原始结束序号,
+            标的K线: Rc::clone(&self.标的K线),
+            买卖点信息: None,
+        }
+    }
+
+    /// 与MACD柱子匹配 — 底分型时MACD柱应<0, 顶分型时>0
+    pub fn 与MACD柱子匹配(&self) -> bool {
+        match self.分型 {
+            Some(分型结构::底) | Some(分型结构::下) => {
+                if let Some(ref macd) = self.标的K线.macd {
+                    macd.MACD柱 < 0.0
+                } else {
+                    false
+                }
+            }
+            Some(分型结构::顶) | Some(分型结构::上) => {
+                if let Some(ref macd) = self.标的K线.macd {
+                    macd.MACD柱 > 0.0
+                } else {
+                    false
+                }
+            }
+            _ => false,
+        }
+    }
+
+    /// 与RSI匹配 — 底分型时RSI应低于SMA, 顶分型时高于SMA
+    pub fn 与RSI匹配(&self) -> bool {
+        match self.分型 {
+            Some(分型结构::底) | Some(分型结构::下) => {
+                if let Some(ref rsi) = self.标的K线.rsi {
+                    match (rsi.RSI, rsi.RSI_SMA) {
+                        (Some(r), Some(sma)) => r < sma,
+                        _ => false,
+                    }
+                } else {
+                    false
+                }
+            }
+            Some(分型结构::顶) | Some(分型结构::上) => {
+                if let Some(ref rsi) = self.标的K线.rsi {
+                    match (rsi.RSI, rsi.RSI_SMA) {
+                        (Some(r), Some(sma)) => r > sma,
+                        _ => false,
+                    }
+                } else {
+                    false
+                }
+            }
+            _ => false,
+        }
+    }
+
+    /// 与KDJ匹配 — 底分型时K应低于D(死叉后), 顶分型时K应高于D(金叉后)
+    pub fn 与KDJ匹配(&self) -> bool {
+        match self.分型 {
+            Some(分型结构::底) | Some(分型结构::下) => {
+                if let Some(ref kdj) = self.标的K线.kdj {
+                    match (kdj.K, kdj.D) {
+                        (Some(k), Some(d)) => k < d,
+                        _ => false,
+                    }
+                } else {
+                    false
+                }
+            }
+            Some(分型结构::顶) | Some(分型结构::上) => {
+                if let Some(ref kdj) = self.标的K线.kdj {
+                    match (kdj.K, kdj.D) {
+                        (Some(k), Some(d)) => k > d,
+                        _ => false,
+                    }
+                } else {
+                    false
+                }
+            }
+            _ => false,
+        }
+    }
+
+    /// 时间戳对齐 — 从基线序列中找匹配的时间戳
+    pub fn 时间戳对齐(基线: &[Rc<缠论K线>], k线: &缠论K线) -> i64 {
+        if let Some(基) = 基线.first() {
+            for k in 基线.iter().rev() {
+                if 基.周期 < k线.周期 {
+                    if k线.时间戳 <= k.时间戳 && k.时间戳 <= k线.时间戳 + k线.周期 {
+                        if (k线.分型特征值 - k.分型特征值).abs() < f64::EPSILON {
+                            return k.时间戳;
+                        }
+                    }
+                } else if k.时间戳 <= k线.时间戳 && k线.时间戳 <= k.时间戳 + k.周期 {
+                    if (k线.分型特征值 - k.分型特征值).abs() < f64::EPSILON {
+                        return k.时间戳;
+                    }
+                }
+            }
+        }
+        k线.时间戳
+    }
+
+    /// 创建缠K
+    pub fn 创建缠K(
+        时间戳: i64,
+        高: f64,
+        低: f64,
+        方向: 相对方向,
+        结构: Option<分型结构>,
+        原始序号: i64,
+        普k: Rc<K线>,
+        之前: Option<&缠论K线>,
+    ) -> Self {
+        assert!(高 >= 低, "缠K高必须>=低: 高={高}, 低={低}");
+
+        let 周期 = 普k.周期;
+        let 标识 = 普k.标识.clone();
+
+        let mut 当前 = Self {
+            序号: 0,
+            时间戳,
+            高,
+            低,
+            方向,
+            分型: 结构,
+            周期,
+            标识,
+            分型特征值: 高,
+            原始起始序号: 原始序号,
+            原始结束序号: 原始序号,
+            标的K线: 普k,
+            买卖点信息: None,
+        };
+
+        if let Some(之前) = 之前 {
+            当前.序号 = 之前.序号 + 1;
+            let 关系 = 相对方向::分析(之前.高, 之前.低, 当前.高, 当前.低);
+            if 关系.是否包含() {
+                panic!(
+                    "创建缠K 包含关系: {:?}\n  之前: {}\n  当前: {}",
+                    关系, 之前, 当前
+                );
+            }
+        }
+        当前
+    }
+
+    /// 兼并（合并）处理 — 缠论包含处理的核心算法
+    ///
+    /// 返回 (新缠K, 模式) — 模式: "添加"/"替换"/None
+    pub fn 兼并(
+        之前缠K: Option<&缠论K线>,
+        当前缠K: &缠论K线,
+        当前普K: &K线,
+        配置: &缠论配置,
+    ) -> (Option<Rc<缠论K线>>, Option<String>) {
+        let 关系 = 相对方向::分析(当前缠K.高, 当前缠K.低, 当前普K.高, 当前普K.低);
+
+        // 无包含关系 — 创建新元素追加
+        if !关系.是否包含() {
+            let 结构 = if 关系.是否向下() {
+                Some(分型结构::下)
+            } else {
+                Some(分型结构::上)
+            };
+            let mut 新缠K = Self::创建缠K(
+                当前普K.时间戳,
+                当前普K.高,
+                当前普K.低,
+                当前普K.方向(),
+                结构,
+                当前普K.序号,
+                Rc::new(当前普K.clone()),
+                Some(当前缠K),
+            );
+            新缠K.序号 = 当前缠K.序号 + 1;
+            return (Some(Rc::new(新缠K)), Some("添加".into()));
+        }
+
+        // 包含关系 — 合并到当前缠K
+        // 取值方向：向下 → 取低低、高高（即全部取最低）；向上 → 取高高、低低（即全部取最高）
+        // 方向由之前缠K与当前缠K的关系决定
+        let 取值函数: fn(f64, f64) -> f64 = if let Some(之前) = 之前缠K {
+            if 相对方向::分析(之前.高, 之前.低, 当前缠K.高, 当前缠K.低).是否向下() {
+                f64::min
+            } else {
+                f64::max
+            }
+        } else {
+            f64::max // 默认向上取max
+        };
+
+        let mut 合并后 = 当前缠K.镜像();
+
+        // 逆序包含时更新时间和标的K线
+        if 关系 != 相对方向::顺 {
+            合并后.时间戳 = 当前普K.时间戳;
+            合并后.标的K线 = Rc::new(当前普K.clone());
+        }
+        合并后.高 = 取值函数(合并后.高, 当前普K.高);
+        合并后.低 = 取值函数(合并后.低, 当前普K.低);
+        合并后.原始结束序号 = 当前普K.序号;
+        合并后.方向 = 当前普K.方向();
+
+        if let Some(之前) = 之前缠K {
+            合并后.序号 = 之前.序号 + 1;
+        }
+
+        if 配置.缠K合并替换 {
+            (Some(Rc::new(合并后)), Some("替换".into()))
+        } else {
+            // 兼并：返回新值让调用方决定是原地修改还是替换
+            (Some(Rc::new(合并后)), Some("兼并".into()))
+        }
+    }
+
+    /// 完整的缠K分析 — 普K → 缠K + 分型
+    ///
+    /// 返回 (状态, 形态)
+    pub fn 分析(
+        当前K线: &mut K线,
+        缠K序列: &mut Vec<Rc<缠论K线>>,
+        普K序列: &mut Vec<Rc<K线>>,
+        配置: &缠论配置,
+    ) -> (String, Option<Rc<分型>>) {
+        当前K线.标识 = 配置.标识.clone();
+
+        // ---- 阶段1: 普K序列管理 + 指标增量计算 ----
+        if 普K序列.is_empty() {
+            if 配置.计算指标 {
+                当前K线.macd = Some(平滑异同移动平均线::首次计算(
+                    K线取值(当前K线.开盘价, 当前K线.高, 当前K线.低, 当前K线.收盘价, &配置.指标计算方式),
+                    当前K线.时间戳,
+                    配置.平滑异同移动平均线_快线周期,
+                    配置.平滑异同移动平均线_慢线周期,
+                    配置.平滑异同移动平均线_信号周期,
+                ));
+                当前K线.rsi = Some(相对强弱指数::首次计算(
+                    K线取值(当前K线.开盘价, 当前K线.高, 当前K线.低, 当前K线.收盘价, &配置.指标计算方式),
+                    当前K线.时间戳,
+                    配置.相对强弱指数_周期,
+                    配置.相对强弱指数_超买阈值,
+                    配置.相对强弱指数_超卖阈值,
+                    Some(配置.相对强弱指数_移动平均线周期),
+                ));
+                当前K线.kdj = Some(随机指标::首次计算(
+                    当前K线.高,
+                    当前K线.低,
+                    当前K线.收盘价,
+                    当前K线.时间戳,
+                    配置.随机指标_RSV周期,
+                    配置.随机指标_K值平滑周期,
+                    配置.随机指标_D值平滑周期,
+                    配置.随机指标_超买阈值,
+                    配置.随机指标_超卖阈值,
+                ));
+            }
+            let 当前K线_rc = Rc::new(当前K线.clone());
+            普K序列.push(当前K线_rc);
+        } else {
+            let 之前普K = 普K序列.last().unwrap();
+            if 之前普K.时间戳 == 当前K线.时间戳 {
+                // 同时间戳更新
+                当前K线.序号 = 之前普K.序号;
+                if 配置.计算指标 {
+                    if 普K序列.len() >= 2 {
+                        if let Some(ref prev_macd) = 普K序列[普K序列.len() - 2].macd {
+                            当前K线.macd = Some(平滑异同移动平均线::增量计算(
+                                prev_macd,
+                                K线取值(当前K线.开盘价, 当前K线.高, 当前K线.低, 当前K线.收盘价, &配置.指标计算方式),
+                                当前K线.时间戳,
+                            ));
+                        }
+                        if let Some(ref prev_rsi) = 普K序列[普K序列.len() - 2].rsi {
+                            当前K线.rsi = Some(相对强弱指数::增量计算(
+                                prev_rsi,
+                                K线取值(当前K线.开盘价, 当前K线.高, 当前K线.低, 当前K线.收盘价, &配置.指标计算方式),
+                                当前K线.时间戳,
+                            ));
+                        }
+                        if let Some(ref prev_kdj) = 普K序列[普K序列.len() - 2].kdj {
+                            当前K线.kdj = Some(随机指标::增量计算(
+                                prev_kdj,
+                                当前K线.高,
+                                当前K线.低,
+                                当前K线.收盘价,
+                                当前K线.时间戳,
+                            ));
+                        }
+                    }
+                }
+                普K序列.pop();
+                普K序列.push(Rc::new(当前K线.clone()));
+            } else {
+                if 之前普K.时间戳 > 当前K线.时间戳 {
+                    panic!("时序错误: 之前={}, 当前={}", 之前普K.时间戳, 当前K线.时间戳);
+                }
+                当前K线.序号 = 之前普K.序号 + 1;
+                if 配置.计算指标 {
+                    if let Some(ref prev_macd) = 之前普K.macd {
+                        当前K线.macd = Some(平滑异同移动平均线::增量计算(
+                            prev_macd,
+                            K线取值(当前K线.开盘价, 当前K线.高, 当前K线.低, 当前K线.收盘价, &配置.指标计算方式),
+                            当前K线.时间戳,
+                        ));
+                    }
+                    if let Some(ref prev_rsi) = 之前普K.rsi {
+                        当前K线.rsi = Some(相对强弱指数::增量计算(
+                            prev_rsi,
+                            K线取值(当前K线.开盘价, 当前K线.高, 当前K线.低, 当前K线.收盘价, &配置.指标计算方式),
+                            当前K线.时间戳,
+                        ));
+                    }
+                    if let Some(ref prev_kdj) = 之前普K.kdj {
+                        当前K线.kdj = Some(随机指标::增量计算(
+                            prev_kdj,
+                            当前K线.高,
+                            当前K线.低,
+                            当前K线.收盘价,
+                            当前K线.时间戳,
+                        ));
+                    }
+                }
+                普K序列.push(Rc::new(当前K线.clone()));
+            }
+        }
+
+        // ---- 阶段2: 缠K合并 ----
+        let 之前缠K: Option<&缠论K线> = if 缠K序列.len() >= 2 {
+            Some(&缠K序列[缠K序列.len() - 2])
+        } else {
+            None
+        };
+
+        let 状态: String;
+        if !缠K序列.is_empty() {
+            let 最后一个缠K = &缠K序列[缠K序列.len() - 1];
+            // 需要从 Rc 中取出引用
+            let 最后一个缠K_ref = Rc::as_ref(最后一个缠K);
+            let (新缠K, 模式) = Self::兼并(之前缠K, 最后一个缠K_ref, 当前K线, 配置);
+
+            if let Some(k) = 新缠K {
+                if let Some(ref m) = 模式 {
+                    if m == "添加" {
+                        缠K序列.push(k);
+                        状态 = "创建".into();
+                    } else if m == "替换" {
+                        缠K序列.pop();
+                        缠K序列.push(k);
+                        状态 = "替换".into();
+                    } else {
+                        // 兼并：尝试原地修改以保持Rc指针不变
+                        let 最后_idx = 缠K序列.len() - 1;
+                        if let Some(原地) = Rc::get_mut(&mut 缠K序列[最后_idx]) {
+                            原地.高 = k.高;
+                            原地.低 = k.低;
+                            原地.时间戳 = k.时间戳;
+                            原地.方向 = k.方向;
+                            原地.原始结束序号 = k.原始结束序号;
+                            原地.标的K线 = k.标的K线.clone();
+                            原地.序号 = k.序号;
+                            状态 = "兼并".into();
+                        } else {
+                            // 有其他引用时回退到替换
+                            缠K序列.pop();
+                            缠K序列.push(k);
+                            状态 = "兼并".into();
+                        }
+                    }
+                } else {
+                    状态 = "兼并".into();
+                }
+            } else {
+                状态 = "兼并".into();
+            }
+        } else {
+            let 新缠K = Self::创建缠K(
+                当前K线.时间戳,
+                当前K线.高,
+                当前K线.低,
+                当前K线.方向(),
+                None,
+                当前K线.序号,
+                Rc::new(当前K线.clone()),
+                None,
+            );
+            缠K序列.push(Rc::new(新缠K));
+            状态 = "新建".into();
+        }
+
+        // ---- 阶段3: 分型识别 ----
+        if 缠K序列.len() < 3 {
+            return (状态, None);
+        }
+
+        let idx = 缠K序列.len();
+        let 左 = Rc::clone(&缠K序列[idx - 3]);
+        let 中 = Rc::clone(&缠K序列[idx - 2]);
+        let 右 = Rc::clone(&缠K序列[idx - 1]);
+
+        let 结构 = 分型结构::分析(&*左, &*中, &*右, false, false);
+
+        // 需要通过 Rc::get_mut 或 RefCell 修改 中.分型
+        // 由于使用 Rc，中是不可变的。这里采用创建新 Rc 替换的方式。
+        // 但这是在 Vec 内部修改，需要使用 Rc::make_mut 或重新构建
+        if let Some(结构) = 结构 {
+            // 只在分型未设置或需要更新时才修改缠K，以保持 Rc 指针不变
+            let 当前分型标记 = 缠K序列[idx - 2].分型;
+            let 中需要更新 = 当前分型标记.is_none() || 当前分型标记 != Some(结构);
+
+            if 中需要更新 {
+                let 中_mut = Rc::make_mut(&mut 缠K序列[idx - 2]);
+                中_mut.分型 = Some(结构);
+
+                match 结构 {
+                    分型结构::底 => {
+                        中_mut.分型特征值 = 中_mut.低;
+                        let 右标记 = 缠K序列[idx - 1].分型;
+                        if 右标记.is_none() {
+                            let 右_mut = Rc::make_mut(&mut 缠K序列[idx - 1]);
+                            右_mut.分型特征值 = 右_mut.高;
+                            右_mut.分型 = Some(分型结构::顶);
+                        }
+                    }
+                    分型结构::顶 => {
+                        中_mut.分型特征值 = 中_mut.高;
+                        let 右标记 = 缠K序列[idx - 1].分型;
+                        if 右标记.is_none() {
+                            let 右_mut = Rc::make_mut(&mut 缠K序列[idx - 1]);
+                            右_mut.分型特征值 = 右_mut.低;
+                            右_mut.分型 = Some(分型结构::底);
+                        }
+                    }
+                    分型结构::上 => {
+                        中_mut.分型特征值 = 中_mut.高;
+                        let 右标记 = 缠K序列[idx - 1].分型;
+                        if 右标记.is_none() {
+                            let 右_mut = Rc::make_mut(&mut 缠K序列[idx - 1]);
+                            右_mut.分型特征值 = 右_mut.高;
+                            右_mut.分型 = Some(分型结构::顶);
+                        }
+                    }
+                    分型结构::下 => {
+                        中_mut.分型特征值 = 中_mut.低;
+                        let 右标记 = 缠K序列[idx - 1].分型;
+                        if 右标记.is_none() {
+                            let 右_mut = Rc::make_mut(&mut 缠K序列[idx - 1]);
+                            右_mut.分型特征值 = 右_mut.低;
+                            右_mut.分型 = Some(分型结构::底);
+                        }
+                    }
+                    分型结构::散 => {}
+                }
+            }
+
+            let 形态 = if matches!(结构, 分型结构::上 | 分型结构::下) {
+                // 三连方向不算完整分型 — 只有中+右
+                Rc::new(分型::new(
+                    None,
+                    Rc::clone(&缠K序列[idx - 2]),
+                    None,
+                ))
+            } else {
+                Rc::new(分型::new(
+                    Some(Rc::clone(&缠K序列[idx - 3])),
+                    Rc::clone(&缠K序列[idx - 2]),
+                    Some(Rc::clone(&缠K序列[idx - 1])),
+                ))
+            };
+
+            return (状态, Some(形态));
+        }
+
+        (状态, None)
+    }
+
+    /// 截取缠K序列从始到终
+    pub fn 截取(序列: &[Rc<缠论K线>], 始: &缠论K线, 终: &缠论K线) -> Option<Vec<Rc<缠论K线>>> {
+        let 始_idx = 序列.iter().position(|k| Rc::as_ptr(k) == (始 as *const _))?;
+        let 终_idx = 序列.iter().position(|k| Rc::as_ptr(k) == (终 as *const _))?;
+        Some(序列[始_idx..=终_idx].to_vec())
+    }
+}
+
+impl crate::types::fractal::有高低 for 缠论K线 {
+    fn 高(&self) -> f64 {
+        self.高
+    }
+    fn 低(&self) -> f64 {
+        self.低
+    }
+}
+
+#[cfg(test)]
+mod tests {
+    use super::*;
+    use crate::config::缠论配置;
+
+    fn make_普K(时间戳: i64, 开: f64, 高: f64, 低: f64, 收: f64, 序号: i64) -> K线 {
+        K线::创建普K("test", 时间戳, 开, 高, 低, 收, 1000.0, 序号, 60)
+    }
+
+    #[test]
+    fn test_创建缠K_basic() {
+        let pk = Rc::new(make_普K(1000, 100.0, 110.0, 95.0, 105.0, 0));
+        let ck = 缠论K线::创建缠K(1000, 110.0, 95.0, 相对方向::向上, None, 0, pk, None);
+        assert_eq!(ck.高, 110.0);
+        assert_eq!(ck.低, 95.0);
+        assert_eq!(ck.序号, 0);
+    }
+
+    #[test]
+    fn test_分析_empty_sequence() {
+        let config = 缠论配置::default();
+        let mut pk = make_普K(1000, 100.0, 110.0, 95.0, 105.0, 0);
+        let mut 缠K序列 = Vec::new();
+        let mut 普K序列 = Vec::new();
+
+        let (状态, 形态) = 缠论K线::分析(&mut pk, &mut 缠K序列, &mut 普K序列, &config);
+        assert_eq!(状态, "新建");
+        assert_eq!(缠K序列.len(), 1);
+        assert!(形态.is_none()); // 不够3根
+    }
+
+    #[test]
+    fn test_分析_three_bars_fractal() {
+        let config = 缠论配置::default();
+        let mut 缠K序列 = Vec::new();
+        let mut 普K序列 = Vec::new();
+
+        // 三根形成顶分型: 低高 → 更高高 → 低高
+        let mut pk1 = make_普K(1000, 100.0, 110.0, 95.0, 105.0, 0);
+        let 状态1 = 缠论K线::分析(&mut pk1, &mut 缠K序列, &mut 普K序列, &config);
+        assert_eq!(状态1.0, "新建");
+
+        let mut pk2 = make_普K(1001, 105.0, 115.0, 102.0, 112.0, 1);
+        let 状态2 = 缠论K线::分析(&mut pk2, &mut 缠K序列, &mut 普K序列, &config);
+        assert!(状态2.1.is_none()); // 仍不够
+
+        let mut pk3 = make_普K(1002, 112.0, 113.0, 100.0, 103.0, 2);
+        let (_状态3, 形态) = 缠论K线::分析(&mut pk3, &mut 缠K序列, &mut 普K序列, &config);
+        assert!(形态.is_some()); // 分型产生了
+    }
+}
diff --git a/chanlun/src/kline/mod.rs b/chanlun/src/kline/mod.rs
new file mode 100644
index 0000000..9b68892
--- /dev/null
+++ b/chanlun/src/kline/mod.rs
@@ -0,0 +1,2 @@
+pub mod bar;
+pub mod chan_kline;
diff --git a/chanlun/src/lib.rs b/chanlun/src/lib.rs
new file mode 100644
index 0000000..731e928
--- /dev/null
+++ b/chanlun/src/lib.rs
@@ -0,0 +1,11 @@
+#![allow(non_snake_case)]
+#![allow(non_camel_case_types)]
+
+pub mod algorithm;
+pub mod business;
+pub mod config;
+pub mod indicators;
+pub mod kline;
+pub mod structure;
+pub mod types;
+pub mod utils;
diff --git a/chanlun/src/main.rs b/chanlun/src/main.rs
new file mode 100644
index 0000000..6ddc285
--- /dev/null
+++ b/chanlun/src/main.rs
@@ -0,0 +1,34 @@
+use chanlun::business::observer::观察者;
+use std::env;
+
+fn main() {
+    let args: Vec<String> = env::args().collect();
+    if args.len() < 2 {
+        eprintln!("用法: {} <.nb文件路径>", args[0]);
+        std::process::exit(1);
+    }
+
+    let 文件路径 = &args[1];
+    println!("读取文件: {}", 文件路径);
+
+    match 观察者::读取数据文件(文件路径, None) {
+        Ok(观察员) => {
+            println!("符号: {}", 观察员.符号);
+            println!("周期: {}", 观察员.周期);
+            println!("普K数量: {}", 观察员.普通K线序列.len());
+            println!("缠K数量: {}", 观察员.缠论K线序列.len());
+            println!("分型数量: {}", 观察员.分型序列.len());
+            println!("笔数量: {}", 观察员.笔序列.len());
+            println!("笔中枢数量: {}", 观察员.笔_中枢序列.len());
+            println!("线段数量: {}", 观察员.线段序列.len());
+            println!("中枢数量: {}", 观察员.中枢序列.len());
+
+            println!("\n===== 数据分析 =====\n");
+            观察员.测试_保存数据(None);
+        }
+        Err(e) => {
+            eprintln!("读取失败: {}", e);
+            std::process::exit(1);
+        }
+    }
+}
diff --git a/chanlun/src/structure/dash_line.rs b/chanlun/src/structure/dash_line.rs
new file mode 100644
index 0000000..8114ce1
--- /dev/null
+++ b/chanlun/src/structure/dash_line.rs
@@ -0,0 +1,771 @@
+use crate::algorithm::hub::中枢;
+use crate::config::缠论配置;
+use crate::kline::chan_kline::缠论K线;
+use crate::kline::bar::K线;
+use crate::structure::fractal_obj::分型;
+use crate::structure::segment_feat::线段特征;
+use crate::types::{分型结构, 相对方向, 缺口};
+use std::rc::Rc;
+
+/// 虚线 — 笔和线段的通用数据结构
+///
+/// 笔和线段共享此 struct，通过 `标识` 字段区分 ("笔"/"线段"/"扩展线段"等)
+#[derive(Debug, Clone)]
+pub struct 虚线 {
+    pub 标识: String,
+    pub 序号: i64,
+    pub 级别: i64,
+    pub 文: Rc<分型>,
+    pub 武: Rc<分型>,
+    pub 有效性: bool,
+    pub 基础序列: Vec<Rc<虚线>>,
+    pub 特征序列: Vec<Option<Rc<线段特征>>>,
+    pub 实_中枢序列: Vec<Rc<中枢>>,
+    pub 虚_中枢序列: Vec<Rc<中枢>>,
+    pub 合_中枢序列: Vec<Rc<中枢>>,
+    pub 确认K线: Option<Rc<缠论K线>>,
+    pub 模式: String,
+    pub _特征序列_显示: bool,
+    pub 前一缺口: Option<缺口>,
+    pub 前一结束位置: Option<Rc<虚线>>,
+    pub 短路修正: bool,
+}
+
+impl 虚线 {
+    pub fn new(序号: i64, 标识: String, 文: Rc<分型>, 武: Rc<分型>, 级别: i64, 有效性: bool) -> Self {
+        Self {
+            序号,
+            标识,
+            级别,
+            文,
+            武,
+            有效性,
+            基础序列: Vec::new(),
+            特征序列: Vec::new(),
+            实_中枢序列: Vec::new(),
+            虚_中枢序列: Vec::new(),
+            合_中枢序列: Vec::new(),
+            确认K线: None,
+            模式: "文武".into(),
+            _特征序列_显示: false,
+            前一缺口: None,
+            前一结束位置: None,
+            短路修正: false,
+        }
+    }
+
+    /// 笔序列（基础序列的别名）
+    pub fn 笔序列(&self) -> &Vec<Rc<虚线>> {
+        &self.基础序列
+    }
+
+    pub fn 图表标题(&self) -> String {
+        format!("{}:{}:{}:{}", self.文.中.标识, self.文.中.周期, self.标识, self.序号)
+    }
+
+    /// 方向 — 文到武的方向
+    pub fn 方向(&self) -> 相对方向 {
+        match (self.文.结构, self.武.结构) {
+            (分型结构::顶, 分型结构::底) => 相对方向::向下,
+            (分型结构::顶, 分型结构::下) => 相对方向::向下,
+            (分型结构::上, 分型结构::底) => 相对方向::向下,
+            (分型结构::上, 分型结构::下) => 相对方向::向下,
+            _ => 相对方向::向上,
+        }
+    }
+
+    /// 虚线高 — 文和武中高的那个
+    pub fn 高(&self) -> f64 {
+        self.武.分型特征值.max(self.文.分型特征值)
+    }
+
+    /// 虚线低 — 文和武中低的那个
+    pub fn 低(&self) -> f64 {
+        self.武.分型特征值.min(self.文.分型特征值)
+    }
+
+    /// 判断两个虚线是否首尾相连
+    pub fn 之前是(&self, 之前: &虚线) -> bool {
+        self.文.中.序号 == 之前.武.中.序号
+    }
+
+    /// 判断两个虚线是否首尾相连
+    pub fn 之后是(&self, 之后: &虚线) -> bool {
+        self.武.中.序号 == 之后.文.中.序号
+    }
+
+    /// 获取该虚线范围内的普K序列
+    pub fn 获取普K序列(&self, 普K序列: &[Rc<K线>]) -> Vec<Rc<K线>> {
+        let 始 = self.文.中.原始起始序号 as usize;
+        let 终 = self.武.中.原始结束序号 as usize;
+        if 始 < 普K序列.len() && 终 < 普K序列.len() && 始 <= 终 {
+            普K序列[始..=终].to_vec()
+        } else {
+            Vec::new()
+        }
+    }
+
+    /// 获取该虚线范围内的缠K序列
+    pub fn 获取缠K序列(&self, 缠K序列: &[Rc<缠论K线>]) -> Vec<Rc<缠论K线>> {
+        缠论K线::截取(缠K序列, &self.文.中, &self.武.中).unwrap_or_default()
+    }
+
+    /// 获取数据文本（用于保存/调试）
+    pub fn 获取数据文本(&self) -> String {
+        use crate::utils::format_f64_g;
+        if self.标识 == "笔" {
+            return format!(
+                "{}, {}, {}, 文:({},{}), 武:({},{}), {}",
+                self.标识,
+                self.序号,
+                self.级别,
+                self.文.时间戳,
+                format_f64_g(self.文.分型特征值),
+                self.武.时间戳,
+                format_f64_g(self.武.分型特征值),
+                if self.有效性 { "True" } else { "False" },
+            );
+        }
+
+        // 非笔：线段/扩展线段等，完整输出
+        let (前, 后, 三, 贯穿伤) =
+            crate::algorithm::segment::线段::分割序列(self, None);
+        let (特征_a, 特征_b, 特征_c) = crate::algorithm::segment::线段::特征序列状态(self);
+        let 特征_bool = |b: bool| -> &str { if b { "True" } else { "False" } };
+
+        let 前一缺口_str = match &self.前一缺口 {
+            Some(g) => format!("{}", g),
+            None => "None".to_string(),
+        };
+        let 前一结束位置_str = match &self.前一结束位置 {
+            Some(d) => format!("{}", d),
+            None => "None".to_string(),
+        };
+
+        // Format中枢序列 as Python-style list representations
+        let 实_str = format!("[{}]", self.实_中枢序列.iter().map(|h| format!("{}", h)).collect::<Vec<_>>().join(", "));
+        let 虚_str = format!("[{}]", self.虚_中枢序列.iter().map(|h| format!("{}", h)).collect::<Vec<_>>().join(", "));
+        let 合_str = format!("[{}]", self.合_中枢序列.iter().map(|h| format!("{}", h)).collect::<Vec<_>>().join(", "));
+
+        let 前_str = format!("[{}]", 前.iter().map(|d| format!("{}", d)).collect::<Vec<_>>().join(", "));
+        let 后_str = format!("[{}]", 后.iter().map(|d| format!("{}", d)).collect::<Vec<_>>().join(", "));
+        let 三_str = format!("[{}]", 三.iter().map(|d| format!("{}", d)).collect::<Vec<_>>().join(", "));
+
+        format!(
+            "{}, {}, {}, 文:({},{}), 武:({},{}), {}, {}, ({}, {}, {}), (前: {}, 后: {}, 三: {}, 伤: {}), 实: {}, 虚: {}, 合: {}, {}, {}, {}, {}",
+            self.标识,
+            self.序号,
+            self.级别,
+            self.文.时间戳,
+            format_f64_g(self.文.分型特征值),
+            self.武.时间戳,
+            format_f64_g(self.武.分型特征值),
+            if self.有效性 { "True" } else { "False" },
+            self.基础序列.len(),
+            特征_bool(特征_a),
+            特征_bool(特征_b),
+            特征_bool(特征_c),
+            前_str,
+            后_str,
+            三_str,
+            match &贯穿伤 { Some(d) => format!("{}", d), None => "None".to_string() },
+            实_str,
+            虚_str,
+            合_str,
+            self.模式,
+            前一缺口_str,
+            前一结束位置_str,
+            if self.短路修正 { "True" } else { "False" },
+        )
+    }
+
+    // ---- 关联函数（静态工厂方法） ----
+
+    /// 创建笔
+    pub fn 创建笔(文: Rc<分型>, 武: Rc<分型>, 有效性: bool) -> Self {
+        Self::new(0, "笔".into(), 文, 武, 1, 有效性)
+    }
+
+    /// 创建线段
+    pub fn 创建线段(虚线序列: &[Rc<虚线>]) -> Self {
+        let 文 = Rc::clone(&虚线序列[0].文);
+        let 武 = Rc::clone(&虚线序列[虚线序列.len() - 1].武);
+        let 标识 = if 虚线序列[0].标识 == "笔" {
+            "线段".into()
+        } else {
+            format!("线段<{}>", 虚线序列[0].标识)
+        };
+        let 级别 = 虚线序列[0].级别 + 1;
+        let mut 段 = Self::new(0, 标识, 文, 武, 级别, true);
+        段.基础序列 = 虚线序列.to_vec();
+        段.模式 = "文武".into();
+        段
+    }
+
+    // ---- 买卖点模式匹配 ----
+
+    /// 缠K买卖点模式 — 根据模式字符串选择匹配方法
+    pub fn 缠K买卖点模式(模式: &str, 缠K: &缠论K线, 配置: &缠论配置) -> bool {
+        match 模式 {
+            "全量" => Self::买卖点全量匹配(缠K),
+            "任意" => Self::买卖点任意匹配(缠K),
+            "配置" => Self::买卖点配置匹配(缠K, 配置),
+            "相对" => Self::买卖点相对匹配(缠K),
+            _ => false,
+        }
+    }
+
+    /// 买卖点配置匹配 — 根据配置中的指标开关组合判断
+    pub fn 买卖点配置匹配(缠K: &缠论K线, 配置: &缠论配置) -> bool {
+        match (配置.买卖点_指标匹配_MACD, 配置.买卖点_指标匹配_KDJ, 配置.买卖点_指标匹配_RSI) {
+            (true, true, true) => 缠K.与MACD柱子匹配() && 缠K.与KDJ匹配() && 缠K.与RSI匹配(),
+            (false, false, false) => false,
+            (true, false, true) => 缠K.与MACD柱子匹配() && 缠K.与RSI匹配(),
+            (false, true, false) => 缠K.与KDJ匹配(),
+            (true, false, false) => 缠K.与MACD柱子匹配(),
+            (false, true, true) => 缠K.与KDJ匹配() && 缠K.与RSI匹配(),
+            (false, false, true) => 缠K.与RSI匹配(),
+            (true, true, false) => 缠K.与MACD柱子匹配() && 缠K.与KDJ匹配(),
+        }
+    }
+
+    /// 买卖点任意匹配 — 任一指标匹配
+    pub fn 买卖点任意匹配(缠K: &缠论K线) -> bool {
+        缠K.与MACD柱子匹配() || 缠K.与KDJ匹配() || 缠K.与RSI匹配()
+    }
+
+    /// 买卖点全量匹配 — 全部指标匹配
+    pub fn 买卖点全量匹配(缠K: &缠论K线) -> bool {
+        缠K.与MACD柱子匹配() && 缠K.与KDJ匹配() && 缠K.与RSI匹配()
+    }
+
+    /// 买卖点相对匹配 — 至少两个指标匹配
+    pub fn 买卖点相对匹配(缠K: &缠论K线) -> bool {
+        let 混沌槽 = [
+            缠K.与MACD柱子匹配(),
+            缠K.与KDJ匹配(),
+            缠K.与RSI匹配(),
+        ];
+        混沌槽.iter().filter(|&&x| x).count() >= 2
+    }
+
+    // ---- MACD柱子均值计算 ----
+
+    /// 计算MACD柱子均值 — 虚线范围内所有MACD柱的绝对值均值
+    pub fn 计算MACD柱子均值(普K序列: &[Rc<K线>], 实线: &虚线) -> f64 {
+        let K线序列 = K线::截取rc(普K序列, &实线.文.中.标的K线, &实线.武.中.标的K线);
+        if K线序列.is_empty() {
+            return 0.0;
+        }
+        let 总: f64 = K线序列
+            .iter()
+            .filter_map(|k| k.macd.as_ref())
+            .map(|m| m.MACD柱.abs())
+            .sum();
+        总 / K线序列.len() as f64
+    }
+
+    /// 计算MACD柱子均值_阴 — 负柱的绝对值均值
+    pub fn 计算MACD柱子均值_阴(普K序列: &[Rc<K线>], 实线: &虚线) -> Option<f64> {
+        let K线序列 = K线::截取rc(普K序列, &实线.文.中.标的K线, &实线.武.中.标的K线);
+        let 总: Vec<f64> = K线序列
+            .iter()
+            .filter_map(|k| k.macd.as_ref())
+            .filter(|m| m.MACD柱 < 0.0)
+            .map(|m| m.MACD柱.abs())
+            .collect();
+        if 总.is_empty() {
+            None
+        } else {
+            Some(总.iter().sum::<f64>() / 总.len() as f64)
+        }
+    }
+
+    /// 计算MACD柱子均值_阳 — 正柱的绝对值均值
+    pub fn 计算MACD柱子均值_阳(普K序列: &[Rc<K线>], 实线: &虚线) -> Option<f64> {
+        let K线序列 = K线::截取rc(普K序列, &实线.文.中.标的K线, &实线.武.中.标的K线);
+        let 总: Vec<f64> = K线序列
+            .iter()
+            .filter_map(|k| k.macd.as_ref())
+            .filter(|m| m.MACD柱 > 0.0)
+            .map(|m| m.MACD柱.abs())
+            .collect();
+        if 总.is_empty() {
+            None
+        } else {
+            Some(总.iter().sum::<f64>() / 总.len() as f64)
+        }
+    }
+
+    // ---- 武之MACD比较 ----
+
+    /// 武之全量MACD均值 — 武端MACD柱是否小于均值（背驰）
+    pub fn 武之全量MACD均值(普K序列: &[Rc<K线>], 实线: &虚线) -> bool {
+        let 武_MACD = match &实线.武.中.标的K线.macd {
+            Some(m) => m.MACD柱.abs(),
+            None => return false,
+        };
+        武_MACD < Self::计算MACD柱子均值(普K序列, 实线)
+    }
+
+    /// 武之MACD均值 — 按方向选择阴/阳均值比对
+    pub fn 武之MACD均值(普K序列: &[Rc<K线>], 实线: &虚线) -> bool {
+        if 实线.方向() == 相对方向::向上 {
+            Self::武之MACD均值_阳(普K序列, 实线)
+        } else {
+            Self::武之MACD均值_阴(普K序列, 实线)
+        }
+    }
+
+    /// 武之MACD均值_阴 — 武端负柱是否小于阴均值
+    pub fn 武之MACD均值_阴(普K序列: &[Rc<K线>], 实线: &虚线) -> bool {
+        let 武_MACD = match &实线.武.中.标的K线.macd {
+            Some(m) => m.MACD柱.abs(),
+            None => return false,
+        };
+        match Self::计算MACD柱子均值_阴(普K序列, 实线) {
+            Some(均值) => 武_MACD < 均值.abs(),
+            None => false,
+        }
+    }
+
+    /// 武之MACD均值_阳 — 武端正柱是否小于阳均值
+    pub fn 武之MACD均值_阳(普K序列: &[Rc<K线>], 实线: &虚线) -> bool {
+        let 武_MACD = match &实线.武.中.标的K线.macd {
+            Some(m) => m.MACD柱.abs(),
+            None => return false,
+        };
+        match Self::计算MACD柱子均值_阳(普K序列, 实线) {
+            Some(均值) => 武_MACD < 均值,
+            None => false,
+        }
+    }
+
+    /// 武之MACD极值 — 武端MACD柱是否为区间极值
+    pub fn 武之MACD极值(普K序列: &[Rc<K线>], 实线: &虚线) -> bool {
+        let 武_MACD = match &实线.武.中.标的K线.macd {
+            Some(m) => m.MACD柱,
+            None => return false,
+        };
+        let K线序列 = K线::截取rc(普K序列, &实线.文.中.标的K线, &实线.武.中.标的K线);
+        let 所有柱子: Vec<f64> = K线序列
+            .iter()
+            .filter_map(|k| k.macd.as_ref())
+            .map(|m| m.MACD柱)
+            .collect();
+        if 所有柱子.is_empty() {
+            return false;
+        }
+        if 武_MACD > 0.0 {
+            let 极值 = 所有柱子.iter().cloned().fold(f64::NEG_INFINITY, f64::max);
+            极值 == 武_MACD
+        } else {
+            let 极值 = 所有柱子.iter().cloned().fold(f64::INFINITY, f64::min);
+            极值 == 武_MACD
+        }
+    }
+
+    // ---- MACD趋向背驰 ----
+
+    /// 计算K线序列MACD趋向背驰 — 分析 MACD柱/DIF/DEA 三项背驰信号
+    pub fn 计算K线序列MACD趋向背驰(普K序列: &[Rc<K线>], 方向: 相对方向) -> [bool; 3] {
+        if 普K序列.is_empty() {
+            return [false, false, false];
+        }
+        let 最后 = &普K序列[普K序列.len() - 1];
+
+        if 方向 == 相对方向::向上 {
+            let 柱子序列: Vec<&Rc<K线>> = 普K序列
+                .iter()
+                .filter(|k| k.macd.as_ref().map_or(false, |m| m.MACD柱 > 0.0))
+                .collect();
+            if 柱子序列.is_empty() {
+                return [false, false, false];
+            }
+
+            let mut 结果 = [false; 3];
+
+            // MACD柱背驰
+            let 最高柱子 = 柱子序列
+                .iter()
+                .max_by(|a, b| {
+                    a.macd.as_ref().unwrap().MACD柱
+                        .partial_cmp(&b.macd.as_ref().unwrap().MACD柱)
+                        .unwrap()
+                })
+                .unwrap();
+            let mut 柱对 = vec![Rc::clone(*最高柱子), Rc::clone(最后)];
+            柱对.sort_by_key(|k| k.时间戳);
+            if let (Some(m0), Some(m1)) = (柱对[0].macd.as_ref(), 柱对[1].macd.as_ref()) {
+                if m0.MACD柱 > m1.MACD柱 && 柱对[0].高 < 柱对[1].高 {
+                    结果[0] = true;
+                }
+            }
+
+            // DIF背驰
+            let 最高离差值 = 柱子序列
+                .iter()
+                .max_by(|a, b| {
+                    let da = a.macd.as_ref().and_then(|m| m.DIF).unwrap_or(0.0);
+                    let db = b.macd.as_ref().and_then(|m| m.DIF).unwrap_or(0.0);
+                    da.partial_cmp(&db).unwrap()
+                })
+                .unwrap();
+            let mut 柱对2 = vec![Rc::clone(*最高离差值), Rc::clone(最后)];
+            柱对2.sort_by_key(|k| k.时间戳);
+            if let (Some(m0), Some(m1)) = (柱对2[0].macd.as_ref(), 柱对2[1].macd.as_ref()) {
+                let dif0 = m0.DIF.unwrap_or(0.0);
+                let dif1 = m1.DIF.unwrap_or(0.0);
+                if dif0 > dif1 && 柱对2[0].高 < 柱对2[1].高 {
+                    结果[1] = true;
+                }
+            }
+
+            // DEA背驰
+            let 最高信号线 = 柱子序列
+                .iter()
+                .max_by(|a, b| {
+                    let da = a.macd.as_ref().and_then(|m| m.DEA).unwrap_or(0.0);
+                    let db = b.macd.as_ref().and_then(|m| m.DEA).unwrap_or(0.0);
+                    da.partial_cmp(&db).unwrap()
+                })
+                .unwrap();
+            let mut 柱对3 = vec![Rc::clone(*最高信号线), Rc::clone(最后)];
+            柱对3.sort_by_key(|k| k.时间戳);
+            if let (Some(m0), Some(m1)) = (柱对3[0].macd.as_ref(), 柱对3[1].macd.as_ref()) {
+                let dea0 = m0.DEA.unwrap_or(0.0);
+                let dea1 = m1.DEA.unwrap_or(0.0);
+                if dea0 > dea1 && 柱对3[0].高 < 柱对3[1].高 {
+                    结果[2] = true;
+                }
+            }
+
+            结果
+        } else {
+            let 柱子序列: Vec<&Rc<K线>> = 普K序列
+                .iter()
+                .filter(|k| k.macd.as_ref().map_or(false, |m| m.MACD柱 < 0.0))
+                .collect();
+            if 柱子序列.is_empty() {
+                return [false, false, false];
+            }
+
+            let mut 结果 = [false; 3];
+
+            // MACD柱背驰 (负向: absolute value comparison)
+            let 最高柱子 = 柱子序列
+                .iter()
+                .max_by(|a, b| {
+                    a.macd.as_ref().unwrap().MACD柱.abs()
+                        .partial_cmp(&b.macd.as_ref().unwrap().MACD柱.abs())
+                        .unwrap()
+                })
+                .unwrap();
+            let mut 柱对 = vec![Rc::clone(*最高柱子), Rc::clone(最后)];
+            柱对.sort_by_key(|k| k.时间戳);
+            if let (Some(m0), Some(m1)) = (柱对[0].macd.as_ref(), 柱对[1].macd.as_ref()) {
+                if m0.MACD柱 < m1.MACD柱 && 柱对[0].低 > 柱对[1].低 {
+                    结果[0] = true;
+                }
+            }
+
+            // DIF背驰
+            let 最高离差值 = 柱子序列
+                .iter()
+                .max_by(|a, b| {
+                    let da = a.macd.as_ref().and_then(|m| m.DIF).unwrap_or(0.0).abs();
+                    let db = b.macd.as_ref().and_then(|m| m.DIF).unwrap_or(0.0).abs();
+                    da.partial_cmp(&db).unwrap()
+                })
+                .unwrap();
+            let mut 柱对2 = vec![Rc::clone(*最高离差值), Rc::clone(最后)];
+            柱对2.sort_by_key(|k| k.时间戳);
+            if let (Some(m0), Some(m1)) = (柱对2[0].macd.as_ref(), 柱对2[1].macd.as_ref()) {
+                let dif0 = m0.DIF.unwrap_or(0.0);
+                let dif1 = m1.DIF.unwrap_or(0.0);
+                if dif0 < dif1 && 柱对2[0].低 > 柱对2[1].低 {
+                    结果[1] = true;
+                }
+            }
+
+            // DEA背驰
+            let 最高信号线 = 柱子序列
+                .iter()
+                .max_by(|a, b| {
+                    let da = a.macd.as_ref().and_then(|m| m.DEA).unwrap_or(0.0).abs();
+                    let db = b.macd.as_ref().and_then(|m| m.DEA).unwrap_or(0.0).abs();
+                    da.partial_cmp(&db).unwrap()
+                })
+                .unwrap();
+            let mut 柱对3 = vec![Rc::clone(*最高信号线), Rc::clone(最后)];
+            柱对3.sort_by_key(|k| k.时间戳);
+            if let (Some(m0), Some(m1)) = (柱对3[0].macd.as_ref(), 柱对3[1].macd.as_ref()) {
+                let dea0 = m0.DEA.unwrap_or(0.0);
+                let dea1 = m1.DEA.unwrap_or(0.0);
+                if dea0 < dea1 && 柱对3[0].低 > 柱对3[1].低 {
+                    结果[2] = true;
+                }
+            }
+
+            结果
+        }
+    }
+
+    // ---- MACD柱子分段 ----
+
+    /// 计算MACD柱子分段 — 按正负号将MACD柱子分段
+    pub fn 计算MACD柱子分段(k线序列: &[Rc<K线>]) -> Vec<Vec<f64>> {
+        if k线序列.is_empty() {
+            return Vec::new();
+        }
+
+        let 符号 = |x: f64| -> &str {
+            if x > 0.0 { "正" } else { "负" }
+        };
+
+        let 首_MACD = match &k线序列[0].macd {
+            Some(m) => m.MACD柱,
+            None => return Vec::new(),
+        };
+        let mut 当前符号 = 符号(首_MACD);
+        let mut 当前段 = vec![首_MACD];
+        let mut 结果 = Vec::new();
+
+        for k线 in &k线序列[1..] {
+            let macd = match &k线.macd {
+                Some(m) => m.MACD柱,
+                None => continue,
+            };
+            let 新符号 = 符号(macd);
+            if 新符号 == 当前符号 {
+                当前段.push(macd);
+            } else {
+                结果.push(std::mem::take(&mut 当前段));
+                当前段.push(macd);
+                当前符号 = 新符号;
+            }
+        }
+        if !当前段.is_empty() {
+            结果.push(当前段);
+        }
+        结果
+    }
+
+    // ---- 密集区域按间隔 ----
+
+    /// 密集区域按间隔 — 找出交叉标记中的密集区域
+    pub fn 密集区域按间隔(
+        交叉标记: &[i32],
+        最大间隔: usize,
+        最少交叉数: usize,
+    ) -> Vec<(usize, usize, usize)> {
+        let 交叉索引: Vec<usize> = (0..交叉标记.len()).filter(|&i| 交叉标记[i] != 0).collect();
+        if 交叉索引.is_empty() {
+            return Vec::new();
+        }
+
+        let mut 密集区 = Vec::new();
+        let mut 当前块起始 = 交叉索引[0];
+        let mut 当前块交叉数 = 1;
+
+        for i in 1..交叉索引.len() {
+            let prev = 交叉索引[i - 1];
+            let curr = 交叉索引[i];
+            if curr - prev <= 最大间隔 {
+                当前块交叉数 += 1;
+            } else {
+                if 当前块交叉数 >= 最少交叉数 {
+                    密集区.push((当前块起始, prev, 当前块交叉数));
+                }
+                当前块起始 = curr;
+                当前块交叉数 = 1;
+            }
+        }
+
+        if 当前块交叉数 >= 最少交叉数 {
+            密集区.push((当前块起始, 交叉索引[交叉索引.len() - 1], 当前块交叉数));
+        }
+
+        密集区
+    }
+
+    // ---- 统计MACD行为 ----
+
+    /// 统计MACD行为 — 分析DIF/DEA穿零轴和金叉死叉
+    pub fn 统计MACD行为(普K序列: &[Rc<K线>], 最大间隔: usize, 最少交叉数: usize) -> std::collections::HashMap<String, String> {
+        use std::collections::HashMap;
+
+        let mut dif_up = 0;
+        let mut dif_down = 0;
+        let mut dea_up = 0;
+        let mut dea_down = 0;
+
+        for i in 1..普K序列.len() {
+            let pre = &普K序列[i - 1].macd;
+            let cur = &普K序列[i].macd;
+            if pre.is_none() || cur.is_none() {
+                continue;
+            }
+            let (pre_dif, cur_dif) = (pre.as_ref().unwrap().DIF, cur.as_ref().unwrap().DIF);
+            let (pre_dea, cur_dea) = (pre.as_ref().unwrap().DEA, cur.as_ref().unwrap().DEA);
+
+            if let (Some(pd), Some(cd)) = (pre_dif, cur_dif) {
+                if pd < 0.0 && cd >= 0.0 { dif_up += 1; }
+                if pd > 0.0 && cd <= 0.0 { dif_down += 1; }
+            }
+            if let (Some(pd), Some(cd)) = (pre_dea, cur_dea) {
+                if pd < 0.0 && cd >= 0.0 { dea_up += 1; }
+                if pd > 0.0 && cd <= 0.0 { dea_down += 1; }
+            }
+        }
+
+        let mut golden = 0;
+        let mut death = 0;
+        let mut 交叉标记 = vec![0i32];
+
+        for i in 1..普K序列.len() {
+            let pre = &普K序列[i - 1].macd;
+            let cur = &普K序列[i].macd;
+            if pre.is_none() || cur.is_none() {
+                交叉标记.push(0);
+                continue;
+            }
+            let pre_dif = pre.as_ref().unwrap().DIF;
+            let pre_dea = pre.as_ref().unwrap().DEA;
+            let cur_dif = cur.as_ref().unwrap().DIF;
+            let cur_dea = cur.as_ref().unwrap().DEA;
+
+            if let (Some(pd), Some(cd), Some(pe), Some(ce)) = (pre_dif, cur_dif, pre_dea, cur_dea) {
+                if pd <= pe && cd > ce {
+                    golden += 1;
+                    交叉标记.push(1);
+                } else if pd >= pe && cd < ce {
+                    death += 1;
+                    交叉标记.push(-1);
+                } else {
+                    交叉标记.push(0);
+                }
+            } else {
+                交叉标记.push(0);
+            }
+        }
+
+        let 密集区 = Self::密集区域按间隔(&交叉标记, 最大间隔, 最少交叉数);
+
+        let mut map = HashMap::new();
+        map.insert("DIF上穿0".into(), dif_up.to_string());
+        map.insert("DIF下穿0".into(), dif_down.to_string());
+        map.insert("DEA上穿0".into(), dea_up.to_string());
+        map.insert("DEA下穿0".into(), dea_down.to_string());
+        map.insert("金叉次数".into(), golden.to_string());
+        map.insert("死叉次数".into(), death.to_string());
+        map.insert("密集交叉区域".into(), format!("{:?}", 密集区));
+        map
+    }
+
+    // ---- 买卖意义 ----
+
+    /// 买卖意义 — 核心买卖点判断逻辑
+    ///
+    /// 返回 (是否有意义, 原因字符串)
+    pub fn 买卖意义(实线: &虚线, 观察员: &crate::business::observer::观察者) -> (bool, String) {
+        let 普K序列 = &观察员.普通K线序列;
+        let 配置 = &观察员.配置;
+
+        if 实线.标识 != "笔" && 实线.标识 != "线段" && !实线.标识.starts_with("线段<") {
+            return (false, "标识不在范围内".into());
+        }
+
+        // KDJ指标完整性检查
+        match &实线.武.中.标的K线.kdj {
+            Some(kdj) if kdj.K.is_some() && kdj.D.is_some() && kdj.J.is_some() => {}
+            _ => return (false, "KDJ指标不完整".into()),
+        }
+
+        let 意义 = Self::缠K买卖点模式(&配置.买卖点_指标模式, &实线.武.中, 配置);
+        let 结果 = false;
+
+        let 背驰过: Vec<Rc<分型>> = if 实线.标识 == "笔" {
+            crate::algorithm::bi::笔::是否背驰过(实线, 观察员)
+        } else {
+            crate::algorithm::segment::线段::是否背驰过(实线, 观察员)
+        };
+
+        if 意义 {
+            if 实线.标识 == "笔" {
+                if Self::武之MACD均值(普K序列, 实线) {
+                    return (true, "武之MACD均值".into());
+                }
+                if Self::武之MACD极值(普K序列, 实线) && !背驰过.is_empty() {
+                    return (true, "背驰过且极值".into());
+                } else if 实线.武.与MACD柱子分型匹配() {
+                    return (
+                        true,
+                        format!(
+                            "背驰过:{},极值:{},柱子分型匹配",
+                            背驰过.len(),
+                            Self::武之MACD极值(普K序列, 实线)
+                        ),
+                    );
+                }
+            }
+            if 实线.标识 != "笔"
+                && crate::algorithm::segment::线段::判断线段内部是否背驰(实线, 观察员)
+            {
+                return (true, "线段内部背驰".into());
+            }
+        }
+
+        if !结果 && 意义 && 实线.武.中.与MACD柱子匹配() {
+            if Self::武之MACD极值(普K序列, 实线) && 背驰过.len() > 2 {
+                return (
+                    true,
+                    "没结果, 极值, 柱子分型匹配, 背驰过大于2次".into(),
+                );
+            }
+        }
+
+        (结果, "".into())
+    }
+}
+
+impl std::fmt::Display for 虚线 {
+    fn fmt(&self, f: &mut std::fmt::Formatter<'_>) -> std::fmt::Result {
+        if self.标识 == "笔" {
+            write!(
+                f,
+                "笔({}, {}, {}, {}, 周期: {}, 数量: {})",
+                self.序号,
+                self.方向(),
+                self.文,
+                self.武,
+                self.文.中.周期,
+                self.武.中.序号 - self.文.中.序号 + 1
+            )
+        } else {
+            let 四象 = crate::algorithm::segment::线段::四象(self);
+            let 缺口 = crate::algorithm::segment::线段::获取缺口(self);
+            let 缺口_str = match 缺口 {
+                Some(g) => format!("{}", g),
+                None => "None".to_string(),
+            };
+            let 确认K线_str = match &self.确认K线 {
+                Some(k) => format!("{}", k),
+                None => "None".to_string(),
+            };
+            write!(
+                f,
+                "{}<{}, {}, {}, {}, {}, 数量: {}, 缺口: {}, {}>",
+                self.标识,
+                self.序号,
+                四象,
+                self.方向(),
+                self.文,
+                self.武,
+                self.基础序列.len(),
+                缺口_str,
+                确认K线_str,
+            )
+        }
+    }
+}
diff --git a/chanlun/src/structure/feat_fractal.rs b/chanlun/src/structure/feat_fractal.rs
new file mode 100644
index 0000000..64b461e
--- /dev/null
+++ b/chanlun/src/structure/feat_fractal.rs
@@ -0,0 +1,24 @@
+use crate::structure::segment_feat::线段特征;
+use crate::types::分型结构;
+use std::rc::Rc;
+
+/// 特征分型 — 由三个线段特征元素构成的分型
+#[derive(Debug, Clone)]
+pub struct 特征分型 {
+    pub 左: Rc<线段特征>,
+    pub 中: Rc<线段特征>,
+    pub 右: Rc<线段特征>,
+    pub 结构: 分型结构,
+}
+
+impl 特征分型 {
+    pub fn new(左: Rc<线段特征>, 中: Rc<线段特征>, 右: Rc<线段特征>, 结构: 分型结构) -> Self {
+        Self { 左, 中, 右, 结构 }
+    }
+}
+
+impl std::fmt::Display for 特征分型 {
+    fn fmt(&self, f: &mut std::fmt::Formatter<'_>) -> std::fmt::Result {
+        write!(f, "特征分型<{}, {}>", self.结构, self.中)
+    }
+}
diff --git a/chanlun/src/structure/fractal_obj.rs b/chanlun/src/structure/fractal_obj.rs
new file mode 100644
index 0000000..7d0f8db
--- /dev/null
+++ b/chanlun/src/structure/fractal_obj.rs
@@ -0,0 +1,173 @@
+use crate::kline::chan_kline::缠论K线;
+use crate::types::分型结构;
+use crate::types::相对方向;
+use std::rc::Rc;
+
+/// 分型 — 由三根缠K构成（可能缺左或右）
+#[derive(Debug, Clone)]
+pub struct 分型 {
+    pub 左: Option<Rc<缠论K线>>,
+    pub 中: Rc<缠论K线>,
+    pub 右: Option<Rc<缠论K线>>,
+    pub 结构: 分型结构,
+    pub 时间戳: i64,
+    pub 分型特征值: f64,
+}
+
+impl 分型 {
+    pub fn new(左: Option<Rc<缠论K线>>, 中: Rc<缠论K线>, 右: Option<Rc<缠论K线>>) -> Self {
+        let 结构 = 中.分型.unwrap_or(分型结构::散);
+        let 时间戳 = 中.时间戳;
+        let 分型特征值 = 中.分型特征值;
+        Self {
+            左,
+            中,
+            右,
+            结构,
+            时间戳,
+            分型特征值,
+        }
+    }
+
+    /// 左中右三组关系
+    pub fn 关系组(&self) -> Option<(相对方向, 相对方向, 相对方向)> {
+        let 左 = self.左.as_ref()?;
+        let 右 = self.右.as_ref()?;
+        Some((
+            相对方向::分析(左.高, 左.低, self.中.高, self.中.低),
+            相对方向::分析(self.中.高, self.中.低, 右.高, 右.低),
+            相对方向::分析(左.高, 左.低, 右.高, 右.低),
+        ))
+    }
+
+    /// 分型强度
+    pub fn 强度(&self) -> f64 {
+        match self.结构 {
+            分型结构::顶 | 分型结构::上 => {
+                if let Some(ref 左) = self.左 {
+                    self.中.高 - 左.高
+                } else {
+                    0.0
+                }
+            }
+            分型结构::底 | 分型结构::下 => {
+                if let Some(ref 左) = self.左 {
+                    左.低 - self.中.低
+                } else {
+                    0.0
+                }
+            }
+            分型结构::散 => 0.0,
+        }
+    }
+
+    /// MACD柱子分型匹配
+    pub fn 与MACD柱子分型匹配(&self) -> bool {
+        match self.结构 {
+            分型结构::顶 | 分型结构::上 => {
+                if let Some(ref 左) = self.左 {
+                    左.与MACD柱子匹配()
+                } else {
+                    false
+                }
+            }
+            分型结构::底 | 分型结构::下 => {
+                if let Some(ref 右) = self.右 {
+                    右.与MACD柱子匹配()
+                } else {
+                    false
+                }
+            }
+            分型结构::散 => false,
+        }
+    }
+
+    /// 判断两个分型是否匹配
+    pub fn 判断分型(左: &分型, 右: &分型, 模式: &str) -> bool {
+        match 模式 {
+            "中" => 左.中.序号 == 右.中.序号,
+            _ => false,
+        }
+    }
+
+    /// 从缠K序列中获取以指定缠K为中元素的分型
+    pub fn 从缠K序列中获取分型(K线序列: &[Rc<缠论K线>], 中: &Rc<缠论K线>) -> Option<Self> {
+        let idx = K线序列.iter().position(|k| Rc::as_ptr(k) == Rc::as_ptr(中))?;
+        let 左 = if idx > 0 {
+            Some(Rc::clone(&K线序列[idx - 1]))
+        } else {
+            None
+        };
+        let 右 = if idx + 1 < K线序列.len() {
+            Some(Rc::clone(&K线序列[idx + 1]))
+        } else {
+            None
+        };
+        Some(Self::new(左, Rc::clone(中), 右))
+    }
+
+    /// 向分型序列中添加新分型
+    pub fn 向序列中添加(分型序列: &mut Vec<Rc<分型>>, 当前分型: Rc<分型>) {
+        if let Some(前一个) = 分型序列.last() {
+            if 前一个.时间戳 == 当前分型.时间戳 {
+                // 同一时间戳: 比较强度，保留更强的
+                match 当前分型.结构 {
+                    分型结构::顶 | 分型结构::上 => {
+                        if 当前分型.分型特征值 >= 前一个.分型特征值 {
+                            分型序列.pop();
+                            分型序列.push(当前分型);
+                        }
+                        return;
+                    }
+                    分型结构::底 | 分型结构::下 => {
+                        if 当前分型.分型特征值 <= 前一个.分型特征值 {
+                            分型序列.pop();
+                            分型序列.push(当前分型);
+                        }
+                        return;
+                    }
+                    分型结构::散 => {}
+                }
+            }
+            // 相同结构只保留更强的
+            if 前一个.结构 == 当前分型.结构 {
+                if (当前分型.结构 == 分型结构::顶 || 当前分型.结构 == 分型结构::上)
+                    && 当前分型.分型特征值 >= 前一个.分型特征值
+                {
+                    分型序列.pop();
+                    分型序列.push(当前分型);
+                } else if (当前分型.结构 == 分型结构::底 || 当前分型.结构 == 分型结构::下)
+                    && 当前分型.分型特征值 <= 前一个.分型特征值
+                {
+                    分型序列.pop();
+                    分型序列.push(当前分型);
+                }
+                return;
+            }
+        }
+        分型序列.push(当前分型);
+    }
+}
+
+impl crate::types::fractal::有高低 for 分型 {
+    fn 高(&self) -> f64 {
+        self.中.高
+    }
+    fn 低(&self) -> f64 {
+        self.中.低
+    }
+}
+
+impl std::fmt::Display for 分型 {
+    fn fmt(&self, f: &mut std::fmt::Formatter<'_>) -> std::fmt::Result {
+        write!(
+            f,
+            "{}<{}, {}, None: {}, None: {}>",
+            self.中.分型.unwrap_or(crate::types::分型结构::散),
+            self.时间戳,
+            crate::utils::format_f64_g(self.分型特征值),
+            if self.左.is_none() { "True" } else { "False" },
+            if self.右.is_none() { "True" } else { "False" },
+        )
+    }
+}
diff --git a/chanlun/src/structure/mod.rs b/chanlun/src/structure/mod.rs
new file mode 100644
index 0000000..8ccac6b
--- /dev/null
+++ b/chanlun/src/structure/mod.rs
@@ -0,0 +1,4 @@
+pub mod dash_line;
+pub mod feat_fractal;
+pub mod fractal_obj;
+pub mod segment_feat;
diff --git a/chanlun/src/structure/segment_feat.rs b/chanlun/src/structure/segment_feat.rs
new file mode 100644
index 0000000..4cc5e4c
--- /dev/null
+++ b/chanlun/src/structure/segment_feat.rs
@@ -0,0 +1,254 @@
+use crate::structure::dash_line::虚线;
+use crate::structure::feat_fractal::特征分型;
+use crate::structure::fractal_obj::分型;
+use crate::types::{分型结构, 相对方向};
+use std::rc::Rc;
+
+/// 线段特征 — 特征序列元素（内部是虚线的集合）
+#[derive(Debug, Clone)]
+pub struct 线段特征 {
+    pub 序号: i64,
+    pub 标识: String,
+    pub 线段方向: 相对方向,
+    pub 元素: Vec<Rc<虚线>>,
+}
+
+impl 线段特征 {
+    pub fn new(标识: String, 基础序列: Vec<Rc<虚线>>, 线段方向: 相对方向) -> Self {
+        Self {
+            序号: 0,
+            标识,
+            线段方向,
+            元素: 基础序列,
+        }
+    }
+
+    pub fn 图表标题(&self) -> String {
+        self.标识.clone()
+    }
+
+    /// 文 — 取特征序列元素中分型特征值最大/最小的文分型
+    pub fn 文(&self) -> Rc<分型> {
+        if self.线段方向.是否向上() {
+            // 向上 → 取最大的文
+            self.元素
+                .iter()
+                .max_by(|a, b| {
+                    a.文
+                        .分型特征值
+                        .partial_cmp(&b.文.分型特征值)
+                        .unwrap_or(std::cmp::Ordering::Equal)
+                })
+                .map(|x| Rc::clone(&x.文))
+                .unwrap_or_else(|| Rc::clone(&self.元素[0].文))
+        } else {
+            // 向下 → 取最小的文
+            self.元素
+                .iter()
+                .min_by(|a, b| {
+                    a.文
+                        .分型特征值
+                        .partial_cmp(&b.文.分型特征值)
+                        .unwrap_or(std::cmp::Ordering::Equal)
+                })
+                .map(|x| Rc::clone(&x.文))
+                .unwrap_or_else(|| Rc::clone(&self.元素[0].文))
+        }
+    }
+
+    /// 武 — 取特征序列元素中分型特征值最大/最小的武分型
+    pub fn 武(&self) -> Rc<分型> {
+        if self.线段方向.是否向上() {
+            self.元素
+                .iter()
+                .max_by(|a, b| {
+                    a.武
+                        .分型特征值
+                        .partial_cmp(&b.武.分型特征值)
+                        .unwrap_or(std::cmp::Ordering::Equal)
+                })
+                .map(|x| Rc::clone(&x.武))
+                .unwrap_or_else(|| Rc::clone(&self.元素[0].武))
+        } else {
+            self.元素
+                .iter()
+                .min_by(|a, b| {
+                    a.武
+                        .分型特征值
+                        .partial_cmp(&b.武.分型特征值)
+                        .unwrap_or(std::cmp::Ordering::Equal)
+                })
+                .map(|x| Rc::clone(&x.武))
+                .unwrap_or_else(|| Rc::clone(&self.元素[0].武))
+        }
+    }
+
+    pub fn 高(&self) -> f64 {
+        let 文 = self.文();
+        let 武 = self.武();
+        文.分型特征值.max(武.分型特征值)
+    }
+
+    pub fn 低(&self) -> f64 {
+        let 文 = self.文();
+        let 武 = self.武();
+        文.分型特征值.min(武.分型特征值)
+    }
+
+    /// 方向 — 线段方向的翻转
+    pub fn 方向(&self) -> 相对方向 {
+        self.线段方向.翻转()
+    }
+
+    /// 向特征序列元素中添加虚线
+    pub fn 添加(&mut self, 待添加虚线: Rc<虚线>) -> Result<(), String> {
+        if 待添加虚线.方向() == self.线段方向 {
+            return Err("添加方向与线段方向相同".into());
+        }
+        self.元素.push(待添加虚线);
+        Ok(())
+    }
+
+    /// 新建特征序列元素
+    pub fn 新建(虚线序列: Vec<Rc<虚线>>, 线段方向: 相对方向) -> Self {
+        let 标识 = format!("特征<虚线>");
+        Self::new(标识, 虚线序列, 线段方向)
+    }
+
+    /// 静态分析 — 从虚线序列生成特征序列元素列表
+    pub fn 静态分析(
+        虚线序列: &[Rc<虚线>],
+        线段方向: 相对方向,
+        四象: &str,
+        是否忽视: bool,
+    ) -> Vec<Rc<线段特征>> {
+        let mut 结果: Vec<Rc<线段特征>> = Vec::new();
+
+        // 需要被合并的方向集合
+        let 需要合并: Vec<相对方向> = match 四象 {
+            "老阳" | "老阴" if !是否忽视 => vec![相对方向::顺, 相对方向::逆, 相对方向::同],
+            _ => vec![相对方向::顺, 相对方向::同],
+        };
+
+        for 虚线 in 虚线序列 {
+            // 情况1：方向相同（可能触发分型替换）
+            if 虚线.方向() == 线段方向 {
+                if 结果.len() >= 3 {
+                    let 左 = Rc::clone(&结果[结果.len() - 3]);
+                    let 中 = Rc::clone(&结果[结果.len() - 2]);
+                    let 右 = Rc::clone(&结果[结果.len() - 1]);
+
+                    if let Some(结构) = 分型结构::分析(&*左, &*中, &*右, true, true) {
+                        let 应替换 = (线段方向 == 相对方向::向上
+                            && 结构 == 分型结构::顶
+                            && 虚线.高() > 中.高())
+                            || (线段方向 == 相对方向::向下
+                                && 结构 == 分型结构::底
+                                && 虚线.低() < 中.低());
+
+                        if 应替换 {
+                            let 小号虚线 = if 中.元素[0].序号 < 右.元素[0].序号 {
+                                &中.元素[0]
+                            } else {
+                                &右.元素[0]
+                            };
+                            let 大号虚线 = if 中.元素.last().unwrap().序号
+                                > 右.元素.last().unwrap().序号
+                            {
+                                &中.元素[中.元素.len() - 1]
+                            } else {
+                                &右.元素[右.元素.len() - 1]
+                            };
+                            let fake = 虚线::创建笔(
+                                Rc::clone(&小号虚线.文),
+                                Rc::clone(&大号虚线.武),
+                                false,
+                            );
+                            结果.pop();
+                            let idx = 结果.len() - 1;
+                            结果[idx] =
+                                Rc::new(Self::新建(vec![Rc::new(fake)], 线段方向));
+                        }
+                    }
+                }
+                continue;
+            }
+
+            // 情况2：方向不同（执行特征序列的合并/添加）
+            if 结果.is_empty() {
+                结果.push(Rc::new(Self::新建(vec![Rc::clone(虚线)], 线段方向)));
+                continue;
+            }
+
+            // 检查与最后一个特征序列的方向关系
+            let 最后_idx = 结果.len() - 1;
+            let 之前线段特征 = &*结果[最后_idx];
+            if 需要合并.contains(&相对方向::分析(
+                之前线段特征.高(),
+                之前线段特征.低(),
+                虚线.高(),
+                虚线.低(),
+            )) {
+                // Clone-modify-replace
+                let mut 新特征 = (*结果[最后_idx]).clone();
+                let _ = 新特征.添加(Rc::clone(虚线));
+                结果[最后_idx] = Rc::new(新特征);
+            } else {
+                结果.push(Rc::new(Self::新建(vec![Rc::clone(虚线)], 线段方向)));
+            }
+        }
+
+        结果
+    }
+
+    /// 获取分型序列
+    pub fn 获取分型序列(特征序列: &[Rc<线段特征>]) -> Vec<特征分型> {
+        let mut 结果 = Vec::new();
+        if 特征序列.len() < 3 {
+            return 结果;
+        }
+        for i in 2..特征序列.len() {
+            let 左 = Rc::clone(&特征序列[i - 2]);
+            let 中 = Rc::clone(&特征序列[i - 1]);
+            let 右 = Rc::clone(&特征序列[i]);
+
+            if let Some(结构) = 分型结构::分析_对象(
+                &*左 as &dyn crate::types::fractal::有高低,
+                &*中 as &dyn crate::types::fractal::有高低,
+                &*右 as &dyn crate::types::fractal::有高低,
+                true,
+                true,
+            ) {
+                结果.push(特征分型::new(左, 中, 右, 结构));
+            }
+        }
+        结果
+    }
+}
+
+impl crate::types::fractal::有高低 for 线段特征 {
+    fn 高(&self) -> f64 {
+        self.高()
+    }
+    fn 低(&self) -> f64 {
+        self.低()
+    }
+}
+
+impl std::fmt::Display for 线段特征 {
+    fn fmt(&self, f: &mut std::fmt::Formatter<'_>) -> std::fmt::Result {
+        if self.元素.is_empty() {
+            write!(f, "{}<{}, 空>", self.标识, self.线段方向)
+        } else {
+            write!(
+                f,
+                "{}<{}, {}, {}, {}>",
+                self.标识,
+                self.线段方向,
+                self.文(),
+                self.武(),
+                self.元素.len()
+            )
+        }
+    }
+}
diff --git a/chanlun/src/types/bsp_type.rs b/chanlun/src/types/bsp_type.rs
new file mode 100644
index 0000000..f873f81
--- /dev/null
+++ b/chanlun/src/types/bsp_type.rs
@@ -0,0 +1,99 @@
+use serde::{Deserialize, Serialize};
+
+/// 买卖点类型 —— 六类买卖点（一二三 + T1/T1P/T2/T2S/T3A/T3B）
+#[derive(Debug, Clone, Copy, PartialEq, Eq, Serialize, Deserialize)]
+pub enum 买卖点类型 {
+    #[serde(rename = "一买")]
+    一买,
+    #[serde(rename = "一卖")]
+    一卖,
+    #[serde(rename = "二买")]
+    二买,
+    #[serde(rename = "二卖")]
+    二卖,
+    #[serde(rename = "三买")]
+    三买,
+    #[serde(rename = "三卖")]
+    三卖,
+    #[serde(rename = "T1买")]
+    T1买,
+    #[serde(rename = "T1卖")]
+    T1卖,
+    #[serde(rename = "T1P买")]
+    T1P买,
+    #[serde(rename = "T1P卖")]
+    T1P卖,
+    #[serde(rename = "T2买")]
+    T2买,
+    #[serde(rename = "T2卖")]
+    T2卖,
+    #[serde(rename = "T2S买")]
+    T2S买,
+    #[serde(rename = "T2S卖")]
+    T2S卖,
+    #[serde(rename = "T3A买")]
+    T3A买,
+    #[serde(rename = "T3A卖")]
+    T3A卖,
+    #[serde(rename = "T3B买")]
+    T3B买,
+    #[serde(rename = "T3B卖")]
+    T3B卖,
+}
+
+impl std::fmt::Display for 买卖点类型 {
+    fn fmt(&self, f: &mut std::fmt::Formatter<'_>) -> std::fmt::Result {
+        match self {
+            Self::一买 => write!(f, "一买"),
+            Self::一卖 => write!(f, "一卖"),
+            Self::二买 => write!(f, "二买"),
+            Self::二卖 => write!(f, "二卖"),
+            Self::三买 => write!(f, "三买"),
+            Self::三卖 => write!(f, "三卖"),
+            Self::T1买 => write!(f, "T1买"),
+            Self::T1卖 => write!(f, "T1卖"),
+            Self::T1P买 => write!(f, "T1P买"),
+            Self::T1P卖 => write!(f, "T1P卖"),
+            Self::T2买 => write!(f, "T2买"),
+            Self::T2卖 => write!(f, "T2卖"),
+            Self::T2S买 => write!(f, "T2S买"),
+            Self::T2S卖 => write!(f, "T2S卖"),
+            Self::T3A买 => write!(f, "T3A买"),
+            Self::T3A卖 => write!(f, "T3A卖"),
+            Self::T3B买 => write!(f, "T3B买"),
+            Self::T3B卖 => write!(f, "T3B卖"),
+        }
+    }
+}
+
+impl 买卖点类型 {
+    pub fn 是买点(&self) -> bool {
+        matches!(
+            self,
+            Self::一买
+                | Self::二买
+                | Self::三买
+                | Self::T1买
+                | Self::T1P买
+                | Self::T2买
+                | Self::T2S买
+                | Self::T3A买
+                | Self::T3B买
+        )
+    }
+
+    pub fn 是卖点(&self) -> bool {
+        matches!(
+            self,
+            Self::一卖
+                | Self::二卖
+                | Self::三卖
+                | Self::T1卖
+                | Self::T1P卖
+                | Self::T2卖
+                | Self::T2S卖
+                | Self::T3A卖
+                | Self::T3B卖
+        )
+    }
+}
diff --git a/chanlun/src/types/direction.rs b/chanlun/src/types/direction.rs
new file mode 100644
index 0000000..e47bfc8
--- /dev/null
+++ b/chanlun/src/types/direction.rs
@@ -0,0 +1,108 @@
+use serde::{Deserialize, Serialize};
+
+/// 相对方向 —— K线之间的相对位置关系
+#[derive(Debug, Clone, Copy, PartialEq, Eq, Serialize, Deserialize)]
+pub enum 相对方向 {
+    #[serde(rename = "交叠向上")]
+    向上,
+    #[serde(rename = "交叠向下")]
+    向下,
+    #[serde(rename = "向上缺口")]
+    向上缺口,
+    #[serde(rename = "向下缺口")]
+    向下缺口,
+    #[serde(rename = "衔接向上")]
+    衔接向上,
+    #[serde(rename = "衔接向下")]
+    衔接向下,
+    #[serde(rename = "顺序包含")]
+    顺,
+    #[serde(rename = "逆序包含")]
+    逆,
+    #[serde(rename = "相同包含")]
+    同,
+}
+
+impl 相对方向 {
+    pub fn 翻转(&self) -> Self {
+        match self {
+            Self::向上 => Self::向下,
+            Self::向下 => Self::向上,
+            Self::向上缺口 => Self::向下缺口,
+            Self::向下缺口 => Self::向上缺口,
+            Self::衔接向上 => Self::衔接向下,
+            Self::衔接向下 => Self::衔接向上,
+            Self::顺 => Self::逆,
+            Self::逆 => Self::顺,
+            other => *other,
+        }
+    }
+
+    pub fn 是否向上(&self) -> bool {
+        matches!(self, Self::向上 | Self::向上缺口 | Self::衔接向上)
+    }
+
+    pub fn 是否向下(&self) -> bool {
+        matches!(self, Self::向下 | Self::向下缺口 | Self::衔接向下)
+    }
+
+    pub fn 是否包含(&self) -> bool {
+        matches!(self, Self::顺 | Self::逆 | Self::同)
+    }
+
+    pub fn 是否缺口(&self) -> bool {
+        matches!(self, Self::向下缺口 | Self::向上缺口)
+    }
+
+    pub fn 是否衔接(&self) -> bool {
+        matches!(self, Self::衔接向下 | Self::衔接向上)
+    }
+
+    /// 分析两个K线之间的相对方向
+    pub fn 分析(前高: f64, 前低: f64, 后高: f64, 后低: f64) -> Self {
+        if (前高 - 后高).abs() < f64::EPSILON && (前低 - 后低).abs() < f64::EPSILON {
+            return Self::同;
+        }
+        if 前高 > 后高 && 前低 > 后低 {
+            if (前低 - 后高).abs() < f64::EPSILON {
+                return Self::衔接向下;
+            }
+            if 前低 > 后高 {
+                return Self::向下缺口;
+            }
+            return Self::向下;
+        }
+        if 前高 < 后高 && 前低 < 后低 {
+            if (前高 - 后低).abs() < f64::EPSILON {
+                return Self::衔接向上;
+            }
+            if 前高 < 后低 {
+                return Self::向上缺口;
+            }
+            return Self::向上;
+        }
+        if 前高 >= 后高 && 前低 <= 后低 {
+            return Self::顺;
+        }
+        if 前高 <= 后高 && 前低 >= 后低 {
+            return Self::逆;
+        }
+        panic!("无法识别的方向: 前({},{}), 后({},{})", 前高, 前低, 后高, 后低);
+    }
+}
+
+impl std::fmt::Display for 相对方向 {
+    fn fmt(&self, f: &mut std::fmt::Formatter<'_>) -> std::fmt::Result {
+        match self {
+            Self::向上 => write!(f, "相对方向.向上"),
+            Self::向下 => write!(f, "相对方向.向下"),
+            Self::向上缺口 => write!(f, "相对方向.向上缺口"),
+            Self::向下缺口 => write!(f, "相对方向.向下缺口"),
+            Self::衔接向上 => write!(f, "相对方向.衔接向上"),
+            Self::衔接向下 => write!(f, "相对方向.衔接向下"),
+            Self::顺 => write!(f, "相对方向.顺"),
+            Self::逆 => write!(f, "相对方向.逆"),
+            Self::同 => write!(f, "相对方向.同"),
+        }
+    }
+}
diff --git a/chanlun/src/types/fractal.rs b/chanlun/src/types/fractal.rs
new file mode 100644
index 0000000..a8b873a
--- /dev/null
+++ b/chanlun/src/types/fractal.rs
@@ -0,0 +1,109 @@
+use serde::{Deserialize, Serialize};
+
+/// 分型结构 —— 三根K线构成的结构形态
+#[derive(Debug, Clone, Copy, PartialEq, Eq, Serialize, Deserialize)]
+pub enum 分型结构 {
+    #[serde(rename = "三连向上")]
+    上,
+    #[serde(rename = "三连向下")]
+    下,
+    #[serde(rename = "顶分型")]
+    顶,
+    #[serde(rename = "底分型")]
+    底,
+    #[serde(rename = "向右扩散")]
+    散,
+}
+
+impl std::fmt::Display for 分型结构 {
+    fn fmt(&self, f: &mut std::fmt::Formatter<'_>) -> std::fmt::Result {
+        match self {
+            Self::上 => write!(f, "上"),
+            Self::下 => write!(f, "下"),
+            Self::顶 => write!(f, "顶"),
+            Self::底 => write!(f, "底"),
+            Self::散 => write!(f, "散"),
+        }
+    }
+}
+
+impl 分型结构 {
+    /// 分析三根K线构成的分型结构（泛型版本）
+    pub fn 分析(
+        左: &impl 有高低,
+        中: &impl 有高低,
+        右: &impl 有高低,
+        可以逆序包含: bool,
+        忽视顺序包含: bool,
+    ) -> Option<Self> {
+        Self::分析_内部(左.高(), 左.低(), 中.高(), 中.低(), 右.高(), 右.低(), 可以逆序包含, 忽视顺序包含)
+    }
+
+    /// 分析三元素构成的分型结构（trait object 版本）
+    pub fn 分析_对象(
+        左: &dyn 有高低,
+        中: &dyn 有高低,
+        右: &dyn 有高低,
+        可以逆序包含: bool,
+        忽视顺序包含: bool,
+    ) -> Option<Self> {
+        Self::分析_内部(左.高(), 左.低(), 中.高(), 中.低(), 右.高(), 右.低(), 可以逆序包含, 忽视顺序包含)
+    }
+
+    fn 分析_内部(
+        左高: f64, 左低: f64,
+        中高: f64, 中低: f64,
+        右高: f64, 右低: f64,
+        可以逆序包含: bool,
+        忽视顺序包含: bool,
+    ) -> Option<Self> {
+        use crate::types::direction::相对方向;
+
+        let 左中关系 = 相对方向::分析(左高, 左低, 中高, 中低);
+        let 中右关系 = 相对方向::分析(中高, 中低, 右高, 右低);
+
+        let 向上类 = |d: 相对方向| d.是否向上();
+        let 向下类 = |d: 相对方向| d.是否向下();
+
+        match (左中关系, 中右关系) {
+            // 顺序包含 — 忽视时可以绕过
+            (相对方向::顺, _) if !忽视顺序包含 => {
+                panic!("顺序包含: {:?} {:?}", 左中关系, 中右关系);
+            }
+            (_, 相对方向::顺) if !忽视顺序包含 => {
+                panic!("顺序包含: {:?} {:?}", 左中关系, 中右关系);
+            }
+            // 向上 + 向上 = 三连上
+            (a, b) if 向上类(a) && 向上类(b) => Some(Self::上),
+            // 向上 + 向下 = 顶分型
+            (a, b) if 向上类(a) && 向下类(b) => Some(Self::顶),
+            // 向上 + 逆序包含 = 上
+            (a, 相对方向::逆) if 向上类(a) && 可以逆序包含 => Some(Self::上),
+            // 向下 + 向上 = 底分型
+            (a, b) if 向下类(a) && 向上类(b) => Some(Self::底),
+            // 向下 + 向下 = 三连下
+            (a, b) if 向下类(a) && 向下类(b) => Some(Self::下),
+            // 向下 + 逆序包含 = 下
+            (a, 相对方向::逆) if 向下类(a) && 可以逆序包含 => Some(Self::下),
+            // 逆序包含 + 向上 = 底
+            (相对方向::逆, a) if 向上类(a) && 可以逆序包含 => Some(Self::底),
+            // 逆序包含 + 向下 = 顶
+            (相对方向::逆, a) if 向下类(a) && 可以逆序包含 => Some(Self::顶),
+            // 逆序包含 + 逆序包含 = 散
+            (相对方向::逆, 相对方向::逆) if 可以逆序包含 => Some(Self::散),
+            _ => {
+                eprintln!(
+                    "无法识别的分型结构: 左中={:?}, 中右={:?}",
+                    左中关系, 中右关系
+                );
+                None
+            }
+        }
+    }
+}
+
+/// Trait for types that have 高 and 低 (used by 分型结构::分析)
+pub trait 有高低 {
+    fn 高(&self) -> f64;
+    fn 低(&self) -> f64;
+}
diff --git a/chanlun/src/types/gap.rs b/chanlun/src/types/gap.rs
new file mode 100644
index 0000000..cef1fd0
--- /dev/null
+++ b/chanlun/src/types/gap.rs
@@ -0,0 +1,51 @@
+use serde::{Deserialize, Serialize};
+
+/// 缺口 —— 两个价格区间之间的空隙
+#[derive(Debug, Clone, Copy, PartialEq, Serialize, Deserialize)]
+pub struct 缺口 {
+    pub 高: f64,
+    pub 低: f64,
+}
+
+impl 缺口 {
+    pub fn new(高: f64, 低: f64) -> Self {
+        assert!(高 > 低, "缺口高必须大于低: 高={高}, 低={低}");
+        Self { 高, 低 }
+    }
+
+    /// 在 [起点, 终点] 区间内居中截取一个子区间
+    pub fn 居中截取区间(起点: f64, 终点: f64, 比例: f64) -> Option<Self> {
+        let (起点, 终点) = if 起点 <= 终点 {
+            (起点, 终点)
+        } else {
+            (终点, 起点)
+        };
+
+        let 总长 = 终点 - 起点;
+        let 偏移 = 总长 * 比例;
+        let 中心 = (起点 + 终点) / 2.0;
+
+        let 下界 = 中心 - 偏移;
+        let 上界 = 中心 + 偏移;
+
+        if 下界 > 终点 || 上界 < 起点 {
+            return None;
+        }
+
+        let 下界 = 下界.max(起点);
+        let 上界 = 上界.min(终点);
+
+        Some(Self::new(上界.max(下界), 上界.min(下界)))
+    }
+}
+
+impl std::fmt::Display for 缺口 {
+    fn fmt(&self, f: &mut std::fmt::Formatter<'_>) -> std::fmt::Result {
+        write!(
+            f,
+            "缺口区间<{} <=> {}>",
+            crate::utils::format_f64_g(self.低),
+            crate::utils::format_f64_g(self.高)
+        )
+    }
+}
diff --git a/chanlun/src/types/mod.rs b/chanlun/src/types/mod.rs
new file mode 100644
index 0000000..a398ef1
--- /dev/null
+++ b/chanlun/src/types/mod.rs
@@ -0,0 +1,9 @@
+pub mod bsp_type;
+pub mod direction;
+pub mod fractal;
+pub mod gap;
+
+pub use bsp_type::买卖点类型;
+pub use direction::相对方向;
+pub use fractal::分型结构;
+pub use gap::缺口;
diff --git a/chanlun/src/utils/datetime.rs b/chanlun/src/utils/datetime.rs
new file mode 100644
index 0000000..7e0be6d
--- /dev/null
+++ b/chanlun/src/utils/datetime.rs
@@ -0,0 +1,27 @@
+use chrono::DateTime;
+
+/// 将多种类型统一转为时间戳 (Unix epoch 秒)
+pub fn 转化为时间戳(ts: &str) -> Option<i64> {
+    // 尝试解析为整数时间戳
+    if let Ok(v) = ts.parse::<i64>() {
+        return Some(v);
+    }
+    // 尝试解析为浮点时间戳
+    if let Ok(v) = ts.parse::<f64>() {
+        return Some(v as i64);
+    }
+    // 尝试 ISO 格式日期字符串
+    if let Ok(dt) = DateTime::parse_from_rfc3339(ts) {
+        return Some(dt.timestamp());
+    }
+    // 尝试 "YYYY-MM-DD HH:MM:SS" 格式
+    if let Ok(dt) = chrono::NaiveDateTime::parse_from_str(ts, "%Y-%m-%d %H:%M:%S") {
+        return Some(dt.and_utc().timestamp());
+    }
+    None
+}
+
+/// 将多种类型转为时间戳数字 (i64)
+pub fn 转化为时间戳_数字(ts: &str) -> Option<i64> {
+    转化为时间戳(ts)
+}
diff --git a/chanlun/src/utils/format.rs b/chanlun/src/utils/format.rs
new file mode 100644
index 0000000..a688b39
--- /dev/null
+++ b/chanlun/src/utils/format.rs
@@ -0,0 +1,14 @@
+/// Format f64 with Python :g semantics — strip trailing zeros, no scientific notation for common values
+pub fn format_f64_g(value: f64) -> String {
+    if value.is_nan() {
+        return "nan".to_string();
+    }
+    if value.is_infinite() {
+        return if value > 0.0 { "inf".to_string() } else { "-inf".to_string() };
+    }
+
+    // Use high precision then trim trailing zeros
+    let s = format!("{:.15}", value);
+    let s = s.trim_end_matches('0');
+    s.trim_end_matches('.').to_string()
+}
diff --git a/chanlun/src/utils/mod.rs b/chanlun/src/utils/mod.rs
new file mode 100644
index 0000000..6070737
--- /dev/null
+++ b/chanlun/src/utils/mod.rs
@@ -0,0 +1,5 @@
+pub mod datetime;
+pub mod format;
+
+pub use datetime::{转化为时间戳, 转化为时间戳_数字};
+pub use format::format_f64_g;