Revert chan to the most valuable one

ChanKLC.py

@@ -31,10 +31,6 @@ class ChanKLC():
         self.rsi = klu.rsi
         self.volume_ratio = klu.volume_ratio
         self.macdhist = 0
-        
-        # === 新增：KLC类型 ===
-        self.klc_type = None  # KLC类型：大阳线、大阴线、小阳线、小阴线
-        
     def set_klc_fx_type(self, klc_fx_type):
         #print(self.start_time, klc_fx_type, self.get_feature_data()['klu_macd'], self.get_feature_data()['klu_macdhist'], self.get_feature_data()['klu_rsi'])
         self.klc_fx_type = klc_fx_type
@@ -53,13 +49,7 @@ class ChanKLC():
         self.volume_ratio = self.volume_ratio / len(self.klus)
         self.volume = self.volume / len(self.klus)
         self.macdhist = self.macdhist / len(self.klus)
-    def contain_klu_fx(self):
-        if len(self.klus) > 0:
-            for klu in self.klus:
-                klu.update_realtime_analysis()
-                if klu.fx_type == self.fx and klu.fx_strength > 1.8:
-                    return True
-        return False
+   
     def set_next(self, klc):
         self.next = klc
     def set_pre(self, klc):
@@ -1157,78 +1147,6 @@ class ChanKLC():
         
         return features
 
-    def check_fx_klu_strength(self):
-        if self.pre and self.next and self.next.end_klu:
-            strength = 0
-            klc1 = self.pre
-            klc2 = self
-            klc3 = self.next
-            # 检查包含关系
-            inc = self.check_include_relation(klc1, klc2, klc3)
-            if not inc:
-                # 检查分型类型
-                if self.fx == Chan_FX_TYPE.TOP:
-                    # (1)没有包含关系+1
-                    strength += 0
-                    print(self.start_time, "1")
-                    # (2)第1条K线是一条大阳线，而第2、3条K线是小阴线、小阳线，那么这个分型结构的意义就不大了，强度 -1
-                    if self.pre.cal_klu_min_max() > 0.5 and self.cal_klu_min_max() < 0.2 and self.next.cal_klu_min_max() < 0.2:
-                        strength += -1
-                        print(self.start_time, "2")
-                    # (3)第2条K线有长上影线或者就是大阴线，而第3条K线不能以阳线收在第2条K线区间的一半之上，那么该顶分型的力度就比较大
-                    if ((self.close < self.open and self.cal_klu_min_max() > 0.5) or self.cal_klu_upper_shadow() > 0.6) and not (self.next.close > self.next.open and self.next.close > (self.high-self.low)/2):
-                        strength += 1
-                        print(self.start_time, "3")
-            else:
-                if self.fx == Chan_FX_TYPE.TOP:
-                    # (4)第2条K线和第3条K线为包含关系，而第3条K线为大阴线(直接把为阳线的第2条K线“吃掉”)，这是最坏的一种包含关系。
-                    if self.start_klu.index - self.end_klu.index < 0:
-                        klu1 = self.start_klu
-                        klu2 = self.klus[1]
-                        print(self.start_time, self.end_time, "length: ", len(self.klus), klu1.index, klu2.index)
-                        if klu2.close < klu2.open and 100*abs(klu2.open - klu2.close) / klu2.open > 0.5 and klu1.high <= klu2.high and klu1.low >= klu2.low:
-                            strength += 1
-                            print(self.start_time, "4")
-                    # (5)第3条K线如果跌破第1条K线的底而且不能高于第1条K线区间的一半之上，则属于较弱的一种，也就是说这种顶分型出现后股价见顶的可能性不大。
-                    if self.next.low < self.pre.low and self.next.high < (self.pre.high + self.pre.low)/2:
-                        strength += -1
-                        print(self.start_time, "5")
-            return strength
-        else:
-            return 0
-    def cal_klu_upper_shadow(self):
-        """
-        计算KLC的上影线长度
-        上影线 = 最高价 - max(开盘价, 收盘价)
-        """
-        if self.high <= 0:  # 避免无效数据
-            return 0
-            
-        # 计算上影线长度
-        upper_shadow = self.high - max(self.open, self.close)
-        
-        # 计算相对上影线长度（相对于整个K线区间）
-        total_range = self.high - self.low
-        if total_range > 0:
-            upper_shadow_ratio = upper_shadow / total_range
-        else:
-            upper_shadow_ratio = 0
-            
-        return upper_shadow_ratio
-    def cal_klu_min_max(self):
-        """
-        计算KLC类型：大阳线、大阴线、小阳线、小阴线
-        """
-        if self.open <= 0:  # 避免除零错误
-            return 0
-        line_type = 1000*abs(self.open - self.close) / self.open
-        print(self.start_time, line_type)
-        return line_type
-    def check_include_relation(self, klc1, klc2, klc3):
-        if klc1.start_klu.index - klc1.end_klu.index == 0 and klc2.start_klu.index - klc2.end_klu.index == 0 and klc3.start_klu.index - klc3.end_klu.index == 0:
-            return False
-        else:
-            return True
     def cal_fx_strength(self):
         """
         用self.pre和self.next实现分型强弱判断
@@ -1246,12 +1164,11 @@ class ChanKLC():
         -2: 弱分型（明显中继）
         -3: 极弱分型（无效分型）
         """
-        #return self.check_fx_klu_strength()
         # 检查是否为分型，且有前后K线数据
-        if self.fx == Chan_FX_TYPE.UNKNOWN or self.klc_fx_type == Chan_FX_TYPE.UNKNOWN:
+        if self.fx == Chan_FX_TYPE.UNKNOWN:
             return 0
         if not self.pre or not self.next:
-            return -100
+            return 100
         # === 核心判断：分型在笔中的位置 ===
         
         # 1. 检查这个分型是否能够终结当前笔
@@ -1283,7 +1200,6 @@ class ChanKLC():
         
         # 分型质量调整
         base_score += fx_quality
-        #base_score += self.check_fx_klu_strength()
         #print(self.start_time, base_score, is_bi_end, post_fx_confirmation, fx_quality)
         # 限制在-3到3范围内
         return max(-3, min(3, base_score))
@@ -1334,7 +1250,7 @@ class ChanKLC():
         first_low = self.pre.low
         middle_low = self.low
         key_support = min(first_low, middle_low)
-        last_klc = None
+        
         for i, klc in enumerate(subsequent_klcs):
             # 检查是否跌破关键支撑
             if klc.low < key_support:
@@ -1347,8 +1263,7 @@ class ChanKLC():
             # 检查下跌趋势
             if i > 0 and klc.close < subsequent_klcs[i-1].close:
                 downward_trend += 1
-            last_klc = klc
-        print(last_klc.start_time, last_klc.end_time)
+        
         # 强烈笔终结：跌破关键位且无新高
         if broken_key_levels >= 1 and new_highs == 0 and downward_trend >= 2:
             return 2
@@ -1381,7 +1296,7 @@ class ChanKLC():
         first_high = self.pre.high
         middle_high = self.high
         key_resistance = max(first_high, middle_high)
-        last_klc = None
+        
         for i, klc in enumerate(subsequent_klcs):
             # 检查是否突破关键阻力
             if klc.high > key_resistance:
@@ -1394,8 +1309,7 @@ class ChanKLC():
             # 检查上涨趋势
             if i > 0 and klc.close > subsequent_klcs[i-1].close:
                 upward_trend += 1
-            last_klc = klc
-        print(last_klc.start_time, last_klc.end_time)
+        
         # 强烈笔终结：突破关键位且无新低
         if broken_key_levels >= 1 and new_lows == 0 and upward_trend >= 2:
             return 2