change the klc fx strength

ChanKLC.py

@@ -1214,7 +1214,8 @@ class ChanKLC():
 		
 		# 分型质量调整
 		base_score += fx_quality
-		#print(self.start_time, base_score, is_bi_end, post_fx_confirmation, fx_quality)
+		print(self.start_time, base_score, is_bi_end, post_fx_confirmation, fx_quality)
+		# 2025-06-07 08:15:00 1.5 0 0.8 0.7
 		# 限制在-3到3范围内
 		return max(-3, min(3, base_score))
 	
@@ -1235,7 +1236,7 @@ class ChanKLC():
 		# 获取分型后的几根K线数据
 		subsequent_klcs = []
 		temp = self.next
-		for i in range(klc_offset):  # 检查后续4根K线
+		for i in range(klc_offset): 
 			if temp:
 				subsequent_klcs.append(temp)
 				temp = temp.next if hasattr(temp, 'next') else None
@@ -1244,7 +1245,7 @@ class ChanKLC():
 		
 		if len(subsequent_klcs) < 2:
 			return 0
-			
+		print(subsequent_klcs[len(subsequent_klcs)-1].start_time)
 		if self.fx == Chan_FX_TYPE.TOP:
 			return self._check_top_bi_ending(subsequent_klcs)
 		else:  # BOTTOM
@@ -1283,7 +1284,7 @@ class ChanKLC():
 			return 2
 			
 		# 可能笔终结：部分条件满足
-		if (broken_key_levels >= 1 and new_highs <= 1) or (new_highs == 0 and downward_trend >= 3):
+		if (broken_key_levels >= 1 and new_highs <= 1) or (new_highs == 0 and downward_trend >= 1):
 			return 1
 			
 		# 明显中继：出现新高且未跌破关键位
@@ -1323,13 +1324,13 @@ class ChanKLC():
 			# 检查上涨趋势
 			if i > 0 and klc.close > subsequent_klcs[i-1].close:
 				upward_trend += 1
-		
+			
 		# 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
 			
 		# 可能笔终结：部分条件满足
-		if (broken_key_levels >= 1 and new_lows <= 1) or (new_lows == 0 and upward_trend >= 3):
+		if (broken_key_levels >= 1 and new_lows <= 1) or (new_lows == 0 and upward_trend >= 1):
 			return 1
 			
 		# 明显中继：出现新低且未突破关键位
@@ -1392,7 +1393,7 @@ class ChanKLC():
 			high_diff1 = (self.high - self.pre.high) / self.high if self.high > 0 else 0
 			high_diff2 = (self.high - self.next.high) / self.high if self.high > 0 else 0
 			min_diff = 33*min(high_diff1, high_diff2)
-			print(min_diff)
+			
 			if min_diff > 0.03:  # 非常突出
 				score += 0.5
 			elif min_diff > 0.01:  # 比较突出
@@ -1404,7 +1405,7 @@ class ChanKLC():
 			# 低点突出程度
 			low_diff1 = (self.pre.low - self.low) / self.pre.low if self.pre.low > 0 else 0
 			low_diff2 = (self.next.low - self.low) / self.next.low if self.next.low > 0 else 0
-			min_diff = min(low_diff1, low_diff2)
+			min_diff = 33*min(low_diff1, low_diff2)
 			
 			if min_diff > 0.03:  # 非常突出
 				score += 0.5