修改排版，加入up，down，flat，unknown显示

web/app.py

@@ -352,12 +352,13 @@ def analyze_chan(df, symbol=None, timeframe=None):
     
     # 初始化多时间周期数据以获取EMA52
     ema52_dict = None
-    if symbol and timeframe:
+    # 先暂时不用这个功能，太慢了
+    if symbol and timeframe and False:
         try:
             # 获取不同时间周期的数据用于初始化
-            df_1h = get_kl_data(symbol, '1h', limit=800) if timeframe != '1h' else df
-            df_1d = get_kl_data(symbol, '1d', limit=800) if timeframe != '1d' else df
-            df_1M = get_kl_data(symbol, '1M', limit=800) if timeframe != '1M' else df
+            df_1h = get_kl_data(symbol, '1h', limit=1500) if timeframe != '1h' else df
+            df_1d = get_kl_data(symbol, '1d', limit=2000) if timeframe != '1d' else df
+            df_1M = get_kl_data(symbol, '1M', limit=1500) if timeframe != '1M' else df
             
             # 添加指标
             if df_1h is not None and len(df_1h) > 0:
@@ -1659,6 +1660,24 @@ def analyze():
         else:
             replay_data = None
         
+        # 基于已有 KLC 列表生成趋势标记（不做额外计算）
+        klc_trend = []
+        try:
+            for klc in analysis_result.get('klc_list', []):
+                trend_val = getattr(klc, 'trend', None)
+                t_obj = getattr(klc, 'end_time', None) or getattr(klc, 'start_time', None)
+                if trend_val is None or t_obj is None:
+                    continue
+                # 统一成字符串：UP/DOWN/FLAT/UNKNOWN
+                trend_name = str(trend_val)
+                if '.' in trend_name:
+                    trend_name = trend_name.split('.')[-1]
+                time_str = format_time_safely(t_obj, client_tz)
+                if time_str:
+                    klc_trend.append({'time': time_str, 'trend': trend_name})
+        except Exception:
+            klc_trend = []
+
         # 添加主周期分析结果到返回数据
         result.update({
             'kline_data': clean_dataframe_for_json(df).to_dict('records'),
@@ -1753,7 +1772,9 @@ def analyze():
             # 添加ChanMACD分析数据
             'chan_macd': serialize_chan_macd_data(analysis_result.get('chan_macd', {}), client_tz),
             # 添加多时间周期EMA52数据
-            'ema52_dict': analysis_result.get('ema52_dict', {})
+            'ema52_dict': analysis_result.get('ema52_dict', {}),
+            # 直接输出KLC趋势标记（使用已有trend字段）
+            'klc_trend': klc_trend
         })
         
         # 如果生成了回放数据，添加到返回结果中
@@ -1775,6 +1796,23 @@ def analyze():
             # 计算小周期MACD数据
             element_macd_data = calculate_macd(element_df)
             
+            # 组装小周期 KLC 趋势（仅提取已有 trend，不做重算）
+            try:
+                element_klc_trend = []
+                for klc in element_analysis.get('klc_list', []):
+                    trend_val = getattr(klc, 'trend', None)
+                    t_obj = getattr(klc, 'end_time', None) or getattr(klc, 'start_time', None)
+                    if trend_val is None or t_obj is None:
+                        continue
+                    trend_name = str(trend_val)
+                    if '.' in trend_name:
+                        trend_name = trend_name.split('.')[-1]
+                    time_str = format_time_safely(t_obj, client_tz)
+                    if time_str:
+                        element_klc_trend.append({'time': time_str, 'trend': trend_name})
+            except Exception:
+                element_klc_trend = []
+
             # 添加小周期分析结果到返回数据
             result['element_timeframe'] = element_timeframe
             result['element_macd'] = element_macd_data  # 添加小周期MACD数据
@@ -1880,6 +1918,9 @@ def analyze():
             # 添加次周期ChanMACD分析数据
             result['element_chan_macd'] = serialize_chan_macd_data(element_analysis.get('chan_macd', {}), client_tz)
             
+            # 添加小周期 KLC 趋势标记
+            result['element_klc_trend'] = element_klc_trend
+
             pass
     
     return jsonify(result)