update Decoder

Decoder.py

@@ -112,8 +112,8 @@ class Decoder_main(threading.Thread):
         elif decoder_class == 'mi' or decoder_class == 'ma':
             self.zmqServer.interval_init(decoder_class)
             self.n_chan = 21
-            self.interval_epoch = ast.literal_eval(IniRead('system', 'MI_IntervalEpoch'))
-            self.sample_length = round(self.interval_epoch[1] - self.interval_epoch[0], 6)  # 解码数据长度2s,# 精确到小数点后6位
+            self.interval_epoch = ast.literal_eval(IniRead('system', 'MI_IntervalEpoch'))  # [0.5, 4.5]
+            self.sample_length = round(self.interval_epoch[1] - self.interval_epoch[0], 6)  # 解码数据长度4s,# 精确到小数点后6位
             self.single_train = 40  # 单类别数量
             self.num_target = 2  # 分类目标数目
 
@@ -370,7 +370,7 @@ class Decoder_main(threading.Thread):
         '''训练阶段采集数据'''
         if self.zmqServer.state_mode == 'train' and self.train_started == False:  # 训练状态
             if self.zmqServer.epoch_finished and self.zmqServer.paradigmBuffer.GetDataLenCount() >= \
-                    self.interval_epoch[1] + self.zmqServer.event_inner_idx:
+                    self.zmqServer.train_epoch[1] + self.zmqServer.event_inner_idx:
                 self.currentLabel = self.zmqServer.currentLabel  # 同步当前标签
                 algo_log(f"训练队列数据：{self.zmqServer.paradigmBuffer.GetDataLenCount()}", level="DEBUG")
                 originalTrial = self.zmqServer.paradigmBuffer.get_MIData()  # 取出MI导联数据