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update Decoder

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lizhao
2026-06-10 15:18:22 +08:00
parent b329989181
commit 43adc6fb42
3 changed files with 25 additions and 10 deletions
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6
Decoder.py
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@@ -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

25
Zmq/zmqServer.py
View File

@@ -96,6 +96,7 @@ class zmqServer(threading.Thread):
self.pack_contain_event = False
self.event_inner_idx = -1
self.interval_inited = False
self.last_epoch_finish_time = None
def reset_state(self):
"""清空采集器状态和缓存数据"""
@@ -119,11 +120,11 @@ class zmqServer(threading.Thread):
self.train_latency = (self.train_epoch[1] + 0.1 * self.device_info['sample_rate']) // 5 #120包 600个点
elif decoder_class == 'mi':
interval_epoch = ast.literal_eval(IniRead('system', 'MI_IntervalEpoch'))
self.interval_epoch = [int(i * self.device_info['sample_rate']) for i in interval_epoch]
interval_epoch = ast.literal_eval(IniRead('system', 'MI_IntervalEpoch')) # [0.5, 4.5]
self.interval_epoch = [int(i * self.device_info['sample_rate']) for i in interval_epoch] #[125, 1125]
self.train_epoch = self.interval_epoch.copy()
self.latency = self.interval_epoch[1] // 5
self.train_latency = self.latency
self.latency = self.interval_epoch[1] // 5 #225
self.train_latency = self.latency #225
algo_log(f"时间窗初始化完成: {interval_epoch}", level="INFO")
self.count_events: Dict[str, int] = {}
@@ -325,8 +326,22 @@ class zmqServer(threading.Thread):
if self.pack_contain_event:
self.paradigmBuffer.resetAllPara()
self.paradigmBuffer.appendBuffer(data_np)
if self.epoch_finished:
algo_log('Epoch采集完成: ' + datetime.datetime.now().strftime('%H:%M:%S.%f')[:-3], level="DEBUG")
now = datetime.datetime.now()
time_diff_str = ""
# 计算与上一次Epoch完成的时间差
if self.last_epoch_finish_time is not None:
# 时间差 单位：秒，保留3位小数
delta_seconds = (now - self.last_epoch_finish_time).total_seconds()
time_diff_str = f" | 与上一次间隔: {delta_seconds:.3f} s"
# 拼接日志，增加时间差信息
log_msg = f"Epoch采集完成: {now.strftime('%H:%M:%S.%f')[:-3]}{time_diff_str}"
algo_log(log_msg, level="DEBUG")
# 更新上一次Epoch完成时间为当前时间
self.last_epoch_finish_time = now
else:
self.paradigmBuffer.appendBuffer(data_np)

4
upperHost_stimmock/MI_headless.py
View File

@@ -172,8 +172,8 @@ def run_headless():
client.send_data('decoderClass', 'mi')
# MI_IntervalEpoch = [0.5, 4.5]，trial时长 = 4.5-0.5 = 4.0s
_mi_iv = ast.literal_eval(IniRead('system', 'MI_IntervalEpoch'))
_trial_sec = float(_mi_iv[1] - _mi_iv[0])
_mi_iv = ast.literal_eval(IniRead('system', 'MI_IntervalEpoch')) # [0.5, 4.5]
_trial_sec = float(_mi_iv[1] - _mi_iv[0]) # 4.0s
_margin = 1.0
train_time = max(5.0, _trial_sec + _margin) # 训练刺激时长（与 MI_main.py 保持一致）