From ba4ae9264798d43eb683f6f482e205c963ac36fe Mon Sep 17 00:00:00 2001 From: lizhao Date: Wed, 10 Jun 2026 16:04:02 +0800 Subject: [PATCH] replace print with algo_log --- Decoder.py | 6 +++--- MI/Algorithm/conformer_2class.py | 31 ++++++++++++++-------------- MI/Algorithm/conformer_2class_cpu.py | 3 ++- SSVEP/dwfbcca.py | 15 +++++++------- Zmq/zmqServer.py | 8 +++---- config.ini | 1 + nuitka_3in1_package.sh | 2 +- 7 files changed, 33 insertions(+), 33 deletions(-) diff --git a/Decoder.py b/Decoder.py index cde5d7c..827142c 100644 --- a/Decoder.py +++ b/Decoder.py @@ -14,8 +14,8 @@ from torch.autograd import Variable # from Device.SunnyLinker import SunnyLinker64 from SSMVEP.algorithm.tdca import TDCA from SSMVEP.algorithm.base import generate_cca_references -from concentration.algorithm.calculate_focus import Calculate -from blinkdetection.algorithm.eye_detection import blink_detection +# from concentration.algorithm.calculate_focus import Calculate +# from blinkdetection.algorithm.eye_detection import blink_detection from Zmq.zmqServer import zmqServer from Zmq.zmqClient import zmqClient from MI.Algorithm.conformer_2class import onlineTrain @@ -425,7 +425,7 @@ class Decoder_main(threading.Thread): algo_log(f"MI运动意图识别: {y_pred}") self.zmqServer.broadcast_message('paradigm', int(y_pred.item())) end = time.time() - print(f'发送给界面完成,耗时{end - start:.3f}s。') + algo_log(f'MI发送给界面完成,耗时{end - start:.3f}s。') else: # 休息状态 if self.zmqServer.paradigmBuffer.GetDataLenCount() < 25: time.sleep(0.005) diff --git a/MI/Algorithm/conformer_2class.py b/MI/Algorithm/conformer_2class.py index f2a02ae..69a77f3 100644 --- a/MI/Algorithm/conformer_2class.py +++ b/MI/Algorithm/conformer_2class.py @@ -34,7 +34,7 @@ cudnn.benchmark = True cudnn.deterministic = True from sklearn.model_selection import train_test_split # writer = SummaryWriter('./TensorBoardX/') - +from logs.log import algo_log # Convolution module # use conv to capture local features, instead of postion embedding. @@ -318,11 +318,11 @@ class ExP(): train_pred = torch.max(outputs, 1)[1] train_acc = float((train_pred == label).cpu().numpy().astype(int).sum()) / float(label.size(0)) - print('Epoch:', e, + algo_log('Epoch:', e, ' Train loss: %.6f' % loss.detach().cpu().numpy(), ' Test loss: %.6f' % loss_test.detach().cpu().numpy(), ' Train accuracy %.6f' % train_acc, - ' Test accuracy is %.6f' % acc) + ' Test accuracy is %.6f' % acc, level="debug") self.log_write.write(str(e) + " " + str(acc) + "\n") num = num + 1 @@ -335,8 +335,8 @@ class ExP(): torch.save(self.model, model_path) averAcc = averAcc / num - print('The average accuracy is:', averAcc) - print('The best accuracy is:', bestAcc) + algo_log('The average accuracy is:', averAcc, level="debug") + algo_log('The best accuracy is:', bestAcc, level="debug") self.log_write.write('The average accuracy is: ' + str(averAcc) + "\n") self.log_write.write('The best accuracy is: ' + str(bestAcc) + "\n") @@ -346,10 +346,10 @@ class ExP(): def onlineTrain(data_queue,result_queue): import torch - print(f"[DEBUG] torch.__version__ = {torch.__version__}") - print(f"[DEBUG] torch.cuda.is_available() = {torch.cuda.is_available()}") + algo_log(f"[DEBUG] torch.__version__ = {torch.__version__}", level="debug") + algo_log(f"[DEBUG] torch.cuda.is_available() = {torch.cuda.is_available()}", level="debug") if torch.cuda.is_available(): - print(f"[DEBUG] GPU = {torch.cuda.get_device_name(0)}") + algo_log(f"[DEBUG] GPU = {torch.cuda.get_device_name(0)}", level="debug") try: starttime = datetime.datetime.now() @@ -366,12 +366,12 @@ def onlineTrain(data_queue,result_queue): data = data_queue.get(timeout=30) all_data, all_label,model_path,n_chan = data['data'], data['label'],data['modelPath'],data['n_chan'] exp = ExP(n_chan) - print('训练参数： ',np.shape(all_data),np.shape(all_label),model_path) + algo_log('训练参数： ',np.shape(all_data),np.shape(all_label),model_path, level="debug") bestAcc, averAcc, Y_true, Y_pred = exp.train(all_data,all_label,model_path) - print('THE BEST ACCURACY IS ' + str(bestAcc)) + algo_log('THE BEST ACCURACY IS ' + str(bestAcc), level="debug") endtime = datetime.datetime.now() - print('train duration: ',str(endtime - starttime)) + algo_log('train duration: ',str(endtime - starttime), level="debug") # 将模型或参数传回 result_queue.put({ @@ -387,7 +387,7 @@ def offlineTrain(all_data,all_label,modelPath): # seed_n = np.random.randint(2025) seed_n = 1877 - print('seed is ' + str(seed_n)) + algo_log('seed is ' + str(seed_n), level="debug") random.seed(seed_n) np.random.seed(seed_n) torch.manual_seed(seed_n) @@ -397,13 +397,12 @@ def offlineTrain(all_data,all_label,modelPath): exp = ExP() bestAcc, averAcc, Y_true, Y_pred = exp.train(all_data,all_label,modelPath) - print('THE BEST ACCURACY IS ' + str(bestAcc)) + algo_log('THE BEST ACCURACY IS ' + str(bestAcc), level="debug") endtime = datetime.datetime.now() - print('train duration: ',str(endtime - starttime)) + algo_log('train duration: ',str(endtime - starttime), level="debug") if __name__ == "__main__": - print(time.asctime(time.localtime(time.time()))) - print(time.asctime(time.localtime(time.time()))) + algo_log(f"[DEBUG] time.asctime(time.localtime(time.time())) = {time.asctime(time.localtime(time.time()))}", level="debug") diff --git a/MI/Algorithm/conformer_2class_cpu.py b/MI/Algorithm/conformer_2class_cpu.py index 1ffe523..3f92afc 100644 --- a/MI/Algorithm/conformer_2class_cpu.py +++ b/MI/Algorithm/conformer_2class_cpu.py @@ -22,6 +22,7 @@ from einops import rearrange from einops.layers.torch import Rearrange, Reduce from torch.backends import cudnn from sklearn.model_selection import train_test_split +from logs.log import algo_log # writer = SummaryWriter('./TensorBoardX/') @@ -190,7 +191,7 @@ class ExP(): # 自动选择设备：有 GPU 用 GPU，否则用 CPU self.device = torch.device("cuda" if torch.cuda.is_available() else "cpu") # self.device = torch.device("cpu") - print(f"Using device: {self.device}") + algo_log(f"Using device: {self.device}", level="debug") # 定义张量类型（不再强制使用 cuda） self.Tensor = torch.FloatTensor diff --git a/SSVEP/dwfbcca.py b/SSVEP/dwfbcca.py index 3fe0739..b8474ad 100644 --- a/SSVEP/dwfbcca.py +++ b/SSVEP/dwfbcca.py @@ -12,16 +12,17 @@ from scipy.io import loadmat from scipy.linalg import qr from scipy.signal import filtfilt, lfilter # from numpy.linalg import _umath_linalg +from logs.log import algo_log class FbccaDw: def __init__(self, fs, num_target, num_chans, num_filter, num_harms, stimTime, parameter, width, winNum,method): - print('******************************************') - print('parameter list') - print('target:', num_target) - print('number of filter bank:', num_filter) - print('parameter:', parameter) - print('width:', width) + algo_log('******************************************', level="debug") + algo_log('parameter list', level="debug") + algo_log('target:', num_target, level="debug") + algo_log('number of filter bank:', num_filter, level="debug") + algo_log('parameter:', parameter, level="debug") + algo_log('width:', width, level="debug") self.phase = 0 self.bandWidth = width self.winNum = winNum @@ -237,7 +238,7 @@ class FbccaDw: dataFiltered, self.notchZh[0] = lfilter(self.north_b, self.north_a, data, zi=self.notchZh[0]) return np.asmatrix(dataFiltered) except Exception: - print(Exception) + algo_log(f"Exception: {Exception}", level="debug") ''' getDataQ diff --git a/Zmq/zmqServer.py b/Zmq/zmqServer.py index 5dea432..a21bd33 100644 --- a/Zmq/zmqServer.py +++ b/Zmq/zmqServer.py @@ -2,6 +2,7 @@ import ast import numpy as np import threading +import zmq import json import queue from typing import Dict @@ -13,17 +14,14 @@ from Zmq.filterProcess import FilterRingBuffer from PubLibrary.InifileHelper import IniRead from logs.log import algo_log -import zmq +zmqServer_host = str(IniRead('system', 'zmqServer_host', '127.0.0.1')) class zmqServer(threading.Thread): def __init__(self, host='0.0.0.0', cmd_port=8099, data_port=8100, device_info=None): threading.Thread.__init__(self) self.device_info = device_info - self.host = host - - # test_host = "192.168.254.102" - # self.host = test_host + self.host = zmqServer_host self.cmd_port = cmd_port # 命令交互端口：收JSON命令 + 返JSON结果 self.data_port = data_port # 数据交互端口：收二进制原始脑电 + 返二进制滤波结果 diff --git a/config.ini b/config.ini index d025251..eaabfb0 100644 --- a/config.ini +++ b/config.ini @@ -21,6 +21,7 @@ Serial_port = COM44 algo_log_level = DEBUG console_output = 1 save_train_data = 0 +zmqServer_host = 127.0.0.1 ; 64 导设备配置 [device_type_1] diff --git a/nuitka_3in1_package.sh b/nuitka_3in1_package.sh index 35d9577..f051d13 100644 --- a/nuitka_3in1_package.sh +++ b/nuitka_3in1_package.sh @@ -28,7 +28,7 @@ echo "输出目录：${OUT_DIR}" python -m nuitka \ --standalone \ --msvc=latest \ ---windows-console-mode=force \ +--windows-console-mode=disable \ --module-parameter=torch-disable-jit=yes \ --enable-plugin=no-qt \ --include-package=numpy \