365 lines
14 KiB
Python
365 lines
14 KiB
Python
import time
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from psychopy import visual, core, logging # import some libraries from PsychoPy
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import random
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from datetime import datetime
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# LAB STREAMING LAYER1
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from pylsl import StreamInfo, StreamOutlet
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from psychopy import event
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import numpy as np
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from DecoderDW.Server import TCPServer
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from DecoderDW.Client import TCPClient
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# import subprocess
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# ----------------------
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# constants
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# size of the window
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WINWIDTH = 1920
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WINHEIGHT = 1080
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REFRESH_RATE = 144
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def get_keypress():
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keys = event.getKeys()
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if keys:
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return keys[0]
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else:
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return None
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def shutdown(win,client):
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client.send_data('saveData', 0)
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client.send_data('predict',2)
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win.close()
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core.quit()
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# end of configuration
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# ----------------------
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def generate_square_wave(frequency, sampling_rate=REFRESH_RATE, duration=5):
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"""
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生成方波序列
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参数：
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frequency (float): 频率（Hz）
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sampling_rate (int): 采样率（Hz），应与屏幕刷新率一致
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duration (float): 时长（秒）
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返回：
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square_wave (list): 方波序列
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"""
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# 计算总点数
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n_points = int(duration * sampling_rate)
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# 生成时间序列
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time = np.linspace(0, duration, n_points, endpoint=False)
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# 生成正弦波数据
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sin_wave = np.sin(2 * np.pi * frequency * time)
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# 生成方波数据
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square_wave = np.where(sin_wave >= 0, 1, 0)
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return square_wave.tolist()
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# 启动一个进程，不等待其完成
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import os
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if __name__ == "__main__":
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# ----------------------------------------------------------------------------------
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# main window settings
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main_win = visual.Window(size=(WINWIDTH, WINHEIGHT), units='height', screen=0, fullscr=False,
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gammaErrorPolicy='warn', color=(0.7, 0.7, 0.7))
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print('starting 1')
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# Set up LabStreamingLayer stream.
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info = StreamInfo(name='psychopy_stimuli', type='Markers', channel_count=1, channel_format='string',
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source_id='psychopy_stimuli_001')
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outlet = StreamOutlet(info) # Broadcast the stream.
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imageStim1 = visual.ImageStim(main_win, size=(300, 300), pos=(-600, 300), units='pix', image='UI/figures/xy.jpg')
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txtStim1 = visual.TextStim(win=main_win, text='△', font='SimHei', height=80, color='black', units='pix', bold=True,
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italic=False, pos=(-600, 30))
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imageStim2 = visual.ImageStim(main_win, size=(300, 300), pos=(0, 300), units='pix', image='UI/figures/xy.jpg')
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txtStim2 = visual.TextStim(win=main_win, text='△', font='SimHei', height=80, color='black', units='pix', bold=True,
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italic=False, pos=(0, 30))
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imageStim3 = visual.ImageStim(main_win, size=(300, 300), pos=(600, 300), units='pix', image='UI/figures/xy.jpg')
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txtStim3 = visual.TextStim(win=main_win, text='△', font='SimHei', height=80, color='black', units='pix', bold=True,
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italic=False, pos=(600, 30))
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imageStim4 = visual.ImageStim(main_win, size=(300, 300), pos=(-600, -200), units='pix', image='UI/figures/xy.jpg')
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txtStim4 = visual.TextStim(win=main_win, text='△', font='SimHei', height=80, color='black', units='pix', bold=True,
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italic=False, pos=(-600, -470))
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imageStim5 = visual.ImageStim(main_win, size=(300, 300), pos=(0, -200), units='pix', image='UI/figures/xy.jpg')
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txtStim5 = visual.TextStim(win=main_win, text='△', font='SimHei', height=80, color='black', units='pix', bold=True,
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italic=False, pos=(0, -470))
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imageStim6 = visual.ImageStim(main_win, size=(300, 300), pos=(600, -200), units='pix', image='UI/figures/xy.jpg')
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txtStim6 = visual.TextStim(win=main_win, text='△', font='SimHei', height=80, color='black', units='pix', bold=True,
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italic=False, pos=(600, -470))
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imageStim1red = visual.ImageStim(main_win, size=(300, 300), pos=(-600, 300), units='pix', image='UI/figures/xy_red.jpg')
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imageStim2red = visual.ImageStim(main_win, size=(300, 300), pos=(0, 300), units='pix', image='UI/figures/xy_red.jpg')
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imageStim3red = visual.ImageStim(main_win, size=(300, 300), pos=(600, 300), units='pix', image='UI/figures/xy_red.jpg')
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imageStim4red = visual.ImageStim(main_win, size=(300, 300), pos=(-600, -200), units='pix', image='UI/figures/xy_red.jpg')
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imageStim5red = visual.ImageStim(main_win, size=(300, 300), pos=(0, -200), units='pix', image='UI/figures/xy_red.jpg')
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imageStim6red = visual.ImageStim(main_win, size=(300, 300), pos=(600, -200), units='pix', image='UI/figures/xy_red.jpg')
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frequencies = [25,26,27,28,29,30] #[9,10,11,12,13,14] #[30,31,32,33,34,35] [25,26,27,28,29,30]
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# 生成方波数据
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square_wave_9 = generate_square_wave(frequencies[0], REFRESH_RATE, 5)
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square_wave_11 = generate_square_wave(frequencies[1], REFRESH_RATE, 5)
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square_wave_12 = generate_square_wave(frequencies[2], REFRESH_RATE, 5)
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square_wave_13 = generate_square_wave(frequencies[3], REFRESH_RATE, 5)
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square_wave_14 = generate_square_wave(frequencies[4], REFRESH_RATE, 5)
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square_wave_15 = generate_square_wave(frequencies[5], REFRESH_RATE, 5)
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# 创建刺激对象列表，便于管理
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image_stims = [imageStim1, imageStim2, imageStim3, imageStim4, imageStim5, imageStim6]
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txt_stims = [txtStim1, txtStim2, txtStim3, txtStim4, txtStim5, txtStim6]
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square_waves = [square_wave_9, square_wave_11, square_wave_12, square_wave_13, square_wave_14, square_wave_15]
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time.sleep(2)
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# grating.color = 'black'
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server = TCPServer()
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server.start()
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client = TCPClient('127.0.0.1', 8099)
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client.connect()
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print('Connected decoder_main')
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# client.send_data('impedance', 1)
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# time.sleep(20)
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# client.send_data('impedance', 2)
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client.send_data('targetFreqs', frequencies) # 使用frequencies变量，确保与刺激频率一致
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time.sleep(1)
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# 开启全程数据保存到 EEGFiles
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client.send_data('saveData',1)
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# client.send_data('impedance',1)
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# 实验参数
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repeats = 3
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seq_freq = frequencies * repeats
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seq_freq = np.random.permutation(seq_freq).tolist()
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num_trials = len(seq_freq) # 总试验次数, 6*6=36
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trial_count = 0
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# 在线解码精度计算
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online_results = [] # 存储每个trial的解码结果
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correct_predictions = 0 # 正确预测计数
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# 保存序列信息
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seq_info = {
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'total_trials': num_trials,
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'frequencies': frequencies,
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'sequence': seq_freq,
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'start_time': datetime.now().strftime('%Y-%m-%d %H:%M:%S')
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}
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# 保存序列信息到文件
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import json
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seq_file_path = f'EEGFiles/sequence_{datetime.now().strftime("%Y-%m-%d-%H-%M-%S")}.json'
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with open(seq_file_path, 'a', encoding='utf-8') as f:
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json.dump(seq_info, f, ensure_ascii=False, indent=2)
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#========================Trials Started======================#
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while trial_count < num_trials:
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# 从序列中获取当前试验的目标频率
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target_freq = seq_freq[trial_count]
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target_freq_index = frequencies.index(target_freq)
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print(f'Trials {trial_count + 1}/{num_trials} - Target Frequency: {target_freq}Hz (Label: {target_freq_index + 1})')
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# Stage 1: Cue Stage
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# print('Cue Stage: The target frequency is in Red')
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client.send_data('setLabelAndTrialInfo', {
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'label': 0,
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'trial_info': {
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'trial': trial_count + 1,
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'phase': 'cue',
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'target_freq': target_freq
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}
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})
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for frameN in range(int(1 * REFRESH_RATE)): # 1秒提示
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key_press = get_keypress()
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if key_press in ['q']:
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shutdown(main_win, client)
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# 显示所有刺激，目标刺激为红色
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for i, stim in enumerate(image_stims):
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if i == target_freq_index:
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# 目标刺激显示红色
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if i == 0:
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imageStim1red.draw()
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elif i == 1:
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imageStim2red.draw()
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elif i == 2:
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imageStim3red.draw()
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elif i == 3:
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imageStim4red.draw()
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elif i == 4:
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imageStim5red.draw()
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elif i == 5:
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imageStim6red.draw()
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else:
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# 其他刺激显示正常颜色
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stim.draw()
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main_win.flip()
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# Stage 2: Flanker Stimulus
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# print('Flanker Stage: flank all frequencies')
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client.send_data('predict', 1)
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client.send_data('setLabelAndTrialInfo', {
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'label': target_freq_index + 1, # 设置目标频率标签 这里+1，是因为0代表不记录数据
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'trial_info': {
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'trial': trial_count + 1, # trial 从0开始
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'phase': 'stimulus',
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'target_freq': target_freq
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}
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})
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outlet.push_sample(['S 1'])
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for frameN in range(6 * REFRESH_RATE): # 6秒刺激
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key_press = get_keypress()
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if key_press in ['q']:
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shutdown(main_win, client)
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# 所有频率按照方波闪烁
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if square_wave_9[frameN % len(square_wave_9)] == 1:
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imageStim1.draw()
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if square_wave_11[frameN % len(square_wave_11)] == 1:
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imageStim2.draw()
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if square_wave_12[frameN % len(square_wave_12)] == 1:
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imageStim3.draw()
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if square_wave_13[frameN % len(square_wave_13)] == 1:
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imageStim4.draw()
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if square_wave_14[frameN % len(square_wave_14)] == 1:
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imageStim5.draw()
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if square_wave_15[frameN % len(square_wave_15)] == 1:
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imageStim6.draw()
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main_win.flip()
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if server.ChoosenNum != -1:
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break
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# 记录在线解码结果
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predicted_freq_index = server.ChoosenNum # 解码结果
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predicted_freq = frequencies[predicted_freq_index] if predicted_freq_index != -1 else -1
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# 判断解码是否正确
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is_correct = (predicted_freq_index == target_freq_index) if predicted_freq_index != -1 else False
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if is_correct:
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correct_predictions += 1
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# 记录trial结果
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trial_result = {
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'trial': trial_count + 1,
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'target_freq': target_freq,
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'target_freq_index': target_freq_index,
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'predicted_freq': predicted_freq,
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'predicted_freq_index': predicted_freq_index,
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'is_correct': is_correct,
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'status': 'Success' if predicted_freq_index != -1 else 'Failed'
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}
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online_results.append(trial_result)
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# 打印当前trial结果
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status_symbol = "✓" if is_correct else "✗"
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if predicted_freq_index == -1:
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print(f'Trial {trial_count + 1}: 目标{target_freq}Hz -> 解码失败 - {status_symbol}')
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else:
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print(f'Trial {trial_count + 1}: 目标{target_freq}Hz -> 预测{predicted_freq}Hz - {status_symbol}')
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# Stage 3: Decoding Feedback
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outlet.push_sample(['S 2'])
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client.send_data('setLabelAndTrialInfo', {
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'label': 0, # 反馈阶段标签为0
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'trial_info': {
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'trial': trial_count + 1,
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'phase': 'feedback',
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'target_freq': target_freq
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}
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})
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# print('反馈阶段: 显示解码结果')
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for frameN in range(1 * REFRESH_RATE): # 1秒反馈
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key_press = get_keypress()
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if key_press in ['q']:
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shutdown(main_win, client)
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# 显示所有刺激但不闪烁
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for stim in image_stims:
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stim.draw()
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# 显示解码结果
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if server.ChoosenNum == 0:
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txtStim1.draw()
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elif server.ChoosenNum == 1:
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txtStim2.draw()
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elif server.ChoosenNum == 2:
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txtStim3.draw()
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elif server.ChoosenNum == 3:
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txtStim4.draw()
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elif server.ChoosenNum == 4:
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txtStim5.draw()
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elif server.ChoosenNum == 5:
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txtStim6.draw()
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main_win.flip()
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server.ChoosenNum = -1
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trial_count += 1
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# 计算总体在线解码精度
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total_trials = len(online_results)
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successful_trials = len([r for r in online_results if r['status'] == 'Success'])
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failed_trials = len([r for r in online_results if r['status'] == 'Failed'])
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overall_accuracy = correct_predictions / total_trials if total_trials > 0 else 0
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# Print Accuracy
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print(f"Total Accuracy: {overall_accuracy:.3f} ({correct_predictions}/{total_trials})")
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# 按频率分析准确率
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print(f"\n=== 按频率分析准确率 ===")
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freq_accuracy = {}
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for result in online_results:
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freq = result['target_freq']
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if freq not in freq_accuracy:
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freq_accuracy[freq] = {'correct': 0, 'total': 0, 'failed': 0}
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freq_accuracy[freq]['total'] += 1
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if result['status'] == 'Failed':
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freq_accuracy[freq]['failed'] += 1
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elif result['is_correct']:
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freq_accuracy[freq]['correct'] += 1
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print(f"{'频率':<8} {'准确率':<8} {'正确/总数':<10} {'失败数':<8}")
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print("-" * 40)
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for freq in sorted(freq_accuracy.keys()):
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stats = freq_accuracy[freq]
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accuracy = stats['correct'] / stats['total'] if stats['total'] > 0 else 0
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print(f"{freq}Hz{'':<4} {accuracy:.3f}{'':<4} {stats['correct']}/{stats['total']}{'':<6} {stats['failed']}")
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# 保存在线解码结果到文件
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online_results_file = f'EEGFiles/online_results_{datetime.now().strftime("%Y-%m-%d-%H-%M-%S")}.json'
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online_summary = {
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'total_trials': total_trials,
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'successful_trials': successful_trials,
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'failed_trials': failed_trials,
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'correct_predictions': correct_predictions,
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'overall_accuracy': overall_accuracy,
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# 'freq_accuracy': freq_accuracy,
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'trial_results': online_results,
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# 'end_time': datetime.now().strftime('%Y-%m-%d %H:%M:%S')
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}
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with open(online_results_file, 'w', encoding='utf-8') as f:
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json.dump(online_summary, f, ensure_ascii=False, indent=2)
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client.send_data('predict',2) # 关闭系统
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main_win.close()
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