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upper mock

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Ivey Song
2026-06-10 09:19:31 +08:00
parent 73e01782df
commit 81a8d78ab2
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upperHost_stimmock/ssvep_main.py Normal file
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import time
from psychopy import visual, core, logging # import some libraries from PsychoPy
import random
from datetime import datetime
# LAB STREAMING LAYER1
from pylsl import StreamInfo, StreamOutlet
from psychopy import event
import numpy as np
from DecoderDW.Server import TCPServer
from DecoderDW.Client import TCPClient
# import subprocess
# ----------------------
# constants
# size of the window
WINWIDTH = 1920
WINHEIGHT = 1080
REFRESH_RATE = 144
def get_keypress():
keys = event.getKeys()
if keys:
return keys[0]
else:
return None
def shutdown(win,client):
client.send_data('saveData', 0)
client.send_data('predict',2)
win.close()
core.quit()
# end of configuration
# ----------------------
def generate_square_wave(frequency, sampling_rate=REFRESH_RATE, duration=5):
"""
生成方波序列
参数：
frequency (float): 频率（Hz）
sampling_rate (int): 采样率（Hz），应与屏幕刷新率一致
duration (float): 时长（秒）
返回：
square_wave (list): 方波序列
"""
# 计算总点数
n_points = int(duration * sampling_rate)
# 生成时间序列
time = np.linspace(0, duration, n_points, endpoint=False)
# 生成正弦波数据
sin_wave = np.sin(2 * np.pi * frequency * time)
# 生成方波数据
square_wave = np.where(sin_wave >= 0, 1, 0)
return square_wave.tolist()
# 启动一个进程，不等待其完成
import os
if __name__ == "__main__":
# ----------------------------------------------------------------------------------
# main window settings
main_win = visual.Window(size=(WINWIDTH, WINHEIGHT), units='height', screen=0, fullscr=False,
gammaErrorPolicy='warn', color=(0.7, 0.7, 0.7))
print('starting 1')
# Set up LabStreamingLayer stream.
info = StreamInfo(name='psychopy_stimuli', type='Markers', channel_count=1, channel_format='string',
source_id='psychopy_stimuli_001')
outlet = StreamOutlet(info) # Broadcast the stream.
imageStim1 = visual.ImageStim(main_win, size=(300, 300), pos=(-600, 300), units='pix', image='UI/figures/xy.jpg')
txtStim1 = visual.TextStim(win=main_win, text='△', font='SimHei', height=80, color='black', units='pix', bold=True,
italic=False, pos=(-600, 30))
imageStim2 = visual.ImageStim(main_win, size=(300, 300), pos=(0, 300), units='pix', image='UI/figures/xy.jpg')
txtStim2 = visual.TextStim(win=main_win, text='△', font='SimHei', height=80, color='black', units='pix', bold=True,
italic=False, pos=(0, 30))
imageStim3 = visual.ImageStim(main_win, size=(300, 300), pos=(600, 300), units='pix', image='UI/figures/xy.jpg')
txtStim3 = visual.TextStim(win=main_win, text='△', font='SimHei', height=80, color='black', units='pix', bold=True,
italic=False, pos=(600, 30))
imageStim4 = visual.ImageStim(main_win, size=(300, 300), pos=(-600, -200), units='pix', image='UI/figures/xy.jpg')
txtStim4 = visual.TextStim(win=main_win, text='△', font='SimHei', height=80, color='black', units='pix', bold=True,
italic=False, pos=(-600, -470))
imageStim5 = visual.ImageStim(main_win, size=(300, 300), pos=(0, -200), units='pix', image='UI/figures/xy.jpg')
txtStim5 = visual.TextStim(win=main_win, text='△', font='SimHei', height=80, color='black', units='pix', bold=True,
italic=False, pos=(0, -470))
imageStim6 = visual.ImageStim(main_win, size=(300, 300), pos=(600, -200), units='pix', image='UI/figures/xy.jpg')
txtStim6 = visual.TextStim(win=main_win, text='△', font='SimHei', height=80, color='black', units='pix', bold=True,
italic=False, pos=(600, -470))
imageStim1red = visual.ImageStim(main_win, size=(300, 300), pos=(-600, 300), units='pix', image='UI/figures/xy_red.jpg')
imageStim2red = visual.ImageStim(main_win, size=(300, 300), pos=(0, 300), units='pix', image='UI/figures/xy_red.jpg')
imageStim3red = visual.ImageStim(main_win, size=(300, 300), pos=(600, 300), units='pix', image='UI/figures/xy_red.jpg')
imageStim4red = visual.ImageStim(main_win, size=(300, 300), pos=(-600, -200), units='pix', image='UI/figures/xy_red.jpg')
imageStim5red = visual.ImageStim(main_win, size=(300, 300), pos=(0, -200), units='pix', image='UI/figures/xy_red.jpg')
imageStim6red = visual.ImageStim(main_win, size=(300, 300), pos=(600, -200), units='pix', image='UI/figures/xy_red.jpg')
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]
# 生成方波数据
square_wave_9 = generate_square_wave(frequencies[0], REFRESH_RATE, 5)
square_wave_11 = generate_square_wave(frequencies[1], REFRESH_RATE, 5)
square_wave_12 = generate_square_wave(frequencies[2], REFRESH_RATE, 5)
square_wave_13 = generate_square_wave(frequencies[3], REFRESH_RATE, 5)
square_wave_14 = generate_square_wave(frequencies[4], REFRESH_RATE, 5)
square_wave_15 = generate_square_wave(frequencies[5], REFRESH_RATE, 5)
# 创建刺激对象列表，便于管理
image_stims = [imageStim1, imageStim2, imageStim3, imageStim4, imageStim5, imageStim6]
txt_stims = [txtStim1, txtStim2, txtStim3, txtStim4, txtStim5, txtStim6]
square_waves = [square_wave_9, square_wave_11, square_wave_12, square_wave_13, square_wave_14, square_wave_15]
time.sleep(2)
# grating.color = 'black'
server = TCPServer()
server.start()
client = TCPClient('127.0.0.1', 8099)
client.connect()
print('Connected decoder_main')
# client.send_data('impedance', 1)
# time.sleep(20)
# client.send_data('impedance', 2)
client.send_data('targetFreqs', frequencies) # 使用frequencies变量，确保与刺激频率一致
time.sleep(1)
# 开启全程数据保存到 EEGFiles
client.send_data('saveData',1)
# client.send_data('impedance',1)
# 实验参数
repeats = 3
seq_freq = frequencies * repeats
seq_freq = np.random.permutation(seq_freq).tolist()
num_trials = len(seq_freq) # 总试验次数, 6*6=36
trial_count = 0
# 在线解码精度计算
online_results = [] # 存储每个trial的解码结果
correct_predictions = 0 # 正确预测计数
# 保存序列信息
seq_info = {
'total_trials': num_trials,
'frequencies': frequencies,
'sequence': seq_freq,
'start_time': datetime.now().strftime('%Y-%m-%d %H:%M:%S')
}
# 保存序列信息到文件
import json
seq_file_path = f'EEGFiles/sequence_{datetime.now().strftime("%Y-%m-%d-%H-%M-%S")}.json'
with open(seq_file_path, 'a', encoding='utf-8') as f:
json.dump(seq_info, f, ensure_ascii=False, indent=2)
#========================Trials Started======================#
while trial_count < num_trials:
# 从序列中获取当前试验的目标频率
target_freq = seq_freq[trial_count]
target_freq_index = frequencies.index(target_freq)
print(f'Trials {trial_count + 1}/{num_trials} - Target Frequency: {target_freq}Hz (Label: {target_freq_index + 1})')
# Stage 1: Cue Stage
# print('Cue Stage: The target frequency is in Red')
client.send_data('setLabelAndTrialInfo', {
'label': 0,
'trial_info': {
'trial': trial_count + 1,
'phase': 'cue',
'target_freq': target_freq
}
})
for frameN in range(int(1 * REFRESH_RATE)): # 1秒提示
key_press = get_keypress()
if key_press in ['q']:
shutdown(main_win, client)
# 显示所有刺激，目标刺激为红色
for i, stim in enumerate(image_stims):
if i == target_freq_index:
# 目标刺激显示红色
if i == 0:
imageStim1red.draw()
elif i == 1:
imageStim2red.draw()
elif i == 2:
imageStim3red.draw()
elif i == 3:
imageStim4red.draw()
elif i == 4:
imageStim5red.draw()
elif i == 5:
imageStim6red.draw()
else:
# 其他刺激显示正常颜色
stim.draw()
main_win.flip()
# Stage 2: Flanker Stimulus
# print('Flanker Stage: flank all frequencies')
client.send_data('predict', 1)
client.send_data('setLabelAndTrialInfo', {
'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
'trial_info': {
'trial': trial_count + 1, # trial 从0开始
'phase': 'stimulus',
'target_freq': target_freq
}
})
outlet.push_sample(['S 1'])
for frameN in range(6 * REFRESH_RATE): # 6秒刺激
key_press = get_keypress()
if key_press in ['q']:
shutdown(main_win, client)
# 所有频率按照方波闪烁
if square_wave_9[frameN % len(square_wave_9)] == 1:
imageStim1.draw()
if square_wave_11[frameN % len(square_wave_11)] == 1:
imageStim2.draw()
if square_wave_12[frameN % len(square_wave_12)] == 1:
imageStim3.draw()
if square_wave_13[frameN % len(square_wave_13)] == 1:
imageStim4.draw()
if square_wave_14[frameN % len(square_wave_14)] == 1:
imageStim5.draw()
if square_wave_15[frameN % len(square_wave_15)] == 1:
imageStim6.draw()
main_win.flip()
if server.ChoosenNum != -1:
break
# 记录在线解码结果
predicted_freq_index = server.ChoosenNum # 解码结果
predicted_freq = frequencies[predicted_freq_index] if predicted_freq_index != -1 else -1
# 判断解码是否正确
is_correct = (predicted_freq_index == target_freq_index) if predicted_freq_index != -1 else False
if is_correct:
correct_predictions += 1
# 记录trial结果
trial_result = {
'trial': trial_count + 1,
'target_freq': target_freq,
'target_freq_index': target_freq_index,
'predicted_freq': predicted_freq,
'predicted_freq_index': predicted_freq_index,
'is_correct': is_correct,
'status': 'Success' if predicted_freq_index != -1 else 'Failed'
}
online_results.append(trial_result)
# 打印当前trial结果
status_symbol = "✓" if is_correct else "✗"
if predicted_freq_index == -1:
print(f'Trial {trial_count + 1}: 目标{target_freq}Hz -> 解码失败 - {status_symbol}')
else:
print(f'Trial {trial_count + 1}: 目标{target_freq}Hz -> 预测{predicted_freq}Hz - {status_symbol}')
# Stage 3: Decoding Feedback
outlet.push_sample(['S 2'])
client.send_data('setLabelAndTrialInfo', {
'label': 0, # 反馈阶段标签为0
'trial_info': {
'trial': trial_count + 1,
'phase': 'feedback',
'target_freq': target_freq
}
})
# print('反馈阶段: 显示解码结果')
for frameN in range(1 * REFRESH_RATE): # 1秒反馈
key_press = get_keypress()
if key_press in ['q']:
shutdown(main_win, client)
# 显示所有刺激但不闪烁
for stim in image_stims:
stim.draw()
# 显示解码结果
if server.ChoosenNum == 0:
txtStim1.draw()
elif server.ChoosenNum == 1:
txtStim2.draw()
elif server.ChoosenNum == 2:
txtStim3.draw()
elif server.ChoosenNum == 3:
txtStim4.draw()
elif server.ChoosenNum == 4:
txtStim5.draw()
elif server.ChoosenNum == 5:
txtStim6.draw()
main_win.flip()
server.ChoosenNum = -1
trial_count += 1
# 计算总体在线解码精度
total_trials = len(online_results)
successful_trials = len([r for r in online_results if r['status'] == 'Success'])
failed_trials = len([r for r in online_results if r['status'] == 'Failed'])
overall_accuracy = correct_predictions / total_trials if total_trials > 0 else 0
# Print Accuracy
print(f"Total Accuracy: {overall_accuracy:.3f} ({correct_predictions}/{total_trials})")
# 按频率分析准确率
print(f"\n=== 按频率分析准确率 ===")
freq_accuracy = {}
for result in online_results:
freq = result['target_freq']
if freq not in freq_accuracy:
freq_accuracy[freq] = {'correct': 0, 'total': 0, 'failed': 0}
freq_accuracy[freq]['total'] += 1
if result['status'] == 'Failed':
freq_accuracy[freq]['failed'] += 1
elif result['is_correct']:
freq_accuracy[freq]['correct'] += 1
print(f"{'频率':<8} {'准确率':<8} {'正确/总数':<10} {'失败数':<8}")
print("-" * 40)
for freq in sorted(freq_accuracy.keys()):
stats = freq_accuracy[freq]
accuracy = stats['correct'] / stats['total'] if stats['total'] > 0 else 0
print(f"{freq}Hz{'':<4} {accuracy:.3f}{'':<4} {stats['correct']}/{stats['total']}{'':<6} {stats['failed']}")
# 保存在线解码结果到文件
online_results_file = f'EEGFiles/online_results_{datetime.now().strftime("%Y-%m-%d-%H-%M-%S")}.json'
online_summary = {
'total_trials': total_trials,
'successful_trials': successful_trials,
'failed_trials': failed_trials,
'correct_predictions': correct_predictions,
'overall_accuracy': overall_accuracy,
# 'freq_accuracy': freq_accuracy,
'trial_results': online_results,
# 'end_time': datetime.now().strftime('%Y-%m-%d %H:%M:%S')
}
with open(online_results_file, 'w', encoding='utf-8') as f:
json.dump(online_summary, f, ensure_ascii=False, indent=2)
client.send_data('predict',2) # 关闭系统
main_win.close()