302 lines
12 KiB
Python
302 lines
12 KiB
Python
|
"""
|
|||
|
|
ssmvep_headless.py
|
|||
|
|
无界面版 SSMVEP 范式通讯流程模拟脚本。
|
|||
|
|
复现 ssmvep_main.py 的完整指令序列（train 0/1/2, rest, predict, saveData），
|
|||
|
|
但不依赖 psychopy 也不打开任何窗口/音频，用 time.sleep 替代帧循环等待。
|
|||
|
|
|
|||
|
|
启动顺序:
|
|||
|
|
1. runDecoder.py
|
|||
|
|
2. datamock.py
|
|||
|
|
3. ssmvep_headless.py
|
|||
|
|
"""
|
|||
|
|
|
|||
|
|
import sys
|
|||
|
|
import os
|
|||
|
|
import json
|
|||
|
|
import time
|
|||
|
|
import threading
|
|||
|
|
import zmq
|
|||
|
|
import numpy as np
|
|||
|
|
from datetime import datetime
|
|||
|
|
|
|||
|
|
sys.path.append(os.path.dirname(os.path.dirname(os.path.abspath(__file__))))
|
|||
|
|
from PubLibrary.InifileHelper import IniRead
|
|||
|
|
|
|||
|
|
personname = 'demo'
|
|||
|
|
session = '01'
|
|||
|
|
|
|||
|
|
DATAMOCK_LABEL_ADDR = 'tcp://127.0.0.1:8101' # datamock 标签命令地址
|
|||
|
|
|
|||
|
|
|
|||
|
|
# ========== ZMQ 结果接收服务 ==========
|
|||
|
|
class ZmqResultServer(threading.Thread):
|
|||
|
|
def __init__(self, port=8088):
|
|||
|
|
threading.Thread.__init__(self)
|
|||
|
|
self.port = port
|
|||
|
|
self.running = True
|
|||
|
|
self.energy = 0
|
|||
|
|
self.paradigm = 0 # 0=个体校准, 1=康复训练, 2=等待模型训练
|
|||
|
|
self.ChoosenNum = -1
|
|||
|
|
self.context = zmq.Context()
|
|||
|
|
self.socket = self.context.socket(zmq.ROUTER)
|
|||
|
|
self.socket.bind(f"tcp://0.0.0.0:{self.port}")
|
|||
|
|
self.daemon = True
|
|||
|
|
self.trial_idx = 0
|
|||
|
|
|
|||
|
|
def run(self):
|
|||
|
|
print(f"[Server] UpperHost_Server listening on {self.port}")
|
|||
|
|
while self.running:
|
|||
|
|
try:
|
|||
|
|
frames = self.socket.recv_multipart(zmq.NOBLOCK)
|
|||
|
|
if len(frames) < 3:
|
|||
|
|
continue
|
|||
|
|
message = json.loads(frames[2].decode('utf-8'))
|
|||
|
|
method = message.get('method')
|
|||
|
|
params = message.get('params')
|
|||
|
|
if method == 'energy':
|
|||
|
|
self.energy = params
|
|||
|
|
elif method == 'paradigm':
|
|||
|
|
self.paradigm = params
|
|||
|
|
print(f"[Server] paradigm -> {params}")
|
|||
|
|
elif method == 'result':
|
|||
|
|
self.ChoosenNum = params
|
|||
|
|
self.trial_idx += 1
|
|||
|
|
print(f"[Server] result={self.ChoosenNum} (trial {self.trial_idx})")
|
|||
|
|
except zmq.Again:
|
|||
|
|
time.sleep(0.005)
|
|||
|
|
except Exception as e:
|
|||
|
|
print(f"[Server] error: {e}")
|
|||
|
|
|
|||
|
|
def stop(self):
|
|||
|
|
self.running = False
|
|||
|
|
self.socket.close()
|
|||
|
|
self.context.term()
|
|||
|
|
|
|||
|
|
|
|||
|
|
# ========== ZMQ 命令发送客户端 ==========
|
|||
|
|
class ZmqCmdClient:
|
|||
|
|
def __init__(self, host, port):
|
|||
|
|
self.host = host
|
|||
|
|
self.port = port
|
|||
|
|
self.context = zmq.Context()
|
|||
|
|
self.socket = self.context.socket(zmq.DEALER)
|
|||
|
|
# PUSH socket 用于向 datamock.py 发送标签命令
|
|||
|
|
self._label_sock = self.context.socket(zmq.PUSH)
|
|||
|
|
self._label_sock.connect(DATAMOCK_LABEL_ADDR)
|
|||
|
|
print(f"[Client] label PUSH connected to {DATAMOCK_LABEL_ADDR}")
|
|||
|
|
|
|||
|
|
def connect(self):
|
|||
|
|
self.socket.connect(f"tcp://{self.host}:{self.port}")
|
|||
|
|
print(f"[Client] connected to {self.host}:{self.port}")
|
|||
|
|
|
|||
|
|
def start_recv_thread(self, result_server):
|
|||
|
|
"""启动后台线程，持续接收 decoder 通过 8099 ROUTER 回发的消息，并更新 result_server 的状态"""
|
|||
|
|
self._result_server = result_server
|
|||
|
|
self._stop_recv = threading.Event()
|
|||
|
|
|
|||
|
|
def _recv_loop():
|
|||
|
|
while not self._stop_recv.is_set():
|
|||
|
|
try:
|
|||
|
|
frames = self.socket.recv_multipart(zmq.NOBLOCK)
|
|||
|
|
# DEALER 收到的格式: [b'', json_bytes]
|
|||
|
|
data_bytes = frames[-1]
|
|||
|
|
message = json.loads(data_bytes.decode('utf-8'))
|
|||
|
|
method = message.get('method')
|
|||
|
|
params = message.get('params')
|
|||
|
|
ts = datetime.now().strftime('%H:%M:%S.%f')[:-3]
|
|||
|
|
print(f"[{ts}] [CmdClient] recv: {method}={params}")
|
|||
|
|
if method == 'paradigm':
|
|||
|
|
self._result_server.paradigm = params
|
|||
|
|
print(f"[{ts}] [CmdClient] paradigm updated -> {params}")
|
|||
|
|
elif method == 'result':
|
|||
|
|
self._result_server.ChoosenNum = params
|
|||
|
|
self._result_server.trial_idx += 1
|
|||
|
|
print(f"[{ts}] [CmdClient] result={params} (trial {self._result_server.trial_idx})")
|
|||
|
|
elif method == 'energy':
|
|||
|
|
self._result_server.energy = params
|
|||
|
|
except zmq.Again:
|
|||
|
|
time.sleep(0.005)
|
|||
|
|
except Exception as e:
|
|||
|
|
print(f"[CmdClient recv] error: {e}")
|
|||
|
|
time.sleep(0.01)
|
|||
|
|
|
|||
|
|
self._recv_thread = threading.Thread(target=_recv_loop, daemon=True)
|
|||
|
|
self._recv_thread.start()
|
|||
|
|
print(f"[Client] 后台接收线程已启动（监听 decoder 8099 回发消息）")
|
|||
|
|
|
|||
|
|
def stop_recv_thread(self):
|
|||
|
|
if hasattr(self, '_stop_recv'):
|
|||
|
|
self._stop_recv.set()
|
|||
|
|
|
|||
|
|
def _send_label(self, label_value):
|
|||
|
|
"""向 datamock.py 发送标签命令"""
|
|||
|
|
try:
|
|||
|
|
self._label_sock.send_string(str(label_value), zmq.NOBLOCK)
|
|||
|
|
except Exception as e:
|
|||
|
|
print(f"[Client] label send error: {e}")
|
|||
|
|
|
|||
|
|
def send_data(self, method, params):
|
|||
|
|
msg = {'method': method, 'params': params}
|
|||
|
|
try:
|
|||
|
|
self.socket.send_multipart([b'', json.dumps(msg).encode('utf-8')])
|
|||
|
|
ts = datetime.now().strftime('%H:%M:%S.%f')[:-3]
|
|||
|
|
print(f"[{ts}] send_data: {method}={params}")
|
|||
|
|
# 根据 train/predict 命令向 datamock 发送标签
|
|||
|
|
if method == 'train':
|
|||
|
|
if params == 0:
|
|||
|
|
self._send_label(1)
|
|||
|
|
print(f"[Label] train 0 -> datamock label=1")
|
|||
|
|
elif params == 1:
|
|||
|
|
self._send_label(2)
|
|||
|
|
print(f"[Label] train 1 -> datamock label=2")
|
|||
|
|
elif method == 'predict':
|
|||
|
|
self._send_label(99)
|
|||
|
|
print(f"[Label] predict -> datamock label=99")
|
|||
|
|
except Exception as e:
|
|||
|
|
print(f"[Client] send error: {e}")
|
|||
|
|
|
|||
|
|
|
|||
|
|
# ========== 主流程 ==========
|
|||
|
|
def run_headless():
|
|||
|
|
server = ZmqResultServer(port=8088)
|
|||
|
|
server.start()
|
|||
|
|
|
|||
|
|
_dh = str(IniRead('system', 'Decoder_Host'))
|
|||
|
|
_dp = int(IniRead('system', 'Decoder_Port'))
|
|||
|
|
client = ZmqCmdClient(_dh, _dp)
|
|||
|
|
client.connect()
|
|||
|
|
client.start_recv_thread(server) # 启动后台接收线程，监听 decoder 8099 回发的 paradigm/result 消息
|
|||
|
|
|
|||
|
|
time.sleep(1) # 等待连接建立
|
|||
|
|
client.send_data('decoderClass', 'ssmvep')
|
|||
|
|
|
|||
|
|
train_time = 2.5 # 每轮训练刺激时长 (s)
|
|||
|
|
test_time = 2.5 # 每轮测试刺激时长 (s)
|
|||
|
|
right_rehabilitation = float(IniRead('system', 'Right_rehabilitation'))
|
|||
|
|
fault_rehabilitation = float(IniRead('system', 'Fault_rehabilitation'))
|
|||
|
|
rest_time = float(IniRead('system', 'Rest_time'))
|
|||
|
|
|
|||
|
|
num_blocks = int(IniRead('system', 'Num_blocks'))
|
|||
|
|
num_trials = int(IniRead('system', 'Num_trials'))
|
|||
|
|
|
|||
|
|
position = [0, 1]
|
|||
|
|
truePos_seq = position * int(num_trials / len(position))
|
|||
|
|
truePos_seq = np.random.permutation(truePos_seq).tolist()
|
|||
|
|
user_choice = []
|
|||
|
|
|
|||
|
|
os.makedirs('EEGFiles', exist_ok=True)
|
|||
|
|
seq_file_path = f'EEGFiles/pos_seq_{personname}{session}_{datetime.now().strftime("%Y-%m-%d-%H-%M-%S")}.json'
|
|||
|
|
seq_info = {
|
|||
|
|
'position': position,
|
|||
|
|
'sequence': truePos_seq,
|
|||
|
|
'start_time': datetime.now().strftime('%Y-%m-%d %H:%M:%S')
|
|||
|
|
}
|
|||
|
|
with open(seq_file_path, 'w', encoding='utf-8') as f:
|
|||
|
|
json.dump(seq_info, f, ensure_ascii=False, indent=2)
|
|||
|
|
|
|||
|
|
trained = 0
|
|||
|
|
Num_Total = 0
|
|||
|
|
Num_Success = 0
|
|||
|
|
|
|||
|
|
print("=" * 50)
|
|||
|
|
print("[Headless] 开始运行 SSMVEP 通讯流程（无界面）")
|
|||
|
|
print(f" num_blocks={num_blocks}, num_trials={num_trials}")
|
|||
|
|
print(f" train_time={train_time}s, test_time={test_time}s")
|
|||
|
|
print("=" * 50)
|
|||
|
|
|
|||
|
|
try:
|
|||
|
|
while True:
|
|||
|
|
# -------- 个体校准阶段 --------
|
|||
|
|
print("\n[Phase] 个体校准阶段 (paradigm=0)")
|
|||
|
|
client.send_data('rest', 0)
|
|||
|
|
time.sleep(1)
|
|||
|
|
|
|||
|
|
# epoch完成需要的额外等待时间：train_latency=120包×20ms=2.4s
|
|||
|
|
# 在train_time后需再等epoch_wait秒，decoder才能完成epoch采集并取出数据
|
|||
|
|
epoch_wait = 2.4 # 秒，与train_latency对应
|
|||
|
|
|
|||
|
|
while server.paradigm == 0:
|
|||
|
|
# 左腿刺激
|
|||
|
|
print(f"\n[Train] 左腿刺激 (train 0) trained={trained}")
|
|||
|
|
client.send_data('train', 0)
|
|||
|
|
time.sleep(train_time + epoch_wait) # 等待刺激时间+epoch完成时间
|
|||
|
|
|
|||
|
|
trained += 1
|
|||
|
|
client.send_data('rest', 0)
|
|||
|
|
time.sleep(max(0, abs(fault_rehabilitation - train_time) - epoch_wait))
|
|||
|
|
|
|||
|
|
# 右腿刺激
|
|||
|
|
print(f"\n[Train] 右腿刺激 (train 1) trained={trained}")
|
|||
|
|
client.send_data('train', 1)
|
|||
|
|
time.sleep(train_time + epoch_wait) # 等待刺激时间+epoch完成时间
|
|||
|
|
|
|||
|
|
trained += 1
|
|||
|
|
client.send_data('rest', 0)
|
|||
|
|
time.sleep(max(0, fault_rehabilitation - epoch_wait))
|
|||
|
|
|
|||
|
|
# 个体校准阶段结束
|
|||
|
|
print("\n[Phase] 个体校准结束，等待 paradigm=1 ...")
|
|||
|
|
trained = 0
|
|||
|
|
time.sleep(1)
|
|||
|
|
|
|||
|
|
# -------- 康复训练阶段 --------
|
|||
|
|
while server.paradigm == 1:
|
|||
|
|
print("\n[Phase] 康复训练阶段 (paradigm=1)")
|
|||
|
|
for block_idx in range(num_blocks):
|
|||
|
|
print(f"\n [Block {block_idx+1}/{num_blocks}]")
|
|||
|
|
time.sleep(10) # 每轮开始前等待
|
|||
|
|
|
|||
|
|
for trial_idx in range(num_trials):
|
|||
|
|
true_position = truePos_seq[trial_idx]
|
|||
|
|
print(f" [Trial {trial_idx+1}/{num_trials}] true_pos={true_position}")
|
|||
|
|
|
|||
|
|
time.sleep(0.5) # 提示 + 叮声
|
|||
|
|
server.ChoosenNum = -1
|
|||
|
|
|
|||
|
|
# 开始测试
|
|||
|
|
# predict epoch latency = 115包×20ms = 2.3s，需额外等待epoch完成
|
|||
|
|
predict_epoch_wait = 2.3 # 秒，与predict latency=115包对应
|
|||
|
|
client.send_data('predict', 1)
|
|||
|
|
t_start = time.perf_counter()
|
|||
|
|
while time.perf_counter() - t_start < test_time + predict_epoch_wait:
|
|||
|
|
if server.ChoosenNum >= 0:
|
|||
|
|
Num_Total += 1
|
|||
|
|
user_choice.append(server.ChoosenNum)
|
|||
|
|
if server.ChoosenNum in [0, 1]:
|
|||
|
|
Num_Success += 1
|
|||
|
|
rest_time = right_rehabilitation
|
|||
|
|
break
|
|||
|
|
time.sleep(0.02)
|
|||
|
|
|
|||
|
|
trained += 1
|
|||
|
|
client.send_data('rest', 0)
|
|||
|
|
time.sleep(0.5)
|
|||
|
|
time.sleep(rest_time)
|
|||
|
|
server.ChoosenNum = -1
|
|||
|
|
|
|||
|
|
# 训练结束
|
|||
|
|
print("\n[Phase] 康复训练结束")
|
|||
|
|
break # 退出康复训练循环
|
|||
|
|
|
|||
|
|
# 统计结果
|
|||
|
|
overall_accuracy = Num_Success / Num_Total if Num_Total > 0 else 0
|
|||
|
|
expected_seq = truePos_seq * num_blocks
|
|||
|
|
min_len = min(len(user_choice), len(expected_seq))
|
|||
|
|
same_count = sum(1 for a, b in zip(user_choice[:min_len], expected_seq[:min_len]) if a == b)
|
|||
|
|
true_accuracy = same_count / min_len if min_len > 0 else 0
|
|||
|
|
print(f"\n[Result] Overall={overall_accuracy:.3f} ({Num_Success}/{Num_Total})")
|
|||
|
|
print(f"[Result] TrueAcc={true_accuracy:.3f} ({same_count}/{min_len})")
|
|||
|
|
break # 完成一个完整流程后退出
|
|||
|
|
|
|||
|
|
except KeyboardInterrupt:
|
|||
|
|
print("\n[Headless] 用户中断")
|
|||
|
|
finally:
|
|||
|
|
client.send_data('predict', 2) # 关闭系统
|
|||
|
|
client.send_data('saveData', 0)
|
|||
|
|
server.stop()
|
|||
|
|
print("[Headless] 已发送关闭指令，退出。")
|
|||
|
|
|
|||
|
|
|
|||
|
|
if __name__ == '__main__':
|
|||
|
|
run_headless()
|