add filter process
This commit is contained in:
365
Zmq/zmqServer.py
365
Zmq/zmqServer.py
@@ -1,3 +1,4 @@
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# -*-coding:utf-8 -*-
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import ast
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import numpy as np
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import threading
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@@ -7,7 +8,6 @@ from typing import Dict
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import datetime
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import time
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# from Device.SunnyLinker import SunnyLinker64
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from Zmq.dataBuffer import ParadigmRingBuffer
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from Zmq.filterProcess import FilterRingBuffer
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from PubLibrary.InifileHelper import IniRead
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@@ -21,63 +21,68 @@ class zmqServer(threading.Thread):
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self.device_info = device_info
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self.host = host
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self.cmd_port = cmd_port # 命令交互端口
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self.data_port = data_port # 数据接收端口
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self.cmd_port = cmd_port # 命令交互端口：收JSON命令 + 返JSON结果
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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
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self.running = False
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# 原有业务状态变量
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# self.get_Impedance = False # 是否返回阻抗值
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self.open_Impedance = False # 是否开启阻抗检测功能
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self.StartDecode = False # false 停止解码，true=开始解码
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self.StartTrain = False # False未进入训练状态，True处于训练状态
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self.state_mode = None # 'train'为训练状态，’rest'为休息状态,'test'为测试状态
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self.currentLabel = -1 # 接收刺激端消息，了解刺激端当前的训练标签
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self.IsExitApp = False # 当socket收到2的时候，就置为True，代表要退出系统了。
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# self.getReport = False # 获取训练报告内容
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self.open_Impedance = False #当前系统处于阻抗检测状态
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self.StartDecode = False
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self.StartTrain = False
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self.state_mode = None
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self.currentLabel = -1
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self.IsExitApp = False
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self.daemon = True
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# 范式数据缓存
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self.paradigmBuffer = ParadigmRingBuffer(self.device_info['channel_nums'], self.device_info['sample_rate'] * 10)
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self.filterBuffer = FilterRingBuffer(self.device_info['channel_nums'], self.device_info['sample_rate'] * 10)
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self.paradigmBufferLock= threading.Lock()
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# 双环形缓冲区
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self.paradigmBuffer = ParadigmRingBuffer(
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self.device_info['channel_nums'],
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self.device_info['sample_rate'] * 10
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)
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self.filterBuffer = FilterRingBuffer(
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self.device_info['channel_nums'],
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self.device_info['sample_rate'] * 10
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)
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self.paradigmBufferLock = threading.Lock()
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self.filterBufferLock = threading.Lock()
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# 命令与数据通信
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# ZMQ上下文与套接字
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self.context = zmq.Context()
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# 指令通道 (8099) - ROUTER：短JSON命令，低频率
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# 8099命令端口：ROUTER
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self.cmd_socket = self.context.socket(zmq.ROUTER)
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# 通用套接字选项：仍在 SocketOption 中
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self.cmd_socket.setsockopt(zmq.SocketOption.RCVHWM, 100)
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self.cmd_socket.setsockopt(zmq.SocketOption.SNDHWM, 100)
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self.cmd_socket.bind(f"tcp://{self.host}:{cmd_port}")
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# 数据通道 (8100) - ROUTER：高频脑电二进制流
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# 8100数据端口：ROUTER
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self.data_socket = self.context.socket(zmq.ROUTER)
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self.data_socket.setsockopt(zmq.SocketOption.RCVHWM, 500)
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self.data_socket.setsockopt(zmq.SocketOption.SNDHWM, 100) # 添加发送高水位线
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self.data_socket.bind(f"tcp://{self.host}:{data_port}")
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# Poller 轮训器（保持不变）
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# Poller轮询器
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self.poller = zmq.Poller()
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self.poller.register(self.cmd_socket, zmq.POLLIN)
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self.poller.register(self.data_socket, zmq.POLLIN)
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# 业务变量
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self.targetFreqs = []
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self.changeTarget = False # 更换目标频率
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# self.sunnyLinker = SunnyLinker64(None, None, None, None,None) #单例模式类，已在Decoder实例化
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self.labels = [0x01, 0x02,0x03]
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self.decoder_switch = False #更换解码器
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self.decoder_class = None #解码器类别 'ssvep','ssmvep','mi'
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self.changeTarget = False
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self.labels = [0x01, 0x02, 0x03]
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self.decoder_switch = False
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self.decoder_class = None
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# 客户端管理 - 区分命令/数据客户端
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self.cmd_clients = set() # 命令端口客户端ID
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self.data_clients = set() # 数据端口客户端ID
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self.send_queue = queue.Queue() # 发送队列（仅用于命令端口广播）
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# 客户端管理（单客户端场景）
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self.cmd_clients = set()
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self.data_clients = set()
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self.current_data_client = None # 唯一数据客户端身份，用于发送滤波结果
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# 范式buffer参数, 事件检测相关
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self._event_lock = threading.Lock()
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# 发送队列（双端口分离）
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self.cmd_send_queue = queue.Queue() # 8099端口命令结果队列
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self.data_send_queue = queue.Queue() # 8100端口滤波数据队列
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# 范式buffer与事件检测参数
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self.predict_event = 99
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self.events = [1, 2, self.predict_event]
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self.latency = 50
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@@ -98,60 +103,131 @@ class zmqServer(threading.Thread):
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self.event_inner_idx = -1
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self.interval_inited = False
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def interval_init(self, decoder_class):
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if decoder_class == 'ssmvep':
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interval_epoch = ast.literal_eval(IniRead('system', 'SSMVEP_IntervalEpoch'))
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self.interval_epoch = [int(i * self.device_info['sample_rate']) for i in interval_epoch] # epoch截取信息
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self.train_epoch = [int(self.interval_epoch[0]),
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int(self.interval_epoch[1] + 0.1 * self.device_info['sample_rate'])] # 训练样本epoch
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self.latency = (self.interval_epoch[
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1] + 0.1 * self.device_info['sample_rate']) // 5 # 提取epoch的延迟标记，5代表每次解包得到的5位采样点;0.1表示比实际需要的长度多取0.1，会被截掉
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self.interval_epoch = [int(i * self.device_info['sample_rate']) for i in interval_epoch]
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self.train_epoch = [
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int(self.interval_epoch[0]),
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int(self.interval_epoch[1] + 0.1 * self.device_info['sample_rate'])
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]
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self.latency = (self.interval_epoch[1] + 0.1 * self.device_info['sample_rate']) // 5
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self.train_latency = (self.train_epoch[1] + 0.1 * self.device_info['sample_rate']) // 5
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elif decoder_class == 'mi':
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interval_epoch = ast.literal_eval(IniRead('system', 'MI_IntervalEpoch'))
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self.interval_epoch = [int(i * self.device_info['sample_rate']) for i in interval_epoch] # epoch截取信息
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self.interval_epoch = [int(i * self.device_info['sample_rate']) for i in interval_epoch]
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self.train_epoch = self.interval_epoch.copy()
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self.latency = (self.interval_epoch[1]) // 5 # 提取epoch的延迟标记，5代表每次解包得到的5位采样点;
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self.latency = self.interval_epoch[1] // 5
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self.train_latency = self.latency
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print('时间窗：', (interval_epoch))
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self.count_events: Dict[str, int] = {} # 表示包延迟的计数信息
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self.event_inner_idx = -1 # event在5位数据包内部的idx
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self.epoch_finished = False # 接收epoch是否完整
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self.pack_contain_event = False # 当前包是否含有event
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algo_log(f"时间窗初始化完成: {interval_epoch}", level="INFO")
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self.count_events: Dict[str, int] = {}
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self.event_inner_idx = -1
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self.epoch_finished = False
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self.pack_contain_event = False
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self.predict_event = 99
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self.events = [1, 2, self.predict_event]
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self.interval_inited = True
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# -------------------------- 8099端口：命令结果广播 --------------------------
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def broadcast_message(self, method, params):
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"""Put message into queue to be sent to all command clients"""
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self.send_queue.put((method, params))
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"""
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向所有8099端口客户端广播JSON格式的命令结果
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用于：解码结果、训练状态、错误提示、进度通知等
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"""
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self.cmd_send_queue.put((method, params))
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def _handle_cmd_message(self, frames):
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"""处理命令端口消息（原有命令交互逻辑）"""
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if len(frames) < 3:
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def _process_cmd_send_queue(self):
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"""处理8099端口发送队列，在主线程执行（保证ZMQ线程安全）"""
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while not self.cmd_send_queue.empty():
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method, params = self.cmd_send_queue.get()
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if not self.cmd_clients:
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continue
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try:
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msg = {'method': method, 'params': params}
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msg_bytes = json.dumps(msg).encode('utf-8')
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algo_log(f"发送命令结果: {msg}", level="DEBUG")
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# 广播到所有命令客户端
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for client_id in list(self.cmd_clients):
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try:
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self.cmd_socket.send_multipart([client_id, b"", msg_bytes])
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except Exception as e:
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algo_log(f"向命令客户端{client_id}发送失败: {e}", level="ERROR")
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self.cmd_clients.discard(client_id)
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except Exception as e:
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algo_log(f"命令结果打包失败: {e}", level="ERROR")
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# -------------------------- 8100端口：滤波结果发送 --------------------------
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def send_filtered_data(self, filtered_data):
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"""
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向8100端口客户端发送二进制格式的滤波结果
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用于：上位机实时绘图的脑电波形数据
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:param filtered_data: 滤波后数据，shape=(通道数, 50)，float64格式
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"""
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if self.current_data_client is None:
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algo_log("数据客户端未连接，跳过滤波数据发送", level="WARNING")
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return
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# 转置为上位机需要的[50, 通道数]格式
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filtered_data = filtered_data.T.astype(np.float32)
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send_buf = filtered_data.tobytes()
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algo_log(f"发送滤波数据，长度: {len(send_buf)}字节, filtered_data.shape: {filtered_data.shape}", level="DEBUG")
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self.data_send_queue.put(send_buf)
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def _process_data_send_queue(self):
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"""处理8100端口发送队列，在主线程执行（保证ZMQ线程安全）"""
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while not self.data_send_queue.empty():
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send_buf = self.data_send_queue.get()
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if self.current_data_client is None:
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continue
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try:
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# 标准ROUTER发送格式：[客户端ID, 空分隔帧, 数据帧]
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self.data_socket.send_multipart([
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self.current_data_client,
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b"",
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send_buf
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])
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algo_log(f"发送滤波数据成功，长度: {len(send_buf)}字节", level="DEBUG")
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except Exception as e:
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algo_log(f"发送滤波数据失败: {e}", level="ERROR")
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# 客户端断开，重置身份
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self.current_data_client = None
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self.data_clients.clear()
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# -------------------------- 命令端口消息处理 --------------------------
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def _handle_cmd_message(self, frames):
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"""处理8099端口JSON命令消息"""
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if len(frames) < 3:
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algo_log(f"无效命令帧：长度不足3帧，实际{len(frames)}", level="ERROR")
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return
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ident, _, message_bytes = frames[:3]
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# 注册新的命令客户端
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if ident not in self.cmd_clients:
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self.cmd_clients.add(ident)
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algo_log(f"New CMD Client Connected: {ident} (port: {self.cmd_port})")
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algo_log(f"新命令客户端连接成功: {ident}", level="INFO")
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# 解析消息
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# 解析JSON命令
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try:
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message = json.loads(message_bytes.decode('utf-8'))
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except json.JSONDecodeError:
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algo_log(f"Invalid JSON from CMD client {ident}")
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algo_log(f"无效JSON命令: {message_bytes.hex()}", level="ERROR")
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self.broadcast_message("error", {"code": 400, "message": "无效JSON格式"})
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return
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algo_log(f"Received CMD request: {message}")
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algo_log(f"收到命令: {message}", level="INFO")
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method = message.get("method")
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params = message.get("params")
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# 原有命令处理逻辑
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# 命令处理逻辑
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if method == "sync":
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self.state_mode = 'sync'
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elif method == "targetFreqs":
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@@ -163,108 +239,89 @@ class zmqServer(threading.Thread):
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self.changeTarget = True
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elif method == "decoderClass":
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if not isinstance(params, str):
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algo_log(f"decoderClass must be a str")
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algo_log(f"decoderClass必须是字符串")
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return
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if params != self.decoder_class:
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self.decoder_class = params
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self.decoder_switch = True
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elif method == "train":#训练状态
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elif method == "train":
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self.state_mode = 'train'
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self.StartTrain = True
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self.currentLabel = params # 当前刺激端的训练标签
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# self.sunnyLinker.push_trigger(self.labels[self.currentLabel])
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elif method == "predict":#预测状态
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self.currentLabel = params
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elif method == "predict":
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self.state_mode = 'predict'
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if params == 1: #开始解码
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self.StartDecode = True
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# self.sunnyLinker.push_trigger(0x63)
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elif params == 2: #停止解码
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self.IsExitApp = True
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self.running = False
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elif method == "rest": #休息状态
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elif method == "rest":
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self.state_mode = 'rest'
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elif method == "impedance":
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if params == 1:
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self.open_Impedance = True # 开启阻抗
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# self.get_Impedance = True # 返回阻抗
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self.open_Impedance = True
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elif params == 2:
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self.open_Impedance = False # 关闭阻抗
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self.open_Impedance = False
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else:
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algo_log(f"未知命令：{method}", level="WARNING")
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# elif method == "getReport":
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# self.getReport = True
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# elif params == 2:
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# self.open_Impedance = False # 关闭阻抗
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# self.get_Impedance = False # 停止返回阻抗
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self.broadcast_message("error", {"code": 404, "message": f"未知命令: {method}"})
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# -------------------------- 数据端口消息处理 --------------------------
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def _handle_data_message(self, frames):
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"""
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处理8100端口原始脑电二进制数据
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固定格式：上位机发送 (5,66) float32 二维数组字节流（已转换为微伏物理量）→ 转置为 (66,5) 写入双缓冲区
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"""
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# 1. 校验ZMQ消息帧完整性（ROUTER接收DEALER消息的帧格式：[客户端ID, 发送方ID, 空帧, 数据帧]）
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if len(frames) < 4: # 至少需要4帧
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algo_log(f"Invalid data frame: 帧数量不足，期望≥4，实际{len(frames)}", level="ERROR")
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"""处理8100端口二进制脑电数据消息"""
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algo_log(f"收到数据帧，总帧数：{len(frames)}", level="DEBUG", record_once=True)
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# 然后再进行解析
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if len(frames) == 4:
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# 你的上位机格式
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ident, sender_ident, empty_sep, data_bytes = frames[:4]
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elif len(frames) == 3:
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# 标准格式
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ident, empty_sep, data_bytes = frames[:3]
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else:
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return
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# 2. 正确解析帧（适配DEALER→ROUTER的帧格式）
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client_ident, sender_ident, empty_sep, data_bytes = frames[:4]
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if empty_sep != b'': # 校验空分隔帧
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algo_log(f"Invalid frame separator: 期望空字节，实际{empty_sep}", level="ERROR")
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return
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# 3. 客户端管理（单客户端场景，自动更新最新身份）
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if client_ident not in self.data_clients:
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self.data_clients.add(client_ident)
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self.current_data_client = client_ident # 保存唯一客户端身份，用于后续回复滤波结果
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print(f"[INFO] 新数据客户端连接成功：{client_ident}")
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# 注册新的数据客户端（单客户端场景，自动覆盖旧身份）
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if ident not in self.data_clients:
|
||||
self.data_clients.clear() # 单客户端，只保留最新连接
|
||||
self.data_clients.add(ident)
|
||||
self.current_data_client = ident
|
||||
algo_log(f"新数据客户端连接成功: {ident}", level="INFO")
|
||||
try:
|
||||
# 4. 精确长度校验（核心：固定(5,66) float32 = 5*66*4=1320字节）
|
||||
EXPECTED_BYTES = self.device_info['frame_points'] * self.device_info['channel_nums'] * 4 # 每个float32占4字节
|
||||
# 精确长度校验
|
||||
EXPECTED_BYTES = self.device_info['frame_points'] * self.device_info['channel_nums'] * 4
|
||||
if len(data_bytes) != EXPECTED_BYTES:
|
||||
algo_log(f"[ERROR] 数据长度错误：期望{EXPECTED_BYTES}字节，实际{len(data_bytes)}字节", level="ERROR")
|
||||
algo_log(f"数据长度错误：期望{EXPECTED_BYTES}字节，实际{len(data_bytes)}字节", level="ERROR")
|
||||
return
|
||||
|
||||
# 5. 零拷贝二进制解析 + 维度转换
|
||||
|
||||
# 零拷贝解析 + 维度转换
|
||||
data_np = np.frombuffer(data_bytes, dtype=np.float32)
|
||||
data_np = data_np.reshape(self.device_info['frame_points'], self.device_info['channel_nums'])
|
||||
data_np = data_np.T.astype(np.float64)
|
||||
|
||||
# 6. 写入滤波缓冲区
|
||||
self.filterBuffer.appendBuffer(data_np)
|
||||
# 写入滤波缓冲区
|
||||
with self.filterBufferLock:
|
||||
self.filterBuffer.appendBuffer(data_np)
|
||||
|
||||
# 7. 写入范式缓冲区
|
||||
try:
|
||||
with self.paradigmBufferLock:
|
||||
if self.interval_inited:
|
||||
self.epoch_finished = self.detect_event(data_np)
|
||||
if self.pack_contain_event:
|
||||
self.paradigmBuffer.resetAllPara() # 检测到当前pack含有event，清除ringbuffer中之前的数据
|
||||
self.paradigmBuffer.appendBuffer(data_np)
|
||||
if self.epoch_finished:
|
||||
time.sleep(0.005)
|
||||
algo_log('epoch_finished: ' + datetime.datetime.now().strftime('%H:%M:%S.%f')[:-3], level="DEBUG")
|
||||
else:
|
||||
self.paradigmBuffer.appendBuffer(data_np)
|
||||
except Exception as e:
|
||||
print("锁：写入异常",e)
|
||||
self.paradigmBuffer.appendBuffer(data_np)
|
||||
|
||||
# algo_log(f"数据写入成功：shape={data_np.shape}, 范围=[{data_np.min():.2f}, {data_np.max():.2f}] μV", level="DEBUG")
|
||||
# 写入范式缓冲区
|
||||
with self.paradigmBufferLock:
|
||||
if self.interval_inited:
|
||||
self.epoch_finished = self.detect_event(data_np)
|
||||
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")
|
||||
else:
|
||||
self.paradigmBuffer.appendBuffer(data_np)
|
||||
|
||||
except Exception as e:
|
||||
algo_log(f"数据处理失败：{str(e)}", level="ERROR")
|
||||
algo_log(f"数据处理失败: {str(e)}", level="ERROR")
|
||||
if IniRead('system', 'algo_log_level', 'INFO') == 'DEBUG':
|
||||
import traceback
|
||||
traceback.print_exc()
|
||||
|
||||
# 检测是否含有标签
|
||||
# -------------------------- 事件检测 --------------------------
|
||||
def detect_event(self, samples):
|
||||
self.pack_contain_event = False
|
||||
# 第65通道为事件通道
|
||||
events = np.array(samples[-2])[0].tolist()
|
||||
for idx, event in enumerate(events):
|
||||
if int(event) in self.events:
|
||||
@@ -281,76 +338,54 @@ class zmqServer(threading.Thread):
|
||||
self.count_events[new_key] = self.train_latency + 1
|
||||
self.event_inner_idx = idx
|
||||
self.pack_contain_event = True
|
||||
|
||||
# 倒计时并清理过期事件
|
||||
drop_items = []
|
||||
for key, value in self.count_events.items():
|
||||
value = value - 1
|
||||
value -= 1
|
||||
if value == 0:
|
||||
drop_items.append(key)
|
||||
self.count_events[key] = value
|
||||
|
||||
for key in drop_items:
|
||||
del self.count_events[key]
|
||||
|
||||
if drop_items:
|
||||
return True
|
||||
return False
|
||||
|
||||
|
||||
|
||||
def _process_send_queue(self):
|
||||
"""处理发送队列，向所有命令客户端广播消息"""
|
||||
while not self.send_queue.empty():
|
||||
method, params = self.send_queue.get()
|
||||
if self.cmd_clients:
|
||||
try:
|
||||
msg = {'method': method, 'params': params}
|
||||
msg_bytes = json.dumps(msg).encode('utf-8')
|
||||
|
||||
# 打印日志（隐藏大尺寸数据）
|
||||
if method in ['single_trial_plot', 'miReport']:
|
||||
print(f"{{'method': '{method}', 'params': <Base64 Image Data>}}")
|
||||
else:
|
||||
print(f"Sending CMD message: {msg}")
|
||||
|
||||
# 广播到所有命令客户端
|
||||
for client_id in list(self.cmd_clients):
|
||||
try:
|
||||
self.cmd_socket.send_multipart([client_id, b'', msg_bytes])
|
||||
except Exception as e:
|
||||
print(f"Error sending to CMD client {client_id}: {e}")
|
||||
self.cmd_clients.discard(client_id) # 移除失效客户端
|
||||
except Exception as e:
|
||||
print(f"Error preparing broadcast: {e}")
|
||||
|
||||
# -------------------------- 主循环 --------------------------
|
||||
def run(self):
|
||||
self.running = True
|
||||
algo_log(f"algo ZMQ Server started - CMD Port: {self.cmd_port}, DATA Port: {self.data_port}", level="INFO")
|
||||
algo_log(f"ZMQ服务器启动成功 - 命令端口: {self.cmd_port}, 数据端口: {self.data_port}", level="INFO")
|
||||
|
||||
try:
|
||||
while self.running:
|
||||
# 1. 处理发送队列（命令端口广播）
|
||||
self._process_send_queue()
|
||||
# 1. 处理两个端口的发送队列（必须在主线程执行）
|
||||
self._process_cmd_send_queue()
|
||||
self._process_data_send_queue()
|
||||
|
||||
# 2. 轮训监听两个Socket的输入事件
|
||||
# 2. 轮询监听两个端口的输入事件
|
||||
socks = dict(self.poller.poll(50))
|
||||
|
||||
# 处理命令端口消息
|
||||
# 处理8099命令端口消息
|
||||
if self.cmd_socket in socks and socks[self.cmd_socket] == zmq.POLLIN:
|
||||
frames = self.cmd_socket.recv_multipart()
|
||||
self._handle_cmd_message(frames)
|
||||
|
||||
# 处理数据端口消息
|
||||
# 处理8100数据端口消息
|
||||
if self.data_socket in socks and socks[self.data_socket] == zmq.POLLIN:
|
||||
frames = self.data_socket.recv_multipart()
|
||||
self._handle_data_message(frames)
|
||||
|
||||
except Exception as e:
|
||||
print(f"Server error occurred: {e}")
|
||||
algo_log(f"服务器主循环异常: {e}", level="ERROR")
|
||||
finally:
|
||||
self.running = False
|
||||
# 关闭所有Socket和上下文
|
||||
# 优雅关闭所有资源
|
||||
self.cmd_socket.close()
|
||||
self.data_socket.close()
|
||||
self.context.term()
|
||||
print("Server sockets and context closed.")
|
||||
algo_log("ZMQ服务器已关闭", level="INFO")
|
||||
|
||||
def stop(self):
|
||||
"""显式关闭服务器"""
|
||||
@@ -358,10 +393,10 @@ class zmqServer(threading.Thread):
|
||||
self.cmd_socket.close()
|
||||
self.data_socket.close()
|
||||
self.context.term()
|
||||
print(f"Server closed explicitly - CMD Port: {self.cmd_port}, DATA Port: {self.data_port}")
|
||||
algo_log(f"服务器已显式关闭 - 命令端口: {self.cmd_port}, 数据端口: {self.data_port}", level="INFO")
|
||||
|
||||
if __name__ == '__main__':
|
||||
# 初始化并启动服务器（默认cmd=8099, data=8100）
|
||||
# 初始化并启动服务器
|
||||
server = zmqServer()
|
||||
server.start()
|
||||
|
||||
@@ -370,5 +405,5 @@ if __name__ == '__main__':
|
||||
while server.running:
|
||||
threading.Event().wait(1)
|
||||
except KeyboardInterrupt:
|
||||
print("Received KeyboardInterrupt, stopping server...")
|
||||
server.stop()
|
||||
algo_log("收到键盘中断信号，正在停止服务器...", level="INFO")
|
||||
server.stop()
|
||||
Reference in New Issue
Block a user