如何解决使用线程实时绘制高频数据而无需冻结Tkinter
我正在尝试创建一个可以读取@ 250Hz的EEG信号（OpenBCI）并同时显示它的界面。将来，我将其与一些实验（例如oddball和p300）集成。几个月前，我已经在这个问题中解决了部分问题，当时我在努力建立线程以获取数据并显示图形：Reading higher frequency data in thread and plotting graph in real-time with Tkinter。
但是最近，当我试图使该应用程序获取样本直到按下停止按钮时，我才意识到它无法“实时”运行。给定处理时间，线程的采集部分运行良好，但是图形仅在收集完所有样本后显示（我用1500个样本对其进行了测试，理论上在250Hz的频率下需要6秒，并且仅图形在大约6秒钟后开始刷新），并且我的界面死机了，没有让我单击按钮使其停止。
有人知道如何处理此案吗？我是否也应该在线程中获取“绘图图”函数（如果可以，我应该将其app.root.after当作处理对象）吗？并且在所有信号采集发生时如何使我的界面仍然可操作？
感谢所有帮助。 谢谢！
##INTERFACE SCRIPT
import tkinter as tk
from tkinter import ttk
from tkinter.scrolledtext import ScrolledText
import scroller as scrl
import logging
import requests
import matplotlib
import matplotlib.pyplot as plt
import matplotlib.animation as animation
from matplotlib.backends.backend_tkagg import FigureCanvasTkAgg #NavigationToolbar2TkAgg <<Did not work
import random
from pandas import DataFrame
import stream_lsl_eeg as leeg
from FlickeringBoxes import *
import numpy as np
class AppWindow:
def plotGraph(self,x,y):
self.ax.clear()
if isinstance(y,list):
self.ax.plot(x,y,color = tx_color)
elif isinstance(y,np.ndarray):
for i in range(np.size(y,1)):
self.ax.plot(x,y[:,i],color = tx_color)
# self.ax.set_xlim([0,249]) def plotGraph(self,list):
# plot data alternatively
self.ax.plot(x,np.ndarray):
# print("\n<>Receiveing Array:")
# print(type(y))
# print(np.shape(y))
# print(np.size(y,1))
for i in range(np.size(y,color = tx_color)
self.figure.canvas.draw()
def __init__(self):
#SOME TKINTER ELEMENTS
##Application Design
self.root = tk.Tk() #start of application
#Button for Getting EEG LSLs inlet
self.btn_StartEEGLSL = tk.Button(self.EEG_frame,text = "Start EEG LSL Inlet",bg = bg_color,fg = tx_color,state = tk.DISABLED,command = lambda: leeg.getInlet(self))
self.btn_StartEEGLSL.place(anchor = 'nw',relx = 0.52,rely = 0.15,width = 196,height = 40)
#Button to test the SSVEP only w/ EEG
self.btn_txt_Receive = tk.StringVar()
self.btn_ReceiveEEG = tk.Button(self.EEG_frame,text = "Receive EEG signal",command = lambda: leeg.getEEGstream(self))
self.btn_txt_Receive.set("Receive EEG signal")
self.btn_ReceiveEEG.place(anchor = 'nw',rely = 0.5,height = 40)
#MORE TKINTER ELEMENTS
#stream_lsl_eeg SCRIPT
from pylsl import StreamInlet,resolve_stream
import tkinter as tk
import AppWindow as app
import matplotlib.pyplot as plt
import matplotlib.animation as animation
import threading
import queue
from queue import Empty
import time
from datetime import datetime
import pandas as pd
import numpy as np
from scipy.signal import butter,lfilter
class myThread(threading.Thread):
def __init__(self,threadID,name,q,raw,flag,app = float("NaN")):
threading.Thread.__init__(self)
self.threadID = threadID
self.name = name
self.q = q
self.raw = raw
self.flag = flag
self.app = app
def run(self):
print("Starting ",self.name)
pullSamples(self.q,self.raw,self.flag) #place where function is called
#Thread elements
threadLock = threading.Lock()
dataqueue = queue.Queue()
filteredq = queue.Queue()
rawqueue = queue.Queue()
flag = queue.Queue()
flag.put(0)
thread1 = myThread(1,"Thread-1",dataqueue,rawqueue,flag)
#Golbal Variables declaration
rawsamples = []
filtsamples = []
rawtimestamps = np.empty([1,1])
prosamples = []
show_samples,show_timestamps = [],[]
stopcollecting = 0
kounter = 0
chk_chs = [] #this is an array with the channels that will be used
def getInlet(app):
global inlet
app.logger.warn('Looking for an EEG strean...')
streams = resolve_stream('type','EEG')
inlet = StreamInlet(streams[0])
app.logger.warn('Connected\n--')
app.btn_ReceiveEEG.config(state = tk.NORMAL)
def pullSamples(q,flag): #THREAD #1
global stopcollecting
i = 0
while i<1500: #<<< in the future: "while flag.get() not 2"?
flag.put(0) #putting a value at every round because the other function will test it every round
sample,timestamp = inlet.pull_sample()
threadLock.acquire() #thread locks to put info in the queue
q.put([sample,timestamp]) #data is put in the queue for other threads to access
raw.put([sample,timestamp]) #raw data
threadLock.release() #thread unlocks after info is in
i += 1
stopcollecting = 1
flag.put(1) #thread sends a last flag to indicat it is finished. Once the other thread unpacks the 1,it will know info stream is over
def plotRawSamples(flag,app): #Outside Threads
global rawsamples
global rawtimestamps
rawsamples = np.empty([len(chk_chs),1])
filtsamples = np.empty([len(chk_chs),1])
global kounter
# rawsamples = np.array([[]])
# rawtimestamps = np.array([])
while dataqueue.qsize( ):
try:
ss,ts = queue2var(dataqueue,chk_chs)
if not rawsamples.size == 0:
rawsamples = np.hstack((rawsamples,ss))
else:
rawsamples = np.array(ss)
if not rawtimestamps.size == 0:
rawtimestamps = np.append(rawtimestamps,ts)
else:
rawtimestamps = np.array(ts)
if kounter>0 and kounter % 15 == 0:
if np.size(rawsamples,1)>=250:
# app.plotGraph(rawtimestamps[-250:-1],rawsamples[-250:-1,:]) #for lists
app.plotGraph(rawtimestamps[-250:-1],rawsamples[:,-250:-1].transpose()) #for numpy
else:
app.plotGraph(rawtimestamps,rawsamples.transpose()) #for lists
kounter += 1
except Empty:
return
app.root.after(200,plotRawSamples,app)
def queue2var(q,chans):
ss,t = [],[]
s,t = q.get(0)
for ch in chans:
ss.append([s[ch]])
# t = pd.Timestamp(t,unit ='s')
ss = np.array(ss)
ss = ss #.transpose()
return ss,t
def getEEGstream(app):
app.logger.warn('|Starting threads...')
start = time.perf_counter()
thread1.start()
##
app.logger.warn('|Started...')
plotRawSamples(flag,app)
##
thread1.join()
## CLOSE THREAD SOMEWHERE HERE?
finish = time.perf_counter()
app.logger.warn(f'|Sizes: Samples [{rawsamples.shape}],Timestamp [{rawtimestamps.shape}]')
app.logger.warn(f'|Sucessfully streamed in {round(finish-start,3)}s!\n--')
print("\n\n>>>DONE<<<\n\n")
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