如何使用Python实时绘制串行数据

Question

我试图实时绘制从串行设备接收的制表符分隔值。我是python的新手，但是设法将一个管理它的脚本拼凑在一起，但是它似乎无法处理数据的接收速率，并且在减慢并最终冻结之前无法使用大量的处理能力。我能做些什么来防止这种情况。我已经附上了我正在使用的数据和脚本的示例]

我接收到的数据看起来像这样，并且每半秒以大约一行的速度接收。

546 5986637 3598844 +26.0 01A0

547 5986641 3598843 +25.50 0198

548 5986634 3598844 +24.50 0188

from matplotlib import pyplot as plt
from matplotlib import animation
import serial
from pandas import DataFrame
from datetime import datetime
import csv


filename = datetime.now().strftime("%d-%m-%Y_%I-%M-%S_%p") #Gets time and date in readable format for filenaming.
Data1 = {'Value':[0],'Frequency 1':[0],'Frequency2':[0], 'Temperature':[0]}
df = DataFrame(Data1,columns=['Value', 'Frequency1','Frequency2','Temperature'])
serial_port = 'COM5'; #Different port for linux/mac
baud_rate = 9600; #In arduino, Serial.begin(baud_rate)
write_to_file_path = "output.txt"; 
data = []
ft = []
output_file = open(write_to_file_path, "w+");
ser = serial.Serial(serial_port, baud_rate)

plt.ion()
fig, (ax1, ax2, ax3)  = plt.subplots(3, 1, sharex=True, sharey=False, )

ax1.set_title('Temp')
ax2.set_title('Freq 1')
ax3.set_title('Freq 2')
ax1.set_ylabel('Temperature')
ax2.set_ylabel('Frequency')
ax3.set_ylabel('Frequency')
ax1.ticklabel_format(useOffset=False)
ax2.ticklabel_format(useOffset=False)
ax3.ticklabel_format(useOffset=False)
ax1.ticklabel_format(style = 'plain', axis='y', scilimits=(0,0))
ax2.ticklabel_format(style = 'sci', axis='y', scilimits=(6,6))
ax3.ticklabel_format(style = 'sci', axis='y', scilimits=(6,6))
while True:
    line = ser.readline();
    line = line.decode("utf-8") #ser.readline returns a binary, convert to string
    print(line)
    line1 = line.split('\t') #Separates values by tabs
    output_file.write(line); #Writes to text file
    data.append(line1) #Adds line to data file
    newline = [float(line1[0]), float(line1[1]), float(line1[2]), float(line1[3])] #Creates line of float values
    ft.append(newline) # Adds to list of floats
    f1 = float(line1[0]) # Line number (count)
    f2 = float(line1[1]) # Frequency 1
    f3 = float(line1[2]) # Frequency 2
    f4 = float(line1[3]) # Temperature in C
    f5 = str(line1[4])   # Temperature in Hex, treated as a string
#    Data2 = {'Value':[f1],'Frequency 1':[f2],'Frequency2':[f3], 'Temperature':[f4]}
#    df2 = DataFrame(Data2,columns=['Value', 'Frequency1','Frequency2','Temperature'])
#    df.append(df2)

    #DataFrame still not working, need to fix so that data is stores as integer or float
    plt.pause(0.1)


    ax1.plot(f1, f4, marker='.', linestyle='solid') #subplot of freq 1
    ax2.plot(f1, f2, marker='.', linestyle='solid') #subplot of freq 2
    ax3.plot(f1, f3, marker='.', linestyle='solid') #subplot of Temp in C
    plt.subplot
    plt.xlabel("Count")
    with open(filename +".csv","a") as f: # Writes data to CSV, hex values for temp don't seem to be writing
        writer = csv.writer(f,delimiter=",")
        writer.writerow([f1, f2, f3 , f4, f5 ])


    plt.draw()
    plt.savefig(filename +'.png',bbox_inches='tight') #Saves the plot

Answer 1

您可以考虑使用线程来拆分您的任务。您可能不需要每次接收新数据时都保存该数字。您可以通过仅每30秒更新一次绘图来减少计算量。您还可以拆分写入csv的方式，这样您就有了三个线程，一个线程在寻找数据，一个线程在存储缓冲的数据，另一个线程在更新绘图。

This answer可能是一个很好的参考。

在foo（）的末尾，创建一个计时器，该计时器将在10秒后调用foo（）本身。因为，Timer创建了一个新线程来调用foo（）。

import time, threading
def foo():
    print(time.ctime())
    threading.Timer(10, foo).start()

foo()

#output:
#Thu Dec 22 14:46:08 2011
#Thu Dec 22 14:46:18 2011
#Thu Dec 22 14:46:28 2011
#Thu Dec 22 14:46:38 2011