使用python和matplotlib同時獲取數據和更新圖表

Question

我正在使用Python編寫代碼以通過串行端口與超聲波測距儀進行通信，以執行以下操作：
- 每隔0.1秒發送一條命令給傳感器進行距離測量，並記錄傳感器
- 顯示所有的距離測量從最後5秒

這裏的陰謀是我的代碼的響應：

import serial 
import numpy as np 
import time 
from matplotlib import pyplot as plt 

tagnr=2#Tag number of the sensor that we're pinging 
samplingRate=.1#Sampling Rate in seconds 
graphbuf=50.#Buffer length in samples of logger graph 

!#Initialize logger graph 
gdists=np.zeros(graphbuf) 
ax1=plt.axes() 

!#Main loop 
nsr=time.time()#Next sample request 
try: 
    while True: 
     statreq(tagnr)#Send status request to sensor over serial port 
     temp,dist=statread(tagnr)#Read reply from sensor over serial port 
     gdists=np.concatenate((gdists[1:],np.array([dist]))) 
     print gdists 
     nsr=nsr+samplingRate 
     while time.time()<nsr: 
      pass 

finally: 
    ser.close()#Close serial port 
    print 'Serial port closed.' 

現在，我的代碼可以獲取最後50個mea的數組但我不知道如何在圖表中同時顯示這些內容（我通常使用Matplotlib繪製圖表）。我應該使用線程嗎？或者使用pyGTK或pyQt4使用動畫圖形？我也在考慮使用pygame？我的計時機制並不是非常優化，但我認爲它非常準確。

Answer 1

matplotlib有動畫的圖表，允許數據在圖表顯示時更新：take a look at this page。

您的代碼可能是這樣的：

import serial 
import numpy as np 
import time 
from matplotlib import pyplot as plt 

plt.ion() # set plot to animated 

tagnr=2#Tag number of the sensor that we're pinging 
samplingRate=.1#Sampling Rate in seconds 
graphbuf=50.#Buffer length in samples of logger graph 

!#Initialize logger graph 
gdists=np.zeros(graphbuf) 
ax1=plt.axes() 

# make plot 
line, = plt.plot(gdists) 

!#Main loop 
nsr=time.time()#Next sample request 
try: 
    while True: 
     statreq(tagnr)#Send status request to sensor over serial port 
     temp,dist=statread(tagnr)#Read reply from sensor over serial port 
     gdists=np.concatenate((gdists[1:],np.array([dist]))) 
     print gdists 

     line.set_ydata(gdists) # update the data 
     plt.draw() # update the plot 

     nsr=nsr+samplingRate 
     while time.time()<nsr: 
      pass 

finally: 
    ser.close()#Close serial port 
    print 'Serial port closed.' 

只是一些建議（可能是壞的）：我個人使用time.sleep在釋放一些處理器不失精確度的方法。我也會在你的try/except塊中加入一些錯誤類型。我認爲np.roll比concatenate更好/更快。