04 April, 2014

Generating Real-Time Plots with Python

In my previous post we described plotting data using MatplotLib utilities and Python.  While this may be valuable, it becomes notably more valuable when you can generate 'live' plots during run-time.  In a past employment I worked with a series of controls engineers that utilized real-time data plots to debug and develop a highly complex multi-axis weapons system and it was the first time I understood how a real-time plot of sequence of steps simplified the development effort.

Let's get started.
Unlike the previous post, let's create the data and plot it as it is generated.


#!/usr/bin/python
from pylab import *;
import time;

def log(M):
  print "__(log) " + M;

def test01():
  plt.ion();
  fig=plt.figure(1);
  ax1=fig.add_subplot(111);
  l1,=ax1.plot(100,100,'r-');

  D=[];
  i=0.0;
  while (i < 50.0):
    D.append((i,sin(i)));
    T=[x[0] for x in D];
    L=[x[1] for x in D];
    l1.set_xdata(T);
    l1.set_ydata(L);
    ax1.relim();
    ax1.autoscale_view();
    plt.draw();
    i+=0.10;
    time.sleep(1/10.0);
  show(block=True);

#---main---
log("main process initializing");
test01();
log("main process terminating");

The result is a dynamically generated plot that resembles the following;
video

Tie this plotting routine to a system providing run-time information via a socket, or perhaps monitoring network traffic via pcapture libraries and you've got yourself the foundation of a real-time data monitoring system.

Cheers.

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