Complex numerical simulations usually take a long time to run while using full CPU(s). If something goes wrong during such a run, we generally only find out in the end of the run when the traces of what went wrong are no longer available, debugging such codes is also not an easy task, because the code gets even slower running through the debugger, and when we don't know where the code is going to break down, it can become a painstaking process.
So any way to monitor such a running code without slowing it down is always welcome. As the title of this article points out, if your code is a numerical simulation, real-time plots of its progress is an extremely useful thing to have. However, traditional Python plotting tools such as Matplotlib, which I have been using for many years, is not a viable solution since it is not very fast and don't support very well real-time plotting.
Recently, while going crazy debugging one such simulation I decide to come up with a solution for real-time plotting in Python. I examine many candidates which I won't mention here, in order to keep this story simple. I finally settled down on a old but still very good solution: Gnuplot!
Since Gnuplot is a stand-alone program, implemented in C, it is very fast at drawing plots and with the help of python-gnuplot, I was able write a class with methods which would send data to Gnuplot and returned immediately without slowing down my running Python code! Gnuplot, on it's side plotted whatever data I throwed at it very fastly, giving me my much needed real-time scope into my simulations. Gnuplot is a real example of the Unix philosophy: Do one thing, and do it well!!