tplot2 (diagnostics part 5)

In previous posts, (1, 2, 3, 4), I covered the updates I made to the underlying serialization and log file format used in mjlib and the quad A1.  This time I’ll talk about the graphical application that uses that data to investigate live operation.


You might note the “2” in the name and realize that yes, this is the second incarnation in the mjmech repository, tplot being the initial.  The original was a largely a one-day hack job that glued together the python log bindings I had with matplotlib.  It provided a time scrubber, a tree view, and a plot window where any number of things could be plotted against one another.


It did have a number of problems:

  • Speed: The original tplot read the entirety of the log into memory before letting you view any of it.  Further, while reading it into memory, it converted everything into python structures.  This took some time for even relatively short logs.
  • Coding efficiency: This might seem paradoxical, but developing GUIs in PySide still takes a decent amount of time, even if you don’t care what they look like at all.  Either you have all the overhead of using Qt Designer and thus have to manage either UI file loading or compiling, or you design the layouts in code and have mysterious layout issues because the exact construction requirements to get valid layouts are very hard to determine without looking at the QT source.  There are so many signals to connect to slots, and so much state to manage, and anything non-trivial requires deriving custom widget classes with many virtual methods to overload.
  • Integration with video: Yes, QT has a video subsystem, but it is intended for live playback, not frame accurate seeking, and also has a lot of overhead to use it effectively.
  • Build footprint: Except for tplot, I have moved the entirety of the code and its transitive dependencies for the quad A1 to be built from source under bazel.  This makes cross compiling easy, and well as making cross platform and cross distribution support relatively painless.  While I have converted some large things to bazel (gstreamer), QT and PySide was a bridge too far.
  • Python support: PySide1 only supports QT 4.  QT5 had no permissive python bindings until very recently, which while they are in Ubuntu 20.04, didn’t make it into 18.04.  That isn’t of course a deal-breaker, just an annoyance.


For tplot2, I decided to try my hand using the Dear Imgui library that I used for the Mech Warfare control interface.  It is remarkably concise, very quick to develop for, looks at least “OK”, and has no dependencies other than OpenGL.  Once I had multiple axis support in implot, getting to tplot1 level functionality was remarkably quick, maybe a day of effort in total:



Next up, I’ll cover the improvements that I made to tplot2 that made it worth all the effort.

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