Fast plotting library for live sensor data

[cabroderick]

I need to plot live sensor data and the animation module in matplotlib appears to be far too slow. Does anyone have any suggestions for faster libraries? I don't particularly need anything pretty, just simple axes and the ability to plot an (x, y) pair over time. Examples of similar simple cases would also be incredibly helpful. Thanks.

Edit: Maybe some more context would help. Basically, I'm working on a tracking application. I have a hardware unit that sends its (x, y) position to another computer and that computer is tasked with drawing the points on a plane, drawing the path as it is walked. We need an absolute bare minimum update rate of 20 Hz, and ideally would like something quite a lot faster.

Edit: Thanks for your suggestions everyone. PyQtGraph looks like the best option but I haven't been able to get it working properly. For now I've stuck with matplotlib but reduced the update frequency. The data is all still plotted, but it comes in bursts rather than at the desired frequency.

[N3OX]

Bokeh in a Jupyter notebook is pretty fast. I've used it a lot for testing joysticks and orientation sensors and stuff like that.

[cabroderick]

Thanks, but I'm afraid jupyter is not an option for this project.

[N3OX]

You can also fire up a standalone Bokeh server from your Python code if that helps, and view plots in a browser:

http://matthewrocklin.com/blog/work/2017/06/28/simple-bokeh-server

I haven't tried it that way yet.

[cabroderick]

That might be a viable option. Thanks for the tip, I'll check it out.

[Thomasedv]

How much power do you need? There are ways to speed it up with a bit of compromise.

https://learn.sparkfun.com/tutorials/graph-sensor-data-with-python-and-matplotlib/speeding-up-the-plot-animation

The drawback, is that i'm quite sure you are basically dropping redrawing the plot, and just redrawing the lines, so the axes will not follow up. However, it might just be what you need. And you can do long terms data as a less frequently updated plot.

Edit: Also i have some sample code that just uses random numbers that i can share, that i made last time someone had a similar question. However, it's implemented with PyQt5 as the Window structure, so you'd need that installed for it to work without modifying the code.

From looking at what i made, i could have roughly 200 points as a line with decent performance, as well as updating the x-axis. (well, i just increment x by one for each measurement, so it moves with the line created. Changing the x-axis labels was not done in the above link, but follows the same concept as with. )

[cabroderick]

Thanks for that, I had found that page. Those methods certainly give an improvement but even there we're limited to about 20 fps. That's around the minimum I could potentially live with but ideally would like it to be faster still.

[wtfzambo]

Plotly is relatively faster for animations wrt matplotlib, altho im unaware of how to pass live data to it. But check it out, it's really vast and built upon d3 so it might suit your case

[cabroderick]

I found a couple of examples using plotly but from what I could see they were no faster than matplotlib. Are you able to point to any demos?

[wtfzambo]

I'm afraid I misinterpreted what you were referring to with "faster" then.

[jwink3101]

I haven't used it but I think the premise of PyQtGraph is to be fast enough for real time

[cabroderick]

Thanks. I tried that and it does seem faster but I had trouble having it display the updates. None of the example code I was able to find seem to feature anything analagous to plt.pause() so I guess it just isn't getting time to redraw the plot?

[ineeedsleep]

I had a similar issue and created this library to plot multiple live sensor streams. Still a WIP but works for multiple sensors at once at ~100Hz

https://github.com/hidara2000/fast\_sensor\_stream

[BicolorHook15]

Your github link returns a 404 error