Here’s a topic for workbench computer associated with your instruments / equipment and how it applies to electronics, not so much about the PC/mac itself. Let me know if this is a duplicate and I missed it.
Using software to control instruments for ad hoc measurements isn’t very valuable to me, however, for running tests over time it’s highly valuable.
PC
Intel NUC BOXNUC8i7BEH1 (new, fresh start with a smaller footprint)
Asus MG28UQ 28" monitor
Windows 10 Home
Office 365 Home (Excel for charting, PowerPoint for documentation)
Instrument software
Keysight Benchvue 2018 Update 2
Rigol Ultrascope and Ultapower
Siglent EasyDMM
Altium Circuitmaker
KiCad (now that I’ve joined CE)
I’ve tried using Keithley Kickstart but ran into some VISA issues given the other apps installed. Ultimately, the software for the 2281S is less important than what I get out of Benchvue.
I’d love to hear from someone using NI tools compared to Keysight. I’m really happy with Benchvue and will post some results of how I use it for my projects in my build log(s). I think though that LabVIEW handles IVI drivers better based on some testing I did on my previous PC.
It’d be interesting also to see how people feel about Altium CircuitMaker versus KiCad as well. Does one produce better Gerber files or have better component libraries or provide a better community?
Often in plotting the underlying data changes. It is best to use something that can take advantage of it and concentrate on underlying data instead of re-plotting the same things all the time in Excel. You can do some serious plotting and analysis with Python + Matplotlib. It is relatively simple to learn. From my own experience – I read a python tutorial (a funny language) and after 4 hours was plotting GPS receiver performance histograms from live data. Later it was much easier. A good investment, serious power-tool. You can do same in Matlab and R.
(Disclaimer: I used to use Excel heavily for this before)
I exclusively use Python for this, specifically using the Anaconda 3.x package which includes many useful data analysis and plotting tool. I especially like to use Jupyter Notebooks to organize code and do inline plotting… highly recommend.
Interesting, I didn’t know that Azure had that service. That is really cool.
With the Anaconda package I really like running it locally but to each their own.
I have a PC with 64GB of ram and the fastest i7 I could buy, very nice to never worry about using too much ram or being processor limited.
The nice thing about running locally is that you can develop scripts to talk with locally connected hardware. For example last week I was using the hid library to read and write data to a mcu project I was working on.
Definitely advantages to having a cloud accessible notebook too!
The Azure node is limited to 4GB RAM Python instance. This for 99% of my stuff is way more than sufficient. Interesting here is that it works twice as fast as my i7 laptop and little bit faster than my 8-core Xeon desktops when benchmarked. And always has better internet connection, if this matters.
