PlainDAQ - DAQ Module for Raspberry Pi Pico

I was advised to manually handle garbage collection to make it faster and smoother in eevblog forum.
The problem is that the term garbage collection is pretty foreign to me.

As it turns out by using garbage collection optimally we can overcome much of the "Hiccups" that we saw in the previous log's stress test.

I guess I start learning about garbage collecton concept soon, but right now I'll just develop the GUI with python handling the garbage collection maybe later I go into it.

Kudos to Berni the super contributor in eevblog:

eevblog link: https://www.eevblog.com/forum/crowd-funded-projects/plaindaq-open-source-daq-module-for-raspberry-pi-pico/

Before I start developing GUI for PlainDAQ, I wanted to see how far I can push matplotlib

It can run at 60 FPS if you push it to its limits, which is more than I need.
There are occasional hiccups, but I think it's fine.

Here is the code if you're curious:

https://github.com/AlperenAkkuncu/PlainDAQ/blob/main/Development/GUI/sinewave_stress_test.py

The graph is embedded in tkinter because I am thinking about developing the GUI with tkinter and matplotlib.

I've been searching for better looking terminals, and I've found 3 different terminals with colors. They are shown below.

I'm not sure which one to pick really, but once I get my hands on them I'll be sharing photos of PlainDAQ with each one to get some feedback, stay tuned!

PlainDAQ needs transfer lots of data and it's gotta do it fast. 

I wanted to test how fast I can tranfer data via USB. I used two raspberry pi pico's one of them doing the debugging and the other is doing the actual work. 

Ultimately I am going to need to transfer 6MBit/s of data from pico to computer (12-bit 500ksps ADC = 6Mbits/s)

The Test Setup

Pico on the lower side of the picture is debugging and the other is the DUT (device under test)

USB Speed Test

The USB is in bulk transfer mode. I don't really know much inner workings of the USB protocol, but it allows me to send 64 bytes at a time, and therefore I needed be clever about transferring 1000s of 64 bytes packages. 

I imported the the example code provided in raspberry pi's github page and modified it in a way that I can receive multiple packages easily. To do that I erased every print statement (they are SLOW!) and implemented a counter to keep track of number of packages sent.

You can check my code here. I also included the python file to work with it as well.

And finally, here are the results:

I can reach up to more than 7Mbits/s. The speed depends on your setup as well. For example, if you use a hub it's slower.

That's it for this update!