WaveViz is a CircuitPython class to create a positionable displayio.TileGrid graphics widget from a synthio.waveformwave table or synthio.Envelope object (or any one-dimensional list for that matter). The class also makes the underlying bitmap and palette objects available for other uses such as saving the widget to an image file.

The long-term objective is to be able to save and import sounds and ADSR envelopes from a library of synthio wave table files and envelope objects. The first step in the process is to create a visualizer to help characterize the sounds graphically. We'll worry about saving and retrieving waveform and envelope objects sometime in the future (watch for a new class, WaveStore to appear soon). For now, let's work on getting images of wave tables and envelopes.

Inspiration

This project was born from two desires. One, see if our dog could be taught to use buttons without spending piles of money. Two, to make use of an ancient Raspberry Pi.

Lots of people have done a project like this, and it isn’t necessary to use a Raspberry Pi. That just happened to be the only unused piece of electronics I had on hand with audio output. But, I will say that I definitely recommend this approach for a couple reasons. Firstly, it’s very easy to get running in Python with Adafruit’s Blinka library. Second, it leaves lots of room for growth (both in number of buttons and features like button presses sending digital messages).

Be sure to read all the way to the bottom for a cute puppy photo!

Materials Used

• Raspberry Pi (low cost model A)
  • Gifted by a coworker who was going to throw it out
• 16GB (full size) SD card
  • Came with my 3D printer, but is overkill for that purpose
• Audio cable
  • From a box of junk computer parts
• Audio amplifier
  • Included in a box of junk that got shipped to me
• Speakers
  • From an old CRT TV
• Jumper wires
  • Reused from multiple projects
• Keyboard breakout
  • Hand made from salvaged diodes, jumper headers, perf-board, wires, and solder.  Let's call it 50% recycled.
• 3D printed buttons (and some hotglue)
  • Technically new, but I don't count 3D prints if they displace buying other plastic
• Electronic buttons inside the prints (also a boot button shutdown switch)
  • All salvaged from ewaste or otherwise discarded
• Wooden mounting board
  • Had to buy it from a hobby store

Salvage percentage ~83%!  Hard to give an exact number... do you measure by count?  By volume?  By mass?  By value?  Do you count new tools you had to buy?  Whatever, I'm going to call it 83%.

I'm in a radical marching band called Brass Your Heart, and I wanted to make our instruments light up when we play them. I started this project by making one for my friend who plays a marching baritone. Below is a mostly step by step process for how I made them using: sewable neopixels, conductive thread, snaps, a Gemma M0, and an electret microphone. 

 

 

Step One:

The diameter of the baritone measured 26 inches, so I used tailor's chalk to draw the outer circle you see here. Then I drew another circle, about an inch in for the lights, so that the neopixels and the conductive thread is far away from the metal of the instrument. I also make 8 markings where the neopixels would go and started to sew them into position with regular black thread.

 

I was looking for a clock that would tell the time in words rather than just hands (analog) or numbers (digital). I found a few for sale on places like Amazon and eBay, but none of those particularly stood out, so I decided to create a customizable one myself.

I designed and built two variants. Both use the same RGB matrix panel. Both use CircuitPython on the ESP32-S3, but one uses the Matrix Portal S3, and the other uses a standalone Feather ESP32-S3 with an Adafruit RGB Matrix Featherwing Kit. The Matrix Portal version requires no soldering; the Feather version requires some simple soldering. I will show both here.

The text is left justified, vertically centered on the display and each line is in a random color which changes every time the minute changes. Since you control the CircuitPython code, you can change this formatting any way you choose, e.g. same color lines, individually horizontally centered lines, etc.

Common Hardware

Overview

Welcome to the Adafruit guide on creating a stunning Badger Mountain themed art piece! In this guide, we'll show you how to bring your artistic vision to life using the powerful Feather RP2040 microcontroller, along with an array of components including audio jacks, buttons, and LED strips.

Circuit Diagram

Better SD write performance is probably a common goal. My project uses the Adafruit SD Micro SDIO breakout, the Adafruit OV5640 Camera breakout and the Unexpected Maker ESP32S3 feather in a compact stack (with a custom PCB to connect them) that fits in a GoPro waterproof case. I want GoPro-like video recording but with BLE time synchronization and start/stop functions with multiple cameras. It's like a GoPro but it's not, it's a NoPro!

I'm programming with the Arduino IDE and using the SD_MMC library. The ESP32S3 has an SDIO interface with programmable pins, which the library supports. But for the longest time, I could only get sustainable write speeds of 150-200 kilobytes per second. I'm using a Sandisk Extreme V30 32GB which should get 30MB/s. For the frame rates and resolution I want, I need about 3MB/s.

I initially played with the file system buffer size but never got consistent results. I might occasionally get a few frames written at target speeds but never a whole video. So I set my code aside and started from scratch to explore how to get better speed.

There definitely seemed to be a dependence on file buffer size as well as on the size of data being written. So I tried lots of combinations and got the same results - usually about 150-200 kB/s but occasionally over 3MB/s.

But I had noticed a pattern of good performance when the write lengths were certain powers of 2 so I tried multiples of 512 bytes and got much better speeds. With a file buffer size of 4096 and data sizes over 75kB I could get consistent speed over 3MB/s, just what I need.  4096 also gets consistent small writes at over 1MB/s.  Buffer sizes of 8192 and greater actually worked worse.

How to fail with CircuitPython

 

All code will have errors. You might find it sooner or later, or the error might be in your code, in a library that you are using or even in CircuitPython itself!

It is also very common to write some code on your lab environment, test it a bunch of times, then take it out into the field and watch it fail in lots of ways you would never though of. Exactly the same happens when you give your device to a user or a kid who will test it in ways that will make your coding skills feel silly.

In my case this is happening for a weather station. This should be a simple project, right? Grab some data from a sensor like a Stemma QT thermometer, then send that data to Adafruit.IO and watch it get graphed in a lovely dashboard. Or at least that was my expectation for this project.

As you can see, I started getting missing data for days, and only when I went to the semi-remote location where I am testing my weather station, and manually rebooted the devices, I would get start getting data again. But now the graph is ruined, it has a large gap in the data and to all whom I showed the graphs, the first thing they mentioned is 'what happened to the missing data?'. Now what do I do?

Look at the last hours of the graph. Even if I am missing only a little bit of data, it looks terrible right? You, the reader have no idea how hot it is during the day, how cold it is during the night, or what is the coldest hour. Your eyes go straight to the missing data at the end, with the graphs looking like a shark tooth and being jumpy. What a disaster.

I thought about blaming Adafruit.IO or maybe CircuitPython or maybe it's the fault of the ESP32 that is reading the data. Then I thought about adding extra hardware to it like a TPL5110 power timer but that would require some soldering and would break the wifi workflow that I love so much from CircuitPython 8.

I cloud also get my code full of try and except Python blocks on all of the parts of my code. To be honest, I did tried to do it this way, but things would still keep failing so I kept adding more try/except blocks until the code looked terrible. I was this close to having a project that was not fun for me, and that I would not like to share how it works with this amazing community that makes CircuitPython what it is. Not sharing? That doesn't sound like me at all. Time to do things a different way.

Loving to fail

There is a bit of a hidden gem in CircuitPython and it's the supervisor module. I was only able to find a little bit of technical documentation without a simple example that I could just copy and paste into my project, and I also found another example which was close to what I wanted to do in Tod's CircuitPython tricks.

After staring at the code I had available for a couple of minutes, I realized that this is what I had to do. I needed to let go of my impulse of keep the code failure free, and embrace CircuitPython failing. I would let if fail any time it wanted, and then I would ask it to try again.

With two simple lines, my weather station code can now fail because the wifi router is down, because the Stemma QT cables had a problem with talking to the sensor, because it was running for so long that it was finding errors in the CircuitPython base code or the request library. It doesn't matter, the board will accept that something weird happened, and would try again. Try this in your code and love to fail as much as I do now!

import supervisor

supervisor.set_next_code_file(filename='code.py', reload_on_error=True)

It should not be this simple, right? Here's how it works:

In the first line of code we are calling a library called supervisor. Don't worry, you don't have to install anything, it comes as a standard CircuitPython library and will probably work on any board that you have CircuitPython running on. What it does, is talk to one of the internal parts of CircuitPython and modify how it will behave.

The second like, is the one that changes how it works. It's using a function called set_next_code_file. It's normally used so that you can run the well known code.py file and if something happens, you can define a second file with another name and that code would do something like recover things, blink a light or beep to indicate that it will not behave as it would normally do. I am not calling a second file, instead I'm telling it to go to code.py so that it can try again.

And my favorite part comes with the code that says reload_on_error=True. The way CircuitPython works is that when it fails it will take you to the REPL console, and show you why it failed. This is a good thing as that is the way that we learn, we make mistakes, the REPL shows us what those mistakes are, and we go and fix them.

But for my weather station, once the code was ready and it was doing what I wanted, if there is a failure like the wifi is down, it would go to the console and wait for me to do something. This weather station is located on a dry forest in Costa Rica and it doesn't know that is not next to my computer where it's easy for me to tell it to try again. So what reload_on_error=True tells it to do, is to change what it would have usually do and take me to the console, and instead it will do something similar as if I was close so the board, pushing the RESET button every time something unexpected happens.

This way, CircuitPython will keep on trying over and over until wifi comes back, and hopefully the graphs will have smaller gaps in the data, and they will look much better and should be able to work like a weather station should. Read the thermometer. Send it to Adafruit.IO. Go to sleep to save some battery.

I love you CircuitPython! You and me can fail as many times as we need to, as long as we do it together and without feeling bad. <3.

 

Inspiration

I needed a soldering lamp that didn't cast strong shadows and was an opportunity to salvage the LEDs from a broken TV left by the dumpster.

There are lots of ways to make a good soldering lamp from LEDs.  I happened to pick a difficult path that required some reverse engineering but I hope you'll find the journey... illuminating. ;-)

Awhile back Adafruit featured a story on their blog about a really cool fidget toy built using a rotary encoder and a NeoPixel-compatible LED ring. I loved the idea so much that I wanted to make my own version, and spent a few days designing my own with parts I had on-hand. As it turns out, I wasn't the only one: the Ruiz Brothers built an incredibly stylish take on this idea using an ANO rotary encoder and published an excellent learn guide for it!

While there are physical differences between the two versions, the hardware is similar enough that I wanted to write a CircuitPython firmware that would work their version as well as mine. I wanted the firmware to have multiple modes, with the ability to add more in the future as ideas came to me. Ideally it would be something others could build on as well.

Update: You can see a live demo of the firmware running on the Ruiz brothers' fidget toy in this episode of 3D Hangouts

Basic premise:      Add lights (speed / noise / air-purity indicators, or needless dotstar+neopixel love), use small board to receive tachometer input and drive 24V fan PWM signal from particle sensor, along with new inputs for noise level.   Plus show off Blockly based programming on Adafruit IO, and update as and when the new maths functions become available, but for now write a quick CircuitPython version that illustrates all the desired functionality (to port to Adafruit IO).

Semi-finished code: - Functionally capable but no reactive light use, rainbow:
[Reproduced from https://github.com/tyeth/Ikea_ItsyBitsyEsp32_Air_Purifier/ ]

Just stumbled upon this again over the weekend (I'd seen it before once, but never used it). It's the Randomizer service in Adafruit IO, which offers random words, colours, numbers, or entries from a list. See more here (if you're signed in), and you access the values via MQTT or the HTTP API (instructions on the page).

Anyway, while fantasising about data (specifically how long could my list of values be in randomizer), my mind got caught in rainbow colour sequences, and here we are...

I wanted to insert a long list of items, and thought that's the perfect use for ChatGPT, monotonous lists. It's especially good at understanding simple instructions, although I usually find I need to refine my initial request/prompt.

I asked:

" generate me a rainbow sequence of colours, hash prefixed and comma separated. the sequence should effectively loop if repeated."

It failed to intuit (I never said), that I wanted a long sequence, and instead offered me the 7 colours of the rainbow in a list.

Realising my error, of implicit assumed knowledge, I added an extra phrase to clarify my desire:

"generate me a rainbow sequence of colours, hash prefixed and comma separated. the sequence should effectively loop if repeated. Give me a 100 value transition through the colour spectrum

And there we have it, a nice colour sequence, which I then increased to 256 items. Communication is key, and not easy, or at least it is easy to make grave assumptions and inadvertently mess-up.

100 Items:

Extension Project - Questionably useful things

The last thing to add is that ChatGPT fails in many places/ways, but it's always interesting to test, so I went further and tried to get it to colour-correct the values in the list, based on the human perception of some colours being better than others, along with the issue of RGB lights having different strengths in each colour, then while writing this I also remembered I'd not clarified the rgb issue enough as the individual coloured LEDs are fine at higher brightness's.

What I found most interesting was after the last clarification (but the second query mentioning RGBW LEDs) it offered me colour hex values including a fourth white component, which is actually what I'd originally questioned if I'd wanted all along...

For posterity I've included it all in collapsible sections, so I suggest you collapse them all and use the last one, but read them by all means! My questions/prompts are in bold (title of collapsible), and ChatGPT is the collapsible content:

The arbitrary waveform capability along with ADSR envelopes and filters has made it very easy to create custom musical voices with CircuitPython synthio. And if you use an additive synthesis tool like WaveBuilder, you'll begin to quickly amass quite a few custom musical voices as you experiment with the nearly infinite number of oscillator combinations.

Hearing Voices

Up to this point, I've been keeping track of the numeric specifications for WaveBuilder oscillators and synthio.Envelopes in project code or scribbled on a note pad. That means that when building a new project that needs to use a previously created voice, I'll cut and paste the voice definition code into the new project. The process works, but isn't ideal. What if a synthio musical voice could be loaded from a collection in a file folder, kind of like working with a font file?

So a concept for the WaveStore project began to develop. Here are the initial requirements.

• Library File Management -- We'll make it easy at first and just work with a collection stored on an SD card. No need to tax the brain to conjure up a way to write to the CircuitPython root directory just yet. After creating and storing a voice to a file, we'll manually copy the files from the SD card in order to use and share between projects.
• Files -- In the spirit of keeping it simple, only files representing waveforms and envelopes will be created. Those objects form the fundamental elements of a musical voice. Perhaps we can add filters and other effects later.
• Library File Names -- Waveforms will be stored in a standard wave file with a .wav extension,  thanks to the awesome Adafruit_CircuitPython_Wave library. Envelopes and filters definitions will be stored in plain text files with .adsr and .fltr extensions but will transform to synthio.Envelope and synthio.BiQuad objects when retrieved.
• Icons -- Imagine being able to select a musical voice waveform or envelope by touching a screen icon. Functions will be provided to save and retrieve bitmap images of waveforms and envelopes as well as capturing the contents of an entire screen. We'll start with 64x64 pixel bitmaps created by WaveViz. A graphical frequency response representation of a bi-quad filter's coefficients is in the works but is a bit beyond today's skillset. There's a potential workaround, but I'd rather derive it directly from the numbers. Hoping for an epiphany soon.

In the future, more features will likely be added to WaveStore such as support for filters and on-screen icon buttons -- as my experience and Python skill set grows. What would you add?

Enter WaveStore

WaveStore GitHub repository

WaveStore is under development but is available for testing. The current alpha version of the WaveStore class provides the following helpers:

• Wavetables
  • read_wavetable -- Read a .wav file and return a memory view object.
  • read_wavetable_ulab -- Read a .wav file and return a ulab.numpy array object. The ulab array can be mixed with other wavetable array files.
  • write_wavetable -- Format a wavetable and write it as a standard .wav file.
• Envelopes
  • read_envelope -- Read an .adsr file and return a synthio.Envelope object.
  • write_envelope -- Write a text interpretation of a synthio.Envelope object to an .adsr file.
• Bitmaps
  
  • read_bitmap -- Read a .bmp file and return the bitmap as a TileGrid object that can be added to a displayio.Group object.
  • write_bitmap -- Write a bitmap image to a .bmp file.
  • write_screen -- Write the screen contents to a .bmp file on the SD card.
• Utilities
  • get_catalog -- Returns a list of files in a specified folder.

If you've been playing the awesome new co-op game Helldivers 2, you'll be familiar with the "stratagem" gameplay mechanic in which you summon various weaponry from airborne and satellite craft. This mechanic requires you to hold down a key/button to activate the stratagem input mode, while entering a sequence of directional key input.

Often during the game I tend to get overstimulated in the middle of a heated battle and my mind goes completely blank when trying to recall the one of the myriad codes I need to use to summon the effect I want. Even though the game UI displays them, it's still pretty hectic to precisely enter the sometimes lengthy codes when a giant scorpion is trying to rip my head off. To help spread liberty and democracy in the most efficient way possible, I thought I'd try to see if I could set up some stratagem macros using the awesome MACROPAD Hotkeys project from Phillip Burgess. NOTE: For simplicity, this particular setup mimics keyboard input, so until I hear otherwise I'm assuming this only works on the PC version of Helldivers II.

Custom Code

It took a few tries to figure out how to set up the macros so that the game would consistently accept them. Thankfully, the MACROPAD Hotkeys project is incredibly versatile and I was able to do this using the built-in features of the project without having to modify any of the core code. The main factors involved in getting this to work seemed to be:

1. After pressing the stratagem input button, a significant delay was needed before the game would accept the directional input. I'm assuming this is due to needing to wait for the UI to fully present in-game before allowing further input. With experimentation it seems like the smallest delay possible is about 0.4 seconds.
2. Each directional key needed to be pressed for a certain duration. The smallest duration I've tried for this so far is 0.05 seconds.
3. A small delay is needed after each direction key is released. The smallest duration I've tried for this so far is 0.05 seconds.

In the /macros folder on my macropad CIRCUITPY drive, I created a new file named helldivers-2.py. Since I anticipate changing this file frequently as I progress through the game, I wanted to make it as simple as I could to add/edit new macros, so that I could even edit them in real-time as I played the game. To make this a little easier, I wrote a bit of custom code at the top of the file.

Introduction

The flight simulator industry has spawned dozens of custom controllers for those who are looking for a more realistic and entertaining experience. These controllers range from yolks and throttles to communication and GPS systems and their price can rival the costs of actual aviation equipment.

Thankfully there is a way to create your own controllers using low cost microcontrollers, buttons, encoders and many other input devices. There are even ways to output settings to LEDs, LED segments and displays but this guide does not cover output scenarios.

For this hookup guide I am using a controller I made for myself. The G1000 glass cockpit has a dual-rotary encoder in the lower right corner labeled FMS (Flight Management System) that is a pain to control with a mouse, even more so while the plane is in the air. So I decided to build my own controller to simulate the G1000 corner. My controller includes the FMS encoder knobs and the 6 buttons that tend to be used at the same time.

You can find the source files and STL files I used on GitHub.

The Controller

For my FMS controller I found the PEC11D-4120F-H0015, a dual concentric rotary encoder (meaning it has an inner and outer encoder ring that can turn). This is not the FAA approved version on the actual G1000 but works the same and cheaper. The dual rotary encoder is similar to a single encoder except has two sets of A/B/C pins. The encoder also has a push switch. The push buttons above the encoder are standard push buttons.

The encoder and buttons are wired to a Feather board but almost any board that can run CircuitPython with USB HID enabled will work.