If your only exposure to seismologists at work is through film and television, you can be forgiven for thinking they still lay out rolls of paper to examine lines of ink under a magnifying glass. The reality is far more interesting in a field that has eagerly adopted all available technology. A dramatic demonstration of modern earthquake data gathering, processing, and visualization was Tweeted by @IRIS_EPO following a central California quake on July 4th, 2019. In this video can see the quake’s energy propagate across the continental United States in multiple waves of varying speed and intensity. The video is embedded below, but click through to the Twitter thread too as it has a lot more explanation.
The acronym IRIS EPO expands out to Incorporated Research Institutions for Seismology, Education and Public Outreach. We agree with their publicity mission; more people need to know how cool modern seismology is. By combining information from thousands of seismometers, we could see forces that we could not see from any individual location. IRIS makes seismic data available to researchers (or curious data science hackers) in a vast historical database or a real time data stream. Data compilations are presented in several different forms, this particular video is a GMV or Ground Motion Visualization. Significant events like the 4th of July earthquake get their own GMV page where we can see additional details, like the fact this visualization compiled data from 2,132 stations.
If you need help visualizing magnetic fields, these slow-motion video captures should educate or captivate you. Flux lines are difficult to describe in words, because magnet shape and strength play a part. It might thus be difficult to visualize what is happening with a conical magnet, for a person used to a bar magnet. We should advise you before you watch the video below the break, if you are repelled by the sight of magnetite sand clogging a bare magnet then flying on the floor, this is your only warning.
The technique and equipment are simple and shown in the video. A layer of black sand is spread on a piece of tense plastic to make something like a dirty trampoline, and a neodymium magnet is dropped in the middle. The bouncing action launches the sand and magnet simultaneously so they are hanging in the air and the particles can move with little more than air resistance.
These videos were all taken with a single camera and a single magnet. Multiple cameras would yield 3D visuals, and the intertwining fields of multiple magnets can be beautiful. Perhaps a helix of spherical magnets? What do you have lying around the hosue? In a twist, we can use magnets to simulate gas atoms and trick them into performing unusual feats.
In a previous post, I showed how you could upload images into a Discord server from Python; leveraging the popular chat platform to simplify things like remote monitoring and push notifications on mobile devices. As an example, I showed an automatically generated image containing the statistics for my Battlefield 1 platoon which gets pushed to member’s devices on a weekly basis.
The generation of that image was outside the scope of the original post, but I think it’s a technique worth discussing on its own. After all, they say that a picture is worth 1000 words. So that means a picture that actually contains words must be worth way more. Like, at least 2000, easy.
Being able to create images from your textual data can lend a bit of flair to your projects without the need to create an entire graphical user interface. By putting a text overlay on a pre-rendered image, you can pull off some very slick visuals with a minimum amount of system resources. So long as you have a way of displaying an image file, you’re good to go.
In this post I’ll quickly demonstrate how to load an image, overlay it with text, and then save the resulting image to a new file. This technique is ideal in situations where a display doesn’t need to be updated in real-time; visuals can be generated at regular intervals and simply displayed as static images. Possible uses include weather displays, “magic” mirrors, public signage, etc. Continue reading “Making Pictures Worth 1000 Words In Python”→
I’ve got virtual circuits on the mind lately. There are a myriad of tools out there that I could pick up to satisfy this compulsion. But the one I’m reaching for is Minecraft. I know what you’re thinking… a lot of people think Minecraft is getting long in the tooth. But chances are you never tried some of the really incredible things Minecraft can do when it comes to understanding logic structures. This goes way beyond simple circuits and easily hops back and forth over the divide between hardware logic and software logic.
Finding a product that is everything you want isn’t always possible. Making your own that checks off all those boxes can be. [Peter Clough] took the latter route and built a small Bluetooth speaker with an LED visualization display that he calls Magic Box.
A beefy 20W, 4Ohm speaker was screwed to the lid of a wooden box converted to the purpose. [Clough] cut a clear plastic sheet to the dimensions of the box, notching it 2cm from the edge to glue what would become the sound reactive neopixel strip into place — made possible by an electret microphone amplifier. There ended up being plenty of room inside the speaker box to cram an Arduino Pro Mini 3.3V, the RN-52 Bluetooth receiver, and the rest of the components, with an aux cable running out the base of the speaker. As a neat touch, neodymium magnets hold the lid closed.
People like music, but they are also visual creatures. Perhaps that’s why music visualization is such a common project. Usually, you think of music visualization as using LEDs or a computer screen. However, [Gieeel] did his music visualization using a 3D printer.
Sure, the visualization is a little static compared to LEDs, but it does make an interesting conversation piece. The actual process isn’t very difficult, once you have the idea. [Gieeel] captured the waveform in Audacity, did a screen capture, and then converts the image to an SVG file using Inkscape.
From there, you can use many different CAD tools to convert the image into a 3D object. [Gieeel] used Autodesk Fusion 360 and had the resulting object professionally 3D printed.
Last week we saw a lot of interest in faux visualization of wireless signals. It used a tablet as an interface device to show you what the wireless signals around you looked like and was kind of impressive if you squinted your eyes and didn’t think too much about it. But for me it was disappointing because I know it is actually possible to see what radio waves look like. In this post I will show you how to actually do it by modifying a coffee can radar which you can build at home.
The late great Prof. David Staelin from MIT once told me once that, ‘if you make a new instrument and point it at nature you will learn something new.’ Of all the things I’ve pointed Coffee Can Radars at, one of the most interesting thus far is the direct measurement and visualization of 2.4 GHz radiation which is in use in our WiFi, cordless phones (if you still have one) and many other consumer goods. There is no need to fool yourself with fake visualizations when you can do it for real.