By: Simon Danisch
GLVisualize is a package written in pure Julia, which can create 2D/3D visualizations and GUIs. It’s GPU accelerated and can thus easily handle large datasets and complex 2D/3D scenes. At its core it’s a visualization library heavily using Reactive signals allowing the user to animate and interact with the graphics. I recently wrote a backend for Plots which is a great general purpose plotting library. As a result you can have much of the standard plotting functionality known from libraries such as Matplotlib with GLVisualize + Plots.jl.
Just install it and try it out! I’ve collected some videos, which should give a good overview about what’s possible:
Creating a library like GLVisualize completely from scratch is pretty involved. So I’ve been asking myself why go through all this trouble when there are wonderful alternatives to GLVisualize. Why not concentrate on one existing package?
First of all, some of the established libraries don’t really hold up to what I would call a fast, modern and easy to extend library.
More modern libraries seem to be mostly written for the web. It’s great, but sometimes one really wants a library that works well on the desktop, is not written in JS, and plays well with other desktop APIs (e.g. GPGPU). But I see the beauty of sharing things online, so I do want to break with my `all Julia` approach and write a web backend for GLVisualize as soon as possible!
GUIs are another important aspect to look at. I’ve seen a lot of frameworks using third party GUI libraries which is a very reasonable way to go! But I’ve some use cases in mind which need the graphics rendering to seamlessly integrate with the GUI library. E.g. creating a point cloud where every point is a button. Or draw a line plot which acts as the control for a complex parameter space. I already needed to create quite a few complex 3D UI elements which wouldn’t be possible in most GUI libraries. So at the end of the day putting time into an API for interactive widgets makes a lot of sense.
Another piece of motivation is that in the long run Julia will need some native graphic tools for several reasons. It’s impossible to write one plotting library solving everyone’s needs, so people will start to create their own visualization tools. Having no graphics libraries to build upon will mean throwing these users into the cold water or make them change the language. The livelier Julia’s own (GPU accelerated) Graphics ecosystem, the higher the probability that you can create great, novel visualizations and get insights into your data. GLVisualize can be the starting point, and we as a community have full control over the features and use cases!
Finally, I still haven’t seen another language bringing together speed, scientific computing and easy usage as beautifully as Julia. These are all elements crucial to any visualization library, so GLVisualize is at a very good place with Julia!
This is the first version of GLVisualize where I feel comfortable to recommend it to the public! I’ve been working on fixing bugs, backend issues and adding most crucial features for general plotting. As you saw in the video, it now contains a large collection of widgets and many visualization types to chose from. Please note that I haven’t optimized GLVisualize much yet. This means GLVisualize should only get faster from here on! But it also means that there are a couple of bottlenecks. I sketched out a road map to remove them and to improve latency/performance in general. Depending on the use case, you can expect speed improvements by an order of magnitude. One such use case is animations with Plots.jl, which is quite slow right now. For every frame it completely tears down GLVisualize’s state and rebuilds it, which is not what I’ve optimized for yet. So even though that GLVisualize might offer the fastest animation speeds of all backends, animations done with Plots.jl can be slow due to this bad interaction. There are a couple of other things which I collected in one meta issue.
Please report bugs and feedback swiftly