<?xml version="1.0" encoding="utf-8" standalone="yes"?><rss version="2.0" xmlns:atom="http://www.w3.org/2005/Atom" xmlns:content="http://purl.org/rss/1.0/modules/content/"><channel><title>Vispy on Hojae Lee</title><link>https://hojaeklee.github.io/tags/vispy/</link><description>Recent content in Vispy on Hojae Lee</description><generator>Hugo -- 0.160.1</generator><language>en</language><lastBuildDate>Fri, 25 Sep 2026 00:00:00 +0000</lastBuildDate><atom:link href="https://hojaeklee.github.io/tags/vispy/index.xml" rel="self" type="application/rss+xml"/><item><title>Playing with VisPy</title><link>https://hojaeklee.github.io/til/vispy/20260925_playing_with_vispy/</link><pubDate>Fri, 25 Sep 2026 00:00:00 +0000</pubDate><guid>https://hojaeklee.github.io/til/vispy/20260925_playing_with_vispy/</guid><description>&lt;p&gt;I somehow came across this beautiful visualization of &lt;a href="https://blog.shashanktomar.com/posts/strange-attractors" target="_blank" rel="noopener noreferrer"&gt;strange attractors&lt;/a&gt;
written in Three.js. Then I remembered &lt;a href="https://vispy.org/index.html" target="_blank" rel="noopener noreferrer"&gt;VisPy&lt;/a&gt;
, a scientific visualization package in Python that I heard of in context of &lt;a href="https://vedo.embl.es/" target="_blank" rel="noopener noreferrer"&gt;Vedo&lt;/a&gt;
. We use Vedo for visualization at the &lt;a href="https://thousandbrains.org/" target="_blank" rel="noopener noreferrer"&gt;Thousand Brains Project&lt;/a&gt;
, so I decided to poke around the VisPy API and write some code without using LLM.&lt;sup id="fnref:1"&gt;&lt;a href="#fn:1" class="footnote-ref" role="doc-noteref"&gt;1&lt;/a&gt;&lt;/sup&gt;&lt;/p&gt;</description></item></channel></rss>