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cortesi
spacecurve
Rust2013–2021
cortesi / spacecurve

spacecurve

A library for drawing space-filling curves like the Hilbert Curve.

2Distinct people
4Mentions
0Explicit recommenders
530GitHub stars
REPOSITORY AT A GLANCE

What to know before exploring

What it is

A library for drawing space-filling curves like the Hilbert Curve.

GitHub

Where it is used

No documented product use has been verified yet.

What people are saying

No recommendation phrase was found in the indexed comments.

No classified warning is attached to this page. Read the discussions before treating silence as approval.

Also in these discussions

No other repository is repeatedly linked in the same discussions.

This week on Hacker News

Nov 7–Nov 14 UTC · Direct repository links and separately labeled related project stories. Indexed through 11/14/2026, 3:56:07 PM UTC.

No direct repository links were found in the indexed HN discussions over the past seven days. Older discussions are available below.

Mentions over time

HN mentions by year4 dated mentions

Observed mentions: 2013-09-01 21:39:42 UTC to 2021-11-03 04:46:42 UTC.

012013-01-01 00:00:00 UTC to 2014-01-01 00:00:00 UTC (exclusive): 1 mentions; 0 submissions, 1 comments20132014-01-01 00:00:00 UTC to 2015-01-01 00:00:00 UTC (exclusive): 1 mentions; 0 submissions, 1 comments2015-01-01 00:00:00 UTC to 2016-01-01 00:00:00 UTC (exclusive): 0 mentions; 0 submissions, 0 comments2016-01-01 00:00:00 UTC to 2017-01-01 00:00:00 UTC (exclusive): 0 mentions; 0 submissions, 0 comments2017-01-01 00:00:00 UTC to 2018-01-01 00:00:00 UTC (exclusive): 0 mentions; 0 submissions, 0 comments20172018-01-01 00:00:00 UTC to 2019-01-01 00:00:00 UTC (exclusive): 1 mentions; 0 submissions, 1 comments2019-01-01 00:00:00 UTC to 2020-01-01 00:00:00 UTC (exclusive): 0 mentions; 0 submissions, 0 comments2020-01-01 00:00:00 UTC to 2021-01-01 00:00:00 UTC (exclusive): 0 mentions; 0 submissions, 0 comments2021-01-01 00:00:00 UTC to 2022-01-01 00:00:00 UTC (exclusive): 1 mentions; 1 submissions, 0 comments2021

Counts come from the repository’s dated source evidence. Index cutoff: 2026-11-02 08:16:59 UTC.

View mention counts and date ranges
UTC ranges include their start and exclude their end. Select a period to filter the source evidence.
PeriodStart (UTC)End (exclusive, UTC)MentionsSubmissionsComments
20132013-01-01 00:00:00 UTC2014-01-01 00:00:00 UTC101
20142014-01-01 00:00:00 UTC2015-01-01 00:00:00 UTC101
20152015-01-01 00:00:00 UTC2016-01-01 00:00:00 UTC000
20162016-01-01 00:00:00 UTC2017-01-01 00:00:00 UTC000
20172017-01-01 00:00:00 UTC2018-01-01 00:00:00 UTC000
20182018-01-01 00:00:00 UTC2019-01-01 00:00:00 UTC101
20192019-01-01 00:00:00 UTC2020-01-01 00:00:00 UTC000
20202020-01-01 00:00:00 UTC2021-01-01 00:00:00 UTC000
20212021-01-01 00:00:00 UTC2022-01-01 00:00:00 UTC110

What Hacker News says

4 sources
It looks like we've traveled a similar path. The precursor to binvis is scurve, a (slow, dodgy) command-line tool to do basically what dump2png does: https://github.com/cortesi/scurve I have a blazing fast command-line version of binvis in Rust that I plan to release in the next month or so. I really need make some time to turn back to this.
In Netflix FlameScope
Right - these are the frequency dot plots I first saw in Greg Conti's work (some examples here: http://sebug.net/paper/Meeting-Documents/BlackHat-USA2008/BH...). They're definitely on the way. Regarding other space-filling curves - I'm in two minds about this. I've implemented z-order and the H-curve for binvis, but for different reasons neither of these are as useful as the Hilbert curve, so they're not exposed in the interface. My feeling now is that I should pick one locality preserving layout and one intuitive layout to keep things simple and usable. I want binvis to be a workaday tool, so I'm keeping my space-filling curve geekery to another project (https://github.com/cortesi/scurve).
In Visualizing Entropy in Binary Files
I'm somewhat late to the party, but I spent some time playing with procedural colour picking using space-filling curves (the Hilbert curve in particular). I describe the basic technique here: http://corte.si/posts/code/hilbert/portrait/index.html And you can see what this looks like when used to visualize sorting algorithms at large scale here: http://corte.si/posts/code/sortvis-fruitsalad/index.html And here: http://sortvis.org/ I've also published an Open Source project that might be useful to anyone who wants to play with these ideas: https://github.com/cortesi/scurve There are some limitations to the process as described - most obviously the fact that I'm using the RGB color space which is not the best match for human color perception. RGB is convenient because it is a regular cube and therefore easy to map onto the Hilbert curve, but
Read the rest
with a little work the process could be generalized.
In How to Choose Colours Procedurally

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