Jason Davies, a developer and data visualization specialist, builds interactive D3.js demos of maps, curves, algorithms and math patterns.
HN links it for interactive demos like animated Bézier curves and map projections, which commenters describe as excellent work.
This is a truly impressive implementation, based on previous work by Jonathan Feinberg [1]. The display uses SVG, but the character outlines are computed by canvas bitmaps. Then, Jason implemented hierarchical bounding boxes to accelerate the intersection checks. Be sure to play with the draggable "0" and "1" letters beneath the demo!
Try clicking on words to navigate between word clouds. The cross-fade transition is beautiful, and words that overlap between clouds transform in their new position.
Non-English word clouds look amazing, too:
http://www.jasondavies.com/wordcloud/#http%3A%2F%2Fsearch.twitter.com%2Fsearch.json%3Frpp%3D100%26q%3D%7Bword%7D@%D8%B3%D9%88%D8%B1%D9%8A%D8%A9%E2%80%8E
[1] http://static.mrfeinberg.com/bv_ch03.pdf
Many of you will be well aware that you can't have a distance-preserving "map", that is a projection from the globe to a segment to of the plane where the length of an arbitrary path is preserved. Hence you can't measure real-world distances using string and a paper map.
That said you can preserve distance in special cases, for example any two chosen points. For example you can go to https://www.jasondavies.com/maps/two-point-equidistant/ and put your points at the Suez Canal and the Cape of Good Hope. While that still won't let you measure wiggly ship routes along the coast, it does a better job than Mercator.
Failing that you can use Gall-Peters which does a better job of conveying the vastness of Africa, since it's area preserving.
Perfect timing, just learning how to make a map in d3 for Bower stats [1]. Thought after experimenting with choropleth maps [2], bubbles on maps and dorling maps [3] [4], dorling maps appear to be the best way to show very dense info on relationships with vague references to geography.
[1] https://shan.io/bower/
[2] http://bl.ocks.org/mbostock/4060606
[3] http://www.dannydorling.org/wp-content/files/dannydorling_publication_id0120.pdf
[4] http://www.jasondavies.com/maps/dorling-world/
In my opinion all maps of single airplane routes should be shown with a two-point equidistant projection. This clearly shows the straight line between the start and end as the shortest direction, and minimizes distortion along that line. Additionally, all points on the map have accurate distances from either point, and deviations from the geodesic (such as for administrative or weather related reasons) are easily seen.
https://www.jasondavies.com/maps/two-point-equidistant/
It's common to want some minimum spacing between your random points, so they don't get clumped together, i.e. approximating uniform spacing rather than uniform probability distribution. For that, Poisson-disk sampling is good. See e.g. https://www.jasondavies.com/maps/random-points/, https://www.cs.ubc.ca/~rbridson/docs/bridson-siggraph07-poissondisk.pdf, https://www.jasondavies.com/poisson-disc/.
It's really cool that Poisson disc sampling is used to generate the points. Here, best-candidate sampling is used, based on [1]. But have you considered using the possibly faster Bridson's algorithm [2]?
Using Harris corners to analyze the picture is a cool idea too. Good job!
[1] http://bl.ocks.org/mbostock/b17e0b2aa8b2d50de465
[2] https://www.jasondavies.com/poisson-disc/