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What property makes the Hilbert curve desirable compared to, say, a snake pattern, with which neighbouring ISBNs are also neighbours in the visualisation? The

by n2d4 2y ago

What property makes the Hilbert curve desirable compared to, say, a snake pattern, with which neighbouring ISBNs are also neighbours in the visualisation? The worry I have with Hilbert curves is that they make the result look like there are distinct "squares" of data [0] when really this is just an artifact of how Hilbert curves work. In that sense, the current visualization is more useful, because it's straightforward to identify the location of each country in it. [0] https://raw.githubusercontent.com/jakubcerveny/gilbert/master/img/55x31.png https://raw.githubusercontent.com/jakubcerveny/gilbert/maste...

NooneAtAll3 2y ago
> What property makes the Hilbert curve desirable compared to, say, a snake pattern, with which neighbouring ISBNs are also neighbours in the visualisation? 2D neighbourhood is better than 1D one > The worry I have with Hilbert curves is that they make the result look like there are distinct "squares" of data that's the point, tho? instead of distinct lines of taken ISBNs in a row, you get distinct squares if taken ISBNs in a row - much more noticeable
graypegg 2y ago
In a snake pattern, the neighbouring pixels on the left and right are related, but the ones above and below have skipped a whole row. And yeah that’s true! you end up with squares with Hilbert curves. But those squares are all « related » data. Then those squares are related to the squares near it. Zoom out more and that grouping of squares is related to the neighbouring macro-squares etc etc. Basically the square shape is a positive. Kind of like how charting the derivative lets you see how random/related information is, grouping into these squares gives you a visualization of pattern-ness, rather than any specific measurement.
- n2d4 2y ago
  > In a snake pattern, the neighbouring pixels on the left and right are related, but the ones above and below have skipped a whole row. But this is also true in Hilbert curves across the boundaries of the "squares" that I mentioned. The two center pixels in the top row are much more distant than any two pixels would be in a snake pattern.

by n2d4 2y ago

NooneAtAll3 2y ago

> What property makes the Hilbert curve desirable compared to, say, a snake pattern, with which neighbouring ISBNs are also neighbours in the visualisation? 2D neighbourhood is better than 1D one > The worry I have with Hilbert curves is that they make the result look like there are distinct "squares" of data that's the point, tho? instead of distinct lines of taken ISBNs in a row, you get distinct squares if taken ISBNs in a row - much more noticeable

graypegg 2y ago

In a snake pattern, the neighbouring pixels on the left and right are related, but the ones above and below have skipped a whole row. And yeah that’s true! you end up with squares with Hilbert curves. But those squares are all « related » data. Then those squares are related to the squares near it. Zoom out more and that grouping of squares is related to the neighbouring macro-squares etc etc. Basically the square shape is a positive. Kind of like how charting the derivative lets you see how random/related information is, grouping into these squares gives you a visualization of pattern-ness, rather than any specific measurement.

n2d4 2y ago
> In a snake pattern, the neighbouring pixels on the left and right are related, but the ones above and below have skipped a whole row. But this is also true in Hilbert curves across the boundaries of the "squares" that I mentioned. The two center pixels in the top row are much more distant than any two pixels would be in a snake pattern.