s2geometry
0.30000000000000004
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s2geometry | 0.30000000000000004 | |
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26 | 245 | |
2,181 | 1,398 | |
2.5% | - | |
5.8 | 2.0 | |
26 days ago | 29 days ago | |
C++ | CSS | |
Apache License 2.0 | GNU General Public License v3.0 only |
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s2geometry
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Hexagons and Hilbert Curves – The Horrors of Distributed Spatial Indices
I experimented with geospatial Hilbert Curves as a Postgres extension [0] for PostGIS using the S2 [1] spherical geometry library. S2 uses a scale free cell coverage pattern that is numbered using six interlocking space filling Hilbert Curves [2].
By having both high level (cell) and low level (cell id) geometries it was a very powerful library which allowed projection from the hilbert space into a Postgres spatial index (spgist) including various trees, like noted in this article. It appears to be still quite active in development.
[0] https://github.com/michelp/pgs2
[1] https://s2geometry.io/
[2] https://s2geometry.io/devguide/s2cell_hierarchy
- Show HN: TG – Fast geometry library in C
- Unum: Vector Search engine in a single file
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Understanding Geohashes
If you check the h3geo comparison page, you should see plenty of alternatives to geohash, such as s2 or even h3 itself.
- Evaluation of Location Encoding Systems
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Inscribed angle theorem in 3D/higher dimension
See some discussion I started at https://github.com/google/s2geometry/issues/190
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An Interactive Explanation of Quadtrees
> It was quite hard for me to find open-source implementations of linear quadtrees.
You probably know this, but the S2 library has one: https://github.com/google/s2geometry
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Why doesn’t my pokèstop show up?
https://s2geometry.io shows how this works
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Needing advice to improve geodesic calculation time
If your points are distributed globally, however, I'd suggest using something like s2geometry (calculates over a sphere instead of an ellipsoid which is much faster + already has something called S2ClosestPointQuery).
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What is the best data structure for this problem?
Some alternative solutions are S2 from Google and H3 from Uber. These don't have the same issues as geohash because they work on a 3-d model of the geoid and not a 2-d cylindrical projection like Geohash.
0.30000000000000004
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What even is a JSON number?
https://0.30000000000000004.com/
Although it would be good to move in the direction of using a BigDecimal equivalent by default when ingesting unknown data.
- Floating Point Math
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Working with Numpy floats and Forex financial instruments
There's no such thing as precision for floats. Floating-point calculations are always inaccurate: read this: https://0.30000000000000004.com/
- Just learned the difference between decimal and float
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how do i make the decimals not fucked up
Edit: This specific example even has its own website: https://0.30000000000000004.com/
- why doest this loop ever terminate?
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Decoding Why 0.6 + 0.3 = 0.8999999999999999 in JS and How to Solve?
In everyday math, we know adding 0.6 + 0.3 equals 0.9, right? But when we turn to computers it results in 0.8999999999999999. Surprisingly, this doesn’t just happen only in JavaScript; it’s the same in many programming languages like Python, Java, C too. Also, it’s not just about this specific calculation. There are many more decimal calculations showing similar not-quite-right answers.
- Lies My Calculator and Computer Told Me [pdf]
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64-Bit Bank Balances ‘Ought to Be Enough for Anybody’?
Surprisingly common values like 0.1 don't have a precise representation in binary for most formats, including standard floating point number formats. See https://0.30000000000000004.com/ for more detail than you can shake a stick at.
Also if the local tax code states using 5 decimal places for intermediate values when you will introduce “errors” using formats that give greater precision as well as those that give less precision. Having work on mortgage and pension calculations I can state that the (very) small errors seen at individual steps because of this can balloon significantly through repeated calculations.
Furthmore, the name floating point gives away the other issue. Floating point numbers are accurate to a given number of significant figures not decimal places. For large numbers any decimal places you have in the result are at best an estimate, and as above any rounding errors at each stage can compound into a much larger error by the end of a calculation.
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I don't get these people
You'll love this https://0.30000000000000004.com/
What are some alternatives?
h3 - Hexagonal hierarchical geospatial indexing system
glibc - Unofficial mirror of sourceware glibc repository. Updated daily.
S2 geometry - S2 geometry library in Go
gcc
s2 - Node.js JavaScript / TypeScript bindings for Google S2
v8.dev - The source code of v8.dev, the official website of the V8 project.
Kyrix - Interactive details-on-demand data visualizations at scale
proposal-decimal - Built-in decimal datatype in JavaScript
sled - the champagne of beta embedded databases
import-maps - How to control the behavior of JavaScript imports
protoc-gen-star - protoc plugin library for efficient proto-based code generation
media