The avatar for @visionscarto
Visionscarto
Maps — and other representations of the world.
Public
Edited
Aug 8, 2023
3 forks
39 stars
1
Algorithms
Chandrupatla’s root-finding methodSidi’s root-finding methodRegular numbersDruidJS worker
Natural breaks
Distance to a segmentRay out of a convex hullWord Tour: 40k words and their friendsHello, @thi.ng/grid-iteratorsHead/tail breaksPseudo-blue noise shaderHow fast does walk-on-spheres converge?AoC 12: shortest path under constraintsKDE estimationPlot: Correlation heatmapPoisson Finish 2Poisson disk sampling functionsWoS with transportSimple and surprising sortLocal medianTime series topological subsamplingUnion-FindLevel set experiment 1Mean value coordinatesPoisson potentialMiddle-squareWorld of squares (spherical)World of squaresLargest Inscribed SquareHello, PyWaveletsGeothmetic meandianHello, Reorder.jsGeometric MedianImage FFTTransport to a mapDisc TransportTP3: Power Diagram and Semi-Discrete Optimal TransportThe blue waveHello, genetic-jsSliced Optimal TransportDruidJSSelf-Organizing Maps meet DelaunayHello, polygon-clippingseedrandom, minimalWalk on Spheres 2Walk on SpheresHello, AutoencoderKaprekar’s numberVoronoiMap2DHello, ccwt.jsPolygon TriangulationQuantile.invert?Linear congruential generatorHue blurNeedle in a haystackMoving average blurApollo 11 implementation of trigonometric functions, by Margaret H. Hamilton (march 1969)2D curves intersectionThe 2D approximate Newton-Raphson methodInverting Lee’s Tetrahedral projectionLinde–Buzo–Gray stipplingMean shift clustering with kd-tree2D point distributionsShortest pathKahan SummationHello, delatinDijkstra’s algorithm in gpu.jsLloyd’s relaxation on a graphManhattan DiameterManhattan VoronoiMobility landscapes — an introductionDijkstra’s shortest-path treeH3 odditiesProtein MatrixConvex Spectral WeightsSort stuff by similarityKrigingDelaunay.findTrianglen-dimensions binning?Travelling with a self-organizing mapUMAP-o-MaticMNIST & UMAP-jsHello UMAP-jsMean shift clusteringLevenshtein transitionRd quasi-random sequencesAutomated label placement (countries)Phyllotaxis explainedMotionrugsPlanar hull (Andrew’s monotone chain algorithm)South Africa’s medial axisTravelling salesperson approximation with t-SNEDistance to shoreWorkerngraph: pagerank, louvain…t-SNE VoronoiCloud ContoursCircular function drawingKruskal MazeMyceliumTravelling salesperson approximation on the globe, with t-SNEtsne.jstsne.js & worker
Also listed in…
Clustering
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numbers = {
const k = [
d3.randomNormal.source(d3.randomLcg(40))(2, 0.5),
d3.randomNormal.source(d3.randomLcg(41))(3, 0.3),
d3.randomNormal.source(d3.randomLcg(42))(4, 0.2)
];
return Float64Array.from({ length: 250 }, (_, i) => k[i % 3]());
}
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cuts = simple.jenks(numbers, 3) // note: this implementation returns [min, break1, break2, max]
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roundBreaks = (numbers, k) =>
d3.pairs(simple.ckmeans(numbers, k)).map(([low, hi]) => {
const p = 10 ** Math.floor(1 - Math.log10(hi.at(0) - low.at(-1)));
return Math.floor(((hi.at(0) + low.at(-1)) / 2) * p) / p;
})
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roundBreaks(numbers, 3)
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variances = d3.range(1, 20)
.map((k) => ({
k,
intra_sum_squares: d3.sum(simple.ckmeans(numbers, k), (v) => d3.variance(v))
}))
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elbowiness = (numbers) => {
const intrass = [
{},
...d3
.range(1, 15)
.map((k) =>
k === 1
? d3.variance(numbers)
: d3.sum(simple.ckmeans(numbers, k), (v) => d3.variance(v))
)
];
return d3
.range(0, intrass.length - 1)
.map((k) =>
k < 2
? NaN
: Math.log(intrass[k - 1]) +
Math.log(intrass[k + 1]) -
2 * Math.log(intrass[k])
);
}
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autoK = (numbers) =>
d3.maxIndex(elbowiness(numbers), (score, k) => score / (1 + Math.sqrt(k)))
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autoK(numbers)
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{
const values = new Map(gdp.map((d) => [d.country, d.gdp_per_capita]));
return Plot.plot({
color: {
legend: true,
scheme: "Cool",
type: "threshold",
domain: roundBreaksLog(
gdp.map((d) => d["gdp_per_capita"]),
k_gdp_log
),
width: Math.sqrt(k_gdp_log) * 100,
tickFormat: (d) => d / 1000,
label: "GDP per capita (dollars, thousands)",
unknown: "#ccc"
},
projection: "equal-earth",
marks: [
Plot.geo(
countries,
Plot.centroid({
fill: (d) => values.get(d.properties.a3),
stroke: "white",
title: (d) => `${d.properties.a3}\n${values.get(d.properties.a3)}`,
strokeWidth: 0.5,
tip: true
})
),
Plot.sphere()
]
});
}
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roundBreaksLog = (numbers, k) =>
d3
.pairs(
simple.ckmeans(
numbers.map((d) => Math.log(d)),
k
)
)
.map(([low, hi]) => {
const a = Math.exp(hi.at(0));
const b = Math.exp(low.at(-1));
const p = 10 ** Math.floor(1 - Math.log10(a - b));
return Math.floor(((a + b) / 2) * p) / p;
})
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import { countries } from "@visionscarto/geo"
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breaks = roundBreaksLog(
gdp.map((d) => d["gdp_per_capita"]),
k_gdp_log
)
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simple = require("simple-statistics@7")
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