Published
Edited
Jun 21, 2020
1 fork
1 star
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side = 1000 // Change here the size of the visualization (it's a square).
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backgroundDotsNumber = 2500 // Change here the number of dots randomly positioned in the background.
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opacity = 0.8 // Change here the opacity of circles.
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red = "#FF5555" // This is IXT red.
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pathToSample = `<path d="M554,500 C460.663877,500 385,424.336123 385,331 C385,237.663877 460.663877,162 554,162 C647.336123,162 723,237.663877 723,331 C723,424.336123 647.336123,500 554,500 Z M276.5,493 L276.5,169.962788 L276.5,493 Z"></path>`
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M = 400 // Change here the number of points along the path to sample: the more dots, the denser it will look!
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shape = svg`<svg style="width:${side}px; height:${side}px; display: block;" viewBox="0 0 ${side} ${side}">
${pathToSample}
</svg>`

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path = shape.querySelector("path")
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// from https://observablehq.com/@mbostock/fourier-series-path-sampling
linearSamples = {
const L = path.getTotalLength();
return Array.from({length: M}, (_, i) => {
const {x, y} = path.getPointAtLength(i / M * L);
return [x, y];
});
}
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html`<svg style="width:${side}px; height:${side}px; display: block;" viewBox="0 0 ${side} ${side}">
${linearSamples.map(([x, y]) => svg`<circle cx=${x} cy=${y} r=1>`)}
</svg>`
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width = side
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height = side
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margin = ({top: 0, right: 0, bottom: 0, left: 0})
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small = 2
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medium = 3
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big = 4
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x = d3.scaleLinear()
.domain(d3.extent(data, d => d.x))
.range([margin.left, width - margin.right])
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y = d3.scaleLinear()
.domain(d3.extent(data, d => d.y))
.range([margin.top,height - margin.bottom])
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data = Array.from({length: backgroundDotsNumber}, () => ({x:Math.floor(Math.random() * side), y:Math.floor(Math.random() * side)}));

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import {slider} from "@jashkenas/inputs"
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import {color} from "@jashkenas/inputs"
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d3 = require("d3@5")
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Observable is your go-to platform for exploring data and creating expressive data visualizations. Use reactive JavaScript notebooks for prototyping and a collaborative canvas for visual data exploration and dashboard creation.
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