The avatar for @makio135
Lionel Radisson
Generative artist, sharing my journey in visual experiments.
Public
Edited
Jan 12, 2024
7 forks
Importers
289 stars
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greys = t => `hsl(0, 0%, ${100 - t * 100}%)`
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rainbow = t => `hsl(${t * 360}, 100%, 50%)`
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d3scales = require("d3-scale-chromatic@1", "d3-interpolate@1")
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ramp(scales.cool)
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ramp(scales.turbo)
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ramp(scales.inferno)
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ramp(scales.warm)
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procScale = (a, b, c, d) => {
const channel = (i, t) => Math.max(Math.min((a[i] + b[i] * Math.cos(Math.PI * 2 * (c[i] * t + d[i]))) * 255, 255), 0) | 0
return t => `rgb(${channel(0, t)}, ${channel(1, t)}, ${channel(2, t)})`
}
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ramp(scales.procA)
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ramp(scales.procB)
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ramp(scales.procC)
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ramp(scales.procD)
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ramp(scales.procE)
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ramp(scales.procF)
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ramp(scales.procG)
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ramp(scales.procH)
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ramp(randomProc())
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ramp(scales.geoffrey)
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imageData = readPixels('https://source.unsplash.com/featured?forest', { w: width, h: width / 2.5 , format: 'hsl', fit: true })
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extractPalette = async uri => {
const palette = await Vibrant.from(uri).getPalette()
return Object.values(palette).map(d => d.rgb.reduce((acc, n) => acc + (n|0).toString(16).padStart(2, '0'), '#'))
}
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paletteFromImage = extractPalette(uri)
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atcq = async (url, maxColors = 12) => {
const imageData = await readPixels(url)
return ATCQ.quantizeSync(imageData.pixels, { maxColors }).map(c => rgbToHex(c.map(d => d | 0)))
}
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paletteFromImage2 = await atcq(uri, 6)
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lerpColor([255, 10, 20], [255, 135, 67], 0.5)
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hexToRgb('#7abdff')
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hexToRgb('#222')
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rgbToHex([255, 10, 51])
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rgbToHsl([255, 10, 51])
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hslToRgb([349.9591836734694, 1, 0.5196078431372549])
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rgbToHsv([255, 10, 51])
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hsvToRgb([349.9591836734694, 0.9607843137254902, 1])
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contrastYiq = ([r,g,b]) => {
const yiq = (r * 299 + g * 587 + b * 114) / 1000;
return yiq >= 128 ? 0x0 : 0xffffff;
}
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contrastYiq([255, 255, 255])
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contrastYiq([200,200,200])
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rgbToGrayscaleAverage = ([r,g,b]) => {
const gray = (r + g + b) / 3 >> 0
return [gray, gray, gray]
}
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rgbToGrayscaleAverage([255,0,0])
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rgbToGrayscaleLuma = ([r,g,b]) => {
const gray = (r * 0.299 + g * 0.587 + b * 0.114) >> 0
return [gray, gray, gray]
}
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rgbToGrayscaleLuma2 = ([r,g,b]) => {
const gray = (r * 0.2126 + g * 0.7152 + b * 0.0722) >> 0
return [gray, gray, gray]
}
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One platform to build and deploy the best data apps

Experiment and prototype by building visualizations in live JavaScript notebooks. Collaborate with your team and decide which concepts to build out.
Use Observable Framework to build data apps locally. Use data loaders to build in any language or library, including Python, SQL, and R.
Seamlessly deploy to Observable. Test before you ship, use automatic deploy-on-commit, and ensure your projects are always up-to-date.
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