Published
Edited
Nov 22, 2019
6 stars
Insert cell
Insert cell
{
const context = DOM.context2d(imagedata.width, imagedata.height / 2);
const img1 = rainbowify(imagedata, context, 1);
context.putImageData(img1, 0, 0);
const img2 = rainbowify(imagedata, context, 2);
context.putImageData(img2, imagedata.width, 0);
yield context.canvas;
}
Insert cell
function rainbowify(input, context, mode) {
const output = context.createImageData(input.width, input.height);

for (let i = 0; i < input.data.length; i += 4) {
const oldPixel = [
input.data[i + 0],
input.data[i + 1],
input.data[i + 2],
input.data[i + 3]
];
const nextPixel = findClosestPaletteColor(oldPixel, mode);
output.data[i + 0] = nextPixel[0];
output.data[i + 1] = nextPixel[1];
output.data[i + 2] = nextPixel[2];
output.data[i + 3] = nextPixel[3];
}

return output;
}
Insert cell
function findClosestPaletteColor([r, g, b, a], mode) {
// "length" of color vec
const l = Math.hypot(r, g, b);
// maximal distance use to normalize
const m = Math.hypot(255, 255, 255);

let rgbString;
if (mode === 1) {
rgbString = d3.interpolateTurbo(l / m);
} else {
rgbString = d3.interpolateRainbow(l / m);
}
// const rgbString = d3.interpolateSinebow(l / m);

// rgb string to components array
const [nextR, nextG, nextB] = rgbString
.replace(/rgb\(|/, '')
.split(',')
.map(n => parseInt(n));

return [nextR, nextG, nextB, 255];
}
Insert cell
imagedata = imagedataFromImg(image)
Insert cell
function ix(i, j) {
return (j * imagedata.width + i) * 4;
}
Insert cell
function imagedataFromImg(img) {
const canvas = document.createElement('canvas');
canvas.width = img.width;
canvas.height = img.height;
const context = canvas.getContext('2d');
context.drawImage(img, 0, 0, img.width, img.height);
return context.getImageData(0, 0, img.width, img.height);
}
Insert cell
Insert cell
Insert cell
d3 = require( "d3-scale-chromatic@1")
Insert cell

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.
Learn more