thresholdView = slider({
min: 0.2,
max: 1,
value: 0.3,
step: 0.1,
description: md`Neighbourhood Threshold`,
})
eigs = mathjs.eigs(laplacian)
eigs.values
numberOfClusters = eigs.values.filter(e => e <= eigValueThreshold).length
clusterAssignment = {
const clusterAssignment = Array.from({ length: data.length }).map(u => 0)
for (let i = 1; i < numberOfClusters; i++) {
const ev = mathjs.transpose(eigs.vectors)[i]
const embedding = mathjs.multiply(normalizedMatrix, ev)
embedding.forEach((magnitude, j) => {
if(magnitude > 0) {
clusterAssignment[j] = i
}
})
}
return clusterAssignment
}
showConnectionsView = Inputs.toggle({label: "Show Connections", value: true})
showClusterLabelView = Inputs.toggle({label: md`Show Clusters`, value: true})
dataMax = Math.ceil(mathjs.max(mathjs.abs(data)))
mathjs = require('https://unpkg.com/mathjs@6.6.0/dist/math.min.js')
import {dataset_swiss_roll} from "@heytitle/stein-variational-gradient-descent"
import {slider} from "@jashkenas/inputs"
Purpose-built for displays of data
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.
