pcaTable = {
const { data: feature1 } = predict,
{ n } = data;
const table = [];
for (let i = 0; i < n; ++i) {
table.push({
f1: feature1[i][0],
f2: feature1[i][1],
f3: feature1[i][2],
signal: i
});
}
return table;
}
predict = pca.predict(distanceMatrix)
pca = new PCA(distanceMatrix, { center: true, scale: true })
PCA = (await require("https://bundle.run/ml-pca@4.0.2")).PCA
distanceTable = {
const mat = distanceMatrix,
{ T, n } = data,
distanceTable = [];
for (let i = 0; i < n; ++i) {
for (let j = 0; j < n; ++j) {
distanceTable.push({ i, j, v: mat[i][j] });
}
}
return distanceTable;
}
distanceMatrix = {
const matrix = matrixBrownianBridge,
{ T, n } = data,
distance = [];
for (let i = 0; i < n; ++i) {
const array = [...new Array(n).fill(0)];
for (let j = i; j < n; ++j) {
for (let t = 0; t < T; ++t) {
array[j] += (matrix[t][i] - matrix[t][j]) ** 2;
}
}
distance.push(array);
}
for (let i = 0; i < n; ++i) {
for (let j = i; j < n; ++j) {
distance[i][j] = Math.sqrt(distance[i][j]) / T;
distance[j][i] = distance[i][j];
}
}
return distance;
}
matrixBrownianBridge = table2matrix("brownianBridge")
table2matrix = (column = "brownianBridge") => {
const { T, n } = data;
const matrix = [];
for (let t = 0; t < T; ++t) {
matrix.push([...new Array(n).fill(0)]);
}
data.map((d) => {
matrix[d.time][d.signal] = d[column];
});
return matrix;
}
data = mkData(dataSetup.length, dataSetup.signals)
rndEngine = d3.randomNormal()
rndEngine1 = d3.randomBernoulli(0.5) //d3.randomUniform()
rnd = () => {
// return rndEngine1() * 2 - 1;
return rndEngine();
}
/**
* Make data for T length and n signals.
**/
mkData = (T, n) => {
const data = [];
var x,
xT = [],
b,
invT = 1.0 / T;
for (let i = 0; i < n; ++i) {
x = 0;
for (let t = 0; t < T; ++t) {
data.push({
signal: i,
time: t,
brownian: x,
brownianAccumulate: x + (i > 0 ? d3.sum(xT.slice(0, i)) : 0)
});
if (t === T - 1) {
xT.push(x);
} else {
x += rnd();
}
}
}
data.map((d) => {
b = d.brownian - (d.time + 1) * invT * xT[d.signal];
Object.assign(d, { brownianBridge: b });
});
Object.assign(data, { T, n });
return data;
}
d3 = require("d3")
import { toc } from "@nebrius/indented-toc"
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.
