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const getDataRanges = (extremes) => {
var ranges = [];
for (var dimension in extremes) {
ranges[dimension] = extremes[dimension].max - extremes[dimension].min;
}
return ranges;
}
const getDataExtremes = (data)=> {
var extremes = [];
for (var i in data) {
var point = data[i];
for (var dimension in point) {
if (!extremes[dimension]) {
extremes[dimension] = { min: 1000, max: 0 };
}
if (point[dimension] < extremes[dimension].min) {
extremes[dimension].min = point[dimension];
}
if (point[dimension] > extremes[dimension].max) {
extremes[dimension].max = point[dimension];
}
}
}
return extremes;
}
const initMeans = (k, dataExtremes, dataRange) => {
if (!k) {
k = 3;
}
const means = [];
while (k--) {
var mean = [];
for (var dimension in dataExtremes) {
mean[dimension] = dataExtremes[dimension].min + Math.random() * dataRange[dimension];
}
means.push(mean);
}
return means;
}
const makeAssignments = (means, data) => {
const assignments = {};
for (var i in data) {
var point = data[i];
var distances = [];
for (var j in means) {
var mean = means[j];
var sum = 0;
for (var dimension in point) {
var difference = point[dimension] - mean[dimension];
difference *= difference;
sum += difference;
}
distances[j] = Math.sqrt(sum);
}
assignments[i] = distances.indexOf(Math.min.apply(null, distances));
}
return assignments;
}
const setup = (data) => {
const dataExtremes = getDataExtremes(data);
const dataRange = getDataRanges(dataExtremes);
const means = initMeans(3, dataExtremes, dataRange);
return makeAssignments(means, data);
}
export default setup;