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Dynamic scales deprive dashboards of institutional memory
latencyData = {
const today = new Date();
const data = [];
const dist1 = d3.randomNormal(200, 20);
const dist2 = d3.randomNormal(300, 30);
for (let i = -60; i < 0; i++) {
data.push({
date: d3.timeDay.offset(today, i),
value: (i < -30 ? dist1 : dist2)()
});
}
return data;
}
exponentialData = {
const rand = d3.randomNormal(0.1, 0.1);
const data = [{time: new Date(1989, 9, 19, 4, 30), value: 2}];
for (let i = 0; i < 1000; i++) {
const {time: t0, value: v0} = data.at(-1);
data.push({
time: d3.timeDay.offset(t0, 1),
value: v0 + (v0 * rand())
});
}
return data;
}
exponentialDataSlices = {
const randLen = d3.randomUniform(10, exponentialData.length);
return d3.range(9).map(() => exponentialData.slice(0, Math.floor(randLen())))
}
maxObservedExponential = d3.max(exponentialDataSlices.flatMap(d => d.map(d => d.value)))
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