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delayProbabilities = { // derive onset to confirmed delay probabilities from a histogram of delays
let sum = 0;
for (let d of delays) sum += d;
return delays.map(d => d / sum);
}
confirmedDaily = confirmedTotal.map((v, i, arr) => v - (arr[i - 1] || 0)) // daily numbers from totals
onset = {
// convolve confirmed daily case counts with onset delay probabilities
const onset = convolve(confirmedDaily, delayProbabilities.slice().reverse());
// adjust for right-censoring
for (let i = 0, p = 0; i < delayProbabilities.length; i++) {
p += delayProbabilities[i];
onset[onset.length - 1 - i] /= p;
}
// round and align with data for confirmed cases
return onset.slice(delays.length - 1).map(Math.round);
}
convolve = (volume, kernel) => { // equivalent of numpy.convolve in the "full" mode
const out = [];
for (let i = 0; i < volume.length; i++) {
for (let j = 0; j < kernel.length; j++) {
out[i + j] = (out[i + j] || 0) + volume[i] * kernel[j];
}
}
return out;
}
formatDate = d => d.toLocaleDateString('en-US', {month: 'long', day: 'numeric', year: 'numeric'})
uPlot = (await import('https://unpkg.com/uplot@1.0.8/dist/uPlot.esm.js')).default
html`<link rel='stylesheet' href='https://unpkg.com/uplot@1.0.8/dist/uPlot.min.css' />`
html`<style>
.uplot tr { border: none; }
.uplot .legend { line-height: 1.2; }
.uplot .legend .series > * { padding: 0; }
.uplot .legend .series > th { padding-right: 5px; }
.uplot .over { cursor: crosshair; }
</style>`
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