Published
Edited
Jun 3, 2020
md`# Gauss prices`
html`<svg viewBox="0 0 ${width} ${height}">
<path d="${line(prices)}" fill="none" stroke="steelblue" stroke-width="1.5" stroke-miterlimit="1"></path>
${d3.select(svg`<g>`).call(xAxis).node()}
${d3.select(svg`<g>`).call(yAxis).node()}
</svg>`
x = d3.scaleLinear()
.domain([0, prices.length - 1])
.range([margin.left, width - margin.right])
xAxis = g => g
.attr("transform", `translate(0,${height - margin.bottom})`)
.call(d3.axisBottom(x).ticks(width / 80).tickSizeOuter(0))
line(prices)
line = d3.line()
.x((_, i) => x(i))
.y(y)
y = d3.scaleLinear()
.domain([0, d3.max(prices)])
.range([height - margin.bottom, margin.top])
prices = {
let p = 50
return Array.from(Array(1000), () => p += gauss(0, 1))
}
gauss = {
const { EPSILON: epsilon } = Number
const { random, sqrt, PI: pi, log, sin, cos } = Math
const tau = pi * 2
let flip = false
let z1 = 0
/** @returns normally distributed random number(s) with `mean` and `standardDeviation`. */
const randomOfNormalDistribution /*: (mean?: number, standardDeviation?: number) => number */ =
(mean = 0, standardDeviation = 1) => {
if (!(flip = !flip)) {
return (z1 * standardDeviation) + mean
}
let u1
do {
u1 = random()
} while (u1 <= epsilon)
const u2 = random()
const z0 = sqrt(-2.0 * log(u1)) * cos(tau * u2)
z1 = sqrt(-2.0 * log(u1)) * sin(tau * u2)
return (z0 * standardDeviation) + mean
}
return randomOfNormalDistribution
}
yAxis = g => g
.attr("transform", `translate(${margin.left},0)`)
.call(d3.axisLeft(y).ticks(height / 40))
.call(g => g.select(".domain").remove())
height = 240
margin = ({top: 20, right: 30, bottom: 30, left: 40})
d3 = require("d3@5")
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