chart = {
const width = 640;
const height = width;
const marginTop = 20;
const marginRight = 40;
const marginBottom = 30;
const marginLeft = 40;
const x = d3.scaleLinear()
.domain([-3, 3]).nice()
.range([marginLeft, width - marginRight]);
const regression = x.domain().map(ss.linearRegressionLine(ss.linearRegression(Array.from(qy, (d, i) => ([z(i), d])))));
const y = d3.scaleLinear()
.domain(regression).nice()
.range([height - marginBottom, marginTop]);
const svg = d3.create("svg")
.attr("viewBox", [0, 0, width, height])
.style("max-width", `${width}px`);
svg.append("g")
.attr("transform", `translate(0,${height - marginBottom + 6})`)
.call(d3.axisBottom(x.copy().interpolate(d3.interpolateRound)))
.call(g => g.select(".domain").remove())
.call(g => g.selectAll(".tick line").clone()
.attr("stroke-opacity", 0.1)
.attr("y1", -height))
.call(g => g.append("text")
.attr("x", width - marginRight)
.attr("y", -3)
.attr("fill", "currentColor")
.attr("font-weight", "bold")
.text("z"));
svg.append("g")
.attr("transform", `translate(${marginLeft - 6},0)`)
.call(d3.axisLeft(y.copy().interpolate(d3.interpolateRound)))
.call(g => g.select(".domain").remove())
.call(g => g.selectAll(".tick line").clone()
.attr("stroke-opacity", 0.1)
.attr("x1", width))
.call(g => g.select(".tick:last-of-type text").clone()
.attr("x", 3)
.attr("text-anchor", "start")
.attr("font-weight", "bold")
.text("Strength"));
svg.append("line")
.attr("stroke", "currentColor")
.attr("stroke-opacity", 0.3)
.attr("x1", x.range()[0])
.attr("x2", x.range()[1])
.attr("y1", y(regression[0]))
.attr("y2", y(regression[1]));
svg.append("g")
.attr("fill", "none")
.attr("stroke", "steelblue")
.attr("stroke-width", 1.5)
.selectAll("circle")
.data(d3.range(n))
.join("circle")
.attr("cx", i => x(z(i)))
.attr("cy", i => y(qy[i]))
.attr("r", 3);
return svg.node();
}
qy = Float64Array.from(data).sort()
n = qy.length
z = i => qnorm((i + a) / (n + 1 - 2 * a))
a = n <= 10 ? 5 / 8 : 0.5
qnorm = p => Math.SQRT2 * erfinv(2 * p - 1)
erfinv = {
const a = 8 * (Math.PI - 3) / (3 * Math.PI * (4 - Math.PI));
return x => {
const b = Math.log(1 - x * x);
const c = b / 2 + (2 / (Math.PI * a));
return Math.sign(x) * Math.sqrt(Math.sqrt((c * c) - b / a) - c);
};
}
data = FileAttachment("JAHANMI2.DAT")
.text()
.then((text) =>
text.split("\r\n")
.slice(50, -1)
.map((l) => +l.trim().split(/\s+/g)[4])
)
ss = require("simple-statistics@7")
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.
