31:T437,This notebook contains a JavaScript translation of algorithm I wrote earlier this year for the `beeswarm` R package. (In the end, it was not used in that package.) The values are initially divided by the required radius so that two circles overlap if and only if the distance between them is less than 1. The algorithm uses sorting in both x and y directions to avoid checking for overlaps with circles that are more than a horizontal or vertical distance of 1 away. This should make it very fast for large datasets. Although I'm sharing this code in case it might be useful to someone, this isn't my favourite type of visualisation for a one-dimensional dataset, in part because it often creates distracting artifacts such as a "wind-blown" appearance. I prefer [raincloud plots](https://observablehq.com/@spren9er/raincloud-plots-with-observable-plot), [unit histograms](https://www.flerlagetwins.com/2020/11/beeswarm.html), [dot plots](https://observablehq.com/@uwdata/dot-plots), and [compact beeswarms](https://observablehq.com/@jtrim-ons/compact-beeswarm-plot#cell-441).32:T8ac,function beeswarm( data, { radius = 1, x = (d) => d, side = 1, sort = true } = {} ) { const circles = data .map((d, i, data) => ({ x: +x(d, i, data) / radius, // divide by radius to simplify calculations data: d, y: 0, priority: i })) .sort((a, b) => a.x - b.x); let n = data.length; let order = []; for (let i = 0; i < n; i++) { if (sort) circles[i].priority = i; order[circles[i].priority] = i; } for (let iter = 0; iter < n; iter++) { let i = order[iter]; let nearby_circles = []; let start = i; while (start > 0 && circles[start - 1].x > circles[i].x - 1) --start; for (let j = start; j < n; j++) { if (circles[j].priority >= iter) continue; // skip unplaced points if (circles[j].x >= circles[i].x + 1) break; let x_diff = circles[i].x - circles[j].x; let dx_sq = x_diff * x_diff; nearby_circles.push({ y: circles[j].y, priority: circles[j].priority, forbiddenYBottom: circles[j].y - Math.sqrt(1 - dx_sq), forbiddenYTop: circles[j].y + Math.sqrt(1 - dx_sq) }); } nearby_circles.sort((a, b) => a.y - b.y); if (is_y_feasible(0, nearby_circles, 0, nearby_circles.length)) { circles[i].y = 0; } else { let yAbs = Infinity; let sides = side === 0 ? [1, -1] : side === 1 ? [1] : [-1]; for (let s of sides) { let p = s === 1 ? n : -1; // priority of the existing point from which circles[i].y was computed for (let j = 0; j < nearby_circles.length; j++) { let poty = s == -1 ? nearby_circles[j].forbiddenYBottom : nearby_circles[j].forbiddenYTop; let potyAbs = Math.abs(poty); let is_improvement = potyAbs <= yAbs && (potyAbs < yAbs || nearby_circles[j].priority < p); if (is_improvement && can_use_poty(j, poty, nearby_circles)) { circles[i].y = poty; yAbs = Math.abs(poty); p = nearby_circles[j].priority; } } } } } var result = circles.map(({ x, y, data }) => ({ x: x * radius, y: y * radius, data })); return result; }33:[{"id":"53c407ee531bab128477148c9e28c49dd06bf83a93ae317e58dbb9fc819db0d4f6c4fb9646fa2fe20faad76addee20cfc360eab2362eeaec3340a5e4655b9996","href":"https://static.observableusercontent.com/files/53c407ee531bab128477148c9e28c49dd06bf83a93ae317e58dbb9fc819db0d4f6c4fb9646fa2fe20faad76addee20cfc360eab2362eeaec3340a5e4655b9996","name":"cars-2.csv","type":"application/octet-stream","lastModified":1632860519718.491,"size":20140}] 2f:{"title":"Fast Beeswarm","cells":[{"id":1,"value":"md`# Fast Beeswarm`","pinned":false,"hidden":false,"mode":"ojs"},{"id":290,"value":"$31","pinned":false,"hidden":false,"mode":"md"},{"id":280,"value":"viewof side = Inputs.range([-1, 1], { step: 1, value: 1, label: \"Side\" })","pinned":false,"hidden":false,"mode":"ojs"},{"id":283,"value":"viewof sort = Inputs.toggle({ label: \"Sort\", value: true })","pinned":false,"hidden":false,"mode":"ojs"},{"id":7,"value":"chart = {\n const svg = d3.create(\"svg\").attr(\"viewBox\", [0, 0, width, height]);\n\n svg.append(\"g\").call(xAxis);\n\n const h = height - margin.bottom - radius - padding;\n\n svg\n .append(\"g\")\n .selectAll(\"circle\")\n .data(\n beeswarm(data, {\n radius: radius * 2 + padding,\n x: (d) => x(d.value),\n sort: sort,\n side: side\n })\n )\n .join(\"circle\")\n .attr(\"cx\", (d) => d.x)\n .attr(\"cy\", (d) => (h * side) / 2 + h / 2 - d.y)\n .attr(\"r\", radius)\n .append(\"title\")\n .text((d) => d.data.name);\n\n return svg.node();\n}","pinned":true,"hidden":false,"mode":"ojs"},{"id":275,"value":"function is_y_feasible(poty, nearby_circles, start_idx, end_idx) {\n for (let i = start_idx; i < end_idx; i++) {\n let { forbiddenYBottom, forbiddenYTop } = nearby_circles[i];\n if (poty > forbiddenYBottom && poty < forbiddenYTop) return false;\n }\n return true;\n}","pinned":true,"hidden":false,"mode":"ojs"},{"id":277,"value":"function can_use_poty(j, poty, nearby_circles) {\n // For speed, only check circles that are within a y distance of 1 from the potential y value `poty`\n let start = j;\n while (start > 0 && nearby_circles[start - 1].y > poty - 1) --start;\n let end = j;\n while (end < nearby_circles.length && nearby_circles[end].y < poty + 1) ++end;\n return is_y_feasible(poty, nearby_circles, start, end);\n}","pinned":true,"hidden":false,"mode":"ojs"},{"id":195,"value":"$32","pinned":true,"hidden":false,"mode":"ojs"},{"id":3,"value":"data = (await FileAttachment(\"cars-2.csv\").csv({typed: true})).map(({Name: name, Weight_in_lbs: value}) => ({name, value: +value}))","pinned":true,"hidden":false,"mode":"ojs"},{"id":77,"value":"x = d3.scaleLinear()\n .domain(d3.extent(data, d => d.value))\n .range([margin.left, width - margin.right])","pinned":true,"hidden":false,"mode":"ojs"},{"id":108,"value":"xAxis = g => g\n .attr(\"transform\", `translate(0,${height - margin.bottom})`)\n .call(d3.axisBottom(x).tickSizeOuter(0))","pinned":true,"hidden":false,"mode":"ojs"},{"id":32,"value":"height = 240","pinned":true,"hidden":false,"mode":"ojs"},{"id":206,"value":"radius = 3","pinned":true,"hidden":false,"mode":"ojs"},{"id":208,"value":"padding = 1.5","pinned":true,"hidden":false,"mode":"ojs"},{"id":102,"value":"margin = ({top: 20, right: 20, bottom: 30, left: 20})","pinned":true,"hidden":false,"mode":"ojs"}],"files":"$W33","stdlib":"1","titling":"auto"}