31:T933,{ replay; const context = DOM.context2d(width, height); context.translate(-50, -40); context.scale(1.5, 1.5); context.font = `15px Georgia, serif`; context.shadowColor = "rgba(0, 0, 0, 0.4)"; context.shadowOffsetX = 1.5; context.shadowOffsetY = 1.5; context.shadowBlur = 2; context.fillText(`${deck}`, 50, 55); context.font = `${headline_size}px Georgia, serif`; context.shadowColor = "rgba(0, 0, 0, 0.4)"; context.shadowOffsetX = 3; context.shadowOffsetY = 3; context.shadowBlur = 4; context.fillText(`${headline}`, 50, 102); context.shadowOffsetX = 0; context.shadowOffsetY = 0; context.shadowColor = "rgba(0,0,0,0)"; context.shadowBlur = 0; context.fillStyle = "rgba(0, 0, 0, 0.02)"; context.fillRect(0,0, width, height); context.globalCompositeOperation = "darken"; context.beginPath(); delaunay.render(context); context.strokeStyle = "rgba(204,204,204,0.5)"; context.stroke(); context.fillStyle = "rgba(0, 0, 0, 0)"; context.strokeStyle = "lightgray"; yield context.canvas; context.fillStyle = "rgba(255,84,67, 0.45)"; context.strokeStyle = "rgba(255,84,67, 0.45)"; yield visibility(context.canvas); for (let i = 0, n = delaunay.triangles.length / 3; i < n; ++i) { let cx = voronoi.circumcenters[i * 2]; let cy = voronoi.circumcenters[i * 2 + 1]; let x0 = delaunay.points[delaunay.triangles[i * 3] * 2]; let y0 = delaunay.points[delaunay.triangles[i * 3] * 2 + 1]; let r = Math.sqrt((cx - x0) ** 2 + (cy - y0) ** 2); context.beginPath(); context.moveTo(cx + r, cy); context.arc(cx, cy, r, 0, 2 * Math.PI); context.stroke(); context.beginPath(); context.moveTo(cx + 2, cy); context.arc(cx, cy, 2, 0, 6 * Math.PI); context.fill(); yield context.canvas; } // context.strokeStyle = "rgba(255,84,67, 0.45)"; // yield visibility(context.canvas); // for (let i = 0, n = delaunay.halfedges.length; i < n; ++i) { // let j = delaunay.halfedges[i]; // if (i < j) continue; // let vi = Math.floor(i / 3) * 2; // let vj = Math.floor(j / 3) * 2; // context.beginPath(); // context.moveTo(voronoi.circumcenters[vi], voronoi.circumcenters[vi + 1]); // context.lineTo(voronoi.circumcenters[vj], voronoi.circumcenters[vj + 1]); // context.stroke(); // yield context.canvas; // } }32:T872,function* poissonDiscSampler(x0, y0, x1, y1, radius) { const k = 30; // maximum number of samples before rejection const width = x1 - x0; const height = y1 - y0; const radius2 = radius * radius; const radius2_3 = 3 * radius2; const cellSize = radius * Math.SQRT1_2; const gridWidth = Math.ceil(width / cellSize); const gridHeight = Math.ceil(height / cellSize); const grid = new Array(gridWidth * gridHeight); const queue = []; // Pick the first sample. yield sample(width / 2 + Math.random() * radius, height / 2 + Math.random() * radius); // Pick a random existing sample from the queue. pick: while (queue.length) { const i = Math.random() * queue.length | 0; const parent = queue[i]; // Make a new candidate between [radius, 2 * radius] from the existing sample. for (let j = 0; j < k; ++j) { const a = 2 * Math.PI * Math.random(); const r = Math.sqrt(Math.random() * radius2_3 + radius2); const x = parent[0] + r * Math.cos(a); const y = parent[1] + r * Math.sin(a); // Accept candidates that are inside the allowed extent // and farther than 2 * radius to all existing samples. if (0 <= x && x < width && 0 <= y && y < height && far(x, y)) { yield sample(x, y); continue pick; } } // If none of k candidates were accepted, remove it from the queue. const r = queue.pop(); if (i < queue.length) queue[i] = r; } function far(x, y) { const i = x / cellSize | 0; const j = y / cellSize | 0; const i0 = Math.max(i - 2, 0); const j0 = Math.max(j - 2, 0); const i1 = Math.min(i + 3, gridWidth); const j1 = Math.min(j + 3, gridHeight); for (let j = j0; j < j1; ++j) { const o = j * gridWidth; for (let i = i0; i < i1; ++i) { const s = grid[o + i]; if (s) { const dx = s[0] - x; const dy = s[1] - y; if (dx * dx + dy * dy < radius2) return false; } } } return true; } function sample(x, y, parent) { queue.push(grid[gridWidth * (y / cellSize | 0) + (x / cellSize | 0)] = [x, y]); return [x + x0, y + y0]; } }33:[] 2f:{"title":"Delaunay headline hero","cells":[{"id":0,"value":"md`# Delaunay headline hero\n\nThis modification of [Mike Bostock's Delaunay Dual](https://beta.observablehq.com/@mbostock/the-delaunays-dual) diagram was drafted for consideration as lead art on a gallery of data analysis pieces [published by the Los Angeles Times in 2018](https://beta.observablehq.com/@palewire/hexbin-headline-hero). It was ultimately discarded in favor of a similar design using [hexagonal binning](https://beta.observablehq.com/@palewire/hexbin-headline-hero).\n`","pinned":false,"hidden":false,"mode":"ojs"},{"id":8,"value":"$31","pinned":false,"hidden":false,"mode":"ojs"},{"id":377,"value":"md`### Configuration`","pinned":false,"hidden":false,"mode":"ojs"},{"id":252,"value":"viewof replay = html`