2b:null 2c:["$","title",null,{"children":"Moving average blur (stackblur approach) | Fil | Observable"}] 31:Tae6,// used to demonstrate the various intermediate steps of blur2 in the "profile" above blur3 = { const { floor, max, min, round } = Math; function show() { return arguments[+what_to_show]; } function blurTransfer(V, r, n, vertical) { if (!r) return; // radius 0 is a noop const [source, target] = V, m = floor(source.length / n), w = (r << 1) + 1, w2 = (r << 2) + 1, ki = vertical ? m : 1, kj = vertical ? 1 : n, W = w * ki, R = r * ki, R2 = R * 2, blocks = 1 / (r * r * w); for (let j = 0; j < m; ++j) { const k0 = kj * j, kn = k0 + ki * (n - 1); let k, kd; for ( let i = 0, sr0, sr1 = w * source[k0], sr2 = w2 * source[k0], dr = 0, dr2 = source[k0]; i < n + 2 * r; ++i ) { // I believe this is equivalent to the stackblur approach: // sr0: central value at x // sr1: running sum on the interval [x - r, x + r] // sr2: running sum on the interval [x - 2r, x + 2r] // dr: integral of sr2 - 2 sr1 + sr0 // dr2: integral of dr k = ki * i + kj * j; sr0 = source[(kd = max(k - R2, k0))]; sr1 += source[min(max(k - R, k0), kn)] - source[max(k - R - W, k0)]; sr2 += source[min(k, kn)] - source[max(k - W - R2, k0)]; target[kd] = show(sr0, sr1, sr2, sr2 - 2 * sr1 + sr0, dr, dr2); dr += (sr2 - 2 * sr1 + sr0) * blocks; dr2 += dr; } } V.reverse(); // target becomes V[0] and will be used as source in the next iteration } return function blur() { var radius = 7, accessor, width, iterations = 1, direction = null; function blur(data) { const n = width || data.length, m = floor(data.length / n), V = [ accessor ? Float32Array.from(data, accessor) : Float32Array.from(data), new Float32Array(data.length) ]; for (var i = 0; i < iterations; i++) { if (direction !== "y" && n > 1) { blurTransfer(V, radius, n, false); } if (direction !== "x" && m > 1) { blurTransfer(V, radius, m, true); } } V[0].width = n; V[0].height = m; return V[0]; } blur.radius = _ => _ === undefined ? radius : ((radius = round(+_)), blur); blur.width = _ => (_ === undefined ? width : ((width = round(+_)), blur)); blur.iterations = _ => _ === undefined ? iterations : ((iterations = +_), blur); blur.direction = _ => _ === undefined ? direction : ((direction = _), blur); blur.value = _ => typeof _ === "function" ? ((accessor = _), blur) : accessor; return blur; }; }32:Ta24,blur2 = { const { floor, max, min, round } = Math; function blurTransfer(V, r, n, vertical) { if (!r) return; // radius 0 is a noop const [source, target] = V, m = floor(source.length / n), w = (r << 1) + 1, w2 = (r << 2) + 1, ki = vertical ? m : 1, kj = vertical ? 1 : n, W = w * ki, R = r * ki, R2 = R * 2, blocks = 1 / (r * r * w); for (let j = 0; j < m; ++j) { const k0 = kj * j, kn = k0 + ki * (n - 1); let k, kd; for ( let i = 0, sr0, sr1 = w * source[k0], sr2 = w2 * source[k0], dr = 0, dr2 = source[k0]; i < n + 2 * r; ++i ) { // I believe this is equivalent to the stackblur approach: // sr0: central value at x // sr1: running sum on the interval [x - r, x + r] // sr2: running sum on the interval [x - 2r, x + 2r] // dr: integral of sr2 - 2 sr1 + sr0 // dr2: integral of dr k = ki * i + kj * j; sr0 = source[(kd = max(k - R2, k0))]; sr1 += source[min(max(k - R, k0), kn)] - source[max(k - R - W, k0)]; sr2 += source[min(k, kn)] - source[max(k - W - R2, k0)]; target[kd] = dr2; dr += (sr2 - 2 * sr1 + sr0) * blocks; dr2 += dr; } } V.reverse(); // target becomes V[0] and will be used as source in the next iteration } return function blur() { var radius = 7, accessor, width, iterations = 1, direction = null; function blur(data) { const n = width || data.length, m = floor(data.length / n), V = [ accessor ? Float32Array.from(data, accessor) : Float32Array.from(data), new Float32Array(data.length) ]; for (var i = 0; i < iterations; i++) { if (direction !== "y" && n > 1) { blurTransfer(V, radius, n, false); } if (direction !== "x" && m > 1) { blurTransfer(V, radius, m, true); } } V[0].width = n; V[0].height = m; return V[0]; } blur.radius = _ => _ === undefined ? radius : ((radius = round(+_)), blur); blur.width = _ => (_ === undefined ? width : ((width = round(+_)), blur)); blur.iterations = _ => _ === undefined ? iterations : ((iterations = +_), blur); blur.direction = _ => _ === undefined ? direction : ((direction = _), blur); blur.value = _ => typeof _ === "function" ? ((accessor = _), blur) : accessor; return blur; }; }33:T749,blur = { const { floor, max, min, round } = Math; function blurTransfer(V, r, n, vertical) { const [source, target] = V, m = floor(source.length / n), w = (r << 1) + 1, w1 = 1 / w, ki = vertical ? m : 1, kj = vertical ? 1 : n, W = w * ki, R = r * ki; for (let j = 0; j < m; ++j) { const k0 = kj * j, kn = k0 + ki * (n - 1); for (let i = 0, sr = w * source[k0]; i < n + r; ++i) { const k = ki * i + kj * j; sr += source[min(k, kn)] - source[max(k - W, k0)]; target[max(k - R, k0)] = sr * w1; } } V.reverse(); // target becomes V[0] and will be used as source in the next iteration } return function blur() { var radius = 5, accessor, width, iterations = 3, direction = null; function blur(data) { const n = width || data.length, m = floor(data.length / n), V = [ accessor ? Float32Array.from(data, accessor) : Float32Array.from(data), new Float32Array(data.length) ]; for (var i = 0; i < iterations; i++) { if (direction !== "y" && n > 1) { blurTransfer(V, radius, n, false); } if (direction !== "x" && m > 1) { blurTransfer(V, radius, m, true); } } V[0].width = n; V[0].height = m; return V[0]; } blur.radius = _ => _ === undefined ? radius : ((radius = round(+_)), blur); blur.width = _ => (_ === undefined ? width : ((width = round(+_)), blur)); blur.iterations = _ => _ === undefined ? iterations : ((iterations = +_), blur); blur.direction = _ => _ === undefined ? direction : ((direction = _), blur); blur.value = _ => typeof _ === "function" ? ((accessor = _), blur) : accessor; return blur; }; }34:T89e,// original code from D3 mmblur1 = { function blurX(source, target, r) { var n = source.width, m = source.height, w = (r << 1) + 1; for (var j = 0; j < m; ++j) { for (var i = 0, sr = 0; i < n + r; ++i) { if (i < n) { sr += source.data[i + j * n]; } if (i >= r) { if (i >= w) { sr -= source.data[i - w + j * n]; } target.data[i - r + j * n] = sr / Math.min(i + 1, n - 1 + w - i, w); } } } } // TODO Optimize edge cases. // TODO Optimize index calculation. // TODO Optimize arguments. function blurY(source, target, r) { var n = source.width, m = source.height, w = (r << 1) + 1; for (var i = 0; i < n; ++i) { for (var j = 0, sr = 0; j < m + r; ++j) { if (j < m) { sr += source.data[i + j * n]; } if (j >= r) { if (j >= w) { sr -= source.data[i + (j - w) * n]; } target.data[i + (j - r) * n] = sr / Math.min(j + 1, m - 1 + w - j, w); } } } } return function blur(source, r, n) { if (n === undefined) n = source.length; const m = source.length / n; var values0 = Float32Array.from(source), values1 = new Float32Array(n * m); blurX( { width: n, height: m, data: values0 }, { width: n, height: m, data: values1 }, r ); blurY( { width: n, height: m, data: values1 }, { width: n, height: m, data: values0 }, r ); blurX( { width: n, height: m, data: values0 }, { width: n, height: m, data: values1 }, r ); blurY( { width: n, height: m, data: values1 }, { width: n, height: m, data: values0 }, r ); blurX( { width: n, height: m, data: values0 }, { width: n, height: m, data: values1 }, r ); blurY( { width: n, height: m, data: values1 }, { width: n, height: m, data: values0 }, r ); return Object.assign(values0, { width: n, height: m }); }; // this is the true function in d3 /* function blur(source, r) { const k = 2; return blur(source, r >> k); }; */ }35:[] 2f:{"id":"63ded3c5ba9dcd1f","slug":null,"title":"Moving average blur (stackblur approach)","thumbnail":"96e65ddda4485edc7bf08d66646514dd8cda862c7f14d225207e4fea77982414","access_level":"unlisted","create_time":"$D2020-06-13T14:04:44.716Z","update_time":"$D2020-06-19T14:30:45.923Z","view_time":null,"first_public_time":null,"has_unpublished_edits":null,"fork":{"id":"6b810e3f43ae255e","slug":"moving-average-blur","title":"Moving average blur","owner":{"id":"da2a32154638c457","login":"fil","name":"Fil"}},"stars":1,"starred":false,"owner":{"type":"team","id":"da2a32154638c457","login":"fil","name":"Fil","avatar_url":"https://avatars-next.observableusercontent.com/d5b1777907117a2bdf2a07eb98600d7a9beb21639fde42b9753e95c88c7731a6","tier":"starter_2024"},"version":1572,"publish_version":1572,"role":null,"authored":false,"authors":[{"type":"individual","id":"45a379fcfcb14253","login":"fil","name":"Fil","avatar_url":"https://avatars-next.observableusercontent.com/d5b1777907117a2bdf2a07eb98600d7a9beb21639fde42b9753e95c88c7731a6","tier":null}],"members":[{"type":"individual","id":"45a379fcfcb14253","login":"fil","name":"Fil","avatar_url":"https://avatars-next.observableusercontent.com/d5b1777907117a2bdf2a07eb98600d7a9beb21639fde42b9753e95c88c7731a6","tier":null,"role":"editor"}],"comments":[],"custom_thumbnail":false,"trashed":false,"lapsed":null,"subscribed":null,"forks":0,"collection":null,"type":"notebook","body":{"title":"Moving average blur (stackblur approach)","cells":[{"id":0,"value":"md`# Moving average blur (stackblur approach)\n\n_Note: the new new code is quite a bit more complex but with proper explanations it could be useable. And it's about 30% faster._`","pinned":false,"hidden":false,"mode":"ojs","author":"$undefined","summary":"$undefined","output":"$undefined","database":"$undefined"},{"id":2,"value":"md`To compute its [density contours](https://github.com/d3/d3-contour/blob/master/README.md#contourDensity), D3 uses a moving-average [blur](https://github.com/d3/d3-contour/blob/master/src/blur.js), which alternates blurring rows then columns, [3 times each](https://github.com/d3/d3-contour/blob/master/src/density.js#L46). Let’s try and see if we can use it for flat data (1D), and speed it up a bit.`","pinned":false,"hidden":false,"mode":"ojs","author":"$undefined","summary":"$undefined","output":"$undefined","database":"$undefined"},{"id":736,"value":"md`First, the source is a flat array representing numerical values in a rectangle width × height. In our case width = ${n} and height = ${m}.`","pinned":false,"hidden":false,"mode":"ojs","author":"$undefined","summary":"$undefined","output":"$undefined","database":"$undefined"},{"id":741,"value":"n = 400","pinned":false,"hidden":false,"mode":"ojs","author":"$undefined","summary":"$undefined","output":"$undefined","database":"$undefined"},{"id":742,"value":"m = 300","pinned":false,"hidden":false,"mode":"ojs","author":"$undefined","summary":"$undefined","output":"$undefined","database":"$undefined"},{"id":71,"value":"source = Float32Array.from({ length: n * m }, Math.random)","pinned":true,"hidden":false,"mode":"ojs","author":"$undefined","summary":"$undefined","output":"$undefined","database":"$undefined"},{"id":1472,"value":"show(blur2().width(n)) // new new code (stackblur)","pinned":true,"hidden":false,"mode":"ojs","author":"$undefined","summary":"$undefined","output":"$undefined","database":"$undefined"},{"id":189,"value":"show(blur().width(n)) // new code","pinned":true,"hidden":false,"mode":"ojs","author":"$undefined","summary":"$undefined","output":"$undefined","database":"$undefined"},{"id":266,"value":"show(source => mmblur1(source, 5, n)) // calls the code extracted from d3-contour, for comparison","pinned":true,"hidden":false,"mode":"ojs","author":"$undefined","summary":"$undefined","output":"$undefined","database":"$undefined"},{"id":878,"value":"md`The moving average procedure also works in 1-D, resulting in a smooth approximation of data (here, a random walk). Note that this diverges a little from a previous [“Moving average” notebook](https://observablehq.com/@d3/moving-average): in our case the averaged data is defined everywhere on the domain (instead of losing the extremities), and the values are centered instead of being pushed at the end of the interval they average.`","pinned":false,"hidden":false,"mode":"ojs","author":"$undefined","summary":"$undefined","output":"$undefined","database":"$undefined"},{"id":848,"value":"embed(\n {\n title: \"1D smoothing of a random walk\",\n width: Math.max(300, width * 0.7),\n height: 250,\n layer: [\n {\n mark: \"line\",\n data: {\n values: [\n values.map((y, i) => ({\n x: i,\n y,\n type: \"source\"\n })),\n Array.from(blurred, (y, i) => ({\n x: i,\n y,\n type: \"blurred\"\n })),\n [\n { x: 0, y: 0, type: \"interval\" },\n { x: 2 * radius, y: 0, type: \"interval\" }\n ]\n ].flat()\n },\n encoding: {\n x: {\n field: \"x\",\n type: \"quantitative\"\n },\n y: {\n field: \"y\",\n type: \"quantitative\"\n },\n stroke: { field: \"type\", sort: null }\n }\n }\n ]\n },\n { actions: false }\n)","pinned":false,"hidden":false,"mode":"ojs","author":"$undefined","summary":"$undefined","output":"$undefined","database":"$undefined"},{"id":867,"value":"viewof radius = slider({\n min: 0,\n max: 15,\n value: 5,\n step: 1,\n description: \"radius (default: 5)\"\n})","pinned":false,"hidden":false,"mode":"ojs","author":"$undefined","summary":"$undefined","output":"$undefined","database":"$undefined"},{"id":1027,"value":"viewof iterations = slider({\n min: 1,\n max: 10,\n value: 1,\n step: 1,\n description: \"iterations (default: 1)\"\n})","pinned":false,"hidden":false,"mode":"ojs","author":"$undefined","summary":"$undefined","output":"$undefined","database":"$undefined"},{"id":862,"value":"// random walk\nvalues = {\n let x = 1;\n return Array.from({ length: 300 }, () => (x += Math.sin(1e6 * x)));\n}","pinned":false,"hidden":false,"mode":"ojs","author":"$undefined","summary":"$undefined","output":"$undefined","database":"$undefined"},{"id":883,"value":"blurred = blur2()\n .radius(radius)\n .iterations(iterations)(values)","pinned":true,"hidden":false,"mode":"ojs","author":"$undefined","summary":"$undefined","output":"$undefined","database":"$undefined"},{"id":1076,"value":"PROFILE = md`## Profile\n\nThe chart below shows how one Dirac signal (value 1 in position 0) is blurred with radius ${profile_radius} and ${profile_iterations} iterations.`","pinned":false,"hidden":false,"mode":"ojs","author":"$undefined","summary":"$undefined","output":"$undefined","database":"$undefined"},{"id":1075,"value":"embed(\n {\n title: `Blurring profile for radius=${profile_radius} with ${profile_iterations} iterations`,\n width: Math.max(300, width * 0.7),\n height: 270,\n layer: [\n {\n mark: \"bar\",\n data: {\n values: Array.from(\n blur3()\n .iterations(profile_iterations)\n .radius(profile_radius)(\n Float32Array.from({ length: 59 }, (d, i) => i === 29)\n )\n ).map((y, i) => ({\n x: i - 29,\n y: y + 1e-12,\n type: \"profile\"\n }))\n },\n encoding: {\n x: {\n field: \"x\",\n type: \"quantitative\"\n },\n y: {\n field: \"y\",\n type: \"quantitative\"\n }\n //stroke: { field: \"type\", sort: null }\n }\n }\n ]\n },\n { actions: false }\n)","pinned":false,"hidden":false,"mode":"ojs","author":"$undefined","summary":"$undefined","output":"$undefined","database":"$undefined"},{"id":1314,"value":"embed(\n {\n title: `Blurring profile for radius=${profile_radius} with ${profile_iterations} iterations`,\n width: Math.max(300, width * 0.7),\n height: 270,\n layer: [\n {\n mark: \"bar\",\n data: {\n values: Array.from(\n blur3()\n .iterations(profile_iterations)\n .radius(profile_radius)(\n Float32Array.from({ length: 59 }, (d, i) => i === 1)\n )\n ).map((y, i) => ({\n x: i - 1,\n y: y + 1e-12,\n type: \"profile\"\n }))\n },\n encoding: {\n x: {\n field: \"x\",\n type: \"quantitative\"\n },\n y: {\n field: \"y\",\n type: \"quantitative\"\n }\n //stroke: { field: \"type\", sort: null }\n }\n }\n ]\n },\n { actions: false }\n)","pinned":false,"hidden":false,"mode":"ojs","author":"$undefined","summary":"$undefined","output":"$undefined","database":"$undefined"},{"id":1074,"value":"viewof profile_radius = slider({\n min: 0,\n max: 25,\n value: 7,\n step: 1,\n description: \"radius (default: 7)\"\n})","pinned":false,"hidden":false,"mode":"ojs","author":"$undefined","summary":"$undefined","output":"$undefined","database":"$undefined"},{"id":1073,"value":"viewof profile_iterations = slider({\n min: 0,\n max: 10,\n value: 1,\n step: 1,\n description: \"iterations (default: 1)\"\n})","pinned":false,"hidden":false,"mode":"ojs","author":"$undefined","summary":"$undefined","output":"$undefined","database":"$undefined"},{"id":1556,"value":"viewof what_to_show = select({\n options: [\n { label: \"s0 (original value)\", value: 0 },\n { label: \"s1 (block of radius r)\", value: 1 },\n { label: \"s2 (block of radius 2r)\", value: 2 },\n { label: \"delta (s2 - 2s1 + s0)\", value: 3 },\n { label: \"dr (first integral)\", value: 4 },\n { label: \"dr2 (second integral & final result)\", value: 5 }\n ],\n description: \"profile variable\"\n})","pinned":false,"hidden":false,"mode":"ojs","author":"$undefined","summary":"$undefined","output":"$undefined","database":"$undefined"},{"id":1555,"value":"$31","pinned":true,"hidden":false,"mode":"ojs","author":"$undefined","summary":"$undefined","output":"$undefined","database":"$undefined"},{"id":1083,"value":"$32","pinned":true,"hidden":false,"mode":"ojs","author":"$undefined","summary":"$undefined","output":"$undefined","database":"$undefined"},{"id":923,"value":"md`## API\n\nThe current API is:\n~~~{js}\nconst B = blur()\n .value([accessor = d => d])\n .radius([radius = 5])\n .iterations([iterations = 3])\n .width([width = 1])\n .direction([direction = null|\"x\"|\"y\"])\nB(data);\n~~~\n`","pinned":false,"hidden":false,"mode":"ojs","author":"$undefined","summary":"$undefined","output":"$undefined","database":"$undefined"},{"id":457,"value":"blur()([0, 1, 2, 3, 8, 10, 12, 27])","pinned":true,"hidden":false,"mode":"ojs","author":"$undefined","summary":"$undefined","output":"$undefined","database":"$undefined"},{"id":624,"value":"blur()\n .radius(2)\n .iterations(1)\n .width(4)([0, 1, 2, 3, 8, 10, 12, 27])","pinned":true,"hidden":false,"mode":"ojs","author":"$undefined","summary":"$undefined","output":"$undefined","database":"$undefined"},{"id":1022,"value":"md`A *value* accessor allows complex input data and intermediate computations:`","pinned":false,"hidden":false,"mode":"ojs","author":"$undefined","summary":"$undefined","output":"$undefined","database":"$undefined"},{"id":1021,"value":"data = Array.from(values, (d, i) => ({ value: d, index: i }))","pinned":true,"hidden":false,"mode":"ojs","author":"$undefined","summary":"$undefined","output":"$undefined","database":"$undefined"},{"id":1020,"value":"blur().value(d => Math.sin(d.value))(data)","pinned":true,"hidden":false,"mode":"ojs","author":"$undefined","summary":"$undefined","output":"$undefined","database":"$undefined"},{"id":1019,"value":"md`And the function accepts iterables:`","pinned":false,"hidden":false,"mode":"ojs","author":"$undefined","summary":"$undefined","output":"$undefined","database":"$undefined"},{"id":1018,"value":"blur()(new Set(values.slice().sort()))","pinned":true,"hidden":false,"mode":"ojs","author":"$undefined","summary":"$undefined","output":"$undefined","database":"$undefined"},{"id":671,"value":"md`The graphs below show 1D blurring applied to 2D data (don't ask), and the {iterations, direction} options that the new function allows:`","pinned":false,"hidden":false,"mode":"ojs","author":"$undefined","summary":"$undefined","output":"$undefined","database":"$undefined"},{"id":629,"value":"show(blur2()) // 1D horizontal","pinned":true,"hidden":false,"mode":"ojs","author":"$undefined","summary":"$undefined","output":"$undefined","database":"$undefined"},{"id":714,"value":"show(\n blur()\n .width(n)\n .direction(\"y\")\n)","pinned":true,"hidden":false,"mode":"ojs","author":"$undefined","summary":"$undefined","output":"$undefined","database":"$undefined"},{"id":1016,"value":"// compose a heavy \"x\" blur with a light \"y\" blur\nshow(data =>\n blur2()\n .width(n)\n .radius(1)\n .iterations(1)\n .direction(\"y\")(\n blur2()\n .width(n)\n .radius(20)\n .iterations(4)\n .direction(\"x\")(data)\n )\n)","pinned":true,"hidden":false,"mode":"ojs","author":"$undefined","summary":"$undefined","output":"$undefined","database":"$undefined"},{"id":1059,"value":"show(\n blur()\n .width(n)\n .radius(1)\n)","pinned":true,"hidden":false,"mode":"ojs","author":"$undefined","summary":"$undefined","output":"$undefined","database":"$undefined"},{"id":284,"value":"$33","pinned":true,"hidden":false,"mode":"ojs","author":"$undefined","summary":"$undefined","output":"$undefined","database":"$undefined"},{"id":264,"value":"$34","pinned":true,"hidden":false,"mode":"ojs","author":"$undefined","summary":"$undefined","output":"$undefined","database":"$undefined"},{"id":111,"value":"d3 = require(\"d3@5\")","pinned":true,"hidden":false,"mode":"ojs","author":"$undefined","summary":"$undefined","output":"$undefined","database":"$undefined"},{"id":870,"value":"import { select, slider } from \"@jashkenas/inputs\"","pinned":true,"hidden":false,"mode":"ojs","author":"$undefined","summary":"$undefined","output":"$undefined","database":"$undefined"},{"id":847,"value":"embed = require(\"vega-embed@6\")","pinned":true,"hidden":false,"mode":"ojs","author":"$undefined","summary":"$undefined","output":"$undefined","database":"$undefined"},{"id":844,"value":"html``","pinned":true,"hidden":false,"mode":"ojs","author":"$undefined","summary":"$undefined","output":"$undefined","database":"$undefined"},{"id":110,"value":"function show(blur, { nn = n, runs = 50 } = {}) {\n const m = source.length / nn;\n const scale = Math.pow(2, -Math.ceil(Math.log2(Math.max(nn, m) / 400)));\n\n const w = scale * n,\n h = scale * m;\n const x = d3.scaleLinear([0, nn], [0, w]),\n y = d3.scaleLinear([0, m], [0, h]);\n const c = d3.scaleSequential(d3.interpolateGreys);\n\n const context = DOM.context2d(width, h);\n\n let blurred;\n let t = performance.now();\n for (let i = 0; i < runs; i++) blurred = blur(source);\n t = (performance.now() - t) / runs;\n\n // a rather inefficient way to show the output :-)\n function draw(array) {\n for (let k = 0; k < array.length; k++) {\n const i = k % nn,\n j = Math.floor(k / nn);\n context.fillStyle = c(array[i + n * j]);\n context.fillRect(x(i), y(j), x(i + 1) - x(i), y(j + 1) - y(j));\n }\n }\n\n draw(source);\n context.translate(x(nn) + 50, 0);\n context.fillStyle = \"red\";\n context.fillText(`${+t.toFixed(1)}ms`, -40, 10);\n draw(blurred);\n\n return context.canvas;\n}","pinned":true,"hidden":false,"mode":"ojs","author":"$undefined","summary":"$undefined","output":"$undefined","database":"$undefined"}],"files":"$W35","stdlib":"1","titling":"auto"}} 30:"$2f:body"