30:T4c6,viz = { const width = 500 const height = 0.6*width; const svg = d3.select(DOM.svg(width, height)) const renderData = result.map(r => ({ ...r, values: r.values.reduce((t,v,i) => [ ...t, { value: v, cumulative: v + (i === 0 ? 0 : t[i-1].cumulative) } ], []) })) const yScale = d3.scaleLinear() .domain([0, d3.max(result, d => d.sum)]) .range([0, height]) const xScale = d3.scaleBand() .domain(result.map((_,i) => i)) .range([0, width]) .paddingInner(0.2) const colorScale = d3.scaleSequential(d3.interpolateSpectral) .domain([0, data.length]) const column = createMerge(svg, 'g', 'column', renderData) .attr('transform', (d,i) => `translate(${xScale(i)}, 0)`) let layer = column.selectAll('rect') .data(d => d.values) const layerEnter = layer.enter() .append('rect') .attr('y', height) .attr('height', 0) layer = layerEnter.merge(layer) .attr('fill', d => colorScale(data.indexOf(d.value))) .attr('width', xScale.bandwidth()); layer.transition() .delay(d => data.indexOf(d.value) * 100) .attr('height', d => yScale(d.value)) .attr('y', d => height - yScale(d.cumulative)) return svg.node(); }31:[] 2e:{"title":"Partitioning","cells":[{"id":0,"value":"md`# Partitioning`","pinned":false,"hidden":false,"mode":"ojs"},{"id":4,"value":"data = [254, 159, 133, 120, 115, 105, 102, 100, 99, 95, 93, 92, 88, 87, 83, 82, 78, 77, 75, 72, 67, 67, 67, 66, 64, 64, 62, 58, 56, 55, 53, 46, 44, 39, 36, 33, 29, 29, 24, 23, 21, 17, 16, 15, 14, 14, 10, 8, 5, 5, 3, 1]","pinned":false,"hidden":false,"mode":"ojs"},{"id":8,"value":"md`Partition the data into ${nCols} approximately equally-sized columns`","pinned":false,"hidden":false,"mode":"ojs"},{"id":6,"value":"viewof nCols = DOM.range(1, 10, 1)","pinned":false,"hidden":false,"mode":"ojs"},{"id":54,"value":"$30","pinned":false,"hidden":false,"mode":"ojs"},{"id":12,"value":"function partition(arr, ngroups){\n // greedy algorithm\n const target = Math.floor( arr.reduce((t,v) => t+v,0) / ngroups );\n // console.log('Target size is ',target);\n let grouped = [];\n for (var j = 0; j < ngroups; j++){\n grouped.push({ sum: 0, values: [] })\n }\n while (arr.length > 0){\n let k = 0;\n let found = false;\n let el = +arr.splice(0, 1);\n // just put el in the first available bucket\n while (k < ngroups && !found){\n if (grouped[k].sum < target && el < target - grouped[k].sum){\n grouped[k].values.push(el)\n grouped[k].sum += el;\n found = true;\n }\n k += 1;\n }\n // if all buckets are full, put it in the smallest bucket\n if (!found) {\n const next = grouped.find(d => d.sum === Math.min(...grouped.map(e => e.sum)))\n next.values.push(el)\n next.sum += el;\n }\n }\n return grouped;\n}","pinned":false,"hidden":false,"mode":"ojs"},{"id":19,"value":"result = partition([...data], nCols)","pinned":false,"hidden":false,"mode":"ojs"},{"id":65,"value":"import { createMerge } from '@anbnyc/utility-library'","pinned":false,"hidden":false,"mode":"ojs"},{"id":56,"value":"d3 = require('d3')","pinned":false,"hidden":false,"mode":"ojs"},{"id":110,"value":"html`Created at

. Visit us online, @2nfo, and @2ngrams.`","pinned":false,"hidden":false,"mode":"ojs"}],"files":"$W31","stdlib":"1","titling":"auto"}