!(async function(){ var isLock = false var csvstr = await (await fetch('rotated-accuracy.csv')).text() var allData = d3.csvParse(csvstr) .filter(d => { d.slug = [d.dataset_size, d.aVal, d.minority_percent].join(' ') d.accuracy_orig = (+d.accuracy_test_data_1 + +d.accuracy_test_data_7)/2000 d.accuracy_rot = (+d.accuracy_test_data_1_rot + +d.accuracy_test_data_7_rot)/2000 d.accuracy_dif = d.accuracy_orig - d.accuracy_rot return d.accuracy_orig > 0 && d.accuracy_rot > 0 }) var data = d3.nestBy(allData, d => d.slug) data.forEach(slug => { slug.accuracy_orig = d3.median(slug, d => d.accuracy_orig) slug.accuracy_rot = d3.median(slug, d => d.accuracy_rot) slug.accuracy_dif = slug.accuracy_orig - slug.accuracy_rot slug.dataset_size = +slug[0].dataset_size slug.aVal = +slug[0].aVal slug.minority_percent = +slug[0].minority_percent }) // d3.nestBy(data, d => d.length).forEach(d => { // console.log(d.key, d.length) // }) var byMetrics = 'dataset_size aVal minority_percent' .split(' ') .map(metricStr => { var byMetric = d3.nestBy(data, d => d[metricStr]) byMetric.forEach(d => d.key = +d.key) byMetric = _.sortBy(byMetric, d => d.key) byMetric.forEach((d, i) => { d.metricIndex = i d.forEach(e => e['metric_' + metricStr] = d) }) byMetric.forEach((d, i) => { if (metricStr == 'dataset_size') d.label = i % 2 == 0 ? '' : d3.format(',')(d.key) if (metricStr == 'aVal') d.label = '' if (metricStr == 'minority_percent') d.label = i % 2 ? '' : d3.format('.0%')(d.key) }) byMetric.active = byMetric[5] byMetric.metricStr = metricStr byMetric.label = {dataset_size: 'Training Points', aVal: 'Less Privacy', minority_percent: 'Percent Rotated In Training Data'}[metricStr] return byMetric }) // Heat map !(function(){ var sel = d3.select('.rotated-accuracy-heatmap').html('') .st({width: 1100, position: 'relative', left: (850 - 1100)/2}) .at({role: 'graphics-document', 'aria-label': `Faceted MNIST models by the percent of rotated digits in training data. Heatmaps show how privacy and training data change accuracy on rotated and original digits.`}) sel.append('div.chart-title').text('Percentage of training data rotated 90° →') sel.appendMany('div', byMetrics[2])//.filter((d, i) => i % 2 == 0)) .st({display: 'inline-block'}) .each(drawHeatmap) })() function drawHeatmap(sizeData, chartIndex){ var s = 8 var n = 11 var c = d3.conventions({ sel: d3.select(this), width: s*n, height: s*n, margin: {left: 5, right: 5, top: 30, bottom: 50}, }) c.svg.append('rect').at({width: c.width, height: c.height, fillOpacity: 0}) c.svg.append('text.chart-title') .text(d3.format('.0%')(sizeData.key)).at({dy: -4, textAnchor: 'middle', x: c.width/2}) .st({fontWeight: 300}) var linearScale = d3.scaleLinear().domain([0, .5]).clamp(1) var colorScale = d => d3.interpolatePlasma(linearScale(d)) var pad = .5 var dataSel = c.svg .on('mouseleave', () => isLock = false) .append('g').translate([.5, .5]) .appendMany('g.accuracy-rect', sizeData) .translate(d => [ s*d.metric_dataset_size.metricIndex, s*(n - d.metric_aVal.metricIndex) ]) .call(d3.attachTooltip) .on('mouseover', (d, i, node, isClickOverride) => { updateTooltip(d) if (isLock && !isClickOverride) return byMetrics[0].setActiveCol(d.metric_dataset_size) byMetrics[1].setActiveCol(d.metric_aVal) byMetrics[2].setActiveCol(d.metric_minority_percent) return d }) .on('click', clickCb) .st({cursor: 'pointer'}) dataSel.append('rect') .at({ width: s - pad, height: s - pad, fillOpacity: .1 }) // dataSel.append('rect') // .at({ // width: d => Math.max(1, (s - pad)*(d.accuracy_orig - .5)*2), // height: d => Math.max(1, (s - pad)*(d.accuracy_rot - .5)*2), // }) sizeData.forEach(d => { d.y_orig = Math.max(0, (s - pad)*(d.accuracy_orig - .5)*2) d.y_rot = Math.max(0, (s - pad)*(d.accuracy_rot - .5)*2) }) dataSel.append('rect') .at({ height: d => d.y_orig, y: d => s - d.y_orig, width: s/2, x: s/2, fill: 'purple', }) dataSel.append('rect') .at({ height: d => d.y_rot, y: d => s - d.y_rot, width: s/2, fill: 'orange', }) sizeData.updateActiveRect = function(match){ dataSel .classed('active', d => match == d) .filter(d => match == d) .raise() } if (chartIndex == 0){ c.svg.append('g.x.axis').translate([10, c.height]) c.svg.append('g.y.axis').translate([0, 5]) util.addAxisLabel(c, 'Training Points →', 'Less Privacy →', 30, -15) } if (chartIndex == 8){ c.svg.appendMany('g.axis', ['Original Digit Accuracy', 'Rotated Digit Accuracy']) .translate((d, i) => [c.width - 230*i - 230 -50, c.height + 30]) .append('text.axis-label').text(d => d) .st({fontSize: 14}) .parent() .appendMany('rect', (d, i) => d3.range(.2, 1.2, .2).map((v, j) => ({i, v, j}))) .at({ width: s/2, y: d => s - d.v*s - s, height: d => d.v*s, fill: d => ['purple', 'orange'][d.i], x: d => d.j*s*.75 - 35 }) } } // Metric barbell charts !(function(){ var sel = d3.select('.rotated-accuracy').html('') .at({role: 'graphics-document', 'aria-label': `Barbell charts showing up privacy / data / percent underrepresented data all trade-off in complex ways.`}) sel.appendMany('div', byMetrics) .st({display: 'inline-block', width: 300, marginRight: 10, marginBottom: 50, marginTop: 10}) .each(drawMetricBarbell) })() function drawMetricBarbell(byMetric, byMetricIndex){ var sel = d3.select(this) var c = d3.conventions({ sel, height: 220, width: 220, margin: {bottom: 10, top: 5}, layers: 's', }) c.svg.append('rect').at({width: c.width, height: c.height, fillOpacity: 0}) c.y.domain([.5, 1]).interpolate(d3.interpolateRound) c.x.domain([0, byMetric.length - 1]).clamp(1).interpolate(d3.interpolateRound) c.xAxis .tickValues(d3.range(byMetric.length)) .tickFormat(i => byMetric[i].label) c.yAxis.ticks(5).tickFormat(d => d3.format('.0%')(d)) d3.drawAxis(c) util.addAxisLabel(c, byMetric.label + ' →', byMetricIndex ? '' : 'Accuracy') util.ggPlotBg(c, false) c.svg.select('.x').raise() c.svg.selectAll('.axis').st({pointerEvents: 'none'}) c.svg.append('defs').append('linearGradient#purple-to-orange') .at({x1: '0%', x2: '0%', y1: '0%', y2: '100%'}) .append('stop').at({offset: '0%', 'stop-color': 'purple'}).parent() .append('stop').at({offset: '100%', 'stop-color': 'orange'}) c.svg.append('defs').append('linearGradient#orange-to-purple') .at({x1: '0%', x2: '0%', y2: '0%', y1: '100%'}) .append('stop').at({offset: '0%', 'stop-color': 'purple'}).parent() .append('stop').at({offset: '100%', 'stop-color': 'orange'}) var colSel = c.svg.appendMany('g', byMetric) .translate(d => c.x(d.metricIndex) + .5, 0) .st({pointerEvents: 'none'}) var pathSel = colSel.append('path') .at({stroke: 'url(#purple-to-orange)', strokeWidth: 1}) var rectSel = colSel.append('rect') .at({width: 1, x: -.5}) var origCircleSel = colSel.append('circle') .at({r: 3, fill: 'purple', stroke: '#000', strokeWidth: .5}) var rotCircleSel = colSel.append('circle') .at({r: 3, fill: 'orange', stroke: '#000', strokeWidth: .5}) function clampY(d){ return d3.clamp(0, c.y(d), c.height + 3) } byMetric.updateActiveCol = function(){ var findObj = {} byMetrics .filter(d => d != byMetric) .forEach(d => { findObj[d.metricStr] = d.active.key }) byMetric.forEach(col => { col.active = _.find(col, findObj) }) origCircleSel.at({cy: d => clampY(d.active.accuracy_orig)}) rotCircleSel.at({cy: d => clampY(d.active.accuracy_rot)}) // pathSel.at({ // d: d => 'M 0 ' + clampY(d.active.accuracy_orig) + ' L 1 ' + clampY(d.active.accuracy_rot) // }) rectSel.at({ y: d => Math.min(clampY(d.active.accuracy_orig), clampY(d.active.accuracy_rot)), height: d => Math.abs(clampY(d.active.accuracy_orig) - clampY(d.active.accuracy_rot)), fill: d => d.active.accuracy_orig > d.active.accuracy_rot ? 'url(#purple-to-orange)' : 'url(#orange-to-purple)' }) } byMetric.updateActiveCol() c.svg .call(d3.attachTooltip) .st({cursor: 'pointer'}) .on('mousemove', function(d, i, node, isClickOverride){ var [mx] = d3.mouse(this) var metricIndex = Math.round(c.x.invert(mx)) var prevActive = byMetric.active byMetric.active = byMetric[metricIndex] updateTooltip() byMetric.active = prevActive if (isLock && !isClickOverride) return byMetric.setActiveCol(byMetric[metricIndex]) return byMetric[metricIndex] }) .on('click', clickCb) .on('mouseexit', () => isLock = false) byMetric.setActiveCol = function(col){ if (col) byMetric.active = col c.svg.selectAll('.x .tick') .classed('active', i => i == byMetric.active.metricIndex) colSel.classed('active', d => d == byMetric.active) if (col) renderActiveCol() } byMetric.setActiveCol() } function renderActiveCol(){ byMetrics.forEach(d => { if (d.updateActiveCol) d.updateActiveCol() }) var findObj = {} byMetrics.forEach(d => findObj[d.metricStr] = d.active.key) var match = _.find(data, findObj) byMetrics[2].forEach(d => { if (d.updateActiveRect) d.updateActiveRect(match) }) } function updateTooltip(d){ if (!d){ var findObj = {} byMetrics.forEach(d => findObj[d.metricStr] = d.active.key) d = _.find(data, findObj) } var epsilon = Math.round(d[0].epsilon*100)/100 ttSel.html(`
${d3.format('.0%')(d.accuracy_orig)} accuracy on original digits
${d3.format('.0%')(d.accuracy_rot)} accuracy on rotated digits

Training points: ${d3.format(',')(d.dataset_size)}
Privacy: ${epsilon} ε
Rotated in training data: ${d3.format('.0%')(d.minority_percent)}
`).st({width: 230}) ttSel.classed('tooltip-footnote', 0) } function clickCb(d, i, node){ var mFn = d3.select(this).on('mouseover') || d3.select(this).on('mousemove') var e = mFn.call(this, d, i, node, true) isLock = e == isLock ? null : e } })()