Spaces:
Running
Running
!(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(` | |
<div> | |
<b>${d3.format('.0%')(d.accuracy_orig)}</b> | |
accuracy on | |
<span style='padding: 2px; background: purple; color: #fff'> | |
original digits | |
</span> | |
<div> | |
<div> | |
<b>${d3.format('.0%')(d.accuracy_rot)}</b> | |
accuracy on | |
<span style='padding: 2px; background: orange; color: #000'> | |
rotated digits | |
</span> | |
<br> | |
<br> | |
<div>Training points: ${d3.format(',')(d.dataset_size)}</div> | |
<div>Privacy: ${epsilon} ε</div> | |
<div>Rotated in training data: ${d3.format('.0%')(d.minority_percent)} </div> | |
`).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 | |
} | |
})() | |