hidden-bias / public /uncertainty-calibration /draw_calibrationcurve.js
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commit files to HF hub
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window.drawCalibrationCurve = function (graphSel, fig_height, fig_width){
var width = Math.min(fig_height, fig_width)
var sel = graphSel
.append('div').st({textAlign: 'center'})
.append('div').st({display: 'inline-block'})
var c = d3.conventions({
sel,
width,
height: width,
margin: {top: 40}
});
c.svg.parent()
//TODO(nthain) Who owns the buckets? We have at least 2 instances, reduce to 1
var buckets = d3.pairs(window.weatherGraph.thresholds)
buckets.forEach(bucket => {
bucket.val = d3.mean(bucket, d => d.origVal)
})
c.xAxis.tickValues(buckets.map(d => d.val)).tickFormat(d3.format('.2f'))
c.yAxis.tickValues(buckets.map(d => d.val)).tickFormat(d3.format('.2f'))
d3.drawAxis(c)
window.util.ggPlotBg(c)
window.util.addAxisLabel(c, 'Calibrated Model Score', 'Probability of Rain')
var eceSel = c.svg.append('g.ece')
var eceBox = eceSel.append('rect.val-box')
.at({width: 55, height: 20, x: c.width/2 + 72.5, y: -35, rx: 3, ry: 3})
var eceText = eceSel.append('text.big-text')
.at({y: -20, x: c.width/2-30, textAnchor: 'middle'})
var eceVal = eceSel.append('text.val-text')
.at({y: -20, x: c.width/2+100, textAnchor: 'middle'})
c.svg.append('path')
.at({
d: ['M', 0, c.height, 'L', c.width, 0].join(' '),
stroke: '#555',
strokeDasharray: '3 3',
})
var bucketSel = c.svg.appendMany('g.bucket', buckets)
var circleSel = bucketSel.append('circle')
.at({fillOpacity: .4, fill: 'steelblue'})
var pathSel = bucketSel.append('path')
.at({stroke: 'steelblue', strokeWidth: 3})
var bucketText = bucketSel.append('text').text('8 / 10')
.at({textAnchor: 'start', dy: '.33em', fontSize: 10, fill: '#000'})
// function remap_score(s) {
// // new_score = min_threshold_new + (old_score-min_threshold_old)(max_threshold_new-min_threshold_new)/(max_threshold_old-min_threshold_old)
// //find index less than score
// }
function renderBuckets(){
var filter_rain = window.slides.slide?.filter_rain
buckets.forEach(bucket => {
bucket.data = weatherdata
.filter(d => bucket[0].val <= d.score && d.score <= bucket[1].val)
.filter(d => !filter_rain || !d.is_filter)
bucket.nPositive = d3.sum(bucket.data, d => d.label)
bucket.percent = bucket.nPositive/bucket.data.length
if (isNaN(bucket.percent)) bucket.percent = bucket[0].val
})
var ece = d3.sum(buckets, d => d.data.length*Math.abs(d.val - d.percent))
ece = ece/d3.sum(buckets, d => d.data.length)
eceText.text('Expected Calibration Error: ')
eceVal.text(d3.format('.3f')(ece))
var rScale = d3.scaleSqrt().domain([0, 50]).range([0, 20])
bucketSel
.st({opacity: d => d.data.length})
.filter(d => d.data.length)
.translate(d => [c.x(d.val), c.y(d.percent)])
circleSel
.at({r: d => rScale(d.data.length)})
pathSel.at({d: d => 'M 0 0 V ' + (c.y(d.val) - c.y(d.percent))})
bucketText
.text(d => `${d.nPositive} / ${d.data.length}`)
.at({x: d => rScale(d.data.length) + 2})
}
return {renderBuckets, c, buckets, calibrationDataFn: () => console.log('test')}
}
if (window.init) window.init()