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window.ttSel = d3.select('body').selectAppend('div.tooltip.tooltip-hidden')
window.util = (function(){
var data = window.__datacache = window.__datacache || {}
async function getFile(path){
var [slug, type] = path.split('.')
if (data[slug]) return data[slug]
var datadir = 'https://storage.googleapis.com/uncertainty-over-space/explore-dp/'
var res = await fetch(datadir + path + '?t=5')
if (type == 'csv'){
var parsed = d3.csvParse(await res.text())
} else if (type == 'npy'){
var parsed = npyjs.parse(await(res).arrayBuffer())
} else if (type == 'json'){
var parsed = await res.json()
} else{
throw 'unknown type'
}
data[slug] = parsed
return parsed
}
async function drawDigit(ctx, index, s=4, offsetX=0, offsetY=0){
var digitMetadata = await util.getFile('mnist_train.csv')
if (!digitMetadata[0].label) decorateDigitMetadata(digitMetadata)
var {label, labelIndex} = digitMetadata[index]
if (!label) console.log('missing ', index)
var rawdigits = await util.getFile(`cns-cache/mnist_train_raw_${label}.npy`)
if (!rawdigits) return console.log('digits not loaded')
d3.cross(d3.range(28), d3.range(28)).forEach(([i, j]) => {
var r = rawdigits.data[labelIndex*28*28 + j*28 + i + 0]
var g = rawdigits.data[labelIndex*28*28 + j*28 + i + 0]
var b = rawdigits.data[labelIndex*28*28 + j*28 + i + 0]
ctx.beginPath()
ctx.fillStyle = `rgb(${r},${g},${b})`
ctx.rect(i*s + offsetX, j*s + offsetY, s, s)
ctx.fill()
})
}
function decorateDigitMetadata(digitMetadata){
digitMetadata.forEach(d => {
delete d['']
d.i = +d.i
d.label = +d.y
d.priv_order = +d.priv_order
})
var byLabel = d3.nestBy(digitMetadata, d => d.y)
byLabel = _.sortBy(byLabel, d => d.key)
byLabel.forEach(digit => {
digit.forEach((d, i) => d.labelIndex = i)
})
return {digitMetadata, byLabel}
}
var colors = [d3.interpolateTurbo(.15), d3.interpolateTurbo(.85)]
var epsilonExtent = [400000, .01]
// var epsilonExtent = [65, .01]
var addAxisLabel = (c, xText, yText, xOffset=40, yOffset=-40) => {
c.svg.select('.x').append('g')
.translate([c.width/2, xOffset])
.append('text.axis-label')
.text(xText)
.at({textAnchor: 'middle'})
.st({fill: '#000', fontSize: 14})
c.svg.select('.y')
.append('g')
.translate([yOffset, c.height/2])
.append('text.axis-label')
.text(yText)
.at({textAnchor: 'middle', transform: 'rotate(-90)'})
.st({fill: '#000', fontSize: 14})
}
var ggPlotBg = (c, isBlack=true) => {
if (!isBlack){
c.svg.append('rect')
.at({width: c.width, height: c.height, fill: '#eee'})
.lower()
}
c.svg.selectAll('.tick').selectAll('line').remove()
c.svg.selectAll('.y .tick')
.append('path').at({d: 'M 0 0 H ' + c.width, stroke: '#fff', strokeWidth: 1})
c.svg.selectAll('.y text').at({x: -3})
c.svg.selectAll('.x .tick')
.append('path').at({d: 'M 0 0 V -' + c.height, stroke: '#fff', strokeWidth: 1})
}
return {data, getFile, drawDigit, colors, epsilonExtent, addAxisLabel, ggPlotBg, decorateDigitMetadata}
})()
// mnist_train.csv
// mnist_train_raw.npy
// umap_train_0.npy
// umap_train_1.npy
// umap_train_2.npy
// umap_train_3.npy
// umap_train_4.npy
// umap_train_5.npy
// umap_train_6.npy
// umap_train_7.npy
// umap_train_8.npy
// umap_train_9.npy
// umap_train_all.npy
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