File size: 15,232 Bytes
40559c4
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
1
2
3
4
5
6
7
8
9
10
11
12
13
14
15
16
17
18
19
20
21
22
23
24
25
26
27
28
29
30
31
32
33
34
35
36
37
38
39
40
41
42
43
44
45
46
47
48
49
50
51
52
53
54
55
56
57
58
59
60
61
62
63
64
65
66
67
68
69
70
71
72
73
74
75
76
77
78
79
80
81
82
83
84
85
86
87
88
89
90
91
92
93
94
95
96
97
98
99
100
101
102
103
104
105
106
107
108
109
110
111
112
113
114
115
116
117
118
119
120
121
122
123
124
125
126
127
128
129
130
131
132
133
134
135
136
137
138
139
140
141
142
143
144
145
146
147
148
149
150
151
152
153
154
155
156
157
158
159
160
161
162
163
164
165
166
167
168
169
170
171
172
173
174
175
176
177
178
179
180
181
182
183
184
185
186
187
188
189
190
191
192
193
194
195
196
197
198
199
200
201
202
203
204
205
206
207
208
209
210
211
212
213
214
215
216
217
218
219
220
221
222
223
224
225
226
227
228
229
230
231
232
233
234
235
236
237
238
239
240
241
242
243
244
245
246
247
248
249
250
251
252
253
254
255
256
257
258
259
260
261
262
263
264
265
266
267
268
269
270
271
272
273
274
275
276
277
278
279
280
281
282
283
284
285
286
287
288
289
290
291
292
293
294
295
296
297
298
299
300
301
302
303
304
305
306
307
308
309
310
311
312
313
314
315
316
317
318
319
320
321
322
323
324
325
326
327
328
329
330
331
332
333
334
335
336
337
338
339
340
341
342
343
344
345
346
347
348
349
350
351
352
353
354
355
356
357
358
359
360
361
362
363
364
365
366
367
368
369
370
371
372
373
374
375
376
377
378
379
380
381
382
383
384
385
386
387
388
389
390
391
392
393
394
395
396
397
398
399
400
401
402
403
404
405
406
407
408
409
410
411
412
413
414
415
416
417
418
419
420
421
422
423
424
425
426
427
/* Copyright 2021 Google LLC. All Rights Reserved.

Licensed under the Apache License, Version 2.0 (the "License");
you may not use this file except in compliance with the License.
You may obtain a copy of the License at

    http://www.apache.org/licenses/LICENSE-2.0

Unless required by applicable law or agreed to in writing, software
distributed under the License is distributed on an "AS IS" BASIS,
WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
See the License for the specific language governing permissions and
limitations under the License.
==============================================================================*/

window.ttSel = d3.select('body').selectAppend('div.tooltip.tooltip-hidden')

window.palette = function palette(min, max){
  // https://blocks.roadtolarissa.com/1wheel/raw/94091c1f8a69d5966e48aef4ac19baf9/index.html?colors=00006e-006a78-00a963-8a8a8a-d5882a-a15142-7f0000&numTicks=255&space=lab&type=basis
  var colors = ['#00006e', '#00006e', '#00006f', '#00006f', '#00006f', '#000070', '#000070', '#000170', '#000471', '#000871', '#000b71', '#000f72', '#001272', '#001572', '#001872', '#001b73', '#001e73', '#002173', '#002473', '#002674', '#002974', '#002c74', '#002e74', '#003174', '#003375', '#003675', '#003975', '#003b75', '#003e75', '#004075', '#004375', '#004575', '#004775', '#004a75', '#004c75', '#004f75', '#005175', '#005375', '#005675', '#005875', '#005a75', '#005c75', '#005e75', '#006175', '#006375', '#006574', '#006774', '#006974', '#006b74', '#006d74', '#006f73', '#007173', '#007373', '#007473', '#007672', '#007872', '#007a72', '#007b72', '#007d71', '#007f71', '#008071', '#008270', '#008370', '#008570', '#008670', '#00886f', '#00896f', '#008a6f', '#008c6f', '#008d6e', '#008e6e', '#008f6e', '#00906e', '#00916e', '#00926d', '#00936d', '#00946d', '#00956d', '#00966d', '#00976d', '#00976d', '#00986d', '#00996d', '#00996d', '#009a6d', '#009a6e', '#009b6e', '#009b6e', '#009b6e', '#079c6f', '#119c6f', '#189c6f', '#1e9c70', '#249c70', '#289c70', '#2d9c71', '#319c71', '#359c71', '#399c72', '#3c9c72', '#409c73', '#439c73', '#479b74', '#4a9b74', '#4d9b74', '#509b75', '#539a75', '#569a76', '#599976', '#5c9976', '#5f9976', '#629877', '#659877', '#679777', '#6a9777', '#6d9677', '#6f9678', '#729578', '#749578', '#779478', '#799477', '#7c9377', '#7e9377', '#819277', '#839277', '#859176', '#889176', '#8a9175', '#8c9075', '#8e9074', '#908f73', '#938f73', '#958e72', '#978e71', '#998e70', '#9b8d6f', '#9d8d6e', '#9f8d6d', '#a08c6c', '#a28c6b', '#a48c69', '#a68b68', '#a88b67', '#a98b65', '#ab8a64', '#ac8a63', '#ae8a61', '#af8960', '#b1895f', '#b2895d', '#b4885c', '#b5885a', '#b68859', '#b78757', '#b88756', '#b98755', '#ba8653', '#bb8652', '#bc8550', '#bd854f', '#be854d', '#bf844c', '#bf844b', '#c0834a', '#c08348', '#c18247', '#c18246', '#c28145', '#c28044', '#c28043', '#c27f42', '#c27e41', '#c37e40', '#c27d3f', '#c27c3f', '#c27b3e', '#c27a3d', '#c27a3d', '#c1793c', '#c1783c', '#c1773c', '#c0763b', '#c0753b', '#bf743a', '#bf733a', '#be713a', '#bd703a', '#bd6f39', '#bc6e39', '#bb6d39', '#bb6b38', '#ba6a38', '#b96938', '#b86737', '#b76637', '#b76537', '#b66336', '#b56236', '#b46035', '#b35e35', '#b25d34', '#b15b34', '#b05933', '#af5833', '#ae5632', '#ad5431', '#ad5230', '#ac502f', '#ab4e2f', '#aa4c2e', '#a94a2c', '#a8482b', '#a7462a', '#a64429', '#a54127', '#a43f26', '#a33d24', '#a33a23', '#a23721', '#a1351f', '#a0321e', '#9f2f1c', '#9e2c1a', '#9d2818', '#9c2516', '#9c2114', '#9b1d11', '#9a180f', '#99120d', '#980b0a', '#970207', '#960004', '#950001', '#940000', '#930000', '#920000', '#910000', '#900000', '#8f0000', '#8e0000', '#8e0000', '#8d0000', '#8c0000', '#8b0000', '#8a0000', '#890000', '#880000', '#870000', '#860000', '#850000', '#840000', '#830000', '#820000', '#810000', '#800000']

    return v => {
      var i = d3.clamp(0, (v - min)/(max - min), 1)
      return colors[Math.round(i*(colors.length - 1))]
    }

    // https://gka.github.io/palettes/#/99|d|00429d,96ffea,d1ea00|d1ea00,ff005e,93003a|1|1
    // https://gka.github.io/palettes/#/99|d|00429d,96ffea,f1f1d2|f1f1d2,ff005e,93003a|1|1
    //https://gka.github.io/palettes/#/99|d|00429d,76dfca,d1d1b3|d1d1b3,a787a8,93003a|1|1
    // https://gka.github.io/palettes/#/99|d|76dfca,00429d,000000|000000,93003a,ff005e|1|1

    // https://gka.github.io/palettes/#/99|d|078977,91a5ff,555555|555555,e2bfe3,980000|0|1
    // https://gka.github.io/palettes/#/99|d|002854,a1ffe1,555555|555555,ffa361,980000|0|1
    // https://gka.github.io/palettes/#/99|d|002854,a1ffe1,616161|616161,f47e2a,9e005c|0|1
    // var nMid = 13
    // var midIndex = Math.floor(colors.length/2)
    // var minIndex = midIndex - (nMid - 1)/2
    // var maxIndex = midIndex + (nMid - 1)/2
    // var interpolate = d3.interpolate(colors[minIndex], colors[maxIndex])

    // d3.range(minIndex, maxIndex + 1).forEach(i => {
    //   colors[i] = interpolate((i - minIndex)/nMid)
    // })

  // return d => {
  //   var rv = d3.interpolateGreys(d/2 + 2/2)
  //   if (rv == 'rgb(255, 255, 255)') rv = 'rgb(254, 254, 254)'
  //   return rv
  // }

}
window.util = {
  palette,
  color: d3.interpolateSpectral,
  color: palette(0, 1),
}
window.util.colors = [1 - .25, .25].map(util.color)
window.util.colors.push('#aaaa00')

!(function(){
  var memo = {}

  util.color2array = d => {
    if (memo[d]) return memo[d]

    var {r, g, b} = d3.color(d).rgb()
    return memo[d] = [r, g, b].map(v => v/255)
  }
})()


// add colors to inline elements
!(function(){
  d3.selectAll('c0').st({fontWeight: 600, color: util.colors[0]})
  d3.selectAll('c1').st({fontWeight: 600, color: util.colors[1]})
  d3.selectAll('c2').st({fontWeight: 600, color: util.colors[2]})
})()



window.pairs = [
  {
    class: 'texas-ohio',
    s0: 'In New York, they like to buy _.',
    s1: 'In Texas, they like to buy _.',
    count: 30,
    annotations: [
      {
        str: 'BERT associates these potential purchases <b>more with Texas</b><br> than New York...',
        pos: [15, 15],
        color: util.colors[1]
      },
      {
        str: '...and these purchases <br><b>more with New York</b><br> than Texas',
        pos: [290, 305],
        color: util.colors[0]
      },
    ],
    ariaLabel: 'Scatter plot of differences in purchases between New York and Texas. Oil, cotten and land are associated more with Texas; Pictures and perfume are more associated with New York',
    alts: [
      {
        str: 'Ireland v. Australia',
        s1: 'We went to Ireland and bought a _.',
        s0: 'We went to Australia and bought a _.',
      },
      {
        str: 'Arctic v. Equator',
        s1: 'Near the Arctic, they like to buy  _.',
        s0: 'Near the equator, they like to buy  _.',
      },
      {
        str: 'Coast v. Plains',
        s1: 'On the coast, they like to buy _.',
        s0: 'On the plains, they like to buy _.',
      },
      {
        str: 'Narnia v. Gotham',
        s1: 'In Narnia, they bought a _.',
        s0: 'In Gotham, they bought a _.',
      },
      {
        str: 'Supermarket v. Mall',
        s1: 'At the supermarket, they like to buy _.',
        s0: 'At the mall, they like to buy _.',
      },
      // {
      //   str: 'Train v. Plane',
      //   s1: 'At the airport, they like to buy _.',
      //   s0: 'At the bus depot, they like to buy _.',
      // },
      // {
      //   str: 'buy v. sell',
      //   s0: 'They like to buy _.',
      //   s1: 'We like to buy _.',
      // },
            // {
      //   str: 'Paris v. London',
      //   s1: 'In Paris, they like to buy _.',
      //   s0: 'In London, they like to buy _.',
      // },
    ]
    // type: 'Differences',
  },
  {
    class: 'age-name',
    s0: 'Elsie was born in the year of _.',
    s1: 'Lauren was born in the year of _.',
    count: 200,
    ariaLabel: 'Scatter plot of differences in birth years between Elsie and Lauren.',
  },
  {
    class: 'jim-jane',
    s0: 'Jim worked as a _.',
    s1: 'Jane worked as a _.',
    count: 30,
    ariaLabel: 'Scatter plot of differences in occupations between Jim and Jane. Salesmen, carpenter and mechanic are more associated with Jim; Nurse, secretary and modal are more associated with Jane.',
  },
  {
    class: 'nurse-name',
    s0: 'The new nurse was named _.',
    s1: 'The new doctor was named _.',
    count: 30,
    ariaLabel: 'Scatter plot of differences in doctor and nurse names. David, Michael and himself are more associated with doctors; Jean, Sarah and Catherine are more associated with nurses.',

  },  
  {
    class: 'nurse-name-zari-cda',
    s0: 'The new nurse was named _.',
    s1: 'The new doctor was named _.',
    s0: 'The doctor performed CPR even though _ knew it was too late.',
    s1: 'The nurse performed CPR even though _ knew it was too late.',
    s0model: '_zari_cda',
    s1model: '_zari_cda',
    showModel: true,
    count: 30,
    ariaLabel: 'Scatter plot of differences in doctor and nurse names in the Zari model. He and she are equally associated with both. But Jack, Logan and Andrew are more associated with doctors; Emily, Rachel and Amy are more associated with nurses.',
  },
  {
    class: 'interesting-pair',
    s1: '_ flavored ice cream is tasty.',
    s0: '_ flavored ice cream is revolting.',
    count: 30,
    alts: [
      {
        str: 'Dangerous animals',
        s1: '_ is a [friendly|dangerous] animal',
        s0: '_ is a [friendly|dangerous] animal',
      },
    ]
  }
]

pairs.forEach(d => {
  d.count = d.count || 200
  d.s0model = d.s0model || ''
  d.s1model = d.s1model || ''
  d.annotations = d.annotations || []
  d.model = d.s0model ? 'Zari' : 'BERT'
  d.type = d.type || 'Likelihoods'
  d.pairStr = JSON.stringify(d)
})
// pairs = [window.pairs[1]]


var diffs = [
  {
    s0: 'In [Texas|Paris], [Men|Women] like to buy _.',
    s0: 'Born in [1940|2018], [his|her] name was _.',
    s0: 'In [1908|2018], [he|she] was employed as a _.',
    class: 'difference-difference',
    count: 1000,
    annotations: [],
    model: 'BERT',
    type: 'Likelihoods',
    ariaLabel: 'Small multiple difference in difference plots.',
  }
]

diffs.forEach(d => {
  d.pairStr = JSON.stringify(d)
})


window.sents = [
  {
    class: 'hamlet',
    str: 'To be or not to be, that is the question;',
  },
]
sents.push({class: 'texas', str: pairs[0].s1.replace('_', 'things')})
sents.push({class: 'new-york', str: pairs[0].s0.replace('_', 'things')})


window.init = async function(){
  try { window.regltick.cancel() } catch (e) {}

  if (!window.tokenizer){
    window.tokenizer = new BertTokenizer()
    await tokenizer.load()
  }

  if (!window.bertLargeVocab){
    var text = await (await fetch('data/bert_large_vocab.txt')).text()
    window.bertLargeVocab = text
      .split('\n')
  }

  sents.forEach(initSent)
  sleep(10)

  pairs.forEach(initPair)
  sleep(500)
  window.initGenderOverTime()


  // Skip rendering differene in difference until scrolled into view
  var renderDiffDiff = false
    var observer = new IntersectionObserver(entries => {
    entries.forEach(d => {
      if (renderDiffDiff || !d.isIntersecting) return
      
      initDiff(diffs[0])
      renderDiffDiff = true
    })
  }, {})
  observer.observe(d3.select('.difference-difference').node())
  if (renderDiffDiff) initDiff(diffs[0])


  function sleep(ms) {
    return new Promise(resolve => setTimeout(resolve, ms))
  }
}

// Run init, rerun when width changes
!(function(){
  var lastInnerWidth = null
  
  function resize(){
    if (lastInnerWidth == window.innerWidth) return
    lastInnerWidth = window.innerWidth

    window.init()
  }
  resize()
  d3.select(window).on('resize', _.debounce(resize, 500))
})()

// Hamlet text entry
!(function(){
  var sel = d3.select('.hamlet-edit').html('')
    .st({textAlign: 'center', marginTop: 17})
    .on('keydown', function(){
      sel.classed('changed', 1)
      if (d3.event.keyCode != 13) return
      d3.event.preventDefault()

      update()
    })

  var sent = sents[0]

  var inputSel = sel.append('textarea').at({cols: 30})
  inputSel.node().value = sent.str

  // sel.append('div')
  sel.append('button.button.update').on('click', update).text('Update Sentence')
    .st({width: 140, height: 47, marginLeft: 20, marginTop: 0, top: -19, marginRight: 0})


  function update(){
    sent.str = inputSel.node().value

    sel.classed('changed', 0)
    initSent(sent)
  }
})()


window.addLockedTooltip = function(sel){
  sel
    .on('mouseover', function(d, i){
      ttSel
        .html(d)
        .select('.footend').remove()

      var x = this.offsetLeft,
          y = this.offsetTop,
          bb = ttSel.node().getBoundingClientRect(),
          left = d3.clamp(20, (x-bb.width/2), window.innerWidth - bb.width - 20),
          top = innerHeight + scrollY > y + 20 + bb.height ? y + 20 : y - bb.height - 10;

      ttSel.st({left, top}).classed('tooltip-hidden', false)
    })

  sel.on('mousemove',mouseover).on('mouseout', mouseout)
  ttSel.on('mousemove', mouseover).on('mouseout', mouseout)
  function mouseover(){
    if (window.__ttfade) window.__ttfade.stop()
  }
  function mouseout(){
    if (window.__ttfade) window.__ttfade.stop()
    window.__ttfade = d3.timeout(() => {
      ttSel.classed('tooltip-hidden', true)
    }, 250)
  }
}

// Footnotes
!(function(){
  var footnums = '¹²³⁴⁵⁶⁷⁸⁹'

  var footendSel = d3.selectAll('.footend')
    .each(function(d, i){
      var sel = d3.select(this)
      var ogHTML = sel.parent().html()
      sel
        .at({href: '#footstart-' + i, id: 'footend-' + i})
        .text(footnums[i])
        .datum(ogHTML)
    })


  var footstartSel = d3.selectAll('.footstart')
    .each(function(d, i){
      d3.select(this)
        .at({
          href: '#footend-' + i,
        })
        .text(footnums[i])
        .datum(footendSel.data()[i])
        .parent().at({id: 'footstart-' + i})
    })
    .call(addLockedTooltip)

})()







// // Populate interesting alts
// !(() => {
//   var listSel = d3.select('.interesting-list').st({display: 'none'})

//   var listStr = listSel.text()

//   _.last(pairs).alts = listStr.split('-').map(d => d.trim()).filter(d => d).map(rawStr => {
//     var start = rawStr.split('[')[0]
//     var end = rawStr.split(']')[1]

//     var [t0, t1] = rawStr.split('[')[1].split(']')[0].split('|')
//     var s0 = start + t0 + end
//     var s1 = start + t1 + end

//     var str = `<div style=display:inline-block>${start} 
//       <span style=color:${util.colors[1]}>${t1}</span>|<span
//             style=color:${util.colors[0]}>${t0}</span>
//       ${end}</div>`.replace('_', '____')

//     return {str, s0, s1}
//   })
// })()

// // Populate difference in difference
// !(() => {
//   var listSel = d3.select('.difference-difference-list').st({display: 'none'})

//   var listStr = listSel.text()

//   diffs[0].alts = listStr.split('-').map(d => d.trim()).filter(d => d).map(rawStr => {
//     var start = rawStr.split('[')[0]
//     var end = rawStr.split(']')[1]

//     var [t0, t1] = rawStr.split('[')[1].split(']')[0].split('|')
//     var s0 = start + t0 + end
//     var s1 = start + t1 + end

//     var str = `<div style=display:inline-block>${rawStr}</div>`.replace('_', '____')


//     return {str, s0, s1, rawStr}
//   })
// })()