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render.js
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render.js
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import * as Plot from '@observablehq/plot'
import * as d3 from 'd3'
import fs from 'fs'
import {JSDOM} from "jsdom";
const {window} = new JSDOM("")
const anonymous = false
// const anonymous = false
const egwalkerName = anonymous ? 'Feathertail' : 'Eg-walker'
const stem = process.cwd() === import.meta.dirname ? '..' : '.'
const savePlot = (plot, filename) => {
// plot.setAttribute('style', "background-color:green")
// plot.setAttribute('fill', "green")
// const svg = window.document.createElement('svg')
plot.setAttribute('xmlns', "http://www.w3.org/2000/svg")
plot.setAttribute('xmlns:xlink', "http://www.w3.org/1999/xlink")
plot.setAttribute('version', "1.1")
// console.log(plot.outerHTML)
// console.log(plot.innerHTML)
// plot.
fs.writeFileSync(`${stem}/diagrams/` + filename, plot.outerHTML)
console.log('wrote', `${stem}/diagrams/` + filename)
}
const loadJson = filename => JSON.parse(fs.readFileSync(`${stem}/${filename}`, 'utf8'))
const rawTimings = loadJson('results/timings.json')
let datasets = ["S1", "S2", "S3", "C1", "C2", "A1", "A2"]
// "automerge-paperx3",
// "seph-blog1x3",
// "node_nodeccx1",
// "friendsforeverx25",
// "clownschoolx25",
// "egwalkerx1",
// "git-makefilex2",
// ]
const dstype = { "S1": 'seq', "S2": 'seq', "A1": 'async', "A2": 'async', "C1": 'conc', "C2": 'conc', "S3": 'seq', }
const formatMs = (ms) => (
// ms < 1 ? `${roundAuto(ms * 1000)} μs`
ms < 1000 ? `${roundAuto(ms)} ms`
: ms < 60*1000 ? `${roundAuto(ms / 1000)} sec`
: `${roundAuto(ms / (60 * 1000))} min`
)
const KB = 1024
const MB = 1024 * 1024
const GB = 1024 * 1024 * 1024
const KiB = 1000
const MiB = 1000 * 1000
const GiB = 1000 * 1000 * 1000
const formatBytes = b => (
b >= GiB ? `${roundAuto(b/GiB)} GiB`
: b >= MiB ? `${roundAuto(b/MiB)} MiB`
: b >= KiB ? `${roundAuto(b/KiB)} KiB`
: `${roundAuto(b)} B`
)
// const formatBytes = b => (
// b >= GB ? `${roundAuto(b/GB)} GB`
// : b >= MB ? `${roundAuto(b/MB)} MB`
// : b >= KB ? `${roundAuto(b/KB)} KB`
// : `${roundAuto(b)} B`
// )
const roundN = (n, digits) => {
const m = Math.pow(10, digits)
return Math.round(n * m) / m
}
const roundAuto = n => {
const digits = n < 1 ? 2
: n > 100 ? 0
: 1
return roundN(n, digits)
}
const mean = list => (list.reduce((a, b) => a + b) / list.length)
const meanFor = (type, data) => (
{
type,
val: mean(datasets.map(name => (
typeof data === 'function' ? data(name) : data[name]
))),
}
)
const plotTimes = () => {
const algnames = {
dt: [egwalkerName],
dtmerge: [`${egwalkerName}`, "(merge)"],
dtload: [`${egwalkerName}`, "(cached load)"],
ot: ['OT'],
otmerge: ["OT", "(merge)"],
otload: ["OT", "(cached load)"],
dtcrdt: ["Ref CRDT"],
yjs: ["Yjs"],
automerge: ["Automerge"],
}
const data = [
...datasets.map(name => ({ dataset: name, type: 'dtmerge', val: rawTimings.dt_merge_norm[name], })),
...datasets.map(name => ({ dataset: name, type: 'dtload', val: rawTimings.dt_opt_load[name], })),
...datasets.map(name => ({ dataset: name, type: 'otmerge', val: rawTimings.ot[name], })),
...datasets.map(name => ({ dataset: name, type: 'otload', val: rawTimings.dt_opt_load[name], })),
...datasets.map(name => ({ dataset: name, type: 'dtcrdt', val: rawTimings['dt-crdt_process_remote_edits'][name], })),
...datasets.map(name => ({ dataset: name, type: 'automerge', val: rawTimings.automerge_remote[name], })),
...datasets.map(name => ({ dataset: name, type: 'yjs', val: rawTimings.yjs_remote[name], })),
]
const baseline = 1.2
// const means = [
// meanFor('dtmerge', rawTimings.dt_merge_norm),
// meanFor('dtload', rawTimings.dt_opt_load),
// meanFor('otmerge', rawTimings.ot),
// meanFor('otload', rawTimings.dt_opt_load),
// meanFor('dtcrdt', rawTimings['dt-crdt_process_remote_edits']),
// meanFor('automerge', rawTimings.automerge_remote),
// meanFor('yjs', rawTimings.yjs_remote),
// ] //.filter(m => m.val > baseline)
// console.log(data)
return Plot.plot({
figure: false,
document: window.document,
// marginLeft: 130,
marginLeft: 120,
// marginRight: 60,
// marginBottom: 40,
width: 500,
height: 580,
style: {
background: 'white',
// 'background-color': 'green',
// "font-size": "14px",
'font-family': 'Helvetica Neue, Helvetica, Arial, sans-serif',
},
fy: {
// paddingInner: 0.18,
},
// fy: {
// // tickRotate: '-90',
// label: null,
// tickFormat: (d, i, _) => algnames[d],
// // axis: 'left',
// },
y: {
// label: 'Algorithm',
// label: null,
// domain: data.map(d => d.dataset),
axis: null,
// tickFormat: 's',
// inset: 0.1,
// inset: 1.5,
// insetTop: 2,
marginLeft: 0,
},
x: {
label: 'Time taken (in milliseconds) to merge and reload changes. Log scale. (Less is better)',
fontSize: "20px",
grid: true,
domain: [baseline, 37000000],
// type: 'linear',
// nice: true,
type: 'log',
axis: 'bottom',
tickSpacing: 50,
// marginBottom: 40,
// labelOffset: 40,
// tickFormat: '1s',
// tickSize: 4,
// tickSpacing: 40,
// strokeOpacity: 1,
// tickFormat: (a, b, c) => `${formatMs(a)}`,
},
color: {
scheme: "Dark2"
},
marks: [
Plot.gridX({
strokeWidth: 0.5,
strokeOpacity: 0.15,
tickSpacing: 45,
}),
Plot.axisY({
// textAnchor: 'start',
// fill: 'white',
// dx: 10,
// ticks: null,
label: null,
fontSize: 8,
opacity: 0.4,
fontWeight: 700,
// inset: 5,
}),
// Plot.frame({
// fy: 'dt',
// // stroke: null,
// fill: 'green',
// opacity: 0.1,
// }),
// Plot.link(data, {
// y: 'dataset', fy: 'type',
// x1: d => Math.max(baseline, d.val.p10),
// // x2: d => Math.max(baseline, d.val.p90 * 2),
// x2: d => Math.max(baseline, d.val.p90),
// // stroke: 'black',
// }),
// Plot.ruleX(means.filter(m => m.val > baseline), {
// x: d => Math.max(d.val, baseline),
// fy: 'type',
// stroke: 'black',
// opacity: 0.4,
// strokeWidth: 1,
// inset: 2,
// }),
Plot.ruleX([1000/60], {stroke: '#800000', strokeOpacity: 0.5, inset: -4}),
Plot.barX(data, {
y: 'dataset',
fy: 'type',
x1: baseline,
x2: d => Math.max(d.val.mean, baseline),
// fill: 'type',
fill: d => dstype[d.dataset],
// sort: null,
sort: {y: null, color: null, fy: {type: "x"}},
// sort: d => ord.indexOf(d.dataset)
}),
// Plot.axisFy({
// fontSize: '15px',
// label: null,
// anchor: 'left',
// dx: -17,
// tickFormat: (d, i, _) => algnames[d],
// lineHeight: 1.2,
// // marginTop: 10,
// }),
Plot.axisFy({ // title
fontSize: '15px',
label: null,
anchor: 'left',
// dx: -52,
dx: -17,
dy: 2,
tickFormat: (d) => algnames[d][0],
// textAnchor: 'middle',
lineAnchor: 'bottom',
}),
Plot.axisFy({ // subtitle
fontSize: 12,
label: null,
anchor: 'left',
// dx: -52,
dx: -17,
dy: 7,
lineAnchor: 'top',
tickFormat: (d) => algnames[d][1],
// textAnchor: 'middle',
opacity: 0.7,
lineHeight: 1.1,
}),
Plot.tickX(data, {fy: 'type', x: d => Math.max(d.val.mean, baseline), y: "dataset"}),
Plot.text(data, {
y: 'dataset', fy: 'type',
x: d => Math.max(d.val.mean, baseline),
// text: d => d.val < baseline ? '<1ms' : `${formatMs(d.val)}`,
text: d => `${formatMs(d.val.mean)}`,
fontSize: 9,
textAnchor: 'start',
fill: 'black',
dx: 6,
}),
// Plot.textX(means, {
// x: d => Math.max(d.val, baseline),
// fy: 'type',
// text: d => `x̄ = ${formatMs(d.val)}`,
// fontWeight: 700,
// fontSize: 9,
// opacity: 0.6,
// frameAnchor: 'top',
// dy: -8,
// // textAnchor: 'bottom',
// }),
// Plot.text(data, {
// y: 'dataset', fy: 'type',
// x: baseline,
// textAnchor: 'start',
// dx: 3,
// fontWeight: 800,
// text: d => d.dataset,
// fill: 'white',
// }),
// Plot.text(data, {y: 'dataset', fy: 'type', text: (d) => (d.val * 100).toFixed(1), dx: -6, lineAnchor: "bottom"}),
// Plot.text(data, {
// text: d => `${Math.floor(d.value / 1000)} ms`,
// y: "type",
// x: "val",
// textAnchor: "end",
// dx: -3,
// fill: "white"
// }),
// Plot.text(data, {x: 'val', y: 'type', text: 'asdf', textAnchor: 'end', dx: 5}),
Plot.ruleX([baseline], {strokeWidth: 1.5}),
// Plot.ruleX([baseline], {
// dx: -22,
// strokeWidth: 1.5
// }),
// Plot.ruleY([0]),
]
})
}
const plotMemusage = () => {
const algnames = {
dtsteady: [`${egwalkerName}`, '(steady)'],
dtpeak: [`${egwalkerName}`, '(peak)'],
otsteady: ["OT", "(steady)"],
otpeak: ["OT", "(peak)"],
dtcrdt: ["Ref CRDT", ''],
yjs: ["Yjs", ''],
automerge: ["Automerge", ''],
}
const dtmem = loadJson("results/dt_memusage.json")
const dtcrdtmem = loadJson("results/dtcrdt_memusage.json")
const otmem = loadJson("results/ot_memusage.json")
const yjsmem = loadJson("results/yjs_memusage.json")
const ammem = loadJson("results/automerge_memusage.json")
const data = [
...datasets.map(dataset => ({ dataset, type: 'dtpeak', val: dtmem[dataset].peak, })),
...datasets.map(dataset => ({ dataset, type: 'dtsteady', val: dtmem[dataset].steady_state, })),
...datasets.map(dataset => ({ dataset, type: 'otpeak', val: otmem[dataset].peak, })),
...datasets.map(dataset => ({ dataset, type: 'otsteady', val: otmem[dataset].steady_state, })),
// Steady and peak are basically the same for the CRDT data sets
...datasets.map(dataset => ({ dataset, type: 'dtcrdt', val: dtcrdtmem[dataset].steady_state, })),
...datasets.map(dataset => ({ dataset, type: 'yjs', val: yjsmem[dataset].steady_state, })),
...datasets.map(dataset => ({ dataset, type: 'automerge', val: ammem[dataset].steady_state, })),
// ...datasets.map(dataset => ({ dataset, type: 'dtcrdtsteady', val: dtcrdtmem[dataset].steady_state, })),
// ...datasets.map(dataset => ({ dataset, type: 'otmerge', val: rawTimings.ot[dataset], })),
// ...datasets.map(dataset => ({ dataset, type: 'dtcrdt', val: rawTimings['dt-crdt_process_remote_edits'][dataset], })),
// ...datasets.map(dataset => ({ dataset, type: 'automerge', val: rawTimings.automerge_remote[dataset], })),
// ...datasets.map(dataset => ({ dataset, type: 'yjs', val: rawTimings.yjs_remote[dataset], })),
]
// const means = [
// meanFor('dtpeak', dataset => dtmem[dataset].peak),
// meanFor('dtsteady', dataset => dtmem[dataset].steady_state),
// meanFor('otpeak', dataset => otmem[dataset].peak),
// meanFor('otsteady', dataset => otmem[dataset].steady_state),
// meanFor('dtcrdt', dataset => dtcrdtmem[dataset].peak),
// meanFor('yjs', dataset => yjsmem[dataset].peak),
// meanFor('automerge', dataset => ammem[dataset].peak),
// ] //.filter(m => m.val > baseline)
// console.log(data)
const baseline = 60 * KB
return Plot.plot({
figure: false,
document: window.document,
// marginLeft: 130,
marginLeft: 110,
// marginRight: 60,
// marginBottom: 40,
width: 500,
height: 530,
style: {
background: 'white',
// 'background-color': 'green',
// "font-size": "14px",
'font-family': 'Helvetica Neue, Helvetica, Arial, sans-serif',
},
// facet: {
// margin: 10,
// },
// fy: {
// // tickRotate: '-90',
// label: null,
// tickFormat: (d, i, _) => algnames[d],
// // axis: 'left',
// },
fy: {
// paddingInner: 0.15,
},
y: {
// label: 'Algorithm',
// label: null,
// domain: data.map(d => d.dataset),
axis: null,
// tickFormat: 's',
// inset: 0.1,
},
x: {
label: 'RAM used, log scale. (Less is better)',
fontSize: "20px",
grid: true,
domain: [baseline, 20e9],
// type: 'linear',
// nice: true,
type: 'log',
// base: Math.pow(1024, 1/3),
axis: 'bottom',
// tickSpacing: 50,
// marginBottom: 40,
// labelOffset: 40,
// tickFormat: '1s',
// tickSize: 4,
// tickSpacing: 40,
// strokeOpacity: 1,
// tickFormat: (a, b, c) => (''+a).startsWith('1') ? formatBytes(a) : '',
tickFormat: (a, b, c) => formatBytes(a),
},
color: {
scheme: "Dark2"
},
marks: [
Plot.gridX({
strokeWidth: 0.5,
strokeOpacity: 0.15,
tickSpacing: 45,
}),
Plot.axisY({
// textAnchor: 'start',
// fill: 'white',
// dx: 10,
// ticks: null,
label: null,
fontSize: 8,
opacity: 0.4,
fontWeight: 700,
}),
// Plot.frame({
// fy: 'dt',
// // stroke: null,
// fill: 'green',
// opacity: 0.1,
// }),
// Plot.ruleX(means.filter(m => m.val > baseline), {
// x: d => Math.max(d.val, baseline),
// fy: 'type',
// stroke: 'black',
// opacity: 0.4,
// strokeWidth: 1,
// inset: 2,
// }),
Plot.barX(data, {
y: 'dataset',
fy: 'type',
x1: baseline,
x2: d => Math.max(d.val, baseline),
// fill: 'type',
fill: d => dstype[d.dataset],
// sort: null,
sort: {y: null, color: null, fy: {type: "x"}},
// sort: d => ord.indexOf(d.dataset)
}),
// Plot.axisFy({
// fontSize: '15px',
// label: null,
// anchor: 'left',
// dx: -17,
// tickFormat: (d, i, _) => algnames[d],
// lineHeight: 1.2,
// }),
Plot.axisFy({ // title
fontSize: '15px',
label: null,
anchor: 'left',
// dx: -52,
dx: -17,
dy: 2,
tickFormat: (d) => algnames[d][0],
// textAnchor: 'middle',
lineAnchor: 'bottom',
}),
Plot.axisFy({ // subtitle
fontSize: 12,
label: null,
anchor: 'left',
// dx: -52,
dx: -17,
dy: 7,
lineAnchor: 'top',
tickFormat: (d) => algnames[d][1],
// textAnchor: 'middle',
opacity: 0.7,
lineHeight: 1.1,
}),
Plot.ruleX([1000/60], {stroke: '#800000', strokeOpacity: 0.5}),
Plot.tickX(data, {fy: 'type', x: d => Math.max(d.val, baseline), y: "dataset"}),
Plot.text(data, {
y: 'dataset', fy: 'type',
x: d => Math.max(d.val, baseline),
// text: d => d.val < baseline ? '<1ms' : `${formatMs(d.val)}`,
text: d => `${formatBytes(d.val)}`,
fontSize: 8.5,
textAnchor: 'start',
fill: 'black',
dx: 6,
}),
// Plot.textX(means, {
// x: d => Math.max(d.val, baseline),
// fy: 'type',
// text: d => `x̄ = ${formatBytes(d.val)}`,
// fontWeight: 700,
// fontSize: 9,
// opacity: 0.6,
// frameAnchor: 'top',
// dy: -8,
// // textAnchor: 'bottom',
// }),
// Plot.text(data, {
// y: 'dataset', fy: 'type',
// x: baseline,
// textAnchor: 'start',
// dx: 3,
// fontWeight: 800,
// text: d => d.dataset,
// fill: 'white',
// }),
// Plot.text(data, {y: 'dataset', fy: 'type', text: (d) => (d.val * 100).toFixed(1), dx: -6, lineAnchor: "bottom"}),
// Plot.text(data, {
// text: d => `${Math.floor(d.value / 1000)} ms`,
// y: "type",
// x: "val",
// textAnchor: "end",
// dx: -3,
// fill: "white"
// }),
// Plot.text(data, {x: 'val', y: 'type', text: 'asdf', textAnchor: 'end', dx: 5}),
Plot.ruleX([baseline], {strokeWidth: 1.5}),
// Plot.ruleX([baseline], {
// dx: -22,
// strokeWidth: 1.5
// }),
// Plot.ruleY([0]),
]
})
}
const yjs_am_sizes = loadJson("results/yjs_am_sizes.json")
const dt_stats = loadJson("results/dataset_stats.json")
const plotSize = (algnames, data, totals, max, opts = {}) => {
return Plot.plot({
figure: false,
document: window.document,
// marginLeft: 130,
marginLeft: 110,
// marginRight: 60,
// marginBottom: 40,
width: 500,
height: 300,
...opts,
style: {
background: 'white',
// 'background-color': 'green',
// "font-size": "14px",
'font-family': 'Helvetica Neue, Helvetica, Arial, sans-serif',
},
// fy: {
// // tickRotate: '-90',
// label: null,
// tickFormat: (d, i, _) => algnames[d],
// // axis: 'left',
// },
y: {
// label: 'Algorithm',
// label: null,
// domain: data.map(d => d.dataset),
axis: null,
// tickFormat: 's',
// inset: 0.1,
},
x: {
label: 'Encoded size (lower is better)',
fontSize: "20px",
grid: true,
domain: [0, max],
type: 'linear',
// nice: true,
// type: 'log',
axis: 'bottom',
// tickSpacing: 50,
// marginBottom: 40,
// labelOffset: 40,
// tickFormat: '1s',
// tickSize: 4,
// tickSpacing: 40,
// strokeOpacity: 1,
// tickFormat: (a, b, c) => (''+a).startsWith('1') ? formatBytes(a) : '',
tickFormat: (a, b, c) => formatBytes(a),
},
color: {
scheme: "Dark2"
},
marks: [
Plot.gridX({
strokeWidth: 0.5,
strokeOpacity: 0.15,
tickSpacing: 45,
}),
Plot.axisY({
// textAnchor: 'start',
// fill: 'white',
// dx: 10,
// ticks: null,
label: null,
fontSize: 8,
opacity: 0.4,
fontWeight: 700,
}),
// Plot.frame({
// fy: 'dt',
// // stroke: null,
// fill: 'green',
// opacity: 0.1,
// }),
Plot.barX(data, {
y: 'dataset',
fy: 'type',
// x1: baseline,
x: 'val',
fill: d => dstype[d.dataset],
fillOpacity: d => ({
lowerbound: 0.5,
cache: 0.5,
overhead: 1,
})[d.t],
// fill: d => d.t == 'overhead' ? dstype[d.dataset] : 'red',
// fill: d => d.t == 'overhead' ? 'blue' : 'red',
// sort: null,
sort: {y: null, color: null, fy: {type: "x"}},
// sort: d => ord.indexOf(d.dataset)
}),
Plot.axisFy({ // title
fontSize: '15px',
label: null,
anchor: 'left',
dx: -52,
// dx: -17,
dy: -0,
tickFormat: (d) => algnames[d][0],
textAnchor: 'middle',
lineAnchor: 'bottom',
}),
Plot.axisFy({ // subtitle
fontSize: 12,
label: null,
anchor: 'left',
dx: -52,
dy: 6,
lineAnchor: 'top',
tickFormat: (d) => algnames[d][1],
textAnchor: 'middle',
opacity: 0.7,
lineHeight: 1.1,
}),
// Plot.tickX(data.filter(d => d.t == 'overhead'), {fy: 'type', x: 'aggregate', y: "dataset"}),
Plot.tickX(totals, {fy: 'type', x: 'val', y: "dataset"}),
Plot.text(totals, {
y: 'dataset', fy: 'type',
x: 'val',
// text: d => d.val < baseline ? '<1ms' : `${formatMs(d.val)}`,
text: d => `${formatBytes(d.val)}`,
fontSize: 9,
textAnchor: 'start',
fill: 'black',
dx: 6,
}),
// Plot.text(data, {
// y: 'dataset', fy: 'type',
// x: baseline,
// textAnchor: 'start',
// dx: 3,
// fontWeight: 800,
// text: d => d.dataset,
// fill: 'white',
// }),
// Plot.text(data, {y: 'dataset', fy: 'type', text: (d) => (d.val * 100).toFixed(1), dx: -6, lineAnchor: "bottom"}),
// Plot.text(data, {
// text: d => `${Math.floor(d.value / 1000)} ms`,
// y: "type",
// x: "val",
// textAnchor: "end",
// dx: -3,
// fill: "white"
// }),
// Plot.text(data, {x: 'val', y: 'type', text: 'asdf', textAnchor: 'end', dx: 5}),
Plot.ruleX([0], {strokeWidth: 1.5}),
// Plot.ruleX([baseline], {
// dx: -22,
// strokeWidth: 1.5
// }),
// Plot.ruleY([0]),
]
})
}
const plotSizeBig = () => {
const algnames = {
dt: [`${egwalkerName}`],
dtplus: [`${egwalkerName}`, '+ cached\nfinal doc'],
automerge: ["Automerge"],
}
const totals = [
...datasets.map(dataset => ({
dataset,
type: 'dt',
val: dt_stats[dataset].uncompressed_size,
})),
...datasets.map(dataset => ({
dataset,
type: 'dtplus',
val: dt_stats[dataset].uncompressed_size + dt_stats[dataset].final_doc_len_utf8,
})),
...datasets.map(dataset => ({
dataset,
type: 'automerge',
val: yjs_am_sizes[dataset].automergeUncompressed,
})),
]
const data = [
...datasets.map(dataset => ({
dataset,
type: 'dt',
val: dt_stats[dataset].ins_content_len_utf8,
t: 'lowerbound'
})),
...datasets.map(dataset => ({
dataset,
type: 'dt',
val: dt_stats[dataset].uncompressed_size - dt_stats[dataset].ins_content_len_utf8,
t: 'overhead',
})),
...datasets.map(dataset => ({
dataset,
type: 'dtplus',
val: dt_stats[dataset].ins_content_len_utf8,
t: 'lowerbound'
})),
...datasets.map(dataset => ({
dataset,
type: 'dtplus',
val: dt_stats[dataset].final_doc_len_utf8,
t: 'cache',
})),
...datasets.map(dataset => ({
dataset,
type: 'dtplus',
val: dt_stats[dataset].uncompressed_size - dt_stats[dataset].ins_content_len_utf8,
t: 'overhead',
})),
...datasets.map(dataset => ({
dataset,
type: 'automerge',
val: dt_stats[dataset].ins_content_len_utf8,
t: 'lowerbound'
})),
...datasets.map(dataset => ({
dataset,
type: 'automerge',
val: yjs_am_sizes[dataset].automergeUncompressed - dt_stats[dataset].ins_content_len_utf8,
t: 'overhead',
})),
]
// console.log(data)
return plotSize(algnames, data, totals, 2e6)
}
const plotSizeSmol = () => {
const algnames = {
dt: [`${egwalkerName}`, 'final doc text\nonly'],
yjs: ["Yjs"],
}
const data = [
...datasets.map(dataset => ({
dataset,
type: 'dt',
val: dt_stats[dataset].final_doc_len_utf8,
t: 'lowerbound'
})),
...datasets.map(dataset => ({
dataset,
type: 'dt',
val: dt_stats[dataset].uncompressed_smol_size - dt_stats[dataset].final_doc_len_utf8,
t: 'overhead',
})),
...datasets.map(dataset => ({
dataset,
type: 'yjs',
val: dt_stats[dataset].final_doc_len_utf8,
t: 'lowerbound'
})),
...datasets.map(dataset => ({
dataset,
type: 'yjs',
val: yjs_am_sizes[dataset].yjs - dt_stats[dataset].final_doc_len_utf8,
t: 'overhead',
})),
]
const totals = [
...datasets.map(dataset => ({
dataset,
type: 'dt',
val: dt_stats[dataset].uncompressed_smol_size,
})),
...datasets.map(dataset => ({
dataset,
type: 'yjs',
val: yjs_am_sizes[dataset].yjs,
})),
]
// console.log(data)
return plotSize(algnames, data, totals, 1.3e6, {
marginLeft: 120,
height: 230,
})
}
const plotFF = () => {
const algnames = {
ff_off: 'Opt disabled',
ff_on: 'Opt enabled',
}
const data = [
...datasets.map(dataset => ({ dataset, type: 'ff_on', val: rawTimings.dt_merge_norm[dataset].mean, })),
//...datasets.map(dataset => ({ dataset, type: 'ff_on', val: rawTimings.dt_ff_on[dataset], })),
...datasets.map(dataset => ({ dataset, type: 'ff_off', val: rawTimings.dt_ff_off[dataset].mean, })),
]
// const means = [
// meanFor('ff_on', rawTimings.dt_merge_norm),
// meanFor('ff_off', rawTimings.dt_ff_off),
// ] //.filter(m => m.val > baseline)
// console.log(data)
return Plot.plot({
figure: false,
document: window.document,
// marginLeft: 130,
marginLeft: 115,
// marginRight: 60,
// marginBottom: 40,
width: 500,
height: 200,
style: {
background: 'white',
// 'background-color': 'green',
// "font-size": "14px",
'font-family': 'Helvetica Neue, Helvetica, Arial, sans-serif',
},
// fy: {
// // tickRotate: '-90',
// label: null,
// tickFormat: (d, i, _) => algnames[d],
// // axis: 'left',
// },
y: {
// label: 'Algorithm',
// label: null,
// domain: data.map(d => d.dataset),
axis: null,
// tickFormat: 's',
// inset: 0.1,
},
x: {
label: 'Time taken to merge all events, in milliseconds. (Less is better)',
fontSize: "20px",
grid: true,
domain: [0, 105],
// type: 'linear',
// nice: true,
// type: 'log',
axis: 'bottom',
// tickSpacing: 50,
// marginBottom: 40,
// labelOffset: 40,
// tickFormat: '1s',
// tickSize: 4,
// tickSpacing: 40,
// strokeOpacity: 1,
// tickFormat: (a, b, c) => formatMs(a),
},
color: {
scheme: "Dark2"
},
marks: [
Plot.gridX({
strokeWidth: 0.5,
strokeOpacity: 0.15,
tickSpacing: 45,
}),
Plot.axisY({
// textAnchor: 'start',
// fill: 'white',
// dx: 10,
// ticks: null,
label: null,
fontSize: 8,
opacity: 0.4,
fontWeight: 700,
}),
// Plot.frame({
// fy: 'dt',
// // stroke: null,
// fill: 'green',
// opacity: 0.1,
// }),
// Plot.ruleX(means, {
// x: 'val',
// fy: 'type',
// stroke: 'black',
// opacity: 0.4,
// strokeWidth: 1,
// inset: 2,
// }),
Plot.barX(data, {
y: 'dataset',
fy: 'type',
x1: 0,
x2: d => Math.max(d.val, 0),
// fill: 'type',
fill: d => dstype[d.dataset],
// sort: null,
sort: {y: null, color: null, fy: {type: "x"}},
// sort: d => ord.indexOf(d.dataset)
}),
Plot.axisFy({
fontSize: '15px',
label: null,