Public
Edited
Feb 24, 2021
Type JavaScript, then Shift-Enter. Ctrl-space for more options. Arrow ↑/↓ to switch modes.
vl.markPoint()
.width(400).height(400)
.data(aes)
.encode(
vl.x().fieldQ('placebo_n'),
vl.y().fieldQ('gdnf_n'),
vl.tooltip().fieldN('adverse_events'),
vl.color().fieldQ('surprisal_bits').scale({scheme: 'turbo'}),
vl.size().fieldQ('seq').legend(false)
)
.render()
printTable(aes)
md`## *I<sub>q</sub>* via Fisher's *F* distribution`
function F(k, n, p) {
let odds = p/(1-p);
let x = (1/odds) * (k+1)/(n-k);
let df1 = 2*(n-k); // NB: Fails (appropriately) when k==n
let df2 = 2*(k+1);
return stdlib.stats.base.dists.f.cdf(x, df1, df2)
}
function S(x, y, odds) {
let p = odds/(odds+1)
let n = x+y
let tailprob = ( x/n < p ? F(x, n, p) : F(y, n, 1-p));
return -Math.log2(tailprob)
}
probtab = {
let N = 51;
var ptab = [];
for (var j = 1; j < N; ++j) {
for (var i = 1; i < N; ++i) {
let x = 10.0*i/N;
let y = 10.0*j/N;
ptab.push({ x : i, y : -j, S_bits : S(x,y,21/20) });
}
}
return ptab;
}
vl.markRect({tooltip: {"content": "data"}, clip: true})
.width(400).height(400)
.data(probtab)
.encode(
vl.y().fieldO('y').axis({labels:false}),
vl.x().fieldO('x').axis({labels:false}),
vl.color().fieldQ('S_bits').scale({ scheme: "turbo", reverse: false }),
)
.render()
md`## Data`
aes = {
const tableA8 = d3.tsvParse(rawData, d3.autoType);
const [, ...raw] = tableA8; // TODO: Remove 0th row, which is a precalculated margin
const aes = raw.map(r => Object.assign(r, { surprisal_bits : S(r.placebo_n,r.gdnf_n,r.placebo_N/r.gdnf_N) }));
var j = 3;
var aes2 = [Object.assign(aes[0], { seq : j*j })];
for (var i = 1; i < aes.length; ++i) {
if (aes[i].gdnf_n == aes[i-1].gdnf_n && aes[i].placebo_n == aes[i-1].placebo_n){
--j;
} else {
j = 3;
}
aes2.push(Object.assign(aes[i], { seq: j*j }));
}
return aes2;
}
d3 = require('d3@6')
stdlib = require('@stdlib/dist-tree')
import {vl} from '@vega/vega-lite-api'
import {printTable} from '@uwdata/data-utilities'
One platform to build and deploy the best data apps
Experiment and prototype by building visualizations in live JavaScript notebooks. Collaborate with your team and decide which concepts to build out.
Use Observable Framework to build data apps locally. Use data loaders to build in any language or library, including Python, SQL, and R.
Seamlessly deploy to Observable. Test before you ship, use automatic deploy-on-commit, and ensure your projects are always up-to-date.