Public
Edited
Mar 15
Paused
{
function m(d) {
let nextImpact = getNextImpactData(d);
let o = {fetched:d.fetched,...nextImpact,...d.summary,...nextImpact};
return o;
}
return objectHistory.map(m);
}
objectHistory.filter(d=>!d.data)
daysObserved = Number(objectDetails.summary.darc.split(" ")[0])
mutable objectDetails = null;
method = objectDetails.summary.method
objectHistory = rawHistory.results.map(d=>({fetched:d.fetched,...JSON.parse(d.text,)})).concat(oldData).map(canonicalizeDetails)
uniqueHistories.map(d=>d.data[0].ip)
uniqueHistories = d3.reverse(objectHistory).filter((d,i,a)=> {
if (!i) {
return true;
}
const d1 = canonicalizeDetails(a[i-1]);
delete d1.fetched ;
delete d1.summary.pdate;
const d2 = canonicalizeDetails(d);
delete d2.fetched
delete d2.summary.pdate;
return (JSON.stringify(d1) !== JSON.stringify(d2));
})
compareObjects(canonicalizeDetails(uniqueHistories.slice(-1)[0]),canonicalizeDetails(uniqueHistories.slice(-2)[0]))
compareObjects(canonicalizeDetails(objectHistory[0]),canonicalizeDetails(objectHistory[1]))
canonicalizeDetails(uniqueHistories[1])
canonicalizeDetails(uniqueHistories[2])
function compareObjects(o1,o2) {
let d1 = {};
let d2 = {};
Object.keys(o1).forEach(k=>{
if (k in o2) {
if (o1[k] === o2[k]) {
return ;
}
if (typeof(o1[k])== "object" && o1[k] && typeof(o2[k])== "object" && o2[k]) {
let c = compareObjects(o1[k],o2[k]);
if (Object.keys(c.d1).length) {
d1[k] = c.d1;
}
if (Object.keys(c.d2).length) {
d2[k] = c.d2;
}
return;
}
d1[k] = o1[k];
d2[k] = o2[k]
}
else {
d1[k] = o1[k];
}
});
Object.keys(o2).forEach(k=>{
if (!(k in o1)) {
d2[k] = o2[k];
}
});
return {d1,d2};
}
{
while (true) {
yield await checkForChanges() ;
yield Promises.tick(5*1000*60);
}
}
function getNextImpactData(objDetails) {
return d3.sort(objDetails.data,d=>d.date)[0];
}
config =({
apiURL: "https://ssd-api.jpl.nasa.gov/sentry.api",
objDes: "2024%20YR4",
});
async function getObjectDetails(des, trackChanges = false) {
let url = config.apiURL + "?des=" + des;
url = getProxyURL(url, false, trackChanges);
const response = await fetch(url);
let json = await response.json();
return canonicalizeDetails(json);
}
JSON.stringify(null)
async function checkForChanges(){
if (!objectDetails || objectDetailsJSON === "null") {
return {};
}
let newObjectDetails = await getObjectDetails(config.objDes);
let d = canonicalizeDetails(newObjectDetails) ;
delete d.fetched;
let newObjectDetailsJSON = JSON.stringify(d);
let changed = newObjectDetailsJSON !== objectDetailsJSON;
if (changed) {
let oldObjectDetails = objectDetails;
mutable objectDetails = newObjectDetails;
let newObjectDetails2 = getObjectDetails(config.objDes, true);
let d = canonicalizeDetails(newObjectDetails2) ;
delete d.fetched;
let newObjectDetails2JSON = JSON.stringify(d);
let changed2 = newObjectDetailsJSON !== newObjectDetails2JSON;
let changedBack = objectDetailsJSON == newObjectDetails2JSON;
console.log("new objectDetails",{changed, changed2, changedBack, oldObjectDetails, newObjectDetails, newObjectDetails2});
if (changed2) {
mutable objectDetails = newObjectDetails2;
return {changed, ...newObjectDetails2};
}
}
else {
console.log("objectDetails unchanged");
}
return {changed, ...newObjectDetails};
}
rawHistory = getHistory()
{
if (objectHistory && objectHistory.length && !objectDetails) {
mutable objectDetails = objectHistory[0];
}
}
oldData = d3.sort([
{
fetched: 1736105294000,
url: "https://web.archive.org/web/20250105112814/https://ssd-api.jpl.nasa.gov/sentry.api?des=2024%20YR4&www=1",
"summary": {
"h": "23.86",
"fullname": "(2024 YR4)",
"nsat": "0",
"first_obs": "2024-12-26",
"mass": "2.52e+08",
"ps_max": "-1.61",
"v_inf": "13.26",
"energy": "9.019e+00",
"last_obs": "2025-01-04",
"ndop": 0,
"ndel": 0,
"method": "IOBS",
"nobs": 137,
"n_imp": 8,
"cdate": "2025-01-04 11:30:30",
"des": "2024 YR4",
"ps_cum": "-1.48",
"diameter": "0.057",
"darc": "8.9206 days",
"pdate": "2025-01-04 23:55:08",
"v_imp": "17.32",
"ip": "0.001359994838",
"ts_max": "1"
},
"signature": {
"version": "2.0",
"source": "NASA/JPL Sentry Data API"
},
"data": [
{
"ts": "0",
"ps": "-6.64",
"sigma_vi": "0.7151",
"energy": "8.775e+00",
"ip": "2.796e-08",
"date": "2047-12-22.05"
},
{
"ts": "0",
"sigma_vi": "0.6821",
"ps": "-5.95",
"ip": "8.765e-08",
"date": "2039-12-23.35",
"energy": "9.022e+00"
},
{
"ts": "0",
"ps": "-7.47",
"sigma_vi": "0.7318",
"energy": "8.993e+00",
"date": "2043-12-23.18",
"ip": "3.302e-09"
},
{
"sigma_vi": "0.6830",
"ps": "-8.07",
"energy": "8.889e+00",
"ip": "2.457e-09",
"date": "2079-12-22.73",
"ts": "0"
},
{
"ts": "0",
"energy": "8.791e+00",
"date": "2047-12-22.07",
"ip": "7.569e-09",
"sigma_vi": "0.7463",
"ps": "-7.20"
},
{
"ip": "1.659e-07",
"date": "2047-12-22.05",
"energy": "8.778e+00",
"ps": "-5.86",
"sigma_vi": "0.6998",
"ts": "0"
},
{
"energy": "9.036e+00",
"date": "2032-12-22.62",
"ip": "3.377e-04",
"ps": "-2.09",
"sigma_vi": "0.7295",
"ts": "0"
},
{
"ts": "1",
"energy": "9.014e+00",
"ip": "1.022e-03",
"date": "2032-12-22.59",
"sigma_vi": "0.6629",
"ps": "-1.61"
}
]
},
{fetched: 1737566113000, url:"https://web.archive.org/web/20250122091513/https://ssd-api.jpl.nasa.gov/sentry.api?des=2024%20YR4&www=1","signature":{"version":"2.0","source":"NASA/JPL Sentry Data API"},"data":[{"ts":"0","ip":"3.410e-09","ps":"-7.84","energy":"8.282e+00","sigma_vi":"0.0713","date":"2067-06-22.73"},{"ts":"0","ip":"2.806e-09","ps":"-7.97","energy":"8.296e+00","sigma_vi":"3.0660","date":"2071-06-22.72"},{"ts":"0","ip":"1.464e-07","ps":"-5.95","energy":"8.088e+00","sigma_vi":"0.1432","date":"2047-12-22.05"},{"ts":"0","ip":"8.672e-07","energy":"8.091e+00","ps":"-5.17","sigma_vi":"0.0810","date":"2047-12-22.05"},{"ip":"4.567e-07","ps":"-5.26","energy":"8.315e+00","ts":"0","date":"2039-12-23.35","sigma_vi":"0.0164"},{"ip":"5.213e-03","ps":"-0.93","energy":"8.308e+00","ts":"1","date":"2032-12-22.59","sigma_vi":"0.0702"}],"summary":{"cdate":"2025-01-21 07:27:44","mass":"2.33e+08","h":"23.92","n_imp":6,"nsat":"0","ndel":0,"v_imp":"17.32","ndop":0,"first_obs":"2024-12-25","v_inf":"13.26","ps_cum":"-0.93","method":"IOBS","ts_max":"1","des":"2024 YR4","diameter":"0.056","fullname":"(2024 YR4)","pdate":"2025-01-21 15:50:50","nobs":206,"darc":"26.836 days","last_obs":"2025-01-21","ps_max":"-0.93","ip":"0.005214476516","energy":"8.308e+00"}}
],
d=>-d.fetched)
async function getHistory(des = config.objDes) {
objectDetails;
let url = config.apiURL + "?des=" + des;
console.log("getting history of "+url);
let r = await getURLhistory(url);
return r;
}
function isObject(obj) {
return typeof obj === 'object' && obj !== null;
}
function canonicalizeDetails(o) {
return {
data: d3.sort(o.data,d=>d.date, d=>d.ps).map(deepCopyWithSort),
signature:deepCopyWithSort(o.signature),
summary: deepCopyWithSort(o.summary),
fetched: o.fetched,
}
}
objectHistory[0]
function deepCopyWithSort(i) {
if (! isObject(i)) {
return i;
}
if (Array.isArray(i)) {
return i.map(deepCopyWithSort);
}
let o = {};
d3.sort(Object.keys(i)).forEach(k=>{
o[k] = deepCopyWithSort(i[k]);
});
return o;
}
canonicalizeDetails(objectDetails)
objectDetailsJSON = {
let d = canonicalizeDetails(objectDetails) ;
delete d.fetched;
return JSON.stringify(d);
}
viewof sigmaRange = Inputs.range([0.005, 2], {label: "Sigma", step: 0.005, value:1})
viewof xRange = Inputs.range([-1, 0], {label: "Distance from mean", step: 0.01, value:-1})
viewof radiusOfImpact = Inputs.range([0.001, 0.2], {label: "Radius for impact", step: 0.001, value:0.01})
daysUntilImpact = 8*365.25 - 4;
randDataSigma = 1;
function pathProb(samples,sigma,line,) {
let p = 1;
samples.forEach((sample,i)=>{
p = updatePathProb(p,sample,sigma,line);
});
return p;
}
function updatePathProb(p,sample,sigma,line,) {
const lineY = line.intercept + line.slope * sample.x;
const pi = normDistUnscaled(sample.y-lineY,0,sigma);
return p * pi;
}
function updatePathProbs(sample,sigma, a=pathProbs){
let finalProbs = {};
let totalP = 0;
a.forEach(d=>{
d.p = updatePathProb(d.p,sample,sigma,d.line);
finalProbs[d.line.finalY] = (finalProbs[d.line.finalY] || 0) + d.p;
totalP += d.p;
});
let probData = Object.entries(finalProbs).map(kv=>{
let y = Number(kv[0]);
let p = kv[1]/totalP;
return {
x: sample.x,
y,
p
};
});
return probData;
}
allFinalProbs = calcAllFinalProbs()
function calcAllFinalProbs(samples=randData, sigma=1, pathProbs=null) {
if (!pathProbs) {
pathProbs = initPathProbs();
}
//return pathProbs;
let a = [];
samples.forEach(sample=>{
// TODO: Find peak probability and position of it
a.push(updatePathProbs(sample,sigma,pathProbs));
});
return a;
}
positionDist = d3.randomNormal(0,randDataSigma);
randData = {
let data = d3.range(0,daysUntilImpact).map(x=>{
let y = positionDist();
return {
x,
y,
};
});
return data;
}
function changeDay(day) {
randData[day].y = positionDist();
return randData[day].y;
}
dayChanged = changeDay(daysRange-1);
viewof daysRange = Inputs.range([2, daysUntilImpact], {label: "Days of observation", step: 1, value: Math.floor(daysObserved)})
{
return "disabled";
dayChanged;
let plotData = finalProbs;
let p0 = plotData.find(d=>d.y==0).p;
let p2 = plotData.find(d=>d.y==2).p;
let pm2 = plotData.find(d=>d.y==-2).p;
//return plotData;
return Plot.plot({
title: "Predicted probability of final position with " + daysRange + " days of observation.",
subtitle: html`P(-2): ${Math.round(pm2*100000)/1000}%<br>P(0): ${Math.round(p0*100000)/1000}%<br>P(2): ${Math.round(p2*100000)/1000}%`,
marginLeft: 55,
marginRight: 55,
width,
x: {
grid: true,
label: "Position"
},
y: {
label: "Probability",
grid: true,
percent: true,
},
marks: [
Plot.dot(plotData, {x: d=>d.y, y: d=>d.p, tip:true}),
]
});
}
peakFinalProb = finalProbs[d3.maxIndex(finalProbs,d=>d.p)]
finalProbs = calcFinalProbs(randData,daysRange);
function calcFinalProbs(data, days) {
let regData = data.slice(0,days);
let y0max = 4/Math.sqrt(days);
//let yFinalMax = 3*y0max * daysUntilImpact / days ;
//let yFinalMax = 2*Math.sqrt(daysUntilImpact);
let yFinalMax = 100;
let steps = 100;
let totalP = 0;
let r = {};
for (let y0 = -y0max ; y0 <= y0max ; y0 += y0max/steps*2) {
for (let y1 = -yFinalMax ; y1 <= yFinalMax ; y1 += yFinalMax/steps*2) {
let slope = (y1 - y0) / daysUntilImpact ;
let p = pathProb(regData,randDataSigma,{intercept:y0,slope, finalY:y1});
totalP += steps*p;
r[y1] = (r[y1] || 0) + steps*p;
}
}
let probData = Object.entries(r).map(kv=>{
return {
y: Number(kv[0]),
p: kv[1]/totalP
};
});
return probData;
}
pathProbs = initPathProbs()
{
return "disabled";
let data = randData ;
let days = daysRange;
let regData = data.slice(0,days);
let dataLM = new ML.SimpleLinearRegression(regData.map(x), regData.map(y));
console.log(dataLM);
let dataCorr = dataLM.score(regData.map(x), regData.map(y));
console.log(dataCorr);
regData.push({
x: daysUntilImpact,
y: dataLM.intercept + dataLM.slope * daysUntilImpact
});
let regLine = [
{x: 0, y:dataLM.intercept},
{x: daysUntilImpact, y:dataLM.intercept + dataLM.slope * daysUntilImpact},
]
//return data;
data.forEach((d,i,a)=>{
});
function y(d) {
return d.y;
}
function x(d) {
return d.x;
}
//return data;
return Plot.plot({
title: "Position at day",
marginLeft: 55,
marginRight: 55,
width,
x: {
grid: true,
label: "Day"
},
y: {
label: "Observed position offset from actual",
grid: true,
percent: false,
},
marks: [
Plot.dot(data, {x, y, opacity: d=>d.x < days ? 1: 0.1 , tip:true}),
Plot.linearRegressionY(data.slice(0,days), {x, y}),
Plot.line(regLine, {x, y, tip:false}),
]
});
}
function normDist(x,mean=0,sigma=1) {
const x1 = (x - mean)/sigma;
const a = 1 / Math.sqrt(2*Math.PI)/sigma;
return Math.exp(-x1*x1/2) * a ;
}
function normDistUnscaled(x,mean=0,sigma=1) {
const x1 = (x - mean)/sigma;
return Math.exp(-x1*x1/2) ;
}
ML = require("https://www.lactame.com/lib/ml/6.0.0/ml.min.js")
constants = ({
au: 149597870700, // meters https://en.wikipedia.org/wiki/Astronomical_unit
ld: 385000000, // https://en.wikipedia.org/wiki/Lunar_distance
})
constants.au / constants.ld
Purpose-built for displays of data
Observable is your go-to platform for exploring data and creating expressive data visualizations. Use reactive JavaScript notebooks for prototyping and a collaborative canvas for visual data exploration and dashboard creation.
