md`# Region rings ${filterString} ${regionName}`
// Set to either "inside" or "outside" to see paths
// staying comopletely inside the region or paths going outside the
// region, respectively
filterString = "inside"
filterType = ({ "inside": inFilter, "outside": outFilter })[filterString]
regionName = region.charAt(0).toUpperCase() + region.slice(1).replace("-"," ");
regionCountries = ["KZ", //Kazakhstan
"KG", // Kyrgyzstan
"TJ", // Tajikistan
"TM", // Turkmenistan
"UZ"
]
excludeProbes=[];
center = turf.envelope(prbGeoJson)
filteredPaths = lineLocs.geo.features.filter(p => enduserAsns.some(asn => {
let mp = probes.find(pp => pp.probe_id === p.properties.src_prb_id || pp.probe_id===p.properties.src_prb_id);
return mp ? (asn===mp.asn_v4 || asn===mp.asn_v6) : false;
})).filter(f => !excludeProbes.some(prbId => prbId===f.properties.dst_prb_id || prbId===f.properties.src_prb_id))
md`### stats`
[d3.min(filteredPaths, d => d.properties.pathLength), d3.max(filteredPaths, d => d.properties.pathLength), d3.median(filteredPaths, d => d.properties.pathLength)]
maxFarthestCount = d3.max(ffLocs, d => d.properties.aggFarthestCount) || d3.max(ffLocs, d => d.properties.farthestCount);
minFarthestCount = d3.min(ffLocs, d => d.properties.aggFarthestCount) || d3.min(ffLocs, d => d.properties.farthestCount);
// Specify either inFilter or outFilter here, so you'll see only the farthest Locations and transit Locations inside the SEE region or outside of it.
// ooc = lineLocs.locations.filter(inFilter);
outFilter = c => { const cc = c.properties.countryCodeAlpha2; return !regionCountries.some(ccc => ccc === cc)}
inFilter = c => { const cc = c.properties.countryCodeAlpha2; return regionCountries.some(ccc => ccc === cc)}
oocGeoIps = lineLocs.geo.features
.flatMap(s => s.properties.locationString)
//.filter(ls => ooc.some(ll => ll.id===ls.locationId))
.reduce((locIps, locIp) => {
let eLocIp = locIps.indexOf(locIps.find(li => li.locationId === locIp.locationId));
if (eLocIp===-1) {
locIps = [...locIps, {locationId: locIp.locationId, ips: [locIp.ip], passThroughCount: 1}]
}
else {
locIps[eLocIp] = {
locationId: locIps[eLocIp].locationId,
passThroughCount: ++locIps[eLocIp].passThroughCount,
ips: Array.from(new Set([...locIps[eLocIp].ips, locIp.ip]))};
}
return locIps;
},[]);
asns = probes.reduce((asnArr, p) => {
let asn_v4 = asnArr.asn_v4.find(ac => ac.asn===p.asn_v4);
if (asn_v4) {
asn_v4.count++
} else {
asnArr.asn_v4.push({ asn: p.asn_v4, count: 1});
}
let asn_v6 = asnArr.asn_v6.find(ac => ac.asn===p.asn_v6);
if (asn_v6) {
asn_v6.count++
} else {
asnArr.asn_v6.push({ asn: p.asn_v6, count: 1});
}
return asnArr;
}, {asn_v4:[], asn_v6:[]});
// All farthest locations with passtroughCount and farthesLocationCount.
fLocs = lineLocs.geo.features.map(s => s.properties.farthestLocation[0]).reduce((ffLocs, loc) => {
let eLoc = ffLocs.indexOf(ffLocs.find(li => li.locationId === loc));
if (eLoc===-1) {
ffLocs = [...ffLocs, {locationId: loc, farthestCount: 1}];
}
else {
ffLocs[eLoc] = { locationId: ffLocs[eLoc].locationId, farthestCount: ++ffLocs[eLoc].farthestCount }
}
return ffLocs;
},[])
.map(lId => {
let loc = lineLocs.locations.find(ll => ll.id===lId.locationId);
return loc && {
type: 'Feature',
properties: {
...loc,
passThroughCount: oocGeoIps.find(ll => ll.locationId===lId.locationId).passThroughCount,
farthestCount: lId.farthestCount,
medianPathLength: d3.median(filteredPaths.filter(p => p.properties.farthestLocation[0]===lId.locationId).map(p => p.properties.pathLength))
},
geometry: {
type: 'Point',
coordinates: [loc.longitude, loc.latitude]
}
}
}).filter(l => l);
scan = turf.clustersDbscan({ type: "FeatureCollection", features: fLocs }, 30, {minPoints: 2});
// clustered locations, set 2nd arg in scan for clustering radius.
ffLocs = scan.features.reduce(
(ffLocs, loc) => {
let cluster = scan.features.filter(ll => ll.properties.cluster === loc.properties.cluster);
if (loc.properties.dbscan === "noise") {
ffLocs.push(loc);
};
if (loc.properties.cluster>=0) {
if (
cluster.every(ll => ll.properties.cityPopulation <= loc.properties.cityPopulation)
) {
ffLocs.push({
...loc,
properties: {
...loc.properties,
aggPassThroughCount: cluster.reduce((count, cm) => count + cm.properties.passThroughCount, 0),
aggFarthestCount: cluster.reduce((count, cm) => count + cm.properties.farthestCount, 0),
avgMedianPathLength: d3.mean(cluster.map(cm => cm.properties.medianPathLength))
}
});
}
}
return ffLocs; },[]).sort((a,b) => a.properties.farthestCount > b.properties.farthestCount && -1 || 1)
// specify inFilter (locations in SEE only) or outFilter (locations outside SEE only)
.filter(filterType);
probeCenter = turf.center(prbGeoJson);
region = "central-asia"
mapScale= 850
map = html`<h1>Paths ${filterString} ${regionName}</h1><svg viewBox="0 0 ${width} ${height}" style="display: block;">
<style>
.world { stroke: #eeeeee; stroke-width: 0.5; fill-opacity: 0.3 }
.hop-loc { fill: none; stroke-width: 1.5; stroke: black; }
.probe-loc { stroke-width: 2; stroke: none; fill: white; fill-opacity: 0.8 }
.l-path { fill: none; stroke-width: 2; stroke: lightBlue; }
.kreis { fill-opacity: 0.8; }
.bunch-of-lines { stroke: black; stroke-width: 0.2; fill: none; stroke-opacity: 1; }
.f-locs { fill: white; fill-opacity: 0.6; stroke: black; stroke-width: 1; }
.pt-locs { fill: none; stroke: #a2cade; }
.e-line { fill: none; stroke: #ff8e19; stroke-opacity: 0.7; }
.probe-center { fill: none; stroke: none; }
.cc-name { fill: white; stroke: none; font: normal 14px arial; }
</style>
<defs>
<path id="outline" d="${path(outline)}" />
<clipPath id="clip"><use xlink:href="${new URL("#outline", location)}" /></clipPath>
</defs>
<g class="world" clip-path="url(${new URL("#clip", location)})">
<use xlink:href="${new URL("#outline", location)}" fill="#fff" />
${land.features.filter(c => { const cc = c.properties.countryCode; return regionCountries.find(ccc => ccc === cc) }).map(l => { const center = projection(turf.centerOfMass(l.geometry).geometry.coordinates); return `<path class="kreis" d="${path(l.geometry)}" style="fill: ${popKreisColor(l.properties.pop_density)}"></path><text class="cc-name" x=${center[0]} y=${center[1]}>${l.properties.countryCode}</text>`; })}
</g>
<g>${filterString === "outside" && ffLocs.map(l => {
let eCoords = projection(l.geometry.coordinates);
let bCoords = projection(probeCenter.geometry.coordinates);
//d="M 10 10 H 90 V 90 H 10 L 10 10"
return `<line class="e-line" x1="${bCoords[0]}" y1="${bCoords[1]}" x2="${eCoords[0]}" y2="${eCoords[1]}" style="stroke-width: ${farthestLine(l.properties.farthestCount)};"/>`;
})}</g>
<g>${ffLocs.map(l => { let coords = projection(l.geometry.coordinates);
return `<circle class="pt-locs" r="${farthestScale(l.properties.aggPassThroughCount || l.properties.passThroughCount)}" cx="${coords[0]}" cy="${coords[1]}"/><circle class="f-locs" style="fill: ${pathLengthScale(l.properties.avgMedianPathLength || l.properties.medianPathLength)}" r="${farthestScale(l.properties.aggFarthestCount || l.properties.farthestCount)}" cx="${coords[0]}" cy="${coords[1]}"/><text x="${coords[0]}" y="${coords[1]}">${l.properties.cityName !== "Astana" && l.properties.cityName || "Nur-Sultan"}</text>`})}
</g>
<g><circle class="probe-center" cx="${projection(probeCenter.geometry.coordinates)[0]}" cy="${projection(probeCenter.geometry.coordinates)[1]}" r="5"/></g>
<use xlink:href="${new URL("#outline", location)}" fill="none" stroke="#000" />
</svg>`
// radical researcher
// jediIxp="#ff8e19"
// jediTransit="#a2cade";
// jediEyeballs="#64d46a";
// jediEyeballsNoProbes="#dcede6";
// jediAnthracite="#363738";
// html`<svg><g class="bunch-of-lines">${filteredPaths.map(s => `<path d="${path(s)}" style="stroke: ${stringColor[s.properties.idx % stringColor.length]};"/>`)}</g></svg>`
farthestScale = d3.scaleLinear()
.domain([1, maxFarthestCount])
.range([2, 30]);
farthestLine = d3.scaleLinear()
.domain([1, maxFarthestCount])
.range([0.2, 60])
pathLengthScale = d3.scaleLinear()
.domain([30, 500, 1800])
.range(["#64d46a","yellow","#ff0000"])
height = 800
popKreisColor = d3.scaleLinear()
.domain([30, 580])
.range(["#ffffff", "#cccccc"])
.interpolate(d3.interpolateLab);
stringColor =["#1f77b4","#ff7f0e","#2ca02c","#d62728","#9467bd","#8c564b","#e377c2","#7f7f7f","#bcbd22","#17becf"]
projection = d3.geoMercator()
lineLocs = fetch(`https://sg-pub.ripe.net/jasper/central-asia-cr/region-jedi.linestrings.geo.json`).then(d => d.json(), e => console.log(e));
probes = fetch(`https://sg-pub.ripe.net/jasper/central-asia-cr/${region}_probes.json` ).then(d => d.json())
apnic_file = fetch("https://sg-pub.ripe.net/jasper/central-asia-cr/pop_coverage_v2.json").then(d => d.json())
enduserAsns = apnic_file.filter(d => regionCountries.find(c => c===d.country)).flatMap(d => d.eyeball_networks).map(en => en.as)
world = fetch("https://sg-pub.ripe.net/jasper/see-cr/openipmapCountries_50m.topo.json").then(r => r.json())
land = topojson.feature(world, world.objects["openipmapCountries_50m"])
outline = ({type: "Sphere"})
turf = require("https://npmcdn.com/@turf/turf@5.1.6/turf.js")
d3 = require("d3@5")
topojson = import("topojson-client@3")
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