Fil/.block

## .block
license: mit

## README.md

      
    Raw
  

              README.md
            
          
    Working on Visionscarto.net sitemap.
From tf/idf on articles keywords, compute a cosine similarity, feed that to t-SNE, k-means coloring, extraction of main term(s) per k-means center.
Original work by Philippe Rivière for Visionscarto.net. Comments and variants very welcome!
Forked from Fil's block: t-SNE with Levenshtein distances

  
## index.html
<!DOCTYPE html>

<head>
    <meta charset="utf-8">
    <script src="https://d3js.org/d3.v4.min.js"></script>

    <style>
        body {
            margin: 0;
            position: fixed;
            top: 0;
            right: 0;
            bottom: 0;
            left: 0;
          font-family: monospace;
        }
    </style>
</head>

<body>
<script>
    const width = 960,
        height = 500,
        margin = { top: 20, bottom: 20, left: 120, right: 120 },
        scalepop = d3.scalePow().exponent(1/2.5).domain([1, 10000]).range([0, 15]),
        scalepop2 = d3.scaleLog().domain([1, 1000]).range([0, 20]),
        scalecountry = d3.scaleOrdinal(d3.merge([d3.schemeCategory10, d3.schemeCategory20c])),
        centerx = d3.scaleLinear()
        .range([margin.left, width - margin.right]),
        centery = d3.scaleLinear()
        .range([margin.top, height - margin.bottom]);
const voronoi = d3.voronoi();
  let tfidf;

    d3.json('plan.json', function (articles) {
        const data = articles
            .map((d, i) => {
              return {
                lon: Math.random(),
                lat: Math.random(),
                name: d['title'].replace(/&#\d+;/g, '’'),
                props: d3.set(d3.merge([ [ "trad" + (d.trad || d.id) ], d.authors, d.tags ])).values(),
                //props: d['title'].substring(0,1),
                r: scalepop(+d['views']) + scalepop2(+d['pop']+1),
                p: scalepop2(+d['popularity']),
                color: scalecountry(''+d.authors)
              };
            })
        .slice(0,400);

      /*
      const canvas = d3.select("body").append("canvas")
            .attr("width", width)
            .attr("height", height);
       */
        const svg = d3.select("body").append("svg")
            .attr("width", width)
            .attr("height", height);

      const lines = svg.append('g');
      const garticles = svg.append('g');
      const gmeans = svg.append('g');

        // pos is the array of positions that will be updated by the tsne worker
        // start with the geographic coordinates as is (plate-carrée)
        // random or [0,0] is fine too
        let pos = data.map(d => [Math.random(), Math.random()]);

  var K = 20,
      centers = d3.range(K).map(i => [0,0]),
      colorscale = d3.scaleOrdinal(d3.schemeCategory20c);

      let links = [];

        const forcetsne = d3.forceSimulation(
          data.map(d => (d.x = width / 2, d.y = height / 2, d))
        )
        //.stop()
            .alphaDecay(0.001)
            .alpha(0.1)
            .force('tsne', function (alpha) {
                centerx.domain(d3.extent(pos.map(d => d[0])));
                centery.domain(d3.extent(pos.map(d => d[1])));

                data.forEach((d, i) => {
                    d.x += alpha * (centerx(pos[i][0]) - d.x);
                    d.y += alpha * (centery(pos[i][1]) - d.y);
                });
            })

        .force('collide', d3.forceCollide().radius(d => 1 * (1.5 + d.r)))

        .force('kmeans', function(){

          // a central point to re-init empty groups
          var m = [d3.mean(centers.map(d => d[0] || 0)),
                   d3.mean(centers.map(d => d[1] || 0))];

          // the order is important: move the centers before re-making the groups
          // so that the centers follow the general movement and keep "their"
          // points, instead of having points pass through them

          // 1. move K-centers towards the barycenter of their group
          centers.forEach((c,i) => {
            c[0] = d3.mean(pos.filter((d,j) => data[j].group == i).map(d => d[0])) || m[0];
            c[1] = d3.mean(pos.filter((d,j) => data[j].group == i).map(d => d[1])) || m[1];
          });

          // 2. group each point according to its closest K-center
          data.forEach((d,i) => {
             d.group = d3.scan(centers.map(c => {
               var dx = pos[i][0] - c[0],
                   dy = pos[i][1] - c[1];
               return  (dx*dx + dy*dy);
             }));
          });

        }
      )
        .on('tick', function () {

              // drawcanvas(canvas, data);
              drawsvg(garticles, data);
              drawlines(lines, links);
              drawgmeans(gmeans, centers);
            });

        function drawcanvas(canvas, nodes) {
            let context = canvas.node().getContext("2d");
            context.clearRect(0, 0, width, width);

            for (var i = 0, n = nodes.length; i < n; ++i) {
                var node = nodes[i];
                context.beginPath();
                context.moveTo(node.x, node.y);
                context.arc(node.x, node.y, node.r, 0, 2 * Math.PI);
                context.lineWidth = 0.5;
                context.fillStyle = colorscale(node.group);
                context.fill();
            }
        }

      function mainterms(i) {
        if (!tfidf) return;
        var articles = data.filter(d => d.group === i), v = null;
        if (articles.length ===0) return '';

        var tags = d3.merge(articles.map(d => d.props))
        .filter(d => {
          return !d.match(/^trad/) && !d.match(/^[A-Z]/);
        });
        var freq = {}, max = 0;
        tags.forEach(d => {
          freq[d] = (freq[d]||0) + tfidf[d];
          if (freq[d] > max) {
            v = d;
            max = freq[d];
          }
        });
        return v;
      }

      function drawgmeans(svg, centers){

          const means = svg.selectAll('text')
          .data(centers);

          var enter = means.enter()
          .append('text')
          .attr('stroke', 'black')
          .attr('text-anchor', 'middle');

          means.exit().remove();

          means.merge(enter)
          .attr('x', d => centerx(d[0]))
          .attr('y', d => centery(d[1]))
          .text((d,i) => mainterms(i));

      }

      function drawlines(svg, links){

          const lines = svg.selectAll('line')
          .data(links, l => l.index);

          var enter = lines.enter()
          .append('line');

          lines.exit().remove();

          lines.merge(enter)
          .attr('x1', d => d.target.x)
          .attr('x2', d => d.source.x)
          .attr('y1', d => d.target.y)
          .attr('y2', d => d.source.y)
          .attr('stroke', 'black');

      }

        function drawsvg(svg, nodes) {
          const g = svg.selectAll('g.city')
          .data(nodes);

          var enter = g.enter().append('g').classed('city', true);

          enter.append('circle')
          .attr('r', d => d.r)
          //.attr('fill', d => d.color)
          .append('title')
          .text(d => d.name);

          enter
          .filter(d => d.r > 7)
          .append('text')
          .attr('fill', 'white')
          .style('font-size', d => d.r > 9 ? '12px' : '9px')
          .attr('text-anchor', 'middle')
          .attr('dominant-baseline', 'middle')
          .attr('pointer-events', 'none')
          .text(d => d.name.replace(/^(L([ea] |’)|À |Un )/, '').substring(0,d.r/4));

          g.merge(enter)
             .attr('fill', d => /*d.color ||*/ colorscale(d.group))
            .attr('transform', d => `translate(${d.x},${d.y})`);

        }

d3.queue()
    .defer(d3.text, 'tsne.js')
    .defer(d3.text, 'https://unpkg.com/d3-geo')
    .defer(d3.text, 'worker.js')
    .awaitAll(function (err, scripts) {

    const worker = new Worker(
      window.URL.createObjectURL(
        new Blob(scripts, {
          type: "text/javascript"
        })
      )
    );

  worker.postMessage({
      maxIter: 10,
      dim: 2,
      perplexity: 100.0,
      data: data
  });

  worker.onmessage = function (e) {
    if (e.data.log) console.log.apply(this, e.data.log);
    if (e.data.tfidf) tfidf = e.data.tfidf;
    //if (isNaN(e.data.cost)) console.log('isNaN');
    if (e.data.pos) {
      pos = e.data.pos;
      let sc = d3.max(pos.map(d => d[0]))
      let diagram = voronoi(pos.map((d,i) => (d.index = i, d[0]/=sc, d[1]/=sc, d)));
      links = urquhart(diagram, (a,b) =>
        (a[0]-b[0])*(a[0]-b[0]) + (a[1]-b[1])*(a[1]-b[1])
      )
        .map(d => {
        d.source = data[d.source.index];
        d.target = data[d.target.index];
        return d;
      });
      /*
forcetsne.force('links', forcelinks.links(links.map(d => {
        d.source = data[d.source.index];
        d.target = data[d.target.index];
        return d;
      })));
*/
}
    if (e.data.done && e.data.done < 10000  && e.data.cost > 1e-2) {
      worker.postMessage({
            maxIter: e.data.done + 10,
      });
    }
    //console.log('pos', pos);
  };
});

    });

  function urquhart(diagram, distance) {
    var urquhart = d3.map();
    diagram.links()
        .forEach(function (link) {
            var v = d3.extent([link.source.index, link.target.index]);
            urquhart.set(v, link);
        });
    urquhart._remove = [];

    diagram.triangles()
        .forEach(function (t) {

            var l = 0,
                length = 0,
                i = -1,
                v;
            for (var j = 0; j < 3; j++) {
                var a = t[j],
                    b = t[(j + 1) % 3];
                v = d3.extent([a.index, b.index]);
                if (!distance) {
                  length = (a.x - b.x) * (a.x - b.x) + (a.y - b.y) * (a.y - b.y);
                } else {
                    length = distance(a, b);
                }
                if (length >= l) {
                    l = length;
                    i = v;
                }
            }
            urquhart._remove.push(i);
        });
    urquhart._remove.forEach(function (i) {
        if (urquhart.has(i)) urquhart.remove(i);
    });
    return urquhart.values();
}

</script>
</body>

## plan.json
[

{
	"id": 190,
	"title": "Qui fabrique les armes, et qui les ach\u00e8te\u00a0?",
	"url": "qui-fabrique-les-armes-et-qui-les-achete",
	"date": "2015-11-18T18:48:16Z",
	"rub": "7",
	"trad": 190,
	"pop": 63,
	"views": "34282",
	"authors": ["Philippe Rekacewicz"],
	"affdate": "18 novembre 2015",
	"tags": ["armement","conflits","guerre","russie","etats-unis","chine","france","europe","ressources pedagogiques"]
},
{
	"id": 94,
	"title": "Index du site",
	"url": "sitemap",
	"date": "2014-04-01T06:34:00Z",
	"rub": "1",
	"pop": 63,
	"views": "17503",
	"authors": [],
	"affdate": "1er avril 2014",
	"tags": []
},
{
	"id": 9,
	"title": "Mourir aux portes de l&#8217;Europe",
	"url": "mourir-aux-portes-de-l-europe",
	"date": "2014-04-27T22:17:50Z",
	"rub": "3",
	"trad": 9,
	"pop": 9,
	"views": "11272",
	"authors": ["Philippe Rekacewicz"],
	"affdate": "28 avril 2014",
	"tags": ["migrations","asile","frontieres","mer mediterranee","mediterranee","mourir en mer"]
},
{
	"id": 100,
	"title": "Cartographies traverses, des espaces o\u00f9 l&#8217;on ne finit jamais d&#8217;arriver",
	"url": "cartographies-traverses",
	"date": "2015-02-27T10:40:16Z",
	"rub": "3",
	"trad": 100,
	"pop": 18,
	"views": "9562",
	"authors": ["Sarah Mekdjian", "Anne-Laure Amilhat Szary"],
	"affdate": "27 f\u00e9vrier 2015",
	"tags": ["cartographie","cartographie sensible","cartographie participative","migrations","frontieres"]
},
{
	"id": 125,
	"title": "Terrorisme, insurrection ou r\u00e9sistance\u00a0: cartographier et nommer \u00ab\u00a0l&#8217;internationale djihadiste\u00a0\u00bb",
	"url": "djihadisme-international",
	"date": "2015-06-08T04:00:00Z",
	"rub": "3",
	"trad": 125,
	"pop": 6,
	"views": "8849",
	"authors": ["Philippe Rekacewicz"],
	"affdate": "8 juin 2015",
	"tags": ["djihadisme","etat islamique","daesh","ei","is","isis","al-qaida","insurrection","resistance","terrorisme"]
},
{
	"id": 83,
	"title": "Les nouvelles couleurs de Port-au-Prince",
	"url": "couleurs-de-port-au-prince",
	"date": "2014-10-24T09:00:00Z",
	"rub": "3",
	"pop": 3,
	"views": "8210",
	"authors": ["Romain Cruse", "Pierre Morel"],
	"affdate": "24 octobre 2014",
	"tags": ["haiti","richesse","pauvrete","caraibes"]
},
{
	"id": 240,
	"title": "Voyager sans visa",
	"url": "voyager-sans-visa",
	"date": "2016-02-22T11:13:37Z",
	"rub": "3",
	"pop": 5,
	"views": "8197",
	"authors": ["Philippe Rivi\u00e8re"],
	"affdate": "22 f\u00e9vrier 2016",
	"tags": ["frontieres","migrations","voyage","tourisme","passeport","visas","utopie","geopolitique","passeport","nation","visas","libre circulation","murs","cartographie","visualisation","frontieres","migrations","geopolitique"]
},
{
	"id": 107,
	"title": "Viols en temps de guerre, le silence et l&#8217;impunit\u00e9",
	"url": "viols-en-temps-de-guerre",
	"date": "2015-08-04T08:02:09Z",
	"rub": "3",
	"pop": 9,
	"views": "7648",
	"authors": ["Agn\u00e8s Stienne"],
	"affdate": "4 ao\u00fbt 2015",
	"tags": ["viols","culture du viol","droit des femmes","guerre","conventions internationales","conflits armes","femmes","filles"]
},
{
	"id": 223,
	"title": "Les cinquante cartes de Charles-Joseph Minard ",
	"url": "charles-joseph-minard-cinquante-cartes",
	"date": "2016-03-03T06:53:27Z",
	"rub": "3",
	"pop": 6,
	"views": "6872",
	"authors": ["Sandra Rendgen"],
	"affdate": "3 mars 2016",
	"tags": ["visualisation","cartographie","statistique","graphique","semiologie graphique","precurseurs","charles-joseph minard"]
},
{
	"id": 46,
	"title": "Le transport maritime et les rivages de la mer",
	"url": "transport-maritime-rivages-de-la-mer",
	"date": "2014-09-01T13:41:03Z",
	"rub": "3",
	"pop": 8,
	"views": "6839",
	"authors": ["Jean-Marie Miossec"],
	"affdate": "1er septembre 2014",
	"tags": ["transport","transport maritime","mer","oceans","europe","asie","conteneurs"]
},
{
	"id": 98,
	"title": "Bob Marley entre deux mondes",
	"url": "bob-marley-entre-deux-mondes",
	"date": "2015-02-05T23:22:20Z",
	"rub": "3",
	"pop": 15,
	"views": "6514",
	"authors": ["Romain Cruse", "Romain Philippon"],
	"affdate": "6 f\u00e9vrier 2015",
	"tags": ["musique","reggae","jamaique","caraibes"]
},
{
	"id": 202,
	"title": "Sahel\u00a0: la guerre des sables, par dessus les fronti\u00e8res",
	"url": "sahel-la-guerre-des-sables",
	"date": "2016-01-22T11:37:05Z",
	"rub": "3",
	"pop": 5,
	"views": "6354",
	"authors": ["Philippe Leymarie"],
	"affdate": "22 janvier 2016",
	"tags": ["sahel","mali","niger","guerres","conflits","afrique occidentale","france","armee","nigeria","boko haram"]
},
{
	"id": 1,
	"title": "\u00c0 propos de Visionscarto",
	"url": "a-propos",
	"date": "2014-04-01T08:50:28Z",
	"rub": "1",
	"pop": 4,
	"views": "6259",
	"authors": [],
	"affdate": "1er avril 2014",
	"tags": []
},
{
	"id": 274,
	"title": "Lieux de pouvoir \u00e0 Paris",
	"url": "lieux-de-pouvoir-a-paris",
	"date": "2016-04-23T18:44:40Z",
	"rub": "7",
	"pop": 3,
	"views": "5665",
	"authors": ["Agn\u00e8s Stienne"],
	"affdate": "23 avril 2016",
	"tags": ["paris","france","territoire","oligarchie"]
},
{
	"id": 78,
	"title": "Accaparement de terres\u00a0: la Chine, l&#8217;Inde et les \u00c9tats-Unis aussi...",
	"url": "accaparement-chine-inde-etats-unis",
	"date": "2014-10-06T09:35:35Z",
	"rub": "3",
	"pop": 6,
	"views": "5655",
	"authors": ["Agn\u00e8s Stienne"],
	"affdate": "6 octobre 2014",
	"tags": ["accaparement","agriculture","chine","inde","etats-unis","land grabbing"]
},
{
	"id": 129,
	"title": "Dans la r\u00e9gion de l&#8217;Evros, un mur inutile sur la fronti\u00e8re gr\u00e9co-turque",
	"url": "evros-mur-inutile",
	"date": "2015-06-25T06:09:40Z",
	"rub": "3",
	"pop": 21,
	"views": "5492",
	"authors": ["Cristina Del Biaggio", "Alberto Campi"],
	"affdate": "25 juin 2015",
	"tags": ["migrations","asile","migrants","refugies","grece","turquie","evros","murs","frontieres","barriere frontaliere"]
},
{
	"id": 79,
	"title": "G\u00e9ographie de l&#8217;enfance",
	"url": "geographie-de-l-enfance",
	"date": "2014-10-10T14:25:36Z",
	"rub": "3",
	"pop": 14,
	"views": "5475",
	"authors": ["Philippe Rekacewicz"],
	"affdate": "10 octobre 2014",
	"tags": ["enfance","travail","sante","inegalites","developpement","anamorphose","enfants","demographie","travail des enfants","prix nobel"]
},
{
	"id": 161,
	"title": "\u00ab\u00a0Dessine-moi une \u00eele\u00a0!\u00a0\u00bb",
	"url": "dessine-moi-une-ile",
	"date": "2015-10-02T18:50:46Z",
	"rub": "3",
	"pop": 10,
	"views": "5475",
	"authors": ["Fran\u00e7ois Arnal"],
	"affdate": "2 octobre 2015",
	"tags": ["imaginaire","geographie","representations","paysage","cartographie","carte mentale","insularite","ileite"]
},
{
	"id": 148,
	"title": "\u00c0 Ath\u00e8nes, (sur)vivre dans la terreur",
	"url": "a-athenes-survivre",
	"date": "2015-08-31T06:06:29Z",
	"rub": "3",
	"pop": 9,
	"views": "5162",
	"authors": ["Cristina Del Biaggio", "Alberto Campi"],
	"affdate": "31 ao\u00fbt 2015",
	"tags": ["migrations","asile","migrants","refugies","grece","segregation","racisme","extreme droite","athenes","petrou ralli"]
},
{
	"id": 97,
	"title": "No\u00ebl \u00e0 Bethl\u00e9em, au pied du mur",
	"url": "noel-a-bethleem",
	"date": "2014-12-24T07:18:58Z",
	"rub": "3",
	"pop": 29,
	"views": "4668",
	"authors": ["Elisabeth Vallet"],
	"affdate": "24 d\u00e9cembre 2014",
	"tags": ["murs","frontieres","palestine","israel","occupation","bethleem","barriere frontaliere"]
},
{
	"id": 82,
	"title": "Le Daghestan, l\u2019islam et les soviets",
	"url": "le-daghestan-l-islam-et-les-soviets",
	"date": "2014-10-28T09:35:59Z",
	"rub": "3",
	"pop": 22,
	"views": "4650",
	"authors": ["Fr\u00e9d\u00e9rique Longuet-Marx"],
	"affdate": "28 octobre 2014",
	"tags": ["daghestan","caucase","russie","caucase-nord","islam","documentaire","soufisme","salafisme"]
},
{
	"id": 147,
	"title": "L&#8217;arc des r\u00e9fugi\u00e9s en 2014",
	"url": "l-arc-des-refugies-en-2014",
	"date": "2015-07-11T10:16:18Z",
	"rub": "7",
	"trad": 147,
	"pop": 3,
	"views": "4556",
	"authors": ["Philippe Rekacewicz"],
	"affdate": "11 juillet 2015",
	"tags": ["refugies","droits humains","discrimination","asile","guerre","conflits"]
},
{
	"id": 276,
	"title": "Le sol, ce bien commun o\u00f9 la vie prend\u00a0racine",
	"url": "le-sol-ce-bien-commun",
	"date": "2016-06-01T12:53:42Z",
	"rub": "3",
	"pop": 14,
	"views": "4306",
	"authors": ["Agn\u00e8s Stienne"],
	"affdate": "1er juin 2016",
	"tags": ["sols","agriculture","degradations","pollutions"]
},
{
	"id": 155,
	"title": "Traverser la fronti\u00e8re et arriver en Bulgarie\u00a0: paroles de r\u00e9fugi\u00e9s",
	"url": "refugies-bulgarie",
	"date": "2015-09-21T09:49:28Z",
	"rub": "3",
	"pop": 7,
	"views": "4087",
	"authors": ["Stefania Summermatter"],
	"affdate": "21 septembre 2015",
	"tags": ["refugies","migrations","bulgarie","turquie","syrie","migrants","asile"]
},
{
	"id": 195,
	"title": "Irak\u00a0: apr\u00e8s les feux de la guerre, les cancers",
	"url": "irak-apres-les-feux-de-la-guerre",
	"date": "2015-12-05T16:04:39Z",
	"rub": "3",
	"pop": 3,
	"views": "4042",
	"authors": ["Agn\u00e8s Stienne"],
	"affdate": "5 d\u00e9cembre 2015",
	"tags": ["irak","sante","cancer","natalite","guerre","armes","pollution"]
},
{
	"id": 191,
	"title": "Who is selling arms, and who buys them?",
	"url": "who-is-selling-arms-and-who-buys",
	"date": "2015-11-24T09:08:58Z",
	"rub": "7",
	"trad": 190,
	"pop": 3,
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	"rub": "7",
	"trad": 190,
	"pop": 3,
	"views": "917",
	"authors": ["Philippe Rekacewicz", "Cristina Del Biaggio"],
	"affdate": "17 gennaio 2016",
	"tags": ["armi","conflitti","guerra","russia","stati uniti d'america","cina","francia","europa"]
},
{
	"id": 157,
	"title": "La guerre isra\u00e9lo-arabe de 1967",
	"url": "la-guerre-israelo-arabe-de-1967",
	"date": "2015-09-23T12:47:18Z",
	"rub": "7",
	"pop": 7,
	"views": "916",
	"authors": ["Philippe Rekacewicz"],
	"affdate": "23 septembre 2015",
	"tags": ["israel","palestine","guerre","occupation","colonisation","guerre de 1967","proche-orient","moyen-orient"]
},
{
	"id": 89,
	"title": "La d\u00e9colonisation et les nouveaux territoires",
	"url": "decolonisation-nouveaux-territoires",
	"date": "2014-11-12T17:29:06Z",
	"rub": "7",
	"pop": 7,
	"views": "905",
	"authors": ["Philippe Rekacewicz"],
	"affdate": "12 novembre 2014",
	"tags": ["colonisation","imperialisme","decolonisation","independances","resistances","territoires"]
},
{
	"id": 219,
	"title": "Un Tsigane n\u2019est pas tous les Tsiganes",
	"url": "un-tsigane-pas-tous-les-tsiganes",
	"date": "2016-01-29T13:59:03Z",
	"rub": "3",
	"pop": 4,
	"views": "903",
	"authors": ["C\u00e9cile Kovacshazy"],
	"affdate": "29 janvier 2016",
	"tags": ["roms","europe","minorites","discrimination","union europeenne","ue","population"]
},
{
	"id": 158,
	"title": "La guerre isra\u00e9lo-arabe de 1973",
	"url": "la-guerre-israelo-arabe-de-1973",
	"date": "2015-09-23T12:47:24Z",
	"rub": "7",
	"pop": 3,
	"views": "902",
	"authors": ["Philippe Rekacewicz"],
	"affdate": "23 septembre 2015",
	"tags": ["israel","palestine","guerre","occupation","colonisation","guerre de 1973","proche orient","moyen orient","guerre du kippour","egypte"]
},
{
	"id": 29,
	"title": "Otto Neurath and the Politics of Orchestration",
	"url": "neurath-politics-of-orchestration",
	"date": "2014-05-28T12:56:37Z",
	"rub": "3",
	"trad": 29,
	"pop": 3,
	"views": "886",
	"authors": ["Sophie Hochh\u00e4usl"],
	"affdate": "28 May 2014",
	"tags": ["isotype","visualisation","otto neurath","architecture","urbanism"]
},
{
	"id": 56,
	"title": "\u00c9volution du transport maritime entre 1950 et 2014",
	"url": "evolution-transport-maritime",
	"date": "2014-08-31T22:20:07Z",
	"rub": "7",
	"pop": 3,
	"views": "886",
	"authors": ["Philippe Rekacewicz"],
	"affdate": "1er septembre 2014",
	"tags": ["transport","transport maritime","visualisation","esquisse"]
},
{
	"id": 206,
	"title": "La projection Bottomley",
	"url": "la-projection-bottomley",
	"date": "2016-01-11T08:52:48Z",
	"rub": "3",
	"pop": 3,
	"views": "885",
	"authors": ["Philippe Rivi\u00e8re"],
	"affdate": "11 janvier 2016",
	"tags": ["projection","cartographie","code","programmation","d3.js"]
},
{
	"id": 266,
	"title": "\u00c9volution de l&#8217;esp\u00e9rance de vie \u00e0 la naissance entre 1990 et 2006",
	"url": "esperance-de-vie-1990-2006",
	"date": "2016-04-09T08:27:30Z",
	"rub": "7",
	"pop": 3,
	"views": "883",
	"authors": ["Philippe Rekacewicz"],
	"affdate": "9 avril 2016",
	"tags": ["demographie","sante","esperance de vie"]
},
{
	"id": 342,
	"title": "In\u00e9galit\u00e9s fonci\u00e8res en Am\u00e9rique du Sud et aux \u00c9tats-Unis",
	"url": "inegalites-foncieres-en-amerique",
	"date": "2016-11-02T15:01:35Z",
	"rub": "3",
	"pop": 7,
	"views": "869",
	"authors": ["Agn\u00e8s Stienne"],
	"affdate": "2 novembre 2016",
	"tags": ["accaparements de terres","foncier","agriculture","agroindustrie","amerique du sud","etats-unis"]
},
{
	"id": 35,
	"title": "R\u012bga 2014, la f\u00eate de tout un peuple\u00a0?",
	"url": "riga-2014",
	"date": "2014-05-19T10:56:30Z",
	"rub": "3",
	"pop": 3,
	"views": "843",
	"authors": ["Nicolas Escach"],
	"affdate": "19 mai 2014",
	"tags": ["culture","r\u012bga","lettonie","russie","r\u012bga 2014"]
},
{
	"id": 258,
	"title": "Human Settlements",
	"url": "human-settlements",
	"date": "2016-04-26T05:41:13Z",
	"rub": "7",
	"trad": 256,
	"pop": 3,
	"views": "809",
	"authors": ["Philippe Rivi\u00e8re"],
	"affdate": "26 April 2016",
	"tags": ["cities","roads","world","population","basics"]
},
{
	"id": 143,
	"title": "Structures agraires en Europe de l&#8217;Est",
	"url": "structures-agraires-europe",
	"date": "2015-06-23T19:45:36Z",
	"rub": "7",
	"pop": 3,
	"views": "806",
	"authors": ["Agn\u00e8s Stienne"],
	"affdate": "23 juin 2015",
	"tags": ["europe","agriculture","inegalites","foncier","slovenie","croatie","pologne","lituanie","lettonie","roumanie","allemagne","hongrie","estonie","bulgarie","republique tcheque","slovaquie","europe orientale"]
},
{
	"id": 262,
	"title": "Croissance et d\u00e9croissance de la population mondiale\u00a0: 2005-2010",
	"url": "croissance-et-decroissance-de-la-population",
	"date": "2016-05-18T08:37:22Z",
	"rub": "7",
	"pop": 3,
	"views": "796",
	"authors": ["Philippe Rekacewicz"],
	"affdate": "18 mai 2016",
	"tags": ["demographie","population","natalite","mortalite"]
},
{
	"id": 267,
	"title": "Esp\u00e9rance de vie en bonne sant\u00e9 en 2010",
	"url": "esperance-de-vie-en-bonne-sante-2010",
	"date": "2016-04-09T08:25:55Z",
	"rub": "7",
	"pop": 3,
	"views": "790",
	"authors": ["Philippe Rekacewicz"],
	"affdate": "9 avril 2016",
	"tags": ["demographie","sante","esperance de vie"]
},
{
	"id": 186,
	"title": "Giving peace a chance: international initiatives, ongoing and recently accomplished operations, 1990-2015",
	"url": "giving-peace-a-chance",
	"date": "2015-11-24T09:09:13Z",
	"rub": "7",
	"trad": 185,
	"pop": 3,
	"views": "788",
	"authors": ["Philippe Rekacewicz"],
	"affdate": "24 November 2015",
	"tags": ["war","conflicts","borders","un","united nations","osce","eu","european union","peace"]
},
{
	"id": 249,
	"title": "Conflits et tensions politiques dans le Caucase en 2012",
	"url": "conflits-et-tensions-politiques-2012",
	"date": "2016-03-14T10:12:19Z",
	"rub": "7",
	"pop": 3,
	"views": "781",
	"authors": ["Philippe Rekacewicz", "Jean Radvanyi", "Manana Kurtubadze"],
	"affdate": "14 mars 2016",
	"tags": ["caucase","caucase-sud","caucase-nord","guerres","conflits","russie","energie"]
},
{
	"id": 312,
	"title": "Le syst\u00e8me Chine dans la mondialisation",
	"url": "le-systeme-chine",
	"date": "2016-11-25T11:37:10Z",
	"rub": "7",
	"pop": 39,
	"views": "770",
	"authors": ["Philippe Rekacewicz"],
	"affdate": "25 novembre 2016",
	"tags": ["chine","economie","mondialisation","systeme","analyse systemique","soft power"]
},
{
	"id": 77,
	"title": "La valise et son artiste partent en voyage...",
	"url": "thomas-philibert-la-valise-et-son-artiste",
	"date": "2014-10-01T18:34:56Z",
	"rub": "3",
	"pop": 5,
	"views": "770",
	"authors": ["Philippe Rekacewicz"],
	"affdate": "1er octobre 2014",
	"tags": ["art","graffiti","voyage","dessin","scandinavie","monde nordique","valise","thomas philibert"]
},
{
	"id": 88,
	"title": "Le Hold-up colonial",
	"url": "le-hold-up-colonial",
	"date": "2014-11-12T17:27:57Z",
	"rub": "7",
	"pop": 3,
	"views": "765",
	"authors": ["Philippe Rekacewicz"],
	"affdate": "12 novembre 2014",
	"tags": ["colonisation","imperialisme","decolonisation"]
},
{
	"id": 224,
	"title": "Trois Tsiganes ordinaires en Tch\u00e9quie et Slovaquie",
	"url": "trois-tsiganes-ordinaires",
	"date": "2016-01-29T13:58:49Z",
	"rub": "3",
	"pop": 3,
	"views": "764",
	"authors": ["C\u00e9cile Kovacshazy"],
	"affdate": "29 janvier 2016",
	"tags": ["roms","bd","bande dessinee","slovaquie","tchequie","tchecoslovaquie"]
},
{
	"id": 253,
	"title": "Croissance d\u00e9mographique dans le Caucase",
	"url": "croissance-demographique-dans-le-caucase",
	"date": "2016-03-14T10:13:40Z",
	"rub": "7",
	"pop": 3,
	"views": "764",
	"authors": ["Philippe Rekacewicz"],
	"affdate": "14 mars 2016",
	"tags": ["caucase","caucase-sud","caucase-nord","demographie","population","russie"]
},
{
	"id": 137,
	"title": "G\u00e9ographie de la pauvret\u00e9 aux \u00c9tats-Unis en 2013",
	"url": "geographie-de-la-pauvrete-aux-etats-unis",
	"date": "2015-06-22T06:44:51Z",
	"rub": "7",
	"pop": 3,
	"views": "751",
	"authors": ["Philippe Rekacewicz"],
	"affdate": "22 juin 2015",
	"tags": ["etats-unis","revenus","inegalites","pauvrete","richesse","riches","pauvres"]
},
{
	"id": 346,
	"title": "How ZIP codes nearly masked the lead problem in Flint",
	"url": "zip-codes-flint",
	"date": "2016-11-15T17:08:03Z",
	"rub": "3",
	"trad": 345,
	"pop": 7,
	"views": "748",
	"authors": ["Richard Casey Sadler"],
	"affdate": "15 November 2016",
	"tags": ["methodology","cartography","bias","health"]
},
{
	"id": 5,
	"title": "La route de tous les p\u00e9rils",
	"url": "la-route-de-tous-les-perils",
	"date": "2014-05-09T09:22:00Z",
	"rub": "3",
	"pop": 3,
	"views": "743",
	"authors": ["madmeg"],
	"affdate": "9 mai 2014",
	"tags": ["art","dessin","manga","imaginaires"]
},
{
	"id": 188,
	"title": "Op\u00e9rations de maintien de la paix en 2015 et principaux contributeurs (2005-2015)",
	"url": "operations-de-maintien-de-la-paix",
	"date": "2015-11-12T10:31:27Z",
	"rub": "7",
	"trad": 188,
	"pop": 3,
	"views": "734",
	"authors": ["Philippe Rekacewicz"],
	"affdate": "12 novembre 2015",
	"tags": ["guerre","conflits","frontieres","paix","nations unies","onu","ressources pedagogiques"]
},
{
	"id": 20,
	"title": "Logiciels",
	"url": "logiciels",
	"date": "2014-04-27T15:15:23Z",
	"rub": "1",
	"pop": 3,
	"views": "723",
	"authors": ["Philippe Rivi\u00e8re"],
	"affdate": "27 avril 2014",
	"tags": []
},
{
	"id": 198,
	"title": "Prezzi degli accessi ad internet nel mondo",
	"url": "prezzi-degli-accessi-ad-internet",
	"date": "2015-12-24T16:51:41Z",
	"rub": "7",
	"trad": 198,
	"pop": 3,
	"views": "721",
	"authors": ["Philippe Rivi\u00e8re", "Cristina Del Biaggio"],
	"affdate": "24 dicembre 2015",
	"tags": ["internet","comunicazione","informatica","ineguaglianze","acesso","tic"]
},
{
	"id": 252,
	"title": "Conflits et tensions politiques dans le Caucase en 2009",
	"url": "conflits-et-tensions-politiques-2009",
	"date": "2016-03-14T10:12:39Z",
	"rub": "7",
	"pop": 3,
	"views": "721",
	"authors": ["Philippe Rekacewicz"],
	"affdate": "14 mars 2016",
	"tags": ["caucase","caucase-sud","caucase-nord","guerres","conflits","russie"]
},
{
	"id": 211,
	"title": "A nuclearized world",
	"url": "a-nuclearized-world",
	"date": "2016-01-26T07:00:29Z",
	"rub": "7",
	"trad": 210,
	"pop": 3,
	"views": "706",
	"authors": ["Philippe Rekacewicz"],
	"affdate": "26 January 2016",
	"tags": ["nuclear","armament","ntp","atomic bomb","nuclear powerplant","nuclear states"]
},
{
	"id": 21,
	"title": "La Palestine, \u00c9tat observateur non-membre aupr\u00e8s de l&#8217;ONU",
	"url": "la-palestine-etat-observateur-non",
	"date": "2014-04-27T22:13:56Z",
	"rub": "7",
	"pop": 3,
	"views": "701",
	"authors": ["Philippe Rekacewicz"],
	"affdate": "28 avril 2014",
	"tags": ["palestine","nations unies","onu","israel","occupation","colonisation","kosovo","independance"]
},
{
	"id": 323,
	"title": "Le prix des armes et des arm\u00e9es",
	"url": "armement-et-armees",
	"date": "2016-10-06T08:45:28Z",
	"rub": "7",
	"pop": 3,
	"views": "689",
	"authors": ["Philippe Rekacewicz"],
	"affdate": "6 octobre 2016",
	"tags": ["armement","armee","budgets militaires","russie","etats-unis","otan","chine","inde"]
},
{
	"id": 12,
	"title": "\u00c9tats-Unis - Russie\u00a0: l&#8217;autre menace nucl\u00e9aire",
	"url": "etats-unis-russie-l-autre-menace",
	"date": "2014-04-27T22:14:15Z",
	"rub": "7",
	"pop": 3,
	"views": "680",
	"authors": ["Philippe Rekacewicz"],
	"affdate": "28 avril 2014",
	"tags": ["nucleaire militaire","armement non conventionnel","bombe atomique","geostrategie","etats-unis","russie","edm"]
},
{
	"id": 58,
	"title": "Enfants palestiniens tu\u00e9s par l&#8217;arm\u00e9e ou les colons alors qu&#8217;ils ne participaient pas aux hostilit\u00e9s, 2000-2014",
	"url": "enfants-palestiniens-tues",
	"date": "2014-09-03T16:14:21Z",
	"rub": "7",
	"pop": 3,
	"views": "677",
	"authors": ["Philippe Rekacewicz"],
	"affdate": "3 septembre 2014",
	"tags": ["enfance","enfants","massacre","occupation","colonisation","israel"]
},
{
	"id": 327,
	"title": "Investissez dans l&#8217;armement, c&#8217;est plus rentable",
	"url": "spad-index",
	"date": "2016-10-06T08:44:30Z",
	"rub": "7",
	"pop": 3,
	"views": "663",
	"authors": ["Philippe Rekacewicz"],
	"affdate": "6 octobre 2016",
	"tags": ["armement","armee","budgets militaires","bourse","indices financiers","speculation"]
}
]

## thumbnail.png

      
    Raw
  

              thumbnail.png
            
          
## tsne.js
// create main global object
var tsnejs = tsnejs || { REVISION: 'ALPHA' };

(function(global) {
  "use strict";

  // utility function
  var assert = function(condition, message) {
    if (!condition) { throw message || "Assertion failed"; }
  }

  // syntax sugar
  var getopt = function(opt, field, defaultval) {
    if(opt.hasOwnProperty(field)) {
      return opt[field];
    } else {
      return defaultval;
    }
  }

  // return 0 mean unit standard deviation random number
  var return_v = false;
  var v_val = 0.0;
  var gaussRandom = function() {
    if(return_v) {
      return_v = false;
      return v_val;
    }
    var u = 2*Math.random()-1;
    var v = 2*Math.random()-1;
    var r = u*u + v*v;
    if(r == 0 || r > 1) return gaussRandom();
    var c = Math.sqrt(-2*Math.log(r)/r);
    v_val = v*c; // cache this for next function call for efficiency
    return_v = true;
    return u*c;
  }

  // return random normal number
  var randn = function(mu, std){ return mu+gaussRandom()*std; }

  // utilitity that creates contiguous vector of zeros of size n
  var zeros = function(n) {
    if(typeof(n)==='undefined' || isNaN(n)) { return []; }
    if(typeof ArrayBuffer === 'undefined') {
      // lacking browser support
      var arr = new Array(n);
      for(var i=0;i<n;i++) { arr[i]= 0; }
      return arr;
    } else {
      return new Float64Array(n); // typed arrays are faster
    }
  }

  // utility that returns 2d array filled with random numbers
  // or with value s, if provided
  var randn2d = function(n,d,s) {
    var uses = typeof s !== 'undefined';
    var x = [];
    for(var i=0;i<n;i++) {
      var xhere = [];
      for(var j=0;j<d;j++) {
        if(uses) {
          xhere.push(s);
        } else {
          xhere.push(randn(0.0, 1e-4));
        }
      }
      x.push(xhere);
    }
    return x;
  }

  // compute L2 distance between two vectors
  var L2 = function(x1, x2) {
    var D = x1.length;
    var d = 0;
    for(var i=0;i<D;i++) {
      var x1i = x1[i];
      var x2i = x2[i];
      d += (x1i-x2i)*(x1i-x2i);
    }
    return d;
  }

  // compute pairwise distance in all vectors in X
  var xtod = function(X) {
    var N = X.length;
    var dist = zeros(N * N); // allocate contiguous array
    for(var i=0;i<N;i++) {
      for(var j=i+1;j<N;j++) {
        var d = L2(X[i], X[j]);
        dist[i*N+j] = d;
        dist[j*N+i] = d;
      }
    }
    return dist;
  }

  // compute (p_{i|j} + p_{j|i})/(2n)
  var d2p = function(D, perplexity, tol) {
    var Nf = Math.sqrt(D.length); // this better be an integer
    var N = Math.floor(Nf);
    assert(N === Nf, "D should have square number of elements.");
    var Htarget = Math.log(perplexity); // target entropy of distribution
    var P = zeros(N * N); // temporary probability matrix

    var prow = zeros(N); // a temporary storage compartment
    for(var i=0;i<N;i++) {
      var betamin = -Infinity;
      var betamax = Infinity;
      var beta = 1; // initial value of precision
      var done = false;
      var maxtries = 50;

      // perform binary search to find a suitable precision beta
      // so that the entropy of the distribution is appropriate
      var num = 0;
      while(!done) {
        //debugger;

        // compute entropy and kernel row with beta precision
        var psum = 0.0;
        for(var j=0;j<N;j++) {
          var pj = Math.exp(- D[i*N+j] * beta);
          if(i===j) { pj = 0; } // we dont care about diagonals
          prow[j] = pj;
          psum += pj;
        }
        // normalize p and compute entropy
        var Hhere = 0.0;
        for(var j=0;j<N;j++) {
          if(psum == 0) {
             var pj = 0;
          } else {
             var pj = prow[j] / psum;
          }
          prow[j] = pj;
          if(pj > 1e-7) Hhere -= pj * Math.log(pj);
        }

        // adjust beta based on result
        if(Hhere > Htarget) {
          // entropy was too high (distribution too diffuse)
          // so we need to increase the precision for more peaky distribution
          betamin = beta; // move up the bounds
          if(betamax === Infinity) { beta = beta * 2; }
          else { beta = (beta + betamax) / 2; }

        } else {
          // converse case. make distrubtion less peaky
          betamax = beta;
          if(betamin === -Infinity) { beta = beta / 2; }
          else { beta = (beta + betamin) / 2; }
        }

        // stopping conditions: too many tries or got a good precision
        num++;
        if(Math.abs(Hhere - Htarget) < tol) { done = true; }
        if(num >= maxtries) { done = true; }
      }

      // console.log('data point ' + i + ' gets precision ' + beta + ' after ' + num + ' binary search steps.');
      // copy over the final prow to P at row i
      for(var j=0;j<N;j++) { P[i*N+j] = prow[j]; }

    } // end loop over examples i

    // symmetrize P and normalize it to sum to 1 over all ij
    var Pout = zeros(N * N);
    var N2 = N*2;
    for(var i=0;i<N;i++) {
      for(var j=0;j<N;j++) {
        Pout[i*N+j] = Math.max((P[i*N+j] + P[j*N+i])/N2, 1e-100);
      }
    }

    return Pout;
  }

  // helper function
  function sign(x) { return x > 0 ? 1 : x < 0 ? -1 : 0; }

  var tSNE = function(opt) {
    var opt = opt || {};
    this.perplexity = getopt(opt, "perplexity", 30); // effective number of nearest neighbors
    this.dim = getopt(opt, "dim", 2); // by default 2-D tSNE
    this.epsilon = getopt(opt, "epsilon", 10); // learning rate

    this.iter = 0;
  }

  tSNE.prototype = {

    // this function takes a set of high-dimensional points
    // and creates matrix P from them using gaussian kernel
    initDataRaw: function(X) {
      var N = X.length;
      var D = X[0].length;
      assert(N > 0, " X is empty? You must have some data!");
      assert(D > 0, " X[0] is empty? Where is the data?");
      var dists = xtod(X); // convert X to distances using gaussian kernel
      this.P = d2p(dists, this.perplexity, 1e-4); // attach to object
      this.N = N; // back up the size of the dataset
      this.initSolution(); // refresh this
    },

    // this function takes a given distance matrix and creates
    // matrix P from them.
    // D is assumed to be provided as a list of lists, and should be symmetric
    initDataDist: function(D) {
      var N = D.length;
      assert(N > 0, " X is empty? You must have some data!");
      // convert D to a (fast) typed array version
      var dists = zeros(N * N); // allocate contiguous array
      for(var i=0;i<N;i++) {
        for(var j=i+1;j<N;j++) {
          var d = D[i][j];
          dists[i*N+j] = d;
          dists[j*N+i] = d;
        }
      }
      this.P = d2p(dists, this.perplexity, 1e-4);
      this.N = N;
      this.initSolution(); // refresh this
    },

    // (re)initializes the solution to random
    initSolution: function() {
      // generate random solution to t-SNE
      this.Y = randn2d(this.N, this.dim); // the solution
      this.gains = randn2d(this.N, this.dim, 1.0); // step gains to accelerate progress in unchanging directions
      this.ystep = randn2d(this.N, this.dim, 0.0); // momentum accumulator
      this.iter = 0;
    },

    // return pointer to current solution
    getSolution: function() {
      return this.Y;
    },

    // perform a single step of optimization to improve the embedding
    step: function() {
      this.iter += 1;
      var N = this.N;

      var cg = this.costGrad(this.Y); // evaluate gradient
      var cost = cg.cost;
      var grad = cg.grad;

      // perform gradient step
      var ymean = zeros(this.dim);
      for(var i=0;i<N;i++) {
        for(var d=0;d<this.dim;d++) {
          var gid = grad[i][d];
          var sid = this.ystep[i][d];
          var gainid = this.gains[i][d];

          // compute gain update
          var newgain = sign(gid) === sign(sid) ? gainid * 0.8 : gainid + 0.2;
          if(newgain < 0.01) newgain = 0.01; // clamp
          this.gains[i][d] = newgain; // store for next turn

          // compute momentum step direction
          var momval = this.iter < 250 ? 0.5 : 0.8;
          var newsid = momval * sid - this.epsilon * newgain * grad[i][d];
          this.ystep[i][d] = newsid; // remember the step we took

          // step!
          this.Y[i][d] += newsid;

          ymean[d] += this.Y[i][d]; // accumulate mean so that we can center later
        }
      }

      // reproject Y to be zero mean
      for(var i=0;i<N;i++) {
        for(var d=0;d<this.dim;d++) {
          this.Y[i][d] -= ymean[d]/N;
        }
      }

      //if(this.iter%100===0) console.log('iter ' + this.iter + ', cost: ' + cost);
      return cost; // return current cost
    },

    // for debugging: gradient check
    debugGrad: function() {
      var N = this.N;

      var cg = this.costGrad(this.Y); // evaluate gradient
      var cost = cg.cost;
      var grad = cg.grad;

      var e = 1e-5;
      for(var i=0;i<N;i++) {
        for(var d=0;d<this.dim;d++) {
          var yold = this.Y[i][d];

          this.Y[i][d] = yold + e;
          var cg0 = this.costGrad(this.Y);

          this.Y[i][d] = yold - e;
          var cg1 = this.costGrad(this.Y);

          var analytic = grad[i][d];
          var numerical = (cg0.cost - cg1.cost) / ( 2 * e );
          console.log(i + ',' + d + ': gradcheck analytic: ' + analytic + ' vs. numerical: ' + numerical);

          this.Y[i][d] = yold;
        }
      }
    },

    // return cost and gradient, given an arrangement
    costGrad: function(Y) {
      var N = this.N;
      var dim = this.dim; // dim of output space
      var P = this.P;

      var pmul = this.iter < 100 ? 4 : 1; // trick that helps with local optima

      // compute current Q distribution, unnormalized first
      var Qu = zeros(N * N);
      var qsum = 0.0;
      for(var i=0;i<N;i++) {
        for(var j=i+1;j<N;j++) {
          var dsum = 0.0;
          for(var d=0;d<dim;d++) {
            var dhere = Y[i][d] - Y[j][d];
            dsum += dhere * dhere;
          }
          var qu = 1.0 / (1.0 + dsum); // Student t-distribution
          Qu[i*N+j] = qu;
          Qu[j*N+i] = qu;
          qsum += 2 * qu;
        }
      }
      // normalize Q distribution to sum to 1
      var NN = N*N;
      var Q = zeros(NN);
      for(var q=0;q<NN;q++) { Q[q] = Math.max(Qu[q] / qsum, 1e-100); }

      var cost = 0.0;
      var grad = [];
      for(var i=0;i<N;i++) {
        var gsum = new Array(dim); // init grad for point i
        for(var d=0;d<dim;d++) { gsum[d] = 0.0; }
        for(var j=0;j<N;j++) {
          cost += - P[i*N+j] * Math.log(Q[i*N+j]); // accumulate cost (the non-constant portion at least...)
          var premult = 4 * (pmul * P[i*N+j] - Q[i*N+j]) * Qu[i*N+j];
          for(var d=0;d<dim;d++) {
            gsum[d] += premult * (Y[i][d] - Y[j][d]);
          }
        }
        grad.push(gsum);
      }

      return {cost: cost, grad: grad};
    }
  }

  global.tSNE = tSNE; // export tSNE class
})(tsnejs);


// export the library to window, or to module in nodejs
(function(lib) {
  "use strict";
  if (typeof module === "undefined" || typeof module.exports === "undefined") {
    if (typeof window == "object")
        window.tsnejs = lib; // in ordinary browser attach library to window
  } else {
    module.exports = lib; // in nodejs
  }
})(tsnejs);

## worker.js
importScripts('https://d3js.org/d3.v4.min.js');

// in worker.onmessage add : `if (e.data.log) console.log.apply(this, e.data.log);`
console.log = function() {
  self.postMessage({ log: [...arguments] });
}

  function levenshtein(a, b) {
  var t = [], u, i, j, m = a.length, n = b.length;
  if (!m) { return n; }
  if (!n) { return m; }
  for (j = 0; j <= n; j++) { t[j] = j; }
  for (i = 1; i <= m; i++) {
    for (u = [i], j = 1; j <= n; j++) {
      u[j] = a[i - 1] === b[j - 1] ? t[j - 1] : Math.min(t[j - 1], t[j], u[j - 1]) + 1;
    } t = u;
  } return u[n];
}

let iterations = 0,
    model;

self.onmessage = function(e) {
  const msg = e.data,
        data = msg.data,
        maxIter = msg.maxIter || 500,
        perplexity = msg.perplexity || 30;

  var z = 0;
  let dists = msg.dist;
  if (data && !dists){
    let now = performance.now();
    let tfidf = {};
    d3.set(d3.merge(data.map(d => d.props)))
    .values()
    .map(d => {
      let t = data.filter(e => e.props.indexOf(d) > -1).length;
      if (t > 1) tfidf[d] = 1/t;
    });
    self.postMessage({"tfidf": tfidf});
    let similarities = data.map(
      a => data.map(
        b => b.props.filter(e => a.props.indexOf(e) > -1)
          .map(e => tfidf[e])
          .reduce((a,b) => a+b, 0)
      )
    );
    console.log("similarities", similarities);
    dists = similarities.map(r => r.map(s => Math.exp(-2 * s)));

    console.log('computed', data.length * data.length,'distances in', Math.round(performance.now()-now),'ms');
  }

 // console.log(dists);

//  dists = null;
  if (dists) {
      model = new tsnejs.tSNE({
          dim: msg.dim,
          perplexity: perplexity,
      });
      model.initDataDist(dists);
  }

  let startpos = model.getSolution().map(d=>d.slice()),
      pos;

  while (iterations++ < maxIter) {
       // every time you call this, solution gets better
       model.step();

    pos = model.getSolution();
//if (iterations%10 == 0) console.log("pos",pos);
       // Y is an array of 2-D points that you can plot
       self.postMessage({
         iterations: iterations - 1,
         pos: pos,
         //log: [ 'step', iterations-1 ]
       });

   }

  let cost = startpos
       .map((d,i) => sqdist(d, pos[i]))
       .reduce ((a,b) => a + b, 0) / pos.length / Math.max(...pos.map(d => Math.abs(d[0]) + Math.abs(d[1])));

   self.postMessage({
     done: iterations - 1,
     cost: cost,
     log: [ 'done', iterations - 1, cost ]
   });
};

function sqdist (a,b) {
  let d = [a[0] - b[0], a[1] - b[1]].map(Math.abs);
  return Math.max(d[0], d[1]);
}
	<!DOCTYPE html>

	<head>
	<meta charset="utf-8">
	<script src="https://d3js.org/d3.v4.min.js"></script>

	<style>
	body {
	margin: 0;
	position: fixed;
	top: 0;
	right: 0;
	bottom: 0;
	left: 0;
	font-family: monospace;
	}
	</style>
	</head>

	<body>
	<script>
	const width = 960,
	height = 500,
	margin = { top: 20, bottom: 20, left: 120, right: 120 },
	scalepop = d3.scalePow().exponent(1/2.5).domain([1, 10000]).range([0, 15]),
	scalepop2 = d3.scaleLog().domain([1, 1000]).range([0, 20]),
	scalecountry = d3.scaleOrdinal(d3.merge([d3.schemeCategory10, d3.schemeCategory20c])),
	centerx = d3.scaleLinear()
	.range([margin.left, width - margin.right]),
	centery = d3.scaleLinear()
	.range([margin.top, height - margin.bottom]);
	const voronoi = d3.voronoi();
	let tfidf;

	d3.json('plan.json', function (articles) {
	const data = articles
	.map((d, i) => {
	return {
	lon: Math.random(),
	lat: Math.random(),
	name: d['title'].replace(/&#\d+;/g, '’'),
	props: d3.set(d3.merge([ [ "trad" + (d.trad \|\| d.id) ], d.authors, d.tags ])).values(),
	//props: d['title'].substring(0,1),
	r: scalepop(+d['views']) + scalepop2(+d['pop']+1),
	p: scalepop2(+d['popularity']),
	color: scalecountry(''+d.authors)
	};
	})
	.slice(0,400);

	/*
	const canvas = d3.select("body").append("canvas")
	.attr("width", width)
	.attr("height", height);
	*/
	const svg = d3.select("body").append("svg")
	.attr("width", width)
	.attr("height", height);

	const lines = svg.append('g');
	const garticles = svg.append('g');
	const gmeans = svg.append('g');

	// pos is the array of positions that will be updated by the tsne worker
	// start with the geographic coordinates as is (plate-carrée)
	// random or [0,0] is fine too
	let pos = data.map(d => [Math.random(), Math.random()]);

	var K = 20,
	centers = d3.range(K).map(i => [0,0]),
	colorscale = d3.scaleOrdinal(d3.schemeCategory20c);

	let links = [];

	const forcetsne = d3.forceSimulation(
	data.map(d => (d.x = width / 2, d.y = height / 2, d))
	)
	//.stop()
	.alphaDecay(0.001)
	.alpha(0.1)
	.force('tsne', function (alpha) {
	centerx.domain(d3.extent(pos.map(d => d[0])));
	centery.domain(d3.extent(pos.map(d => d[1])));

	data.forEach((d, i) => {
	d.x += alpha * (centerx(pos[i][0]) - d.x);
	d.y += alpha * (centery(pos[i][1]) - d.y);
	});
	})

	.force('collide', d3.forceCollide().radius(d => 1 * (1.5 + d.r)))

	.force('kmeans', function(){

	// a central point to re-init empty groups
	var m = [d3.mean(centers.map(d => d[0] \|\| 0)),
	d3.mean(centers.map(d => d[1] \|\| 0))];

	// the order is important: move the centers before re-making the groups
	// so that the centers follow the general movement and keep "their"
	// points, instead of having points pass through them

	// 1. move K-centers towards the barycenter of their group
	centers.forEach((c,i) => {
	c[0] = d3.mean(pos.filter((d,j) => data[j].group == i).map(d => d[0])) \|\| m[0];
	c[1] = d3.mean(pos.filter((d,j) => data[j].group == i).map(d => d[1])) \|\| m[1];
	});

	// 2. group each point according to its closest K-center
	data.forEach((d,i) => {
	d.group = d3.scan(centers.map(c => {
	var dx = pos[i][0] - c[0],
	dy = pos[i][1] - c[1];
	return (dxdx + dydy);
	}));
	});

	}
	)
	.on('tick', function () {

	// drawcanvas(canvas, data);
	drawsvg(garticles, data);
	drawlines(lines, links);
	drawgmeans(gmeans, centers);
	});

	function drawcanvas(canvas, nodes) {
	let context = canvas.node().getContext("2d");
	context.clearRect(0, 0, width, width);

	for (var i = 0, n = nodes.length; i < n; ++i) {
	var node = nodes[i];
	context.beginPath();
	context.moveTo(node.x, node.y);
	context.arc(node.x, node.y, node.r, 0, 2 * Math.PI);
	context.lineWidth = 0.5;
	context.fillStyle = colorscale(node.group);
	context.fill();
	}
	}

	function mainterms(i) {
	if (!tfidf) return;
	var articles = data.filter(d => d.group === i), v = null;
	if (articles.length ===0) return '';

	var tags = d3.merge(articles.map(d => d.props))
	.filter(d => {
	return !d.match(/^trad/) && !d.match(/^[A-Z]/);
	});
	var freq = {}, max = 0;
	tags.forEach(d => {
	freq[d] = (freq[d]\|\|0) + tfidf[d];
	if (freq[d] > max) {
	v = d;
	max = freq[d];
	}
	});
	return v;
	}

	function drawgmeans(svg, centers){

	const means = svg.selectAll('text')
	.data(centers);

	var enter = means.enter()
	.append('text')
	.attr('stroke', 'black')
	.attr('text-anchor', 'middle');

	means.exit().remove();

	means.merge(enter)
	.attr('x', d => centerx(d[0]))
	.attr('y', d => centery(d[1]))
	.text((d,i) => mainterms(i));

	}

	function drawlines(svg, links){

	const lines = svg.selectAll('line')
	.data(links, l => l.index);

	var enter = lines.enter()
	.append('line');

	lines.exit().remove();

	lines.merge(enter)
	.attr('x1', d => d.target.x)
	.attr('x2', d => d.source.x)
	.attr('y1', d => d.target.y)
	.attr('y2', d => d.source.y)
	.attr('stroke', 'black');

	}

	function drawsvg(svg, nodes) {
	const g = svg.selectAll('g.city')
	.data(nodes);

	var enter = g.enter().append('g').classed('city', true);

	enter.append('circle')
	.attr('r', d => d.r)
	//.attr('fill', d => d.color)
	.append('title')
	.text(d => d.name);

	enter
	.filter(d => d.r > 7)
	.append('text')
	.attr('fill', 'white')
	.style('font-size', d => d.r > 9 ? '12px' : '9px')
	.attr('text-anchor', 'middle')
	.attr('dominant-baseline', 'middle')
	.attr('pointer-events', 'none')
	.text(d => d.name.replace(/^(L([ea] \|’)\|À \|Un )/, '').substring(0,d.r/4));

	g.merge(enter)
	.attr('fill', d => /d.color \|\|/ colorscale(d.group))
	.attr('transform', d => `translate(${d.x},${d.y})`);

	}

	d3.queue()
	.defer(d3.text, 'tsne.js')
	.defer(d3.text, 'https://unpkg.com/d3-geo')
	.defer(d3.text, 'worker.js')
	.awaitAll(function (err, scripts) {

	const worker = new Worker(
	window.URL.createObjectURL(
	new Blob(scripts, {
	type: "text/javascript"
	})
	)
	);

	worker.postMessage({
	maxIter: 10,
	dim: 2,
	perplexity: 100.0,
	data: data
	});

	worker.onmessage = function (e) {
	if (e.data.log) console.log.apply(this, e.data.log);
	if (e.data.tfidf) tfidf = e.data.tfidf;
	//if (isNaN(e.data.cost)) console.log('isNaN');
	if (e.data.pos) {
	pos = e.data.pos;
	let sc = d3.max(pos.map(d => d[0]))
	let diagram = voronoi(pos.map((d,i) => (d.index = i, d[0]/=sc, d[1]/=sc, d)));
	links = urquhart(diagram, (a,b) =>
	(a[0]-b[0])(a[0]-b[0]) + (a[1]-b[1])(a[1]-b[1])
	)
	.map(d => {
	d.source = data[d.source.index];
	d.target = data[d.target.index];
	return d;
	});
	/*
	forcetsne.force('links', forcelinks.links(links.map(d => {
	d.source = data[d.source.index];
	d.target = data[d.target.index];
	return d;
	})));
	*/
	}
	if (e.data.done && e.data.done < 10000 && e.data.cost > 1e-2) {
	worker.postMessage({
	maxIter: e.data.done + 10,
	});
	}
	//console.log('pos', pos);
	};
	});

	});

	function urquhart(diagram, distance) {
	var urquhart = d3.map();
	diagram.links()
	.forEach(function (link) {
	var v = d3.extent([link.source.index, link.target.index]);
	urquhart.set(v, link);
	});
	urquhart._remove = [];

	diagram.triangles()
	.forEach(function (t) {

	var l = 0,
	length = 0,
	i = -1,
	v;
	for (var j = 0; j < 3; j++) {
	var a = t[j],
	b = t[(j + 1) % 3];
	v = d3.extent([a.index, b.index]);
	if (!distance) {
	length = (a.x - b.x) * (a.x - b.x) + (a.y - b.y) * (a.y - b.y);
	} else {
	length = distance(a, b);
	}
	if (length >= l) {
	l = length;
	i = v;
	}
	}
	urquhart._remove.push(i);
	});
	urquhart._remove.forEach(function (i) {
	if (urquhart.has(i)) urquhart.remove(i);
	});
	return urquhart.values();
	}

	</script>
	</body>
	// create main global object
	var tsnejs = tsnejs \|\| { REVISION: 'ALPHA' };

	(function(global) {
	"use strict";

	// utility function
	var assert = function(condition, message) {
	if (!condition) { throw message \|\| "Assertion failed"; }
	}

	// syntax sugar
	var getopt = function(opt, field, defaultval) {
	if(opt.hasOwnProperty(field)) {
	return opt[field];
	} else {
	return defaultval;
	}
	}

	// return 0 mean unit standard deviation random number
	var return_v = false;
	var v_val = 0.0;
	var gaussRandom = function() {
	if(return_v) {
	return_v = false;
	return v_val;
	}
	var u = 2*Math.random()-1;
	var v = 2*Math.random()-1;
	var r = uu + vv;
	if(r == 0 \|\| r > 1) return gaussRandom();
	var c = Math.sqrt(-2*Math.log(r)/r);
	v_val = v*c; // cache this for next function call for efficiency
	return_v = true;
	return u*c;
	}

	// return random normal number
	var randn = function(mu, std){ return mu+gaussRandom()*std; }

	// utilitity that creates contiguous vector of zeros of size n
	var zeros = function(n) {
	if(typeof(n)==='undefined' \|\| isNaN(n)) { return []; }
	if(typeof ArrayBuffer === 'undefined') {
	// lacking browser support
	var arr = new Array(n);
	for(var i=0;i<n;i++) { arr[i]= 0; }
	return arr;
	} else {
	return new Float64Array(n); // typed arrays are faster
	}
	}

	// utility that returns 2d array filled with random numbers
	// or with value s, if provided
	var randn2d = function(n,d,s) {
	var uses = typeof s !== 'undefined';
	var x = [];
	for(var i=0;i<n;i++) {
	var xhere = [];
	for(var j=0;j<d;j++) {
	if(uses) {
	xhere.push(s);
	} else {
	xhere.push(randn(0.0, 1e-4));
	}
	}
	x.push(xhere);
	}
	return x;
	}

	// compute L2 distance between two vectors
	var L2 = function(x1, x2) {
	var D = x1.length;
	var d = 0;
	for(var i=0;i<D;i++) {
	var x1i = x1[i];
	var x2i = x2[i];
	d += (x1i-x2i)*(x1i-x2i);
	}
	return d;
	}

	// compute pairwise distance in all vectors in X
	var xtod = function(X) {
	var N = X.length;
	var dist = zeros(N * N); // allocate contiguous array
	for(var i=0;i<N;i++) {
	for(var j=i+1;j<N;j++) {
	var d = L2(X[i], X[j]);
	dist[i*N+j] = d;
	dist[j*N+i] = d;
	}
	}
	return dist;
	}

	// compute (p_{i\|j} + p_{j\|i})/(2n)
	var d2p = function(D, perplexity, tol) {
	var Nf = Math.sqrt(D.length); // this better be an integer
	var N = Math.floor(Nf);
	assert(N === Nf, "D should have square number of elements.");
	var Htarget = Math.log(perplexity); // target entropy of distribution
	var P = zeros(N * N); // temporary probability matrix

	var prow = zeros(N); // a temporary storage compartment
	for(var i=0;i<N;i++) {
	var betamin = -Infinity;
	var betamax = Infinity;
	var beta = 1; // initial value of precision
	var done = false;
	var maxtries = 50;

	// perform binary search to find a suitable precision beta
	// so that the entropy of the distribution is appropriate
	var num = 0;
	while(!done) {
	//debugger;

	// compute entropy and kernel row with beta precision
	var psum = 0.0;
	for(var j=0;j<N;j++) {
	var pj = Math.exp(- D[iN+j] beta);
	if(i===j) { pj = 0; } // we dont care about diagonals
	prow[j] = pj;
	psum += pj;
	}
	// normalize p and compute entropy
	var Hhere = 0.0;
	for(var j=0;j<N;j++) {
	if(psum == 0) {
	var pj = 0;
	} else {
	var pj = prow[j] / psum;
	}
	prow[j] = pj;
	if(pj > 1e-7) Hhere -= pj * Math.log(pj);
	}

	// adjust beta based on result
	if(Hhere > Htarget) {
	// entropy was too high (distribution too diffuse)
	// so we need to increase the precision for more peaky distribution
	betamin = beta; // move up the bounds
	if(betamax === Infinity) { beta = beta * 2; }
	else { beta = (beta + betamax) / 2; }

	} else {
	// converse case. make distrubtion less peaky
	betamax = beta;
	if(betamin === -Infinity) { beta = beta / 2; }
	else { beta = (beta + betamin) / 2; }
	}

	// stopping conditions: too many tries or got a good precision
	num++;
	if(Math.abs(Hhere - Htarget) < tol) { done = true; }
	if(num >= maxtries) { done = true; }
	}

	// console.log('data point ' + i + ' gets precision ' + beta + ' after ' + num + ' binary search steps.');
	// copy over the final prow to P at row i
	for(var j=0;j<N;j++) { P[i*N+j] = prow[j]; }

	} // end loop over examples i

	// symmetrize P and normalize it to sum to 1 over all ij
	var Pout = zeros(N * N);
	var N2 = N*2;
	for(var i=0;i<N;i++) {
	for(var j=0;j<N;j++) {
	Pout[iN+j] = Math.max((P[iN+j] + P[j*N+i])/N2, 1e-100);
	}
	}

	return Pout;
	}

	// helper function
	function sign(x) { return x > 0 ? 1 : x < 0 ? -1 : 0; }

	var tSNE = function(opt) {
	var opt = opt \|\| {};
	this.perplexity = getopt(opt, "perplexity", 30); // effective number of nearest neighbors
	this.dim = getopt(opt, "dim", 2); // by default 2-D tSNE
	this.epsilon = getopt(opt, "epsilon", 10); // learning rate

	this.iter = 0;
	}

	tSNE.prototype = {

	// this function takes a set of high-dimensional points
	// and creates matrix P from them using gaussian kernel
	initDataRaw: function(X) {
	var N = X.length;
	var D = X[0].length;
	assert(N > 0, " X is empty? You must have some data!");
	assert(D > 0, " X[0] is empty? Where is the data?");
	var dists = xtod(X); // convert X to distances using gaussian kernel
	this.P = d2p(dists, this.perplexity, 1e-4); // attach to object
	this.N = N; // back up the size of the dataset
	this.initSolution(); // refresh this
	},

	// this function takes a given distance matrix and creates
	// matrix P from them.
	// D is assumed to be provided as a list of lists, and should be symmetric
	initDataDist: function(D) {
	var N = D.length;
	assert(N > 0, " X is empty? You must have some data!");
	// convert D to a (fast) typed array version
	var dists = zeros(N * N); // allocate contiguous array
	for(var i=0;i<N;i++) {
	for(var j=i+1;j<N;j++) {
	var d = D[i][j];
	dists[i*N+j] = d;
	dists[j*N+i] = d;
	}
	}
	this.P = d2p(dists, this.perplexity, 1e-4);
	this.N = N;
	this.initSolution(); // refresh this
	},

	// (re)initializes the solution to random
	initSolution: function() {
	// generate random solution to t-SNE
	this.Y = randn2d(this.N, this.dim); // the solution
	this.gains = randn2d(this.N, this.dim, 1.0); // step gains to accelerate progress in unchanging directions
	this.ystep = randn2d(this.N, this.dim, 0.0); // momentum accumulator
	this.iter = 0;
	},

	// return pointer to current solution
	getSolution: function() {
	return this.Y;
	},

	// perform a single step of optimization to improve the embedding
	step: function() {
	this.iter += 1;
	var N = this.N;

	var cg = this.costGrad(this.Y); // evaluate gradient
	var cost = cg.cost;
	var grad = cg.grad;

	// perform gradient step
	var ymean = zeros(this.dim);
	for(var i=0;i<N;i++) {
	for(var d=0;d<this.dim;d++) {
	var gid = grad[i][d];
	var sid = this.ystep[i][d];
	var gainid = this.gains[i][d];

	// compute gain update
	var newgain = sign(gid) === sign(sid) ? gainid * 0.8 : gainid + 0.2;
	if(newgain < 0.01) newgain = 0.01; // clamp
	this.gains[i][d] = newgain; // store for next turn

	// compute momentum step direction
	var momval = this.iter < 250 ? 0.5 : 0.8;
	var newsid = momval * sid - this.epsilon * newgain * grad[i][d];
	this.ystep[i][d] = newsid; // remember the step we took

	// step!
	this.Y[i][d] += newsid;

	ymean[d] += this.Y[i][d]; // accumulate mean so that we can center later
	}
	}

	// reproject Y to be zero mean
	for(var i=0;i<N;i++) {
	for(var d=0;d<this.dim;d++) {
	this.Y[i][d] -= ymean[d]/N;
	}
	}

	//if(this.iter%100===0) console.log('iter ' + this.iter + ', cost: ' + cost);
	return cost; // return current cost
	},

	// for debugging: gradient check
	debugGrad: function() {
	var N = this.N;

	var cg = this.costGrad(this.Y); // evaluate gradient
	var cost = cg.cost;
	var grad = cg.grad;

	var e = 1e-5;
	for(var i=0;i<N;i++) {
	for(var d=0;d<this.dim;d++) {
	var yold = this.Y[i][d];

	this.Y[i][d] = yold + e;
	var cg0 = this.costGrad(this.Y);

	this.Y[i][d] = yold - e;
	var cg1 = this.costGrad(this.Y);

	var analytic = grad[i][d];
	var numerical = (cg0.cost - cg1.cost) / ( 2 * e );
	console.log(i + ',' + d + ': gradcheck analytic: ' + analytic + ' vs. numerical: ' + numerical);

	this.Y[i][d] = yold;
	}
	}
	},

	// return cost and gradient, given an arrangement
	costGrad: function(Y) {
	var N = this.N;
	var dim = this.dim; // dim of output space
	var P = this.P;

	var pmul = this.iter < 100 ? 4 : 1; // trick that helps with local optima

	// compute current Q distribution, unnormalized first
	var Qu = zeros(N * N);
	var qsum = 0.0;
	for(var i=0;i<N;i++) {
	for(var j=i+1;j<N;j++) {
	var dsum = 0.0;
	for(var d=0;d<dim;d++) {
	var dhere = Y[i][d] - Y[j][d];
	dsum += dhere * dhere;
	}
	var qu = 1.0 / (1.0 + dsum); // Student t-distribution
	Qu[i*N+j] = qu;
	Qu[j*N+i] = qu;
	qsum += 2 * qu;
	}
	}
	// normalize Q distribution to sum to 1
	var NN = N*N;
	var Q = zeros(NN);
	for(var q=0;q<NN;q++) { Q[q] = Math.max(Qu[q] / qsum, 1e-100); }

	var cost = 0.0;
	var grad = [];
	for(var i=0;i<N;i++) {
	var gsum = new Array(dim); // init grad for point i
	for(var d=0;d<dim;d++) { gsum[d] = 0.0; }
	for(var j=0;j<N;j++) {
	cost += - P[iN+j] Math.log(Q[i*N+j]); // accumulate cost (the non-constant portion at least...)
	var premult = 4 * (pmul * P[iN+j] - Q[iN+j]) * Qu[i*N+j];
	for(var d=0;d<dim;d++) {
	gsum[d] += premult * (Y[i][d] - Y[j][d]);
	}
	}
	grad.push(gsum);
	}

	return {cost: cost, grad: grad};
	}
	}

	global.tSNE = tSNE; // export tSNE class
	})(tsnejs);


	// export the library to window, or to module in nodejs
	(function(lib) {
	"use strict";
	if (typeof module === "undefined" \|\| typeof module.exports === "undefined") {
	if (typeof window == "object")
	window.tsnejs = lib; // in ordinary browser attach library to window
	} else {
	module.exports = lib; // in nodejs
	}
	})(tsnejs);
	importScripts('https://d3js.org/d3.v4.min.js');

	// in worker.onmessage add : `if (e.data.log) console.log.apply(this, e.data.log);`
	console.log = function() {
	self.postMessage({ log: [...arguments] });
	}

	function levenshtein(a, b) {
	var t = [], u, i, j, m = a.length, n = b.length;
	if (!m) { return n; }
	if (!n) { return m; }
	for (j = 0; j <= n; j++) { t[j] = j; }
	for (i = 1; i <= m; i++) {
	for (u = [i], j = 1; j <= n; j++) {
	u[j] = a[i - 1] === b[j - 1] ? t[j - 1] : Math.min(t[j - 1], t[j], u[j - 1]) + 1;
	} t = u;
	} return u[n];
	}

	let iterations = 0,
	model;

	self.onmessage = function(e) {
	const msg = e.data,
	data = msg.data,
	maxIter = msg.maxIter \|\| 500,
	perplexity = msg.perplexity \|\| 30;

	var z = 0;
	let dists = msg.dist;
	if (data && !dists){
	let now = performance.now();
	let tfidf = {};
	d3.set(d3.merge(data.map(d => d.props)))
	.values()
	.map(d => {
	let t = data.filter(e => e.props.indexOf(d) > -1).length;
	if (t > 1) tfidf[d] = 1/t;
	});
	self.postMessage({"tfidf": tfidf});
	let similarities = data.map(
	a => data.map(
	b => b.props.filter(e => a.props.indexOf(e) > -1)
	.map(e => tfidf[e])
	.reduce((a,b) => a+b, 0)
	)
	);
	console.log("similarities", similarities);
	dists = similarities.map(r => r.map(s => Math.exp(-2 * s)));

	console.log('computed', data.length * data.length,'distances in', Math.round(performance.now()-now),'ms');
	}

	// console.log(dists);

	// dists = null;
	if (dists) {
	model = new tsnejs.tSNE({
	dim: msg.dim,
	perplexity: perplexity,
	});
	model.initDataDist(dists);
	}

	let startpos = model.getSolution().map(d=>d.slice()),
	pos;

	while (iterations++ < maxIter) {
	// every time you call this, solution gets better
	model.step();

	pos = model.getSolution();
	//if (iterations%10 == 0) console.log("pos",pos);
	// Y is an array of 2-D points that you can plot
	self.postMessage({
	iterations: iterations - 1,
	pos: pos,
	//log: [ 'step', iterations-1 ]
	});

	}

	let cost = startpos
	.map((d,i) => sqdist(d, pos[i]))
	.reduce ((a,b) => a + b, 0) / pos.length / Math.max(...pos.map(d => Math.abs(d[0]) + Math.abs(d[1])));

	self.postMessage({
	done: iterations - 1,
	cost: cost,
	log: [ 'done', iterations - 1, cost ]
	});
	};

	function sqdist (a,b) {
	let d = [a[0] - b[0], a[1] - b[1]].map(Math.abs);
	return Math.max(d[0], d[1]);
	}