| <!DOCTYPE html> |
| <html> |
| <head> |
| <title>DeReKo-Word-Vector-Distances: <%= $word %></title> |
| <link rel="stylesheet" href="//code.jquery.com/ui/1.12.1/themes/base/jquery-ui.css"> |
| <script src="http://code.jquery.com/jquery-latest.min.js"></script> |
| <script |
| src="http://code.jquery.com/ui/1.12.1/jquery-ui.min.js" |
| integrity="sha256-VazP97ZCwtekAsvgPBSUwPFKdrwD3unUfSGVYrahUqU=" |
| crossorigin="anonymous"></script> |
| <script> |
| $(function() { |
| $( document ).tooltip({ |
| content: function() { |
| return $(this).attr('title'); |
| }} |
| ) |
| }) |
| </script> |
| <script src="//d3js.org/d3.v3.min.js" charset="utf-8"></script> |
| <script src="/word2vec/js/tsne.js"></script> |
| <script src="/word2vec/js/som.js"></script> |
| <script src="/word2vec/js/labeler.js"></script> |
| <style> |
| body, input { |
| font-family: Arial, sans-serif; |
| font-size: 11pt; |
| } |
| |
| .ui-tooltip-content { |
| font-size: 9pt; |
| color: #222222; |
| } |
| |
| svg > .ui-tooltip-content { |
| font-size: 8pt; |
| color: #222222; |
| } |
| |
| a.merged { |
| color: green; |
| fill: green; |
| } |
| |
| #first a { |
| text-decoration: none; |
| } |
| |
| a.marked, #first a.marked { |
| text-decoration: underline; |
| } |
| |
| a.target { |
| color: red; |
| fill: red; |
| } |
| |
| #collocators { |
| margin-bottom: 15px; |
| } |
| |
| #wrapper { |
| width: 100%; |
| // border: 1px solid red; |
| overflow: hidden; /* will contain if #first is longer than #second */ |
| } |
| #first { |
| margin-right: 20px; |
| float: left; |
| // border: 1px solid green; |
| } |
| #second { |
| border: 1px solid #333; |
| overflow: hidden; /* if you don't want #second to wrap below #first */ |
| } |
| #som2 svg { |
| border: 1px solid #333; |
| } |
| |
| #cost { |
| font-size: 8pt; |
| color: #222222; |
| margin-top: 4px; |
| margin-bottom: 12px; |
| } |
| |
| #sominfo1, #sominfo { |
| font-size: 8pt; |
| color: #222222; |
| margin-top: 0px; |
| } |
| |
| #somcolor1, #somcolor2, #somcolor3 { |
| display: inline-block; |
| height: 10px; |
| width: 10px; |
| } |
| |
| #third { |
| border: 1px solid #333; |
| } |
| |
| </style> |
| <script> |
| |
| var opt = {epsilon: <%= $epsilon %>, perplexity: <%= $perplexity %>}, |
| mapWidth = 800, // width map |
| mapHeight = 800, |
| jitterRadius = 7; |
| |
| var T = new tsnejs.tSNE(opt); // create a tSNE instance |
| |
| var Y; |
| |
| var data; |
| var labeler; |
| |
| function applyJitter() { |
| svg.selectAll('.tsnet') |
| .data(labels) |
| .transition() |
| .duration(50) |
| .attr("transform", function(d, i) { |
| T.Y[i][0] = (d.x - mapWidth/2 - tx)/ss/20; |
| T.Y[i][1] = (d.y - mapHeight/2 - ty)/ss/20; |
| return "translate(" + |
| (d.x) + "," + |
| (d.y) + ")"; |
| }); |
| } |
| |
| function updateEmbedding() { |
| var Y = T.getSolution(); |
| svg.selectAll('.tsnet') |
| .data(data.words) |
| .attr("transform", function(d, i) { |
| return "translate(" + |
| ((Y[i][0]*20*ss + tx) + mapWidth/2) + "," + |
| ((Y[i][1]*20*ss + ty) + mapHeight/2) + ")"; }); |
| } |
| |
| var svg; |
| var labels = []; |
| var anchor_array = []; |
| var text; |
| |
| function drawEmbedding() { |
| $("#embed").empty(); |
| var div = d3.select("#embed"); |
| |
| // get min and max in each column of Y |
| var Y = T.Y; |
| |
| svg = div.append("svg") // svg is global |
| .attr("width", mapWidth) |
| .attr("height", mapHeight); |
| |
| var g = svg.selectAll(".b") |
| .data(data.words) |
| .enter().append("g") |
| .attr("class", "tsnet"); |
| |
| g.append("a") |
| .attr("xlink:href", function(word) { |
| return (data.urlprefix+word);}) |
| .attr("class", function(d, i) { |
| var res=""; |
| if(data.marked[i]) { |
| res="marked "; |
| } |
| if(data.target.indexOf(" "+d+" ") >= 0) { |
| return res+"target"; |
| } else if(data.ranks[i] < data.mergedEnd) { |
| return res+"merged"; |
| } else { |
| return res; |
| } |
| }) |
| .attr("title", function(d, i) { |
| if(data.mergedEnd > 0) { |
| if(data.ranks[i] >= data.mergedEnd) { |
| return "rank: "+i +" "+"freq. rank: "+(data.ranks[i]).toString().replace(/\B(?=(\d{3})+(?!\d))/g, ","); |
| } else { |
| return "rank: "+i +" "+"freq. rank: "+data.ranks[i].toString().replace(/\B(?=(\d{3})+(?!\d))/g, ",") + " (merged vocab)"; |
| } |
| } else { |
| return "rank: "+i +" "+"freq. rank: "+data.ranks[i].toString().replace(/\B(?=(\d{3})+(?!\d))/g, ","); |
| } |
| }) |
| .append("text") |
| .attr("text-anchor", "top") |
| .attr("font-size", 12) |
| .text(function(d) { return d; }); |
| |
| var zoomListener = d3.behavior.zoom() |
| .scaleExtent([0.1, 10]) |
| .center([0,0]) |
| .on("zoom", zoomHandler); |
| zoomListener(svg); |
| } |
| |
| var tx=0, ty=0; |
| var ss=1; |
| var iter_id=-1; |
| |
| function zoomHandler() { |
| tx = d3.event.translate[0]; |
| ty = d3.event.translate[1]; |
| ss = d3.event.scale; |
| updateEmbedding(); |
| } |
| |
| var stepnum = 0; |
| |
| function stopStep() { |
| clearInterval(iter_id); |
| text = svg.selectAll("text"); |
| |
| // jitter function needs different data and co-ordinate representation |
| labels = d3.range(data.words.length).map(function(i) { |
| var x = (T.Y[i][0]*20*ss + tx) + mapWidth/2; |
| var y = (T.Y[i][1]*20*ss + ty) + mapHeight/2; |
| anchor_array.push({x: x, y: y, r: jitterRadius}); |
| return { |
| x: x, |
| y: y, |
| name: data.words[i] |
| }; |
| }); |
| |
| // get the actual label bounding boxes for the jitter function |
| var index = 0; |
| text.each(function() { |
| labels[index].width = this.getBBox().width; |
| labels[index].height = this.getBBox().height; |
| index += 1; |
| }); |
| |
| |
| // setTimeout(updateEmbedding, 1); |
| // setTimeout( |
| labeler = d3.labeler() |
| .label(labels) |
| .anchor(anchor_array) |
| .width(mapWidth) |
| .height(mapHeight) |
| .update(applyJitter); |
| // .start(1000); |
| |
| iter_id = setInterval(jitterStep, 1); |
| } |
| |
| var jitter_i=0; |
| |
| function jitterStep() { |
| if(jitter_i++ > 100) { |
| clearInterval(iter_id); |
| } else { |
| labeler.start2(10); |
| applyJitter(); |
| } |
| } |
| |
| var last_cost=1000; |
| |
| function step() { |
| var i = T.iter; |
| |
| if(i > <%= $no_iterations %>) { |
| stopStep(); |
| } else { |
| var cost = Math.round(T.step() * 100000) / 100000; // do a few steps |
| $("#cost").html("tsne iteration " + i + ", cost: " + cost.toFixed(5)); |
| if(i % 250 == 0 && cost >= last_cost) { |
| stopStep(); |
| } else { |
| last_cost = cost; |
| updateEmbedding(); |
| } |
| } |
| } |
| |
| function showMap(j) { |
| data=j; |
| T.iter=0; |
| T.initDataRaw(data.vecs); // init embedding |
| drawEmbedding(); // draw initial embedding |
| |
| if(iter_id >= 0) { |
| clearInterval(iter_id); |
| } |
| //T.debugGrad(); |
| iter_id = setInterval(step, 1); |
| if(<%= $show_som %>) { |
| makeSOM(j, <%= $no_iterations %>); |
| } |
| } |
| |
| </script> |
| </head> |
| <body> |
| <form method="GET"> |
| word(s): |
| <input type="text" name="word" size="20" value="<%= $word %>" title="When looking for multiple words use spaces as separators to search around the average vector and | as separator to get the neighbours for each word."> |
| % if($mergedEnd > 0) { |
| backw. <input type="checkbox" name="sbf" value="1" <%= ($searchBaseVocabFirst ? "checked" : "") %> title="If checkecked base vocabulary will be searched first. Otherwise merged vocabulray will be searched first."> |
| % } |
| max. neighbours: <input type="text" size="8" name="n" value="<%= $no_nbs %>"> |
| max. iterations: <input type="text" name="N" size="8" value="<%= $no_iterations %>"> |
| SOM <input type="checkbox" name="som" value="1" <%= ($show_som ? "checked" : "") %>> |
| % if($collocators) { |
| <span> </span>sort collocators by |
| <select name="sort"> |
| <option value="0" <%= ($sort!=1? "selected":"") %>>responsiveness</option> |
| <option value="1" <%= ($sort==1? "selected":"") %>>mean p</option> |
| </select> |
| % } |
| <span> </span><input type="submit" value="Show"> |
| </form> |
| <br> |
| % if($lists) { |
| <div id="wrapper"> |
| <table id="first"> |
| <tr> |
| <th align="right">#</th><th align="right">cos</th><th align="left">paradigmatic</th> |
| % if($collocators) { |
| <th title="Position in winodw around target word. Absolute value can be too low because of sub-sampling frequent words.">@</th><th align="right" title=""Responsivenes" of the collocator at the relative position @. Approximation of the probability that the combination of the target word and the collocator at the relative position @ come from the corpus.">resp.</th><th title="Probability of the collocator at window location @."align="right">p(c<sub><small>@</small></sub>)</th><th align="right">Σp(c<sub><small>@</small></sub>)/|w|</th><th align="left">syntagmatic</th> |
| % } |
| </tr> |
| % my $j=0; my @words; my @vecs; my @ranks; my @marked; |
| % for my $list (@$lists) { |
| % my $i=0; while($list) { |
| % my $item = (@$list)[$i]; |
| % my $c = ($collocators? (@$collocators)[$i] : 0); |
| % last if(!$c && !$item); |
| <tr> |
| <td align="right"> |
| <%= ++$i %>. |
| </td> |
| % if($item) { |
| % if(!grep{$_ eq $item->{word}} @words) { |
| % push @vecs, $item->{vector}; |
| % push @words, $item->{word}; |
| % push @ranks, $item->{rank}; |
| % push @marked, ($marked->{$item->{word}}? 1 : 0); |
| % } |
| <td align="right"> |
| <%= sprintf("%.3f", $item->{dist}) %> |
| </td> |
| <td> |
| % my $class = ($marked->{$item->{word}}? "marked " : ""); |
| % my $r = $item->{rank}; |
| % if($r < $mergedEnd) { |
| % $class .= "merged"; |
| % $r .= " (merged vocab)"; |
| % } elsif($mergedEnd!=0 && $r > $mergedEnd) { |
| % $r -= $mergedEnd; |
| % } |
| <a class="<%= $class =%>" |
| title="freq. rank: <%= $r =%>" |
| href="<%= url_with->query([word => $item->{word}]) =%>"> |
| <%= $item->{word} =%> |
| </a> |
| </td> |
| % } else { |
| <td colspan="2"/> |
| % } |
| % if($c) { |
| <td align="right"> |
| <%= $c->{pos} %>: |
| </td> |
| <td align="right"> |
| <%= sprintf("%.3f", $c->{dist}) %> |
| </td> |
| <td align="right"> |
| <%= sprintf("%.3e", $c->{norm}) %> |
| </td> |
| <td align="right"> |
| <%= sprintf("%.3e", $c->{sum}) %> |
| </td> |
| <td align="left"> |
| <a href="<%= url_with->query([word => $c->{word}]) =%>"> |
| <%= $c->{word} %> |
| </td> |
| % } else { |
| <td colspan="5"/> |
| % } |
| </tr> |
| % } |
| % } |
| </table> |
| <script> |
| % use Mojo::ByteStream 'b'; |
| % my $urlprefix = url_with->query([word=>'']); |
| $(window).load(function() { |
| showMap(<%= b(Mojo::JSON::to_json({target => " $word ", mergedEnd=> $mergedEnd, words => \@words, vecs => \@vecs, ranks => \@ranks, marked => \@marked, urlprefix => $urlprefix})); %>); |
| }); |
| </script> |
| % } |
| <div id="second" style="width:800px; height:800px; font-family: arial;"> |
| <div id="embed"> |
| </div> |
| </div> |
| <div id="cost"></div> |
| % if($show_som) { |
| <div id="som2"> |
| </div> |
| <div id="sominfo1"><span id="somcolor1"> </span> <span id="somword1"> </span> <span id="somcolor2"> </span> <span id="somword2"> </span> <span id="somcolor3"> </span></div> |
| <div id="sominfo">SOM iteration <span id="iterations">0</span></div> |
| % } |
| </div> |
| % if($training_args) { |
| <p> |
| Word vector model trained with <a href="https://code.google.com/p/word2vec/">word2vec</a> using the following parameters: <pre><%= $training_args %></pre> |
| </p> |
| % } |
| </body> |
| </html> |