#!/usr/local/bin/perl
use Inline C;
use Mojolicious::Lite;
use Mojo::JSON qw(decode_json encode_json to_json);
use Encode qw(decode encode);
use Mojo::Server::Daemon;

# -cbow 1 -size 200 -window 8 -negative 25 -hs 0 -sample 1e-4 -threads 40 -binary 1 -iter 15
init_net("vectors14.bin");

get '/' => sub {
  my $c    = shift;
	my $word=$c->param('word');
	my $no_nbs=$c->param('n') || 50;
	my $list;
	if(defined($word) && $word !~ /^\s*$/) {
		$c->inactivity_timeout(300);
		$c->app->log->debug('Looking for neighbours of '.$word);
		$list = get_neighbours(encode("iso-8859-1", $word), $no_nbs);
	}
  $c->render(template=>"index", word=>$word, no_nbs=>$no_nbs, list=> $list);
};

app->start;

exit;

__END__

__C__
#include <stdio.h>
#include <string.h>
#include <math.h>
#include <malloc.h>
#include <stdlib.h>    //strlen

#define max_size 2000
#define max_w 50
#define MAX_NEIGHBOURS 1000

//the thread function
void *connection_handler(void *);
 
char *bestw[MAX_NEIGHBOURS];
char file_name[max_size], st[100][max_size];
float dist, len, bestd[MAX_NEIGHBOURS], vec[max_size];
long long words, size, a, b, c, d, cn, bi[100], besti[MAX_NEIGHBOURS];
char ch;
float *M;
char *vocab;
char *stringBuffer;

int init_net(char *file_name) {
  FILE *f;

	stringBuffer = malloc(64000);
  f = fopen(file_name, "rb");
  if (f == NULL) {
    printf("Input file %s not found\n", file_name);
    return -1;
  }
  fscanf(f, "%lld", &words);
  fscanf(f, "%lld", &size);
  vocab = (char *)malloc((long long)words * max_w * sizeof(char));
  for (a = 0; a < MAX_NEIGHBOURS; a++) bestw[a] = (char *)malloc(max_size * sizeof(char));
  M = (float *)malloc((long long)words * (long long)size * sizeof(float));
  if (M == NULL) {
    printf("Cannot allocate memory: %lld MB    %lld  %lld\n", (long long)words * size * sizeof(float) / 1048576, words, size);
    return -1;
  }
  for (b = 0; b < words; b++) {
    a = 0;
    while (1) {
      vocab[b * max_w + a] = fgetc(f);
      if (feof(f) || (vocab[b * max_w + a] == ' ')) break;
      if ((a < max_w) && (vocab[b * max_w + a] != '\n')) a++;
    }
    vocab[b * max_w + a] = 0;
    fread(&M[b * size], sizeof(float), size, f);
    len = 0;
    for (a = 0; a < size; a++) len += M[a + b * size] * M[a + b * size];
    len = sqrt(len);
    for (a = 0; a < size; a++) M[a + b * size] /= len;
  }
  fclose(f);
	return 0;
}

SV *get_neighbours(char *st1, int N) {
  if(N>MAX_NEIGHBOURS) N=MAX_NEIGHBOURS;

	FILE *out=stdout;
	*stringBuffer=0;

	for (a = 0; a < N; a++) bestd[a] = 0;
	for (a = 0; a < N; a++) bestw[a][0] = 0;
	a = 0;
	cn = 0;
	b = 0;
	c = 0;
	while (1) {
		st[cn][b] = st1[c];
		b++;
		c++;
		st[cn][b] = 0;
		if (st1[c] == 0) break;
		if (st1[c] == ' ') {
			cn++;
			b = 0;
			c++;
		}
	}
	cn++;
	for (a = 0; a < cn; a++) {
		for (b = 0; b < words; b++) if (!strcmp(&vocab[b * max_w], st[a])) break;
		if (b == words) b = -1;
		bi[a] = b;
		fprintf(stderr, "Word: \"%s\"  Position in vocabulary: %lld\n", st[a], bi[a]);
		if (b == -1) {
			fprintf(stderr, "Out of dictionary word!\n");
			break;
		}
	}
	if (b == -1) goto end;
	for (a = 0; a < size; a++) vec[a] = 0;
	for (b = 0; b < cn; b++) {
		if (bi[b] == -1) continue;
		for (a = 0; a < size; a++) vec[a] += M[a + bi[b] * size];
	}
	len = 0;
	for (a = 0; a < size; a++) len += vec[a] * vec[a];
	len = sqrt(len);
	for (a = 0; a < size; a++) vec[a] /= len;
	for (a = 0; a < N; a++) bestd[a] = -1;
	for (a = 0; a < N; a++) bestw[a][0] = 0;
	for (c = 0; c < words; c++) {
		a = 0;
// don not skip taget word
//		for (b = 0; b < cn; b++) if (bi[b] == c) a = 1;
//		if (a == 1) continue;
		dist = 0;
		for (a = 0; a < size; a++) dist += vec[a] * M[a + c * size];
		for (a = 0; a < N; a++) {
			if (dist > bestd[a]) {
				for (d = N - 1; d > a; d--) {
					bestd[d] = bestd[d - 1];
					strcpy(bestw[d], bestw[d - 1]);
				}
				bestd[a] = dist;
				besti[a] = c;
				strcpy(bestw[a], &vocab[c * max_w]);
				break;
			}
		}
	}
	AV* array = newAV();
	for (a = 0; a < N; a++) {
		HV* hash = newHV();
		hv_store(hash, "word", strlen("word"), newSVpvf(bestw[a], 0), 0);
		hv_store(hash, "dist", strlen("dist"), newSVnv(bestd[a]), 0);
		AV *vector = newAV();
		for (b = 0; b < size; b++) {
			av_push(vector, newSVnv(M[b + besti[a] * size]));
		}
		hv_store(hash, "vector", strlen("vector"), newRV_noinc((SV*)vector), 0);
		av_push(array, newRV_noinc((SV*)hash));
	}
 end:
	return newRV_noinc((SV*)array);
}


__DATA__

@@ index.html.ep
<!DOCTYPE html>
<html>
<head>
	<title>DeReKo-Word-Vector-Distances</title>
	<script src="http://code.jquery.com/jquery-latest.min.js"></script>
	<script src="//d3js.org/d3.v3.min.js" charset="utf-8"></script>
	<script src="http://klinux10/word2vec/tsne.js"></script>
<style>
svg {
//  border: 1px solid #333;
//  margin-right: 5px;
//  margin-bottom: 5px;
}
#wrapper {
    width: 100%;
//   border: 1px solid red; 
    overflow: hidden; /* will contain if #first is longer than #second */
}
#first {
 width: 300px;
 margin-right: 20px;
    float:left; /* add this */
//    border: 1px solid green;
}
#second {
    border: 1px solid #333;
    overflow: hidden; /* if you don't want #second to wrap below #first */
}
</style>
<script>

var opt = {epsilon: 1, perplexity: 8};
var T = new tsnejs.tSNE(opt); // create a tSNE instance

var Y;

var data;

function updateEmbedding() {
  var Y = T.getSolution();
  svg.selectAll('.u')
    .data(data.words)
    .attr("transform", function(d, i) { return "translate(" +
                                          ((Y[i][0]*20*ss + tx) + 400) + "," +
                                          ((Y[i][1]*20*ss + ty) + 400) + ")"; });
}

var svg;
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", 800)
    .attr("height", 800);

    var g = svg.selectAll(".b")
      .data(data.words)
      .enter().append("g")
      .attr("class", "u");

    g.append("text")
      .attr("text-anchor", "top")
      .attr("font-size", 12)
      .attr("fill", function(d) {
				if(d == data.target) {
					return "red";
				} else {
					return "#333"
				}
			})
      .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);
}

function step() {
  var i = T.iter;
  if(i >= 1000) {
   stopStep();
  } else {
    var cost = T.step(); // do a few steps
    $("#cost").html("iteration " + i + ", 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);
    //step();
	}

$(window).xxload(function() {
  $.getJSON( "http://klinux10/word2vec/dings.json", function( j ) {
    data = j;
    T.initDataRaw(data.vecs); // init embedding
    drawEmbedding(); // draw initial embedding

    // T.debugGrad();
    iter_id = setInterval(step, 1);
    // step();

  });
});

</script>
</head>
<body>
	<p>Word vector model based on  DeReKo-2015-II. Trained with <a href="https://code.google.com/p/word2vec/">word2vec</a> using the following parameters:</p>
  <pre>
-cbow 1 -size 300 -window 7 -negative 5 -hs 0 -sample 1e-5 -threads 44 -binary 1 -iter 5
</pre>
</p>
  <form action="<%=url_for('/')->to_abs%>" method="GET">
    Word: <input type="text" name="word" value="<%= $word %>"> 
    Neighbours: <input type="text" name="n" value="<%= $no_nbs %>">
    <input type="submit" value="Show neighbours">
  </form>
  <br>
	% if($list) {
  <h3>Nearest neighbours of "<%= $word %>"</h3>
<div id="wrapper">
    <table id="first">
		<tr>
     <th align="right">Pos.</th><th align="left">Word</th><th align="right">Cosine dist.</th>
   </tr>
	% my $i=1; my @words; my @vecs; for my $item (@$list) {
  % push @vecs, $item->{vector};
  % push @words, $item->{word};
		<tr>
     <td align="right">
  		<%= $i++ %>.
     </td>
     <td>
  		<a href="/?word=<%= $item->{word} %>">
				<%= $item->{word} %>
			</a>
     </td>
     <td align="right">
  		<%= sprintf("%.3f", $item->{dist}) %>
     </td>
		</tr>
	% }
  </table>
		<script>
			% use Mojo::ByteStream 'b';
$(window).load(function() {
			showMap(<%= b(Mojo::JSON::to_json({target => $word, words => \@words, vecs => \@vecs})); %>);
});
    </script>
	% }
<div id="second" style="width:800px; height:800px; font-family: arial;">
<div id="embed"></div>
<div id="cost" style="text-align:left; font-family: Impact;"></div>
  </div>
  </div>
  </body>
</html>