w2v-server.pl

#!/usr/local/bin/perl
use Inline C;
use Inline C => Config => CLEAN_AFTER_BUILD => 0, BUILD_NOISY => 1, ccflags =>  $Config{ccflags}." -I/vol/work/kupietz/Work2/kl/trunk/CollocatorDB -I, -L. -Wall -O4", libs => "-shared -lpthread -lcollocatordb -lrt -lsnappy -lz -lbz2 -llz4 -lzstd -lrocksdb -lgomp";
#use Inline C => Config => BUILD_NOISY => 1, CFLAGS => $Config{cflags}." -O4 -mtune k9";
#use Inline C => Config => CLEAN_AFTER_BUILD => 0, ccflags => $Config{ccflags}." -Ofast -march k8 -mtune k8 ";
use Mojolicious::Lite;
use Mojo::JSON qw(decode_json encode_json to_json);
use base 'Mojolicious::Plugin';

use Encode qw(decode encode);
use Getopt::Std;
use Mojo::Server::Daemon;
use Cwd;

app->static->paths->[0] = getcwd;

plugin 'Log::Access';
plugin "RequestBase";

our $opt_i = 0; # latin1-input?
our $opt_l = undef;
our $opt_p = 5676;
our $opt_m;
our $opt_M;
our $opt_n = '';
our $opt_d;
our $opt_D;
our $opt_G;

my %marked;
my $title="";
my $training_args="";
my $mergedEnd=0;
my %cache;
my %cccache; # classic collocator cache
my %spcache; # similar profile cache

getopts('d:D:Gil:p:m:n:M:');

if($opt_M) {
  open my $handle, '<:encoding(UTF-8)', $opt_M
    or die "Can't open '$opt_M' for reading: $!";
  while(<$handle>) {
    foreach my $mw (split /\s+/) {
      $marked{$mw}=1
    }
  }
  close($handle);
}

# -cbow 1 -size 200 -window 8 -negative 25 -hs 0 -sample 1e-4 -threads 40 -binary 1 -iter 15
if(!$ARGV[0]) {
  init_net("vectors15.bin", $opt_n, ($opt_i? 1 : 0));
} else {
  init_net($ARGV[0], $opt_n, ($opt_i? 1 : 0));
  if(open(FILE, "$ARGV[0].args")) {
    $training_args = <FILE>;
  }
  close(FILE);
  $title = fname2corpusname($ARGV[0]);
}

my $have_sprofiles = load_sprofiles($ARGV[0]);

if($opt_m) {
  $mergedEnd = mergeVectors($opt_m);
  $title = "<span class=\"merged\">" . $title . "</span> vs. " . fname2corpusname($opt_m);
}


if($opt_d) { # -d: dump  vecs and exit
	dump_vecs($opt_d);
	exit;
}

if($opt_D) { # -D: dump  vecs for numpy and exit
	dump_for_numpy($opt_D);
	exit;
}

my $daemon = Mojo::Server::Daemon->new(
    app    => app,
    listen => ['http://'.($opt_l ? $opt_l : '*').":$opt_p"]
);

if($opt_G) {
  print "Filtering garbage\n";
  filter_garbage();
}

get '*/js/*' => sub {
	my $c = shift;
	my $url = $c->req->url;
	$url =~ s@/derekovecs@@g;
  $c->app->log->info("GET: " . $url);
	$c->reply->static($url);
};

get '*/css/*' => sub {
	my $c = shift;
	my $url = $c->req->url;
	$url =~ s@/derekovecs/@/@g;
  $c->app->log->info("GET: " . $url);
	$c->reply->static($url);
};

sub fname2corpusname {
  ($_) = @_;
  s@.*/@@;
  s@\.en@-en@;
  s@\..*@@;
  return $_;
}

sub getClassicCollocatorsCached {
  my ($c, $word) = @_;
  my $s2 = "";
  if($word > $mergedEnd) {
    $word-=$mergedEnd;
  }

  if($opt_p >= 5000 && $opt_p < 5600) { # German non-reference
    open PIPE, "GET http://compute:5673/getClassicCollocators?w=$word  |" or
      open PIPE, "GET http://klinux10:5673/getClassicCollocators?w=$word  |";
  }
  if(!$cccache{$word}) {
    $c->app->log->info("Getting classic collocates of $word.");
    $cccache{$word} = getClassicCollocators($word);
    $cccache{$word} =~ s/:(-?)(nan|inf)/:"${1}${2}"/g;
  } else {
    $c->app->log->info("Getting classic collocates for $word from cache.");
  }
  if($opt_p >= 5000 && $opt_p < 5600) { # German non-reference
    while(<PIPE>) {
      $s2 .= $_;
    }
    close(PIPE);
  }

  if(length($s2) > 2000) {
    my $d1 = decode_json($cccache{$word});
    my $d2 = decode_json($s2);
    my %d2ld;
    my $minLd = 14;
    foreach my $i (@{$d2->{collocates}}) {
      $d2ld{$i->{word}}=$i->{ld};
      $minLd=$i->{ld} if($i->{ld} < $minLd);
    }
    foreach my $i (@{$d1->{collocates}}) {
      my $w = $i->{word};
      $i->{delta} = $i->{ld} - (defined $d2ld{$w} ? $d2ld{$w} : $minLd-0.1);
    }
    return(encode_json($d1));
  } else {
    my $d1 = decode_json($cccache{$word});
    foreach my $i (@{$d1->{collocates}}) {
      $i->{delta} = 0;
    }
    return(encode_json($d1));
  }
}

sub getSimilarProfilesCached {
  my ($c, $word) = @_;
  if(!$spcache{$word}) {
    $spcache{$word} = getSimilarProfiles($word);
  } else {
    $c->app->log->info("Getting similar profiles for $word from cache:");
  }
  return $spcache{$word};
}

post '/derekovecs/getVecsByRanks' => sub {
  my $self = shift;
  my $vec = getVecs($self->req->json);
  $self->render(json => $vec);
};

any '*/getClassicCollocators' => sub {
  my $self = shift;
  $self->render(data => getClassicCollocatorsCached($self, $self->param("w") ? $self->param("w") : $self->req->json), format=>'json');
};

any '/getClassicCollocators' => sub {
  my $self = shift;
  $self->render(data => getClassicCollocatorsCached($self, $self->param("w") ? $self->param("w") : $self->req->json), format=>'json');
};

any '/getBiggestVocabDistances' => sub {
  my $self = shift;
  $self->render(data => getBiggestMergedDifferences(), format=>'json');
};

any '*/getBiggestVocabDistances' => sub {
  my $self = shift;
  $self->render(data => getBiggestMergedDifferences(), format=>'json');
};

any '*/getPosWiseW2VCollocators' => sub {
  my $self = shift;
  $self->render(data => getPosWiseW2VCollocatorsAsTsv($self->param("w"),
                                            ($self->param("max")? $self->param("max") : 200),
                                            ($self->param("cutoff")? $self->param("cutoff") :750000),
                                            ($self->param("threshold")? $self->param("threshold") : 0.2)),
                                            format=>'tsv');
};

any '/getPosWiseW2VCollocators' => sub {
  my $self = shift;
  $self->render(data => getPosWiseW2VCollocatorsAsTsv($self->param("w"), 
                                            ($self->param("max")? $self->param("max") : 200),
                                            ($self->param("cutoff")? $self->param("cutoff") : 750000),
                                            ($self->param("threshold")? $self->param("threshold") : 0.2)),
                                            format=>'tsv');
};

any '*/getSimilarProfiles' => sub {
  my $self = shift;
  $self->render(data => getSimilarProfilesCached($self, $self->param("w") ? $self->param("w") : $self->req->json), format=>'json');
};

any '/getSimilarProfiles' => sub {
  my $self = shift;
  $self->render(data => getSimilarProfilesCached($self, $self->param("w") ? $self->param("w") : $self->req->json), format=>'json');
};

any '/getSimilarity' => sub {
  my $self = shift;
  my $w1 = $self->param("w1");
  my $w2 = $self->param("w2");
  $self->render(data => cos_similarity_as_json($w1, $w2), format=>'json');
};

any '*/getSimilarity' => sub {
  my $self = shift;
  my $w1 = $self->param("w1");
  my $w2 = $self->param("w2");
  $self->render(data => cos_similarity_as_json($w1, $w2), format=>'json');
};

get '*/img/*' => sub {
	my $c = shift;
	my $url = $c->req->url;
	$url =~ s@/derekovecs@@g;
  $c->app->log->info("GET: " . $url);
	$c->reply->static($url);
};

get '/' => sub {
  my $c    = shift;
  $c->app->log->info("get: ".$c->req->url->to_abs);
	my $word=$c->param('word');
  my $no_nbs=$c->param('n') || ($opt_m? 50 : 100);
  my $no_iterations=$c->param('N') || 2000;
  my $perplexity=$c->param('perplexity') || 20;
  my $epsilon=$c->param('epsilon') || 5;
  my $som=$c->param('som') || 0;
	my $searchBaseVocabFirst=$c->param('sbf') || 0;
  my $sort=$c->param('sort') || 0;
  my $csv=$c->param('csv') || 0;
  my $json=$c->param('json') || 0;
  my $cutoff=$c->param('cutoff') || 500000;
  my $dedupe=$c->param('dedupe') || 0;
  my $nosp=$c->param('nosp') || 0;
  my $res;
	my @lists;
	my @collocations;
	$word="idea" if(!defined($word));
  if(defined($word) && $word !~ /^\s*$/) {
		$c->inactivity_timeout(300);
		$word =~ s/\s+/ /g;
    if($opt_m && $word !~ /\|/) {
      $word .= "|$word";
    }
    for my $w (split(' *\| *', $word)) {
      if($opt_m) {
        if($searchBaseVocabFirst) {
          $searchBaseVocabFirst=0;
        } else {
          $searchBaseVocabFirst=1;
        }
      }
      if ($cache{$w.$cutoff.$no_nbs.$sort.$dedupe,$searchBaseVocabFirst}) {
        $c->app->log->info("Getting $w results from cache");
        $res = $cache{$w.$cutoff.$no_nbs.$sort.$dedupe.$searchBaseVocabFirst}
      } else {
        $c->app->log->info('Looking for neighbours of '.$w);
        if($opt_i) {
          $res = get_neighbours(encode("iso-8859-1", $w), $no_nbs, $sort, $searchBaseVocabFirst, $cutoff, $dedupe, $nosp);
        } else {
          $res = get_neighbours($w, $no_nbs, $sort, $searchBaseVocabFirst, $cutoff, $dedupe, $nosp);
        }
        $cache{$w.$cutoff.$no_nbs.$sort.$dedupe} = $res;
      }
      push(@lists, $res->{paradigmatic});
    }
  }
	$word =~ s/ *\| */ | /g;
  if($json) {
    return $c->render(json => {word => $word, list => \@lists, collocators=>$res->{syntagmatic}});
  } elsif($csv) {
    my $csv_data="";
    for (my $i=0; $i <= $no_nbs; $i++) {
      $csv_data .= $res->{paradigmatic}->[$i]->{word} . ", ";
    }
    for (my $i=0; $i < $no_nbs; $i++) {
      $csv_data .= $res->{syntagmatic}->[$i]->{word} . ", ";
    }
    chop $csv_data;
    chop $csv_data;
    $csv_data .= "\n";
    return $c->render(text=>$csv_data);
  } else {
    my $distantWords="";
    if(!defined($word) || $word !~ /^\s*$/) {
      $distantWords = getBiggestMergedDifferences();
    }
    $c->render(template=>"index", title=>$title, word=>$word, distantWords=>$distantWords, cutoff=>$cutoff, no_nbs=>$no_nbs, no_iterations => $no_iterations, epsilon=> $epsilon, perplexity=> $perplexity, show_som=>$som, searchBaseVocabFirst=>$searchBaseVocabFirst, sort=>$sort, training_args=>$training_args, mergedEnd=> $mergedEnd, haveSProfiles=> $have_sprofiles, dedupe=> $dedupe, marked=>\%marked, lists=> \@lists, collocators=> $res->{syntagmatic});
  }
};

helper(bitvec2window => sub {
         my ($self, $n) = @_;
         my $str = unpack("B32", pack("N", $n));
         $str =~ s/^\d{22}//;
         $str =~ s/^(\d{5})/$1x/;
         $str =~ s/0/·/g;
         $str =~ s/1/+/g;
         return $str;
      });

$daemon->run; # app->start;

exit;

__END__

__C__
#include <stdio.h>
#include <string.h>
#include <math.h>
#include <malloc.h>
#include <stdlib.h>    //strlen
#include <sys/mman.h>
#include <pthread.h>
#include <collocatordb.h>

#define max_size 2000
#define max_w 50
#define MAX_NEIGHBOURS 1000
#define MAX_WORDS -1
#define MAX_THREADS 100
#define MAX_CC 50
#define EXP_TABLE_SIZE 1000
#define MAX_EXP 6
#define MIN_RESP 0.50

//the thread function
void *connection_handler(void *);

typedef struct {
	long long wordi;
	long position;
	float activation;
	float average;
	float cprobability; // column wise probability
	float cprobability_sum;
	float probability;
	float activation_sum;
	float max_activation;
	float heat[16];
} collocator;

typedef struct {
	collocator *best;
	int length;
} knn;
  
typedef struct {
  long long wordi[MAX_NEIGHBOURS];
  char sep[MAX_NEIGHBOURS];
  int length;
} wordlist;

typedef struct {
  long cutoff;
  wordlist *wl;
	char *token;
	int N;
	long from;
	unsigned long upto;
  collocator *best;
  float *target_sums;
  float *window_sums;
  float threshold;
} knnpars;

typedef struct {
  uint32_t index;
  float value;
} sparse_t;

typedef struct {
  uint32_t len;
  sparse_t nbr[100];
} profile_t;

float *M, *M2=0L, *syn1neg_window, *expTable;
float *window_sums;
char *vocab;
char *garbage = NULL;
COLLOCATORDB *cdb = NULL;
profile_t *sprofiles = NULL;
size_t sprofiles_qty = 0;

long long words, size, merged_end;
long long merge_words = 0;
int num_threads=20;
int latin_enc=0;
int window;

/* load collocation profiles if file exists */
int load_sprofiles(char *vecsname) {
  char *basename = strdup(vecsname);
  char *pos = strstr(basename, ".vecs");
  if(pos)
    *pos=0;
  
  char binsprofiles_fname[256];
  strcpy(binsprofiles_fname, basename);
	strcat(binsprofiles_fname, ".sprofiles.bin");
  FILE *fp = fopen(binsprofiles_fname, "rb");
  if (fp == NULL) {
    printf("Collocation profiles %s not found. No problem.\n", binsprofiles_fname);
    return 0;
  }
  fseek(fp, 0L, SEEK_END);
  size_t sz = ftell(fp);
  fclose(fp);

  int fd = open(binsprofiles_fname, O_RDONLY);
  sprofiles = mmap(0,  sz, PROT_READ, MAP_SHARED, fd, 0);
  if (sprofiles == MAP_FAILED) {
    close(fd);
    fprintf(stderr, "Cannot mmap %s\n", binsprofiles_fname);
    sprofiles = NULL;
    return 0;
  }  else {
    sprofiles_qty = sz / sizeof(profile_t);
    fprintf(stderr, "Successfully mmaped %s containing similar profiles for %ld word forms.\n", binsprofiles_fname, sprofiles_qty);
  }
  return 1;
}

int init_net(char *file_name, char *net_name, int latin) {
  FILE *f, *binvecs, *binwords;
	int binwords_fd, binvecs_fd, net_fd, i;
	long long a, b, c, d, cn;
	float len;
  double val;

	char binvecs_fname[256], binwords_fname[256];
	strcpy(binwords_fname, file_name);
	strcat(binwords_fname, ".words");
	strcpy(binvecs_fname, file_name);
	strcat(binvecs_fname, ".vecs");

  latin_enc = latin;
  f = fopen(file_name, "rb");
  if (f == NULL) {
    printf("Input file %s not found\n", file_name);
    return -1;
  }
  fscanf(f, "%lld", &words);
	if(MAX_WORDS > 0 && words > MAX_WORDS) words = MAX_WORDS;
  fscanf(f, "%lld", &size);
	if( (binvecs_fd = open(binvecs_fname, O_RDONLY)) < 0  || (binwords_fd = open(binwords_fname, O_RDONLY)) < 0) {
    printf("Converting %s to memory mappable structures\n", file_name);
		vocab = (char *)malloc((long long)words * max_w * 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;
		}
    if(strstr(file_name, ".txt")) {
      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;
        len = 0;
        for (a = 0; a < size; a++) {
          fscanf(f, "%lf", &val);
          M[a + b * size] = val;
          len += val * val;
        } 
        len = sqrt(len);
        for (a = 0; a < size; a++) M[a + b * size] /= len;
      }
    } else {
      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;
      }
    }
		if( (binvecs = fopen(binvecs_fname, "wb")) != NULL && (binwords = fopen(binwords_fname, "wb")) != NULL) {
			fwrite(M, sizeof(float), (long long)words * (long long)size, binvecs);
			fclose(binvecs);
			fwrite(vocab, sizeof(char), (long long)words * max_w, binwords);
			fclose(binwords);
		}
  }
	if( (binvecs_fd = open(binvecs_fname, O_RDONLY)) >= 0 && (binwords_fd = open(binwords_fname, O_RDONLY)) >= 0) {
		M = mmap(0, sizeof(float) * (long long)words * (long long)size, PROT_READ, MAP_SHARED, binvecs_fd, 0);
		vocab = mmap(0,  sizeof(char) * (long long)words * max_w, PROT_READ, MAP_SHARED, binwords_fd, 0);
    if (M == MAP_FAILED || vocab == MAP_FAILED) {
			close(binvecs_fd);
			close(binwords_fd);
			fprintf(stderr, "Cannot mmap %s or %s\n", binwords_fname, binvecs_fname);
			exit(-1);
    }
	} else {
    fprintf(stderr, "Cannot open %s or %s\n", binwords_fname, binvecs_fname);
    exit(-1);
	}
  fclose(f);

  if(net_name && strlen(net_name) > 0) {
    if( (net_fd = open(net_name, O_RDONLY)) >= 0) {
      window = (lseek(net_fd, 0, SEEK_END) -  sizeof(float) * words * size) / words / size / sizeof(float) / 2;
      //      lseek(net_fd, sizeof(float) * words * size, SEEK_SET);
      // munmap(M,  sizeof(float) * words * size);
      M2 = mmap(0, sizeof(float) * words * size + sizeof(float) * 2 * window * size * words, PROT_READ, MAP_SHARED, net_fd, 0);
      if (M2 == MAP_FAILED) {
        close(net_fd);
        fprintf(stderr, "Cannot mmap %s\n", net_name);
        exit(-1);
      }
      syn1neg_window =  M2 + words * size;
    } else {
      fprintf(stderr, "Cannot open %s\n", net_name);
      exit(-1);
    }
    fprintf(stderr, "Successfully memmaped %s. Determined window size: %d\n", net_name, window);

		char collocatordb_name[2048];
		strcpy(collocatordb_name, net_name);
		char *ext = rindex(collocatordb_name, '.');
		if(ext) {
			strcpy(ext, ".rocksdb");
			if(access(collocatordb_name, R_OK) == 0) {
				*ext = 0;
				fprintf(stderr, "Opening collocator DB	%s\n", collocatordb_name);
				cdb = open_collocatordb(collocatordb_name);
			}
		}
	}

	expTable = (float *) malloc((EXP_TABLE_SIZE + 1) * sizeof(float));
	for (i = 0; i < EXP_TABLE_SIZE; i++) {
		expTable[i] = exp((i / (float) EXP_TABLE_SIZE * 2 - 1) * MAX_EXP); // Precompute the exp() table
		expTable[i] = expTable[i] / (expTable[i] + 1); // Precompute f(x) = x / (x + 1)
	}
	window_sums = malloc(sizeof(float) * (window+1) * 2);

  return 0;
}

long mergeVectors(char *file_name){
  FILE *f, *binvecs, *binwords;
	int binwords_fd, binvecs_fd, net_fd, i;
	long long a, b, c, d, cn;
	float len;
  float *merge_vecs;
  char *merge_vocab;
 /*  long long merge_words, merge_size; */
  long long merge_size;

	char binvecs_fname[256], binwords_fname[256];
	strcpy(binwords_fname, file_name);
	strcat(binwords_fname, ".words");
	strcpy(binvecs_fname, file_name);
	strcat(binvecs_fname, ".vecs");

  f = fopen(file_name, "rb");
  if (f == NULL) {
    printf("Input file %s not found\n", file_name);
    exit -1;
  }
  fscanf(f, "%lld", &merge_words);
  fscanf(f, "%lld", &merge_size);
  if(merge_size != size){
		fprintf(stderr, "vectors must have the same length\n");
		exit(-1);
	}
	if( (binvecs_fd = open(binvecs_fname, O_RDONLY)) >= 0 && (binwords_fd = open(binwords_fname, O_RDONLY)) >= 0) {
		merge_vecs = malloc(sizeof(float) * (words + merge_words) * size);
		merge_vocab = malloc(sizeof(char) * (words + merge_words) * max_w);
    if (merge_vecs == NULL || merge_vocab == NULL) {
			close(binvecs_fd);
			close(binwords_fd);
			fprintf(stderr, "Cannot reserve memory for %s or %s\n", binwords_fname, binvecs_fname);
			exit(-1);
    }
    read(binvecs_fd, merge_vecs, merge_words * size * sizeof(float));
    read(binwords_fd, merge_vocab, merge_words * max_w);
	} else {
    fprintf(stderr, "Cannot open %s or %s\n", binwords_fname, binvecs_fname);
    exit(-1);
	}
	printf("Successfully reallocated memory\nMerging...\n");
	fflush(stdout);
  memcpy(merge_vecs + merge_words * size, M, words * size * sizeof(float));
  memcpy(merge_vocab + merge_words * max_w, vocab, words * max_w);
  munmap(M, words * size * sizeof(float));
  munmap(vocab, words * max_w);
  M = merge_vecs;
  vocab = merge_vocab;
  merged_end = merge_words;
  words += merge_words;
  fclose(f);
	printf("merged_end: %lld, words: %lld\n", merged_end, words);
	//printBiggestMergedDifferences();
  return((long) merged_end);
}

void filter_garbage() {
  long i;
  unsigned char *w, previous, c;
  garbage = malloc(words);
  memset(garbage, 0, words);
  for (i = 0; i < words; i++) {
    w = vocab + i * max_w;
    previous = 0;
    if(strncmp("quot", w, 4) == 0) {
      garbage[i]=1;
//      printf("Gargabe: %s\n", vocab + i * max_w);
    } else {
      while((c = *w++) && !garbage[i]) {
        if( ((c <= 90 && c >= 65) && (previous >= 97 && previous <= 122)) || 
            (previous == '-' && (c & 32)) ||
            (previous == 0xc2 && (c == 0xa4 || c == 0xb6 )) ||
            (previous == 'q' && c == 'u' && *(w) == 'o' && *(w+1) == 't') || /* quot */
            c == '<'
          ) {
          garbage[i]=1;
          continue;
        }
        previous = c;
      }
    }
  }
  return;
}

  
knn *simpleGetCollocators(int word, int number, long cutoff, int *result) {
  knnpars *pars = calloc(sizeof(knnpars), 1);
  float *target_sums;
	float *window_sums = malloc(sizeof(float) * (window+1) * 2);
  pars->cutoff = (cutoff? cutoff : 300000);
	long a = posix_memalign((void **) &target_sums, 128, pars->cutoff * sizeof(float));
  for(a = 0; a < cutoff; a++)
    target_sums[a] = 0;
  pars->target_sums = target_sums;
  pars->window_sums = window_sums;
  pars->N = (number? number : 20);
  pars->from = 0;
  pars->upto = window * 2 -1;
  knn *syn_nbs = NULL; // = (knn*) getCollocators(pars);
  free(pars);
  free(window_sums);
  free(target_sums);
  return syn_nbs;
}

void *getCollocators(void *args) {
  knnpars *pars = args;
	int N = pars->N;

  int cc = pars->wl->wordi[0];
	knn *nbs = NULL;
  long window_layer_size = size * window * 2;
	long a, b, c, d, e, window_offset, target, max_target=0, maxmax_target;
	float f, max_f, maxmax_f;
	float *target_sums=NULL, worstbest, wpos_sum;
	collocator *best;

  if(M2 == NULL || cc == -1)
    return NULL;

	a = posix_memalign((void **) &target_sums, 128, pars->cutoff * sizeof(float));
  memset(target_sums, 0, pars->cutoff * sizeof(float));
	best = malloc((N>200?N:200) * sizeof(collocator));
  memset(best, 0, (N>200?N:200) * sizeof(collocator));
  worstbest = pars->threshold;

  for (b = 0; b < pars->cutoff; b++)
			target_sums[b]=0;
  for (b = 0; b < N; b++) {
      best[b].wordi = -1;
      best[b].probability = 1;
      best[b].activation = worstbest;
  }

  d = cc;
  maxmax_f = -1;
  maxmax_target = 0;

  for (a = pars->from; a < pars->upto; a++) {
    if(a >= window)
      a++;
    wpos_sum = 0;
    printf("window pos: %ld\n", a);
    if (a != window) {
      max_f = -1;
      window_offset = a * size;
      if (a > window)
        window_offset -= size;
      for(target = 0; target < pars->cutoff; target ++) {
				if(garbage && garbage[target]) continue;
        if(target == d)
          continue;
        f = 0;
        for (c = 0; c < size; c++)
          f += M2[d* size + c]	* syn1neg_window[target * window_layer_size	+ window_offset + c];
        if (f < -MAX_EXP)
          continue;
        else if (f > MAX_EXP)
          continue;
        else
          f = expTable[(int) ((f + MAX_EXP)	* (EXP_TABLE_SIZE / MAX_EXP / 2))];
        wpos_sum += f;

        target_sums[target] += f;
        if(f > worstbest) {
          for (b = 0; b < N; b++) {
            if (f > best[b].activation) {
							memmove(best + b + 1, best + b, (N - b -1) * sizeof(collocator));
							best[b].activation = f;
							best[b].wordi = target;
							best[b].position = window-a;
							break;
            }
          }
          if(b == N - 1)
            worstbest = best[N-1].activation;
        }
      }
      printf("%d %.2f\n", max_target, max_f);
      printf("%s (%.2f) ", &vocab[max_target * max_w], max_f);
      if(max_f > maxmax_f) {
        maxmax_f = max_f;
        maxmax_target = max_target;
      }
      for (b = 0; b < N; b++)
        if(best[b].position == window-a)
          best[b].cprobability = best[b].activation / wpos_sum;
    } else {
      printf("\x1b[1m%s\x1b[0m ", &vocab[d*max_w]);
    }
    pars->window_sums[a] = wpos_sum;
  }
  for (b = 0; b < pars->cutoff; b++)
      pars->target_sums[b] += target_sums[b]; //(target_sums[b] / wpos_sum ) / (window * 2);

  free(target_sums);
  for(b=0; b<N && best[b].wordi >= 0; b++);; // THIS LOOP IS NEEDED (b...)
//		printf("%d: best syn: %s %.2f %.5f\n", b, &vocab[best[b].wordi*max_w], best[b].activation, best[b].probability);
//	printf("\n");
  nbs = malloc(sizeof(knn));
	nbs->best = best;
	nbs->length = b-1;
  pthread_exit(nbs);
}


AV *getVecs(AV *array) {
  int i, b;
  AV *result = newAV();
  for (i=0; i<=av_len(array); i++) {
    SV** elem = av_fetch(array, i, 0);
    if (elem != NULL) {
      long j = (long) SvNV(*elem);
      AV *vector = newAV();
      for (b = 0; b < size; b++) {
        av_push(vector, newSVnv(M[b + j * size]));
      }
      av_push(result, newRV_noinc(vector));
    }
  }
  return result;
}

char *getSimilarProfiles(long node) {
  int i;
  char buffer[120000];
  char pair_buffer[2048];
  buffer[0]='[';
  buffer[1]=0;
  if(node >= sprofiles_qty) {
    printf("Not available in precomputed profile\n");
    return(strdup("[{\"w\":\"not available\", \"v\":0}]\n"));
  }

  printf("******* %s ******\n", &vocab[max_w * node]);
  
  for(i=0; i < 100 && i < sprofiles[node].len; i++) {
    sprintf(pair_buffer, "{\"w\":\"%s\", \"v\":%f},", &vocab[max_w * (sprofiles[node].nbr[i].index)], sprofiles[node].nbr[i].value);
    strcat(buffer, pair_buffer);
  }
  buffer[strlen(buffer)-1]=']';
  strcat(buffer, "\n");
  printf(buffer);
  return(strdup(buffer));
}

char *getClassicCollocators(long node) {
	char *res = (cdb? strdup(get_collocators_as_json(cdb, node)) : "[]");
	return res;
}

wordlist *getTargetWords(char *st1, int search_backw) {
  wordlist *wl = malloc(sizeof(wordlist));
  char st[100][max_size], sep[100];
  long a, b=0, c=0, cn=0;
  int unmerged;

  while (1) {
    st[cn][b] = st1[c];
    b++;
    c++;
    st[cn][b] = 0;
    if (st1[c] == 0) break;
    if (st1[c] == ' ' || st1[c] == '-') {
      sep[cn++] = st1[c];
      b = 0;
      c++;
    }
  }
  cn++;
  for (a = 0; a < cn; a++) {
    if (search_backw) {
      for (b = words - 1; b >= (merge_words? merge_words : 0) && strcmp(&vocab[b * max_w], st[a]) !=0; b--);
    } else {
      for (b = 0;     b < (merge_words? merge_words : words) && strcmp(&vocab[b * max_w], st[a]) != 0; b++);
    }
    if (b == words) b = -1;
    wl->wordi[a] = b;
    if (b == -1) {
      fprintf(stderr, "Out of dictionary word!\n");
      cn--;
    } else {
      fprintf(stderr, "Word: \"%s\"  Position in vocabulary: %lld\n", &vocab[wl->wordi[a]*max_w], wl->wordi[a]);
    }
  }
  wl->length=cn;
  return(wl);
}

float get_distance(long b, long c) {
  long a;
  float dist = 0;
  for (a = 0; a < size; a++) dist += M[a + c * size] * M[a + b * size];
  return dist;
}

char  *getBiggestMergedDifferences() {
  static char *result = NULL;
  float dist, len, vec[max_size];
  long long a, b, c, d, cn, *bi;
  char ch;
  knn *nbs = NULL;
  int N = 1000;

  if(merged_end == 0)
    result = "[]";
    
  if(result != NULL)
    return result;

  printf("Looking for biggest distances between main and merged vectors ...\n");
  collocator *best;
  best = malloc(N * sizeof(collocator));
  memset(best, 0, N * sizeof(collocator));

  float worstbest=1000000;

  for (a = 0; a < N; a++) best[a].activation = worstbest;

  for (c = 0; c < 500000; c++) {
    if(garbage && garbage[c]) continue;
    a = 0;
    dist = 0;
    for (a = 0; a < size; a++) dist += M[a + c * size] * M[a + (c+merged_end) * size];
    if(dist < worstbest) {
      for (a = 0; a < N; a++) {
        if (dist < best[a].activation) {
          memmove(best + a + 1, best + a, (N - a -1) * sizeof(collocator));
          best[a].activation = dist;
          best[a].wordi = c;
          break;
        }
      }
      worstbest = best[N-1].activation;
    }
  }

  result = malloc(N*max_w);
  char *p = result;
  *p++ = '['; *p = 0;
  for (a = 0; a < N; a++) {
    p += sprintf(p, "{\"rank\":%d,\"word\":\"%s\",\"dist\":%.3f},", a, &vocab[best[a].wordi * max_w], 1-best[a].activation);
  }
  *--p = ']';
  return(result);
}


float cos_similarity(long b, long c) {
  float dist=0;
  long a;
 	for (a = 0; a < size; a++) dist += M[b * size + a] * M[c * size + a];
  return dist;
}

char *cos_similarity_as_json(char *w1, char *w2) {
  wordlist *a, *b;
  float res;
  a = getTargetWords(w1, 0);
  b = getTargetWords(w2, 0);
  if (a == NULL || b==NULL || a->length != 1 || b->length != 1)
    res = -1;
  else
    res = cos_similarity(a->wordi[0], b->wordi[0]);
  fprintf(stderr, "a: %lld b: %lld res:%f\n", a->wordi[0], b->wordi[0], res);
  char *json = malloc(16);
  sprintf(json, "%.5f", res);
  return json;
}

void *_get_neighbours(void *arg) {
  knnpars *pars = arg;
	char *st1 = pars->token;
	int N = pars->N;
	long from = pars -> from;
	unsigned long upto = pars -> upto;
	char file_name[max_size], st[100][max_size], *sep;
	float dist, len, vec[max_size];
	long long a, b, c, d, cn, *bi;
	char ch;
	knn *nbs = NULL;
  wordlist *wl = pars->wl;
  
	collocator *best = pars->best;

	float worstbest=-1;

	for (a = 0; a < N; a++) best[a].activation = 0;
	a = 0;
  bi = wl->wordi;
	cn = wl->length;
  sep = wl->sep;
	b = bi[0];
	c = 0;
	if (b == -1) {
    N = 0;
	  goto end;
  }
	for (a = 0; a < size; a++) vec[a] = 0;
	for (b = 0; b < cn; b++) {
		if (bi[b] == -1) continue;
    if(b>0 && sep[b-1] == '-')
      for (a = 0; a < size; a++) vec[a] -= M[a + bi[b] * size];
    else
      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++) best[a].activation = -1;
	for (c = from; c < upto; c++) {
    if(garbage && garbage[c]) continue;
		a = 0;
// do 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];
		if(dist > worstbest) {
			for (a = 0; a < N; a++) {
				if (dist > best[a].activation) {
					memmove(best + a + 1, best + a, (N - a -1) * sizeof(collocator));
					best[a].activation = dist;
					best[a].wordi = c;
					break;
				}
			}
			worstbest = best[N-1].activation;
		}
	}

end:
	pthread_exit(nbs);
}

int cmp_activation (const void * a, const void * b) {
   float fb = ((collocator *)a)->activation;
   float fa = ((collocator *)b)->activation;
   return (fa > fb) - (fa < fb);
}

int cmp_probability (const void * a, const void * b) {
   float fb = ((collocator *)a)->probability;
   float fa = ((collocator *)b)->probability;
   return (fa > fb) - (fa < fb);
}

char* getPosWiseW2VCollocatorsAsTsv(char *word, long maxPerPos, long cutoff, float threshold) {
    HV *result = newHV();
	float *target_sums=NULL, vec[max_size];
	long long old_words;
	long a, b, c, d;
	knn *para_nbs[MAX_THREADS];
	knn *syn_nbs[MAX_THREADS];
	knnpars pars[MAX_THREADS];
  pthread_t *pt = (pthread_t *)malloc((num_threads+1) * sizeof(pthread_t));
  wordlist *wl;
  int syn_threads = (M2? window * 2 : 0);
  int search_backw = 0;
  collocator *best = NULL;
  posix_memalign((void **) &best, 128, 10 * (maxPerPos>=200? maxPerPos : 200)  * sizeof(collocator));
  memset(best, 0, (maxPerPos>=200? maxPerPos : 200) * sizeof(collocator));


  if(cutoff < 1 || cutoff > words)
    cutoff=words;

  wl = getTargetWords(word, search_backw);
  if(wl == NULL || wl->length < 1)
    return "";

	a = posix_memalign((void **) &target_sums, 128, cutoff * sizeof(float));
  memset(target_sums, 0, cutoff * sizeof(float));

  printf("Starting %d threads\n", syn_threads);
  fflush(stdout);
  for(a=0; a < syn_threads; a++) {
			pars[a].cutoff = cutoff;
      pars[a].target_sums = target_sums;
      pars[a].window_sums = window_sums;
      pars[a].wl = wl;
      pars[a].N = maxPerPos;
      pars[a].threshold = threshold;
      pars[a].from = a;
      pars[a].upto = a+1;
      pthread_create(&pt[a], NULL, getCollocators, (void *) &pars[a]);
  }
  printf("Waiting for syn threads to join\n");
  fflush(stdout);
  for (a = 0; a < syn_threads; a++) pthread_join(pt[a], (void *) &syn_nbs[a]);
  printf("Syn threads joint\n");
  fflush(stdout);
  result = malloc(maxPerPos*80*syn_threads);
  char *p = result;
  *p = 0;
	for (a = syn_threads -1; a >= 0; a--) {
    for (b=0; b < syn_nbs[a]->length; b++) {
      p += sprintf(p, "%ld\t%s\t%f\n", syn_nbs[a]->best[b].position, &vocab[syn_nbs[a]->best[b].wordi * max_w], syn_nbs[a]->best[b].activation);
    }
	}
  return(result);
}

SV *get_neighbours(char *st1, int N, int sort_by, int search_backw, long cutoff, int dedupe, int no_similar_profiles) {
  HV *result = newHV();
	float *target_sums=NULL, vec[max_size];
	long long old_words;
	long a, b, c, d, slice;
	knn *para_nbs[MAX_THREADS];
	knn *syn_nbs[MAX_THREADS];
	knnpars pars[MAX_THREADS];
  pthread_t *pt = (pthread_t *)malloc((num_threads+1) * sizeof(pthread_t));
  wordlist *wl;
  int syn_threads = (M2? window * 2 : 0);
  int para_threads = (no_similar_profiles? 0 : num_threads - syn_threads);

  collocator *best = NULL;
  posix_memalign((void **) &best, 128, 10 * (N>=200? N : 200)  * sizeof(collocator));
  memset(best, 0, (N>=200? N : 200) * sizeof(collocator));

  if(N>MAX_NEIGHBOURS) N=MAX_NEIGHBOURS;
	
  if(cutoff < 1 || cutoff > words)
    cutoff=words;

  wl = getTargetWords(st1, search_backw);
  if(wl == NULL || wl->length < 1)
    goto end;

	old_words = cutoff;
	slice = cutoff / para_threads;

	a = posix_memalign((void **) &target_sums, 128, cutoff * sizeof(float));
  memset(target_sums, 0, cutoff * sizeof(float));

  printf("Starting %d threads\n", para_threads);
  fflush(stdout);
	for(a=0; a < para_threads; a++) {
		pars[a].cutoff = cutoff;
		pars[a].token = st1;
		pars[a].wl = wl;
		pars[a].N = N;
    pars[a].best = &best[N*a];
    if(merge_words == 0 || search_backw == 0) {
      pars[a].from = a*slice;
      pars[a].upto = ((a+1)*slice > cutoff? cutoff : (a+1) * slice);
    } else {
      pars[a].from = merge_words + a * slice;
      pars[a].upto = merge_words + ((a+1)*slice > cutoff? cutoff : (a+1) * slice);
    }
    printf("From: %ld, Upto: %ld\n",  pars[a].from, pars[a].upto);
		pthread_create(&pt[a], NULL, _get_neighbours, (void *) &pars[a]);
	}
  if(M2) {
    for(a=0; a < syn_threads; a++) {
			pars[a + para_threads].cutoff = cutoff;
      pars[a + para_threads].target_sums = target_sums;
      pars[a + para_threads].window_sums = window_sums;
      pars[a + para_threads].wl = wl;
      pars[a + para_threads].N = N;
      pars[a + para_threads].threshold = MIN_RESP;
      pars[a + para_threads].from = a;
      pars[a + para_threads].upto = a+1;
      pthread_create(&pt[a + para_threads], NULL, getCollocators, (void *) &pars[a + para_threads]);
    }
  }
  printf("Waiting for para threads to join\n");
  fflush(stdout);
  for (a = 0; a < para_threads; a++) pthread_join(pt[a], (void *) &para_nbs[a]);
  printf("Para threads joint\n");
  fflush(stdout);

	/* if(!syn_nbs[0]) */
	/* 	goto end; */

  qsort(best, N*para_threads, sizeof(collocator), cmp_activation);


  long long chosen[MAX_NEIGHBOURS];
  printf("N: %ld\n", N);

  AV* array = newAV();
  int i, j;
  int l1_words=0, l2_words=0;
 
  for (a = 0, i = 0; i < N && a < N*para_threads; a++) {
    int filtered=0;
    long long c = best[a].wordi;
    if ((merge_words && dedupe && i > 1) || (!merge_words && dedupe && i > 0)) {
      for (j=0; j<i && !filtered; j++)
        if (strcasestr(&vocab[c * max_w], &vocab[chosen[j] * max_w]) ||
            strcasestr(&vocab[chosen[j] * max_w], &vocab[c * max_w])) {
              printf("filtering %s %s\n", &vocab[chosen[j] * max_w], &vocab[c * max_w]);
              filtered = 1;
        }
      if(filtered)
        continue;
    }


    if(0 && merge_words > 0) {
        if(c >= merge_words) {
            if(l1_words > N / 2)
                continue;
            else
                l1_words++;
        } else {
            if(l2_words > N / 2)
                continue;
            else
                l2_words++;
        }
    }

//    printf("%s l1:%d l2:%d i:%d a:%ld\n", &vocab[c * max_w], l1_words, l2_words, i, a);
//    fflush(stdout);
    HV* hash = newHV();
    SV* word = newSVpvf(&vocab[c * max_w], 0);
		chosen[i] = c;
    if(latin_enc == 0) SvUTF8_on(word);
    fflush(stdout);
    hv_store(hash, "word", strlen("word"), word , 0);
    hv_store(hash, "dist", strlen("dist"), newSVnv(best[a].activation), 0);
    hv_store(hash, "rank", strlen("rank"), newSVuv(best[a].wordi), 0);
    AV *vector = newAV();
    for (b = 0; b < size; b++) {
      av_push(vector, newSVnv(M[b + best[a].wordi * size]));
    }
    hv_store(hash, "vector", strlen("vector"), newRV_noinc((SV*)vector), 0);
    av_push(array, newRV_noinc((SV*)hash));
    i++;
  }
  hv_store(result, "paradigmatic", strlen("paradigmatic"), newRV_noinc((SV*)array), 0);

  for(b=0; b < MAX_NEIGHBOURS; b++) {
    best[b].wordi = -1L;
    best[b].activation = 0;
    best[b].probability = 0;
    best[b].position = 0;
    best[b].activation_sum = 0;
    memset(best[b].heat, 0, sizeof(float)*16);
  }

	float total_activation = 0;

  if (M2) {
    printf("Waiting for syn threads to join\n");
    fflush(stdout);
    for (a = 0; a < syn_threads; a++) pthread_join(pt[a+para_threads], (void *) &syn_nbs[a]);
		for (a = 0; a <= syn_threads; a++) {
      if(a == window) continue;
			total_activation += window_sums[a];
			printf("window pos: %d, sum: %f\n", a, window_sums[a]);
		}
    printf("syn threads joint\n");
    fflush(stdout);

    for(b=0; b < syn_nbs[0]->length; b++) {
			memcpy(best + b, &syn_nbs[0]->best[b], sizeof(collocator));
      best[b].position = -1; //  syn_nbs[0]->pos[b];
      best[b].activation_sum = target_sums[syn_nbs[0]->best[b].wordi];
			best[b].max_activation = 0.0;
			best[b].average = 0.0;
			best[b].probability = 0.0;
			best[b].cprobability = syn_nbs[0]->best[b].cprobability;
			memset(best[b].heat, 0, sizeof(float)*16);
    }
		
		float best_window_sum[MAX_NEIGHBOURS];
    int found_index=0, i=0, j, w;
    for(a=0; a < syn_threads; a++) {
      for(b=0; b < syn_nbs[a]->length; b++) {
				for(i=0; i < found_index; i++)
					if(best[i].wordi == syn_nbs[a]->best[b].wordi)
						break;
				if(i >= found_index) {
					best[found_index].max_activation = 0.0;
					best[found_index].average = 0.0;
					best[found_index].probability = 0.0;
					memset(best[found_index].heat, 0, sizeof(float)*16);
					best[found_index].cprobability = syn_nbs[a]->best[b].cprobability;
					best[found_index].activation_sum = target_sums[syn_nbs[a]->best[b].wordi]; // syn_nbs[a]->best[b].activation_sum;
					best[found_index++].wordi = syn_nbs[a]->best[b].wordi;
					//						printf("found: %s\n", &vocab[syn_nbs[a]->index[b] * max_w]);
				}
			}
		}
		sort_by =0; // ALWAYS AUTO-FOCUS
    if(sort_by != 1 && sort_by != 2) { // sort by auto focus mean
			printf("window: %d  -  syn_threads: %d, %d\n", window, syn_threads, (1 << syn_threads) -1);
			int wpos;
      int bits_set = 0;
			for(i=0; i < found_index; i++) {
				best[i].activation = best[i].probability = best[i].average = best[i].cprobability_sum = 0;
				for(w=1; w <  (1 << syn_threads); w++) { // loop through all possible windows
					float word_window_sum = 0, word_window_average=0, word_cprobability_sum=0, word_activation_sum = 0, total_window_sum = 0;
          bits_set = 0;
					for(a=0; a < syn_threads; a++) {
						if((1 << a) & w) {
							wpos = (a >= window? a+1 : a);
							total_window_sum += window_sums[wpos];
						}
					}
//					printf("%d window-sum %f\n", w, total_window_sum);
					for(a=0; a < syn_threads; a++) {
						if((1 << a) & w) {
							wpos = (a >= window? a+1 : a);
 						  bits_set++;
						  for(b=0; b < syn_nbs[a]->length; b++)
							  if(best[i].wordi == syn_nbs[a]->best[b].wordi) {
//									float acti = syn_nbs[a]->best[b].activation / total_window_sum;
//                  word_window_sum += syn_nbs[a]->dist[b] *  syn_nbs[a]->norm[b]; // / window_sums[wpos];  // syn_nbs[a]->norm[b];
//                    word_window_sum += syn_nbs[a]->norm[b]; // / window_sums[wpos];  // syn_nbs[a]->norm[b];
//                  word_window_sum = (word_window_sum + syn_nbs[a]->norm[b]) - (word_window_sum * syn_nbs[a]->norm[b]);  // syn_nbs[a]->norm[b];

                  word_window_sum += syn_nbs[a]->best[b].activation; // / window_sums[wpos];  // syn_nbs[a]->norm[b];
//                  word_window_sum += acti - (word_window_sum * acti); syn_nbs[a]->best[b].activation; // / window_sums[wpos];  // syn_nbs[a]->norm[b];

                  word_window_average += syn_nbs[a]->best[b].activation; // - word_window_average * syn_nbs[a]->best[b].activation;  // conormalied activation sum
                  word_cprobability_sum += syn_nbs[a]->best[b].cprobability - word_cprobability_sum * syn_nbs[a]->best[b].cprobability;  // conormalied column probability sum
									word_activation_sum += syn_nbs[a]->best[b].activation;
                  if(syn_nbs[a]->best[b].activation > best[i].max_activation)
										best[i].max_activation = syn_nbs[a]->best[b].activation;
                  if(syn_nbs[a]->best[b].activation > best[i].heat[wpos] )
										best[i].heat[wpos] = syn_nbs[a]->best[b].activation;
								}
						}
					}
          if(bits_set) {
            word_window_average /= bits_set;
//						word_activation_sum /= bits_set;
//						word_window_sum /= bits_set;
          }

					word_window_sum /= total_window_sum;

          if(word_window_sum > best[i].probability) {
//						best[i].position = w;
						best[i].probability = word_window_sum;
					}

          if(word_cprobability_sum > best[i].cprobability_sum) {
						best[i].position = w;
						best[i].cprobability_sum = word_cprobability_sum;
					}

						best[i].average = word_window_average;
//						best[i].activation = word_activation_sum;
        }
			}
			qsort(best, found_index, sizeof(collocator), cmp_probability);
//      for(i=0; i < found_index; i++) {
//				printf("found: %s - sum: %f - window: %d\n", &vocab[best[i].wordi * max_w], best[i].activation, best[i].position);
//			}

    } else if(sort_by == 1) { // responsiveness any window position
			int wpos;
			for(i=0; i < found_index; i++) {
 					float word_window_sum = 0, word_activation_sum = 0, total_window_sum = 0;
					for(a=0; a < syn_threads; a++) {
							wpos = (a >= window? a+1 : a);
						  for(b=0; b < syn_nbs[a]->length; b++)
							  if(best[i].wordi == syn_nbs[a]->best[b].wordi) {
                  best[i].probability += syn_nbs[a]->best[b].probability;
									if(syn_nbs[a]->best[b].activation > 0.25)
									  best[i].position |= 1 << wpos;
									if(syn_nbs[a]->best[b].activation > best[i].activation) {
										best[i].activation = syn_nbs[a]->best[b].activation;
                  }
								}
					}
			}
			qsort(best, found_index, sizeof(collocator), cmp_activation);
     } else if(sort_by == 2) { // single window position
       for(a=1; a < syn_threads; a++) {
        for(b=0; b < syn_nbs[a]->length; b++) {
          for(c=0; c < MAX_NEIGHBOURS; c++) {
            if(syn_nbs[a]->best[b].activation > best[c].activation) {
              for(d=MAX_NEIGHBOURS-1; d>c; d--) {
								memmove(best + d, best + d - 1, sizeof(collocator));
              }
              memcpy(best + c, &syn_nbs[a]->best[b], sizeof(collocator));
              best[c].position = 1 << (-syn_nbs[a]->best[b].position+window - (syn_nbs[a]->best[b].position < 0 ? 1:0));
              break;
            }
          }
        }
      }
    } else { // sort by mean p
      for(a=1; a < syn_threads; a++) {
        for(b=0; b < syn_nbs[a]->length; b++) {
          for(c=0; c < MAX_NEIGHBOURS; c++) {
            if(target_sums[syn_nbs[a]->best[b].wordi] > best[c].activation_sum) {
              for(d=MAX_NEIGHBOURS-1; d>c; d--) {
								memmove(best + d, best + d - 1, sizeof(collocator));
              }
              memcpy(best + c, &syn_nbs[a]->best[b], sizeof(collocator));
              best[c].position = (1 << 2*window) - 1; // syn_nbs[a]->pos[b];
              best[c].activation_sum = target_sums[syn_nbs[a]->best[b].wordi];
              break;
            }
          }
        }
      }
    }
    array = newAV();
    for (a = 0, i=0; a < MAX_NEIGHBOURS && best[a].wordi >= 0; a++) {
      long long c = best[a].wordi;
/*
      if (dedupe) {
	  		int filtered=0;
        for (j=0; j<i; j++)
          if (strcasestr(&vocab[c * max_w], chosen[j]) ||
              strcasestr(chosen[j], &vocab[c * max_w])) {
						printf("filtering %s %s\n", chosen[j], &vocab[c * max_w]);
						filtered = 1;
					}
				if(filtered)
					continue;
			}
*/
			chosen[i++]=c;
      HV* hash = newHV();
      SV* word = newSVpvf(&vocab[best[a].wordi * max_w], 0);
      AV* heat = newAV();
      if(latin_enc == 0) SvUTF8_on(word);
      hv_store(hash, "word", strlen("word"), word , 0);
      hv_store(hash, "rank", strlen("rank"), newSVuv(best[a].wordi), 0);
      hv_store(hash, "average", strlen("average"), newSVnv(best[a].average), 0);
      hv_store(hash, "prob", strlen("prob"), newSVnv(best[a].probability), 0);
      hv_store(hash, "cprob", strlen("cprob"), newSVnv(best[a].cprobability_sum), 0);
      hv_store(hash, "max", strlen("max"), newSVnv(best[a].max_activation), 0); // newSVnv(target_sums[best[a].wordi]), 0);
      hv_store(hash, "overall", strlen("overall"), newSVnv(best[a].activation_sum/total_activation), 0); // newSVnv(target_sums[best[a].wordi]), 0);
      hv_store(hash, "pos", strlen("pos"), newSVnv(best[a].position), 0);
      best[a].heat[5]=0;
      for(i=10; i >= 0; i--) av_push(heat, newSVnv(best[a].heat[i]));
      hv_store(hash, "heat", strlen("heat"), newRV_noinc((SV*)heat), 0);
      av_push(array, newRV_noinc((SV*)hash));
    }
    hv_store(result, "syntagmatic", strlen("syntagmatic"), newRV_noinc((SV*)array), 0);
  }
end:
  //  words = old_words; // why was this here?
	free(best);
	return newRV_noinc((SV*)result);
}

int dump_vecs(char *fname) {
	long i, j;
	FILE *f;
  if(words>100000)
	 	words=100000;

	if((f=fopen(fname, "w")) == NULL) {
			fprintf(stderr, "cannot open %s for writing\n", fname);
			return(-1);
	}
	fprintf(f, "%lld %lld\n", words, size);
	for (i=0; i < words; i++) {
		fprintf(f, "%s ", &vocab[i * max_w]);
		for(j=0; j < size - 1; j++)
			fprintf(f, "%f ", M[i*size + j]);
		fprintf(f, "%f\n", M[i*size + j]);
	}
	fclose(f);
	return(0);
}

int dump_for_numpy(char *fname) {
	long i, j;
	FILE *f;
  int max;
  if(merged_end > 0)
    max = 150000;
  else
    max = 300000;
  
	if(words>300000)
	 	words=300000;

	if((f=fopen(fname, "w")) == NULL) {
			fprintf(stderr, "cannot open %s for writing\n", fname);
			return(-1);
	}
	for (i=0; i < max; i++) {
		for(j=0; j < size - 1; j++)
			fprintf(f, "%f\t", M[i*size + j]);
		fprintf(f, "%f\n", M[i*size + j]);
		printf("%s\n", &vocab[i * max_w]);

    if(merged_end > 0) {
      for(j=0; j < size - 1; j++)
        fprintf(f, "%f\t", M[(merged_end + i)*size + j]);
      fprintf(f, "%f\n", M[(merged_end + i)*size + j]);
      printf("_%s\n", &vocab[i * max_w]);
    }
	}
	fclose(f);
 	return(0);
}