/**
* Correlation
*/
function correl(array $x_values, array $y_values)
{
return correlation($x_values, $y_values);
}
function clusterize_aggregative($type, $cl_useold)
{
global $CONFIG;
set_time_limit(0);
//this avoids timeouts
include $CONFIG->path . "mod/profile_manager/views/default/profile_manager/members/config.php";
include_once $CONFIG->path . "mod/profile_manager/views/default/profile_manager/members/classes.php";
switch ($type) {
case 'metadata':
$docterm = unserialize(file_get_contents($IOdir . 'metadata_dt'));
$docdoc = unserialize(file_get_contents($IOdir . 'metadata_dd'));
break;
case 'tags':
$docterm = unserialize(file_get_contents($IOdir . 'tags_dt'));
$docdoc = unserialize(file_get_contents($IOdir . 'tags_dd'));
break;
case 'uses':
$docterm = unserialize(file_get_contents($IOdir . 'uses_dt'));
$docdoc = unserialize(file_get_contents($IOdir . 'uses_dd'));
break;
case 'replinks':
$docdoc = unserialize(file_get_contents($IOdir . 'replinks_dd'));
break;
}
$docdoc = sort_matrix($docdoc);
$clusters = array();
foreach ($docdoc as $g => $row) {
$c = new Cluster($type, get_loggedin_user()->username, "aggregative", 1);
$c->array_docs[] = $g;
$clusters[] = $c;
}
$def_cluster = array();
$it = 0;
while (true) {
$it++;
$current = $clusters;
$next = array();
$excluded = array();
$changes = false;
for ($i = 0; $i < count($clusters); $i++) {
if (in_array($current[$i]->id, $excluded)) {
continue;
}
$dist_v = array();
for ($j = 0; $j < count($clusters); $j++) {
if (in_array($current[$j]->id, $excluded)) {
continue;
}
if ($i != $j) {
$dist_v[$current[$j]->id] = correlation($current[$i], $current[$j], $docdoc);
}
}
arsort($dist_v);
foreach ($dist_v as $id => $correlation) {
$fuse = find_cluster_by_id($id, $current);
if (!$fuse) {
continue;
}
$qi1 = quality_index($current[$i], $docdoc);
$qi2 = quality_index($current[$fuse], $docdoc);
if ($correlation == 0 || $correlation < $qi1 || $correlation < $qi2) {
break;
}
$c = new Cluster($type, get_loggedin_user()->username, "aggregative", 1);
$c->array_docs = array_merge($current[$i]->array_docs, $current[$fuse]->array_docs);
$next[] = $c;
$excluded[] = $current[$fuse]->id;
$excluded[] = $current[$i]->id;
$changes = true;
break;
}
}
foreach ($current as $remaining) {
if (!in_array($remaining->id, $excluded)) {
$next[] = $remaining;
}
}
// usort($next,'sort_clusters');
$clusters = $next;
if ($it > 50 || !$changes) {
$def_cluster = $next;
break;
}
}
//delete clusters that contain only one element
foreach ($def_cluster as $key => $cluster) {
if (count($cluster->array_docs) == 1) {
unset($def_cluster[$key]);
}
}
//sort clusters documents by guid
foreach ($def_cluster as $key => $cluster) {
sort($def_cluster[$key]->array_docs);
}
return $def_cluster;
}
function clusterize_aggregative($type)
{
global $IOdir;
global $usern;
switch ($type) {
case 'metadata':
$docterm = unserialize(file_get_contents($IOdir . 'metadata_dt'));
$docdoc = unserialize(file_get_contents($IOdir . 'metadata_dd'));
break;
case 'tags':
$docterm = unserialize(file_get_contents($IOdir . 'tags_dt'));
$docdoc = unserialize(file_get_contents($IOdir . 'tags_dd'));
break;
case 'uses':
$docterm = unserialize(file_get_contents($IOdir . 'uses_dt'));
$docdoc = unserialize(file_get_contents($IOdir . 'uses_dd'));
break;
case 'replinks':
$docdoc = unserialize(file_get_contents($IOdir . 'replinks_dd'));
break;
}
$docdoc = sort_matrix($docdoc);
$clusters = array();
foreach ($docdoc as $g => $row) {
$c = new Cluster($type, $usern, "aggregative", 1);
$c->array_docs[] = $g;
$clusters[] = $c;
}
$def_cluster = array();
$it = 0;
while (true) {
$it++;
$current = $clusters;
$next = array();
$excluded = array();
$changes = false;
for ($i = 0; $i < count($clusters); $i++) {
if (in_array($current[$i]->id, $excluded)) {
continue;
}
$dist_v = array();
for ($j = 0; $j < count($clusters); $j++) {
if (in_array($current[$j]->id, $excluded)) {
continue;
}
if ($i != $j) {
$dist_v[$current[$j]->id] = correlation($current[$i], $current[$j], $docdoc);
}
}
arsort($dist_v);
foreach ($dist_v as $id => $correlation) {
$fuse = find_cluster_by_id($id, $current);
if (!$fuse) {
continue;
}
$qi1 = quality_index($current[$i], $docdoc);
$qi2 = quality_index($current[$fuse], $docdoc);
if ($correlation == 0 || $correlation < $qi1 || $correlation < $qi2) {
break;
}
$c = new Cluster($type, $usern, "aggregative", 1);
$c->array_docs = array_merge($current[$i]->array_docs, $current[$fuse]->array_docs);
$next[] = $c;
$excluded[] = $current[$fuse]->id;
$excluded[] = $current[$i]->id;
$changes = true;
break;
}
}
foreach ($current as $remaining) {
if (!in_array($remaining->id, $excluded)) {
$next[] = $remaining;
}
}
// usort($next,'sort_clusters');
$clusters = $next;
if ($it > 50 || !$changes) {
$def_cluster = $next;
break;
}
}
//delete clusters that contain only one element
foreach ($def_cluster as $key => $cluster) {
if (count($cluster->array_docs) == 1) {
unset($def_cluster[$key]);
}
}
echo "\nCalculating positive features for {$type}...\n";
if ($type != 'replinks') {
$array_cluster = get_positive_features($def_cluster, $docterm, $type);
}
//sort clusters documents by guid
foreach ($array_cluster as $key => $cluster) {
sort($array_cluster[$key]->array_docs);
}
return $array_cluster;
}