Example #1
0
 public function testGetPrefixUtf8()
 {
     // UTF-8 string with non-ascii symbols (Russian alphabet)
     $this->assertEquals(Index\Term::getPrefix('абвгдеёжзийклмнопрстуфхцчшщьыъэюя', 64), 'абвгдеёжзийклмнопрстуфхцчшщьыъэюя');
     $this->assertEquals(Index\Term::getPrefix('абвгдеёжзийклмнопрстуфхцчшщьыъэюя', 33), 'абвгдеёжзийклмнопрстуфхцчшщьыъэюя');
     $this->assertEquals(Index\Term::getPrefix('абвгдеёжзийклмнопрстуфхцчшщьыъэюя', 4), 'абвг');
     $this->assertEquals(Index\Term::getPrefix('абвгдеёжзийклмнопрстуфхцчшщьыъэюя', 0), '');
 }
Example #2
0
 /**
  * Scans terms dictionary and returns next term
  *
  * @return \Zend\Search\Lucene\Index\Term|null
  */
 public function nextTerm()
 {
     if ($this->_tisFile === null || $this->_termCount == 0) {
         $this->_lastTerm = null;
         $this->_lastTermInfo = null;
         $this->_lastTermPositions = null;
         $this->_docMap = null;
         // may be necessary for "empty" segment
         $this->_tisFile = null;
         $this->_frqFile = null;
         $this->_prxFile = null;
         return null;
     }
     $termPrefixLength = $this->_tisFile->readVInt();
     $termSuffix = $this->_tisFile->readString();
     $termFieldNum = $this->_tisFile->readVInt();
     $termValue = Term::getPrefix($this->_lastTerm->text, $termPrefixLength) . $termSuffix;
     $this->_lastTerm = new Term($termValue, $this->_fields[$termFieldNum]->name);
     $docFreq = $this->_tisFile->readVInt();
     $freqPointer = $this->_lastTermInfo->freqPointer + $this->_tisFile->readVInt();
     $proxPointer = $this->_lastTermInfo->proxPointer + $this->_tisFile->readVInt();
     if ($docFreq >= $this->_skipInterval) {
         $skipOffset = $this->_tisFile->readVInt();
     } else {
         $skipOffset = 0;
     }
     $this->_lastTermInfo = new TermInfo($docFreq, $freqPointer, $proxPointer, $skipOffset);
     if ($this->_termsScanMode == self::SM_FULL_INFO || $this->_termsScanMode == self::SM_MERGE_INFO) {
         $this->_lastTermPositions = array();
         $this->_frqFile->seek($this->_lastTermInfo->freqPointer + $this->_frqFileOffset, SEEK_SET);
         $freqs = array();
         $docId = 0;
         for ($count = 0; $count < $this->_lastTermInfo->docFreq; $count++) {
             $docDelta = $this->_frqFile->readVInt();
             if ($docDelta % 2 == 1) {
                 $docId += ($docDelta - 1) / 2;
                 $freqs[$docId] = 1;
             } else {
                 $docId += $docDelta / 2;
                 $freqs[$docId] = $this->_frqFile->readVInt();
             }
         }
         $this->_prxFile->seek($this->_lastTermInfo->proxPointer + $this->_prxFileOffset, SEEK_SET);
         foreach ($freqs as $docId => $freq) {
             $termPosition = 0;
             $positions = array();
             for ($count = 0; $count < $freq; $count++) {
                 $termPosition += $this->_prxFile->readVInt();
                 $positions[] = $termPosition;
             }
             if (isset($this->_docMap[$docId])) {
                 $this->_lastTermPositions[$this->_docMap[$docId]] = $positions;
             }
         }
     }
     $this->_termCount--;
     if ($this->_termCount == 0) {
         $this->_tisFile = null;
         $this->_frqFile = null;
         $this->_prxFile = null;
     }
     return $this->_lastTerm;
 }
Example #3
0
File: Fuzzy.php Project: stunti/zf2
 /**
  * Query specific matches highlighting
  *
  * @param \Zend\Search\Lucene\Search\Highlighter\HighlighterInterface $highlighter  Highlighter object (also contains doc for highlighting)
  */
 protected function _highlightMatches(Highlighter\HighlighterInterface $highlighter)
 {
     $words = array();
     $prefix = Index\Term::getPrefix($this->_term->text, $this->_prefixLength);
     $prefixByteLength = strlen($prefix);
     $prefixUtf8Length = Index\Term::getLength($prefix);
     $termLength = Index\Term::getLength($this->_term->text);
     $termRest = substr($this->_term->text, $prefixByteLength);
     // we calculate length of the rest in bytes since levenshtein() is not UTF-8 compatible
     $termRestLength = strlen($termRest);
     $scaleFactor = 1 / (1 - $this->_minimumSimilarity);
     $docBody = $highlighter->getDocument()->getFieldUtf8Value('body');
     $tokens = Lucene\Analysis\Analyzer\Analyzer::getDefault()->tokenize($docBody, 'UTF-8');
     foreach ($tokens as $token) {
         $termText = $token->getTermText();
         if (substr($termText, 0, $prefixByteLength) == $prefix) {
             // Calculate similarity
             $target = substr($termText, $prefixByteLength);
             $maxDistance = isset($this->_maxDistances[strlen($target)]) ? $this->_maxDistances[strlen($target)] : $this->_calculateMaxDistance($prefixUtf8Length, $termRestLength, strlen($target));
             if ($termRestLength == 0) {
                 // we don't have anything to compare.  That means if we just add
                 // the letters for current term we get the new word
                 $similarity = $prefixUtf8Length == 0 ? 0 : 1 - strlen($target) / $prefixUtf8Length;
             } else {
                 if (strlen($target) == 0) {
                     $similarity = $prefixUtf8Length == 0 ? 0 : 1 - $termRestLength / $prefixUtf8Length;
                 } else {
                     if ($maxDistance < abs($termRestLength - strlen($target))) {
                         //just adding the characters of term to target or vice-versa results in too many edits
                         //for example "pre" length is 3 and "prefixes" length is 8.  We can see that
                         //given this optimal circumstance, the edit distance cannot be less than 5.
                         //which is 8-3 or more precisesly abs(3-8).
                         //if our maximum edit distance is 4, then we can discard this word
                         //without looking at it.
                         $similarity = 0;
                     } else {
                         $similarity = 1 - levenshtein($termRest, $target) / ($prefixUtf8Length + min($termRestLength, strlen($target)));
                     }
                 }
             }
             if ($similarity > $this->_minimumSimilarity) {
                 $words[] = $termText;
             }
         }
     }
     $highlighter->highlight($words);
 }