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<?php |
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|
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if (!defined('ABSPATH')) { |
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exit; |
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} |
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|
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/** |
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* Per-call accumulator that ranks candidate page IDs by approximate edit |
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* distance for the spell-checking subsystem. |
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* |
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* One instance is created for each {@see ABJ_404_Solution_SpellLevenshteinEngine::getLikelyMatchIDs()} |
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* call. The engine feeds it one candidate at a time via {@see score()}; the |
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* ranker files each candidate into min/max edit-distance buckets. Once the |
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* batch is exhausted the engine calls {@see prioritize()} to harvest the |
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* closest-matching IDs (closest distance first, IDs that share whole words |
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* with the requested URL promoted ahead of the rest). |
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* |
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* This responsibility was extracted from the engine: holding the bucket state |
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* here (rather than passing three accumulator arrays through the hot loop by |
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* reference) keeps the scoring logic independently testable and the engine's |
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* orchestration loop allocation-clean. |
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*/ |
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// allow-no-test-found: behavior-identical extraction from ABJ_404_Solution_SpellLevenshteinEngine::getLikelyMatchIDs; exercised end-to-end through that path in SpellCheckerMatchingTest, SpellCheckerAlgorithmTest, SpellCheckerPrefilteringTest and the @group integration SpellCheckerLargeScaleTest. Same integration-coverage strategy as the sibling spell collaborators (SpellNGramPrefilter, SpellCandidatePermalinkLookup). |
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class ABJ_404_Solution_SpellCandidateDistanceRanker { |
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|
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const MAX_DIST = 2083; |
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|
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const MAX_LIKELY_DISTANCE = 300; |
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|
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/** @var ABJ_404_Solution_Functions */ |
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private $f; |
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|
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/** @var ABJ_404_Solution_PluginLogic */ |
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private $logic; |
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|
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/** @var ABJ_404_Solution_Logging */ |
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private $logger; |
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|
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/** @var ABJ_404_Solution_SpellURLMatcher */ |
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private $urlMatcher; |
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|
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/** @var array<int, string> */ |
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private array $separatingCharacters; |
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|
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/** @var ABJ_404_Solution_SpellNGramPrefilter */ |
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private $ngramPrefilter; |
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|
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/** @var array<int, array<int, mixed>> candidate IDs keyed by minimum possible edit distance */ |
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private array $minDistances; |
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|
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/** @var array<int, array<int, mixed>> candidate IDs keyed by maximum possible edit distance */ |
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private array $maxDistances; |
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|
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/** @var array<int, mixed> candidate IDs that share at least one whole word with the request */ |
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private array $idsWithWordsInCommon = array(); |
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|
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/** |
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* @param ABJ_404_Solution_SpellLevenshteinEngineDependencies $deps shared collaborator bundle |
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* @param ABJ_404_Solution_SpellNGramPrefilter $ngramPrefilter the engine's prefilter, reused for the secondary filter |
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*/ |
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public function __construct(ABJ_404_Solution_SpellLevenshteinEngineDependencies $deps, |
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ABJ_404_Solution_SpellNGramPrefilter $ngramPrefilter) { |
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$this->f = $deps->functions; |
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$this->logic = $deps->logic; |
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$this->logger = $deps->logger; |
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$this->urlMatcher = $deps->urlMatcher; |
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$this->separatingCharacters = $deps->separatingCharacters; |
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$this->ngramPrefilter = $ngramPrefilter; |
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|
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// Allocate the empty min/max edit-distance bucket arrays, one slot per |
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// possible distance from 0 to self::MAX_DIST inclusive. |
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$this->minDistances = array(); |
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$this->maxDistances = array(); |
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for ($currentDistanceIndex = 0; $currentDistanceIndex <= self::MAX_DIST; $currentDistanceIndex++) { |
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$this->maxDistances[$currentDistanceIndex] = array(); |
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$this->minDistances[$currentDistanceIndex] = array(); |
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} |
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} |
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|
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/** |
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* Compute the min/max edit-distance bounds for one candidate URL and file |
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* its id into the distance buckets. Pure scoring: no I/O, mutates only this |
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* instance's bucket state. |
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* |
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* @param mixed $id the raw candidate id, as gathered from the row |
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* @param string $existingPageURLPath the candidate URL path (urlParts['path']) |
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* @param int $requestedURLCleanedLength |
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* @param string $fullURLspaces |
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* @param int $fullURLspacesLength |
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* @param array<int, string> $userRequestedURLWords |
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*/ |
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public function score($id, string $existingPageURLPath, int $requestedURLCleanedLength, |
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string $fullURLspaces, int $fullURLspacesLength, array $userRequestedURLWords): void { |
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$existingPageURL = $this->logic->urlNormalization()->removeHomeDirectory($existingPageURLPath); |
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|
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$existingPageURLSpaces = $this->f->str_replace($this->separatingCharacters, " ", $existingPageURL); |
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|
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$existingPageURLCleaned = $this->urlMatcher->getLastURLPart($existingPageURLSpaces); |
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$existingPageURLSpaces = null; |
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|
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$minDist = abs($this->f->strlen($existingPageURLCleaned) - $requestedURLCleanedLength); |
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if ($fullURLspaces != '') { |
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$minDist = min($minDist, abs($fullURLspacesLength - $requestedURLCleanedLength)); |
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} |
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$maxDist = $this->f->strlen($existingPageURLCleaned); |
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if ($fullURLspaces != '') { |
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$maxDist = min($maxDist, $fullURLspacesLength); |
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} |
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|
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$existingPageURLCleanedWords = explode(" ", $existingPageURLCleaned); |
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$wordsInCommon = array_intersect($userRequestedURLWords, $existingPageURLCleanedWords); |
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$wordsInCommon = array_merge(array_unique($wordsInCommon, SORT_REGULAR), array()); |
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if (count($wordsInCommon) > 0) { |
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array_push($this->idsWithWordsInCommon, $id); |
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$lengthOfTheLongestWordInCommon = max(array_map(array($this->f,'strlen'), $wordsInCommon)); |
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$maxDist = $maxDist - $lengthOfTheLongestWordInCommon; |
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} |
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|
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if (isset($this->minDistances[$minDist])) { |
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array_push($this->minDistances[$minDist], $id); |
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} else { |
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$this->minDistances[$minDist] = [$id]; |
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} |
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|
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if ($maxDist < 0) { |
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$this->logger->errorMessage("maxDist is less than 0 (" . $maxDist . |
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") for '" . $existingPageURLCleaned . "', wordsInCommon: " . |
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json_encode($wordsInCommon) . ", "); |
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$maxDist = 0; |
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} else if ($maxDist > self::MAX_DIST) { |
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$maxDist = self::MAX_DIST; |
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} |
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|
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if (is_array($this->maxDistances[$maxDist])) { |
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array_push($this->maxDistances[$maxDist], $id); |
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} |
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} |
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|
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/** |
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* The largest max-distance bucket index we need to scan to have seen at |
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* least $onlyNeedThisManyPages candidates, scaled up 10% for headroom. |
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* Used by the engine to bound how many more rows it pulls from the batch. |
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* |
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* @param int $onlyNeedThisManyPages |
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* @return int |
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*/ |
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public function getMaxAcceptableDistance(int $onlyNeedThisManyPages): int { |
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$pagesSeenSoFar = 0; |
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$maxDistFound = self::MAX_LIKELY_DISTANCE; |
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for ($currentDistanceIndex = 0; $currentDistanceIndex <= self::MAX_LIKELY_DISTANCE; $currentDistanceIndex++) { |
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$pagesSeenSoFar += sizeof($this->maxDistances[$currentDistanceIndex]); |
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|
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if ($pagesSeenSoFar >= $onlyNeedThisManyPages) { |
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$maxDistFound = $currentDistanceIndex; |
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break; |
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} |
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} |
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|
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$acceptableDistance = (int)($maxDistFound * 1.1); |
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return $acceptableDistance; |
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} |
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|
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/** |
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* Harvest the prioritized candidate IDs from the accumulated buckets: |
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* closest min-distance first, IDs sharing whole words promoted ahead of |
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* the rest, then the n-gram secondary filter applied. |
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* |
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* @param int $onlyNeedThisManyPages |
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* @param bool $ngramPrefilterApplied |
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* @param string $requestedURLCleaned |
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* @return array<int, mixed> |
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*/ |
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public function prioritize(int $onlyNeedThisManyPages, bool $ngramPrefilterApplied, |
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string $requestedURLCleaned): array { |
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$pagesSeenSoFar = 0; |
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$maxDistFound = self::MAX_LIKELY_DISTANCE; |
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for ($currentDistanceIndex = 0; $currentDistanceIndex <= self::MAX_LIKELY_DISTANCE; $currentDistanceIndex++) { |
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$pagesSeenSoFar += sizeof($this->maxDistances[$currentDistanceIndex]); |
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if ($pagesSeenSoFar >= $onlyNeedThisManyPages) { |
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$maxDistFound = $currentDistanceIndex; |
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break; |
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} |
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} |
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|
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$listOfIDsToReturn = array(); |
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for ($currentDistanceIndex = 0; $currentDistanceIndex <= $maxDistFound; $currentDistanceIndex++) { |
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$listOfMinDistanceIDs = $this->minDistances[$currentDistanceIndex]; |
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$listOfIDsToReturn = array_merge($listOfIDsToReturn, $listOfMinDistanceIDs); |
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} |
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|
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$listOfIDsToReturn = $this->normalizeScalarIds($listOfIDsToReturn); |
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$idsWithWordsInCommon = $this->normalizeScalarIds($this->idsWithWordsInCommon); |
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$idsWithWords = array_intersect($listOfIDsToReturn, $idsWithWordsInCommon); |
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$idsWithoutWords = array_diff($listOfIDsToReturn, $idsWithWordsInCommon); |
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$listOfIDsToReturn = array_merge($idsWithWords, $idsWithoutWords); |
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|
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$listOfIDsToReturn = $this->normalizeScalarIds( |
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$this->ngramPrefilter->applySecondaryFilter( |
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$listOfIDsToReturn, |
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$ngramPrefilterApplied, |
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$requestedURLCleaned |
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) |
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); |
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|
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if (count($listOfIDsToReturn) > 300 && count($idsWithWordsInCommon) >= $onlyNeedThisManyPages) { |
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$maybeOKguesses = array_intersect($listOfIDsToReturn, $idsWithWordsInCommon); |
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return (count($maybeOKguesses) >= $onlyNeedThisManyPages) |
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? $maybeOKguesses : $idsWithWordsInCommon; |
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} |
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return $listOfIDsToReturn; |
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} |
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|
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/** |
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* @param array<int, mixed> $ids |
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* @return array<int, int|string> |
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*/ |
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private function normalizeScalarIds(array $ids): array { |
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$normalized = array(); |
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foreach ($ids as $id) { |
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if (is_int($id) || is_string($id)) { |
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$normalized[] = $id; |
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} else if (is_scalar($id)) { |
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$normalized[] = (string)$id; |
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} |
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} |
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return $normalized; |
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} |
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} |
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|