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726cf4cddf
* travis: move coveralls here, decouple from package * composer: use PSR4 * phpunit: simpler config * travis: add ecs run * composer: add ecs dev * use standard vendor/bin directory for dependency bins, confuses with local bins and require gitignore handling * ecs: add PSR2 * [cs] PSR2 spacing fixes * [cs] PSR2 class name fix * [cs] PHP7 fixes - return semicolon spaces, old rand functions, typehints * [cs] fix less strict typehints * fix typehints to make tests pass * ecs: ignore typehint-less elements * [cs] standardize arrays * [cs] standardize docblock, remove unused comments * [cs] use self where possible * [cs] sort class elements, from public to private * [cs] do not use yoda (found less yoda-cases, than non-yoda) * space * [cs] do not assign in condition * [cs] use namespace imports if possible * [cs] use ::class over strings * [cs] fix defaults for arrays properties, properties and constants single spacing * cleanup ecs comments * [cs] use item per line in multi-items array * missing line * misc * rebase
255 lines
6.0 KiB
PHP
255 lines
6.0 KiB
PHP
<?php
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declare(strict_types=1);
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namespace tests\Phpml\FeatureExtraction;
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use Phpml\FeatureExtraction\StopWords;
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use Phpml\FeatureExtraction\TokenCountVectorizer;
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use Phpml\Tokenization\WhitespaceTokenizer;
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use PHPUnit\Framework\TestCase;
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class TokenCountVectorizerTest extends TestCase
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{
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public function testTransformationWithWhitespaceTokenizer(): void
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{
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$samples = [
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'Lorem ipsum dolor sit amet dolor',
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'Mauris placerat ipsum dolor',
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'Mauris diam eros fringilla diam',
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];
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$vocabulary = [
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0 => 'Lorem',
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1 => 'ipsum',
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2 => 'dolor',
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3 => 'sit',
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4 => 'amet',
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5 => 'Mauris',
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6 => 'placerat',
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7 => 'diam',
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8 => 'eros',
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9 => 'fringilla',
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];
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$tokensCounts = [
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[
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0 => 1,
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1 => 1,
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2 => 2,
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3 => 1,
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4 => 1,
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5 => 0,
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6 => 0,
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7 => 0,
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8 => 0,
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9 => 0,
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],
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[
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0 => 0,
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1 => 1,
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2 => 1,
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3 => 0,
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4 => 0,
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5 => 1,
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6 => 1,
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7 => 0,
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8 => 0,
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9 => 0,
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],
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[
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0 => 0,
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1 => 0,
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2 => 0,
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3 => 0,
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4 => 0,
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5 => 1,
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6 => 0,
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7 => 2,
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8 => 1,
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9 => 1,
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],
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];
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$vectorizer = new TokenCountVectorizer(new WhitespaceTokenizer());
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$vectorizer->fit($samples);
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$this->assertSame($vocabulary, $vectorizer->getVocabulary());
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$vectorizer->transform($samples);
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$this->assertSame($tokensCounts, $samples);
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}
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public function testTransformationWithMinimumDocumentTokenCountFrequency(): void
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{
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// word at least in half samples
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$samples = [
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'Lorem ipsum dolor sit amet',
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'Lorem ipsum sit amet',
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'ipsum sit amet',
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'ipsum sit amet',
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];
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$vocabulary = [
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0 => 'Lorem',
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1 => 'ipsum',
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2 => 'dolor',
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3 => 'sit',
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4 => 'amet',
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];
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$tokensCounts = [
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[
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0 => 1,
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1 => 1,
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2 => 0,
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3 => 1,
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4 => 1,
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],
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[
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0 => 1,
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1 => 1,
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2 => 0,
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3 => 1,
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4 => 1,
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],
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[
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0 => 0,
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1 => 1,
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2 => 0,
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3 => 1,
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4 => 1,
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],
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[
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0 => 0,
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1 => 1,
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2 => 0,
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3 => 1,
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4 => 1,
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],
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];
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$vectorizer = new TokenCountVectorizer(new WhitespaceTokenizer(), null, 0.5);
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$vectorizer->fit($samples);
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$this->assertSame($vocabulary, $vectorizer->getVocabulary());
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$vectorizer->transform($samples);
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$this->assertSame($tokensCounts, $samples);
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// word at least once in all samples
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$samples = [
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'Lorem ipsum dolor sit amet',
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'Morbi quis sagittis Lorem',
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'eros Lorem',
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];
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$tokensCounts = [
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[
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0 => 1,
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1 => 0,
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2 => 0,
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3 => 0,
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4 => 0,
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5 => 0,
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6 => 0,
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7 => 0,
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8 => 0,
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],
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[
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0 => 1,
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1 => 0,
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2 => 0,
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3 => 0,
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4 => 0,
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5 => 0,
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6 => 0,
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7 => 0,
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8 => 0,
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],
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[
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0 => 1,
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1 => 0,
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2 => 0,
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3 => 0,
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4 => 0,
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5 => 0,
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6 => 0,
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7 => 0,
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8 => 0,
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],
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];
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$vectorizer = new TokenCountVectorizer(new WhitespaceTokenizer(), null, 1);
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$vectorizer->fit($samples);
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$vectorizer->transform($samples);
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$this->assertSame($tokensCounts, $samples);
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}
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public function testTransformationWithStopWords(): void
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{
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$samples = [
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'Lorem ipsum dolor sit amet dolor',
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'Mauris placerat ipsum dolor',
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'Mauris diam eros fringilla diam',
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];
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$stopWords = new StopWords(['dolor', 'diam']);
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$vocabulary = [
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0 => 'Lorem',
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1 => 'ipsum',
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//2 => 'dolor',
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2 => 'sit',
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3 => 'amet',
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4 => 'Mauris',
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5 => 'placerat',
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//7 => 'diam',
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6 => 'eros',
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7 => 'fringilla',
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];
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$tokensCounts = [
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[
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0 => 1,
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1 => 1,
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2 => 1,
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3 => 1,
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4 => 0,
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5 => 0,
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6 => 0,
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7 => 0,
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],
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[
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0 => 0,
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1 => 1,
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2 => 0,
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3 => 0,
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4 => 1,
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5 => 1,
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6 => 0,
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7 => 0,
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],
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[
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0 => 0,
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1 => 0,
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2 => 0,
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3 => 0,
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4 => 1,
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5 => 0,
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6 => 1,
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7 => 1,
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],
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];
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$vectorizer = new TokenCountVectorizer(new WhitespaceTokenizer(), $stopWords);
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$vectorizer->fit($samples);
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$this->assertSame($vocabulary, $vectorizer->getVocabulary());
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$vectorizer->transform($samples);
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$this->assertSame($tokensCounts, $samples);
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}
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}
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