69 lines
1.9 KiB
PHP
69 lines
1.9 KiB
PHP
<?php
|
|
|
|
declare(strict_types=1);
|
|
|
|
namespace Phpml\Tests\Preprocessing;
|
|
|
|
use Phpml\Preprocessing\LabelEncoder;
|
|
use PHPUnit\Framework\TestCase;
|
|
|
|
final class LabelEncoderTest extends TestCase
|
|
{
|
|
/**
|
|
* @dataProvider labelEncoderDataProvider
|
|
*/
|
|
public function testFitAndTransform(array $samples, array $transformed): void
|
|
{
|
|
$le = new LabelEncoder();
|
|
$le->fit($samples);
|
|
$le->transform($samples);
|
|
|
|
self::assertEquals($transformed, $samples);
|
|
}
|
|
|
|
public function labelEncoderDataProvider(): array
|
|
{
|
|
return [
|
|
[['one', 'one', 'two', 'three'], [0, 0, 1, 2]],
|
|
[['one', 1, 'two', 'three'], [0, 1, 2, 3]],
|
|
[['one', null, 'two', 'three'], [0, 1, 2, 3]],
|
|
[['one', 'one', 'one', 'one'], [0, 0, 0, 0]],
|
|
[['one', 'one', 'one', 'one', null, null, 1, 1, 2, 'two'], [0, 0, 0, 0, 1, 1, 2, 2, 3, 4]],
|
|
];
|
|
}
|
|
|
|
public function testResetClassesAfterNextFit(): void
|
|
{
|
|
$samples = ['Shanghai', 'Beijing', 'Karachi'];
|
|
|
|
$le = new LabelEncoder();
|
|
$le->fit($samples);
|
|
|
|
self::assertEquals(['Shanghai', 'Beijing', 'Karachi'], $le->classes());
|
|
|
|
$samples = ['Istanbul', 'Dhaka', 'Tokyo'];
|
|
|
|
$le->fit($samples);
|
|
|
|
self::assertEquals(['Istanbul', 'Dhaka', 'Tokyo'], $le->classes());
|
|
}
|
|
|
|
public function testFitAndTransformFullCycle(): void
|
|
{
|
|
$samples = ['Shanghai', 'Beijing', 'Karachi', 'Beijing', 'Beijing', 'Karachi'];
|
|
$encoded = [0, 1, 2, 1, 1, 2];
|
|
|
|
$le = new LabelEncoder();
|
|
$le->fit($samples);
|
|
|
|
self::assertEquals(['Shanghai', 'Beijing', 'Karachi'], $le->classes());
|
|
|
|
$transformed = $samples;
|
|
$le->transform($transformed);
|
|
self::assertEquals($encoded, $transformed);
|
|
|
|
$le->inverseTransform($transformed);
|
|
self::assertEquals($samples, $transformed);
|
|
}
|
|
}
|