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Moved UnitTests to tests/ and Skills to src/
This commit is contained in:
Alexander Liljengård
15
tests/Numerics/BasicMathTest.php
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15
tests/Numerics/BasicMathTest.php
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<?php
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require_once 'PHPUnit/Framework.php';
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require_once(dirname(__FILE__) . '/../../Skills/Numerics/BasicMath.php');
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class BasicMathTest extends PHPUnit_Framework_TestCase
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{
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public function testSquare()
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{
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$this->assertEquals( 1, Moserware\Numerics\square(1) );
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$this->assertEquals( 1.44, Moserware\Numerics\square(1.2) );
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$this->assertEquals( 4, Moserware\Numerics\square(2) );
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}
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}
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?>
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106
tests/Numerics/GaussianDistributionTest.php
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106
tests/Numerics/GaussianDistributionTest.php
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<?php
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namespace Moserware\Numerics;
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require_once 'PHPUnit/Framework.php';
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require_once 'PHPUnit/TextUI/TestRunner.php';
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require_once(dirname(__FILE__) . '/../../Skills/Numerics/GaussianDistribution.php');
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use \PHPUnit_Framework_TestCase;
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class GaussianDistributionTest extends PHPUnit_Framework_TestCase
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{
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const ERROR_TOLERANCE = 0.000001;
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public function testCumulativeTo()
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{
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// Verified with WolframAlpha
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// (e.g. http://www.wolframalpha.com/input/?i=CDF%5BNormalDistribution%5B0%2C1%5D%2C+0.5%5D )
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$this->assertEquals( 0.691462, GaussianDistribution::cumulativeTo(0.5),'', GaussianDistributionTest::ERROR_TOLERANCE);
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}
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public function testAt()
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{
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// Verified with WolframAlpha
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// (e.g. http://www.wolframalpha.com/input/?i=PDF%5BNormalDistribution%5B0%2C1%5D%2C+0.5%5D )
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$this->assertEquals(0.352065, GaussianDistribution::at(0.5), '', GaussianDistributionTest::ERROR_TOLERANCE);
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}
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public function testMultiplication()
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{
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// I verified this against the formula at http://www.tina-vision.net/tina-knoppix/tina-memo/2003-003.pdf
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$standardNormal = new GaussianDistribution(0, 1);
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$shiftedGaussian = new GaussianDistribution(2, 3);
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$product = GaussianDistribution::multiply($standardNormal, $shiftedGaussian);
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$this->assertEquals(0.2, $product->getMean(), '', GaussianDistributionTest::ERROR_TOLERANCE);
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$this->assertEquals(3.0 / sqrt(10), $product->getStandardDeviation(), '', GaussianDistributionTest::ERROR_TOLERANCE);
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$m4s5 = new GaussianDistribution(4, 5);
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$m6s7 = new GaussianDistribution(6, 7);
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$product2 = GaussianDistribution::multiply($m4s5, $m6s7);
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$expectedMean = (4 * square(7) + 6 * square(5)) / (square(5) + square(7));
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$this->assertEquals($expectedMean, $product2->getMean(), '', GaussianDistributionTest::ERROR_TOLERANCE);
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$expectedSigma = sqrt(((square(5) * square(7)) / (square(5) + square(7))));
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$this->assertEquals($expectedSigma, $product2->getStandardDeviation(), '', GaussianDistributionTest::ERROR_TOLERANCE);
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}
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public function testDivision()
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{
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// Since the multiplication was worked out by hand, we use the same numbers but work backwards
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$product = new GaussianDistribution(0.2, 3.0 / sqrt(10));
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$standardNormal = new GaussianDistribution(0, 1);
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$productDividedByStandardNormal = GaussianDistribution::divide($product, $standardNormal);
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$this->assertEquals(2.0, $productDividedByStandardNormal->getMean(), '', GaussianDistributionTest::ERROR_TOLERANCE);
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$this->assertEquals(3.0, $productDividedByStandardNormal->getStandardDeviation(),'', GaussianDistributionTest::ERROR_TOLERANCE);
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$product2 = new GaussianDistribution((4 * square(7) + 6 * square(5)) / (square(5) + square(7)), sqrt(((square(5) * square(7)) / (square(5) + square(7)))));
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$m4s5 = new GaussianDistribution(4,5);
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$product2DividedByM4S5 = GaussianDistribution::divide($product2, $m4s5);
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$this->assertEquals(6.0, $product2DividedByM4S5->getMean(), '', GaussianDistributionTest::ERROR_TOLERANCE);
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$this->assertEquals(7.0, $product2DividedByM4S5->getStandardDeviation(), '', GaussianDistributionTest::ERROR_TOLERANCE);
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}
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public function testLogProductNormalization()
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{
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// Verified with Ralf Herbrich's F# implementation
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$standardNormal = new GaussianDistribution(0, 1);
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$lpn = GaussianDistribution::logProductNormalization($standardNormal, $standardNormal);
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$this->assertEquals(-1.2655121234846454, $lpn, '', GaussianDistributionTest::ERROR_TOLERANCE);
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$m1s2 = new GaussianDistribution(1, 2);
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$m3s4 = new GaussianDistribution(3, 4);
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$lpn2 = GaussianDistribution::logProductNormalization($m1s2, $m3s4);
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$this->assertEquals(-2.5168046699816684, $lpn2, '', GaussianDistributionTest::ERROR_TOLERANCE);
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}
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public function testLogRatioNormalization()
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{
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// Verified with Ralf Herbrich's F# implementation
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$m1s2 = new GaussianDistribution(1, 2);
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$m3s4 = new GaussianDistribution(3, 4);
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$lrn = GaussianDistribution::logRatioNormalization($m1s2, $m3s4);
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$this->assertEquals(2.6157405972171204, $lrn, '', GaussianDistributionTest::ERROR_TOLERANCE);
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}
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public function testAbsoluteDifference()
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{
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// Verified with Ralf Herbrich's F# implementation
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$standardNormal = new GaussianDistribution(0, 1);
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$absDiff = GaussianDistribution::absoluteDifference($standardNormal, $standardNormal);
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$this->assertEquals(0.0, $absDiff, '', GaussianDistributionTest::ERROR_TOLERANCE);
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$m1s2 = new GaussianDistribution(1, 2);
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$m3s4 = new GaussianDistribution(3, 4);
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$absDiff2 = GaussianDistribution::absoluteDifference($m1s2, $m3s4);
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$this->assertEquals(0.4330127018922193, $absDiff2, '', GaussianDistributionTest::ERROR_TOLERANCE);
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}
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}
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?>
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196
tests/Numerics/MatrixTest.php
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196
tests/Numerics/MatrixTest.php
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<?php
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require_once 'PHPUnit/Framework.php';
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require_once 'PHPUnit/TextUI/TestRunner.php';
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require_once(dirname(__FILE__) . '/../../Skills/Numerics/Matrix.php');
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use \PHPUnit_Framework_TestCase;
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use Moserware\Numerics\Matrix;
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use Moserware\Numerics\IdentityMatrix;
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use Moserware\Numerics\SquareMatrix;
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class MatrixTest extends PHPUnit_Framework_TestCase
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{
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public function testTwoByTwoDeterminant()
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{
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$a = new SquareMatrix(1, 2,
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3, 4);
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$this->assertEquals(-2, $a->getDeterminant());
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$b = new SquareMatrix(3, 4,
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5, 6);
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$this->assertEquals(-2, $b->getDeterminant());
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$c = new SquareMatrix(1, 1,
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1, 1);
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$this->assertEquals(0, $c->getDeterminant());
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$d = new SquareMatrix(12, 15,
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17, 21);
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$this->assertEquals(12 * 21 - 15 * 17, $d->getDeterminant());
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}
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public function testThreeByThreeDeterminant()
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{
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$a = new SquareMatrix(1, 2, 3,
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4, 5, 6,
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7, 8, 9);
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$this->assertEquals(0, $a->getDeterminant());
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$pi = new SquareMatrix(3, 1, 4,
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1, 5, 9,
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2, 6, 5);
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// Verified against http://www.wolframalpha.com/input/?i=determinant+%7B%7B3%2C1%2C4%7D%2C%7B1%2C5%2C9%7D%2C%7B2%2C6%2C5%7D%7D
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$this->assertEquals(-90, $pi->getDeterminant());
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}
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public function testFourByFourDeterminant()
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{
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$a = new SquareMatrix( 1, 2, 3, 4,
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5, 6, 7, 8,
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9, 10, 11, 12,
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13, 14, 15, 16);
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$this->assertEquals(0, $a->getDeterminant());
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$pi = new SquareMatrix(3, 1, 4, 1,
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5, 9, 2, 6,
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5, 3, 5, 8,
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9, 7, 9, 3);
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// Verified against http://www.wolframalpha.com/input/?i=determinant+%7B+%7B3%2C1%2C4%2C1%7D%2C+%7B5%2C9%2C2%2C6%7D%2C+%7B5%2C3%2C5%2C8%7D%2C+%7B9%2C7%2C9%2C3%7D%7D
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$this->assertEquals(98, $pi->getDeterminant());
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}
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public function testEightByEightDeterminant()
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{
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$a = new SquareMatrix( 1, 2, 3, 4, 5, 6, 7, 8,
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9, 10, 11, 12, 13, 14, 15, 16,
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17, 18, 19, 20, 21, 22, 23, 24,
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25, 26, 27, 28, 29, 30, 31, 32,
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33, 34, 35, 36, 37, 38, 39, 40,
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41, 42, 32, 44, 45, 46, 47, 48,
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49, 50, 51, 52, 53, 54, 55, 56,
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57, 58, 59, 60, 61, 62, 63, 64);
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$this->assertEquals(0, $a->getDeterminant());
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$pi = new SquareMatrix(3, 1, 4, 1, 5, 9, 2, 6,
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5, 3, 5, 8, 9, 7, 9, 3,
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2, 3, 8, 4, 6, 2, 6, 4,
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3, 3, 8, 3, 2, 7, 9, 5,
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0, 2, 8, 8, 4, 1, 9, 7,
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1, 6, 9, 3, 9, 9, 3, 7,
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5, 1, 0, 5, 8, 2, 0, 9,
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7, 4, 9, 4, 4, 5, 9, 2);
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// Verified against http://www.wolframalpha.com/input/?i=det+%7B%7B3%2C1%2C4%2C1%2C5%2C9%2C2%2C6%7D%2C%7B5%2C3%2C5%2C8%2C9%2C7%2C9%2C3%7D%2C%7B2%2C3%2C8%2C4%2C6%2C2%2C6%2C4%7D%2C%7B3%2C3%2C8%2C3%2C2%2C7%2C9%2C5%7D%2C%7B0%2C2%2C8%2C8%2C4%2C1%2C9%2C7%7D%2C%7B1%2C6%2C9%2C3%2C9%2C9%2C3%2C7%7D%2C%7B5%2C1%2C0%2C5%2C8%2C2%2C0%2C9%7D%2C%7B7%2C4%2C9%2C4%2C4%2C5%2C9%2C2%7D%7D
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$this->assertEquals(1378143, $pi->getDeterminant());
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}
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public function testEquals()
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{
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$a = new SquareMatrix(1, 2,
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3, 4);
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$b = new SquareMatrix(1, 2,
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3, 4);
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$this->assertTrue($a->equals($b));
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$c = Matrix::fromRowsColumns(2, 3,
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1, 2, 3,
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4, 5, 6);
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$d = Matrix::fromRowsColumns(2, 3,
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1, 2, 3,
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4, 5, 6);
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$this->assertTrue($c->equals($d));
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$e = Matrix::fromRowsColumns(3, 2,
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1, 4,
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2, 5,
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3, 6);
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$f = $e->getTranspose();
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$this->assertTrue($d->equals($f));
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// Test rounding (thanks to nsp on GitHub for finding this case)
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$g = new SquareMatrix(1, 2.00000000000001,
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3, 4);
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$h = new SquareMatrix(1, 2,
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3, 4);
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$this->assertTrue($g->equals($h));
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}
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public function testAdjugate()
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{
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// From Wikipedia: http://en.wikipedia.org/wiki/Adjugate_matrix
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$a = new SquareMatrix(1, 2,
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3, 4);
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$b = new SquareMatrix( 4, -2,
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-3, 1);
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$this->assertTrue($b->equals($a->getAdjugate()));
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$c = new SquareMatrix(-3, 2, -5,
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-1, 0, -2,
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3, -4, 1);
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$d = new SquareMatrix(-8, 18, -4,
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-5, 12, -1,
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4, -6, 2);
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$this->assertTrue($d->equals($c->getAdjugate()));
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}
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public function testInverse()
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{
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// see http://www.mathwords.com/i/inverse_of_a_matrix.htm
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$a = new SquareMatrix(4, 3,
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3, 2);
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$b = new SquareMatrix(-2, 3,
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3, -4);
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$aInverse = $a->getInverse();
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$this->assertTrue($b->equals($aInverse));
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$identity2x2 = new IdentityMatrix(2);
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$aaInverse = Matrix::multiply($a, $aInverse);
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$this->assertTrue($identity2x2->equals($aaInverse));
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$c = new SquareMatrix(1, 2, 3,
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0, 4, 5,
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1, 0, 6);
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$cInverse = $c->getInverse();
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$d = Matrix::scalarMultiply((1.0 / 22), new SquareMatrix(24, -12, -2,
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5, 3, -5,
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-4, 2, 4));
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$this->assertTrue($d->equals($cInverse));
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$identity3x3 = new IdentityMatrix(3);
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$ccInverse = Matrix::multiply($c, $cInverse);
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$this->assertTrue($identity3x3->equals($ccInverse));
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}
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}
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$testSuite = new \PHPUnit_Framework_TestSuite();
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$testSuite->addTest( new MatrixTest("testInverse"));
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\PHPUnit_TextUI_TestRunner::run($testSuite);
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?>
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