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implements and test multilayer perceptron methods
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<?php
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declare (strict_types = 1);
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namespace tests\Phpml\NeuralNetwork\Network;
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use Phpml\NeuralNetwork\Network\MultilayerPerceptron;
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use Phpml\NeuralNetwork\Node\Neuron;
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class MultilayerPerceptronTest extends \PHPUnit_Framework_TestCase
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{
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public function testMultilayerPerceptronLayersInitialization()
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{
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$mlp = new MultilayerPerceptron([2, 2, 1]);
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$this->assertCount(3, $mlp->getLayers());
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$layers = $mlp->getLayers();
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// input layer
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$this->assertCount(3, $layers[0]->getNodes());
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$this->assertNotContainsOnly(Neuron::class, $layers[0]->getNodes());
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// hidden layer
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$this->assertCount(3, $layers[1]->getNodes());
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$this->assertNotContainsOnly(Neuron::class, $layers[0]->getNodes());
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// output layer
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$this->assertCount(1, $layers[2]->getNodes());
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$this->assertContainsOnly(Neuron::class, $layers[2]->getNodes());
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}
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public function testSynapsesGeneration()
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{
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$mlp = new MultilayerPerceptron([2, 2, 1]);
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$layers = $mlp->getLayers();
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foreach ($layers[1]->getNodes() as $node) {
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if ($node instanceof Neuron) {
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$synapses = $node->getSynapses();
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$this->assertCount(3, $synapses);
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$synapsesNodes = $this->getSynapsesNodes($synapses);
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foreach ($layers[0]->getNodes() as $prevNode) {
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$this->assertContains($prevNode, $synapsesNodes);
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}
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}
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}
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}
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/**
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* @param array $synapses
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*
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* @return array
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*/
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private function getSynapsesNodes(array $synapses): array
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{
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$nodes = [];
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foreach ($synapses as $synapse) {
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$nodes[] = $synapse->getNode();
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}
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return $nodes;
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}
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/**
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* @expectedException \Phpml\Exception\InvalidArgumentException
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*/
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public function testThrowExceptionOnInvalidLayersNumber()
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{
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new MultilayerPerceptron([2]);
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}
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}
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