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✏️ Editing: Neuron.php

<?php

declare(strict_types=1);

namespace Phpml\NeuralNetwork\Node;

use Phpml\NeuralNetwork\ActivationFunction;
use Phpml\NeuralNetwork\ActivationFunction\Sigmoid;
use Phpml\NeuralNetwork\Node;
use Phpml\NeuralNetwork\Node\Neuron\Synapse;

class Neuron implements Node
{
    /**
     * @var Synapse[]
     */
    protected $synapses = [];

/**
     * @var ActivationFunction
     */
    protected $activationFunction;

/**
     * @var float
     */
    protected $output = 0.0;

/**
     * @var float
     */
    protected $z = 0.0;

public function __construct(?ActivationFunction $activationFunction = null)
    {
        $this->activationFunction = $activationFunction ?? new Sigmoid();
    }

public function addSynapse(Synapse $synapse): void
    {
        $this->synapses[] = $synapse;
    }

/**
     * @return Synapse[]
     */
    public function getSynapses(): array
    {
        return $this->synapses;
    }

public function getOutput(): float
    {
        if ($this->output === 0.0) {
            $this->z = 0;
            foreach ($this->synapses as $synapse) {
                $this->z += $synapse->getOutput();
            }

$this->output = $this->activationFunction->compute($this->z);
        }

return $this->output;
    }

public function getDerivative(): float
    {
        return $this->activationFunction->differentiate($this->z, $this->output);
    }

public function reset(): void
    {
        $this->output = 0.0;
        $this->z = 0.0;
    }
}

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