Phpml\NeuralNetwork\Node\Neuron

Complexity

Total Complexity

9

Size/Duplication

Total Lines	61
Duplicated Lines	0 %

Coupling/Cohesion

Components	1
Dependencies	3

Importance

Changes

0

6 Methods

Rating	Name	Duplication	Size	Complexity
A	__construct()	0	6	2
A	addSynapse()	0	4	1
A	getSynapses()	0	4	1
A	getOutput()	0	13	3
A	getDerivative()	0	4	1
A	reset()	0	4	1

<?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;

    public function __construct(?ActivationFunction $activationFunction = null)
    {
        $this->activationFunction = $activationFunction ?: new Sigmoid();
        $this->synapses = [];
        $this->output = 0;

The property $output was declared of type double, but 0 is of type integer. Maybe add a type cast?

    }

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

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

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

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

        return $this->output;
    }

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

    public function reset(): void
    {
        $this->output = 0;

The property $output was declared of type double, but 0 is of type integer. Maybe add a type cast?

    }
}