Layer::getNodes() - Code Metrics - Inspection of "Add load/save feature for MultilayerPerceptron tra..." - php-ai/php-ml - Measure and Improve Code Quality continuously with Scrutinizer

Passed

Pull Request — master (#399)

unknown

created 2019-07-29 19:09 UTC

Layer::getNodes() A

↳ Parent: Layer

Complexity

Conditions	1
Paths	1

Size

Total Lines	3
Code Lines	1

Duplication

Lines	0
Ratio	0 %

Importance

Changes

Metric	Value
eloc	1
dl	0
loc	3
rs	10
c	0
b	0
f	0
cc	1
nc	1
nop	0

<?php

declare(strict_types=1);

namespace Phpml\NeuralNetwork;

use Phpml\Exception\BadNeuralNetworkStructureException;
use Phpml\Exception\InvalidArgumentException;
use Phpml\NeuralNetwork\Node\Neuron;

class Layer
{
    /**
     * @var Node[]
     */
    private $nodes = [];

    /**
     * @throws InvalidArgumentException
     */
    public function __construct(int $nodesNumber = 0, string $nodeClass = Neuron::class, ?ActivationFunction $activationFunction = null)
    {
        if (!in_array(Node::class, class_implements($nodeClass), true)) {
            throw new InvalidArgumentException('Layer node class must implement Node interface');
        }

        for ($i = 0; $i < $nodesNumber; ++$i) {
            $this->nodes[] = $this->createNode($nodeClass, $activationFunction);
        }
    }

    public function addNode(Node $node): void
    {
        $this->nodes[] = $node;
    }

    /**
     * @return Node[]
     */
    public function getNodes(): array
    {
        return $this->nodes;
    }

    public function getTrainedCharacteristics(): array
    {
        $result = [];
        foreach ($this->nodes as $node) {
            if ($node instanceof Neuron) {
                $result[] = $node->getTrainedCharacteristics();
            }
        }

        return $result;
    }

    public function setTrainedCharacteristics(array $characteristics): void
    {
        // iterate over the node instances
        $iNode = -1;
        for ($i = 0; $i < count($this->nodes); $i++) {
for ($i=0; $i<count($array); $i++) { // calls count() on each iteration
}

// Better
for ($i=0, $c=count($array); $i<$c; $i++) { // calls count() just once
}
            $node = $this->nodes[$i];
            if ($node instanceof Neuron) {
                $iNode ++;

                if (count($characteristics) < $iNode + 1) {
                    throw new BadNeuralNetworkStructureException();
                }

                $node->setTrainedCharacteristics($characteristics[$iNode]);
            }
        }
    }

    private function createNode(string $nodeClass, ?ActivationFunction $activationFunction = null): Node
    {
        if ($nodeClass === Neuron::class) {
            return new Neuron($activationFunction);
        }

        return new $nodeClass();
    }
}


1			<?php
2
3			declare(strict_types=1);
4
5			namespace Phpml\NeuralNetwork;
6
7			use Phpml\Exception\BadNeuralNetworkStructureException;
8			use Phpml\Exception\InvalidArgumentException;
9			use Phpml\NeuralNetwork\Node\Neuron;
10
11			class Layer
12			{
13			/**
14			* @var Node[]
15			*/
16			private $nodes = [];
17
18			/**
19			* @throws InvalidArgumentException
20			*/
21			public function __construct(int $nodesNumber = 0, string $nodeClass = Neuron::class, ?ActivationFunction $activationFunction = null)
22			{
23			if (!in_array(Node::class, class_implements($nodeClass), true)) {
24			throw new InvalidArgumentException('Layer node class must implement Node interface');
25			}
26
27			for ($i = 0; $i < $nodesNumber; ++$i) {
28			$this->nodes[] = $this->createNode($nodeClass, $activationFunction);
29			}
30			}
31
32			public function addNode(Node $node): void
33			{
34			$this->nodes[] = $node;
35			}
36
37			/**
38			* @return Node[]
39			*/
40			public function getNodes(): array
41			{
42			return $this->nodes;
43			}
44
45			public function getTrainedCharacteristics(): array
46			{
47			$result = [];
48			foreach ($this->nodes as $node) {
49			if ($node instanceof Neuron) {
50			$result[] = $node->getTrainedCharacteristics();
51			}
52			}
53
54			return $result;
55			}
56
57			public function setTrainedCharacteristics(array $characteristics): void
58			{
59			// iterate over the node instances
60			$iNode = -1;
61			for ($i = 0; $i < count($this->nodes); $i++) {
			0 ignored issues – show Performance Best Practice introduced 2019-07-24 12:54 UTC by Report Bug Copy Issue Report It seems like you are calling the size function `count()` as part of the test condition. You might want to compute the size beforehand, and not on each iteration. If the size of the collection does not change during the iteration, it is generally a good practice to compute it beforehand, and not on each iteration: for ($i=0; $i<count($array); $i++) { // calls count() on each iteration } // Better for ($i=0, $c=count($array); $i<$c; $i++) { // calls count() just once } Loading history...
62			$node = $this->nodes[$i];
63			if ($node instanceof Neuron) {
64			$iNode ++;
65
66			if (count($characteristics) < $iNode + 1) {
67			throw new BadNeuralNetworkStructureException();
68			}
69
70			$node->setTrainedCharacteristics($characteristics[$iNode]);
71			}
72			}
73			}
74
75			private function createNode(string $nodeClass, ?ActivationFunction $activationFunction = null): Node
76			{
77			if ($nodeClass === Neuron::class) {
78			return new Neuron($activationFunction);
79			}
80
81			return new $nodeClass();
82			}
83			}
84

php-ai / php-ml

Pull Request — master (#399)

Layer::getNodes() A

Complexity

Size

Duplication

Importance

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