LayeredNetwork::getLayers() - 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

LayeredNetwork::getLayers() A

↳ Parent: LayeredNetwork

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\Network;

use Phpml\Exception\BadNeuralNetworkStructureException;
use Phpml\NeuralNetwork\Layer;
use Phpml\NeuralNetwork\Network;
use Phpml\NeuralNetwork\Node\Input;
use Phpml\NeuralNetwork\Node\Neuron;

abstract class LayeredNetwork implements Network
{
    /**
     * @var Layer[]
     */
    protected $layers = [];

    public function addLayer(Layer $layer): void
    {
        $this->layers[] = $layer;
    }

    /**
     * @return Layer[]
     */
    public function getLayers(): array
    {
        return $this->layers;
    }

    public function removeLayers(): void
    {
        unset($this->layers);
    }

    public function getOutputLayer(): Layer
    {
        return $this->layers[count($this->layers) - 1];
    }

    public function getOutput(): array
    {
        $result = [];
        foreach ($this->getOutputLayer()->getNodes() as $neuron) {
            $result[] = $neuron->getOutput();
        }

        return $result;
    }

    /**
     * @param mixed $input
     */
    public function setInput($input): Network
    {
        $firstLayer = $this->layers[0];

        foreach ($firstLayer->getNodes() as $key => $neuron) {
            if ($neuron instanceof Input) {
                $neuron->setInput($input[$key]);
            }
        }

        foreach ($this->getLayers() as $layer) {
            foreach ($layer->getNodes() as $node) {
                if ($node instanceof Neuron) {
                    $node->reset();
                }
            }
        }

        return $this;
    }

    public function getTrainedCharacteristics(): array
    {
        $result = [];
        foreach ($this->layers as $layer) {
            $result[] = $layer->getTrainedCharacteristics();
        }

        return $result;
    }

    public function setTrainedCharacteristics(array $characteristics): void
    {
        if (count($characteristics) != count($this->layers)) {
            throw new BadNeuralNetworkStructureException();
        }

        for ($i = 0; $i < count($this->layers); $i++) {
for ($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
}
            $this->layers[$i]->setTrainedCharacteristics($characteristics[$i]);
        }
    }
}


1			<?php
2
3			declare(strict_types=1);
4
5			namespace Phpml\NeuralNetwork\Network;
6
7			use Phpml\Exception\BadNeuralNetworkStructureException;
8			use Phpml\NeuralNetwork\Layer;
9			use Phpml\NeuralNetwork\Network;
10			use Phpml\NeuralNetwork\Node\Input;
11			use Phpml\NeuralNetwork\Node\Neuron;
12
13			abstract class LayeredNetwork implements Network
14			{
15			/**
16			* @var Layer[]
17			*/
18			protected $layers = [];
19
20			public function addLayer(Layer $layer): void
21			{
22			$this->layers[] = $layer;
23			}
24
25			/**
26			* @return Layer[]
27			*/
28			public function getLayers(): array
29			{
30			return $this->layers;
31			}
32
33			public function removeLayers(): void
34			{
35			unset($this->layers);
36			}
37
38			public function getOutputLayer(): Layer
39			{
40			return $this->layers[count($this->layers) - 1];
41			}
42
43			public function getOutput(): array
44			{
45			$result = [];
46			foreach ($this->getOutputLayer()->getNodes() as $neuron) {
47			$result[] = $neuron->getOutput();
48			}
49
50			return $result;
51			}
52
53			/**
54			* @param mixed $input
55			*/
56			public function setInput($input): Network
57			{
58			$firstLayer = $this->layers[0];
59
60			foreach ($firstLayer->getNodes() as $key => $neuron) {
61			if ($neuron instanceof Input) {
62			$neuron->setInput($input[$key]);
63			}
64			}
65
66			foreach ($this->getLayers() as $layer) {
67			foreach ($layer->getNodes() as $node) {
68			if ($node instanceof Neuron) {
69			$node->reset();
70			}
71			}
72			}
73
74			return $this;
75			}
76
77			public function getTrainedCharacteristics(): array
78			{
79			$result = [];
80			foreach ($this->layers as $layer) {
81			$result[] = $layer->getTrainedCharacteristics();
82			}
83
84			return $result;
85			}
86
87			public function setTrainedCharacteristics(array $characteristics): void
88			{
89			if (count($characteristics) != count($this->layers)) {
90			throw new BadNeuralNetworkStructureException();
91			}
92
93			for ($i = 0; $i < count($this->layers); $i++) {
			0 ignored issues – show Performance Best Practice introduced 2019-07-24 12:54 UTC by Report Bug Copy Issue Report It seems like you are calling the size function `count()` as part of the test condition. You might want to compute the size beforehand, and not on each iteration. If the size of the collection does not change during the iteration, it is generally a good practice to compute it beforehand, and not on each iteration: for ($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...
94			$this->layers[$i]->setTrainedCharacteristics($characteristics[$i]);
95			}
96			}
97			}
98

php-ai / php-ml

Pull Request — master (#399)

LayeredNetwork::getLayers() A

Complexity

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Duplication

Importance

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