LayeredNetwork::setInput() - Code Metrics - Inspection of "Neural networks partial training and persistency (..." - php-ai/php-ml - Measure and Improve Code Quality continuously with Scrutinizer

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by Arkadiusz

created 2017-05-23 07:03 UTC

LayeredNetwork::setInput() B

↳ Parent: LayeredNetwork

Complexity

Conditions	6
Paths	12

Size

Total Lines	20
Code Lines	10

Duplication

Lines	0
Ratio	0 %

Importance

Changes

Metric	Value
dl	0
loc	20
c	0
b	0
f	0
rs	8.8571
cc	6
eloc	10
nc	12
nop	1

<?php

declare(strict_types=1);

namespace Phpml\NeuralNetwork\Network;

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;

    /**
     * @param Layer $layer
     */
    public function addLayer(Layer $layer)
    {
        $this->layers[] = $layer;
    }

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

    /**
     * @return void
     */
    public function removeLayers()
    {
        unset($this->layers);
    }

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

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

        return $result;
    }

    /**
     * @param mixed $input
     *
     * @return $this
     */
    public function setInput($input)
    {
        $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;
    }
}


1			<?php
2
3			declare(strict_types=1);
4
5			namespace Phpml\NeuralNetwork\Network;
6
7			use Phpml\NeuralNetwork\Layer;
8			use Phpml\NeuralNetwork\Network;
9			use Phpml\NeuralNetwork\Node\Input;
10			use Phpml\NeuralNetwork\Node\Neuron;
11
12			abstract class LayeredNetwork implements Network
13			{
14			/**
15			* @var Layer[]
16			*/
17			protected $layers;
18
19			/**
20			* @param Layer $layer
21			*/
22			public function addLayer(Layer $layer)
23			{
24			$this->layers[] = $layer;
25			}
26
27			/**
28			* @return Layer[]
29			*/
30			public function getLayers(): array
31			{
32			return $this->layers;
33			}
34
35			/**
36			* @return void
37			*/
38			public function removeLayers()
39			{
40			unset($this->layers);
41			}
42
43			/**
44			* @return Layer
45			*/
46			public function getOutputLayer(): Layer
47			{
48			return $this->layers[count($this->layers) - 1];
49			}
50
51			/**
52			* @return array
53			*/
54			public function getOutput(): array
55			{
56			$result = [];
57			foreach ($this->getOutputLayer()->getNodes() as $neuron) {
58			$result[] = $neuron->getOutput();
59			}
60
61			return $result;
62			}
63
64			/**
65			* @param mixed $input
66			*
67			* @return $this
68			*/
69			public function setInput($input)
70			{
71			$firstLayer = $this->layers[0];
72
73			foreach ($firstLayer->getNodes() as $key => $neuron) {
74			if ($neuron instanceof Input) {
75			$neuron->setInput($input[$key]);
76			}
77			}
78
79			foreach ($this->getLayers() as $layer) {
80			foreach ($layer->getNodes() as $node) {
81			if ($node instanceof Neuron) {
82			$node->reset();
83			}
84			}
85			}
86
87			return $this;
88			}
89			}
90

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LayeredNetwork::setInput() B

Complexity

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