neuralnet.php/build/neuralnetwork/core/Genome.php

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<?php
namespace neuralnetwork\core;
use filemanager\core\FileManager;
class Genome/* implements \Serializable*/{
/************************************************
**** Constants ****
************************************************/
const MIN = 0;
const MAX = 1e9;
/************************************************
**** LOCAL ATTRIBUTES ****
************************************************/
public $layers; // Number of layers
public $neurons; // Neurons of the genome
public $synapses; // Synapses between neurons
/* CONSTRUCTOR
*
* -- RANDOM CREATION --
* @layers<int> Number of layers to manage
* @neurons<int> Number of neurons per layer
*
* -- CLONING --
* @base<Genom> Genome to clone to
*
* -- CROSS-OVER CREATION --
* @father<Genome> First parent
* @mother<Genome> Second parent
*
*
*/
public function __construct(){
/* (1) Get arguments */
$argv = func_get_args();
$argc = count($argv);
/* (2) If CrossoverCreation */
if( $argc > 1 && $argv[0] instanceof Genome && $argv[1] instanceof Genome )
$this->construct_crossover($argv[0], $argv[1]);
/* (3) If RandomCreation */
else if( $argc > 1 && abs(intval($argv[0])) === $argv[0] && abs(intval($argv[1])) === $argv[1] )
$this->construct_new($argv[0], $argv[1]);
/* (4) If InheritanceCreation (clone) */
else if( $argc > 0 && $argv[0] instanceof Genome )
$this->construct_inheritance($argv[0]);
/* (5) If no match */
else
throw new \Error('Invalid Genome constructor\'s arguments.');
}
/* BUILDS A Genome RANDOMLY WITH PARAMETERS
*
* @layers<int> The number of hidden layers to manage
* @neurons<int> The number neurons per layer
*
* @return created<Boolean> If Genome has been successfully created
*
*/
private function construct_new($layers=-1, $neurons=-1){
/* (1) Checks parameters */
if( abs(intval($layers)) !== $layers || abs(intval($neurons)) !== $neurons )
return false;
// set layers
$this->layers = $layers;
/* (2) Creating random neurons */
$this->neurons = [];
for( $i = 0, $l = $neurons*$layers ; $i < $l ; $i++ )
$this->neurons[$i] = rand(self::MIN, self::MAX) / self::MAX;
/* (3) Creating random synapses */
$this->synapses = [];
for( $i = 0, $l = pow($neurons, $layers) ; $i < $l ; $i++ )
$this->synapses[$i] = rand(self::MIN, self::MAX) / self::MAX;
// Success status
return true;
}
/* BUILDS A Genome BASED ON A PARENT
*
* @parent<Genome> Parent genome to clone into children
*
* @return created<Boolean> If cloned Genome has been created successfully
*
*/
private function construct_inheritance($parent=null){
/* (1) Checks parent type */
if( !($parent instanceof Genome) )
return false;
/* (2) Clones into this Genome */
$this->layers = $parent->layers;
$this->neurons = array_slice($parent->neurons, 0);
$this->synapses = array_slice($parent->synapses, 0);
// Success state
return true;
}
/* BUILDS A Genome BASED ON TWO PARENTS
*
* @father<Genome> First parent ($father)
* @mother<Genome> Second parent ($mother)
*
* @return created<Boolean> If crossed-over Genome has been created successfully
*
*/
private function construct_crossover($father=null, $mother=null){
/* (1) Checks parent type */
if( !($father instanceof Genome) || !($mother instanceof Genome) )
return false;
/* (2) Checks number of layers+neurons (same species) */
if( $father->layers !== $mother->layers || count($father->neurons) !== count($mother->neurons) )
return false;
/* (3) Set layer count */
$this->layers = $father->layers;
/* (4) Do random crossover for neurons */
$this->neurons = [];
for( $i = 0, $l = count($father->neurons) ; $i < $l ; $i++ )
if( !!rand(0,1) ) $this->neurons[$i] = $father->neurons[$i];
else $this->neurons[$i] = $mother->neurons[$i];
/* (5) Do random crossover for synapses */
$this->synapses = [];
for( $i = 0, $l = pow(count($this->neurons)/$this->layers, $this->layers) ; $i < $l ; $i++ )
if( !!rand(0,1) ) $this->synapses[$i] = $father->synapses[$i];
else $this->synapses[$i] = $mother->synapses[$i];
// Success state
return true;
}
/* APPLIES A MUTATION ON THE Genome WITH A SPECIFIC @threshold
*
* @threshold<double> Mutation threshold
*
*/
public function mutation($threshold=0.5){
/* (1) Checks @threshold argument */
if( floatval($threshold) !== $threshold || $threshold < 0 || $threshold > 1 )
throw new \Error('Invalid threshold for Genome mutation.');
/* (2) Calculates how many neurons/synapses to mutate */
$neuronsMutations = round( (count($this->neurons) - 1) * $threshold );
$synapsesMutations = round( (count($this->synapses) - 1) * $threshold );
/* (3) Choose random neurons' indexes */
$iNeurons = [];
while( count($iNeurons) < $neuronsMutations ){
$r = rand(0, count($this->neurons)-1);
if( !in_array($r, $iNeurons) )
$iNeurons[] = $r;
}
/* (4) Choose random synapses' indexes */
$iSynapses = [];
while( count($iSynapses) < $synapsesMutations ){
$r = rand(0, count($this->synapses)-1);
if( !in_array($r, $iSynapses) )
$iSynapses[] = $r;
}
/* (5) Update chosen neurons */
for( $i = 0, $l = count($iNeurons) ; $i < $l ; $i++ )
$this->neurons[$iNeurons[$i]] = rand(self::MIN, self::MAX) / self::MAX;
/* (6) Update chosen synapses */
for( $i = 0, $l = count($iSynapses) ; $i < $l ; $i++ )
$this->synapses[$iSynapses[$i]] = rand(self::MIN, self::MAX) / self::MAX;
}
}
/************************************************
**** USE CASE ****
************************************************/
$use_case = false;
if( $use_case ){
/* (1) Basic Creation */
$a = new Genome(2, 3); // 2 layers of 3 neurons each -> randomly filled
/* (2) Inheritance */
$b = new Genome($a); // Clone of @a
/* (3) Section Title */
$b->mutation(0.3); // @b has now mutated with a threshold of 30%
/* (4) Cross-over (father+mother) */
$c = new Genome($a, $b); // @c is a randomly-done mix of @a and @b
}
?>