test abstraction from LayeredNetwork

src/Phpml/NeuralNetwork/Network.php

@@ -4,9 +4,8 @@ declare (strict_types = 1);
 
 namespace Phpml\NeuralNetwork;
 
-interface Network extends Node
+interface Network
 {
-
     /**
      * @param mixed $input
      */
@@ -15,6 +14,15 @@ interface Network extends Node
     /**
      * @return array
      */
-    public function getLayers(): array;
+    public function getOutput(): array;
 
+    /**
+     * @param Layer $layer
+     */
+    public function addLayer(Layer $layer);
+
+    /**
+     * @return Layer[]
+     */
+    public function getLayers(): array;
 }

src/Phpml/NeuralNetwork/Network/LayeredNetwork.php

@@ -4,25 +4,51 @@ declare (strict_types = 1);
 
 namespace Phpml\NeuralNetwork\Network;
 
+use Phpml\NeuralNetwork\Layer;
 use Phpml\NeuralNetwork\Network;
 
 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 Layer
+     */
+    public function getOutputLayer(): Layer
+    {
+        return $this->layers[count($this->layers) - 1];
+    }
 
     /**
      * @return array
      */
-    public function getLayers(): array
-    {
-
-    }
-
-    /**
-     * @return float
-     */
-    public function getOutput(): float
+    public function getOutput(): array
     {
+        $result = [];
+        foreach ($this->getOutputLayer()->getNodes() as $neuron) {
+            $result[] = $neuron->getOutput();
+        }
 
+        return $result;
     }
 
     /**
@@ -30,7 +56,10 @@ abstract class LayeredNetwork implements Network
      */
     public function setInput($input)
     {
+        $firstLayer = $this->layers[0];
 
+        foreach ($firstLayer->getNodes() as $key => $neuron) {
+            $neuron->setInput($input[$key]);
+        }
     }
-
 }

src/Phpml/NeuralNetwork/Network/MultilayerPerceptron.php

@@ -6,5 +6,4 @@ namespace Phpml\NeuralNetwork\Network;
 
 class MultilayerPerceptron extends LayeredNetwork
 {
-
 }

src/Phpml/NeuralNetwork/Training.php

@@ -10,7 +10,7 @@ interface Training
      * @param array $samples
      * @param array $targets
      * @param float $desiredError
-     * @param int $maxIterations
+     * @param int   $maxIterations
      */
     public function train(array $samples, array $targets, float $desiredError = 0.001, int $maxIterations = 10000);
 }

src/Phpml/NeuralNetwork/Training/Backpropagation.php

@@ -8,16 +8,13 @@ use Phpml\NeuralNetwork\Training;
 
 class Backpropagation implements Training
 {
-
     /**
      * @param array $samples
      * @param array $targets
      * @param float $desiredError
-     * @param int $maxIterations
+     * @param int   $maxIterations
      */
     public function train(array $samples, array $targets, float $desiredError = 0.001, int $maxIterations = 10000)
     {
-
     }
-
 }