Gradient descent training + Added all dataset + graphs improvements

app/Models/ActivationsFunctions.php

@@ -5,6 +5,7 @@ namespace App\Models;
 enum ActivationsFunctions: string
 {
     case STEP = 'step';
+    case LINEAR = 'linear';
     case SIGMOID = 'sigmoid';
     case RELU = 'relu';
 }

app/Models/GradientDescentPerceptron.php

@@ -2,7 +2,7 @@
 
 namespace App\Models;
 
-class SimplePerceptron extends Perceptron {
+class GradientDescentPerceptron extends Perceptron {
 
     public function __construct(
         array $synaptic_weights,
@@ -10,9 +10,9 @@ class SimplePerceptron extends Perceptron {
         parent::__construct($synaptic_weights);
     }
 
-    public function activationFunction(float $weighted_sum): int
+    public function activationFunction(float $weighted_sum): float
     {
-        return $weighted_sum >= 0 ? 1 : 0;
+        return $weighted_sum;
     }
 
 }

app/Models/GradientDescentPerceptronTraining.php

@@ -0,0 +1,91 @@
+<?php
+
+namespace App\Models;
+
+use App\Events\PerceptronTrainingEnded;
+use App\Services\DataSetReader;
+use App\Services\ISynapticWeightsProvider;
+use App\Services\PerceptronIterationEventBuffer;
+
+class GradientDescentPerceptronTraining extends NetworkTraining
+{
+    private Perceptron $perceptron;
+
+    public ActivationsFunctions $activationFunction = ActivationsFunctions::LINEAR;
+
+    private float $epochError;
+
+    public function __construct(
+        DataSetReader $datasetReader,
+        protected float $learningRate,
+        int $maxIterations,
+        protected ISynapticWeightsProvider $synapticWeightsProvider,
+        PerceptronIterationEventBuffer $iterationEventBuffer,
+        string $sessionId,
+        string $trainingId,
+        private float $minError,
+    ) {
+        parent::__construct($datasetReader, $maxIterations, $iterationEventBuffer, $sessionId, $trainingId);
+        $this->perceptron = new GradientDescentPerceptron($synapticWeightsProvider->generate($datasetReader->getInputSize()));
+    }
+
+    public function start(): void
+    {
+        $this->iteration = 0;
+        do {
+            $this->epochError = 0;
+            $iterationErrorPerWeight = [];
+            $this->iteration++;
+
+            while ($nextRow = $this->datasetReader->getRandomLine()) {
+                $inputs = array_slice($nextRow, 0, -1);
+                $correctOutput = (float) end($nextRow);
+
+                $iterationError = $this->iterationFunction($inputs, $correctOutput);
+                $this->epochError += (1 / 2) * (abs($iterationError) ** 2); // TDDO REMOVEME abs()
+
+                // Store the iteration error for each weight
+                $inputs_with_bias = array_merge([1], $inputs); // Add bias input
+                foreach ($inputs_with_bias as $index => $input) {
+                    $iterationErrorPerWeight[$index][] = $iterationError * $input;
+                }
+
+                // Broadcast the training iteration event
+                $this->addIterationToBuffer($iterationError, [[$this->perceptron->getSynapticWeights()]]);
+            }
+
+            // Synaptic weights correction after each epoch
+            $synaptic_weights = $this->perceptron->getSynapticWeights();
+            $new_weights = array_map(
+                fn($weight, $weightIndex) => $weight + $this->learningRate * array_sum($iterationErrorPerWeight[$weightIndex]),
+                $synaptic_weights,
+                array_keys($synaptic_weights)
+            );
+            $this->perceptron->setSynapticWeights($new_weights);
+
+            $this->datasetReader->reset(); // Reset the dataset for the next iteration
+        } while ($this->iteration < $this->maxIterations && !$this->stopCondition());
+
+        $this->iterationEventBuffer->flush(); // Ensure all iterations are sent to the frontend
+
+        $this->checkPassedMaxIterations($this->epochError);
+    }
+
+    protected function stopCondition(): bool
+    {
+        $condition = $this->epochError <= $this->minError && $this->perceptron->getSynapticWeights() !== [[0.0, 0.0, 0.0]];
+        if ($condition === true) {
+            event(new PerceptronTrainingEnded('Le perceptron à atteint l\'erreur minimale', $this->sessionId, $this->trainingId));
+        }
+        return $condition;
+    }
+
+    private function iterationFunction(array $inputs, int $correctOutput)
+    {
+        $output = $this->perceptron->test($inputs);
+
+        $error = $correctOutput - $output;
+
+        return $error;
+    }
+}

app/Models/Network.php

@@ -0,0 +1,8 @@
+<?php
+
+namespace App\Models;
+
+abstract class Network
+{
+
+}

app/Models/NetworkTraining.php

@@ -28,9 +28,14 @@ abstract class NetworkTraining
     abstract public function start() : void;
     abstract protected function stopCondition(): bool;
 
-    protected function checkPassedMaxIterations() {
+    protected function checkPassedMaxIterations(?float $finalError) {
         if ($this->iteration >= $this->maxIterations) {
-            event(new PerceptronTrainingEnded('Le nombre maximal d\'itérations a été atteint', $this->sessionId, $this->trainingId));
+            $message = 'Le nombre maximal d\'itérations a été atteint';
+            if ($finalError) {
+                $message .= " avec une erreur finale de $finalError";
+            }
+
+            event(new PerceptronTrainingEnded($message, $this->sessionId, $this->trainingId));
         }
     }
 

app/Models/Perceptron.php

@@ -12,7 +12,7 @@ abstract class Perceptron extends Model
         $this->synaptic_weights = $synaptic_weights;
     }
 
-    public function test(array $inputs): int
+    public function test(array $inputs): float
     {
         $inputs = array_merge([1], $inputs); // Add bias input
 
@@ -24,7 +24,7 @@ abstract class Perceptron extends Model
         return $this->activationFunction($weighted_sum);
     }
 
-    abstract public function activationFunction(float $weighted_sum): int;
+    abstract public function activationFunction(float $weighted_sum): float;
 
     public function getSynapticWeights(): array
     {

app/Models/SimpleBinaryPerceptron.php

@@ -0,0 +1,18 @@
+<?php
+
+namespace App\Models;
+
+class SimpleBinaryPerceptron extends Perceptron {
+
+    public function __construct(
+        array $synaptic_weights,
+    ) {
+        parent::__construct($synaptic_weights);
+    }
+
+    public function activationFunction(float $weighted_sum): float
+    {
+        return $weighted_sum >= 0.0 ? 1.0 : 0.0;
+    }
+
+}

app/Models/SimpleBinaryPerceptronTraining.php

@@ -6,9 +6,8 @@ use App\Events\PerceptronTrainingEnded;
 use App\Services\DataSetReader;
 use App\Services\ISynapticWeightsProvider;
 use App\Services\PerceptronIterationEventBuffer;
-use Illuminate\Support\Facades\Log;
 
-class SimplePerceptronTraining extends NetworkTraining
+class SimpleBinaryPerceptronTraining extends NetworkTraining
 {
     private Perceptron $perceptron;
     private int $iterationErrorCounter = 0;
@@ -27,7 +26,7 @@ class SimplePerceptronTraining extends NetworkTraining
         string $trainingId,
     ) {
         parent::__construct($datasetReader, $maxIterations, $iterationEventBuffer, $sessionId, $trainingId);
-        $this->perceptron = new SimplePerceptron($synapticWeightsProvider->generate(2));
+        $this->perceptron = new SimpleBinaryPerceptron($synapticWeightsProvider->generate($datasetReader->getInputSize()));
     }
 
     public function start(): void
@@ -40,13 +39,11 @@ class SimplePerceptronTraining extends NetworkTraining
 
             while ($nextRow = $this->datasetReader->getRandomLine()) {
                 $inputs = array_slice($nextRow, 0, -1);
-                $correctOutput = end($nextRow);
+                $correctOutput = (float) end($nextRow);
                 $correctOutput = $correctOutput > 0 ? 1 : 0; // Modify labels for non binary datasets
 
                 $error = $this->iterationFunction($inputs, $correctOutput);
 
-                $error = abs($error); // Use absolute error
-
                 // Broadcast the training iteration event
                 $this->addIterationToBuffer($error, [[$this->perceptron->getSynapticWeights()]]);
             }
@@ -55,7 +52,7 @@ class SimplePerceptronTraining extends NetworkTraining
 
         $this->iterationEventBuffer->flush(); // Ensure all iterations are sent to the frontend
 
-        $this->checkPassedMaxIterations();
+        $this->checkPassedMaxIterations(null);
     }
 
     protected function stopCondition(): bool