Added ADALINE training

app/Models/NetworksTraining/ADALINEPerceptronTraining.php

@@ -0,0 +1,105 @@
+<?php
+
+namespace App\Models\NetworksTraining;
+
+use App\Events\PerceptronTrainingEnded;
+use App\Models\ActivationsFunctions;
+use App\Models\Perceptrons\GradientDescentPerceptron;
+use App\Models\Perceptrons\Perceptron;
+use App\Services\DatasetReader\IDataSetReader;
+use App\Services\IterationEventBuffer\IPerceptronIterationEventBuffer;
+use App\Services\SynapticWeightsProvider\ISynapticWeightsProvider;
+
+class ADALINEPerceptronTraining extends NetworkTraining
+{
+    private Perceptron $perceptron;
+
+    public ActivationsFunctions $activationFunction = ActivationsFunctions::LINEAR;
+
+    private float $epochError;
+
+    public function __construct(
+        IDataSetReader $datasetReader,
+        protected float $learningRate,
+        int $maxEpochs,
+        protected ISynapticWeightsProvider $synapticWeightsProvider,
+        IPerceptronIterationEventBuffer $iterationEventBuffer,
+        string $sessionId,
+        string $trainingId,
+        private float $minError,
+    ) {
+        parent::__construct($datasetReader, $maxEpochs, $iterationEventBuffer, $sessionId, $trainingId);
+        $this->perceptron = new GradientDescentPerceptron($synapticWeightsProvider->generate($datasetReader->getInputSize()));
+    }
+
+    public function start(): void
+    {
+        $this->epoch = 0;
+        do {
+            $this->epochError = 0;
+            $this->epoch++;
+
+            $inputsForCurrentEpoch = [];
+
+            while ($nextRow = $this->datasetReader->getNextLine()) {
+                $inputsForCurrentEpoch[] = $nextRow;
+                $inputs = array_slice($nextRow, 0, -1);
+                $correctOutput = (float) end($nextRow);
+
+                $iterationError = $this->iterationFunction($inputs, $correctOutput);
+
+                // Synaptic weights correction after each example
+                $synaptic_weights = $this->perceptron->getSynapticWeights();
+                $inputs_with_bias = array_merge([1], $inputs); // Add bias input
+                $new_weights = array_map(
+                    fn($weight, $weightIndex) => $weight + ($this->learningRate * $iterationError * $inputs_with_bias[$weightIndex]),
+                    $synaptic_weights,
+                    array_keys($synaptic_weights)
+                );
+                $this->perceptron->setSynapticWeights($new_weights);
+
+                // Broadcast the training iteration event
+                $this->addIterationToBuffer($iterationError, [[$this->perceptron->getSynapticWeights()]]);
+            }
+
+            // Calculte the average error for the epoch with the last synaptic weights
+            foreach ($inputsForCurrentEpoch as $inputsWithLabel) {
+                $inputs = array_slice($inputsWithLabel, 0, -1);
+                $correctOutput = (float) end($inputsWithLabel);
+                $output = $this->perceptron->test($inputs);
+                $iterationError = $correctOutput - $output;
+                $this->epochError += ($iterationError ** 2) / 2; // Squared error for the example
+            }
+            $this->epochError /= $this->datasetReader->getEpochExamplesCount(); // Average error for the epoch
+
+            $this->datasetReader->reset(); // Reset the dataset for the next iteration
+        } while ($this->epoch < $this->maxEpochs && !$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 $error;
+    }
+
+    public function getSynapticWeights(): array
+    {
+        return [[$this->perceptron->getSynapticWeights()]];
+    }
+}