<?php

namespace App\Models;

use App\Events\PerceptronTrainingEnded;
use App\Services\DataSetReader;
use App\Services\ISynapticWeightsProvider;
use App\Services\PerceptronIterationEventBuffer;

class SimpleBinaryPerceptronTraining extends NetworkTraining
{
    private Perceptron $perceptron;
    private int $iterationErrorCounter = 0;

    public ActivationsFunctions $activationFunction = ActivationsFunctions::STEP;

    public const MIN_ERROR = 0;

    public function __construct(
        DataSetReader $datasetReader,
        protected float $learningRate,
        int $maxIterations,
        protected ISynapticWeightsProvider $synapticWeightsProvider,
        PerceptronIterationEventBuffer $iterationEventBuffer,
        string $sessionId,
        string $trainingId,
    ) {
        parent::__construct($datasetReader, $maxIterations, $iterationEventBuffer, $sessionId, $trainingId);
        $this->perceptron = new SimpleBinaryPerceptron($synapticWeightsProvider->generate($datasetReader->getInputSize()));
    }

    public function start(): void
    {
        $this->iteration = 0;
        $error = 0;
        do {
            $this->iterationErrorCounter = 0;
            $this->iteration++;

            while ($nextRow = $this->datasetReader->getRandomLine()) {
                $inputs = array_slice($nextRow, 0, -1);
                $correctOutput = (float) end($nextRow);
                $correctOutput = $correctOutput > 0 ? 1 : 0; // Modify labels for non binary datasets

                $error = $this->iterationFunction($inputs, $correctOutput);

                // Broadcast the training iteration event
                $this->addIterationToBuffer($error, [[$this->perceptron->getSynapticWeights()]]);
            }
            $this->datasetReader->reset(); // Reset the dataset for the next iteration
        } while ($this->iteration < $this->maxIterations && !$this->stopCondition());

        $this->iterationEventBuffer->flush(); // Ensure all iterations are sent to the frontend

        $this->checkPassedMaxIterations(null);
    }

    protected function stopCondition(): bool
    {
        $condition = $this->iterationErrorCounter == 0;
        if ($condition === true) {
            event(new PerceptronTrainingEnded('Le perceptron ne commet plus d\'erreurs sur aucune des données', $this->sessionId, $this->trainingId));
        }
        return $this->iterationErrorCounter == 0;
    }

    private function iterationFunction(array $inputs, int $correctOutput)
    {
        $output = $this->perceptron->test($inputs);

        $error = $correctOutput - $output;
        if (abs($error) > $this::MIN_ERROR) {
            $this->iterationErrorCounter++;
        }

        if ($error !== 0) { // Update synaptic weights if needed
            $synaptic_weights = $this->perceptron->getSynapticWeights();
            $inputs_with_bias = array_merge([1], $inputs); // Add bias input
            $new_weights = array_map(fn($weight, $input) => $weight + $this->learningRate * $error * $input, $synaptic_weights, $inputs_with_bias);
            $this->perceptron->setSynapticWeights($new_weights);
        }
        return $error;
    }
}