Various fixess and xor

app/Events/PerceptronTrainingIteration.php

@@ -6,6 +6,7 @@ use Illuminate\Broadcasting\Channel;
 use Illuminate\Broadcasting\InteractsWithSockets;
 use Illuminate\Contracts\Broadcasting\ShouldBroadcast;
 use Illuminate\Foundation\Events\Dispatchable;
+use Illuminate\Support\Arr;
 use Illuminate\Queue\SerializesModels;
 
 class PerceptronTrainingIteration implements ShouldBroadcast
@@ -38,9 +39,15 @@ class PerceptronTrainingIteration implements ShouldBroadcast
 
     public function broadcastWith(): array
     {
+        $weights = collect($this->iterations)
+            ->pluck('weights')
+            ->first(fn (array $weights): bool => $weights !== []);
+        $shouldBroadcastAllWeights = $weights !== null
+            && count(Arr::flatten($weights)) <= config('perceptron.max_displayed_weights');
+
         $lastIterationIndex = count($this->iterations) - 1;
         $iterations = array_map(
-            fn (array $iteration, int $index): array => $index === $lastIterationIndex
+            fn (array $iteration, int $index): array => $shouldBroadcastAllWeights || $index === $lastIterationIndex
                 ? $iteration
                 : [...$iteration, 'weights' => []],
             $this->iterations,

app/Http/Controllers/PerceptronController.php

@@ -47,6 +47,7 @@ class PerceptronController extends Controller
                 break;
             case 'multilayer':
                 $learningRate = 0.8;
+                $maxIterations = 2000;
                 break;
         }
 
@@ -109,6 +110,17 @@ class PerceptronController extends Controller
                                 break;
                         }
                         break;
+                    case 'logic_xor':
+                        switch ($perceptronType) {
+                            case 'multilayer':
+                                $dataset['defaultLearningRate'] = 0.3;
+                                $dataset['defaultMinError'] = 0.001;
+                                $dataset['defaultMaxIterations'] = 500;
+                                $dataset['defaultHiddenLayers'] = 1;
+                                $dataset['defaultHiddenLayersNeurons'] = 2;
+                                break;
+                        }
+                        break;
                     case 'table_2_9':
                         switch ($perceptronType) {
                             case 'simple':
@@ -132,6 +144,15 @@ class PerceptronController extends Controller
                                 break;
                         }
                         break;
+                    case 'table_4_17':
+                        switch ($perceptronType) {
+                            case 'multilayer':
+                                $dataset['defaultLearningRate'] = 0.5;
+                                $dataset['defaultMinError'] = 0.08;
+                                $dataset['defaultMaxIterations'] = 400;
+                                break;
+                        }
+                        break;
                 }
                 $datasets[] = $dataset;
             }

config/perceptron.php

@@ -20,9 +20,10 @@ return [
     'broadcast_iteration_size' => 75,
 
     /**
-     * Hide the weight columns in the iteration table above this count.
+     * Maximum number of weights for which all iteration weights are broadcast
+     * and displayed in the iteration table.
      */
-    'max_displayed_weights' => 25,
+    'max_displayed_weights' => 5,
 
     'run_inputs_validation' => [
         'hidden_layers' => 'required|integer|min:1|max:5',

resources/js/components/PerceptronSetup.vue

@@ -66,6 +66,15 @@ watch(selectedDatasetCopy, (newvalue) => {
     if (selectedDatasetCopy && selectedDatasetCopy.defaultMaxIterations !== undefined) {
         maxIterations.value = selectedDatasetCopy.defaultMaxIterations;
     }
+    // HiddenLayers
+    hiddenLayers.value = props.hiddenLayers;
+    if (selectedDatasetCopy && selectedDatasetCopy.defaultHiddenLayers !== undefined) {
+        hiddenLayers.value = selectedDatasetCopy.defaultHiddenLayers;
+    }
+    hiddenLayersNeurons.value = props.hiddenLayersNeurons;
+    if (selectedDatasetCopy && selectedDatasetCopy.defaultHiddenLayersNeurons !== undefined) {
+        hiddenLayersNeurons.value = selectedDatasetCopy.defaultHiddenLayersNeurons;
+    }
 })
 
 const trainingId  = ref<string>('');

resources/js/pages/PerceptronViewer.vue

@@ -140,6 +140,10 @@ function perceptronTrainingEnded(data: any) {
 }
 
 const activationFunction = ref<string>('');
+const isRegression = computed(
+    () => props.type === 'multilayer' && activationFunction.value === 'linear',
+);
+
 function perceptroninitialization(data: any) {
     console.log('Perceptron training initialized:', data);
     if (data.trainingId !== trainingId.value) {
@@ -216,7 +220,7 @@ function resetTraining() {
                     <PerceptronDecisionGraph
                         :cleanedDataset="cleanedDataset"
                         :iterations="iterations"
-                        :is-regression="activationFunction === 'linear'"
+                        :is-regression="isRegression"
                         :activation-function="
                             getActivationFunction(activationFunction)
                         "
@@ -225,7 +229,7 @@ function resetTraining() {
                 <div>
                     <PerceptronIterationsErrorsGraph
                         :iterations="iterations"
-                        :is-regression="activationFunction === 'linear'"
+                        :is-regression="isRegression"
                         v-if="iterations.length > 0"
                     />
                 </div>

resources/js/types/perceptron.ts

@@ -11,6 +11,8 @@ export type Dataset = {
     defaultLearningRate?: number;
     defaultMinError?: number;
     defaultMaxIterations?: number;
+    defaultHiddenLayers?: number;
+    defaultHiddenLayersNeurons?: number;
 };
 
 export type DatasetPoint = {

tests/Unit/Events/PerceptronTrainingIterationTest.php

@@ -0,0 +1,44 @@
+<?php
+
+namespace Tests\Unit\Events;
+
+use App\Events\PerceptronTrainingIteration;
+use Tests\TestCase;
+
+class PerceptronTrainingIterationTest extends TestCase
+{
+    public function test_small_networks_keep_weights_for_every_iteration(): void
+    {
+        $event = new PerceptronTrainingIteration(
+            iterations: [
+                ['epoch' => 1, 'exampleIndex' => 0, 'error' => 1, 'weights' => [[[1, 2]]]],
+                ['epoch' => 1, 'exampleIndex' => 1, 'error' => 0, 'weights' => [[[3, 4]]]],
+            ],
+            sessionId: 'session',
+            trainingId: 'training',
+        );
+
+        $iterations = $event->broadcastWith()['iterations'];
+
+        $this->assertSame([[[1, 2]]], $iterations[0]['weights']);
+        $this->assertSame([[[3, 4]]], $iterations[1]['weights']);
+    }
+
+    public function test_large_networks_only_keep_the_last_iteration_weights(): void
+    {
+        $largeWeights = [[array_fill(0, config('perceptron.max_displayed_weights') + 1, 0)]];
+        $event = new PerceptronTrainingIteration(
+            iterations: [
+                ['epoch' => 1, 'exampleIndex' => 0, 'error' => 1, 'weights' => $largeWeights],
+                ['epoch' => 1, 'exampleIndex' => 1, 'error' => 0, 'weights' => $largeWeights],
+            ],
+            sessionId: 'session',
+            trainingId: 'training',
+        );
+
+        $iterations = $event->broadcastWith()['iterations'];
+
+        $this->assertSame([], $iterations[0]['weights']);
+        $this->assertSame($largeWeights, $iterations[1]['weights']);
+    }
+}