prepareNeuralNetworkFile geschrieben und Tests laufen gelassen

neuralNetworkTests.c

@@ -5,10 +5,47 @@
 #include "unity.h"
 #include "neuralNetwork.h"
 
+#define FILE_HEADER_STRING "__info2_neural_network_file_format__"
 
 static void prepareNeuralNetworkFile(const char *path, const NeuralNetwork nn)
 {
-    // TODO
+    FILE *file = fopen(path, "wb");
+    if (file == NULL) {
+        return;
+    }
+    
+    // Magic String (File Header) schreiben
+    size_t headerLen = strlen(FILE_HEADER_STRING);
+    fwrite(FILE_HEADER_STRING, sizeof(char), headerLen, file);
+    
+    // Erste inputDimension schreiben (vom ersten Layer)
+    if (nn.numberOfLayers > 0) {
+        unsigned int inputDim = nn.layers[0].weights.cols;
+        fwrite(&inputDim, sizeof(unsigned int), 1, file);
+    }
+    
+    // Für jeden Layer: outputDimension, weights und biases schreiben
+    for (unsigned int i = 0; i < nn.numberOfLayers; i++) {
+        Layer layer = nn.layers[i];
+        
+        // Output-Dimension dieses Layers schreiben
+        unsigned int outputDim = layer.weights.rows;
+        fwrite(&outputDim, sizeof(unsigned int), 1, file);
+        
+        // Weights schreiben (alle Daten)
+        unsigned int weightSize = layer.weights.rows * layer.weights.cols;
+        fwrite(layer.weights.buffer, sizeof(MatrixType), weightSize, file);
+        
+        // Biases schreiben (alle Daten)
+        unsigned int biasSize = layer.biases.rows * layer.biases.cols;
+        fwrite(layer.biases.buffer, sizeof(MatrixType), biasSize, file);
+    }
+    
+    // Endmarkierung schreiben (0 als nächste outputDimension)
+    unsigned int endMarker = 0;
+    fwrite(&endMarker, sizeof(unsigned int), 1, file);
+    
+    fclose(file);
 }
 
 void test_loadModelReturnsCorrectNumberOfLayers(void)