From 58f9fd81158b8bfd22a6030eb2244ae500d87f65 Mon Sep 17 00:00:00 2001
From: silvana884 <sil.gosewehr@gmail.com>
Date: Mon, 24 Nov 2025 21:34:02 +0100
Subject: [PATCH] Testen moeglich, 6 Failures

---
 .idea/workspace.xml  |  2 +-
 matrix.h             |  8 ++++++++
 neuralNetwork.c      |  2 +-
 neuralNetwork.h      |  2 ++
 neuralNetworkTests.c | 35 +++++++++++++++++++++++++++--------
 5 files changed, 39 insertions(+), 10 deletions(-)

diff --git a/.idea/workspace.xml b/.idea/workspace.xml
index 4b2931a..5533b38 100644
--- a/.idea/workspace.xml
+++ b/.idea/workspace.xml
@@ -20,7 +20,7 @@
     </configurations>
   </component>
   <component name="ChangeListManager">
-    <list default="true" id="93ee913b-6a02-4be9-9f16-9e5959cb8dc8" name="Changes" comment="" />
+    <list default="true" id="df1feb62-39b8-4aeb-a745-19618bf4ab77" name="Changes" comment="" />
     <option name="SHOW_DIALOG" value="false" />
     <option name="HIGHLIGHT_CONFLICTS" value="true" />
     <option name="HIGHLIGHT_NON_ACTIVE_CHANGELIST" value="false" />
diff --git a/matrix.h b/matrix.h
index cc640d1..dfe05c9 100644
--- a/matrix.h
+++ b/matrix.h
@@ -6,6 +6,11 @@
 typedef float MatrixType;
 
 // TODO Matrixtyp definieren
+typedef struct{
+    unsigned int rows;
+    unsigned int cols;
+    MatrixType *buffer; //Data wird in einem eindimensionalen Array gespeichert (Spalten und Reihen liegen ja im Speicher hintereinannder)
+} Matrix;
 
 
 Matrix createMatrix(unsigned int rows, unsigned int cols);
@@ -13,7 +18,10 @@ void clearMatrix(Matrix *matrix);
 void setMatrixAt(MatrixType value, Matrix matrix, unsigned int rowIdx, unsigned int colIdx);
 MatrixType getMatrixAt(const Matrix matrix, unsigned int rowIdx, unsigned int colIdx);
 Matrix add(const Matrix matrix1, const Matrix matrix2);
+Matrix broadcasting(const Matrix matrix1, const Matrix matrix2);
 Matrix multiply(const Matrix matrix1, const Matrix matrix2);
+int rows(const Matrix matrix);
+int cols(const Matrix matrix);
 
 
 #endif
diff --git a/neuralNetwork.c b/neuralNetwork.c
index bd8f164..5bec5b4 100644
--- a/neuralNetwork.c
+++ b/neuralNetwork.c
@@ -170,7 +170,7 @@ NeuralNetwork loadModel(const char *path)
 
 static Matrix imageBatchToMatrixOfImageVectors(const GrayScaleImage images[], unsigned int count)
 {
-    Matrix matrix = {NULL, 0, 0};
+    Matrix matrix = {0,0, NULL};
 
     if(count > 0 && images != NULL)
     {
diff --git a/neuralNetwork.h b/neuralNetwork.h
index 7f06607..78a6102 100644
--- a/neuralNetwork.h
+++ b/neuralNetwork.h
@@ -1,6 +1,8 @@
 #ifndef NEURALNETWORK_H
 #define NEURALNETWORK_H
 
+#define FILE_HEADER_STRING "__info2_neural_network_file_format__"
+
 #include "imageInput.h"
 #include "matrix.h"
 
diff --git a/neuralNetworkTests.c b/neuralNetworkTests.c
index 6489a55..9be45e2 100644
--- a/neuralNetworkTests.c
+++ b/neuralNetworkTests.c
@@ -4,28 +4,47 @@
 #include <math.h>
 #include "unity.h"
 #include "neuralNetwork.h"
-#include "neuralNetwork.c"
 //Dateischichten sind in neuralNetwork.h definiert
 // Dateiname: __info2_neural_network_file_format__
 
 static void prepareNeuralNetworkFile(const char *path, const NeuralNetwork nn)
 {
-    // Datei oeffnen
     FILE *file = fopen(path, "wb");
+    if (!file) return;
 
+    // Header schreiben
+    fwrite(FILE_HEADER_STRING, 1, strlen(FILE_HEADER_STRING), file);
 
-    if (file == NULL) 
-        return 1;
+    // Anzahl Layer schreiben
+    uint32_t nLayers = nn.numberOfLayers;
+    fwrite(&nLayers, sizeof(uint32_t), 1, file);
 
-    // header schreiben
-    fwrite(FILE_HEADER_STRING, sizeof(char), strlen(FILE_HEADER_STRING), file);
+    for (uint32_t i = 0; i < nLayers; i++) {
+        Layer layer = nn.layers[i];
 
-    
+        // Weights-Dimensionen
+        uint32_t rW = layer.weights.rows;
+        uint32_t cW = layer.weights.cols;
+        fwrite(&rW, sizeof(uint32_t), 1, file);
+        fwrite(&cW, sizeof(uint32_t), 1, file);
+
+        // Weights-Werte
+        fwrite(layer.weights.buffer, sizeof(MatrixType), rW * cW, file);
+
+        // Bias-Dimensionen
+        uint32_t rB = layer.biases.rows;
+        uint32_t cB = layer.biases.cols;
+        fwrite(&rB, sizeof(uint32_t), 1, file);
+        fwrite(&cB, sizeof(uint32_t), 1, file);
+
+        // Bias-Werte
+        fwrite(layer.biases.buffer, sizeof(MatrixType), rB * cB, file);
+    }
 
-    // Datei wieder schließen!
     fclose(file);
 }
 
+
 void test_loadModelReturnsCorrectNumberOfLayers(void)
 {
     const char *path = "some__nn_test_file.info2";