Merge branch 'branchflorian'

matrix.c

@@ -6,30 +6,122 @@
 
 Matrix createMatrix(unsigned int rows, unsigned int cols)
 {
+    Matrix matrix;
 
+    matrix.rows = rows;
+    matrix.cols = cols;
+    matrix.buffer = malloc(rows * cols * sizeof(float));
+
+    if(matrix.buffer == NULL)
+    {
+        printf("Fehler bei der Speicherreservierung! Keine Matrix erstellt!");
+        matrix.rows = 0;
+        matrix.cols = 0;
+    }
+
+    return matrix;
 }
 
 void clearMatrix(Matrix *matrix)
 {
+    free(matrix.buffer);
 
+    matrix->buffer = NULL;
+    matrix->rows = 0;
+    matrix->cols = 0;
 }
 
-void setMatrixAt(MatrixType value, Matrix matrix, unsigned int rowIdx, unsigned int colIdx)
+void setMatrixAt(MatrixType value, Matrix *matrix, unsigned int rowIdx, unsigned int colIdx)
 {
+    if(matrix->buffer == NULL)
+    {
+        printf("Fehler beim Setzen! Matrix nicht initialisiert");
+        return;
+    }
 
+    if(rowIdx >= matrix->rows || colIdx >= matrix->cols)
+    {
+        printf("Ungueltige Indizes beim Setzen!\n");
+        return;
+    }
+
+    matrix->buffer[rowIdx * matrix->cols + colIdx] = value;
 }
 
 MatrixType getMatrixAt(const Matrix matrix, unsigned int rowIdx, unsigned int colIdx)
 {
+    if(matrix.buffer == NULL)
+    {
+        printf("Fehler beim Lesen! Matrix nicht initialisiert");
+        return 0;
+    }
 
+    if(rowIdx >= matrix.rows || colIdx >= matrix.cols)
+    {
+        printf("Ungueltige Indizes beim Lesen!\n");
+        return 0;
+    }
+
+    return matrix.buffer[rowIdx * matrix.cols + colIdx];
 }
 
 Matrix add(const Matrix matrix1, const Matrix matrix2)
 {
+    if((matrix1.rows != matrix2.rows) || (matrix1.cols != matrix2.cols))
+    {
+        printf("Fehler bei Addition: Matrix Dimensionen passen nicht ueberein!\n");
+        Matrix empty = {0, 0, NULL};
+        return empty;
+    }
 
+    float matrix1Wert = 0;
+    float matrix2Wert = 0;
+    float summe = 0;
+
+    Matrix ergebnisMatrix = createMatrix(matrix1.rows, matrix1.cols);
+
+    for(int row = 0; row < ergebnisMatrix.rows; row++)
+    {
+        for(int col = 0; col < ergebnisMatrix.cols; col++)
+        {
+            matrix1Wert = getMatrixAt(matrix1, row, col);
+            matrix2Wert = getMatrixAt(matrix2, row, col);
+            summe = matrix1Wert + matrix2Wert;
+
+            setMatrixAt(summe, &ergebnisMatrix, row, col);
+        }
+    }
+
+    return ergebnisMatrix;
 }
 
 Matrix multiply(const Matrix matrix1, const Matrix matrix2)
 {
+    if(matrix1.cols != matrix2.rows)
+    {
+        printf("Fehler bei Multiplikation: Matrix Dimensionen passen nicht ueberein!\n");
+        Matrix empty = {0, 0, NULL};
+        return empty;
+    }
 
+    float erg = 0;
+
+    Matrix ergebnisMatrix = createMatrix(matrix1.rows, matrix2.cols);
+
+    for(int row = 0; row < ergebnisMatrix.rows; row++)
+    {
+        for(int col = 0; col < ergebnisMatrix.cols; col++)
+        {
+            erg = 0;
+
+            for(int k = 0; k < matrix1.cols; k++)
+            {
+                erg += getMatrixAt(matrix1, row, k) * getMatrixAt(matrix2, k, col);
+            }
+
+            setMatrixAt(erg, &ergebnisMatrix, row, col);
+        }
+    }
+
+    return ergebnisMatrix;
 }

matrix.h

@@ -6,7 +6,12 @@
 typedef float MatrixType;
 
 // TODO Matrixtyp definieren
-
+typedef struct
+{
+    int rows;
+    int cols;
+    float *buffer;
+} Matrix;
 
 Matrix createMatrix(unsigned int rows, unsigned int cols);
 void clearMatrix(Matrix *matrix);

neuralNetworkTests.c

@@ -5,10 +5,45 @@
 #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 *f = fopen(path, "wb");
+    if (!f) return;
+
+    fwrite(FILE_HEADER_STRING, sizeof(char), strlen(FILE_HEADER_STRING), f);
+
+    int inputDim = nn.layers[0].weights.cols;
+    int outputDim = nn.layers[0].weights.rows;
+
+    fwrite(&inputDim, sizeof(int), 1, f);
+    fwrite(&outputDim, sizeof(int), 1, f);
+
+    for (int i = 0; i < nn.numberOfLayers; i++)
+    {
+        Matrix weights = nn.layers[i].weights;
+        Matrix biases  = nn.layers[i].biases;
+
+        int numWeightValues = weights.rows * weights.cols;
+        int numBiasValues   = biases.rows * biases.cols;
+
+        fwrite(weights.buffer, sizeof(MatrixType), numWeightValues, f);
+        fwrite(biases.buffer, sizeof(MatrixType), numBiasValues, f);
+
+        if (i < nn.numberOfLayers - 1)
+        {
+            int nextOutputDim = nn.layers[i + 1].weights.rows;
+            fwrite(&nextOutputDim, sizeof(int), 1, f);
+        }
+    }
+
+    int endMarker = 0;
+    fwrite(&endMarker, sizeof(int), 1, f);
+
+    fclose(f);
 }
 
 void test_loadModelReturnsCorrectNumberOfLayers(void)