Neuronetz_V2/matrix.c

120 lines
3.7 KiB
C

#include <stdlib.h>
#include <string.h>
#include <stdio.h>
#include "matrix.h"
/* Implementierung der Matrix-Funktionen */
Matrix createMatrix(unsigned int rows, unsigned int cols)
{
Matrix m = {NULL,0,0};
if (rows > 0 && cols > 0) {
m.rows = rows;
m.cols = cols;
/* calloc initialisiert den Speicher mit 0 */
m.buffer = (MatrixType*)calloc(rows * cols, sizeof(MatrixType));
}
return m;
}
void clearMatrix(Matrix *matrix)
{
if (matrix != NULL) {
if (matrix->buffer != NULL) {
free(matrix->buffer);
matrix->buffer = NULL;
}
matrix->rows = 0;
matrix->cols = 0;
}
}
void setMatrixAt(MatrixType value, Matrix matrix, unsigned int rowIdx, unsigned int colIdx)
{
if (matrix.buffer != NULL && rowIdx < matrix.rows && colIdx < matrix.cols) {
matrix.buffer[rowIdx * matrix.cols + colIdx] = value;
}
}
/* um das eindimensionale arry umzurechenen rechnet um wo splaten und zeile ist */
MatrixType getMatrixAt(const Matrix matrix, unsigned int rowIdx, unsigned int colIdx)
{
if (matrix.buffer != NULL && rowIdx < matrix.rows && colIdx < matrix.cols) {
return matrix.buffer[rowIdx * matrix.cols + colIdx];
}
return UNDEFINED_MATRIX_VALUE;
}
Matrix add(const Matrix matrix1, const Matrix matrix2)
{
Matrix result;
unsigned int r, c;
/* Fall 1: Normale Addition (Dimensionen identisch) */
if (matrix1.rows == matrix2.rows && matrix1.cols == matrix2.cols) {
result = createMatrix(matrix1.rows, matrix1.cols);
if (result.buffer != NULL) {
unsigned int i;
for (i = 0; i < matrix1.rows * matrix1.cols; i++) {
result.buffer[i] = matrix1.buffer[i] + matrix2.buffer[i];
}
}
return result;
}
/* Fall 2: Broadcasting (Matrix + Spaltenvektor) */
else if (matrix1.rows == matrix2.rows && matrix2.cols == 1) {
result = createMatrix(matrix1.rows, matrix1.cols);
if (result.buffer != NULL) {
for (r = 0; r < matrix1.rows; r++) {
for (c = 0; c < matrix1.cols; c++) {
MatrixType sum = getMatrixAt(matrix1, r, c) + getMatrixAt(matrix2, r, 0);
setMatrixAt(sum, result, r, c);
}
}
}
return result;
}
/* Fall 3: Broadcasting (Spaltenvektor + Matrix) */
else if (matrix2.rows == matrix1.rows && matrix1.cols == 1) {
result = createMatrix(matrix2.rows, matrix2.cols);
if (result.buffer != NULL) {
for (r = 0; r < matrix2.rows; r++) {
for (c = 0; c < matrix2.cols; c++) {
MatrixType sum = getMatrixAt(matrix1, r, 0) + getMatrixAt(matrix2, r, c);
setMatrixAt(sum, result, r, c);
}
}
}
return result;
}
/* Fehlerfall: Leere Matrix zurückgeben */
return createMatrix(0, 0);
}
Matrix multiply(const Matrix matrix1, const Matrix matrix2)
{
Matrix result;
unsigned int r, c, k;
/* Prüfen, ob Multiplikation erlaubt ist (Spalten von A == Zeilen von B) */
if (matrix1.cols != matrix2.rows) {
return createMatrix(0, 0);
}
result = createMatrix(matrix1.rows, matrix2.cols);
if (result.buffer != NULL) {
for (r = 0; r < result.rows; r++) {
for (c = 0; c < result.cols; c++) {
MatrixType sum = 0;
/* Skalarprodukt berechnen */
for (k = 0; k < matrix1.cols; k++) {
sum += getMatrixAt(matrix1, r, k) * getMatrixAt(matrix2, k, c);
}
setMatrixAt(sum, result, r, c);
}
}
}
return result;
}