generated from freudenreichan/info2Praktikum-NeuronalesNetz
97 lines
1.7 KiB
C
97 lines
1.7 KiB
C
#include <stdlib.h>
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#include <string.h>
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#include "matrix.h"
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// TODO Matrix-Funktionen implementieren
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/*
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Alte Funktion
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Matrix createMatrix(unsigned int rows, unsigned int cols)
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{
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Matrix m;
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m.rows = rows;
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m.cols = cols;
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m.data = NULL;
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if(rows == 0 || cols == 0){
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m.rows = m.cols = 0;
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return m;
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}
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m.data = malloc(rows * sizeof *m.data);
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if(!m.data){
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m.rows = m.cols = 0;
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return m;
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}
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for(unsigned int i = 0; i < rows; i++){
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m.data[i] = malloc(cols * sizeof *m.data[i]);
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if(!m.data[i]){
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for(unsigned int j = 0; j < i; j++){
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free(m.data[j]);
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}
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free(m.data);
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m.data = NULL;
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m.rows = m.cols = 0;
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return m;
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}
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}
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return m;
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}
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*/
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Matrix createMatrix(size_t cols, size_t rows)
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{
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Matrix m;
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m.rows = rows;
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m.cols = cols;
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m.buffer = NULL;
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if(rows == 0 || cols == 0){
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m.rows = m.cols = 0;
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return m;
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}
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// Single allocation for entire matrix
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m.buffer = malloc(rows * cols * sizeof(MatrixType));
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if(!m.buffer){
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m.rows = m.cols = 0;
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return m;
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}
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// Initialize (optional)
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for(unsigned int i = 0; i < rows * cols; i++){
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m.buffer[i] = UNDEFINED_MATRIX_VALUE;
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}
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return m;
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}
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void clearMatrix(Matrix *matrix)
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{
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}
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void setMatrixAt(MatrixType value, Matrix matrix, unsigned int rowIdx, unsigned int colIdx)
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{
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}
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MatrixType getMatrixAt(const Matrix matrix, unsigned int rowIdx, unsigned int colIdx)
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{
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}
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Matrix add(const Matrix matrix1, const Matrix matrix2)
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{
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}
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Matrix multiply(const Matrix matrix1, const Matrix matrix2)
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{
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} |