generated from freudenreichan/info2Praktikum-NeuronalesNetz
83 lines
2.2 KiB
C
83 lines
2.2 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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MatrixType createMatrix(unsigned int rows, unsigned int cols)
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{
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MatrixType m;
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m.rows = rows;
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m.cols = cols;
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m.values = (MatrixType *)malloc(rows * cols * sizeof(MatrixType));
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if (m.values == NULL) {
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m.rows = 0;
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m.cols = 0;
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return m;
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}
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for (unsigned int i = 0; i < rows * cols; ++i) {
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m.values[i] = 0.0; // Standardwert
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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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if (matrix->values != NULL) {
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free(matrix->values);
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}
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matrix->values = NULL;
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matrix->rows = 0;
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matrix->cols = 0;
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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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if (rowIdx < matrix.rows && colIdx < matrix.cols) {
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matrix.values[rowIdx * matrix.cols + colIdx] = value;
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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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if (rowIdx < matrix.rows && colIdx < matrix.cols) {
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return matrix.values[rowIdx * matrix.cols + colIdx];
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}
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return 0.0; // Fallback-Wert
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}
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Matrix add(const Matrix matrix1, const Matrix matrix2)
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{
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Matrix result = createMatrix(0, 0);
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if (matrix1.rows != matrix2.rows || matrix1.cols != matrix2.cols) {
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return result;
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}
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result = createMatrix(matrix1.rows, matrix1.cols);
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for (unsigned int i = 0; i < matrix1.rows; ++i) {
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for (unsigned int j = 0; j < matrix1.cols; ++j) {
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MatrixType sum = getMatrixAt(matrix1, i, j) + getMatrixAt(matrix2, i, j);
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setMatrixAt(sum, result, i, j);
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}
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}
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return result;
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}
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Matrix multiply(const Matrix matrix1, const Matrix matrix2)
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{
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Matrix result = createMatrix(0, 0);
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if (matrix1.cols != matrix2.rows) {
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return result;
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}
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result = createMatrix(matrix1.rows, matrix2.cols);
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for (unsigned int i = 0; i < matrix1.rows; ++i) {
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for (unsigned int j = 0; j < matrix2.cols; ++j) {
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MatrixType sum = 0.0;
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for (unsigned int k = 0; k < matrix1.cols; ++k) {
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sum += getMatrixAt(matrix1, i, k) * getMatrixAt(matrix2, k, j);
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}
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setMatrixAt(sum, result, i, j);
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}
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}
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return result; |