generated from freudenreichan/info2Praktikum-NeuronalesNetz
matrix programmiert
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matrix.c
78
matrix.c
@ -2,34 +2,96 @@
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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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// Matrix erstellen
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Matrix createMatrix(unsigned int rows, unsigned int cols)
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{
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Matrix matrix = {NULL, 0, 0};
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if (rows == 0 || cols == 0) {
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return matrix; // Keine Speicherallokation
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}
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matrix.buffer = (MatrixType *)calloc(rows * cols, sizeof(MatrixType));
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matrix.rows = rows;
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matrix.cols = cols;
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return matrix;
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}
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// Speicher freigeben
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void clearMatrix(Matrix *matrix)
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{
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if (matrix->buffer != NULL) {
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free(matrix->buffer);
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matrix->buffer = NULL;
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}
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matrix->rows = 0;
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matrix->cols = 0;
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}
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// Wert setzen
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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 && matrix.buffer != NULL) {
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matrix.buffer[rowIdx * matrix.cols + colIdx] = value;
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}
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}
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// Wert auslesen
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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 && matrix.buffer != NULL) {
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return matrix.buffer[rowIdx * matrix.cols + colIdx];
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}
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return UNDEFINED_MATRIX_VALUE; // Fehlerbehandlung
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}
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// Matrizen addieren (mit Broadcasting)
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Matrix add(const Matrix matrix1, const Matrix matrix2)
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{
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if (matrix1.buffer == NULL || matrix2.buffer == NULL) {
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return (Matrix){NULL, 0, 0};
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}
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// Prüfen auf Broadcasting-Kompatibilität
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if (!((matrix1.rows == matrix2.rows) || (matrix1.rows == 1) || (matrix2.rows == 1))) {
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return (Matrix){NULL, 0, 0};
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}
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if (!((matrix1.cols == matrix2.cols) || (matrix1.cols == 1) || (matrix2.cols == 1))) {
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return (Matrix){NULL, 0, 0};
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}
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unsigned int resultRows = (matrix1.rows > matrix2.rows) ? matrix1.rows : matrix2.rows;
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unsigned int resultCols = (matrix1.cols > matrix2.cols) ? matrix1.cols : matrix2.cols;
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Matrix result = createMatrix(resultRows, resultCols);
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for (unsigned int i = 0; i < resultRows; i++) {
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for (unsigned int j = 0; j < resultCols; j++) {
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MatrixType val1 = matrix1.buffer[(matrix1.rows == 1 ? 0 : i) * matrix1.cols +
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(matrix1.cols == 1 ? 0 : j)];
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MatrixType val2 = matrix2.buffer[(matrix2.rows == 1 ? 0 : i) * matrix2.cols +
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(matrix2.cols == 1 ? 0 : j)];
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result.buffer[i * resultCols + j] = val1 + val2;
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}
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}
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return result;
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}
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// Matrizen multiplizieren
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Matrix multiply(const Matrix matrix1, const Matrix matrix2)
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{
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if (matrix1.cols != matrix2.rows || matrix1.buffer == NULL || matrix2.buffer == NULL) {
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return (Matrix){NULL, 0, 0};
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}
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Matrix 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;
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for (unsigned int k = 0; k < matrix1.cols; k++) {
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sum += matrix1.buffer[i * matrix1.cols + k] * matrix2.buffer[k * matrix2.cols + j];
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}
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result.buffer[i * result.cols + j] = sum;
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}
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}
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return result;
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}
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6
matrix.h
6
matrix.h
@ -6,7 +6,11 @@
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typedef float MatrixType;
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// TODO Matrixtyp definieren
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typedef struct {
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MatrixType *buffer; // zuerst der Speicherbereich
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unsigned int rows; // dann die Anzahl Zeilen
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unsigned int cols; // dann die Anzahl Spalten
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} Matrix;
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Matrix createMatrix(unsigned int rows, unsigned int cols);
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void clearMatrix(Matrix *matrix);
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