forked from freudenreichan/info2Praktikum-NeuronalesNetz
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5 Commits
| Author | SHA1 | Date | |
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| 2436240736 | |||
| fde82f2d9a | |||
| 0fc70f982c | |||
| b271c865cb | |||
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077c6def78 |
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47
imageInput.c
47
imageInput.c
@ -5,59 +5,12 @@
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#define BUFFER_SIZE 100
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#define FILE_HEADER_STRING "__info2_image_file_format__"
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#define FILE_HEADER_SIZE (sizeof(FILE_HEADER_STRING)-1)
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// TODO Implementieren Sie geeignete Hilfsfunktionen für das Lesen der Bildserie aus einer Datei
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FILE *checkFile(const char *path)
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{
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FILE *datei = fopen(path,"rb");
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if (datei == NULL)
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{
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perror("Datei konnte nicht geoeffnet werden");
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return NULL;
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}
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char buffer[FILE_HEADER_SIZE+1];
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if (fread(buffer,1,FILE_HEADER_SIZE,datei)!=FILE_HEADER_SIZE)
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{
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perror("Header konnte nicht eingelessen werden");
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fclose(datei);
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return NULL;
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}
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buffer[FILE_HEADER_SIZE] = '\0';
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if (strcmp(buffer,FILE_HEADER_STRING)!=0)
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{
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printf("Falscher Dateikopf");
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//printf("\n%s",buffer);
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//printf("\n%s",FILE_HEADER_STRING);
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//printf("\n%d",strcmp(buffer,FILE_HEADER_STRING));
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fclose(datei);
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return NULL;
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}
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return datei;
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}
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// TODO Vervollständigen Sie die Funktion readImages unter Benutzung Ihrer Hilfsfunktionen
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GrayScaleImageSeries *readImages(const char *path)
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{
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FILE *datei = checkFile(path);
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if (datei==NULL)
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{
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return NULL;
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}
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unsigned short image_count, width, height;
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fread(&image_count,1,sizeof(unsigned short),datei);
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fread(&width,1,sizeof(unsigned short),datei);
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fread(&height,1,sizeof(unsigned short),datei);
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//printf("%u Bilder und %u mal %u",image_count,width,height);
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fclose(datei);
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GrayScaleImageSeries *series = NULL;
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return series;
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@ -19,5 +19,5 @@ typedef struct
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GrayScaleImageSeries *readImages(const char *path);
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void clearSeries(GrayScaleImageSeries *series);
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FILE *checkFile(const char *path);
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#endif
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@ -54,7 +54,7 @@ void test_readImagesReturnsCorrectImageWidth(void)
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GrayScaleImageSeries *series = NULL;
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const unsigned short expectedWidth = 10;
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const char *path = "testFile.info2";
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prepareImageFile(path, 8, expectedWidth, 2, 1);
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prepareImageFile(path, expectedWidth, 8, 2, 1);
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series = readImages(path);
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TEST_ASSERT_NOT_NULL(series);
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TEST_ASSERT_NOT_NULL(series->images);
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@ -70,7 +70,7 @@ void test_readImagesReturnsCorrectImageHeight(void)
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GrayScaleImageSeries *series = NULL;
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const unsigned short expectedHeight = 10;
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const char *path = "testFile.info2";
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prepareImageFile(path, expectedHeight, 8, 2, 1);
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prepareImageFile(path, 8, expectedHeight, 2, 1);
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series = readImages(path);
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TEST_ASSERT_NOT_NULL(series);
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TEST_ASSERT_NOT_NULL(series->images);
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7
main.c
7
main.c
@ -1,13 +1,11 @@
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#include <stdio.h>
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#include <stdlib.h>
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#include "imageInput.h"
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//#include "mnistVisualization.h"
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//#include "neuralNetwork.h"
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#include "mnistVisualization.h"
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#include "neuralNetwork.h"
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int main(int argc, char *argv[])
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{
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readImages("mnist_test.info2");
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/*
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const unsigned int windowWidth = 800;
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const unsigned int windowHeight = 600;
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@ -67,5 +65,4 @@ int main(int argc, char *argv[])
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}
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return exitCode;
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*/
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}
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81
matrix.c
81
matrix.c
@ -4,103 +4,32 @@
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// TODO Matrix-Funktionen implementieren
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// Matrix erzeugen
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Matrix createMatrix(unsigned int rows, unsigned int cols)
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{
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Matrix matrix;
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matrix.rows = rows;
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matrix.cols = cols;
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if (rows == 0 || cols == 0) {
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matrix.buffer = NULL;
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return matrix;
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}
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matrix.buffer = (MatrixType *)malloc(rows * cols * sizeof(MatrixType));
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if (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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return matrix;
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}
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// Matrix 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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{
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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)
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{
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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)
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{
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return matrix.buffer[rowIdx * matrix.cols + colIdx];
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}
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return 0; // Fallback
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}
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// Matrizen addieren
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Matrix add(const Matrix m1, const Matrix m2)
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Matrix add(const Matrix matrix1, const Matrix matrix2)
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{
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if (m1.rows != m2.rows || m1.cols != m2.cols)
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{
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return createMatrix(0, 0); // Falls Matrix-Dimensionen nicht passen
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}
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Matrix result = createMatrix(m1.rows, m1.cols);
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if (result.buffer == NULL) return result;
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for (unsigned int r = 0; r < m1.rows; r++)
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{
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for (unsigned int c = 0; c < m1.cols; c++)
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{
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result.buffer[r * m1.cols + c] =
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getMatrixAt(m1, r, c) + getMatrixAt(m2, r, c);
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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 m1, const Matrix m2)
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Matrix multiply(const Matrix matrix1, const Matrix matrix2)
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{
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if (m1.cols != m2.rows)
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{
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return createMatrix(0, 0); // Falls Matrix-Dimensionen nicht passen
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}
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Matrix result = createMatrix(m1.rows, m2.cols);
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if (result.buffer == NULL) return result;
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for (unsigned int r = 0; r < m1.rows; r++)
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{
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for (unsigned int c = 0; c < m2.cols; c++)
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{
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MatrixType sum = 0;
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for (unsigned int k = 0; k < m1.cols; k++)
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{
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sum += getMatrixAt(m1, r, k) * getMatrixAt(m2, k, c);
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}
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result.buffer[r * m2.cols + c] = 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
@ -6,12 +6,6 @@
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typedef float MatrixType;
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// TODO Matrixtyp definieren
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typedef struct
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{
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unsigned int rows;
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unsigned int cols;
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MatrixType *buffer;
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} Matrix;
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Matrix createMatrix(unsigned int rows, unsigned int cols);
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@ -71,6 +71,32 @@ void test_addFailsOnDifferentInputDimensions(void)
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TEST_ASSERT_EQUAL_UINT32(0, result.cols);
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}
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void test_addSupportsBroadcasting(void)
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{
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MatrixType buffer1[] = {1, 2, 3, 4, 5, 6};
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MatrixType buffer2[] = {7, 8};
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Matrix matrix1 = {.rows=2, .cols=3, .buffer=buffer1};
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Matrix matrix2 = {.rows=2, .cols=1, .buffer=buffer2};
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Matrix result1 = add(matrix1, matrix2);
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Matrix result2 = add(matrix2, matrix1);
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float expectedResults[] = {8, 9, 10, 12, 13, 14};
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TEST_ASSERT_EQUAL_UINT32(matrix1.rows, result1.rows);
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TEST_ASSERT_EQUAL_UINT32(matrix1.cols, result1.cols);
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TEST_ASSERT_EQUAL_UINT32(matrix1.rows, result2.rows);
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TEST_ASSERT_EQUAL_UINT32(matrix1.cols, result2.cols);
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TEST_ASSERT_EQUAL_INT(sizeof(expectedResults)/sizeof(expectedResults[0]), result1.rows * result1.cols);
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TEST_ASSERT_EQUAL_FLOAT_ARRAY(expectedResults, result1.buffer, result1.cols * result1.rows);
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TEST_ASSERT_EQUAL_INT(sizeof(expectedResults)/sizeof(expectedResults[0]), result2.rows * result2.cols);
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TEST_ASSERT_EQUAL_FLOAT_ARRAY(expectedResults, result2.buffer, result2.cols * result2.rows);
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free(result1.buffer);
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free(result2.buffer);
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}
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void test_multiplyReturnsCorrectResults(void)
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{
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MatrixType buffer1[] = {1, 2, 3, 4, 5, 6};
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@ -138,7 +164,7 @@ void test_setMatrixAtFailsOnIndicesOutOfRange(void)
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Matrix matrixToTest = {.rows=2, .cols=3, .buffer=buffer};
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setMatrixAt(-1, matrixToTest, 2, 3);
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TEST_ASSERT_EQUAL_FLOAT_ARRAY(expectedResults, matrixToTest.buffer, matrixToTest.cols * matrixToTest.rows);
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TEST_ASSERT_EQUAL_FLOAT_ARRAY(expectedResults, matrixToTest.buffer, sizeof(buffer)/sizeof(MatrixType));
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}
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void setUp(void) {
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@ -159,6 +185,7 @@ int main()
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RUN_TEST(test_clearMatrixSetsMembersToNull);
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RUN_TEST(test_addReturnsCorrectResult);
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RUN_TEST(test_addFailsOnDifferentInputDimensions);
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RUN_TEST(test_addSupportsBroadcasting);
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RUN_TEST(test_multiplyReturnsCorrectResults);
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RUN_TEST(test_multiplyFailsOnWrongInputDimensions);
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RUN_TEST(test_getMatrixAtReturnsCorrectResult);
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