forked from freudenreichan/info2Praktikum-NeuronalesNetz
multiply fix
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parent
c560fd5241
commit
14388a5637
41
matrix.c
41
matrix.c
@ -14,7 +14,7 @@ Matrix createMatrix(unsigned int rows, unsigned int cols)
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if (rows > 0 || cols > 0)
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if (rows > 0 || cols > 0)
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{
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{
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m.buffer = malloc (rows * cols * sizeof(int));
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m.buffer = malloc(rows * cols * sizeof(int));
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}
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}
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return m;
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return m;
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@ -23,7 +23,8 @@ Matrix createMatrix(unsigned int rows, unsigned int cols)
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void clearMatrix(Matrix *matrix)
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void clearMatrix(Matrix *matrix)
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{
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{
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if (matrix == NULL) {
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if (matrix == NULL)
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{
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return;
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return;
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}
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}
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@ -38,21 +39,21 @@ void clearMatrix(Matrix *matrix)
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void setMatrixAt(MatrixType value, Matrix matrix, unsigned int rowIdx, unsigned int colIdx)
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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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matrix.buffer[rowIdx * matrix.cols + colIdx] = value; //setzte Matrix auf den Wert value am Punkt (row col)
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matrix.buffer[rowIdx * matrix.cols + colIdx] = value; // setzte Matrix auf den Wert value am Punkt (row col)
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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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MatrixType getMatrixAt(const Matrix matrix, unsigned int rowIdx, unsigned int colIdx)
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{
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{
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MatrixType value = 0;
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MatrixType value = 0;
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return value = matrix.buffer[rowIdx * matrix.cols + colIdx]; //hole Wert value am Punkt (row col)
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return value = matrix.buffer[rowIdx * matrix.cols + colIdx]; // hole Wert value am Punkt (row col)
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}
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}
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Matrix add(const Matrix matrix1, const Matrix matrix2)
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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 result = {0};
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Matrix result = {0};
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if(matrix1.rows != matrix2.rows || matrix1.cols != matrix2.cols)
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if (matrix1.rows != matrix2.rows || matrix1.cols != matrix2.cols)
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{
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{
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return result;
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return result;
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}
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}
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@ -61,21 +62,20 @@ Matrix add(const Matrix matrix1, const Matrix matrix2)
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result.cols = matrix1.cols;
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result.cols = matrix1.cols;
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result.buffer = malloc(result.rows * result.cols * sizeof(MatrixType));
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result.buffer = malloc(result.rows * result.cols * sizeof(MatrixType));
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//wenn buffer nicht allokiert werden kann dann zurücksetzen und abbrechen
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// wenn buffer nicht allokiert werden kann dann zurücksetzen und abbrechen
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if(result.buffer == NULL)
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if (result.buffer == NULL)
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{
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{
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result.rows = result.cols = 0;
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result.rows = result.cols = 0;
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return result;
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return result;
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}
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}
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//Matritzenaddition
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// Matritzenaddition
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for (unsigned int i = 0; i < result.rows; i++)
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for (unsigned int i = 0; i < result.rows; i++)
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{
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{
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for (unsigned int j = 0; j < result.cols; j++)
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for (unsigned int j = 0; j < result.cols; j++)
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{
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{
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result.buffer[i * result.cols + j] = matrix1.buffer[i * matrix1.cols + j] + matrix2.buffer[i * matrix2.cols + j];
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result.buffer[i * result.cols + j] = matrix1.buffer[i * matrix1.cols + j] + matrix2.buffer[i * matrix2.cols + j];
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}
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}
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}
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}
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return result;
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return result;
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@ -85,34 +85,37 @@ Matrix multiply(const Matrix matrix1, const Matrix matrix2)
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{
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{
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Matrix result = {0};
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Matrix result = {0};
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if(matrix1.rows != matrix2.rows || matrix1.cols != matrix2.cols)
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if (matrix1.cols != matrix2.rows)
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{
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{
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return result;
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return result;
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}
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}
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result.rows = matrix1.rows;
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result.rows = matrix1.rows;
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result.cols = matrix1.cols;
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result.cols = matrix2.cols;
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result.buffer = malloc(result.rows * result.cols * sizeof(MatrixType));
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result.buffer = malloc(result.rows * result.cols * sizeof(MatrixType));
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//wenn buffer nicht allokiert werden kann dann zurücksetzen und abbrechen
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// wenn buffer nicht allokiert werden kann dann zurücksetzen und abbrechen
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if(result.buffer == NULL)
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if (result.buffer == NULL)
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{
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{
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result.rows = result.cols = 0;
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result.rows = result.cols = 0;
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return result;
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return result;
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}
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}
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//Matritzenmultiplikation
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// Matritzenmultiplikation
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for (unsigned int i = 0; i < result.rows; i++)
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for (int r = 0; r < result.rows; r++) // Zeile in Ergebnis
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{
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{
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for (unsigned int j = 0; j < result.cols; j++)
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for (int m = 0; m < result.cols; m++) // Spalte in Ergebnis
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{
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{
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MatrixType sum = 0;
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MatrixType sum = 0;
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for (unsigned int k = 0; k < matrix1.cols; k++)
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for (int n = 0; n < matrix1.cols; n++)
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{
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{
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sum += matrix1.buffer[i * matrix1.cols + k] * matrix2.buffer[k * matrix2.cols + j];
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sum += matrix1.buffer[r * matrix1.cols + n] *
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matrix2.buffer[n * matrix2.cols + m];
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}
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}
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result.buffer[i * result.cols + j] = sum;
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result.buffer[r * result.cols + m] = sum;
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}
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}
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}
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}
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