forked from freudenreichan/info2Praktikum-NeuronalesNetz
makefile für alle Betriebssysteme
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3
makefile
3
makefile
@ -63,5 +63,6 @@ imageInputTests: imageInput.o imageInputTests.c $(unityfolder)/unity.c
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#else
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#else
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# rm -f *.o mnist runMatrixTests runNeuralNetworkTests runImageInputTests
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# rm -f *.o mnist runMatrixTests runNeuralNetworkTests runImageInputTests
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#endif
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#endif
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# clean für windows
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clean:
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clean:
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rm -f *.o *.exe
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rm -f *.o *.exe
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28
matrix.c
28
matrix.c
@ -20,9 +20,9 @@ void clearMatrix(Matrix *matrix) {
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matrix->cols = UNDEFINED_MATRIX_VALUE;
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matrix->cols = UNDEFINED_MATRIX_VALUE;
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free((*matrix).buffer); // Speicher freigeben
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free((*matrix).buffer); // Speicher freigeben
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}
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}
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void setMatrixAt(MatrixType value, Matrix matrix,
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void setMatrixAt(const MatrixType value, Matrix matrix,
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unsigned int rowIdx, // Kopie der Matrix wird übergeben
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const unsigned int rowIdx, // Kopie der Matrix wird übergeben
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unsigned int colIdx) {
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const unsigned int colIdx) {
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matrix.buffer[rowIdx * matrix.cols + colIdx] =
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matrix.buffer[rowIdx * matrix.cols + colIdx] =
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value; // rowIdx * matrix.cols -> Beginn der Zeile colIdx ->Spalte
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value; // rowIdx * matrix.cols -> Beginn der Zeile colIdx ->Spalte
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@ -41,7 +41,25 @@ MatrixType getMatrixAt(const Matrix matrix,
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return value;
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return value;
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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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// broadcasting
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return matrix1;
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// Ergebnismatrix
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Matrix result;
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// Broadcasting nur bei Vektor und Matrix, Fehlermeldung bei zwei unpassender
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// Matrix
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if (matrix1.rows != matrix2.rows) {
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// check, which one is smaller
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// realloc
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}
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if (matrix1.cols != matrix2.cols) {
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}
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// Speicher reservieren
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// Matrix addieren
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return result;
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}
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}
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Matrix multiply(const Matrix matrix1, const Matrix matrix2) { return matrix1; }
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Matrix multiply(const Matrix matrix1, const Matrix matrix2) { return matrix1; }
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