generated from freudenreichan/info2Praktikum-NeuronalesNetz
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98aa5f354a
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5ce0982e17
7
matrix.c
7
matrix.c
@ -150,6 +150,7 @@ Matrix add(const Matrix matrix1, const Matrix matrix2)
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//size of the matrices should be the same, if the addition is supposed to happen
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//size of the matrices should be the same, if the addition is supposed to happen
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// Matrix outputMatrix = createMatrix(matrix1.rows, matrix1.cols);
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Matrix outputMatrix = createMatrix(matrix1.rows, matrix1.cols);
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Matrix outputMatrix = createMatrix(matrix1.rows, matrix1.cols);
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if(!outputMatrix.buffer){
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if(!outputMatrix.buffer){
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@ -265,12 +266,16 @@ Matrix multiply(const Matrix matrix1, const Matrix matrix2)
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//Matrix outputMatrix = createMatrix(matrix2.cols, matrix1.rows);
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//Matrix outputMatrix = createMatrix(matrix2.cols, matrix1.rows);
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for(int i = 0; i < matrix1.rows; i++) {
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for(int i = 0; i < matrix1.rows; i++) {
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for (int j = 0; j < matrix2.cols; j++) {
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for (int j = 0; j < matrix2.cols; j++) {
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MatrixType sum = 0;
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for (int k = 0; k < matrix1.cols; k++) {
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for (int k = 0; k < matrix1.cols; k++) {
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// how this should work in normal Matrix version:
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// how this should work in normal Matrix version:
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// outputMatrix.buffer[i][j] = matrix1.buffer[i][k] * matrix2.buffer[k][j];
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// outputMatrix.buffer[i][j] = matrix1.buffer[i][k] * matrix2.buffer[k][j];
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//outputMatrix.buffer[i + outputMatrix.rows * j] += matrix1.buffer[i + matrix1.rows * k] * matrix2.buffer[k + matrix2.rows * j];
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//outputMatrix.buffer[i + outputMatrix.rows * j] += matrix1.buffer[i + matrix1.rows * k] * matrix2.buffer[k + matrix2.rows * j];
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outputMatrix.buffer[i * outputMatrix.cols + j] += matrix1.buffer[i * matrix1.cols + k] * matrix2.buffer[j + matrix2.cols * k];
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sum += matrix1.buffer[i * matrix1.cols + k] * matrix2.buffer[j + matrix2.cols * k];
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}
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}
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outputMatrix.buffer[i * outputMatrix.cols + j] = sum;
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}
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}
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}
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}
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return outputMatrix;
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return outputMatrix;
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@ -1 +0,0 @@
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make clean && make matrixTests && ./runMatrixTests
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