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function A = gaussLR(A)
% Gaussian Elimination for reforming the matrix into left-lower and right-upper triangular matrix
% A: A R^(n \times n) matrix
% actually not used here (but it was planned to be used): bsxfun, which makes this possible: bsxfun(@times, [1,2;3,4], [1;2]) = [1,2;6,8]. It multiplies the first row by 1, and the second one by 2.
% newer (and actually (still not) used here): [1,2;3,4].*[1;2] = [1,2;6,8]
% for convenience
len = length(A)
for i = 1:len
prefactor = A(i,i)
if prefactor == 0
error("LR-Zerlegung failed. Please use pivotization, or check that the matrix is regular!")
end
% elimination (find R)
factors = zeros(len, 1);
for j = (i+1):len
factors(j) = A(j, i) / prefactor;
end
% A(:,i:len) describes the matrix A with only the last i cols (so, for example, a 3x3 matrix with (:,2,len) with len=3) is the last 2 cols of the matrix, and with that a 2x3 matrix
% extra step for traceability, could also be compressed to a single line
multmatrix = (-factors * A(i,i:len))
A(:,i:len) = A(:,i:len) + multmatrix;
% save factors for L
A(:,i) = A(:,i) + factors
end
end