main2.py - constains larger user-input of size N, matrix a and vector b.main.py - contains basic usage demonstration of jacobi_calc() or gauss_seidel_calc(), using a 3x3 matrix, and basic arguments.rel_diff, the relative difference between last 2.If max_iter is None, the default value will set as 200. max_iter, the maxim number of possible iterations to receive the most exact solution.If tolerance is None, the default value will set as 1e-16. tolerance, the desired limitation of tolerance of solution's anomaly.If x is None, the initial guess will bw determined as a vector of 0's. if b is None - the functions returns None. If a is None or NxM, where N != M - the functions returns None. a, the NxN matrix that the method is being performed on.The algorithms will terminate when the change in x is less than tolerance, or if max_iter iterations have been exceeded.įor each function: (jacobi_calc() or gauss_seidel_calc()) Jacobi & Gauss-Seidel Algorithms Using Python The following methods solve the line system of equations, Ax=b,using Jacobi OR Gauss-Seidel algorithms, starting from an initial guess, x0.
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