at the first while iteration, x1 entries contain garbage, so the first print output will have a correct entry of x1 and garbage for x1.So, if you don't zero out x1 before the for-loop: The print expression is inside the for-loop, while the entries of x1 are updated one by one. Notice, that in the following piece of code: x1 = np.zeros(n) However, I think I see the source of confusion. I am not entirely sure what are you trying to achieve and why do you want to AVOID zeroing out x1 if you care about what is being printed. Iter.=3 duration=0.156000 err=3.409068e-05Įven if I don't assing zeros to x1 in each cycle, the solution are computed correctly. Unwanted output if I comment x1 = np.zeros(n) at the beginning of while : begin while with k = 0 Wanted output: - As you can see x0 contains the x1 of of the previous while iteration begin while with k = 0 Print('Iter.=%d duration=%f err=%e' % (k,duration,err)) Print('Not converges in %d iterations' % Kmax) This is the code, you can see the wanted and unwanted output below: def GaussSeidel(A,b): The result seems to be correct, but when I comment the vector x1 at the beginning of the while, I obtain an unwanted result:įor example, before the assignment x0=x1, when k=1, x0 is equal to x1 instead x0 when k=1, would be equal to x1 when k=0.Ĭonsequently, the norm(x1-x0) is always 0, after the first while.
In the following code for the Gauss Seidel method, I enter one given matrix A.
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