Python problem

Make a function defined as: def GaussJacobi(Aaug, x, niter = 15):

Purpose: use the Gauss-Jacobi method to estimate the solution to a set of N linear equations expressed in matrix form as A x = b. Both A and b are contained in the function argument - Aaug - an augmented A-matrix Do NOT use pivoting to try to improve the solution. Simply use the values as given.

Aaug: an augmented matrix containing [A | b ] having N rows and N+1 columns, where N is the number of equations in the set.

x: a vector (array) contain the values of the initial guess

niter: the number of iterations (new x solutions) to compute

return value: the final new x vector.

Write and call a main() function that uses your GaussJacobi function to estimate and print the solution to the sets of linear equations contained in the following Augmented A-matrices: MyA = [[4, -1, -1, 3], [-2, -3, 1, 9], using initial guesses of all ZEROS. Perform 22 iterations. [-1, 1, 7, -6]] anotherA = [[ 4, 3, 1, -1, 2], [ 2, -5, 0, -2, -3], using initial guesses of all ONES. Perform 3 [ -3, 3, -6, 1, 5], iterations. [ 0, 1, 4, 8, -2] ]