Standard condition in the Gauss-Seidel method in Python

Hello, I'm trying to put a new condition in the Gauss-Seidel method. In the case, A, q and x are three matrices, and w is the number of times the interaction is made:

def gauss(A, q, x, w):
    L = np.tril(A)
    U = A - L
    for i in range(w):
        x = np.dot(np.linalg.inv(L), q - np.dot(U, x))
        print str(i).zfill(n),
        print(x)
    return x

#número de interações
w = 500

In this case, I am trying to add a new condition: what is the largest and smallest number that can appear in the output within the array. In this case, it would be:

for i in range(0,len(gauss(A, q, x, w))):
  for j in range(0,len(gauss(A, q, x, w)[i])):
    if gauss(A, q, x, w)[i][j] >= -1 * (10 **(-2)):
        gauss(A, q, x, w)[i][j] = -1 * (10 **(-2))
    if gauss(A, q, x, w)[i][j] >= 1 * (10 **(-2)):
        gauss(A, q, x, w)[i][j] = 1 * (10 **(-2))

However, the program does not understand the command when adding in the rest and I do not know exactly if I am putting in the wrong order, if the command is wrong or if I should add all this out into a new function:

def gauss(A, q, x, w):
    L = np.tril(A)
    U = A - L
    for i in range(w):
        x = np.dot(np.linalg.inv(L), q - np.dot(U, x))
        for i in range(0,len(gauss(A, q, x, w))):
           for j in range(0,len(gauss(A, q, x, w)[i])):
              if gauss(A, q, x, w)[i][j] >= -1 * (10 **(-2)):
                  gauss(A, q, x, w)[i][j] = -1 * (10 **(-2))
              if gauss(A, q, x, w)[i][j] >= 1 * (10 **(-2)):
                  gauss(A, q, x, w)[i][j] = 1 * (10 **(-2))
              print str(i).zfill(n),
              print(x)
    return x
w = 500
print gauss(A, q, x, w)
solve = np.linalg.solve(A, q)
print solve