Question

import math
import numpy as np
import numpy.linalg
from scipy.linalg import solve



A = np.array([[-math.cos(math.pi/6),0, math.cos(math.pi/3),0, 0, 0],
             [-math.sin(math.pi/6), 0, -math.sin(math.pi/3), 0, 0, 0],
             [math.cos(math.pi/6), 1, 0, 1, 0, 0],
             [math.sin(math.pi/6), 0, 0, 0, 1, 0],
             [0, -1, -math.cos(math.pi/3), 0, 0, 0],
             [0, 0, math.sin(math.pi/3), 0, 0, 1]])

b = np.array([0, 2000, 0, 0, 0, 0])

x = [0, 0, 0, 0, 0, 0]



def seidel(a, x, b):
    # Finding length of a(3)
    n = len(a)
    # for loop for 3 times as to calculate x, y , z
    for j in range(0, n):
        # temp variable d to store b[j]
        d = b[j]

        # to calculate respective xi, yi, zi
        for i in range(0, n):
            if (j != i):
                d -= a[j][i] * x[i]
        # updating the value of our solution
        x[j] = d / a[j][j]
    # returning our updated solution
    return x


seidel(A, x, b)

RESULTS:

:\Users\mauri\Anaconda3\python.exe "C:/Users/mauri/PycharmProjects/OCEN 261 APPLIED NUMERICAL METHODS/HW 7.py"
C:/Users/mauri/PycharmProjects/OCEN 261 APPLIED NUMERICAL METHODS/HW 7.py:75: RuntimeWarning: divide by zero encountered in double_scalars
x[j] = d / a[j][j]
C:/Users/mauri/PycharmProjects/OCEN 261 APPLIED NUMERICAL METHODS/HW 7.py:73: RuntimeWarning:

PLEASE HELP MEND MY GAUSS-Seidel Code

Answer 1

CODE:

import math
import numpy as np
import warnings
#import numpy.linalg
#from scipy.linalg import solve

A = np.array([[-math.cos(math.pi/6),0, math.cos(math.pi/3),0, 0, 0],
[-math.sin(math.pi/6), 0, -math.sin(math.pi/3), 0, 0, 0],
[math.cos(math.pi/6), 1, 0, 1, 0, 0],
[math.sin(math.pi/6), 0, 0, 0, 1, 0],
[0, -1, -math.cos(math.pi/3), 0, 0, 0],
[0, 0, math.sin(math.pi/3), 0, 0, 1]])

b = np.array([0, 2000, 0, 0, 0, 0])
x = [0, 0, 0, 0, 0, 0]

def seidel(a, x, b):
# Finding length of a(3)
n = len(a)
# for loop for 3 times as to calculate x, y , z
for j in range(0, n):
# temp variable d to store b[j]
d = b[j]

# to calculate respective xi, yi, zi
for i in range(0, n):
if (j != i):
d -= a[j][i] * x[i]
# updating the value of our solution
warnings.filterwarnings("ignore")
x[j] = d / a[j][j]
# returning our updated solution
return x
seidel(A, x, b)

OUTPUT: