def otherGaussSiedel(m,A,a,epsilon,p):
VECTOR = 1 # See above. Here, it is 1 because we use math notation
nOptim = 0
xOptim = Matrix(m,m)
mathP = p+1 #We use mathP (p+1) because the algorithm is written in mathematical notation (k = 1,p). By employing the matrix API, we can directly use the mathematical notation
mathM = m+1 #We use mathM for the same reason we use mathP. It is used only for iterations, not defining sizes
B = Matrix(m,m)
B = copy.deepcopy(otherGaussSiedelB(A,m))
q0 = B.normOne()
q1 = B.infiniteNorm()
q = -1
norm = -1
if q0 < 1 or q1 < 1:
if q0 < 1:
q = q0
norm = 1
elif q1 < 1:
q = q1
norm = 999
#Initialize x
x = Matrix(m,VECTOR)
#print("X:")
#x.display()
x.mathInsert(random.randrange(1,mathM),VECTOR,random.randrange(1,5))
#print("X after first insertion:")
#x.display()
x.mathInsert(random.randrange(1,mathM)-1,VECTOR,random.randrange(1,5)+2)
#print("X after second insertion:")
#x.display()
x.mathInsert(random.randrange(1,mathM)-1,VECTOR,random.randrange(1,5)+7)
#print("X after third insertion:")
#x.display()
newX = copy.deepcopy(Matrix(m,VECTOR))
condition = True
iteration = 0
while condition:
iteration += 1
newX = copy.deepcopy(Matrix(m,VECTOR))
for i in range(1,mathM):
newElementOfX = otherGaussSiedelSum(B,x,a,i,mathM)
#print(">!< Haha")
newX.mathInsert(i,VECTOR,newElementOfX)
conditionValue = ( (q/(1-q))*computeNorm(x,newX,norm) )
condition = conditionValue > epsilon
'''
print("Old x:")
x.display()
print("New x:")
newX.display()
'''
for xIndex in range(1,mathM):
x.mathInsert(xIndex,VECTOR,newX.mathAt(xIndex,VECTOR))
'''
print("X after reasignment:")
x.display()
'''
#print("Iteration:",iteration," - ",conditionValue,"out of",epsilon,".")
print("===== Other Gauss Siedel =====")
print("Optim solution (x):")
x.display()
print("Test:")
result = A.multiplyMatrix(newX)
result.display()
print("====================")
else:
print("Else Other Gauss Siedel.")
