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__author__ = 'chunk'
import numpy as np
import math
def gen_hilbert(n):
return np.array([1.0 / (i + j + 1) for i in range(n) for j in range(n)]).reshape((n, -1))
def gen_b(n):
return np.array([1.0 / i for i in range(1, n + 1)])
def norm(l):
s = 0
for item in l:
if np.absolute(item) > s:
s = np.absolute(item)
return s
def jacobi(A, b, epsilon=0.0001, x=None):
n = len(A)
assert n == len(b)
if x is None:
x = np.zeros(n, dtype=np.float32)
x_old = None
D = np.diag(A)
R = A - np.diagflat(D)
# for i in range(N):
iter = 0
while x_old is None or norm(x - x_old) >= epsilon:
iter += 1
x_old = np.copy(x)
x = (b - np.dot(R, x_old)) / D
print iter, x
return x
def SOR(A, b, omega, epsilon=0.0001, x=None):
n = len(A)
assert n == len(b)
if x is None:
x = np.zeros(n, dtype=np.float32)
x_old = None
iter = 0
while x_old is None or norm(x - x_old) >= epsilon:
iter += 1
x_old = np.copy(x)
for i in range(n):
s = 0.0
for j in range(n):
if j != i:
s += A[i][j] * x[j]
x[i] = (1 - omega) * x[i] + omega * (b[i] - s) / A[i][i]
# print iter, x
return iter, x
def test():
# A = [[10, 3, 1], [2, -10, 3], [1, 3, 10]]
# b = [14, -5, 14]
# print SOR(A, b, 1.25)
# print jacobi(A, b)
n = 10
A = gen_hilbert(n)
b = gen_b(n)
# print jacobi(A, b)
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for w in np.linspace(0.5, 1.5, num=11):
iter, x = SOR(A, b, w)
# print "w:%f\titer:%d\tx:%s\t" % (w, iter, x)
# print "norm(delta):%s\n" % (norm(np.array([1.0] + [0.0] * (n - 1)) - x))
print "w:%f\titer:%d\tnorm(delta):%s\n" % (
w, iter, norm(np.array([1.0] + [0.0] * (n - 1)) - x))
if __name__ == '__main__':
test()
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