7d0297f3
 Chunk
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__author__ = 'chunk'
import numpy as np
import math
def norm(l):
s = 0
for item in l:
if np.absolute(item) > s:
s = np.absolute(item)
return s
def norm_vec(l):
s = 0
loc = 0
i = -1
for item in l:
i += 1
if np.absolute(item) > s:
s = np.absolute(item)
loc = i
return l[loc], np.array(l, dtype=np.float32) / l[loc]
def power_method(A, epsilon=0.00001, v=None):
n = len(A)
if v == None:
v = np.random.rand(n)
u = np.copy(v)
lmbda = None
lmbda_old = None
iter = 0
while lmbda_old is None or np.absolute(lmbda - lmbda_old) >= epsilon:
iter += 1
lmbda_old = lmbda
v = np.dot(A, u)
lmbda, u = norm_vec(v)
print iter, lmbda
return lmbda, u
def test():
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staged.
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ll = [0, 2, 0.5, 1, -3, 0.2]
ll2 = [i * 2 for i in ll]
print norm_vec(ll)
print norm_vec(ll2)
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7d0297f3
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A = [[5, -4, 1], [-4, 6, -4], [1, -4, 7]]
B = [[25, -41, 10, -6], [-41, 68, -17, 10], [10, -17, 5, -3], [-6, 10, -3, 2]]
print power_method(A)
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