def test_beta():
N = 30
dv = 3
dc = 6
num_codewords = 10
H = get_H(N, dv, dc)
codewords = get_codewords(H, num_codewords)
p = 0.25
max_iter = 10
trials = 100
print 'GOT ALL CODEWORDS'
step = 0.1
b = np.arange(0, 0.5, step)
results = set()
for beta in b:
success_rate = [0] * num_codewords
print beta,
for i, word in enumerate(codewords):
for _ in xrange(trials):
codeword = word
codeword = convert_to_posneg(codeword)
codeword = simulateBEC(p, codeword)
f = FactorGraph(H)
codeword = f.decode_BEC_memoryless(codeword, beta, max_iter)
codeword = convert_to_zeroone(codeword)
if tuple(codeword) == word:
success_rate[i] += 1 / float(trials)
stat = np.average(success_rate)
print stat
results.add(tuple([beta, stat]))
print results
for point in results:
plt.plot(point[0], point[1], 'ro')
plt.show()
def test_beta():
N = 30
dv = 3
dc = 6
num_codewords = 10
H = get_H(N,dv,dc)
codewords = get_codewords(H, num_codewords)
p = 0.25
max_iter = 10
trials = 100
print 'GOT ALL CODEWORDS'
step = 0.1
b = np.arange(0, 0.5, step)
results = set()
for beta in b:
success_rate = [0] * num_codewords
print beta,
for i, word in enumerate(codewords):
for _ in xrange(trials):
codeword = word
codeword = convert_to_posneg(codeword)
codeword = simulateBEC(p, codeword)
f = FactorGraph(H)
codeword = f.decode_BEC_memoryless(codeword, beta, max_iter)
codeword = convert_to_zeroone(codeword)
if tuple(codeword) == word:
success_rate[i] += 1 / float(trials)
stat = np.average(success_rate)
print stat
results.add(tuple([beta, stat]))
print results
for point in results:
plt.plot(point[0], point[1], 'ro')
plt.show()
