def test_1024_rate_1_code():
# effectively a Monte-Carlo simulation for channel polarization.
ntests = 10000
n = 256
k = n
transition_prob = 0.11
num_transitions = int(k * transition_prob)
frozenbits = np.zeros(n - k)
frozenbitposition = np.array((), dtype=int)
encoder = PolarEncoder(n, k, frozenbitposition, frozenbits)
decoder = PolarDecoder(n, k, frozenbitposition, frozenbits)
channel_counter = np.zeros(k)
possible_indices = np.arange(n, dtype=int)
for i in range(ntests):
bits = np.random.randint(2, size=k)
tx = encoder.encode(bits)
np.random.shuffle(possible_indices)
tx[possible_indices[0:num_transitions]] = (tx[possible_indices[0:num_transitions]] + 1) % 2
rx = tx
recv = decoder.decode(rx)
channel_counter += (bits == recv)
print channel_counter
print(np.min(channel_counter), np.max(channel_counter))
np.save('channel_counter_' + str(ntests) + '.npy', channel_counter)
def test_1024_rate_1_code():
# effectively a Monte-Carlo simulation for channel polarization.
ntests = 10000
n = 256
k = n
transition_prob = 0.11
num_transitions = int(k * transition_prob)
frozenbits = np.zeros(n - k)
frozenbitposition = np.array((), dtype=int)
encoder = PolarEncoder(n, k, frozenbitposition, frozenbits)
decoder = PolarDecoder(n, k, frozenbitposition, frozenbits)
channel_counter = np.zeros(k)
possible_indices = np.arange(n, dtype=int)
for i in range(ntests):
bits = np.random.randint(2, size=k)
tx = encoder.encode(bits)
np.random.shuffle(possible_indices)
tx[possible_indices[0:num_transitions]] = (tx[possible_indices[0:num_transitions]] + 1) % 2
rx = tx
recv = decoder.decode(rx)
channel_counter += (bits == recv)
print channel_counter
print(np.min(channel_counter), np.max(channel_counter))
np.save('channel_counter_' + str(ntests) + '.npy', channel_counter)
def systematic_encoder_decoder_chain_test():
print('systematic encoder decoder chain test')
block_size = int(2 ** 8)
info_bit_size = block_size // 2
ntests = 100
frozenbitposition = cc.get_frozen_bit_indices_from_z_parameters(cc.bhattacharyya_bounds(0.0, block_size), block_size - info_bit_size)
encoder = PolarEncoder(block_size, info_bit_size, frozenbitposition)
decoder = PolarDecoder(block_size, info_bit_size, frozenbitposition)
for i in range(ntests):
bits = np.random.randint(2, size=info_bit_size)
y = encoder.encode_systematic(bits)
u_hat = decoder.decode_systematic(y)
assert (bits == u_hat).all()
def systematic_encoder_decoder_chain_test():
print('systematic encoder decoder chain test')
block_size = int(2**8)
info_bit_size = block_size // 2
ntests = 100
frozenbitposition = cc.get_frozen_bit_indices_from_z_parameters(
cc.bhattacharyya_bounds(0.0, block_size), block_size - info_bit_size)
encoder = PolarEncoder(block_size, info_bit_size, frozenbitposition)
decoder = PolarDecoder(block_size, info_bit_size, frozenbitposition)
for i in range(ntests):
bits = np.random.randint(2, size=info_bit_size)
y = encoder.encode_systematic(bits)
u_hat = decoder.decode_systematic(y)
assert (bits == u_hat).all()
def test_enc_dec_chain():
ntests = 100
n = 256
k = n // 2
frozenbits = np.zeros(n - k)
frozenbitposition = get_frozen_bit_position()
for i in range(ntests):
bits = np.random.randint(2, size=k)
encoder = PolarEncoder(n, k, frozenbitposition, frozenbits)
decoder = PolarDecoder(n, k, frozenbitposition, frozenbits)
encoded = encoder.encode(bits)
rx = decoder.decode(encoded)
if not is_equal(bits, rx):
raise ValueError('Test #', i, 'failed, input and output differ', bits, '!=', rx)
return
def test_enc_dec_chain():
ntests = 100
n = 256
k = n // 2
frozenbits = np.zeros(n - k)
frozenbitposition = get_frozen_bit_position()
for i in range(ntests):
bits = np.random.randint(2, size=k)
encoder = PolarEncoder(n, k, frozenbitposition, frozenbits)
decoder = PolarDecoder(n, k, frozenbitposition, frozenbits)
encoded = encoder.encode(bits)
rx = decoder.decode(encoded)
if not is_equal(bits, rx):
raise ValueError('Test #', i, 'failed, input and output differ', bits, '!=', rx)
return
