def test_audio(systematic, log, sparse):
n = 25
d_v = 4
d_c = 5
seed = 0
rnd = np.random.RandomState(seed)
H, G = make_ldpc(n,
d_v,
d_c,
seed=seed,
systematic=systematic,
sparse=sparse)
assert not binaryproduct(H, G).any()
n, k = G.shape
print(k)
snr = 1000
audio = rnd.randint(0, 255, size=5)
audio_bin = audio2bin(audio)
coded, noisy = ldpc_audio.encode_audio(G, audio_bin, snr, seed)
x = ldpc_audio.decode_audio(G, H, coded, snr, maxiter=10, log=log)
ber = ldpc_audio.ber_audio(audio_bin, audio2bin(x))
assert ber == 0
def test_image_rgb(systematic, log, sparse):
n = 26
d_v = 1
d_c = 2
seed = 0
rnd = np.random.RandomState(seed)
H, G = make_ldpc(n,
d_v,
d_c,
seed=seed,
systematic=systematic,
sparse=sparse)
assert not binaryproduct(H, G).any()
n, k = G.shape
snr = 100
img = rnd.randint(0, 255, size=(3, 3, 3))
img_bin = rgb2bin(img)
coded, noisy = ldpc_images.encode_img(G, img_bin, snr, seed)
x = ldpc_images.decode_img(G, H, coded, snr, maxiter=100, log=log)
assert ldpc_images.ber_img(img_bin, rgb2bin(x)) == 0
def test_image_gray(systematic, sparse):
n = 100
d_v = 3
d_c = 4
seed = 0
rnd = np.random.RandomState(seed)
H, G = make_ldpc(n,
d_v,
d_c,
seed=seed,
systematic=systematic,
sparse=sparse)
assert not binaryproduct(H, G).any()
n, k = G.shape
snr = 10
img = rnd.randint(0, 255, size=(3, 3))
img_bin = gray2bin(img)
img_shape = img_bin.shape
coded, noisy = ldpc_images.encode_img(G, img_bin, snr, seed)
x = ldpc_images.decode_img(G, H, coded, snr, img_shape=img_shape)
assert ldpc_images.ber_img(img_bin, gray2bin(x)) == 0
def test_decoding_did_not_converge(systematic, sparse):
n = 15
d_v = 4
d_c = 5
seed = 0
H, G = make_ldpc(n, d_v, d_c, seed=seed, systematic=systematic,
sparse=sparse)
assert not binaryproduct(H, G).any()
n, k = G.shape
snr = 1
v = np.arange(k) % 2
y = encode(G, v, snr, seed=seed)
with pytest.warns(UserWarning, match="stopped before convergence"):
decode(H, y, snr, maxiter=1)
def test_decoding_random(systematic, sparse):
n = 15
d_v = 4
d_c = 5
seed = 0
H, G = make_ldpc(n, d_v, d_c, seed=seed, systematic=systematic,
sparse=sparse)
assert not binaryproduct(H, G).any()
n, k = G.shape
snr = 100
v, y = encode_random_message(G, snr, seed)
d = decode(H, y, snr)
x = get_message(G, d)
assert abs(v - x).sum() == 0
def test_audio(systematic, sparse):
n = 48
d_v = 2
d_c = 3
seed = 0
rnd = np.random.RandomState(seed)
H, G = make_ldpc(n,
d_v,
d_c,
seed=seed,
systematic=systematic,
sparse=sparse)
assert not binaryproduct(H, G).any()
n, k = G.shape
snr = 10
audio = rnd.randint(0, 255, size=2)
audio_bin = audio2bin(audio)
coded, noisy = ldpc_audio.encode_audio(G, audio_bin, snr, seed)
x = ldpc_audio.decode_audio(G, H, coded, snr, audio_bin.shape)
ber = ldpc_audio.ber_audio(audio_bin, audio2bin(x))
assert ber == 0
def test_decoding(systematic, log, sparse):
n = 15
d_v = 4
d_c = 5
seed = 0
H, G = make_ldpc(n,
d_v,
d_c,
seed=seed,
systematic=systematic,
sparse=sparse)
assert not binaryproduct(H, G).any()
n, k = G.shape
snr = 100
v = np.arange(k) % 2
y = encode(G, v, snr, seed)
d = decode(H, y, snr, maxiter=10, log=log)
x = get_message(G, d)
assert abs(v - x).sum() == 0
