def test_rans():
x = rans.x_init
scale_bits = 8
starts = rng.randint(0, 256, size=1000)
freqs = rng.randint(1, 256, size=1000) % (256 - starts)
freqs[freqs == 0] = 1
assert np.all(starts + freqs <= 256)
print("Exact entropy: " + str(np.sum(np.log2(256 / freqs))) + " bits.")
# Encode
for start, freq in zip(starts, freqs):
x = rans.append(x, start, freq, scale_bits)
coded_arr = rans.flatten(x)
assert coded_arr.dtype == np.uint32
print("Actual output size: " + str(32 * len(coded_arr)) + " bits.")
# Decode
x = rans.unflatten(coded_arr)
for start, freq in reversed(list(zip(starts, freqs))):
def statfun(cf):
assert start <= cf < start + freq
return None, (start, freq)
x, symbol = rans.pop(x, statfun, scale_bits)
assert x == (rans.head_min, ())
def test_flatten_unflatten():
state = rans.x_init
some_bits = rng.randint(1 << 8, size=5)
for b in some_bits:
state = rans.append(state, b, 1, 8)
flat = rans.flatten(state)
state_ = rans.unflatten(flat)
flat_ = rans.flatten(state_)
assert np.all(flat == flat_)
assert state == state_