qam: refactor modulation out of dsp.py

tests/test_dsp.py

@@ -1,5 +1,3 @@
-import random
-import itertools
 import numpy as np
 from numpy.linalg import norm
 
@@ -8,38 +6,6 @@ from amodem import config
 from amodem import sampling
 
 
-def test_qam():
-    q = dsp.QAM(config.symbols)
-    r = random.Random(0)
-    m = q.bits_per_symbol
-    bits = [tuple(r.randint(0, 1) for j in range(m)) for i in range(1024)]
-    stream = itertools.chain(*bits)
-    S = list(q.encode(list(stream)))
-    decoded = list(q.decode(S))
-    assert decoded == bits
-
-    noise = lambda A: A*(r.uniform(-1, 1) + 1j*r.uniform(-1, 1))
-    noised_symbols = [(s + noise(1e-3)) for s in S]
-    decoded = list(q.decode(noised_symbols))
-    assert decoded == bits
-
-
-def quantize(q, s):
-    bits, = list(q.decode([s]))
-    r, = q.encode(bits)
-    index = np.argmin(np.abs(s - q.symbols))
-    expected = q.symbols[index]
-    assert r == expected
-
-
-def test_overflow():
-    q = dsp.QAM(config.symbols)
-    r = np.random.RandomState(seed=0)
-    for i in range(10000):
-        s = 10*(r.normal() + 1j * r.normal())
-        quantize(q, s)
-
-
 def test_linreg():
     x = np.array([1, 3, 2, 8, 4, 6, 9, 7, 0, 5])
     a, b = 12.3, 4.56