refactor QAM object into MODEM

tests/test_dsp.py

@@ -5,6 +5,9 @@ from amodem import dsp
 from amodem import config
 from amodem import sampling
 
+import random
+import itertools
+
 
 def test_linreg():
     x = np.array([1, 3, 2, 8, 4, 6, 9, 7, 0, 5])
@@ -63,3 +66,35 @@ def test_demux():
     res = dsp.Demux(sampling.Sampler(sig.real), freqs)
     res = np.array(list(res))
     assert np.max(np.abs(res - syms)) < 1e-12
+
+
+def test_qam():
+    q = dsp.MODEM(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.MODEM(config.symbols)
+    r = np.random.RandomState(seed=0)
+    for i in range(10000):
+        s = 10*(r.normal() + 1j * r.normal())
+        quantize(q, s)

tests/test_qam.py

@@ -1,39 +0,0 @@
-import random
-import itertools
-
-import numpy as np
-
-from amodem import qam
-from amodem import config
-
-
-def test_qam():
-    q = qam.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 = qam.QAM(config.symbols)
-    r = np.random.RandomState(seed=0)
-    for i in range(10000):
-        s = 10*(r.normal() + 1j * r.normal())
-        quantize(q, s)