rename sigproc -> dsp

tests/test_dsp.py

@@ -0,0 +1,88 @@
+import random
+import itertools
+import numpy as np
+from numpy.linalg import norm
+
+from amodem import dsp
+from amodem import config
+
+
+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
+    y = a * x + b
+    a_, b_ = dsp.linear_regression(x, y)
+    assert abs(a - a_) < 1e-10
+    assert abs(b - b_) < 1e-10
+
+
+def test_filter():
+    x = range(10)
+    y = dsp.lfilter(b=[1], a=[1], x=x)
+    assert (np.array(x) == y).all()
+
+    x = [1] + [0] * 10
+    y = dsp.lfilter(b=[0.5], a=[1, -0.5], x=x)
+    assert list(y) == [0.5 ** (i+1) for i in range(len(x))]
+
+
+def test_estimate():
+    r = np.random.RandomState(seed=0)
+    x = r.uniform(-1, 1, [1000])
+    x[:10] = 0
+    x[len(x)-10:] = 0
+
+    c = 1.23
+    y = c * x
+    c_, = sigproc.estimate(x=x, y=y, order=1)
+    assert abs(c - c_) < 1e-12
+
+    h = [1, 1]
+    y = sigproc.lfilter(b=h, a=[1], x=x)
+    h_ = sigproc.estimate(x=x, y=y, order=len(h))
+    assert norm(h - h_) < 1e-12
+
+    h = [0.1, 0.6, 0.9, 0.7, -0.2]
+    L = len(h) // 2
+
+    y = dsp.lfilter(b=h, a=[1], x=x)
+    h_ = dsp.estimate(
+        x=x[:len(x)-L], y=y[L:],
+        order=len(h), lookahead=L
+    )
+    assert norm(h - h_) < 1e-12
+
+    y_ = sigproc.lfilter(b=h_, a=[1], x=x)
+    assert norm(y - y_) < 1e-12