equalizer: remove unused code

amodem/equalizer.py

@@ -38,32 +38,6 @@ class Equalizer(object):
                             omegas=self.omegas, Nsym=self.Nsym)
         return np.array(list(itertools.islice(symbols, size)))
 
-    def equalize_symbols(self, signal, symbols, order, lookahead=0):
-        assert symbols.shape[1] == self.Nfreq
-        length = symbols.shape[0]
-
-        matched = np.array(self.carriers) / (0.5*self.Nsym)
-        matched = matched[:, ::-1].transpose().conj()
-        signal = np.concatenate([signal, np.zeros(lookahead)])
-        y = dsp.lfilter(x=signal, b=matched, a=[1])
-
-        A = []
-        b = []
-
-        for j in range(self.Nfreq):
-            for i in range(length):
-                offset = (i+1)*self.Nsym
-                row = y[offset-order:offset+lookahead, j]
-                A.append(row)
-                b.append(symbols[i, j])
-
-        A = np.array(A)
-        b = np.array(b)
-        h = lstsq(A, b)[0]
-        h = h[::-1].real
-
-        return h
-
     def equalize_signal(self, signal, expected, order, lookahead=0):
         signal = [np.zeros(order-1), signal, np.zeros(lookahead)]
         signal = np.concatenate(signal)

tests/test_equalizer.py

@@ -45,31 +45,6 @@ def test_modem():
     assert_approx(sent, received)
 
 
-def test_symbols():
-    length = 100
-    gain = float(config.Nfreq)
-
-    e = equalizer.Equalizer(config)
-    symbols = e.train_symbols(length=length)
-    x = e.modulator(symbols) * gain
-    assert_approx(e.demodulator(x, size=length), symbols)
-
-    den = np.array([1, -0.6, 0.1])
-    num = np.array([0.5])
-    y = dsp.lfilter(x=x, b=num, a=den)
-
-    lookahead = 2
-    h = e.equalize_symbols(
-        signal=y, symbols=symbols, order=len(den), lookahead=lookahead
-    )
-    assert norm(h[:lookahead]) < 1e-12
-    assert_approx(h[lookahead:], den / num)
-
-    y = dsp.lfilter(x=y, b=h[lookahead:], a=[1])
-    z = e.demodulator(y, size=length)
-    assert_approx(z, symbols)
-
-
 def test_signal():
     length = 100
     x = np.sign(RandomState(0).normal(size=length))