train: remove unneeded file

amodem/detect.py

@@ -6,7 +6,7 @@ import collections
 log = logging.getLogger(__name__)
 
 from . import dsp
-from . import train
+from . import equalizer
 from . import common
 
 
@@ -14,7 +14,7 @@ class Detector(object):
 
     COHERENCE_THRESHOLD = 0.9
 
-    CARRIER_DURATION = sum(train.prefix)
+    CARRIER_DURATION = sum(equalizer.prefix)
     CARRIER_THRESHOLD = int(0.9 * CARRIER_DURATION)
     SEARCH_WINDOW = int(0.1 * CARRIER_DURATION)
 

amodem/equalizer.py

@@ -58,3 +58,8 @@ def train(signal, expected, order, lookahead=0):
     h = lstsq(A, b)[0]
     h = h[::-1].real
     return h
+
+
+prefix = [1]*400 + [0]*50
+equalizer_length = 500
+silence_length = 100

amodem/recv.py

@@ -9,7 +9,6 @@ log = logging.getLogger(__name__)
 from . import stream
 from . import dsp
 from . import sampling
-from . import train
 from . import common
 from . import framing
 from . import equalizer
@@ -33,7 +32,7 @@ class Receiver(object):
         self.output_size = 0  # number of bytes written to output stream
 
     def _prefix(self, symbols, gain=1.0, skip=5):
-        S = common.take(symbols, len(train.prefix))
+        S = common.take(symbols, len(equalizer.prefix))
         S = S[:, self.carrier_index] * gain
         sliced = np.round(np.abs(S))
         self.plt.figure()
@@ -43,13 +42,13 @@ class Receiver(object):
         bits = np.array(sliced, dtype=int)
         self.plt.subplot(122)
         self.plt.plot(np.abs(S))
-        self.plt.plot(train.prefix)
-        if any(bits != train.prefix):
+        self.plt.plot(equalizer.prefix)
+        if any(bits != equalizer.prefix):
             raise ValueError('Incorrect prefix')
 
         log.debug('Prefix OK')
 
-        nonzeros = np.array(train.prefix, dtype=bool)
+        nonzeros = np.array(equalizer.prefix, dtype=bool)
         pilot_tone = S[nonzeros]
         phase = np.unwrap(np.angle(pilot_tone)) / (2 * np.pi)
         indices = np.arange(len(phase))
@@ -68,11 +67,12 @@ class Receiver(object):
 
     def _train(self, sampler, order, lookahead):
         Nfreq = len(self.frequencies)
-        train_symbols = self.equalizer.train_symbols(train.equalizer_length)
+        equalizer_length = equalizer.equalizer_length
+        train_symbols = self.equalizer.train_symbols(equalizer_length)
         train_signal = self.equalizer.modulator(train_symbols) * Nfreq
 
-        prefix = postfix = train.silence_length * self.Nsym
-        signal_length = train.equalizer_length * self.Nsym + prefix + postfix
+        prefix = postfix = equalizer.silence_length * self.Nsym
+        signal_length = equalizer_length * self.Nsym + prefix + postfix
 
         signal = sampler.take(signal_length + lookahead)
 
@@ -92,7 +92,8 @@ class Receiver(object):
         return equalization_filter
 
     def _verify_training(self, equalized, train_symbols):
-        symbols = self.equalizer.demodulator(equalized, train.equalizer_length)
+        equalizer_length = equalizer.equalizer_length
+        symbols = self.equalizer.demodulator(equalized, equalizer_length)
         sliced = np.array(symbols).round()
         errors = np.array(sliced - train_symbols, dtype=np.bool)
         error_rate = errors.sum() / errors.size

amodem/send.py

@@ -4,8 +4,6 @@ import itertools
 
 log = logging.getLogger(__name__)
 
-from . import train
-
 from . import common
 from . import stream
 from . import framing
@@ -20,7 +18,7 @@ class Sender(object):
         self.modem = dsp.MODEM(config.symbols)
         self.carriers = config.carriers / config.Nfreq
         self.pilot = config.carriers[config.carrier_index]
-        self.silence = np.zeros(train.silence_length * config.Nsym)
+        self.silence = np.zeros(equalizer.silence_length * config.Nsym)
         self.iters_per_report = config.baud  # report once per second
         self.padding = [0] * config.bits_per_baud
         self.equalizer = equalizer.Equalizer(config)
@@ -32,10 +30,10 @@ class Sender(object):
         self.offset += len(sym)
 
     def start(self):
-        for value in train.prefix:
+        for value in equalizer.prefix:
             self.write(self.pilot * value)
 
-        symbols = self.equalizer.train_symbols(train.equalizer_length)
+        symbols = self.equalizer.train_symbols(equalizer.equalizer_length)
         signal = self.equalizer.modulator(symbols)
         self.write(self.silence)
         self.write(signal)

amodem/train.py

@@ -1,3 +0,0 @@
-prefix = [1]*400 + [0]*50
-equalizer_length = 500
-silence_length = 100

tests/test_detect.py

@@ -4,14 +4,14 @@ import pytest
 from amodem import dsp
 from amodem import recv
 from amodem import detect
-from amodem import train
+from amodem import equalizer
 from amodem import sampling
 from amodem import config
 config = config.fastest()
 
 
 def test_detect():
-    P = sum(train.prefix)
+    P = sum(equalizer.prefix)
     t = np.arange(P * config.Nsym) * config.Ts
     x = np.cos(2 * np.pi * config.Fc * t)
 
@@ -31,7 +31,7 @@ def test_detect():
 def test_prefix():
     omega = 2 * np.pi * config.Fc / config.Fs
     symbol = np.cos(omega * np.arange(config.Nsym))
-    signal = np.concatenate([c * symbol for c in train.prefix])
+    signal = np.concatenate([c * symbol for c in equalizer.prefix])
 
     def symbols_stream(signal):
         sampler = sampling.Sampler(signal)