refactor recv

recv.py

@@ -9,10 +9,10 @@ log = logging.getLogger(__name__)
 import sigproc
 from common import *
 
-COHERENCE_THRESHOLD = 0.9
+COHERENCE_THRESHOLD = 0.95
 
 CARRIER_DURATION = 300
-CARRIER_THRESHOLD = int(0.9 * CARRIER_DURATION)
+CARRIER_THRESHOLD = int(0.95 * CARRIER_DURATION)
 
 def power(x):
     return np.dot(x.conj(), x).real / len(x)
@@ -29,7 +29,8 @@ def coherence(x, freq):
 
 def detect(x, freq):
     counter = 0
-    for offset, coeff in iterate(x, Nsym, advance=Nsym, func=lambda x: coherence(x, Fc)):
+    for offset, buf in iterate(x, Nsym, advance=Nsym):
+        coeff = coherence(buf, Fc)
         if abs(coeff) > COHERENCE_THRESHOLD:
             counter += 1
         else:
@@ -48,7 +49,7 @@ def find_start(x, start):
     Hc = exp_iwt(Fc, len(x_))
     P = np.abs(Hc.conj() * x_) ** 2
     cumsumP = P.cumsum()
-    start = np.argmax(cumsumP[length:] - cumsumP[:-length]) + begin
+    start = begin + np.argmax(cumsumP[length:] - cumsumP[:-length])
     log.info('Carrier starts at {:.3f} ms'.format(start * Tsym * 1e3 / Nsym))
     return start
 
@@ -60,15 +61,14 @@ def extract_symbols(x, freq, offset=0):
 
 def demodulate(x, freq, filt):
     S = extract_symbols(x, freq)
-    S = np.array(list(filt.apply(S)))
-    #constellation(S)
+    S = filt(S)
     for bits in sigproc.modulator.decode(S):  # list of bit tuples
         yield bits
 
-def equalize(x, freqs):
+def receive(x, freqs):
     prefix = [1]*300 + [0]*100
-    symbols = list(itertools.islice(extract_symbols(x, Fc), len(prefix)))
-    bits = np.round(np.abs(symbols))
+    symbols = itertools.islice(extract_symbols(x, Fc), len(prefix))
+    bits = np.round(np.abs(list(symbols)))
     bits = np.array(bits, dtype=int)
     if all(bits[:len(prefix)] != prefix):
         return None
@@ -80,10 +80,10 @@ def equalize(x, freqs):
         training = ([1]*10 + [0]*10)*20 + [0]*100
         S = list(itertools.islice(extract_symbols(x, freq), len(training)))
 
-        filt = sigproc.Filter.train(S, training)
+        filt = sigproc.train(S, training)
         filters[freq] = filt
 
-        S = list(filt.apply(S))
+        S = list(filt(S))
         y = np.array(S).real
 
         train_result = y > 0.5
@@ -149,7 +149,7 @@ def main(fname):
     if peak > SATURATION_THRESHOLD:
         raise ValueError('Saturation detected: {:.3f}'.format(peak))
 
-    data_bits = equalize(x / amp, frequencies)
+    data_bits = receive(x / amp, frequencies)
     if data_bits is None:
         log.info('Cannot demodulate symbols!')
     else: