refactor Filter at sigproc

sigproc.py

@@ -4,26 +4,26 @@ from numpy import linalg
 import common
 
 
-def lfilter(b, a, x):
-    b = np.array(b) / a[0]
-    a = np.array(a[1:]) / a[0]
+class Filter(object):
+    def __init__(self, b, a):
+        self.b = np.array(b) / a[0]
+        self.a = np.array(a[1:]) / a[0]
 
-    x_ = [0] * len(b)
-    y_ = [0] * len(a)
-    for v in x:
-        x_ = [v] + x_[:-1]
-        u = np.dot(x_, b)
-        u = u - np.dot(y_, a)
-
-        y_ = [u] + y_[1:]
-        yield u
+    def __call__(self, x):
+        x_ = [0] * len(self.b)
+        y_ = [0] * len(self.a)
+        for v in x:
+            x_ = [v] + x_[:-1]
+            y = np.dot(x_, self.b) - np.dot(y_, self.a)
+            y_ = [y] + y_[1:]
+            yield y
 
 
 def train(S, training):
     A = np.array([S[1:], S[:-1], training[:-1]]).T
     b = training[1:]
     b0, b1, a1 = linalg.lstsq(A, b)[0]
-    return lambda x: lfilter(b=[b0, b1], a=[1, -a1], x=x)
+    return Filter(b=[b0, b1], a=[1, -a1])
 
 
 class QAM(object):
@@ -63,7 +63,8 @@ class QAM(object):
 
 modulator = QAM(common.symbols)
 
-modem_bps = common.baud * modulator.bits_per_symbol * len(common.frequencies)
+bits_per_baud = modulator.bits_per_symbol * len(common.frequencies)
+modem_bps = common.baud * bits_per_baud
 
 
 def clip(x, lims):