From add88dc7387ef41efb2c6aca9e2eccbf311e8f3d Mon Sep 17 00:00:00 2001
From: Marcus Müller <mueller@kit.edu>
Date: Mon, 18 Jun 2018 11:36:54 +0200
Subject: increased PEP compliance of fsm_utils
---
gr-trellis/python/trellis/fsm_utils.py | 177 +++++++++++++++------------------
1 file changed, 82 insertions(+), 95 deletions(-)
(limited to 'gr-trellis/python/trellis/fsm_utils.py')
diff --git a/gr-trellis/python/trellis/fsm_utils.py b/gr-trellis/python/trellis/fsm_utils.py
index 72aa1d3660..f4076623a5 100755
--- a/gr-trellis/python/trellis/fsm_utils.py
+++ b/gr-trellis/python/trellis/fsm_utils.py
@@ -20,7 +20,6 @@
# Boston, MA 02110-1301, USA.
#
-
import re
import math
import sys
@@ -36,47 +35,44 @@ except ImportError:
sys.exit(1)
-
-######################################################################
-# Decimal to any base conversion.
-# Convert 'num' to a list of 'l' numbers representing 'num'
-# to base 'base' (most significant symbol first).
-######################################################################
-def dec2base(num,base,l):
- s=range(l)
- n=num
+def dec2base(num, base, l):
+ """
+ Decimal to any base conversion.
+ Convert 'num' to a list of 'l' numbers representing 'num'
+ to base 'base' (most significant symbol first).
+ """
+ s = range(l)
+ n = num
for i in range(l):
- s[l-i-1]=n%base
- n=int(n/base)
- if n!=0:
+ s[l - i - 1] = n % base
+ n = int(n / base)
+ if n != 0:
print 'Number ', num, ' requires more than ', l, 'digits.'
return s
-######################################################################
-# Conversion from any base to decimal.
-# Convert a list 's' of symbols to a decimal number
-# (most significant symbol first)
-######################################################################
-def base2dec(s,base):
- num=0
+def base2dec(s, base):
+ """
+ Conversion from any base to decimal.
+ Convert a list 's' of symbols to a decimal number
+ (most significant symbol first)
+ """
+ num = 0
for i in range(len(s)):
- num=num*base+s[i]
+ num = num * base + s[i]
return num
-
-
-######################################################################
-# Automatically generate the lookup table that maps the FSM outputs
-# to channel inputs corresponding to a channel 'channel' and a modulation
-# 'mod'. Optional normalization of channel to unit energy.
-# This table is used by the 'metrics' block to translate
-# channel outputs to metrics for use with the Viterbi algorithm.
-# Limitations: currently supports only one-dimensional modulations.
-######################################################################
-def make_isi_lookup(mod,channel,normalize):
- dim=mod[0]
+def make_isi_lookup(mod, channel, normalize):
+ """
+ Automatically generate the lookup table that maps the FSM outputs
+ to channel inputs corresponding to a channel 'channel' and a modulation
+ 'mod'. Optional normalization of channel to unit energy.
+ This table is used by the 'metrics' block to translate
+ channel outputs to metrics for use with the Viterbi algorithm.
+ Limitations: currently supports only one-dimensional modulations.
+ """
+ dim = mod[0]
constellation = mod[1]
if normalize:
@@ -84,104 +80,96 @@ def make_isi_lookup(mod,channel,normalize):
for i in range(len(channel)):
p = p + channel[i]**2
for i in range(len(channel)):
- channel[i] = channel[i]/math.sqrt(p)
+ channel[i] = channel[i] / math.sqrt(p)
- lookup=range(len(constellation)**len(channel))
+ lookup = range(len(constellation)**len(channel))
for o in range(len(constellation)**len(channel)):
- ss=dec2base(o,len(constellation),len(channel))
- ll=0
+ ss = dec2base(o, len(constellation), len(channel))
+ ll = 0
for i in range(len(channel)):
- ll=ll+constellation[ss[i]]*channel[i]
- lookup[o]=ll
- return (1,lookup)
-
-
-
-
-
-
-######################################################################
-# Automatically generate the signals appropriate for CPM
-# decomposition.
-# This decomposition is based on the paper by B. Rimoldi
-# "A decomposition approach to CPM", IEEE Trans. Info Theory, March 1988
-# See also my own notes at http://www.eecs.umich.edu/~anastas/docs/cpm.pdf
-######################################################################
-def make_cpm_signals(K,P,M,L,q,frac):
-
- Q=numpy.size(q)/L
- h=(1.0*K)/P
- f0=-h*(M-1)/2
- dt=0.0; # maybe start at t=0.5
- t=(dt+numpy.arange(0,Q))/Q
- qq=numpy.zeros(Q)
+ ll = ll + constellation[ss[i]] * channel[i]
+ lookup[o] = ll
+ return (1, lookup)
+
+
+def make_cpm_signals(K, P, M, L, q, frac):
+ """
+ Automatically generate the signals appropriate for CPM
+ decomposition.
+ This decomposition is based on the paper by B. Rimoldi
+ "A decomposition approach to CPM", IEEE Trans. Info Theory, March 1988
+ See also my own notes at http://www.eecs.umich.edu/~anastas/docs/cpm.pdf
+ """
+ Q = numpy.size(q) / L
+ h = (1.0 * K) / P
+ f0 = -h * (M - 1) / 2
+ dt = 0.0
+ # maybe start at t=0.5
+ t = (dt + numpy.arange(0, Q)) / Q
+ qq = numpy.zeros(Q)
for m in range(L):
- qq=qq + q[m*Q:m*Q+Q]
- w=math.pi*h*(M-1)*t-2*math.pi*h*(M-1)*qq+math.pi*h*(L-1)*(M-1)
+ qq = qq + q[m * Q:m * Q + Q]
+ w = math.pi * h * (M - 1) * t - 2 * math.pi * h * (
+ M - 1) * qq + math.pi * h * (L - 1) * (M - 1)
- X=(M**L)*P
- PSI=numpy.empty((X,Q))
+ X = (M**L) * P
+ PSI = numpy.empty((X, Q))
for x in range(X):
- xv=dec2base(x/P,M,L)
- xv=numpy.append(xv, x%P)
- qq1=numpy.zeros(Q)
- for m in range(L):
- qq1=qq1+xv[m]*q[m*Q:m*Q+Q]
- psi=2*math.pi*h*xv[-1]+4*math.pi*h*qq1+w
- #print psi
- PSI[x]=psi
- PSI = numpy.transpose(PSI)
- SS=numpy.exp(1j*PSI) # contains all signals as columns
- #print SS
-
+ xv = dec2base(x / P, M, L)
+ xv = numpy.append(xv, x % P)
+ qq1 = numpy.zeros(Q)
+ for m in range(L):
+ qq1 = qq1 + xv[m] * q[m * Q:m * Q + Q]
+ psi = 2 * math.pi * h * xv[-1] + 4 * math.pi * h * qq1 + w
+ PSI[x] = psi
+ PSI = numpy.transpose(PSI)
+ SS = numpy.exp(1j * PSI) # contains all signals as columns
# Now we need to orthogonalize the signals
- F = scipy.linalg.orth(SS) # find an orthonormal basis for SS
+ F = scipy.linalg.orth(SS) # find an orthonormal basis for SS
#print numpy.dot(numpy.transpose(F.conjugate()),F) # check for orthonormality
- S = numpy.dot(numpy.transpose(F.conjugate()),SS)
+ S = numpy.dot(numpy.transpose(F.conjugate()), SS)
#print F
#print S
# We only want to keep those dimensions that contain most
# of the energy of the overall constellation (eg, frac=0.9 ==> 90%)
# evaluate mean energy in each dimension
- E=numpy.sum(numpy.absolute(S)**2,axis=1)/Q
- E=E/numpy.sum(E)
+ E = numpy.sum(numpy.absolute(S)**2, axis=1) / Q
+ E = E / numpy.sum(E)
#print E
Es = -numpy.sort(-E)
Esi = numpy.argsort(-E)
#print Es
#print Esi
- Ecum=numpy.cumsum(Es)
+ Ecum = numpy.cumsum(Es)
#print Ecum
- v0=numpy.searchsorted(Ecum,frac)
- N = v0+1
+ v0 = numpy.searchsorted(Ecum, frac)
+ N = v0 + 1
#print v0
#print Esi[0:v0+1]
- Ff=numpy.transpose(numpy.transpose(F)[Esi[0:v0+1]])
+ Ff = numpy.transpose(numpy.transpose(F)[Esi[0:v0 + 1]])
#print Ff
- Sf = S[Esi[0:v0+1]]
+ Sf = S[Esi[0:v0 + 1]]
#print Sf
-
- return (f0,SS,S,F,Sf,Ff,N)
- #return f0
-
+ return (f0, SS, S, F, Sf, Ff, N)
+#return f0
######################################################################
# A list of common modulations.
# Format: (dimensionality,constellation)
######################################################################
-pam2 = (1,[-1, 1])
-pam4 = (1,[-3, -1, 3, 1]) # includes Gray mapping
-pam8 = (1,[-7, -5, -3, -1, 1, 3, 5, 7])
+pam2 = (1, [-1, 1])
+pam4 = (1, [-3, -1, 3, 1]) # includes Gray mapping
+pam8 = (1, [-7, -5, -3, -1, 1, 3, 5, 7])
psk4=(2,[1, 0, \
0, 1, \
0, -1,\
- -1, 0]) # includes Gray mapping
+ -1, 0]) # includes Gray mapping
psk8=(2,[math.cos(2*math.pi*0/8), math.sin(2*math.pi*0/8), \
math.cos(2*math.pi*1/8), math.sin(2*math.pi*1/8), \
@@ -231,4 +219,3 @@ orth4=(4,[1, 0, 0, 0, \
# C test channel (J. Proakis, Digital Communications, McGraw-Hill Inc., 2001)
c_channel = [0.227, 0.460, 0.688, 0.460, 0.227]
-
--
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