From f919f9dcbb54a08e6e26d6c229ce92fb784fa1b2 Mon Sep 17 00:00:00 2001
From: Tom Rondeau <trondeau@vt.edu>
Date: Fri, 13 Apr 2012 18:36:53 -0400
Subject: Removed whitespace and added dtools/bin/remove-whitespace as a tool
to do this in the future.
The sed script was provided by Moritz Fischer.
---
gr-trellis/src/examples/python/fsm_utils.py | 14 +++++++-------
1 file changed, 7 insertions(+), 7 deletions(-)
(limited to 'gr-trellis/src/examples/python/fsm_utils.py')
diff --git a/gr-trellis/src/examples/python/fsm_utils.py b/gr-trellis/src/examples/python/fsm_utils.py
index e9243f8999..06855ea775 100755
--- a/gr-trellis/src/examples/python/fsm_utils.py
+++ b/gr-trellis/src/examples/python/fsm_utils.py
@@ -72,7 +72,7 @@ def base2dec(s,base):
# 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.
+# channel outputs to metrics for use with the Viterbi algorithm.
# Limitations: currently supports only one-dimensional modulations.
######################################################################
def make_isi_lookup(mod,channel,normalize):
@@ -102,7 +102,7 @@ def make_isi_lookup(mod,channel,normalize):
######################################################################
# Automatically generate the signals appropriate for CPM
-# decomposition.
+# 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
@@ -118,7 +118,7 @@ def make_cpm_signals(K,P,M,L,q,frac):
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)
-
+
X=(M**L)*P
PSI=numpy.empty((X,Q))
for x in range(X):
@@ -133,9 +133,9 @@ def make_cpm_signals(K,P,M,L,q,frac):
PSI = numpy.transpose(PSI)
SS=numpy.exp(1j*PSI) # contains all signals as columns
#print SS
-
- # Now we need to orthogonalize the signals
+
+ # Now we need to orthogonalize the signals
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)
@@ -162,11 +162,11 @@ def make_cpm_signals(K,P,M,L,q,frac):
#print Ff
Sf = S[Esi[0:v0+1]]
#print Sf
-
+
return (f0,SS,S,F,Sf,Ff,N)
#return f0
-
+
--
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