diff options
Diffstat (limited to 'gr-trellis/python/trellis/fsm_utils.py')
| -rw-r--r--[-rwxr-xr-x] | gr-trellis/python/trellis/fsm_utils.py | 90 |
1 files changed, 47 insertions, 43 deletions
diff --git a/gr-trellis/python/trellis/fsm_utils.py b/gr-trellis/python/trellis/fsm_utils.py index f4076623a5..25c552a226 100755..100644 --- a/gr-trellis/python/trellis/fsm_utils.py +++ b/gr-trellis/python/trellis/fsm_utils.py @@ -20,18 +20,19 @@ # Boston, MA 02110-1301, USA. # -import re +from __future__ import print_function +from __future__ import division +from __future__ import unicode_literals + import math import sys -import operator -import numpy -#from gnuradio import trellis +import numpy try: import scipy.linalg except ImportError: - print "Error: Program requires scipy (see: www.scipy.org)." + print("Error: Program requires scipy (see: www.scipy.org).") sys.exit(1) @@ -41,13 +42,13 @@ def dec2base(num, base, l): Convert 'num' to a list of 'l' numbers representing 'num' to base 'base' (most significant symbol first). """ - s = range(l) + s = list(range(l)) n = num for i in range(l): - s[l - i - 1] = n % base - n = int(n / base) - if n != 0: - print 'Number ', num, ' requires more than ', l, 'digits.' + s[l-i-1]=n%base + n=int(n / base) + if n!=0: + print('Number ', num, ' requires more than ', l, 'digits.') return s @@ -82,14 +83,14 @@ def make_isi_lookup(mod, channel, normalize): for i in range(len(channel)): channel[i] = channel[i] / math.sqrt(p) - lookup = range(len(constellation)**len(channel)) + lookup=list(range(len(constellation)**len(channel))) for o in range(len(constellation)**len(channel)): 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) + ll=ll+constellation[ss[i]]*channel[i] + lookup[o]=ll + return (1,lookup) def make_cpm_signals(K, P, M, L, q, frac): @@ -115,43 +116,46 @@ def make_cpm_signals(K, P, M, L, q, frac): 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 - PSI[x] = psi - PSI = numpy.transpose(PSI) - SS = numpy.exp(1j * PSI) # contains all signals as columns + 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) + # 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) - #print F - #print S + 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) + #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) - #print 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) - #print Ecum - 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]]) - #print Ff - Sf = S[Esi[0:v0 + 1]] - #print Sf + #print(Es) + #print(Esi) + Ecum=numpy.cumsum(Es) + #print(Ecum) + 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]]) + #print(Ff) + Sf = S[Esi[0:v0+1]] + #print(Sf) return (f0, SS, S, F, Sf, Ff, N) |