#!/usr/bin/env python # # Copyright 2009,2012 Free Software Foundation, Inc. # # This file is part of GNU Radio # # GNU Radio is free software; you can redistribute it and/or modify # it under the terms of the GNU General Public License as published by # the Free Software Foundation; either version 3, or (at your option) # any later version. # # GNU Radio is distributed in the hope that it will be useful, # but WITHOUT ANY WARRANTY; without even the implied warranty of # MERCHANTABILITY or FITNESS FOR A PARTICULAR PURPOSE. See the # GNU General Public License for more details. # # You should have received a copy of the GNU General Public License # along with GNU Radio; see the file COPYING. If not, write to # the Free Software Foundation, Inc., 51 Franklin Street, # Boston, MA 02110-1301, USA. # from gnuradio import gr, blks2 from gnuradio import filter import sys, time try: import scipy from scipy import fftpack except ImportError: print "Error: Program requires scipy (see: www.scipy.org)." sys.exit(1) try: import pylab from pylab import mlab except ImportError: print "Error: Program requires matplotlib (see: matplotlib.sourceforge.net)." sys.exit(1) class pfb_top_block(gr.top_block): def __init__(self): gr.top_block.__init__(self) self._N = 2000000 # number of samples to use self._fs = 1000 # initial sampling rate self._M = M = 9 # Number of channels to channelize self._ifs = M*self._fs # initial sampling rate # Create a set of taps for the PFB channelizer self._taps = filter.firdes.low_pass_2(1, self._ifs, 475.50, 50, attenuation_dB=100, window=filter.firdes.WIN_BLACKMAN_hARRIS) # Calculate the number of taps per channel for our own information tpc = scipy.ceil(float(len(self._taps)) / float(self._M)) print "Number of taps: ", len(self._taps) print "Number of channels: ", self._M print "Taps per channel: ", tpc # Create a set of signals at different frequencies # freqs lists the frequencies of the signals that get stored # in the list "signals", which then get summed together self.signals = list() self.add = gr.add_cc() freqs = [-70, -50, -30, -10, 10, 20, 40, 60, 80] for i in xrange(len(freqs)): f = freqs[i] + (M/2-M+i+1)*self._fs self.signals.append(gr.sig_source_c(self._ifs, gr.GR_SIN_WAVE, f, 1)) self.connect(self.signals[i], (self.add,i)) self.head = gr.head(gr.sizeof_gr_complex, self._N) # Construct the channelizer filter self.pfb = filter.pfb.channelizer_ccf(self._M, self._taps, 1) # Construct a vector sink for the input signal to the channelizer self.snk_i = gr.vector_sink_c() # Connect the blocks self.connect(self.add, self.head, self.pfb) self.connect(self.add, self.snk_i) # Use this to play with the channel mapping #self.pfb.set_channel_map([5,6,7,8,0,1,2,3,4]) # Create a vector sink for each of M output channels of the filter and connect it self.snks = list() for i in xrange(self._M): self.snks.append(gr.vector_sink_c()) self.connect((self.pfb, i), self.snks[i]) def main(): tstart = time.time() tb = pfb_top_block() tb.run() tend = time.time() print "Run time: %f" % (tend - tstart) if 1: fig_in = pylab.figure(1, figsize=(16,9), facecolor="w") fig1 = pylab.figure(2, figsize=(16,9), facecolor="w") fig2 = pylab.figure(3, figsize=(16,9), facecolor="w") Ns = 1000 Ne = 10000 fftlen = 8192 winfunc = scipy.blackman fs = tb._ifs # Plot the input signal on its own figure d = tb.snk_i.data()[Ns:Ne] spin_f = fig_in.add_subplot(2, 1, 1) X,freq = mlab.psd(d, NFFT=fftlen, noverlap=fftlen/4, Fs=fs, window = lambda d: d*winfunc(fftlen), scale_by_freq=True) X_in = 10.0*scipy.log10(abs(X)) f_in = scipy.arange(-fs/2.0, fs/2.0, fs/float(X_in.size)) pin_f = spin_f.plot(f_in, X_in, "b") spin_f.set_xlim([min(f_in), max(f_in)+1]) spin_f.set_ylim([-200.0, 50.0]) spin_f.set_title("Input Signal", weight="bold") spin_f.set_xlabel("Frequency (Hz)") spin_f.set_ylabel("Power (dBW)") Ts = 1.0/fs Tmax = len(d)*Ts t_in = scipy.arange(0, Tmax, Ts) x_in = scipy.array(d) spin_t = fig_in.add_subplot(2, 1, 2) pin_t = spin_t.plot(t_in, x_in.real, "b") pin_t = spin_t.plot(t_in, x_in.imag, "r") spin_t.set_xlabel("Time (s)") spin_t.set_ylabel("Amplitude") Ncols = int(scipy.floor(scipy.sqrt(tb._M))) Nrows = int(scipy.floor(tb._M / Ncols)) if(tb._M % Ncols != 0): Nrows += 1 # Plot each of the channels outputs. Frequencies on Figure 2 and # time signals on Figure 3 fs_o = tb._fs Ts_o = 1.0/fs_o Tmax_o = len(d)*Ts_o for i in xrange(len(tb.snks)): # remove issues with the transients at the beginning # also remove some corruption at the end of the stream # this is a bug, probably due to the corner cases d = tb.snks[i].data()[Ns:Ne] sp1_f = fig1.add_subplot(Nrows, Ncols, 1+i) X,freq = mlab.psd(d, NFFT=fftlen, noverlap=fftlen/4, Fs=fs_o, window = lambda d: d*winfunc(fftlen), scale_by_freq=True) X_o = 10.0*scipy.log10(abs(X)) f_o = scipy.arange(-fs_o/2.0, fs_o/2.0, fs_o/float(X_o.size)) p2_f = sp1_f.plot(f_o, X_o, "b") sp1_f.set_xlim([min(f_o), max(f_o)+1]) sp1_f.set_ylim([-200.0, 50.0]) sp1_f.set_title(("Channel %d" % i), weight="bold") sp1_f.set_xlabel("Frequency (Hz)") sp1_f.set_ylabel("Power (dBW)") x_o = scipy.array(d) t_o = scipy.arange(0, Tmax_o, Ts_o) sp2_o = fig2.add_subplot(Nrows, Ncols, 1+i) p2_o = sp2_o.plot(t_o, x_o.real, "b") p2_o = sp2_o.plot(t_o, x_o.imag, "r") sp2_o.set_xlim([min(t_o), max(t_o)+1]) sp2_o.set_ylim([-2, 2]) sp2_o.set_title(("Channel %d" % i), weight="bold") sp2_o.set_xlabel("Time (s)") sp2_o.set_ylabel("Amplitude") pylab.show() if __name__ == "__main__": try: main() except KeyboardInterrupt: pass