#!/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 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 = 10000000 # number of samples to use self._fs = 10000 # initial sampling rate self._decim = 20 # Decimation rate # Generate the prototype filter taps for the decimators with a 200 Hz bandwidth self._taps = filter.firdes.low_pass_2(1, self._fs, 200, 150, attenuation_dB=120, 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._decim)) print "Number of taps: ", len(self._taps) print "Number of filters: ", self._decim print "Taps per channel: ", tpc # Build the input signal source # We create a list of freqs, and a sine wave is generated and added to the source # for each one of these frequencies. self.signals = list() self.add = gr.add_cc() freqs = [10, 20, 2040] for i in xrange(len(freqs)): self.signals.append(gr.sig_source_c(self._fs, gr.GR_SIN_WAVE, freqs[i], 1)) self.connect(self.signals[i], (self.add,i)) self.head = gr.head(gr.sizeof_gr_complex, self._N) # Construct a PFB decimator filter self.pfb = filter.pfb.decimator_ccf(self._decim, self._taps, 0) # Construct a standard FIR decimating filter self.dec = filter.fir_filter_ccf(self._decim, self._taps) 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) # Create the sink for the decimated siganl self.snk = gr.vector_sink_c() self.connect(self.pfb, self.snk) def main(): tb = pfb_top_block() tstart = time.time() tb.run() tend = time.time() print "Run time: %f" % (tend - tstart) if 1: fig1 = pylab.figure(1, figsize=(16,9)) fig2 = pylab.figure(2, figsize=(16,9)) Ns = 10000 Ne = 10000 fftlen = 8192 winfunc = scipy.blackman fs = tb._fs # Plot the input to the decimator d = tb.snk_i.data()[Ns:Ns+Ne] sp1_f = fig1.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(fftpack.fftshift(X))) f_in = scipy.arange(-fs/2.0, fs/2.0, fs/float(X_in.size)) p1_f = sp1_f.plot(f_in, X_in, "b") sp1_f.set_xlim([min(f_in), max(f_in)+1]) sp1_f.set_ylim([-200.0, 50.0]) sp1_f.set_title("Input Signal", weight="bold") sp1_f.set_xlabel("Frequency (Hz)") sp1_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) sp1_t = fig1.add_subplot(2, 1, 2) p1_t = sp1_t.plot(t_in, x_in.real, "b") p1_t = sp1_t.plot(t_in, x_in.imag, "r") sp1_t.set_ylim([-tb._decim*1.1, tb._decim*1.1]) sp1_t.set_xlabel("Time (s)") sp1_t.set_ylabel("Amplitude") # Plot the output of the decimator fs_o = tb._fs / tb._decim sp2_f = fig2.add_subplot(2, 1, 1) d = tb.snk.data()[Ns:Ns+Ne] 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(fftpack.fftshift(X))) f_o = scipy.arange(-fs_o/2.0, fs_o/2.0, fs_o/float(X_o.size)) p2_f = sp2_f.plot(f_o, X_o, "b") sp2_f.set_xlim([min(f_o), max(f_o)+1]) sp2_f.set_ylim([-200.0, 50.0]) sp2_f.set_title("PFB Decimated Signal", weight="bold") sp2_f.set_xlabel("Frequency (Hz)") sp2_f.set_ylabel("Power (dBW)") Ts_o = 1.0/fs_o Tmax_o = len(d)*Ts_o x_o = scipy.array(d) t_o = scipy.arange(0, Tmax_o, Ts_o) sp2_t = fig2.add_subplot(2, 1, 2) p2_t = sp2_t.plot(t_o, x_o.real, "b-o") p2_t = sp2_t.plot(t_o, x_o.imag, "r-o") sp2_t.set_ylim([-2.5, 2.5]) sp2_t.set_xlabel("Time (s)") sp2_t.set_ylabel("Amplitude") pylab.show() if __name__ == "__main__": try: main() except KeyboardInterrupt: pass