1#!/usr/bin/env python 2# 3# Copyright 2009,2012,2013 Free Software Foundation, Inc. 4# 5# This file is part of GNU Radio 6# 7# GNU Radio is free software; you can redistribute it and/or modify 8# it under the terms of the GNU General Public License as published by 9# the Free Software Foundation; either version 3, or (at your option) 10# any later version. 11# 12# GNU Radio is distributed in the hope that it will be useful, 13# but WITHOUT ANY WARRANTY; without even the implied warranty of 14# MERCHANTABILITY or FITNESS FOR A PARTICULAR PURPOSE. See the 15# GNU General Public License for more details. 16# 17# You should have received a copy of the GNU General Public License 18# along with GNU Radio; see the file COPYING. If not, write to 19# the Free Software Foundation, Inc., 51 Franklin Street, 20# Boston, MA 02110-1301, USA. 21# 22 23from __future__ import print_function 24from __future__ import division 25from __future__ import unicode_literals 26from gnuradio import gr 27from gnuradio import blocks 28from gnuradio import filter 29import sys, time 30import numpy 31 32try: 33 from gnuradio import analog 34except ImportError: 35 sys.stderr.write("Error: Program requires gr-analog.\n") 36 sys.exit(1) 37 38try: 39 import pylab 40 from pylab import mlab 41except ImportError: 42 sys.stderr.write("Error: Program requires matplotlib (see: matplotlib.sourceforge.net).\n") 43 sys.exit(1) 44 45class pfb_top_block(gr.top_block): 46 def __init__(self): 47 gr.top_block.__init__(self) 48 49 self._N = 100000 # number of samples to use 50 self._fs = 2000 # initial sampling rate 51 self._interp = 5 # Interpolation rate for PFB interpolator 52 self._ainterp = 5.5 # Resampling rate for the PFB arbitrary resampler 53 54 # Frequencies of the signals we construct 55 freq1 = 100 56 freq2 = 200 57 58 # Create a set of taps for the PFB interpolator 59 # This is based on the post-interpolation sample rate 60 self._taps = filter.firdes.low_pass_2(self._interp, 61 self._interp*self._fs, 62 freq2+50, 50, 63 attenuation_dB=120, 64 window=filter.firdes.WIN_BLACKMAN_hARRIS) 65 66 # Create a set of taps for the PFB arbitrary resampler 67 # The filter size is the number of filters in the filterbank; 32 will give very low side-lobes, 68 # and larger numbers will reduce these even farther 69 # The taps in this filter are based on a sampling rate of the filter size since it acts 70 # internally as an interpolator. 71 flt_size = 32 72 self._taps2 = filter.firdes.low_pass_2(flt_size, 73 flt_size*self._fs, 74 freq2+50, 150, 75 attenuation_dB=120, 76 window=filter.firdes.WIN_BLACKMAN_hARRIS) 77 78 # Calculate the number of taps per channel for our own information 79 tpc = numpy.ceil(float(len(self._taps)) / float(self._interp)) 80 print("Number of taps: ", len(self._taps)) 81 print("Number of filters: ", self._interp) 82 print("Taps per channel: ", tpc) 83 84 # Create a couple of signals at different frequencies 85 self.signal1 = analog.sig_source_c(self._fs, analog.GR_SIN_WAVE, freq1, 0.5) 86 self.signal2 = analog.sig_source_c(self._fs, analog.GR_SIN_WAVE, freq2, 0.5) 87 self.signal = blocks.add_cc() 88 89 self.head = blocks.head(gr.sizeof_gr_complex, self._N) 90 91 # Construct the PFB interpolator filter 92 self.pfb = filter.pfb.interpolator_ccf(self._interp, self._taps) 93 94 # Construct the PFB arbitrary resampler filter 95 self.pfb_ar = filter.pfb.arb_resampler_ccf(self._ainterp, self._taps2, flt_size) 96 self.snk_i = blocks.vector_sink_c() 97 98 #self.pfb_ar.pfb.print_taps() 99 #self.pfb.pfb.print_taps() 100 101 # Connect the blocks 102 self.connect(self.signal1, self.head, (self.signal,0)) 103 self.connect(self.signal2, (self.signal,1)) 104 self.connect(self.signal, self.pfb) 105 self.connect(self.signal, self.pfb_ar) 106 self.connect(self.signal, self.snk_i) 107 108 # Create the sink for the interpolated signals 109 self.snk1 = blocks.vector_sink_c() 110 self.snk2 = blocks.vector_sink_c() 111 self.connect(self.pfb, self.snk1) 112 self.connect(self.pfb_ar, self.snk2) 113 114 115def main(): 116 tb = pfb_top_block() 117 118 tstart = time.time() 119 tb.run() 120 tend = time.time() 121 print("Run time: %f" % (tend - tstart)) 122 123 124 if 1: 125 fig1 = pylab.figure(1, figsize=(12,10), facecolor="w") 126 fig2 = pylab.figure(2, figsize=(12,10), facecolor="w") 127 fig3 = pylab.figure(3, figsize=(12,10), facecolor="w") 128 129 Ns = 10000 130 Ne = 10000 131 132 fftlen = 8192 133 winfunc = numpy.blackman 134 135 # Plot input signal 136 fs = tb._fs 137 138 d = tb.snk_i.data()[Ns:Ns+Ne] 139 sp1_f = fig1.add_subplot(2, 1, 1) 140 141 X,freq = mlab.psd(d, NFFT=fftlen, noverlap=fftlen / 4, Fs=fs, 142 window = lambda d: d*winfunc(fftlen), 143 scale_by_freq=True) 144 X_in = 10.0*numpy.log10(abs(numpy.fft.fftshift(X))) 145 f_in = numpy.arange(-fs / 2.0, fs / 2.0, fs / float(X_in.size)) 146 p1_f = sp1_f.plot(f_in, X_in, "b") 147 sp1_f.set_xlim([min(f_in), max(f_in)+1]) 148 sp1_f.set_ylim([-200.0, 50.0]) 149 150 151 sp1_f.set_title("Input Signal", weight="bold") 152 sp1_f.set_xlabel("Frequency (Hz)") 153 sp1_f.set_ylabel("Power (dBW)") 154 155 Ts = 1.0 / fs 156 Tmax = len(d)*Ts 157 158 t_in = numpy.arange(0, Tmax, Ts) 159 x_in = numpy.array(d) 160 sp1_t = fig1.add_subplot(2, 1, 2) 161 p1_t = sp1_t.plot(t_in, x_in.real, "b-o") 162 #p1_t = sp1_t.plot(t_in, x_in.imag, "r-o") 163 sp1_t.set_ylim([-2.5, 2.5]) 164 165 sp1_t.set_title("Input Signal", weight="bold") 166 sp1_t.set_xlabel("Time (s)") 167 sp1_t.set_ylabel("Amplitude") 168 169 170 # Plot output of PFB interpolator 171 fs_int = tb._fs*tb._interp 172 173 sp2_f = fig2.add_subplot(2, 1, 1) 174 d = tb.snk1.data()[Ns:Ns+(tb._interp*Ne)] 175 X,freq = mlab.psd(d, NFFT=fftlen, noverlap=fftlen / 4, Fs=fs, 176 window = lambda d: d*winfunc(fftlen), 177 scale_by_freq=True) 178 X_o = 10.0*numpy.log10(abs(numpy.fft.fftshift(X))) 179 f_o = numpy.arange(-fs_int / 2.0, fs_int / 2.0, fs_int / float(X_o.size)) 180 p2_f = sp2_f.plot(f_o, X_o, "b") 181 sp2_f.set_xlim([min(f_o), max(f_o)+1]) 182 sp2_f.set_ylim([-200.0, 50.0]) 183 184 sp2_f.set_title("Output Signal from PFB Interpolator", weight="bold") 185 sp2_f.set_xlabel("Frequency (Hz)") 186 sp2_f.set_ylabel("Power (dBW)") 187 188 Ts_int = 1.0 / fs_int 189 Tmax = len(d)*Ts_int 190 191 t_o = numpy.arange(0, Tmax, Ts_int) 192 x_o1 = numpy.array(d) 193 sp2_t = fig2.add_subplot(2, 1, 2) 194 p2_t = sp2_t.plot(t_o, x_o1.real, "b-o") 195 #p2_t = sp2_t.plot(t_o, x_o.imag, "r-o") 196 sp2_t.set_ylim([-2.5, 2.5]) 197 198 sp2_t.set_title("Output Signal from PFB Interpolator", weight="bold") 199 sp2_t.set_xlabel("Time (s)") 200 sp2_t.set_ylabel("Amplitude") 201 202 203 # Plot output of PFB arbitrary resampler 204 fs_aint = tb._fs * tb._ainterp 205 206 sp3_f = fig3.add_subplot(2, 1, 1) 207 d = tb.snk2.data()[Ns:Ns+(tb._interp*Ne)] 208 X,freq = mlab.psd(d, NFFT=fftlen, noverlap=fftlen / 4, Fs=fs, 209 window = lambda d: d*winfunc(fftlen), 210 scale_by_freq=True) 211 X_o = 10.0*numpy.log10(abs(numpy.fft.fftshift(X))) 212 f_o = numpy.arange(-fs_aint / 2.0, fs_aint / 2.0, fs_aint / float(X_o.size)) 213 p3_f = sp3_f.plot(f_o, X_o, "b") 214 sp3_f.set_xlim([min(f_o), max(f_o)+1]) 215 sp3_f.set_ylim([-200.0, 50.0]) 216 217 sp3_f.set_title("Output Signal from PFB Arbitrary Resampler", weight="bold") 218 sp3_f.set_xlabel("Frequency (Hz)") 219 sp3_f.set_ylabel("Power (dBW)") 220 221 Ts_aint = 1.0 / fs_aint 222 Tmax = len(d)*Ts_aint 223 224 t_o = numpy.arange(0, Tmax, Ts_aint) 225 x_o2 = numpy.array(d) 226 sp3_f = fig3.add_subplot(2, 1, 2) 227 p3_f = sp3_f.plot(t_o, x_o2.real, "b-o") 228 p3_f = sp3_f.plot(t_o, x_o1.real, "m-o") 229 #p3_f = sp3_f.plot(t_o, x_o2.imag, "r-o") 230 sp3_f.set_ylim([-2.5, 2.5]) 231 232 sp3_f.set_title("Output Signal from PFB Arbitrary Resampler", weight="bold") 233 sp3_f.set_xlabel("Time (s)") 234 sp3_f.set_ylabel("Amplitude") 235 236 pylab.show() 237 238 239if __name__ == "__main__": 240 try: 241 main() 242 except KeyboardInterrupt: 243 pass 244 245