--- /dev/null
+#!/usr/bin/env python
+#
+# Copyright 2009 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
+import os
+import scipy, pylab
+from scipy import fftpack
+from pylab import mlab
+import time
+
+#print os.getpid()
+#raw_input()
+
+class pfb_top_block(gr.top_block):
+ def __init__(self):
+ gr.top_block.__init__(self)
+
+ self._N = 100000 # number of samples to use
+ self._fs = 2000 # initial sampling rate
+ self._interp = 5 # Interpolation rate for PFB interpolator
+ self._ainterp = 5.5 # Resampling rate for the PFB arbitrary resampler
+
+ # Frequencies of the signals we construct
+ freq1 = 100
+ freq2 = 200
+
+ # Create a set of taps for the PFB interpolator
+ # This is based on the post-interpolation sample rate
+ self._taps = gr.firdes.low_pass_2(self._interp, self._interp*self._fs, freq2+50, 50,
+ attenuation_dB=120, window=gr.firdes.WIN_BLACKMAN_hARRIS)
+
+ # Create a set of taps for the PFB arbitrary resampler
+ # The filter size is the number of filters in the filterbank; 32 will give very low side-lobes,
+ # and larger numbers will reduce these even farther
+ # The taps in this filter are based on a sampling rate of the filter size since it acts
+ # internally as an interpolator.
+ flt_size = 32
+ self._taps2 = gr.firdes.low_pass_2(flt_size, flt_size*self._fs, freq2+50, 150,
+ attenuation_dB=120, window=gr.firdes.WIN_BLACKMAN_hARRIS)
+
+ # Calculate the number of taps per channel for our own information
+ tpc = scipy.ceil(float(len(self._taps)) / float(self._interp))
+ print "Number of taps: ", len(self._taps)
+ print "Number of filters: ", self._interp
+ print "Taps per channel: ", tpc
+
+ # Create a couple of signals at different frequencies
+ self.signal1 = gr.sig_source_c(self._fs, gr.GR_SIN_WAVE, freq1, 0.5)
+ self.signal2 = gr.sig_source_c(self._fs, gr.GR_SIN_WAVE, freq2, 0.5)
+ self.signal = gr.add_cc()
+
+ self.head = gr.head(gr.sizeof_gr_complex, self._N)
+
+ # Construct the PFB interpolator filter
+ self.pfb = blks2.pfb_interpolator_ccf(self._interp, self._taps)
+
+ # Construct the PFB arbitrary resampler filter
+ self.pfb_ar = blks2.pfb_arb_resampler_ccf(self._ainterp, self._taps2, flt_size)
+ self.snk_i = gr.vector_sink_c()
+
+ #self.pfb_ar.pfb.print_taps()
+ #self.pfb.pfb.print_taps()
+
+ # Connect the blocks
+ self.connect(self.signal1, self.head, (self.signal,0))
+ self.connect(self.signal2, (self.signal,1))
+ self.connect(self.signal, self.pfb)
+ self.connect(self.signal, self.pfb_ar)
+ self.connect(self.signal, self.snk_i)
+
+ # Create the sink for the interpolated signals
+ self.snk1 = gr.vector_sink_c()
+ self.snk2 = gr.vector_sink_c()
+ self.connect(self.pfb, self.snk1)
+ self.connect(self.pfb_ar, self.snk2)
+
+
+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=(12,10), facecolor="w")
+ fig2 = pylab.figure(2, figsize=(12,10), facecolor="w")
+ fig3 = pylab.figure(3, figsize=(12,10), facecolor="w")
+
+ Ns = 10000
+ Ne = 10000
+
+ fftlen = 8192
+ winfunc = scipy.blackman
+
+ # Plot input signal
+ fs = tb._fs
+
+ 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-o")
+ #p1_t = sp1_t.plot(t_in, x_in.imag, "r-o")
+ sp1_t.set_ylim([-2.5, 2.5])
+
+ sp1_t.set_title("Input Signal", weight="bold")
+ sp1_t.set_xlabel("Time (s)")
+ sp1_t.set_ylabel("Amplitude")
+
+
+ # Plot output of PFB interpolator
+ fs_int = tb._fs*tb._interp
+
+ sp2_f = fig2.add_subplot(2, 1, 1)
+ d = tb.snk1.data()[Ns:Ns+(tb._interp*Ne)]
+ X,freq = mlab.psd(d, NFFT=fftlen, noverlap=fftlen/4, Fs=fs,
+ 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_int/2.0, fs_int/2.0, fs_int/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("Output Signal from PFB Interpolator", weight="bold")
+ sp2_f.set_xlabel("Frequency (Hz)")
+ sp2_f.set_ylabel("Power (dBW)")
+
+ Ts_int = 1.0/fs_int
+ Tmax = len(d)*Ts_int
+
+ t_o = scipy.arange(0, Tmax, Ts_int)
+ x_o1 = scipy.array(d)
+ sp2_t = fig2.add_subplot(2, 1, 2)
+ p2_t = sp2_t.plot(t_o, x_o1.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_title("Output Signal from PFB Interpolator", weight="bold")
+ sp2_t.set_xlabel("Time (s)")
+ sp2_t.set_ylabel("Amplitude")
+
+
+ # Plot output of PFB arbitrary resampler
+ fs_aint = tb._fs * tb._ainterp
+
+ sp3_f = fig3.add_subplot(2, 1, 1)
+ d = tb.snk2.data()[Ns:Ns+(tb._interp*Ne)]
+ X,freq = mlab.psd(d, NFFT=fftlen, noverlap=fftlen/4, Fs=fs,
+ 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_aint/2.0, fs_aint/2.0, fs_aint/float(X_o.size))
+ p3_f = sp3_f.plot(f_o, X_o, "b")
+ sp3_f.set_xlim([min(f_o), max(f_o)+1])
+ sp3_f.set_ylim([-200.0, 50.0])
+
+ sp3_f.set_title("Output Signal from PFB Arbitrary Resampler", weight="bold")
+ sp3_f.set_xlabel("Frequency (Hz)")
+ sp3_f.set_ylabel("Power (dBW)")
+
+ Ts_aint = 1.0/fs_aint
+ Tmax = len(d)*Ts_aint
+
+ t_o = scipy.arange(0, Tmax, Ts_aint)
+ x_o2 = scipy.array(d)
+ sp3_f = fig3.add_subplot(2, 1, 2)
+ p3_f = sp3_f.plot(t_o, x_o2.real, "b-o")
+ p3_f = sp3_f.plot(t_o, x_o1.real, "m-o")
+ #p3_f = sp3_f.plot(t_o, x_o2.imag, "r-o")
+ sp3_f.set_ylim([-2.5, 2.5])
+
+ sp3_f.set_title("Output Signal from PFB Arbitrary Resampler", weight="bold")
+ sp3_f.set_xlabel("Time (s)")
+ sp3_f.set_ylabel("Amplitude")
+
+ pylab.show()
+
+
+if __name__ == "__main__":
+ try:
+ main()
+ except KeyboardInterrupt:
+ pass
+
projects / debian / gnuradio / blobdiff