README change

1 files changed, 240 insertions, 0 deletions

diff --git a/gr-filter/examples/interpolate.py b/gr-filter/examples/interpolate.py
new file mode 100755
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+++ b/gr-filter/examples/interpolate.py
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+#!/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 = 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 = filter.firdes.low_pass_2(self._interp,
+                                              self._interp*self._fs,
+                                              freq2+50, 50,
+                                              attenuation_dB=120,
+                                              window=filter.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 = filter.firdes.low_pass_2(flt_size,
+                                               flt_size*self._fs,
+                                               freq2+50, 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._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 = filter.pfb.interpolator_ccf(self._interp, self._taps)
+
+        # Construct the PFB arbitrary resampler filter
+        self.pfb_ar = filter.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
+