content: #!/usr/bin/env python
  #
  # Copyright 2009,2012,2013 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 blocks
  from gnuradio import filter
  import sys, time
  
  try:
      from gnuradio import analog
  except ImportError:
      sys.stderr.write("Error: Program requires gr-analog.\n")
      sys.exit(1)
  
  try:
      import scipy
      from scipy import fftpack
  except ImportError:
      sys.stderr.write("Error: Program requires scipy (see: www.scipy.org).\n")
      sys.exit(1)
  
  try:
      import pylab
      from pylab import mlab
  except ImportError:
      sys.stderr.write("Error: Program requires matplotlib (see: matplotlib.sourceforge.net).\n")
      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 = blocks.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(analog.sig_source_c(self._ifs, analog.GR_SIN_WAVE, f, 1))
              self.connect(self.signals[i], (self.add,i))
  
          self.head = blocks.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 = blocks.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(blocks.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
  
  