#!/usr/bin/env python # # Copyright 2004,2005 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 2, 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. # # # # Pulsar receiver application # # Performs both harmonic folding analysis # and epoch folding analysis # # from gnuradio import gr, gru, blks, audio from usrpm import usrp_dbid from gnuradio import usrp, optfir from gnuradio import eng_notation from gnuradio.eng_option import eng_option from gnuradio.wxgui import stdgui, ra_fftsink, ra_stripchartsink, form, slider from optparse import OptionParser import wx import sys import Numeric import FFT import ephem import time import os import math class app_flow_graph(stdgui.gui_flow_graph): def __init__(self, frame, panel, vbox, argv): stdgui.gui_flow_graph.__init__(self) self.frame = frame self.panel = panel parser = OptionParser(option_class=eng_option) parser.add_option("-R", "--rx-subdev-spec", type="subdev", default=(0, 0), help="select USRP Rx side A or B (default=A)") parser.add_option("-d", "--decim", type="int", default=16, help="set fgpa decimation rate to DECIM [default=%default]") parser.add_option("-f", "--freq", type="eng_float", default=None, help="set frequency to FREQ", metavar="FREQ") parser.add_option("-Q", "--observing", type="eng_float", default=0.0, help="set observing frequency to FREQ") parser.add_option("-a", "--avg", type="eng_float", default=1.0, help="set spectral averaging alpha") parser.add_option("-V", "--favg", type="eng_float", default=2.0, help="set folder averaging alpha") parser.add_option("-g", "--gain", type="eng_float", default=None, help="set gain in dB (default is midpoint)") parser.add_option("-l", "--reflevel", type="eng_float", default=30.0, help="Set pulse display reference level") parser.add_option("-L", "--lowest", type="eng_float", default=1.5, help="Lowest valid frequency bin") parser.add_option("-e", "--longitude", type="eng_float", default=-76.02, help="Set Observer Longitude") parser.add_option("-c", "--latitude", type="eng_float", default=44.85, help="Set Observer Latitude") parser.add_option("-F", "--fft_size", type="eng_float", default=1024, help="Size of FFT") parser.add_option ("-t", "--threshold", type="eng_float", default=2.5, help="pulsar threshold") parser.add_option("-p", "--lowpass", type="eng_float", default=100, help="Pulse spectra cutoff freq") parser.add_option("-P", "--prefix", default="./", help="File prefix") parser.add_option("-u", "--pulsefreq", type="eng_float", default=0.748, help="Observation pulse rate") parser.add_option("-D", "--dm", type="eng_float", default=1.0e-5, help="Dispersion Measure") parser.add_option("-O", "--doppler", type="eng_float", default=1.0, help="Doppler ratio") parser.add_option("-B", "--divbase", type="eng_float", default=20, help="Y/Div menu base") parser.add_option("-I", "--division", type="eng_float", default=100, help="Y/Div") parser.add_option("-A", "--audio_source", default="plughw:0,0", help="Audio input device spec") (options, args) = parser.parse_args() if len(args) != 0: parser.print_help() sys.exit(1) self.show_debug_info = True self.reflevel = options.reflevel self.divbase = options.divbase self.division = options.division self.audiodev = options.audio_source # Low-pass cutoff for post-detector filter # Set to 100Hz usually, since lots of pulsars fit in this # range self.lowpass = options.lowpass # What is lowest valid frequency bin in post-detector FFT? # There's some pollution very close to DC self.lowest_freq = options.lowest # What (dB) threshold to use in determining spectral candidates self.threshold = options.threshold # Filename prefix for recording file self.prefix = options.prefix # Dispersion Measure (DM) self.dm = options.dm # Doppler shift, as a ratio # 1.0 == no doppler shift # 1.005 == a little negative shift # 0.995 == a little positive shift self.doppler = options.doppler # # Input frequency and observing frequency--not necessarily the # same thing, if we're looking at the IF of some downconverter # that's ahead of the USRP and daughtercard. This distinction # is important in computing the correct de-dispersion filter. # self.frequency = options.freq if options.observing <= 0: self.observing_freq = options.freq else: self.observing_freq = options.observing # build the graph self.u = usrp.source_c(decim_rate=options.decim) self.u.set_mux(usrp.determine_rx_mux_value(self.u, options.rx_subdev_spec)) # # Recording file, in case we ever need to record baseband data # self.recording = gr.file_sink(gr.sizeof_char, "/dev/null") self.recording_state = False self.pulse_recording = gr.file_sink(gr.sizeof_short, "/dev/null") self.pulse_recording_state = False # # We come up with recording turned off, but the user may # request recording later on self.recording.close() self.pulse_recording.close() # # Need these two for converting 12-bit baseband signals to 8-bit # self.tofloat = gr.complex_to_float() self.tochar = gr.float_to_char() # Need this for recording pulses (post-detector) self.toshort = gr.float_to_short() # # The spectral measurer sets this when it has a valid # average spectral peak-to-peak distance # We can then use this to program the parameters for the epoch folder # # We set a sentimental value here self.pulse_freq = options.pulsefreq # Folder runs at this raw sample rate self.folder_input_rate = 20000 # Each pulse in the epoch folder is sampled at 128 times the nominal # pulse rate self.folding = 128 # # Try to find candidate parameters for rational resampler # save_i = 0 candidates = [] for i in range(20,300): input_rate = self.folder_input_rate output_rate = int(self.pulse_freq * i) interp = gru.lcm(input_rate, output_rate) / input_rate decim = gru.lcm(input_rate, output_rate) / output_rate if (interp < 500 and decim < 250000): candidates.append(i) # We didn't find anything, bail! if (len(candidates) < 1): print "Couldn't converge on resampler parameters" sys.exit(1) # # Now try to find candidate with the least sampling error # mindiff = 999.999 for i in candidates: diff = self.pulse_freq * i diff = diff - int(diff) if (diff < mindiff): mindiff = diff save_i = i # Recompute rates input_rate = self.folder_input_rate output_rate = int(self.pulse_freq * save_i) # Compute new interp and decim, based on best candidate interp = gru.lcm(input_rate, output_rate) / input_rate decim = gru.lcm(input_rate, output_rate) / output_rate # Save optimized folding parameters, used later self.folding = save_i self.interp = int(interp) self.decim = int(decim) # So that we can view 4 pulses in the pulse viewer window FOLD_MULT=1 # determine the daughterboard subdevice we're using self.subdev = usrp.selected_subdev(self.u, options.rx_subdev_spec) self.cardtype = self.u.daughterboard_id(0) # Compute raw input rate input_rate = self.u.adc_freq() / self.u.decim_rate() # BW==input_rate for complex data self.bw = input_rate # # Set baseband filter bandwidth if DBS_RX: # if self.cardtype == usrp_dbid.DBS_RX: lbw = input_rate / 2 if lbw < 1.0e6: lbw = 1.0e6 self.subdev.set_bw(lbw) # # We use this as a crude volume control for the audio output # self.volume = gr.multiply_const_ff(10**(-1)) # # Create location data for ephem package # self.locality = ephem.Observer() self.locality.long = str(options.longitude) self.locality.lat = str(options.latitude) # # What is the post-detector LPF cutoff for the FFT? # PULSAR_MAX_FREQ=int(options.lowpass) # First low-pass filters down to input_rate/FIRST_FACTOR # and decimates appropriately FIRST_FACTOR=int(input_rate/(self.folder_input_rate/2)) first_filter = gr.firdes.low_pass (1.0, input_rate, input_rate/FIRST_FACTOR, input_rate/(FIRST_FACTOR*20), gr.firdes.WIN_HAMMING) # Second filter runs at the output rate of the first filter, # And low-pass filters down to PULSAR_MAX_FREQ*10 # second_input_rate = int(input_rate/(FIRST_FACTOR/2)) second_filter = gr.firdes.band_pass(1.0, second_input_rate, 0.10, PULSAR_MAX_FREQ*10, PULSAR_MAX_FREQ*1.5, gr.firdes.WIN_HAMMING) # Third filter runs at PULSAR_MAX_FREQ*20 # and filters down to PULSAR_MAX_FREQ # third_input_rate = PULSAR_MAX_FREQ*20 third_filter = gr.firdes_band_pass(1.0, third_input_rate, 0.10, PULSAR_MAX_FREQ, PULSAR_MAX_FREQ/10.0, gr.firdes.WIN_HAMMING) # # Create the appropriate FFT scope # self.scope = ra_fftsink.ra_fft_sink_f (self, panel, fft_size=int(options.fft_size), sample_rate=PULSAR_MAX_FREQ*2, title="Post-detector spectrum", ofunc=self.pulsarfunc, xydfunc=self.xydfunc, fft_rate=200) # # Tell scope we're looking from DC to PULSAR_MAX_FREQ # self.scope.set_baseband_freq (0.0) # # Setup stripchart for showing pulse profiles # hz = "%5.3fHz " % self.pulse_freq per = "(%5.3f sec)" % (1.0/self.pulse_freq) sr = "%d sps" % (int(self.pulse_freq*self.folding)) self.chart = ra_stripchartsink.stripchart_sink_f (self, panel, sample_rate=1, stripsize=self.folding*FOLD_MULT, parallel=True, title="Pulse Profiles: "+hz+per, xlabel="Seconds @ "+sr, ylabel="Level", autoscale=True, divbase=self.divbase, scaling=1.0/(self.folding*self.pulse_freq)) self.chart.set_ref_level(self.reflevel) self.chart.set_y_per_div(self.division) # De-dispersion filter setup # # Do this here, just before creating the filter # that will use the taps. # ntaps = self.compute_disp_ntaps(self.dm,self.bw,self.observing_freq) # Taps for the de-dispersion filter self.disp_taps = Numeric.zeros(ntaps,Numeric.Complex64) # Compute the de-dispersion filter now self.compute_dispfilter(self.dm,self.doppler, self.bw,self.observing_freq) # # Call constructors for receive chains # # # Now create the FFT filter using the computed taps self.dispfilt = gr.fft_filter_ccc(1, self.disp_taps) # # Audio sink # self.audio = audio.sink(second_input_rate, self.audiodev) # # The three post-detector filters # Done this way to allow an audio path (up to 10Khz) # ...and also because going from xMhz down to ~100Hz # In a single filter doesn't seem to work. # self.first = gr.fir_filter_fff (FIRST_FACTOR/2, first_filter) p = second_input_rate / (PULSAR_MAX_FREQ*20) self.second = gr.fir_filter_fff (int(p), second_filter) self.third = gr.fir_filter_fff (10, third_filter) # Detector self.detector = gr.complex_to_mag_squared() self.enable_comb_filter = False # Epoch folder comb filter if self.enable_comb_filter == True: bogtaps = Numeric.zeros(512, Numeric.Float64) self.folder_comb = gr.fft_filter_ccc(1,bogtaps) # Rational resampler self.folder_rr = blks.rational_resampler_fff(self, self.interp, self.decim) # Epoch folder bandpass bogtaps = Numeric.zeros(1, Numeric.Float64) self.folder_bandpass = gr.fir_filter_fff (1, bogtaps) # Epoch folder F2C/C2F self.folder_f2c = gr.float_to_complex() self.folder_c2f = gr.complex_to_float() # Epoch folder S2P self.folder_s2p = gr.serial_to_parallel (gr.sizeof_float, self.folding*FOLD_MULT) # Epoch folder IIR Filter (produces average pulse profiles) self.folder_iir = gr.single_pole_iir_filter_ff(1.0/options.favg, self.folding*FOLD_MULT) # # Set all the epoch-folder goop up # self.set_folding_params() # # Start connecting configured modules in the receive chain # # Connect raw USRP to de-dispersion filter, detector self.connect(self.u, self.dispfilt, self.detector) # Connect detector output to FIR LPF # in two stages, followed by the FFT scope self.connect(self.detector, self.first, self.second, self.third, self.scope) # Connect audio output self.connect(self.first, self.volume) self.connect(self.volume, (self.audio, 0)) self.connect(self.volume, (self.audio, 1)) # Connect epoch folder if self.enable_comb_filter == True: self.connect (self.first, self.folder_bandpass, self.folder_rr, self.folder_f2c, self.folder_comb, self.folder_c2f, self.folder_s2p, self.folder_iir, self.chart) else: self.connect (self.first, self.folder_bandpass, self.folder_rr, self.folder_s2p, self.folder_iir, self.chart) # Connect baseband recording file (initially /dev/null) self.connect(self.u, self.tofloat, self.tochar, self.recording) # Connect pulse recording file (initially /dev/null) self.connect(self.first, self.toshort, self.pulse_recording) # # Build the GUI elements # self._build_gui(vbox) # Make GUI agree with command-line self.myform['average'].set_value(int(options.avg)) self.myform['foldavg'].set_value(int(options.favg)) # Make spectral averager agree with command line if options.avg != 1.0: self.scope.set_avg_alpha(float(1.0/options.avg)) self.scope.set_average(True) # set initial values if options.gain is None: # if no gain was specified, use the mid-point in dB g = self.subdev.gain_range() options.gain = float(g[0]+g[1])/2 if options.freq is None: # if no freq was specified, use the mid-point r = self.subdev.freq_range() options.freq = float(r[0]+r[1])/2 self.set_gain(options.gain) self.set_volume(-10.0) if not(self.set_freq(options.freq)): self._set_status_msg("Failed to set initial frequency") self.myform['decim'].set_value(self.u.decim_rate()) self.myform['fs@usb'].set_value(self.u.adc_freq() / self.u.decim_rate()) self.myform['dbname'].set_value(self.subdev.name()) self.myform['DM'].set_value(self.dm) self.myform['Doppler'].set_value(self.doppler) # # Start the timer that shows current LMST on the GUI # self.lmst_timer.Start(1000) def _set_status_msg(self, msg): self.frame.GetStatusBar().SetStatusText(msg, 0) def _build_gui(self, vbox): def _form_set_freq(kv): return self.set_freq(kv['freq']) def _form_set_dm(kv): return self.set_dm(kv['DM']) def _form_set_doppler(kv): return self.set_doppler(kv['Doppler']) # Position the FFT or Waterfall vbox.Add(self.scope.win, 5, wx.EXPAND) vbox.Add(self.chart.win, 5, wx.EXPAND) # add control area at the bottom self.myform = myform = form.form() hbox = wx.BoxSizer(wx.HORIZONTAL) hbox.Add((7,0), 0, wx.EXPAND) vbox1 = wx.BoxSizer(wx.VERTICAL) myform['freq'] = form.float_field( parent=self.panel, sizer=vbox1, label="Center freq", weight=1, callback=myform.check_input_and_call(_form_set_freq, self._set_status_msg)) vbox1.Add((3,0), 0, 0) # To show current Local Mean Sidereal Time myform['lmst_high'] = form.static_text_field( parent=self.panel, sizer=vbox1, label="Current LMST", weight=1) vbox1.Add((3,0), 0, 0) # To show current spectral cursor data myform['spec_data'] = form.static_text_field( parent=self.panel, sizer=vbox1, label="Pulse Freq", weight=1) vbox1.Add((3,0), 0, 0) # To show best pulses found in FFT output myform['best_pulse'] = form.static_text_field( parent=self.panel, sizer=vbox1, label="Best freq", weight=1) vbox1.Add((3,0), 0, 0) vboxBogus = wx.BoxSizer(wx.VERTICAL) vboxBogus.Add ((2,0), 0, wx.EXPAND) vbox2 = wx.BoxSizer(wx.VERTICAL) g = self.subdev.gain_range() myform['gain'] = form.slider_field(parent=self.panel, sizer=vbox2, label="RF Gain", weight=1, min=int(g[0]), max=int(g[1]), callback=self.set_gain) vbox2.Add((6,0), 0, 0) myform['average'] = form.slider_field(parent=self.panel, sizer=vbox2, label="Spectral Averaging", weight=1, min=1, max=200, callback=self.set_averaging) vbox2.Add((6,0), 0, 0) myform['foldavg'] = form.slider_field(parent=self.panel, sizer=vbox2, label="Folder Averaging", weight=1, min=1, max=20, callback=self.set_folder_averaging) vbox2.Add((6,0), 0, 0) myform['volume'] = form.quantized_slider_field(parent=self.panel, sizer=vbox2, label="Audio Volume", weight=1, range=(-20, 0, 0.5), callback=self.set_volume) vbox2.Add((6,0), 0, 0) myform['DM'] = form.float_field( parent=self.panel, sizer=vbox2, label="DM", weight=1, callback=myform.check_input_and_call(_form_set_dm)) vbox2.Add((6,0), 0, 0) myform['Doppler'] = form.float_field( parent=self.panel, sizer=vbox2, label="Doppler", weight=1, callback=myform.check_input_and_call(_form_set_doppler)) vbox2.Add((6,0), 0, 0) # Baseband recording control buttonbox = wx.BoxSizer(wx.HORIZONTAL) self.record_control = form.button_with_callback(self.panel, label="Recording baseband: Off ", callback=self.toggle_recording) self.record_pulse_control = form.button_with_callback(self.panel, label="Recording pulses: Off ", callback=self.toggle_pulse_recording) buttonbox.Add(self.record_control, 0, wx.CENTER) buttonbox.Add(self.record_pulse_control, 0, wx.CENTER) vbox.Add(buttonbox, 0, wx.CENTER) hbox.Add(vbox1, 0, 0) hbox.Add(vboxBogus, 0, 0) hbox.Add(vbox2, wx.ALIGN_RIGHT, 0) vbox.Add(hbox, 0, wx.EXPAND) self._build_subpanel(vbox) self.lmst_timer = wx.PyTimer(self.lmst_timeout) self.lmst_timeout() def _build_subpanel(self, vbox_arg): # build a secondary information panel (sometimes hidden) # FIXME figure out how to have this be a subpanel that is always # created, but has its visibility controlled by foo.Show(True/False) if not(self.show_debug_info): return panel = self.panel vbox = vbox_arg myform = self.myform #panel = wx.Panel(self.panel, -1) #vbox = wx.BoxSizer(wx.VERTICAL) hbox = wx.BoxSizer(wx.HORIZONTAL) hbox.Add((5,0), 0) myform['decim'] = form.static_float_field( parent=panel, sizer=hbox, label="Decim") hbox.Add((5,0), 1) myform['fs@usb'] = form.static_float_field( parent=panel, sizer=hbox, label="Fs@USB") hbox.Add((5,0), 1) myform['dbname'] = form.static_text_field( parent=panel, sizer=hbox) hbox.Add((5,0), 1) myform['baseband'] = form.static_float_field( parent=panel, sizer=hbox, label="Analog BB") hbox.Add((5,0), 1) myform['ddc'] = form.static_float_field( parent=panel, sizer=hbox, label="DDC") hbox.Add((5,0), 0) vbox.Add(hbox, 0, wx.EXPAND) def set_freq(self, target_freq): """ Set the center frequency we're interested in. @param target_freq: frequency in Hz @rypte: bool Tuning is a two step process. First we ask the front-end to tune as close to the desired frequency as it can. Then we use the result of that operation and our target_frequency to determine the value for the digital down converter. """ r = usrp.tune(self.u, 0, self.subdev, target_freq) if r: self.myform['freq'].set_value(target_freq) # update displayed value self.myform['baseband'].set_value(r.baseband_freq) self.myform['ddc'].set_value(r.dxc_freq) # Adjust self.frequency, and self.observing_freq # We pick up the difference between the current self.frequency # and the just-programmed one, and use this to adjust # self.observing_freq. We have to do it this way to # make the dedispersion filtering work out properly. delta = target_freq - self.frequency self.frequency = target_freq self.observing_freq += delta # Now that we're adjusted, compute a new dispfilter, and # set the taps for the FFT filter. ntaps = self.compute_disp_ntaps(self.dm, self.bw, self.observing_freq) self.disp_taps = Numeric.zeros(ntaps, Numeric.Complex64) self.compute_dispfilter(self.dm,self.doppler,self.bw, self.observing_freq) self.dispfilt.set_taps(self.disp_taps) return True return False # Callback for gain-setting slider def set_gain(self, gain): self.myform['gain'].set_value(gain) # update displayed value self.subdev.set_gain(gain) def set_volume(self, vol): self.myform['volume'].set_value(vol) self.volume.set_k((10**(vol/10))/8192) # Callback for spectral-averaging slider def set_averaging(self, avval): self.myform['average'].set_value(avval) self.scope.set_avg_alpha(1.0/(avval)) self.scope.set_average(True) def set_folder_averaging(self, avval): self.myform['foldavg'].set_value(avval) self.folder_iir.set_taps(1.0/avval) # Timer callback to update LMST display def lmst_timeout(self): self.locality.date = ephem.now() sidtime = self.locality.sidereal_time() self.myform['lmst_high'].set_value(str(ephem.hours(sidtime))) # # Turn recording on/off # Called-back by "Recording" button # def toggle_recording(self): # Pick up current LMST self.locality.date = ephem.now() sidtime = self.locality.sidereal_time() # Pick up localtime, for generating filenames foo = time.localtime() # Generate filenames for both data and header file filename = "%04d%02d%02d%02d%02d.pdat" % (foo.tm_year, foo.tm_mon, foo.tm_mday, foo.tm_hour, foo.tm_min) hdrfilename = "%04d%02d%02d%02d%02d.phdr" % (foo.tm_year, foo.tm_mon, foo.tm_mday, foo.tm_hour, foo.tm_min) # Current recording? Flip state if (self.recording_state == True): self.recording_state = False self.record_control.SetLabel("Recording baseband: Off ") self.recording.close() # Not recording? else: self.recording_state = True self.record_control.SetLabel("Recording baseband to: "+filename) # Cause gr_file_sink object to accept new filename # note use of self.prefix--filename prefix from # command line (defaults to ./) # self.recording.open (self.prefix+filename) # # We open the header file as a regular file, write header data, # then close hdrf = open(self.prefix+hdrfilename, "w") hdrf.write("receiver center frequency: "+str(self.frequency)+"\n") hdrf.write("observing frequency: "+str(self.observing_freq)+"\n") hdrf.write("DM: "+str(self.dm)+"\n") hdrf.write("doppler: "+str(self.doppler)+"\n") hdrf.write("sidereal: "+str(ephem.hours(sidtime))+"\n") hdrf.write("bandwidth: "+str(self.u.adc_freq() / self.u.decim_rate())+"\n") hdrf.write("sample type: complex_char\n") hdrf.write("sample size: "+str(gr.sizeof_char*2)+"\n") hdrf.close() # # Turn recording on/off # Called-back by "Recording" button # def toggle_pulse_recording(self): # Pick up current LMST self.locality.date = ephem.now() sidtime = self.locality.sidereal_time() # Pick up localtime, for generating filenames foo = time.localtime() # Generate filenames for both data and header file filename = "%04d%02d%02d%02d%02d.padat" % (foo.tm_year, foo.tm_mon, foo.tm_mday, foo.tm_hour, foo.tm_min) hdrfilename = "%04d%02d%02d%02d%02d.pahdr" % (foo.tm_year, foo.tm_mon, foo.tm_mday, foo.tm_hour, foo.tm_min) # Current recording? Flip state if (self.pulse_recording_state == True): self.pulse_recording_state = False self.record_pulse_control.SetLabel("Recording pulses: Off ") self.pulse_recording.close() # Not recording? else: self.pulse_recording_state = True self.record_pulse_control.SetLabel("Recording pulses to: "+filename) # Cause gr_file_sink object to accept new filename # note use of self.prefix--filename prefix from # command line (defaults to ./) # self.pulse_recording.open (self.prefix+filename) # # We open the header file as a regular file, write header data, # then close hdrf = open(self.prefix+hdrfilename, "w") hdrf.write("receiver center frequency: "+str(self.frequency)+"\n") hdrf.write("observing frequency: "+str(self.observing_freq)+"\n") hdrf.write("DM: "+str(self.dm)+"\n") hdrf.write("doppler: "+str(self.doppler)+"\n") hdrf.write("pulse rate: "+str(self.pulse_freq)+"\n") hdrf.write("pulse sps: "+str(self.pulse_freq*self.folding)+"\n") hdrf.write("file sps: "+str(self.folder_input_rate)+"\n") hdrf.write("sidereal: "+str(ephem.hours(sidtime))+"\n") hdrf.write("bandwidth: "+str(self.u.adc_freq() / self.u.decim_rate())+"\n") hdrf.write("sample type: short\n") hdrf.write("sample size: 1\n") hdrf.close() # We get called at startup, and whenever the GUI "Set Folding params" # button is pressed # def set_folding_params(self): if (self.pulse_freq <= 0): return # Compute required sample rate self.sample_rate = int(self.pulse_freq*self.folding) # And the implied decimation rate required_decimation = int(self.folder_input_rate / self.sample_rate) # We also compute a new FFT comb filter, based on the expected # spectral profile of our pulse parameters # # FFT-based comb filter # N_COMB_TAPS=int(self.sample_rate*4) if N_COMB_TAPS > 2000: N_COMB_TAPS = 2000 self.folder_comb_taps = Numeric.zeros(N_COMB_TAPS,Numeric.Complex64) fincr = (self.sample_rate)/float(N_COMB_TAPS) for i in range(0,len(self.folder_comb_taps)): self.folder_comb_taps[i] = complex(0.0, 0.0) freq = 0.0 harmonics = [1.0,2.0,3.0,4.0,5.0,6.0,7.0] for i in range(0,len(self.folder_comb_taps)/2): for j in range(0,len(harmonics)): if abs(freq - harmonics[j]*self.pulse_freq) <= fincr: self.folder_comb_taps[i] = complex(4.0, 0.0) if harmonics[j] == 1.0: self.folder_comb_taps[i] = complex(8.0, 0.0) freq += fincr if self.enable_comb_filter == True: # Set the just-computed FFT comb filter taps self.folder_comb.set_taps(self.folder_comb_taps) # And compute a new decimated bandpass filter, to go in front # of the comb. Primary function is to decimate and filter down # to an exact-ish multiple of the target pulse rate # self.folding_taps = gr.firdes_band_pass (1.0, self.folder_input_rate, 0.10, self.sample_rate/2, 10, gr.firdes.WIN_HAMMING) # Set the computed taps for the bandpass/decimate filter self.folder_bandpass.set_taps (self.folding_taps) # # Record a spectral "hit" of a possible pulsar spectral profile # def record_hit(self,hits, hcavg, hcmax): # Pick up current LMST self.locality.date = ephem.now() sidtime = self.locality.sidereal_time() # Pick up localtime, for generating filenames foo = time.localtime() # Generate filenames for both data and header file hitfilename = "%04d%02d%02d%02d.phit" % (foo.tm_year, foo.tm_mon, foo.tm_mday, foo.tm_hour) hitf = open(self.prefix+hitfilename, "a") hitf.write("receiver center frequency: "+str(self.frequency)+"\n") hitf.write("observing frequency: "+str(self.observing_freq)+"\n") hitf.write("DM: "+str(self.dm)+"\n") hitf.write("doppler: "+str(self.doppler)+"\n") hitf.write("sidereal: "+str(ephem.hours(sidtime))+"\n") hitf.write("bandwidth: "+str(self.u.adc_freq() / self.u.decim_rate())+"\n") hitf.write("spectral peaks: "+str(hits)+"\n") hitf.write("HCM: "+str(hcavg)+" "+str(hcmax)+"\n") hitf.close() # This is a callback used by ra_fftsink.py (passed on creation of # ra_fftsink) # Whenever the user moves the cursor within the FFT display, this # shows the coordinate data # def xydfunc(self,xyv): s = "%.6fHz\n%.3fdB" % (xyv[0], xyv[1]) if self.lowpass >= 500: s = "%.6fHz\n%.3fdB" % (xyv[0]*1000, xyv[1]) self.myform['spec_data'].set_value(s) # This is another callback used by ra_fftsink.py (passed on creation # of ra_fftsink). We pass this as our "calibrator" function, but # we create interesting side-effects in the GUI. # # This function finds peaks in the FFT output data, and reports # on them through the "Best" text object in the GUI # It also computes the Harmonic Compliance Measure (HCM), and displays # that also. # def pulsarfunc(self,d,l): x = range(0,l) incr = float(self.lowpass)/float(l) incr = incr * 2.0 bestdb = -50.0 bestfreq = 0.0 avg = 0 dcnt = 0 # # First, we need to find the average signal level # for i in x: if (i * incr) > self.lowest_freq and (i*incr) < (self.lowpass-2): avg += d[i] dcnt += 1 # Set average signal level avg /= dcnt s2=" " findcnt = 0 # # Then we find candidates that are greater than the user-supplied # threshold. # # We try to cluster "hits" whose whole-number frequency is the # same, and compute an average "hit" frequency. # lastint = 0 hits=[] intcnt = 0 freqavg = 0 for i in x: freq = i*incr # If frequency within bounds, and the (dB-avg) value is above our # threshold if freq > self.lowest_freq and freq < self.lowpass-2 and (d[i] - avg) > self.threshold: # If we're finding a new whole-number frequency if lastint != int(freq): # Record "center" of this hit, if this is a new hit if lastint != 0: s2 += "%5.3fHz " % (freqavg/intcnt) hits.append(freqavg/intcnt) findcnt += 1 lastint = int(freq) intcnt = 1 freqavg = freq else: intcnt += 1 freqavg += freq if (findcnt >= 14): break if intcnt > 1: s2 += "%5.3fHz " % (freqavg/intcnt) hits.append(freqavg/intcnt) # # Compute the HCM, by dividing each of the "hits" by each of the # other hits, and comparing the difference between a "perfect" # harmonic, and the observed frequency ratio. # measure = 0 max_measure=0 mcnt = 0 avg_dist = 0 acnt = 0 for i in range(1,len(hits)): meas = hits[i]/hits[0] - int(hits[i]/hits[0]) if abs((hits[i]-hits[i-1])-hits[0]) < 0.1: avg_dist += hits[i]-hits[i-1] acnt += 1 if meas > 0.98 and meas < 1.0: meas = 1.0 - meas meas *= hits[0] if meas >= max_measure: max_measure = meas measure += meas mcnt += 1 if mcnt > 0: measure /= mcnt if acnt > 0: avg_dist /= acnt if len(hits) > 1: measure /= mcnt s3="\nHCM: Avg %5.3fHz(%d) Max %5.3fHz Dist %5.3fHz(%d)" % (measure,mcnt,max_measure, avg_dist, acnt) if max_measure < 0.5 and len(hits) >= 2: self.record_hit(hits, measure, max_measure) self.avg_dist = avg_dist else: s3="\nHCM: --" s4="\nAvg dB: %4.2f" % avg self.myform['best_pulse'].set_value("("+s2+")"+s3+s4) # Since we are nominally a calibrator function for ra_fftsink, we # simply return what they sent us, untouched. A "real" calibrator # function could monkey with the data before returning it to the # FFT display function. return(d) # # Callback for the "DM" gui object # # We call compute_dispfilter() as appropriate to compute a new filter, # and then set that new filter into self.dispfilt. # def set_dm(self,dm): self.dm = dm ntaps = self.compute_disp_ntaps (self.dm, self.bw, self.observing_freq) self.disp_taps = Numeric.zeros(ntaps, Numeric.Complex64) self.compute_dispfilter(self.dm,self.doppler,self.bw,self.observing_freq) self.dispfilt.set_taps(self.disp_taps) self.myform['DM'].set_value(dm) return(dm) # # Callback for the "Doppler" gui object # # We call compute_dispfilter() as appropriate to compute a new filter, # and then set that new filter into self.dispfilt. # def set_doppler(self,doppler): self.doppler = doppler ntaps = self.compute_disp_ntaps (self.dm, self.bw, self.observing_freq) self.disp_taps = Numeric.zeros(ntaps, Numeric.Complex64) self.compute_dispfilter(self.dm,self.doppler,self.bw,self.observing_freq) self.dispfilt.set_taps(self.disp_taps) self.myform['Doppler'].set_value(doppler) return(doppler) # # Compute a de-dispersion filter # From Hankins, et al, 1975 # # This code translated from dedisp_filter.c from Swinburne # pulsar software repository # def compute_dispfilter(self,dm,doppler,bw,centerfreq): npts = len(self.disp_taps) tmp = Numeric.zeros(npts, Numeric.Complex64) M_PI = 3.14159265358 DM = dm/2.41e-10 # # Because astronomers are a crazy bunch, the "standard" calcultion # is in Mhz, rather than Hz # centerfreq = centerfreq / 1.0e6 bw = bw / 1.0e6 isign = int(bw / abs (bw)) # Center frequency may be doppler shifted cfreq = centerfreq / doppler # As well as the bandwidth.. bandwidth = bw / doppler # Bandwidth divided among bins binwidth = bandwidth / npts # Delay is an "extra" parameter, in usecs, and largely # untested in the Swinburne code. delay = 0.0 # This determines the coefficient of the frequency response curve # Linear in DM, but quadratic in center frequency coeff = isign * 2.0*M_PI * DM / (cfreq*cfreq) # DC to nyquist/2 n = 0 for i in range(0,int(npts/2)): freq = (n + 0.5) * binwidth phi = coeff*freq*freq/(cfreq+freq) + (2.0*M_PI*freq*delay) tmp[i] = complex(math.cos(phi), math.sin(phi)) n += 1 # -nyquist/2 to DC n = int(npts/2) n *= -1 for i in range(int(npts/2),npts): freq = (n + 0.5) * binwidth phi = coeff*freq*freq/(cfreq+freq) + (2.0*M_PI*freq*delay) tmp[i] = complex(math.cos(phi), math.sin(phi)) n += 1 self.disp_taps = FFT.inverse_fft(tmp) return(self.disp_taps) # # Compute minimum number of taps required in de-dispersion FFT filter # def compute_disp_ntaps(self,dm,bw,freq): # # Dt calculations are in Mhz, rather than Hz # crazy astronomers.... mbw = bw/1.0e6 mfreq = freq/1.0e6 f_lower = mfreq-(mbw/2) f_upper = mfreq+(mbw/2) # Compute smear time Dt = dm/2.41e-4 * (1.0/(f_lower*f_lower)-1.0/(f_upper*f_upper)) # ntaps is now bandwidth*smeartime # Should be bandwidth*smeartime*2, but the Gnu Radio FFT filter # already expands it by a factor of 2 ntaps = bw*Dt if ntaps < 64: ntaps = 64 return(int(ntaps)) def main (): app = stdgui.stdapp(app_flow_graph, "RADIO ASTRONOMY PULSAR RECEIVER: $Revision$", nstatus=1) app.MainLoop() if __name__ == '__main__': main ()