def __call__(self, parser, namespace, values, option_string):
colour.cprint("Available Cleaners:", \
bold=True, underline=True)
for name in sorted(cleaners.registered_cleaners):
cleaner = cleaners.load_cleaner(name)
print cleaner.get_help()
sys.exit(1)
def sort_fb_files(fbfiles):
"""Given a list of filterbank objects sort by frequency.
"""
freqbands = []
reversed = []
for fb in fbfiles:
chanbw = fb.header['foff']
if chanbw < 0:
reversed.append(True)
else:
reversed.append(False)
totalbw = chanbw * fb.header['nchans']
lofreq = fb.header['fch1']
hifreq = lofreq + totalbw
freqbands.append([lofreq, hifreq])
reversed = np.array(reversed)
if not (reversed.all() or np.bitwise_not(reversed)):
raise ValueError(colour.cstring("Frequency bands are not ordered" \
"the same.", 'error'))
freqbands = np.array(freqbands).astype(float)
order = freqbands.argsort(axis=0).transpose()[0]
if reversed.all():
# reverse order
if options.debug:
colour.cprint("Frequency bands are all inverted.", 'debug')
order = order[::-1]
freqbands = freqbands[order]
if np.any(
freqbands.flat != sorted(freqbands.flat, reverse=reversed.all())):
if options.debug:
colour.cprint(freqbands, 'debug')
raise ValueError(colour.cstring("Frequency bands have overlaps or " \
"are inverted.", 'error'))
sorted_fbfiles = []
for i in order:
sorted_fbfiles.append(fbfiles[i])
return sorted_fbfiles
def sort_fb_files(fbfiles):
"""Given a list of filterbank objects sort by frequency.
"""
freqbands = []
reversed = []
for fb in fbfiles:
chanbw = fb.header['foff']
if chanbw < 0:
reversed.append(True)
else:
reversed.append(False)
totalbw = chanbw*fb.header['nchans']
lofreq = fb.header['fch1']
hifreq = lofreq + totalbw
freqbands.append([lofreq, hifreq])
reversed = np.array(reversed)
if not (reversed.all() or np.bitwise_not(reversed)):
raise ValueError(colour.cstring("Frequency bands are not ordered" \
"the same.", 'error'))
freqbands = np.array(freqbands).astype(float)
order = freqbands.argsort(axis=0).transpose()[0]
if reversed.all():
# reverse order
if options.debug:
colour.cprint("Frequency bands are all inverted.", 'debug')
order = order[::-1]
freqbands = freqbands[order]
if np.any(freqbands.flat != sorted(freqbands.flat, reverse=reversed.all())):
if options.debug:
colour.cprint(freqbands, 'debug')
raise ValueError(colour.cstring("Frequency bands have overlaps or " \
"are inverted.", 'error'))
sorted_fbfiles = []
for i in order:
sorted_fbfiles.append(fbfiles[i])
return sorted_fbfiles
def main():
# Open file
datfn = args[0]
timeseries = datfile.Datfile(datfn)
if options.shift_phase != 0.0:
# Only shift phase by a fraction of one rotation
options.shift_phase -= int(options.shift_phase)
if options.shift_phase < 0.0:
options.shift_phase += 1.0
else:
shift_time = 0.0
print "Searching %s for single pulses." % timeseries.datfn
if options.parfile is not None:
print "Using parfile: %s" % options.parfile
# generate polycos
print "Automatically generating polycos..."
polycos = mypolycos.create_polycos_from_inf(options.parfile, timeseries.infdata)
mjd = timeseries.infdata.epoch
mjdi = int(mjd) # integer part of mjd
mjdf = mjd-mjdi # fractional part of mjd
phase, freq = polycos.get_phs_and_freq(mjdi, mjdf)
if options.on_pulse_regions == [] or options.on_pulse_regions is None:
# Use polycos to determine on-pulse region
fidphase = 1.0-phase # phase of fiducial point in profile
if fidphase>=0.9 or fidphase<=0.1:
# Shift start of observation by 0.25 in phase
options.shift_phase = phase + 0.25
fidphase = (fidphase - 0.25) % 1.0
options.on_pulse_regions = [(fidphase-0.1, fidphase+0.1)]
if options.debug:
colour.cprint("MJD at start of file: %r" % mjd, 'debug')
colour.cprint("Phase at start of file: %f" % phase, 'debug')
if options.shift_phase != 0.0:
prof_start_phase = options.shift_phase
shift_phase = options.shift_phase - phase
if shift_phase < 0.0:
shift_phase += 1.0
shift_time = shift_phase * 1.0/freq
else:
prof_start_phase = phase
# get periods from polycos
get_period = lambda mjd: 1.0/polycos.get_phs_and_freq(int(mjd), \
mjd-int(mjd))[1]
elif options.polycofile is not None:
print "Using polycos file: %s" % options.polycos
polycos = mypolycos.polycos(options.polycos)
mjd = timeseries.infdata.epoch
mjdi = int(mjd) # integer part of mjd
mjdf = mjd-mjdi # fractional part of mjd
phase, freq = polycos.get_phs_and_freq(mjdi, mjdf)
if options.on_pulse_regions == [] or options.on_pulse_regions is None:
# Use polycos to determine on-pulse region
fidphase = 1.0-phase # phase of fiducial point in profile
if fidphase>=0.9 or fidphase<=0.1:
# Shift start of observation by 0.25 in phase
options.shift_phase = phase + 0.25
fidphase = (fidphase - 0.25) % 1.0
options.on_pulse_regions = [(fidphase-0.1, fidphase+0.1)]
if options.debug:
colour.cprint("MJD at start of file: %r" % mjd, 'debug')
colour.cprint("Phase at start of file: %f" % phase, 'debug')
if options.shift_phase != 0.0:
prof_start_phase = options.shift_phase
shift_phase = options.shift_phase - phase
if shift_phase < 0.0:
shift_phase += 1.0
shift_time = shift_phase * 1.0/freq
else:
prof_start_phase = phase
# get periods from polycos
get_period = lambda mjd: 1.0/polycos.get_phs_and_freq(int(mjd), \
mjd-int(mjd))[1]
elif options.period is not None:
print "Using constant period: %f" % options.period
if options.shift_phase != 0.0:
shift_time = options.shift_phase * options.period
get_period = lambda mjd: options.period
else:
raise ValueError("Unknown option for reading periods.")
print "On-pulse regions will be set to: %s" % \
','.join(['%s:%s' % t for t in options.on_pulse_regions])
print "Boxcar widths to be used: %s" % \
', '.join(['%s' % w for w in options.widths])
print "Single-pulse SNR threshold: %s" % options.threshold
# Loop over pulses in timeseries. Examine pulses one at a time.
good_pulses = []
snrs = []
widths = []
notes = []
nummasked = 0
numpulses = 0
for current_pulse in timeseries.pulses(get_period, \
time_to_skip=shift_time):
numpulses += 1
maxsnr = 0
bestfactor = 0
current_pulse.set_onoff_pulse_regions(options.on_pulse_regions)
if current_pulse.is_masked(numchunks=5) and not options.no_toss:
nummasked += 1
continue
for numbins in options.widths:
pulse = current_pulse.make_copy()
pulse.smooth(numbins)
snr = get_snr(pulse)
if np.isnan(snr) or snr < 0:
snr = 0
if snr > options.threshold:
if snr >= maxsnr:
if maxsnr==0 and bestfactor==0:
# First time snr is above threshold
snrs.append(snr)
notes.append("smoothed by %3d bins" % numbins)
widths.append(numbins)
good_pulses.append(current_pulse)
else:
# Better smootfactor/snr found, update, but don't
# add pulse to good_pulses again.
snrs[-1] = snr
widths[-1] = numbins
notes[-1] = "smoothed by %3d bins" % numbins
maxsnr = snr
bestfactor = numbins
print_report(good_pulses, numpulses, nummasked, snrs=snrs, notes=notes, \
quiet=options.quiet)
if options.create_output_files and len(good_pulses) > 0:
if options.create_text_files:
print "Writing pulse text files..."
write_pulses(good_pulses, timeseries)
if options.create_plot_files:
print "Creating pulse plots..."
plot_pulses(good_pulses, timeseries, options.downfactor,
widths=widths)
if options.create_joydiv_plot:
print "Making JoyDiv plot..."
joy_division_plot(good_pulses, timeseries, options.downfactor, \
options.heightstretch)
if (options.polycofile is not None or options.parfile is not None) and \
options.write_toas and len(good_pulses) > 0:
numtoas = 0
print "Generating TOAs. Please wait..."
print "TOA threshold:", options.toa_threshold
print "Min number of pulses for a TOA:", options.min_pulses
print "Profile template used:", options.template
# Extract second column from template file
# First column is index
template = np.loadtxt(options.template, usecols=(1,))
# Get TOAs and write them to stdout
current_pulse = None
numpulses = 0
for pulse in good_pulses:
if current_pulse is None:
current_pulse = pulse.to_summed_pulse()
numpulses = 1
else:
current_pulse += pulse
numpulses += 1
if numpulses < options.min_pulses:
continue
if get_snr(current_pulse) > options.toa_threshold:
# Interpolate and downsample current_pulse so
# it is same size as template profile
current_pulse.interp_and_downsamp(template.size)
# current_pulse.downsample_Nbins(template.size) ## ADDED FOR DEBUGGING
current_pulse.scale()
pulseshift, templateshift = write_toa(current_pulse, \
polycos, template, timeseries, prof_start_phase, \
options.debug)
numtoas += 1
if options.write_toa_files:
# TOA profiles are already downfactored
# do not downfactor more when creating plot
plot_toa(numtoas, current_pulse, template, \
pulseshift, templateshift)
current_pulse.write_to_file("TOA%d" % numtoas)
current_pulse = None
numpulses = 0
print "Number of TOAs: %d" % numtoas
print "Number of pulses thrown out because 'min pulses' requirement " \
"or SNR threshold not met: %d" % numpulses
def write_toa(summed_pulse, polycos, template_profile, \
timeseries, start_phase=0.0, debug=False):
"""Given a SummedPulse generate a TOA and write it to stdout.
A polycos file is required. 'template_profile' is simply
a numpy array. 'timeseries' is a Datfile object.
'start_phase' is the phase at the start of the profile.
'debug' is a boolean value that determines if debugging
info should be displayed.
Returns shift required to line up template and pulse.
"""
if template_profile is None:
raise ValueError("A template profile MUST be provided.")
# This code is taken from Scott Ransom's PRESTO's get_TOAs.py
mjdi = int(summed_pulse.mjd) # integer part of MJD
mjdf = summed_pulse.mjd - mjdi # fractional part of MJD
(phs, freq) = polycos.get_phs_and_freq(mjdi, mjdf)
phs -= start_phase
period = 1.0/freq
# Caclulate offset due to shifting channels to account for DM
# Hifreq doesn't have a half-channel offset
# (why? because get_TOAs.py doesn't. Why...)
# Why subtract 1 channel to get hifreq?
hifreq = timeseries.infdata.lofreq + timeseries.infdata.BW - \
timeseries.infdata.chan_width
midfreq = timeseries.infdata.lofreq - 0.5*timeseries.infdata.chan_width + \
0.5*timeseries.infdata.BW
dmdelay = psr_utils.delay_from_DM(timeseries.infdata.DM, midfreq) - \
psr_utils.delay_from_DM(timeseries.infdata.DM, hifreq)
dmdelay_mjd = dmdelay/float(psr_utils.SECPERDAY)
if debug:
colour.cprint("High frequency (MHz): %f" % hifreq, 'debug')
colour.cprint("Mid frequency (MHz): %f" % midfreq, 'debug')
colour.cprint("DM delay added to TOAs (s): %g" % dmdelay, 'debug')
colour.cprint("DM delay added to TOAs (MJD): %g" % dmdelay_mjd, 'debug')
t0f = mjdf - phs*period/psr_utils.SECPERDAY + dmdelay_mjd
t0i = mjdi
shift,eshift,snr,esnr,b,errb,ngood,tphs = measure_phase(summed_pulse.profile, \
template_profile)
# tphs is amount template is rotated by. It is originally
# measured in radians, convert to rotational phase
tphs = tphs/(np.pi*2.0) % 1.0
# tau and tau_err are the predicted phase of the pulse arrival
tau, tau_err = shift/summed_pulse.N, eshift/summed_pulse.N
if debug:
colour.cprint("FFTFIT: Shift (bins): %f, Tau (phase): %f" % (shift, tau), 'debug')
colour.cprint("FFTFIT: Shift error (bins): %f, Tau error (phase): %f" % \
(eshift, tau_err), 'debug')
# Note: "error" flags are shift = 0.0 and eshift = 999.0
if (np.fabs(shift) < 1e-7 and np.fabs(eshift-999.0) < 1e-7):
raise FFTFitError("Error in FFTFIT. Bad return values.")
# Send the TOA to STDOUT
toaf = t0f + tau*period/float(psr_utils.SECPERDAY)
if debug:
colour.cprint("t0f (MJD): %r" % t0f, 'debug')
colour.cprint("period (s): %r" % period, 'debug')
colour.cprint("toaf (MJD): %r" % toaf, 'debug')
newdays = int(np.floor(toaf))
obs_code = telescopes.telescope_to_id[timeseries.infdata.telescope]
psr_utils.write_princeton_toa(t0i+newdays, toaf-newdays, \
tau_err*period*1e6, midfreq, \
timeseries.infdata.DM, obs=obs_code)
return tau, tphs