def parse_eph(filenm):
global period, time
suffix = filenm.split(".")[-1]
if suffix=="bestprof":
x = bestprof.bestprof(filenm)
fs = pu.p_to_f(x.p0_bary, x.p1_bary, x.p2_bary)
epoch = x.epochi_bary + x.epochf_bary
T = x.T
elif suffix=="par":
x = parfile.psr_par(filenm)
# Try to see how many freq derivs we have
fs = [x.F0]
for ii in range(1, 20): # hopefully 20 is an upper limit!
attrib = "F%d"%ii
if hasattr(x, attrib):
fs.append(getattr(x, attrib))
else:
break
epoch = x.PEPOCH
T = (x.FINISH - x.START) * 86400.0
else:
print("I don't recognize the file type for", filenm)
sys.exit()
newts = epoch + num.arange(int(T/10.0+0.5), dtype=num.float)/8640.0
time = num.concatenate((time, newts))
newps = 1.0 / pu.calc_freq(newts, epoch, *fs)
period = num.concatenate((period, newps))
print("%13.7f (%0.1f sec): " % (epoch, T), fs)
def parse_eph(filenm):
global period, time
suffix = filenm.split(".")[-1]
if suffix == "bestprof":
x = bestprof.bestprof(filenm)
fs = pu.p_to_f(x.p0_bary, x.p1_bary, x.p2_bary)
epoch = x.epochi_bary + x.epochf_bary
T = x.T
elif suffix == "par":
x = parfile.psr_par(filenm)
# Try to see how many freq derivs we have
fs = [x.F0]
for ii in range(1, 20): # hopefully 20 is an upper limit!
attrib = "F%d" % ii
if hasattr(x, attrib):
fs.append(getattr(x, attrib))
else:
break
epoch = x.PEPOCH
T = (x.FINISH - x.START) * 86400.0
else:
print "I don't recognize the file type for", filenm
sys.exit()
newts = epoch + num.arange(int(T / 10.0 + 0.5), dtype=num.float) / 8640.0
time = num.concatenate((time, newts))
newps = 1.0 / pu.calc_freq(newts, epoch, *fs)
period = num.concatenate((period, newps))
print "%13.7f (%0.1f sec): " % (epoch, T), fs
def read_pfds(fns):
"""
Read pfd files and return arrays of period, period error and mjds
Input: fns - a list of files that contain a list of pfd files to read
"""
ps = []
perrs = []
mjds = []
for fn in fns:
file = open(fn, 'r')
pfdfns = [x.strip() for x in file.readlines() if x.strip()[0] != '#']
file.close()
for pfdfn in pfdfns:
p = prepfold.pfd(pfdfn)
b = bestprof.bestprof("%s.bestprof" % pfdfn)
if options.extendnum and (b.p1err_bary < b.p1_bary):
# If extension is reqested and p-dot is at least a 4-sigma detection
maxt = 300#np.sqrt((0.25*b.p0_bary)**2 - b.p0err_bary**2)/b.p1err_bary
tstep = maxt/options.extendnum
if options.debuglevel:
print "Bary Period (s): %g +/- %g" % (b.p0_bary, b.p0err_bary)
print "Bary P-dot (s/s): %g +/- %g" % (b.p1_bary, b.p1err_bary)
print "Bary Epoch (MJD): %.12f" % p.bepoch
print " Period points (included phantom period measurements)"
print " (T_max = %g (s), T_step = %g (s))" % (maxt, tstep)
for ii in np.arange(-options.extendnum, options.extendnum+1):
ps.append(b.p0_bary+b.p1_bary*ii*tstep)
perrs.append(np.sqrt((b.p0err_bary)**2+(ii*tstep*b.p1err_bary)**2)*options.efac)
mjds.append(p.bepoch+ii*tstep/psr_utils.SECPERDAY)
print " %.15f %.10f %.10f" % (mjds[-1], ps[-1]*1000, perrs[-1]*1000)
if options.debuglevel:
print " P (s): %g +/- %g @ MJD=%.12f" % (ps[-1], perrs[-1], mjds[-1])
else:
ps.append(b.p0_bary)
perrs.append(b.p0err_bary*options.efac)
mjds.append(p.bepoch)
print " %.15f %.10f %.10f" % (mjds[-1], ps[-1]*1000, perrs[-1]*1000)
return np.array(ps), np.array(perrs), np.array(mjds)
def __init__(self, filename):
self.pfd_filename = filename
infile = open(filename, "rb")
# See if the .bestprof file is around
try:
self.bestprof = bestprof(filename+".bestprof")
except IOError:
self.bestprof = 0
swapchar = '<' # this is little-endian
data = infile.read(5*4)
testswap = struct.unpack(swapchar+"i"*5, data)
# This is a hack to try and test the endianness of the data.
# None of the 5 values should be a large positive number.
if (Num.fabs(Num.asarray(testswap))).max() > 100000:
swapchar = '>' # this is big-endian
(self.numdms, self.numperiods, self.numpdots, self.nsub, self.npart) = \
struct.unpack(swapchar+"i"*5, data)
(self.proflen, self.numchan, self.pstep, self.pdstep, self.dmstep, \
self.ndmfact, self.npfact) = struct.unpack(swapchar+"i"*7, infile.read(7*4))
self.filenm = infile.read(struct.unpack(swapchar+"i", infile.read(4))[0])
self.candnm = infile.read(struct.unpack(swapchar+"i", infile.read(4))[0])
self.telescope = infile.read(struct.unpack(swapchar+"i", infile.read(4))[0])
self.pgdev = infile.read(struct.unpack(swapchar+"i", infile.read(4))[0])
test = infile.read(16)
if not test[:8]=="Unknown":
self.rastr = test[:test.find('\0')]
test = infile.read(16)
self.decstr = test[:test.find('\0')]
else:
self.rastr = "Unknown"
self.decstr = "Unknown"
(self.dt, self.startT) = struct.unpack(swapchar+"dd", infile.read(2*8))
(self.endT, self.tepoch, self.bepoch, self.avgvoverc, self.lofreq, \
self.chan_wid, self.bestdm) = struct.unpack(swapchar+"d"*7, infile.read(7*8))
# The following "fixes" (we think) the observing frequency of the Spigot
# based on tests done by Ingrid on 0737 (comparing it to GASP)
# The same sorts of corrections should be made to WAPP data as well...
# The tepoch corrections are empirically determined timing corrections
# Note that epoch is only double precision and so the floating
# point accuracy is ~1 us!
if self.telescope=='GBT':
if (Num.fabs(Num.fmod(self.dt, 8.192e-05) < 1e-12) and \
("spigot" in filename.lower() or "guppi" not in filename.lower()) and \
(self.tepoch < 54832.0)):
sys.stderr.write("Assuming SPIGOT data...\n")
if self.chan_wid==800.0/1024: # Spigot 800 MHz mode 2
self.lofreq -= 0.5 * self.chan_wid
# original values
#if self.tepoch > 0.0: self.tepoch += 0.039334/86400.0
#if self.bestprof: self.bestprof.epochf += 0.039334/86400.0
# values measured with 1713+0747 wrt BCPM2 on 13 Sept 2007
if self.tepoch > 0.0: self.tepoch += 0.039365/86400.0
if self.bestprof: self.bestprof.epochf += 0.039365/86400.0
elif self.chan_wid==800.0/2048:
self.lofreq -= 0.5 * self.chan_wid
if self.tepoch < 53700.0: # Spigot 800 MHz mode 16 (downsampled)
if self.tepoch > 0.0: self.tepoch += 0.039352/86400.0
if self.bestprof: self.bestprof.epochf += 0.039352/86400.0
else: # Spigot 800 MHz mode 14
# values measured with 1713+0747 wrt BCPM2 on 13 Sept 2007
if self.tepoch > 0.0: self.tepoch += 0.039365/86400.0
if self.bestprof: self.bestprof.epochf += 0.039365/86400.0
elif self.chan_wid==50.0/1024 or self.chan_wid==50.0/2048: # Spigot 50 MHz modes
self.lofreq += 0.5 * self.chan_wid
# Note: the offset has _not_ been measured for the 2048-lag mode
if self.tepoch > 0.0: self.tepoch += 0.039450/86400.0
if self.bestprof: self.bestprof.epochf += 0.039450/86400.0
(self.topo_pow, tmp) = struct.unpack(swapchar+"f"*2, infile.read(2*4))
(self.topo_p1, self.topo_p2, self.topo_p3) = struct.unpack(swapchar+"d"*3, \
infile.read(3*8))
(self.bary_pow, tmp) = struct.unpack(swapchar+"f"*2, infile.read(2*4))
(self.bary_p1, self.bary_p2, self.bary_p3) = struct.unpack(swapchar+"d"*3, \
infile.read(3*8))
(self.fold_pow, tmp) = struct.unpack(swapchar+"f"*2, infile.read(2*4))
(self.fold_p1, self.fold_p2, self.fold_p3) = struct.unpack(swapchar+"d"*3, \
infile.read(3*8))
# Save current p, pd, pdd
# NOTE: Fold values are actually frequencies!
self.curr_p1, self.curr_p2, self.curr_p3 = \
psr_utils.p_to_f(self.fold_p1, self.fold_p2, self.fold_p3)
self.pdelays_bins = Num.zeros(self.npart, dtype='d')
(self.orb_p, self.orb_e, self.orb_x, self.orb_w, self.orb_t, self.orb_pd, \
self.orb_wd) = struct.unpack(swapchar+"d"*7, infile.read(7*8))
self.dms = Num.asarray(struct.unpack(swapchar+"d"*self.numdms, \
infile.read(self.numdms*8)))
if self.numdms==1:
self.dms = self.dms[0]
self.periods = Num.asarray(struct.unpack(swapchar+"d"*self.numperiods, \
infile.read(self.numperiods*8)))
self.pdots = Num.asarray(struct.unpack(swapchar+"d"*self.numpdots, \
infile.read(self.numpdots*8)))
self.numprofs = self.nsub*self.npart
if (swapchar=='<'): # little endian
self.profs = Num.zeros((self.npart, self.nsub, self.proflen), dtype='d')
for ii in range(self.npart):
for jj in range(self.nsub):
self.profs[ii,jj,:] = Num.fromfile(infile, Num.float64, self.proflen)
else:
self.profs = Num.asarray(struct.unpack(swapchar+"d"*self.numprofs*self.proflen, \
infile.read(self.numprofs*self.proflen*8)))
self.profs = Num.reshape(self.profs, (self.npart, self.nsub, self.proflen))
if (self.numchan==1):
try:
idata = infodata.infodata(self.filenm[:self.filenm.rfind('.')]+".inf")
try:
if idata.waveband=="Radio":
self.bestdm = idata.DM
self.numchan = idata.numchan
except:
self.bestdm = 0.0
self.numchan = 1
except IOError:
print "Warning! Can't open the .inf file for "+filename+"!"
self.binspersec = self.fold_p1*self.proflen
self.chanpersub = self.numchan/self.nsub
self.subdeltafreq = self.chan_wid*self.chanpersub
self.hifreq = self.lofreq + (self.numchan-1)*self.chan_wid
self.losubfreq = self.lofreq + self.subdeltafreq - self.chan_wid
self.subfreqs = Num.arange(self.nsub, dtype='d')*self.subdeltafreq + \
self.losubfreq
self.subdelays_bins = Num.zeros(self.nsub, dtype='d')
# Save current DM
self.currdm = 0
self.killed_subbands = []
self.killed_intervals = []
self.pts_per_fold = []
# Note: a foldstats struct is read in as a group of 7 doubles
# the correspond to, in order:
# numdata, data_avg, data_var, numprof, prof_avg, prof_var, redchi
self.stats = Num.zeros((self.npart, self.nsub, 7), dtype='d')
for ii in range(self.npart):
currentstats = self.stats[ii]
for jj in range(self.nsub):
if (swapchar=='<'): # little endian
currentstats[jj] = Num.fromfile(infile, Num.float64, 7)
else:
currentstats[jj] = Num.asarray(struct.unpack(swapchar+"d"*7, \
infile.read(7*8)))
self.pts_per_fold.append(self.stats[ii][0][0]) # numdata from foldstats
self.start_secs = Num.add.accumulate([0]+self.pts_per_fold[:-1])*self.dt
self.pts_per_fold = Num.asarray(self.pts_per_fold)
self.mid_secs = self.start_secs + 0.5*self.dt*self.pts_per_fold
if (not self.tepoch==0.0):
self.start_topo_MJDs = self.start_secs/86400.0 + self.tepoch
self.mid_topo_MJDs = self.mid_secs/86400.0 + self.tepoch
if (not self.bepoch==0.0):
self.start_bary_MJDs = self.start_secs/86400.0 + self.bepoch
self.mid_bary_MJDs = self.mid_secs/86400.0 + self.bepoch
self.Nfolded = Num.add.reduce(self.pts_per_fold)
self.T = self.Nfolded*self.dt
self.avgprof = (self.profs/self.proflen).sum()
self.varprof = self.calc_varprof()
# nominal number of degrees of freedom for reduced chi^2 calculation
self.DOFnom = float(self.proflen) - 1.0
# corrected number of degrees of freedom due to inter-bin correlations
self.dt_per_bin = self.curr_p1 / self.proflen / self.dt
self.DOFcor = self.DOFnom * self.DOF_corr()
infile.close()
self.barysubfreqs = None
if self.avgvoverc==0:
if self.candnm.startswith("PSR_"):
# If this doesn't work, we should try to use the barycentering calcs
# in the presto module.
try:
self.polycos = polycos.polycos(self.candnm[4:],
filenm=self.pfd_filename+".polycos")
midMJD = self.tepoch + 0.5*self.T/86400.0
self.avgvoverc = self.polycos.get_voverc(int(midMJD), midMJD-int(midMJD))
#sys.stderr.write("Approximate Doppler velocity (in c) is: %.4g\n"%self.avgvoverc)
# Make the Doppler correction
self.barysubfreqs = self.subfreqs*(1.0+self.avgvoverc)
except IOError:
self.polycos = 0
if self.barysubfreqs is None:
self.barysubfreqs = self.subfreqs
print "usage: python pygaussfit.py bestprof_file prof_stdev"
N = 128
DC = 600.0
noise_stdev = 8.0
params = [DC]
params += [0.25, 0.1, 30.0]
params += [0.3, 0.2, 15.0]
params += [0.8, 0.05, 20.0]
prof = normal(0.0, noise_stdev, N) + gen_gaussians(params, N)
filenm = "test"
else:
filenm = sys.argv[1]
prof = read_profile(filenm, normalize=0)
if len(sys.argv)>=3:
noise_stdev = float(sys.argv[2])
else:
try:
bprof = bestprof(sys.argv[1])
noise_stdev = bprof.prof_std
except:
noise_stdev = 1.0
fig = plt.figure()
dataplot = fig.add_subplot(211)
interactor = GaussianSelector(dataplot, prof, noise_stdev, filenm)
plt.show()
def __init__(self, filename):
self.pfd_filename = filename
infile = open(filename, "rb")
# See if the .bestprof file is around
try:
self.bestprof = bestprof(filename+".bestprof")
except IOError:
self.bestprof = 0
swapchar = '<' # this is little-endian
data = infile.read(5*4)
testswap = struct.unpack(swapchar+"i"*5, data)
# This is a hack to try and test the endianness of the data.
# None of the 5 values should be a large positive number.
if (Num.fabs(Num.asarray(testswap))).max() > 100000:
swapchar = '>' # this is big-endian
(self.numdms, self.numperiods, self.numpdots, self.nsub, self.npart) = \
struct.unpack(swapchar+"i"*5, data)
(self.proflen, self.numchan, self.pstep, self.pdstep, self.dmstep, \
self.ndmfact, self.npfact) = struct.unpack(swapchar+"i"*7, infile.read(7*4))
self.filenm = infile.read(struct.unpack(swapchar+"i", infile.read(4))[0])
self.candnm = infile.read(struct.unpack(swapchar+"i", infile.read(4))[0])
self.telescope = infile.read(struct.unpack(swapchar+"i", infile.read(4))[0])
self.pgdev = infile.read(struct.unpack(swapchar+"i", infile.read(4))[0])
test = infile.read(16)
has_posn = 1
for ii in range(16):
if test[ii] not in '0123456789:.-\0':
has_posn = 0
break
if has_posn:
self.rastr = test[:test.find('\0')]
test = infile.read(16)
self.decstr = test[:test.find('\0')]
(self.dt, self.startT) = struct.unpack(swapchar+"dd", infile.read(2*8))
else:
self.rastr = "Unknown"
self.decstr = "Unknown"
(self.dt, self.startT) = struct.unpack(swapchar+"dd", test)
(self.endT, self.tepoch, self.bepoch, self.avgvoverc, self.lofreq, \
self.chan_wid, self.bestdm) = struct.unpack(swapchar+"d"*7, infile.read(7*8))
# The following "fixes" (we think) the observing frequency of the Spigot
# based on tests done by Ingrid on 0737 (comparing it to GASP)
# The same sorts of corrections should be made to WAPP data as well...
# The tepoch corrections are empirically determined timing corrections
# Note that epoch is only double precision and so the floating
# point accuracy is ~1 us!
if self.telescope=='GBT':
if (Num.fabs(Num.fmod(self.dt, 8.192e-05) < 1e-12) and \
("spigot" in filename.lower() or "guppi" not in filename.lower()) and \
(self.tepoch < 54832.0)):
sys.stderr.write("Assuming SPIGOT data...\n")
if self.chan_wid==800.0/1024: # Spigot 800 MHz mode 2
self.lofreq -= 0.5 * self.chan_wid
# original values
#if self.tepoch > 0.0: self.tepoch += 0.039334/86400.0
#if self.bestprof: self.bestprof.epochf += 0.039334/86400.0
# values measured with 1713+0747 wrt BCPM2 on 13 Sept 2007
if self.tepoch > 0.0: self.tepoch += 0.039365/86400.0
if self.bestprof: self.bestprof.epochf += 0.039365/86400.0
elif self.chan_wid==800.0/2048:
self.lofreq -= 0.5 * self.chan_wid
if self.tepoch < 53700.0: # Spigot 800 MHz mode 16 (downsampled)
if self.tepoch > 0.0: self.tepoch += 0.039352/86400.0
if self.bestprof: self.bestprof.epochf += 0.039352/86400.0
else: # Spigot 800 MHz mode 14
# values measured with 1713+0747 wrt BCPM2 on 13 Sept 2007
if self.tepoch > 0.0: self.tepoch += 0.039365/86400.0
if self.bestprof: self.bestprof.epochf += 0.039365/86400.0
elif self.chan_wid==50.0/1024 or self.chan_wid==50.0/2048: # Spigot 50 MHz modes
self.lofreq += 0.5 * self.chan_wid
# Note: the offset has _not_ been measured for the 2048-lag mode
if self.tepoch > 0.0: self.tepoch += 0.039450/86400.0
if self.bestprof: self.bestprof.epochf += 0.039450/86400.0
(self.topo_pow, tmp) = struct.unpack(swapchar+"f"*2, infile.read(2*4))
(self.topo_p1, self.topo_p2, self.topo_p3) = struct.unpack(swapchar+"d"*3, \
infile.read(3*8))
(self.bary_pow, tmp) = struct.unpack(swapchar+"f"*2, infile.read(2*4))
(self.bary_p1, self.bary_p2, self.bary_p3) = struct.unpack(swapchar+"d"*3, \
infile.read(3*8))
(self.fold_pow, tmp) = struct.unpack(swapchar+"f"*2, infile.read(2*4))
(self.fold_p1, self.fold_p2, self.fold_p3) = struct.unpack(swapchar+"d"*3, \
infile.read(3*8))
# Save current p, pd, pdd
# NOTE: Fold values are actually frequencies!
self.curr_p1, self.curr_p2, self.curr_p3 = \
psr_utils.p_to_f(self.fold_p1, self.fold_p2, self.fold_p3)
self.pdelays_bins = Num.zeros(self.npart, dtype='d')
(self.orb_p, self.orb_e, self.orb_x, self.orb_w, self.orb_t, self.orb_pd, \
self.orb_wd) = struct.unpack(swapchar+"d"*7, infile.read(7*8))
self.dms = Num.asarray(struct.unpack(swapchar+"d"*self.numdms, \
infile.read(self.numdms*8)))
if self.numdms==1:
self.dms = self.dms[0]
self.periods = Num.asarray(struct.unpack(swapchar+"d"*self.numperiods, \
infile.read(self.numperiods*8)))
self.pdots = Num.asarray(struct.unpack(swapchar+"d"*self.numpdots, \
infile.read(self.numpdots*8)))
self.numprofs = self.nsub*self.npart
if (swapchar=='<'): # little endian
self.profs = Num.zeros((self.npart, self.nsub, self.proflen), dtype='d')
for ii in range(self.npart):
for jj in range(self.nsub):
self.profs[ii,jj,:] = Num.fromfile(infile, Num.float64, self.proflen)
else:
self.profs = Num.asarray(struct.unpack(swapchar+"d"*self.numprofs*self.proflen, \
infile.read(self.numprofs*self.proflen*8)))
self.profs = Num.reshape(self.profs, (self.npart, self.nsub, self.proflen))
if (self.numchan==1):
try:
idata = infodata.infodata(self.filenm[:self.filenm.rfind('.')]+".inf")
if idata.waveband=="Radio":
self.bestdm = idata.DM
self.numchan = idata.numchan
else: # i.e. for events
self.bestdm = 0.0
self.numchan = 1
except IOError:
print "Warning! Can't open the .inf file for "+filename+"!"
self.binspersec = self.fold_p1*self.proflen
self.chanpersub = self.numchan/self.nsub
self.subdeltafreq = self.chan_wid*self.chanpersub
self.hifreq = self.lofreq + (self.numchan-1)*self.chan_wid
self.losubfreq = self.lofreq + self.subdeltafreq - self.chan_wid
self.subfreqs = Num.arange(self.nsub, dtype='d')*self.subdeltafreq + \
self.losubfreq
self.subdelays_bins = Num.zeros(self.nsub, dtype='d')
# Save current DM
self.currdm = 0
self.killed_subbands = []
self.killed_intervals = []
self.pts_per_fold = []
# Note: a foldstats struct is read in as a group of 7 doubles
# the correspond to, in order:
# numdata, data_avg, data_var, numprof, prof_avg, prof_var, redchi
self.stats = Num.zeros((self.npart, self.nsub, 7), dtype='d')
for ii in range(self.npart):
currentstats = self.stats[ii]
for jj in range(self.nsub):
if (swapchar=='<'): # little endian
currentstats[jj] = Num.fromfile(infile, Num.float64, 7)
else:
currentstats[jj] = Num.asarray(struct.unpack(swapchar+"d"*7, \
infile.read(7*8)))
self.pts_per_fold.append(self.stats[ii][0][0]) # numdata from foldstats
self.start_secs = Num.add.accumulate([0]+self.pts_per_fold[:-1])*self.dt
self.pts_per_fold = Num.asarray(self.pts_per_fold)
self.mid_secs = self.start_secs + 0.5*self.dt*self.pts_per_fold
if (not self.tepoch==0.0):
self.start_topo_MJDs = self.start_secs/86400.0 + self.tepoch
self.mid_topo_MJDs = self.mid_secs/86400.0 + self.tepoch
if (not self.bepoch==0.0):
self.start_bary_MJDs = self.start_secs/86400.0 + self.bepoch
self.mid_bary_MJDs = self.mid_secs/86400.0 + self.bepoch
self.Nfolded = Num.add.reduce(self.pts_per_fold)
self.T = self.Nfolded*self.dt
self.avgprof = (self.profs/self.proflen).sum()
self.varprof = self.calc_varprof()
infile.close()
self.barysubfreqs = None
if self.avgvoverc==0:
if self.candnm.startswith("PSR_"):
# If this doesn't work, we should try to use the barycentering calcs
# in the presto module.
try:
self.polycos = polycos.polycos(self.candnm[4:],
filenm=self.pfd_filename+".polycos")
midMJD = self.tepoch + 0.5*self.T/86400.0
self.avgvoverc = self.polycos.get_voverc(int(midMJD), midMJD-int(midMJD))
#sys.stderr.write("Approximate Doppler velocity (in c) is: %.4g\n"%self.avgvoverc)
# Make the Doppler correction
self.barysubfreqs = self.subfreqs*(1.0+self.avgvoverc)
except IOError:
self.polycos = 0
if self.barysubfreqs is None:
self.barysubfreqs = self.subfreqs
in get_TOAs.py or sum_profiles.py with the '-g' parameter as a template."""
N = 128
DC = 600.0
noise_stdev = 8.0
params = [DC]
params += [0.25, 0.1, 30.0]
params += [0.3, 0.2, 15.0]
params += [0.8, 0.05, 20.0]
prof = normal(0.0, noise_stdev, N) + gen_gaussians(params, N)
filenm = "test"
else:
filenm = sys.argv[1]
prof = read_profile(filenm, normalize=0)
if len(sys.argv)>=3:
noise_stdev = float(sys.argv[2])
else:
try:
bprof = bestprof(sys.argv[1])
noise_stdev = bprof.prof_std
except:
noise_stdev = 1.0
fig = plt.figure()
dataplot = fig.add_subplot(211)
interactor = GaussianSelector(dataplot, prof, noise_stdev, filenm)
plt.show()
if not opts.is_presto:
import psrchive as pc
else:
import bestprof as bp
if opts.is_presto and opts.method == "Psrstat":
print "You can't use 'Psrstat' method when option --presto is used!"
sys.exit(1)
# to make sure to set up boolean switch in case only adjust option was used
if opts.auto_off_adjust != "0":
opts.is_auto_off = True
for infile in args:
if opts.is_presto: # Presto's .bestprof
bpobj = bp.bestprof(infile)
data = bpobj.profile
target = bpobj.psr
if opts.bscr > 1:
data = bestprof_bscrunch(data, opts.bscr)
nbins = len(data)
# auto-find of the OFF-pulse window
if opts.is_auto_off:
(data, opts.rot_bins, opts.off_left,
opts.off_right) = auto_find_off_window(
data, opts.rot_bins, nbins, opts.auto_off_adjust)
else:
if opts.rot_bins != 0:
data = bestprof_rotate(data, opts.rot_bins)
if not opts.is_presto: import psrchive as pc else: import bestprof as bp if opts.is_presto and opts.method == "Psrstat": print "You can't use 'Psrstat' method when option --presto is used!" sys.exit(1) # to make sure to set up boolean switch in case only adjust option was used if opts.auto_off_adjust != "0": opts.is_auto_off = True for infile in args: if opts.is_presto: # Presto's .bestprof bpobj = bp.bestprof(infile) data = bpobj.profile target = bpobj.psr if opts.bscr > 1: data = bestprof_bscrunch(data, opts.bscr) nbins = len(data) # auto-find of the OFF-pulse window if opts.is_auto_off: (data, opts.rot_bins, opts.off_left, opts.off_right) = auto_find_off_window(data, opts.rot_bins, nbins, opts.auto_off_adjust) else: if opts.rot_bins != 0: data = bestprof_rotate(data, opts.rot_bins) else: # Psrchive's file raw = pc.Archive_load(infile)
