def savedat(self, fname, withnoise=True):
"""
Save a presto-readable .dat file (with a corresponding .inf file)
containing the time series.
fname: filename without suffix, to be used for .inf and .dat files
"""
inf = infodata()
inf.name = fname
inf.telescope = 'NA'
inf.instrument = 'NA'
inf.object = self.profile.pars['PSR']
inf.observer = 'NA'
inf.mjd_i = self.start.day_int
inf.mjd_f = self.start.day_frac
inf.bary = int(self.bary)
inf.N = self.nbins
inf.dt = self.tres
inf.band = 'Radio'
inf.filt = 'NA'
inf.analyzer = 'NA'
inf.notes = 'Completely fake data set.'
print "Writing %s.dat and %s.inf..." % (fname, fname)
# round since .dat files use integers
if withnoise:
write_dat(np.round(self.ts_pulses+self.ts_noise), fname)
else:
write_dat(np.round(self.ts_pulses), fname)
writeinf(inf)
print "Done."
def multi_psr_ts(psr_list, amp_list, start, tres, noise, length, fname,\
fpath='.', obs=-1, zero=0.):
"""
fname: no extension
fpath: directory to place dat and inf files into
psr_list: iterable set of psrProfile objects
amp_list: corresponding list of pulse heights as fraction of noise sigma
(if no noise is present, values are simply used as heights)
start: start time as MJD object
noise: sigma of white noise in time series
"""
amp_list = np.array(amp_list)
if noise: amp_list *= noise
nbins = int(np.ceil(length/tres))
if nbins % 2: nbins -= 1
chunk_nbins = 2**22
chunk_length = chunk_nbins * tres
n_full_chunks = nbins / chunk_nbins
extra_nbins = nbins % chunk_nbins
# So we can correctly print which chunk we're on:
if extra_nbins: n_chunks = n_full_chunks + 1
else: n_chunks = n_full_chunks
outfile = open("%s/%s.dat" % (fpath, fname), 'w')
for chunk_ii in range(n_full_chunks):
chunk_start = start + chunk_ii*(chunk_length/86400.)
print "Writing time series chunk %d of %d to %s.dat..." % (chunk_ii+1,\
n_chunks, fname)
write_to_dat(outfile, psr_list, amp_list, chunk_start, tres, noise,\
chunk_nbins, obs, zero)
print "Time series chunk complete."
if extra_nbins:
chunk_start = start + n_full_chunks*(chunk_length/86400.)
print "Writing time series chunk %d of %d to %s.dat..." % (n_chunks,\
n_chunks, fname)
write_to_dat(outfile, psr_list, amp_list, chunk_start, tres, noise,\
extra_nbins, obs, zero)
print "Time series chunk complete."
outfile.close()
print "Writing %s.inf..." % fname
inf = infodata()
inf.name = fname
inf.telescope = 'NA'
inf.instrument = 'NA'
inf.object = 'NA'
inf.observer = 'NA'
inf.mjd_i = start.day_int
inf.mjd_f = start.day_frac
inf.bary = 1
inf.N = nbins
inf.dt = tres
inf.band = 'Radio'
inf.filt = 'NA'
inf.analyzer = 'NA'
inf.notes = 'Completely fake data set.'
writeinf(inf)
print "Done."
3: 1.0 / 12,
4: 1.0 / 12,
5: 1.0 / 60,
6: 1.0 / 60
}
# The following are for the lowest harmonic
zmax = 20
dr = drs[numharm]
dz = dr * 4.0
numrs = int(round(4 * zmax / dr))
numzs = int(round(2 * zmax / dz)) + 1
infilenm = sys.argv[1]
infile = open(infilenm, 'rb')
idata = infodata(infilenm[:-4] + ".inf")
idata.T = idata.N * idata.dt
ctrr = int(round(float(sys.argv[2]) * idata.T))
startr = int(ctrr - numrs / 2 * dr)
ctrfreq = ctrr / idata.T
ffdps = []
maxvals = []
maxargs = []
for harmnum in range(1, numharm + 1):
print("Computing harmonic", harmnum)
ldr = dr * harmnum
ldz = dz * harmnum
lor = startr * harmnum