def __init__(self, header_id, cand_num, pfd , snr, \
coherent_power, incoherent_power, \
num_hits, num_harmonics, versionnum, sigma):
self.header_id = header_id # Header ID from database
self.cand_num = cand_num # Unique identifier of candidate within beam's
# list of candidates; Candidate's position in
# a list of all candidates produced in beam
# ordered by decreasing sigma (where largest
# sigma has cand_num=1).
self.topo_freq, self.topo_f_dot, fdd = \
psr_utils.p_to_f(pfd.topo_p1, pfd.topo_p2, pfd.topo_p3)
self.bary_freq, self.bary_f_dot, baryfdd = \
psr_utils.p_to_f(pfd.bary_p1, pfd.bary_p2, pfd.bary_p3)
self.dm = pfd.bestdm # Dispersion measure
self.snr = snr # signal-to-noise ratio
self.coherent_power = coherent_power # Coherent power
self.incoherent_power = incoherent_power # Incoherent power
self.num_hits = num_hits # Number of dedispersed timeseries candidate was found in
self.num_harmonics = num_harmonics # Number of harmonics candidate was
# most significant with
self.versionnum = versionnum # Version number; a combination of PRESTO's githash
# and pipeline's githash
self.sigma = sigma # PRESTO's sigma value
# Calculate a few more values
self.topo_period = 1.0/self.topo_freq
self.bary_period = 1.0/self.bary_freq
def __init__(self, header_id, cand_num, pfd , snr, \
coherent_power, incoherent_power, \
num_hits, num_harmonics, versionnum, sigma):
self.header_id = header_id # Header ID from database
self.cand_num = cand_num # Unique identifier of candidate within beam's
# list of candidates; Candidate's position in
# a list of all candidates produced in beam
# ordered by decreasing sigma (where largest
# sigma has cand_num=1).
self.topo_freq, self.topo_f_dot, fdd = \
psr_utils.p_to_f(pfd.topo_p1, pfd.topo_p2, pfd.topo_p3)
self.bary_freq, self.bary_f_dot, baryfdd = \
psr_utils.p_to_f(pfd.bary_p1, pfd.bary_p2, pfd.bary_p3)
self.dm = pfd.bestdm # Dispersion measure
self.snr = snr # signal-to-noise ratio
self.coherent_power = coherent_power # Coherent power
self.incoherent_power = incoherent_power # Incoherent power
self.num_hits = num_hits # Number of dedispersed timeseries candidate was found in
self.num_harmonics = num_harmonics # Number of harmonics candidate was
# most significant with
self.versionnum = versionnum # Version number; a combination of PRESTO's githash
# and pipeline's githash
self.sigma = sigma # PRESTO's sigma value
# Calculate a few more values
self.topo_period = 1.0 / self.topo_freq
self.bary_period = 1.0 / self.bary_freq
def __init__(self, cand_num, pfd , snr, coherent_power, \
incoherent_power, num_hits, num_harmonics, \
versionnum, sigma, header_id=None):
self.header_id = header_id # Header ID from database
self.cand_num = cand_num # Unique identifier of candidate within beam's
# list of candidates; Candidate's position in
# a list of all candidates produced in beam
# ordered by decreasing sigma (where largest
# sigma has cand_num=1).
self.topo_freq, self.topo_f_dot, fdd = \
psr_utils.p_to_f(pfd.topo_p1, pfd.topo_p2, pfd.topo_p3)
self.bary_freq, self.bary_f_dot, baryfdd = \
psr_utils.p_to_f(pfd.bary_p1, pfd.bary_p2, pfd.bary_p3)
self.dm = pfd.bestdm # Dispersion measure
self.snr = snr # signal-to-noise ratio
self.coherent_power = coherent_power # Coherent power
self.incoherent_power = incoherent_power # Incoherent power
self.num_hits = num_hits # Number of dedispersed timeseries candidate was found in
self.num_harmonics = num_harmonics # Number of harmonics candidate was
# most significant with
self.versionnum = versionnum # Version number; a combination of PRESTO's githash
# and pipeline's githash
self.sigma = sigma # PRESTO's sigma value
# Store a few configurations so the upload can be checked
self.pipeline = config.basic.pipeline
self.institution = config.basic.institution
# Calculate a few more values
self.topo_period = 1.0 / self.topo_freq
self.bary_period = 1.0 / self.bary_freq
# List of dependents (ie other uploadables that require
# the pdm_cand_id from this candidate)
self.dependents = []
def __init__(self, cand_num, pfd , snr, coherent_power, \
incoherent_power, num_hits, num_harmonics, \
versionnum, sigma, header_id=None):
self.header_id = header_id # Header ID from database
self.cand_num = cand_num # Unique identifier of candidate within beam's
# list of candidates; Candidate's position in
# a list of all candidates produced in beam
# ordered by decreasing sigma (where largest
# sigma has cand_num=1).
self.topo_freq, self.topo_f_dot, fdd = \
psr_utils.p_to_f(pfd.topo_p1, pfd.topo_p2, pfd.topo_p3)
self.bary_freq, self.bary_f_dot, baryfdd = \
psr_utils.p_to_f(pfd.bary_p1, pfd.bary_p2, pfd.bary_p3)
self.dm = pfd.bestdm # Dispersion measure
self.snr = snr # signal-to-noise ratio
self.coherent_power = coherent_power # Coherent power
self.incoherent_power = incoherent_power # Incoherent power
self.num_hits = num_hits # Number of dedispersed timeseries candidate was found in
self.num_harmonics = num_harmonics # Number of harmonics candidate was
# most significant with
self.versionnum = versionnum # Version number; a combination of PRESTO's githash
# and pipeline's githash
self.sigma = sigma # PRESTO's sigma value
# Store a few configurations so the upload can be checked
self.pipeline = config.basic.pipeline
self.institution = config.basic.institution
# Calculate a few more values
self.topo_period = 1.0/self.topo_freq
self.bary_period = 1.0/self.bary_freq
# List of dependents (ie other uploadables that require
# the pdm_cand_id from this candidate)
self.dependents = []
def adjust_period(self, p=None, pd=None, pdd=None):
"""
adjust_period(p=*currp*, pd=*currpd*, pdd=*currpdd*):
Rotate (internally) the profiles so that they are adjusted
the given period and period derivatives
"""
if p is None:
p = self.curr_p
if pd is None:
pd = self.curr_pd
if pdd is None:
pdd = self.curr_pdd
# Cast to single precision and back to double precision to
# emulate prepfold_plot.c, where parttimes is of type "float"
# but values are upcast to "double" during computations.
# (surprisingly, it affects the resulting profile occasionally.)
parttimes = self.start_secs.astype('float32').astype('float64')
# Get delays
ref_p, ref_pd, ref_pdd = psr_utils.p_to_f(self.ref_f, \
self.ref_fd, \
self.ref_fdd)
#print "DEBUG: in dataproducts.py -- ref_p, ref_pd, pdd", ref_p, ref_pd, pdd
fdd = psr_utils.p_to_f(ref_p, ref_pd, pdd)[2]
fd = psr_utils.p_to_f(ref_p, pd)[1]
f = 1.0/p
f_diff = f - self.ref_f
fd_diff = fd - self.ref_fd
if pdd != 0.0:
fdd_diff = fdd - self.ref_fdd
else:
fdd_diff = 0.0
#print "DEBUG: in dataproducts.py -- self.ref_f, self.ref_fd, self.ref_fdd", self.ref_f, self.ref_fd, self.ref_fdd
#print "DEBUG: in dataproducts.py -- f, fd, fdd", f, fd, fdd
#print "DEBUG: in dataproducts.py -- f_diff, fd_diff, fdd_diff", f_diff, fd_diff, fdd_diff
#print "DEBUG: in dataproducts.py -- parttimes", parttimes
delays = psr_utils.delay_from_foffsets(f_diff, fd_diff, fdd_diff, \
parttimes)
# Convert from delays in phase to delays in bins
bin_delays = np.fmod(delays * self.nbin, self.nbin) - self.pdelays_bins
new_pdelays_bins = np.floor(bin_delays+0.5)
# Rotate subintegrations
for ii in range(self.nsubint):
tmp_prof = self.data[ii,:]
# Negative sign in num bins to shift because we calculated delays
# Assuming +ve is shift-to-right, psr_utils.rotate assumes +ve
# is shift-to-left
self.data[ii,:] = psr_utils.rotate(tmp_prof, \
-new_pdelays_bins[ii])
# Save new p, pd, pdd
self.curr_p, self.curr_pd, self.curr_pdd = p, pd, pdd
self.pdelays_bins += new_pdelays_bins
def adjust_period(self, p=None, pd=None, pdd=None):
"""
adjust_period(p=*currp*, pd=*currpd*, pdd=*currpdd*):
Rotate (internally) the profiles so that they are adjusted
the given period and period derivatives
"""
if p is None:
p = self.curr_p
if pd is None:
pd = self.curr_pd
if pdd is None:
pdd = self.curr_pdd
# Cast to single precision and back to double precision to
# emulate prepfold_plot.c, where parttimes is of type "float"
# but values are upcast to "double" during computations.
# (surprisingly, it affects the resulting profile occasionally.)
parttimes = self.start_secs.astype('float32').astype('float64')
# Get delays
ref_p, ref_pd, ref_pdd = psr_utils.p_to_f(self.ref_f, \
self.ref_fd, \
self.ref_fdd)
#print "DEBUG: in dataproducts.py -- ref_p, ref_pd, pdd", ref_p, ref_pd, pdd
fdd = psr_utils.p_to_f(ref_p, ref_pd, pdd)[2]
fd = psr_utils.p_to_f(ref_p, pd)[1]
f = 1.0 / p
f_diff = f - self.ref_f
fd_diff = fd - self.ref_fd
if pdd != 0.0:
fdd_diff = fdd - self.ref_fdd
else:
fdd_diff = 0.0
#print "DEBUG: in dataproducts.py -- self.ref_f, self.ref_fd, self.ref_fdd", self.ref_f, self.ref_fd, self.ref_fdd
#print "DEBUG: in dataproducts.py -- f, fd, fdd", f, fd, fdd
#print "DEBUG: in dataproducts.py -- f_diff, fd_diff, fdd_diff", f_diff, fd_diff, fdd_diff
#print "DEBUG: in dataproducts.py -- parttimes", parttimes
delays = psr_utils.delay_from_foffsets(f_diff, fd_diff, fdd_diff, \
parttimes)
# Convert from delays in phase to delays in bins
bin_delays = np.fmod(delays * self.nbin, self.nbin) - self.pdelays_bins
new_pdelays_bins = np.floor(bin_delays + 0.5)
# Rotate subintegrations
for ii in range(self.nsubint):
tmp_prof = self.data[ii, :]
# Negative sign in num bins to shift because we calculated delays
# Assuming +ve is shift-to-right, psr_utils.rotate assumes +ve
# is shift-to-left
self.data[ii,:] = psr_utils.rotate(tmp_prof, \
-new_pdelays_bins[ii])
# Save new p, pd, pdd
self.curr_p, self.curr_pd, self.curr_pdd = p, pd, pdd
self.pdelays_bins += new_pdelays_bins
def freq_offsets(self, p=None, pd=None, pdd=None):
"""
freq_offsets(p=*bestp*, pd=*bestpd*, pdd=*bestpdd*):
Return the offsets between given frequencies
and fold frequencies.
If p, pd or pdd are None use the best values.
A 3-tuple is returned.
"""
if self.fold_pow == 1.0:
bestp = self.bary_p1
bestpd = self.bary_p2
bestpdd = self.bary_p3
else:
if self.topo_p1 == 0.0:
bestp = self.fold_p1
bestpd = self.fold_p2
bestpdd = self.fold_p3
else:
bestp = self.topo_p1
bestpd = self.topo_p2
bestpdd = self.topo_p3
if p is not None:
bestp = p
if pd is not None:
bestpd = pd
if pdd is not None:
bestpdd = pdd
# self.fold_p[123] are actually frequencies, convert to periods
foldf, foldfd, foldfdd = self.fold_p1, self.fold_p2, self.fold_p3
foldp, foldpd, foldpdd = psr_utils.p_to_f(self.fold_p1, \
self.fold_p2, self.fold_p3)
# Get best f, fd, fdd
# Use folding values to be consistent with prepfold_plot.c
bestfdd = psr_utils.p_to_f(foldp, foldpd, bestpdd)[2]
bestfd = psr_utils.p_to_f(foldp, bestpd)[1]
bestf = 1.0/bestp
# Get frequency and frequency derivative offsets
f_diff = bestf - foldf
fd_diff = bestfd - foldfd
# bestpdd=0.0 only if there was no searching over pdd
if bestpdd != 0.0:
fdd_diff = bestfdd - foldfdd
else:
fdd_diff = 0.0
return (f_diff, fd_diff, fdd_diff)
def freq_offsets(self, p=None, pd=None, pdd=None):
"""
freq_offsets(p=*bestp*, pd=*bestpd*, pdd=*bestpdd*):
Return the offsets between given frequencies
and fold frequencies.
If p, pd or pdd are None use the best values.
A 3-tuple is returned.
"""
if self.fold_pow == 1.0:
bestp = self.bary_p1
bestpd = self.bary_p2
bestpdd = self.bary_p3
else:
if self.topo_p1 == 0.0:
bestp = self.fold_p1
bestpd = self.fold_p2
bestpdd = self.fold_p3
else:
bestp = self.topo_p1
bestpd = self.topo_p2
bestpdd = self.topo_p3
if p is not None:
bestp = p
if pd is not None:
bestpd = pd
if pdd is not None:
bestpdd = pdd
# self.fold_p[123] are actually frequencies, convert to periods
foldf, foldfd, foldfdd = self.fold_p1, self.fold_p2, self.fold_p3
foldp, foldpd, foldpdd = psr_utils.p_to_f(self.fold_p1, \
self.fold_p2, self.fold_p3)
# Get best f, fd, fdd
# Use folding values to be consistent with prepfold_plot.c
bestfdd = psr_utils.p_to_f(foldp, foldpd, bestpdd)[2]
bestfd = psr_utils.p_to_f(foldp, bestpd)[1]
bestf = 1.0/bestp
# Get frequency and frequency derivative offsets
f_diff = bestf - foldf
fd_diff = bestfd - foldfd
# bestpdd=0.0 only if there was no searching over pdd
if bestpdd != 0.0:
fdd_diff = bestfdd - foldfdd
else:
fdd_diff = 0.0
return (f_diff, fd_diff, fdd_diff)
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 params_from_ppdot(p, pdot):
"""Return B-field, age and Edot in a tuple given p and pdot.
If either P or Pdot is None, return tuple of Nones
"""
if p is None or pdot is None:
bfield = None
age = None
edot = None
else:
f, fdot = psr_utils.p_to_f(p, pdot)
bfield = psr_utils.pulsar_B(f, fdot)
age = psr_utils.pulsar_age(f, fdot)
edot = psr_utils.pulsar_edot(f, fdot)
return (bfield, age, edot)
def params_from_ppdot(p, pdot):
"""Return B-field, age and Edot in a tuple given p and pdot.
If either P or Pdot is None, return tuple of Nones
"""
if p is None or pdot is None:
bfield = None
age = None
edot = None
else:
f, fdot = psr_utils.p_to_f(p, pdot)
bfield = psr_utils.pulsar_B(f, fdot)
age = psr_utils.pulsar_age(f, fdot)
edot = psr_utils.pulsar_edot(f, fdot)
return (bfield, age, edot)
try: obs = scopes[fold_pfd.telescope.split()[0]]
except KeyError: print "Unknown telescope!!!"
# Read the polyco file (if required)
if (fold.psr and fold.topo):
if (fold_pfd.__dict__.has_key("polycos") and
not fold_pfd.polycos==0):
pcs = fold_pfd.polycos
else:
pcs = polycos(fold.psr, sys.argv[-1]+".polycos")
(fold.phs0, fold.f0) = pcs.get_phs_and_freq(fold.epochi, fold.epochf)
fold.f1 = fold.f2 = 0.0
else:
pcs = None
fold.phs0 = 0.0
(fold.f0, fold.f1, fold.f2) = psr_utils.p_to_f(fold.p0, fold.p1, fold.p2)
#
# Calculate the TOAs
#
for ii in range(numtoas):
# The .pfd file was generated using -nosearch and a specified
# folding period, p-dot, and p-dotdot (or f, f-dot, and f-dotdot).
if (pcs is None):
# Time at the middle of the interval in question
midtime = fold.epoch + (ii+0.5)*timestep_day
p = 1.0/psr_utils.calc_freq(midtime, fold.epoch, fold.f0, fold.f1, fold.f2)
t0 = psr_utils.calc_t0(midtime, fold.epoch, fold.f0, fold.f1, fold.f2)
t0i= int(t0 + 1e-9)
except KeyError:
sys.stderr.write("Unknown telescope!!! : " + fold_pfd.telescope)
# Read the polyco file (if required)
if (fold.psr and fold.topo):
if (fold_pfd.__dict__.has_key("polycos")
and not fold_pfd.polycos == 0):
pcs = fold_pfd.polycos
else:
pcs = polycos(fold.psr, sys.argv[-1] + ".polycos")
(fold.phs0, fold.f0) = pcs.get_phs_and_freq(fold.epochi, fold.epochf)
fold.f1 = fold.f2 = 0.0
else:
pcs = None
fold.phs0 = 0.0
(fold.f0, fold.f1, fold.f2) = psr_utils.p_to_f(fold.p0, fold.p1,
fold.p2)
#
# Calculate the TOAs
#
if t2format:
print "FORMAT 1"
for ii in range(numtoas):
# The .pfd file was generated using -nosearch and a specified
# folding period, p-dot, and p-dotdot (or f, f-dot, and f-dotdot).
if (pcs is None):
# Time at the middle of the interval in question
midtime = fold.epoch + (ii + 0.5) * timestep_day
def __init__(self, cand_num, pfd , snr, coherent_power, \
incoherent_power, num_hits, num_harmonics, \
versionnum, sigma, sifting_period, sifting_dm, \
cand_attribs, header_id=None):
self.header_id = header_id # Header ID from database
self.cand_num = cand_num # Unique identifier of candidate within beam's
# list of candidates; Candidate's position in
# a list of all candidates produced in beam
# ordered by decreasing sigma (where largest
# sigma has cand_num=1).
self.topo_freq, self.topo_f_dot, fdd = \
psr_utils.p_to_f(pfd.topo_p1, pfd.topo_p2, pfd.topo_p3)
self.bary_freq, self.bary_f_dot, baryfdd = \
psr_utils.p_to_f(pfd.bary_p1, pfd.bary_p2, pfd.bary_p3)
self.dm = pfd.bestdm # Dispersion measure
self.snr = snr # signal-to-noise ratio
self.coherent_power = coherent_power # Coherent power
self.incoherent_power = incoherent_power # Incoherent power
self.num_hits = num_hits # Number of dedispersed timeseries candidate was found in
self.num_harmonics = num_harmonics # Number of harmonics candidate was
# most significant with
self.versionnum = versionnum # Version number; a combination of PRESTO's githash
# and pipeline's githash
self.sigma = sigma # PRESTO's sigma value
#red_chi2 = pfd.bestprof.chi_sqr #prepfold reduced chi-squared
#dof = pfd.proflen - 1 # degrees of freedom
##prepfold sigma
#self.prepfold_sigma = \
# scipy.special.ndtri(scipy.special.chdtr(dof,dof*red_chi2))
#off_red_chi2 = pfd.estimate_offsignal_redchi2()
#chi2_scale = 1.0/off_red_chi2
#new_red_chi2 = chi2_scale * red_chi2
## prepfold sigma rescaled to deal with chi-squared suppression
## a problem when strong rfi is present
#self.rescaled_prepfold_sigma = \
# scipy.special.ndtri(scipy.special.chdtr(dof,dof*new_red_chi2))
self.prepfold_sigma = float(cand_attribs['prepfold_sigma'])
self.rescaled_prepfold_sigma = float(cand_attribs['rescaled_prepfold_sigma'])
if np.isinf(self.prepfold_sigma):
self.prepfold_sigma = 9999.0
if np.isinf(self.rescaled_prepfold_sigma):
self.rescaled_prepfold_sigma = 9999.0
self.sifting_period = sifting_period # the period returned by accelsearch
# (not optimized by prepfold)
self.sifting_dm = sifting_dm # the DM returned by accelsearch
# (not optimized by prepfold)
# Store a few configurations so the upload can be checked
self.pipeline = config.basic.pipeline
self.institution = config.basic.institution
# Calculate a few more values
self.topo_period = 1.0/self.topo_freq
self.bary_period = 1.0/self.bary_freq
# List of dependents (ie other uploadables that require
# the pdm_cand_id from this candidate)
self.dependents = []
psrs = pulsars.values()
psrs.sort()
# Now create a new dictionary of pulsars with aliases
psr_aliases = {}
for psr in psrs:
if psr.alias:
psr_aliases[psr.alias] = psr
# Add a couple important pulsars
for psr in psrs:
if psr.jname=="1614-23":
psr.jname=="1614-2318"
psr.f = 29.8475387364133766
psr.fd = -4.683105034721e-17
psr.p, psr.pd = psr_utils.p_to_f(psr.f, psr.fd)
psr.x = 1.327490
psr.e = 0.0
psr.To = 52819.878171
psr.pb = 3.15238573
psr.w = 0.0
psr.dm = 52.43
psr.l = 351.91856
psr.b = 19.74496
psr.dist = 1.80
# If calling this as a main program, then write out the new pulsars.cat file
if __name__ == '__main__' :
presto_path = os.getenv("PRESTO")
outfilename = os.path.join(presto_path, "lib", "pulsars.cat")
outfile = open(outfilename, "w")
def __init__(self, parfilenm):
self.FILE = parfilenm
pf = open(parfilenm)
for line in pf.readlines():
# Skip comments
if line[0] == "#":
continue
# Convert any 'D-' or 'D+' to 'E-' or 'E+'
line = line.replace("D-", "E-")
line = line.replace("D+", "E+")
splitline = line.split()
# Skip blank lines
if len(splitline) == 0:
continue
key = splitline[0]
if key in str_keys:
setattr(self, key, splitline[1])
elif key in float_keys:
try:
setattr(self, key, float(splitline[1]))
except ValueError:
pass
if len(splitline) == 3: # Some parfiles don't have flags, but do have errors
if splitline[2] not in ["0", "1"]:
setattr(self, key + "_ERR", float(splitline[2]))
if len(splitline) == 4:
setattr(self, key + "_ERR", float(splitline[3]))
# Deal with Ecliptic coords
if hasattr(self, "BETA") and hasattr(self, "LAMBDA"):
setattr(self, "ELAT", self.BETA)
setattr(self, "ELONG", self.LAMBDA)
if slalib and hasattr(self, "ELAT") and hasattr(self, "ELONG"):
if hasattr(self, "POSEPOCH"):
epoch = self.POSEPOCH
else:
epoch = self.PEPOCH
ra_rad, dec_rad = sla_ecleq(self.ELONG * pu.DEGTORAD, self.ELAT * pu.DEGTORAD, epoch)
rstr = pu.coord_to_string(*pu.rad_to_hms(ra_rad))
dstr = pu.coord_to_string(*pu.rad_to_dms(dec_rad))
setattr(self, "RAJ", rstr)
setattr(self, "DECJ", dstr)
if hasattr(self, "RAJ"):
setattr(self, "RA_RAD", pu.ra_to_rad(self.RAJ))
if hasattr(self, "DECJ"):
setattr(self, "DEC_RAD", pu.dec_to_rad(self.DECJ))
# Compute the Galactic coords
if slalib and hasattr(self, "RA_RAD") and hasattr(self, "DEC_RAD"):
l, b = sla_eqgal(self.RA_RAD, self.DEC_RAD)
setattr(self, "GLONG", l * pu.RADTODEG)
setattr(self, "GLAT", b * pu.RADTODEG)
# Compute the Ecliptic coords
if slalib and hasattr(self, "RA_RAD") and hasattr(self, "DEC_RAD"):
if hasattr(self, "POSEPOCH"):
epoch = self.POSEPOCH
else:
epoch = self.PEPOCH
elon, elat = sla_eqecl(self.RA_RAD, self.DEC_RAD, epoch)
setattr(self, "ELONG", elon * pu.RADTODEG)
setattr(self, "ELAT", elat * pu.RADTODEG)
if hasattr(self, "P"):
setattr(self, "P0", self.P)
if hasattr(self, "P0"):
setattr(self, "F0", 1.0 / self.P0)
if hasattr(self, "F0"):
setattr(self, "P0", 1.0 / self.F0)
if hasattr(self, "FB0"):
setattr(self, "PB", (1.0 / self.FB0) / 86400.0)
if hasattr(self, "P0_ERR"):
if hasattr(self, "P1_ERR"):
f, ferr, fd, fderr = pu.pferrs(self.P0, self.P0_ERR, self.P1, self.P1_ERR)
setattr(self, "F0_ERR", ferr)
setattr(self, "F1", fd)
setattr(self, "F1_ERR", fderr)
else:
f, fd, = pu.p_to_f(self.P0, self.P1)
setattr(self, "F0_ERR", self.P0_ERR / (self.P0 * self.P0))
setattr(self, "F1", fd)
if hasattr(self, "F0_ERR"):
if hasattr(self, "F1_ERR"):
p, perr, pd, pderr = pu.pferrs(self.F0, self.F0_ERR, self.F1, self.F1_ERR)
setattr(self, "P0_ERR", perr)
setattr(self, "P1", pd)
setattr(self, "P1_ERR", pderr)
else:
p, pd, = pu.p_to_f(self.F0, self.F1)
setattr(self, "P0_ERR", self.F0_ERR / (self.F0 * self.F0))
setattr(self, "P1", pd)
if hasattr(self, "EPS1") and hasattr(self, "EPS2"):
ecc = math.sqrt(self.EPS1 * self.EPS1 + self.EPS2 * self.EPS2)
omega = math.atan2(self.EPS1, self.EPS2)
setattr(self, "E", ecc)
setattr(self, "OM", omega * pu.RADTODEG)
setattr(self, "T0", self.TASC + self.PB * omega / pu.TWOPI)
if hasattr(self, "PB") and hasattr(self, "A1") and not (hasattr(self, "E") or hasattr(self, "ECC")):
setattr(self, "E", 0.0)
if hasattr(self, "T0") and not hasattr(self, "TASC"):
setattr(self, "TASC", self.T0 - self.PB * self.OM / 360.0)
pf.close()
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
def read(self, parfilenm):
self.FILE = parfilenm
#print parfilenm
pf = open(parfilenm)
for line in pf.readlines():
# Convert any 'D-' or 'D+' to 'E-' or 'E+'
line = line.replace("D-", "E-")
line = line.replace("D+", "E+")
try:
splitline = line.split()
key = splitline[0]
if key in str_keys:
setattr(self, key, splitline[1])
elif key in float_keys:
try:
setattr(self, key, float(splitline[1]))
except ValueError:
pass
if len(
splitline
) == 3: # Some parfiles don't have flags, but do have errors
if splitline[2] not in ['0', '1']:
setattr(self, key + '_ERR', float(splitline[2]))
if len(splitline) == 4:
setattr(self, key + '_ERR', float(splitline[3]))
except:
if line.strip():
print ' ', line
# Read PSR name
if hasattr(self, 'PSR'):
setattr(self, 'PSR', self.PSR)
if hasattr(self, 'PSRJ'):
setattr(self, 'PSRJ', self.PSRJ)
# Deal with Ecliptic coords
if (hasattr(self, 'BETA') and hasattr(self, 'LAMBDA')):
self.use_eclip = True
setattr(self, 'ELAT', self.BETA)
setattr(self, 'ELONG', self.LAMBDA)
if (slalib and hasattr(self, 'ELAT') and hasattr(self, 'ELONG')):
self.use_eclip = True
if hasattr(self, 'POSEPOCH'):
epoch = self.POSEPOCH
else:
epoch = self.PEPOCH
ra_rad, dec_rad = sla_ecleq(self.ELONG * pu.DEGTORAD,
self.ELAT * pu.DEGTORAD, epoch)
rstr = pu.coord_to_string(*pu.rad_to_hms(ra_rad))
dstr = pu.coord_to_string(*pu.rad_to_dms(dec_rad))
setattr(self, 'RAJ', rstr)
setattr(self, 'DECJ', dstr)
if (slalib and hasattr(self, 'ELAT') and hasattr(self, 'ELONG')):
setattr(self, 'PMELONG', self.PMELONG)
setattr(self, 'PMELAT', self.PMELAT)
if hasattr(self, 'RAJ'):
setattr(self, 'RA_RAD', pu.ra_to_rad(self.RAJ))
if hasattr(self, 'DECJ'):
setattr(self, 'DEC_RAD', pu.dec_to_rad(self.DECJ))
# Compute the Galactic coords
if (slalib and hasattr(self, 'RA_RAD') and hasattr(self, 'DEC_RAD')):
l, b = sla_eqgal(self.RA_RAD, self.DEC_RAD)
setattr(self, 'GLONG', l * pu.RADTODEG)
setattr(self, 'GLAT', b * pu.RADTODEG)
# Compute the Ecliptic coords
if (slalib and hasattr(self, 'RA_RAD') and hasattr(self, 'DEC_RAD')):
if hasattr(self, 'POSEPOCH'):
epoch = self.POSEPOCH
else:
epoch = self.PEPOCH
elon, elat = sla_eqecl(self.RA_RAD, self.DEC_RAD, epoch)
setattr(self, 'ELONG', elon * pu.RADTODEG)
setattr(self, 'ELAT', elat * pu.RADTODEG)
if hasattr(self, 'P'):
setattr(self, 'P0', self.P)
if hasattr(self, 'P0'):
setattr(self, 'F0', 1.0 / self.P0)
if hasattr(self, 'F0'):
setattr(self, 'P0', 1.0 / self.F0)
if hasattr(self, 'F1'):
setattr(self, 'P1', -self.F1 / (self.F0 * self.F0))
if hasattr(self, 'FB0'):
setattr(self, 'PB', (1.0 / self.FB0) / 86400.0)
if hasattr(self, 'P0_ERR'):
if hasattr(self, 'P1_ERR'):
f, ferr, fd, fderr = pu.pferrs(self.P0, self.P0_ERR, self.P1,
self.P1_ERR)
setattr(self, 'F0_ERR', ferr)
setattr(self, 'F1', fd)
setattr(self, 'F1_ERR', fderr)
else:
f, fd, = pu.p_to_f(self.P0, self.P1)
setattr(self, 'F0_ERR', self.P0_ERR / (self.P0 * self.P0))
setattr(self, 'F1', fd)
if hasattr(self, 'F0_ERR'):
if hasattr(self, 'F1_ERR'):
p, perr, pd, pderr = pu.pferrs(self.F0, self.F0_ERR, self.F1,
self.F1_ERR)
setattr(self, 'P0_ERR', perr)
setattr(self, 'P1', pd)
setattr(self, 'P1_ERR', pderr)
else:
p, pd, = pu.p_to_f(self.F0, self.F1)
setattr(self, 'P0_ERR', self.F0_ERR / (self.F0 * self.F0))
setattr(self, 'P1', pd)
if hasattr(self, 'DM'):
setattr(self, 'DM', self.DM)
if hasattr(self, 'DM1'):
setattr(self, 'DM1', self.DM1)
if hasattr(self, 'DM2'):
setattr(self, 'DM2', self.DM2)
if hasattr(self, 'EPS1') and hasattr(self, 'EPS2'):
self.use_ell = True
ecc = math.sqrt(self.EPS1 * self.EPS1 + self.EPS2 * self.EPS2)
omega = math.atan2(self.EPS1, self.EPS2)
if self.EPS1 == 0.0 and self.EPS2 == 0.0:
ecc_err = pow(
pow(self.EPS1_ERR, 2) + pow(self.EPS2_ERR, 2), .5)
else:
ecc_err = pow(
pow(self.EPS1 * self.EPS1_ERR, 2) +
pow(self.EPS2 * self.EPS2_ERR, 2), 0.5) / ecc
setattr(self, 'ECC', ecc)
setattr(self, 'ECC_ERR', ecc_err)
setattr(self, 'OM', omega)
if hasattr(self, 'PB') and hasattr(self,
'A1') and not hasattr(self, 'ECC'):
setattr(self, 'ECC', 0.0)
if hasattr(self, 'BINARY'):
setattr(self, 'BINARY', self.BINARY)
if hasattr(self, 'KIN'):
setattr(self, 'SINI', math.sin(self.KIN * np.pi / 180.))
setattr(
self, 'SINI_ERR',
math.sin(self.KIN * np.pi / 180.) -
math.sin(self.KIN * np.pi / 180. -
self.KIN_ERR * np.pi / 180.))
pf.close()
def __init__(self, parfilenm):
self.FILE = parfilenm
pf = open(parfilenm)
for line in pf.readlines():
# Convert any 'D-' or 'D+' to 'E-' or 'E+'
line = line.replace("D-", "E-")
line = line.replace("D+", "E+")
splitline = line.split()
key = splitline[0]
if key in str_keys:
setattr(self, key, splitline[1])
elif key in float_keys:
try:
setattr(self, key, float(splitline[1]))
except ValueError:
pass
if len(splitline)==3: # Some parfiles don't have flags, but do have errors
if splitline[2] not in ['0', '1']:
setattr(self, key+'_ERR', float(splitline[2]))
if len(splitline)==4:
setattr(self, key+'_ERR', float(splitline[3]))
# Deal with Ecliptic coords
if (hasattr(self, 'BETA') and hasattr(self, 'LAMBDA')):
setattr(self, 'ELAT', self.BETA)
setattr(self, 'ELONG', self.LAMBDA)
if (slalib and hasattr(self, 'ELAT') and hasattr(self, 'ELONG')):
if hasattr(self, 'POSEPOCH'):
epoch = self.POSEPOCH
else:
epoch = self.PEPOCH
ra_rad, dec_rad = sla_ecleq(self.ELONG*pu.DEGTORAD,
self.ELAT*pu.DEGTORAD, epoch)
rstr = pu.coord_to_string(*pu.rad_to_hms(ra_rad))
dstr = pu.coord_to_string(*pu.rad_to_dms(dec_rad))
setattr(self, 'RAJ', rstr)
setattr(self, 'DECJ', dstr)
if hasattr(self, 'RAJ'):
setattr(self, 'RA_RAD', pu.ra_to_rad(self.RAJ))
if hasattr(self, 'DECJ'):
setattr(self, 'DEC_RAD', pu.dec_to_rad(self.DECJ))
# Compute the Galactic coords
if (slalib and hasattr(self, 'RA_RAD') and hasattr(self, 'DEC_RAD')):
l, b = sla_eqgal(self.RA_RAD, self.DEC_RAD)
setattr(self, 'GLONG', l*pu.RADTODEG)
setattr(self, 'GLAT', b*pu.RADTODEG)
# Compute the Ecliptic coords
if (slalib and hasattr(self, 'RA_RAD') and hasattr(self, 'DEC_RAD')):
if hasattr(self, 'POSEPOCH'):
epoch = self.POSEPOCH
else:
epoch = self.PEPOCH
elon, elat = sla_eqecl(self.RA_RAD, self.DEC_RAD, epoch)
setattr(self, 'ELONG', elon*pu.RADTODEG)
setattr(self, 'ELAT', elat*pu.RADTODEG)
if hasattr(self, 'P'):
setattr(self, 'P0', self.P)
if hasattr(self, 'P0'):
setattr(self, 'F0', 1.0/self.P0)
if hasattr(self, 'F0'):
setattr(self, 'P0', 1.0/self.F0)
if hasattr(self, 'FB0'):
setattr(self, 'PB', (1.0/self.FB0)/86400.0)
if hasattr(self, 'P0_ERR'):
if hasattr(self, 'P1_ERR'):
f, ferr, fd, fderr = pu.pferrs(self.P0, self.P0_ERR,
self.P1, self.P1_ERR)
setattr(self, 'F0_ERR', ferr)
setattr(self, 'F1', fd)
setattr(self, 'F1_ERR', fderr)
else:
f, fd, = pu.p_to_f(self.P0, self.P1)
setattr(self, 'F0_ERR', self.P0_ERR/(self.P0*self.P0))
setattr(self, 'F1', fd)
if hasattr(self, 'F0_ERR'):
if hasattr(self, 'F1_ERR'):
p, perr, pd, pderr = pu.pferrs(self.F0, self.F0_ERR,
self.F1, self.F1_ERR)
setattr(self, 'P0_ERR', perr)
setattr(self, 'P1', pd)
setattr(self, 'P1_ERR', pderr)
else:
p, pd, = pu.p_to_f(self.F0, self.F1)
setattr(self, 'P0_ERR', self.F0_ERR/(self.F0*self.F0))
setattr(self, 'P1', pd)
if hasattr(self, 'EPS1') and hasattr(self, 'EPS2'):
ecc = math.sqrt(self.EPS1 * self.EPS1 + self.EPS2 * self.EPS2)
omega = math.atan2(self.EPS1, self.EPS2)
setattr(self, 'E', ecc)
setattr(self, 'OM', omega * pu.RADTODEG)
setattr(self, 'T0', self.TASC + self.PB * omega/pu.TWOPI)
if hasattr(self, 'PB') and hasattr(self, 'A1') and not \
(hasattr(self, 'E') or hasattr(self, 'ECC')):
setattr(self, 'E', 0.0)
if hasattr(self, 'T0') and hasattr(self, 'PB') and hasattr(self, 'OM') and not hasattr(self, 'TASC'):
setattr(self, 'TASC', self.T0 - self.PB * self.OM/360.0)
pf.close()
def __init__(self, parfilenm):
self.FILE = parfilenm
pf = open(parfilenm)
for line in pf.readlines():
# Skip comments
if line[0] == '#':
continue
# Convert any 'D-' or 'D+' to 'E-' or 'E+'
line = line.replace("D-", "E-")
line = line.replace("D+", "E+")
splitline = line.split()
# Skip blank lines
if len(splitline) == 0:
continue
key = splitline[0]
if key in str_keys:
setattr(self, key, splitline[1])
elif key in float_keys:
try:
setattr(self, key, float(splitline[1]))
except ValueError:
pass
if len(
splitline
) == 3: # Some parfiles don't have flags, but do have errors
if splitline[2] not in ['0', '1']:
setattr(self, key + '_ERR', float(splitline[2]))
if len(splitline) == 4:
setattr(self, key + '_ERR', float(splitline[3]))
# Deal with Ecliptic coords
if (hasattr(self, 'BETA') and hasattr(self, 'LAMBDA')):
setattr(self, 'ELAT', self.BETA)
setattr(self, 'ELONG', self.LAMBDA)
if (slalib and hasattr(self, 'ELAT') and hasattr(self, 'ELONG')):
if hasattr(self, 'POSEPOCH'):
epoch = self.POSEPOCH
else:
epoch = self.PEPOCH
ra_rad, dec_rad = sla_ecleq(self.ELONG * pu.DEGTORAD,
self.ELAT * pu.DEGTORAD, epoch)
rstr = pu.coord_to_string(*pu.rad_to_hms(ra_rad))
dstr = pu.coord_to_string(*pu.rad_to_dms(dec_rad))
setattr(self, 'RAJ', rstr)
setattr(self, 'DECJ', dstr)
if hasattr(self, 'RAJ'):
setattr(self, 'RA_RAD', pu.ra_to_rad(self.RAJ))
if hasattr(self, 'DECJ'):
setattr(self, 'DEC_RAD', pu.dec_to_rad(self.DECJ))
# Compute the Galactic coords
if (slalib and hasattr(self, 'RA_RAD') and hasattr(self, 'DEC_RAD')):
l, b = sla_eqgal(self.RA_RAD, self.DEC_RAD)
setattr(self, 'GLONG', l * pu.RADTODEG)
setattr(self, 'GLAT', b * pu.RADTODEG)
# Compute the Ecliptic coords
if (slalib and hasattr(self, 'RA_RAD') and hasattr(self, 'DEC_RAD')):
if hasattr(self, 'POSEPOCH'):
epoch = self.POSEPOCH
else:
epoch = self.PEPOCH
elon, elat = sla_eqecl(self.RA_RAD, self.DEC_RAD, epoch)
setattr(self, 'ELONG', elon * pu.RADTODEG)
setattr(self, 'ELAT', elat * pu.RADTODEG)
if hasattr(self, 'P'):
setattr(self, 'P0', self.P)
if hasattr(self, 'P0'):
setattr(self, 'F0', 1.0 / self.P0)
if hasattr(self, 'F0'):
setattr(self, 'P0', 1.0 / self.F0)
if hasattr(self, 'FB0'):
setattr(self, 'PB', (1.0 / self.FB0) / 86400.0)
if hasattr(self, 'P0_ERR'):
if hasattr(self, 'P1_ERR'):
f, ferr, fd, fderr = pu.pferrs(self.P0, self.P0_ERR, self.P1,
self.P1_ERR)
setattr(self, 'F0_ERR', ferr)
setattr(self, 'F1', fd)
setattr(self, 'F1_ERR', fderr)
else:
f, fd, = pu.p_to_f(self.P0, self.P1)
setattr(self, 'F0_ERR', self.P0_ERR / (self.P0 * self.P0))
setattr(self, 'F1', fd)
if (hasattr(self, 'F0_ERR') and hasattr(self, 'F1_ERR')):
p, perr, pd, pderr = pu.pferrs(self.F0, self.F0_ERR, self.F1,
self.F1_ERR)
setattr(self, 'P0_ERR', perr)
setattr(self, 'P1', pd)
setattr(self, 'P1_ERR', pderr)
elif (hasattr(self, 'F0') and hasattr(self, 'F0_ERR')):
setattr(self, 'P0_ERR', self.F0_ERR / (self.F0 * self.F0))
if hasattr(self, 'EPS1') and hasattr(self, 'EPS2'):
ecc = math.sqrt(self.EPS1 * self.EPS1 + self.EPS2 * self.EPS2)
omega = math.atan2(self.EPS1, self.EPS2)
setattr(self, 'E', ecc)
setattr(self, 'OM', omega * pu.RADTODEG)
setattr(self, 'T0', self.TASC + self.PB * omega / pu.TWOPI)
if hasattr(self, 'PB') and hasattr(self, 'A1') and not \
(hasattr(self, 'E') or hasattr(self, 'ECC')):
setattr(self, 'E', 0.0)
if hasattr(self, 'T0') and not hasattr(self, 'TASC'):
setattr(self, 'TASC', self.T0 - self.PB * self.OM / 360.0)
pf.close()
params_start = [p_start, pb_sec_start, x_start, T0_start, e_start, w_start]
# build the dictionary of parameter information
params_info = get_params_info(params_start, const_params)
period = []
time = []
pepochs = []
p0s = []
p1s = []
# get the observed periods and times from the .bestprof files
for in_file in in_files:
if in_file.endswith(".par"):
(epoch, T, fs) = read_par(in_file)
if fs[1] != 0.0:
p0tmp, p1tmp = psr_utils.p_to_f(fs[0], fs[1])
p0s.append(p0tmp)
p1s.append(p1tmp)
pepochs.append(epoch)
for minute in arange(int(T / 60.0 + 0.5)):
t = epoch + minute / 1440.0
time.append(t)
period.append(1.0 / psr_utils.calc_freq(t, epoch, *fs))
else:
(epoch, T, p0, p1, p2) = read_bestprof(in_file)
for minute in arange(int(T / 60.0 + 0.5)):
t = minute * 60.0
time.append(epoch + minute / 1440.0)
period.append(p0 + t * (p1 + 0.5 * t * p2))
if p1 != 0.0:
p0s.append(p0)
def __init__(self, parfilenm):
self.FILE = parfilenm
pf = open(parfilenm)
for line in pf.readlines():
# Skip comments
if line[0] == '#':
continue
# Convert any 'D-' or 'D+' to 'E-' or 'E+'
line = line.replace("D-", "E-")
line = line.replace("D+", "E+")
splitline = line.split()
# Skip blank lines
if len(splitline) == 0:
continue
key = splitline[0]
# Regex checks for non-digit chars, followed by digit chars
m1 = re.search(r'(\D+)(\d+)$', key)
# This one looks for the DMX[RF][12]_* params
m2 = re.search(r'(\D+\d+_)(\d+)$', key)
if key == "JUMP":
if splitline[3] not in ['0', '1']:
setattr(self, key + '_%s' % splitline[2],
float(splitline[3]))
if len(splitline) == 5:
if splitline[4] not in ['0', '1']:
setattr(self, key + '_%s' % splitline[2] + '_ERR',
float(splitline[4]))
elif len(splitline) == 6:
setattr(self, key + '_%s' % splitline[2] + '_ERR',
float(splitline[5]))
if key in str_keys:
setattr(self, key, splitline[1])
elif key in float_keys:
try:
setattr(self, key, float(splitline[1]))
except ValueError:
pass
elif m1 is not None:
m = m1
if m2 is not None:
m = m2
if m.group(1) in floatn_keys:
try:
setattr(self, key, float(splitline[1]))
except ValueError:
pass
if len(
splitline
) == 3: # Some parfiles don't have flags, but do have errors
if splitline[2] not in ['0', '1']:
setattr(self, key + '_ERR', float(splitline[2]))
if len(splitline) == 4:
setattr(self, key + '_ERR', float(splitline[3]))
# Deal with Ecliptic coords
if (hasattr(self, 'BETA') and hasattr(self, 'LAMBDA')):
setattr(self, 'ELAT', self.BETA)
setattr(self, 'ELONG', self.LAMBDA)
if (slalib and hasattr(self, 'ELAT') and hasattr(self, 'ELONG')):
# TEMPO's ecliptic coords are always based on J2000 epoch
ra_rad, dec_rad = sla_ecleq(self.ELONG * pu.DEGTORAD,
self.ELAT * pu.DEGTORAD, J2000)
rstr = pu.coord_to_string(*pu.rad_to_hms(ra_rad))
dstr = pu.coord_to_string(*pu.rad_to_dms(dec_rad))
setattr(self, 'RAJ', rstr)
setattr(self, 'DECJ', dstr)
if hasattr(self, 'RAJ'):
setattr(self, 'RA_RAD', pu.ra_to_rad(self.RAJ))
if hasattr(self, 'DECJ'):
setattr(self, 'DEC_RAD', pu.dec_to_rad(self.DECJ))
# Compute the Galactic coords
if (slalib and hasattr(self, 'RA_RAD') and hasattr(self, 'DEC_RAD')):
l, b = sla_eqgal(self.RA_RAD, self.DEC_RAD)
setattr(self, 'GLONG', l * pu.RADTODEG)
setattr(self, 'GLAT', b * pu.RADTODEG)
# Compute the Ecliptic coords
if (slalib and hasattr(self, 'RA_RAD') and hasattr(self, 'DEC_RAD')):
# TEMPO's ecliptic coords are always based on J2000 epoch
elon, elat = sla_eqecl(self.RA_RAD, self.DEC_RAD, J2000)
setattr(self, 'ELONG', elon * pu.RADTODEG)
setattr(self, 'ELAT', elat * pu.RADTODEG)
if hasattr(self, 'P'):
setattr(self, 'P0', self.P)
if hasattr(self, 'P0'):
setattr(self, 'F0', 1.0 / self.P0)
if hasattr(self, 'F0'):
setattr(self, 'P0', 1.0 / self.F0)
if hasattr(self, 'FB0'):
setattr(self, 'PB', (1.0 / self.FB0) / 86400.0)
if hasattr(self, 'P0_ERR'):
if hasattr(self, 'P1_ERR'):
f, ferr, fd, fderr = pu.pferrs(self.P0, self.P0_ERR, self.P1,
self.P1_ERR)
setattr(self, 'F0_ERR', ferr)
setattr(self, 'F1', fd)
setattr(self, 'F1_ERR', fderr)
else:
f, fd, = pu.p_to_f(self.P0, self.P1)
setattr(self, 'F0_ERR', self.P0_ERR / (self.P0 * self.P0))
setattr(self, 'F1', fd)
else:
if hasattr(self, 'P1'):
f, fd, = pu.p_to_f(self.P0, self.P1)
setattr(self, 'F1', fd)
elif hasattr(self, 'F1'):
p, pd, = pu.p_to_f(self.F0, self.F1)
setattr(self, 'P1', pd)
if (hasattr(self, 'F0_ERR') and hasattr(self, 'F1_ERR')):
p, perr, pd, pderr = pu.pferrs(self.F0, self.F0_ERR, self.F1,
self.F1_ERR)
setattr(self, 'P0_ERR', perr)
setattr(self, 'P1', pd)
setattr(self, 'P1_ERR', pderr)
elif (hasattr(self, 'F0') and hasattr(self, 'F0_ERR')):
setattr(self, 'P0_ERR', self.F0_ERR / (self.F0 * self.F0))
if hasattr(self, 'EPS1') and hasattr(self, 'EPS2'):
ecc = math.sqrt(self.EPS1 * self.EPS1 + self.EPS2 * self.EPS2)
omega = math.atan2(self.EPS1, self.EPS2)
setattr(self, 'E', ecc)
setattr(self, 'OM', omega * pu.RADTODEG)
setattr(self, 'T0', self.TASC + self.PB * omega / pu.TWOPI)
if hasattr(self, 'PB') and hasattr(self, 'A1') and not \
(hasattr(self, 'E') or hasattr(self, 'ECC')):
setattr(self, 'E', 0.0)
if hasattr(self, 'T0') and not hasattr(self, 'TASC'):
setattr(self, 'TASC', self.T0 - self.PB * self.OM / 360.0)
if hasattr(self, 'E') and not hasattr(self, 'ECC'):
setattr(self, 'ECC', self.E)
if not hasattr(self, 'EPS1'):
setattr(self, 'ECC_ERR', self.E_ERR)
if hasattr(self, 'ECC') and not hasattr(self, 'E'):
setattr(self, 'E', self.ECC)
setattr(self, 'E_ERR', self.ECC_ERR)
pf.close()
params_start = [p_start, pb_sec_start, x_start, T0_start, e_start, w_start]
# build the dictionary of parameter information
params_info = get_params_info(params_start, const_params)
period = []
time = []
pepochs = []
p0s = []
p1s = []
# get the observed periods and times from the .bestprof files
for in_file in in_files:
if in_file.endswith('.par'):
(epoch, T, fs) = read_par(in_file)
if (fs[1] != 0.0):
p0tmp, p1tmp = psr_utils.p_to_f(fs[0], fs[1])
p0s.append(p0tmp)
p1s.append(p1tmp)
pepochs.append(epoch)
for minute in arange(int(T / 60.0 + 0.5)):
t = epoch + minute / 1440.0
time.append(t)
period.append(1.0 / psr_utils.calc_freq(t, epoch, *fs))
else:
(epoch, T, p0, p1, p2) = read_bestprof(in_file)
for minute in arange(int(T / 60.0 + 0.5)):
t = minute * 60.0
time.append(epoch + minute / 1440.0)
period.append(p0 + t * (p1 + 0.5 * t * p2))
if p1 != 0.0:
p0s.append(p0)
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
psrs = pulsars.values()
psrs.sort()
# Now create a new dictionary of pulsars with aliases
psr_aliases = {}
for psr in psrs:
if psr.alias:
psr_aliases[psr.alias] = psr
# Add a couple important pulsars
for psr in psrs:
if psr.jname == "1614-23":
psr.jname == "1614-2318"
psr.f = 29.8475387364133766
psr.fd = -4.683105034721e-17
psr.p, psr.pd = psr_utils.p_to_f(psr.f, psr.fd)
psr.x = 1.327490
psr.e = 0.0
psr.To = 52819.878171
psr.pb = 3.15238573
psr.w = 0.0
psr.dm = 52.43
psr.l = 351.91856
psr.b = 19.74496
psr.dist = 1.80
# If calling this as a main program, then write out the new pulsars.cat file
if __name__ == '__main__':
presto_path = os.getenv("PRESTO")
outfilename = os.path.join(presto_path, "lib", "pulsars.cat")
outfile = open(outfilename, "w")
def __init__(self, parfilenm):
self.FILE = parfilenm
pf = open(parfilenm)
for line in pf.readlines():
# Skip comments
if line[0]=='#':
continue
# Convert any 'D-' or 'D+' to 'E-' or 'E+'
line = line.replace("D-", "E-")
line = line.replace("D+", "E+")
splitline = line.split()
# Skip blank lines
if len(splitline)==0:
continue
key = splitline[0]
# Regex checks for non-digit chars, followed by digit chars
m1 = re.search(r'(\D+)(\d+)$', key)
# This one looks for the DMX[RF][12]_* params
m2 = re.search(r'(\D+\d+_)(\d+)$', key)
if key == "JUMP":
if splitline[3] not in ['0', '1']:
setattr(self, key+'_%s'%splitline[2], float(splitline[3]))
if len(splitline)==5:
if splitline[4] not in ['0', '1']:
setattr(self, key+'_%s'%splitline[2]+'_ERR',
float(splitline[4]))
elif len(splitline)==6:
setattr(self, key+'_%s'%splitline[2]+'_ERR',
float(splitline[5]))
if key in str_keys:
setattr(self, key, splitline[1])
elif key in float_keys:
try:
setattr(self, key, float(splitline[1]))
except ValueError:
pass
elif m1 is not None:
m = m1
if m2 is not None:
m = m2
if m.group(1) in floatn_keys:
try:
setattr(self, key, float(splitline[1]))
except ValueError:
pass
if len(splitline)==3: # Some parfiles don't have flags, but do have errors
if splitline[2] not in ['0', '1']:
setattr(self, key+'_ERR', float(splitline[2]))
if len(splitline)==4:
setattr(self, key+'_ERR', float(splitline[3]))
# Deal with Ecliptic coords
if (hasattr(self, 'BETA') and hasattr(self, 'LAMBDA')):
setattr(self, 'ELAT', self.BETA)
setattr(self, 'ELONG', self.LAMBDA)
if (slalib and hasattr(self, 'ELAT') and hasattr(self, 'ELONG')):
if hasattr(self, 'POSEPOCH'):
epoch = self.POSEPOCH
else:
epoch = self.PEPOCH
ra_rad, dec_rad = sla_ecleq(self.ELONG*pu.DEGTORAD,
self.ELAT*pu.DEGTORAD, epoch)
rstr = pu.coord_to_string(*pu.rad_to_hms(ra_rad))
dstr = pu.coord_to_string(*pu.rad_to_dms(dec_rad))
setattr(self, 'RAJ', rstr)
setattr(self, 'DECJ', dstr)
if hasattr(self, 'RAJ'):
setattr(self, 'RA_RAD', pu.ra_to_rad(self.RAJ))
if hasattr(self, 'DECJ'):
setattr(self, 'DEC_RAD', pu.dec_to_rad(self.DECJ))
# Compute the Galactic coords
if (slalib and hasattr(self, 'RA_RAD') and hasattr(self, 'DEC_RAD')):
l, b = sla_eqgal(self.RA_RAD, self.DEC_RAD)
setattr(self, 'GLONG', l*pu.RADTODEG)
setattr(self, 'GLAT', b*pu.RADTODEG)
# Compute the Ecliptic coords
if (slalib and hasattr(self, 'RA_RAD') and hasattr(self, 'DEC_RAD')):
if hasattr(self, 'POSEPOCH'):
epoch = self.POSEPOCH
else:
epoch = self.PEPOCH
elon, elat = sla_eqecl(self.RA_RAD, self.DEC_RAD, epoch)
setattr(self, 'ELONG', elon*pu.RADTODEG)
setattr(self, 'ELAT', elat*pu.RADTODEG)
if hasattr(self, 'P'):
setattr(self, 'P0', self.P)
if hasattr(self, 'P0'):
setattr(self, 'F0', 1.0/self.P0)
if hasattr(self, 'F0'):
setattr(self, 'P0', 1.0/self.F0)
if hasattr(self, 'FB0'):
setattr(self, 'PB', (1.0/self.FB0)/86400.0)
if hasattr(self, 'P0_ERR'):
if hasattr(self, 'P1_ERR'):
f, ferr, fd, fderr = pu.pferrs(self.P0, self.P0_ERR,
self.P1, self.P1_ERR)
setattr(self, 'F0_ERR', ferr)
setattr(self, 'F1', fd)
setattr(self, 'F1_ERR', fderr)
else:
f, fd, = pu.p_to_f(self.P0, self.P1)
setattr(self, 'F0_ERR', self.P0_ERR/(self.P0*self.P0))
setattr(self, 'F1', fd)
else:
if hasattr(self, 'P1'):
f, fd, = pu.p_to_f(self.P0, self.P1)
setattr(self, 'F1', fd)
elif hasattr(self, 'F1'):
p, pd, = pu.p_to_f(self.F0, self.F1)
setattr(self, 'P1', pd)
if (hasattr(self, 'F0_ERR') and hasattr(self, 'F1_ERR')):
p, perr, pd, pderr = pu.pferrs(self.F0, self.F0_ERR,
self.F1, self.F1_ERR)
setattr(self, 'P0_ERR', perr)
setattr(self, 'P1', pd)
setattr(self, 'P1_ERR', pderr)
elif (hasattr(self, 'F0') and hasattr(self, 'F0_ERR')):
setattr(self, 'P0_ERR', self.F0_ERR/(self.F0*self.F0))
if hasattr(self, 'EPS1') and hasattr(self, 'EPS2'):
ecc = math.sqrt(self.EPS1 * self.EPS1 + self.EPS2 * self.EPS2)
omega = math.atan2(self.EPS1, self.EPS2)
setattr(self, 'E', ecc)
setattr(self, 'OM', omega * pu.RADTODEG)
setattr(self, 'T0', self.TASC + self.PB * omega/pu.TWOPI)
if hasattr(self, 'PB') and hasattr(self, 'A1') and not \
(hasattr(self, 'E') or hasattr(self, 'ECC')):
setattr(self, 'E', 0.0)
if hasattr(self, 'T0') and not hasattr(self, 'TASC'):
setattr(self, 'TASC', self.T0 - self.PB * self.OM/360.0)
pf.close()
def __init__(self, cand_num, pfd , snr, coherent_power, \
incoherent_power, num_hits, num_harmonics, \
versionnum, sigma, sifting_period, sifting_dm, \
cand_attribs, search_type, header_id=None):
self.header_id = header_id # Header ID from database
self.cand_num = cand_num # Unique identifier of candidate within beam's
# list of candidates; Candidate's position in
# a list of all candidates produced in beam
# ordered by decreasing sigma (where largest
# sigma has cand_num=1).
self.search_type = search_type
self.topo_freq, self.topo_f_dot, fdd = \
psr_utils.p_to_f(pfd.topo_p1, pfd.topo_p2, pfd.topo_p3)
self.bary_freq, self.bary_f_dot, baryfdd = \
psr_utils.p_to_f(pfd.bary_p1, pfd.bary_p2, pfd.bary_p3)
self.dm = pfd.bestdm # Dispersion measure
self.snr = snr # signal-to-noise ratio
self.coherent_power = coherent_power # Coherent power
self.incoherent_power = incoherent_power # Incoherent power
self.num_hits = num_hits # Number of dedispersed timeseries candidate was found in
self.num_harmonics = num_harmonics # Number of harmonics candidate was
# most significant with
self.versionnum = versionnum # Version number; a combination of PRESTO's githash
# and pipeline's githash
self.sigma = sigma # PRESTO's sigma value
#red_chi2 = pfd.bestprof.chi_sqr #prepfold reduced chi-squared
#dof = pfd.proflen - 1 # degrees of freedom
##prepfold sigma
#self.prepfold_sigma = \
# scipy.special.ndtri(scipy.special.chdtr(dof,dof*red_chi2))
#off_red_chi2 = pfd.estimate_offsignal_redchi2()
#chi2_scale = 1.0/off_red_chi2
#new_red_chi2 = chi2_scale * red_chi2
## prepfold sigma rescaled to deal with chi-squared suppression
## a problem when strong rfi is present
#self.rescaled_prepfold_sigma = \
# scipy.special.ndtri(scipy.special.chdtr(dof,dof*new_red_chi2))
self.prepfold_sigma = float(cand_attribs['prepfold_sigma'])
self.rescaled_prepfold_sigma = float(cand_attribs['rescaled_prepfold_sigma'])
if np.isinf(self.prepfold_sigma):
self.prepfold_sigma = 9999.0
if np.isinf(self.rescaled_prepfold_sigma):
self.rescaled_prepfold_sigma = 9999.0
self.sifting_period = sifting_period # the period returned by accelsearch
# (not optimized by prepfold)
self.sifting_dm = sifting_dm # the DM returned by accelsearch
# (not optimized by prepfold)
# Store a few configurations so the upload can be checked
self.pipeline = config.basic.pipeline
self.institution = config.basic.institution
# Calculate a few more values
self.topo_period = 1.0/self.topo_freq
self.bary_period = 1.0/self.bary_freq
# List of dependents (ie other uploadables that require
# the pdm_cand_id from this candidate)
self.dependents = []