def sampleQSO(parser):
(options, args) = parser.parse_args()
if len(args) == 0:
parser.print_help()
return
if len(args) == 2:
othersavefilename = args[1]
othersavefile = open(othersavefilename, 'rb')
othersamples = pickle.load(othersavefile)
othersavefile.close()
else:
othersamples = {}
savefilename = args[0]
if os.path.exists(savefilename):
savefile = open(savefilename, 'rb')
samples = pickle.load(savefile)
type = pickle.load(savefile)
band = pickle.load(savefile)
mean = pickle.load(savefile)
savefile.close()
else:
samples = {}
type = options.type
mean = options.mean
band = options.band
if os.path.exists(options.fitsfile):
fitsfile = open(options.fitsfile, 'rb')
params = pickle.load(fitsfile)
fitsfile.close()
else:
raise IOError(
"--fitsfile (or -f) has to be set to the file holding the best-fits"
)
if options.star:
dir = '../data/star/'
elif options.nuvx:
dir = '../data/nuvx/'
elif options.nuvxall:
dir = '../data/nuvx_all/'
elif options.uvx:
dir = '../data/uvx/'
elif options.rrlyrae:
dir = '../data/rrlyrae/'
else:
dir = '../data/s82qsos/'
if options.resampled:
raise NotImplementedError("resampled not implemented yet")
if os.path.exists(options.infile):
samplefile = open(options.infile, 'rb')
qsos = pickle.load(samplefile)
samplefile.close()
else:
print "'--resampled' is set, but -i filename does not exist ..."
print "Returning ..."
return None
else:
qsos = QSOfilenames(dir=dir)
#Register time-out handler
signal.signal(signal.SIGALRM, handler)
savecount = 0
count = len(samples)
for qso in qsos:
if options.resampled:
key = qso[0]
else:
key = os.path.basename(qso)
if samples.has_key(key) or othersamples.has_key(key):
continue
try:
if int(key[5:7]) != options.rah and options.rah != -1:
continue
except ValueError:
if options.rah == -2 or options.rah == -1:
pass
else:
print "Skipping ValueError " + key
continue
print "Working on " + str(count) + ": " + key
if options.resampled:
v = qso[1]
else:
v = VarQso(qso)
if v.nepochs(band) < 20:
print "This object does not have enough epochs ..."
continue
#Set best-fit
v.LCparams = params[key]
v.LC = LCmodel(trainSet=v._build_trainset(band), type=type, mean=mean)
v.LCtype = type
v.LCmean = mean
v.fitband = band
#Now sample
signal.alarm(options.timeout)
try:
v.sampleGP(nsamples=options.nsamples,
metropolis=options.metropolis,
markovpy=options.markovpy,
burnin=int(nu.floor(0.2 * options.nsamples)))
except Exception, exc:
if str(exc) == "Sampling timed out":
print exc
continue
else:
raise
signal.alarm(0)
samples[key] = v.get_sampleGP()
if _DEBUG:
_print_diagnostics(samples[key])
#print samples[key][options.nsamples]
savecount += 1
if savecount == options.saveevery:
print "Saving ..."
save_pickles(samples, type, band, mean, savefilename)
savecount = 0
count += 1
def sampleQSO(parser):
(options,args)= parser.parse_args()
if len(args) == 0:
parser.print_help()
return
if len(args) == 2:
othersavefilename= args[1]
othersavefile= open(othersavefilename,'rb')
othersamples= pickle.load(othersavefile)
othersavefile.close()
else:
othersamples= {}
savefilename= args[0]
if os.path.exists(savefilename):
savefile= open(savefilename,'rb')
samples= pickle.load(savefile)
type= pickle.load(savefile)
band= pickle.load(savefile)
mean= pickle.load(savefile)
savefile.close()
else:
samples= {}
type= options.type
mean= options.mean
band= options.band
if os.path.exists(options.fitsfile):
fitsfile= open(options.fitsfile,'rb')
params= pickle.load(fitsfile)
fitsfile.close()
else:
raise IOError("--fitsfile (or -f) has to be set to the file holding the best-fits")
if options.star:
dir= '../data/star/'
elif options.nuvx:
dir= '../data/nuvx/'
elif options.nuvxall:
dir= '../data/nuvx_all/'
elif options.uvx:
dir= '../data/uvx/'
elif options.rrlyrae:
dir= '../data/rrlyrae/'
else:
dir= '../data/s82qsos/'
if options.resampled:
raise NotImplementedError("resampled not implemented yet")
if os.path.exists(options.infile):
samplefile= open(options.infile,'rb')
qsos= pickle.load(samplefile)
samplefile.close()
else:
print "'--resampled' is set, but -i filename does not exist ..."
print "Returning ..."
return None
else:
qsos= QSOfilenames(dir=dir)
#Register time-out handler
signal.signal(signal.SIGALRM, handler)
savecount= 0
count= len(samples)
for qso in qsos:
if options.resampled:
key= qso[0]
else:
key= os.path.basename(qso)
if samples.has_key(key) or othersamples.has_key(key):
continue
try:
if int(key[5:7]) != options.rah and options.rah != -1:
continue
except ValueError:
if options.rah == -2 or options.rah == -1:
pass
else:
print "Skipping ValueError "+key
continue
print "Working on "+str(count)+": "+key
if options.resampled:
v= qso[1]
else:
v= VarQso(qso)
if options.lownepochs:
if v.nepochs(band) >= 20:
print "This object has too many epochs ..."
continue
elif v.nepochs(band) < 3:
print "This object has < 3 epochs ..."
continue
elif not options.lownepochs and v.nepochs(band) < 20:
print "This object does not have enough epochs ..."
continue
#Set best-fit
v.LCparams= params[key]
v.LC= LCmodel(trainSet=v._build_trainset(band),type=type,mean=mean,
init_params=params[key])
v.LCtype= type
v.LCmean= mean
v.fitband= band
#Now sample
signal.alarm(options.timeout)
try:
v.sampleGP(nsamples=options.nsamples,metropolis=options.metropolis,
markovpy=options.markovpy,
burnin=int(nu.floor(0.2*options.nsamples)))
except Exception, exc:
if str(exc) == "Sampling timed out":
print exc
continue
else:
raise
signal.alarm(0)
samples[key]= v.get_sampleGP()
if _DEBUG:
_print_diagnostics(samples[key])
#print samples[key][options.nsamples]
savecount+= 1
if savecount == options.saveevery:
print "Saving ..."
save_pickles(samples,type,band,mean,savefilename)
savecount= 0
count+= 1
print exc
continue
else:
raise
signal.alarm(0)
samples[key] = v.get_sampleGP()
if _DEBUG:
_print_diagnostics(samples[key])
#print samples[key][options.nsamples]
savecount += 1
if savecount == options.saveevery:
print "Saving ..."
save_pickles(samples, type, band, mean, savefilename)
savecount = 0
count += 1
save_pickles(samples, type, band, mean, savefilename)
print "All done"
def _print_diagnostics(sample):
"""Internal function to print some diagnostics"""
keys = sample[0].keys()
for key in sample[0].keys():
xs = []
for ii in range(len(sample)):
xs.append(sample[ii][key][0])
xs = nu.array(xs)
print key, nu.mean(xs), nu.std(xs)
def get_options():
print exc
continue
else:
raise
signal.alarm(0)
samples[key]= v.get_sampleGP()
if _DEBUG:
_print_diagnostics(samples[key])
#print samples[key][options.nsamples]
savecount+= 1
if savecount == options.saveevery:
print "Saving ..."
save_pickles(samples,type,band,mean,savefilename)
savecount= 0
count+= 1
save_pickles(samples,type,band,mean,savefilename)
print "All done"
def _print_diagnostics(sample):
"""Internal function to print some diagnostics"""
keys= sample[0].keys()
for key in sample[0].keys():
xs= []
for ii in range(len(sample)):
xs.append(sample[ii][key][0])
xs= nu.array(xs)
print key, nu.mean(xs), nu.std(xs)
def get_options():
usage = "usage: %prog [options] <savefilename>\n\nsavefilename= name of the file that the samples will be saved to"
parser = OptionParser(usage=usage)