def plotBayesGrid(lcfile,
ax='',
trestrange=[-15, 30],
CCmoderr=0.1,
Nsim=2000,
kcorfile='PS1/kcor_tonry_SALT2.fits',
nlogz=0):
close('all')
import snana
sn = snana.SuperNova(lcfile)
sn.doGridClassify(clobber=3,
noCosmoPrior=True,
kcorfile=kcorfile,
trestrange=trestrange,
modelerror=[0.08, CCmoderr],
Nsim=Nsim,
nlogz=nlogz)
if not ax:
close('all')
ax1 = axes([0.12, 0.09, 0.75, 0.27])
ax2 = axes([0.12, 0.36, 0.75, 0.27])
ax3 = axes([0.12, 0.63, 0.75, 0.27])
#plot the data points
for m, f, e, flt in zip(sn.MJD, sn.FLUXCAL, sn.FLUXCALERR, sn.FLT):
ax1.errorbar(m, f, yerr=e, color=filt_color[flt], fmt='.')
ax2.errorbar(m, f, yerr=e, color=filt_color[flt], fmt='.')
ax3.errorbar(m, f, yerr=e, color=filt_color[flt], fmt='.')
for f in sn.FILTERS:
row = where(sn.ClassSim.Ia.FLT[0] == f)[0]
ax1.plot(sn.trestbestIa * (1 + sn.z) + sn.pkmjd,
sn.bestlcIa[row],
color=filt_color[f])
ax2.plot(sn.trestbestIbc * (1 + sn.z) + sn.pkmjd,
sn.bestlcIbc[row],
color=filt_color[f])
ax3.plot(sn.trestbestII * (1 + sn.z) + sn.pkmjd,
sn.bestlcII[row],
color=filt_color[f])
ax2.set_ylabel('Flux')
ax1.set_xlabel('MJD')
ax1.set_ylim([0, max(sn.FLUXCAL) + 5])
ax1.set_xlim([sn.pkmjd - 20, sn.pkmjd + 60])
ax2.set_ylim([0, max(sn.FLUXCAL) + 5])
ax2.set_xlim([sn.pkmjd - 20, sn.pkmjd + 60])
ax3.set_ylim([0, max(sn.FLUXCAL) + 5])
ax3.set_xlim([sn.pkmjd - 20, sn.pkmjd + 60])
print('# PIa PIbc PII')
print sn.PIa, sn.PIbc, sn.PII
import pdb
pdb.set_trace()
return
def uploadSNANAPhotometry(self, db=None):
import snana
sn = snana.SuperNova(self.options.inputfile)
if self.options.foundationdefaults:
sn.SNID = sn.otherID[2:]
transid = db.get_transient_from_DB(sn.SNID)
if self.options.onlyexisting and not transid:
if 'otherID' in sn.__dict__.keys():
print('Object %s not found! Trying %s' %
(sn.SNID, sn.otherID))
sn.SNID = sn.otherID
transid = db.get_transient_from_DB(sn.SNID)
if self.options.onlyexisting and not transid:
print('Object %s not found! Returning' % sn.SNID)
return ()
print('uploading object %s' % sn.SNID)
if self.options.useheader:
transid = self.uploadHeader(sn)
transname = sn.SNID
else:
transid = db.get_transient_from_DB(sn.SNID)
transname = sn.SNID
# get dictionaries for transient and photometry
if type(sn.RA) == float:
transientdict, photdict = self.parsePhotHeaderData(
transname, sn.RA, sn.DECL)
else:
transientdict, photdict = self.parsePhotHeaderData(
transname,
sn.RA.split()[0],
sn.DECL.split()[0])
# get the filter IDs
PhotUploadAll = {'transient': transientdict, 'photheader': photdict}
# upload the photometry
for mjd, flux, fluxerr, mag, magerr, flt, i in zip(
sn.MJD, sn.FLUXCAL, sn.FLUXCALERR, sn.MAG, sn.MAGERR, sn.FLT,
range(len(sn.FLT))):
obsdate = Time(mjd, format='mjd').isot
PhotUploadDict = {
'obs_date': obsdate,
'flux': flux,
'flux_err': fluxerr,
'forced': self.options.forcedphot,
'diffim': self.options.diffim,
'band': flt,
'groups': []
}
if flux > 0:
PhotUploadDict['mag'] = mag
PhotUploadDict['mag_err'] = magerr
else:
PhotUploadDict['mag'] = None
PhotUploadDict['mag_err'] = None
if self.options.fluxzpt:
PhotUploadDict['flux_zero_point'] = self.options.fluxzpt
else:
PhotUploadDict['flux_zero_point'] = None
if 'SEARCH_PEAKMJD' in sn.__dict__.keys(
) and np.abs(mjd - sn.SEARCH_PEAKMJD) < 0.5:
PhotUploadDict['discovery_point'] = 1
else:
PhotUploadDict['discovery_point'] = 0
if 'DQ' in sn.__dict__.keys():
if sn.DQ[i]:
PhotUploadDict['data_quality'] = str(sn.DQ[i])
else:
PhotUploadDict['data_quality'] = None
else:
PhotUploadDict['data_quality'] = None
PhotUploadAll['%s_%i' % (obsdate, i)] = PhotUploadDict
PhotUploadAll['header'] = {
'clobber': self.options.clobber,
'mjdmatchmin': self.options.mjdmatchmin
}
print(PhotUploadAll)
import requests
from requests.auth import HTTPBasicAuth
url = '%s' % db.dburl.replace('/api', '/add_transient_phot')
def myconverter(obj):
if obj is np.nan:
return None
elif isinstance(obj, np.integer):
return int(obj)
elif isinstance(obj, np.floating):
return float(obj)
elif isinstance(obj, np.ndarray):
return obj.tolist()
elif isinstance(obj, datetime.datetime):
return obj.__str__()
r = requests.post(url=url,
data=json.dumps(PhotUploadAll, default=myconverter),
auth=HTTPBasicAuth(db.dblogin, db.dbpassword))
print('YSE_PZ says: %s' % json.loads(r.text)['message'])
def mktib(lcfile='/Users/David/tib.DAT',
ax='',
trestrange=[-15, 30],
CCmoderr=0.1,
Nsim=2000,
kcorfile='PS1/kcor_tonry_SALT2.fits',
nlogz=0,
sn=''):
"""Separate plots of best-fit tiberius light curves for Brandon"""
close('all')
import snana
if not sn:
sn = snana.SuperNova(lcfile)
sn.doGridClassify(clobber=3,
noCosmoPrior=True,
kcorfile=kcorfile,
trestrange=trestrange,
modelerror=[0.08, CCmoderr],
Nsim=Nsim,
nlogz=nlogz)
if not ax:
close('all')
import rcpar
reload(rcpar)
fig = rcpar.fullpaperfig()
ax1 = fig.add_subplot(331)
ax2 = fig.add_subplot(332)
ax3 = fig.add_subplot(333)
ax4 = fig.add_subplot(334)
ax5 = fig.add_subplot(335)
ax6 = fig.add_subplot(336)
ax7 = fig.add_subplot(337)
ax8 = fig.add_subplot(338)
ax9 = fig.add_subplot(339)
filtorder = array([0, 4, 1, 6, 7, 5, 2, 3])
axlist = [ax1, ax2, ax3, ax4, ax5, ax6, ax7, ax8]
axlist = array(axlist)[filtorder]
#plot the data points
for m, f, e, flt in zip(sn.MJD, sn.FLUXCAL, sn.FLUXCALERR, sn.FLT):
row = where(flt == unique(sn.FLT))[0][0]
limrow = where(flt == sn.FLT)[0]
axlist[row].set_ylim([0, max(sn.FLUXCAL[limrow]) + 10])
if flt == 'H' or flt == 'J' or flt == 'Z':
axlist[row].set_ylim([0, max(sn.FLUXCAL[limrow]) + 20])
if flt == 'R': axlist[row].set_ylim([0, 10])
if flt == 'V': axlist[row].set_ylim([0, 6])
axlist[row].errorbar(m, f, yerr=e, color='k', fmt='o')
frow = where(array(filter2band.values()) == flt)[0]
filter = filter2band.keys()[frow]
if flt != 'H' and flt != 'J' and flt != 'Z' and flt != 'R' and flt != 'V':
axlist[row].text(sn.pkmjd + 30,
max(sn.FLUXCAL[limrow] + 10.) * 6 / 8.,
'%s' % filter,
fontsize=20,
style='normal')
elif flt == 'H' or flt == 'J' or flt == 'Z':
axlist[row].text(sn.pkmjd + 30,
max(sn.FLUXCAL[limrow] + 20.) * 6 / 8.,
'%s' % filter,
fontsize=20,
style='normal')
elif flt == 'R':
axlist[row].text(sn.pkmjd + 30,
10. * 6 / 8.,
'%s' % filter,
fontsize=20,
style='normal')
elif flt == 'V':
axlist[row].text(sn.pkmjd + 30,
6. * 6 / 8.,
'%s' % filter,
fontsize=20,
style='normal')
for f, ax in zip(unique(sn.FLT), axlist):
row = where(sn.ClassSim.Ia.FLT[0] == f)[0]
if f == 'H':
pkmjdrow = where(sn.maxLikeIaModel.FLUXCAL[row] == max(
sn.maxLikeIaModel.FLUXCAL[row]))[0]
pkmjd = sn.maxLikeIaModel.MJD[pkmjdrow]
ax.plot(sn.maxLikeIaModel.MJD[row],
sn.maxLikeIaModel.FLUXCAL[row],
color='r')
ax.plot(sn.maxLikeIbcModel.MJD[row],
sn.maxLikeIbcModel.FLUXCAL[row],
color='g')
ax.plot(sn.maxLikeIIModel.MJD[row],
sn.maxLikeIIModel.FLUXCAL[row],
color='b')
for ax, i in zip(axlist, range(8)):
ax.set_ylabel('Flux')
ax.set_xlabel('MJD', fontsize='small')
ax.set_xlim([sn.pkmjd - 20, sn.pkmjd + 60])
ax.set_xticks([55550, 55560, 55570, 55580, 55590, 55600, 55610, 55620])
ax.set_xticklabels([
'55550', '55560', '55570', '55580', '55590', '55600', '55610',
'55620'
])
axtop = ax.twiny()
if i == 0 or i == 2 or i == 6:
axtop.set_xlabel('Time relative SN Ia peak (rest frame)',
fontsize='small')
axtop.set_xlim((array(ax.get_xlim()) - pkmjd) / (1 + sn.z))
axtop.set_xticks([-10, 0, 10, 20])
ax9.set_xticks([-1, -2])
ax9.set_yticks([-1, -1])
ax9.set_xticklabels(['', '', '', '', '', ''])
ax9.set_yticklabels(['', '', '', '', '', ''])
ax9.set_ylim([0, 1])
ax9.set_xlim([0, 1])
ax9.text(0.1,
0.7,
r"""Type Ia (red curves)
Best $\chi^2/\nu$ = %.1f/%i""" % (min(sn.chi2Ia), sn.Ndof),
color='r',
fontsize='large')
ax9.text(0.1,
0.4,
r"""Type Ib/c (green curves)
Best match: SN SDSS-002744 (Type Ib)
Best $\chi^2/\nu$ = %.1f/%i""" % (min(sn.chi2Ibc), sn.Ndof),
color='g',
fontsize='large')
ax9.text(0.1,
0.1,
r"""Type II (blue curves)
Best match: SN SDSS-015339 (Type IIP)
Best $\chi^2/\nu$ = %.1f/%i""" % (min(sn.chi2II), sn.Ndof),
color='b',
fontsize='large')
#ax2.legend(numpoints=1,prop={'size':8})
print('# PIa PIbc PII')
print sn.PIa, sn.PIbc, sn.PII
#import pdb; pdb.set_trace()
return
def plottib(lcfile='/Users/David/tib.DAT',
ax='',
trestrange=[-15, 30],
CCmoderr=0.1,
Nsim=2000,
kcorfile='PS1/kcor_tonry_SALT2.fits',
nlogz=0):
close('all')
import snana
sn = snana.SuperNova(lcfile)
sn.doGridClassify(clobber=3,
noCosmoPrior=True,
kcorfile=kcorfile,
trestrange=trestrange,
modelerror=[0.08, CCmoderr],
Nsim=Nsim,
nlogz=nlogz)
if not ax:
close('all')
import rcpar
rcpar.lcpaperfig()
ax3 = axes([0.12, 0.09, 0.75, 0.27])
ax2 = axes([0.12, 0.36, 0.75, 0.27])
ax1 = axes([0.12, 0.63, 0.75, 0.27])
#plot the data points
for m, f, e, flt in zip(sn.MJD, sn.FLUXCAL, sn.FLUXCALERR, sn.FLT):
ax1.errorbar(m, f, yerr=e, color=filt_color[flt], fmt='.')
ax2.errorbar(m, f, yerr=e, color=filt_color[flt], fmt='.')
ax3.errorbar(m, f, yerr=e, color=filt_color[flt], fmt='.')
for flt in sn.FILTERS:
row = where(array(filter2band.values()) == flt)[0]
filter = filter2band.keys()[row]
ax2.plot(min(sn.MJD) - 500,
sn.FLUXCAL[0],
'.',
color=filt_color[flt],
label=filter)
for f in sn.FILTERS:
row = where(sn.ClassSim.Ia.FLT[0] == f)[0]
ax1.plot(sn.trestbestIa * (1 + sn.z) + sn.pkmjd,
sn.bestlcIa[row],
color=filt_color[f])
ax2.plot(sn.trestbestIbc * (1 + sn.z) + sn.pkmjd,
sn.bestlcIbc[row],
color=filt_color[f])
ax3.plot(sn.trestbestII * (1 + sn.z) + sn.pkmjd,
sn.bestlcII[row],
color=filt_color[f])
ax2.set_ylabel('Flux')
ax3.set_xlabel('MJD')
ax1.set_ylim([0, max(sn.FLUXCAL) + 10])
ax1.set_xlim([sn.pkmjd - 20, sn.pkmjd + 60])
ax2.set_ylim([0, max(sn.FLUXCAL) + 10])
ax2.set_xlim([sn.pkmjd - 20, sn.pkmjd + 60])
ax3.set_ylim([0, max(sn.FLUXCAL) + 10])
ax3.set_xlim([sn.pkmjd - 20, sn.pkmjd + 60])
ax1.set_xticklabels(['', '', '', '', '', ''])
ax2.set_xticklabels(['', '', '', '', '', ''])
ax3.set_xticks([55550, 55560, 55570, 55580, 55590, 55600, 55610, 55620])
ax3.set_xticklabels([
'55510', '55520', '55530', '55540', '55550', '55560', '55570', '55580'
])
ax1.text(sn.pkmjd + 30,
max(sn.FLUXCAL) * 3 / 4.,
r"""Type Ia
Best $\chi^2/\nu$ = %.1f/%i""" % (min(sn.chi2Ia), sn.Ndof),
color='k',
fontsize='medium')
ax2.text(sn.pkmjd + 30,
max(sn.FLUXCAL) * 3 / 4.,
r"""Type Ib/c
Best $\chi^2/\nu$ = %.1f/%i""" % (min(sn.chi2Ibc), sn.Ndof),
color='k',
fontsize='medium')
ax3.text(sn.pkmjd + 30,
max(sn.FLUXCAL) * 3 / 4.,
r"""Type II
Best $\chi^2/\nu$ = %.1f/%i""" % (min(sn.chi2II), sn.Ndof),
color='k',
fontsize='medium')
ax2.legend(numpoints=1, prop={'size': 8})
print('# PIa PIbc PII')
print sn.PIa, sn.PIbc, sn.PII
import pdb
pdb.set_trace()
return
def uploadSNANAPhotometry(self, db=None):
import snana
sn = snana.SuperNova(self.options.inputfile)
if self.options.foundationdefaults:
sn.SNID = sn.otherID[2:]
transid = db.get_ID_from_DB('transients', sn.SNID)
if self.options.onlyexisting and not transid:
print('Object %s not found! Returning' % sn.SNID)
return ()
print('uploading object %s' % sn.SNID)
if self.options.useheader:
transid = self.uploadHeader(sn)
transname = sn.SNID
else:
transid = db.get_ID_from_DB('transients', sn.SNID)
transname = sn.SNID
# create photometry object, if it doesn't exist
photheaderdata = db.get_objects_from_DB('photometry')
if type(sn.RA) == float:
self.parsePhotHeaderData(photheaderdata,
transname,
sn.RA,
sn.DECL,
db=db)
else:
self.parsePhotHeaderData(photheaderdata,
transname,
sn.RA.split()[0],
sn.DECL.split()[0],
db=db)
# get the filter IDs
# upload the photometry
for mjd, flux, fluxerr, mag, magerr, flt in zip(
sn.MJD, sn.FLUXCAL, sn.FLUXCALERR, sn.MAG, sn.MAGERR, sn.FLT):
obsdate = Time(mjd, format='mjd').isot
bandid = db.getBandfromDB('band', flt, self.instid)
if not bandid:
raise RuntimeError(
'Error : band %s is not defined in the DB!!' % flt)
PhotUploadDict = {
'obs_date': obsdate,
'flux': flux,
'flux_err': fluxerr,
'photometry': self.photdataid,
'forced': 1,
'dq': 1,
'band': bandid,
'flux_zero_point': 27.5
}
if flux > 0:
PhotUploadDict['mag'] = mag
PhotUploadDict['mag_err'] = magerr
if 'SEARCH_PEAKMJD' in sn.__dict__.keys(
) and np.abs(mjd - sn.SEARCH_PEAKMJD) < 0.5:
PhotUploadDict['discovery_point'] = 1
if not transid:
photdata = db.post_object_to_DB('photdata', PhotUploadDict)
else:
# if the transient is already in the DB, we need to check for photometry
# and avoid duplicate epochs
photepochs = db.get_objects_from_DB('photdata')
closeID = None
for p in photepochs:
pmjd = Time(p['obs_date'], format='isot').mjd
if p['photometry'] == self.photdataid and np.abs(
pmjd - mjd
) < self.options.mjdmatchmin and p['band'] == bandid:
closeID = p['url']
break
if closeID and self.options.clobber:
photdata = db.patch_object_to_DB('photdata',
PhotUploadDict, closeID)
elif closeID and not self.options.clobber:
print('data point at MJD %i exists! not clobbering' %
pmjd)
else:
photdata = db.post_object_to_DB('photdata', PhotUploadDict)