def inferParams(snid,
snmodel,
paramsDF,
lcsDF,
infer_method=sncosmo.fit_lc,
minsnr=0.):
"""
infer the parameters for the ith supernova in the simulation
"""
pdict, ra, dec = paramDict(snid, paramsDF)
snmodel.setCoords(ra, dec)
snmodel.mwEBVfromMaps()
snmodel.set(**pdict)
truth = copy(snmodel.equivalentSNCosmoModel()) #.copy()
#print(model)
#z = params.ix[snid, 'z']
lcinstance = LightCurve(lcsDF.query('snid==@snid'))
fig = None
try:
print('trying fit')
resfit = infer_method(lcinstance.snCosmoLC(),
snmodel.equivalentSNCosmoModel(),
vparam_names=['t0', 'x0', 'x1', 'c'],
modelcov=False,
minsnr=minsnr) #, bounds=dict(z=(0.0001, 1.6)))
reschar = ResChar.fromSNCosmoRes(resfit)
print('fit passed')
except:
reschar = 'failure'
print('failed for SNID {0} with {1} points'.format(
snid, len(lcinstance.snCosmoLC())))
#if reschar != 'failure':
# pass
# fig = None#sncosmo.plot_lc(lcinstance.snCosmoLC(), model=(truth, reschar.sncosmoModel))
return snid, lcinstance, reschar, truth, fig
def inferParams3(snanaSims3, model3, infer_method3, i, minsnr=3.):
"""
infer the parameters for the ith supernova in the simulation
"""
snid3 = snanaSims3.headData.index.values[i]
z3 = snanaSims3.headData.ix[snid3, 'REDSHIFT_FINAL']
lcinstance = snanaSims3.get_SNANA_photometry(snid=snid3)
model3.set(z=z3)
print(z3)
resfit3 = infer_method3(lcinstance.snCosmoLC(), model3, vparam_names=['t0', 'x0', 'x1', 'c'],
modelcov=True, minsnr=minsnr)
reschar3 = ResChar.fromSNCosmoRes(resfit3)
return snid3, reschar3
def inferParams2(snanaSims2, model2, infer_method2, i, minsnr=3.):
"""
infer the parameters for the ith supernova in the simulation
"""
snid2 = snanaSims2.headData.index.values[i]
z2 = snanaSims2.headData.ix[snid2, 'REDSHIFT_FINAL']
lcinstance = snanaSims2.get_SNANA_photometry(snid=snid2)
model2.set(z=z2)
print(z2)
resfit2 = infer_method2(lcinstance.snCosmoLC(), model2, vparam_names=['t0', 'x0', 'x1', 'c'],
modelcov=True, minsnr=minsnr)
reschar2 = ResChar.fromSNCosmoRes(resfit2)
return snid2, reschar2
def inferParams1(snanaSims1, model1, infer_method1, i, minsnr=3.):
"""
infer the parameters for the ith supernova in the simulation
"""
snid1 = snanaSims1.headData.index.values[i]
z1 = snanaSims1.headData.ix[snid1, 'REDSHIFT_FINAL']
lcinstance = snanaSims1.get_SNANA_photometry(snid=snid1)
model1.set(z=z1)
print(z1)
resfit1 = infer_method1(lcinstance.snCosmoLC(), model1, vparam_names=['t0', 'x0', 'x1', 'c'],
modelcov=True, minsnr=minsnr)
reschar1 = ResChar.fromSNCosmoRes(resfit1)
return snid1, reschar1
def inferParams(snanaSims, model, infer_method, i, minsnr=3.):
"""
infer the parameters for the ith supernova in the simulation
"""
snid = snanaSims.headData.index.values[i]
z = snanaSims.headData.ix[snid, 'REDSHIFT_FINAL']
lcinstance = snanaSims.get_SNANA_photometry(snid=snid)
model.set(z=z)
print(z)
resfit = infer_method(lcinstance.snCosmoLC(),
model,
vparam_names=['t0', 'x0', 'x1', 'c'],
modelcov=True,
minsnr=minsnr)
reschar = ResChar.fromSNCosmoRes(resfit)
return snid, reschar