def testFWHMconversions(self):
FWHMeff = 0.8
FWHMgeom = snr.FWHMeff2FWHMgeom(FWHMeff)
self.assertEqual(FWHMgeom, (0.822 * FWHMeff + 0.052))
FWHMgeom = 0.8
FWHMeff = snr.FWHMgeom2FWHMeff(FWHMgeom)
self.assertEqual(FWHMeff, (FWHMgeom - 0.052) / 0.822)
def Calc_Sky(self, paper, infos, transmission):
Diameter = 6.5 #m
Deltat = 30 #s
platescale = 0.2 #arsec
gain = 2.3
for filtre in self.filters:
filtre_trans = transmission.lsst_system[filtre]
wavelen_min, wavelen_max, wavelen_step = filtre_trans.getWavelenLimits(
None, None, None)
photParams = PhotometricParameters()
#photParams._exptime=30.
bandpass = Bandpass(wavelen=filtre_trans.wavelen,
sb=filtre_trans.sb)
infos['Skyb'][filtre] = 5455 * np.power(
Diameter / 6.5, 2.) * np.power(Deltat / 30., 2.) * np.power(
platescale, 2.) * np.power(
10., 0.4 *
(25. -
infos['mbsky'][filtre])) * infos['Sigmab'][filtre]
Zb = 181.8 * np.power(Diameter / 6.5, 2.) * infos['Tb'][filtre]
mbZ = 25. + 2.5 * np.log10(Zb)
flatSed = Sed()
flatSed.setFlatSED(wavelen_min, wavelen_max, wavelen_step)
flux0 = np.power(10., -0.4 * mbZ)
flatSed.multiplyFluxNorm(flux0)
counts = flatSed.calcADU(
bandpass, photParams=photParams) #number of counts for exptime
infos['mb_Z'][filtre] = mbZ
infos['counts_mb_Z'][filtre] = counts / photParams.exptime
flatSedb = Sed()
flatSedb.setFlatSED(wavelen_min, wavelen_max, wavelen_step)
flux0b = np.power(10., -0.4 * infos['mbsky'][filtre])
flatSedb.multiplyFluxNorm(flux0b)
FWHMeff = SignalToNoise.FWHMgeom2FWHMeff(paper['Seeing'][filtre])
#FWHMeff = paper['Seeing'][filtre]
#m5_calc=SignalToNoise.calcM5(flatSedb,transmission.lsst_atmos[filtre],transmission.lsst_system[filtre],photParams=photParams,FWHMeff=FWHMeff)
m5_calc = SignalToNoise.calcM5(
flatSedb,
transmission.lsst_atmos[filtre],
transmission.lsst_system[filtre],
photParams=photParams,
FWHMeff=self.paper['FWHMeff'][filtre])
infos['fiveSigmaDepth'][filtre] = m5_calc
def CalcMyABMagnitudesError_filter(self, band, SkyBrightnessMag, FWHMGeom):
"""
CalcMyABMagnitudesError_filter(self,band,SkyBrightnessMag,FWHMGeom)
- author : Sylvie Dagoret-Campagne
- affiliation : LAL/IN2P3/CNRS/FRANCE
- date : July 5th 2018
Calculate magnitude errors for one band.
Input args:
- band : filter band
- SkyBrighnessMag : Sky Brighness Magnitude in the band
- FWHMGeom : Geometrical PSF in the band
"""
filtre_atm = self.lsst_atmos[band]
filtre_syst = self.lsst_system[band]
wavelen_min, wavelen_max, wavelen_step = filtre_syst.getWavelenLimits(
None, None, None)
#calculation of effective PSF
FWHMeff = SignalToNoise.FWHMgeom2FWHMeff(FWHMGeom)
photParams = PhotometricParameters(bandpass=band)
# create a Flat sed S_nu from the sky brightness magnitude
skysed = Sed()
skysed.setFlatSED(wavelen_min, wavelen_max, wavelen_step)
flux0b = np.power(10., -0.4 * SkyBrightnessMag)
skysed.multiplyFluxNorm(flux0b)
#calcMagError filled according doc
mag_err = SignalToNoise.calcMagError_sed(self.sed,
filtre_atm,
skysed,
filtre_syst,
photParams,
FWHMeff,
verbose=False)
return mag_err
def Simulate_and_Fit_LC(self, observations, transmission, zmin, zmax):
#print 'time',observations['expMJD'],observations['filter']
#print 'simulate and fit'
ra = observations[self.fieldRA][0]
dec = observations[self.fieldDec][0]
if self.SN.sn_type == 'Ia':
mbsim = self.SN.SN._source.peakmag('bessellb', 'vega')
else:
mbsim = -1
#This will be the data for sncosmo fitting
table_for_fit = {}
table_for_fit['error_calc'] = Table(names=('time', 'flux', 'fluxerr',
'band', 'zp', 'zpsys'),
dtype=('f8', 'f8', 'f8', 'S7',
'f4', 'S4'))
table_for_fit['error_coadd_calc'] = Table(
names=('time', 'flux', 'fluxerr', 'band', 'zp', 'zpsys'),
dtype=('f8', 'f8', 'f8', 'S7', 'f4', 'S4'))
table_for_fit['error_opsim'] = Table(names=('time', 'flux', 'fluxerr',
'band', 'zp', 'zpsys'),
dtype=('f8', 'f8', 'f8', 'S7',
'f4', 'S4'))
table_for_fit['error_coadd_opsim'] = Table(
names=('time', 'flux', 'fluxerr', 'band', 'zp', 'zpsys'),
dtype=('f8', 'f8', 'f8', 'S7', 'f4', 'S4'))
table_for_fit['error_through'] = Table(
names=('time', 'flux', 'fluxerr', 'band', 'zp', 'zpsys'),
dtype=('f8', 'f8', 'f8', 'S7', 'f4', 'S4'))
table_for_fit['error_coadd_through'] = Table(
names=('time', 'flux', 'fluxerr', 'band', 'zp', 'zpsys'),
dtype=('f8', 'f8', 'f8', 'S7', 'f4', 'S4'))
mytype = [('obsHistID', np.int), ('filtSkyBrightness', np.float),
('airmass', np.float), ('moonPhase', np.float),
('fieldRA', np.float), ('fieldDec', np.float),
('visitExpTime', np.float), ('expDate', np.int),
('filter', np.dtype('a15')), ('fieldID', np.int),
('fiveSigmaDepth', np.float), ('ditheredDec', np.float),
('expMJD', np.float), ('ditheredRA', np.float),
('rawSeeing', np.float), ('flux', np.float),
('err_flux', np.float), ('err_flux_opsim', np.float),
('err_flux_through', np.float), ('finSeeing', np.float),
('katm_opsim', np.float), ('katm_calc', np.float),
('m5_calc', np.float), ('Tb', np.float),
('Sigmab', np.float), ('Cm', np.float), ('dCm', np.float),
('mag_SN', np.float), ('snr_m5_through', np.float),
('snr_m5_opsim', np.float), ('gamma_through', np.float),
('gamma_opsim', np.float), ('snr_SED', np.float)]
myobservations = np.zeros((60, 1), dtype=mytype)
#print 'Nobservations',len(observations)
nobs = -1
for filtre in self.filterNames:
obs_filtre = observations[np.where(
observations['filter'] == filtre)]
#print 'ehehe',obs_filtre
for obs in obs_filtre:
nobs += 1
if len(myobservations) <= nobs:
myobservations = np.resize(myobservations,
(len(myobservations) + 100, 1))
for name in observations.dtype.names:
myobservations[name][nobs] = obs[name]
#print 'time uu',obs['expMJD']
seeing = obs['rawSeeing']
#seeing=obs['finSeeing']
time_obs = obs['expMJD']
m5_opsim = obs['fiveSigmaDepth']
#print 'getting SED'
sed_SN = self.SN.get_SED(time_obs)
#print 'got SED',sed_SN.wavelen,sed_SN.flambda,obs['expMJD']
"""
outf = open('SN_'+str(time)+'.dat', 'wb')
for i,wave in enumerate(sn.SEDfromSNcosmo.wavelen):
print >> outf,wave,sn.SEDfromSNcosmo.flambda[i]
outf.close()
"""
#print 'loading transmission airmass'
transmission.Load_Atmosphere(obs['airmass'])
flux_SN = sed_SN.calcFlux(
bandpass=transmission.lsst_atmos_aerosol[filtre])
#print 'this is my flux',flux_SN
#flux_SN=sed_SN.calcFlux(bandpass=transmission.lsst_system[filtre]) / 3631.0
myup = transmission.darksky.calcInteg(
transmission.lsst_system[filtre])
"""
wavelen, sb = transmission.lsst_system[filtre].multiplyThroughputs(transmission.lsst_atmos[filtre].wavelen, transmission.lsst_atmos[filtre].sb)
lsst_total= Bandpass(wavelen=wavelen, sb=sb)
"""
Tb = self.Calc_Integ(transmission.lsst_atmos[filtre])
Sigmab = self.Calc_Integ(transmission.lsst_system[filtre])
katm = -2.5 * np.log10(Tb / Sigmab)
mbsky_through = -2.5 * np.log10(myup / (3631. * Sigmab))
#print 'there mbsky',filtre,mbsky_through,obs['filtSkyBrightness'],katm,self.kAtm[filtre],Tb,Sigmab,obs['airmass']
Filter_Wavelength_Correction = np.power(
500.0 / self.params.filterWave[filtre], 0.3)
Airmass_Correction = math.pow(obs['airmass'], 0.6)
FWHM_Sys = self.params.FWHM_Sys_Zenith * Airmass_Correction
FWHM_Atm = seeing * Filter_Wavelength_Correction * Airmass_Correction
finSeeing = self.params.scaleToNeff * math.sqrt(
np.power(FWHM_Sys, 2) +
self.params.atmNeffFactor * np.power(FWHM_Atm, 2))
#print 'hello pal',filtre,finSeeing,obs['visitExpTime']
Tscale = obs['visitExpTime'] / 30.0 * np.power(
10.0, -0.4 *
(obs['filtSkyBrightness'] - self.params.msky[filtre]))
dCm = self.params.dCm_infinity[filtre] - 1.25 * np.log10(
1 + np.power(10., 0.8 * self.params.dCm_infinity[filtre] -
1.) / Tscale)
m5_recalc = dCm + self.params.Cm[filtre] + 0.5 * (
obs['filtSkyBrightness'] - 21.) + 2.5 * np.log10(
0.7 / finSeeing) - self.params.kAtm[filtre] * (
obs['airmass'] - 1.) + 1.25 * np.log10(
obs['visitExpTime'] / 30.)
myobservations['Cm'][nobs] = self.params.Cm[filtre]
myobservations['dCm'][nobs] = dCm
myobservations['finSeeing'][nobs] = finSeeing
myobservations['Tb'][nobs] = Tb
myobservations['Sigmab'][nobs] = Sigmab
myobservations['katm_calc'][nobs] = katm
myobservations['katm_opsim'][nobs] = self.params.kAtm[filtre]
wavelen_min, wavelen_max, wavelen_step = transmission.lsst_system[
filtre].getWavelenLimits(None, None, None)
flatSed = Sed()
flatSed.setFlatSED(wavelen_min, wavelen_max, wavelen_step)
flux0 = np.power(10., -0.4 * obs['filtSkyBrightness'])
flatSed.multiplyFluxNorm(flux0)
if flux_SN > 0:
#print 'positive flux',flux_SN
mag_SN = -2.5 * np.log10(flux_SN / 3631.0)
FWHMeff = SignalToNoise.FWHMgeom2FWHMeff(finSeeing)
#FWHMeff = SignalToNoise.FWHMgeom2FWHMeff(seeing)
photParams = PhotometricParameters()
snr_SN = SignalToNoise.calcSNR_sed(
sed_SN,
transmission.lsst_atmos_aerosol[filtre],
transmission.darksky,
transmission.lsst_system[filtre],
photParams,
FWHMeff=FWHMeff,
verbose=False)
#m5_calc=SignalToNoise.calcM5(transmission.darksky,transmission.lsst_atmos_aerosol[filtre],transmission.lsst_system[filtre],photParams=photParams,FWHMeff=FWHMeff)
m5_calc = SignalToNoise.calcM5(
flatSed,
transmission.lsst_atmos_aerosol[filtre],
transmission.lsst_system[filtre],
photParams=photParams,
FWHMeff=FWHMeff)
snr_m5_through, gamma_through = SignalToNoise.calcSNR_m5(
mag_SN, transmission.lsst_atmos_aerosol[filtre],
m5_calc, photParams)
snr_m5_opsim, gamma_opsim = SignalToNoise.calcSNR_m5(
mag_SN, transmission.lsst_atmos_aerosol[filtre],
m5_opsim, photParams)
#print 'm5 diff',filtre,m5_calc,m5_opsim,m5_calc/m5_opsim,m5_recalc,(m5_opsim/m5_recalc)
err_flux_SN = flux_SN / snr_SN
err_flux_SN_opsim = flux_SN / snr_m5_opsim
err_flux_SN_through = flux_SN / snr_m5_through
#print 'test errors',flux_SN,err_flux_SN,err_flux_SN_opsim,err_flux_SN_through,err_flux_SN_through/err_flux_SN_opsim,m5_opsim-m5_calc
myobservations['mag_SN'][nobs] = mag_SN
myobservations['flux'][nobs] = flux_SN
myobservations['err_flux'][nobs] = err_flux_SN
myobservations['err_flux_opsim'][nobs] = err_flux_SN_opsim
myobservations['err_flux_through'][
nobs] = err_flux_SN_through
myobservations['m5_calc'][nobs] = m5_calc
myobservations['snr_m5_through'][nobs] = snr_m5_through
myobservations['snr_m5_opsim'][nobs] = snr_m5_opsim
myobservations['gamma_through'][nobs] = gamma_through
myobservations['gamma_opsim'][nobs] = gamma_opsim
myobservations['snr_SED'][nobs] = snr_SN
#print 'SNR',flux_SN,flux_SN/err_flux_SN,flux_SN/err_flux_SN_opsim
#if flux_SN/err_flux_SN >=5:
#table_for_fit['error_calc'].add_row((time_obs,flux_SN,err_flux_SN,'LSST::'+filtre,25,'ab'))
#if flux_SN/err_flux_SN_opsim >=5.:
table_for_fit['error_opsim'].add_row(
(time_obs, flux_SN, err_flux_SN_opsim,
'LSST::' + filtre, 25, 'ab'))
table_for_fit['error_through'].add_row(
(time_obs, flux_SN, err_flux_SN_through,
'LSST::' + filtre, 25, 'ab'))
#print 'Getting fluxes and errors',time.time()-self.thetime,filtre,nobs
else:
err_flux_SN = -999.
err_flux_SN_opsim = -999.
myobservations['mag_SN'][nobs] = -999
myobservations['flux'][nobs] = flux_SN
myobservations['err_flux'][nobs] = -999.
myobservations['err_flux_opsim'][nobs] = -999.
myobservations['err_flux_through'][nobs] = -999.
myobservations['m5_calc'][nobs] = -999.
myobservations['snr_m5_through'][nobs] = -999
myobservations['snr_m5_opsim'][nobs] = -999
myobservations['gamma_through'][nobs] = -999
myobservations['gamma_opsim'][nobs] = -999
myobservations['snr_SED'][nobs] = -999
#print 'flux SN',flux_SN,err_flux_SN,mag_SN,snr_SN,snr_m5_through,snr_m5_opsim
#t.add_row((time,flux_SN,err_flux_SN,'LSST::'+filtre,0.,'vega'))
#break
#t = Table([list(data['time']), list(data['band']),data['flux'],data['fluxerr'],data['flux_aero'],data['fluxerr_aero'],data['fluxerr_new'],data['zp'],data['zpsys']], names=('time','band','flux','fluxerr','flux_aero','fluxerr_aero','fluxerr_new','zp','zpsys'), meta={'name': 'first table'})
#model.set(z=0.5)
#print SN.SN
myobservations = np.resize(myobservations, (nobs + 1, 1))
#print 'there obs',myobservations
#print 'Getting coadds',time.time()-self.thetime
for band in ['u', 'g', 'r', 'i', 'z', 'y']:
#sela=table_for_fit['error_calc'][np.where(table_for_fit['error_calc']['band']=='LSST::'+band)]
#sela=sela[np.where(np.logical_and(sela['flux']/sela['fluxerr']>5.,sela['flux']>0.))]
selb = table_for_fit['error_opsim'][np.where(
table_for_fit['error_opsim']['band'] == 'LSST::' + band)]
#selb=selb[np.where(np.logical_and(selb['flux']/selb['fluxerr']>5.,selb['flux']>0.))]
selc = table_for_fit['error_through'][np.where(
table_for_fit['error_through']['band'] == 'LSST::' + band)]
#table_for_fit['error_coadd_calc']=vstack([table_for_fit['error_coadd_calc'],self.Get_coadd(sela)])
table_for_fit['error_coadd_opsim'] = vstack(
[table_for_fit['error_coadd_opsim'],
self.Get_coadd(selb)])
table_for_fit['error_coadd_through'] = vstack(
[table_for_fit['error_coadd_through'],
self.Get_coadd(selc)])
#print 'There we go fitting',time.time()-self.thetime
dict_fit = {}
#for val in ['error_calc','error_coadd_calc','error_opsim','error_coadd_opsim']:
for val in ['error_coadd_opsim', 'error_coadd_through']:
dict_fit[val] = {}
dict_fit[val]['sncosmo_fitted'] = {}
dict_fit[val]['table_for_fit'] = table_for_fit[val]
#print 'fit',val,time.time()-self.thetime
res, fitted_model, mbfit, fit_status = self.Fit_SN(
table_for_fit[val], zmin, zmax)
if res is not None:
dict_fit[val]['sncosmo_res'] = res
#self.dict_fit[val]['fitted_model']=fitted_model
for i, par in enumerate(fitted_model.param_names):
dict_fit[val]['sncosmo_fitted'][
par] = fitted_model.parameters[i]
dict_fit[val]['mbfit'] = mbfit
dict_fit[val]['fit_status'] = fit_status
return dict_fit, mbsim, myobservations
#plt.plot(sed_SNb.wavelen*(1.+redshift)/(1.+redshiftb),ratio_cosmo*sed_SNb.flambda,linestyle='-',color='g')
Filter_Wavelength_Correction = np.power(500.0 / filterWave[band], 0.3)
Airmass_Correction = math.pow(obs['airmass'], 0.6)
FWHM_Sys = FWHM_Sys_Zenith * Airmass_Correction
FWHM_Atm = seeing * Filter_Wavelength_Correction * Airmass_Correction
finSeeing = scaleToNeff * math.sqrt(
np.power(FWHM_Sys, 2) + atmNeffFactor * np.power(FWHM_Atm, 2))
#print 'flux_SN',band,flux_SN
if flux_SN > 0:
mag_SN = -2.5 * np.log10(flux_SN)
plt.show()
FWHMeff = SignalToNoise.FWHMgeom2FWHMeff(finSeeing)
photParams = PhotometricParameters()
snr_SN = SignalToNoise.calcSNR_sed(
sed_SN,
transmission.lsst_atmos_aerosol[band],
transmission.darksky,
transmission.lsst_system[band],
photParams,
FWHMeff=FWHMeff,
verbose=False)
m5_calc = SignalToNoise.calcM5(
transmission.darksky,
transmission.lsst_atmos_aerosol[band],
transmission.lsst_system[band],
photParams=photParams,
FWHMeff=FWHMeff)
