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)