def volume(L,Lval,volbins):
'''
Function linearly interpolating between volume bins to get a volume value
'''
if L < np.min(Lval):
vol = 0.0
elif L > np.max(Lval):
sys.exit(':: ERROR :: Input Volume L in volume function is larger than max(Lvector) --> ABORTING')
else:
newL = np.sort(np.append(Lval,L))
newV = kbs.interpn(Lval,volbins,newL)
ent = np.where(newL == L)
vol = newV[ent]
return vol
def spectrans(waveval, wavevec, specvec, transvec):
"""
Retunring the (interpolated) value of the spectrum for a given wavelength
"""
STvec = specvec * transvec
ent = np.where(wavevec == waveval)
if len(ent[0]) == 1:
STval = STvec[ent]
else:
wavenew = np.sort(np.append(wavevec, waveval))
STvecnew = kbs.interpn(wavevec, STvec, wavenew)
ent = np.where(wavenew == waveval)
STval = STvecnew[ent]
return STval
def spectrans(waveval,wavevec,specvec,transvec):
"""
Retunring the (interpolated) value of the spectrum for a given wavelength
"""
STvec = specvec*transvec
ent = np.where(wavevec == waveval)
if len(ent[0]) == 1 :
STval = STvec[ent]
else:
wavenew = np.sort(np.append(wavevec,waveval))
STvecnew = kbs.interpn(wavevec,STvec,wavenew)
ent = np.where(wavenew == waveval)
STval = STvecnew[ent]
return STval
def volume(L, Lval, volbins):
'''
Function linearly interpolating between volume bins to get a volume value
'''
if L < np.min(Lval):
vol = 0.0
elif L > np.max(Lval):
sys.exit(
':: ERROR :: Input Volume L in volume function is larger than max(Lvector) --> ABORTING'
)
else:
newL = np.sort(np.append(Lval, L))
newV = kbs.interpn(Lval, volbins, newL)
ent = np.where(newL == L)
vol = newV[ent]
return vol
def kappa(waveval, site='maunakea', intmethod='linear', plot=0):
"""
---- PURPOSE ----
Returning the (interpolated) value of the extinction coefficient
needed to correct magnitudes for atmospheric extinction (air mass)
---- INPUT ----
wave wavelength in [A]
site name of site (data) to use when interpolating
intmethod the interpolation to perform
---- OUTPUT ----
kappa(lambda) The atmospheric instinction coefficient for lambda[A]
---- EXAMPLE OF USAGE ----
"""
if site == 'maunakea':
#data taken from http://www.gemini.edu/?q=node/10790#Mauna%20Kea
wavedat = np.array([
0.310, 0.320, 0.340, 0.360, 0.380, 0.400, 0.450, 0.500, 0.550,
0.600, 0.650, 0.700, 0.800, 0.900, 1.25, 1.65, 2.20
]) * 1e4
kappadat = np.array([
1.37, 0.82, 0.51, 0.37, 0.30, 0.25, 0.17, 0.13, 0.12, 0.11, 0.11,
0.10, 0.07, 0.05, 0.015, 0.015, 0.033
])
else:
sys.exit(':: kappa :: ERROR: Chosen site not available --> ABORTING')
wavenew = np.sort(np.append(wavedat, waveval))
if waveval < np.min(wavedat):
print 'NB! Selected wavelength is shorter than shortest wavelength in data. '
print ' Setting output to kappa of shortest wavelength in data.'
kappa = kappadat[0]
kappanew = np.insert(kappadat, 0, kappa)
elif waveval > np.max(wavedat):
print 'NB! Selected wavelength is longer than longest wavelength in data. '
print ' Setting output to kappa of longest wavelength in data.'
kappa = kappadat[-1]
kappanew = np.append(kappadat, kappa)
else:
kappanew = kbs.interpn(wavedat, kappadat, wavenew, method=intmethod)
kappa = kappanew[np.where(wavenew == waveval)]
if plot == 1:
import pylab as plt
plt.clf()
plt.plot(wavedat, kappadat, 'ro', label='data for ' + site)
plt.plot(wavenew, kappanew, 'r--', label='interpolation of data')
#kappanew = kbs.interpn(wavedat,kappadat,wavenew,method='cubic')
#plt.plot(wavenew,kappanew,'g--',label='cubic')
#kappanew = kbs.interpn(wavedat,kappadat,wavenew,method='nearest')
#plt.plot(wavenew,kappanew,'b--',label='nearest')
#kappanew = kbs.interpn(wavedat,kappadat,wavenew,method='slinear')
#plt.plot(wavenew,kappanew,'y--',label='slinear')
#kappanew = kbs.interpn(wavedat,kappadat,wavenew,method='quadratic')
#plt.plot(wavenew,kappanew,'m--',label='quadratic')
#kappanew = kbs.interpn(wavedat,kappadat,wavenew,method='zero')
#plt.plot(wavenew,kappanew,'r:',label='zero')
plt.plot(waveval, kappa, 'go', label='obtained value')
plt.legend(
fancybox=True,
loc='upper right') # add the legend in the middle of the plot
plt.show()
return kappa
utcstart_sci = parameters[16]
utcstop_sci = parameters[17]
throughput = np.genfromtxt(tpfile) # reading througput into array
#-------------------------------------------------------------------------------------------------------------
# A: TELLURIC STAR
#-------------------------------------------------------------------------------------------------------------
# reading wavelengths, spectrum and ra dec from file
wave_tel, spec1D_tel_eps, radec_tel = cal.readfitsspec1D(spec1D_tel,
spec='SPEC1D_SUM')
# get E(B-V) for ra and dec
AV, extval_tel = kbs.getAv(radec_tel[0], radec_tel[1],
'F098M') # filter only important when using AV
# interpolating throughput to telluric wavelengths
tpinterp_tel = kbs.interpn(throughput[:, 0] * 10**4, throughput[:, 1],
wave_tel)
# loading expected initial 'template' spectrum of standard star (in flux units: [erg/s/cm2/A]
standat = np.genfromtxt(spec1Dstandard)
wave_stan = standat[:, 0]
flux_stan = standat[:, 1]
spec_stan_flux = kbs.interpn(wave_stan, flux_stan, wave_tel)
# rescale 'template' spec to match telluric's magnitude
magABstan = cal.magFromSpec(wave_tel, spec_stan_flux,
tpinterp_tel) # magnitude of standard in band
magABtel = magV_tel + magABstan # assuming telluric A0V (Vega) star => magABtel_band - magABtel_V = magABstan_band
spec_stanscale = cal.scalespec(
wave_tel, spec_stan_flux, tpinterp_tel,
magABtel) # scaling standard spectrum to match telluric
# - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - -
spec1D_sci = parameters[14] nightdate_sci = parameters[15] utcstart_sci = parameters[16] utcstop_sci = parameters[17] throughput = np.genfromtxt(tpfile) # reading througput into array #------------------------------------------------------------------------------------------------------------- # A: TELLURIC STAR #------------------------------------------------------------------------------------------------------------- # reading wavelengths, spectrum and ra dec from file wave_tel, spec1D_tel_eps, radec_tel = cal.readfitsspec1D(spec1D_tel,spec='SPEC1D_SUM') # get E(B-V) for ra and dec AV, extval_tel = kbs.getAv(radec_tel[0],radec_tel[1],'F098M') # filter only important when using AV # interpolating throughput to telluric wavelengths tpinterp_tel = kbs.interpn(throughput[:,0]*10**4,throughput[:,1],wave_tel) # loading expected initial 'template' spectrum of standard star (in flux units: [erg/s/cm2/A] standat = np.genfromtxt(spec1Dstandard) wave_stan = standat[:,0] flux_stan = standat[:,1] spec_stan_flux = kbs.interpn(wave_stan,flux_stan,wave_tel) # rescale 'template' spec to match telluric's magnitude magABstan = cal.magFromSpec(wave_tel,spec_stan_flux,tpinterp_tel) # magnitude of standard in band magABtel = magV_tel+magABstan # assuming telluric A0V (Vega) star => magABtel_band - magABtel_V = magABstan_band spec_stanscale = cal.scalespec(wave_tel,spec_stan_flux,tpinterp_tel,magABtel) # scaling standard spectrum to match telluric # - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - # model spectrum of a telluric standard (i.e. manipulating standard) for testing telmodel = 0 modelstr = ' '
def kappa(waveval,site='maunakea',intmethod='linear',plot=0):
"""
---- PURPOSE ----
Returning the (interpolated) value of the extinction coefficient
needed to correct magnitudes for atmospheric extinction (air mass)
---- INPUT ----
wave wavelength in [A]
site name of site (data) to use when interpolating
intmethod the interpolation to perform
---- OUTPUT ----
kappa(lambda) The atmospheric instinction coefficient for lambda[A]
---- EXAMPLE OF USAGE ----
"""
if site == 'maunakea':
#data taken from http://www.gemini.edu/?q=node/10790#Mauna%20Kea
wavedat = np.array([0.310,0.320,0.340,0.360,0.380,0.400,0.450,0.500,0.550,0.600,0.650,0.700,0.800,0.900,1.25,1.65,2.20])*1e4
kappadat = np.array([1.37,0.82,0.51,0.37,0.30,0.25,0.17,0.13,0.12,0.11,0.11,0.10,0.07,0.05,0.015,0.015,0.033])
else:
sys.exit(':: kappa :: ERROR: Chosen site not available --> ABORTING')
wavenew = np.sort(np.append(wavedat,waveval))
if waveval < np.min(wavedat):
print 'NB! Selected wavelength is shorter than shortest wavelength in data. '
print ' Setting output to kappa of shortest wavelength in data.'
kappa = kappadat[0]
kappanew = np.insert(kappadat,0,kappa)
elif waveval > np.max(wavedat):
print 'NB! Selected wavelength is longer than longest wavelength in data. '
print ' Setting output to kappa of longest wavelength in data.'
kappa = kappadat[-1]
kappanew = np.append(kappadat,kappa)
else:
kappanew = kbs.interpn(wavedat,kappadat,wavenew,method=intmethod)
kappa = kappanew[np.where(wavenew == waveval)]
if plot == 1:
import pylab as plt
plt.clf()
plt.plot(wavedat,kappadat,'ro',label='data for '+site)
plt.plot(wavenew,kappanew,'r--',label='interpolation of data')
#kappanew = kbs.interpn(wavedat,kappadat,wavenew,method='cubic')
#plt.plot(wavenew,kappanew,'g--',label='cubic')
#kappanew = kbs.interpn(wavedat,kappadat,wavenew,method='nearest')
#plt.plot(wavenew,kappanew,'b--',label='nearest')
#kappanew = kbs.interpn(wavedat,kappadat,wavenew,method='slinear')
#plt.plot(wavenew,kappanew,'y--',label='slinear')
#kappanew = kbs.interpn(wavedat,kappadat,wavenew,method='quadratic')
#plt.plot(wavenew,kappanew,'m--',label='quadratic')
#kappanew = kbs.interpn(wavedat,kappadat,wavenew,method='zero')
#plt.plot(wavenew,kappanew,'r:',label='zero')
plt.plot(waveval,kappa,'go',label='obtained value')
plt.legend(fancybox=True, loc='upper right') # add the legend in the middle of the plot
plt.show()
return kappa
