Ejemplo n.º 1
0
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
Ejemplo n.º 2
0
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
Ejemplo n.º 3
0
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
Ejemplo n.º 4
0
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
Ejemplo n.º 5
0
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
Ejemplo n.º 6
0
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
# - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - -
Ejemplo n.º 7
0
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           = ' '
Ejemplo n.º 8
0
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