Esempio n. 1
0
    def calibFlux(self, inIm, **kwargs):

        print "\nCALIBRATING FLUX IN " + inIm

        # determine which extinction file to use
        hdu = fits.open(inIm)
        if hdu[0].header["OBSERVAT"] == "Gemini-North":
            self.extDat = "gmos$calib/mkoextinct.dat"
        else:
            self.extDat = "onedstds$ctioextinct.dat"

        # determine which sensitivity function to use
        centWave = str(int(hdu[0].header["CENTWAVE"]))
        sFunc = self.sFunc.replace("X", centWave)
        hdu.close()

        # delete previous flux calibrated spectra and generate new one
        iraf.imdelete("c" + inIm)
        iraf.gscalibrate(inIm,
                         sfunction=sFunc,
                         extinction=self.extDat,
                         **kwargs)

        # view the result
        print "Displaying calibrated data cube"
        self.viewCube("c" + inIm, version="1")

        return
Esempio n. 2
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def calibrate(scifiles, extfile, observatory):
    for f in scifiles:
        redorblue = getredorblue(f)
        iraf.unlearn(iraf.gscalibrate)
        iraf.gscalibrate('et' + f[:-4] + '.fits',
                         sfunc='sens' + redorblue + '.fits', fl_ext=True,
                         extinction=extfile, observatory=observatory)
        
        if os.path.exists('cet' + f[:-4] + '.fits'):
            iraf.unlearn(iraf.splot)
            iraf.splot('cet' + f.replace('.txt', '.fits') + '[sci]')  # just to check
Esempio n. 3
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def calibrate(scifiles, extfile, observatory):
    for f in scifiles:
        redorblue = getredorblue(f)
        iraf.unlearn(iraf.gscalibrate)
        iraf.gscalibrate('et' + f[:-4] + '.fits',
                         sfunc='sens' + redorblue + '.fits', fl_ext=True, fl_vardq=dodq,
                         extinction=extfile, observatory=observatory)
        
        if os.path.exists('cet' + f[:-4] + '.fits'):
            iraf.unlearn(iraf.splot)
            iraf.splot('cet' + f.replace('.txt', '.fits') + '[sci]')  # just to check
Esempio n. 4
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def reduce_science(rawdir, rundir, flat, arc, twilight, twilight_flat, sciimg,
                   starimg, bias, overscan, vardq, observatory, lacos,
                   apply_lacos, lacos_xorder, lacos_yorder, lacos_sigclip,
                   lacos_objlim, bpm, instrument, slits, fl_gscrrej,
                   wltrim_frac, grow_gap, cube_bit_mask):
    """
    Reduction pipeline for standard star.

    Parameters
    ----------
    rawdir: string
        Directory containing raw images.
    rundir: string
        Directory where processed files are saved.
    flat: string
        Names of the files containing flat field images.
    arc: string
        Arc images.
    twilight: string
        Twilight flat images.
    twilight_flat: string
        Flat field for twilight image.
    starimg: string
        Name of the file containing the image to be reduced.
    bias: string
        Bias images.
    grow_gap: number
        Number of pixels by which to grow the bad pixel mask around
        the chip gaps.

    """

    iraf.set(stdimage='imtgmos')

    iraf.gemini()
    iraf.unlearn('gemini')

    iraf.gmos()
    iraf.unlearn('gmos')

    iraf.gemtools()
    iraf.unlearn('gemtools')

    # os.path.isfile('arquivo')

    iraf.unlearn('gemini')
    iraf.unlearn('gmos')

    iraf.task(lacos_spec=lacos)

    # set directories
    iraf.set(caldir=rawdir)  #
    iraf.set(rawdir=rawdir)  # raw files
    iraf.set(procdir=rundir)  # processed files

    iraf.gmos.logfile = 'logfile.log'
    iraf.gfextract.verbose = 'no'

    iraf.cd('procdir')

    flat = flat.replace('.fits', '')
    twilight = twilight.replace('.fits', '')
    twilight_flat = twilight_flat.replace('.fits', '')
    arc = arc.replace('.fits', '')
    starimg = starimg.replace('.fits', '')
    sciimg = sciimg.replace('.fits', '')
    mdffile = 'mdf' + flat + '.fits'

    iraf.gfreduce.bias = 'caldir$' + bias
    iraf.gfreduce.fl_fulldq = 'yes'
    iraf.gfreduce.fl_fixgaps = 'yes'
    iraf.gfreduce.grow = grow_gap
    iraf.gireduce.bpm = 'rawdir$' + bpm
    iraf.gfextract.verbose = 'no'

    cal_reduction(rawdir=rawdir,
                  rundir=rundir,
                  flat=flat,
                  arc=arc,
                  twilight=twilight,
                  bias=bias,
                  bpm=bpm,
                  overscan=overscan,
                  vardq=vardq,
                  instrument=instrument,
                  slits=slits,
                  twilight_flat=twilight_flat,
                  grow_gap=grow_gap)
    #
    #   Actually reduce science
    #
    image_name = 'rg' + sciimg + '.fits'
    if os.path.isfile(image_name):
        pipe.skipwarn(image_name)
    else:
        iraf.gfreduce(sciimg,
                      slits='header',
                      rawpath='rawdir$',
                      fl_inter='no',
                      fl_addmdf='yes',
                      key_mdf='MDF',
                      mdffile=mdffile,
                      weights='no',
                      fl_over=overscan,
                      fl_trim='yes',
                      fl_bias='yes',
                      trace='no',
                      recenter='no',
                      fl_fulldq='yes',
                      fl_flux='no',
                      fl_gscrrej='no',
                      fl_extract='no',
                      fl_gsappwave='no',
                      fl_wavtran='no',
                      fl_novl='yes',
                      fl_skysub='no',
                      fl_vardq=vardq,
                      mdfdir='procdir$')
    prefix = 'rg'

    # Gemfix
    image_name = 'p' + prefix + sciimg + '.fits'
    if os.path.isfile(image_name):
        pipe.skipwarn(image_name)
    else:
        iraf.gemfix(prefix + sciimg,
                    out='p' + prefix + sciimg,
                    method='fit1d',
                    bitmask=65535,
                    axis=1)
    prefix = 'p' + prefix

    # LA Cosmic - cosmic ray removal
    if apply_lacos:
        image_name = 'l' + prefix + sciimg + '.fits'
        if os.path.isfile(image_name):
            pipe.skipwarn(image_name)
        else:
            iraf.gemcrspec(prefix + sciimg,
                           out='l' + prefix + sciimg,
                           sigfrac=0.5,
                           niter=4,
                           fl_vardq=vardq,
                           xorder=lacos_xorder,
                           yorder=lacos_yorder,
                           sigclip=lacos_sigclip,
                           objlim=lacos_objlim)
        prefix = 'l' + prefix

    if fl_gscrrej:
        image_name = 'ex' + prefix + sciimg + '.fits'
    else:
        image_name = 'e' + prefix + sciimg + '.fits'

    if os.path.isfile(image_name):
        pipe.skipwarn(image_name)
    else:
        iraf.gfreduce(prefix + sciimg,
                      slits='header',
                      rawpath='./',
                      fl_inter='no',
                      fl_addmdf='no',
                      key_mdf='MDF',
                      mdffile=mdffile,
                      fl_over='no',
                      fl_trim='no',
                      fl_bias='no',
                      trace='no',
                      recenter='no',
                      fl_flux='no',
                      fl_gscrrej=fl_gscrrej,
                      fl_extract='yes',
                      fl_gsappwave='yes',
                      fl_wavtran='no',
                      fl_novl='no',
                      fl_skysub='no',
                      grow=grow_gap,
                      reference='eprg' + flat,
                      weights='no',
                      wavtraname='eprg' + arc,
                      response='eprg' + flat + '_response.fits',
                      fl_vardq=vardq,
                      fl_fulldq='yes',
                      fl_fixgaps='yes')

    if fl_gscrrej:
        prefix = 'ex' + prefix
    else:
        prefix = 'e' + prefix

    # if wl2 > 7550.0:
    #     wl2 = 7550.0

    #
    #   Apply wavelength transformation
    #

    wl1, wl2 = wl_lims(prefix + sciimg + '.fits', wltrim_frac)

    image_name = 't' + prefix + sciimg + '.fits'
    if os.path.isfile(image_name):
        pipe.skipwarn(image_name)
    else:
        iraf.gftransform(
            prefix + sciimg,
            wavtraname='eprg' + arc,
            fl_vardq=vardq,
            w1=wl1,
            w2=wl2,
        )

    prefix = 't' + prefix
    #
    #   Sky subtraction
    #
    image_name = 's' + prefix + sciimg + '.fits'
    if os.path.isfile(image_name):
        pipe.skipwarn(image_name)
    else:
        iraf.gfskysub(
            prefix + sciimg,
            expr='default',
            combine='median',
            reject='avsigclip',
            scale='none',
            zero='none',
            weight='none',
            sepslits='yes',
            fl_inter='no',
            lsigma=1,
            hsigma=1,
        )

    prefix = 's' + prefix
    #
    #   Apply flux calibration to galaxy
    #
    image_name = 'c' + prefix + sciimg + '.fits'
    if os.path.isfile(image_name):
        pipe.skipwarn(image_name)
    else:
        iraf.gscalibrate(prefix + sciimg,
                         sfuncti=starimg,
                         extinct='onedstds$ctioextinct.dat',
                         observatory=observatory,
                         fluxsca=1,
                         fl_vardq=vardq)
    prefix = 'c' + prefix
    #
    # Remove spurious data with PCA
    #
    image_name = 'x' + prefix + sciimg + '.fits'
    print(os.getcwd())
    print(image_name)
    if os.path.isfile(image_name):
        pipe.skipwarn(image_name)
    else:
        t = pca.Tomography(prefix + sciimg + '.fits')
        t.decompose()
        t.remove_cosmic_rays(sigma_threshold=10.0)
        t.write(image_name)
    prefix = 'x' + prefix
    #
    #   Create data cubes
    #
    image_name = 'd' + prefix + sciimg + '.fits'
    if os.path.isfile(image_name):
        pipe.skipwarn(image_name)
    else:
        data_cube = CubeBuilder(prefix + sciimg + '.fits')
        data_cube.build_cube()
        data_cube.fit_refraction_function()
        data_cube.fix_atmospheric_refraction()
        data_cube.write(image_name)
Esempio n. 5
0
def reduce_stdstar(rawdir,
                   rundir,
                   caldir,
                   starobj,
                   stdstar,
                   flat,
                   arc,
                   twilight,
                   twilight_flat,
                   starimg,
                   bias,
                   overscan,
                   vardq,
                   lacos,
                   observatory,
                   apply_lacos,
                   lacos_xorder,
                   lacos_yorder,
                   lacos_objlim,
                   lacos_sigclip,
                   bpm,
                   instrument,
                   slits,
                   fl_gscrrej,
                   wltrim_frac=0.03,
                   sens_order=6,
                   sens_function='spline3',
                   apsum_radius=1):
    """
    Reduction pipeline for standard star.

    Parameters
    ----------
    rawdir: string
        Directory containing raw images.
    rundi: string
        Directory where processed files are saved.
    caldir: string
        Directory containing standard star calibration files.
    starobj: string
        Object keyword for the star image.
    stdstar: string
        Star name in calibration file.
    flat: list
        Names of the files containing flat field images.
    arc: list
        Arc images.
    twilight: list
        Twilight flat images.
    starimg: string
        Name of the file containing the image to be reduced.
    bias: list
        Bias images.

    """

    iraf.set(stdimage='imtgmos')

    iraf.task(lacos_spec=lacos)

    iraf.gemini()
    iraf.unlearn('gemini')

    iraf.gmos()
    iraf.unlearn('gmos')

    iraf.gemtools()
    iraf.unlearn('gemtools')

    iraf.gmos.logfile = 'logfile.log'
    iraf.gemtools.gloginit.logfile = 'logfile.log'
    iraf.gfextract.verbose = 'no'

    # set directories
    iraf.set(caldir=rawdir)  #
    iraf.set(rawdir=rawdir)  # raw files
    iraf.set(procdir=rundir)  # processed files

    # os.path.isfile('arquivo')

    iraf.cd('procdir')

    flat = flat.strip('.fits')
    twilight = twilight.strip('.fits')
    twilight_flat = twilight_flat.strip('.fits')
    arc = arc.strip('.fits')
    starimg = starimg.strip('.fits')
    mdffile = 'mdf' + flat + '.fits'

    iraf.gfreduce.bias = 'rawdir$' + bias
    iraf.gfreduce.fl_fulldq = 'yes'
    iraf.gfreduce.fl_fixgaps = 'yes'
    iraf.gireduce.bpm = 'rawdir$' + bpm

    cal_reduction(rawdir=rawdir,
                  rundir=rundir,
                  flat=flat,
                  arc=arc,
                  twilight=twilight,
                  bias=bias,
                  bpm=bpm,
                  overscan=overscan,
                  vardq=vardq,
                  instrument=instrument,
                  slits=slits,
                  twilight_flat=twilight_flat)
    #
    #   Actually reduce star
    #
    imageName = 'rg' + starimg + '.fits'
    if os.path.isfile(imageName):
        skipwarn(imageName)
    else:

        imageName = 'g' + starimg + '.fits'
        if os.path.isfile(imageName):
            iraf.printlog(
                'GIREDS: WARNING: Removing file {:s}'.format(imageName),
                'logfile.log', 'yes')
            iraf.delete(imageName)

        iraf.gfreduce(starimg,
                      slits='header',
                      rawpath='rawdir$',
                      fl_inter='no',
                      fl_addmdf='yes',
                      key_mdf='MDF',
                      mdffile=mdffile,
                      weights='no',
                      fl_over=overscan,
                      fl_trim='yes',
                      fl_bias='yes',
                      trace='no',
                      recenter='no',
                      fl_flux='no',
                      fl_gscrrej='no',
                      fl_extract='no',
                      fl_gsappwave='no',
                      fl_wavtran='no',
                      fl_novl='yes',
                      fl_skysub='no',
                      fl_vardq=vardq,
                      mdfdir='procdir$')
    prefix = 'rg'
    #
    # Gemfix
    #
    imageName = 'p' + prefix + starimg + '.fits'
    if os.path.isfile(imageName):
        skipwarn(imageName)
    else:
        iraf.gemfix(prefix + starimg,
                    out='p' + prefix + starimg,
                    method='fit1d',
                    bitmask=1,
                    axis=1)
    prefix = 'p' + prefix
    #
    # LA Cosmic
    #
    if apply_lacos:

        imageName = 'l' + prefix + starimg + '.fits'
        if os.path.isfile(imageName):
            skipwarn(imageName)
        else:
            if apply_lacos:
                iraf.gemcrspec(prefix + starimg,
                               out='l' + prefix + starimg,
                               sigfrac=0.32,
                               niter=4,
                               fl_vardq=vardq,
                               xorder=lacos_xorder,
                               yorder=lacos_yorder,
                               objlim=lacos_objlim,
                               sigclip=lacos_sigclip)

        prefix = 'l' + prefix
    #
    # Extraction and Gemini's comsmic ray rejection
    #
    if fl_gscrrej:
        imageName = 'x' + prefix + starimg + '.fits'

        if os.path.isfile(imageName):
            skipwarn(imageName)
            fl_gscrrej = False
        else:
            imageName = 'ex' + prefix + starimg + '.fits'
            if os.path.isfile(imageName):
                skipwarn(imageName)
            else:
                iraf.gfreduce(prefix + starimg,
                              slits='header',
                              rawpath='./',
                              fl_inter='no',
                              fl_addmdf='no',
                              key_mdf='MDF',
                              mdffile=mdffile,
                              fl_over='no',
                              fl_trim='no',
                              fl_bias='no',
                              trace='no',
                              recenter='no',
                              fl_flux='no',
                              fl_gscrrej=fl_gscrrej,
                              fl_extract='yes',
                              fl_gsappwave='yes',
                              fl_wavtran='no',
                              fl_novl='no',
                              fl_skysub='no',
                              reference='eprg' + flat,
                              weights='no',
                              wavtraname='eprg' + arc,
                              response='eprg' + flat + '_response.fits',
                              fl_vardq=vardq)
        prefix = 'ex' + prefix
    else:
        imageName = 'e' + prefix + starimg + '.fits'

        if os.path.isfile(imageName):
            skipwarn(imageName)
        else:
            iraf.gfreduce(prefix + starimg,
                          slits='header',
                          rawpath='./',
                          fl_inter='no',
                          fl_addmdf='no',
                          key_mdf='MDF',
                          mdffile=mdffile,
                          fl_over='no',
                          fl_trim='no',
                          fl_bias='no',
                          trace='no',
                          recenter='no',
                          fl_flux='no',
                          fl_gscrrej=fl_gscrrej,
                          fl_extract='yes',
                          fl_gsappwave='yes',
                          fl_wavtran='no',
                          fl_novl='no',
                          fl_skysub='no',
                          reference='eprg' + flat,
                          weights='no',
                          wavtraname='eprg' + arc,
                          response='eprg' + flat + '_response.fits',
                          fl_vardq=vardq)
        prefix = 'e' + prefix
    #
    # Wavelength transform
    #
    wl1, wl2 = wl_lims(prefix + starimg + '.fits', wltrim_frac)
    imageName = 't' + prefix + starimg + '.fits'
    if os.path.isfile(imageName):
        skipwarn(imageName)
    else:
        iraf.gfreduce(prefix + starimg,
                      slits='header',
                      rawpath='./',
                      fl_inter='no',
                      fl_addmdf='no',
                      key_mdf='MDF',
                      mdffile=mdffile,
                      fl_over='no',
                      fl_trim='no',
                      fl_bias='no',
                      trace='no',
                      recenter='no',
                      fl_flux='no',
                      fl_gscrrej='no',
                      fl_extract='no',
                      fl_gsappwave='no',
                      fl_wavtran='yes',
                      fl_novl='no',
                      fl_skysub='no',
                      reference='eprg' + flat,
                      weights='no',
                      wavtraname='eprg' + arc,
                      response='eprg' + flat + '_response.fits',
                      fl_vardq=vardq,
                      w1=wl1,
                      w2=wl2)
    prefix = 't' + prefix

    #
    # Sky subtraction
    #
    imageName = 's' + prefix + starimg + '.fits'
    if os.path.isfile(imageName):
        skipwarn(imageName)
    else:
        iraf.gfreduce(prefix + starimg,
                      slits='header',
                      rawpath='./',
                      fl_inter='no',
                      fl_addmdf='no',
                      key_mdf='MDF',
                      mdffile=mdffile,
                      fl_over='no',
                      fl_trim='no',
                      fl_bias='no',
                      trace='no',
                      recenter='no',
                      fl_flux='no',
                      fl_gscrrej='no',
                      fl_extract='no',
                      fl_gsappwave='no',
                      fl_wavtran='no',
                      fl_novl='no',
                      fl_skysub='yes',
                      reference='eprg' + flat,
                      weights='no',
                      wavtraname='eprg' + arc,
                      response='eprg' + flat + '_response.fits',
                      fl_vardq=vardq,
                      w1=wl1,
                      w2=wl2)
    prefix = 's' + prefix
    #
    #   Apsumming the stellar spectra
    #
    xinst = pf.getdata(prefix + starimg + '.fits', ext=1)['XINST']
    if instrument == 'GMOS-N':
        x0 = np.average(xinst[xinst < 10])
    elif instrument == 'GMOS-S':
        x0 = np.average(xinst[xinst > 10])

    ap_expression = '((XINST-{:.2f})**2 + '\
        '(YINST-2.45)**2)**0.5 < {:.2f}'.format(x0, apsum_radius)

    imageName = 'a' + prefix + starimg + '.fits'
    if os.path.isfile(imageName):
        skipwarn(imageName)
    else:
        iraf.gfapsum(prefix + starimg,
                     fl_inter='no',
                     lthreshold='INDEF',
                     hthreshold='INDEF',
                     reject='avsigclip',
                     expr=ap_expression)
    #
    #   Building sensibility function
    #
    if os.path.isfile('std' + starimg)\
            and os.path.isfile('sens' + starimg + '.fits'):
        skipwarn('std{0:s} and sens{0:s}.fits'.format(starimg))
    else:

        imageName = 'std' + starimg
        if os.path.isfile(imageName):
            iraf.printlog(
                'GIREDS: WARNING: Removing file {:s}'.format(imageName),
                'logfile.log', 'yes')
            iraf.delete(imageName)

        imageName = 'sens' + starimg + '.fits'
        if os.path.isfile(imageName):
            iraf.printlog(
                'GIREDS: WARNING: Removing file {:s}'.format(imageName),
                'logfile.log', 'yes')
            iraf.delete(imageName)

        iraf.gsstandard('a' + prefix + starimg,
                        starname=stdstar,
                        observatory=observatory,
                        sfile='std' + starimg,
                        sfunction='sens' + starimg,
                        caldir=caldir,
                        order=sens_order,
                        function=sens_function)
    #
    #   Apply flux calibration to star
    #
    imageName = 'c' + prefix + starimg + '.fits'
    if os.path.isfile(imageName):
        skipwarn(imageName)
    else:
        iraf.gscalibrate(prefix + starimg,
                         sfuncti='sens' + starimg,
                         extinct='onedstds$ctioextinct.dat',
                         observatory=observatory,
                         fluxsca=1,
                         fl_vardq=vardq)
    #
    #   Create data cubes
    #
    imageName = 'dc' + prefix + starimg + '.fits'
    if os.path.isfile(imageName):
        skipwarn(imageName)
    else:
        data_cube = CubeBuilder('c' + prefix + starimg + '.fits')
        data_cube.build_cube()
        data_cube.fit_refraction_function()
        data_cube.fix_atmospheric_refraction()
        data_cube.write(imageName)

    #
    # Test calibration
    #
    iraf.cd(caldir)
    caldata = np.loadtxt(stdstar + '.dat', unpack=True)
    iraf.cd('procdir')
    calflux = mag2flux(caldata[0], caldata[1])

    imageName = 'ca' + prefix + starimg + '.fits'
    if os.path.isfile(imageName):
        skipwarn(imageName)
    else:
        iraf.gscalibrate('a' + prefix + starimg,
                         sfuncti='sens' + starimg,
                         extinct='onedstds$ctioextinct.dat',
                         observatory=observatory,
                         fluxsca=1)

    sumflux = pf.getdata('ca' + prefix + starimg + '.fits', ext=2)
    sumhead = pf.getheader('ca' + prefix + starimg + '.fits', ext=2)
    sumwl = sumhead['crval1'] + np.arange(
        sumhead['naxis1']) * sumhead['cdelt1']

    plt.close('all')
    plt.plot(sumwl, sumflux, 'b', lw=.5)
    plt.plot(caldata[0], calflux, 'r', lw=1.5)
    plt.xlim(sumwl[0] * .99, sumwl[-1] * 1.01)
    plt.ylim(min(calflux) * .8, max(calflux) * 1.2)
    plt.savefig('calib' + starimg + '.eps')
Esempio n. 6
0
import glob, os
import g0_init_cfg as ic


# ----- Importing IRAF from the root directory ----- #
current_dir = os.getcwd()
os.chdir(ic.dir_iraf)

from pyraf import iraf
from pyraf.iraf import gemini, gmos

os.chdir(current_dir)
iraf.chdir(current_dir)


# ----- Spectrophotometric calibration ----- #
iraf.imdelete('cstxeqxbrg@'+ic.lst_sci, verify='no')
for sci in iraf.type(ic.lst_sci, Stdout=1):
	sci = sci.strip()
	iraf.gscalibrate('stxeqxbrg'+sci, sfunction=ic.caldir+ic.sensfunc,
		             obs=ic.obs_site, extinction=ic.extinction,
		             fl_ext='yes', fl_vardq='yes')

os.system('ds9 &')
iraf.sleep(5.0)
for sci in iraf.type(ic.lst_sci, Stdout=1):
	iraf.gfdisplay('cstxeqxbrg'+sci, 1, version=1)


# Printing the running time
print('--- %s seconds ---' %(time.time()-start_time))
Esempio n. 7
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    vardq = 'yes'
    for i in gal:
        iraf.gsreduce(rawdir + i,
                      rawpath=rawdir,
                      bias=rawdir + bias,
                      fl_fixpix='yes',
                      flat='flat.fits',
                      fl_over='no',
                      fl_gscrrej='yes',
                      fl_vardq=vardq,
                      fl_fulldq=vardq)
        iraf.gstransform('gs' + i,
                         wavtraname='gs' + arc.replace('.fits', ''),
                         fl_vardq=vardq)
        iraf.gsskysub('tgs' + i, long_sample='800:900', fl_vardq=vardq)
        iraf.gscalibrate('stgs' + i, fl_vardq=vardq)

    a = iraf.hselect((3 * 'cstgs{:s}[0],').format(*gal),
                     'xoffset,yoffset',
                     'yes',
                     Stdout=1)

    pixscale = 0.292  # arcsec/pix along the direction of the slit
    b = np.array([[float(j) for j in i.split('\t')] for i in a]) / pixscale
    np.savetxt('offsets.dat', b)

    iraf.imcombine((3 * 'cstgs{:s}[2],').format(*gal),
                   'ngc3081_545.fits',
                   offsets='offsets.dat',
                   combine='average',
                   reject='sigclip')
Esempio n. 8
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    iraf.gsskysub(
        'tgs' + star, long_sample='150:200')
    iraf.gsextract(
        'stgs' + star)
    iraf.gsstandard(
        'estgs' + star, caldir='onedstds$ctionewcal/', starname='l3218')   
    
    for i in gal:
        iraf.gsreduce(
            rawdir + i, rawpath=rawdir, bias=rawdir + bias,
            fl_fixpix='yes', flat='flat.fits', fl_over='no',
            fl_gscrrej='yes')
        iraf.gstransform(
            'gs' + i, wavtraname='gs' + arc.replace('.fits', ''))
        iraf.gsskysub(
            'tgs' + i, long_sample='800:900')
        iraf.gscalibrate(
            'stgs' + i)

    a = iraf.hselect(
        (3*'cstgs{:s}[0],').format(*gal), 'xoffset,yoffset', 'yes', Stdout=1)
    
    pixscale = 0.292  # arcsec/pix along the direction of the slit
    b = np.array([[float(j) for j in i.split('\t')] for i in a]) / pixscale
    np.savetxt('offsets.dat', b)

    iraf.imcombine(
        (3*'cstgs{:s}[2],').format(*gal), 'ngc3081_545.fits',
        offsets='offsets.dat', combine='average', reject='sigclip')

Esempio n. 9
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        iraf.gsstandard(
            'astexlrg'+n, starname=stdstar[m],
            observatory=observatory[m], sfile='std'+str(m)+'_'+str(i),
            sfunction='sens'+str(m), caldir=caldir[m])
'''


# (B)Test calibration
import matplotlib.pyplot as plt

starflux = [locrep+starinfo[i]['flux'] for i in starinfo_idx]
for m, i in enumerate(star):
    iraf.delete('castexlrg'+i+'.fits')

    iraf.gscalibrate(
        'astexlrg'+i, sfuncti='sens'+str(m),
        observa=observatory[m], fluxsca=1)

    starcal_fl = pf.getdata('castexlrg'+i+'.fits', ext=2)
    starcal_he = pf.getheader('castexlrg'+i+'.fits', ext=2)
    starcal_wl = starcal_he['crval1'] + np.arange(starcal_he['naxis1'])*starcal_he['cdelt1']
    starrep = np.loadtxt(starflux[m], unpack=True)

    # Need: baixar arquivos de todas estrelas com contagem em fluxo
    #       ou converter o arquivo do gmos de mag>fluxo
    # Need: limitar range(x) do arquivo do repositorio
    # Need: limitar range(y) do plot. 
    plt.close('all')
    plt.plot(starcal_wl, starcal_fl, 'b')
    plt.plot(starrep[0], starrep[1], 'r', lw=1.56)
    plt.xlim(starcal_wl[0], starcal_wl[-1])