Ejemplo n.º 1
0
	def findWorldPosition(self, write=False):

                # Convert the GRB pixel position to WCS
                # Make the input file for the IRAF task
                if self._pixelx == "" or self._pixely == "":
                        print "You did not set an pixel x or pixel y"
                        return 1
                coordfilenamein = "%s" % (self._parentimage.replace(".fits", "_skyctran_pixel_in.coo"))
                coordfilenameout = "%s" % (self._parentimage.replace(".fits", "_skyctran_pixel_out.coo"))

		try:
			self.cleanOutputFiles(coordfilenameout)
		except:
			print "Error cleaning files"
			print sys.exc_info()[0]

                try:
                        coordout = open(coordfilenamein, "w")
                        coordout.write("%10.7f %10.7f" % (self._pixelx, self._pixely))
                        coordout.close()
                except:
                        print "File opening failed:"
                        print sys.exc_info()[0]

                # This subroutine lies in imcoords on IRAF
                iraf.image()
                iraf.imcoords()

                # Set the parameters of skyctran
                # 
                # input
                # output
                # insystem: input coordinate system
                # outsystem: output coordinate system
                # lngcolu: RA column no. 
                # latcolu: DEC column no.
                # ilnguni: RA input coord type
                # ilnlatuni: DEC input coord type
                # olnguni: RA output coord type
                # olatuni: DEC output coord type
                # ilngfor: RA input float format
                # ilatfor: DEC input float format
                # olngfor: RA output float format
                # olatfor: DEC output float format
                iraf.skyctran.setParam('input', coordfilenamein)
                iraf.skyctran.setParam('output', coordfilenameout)
                iraf.skyctran.setParam('insystem', '%s logical' % self._parentimage)
                iraf.skyctran.setParam('outsystem', '%s world' % self._parentimage)
                iraf.skyctran.setParam('lngcolu', '1')
                iraf.skyctran.setParam('latcolu', '2')
                iraf.skyctran.setParam('ilnguni', 'logical') 
                iraf.skyctran.setParam('ilatuni', 'logical') 
                iraf.skyctran.setParam('olnguni', 'degrees')
                iraf.skyctran.setParam('olatuni', 'degrees')
                iraf.skyctran.setParam('ilngfor', '%10.7f')
                iraf.skyctran.setParam('ilatfor', '%10.7f')
                iraf.skyctran.setParam('olngfor', '%10.3f')
                iraf.skyctran.setParam('olatfor', '%10.3f')
                iraf.skyctran.setParam('verbose', 'yes')

                # savepars
                skyctran = "skyctranpars.par"
                #iraf.skyctran.saveParList(skyctran)

                # run skyctran
                tmp = iraf.skyctran(mode='h', Stdout=1) 

                # Set properties of this object from the output
                try:
                        coordfile = open(coordfilenameout, "r")

                        # parse the input file
                        coords = coordfile.readlines()
                        coordfile.close()
                        for coord in coords:
                                if coord[0] != "#" and coord[0] != "\n":
                                        coordinates = [i for i in coord.replace("\n","").split(" ") if i != ""]

                        # Set the object parameters
                        self._ra = float(coordinates[2])
                        self._dec = float(coordinates[3])

                except:
                        print "File opening failed"
                        print sys.exc_info()[0]


                # region file for object of interest
                if write:
                        try:
                                regionout = open("%s" % (self._parentimage.replace(".fits", "_skyctran_object.reg")), "w")
				if self._MEDFWHM == "":
					circ = 4.0
				else:
					circ = self._MEDFWHM*1.5
                                regionout.write("image; circle(%f,%f,%f) # color = red\n" % (self._pixelx, self._pixely, circ))
                                regionout.close()
                        except:
                                print "Unexpected error:"
                                print sys.exc_info()[0]
Ejemplo n.º 2
0
def performPhotometry(task, logger):
  #iraf.prcacheOff()
  [iraf.unlearn(t) for t in ('phot','pstselect','psf','allstar')]
  iraf.set(imtype="fits,noinherit")   # set image output format
  iraf.set(clobber="yes")
  hdu=pyfits.open(task['images'])[0] 
  hdr = hdu.header
  imdata = hdu.data  
  for key,value in task['fits'].iteritems():
    task[key] = hdr.get(value,1)

  #Sextractor to find stars; add an object for the force detect
  logger.info('Running SExtractor on [%s]' % os.path.basename(task['images']))
  sex = sextractor.SExtractor()
  makeSexConfig(sex,task)
  sex.run(task['images'])
  catalog = sex.catalog()

  #Set up image parameters
  MIN_X = max(1,int(task['numpixx']*task['filtfactor']))
  MIN_Y = max(1,int(task['numpixy']*task['filtfactor']))
  MAX_X = int(task['numpixx']*(1-task['filtfactor']))
  MAX_Y = int(task['numpixy']*(1-task['filtfactor']))
  AREAXY = '[%s:%s,%s:%s]' % (MIN_X, MAX_X, MIN_Y, MAX_Y)
  AREANO = '[%s:%s,%s:%s]' % (MIN_X, MAX_X-2*MIN_X, MIN_Y, MAX_Y-2*MIN_Y)
  try:
    task['pixscale'] = abs(hdr.get('CD1_1'))*3600.
  except TypeError:
    task['pixscale'] = abs(hdr.get('CDELT1'))*3600.
  task['seeing'] = np.median( sorted([i['FWHM_IMAGE'] for i in catalog])[:int(-len(catalog)*0.5)] ) #Take the median of the "bottom" 50% of objects
  
  logger.info('--> %s SExtractor detected bright objects in the field' % (len(catalog),) )
  logger.info('--> %0.2f median FWHM of bright objects in the field, in arcsec' % (task['seeing']*task['pixscale'],))

  task['objects'] = [(i['ALPHA_J2000'],i['DELTA_J2000']) for i in catalog]
  task['objects'].append(task['objwcs'])  
  task['objectlist'] = open(os.path.join(task['output_directory'],'objectlist'),'w')  
  task['objectlist'].write('\n'.join([' %s %s' % (i[0],i[1]) for i in task['objects']]))
  task['objectlist'].close()

  logger.info('Running iraf.imstat')
  irafoutput = iraf.imstat(images=task['images']+AREANO,fields='midpt,min,max,stddev', format=0, Stdout=1)
  task['nimgs'] = hdr.get('NIMGS',1)
  task['gain'] *= task['nimgs']*2/3.
  task['ron'] *= np.sqrt(task['nimgs'])/task['nimgs']*constants.INTERPSM[task['band']]
  task['datamean'], task['datamin'], task['datamax'], task['datastdev']  = map(float, irafoutput[0].split())
  irafoutput = iraf.imstat(images=task['images'],fields='stddev,midpt',nclip=25,format=0,cache='yes',Stdout=1)
  task['skynoise'], task['datamean'] = map(float, irafoutput[0].split() )
  task['skynoise'] *= constants.INTERPSM[task['band']]
  task['airmass'] = hdr.get('AIRMASS',1)
  task['zmag'] -= (float(task['airmass'])-1.0)*constants.extinction_coefficients[task['band']]  
  task['match_proximity'] = 2.5 * task['seeing']
  logger.info('--> %5.2f counts: Sky noise, corrected for drizzle imcombine' % task['skynoise'])
  logger.info('--> %5.2f Median count value, after background subtraction' % task['datamean'])
  logger.info('--> %5.2f Airmass' % task['airmass'])

  #prepare temp files that iraf will use
  for filename in ('photfile','pstfile','psfimg','opstfile','groupfile','allstarfile','rejfile','subimage'): 
    task[filename] = open(os.path.join(task['output_directory'],filename),'w')
    task[filename].close()

  #iraf.phot to get APP magnitudes
  logger.info('Running iraf.apphot.phot')
  #apsizes = [i*task['faperture']*task['seeing'] for i in (0.4,0.5,0.6,0.8,1.0,1.2,1.5,2.0,2.5,3.0)]
  #irafapsizes = ','.join(['%.2f' % i for i in apsizes])
  irafapsizes = '%0.2f' % (task['faperture']*task['seeing'])
  kwargs = dict(image=task['images'],coords=task['objectlist'].name,
    output=task['photfile'].name,
    interac='no',scale=1,
    fwhmpsf=task['seeing'], 
    wcsin='world', wcsout='physical',
    sigma=task['skynoise'],
    datamin=task['datamin'],
    datamax=task['datamax'],
    readnoi=task['ron'],
    epadu=task['gain'],
    itime=task['exposure'],
    xairmass=task['airmass'],
    ifilter=task['band'],
    otime=task['dateobs'],
    aperture= irafapsizes,
    zmag=task['zmag'],
    annulus=task['fannulus']*task['seeing'],
    dannulus=task['fdannulus']*task['seeing'],
    calgorithm='gauss',
    cbox = 1.5*task['seeing'],
    maxshift=2.0*task['seeing'],
    mode="h",Stdout=1,verify=0)
  iraf.phot(**kwargs)

  if task['band'] not in constants.infrared:
    #iraf.pstselect to choose objects for PSF modelling
    logger.info('Running iraf.daophot.pstselect')
    kwargs = dict(image=task['images'],
                     photfile=task['photfile'].name,pstfile=task['pstfile'].name,
                     maxnpsf=task['pstnumber'],
                     wcsin='physical',
                     wcsout='physical',
                     interac="no",verify='no',scale=1,
                     fwhmpsf=task['seeing'],
                     datamin=0,
                     datamax=task['datamax'],
                     psfrad=3.0*task['seeing'],
                     fitrad=1.0*task['seeing'],
                     recente='yes',
                     nclean=task['nclean'],
                     mode="h",Stdout=1)
    iraf.pstselect(**kwargs)

    #iraf.psf to model PSF
    logger.info('Running iraf.daophot.psf')
    kwargs = dict( image=task['images'],
              photfile=task['photfile'].name,
              pstfile=task['pstfile'].name,
              psfimage=task['psfimg'].name,
              opstfile=task['opstfile'].name,
              groupfile=task['groupfile'].name,
              wcsin='physical',wcsout='physical',
              interac="no",verify="no",scale=1,
              fwhmpsf=task['seeing'],
              sigma=task['skynoise'],
              datamin=task['datamin'],
              datamax=task['datamax'],
              readnoi=task['ron'],
              epadu=task['gain'],
              itime=task['exposure'],
              xairmass=task['airmass'],
              ifilter=task['band'],
              otime=task['dateobs'],
              function=task['func'],
              varorder=task['varorder'],
              saturat='no',
              psfrad=3.0*task['seeing'],
              fitrad=1.*task['faperture']*task['seeing'],
              nclean=task['nclean'],
              mergerad=1.5*task['seeing'],
              mode='h',Stdout=1)  

    iraf.psf(**kwargs)
    logger.info('Running iraf.daophot.allstar')
    #iraf.allstars to compute PSF photometry; recenter with recenter='yes', mergerad=<value> to avoid duplicate detection
    kwargs = dict(image=task['images'],
                  photfile=task['photfile'].name,
                  wcsin='physical',
                  wcsout='physical',
                  psfimage=task['psfimg'].name,
                  allstarf=task['allstarfile'].name,
                  rejfile=task['rejfile'].name,
                  subimage=task['subimage'].name,
                  verbose=1,verify='no',scale=1,
                  fwhmpsf=task['seeing'],
                  sigma=task['skynoise'],
                  datamin=task['datamin'],
                  datamax=task['datamax'],
                  readnoi=task['ron'],
                  epadu=task['gain'],
                  itime=task['exposure'],
                  xairmass=task['airmass'],
                  ifilter=task['band'],
                  otime=task['dateobs'],
                  function=task['func'],
                  varorder=task['varorder'],
                  psfrad=3.*task['seeing'],
                  fitrad=1.*task['faperture']*task['seeing'],
                  recenter='yes',
                  mergerad=1.5*task['seeing'],
                  mode='h',Stdout=1)
    iraf.allstar(**kwargs)
  

  #Parse both photometry, convert to RA,DEC,MAG,MAGERR
  logger.info('iraf tasks complete. Parsing results and calibrating')
  photometry = {}
  photometry['APP'] = iraf.txdump(textfiles=task['photfile'].name,
                        fields='XCENTER,YCENTER,MAG,MERR',expr='yes',
                        headers='no',Stdout=1)

  if task['band'] not in constants.infrared:
    photometry['PSF'] = iraf.txdump(textfiles=task['allstarfile'].name,
                          fields='XCENTER,YCENTER,MAG,MERR',expr='yes',
                          headers='no',Stdout=1)


  for phototype in photometry:
    kwargs = dict(input='STDIN',
                  output='STDOUT',
                  insystem='%s physical' % task['images'],
                  outsystem='%s world' % task['images'],
                  ilatuni='physical',
                  ilnguni='physical',
                  olnguni='degrees',
                  olatuni='degrees',
                  ilngfor='%10.7f',
                  ilatfor='%10.7f',
                  olngfor='%10.5f',
                  olatfor='%10.5f',
                  Stdin=photometry[phototype],Stdout=1)
    photometry[phototype] = [i.split() for i in iraf.skyctran(**kwargs) if i and not i.startswith('#') and 'INDEF' not in i]
    photometry[phototype] = [map(float,(i[4],i[5],i[2],i[3])) for i in photometry[phototype] ] #Now we have [(ra,dec,'mag','mageerr'),...]
  results = calibrate((task['objwcs'][0],task['objwcs'][1]),task,photometry,logger)
#  if 'PSF' not in results:
    
  return results