Python iraf.imred函数代码示例

def wl_cal(filename, outname, cals):
    print 'run wavelength calibration...'
    if os.path.isfile(outname):
        print 'file %s is already exist' % outname
    else:
        iraf.imred()
        iraf.specred()
        print 'The calibration file is listed below:'
        for i in xrange(len(cals)):
            print i, cals[i], get_fits_objname(cals[i])
        valget = 0
        if len(cals) > 1:
            valget = raw_input('Which one are you want to use?:')
            while type(eval(valget)) != int:
                valget = raw_input('input is not a int type, please reinput:')
            valget = int(valget)
        iraf.refspectra(input = filename
                , references = cals[valget], apertures = '', refaps = ''
                , ignoreaps = True, select = 'interp', sort = ''
                , group = '', time = False, timewrap = 17.0
                , override = False, confirm = True, assign = True
                , logfiles = 'STDOUT,logfile', verbose = False, answer = 'yes')
        print 'make file ' + outname + '...'
        iraf.dispcor(input = filename
                , output = outname, linearize = True, database = 'database'
                , table = '', w1 = 'INDEF', w2 = 'INDEF', dw = 'INDEF'
                , nw = 'INDEF', log = False, flux = True, blank = 0.0
                , samedisp = False, ignoreaps = True
                , confirm = False, listonly = False, verbose = True
                , logfile = '')
    print 'splot %s' % outname
    iraf.splot(images = outname)

def divflat(imagesre, flat='Flat'):
    '''Run ccdproc task to images'''

    imageslist = glob.glob(imagesre)
    imagesin = ', '.join(imageslist)

    # Load packages
    iraf.imred()
    iraf.ccdred()
    # Unlearn settings
    iraf.ccdred.ccdproc.unlearn()
    iraf.ccdred.combine.unlearn()
    # Setup and run task
    iraf.ccdred.ccdproc.ccdtype = ''
    iraf.ccdred.ccdproc.noproc = False
    iraf.ccdred.ccdproc.fixpix = False
    iraf.ccdred.ccdproc.overscan = False
    iraf.ccdred.ccdproc.darkcor = False
    iraf.ccdred.ccdproc.illumcor = False
    iraf.ccdred.ccdproc.fringecor = False
    iraf.ccdred.ccdproc.readcor = False
    iraf.ccdred.ccdproc.scancor = False
    iraf.ccdred.ccdproc.trim = False
    iraf.ccdred.ccdproc.trimsec = ''
    iraf.ccdred.ccdproc.readaxis = 'line'
    iraf.ccdred.ccdproc.zerocor = False
    iraf.ccdred.ccdproc.zero = ''
    iraf.ccdred.ccdproc.flatcor = True
    iraf.ccdred.ccdproc.flat = flat
    iraf.ccdred.ccdproc(images=imagesin)

def coroverbiastrim(lstfile):
    iraf.noao()
    iraf.imred()
    iraf.ccdred()
    x1,x2,y1,y2 = get_trim_sec()
    iraf.ccdproc(images = '@' + lstfile + '//[1]'
        , output = '%bo%bo%@' + lstfile
        , ccdtype = '', max_cache = 0, noproc = False
        , fixpix = False, overscan = True, trim = False
        , zerocor = True, darkcor = False, flatcor = False
        , illumcor = False, fringecor = False, readcor = False
        , scancor = False, readaxis = 'line', fixfile = ''
        , biassec = '[5:45,%s:%s]'%(y1,y2), trimsec = '[%s:%s,%s:%s]'%(x1,x2,y1,y2)
        , zero = 'Zero', dark = '', flat = '', illum = '', fringe = ''
        , minreplace = 1.0, scantype = 'shortscan', nscan = 1
        , interactive = False, function = 'chebyshev', order = 1
        , sample = '*', naverage = 1, niterate = 1
        , low_reject = 3.0, high_reject = 3.0, grow = 1.0)
    iraf.ccdproc(images = '%bo%bo%@' + lstfile
        , output = '%tbo%tbo%@' + lstfile
        , ccdtype = '', max_cache = 0, noproc = False
        , fixpix = False, overscan = False, trim = True
        , zerocor = False, darkcor = False, flatcor = False
        , illumcor = False, fringecor = False, readcor = False
        , scancor = False, readaxis = 'line', fixfile = ''
        , biassec = '[5:45,%s:%s]'%(y1,y2), trimsec = '[%s:%s,%s:%s]'%(x1,x2,y1,y2)
        , zero = 'Zero', dark = '', flat = '', illum = '', fringe = ''
        , minreplace = 1.0, scantype = 'shortscan', nscan = 1
        , interactive = False, function = 'chebyshev', order = 1
        , sample = '*', naverage = 1, niterate = 1
        , low_reject = 3.0, high_reject = 3.0, grow = 1.0)
    iraf.flpr()

def correctimages(imagesre, zero='Zero', flat='nFlat'):
    '''Run ccdproc task to correct images'''

    imageslist = glob.glob(imagesre)
    imagesin = ', '.join(imageslist)

    trimsection = str(raw_input('Enter trim section (or Hit <Enter>): '))
    trimquery = True
    if trimsection == '':
        trimquery = False

    # Load Packages
    iraf.imred()
    iraf.ccdred()
    # Unlearn Settings
    iraf.ccdred.ccdproc.unlearn()
    iraf.ccdred.combine.unlearn()
    # Setup and run task
    iraf.ccdred.ccdproc.ccdtype = ''
    iraf.ccdred.ccdproc.noproc = False
    iraf.ccdred.ccdproc.fixpix = False
    iraf.ccdred.ccdproc.overscan = False
    iraf.ccdred.ccdproc.darkcor = False
    iraf.ccdred.ccdproc.illumcor = False
    iraf.ccdred.ccdproc.fringecor = False
    iraf.ccdred.ccdproc.readcor = False
    iraf.ccdred.ccdproc.scancor = False
    iraf.ccdred.ccdproc.trim = trimquery
    iraf.ccdred.ccdproc.trimsec = trimsection
    iraf.ccdred.ccdproc.readaxis = 'line'
    iraf.ccdred.ccdproc.zerocor = True
    iraf.ccdred.ccdproc.zero = zero
    iraf.ccdred.ccdproc.flatcor = True
    iraf.ccdred.ccdproc.flat = flat
    iraf.ccdred.ccdproc(images=imagesin)

def subzero(imagesre, zero='Zero'):
    '''Run ccdproc remove Zero level noise'''

    imageslist = glob.glob(imagesre)
    imagesin = ', '.join(imageslist)

    # Load packages
    iraf.imred()
    iraf.ccdred()
    # Unlearn previouse settings
    iraf.ccdred.ccdproc.unlearn()
    iraf.ccdred.combine.unlearn()
    # setup and run task
    iraf.ccdred.ccdproc.ccdtype = ''
    iraf.ccdred.ccdproc.noproc = False
    iraf.ccdred.ccdproc.fixpix = False
    iraf.ccdred.ccdproc.overscan = False
    iraf.ccdred.ccdproc.darkcor = False
    iraf.ccdred.ccdproc.illumcor = False
    iraf.ccdred.ccdproc.fringecor = False
    iraf.ccdred.ccdproc.readcor = False
    iraf.ccdred.ccdproc.scancor = False
    iraf.ccdred.ccdproc.trim = False
    iraf.ccdred.ccdproc.trimsec = ''
    iraf.ccdred.ccdproc.readaxis = 'line'
    iraf.ccdred.ccdproc.zerocor = True
    iraf.ccdred.ccdproc.zero = zero
    iraf.ccdred.ccdproc.flatcor = False
    iraf.ccdred.ccdproc.flat = ''
    iraf.ccdred.ccdproc(images=imagesin)

def masterbias(biasre, output='Zero', combine='median', reject='minmax',
        ccdtype='', rdnoise='rdnoise', gain='gain'):
    '''run the task ccdred.zerocombine with chosen parameters

    Input:
    -------
     str biasre: regular expression to identify zero level images

    Output:
    -------
     file Zero.fits: combined zerolevel images
    '''

    biaslist = glob.glob(biasre)
    biasstring = ', '.join(biaslist)

    # load packages
    iraf.imred()
    iraf.ccdred()
    # unlearn settings
    iraf.imred.unlearn()
    iraf.ccdred.unlearn()
    iraf.ccdred.ccdproc.unlearn()
    iraf.ccdred.combine.unlearn()
    iraf.ccdred.zerocombine.unlearn()
    iraf.ccdred.setinstrument.unlearn()
    # setup task
    iraf.ccdred.zerocombine.output = output
    iraf.ccdred.zerocombine.combine = combine
    iraf.ccdred.zerocombine.reject = reject
    iraf.ccdred.zerocombine.ccdtype = ccdtype
    iraf.ccdred.zerocombine.rdnoise = rdnoise
    iraf.ccdred.zerocombine.gain = gain
    # run task
    iraf.ccdred.zerocombine(input=biasstring)

def scalewavelenght(calspec):
    ''' Creates a wavelenght solution for 'calspec' '''
    iraf.imred()
    iraf.specred()

    linelist = str(raw_input('Enter file with list of lines (linelists$thar.dat) : '))
    if linelist == '':
        linelist = 'linelists$thar.dat'
    iraf.specred.identify.coordlist = linelist
    iraf.specred.identify(images=calspec)

def combinebias(filename):
    iraf.noao()
    iraf.imred()
    iraf.ccdred()
    iraf.zerocombine(input = 'o//@' + filename
	, output = 'Zero', combine = 'average', reject = 'minmax'
	, ccdtype = '', process = False, delete = False
	, clobber = False, scale = 'none', statsec = ''
	, nlow = 0, nhigh = 1, nkeep = 1, mclip = True
	, lsigma = 3.0, hsigma = 3.0, rdnoise = 'rdnoise'
	, gain = 'gain', snoise = 0.0, pclip = -0.5, blank = 0.0)

def main():
	iraf.noao()
	iraf.imred()
	iraf.ccdred()
        print '=' * 20, 'Overscan', '=' * 20
	correct_overscan('spec.lst')
	print '=' * 20, 'combine bias', '=' * 20
	combine_bias('bias.lst')
	print '=' * 20, 'correct bias', '=' * 20
	correct_bias('spec_no_bias.lst', 'bias_spec.fits')
        name = os.popen('ls object*.lst').readlines()
        name = [i.split()[0] for i in name]
        for i in name:
            ntrim_flat(i)

def flatresponse(input='Flat', output='nFlat'):
    ''' normalize Flat to correct illumination patterns'''

    iraf.imred()
    iraf.ccdred()
    iraf.specred()

    iraf.ccdred.combine.unlearn()
    iraf.ccdred.ccdproc.unlearn()
    iraf.specred.response.unlearn()
    iraf.specred.response.interactive = True
    iraf.specred.response.function = 'chebyshev'
    iraf.specred.response.order = 1
    iraf.specred.response(calibration=input, normalization=input,
            response=output)

def ImportPackages():
	iraf.noao(_doprint=0)
	iraf.rv(_doprint=0)
	iraf.imred(_doprint=0)
	iraf.kpnoslit(_doprint=0)	
	iraf.ccdred(_doprint=0)
	iraf.astutil(_doprint=0)
	
	iraf.keywpars.setParam('ra','CAT-RA') 
	iraf.keywpars.setParam('dec','CAT-DEC')
	iraf.keywpars.setParam('ut','UT')
	iraf.keywpars.setParam('utmiddl','UT-M_E')
	iraf.keywpars.setParam('exptime','EXPTIME')
	iraf.keywpars.setParam('epoch','CAT-EPOC')
	iraf.keywpars.setParam('date_ob','DATE-OBS')
	iraf.keywpars.setParam('hjd','HJD')
	iraf.keywpars.setParam('mjd_obs','MJD-OBS')
	iraf.keywpars.setParam('vobs','VOBS')
	iraf.keywpars.setParam('vrel','VREL')
	iraf.keywpars.setParam('vhelio','VHELIO')
	iraf.keywpars.setParam('vlsr','VLSR')
	iraf.keywpars.setParam('vsun','VSUN')
	iraf.keywpars.setParam('mode','ql')
	iraf.fxcor.setParam('continu','both')
	iraf.fxcor.setParam('filter','none')
	iraf.fxcor.setParam('rebin','smallest')
	iraf.fxcor.setParam('pixcorr','no')
	iraf.fxcor.setParam('apodize','0.2')
	iraf.fxcor.setParam('function','gaussian')
	iraf.fxcor.setParam('width','INDEF')
	iraf.fxcor.setParam('height','0.')
	iraf.fxcor.setParam('peak','no')
	iraf.fxcor.setParam('minwidt','3.')
	iraf.fxcor.setParam('maxwidt','21.')
	iraf.fxcor.setParam('weights','1.')
	iraf.fxcor.setParam('backgro','0.')
	iraf.fxcor.setParam('window','INDEF')
	iraf.fxcor.setParam('wincent','INDEF')
	iraf.fxcor.setParam('verbose','long')
	iraf.fxcor.setParam('imupdat','no')
	iraf.fxcor.setParam('graphic','stdgraph')
	iraf.fxcor.setParam('interac','yes')
	iraf.fxcor.setParam('autowri','yes')
	iraf.fxcor.setParam('autodra','yes')
	iraf.fxcor.setParam('ccftype','image')
	iraf.fxcor.setParam('observa','lapalma')
	iraf.fxcor.setParam('mode','ql')
	return 0

def corhalogen(lstfile):
    iraf.noao()
    iraf.imred()
    iraf.ccdred()
    iraf.ccdproc(images = '[email protected]' + lstfile
        , output = '%ftbo%ftbo%@' + lstfile
        , ccdtype = '', max_cache = 0, noproc = False
        , fixpix = False, overscan = False, trim = False
        , zerocor = False, darkcor = False, flatcor = True
        , illumcor = False, fringecor = False, readcor = False
        , scancor = False, readaxis = 'line', fixfile = ''
        , biassec = '', trimsec = ''
        , zero = 'Zero', dark = '', flat = 'Resp', illum = '', fringe = ''
        , minreplace = 1.0, scantype = 'shortscan', nscan = 1
        , interactive = False, function = 'chebyshev', order = 1
        , sample = '*', naverage = 1, niterate = 1
        , low_reject = 3.0, high_reject = 3.0, grow = 1.0)
    iraf.flpr()

def coroverscan(filename):
    iraf.noao()
    iraf.imred()
    iraf.ccdred()
    iraf.ccdproc(images = '@' + filename + '//[1]'
    	, output = '%o%o%@' + filename
	, ccdtype = '', max_cache = 0, noproc = False
	, fixpix = False, overscan = True, trim = False
	, zerocor = False, darkcor = False, flatcor = False
	, illumcor = False, fringecor = False, readcor = False
	, scancor = False, readaxis = 'line', fixfile = ''
	, biassec = '[5:45,1:4612]', trimsec = '', zero = ''
	, dark = '', flat = '', illum = '', fringe = ''
	, minreplace = 1.0, scantype = 'shortscan', nscan = 1
	, interactive = False, function = 'chebyshev', order = 1
	, sample = '*', naverage = 1, niterate = 1
	, low_reject = 3.0, high_reject = 3.0, grow = 1.0)
    iraf.flpr()

def runapall(imagesre, gain='gain', rdnoise='rdnoise'):
    '''Extract aperture spectra for science images ...'''

    imageslist = glob.glob(imagesre)
    imagesin = ', '.join(imageslist)

    # load packages
    iraf.imred()
    iraf.ccdred()
    iraf.specred()
    # unlearn previous settings
    iraf.ccdred.combine.unlearn()
    iraf.ccdred.ccdproc.unlearn()
    iraf.specred.apall.unlearn()
    # setup and run task
    iraf.specred.apall.format = 'onedspec'
    iraf.specred.apall.readnoise = rdnoise
    iraf.specred.apall.gain = gain
    iraf.specred.apall(input=imagesin)

def findaperture(img, _interactive=False):
    # print "LOGX:: Entering `findaperture` method/function in %(__file__)s" %
    # globals()
    import re
    import string
    import os
    from pyraf import iraf
    import ntt
    iraf.noao(_doprint=0)
    iraf.imred(_doprint=0)
    iraf.specred(_doprint=0)
    toforget = ['specred.apfind']
    for t in toforget:
        iraf.unlearn(t)

    iraf.specred.databas = 'database'
    iraf.specred.dispaxi = 2
    iraf.specred.apedit.thresho = 0

    dv = ntt.dvex()
    grism = ntt.util.readkey3(ntt.util.readhdr(img), 'grism')
    if _interactive:
        _interac = 'yes'
        _edit = 'yes'
    else:
        _interac = 'no'
        _edit = 'no'
    if os.path.isfile('database/ap' + re.sub('.fits', '', img)):
        ntt.util.delete('database/ap' + re.sub('.fits', '', img))
    xx = iraf.specred.apfind(img, interac=_interac, find='yes', recenter='yes', edit=_edit, resize='no',
                             aperture=1, Stdout=1, nfind=1, line=dv['line'][grism], nsum=50, mode='h')
    try:
        for line in open('database/ap' + re.sub('.fits', '', img)):
            if "center" in line:
                center = float(string.split(line)[1])
    except:
        center = 9999
    return center