Python AIPSTask.outcl方法代码示例

# 需要导入模块: from AIPSTask import AIPSTask [as 别名]
# 或者: from AIPSTask.AIPSTask import outcl [as 别名]
def remove_continuum(outseq):
    trans = AIPSTask("trans")
    imlin = AIPSTask("imlin")

    entry = cat.get_entry(1)  # get SDGRD entry
    img = cat.get_image(entry)
    nChan = round(img.header.naxis[2])

    # transpose image in order to run IMLIN
    trans.indisk = DISK_ID
    trans.outdisk = DISK_ID
    trans.baddisk[1] = BADDISK
    trans.inname = entry.name
    trans.inclass = "SDGRD"
    trans.inseq = outseq
    trans.transc = "312"
    trans.outcl = "trans"
    trans.go()

    # Run imlin task on trans file
    # remove a spectral baseline.  Output image is in Freq-RA-Dec order
    # (Transcod 312)
    imlin.indisk = DISK_ID
    imlin.outdisk = DISK_ID
    imlin.outcl = "IMLIN"
    last = cat.last_entry()
    imlin.inname = last.name
    imlin.inclass = last.klass
    imlin.inseq = last.seq
    imlin.nbox = 2
    # use only the end channels for the default baseline fits
    imlin.box[1][1] = round(nChan * 0.04)  # 4-12%
    imlin.box[1][2] = round(nChan * 0.12)
    imlin.box[1][3] = round(nChan * 0.81)  # 82-89%
    imlin.box[1][4] = round(nChan * 0.89)

    imlin.order = 0  # polynomial order
    print "IMLIN box", imlin.box
    imlin.go()

    # Run transpose again task on sdgrd file produced by IMLIN
    last = cat.last_entry()
    trans.inname = last.name
    trans.inclass = last.klass
    trans.inseq = last.seq
    trans.transc = "231"
    trans.outdi = DISK_ID
    trans.outcl = "baseli"
    trans.go()

# 需要导入模块: from AIPSTask import AIPSTask [as 别名]
# 或者: from AIPSTask.AIPSTask import outcl [as 别名]
def time_sort_data():
    """Time-sort data in AIPS with the UVSRT task."""

    print_header("Time-sorting data")

    uvsrt = AIPSTask('uvsrt')
    uvsrt.userno = AIPS.userno

    # -------------------------------------------------------------------------
    #    UVSRT the data
    # -------------------------------------------------------------------------

    # sort data to prevent down stream problems
    uvsrt.indisk = uvsrt.outdisk = DISK_ID
    uvsrt.baddisk[1] = BADDISK
    uvsrt.outcl = 'UVSRT'
    uvsrt.sort = 'TB'
    last = cat.last_entry()
    uvsrt.inname = last.name
    uvsrt.inclass = last.klass
    uvsrt.inseq = last.seq

    # will write to entry 1 because input sdf/uv files were removed
    uvsrt.go()

    nfiles = len(cat)

    for dbcon_entry in range(nfiles-1):
        cat.zap_entry(-1)  # remove the DBCON entries

# 需要导入模块: from AIPSTask import AIPSTask [as 别名]
# 或者: from AIPSTask.AIPSTask import outcl [as 别名]
def pload (filename,aipsname,indisk,outcl,logfiledir='./',doindxr=True):
    fitld = AIPSTask ('FITLD')
    fitld.datain = str(filename)
    fitld.outna = aipsname
    fitld.outcl = outcl
    fitld.outdisk = indisk
    stdout = sys.stdout; sys.stdout = open(logfiledir+aipsname+'.log','a')
    fitld.go ()
    if doindxr:
        uvdata = AIPSUVData (aipsname,'FITS',1,1)
        indxr = AIPSTask ('INDXR')
        indxr.cparm[1:] = [0,0,0.5,0,0,0,0,0,0,0]
        indxr.indata = uvdata
        indxr.go()
    sys.stdout.close(); sys.stdout = stdout

# 需要导入模块: from AIPSTask import AIPSTask [as 别名]
# 或者: from AIPSTask.AIPSTask import outcl [as 别名]
def average_channels(binsize):
    if binsize > 1:
        print "Averaging ", binsize, " Spectral Channels"
    else:
        print "Not Averaging Spectral Channels"
        return

    avspc = AIPSTask("avspc")

    last = cat.last_entry()
    spectra = cat.get_uv(last)
    nChan = round(spectra.header.naxis[2])
    print spectra.header.naxis, nChan

    # now average channels to reduce the image plane data volumn
    avspc.indisk = avspc.outdisk = DISK_ID
    avspc.outclass = ""
    avspc.inname = last.name
    avspc.inclass = last.klass
    avspc.inseq = last.seq
    avspc.channel = binsize
    avspc.ichansel[1][1] = 1
    avspc.ichansel[2][1] = nChan
    avspc.ichansel[3][1] = 1
    avspc.avoption = "SUBS"
    avspc.outcl = "avg"
    avspc.go()

    # now have fewer channels, with broader frequencies
    spectra.header.naxis[2] = round(nChan / binsize)  # write back to header
    print "naxis", spectra.header.naxis
    print "cdelt", spectra.header.cdelt
    dNu = spectra.header.cdelt[2]
    dNu = binsize * dNu  # write back to header !!!
    print "cdelt", spectra.header.cdelt, "dNu", dNu, "binsize", binsize

    refChan = spectra.header.crpix[2]
    print "refChan", refChan, "crpix", spectra.header.crpix
    refChan = refChan / binsize  # write back to header !!!
    print "refChan", refChan, "crpix", spectra.header.crpix
    return

# 需要导入模块: from AIPSTask import AIPSTask [as 别名]
# 或者: from AIPSTask.AIPSTask import outcl [as 别名]
fittp.inseq=AIPSCat()[mydisk][-1].seq
outimage = os.path.splitext(myfiles[0])[0]+'_cont.fits'
if os.path.exists(outimage):
    os.remove(outimage)
    print 'Removed existing file to make room for new one :',outimage
fittp.dataout='PWD:'+outimage
fittp.go()

#Run trans task on sdgrd file to prepare for the Moment map
trans.indisk=mydisk
trans.outdisk=mydisk
trans.inname=AIPSCat()[mydisk][-1].name
trans.inclass='SDGRD'
trans.inseq=1
trans.transc= '312'
trans.outcl='312'
trans.go()

#Run imlin task on trans file
#remove a spectral baseline.  Output image is in Freq-RA-Dec order
#(Transcod 312)
imlin.indisk=mydisk
imlin.outdisk=mydisk
imlin.outcl='IMLIN'
imlin.inname=AIPSCat()[mydisk][-1].name
imlin.inclass=AIPSCat()[mydisk][-1].klass
imlin.inseq=AIPSCat()[mydisk][-1].seq
imlin.nbox=2
# use only the end channels for the default fits
imlin.box[1][1]=round(nChan*0.05)
imlin.box[1][2]=round(nChan*0.1)

# 需要导入模块: from AIPSTask import AIPSTask [as 别名]
# 或者: from AIPSTask.AIPSTask import outcl [as 别名]

#.........这里部分代码省略.........
            for iii in range(0,nObjects):
                if (allObjects[iii] == spectra.header.object):
                    notFound = False
            # if not in the list add to list and increment count
            if (notFound):
                allObjects[nObjects] = spectra.header.object
                nObjects = nObjects+1
            spectra.zap()
    
    #print nObjects,' Object(s) Observed: ', allObjects
    objectName = allObjects[0]
    for iii in range(1,nObjects):
        if len(allObjects[iii]) > 0:
            objectName = objectName + '+' + allObjects[iii]
    
    print nObjects,' Object(s) Observed: ', objectName
    
    if nObjects > 2:
        objectName = allObjects[0] + '+' + str( nObjects-1)
    
    # Extract the observations summary
    spectra = AIPSUVData(AIPSCat()[mydisk][-1].name, AIPSCat()[mydisk][-1].klass, mydisk, AIPSCat()[mydisk][-1].seq)
    
    # Read parameters passed inside the spectra data header
    nChan    = round(spectra.header.naxis[2])
    cellsize = round(spectra.header.cdelt[4] * 3600.)
    refChan  = spectra.header.crpix[2]
    imxSize  = 2*round(spectra.header.crpix[3]/1.5 )
    imySize  = 2*round(spectra.header.crpix[4]/1.5 )
    raDeg    = spectra.header.crval[3]
    decDeg   = spectra.header.crval[4]
    nuRef    = spectra.header.crval[2]
    dNu      = spectra.header.cdelt[2]
    
    print "Ra,Dec:", raDeg, decDeg, "Image:", imxSize, imySize, cellsize, 
    #print spectra.header
    
    #now free up slot 0
    image = WizAIPSImage(AIPSCat()[mydisk][0].name, \
                         AIPSCat()[mydisk][0].klass, \
                         mydisk, AIPSCat()[mydisk][0].seq)
    image.zap()
    
    # sort data to prevent down stream probelms
    uvsrt.indisk=mydisk
    uvsrt.outdisk=mydisk
    uvsrt.baddisk[1]=baddisk
    uvsrt.outcl='UVSRT'
    uvsrt.sort='TB'
    uvsrt.inname=AIPSCat()[mydisk][-1].name
    if kount < 2:
        uvsrt.inclass=AIPSCat()[mydisk][-1].klass
        uvsrt.inseq=kount    
    else:
        uvsrt.inclass='DBCON'
        uvsrt.inseq=kount - 1
    uvsrt.go()
    
    # now clean up the last of the input files
    spectra.zap()
    
    ## and write the last thing now in the catalog to disk
    fittp.indisk=mydisk
    fittp.inname=AIPSCat()[mydisk][-1].name
    fittp.inclass=AIPSCat()[mydisk][-1].klass
    fittp.inseq=AIPSCat()[mydisk][-1].seq
    outName = os.path.splitext(sdf_files[0])[0]
    # Trim out the source name
    iUnder = outName.find("_")
    if iUnder > 0:
        outName = outName[iUnder+1:]
    # Trim out the beam number
    iUnder = outName.find("_")
    if iUnder > 0:
        outName = outName[iUnder+1:]
    # Trim out the first scan number
    iUnder = outName.find("_")
    if iUnder > 0:
        outName = outName[iUnder+1:]
    # Trim out the sampler number
    iUnder = outName.rfind("_")
    if iUnder > 0:
        outName = outName[0:iUnder]
    #Now prepend the objects
    lObjectName = len(objectName)
    if lObjectName > 40:
        objectName = objectName[:40]
    outimage = objectName+'_'+outName+'_dbcon.fits'
    if os.path.exists(outimage):
        os.remove(outimage)
        print 'Removed existing file to make room for new one :',outimage
    
    fittp.dataout='PWD:'+outimage
    fittp.go()

    if keeptempfiles != '1':
        [os.unlink(xx) for xx in sdf_files]
        if os.path.isdir('summary'):
            [os.unlink('summary/'+xx) for xx in os.listdir('summary')]
            os.rmdir('summary')

# 需要导入模块: from AIPSTask import AIPSTask [as 别名]
# 或者: from AIPSTask.AIPSTask import outcl [as 别名]
#make a unit image for later use
comb.outdisk=mydisk
comb.indisk=mydisk
comb.inname=AIPSCat()[mydisk][-1].name
comb.inclass=AIPSCat()[mydisk][-1].klass
comb.inseq=AIPSCat()[mydisk][-1].seq
comb.in2disk=mydisk
comb.in2name=AIPSCat()[mydisk][-1].name
comb.in2class=AIPSCat()[mydisk][-1].klass
comb.in2seq=AIPSCat()[mydisk][-1].seq
comb.aparm[1]=1.
comb.aparm[2]=-1.
comb.aparm[3]=1.
comb.opcode='SUM'
comb.outcl='ONE'
comb.go()

#make a N(2,2) image
comb.aparm[1] = cLightKmS*(6./4.)*1.55e14/(restFreq22*restFreq22*1.E-9)
comb.aparm[2] = 1.E-10
comb.aparm[3] = 0
comb.aparm[4] = 0
comb.outcl='N(2,2)'
comb.opcode='SUM'
comb.go()

#make a N(1,1) image
comb.aparm[1] = cLightKmS*(2./1.)*1.55e14/(restFreq11*restFreq11*1.E-9)
comb.inclass='11'
comb.in2class='11'