# RA
sdgrd.aparm[1] = 19
sdgrd.aparm[2] = 23
sdgrd.aparm[3] = 40
# DEC
sdgrd.aparm[4] = 14
sdgrd.aparm[5] = 31
sdgrd.aparm[6] = 30
# Imsize
sdgrd.imsize[1] = 100
sdgrd.imsize[2] = 110
sdgrd.go()
from Wizardry.AIPSData import AIPSImage as WizAIPSImage
image = WizAIPSImage(AIPSCat()[mydisk][-1].name, \
AIPSCat()[mydisk][-1].klass, \
mydisk, AIPSCat()[mydisk][-1].seq)
image.header.niter = 1 # Allow down stream IMSTATs to sum correctly
image.header.update()
image.update()
## 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
outimage = os.path.splitext(myfiles[0])[0]+'_cube.fits'
if os.path.exists(outimage):
os.remove(outimage)
print 'Removed existing file to make room for new one :',outimage
sdgrd.imsize[2] = imySize
## The above lines set the default image parameters
## Below, override imaging center coordinate
# RA
#sdgrd.aparm[1] = 04 #hours
#sdgrd.aparm[2] = 41 #minutes
#sdgrd.aparm[3] = 15.0 #seconds
# DEC
#sdgrd.aparm[4] = 25 #degrees
#sdgrd.aparm[5] = 50 #arcmins
#sdgrd.aparm[6] = 00 #arcseconds
sdgrd.go()
from Wizardry.AIPSData import AIPSImage as WizAIPSImage
image = WizAIPSImage(AIPSCat()[mydisk][-1].name, \
AIPSCat()[mydisk][-1].klass, \
mydisk, AIPSCat()[mydisk][-1].seq)
image.header.niter = 1 # Allow down stream IMSTATs to sum correctly
#print image.header
bmaj = image.header.bmaj
#assume no smoothing in convolving function (sdgrd.xtype = -16)
newBmaj = bmaj
if sdgrd.xtype == -12:
convolveMaj = sdgrd.xparm[2] / 3600. # convolving function FWHM in degrees
#Convolved image resolution adds in quadrature
newBmaj = math.sqrt((bmaj * bmaj) + (convolveMaj * convolveMaj))
print 'Gaussian Convolving function:'
print bmaj * 3600., convolveMaj * 3600., '->', newBmaj * 3600.
if sdgrd.xtype == -16:
#Convolved image resolution adds in quadrature
sdgrd.imsize[2] = imySize
## The above lines set the default image parameters
## Below, override imaging center coordinate
# RA
#sdgrd.aparm[1] = 04 #hours
#sdgrd.aparm[2] = 41 #minutes
#sdgrd.aparm[3] = 15.0 #seconds
# DEC
#sdgrd.aparm[4] = 25 #degrees
#sdgrd.aparm[5] = 50 #arcmins
#sdgrd.aparm[6] = 00 #arcseconds
sdgrd.go()
from Wizardry.AIPSData import AIPSImage as WizAIPSImage
image = WizAIPSImage(AIPSCat()[mydisk][-1].name, \
AIPSCat()[mydisk][-1].klass, \
mydisk, AIPSCat()[mydisk][-1].seq)
image.header.niter = 1 # Allow down stream IMSTATs to sum correctly
#print image.header
bmaj = image.header.bmaj
#assume no smoothing in convolving function (sdgrd.xtype = -16)
newBmaj = bmaj
if sdgrd.xtype == -12:
convolveMaj = sdgrd.xparm[2]/3600. # convolving function FWHM in degrees
#Convolved image resolution adds in quadrature
newBmaj = math.sqrt( (bmaj*bmaj) + (convolveMaj*convolveMaj))
print 'Gaussian Convolving function:'
print bmaj*3600., convolveMaj*3600., '->',newBmaj*3600.
if sdgrd.xtype == -16:
#Convolved image resolution adds in quadrature
def dbcon(sys):
argc = len(sys.argv)
if argc < 3:
print ''
print 'dbcon: Combine all observations into a single dish fits file'
print 'usage: doImage dbcon.py <aipsNumber> <feeds>'
print ' <average> <channels> <display> <rmsflag> <verbose> <baseline-subtract>'
print ' <keeptempfiles> <spectra File 1> [<spectra File n>]'
print 'where <aipsNumber> Your *PIPELINE* AIPS number (should always be the same)'
print ' <spectra File 1> One or more calibrated spectra files (*.fits)'
print ' Combined spectra are placed in catalog slot 1'
print ''
quit()
feeds = sys.argv[2].split(',')
average = sys.argv[3]
channels = sys.argv[4]
display_idlToSdfits = sys.argv[5]
idlToSdfits_rms_flag = sys.argv[6]
verbose = sys.argv[7]
idlToSdfits_baseline_subtract = sys.argv[8]
keeptempfiles = sys.argv[9]
imfiles = sys.argv[10:]
if not imfiles:
return
sdf_files = []
for feed in feeds:
files = []
for xx in imfiles:
if 'feed{num}'.format(num=feed) in xx:
files.append(xx)
if not files:
continue
sdf = run_idlToSdfits(files, average, channels, display_idlToSdfits,
idlToSdfits_rms_flag, verbose, idlToSdfits_baseline_subtract)
sdf_files.append(sdf)
AIPS.userno=int(sys.argv[1]) # retrieve AIPS pipeline user number
mydisk=2 # choose a good default work disk
baddisk=1 # list a disk to avoid (0==no avoidance)
AIPSCat().zap() # empty the catalog
uvlod=AIPSTask('uvlod') # Create structures for AIPS tasks
uvlod.outdisk=mydisk # write all input data to a select disk
fittp=AIPSTask('fittp')
dbcon=AIPSTask('dbcon')
uvsrt=AIPSTask('uvsrt')
mandl=AIPSTask('mandl')
# Need a temporary small file to reserve slot 1
mandl.outdisk = mydisk
# create an image that will be deleted at end
mandl.go()
#
kount = 0 # init count of similar input files
for thisFile in sdf_files: # input all AIPS single dish FITS files
uvlod.datain='PWD:'+thisFile
print uvlod.datain
uvlod.outdisk=mydisk
uvlod.go()
spectra = AIPSUVData(AIPSCat()[mydisk][-1].name, AIPSCat()[mydisk][-1].klass, mydisk, AIPSCat()[mydisk][-1].seq)
nuRef = spectra.header.crval[2]
if kount == 0:
firstNu = nuRef
if ((firstNu - nuRef) < -1.E5) or ((firstNu - nuRef) > 1.E5):
print 'Frequencies differ: ',nuRef,' != ',firstNu
spectra.zap()
else:
kount = kount+1
spectra = AIPSUVData(AIPSCat()[mydisk][-1].name, AIPSCat()[mydisk][-1].klass, mydisk, AIPSCat()[mydisk][-1].seq)
# prepare to accumulate source names
allObjects = ["","","","","","","","","","","","","","","","","","","",
"","","","","","","","","","","","","","","","","","",""]
allObjects[0] = spectra.header.object
nObjects = 1
if kount > 1: # if more than 1 file DBCON them
# always do first 2
dbcon.indisk=mydisk
dbcon.outdisk=mydisk
dbcon.in2disk=mydisk
dbcon.inname = AIPSCat()[mydisk][1].name
dbcon.inclass = AIPSCat()[mydisk][1].klass
dbcon.inseq = AIPSCat()[mydisk][1].seq
dbcon.in2name = AIPSCat()[mydisk][2].name
dbcon.in2class = AIPSCat()[mydisk][2].klass
dbcon.in2seq = AIPSCat()[mydisk][2].seq
print 'combining 1: ', dbcon.inname, dbcon.inclass, dbcon.inseq
print 'combining 2: ', dbcon.in2name, dbcon.in2class, dbcon.in2seq
dbcon.reweight[1] = 0
dbcon.reweight[2] = 0
dbcon.go()
# and keep adding in one
for i in range(2,kount):
# end of cat is always most recent dbcon result
dbcon.inname = AIPSCat()[mydisk][-1].name
dbcon.inclass = 'DBCON'
dbcon.inseq = i - 1
dbcon.in2name = AIPSCat()[mydisk][i+1].name
dbcon.in2class = AIPSCat()[mydisk][i+1].klass
dbcon.in2seq = AIPSCat()[mydisk][i+1].seq
print 'combining 1: ', dbcon.inname, dbcon.inclass, dbcon.inseq
print 'combining 2: ', dbcon.in2name, dbcon.in2class, dbcon.in2seq
#prepare to zap revious dbconned file
dbcon.go()
# now zap previous big input file
spectra = AIPSUVData(AIPSCat()[mydisk][-1].name, 'DBCON',mydisk, i-1)
spectra.zap()
# remove input files, must remove them in reverse to presurve catalog order
for i in range(1,kount+1):
j = kount+1-i
aname = AIPSCat()[mydisk][j].name
aclass = AIPSCat()[mydisk][j].klass
aseq = AIPSCat()[mydisk][j].seq
# print i, j, aname, aclass, aseq
spectra = AIPSUVData( aname, aclass, mydisk, aseq)
notFound = True
# check if this object is already in the list
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')