def wgains(lpars):
'''
Write the gains into a new file.
'''
mirout, mirerr = lib.mirrun(task='uvcat', vis=lpars.vis, out='.temp')
#tout = uvcat.snarf()
o, e = lib.shrun('rm -r '+lpars.vis)
o, e = lib.shrun('mv .temp '+lpars.vis)
def selfcal_multi(settings):
'''
Main module that controls the multi-threaded selfcal.
selfcal_main(settings), where settings is grabbed from a config file through:
settings = apercal.lib.settings('someconfigfile.txt')
'''
logger = logging.getLogger('selfcal_multi')
logger.setLevel(logging.DEBUG)
# NOTE: The script parameters, spars, are grabbed here and used throughout the script.
spars = settings.get('selfcal_multi')
nt = 0
if lib.str2bool(spars.imall)!=False:
print "Making Wide Band Image..."
spars.line=""
#NOTE: Increase the CLEAN depth by the nominal increase in sensitivity.
spars.dc = float(spars.dc) * pl.sqrt(8.)
#NOTE: Increase the BW
spars.bw = float(spars.bw) * 8.
for i in range(0,int(spars.nloops)):
print "Loop=", str(i)
iteri(spars, i=i+1)
image_cycle(settings, spars, j=i+1)
print "Completed Wide Band Image"
sys.exit(0)
spars.nloops = int(spars.nloops)
THREADS = []
for v in spars.vis.split(','):
# NOTE: Here we make the new directory and move to it.
if lib.str2bool(spars.cleanup)!=False:
o, e = lib.shrun("rm -r "+v+"/gains")
o, e = lib.shrun("rm -r "+v+"_*")
logger.info("Assigned Thread "+str(nt)+" for "+v)
nt+=1
# NOTE: Now mpars only exists in this for loop, and is reserved for the
# farming of the threads. It is a copy of spars
#mpars = spars
#mpars.vis = v
#mpars.tag = v
THREADS.append(selfcal_main(v, settings))
time.sleep(1)
for T in THREADS:
logger.info("Starting "+str(T))
T.start()
for T in THREADS:
time.sleep(1)
logger.info("Joining "+ str(T))
T.join()
logger.info("DONE.")
def invertr(settings, spars):
'''
output = invertr(settings, spars)
Runs MIRIAD's invert on spars.vis, using settings.get('image'). Returns the output from
mirrun.
'''
vis = spars.vis
lpars = settings.get('image')
#NOTE: Clean up
o, e = lib.shrun('rm -r '+spars.map)
o, e = lib.shrun('rm -r '+spars.beam)
mirout, mirerr = lib.mirrun(task='invert', vis=vis, select=lpars.select,
line=lpars.line, map = spars.map, beam=spars.beam, options=lpars.options,
slop=lpars.slop, stokes=lpars.stokes, imsize=lpars.imsize, cell=lpars.cell,
fwhm=lpars.fwhm, robust=lpars.robust)
lib.exceptioner(mirout, mirerr)
return mirout
def restor(lpars, mode='clean'):
'''
output = restor(params, mode='clean')
Uses the MIRIAD task restor to restor a model image, creating either an image or a
residual.
'''
if mode.upper()!="CLEAN":
# Make the residual
# Cleanup
o, e = lib.shrun('rm -r '+lpars.residual)
mirout, mirerr = lib.mirrun(task='restor', beam=lpars.beam, map=lpars.map,
model=lpars.model, out=lpars.residual, mode='residual')
else:
# Make the image
# Cleanup
o, e = lib.shrun('rm -r '+lpars.image)
mirout, mirerr = lib.mirrun(task='restor', beam=lpars.beam, map=lpars.map,
model=lpars.model, out=lpars.image, mode=mode)
return mirout
def make_mask(image, cutoff, mask):
'''
output = make_mask(image, cutoff, mask)
Uses the MIRIAD task MATHS to make a threshold mask. The input <image> is thresholded with
cutoff, and a <mask> is created.
'''
# Cleanup
o, e = lib.shrun('rm -r '+mask)
# NOTE: MATHS is stupid and doesn't know how to follow paths. So we have to make a symbolic
# link to the images.
lib.shrun('ln -s '+image)
mirout, mirerr = lib.mirrun(task='maths', exp=os.path.split(image)[1],
mask=os.path.split(image)[1]+".gt."+str(cutoff),
out=mask)
lib.exceptioner(mirout, mirerr)
# Remove the symbolic link
lib.shrun('rm '+os.path.split(image)[-1])
# Climb up back to the original path
return mirout
def clean(lpars):
'''
output = clean(lpars)
Runs MIRIAD's clean, using standard settings.
'''
#NOTE: Cleanup
o, e = lib.shrun("rm -r "+lpars.model)
if lpars.mask!=None:
#NOTE: Use mask if provided.
mirout, mirerr = lib.mirrun(task='clean', map=lpars.map, beam=lpars.beam,
out=lpars.model, cutoff=lpars.cutoff,
region="'mask("+lpars.mask+")'", niters=100000)
lib.exceptioner(mirout, mirerr)
else:
#NOTE: Do a 'light' clean if no mask provided.
mirout, mirerr = lib.mirrun(task='clean', map=lpars.map, beam=lpars.beam,
out=lpars.model, cutoff=lpars.cutoff, niters=1000)
lib.exceptioner(mirout, mirerr)
return mirout
def make_nvss_lsm(params): #TODO: NVSS needs to be integrated here!!!! c = "python mk-nvss-lsm.py -i "+params.map+" -o "+params.lsm o, e = lib.shrun(c) tout = selfcal(params)