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doDDE_reimage_wsclean.py
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doDDE_reimage_wsclean.py
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import matplotlib
#matplotlib.use('GTK')
import numpy
import os
import sys
from scipy import interpolate
import time
#import subprocess
from subprocess import Popen, PIPE, STDOUT
import pyrap.tables as pt
import pyrap.images
import pwd
import logging
import blank
from coordinates_mode import *
from facet_utilities import run, bg, angsep, dec_to_str, ra_to_str
from numpy import pi
import lofar.parmdb
# check high-DR
# check old selfcalv15
# check point source model
# TO DO
# - problem with e1 mask (sources not in clean mask)
# - problem with s3, diffuse source not in clean mask causes neg. bowl --> FIXED
# - check for mask gaps --> DONE
# - fit for clock in selfcal --> DONE
# - clean component overlap check -> avoid by giving up patches
# - reset phases to zero in selfcal part --> DONE
# - gain normalization --> DONE
# - HIGH-DYNAMIC RANGE (need to adjust merger/join parmdb, solution smoohting as well)
# - move m10 direction --> DONE
# - make normal template names files --> DONE
# - remove source list loading to prevent segfaults --> DONE
# - run the addback sources in seperate python script to avoid frequent Bus Errors DONE
# - run the addback sources FIELD in seperate python script to avoid frequent Bus Errors DONE
# - make sure parrallel FFT does not run out of memory (limit max. processes)/facets? DONE
# - automatic w-planes computation in imaging
# - how to deal with outlier sources low-freqs? # peel them first using low-freq bands only?
# - combine images into big image --> DONE
# - make fake avg pb images from mask to work with msss mosaic --> DONE
# - convolve images all to the same resolution (use casapy for that, easy to do)
# - What about second imaging and calibration cycle?
# - 1. ADD back skymodel using "master solutions", then CORRECT using "master solutions"
# - 2. image that again using the same setting
# - 3. redo the subtract (will be slightly better....but solutions remained the same, just better noise) or just proceed to the next field?
# - how to deal with Toothbrush, how to subtract it from the data properly (make low-res images for that?)
# - memory control in full resolution subtract step --> DONE
# v6
# - added SCRIPTPATH - makes it easier to switch between cep and para
# - added check of return values on some system calls (esp NDPPP which returns 0 on success)
# v7
# increase niter (for deeper clean)
# change scheme 2 to 3
#2. your new scheme
#- correct with solutions
#- phaseshift to updated position +avg
#- facet imaging
#3. proposed scheme
#- correct with solutions
#- phaseshift to selfcal center + avg
#- phaseshift to updated position (from selfcal center)
#- facet imaging
# v8
# go back... to scheme 2
# v9
# for difficult to low snr facet, but not so far from another facet try just using the other facet solutions
def find_newsize(mask):
img = pyrap.images.image(mask)
pixels = numpy.copy(img.getdata())
sh = numpy.shape(pixels)[3:4]
newsize = numpy.copy(sh[0])
sh = sh[0]
#print mask, newsize
trysizes = numpy.copy(sorted([6400,6144,5600,5400,5184,5000,4800,4608,4320,4096,3840,3600,3200,3072,2880,2560,2304,2048, 1600, 1536, 1200, 1024, 800, 512]))
trysizes1 = numpy.copy(trysizes[::-1]) # reverse sorted
idx = numpy.where(pixels != 0)
idx_x = idx[2]
idx_y = idx[3]
span_x1 = 2*abs(max(idx_x) - sh/2)
span_x2 = 2*abs(sh/2 - min(idx_x))
span_y1 = 2*abs(max(idx_y)- sh/2)
span_y2 = 2*abs(sh/2 - min(idx_y))
max_span = max(span_x1, span_y1, span_x2, span_y2)
this_size = trysizes1[numpy.sum(trysizes1>= max_span)-1]
newsize = this_size
return newsize
def runbbs(mslist, skymodel, parset, parmdb, replacesource):
#NOTE WORK FROM MODEL_DATA (contains correct phase data from 10SB calibration)
for ms in mslist:
log = ms + '.bbslog'
if replacesource:
cmd = 'calibrate-stand-alone --replace-sourcedb --parmdb-name ' + parmdb + ' ' + ms + ' ' + parset + ' ' + skymodel + '>' + log + ' 2>&1 &'
else:
cmd = 'calibrate-stand-alone --parmdb-name ' + parmdb + ' ' + ms + ' ' + parset + ' ' + skymodel + '>' + log + ' 2>&1 &'
print cmd
os.system(cmd)
time.sleep(10)
done = 0
while(done < len(mslist)):
done = 0
for ms in mslist:
cmd = "grep 'bbs-reducer terminated successfully.' " + ms + ".bbslog"
output=Popen(cmd, shell=True, stdout=PIPE).communicate()[0]
if 'INFO' in output:
done = done + 1
print ms, 'is done'
time.sleep(5)
return
def runbbs16(mslist, skymodel, parset, parmdb, replacesource):
#NOTE WORK FROM MODEL_DATA (contains correct phase data from 10SB calibration)
mslist1 = mslist[0:15]
mslist2 = mslist[15:len(mslist)]
# PART1
for ms in mslist1:
log = ms + '.bbslog'
if replacesource:
cmd = 'calibrate-stand-alone --replace-sourcedb --parmdb-name ' + parmdb + ' ' + ms + ' ' + parset + ' ' + skymodel + '>' + log + ' 2>&1 &'
else:
cmd = 'calibrate-stand-alone --parmdb-name ' + parmdb + ' ' + ms + ' ' + parset + ' ' + skymodel + '>' + log + ' 2>&1 &'
print cmd
os.system(cmd)
time.sleep(10)
done = 0
while(done < len(mslist1)):
done = 0
for ms in mslist1:
cmd = "grep 'bbs-reducer terminated successfully.' " + ms + ".bbslog"
output=Popen(cmd, shell=True, stdout=PIPE).communicate()[0]
if 'INFO' in output:
done = done + 1
print ms, 'is done'
time.sleep(5)
# PART2
for ms in mslist2:
log = ms + '.bbslog'
if replacesource:
cmd = 'calibrate-stand-alone --replace-sourcedb --parmdb-name ' + parmdb + ' ' + ms + ' ' + parset + ' ' + skymodel + '>' + log + ' 2>&1 &'
else:
cmd = 'calibrate-stand-alone --parmdb-name ' + parmdb + ' ' + ms + ' ' + parset + ' ' + skymodel + '>' + log + ' 2>&1 &'
print cmd
os.system(cmd)
time.sleep(10)
done = 0
while(done < len(mslist2)):
done = 0
for ms in mslist2:
cmd = "grep 'bbs-reducer terminated successfully.' " + ms + ".bbslog"
output=Popen(cmd, shell=True, stdout=PIPE).communicate()[0]
if 'INFO' in output:
done = done + 1
print ms, 'is done'
time.sleep(5)
return
def create_subtract_parset_field_outlier(outputcolumn, TEC, clock):
bbs_parset = 'sub.parset'
os.system('rm -f ' + bbs_parset)
f=open(bbs_parset, 'w')
chunksize = 100
f.write('Strategy.InputColumn = MODEL_DATA\n')
f.write('Strategy.ChunkSize = %s\n' % chunksize)
f.write('Strategy.UseSolver = F\n')
f.write('Strategy.Steps = [subtract]\n\n\n')
f.write('Step.subtract.Model.Sources = []\n')
f.write('Step.subtract.Model.Cache.Enable = T\n')
f.write('Step.subtract.Model.Phasors.Enable = F\n')
f.write('Step.subtract.Model.DirectionalGain.Enable = F\n')
f.write('Step.subtract.Model.Gain.Enable = T\n')
f.write('Step.subtract.Model.Rotation.Enable = F\n')
f.write('Step.subtract.Model.CommonScalarPhase.Enable = T\n')
if TEC == "True":
f.write('Step.subtract.Model.TEC.Enable = T\n')
if clock == "True":
f.write('Step.subtract.Model.Clock.Enable = T\n')
f.write('Step.subtract.Model.CommonRotation.Enable = F\n')
f.write('Step.subtract.Operation = SUBTRACT\n')
f.write('Step.subtract.Model.Beam.Enable = F\n')
f.write('Step.subtract.Output.WriteCovariance = F\n')
f.write('Step.subtract.Output.Column = %s\n' % outputcolumn)
f.close()
return bbs_parset
def runbbs_diffskymodel_addback(mslist, parmdb, replacesource, direction, imsize, output_template_im):
for ms in mslist:
log = ms + '.bbslog'
#set skymodel # ~weeren does not work in numpy.load
skymodel = ms.split('.')[0] + '.skymodel'
# find sources to add back, make parset
#callist, callistarraysources = cal_return_slist(output_template_im +'.masktmp',skymodel, direction, imsize)
cmd = 'python '+SCRIPTPATH+'/cal_return_slist.py '+ output_template_im+' '+skymodel +' "'+str(direction) +'" ' + str(imsize)
output = Popen(cmd, shell=True, stdout=PIPE).communicate()[0]
callist = output.strip()
callistarraysources = callist.split(',')
print 'Adding back for calibration:', callist
parset = create_add_parset_ms(callist, ms)
if replacesource:
cmd = 'calibrate-stand-alone --replace-sourcedb --parmdb-name ' + parmdb + ' ' + ms + ' ' + parset + ' ' + skymodel + '>' + log + ' 2>&1 &'
else:
cmd = 'calibrate-stand-alone --parmdb-name ' + parmdb + ' ' + ms + ' ' + parset + ' ' + skymodel + '>' + log + ' 2>&1 &'
print cmd
os.system(cmd)
time.sleep(10) # otherwise add.parset is deleted (takes time for BBS to start up)
time.sleep(10)
done = 0
while(done < len(mslist)):
done = 0
for ms in mslist:
cmd = "grep 'bbs-reducer terminated successfully.' " + ms + ".bbslog"
output=Popen(cmd, shell=True, stdout=PIPE).communicate()[0]
if 'INFO' in output:
done = done + 1
print ms, 'is done'
time.sleep(5)
return
def runbbs_diffskymodel_addback16(mslist, parmdb, replacesource, direction, imsize, output_template_im):
mslist1 = mslist[0:16]
mslist2 = mslist[16:len(mslist)]
#part1
for ms in mslist1:
log = ms + '.bbslog'
#set skymodel # ~weeren does not work in numpy.load
skymodel = ms.split('.')[0] + '.skymodel'
# find sources to add back, make parset
#callist, callistarraysources = cal_return_slist(output_template_im +'.masktmp',skymodel, direction, imsize)
cmd = 'python '+SCRIPTPATH+'/cal_return_slist.py '+ output_template_im+' '+skymodel +' "'+str(direction) +'" ' + str(imsize)
output = Popen(cmd, shell=True, stdout=PIPE).communicate()[0]
callist = output.strip()
callistarraysources = callist.split(',')
print 'Adding back for calibration:', callist
parset = create_add_parset_ms(callist, ms)
if replacesource:
cmd = 'calibrate-stand-alone --replace-sourcedb --parmdb-name ' + parmdb + ' ' + ms + ' ' + parset + ' ' + skymodel + '>' + log + ' 2>&1 &'
else:
cmd = 'calibrate-stand-alone --parmdb-name ' + parmdb + ' ' + ms + ' ' + parset + ' ' + skymodel + '>' + log + ' 2>&1 &'
print cmd
os.system(cmd)
time.sleep(10) # otherwise add.parset is deleted (takes time for BBS to start up)
time.sleep(10)
done = 0
while(done < len(mslist1)):
done = 0
for ms in mslist1:
cmd = "grep 'bbs-reducer terminated successfully.' " + ms + ".bbslog"
output=Popen(cmd, shell=True, stdout=PIPE).communicate()[0]
if 'INFO' in output:
done = done + 1
print ms, 'is done'
time.sleep(5)
#part2
for ms in mslist2:
log = ms + '.bbslog'
#set skymodel # ~weeren does not work in numpy.load
skymodel = ms.split('.')[0] + '.skymodel'
# find sources to add back, make parset
#callist, callistarraysources = cal_return_slist(output_template_im +'.masktmp',skymodel, direction, imsize)
cmd = 'python '+SCRIPTPATH+'/cal_return_slist.py '+ output_template_im+' '+skymodel +' "'+str(direction) +'" ' + str(imsize)
output = Popen(cmd, shell=True, stdout=PIPE).communicate()[0]
callist = output.strip()
callistarraysources = callist.split(',')
print 'Adding back for calibration:', callist
parset = create_add_parset_ms(callist, ms)
if replacesource:
cmd = 'calibrate-stand-alone --replace-sourcedb --parmdb-name ' + parmdb + ' ' + ms + ' ' + parset + ' ' + skymodel + '>' + log + ' 2>&1 &'
else:
cmd = 'calibrate-stand-alone --parmdb-name ' + parmdb + ' ' + ms + ' ' + parset + ' ' + skymodel + '>' + log + ' 2>&1 &'
print cmd
os.system(cmd)
time.sleep(10) # otherwise add.parset is deleted (takes time for BBS to start up)
time.sleep(10)
done = 0
while(done < len(mslist2)):
done = 0
for ms in mslist2:
cmd = "grep 'bbs-reducer terminated successfully.' " + ms + ".bbslog"
output=Popen(cmd, shell=True, stdout=PIPE).communicate()[0]
if 'INFO' in output:
done = done + 1
print ms, 'is done'
time.sleep(5)
return
def runbbs_diffskymodel_addbackfield(mslist, parmdb, replacesource, direction, imsize, output_template_im):
for ms in mslist:
log = ms + '.bbslog'
#set skymodel
skymodel = ms.split('.')[0] + '.skymodel'
# find peeling sources (from previous step)
#callist, callistarraysources = cal_return_slist(output_template_im +'.masktmp',skymodel, direction, imsize)
cmd = 'python '+SCRIPTPATH+'/cal_return_slist.py '+ output_template_im+' '+skymodel +' "'+str(direction) +'" ' + str(imsize)
output = Popen(cmd, shell=True, stdout=PIPE).communicate()[0]
callist = output.strip()
callistarraysources = callist.split(',')
print 'Add field back step 1'
# return the source list from the source to be added back sourrinding the peeling source and which fall within the mask boundaries
# put in MODEL_DATA
#addback_sourcelist = return_slist(output_template_im +'.masktmp', skymodel, callistarraysources)
cmd = 'python '+SCRIPTPATH+'/return_slist.py '+ output_template_im+' '+skymodel +' "'+str(callist)+'"'
output = Popen(cmd, shell=True, stdout=PIPE).communicate()[0]
addback_sourcelist = output.strip()
print 'Field source added back are: ', addback_sourcelist
if len(addback_sourcelist) != 0: # otherwise do not have to add
parset = create_add_parset_field_ms(addback_sourcelist, ms)
if replacesource:
cmd = 'calibrate-stand-alone --replace-sourcedb --parmdb-name ' + parmdb + ' ' + ms + ' ' + parset + ' ' + skymodel + '>' + log + ' 2>&1 &'
else:
cmd = 'calibrate-stand-alone --parmdb-name ' + parmdb + ' ' + ms + ' ' + parset + ' ' + skymodel + '>' + log + ' 2>&1 &'
print cmd
os.system(cmd)
else:
os.system("taql 'update " + ms + " set MODEL_DATA=ADDED_DATA_SOURCE'") # in case no sources are put back
time.sleep(10) # otherwise addfield.parset is deleted (takes time for BBS to start up)
time.sleep(10)
done = 0
while(done < len(mslist)):
done = 0
for ms in mslist:
cmd = "grep 'bbs-reducer terminated successfully.' " + ms + ".bbslog"
output=Popen(cmd, shell=True, stdout=PIPE).communicate()[0]
if 'INFO' in output:
done = done + 1
print ms, 'is done'
time.sleep(5)
return
def runbbs_2(mslist, msparmdb, skymodel, parset, parmdb):
for ms_id, ms in enumerate(mslist):
log = ms + '.bbslog'
cmd = 'calibrate-stand-alone --parmdb ' + msparmdb[ms_id]+'/'+parmdb + ' ' + ms + ' ' + parset + ' ' + skymodel + '>' + log + ' 2>&1 &'
print cmd
os.system(cmd)
time.sleep(10)
done = 0
while(done < len(mslist)):
done = 0
for ms in mslist:
cmd = "grep 'bbs-reducer terminated successfully.' " + ms + ".bbslog"
output=Popen(cmd, shell=True, stdout=PIPE).communicate()[0]
if 'INFO' in output:
done = done + 1
print ms, 'is done'
time.sleep(5)
return
def create_phaseshift_parset_full(msin, msout, direction, column):
ndppp_parset = 'ndppp_phaseshiftfull.parset'
os.system('rm -f ' + ndppp_parset)
f=open(ndppp_parset, 'w')
f.write('msin ="%s"\n' % msin)
f.write('msin.datacolumn = "%s"\n' % column)
f.write('msin.autoweight = false\n')
f.write('msout ="%s"\n' % msout)
f.write('msout.writefullresflag=False\n')
f.write('steps = [shift]\n')
f.write('shift.type = phaseshift\n')
f.write('shift.phasecenter = [%s]\n' % direction)
f.close()
return ndppp_parset
def create_phaseshift_parset(msin, msout, source, direction):
ndppp_parset = (msin.split('.')[0]) +'_ndppp_avgphaseshift.parset'
os.system('rm -f ' + ndppp_parset)
f=open(ndppp_parset, 'w')
f.write('msin ="%s"\n' % msin)
f.write('msin.datacolumn = ADDED_DATA_SOURCE\n')
f.write('msin.autoweight = false\n')
f.write('msout ="%s"\n' % msout)
f.write('msout.writefullresflag=False\n')
f.write('steps = [shift,avg1]\n')
f.write('shift.type = phaseshift\n')
f.write('shift.phasecenter = [%s]\n' % direction)
f.write('avg1.type = squash\n')
# just to test
f.write('avg1.freqstep = 20\n')
f.write('avg1.timestep = 1\n')
f.close()
return ndppp_parset
def create_phaseshift_parset_formasks(msin, msout, source, direction):
ndppp_parset = (msin.split('.')[0]) +'_ndppp_avgphaseshift.parset'
os.system('rm -f ' + ndppp_parset)
f=open(ndppp_parset, 'w')
f.write('msin ="%s"\n' % msin)
f.write('msin.datacolumn = DATA\n')
f.write('msin.autoweight = false\n')
f.write('msout ="%s"\n' % msout)
f.write('msout.writefullresflag=False\n')
f.write('steps = [shift,avg1]\n')
f.write('shift.type = phaseshift\n')
f.write('shift.phasecenter = [%s]\n' % direction)
f.write('avg1.type = squash\n')
f.write('avg1.freqstep = 20\n')
f.write('avg1.timestep = 1\n')
f.close()
return ndppp_parset
def create_phaseshift_parset_field(msin, msout, source, direction):
ndppp_parset = msin.split('.')[0] +'ndppp_avgphaseshift_field2.parset'
os.system('rm -f ' + ndppp_parset)
f=open(ndppp_parset, 'w')
f.write('msin ="%s"\n' % msin)
f.write('msin.datacolumn = DATA\n') # this is the second phaseshift
f.write('msin.autoweight = false\n')
f.write('msout ="%s"\n' % msout)
f.write('msout.writefullresflag=False\n')
f.write('steps = [shift]\n')
f.write('shift.type = phaseshift\n')
f.write('shift.phasecenter = [%s]\n' % direction)
f.close()
return ndppp_parset
def create_phaseshift_parset_field_avg(msin, msout, source, direction):
ndppp_parset = msin.split('.')[0] +'ndppp_avgphaseshift_field1.parset'
os.system('rm -f ' + ndppp_parset)
f=open(ndppp_parset, 'w')
f.write('msin ="%s"\n' % msin)
f.write('msin.datacolumn = CORRECTED_DATA\n')
f.write('msin.autoweight = false\n')
f.write('msout ="%s"\n' % msout)
f.write('msout.writefullresflag=False\n')
f.write('steps = [shift,avg1]\n')
f.write('shift.type = phaseshift\n')
f.write('shift.phasecenter = [%s]\n' % direction)
f.write('avg1.type = squash\n')
f.write('avg1.freqstep = 5\n')
f.write('avg1.timestep = 3\n')
f.close()
return ndppp_parset
def create_add_parset_ms(source, ms):
bbs_parset = ms + '_add.parset'
os.system('rm -f ' + bbs_parset)
f=open(bbs_parset, 'w')
f.write('Strategy.InputColumn = SUBTRACTED_DATA_ALL\n')
f.write('Strategy.ChunkSize = 200\n')
f.write('Strategy.UseSolver = F\n')
f.write('Strategy.Steps = [add]\n\n\n')
f.write('Step.add.Model.Sources = [%s]\n' % source)
f.write('Step.add.Model.Cache.Enable = T\n')
f.write('Step.add.Model.Phasors.Enable = F\n')
f.write('Step.add.Model.DirectionalGain.Enable = F\n')
f.write('Step.add.Model.Gain.Enable = T\n')
f.write('Step.add.Model.Rotation.Enable = F\n')
f.write('Step.add.Model.CommonScalarPhase.Enable = F\n')
f.write('Step.add.Model.CommonRotation.Enable = F\n')
f.write('Step.add.Operation = ADD\n')
f.write('Step.add.Model.Beam.Enable = F\n')
f.write('Step.add.Output.WriteCovariance = F\n')
f.write('Step.add.Output.Column = ADDED_DATA_SOURCE\n')
f.close()
return bbs_parset
#def create_add_parset_field(source):
#bbs_parset = 'addfield.parset'
#os.system('rm -f ' + bbs_parset)
#f=open(bbs_parset, 'w')
#f.write('Strategy.InputColumn = ADDED_DATA_SOURCE\n') # already contains peeling source
#f.write('Strategy.ChunkSize = 200\n')
#f.write('Strategy.UseSolver = F\n')
#f.write('Strategy.Steps = [add]\n\n\n')
#f.write('Step.add.Model.Sources = [%s]\n' % source)
#f.write('Step.add.Model.Cache.Enable = T\n')
#f.write('Step.add.Model.Phasors.Enable = F\n')
#f.write('Step.add.Model.DirectionalGain.Enable = F\n')
#f.write('Step.add.Model.Gain.Enable = T\n')
#f.write('Step.add.Model.Rotation.Enable = F\n')
#f.write('Step.add.Model.CommonScalarPhase.Enable = F\n')
#f.write('Step.add.Model.CommonRotation.Enable = F\n')
#f.write('Step.add.Operation = ADD\n')
#f.write('Step.add.Model.Beam.Enable = F\n')
#f.write('Step.add.Output.WriteCovariance = F\n')
#f.write('Step.add.Output.Column = MODEL_DATA\n') # use use to save disk space
#f.close()
#return bbs_parset
def create_add_parset_field_ms(source, ms):
bbs_parset = ms + '_addfield.parset'
os.system('rm -f ' + bbs_parset)
f=open(bbs_parset, 'w')
f.write('Strategy.InputColumn = ADDED_DATA_SOURCE\n') # already contains peeling source
f.write('Strategy.ChunkSize = 200\n')
f.write('Strategy.UseSolver = F\n')
f.write('Strategy.Steps = [add]\n\n\n')
f.write('Step.add.Model.Sources = [%s]\n' % source)
f.write('Step.add.Model.Cache.Enable = T\n')
f.write('Step.add.Model.Phasors.Enable = F\n')
f.write('Step.add.Model.DirectionalGain.Enable = F\n')
f.write('Step.add.Model.Gain.Enable = T\n')
f.write('Step.add.Model.Rotation.Enable = F\n')
f.write('Step.add.Model.CommonScalarPhase.Enable = F\n')
f.write('Step.add.Model.CommonRotation.Enable = F\n')
f.write('Step.add.Operation = ADD\n')
f.write('Step.add.Model.Beam.Enable = F\n')
f.write('Step.add.Output.WriteCovariance = F\n')
f.write('Step.add.Output.Column = MODEL_DATA\n') # use use to save disk space
f.close()
return bbs_parset
def create_subtract_parset(outputcolumn):
bbs_parset = 'sub.parset'
os.system('rm -f ' + bbs_parset)
f=open(bbs_parset, 'w')
f.write('Strategy.InputColumn = ADDED_DATA_SOURCE\n')
f.write('Strategy.ChunkSize = 100\n')
f.write('Strategy.UseSolver = F\n')
f.write('Strategy.Steps = [subtract]\n\n\n')
f.write('Step.subtract.Model.Sources = []\n')
f.write('Step.subtract.Model.Cache.Enable = T\n')
f.write('Step.subtract.Model.Phasors.Enable = F\n')
f.write('Step.subtract.Model.DirectionalGain.Enable = F\n')
f.write('Step.subtract.Model.Gain.Enable = T\n')
f.write('Step.subtract.Model.Rotation.Enable = F\n')
f.write('Step.subtract.Model.CommonScalarPhase.Enable = T\n')
f.write('Step.subtract.Model.CommonRotation.Enable = F\n')
f.write('Step.subtract.Operation = SUBTRACT\n')
f.write('Step.subtract.Model.Beam.Enable = F\n')
f.write('Step.subtract.Output.WriteCovariance = F\n')
f.write('Step.subtract.Output.Column = %s\n' % outputcolumn)
f.close()
return bbs_parset
def create_subtract_parset_field(outputcolumn, TEC, clock):
bbs_parset = 'sub.parset'
os.system('rm -f ' + bbs_parset)
f=open(bbs_parset, 'w')
chunksize = 175
f.write('Strategy.InputColumn = MODEL_DATA\n')
f.write('Strategy.ChunkSize = %s\n' % chunksize)
f.write('Strategy.UseSolver = F\n')
f.write('Strategy.Steps = [subtract]\n\n\n')
f.write('Step.subtract.Model.Sources = [@ADDED_DATA_SOURCE]\n')
f.write('Step.subtract.Model.Cache.Enable = T\n')
f.write('Step.subtract.Model.Phasors.Enable = F\n')
f.write('Step.subtract.Model.DirectionalGain.Enable = F\n')
f.write('Step.subtract.Model.Gain.Enable = T\n')
f.write('Step.subtract.Model.Rotation.Enable = F\n')
f.write('Step.subtract.Model.CommonScalarPhase.Enable = T\n')
if TEC == "True":
f.write('Step.subtract.Model.TEC.Enable = T\n')
if clock == "True":
f.write('Step.subtract.Model.Clock.Enable = T\n')
f.write('Step.subtract.Model.CommonRotation.Enable = F\n')
f.write('Step.subtract.Operation = SUBTRACT\n')
f.write('Step.subtract.Model.Beam.Enable = F\n')
f.write('Step.subtract.Output.WriteCovariance = F\n')
f.write('Step.subtract.Output.Column = %s\n' % outputcolumn)
f.close()
return bbs_parset
def create_add_parset_field(outputcolumn, TEC, clock):
bbs_parset = 'add.parset'
os.system('rm -f ' + bbs_parset)
f=open(bbs_parset, 'w')
chunksize = 175
f.write('Strategy.InputColumn = SUBTRACTED_DATA_ALL\n')
f.write('Strategy.ChunkSize = %s\n' % chunksize)
f.write('Strategy.UseSolver = F\n')
f.write('Strategy.Steps = [add]\n\n\n')
f.write('Step.add.Model.Sources = [@ADDED_DATA_SOURCE]\n') ## comes from ft_allbands, then copy over columns
f.write('Step.add.Model.Cache.Enable = T\n')
f.write('Step.add.Model.Phasors.Enable = F\n')
f.write('Step.add.Model.DirectionalGain.Enable = F\n')
f.write('Step.add.Model.Gain.Enable = T\n')
f.write('Step.add.Model.Rotation.Enable = F\n')
f.write('Step.add.Model.CommonScalarPhase.Enable = T\n')
if TEC == "True":
f.write('Step.add.Model.TEC.Enable = T\n')
if clock == "True":
f.write('Step.add.Model.Clock.Enable = T\n')
f.write('Step.add.Model.CommonRotation.Enable = F\n')
f.write('Step.add.Operation = ADD\n')
f.write('Step.add.Model.Beam.Enable = F\n')
f.write('Step.add.Output.WriteCovariance = F\n')
f.write('Step.add.Output.Column = %s\n' % outputcolumn)
f.close()
return bbs_parset
def join_parmdb(ms, parmdb_selfcal,parmdb_nondde, parmdb_template, parmdb_out, TEC, clock):
pdb_s = lofar.parmdb.parmdb(parmdb_selfcal)
pdb_p = lofar.parmdb.parmdb(parmdb_nondde)
pdb_t = lofar.parmdb.parmdb(parmdb_template)
parms_s = pdb_s.getValuesGrid("*")
parms_p = pdb_p.getValuesGrid("*")
parms_t = pdb_t.getValuesGrid("*")
keynames = parms_s.keys()
os.system('rm -rf ' + parmdb_out)
for key in keynames:
# copy over the selfcal solutions, can copy all (Real, Imag, CommonScalarPhase, TEC, clock)
parms_t[key]['values'][:,0] = numpy.copy(parms_s[key]['values'][:,0])
pol_list = ['0:0','1:1']
gain = 'Gain'
anttab = pt.table(ms + '/ANTENNA')
antenna_list = anttab.getcol('NAME')
anttab.close()
for pol in pol_list:
for antenna in antenna_list:
real1 = numpy.copy(parms_p[gain + ':' + pol + ':Real:'+ antenna]['values'][:, 0])
imag1 = numpy.copy(parms_p[gain + ':' + pol + ':Imag:'+ antenna]['values'][:, 0])
real2 = numpy.copy(parms_s[gain + ':' + pol + ':Real:'+ antenna]['values'][:, 0])
imag2 = numpy.copy(parms_s[gain + ':' + pol + ':Imag:'+ antenna]['values'][:, 0])
G1 = real1 + 1j*imag1
G2 = real2 + 1j*imag2
#G_new = G_nondde*G_selfcal
if TEC == "True":
Gnew = numpy.copy(G2)
else:
Gnew = numpy.copy(G1*G2)
parms_t[gain + ':' + pol + ':Imag:'+ antenna]['values'][:, 0] = numpy.copy(numpy.imag(Gnew))
parms_t[gain + ':' + pol + ':Real:'+ antenna]['values'][:, 0] = numpy.copy(numpy.real(Gnew))
#lofar.expion.parmdbmain.store_parms(parmdb_out, parms_t, create_new = True)
pdbnew = lofar.parmdb.parmdb(parmdb_out, create=True)
pdbnew.addValues(parms_t)
pdbnew.flush()
return
def normalize_parmdbs(mslist, parmdbname, parmdboutname):
amplist = []
# create antenna list
pol_list = ['0:0','1:1']
gain = 'Gain'
anttab = pt.table(mslist[0] + '/ANTENNA')
antenna_list = anttab.getcol('NAME')
anttab.close()
for ms in mslist:
pdb = lofar.parmdb.parmdb(ms + '/' + parmdbname)
parms = pdb.getValuesGrid("*")
for pol in pol_list:
for antenna in antenna_list:
real = numpy.copy(parms[gain + ':' + pol + ':Real:'+ antenna]['values'][:, 0])
imag = numpy.copy(parms[gain + ':' + pol + ':Imag:'+ antenna]['values'][:, 0])
amp = numpy.copy(numpy.sqrt(real**2 + imag**2))
amplist.append(amp)
norm_factor = 1./(numpy.mean(amplist))
print 'Normalizing gains: average gain value is', 1./norm_factor
print 'Multiplying gains by:', norm_factor
if (norm_factor > 1.5) or (norm_factor < (1./1.5)):
print 'Check normalization'
raise Exception('Wrong normalization')
# now normalize the parmdbs
for ms in mslist:
pdb = lofar.parmdb.parmdb(ms + '/' + parmdbname)
parms = pdb.getValuesGrid("*")
os.system('rm -rf ' + ms + '/' + parmdboutname)
for pol in pol_list:
for antenna in antenna_list:
real = numpy.copy(parms[gain + ':' + pol + ':Real:'+ antenna]['values'][:, 0])
imag = numpy.copy(parms[gain + ':' + pol + ':Imag:'+ antenna]['values'][:, 0])
parms[gain + ':' + pol + ':Imag:'+ antenna]['values'][:, 0] = numpy.copy(imag*norm_factor)
parms[gain + ':' + pol + ':Real:'+ antenna]['values'][:, 0] = numpy.copy(real*norm_factor)
pdbnew = lofar.parmdb.parmdb(ms + '/' +parmdboutname, create=True)
pdbnew.addValues(parms)
pdbnew.flush()
return
def return_slist(imagename, skymodel, ref_source):
fluxweight = False
data = load_bbs_skymodel(skymodel)
if len(numpy.shape(data)) == 1: # in this case not issue and we do not use Pythonlibs
patchest,ra_patches,dec_patches, flux_patches = compute_patch_center(data,fluxweight)
print 'option 1'
if len(numpy.shape(data)) == 2:
patchest,ra_patches,dec_patches, flux_patches = compute_patch_center_libsproblem(data,fluxweight)
print 'option 2'
# remove sources already in the field and convert to radians
if len(ref_source) == 1:
idx = numpy.where(patchest != ref_source)
ralist = pi*(ra_patches[idx])/180.
declist = pi*(dec_patches[idx])/180.
patches = patchest[idx]
else:
idx = numpy.asarray([numpy.where(patchest == y)[0][0] for y in ref_source])
accept_idx = sorted(set(range(patchest.size)) - set(idx))
ralist = pi*(ra_patches[accept_idx])/180.
declist = pi*(dec_patches[accept_idx])/180.
patches = patchest[accept_idx]
img = pyrap.images.image(imagename)
pixels = numpy.copy(img.getdata())
plist = []
sh = numpy.shape(pixels)[2:4]
for patch_id,patch in enumerate(patches):
coor = [0,1,declist[patch_id],ralist[patch_id]]
pix = img.topixel(coor)[2:4]
if (pix[0] >= 0) and (pix[0] <= (sh[0]-1)) and \
(pix[1] >= 0) and (pix[1] <= (sh[1]-1)):
if pixels[0,0,pix[0],pix[1]] != 0.0: # only include if withtin the clean mask (==1)
plist.append(patches[patch_id])
sourcess = ''
if len(plist) == 1:
sourcess = str(plist[0])
else:
for patch in plist:
sourcess = sourcess+patch+','
sourcess = sourcess[:-1]
return sourcess
def cal_return_slist(imagename,skymodel, direction, imsize):
factor = 0.8 # only add back in the center 80%
cut = 1.5*(imsize/2.)*factor/3600.
ra = direction.split(',')[0]
dec = direction.split(',')[1]
ra1 = float(ra.split('h')[0])*15.
ratmp = (ra.split('h')[1])
ra2 = float(ratmp.split('m')[0])*15./60
ra3 = float(ratmp.split('m')[1])*15./3600.
ref_ra= ra1 + ra2 +ra3
dec1 = float(dec.split('d')[0])
dectmp = (dec.split('d')[1])
dec2 = float(dectmp.split('m')[0])/60
dec3 = float(dectmp.split('m')[1])/3600.
ref_dec= dec1 + dec2 +dec3
fluxweight = False
data = load_bbs_skymodel(skymodel)
if len(numpy.shape(data)) == 1: # in this case not issue and we do not use Pythonlibs
patches,ra_patches,dec_patches, flux_patches = compute_patch_center(data,fluxweight)
print 'option 1'
if len(numpy.shape(data)) == 2:
patches,ra_patches,dec_patches, flux_patches = compute_patch_center_libsproblem(data,fluxweight)
print 'option 2'
ralist = pi*(ra_patches)/180.
declist = pi*(dec_patches)/180.
plist = []
print ref_ra, ref_dec
# load image to check if source within boundaries
img = pyrap.images.image(imagename)
pixels = numpy.copy(img.getdata())
plist = []
sh = numpy.shape(pixels)[2:4]
# CHECK TWO THINGS
# - sources fall within the image size
# - sources fall within the mask from the tessellation
for patch_id,patch in enumerate(patches):
coor = [0,1,declist[patch_id],ralist[patch_id]]
pix = img.topixel(coor)[2:4]
# compute radial distance to image center
dis = angsep(ra_patches[patch_id],dec_patches[patch_id], ref_ra, ref_dec)
if dis < cut: # ok sources is within image
# check if the sources is within the mask region (because mask can be smaller than image)
if (pix[0] >= 0) and (pix[0] <= (sh[0]-1)) and \
(pix[1] >= 0) and (pix[1] <= (sh[1]-1)):
if pixels[0,0,pix[0],pix[1]] != 0.0: # only include if withtin the clean mask (==1)
plist.append(patches[patch_id])
# make the string type source list
sourcess = ''
if len(plist) == 1:
sourcess = str(plist[0])
else:
for patch in plist:
sourcess = sourcess+patch+','
sourcess = sourcess[:-1]
return sourcess, plist
def make_image(mslist, cluster, callnumber, threshpix, threshisl, nterms, atrous_do, imsize, inputmask, mscale, region):
niter = numpy.int(2000 * (numpy.sqrt(numpy.float(len(mslist)))))
#depth = 0.7 / (numpy.sqrt(numpy.float(len(mslist))))
depth = 0.5 / (numpy.sqrt(numpy.float(len(mslist))))
cleandepth1 = str(depth*1.5) + 'mJy'
cleandepth2 = str(depth) + 'mJy'
# get size from mask image
if imsize is None:
imsize = image_size_from_mask(inputmask)
# already done in facetting step
## speed up the imaging if possible by reducing image size within the mask region
#newsize = find_newsize(inputmask)
#if newsize < imsize: # ok so we can use a smaller image size then
##make a new template
#os.system('casapy --nogui -c '+SCRIPTPATH+'/make_empty_image.py '+ str(mslist[0]) + ' ' + inputmask+'2' + ' ' + str(newsize) + ' ' +'1.5arcsec')
#os.system('casapy --nogui -c '+SCRIPTPATH+'/regrid_image.py ' + inputmask + ' ' + inputmask+'2' + ' ' + inputmask+'3')
## reset the imsize and the mask
#imsize = newsize
#inputmask = inputmask+'3'
ms = ''
for m in mslist:
ms = ms + ' ' + m
imout = 'im'+ callnumber +'_cluster'+cluster+'nm'
os.system('casapy --nogui --logfile casapy-'+imout+'.log -c '+SCRIPTPATH+'/dde_weeren/a2256_hba/casapy_cleanv4.py ' + ms + ' ' + imout + ' ' + 'None' +\
' ' + cleandepth1 + ' ' + str(niter) + ' ' + str(nterms) + ' ' + str(imsize) + ' ' + mscale)
# make mask
if nterms > 1:
os.system('python '+SCRIPTPATH+'/makecleanmask_field.py --threshpix '+str(threshpix)+\
' --threshisl '+str(threshisl) +' --atrous_do '+ str(atrous_do) +' ' +imout +'.image.tt0')
else:
os.system('python '+SCRIPTPATH+'/makecleanmask_field.py --threshpix '+str(threshpix)+\
' --threshisl '+str(threshisl) +' --atrous_do '+ str(atrous_do) + ' ' + imout +'.image')
mask_sources = imout+'.cleanmask'
os.system('rm -rf ' + mask_sources + 'field')
os.system('cp -r ' + mask_sources + ' ' + mask_sources + 'field')
#Merge the two masks
img = pyrap.images.image(mask_sources+'field')
pixels = numpy.copy(img.getdata())
img2 = pyrap.images.image(inputmask)
pixels2 = numpy.copy(img2.getdata())
idx = numpy.where(pixels2 == 0.0)
pixels[idx] = 0.0
img.putdata(pixels)
img.unlock()
del img
del img2
#niter = numpy.int(niter*1.2) # clean a bit deeper (will actually be quite a bit deeper because of mask)
niter = numpy.int(niter*2.0) # clean a bit deeper (will actually be quite a bit deeper because of mask)
imout = 'im'+ callnumber +'_cluster'+cluster
if region != 'empty': # in that case we have a extra region file for the clean mask
if 'fs' in region:
niter = numpy.int(niter*3.0) # increase niter, tune manually if needed (change back)
else:
niter = numpy.int(niter*3.0) # increase niter, tune manually if needed
os.system('casapy --nogui --logfile casapy-'+imout+'.log -c '+SCRIPTPATH+'/dde_weeren/a2256_hba/casapy_cleanv4.py '+ ms + ' ' + imout + ' ' + mask_sources+'field,'+region + \
' ' + cleandepth2 + ' ' + str(niter) + ' ' + str(nterms) + ' ' + str(imsize) + ' ' + mscale)
else:
os.system('casapy --nogui --logfile casapy-'+imout+'.log -c '+SCRIPTPATH+'/dde_weeren/a2256_hba/casapy_cleanv4.py '+ ms + ' ' + imout + ' ' + mask_sources+'field' + \
' ' + cleandepth2 + ' ' + str(niter) + ' ' + str(nterms) + ' ' + str(imsize) + ' ' + mscale)
# convert to FITS
if nterms > 1:
os.system('image2fits in=' + imout +'.image.tt0' + ' ' + 'out='+ imout + '.fits')
else:
os.system('image2fits in=' + imout +'.image' + ' ' + 'out='+ imout + '.fits')