def makecontimage(self, im, novaliddata, imname):
makeblanks=lambda imn,im: [im.make(imn+eltypo) for eltypo in ['.image', '.residual', '.model', '.psf', '.wgt'] ]
if(novaliddata==True):
###make blanks
###The images may still be open...as we don't have
###a reset function; setscales is the closest which will destroy
###the skyequation without much of anything else.
im.setscales()
makeblanks(imname, im)
return novaliddata
if(not self.imageparamset):
try:
im.clean(algorithm='mfclark', gain=self.gain, niter=0, threshold='0.05mJy',
model=imname+'.model', image=imname+'.image',
residual=imname+'.residual', psfimage=imname+'.psf')
ia=casac.image()
for ima in [imname+'.residual', imname+'.psf']:
ia.open(ima)
statout=ia.statistics(verbose=False, list=False)
ia.done()
if(statout['max'][0]==0.0):
novaliddata=True
except Exception, instance:
if(string.count(instance.message, 'PSFZero') >0):
novaliddata=True
###The images may still be open...as we don't have
###a reset function; setscales is the closest which will destroy
###the skyequation without much of anything else.
im.setscales()
###make a blank image
makeblanks(imname, im)
else:
raise instance
def compImages(im0,im1,keys=['flux','min','max','maxpos','rms'],tol=1e-4,verbose=False):
"""
compare two images using imstat and the specified keys,
to a tolerance tol, and printing the comparison if verbose==True
note that the string keys like 'blcf' will fail
"""
from os import F_OK
if isinstance(tol,float):
tol=tol+np.zeros(len(keys))
myia=casac.image()
ims=[im0,im1]
s=[]
for i in range(2):
if not os.access(ims[i],F_OK):
print ims[i]+" not found"
return False
myia.open(ims[1])
s.append(myia.statistics())
myia.done()
status=True
for ik in range(len(keys)):
k=keys[ik]
s0=s[0][k][0]
s1=s[1][k][0]
if abs(s0-s1)*2/(s0+s1)>tol[ik]: status=False
if verbose:
print ("%7s: "%k),s0,s1
return status
def concatimages(cubeimage, inim, csys=None, removeinfile=True):
if((csys==None) and os.path.exists(cubeimage)):
ia.open(cubeimage)
csys=ia.coordsys()
ia.done()
if(type(inim) != list):
inim=[inim]
###Temporary bypass of CAS-4423
#elbeamo={}
#for elim in inim:
# ia.open(elim)
# beam=ia.restoringbeam()
#if( (len(beam) > 0) and (not beam.has_key('beams'))):
# ia.setrestoringbeam(remove=True)
# nchan=ia.shape()[3]
# for k in range(nchan):
# ia.setrestoringbeam(major=beam['major'], minor=beam['minor'], pa=beam['positionangle'], channel=k, polarization=0)
# ia.setrestoringbeam(remove=True)
# elbeamo=beam if(not beam.has_key('beams')) else beam['beams']['*0']['*0']
# ia.done()
####
if(len(inim)==1):
ib=ia.fromimage(outfile=cubeimage, infile=inim[0], overwrite=True)
else:
#ib=ia.imageconcat(outfile=cubeimage, infiles=inim,
# axis=3, relax=True, overwrite=True)
############
strnames='"'
for k in range(len(inim)):
strnames=strnames+' '+inim[k] if (k > 0) else strnames+inim[k]
strnames=strnames+'"'
comm='imageconcat '+ strnames + ' '+ cubeimage
casalog.post('Command '+comm)
exitval=os.system(comm)
#print "exitval", exitval
if(exitval > 0):
raise Exception('Failed to concat '+str(inim))
ib=casac.image()
ib.open(cubeimage)
##############
ia.done()
##### CAS-4423 temp
#if(len(elbeamo) >0):
# ib.setrestoringbeam(beam=elbeamo)
#####
if(csys != None):
if(type(csys)==dict):
ib.setcoordsys(csys=csys)
else:
ib.setcoordsys(csys=csys.torecord())
ib.done()
if(removeinfile):
for k in range(len(inim)):
ia.removefile(inim[k])
def pixelmask2cleanmask(imagename='',
maskname='mask0',
maskimage='',
usemasked=False):
"""
convert pixel(T/F) mask (in a CASA image) to a mask image (1/0)
used for clean
imagename - input imagename that contain a mask to be used
maskname - mask name in the image (default: mask0)
maskimage - output mask image name
usemasked - if True use masked region as a valid region
"""
ia = casac.image()
ia.open(imagename)
masks = ia.maskhandler('get')
ia.close()
inmaskname = ''
if type(masks) != list:
masks = [masks]
for msk in masks:
if maskname == msk:
inmaskname = msk
break
if inmaskname == '':
raise Exception, "mask %s does not exist. Available masks are: %s" % (
maskname, masks)
tb = casac.table()
tb.open(imagename + '/' + maskname)
dat0 = tb.getcol('PagedArray')
tb.close()
#os.system('cp -r %s %s' % (imagename, maskimage))
shutil.copytree(imagename, maskimage)
ia.open(maskimage)
# to unset mask
ia.maskhandler('set', [''])
# make all valid
if (usemasked):
ia.set(1)
else:
ia.set(0)
ia.close()
#
tb.open(maskimage, nomodify=False)
imd = tb.getcol('map')
# maybe shape check here
#by default use True part of bool mask
masked = 1
if (usemasked): masked = 0
imd[dat0] = masked
tb.putcol('map', imd)
tb.close()
def fitCube2(self,x0,y0):
result=[]
box = str(x0) + ", " + str(y0) + ", " + str(x0) + ", " + str(y0)
reg=self.rgTool.box(blc=[x0,y0], trc=[x0,y0])
model = "mymodel.im"
resid = "myresid.im"
myia = casac.image()
for x in ([model, resid]):
if (os.path.exists(x)):
myia.open(x)
myia.remove()
myia.close()
retval=self.imTool.fitprofile(box=box, ngauss=1, model=model, residual=resid)
myia.open(model)
theFit = myia.getchunk().flatten()
myia.close()
myia.open(resid)
theResid = myia.getchunk().flatten()
myia.done()
for x in ([model, resid]):
if (os.path.exists(x)):
myia.open(x)
myia.remove()
myia.close()
result.append([retval['gs']['amp'].flatten()[0], retval['gs']['center'].flatten()[0], retval['gs']['fwhm'].flatten()[0]])
result.append([retval['gs']['ampErr'].flatten()[0], retval['gs']['centerErr'].flatten()[0], retval['gs']['fwhmErr'].flatten()[0]])
s='fit at [%d,%d]\n\tFWHM: %f \n\peak: %f \t with errors: %f, %f '%(x0,y0, result[0][2], result[0][0], result[1][2], result[1][0])
print s
if self.write: self.body2.append('<pre>%s</pre>'%s)
data=self.imTool.getchunk(blc=[int(x0),int(y0)], trc=[int(x0),int(y0)], dropdeg=True)
pylab.clf()
pylab.plot(data,'r-')
pylab.plot(theFit, 'bo')
pylab.plot(theResid,'g.-.')
pylab.xlabel('Layer of image cube @ pixel [%d,%d]'%(x0,y0))
pylab.ylabel('Intensity')
pylab.title('Fit on Image '+self.imageName)
if self.write:
header='Image cube Fit: %s'%self.imageName
self.body1=['<pre>Plot of layers @ pixel [%d,%d]:</pre>'%(x0,y0)]
saveDir=self.imDir+self.fname[11:-5]+'-cube-min_max%d.png'%self.iterate
pylab.savefig(saveDir)
self.htmlPub.doBlk(self.body1, self.body2, saveDir,header)
self.iterate+=1
XY=[]
fwhm=[]
for i in range(len(result)):
fwhm.append(result[i][2])
XY.append([result[i][0],result[i][1]])
return XY, fwhm
from casac import casac
import os
import numpy as np
import pdb
iaim = casac.image()
iamask = casac.image()
qa = casac.quanta()
rg = casac.regionmanager()
def automask(image='',
maskimage='',
fracofpeak=0,
rmsthresh=3.0,
resolution=None,
twopass=False):
"""
image : dirty image or residual to mask
maskimage: name of mask to create. If already existant has to be same shape
and coordsys as image
fracofpeak : Fraction of peak to use as masking threshold (a number between 0 and 1)
if 0 then rmsthresh or a value based on the rms of the image is used
rmsthresh : Threshold in sigma to use; default is 3 sigma
resolution: if image has no restoring beam ..this value is used for resolution of
image (e.g '4arcsec')
twopass: set to True if faint fluffy stuff is wanted else false if a less agressive masking
is needed especially a multi pass masking after some cleaning
"""
# print '2pass ', twopass
iaim.open(image)
from casac import casac
import os
import numpy as np
import pdb
iaim=casac.image()
iamask=casac.image()
qa=casac.quanta()
rg=casac.regionmanager()
def automask(image='', maskimage='', fracofpeak=0, rmsthresh=3.0, resolution=None, twopass=False):
"""
image : dirty image or residual to mask
maskimage: name of mask to create. If already existant has to be same shape
and coordsys as image
fracofpeak : Fraction of peak to use as masking threshold (a number between 0 and 1)
if 0 then rmsthresh or a value based on the rms of the image is used
rmsthresh : Threshold in sigma to use; default is 3 sigma
resolution: if image has no restoring beam ..this value is used for resolution of
image (e.g '4arcsec')
twopass: set to True if faint fluffy stuff is wanted else false if a less agressive masking
is needed especially a multi pass masking after some cleaning
"""
# print '2pass ', twopass
iaim.open(image)
stat=iaim.statistics(mask='abs("'+image+'") > 0.0')
csys=iaim.coordsys()
rb=iaim.restoringbeam()
numpix=10
shp=iaim.shape()
resol=qa.quantity(resolution, 'arcsec')
from tasks import * casalog = casac.logsink() casalog.setglobal(True) quanta = casac.quanta() measures = casac.measures() imager = casac.imager() calibrater = casac.calibrater() ms = casac.ms() tableplot = casac.tableplot() msplot = casac.msplot() calplot = casac.calplot() table = casac.table() #flagger = casac.flagger() agentflagger = casac.agentflagger() image = casac.image() imagepol = casac.imagepol() simulator = casac.simulator() componentlist = casac.componentlist() coordsys = casac.coordsys() regionmanager = casac.regionmanager() spectralline = casac.spectralline() utils = casac.utils() deconvolver = casac.deconvolver() vpmanager = casac.vpmanager() vlafillertask = casac.vlafillertask() atmosphere = casac.atmosphere() cu = casac.utils() mstransformer = casac.mstransformer() #plotms = __plotmshome__.create( )
from casac import casac
from locatescript import copydata
quantity = casac.quanta()
im = casac.imager()
ia = casac.image()
def data():
return ['ic2233_1.ms']
def run(fetch=False):
#####fetch data
if fetch:
for f in data():
copydata(f, os.getcwd())
im.open('ic2233_1.ms')
npix = 1024
im.selectvis(spw='0', nchan=[6], start=[0], step=[1])
im.defineimage(nx=npix,
ny=npix,
cellx='3.0arcsec',
celly='3.0arcsec',
stokes="IV",
spw=[0])
im.weight(type='briggs', robust=0.7)
im.setoptions(imagetilevol=-1000000)
im.setvp(dovp=bool(1),
def imagecontbychan(self, msname='spw00_4chan351rowTile.ms', start=[0], numchan=[1], spw=[0], field=0, freq='1.20GHz', band='200MHz', imname='newmodel'):
ia=casac.image()
if(type(spw) == int):
spw=[spw]
start=[start]
numchan=[numchan]
totchan=np.sum(numchan)
if(not self.imageparamset):
if(totchan==0):
###make blanks
self.im.selectvis(vis=msname, field=field, spw=spw, nchan=numchan, start=start, step=1, time=self.timerange, uvrange=self.uvrange, baseline=self.baselines, scan=self.scan, observation=self.observation,writeaccess=False)
self.im.defineimage(nx=self.pixels[0], ny=self.pixels[1], cellx=self.cell[0], celly=self.cell[1], phasecenter=self.phCen, mode='frequency', nchan=1, start=freq, step=band, facets=self.facets)
self.im.make(imname+'.image')
self.im.make(imname+'.residual')
self.im.make(imname+'.model')
self.im.make(imname+'.psf')
self.imageparamset=True
return
del self.im
self.im=[]
del self.novaliddata
self.novaliddata=[]
selkey={}
spwind=0
chancounter=0
for k in range(totchan):
if(chancounter==numchan[spwind]):
chancounter=0
spwind+=1
selkey[k]= {'spw': spw[spwind], 'start':start[spwind]+chancounter}
chancounter += 1
self.im.append(casac.imager())
self.novaliddata.append(False)
print 'selkey', selkey
else:
if(totchan==0):
return
origname=msname
for k in range(totchan):
###either psf 0 or no channel selected
if(k==0):
image=imname+'.image'
residual=imname+'.residual'
psf=imname+'.psf'
else:
image=imname+'_'+str(k)+'.image'
residual=imname+'_'+str(k)+'.residual'
psf=imname+'_'+str(k)+'.psf'
if(not self.novaliddata[k]):
msname=origname
if(not self.imageparamset):
self.im[k].selectvis(vis=msname, field=field, spw=selkey[k]['spw'], nchan=1, start=selkey[k]['start'], step=1, datainmemory=self.visInMem, time=self.timerange, uvrange=self.uvrange, baseline=self.baselines, scan=self.scan, observation=self.observation, writeaccess=False)
self.im[k].defineimage(nx=self.pixels[0], ny=self.pixels[1], cellx=self.cell[0], celly=self.cell[1], phasecenter=self.phCen, mode='frequency', nchan=1, start=freq, step=band, facets=self.facets)
self.im[k].weight(type=self.weight, rmode='norm', npixels=self.weightnpix,
robust=self.robust)
self.im[k].setoptions(ftmachine=self.ft, wprojplanes=self.wprojplanes, pastep=self.painc, pblimit=self.pblimit, cfcachedirname=self.cfcache, dopbgriddingcorrections=self.dopbcorr, applypointingoffsets=self.applyoffsets, imagetilevol=self.imagetilevol, singleprecisiononly=True, numthreads=self.numthreads)
#im.regionmask(mask='lala.mask', boxes=[[0, 0, 3599, 3599]])
#im.setmfcontrol(cyclefactor=0.0)
if(not self.imageparamset):
try:
self.im[k].clean(algorithm='clark', gain=self.gain, niter=0, model=imname+'.model', image=image, residual=residual, psfimage=psf)
if(k > 0):
ia.open(imname+'.psf')
ia.calc('"'+imname+'.psf'+'" + "'+psf+'"')
ia.done()
except Exception, instance:
if(string.count(instance.message, 'PSFZero') >0):
self.novaliddata[k]=True
###make a blank image
if(k==0):
self.im[k].make(image)
self.im[k].make(residual)
else:
raise instance
else:
if(not self.novaliddata[k]):
self.im[k].restore(model=imname+'.model', image=image, residual=residual)
if(k > 0):
ia.open(imname+'.residual')
ia.calc('"'+imname+'.residual'+'" + "'+residual+'"')
ia.done()
ia.open(imname+'.image')
ia.calc('"'+imname+'.image'+'" + "'+residual+'"')
ia.done()
tb.showcache()
from casac import casac
from locatescript import copydata
quantity=casac.quanta()
im = casac.imager()
ia = casac.image()
def data():
return ['ic2233_1.ms']
def run(fetch=False) :
#####fetch data
if fetch:
for f in data( ):
copydata( f, os.getcwd( ) )
im.open('ic2233_1.ms')
npix=1024
im.selectvis(spw='0', nchan=[6], start=[0], step=[1])
im.defineimage(nx=npix, ny=npix, cellx='3.0arcsec', celly='3.0arcsec', stokes="IV", spw=[0])
im.weight(type='briggs', robust=0.7)
im.setoptions(imagetilevol=-1000000);
im.setvp(dovp=bool(1), usedefaultvp=bool(1), dosquint=bool(1),
parangleinc='5.0deg')
im.make('squint_corr')
im.clean(algorithm='mfhogbom', niter=1000, model=['squint_corr'], residual=['squint_corr.residual'], image=['squint_corr.restored'], threshold='0Jy')
im.done()
return ['squint_corr.restored']
def fitCube2(self, x0, y0):
result = []
box = str(x0) + ", " + str(y0) + ", " + str(x0) + ", " + str(y0)
reg = self.rgTool.box(blc=[x0, y0], trc=[x0, y0])
model = "mymodel.im"
resid = "myresid.im"
myia = casac.image()
for x in ([model, resid]):
if (os.path.exists(x)):
myia.open(x)
myia.remove()
myia.close()
retval = self.imTool.fitprofile(box=box,
ngauss=1,
model=model,
residual=resid)
myia.open(model)
theFit = myia.getchunk().flatten()
myia.close()
myia.open(resid)
theResid = myia.getchunk().flatten()
myia.done()
for x in ([model, resid]):
if (os.path.exists(x)):
myia.open(x)
myia.remove()
myia.close()
result.append([
retval['gs']['amp'].flatten()[0],
retval['gs']['center'].flatten()[0],
retval['gs']['fwhm'].flatten()[0]
])
result.append([
retval['gs']['ampErr'].flatten()[0],
retval['gs']['centerErr'].flatten()[0],
retval['gs']['fwhmErr'].flatten()[0]
])
s = 'fit at [%d,%d]\n\tFWHM: %f \n\peak: %f \t with errors: %f, %f ' % (
x0, y0, result[0][2], result[0][0], result[1][2], result[1][0])
print s
if self.write: self.body2.append('<pre>%s</pre>' % s)
data = self.imTool.getchunk(blc=[int(x0), int(y0)],
trc=[int(x0), int(y0)],
dropdeg=True)
pylab.clf()
pylab.plot(data, 'r-')
pylab.plot(theFit, 'bo')
pylab.plot(theResid, 'g.-.')
pylab.xlabel('Layer of image cube @ pixel [%d,%d]' % (x0, y0))
pylab.ylabel('Intensity')
pylab.title('Fit on Image ' + self.imageName)
if self.write:
header = 'Image cube Fit: %s' % self.imageName
self.body1 = [
'<pre>Plot of layers @ pixel [%d,%d]:</pre>' % (x0, y0)
]
saveDir = self.imDir + self.fname[
11:-5] + '-cube-min_max%d.png' % self.iterate
pylab.savefig(saveDir)
self.htmlPub.doBlk(self.body1, self.body2, saveDir, header)
self.iterate += 1
XY = []
fwhm = []
for i in range(len(result)):
fwhm.append(result[i][2])
XY.append([result[i][0], result[i][1]])
return XY, fwhm
def __init__(self,
imageName,
write=True,
resultDir='WEBPAGES/imageTest/',
imDir='IMAGES/'):
import shutil
self.imTool = casac.image()
self.imTool.open(imageName) #open('tables/squint_corr.restored')
# fix up images that don't have CASA-canonical stokes and spec:
# assume for now that direction is in 01 at least,
mycs = self.imTool.coordsys()
findstok = mycs.findcoordinate("stokes")
if not findstok['return']:
myImagename = imageName + ".k"
self.imTool.adddegaxes(stokes=True,
outfile=myImagename,
overwrite=True)
mystokpix = self.imTool.summary()['ndim'] # ct from 0
self.imTool.close()
shutil.rmtree(imageName)
shutil.move(myImagename, imageName)
self.imTool.open(imageName)
mycs.done()
mycs = self.imTool.coordsys()
else:
mystokpix = findstok['pixel']
findspec = mycs.findcoordinate("spectral")
if not findspec['return']:
myImagename = imageName + ".s"
self.imTool.adddegaxes(spectral=True,
outfile=myImagename,
overwrite=True)
myspecpix = self.imTool.summary()['ndim'] # ct from 0
self.imTool.close()
shutil.rmtree(imageName)
shutil.move(myImagename, imageName)
self.imTool.open(imageName)
mycs.done()
mycs = self.imTool.coordsys()
else:
myspecpix = findspec['pixel']
curr_order = [mystokpix, myspecpix]
if curr_order != [2, 3]:
myImagename = imageName + ".t"
self.imTool.transpose(order="01%1i%1i" % (mystokpix, myspecpix),
outfile=myImagename,
overwrite=True)
shutil.rmtree(imageName)
shutil.move(myImagename, imageName)
self.imTool.open(imageName)
self.rgTool = casac.regionmanager()
self.qaTool = casac.quanta()
self.getArr() #instead make explicit call to getArr()
self.write = write
self.imageName = imageName
self.iterate = 0 #for multiple cubeFit() tests
if self.write:
self.resultDir = resultDir + strftime('/%Y_%m_%d/')
if os.access(self.resultDir, os.F_OK) is False:
print self.resultDir + ' directory DNE, so am making one!'
os.mkdir(self.resultDir)
else:
print self.resultDir + ' directory exists; will add to it!'
self.imDir = imDir
if os.access(imDir, os.F_OK) is False:
print imDir + ' directory DNE, so am making one!'
os.mkdir(imDir)
else:
print imDir + ' directory exists; will add to it!'
t = localtime(time())
self.fname = 'Regression-%s-%s-%s-%s-%s-%s.html' % (
t[0], t[1], t[2], t[3], t[4], t[5])
self.html = self.resultDir + self.fname
self.body1 = []
self.body2 = []
self.htmlPub = htmlPub(self.html, 'Image tests')
else:
print 'stats-only mode; will not write to html file!'
def __init__(self, imageName, write=True,
resultDir='WEBPAGES/imageTest/',
imDir='IMAGES/'):
import shutil
self.imTool=casac.image()
self.imTool.open(imageName) #open('tables/squint_corr.restored')
# fix up images that don't have CASA-canonical stokes and spec:
# assume for now that direction is in 01 at least,
mycs=self.imTool.coordsys()
findstok=mycs.findcoordinate("stokes")
if not findstok['return']:
myImagename=imageName+".k"
self.imTool.adddegaxes(stokes=True,outfile=myImagename,overwrite=True)
mystokpix=self.imTool.summary()['ndim'] # ct from 0
self.imTool.close()
shutil.rmtree(imageName)
shutil.move(myImagename,imageName)
self.imTool.open(imageName)
mycs.done()
mycs=self.imTool.coordsys()
else:
mystokpix=findstok['pixel']
findspec=mycs.findcoordinate("spectral")
if not findspec['return']:
myImagename=imageName+".s"
self.imTool.adddegaxes(spectral=True,outfile=myImagename,overwrite=True)
myspecpix=self.imTool.summary()['ndim'] # ct from 0
self.imTool.close()
shutil.rmtree(imageName)
shutil.move(myImagename,imageName)
self.imTool.open(imageName)
mycs.done()
mycs=self.imTool.coordsys()
else:
myspecpix=findspec['pixel']
curr_order=[mystokpix,myspecpix]
if curr_order != [2,3]:
myImagename=imageName+".t"
self.imTool.transpose(order="01%1i%1i" % (mystokpix,myspecpix),outfile=myImagename,overwrite=True)
shutil.rmtree(imageName)
shutil.move(myImagename,imageName)
self.imTool.open(imageName)
self.rgTool=casac.regionmanager()
self.qaTool=casac.quanta()
self.getArr() #instead make explicit call to getArr()
self.write=write
self.imageName=imageName
self.iterate=0 #for multiple cubeFit() tests
if self.write:
self.resultDir=resultDir+strftime('/%Y_%m_%d/')
if os.access(self.resultDir,os.F_OK) is False:
print self.resultDir+' directory DNE, so am making one!'
os.mkdir(self.resultDir)
else:
print self.resultDir+' directory exists; will add to it!'
self.imDir=imDir
if os.access(imDir,os.F_OK) is False:
print imDir+' directory DNE, so am making one!'
os.mkdir(imDir)
else:
print imDir+' directory exists; will add to it!'
t=localtime( time() )
self.fname='Regression-%s-%s-%s-%s-%s-%s.html'%(t[0],t[1],t[2],t[3],t[4],t[5])
self.html=self.resultDir+self.fname
self.body1=[]
self.body2=[]
self.htmlPub=htmlPub(self.html,'Image tests')
else:
print 'stats-only mode; will not write to html file!'
