def drawmaskinimage(image='', maskname='maskoo', makedefault=True):
"""
Till casa think graphical interaction is important.
Ugly Function that uses interactive clean image mask to
allow users to draw a mask and store it as a bit mask in the image
so it can be used by imageanalysis methods or to mask an image
Parameters
image: is the image to put a bit mask in
maskname: name of bit mask
makedefault: if True will make new bit mask drawn be the default mask
"""
if (not os.path.exists(image)):
return
tmpmaskimage = '__muluktani'
if (os.path.exists(tmpmaskimage)):
shutil.rmtree(tmpmaskimage, True)
im.drawmask(image=image, mask=tmpmaskimage)
ia.open(image)
ia.calcmask(mask='__muluktani < 0.5', name=maskname, asdefault=makedefault)
ia.done()
print 'regions/mask in ', image, rg.namesintable(image)
shutil.rmtree(tmpmaskimage, True)
def radialMaxLevel(self, rmin, rmax, Nbin):
"Compute the maximum (absolute) level for the image and return the array of radius (arcsec) and values"
dr = (rmax - rmin) / Nbin
radius = np.arange(Nbin) * dr + rmin
radMaxLevel = np.zeros(Nbin)
## loop over the pixels
ia.open(self.beamImage)
for i in range(self.Nx):
for j in range(self.Ny):
xx = (i - self.refx) * self.dx
yy = (j - self.refy) * self.dy
rr = sqrt(xx * xx + yy * yy)
indexR = floor((rr - rmin) / dr)
if indexR >= 0 and indexR < Nbin:
val = ia.pixelvalue([i, j])['value']['value']
if abs(val) > abs(radMaxLevel[indexR]):
radMaxLevel[indexR] = val
ia.close()
return (radius, radMaxLevel)
def drawmaskinimage(image='', maskname='maskoo', makedefault=True):
"""
Till casa think graphical interaction is important.
Ugly Function that uses interactive clean image mask to
allow users to draw a mask and store it as a bit mask in the image
so it can be used by imageanalysis methods or to mask an image
Parameters
image: is the image to put a bit mask in
maskname: name of bit mask
makedefault: if True will make new bit mask drawn be the default mask
"""
if(not os.path.exists(image)):
return
tmpmaskimage='__muluktani'
if(os.path.exists(tmpmaskimage)):
shutil.rmtree(tmpmaskimage, True)
im.drawmask(image=image, mask=tmpmaskimage)
ia.open(image)
ia.calcmask(mask='__muluktani < 0.5', name=maskname, asdefault=makedefault)
ia.done()
print 'regions/mask in ', image, rg.namesintable(image)
shutil.rmtree(tmpmaskimage, True)
def printProperties(filenames):
from casa import imstat
from casa import image as ia
from casa import imager as im
imageDir = './'
for i, image in enumerate(filenames):
flux = imstat(imageDir + image + '.mom0.blk.image')['flux'][0]
ia.open(imageDir + image + '.mom0.blk.image')
beammaj = ia.restoringbeam(channel=0)['major']['value']
beammin = ia.restoringbeam(channel=0)['minor']['value']
beamsizeUnit = ia.restoringbeam(channel=0)['major']['unit']
ia.close()
ia.open(imageDir + image + '.image')
noise = ia.statistics()['sigma'][0]
ia.close()
if True: mosaic, res = 'Multiscale clean', i
#else: mosaic,res = 'Mosaic', i*3 -3
print '\nImage: '+mosaic+' resolution #' + str(res) + \
'\nBeamsize: ' + str(beammaj) + '" X ' + str(beammin) + '"' + \
'\nStd: ' + str(noise) + ' Jy/Bm' + \
'\nFlux: ' + str(flux) + ' Jy km/s'
def printProperties(filenames):
from casa import imstat
from casa import image as ia
from casa import imager as im
imageDir = './'
for i, image in enumerate(filenames):
flux = imstat(imageDir + image+ '.mom0.blk.image')['flux'][0]
ia.open(imageDir + image + '.mom0.blk.image')
beammaj = ia.restoringbeam(channel=0)['major']['value']
beammin = ia.restoringbeam(channel=0)['minor']['value']
beamsizeUnit = ia.restoringbeam(channel=0)['major']['unit']
ia.close()
ia.open(imageDir + image + '.image')
noise = ia.statistics()['sigma'][0]
ia.close()
if True: mosaic,res = 'Multiscale clean', i
#else: mosaic,res = 'Mosaic', i*3 -3
print '\nImage: '+mosaic+' resolution #' + str(res) + \
'\nBeamsize: ' + str(beammaj) + '" X ' + str(beammin) + '"' + \
'\nStd: ' + str(noise) + ' Jy/Bm' + \
'\nFlux: ' + str(flux) + ' Jy km/s'
def radialMaxLevel(self,rmin,rmax,Nbin):
"Compute the maximum (absolute) level for the image and return the array of radius (arcsec) and values"
dr=(rmax-rmin)/Nbin
radius=np.arange(Nbin)*dr+rmin
radMaxLevel=np.zeros(Nbin)
## loop over the pixels
ia.open(self.beamImage)
for i in range(self.Nx):
for j in range(self.Ny):
xx=(i-self.refx)*self.dx
yy=(j-self.refy)*self.dy
rr=sqrt(xx*xx+yy*yy)
indexR=floor((rr-rmin)/dr)
if indexR >=0 and indexR < Nbin:
val=ia.pixelvalue([i,j])['value']['value']
if abs(val) > abs(radMaxLevel[indexR]):
radMaxLevel[indexR]=val
ia.close()
return(radius,radMaxLevel)
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.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.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 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.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.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 __setImage(self):
"Set the parameters of the image"
ia.open(self.beamImage)
hdr = ia.summary()
print hdr
## Image Size
self.Nx = hdr['shape'][0]
self.Ny = hdr['shape'][1]
## Pixel reference
self.refx = hdr['refpix'][0]
self.refy = hdr['refpix'][0]
##Increment (radians)
self.dx = hdr['incr'][0]
self.dy = hdr['incr'][1]
self.dx *= RAD2ARCSEC
self.dy *= RAD2ARCSEC
ia.close()
def __setImage(self):
"Set the parameters of the image"
ia.open(self.beamImage)
hdr = ia.summary()
print hdr
## Image Size
self.Nx=hdr['shape'][0]
self.Ny=hdr['shape'][1]
## Pixel reference
self.refx=hdr['refpix'][0]
self.refy=hdr['refpix'][0]
##Increment (radians)
self.dx=hdr['incr'][0]
self.dy=hdr['incr'][1]
self.dx*=RAD2ARCSEC
self.dy*=RAD2ARCSEC
ia.close()
def curveFluxDiskSize(self,
antennaCfg,
trackDuration,
sizeMin,
sizeMax,
sizeStep,
declination,
cellsize='0.2arcsec',
hourAngle='transit',
shapeCL='Gaussian',
threshClean='0mJy'):
"""
Compute the flux of disk with different size
antennaCfg: antenna configuration
trackDuration: time duration, e.g. "6h"
sizeMin,sizeMax: range of the disk size in arcsec. The total flux is 1 Jy
sizeStep: step for the disk size
declination: disk declination
cellsize : size of the cell
Output: array [sizeDisk, flux]
"""
## setting simobserve
projectName = "tempDiskFlux"
nStep = int((sizeMax - sizeMin) / sizeStep)
sizeArr = np.arange(nStep) * sizeStep + sizeMin
flux = np.zeros(nStep)
size = np.zeros(nStep)
las100 = np.zeros(nStep)
totalSize = 120.
mapSize = "%3.1farcsec" % (totalSize)
cellF = float(cellsize[:-6]) ## to be improved ....
imagesize = int(totalSize / cellF)
index = 0
print "image size: %d " % (imagesize)
print "mapsize :%s" % (mapSize)
# simulation with one arcsec component. We clean the old files.
os.system("rm -Rf *%s*" % (projectName))
if declination <= -10:
decString = "J2000 0h00m00s %3dd00m00s" % (declination)
raDisk = "0h00m00s"
decDisk = "%3dd00m00s" % (declination)
elif declination < 0 and dec > -10:
decString = "J2000 0h00m00s -0%1dd00m00s" % (-declination)
raDisk = "0h00m00s"
decDisk = "-0%1d00m00s" % (declination)
elif declination >= 0 and dec < 10:
decString = "J2000 0h00m00s +0%1dd00m00s" % (declination)
raDisk = "0h00m00s"
decDisk = "+0%1d00m00s" % (declination)
elif declination >= 10:
decString = "J2000 0h00m00s +%2dd00m00s" % (declination)
raDisk = "0h00m00s"
decDisk = "+0%2d00m00s" % (declination)
## Estimation of the spatial resolution at 100 GHz for the mask
arrCfg = aT.ArrayInfo(antennaCfg)
arrCfg.stats()
maxBL = arrCfg.maxBl
resEstimated = 61800. / (maxBL * 100.)
print("Estimated RES: %3.2f" % (resEstimated))
for disksize in sizeArr:
#cl.done()
cl.addcomponent(dir=decString,
flux=1.,
freq='100GHz',
shape=shapeCL,
majoraxis="%2.2farcsec" % (disksize),
minoraxis="%2.2farcsec" % (disksize),
positionangle="0deg")
cl.rename(projectName + "%d.cl" % (index))
cl.done()
print projectName + "%d.cl" % (index)
so.simobserve(
project=projectName + "%d" % (index),
complist=projectName + "%d.cl" % (index),
compwidth='8GHz',
antennalist=antennaCfg,
totaltime=trackDuration,
integration='10s',
mapsize=mapSize,
user_pwv=0.,
)
maxDisk = max(disksize, resEstimated)
regDiskClean = 'circle[[%s , %s], %3.1farcsec ]' % (
raDisk, decDisk, maxDisk * 1.5)
regDiskFlux = 'circle[[%s , %s], %3.1farcsec ]' % (raDisk, decDisk,
maxDisk * 1.5)
sa.simanalyze(
project=projectName + "%d" % (index),
image=True,
weighting='briggs',
imsize=imagesize,
cell=cellsize,
mask=regDiskClean,
niter=2000,
threshold=threshClean,
imdirection=decString,
# graphics = 'file'
)
msName = projectName + "%d/" % (
index) + projectName + "%d.%s.ms" % (index,
antennaCfg.split('.')[0])
imageName = projectName + "%d/" % (
index) + projectName + "%d.%s.noisy.image" % (
index, antennaCfg.split('.')[0])
print(" ")
print("## analysis ...")
print "Mask Clean :: %s" % (regDiskClean)
print "Mask Flux :: %s" % (regDiskFlux)
print "Component Size :: %2.2f" % (disksize)
ia.open(imageName)
data = ia.restoringbeam()
bmaj = data['major']['value']
stat = ia.statistics(region=regDiskFlux)
flux[index] = stat['flux']
ia.close()
print data
ms = uvw.UVW(msName)
dUV = ms.distUV(noShadow=True)
duvMin = min(dUV)
las100[
index] = RAD2ARCSEC * 0.0017987547479999 / duvMin ## 0.6 * Lambda / BL_min
print "mininum BL:", duvMin
print "LAS (100 GHz & min BL):", las100[index]
print "Flux: %2.3f" % (flux[index])
print "--"
index += 1
return ([sizeArr, flux])
def curveBeamResolutiongDeclination(self,
antennaCfg,
trackDuration,
declinationMin,
declinationMax,
decStep,
ha='transit'):
"""
Compute the minor,Major axis vs. Declination for a given configuration
antennaCfg: antenna configuration
trackDuration: time duration, e.g. "6h"
declinationMin,declinationMax: range of declination
decStep: step for the declination, needs to be an integer...
Output : arrays [declination] [minor] [major]
"""
projectName = "tempCurveBeamDeclination"
nStep = math.floor((declinationMax - declinationMin) / decStep)
decArr = np.arange(nStep) * decStep + declinationMin
minorAxis = np.zeros(nStep)
majorAxis = np.zeros(nStep)
las100 = np.zeros(nStep)
index = 0
# simulation with one arcsec component. We clean the old files.
os.system("rm -Rf *%s*" % (projectName))
for dec in decArr:
if dec <= -10:
decString = "J2000 0h00m00s %3dd00m00s" % (dec)
elif dec < 0 and dec > -10:
decString = "J2000 0h00m00s -0%1dd00m00s" % (-dec)
elif dec >= 0 and dec < 10:
decString = "J2000 0h00m00s +0%1dd00m00s" % (dec)
elif dec >= 10:
decString = "J2000 0h00m00s +%2dd00m00s" % (dec)
# simulayion with one arcsec component
#os.system("rm -Rf *%s*"%(projectName))
print decString
#cl.done()
cl.addcomponent(dir=decString,
flux=1,
freq='100GHz',
shape="Gaussian",
majoraxis="0.1arcsec",
minoraxis="0.1arcsec",
positionangle="0deg")
cl.rename(projectName + "%d.cl" % (index))
cl.done()
print projectName + "%d.cl" % (index)
so.simobserve(project=projectName + "%d" % (index),
complist=projectName + "%d.cl" % (index),
compwidth='8GHz',
antennalist=antennaCfg,
totaltime=trackDuration,
integration='10s',
hourangle='ha')
sa.simanalyze(
project=projectName + "%d" % (index),
image=True,
weighting='briggs',
# imsize = 256,
# cell = cellsize,
# mask = maskClean,
niter=100,
# threshold = '0.1mJy',
# graphics = 'file'
)
psfName = projectName + "%d/" % (
index) + projectName + "%d.%s.psf" % (index,
antennaCfg.split('.')[0])
psfQuickName = projectName + "%d/" % (
index) + projectName + "%d.%s.quick.psf" % (
index, antennaCfg.split('.')[0])
msName = projectName + "%d/" % (
index) + projectName + "%d.%s.ms" % (index,
antennaCfg.split('.')[0])
imageName = projectName + "%d/" % (
index) + projectName + "%d.%s.noisy.image" % (
index, antennaCfg.split('.')[0])
# if os.path.exists(psfName):
# psfRes = psf.psf_calc(psfName)
# else:
# psfRes = psf.psf_calc(psfQuickName)
ia.open(imageName)
data = ia.restoringbeam()
ia.close()
print data
minorAxis[index] = data['minor']['value']
majorAxis[index] = data['major']['value']
print "minor Axis:", minorAxis[index]
print "major Axis:", majorAxis[index]
ms = uvw.UVW(msName)
dUV = ms.distUV(noShadow=True)
duvMin = min(dUV)
rds = np.sort(dUV)
nuv = len(rds)
i05 = (int)(0.05 * nuv)
L05 = rds[i05]
las = RAD2ARCSEC * 0.0017987547479999 / duvMin ## 0.6 * Lambda / BL_min
## Definition of LAS from SCIREQ-328
las100[index] = RAD2ARCSEC * 0.983296 * 0.0029979245799998332 / L05
# if las100[index] > las :
# las100[index] = las
# las100[index] = las
print "mininum BL:", duvMin
print "L05:", L05
print "LAS (old definition)", las
print "LAS (100 GHz):", las100[index]
index += 1
# fout=open("curveBeamDec.last","wb")
# data={'Dec':decArr,'Shadow':fractionShadowing}
# pickle.dump(data,fout)
# fout.close()
return (decArr, minorAxis, majorAxis, las100)
def runFiltering(self, antennaCfg, trackDuration, frequency, dec,
imageTotalSize, resolutionStart, resolutionEnd,
resolutionStep):
"""
use the disk100.fits image of a uniform disk of 100 pixel size (diameter)
Run a set of simulations to account for the filtering at different scales.
antennaCfg: antenna configuration file
trackDuration : trackDuration
resolutionStart,resolutionEnd,resolutionStep: range for the resolution to simulate
dec: declination
OUTPUT:
resolution, flux: resolution and flux output (1 Jy in entry)
"""
maskClean = [70, 70, 180, 180]
projectName = "tempCurveFiltering"
nStep = math.floor((resolutionEnd - resolutionStart) / resolutionStep)
resolutionArr = np.arange(nStep) * resolutionStep + resolutionStart
flux = np.zeros(nStep)
boxStat = '%d,%d,%d,%d' % (maskClean[0], maskClean[1], maskClean[2],
maskClean[3])
os.system("rm -Rf *%s*" % (projectName))
if dec <= -10:
decString = "J2000 10h00m00s %3dd00m00s" % (dec)
elif dec < 0 and dec > -10:
decString = "J2000 10h00m00s -0%1dd00m00s" % (-dec)
elif dec >= 0 and dec < 10:
decString = "J2000 10h00m00s +0%1dd00m00s" % (dec)
elif dec >= 10:
decString = "J2000 10h00m00s +%2dd00m00s" % (dec)
# simulayion with one arcsec component
##os.system("rm -Rf *%s*"%(projectName))
print decString
index = 0
print resolutionArr
for res in resolutionArr:
resolutionDisk = "%4.2farcsec" % (res / 100.)
print resolutionDisk
print antennaCfg
so.sim_observe(
project=projectName + "%d" % (index),
skymodel='disk100.fits',
inbright='1Jy/pixel',
indirection=decString,
incell=resolutionDisk,
incenter=frequency,
inwidth='8GHz',
antennalist=antennaCfg,
totaltime=trackDuration,
integration='10s',
direction=decString,
maptype='ALMA',
# mapsize = ['2arcmin','2arcmin'],
# pointingspacing = "2arcmin"
)
sa.sim_analyze(
project=projectName + "%d" % (index),
image=True,
imsize=imageTotalSize,
# cell = cellsize,
mask=maskClean,
niter=2000,
threshold='0.1mJy',
graphics='file')
imageName = projectName + "%d/" % (
index) + projectName + "%d.%s.image" % (
index, antennaCfg.split('.')[0])
# imageName=projectName+"%d/"%(index)+projectName+"%d.image"%(index)
print "Read %s" % (imageName)
ia.open(imageName)
# flux0=ia.statistics()['flux'][0]
stat = ims.imstat(
imagename=imageName,
box=boxStat,
)
flux0 = stat['flux'][0]
print flux0
if res == resolutionArr[0]:
fluxNormalization = flux0
fluxRes = flux0 / fluxNormalization
print "Flux: %4.3f" % (fluxRes)
flux[index] = fluxRes
ia.close()
index += 1
return (resolutionArr, flux)
def curveBeamResolutiongDeclination(self, trackDuration, declinationMin,
declinationMax, decStep):
"""
Compute the minor,Major axis vs. Declination for a given configuration
trackDuration: time duration, e.g. "6h"
declinationMin,declinationMax: range of declination
decStep: step for the declination, needs to be an integer...
Output : arrays [declination] [minor] [major]
"""
antennaCfg = self.fileCfg
print antennaCfg
projectName = "tempCurveBeamDeclination"
nStep = floor((declinationMax - declinationMin) / decStep)
decArr = np.arange(nStep) * decStep + declinationMin
minorAxis = np.zeros(nStep)
majorAxis = np.zeros(nStep)
las100 = np.zeros(nStep)
index = 0
# simulation with one arcsec component. We clean the old files.
os.system("rm -Rf *%s*" % (projectName))
for dec in decArr:
if dec <= -10:
decString = "J2000 0h00m00s %3dd00m00s" % (dec)
elif dec < 0 and dec > -10:
decString = "J2000 0h00m00s -0%1dd00m00s" % (-dec)
elif dec >= 0 and dec < 10:
decString = "J2000 0h00m00s +0%1dd00m00s" % (dec)
elif dec >= 10:
decString = "J2000 0h00m00s +%2dd00m00s" % (dec)
# simulayion with one arcsec component
#os.system("rm -Rf *%s*"%(projectName))
print decString
#cl.done()
cl.addcomponent(dir=decString,
flux=1,
freq='100GHz',
shape="Gaussian",
majoraxis="0.1arcsec",
minoraxis="0.1arcsec",
positionangle="0deg")
cl.rename(projectName + "%d.cl" % (index))
cl.done()
print projectName + "%d.cl" % (index)
sim = inspect.getargspec(casa.simobserve)
ind = 0
for arg in sim.args:
casa.simobserve.__setattr__(arg, sim.defaults[ind])
ind += 1
casa.simobserve.__setattr__('project',
projectName + "%d" % (index))
casa.simobserve.__setattr__('complist',
projectName + "%d.cl" % (index))
casa.simobserve.__setattr__('compwidth', '8GHz')
casa.simobserve.__setattr__('antennalist', antennaCfg)
casa.simobserve.__setattr__('totaltime', trackDuration)
casa.simobserve.__setattr__('integration', '10s')
casa.simobserve(antennalist='best-O-1_step2_88.cfg',
complist='tempCurveBeamDeclination0.cl')
simanalyze(
project=projectName + "%d" % (index),
image=True,
weighting='briggs',
# imsize = 256,
# cell = cellsize,
# mask = maskClean,
niter=100,
# threshold = '0.1mJy',
# graphics = 'file'
)
psfName = projectName + "%d/" % (
index) + projectName + "%d.%s.psf" % (index,
antennaCfg.split('.')[0])
psfQuickName = projectName + "%d/" % (
index) + projectName + "%d.%s.quick.psf" % (
index, antennaCfg.split('.')[0])
msName = projectName + "%d/" % (
index) + projectName + "%d.%s.ms" % (index,
antennaCfg.split('.')[0])
imageName = projectName + "%d/" % (
index) + projectName + "%d.%s.image" % (
index, antennaCfg.split('.')[0])
# if os.path.exists(psfName):
# psfRes = psf.psf_calc(psfName)
# else:
# psfRes = psf.psf_calc(psfQuickName)
ia.open(imageName)
data = ia.restoringbeam()
ia.close()
print data
minorAxis[index] = data['minor']['value']
majorAxis[index] = data['major']['value']
print "minor Axis:", minorAxis[index]
print "major Axis:", majorAxis[index]
ms = uvw.UVW(msName)
dUV = ms.distUV(noShadow=True)
duvMin = min(dUV)
las100[
index] = RAD2ARCSEC * 0.0017987547479999 / duvMin ## 0.6 * Lambda / BL_min
print "mininum BL:", duvMin
print "LAS (100 GHz):", las100[index]
index += 1
# fout=open("curveBeamDec.last","wb")
# data={'Dec':decArr,'Shadow':fractionShadowing}
# pickle.dump(data,fout)
# fout.close()
return (decArr, minorAxis, majorAxis, las100)
def blankcube(image,
dummyMS,
smooth=True,
verbose=True,
region='centerbox[[10h21m45s,18.05.14.9],[15arcmin,15arcmin]]',
ruthless=False,
extension='.image',
beamround='int',
blankThreshold=2.5,
moments=[0]):
'''
Parameters
----------
image : string
Base name of image. If target image has extension other than '.image',
change the extension keyword.
dummyMS : string
MS file required for blanking process in CASA
smooth : bool, optional
Smooth the image to a circular beam before blanking?
Default True
verbose : bool, optional
region : string, optional
region parameter featured in CASA
ruthless : bool, optional
Delete previous outputs from blankcube
extension : string, optional
Extension of the target image. Must include the '.', e.g., '.restored'
Default '.image'
beamround : string,float
P
blankThreshold : float, optional
Initial blanking threshold of all pixels scaled by the standard
deviation times the blankingthreshold
Default = 2.5 (Walter et al. 2008)
moments : list, optional
Moments to calculate from cube. Options are 0,1,2.
Example: [0,1,2]
Default: [0]
Returns
-------
out : null
Examples
--------
'''
from casa import immath, imsmooth, immoments
from casa import image as ia
from casa import imager as im
from casa import quanta as qa
import os
import numpy as np
# Delete files associated with previous runs
if ruthless:
os.system('rm -rf ' + image + '.smooth.blk.image')
os.system('rm -rf ' + image + '.smooth.image')
os.system('rm -rf ' + image + '.blk.image')
os.system('rm -rf ' + image + '.mask')
imageDir = './'
# Create moment maps
mom0, mom1, mom2 = False, False, False
if len(moments) > 0:
for i, moment in enumerate(moments):
if moment == 0:
mom0 = True
if moment == 1:
mom1 = True
if moment == 2:
mom2 = True
if mom1 == True or mom2 == True:
beamScale = 1.01
elif mom0 == True:
beamScale = 2.
# determine beamsize of cube
ia.open(imageDir + image + extension)
beamsizes = np.zeros(ia.shape()[2])
for i in range(ia.shape()[2]):
beamsizes[i] = ia.restoringbeam(channel=i)['major']['value']
beamsizeUnit = ia.restoringbeam(channel=i)['major']['unit']
beamsize = qa.convert(str(beamsizes.max()) + beamsizeUnit,
'arcsec')['value']
if type(beamround) == float:
beamsize_smooth = beamround * beamsize
else:
beamsize_smooth = np.ceil(beamsize) #beamsize_smooth = 1.01 * beamsize
ia.close()
if verbose:
print 'Max beamsize is ' + str(beamsize) + '"'
if not os.path.exists(image + '.blk.image'):
# create cube for blanking
if smooth: # smooth to a larger beam if the user desires
if verbose:
print 'Convolving to ' + str(beamsize_smooth) + '"'
imsmooth(imagename=image + extension,
outfile=image + '.blk.image',
major=str(beamsize_smooth) + 'arcsec',
minor=str(beamsize_smooth) + 'arcsec',
region=region,
pa='0deg',
targetres=True)
else: # do no smooth
immath(imagename=image + extension,
outfile=image + '.blk.image',
mode='evalexpr',
region=region,
expr='IM0')
if not os.path.exists(image + '.smooth.image'):
# convolve cube to 2X beam for blanking
imsmooth(imagename=image + extension,
outfile=image + '.smooth.image',
major=str(beamsize * beamScale) + 'arcsec',
minor=str(beamsize * beamScale) + 'arcsec',
pa='0deg',
region=region,
targetres=True)
# determine threshold of cube
ia.open(image + '.smooth.image')
threshold = ia.statistics()['sigma'][0] * blankThreshold
ia.close()
# blank the cube at threshold*sigma
ia.open(image + '.smooth.image')
ia.calcmask(mask=image + '.smooth.image > ' + str(threshold), name='mask1')
wait = 'waits for calcmask to close'
ia.close()
# hand blank the cube
im.open(dummyMS)
pause = None
while pause is None:
im.drawmask(image=image + '.smooth.image', mask=image + '.mask')
pause = 0
im.close
# mask contains values of 0 and 1, change to a mask with only values of 1
ia.open(image + '.mask')
ia.calcmask(image + '.mask' + '>0.5')
ia.close()
# apply mask on smoothed image
immath(imagename=image + '.smooth.image',
outfile=image + '.smooth.blk.image',
mode='evalexpr',
mask='mask(' + image + '.mask)',
expr='IM0')
# apply mask on image
ia.open(imageDir + image + '.blk.image')
ia.maskhandler('copy', [image + '.smooth.blk.image:mask0', 'newmask'])
ia.maskhandler('set', 'newmask')
ia.done()
cube = '.blk.image' # specify name of cube for moment calculation
# create moment 0 map
if mom0:
if ruthless:
os.system('rm -rf ' + image + '.mom0.image')
immoments(imagename=image + cube,
moments=[0],
axis='spectra',
chans='',
mask='mask(' + image + cube + ')',
outfile=image + '.mom0.image')
# create moment 1 map
if mom1:
if ruthless:
os.system('rm -rf ' + image + '.mom1.image')
immoments(imagename=image + cube,
moments=[1],
axis='spectra',
chans='',
mask='mask(' + image + cube + ')',
outfile=image + '.mom1.image')
# create moment 2 map
if mom2:
if ruthless:
os.system('rm -rf ' + image + '.mom2.image')
immoments(imagename=image + cube,
moments=[2],
axis='spectra',
chans='',
mask='mask(' + image + cube + ')',
outfile=image + '.mom2.image')
if verbose and mom0:
from casa import imstat
flux = imstat(image + '.mom0.image')['flux'][0]
ia.open(image + '.mom0.image')
beammaj = ia.restoringbeam(channel=0)['major']['value']
beammin = ia.restoringbeam(channel=0)['minor']['value']
beamsizeUnit = ia.restoringbeam(channel=0)['major']['unit']
ia.close()
print 'Moment Image: ' + str(image) + '.mom0.image'
print 'Beamsize: ' + str(beammaj) + '" X ' + str(beammin) + '"'
print 'Flux: ' + str(flux) + ' Jy km/s'
def blankcube(image,
dummyMS,
smooth=True,
verbose=True,
region='centerbox[[10h21m45s,18.05.14.9],[15arcmin,15arcmin]]',
ruthless=False,
extension='.image',
beamround='int',
blankThreshold=2.5,
moments=[0]):
'''
Parameters
----------
image : string
Base name of image. If target image has extension other than '.image',
change the extension keyword.
dummyMS : string
MS file required for blanking process in CASA
smooth : bool, optional
Smooth the image to a circular beam before blanking?
Default True
verbose : bool, optional
region : string, optional
region parameter featured in CASA
ruthless : bool, optional
Delete previous outputs from blankcube
extension : string, optional
Extension of the target image. Must include the '.', e.g., '.restored'
Default '.image'
beamround : string,float
P
blankThreshold : float, optional
Initial blanking threshold of all pixels scaled by the standard
deviation times the blankingthreshold
Default = 2.5 (Walter et al. 2008)
moments : list, optional
Moments to calculate from cube. Options are 0,1,2.
Example: [0,1,2]
Default: [0]
Returns
-------
out : null
Examples
--------
'''
from casa import immath,imsmooth,immoments
from casa import image as ia
from casa import imager as im
from casa import quanta as qa
import os
import numpy as np
# Delete files associated with previous runs
if ruthless:
os.system('rm -rf ' + image + '.smooth.blk.image')
os.system('rm -rf ' + image + '.smooth.image')
os.system('rm -rf ' + image + '.blk.image')
os.system('rm -rf ' + image + '.mask')
imageDir = './'
# Create moment maps
mom0,mom1,mom2 = False,False,False
if len(moments) > 0:
for i, moment in enumerate(moments):
if moment == 0:
mom0 = True
if moment == 1:
mom1 = True
if moment == 2:
mom2 = True
if mom1 == True or mom2 == True:
beamScale = 1.01
elif mom0 == True:
beamScale = 2.
# determine beamsize of cube
ia.open(imageDir + image + extension)
beamsizes = np.zeros(ia.shape()[2])
for i in range(ia.shape()[2]):
beamsizes[i] = ia.restoringbeam(channel=i)['major']['value']
beamsizeUnit = ia.restoringbeam(channel=i)['major']['unit']
beamsize = qa.convert(str(beamsizes.max()) + beamsizeUnit,'arcsec')['value']
if type(beamround) == float:
beamsize_smooth = beamround*beamsize
else:
beamsize_smooth = np.ceil(beamsize) #beamsize_smooth = 1.01 * beamsize
ia.close()
if verbose:
print 'Max beamsize is ' + str(beamsize) + '"'
if not os.path.exists(image + '.blk.image'):
# create cube for blanking
if smooth: # smooth to a larger beam if the user desires
if verbose:
print 'Convolving to ' + str(beamsize_smooth) + '"'
imsmooth(imagename=image + extension,
outfile=image + '.blk.image',
major=str(beamsize_smooth) + 'arcsec',
minor=str(beamsize_smooth) + 'arcsec',
region=region,
pa='0deg',
targetres=True)
else: # do no smooth
immath(imagename=image + extension,
outfile=image + '.blk.image',
mode='evalexpr',
region=region,
expr='IM0')
if not os.path.exists(image + '.smooth.image'):
# convolve cube to 2X beam for blanking
imsmooth(imagename=image + extension,
outfile=image + '.smooth.image',
major=str(beamsize*beamScale) + 'arcsec',
minor=str(beamsize*beamScale) + 'arcsec',
pa='0deg',
region=region,
targetres=True)
# determine threshold of cube
ia.open(image + '.smooth.image')
threshold = ia.statistics()['sigma'][0] * blankThreshold
ia.close()
# blank the cube at threshold*sigma
ia.open(image + '.smooth.image')
ia.calcmask(mask=image + '.smooth.image > ' + str(threshold),
name='mask1')
wait = 'waits for calcmask to close'
ia.close()
# hand blank the cube
im.open(dummyMS)
pause = None
while pause is None:
im.drawmask(image=image + '.smooth.image',
mask=image + '.mask')
pause = 0
im.close
# mask contains values of 0 and 1, change to a mask with only values of 1
ia.open(image + '.mask')
ia.calcmask(image + '.mask' + '>0.5')
ia.close()
# apply mask on smoothed image
immath(imagename=image + '.smooth.image',
outfile=image + '.smooth.blk.image',
mode='evalexpr',
mask='mask(' + image + '.mask)',
expr='IM0')
# apply mask on image
ia.open(imageDir + image + '.blk.image')
ia.maskhandler('copy',[image + '.smooth.blk.image:mask0', 'newmask'])
ia.maskhandler('set','newmask')
ia.done()
cube = '.blk.image' # specify name of cube for moment calculation
# create moment 0 map
if mom0:
if ruthless:
os.system('rm -rf ' + image + '.mom0.image')
immoments(imagename=image + cube,
moments=[0],
axis='spectra',
chans='',
mask='mask(' + image + cube + ')',
outfile=image + '.mom0.image')
# create moment 1 map
if mom1:
if ruthless:
os.system('rm -rf ' + image + '.mom1.image')
immoments(imagename=image + cube,
moments=[1],
axis='spectra',
chans='',
mask='mask(' + image + cube + ')',
outfile=image + '.mom1.image')
# create moment 2 map
if mom2:
if ruthless:
os.system('rm -rf ' + image + '.mom2.image')
immoments(imagename=image + cube,
moments=[2],
axis='spectra',
chans='',
mask='mask(' + image + cube + ')',
outfile=image + '.mom2.image')
if verbose and mom0:
from casa import imstat
flux = imstat(image + '.mom0.image')['flux'][0]
ia.open(image + '.mom0.image')
beammaj = ia.restoringbeam(channel=0)['major']['value']
beammin = ia.restoringbeam(channel=0)['minor']['value']
beamsizeUnit = ia.restoringbeam(channel=0)['major']['unit']
ia.close()
print 'Moment Image: ' + str(image) + '.mom0.image'
print 'Beamsize: ' + str(beammaj) + '" X ' + str(beammin) + '"'
print 'Flux: ' + str(flux) + ' Jy km/s'