def cleanup(self):
# finalize image analysis tool
if hasattr(self, "image") and self.image is not None:
if self.image.isopen():
self.image.done()
tools = ["convimage", "imageorg", "realimage", "imagimage"]
for t in tools:
if hasattr(self, t):
v = getattr(self, t)
if v and v.isopen():
v.done(remove=True)
# remove tempolary files
filelist = ["tmpmskname", "tmpconvname", "tmppolyname", "tmprealname", "tmpimagname"]
existing_files = []
for s in filelist:
if hasattr(self, s):
f = getattr(self, s)
if isinstance(f, list):
for g in f:
if os.path.exists(g):
existing_files.append(g)
else:
if os.path.exists(f):
existing_files.append(f)
# CAS-5410 Use private tools inside task scripts
if len(existing_files) > 0:
cu = utilstool()
cu.removetable(existing_files)
def cleanup(self):
# finalize image analysis tool
if hasattr(self,'image') and self.image is not None:
if self.image.isopen(): self.image.done()
tools = ['convimage', 'imageorg', 'realimage', 'imagimage']
for t in tools:
if hasattr(self,t):
v = getattr(self,t)
if v and v.isopen():
v.done(remove=True)
# remove tempolary files
filelist = ['tmpmskname', 'tmpconvname', 'tmppolyname',
'tmprealname', 'tmpimagname']
existing_files = []
for s in filelist:
if hasattr(self, s):
f = getattr(self, s)
if isinstance(f,list):
for g in f:
if os.path.exists(g):
existing_files.append(g)
else:
if os.path.exists(f):
existing_files.append(f)
# CAS-5410 Use private tools inside task scripts
if len(existing_files) > 0:
cu = utilstool()
cu.removetable(existing_files)
def __polynomial_fit_model(self, image=None, model=None, axis=0, order=2):
if not image or not os.path.exists(image):
raise RuntimeError, "No image found to fit."
if os.path.exists(model):
# CAS-5410 Use private tools inside task scripts
cu = utilstool()
cu.removetable([model])
tmpia = gentools(['ia'])[0]
modelimg = tmpia.newimagefromimage(infile=image, outfile=model)
try:
if tmpia.isopen(): tmpia.close()
imshape = modelimg.shape()
# the axis order of [ra, dec, chan(, pol)] is assumed throughout the task.
ndim = len(imshape)
nx = imshape[0]
ny = imshape[1]
# an xy-plane can be fit simultaneously (doing per plane to save memory)
if ndim == 3:
get_blc = lambda i, j: [0, 0, i]
get_trc = lambda i, j: [nx - 1, ny - 1, i]
imshape2 = imshape[2]
imshape3 = 1
elif ndim == 4:
get_blc = lambda i, j: [0, 0, i, j]
get_trc = lambda i, j: [nx - 1, ny - 1, i, j]
imshape2 = imshape[2]
imshape3 = imshape[3]
else: # ndim == 2
get_blc = lambda i, j: [0, 0]
get_trc = lambda i, j: [nx - 1, ny - 1]
imshape2 = 1
imshape3 = 1
for i3 in range(imshape3):
for i2 in range(imshape2):
blc = get_blc(i2, i3)
trc = get_trc(i2, i3)
dslice = modelimg.getchunk(blc, trc)
mslice = modelimg.getchunk(blc, trc, getmask=True)
model = self._get_polyfit_model_array(
dslice.reshape(nx, ny), mslice.reshape(nx, ny), axis,
order)
modelimg.putchunk(model, blc)
# the fit model image itself is free from invalid pixels
modelimg.calcmask('T', asdefault=True)
except:
raise
finally:
modelimg.close()
def __polynomial_fit_model(self, image=None, model=None, axis=0, order=2):
if not image or not os.path.exists(image):
raise RuntimeError, "No image found to fit."
if os.path.exists(model):
# CAS-5410 Use private tools inside task scripts
cu = utilstool()
cu.removetable([model])
tmpia = gentools(['ia'])[0]
modelimg = tmpia.newimagefromimage(infile=image, outfile=model)
try:
if tmpia.isopen(): tmpia.close()
imshape = modelimg.shape()
# the axis order of [ra, dec, chan(, pol)] is assumed throughout the task.
ndim = len(imshape)
nx = imshape[0]
ny = imshape[1]
# an xy-plane can be fit simultaneously (doing per plane to save memory)
if ndim == 3:
for ichan in range(imshape[2]):
dslice = modelimg.getchunk([0, 0, ichan],
[nx - 1, ny - 1, ichan])
mslice = modelimg.getchunk([0, 0, ichan],
[nx - 1, ny - 1, ichan],
getmask=True)
model = self._get_polyfit_model_array(
dslice.reshape(nx, ny), mslice.reshape(nx, ny), axis,
order)
modelimg.putchunk(model, [0, 0, ichan, ipol])
elif ndim == 4:
for ipol in range(imshape[3]):
for ichan in range(imshape[2]):
dslice = modelimg.getchunk(
[0, 0, ichan, ipol], [nx - 1, ny - 1, ichan, ipol])
mslice = modelimg.getchunk(
[0, 0, ichan, ipol], [nx - 1, ny - 1, ichan, ipol],
getmask=True)
model = self._get_polyfit_model_array(
dslice.reshape(nx, ny), mslice.reshape(nx, ny),
axis, order)
modelimg.putchunk(model, [0, 0, ichan, ipol])
else:
# ndim=2 is not supported in this task.
raise RuntimeError, "image dimension should be 3 or 4"
# the fit model image itself is free from invalid pixels
modelimg.calcmask('T', asdefault=True)
except:
raise
finally:
modelimg.close()
def __polynomial_fit_model(self, image=None, model=None, axis=0, order=2):
if not image or not os.path.exists(image):
raise RuntimeError, "No image found to fit."
if os.path.exists( model ):
# CAS-5410 Use private tools inside task scripts
cu = utilstool()
cu.removetable([model])
tmpia = gentools(['ia'])[0]
modelimg = tmpia.newimagefromimage(infile=image,outfile=model)
try:
if tmpia.isopen(): tmpia.close()
imshape = modelimg.shape()
# the axis order of [ra, dec, chan(, pol)] is assumed throughout the task.
ndim = len(imshape)
nx = imshape[0]
ny = imshape[1]
# an xy-plane can be fit simultaneously (doing per plane to save memory)
if ndim == 3:
get_blc = lambda i, j: [0, 0, i]
get_trc = lambda i, j: [nx-1, ny-1, i]
imshape2 = imshape[2]
imshape3 = 1
elif ndim == 4:
get_blc = lambda i, j: [0, 0, i, j]
get_trc = lambda i, j: [nx-1, ny-1, i, j]
imshape2 = imshape[2]
imshape3 = imshape[3]
else: # ndim == 2
get_blc = lambda i, j: [0,0]
get_trc = lambda i, j: [nx-1, ny-1]
imshape2 = 1
imshape3 = 1
for i3 in range(imshape3):
for i2 in range(imshape2):
blc = get_blc(i2, i3)
trc = get_trc(i2, i3)
dslice = modelimg.getchunk(blc, trc)
mslice = modelimg.getchunk(blc, trc, getmask=True)
model = self._get_polyfit_model_array(dslice.reshape(nx,ny),
mslice.reshape(nx,ny),
axis, order)
modelimg.putchunk(model, blc)
# the fit model image itself is free from invalid pixels
modelimg.calcmask('T', asdefault=True)
except: raise
finally: modelimg.close()
def __polynomial_fit_model(self, image=None, model=None, axis=0, order=2):
if not image or not os.path.exists(image):
raise RuntimeError, "No image found to fit."
if os.path.exists(model):
# CAS-5410 Use private tools inside task scripts
cu = utilstool()
cu.removetable([model])
tmpia = gentools(["ia"])[0]
modelimg = tmpia.newimagefromimage(infile=image, outfile=model)
try:
if tmpia.isopen():
tmpia.close()
imshape = modelimg.shape()
# the axis order of [ra, dec, chan(, pol)] is assumed throughout the task.
ndim = len(imshape)
nx = imshape[0]
ny = imshape[1]
# an xy-plane can be fit simultaneously (doing per plane to save memory)
if ndim == 3:
for ichan in range(imshape[2]):
dslice = modelimg.getchunk([0, 0, ichan], [nx - 1, ny - 1, ichan])
mslice = modelimg.getchunk([0, 0, ichan], [nx - 1, ny - 1, ichan], getmask=True)
model = self._get_polyfit_model_array(dslice.reshape(nx, ny), mslice.reshape(nx, ny), axis, order)
modelimg.putchunk(model, [0, 0, ichan, ipol])
elif ndim == 4:
for ipol in range(imshape[3]):
for ichan in range(imshape[2]):
dslice = modelimg.getchunk([0, 0, ichan, ipol], [nx - 1, ny - 1, ichan, ipol])
mslice = modelimg.getchunk([0, 0, ichan, ipol], [nx - 1, ny - 1, ichan, ipol], getmask=True)
model = self._get_polyfit_model_array(
dslice.reshape(nx, ny), mslice.reshape(nx, ny), axis, order
)
modelimg.putchunk(model, [0, 0, ichan, ipol])
else:
# ndim=2 is not supported in this task.
raise RuntimeError, "image dimension should be 3 or 4"
# the fit model image itself is free from invalid pixels
modelimg.calcmask("T", asdefault=True)
except:
raise
finally:
modelimg.close()
def __execute_press(self):
###
# Pressed-out method (Sofue & Reich 1979)
###
casalog.post("Apply Pressed-out method")
# CAS-5410 Use private tools inside task scripts
ia = gentools(["ia"])[0]
# mask
self.image = ia.newimagefromimage(infile=self.infiles, outfile=self.tmpmskname)
# back-up original mask name
is_initial_mask = self.image.maskhandler("default")[0] != ""
temp_maskname = "temporal"
imshape = self.image.shape()
nx = imshape[0]
ny = imshape[1]
nchan = imshape[2]
if len(self.thresh) == 0:
casalog.post("Use whole region")
else:
# mask pixels beyond thresholds
maskstr = "mask('%s')" % self.tmpmskname
if self.thresh[0] != self.nolimit:
maskstr += " && '%s'>=%f" % (self.tmpmskname, self.thresh[0])
if self.thresh[1] != self.nolimit:
maskstr += " && '%s'<=%f" % (self.tmpmskname, self.thresh[1])
# Need to flush to image once to calcmask ... sigh
self.image.done()
self.image = ia.newimage(self.tmpmskname)
self.image.calcmask(mask=maskstr, name=temp_maskname, asdefault=True)
# smoothing
# bmajor = 0.0
# bminor = 0.0
# CAS-5410 Use private tools inside task scripts
qa = qatool()
if type(self.beamsize) == str:
qbeamsize = qa.quantity(self.beamsize)
else:
qbeamsize = qa.quantity(self.beamsize, "arcsec")
if type(self.smoothsize) == str:
# bmajor = smoothsize
# bminor = smoothsize
qsmoothsize = qa.quantity(self.smoothsize)
else:
# bmajor = '%sarcsec' % (beamsize*smoothsize)
# bminor = '%sarcsec' % (beamsize*smoothsize)
qsmoothsize = qa.mul(qbeamsize, self.smoothsize)
bmajor = qsmoothsize
bminor = qsmoothsize
# masked channels are replaced by zero and convolved here.
self.convimage = self.image.convolve2d(outfile=self.tmpconvname, major=bmajor, minor=bminor, overwrite=True)
self.convimage.done()
self.convimage = ia.newimage(self.tmpconvname)
# get dTij (original - smoothed)
if len(imshape) == 4:
# with polarization axis
npol = imshape[3]
for ichan in range(nchan):
for ipol in range(npol):
pixmsk = self.image.getchunk([0, 0, ichan, ipol], [nx - 1, ny - 1, ichan, ipol])
pixsmo = self.convimage.getchunk([0, 0, ichan, ipol], [nx - 1, ny - 1, ichan, ipol])
pixsub = pixmsk - pixsmo
self.convimage.putchunk(pixsub, [0, 0, ichan, ipol])
elif len(imshape) == 3:
for ichan in range(nchan):
# no polarization axis
pixmsk = self.image.getchunk([0, 0, ichan], [nx - 1, ny - 1, ichan])
pixsmo = self.convimage.getchunk([0, 0, ichan], [nx - 1, ny - 1, ichan])
pixsub = pixmsk - pixsmo
self.convimage.putchunk(pixsub, [0, 0, ichan])
# polynomial fit
fitaxis = 0
if self.direction == 0.0:
fitaxis = 0
elif self.direction == 90.0:
fitaxis = 1
else:
raise Exception, "Sorry, the task don't support inclined scan with respect to horizontal or vertical axis, right now."
# Replace duplicated method ia.fitpolynomial with
# ia.fitprofile
# polyimage = convimage.fitpolynomial( fitfile=tmppolyname, axis=fitaxis, order=numpoly, overwrite=True )
# polyimage.done()
if os.path.exists(self.tmppolyname):
# CAS-5410 Use private tools inside task scripts
cu = utilstool()
cu.removetable([self.tmppolyname])
self.convimage.setbrightnessunit("K")
# Unfortunately, ia.fitprofile is very fragile.
# Using numpy instead for fitting with masked pixels (KS, 2014/07/02)
# resultdic = self.convimage.fitprofile( model=self.tmppolyname, axis=fitaxis, poly=self.numpoly, ngauss=0, multifit=True, gmncomps=0 )
self.__polynomial_fit_model(image=self.tmpmskname, model=self.tmppolyname, axis=fitaxis, order=self.numpoly)
polyimage = ia.newimage(self.tmppolyname)
# set back defalut mask (need to get from self.image)
avail_mask = polyimage.maskhandler("get")
if is_initial_mask:
casalog.post("copying mask from %s" % (self.infiles))
polyimage.calcmask("mask('%s')" % self.infiles, asdefault=True)
else: # no mask in the original image
polyimage.calcmask("T", asdefault=True)
if temp_maskname in avail_mask:
polyimage.maskhandler("delete", name=temp_maskname)
# subtract fitted image from original map
imageorg = ia.newimage(self.infiles)
if len(imshape) == 4:
# with polarization axis
npol = imshape[3]
for ichan in range(nchan):
for ipol in range(npol):
pixorg = imageorg.getchunk([0, 0, ichan, ipol], [nx - 1, ny - 1, ichan, ipol])
pixpol = polyimage.getchunk([0, 0, ichan, ipol], [nx - 1, ny - 1, ichan, ipol])
pixsub = pixorg - pixpol
polyimage.putchunk(pixsub, [0, 0, ichan, ipol])
elif len(imshape) == 3:
# no polarization axis
for ichan in range(nchan):
pixorg = imageorg.getchunk([0, 0, ichan], [nx - 1, ny - 1, ichan])
pixpol = polyimage.getchunk([0, 0, ichan], [nx - 1, ny - 1, ichan])
pixsub = pixorg - pixpol
polyimage.putchunk(pixsub, [0, 0, ichan])
# output
polyimage.rename(self.outfile, overwrite=self.overwrite)
polyimage.done()
self.convimage.done(remove=True)
self.image.done()
imageorg.done()
def __execute_press(self):
###
# Pressed-out method (Sofue & Reich 1979)
###
casalog.post( 'Apply Pressed-out method' )
# CAS-5410 Use private tools inside task scripts
ia = gentools(['ia'])[0]
# mask
self.image = ia.newimagefromimage(infile=self.infiles,outfile=self.tmpmskname)
# back-up original mask name
is_initial_mask = (self.image.maskhandler('default')[0] != '')
temp_maskname = "temporal"
imshape = self.image.shape()
ndim = len(imshape)
nx = imshape[0]
ny = imshape[1]
if len(self.thresh) == 0:
casalog.post( 'Use whole region' )
else:
# mask pixels beyond thresholds
maskstr = ("mask('%s')" % self.tmpmskname)
if self.thresh[0] != self.nolimit:
maskstr += (" && '%s'>=%f" % (self.tmpmskname, self.thresh[0]))
if self.thresh[1] != self.nolimit:
maskstr += (" && '%s'<=%f" % (self.tmpmskname, self.thresh[1]))
# Need to flush to image once to calcmask ... sigh
self.image.done()
self.image = ia.newimage( self.tmpmskname )
self.image.calcmask(mask=maskstr, name=temp_maskname, asdefault=True)
# smoothing
#bmajor = 0.0
#bminor = 0.0
# CAS-5410 Use private tools inside task scripts
qa = qatool()
if type(self.beamsize) == str:
qbeamsize = qa.quantity(self.beamsize)
else:
qbeamsize = qa.quantity(self.beamsize,'arcsec')
if type(self.smoothsize) == str:
#bmajor = smoothsize
#bminor = smoothsize
qsmoothsize = qa.quantity(self.smoothsize)
else:
#bmajor = '%sarcsec' % (beamsize*smoothsize)
#bminor = '%sarcsec' % (beamsize*smoothsize)
qsmoothsize = qa.mul(qbeamsize,self.smoothsize)
bmajor = qsmoothsize
bminor = qsmoothsize
pa = qa.quantity(0.0, 'deg')
# masked channels are replaced by zero and convolved here.
self.convimage = self.image.convolve2d( outfile=self.tmppolyname, major=bmajor, minor=bminor, pa=pa,
overwrite=True )
self.convimage.done()
# get dTij (original - smoothed)
self.convimage = ia.imagecalc(outfile=self.tmpconvname,
pixels='"{org}" - "{conv}"'.format(org=self.tmpmskname,
conv=self.tmppolyname),
overwrite=True)
# polynomial fit
fitaxis = 0
if self.direction == 0.0:
fitaxis = 0
elif self.direction == 90.0:
fitaxis = 1
else:
raise Exception, "Sorry, the task don't support inclined scan with respect to horizontal or vertical axis, right now."
# Replace duplicated method ia.fitpolynomial with
# ia.fitprofile
#polyimage = convimage.fitpolynomial( fitfile=tmppolyname, axis=fitaxis, order=numpoly, overwrite=True )
#polyimage.done()
if os.path.exists( self.tmppolyname ):
# CAS-5410 Use private tools inside task scripts
cu = utilstool()
cu.removetable([self.tmppolyname])
self.convimage.setbrightnessunit('K')
# Unfortunately, ia.fitprofile is very fragile.
# Using numpy instead for fitting with masked pixels (KS, 2014/07/02)
#resultdic = self.convimage.fitprofile( model=self.tmppolyname, axis=fitaxis, poly=self.numpoly, ngauss=0, multifit=True, gmncomps=0 )
self.__polynomial_fit_model(image=self.tmpmskname, model=self.tmppolyname,axis=fitaxis, order=self.numpoly)
polyimage = ia.newimage( self.tmppolyname )
# set back defalut mask (need to get from self.image)
avail_mask = polyimage.maskhandler('get')
if is_initial_mask:
casalog.post("copying mask from %s"%(self.infiles))
polyimage.calcmask("mask('%s')"%self.infiles,asdefault=True)
else: #no mask in the original image
polyimage.calcmask('T', asdefault=True)
if temp_maskname in avail_mask:
polyimage.maskhandler('delete', name=temp_maskname)
# subtract fitted image from original map
subtracted = ia.imagecalc(outfile=self.outfile,
pixels='"{org}" - "{fit}"'.format(org=self.infiles,
fit=self.tmppolyname),
overwrite=self.overwrite)
subtracted.done()
# finalization
polyimage.done(remove=True)
self.convimage.done(remove=True)
self.image.done()
