from __future__ import absolute_import
from casatasks.private.casa_transition import is_CASA6
from casatools import synthesisimager, synthesisnormalizer
from casatasks import casalog
from .imager_base import PySynthesisImager
from .parallel_imager_helper import PyParallelImagerHelper
synth_imager_name = 'synthesisimager'
synth_imager_import = 'from casatools import synthesisimager'
from imagerhelpers.imager_base import PySynthesisImager
from imagerhelpers.parallel_imager_helper import PyParallelImagerHelper
synthesisimager = casac.synthesisimager
synthesisnormalizer = casac.synthesisnormalizer
synth_imager_name = 'casac.synthesisimager'
synth_imager_import = 'pass'
An implementation of parallel continuum imaging, using synthesisxxxx tools
Datasets are partitioned by row and major cycles are parallelized.
Gathers and normalization are done before passing the images to a
non-parallel minor cycle. The output model image is them scattered to
all the nodes for the next parallel major cycle.
There are N synthesisimager objects.
There is 1 instance per image field, of the normalizer and deconvolver.
class PyParallelContSynthesisImager(PySynthesisImager):
def __init__(self,params=None):
PySynthesisImager.__init__(self,params)
self.PH = PyParallelImagerHelper()
self.selpars = self.allselpars;
self.allselpars = self.PH.partitionContDataSelection(self.allselpars)
self.listOfNodes = self.PH.getNodeList();