import os
import numpy
from . import display as rmsimages
import pipeline.infrastructure.logging as logging
import pipeline.infrastructure.renderer.basetemplates as basetemplates
from pipeline.infrastructure import casa_tools
LOG = logging.get_logger(__name__)
[docs]class T2_4MDetailsMakermsimagesRenderer(basetemplates.T2_4MDetailsDefaultRenderer):
def __init__(self, uri='makermsimages.mako',
description='Produce rms images',
always_rerender=False):
super(T2_4MDetailsMakermsimagesRenderer, self).__init__(uri=uri,
description=description, always_rerender=always_rerender)
[docs] def update_mako_context(self, ctx, context, results):
weblog_dir = os.path.join(context.report_dir,
'stage%s' % results.stage_number)
# There is only ever one MakermsimagesResults in the ResultsList as it
# operates over multiple measurement sets, so we can set the result to
# the first item in the list
# Get results info
info_dict = {}
# Holds a mapping of image name to image stats. This information is used to scale the MOM8 images.
image_stats = {}
rmsplots = {}
for r in results:
rmsimagenames = r.rmsimagenames
for rmsimagename in rmsimagenames:
image_path = rmsimagename
LOG.info('Getting properties of %s for the weblog.' % (image_path))
with casa_tools.ImageReader(image_path) as image:
info = image.miscinfo()
spw = info.get('spw', None)
field = ''
#if 'field' in info:
# field = '%s (%s)' % (info['field'], r.intent)
coordsys = image.coordsys()
coord_names = numpy.array(coordsys.names())
coord_refs = coordsys.referencevalue(format='s')
coordsys.done()
pol = coord_refs['string'][coord_names == 'Stokes'][0]
info_dict[(field, spw, pol, 'image name')] = image.name(strippath=True)
stats = image.statistics(robust=False)
beam = image.restoringbeam()
# Make the plots of the rms images
plotter = rmsimages.RmsimagesSummary(context, r)
plots = plotter.plot()
ms = os.path.basename(r.inputs['vis'])
rmsplots[ms] = plots
ctx.update({'rmsplots' : rmsplots,
'info_dict' : info_dict,
'dirname' : weblog_dir,
'plotter' : plotter})