def test_readwriteskymodel_no_image(self):
vis = create_blockvisibility(
self.midcore,
self.times,
self.frequency,
channel_bandwidth=self.channel_bandwidth,
phasecentre=self.phasecentre,
polarisation_frame=PolarisationFrame("linear"),
weight=1.0)
gt = create_gaintable_from_blockvisibility(vis, timeslice='auto')
gt = simulate_gaintable(gt, phase_error=1.0, amplitude_error=0.1)
sm = SkyModel(components=[self.comp], gaintable=gt)
config = {
"buffer": {
"directory": self.dir
},
"skymodel": {
"name": "test_bufferskymodel.hdf",
"data_model": "SkyModel"
}
}
bdm = BufferSkyModel(config["buffer"], config["skymodel"], sm)
bdm.sync()
new_bdm = BufferSkyModel(config["buffer"], config["skymodel"])
new_bdm.sync()
newsm = bdm.memory_data_model
assert newsm.components[0].flux.shape == self.comp.flux.shape
assert newsm.gaintable.data.shape == gt.data.shape
def output_skymodel(model_list, comp_list):
if conf['create_skymodel']["fill_image"]:
skymodel = SkyModel(images=model_list, components=[])
else:
skymodel = SkyModel(images=[], components=comp_list)
return BufferSkyModel(conf["buffer"], conf["outputs"]["skymodel"], skymodel).sync()
def test_readwriteimage_assertion(self):
im = create_test_image()
with self.assertRaises(AssertionError):
config = {
"buffer": {
"directory": self.dir
},
"image": {
"name": "test_bufferskyimage.hdf",
"data_model": "Image"
}
}
bdm = BufferImage(config["buffer"], config["image"], im)
bdm.sync()
new_bdm = BufferSkyModel(config["buffer"], config["image"])
new_bdm.sync()
newim = bdm.memory_data_model
def output_images(result):
BufferSkyModel(conf["buffer"], conf['outputs']['skymodel'], SkyModel(images=result[0])).sync()
deconvolved = image_gather_channels(result[0])
residual = image_gather_channels(remove_sumwt(result[1]))
restored = image_gather_channels(result[2])
BufferImage(conf["buffer"], conf['outputs']['deconvolved'], deconvolved).sync()
BufferImage(conf["buffer"], conf['outputs']['residual'], residual).sync()
BufferImage(conf["buffer"], conf['outputs']['restored'], restored).sync()
return result
def predict_vislist_wrapper(conf):
"""Wrapper for prediction
:param conf: Configuration from JSON file
:return:
"""
vis_list = BufferBlockVisibility(conf["buffer"], conf['inputs']['vis_list']).memory_data_model
skymodel = BufferSkyModel(conf["buffer"], conf["inputs"]["skymodel"]).memory_data_model
flux_limit = conf['primary_beam']['flux_limit']
if conf["primary_beam"]["apply"]:
def apply_pb_image(vt, model):
telescope = vt.configuration.name
pb = create_pb(model, telescope)
model.data *= pb.data
return model
def apply_pb_comp(vt, model, comp):
telescope = vt.configuration.name
pb = create_pb(model, telescope)
return apply_beam_to_skycomponent(comp, pb, flux_limit)
image_list = [arlexecute.execute(apply_pb_image, nout=1)(v, skymodel.images[i]) for i, v in enumerate(vis_list)]
if len(skymodel.components) > 1:
component_list = [arlexecute.execute(apply_pb_comp, nout=1)(v, skymodel.images[i], skymodel.components)
for i, v in enumerate(vis_list)]
else:
component_list = []
else:
image_list = [skymodel.images[0] for v in vis_list]
component_list = skymodel.components
future_vis_list = arlexecute.scatter(vis_list)
predicted_vis_list = [arlexecute.execute(predict_skycomponent_visibility)(v, component_list)
for v in future_vis_list]
predicted_vis_list = predict_workflow(predicted_vis_list, image_list,
context=conf['imaging']['context'],
vis_slices=conf['imaging']['vis_slices'])
def output_vislist(v):
bdm = BufferBlockVisibility(conf["buffer"], conf["outputs"]["vis_list"], v)
bdm.sync()
return arlexecute.execute(output_vislist)(predicted_vis_list)
def test_readwriteskymodel(self):
im = create_test_image()
sm = SkyModel(components=[self.comp], images=[im, im])
config = {
"buffer": {
"directory": self.dir
},
"skymodel": {
"name": "test_bufferskymodel.hdf",
"data_model": "SkyModel"
}
}
bdm = BufferSkyModel(config["buffer"], config["skymodel"], sm)
bdm.sync()
new_bdm = BufferSkyModel(config["buffer"], config["skymodel"])
new_bdm.sync()
newsm = bdm.memory_data_model
assert newsm.components[0].flux.shape == self.comp.flux.shape
assert newsm.images[0].data.shape == im.data.shape
assert numpy.max(numpy.abs(newsm.images[0].data - im.data)) < 1e-15