def test_mpccal_MPCCAL_manysources_subimages(self): self.actualSetup() model = create_empty_image_like(self.theta_list[0].image) if arlexecute.using_dask: progress = None else: progress = self.progress future_vis = arlexecute.scatter(self.all_skymodel_noniso_vis) future_model = arlexecute.scatter(model) future_theta_list = arlexecute.scatter(self.theta_list) result = mpccal_skymodel_list_arlexecute_workflow( future_vis, future_model, future_theta_list, mpccal_progress=progress, nmajor=5, context='2d', algorithm='hogbom', scales=[0, 3, 10], fractional_threshold=0.3, threshold=0.2, gain=0.1, niter=1000, psf_support=256, deconvolve_facets=8, deconvolve_overlap=8, deconvolve_taper='tukey') (self.theta_list, residual) = arlexecute.compute(result, sync=True) combined_model = calculate_skymodel_equivalent_image(self.theta_list) psf_obs = invert_list_arlexecute_workflow( [self.all_skymodel_noniso_vis], [model], context='2d', dopsf=True) result = restore_list_arlexecute_workflow([combined_model], psf_obs, [(residual, 0.0)]) result = arlexecute.compute(result, sync=True) if self.persist: export_image_to_fits( residual, arl_path('test_results/test_mpccal_no_edge_residual.fits')) if self.persist: export_image_to_fits( result[0], arl_path('test_results/test_mpccal_no_edge_restored.fits')) if self.persist: export_image_to_fits( combined_model, arl_path('test_results/test_mpccal_no_edge_deconvolved.fits')) recovered_mpccal_components = find_skycomponents(result[0], fwhm=2, threshold=0.32, npixels=12) def max_flux(elem): return numpy.max(elem.flux) recovered_mpccal_components = sorted(recovered_mpccal_components, key=max_flux, reverse=True) assert recovered_mpccal_components[ 0].name == 'Segment 8', recovered_mpccal_components[0].name assert numpy.abs(recovered_mpccal_components[0].flux[0, 0] - 7.773751416364857) < 1e-7, \ recovered_mpccal_components[0].flux[0, 0] newscreen = create_empty_image_like(self.screen) gaintables = [th.gaintable for th in self.theta_list] newscreen, weights = grid_gaintable_to_screen( self.all_skymodel_noniso_blockvis, gaintables, newscreen) if self.persist: export_image_to_fits( newscreen, arl_path('test_results/test_mpccal_no_edge_screen.fits')) if self.persist: export_image_to_fits( weights, arl_path( 'test_results/test_mpccal_no_edge_screenweights.fits')) arlexecute.close()
gaintable=null_gaintable, image=model) ] future_vis = arlexecute.scatter(all_skymodel_vis) future_model = arlexecute.scatter(model) future_theta_list = arlexecute.scatter(ical_skymodel) result = mpccal_skymodel_list_arlexecute_workflow(future_vis, future_model, future_theta_list, mpccal_progress=partial( progress, context='ICAL'), nmajor=args.ical_nmajor, context='2d', algorithm='hogbom', fractional_threshold=0.3, threshold=0.1, gain=0.1, niter=1000, psf_support=512, deconvolve_facets=8, deconvolve_overlap=16, deconvolve_taper='tukey') (ical_skymodel, residual) = arlexecute.compute(result, sync=True) print(qa_image(residual, context='ICAL residual image')) print('ical finished') combined_model = calculate_skymodel_equivalent_image(ical_skymodel)