We import and make pipelines as per usual, albeit we'll now be doing this for multiple pipelines! We then run each pipeline, passing the results of previous pipelines to subsequent pipelines. """ from slam.imaging.with_lens_light.pipelines import source__parametric from slam.imaging.with_lens_light.pipelines import source__inversion from slam.imaging.with_lens_light.pipelines import light__parametric from slam.imaging.with_lens_light.pipelines import mass__light_dark source__parametric = source__parametric.make_pipeline(slam=slam, settings=settings) source_results = source__parametric.run(dataset=imaging, mask=mask) source__inversion = source__inversion.make_pipeline( slam=slam, settings=settings, source_parametric_results=source_results) source_results = source__inversion.run(dataset=imaging, mask=mask) light__parametric = light__parametric.make_pipeline( slam=slam, settings=settings, source_results=source_results) light_results = light__parametric.run(dataset=imaging, mask=mask) mass__light_dark = mass__light_dark.make_pipeline( slam=slam, settings=settings, source_results=source_results, light_results=light_results, ) mass_results = mass__light_dark.run(dataset=imaging, mask=mask)
We import and make pipelines as per usual, albeit we'll now be doing this for multiple pipelines! We then run each pipeline, passing the results of previous pipelines to subsequent pipelines. """ from slam.imaging.with_lens_light.pipelines import source__parametric from slam.imaging.with_lens_light.pipelines import source__inversion from slam.imaging.with_lens_light.pipelines import light__parametric from slam.imaging.with_lens_light.pipelines import mass__light_dark source__parametric = source__parametric.make_pipeline(slam=slam, settings=settings) source_results = source__parametric.run(dataset=imaging, mask=mask) source__inversion = source__inversion.make_pipeline( slam=slam, settings=settings, source_parametric_results=source_results) source_results = source__inversion.run(dataset=imaging, mask=mask) light__parametric = light__parametric.make_pipeline( slam=slam, settings=settings, source_results=source_results) light_results = light__parametric.run(dataset=imaging, mask=mask) mass__light_dark = mass__light_dark.make_pipeline( slam=slam, settings=settings, source_results=source_results, light_results=light_results, end_stochastic=True, ) mass_results = mass__light_dark.run(dataset=imaging, mask=mask)