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return fit_y, fit_x
def fit_for_instance(self, instance):
fit_y = fit_galaxy.FitGalaxy(
masked_galaxy_dataset=self.galaxy_data_y, model_galaxies=instance.galaxies
)
fit_x = fit_galaxy.FitGalaxy(
masked_galaxy_dataset=self.galaxy_data_x, model_galaxies=instance.galaxies
)
return fit_y, fit_x
class PhaseGalaxy(abstract.AbstractPhase):
galaxies = af.PhaseProperty("galaxies")
Analysis = Analysis
def __init__(
self,
phase_name,
search,
folders=tuple(),
galaxies=None,
use_image=False,
use_convergence=False,
use_potential=False,
use_deflections=False,
sub_size=2,
pixel_scales_interp=None,
cosmology=cosmo.Planck15,
import numpy as np
from astropy import cosmology as cosmo
import autofit as af
from autolens.lens import ray_tracing, lens_fit
from autolens.pipeline.phase.phase import AbstractPhase, Phase
class PhasePositions(AbstractPhase):
galaxies = af.PhaseProperty("galaxies")
@property
def phase_property_collections(self):
return [self.galaxies]
def __init__(
self,
phase_name,
phase_folders=tuple(),
galaxies=None,
optimizer_class=af.MultiNest,
cosmology=cosmo.Planck15,
auto_link_priors=False,
):
super().__init__(
phase_name=phase_name,
from astropy import cosmology as cosmo
import autofit as af
from autolens.pipeline import phase_tagging
from autolens.pipeline.phase import dataset
from autolens.pipeline.phase import extensions
from autolens.pipeline.phase.imaging.analysis import Analysis
from autolens.pipeline.phase.imaging.meta_imaging_fit import MetaImagingFit
from autolens.pipeline.phase.imaging.result import Result
class PhaseImaging(dataset.PhaseDataset):
galaxies = af.PhaseProperty("galaxies")
hyper_image_sky = af.PhaseProperty("hyper_image_sky")
hyper_background_noise = af.PhaseProperty("hyper_background_noise")
Analysis = Analysis
Result = Result
@af.convert_paths
def __init__(
self,
paths,
*,
galaxies=None,
hyper_image_sky=None,
hyper_background_noise=None,
optimizer_class=af.MultiNest,
cosmology=cosmo.Planck15,
sub_size=2,
signal_to_noise_limit=None,
import autogalaxy as ag
from astropy import cosmology as cosmo
from autogalaxy.pipeline.phase import dataset
from autogalaxy.pipeline.phase.imaging.phase import PhaseAttributes as AgPhaseAttributes
from autolens.pipeline.phase.settings import PhaseSettingsImaging
from autolens.pipeline.phase.imaging.analysis import Analysis
from autolens.pipeline.phase.imaging.meta_imaging import MetaImaging
from autolens.pipeline.phase.imaging.result import Result
from autolens.pipeline.phase.extensions.stochastic_phase import StochasticPhase
class PhaseImaging(dataset.PhaseDataset):
galaxies = af.PhaseProperty("galaxies")
hyper_image_sky = af.PhaseProperty("hyper_image_sky")
hyper_background_noise = af.PhaseProperty("hyper_background_noise")
Analysis = Analysis
Result = Result
@af.convert_paths
def __init__(
self,
paths,
*,
search,
galaxies=None,
hyper_image_sky=None,
hyper_background_noise=None,
settings=PhaseSettingsImaging(),
cosmology=cosmo.Planck15,
):
from astropy import cosmology as cosmo
import autofit as af
from autofit.tools.phase import Dataset
from autolens.pipeline.phase import abstract
from autolens.pipeline.phase import extensions
from autolens.pipeline.phase.dataset.result import Result
class PhaseDataset(abstract.AbstractPhase):
galaxies = af.PhaseProperty("galaxies")
Result = Result
@af.convert_paths
def __init__(
self,
paths,
galaxies=None,
non_linear_class=af.MultiNest,
cosmology=cosmo.Planck15,
):
"""
A phase in an lens pipeline. Uses the set non_linear optimizer to try to fit models and hyper_galaxies
passed to it.
from autoarray.operators import transformer
from autogalaxy.pipeline.phase import dataset
from autogalaxy.pipeline.phase.interferometer.phase import (
PhaseAttributes as AgPhaseAttributes,
)
from autolens.pipeline.phase.settings import PhaseSettingsInterferometer
from autolens.pipeline.phase.interferometer.analysis import Analysis
from autolens.pipeline.phase.interferometer.meta_interferometer import (
MetaInterferometer,
)
from autolens.pipeline.phase.interferometer.result import Result
class PhaseInterferometer(dataset.PhaseDataset):
galaxies = af.PhaseProperty("galaxies")
hyper_background_noise = af.PhaseProperty("hyper_background_noise")
Analysis = Analysis
Result = Result
@af.convert_paths
def __init__(
self,
paths,
*,
search,
real_space_mask,
galaxies=None,
hyper_background_noise=None,
settings=PhaseSettingsInterferometer(),
cosmology=cosmo.Planck15,
):
import autofit as af
import autogalaxy as ag
from astropy import cosmology as cosmo
from autogalaxy.pipeline.phase import dataset
from autogalaxy.pipeline.phase.imaging.phase import PhaseAttributes as AgPhaseAttributes
from autolens.pipeline.phase.settings import PhaseSettingsImaging
from autolens.pipeline.phase.imaging.analysis import Analysis
from autolens.pipeline.phase.imaging.meta_imaging import MetaImaging
from autolens.pipeline.phase.imaging.result import Result
from autolens.pipeline.phase.extensions.stochastic_phase import StochasticPhase
class PhaseImaging(dataset.PhaseDataset):
galaxies = af.PhaseProperty("galaxies")
hyper_image_sky = af.PhaseProperty("hyper_image_sky")
hyper_background_noise = af.PhaseProperty("hyper_background_noise")
Analysis = Analysis
Result = Result
@af.convert_paths
def __init__(
self,
paths,
*,
search,
galaxies=None,
hyper_image_sky=None,
hyper_background_noise=None,
settings=PhaseSettingsImaging(),
from astropy import cosmology as cosmo
import autofit as af
from autolens.pipeline import phase_tagging
from autolens.pipeline.phase import dataset
from autolens.pipeline.phase import extensions
from autolens.pipeline.phase.imaging.analysis import Analysis
from autolens.pipeline.phase.imaging.meta_imaging_fit import MetaImagingFit
from autolens.pipeline.phase.imaging.result import Result
class PhaseImaging(dataset.PhaseDataset):
galaxies = af.PhaseProperty("galaxies")
hyper_image_sky = af.PhaseProperty("hyper_image_sky")
hyper_background_noise = af.PhaseProperty("hyper_background_noise")
Analysis = Analysis
Result = Result
@af.convert_paths
def __init__(
self,
paths,
*,
galaxies=None,
hyper_image_sky=None,
hyper_background_noise=None,
optimizer_class=af.MultiNest,
cosmology=cosmo.Planck15,
sub_size=2,