Merge pull request #171 from Jammy2211/feature/data_offset

Feature/data offset

autogalaxy/aggregator/dataset_model.py

@@ -8,7 +8,9 @@
 logger = logging.getLogger(__name__)
 
 
-def _dataset_model_from(fit: af.Fit, instance: af.ModelInstance) -> List[aa.DatasetModel]:
+def _dataset_model_from(
+    fit: af.Fit, instance: af.ModelInstance
+) -> List[aa.DatasetModel]:
     """
     Returns a `DatasetModel` object from a `PyAutoFit` sqlite database `Fit` object.
 
@@ -40,7 +42,10 @@ def _dataset_model_from(fit: af.Fit, instance: af.ModelInstance) -> List[aa.Data
         except AttributeError:
             dataset_model = None
     else:
-        dataset_model = fit.instance.dataset_model
+        try:
+            dataset_model = fit.instance.dataset_model
+        except AttributeError:
+            dataset_model = None
 
     if len(fit.children) > 0:
         logger.info(

autogalaxy/aggregator/fit_imaging.py

@@ -76,7 +76,11 @@ def _fit_imaging_from(
     fit_dataset_list = []
 
     for dataset, galaxies, dataset_model, adapt_images, mesh_grids_of_planes in zip(
-        dataset_list, galaxies_list, dataset_model_list, adapt_images_list, mesh_grids_of_planes_list
+        dataset_list,
+        galaxies_list,
+        dataset_model_list,
+        adapt_images_list,
+        mesh_grids_of_planes_list,
     ):
         preloads = agg_util.preloads_from(
             preloads_cls=Preloads,

autogalaxy/aggregator/fit_interferometer.py

@@ -80,7 +80,11 @@ def _fit_interferometer_from(
     fit_dataset_list = []
 
     for dataset, galaxies, dataset_model, adapt_images, mesh_grids_of_planes in zip(
-        dataset_list, galaxies_list, dataset_model_list, adapt_images_list, mesh_grids_of_planes_list
+        dataset_list,
+        galaxies_list,
+        dataset_model_list,
+        adapt_images_list,
+        mesh_grids_of_planes_list,
     ):
         preloads = agg_util.preloads_from(
             preloads_cls=Preloads,

autogalaxy/aggregator/galaxies.py

@@ -50,17 +50,18 @@ def _galaxies_from(fit: af.Fit, instance: af.ModelInstance) -> List[Galaxy]:
         if hasattr(fit.instance, "clumps"):
             galaxies = galaxies + fit.instance.clumps
 
-    if len(fit.children) > 0:
-        logger.info(
-            """
-            Using database for a fit with multiple summed Analysis objects.
-
-            Galaxy objects do not fully support this yet (e.g. variables across Analysis objects may not be correct)
-            so proceed with caution!
-            """
-        )
-
-        return [galaxies] * len(fit.children)
+    if fit.children is not None:
+        if len(fit.children) > 0:
+            logger.info(
+                """
+                Using database for a fit with multiple summed Analysis objects.
+    
+                Galaxy objects do not fully support this yet (e.g. variables across Analysis objects may not be correct)
+                so proceed with caution!
+                """
+            )
+
+            return [galaxies] * len(fit.children)
 
     return [galaxies]
 

autogalaxy/config/priors/dataset_model.yaml

@@ -1,4 +1,10 @@
 DatasetModel:
   background_sky_level:
+    type: Constant
+    value: 0.0
+  grid_offset_0:
+    type: Constant
+    value: 0.0
+  grid_offset_1:
     type: Constant
     value: 0.0

autogalaxy/imaging/fit_imaging.py

@@ -23,7 +23,7 @@ def __init__(
         self,
         dataset: aa.Imaging,
         galaxies: List[Galaxy],
-        dataset_model : Optional[aa.DatasetModel] = None,
+        dataset_model: Optional[aa.DatasetModel] = None,
         adapt_images: Optional[AdaptImages] = None,
         settings_inversion: aa.SettingsInversion = aa.SettingsInversion(),
         preloads: aa.Preloads = Preloads(),
@@ -91,10 +91,6 @@ def __init__(
         self.adapt_images = adapt_images
         self.settings_inversion = settings_inversion
 
-    @property
-    def grid(self) -> aa.type.Grid2DLike:
-        return self.dataset.grid
-
     @property
     def blurred_image(self) -> aa.Array2D:
         """
@@ -107,18 +103,14 @@ def blurred_image(self) -> aa.Array2D:
         if len(self.galaxies.cls_list_from(cls=LightProfile)) == len(
             self.galaxies.cls_list_from(cls=LightProfileOperated)
         ):
-            return (
-                self.galaxies.image_2d_from(
-                    grid=self.dataset.grid,
-                )
+            return self.galaxies.image_2d_from(
+                grid=self.grid,
             )
 
-        return (
-            self.galaxies.blurred_image_2d_from(
-                grid=self.dataset.grid,
-                convolver=self.dataset.convolver,
-                blurring_grid=self.dataset.blurring_grid,
-            )
+        return self.galaxies.blurred_image_2d_from(
+            grid=self.grid,
+            convolver=self.dataset.convolver,
+            blurring_grid=self.blurring_grid,
         )
 
     @property
@@ -136,8 +128,8 @@ def galaxies_to_inversion(self) -> GalaxiesToInversion:
             convolver=self.dataset.convolver,
             w_tilde=self.w_tilde,
             grid=self.grid,
-            grid_pixelization=self.dataset.grid_pixelization,
-            blurring_grid=self.dataset.blurring_grid,
+            grid_pixelization=self.grid_pixelization,
+            blurring_grid=self.blurring_grid,
             border_relocator=self.dataset.border_relocator,
         )
 
@@ -198,7 +190,7 @@ def galaxy_model_image_dict(self) -> Dict[Galaxy, np.ndarray]:
         galaxy_blurred_image_2d_dict = self.galaxies.galaxy_blurred_image_2d_dict_from(
             grid=self.grid,
             convolver=self.dataset.convolver,
-            blurring_grid=self.dataset.blurring_grid,
+            blurring_grid=self.blurring_grid,
         )
 
         galaxy_linear_obj_image_dict = self.galaxy_linear_obj_data_dict_from(

autogalaxy/interferometer/fit_interferometer.py

@@ -78,7 +78,10 @@ def __init__(
         self.galaxies = Galaxies(galaxies=galaxies, run_time_dict=run_time_dict)
 
         super().__init__(
-            dataset=dataset, dataset_model=dataset_model, use_mask_in_fit=False, run_time_dict=run_time_dict
+            dataset=dataset,
+            dataset_model=dataset_model,
+            use_mask_in_fit=False,
+            run_time_dict=run_time_dict,
         )
         AbstractFitInversion.__init__(
             self=self,
@@ -98,7 +101,7 @@ def profile_visibilities(self) -> aa.Visibilities:
         a Fourier transform to the sum of light profile images.
         """
         return self.galaxies.visibilities_from(
-            grid=self.dataset.grid, transformer=self.dataset.transformer
+            grid=self.grid, transformer=self.dataset.transformer
         )
 
     @property
@@ -116,7 +119,7 @@ def galaxies_to_inversion(self) -> GalaxiesToInversion:
             transformer=self.dataset.transformer,
             w_tilde=self.w_tilde,
             grid=self.grid,
-            grid_pixelization=self.dataset.grid_pixelization,
+            grid_pixelization=self.grid_pixelization,
             border_relocator=self.dataset.border_relocator,
         )
 
@@ -157,10 +160,6 @@ def model_data(self) -> aa.Visibilities:
 
         return self.profile_visibilities
 
-    @property
-    def grid(self) -> aa.Grid2D:
-        return self.dataset.grid
-
     @property
     def galaxy_model_image_dict(self) -> Dict[Galaxy, np.ndarray]:
         """
@@ -200,7 +199,7 @@ def galaxy_model_visibilities_dict(self) -> Dict[Galaxy, np.ndarray]:
         data being fitted.
         """
         galaxy_model_visibilities_dict = self.galaxies.galaxy_visibilities_dict_from(
-            grid=self.dataset.grid, transformer=self.dataset.transformer
+            grid=self.grid, transformer=self.dataset.transformer
         )
 
         galaxy_linear_obj_data_dict = self.galaxy_linear_obj_data_dict_from(

autogalaxy/interferometer/plot/fit_interferometer_plotters.py

@@ -111,7 +111,7 @@ def galaxies_plotter_from(self, galaxies: List[Galaxy]) -> GalaxiesPlotter:
         """
         return GalaxiesPlotter(
             galaxies=galaxies,
-            grid=self.fit.dataset.grid,
+            grid=self.fit.grid,
             mat_plot_2d=self.mat_plot_2d,
             visuals_2d=self.get_visuals_2d_real_space(),
             include_2d=self.include_2d,

autogalaxy/profiles/light/standard/__init__.py

@@ -15,4 +15,4 @@
 )
 from .shapelets.polar import ShapeletPolarSph, ShapeletPolar
 from .shapelets.cartesian import ShapeletCartesianSph, ShapeletCartesian
-from .shapelets.exponential import ShapeletExponentialSph, ShapeletExponential
+from .shapelets.exponential import ShapeletExponentialSph, ShapeletExponential

autogalaxy/quantity/fit_quantity.py

@@ -56,7 +56,7 @@ def __init__(
     def model_data(self):
         if self.model_data_manual is None:
             func = getattr(self.light_mass_obj, self.func_str)
-            return func(grid=self.dataset.grid)
+            return func(grid=self.grid)
 
         return self.model_data_manual
 
@@ -104,10 +104,6 @@ def mask(self):
     def inversion(self):
         return None
 
-    @property
-    def grid(self):
-        return self.dataset.grid
-
     @property
     def galaxies(self):
         return self.light_mass_obj

test_autogalaxy/aggregator/conftest.py

@@ -57,16 +57,17 @@ def aggregator_from(database_file, analysis, model, samples):
 
 @pytest.fixture(name="model")
 def make_model():
-
     dataset_model = af.Model(ag.DatasetModel)
-    dataset_model.background_sky_level = af.UniformPrior(lower_limit=0.5, upper_limit=1.5)
+    dataset_model.background_sky_level = af.UniformPrior(
+        lower_limit=0.5, upper_limit=1.5
+    )
 
     return af.Collection(
         dataset_model=dataset_model,
         galaxies=af.Collection(
             g0=af.Model(ag.Galaxy, redshift=0.5, light=ag.lp.Sersic),
             g1=af.Model(ag.Galaxy, redshift=1.0, light=ag.lp.Sersic),
-        )
+        ),
     )
 
 

test_autogalaxy/conftest.py

@@ -105,6 +105,11 @@ def make_masked_imaging_7x7():
     return fixtures.make_masked_imaging_7x7()
 
 
+@pytest.fixture(name="masked_imaging_7x7_sub_2")
+def make_masked_imaging_7x7_sub_2():
+    return fixtures.make_masked_imaging_7x7_sub_2()
+
+
 @pytest.fixture(name="masked_imaging_covariance_7x7")
 def make_masked_imaging_covariance_7x7():
     return fixtures.make_masked_imaging_covariance_7x7()

test_autogalaxy/imaging/test_fit_imaging.py

@@ -191,21 +191,63 @@ def test__fit_figure_of_merit(
 
 
 def test__fit__model_dataset__sky___handles_special_behaviour(masked_imaging_7x7):
-
     g0 = ag.Galaxy(
         redshift=0.5,
         bulge=ag.lp_linear.Sersic(sersic_index=1.0),
     )
 
     fit = ag.FitImaging(
-        dataset=masked_imaging_7x7, galaxies=[g0],
-        dataset_model=ag.DatasetModel(background_sky_level=5.0)
+        dataset=masked_imaging_7x7,
+        galaxies=[g0],
+        dataset_model=ag.DatasetModel(background_sky_level=5.0),
     )
 
     assert fit.perform_inversion is True
     assert fit.figure_of_merit == pytest.approx(-21.6970706693, 1.0e-4)
 
 
+def test__fit__model_dataset__grid_offset__handles_special_behaviour(
+    masked_imaging_7x7,
+    masked_imaging_7x7_sub_2,
+):
+    g0 = ag.Galaxy(redshift=0.5, bulge=ag.lp.Sersic(centre=(-1.0, -2.0), intensity=1.0))
+    g1 = ag.Galaxy(redshift=0.5, bulge=ag.lp.Sersic(centre=(-1.0, -2.0), intensity=1.0))
+
+    fit = ag.FitImaging(
+        dataset=masked_imaging_7x7,
+        galaxies=[g0, g1],
+        dataset_model=ag.DatasetModel(grid_offset=(1.0, 2.0)),
+    )
+
+    assert fit.figure_of_merit == pytest.approx(-75938.05, 1.0e-4)
+
+    g0 = ag.Galaxy(redshift=0.5, bulge=ag.lp.Sersic(centre=(-1.0, -2.0), intensity=1.0))
+    g1 = ag.Galaxy(redshift=0.5, bulge=ag.lp.Sersic(centre=(-1.0, -2.0), intensity=1.0))
+
+    fit = ag.FitImaging(
+        dataset=masked_imaging_7x7_sub_2,
+        galaxies=[g0, g1],
+        dataset_model=ag.DatasetModel(grid_offset=(1.0, 2.0)),
+    )
+
+    assert fit.figure_of_merit == pytest.approx(-14.91028771456, 1.0e-4)
+
+    pixelization = ag.Pixelization(
+        mesh=ag.mesh.Rectangular(shape=(3, 3)),
+        regularization=ag.reg.Constant(coefficient=1.0),
+    )
+
+    galaxy_pix = ag.Galaxy(redshift=0.5, pixelization=pixelization)
+
+    fit = ag.FitImaging(
+        dataset=masked_imaging_7x7,
+        galaxies=[ag.Galaxy(redshift=0.5), galaxy_pix],
+        dataset_model=ag.DatasetModel(grid_offset=(1.0, 2.0)),
+    )
+
+    assert fit.figure_of_merit == pytest.approx(-22.9005, 1.0e-4)
+
+
 def test__galaxy_model_image_dict(masked_imaging_7x7):
     # Normal Light Profiles Only
 

test_autogalaxy/test_regression.py

@@ -11,9 +11,7 @@ class FitInversion(AbstractFitInversion):
     def __init__(
         self, model_obj, settings_inversion: aa.SettingsInversion, light_profiles
     ):
-        super().__init__(
-            model_obj=model_obj, settings_inversion=settings_inversion
-        )
+        super().__init__(model_obj=model_obj, settings_inversion=settings_inversion)
         self.light_profiles = light_profiles
 
     @property