refactor: archive quantity package to autolens_workspace_developer/legacy

AGENTS.md

@@ -26,7 +26,7 @@ NUMBA_CACHE_DIR=/tmp/numba_cache MPLCONFIGDIR=/tmp/matplotlib python -m pytest t
 
 - **Profiles**: `LightProfile` (`lp.*`), `MassProfile` (`mp.*`), `LightProfileLinear` (`lp_linear.*`)
 - **Galaxy** (`galaxy/galaxy.py`): holds light/mass profiles, pixelizations
-- **Fit classes**: `FitImaging`, `FitInterferometer`, `FitQuantity`, `FitEllipse`
+- **Fit classes**: `FitImaging`, `FitInterferometer`, `FitEllipse`
 - **Analysis classes**: `AnalysisImaging`, `AnalysisInterferometer` — implement `log_likelihood_function`
 - **Decorator system** (from autoarray): `@to_array`, `@to_grid`, `@to_vector_yx`, `@transform`
 - **Operate mixins**: `OperateImage`, `OperateDeflections`, `LensCalc`

CLAUDE.md

@@ -83,7 +83,6 @@ Each dataset type has a `Fit*` class that orchestrates the full fitting pipeline
 
 - `FitImaging` (`imaging/fit_imaging.py`) – CCD imaging
 - `FitInterferometer` (`interferometer/fit_interferometer.py`) – ALMA/interferometry
-- `FitQuantity` (`quantity/fit_quantity.py`) – arbitrary quantity datasets
 - `FitEllipse` (`ellipse/fit_ellipse.py`) – isophote/ellipse fitting
 
 All inherit from `AbstractFitInversion` (`abstract_fit.py`), which handles the linear algebra inversion step when `LightProfileLinear` or pixelization-based profiles are present.
@@ -94,7 +93,6 @@ Each dataset type has an `Analysis*` class that implements `log_likelihood_funct
 
 - `AnalysisImaging` (`imaging/model/analysis.py`)
 - `AnalysisInterferometer` (`interferometer/model/analysis.py`)
-- `AnalysisQuantity` (`quantity/model/analysis.py`)
 - `AnalysisEllipse` (`ellipse/model/analysis.py`)
 
 These inherit from `AnalysisDataset` → `Analysis` (in `analysis/analysis/`), which inherits `af.Analysis`. The `log_likelihood_function` builds a `Fit*` object from the `af.ModelInstance` and returns its `figure_of_merit`.

autogalaxy/__init__.py

@@ -79,9 +79,6 @@
 from .interferometer.fit_interferometer import FitInterferometer
 from .interferometer.model.analysis import AnalysisInterferometer
 
-from .quantity.fit_quantity import FitQuantity
-from .quantity.model.analysis import AnalysisQuantity
-from .quantity.dataset_quantity import DatasetQuantity
 from .galaxy.galaxy import Galaxy
 from .galaxy.galaxies import Galaxies
 from .galaxy.galaxy_table import GalaxyTable

autogalaxy/analysis/analysis/analysis.py

@@ -2,7 +2,7 @@
 Abstract `Analysis` class providing shared functionality across all **PyAutoGalaxy** model-fitting analyses.
 
 This module provides `Analysis`, the root analysis class from which all dataset-specific analysis classes
-inherit (`AnalysisImaging`, `AnalysisInterferometer`, `AnalysisEllipse`, `AnalysisQuantity`).
+inherit (`AnalysisImaging`, `AnalysisInterferometer`, `AnalysisEllipse`).
 
 `Analysis` itself inherits from `af.Analysis` (from **PyAutoFit**) and extends it with:
 

autogalaxy/config/visualize/plots.yaml

@@ -51,6 +51,4 @@ fit_ellipse:                               # Settings for plots of ellipse fitti
   subplot_fit_ellipse : true               # Plot subplot of all fit quantities for ellipse fits (e.g. the model data, residual-map, etc.)?
   data : true                              # Plot the data of the ellipse fit?
   data_no_ellipse: true                    # Plot the data without the black data ellipses, which obscure noisy data?
-  ellipse_residuals: true                  # Plot the residuals of the ellipse fit?
-
-fit_quantity: {}                           # Settings for plots of fit quantities (e.g. FitQuantity).
+  ellipse_residuals: true                  # Plot the residuals of the ellipse fit?

autogalaxy/fixtures.py

@@ -149,43 +149,6 @@ def make_dataset_interp_7x7():
     return ag.DatasetInterp(dataset=imaging_7x7)
 
 
-# QUANTITY DATASET AND FIT #
-
-
-def make_dataset_quantity_7x7_array_2d():
-    return ag.DatasetQuantity(
-        data=aa.Array2D.ones(shape_native=(7, 7), pixel_scales=1.0),
-        noise_map=aa.Array2D.full(
-            fill_value=2.0, shape_native=(7, 7), pixel_scales=1.0
-        ),
-    )
-
-
-def make_dataset_quantity_7x7_vector_yx_2d():
-    return ag.DatasetQuantity(
-        data=aa.VectorYX2D.ones(shape_native=(7, 7), pixel_scales=1.0),
-        noise_map=aa.VectorYX2D.full(
-            fill_value=2.0, shape_native=(7, 7), pixel_scales=1.0
-        ),
-    )
-
-
-def make_fit_quantity_7x7_array_2d():
-    return ag.FitQuantity(
-        dataset=make_dataset_quantity_7x7_array_2d(),
-        light_mass_obj=make_galaxies_7x7(),
-        func_str="convergence_2d_from",
-    )
-
-
-def make_fit_quantity_7x7_vector_yx_2d():
-    return ag.FitQuantity(
-        dataset=make_dataset_quantity_7x7_vector_yx_2d(),
-        light_mass_obj=make_galaxies_7x7(),
-        func_str="deflections_yx_2d_from",
-    )
-
-
 # galaxies #
 
 

autogalaxy/plot/__init__.py

@@ -46,10 +46,6 @@
     subplot_fit_real_space,
 )
 
-from autogalaxy.quantity.plot.fit_quantity_plots import (
-    subplot_fit as subplot_fit_quantity,
-)
-
 from autogalaxy.ellipse.plot.fit_ellipse_plots import (
     subplot_fit_ellipse,
     subplot_ellipse_errors,