feat: point domains keep image_with_points.png and fit_image_with_points.png

GALLERY.md

@@ -2,7 +2,7 @@
 
 <!-- Generated by gallery/gallery_build.py from scripts/<domain>/images/. Do not edit by hand: rerun `bash gallery/gallery_run.sh --all`. -->
 
-Rendered with PyAutoLens `2026.8.17.1` · 66 figures.
+Rendered with PyAutoLens `2026.8.17.1` · 68 figures.
 
 Every figure below is what the PyAutoLens visualizers (`VisualizerImaging`, `VisualizerInterferometer`, `VisualizerPoint`, `VisualizerWeak`) write to a model-fit's `image/` folder, rendered on this repo's datasets with the true model. See [README.md](README.md) for how to improve one.
 
@@ -38,10 +38,10 @@ Every figure below is what the PyAutoLens visualizers (`VisualizerImaging`, `Vis
   - [visualization](#multi_galaxy--visualization) (2 figures)
     - [top level](#multi_galaxy--visualization--top-level)
 - [point_source_image_chi_squared](#point_source_image_chi_squared)
-  - [visualization](#point_source_image_chi_squared--visualization) (3 figures)
+  - [visualization](#point_source_image_chi_squared--visualization) (4 figures)
     - [top level](#point_source_image_chi_squared--visualization--top-level)
 - [point_source_source_chi_squared](#point_source_source_chi_squared)
-  - [visualization](#point_source_source_chi_squared--visualization) (3 figures)
+  - [visualization](#point_source_source_chi_squared--visualization) (4 figures)
     - [top level](#point_source_source_chi_squared--visualization--top-level)
 - [weak](#weak)
   - [visualization](#weak--visualization) (2 figures)
@@ -351,6 +351,10 @@ Every figure below is what the PyAutoLens visualizers (`VisualizerImaging`, `Vis
 
 ![fit](scripts/point_source_image_chi_squared/images/visualization/fit.png)
 
+##### fit_image_with_points
+
+![fit_image_with_points](scripts/point_source_image_chi_squared/images/visualization/fit_image_with_points.png)
+
 ##### image_with_points
 
 ![image_with_points](scripts/point_source_image_chi_squared/images/visualization/image_with_points.png)
@@ -369,6 +373,10 @@ Every figure below is what the PyAutoLens visualizers (`VisualizerImaging`, `Vis
 
 ![fit](scripts/point_source_source_chi_squared/images/visualization/fit.png)
 
+##### fit_image_with_points
+
+![fit_image_with_points](scripts/point_source_source_chi_squared/images/visualization/fit_image_with_points.png)
+
 ##### image_with_points
 
 ![image_with_points](scripts/point_source_source_chi_squared/images/visualization/image_with_points.png)

_viz_cli.py

@@ -181,8 +181,8 @@ def keep_dataset_and_fit(
     plotter's ``dataset_point.png``); they are renamed to ``dataset.png`` / ``fit.png``. Every
     other file (other PNGs, FITS, CSV, JSON) and any sub-folder is deleted, so the newer
     domains track only the two figures. ``extra_pngs`` names further figures to keep under their
-    own names (e.g. the point plotter's ``image_with_points.png``). Raises if any expected figure
-    is missing.
+    own names (e.g. the point plotter's ``image_with_points.png`` and
+    ``fit_image_with_points.png``). Raises if any expected figure is missing.
     """
     image_dir = Path(image_dir)
     kept = []

gallery/viz_manifest.yaml

@@ -8,7 +8,7 @@ rendered_with:
   autogalaxy: 2026.8.17.1
   autoarray: 2026.8.17.1
   autofit: 2026.8.17.1
-figure_count: 66
+figure_count: 68
 figures:
 - file: scripts/cluster/images/visualization/point_0/dataset.png
   producer: scripts/cluster/visualization.py
@@ -370,12 +370,18 @@ figures:
   source: ''
   bytes: 28952
   sha256: 6b52412bb75eab16a3dc4ae4e0a4925d5f23c2ff7ed8bb9a6199f406f201cfed
+- file: scripts/point_source_image_chi_squared/images/visualization/fit_image_with_points.png
+  producer: scripts/point_source_image_chi_squared/visualization.py
+  domain: point_source_image_chi_squared
+  source: ''
+  bytes: 78338
+  sha256: 76b4b2b2ce69bcc2f3d3740c901d04d86ba245f217e5f026f1bbdfc3b9db39bd
 - file: scripts/point_source_image_chi_squared/images/visualization/image_with_points.png
   producer: scripts/point_source_image_chi_squared/visualization.py
   domain: point_source_image_chi_squared
   source: ''
-  bytes: 78200
-  sha256: 5972b44e38db7c42e93a108d53530b83a1103cde5a06989c5947eb9e86871114
+  bytes: 66518
+  sha256: 2653419882e5f55d2afe24b067e8d5c9865081aee51517dc05520a12d1787468
 - file: scripts/point_source_source_chi_squared/images/visualization/dataset.png
   producer: scripts/point_source_source_chi_squared/visualization.py
   domain: point_source_source_chi_squared
@@ -388,12 +394,18 @@ figures:
   source: ''
   bytes: 28823
   sha256: caf49de216f6f80553e6c79b03231fd51ee626bd5939dd6864489e56a134320c
+- file: scripts/point_source_source_chi_squared/images/visualization/fit_image_with_points.png
+  producer: scripts/point_source_source_chi_squared/visualization.py
+  domain: point_source_source_chi_squared
+  source: ''
+  bytes: 75775
+  sha256: 4fee595525a08c3f70f79c7d5e4395b69734c3582d3ddd4343b64a5c210a4f23
 - file: scripts/point_source_source_chi_squared/images/visualization/image_with_points.png
   producer: scripts/point_source_source_chi_squared/visualization.py
   domain: point_source_source_chi_squared
   source: ''
-  bytes: 75639
-  sha256: 76c6fa188a4bb9ca4d66fe95e42429ec7d9c900df85de0e00bae345be68146a0
+  bytes: 66518
+  sha256: 2653419882e5f55d2afe24b067e8d5c9865081aee51517dc05520a12d1787468
 - file: scripts/weak/images/visualization/dataset.png
   producer: scripts/weak/visualization.py
   domain: weak

scripts/misc/simulators/point_source.py

@@ -6,7 +6,8 @@
 of one point source (``point_0``) behind an isothermal lens — and writes
 ``point_dataset.json`` (the ``PointDataset``, positions only) and ``tracer.json`` into
 ``dataset/point_source/simple/``, plus the accompanying imaging (``data.fits``, ``psf.fits``,
-``noise_map.fits``) the producers plot the positions over (``image_with_points.png``).
+``noise_map.fits``) the producers plot the positions over (``image_with_points.png`` and
+``fit_image_with_points.png``).
 
 The imaging places one unlensed ``al.lp.PointSource`` per noisy image position on an
 image-plane galaxy at the lens redshift (a delta function is not lensed: its multiple images

scripts/point_source_image_chi_squared/visualization.py

@@ -12,12 +12,14 @@
     scripts/point_source_image_chi_squared/images/visualization/
         dataset.png   <- visualize_before_fit (the plotter writes dataset_point.png; renamed)
         fit.png       <- visualize(quick_update=True)
-        image_with_points.png <- visualize(quick_update=True): the observed positions and the
-                                 model's positions + critical curves over ``data.fits``
+        image_with_points.png     <- visualize_before_fit: the observed positions over
+                                     ``data.fits`` (dataset only, no model)
+        fit_image_with_points.png <- visualize(quick_update=True): the observed
+                                     positions, the model's positions and critical curves over
+                                     ``data.fits``
 
-Every other file the visualizer writes is deleted: this domain tracks only these three
-figures. ``image_with_points.png`` is written before and after the fit to the same file;
-the kept one is the after-fit version, with the model positions.
+Every other file the visualizer writes is deleted: this domain tracks only these four
+figures.
 
 Dataset: ``dataset/point_source/simple`` (four image-plane positions, 5 mas noise; shared by
 both point-source chi-squared producers), from
@@ -70,8 +72,8 @@ def _repo_root() -> Path:
 dataset = al.from_json(file_path=dataset_path / "point_dataset.json")
 
 """
-The accompanying imaging, used only for visualization (``image_with_points.png``), not in the
-likelihood.
+The accompanying imaging, used only for visualization (``image_with_points.png``,
+``fit_image_with_points.png``), not in the likelihood.
 """
 data = al.Array2D.from_fits(
     file_path=dataset_path / "data.fits", hdu=0, pixel_scales=tm.IMAGE_PIXEL_SCALES
@@ -130,7 +132,9 @@ def _repo_root() -> Path:
     quick_update=True,
 )
 keep_dataset_and_fit(
-    image_path, dataset_png="dataset_point.png", extra_pngs=("image_with_points.png",)
+    image_path,
+    dataset_png="dataset_point.png",
+    extra_pngs=("image_with_points.png", "fit_image_with_points.png"),
 )
 print(f"visualize: {time.perf_counter() - t0:.1f}s")
 print(

scripts/point_source_source_chi_squared/visualization.py

@@ -12,12 +12,14 @@
     scripts/point_source_source_chi_squared/images/visualization/
         dataset.png   <- visualize_before_fit (the plotter writes dataset_point.png; renamed)
         fit.png       <- visualize(quick_update=True)
-        image_with_points.png <- visualize(quick_update=True): the observed positions and the
-                                 model's positions + critical curves over ``data.fits``
+        image_with_points.png     <- visualize_before_fit: the observed positions over
+                                     ``data.fits`` (dataset only, no model)
+        fit_image_with_points.png <- visualize(quick_update=True): the observed
+                                     positions and critical curves over ``data.fits`` (a
+                                     source-plane fit has no image-plane model positions)
 
-Every other file the visualizer writes is deleted: this domain tracks only these three
-figures. ``image_with_points.png`` is written before and after the fit to the same file;
-the kept one is the after-fit version, with the model positions.
+Every other file the visualizer writes is deleted: this domain tracks only these four
+figures.
 
 Dataset: ``dataset/point_source/simple`` (four image-plane positions, 5 mas noise; shared by
 both point-source chi-squared producers), from
@@ -70,8 +72,8 @@ def _repo_root() -> Path:
 dataset = al.from_json(file_path=dataset_path / "point_dataset.json")
 
 """
-The accompanying imaging, used only for visualization (``image_with_points.png``), not in the
-likelihood.
+The accompanying imaging, used only for visualization (``image_with_points.png``,
+``fit_image_with_points.png``), not in the likelihood.
 """
 data = al.Array2D.from_fits(
     file_path=dataset_path / "data.fits", hdu=0, pixel_scales=tm.IMAGE_PIXEL_SCALES
@@ -131,7 +133,9 @@ def _repo_root() -> Path:
     quick_update=True,
 )
 keep_dataset_and_fit(
-    image_path, dataset_png="dataset_point.png", extra_pngs=("image_with_points.png",)
+    image_path,
+    dataset_png="dataset_point.png",
+    extra_pngs=("image_with_points.png", "fit_image_with_points.png"),
 )
 print(f"visualize: {time.perf_counter() - t0:.1f}s")
 print(