fix: compose output_search_root with test_mode segment in modeling_visualization_jit scripts

scripts/imaging/modeling_visualization_jit.py

@@ -38,6 +38,8 @@
 import jax.numpy as jnp
 import numpy as np
 
+from autoconf.test_mode import with_test_mode_segment
+
 import autofit as af
 import autolens as al
 
@@ -304,7 +306,7 @@
 # The Nautilus output goes to output/<path_prefix>/<name>/<hash>/image/
 # The quick-update visualizer writes fit.png (via subplot_fit function)
 # to that image folder during each quick update.
-output_search_root = Path("output") / output_root / "mge_linear"
+output_search_root = with_test_mode_segment(Path("output")) / output_root / "mge_linear"
 produced_pngs = list(output_search_root.rglob("fit.png"))
 print(f"fit.png files produced: {len(produced_pngs)}")
 for p in produced_pngs:

scripts/imaging/modeling_visualization_jit_delaunay.py

@@ -35,6 +35,8 @@
 import jax.numpy as jnp
 import numpy as np
 
+from autoconf.test_mode import with_test_mode_segment
+
 import autofit as af
 import autolens as al
 
@@ -348,7 +350,7 @@ def _assert_likelihood_sanity(label, analysis, model):
 print("Running Nautilus ...")
 result = search.fit(model=model, analysis=analysis_live)
 
-output_search_root = Path("output") / output_root / "delaunay"
+output_search_root = with_test_mode_segment(Path("output")) / output_root / "delaunay"
 produced_pngs = list(output_search_root.rglob("fit.png"))
 print(f"fit.png files produced: {len(produced_pngs)}")
 for p in produced_pngs:

scripts/imaging/modeling_visualization_jit_rectangular.py

@@ -34,6 +34,8 @@
 import jax.numpy as jnp
 import numpy as np
 
+from autoconf.test_mode import with_test_mode_segment
+
 import autofit as af
 import autolens as al
 
@@ -336,7 +338,7 @@ def _assert_likelihood_sanity(label, analysis, model):
 print("Running Nautilus ...")
 result = search.fit(model=model, analysis=analysis_live)
 
-output_search_root = Path("output") / output_root / "rectangular"
+output_search_root = with_test_mode_segment(Path("output")) / output_root / "rectangular"
 produced_pngs = list(output_search_root.rglob("fit.png"))
 print(f"fit.png files produced: {len(produced_pngs)}")
 for p in produced_pngs:

scripts/interferometer/modeling_visualization_jit.py

@@ -38,6 +38,8 @@
 import jax.numpy as jnp
 import numpy as np
 
+from autoconf.test_mode import with_test_mode_segment
+
 import autofit as af
 import autolens as al
 
@@ -294,7 +296,7 @@
 # the previous run's cached samples.csv and skips live sampling — so the
 # quick-update visualizer never fires, _jitted_fit_from is never set, and
 # the assertion below would fail on every rerun. Force a fresh run.
-output_search_root = Path("output") / output_root / "mge_linear"
+output_search_root = with_test_mode_segment(Path("output")) / output_root / "mge_linear"
 if output_search_root.exists():
     shutil.rmtree(output_search_root)
 

scripts/point_source/modeling_visualization_jit.py

@@ -35,6 +35,8 @@
 import jax
 import jax.numpy as jnp
 
+from autoconf.test_mode import with_test_mode_segment
+
 import autofit as af
 import autolens as al
 
@@ -245,7 +247,7 @@
 # Also clean the autofit search output so Nautilus performs live sampling
 # instead of resuming from a cached samples.csv — without this the
 # quick-update visualizer never fires on reruns.
-output_search_root = Path("output") / output_root / "point_image_plane"
+output_search_root = with_test_mode_segment(Path("output")) / output_root / "point_image_plane"
 if output_search_root.exists():
     shutil.rmtree(output_search_root)