diff --git a/scripts/imaging/modeling_visualization_jit.py b/scripts/imaging/modeling_visualization_jit.py index d69d5359..5097ef3c 100644 --- a/scripts/imaging/modeling_visualization_jit.py +++ b/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////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: diff --git a/scripts/imaging/modeling_visualization_jit_delaunay.py b/scripts/imaging/modeling_visualization_jit_delaunay.py index 271019ea..be90203f 100644 --- a/scripts/imaging/modeling_visualization_jit_delaunay.py +++ b/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: diff --git a/scripts/imaging/modeling_visualization_jit_rectangular.py b/scripts/imaging/modeling_visualization_jit_rectangular.py index 1db00369..4309401f 100644 --- a/scripts/imaging/modeling_visualization_jit_rectangular.py +++ b/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: diff --git a/scripts/interferometer/modeling_visualization_jit.py b/scripts/interferometer/modeling_visualization_jit.py index 2125377b..776b7118 100644 --- a/scripts/interferometer/modeling_visualization_jit.py +++ b/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) diff --git a/scripts/point_source/modeling_visualization_jit.py b/scripts/point_source/modeling_visualization_jit.py index c301dae9..c881605a 100644 --- a/scripts/point_source/modeling_visualization_jit.py +++ b/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)