Consolidate duplicated critical-curve plot helper into plot_utils

_compute_critical_curve_lines was copy-pasted verbatim into both
autolens/imaging/plot/fit_imaging_plots.py and
autolens/interferometer/plot/fit_interferometer_plots.py, and the two copies
had drifted: the imaging copy narrowly caught (ModuleNotFoundError, ValueError)
and loudly logged anything else (guarding the PyAutoGalaxy abd7b717 / PyAutoFit
#1280 silent-fallback regression), while the interferometer copy still had a
bare 'except Exception' that silently swallowed every failure — the exact mode
that regression guard exists to prevent. Model code imported inconsistent
behaviour: interferometer/model/{visualizer,plotter} got the silent copy,
point/model/* got the hardened one.

Move the single canonical (hardened) definition to autolens/plot/plot_utils.py
— which already re-exports the underlying _critical_curves_from/_caustics_from
primitives — and re-export it from both fit-plot modules so every existing
'from ...fit_{imaging,interferometer}_plots import _compute_critical_curve_lines'
import keeps resolving. All call sites now share one hardened definition.

Behaviour-preserving except on the interferometer error path, which is
intentionally lifted from silent-swallow to the hardened logging behaviour.
_plot_source_plane is deliberately left duplicated: the two copies genuinely
differ (mask source, zoom_extent_scale), so consolidating it is not
behaviour-neutral.

Witness tests (imaging error-path silent/logged assertions) updated to patch
and observe the symbol at its new home; interferometer plot tests do not pin
the error path, so none break. Dead imports (_caustics_from, numpy_lines)
trimmed from both modules.

Co-Authored-By: Claude Opus 4.8 <noreply@anthropic.com>
Claude-Session: https://claude.ai/code/session_01RSRerFzzFttWNeZ5C7U4fx

Author: claude

autolens/imaging/plot/fit_imaging_plots.py

@@ -8,64 +8,16 @@
 from autogalaxy.util.plot_utils import plot_array
 from autoarray.plot.array import _zoom_array_2d
 from autoarray.plot.utils import subplots, save_figure, hide_unused_axes, conf_subplot_figsize, tight_layout
-from autoarray.plot.utils import numpy_lines as _to_lines
 from autoarray.inversion.mappers.abstract import Mapper
 from autoarray.inversion.plot.mapper_plots import plot_mapper
-from autogalaxy.util.plot_utils import _critical_curves_from, _caustics_from
+from autogalaxy.util.plot_utils import _critical_curves_from
 
-logger = logging.getLogger(__name__)
-
-
-def _compute_critical_curve_lines(tracer, grid):
-    """Compute critical-curve and caustic lines for a tracer on a given grid.
-
-    Returns a 4-tuple ``(image_plane_lines, image_plane_line_colors,
-    source_plane_lines, source_plane_line_colors)`` suitable for passing
-    directly to :func:`~autoarray.plot.array.plot_array`.  On failure
-    (e.g. the mass model has no critical curves) returns
-    ``(None, None, None, None)``.
+# Canonical, single-source definition. Re-exported here so existing
+# ``from autolens.imaging.plot.fit_imaging_plots import _compute_critical_curve_lines``
+# imports keep working.
+from autolens.plot.plot_utils import _compute_critical_curve_lines
 
-    Parameters
-    ----------
-    tracer
-        The tracer whose mass distribution is used to trace critical curves
-        and caustics.
-    grid
-        Image-plane grid on which the curves are evaluated.
-    """
-    try:
-        tan_cc, rad_cc = _critical_curves_from(tracer, grid)
-        tan_ca, rad_ca = _caustics_from(tracer, grid)
-        _tan_cc_lines = _to_lines(list(tan_cc) if tan_cc is not None else []) or []
-        _rad_cc_lines = _to_lines(list(rad_cc) if rad_cc is not None else []) or []
-        _tan_ca_lines = _to_lines(list(tan_ca) if tan_ca is not None else []) or []
-        _rad_ca_lines = _to_lines(list(rad_ca) if rad_ca is not None else []) or []
-        image_plane_lines = (_tan_cc_lines + _rad_cc_lines) or None
-        image_plane_line_colors = (
-            ["white"] * len(_tan_cc_lines) + ["yellow"] * len(_rad_cc_lines)
-        )
-        source_plane_lines = (_tan_ca_lines + _rad_ca_lines) or None
-        source_plane_line_colors = (
-            ["white"] * len(_tan_ca_lines) + ["yellow"] * len(_rad_ca_lines)
-        )
-        return image_plane_lines, image_plane_line_colors, source_plane_lines, source_plane_line_colors
-    except (ModuleNotFoundError, ValueError):
-        # ModuleNotFoundError: jax_zero_contour missing — already warned upstream in
-        # plot_utils._critical_curves_method().
-        # ValueError: no zero crossings in the eigenvalue grid (e.g. slope >= 2
-        # isothermal where lambda_r > 0 everywhere). Curves don't exist for this
-        # model, so rendering without overlays is correct.
-        return None, None, None, None
-    except Exception:
-        # Anything else — log loudly with traceback so the next regression of the
-        # "ZeroSolver raised inside model-fit, viz fell back to all-zero" failure
-        # mode (PyAutoGalaxy abd7b717, PyAutoFit #1280) does not stay silent.
-        logger.warning(
-            "Critical-curve computation failed unexpectedly; rendering without "
-            "overlays. Investigate — this used to be a silent fallback.",
-            exc_info=True,
-        )
-        return None, None, None, None
+logger = logging.getLogger(__name__)
 
 
 def _compute_critical_curves_from_fit(fit):

autolens/interferometer/plot/fit_interferometer_plots.py

@@ -8,41 +8,19 @@
 from autogalaxy.util.plot_utils import plot_array
 from autoarray.plot.yx import plot_yx
 from autoarray.plot.utils import subplots, save_figure, conf_subplot_figsize, tight_layout
-from autoarray.plot.utils import numpy_lines as _to_lines
 from autoarray.inversion.mappers.abstract import Mapper
 from autoarray.inversion.plot.mapper_plots import plot_mapper
-from autogalaxy.util.plot_utils import _critical_curves_from, _caustics_from
 from autolens.lens.plot.tracer_plots import plane_image_from
 
-logger = logging.getLogger(__name__)
-
-
-def _compute_critical_curve_lines(tracer, grid):
-    """Compute critical-curve and caustic lines for a tracer on a given grid.
+# Canonical, single-source definition (shared with the imaging fit plots).
+# Re-exported here so existing
+# ``from autolens.interferometer.plot.fit_interferometer_plots import _compute_critical_curve_lines``
+# imports keep working. This also adopts the hardened error handling that the
+# imaging copy carried and this copy previously lacked (a bare ``except`` that
+# silently swallowed every failure).
+from autolens.plot.plot_utils import _compute_critical_curve_lines
 
-    Returns a 4-tuple ``(image_plane_lines, image_plane_line_colors,
-    source_plane_lines, source_plane_line_colors)`` suitable for passing
-    directly to :func:`~autoarray.plot.array.plot_array`.  On failure
-    returns ``(None, None, None, None)``.
-    """
-    try:
-        tan_cc, rad_cc = _critical_curves_from(tracer, grid)
-        tan_ca, rad_ca = _caustics_from(tracer, grid)
-        _tan_cc_lines = _to_lines(list(tan_cc) if tan_cc is not None else []) or []
-        _rad_cc_lines = _to_lines(list(rad_cc) if rad_cc is not None else []) or []
-        _tan_ca_lines = _to_lines(list(tan_ca) if tan_ca is not None else []) or []
-        _rad_ca_lines = _to_lines(list(rad_ca) if rad_ca is not None else []) or []
-        image_plane_lines = (_tan_cc_lines + _rad_cc_lines) or None
-        image_plane_line_colors = (
-            ["white"] * len(_tan_cc_lines) + ["yellow"] * len(_rad_cc_lines)
-        )
-        source_plane_lines = (_tan_ca_lines + _rad_ca_lines) or None
-        source_plane_line_colors = (
-            ["white"] * len(_tan_ca_lines) + ["yellow"] * len(_rad_ca_lines)
-        )
-        return image_plane_lines, image_plane_line_colors, source_plane_lines, source_plane_line_colors
-    except Exception:
-        return None, None, None, None
+logger = logging.getLogger(__name__)
 
 
 def _plot_source_plane(fit, ax, plane_index, zoom_to_brightest=True,

autolens/plot/plot_utils.py

@@ -1 +1,58 @@
+import logging
+
 from autogalaxy.util.plot_utils import _critical_curves_from, _caustics_from
+from autoarray.plot.utils import numpy_lines as _to_lines
+
+logger = logging.getLogger(__name__)
+
+
+def _compute_critical_curve_lines(tracer, grid):
+    """Compute critical-curve and caustic lines for a tracer on a given grid.
+
+    Returns a 4-tuple ``(image_plane_lines, image_plane_line_colors,
+    source_plane_lines, source_plane_line_colors)`` suitable for passing
+    directly to :func:`~autoarray.plot.array.plot_array`.  On failure
+    (e.g. the mass model has no critical curves) returns
+    ``(None, None, None, None)``.
+
+    Parameters
+    ----------
+    tracer
+        The tracer whose mass distribution is used to trace critical curves
+        and caustics.
+    grid
+        Image-plane grid on which the curves are evaluated.
+    """
+    try:
+        tan_cc, rad_cc = _critical_curves_from(tracer, grid)
+        tan_ca, rad_ca = _caustics_from(tracer, grid)
+        _tan_cc_lines = _to_lines(list(tan_cc) if tan_cc is not None else []) or []
+        _rad_cc_lines = _to_lines(list(rad_cc) if rad_cc is not None else []) or []
+        _tan_ca_lines = _to_lines(list(tan_ca) if tan_ca is not None else []) or []
+        _rad_ca_lines = _to_lines(list(rad_ca) if rad_ca is not None else []) or []
+        image_plane_lines = (_tan_cc_lines + _rad_cc_lines) or None
+        image_plane_line_colors = (
+            ["white"] * len(_tan_cc_lines) + ["yellow"] * len(_rad_cc_lines)
+        )
+        source_plane_lines = (_tan_ca_lines + _rad_ca_lines) or None
+        source_plane_line_colors = (
+            ["white"] * len(_tan_ca_lines) + ["yellow"] * len(_rad_ca_lines)
+        )
+        return image_plane_lines, image_plane_line_colors, source_plane_lines, source_plane_line_colors
+    except (ModuleNotFoundError, ValueError):
+        # ModuleNotFoundError: jax_zero_contour missing — already warned upstream in
+        # plot_utils._critical_curves_method().
+        # ValueError: no zero crossings in the eigenvalue grid (e.g. slope >= 2
+        # isothermal where lambda_r > 0 everywhere). Curves don't exist for this
+        # model, so rendering without overlays is correct.
+        return None, None, None, None
+    except Exception:
+        # Anything else — log loudly with traceback so the next regression of the
+        # "ZeroSolver raised inside model-fit, viz fell back to all-zero" failure
+        # mode (PyAutoGalaxy abd7b717, PyAutoFit #1280) does not stay silent.
+        logger.warning(
+            "Critical-curve computation failed unexpectedly; rendering without "
+            "overlays. Investigate — this used to be a silent fallback.",
+            exc_info=True,
+        )
+        return None, None, None, None

test_autolens/imaging/plot/test_fit_imaging_plots.py

@@ -3,7 +3,7 @@
 
 import pytest
 
-from autolens.imaging.plot import fit_imaging_plots
+from autolens.plot import plot_utils
 from autolens.imaging.plot.fit_imaging_plots import (
     _compute_critical_curve_lines,
     subplot_fit,
@@ -179,9 +179,11 @@ def test__compute_critical_curve_lines__known_recoverable_exceptions__silent(
     def boom(*args, **kwargs):
         raise exc_cls("synthetic failure for test")
 
-    monkeypatch.setattr(fit_imaging_plots, "_critical_curves_from", boom)
+    # _compute_critical_curve_lines lives in autolens.plot.plot_utils and is
+    # re-exported by fit_imaging_plots; patch/observe it at its canonical home.
+    monkeypatch.setattr(plot_utils, "_critical_curves_from", boom)
 
-    with caplog.at_level(logging.WARNING, logger=fit_imaging_plots.__name__):
+    with caplog.at_level(logging.WARNING, logger=plot_utils.__name__):
         result = _compute_critical_curve_lines(tracer=None, grid=None)
 
     assert result == (None, None, None, None)
@@ -203,9 +205,9 @@ def test__compute_critical_curve_lines__unexpected_exception__logs_warning(
     def boom(*args, **kwargs):
         raise RuntimeError("synthetic unexpected failure for test")
 
-    monkeypatch.setattr(fit_imaging_plots, "_critical_curves_from", boom)
+    monkeypatch.setattr(plot_utils, "_critical_curves_from", boom)
 
-    with caplog.at_level(logging.WARNING, logger=fit_imaging_plots.__name__):
+    with caplog.at_level(logging.WARNING, logger=plot_utils.__name__):
         result = _compute_critical_curve_lines(tracer=None, grid=None)
 
     assert result == (None, None, None, None)