Fault ribbons from the fault's own surface, and the fault-patch multigrid (#629)

.claude/skills/adapt-on-top-faults/SKILL.md

@@ -359,6 +359,7 @@ Measured guidance, all at matched cell count:
 | FMG under rotated free-slip on a plain (non-adapt) refined mesh | the rotated KSP resolves hierarchies via `custom_mg.build_transfers`: an adapt child's mesh-owned tail is picked up AUTOMATICALLY (#467 fixed the old silent GAMG fallback), but the native `dm_hierarchy` is still not read — on a plain refined mesh, `set_custom_fmg(..., field_id=0)`. |
 | NVB at np>1 raises NotImplementedError | native `_nvb_transform` extension not built (needs the custom-PETSc/amr env). Both `nvb` and `edge_split` are otherwise fully parallel, 2-D and 3-D. |
 | high stress appears in the matrix beside the fault | elements STRADDLING the weak-zone margin: one end sees high strain rate, the other high viscosity. The FE forms `mean(η)·mean(ε̇)`; the honest cell average is `mean(η ε̇)`, and the difference is `−2 Cov(η, ε̇)` across the cell. Zero for any cell wholly in or wholly out. See the band-width section below. |
+| scattered 1-level refinement across the WHOLE domain; far-field quality drops | the metric's far clip ``h_far`` sits below the base mesh's cell DIAMETERS (gmsh ``cellSize`` is a target edge length; diameters run 1.2–2.5x it — measured 0.108–0.223 for cellSize 0.18+ref 1). ``edge_split`` marks on diameter, so 100% of the domain refines once and the unrequested bisection DE-CONDITIONS the grid (far-field median q 0.372 -> 0.295, measured). Set ``h_far >= 1.05 * cell_diameters(base.dm).max()``. |
 | refinement band narrower than the fault's INFLUENCE | measured: η still 0.07 at d=0.06 while the mesh has already coarsened 4×, so the artefact peaks on the transition flank, not on the fault. **85 % of it sits at d>0.01.** Size the flat core from the *influence* width, not the fault. |
 | `uw.function.evaluate` fails "Total components 8 != 6" | cached-interpolation mismatch on a mesh already carrying several solver variables. Sample the field numerically from `surface.unsigned_distance` instead. |
 | bare SIGSEGV, no traceback, after building a Mesh from a raw DM | `uw.discretisation.Mesh(dm, ...)` TAKES THE DM OVER. Read geometry from `child.dm`, never the handle you passed in. |

.claude/skills/uw-visualisation/SKILL.md

@@ -56,6 +56,15 @@ pl.screenshot(out); pl.close()
    high-order DOFs → blocky. **Attach `T.data[:,0]` directly** to the DOF-cloud
    mesh from `meshVariable_to_pv_mesh_object` (it is correct for annulus/box/disc
    — do NOT avoid it). `clim` MUST be passed (default `clim=""` trips `np.any`).
+5. Resampling ANY field (even P1) onto a regular pixel grid via
+   `uw.function.evaluate` **dapples at element boundaries** — grid points that
+   straddle a facet get located into a neighbouring cell with slightly-off
+   reference coords (Louis: "artefacts across the elements", S-fault rig).
+   Render derived fields NODALLY on the mesh's own triangulation instead:
+   evaluate at `mesh_to_pv_mesh(mesh).points` (exact at vertices for P1,
+   whichever cell the locator picks), attach as point_data, let VTK
+   interpolate WITHIN elements. On a SPLIT mesh never Delaunay the DOF cloud
+   (it re-triangulates across the slit) — use the mesh's own cells.
 
 ## Seeing the MESH (adaptation / moving mesh)
 

docs/advanced/stress-visualisation.md

@@ -0,0 +1,197 @@
+# Visualising the Stress Tensor
+
+Scalar fields get colormaps and velocity gets arrows; the stress tensor
+needs its own glyph. `underworld3.visualisation` provides
+principal-stress glyphs — sampled at seed points, the way velocity
+arrows sample the velocity — and stress trajectories, the curvilinear
+net traced by the principal directions. Both work from the same
+recovered stress fields you already checkpoint.
+
+## Principal-stress glyphs
+
+At each seed point we diagonalise the stress and draw one bar per
+principal axis: bar length proportional to the principal-value
+magnitude, blue for compressive ($\lambda < 0$), red for tensile. In
+2-D this is the classical stress cross; in 3-D each seed carries three
+orthogonal bars, best drawn on one or two section planes rather than a
+filled volume.
+
+```python
+import underworld3 as uw
+import underworld3.visualisation as vis
+import sympy
+
+# Recovered stress components (P1 projections of the deviatoric
+# stress) plus pressure give the full stress. Project once after the
+# solve; do not pass raw solver derivative expressions to a plot.
+# A scalar variable's .sym is a 1x1 Matrix — index it before
+# assembling the tensor.
+stress = sympy.Matrix([[Txx.sym[0] - P.sym[0], Txy.sym[0]],
+                       [Txy.sym[0], Tyy.sym[0] - P.sym[0]]])
+
+pl = vis.plot_stress_glyphs(mesh, stress, num_seeds=24,
+                            save_png=True, dir_fname="stress_glyphs.png")
+```
+
+Seeds default to a regular grid over the mesh bounding box, filtered
+to points inside the mesh (an annulus seeds no glyphs in its hole).
+Pass `seeds` explicitly to sample section planes in 3-D or to avoid
+regions — in fault models, keep seeds out of the weak zones, where the
+recovered stress mixes materials across the interface.
+
+```{figure} figures/stress_glyphs_thrust.png
+:alt: Two-panel figure for a thrust-ramp model. Top panel, principal stress crosses on a 26 by 13 seed grid over a 2 by 1 section with two grey parabolic ramps rising from a basal decollement, drawn over a faint peach strain-rate wash in which the quiet wedges riding each ramp glow white and the blind ramp tips smudge darker. Far-field crosses are blue-horizontal (compression); in the wedges the crosses turn red and near-vertical (tension), largest just above the blind tips. Bottom panel, stress trajectories over the same wash: dark sigma-1 lines run horizontally and arch smoothly over each ramp tip, pale sigma-3 lines rise near-vertically between them, crossing at right angles everywhere.
+:name: fig-stress-glyphs-thrust
+
+Principal-stress crosses (top) and stress trajectories (bottom) for a
+blind-thrust model, over a faint strain-rate wash (log scale,
+background-percentile limits, low opacity — the second invariant of
+the strain rate from the same recovered stress). The colour
+convention matches the RdBu_r field convention used across the
+documentation: blue compressive, red tensile. The wash ties the
+stress geometry to the deformation it drives: the near-rigid thrust
+wedges glow white while the blind tips concentrate both quantities.
+```
+
+### The pressure gauge matters for colours, not directions
+
+For incompressible models the full stress is
+$\sigma = \tau - p\,I$ and the pressure datum is a gauge choice.
+Shifting that datum shifts every principal value equally, so it can
+flip bars between red and blue — but it cannot rotate the principal
+directions or reorder the principal values. State the gauge in your
+caption (the examples here demean the pressure), or add the
+lithostatic reference before plotting if absolute compression
+matters.
+
+The same argument answers a common question about map-view regime
+colouring in the style of the World Stress Map (red normal, green
+strike-slip, blue thrust): the regime classification is
+gauge-invariant, but in a 2-D incompressible plane-strain model it is
+also *degenerate* — the out-of-plane deviatoric stress is zero while
+the in-plane deviatoric principals are $\pm s$, so the out-of-plane
+stress is always the intermediate principal stress and every map-view
+point classifies as strike-slip. Regime colouring only carries
+information in 3-D models.
+
+## Stress trajectories (2-D)
+
+Trajectories integrate the principal *direction* field into curves —
+the classical stress-trajectory diagrams of structural geology. A
+principal direction is defined only modulo 180°, so ordinary
+streamline tools cannot draw this field: the integrator in
+`direction_trajectories` sign-aligns each evaluated eigenvector with
+the previous heading, and places lines evenly (Jobard–Lehmann
+occupancy) so the figure stays legible. The two families cross at
+right angles wherever both are drawn — a built-in correctness check.
+
+The direction callable is yours to build, which keeps the integrator
+independent of how the stress is stored. From nodal arrays:
+
+```python
+import numpy as np
+
+def make_direction(interpolate_stress, family="compressive"):
+    # interpolate_stress(p) -> (sxx, syy, sxy) at point p, or None
+    def direction_at(p):
+        values = interpolate_stress(p)
+        if values is None:
+            return None
+        sxx, syy, sxy = values
+        mean_dev = 0.5 * (sxx - syy)
+        radius = np.hypot(mean_dev, sxy)
+        if radius < 1.0e-12:      # isotropic point: direction undefined
+            return None
+        angle = 0.5 * np.arctan2(sxy, mean_dev)   # most-tensile axis
+        if family == "compressive":
+            angle += 0.5 * np.pi
+        return np.array([np.cos(angle), np.sin(angle)])
+    return direction_at
+
+lines = vis.direction_trajectories(
+    direction_at, candidate_seeds, inside,
+    step=0.008, separation=0.04,
+)
+trajectory_lines = vis.trajectories_to_pv_lines(lines)
+```
+
+Draw the compressive family dark and the tensile family pale, as in
+the figure above. In 3-D the analogue of a trajectory is a surface;
+we do not attempt those — draw glyphs on section planes instead.
+
+## Two more regimes, same recipe
+
+The same two panels for the extensional and strike-slip companions of
+the thrust model — nested listric normal faults above a detachment,
+and en-echelon segments in dextral simple shear. Nothing changes in
+the code except the checkpoint being loaded.
+
+```{figure} figures/stress_glyphs_listric.png
+:alt: Two-panel figure for three nested listric normal faults soling into a basal detachment, over a faint peach strain-rate wash with white quiet triangles in the footwall beneath each sole. Top panel, principal stress crosses: red-horizontal tension dominates the upper plate and deepens between the fault traces; blue compression concentrates near the detachment, with strongly rotated mixed crosses hugging each curved fault. Below the detachment the crosses return to uniform red-horizontal. Bottom panel, trajectories: dark sigma-1 lines hang near-vertically in the extending upper plate, bending to meet each listric sole, while pale sigma-3 lines run horizontally; beneath the detachment the net is an undisturbed rectangular grid.
+:name: fig-stress-glyphs-listric
+
+Nested listric normal faults (extension): horizontal tension aloft,
+compression concentrating under the soles, and an undisturbed
+trajectory grid beneath the detachment — the faults decouple the two
+plates.
+```
+
+```{figure} figures/stress_glyphs_enechelon.png
+:alt: Two-panel map-view figure for three en-echelon fault segments in dextral simple shear, over a faint strain-rate wash with bright white lobes at the relay steps between segment tips. Top panel, principal stress crosses at 45 degrees far from the faults, shrinking and rotating through the relay zones, with a blue compressive bridge linking overlapping tips. Bottom panel, trajectories: the dark sigma-1 family sweeps diagonally across the box and kinks sharply as it hands across each relay step; the pale sigma-3 family crosses it orthogonally.
+:name: fig-stress-glyphs-enechelon
+
+En-echelon segments in dextral simple shear (map view): the conjugate
+cross pattern of the far field collapses through the relay steps, and
+the trajectory families kink as stress hands across from segment to
+segment.
+```
+
+## 3-D glyphs
+
+`principal_stress_glyphs` accepts `(n, 3, 3)` tensors and returns
+three bars per seed. Seed one or two planes through the feature of
+interest:
+
+```python
+u = np.linspace(0.05, 0.95, 13)
+gx, gz = np.meshgrid(u, u)
+plane = np.column_stack([gx.ravel(),
+                         np.full(gx.size, 0.5),   # y = centre plane
+                         gz.ravel()])
+pl = vis.plot_stress_glyphs(mesh, stress, seeds=plane)
+```
+
+```{figure} figures/stress_glyphs_sinker3d.png
+:alt: A unit cube drawn in outline with a grey sphere of radius 0.16 near the centre, slightly above mid-height. Three-bar principal stress glyphs are drawn on a vertical section plane and a horizontal section plane through the sphere, via the one-call plot_stress_glyphs with the cube edges and sphere added to the returned plotter. Above the sphere the bars are red and near-vertical (tension as material is pulled down behind the sinker); below and beside it they are blue (compression), fanning outward on the horizontal plane beneath the sphere. Bar length decays with distance from the sphere.
+:name: fig-stress-glyphs-sinker
+
+Three-bar principal-stress glyphs on two section planes through a
+Stokes sinker: a tensile (red) column above the sinking sphere, a
+compressive (blue) fan below and around it. Rendered with
+`plot_stress_glyphs(..., show=False)` so the cube outline and sphere
+could be added to the returned plotter before the screenshot.
+```
+
+## Building blocks
+
+The plot function is a convenience wrapper; every step is available
+separately for custom figures:
+
+| Function | Purpose |
+|---|---|
+| `tensor_fn_to_pv_points(pv_mesh, uw_fn)` | Evaluate a `dim`×`dim` sympy tensor at points |
+| `principal_stress_glyphs(coords, stress, scale)` | Bar segments + `"tensile"` cell array |
+| `direction_trajectories(direction_at, seeds, inside, step, separation)` | Evenly spaced mod-180° trajectories |
+| `trajectories_to_pv_lines(lines)` | Bundle polylines for `add_mesh` |
+| `plot_stress_glyphs(mesh, stress, ...)` | One-call cross plot |
+
+The figures on this page come from checkpointed models (the three
+fault-interaction examples and a Stokes sinker): the solve writes the
+mesh, the velocity, the pressure, and the recovered stress components
+with `mesh.write_timestep`, and the glyph plots load them back with
+`read_timestep` — no re-solving to restyle a figure. The faint
+background in the 2-D panels is the strain-rate second invariant from
+the same recovered stress ($\dot\varepsilon = \tau/2$ at matrix
+viscosity 1), drawn first at low opacity with log scaling and
+background-percentile colour limits, so the glyphs carry the figure
+and the wash only whispers where deformation concentrates.