Sanitize fire time-hull mesh inputs to prevent disappearing Plotly meshes

src/cubedynamics/fire_time_hull.py

@@ -1092,14 +1092,50 @@ def plot_climate_filled_hull(
     scalar_debug_mode: Optional[str] = None,
     debug: bool = False,
 ) -> go.Figure:
-    def _build_vertex_slice_index() -> tuple[np.ndarray, np.ndarray, dict[str, Any]]:
-        t_days_vert = np.asarray(hull.t_days_vert, dtype=float)
-        if t_days_vert.shape[0] != verts.shape[0]:
+    def _sanitize_mesh_inputs(
+        verts_in: np.ndarray,
+        tris_in: np.ndarray,
+        t_days_in: np.ndarray,
+    ) -> tuple[np.ndarray, np.ndarray, np.ndarray]:
+        verts_arr = np.asarray(verts_in, dtype=float)
+        tris_arr = np.asarray(tris_in, dtype=int)
+        t_days_arr = np.asarray(t_days_in, dtype=float)
+
+        if verts_arr.ndim != 2 or verts_arr.shape[1] != 3:
+            raise ValueError("TimeHull verts_km must have shape (N, 3).")
+        if tris_arr.ndim != 2 or tris_arr.shape[1] != 3:
+            raise ValueError("TimeHull tris must have shape (M, 3).")
+        if t_days_arr.shape[0] != verts_arr.shape[0]:
             raise ValueError(
                 "Per-vertex time coordinate mismatch: "
-                f"{t_days_vert.shape[0]} t_days values for {verts.shape[0]} vertices."
+                f"{t_days_arr.shape[0]} t_days values for {verts_arr.shape[0]} vertices."
             )
 
+        valid_vertex_mask = np.isfinite(verts_arr).all(axis=1) & np.isfinite(t_days_arr)
+        if not np.all(valid_vertex_mask):
+            old_to_new = np.full(verts_arr.shape[0], -1, dtype=int)
+            old_to_new[valid_vertex_mask] = np.arange(int(valid_vertex_mask.sum()))
+            verts_arr = verts_arr[valid_vertex_mask]
+            t_days_arr = t_days_arr[valid_vertex_mask]
+            remapped = old_to_new[tris_arr]
+            tri_valid = (remapped >= 0).all(axis=1)
+            tris_arr = remapped[tri_valid]
+
+        if verts_arr.shape[0] == 0:
+            raise ValueError("TimeHull contains no finite vertices to render.")
+        if tris_arr.shape[0] == 0:
+            raise ValueError("TimeHull contains no valid triangles to render.")
+
+        tri_bounds_ok = (tris_arr >= 0).all() and (tris_arr < verts_arr.shape[0]).all()
+        if not tri_bounds_ok:
+            tri_valid = ((tris_arr >= 0) & (tris_arr < verts_arr.shape[0])).all(axis=1)
+            tris_arr = tris_arr[tri_valid]
+        if tris_arr.shape[0] == 0:
+            raise ValueError("TimeHull contains no in-bounds triangles to render.")
+
+        return verts_arr, tris_arr, t_days_arr
+
+    def _build_vertex_slice_index() -> tuple[np.ndarray, np.ndarray, dict[str, Any]]:
         layer_days, vertex_slice_index = np.unique(t_days_vert, return_inverse=True)
         n_layers_local = int(layer_days.size)
         if n_layers_local <= 0:
@@ -1166,8 +1202,7 @@ def _scalar_stats(values: np.ndarray) -> dict[str, Any]:
             "approx_unique_count": int(np.unique(finite).size),
         }
 
-    verts = np.asarray(hull.verts_km)
-    tris = np.asarray(hull.tris)
+    verts, tris, t_days_vert = _sanitize_mesh_inputs(hull.verts_km, hull.tris, hull.t_days_vert)
     n_vertices = int(verts.shape[0])
     layer_days, vertex_slice_index, alignment = _build_vertex_slice_index()
     n_layers = int(layer_days.size)

tests/test_fire_hull_viewer_scalars.py

@@ -194,3 +194,39 @@ def test_plot_climate_filled_hull_debug_output_reports_stats_and_alignment(_plot
     assert "face_alignment" in out
     assert re.search(r"'min_slice_span':\s*1", out)
     assert re.search(r"'max_slice_span':\s*1", out)
+
+
+def test_plot_climate_filled_hull_drops_nonfinite_vertices_and_remaps_tris(_plotly_stub):
+    hull = _synthetic_hull(days=3, verts_per_layer=4)
+    verts = hull.verts_km.copy()
+    verts[0, 0] = np.nan
+    hull = TimeHull(
+        event=hull.event,
+        verts_km=verts,
+        tris=hull.tris,
+        t_days_vert=hull.t_days_vert,
+        t_norm_vert=hull.t_norm_vert,
+        metrics=hull.metrics,
+    )
+    summary = HullClimateSummary(
+        values_inside=np.array([1.0]),
+        values_outside=np.array([0.0]),
+        per_day_mean=pd.Series([1.0, 5.0, 9.0], index=pd.date_range("2020-07-01", periods=3, freq="D")),
+    )
+
+    fig = plot_climate_filled_hull(hull, summary, color_limits=None)
+
+    x = np.asarray(fig.data[0].x, dtype=float)
+    y = np.asarray(fig.data[0].y, dtype=float)
+    z = np.asarray(fig.data[0].z, dtype=float)
+    i = np.asarray(fig.data[0].i, dtype=int)
+    j = np.asarray(fig.data[0].j, dtype=int)
+    k = np.asarray(fig.data[0].k, dtype=int)
+    intensity = np.asarray(fig.data[0].intensity, dtype=float)
+
+    assert x.shape[0] == verts.shape[0] - 1
+    assert np.isfinite(x).all() and np.isfinite(y).all() and np.isfinite(z).all()
+    assert i.size > 0 and j.size > 0 and k.size > 0
+    assert (i >= 0).all() and (j >= 0).all() and (k >= 0).all()
+    assert (i < x.shape[0]).all() and (j < x.shape[0]).all() and (k < x.shape[0]).all()
+    assert intensity.shape[0] == x.shape[0]