refactor!: rename public cell APIs to simplex nomenclature

.github/workflows/codacy.yml

@@ -71,8 +71,9 @@ jobs:
           rsync -a --delete --exclude '.git' ./ "$CODACY_WORKDIR/"
 
       # Execute Codacy Analysis CLI with one selected tool per matrix entry.
-      # Opengrep reads the repository-owned rules from semgrep.yaml; broad
-      # default Semgrep/Opengrep packs remain disabled.
+      # Opengrep should mirror repository-owned rules from semgrep.yaml. The
+      # SARIF splitter below defensively drops any default Codacy/OpenGrep
+      # findings whose rule IDs do not belong to this repository.
       - name: Run Codacy Analysis CLI
         # Cap Codacy runtime so a hung analyzer does not consume the full job timeout.
         timeout-minutes: 20
@@ -98,79 +99,7 @@ jobs:
       - name: Split SARIF runs for upload
         run: |
           set -euo pipefail
-
-          python3 <<'PY'
-          import copy
-          import json
-          import os
-          import re
-          import sys
-          from pathlib import Path
-
-          source = Path(os.environ["CODACY_SARIF"])
-          out_dir = Path(os.environ["RUNNER_TEMP"]) / "codacy-sarif"
-
-          if not source.is_file() or source.stat().st_size == 0:
-              sys.exit(f"Codacy did not produce a SARIF file at {source}")
-
-          try:
-              sarif = json.loads(source.read_text(encoding="utf-8"))
-          except json.JSONDecodeError as exc:
-              raise SystemExit(f"Codacy produced invalid SARIF JSON: {exc}") from exc
-
-          runs = sarif.get("runs")
-          if not isinstance(runs, list):
-              sys.exit("Codacy SARIF did not contain a runs array")
-          if not runs:
-              print("Codacy SARIF did not contain any runs to upload")
-
-          out_dir.mkdir(parents=True, exist_ok=True)
-          for stale in out_dir.glob("*.sarif"):
-              stale.unlink()
-
-          def slug(value: str) -> str:
-              normalized = re.sub(r"[^A-Za-z0-9_.-]+", "-", value.strip().lower())
-              return normalized.strip("-") or "unknown"
-
-          seen_categories: dict[str, int] = {}
-          uploadable_count = 0
-          for index, run in enumerate(runs, start=1):
-              rules = run.get("tool", {}).get("driver", {}).get("rules")
-              results = run.get("results")
-              if not rules and not results:
-                  print(f"Skipping empty SARIF run {index} with no rules or results")
-                  continue
-
-              run_copy = copy.deepcopy(run)
-              tool = run_copy.get("tool", {}).get("driver", {}).get("name")
-              base_category = f"codacy-{slug(str(tool or f'run-{index}'))}"
-              seen_categories[base_category] = seen_categories.get(base_category, 0) + 1
-              suffix = seen_categories[base_category]
-              category = base_category if suffix == 1 else f"{base_category}-{suffix}"
-
-              automation = run_copy.get("automationDetails")
-              if not isinstance(automation, dict):
-                  automation = {}
-              automation["id"] = category
-              run_copy["automationDetails"] = automation
-
-              split_sarif = {key: value for key, value in sarif.items() if key != "runs"}
-              split_sarif.setdefault("$schema", "https://json.schemastore.org/sarif-2.1.0.json")
-              split_sarif.setdefault("version", "2.1.0")
-              split_sarif["runs"] = [run_copy]
-
-              out_file = out_dir / f"{index:02d}-{category}.sarif"
-              out_file.write_text(json.dumps(split_sarif, indent=2), encoding="utf-8")
-              print(f"Wrote {out_file} with category {category}")
-              uploadable_count += 1
-
-          with Path(os.environ["GITHUB_ENV"]).open("a", encoding="utf-8") as env_file:
-              env_file.write(f"CODACY_SPLIT_SARIF_DIR={out_dir}\n")
-              env_file.write(f"CODACY_HAS_UPLOADABLE_SARIF={'true' if uploadable_count else 'false'}\n")
-
-          if uploadable_count == 0:
-              print("No non-empty Codacy SARIF runs to upload")
-          PY
+          python3 scripts/ci/filter_codacy_sarif.py "$CODACY_SARIF" "$RUNNER_TEMP/codacy-sarif"
 
       - name: Upload split SARIF files
         if: env.CODACY_HAS_UPLOADABLE_SARIF == 'true'

AGENTS.md

@@ -261,14 +261,14 @@ in practice; when in doubt, favour the invariant over the convenient edit.
   `src/topology/manifold.rs` and `src/topology/characteristics/`.
 - Repair paths (`repair_delaunay_with_flips`, `repair_facet_oversharing`,
   `delaunayize_by_flips`) bound their work via explicit budgets
-  (`max_flips`, `max_iterations`, `max_cells_removed`) and surface
+  (`max_flips`, `max_iterations`, `max_simplices_removed`) and surface
   non‑convergence as a typed error — never by logging and proceeding.
 
 ### Validation layering
 
 The library exposes four validation levels, each a superset of the last:
 
-1. **Level 1 — elements**: individual cells, vertices, facets are
+1. **Level 1 — elements**: individual simplices, vertices, facets are
    internally consistent (dimensions, UUIDs, coordinate finiteness).
 2. **Level 2 — structure**: adjacency pointers and neighbour links form a
    valid incidence graph; no dangling keys.
@@ -310,7 +310,7 @@ degenerate input, and tests under `tests/proptest_sos.rs` enforce that.
 ### Composability
 
 - Const‑generic `D` on every core type (`DelaunayTriangulation<K, U, V, D>`,
-  `Tds<T, U, V, D>`, `Cell<T, U, V, D>`, `Vertex<T, U, D>`, `Point<T, D>`).
+  `Tds<T, U, V, D>`, `Simplex<T, U, V, D>`, `Vertex<T, U, D>`, `Point<T, D>`).
   No runtime dimension.
 - Per‑simplex data is stack‑allocated (`[T; D]` coordinates,
   `SmallBuffer<VertexKey, MAX_PRACTICAL_DIMENSION_SIZE>`).  The
@@ -330,10 +330,10 @@ degenerate input, and tests under `tests/proptest_sos.rs` enforce that.
   for documented, debug‑only precondition violations; library code in
   `src/` must not panic on user input.
 - Borrow by default (`&T`, `&mut T`, `&[T]`); return borrowed views where
-  possible.  `FacetView`, `AdjacencyIndex`, and the `cells()`/`vertices()`
+  possible.  `FacetView`, `AdjacencyIndex`, and the `simplices()`/`vertices()`
   iterators are examples.
 - Type and function names match the textbook vocabulary: `Triangulation`,
-  `Vertex`, `Cell`, `Facet`, `Ridge`, `InSphere`, `Orientation`,
+  `Vertex`, `Simplex`, `Facet`, `Ridge`, `InSphere`, `Orientation`,
   `insphere`, `circumcenter`, `circumradius`.  Avoid Rust‑ecosystem
   abstractions that obscure the math.
 - Use `tracing::{debug,info,warn,error}!` for committed diagnostics
@@ -392,7 +392,7 @@ degenerate input, and tests under `tests/proptest_sos.rs` enforce that.
 - Unit tests cover known values, error paths, and dimension‑generic
   correctness.  Dimension‑generic tests **must cover D=2 through D=5**
   whenever feasible; use `pastey` macros to generate per‑dimension tests
-  (see `src/core/cell.rs`, `src/core/tds.rs` for patterns).
+  (see `src/core/simplex.rs`, `src/core/tds.rs` for patterns).
 - Proptests under `tests/proptest_*.rs` cover algebraic and
   topological invariants — round‑trips, Euler characteristic, orientation
   sign agreement, SoS consistency — not just "does it not panic".

CONTRIBUTING.md

@@ -542,7 +542,7 @@ The project uses comprehensive CI workflows:
 - **Code Quality** (`.github/workflows/rust-clippy.yml`): Strict linting with SARIF upload
 - **CodeRabbit** (`.coderabbit.yml`): PR review comments for curated quality feedback
 - **Codacy** (`.codacy.yml`): Curated PR quality feedback and duplication/complexity metrics
-- **Codacy SARIF mirror** (`.github/workflows/codacy.yml`): Markdownlint-only SARIF upload
+- **Codacy SARIF mirror** (`.github/workflows/codacy.yml`): Repository-owned Opengrep SARIF upload
 - **Coverage** (`.github/workflows/codecov.yml`): Test coverage tracking with 5-minute per-test timeout
 
 All PRs must pass CI checks before merging.
@@ -569,14 +569,15 @@ tool configuration, but Codacy does not use that file to turn tools on or off.
 - **Configuration**: `.codacy.yml` in the project root
 - **Source of Truth**: Treat the tool lists below as a snapshot; verify current enablement in
   Codacy project settings -> Tools / Code Patterns or Codacy configuration sync before relying on them
-- **Enabled Tools**: Markdownlint, Ruff, ShellCheck, duplication, and advisory Lizard
+- **Enabled Tools**: Markdownlint, Ruff, ShellCheck, repository-owned Opengrep, duplication, and advisory Lizard
 - **Disabled Tools**: Bandit, Prospector, Pylint, broad Opengrep, Trivy, Jackson Linter, and Spectral
 - **Documentation Analysis**: Markdownlint uses `.markdownlint.json`
 - **Python Analysis**: Ruff uses `pyproject.toml`
 - **Local/CI Analysis**: Rust, Python, shell, YAML, TOML, JSON, and GitHub Actions checks run through `just check`
 - **Security Analysis**: Uses CodeQL and cargo-audit rather than Codacy's broader engine set
-- **Code Scanning Mirror**: `.github/workflows/codacy.yml` runs Markdownlint only so Codacy's maintainability
-  findings stay in PR feedback instead of GitHub Code Scanning
+- **Code Scanning Mirror**: `.github/workflows/codacy.yml` uploads only repository-owned Opengrep
+  findings whose rule IDs start with `delaunay.` so Codacy's default maintainability findings stay in
+  PR feedback instead of GitHub Code Scanning
 
 **Key Benefits:**
 
@@ -648,7 +649,7 @@ fix(geometry): handle NaN coordinates in point validation
 fix: resolve memory leak in vertex insertion
 
 # Performance
-perf(core): optimize Bowyer-Watson algorithm with cell caching
+perf(core): optimize Bowyer-Watson algorithm with simplex caching
 perf: reduce allocations in neighbor assignment
 
 # Breaking changes
@@ -721,7 +722,7 @@ algorithm layer. Do not make `crate::core` public or add a broad
 `delaunay::core` facade. The public low-level surface should stay explicit and
 workflow-oriented:
 
-- `delaunay::tds` for cells, facets, vertex keys, TDS validation, and generic
+- `delaunay::tds` for simplices, facets, vertex keys, TDS validation, and generic
   triangulation data structures
 - `delaunay::collections` for collection aliases, small buffers, and secondary
   maps

Cargo.toml

@@ -13,7 +13,6 @@ keywords = [ "delaunay", "triangulation", "geometry", "convex-hull", "simplicial
 categories = [ "algorithms", "mathematics", "science" ]
 readme = "README.md"
 include = [
-    "/Cargo.lock",
     "/Cargo.toml",
     "/CITATION.cff",
     "/LICENSE",

README.md

@@ -101,8 +101,8 @@ complete technical background.
 
 ## ✨ Features
 
-- [x]  Copyable data types associated with vertices and cells (integers,
-  floats, chars, custom enums), plus `CellSecondaryMap` and
+- [x]  Copyable data types associated with vertices and simplices (integers,
+  floats, chars, custom enums), plus `SimplexSecondaryMap` and
   `VertexSecondaryMap` aliases for caller-owned key-indexed algorithm state
 - [x]  D-dimensional [Delaunay triangulations]
 - [x]  D-dimensional [Convex hulls]
@@ -137,7 +137,7 @@ complete technical background.
 - [x]  4-level validation hierarchy (element validity → TDS structural
   validity → manifold topology → Delaunay property), including full
   diagnostics via `validation_report`
-- [x]  Coherent combinatorial orientation validation/normalization for cells,
+- [x]  Coherent combinatorial orientation validation/normalization for simplices,
   maintaining oriented simplicial complexes
 - [x]  Typed construction, insertion, TDS, topology, validation, and repair
   errors that preserve source context for callers and diagnostics
@@ -183,7 +183,7 @@ Choose the smallest prelude that matches the task:
 | Construction telemetry diagnostics | `use delaunay::prelude::triangulation::diagnostics::*` |
 | Construction validation cadence/policy | `use delaunay::prelude::triangulation::validation::*` |
 | Hilbert ordering and quantization utilities | `use delaunay::prelude::ordering::*` |
-| Low-level TDS cells, facets, keys, and validation reports | `use delaunay::prelude::tds::*` |
+| Low-level TDS simplices, facets, keys, and validation reports | `use delaunay::prelude::tds::*` |
 | Collection aliases and small buffers | `use delaunay::prelude::collections::*` |
 | Topology validation and Euler characteristic helpers | `use delaunay::prelude::topology::validation::*` |
 | Topological spaces and topology traits | `use delaunay::prelude::topology::spaces::*` |
@@ -286,7 +286,7 @@ For the full periodic image-point method (Phase 2), see the
 
 | Level | What is validated | Primary API |
 |---|---|---|
-| 1 | Element validity (vertex/cell primitives) | `dt.validate()` / `dt.validation_report()` |
+| 1 | Element validity (vertex/simplex primitives) | `dt.validate()` / `dt.validation_report()` |
 | 2 | TDS structural validity (keys, incidences, neighbors) | `dt.tds().is_valid()` |
 | 3 | Manifold topology (link checks, Euler/topological consistency) | `dt.as_triangulation().is_valid()` |
 | 4 | Delaunay property (empty-circumsphere via local predicates) | `dt.is_valid()` |
@@ -544,7 +544,7 @@ Portions of this library were developed with the assistance of these AI tools:
 [Hilbert curve]: https://en.wikipedia.org/wiki/Hilbert_curve
 [exact predicates]: docs/numerical_robustness_guide.md
 [Simulation of Simplicity]: docs/numerical_robustness_guide.md#simulation-of-simplicity-sos
-[Secondary maps]: docs/workflows.md#builder-api-auxiliary-vertex-and-cell-data
+[Secondary maps]: docs/workflows.md#builder-api-auxiliary-vertex-and-simplex-data
 [Validation Guide]: docs/validation.md
 [ChatGPT]: https://openai.com/chatgpt
 [Claude]: https://www.anthropic.com/claude

REFERENCES.md

@@ -257,7 +257,7 @@ These references ensure the library's geometric computations are mathematically
 ## Mesh Quality Metrics
 
 These references inform the geometric quality measures used for evaluating simplex quality
-and selecting high-quality cells during triangulation repair.
+and selecting high-quality simplices during triangulation repair.
 
 ### Quality Measures for Simplicial Meshes
 

benches/README.md

@@ -225,7 +225,7 @@ large-scale scaling workload and the deeper profiling diagnostics:
 - construction through the default batch construction path
 - process RSS deltas during construction
 - memory allocation profiling with the optional `count-allocations` feature
-- neighbor queries, vertex iteration, and cell iteration
+- neighbor queries, vertex iteration, and simplex iteration
 - circumsphere query latency
 - algorithmic bottlenecks
 - validation component costs