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OR Apache-2.0","homepage":"https://graydonpleasants.github.io/geo-polygonize/","repository":{"type":"git","url":"git+https://github.com/graydonpleasants/geo-polygonize.git"},"description":"A native Rust port of the JTS/GEOS polygonization algorithm (Wasm)","maintainers":[{"name":"graydonpleasants","email":"graydonpleasants@gmail.com"}],"readme":"# Geo Polygonize\n\nA native Rust port of the JTS/GEOS polygonization algorithm. This crate allows you to reconstruct valid polygons from a set of lines, including handling of complex topologies like holes, nested shells, and disconnected components.\n\n[![Ask DeepWiki](https://deepwiki.com/badge.svg)](https://deepwiki.com/graydonpleasants/geo-polygonize)\n\n## Features\n\n- **Robust Polygonization**: Extracts polygons from unstructured linework.\n- **Iterative Grid Noding (Unchecked)**: Splits and snaps dirty linework, without claiming certified snap-rounding guarantees.\n- **Certified Fixed-Precision Noding**: Optional hot-pixel snap rounding with an independent full-noding postcondition check.\n- **Hardware Acceleration**: Uses **SIMD** instructions (via `wide` crate) for critical geometric predicates like Point-in-Polygon checks.\n- **Wasm Optimized**: Tailored for WebAssembly with `talc` allocator and binary GeoArrow support.\n- **Performance**: SIMD, spatial indexing, and optional parallel execution, with checked-in benchmark tooling.\n- **Geo Ecosystem**: Fully integrated with `geo-types` and `geo` crates.\n- **GeoArrow Support**: Arrow C Data Interface and Arrow IPC integration with GeoArrow metadata.\n\n## Engineering Roadmap\n\nFor delivered foundations and the next evidence-gated work, see [ROADMAP.md](ROADMAP.md).\n\n## Support policy\n\nSupported APIs, toolchains, targets, feature combinations, compatibility\nwindows, and failure/threading contracts are defined in\n[SUPPORT.md](SUPPORT.md).\n\nUsers migrating from the 0.x API should also read the\n[0.x to 1.0 migration guide](docs/guide/migration-1-0.md).\n\n## Usage\n\n### Library\n\n```rust\nuse geo_polygonize_core::{polygonize_line_strings, PolygonizerOptions};\nuse geo_types::LineString;\n\nfn main() {\n    let ring = LineString::from(vec![\n        (0.0, 0.0),\n        (10.0, 0.0),\n        (10.0, 10.0),\n        (0.0, 10.0),\n        (0.0, 0.0),\n    ]);\n\n    let result = polygonize_line_strings([&ring], &PolygonizerOptions::default())\n        .expect(\"Polygonization failed\");\n    let polygons = result.into_multi_polygon();\n\n    for polygon in polygons {\n        println!(\"Found polygon: {polygon:?}\");\n    }\n}\n```\n\n`polygonize_line_strings` accepts owned or borrowed `geo_traits::LineStringTrait`\nvalues. Use `polygonize` when source IDs or Z values must be supplied explicitly,\nand keep its full result when dangles, cut edges, invalid rings, or diagnostics are\nneeded.\n\nRust consumers should import the supported facade from the crate root. Graph,\nnoding, containment, utility, mutable-builder, and tiled APIs are internal or\nexperimental research surfaces and may change without 1.x compatibility\nguarantees. `#[doc(hidden)]` is documentation guidance, not Rust privacy;\ncompiler-public research items are governed separately from the supported\nfacade.\n`TiledPolygonizer` validates its grid/options and propagates per-tile errors,\nbut callers must still choose a sufficient buffer and verify untiled equivalence\nfor their workload. Its result includes per-tile topology counts and merge/dedup\ncounts; these are observational and do not certify buffer sufficiency. Canonical\nmode applies the same final ordering pass after tile merge; the equivalence gate\ncovers one, two, four, and many boundary crossings plus concave, hole,\ndirty-intersection, and dangle cases.\n\n### Choosing noding and precision\n\nPolygonization quality is heavily influenced by input noding strategy.\n\n- **`node_input = false`** (default): Fastest path. Use this when your input linework is already noded (all intersections are explicit vertices).\n- **`node_input = true`**: Enables unchecked iterative grid noding. Use this for real-world datasets that may contain slight misalignments, overlaps, or self-intersections, and validate outputs when correctness must be certified.\n- **`PrecisionModel::Floating`** (default) preserves input coordinates and uses floating-point intersections.\n- **`PrecisionModel::FixedGrid { grid_size }`** rounds topology coordinates to an explicit positive grid, even when input noding is disabled. Choose the grid in the units of your data; oversnapping can collapse narrow features.\n\nPractical workflow:\n1. Run with `node_input = false` first on trusted data.\n2. If you observe missing polygons, sliver artifacts, or unresolved intersections, enable `node_input`.\n3. Use a fixed precision model only when your application has an explicit coordinate grid contract.\n\nCanonical options now use `precision_model` instead of `snap_grid_size`.\nLegacy positional Python, Wasm, and C APIs still translate their grid argument\nwhen noding is enabled and ignore it on the non-noding fast path.\n\nSet `options.noding.guarantee` to `NodingGuarantee::Validate` to run an\nindependent full-noding check before graph construction. Validation reports the\nfirst pair with an interior intersection or unnormalized collinear overlap.\nUse `NodingGuarantee::CertifiedFixedPrecision` with `node_input`, `FixedGrid`,\nthe `Snap` backend, and `SnapStrategy::Grid` for hot-pixel snap rounding plus\nthat validation. Certified coordinates must fit exact integer grid indices.\n\n### Z semantics\n\nTopology is always computed in XY. `ZPolicy::InterpolateAlongEdge` is the\ndefault and reconstructs split-vertex Z on each source edge;\n`PreferNearestEndpoint` uses the nearer endpoint, and `Ignore` emits zero Z.\nWhen several source edges meet at the same XY node, the graph chooses the Z\nfrom the lowest line ID (then the lowest Z) and reports conflicts through\ndiagnostics. `ErrorOnConflict` instead returns a typed error when the difference\nexceeds `z.conflict_tolerance`.\n\nUse `Line3D` or the Python/Wasm typed-buffer APIs with `stride=3` for Z-aware\nprocessing. The GeoRust, GeoJSON, and current GeoArrow adapters are XY-only.\n\n### Output semantics\n\nThe polygonizer intentionally returns only valid polygonal areas that can be formed from closed cycles:\n\n- **Dangles are removed**: dead-end edges do not appear in output polygons.\n- **Cut edges are excluded**: edges that are connected but cannot bound a face are ignored.\n- **Holes and nested shells are preserved** when enough boundary information is present.\n\nThis behavior matches classical JTS/GEOS polygonization semantics and is useful for cleaning linework before area analysis.\n\n### GeoArrow Integration\n\nRust Arrow and GeoArrow adapters live in the `geo-polygonize-arrow` crate;\nthe Wasm crate includes it automatically.\n\nFor the Arrow C Data Interface ABI, including ownership and error retrieval,\nsee [docs/C_ABI.md](docs/C_ABI.md).\n\n```rust\nuse geo_polygonize_arrow::{polygonize_arrow, PolygonizerOptions};\n// ... create Arrow array ...\n// let result = polygonize_arrow(&array, &field, options);\n```\n\nThe FlatGeoBuf file adapter lives in the `geo-polygonize-flatgeobuf` crate.\n\n### Python\n\nThe Python package is published as `geo-polygonize-py` and imported as `geo_polygonize`.\n\n```bash\npip install geo-polygonize-py\n```\n\n```python\nimport numpy as np\nfrom geo_polygonize import polygonize, import_probe\n\n# 1. Using Shapely LineStrings or coordinate lists directly\nlines = [\n    [(0, 0), (10, 0), (10, 10), (0, 10), (0, 0)],\n    [(0, 0), (10, 10)]\n]\n\n# return_polygons=True returns a list of shapely.geometry.Polygon objects\npolygons = polygonize(lines=lines, return_polygons=True)\nfor p in polygons:\n    print(p.area)\n\n# 2. Using High-Performance Flat Arrays\n# Flat buffers avoid Python object-per-coordinate overhead\ncoords = np.array([\n    0.0, 0.0, 10.0, 0.0, 10.0, 10.0, 0.0, 10.0, 0.0, 0.0,\n    0.0, 0.0, 10.0, 10.0\n], dtype=np.float64)\n\n# Start indices for each line segment.\n# The final closing offset is computed implicitly.\noffsets = np.array([0, 5], dtype=np.uint32)\n\n# `report` preserves the compatibility result with objects, buffers, fingerprint,\n# diagnostics, and per-binding phase timings.\nresult_dict = polygonize(coords=coords, offsets=offsets)\n\n# Request only the representation you need.\nbuffers = polygonize(coords=coords, offsets=offsets, output=\"buffers\")\nobjects = polygonize(coords=coords, offsets=offsets, output=\"objects\")\n\n# Execution budgets are non-semantic and stay separate from topology options.\nbounded = polygonize(\n    coords=coords,\n    offsets=offsets,\n    output=\"buffers\",\n    execution_limits={\"max_output_coordinates\": 1_000_000},\n)\n\n# Native-extension probes are cheap and safe for optional integrations.\nok, error = import_probe()\n```\n\nCFB/autograder integrations should use the versioned production profile rather\nthan assembling caller-side knobs or using legacy `polygonize(..., node=True,\nsnap=0.5)` calls:\n\n```python\nfrom geo_polygonize import cfb_robust_options, polygonize_with_options\n\nresult = polygonize_with_options(\n    coords=coords,\n    offsets=offsets,\n    options=cfb_robust_options(),\n)\n```\n\nThe default `report` return shape remains a stable dictionary with `polygons`\nas `SimplePolygon` values. `buffers` omits Python geometry objects and the\nfingerprint; `objects` omits flattened arrays and the fingerprint. Use\n`return_polygons=True` only when you want Shapely `Polygon` objects.\n\nWhen provenance is enabled, coincident and partially overlapping input lines\nare dissolved into one topology edge while every contributing nonzero\n`line_id` remains in the polygon's sorted `boundary_line_ids`.\n\n`SnapStrategy::Grid` keeps topology and output coordinates on a configured\nfixed precision grid. The CFB profile uses `GeosCompat`: the grid establishes robust\ntopology, then output nodes regain deterministic source XY coordinates to better\nmatch Shapely `snap` plus full-precision noding. It is not `set_precision`\nemulation, and exact parity is not guaranteed for many-to-one snaps.\n\nFor Shapely parity checks, compare report-mode outputs with the built-in\nmismatch helper:\n\n```python\nfrom geo_polygonize import explain_mismatch, polygonize_with_options\n\noptions = cfb_robust_options()\nresult_a = polygonize_with_options(coords=coords_a, offsets=offsets_a, options=options)\nresult_b = polygonize_with_options(coords=coords_b, offsets=offsets_b, options=options)\nresult_a[\"options\"] = options\nresult_b[\"options\"] = options\n\nmismatch = explain_mismatch(result_a, result_b)\n```\n\nFor a minimal Shapely smoke comparison, use area signatures:\n\n```python\nfrom shapely.ops import polygonize as shapely_polygonize\n\nrust_polys = polygonize_with_options(lines=lines, options=cfb_robust_options(), return_polygons=True)\nrust_areas = sorted(round(poly.area, 6) for poly in rust_polys)\nshapely_areas = sorted(round(poly.area, 6) for poly in shapely_polygonize(lines))\n```\n\n### WebAssembly (WASM)\n\nThis library supports WebAssembly with an ergonomic dual-build configuration that automatically utilizes SIMD instructions where available.\n\n**Installation:**\n```bash\nnpm install geo-polygonize\n```\n\n**Standard Usage (Quick Demos):**\nThe default entry point automatically handles feature detection (SIMD) and lazy-loading of the Wasm binary. The Wasm is inlined as a Base64 Data URI, so no extra bundler configuration is needed. For app builds, prefer the slim entry point below so your bundler keeps the Wasm assets out of the JavaScript chunk.\n\n```javascript\nimport init, { polygonize, polygonize_geoarrow } from \"geo-polygonize\";\n\nasync function run() {\n    await init();\n\n    const geojson = {\n        \"type\": \"FeatureCollection\",\n        \"features\": [\n            // ... your line features\n        ]\n    };\n\n    // Returns a GeoJSON FeatureCollection string\n    // Pass explicitly matching backend configuration if desired\n    const result = polygonize(\n        JSON.stringify(geojson),\n        true, // node_input\n        0.5   // snap_grid_size\n    );\n    console.log(JSON.parse(result));\n\n    // Or use Arrow IPC bytes\n    // const ipcBuffer = ...;\n    // const arrowResult = polygonize_geoarrow(ipcBuffer, false, 1e-10, false);\n}\n```\n\n**Slim Usage (Apps / Manual Loading):**\nFor Vite and other app bundlers, import from `geo-polygonize/slim` and pass explicit Wasm asset URLs.\n\n```javascript\nimport { cfbRobustOptions, initBest } from \"geo-polygonize/slim\";\nimport scalarUrl from \"geo-polygonize/geo_polygonize.wasm?url\";\nimport simdUrl from \"geo-polygonize/geo_polygonize_simd.wasm?url\";\n\nasync function run() {\n    const wasm = await initBest(\n        { module_or_path: scalarUrl },\n        { module_or_path: simdUrl },\n    );\n\n    const result = wasm.polygonizeWithOptions(\n        JSON.stringify(geojson),\n        cfbRobustOptions,\n    );\n}\n```\n\nFor cancellable browser work, use the worker-backed asynchronous entry point.\nAborting terminates its disposable worker; the direct Wasm exports above remain\nsynchronous and cannot be interrupted with an `AbortSignal`.\n\n```javascript\nimport { polygonizeWithOptionsAsync } from \"geo-polygonize\";\n\nconst controller = new AbortController();\nconst result = await polygonizeWithOptionsAsync(\n    JSON.stringify(geojson),\n    cfbRobustOptions,\n    { signal: controller.signal },\n);\n// controller.abort();\n```\n\n**Multithreaded Usage (Experimental):**\nThis library provides a multithreaded build powered by `wasm-bindgen-rayon`.\n\n```javascript\nimport init, { initThreadPool, polygonize } from \"geo-polygonize/threads\";\n\nasync function run() {\n    await init();\n\n    // Initialize thread pool (e.g., with navigator.hardwareConcurrency)\n    await initThreadPool(navigator.hardwareConcurrency);\n\n    // ... use polygonize as usual\n}\n```\n\n**Important:** Multithreaded WebAssembly requires `SharedArrayBuffer`, which is only available in secure contexts. You **must** serve your page with the following headers:\n```text\nCross-Origin-Opener-Policy: same-origin\nCross-Origin-Embedder-Policy: require-corp\n```\n\n### CLI Example\n\nThe repository includes a CLI tool to polygonize GeoJSON files.\n\n```bash\n# Build the example\ncargo build -p geo-polygonize-core --example polygonize --release\n\n# Run on input lines\ncargo run -p geo-polygonize-core --release --example polygonize -- --input lines.geojson --output polygons.geojson --node\n```\n\n### Visualization\n\nYou can visualize the results using the provided Python script (requires `matplotlib` and `shapely`).\n\n```bash\npython3 scripts/visualize.py --input lines.geojson --output polygons.geojson --save result.png\n```\n\n## Examples\n\nBelow are some examples of what the polygonizer can do.\n\n### Nested Holes and Islands\n\nThe algorithm correctly identifies nested structures (Island inside a Hole inside a Shell).\n\n![Nested Holes](images/nested_holes.png)\n\n### Incomplete Grid / Dangles\n\nThe algorithm prunes dangles (dead-end lines) and extracts only closed cycles.\n\n![Incomplete Grid](images/grid_incomplete.png)\n\n### Touching Polygons (Shared Edges)\n\nUsing robust noding (`--node`), it can reconstruct adjacent polygons that share boundaries, even if the input lines are not perfectly noded.\n\n![Touching Polygons](images/touching_polys.png)\n\n### Self-Intersecting Geometry (Bowtie)\n\nSelf-intersecting lines are split at intersection points, and valid cycles are extracted.\n\n![Bowtie](images/complex_bowtie.png)\n\n### Complex Geometries\n\nThe polygonizer can handle complex, curved inputs (approximated by LineStrings) such as overlapping circles and shapes with multiple holes.\n\n**Overlapping Circles**: Note how the intersection regions are correctly identified as separate polygons.\n\n![Overlapping Circles](images/overlapping_circles.png)\n\n**Curved Holes**: A complex polygon with multiple circular holes.\n\n![Curved Holes](images/curved_holes.png)\n\n## Benchmarks\n\nThis library includes a \"severe\" comparison suite against `shapely` (GEOS).\n\nSee [BENCHMARKS.md](BENCHMARKS.md) for detailed results and instructions on how to run them.\n\n## Architecture\n\nThis implementation moves away from the pointer-based graph structures of JTS/GEOS to a Rust-idiomatic Index Graph (Arena) approach.\n\nSee [ARCHITECTURE.md](ARCHITECTURE.md) for a deep dive into the optimization strategies.\n\nKey optimizations include:\n1.  **Noding**: Unchecked iterative grid noding with spatially dispatched intersection detection.\n2.  **Vectorization**: SIMD-accelerated Ray Casting for efficient Hole Assignment.\n3.  **Memory Layout**: Structure of Arrays (SoA) for graph nodes and `talc` allocator for Wasm.\n\n## License\n\nMIT/Apache-2.0\n","readmeFilename":"README.md","author":{"name":"Graydon Pleasants","email":"graydonpleasants@gmail.com"}}