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Library for Linear Reference System

Linear Reference allows to identify a position along a curve (a road, a canal, a railroad…) relative to fixed reference points.

We call:

  • anchor a reference point: it can be milestones, a landmark, an intersection…
  • scale the list of anchors and the theoretical distance between them,
  • curve the physical description of the object to reference,
  • linear referencing method (LRM) the combination of a scale and a curve,
  • linear referencing system (LRS) the complete set of data.

While the logic is quite simple, multiple small subtleties make the LRS difficult to use. Distances between milestones change (construction of a bypass around a town), the origin of curve is displaced (the railway station moved), there is only one scale for a river and its parallel running canal…

This library aims to handle many edge cases and makes little assumptions about the data:

  • anchors are not always numbers,
  • anchors don’t need to be on the curve,
  • distances between anchors are not fixed,
  • distance between anchors might not match the measured distance,
  • works on spherical and projected coordinates,
  • a single scale can be used for many curves.

Using the library

Rust

Use the crate liblrs in your dependencies.

See the documentation to get started

Javascript bindings and HTML demonstrator

The core library is written in rust. We expose javascript binding through WebAssembly. Those bindings can be built in the wasm directory.

cd wasm
npm install
npm build

Demonstrator

A simple HTML demonstrator allows to test the data and the functions. It is available online at https://OpenRailAssociation.github.io/liblrs/.

To run locally:

cd wasm
npm install
npm install -g wasm-pack
npm run serve

And open your browser at http://localhost:8080

You can customize the map background if you provide your own maplibre style:

MAPLIBRE_STYLE="https://your_tile_provider/style.json?key=42" npm run serve

Python bindings

The library is also exposed as python bindings and published on PyPI.

See the dedicated directory for more informations.

Data serialization with FlatBuffers

The data that defines an LRS is serialized using the FlatBuffers format.

The schema is described in schema/lrs.fbs. The library is written in rust and the generated file is commited. This means there is no need to have the flatc executable to build and run this project.

If your contribution changes the schema, you will need to generate the file with flatc. The version must be the release 23.5.26. Do not use a version built from master.

flatc -o src --rust schema/lrs.fbs

Norms

Comment convention

See How to write documentation in Rust to keep the code clean and clear (also this for other examples).

Extracting geometry from OpenStreetMap

We provide a binary that extracts geometry data from OpenStreetMap and saves it in the FlatBuffer format.

For now we only handle Railway data. A tag that describes the LRM must be provided. In France, use the ref:FR:SNCF_Reseau.

Run the binary:

cargo run --release --bin geometry_from_osm -- -i france.rail.osm.pbf -o osm.lrs.bin2 --lrm-tag=ref:FR:SNCF_Reseau

Contributing

To comply with the DCO, all commits must include a Signed-off-by line. You can find more information about this here

For more advice on how to contribute, follow that link: https://osrd.fr/en/docs/guides/contribute/contribute-code

Troubleshooting

pyO3

If you have troubles with rust-analyzer giving errors like pyclass: proc-macro crate build data is missing dylib path then it might be a pyO3 configuration issue.

Setting the PYO3_PYTHON environment variable to a python executable may fix the issue.