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Snap points to a line string keeping a given order or spacing intact

Project description

PySnapping

Snap points to a line string keeping a given order or spacing intact.

The PySnapping python library helps to solve the problem of snapping an ordered sequence of points to a line string, respecting the given input order.

The motivation for this library is to solve the problem of snapping stops onto vehicle trajectories in the GTFS format with inaccurate or missing kilometrage.

In order to be able to work with metric parameters and to treat data with large extent located anywhere on the world, we use the EPSG:4978 Cartesian 3D geocentric coordinate system for the internal representation.

The library aims to automatically classify kilometrage information as trusted or untrusted. Trusted points are always snapped as given by the kilometrage. In between trusted points, untrusted points are snapped by minimizing the sum of square snapping distances among all admissible solutions within certain radii. Admissible solutions are those that respect the order and minimum spacing between points.

Installation

Install the latest stable release from PyPI with pip:

pip install pysnapping

Modules

Linear Referencing

The pysnapping.linear_referencing module contains low-level classes and functions for referencing points along linear features in N-dimensions built on top of numpy. This contains interpolation/extrapolation along a line string and data structures optimized for projecting points to substrings of a line string.

Utils

The pysnapping.util module contains common helper functions used in other parts of the library.

Snapping

The pysnapping.snap module is the main entry point for users of the pysnapping library and provides the classes needed to use the library.

Statistics

The pysnapping.stats module provides tools to aggregate statistics about snapping failures and the methods used in case of success.

Usage

The typical usage pattern is to create a pysnapping.snap.DubiousTrajectory instance which represents a vehicle trajectory with dubious kilometrage and a pysnapping.snap.DubiousTrajectoryTrip dtrip which represents a trip along such a trajectory with dubious kilometrage for the stops. Then dtrip.to_trajectory_trip can be used to get a pysnapping.snap.TrajectorTrip trip with well defined metric kilometrage. trip.trajectory then refers to a pysnapping.snap.Trajectory instance with well defined metric kilometrage.

The trip.snap_trip_points method can be used to snap the trip points onto the trajectory, resulting in a pysnapping.snap.SnappedTripPoints instance snapped. Then you can e.g. split the trajectory at the stops using the snapped.get_inter_point_ls_coords_in_travel_direction method. Snapping can be controlled with parameters given by a pysnapping.snap.SnappingParams instance.

A more detailed usage example (e.g. how to process GTFS input) is planned but not available yet. Until then, please also check the docstrings and source code for additional usage hints/possibilities.

Issue Tracker

Please use the GitHub issue tracker to report bugs/issues.

Development

Contributing

If you want to contribute to the pysnapping library, you can make a pull request at GitHub. Before working on major features/changes, please consider contacting us about your plans. See our GitHub page for contact details.

Editable Installation

Clone this repo and enter the corresponding directory. Create a virtual environment, then install frozen requirements, dev-requirements and this library in editable mode:

python3.9 -m venv env
. env/bin/activate
pip install -U pip
pip install -r requirements.txt -r dev-requirements.txt -e .

Keep env activated for all following instructions.

Pre-Commit Hooks

Enable pre-commit hooks:

pre-commit install

From time to time (not automated yet) run

pre-commit autoupdate

to update frozen revs.

Run Tests

Run tests and analyze code coverage:

pytest --cov=pysnapping --cov-report term --cov-fail-under=85 pysnapping

Changelog

v0.2.0

Breaking Changes

  • Snapping for untrusted points is now done by an exact algorithm instead of the iterative approximate solution. This implies breaking changes to the parameters in snap.SnappingParams as well as to parts of the API of the classes in the snap module. For example: Timing information to guide the initial conditions of the iterative solution is not necessary and thus not supported any more.
  • The ordering module has been removed since it is not needed any more.

Other Changes:

  • The development toolchain now uses ruff where possible.

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