OpenLR location dereferencer
Project description
openlr_dereferencer
This is a Python package for decoding OpenLR™ location references on target maps.
Dependencies
- Python ≥ 3.6
- geographiclib (PyPi package)
- openlr (PyPi package)
- For unittests, SQlite with spatialite extension is required
State
- ☑ Example map format
- ☑ Routing
- ☑ Candidate route rating
- ☑ Backtracking to get correct routes
- ☑ Decoding line locations
- ☐ Decoding 'point along line' locations
- ☐ Decoding 'POI with access point' locations
Structure
It is divided into the following submodules:
maps
Contains an abstract map class, which you may want to implement for your target map.
maps.wgs84
provides methods for reckoning with WGS84 coordinates.
example_sqlite_map
Implements the abstract map class for the example map format used in the unittests and examples
decoding
The actual logic for matching references onto a map.
This includes finding candidate lines and scoring them, and assembling a dereferenced location.
Usage
The decode(reference, mapreader)
function will take a location reference and return map objects.
Usage Example
First, implement the MapReader
class for your map. The example_sqlite_map
module is an implementation you may look at.
Second, construct a location reference. For instance, parse an OpenLR line location string:
from openlr import binary_decode
reference = binary_decode("CwmG8yVjzCq0Dfzr/gErRRs=")
Third, decode the reference on an instance of your map reader class:
from openlr_dereferencer import decode
real_location = decode(reference, mapreader)
real_location.lines # <- A list of map objects
Configuration
Candidates
The configuration value openlr_dereferencer.SEARCH_RADIUS
determines how far away from the LRP road candidates are searched.
The unit is meters, the default 100.
Scores
Every candidate line gets a score from 0
(bad) to 1
(perfect).
There are four scoring weight parameters:
- GEO_WEIGHT = 0.25
- FRC_WEIGHT = 0.25
- FOW_WEIGHT = 0.25
- BEAR_WEIGHT = 0.25
They determine how much influence a single aspect has on an overall candidate's score.
You may just change them before decoding:
from openlr_dereferencer.decoding import scoring
scoring.GEO_WEIGHT = 0.66
scoring.FRC_WEIGHT = 0.17
scoring.FOW_WEIGHT = 0.17
scoring.BEAR_WEIGHT = 0
Logging
openlr-dereferencer
logs all mapmatching decisions using the standard library logging
module.
Use it to turn on debugging:
import logging
logging.basicConfig(level=logging.DEBUG)
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