# mappymatch
Mappymatch is a pure-python package developed and open sourced by the National Renewable Energy Laboratory. It contains a collection of "Matchers" that enable matching a GPS trace (series of GPS coordinates) to a map.
![Map Matching Animation](docs/images/map-matching.gif?raw=true)
The current matchers are:
- `LCSSMatcher`: A matcher that implements the LCSS algorithm described in this [paper](https://doi.org/10.3141%2F2645-08). Works best with high resolution GPS traces.
- `OsrmMatcher`: A light matcher that pings an OSRM server to request map matching results. See the [official documentation](http://project-osrm.org/) for more info.
- `ValhallaMatcher`: A matcher to ping a [Valhalla](https://www.interline.io/valhalla/) server for map matching results.
Currently supported map formats are:
- Open Street Maps
## Installation
```console
pip install mappymatch
```
If you have trouble with that, check out [the docs](https://nrel.github.io/mappymatch/install.html) for more detailed install instructions.
## Example Usage
The current primary workflow is to use [osmnx](https://github.com/gboeing/osmnx) to download a road network and match it using the `LCSSMatcher`.
The `LCSSMatcher` implements the map matching algorithm described in this paper:
[Zhu, Lei, Jacob R. Holden, and Jeffrey D. Gonder.
"Trajectory Segmentation Map-Matching Approach for Large-Scale, High-Resolution GPS Data."
Transportation Research Record: Journal of the Transportation Research Board 2645 (2017): 67-75.](https://doi.org/10.3141%2F2645-08)
usage:
```python
from mappymatch import package_root
from mappymatch.constructs.geofence import Geofence
from mappymatch.constructs.trace import Trace
from mappymatch.maps.nx.nx_map import NxMap
from mappymatch.matchers.lcss.lcss import LCSSMatcher
trace = Trace.from_csv(package_root() / "resources/traces/sample_trace_1.csv")
# generate a geofence polygon that surrounds the trace; units are in meters;
# this is used to query OSM for a small map that we can match to
geofence = Geofence.from_trace(trace, padding=1e3)
# uses osmnx to pull a networkx map from the OSM database
nx_map = NxMap.from_geofence(geofence)
matcher = LCSSMatcher(nx_map)
matches = matcher.match_trace(trace)
# convert the matches to a dataframe
df = matches.matches_to_dataframe()
```
## Example Notebooks
Check out the [LCSS Example](https://nrel.github.io/mappymatch/lcss-example.html) for a more detailed example of working with the LCSSMatcher.
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"description": "# mappymatch\n\nMappymatch is a pure-python package developed and open sourced by the National Renewable Energy Laboratory. It contains a collection of \"Matchers\" that enable matching a GPS trace (series of GPS coordinates) to a map.\n\n![Map Matching Animation](docs/images/map-matching.gif?raw=true)\n\nThe current matchers are:\n\n- `LCSSMatcher`: A matcher that implements the LCSS algorithm described in this [paper](https://doi.org/10.3141%2F2645-08). Works best with high resolution GPS traces.\n- `OsrmMatcher`: A light matcher that pings an OSRM server to request map matching results. See the [official documentation](http://project-osrm.org/) for more info.\n- `ValhallaMatcher`: A matcher to ping a [Valhalla](https://www.interline.io/valhalla/) server for map matching results.\n\nCurrently supported map formats are:\n\n- Open Street Maps\n\n## Installation\n\n```console\npip install mappymatch\n```\n\nIf you have trouble with that, check out [the docs](https://nrel.github.io/mappymatch/install.html) for more detailed install instructions.\n\n## Example Usage\n\nThe current primary workflow is to use [osmnx](https://github.com/gboeing/osmnx) to download a road network and match it using the `LCSSMatcher`.\n\nThe `LCSSMatcher` implements the map matching algorithm described in this paper:\n\n[Zhu, Lei, Jacob R. Holden, and Jeffrey D. Gonder.\n\"Trajectory Segmentation Map-Matching Approach for Large-Scale, High-Resolution GPS Data.\"\nTransportation Research Record: Journal of the Transportation Research Board 2645 (2017): 67-75.](https://doi.org/10.3141%2F2645-08)\n\nusage:\n\n```python\nfrom mappymatch import package_root\nfrom mappymatch.constructs.geofence import Geofence\nfrom mappymatch.constructs.trace import Trace\nfrom mappymatch.maps.nx.nx_map import NxMap\nfrom mappymatch.matchers.lcss.lcss import LCSSMatcher\n\ntrace = Trace.from_csv(package_root() / \"resources/traces/sample_trace_1.csv\")\n\n# generate a geofence polygon that surrounds the trace; units are in meters;\n# this is used to query OSM for a small map that we can match to\ngeofence = Geofence.from_trace(trace, padding=1e3)\n\n# uses osmnx to pull a networkx map from the OSM database\nnx_map = NxMap.from_geofence(geofence)\n\nmatcher = LCSSMatcher(nx_map)\n\nmatches = matcher.match_trace(trace)\n\n# convert the matches to a dataframe\ndf = matches.matches_to_dataframe()\n```\n\n## Example Notebooks\n\nCheck out the [LCSS Example](https://nrel.github.io/mappymatch/lcss-example.html) for a more detailed example of working with the LCSSMatcher.\n",
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