Plot Activity Plan Travel¶
In this example, we show how plans can be plotted spatially using plotly
import os
from pam import read
pop = read.read_matsim(
os.path.join("data", "example_data", "example_plans.xml")
) # load small sample from the test suite
You can generate geopandas.GeoDataFrames for Population's, Household's or Person's travel. the route_id, service_id and network_route refer to the network used for running the simulation. GeoDataFrames are very useful, they let you to generate geojsons simply and quickly, which you can then load up in kepler.
gdf.to_file('path/to/file/gdf.geojson'), driver='GeoJSON')
note that to use this geojson with kepler you will need the geometry to be in 'epsg:4326'. You can do this with the method below.
pop.build_travel_geodataframe(from_epsg="epsg:27700", to_epsg="epsg:4326").head()
| mode | purp | seq | freq | start_time | end_time | start_location | end_location | geometry | distance | service_id | route_id | o_stop | d_stop | network_route | pid | hid | |
|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|
| 0 | pt | work | 1 | None | 1900-01-01 07:24:52 | 1900-01-01 07:24:52 | (515226.0, 188222.0) | (529652.0, 183897.0) | LINESTRING (-0.33843 51.58109, -0.13193 51.53909) | 15060.381834 | None | None | None | None | [] | census_0 | census_0 |
| 1 | pt | None | 2 | None | 1900-01-01 14:50:52 | 1900-01-01 14:50:52 | (529652.0, 183897.0) | (515226.0, 188222.0) | LINESTRING (-0.13193 51.53909, -0.33843 51.58109) | 15060.381834 | None | None | None | None | [] | census_0 | census_0 |
| 2 | pt | work | 1 | None | 1900-01-01 08:27:33 | 1900-01-01 08:27:33 | (542920.0, 174494.0) | (534457.0, 181724.0) | LINESTRING (0.05545 51.45140, -0.06352 51.51844) | 11130.825172 | None | None | None | None | [] | census_1 | census_1 |
| 3 | pt | None | 2 | None | 1900-01-01 17:45:33 | 1900-01-01 17:45:33 | (534457.0, 181724.0) | (542920.0, 174494.0) | LINESTRING (-0.06352 51.51844, 0.05545 51.45140) | 11130.825172 | None | None | None | None | [] | census_1 | census_1 |
| 4 | pt | work | 1 | None | 1900-01-01 07:01:09 | 1900-01-01 07:01:09 | (535063.0, 163365.0) | (531998.0, 166080.0) | LINESTRING (-0.06179 51.35332, -0.10477 51.37843) | 4094.563469 | None | None | None | None | [] | census_10 | census_10 |
You can also plot travel using plotly. You will need a mapbox token, which you can get here: https://docs.mapbox.com/help/how-mapbox-works/access-tokens/. Be careful not to commit your token in the repo.
mapbox_access_token = "token"
You need to specify the coordinate system to plot it on a map. By default the plot will colour by mode:
You can also colour by any column you see in the GeoDataFrame (see above). E.g. to colour by agent id (pid)
