Plot Activity Plan Travel¶

In this example, we show how plans can be plotted spatially using plotly

In [1]:

import os

from pam import read

import os from pam import read

In [2]:

pop = read.read_matsim(
    os.path.join("data", "example_data", "example_plans.xml")
)  # load small sample from the test suite

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.

In [3]:

pop.build_travel_geodataframe(from_epsg="epsg:27700", to_epsg="epsg:4326").head()

pop.build_travel_geodataframe(from_epsg="epsg:27700", to_epsg="epsg:4326").head()

Out[3]:

	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 (-0.33840 51.58109, -0.13191 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 (-0.13191 51.53909, -0.33840 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 (0.05547 51.45140, -0.06349 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 (-0.06349 51.51844, 0.05547 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 (-0.06176 51.35331, -0.10474 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.

In [4]:

mapbox_access_token = "token"

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:

pop.plot_travel_plotly( epsg='epsg:27700', mapbox_access_token=mapbox_access_token )

You can also colour by any column you see in the GeoDataFrame (see above). E.g. to colour by agent id (pid)

pop.plot_travel_plotly( epsg='epsg:27700', mapbox_access_token=mapbox_access_token, colour_by='pid' )