stplanpy.route module

The functions in this module perform various operations on routes.

stplanpy.route.directness(fd: geopandas.geodataframe.GeoDataFrame) → pandas.core.series.Series

Compute the directness of a route

This function computes the directness of the routes in GeoDataFrame fd. Directness is defined as the distance along a route divided by the distance as the crow flies.

Parameters

None –

Returns

Series with directness values.

Return type

pandas.Series

See also

routes

Examples

import pandas as pd
import geopandas as gpd
from shapely import wkt
from stplanpy import route

# Create DataFrames
df = pd.DataFrame(
    {"all": [4, 3, 2, 5],
    "bike": [2, 0, 1, 3],
    "go_dutch": [3, 5, 0, 4],
    "geometry": ["LINESTRING(1 0,0 0,1 1,2 1,3 0)",
    "LINESTRING(0 2,1 1,2 1,3 2,2 2)",
    "LINESTRING(1 0,1 1,2 1,2 0)",
    "LINESTRING(1 2,1 1,2 1,2 2,3 2)"]})

# Convert to WTK
df["geometry"] = gpd.GeoSeries.from_wkt(df["geometry"])

# Create GeoDataFrame
gdf = gpd.GeoDataFrame(df, geometry='geometry')

# Compute directness
gdf["directness"] = gdf.directness()

stplanpy.route.network(fd: geopandas.geodataframe.GeoDataFrame, modes=['bike'], max_rows=1000) → geopandas.geodataframe.GeoDataFrame

Reduce route data to a network

This function reduces route data in GeoDataFrame fd to a network for the modes of transporation listed in modes. All line segments of routes that overlap are reduced to one segment and their mode numbers are summed up.

Parameters

• modes (list of str, defaults to ["bike"]) – List of modes of transportation that the network is computed for. Defaults to [“bike”].

• max_rows (int, defaults to 4000) – To reduce the memory footprint a GeoDataFrames is split up in blocks of max_rows rows. This value can be increased on computers with enough RAM.

Returns

GeoDataFrame containing the network.

Return type

geopandas.GeoDataFrame

See also

routes

Examples

mport pandas as pd
port geopandas as gpd
om shapely import wkt
om stplanpy import route

Create DataFrames
df = pd.DataFrame(
    {"all": [4, 3, 2, 5],
    "bike": [2, 0, 1, 3],
    "go_dutch": [3, 5, 0, 4],
    "geometry": ["LINESTRING(1 0,0 0,1 1,2 1,3 0)",
    "LINESTRING(0 2,1 1,2 1,3 2,2 2)",
    "LINESTRING(1 0,1 1,2 1,2 0)",
    "LINESTRING(1 2,1 1,2 1,2 2,3 2)"]})

# Convert to WTK
df["geometry"] = gpd.GeoSeries.from_wkt(df["geometry"])

# Create GeoDataFrame
gdf = gpd.GeoDataFrame(df, geometry='geometry')

# Compute the network
network = gdf.network(modes=["bike", "go_dutch"])