pyquity 1.8.0

Python toolkit for building and analyzing multimodal street and transit networks with a focus on accessibility and distributive equity

PyQuity

PyQuity is a compact Python toolkit for building and analyzing multimodal street and transit networks with a focus on accessibility and distributive equity. Quickly generate graphs and grids, attach POIs/GTFS, compute route-based accessibility, and evaluate equity (sufficientarianism, egalitarianism, utilitarianism) with seamless GeoPandas/NetworkX/OSMnx integration.

Installation

PyQuity can be installed via PyPI:

pip install pyquity

Examples

Graph Construction

import pyquity

# Create base graphs
G_walk = pyquity.graph_from_place('Barrie, Canada', network_type='walk')
G_bike = pyquity.graph_from_place('Barrie, Canada', network_type='bike')

# Create GTFS graph (GTFS zip file)
G_gtfs = pyquity.graph_from_gtfs('gtfs.zip')

# Combine base graphs with GTFS graph
MG_walk = pyquity.multimodal_graph(G_walk, G_gtfs)
MG_bike = pyquity.multimodal_graph(G_bike, G_gtfs)

Grid Construction

# Create amenity
amenity = pyquity.amenity_from_place('Barrie, Canada', amenity_type='education')

# Create grid
grid = pyquity.grid_from_place('Barrie, Canada', grid_size=1000)

# Add amenity and micromobility into grid
grid = pyquity.amenity_in_grid(grid, amenity)
grid = pyquity.micromobility_in_grid(grid, micromobility_size=100)

Equity Construction

# Create equity properties
equity = pyquity.Equity(MG_walk, MG_bike, grid, amenity)

# Measuring equity
grid = equity.sufficientarianism(served_time=15, weight='travel_time')
grid = equity.utilitarianism(served_time=15, weight='travel_time')
gini, lorenz = equity.egalitarianism(grid)