ObjectNat

Object-oriented Network Analysis Tools

РИДМИ (Russian)

ObjectNat is an open-source library developed by the IDU team for spatial and network analysis in urban studies. The library provides tools for analyzing accessibility, visibility, noise propagation, and service provision. ----

Key Features

Each feature includes a Jupyter Notebook example and full documentation.

1. Isochrones and Transport Accessibility

   Isochrones represent areas reachable from an origin point within a specified time along a transport network. This feature allows the analysis of transport accessibility using pedestrian, road, public transport, or multimodal UrbanGraph objects prepared by IduEdu.

   The library supports several methods for building isochrones:

   • Basic isochrones: display a single zone reachable within a specified time.
   • Step isochrones: divide the accessibility area into time intervals (e.g., 3, 5, 10 minutes).

   📘 Example 🔗 Documentation

2. Graph Coverage Zones from Points

   A function for generating coverage areas from a set of origin points using a transport network. It computes the area reachable from each point by travel time or distance, then builds polygons using Voronoi diagrams and clips them by a given boundary if specified.

   📘 Example 🔗 Documentation

3. Service Provision Analysis

   A function to evaluate how well residential buildings and their populations are provided with services (e.g., schools, clinics) that have limited capacity and a defined accessibility threshold (in minutes or meters). The function models the balance between supply and demand, assessing how well services meet the needs of nearby buildings within an acceptable time. ObjectNat 2.0 returns a structured ProvisionResult with a sparse flow matrix and materialization helpers for buildings, services, and link geometries.

   📘 Example 🔗 Documentation

4. Visibility Analysis

   A function for evaluating visibility from a given point or set of points to nearby buildings within a given radius. It is used to assess visual accessibility in urban environments. The unified get_visibility API supports accurate and simplified methods, including parallel execution for batches of observer points.

   📘 Example 🔗 Documentation

5. Noise Simulation & Noise Frame

   Simulation of noise propagation from sources, taking into account obstacles, vegetation, and environmental factors.

   📘 Example 🔗 Documentation 🧠 Detailed theory

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City Graphs via IduEdu

For optimal performance, ObjectNat is recommended to be used with graphs created by the IduEdu library. Graph-based ObjectNat methods consume iduedu.UrbanGraph directly; ObjectNat does not build NetworkX graphs internally.

IduEdu is an open-source Python library designed for building and processing complex urban networks based on OpenStreetMap data.

IduEdu can be installed via pip:

pip install IduEdu

Example usage:

from iduedu import get_4326_boundary, get_intermodal_graph

poly = get_4326_boundary(osm_id=1114252)
urban_graph = get_intermodal_graph(territory=poly, clip_by_territory=True)

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Installation

ObjectNat can be installed via pip:

pip install ObjectNat

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Configuration

You can adjust logging and progress bar output using the config module:

from objectnat import config

config.change_logger_lvl("INFO")   # mute debug logs
config.set_enable_tqdm(False)      # disable tqdm progress bars

Migration to ObjectNat 2.0

ObjectNat 2.0 replaces NetworkX-based graph inputs with iduedu.UrbanGraph, renames accessibility functions, and returns ProvisionResult from service provision. See the migration guide in the documentation: Migration 1.x to 2.0.

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Contacts

• NCCR — National Center for Cognitive Research
• IDU — Institute of Design and Urban Studies
• Natalya Chichkova — Project Manager
• Danila Oleynikov (Donny) — Lead Software Engineer

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Publications

Coming soon.