Madina

Uses multiprocessing and novel path generation algorithms to handle large-scale urban networks efficiently, as highlighted for pedestrian accessibility and flow simulations.

Leverages GeoPandas for data layer organization and NetworkX for network modeling, streamlining urban analysis with minimal coding requirements.

Includes features like perceived segment costs, elastic trip generation, and KNN-Access metrics for WalkScore-type assessments, enhancing analytical depth.

Provides structured workflows for pedestrian flow simulation between origins and destinations, with example code simplifying setup and execution.