This project implements a Python-based algorithm designed to help identify the most optimal day for public transport usage. It includes a simple graphical user interface (GUI) to make it easier for collaborators or friends to work with and test the algorithm.
- Overview
- Features
- Installation
- [Examples]
The main objective is to find the best day for public transport operations or usage based on specific parameters and data. The accompanying PDF (AADS (3).pdf) provides background information and the mathematical or theoretical basis behind the approach.
Key Points:
- Designed to analyze or simulate transport data to determine “best day” metrics.
- Provides a user-friendly GUI, making it simpler to change parameters, run simulations, or visualize results.
- Primarily written in Python.
- Algorithmic Core
A robust algorithm that processes transport data, aiming to optimize the selection of a best day based on the defined criteria. - Graphical User Interface
Developed in Python to allow easy testing and manipulation of input data without digging directly into the code. - Customizable Parameters
Data inputs and other factors can be adjusted to explore different scenarios.
Description: This chart depicts a broad range of whimsical and real transport methods over time, labeled on the vertical axis. The red dashed line indicates a key date or threshold relevant to the algorithm.
Description: This figure focuses on four major modes of transportation (Eurostar, Bus, Train, and Plane), plotted over several months. The red dashed line marks a transition point or target date.
Description: Displays multiple transport modes, from planes to horse carriages, and indicates their active timelines. The vertical red line again serves as a critical reference date.