growbikenet 0.5.2

Python package to grow urban bicycle networks from scratch, spin-off from the paper 'Growing urban bicycle networks'

GrowBikeNet

Source code for the project GrowBikeNet, building on the code from the research paper Growing Urban Bicycle Networks.

Installation

To install and use the code, you need to have installed JupyterLab.

First clone the repository:

git clone https://github.com/BikeNetKit/GrowBikeNet.git

Go to the cloned folder and create a new virtual environment, see below.

Installation with pixi

Installation with pixi is fastest and most stable. Setup a new virtual environment using the environment.yml file:

pixi init --import environment.yml

Now build the environment and run it:

pixi run jupyter lab

An instance of Jupyter lab is automatically going to open in your browser after the environment is built.

Installation with pip/mamba/conda

Alternatively, use pip, or mamba (or conda, which is slower).

Instructions

You can either create a new virtual environment then install the necessary dependencies with pip using the requirements.txt file:

pip install -r requirements.txt

Or create a new environment with the dependencies with conda or mamba using the environment.yml file:

mamba env create -f environment.yml

Then, install the virtual environment's kernel in Jupyter:

mamba activate growbikenet
ipython kernel install --user --name=growbikenet
mamba deactivate

You can now run jupyter lab with kernel growbikenet (Kernel > Change Kernel > growbikenet).

Repository structure

├── growbikenet             <- Packaged functions and visualizations
├── tests                   <- tests to execute to ensure functionality
├── .gitignore              <- Files and folders ignored by git
├── .pre-commit-config.yaml <- Pre-commit hooks used
├── README.md
├── environment.yml         <- Environment file to set up the environment using conda/mamba/pixi

Credits

Development of GrowBikeNet was supported by the Danish Innovation Fund (Innovationsfonden).