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https://github.com/mszell/bikenwloops

Bicycle node network loop analysis
https://github.com/mszell/bikenwloops

bicycle-infrastructure bicycle-network network-analysis

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Bicycle node network loop analysis

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README 

        
> [!CAUTION]

> This project is under heavy development. Do not use.



# Bicycle node network loop analysis



[![Ruff](https://img.shields.io/endpoint?url=https://raw.githubusercontent.com/astral-sh/ruff/main/assets/badge/v2.json)](https://github.com/astral-sh/ruff)

[![code style: prettier](https://img.shields.io/badge/code_style-prettier-ff69b4.svg?style=flat-square)](https://github.com/prettier/prettier)

[![pre-commit](https://img.shields.io/badge/pre--commit-enabled-brightgreen?logo=pre-commit&logoColor=white)](https://github.com/pre-commit/pre-commit)



This is the source code for the scientific project _Bicycle node network loop analysis_. The code assesses the quality of a proposed bicycle node network in Denmark via loop census analysis.



## Installation



First clone the repository:



```

git clone https://github.com/mszell/bikenwloops

```



Go to the cloned folder and create a new virtual environment via `mamba` using the `environment.yml` file:



```

mamba env create -f environment.yml

```



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



```

mamba activate bikenwloops

ipython kernel install --user --name=bikenwloops

mamba deactivate

```



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



## Data setup



Data of the knudepunkter network comes from [BikeNodePlanner: Data for Denmark](https://github.com/anastassiavybornova/bike-node-planner-data-denmark) and [BikeNodePlanner](https://github.com/anastassiavybornova/bike-node-planner).



### Step 1: Extract data with BikeNodePlanner: Data for Denmark



- Use [BikeNodePlanner: Data for Denmark](https://github.com/anastassiavybornova/bike-node-planner-data-denmark)

- Uncomment the municipalities of your study area in `config-municipalities.yml`. Several config files are already prepared for copy-pasting in the [`retrieval/`](retrieval/) folder for large study areas like Jutland or Zealand.

- Set all values in `config-layers-polygon.yml` to `ignore`. This file is already [prepared](retrieval/config-layers-polygon.yml) for copy-pasting.

- Run the `run.sh` script

- Copy all subfolders of `/input-for-bike-node-planner/` into the `/data/input/` folder of bike-node-planner



### Step 2: Add elevation data with BikeNodePlanner



This step is needed to add elevation data (from `dem/dem.tif`) to the edges, creating an `edges_slope.gpkg` file.



- Use [BikeNodePlanner](https://github.com/anastassiavybornova/bike-node-planner)

- Run scripts 01 to 04

- Let's call `loopspath` the data/input path to your project, for example `bikenwloops/data/input/funen/`

- Copy the file `edges_slope.gpkg` from `bike-node-planner/data/output/elevation` into `loopspath/network/processed/`



## Repository structure



```

├── code                    <- Jupyter notebooks and py scripts

├── data

│   ├── processed           <- Modified data

│   └── raw                 <- Original, immutable data

├── dissemination           <- Material for dissemination

├── plots                   <- Generated figures

├── retrieval               <- Config files for retrieving data

├── .gitignore              <- Files and folders ignored by git

├── .pre-commit-config.yaml <- Pre-commit hooks used

├── LICENSE.txt

├── README.md

└── environment.yml         <- Environment file to set up the environment using conda/mamba

```