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Bike2CAV evaluation

The evaluation of the network-based interaction zones in the scope of the Bike2CAV project. See the evaluation notebook for a description of the workflow and the results.

To reproduce

A Docker image is provided such that you can reproduce and interactively explore the notebook inside a containerized environment containing all required dependencies. Given that you have Docker and git installed, you can do so with the following steps:

1. Clone and access this repository

Clone this repository with git to your computer, and access the cloned directory, as follows:

git clone https://github.com/plus-mobilitylab/bike2cav.git
cd bike2cav

2. Get the input data

The notebook uses a set of input data that are already pre-processed to some extent. Unfortunately, not all these data are openly available. If you are a member of the PLUS Mobility Lab, you can find the data on our network share in the Bike2CAV project directory, under ./5-Projekt/5-7-Evaluation/data.zip. Store this ZIP file in the data directory of the cloned repository. If you do not have access to these data, please contact lucas.vandermeer@plus.ac.at.

3. Build the Docker image

Build the provided Docker image by executing the following command:

docker build -t bike2cav .

4. Run a Docker container

Run a Docker container based on the provided iamge by executing the following command:

docker run --rm --name bike2cav -e DISABLE_AUTH=TRUE -e USERID=$UID -p 8787:8787 -v ${PWD}:/home/rstudio/ bike2cav

5. Open a locally hosted RStudio Server

By running the Docker container you have started a RStudio Server session running on port 8787. To access this, open a browser and navigate to http://localhost:8787/.

6. Launch the RStudio project

In the Files tab (bottom-right of the RStudio interface), open a file called bike2cav.Rproj.

7. Open the notebook

In the Files tab (bottom-right of the RStudio interface), open a file called evaluation.qmd. This will open a Quarto notebook, containing a combination of Markdown formatted text with R code chuncks. You can run each chunck separately and experiment with changing code and/or certain parameters.

8. Render the notebook

To render the full notebook into a HTML document, click Render in the menu above the notebook.