http://laohakunakorn.bio.ac.uk
Plotting templates in Python and Julia. A gallery of basic plots and their code for you to adapt and use. Interact with the Jupyter notebook to learn about plotting features, or use the script to generate all plots in the gallery.
To run locally, make sure you have Python 3 and pipenv installed. Clone and navigate to the repository, then run (for the first time)
pipenv install
pipenv shell
After the first time, you only need to run pipenv shell to activate the environment, and exit to leave it.
Then run jupyter notebook to launch.
More info on pipenv here.
You can run the code from one of our lab's predefined Docker containers. We currently have three Docker containers:
nadanai263/nllab-python:003
nadanai263/nllab-jupyter:005
nadanai263/nllab-julia:004
The numeric tags will increase as the containers are updated, so please check them on DockerHub. To use these, clone the repository, open up a terminal and navigate to the directory containing the repository. Then (making sure you have a working Docker installation in place), run (on Mac, Linux)
docker run -it --rm -v "$PWD":/app nadanai263/nllab-python:003 /bin/bash
On Windows, replace "$PWD" with "%CD%" (for command prompt) or ${pwd} (for powershell).
This will pull and launch a Docker container, and start up a Linux shell. Your current working folder will be mounted to /app. Run the scripts as required.
You can directly start a Jupyter notebook in your current directory, using
docker run -p 8888:8888 --rm -it -v "$PWD":/home/jovyan nadanai263/nllab-jupyter:005
Again, on Windows replace "$PWD" with "%CD%" (for command prompt) or ${pwd} (for powershell).