Jupyter notebooks that provide examples Python code snippets for working with the AI-READI data
This repository contains Jupyter notebooks developed by the AI-READI team to provide examples for working with the AI-READI dataset. The dataset is accessible on FAIRhub. More details about the dataset are available in the dataset documentation.
The overall code is structured according to the FAIR-BioRS guidelines. All the dependencies are documented in the environment.yml file.
We recommend using Anaconda to create and manage your development environment and using JupyterLab to run the notebook. All the subsequent instructions are provided assuming you are using Anaconda (Python 3 version) and JupyterLab.
Clone the repo or download as a zip and extract.
Open Anaconda prompt (Windows) or the system Command line interface then naviguate to the code.
cd ai-readi-notebooks$ conda env create -f environment.ymlCaution: at this time, the pre-commit requires bash shell, so if you plan to make updates to notebooks you may need to use a linux or linux-like environment that has access to a bash shell. A python implementation of the check may be created in the future.
The purpose of this check is to avoid saving sensitive data into github. Be sure to use the jupyter tools to clean the outputs before attempting a check in. Practice with the test_pre_commit notebook to confirm that you are prevented from checking in an update that contains a cell that has been run. Reminder that if you have stage and attempted to commit, use 'git restore --staged test_pre_commit.ipynb' to unstage and correct the file before trying again.
$ conda activate ai-readi-notebooks
$ pre-commit installIf you would like to have one jupyter install that can be used by several environments, set up the connection as shown below. Otherwise, you can install jupyterlab or jupyter notebooks inside your ai-readi-notebooks environment using 'conda install jupyterlab' or 'conda install jupyter notebook'.
$ conda activate ai-readi-notebooks
$ conda install ipykernel
$ ipython kernel install --user --name=ai-readi-notebooks
$ conda deactivateLaunch Jupyter lab and naviguate to main folders to select the notebook you want to use (there is one notebook per data type). Make sure to change the kernel to "ai-readi-notebooks" (e.g., see here). We recommend to use the JupyterLab code formatter along with the Black and isort formatters to facilitate compliance with PEP8 if you are editing the notebook.
The input of the notebooks are the data files from the AI-READI dataset associated with that notebook. Download the AI-READI dataset from FAIRhub before running the notebooks.
To report any issues please open a new issue via the Issues tab. Provide adequate information (operating system, steps leading to error, screenshots) so we can help you efficiently.
This work is licensed under MIT. See LICENSE for more information.
If you are using this software or reusing the source code from this repository for any purpose, please cite as indicated in the CITATION.cff file.
This project is funded by the NIH under award number 1OT2OD032644. The content is solely the responsibility of the authors and does not necessarily represent the official views of the NIH.
