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latte

Data analysis of latent representations.

Getting started with the code

Clone the repository:

$ git clone git@github.com:BoevaLab/latte.git
$ cd latte

At this point it may be beneficial to create a new Python virtual environment. There are multiple solutions for this step, including Miniconda. We aim at Python 3.8 version and above.

Then you install the package in editable mode, together with the testing utilities:

$ pip install -e ".[test]"

Development tools

As a developer, you will use some tools increasing code quality. You can install them by running

   $ pip install -r requirements-dev.txt
   $ pre-commit install

We use black and flake8 to lint the code, pytype to check whether the types agree, and pytest to unit test the code. These code quality checks are applied to every Pull Request via a workflow in the .github/workflows directory.