Installation

Conda environment (recommended)

RepLikCompare depends on the usual scientific Python stack (pandas, numpy, scipy, scikit-learn, seaborn, matplotlib) plus two clustering / dimensionality-reduction extras, hdbscan and umap-learn. An environment.yml file is provided at the root of the repository to create a conda environment with all of them in one go:

conda env create -f environment.yml
conda activate RepLikCompare

This is the easiest way to get a working environment, since hdbscan in particular is a compiled extension that installs more reliably from conda-forge than from PyPI on some platforms.

Installing the package

Once your environment is ready (conda, or any Python environment with pip), you have two options:

Option A – without cloning (once published on PyPI)

pip install RepLikCompare

Option B – from source (works today)

git clone https://github.com/regueialaa/RepLikCompare.git
cd RepLikCompare
pip install .

Either way installs RepLikCompare together with all of its dependencies – including hdbscan and umap-learn – so it is available in both the terminal and Jupyter notebooks.