Installation Instructions

Installation can be done via pip:

pip install

For best performance, we recommend that you install the package in a conda environment and let conda handle the installation of dependencies before installing the package using pip. You can do this by following these steps:

conda create -n -c conda-forge python scipy pandas matplotlib cvxopt
conda activate
pip install

The examples might require you to install additional packages, e.g., seaborn and ipykernel / notebook / jupyterlab if you want to run the notebooks. Using pip to install these packages should not cause any dependency issues.

You can also explore the examples in the cloud without any local installations using Binder. However, note that Binder servers have very limited resources and might not support some of the optimized routines this package uses. If you want access to a stable and optimized environment with persistent storage, please subscribe to our Data Science Server.