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pyvinecopulib

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What are vine copulas?

Vine copulas are a flexible class of dependence models consisting of bivariate building blocks (see e.g., Aas et al., 2009). You can find a comprehensive list of publications and other materials on vine-copula.org.

What is pyvinecopulib?

pyvinecopulib is the python interface to vinecopulib, a header-only C++ library for vine copula models based on Eigen. It provides high-performance implementations of the core features of the popular VineCopula R library, in particular inference algorithms for both vine copula and bivariate copula models. Advantages over VineCopula are

Prerequisites

Installation

With pip

The latest release can be installed using pip:

pip install pyvinecopulib

With conda

Installing pyvinecopulib from the conda-forge channel can be achieved by adding conda-forge to your channels with:

conda config --add channels conda-forge
conda config --set channel_priority strict

Once the conda-forge channel has been enabled, pyvinecopulib can be installed with conda:

conda install pyvinecopulib

or with mamba:

mamba install pyvinecopulib

It is possible to list all of the versions of pyvinecopulib available on your platform with conda:

conda search pyvinecopulib --channel conda-forge

or with mamba:

mamba search pyvinecopulib --channel conda-forge

Alternatively, mamba repoquery may provide more information:

# Search all versions available on your platform:
mamba repoquery search pyvinecopulib --channel conda-forge

# List packages depending on `pyvinecopulib`:
mamba repoquery whoneeds pyvinecopulib --channel conda-forge

# List dependencies of `pyvinecopulib`:
mamba repoquery depends pyvinecopulib --channel conda-forge

From source

To install from source, Eigen and Boost need to be available on your system for the build to succeed, using the environment variables EIGEN3_INCLUDE_DIR and Boost_INCLUDE_DIR respectively. On Linux, you can install the required packages and set the environment variables as follows:

sudo apt-get install libeigen3-dev libboost-all-dev
export Boost_INCLUDE_DIR=/usr/include
export EIGEN3_INCLUDE_DIR=/usr/include/eigen3

Then, just clone this repository and do pip install. Note the --recursive option which is needed for the vinecopulib and wdm submodules:

git clone --recursive https://github.com/vinecopulib/pyvinecopulib.git
pip install ./pyvinecopulib

If the required dependencies are not installed, a reproducible environment, which also include stuff requirement for the library's development and documentation, can be created using:

mamba create -n pyvinecopulib numpy mypy ruff pytest sphinx-rtd-theme sphinx-autodoc-typehints pydot networkx matplotlib pybind11 setuptools-scm python=3.11
mamba activate pyvinecopulib

Examples

Jupyter notebooks with examples can be found in the examples folder.

Documentation

For documentation of the pyvinecopulib's functionality and instructions how to use it, check out our website or the docs/ folder in this repository.

Building the documentation

Documentation for the example project is generated using Sphinx and the "Read the Docs" theme. The following command generates HTML-based reference documentation; for other formats please refer to the Sphinx manual:

License

pyvinecopulib is provided under an MIT license that can be found in the LICENSE file. By using, distributing, or contributing to this project, you agree to the terms and conditions of this license.

Special notes for Windows

Compiler requirements

This package requires a C++11 compliant compiler, i.e Visual Studio 2015 on Windows. Unlike regular C extension modules, it's perfectly fine to compile a pyvinecopulib module with a VS version newer than the target Python's VS version.

Runtime requirements

The Visual C++ 2015 redistributable packages are a runtime requirement for this project.

Contact

If you have any questions regarding the library, feel free to open an issue or send a mail to info@vinecopulib.org.