| Name | pyvinecopulib JSON |
| Version |
0.7.0
JSON |
| download |
| home_page | None |
| Summary | A python interface to vinecopulib |
| upload_time | 2025-01-08 12:38:53 |
| maintainer | None |
| docs_url | None |
| author | None |
| requires_python | >=3.8 |
| license | The MIT License (MIT) Copyright © 2019-2023 Thomas Nagler and Thibault Vatter Permission is hereby granted, free of charge, to any person obtaining a copy of this software and associated documentation files (the “Software”), to deal in the Software without restriction, including without limitation the rights to use, copy, modify, merge, publish, distribute, sublicense, and/or sell copies of the Software, and to permit persons to whom the Software is furnished to do so, subject to the following conditions: The above copyright notice and this permission notice shall be included in all copies or substantial portions of the Software. THE SOFTWARE IS PROVIDED “AS IS”, WITHOUT WARRANTY OF ANY KIND, EXPRESS OR IMPLIED, INCLUDING BUT NOT LIMITED TO THE WARRANTIES OF MERCHANTABILITY, FITNESS FOR A PARTICULAR PURPOSE AND NONINFRINGEMENT. IN NO EVENT SHALL THE AUTHORS OR COPYRIGHT HOLDERS BE LIABLE FOR ANY CLAIM, DAMAGES OR OTHER LIABILITY, WHETHER IN AN ACTION OF CONTRACT, TORT OR OTHERWISE, ARISING FROM, OUT OF OR IN CONNECTION WITH THE SOFTWARE OR THE USE OR OTHER DEALINGS IN THE SOFTWARE. |
| keywords |
copula
vines copulas
pair-copulas constructions
|
| VCS |
 |
| bugtrack_url |
|
| requirements |
No requirements were recorded.
|
| Travis-CI |
No Travis.
|
| coveralls test coverage |
No coveralls.
|
# pyvinecopulib
[](https://vinecopulib.github.io/pyvinecopulib/)
[](https://opensource.org/licenses/MIT)
[](https://github.com/vinecopulib/pyvinecopulib/actions/workflows/pypi.yml)
[](https://www.codacy.com/gh/vinecopulib/pyvinecopulib?utm_source=github.com&utm_medium=referral&utm_content=vinecopulib/pyvinecopulib&utm_campaign=Badge_Grade)
[](https://zenodo.org/badge/latestdoi/196999069)
## Introduction
### 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](https://mediatum.ub.tum.de/doc/1083600/1083600.pdf)).
You can find a comprehensive list of publications and other materials on
[vine-copula.org](http://vine-copula.org).
### What is pyvinecopulib?
[pyvinecopulib](https://vinecopulib.github.io/pyvinecopulib/) is the python interface to vinecopulib, a header-only C++ library for vine copula models based on
[Eigen](http://eigen.tuxfamily.org/index.php?title=Main_Page). It provides
high-performance implementations of the core features of the popular
[VineCopula R library](https://github.com/tnagler/VineCopula), in particular
inference algorithms for both vine copula and bivariate copula models.
Advantages over VineCopula are
* a stand-alone C++ library with interfaces to both R and Python,
* a sleaker and more modern API,
* shorter runtimes and lower memory consumption, especially in high dimensions,
* nonparametric and multi-parameter families.
### 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.
### Contact
If you have any questions regarding the library, feel free to
[open an issue](https://github.com/pyvinecopulib/pyvinecopulib/issues/new) or
send a mail to <info@vinecopulib.org>.
## Installation
### With pip
The latest release can be installed using `pip`:
```bash
pip install pyvinecopulib
```
### With conda
Similarly, it can be installed with `conda`:
```bash
conda install conda-forge::pyvinecopulib
```
Or with `mamba`:
```bash
mamba install conda-forge::pyvinecopulib
```
### From source
The main build time prerequisites are:
* scikit-build-core (>=0.4.3),
* nanobind (>=1.3.2),
* a compiler with C++17 support.
To install from source, `Eigen` and `Boost` also need to be available, and CMake will try to find suitable versions automatically.
A reproducible environment, also including requirements for the `pyvinecopulib`'s development and documentation, can be created using:
```bash
mamba create -n pyvinecopulib eigen boost nanobind scikit-build-core numpy pydot networkx matplotlib mypy ruff pytest sphinx-rtd-theme sphinx-autodoc-typehints nbsphinx myst-parser python=3.11
mamba activate pyvinecopulib
```
You can also specify the location if `Eigen` and `Boost` manually 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:
```bash
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:
```bash
git clone --recursive https://github.com/vinecopulib/pyvinecopulib.git
pip install ./pyvinecopulib
```
### 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:
* `pip install sphinx-rtd-theme sphinx-autodoc-typehints nbsphinx recommonmark`
* `cd pyvinecopulib/docs`
* `python serve_sphinx.py`
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"description": "# pyvinecopulib\n\n[](https://vinecopulib.github.io/pyvinecopulib/)\n[](https://opensource.org/licenses/MIT)\n[](https://github.com/vinecopulib/pyvinecopulib/actions/workflows/pypi.yml)\n[](https://www.codacy.com/gh/vinecopulib/pyvinecopulib?utm_source=github.com&utm_medium=referral&utm_content=vinecopulib/pyvinecopulib&utm_campaign=Badge_Grade)\n[](https://zenodo.org/badge/latestdoi/196999069)\n\n## Introduction\n\n### What are vine copulas?\n\nVine copulas are a flexible class of dependence models consisting of bivariate\nbuilding blocks (see e.g.,\n[Aas et al., 2009](https://mediatum.ub.tum.de/doc/1083600/1083600.pdf)).\nYou can find a comprehensive list of publications and other materials on\n[vine-copula.org](http://vine-copula.org).\n\n### What is pyvinecopulib?\n\n[pyvinecopulib](https://vinecopulib.github.io/pyvinecopulib/) is the python interface to vinecopulib, a header-only C++ library for vine copula models based on\n[Eigen](http://eigen.tuxfamily.org/index.php?title=Main_Page). It provides\nhigh-performance implementations of the core features of the popular\n[VineCopula R library](https://github.com/tnagler/VineCopula), in particular\ninference algorithms for both vine copula and bivariate copula models.\nAdvantages over VineCopula are \n\n* a stand-alone C++ library with interfaces to both R and Python,\n* a sleaker and more modern API,\n* shorter runtimes and lower memory consumption, especially in high dimensions,\n* nonparametric and multi-parameter families.\n\n### License\n\npyvinecopulib is provided under an MIT license that can be found in the LICENSE\nfile. By using, distributing, or contributing to this project, you agree to the\nterms and conditions of this license.\n\n### Contact\n\nIf you have any questions regarding the library, feel free to\n[open an issue](https://github.com/pyvinecopulib/pyvinecopulib/issues/new) or\nsend a mail to <info@vinecopulib.org>.\n\n## Installation\n\n### With pip\n\nThe latest release can be installed using `pip`:\n\n```bash\npip install pyvinecopulib\n```\n\n### With conda\n\nSimilarly, it can be installed with `conda`:\n\n```bash\nconda install conda-forge::pyvinecopulib\n```\n\nOr with `mamba`:\n\n```bash\nmamba install conda-forge::pyvinecopulib\n```\n\n### From source\n\nThe main build time prerequisites are:\n\n* scikit-build-core (>=0.4.3),\n* nanobind (>=1.3.2),\n* a compiler with C++17 support.\n\nTo install from source, `Eigen` and `Boost` also need to be available, and CMake will try to find suitable versions automatically.\nA reproducible environment, also including requirements for the `pyvinecopulib`'s development and documentation, can be created using:\n\n```bash\nmamba create -n pyvinecopulib eigen boost nanobind scikit-build-core numpy pydot networkx matplotlib mypy ruff pytest sphinx-rtd-theme sphinx-autodoc-typehints nbsphinx myst-parser python=3.11\nmamba activate pyvinecopulib\n```\n\nYou can also specify the location if `Eigen` and `Boost` manually using the environment variables `EIGEN3_INCLUDE_DIR` and `Boost_INCLUDE_DIR` respectively.\nOn Linux, you can install the required packages and set the environment variables as follows:\n\n```bash\nsudo apt-get install libeigen3-dev libboost-all-dev\nexport Boost_INCLUDE_DIR=/usr/include\nexport EIGEN3_INCLUDE_DIR=/usr/include/eigen3\n```\n\nThen, just clone this repository and do `pip install`.\nNote the `--recursive` option which is needed for the `vinecopulib` and `wdm` submodules:\n\n```bash\ngit clone --recursive https://github.com/vinecopulib/pyvinecopulib.git\npip install ./pyvinecopulib\n```\n\n\n### Building the documentation\n\nDocumentation for the example project is generated using Sphinx and the \"Read the Docs\" theme.\nThe following command generates HTML-based reference documentation; for other\nformats please refer to the Sphinx manual:\n\n* `pip install sphinx-rtd-theme sphinx-autodoc-typehints nbsphinx recommonmark`\n* `cd pyvinecopulib/docs`\n* `python serve_sphinx.py`\n",
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