Yet another vine copula package, using PyTorch.
- C/D/R-Vine full-simulation/ quantile-regression/ conditional-simulation, all in one package
- Flexible simulation workflow for experienced users
- Vectorized tensor computation with GPU (
device='cuda'
) support - Shorter runtimes for higher dimension simulations
- Decoupled dataclasses and factory methods
- Pure
Python
library, inspired by and tested against pyvinecopulib on Windows, Linux, MacOS - IO and visualization support
# inside the `./pyproject.toml` file;
numpy = "*"
python = "^3.10"
scipy = "*"
# optional to facilitate customization
torch = { version = "^2", optional = true }
For PyTorch with cuda
support on Windows:
pip install torch --index-url https://download.pytorch.org/whl/cu121 --force-reinstall
# check cuda availability
python -c "import torch; print(torch.cuda.is_available())"
Tip
macOS users should set device='cpu'
at this stage, for using device='mps'
won't support dtype=torch.float64
.
- By
pip
fromPyPI
:
pip install torchvinecopulib torch
- Or with full drawing and bivariate dependency metric support:
pip install torchvinecopulib torch matplotlib pot scikit-learn
- Or
pip
from./dist/*.whl
or./dist/*.tar.gz
in this repo. Need to use proper file name.
# inside project root folder
pip install ./dist/torchvinecopulib-2024.10.1-py3-none-any.whl
# or
pip install ./dist/torchvinecopulib-2024.10.1.tar.gz
(Optional) Poetry for Dependency Management and Packaging
After git clone https://github.com/TY-Cheng/torchvinecopulib.git
, cd
into the project root where pyproject.toml
exists,
# inside project root folder
poetry lock && poetry install -E dev_cpu --with dev_cpu --sync
# or
poetry lock && poetry install -E dev_cuda --with dev_cuda --sync
Visit the ./examples/
folder for .ipynb
Jupyter notebooks.
-
Visit GitHub Pages website
-
Or visit html-preview.github.io
-
Or build by yourself (need
Sphinx
, themefuro
and the GNUmake
)
# inside project root folder
sphinx-apidoc -o ./docs ./torchvinecopulib && cd ./docs && make html && cd ..
Tip
the ./tests/test_vinecop.py
may take longer without 'cuda'
# inside project root folder
python -m pytest ./tests
# coverage report
coverage run -m pytest ./tests && coverage html
- more (non-parametric)
bicop
class intorch
- port to TensorFlow Probability for
cuda
-compatible Student's t cdf/ppf
We welcome contributions, whether it's a bug report, feature suggestion, code contribution, or documentation improvement.
- If you encounter any issues with the project or have ideas for new features, please open an issue on GitHub or privately email us. Make sure to include detailed information about the problem or feature request, including steps to reproduce for bugs.
- Fork the repository and create a new branch from the
main
branch. - Make your changes and ensure they adhere to the project's coding style and conventions.
- Write tests for any new functionality and ensure existing tests pass.
- Commit your changes with clear and descriptive commit messages.
- Push your changes to your fork and submit a pull request to the
main
branch of the original repository.
- Keep pull requests focused on addressing a single issue or feature.
- Include a clear and descriptive title and description for your pull request.
- Make sure all tests pass before submitting the pull request.
- If your pull request addresses an open issue, reference the issue number in the description using the syntax
#issue_number
. - in-place ops can be slower
- torch.jit.script can be slower
Copyright (C) 2024- Tuoyuan Cheng, Kan Chen
This file is part of torchvinecopulib. torchvinecopulib is free software: you can redistribute it and/or modify it under the terms of the GNU General Public License as published by the Free Software Foundation, either version 3 of the License, or (at your option) any later version.
torchvinecopulib is distributed in the hope that it will be useful, but WITHOUT ANY WARRANTY; without even the implied warranty of MERCHANTABILITY or FITNESS FOR A PARTICULAR PURPOSE. See the GNU General Public License for more details.
You should have received a copy of the GNU General Public License along with torchvinecopulib. If not, see http://www.gnu.org/licenses/.