MLMC is a Python library implementing the Multilevel Monte Carlo (MLMC) method. It provides tools for sampling, moment estimation, statistical post-processing, and more.
Originally developed as part of the GeoMop project.
- Sample scheduling
- Estimation of generalized moments
- Advanced post-processing with the
Quantitystructure - Approximation of probability density functions using the maximum entropy method
- Bootstrap and regression-based variance estimation
- Diagnostic tools (e.g., consistency checks)
The package is available on PyPI and can be installed with pip:
pip install mlmcTo install the latest development version:
git clone https://github.com/GeoMop/MLMC.git
cd MLMC
pip install -e .Full documentation, including tutorials, is available at: https://mlmc.readthedocs.io/
Topics covered include:
- Basic MLMC workflow and examples
- Definition and composition of
Quantityobjects - Moment and covariance estimation
- Probability density function reconstruction
Contributions are welcome! To contribute, please fork the repository and create a pull request.
Before submitting, make sure all tests pass by running tox:
pip install tox
toxtox creates a clean virtual environment, installs all dependencies,
runs unit tests via pytest, and checks that the package installs correctly.
MLMC depends on the following Python packages:
- Free software: GNU General Public License v3.0