On the recordRead 4 Oct 202612 facts
Synthia
On the record
- Data integration
- Synthia's API natively handles xarray labelled arrays and datasets.dmey.github.io · read 4 Oct 2026
- Distribution
- The package can be installed with pip install synthia, or with pip install synthia[full] to include the optional dependency.dmey.github.io · read 4 Oct 2026
- Example use
- The quickstart demonstrates generating synthetic atmospheric temperature profiles using Gaussian copula and fPCA models.dmey.github.io · read 4 Oct 2026
- Generation methods
- It supports fPCA, Gaussian copula, and vine copula methods for multivariate data generation.dmey.github.io · read 4 Oct 2026
- Implementation
- The fPCA and Gaussian copula implementations are in Python, while vine computations use pyvinecopulib bindings to the C++ vinecopulib library.dmey.github.io · read 4 Oct 2026
- Intended users
- It is designed for scientists and practitioners working with labelled multivariate data typical of computational sciences.dmey.github.io · read 4 Oct 2026
- License
- Synthia is licensed under the MIT License, which permits use, copying, modification, distribution, sublicensing, and sale subject to its stated conditions.dmey.github.io · read 4 Oct 2026
- Optional dependency
- pyvinecopulib is an optional dependency for vine copula and quasirandom number support.dmey.github.io · read 4 Oct 2026
- Purpose
- Synthia is an open source Python package for modeling univariate and multivariate data, parameterizing data, and manipulating marginal distributions.dmey.github.io · read 4 Oct 2026
- Requirements
- Installation requires Python 3.8 or later, NumPy, SciPy, and xarray.dmey.github.io · read 4 Oct 2026
- Variable types
- The documentation says its methods support continuous variables and vine copulas also support discrete and categorical variables.dmey.github.io · read 4 Oct 2026
- Warranty
- The MIT license states that the software is provided as is and disclaims warranties and liability as specified in the license.dmey.github.io · read 4 Oct 2026
