SPUX: Scalable Package for Uncertainty Quantification
SPUX is a modular framework for Bayesian inference and uncertainty quantification. SPUX can be coupled with linear and nonlinear, deterministic and stochastic models. SPUX supports model in any programming language (e.g. Python, R, Julia, C/C++, Fortran, Java). SPUX scales effortlessly from serial run to parallel high performance computing clusters. SPUX is application agnostic, with current examples in environmental data sciences. SPUX is actively developed at Eawag, Swiss Federal Institute of Aquatic Science and Technology, by researchers in the High Performance Scientific Computing Group, https://www.eawag.ch/sc. For the scientific website of the SPUX project, please refer to https://eawag.ch/spux. Documentation is available at https://spux.readthedocs.io. Source code respository is available at https://gitlab.com/siam-sc/spux. You are welcome to browse through the results gallery of the models already coupled to spux at https://spux.readthedocs.io/en/stable/gallery.html. This is free software, distributed under Apache (v2) License.
Download the file for your platform. If you're not sure which to choose, learn more about installing packages.
|Filename, size||File type||Python version||Upload date||Hashes|
|Filename, size spux-0.4.0-py2.py3-none-any.whl (296.5 kB)||File type Wheel||Python version py2.py3||Upload date||Hashes View|
|Filename, size spux-0.4.0.tar.gz (10.0 MB)||File type Source||Python version None||Upload date||Hashes View|