Welcome to UncertainSCI’s documentation!

UncertainSCI source code

About UncertainSCI

UncertainSCI [1] is a Python-based toolkit that harnesses modern techniques to estimate model and parametric uncertainty, with a particular emphasis on needs for biomedical simulations and applications. This toolkit enables non-intrusive integration of these techniques with well-established biomedical simulation software.

Currently implemented in UncertainSCI is Polynomial Chaos Expansion (PCE) with a number of input distributions. For more information about these techniques, see: [2, 3, 4, 5, 6]. For studies using UncertainSCI, see: [7, 8, 9, 10, 11, 12]

Contents:

• Installation
  • From PyPI
  • From Source
• Getting Started with UncertainSCI
  • System Requirements
  • Getting UncertainSCI
  • UncertainSCI Overview
  • Running UncertainSCI Demos
• Support
  • Questions?
  • Bugs and Requests
• Tutorials
  • Simple Example Showing UQ With PCE
  • Demos
  • Adaptive PCE
  • Built-in forward models
  • Using UncertainSCI with External Simulation Software
  • Defining random parameters
  • Template for Tutorial
• Mathematical Formalism
  • Polynomial Chaos Expansions
• Developer Documentation
  • Contribution Guide
  • Making Tutorials
  • API Reference
• References

Contributors

Jake Bergquist, Dana Brooks, Zexin Liu, Rob MacLeod, Akil Narayan, Sumientra Rampersad, Lindsay Rupp, Jess Tate, Dan White

Acknowledgements

This project was supported by grants from the National Institute of Biomedical Imaging and Bioengineering (U24EB029012) from the National Institutes of Health.

Indices and Tables

• Index

• Module Index

• Search Page