SALib - Sensitivity Analysis Library in Python#
Python implementations of commonly used sensitivity analysis methods, including Sobol, Morris, and FAST methods. Useful in systems modeling to calculate the effects of model inputs or exogenous factors on outputs of interest.
Supported Methods#
Sobol Sensitivity Analysis (Sobol 2001, Saltelli 2002, Saltelli et al. 2010)
Method of Morris, including groups and optimal trajectories (Morris 1991, Campolongo et al. 2007)
Fourier Amplitude Sensitivity Test (FAST) (Cukier et al. 1973, Saltelli et al. 1999)
Random Balance Designs - Fourier Amplitude Sensitivity Test (RBD-FAST) (Tarantola et al. 2006, Elmar Plischke 2010, Tissot et al. 2012)
Delta Moment-Independent Measure (Borgonovo 2007, Plischke et al. 2013)
Derivative-based Global Sensitivity Measure (DGSM) (Sobol and Kucherenko 2009)
Fractional Factorial Sensitivity Analysis (Saltelli et al. 2008)
High Dimensional Model Representation (Li et al. 2010)
Regional Sensitivity Analysis (based on Saltelli et al. 2008, Pianosi et al., 2016)
Getting Started#
For Developers#
- API
- FAST - Fourier Amplitude Sensitivity Test
- RBD-FAST - Random Balance Designs Fourier Amplitude Sensitivity Test
- Method of Morris
- Sobol’ Sensitivity Analysis
- Delta Moment-Independent Measure
- Derivative-based Global Sensitivity Measure (DGSM)
- Fractional Factorial
- PAWN Sensitivity Analysis
- High-Dimensional Model Representation
- Regional Sensitivity Analysis
- Developers Guide
- Changes
- Complete Module Reference