Python package gsa_framework is aimed at providing interface for Global Sensitivity Analysis (GSA). It consists of the following modules:
- sampling
- random
- latin hypercube
- Sobol' quasi-random sequences
- Saltelli design
- custom inputs, e.g. obtained from real data / measurements
- sensitivity indices computation
- Pearson and Spearman correlation coefficients
- Sobol firt and total order
- Extended FAST
- Delta moment-independent indices
- Feature importances from gradient boosted trees with XGBoost
- models
- test functions
- life cycle assessment
- custom models
- sensitivity analysis that links all of the above for each sensitivity method
- additional components to support reliability of GSA
- GSA results validation
- Convergence of sensitivity indices
- Robustness with bootstrapping
This package is part of the doctoral work of Aleksandra Kim at Paul Scherrer Institute and ETH Zurich.
For detailed API docs, see the versioned API website.