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Welcome to gsa_framework!

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.