hesseflux.functions.sa_test_functions

Module provides test functions for parameter sensitivity analysis from
Ishigami and Homma (1990) An importance qualification technique in uncertainty analysis for computer models,
Proceedings of the isuma ‘90, First International Symposium on Uncertainty Modelling and Analysis, University of Maryland, Dec. 03 - Dec 05 1990, 398-403
Oakley and O’Hagan (2004) Probabilistic sensitivity analysis of complex models: a Bayesian approach
    1. Statist. Soc. B 66, Part 3, 751-769.
Morris (1991) Factorial sampling plans for preliminary computational experiments,
Technometrics 33, 161-174.

Saltelli et al. (2008) Global Sensitivity Analysis. The Primer, John Wiley & Sons, pp. 292

Saltelli et al. (2010) Variance based sensitivity analysis of model output, Design and estimator
for the total sensitivity index, Comp. Phys. Comm. 181, 259-270.
Sobol’ (1990), Sensitivity estimates for nonlinear mathematical models,
Matematicheskoe Modelirovanie 2, 112-118 (in Russian), translated in English in Sobol’ (1993).
Sobol’ (1993) Sensitivity analysis for non-linear mathematical models,
Mathematical Modelling and Computational Experiment 1, 407-414, English translation of Russian original paper Sobol’ (1990).
Current functions are:

B B of Saltelli et al. (2010)

G / g G-function attributed to Sobol’ (1990, 1993), given by Saltelli et al. (2008, 2010)

Gstar G* of Saltelli et al. (2010)

ishigami_homma Ishigami and Homma (1990), given by Saltelli et al. (2008, page 179)

K / bratley K of Saltelli et al. (2010)

fmorris / morris After Morris (1991)

oakley_ohagan Oakley and O’Hagan (2004), parameters given in Saltelli et al. (2008)
or on http://www.jeremy-oakley.staff.shef.ac.uk/psa_example.txt

This module was written by Matthias Cuntz & Juliane Mai while at Department of Computational Hydrosystems, Helmholtz Centre for Environmental Research - UFZ, Leipzig, Germany, and continued by Matthias Cuntz while at Institut National de Recherche pour l’Agriculture, l’Alimentation et l’Environnement (INRAE), Nancy, France.

Copyright (c) 2015-2020 Matthias Cuntz - mc (at) macu (dot) de Released under the MIT License; see LICENSE file for details.

  • Written Mar 2015 by Matthias Cuntz (mc (at) macu (dot) de) & Juliane Mai
  • Added functions to properly test PAWN method: linear, product, ratio, and ishigami_homma_easy, Dec 2017, Juliane Mai
  • Provide morris function under the name fmorris and the K function under the name bratley, Nov 2019, Matthias Cuntz
  • Changed to Sphinx docstring and numpydoc, Dec 2019, Matthias Cuntz
  • Distinguish iterable and array_like parameter types, Jan 2020, Matthias Cuntz

The following functions are provided:

B(X) B function, Saltelli et al.
g(X, a) G-function
G(X, a) G-function
Gstar(X, alpha, delta, a) G* example, Saltelli et al.
K(X) K example, Saltelli et al.
bratley(*args) K example, Saltelli et al.
fmorris(X, beta0, beta1, beta2, beta3, beta4) Morris-function, Morris (1991) Technometrics 33, 161-174
morris(*args) Morris-function, Morris (1991) Technometrics 33, 161-174
oakley_ohagan(X) Oakley and O’Hagan (2004) J.
ishigami_homma(X, a, b) Ishigami and Homma (1990), given by Saltelli et al.
linear(X, a, b) Linear test function to test PAWN method:
product(X) Product test function to test PAWN method:
ratio(X) Ratio test function:
ishigami_homma_easy(X) Simplified Ishigami and Homma function to test PAWN method:
B(X)[source]

B function, Saltelli et al. (2010) Comp. Phys. Comm. 181, p. 259-270

Parameters:X (array_like) – (nX,) or (nX,npoints) array of floats
Returns:B – float or (npoints,) floats of B function values at X
Return type:float or ndarray
g(X, a)[source]

G-function

Sobol’ (1990) Matematicheskoe Modelirovanie 2, 112-118 (in Russian)

Sobol’ (1993) Mathematical Modelling and Computational Experiment 1, 407-414 (English translation)

Parameters:
  • X (array_like) – (nX,) or (nX,npoints) array of floats
  • a (array_like) – (nX,) array of floats
Returns:

G – float or (npoints,) floats of G function values at X with parameters a

Return type:

float or ndarray

G(X, a)[source]

G-function

Sobol’ (1990) Matematicheskoe Modelirovanie 2, 112-118 (in Russian)

Sobol’ (1993) Mathematical Modelling and Computational Experiment 1, 407-414 (English translation)

Parameters:
  • X (array_like) – (nX,) or (nX,npoints) array of floats
  • a (array_like) – (nX,) array of floats
Returns:

g – float or (npoints,) floats of G function values at X with parameters a

Return type:

float or ndarray

Gstar(X, alpha, delta, a)[source]

G* example, Saltelli et al. (2010) Comp. Phys. Comm., 181, p. 259-270

Parameters:
  • X (array_like) – (nX,) or (nX,npoints) array of floats
  • alpha (array_like) – (nX,) array of floats
  • delta (array_like) – (nX,) array of floats
  • a (array_like) – (nX,) array of floats
Returns:

G* – float or (npoints,) floats of G* function values at X with parameters alpha, delta and a

Return type:

float or ndarray

K(X)[source]

K example, Saltelli et al. (2010) Comp. Phys. Comm., 181, p. 259-270

Parameters:X (array_like) – (nX,) or (nX,npoints) array of floats
Returns:K – float or (npoints,) floats of K function values at X
Return type:float or ndarray
bratley(*args)[source]

K example, Saltelli et al. (2010) Comp. Phys. Comm., 181, p. 259-270

Parameters:X (array_like) – (nX,) or (nX,npoints) array of floats
Returns:bratley – float or (npoints,) floats of K function values at X
Return type:float or ndarray
fmorris(X, beta0, beta1, beta2, beta3, beta4)[source]

Morris-function, Morris (1991) Technometrics 33, 161-174

Parameters:
  • X (array_like) – (20,) or (20,npoints) array of floats
  • beta0 (float) – float
  • beta1 (array_like) – (20,) array of floats
  • beta2 (array_like) – (20,20) array of floats
  • beta3 (array_like) – (20,20,20) array of floats
  • beta4 (array_like) – (20,20,20,20) array of floats
Returns:

fmorris – float or (npoints,) floats of Morris function values at X with parameters beta0-beta4

Return type:

float or ndarray

morris(*args)[source]

Morris-function, Morris (1991) Technometrics 33, 161-174

Parameters:
  • X (array_like) – (20,) or (20,npoints) array of floats
  • beta0 (float) – float
  • beta1 (array_like) – (20,) array of floats
  • beta2 (array_like) – (20,20) array of floats
  • beta3 (array_like) – (20,20,20) array of floats
  • beta4 (array_like) – (20,20,20,20) array of floats
Returns:

morris – float or (npoints,) floats of Morris function values at X with parameters beta0-beta4

Return type:

float or ndarray

oakley_ohagan(X)[source]

Oakley and O’Hagan (2004) J. R. Statist. Soc. B 66, Part 3, 751-769

Parameters:X (array_like) – (15,) or (15,npoints) array of floats
Returns:oakley_ohagan – float or (npoints,) floats of Oakley and O’Hagan function values at X
Return type:float or ndarray
ishigami_homma(X, a, b)[source]

Ishigami and Homma (1990), given by Saltelli et al. (2008, page 179)

Parameters:
  • X (array_like) – (3,) or (3,npoints) array of floats
  • a (array_like) – float or (npoints,) array of floats
  • b (array_like) – float or (npoints,) array of floats
Returns:

ishigami_homma – float or (npoints,) floats of Ishigami and Homma function values at X with parameters a and b

Return type:

float or ndarray

linear(X, a, b)[source]

Linear test function to test PAWN method:

Y = a*X + b
Parameters:
  • X (array_like) – (1,) or (1,npoints) array of floats
  • a (array_like) – float or (npoints,) array of floats
  • b (array_like) – float or (npoints,) array of floats
Returns:

linear – float or (npoints,) floats of linear function values at X with parameters a and b

Return type:

float or ndarray

product(X)[source]

Product test function to test PAWN method:

Y = X[0] * X[1]
Parameters:X (array_like) – (2,) or (2,npoints) array of floats
Returns:product – float or (npoints,) floats of product function values at X
Return type:float or ndarray
ratio(X)[source]

Ratio test function:

Y = X[0] / X[1]

Simple nonlinear model proposed by Liu et al. (2006):

Liu, H., Sudjianto, A., Chen, W., 2006. Relative entropy based method for probabilistic sensitivity analysis in engineering design. J. Mech. Des. 128, 326-336.

Used by Pianosi & Wagener, Environmental Modelling & Software (2015)

Pianosi, F. & Wagener T., 2015 A simple and efficient method for global sensitivity analysis based on cumulative distribution functions. Environmental Modelling & Software 67, 1-11.
Parameters:X (array_like) – (2,) or (2,npoints) array of floats
Returns:ratio – float or (npoints,) floats of ratio function values at X
Return type:float or ndarray
ishigami_homma_easy(X)[source]

Simplified Ishigami and Homma function to test PAWN method:

Y = sin(X[0]) + X[1]

with X[0],X[1] ~ Uniform[-Pi,Pi]

Parameters:X (array_like) – (2,) or (2,npoints) array of floats
Returns:ishigami_homma_easy – float or (npoints,) floats of simplified Ishigami and Homma function values at X
Return type:float or ndarray