# EASI Method

GlobalSensitivity.EASIType
EASI(; max_harmonic::Int = 10, dct_method::Bool = false)
• max_harmonic: Maximum harmonic of the input frequency for which the output power spectrum is analyzed for. Defaults to 10.
• dct_method: Use Discrete Cosine Transform method to compute the power spectrum. Defaults to false.

Method Details

The EASI method is a Fourier-based technique for performing variance-based methods of global sensitivity analysis for the computation of first order effects (Sobol’ indices), hence belonging into the same class of algorithms as FAST and RBD. It is a computationally cheap method for which existing data can be used. Unlike the FAST and RBD methods which use a specially generated sample set that contains suitable frequency data for the input factors, in EASI these frequencies are introduced by sorting and shuffling the available input samples.

API

gsa(f, method::EASI, p_range; samples, batch = false)
gsa(X, Y, method::EASI)

Example

using GlobalSensitivity, Test

function ishi_batch(X)
A= 7
B= 0.1
@. sin(X[1,:]) + A*sin(X[2,:])^2+ B*X[3,:]^4 *sin(X[1,:])
end
function ishi(X)
A= 7
B= 0.1
sin(X) + A*sin(X)^2+ B*X^4 *sin(X)
end

lb = -ones(4)*π
ub = ones(4)*π

res1 = gsa(ishi,EASI(),[[lb[i],ub[i]] for i in 1:4],samples=15000)
res2 = gsa(ishi_batch,EASI(),[[lb[i],ub[i]] for i in 1:4],samples=15000,batch=true)

X = QuasiMonteCarlo.sample(15000, lb, ub, QuasiMonteCarlo.SobolSample())
Y = ishi.([X[:, i] for i in 1:15000])

res1 = gsa(X, Y, EASI())
res1 = gsa(X, Y, EASI(; dct_method = true))
source