Saltelli Sampling
Saltelli sampling is a method to draw samples for the purpose of Sobol’
sensitvity analysis (variance-based sensitivity analysis). Detailed description
of the theory can be found in Saltelli [2002] and Saltelli et al. [2010].
The Saltelli class relies on the Python package SALib [Herman and Usher, 2017].
Saltelli Class
The Saltelli class is imported by:
from psimpy.sampler.saltelli import Saltelli
Methods
- class Saltelli(ndim, bounds=None, calc_second_order=True, skip_values=None)[source]
- Saltelli’s version of Sobol’ sampling. - Parameters
- ndim (int) – Dimension of parameters. 
- bounds (numpy array, optional) – Upper and lower boundaries of each parameter. Shape - (ndim, 2). bounds[:, 0] corresponds to lower boundaries of each parameter and bounds[:, 1] to upper boundaries of each parameter.
- calc_second_order (bool, optional) – If True, calculate second-order Sobol’ indices. If False, second-order Sobol’ indices are not computed. 
- skip_values (int, optional) – Number of points to skip in the Sobol’ sequence. It should be ideally a value of base \(2\). 
 
 - sample(nbase)[source]
- Draw samples using Saltelli’s extension of the Sobol’ sequence. - Parameters
- nbase (int) – Number of base samples. Correspond to the parameter - Nof- SALib.sample.saltelli.sample().
- Returns
- samples – Shape of - (nbase*(2*ndim+2), ndim)if- calc_second_orderis True. Shape of- (nbase*(ndim+2), ndim)if- calc_second_orderis False.
- Return type
- numpy array