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NISP

(31/8447 downloads)
Non Intrusive Spectral Projection
Details
Version
2.7-1
Author(s)
Jean-Marc Martinez
Michael Baudin
John Burkardt
Knut Petras
Chong Gu
Entity
- -
Package maintainer
Michael Baudin
License
Supported Scilab Versions
>= 5.5.0
Dependencies
Specfun (≥ 0.4)
Apifun (≥ 0.2)
Distfun (≥ 0.7)
Stixbox (≥ 2.2)
Creation Date
15th of July 2014
ATOMS packaging system
Available on
How To Install
atomsInstall('NISP')
Description
This module allows to perform sensitivity analysis. This is the analysis of the uncertainty in the output of a given model, depending on the uncertainty in its inputs. The analysis is based on chaos polynomials, which are orthogonal polynomials which are used as an approximation of the original model. Once the coefficients of the chaos polynomial are computed, the associated sensitivity indices are straightforward to get. This toolbox has been created in the context of the OPUS project : http://opus-project.fr/ within the workpackage 2.1.1 "Construction de méta-modèles". This project has received funding (2008-2011) by Agence Nationale de la recherche : http://www.agence-nationale-recherche.fr/ See in the help provided in the help/en_US directory of the toolbox for more information about its use. Use cases are presented in the demos directory. Features -------- Main Features: * randvar: * Manage various types of random variables * uniform, normal, exponential, log-normal * setrandvar: * Manage various sampling methods for sets of random variables * Monte-Carlo, Sobol Quasi-Random, Latin Hypercube Sampling, LHS Max Min sampling, and various samplings based on Smolyak Cubature points. * polychaos: * Manage polynomial chaos expansion and get specific outputs * mean, variance, sensitivity indices, quantiles, Wilks quantiles, correlation, etc... * Generate a stand-alone C source code which computes the output of the polynomial chaos expansion. Tutorials * nisp_theory : Introduction to PC decomposition. * setrandvar_tutorial : A tutorial for the designs from setrandvar. Configuration Functions: * nisp_destroyall : Destroy all current objects. * nisp_getpath : Returns the path to the current module. * nisp_initseed : Sets the seed of the uniform random number generator. * nisp_printall : Prints all current objects. * nisp_shutdown : Shuts down the NISP toolbox. * nisp_startup : Starts up the NISP toolbox. * nisp_verboselevelget : Returns the current verbose level. * nisp_verboselevelset : Sets the current verbose level. Sensitivity Analysis * nisp_bruteforcesa : Compute sensitivity indices by brute force. * nisp_sobolsaAll : Compute sensitivity indices by Sobol, Ishigami, Homma. * nisp_sobolsaFirst : Compute sensitivity indices by Sobol, Ishigami, Homma. * nisp_sobolsaTotal : Compute sensitivity indices by Sobol, Ishigami, Homma. Test functions: * nisp_ishigami : Returns the Ishigami function. * nisp_ishigamisa : Exact sensitivity analysis for the Ishigami function * nisp_product : Returns the value of the Product function * nisp_productsa : Exact sensitivity analysis for the Product function * nisp_sum : Returns the value of the Product function * nisp_sumsa : Returns the sensitivity indices of the Sum function Acknowledgements ---------------- * Paul Beaucaire * Allan Cornet
Files (6)
[947.35 Ko] NISP-2.7-1-src.zip
Same sources as in previous toolbox version, updated to make it available for
Scilab 5.5.0
[1001.69 Ko] NISP_2.7-1.bin.x86_64.linux.tar.gz
Linux version (x86_64)
Automatically generated by the ATOMS compilation chain

[1.15 Mo] NISP_2.7-1.bin.x64.windows.zip
Windows version (x64)
Automatically generated by the ATOMS compilation chain

[1.16 Mo] NISP_2.7-1.bin.windows.zip
Windows version (i686)
Automatically generated by the ATOMS compilation chain

[1018.78 Ko] NISP_2.7-1.bin.i686.linux.tar.gz
Linux version (i686)
Automatically generated by the ATOMS compilation chain

[956.74 Ko] NISP_2.7-1.bin.x86_64.darwin.tar.gz
MacOSX version
Automatically generated by the ATOMS compilation chain

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