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NISP

(3385 downloads for this version - 22664 downloads for all versions)
Details
Version
2.7
Authors
Jean-Marc Martinez
Michael Baudin
John Burkardt
Knut Petras
Chong Gu
Owner Organization
- -
Maintainer
Michael Baudin
License
Dependencies
Creation Date
July 15, 2014
Source created on
Scilab 5.5.x
Binaries available on
Scilab 5.5.x:
Linux 32-bit Windows 32-bit Windows 64-bit MacOSX Linux 64-bit
Install command
--> 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)
[970.09 kB]
Source code archive
Same sources as in previous toolbox version, updated to make it available for
Scilab 5.5.0
[1.04 MB]
Linux 32-bit binary for Scilab 5.5.x
Linux 32-bit
Automatically generated by the ATOMS compilation chain

[1.21 MB]
Windows 32-bit binary for Scilab 5.5.x
Windows 32-bit
Automatically generated by the ATOMS compilation chain

[1.20 MB]
Windows 64-bit binary for Scilab 5.5.x
Windows 64-bit
Automatically generated by the ATOMS compilation chain

[979.70 kB]
MacOSX binary for Scilab 5.5.x
MacOSX version
Automatically generated by the ATOMS compilation chain

[1.03 MB]
Linux 64-bit binary for Scilab 5.5.x
Linux 64-bit
Automatically generated by the ATOMS compilation chain

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