Recent News
SNAP Version 2.6.0 Released
November 21, 2017
AptPlot 6.8.0 Released
December 1, 2017
PyPost 1.3.0 Released
December 1, 2017

Uncertainty Plug-in

The Uncertainty plug-in provides support for performing uncertainty analysis with SNAP models. The plug-in provides a parametric stream type tailored for uncertainty analysis. This stream type defines parametric tasks based on a set number of random samplings. The random samples are defined in the stream type properties and mapped to model variables: parametric tasks are generated for these each set of random samples. The sequence of analysis code steps that utilize the random variates is entirely defined by the user. Once this sequence of steps is complete, the results are fed into an extraction step, which utilizes AptPlot to compute figures-of-merit. Finally, the figures-of-merit are fed into an uncertainty quantification step used to assess the effect of random variation on the model.

The Uncertainty Plug-in User's Manual provides instructions for working with Uncertainty Job Streams in SNAP. This Manual is also available as a searchable help set in SNAP.

Change Log

Version 1.4.2 - Releasd 11/21/2017:

  • The DAKOTA report generator was updated to resolve an issue where the table that contains the variate data could trim the negative sign off values whose magnitude is less than 1000.0, but not essentially zero.
  • The error handling for parsing DAKOTA output files of unsupported versions now identifies why the parsing could not complete.