Recent News
SNAP Version 2.6.6 Released
November 7, 2018
AptPlot 6.8.0 Updated
February 19, 2018
PyPost 1.3.3 Released
February 19, 2018

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 1.5.2 - Released 10/30/2018:

  • The uncertainty quatification framework was updated to support DAKOTA version 6.8. This version is now bundled with the plug-in for Windows installations.
  • The Dakota report step has been updated to suppress an extraneous error message that was reported by Dakota when analyzing the uncertainty quantification results.
  • The legacy odt output file definition which was causing an error to be reported after executing a report job step has been removed from the uncertainty job step. This file definition was replaced by the report file definition which handles either odt or docx output files.