Dakotathon

A Python API for the Dakota iterative systems analysis toolkit.

uncertaintysensitivityoptimizationcalibration

true

Contributor(s)

Initial contribute: 2021-09-15

Authorship

:  
University of Colorado
:  
mark.piper@colorado.edu
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Classification(s)

Application-focused categoriesNatural-perspectiveLand regions
Application-focused categoriesIntegrated-perspectiveRegional scale

Detailed Description

English {{currentDetailLanguage}} English

quoted from:https://csdms.colorado.edu/wiki/Model:Dakotathon

Dakota is a software toolkit, developed at Sandia National Laboratories, that provides an interface between models and a library of analysis methods, including support for sensitivity analysis, uncertainty quantification, optimization, and calibration techniques. Dakotathon is a Python package that wraps and extends Dakota’s file-based user interface. It simplifies the process of configuring and running a Dakota experiment, and it allows a Dakota experiment to be scripted. Any model written in Python that exposes a Basic Model Interface (BMI), as well as any model componentized in the CSDMS modeling framework, automatically works with Dakotathon. Currently, six Dakota analysis methods have been implemented from the much larger Dakota library:

模型元数据

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Mark Piper (2021). Dakotathon, Model Item, OpenGMS, https://geomodeling.njnu.edu.cn/modelItem/1ffcd0f3-0cb1-46a7-9f36-12da60388e0b
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Contributor(s)

Initial contribute : 2021-09-15

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Authorship

:  
University of Colorado
:  
mark.piper@colorado.edu
Is authorship not correct? Feed back

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