Dakotathon: Difference between revisions
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[[File:Dakotathon.jpg| | [[ File:Dakotathon.jpg | 350px | right ]] | ||
[https://dakota.sandia.gov Dakota] is a software toolkit | [https://dakota.sandia.gov Dakota] is a software toolkit developed at Sandia National Laboratories | ||
that provides an interface between models and a library of analysis methods, | that provides an interface between models and a library of analysis methods, | ||
including support for sensitivity analysis, uncertainty quantification, optimization, and calibration techniques. | including support for sensitivity analysis, uncertainty quantification, optimization, and calibration techniques. | ||
Dakota is a powerful tool, but its learning curve is steep: | |||
the user not only must understand the structure and syntax of the Dakota input file, | |||
but also must develop intermediate code | |||
that allows Dakota to set up and run a model, | |||
read outputs from the model, | |||
and calculate a response statistic from the outputs. | |||
The CSDMS Dakota Interface, or '''Dakotathon''', | The CSDMS Dakota Interface, or '''Dakotathon''', | ||
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It simplifies the process of configuring and running a Dakota experiment, | It simplifies the process of configuring and running a Dakota experiment, | ||
and it allows a Dakota experiment to be scripted. | and it allows a Dakota experiment to be scripted. | ||
Dakotathon creates the Dakota input file and provides a generic analysis driver. | |||
Any model componentized in the CSDMS modeling framework | |||
automatically works with Dakotathon. | automatically works with Dakotathon. | ||
Dakotathon has a plugin architecture, so models not wrapped into the CSDMS modeling framework | |||
can be accessed by Dakotathon by programmatically extending a template; | |||
an example is provided in the Dakotathon distribution. | |||
<noinclude> | |||
Currently, six Dakota analysis methods have been implemented from the much larger Dakota library: | Currently, six Dakota analysis methods have been implemented from the much larger Dakota library: | ||
* vector parameter study, | * [https://dakota.sandia.gov/sites/default/files/docs/6.1/html-ref/method-vector_parameter_study.html vector parameter study], | ||
* centered parameter study, | * [https://dakota.sandia.gov/sites/default/files/docs/6.1/html-ref/method-centered_parameter_study.html centered parameter study], | ||
* multidim parameter study, | * [https://dakota.sandia.gov/sites/default/files/docs/6.1/html-ref/method-multidim_parameter_study.html multidim parameter study], | ||
* sampling, | * [https://dakota.sandia.gov/sites/default/files/docs/6.1/html-ref/method-sampling.html sampling], | ||
* polynomial chaos, and | * [https://dakota.sandia.gov/sites/default/files/docs/6.1/html-ref/method-polynomial_chaos.html polynomial chaos], and | ||
* stochastic collocation. | * [https://dakota.sandia.gov/sites/default/files/docs/6.1/html-ref/method-stoch_collocation.html stochastic collocation]. | ||
See Dakotathon's CSDMS Model page | |||
for instructions on installing Dakotathon, | |||
and an example of using it. | |||
== Links == | |||
* The CSDMS [[Model:Dakotathon|Model page]] for Dakotathon | * The CSDMS [[Model:Dakotathon|Model page]] for Dakotathon | ||
* https://github.com/csdms/dakota | |||
* http://csdms-dakota.readthedocs.io | |||
* https://dakota.sandia.gov/ | |||
** https://dakota.sandia.gov/download.html | |||
** https://dakota.sandia.gov/content/install-dakota | |||
* https://dakota.sandia.gov//sites/default/files/docs/6.5/html-ref/index.html | |||
* Slides and repository for AGU talk https://github.com/mdpiper/AGU-2016 | |||
[[User:Mpiper|Mpiper]] ([[User talk:Mpiper|talk]]) 14:09, 27 December 2016 (MST) | |||
<noinclude> | |||
Revision as of 14:10, 27 December 2016
The CSDMS Dakota Interface
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. Dakota is a powerful tool, but its learning curve is steep: the user not only must understand the structure and syntax of the Dakota input file, but also must develop intermediate code that allows Dakota to set up and run a model, read outputs from the model, and calculate a response statistic from the outputs.
The CSDMS Dakota Interface, or 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. Dakotathon creates the Dakota input file and provides a generic analysis driver. Any model componentized in the CSDMS modeling framework automatically works with Dakotathon. Dakotathon has a plugin architecture, so models not wrapped into the CSDMS modeling framework can be accessed by Dakotathon by programmatically extending a template; an example is provided in the Dakotathon distribution.
Currently, six Dakota analysis methods have been implemented from the much larger Dakota library:
- vector parameter study,
- centered parameter study,
- multidim parameter study,
- sampling,
- polynomial chaos, and
- stochastic collocation.
See Dakotathon's CSDMS Model page for instructions on installing Dakotathon, and an example of using it.
Links
- The CSDMS Model page for Dakotathon
- https://github.com/csdms/dakota
- http://csdms-dakota.readthedocs.io
- https://dakota.sandia.gov/
- https://dakota.sandia.gov//sites/default/files/docs/6.5/html-ref/index.html
- Slides and repository for AGU talk https://github.com/mdpiper/AGU-2016
