Versions: [6.12]


Download        : docker pull ghcr.io/autamus/dakota
Compressed Size : 163MB


The Dakota toolkit provides a flexible, extensible interface between analysis codes and iterative systems analysis methods. Dakota contains algorithms for: - optimization with gradient and non gradient-based methods; - uncertainty quantification with sampling, reliability, stochastic - expansion, and epistemic methods; - parameter estimation with nonlinear least squares methods; - sensitivity/variance analysis with design of experiments and - parameter study methods. These capabilities may be used on their own or as components within advanced strategies such as hybrid optimization, surrogate-based optimization, mixed integer nonlinear programming, or optimization under uncertainty.


Pull (Download)

To download the latest version of dakota run,

docker pull ghcr.io/autamus/dakota:latest

or to download a specific version of dakota run,

docker pull ghcr.io/autamus/dakota:6.12


To run the container as an application run,

docker run --rm ghcr.io/autamus/dakota dakota --version

or to run the container in an interactive session run,

docker run -it --rm ghcr.io/autamus/dakota bash

Mounting volumes between the container and your machine

To access files from your machine within the dakota container you’ll have to mount them using the -v external/path:internal/path option.

For example,

docker run -v ~/Documents/Data:/Data ghcr.io/autamus/dakota dakota /Data/myData.csv

which will mount the ~/Documents/Data directory on your computer to the /Data directory within the container.


If you’re looking to use this container in an HPC environment we recommend using Singularity-HPC to use the container just as any other module on the cluster. Check out the SHPC dakota container here.