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.
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.
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.