MADS is an open-source Julia code designed as an integrated high-performance computational framework performing a wide range of model-based analyses:
- Sensitivity Analysis
- Parameter Estimation
- Model Inversion and Calibration
- Uncertainty Quantification
- Model Selection and Averaging
- Decision Support
MADS utilizes adaptive rules and techniques which allows the analyses to be performed with minimum user input. The code provides a series of alternative algorithms to perform each type of model analyses.
All the available MADS modules and functions are described at madsjulia.github.io
After starting Julia, execute:
Pkg.add("Mads")
Julia uses git for package management. Add in the .gitconfig
file in your home directory:
[url "https://"]
insteadOf = git://
or execute:
git config --global url."https://".insteadOf git://
Set proxies:
export ftp_proxy=http://proxyout.<your_site>:8080
export rsync_proxy=http://proxyout.<your_site>:8080
export http_proxy=http://proxyout.<your_site>:8080
export https_proxy=http://proxyout.<your_site>:8080
export no_proxy=.<your_site>
For example, if you are doing this at LANL, you will need to execute the following lines in your bash command-line environment:
export ftp_proxy=http://proxyout.lanl.gov:8080
export rsync_proxy=http://proxyout.lanl.gov:8080
export http_proxy=http://proxyout.lanl.gov:8080
export https_proxy=http://proxyout.lanl.gov:8080
export no_proxy=.lanl.gov
In Julia REPL, do the following commands:
import Mads
To explore getting-started instructions, execute:
Mads.help()
There are various examples located in the examples
directory of the Mads
repository.
For example, execute
include(Mads.madsdir * "/../examples/contamination/contamination.jl")
to perform various analyses related to contaminant transport, or execute
include(Mads.madsdir * "/../examples/bigdt/bigdt.jl")
to perform BIG-DT analysis.