mpilosov/mads.jl

MADS: Model Analysis & Decision Support

MADS (Model Analysis & Decision Support)

MADS is an integrated open-source high-performance computational (HPC) framework in Julia. MADS can execute a wide range of data- and model-based analyses:

• Sensitivity Analysis
• Parameter Estimation
• Model Inversion and Calibration
• Uncertainty Quantification
• Model Selection and Model Averaging
• Model Reduction and Surrogate Modeling
• Machine Learning and Blind Source Separation
• Decision Analysis and Support

MADS has been tested to perform HPC simulations on a wide-range multi-processor clusters and parallel environments (Moab, Slurm, etc.). MADS utilizes adaptive rules and techniques which allows the analyses to be performed with a minimum user input. The code provides a series of alternative algorithms to execute each type of data- and model-based analyses.

Example

import Mads

include(Mads.madsdir * "/../examples/contamination/contamination.jl")
include(Mads.madsdir * "/../examples/bigdt/bigdt.jl")

Documentation

All the available MADS modules and functions are described at madsjulia.github.io

Installation

After starting Julia, execute:

Pkg.add("Mads")

Installation of MADS behind a firewall

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

MADS examples

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 example analyses related to groundwater contaminant transport, or execute

include(Mads.madsdir * "/../examples/bigdt/bigdt.jl")

to perform Bayesian Information Gap Decision Theory (BIG-DT) analysis.