MADS (Model Analysis & Decision Support)

MADS is an integrated high-performance computational framework for data/model/decision analyses.

MADS can be applied to perform:

Sensitivity Analysis
Parameter Estimation
Model Inversion and Calibration
Uncertainty Quantification
Model Selection and Model Averaging
Model Reduction and Surrogate Modeling
Machine Learning (e.g., Blind Source Separation, Source Identification, Feature Extraction, Matrix / Tensor Factorization, etc.)
Decision Analysis and Support

MADS has been tested and verified extensively.

MADS can efficiently utilize available computational resources.

MADS utilizes adaptive rules and techniques which allow the analyses to be performed efficiently with minimum user input.

MADS provides a series of alternative algorithms to execute various types of data- and model-based analyses.

Documentation

Detailed documentation including description of all MADS modules and functions is available at GitHub, ReadtheDocs and LANL sites.

Detailed model diagnostics problem is demonstrated here

Installation

After starting Julia, execute in the REPL:

import Pkg; Pkg.add("Mads")

to access the latest released version.

To utilize the latest updates (commits) use:

import Pkg; Pkg.add(Pkg.PackageSpec(name="Mads", rev="master"))

Docker

docker run --interactive --tty montyvesselinov/madsjulia

Testing

Execute:

import Mads; Mads.test()

import Pkg; Pkg.test("Mads")

Examples

To explore getting-started instructions, execute:

import Mads; Mads.help()

Various examples located in the examples directory of the Mads repository.

To run some of these examples, execute

include(Mads.dir * "/../examples/contamination/contamination.jl")

to perform various example analyses related to groundwater contaminant transport, or execute

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

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

Installation behind a firewall

Set proxies executing the following lines in the bash command-line environment:

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, at LANL, you will need to execute the following lines in the 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

Proxies can be setup directly in the Julia REPL as well:

ENV["ftp_proxy"] =  "http://proxyout.lanl.gov:8080"
ENV["rsync_proxy"] = "http://proxyout.lanl.gov:8080"
ENV["http_proxy"] = "http://proxyout.lanl.gov:8080"
ENV["https_proxy"] = "http://proxyout.lanl.gov:8080"
ENV["no_proxy"] = ".lanl.gov"

Julia uses git for package management. In some cases, you may need to add in the .gitconfig file in your home directory the following lines to support git behind a firewall:

[url "git@github.com:"]
    insteadOf = https://github.com/
[url "git@gitlab.com:"]
    insteadOf = https://gitlab.com/
[url "https://"]
    insteadOf = git://
[url "http://"]
    insteadOf = git://

or execute:

git config --global url."https://".insteadOf git://
git config --global url."http://".insteadOf git://
git config --global url."git@gitlab.com:".insteadOf https://gitlab.com/
git config --global url."git@github.com:".insteadOf https://github.com/