Data

Tools

Indexes

Applications

Experiments

Open Source Science

https://github.com/madsjulia/metaprogtools.jl

Meta Programming Tools

https://github.com/madsjulia/metaprogtools.jl

Science Score: 20.0%

This score indicates how likely this project is to be science-related based on various indicators:

  • ○
    CITATION.cff file
  • ○
    codemeta.json file
  • ○
    .zenodo.json file
  • ○
    DOI references
  • ✓
    Academic publication links
    Links to: scholar.google
  • ✓
    Committers with academic emails
    1 of 2 committers (50.0%) from academic institutions
  • ○
    Institutional organization owner
  • ○
    JOSS paper metadata
  • ○
    Scientific vocabulary similarity
    Low similarity (14.6%) to scientific vocabulary

Keywords

analyses decision-support high-performance-computing julia mads meta-programming
Last synced: 6 months ago · JSON representation

Repository

Meta Programming Tools

Basic Info
  • Host: GitHub
  • Owner: madsjulia
  • License: gpl-3.0
  • Language: Julia
  • Default Branch: master
  • Homepage: http://mads.gitlab.io
  • Size: 41 KB
Statistics
  • Stars: 0
  • Watchers: 8
  • Forks: 3
  • Open Issues: 1
  • Releases: 0
Topics
analyses decision-support high-performance-computing julia mads meta-programming
Created about 10 years ago · Last pushed over 5 years ago
Metadata Files
Readme License

Readme.md

MetaProgTools

Meta Programming Tools.

MetaProgTools is a module of MADS.

MADS

MADS (Model Analysis & Decision Support) 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.

Documentation

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

Installation

julia Pkg.add("Mads")

Installation behind a firewall

Julia uses git for the package management. To install Julia packages behind a firewall, add the following lines in the .gitconfig file in your home directory:

git [url "https://"] insteadOf = git://

or execute:

bash git config --global url."https://".insteadOf git://

Set proxies:

bash 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:

bash 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:

julia import Mads

To explore getting-started instructions, execute:

julia Mads.help()

There are various examples located in the examples directory of the Mads repository.

For example, execute

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

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

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

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

Developers

Publications, Presentations, Projects

Owner

  • Name: MADS: Model Analysis & Decision Support
  • Login: madsjulia
  • Kind: organization
  • Email: velimir.vesselinov@gmail.com
  • Location: USA

High-performance computational framework for data analytics, model diagnostics, machine learning & decision support

GitHub Events

Total
Last Year

Committers

Last synced: 8 months ago

All Time
  • Total Commits: 46
  • Total Committers: 2
  • Avg Commits per committer: 23.0
  • Development Distribution Score (DDS): 0.283
Past Year
  • Commits: 0
  • Committers: 0
  • Avg Commits per committer: 0.0
  • Development Distribution Score (DDS): 0.0
Top Committers
Name Email Commits
monty v****v@g****m 33
Daniel O'Malley o****d@l****v 13
Committer Domains (Top 20 + Academic)
lanl.gov: 1

Issues and Pull Requests

Last synced: 6 months ago

All Time
  • Total issues: 0
  • Total pull requests: 2
  • Average time to close issues: N/A
  • Average time to close pull requests: 23 days
  • Total issue authors: 0
  • Total pull request authors: 2
  • Average comments per issue: 0
  • Average comments per pull request: 1.0
  • Merged pull requests: 0
  • Bot issues: 0
  • Bot pull requests: 0
Past Year
  • Issues: 0
  • Pull requests: 0
  • Average time to close issues: N/A
  • Average time to close pull requests: N/A
  • Issue authors: 0
  • Pull request authors: 0
  • Average comments per issue: 0
  • Average comments per pull request: 0
  • Merged pull requests: 0
  • Bot issues: 0
  • Bot pull requests: 0
View more stats
Top Authors
Issue Authors
Pull Request Authors
  • tkelman (1)
  • JuliaTagBot (1)
Top Labels
Issue Labels
Pull Request Labels

Packages

  • Total packages: 1
  • Total downloads:
    • julia 10 total
  • Total dependent packages: 3
  • Total dependent repositories: 15
  • Total versions: 4
juliahub.com: MetaProgTools

Meta Programming Tools

  • Versions: 4
  • Dependent Packages: 3
  • Dependent Repositories: 15
  • Downloads: 10 Total
Rankings
Dependent repos count: 2.3%
Dependent packages count: 12.5%
Forks count: 27.7%
Average: 29.2%
Stargazers count: 74.3%
Last synced: 6 months ago