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Open Source Science

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

Geostatistical Inversion

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

Science Score: 46.0%

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

  • ○
    CITATION.cff file
  • ✓
    codemeta.json file
    Found codemeta.json file
  • ○
    .zenodo.json file
  • ✓
    DOI references
    Found 8 DOI reference(s) in README
  • ✓
    Academic publication links
    Links to: scholar.google
  • ✓
    Committers with academic emails
    2 of 4 committers (50.0%) from academic institutions
  • ○
    Institutional organization owner
  • ○
    JOSS paper metadata
  • ○
    Scientific vocabulary similarity
    Low similarity (10.7%) to scientific vocabulary

Keywords

aquifer calibration geostatistics heterogenity high-performance-computing inverse-problems inversion julia mads matrix-factorization parameter-estimation permeability randomization stochastic-process

Keywords from Contributors

parallel parallel-computing
Last synced: 5 months ago · JSON representation

Repository

Geostatistical Inversion

Basic Info
  • Host: GitHub
  • Owner: madsjulia
  • License: gpl-3.0
  • Language: Julia
  • Default Branch: master
  • Homepage: http://mads.gitlab.io
  • Size: 188 KB
Statistics
  • Stars: 5
  • Watchers: 5
  • Forks: 6
  • Open Issues: 0
  • Releases: 9
Topics
aquifer calibration geostatistics heterogenity high-performance-computing inverse-problems inversion julia mads matrix-factorization parameter-estimation permeability randomization stochastic-process
Created about 9 years ago · Last pushed about 1 year ago
Metadata Files
Readme License

README.md

GeostatInversion

Coverage Status

This package provides methods for inverse analysis using parameter fields that are represented using geostatistical (stochastic) methods. Currently, two geostatistical methods are implemented. One is the Principal Component Geostatistical Approach (PCGA) proposed by Kitanidis & Lee. The other utilizes a Randomized Geostatistical Approach (RGA) that builds on PCGA.

Randomized Geostatistical Approach (RGA) references:

Two versions of PCGA are implemented in this package

  • pcgadirect, which uses full matrices and direct solvers during iterations
  • pcgalsqr, which uses low-rank representations of the matrices combined with iterative solvers during iterations

The RGA method, rga, can use either of these approaches using the keyword argument. That is, by doing rga(...; pcgafunc=GeostatInversion.pcgadirect) or rga(...; pcgafunc=GeostatInversion.pcgalsqr).

GeostatInversion is a module of MADS.

Example

```julia import GeostatInversion

Ns = map(x->round(Int, 25 * x), 1 + rand(N)) k0 = randn() dk = rand() beta = -2 - rand() k = GeostatInversion.FFTRF.powerlaw_structuredgrid(Ns, k0, dk, beta) ```

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 of 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 analysis.

Documentation

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

Installation

julia Pkg.add("GeostatInversion")

Installation behind a firewall

Julia uses git for 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

Projects:

Publications, Presentations

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
  • Create event: 1
  • Commit comment event: 2
  • Release event: 1
  • Issues event: 1
  • Watch event: 2
  • Issue comment event: 1
  • Push event: 4
  • Pull request event: 1
Last Year
  • Create event: 1
  • Commit comment event: 2
  • Release event: 1
  • Issues event: 1
  • Watch event: 2
  • Issue comment event: 1
  • Push event: 4
  • Pull request event: 1

Committers

Last synced: about 2 years ago

All Time
  • Total Commits: 180
  • Total Committers: 4
  • Avg Commits per committer: 45.0
  • Development Distribution Score (DDS): 0.6
Past Year
  • Commits: 13
  • Committers: 1
  • Avg Commits per committer: 13.0
  • Development Distribution Score (DDS): 0.0
Top Committers
Name Email Commits
monty v****v@g****m 72
Ellen Le e****e@l****v 56
Daniel O'Malley o****d@l****v 50
Harmen Stoppels h****s@g****m 2
Committer Domains (Top 20 + Academic)
lanl.gov: 2

Issues and Pull Requests

Last synced: 6 months ago

All Time
  • Total issues: 3
  • Total pull requests: 2
  • Average time to close issues: over 1 year
  • Average time to close pull requests: over 2 years
  • Total issue authors: 3
  • Total pull request authors: 2
  • Average comments per issue: 5.0
  • Average comments per pull request: 1.0
  • Merged pull requests: 1
  • 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
  • rfourquet (1)
  • tkelman (1)
  • JuliaTagBot (1)
Pull Request Authors
  • JuliaTagBot (2)
  • haampie (1)
Top Labels
Issue Labels
Pull Request Labels

Packages

  • Total packages: 1
  • Total downloads:
    • julia 7 total
  • Total dependent packages: 1
  • Total dependent repositories: 3
  • Total versions: 7
juliahub.com: GeostatInversion

Geostatistical Inversion

  • Versions: 7
  • Dependent Packages: 1
  • Dependent Repositories: 3
  • Downloads: 7 Total
Rankings
Dependent repos count: 6.8%
Forks count: 18.8%
Dependent packages count: 24.0%
Average: 25.6%
Stargazers count: 53.0%
Last synced: 6 months ago

Dependencies

.github/workflows/TagBot.yml actions
  • JuliaRegistries/TagBot v1 composite