HiQGA Documentation

HiQGA Documentation

This is a general purpose package for spatial statistical inference, geophysical forward modeling, Bayesian inference and inversion (both determinstic and probabilistic).

Readily usable geophysical forward operators are to do with AEM, CSEM and MT physics (references underneath), for which the time domain AEM codes are fairly production-ready. The current EM modeling is in 1D, but the inversion framework is dimensionally agnostic (e.g., you can regress images). Adding your own geophysical operators is easy, keep reading down here.

This package implements both the nested (2-layer) and vanilla trans-dimensional Gaussian process algorithm as published in

Installation

To install, in a perfect world we'd use Julia's Pkg REPL by hitting ] to enter pkg> mode. Then enter the following, at the pkg> prompt:

pkg> add https://github.com/GeoscienceAustralia/HiQGA.jl.git

Usage

Examples of how to use the package can be found in the examples directory. Simply cd to the relevant example directory and include the .jl files in the order they are named. If using VSCode make sure to do Julia: Change to this Directory from the three dots menu on the top right. The Markov Chain Monte Carlo sampler is configured to support parallel tempering on multiple CPUs - some of the examples accomplish this with Julia's built-in multiprocessing, and others use MPI in order to support inversions on HPC clusters that don't work with Julia's default SSH-based multiprocessing. The MPI examples require MPI.jl and MPIClusterManagers.jl, which are not installed as dependencies for this package, so you will need to ensure they are installed and configured correctly to run these examples. Please note that MPIClusterManagers.jl has issues with Julia <1.4.2, so please ensure you are using an up-to-date Julia version.

Some example scripts have as a dependency Revise.jl as we're still actively developing this package, so you may need to install Revise if not already installed. All Julia users should be developing with Revise! After installation, to run the examples, simply clone the package separately (or download as a ZIP), navigate to the examples folder and run the scripts in their numerical order.

Updating the package

pkg> update HiQGA

Developing HiQGA or modifying it for your own special forward physics

After you have ]added HiQGA you can simply do: 

pkg>dev HiQGA

If you haven't added it already, you can do:

pkg>dev https://github.com/GeoscienceAustralia/HiQGA.jl.git

It will download to your JULIA_PKG_DEVDIR.

Another way is to simply clone or download this repository to your JULIA_PKG_DEVDIR, rename the cloned directory HiQGA removing the .jl bit and do

pkg>dev HiQGA

Here's a gist on adding your own module if you want to modify the source code. Alternatively, if you only want to use the sampling methods in HiQGA.transD_GP without contributing to the source (boo! j/k) here's another gist which is more appropriate. These gists were written originally for a package called transD_GP so you will have to modify using transD_GP to using HiQGA.transD_GP. Documentation is important and we're working on improving it before a full-release.

Development setup on NCI

The preferred development and usage environment for HiQGA is Visual Studio Code, which provides interactive execution of Julia code through the VSCode Julia extension. To install VSCode on the National Computational Infrastructure (NCI), you need to extract the VSCode rpm package using the steps in this gist, to a location where your account has write access.

It is also useful to use Revise.jl to ensure changes to the package are immediately reflected in a running Julia REPL (this is the reason that Revise is a dependency on some example scripts as noted above). More information on a workflow to use Revise during development can be found here.

References for AEM and CSEM physics