PeleAnalysis documentation

Contents:

• Data Structures
  • Plotfiles
  • FArrayBox and MultiFab
  • MEF - Marc’s Element Format
  • StreamData
  • N-dimensional bins
• buildPMF - Create Fortran 1D interpolator
• conditionalMean - Create data for conditional mean plots
• averagePlotfile - Create a pltfile by averaging existing pltfiles
• combinePlts - Combine plotfiles
• curvature - Curvature of plotfile scalar
• grad - Gradient of plotfile scalar
• isosurface - Isosurface of plotfile scalar
  • Details
  • Signed distance function
• jpdf - Create data for joint PDF files
• stream - Streamlines of plotfile vector
  • Options
• sampleStreamlines - Sample a plotfile to streamlines
• streamSub - Subset streamlines
• streamTubeStats - Stream tube statistics
• subPlt - Subset plotfile
• surfMEF Tools - Manipulate MEF files

README.rst:

PeleAnalysis

This repository contains a collection of standalone routines for processing plotfiles created with the AMReX software framework for block-structured adaptive mesh refinement simulations. Documentation is under development, but is available at

https://peleanalysis.readthedocs.io/en/latest/

AMReX is required for these tools, and is available https://github.com/AMReX-Codes/amrex

In order to build these processing tools, you should clone or fork the amrex repository, and set the environment variable AMREX_HOME to point to the local folder where that is placed. Then clone this repository, cd Src and edit the GNUmakefile to select which tool to build. If AMReX is configured properly, a stand-alone executable will be built locally, based on the selected options, including spatial dimension (2 or 3), compiler choices, whether to build with MPI and/or OpenMP enabled, and whether to build a debugging or optimized version. Note that some of the tools require building a companion f90 source file - you must manually set the flag in the GNUmakefile accordingly. More extensive documentation is available (see building instructions below).

To add a new feature to PeleAnalysis, the procedure is:

1. Create a branch for the new feature (locally)

   git checkout -b AmazingNewFeature
   

2. Develop the feature, merging changes often from the master branch into your AmazingNewFeature branch

   git commit -m "Developed AmazingNewFeature"
   git checkout master
   git pull                     [fix any identified conflicts between local and remote branches of "master"]
   git checkout AmazingNewFeature
   git merge master        [fix any identified conflicts between "master" and "AmazingNewFeature"]
   

3. Push feature branch to PeleAnalysis repository (if you have write access, otherwise fork the repo and push the new branch to your fork):

git push -u origin AmazingNewFeature [Note: -u option required only for the first push of new branch]

4. Submit a merge request through the github project page - be sure you are requesting to merge your branch to the master branch.

Documentation for the analysis routines exists in the Docs directory. To build the documentation:

cd Docs
make html

This research was supported by the Exascale Computing Project (ECP), Project Number: 17-SC-20-SC, a collaborative effort of two DOE organizations – the Office of Science and the National Nuclear Security Administration – responsible for the planning and preparation of a capable exascale ecosystem – including software, applications, hardware, advanced system engineering, and early testbed platforms – to support the nation’s exascale computing imperative.

Indices and tables

• Index
• Search Page