VaMPy

VaMPy: An Automated and Objective Pipeline for Modeling Vascular Geometries - Published in JOSS (2023)

https://github.com/kvslab/vampy

Science Score: 98.0%

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

  • CITATION.cff file
    Found CITATION.cff file
  • codemeta.json file
    Found codemeta.json file
  • .zenodo.json file
    Found .zenodo.json file
  • DOI references
    Found 7 DOI reference(s) in README and JOSS metadata
  • Academic publication links
    Links to: joss.theoj.org, zenodo.org
  • Committers with academic emails
  • Institutional organization owner
  • JOSS paper metadata
    Published in Journal of Open Source Software

Keywords

computational-fluid-dynamics post-processing pre-processing vascular

Keywords from Contributors

fenics fluid-structure-interaction
Last synced: 6 months ago · JSON representation ·

Repository

A collection of tools for pre-processing, simulating, and post-processing vascular morphologies.

Basic Info
Statistics
  • Stars: 17
  • Watchers: 7
  • Forks: 9
  • Open Issues: 10
  • Releases: 8
Topics
computational-fluid-dynamics post-processing pre-processing vascular
Created over 7 years ago · Last pushed 11 months ago
Metadata Files
Readme Contributing License Citation

README.md

VaMPy - Vascular Modeling Pypeline


GPL-3.0 codecov CI GitHub pages DOI DOI


Output pre processing

Pre-processed and simulated artery model. From left to right: A variable density volumetric mesh, zoomed in view of an outlet showing the four boundary layers, corresponding inlet flow rate, outlet flow split, and probes for velocity and pressure sampling. From the simulation results, we have shown the velocity field represented by vectors, and the time averaged wall shear stress (TAWSS) as one of the many hemodynamic indices computed by the post-processing scripts.

Description

The Vascular Modeling Pypeline (VaMPy) is a collection of fully automated scripts used to prepare, run, and analyze cardiac and atrial morphologies. This includes pre-processing scripts for meshing and probe sampling, two Oasis problem files for simulating flow in the internal carotid artery and the left atrium, and a variety of post-processing scripts for computing WSS-based metrics, more advanced turbulence metrics, and a variety of morphological parameters in patient-specific geometries.

Installation

VaMPy is a Python package for Python >= 3.8, with main dependencies to morphMan and Oasis. VaMPy and its dependencies can be installed with conda on n Linux and
macOS using the following command:

conda create -n your_environment -c conda-forge vampy

More details on installation via conda can be found here. The package can also be installed and run through its latest Docker image supported by Windows, Linux, and macOS, and explained here.

Documentation

VaMPy's documentation is hosted here. This includes two tutorials, meant to guide the user through the basic steps of performing a computational fluid dynamic simulation in a vascular body.

Licence

VaMPy is licensed under the GNU GPL, version 3 or (at your option) any later version.

VaMPy is Copyright (2018-2023) by the authors.

Authors

VaMPy has been developed by

Issues

Please report bugs and other issues through the issue tracker at:

https://github.com/KVSlab/VaMPy/issues

Owner

  • Name: KVSlab
  • Login: KVSlab
  • Kind: organization

JOSS Publication

VaMPy: An Automated and Objective Pipeline for Modeling Vascular Geometries
Published
May 19, 2023
Volume 8, Issue 85, Page 5278
Authors
Henrik A. Kjeldsberg ORCID
Department of Computational Physiology, Simula Research Laboratory, Oslo, Norway
Aslak W. Bergersen ORCID
Department of Computational Physiology, Simula Research Laboratory, Oslo, Norway
Kristian Valen-Sendstad ORCID
Department of Computational Physiology, Simula Research Laboratory, Oslo, Norway
Editor
Kevin M. Moerman ORCID
Tags
pre-processing computational fluid dynamics post-processing vascular modeling automated objective pipeline

Citation (CITATION.cff)

cff-version: "1.2.0"
authors:
- family-names: Kjeldsberg
  given-names: Henrik A.
  orcid: "https://orcid.org/0000-0002-7764-4248"
- family-names: Bergersen
  given-names: Aslak W.
  orcid: "https://orcid.org/0000-0001-5063-3680"
- family-names: Valen-Sendstad
  given-names: Kristian
  orcid: "https://orcid.org/0000-0002-2907-0171"
doi: 10.5281/zenodo.7950605
message: If you use this software, please cite our article in the
  Journal of Open Source Software.
preferred-citation:
  authors:
  - family-names: Kjeldsberg
    given-names: Henrik A.
    orcid: "https://orcid.org/0000-0002-7764-4248"
  - family-names: Bergersen
    given-names: Aslak W.
    orcid: "https://orcid.org/0000-0001-5063-3680"
  - family-names: Valen-Sendstad
    given-names: Kristian
    orcid: "https://orcid.org/0000-0002-2907-0171"
  date-published: 2023-05-19
  doi: 10.21105/joss.05278
  issn: 2475-9066
  issue: 85
  journal: Journal of Open Source Software
  publisher:
    name: Open Journals
  start: 5278
  title: "VaMPy: An Automated and Objective Pipeline for Modeling
    Vascular Geometries"
  type: article
  url: "https://joss.theoj.org/papers/10.21105/joss.05278"
  volume: 8
title: "VaMPy: An Automated and Objective Pipeline for Modeling Vascular
  Geometries"

GitHub Events

Total
  • Watch event: 2
  • Delete event: 1
  • Issue comment event: 2
  • Push event: 2
  • Pull request review event: 3
  • Pull request event: 6
  • Fork event: 1
  • Create event: 1
Last Year
  • Watch event: 2
  • Delete event: 1
  • Issue comment event: 2
  • Push event: 2
  • Pull request review event: 3
  • Pull request event: 6
  • Fork event: 1
  • Create event: 1

Committers

Last synced: 7 months ago

All Time
  • Total Commits: 627
  • Total Committers: 8
  • Avg Commits per committer: 78.375
  • Development Distribution Score (DDS): 0.118
Past Year
  • Commits: 11
  • Committers: 3
  • Avg Commits per committer: 3.667
  • Development Distribution Score (DDS): 0.364
Top Committers
Name Email Commits
Henrik Kjedsberg h****g@l****o 553
Kei w****5@g****m 28
Aslak Bergersen a****n@g****m 25
Ehsan Khalili e****n@s****o 7
Jørgen S. Dokken d****n@s****o 6
cardioFluid 4****d 4
Johannes Ring j****g@g****m 2
Stef Smeets s****s 2
Committer Domains (Top 20 + Academic)

Issues and Pull Requests

Last synced: 6 months ago

All Time
  • Total issues: 24
  • Total pull requests: 79
  • Average time to close issues: 5 months
  • Average time to close pull requests: 7 days
  • Total issue authors: 10
  • Total pull request authors: 5
  • Average comments per issue: 2.96
  • Average comments per pull request: 0.82
  • Merged pull requests: 70
  • Bot issues: 0
  • Bot pull requests: 0
Past Year
  • Issues: 0
  • Pull requests: 6
  • Average time to close issues: N/A
  • Average time to close pull requests: 5 days
  • Issue authors: 0
  • Pull request authors: 2
  • Average comments per issue: 0
  • Average comments per pull request: 0.67
  • Merged pull requests: 6
  • Bot issues: 0
  • Bot pull requests: 0
Top Authors
Issue Authors
  • keiyamamo (11)
  • hkjeldsberg (2)
  • johannesring (2)
  • stefsmeets (2)
  • lshahid (2)
  • michaelbernini (1)
  • perolope (1)
  • Owais-Khan (1)
  • yewalenikhil65 (1)
  • perezrmaria (1)
Pull Request Authors
  • hkjeldsberg (65)
  • keiyamamo (16)
  • johannesring (3)
  • jorgensd (2)
  • stefsmeets (1)
Top Labels
Issue Labels
enhancement (4) bug (2)
Pull Request Labels

Dependencies

.github/workflows/check_and_test_package.yml actions
  • actions/cache v2 composite
  • actions/checkout v3 composite
  • codecov/codecov-action v3 composite
  • conda-incubator/setup-miniconda v2 composite
.github/workflows/deploy_pages.yml actions
  • actions/cache v2 composite
  • actions/checkout v3 composite
  • conda-incubator/setup-miniconda v2 composite
  • peaceiris/actions-gh-pages v3.6.1 composite
.github/workflows/docker.yml actions
  • actions/checkout v3 composite
  • docker/build-push-action v3 composite
  • docker/login-action v2 composite
  • docker/metadata-action v4 composite
  • docker/setup-buildx-action v2 composite
  • docker/setup-qemu-action v2 composite
docker/Dockerfile docker
  • condaforge/mambaforge latest build
environment.yml pypi
  • cppimport *
pyproject.toml pypi
  • matplotlib *
  • numpy *
requirements.txt pypi
  • ghp-import *
  • jupyter-book *
  • matplotlib *
  • numpy *