traitblender
Blender addon for simulating raw datasets under known evolutionary models
Science Score: 57.0%
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
Found .zenodo.json file -
✓DOI references
Found 3 DOI reference(s) in README -
✓Academic publication links
Links to: zenodo.org -
○Academic email domains
-
✓Institutional organization owner
Organization imageomics has institutional domain (imageomics.osu.edu) -
○JOSS paper metadata
-
○Scientific vocabulary similarity
Low similarity (10.8%) to scientific vocabulary
Keywords
Repository
Blender addon for simulating raw datasets under known evolutionary models
Basic Info
- Host: GitHub
- Owner: Imageomics
- License: mit
- Language: Python
- Default Branch: main
- Homepage: https://github.com/calcharp/TraitBlender
- Size: 610 MB
Statistics
- Stars: 1
- Watchers: 5
- Forks: 1
- Open Issues: 0
- Releases: 2
Topics
Metadata Files
README.md
TraitBlender 

This is the repo for TraitBlender, a Blender addon and workflow for simulating raw datasets.
Major work on this project began at Image Datapalooza 2023, a workshop hosted by the Imageomics Institute. A major goal of the institute is to use Big Data and modern machine learning methods to better understand traits, such as phenotypes. However, many machine learning methods, such as neural networks, operate as "Black Boxes", making it difficult to understand their results and interpret their decisions. This problem is compounded by the fact that phenotypes themselves are often quite complex, and are often constructed and used differently by different researchers.
The decouple these different sources of confusion, we introduce TraitBlender, and Blender addon and workflow for simulating raw datasets under known processes. By raw data, we mean images and 3D models of simulated taxa.
There have long-been established software ecosystems for simulating tabular data under imaging evolutionary processes, such as the ape or phytools packages in R. These packages have empowered many researchers who develop models to test those models under common assumptions. As far as we know, however, no such accessible ecosystem previously existed for generating images are 3D models under these processes.
Rest in progress
Docker
The following commands need to be run from the base directory of this repo.
Build
docker build -t traitblender .
Run
On Linux or Mac
mkdir results
docker run -v $(pwd)/results:/src/TraitBlender/results -it traitblender
On Windows you will need to replace $(pwd) with your current directory.
When the above command completes check the results directory for images created.
Owner
- Name: Imageomics Institute
- Login: Imageomics
- Kind: organization
- Website: https://imageomics.osu.edu
- Twitter: imageomics
- Repositories: 4
- Profile: https://github.com/Imageomics
GitHub Events
Total
- Watch event: 1
- Push event: 12
- Fork event: 1
- Create event: 1
Last Year
- Watch event: 1
- Push event: 12
- Fork event: 1
- Create event: 1
Issues and Pull Requests
Last synced: about 2 years ago
All Time
- Total issues: 2
- Total pull requests: 3
- Average time to close issues: 4 days
- Average time to close pull requests: about 5 hours
- Total issue authors: 2
- Total pull request authors: 2
- Average comments per issue: 3.0
- Average comments per pull request: 0.33
- Merged pull requests: 3
- Bot issues: 0
- Bot pull requests: 0
Past Year
- Issues: 2
- Pull requests: 3
- Average time to close issues: 4 days
- Average time to close pull requests: about 5 hours
- Issue authors: 2
- Pull request authors: 2
- Average comments per issue: 3.0
- Average comments per pull request: 0.33
- Merged pull requests: 3
- Bot issues: 0
- Bot pull requests: 0
Top Authors
Issue Authors
- johnbradley (1)
Pull Request Authors
- johnbradley (2)
Top Labels
Issue Labels
Pull Request Labels
Dependencies
- ubuntu 22.04 build
- actions/checkout v4 composite
- docker/build-push-action ad44023a93711e3deb337508980b4b5e9bcdc5dc composite
- docker/login-action f054a8b539a109f9f41c372932f1ae047eff08c9 composite
- docker/metadata-action v4 composite