Science Score: 57.0%
This score indicates how likely this project is to be science-related based on various indicators:
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✓CITATION.cff file
Found 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
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○Academic email domains
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○Institutional organization owner
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○JOSS paper metadata
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○Scientific vocabulary similarity
Low similarity (13.7%) to scientific vocabulary
Repository
Fake snow flakes: snowfakes!
Basic Info
- Host: GitHub
- Owner: agilescientific
- License: apache-2.0
- Language: Python
- Default Branch: main
- Homepage: https://code.agilescientific.com/snowfake
- Size: 4.65 MB
Statistics
- Stars: 7
- Watchers: 2
- Forks: 3
- Open Issues: 8
- Releases: 4
Metadata Files
README.md
snowfake
Make Gravner-Griffeath "snowfakes"! This code implements:
Janko Gravner, David Griffeath (2008). Modeling snow crystal growth II: A mesoscopic lattice map with plausible dynamics. Physica D: Nonlinear Phenomena 237 (3), p 385-404. DOI: 10.1016/j.physd.2007.09.008.
Installation
You can install this package with pip (be careful not to type "snowflake"):
pip install snowfake
Installing scikit-image allows you to use a different affine transformation, but I haven't figured out yet if it's better or not.
pip install snowfake[skimage]
Documentation
Read the documentation
Example
You can produce a random snowfake with:
python
import snowfake
s = snowfake.random()
Alternatively, this code produces the crystal in Figure 5b of the Gravner & Griffeath (2008):
```python from snowfake import Snowfake
params = { 'ρ': 0.35, # or 'rho': 0.35 if you prefer... 'β': 1.4, 'α': 0.001, 'θ': 0.015, 'κ': 0.05, 'μ': 0.015, 'γ': 0.01, 'σ': 0.00005, 'random': False, } s = Snowfake(size=801, **params) ```
Now you're ready to grow and plot the snowfake:
python
s.grow()
s.plot()
The various physical parameter arrays are available as s.a (attachment flag), s.b (boundary mass), s.c (the crystal itself) and s.d (the vapour). The arrays exist on hexgrids; you can rectify them with, for example, s.rectify('c').
The parameter σ (note that you can also spell out sigma if you prefer) can be a 1D array with one sample per epoch. This will vary the vapour density ρ through time. The parameter ρ can be a 2D array of shape (size, size); this will vary the initial vapour density through space.
Testing
You can run the tests (requires pytest and pytest-cov) with
pytest
Building
This repo uses PEP 517-style packaging. Read more about this and about Python packaging in general.
Building the project requires build, so first:
pip install build
Then to build snowfake locally:
python -m build
The builds both .tar.gz and .whl files, either of which you can install with pip.
Continuous integration
This repo has two GitHub 'workflows' or 'actions':
- Push to
main: Run all tests on all version of Python. This is the Run tests workflow. - Publish a new release: Build and upload to PyPI. This is the Publish to PyPI workflow. Publish using the GitHub interface, for example (read more
Owner
- Name: Agile*
- Login: agilescientific
- Kind: organization
- Email: hello@agilescientific.com
- Location: Canada
- Website: http://www.agilescientific.com/
- Repositories: 49
- Profile: https://github.com/agilescientific
Agile was a scientific computing and consulting company in Canada, but it is now closed for business.
Citation (CITATION.cff)
cff-version: 1.2.0
title: snowfake
version: 0.1
message: Please use this information to cite this work.
type: software
authors:
- given-names: Matt
family-names: Hall
email: matt@agilescientific.com
affiliation: Agile Scientific
orcid: 'https://orcid.org/0000-0002-4054-8295'
date-released: 2021-11-28
GitHub Events
Total
Last Year
Issues and Pull Requests
Last synced: 8 months ago
All Time
- Total issues: 13
- Total pull requests: 4
- Average time to close issues: 22 days
- Average time to close pull requests: 1 day
- Total issue authors: 2
- Total pull request authors: 2
- Average comments per issue: 0.31
- 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
Top Authors
Issue Authors
- kwinkunks (12)
- EvanBianco (1)
Pull Request Authors
- mtb-za (2)
- EvanBianco (2)
Top Labels
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Dependencies
- JamesIves/github-pages-deploy-action v4.2.3 composite
- actions/checkout v1 composite
- actions/checkout v2 composite
- actions/setup-python v2 composite
- pypa/gh-action-pypi-publish 27b31702a0e7fc50959f5ad993c78deac1bdfc29 composite
- actions/checkout v2 composite
- actions/setup-python v2 composite