mamonca
mamonca: magnetic Monte Carlo code - Published in JOSS (2024)
Science Score: 95.0%
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Found 4 DOI reference(s) in README and JOSS metadata -
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Published in Journal of Open Source Software
Scientific Fields
Repository
Basic Info
- Host: GitHub
- Owner: samwaseda
- License: bsd-3-clause
- Language: Jupyter Notebook
- Default Branch: main
- Size: 5.6 MB
Statistics
- Stars: 2
- Watchers: 1
- Forks: 0
- Open Issues: 1
- Releases: 4
Metadata Files
README.md
mamonca - interactive Magnetic Monte Carlo
This code allows you to launch Metropolis Monte Carlo simulations via Heisenberg Landau models (with various polynomial degrees) from a jupyter notebook.
Model
mamonca is based on the Heisenberg Landau model of the format:
$$\mathcal H = -\frac{1}{2}\sum{ij,\kappa}J{ij,\kappa}mi^{2\kappa+1}mj^{2\kappa+1} + \sum{i,\kappa} A{i,\kappa} m_i^{2\kappa}$$
where $i$ and $j$ go over all atoms and $\kappa$ is the exponent ($\kappa=1$ and $A_{i,\kappa}=0$ for all $i$ and $\kappa$ for the classical Heisenberg model). The evaluation takes place either via Metropolis Monte Carlo (MC) method or spindynamics (SD). MC has the advantage of converging very fast, while SD also delivers the kinetics.
How to compile
mamonca can be installed directly from conda:
conda install -c conda-forge mamonca
In order to use build it from the repository, run
git clone https://github.com/samwaseda/mamonca
cd mamonca
python setup.py build_ext --user
First steps:
In the following simple (but complete) example, we create a bcc Fe system using pyiron (install via conda install pyiron) and launch a Metropolis Monte Carlo simulation with a Heisenberg coefficient J=0.1 (eV) for the first nearest neighbor pairs:
```python from pyiron_atomistics import Project from mamonca import MC
basis = Project('.').create.structure.bulk( name='Fe', cubic=True )
Repeat the structure 10 times in each direction
structure = basis.repeat(10) J = 0.1 # eV neighbors = structure.getneighbors() firstshelltensor = neighbors.getshell_matrix()[0]
mc = MC(len(structure)) mc.setheisenbergcoeff(J * firstshelltensor)
mc.run(temperature=300, numberofiterations=1000) ```
More complete list of examples can be found in notebooks/first_steps.ipynb
How to set inputs and get outputs
As a rule of thumb, you can set all input parameters via functions starting with set_. Similarly, output values can be obtained via functions whose names start with get_. Most notably, you can get all basic output values via get_output() in a dictionary. Otherwise, take a look at the list of auto-complete and see their docstrings
Dependencies
- Cython
- numpy
Notes
- Currently only Linux installation is supported
- You can run tests located in the
testsfolder
Owner
- Name: Sam Dareska
- Login: samwaseda
- Kind: user
- Location: Kamchatka
- Company: Sam and his funny friends
- Website: http://www.sams-studio.com
- Repositories: 5
- Profile: https://github.com/samwaseda
yooooooooo
JOSS Publication
mamonca: magnetic Monte Carlo code
Authors
Max-Planck-Institut für Eisenforschung, Max-Planck-Straße 1, D-40237 Düsseldorf, Germany
Max-Planck-Institut für Eisenforschung, Max-Planck-Straße 1, D-40237 Düsseldorf, Germany
Max-Planck-Institut für Eisenforschung, Max-Planck-Straße 1, D-40237 Düsseldorf, Germany
Editor
Kelly Rowland
Tags
Heisenberg-Landau model Spin dynamics Metadynamics Thermodynamic integrationGitHub Events
Total
- Release event: 2
- Delete event: 2
- Issue comment event: 1
- Push event: 22
- Pull request review event: 6
- Pull request review comment event: 4
- Pull request event: 8
- Create event: 5
Last Year
- Release event: 2
- Delete event: 2
- Issue comment event: 1
- Push event: 22
- Pull request review event: 6
- Pull request review comment event: 4
- Pull request event: 8
- Create event: 5
Committers
Last synced: 5 months ago
Top Committers
| Name | Commits | |
|---|---|---|
| Sam Waseda | o****a@m****e | 349 |
| s4b7r | g****b@s****e | 4 |
| Jan Janssen | j****n@l****v | 1 |
| Osamu Waseda | o****a@i****r | 1 |
Committer Domains (Top 20 + Academic)
Issues and Pull Requests
Last synced: 4 months ago
All Time
- Total issues: 0
- Total pull requests: 35
- Average time to close issues: N/A
- Average time to close pull requests: 5 days
- Total issue authors: 0
- Total pull request authors: 2
- Average comments per issue: 0
- Average comments per pull request: 0.26
- Merged pull requests: 29
- Bot issues: 0
- Bot pull requests: 0
Past Year
- Issues: 0
- Pull requests: 7
- Average time to close issues: N/A
- Average time to close pull requests: about 5 hours
- Issue authors: 0
- Pull request authors: 1
- Average comments per issue: 0
- Average comments per pull request: 0.29
- Merged pull requests: 5
- Bot issues: 0
- Bot pull requests: 0
Top Authors
Issue Authors
Pull Request Authors
- samwaseda (44)
- jan-janssen (2)
Top Labels
Issue Labels
Pull Request Labels
Packages
- Total packages: 1
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Total downloads:
- pypi 18 last-month
- Total dependent packages: 0
- Total dependent repositories: 1
- Total versions: 6
- Total maintainers: 1
pypi.org: mamonca
mamonca - interactive Magnetic Monte Carlo code
- Homepage: https://github.com/samwaseda/mamonca
- Documentation: https://mamonca.readthedocs.io/
- License: BSD
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Latest release: 0.0.8
published over 1 year ago