GrooveMat
Get your atoms moving!
Overview
This software package uses the Crystal Graph Convolutional Neural Networks (CGCNN) framework and M3gnet to create an un-supervised GNN that converges the internal degrees of freedom of a crystal lattice. The package is very simple, allowing you to train the model and predict converged cif files!
Download
To download disco, use the command below
pip install groovemat
To get an overview of the commands, run the following command
groovemat --help
Results
Below is a table containing some of the results gathered from the program.
| CIF ID | Mean Error (Å) | Max Error (Å) |
|---|---|---|
| Nd1 In1 O3 | 0.0087 | 0.0125 |
| Np1 Be1 O3 | 0.0061 | 0.0074 |
| Mn3 Au1 N1 | 0.0039 | 0.0076 |
| Na1 Li1 O3 | 0.0077 | 0.0095 |
| La1 Cr1 O3 | 0.0088 | 0.0135 |
Download
pip install groovemat
1 maintainer
Metadata
1 maintainer
Release files for groovemat 0.9.11
For a detailed explanation of source distributions (sdists) and built distributions (wheels), please see the package formats documentation.
Source distribution (sdist)
| File | Size | Uploaded | |
|---|---|---|---|
| groovemat-0.9.11.tar.gz | 16.5 kB | Details |
Built distribution (wheel)
| File | Interpreter | ABI | Platform | Reset |
|---|---|---|---|---|
| groovemat-0.9.11-py3-none-any.whl | Python 3 | none | any | Details |
Total release size: 34.0 kB
Release files / groovemat-0.9.11.tar.gz
| Download URL | groovemat-0.9.11.tar.gz |
|---|---|
| Size | 16.5 kB |
| Tags | Source |
|
SHA-256 checksum How to use checksums |
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Uploaded using Trusted Publishing? What is trusted publishing? |
No |
| Uploaded via |
twine/6.1.0 CPython/3.10.13
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Release files / groovemat-0.9.11-py3-none-any.whl
| Download URL | groovemat-0.9.11-py3-none-any.whl |
|---|---|
| Size | 17.5 kB |
| Tags | Python 3 |
|
SHA-256 checksum How to use checksums |
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| Upload date | |
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Uploaded using Trusted Publishing? What is trusted publishing? |
No |
| Uploaded via |
twine/6.1.0 CPython/3.10.13
|
