CGCGNet
Coarse-grained crystal graph neural networks
Installation
We strongly recommend the Anaconda distribution of Python (3.10 release is required). You can create and activate a new conda environment with commands
conda create --name cgcgnet python=3.10
conda activate cgcgnet
conda install ipykernel openbabel
CGCGNet can be installed via the following command
pip install cgcgnet
1 maintainer
Metadata
1 maintainer
Release files for cgcgnet 0.1
For a detailed explanation of source distributions (sdists) and built distributions (wheels), please see the package formats documentation.
Source distribution (sdist)
| File | Size | Uploaded | |
|---|---|---|---|
| cgcgnet-0.1.tar.gz | 56.9 MB | Details |
Built distribution (wheel)
| File | Interpreter | ABI | Platform | Reset |
|---|---|---|---|---|
| cgcgnet-0.1-py3-none-any.whl | Python 3 | none | any | Details |
Total release size: 113.9 MB
Release files / cgcgnet-0.1.tar.gz
| Download URL | cgcgnet-0.1.tar.gz |
|---|---|
| Size | 56.9 MB |
| Tags | Source |
|
SHA-256 checksum How to use checksums |
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BLAKE2b-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/4.0.2 CPython/3.10.6
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Release files / cgcgnet-0.1-py3-none-any.whl
| Download URL | cgcgnet-0.1-py3-none-any.whl |
|---|---|
| Size | 57.0 MB |
| Tags | Python 3 |
|
SHA-256 checksum How to use checksums |
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BLAKE2b-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/4.0.2 CPython/3.10.6
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