Overview
PINNFlow is a code for regional outer core flow inversion, using Physics-Informed Neural Networks in a PyTorch framework. If you use this code, please cite this paper.
Documentation
The documentation of the current release is available here.
1 maintainer
Metadata
1 maintainer
Release files for pinnflow 1.0.7
For a detailed explanation of source distributions (sdists) and built distributions (wheels), please see the package formats documentation.
Source distribution (sdist)
| File | Size | Uploaded | Provenance | Actions |
|---|---|---|---|---|
| pinnflow-1.0.7.tar.gz | 2.1 MB | Without provenance | Details for pinnflow-1.0.7.tar.gz |
Built distribution (wheel)
| File | Interpreter | ABI | Platform | Actions Reset |
|---|---|---|---|---|
| pinnflow-1.0.7-py3-none-any.whl | Python 3 | none | any | Details for pinnflow-1.0.7-py3-none-any.whl |
Total release size: 2.1 MB
Release files / pinnflow-1.0.7.tar.gz
| Download URL | pinnflow-1.0.7.tar.gz |
|---|---|
| Size | 2.1 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 | |
|
Uploaded using Trusted Publishing? What is trusted publishing? |
No |
| Uploaded via |
twine/6.1.0 CPython/3.12.1
|
Release files / pinnflow-1.0.7-py3-none-any.whl
| Download URL | pinnflow-1.0.7-py3-none-any.whl |
|---|---|
| Size | 8.0 kB |
| 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 | |
|
Uploaded using Trusted Publishing? What is trusted publishing? |
No |
| Uploaded via |
twine/6.1.0 CPython/3.12.1
|
Security for pinnflow 1.0.7
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No provenance found
None of the files in this release were uploaded with provenance metadata.
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