Skip to main content

# phlearn Package for modelling pseudo-Hamiltonian systems with neural networks as described in [(Eidnes et al., 2022)](https://arxiv.org/pdf/2206.02660.pdf) for ODEs and [(Eidnes and Lye, 2023)](https://arxiv.org/pdf/2304.14374.pdf) for PDEs.

[Documentation available here](https://pseudo-Hamiltonian-neural-networks.readthedocs.io/en/latest/)

  • phlearn
    • phsystems

    • phnns

    • utils

phsystems implements classes and functionality for simulating pseudo-Hamiltonian systems. phnns implements classes and functionality for learning and inference with pseudo-Hamiltonian neural networks.

Metadata

Release files for phlearn 1.1.2

For a detailed explanation of source distributions (sdists) and built distributions (wheels), please see the package formats documentation.

Source distribution (sdist)

Source distribution for phlearn 1.1.2
File Size Uploaded Provenance Actions
phlearn-1.1.2.tar.gz 48.4 kB Without provenance Details for phlearn-1.1.2.tar.gz

Built distribution (wheel)

Table of built distributions (wheels) for phlearn 1.1.2
File Interpreter ABI Platform Actions
phlearn-1.1.2-py3-none-any.whl Python 3 none any Details for phlearn-1.1.2-py3-none-any.whl

Total release size: 148.2 kB

Release files / phlearn-1.1.2.tar.gz

Download URL phlearn-1.1.2.tar.gz
Size 48.4 kB
Tags Source
SHA-256 checksum
How to use checksums
fd65315ed72d8d9e54b8102d17dab98ce40982173c40f1379174f3396a13e6c6
BLAKE2b-256 checksum
How to use checksums
15cc909715f568335ed5fac0061abda6df9ef359c3a488ce3a4914096d82a65d
Upload date
Uploaded using Trusted Publishing?
What is trusted publishing?
No
Uploaded via twine/4.0.2 CPython/3.8.13

Release files / phlearn-1.1.2-py3-none-any.whl

Download URL phlearn-1.1.2-py3-none-any.whl
Size 99.8 kB
Tags Python 3
SHA-256 checksum
How to use checksums
3d5eacabccb74cb5c4bf9c24c3943d5be5f3cb8385b6d3f708fe8d768ebdc10a
BLAKE2b-256 checksum
How to use checksums
e69445d19b09e5d6a2d90f340c96960f04998a2eac8b0acee28335c34307b5f2
Upload date
Uploaded using Trusted Publishing?
What is trusted publishing?
No
Uploaded via twine/4.0.2 CPython/3.8.13

Security for phlearn 1.1.2

Provenance

Provenance describes where a file came from. On PyPI, provenance is shared via attestations, which provide a verifiable record of the build or publishing details. View details, limitations and caveats.

No provenance found

None of the files in this release were uploaded with provenance metadata.

A note on package security

PyPI is a repository for distributing packages, not a service for auditing them. While third-party security researchers and our staff do their best to detect and remove malicious packages, PyPI cannot guarantee the quality, security or suitability of any given package.

To learn more about protecting yourself from malicious actors, visit our package security documentation.

Anthropic, PBC Visionary sponsor Bloomberg Visionary sponsor Hudson River Trading Visionary sponsor Meta Visionary sponsor NVIDIA Visionary sponsor Microsoft Sustainability sponsor Depot Continuous Integration AWS Cloud computing and Security Sponsor Datadog Monitoring Fastly CDN Google Download Analytics Sentry Error logging StatusPage Status page