PhiFlow

Homepage     Documentation     API     Demos     Fluids Tutorial     Playground

PhiFlow is an open-source simulation toolkit built for optimization and machine learning applications. It is written mostly in Python and can be used with NumPy, TensorFlow, Jax or PyTorch. The close integration with machine learning frameworks allows it to leverage their automatic differentiation functionality, making it easy to build end-to-end differentiable functions involving both learning models and physics simulations.

See the installation Instructions on how to compile the optional custom CUDA operations.

Project links

Key dates

PyPI data
Data sourced directly from PyPI's database.
  • Released:
Latest release

1 maintainer

PyPI data
Data sourced directly from PyPI's database.
Avatar for PhilippHoll from gravatar.com PhilippHoll

Credits

Author: Philipp Holl

License

MIT License (MIT)

Tags

Differentiable Simulation Fluid Machine Learning Deep Learning

Classifiers

Report project as malware

Download files

Download the file for your platform. If you're not sure which to choose, learn more about installing packages.

Source Distribution

phiflow-3.4.0.tar.gz (207.4 kB view details)

Uploaded Source

File details

Details for the file phiflow-3.4.0.tar.gz.

File metadata

  • Download URL: phiflow-3.4.0.tar.gz
  • Upload date:
  • Size: 207.4 kB
  • Tags: Source
  • Uploaded using Trusted Publishing? No
  • Uploaded via: twine/5.1.1 CPython/3.11.9

File hashes

Hashes for phiflow-3.4.0.tar.gz
Algorithm Hash digest
SHA256 5e447df3944d418bdaa198cc3ed92904f6f453565a5fdd1553f0996030c7db29
MD5 80f35845647a1cd9e470b0bda209f8de
BLAKE2b-256 b6576990d61a59c6a7daab8e5fd318d37682f72831bcd9b116ed5dd779d1801b

See more details on using hashes here.

Supported by

AWS Cloud computing and Security Sponsor Datadog Monitoring Depot Continuous Integration Fastly CDN Google Download Analytics Sentry Error logging StatusPage Status page