PhiFlow

PhiFlow

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Beginner Guides

Installation Instructions: Requirements, installation, CUDA compilation

Cookbook: Example code snippets for various things

Tensors and Dimensions

Differentiation

Fluids

I/O

Visualization

Neural Networks

Advanced

Module Documentation

Module API Documentation
phi.vis Visualization: Plotting, interactive user interfaces
Dash: Web interface
Console: Command line interface
phi.physics
phi.physics.advect
phi.physics.fluid
phi.physics.diffuse
phi.physics.flip
Fluids Tutorial: Introduction to core classes and fluid-related functions.
Overview: Domains, built-in physics functions
Functions for Fluid Simulations: Advection, projection, diffusion
phi.field Overview: Grids, particles
Staggered Grids: Data layout, usage
Reading and Writing Simulation Data
Scene Format Specification: Directory layout, file format
phi.geom Overview: Differentiable Geometry
phi.math
phi.math.backend
phi.math.extrapolation
phi.math.magic
Overview: Named dimensions, backends, indexing, non-uniform tensors, precision
Optimization and Training: Automatic differentiation, neural network training
Performance: GPU, JIT compilation, profiler
phi.torch.nets
phi.tf.nets
phi.jax.stax.nets
Built-in Neural Networks: Architectures, convenience functions

Core Classes

API Documentation

The API documentation is generated using pdoc3. To manually generate the documentation, add the PhiFlow directory to your Python path and run

$ pdoc --html --output-dir docs --force phi

This requires PyTorch, TensorFlow and Jax to be installed, in addition to the standard ΦFlow requirements.

Contributing to ΦFlow

Contributions are welcome!

If you have changes to merge, check out our style guide before opening a pull request.