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tum-pbs/PhiFlow ★ 1932 234 APPLICATION

PhiFlow is a Python library for differentiable physics simulation, primarily targeting fluid dynamics, particle systems, and PDE-based optimization. It provides a unified field abstraction (CenteredGrid, StaggeredGrid, PointCloud, Mesh) with automatic resampling and boundary handling, enabling seamless integration with machine learning workflows. The library supports multiple backends (NumPy, PyTorch, TensorFlow, JAX) and features a rich geometry module, physics solvers (advection, diffusion, incompressible flow, SPH, waves), and visualization tools. While its core abstractions are clean and well-tested, the codebase exhibits some technical drift due to deprecated API surface, large monolithic Dash-based web UI, and heavy reliance on the external phiml tensor library. Nonetheless, it is actively maintained with extensive test coverage and a growing research community.

RATING: 8.1/10 MAINT: active DRIFT: medium
#differentiable-physics #simulation #pde-solver #fluid-dynamics #machine-learning #python-library #scientific-computing #differentiable-simulations #fluid-simulations #deep-learning #neural-networks
▸ 4 reusable components found
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