Production package for inverse PDE surrogate modeling
Project description
inversepde
A production-ready package for inverse PDE surrogate modeling.
Installation
pip install -e .
Quickstart
import torch
from inversepde import DiffusionFamily, InverseSolver
family = DiffusionFamily()
solver = InverseSolver(family=family)
coords = torch.rand(1, 120, 2)
values = torch.rand(1, 120)
pred = solver.predict(coords, values)
print(pred.shape)
API
PDEFamily: abstract base class for PDE families.DiffusionFamily: diffusion data-generation wrapper.ReactionDiffusionFamily: reaction-diffusion wrapper.InverseSolver: high-level training and inference API.load_pretrainedandlist_available_pretrained: checkpoint helpers.plot_prediction: visualization utility.
Development
pip install -e .[dev]
pytest -q
Reproducibility
- Python:
3.14.x(validated in this workspace) - Install:
pip install -e .[dev] - Tests:
python -m pytest -q - Lock file:
requirements.lock.txt
Release Checks
ruff check .
mypy inversepde/inversepde
python -m build
python -m twine check dist/*
Project details
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