Metadata-Version: 2.1
Name: pina-mathlab
Version: 0.1.2.post2412
Summary: Physic Informed Neural networks for Advance modeling.
Home-page: https://github.com/mathLab/PINA
Author: PINA Contributors
Author-email: demo.nicola@gmail.com, dario.coscia@sissa.it
License: MIT
Keywords: machine-learning deep-learning modeling pytorch ode neural-networks differential-equations pde hacktoberfest pinn physics-informed physics-informed-neural-networks neural-operators equation-learning lightining
Classifier: Development Status :: 3 - Alpha
Classifier: License :: OSI Approved :: MIT License
Classifier: Programming Language :: Python :: 3
Classifier: Programming Language :: Python :: 3.8
Classifier: Programming Language :: Python :: 3.9
Classifier: Programming Language :: Python :: 3.10
Classifier: Programming Language :: Python :: 3.11
Classifier: Programming Language :: Python :: 3.12
Classifier: Intended Audience :: Science/Research
Classifier: Topic :: Scientific/Engineering :: Mathematics
License-File: LICENSE.rst
Requires-Dist: numpy <2.0
Requires-Dist: matplotlib
Requires-Dist: torch
Requires-Dist: lightning
Requires-Dist: pytorch-lightning
Provides-Extra: docs
Requires-Dist: sphinx >5.0 ; extra == 'docs'
Requires-Dist: sphinx-rtd-theme ; extra == 'docs'
Requires-Dist: sphinx-copybutton ; extra == 'docs'
Requires-Dist: sphinx-design ; extra == 'docs'
Requires-Dist: pydata-sphinx-theme ; extra == 'docs'
Provides-Extra: test
Requires-Dist: pytest ; extra == 'test'
Requires-Dist: pytest-cov ; extra == 'test'
Requires-Dist: scipy ; extra == 'test'

PINA is a Python package providing an easy interface to deal with physics-informed neural networks (PINN) for the approximation of (differential, nonlinear, ...) functions. Based on Pytorch, PINA offers a simple and intuitive way to formalize a specific problem and solve it using PINN. The approximated solution of a differential equation can be implemented using PINA in a few lines of code thanks to the intuitive and user-friendly interface.
