2021-07-05 11:18:12 +08:00
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[](https://www.apache.org/licenses/LICENSE-2.0)
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[](https://python.org)
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2021-07-09 08:26:53 +08:00
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[](https://idrlnet.readthedocs.io/en/latest/?badge=latest)
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2021-07-05 11:18:12 +08:00
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## Installation
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### Docker
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```bash
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git clone https://github.com/idrl-lab/idrlnet
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cd idrlnet
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docker build . -t idrlnet_dev
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docker run -it -p [EXPOSED_SSH_PORT]:22 -v [CURRENT_WORK_DIR]:/root/pinnnet idrlnet_dev:latest bash
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```
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### Anaconda
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```bash
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git clone https://github.com/idrl-lab/idrlnet
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cd idrlnet
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conda create -n idrlnet_dev python=3.8 -y
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conda activate idrlnet_dev
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pip install -r requirements.txt
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pip install -e .
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```
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# IDRLnet
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IDRLnet is a machine learning library on top of [Pytorch](https://www.tensorflow.org/). Use IDRLnet if you need a machine
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learning library that solves both forward and inverse partial differential equations (PDEs) via physics-informed neural
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networks (PINN). IDRLnet is a flexible framework inspired by [Nvidia Simnet](https://developer.nvidia.com/simnet>).
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## Features
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IDRLnet supports
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- complex domain geometries without mesh generation. Provided geometries include interval, triangle, rectangle, polygon,
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circle, sphere... Other geometries can be constructed using three boolean operations: union, difference, and
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intersection;
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- sampling in the interior of the defined geometry or on the boundary with given conditions.
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- enables the user code to be structured. Data sources, operations, constraints are all represented by ``Node``. The graph
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will be automatically constructed via label symbols of each node. Getting rid of the explicit construction via
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explicit expressions, users model problems more naturally.
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- solving variational minimization problem;
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- solving integral differential equation;
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- adaptive resampling;
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- recover unknown parameters of PDEs from noisy measurement data.
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It is also easy to customize IDRLnet to meet new demands.
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- Main Dependencies
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- [Matplotlib](https://matplotlib.org/)
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- [NumPy](http://www.numpy.org/)
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- [Sympy](https://https://www.sympy.org/)==1.5.1
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- [pytorch](https://www.tensorflow.org/)>=1.7.0
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## Contributing to IDRLnet
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First off, thanks for taking the time to contribute!
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- **Reporting bugs.** To report a bug, simply open an issue in the GitHub "Issues" section.
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- **Suggesting enhancements.** To submit an enhancement suggestion for IDRLnet, including completely new features and
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minor improvements to existing functionality, let us know by opening an issue.
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- **Pull requests.** If you made improvements to IDRLnet, fixed a bug, or had a new example, feel free to send us a
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pull-request.
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- **Asking questions.** To get help on how to use IDRLnet or its functionalities, you can as well open an issue.
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- **Answering questions.** If you know the answer to any question in the "Issues", you are welcomed to answer.
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## The Team
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IDRLnet was originally developed by IDRL lab.
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