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+# Leeds Institute for Fluid Dynamics Machine Learning For Earth Sciences #
+
# Physics Informed Neural Networks
+
+[![GitHub release](https://img.shields.io/github/release/cemac/LIFD_Physics_Informed_Neural_Networks.svg)](https://github.com/cemac/LIFD_Physics_Informed_Neural_Networks/releases) [![GitHub top language](https://img.shields.io/github/languages/top/cemac/LIFD_Physics_Informed_Neural_Networks.svg)](https://github.com/cemac/LIFD_Physics_Informed_Neural_Networks) [![GitHub issues](https://img.shields.io/github/issues/cemac/LIFD_Physics_Informed_Neural_Networks.svg)](https://github.com/cemac/LIFD_Physics_Informed_Neural_Networks/issues) [![GitHub last commit](https://img.shields.io/github/last-commit/cemac/LIFD_Physics_Informed_Neural_Networks.svg)](https://github.com/cemac/LIFD_Physics_Informed_Neural_Networks/commits/master) [![GitHub All Releases](https://img.shields.io/github/downloads/cemac/LIFD_Physics_Informed_Neural_Networks/total.svg)](https://github.com/cemac/LIFD_Physics_Informed_Neural_Networks/releases) ![GitHub](https://img.shields.io/github/license/cemac/LIFD_Physics_Informed_Neural_Networks.svg)[![DOI](https://zenodo.org/badge/366734586.svg)](https://zenodo.org/badge/latestdoi/366734586)
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+[![LIFD_Physics_Informed_Neural_Networks](https://github.com/cemac/LIFD_Physics_Informed_Neural_Networks/actions/workflows/python-package-conda.yml/badge.svg)](https://github.com/cemac/LIFD_Physics_Informed_Neural_Networks/actions/workflows/python-package-conda.yml)
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These set of notebooks explore Physics Informed Neural Networks to explore Partial Differential Equations
This tutorial has been split into 3 tutorials.
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* [PNNs Navier Stokes example](PNNs_NavierStokesEquation_example.pdf)
* [PNNs Navier Stokes Hidden Fluid Mechanics](PNNs_NavierStokes_HFM.md)
+### Quick start
+
+If you're already familiar with git, anaconda and virtual environments the environment you need to create is found in PINN.yml and the code below to install activate and launch the notebook. The .yml file has been tested on the latest linux, macOS and windows operating systems.
+
+```bash
+git clone --recurse-submodules -j8 git@github.com:cemac/LIFD_Physics_Informed_Neural_Networks.git
+cd LIFD_Physics_Informed_Neural_Networks
+conda env create -f PINN.yml
+conda activate PINN
+jupyter-notebook
+```
+
+
## Installation and Requirements
This notebook is designed to run on a laptop with no special hardware required therefore recommended to do a local installation as outlined in the repository [howtorun](../howtorun.md) and [jupyter_notebooks](../jupyter_notebooks.md) sections.
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**If this does not work please clone the [PINNs](https://github.com/maziarraissi/PINNs) repository into your Physics_Informed_Neural_Networks folder on your computer**
-### Quick start
-If you're already familiar with git, anaconda and virtual environments the environment you need to create is found in CNN.yml and the code below to install activate and launch the notebook
+# Licence information #
-```bash
-conda env create -f PINN.yml
-conda activate PINN
-jupyter-notebook
-```
+
LIFD_ENV_ML_NOTEBOOKS by cemac is licensed under a Creative Commons Attribution 4.0 International License.
+
+## Acknowledgements
+
+Thanks to Matthew Gaddes for the basis of this tutotial. This tutorial is part of the [LIFD ENV ML NOTEBOOKS](https://github.com/cemac/LIFD_ENV_ML_NOTEBOOKS) please refer to for full acknowledgements.