PyAPD 0.1.5
A Python library for generating (optimal) anisotropic power diagrams
Requires Python: >=3.6

![Logo](https://raw.githubusercontent.com/mbuze/PyAPD/main/logo/logo.png)

# PyAPD	

A Python library for computing (optimal) anisotropic power diagrams using GPU acceleration. Current main application concerns geometric modelling of polycrystalline materials with curved boundaries with grains of prescribed volumes and fine control over aspect ratio and location of the grains.

## Installation

__Install with pip:__

    pip install PyAPD

## Example usage
See `/notebooks/tutorials/example_usage.ipynb`  [![nbviewer](https://raw.githubusercontent.com/jupyter/design/master/logos/Badges/nbviewer_badge.svg)](https://nbviewer.org/github/mbuze/PyAPD/blob/main/notebooks/tutorials/example_usage.ipynb?flush_cache=true)

### Google Colab

To quickly test the speed of the GPU-acceleration, you can play around with the notebook `example_usage.ipynb` in Google Colab [![Open In Colab](https://colab.research.google.com/assets/colab-badge.svg)](https://colab.research.google.com/github/mbuze/PyAPD/blob/main/notebooks/tutorials/example_usage.ipynb). 

Note that by default the Google Colab runtime is CPU-only. To change to a GPU runtime, go to `Runtime > Change runtime type` and click on `T4 GPU`. Note that `T4 GPU` is considered pretty slow and is provided by Google Colab free of charge. To access the gold standard `A100 GPU` via Google Colab, a subscription is required.

For local use, if you do not have a GPU, you should expect a warning 
```
[KeOps] Warning : Cuda libraries were not detected on the system ; using cpu only mode
```
but the library is fully functional. 

## Paper examples

This library is accompanied by the paper  

- M. Buze, J. Feydy, S.M. Roper, K. Sedighiani, D.P. Bourne, Anisotropic power diagrams for polycrystal modelling: Efficient generation of curved grains via optimal transport, Computational Materials Science, Volume 245, 2024, [DOI](https://doi.org/10.1016/j.commatsci.2024.113317), [LINK](https://www.sciencedirect.com/science/article/pii/S092702562400538X).

The examples presented in the paper can be found in `/notebooks/paper_examples`, which includes all the Jupyter notebooks as they were run, the data that was generated and the plots from the paper. For the ease of access, here we list them with links to view them statically in NBViewer and also a link to an interactive version in Google Colab. Note that the notebooks relying the loading of data will not work out of the box in Google Colab -- the relevant data will have to be loaded manually. 
- Runtime tests
	1. APD generation
		- Gathering data   [![nbviewer](https://raw.githubusercontent.com/jupyter/design/master/logos/Badges/nbviewer_badge.svg)](https://nbviewer.org/github/mbuze/PyAPD/blob/main/notebooks/paper_examples/runtime_tests/apd_generation/gather_data_apd_gen.ipynb?flush_cache=true) [![Open In Colab](https://colab.research.google.com/assets/colab-badge.svg)](https://colab.research.google.com/github/mbuze/PyAPD/blob/main/notebooks/paper_examples/runtime_tests/apd_generation/gather_data_apd_gen.ipynb) 
		- Plotting the data for the 2D case [![nbviewer](https://raw.githubusercontent.com/jupyter/design/master/logos/Badges/nbviewer_badge.svg)](https://nbviewer.org/github/mbuze/PyAPD/blob/main/notebooks/paper_examples/runtime_tests/apd_generation/plot_data_apd_gen2D.ipynb?flush_cache=true) [![Open In Colab](https://colab.research.google.com/assets/colab-badge.svg)](https://colab.research.google.com/github/mbuze/PyAPD/blob/main/notebooks/paper_examples/runtime_tests/apd_generation/plot_data_apd_gen2D.ipynb) and for the 3D case [![nbviewer](https://raw.githubusercontent.com/jupyter/design/master/logos/Badges/nbviewer_badge.svg)](https://nbviewer.org/github/mbuze/PyAPD/blob/main/notebooks/paper_examples/runtime_tests/apd_generation/plot_data_apd_gen3D.ipynb?flush_cache=true) [![Open In Colab](https://colab.research.google.com/assets/colab-badge.svg)](https://colab.research.google.com/github/mbuze/PyAPD/blob/main/notebooks/paper_examples/runtime_tests/apd_generation/plot_data_apd_gen3D.ipynb)
	2. Finding optimal APDs
		- Gathering data [![nbviewer](https://raw.githubusercontent.com/jupyter/design/master/logos/Badges/nbviewer_badge.svg)](https://nbviewer.org/github/mbuze/PyAPD/blob/main/notebooks/paper_examples/runtime_tests/finding_optimal_apd/gather_optimal_apd.ipynb?flush_cache=true) [![Open In Colab](https://colab.research.google.com/assets/colab-badge.svg)](https://colab.research.google.com/github/mbuze/PyAPD/blob/main/notebooks/paper_examples/runtime_tests/finding_optimal_apd/gather_optimal_apd.ipynb)
		- Plotting the data for the 3D multi-phase case [![nbviewer](https://raw.githubusercontent.com/jupyter/design/master/logos/Badges/nbviewer_badge.svg)](https://nbviewer.org/github/mbuze/PyAPD/blob/main/notebooks/paper_examples/runtime_tests/finding_optimal_apd/plot_optimal_apd.ipynb?flush_cache=true) [![Open In Colab](https://colab.research.google.com/assets/colab-badge.svg)](https://colab.research.google.com/github/mbuze/PyAPD/blob/main/notebooks/paper_examples/runtime_tests/finding_optimal_apd/plot_optimal_apd.ipynb)
	3. EBSD data examples
		- Fitting to data and artificial sample generation [![nbviewer](https://raw.githubusercontent.com/jupyter/design/master/logos/Badges/nbviewer_badge.svg)](https://nbviewer.org/github/mbuze/PyAPD/blob/main/notebooks/paper_examples/ebsd_examples/fitting_and_artificial_apd/EBSD_examples1.ipynb?flush_cache=true) [![Open In Colab](https://colab.research.google.com/assets/colab-badge.svg)](https://colab.research.google.com/github/mbuze/PyAPD/blob/main/notebooks/paper_examples/ebsd_examples/fitting_and_artificial_apd/EBSD_examples1.ipynb)
		- Pixel level comparison [![nbviewer](https://raw.githubusercontent.com/jupyter/design/master/logos/Badges/nbviewer_badge.svg)](https://nbviewer.org/github/mbuze/PyAPD/blob/main/notebooks/paper_examples/ebsd_examples/pixel_level_comparison/EBSD_example_pixel_data.ipynb?flush_cache=true) [![Open In Colab](https://colab.research.google.com/assets/colab-badge.svg)](https://colab.research.google.com/github/mbuze/PyAPD/blob/main/notebooks/paper_examples/ebsd_examples/pixel_level_comparison/EBSD_example_pixel_data.ipynb)
	4. Additive manufacturing example [![nbviewer](https://raw.githubusercontent.com/jupyter/design/master/logos/Badges/nbviewer_badge.svg)](https://nbviewer.org/github/mbuze/PyAPD/blob/main/notebooks/paper_examples/AM_example/AM_example.ipynb?flush_cache=true) [![Open In Colab](https://colab.research.google.com/assets/colab-badge.svg)](https://colab.research.google.com/github/mbuze/PyAPD/blob/main/notebooks/paper_examples/AM_example/AM_example.ipynb)


## Citing this work

If you use `PyAPD` for academic research, you may cite the paper to which our library is tied as follows.
```
@article{PyAPD,
title = {Anisotropic power diagrams for polycrystal modelling: Efficient generation of curved grains via optimal transport},
journal = {Computational Materials Science},
volume = {245},
pages = {113317},
year = {2024},
issn = {0927-0256},
doi = {https://doi.org/10.1016/j.commatsci.2024.113317},
url = {https://www.sciencedirect.com/science/article/pii/S092702562400538X},
author = {M. Buze and J. Feydy and S.M. Roper and K. Sedighiani and D.P. Bourne},
keywords = {Anisotropic power diagrams, Polycrystalline materials, Microstructure generation, Optimal transport},
}
```

## Related projects

* [DREAM.3D](https://github.com/BlueQuartzSoftware/DREAM3D)
* [Kanapy](https://github.com/ICAMS/Kanapy)
* [Neper](https://github.com/neperfepx/neper)
* [LPM: Laguerre-Polycrystalline-Microstructures](https://github.com/DPBourne/Laguerre-Polycrystalline-Microstructures)