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https://github.com/sophiaas/bispectrum

Efficient implementation of the 2D translation-invariant bispectrum in PyTorch
https://github.com/sophiaas/bispectrum

bispectrum harmonic-analysis pytorch

Last synced: 26 days ago
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Efficient implementation of the 2D translation-invariant bispectrum in PyTorch

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# Bispectrum

This repository provides simple implementations and demos of the 2-dimensional translation-invariant bispectrum

## Installation

To install the requirements and package, run:

```
pip install -r requirements.txt
python setup.py install
```

## Dataset

To download the dataset used in the demo, run:

```
wget --load-cookies /tmp/cookies.txt "https://docs.google.com/uc?export=download&confirm=$(wget --quiet --save-cookies /tmp/cookies.txt --keep-session-cookies --no-check-certificate 'https://docs.google.com/uc?export=download&id=1tTj_bJ9nnc2ZfGB3cGZ_I3A5wqWK3aaD' -O- | sed -rn 's/.*confirm=([0-9A-Za-z_]+).*/\1\n/p')&id=1tTj_bJ9nnc2ZfGB3cGZ_I3A5wqWK3aaD" -O van-hateren.zip
rm -rf /tmp/cookies.txt
unzip van-hateren.zip
rm -r van-hateren.zip
mkdir datasets
mv van-hateren datasets
```

If your machine doesn't have wget, follow these steps:
1. Download the zip file [here](https://drive.google.com/file/d/1tTj_bJ9nnc2ZfGB3cGZ_I3A5wqWK3aaD/view?usp=sharing).
2. Place the file in the top node of this directory, i.e. in `bispectral-networks/`.
3. Run:
```
unzip van-hateren.zip
rm -r van-hateren.zip
mkdir datasets
mv van-hateren datasets
```

## Demo

To view a simple demo, open the notebook at:

```
demo.ipynb
```

## License

This repository is licensed under the MIT License.