pywph 1.0.1

Wavelet Phase Harmonics in Python with GPU acceleration.

PyWPH : Wavelet Phase Harmonics in Python

PyWPH is a Python package designed for the computation and handling of the Wavelet Phase Harmonics (WPH) statistics. These statistics can be computed from real or complex images (2D data). Calculations are GPU accelerated using PyTorch/CUDA (torch>=1.9.0).

Install PyWPH and check out the examples/ folder. You will find elementary examples to compute WPH coefficients from an image, as well as more convoluted synthesis or denoising scripts.

This code is a rework and extension of https://github.com/Ttantto/wph_quijote.

If you use this package, please cite the following paper:

• Regaldo-Saint Blancard, B., Allys, E., Boulanger, F., Levrier, F., & Jeffrey, N. (2021). A new approach for the statistical denoising of Planck interstellar dust polarization data. arXiv:2102.03160

Related references:

• Mallat, S., Zhang, S., & Rochette, G. (2020). Phase harmonic correlations and convolutional neural networks. Information and Inference: A Journal of the IMA, 9(3), 721–747. https://doi.org/10.1093/imaiai/iaz019 arXiv:1810.12136
• Allys, E., Marchand, T., Cardoso, J.-F., Villaescusa-Navarro, F., Ho, S., & Mallat, S. (2020). New Interpretable Statistics for Large Scale Structure Analysis and Generation. Physical Review D, 102(10), 103506. arXiv:2006.06298
• Zhang, S., & Mallat, S. (2021). Maximum Entropy Models from Phase Harmonic Covariances. Applied and Computational Harmonic Analysis, 53, 199–230. https://doi.org/10.1016/j.acha.2021.01.003 arXiv:1911.10017

Install/Uninstall

Standard installation (from the Python Package Index)

pip install pywph

Install from source

Clone the repository and type from the main directory:

pip install -r requirements.txt
pip install .

Uninstall

pip uninstall pywph

Changelog