Jax implementation

[andrinr]

This pull request enables importing the library using

import powerbox.jax ...

Summary by Sourcery

Introduce JAX support for core functionalities.

New Features:

• Add a new powerbox.jax sub-package containing JAX implementations of PowerBox, LogNormalPowerBox, get_power, angular_average, and related tools.
• Enable importing the library using import powerbox.jax ...

Enhancements:

• Add a JAXFFT backend for FFT operations using jax.fft.

[sourcery-ai]

Reviewer's Guide by Sourcery

This pull request introduces a new sub-package powerbox.jax which provides a JAX-based implementation of the library's core functionalities, including FFT calculations, power spectrum analysis, and the generation of Gaussian and LogNormal fields. This allows users to leverage JAX for potentially faster or GPU-accelerated computations.

No diagrams generated as the changes look simple and do not need a visual representation.

File-Level Changes

Change	Details	Files
Implement a JAX backend for FFT operations.	Add a new class JAXFFT inheriting from FFTBackend. Implement fftn, ifftn, fftshift, ifftshift, fftfreq, and empty methods using jax.numpy.fft. Include a JAX import check within the JAXFFT constructor.	src/powerbox/dft_backend.py
Add JAX-compatible Discrete Fourier Transform (DFT) functions.	Create fft, ifft, fftfreq, fftshift, and ifftshift functions specifically for JAX. Implement arbitrary convention and normalization logic using JAX NumPy. Integrate with the new JAX FFT backend.	src/powerbox/jax/dft.py
Add JAX utility functions for power spectrum analysis and manipulation.	Implement angular averaging functions (angular_average, angular_average_nd) compatible with JAX. Include helper functions for binning, weighted averaging, and interpolation. Add functions for converting power units (power2delta) and weighting k-modes (ignore_zero_absk, ignore_zero_ki). Implement a function for discretizing particle data onto a grid (discretize_N). Provide the main get_power function for calculating the isotropic power spectrum using the JAX-based utilities.	src/powerbox/jax/tools.py
Implement JAX-based classes for generating fields with specified power spectra.	Create a PowerBox class for generating Gaussian random fields using JAX. Implement methods for generating k-space coefficients and real-space fields. Add a LogNormalPowerBox class inheriting from PowerBox to generate LogNormal fields. Override methods to apply the log-normal transformation while maintaining the desired power spectrum.	src/powerbox/jax/powerbox.py
Establish the powerbox.jax sub-package structure.	Add an __init__.py file to mark the directory as a Python package.	src/powerbox/jax/__init__.py

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[codecov]

Codecov Report

Attention: Patch coverage is 0.38023% with 524 lines in your changes missing coverage. Please review.

Project coverage is 49.00%. Comparing base (69c5cc1) to head (3f69aa0).

Files with missing lines	Patch %	Lines
src/powerbox/jax/tools.py	0.00%	308 Missing ⚠️
src/powerbox/jax/powerbox.py	0.00%	120 Missing ⚠️
src/powerbox/jax/dft.py	0.00%	82 Missing ⚠️
src/powerbox/dft_backend.py	14.28%	12 Missing ⚠️
src/powerbox/jax/__init__.py	0.00%	2 Missing ⚠️

Additional details and impacted files

@@             Coverage Diff             @@
##             main      #79       +/-   ##
===========================================
- Coverage   92.95%   49.00%   -43.95%     
===========================================
  Files           5        9        +4     
  Lines         582     1108      +526     
===========================================
+ Hits          541      543        +2     
- Misses         41      565      +524     

Flag	Coverage Δ
unittests	49.00% <0.38%> (-41.51%)	⬇️

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[steven-murray]

@andrinr have you had any time to work on this branch?

[andrinr]

Pretty short on time, but still in the back of my head 🗡️