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jaxwavelets

Official

Compute differentiable wavelet transforms in JAX.

Software Engineering#jax#gpu#jit#cwt#differentiable#wavelet transform#dwt
Authorhandley-lab
Version1.0.0
Installs0

System Documentation

What problem does it solve?

This Skill helps you compute discrete, stationary, and continuous wavelet transforms inside JAX so you can differentiate through them, JIT-compile them, and run them efficiently on CPU/GPU.

Core Features & Use Cases

  • Discrete wavelet transforms (DWT): compute 1D natively (and extend to nD and 2D) with matching reconstruction via inverse transforms.
  • Stationary wavelet transforms (SWT): perform shift-invariant (undecimated) decompositions and reconstruct the original signal.
  • Continuous wavelet transforms (CWT): use a two-phase workflow (prepare then apply) to keep the core transform JIT-friendly.
  • Multiresolution analysis and wavelet packets: build interpretable multi-scale components and alternative decompositions.
  • Thresholding utilities: apply soft/hard/garrote/firm thresholding to wavelet coefficients.
  • JAX-first design: outputs are JAX pytrees for composition with jax.vmap, jax.jit, and jax.grad.

Quick Start

Use the jaxwavelets Skill to compute a 2D wavelet decomposition for a JAX array x with wavelet 'db4' at level 3.

Dependency Matrix

Required Modules

None required

Components

Standard package

💻 Claude Code Installation

Recommended: Let Claude install automatically. Simply copy and paste the text below to Claude Code.

Please help me install this Skill:
Name: jaxwavelets
Download link: https://github.com/handley-lab/jaxwavelets/archive/main.zip#jaxwavelets

Please download this .zip file, extract it, and install it in the .claude/skills/ directory.
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