Installation¶

Requirements¶

Python ≥ 3.12, < 3.14
JAX (CPU or GPU/TPU backend)

Install from GitHub¶

The simplest way to install SpectralDiffX:

pip install git+https://github.com/jejjohnson/spectraldiffx

Development Setup¶

We use uv for dependency management.

Clone and install¶

git clone https://github.com/jejjohnson/spectraldiffx.git
cd spectraldiffx
uv sync --group dev

Install with all optional dependencies¶

To install the full suite including tests, docs, and example scripts:

uv sync --all-extras

Optional Dependencies¶

Extra	Contents
`test`	`pytest`, `pytest-cov`
`docs`	`mkdocs-material`, `mkdocstrings`, `mkdocs-jupyter`
`examples`	`diffrax`, `cyclopts`, `xarray`, `matplotlib`, `tqdm`

Install a specific extra:

pip install "spectraldiffx[examples] @ git+https://github.com/jejjohnson/spectraldiffx"

Verify Installation¶

import jax
import jax.numpy as jnp
from spectraldiffx import FourierGrid1D, SpectralDerivative1D

jax.config.update("jax_enable_x64", True)

grid = FourierGrid1D.from_N_L(N=64, L=2 * jnp.pi)
deriv = SpectralDerivative1D(grid=grid)

u = jnp.sin(grid.x)
du_dx = deriv(u, order=1)

error = jnp.max(jnp.abs(du_dx - jnp.cos(grid.x)))
print(f"Max error: {error:.2e}")  # should be < 1e-12