# kspace

`kspace` is a Python package for working with scalar and vector fields in 
1, 2, or 3 dimensions for use in physical models and simulations. It provides 
capabilities for generating, analyzing, and manipulating fields in both real 
and Fourier spaces, with a focus on Gaussian random fields (GRFs) and their 
power spectra. This approach is well-suited to producing synthetic turbulent 
velocity or magnetic fields with a prescribed power spectrum.

Core features:

- Generate scalar or vector GRF realizations from an arbitrary power
  spectrum ({class}`~kspace.GaussianRandomField`), including
  divergence-free vector fields.
- Built-in power spectrum models ({class}`~kspace.PowerLaw`,
  {class}`~kspace.PowerLawBetaModel`, {class}`~kspace.DoublePowerLaw`),
  or supply your own callable via {class}`~kspace.PowerSpectrum`.
- FFT-based analysis ({class}`~kspace.FourierAnalysis`): binned power
  spectra, divergence and curl of vector fields, windowing to reduce FFT
  boundary effects, and vector-potential/curl inversion. Works with fields 
  generated by `kspace` or any other gridded data, such as from hydrodynamic
  simulations.

```{toctree}
:maxdepth: 2
:hidden:

installation
quickstart
conventions
tutorials/index
api/index
```