spatialstats is a collection of correlation function routines used to analyze the multi-scale structure of 2D and 3D spatial fields and particle distributions. As of August 2022, this package will no longer be maintained.
Each routine aims to be independent from the rest of the package, so feel free to just pull out the routine that you need!
You can read the docs at https://spatialstats.readthedocs.io/.
If you have a routine that you think would fit in this package, please do reach out! I currently have no plans to implement specific routines--only ones that come up in my research.
Calculate two-point correlation multipoles using pair counting.
Compute power spectrum multipoles of scalar, vector, and tensor fields and particle data, and compute bispectra on 2D and 3D grids.
The following example demonstrates how to interact with the spatialstats configuration object to toggle gpu usage
import numpy as np
import spatialstats as ss
ss.config.gpu = True
shape = (100, 100)
data = np.random.rand(*shape)
result = ss.polyspectra.bispectrum(data)Clone from github and build by running
python setup.py installInstallation from PyPI has been discontinued.
spatialstats does not load any of its routines until the time of import (lazy loading), so the only installation requirements are numpy and scipy. This is to keep the flexibility of spatialstats as a package of disconnected routines. Users may need to add additional dependencies after installation, such as numba>=0.50, cupy>=8.0, and pyfftw, finufft, and sympy.