st_clustering is an open-source software package for spatial-temporal clustering:
- Built on top of
sklearn's clustering algorithms - Scales to memory using chuncking. See the
st_fit_frame_splitmethod
The easiest way to install st_clustering is by using pip :
pip install st_clustering
import st_clustering as stc
st_dbscan = stc.ST_DBSCAN(eps1 = 0.05, eps2 = 10, min_samples = 5)
st_dbscan.st_fit(data)- Demo Notebook: this Jupyter Notebook shows a demo of common features in this package.
A package that implements a straightforward extension for various clustering algorithms to accomodate spatio-temporal data. Available algorithms are:
- ST DBSCAN
- ST Agglomerative
- ST OPTICS
- ST Spectral Clustering
- ST Affinity Propagation
- ST HDBSCAN
For more details please see original paper:
Cakmak, E., Plank, M., Calovi, D. S., Jordan, A., & Keim, D. (2021). Spatio-temporal clustering benchmark for collective animal behavior. In 1st ACM SIGSPATIAL International Workshop on Animal Movement Ecology and Human Mobility (HANIMOB’21).
Released under MIT License. See the LICENSE file for details.