Abstract

seg1d is an open-source Python package for the automated segmentation of one-dimensional data using one or more reference segments. The segmentation process allows users to apply various methods and parameters for the process through weighted features (i.e., additional data attributed to the same set) in a rolling correlation size-varying window of a reference(s) to a target. Correlations can be averaged across the references and a peak detection algorithm finds the most prominent segments. Non-overlapping segments are identified and a clustering algorithm groups the most similar segments within the target. The package was developed for movement sciences but should be useful to anyone interested in extracting correlated subsequences from a dataset.