Distances¶
The aeon.distances
module contains time series specific distance functions
that can be used in aeon and scikit learn estimators. It also contains tools for
extracting the alignment paths for a distance calculation between two series, and
tools for finding all pairwise distances
Amerced Dynamic Time Warping (ADTW)¶

Compute the ADTW distance between two time series. 

Compute the ADTW pairwise distance between a set of time series. 

Compute the ADTW cost matrix between two time series. 

Compute the ADTW alignment path between two time series. 
Derivative Dynamic Time Warping (DDTW)¶

Compute the DDTW distance between two time series. 

Compute the DDTW pairwise distance between a set of time series. 

Compute the DDTW cost matrix between two time series. 

Compute the DDTW alignment path between two time series. 
Dynamic Time Warping (DTW)¶

Compute the DTW distance between two time series. 

Compute the DTW pairwise distance between a set of time series. 

Compute the DTW cost matrix between two time series. 

Compute the DTW alignment path between two time series. 
Edit Real Penalty (ERP)¶

Compute the ERP distance between two time series. 

Compute the ERP pairwise distance between a set of time series. 

Compute the ERP cost matrix between two time series. 

Compute the ERP alignment path between two time series. 
Edit distance for real sequences (EDR)¶

Compute the EDR distance between two time series. 

Compute the pairwise EDR distance between a set of time series. 

Compute the EDR cost matrix between two time series. 

Compute the EDR alignment path between two time series. 
Euclidean¶

Compute the Euclidean distance between two time series. 

Compute the Euclidean pairwise distance between a set of time series. 
Longest Common Subsequence (LCSS)¶

Return the LCSS distance between x and y. 

Compute the LCSS pairwise distance between a set of time series. 

Return the LCSS cost matrix between x and y. 

Compute the LCSS alignment path between two time series. 
Manhattan¶

Compute the manhattan distance between two time series. 

Compute the manhattan pairwise distance between a set of time series. 
Minkowski¶

Compute the Minkowski distance between two time series. 

Compute the Minkowski pairwise distance between a set of time series. 
MoveSplitMerge (MSM)¶

Compute the MSM distance between two time series. 

Compute the msm pairwise distance between a set of time series. 

Compute the MSM cost matrix between two time series. 

Compute the msm alignment path between two time series. 
Shapebased Distance (SBD)¶

Compute the shapebased distance (SBD) between two time series. 

Compute the shapebased distance (SBD) between all pairs of time series. 
Shape Dynamic Time Warping (Shape DTW)¶

Compute the ShapeDTW distance function between two series x and y. 

Compute the ShapeDTW pairwise distance among a set of series. 

Compute the ShapeDTW cost matrix between two series x and y. 

Compute the ShapeDTW alignment path between two series x and y. 
Squared¶

Compute the squared distance between two time series. 

Compute the squared pairwise distance between a set of time series. 
Time Warp Edit (TWE)¶

Compute the TWE distance between two time series. 

Compute the TWE pairwise distance between a set of time series. 

Compute the TWE cost matrix between two time series. 

Compute the TWE alignment path between two time series. 
Weighted Derivative Dynamic Time Warping (WDDTW)¶

Compute the WDDTW distance between two time series. 

Compute the WDDTW pairwise distance between a set of time series. 

Compute the WDDTW cost matrix between two time series. 

Compute the WDDTW alignment path between two time series. 
Weighted Dynamic Time Warping (DTW)¶

Compute the WDTW distance between two time series. 

Compute the WDTW pairwise distance between a set of time series. 

Compute the WDTW cost matrix between two time series. 

Compute the WDTW alignment path between two time series. 
General methods with distance argument¶

Compute the distance between two time series. 

Compute the pairwise distance matrix between two time series. 

Compute the alignment path and distance between two time series. 

Compute the alignment path and distance between two time series. 

Create a bounding matrix for an elastic distance. 
General methods to recover distance functions¶

Get the distance function for a given metric string or callable. 

Get the pairwise distance function for a given metric string or callable. 
Get a list of distance function names in aeon. 


Get the cost matrix function for a given metric string or callable. 

Get the alignment path function for a given metric string or callable. 