The tslearn.barycenters module gathers algorithms for time series barycenter computation.

A barycenter (or Fréchet mean) is a time series \(b\) which minimizes the sum of squared distances to the time series of a given data set \(x\):

\[\min \sum_i d( b, x_i )^2\]

Only the methods dtw_barycenter_averaging() and softdtw_barycenter() can operate on variable-length time-series (see here).

See the barycenter examples for an overview.


euclidean_barycenter(X[, weights])

Standard Euclidean barycenter computed from a set of time series.

dtw_barycenter_averaging(X[, ...])

DTW Barycenter Averaging (DBA) method estimated through Expectation-Maximization algorithm.

dtw_barycenter_averaging_subgradient(X[, ...])

DTW Barycenter Averaging (DBA) method estimated through subgradient descent algorithm.

softdtw_barycenter(X[, gamma, weights, ...])

Compute barycenter (time series averaging) under the soft-DTW [1] geometry.