This example shows three methods to compute barycenters of time series.

# Author: Romain Tavenard
# License: BSD 3 clause

import numpy
import matplotlib.pyplot as plt

from tslearn.barycenters import euclidean_barycenter, dtw_barycenter_averaging, softdtw_barycenter
from tslearn.datasets import CachedDatasets

X_train, y_train, X_test, y_test = CachedDatasets().load_dataset("Trace")
X = X_train[y_train == 2]

plt.subplot(3, 1, 1)
for ts in X:
    plt.plot(ts.ravel(), "k-", alpha=.2)
plt.plot(euclidean_barycenter(X).ravel(), "r-", linewidth=2)
plt.title("Euclidean barycenter")

plt.subplot(3, 1, 2)
dba_bar = dtw_barycenter_averaging(X, max_iter=100, verbose=False)
for ts in X:
    plt.plot(ts.ravel(), "k-", alpha=.2)
plt.plot(dba_bar.ravel(), "r-", linewidth=2)

plt.subplot(3, 1, 3)
sdtw_bar = softdtw_barycenter(X, gamma=1., max_iter=100)
for ts in X:
    plt.plot(ts.ravel(), "k-", alpha=.2)
plt.plot(sdtw_bar.ravel(), "r-", linewidth=2)
plt.title("Soft-DTW barycenter ($\gamma$=1.)")


Total running time of the script: ( 0 minutes 50.201 seconds)

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