for i, y in enumerate(numpy.unique(y_train)):
for k, ts in enumerate(X_train[y_train == y]):
fig_ax3.plot(ts.flatten(), c=viridis(i / 3), alpha=0.25)
fig_ax3.set_title("Input time series")
// Create a scatter plot of the 2D distances for the time series of each class.
for i, y in enumerate(numpy.unique(y_train)):
fig_ax4.scatter(distances[y_train == y][:, 0],
After Change
fig_ax2.set_title("Shapelet $\mathbf{s}_2$")
// Create the time series of each class
for i, subfig in enumerate([fig_ax3a, fig_ax3b, fig_ax3c, fig_ax3d]):
for k, ts in enumerate(X_train[y_train == i + 1]):
subfig.plot(ts.flatten(), c=viridis(i / 3), alpha=0.25)
fig.text(x=.15, y=.02, s="Input time series", fontsize=12)
