Index of changes in PAA and SAX

Is your feature request related to a problem? Please describe.
I'm running the tutorial of PAA and SAX in the doc

import numpy
import matplotlib.pyplot as plt

from tslearn.generators import random_walks
from tslearn.preprocessing import TimeSeriesScalerMeanVariance
from tslearn.piecewise import PiecewiseAggregateApproximation
from tslearn.piecewise import SymbolicAggregateApproximation, \
    OneD_SymbolicAggregateApproximation

numpy.random.seed(0)
# Generate a random walk time series
n_ts, sz, d = 1, 100, 1
dataset = random_walks(n_ts=n_ts, sz=sz, d=d)
scaler = TimeSeriesScalerMeanVariance(mu=0., std=1.)  # Rescale time series
dataset = scaler.fit_transform(dataset)

n_paa_segments = 10
paa = PiecewiseAggregateApproximation(n_segments=n_paa_segments)
paa_data = paa.fit_transform(dataset)
paa_dataset_inv = paa.inverse_transform(paa_data)

After reading the docs, it seems that there is no function to find the index when the paa_data changes occured.

Describe the solution you'd like
paa.get_index(paa_data) should return the index where the paa_data changes occured. That will be nice.

Start with the linked PAA and SAX tutorial and the PiecewiseAggregateApproximation API and implementation. Determine how the requested index should be represented for paa_data changes, then add get_index behavior and tests showing the expected indices for the tutorial data.