tslearn.preprocessing.TimeSeriesResampler

class tslearn.preprocessing.TimeSeriesResampler(sz)

Resampler for time series. Resample time series so that they reach the target size.

Parameters:

szint

Size of the output time series.

Examples

>>> TimeSeriesResampler(sz=5).fit_transform([[0, 3, 6]])
array([[[0. ],
        [1.5],
        [3. ],
        [4.5],
        [6. ]]])

Methods

fit(X[, y])	A dummy method such that it complies to the sklearn requirements.
fit_transform(X[, y])	Fit to data, then transform it.
set_output(*[, transform])	Set output container.
transform(X[, y])	Fit to data, then transform it.

fit(X, y=None, **kwargs)

A dummy method such that it complies to the sklearn requirements. Since this method is completely stateless, it just returns itself.

Parameters:

X

Ignored

Returns:

self

fit_transform(X, y=None, **kwargs)

Fit to data, then transform it.

Parameters:

Xarray-like of shape (n_ts, sz, d)

Time series dataset to be resampled.

Returns:

numpy.ndarray

Resampled time series dataset.

set_output(*, transform=None)

Set output container.

See Introducing the set_output API for an example on how to use the API.

Parameters:

transform{“default”, “pandas”}, default=None

Configure output of transform and fit_transform.

• “default”: Default output format of a transformer

• “pandas”: DataFrame output

• None: Transform configuration is unchanged

Returns:

selfestimator instance

Estimator instance.

transform(X, y=None, **kwargs)

Fit to data, then transform it.

Parameters:

Xarray-like of shape (n_ts, sz, d)

Time series dataset to be resampled.

Returns:

numpy.ndarray

Resampled time series dataset.

Examples using tslearn.preprocessing.TimeSeriesResampler

k-means

k-means