tslearn.preprocessing.TimeSeriesResampler

class tslearn.preprocessing.TimeSeriesResampler(sz)

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

Parameters:

sz : int

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(self, X[, y])	A dummy method such that it complies to the sklearn requirements.
fit_transform(self, X[, y])	Fit to data, then transform it.
transform(self, X[, y])	Fit to data, then transform it.

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

Fit to data, then transform it.

Parameters:

X : array-like of shape (n_ts, sz, d)

Time series dataset to be resampled.

Returns:

numpy.ndarray

Resampled time series dataset.

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

Fit to data, then transform it.

Parameters:

X : array-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