# gtda.time_series: Time series¶

The module gtda.time_series implements transformers to preprocess time series or embed them in a higher dimensional space for persistent homology.

## Preprocessing¶

 time_series.SlidingWindow([size, stride]) Sliding windows onto the data. time_series.Resampler([period]) Time series resampling at regular intervals. time_series.Stationarizer([operation]) Methods for stationarizing time series data.

## Time-delay embedding¶

 time_series.TakensEmbedding([time_delay, …]) Point clouds from collections of time series via independent Takens embeddings. Representation of a single univariate time series as a point cloud.
 Compute the “optimal” parameters for a Takens (time-delay) embedding [1]_ of a univariate time series.

## Target preparation¶

 time_series.Labeller([size, func, …]) Target creation from sliding windows over a univariate time series.

## Dynamical systems¶

 time_series.PermutationEntropy([n_jobs]) Entropies from sets of permutations arg-sorting rows in arrays.

## Multivariate¶

 Pearson dissimilarities from collections of multivariate time series.