calculate_features      Compute features on an input time series
                        dataset
check_vector_quality    Check data quality of a vector
compute_top_features    Return an object containing results from
                        top-performing features on a classification
                        task
demo_multi_outputs      Computed values for multi-feature
                        classification results for use in vignette
demo_outputs            Computed values for top features results for
                        use in vignette
feature_list            All features available in theft in tidy format
fit_multi_feature_classifier
                        Fit a classifier to feature matrix using all
                        features or all features by set
fit_single_feature_classifier
                        Fit a classifier to feature matrix to extract
                        top performers
init_theft              Communicate to R the correct Python version
                        containing the relevant libraries for
                        calculating features
minmax_scaler           This function rescales a vector of numerical
                        values into the unit interval [0,1]
normalise_feature_frame
                        Scale each feature vector into a user-specified
                        range for visualisation and modelling
normalise_feature_vector
                        Scale each value into a user-specified range
                        for visualisation and analysis
normalize_feature_frame
                        Scale each feature vector into a user-specified
                        range for visualisation and modelling
normalize_feature_vector
                        Scale each value into a user-specified range
                        for visualisation and analysis
plot_all_features       Produce a heatmap matrix of the calculated
                        feature value vectors and each unique time
                        series with automatic hierarchical clustering.
plot_feature_correlations
                        Produce a correlation matrix plot showing
                        pairwise correlations of feature vectors by
                        unique id with automatic hierarchical
                        clustering.
plot_feature_matrix     Produce a heatmap matrix of the calculated
                        feature value vectors and each unique time
                        series with automatic hierarchical clustering.
plot_low_dimension      Produce a principal components analysis (PCA)
                        on normalised feature values and render a
                        bivariate plot to visualise it
plot_quality_matrix     Produce a matrix visualisation of data types
                        computed by feature calculation function.
plot_ts_correlations    Produce a correlation matrix plot showing
                        pairwise correlations of time series with
                        automatic hierarchical clustering
process_hctsa_file      Load in hctsa formatted MATLAB files of time
                        series data into a tidy format ready for
                        feature extraction
robustsigmoid_scaler    This function rescales a vector of numerical
                        values with an outlier-robust Sigmoidal
                        transformation
sigmoid_scaler          This function rescales a vector of numerical
                        values with a Sigmoidal transformation
simData                 Sample of randomly-generated time series to
                        produce function tests and vignettes
theft                   Tools for Handling Extraction of Features from
                        Time-series
zscore_scaler           This function rescales a vector of numerical
                        values into z-scores
