TS_FeatureSummaryfunction. The function takes in an operation ID as its input (and can also take inputs specifying a custom data source, or custom annotation parameters), and produces a distribution of outputs from that operation across the dataset, with the ability to then annotate time series onto that plot.
HCTSA.matas a violin plot, with ten 500-point time series subsegments annotated at different points through the distribution, shown to the right of the plot:
TS_FeatureSummarywill plot the distribution for each class separately, as well as an overall distribution. Annotated points can then be added to each class-specific distributions. In the example shown below, we can see that the 'noisy' class (red) has low values for this feature (
CO_tc3_2_denom), whereas the 'periodic' class mostly has high values.
TS_SingleFeatureprovides a simpler way of seeing the class distributions without annotations, as either kernel-smoothed distributions, as in
TS_FeatureSummary, or as violin plots. See below for example implementations: