TS_FeatureSummary
function. 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.mat
as 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_LabelGroups
as: TS_LabelGroups({'seizure','eyesOpen','eyesClosed'},'raw');
), TS_FeatureSummary
will 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_SingleFeature
provides 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: