In this example, we consider a set of 20 periodic and 20 noisy periodic signals. We assigned the time series in HCTSA.mat
to groups (using TS_LabelGroups('raw',{'periodic','noisy'})
), then normalized the data matrix (TS_Normalize
), and then clustered it (TS_Cluster
). So now we have a clustered data matrix containing thousands of summaries of each time series, as well as pre-assigned group information as to which time series are periodic and which are noisy. When the time series have been assigned to groups, this can be accessed by switching on the 'colorGroups'
setting: