# Is there any good practice to cluster 3D data array?

So I'm not sure what word fits best to describe this data, probably "dimension" would be wrong since it may be used for flat samples with 3 features;

but by 3D data I mean some structure in a form of [samples, timesteps, features]. And there are 2 features in each timestamp.

It looks like [ [ [1,2], [3,4] ], [ [5,6], [7,8] ] ], like an LSTM input. [1,2] is a timestep and [[1,2],[3,4]] is a sample.

So one way is to just flatten out timesteps and make them into a 1D array. However is there any better way that would somehow utilize the information conducted by "grouping" of features inside a timestamp?

Also how do I properly describe this data structure?