arXiv:1508.03817physics.data-an
Visualizing long vectors of measurements by use of the Hilbert curve
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Abstract
The use of Hilbert curves to visualize massive vector of data is revisited following previous authors. The Hilbert curve mapping preserves locality and makes meaningful representation of the data. We call such visualization as Hilbert plots. The combination of a Hilbert plot with its Fourier transform allows to identify patterns in the underlying data sequence. The use of different granularity representation also allows to identify periodic intervals within the data. Data from different sources are presented: periodic, aperiodic, logistic map and 1/2-Ising model. A real data example from the study of heartbeat data is also discussed.
Building more understanding of file formats into binvis is perpetually on my todo list. This would let you interpret different segments of files differently, and correctly interpret instructions and other higher-level structures. It would also help with things like entropy…
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