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The compression method starts by linearizing multi-dimensional snapshot data. The key idea is to fit/predict the successive data points with the bestfit selection of curve fitting models. The data that can be predicted precisely will be replaced by the code of the corresponding curve-fitting model. As for the unpredictable data that cannot be approximated by curve-fitting models, we perform an optimized inoptimized lossy compression via a binary representation analysis.

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4. Detailed usage and examples can be found in under the directories doc/user-guide.pdf and example/ respectively, in the package. 

5. Version history: We recommend the latest version SZ 0.5.10 (a.k.a., SZh)

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