The C++20 compression/decompression code, custom TIFF library and an ImageJ/Fiji Java plugin for reading TRPX files are open-sourced on GitHub under the permissive MIT license. ![]() By providing a tailored solution for diffraction and raw cryo-EM data, TRPX facilitates more efficient data analysis and interpretation while mitigating storage and transmission concerns. It can therefore be readily implemented in hardware. TRPX files are byte-order independent and upon compilation the algorithm occupies very little memory. It was 60 times faster than bzip2 (which achieved a similar compression rate), and more than 3 times faster than LZ4, which was the runner-up in terms of speed, but had a much worse compression rate. The results show that TRPX significantly outperforms all these algorithms in terms of speed and compression rate. The algorithm is compared with established lossless compression algorithms implemented in gzip, bzip2, CBF (crystallographic binary file), Zstandard(zstd), LZ4 and HDF5 with gzip, LZF and bitshuffle+LZ4 filters, in terms of compression efficiency and speed, using continuous-rotation electron diffraction data of an inorganic compound and raw cryo-EM data. HDF5Vibez.jar (version ) cisd-jhdf5-batteriesincludedlinwinmac. For ImageJ: Download the plugin and the jhdf5 library and put both files into the plugin-folder of your ImageJ installation. Here, TERSE/PROLIX (or TRPX for short) is presented, a novel lossless compression algorithm specifically designed for diffraction data. Or Fiji Linux, Mac OS X, or Windows, 32bit or 64bit Download and Install.
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