TERSE/PROLIX (TRPX) – a new algorithm for fast and lossless compression and decompression of diffraction and cryo-EM data
Creators
- 1. Biozentrum, University of Basel
- 2. Biozentrum, University of Basel, Basel, Basel-Stadt, Switzerland, Laboratory of Nanoscale Biology, Paul Scherrer Institute, Villigen, Switzerland
Description
TERSE/PROLIX(TRPX) is an efficient compression and decompression algorithm for diffraction data.
TERSE/PROLIX(TRPX) allows efficient and fast compression of integral diffraction data and other integral grey scale data (cryo-EM) into a Terse object that can be decoded by the member function Terse::prolix(iterator). The prolix(iterator) member function decompresses the data starting at the location defined by 'iterator' (which can also be a pointer). A Terse object is constructed by supplying it with uncompressed data or a stream that contains TRPX data.
Files
senikm/trpx-v1.0.0.zip
Files
(3.2 MB)
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Additional details
Related works
- Is supplement to
- https://github.com/senikm/trpx/tree/v1.0.0 (URL)