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Source: libaec
Section: utils
Maintainer: Debian Science Maintainers <debian-science-maintainers@lists.alioth.debian.org>
Uploaders: Alastair McKinstry <mckinstry@debian.org>
Build-Depends: debhelper-compat (= 13),
unzip,
cmake
Rules-Requires-Root: no
Standards-Version: 4.7.3
Homepage: https://gitlab.dkrz.de/k202009/libaec
Vcs-Browser: https://salsa.debian.org/science-team/libaec
Vcs-Git: https://salsa.debian.org/science-team/libaec.git -b debian/latest
Package: libaec0
Section: libs
Architecture: any
Depends: ${misc:Depends}, ${shlibs:Depends}
Multi-Arch: same
Description: Adaptive Entropy Coding library
Libaec provides fast lossless compression of 1 up to 32 bit wide
signed or unsigned integers (samples). The library achieves best
results for low entropy data as often encountered in space imaging
instrument data or numerical model output from weather or climate
simulations. While floating point representations are not directly
supported, they can also be efficiently coded by grouping exponents
and mantissa.
.
Libaec implements Golomb Rice coding as defined in the Space Data
System Standard documents 121.0-B-2 [1] and 120.0-G-2[2].
Package: libsz2
Section: libs
Architecture: any
Depends: ${misc:Depends}, ${shlibs:Depends}
Multi-Arch: same
Description: Adaptive Entropy Coding library - SZIP
Libaec provides fast lossless compression of 1 up to 32 bit wide
signed or unsigned integers (samples).
Libaec implements Golomb Rice coding as defined in the Space Data
System Standard documents 121.0-B-2 [1] and 120.0-G-2[2].
.
This package provides a free drop-in replacement for the SZIP
compression library.
Package: libaec-dev
Section: libdevel
Architecture: any
Depends: ${misc:Depends}, libaec0 (= ${binary:Version}), libsz2 (= ${binary:Version})
Multi-Arch: same
Description: Development files for the Adaptive Entropy Coding library
Libaec provides fast lossless compression of 1 up to 32 bit wide
signed or unsigned integers (samples). The library achieves best
results for low entropy data as often encountered in space imaging
instrument data or numerical model output from weather or climate
simulations. While floating point representations are not directly
supported, they can also be efficiently coded by grouping exponents
and mantissa.
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