ZMAT: A portable C-library and MATLAB toolbox for zlib/gzip/lzma/lz4/lz4hc data compression
- Copyright (C) 2019,2020 Qianqian Fang <q.fang at neu.edu>
- License: GNU General Public License version 3 (GPL v3), see License*.txt
- Version: 0.9.8 (Archie-the-goat - beta)
- URL: http://github.com/fangq/zmat
Table of Contents
ZMat provides both an easy-to-use C-based data compression library - libzmat as well a portable mex function to enable zlib/gzip/lzma/lzip/lz4/lz4hc based data compression/decompression and base64 encoding/decoding support in MATLAB and GNU Octave. It is fast and compact, can process a large array within a fraction of a second.
Among the 6 supported compression methods, lz4 is the fastest for compression/decompression; lzma is the slowest but has the highest compression ratio; zlib/gzip have the best balance between speed and compression time.
The libzmat library, including the static library (libzmat.a) and the dynamic library libzmat.so or libzmat.dll, provides a simple interface to conveniently compress or decompress a memory buffer:
int zmat_run( const size_t inputsize, /* input buffer data length */ unsigned char *inputstr, /* input buffer */ size_t *outputsize, /* output buffer data length */ unsigned char **outputbuf, /* output buffer */ const int zipid, /* 0-zlib,1-gzip,2-base64,3-lzma,4-lzip,5-lz4,6-lz4hc */ int *status, /*return status for error handling*/ const int level /* 1 compress (default level); -1 to -9 compression level, 0 decompress */ );
The library is highly portable and can be directly embedded in the source code
to provide maximal portability. In the
test folder, we provided sample codes
zmat_run/zmat_encode/zmat_decode for stream-level compression and
decompression in C and Fortran90. The Fortran90 C-binding module can be found
The ZMat MATLAB function accepts 3 types of inputs: char-based strings, numerical arrays
or vectors, or logical arrays/vectors. Any other input format will
result in an error unless you typecast the input into
format. A multi-dimensional numerical array is accepeted, and the
original input's type/dimension info is stored in the 2nd output
"info". If one calls
zmat with both the encoded data (in byte vector)
"info" structure, zmat will first decode the binary data
and then restore the original input's type and size.
zlib - an open-source and widely used library for data
compression. On Linux/Mac OSX, you need to have libz.so or libz.dylib
installed in your system library path (defined by the environment
The pre-compiled mex binaries for MATLAB are stored inside the
private. Those precompiled for GNU Octave are
stored in the subfolder named
octave, with one operating system
If you do not want to compile zmat yourself, you can download the precompiled package by either clicking on the "Download ZIP" button on the above URL, or use the below git command:
git clone https://github.com/fangq/zmat.git
The installation of ZMat is no different from any other simple
MATLAB toolboxes. You only need to download/unzip the package
to a folder, and add the folder's path (that contains
"private" folder) to MATLAB's path list by using the
For Octave, one needs to copy the
zipmat.mat file inside the "
from the subfolder matching the OS into the "
If you want to add this path permanently, you need to type "
browse to the zmat root folder and add to the list, then click "Save".
Then, run "
rehash" in MATLAB, and type "
which zmat", if you see an
output, that means ZMat is installed for MATLAB/Octave.
If you use MATLAB in a shared environment such as a Linux server, the best way to add path is to type
mkdir ~/matlab/ nano ~/matlab/startup.m
addpath('/path/to/zmat') in this file, save and quit the editor.
MATLAB will execute this file every time it starts. For Octave, the file
you need to edit is
~/.octaverc , where "
~" is your home directory.
One can directly install zmat on Fedora Linux 29 or later via the below shell command
sudo dnf install octave-zmat
Similarly, the below command installs the
libzmat library for developing
software using this library:
sudo dnf install zmat zmat-devel zmat-static
The above command installs the dynamic library, C/Fortran90 header files and static library, respectively
Similarly, if one uses Debian ("unstable"), the command to install zmat toolbox for Octave (and optionally for MATLAB) is
sudo apt-get install octave-zmat matlab-zmat
and that for installing the development environment is
sudo apt-get install libzmat1 libzmat1-dev
A Ubuntu (16.04/18.04) user can use the same commands as Debian to install these packages but one must first run
sudo add-apt-repository ppa:fangq/ppa sudo apt-get update
to enable the relevant PPA (personal package achieve) first.
ZMat provides a single mex function,
zipmat.mex* -- for both compressing/encoding
or decompresing/decoding data streams. The help info of the function is shown
output=zmat(input) or [output, info]=zmat(input, iscompress, method) output=zmat(input, info) A portable data compression/decompression toolbox for MATLAB/GNU Octave author: Qianqian Fang <q.fang at neu.edu> initial version created on 04/30/2019 input: input: a char, non-complex numeric or logical vector or array iscompress: (optional) if iscompress is 1, zmat compresses/encodes the input, if 0, it decompresses/decodes the input. Default value is 1. if iscompress is set to a negative integer, (-iscompress) specifies the compression level. For zlib/gzip, default level is 6 (1-9); for lzma/lzip, default level is 5 (1-9); for lz4hc, default level is 8 (1-16). the default compression level is used if iscompress is set to 1. zmat removes the trailing newline when iscompress=2 and methpod='base64' all newlines are removed when iscompress=3 and methpod='base64' if one defines iscompress as the info struct (2nd output of zmat), zmat will perform a decoding/decompression operation and recover the original input using the info stored in the info structure. method: (optional) compression method, currently, zmat supports the below methods 'zlib': zlib/zip based data compression (default) 'gzip': gzip formatted data compression 'lzip': lzip formatted data compression 'lzma': lzma formatted data compression 'lz4': lz4 formatted data compression 'lz4hc':lz4hc (LZ4 with high-compression ratio) formatted data compression 'base64': encode or decode use base64 format output: output: a uint8 row vector, storing the compressed or decompressed data; empty when an error is encountered info: (optional) a struct storing additional info regarding the input data, may have 'type': the class of the input array 'size': the dimensions of the input array 'byte': the number of bytes per element in the input array 'method': a copy of the 3rd input indicating the encoding method 'status': the zlib/lzma/lz4 compression/decompression function return value, including potential error codes; see documentation of the respective libraries for details 'level': a copy of the iscompress flag; if non-zero, specifying compression level, see above example: [ss, info]=zmat(eye(5)) orig=zmat(ss,0) orig=zmat(ss,info) ss=char(zmat('zmat test',1,'base64')) orig=char(zmat(ss,0,'base64')) -- this function is part of the zmat toolbox (http://github.com/fangq/zmat)
"example" folder, you can find a demo script showing the
basic utilities of ZMat. Running the
you can see how to compress/decompress a simple array, as well as apply
base64 encoding/decoding to strings.
Please run these examples and understand how ZMat works before you use it to process your data.
To recompile ZMat, you first need to check out ZMat source code, along with the needed submodules from the Github repository using the below command
git clone https://github.com/fangq/zmat.git zmat
Next, you need to make sure your system has
mkoctfile (if compiling for Octave is needed). If not,
please install gcc, MATLAB and GNU Octave and add the paths to
these utilities to the system PATH environment variable.
To compile zmat, you may choose one of the three methods:
- Method 1: please open MATLAB or Octave, and run the below commands
cd zmat/src compilezmat
The above script utilizes the MinGW-w64 MATLAB Compiler plugin.
To install the MinGW-w64 compiler plugin for MATLAB, please follow the below steps
If you have MATLAB R2017b or later, you may skip this step. To compile mcxlabcl in MATLAB R2017a or earlier on Windows, you must pre-install the MATLAB support for MinGW-w64 compiler https://www.mathworks.com/matlabcentral/fileexchange/52848-matlab-support-for-mingw-w64-c-c-compiler
Note: it appears that installing the above Add On is no longer working and may give an error at the download stage. In this case, you should install MSYS2 from https://www.msys2.org/. Once you install MSYS2, run MSYS2.0 MinGW 64bit from Start menu, in the popup terminal window, type
pacman -Syu pacman -S base-devel gcc git zlib-devel
Then, start MATLAB, and in the command window, run
- After installation of MATLAB MinGW support, you must type
mex -setup Cin MATLAB and select "MinGW64 Compiler (C)".
- Once you select the MingW C compiler, you should run
mex -setup C++again in MATLAB and select "MinGW64 Compiler (C++)" to compile C++.
- Method 2: Compile with cmake (3.3 or later)
Please open a terminal, and run the below shall commands
cd zmat/src rm -rf build mkdir build && cd build cmake ../ make clean make
if MATLAB was not installed in a standard path, you may change
cmake ../ to
cmake Matlab_ROOT_DIR=/path/to/matlab/root ../
by default, this will first compile
libzmat.a and then create the
that is statically linked with
libzmat.a. If one prefers to create a dynamic
libzmat.so and then a dynamically linked
.mex file, this can
be done by
cmake Matlab_ROOT_DIR=/path/to/matlab/root -DSTATIC_LIB=off ../
- Method 3: please open a terminal, and run the below shall commands
cd zmat/src make clean mex
to create the mex file for MATLAB, and run
make clean oct to compile
the mex file for Octave.
The compilex mex files are named as
zipmat.mex* under the zmat root folder.
One may move those into the
private folder to overwrite the existing files,
or leave them in the root folder. MATLAB/Octave will use these files when
zmat is called.
ZMat is an open-source project. This means you can not only use it and modify it as you wish, but also you can contribute your changes back to JSONLab so that everyone else can enjoy the improvement. For anyone who want to contribute, please download JSONLab source code from its source code repositories by using the following command:
git clone https://github.com/fangq/zmat.git zmat
or browsing the github site at
You can make changes to the files as needed. Once you are satisfied with your changes, and ready to share it with others, please submit your changes as a "pull request" on github. The project maintainer, Dr. Qianqian Fang will review the changes and choose to accept the patch.
We appreciate any suggestions and feedbacks from you. Please use the iso2mesh mailing list to report any questions you may have regarding ZMat:
(Subscription to the mailing list is needed in order to post messages).
ZMat is linked against 4 open-source data compression libraries
- ZLib library: https://www.zlib.net/
- Copyright (C) 1995-2017 Jean-loup Gailly and Mark Adler
- License: Zlib license
- Eazylzma: https://github.com/lloyd/easylzma
- Author: Lloyd Hilaiel (lloyd)
- License: public domain
- Original LZMA library:
- Author: Igor Pavlov
- License: public domain
- LZ4 library: https://lz4.github.io/lz4/
- Copyright (C) 2011-2019, Yann Collet.
- License: BSD 2-Clause License (http://www.opensource.org/licenses/bsd-license.php)