===============================================================================
= JSONLab =
= An open-source MATLAB/Octave JSON encoder and decoder =
===============================================================================
*Copyright (C) 2011-2019 Qianqian Fang <q.fang at neu.edu>
*License: BSD, License_BSD.txt for details
*Version: 1.9 (Magnus - alpha)
-------------------------------------------------------------------------------
Table of Content:
0. What's New
I. Introduction
II. Installation
III.Using JSONLab
IV. Known Issues and TODOs
V. Contribution and feedback
V. Acknowledgement
-------------------------------------------------------------------------------
0. What's New
JSONLab v1.9 is the alpha release of the next milestone - code named "Magnus".
Notable changes are summarized below, key features marked by *:
2019-05-06 [25ad795] unescape string in loadjson.m
2019-05-04 [2e317c9] explain extra compression fields
2019-05-02 [1b1be65] avoid side effect of removing singletarray
2019-05-02*[8360fd1] support zmat based base64 encoding and decoding
2019-05-01*[c797bb2] integrating zmat, for zlib/gzip data compression
2019-04-29 [70551fe] remove warnings from matlab
2019-04-28 [0d61c4b] complete data compression support, close #52
2019-04-27 [804115b] avoid typecast error
2019-04-27 [c166aa7] change default compressarraysize to 100
2019-04-27*[3322f6f] major new feature: support array compression and decompression
2019-03-13*[9c01046] support saving function handles, close #51
2019-03-13 [a8fde38] add option to parse string array or convert to char, close #50
2019-03-12 [ed2645e] treat string array as cell array in newer matlab
2018-11-18 [c3eb021] allow saving uint64 integers in saveubjson, fix #49
The biggest change in this release, compared to v1.8 released in July 2018,
is the support of data compression via the 'Compression' option for both
savejson and saveubjson. Two compression methods are currently supported -
"zlib" and "gzip". The compression interfaces, zlibencode/zlibdecode/gzipencode/
gzipdecode are modified from the "Byte Encoding Utilities" by Kota Yamaguchi [1],
which has built-in support for java-based compression in MATLAB (when jvm is
enabled). To support Octave, as well as MATLAB in "nojvm" mode, a mex-based
data compression/encoding toolbox, ZMat [2], written by Qianqian Fang, takes priority
over the java-based utilities, if installed. For savejson, a 'base64' encoding is
applied to convert the compressed binary stream into a string; 'base64' encoding
is not used in saveubjson. The encoding and restoration of the binary matlab arrays
are automatically handled in save*json/load*json round-trip conversions.
To save matlab data with compression, one simply append 'Compression', 'method' pair
in the savejson/saveubjson call. For example
jsonstr=savejson('',mydata,'compression','zlib');
data=loadjson(jsonstr);
In addition, the below features are added to JSONLab
* save function handles
* support saving "string" class in MATLAB
* fix two bugs in saveubjson
* unescape strings in loadjson
* [1] https://www.mathworks.com/matlabcentral/fileexchange/39526-byte-encoding-utilities
* [2] http://github.com/fangq/zmat
-------------------------------------------------------------------------------
I. Introduction
JSONLab is a free and open-source implementation of a JSON/UBJSON encoder
and a decoder in the native MATLAB language. It can be used to convert a MATLAB
data structure (array, struct, cell, struct array and cell array) into
JSON/UBJSON formatted strings, or to decode a JSON/UBJSON file into MATLAB
data structure. JSONLab supports both MATLAB and
[http://www.gnu.org/software/octave/ GNU Octave] (a free MATLAB clone).
JSON ([http://www.json.org/ JavaScript Object Notation]) is a highly portable,
human-readable and "[http://en.wikipedia.org/wiki/JSON fat-free]" text format
to represent complex and hierarchical data. It is as powerful as
[http://en.wikipedia.org/wiki/XML XML], but less verbose. JSON format is widely
used for data-exchange in applications, and is essential for the wild success
of [http://en.wikipedia.org/wiki/Ajax_(programming) Ajax] and
[http://en.wikipedia.org/wiki/Web_2.0 Web2.0].
UBJSON ([<http://ubjson.org/ Universal Binary JSON]) is a binary JSON format, specifically
optimized for compact file size and better performance while keeping
the semantics as simple as the text-based JSON format. Using the UBJSON
format allows to wrap complex binary data in a flexible and extensible
structure, making it possible to process complex and large dataset
without accuracy loss due to text conversions.
We envision that both JSON and its binary version will serve as part of
the mainstream data-exchange formats for scientific research in the future.
It will provide the flexibility and generality achieved by other popular
general-purpose file specifications, such as
[http://www.hdfgroup.org/HDF5/whatishdf5.html HDF5], with significantly
reduced complexity and enhanced performance.
-------------------------------------------------------------------------------
II. Installation
The installation of JSONLab is no different than any other simple
MATLAB toolbox. You only need to download/unzip the JSONLab package
to a folder, and add the folder's path to MATLAB/Octave's path list
by using the following command:
addpath('/path/to/jsonlab');
If you want to add this path permanently, you need to type "pathtool",
browse to the zmat root folder and add to the list, then click "Save".
Then, run "rehash" in MATLAB, and type "which savejson", if you see an
output, that means JSONLab 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
and type addpath('/path/to/jsonlab') 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.
-------------------------------------------------------------------------------
III.Using JSONLab
JSONLab provides two functions, loadjson.m -- a MATLAB->JSON decoder,
and savejson.m -- a MATLAB->JSON encoder, for the text-based JSON, and
two equivallent functions -- loadubjson and saveubjson for the binary
JSON. The detailed help info for the four functions can be found below:
=== loadjson.m ===
<pre>
data=loadjson(fname,opt)
or
data=loadjson(fname,'param1',value1,'param2',value2,...)
parse a JSON (JavaScript Object Notation) file or string
authors:Qianqian Fang (q.fang <at> neu.edu)
created on 2011/09/09, including previous works from
Nedialko Krouchev: http://www.mathworks.com/matlabcentral/fileexchange/25713
created on 2009/11/02
François Glineur: http://www.mathworks.com/matlabcentral/fileexchange/23393
created on 2009/03/22
Joel Feenstra:
http://www.mathworks.com/matlabcentral/fileexchange/20565
created on 2008/07/03
$Id$
input:
fname: input file name, if fname contains "{}" or "[]", fname
will be interpreted as a JSON string
opt: a struct to store parsing options, opt can be replaced by
a list of ('param',value) pairs - the param string is equivallent
to a field in opt. opt can have the following
fields (first in [.|.] is the default)
opt.SimplifyCell [0|1]: if set to 1, loadjson will call cell2mat
for each element of the JSON data, and group
arrays based on the cell2mat rules.
opt.FastArrayParser [1|0 or integer]: if set to 1, use a
speed-optimized array parser when loading an
array object. The fast array parser may
collapse block arrays into a single large
array similar to rules defined in cell2mat; 0 to
use a legacy parser; if set to a larger-than-1
value, this option will specify the minimum
dimension to enable the fast array parser. For
example, if the input is a 3D array, setting
FastArrayParser to 1 will return a 3D array;
setting to 2 will return a cell array of 2D
arrays; setting to 3 will return to a 2D cell
array of 1D vectors; setting to 4 will return a
3D cell array.
opt.ShowProgress [0|1]: if set to 1, loadjson displays a progress bar.
opt.ParseStringArray [0|1]: if set to 1, loadjson displays a progress bar.
output:
dat: a cell array, where {...} blocks are converted into cell arrays,
and [...] are converted to arrays
examples:
dat=loadjson('{"obj":{"string":"value","array":[1,2,3]}}')
dat=loadjson(['examples' filesep 'example1.json'])
dat=loadjson(['examples' filesep 'example1.json'],'SimplifyCell',1)
license:
BSD, see LICENSE_BSD.txt file for details
</pre>
=== savejson.m ===
<pre>
json=savejson(rootname,obj,filename)
or
json=savejson(rootname,obj,opt)
json=savejson(rootname,obj,'param1',value1,'param2',value2,...)
convert a MATLAB object (cell, struct or array) into a JSON (JavaScript
Object Notation) string
author: Qianqian Fang (q.fang <at> neu.edu)
created on 2011/09/09
$Id$
input:
rootname: the name of the root-object, when set to '', the root name
is ignored, however, when opt.ForceRootName is set to 1 (see below),
the MATLAB variable name will be used as the root name.
obj: a MATLAB object (array, cell, cell array, struct, struct array,
class instance).
filename: a string for the file name to save the output JSON data.
opt: a struct for additional options, ignore to use default values.
opt can have the following fields (first in [.|.] is the default)
opt.FileName [''|string]: a file name to save the output JSON data
opt.FloatFormat ['%.10g'|string]: format to show each numeric element
of a 1D/2D array;
opt.ArrayIndent [1|0]: if 1, output explicit data array with
precedent indentation; if 0, no indentation
opt.ArrayToStruct[0|1]: when set to 0, savejson outputs 1D/2D
array in JSON array format; if sets to 1, an
array will be shown as a struct with fields
"_ArrayType_", "_ArraySize_" and "_ArrayData_"; for
sparse arrays, the non-zero elements will be
saved to _ArrayData_ field in triplet-format i.e.
(ix,iy,val) and "_ArrayIsSparse_" will be added
with a value of 1; for a complex array, the
_ArrayData_ array will include two columns
(4 for sparse) to record the real and imaginary
parts, and also "_ArrayIsComplex_":1 is added.
opt.ParseLogical [0|1]: if this is set to 1, logical array elem
will use true/false rather than 1/0.
opt.SingletArray [0|1]: if this is set to 1, arrays with a single
numerical element will be shown without a square
bracket, unless it is the root object; if 0, square
brackets are forced for any numerical arrays.
opt.SingletCell [1|0]: if 1, always enclose a cell with "[]"
even it has only one element; if 0, brackets
are ignored when a cell has only 1 element.
opt.ForceRootName [0|1]: when set to 1 and rootname is empty, savejson
will use the name of the passed obj variable as the
root object name; if obj is an expression and
does not have a name, 'root' will be used; if this
is set to 0 and rootname is empty, the root level
will be merged down to the lower level.
opt.Inf ['"$1_Inf_"'|string]: a customized regular expression pattern
to represent +/-Inf. The matched pattern is '([-+]*)Inf'
and $1 represents the sign. For those who want to use
1e999 to represent Inf, they can set opt.Inf to '$11e999'
opt.NaN ['"_NaN_"'|string]: a customized regular expression pattern
to represent NaN
opt.JSONP [''|string]: to generate a JSONP output (JSON with padding),
for example, if opt.JSONP='foo', the JSON data is
wrapped inside a function call as 'foo(...);'
opt.UnpackHex [1|0]: conver the 0x[hex code] output by loadjson
back to the string form
opt.SaveBinary [0|1]: 1 - save the JSON file in binary mode; 0 - text mode.
opt.Compact [0|1]: 1- out compact JSON format (remove all newlines and tabs)
opt.Compression 'zlib' or 'gzip': specify array compression
method; currently only supports 'gzip' or 'zlib'. The
data compression only applicable to numerical arrays
in 3D or higher dimensions, or when ArrayToStruct
is 1 for 1D or 2D arrays. If one wants to
compress a long string, one must convert
it to uint8 or int8 array first. The compressed
array uses three extra fields
"_ArrayCompressionMethod_": the opt.Compression value.
"_ArrayCompressionSize_": a 1D interger array to
store the pre-compressed (but post-processed)
array dimensions, and
"_ArrayCompressedData_": the "base64" encoded
compressed binary array data.
opt.CompressArraySize [100|int]: only to compress an array if the total
element count is larger than this number.
opt can be replaced by a list of ('param',value) pairs. The param
string is equivallent to a field in opt and is case sensitive.
output:
json: a string in the JSON format (see http://json.org)
examples:
jsonmesh=struct('MeshNode',[0 0 0;1 0 0;0 1 0;1 1 0;0 0 1;1 0 1;0 1 1;1 1 1],...
'MeshTetra',[1 2 4 8;1 3 4 8;1 2 6 8;1 5 6 8;1 5 7 8;1 3 7 8],...
'MeshTri',[1 2 4;1 2 6;1 3 4;1 3 7;1 5 6;1 5 7;...
2 8 4;2 8 6;3 8 4;3 8 7;5 8 6;5 8 7],...
'MeshCreator','FangQ','MeshTitle','T6 Cube',...
'SpecialData',[nan, inf, -inf]);
savejson('jmesh',jsonmesh)
savejson('',jsonmesh,'ArrayIndent',0,'FloatFormat','\t%.5g')
license:
BSD, see LICENSE_BSD.txt file for details
</pre>
=== loadubjson.m ===
<pre>
data=loadubjson(fname,opt)
or
data=loadubjson(fname,'param1',value1,'param2',value2,...)
parse a JSON (JavaScript Object Notation) file or string
authors:Qianqian Fang (q.fang <at> neu.edu)
created on 2013/08/01
$Id$
input:
fname: input file name, if fname contains "{}" or "[]", fname
will be interpreted as a UBJSON string
opt: a struct to store parsing options, opt can be replaced by
a list of ('param',value) pairs - the param string is equivallent
to a field in opt. opt can have the following
fields (first in [.|.] is the default)
opt.SimplifyCell [0|1]: if set to 1, loadubjson will call cell2mat
for each element of the JSON data, and group
arrays based on the cell2mat rules.
opt.IntEndian [B|L]: specify the endianness of the integer fields
in the UBJSON input data. B - Big-Endian format for
integers (as required in the UBJSON specification);
L - input integer fields are in Little-Endian order.
opt.NameIsString [0|1]: for UBJSON Specification Draft 8 or
earlier versions (JSONLab 1.0 final or earlier),
the "name" tag is treated as a string. To load
these UBJSON data, you need to manually set this
flag to 1.
output:
dat: a cell array, where {...} blocks are converted into cell arrays,
and [...] are converted to arrays
examples:
obj=struct('string','value','array',[1 2 3]);
ubjdata=saveubjson('obj',obj);
dat=loadubjson(ubjdata)
dat=loadubjson(['examples' filesep 'example1.ubj'])
dat=loadubjson(['examples' filesep 'example1.ubj'],'SimplifyCell',1)
license:
BSD, see LICENSE_BSD.txt file for details
</pre>
=== saveubjson.m ===
<pre>
json=saveubjson(rootname,obj,filename)
or
json=saveubjson(rootname,obj,opt)
json=saveubjson(rootname,obj,'param1',value1,'param2',value2,...)
convert a MATLAB object (cell, struct or array) into a Universal
Binary JSON (UBJSON) binary string
author: Qianqian Fang (q.fang <at> neu.edu)
created on 2013/08/17
$Id$
input:
rootname: the name of the root-object, when set to '', the root name
is ignored, however, when opt.ForceRootName is set to 1 (see below),
the MATLAB variable name will be used as the root name.
obj: a MATLAB object (array, cell, cell array, struct, struct array,
class instance)
filename: a string for the file name to save the output UBJSON data
opt: a struct for additional options, ignore to use default values.
opt can have the following fields (first in [.|.] is the default)
opt.FileName [''|string]: a file name to save the output JSON data
opt.ArrayToStruct[0|1]: when set to 0, saveubjson outputs 1D/2D
array in JSON array format; if sets to 1, an
array will be shown as a struct with fields
"_ArrayType_", "_ArraySize_" and "_ArrayData_"; for
sparse arrays, the non-zero elements will be
saved to _ArrayData_ field in triplet-format i.e.
(ix,iy,val) and "_ArrayIsSparse_" will be added
with a value of 1; for a complex array, the
_ArrayData_ array will include two columns
(4 for sparse) to record the real and imaginary
parts, and also "_ArrayIsComplex_":1 is added.
opt.ParseLogical [1|0]: if this is set to 1, logical array elem
will use true/false rather than 1/0.
opt.SingletArray [0|1]: if this is set to 1, arrays with a single
numerical element will be shown without a square
bracket, unless it is the root object; if 0, square
brackets are forced for any numerical arrays.
opt.SingletCell [1|0]: if 1, always enclose a cell with "[]"
even it has only one element; if 0, brackets
are ignored when a cell has only 1 element.
opt.ForceRootName [0|1]: when set to 1 and rootname is empty, saveubjson
will use the name of the passed obj variable as the
root object name; if obj is an expression and
does not have a name, 'root' will be used; if this
is set to 0 and rootname is empty, the root level
will be merged down to the lower level.
opt.JSONP [''|string]: to generate a JSONP output (JSON with padding),
for example, if opt.JSON='foo', the JSON data is
wrapped inside a function call as 'foo(...);'
opt.UnpackHex [1|0]: conver the 0x[hex code] output by loadjson
back to the string form
opt.Compression 'zlib' or 'gzip': specify array compression
method; currently only supports 'gzip' or 'zlib'. The
data compression only applicable to numerical arrays
in 3D or higher dimensions, or when ArrayToStruct
is 1 for 1D or 2D arrays. If one wants to
compress a long string, one must convert
it to uint8 or int8 array first. The compressed
array uses three extra fields
"_ArrayCompressionMethod_": the opt.Compression value.
"_ArrayCompressionSize_": a 1D interger array to
store the pre-compressed (but post-processed)
array dimensions, and
"_ArrayCompressedData_": the binary stream of
the compressed binary array data WITHOUT
'base64' encoding
opt.CompressArraySize [100|int]: only to compress an array if the total
element count is larger than this number.
opt can be replaced by a list of ('param',value) pairs. The param
string is equivallent to a field in opt and is case sensitive.
output:
json: a binary string in the UBJSON format (see http://ubjson.org)
examples:
jsonmesh=struct('MeshNode',[0 0 0;1 0 0;0 1 0;1 1 0;0 0 1;1 0 1;0 1 1;1 1 1],...
'MeshTetra',[1 2 4 8;1 3 4 8;1 2 6 8;1 5 6 8;1 5 7 8;1 3 7 8],...
'MeshTri',[1 2 4;1 2 6;1 3 4;1 3 7;1 5 6;1 5 7;...
2 8 4;2 8 6;3 8 4;3 8 7;5 8 6;5 8 7],...
'MeshCreator','FangQ','MeshTitle','T6 Cube',...
'SpecialData',[nan, inf, -inf]);
saveubjson('jsonmesh',jsonmesh)
saveubjson('jsonmesh',jsonmesh,'meshdata.ubj')
license:
BSD, see LICENSE_BSD.txt file for details
</pre>
=== examples ===
Under the "examples" folder, you can find several scripts to demonstrate the
basic utilities of JSONLab. Running the "demo_jsonlab_basic.m" script, you
will see the conversions from MATLAB data structure to JSON text and backward.
In "jsonlab_selftest.m", we load complex JSON files downloaded from the Internet
and validate the loadjson/savejson functions for regression testing purposes.
Similarly, a "demo_ubjson_basic.m" script is provided to test the saveubjson
and loadubjson functions for various matlab data structures.
Please run these examples and understand how JSONLab works before you use
it to process your data.
-------------------------------------------------------------------------------
IV. Known Issues and TODOs
JSONLab has several known limitations. We are striving to make it more general
and robust. Hopefully in a few future releases, the limitations become less.
Here are the known issues:
# 3D or higher dimensional cell/struct-arrays will be converted to 2D arrays;
# When processing names containing multi-byte characters, Octave and MATLAB \
can give different field-names; you can use feature('DefaultCharacterSet','latin1') \
in MATLAB to get consistant results
# savejson can not handle class and dataset.
# saveubjson converts a logical array into a uint8 ([U]) array
# an unofficial N-D array count syntax is implemented in saveubjson. We are \
actively communicating with the UBJSON spec maintainer to investigate the \
possibility of making it upstream
# loadubjson can not parse all UBJSON Specification (Draft 9) compliant \
files, however, it can parse all UBJSON files produced by saveubjson.
-------------------------------------------------------------------------------
V. Contribution and feedback
JSONLab 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/jsonlab.git jsonlab
or browsing the github site at
https://github.com/fangq/jsonlab
Please report any bugs or issues to the below URL:
https://github.com/fangq/jsonlab/issues
Sometimes, you may find it is necessary to modify JSONLab to achieve your
goals, or attempt to modify JSONLab functions to fix a bug that you have
encountered. If you are happy with your changes and willing to share those
changes to the upstream author, you are recommended to create a pull-request
on github.
To create a pull-request, you first need to "fork" jsonlab on Github by
clicking on the "fork" button on top-right of jsonlab's github page. Once you forked
jsonlab to your own directory, you should then implement the changes in your
own fork. After thoroughly testing it and you are confident the modification
is complete and effective, you can then click on the "New pull request"
button, and on the left, select fangq/jsonlab as the "base". Then type
in the description of the changes. You are responsible to format the code
updates using the same convention (tab-width: 8, indentation: 4 spaces) as
the upstream code.
We appreciate any suggestions and feedbacks from you. Please use the following
mailing list to report any questions you may have regarding JSONLab:
https://github.com/fangq/jsonlab/issues
(Subscription to the mailing list is needed in order to post messages).
-------------------------------------------------------------------------------
V. Acknowledgement
This toolbox contains modified functions from the below toolboxes:
== zlibdecode.m, zlibencode.m, gzipencode.m, gzipdecode.m, base64encode.m, base64decode.m ==
* Author: Kota Yamaguchi
* URL:https://www.mathworks.com/matlabcentral/fileexchange/39526-byte-encoding-utilities
* License: BSD License, see below
Copyright (c) 2012, Kota Yamaguchi
All rights reserved.
Redistribution and use in source and binary forms, with or without
modification, are permitted provided that the following conditions are met:
* Redistributions of source code must retain the above copyright notice, this
list of conditions and the following disclaimer.
* Redistributions in binary form must reproduce the above copyright notice,
this list of conditions and the following disclaimer in the documentation
and/or other materials provided with the distribution
THIS SOFTWARE IS PROVIDED BY THE COPYRIGHT HOLDERS AND CONTRIBUTORS "AS IS"
AND ANY EXPRESS OR IMPLIED WARRANTIES, INCLUDING, BUT NOT LIMITED TO, THE
IMPLIED WARRANTIES OF MERCHANTABILITY AND FITNESS FOR A PARTICULAR PURPOSE ARE
DISCLAIMED. IN NO EVENT SHALL THE COPYRIGHT OWNER OR CONTRIBUTORS BE LIABLE
FOR ANY DIRECT, INDIRECT, INCIDENTAL, SPECIAL, EXEMPLARY, OR CONSEQUENTIAL
DAMAGES (INCLUDING, BUT NOT LIMITED TO, PROCUREMENT OF SUBSTITUTE GOODS OR
SERVICES; LOSS OF USE, DATA, OR PROFITS; OR BUSINESS INTERRUPTION) HOWEVER
CAUSED AND ON ANY THEORY OF LIABILITY, WHETHER IN CONTRACT, STRICT LIABILITY,
OR TORT (INCLUDING NEGLIGENCE OR OTHERWISE) ARISING IN ANY WAY OUT OF THE USE
OF THIS SOFTWARE, EVEN IF ADVISED OF THE POSSIBILITY OF SUCH DAMAGE.
73bec97625