客服电话
APP下载
迪恩网络APP
随时随地掌握行业动态
官方微信
扫描二维码
关注迪恩网络微信公众号
开源软件名称（OpenSource Name）：fangq/jsonlab开源软件地址(OpenSource Url)：https://github.com/fangq/jsonlab开源编程语言(OpenSource Language)：MATLAB 99.3%开源软件介绍(OpenSource Introduction)：JSONLab: compact, portable, robust JSON/binary-JSON encoder/decoder for MATLAB/Octave
Table of ContentsWhat's NewWe are excited to announce that the JSONLab project, as the official reference library for both the JData and BJData specifications, is funded by the US National Institute of Health (NIH) as part of the NeuroJSON project (https://neurojson.org). The goal of the NeuroJSON project is to develop human-readable, scalable and future-proof neuroimaging data standards and data sharing services. All data produced from the NeuroJSON project will be using JSON/Binary JData formats as the underlying serialization standards and use the lightweight JData specification as language-independent data annotation standard, all of which have been evolved from the over a decade development of JSONLab. JSONLab v2.9.8 - code named "Micronus - beta" - is the beta-release of the next milestone - JSONLab v3.0 - containing a number of key feature enhancement and bug fixes. The major new features include
There have been many major updates added to this release since the previous
release v2.0 in June 2020. A list of the major changes are summarized below
(with key features marked by *), including the support to BJData Draft-2 specification,
new interface functions
Please note that the The BJData spec was derived from UBJSON spec Draft 12, with the following breaking differences:
To avoid using the new features, one should attach savebj('',data,'FileName','myfile.bjd','UBJSON',1, 'Endian','B');To read BJData data files generated by JSONLab v2.0, you should call data=loadbj('my_old_data_file.bjd','Endian','B')You are strongly encouraged to convert all pre-v2.9 JSONLab generated BJD or .jamm files using the new format. IntroductionJSONLab is an open-source JSON/UBJSON/MessagePack encoder and decoder written completely in the native MATLAB language. It can be used to convert most MATLAB data structures (array, struct, cell, struct array, cell array, and objects) into JSON/UBJSON/MessagePack formatted strings and files, or to parse a JSON/UBJSON/MessagePack file into a MATLAB data structure. JSONLab supports both MATLAB and GNU Octave (a free MATLAB clone). Compared to other MATLAB/Octave JSON parsers, JSONLab is uniquely lightweight,
ultra-portable, producing dependable outputs across a wide-range of MATLAB
(tested on R2008) and Octave (tested on v3.8) versions. It also uniquely supports
BinaryJData/UBJSON/MessagePack data files as binary-JSON-like formats, designed
for efficiency and flexibility with loss-less binary storage. As a parser written
completely with the native MATLAB language, it is surprisingly fast when reading
small-to-moderate sized JSON files (1-2 MB) with simple hierarchical structures,
and is heavily optimized for reading JSON files containing large N-D arrays
(known as the "fast array parser" in JSON (JavaScript Object Notation) is a highly portable, human-readable and "fat-free" text format to represent complex and hierarchical data, widely used for data-exchange in applications. UBJSON (Universal Binary JSON) is a binary JSON format, designed to specifically address the limitations of JSON, permitting the storage of binary data with strongly typed data records, resulting in smaller file sizes and fast encoding and decoding. MessagePack is another binary JSON-like data format widely used in data exchange in web/native applications. It is slightly more compact than UBJSON, but is not directly readable compared to UBJSON. We envision that both JSON and its binary counterparts will play important roles for storage, exchange and interoperation of large-scale scientific data among the wide-variety of tools. As container-formats, they offer both the flexibility and generality similar to other more sophisticated formats such as HDF5, but are significantly simpler with a much greater software ecosystem. Towards this goal, we have developed the JData Specification (http://github.com/NeuroJSON/jdata) to standardize serializations of complex scientific data structures, such as N-D arrays, sparse/complex-valued arrays, trees, maps, tables and graphs using JSON/binary JSON constructs. The text and binary formatted JData files are syntactically compatible with JSON/UBJSON formats, and can be readily parsed using existing JSON and UBJSON parsers. JSONLab is not just a parser and writer of JSON/UBJSON data files, but one that systematically converts complex scientific data structures into human-readable and universally supported JSON forms using the standardized JData data annotations. InstallationThe installation of JSONLab is no different from installing any other 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 can type 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.mand type To use the data compression features, please download the ZMat toolbox from
https://github.com/fangq/zmat/releases/latest and follow the instruction to
install ZMat first. The ZMat toolbox is required when compression is used on
MATLAB running in the Install JSONLab on Fedora 24 or laterJSONLab has been available as an official Fedora package since 2015. You may install it directly using the below command sudo dnf install octave-jsonlabTo enable data compression/decompression, you need to install sudo dnf install octave-zmatThen open Octave, and type Install JSONLab on DebianJSONLab is currently available on Debian Bullseye. To install, you may run sudo apt-get install octave-jsonlabOne can alternatively install Install JSONLab on UbuntuJSONLab is currently available on Ubuntu 21.04 or newer as package octave-jsonlab. To install, you may run sudo apt-get install octave-jsonlabFor older Ubuntu releases, one can add the below PPA https://launchpad.net/~fangq/+archive/ubuntu/ppa To install, please run sudo add-apt-repository ppa:fangq/ppa
sudo apt-get updateto add this PPA, and then use sudo apt-get install octave-jsonlabto install the toolbox. Install JSONLab on Arch LinuxJSONLab is also available on Arch Linux. You may install it using the below command sudo pikaur -S jsonlabUsing JSONLabJSONLab provides a pair of functions, In JSONLab 2.9.8 and later versions, a unified file loading and saving interface
is provided for JSON, binary JSON and HDF5, including
In the below section, we provide a few examples on how to us each of the core functions for encoding/decoding JSON/UBJSON/MessagePack data. savejson.mjsonmesh=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],...
'MeshElem',[1 2 4 8;1 3 4 8;1 2 6 8;1 5 6 8;1 5 7 8;1 3 7 8],...
'MeshSurf',[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(jsonmesh)
savejson('jmesh',jsonmesh)
savejson('',jsonmesh,'Compact',1)
savejson('jmesh',jsonmesh,'outputfile.json')
savejson('',jsonmesh,'ArrayIndent',0,'FloatFormat','\t%.5g','FileName','outputfile2.json')
savejson('cpxrand',eye(5)+1i*magic(5))
savejson('ziparray',eye(10),'Compression','zlib','CompressArraySize',1)
savejson('',jsonmesh,'ArrayToStruct',1)
savejson('',eye(10),'UseArrayShape',1)loadjson.mloadjson('{}')
dat=loadjson('{"obj":{"string":"value","array":[1,2,3]}}')
dat=loadjson(['examples' filesep 'example1.json'])
dat=loadjson(['examples' filesep 'example1.json'],'SimplifyCell',0)savebj.m (saveubjson.m as an alias)a={single(rand(2)), struct('va',1,'vb','string'), 1+2i};
savebj(a)
savebj('rootname',a,'testdata.ubj')
savebj('zeros',zeros(100),'Compression','gzip')loadbj.m (loadubjson.m as an alias)obj=struct('string','value','array',single([1 2 3]),'empty',[],'magic',uint8(magic(5)));
ubjdata=savebj('obj',obj);
dat=loadbj(ubjdata)
class(dat.obj.array)
isequaln(obj,dat.obj)
dat=loadbj(savebj('',eye(10),'Compression','zlib','CompressArraySize',1))jdataencode.mjd=jdataencode(struct('a',rand(5)+1i*rand(5),'b',[],'c',sparse(5,5)))
savejson('',jd)jdatadecode.mrawdata=struct('a',rand(5)+1i*rand(5),'b',[],'c',sparse(5,5));
jd=jdataencode(rawdata)
newjd=jdatadecode(jd)
isequaln(newjd,rawdata)examplesUnder the Please run these examples and understand how JSONLab works before you use it to process your data. unit testingUnder the Using
|
2023-10-27
2022-08-15
2022-08-17
2022-09-23
2022-08-13
六六分期app的软件客服如何联系？不知道吗？加qq群【895510560】即可！标题：六六分期
今天小编告诉大家如何处理win10系统火狐flash插件总是崩溃的问题，可能很多用户都不知
今天小编告诉大家如何对win10系统删除桌面回收站图标进行设置，可能很多用户都不知道
今天小编告诉大家如何对win10系统电脑设置节能降温的设置方法，想必大家都遇到过需要
我们在使用xp系统的过程中,经常需要对xp系统无线网络安装向导设置进行设置，可能很多
今天小编告诉大家如何处理win7系统玩cf老是与主机连接不稳定的问题，可能很多用户都不
电脑对日常生活的重要性小编就不多说了，可是一旦碰到win7系统设置cf烟雾头的问题，很
我们在日常使用电脑的时候，有的小伙伴们可能在打开应用的时候会遇见提示应用程序无法
今天小编告诉大家如何对win7系统打开vcf文件进行设置，可能很多用户都不知道怎么对win
今天小编告诉大家如何对win10系统s4开启USB调试模式进行设置，可能很多用户都不知道怎
请发表评论