Qianqian Fang

hi Chuck37

the issue you had reported is related to the cell2mat call on line#248 of loadjson. you can compare the following:

a=struct('one',1,'two',2);
b=[a a];
c={a,a};
class(b)
class(c)
class(cell2mat(c))

in many other cases, this kind of conversion is beneficial because it simplifies the data by looking into the internal regularity. However, it does come with the side-effect you have described.

To solve this issue, I just committed SVN#384, accepting a flag to control cell array->struct array conversion, see

http://iso2mesh.svn.sourceforge.net/viewvc/iso2mesh?view=revision&revision=384

you may check out this version and run the following to compare:

d=loadjson(savejson('',c))
class(d)
d=loadjson(savejson('',c),'SimplifyCell',1)
class(d)

by default, loadjson no longer converts a cell array to a struct array.

hi Mark

I just uploaded a new JSONLAB release, v0.9.0. Aside from various bug fixes, one of the main features of this release is the better round-trip consistency you suggested earlier. A leading underscore is now converted to x0x5F_; all hex codes generated by loadjson are automatically converted back to string forms in savejson.

A remaining issue is the handling of multi-byte characters in matlab. If this is the case, you may have to run feature('DefaultCharacterSet','latin1') in matlab to get consistent results.

Let me know if you are happy with this new release. (download from http://iso2mesh.sf.net/cgi-bin/index.cgi?jsonlab/Download )

hi Mark

regarding your first question, no, the NoRowBracket only applies to "numerical elements". I don't see any problems for processing array of strings though.

For your second question, it is not difficult for me to add a non-standard option to do the conversion. However, the current approach to deal with a leading underscore is to prepend an "x", similar to the behavior of MATLAB function genvarname(). However, once converted, a name in the form of "x_..." becomes difficult to separate from the genuine ones. A conversion from "x_..." to "_..." may have false positives. I am not sure if this is the best way to do, unless I define a unique prefix in the loadjson for this scenario.

I would have liked if there was an option to return as a dataset. Added these lines

data=data.data;
data=struct2cell(data);
data=cell2mat(squeeze(data)');
data= dataset({data(:,1), 'TimeEPOC'}, {data(:,2), 'Value'});

Excellent contribution. For large json files (mine was >100MB), you can make the code >100 times faster by replacing the line "currstr=inStr(pos:end);" with "currstr=inStr(pos:pos+100);" in parse_number().