Awesome
Matlab JSON
This package contains Matlab class to serialize/decode matlab object in
json format. The software uses customized org.json java package to convert
json to java object and then translates it into Matlab object.
API
All functions are scoped under json namespace.
startup Initialize runtime environment.
dump Encode matlab value into a JSON string.
load Load matlab value from a JSON string.
read Load a matlab value from a JSON file.
write Write a matlab value into a JSON file.
Usage
Add path to the directory containing +json before use, and call
json.startup. This is optional, but recommended.
>> addpath /path/to/matlab-json
>> json.startup
To serialize a matlab object:
>> X = struct('field1', magic(2), 'field2', 'hello');
>> S = json.dump(X);
>> disp(S);
{"field2":"hello","field1":[[1,3],[4,2]]}
To decode a json string:
>> X = json.load(S);
>> disp(X);
field2: 'hello'
field1: [2x2 double]
To read from or write to a json file.
>> json.write(X, '/path/to/file.json');
>> X = json.read('/path/to/file.json');
Note
Due to the multiple ways to represent an array in Matlab (i.e., numeric
array, cell array, or struct array), it is impossible to represent
everything in a compatible format. For example, a json string "[[1,2],[3,4]]"
can be interpreted in different ways in Matlab, such as [1,2;3,4], {1,2;3,4},
{[1,2],[3,4]}, etc. Because of this, json.load does not always yield the
exactly same input to json.dump.
This implementation is designed to maximize the ease of data exchange. For that purpose, by default, json parser assumes the following.
- Native arrays precede a cell array.
"[1,2]"is[1,2]in matlab. - Row-major order. e.g.,
"[[1,2],[3,4]]"is[1,2;3,4]in matlab. - N-D array is a nested json array.
- Any other ambiguous arrays are treated as cell array.
"[]"is{}.
For example, a nested array with the same sized elements is treated as an N-D array.
>> x = json.load('[[[1,2],[3,4]],[[5,6],[7,8]]]')
x(:,:,1) =
1 2
3 4
x(:,:,2) =
5 6
7 8
The json.load function can optionally take an option to specify column-major
interpretation or cell-array precedence. Check help json.load for details.
In addition to the standard JSON specification, the included
JSON parser accepts non-finite double values (Infinity, NaN).
The package is designed to make conversion as easy as possible. However, due to Java usage inside Matlab, the package is not optimized for performance. Be cautious when converting a huge variable.
Test
To run a test, invoke json.test.run.
>> json.test.run
License
You may redistribute this software under BSD license.