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Apr 25, 2013
Apr 25, 2013

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.


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.


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);

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 ='/path/to/file.json');


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.


To run a test, invoke



You may redistribute this software under BSD license.


JSON in Java