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Vector dimesions are different before encoding json and after decoding json

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Before encoding to json file the mat files are having vectors are as row vector. But after encoding (jsonencode) and decoding(jsondecode), the vectors are changed to column vectors in workspace. And I want the same dimensions after decoding also, how can I get that ?
b.c = 22;
a= jsonencode(b);
d=jsondecode(a);
  2 Comments
CHV
CHV on 3 Mar 2022
Edited: CHV on 3 Mar 2022
Transpose is easy for few variables and above one I have shown is just one variable.But I am having lot of variables with different dimensions as structure array.After decoding I need same dimensions as before encoding.

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Accepted Answer

Ive J
Ive J on 3 Mar 2022
Edited: Ive J on 3 Mar 2022
How about this?
mystr.f1 = 1:4;
mystr.f2 = (1:4).';
js = jsonencode(mystr);
newstr = jsondecode(js)
newstr = struct with fields:
f1: [4×1 double] f2: [4×1 double]
fnames = fieldnames(mystr);
fnames = fnames(structfun(@isrow, mystr)); % field names to be changed
for i = 1:numel(fnames)
newstr.(fnames{i}) = newstr.(fnames{i}).';
end
newstr
newstr = struct with fields:
f1: [1 2 3 4] f2: [4×1 double]
  3 Comments
Ive J
Ive J on 3 Mar 2022
jsondecode output will be always a column vector irrespective of your input structure. So, you have to find another way of passing dimensions of vectors stored in your initial structure (mystr in my example), because you cannot infer it from a decoded json anyway. You can also work with mps.json.encode which is the schema for MATLAB Production Server, and especially designed for MATLAB data types. Note the difference between column and row vectors in this case:
x.a = 1:3; x.b = (1:3)';
js = mps.json.encode(x)
js = '{"a":[[1,2,3]],"b":[1,2,3]}'
% decode again
newx = mps.json.decode(js)
newx = struct with fields:
a: [1 2 3] b: [3×1 double]

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