Vector dimesions are different before encoding json and after decoding json

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CHV
CHV 2022년 3월 3일
댓글: CHV 2022년 3월 9일
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);
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CHV
CHV 2022년 3월 3일
편집: CHV 2022년 3월 3일
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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Ive J
Ive J 2022년 3월 3일
편집: Ive J 2022년 3월 3일
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]
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Ive J
Ive J 2022년 3월 3일
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]
CHV
CHV 2022년 3월 9일
Thanks for the explanation and its worked.

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