Extract info from .json file by matlab

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Zeynab Mousavikhamene
回答： Wei 2024-8-28
I need to parse a json file and extract many objects and arrays from that file. Then I am going to plot those extracted information.
I used jsondecode but it only created one big char. Shoud I use that?

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回答（4 个）

Neeraj Rajpurohit
Neeraj Rajpurohit 2020-6-30
fileName = 'filename.json'; % filename in JSON extension
fid = fopen(fileName); % Opening the file
raw = fread(fid,inf); % Reading the contents
str = char(raw'); % Transformation
fclose(fid); % Closing the file
data = jsondecode(str); % Using the jsondecode function to parse JSON from string
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Stefan Grandl
Stefan Grandl 2020-7-5
fileName = 'filename.json'; % filename in JSON extension
str = fileread(fileName); % dedicated for reading files as text
data = jsondecode(str); % Using the jsondecode function to parse JSON from string
...this version is even more compact. ;-)
--> fileread() instead of fread()
Vairamani Kanagavel
Vairamani Kanagavel 2021-10-12
tried and working fine for reading .json files

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Navya Seelam
Navya Seelam 2019-8-8
Hi,
In order to plot the data use str2num to covert the string to numeric data type. If the data in JSON was array of numbers rather than strings then the output of jsondecode would have been array of double.
For more details on conversion of JSON datatypes to MATLAB data types refer this link
Arvind Gauns
Arvind Gauns 2022-1-23
I have a bunch of JSON files to get infornmation from. Eah file has got three structs within it.
I want to run a batch process to read all the 50 files and seperate the three structs and compile them into three csv files.
Can you help me with it ? I am sharing my code herebelow. Thank you in advance.
[file_list, path_n] = uigetfile('*dark.pico', 'Grab all the files', 'MultiSelect','on');
if iscell (file_list)== 0
file_list = (file_list)
end
T = array2table(file_list);
for i = 1:length(file_list);
loadfile = loadjson('{1}');
s = struct(loadfile);
x = s.Spectra(1).Pixels(:);
T1 = table(x);
x1 = s.Spectra(1).Metadata().Datetime;
x2 = s.Spectra(1).Metadata().Direction;
writetable(T1,'filename1.csv')
y = s.Spectra(2).Pixels(:);
T2 = table(y);
y1 = s.Spectra(2).Metadata().Datetime;
y2 = s.Spectra(2).Metadata().Direction;
writetable(T2,'filename2.csv')
z = s.Spectra(3).Pixels(:);
T3 = table(z);
z1 = s.Spectra(3).Metadata().Datetime;
z2 = s.Spectra(3).Metadata().Direction;
writetable(T3,'filename3.csv')
end
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Walter Roberson
Walter Roberson 2022-1-24
In the below, you might need to adjust the initialization of Invalid_Direction and Empty_Direction .
Empty_Direction needs to be an empty object with no rows and no columns. Depending on exactly what is being stored in the file, it might potentially be '' or cell(0,0) or strings(0,0)
Invalid_Direction needs to be the appropriate datatype matching Empty_Direction, but with content that signals that the row is unused, padding. It should not typically be blanks, because blanks too often is valid, and you need to distinguish between valid content and padding that exists only to make everything work out to be the same length.
Caution: if the Direction comes out as array of char (so, fixed width) and that it has more than one column, then the code that assigns in Invalid_Direction to pad out to indicate unused rows, needs to be modified to repmat() to the appropriate number of rows, such as
y2(size(y2,1)+1:nty2, 1:end) = repmat(Invalid_Direction, nty2-size(y2,1), 1);
This is not needed if Invalid_Direction is a scalar character that can be repeated for every column (such as '?') . It is also not needed if Invalid_Direction is a cell array of character vector, or a scalar string() object.
[file_list, path_n] = uigetfile('*dark.pico', 'Grab all the files', 'MultiSelect','on');
if ischar(file_list); file_list = {file_list}; end %only one selected
if ~iscell(file_list); return; end %user cancel
Invalid_Direction = '?';
Empty_Direction = '';
T = array2table(file_list);
x = []; x1 = NaT(0,0); x2 = Empty_Direction;
y = []; y1 = NaT(0,0); y2 = Empty_Direction;
z = []; z1 = NaT(0,0); z2 = Invalid_Direction;
for i = 1:length(file_list);
this_file = fullfile(path_n, filelist{i});
loadfile = loadjson(this_file);
s = struct(loadfile);
tx = s.Spectra(1).Pixels(:);
tx1 = s.Spectra(1).Metadata().Datetime;
tx2 = s.Spectra(1).Metadata().Direction;
ntx = size(tx,1); ntx1 = size(tx1,1); ntx2 = size(tx2,1);
x(size(x,1)+1:ntx, 1:end) = nan;
x1(size(x1,1)+1:ntx1, 1:end) = NaT;
x2(size(x2,1)+1:ntx2, 1:end) = Invalid_Direction;
nx = size(x,1); nx1 = size(x1,1); nx2 = size(x2,1);
tx(end+1:ntx) = nan; tx1(end+1:ntx1) = nan; tx2(end+1:ntx2) = Invalid_Direction;
x(:,end+1:end+size(tx,2)) = tx;
x1(:,end+1:end+size(tx1,2)) = tx1;
x2(:,end+1:end+size(tx2,2)) = tx2;
ty = s.Spectra(2).Pixels(:);
ty1 = s.Spectra(2).Metadata().Datetime;
ty2 = s.Spectra(2).Metadata().Direction;
nty = size(ty,1); nty1 = size(ty1,1); nty2 = size(ty2,1);
y(size(y,1)+1:nty, 1:end) = nan;
y1(size(y1,1)+1:nty1, 1:end) = NaT;
y2(size(y2,1)+1:nty2, 1:end) = Invalid_Direction;
ny = size(y,1); nx1 = size(y1,1); ny2 = size(y2,1);
ty(end+1:nty) = nan; ty1(end+1:nty1) = NaT; ty2(end+1:nty2) = Invalid_Direction;
y(:,end+1:end+size(ty,2)) = ty;
y1(:,end+1:end+size(ty1,2)) = ty1;
y2(:,end+1:end+size(ty2,2)) = ty2;
tz = s.Spectra(3).Pixels(:);
tz1 = s.Spectra(3).Metadata().Datetime;
tz2 = s.Spectra(3).Metadata().Direction;
ntz = size(tz,1); ntz1 = size(tz1,1); ntz2 = size(tz2,1);
z(size(z,1)+1:ntz, 1:end) = nan;
z1(size(z1,1)+1:ntz1, 1:end) = NaT;
z2(size(z2,1)+1:ntz2, 1:end) = Invalid_Direction;
nz = size(z,1); nz1 = size(z1,1); nz2 = size(x2,1);
tz(end+1:ntz) = nan; tz1(end+1:ntz1) = NaT; tz2(end+1:ntz2) = Invalid_Direction;
z(:,end+1:end+size(tz,2)) = tz;
z1(:,end+1:end+size(tz1,2)) = tz1;
z2(:,end+1:end+size(tz2,2)) = tz2;
end
xr = max([size(x,1), size(x1,1), size(x2,1)]);
x(end+1:xr, 1:end) = nan;
x1(end+1:xr, 1:end) = NaT;
x2(end+1:xr, 1:end) = Invalid_Direction;
Tx = table(x, x1, x2);
writetable(Tx, 'filename1.csv');
yr = max([size(y,1), size(y1,1), size(y2,1)]);
y(end+1:yr, 1:end) = nan;
y1(end+1:yr, 1:end) = NaT;
y2(end+1:yr, 1:end) = Invalid_Direction;
Ty = table(y, y1, y2);
writetable(Ty, 'filename2.csv');
zr = max([size(z,1), size(z1,1), size(z2,1)]);
z(end+1:zr, 1:end) = nan;
z1(end+1:zr, 1:end) = NaT;
z2(end+1:zr, 1:end) = Invalid_Direction;
Tz = table(z, z1, z2);
writetable(Tz, 'filename3.csv');
Arvind Gauns
Arvind Gauns 2022-1-27
Mr. @Walter Roberson thank you very much for the exact solution for my problem. I workled on the solution provided and came up with the latest code.
Now i am also geting most the results I am looking for. But the issue I am facing is that, first few of my readings doesnt have the 'z' component. ( to tell you a little in the background, the JSON file has 4 arrays, which will be utilised to obtain different readings. first few of them only have 3 arrays so the 4th arrey in the successing files arent retrieved in matrix format). Either i want NAN values or 0 in place of the blank values or a filter which will (1. select the files with 4 arrays & 2. keep the list of the files). can that be added ?
clear all
clc
[file_list, path_n] = uigetfile('*dark.pico', 'Grab all the files', 'MultiSelect','on');
if ischar(file_list); file_list = {file_list}; end %only one selected
if ~iscell(file_list); return; end %user cancel
Invalid_Direction = '?';
Empty_Direction = '';
T = array2table(file_list);
w = []; x = []; y = []; z = [];
w1 = Empty_Direction; x1 = Empty_Direction; y1 = Empty_Direction; z1 = Empty_Direction;
w2 = Empty_Direction; x2 = Empty_Direction; y2 = Empty_Direction; z2 = Empty_Direction;
w3 = []; x3 = []; y3 = []; z3 = [];
for i = 1:length(file_list)
this_file = fullfile(path_n, file_list{i});
loadfile = loadjson(this_file);
s = struct(loadfile);
tw = s.Spectra(1).Pixels(:);
tw1 = s.Spectra(1).Metadata().Datetime;
tw2 = s.Spectra(1).Metadata().Direction;
tw3 = s.Spectra(1).Metadata().IntegrationTime;
ntw1 = size(tw1,1) ; ntw2 = size(tw2,1); ntw3 = size(tw3,1); ntw = size(tw,1);
w(size(w,1)+1:ntw, 1:end) = nan;
w1(size(w1,1)+1:ntw1, 1:end) = nan;
w2(size(w2,1)+1:ntw2, 1:end) = nan;
w3(size(w3,1)+1:ntw2, 1:end) = nan;
nw1 = size(w1,1); nw2 = size(w2,1); nw3 = size(w3,1); nw = size(w,1);
tw1(end+1:ntw1) = nan; tw2(end+1:ntw2) = nan; tw3(end+1:ntw3) = nan; tw(end+1:ntw)=nan;
w(:,end+1:end+size(tw,2)) = tw;
w1(:,end+1:end+size(tw1,2)) = tw1;
w2(:,end+1:end+size(tw2,2)) = tw2;
w3(:,end+1:end+size(tw3,2)) = tw3;
tx = s.Spectra(2).Pixels(:);
tx1 = s.Spectra(2).Metadata().Datetime;
tx2 = s.Spectra(2).Metadata().Direction;
tx3 = s.Spectra(2).Metadata().IntegrationTime;
ntx1 = size(tx1,1) ; ntx2 = size(tx2,1); ntx3 = size(tx3,1); ntx = size(tx,1);
x(size(x,1)+1:ntx, 1:end) = nan;
x1(size(x1,1)+1:ntx1, 1:end) = nan;
x2(size(x2,1)+1:ntx2, 1:end) = nan;
x3(size(x3,1)+1:ntx2, 1:end) = nan;
nx1 = size(x1,1); nx2 = size(x2,1); nx3 = size(x3,1); nx = size(x,1);
tx1(end+1:ntx1) = nan; tx2(end+1:ntx2) = nan; tx3(end+1:ntx3) = nan; tx(end+1:ntx)=nan;
x(:,end+1:end+size(tx,2)) = tx;
x1(:,end+1:end+size(tx1,2)) = tx1;
x2(:,end+1:end+size(tx2,2)) = tx2;
x3(:,end+1:end+size(tx3,2)) = tx3;
ty = s.Spectra(3).Pixels(:);
ty1 = s.Spectra(3).Metadata().Datetime;
ty2 = s.Spectra(3).Metadata().Direction;
ty3 = s.Spectra(3).Metadata().IntegrationTime;
nty1 = size(ty1,1) ; nty2 = size(ty2,1); nty3 = size(ty3,1); nty = size(ty,1);
y(size(y,1)+1:nty, 1:end) = nan;
y1(size(y1,1)+1:nty1, 1:end) = nan;
y2(size(y2,1)+1:nty2, 1:end) = nan;
y3(size(y3,1)+1:nty2, 1:end) = nan;
ny1 = size(y1,1); ny2 = size(y2,1); ny3 = size(y3,1); ny = size(y,1);
ty1(end+1:nty1) = nan; ty2(end+1:nty2) = nan; ty3(end+1:nty3) = nan; ty(end+1:nty)=nan;
y(:,end+1:end+size(ty,2)) = ty;
y1(:,end+1:end+size(ty1,2)) = ty1;
y2(:,end+1:end+size(ty2,2)) = ty2;
y3(:,end+1:end+size(ty3,2)) = ty3;
tz = s.Spectra(4).Pixels(:);
tz1 = s.Spectra(4).Metadata().Datetime;
tz2 = s.Spectra(4).Metadata().Direction;
tz3 = s.Spectra(4).Metadata().IntegrationTime;
ntz1 = size(tz1,1) ; ntz2 = size(tz2,1); ntz3 = size(tz3,1); ntz = size(tz,1);
z(size(z,1)+1:ntz, 1:end) = nan;
z1(size(z1,1)+1:ntz1, 1:end) = nan;
z2(size(z2,1)+1:ntz2, 1:end) = nan;
z3(size(z3,1)+1:ntz2, 1:end) = nan;
nz1 = size(z1,1); nz2 = size(z2,1); nz3 = size(z3,1); nz = size(z,1);
tz1(end+1:ntz1) = nan; tz2(end+1:ntz2) = nan; tz3(end+1:ntz3) = nan; tz(end+1:ntz)=nan;
z(:,end+1:end+size(tz,2)) = tz;
z1(:,end+1:end+size(tz1,2)) = tz1;
z2(:,end+1:end+size(tz2,2)) = tz2;
z3(:,end+1:end+size(tz3,2)) = tz3;
end
wr = max([size(w,1), size(w1,1), size(w2,1),size(w3,1)]);
w(end+1:wr, 1:end) = nan;
w1(end+1:wr, 1:end) = Invalid_Direction;
w2(end+1:wr, 1:end) = Invalid_Direction;
w3(end+1:wr, 1:end) = nan;
w4= table( w./w3(1,:));
%Tw = [w4;w];
writetable(w4, 'QEP01348_downwelling.csv');
xr = max([size(x,1), size(x1,1), size(x2,1),size(x3,1)]);
x(end+1:xr, 1:end) = nan;
x1(end+1:xr, 1:end) = Invalid_Direction;
x2(end+1:xr, 1:end) = Invalid_Direction;
x3(end+1:xr, 1:end) = nan;
x4= table(x./x3(1,:));
% Tx = table(x, x1, x2, x3);
writetable(x4, 'QEP01349_downwelling.csv');
yr = max([size(y,1), size(y1,1), size(y2,1), size(y3,1)]);
y(end+1:yr, 1:end) = nan;
y1(end+1:yr, 1:end) = Invalid_Direction;
y2(end+1:yr, 1:end) = Invalid_Direction;
y3(end+1:yr, 1:end) = nan;
y4= table(y./y3(1,:));
% Ty = table(y, y1, y2, y3);
writetable(y4, 'QEP01348_upwelling.csv');
zr = max([size(z,1), size(z1,1), size(z2,1), size(z3,1)]);
z(end+1:zr, 1:end) = nan;
z1(end+1:zr, 1:end) = Invalid_Direction;
z2(end+1:zr, 1:end) = Invalid_Direction;
z3(end+1:zr, 1:end) = nan;
% Tz = table(z, z1, z2, z3);
z4= table(z./z3(1,:));
writetable(z4, 'QEP01349_upwelling.csv');

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Wei
Wei 2024-8-28
if you have r2023b, readstruct/writestruct should help.

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