Variable time series data
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Hi All,
Please can anyone please help me with a code that can identify if a day had varrying/fluctuating irradiance from the attached txt file. The code should be able differentiate a clear day which follows a normal distribution from a day with intermittent/varrying irradiance (partly cloudy day). Please see attached sample txt file.
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Sulaymon Eshkabilov
2021-6-19
(1) Import the data into matlab using textscan() or fscanf() or best readtable()
%% Set up the Import Options and import the data
opts = delimitedTextImportOptions("NumVariables", 7);
% Specify range and delimiter
opts.DataLines = [16, Inf];
opts.Delimiter = "\t";
% Specify column names and types
opts.VariableNames = ["locationlatitudedegN32066132", "VarName2", "VarName3", "VarName4", "VarName5", "VarName6", "VarName7"];
opts.VariableTypes = ["datetime", "datetime", "double", "double", "double", "double", "double"];
% Specify file level properties
opts.ExtraColumnsRule = "ignore";
opts.EmptyLineRule = "read";
% Specify variable properties
opts = setvaropts(opts, "locationlatitudedegN32066132", "InputFormat", "dd/MM/yyyy");
opts = setvaropts(opts, "VarName2", "InputFormat", "HH:mm:ss");
% Import the data
DATA = readtable("20210107T000414.txt", opts);
(2) Select the data for processing
D1 = DATA.VarName6;
D2 = DATA.VarName6;
(3) Histogram analysis
DL=8640;
Day1 = D1(1:DL);
Day2 = D2(DL+1:2*DL);
Day3 = D2(2*DL+1:3*DL);
...
figure()
histfit(Day1)
...
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