test_OCT_convert.m

function test_OCT_convert()
    % This function demonstrates how to load the mat 'test.mat' file generated by the OCT_converter.py.
    % See the code line load('test.mat');
    %
    % The mat file contains Spectral as 3D or 2D data matrix.
    % All other data are left with the same name without '.data' attached, like 'Chirp', 'OffsetSpectrum', 'OffsetErrors', etc.
    %
    % This demonstration does not apply intensity scaling.
    %
    close('all');
    load('test.mat')

    % The 3D matrix Spectral is immediately after loading test.mat available
    % Here the A-line at 1000 for B-frame (1) is obtained
    pdata = (squeeze(Spectral(1,1000,:)));
    figure('name','Raw spectrum');plot(pdata)

    % Get the mean of the apodisation data if it was stored as a region in Spectral.
    % The variable Spectral_apo will be available.
    mdata = (squeeze(mean(Spectral_apo(1,:,:))))';

    % Get B-frame (1)
    spec = single(squeeze(Spectral(1,:,:)));
    spec_size = size(spec);
    spec_xs = spec_size(1);
    spec_zs = spec_size(2);

    % remove DC
    spec = spec - mdata;
    figure('name','DC removed spectrum');plot(spec(1000,:));hold('on')

    % linearize k-space
    spec_lin = interp1(Chirp,spec',(1:spec_zs-1))';

    % ifft --> z-space
    spec_fft = log10(abs(ifft(spec_lin,[],2)));
    f=figure();
    % The header.xml is converted and stored as Header.
    % Besides Header the substructure Header.DataFileDict is available
    % to access data for each Spectral data set.
    rangeX = str2double(Header.DataFileDict.Spectral0.RangeX);
    rangeZ = str2double(Header.DataFileDict.Spectral0.RangeZ);
    imagesc(spec_fft(:,1:spec_zs/2)','XData',[0,rangeX],'YData',[0,rangeZ],[-1.5,0.5]);
    f.Position = f.Position .* [1,1, rangeX*0.2, rangeZ*0.2]
    colormap('gray');
    colorbar();
end