% === SETTINGS ===

dsp_options.append_to_db = 1;
dsp_options.max_occurences = 15;
dsp_options.database_path = 'C:\Users\Silas\Documents\MATLAB\Datensätze\sioe_labor\';
dsp_options.database_name = 'silas_labor_newdsp_newstructure.db';
dsp_options.storage_path = 'Z:\2024\sioe_labor\';
dsp_options.parameters = struct();
dsp_options.parameters.mu_dc = [0.005];

% === Get Run ID's ===
db = DBHandler("pathToDB", [dsp_options.database_path, dsp_options.database_name], "type", "sqlite");
fp = QueryFilter();
% fp.where('Runs', 'run_id','EQUALS', 5108);            
fp.where('Runs', 'is_mpi','EQUALS', 0);                
% fp.where('Runs', 'fiber_length','EQUALS', 10);       
fp.where('Runs', 'wavelength','EQUALS', 1310);         
fp.where('Runs', 'db_mode','EQUALS', 1);              
fp.where('Runs', 'rop_attenuation','EQUALS', 0);      
fp.where('Runs', 'pam_level','EQUALS', 4);     
% fp.where('Runs', 'bitrate','EQUALS', 360e9);    
% fp.where('Runs', 'power_pd_in','GREATER_THAN', 7);    
[dataTable,~] = db.queryDB(fp, db.getTableFieldNames('Runs'));

% === Initialize DataStorage ===
wh = DataStorage(dsp_options.parameters);
wh.addStorage("ffe_package");
wh.addStorage("mlse_package");
wh.addStorage("vnle_package");
wh.addStorage("dbtgt_package");
wh.addStorage("dbenc_package");

% === RUN IT ===

% [results,wh] = submitJobs(dataTable.run_id(:), dsp_options, "parallel", 'wh', wh, 'waitbar', true);
% wh.getStoValue('ffe_package',0.005);
% wh.getStoValue('mlse_package',0.005);

[dataTable,~] = db.queryDB(fp, [db.getTableFieldNames('Runs');db.getTableFieldNames('Results');db.getTableFieldNames('Equalizer')]);

dataTable = cleanUpTable(dataTable);

% === Look at it ===
y_var = 'BER_precoded';
x_var = 'bitrate';
fixedVars = {'equalizer_structure', x_var};

[dataTableClean, outliersTable] = removeGroupOutliers(dataTable, fixedVars, y_var);

% --- Group and aggregate ---
dataTableGrpd_mean = groupIt(fixedVars, dataTableClean, @mean);
dataTableGrpd_min  = groupIt(fixedVars, dataTableClean, @min);
dataTableGrpd_max  = groupIt(fixedVars, dataTableClean, @max);

% Choose a color map
cols = linspecer(numel(unique(dataTableGrpd_mean.equalizer_structure)));

figure;
hold on;

% Get unique equalizer structures for grouping
unique_eq = unique(dataTableGrpd_mean.equalizer_structure);

for i = 1:numel(unique_eq)
    eq_val = unique_eq(i);

    % Filter grouped data for this equalizer structure
    filt = dataTableGrpd_mean.equalizer_structure == eq_val;

    x = dataTableGrpd_mean.(x_var)(filt);
    y_mean = dataTableGrpd_mean.(y_var)(filt);
    y_min  = dataTableGrpd_min.(y_var)(filt);
    y_max  = dataTableGrpd_max.(y_var)(filt);

    % Bounds for boundedline (distance from mean)
    y_lower = y_mean - y_min;
    y_upper = y_max - y_mean;
    y_bounds = [y_lower, y_upper];

    % --- Bounded line (mean ± min/max) ---
    if exist('boundedline', 'file')
        [hl, hp] = boundedline(x, y_mean, y_bounds, ...
            'alpha', 'transparency', 0.1, ...
            'cmap', cols(i,:), ...
            'nan', 'fill', ...
            'orientation', 'vert');
        set(hl, 'LineWidth', 1.2, 'DisplayName', sprintf('Eq %s', eq_val));
        set(hp, 'HandleVisibility', 'off');
    else
        % If boundedline is not available, use errorbar
        errorbar(x, y_mean, y_lower, y_upper, ...
            'o-', 'Color', cols(i,:), 'LineWidth', 1.2, ...
            'DisplayName', sprintf('Eq %d', eq_val),'HandleVisibility', 'off');
    end

    % --- Normal line (mean only) ---
    plot(x, y_mean, '-', 'Color', cols(i,:), 'LineWidth', 1.5, ...
        'DisplayName', sprintf('Mean Eq %s', eq_val),'HandleVisibility', 'off');

    % --- Scatter plot for individual points (from original data) ---
    % Filter original data for this group
    orig_filt = dataTableClean.equalizer_structure == eq_val;
    x_scatter = dataTableClean.(x_var)(orig_filt);
    y_scatter = dataTableClean.(y_var)(orig_filt);

    scatter(x_scatter, y_scatter, 10,cols(i,:), 'filled', ...
        'MarkerFaceAlpha', 0.5, 'DisplayName', sprintf('Scatter Eq %s', eq_val),'HandleVisibility', 'off');
end

yline([2.2e-4,4.85e-3,2e-2],'HandleVisibility', 'off','LineWidth',1,'LineStyle','--');
set(gca, 'YScale', 'log'); % BER is usually plotted log-scale
xlabel(x_var, 'Interpreter', 'none');
ylabel(y_var, 'Interpreter', 'none');
legend('show', 'Location', 'best');
grid on;
title(sprintf('%s vs. %s', y_var, x_var), 'Interpreter', 'none');
hold off;