CustomCodeForPLotting.m

function funcOut = CustomCodeForPlotting(analyVar, indivDataset, avgDataset)
    %%% CustomCode for BMOT data in 11.11.2024_searchingforrydberg
    
    indVarField = 'imagevcoAtom'; % The Field of an IndivDataset that is to be plotted on the X axis
    depVarField = 'numberAtom'; % The field of an indivdataset that is to be plotted on the y axis
    
    %[xdata_clean, ydata_clean] = getxy_filtered(indVarField, depVarField, analyVar, indivDataset, avgDataset);
    [xdata_clean, ydata_clean] = getxy(indVarField, depVarField, analyVar, indivDataset, avgDataset);
    scanIDs = analyVar.uniqScanList;
    x = cell(length(scanIDs));
    y = cell(length(scanIDs));
    yerr = cell(length(scanIDs));
    
    % Define the AVG sig scalar for each ScanID in the batch files.
    AvgSig = zeros(size(scanIDs));
    AvgSig_err = zeros(size(scanIDs));
    for id = 1:length(scanIDs)
        x{id} = [];

        for basename = 1:analyVar.numBasenamesAtom
            if scanIDs(id) == analyVar.meanListVar(basename)
               x{id} = union(x{id},xdata_clean{basename});
            end
        end

        y{id} = zeros(size(x{id}));
        yerr{id} = zeros(size(x{id}));
        tempy = zeros(size(analyVar.meanListVar));
        for i = 1:length(x{id})
            num=0;
            for basename = 1:analyVar.numBasenamesAtom
                if scanIDs(id) == analyVar.meanListVar(basename)
                    for j = 1:length(xdata_clean{basename})
                        if xdata_clean{basename}(j) == x{id}(i)
                            num = num + 1;
                            tempy(num) = ydata_clean{basename}(j);
                        end
                    end
                end
            end
            num;
            y{id}(i) = mean(tempy(1:num));
            yerr{id}(i) = std(tempy(1:num))/sqrt(num);
        end
        %y{id}
        AvgSig(id) = mean(y{id}); % use this to average over the independent variable and get a scalar for each scanID
        AvgSig_err(id) = std(y{id}); % use this to std over the independent variable and get a scalar for each scanID
    end
    
    avgDataset.(depVarField) = y;
    avgDataset.(strcat(depVarField,'_unc')) = yerr;
    avgDataset.(strcat(depVarField,'_x')) = x;
    % 
    % figure;
    % hold on;
    % for id = 1:length(scanIDs)
    %     errorbar(x{id}, y{id}, yerr{id},...
    %         'LineStyle','-',...
    %         'Marker', analyVar.MARKERS2(id),...
    %         'MarkerSize', analyVar.markerSize,...
    %         'MarkerFaceColor', analyVar.COLORS(id,:),...
    %         'MarkerEdgeColor', 'none',...
    %         'Color', analyVar.COLORS(id,:));
    % end
    % legend(num2str(scanIDs));
    % title('Trapping- Scanning Mot coil Off time - 60 1D2 Line');
    % xlabel('826 nm Synth with doubler ON [MHz]');
    % ylabel('Total MCS Counts');
    % hold off
    % 
    % figure;
    % hold on;
    % errorbar(scanIDs, AvgSig, AvgSig_err,...
    %     'LineStyle','-',...
    %     'Marker', analyVar.MARKERS2(1),...
    %     'MarkerSize', analyVar.markerSize,...
    %     'MarkerFaceColor', analyVar.COLORS(1,:),...
    %     'MarkerEdgeColor', 'none',...
    %     'Color', analyVar.COLORS(1,:));
    % %legend(num2str(scanIDs));
    % title('Variation of Trapped Atoms with Different Zeeman Coil Field Strengths');
    % xlabel('Zeeman Coil Current (A)');
    % ylabel('Total Atom Count (Fast Fitting)');
    % hold off

    %% Custom plot
    %state number of different plots to place onto same figuer
    numberOfPlots = 8;
    %create list for x, y, and error values
    lsx = cell(1,numberOfPlots);
    lsy = cell(1,numberOfPlots);
    lserr = cell(1,numberOfPlots);
    %scan through all the files.
    %Each if statement grabs the files with the same decimal value in their
    %ID and will place them in the same list
    %% Added a hard coded normaliation value to all Avg values
    for id = 1:length(scanIDs)

        % if (round(scanIDs(id)-floor(scanIDs(id)),1) == .1)
        %     lsx{1}{end+1} = scanIDs(id)*80e-3;
        %     lsy{1}{end+1} = AvgSig(id);
        %     lserr{1}{end+1} = AvgSig_err(id);
        % end
        if (round(scanIDs(id)-floor(scanIDs(id)),1) == .2)
            lsx{1}{end+1} = scanIDs(id);%*80e-3;
            lsy{1}{end+1} = AvgSig(id);%/AvgSig(16);
            lserr{1}{end+1} = AvgSig_err(id);%/AvgSig(16);
        end
        if (round(scanIDs(id)-floor(scanIDs(id)),1) == .3)
            lsx{2}{end+1} = scanIDs(id);%*80e-3;
            lsy{2}{end+1} = AvgSig(id);%/AvgSig(1);
            lserr{2}{end+1} = AvgSig_err(id);%/AvgSig(1);
        end
        if (round(scanIDs(id)-floor(scanIDs(id)),1) == .4)
            lsx{3}{end+1} = scanIDs(id);%*80e-3;
            lsy{3}{end+1} = AvgSig(id);%/AvgSig(31);
            lserr{3}{end+1} = AvgSig_err(id);%/AvgSig(31);
        end
        if (round(scanIDs(id)-floor(scanIDs(id)),1) == .5)
            lsx{4}{end+1} = scanIDs(id);%*80e-3;
            lsy{4}{end+1} = AvgSig(id);%/AvgSig(17);
            lserr{4}{end+1} = AvgSig_err(id);%/AvgSig(1);
        end
        if (round(scanIDs(id)-floor(scanIDs(id)),1) == .6)
            lsx{5}{end+1} = scanIDs(id);%*80e-3;
            lsy{5}{end+1} = AvgSig(id);%/AvgSig(33);
            lserr{5}{end+1} = AvgSig_err(id);%/AvgSig(33);
        end
        if (round(scanIDs(id)-floor(scanIDs(id)),1) == .7)
            lsx{6}{end+1} = scanIDs(id);%*80e-3;
            lsy{6}{end+1} = AvgSig(id);%/AvgSig(48);
            lserr{6}{end+1} = AvgSig_err(id);%/AvgSig(48);
        end
        if (round(scanIDs(id)-floor(scanIDs(id)),1) == .8)
            lsx{7}{end+1} = scanIDs(id);%*80e-3;
            lsy{7}{end+1} = AvgSig(id);%/AvgSig(49);
            lserr{7}{end+1} = AvgSig_err(id);%/AvgSig(49);
        end
        if (round(scanIDs(id)-floor(scanIDs(id)),1) == .9)
            lsx{8}{end+1} = scanIDs(id);%*80e-3;
            lsy{8}{end+1} = AvgSig(id);%/AvgSig(end);
            lserr{8}{end+1} = AvgSig_err(id);%/AvgSig(end);
        end


        %%%Original code here
        %    errorbar(scanIDs*80e-3, AvgSig, AvgSig_err,...
        %        'LineStyle','none',...
        %        'Marker', analyVar.MARKERS2(1),...
        %        'MarkerSize', analyVar.markerSize,...
        %        'MarkerFaceColor', analyVar.COLORS(1,:),...
        %        'MarkerEdgeColor', 'none',...
        %        'Color', analyVar.COLORS(1,:));
    end

    %Plot all the different groups depening on how many stated above
    %labels = {"Coil ON 65A, MOT OFF, ZM ON", "Coil ON 65 A, MOT OFF, ZM OFF", "Coil OFF, MOT OFF", "Coil ON 65 A, MOT ON", "Coil OFF, MOT ON", "Coil ON 30 A, MOT OFF, ZM OFF", "Coil ON 15 A, MOT OFF, ZM OFF"};
    labels = {"Fluorescence Image Number", "Absorption Image Number", "MOT Coil = 70A (reverse Polarity)", "MOT Coil = 70A", "MOT Coil = 60A", "MOT Coil = 60A (reverse Polarity)", "MOT Coil = 65A", "MOT Coil = 65A (reverse Polarity)"}
    Z_current = [0 2 4 6 8 10 12 13]
    disp(Z_current)

    figure;
    hold on;
    for plots = 1:numberOfPlots

        x = cell2mat(lsx{plots});
        y = cell2mat(lsy{plots});
        err = cell2mat(lserr{plots});
        errorbar(x, y, err,...
                'LineStyle','none',...
                'Marker', analyVar.MARKERS2(1),...
                'MarkerSize', analyVar.markerSize,...
                'MarkerFaceColor', analyVar.COLORS(plots,:),...
                'MarkerEdgeColor', 'none',...
                'Color', analyVar.COLORS(plots,:));
        title('Atom Numbers for Fluo and Abs')
        xlabel('File Number')
        ylabel('Number Atoms (Counted with Fast Fitting in LabView)')
    end
    legend(labels, 'Location','northeastoutside')
    hold off;
    %labels = {"Coil ON 65 A, MOT OFF, ZM OFF", "Coil OFF, MOT OFF", "Coil ON 30 A, MOT OFF, ZM OFF", "Coil ON 15 A, MOT OFF, ZM OFF"};
    % figure;
    % hold on;
    % for plots = 1:numberOfPlots
    %     if(plots == 1)
    %         continue
    %     end
    %     if(plots == 4)
    %         continue
    %     end
    %     if(plots == 5)
    %         continue
    %     end
    %     x = cell2mat(lsx{plots});
    %     y = cell2mat(lsy{plots});
    %     err = cell2mat(lserr{plots});
    %     errorbar(x, y, err,...
    %             'LineStyle','none',...
    %             'Marker', analyVar.MARKERS2(1),...
    %             'MarkerSize', analyVar.markerSize,...
    %             'MarkerFaceColor', analyVar.COLORS(plots,:),...
    %             'MarkerEdgeColor', 'none',...
    %             'Color', analyVar.COLORS(plots,:));
    % end
    % 
    % for plots = 1:numberOfPlots
    %    if(plots == 1)
    %        continue
    %    end
    %    if(plots == 4)
    %        continue
    %    end
    %    if(plots == 5)
    %        continue
    %    end
    %    x = cell2mat(lsx{plots});
    %    y = cell2mat(lsy{plots});
    %    err = cell2mat(lserr{plots});
    %    errorbar(x, y, err,...
    %            'LineStyle','none',...
    %            'Marker', analyVar.MARKERS2(1),...
    %            'MarkerSize', analyVar.markerSize,...
    %            'MarkerFaceColor', analyVar.COLORS(plots,:),...
    %            'MarkerEdgeColor', 'none',...
    %            'Color', analyVar.COLORS(plots,:));
    % end
    % legend(labels)
    % title('SFI signal dependence vs time of experiment')
    % xlabel('Total time for MCS Data (ms)')
    % ylabel('Total MCS Counts')
    % hold off

    % figure;
    % hold on;
    % for id = 1:length(scanIDs)
    %     plot(x{id}, y{id}/trapz(x{id},y{id}),...
    %         'LineStyle','-',...
    %         'Marker', analyVar.MARKERS2(id),...
    %         'MarkerSize', analyVar.markerSize,...
    %         'MarkerFaceColor', analyVar.COLORS(id,:),...
    %         'MarkerEdgeColor', 'none',...
    %         'Color', analyVar.COLORS(id,:));
    % end
    % legend(num2str(scanIDs))
    % title('Trapping- Scanning Mot coil Off time - 60 1D2 Line')
    % xlabel('826 nm Synth with doubler ON [MHz]')
    % ylabel('Normalized by total signal MCS Counts')
    % hold off
    funcOut.analyVar = analyVar;
    funcOut.indivDataset = indivDataset;
    funcOut.avgDataset = avgDataset;
end