Plots

f_plot

Code

 1function f_plot(rst,stg,mmf)
 2
 3% Inform the user that the plots are being done
 4disp("Plotting ...")
 5
 6data_model = mmf.model.data.data_model;
 7
 8% Import the data on the first run
 9load(data_model,'Data','sbtab')
10
11% Generate figure with Scores
12if isfield(rst,'diag')
13    f_plot_scores(rst.diag,stg,sbtab)
14end
15
16% Generate figure with Inputs
17if isfield(rst,'diag')
18    f_plot_inputs(rst.diag,stg,sbtab)
19end
20
21% Generate figure with Outputs
22if isfield(rst,'diag')
23    f_plot_outputs(rst.diag,stg,sbtab,Data,mmf)
24end
25
26% Generate figure with input and Output of all experiments
27if isfield(rst,'diag')
28    f_plot_in_out(rst.diag,stg,sbtab,Data)
29end
30
31% Generate figure with optimization results
32if isfield(rst,'opt')
33    f_plot_opt(rst,stg)
34end
35
36% Generate figures for Sensitivity Analysis
37if isfield(rst,'gsa')
38    f_plot_gsa_sensitivities(rst.gsa,stg,sbtab);
39end
40end

The function that calls all the custom plot functions when appropriate Plots diagnosis that are important to understand if everything is working as it was supposed, it , expected outputs, observed outputs and scores for the models and conditions specified.

  • Inputs - rst, stg

  • Outputs

    Figure Scores

    _images/Scores_example.png

    Total scores and scores per dataset given the parameters specified in stg.pa

    Code Figure Scores

     1function f_plot_scores(rst,stg,sbtab)
 2set(0,'defaultTextFontName', 'Helvetica')
 3set(0,'defaultAxesFontName', 'Helvetica')
 4
 5% Generates a figure with Scores
 6
 7% Inform the user that fig1 is being ploted
 8disp("Plotting Scores")
 9
10%Closes previous instances of the figure and generates a new one
11figHandles = findobj('type', 'figure', 'name', 'Scores');
12close(figHandles);
13figure('WindowStyle', 'docked','Name','Scores','NumberTitle', 'off');
14
15% Generate top plot of figure 1
16subplot(4,1,1)
17
18% Plot the total scores of each parameter array to test
19scatter(stg.pat,[rst(stg.pat).st],20,'filled')
20ylabel('Total Score')
21set(gca,'xtick',[])
22set(gca,'FontSize',10,'Fontweight','bold')
23
24% Choose correct title according to settings
25if stg.useLog == 1
26    title("Sum of the Log base 10 of the Score of each Experimental Output")
27elseif stg.useLog == 2
28    title("Sum of the Log base 10 of the Score of each Experiment")
29elseif stg.useLog == 3
30    title("Log base 10 of sum of the Score of all Experiments")
31elseif stg.useLog == 4 || stg.useLog == 0
32    title("Sum of the Score of all Experiments")
33end
34
35% Choose the bounds for the x axis so it aligns with the bottom plot
36xlim([min(stg.pat)-0.5 max(stg.pat)+0.5])
37
38% Generate bottom plot of figure 1
39subplot(4,1,[2,3,4])
40
41% Generate labels for left of heatmap (Experiment number Dataset number)
42label = [];
43
44% Iterate over the number of experiments
45for n = stg.exprun
46    
47    % Iterate over the number of datasets in each experiment
48    for j = 1:size(sbtab.datasets(n).output,2)
49        label{size(label,2)+1} = {strrep("E" + (n-1) + " " + ...
50            string(rst(max(stg.pat)).simd{1,n}.DataNames(...
51            end-size(sbtab.datasets(n).output,2)+j)),"_","\_")};
52    end
53end
54
55% Choose wether to use the score of each dataset or its log base 10
56% according to settings
57% if stg.useLog == 1 || stg.useLog == 4
58heatline = [];
59
60% Iterate over the number of parameter arrays to test
61for k = stg.pat
62    heatpoint{k} = [];
63    
64    % Iterate over the number of experiments
65    for n = stg.exprun
66        
67        % Get the score of each dataset
68        heatpoint{k} = [heatpoint{k},rst(k).sd{n,1}];
69    end
70    
71    % Combine heatpoints in order to correctly display heatmap
72    heatline = [heatline;heatpoint{k}];
73end
74
75% Plot the heatmap
76h = heatmap(transpose(heatline),'Colormap',turbo,'YDisplayLabels',label,...
77    'GridVisible','off','FontSize',10);
78h.CellLabelFormat = '%.2e';
79
80title("Score of each Experimental Output")
81h.XLabel = 'Parameter arrays being tested';
82h.YLabel = 'Experimental Outputs';
83
84end

    Figure Inputs

    _images/Inputs_example.png

    Checks inputs to the model

    Code Figure Inputs

     1function f_plot_inputs(rst,stg,sbtab)
 2% Generates a figure with Inputs, one subplot per experiment
 3
 4% Inform the user that fig2 is being ploted
 5disp("Plotting Inputs")
 6
 7plot_n = 1;
 8fig_n = 0;
 9% Iterate over the number of experiments
10for n = stg.exprun
11    
12    % Generate the right amount of figures for all plots and calculates
13    % proper subploting position
14    fig_n = f_get_subplot(size(stg.exprun,2),plot_n,fig_n,"Inputs");
15    
16    plot_n = plot_n +1;
17    
18    hold on
19    
20    % Iterate over the number of inputs in each experiment
21    for j = 1:size(sbtab.datasets(n).input,2)
22        
23        % Iterate over the number of parameter arrays to test
24        for m = stg.pat
25            
26            % (Until a non broken simulation is found)
27            if rst(m).simd{1,n} ~= 0
28                
29                % Plot the inputs to each experiment
30                plot(rst(m).simd{1,n}.Time,rst(m).simd{1,n}.Data(1:end,...
31                    str2double(strrep(sbtab.datasets(n).input(j),'S',''))+1),'LineWidth',1.5)
32                
33                % Get the correct label for each input of the experiment
34                labelfig2(j) = rst(m).simd{1,n}.DataNames(str2double(...
35                    strrep(sbtab.datasets(n).input(j),'S',''))+1);
36                                  
37                ylabel(string(rst(m).simd{1,n}.DataInfo{...
38                    str2double(strrep(sbtab.datasets(n).input(j),'S',''))+1,1}.Units))
39                
40                break
41            end
42        end
43    end
44    
45    xlabel('seconds') 
46    % Add a legend to each plot
47    legend(labelfig2)
48    legend boxoff
49    clear labelfig2
50    
51    ylim([0 inf])
52    
53    % Add a title to each plot
54    title("E"+(n-1))
55    
56    hold off
57end
58
59end

    Figure Outputs

    _images/Outputs_example.png

    Expected outputs, observed outputs

    Code Figure Outputs

      1function f_plot_outputs(rst,stg,sbtab,Data,mmf)
  2% Generates a figure with Outputs, one subplot per experimental output
  3
  4% Inform the user that fig3 is being ploted
  5disp("Plotting Outputs")
  6
  7% Get the total number of outputs to set the total number of plots
  8[plot_tn,~] = f_get_outputs(stg,sbtab);
  9plot_n = 1;
 10fig_n = 0;
 11
 12% Iterate over the number of experiments
 13for n = stg.exprun
 14    
 15    % Iterate over the number of datasets in each experiment
 16    for j = 1:size(sbtab.datasets(n).output,2)
 17        
 18        % Generate the right amount of figures for all plots and calculates
 19        % proper subploting position
 20        fig_n = f_get_subplot(plot_tn,plot_n,fig_n,"Outputs");
 21        
 22        % Add a legend to the figure
 23        if mod(plot_n,24) == 1
 24            Lgnd = legend('show');
 25            Lgnd.Position(1) = 0;
 26            Lgnd.Position(2) = 0.5;
 27            legend boxoff
 28        end
 29        
 30        plot_n = plot_n + 1;
 31        
 32        hold on
 33        
 34        % Iterate over the number of parameter arrays to test
 35        for m = stg.pat
 36            % (Until a non broken simulation is found)
 37            if rst(m).simd{1,n} ~= 0
 38                
 39                time = rst(m).simd{1,n}.Time;
 40                data = Data(n).Experiment.x(:,j);
 41                
 42                data_SD = Data(n).Experiment.x_SD(:,j);
 43                
 44                % Plot the outputs to each dataset (new subplots) as they
 45                % are given in the data provided in sbtab
 46                scatter(time,data,'filled','k',...
 47                    'DisplayName','data')
 48                
 49                errorbar(time,data,data_SD, 'vertical',	'k', 'LineStyle', 'none','LineWidth',1);
 50                
 51                break
 52            end
 53        end
 54        
 55        % Iterate over the number of parameter arrays to test
 56        for m = stg.pat
 57            
 58            % Plot only if the simulation was successful
 59            if rst(m).simd{1,n} ~= 0
 60                
 61                time = rst(m).simd{1,n}.Time;
 62                [sim_results,~] = f_normalize(rst(m),stg,n,j,mmf);
 63                if stg.simdetail
 64                    time_detailed = rst(m).simd{1,n+2*stg.expn}.Time;
 65                    [~,sim_results_detailed]= f_normalize(rst(m),stg,n,j,mmf);
 66                end
 67                
 68                % Plot the outputs to each dataset (new subplots) and
 69                % parameter array to test that are simulated using
 70                % Simbiology
 71                if stg.simdetail
 72                    plot(time_detailed,...
 73                        sim_results_detailed,'DisplayName',...
 74                        string("Parameter set "+m),'LineWidth',1.5)
 75                else
 76                    
 77                    plot(time,...
 78                        sim_results,'DisplayName',...
 79                        string("Parameter set "+m),'LineWidth',1.5)
 80                end
 81                
 82                ylabel(string(rst(m).simd{1,n}.DataInfo{end-...
 83                    size(sbtab.datasets(n).output,2)+j,1}.Units))
 84            end
 85        end
 86        
 87        hold off
 88        
 89        xlabel('seconds')
 90        
 91        if stg.simdetail
 92            ylim([min([0,min(sim_results_detailed),min(sim_results),min(data-data_SD),min(data)]) inf])
 93        else
 94            ylim([min([0,min(sim_results),min(data-data_SD),min(data)]) inf])
 95        end
 96        
 97        % Choose correct title according to settings
 98        if stg.plotoln == 1
 99            title("E" + (n-1) + " " +...
100                strrep(string(sbtab.datasets(n).output_name{1,j}),'_','\_'))
101        else
102            title("E" + (n-1) + " " +...
103                string(sbtab.datasets(n).output{1,j}))
104        end
105        
106        % Choose number of decimal places for y axis
107        ytickformat('%.2g')
108    end
109end
110end

    Figure Input and Outputs per experiment

    _images/Inputs_Outputs_example.png

    Combined figure of the inputs and outputs for each experiment, on the left side we have the inputs of the experiment and on the right side the outputs

    Code Figure Input and Outputs

      1function f_plot_in_out(rst,stg,sbtab,Data)
  2% Generates a figure with input and Output of all experiments on the left
  3% side it plots the inputs of the experiment and on the right side it plots
  4% the outputs
  5
  6for n = stg.exprun
  7    
  8    helper = 1;
  9    f_plot_in_out_left(rst,stg,sbtab,helper,...
 10        size(sbtab.datasets(n).output,2) > 4)
 11    
 12    for j = 1:size(sbtab.datasets(n).output,2)
 13        
 14        if j/4 > helper
 15            helper = helper +1;
 16            f_plot_in_out_left(rst,stg,sbtab,helper,...
 17                size(sbtab.datasets(n).output,2) > 4)
 18        end
 19        
 20        if size(sbtab.datasets(n).output,2) == 1
 21            subplot(1,2,j+ceil(j/(2/2))*1)
 22        elseif size(sbtab.datasets(n).output,2) == 2
 23            subplot(2,2,j+ceil(j/(2/2))*1)
 24        elseif size(sbtab.datasets(n).output,2) > 2 &&...
 25                size(sbtab.datasets(n).output,2) <= 4
 26            subplot(2,4,j+ceil(j/(4/2))*2)
 27        elseif size(sbtab.datasets(n).output,2) > 4
 28            subplot(2,4,j+ceil(j/(4/2))*2-helper*8+8)
 29        end
 30        
 31        hold on
 32        
 33        % Iterate over the number of parameter arrays to test
 34        for m = stg.pat
 35            % (Until a non broken simulation is found)
 36            if rst(m).simd{1,n} ~= 0
 37                
 38                % Plot the outputs to each dataset (new subplots) as they
 39                % are given in the data provided in sbtab
 40                
 41                time = rst(m).simd{1,n}.Time;
 42                data = Data(n).Experiment.x(:,j);
 43                data_SD = Data(n).Experiment.x_SD(:,j);
 44                
 45                scatter(time,data,'filled','k',...
 46                    'DisplayName','data')
 47                
 48                errorbar(time,data,data_SD, 'vertical',	'k', 'LineStyle', 'none','LineWidth',1);
 49                break
 50            end
 51        end
 52        % Iterate over the number of parameter arrays to test
 53        for m = stg.pat
 54            
 55            % Plot only if the simulation was successful
 56            if rst(m).simd{1,n} ~= 0
 57                
 58                time = rst(m).simd{1,n}.Time;
 59                [sim_results] = f_normalize(rst(m),stg,n,j);
 60                
 61                
 62                if stg.simdetail
 63                    time_detailed = rst(m).simd{1,n+2*stg.expn}.Time;
 64                    [~,sim_results_detailed]= f_normalize(rst(m),stg,n,j);
 65                end
 66                
 67                % Plot the outputs to each dataset (new subplots) and
 68                % parameter array to test that are simulated using
 69                % Simbiology
 70                if stg.simdetail
 71                    plot(time_detailed,...
 72                        sim_results_detailed,'DisplayName',...
 73                        string("Parameter set "+m),'LineWidth',1.5)
 74                else
 75                    plot(time,...
 76                        sim_results,...
 77                        'DisplayName',string("Parameter set "+m),...
 78                        'LineWidth',1.5)
 79                end
 80                
 81                ylabel(string(rst(m).simd{1,n}.DataInfo{end-...
 82                    size(sbtab.datasets(n).output,2)+j,1}.Units),...
 83                    'FontSize', 12,'Fontweight','bold')
 84            end
 85        end
 86        
 87        hold off
 88        
 89        set(gca,'FontSize',12,'Fontweight','bold')
 90        
 91        if stg.simdetail
 92            ylim([min([0,min(sim_results_detailed),min(sim_results),min(data-data_SD),min(data)]) inf])
 93        else
 94            ylim([min([0,min(sim_results),min(data-data_SD),min(data)]) inf])
 95        end
 96        
 97        xlabel('seconds','FontSize', 12,'Fontweight','bold')
 98        
 99        % Choose correct title according to settings
100        if stg.plotoln == 1
101            title(strrep(string(sbtab.datasets(n).output_name{1,j}),'_',...
102                '\_'),'FontSize', 16,'Fontweight','bold')
103        else
104            title(string(sbtab.datasets(n).output{1,j}),'FontSize', 16,...
105                'Fontweight','bold')
106        end
107        
108        % Choose number of decimal places for y axis
109        ytickformat('%.2g')
110    end
111end
112
113    function f_plot_in_out_left(rst,stg,sbtab,helper,reuse)
114        if reuse
115            figHandles = findobj('type', 'figure', 'name', "E " + (n-1) +...
116                " " + helper);
117            close(figHandles);
118            figure('WindowStyle', 'docked','Name', "E " + (n-1)+ " " +...
119                helper,'NumberTitle', 'off');
120            sgtitle( "Experiment " + (n-1) + " " + helper + "  (E " +...
121                (n-1) + " " + helper +")",'FontSize', 28);
122        else
123            figHandles = findobj('type', 'figure', 'name', "E " + (n-1));
124            close(figHandles);
125            figure('WindowStyle', 'docked','Name', "E " + (n-1),...
126                'NumberTitle', 'off');
127            sgtitle( "Experiment " + (n-1) + "  (E " + (n-1) +...
128                ")",'FontSize', 28);
129        end
130        
131        subplot(2,4,[1,2,5,6])
132        
133        hold on
134        for o = 1:size(sbtab.datasets(n).input,2)
135            for p = stg.pat
136                
137                % (Until a non broken simulation is found)
138                if rst(p).simd{1,n} ~= 0
139                    % Plot the inputs to each experiment
140                    plot(rst(p).simd{1,n}.Time,rst(p).simd{1,n}.Data(1:end,...
141                        str2double(strrep(sbtab.datasets(n).input(o),'S','')...
142                        )+1),'LineWidth',1.5)
143                    
144                    % Get the correct label for each input of the
145                    % experiment
146                    labelfig2(o) = rst(p).simd{1,n}.DataNames(str2double(...
147                        strrep(sbtab.datasets(n).input(o),'S',''))+1);
148                    
149                    ylabel(string(rst(p).simd{1,n}.DataInfo{...
150                        str2double(strrep(sbtab.datasets(n).input(o),'S',''))+1,1}.Units),...
151                        'FontSize', 12,'Fontweight','bold')
152                    
153                    
154                    break
155                end
156            end
157            
158        end
159        
160        set(gca,'FontSize',12,'Fontweight','bold')
161        
162        xlabel('seconds','FontSize', 12,'Fontweight','bold')
163        % Add a legend to each plot
164        legend(labelfig2,'FontSize', 16,'Fontweight','bold')
165        legend boxoff
166        clear labelfig2
167        
168        ylim([0 inf])
169        
170        % Add a title to each plot
171        title("Inputs",'FontSize', 18,'Fontweight','bold')
172        
173        hold off
174    end
175end

    Figure Sensitivity Analysis \(S_{i}\)

    _images/SA_SI_sd_example.png

    Figure Sensitivity Analysis \(S_{Ti}\)

    _images/SA_STI_sd_example.png

    Code figures SA

      1function f_plot_gsa_sensitivities(rst,stg,sbtab)
  2% Generates figures for Sensitivity Analysis
  3
  4% Get the total number of outputs
  5[~,outputNames.sd] = f_get_outputs(stg,sbtab);
  6
  7for n = 1:size(outputNames.sd,2)
  8    outputNames.sd{n}{:} = strrep(outputNames.sd{n}{:},"_","\_");
  9end
 10for n = stg.exprun
 11    outputNames.se{n} = "E " + string(n-1);
 12end
 13
 14outputNames.xfinal = outputNames.sd;
 15
 16parNames = cell(1,stg.parnum);
 17parNames2 = cell(1,stg.parnum);
 18
 19for n = 1:stg.parnum
 20    parNames{n} = char("P" + find(stg.partest==n));
 21end
 22
 23for n = 1:size(parNames,2)
 24    parNames2{n} = string(parNames{n}(1,:));
 25    for m = 2:size(parNames{n},1)
 26        parNames2{n} = string(parNames2{n}) + ", " +...
 27            string(parNames{n}(m,:));
 28    end
 29end
 30
 31% Bootstrapping quartile mean of first order Sensitivity index for score
 32% per Experimental Output
 33f_generate_plot(rst,stg,outputNames,parNames2,...
 34    "Si seo bm",...
 35    "First order Sensitivities calculated using the Score of each Experimental Output  (Bootstrapping Mean)",...
 36    "outputNames.sd",...
 37    "transpose(reshape(mean(rst.SiQ.sd(:,:,1:stg.parnum)),[size(rst.SiQ.sd,2),size(rst.SiQ.sd,3)]))")
 38
 39% Bootstrapping quartile mean of total order Sensitivity index for score
 40% per Experimental Output
 41f_generate_plot(rst,stg,outputNames,parNames2,"SiT seo bm",...
 42    "Total order Sensitivities calculated using the Score of each Experimental Output (Bootstrapping Mean)",...
 43    "outputNames.sd",...
 44    "transpose(reshape(mean(rst.SiTQ.sd(:,:,1:stg.parnum)),[size(rst.SiQ.sd,2),size(rst.SiQ.sd,3)]))")
 45
 46% Bootstrapping quartile mean of first order Sensitivity index for score
 47% per Experiments
 48f_generate_plot(rst,stg,outputNames,parNames2,"Si se bm",...
 49    "First order Sensitivities calculated using the Score of each Experiment(Bootstrapping Mean)",...
 50    "outputNames.se",...
 51    "transpose(reshape(mean(rst.SiQ.se(:,:,1:stg.parnum)),[size(rst.SiQ.se,2),size(rst.SiQ.se,3)]))")
 52
 53% Bootstrapping quartile mean of total order Sensitivity index for score
 54% per Experiments
 55f_generate_plot(rst,stg,outputNames,parNames2,"SiT se bm",...
 56    "Total order Sensitivities calculated using the Score of each Experiment (Bootstrapping Mean)",...
 57    "outputNames.se",...
 58    "transpose(reshape(mean(rst.SiTQ.se(:,:,1:stg.parnum)),[size(rst.SiQ.se,2),size(rst.SiQ.se,3)]))")
 59
 60% Bootstrapping quartile mean of first order Sensitivity index for the
 61% final points of the simulations for the output beeing measured
 62f_generate_plot(rst,stg,outputNames,parNames2,"Si xfinal bm",...
 63    "First order Sensitivities calculated using the final value of each Experimental Output (Bootstrapping Mean)",...
 64    "outputNames.xfinal",...
 65    "transpose(reshape(mean(rst.SiQ.xfinal(:,:,1:stg.parnum)),[size(rst.SiQ.xfinal,2),size(rst.SiQ.xfinal,3)]))")
 66
 67% Bootstrapping quartile mean of total order Sensitivity index for the
 68% final points of the simulations for the output beeing measured
 69f_generate_plot(rst,stg,outputNames,parNames2,"SiT xfinal bm",...
 70    "Total order Sensitivities calculated using the final value of each Experimental Output (Bootstrapping Mean)",...
 71    "outputNames.xfinal",...
 72    "transpose(reshape(mean(rst.SiTQ.xfinal(:,:,1:stg.parnum)),[size(rst.SiQ.xfinal,2),size(rst.SiQ.xfinal,3)]))")
 73
 74figHandles = findobj('type', 'figure', 'name', 'Si,SiT');
 75close(figHandles);
 76figure('WindowStyle', 'docked','Name','Si,SiT', 'NumberTitle', 'off');
 77
 78for n = 1:size(parNames2,2)
 79    a{n} = char(parNames2{n});
 80end
 81
 82a = categorical(a,a);
 83
 84bar(a,[transpose(rst.Si.st(:,1:stg.parnum)),...
 85    transpose(rst.SiT.st(:,1:stg.parnum))])
 86xlabel('Parameters');
 87ylabel('Sensitivity');
 88title('Sensitivities calculated using the sum of the Score of all Experiments');
 89legend({'SI','SIT'});
 90legend boxoff
 91
 92figHandles = findobj('type', 'figure', 'name', 'Si,SiT b');
 93close(figHandles);
 94figure('WindowStyle', 'docked','Name','Si,SiT b', 'NumberTitle', 'off');
 95
 96T = [];
 97
 98for n = 1:size(a,2)
 99    for m = 1:size(rst.SiQ.st(:,n),1)
100 T = [T;table(rst.SiQ.st(m,n),a(n),"Si")];
101    end
102end
103for n = 1:size(a,2)
104    for m = 1:size(rst.SiTQ.st(:,n),1)
105 T = [T;table(rst.SiTQ.st(m,n),a(n),"SiT")];
106    end
107end
108
109boxchart(T.Var2,T.Var1,'GroupByColor',T.Var3,'MarkerStyle','.','JitterOutliers','on')
110xlabel('Parameters');
111ylabel('Sensitivity');
112title('Sensitivities calculated using the sum of the Score of all Experiments (Bootstrapping)');
113legend({'Si','SiT'},'Location','best');
114legend boxoff
115end
116
117function f_generate_plot(rst,stg,outputNames,parNames2,name,title,...
118    helprer1,helprer2)
119
120eval("figHandles = findobj('type', 'figure', 'name', '" + name + "');")
121close(figHandles);
122eval("figure('WindowStyle', 'docked','Name','" + name +...
123    "','NumberTitle', 'off');")
124
125heatmap_fixer = eval(helprer1);
126heatmap_fixer=heatmap_fixer(~cellfun('isempty',heatmap_fixer));
127
128heatmap_fixer2 = eval(helprer2);
129heatmap_fixer2 = heatmap_fixer2(:,all(~isnan(heatmap_fixer2)));
130
131h = heatmap(heatmap_fixer,parNames2,heatmap_fixer2,'Colormap',turbo,...
132    'ColorLimits',[0 1],'GridVisible','off');
133h.CellLabelFormat = '%.2f';
134
135eval(" h.Title = """ + title + """;")
136h.XLabel = 'Outputs';
137h.YLabel = 'Parameters';
138end

  • Calls

  • Loads - data.mat

f_get_subplot

Code

 1function fig_n = f_get_subplot(plot_tn,plot_n,fig_n,fig_name)
 2
 3size_x = 4;
 4size_y = 6;
 5size_t = 24;
 6ratio_1 = 2;
 7ratio_2 = 3;
 8
 9% If the amount of plots is bigger thatn the maximum amount of plots per
10% figure subdivide the plots to more than one figure
11if plot_tn > 24
12    
13    % Generate a new figure for the first plot and each time the number of
14    % plots is greater than figure number divided by max plot number per
15    % figure
16    if mod(plot_n-1,24) == 0
17        
18        fig_n = fig_n + 1;
19        
20        %Close previous instances of the figure and generates a new one
21        figHandles = findobj('type', 'figure', 'name', fig_name + " " + fig_n);
22        close(figHandles);
23        figure('WindowStyle', 'docked','Name', fig_name + " " + fig_n,'NumberTitle', 'off');
24        sgtitle(fig_name + " " + fig_n);
25    end
26    
27    % Get the correct subploting position for each plot
28    if plot_tn/24 < fig_n
29        subplot(ceil(sqrt((plot_tn-(fig_n-1)*24)/6)*2),ceil(sqrt((plot_tn-(fig_n-1)*24)/6)*3),plot_n-(fig_n-1)*24)
30    else
31        subplot(ceil(sqrt(24/6)*2),ceil(sqrt(24/6)*3),plot_n-(fig_n-1)*24)
32    end
33    
34else
35    
36    % Generate a new figure for the first plot
37    if mod(plot_n-1,24) == 0
38        
39        %Close previous instances of the figure and generates a new one
40        figHandles = findobj('type', 'figure', 'name', fig_name);
41        close(figHandles);
42        figure('WindowStyle', 'docked','Name', fig_name, 'NumberTitle', 'off');
43        sgtitle(fig_name);
44        
45    end
46    
47    % Get the correct subploting position for each plot
48    subplot(ceil(sqrt(plot_tn/6)*2),ceil(sqrt(plot_tn/6)*3),plot_n)
49    
50end
51end

  • Inputs

  • Outputs

  • Calls

  • Loads