Stuff during JLT writing...

Classes/00_signals/Signal.m

@@ -348,6 +348,7 @@ classdef Signal
                 options.displayname = "";
                 options.color = [];
                 options.normalizeToNyquist = 0;
+                options.addDCoffset = 0;
                 options.normalizeTo0dB = 0;
                 options.max_num_lines = []; % Leave empty or omit to disable line rotation
                 options.fft_length = [];
@@ -415,6 +416,8 @@ classdef Signal
             ax = gca;
             hold on
 
+            p_dbm = p_dbm+options.addDCoffset;
+
             for s = 1:min(size(p_dbm))
                 if isempty(options.color)
                     plot(x_vec, p_dbm(:,s), 'DisplayName', options.displayname, 'LineWidth', 1);

Classes/01_transmit/ChannelFreqResp.m

@@ -206,7 +206,7 @@ classdef ChannelFreqResp < handle
 
         function plot(obj)
 
-            figure(55);
+            figure();
             clf;
 
             Havg = obj.H;
@@ -225,7 +225,7 @@ classdef ChannelFreqResp < handle
             xlim([0.2 .5*max(obj.faxis)*1e-9]);
             grid on;
 
-            figure(56);
+            figure();
             clf;
 
 
@@ -246,7 +246,7 @@ classdef ChannelFreqResp < handle
             xlim([0.2 .5*max(obj.faxis)*1e-9]); grid on;
 
             %%% plot for publication
-            figure(1234);
+            figure(101);
             hold all;
             box on;
             title('Magnitude Freq. Response');
@@ -269,6 +269,25 @@ classdef ChannelFreqResp < handle
             legend('Interpreter','latex')
             grid on;
 
+            % 
+            figure(100); hold on;
+            Havg = obj.H;
+            Havg = Havg./max(Havg);
+            Hall = obj.H_all;
+
+            for i = 1:size(Hall,1)
+                Hall(i,:) = Hall(i,:)./max(Hall(i,:));
+            end
+
+            %1)
+            col = cbrewer2('Paired',8);
+            hold all;box on;title('Magnitude Freq. Response');
+            plot(obj.faxis/1e9, 20*log10(abs(Hall)),'linewidth',0.1,'LineStyle','-','Color',col(1,:),'HandleVisibility','off') ;
+            xlim([0.2 .5*max(obj.faxis)*1e-9]);
+            plot(obj.faxis/1e9, 20*log10(abs(Havg)),'LineWidth',2,'Color',col(2,:));
+            grid on;
+
+
 
         end
 

Classes/Warehouse_class/classes/DataStorage.m

@@ -137,7 +137,21 @@ classdef DataStorage < handle
                     if ~isempty(tmp)
 
                         if isa(tmp,'double')
-                            value(i,:) = tmp ;
+                            try
+                                value(i,:) = tmp ;
+                            catch
+                                a = size(value,2);
+                                b = size(tmp,2);
+                                if a > b
+                                    value(i,:) =[tmp,NaN(1,a-b)] ;
+                                elseif a < b
+                                    value(i,:) = tmp(1:size(value,2)) ;
+                                else
+                                    error('unknwon case...')
+                                end
+
+                                
+                            end
                         elseif isa(tmp,'Signal') || isa(tmp,'struct') ||  isa(tmp,'Exfo_laser') ||  isa(tmp,'DC_supply')
                             if i == 1
                                 value = {};

Datatypes/clr.m

@@ -49,22 +49,5 @@ classdef clr
             hold off;
         end
 
-        function showSet(colorStruct)
-            % Show colors from a structure in a bar plot
-            names = fieldnames(colorStruct);
-            colors = cell2mat(struct2cell(colorStruct)');
-
-            figure;
-            hold on;
-            for i = 1:size(colors, 1)
-                fill([0 1 1 0], [i-1 i-1 i i], colors(i, :), 'EdgeColor', 'k');
-                text(1.1, i-0.5, names{i}, 'FontSize', 12, 'Interpreter', 'none');
-            end
-            ylim([0, size(colors, 1)]);
-            xlim([0, 1.5]);
-            axis off;
-            title('Color Preview');
-            hold off;
-        end
     end
 end

Functions/EQ_structures/dsp_runid.m

@@ -95,12 +95,12 @@ try
     adaption= 1;
     use_dd_mode = 1;
 
-    use_ffe         = 0;
+    use_ffe         = 1;
-    use_dfe         = 0;
+    use_dfe         = 1;
     use_vnle_mlse   = 1;
-    use_dbtgt       = 0;
+    use_dbtgt       = 1;
-    use_dbenc       = 0;
+    use_dbenc       = 1;
-    use_ml_mlse     = 0;
+    use_ml_mlse     = 1;
 
     addProcessingResultToDatabase = 0;
 
@@ -140,7 +140,12 @@ try
         % Preprocess signal
         Scpe_sig = preprocessSignal(Scpe_cell{r}, Symbols, fsym);
 
-        Scpe_sig.spectrum("fignum",2223,"normalizeTo0dB",1,"displayname",'Rx');
+        Scpe_sig.spectrum("fignum",200,"normalizeTo0dB",1,"displayname",'Rx','addDCoffset',-6);
+
+        Scpe_sig.spectrum("fignum",201,"normalizeTo0dB",0,"displayname",'Rx');
+
+        ylim([-30,3]);
+    	xlim([-5,100]);
         % Scpe_sig.spectrum("fignum",22233,"normalizeTo0dB",0,"displayname",'Rx');
         % Scpe_sig.eye(fsym,M,"fignum",1024);
 
@@ -239,10 +244,10 @@ try
             if use_ml_mlse
 
                 %ML-based MLSE (L=2)
-                mu_ml = 0.01; training_epochs = 250;
+                mu_ml = 0.01; training_epochs = 100;
                 ml_mlse_equalizer = ML_MLSE("epochs_tr",training_epochs,"epochs_dd",1, ...
                     "len_tr",length(Scpe_sig),"mu_dd",mu_ml,"mu_tr",mu_ml,"order",11,"sps",2, ...
-                    "traceback_depth",128,"L",2,"delta",4,"adaptive_mu",0);
+                    "traceback_depth",128,"L",1,"delta",4,"adaptive_mu",0);
 
                 [ml_mlse_results] = ml_mlse(ml_mlse_equalizer, M, Scpe_sig, Symbols, Tx_bits,"precode_mode",duob_mode);
                 output.mlmlse_package{r} = ml_mlse_results;

Functions/Job_Processing/preprocessSignal.m

@@ -16,9 +16,11 @@ Scpe_sig = Scpe_sig.resample("fs_out", 2*fsym);
 [Scpe_sig, ~] = Scpe_sig.tsynch("reference", Symbols, "fs_ref", fsym, "debug_plots", 0);
 
 % Apply Gaussian filter
+if 1 
 Scpe_sig = Filter('filtdegree', 8, "f_cutoff", Symbols.fs.*0.52, ...
                  "fs", Scpe_sig.fs, "filterType", filtertypes.gaussian, ...
                  "active", true).process(Scpe_sig);
+end
 
 % Remove DC offset
 Scpe_sig = Scpe_sig - mean(Scpe_sig.signal);

Functions/Lab_helper/loadFreqResp.m

@@ -1,5 +1,5 @@
 % Define the precomp path
-precomp_path = "C:\Users\sioe\Documents\MATLAB\imdd_simulation\projects\ECOC_2025\";
+precomp_path = "C:\Users\Silas\Documents\MATLAB\Datensätze\sioe_labor\precomp";
 
 % Step 1: Find all valid files (assume .mat files for ChannelFreqResp)
 fileList = dir(fullfile(precomp_path, '*.mat'));

Functions/Theory/Neuer Ordner/duobinary_histogram.m

@@ -1,51 +0,0 @@
-
-
-
-figure(2)
-tiledlayout(1,3)
-cols = linspecer(5);
-cnt = 1;
-for m = [4,6,8]
-
-    M = m;
-    fsym = 112e9;
-    fdac = 256e9;
-    
-    [Digi_sig,Symbols,Tx_bits] = PAMsource(...
-        "fsym",fsym,"M",M,"order",19,"useprbs",1,...
-        "fs_out",fdac,...
-        "applyclipping",0,"clipfactor",1.5,...
-        "applypulseform",0,"pulseformer",NaN,...
-        "randkey",33,...
-        "db_precode",1,"db_encode",0,...
-        "mrds_code",0,"mrds_blocklength",512).process();
-    
-    Symbols_pre = Duobinary().precode(Symbols);
-    
-    Symbols_db = Duobinary().encode(Symbols_pre);
-    
-    if M == 4
-        Symbols_db.signal = Symbols_db.signal .*sqrt(2.5);
-    elseif M == 6
-        Symbols_db.signal = Symbols_db.signal .*sqrt(5.8);
-    elseif M == 8
-        Symbols_db.signal = Symbols_db.signal .*sqrt(10.5);
-    end
-    
-    % figure(1)
-    % hold on
-    % histogram(Symbols_db.signal,"EdgeAlpha",0.3,"Normalization","probability");
-    
-    
-    % figure(1)
-    nexttile
-    hold on
-    bar(unique(Symbols_db.signal),histcounts(int32(Symbols_db.signal),"Normalization","probability"),"FaceColor",cols(cnt,:),"FaceAlpha",0.6,"BarWidth",1-(0.2*cnt),"LineWidth",0.5,"EdgeColor",'black','DisplayName',['Duobinary PAM-',num2str(M)]);
-    xticks(unique(Symbols_db.signal));
-    ylim([0 0.26]);
-    xlabel("Symbol")
-    
-
-    cnt = cnt+1,
-
-end

Functions/Theory/Neuer Ordner/duobinary_transferfunction.m

@@ -1,18 +0,0 @@
-
-
-% Define the filter taps
-h_ = {[1],[1 1],[1 2 1],[1 3 3 1]};
-
-for i = 1:length(h_)
-    h = h_{i};
-    
-    [H, w] = freqz(h, 1, 1024, 1);
-    
-    figure(1);
-    hold on
-    plot(w, 10*log10(abs(H)), 'LineWidth', 2,'DisplayName',['$(1+D)^2$']); %todo
-    xlabel('Normalized Frequency');
-    ylabel('Amplitude in dB');
-    grid on;
-    ylim([-20,10])
-end

Functions/beautifyBERplot.m

@@ -23,8 +23,8 @@ num_markers = length(markers);
 
 % --- style all lines consistently
 for i = 1:length(lines)
-    lines(i).LineWidth = 1.1;
+    lines(i).LineWidth = 1;
-    lines(i).LineStyle = '-';
+    % lines(i).LineStyle = '-';
     if string(lines(i).Marker) == "none"
         lines(i).Marker = markers{mod(i-1, num_markers) + 1};
     end
@@ -88,10 +88,23 @@ if options.logscale
     set(gca, 'YScale', 'log');
 end
 
+% --- Figure size in centimeters ---
+% width_pt  = 500;
+% height_pt = 300;
+% 
+% pt2cm = 0.03514598;   % TeX point → cm
+% width_cm  = width_pt  * pt2cm;   % = 8.85 cm
+% height_cm = height_pt * pt2cm;   % = 2.81 cm
+% 
+% set(gcf, 'Units', 'centimeters', 'Position', [2 2 width_cm height_cm]);
+% set(gcf, 'PaperUnits', 'centimeters', 'PaperPosition', [0 0 width_cm height_cm]);
+
+% --- Formatting ---
 set(findall(gca, '-property', 'Interpreter'), 'Interpreter', 'latex');
 set(gcf, 'Color', 'w');
 set(gca, 'Box', 'on', 'LineWidth', 0.8);
 grid on;
-set(gca, 'FontSize', 10, 'FontName', 'Times New Roman');
+set(gca, 'FontSize', 10, 'FontName', 'Latin Modern Roman');
+
 
 end

projects/HighSpeedExperiment_2024/Auswertung_JLT/ber_vs_rate.m

@@ -5,7 +5,7 @@ db = DBHandler("dataBase", [dataBase], "type", database_type);
 
 fp = QueryFilter();
 % fp.where('Runs', 'run_id','EQUALS', 987);
-M = 4;
+M = 6;
 fp.where('Runs', 'pam_level','EQUALS', M);
 % fp.where('Runs', 'bitrate','LESS_THAN', 310e9);
 fp.where('Runs', 'fiber_length','EQUALS', 2);
@@ -18,7 +18,7 @@ fp.where('Runs', 'wavelength','EQUALS', 1310);
 fp.where('Runs', 'rop_attenuation','EQUALS', 0);
 
 fields =  db.getTableFieldNames('power_state_info');
-fields = [fields; db.getTableFieldNames('dashboard_ungrouped_new')];
+fields = [fields; db.getTableFieldNames('dashboard_ungrouped_aug_nov_2025')];
 [dataTable,~] = db.queryDB(fp, fields);
 
 eqstructures = unique(dataTable.equalizer_structure);
@@ -29,7 +29,7 @@ show_bitrate = true;
 figure(5);
 hold on
 
-for eqs = [equalizer_structure.vnle, equalizer_structure.vnle_pf_mlse]
+for eqs = [equalizer_structure.vnle]
     
     % figure('Name',string([char(eqs),'']));
     % hold on
@@ -148,13 +148,14 @@ for eqs = [equalizer_structure.vnle, equalizer_structure.vnle_pf_mlse]
         
         xticks(xraw);
         if show_bitrate
-            xticks(200:25:500);
+        %     xticks(200:25:500);
-            xlim([350 500]);
+        %     xlim([350 500]);
+            xlim([min(xraw), max(xraw)]);
         else
             xlim([min(xraw), max(xraw)]);
         end
 
-        ylim([5e-4, 0.3]);
+        ylim([1e-4, 0.5]);
 
     end
     yline([2.2e-4, 4.85e-3, 2e-2],'LineWidth',1,'LineStyle','--','HandleVisibility','off');

projects/HighSpeedExperiment_2024/Auswertung_JLT/ber_vs_rate_only_best_configs.m

@@ -17,7 +17,7 @@ fp.where('Runs', 'wavelength','EQUALS', 1310);
 % fp.where('Runs', 'db_mode','EQUALS', 1);
 fp.where('Runs', 'rop_attenuation','EQUALS', 0);
 
-[dataTable,~] = db.queryDB(fp, db.getTableFieldNames('dashboard'));
+[dataTable,~] = db.queryDB(fp, db.getTableFieldNames('dashboard_ungrouped_after_nov_2025'));
 
 eqstructures = unique(dataTable.equalizer_structure);
 

projects/HighSpeedExperiment_2024/Auswertung_JLT/final/compare_ber_best_results.m

@@ -0,0 +1,223 @@
+
+
+database_type   = 'mysql';
+dataBase   = 'labor_highspeed';
+db = DBHandler("dataBase", [dataBase], "type", database_type);
+
+
+% M = 4;
+fp = QueryFilter();
+% fp.where('Runs', 'pam_level','EQUALS', M);
+fp.where('Runs', 'fiber_length','EQUALS', 2);
+fp.where('Runs', 'wavelength','LESS_THAN', 1312);
+% fp.where('Runs', 'db_mode','EQUALS', 1);         % 0 == high preemphasis // 1 == low preemphasis
+fp.where('Runs', 'rop_attenuation','EQUALS', 0);
+
+fields = db.getTableFieldNames('power_state_info');
+fields = [fields; db.getTableFieldNames('dashboard_ungrouped_alltime')]; %dashboard_ungrouped_after_nov_2025  dashboard_ungrouped_aug_nov_2025
+[dataTable,~] = db.queryDB(fp, fields);
+
+%%
+cfg = struct;
+cfg.x_axis = 'grossrate';          % 'symbol rate' | 'bitrate' | 'wavelength'  grossrate
+cfg.y_axis = 'BER';              % 'BER' | 'GMI' | 'AIR' | ...
+
+cfg.y_scale = 'auto';            % auto -> log for BER*, linear otherwise
+cfg.outlier = 'mad';             % simple, robust; 'none' or 'pctl' also available
+cfg.show_raw = false;
+cfg.show_spread = 'none';        % 'none' or 'iqr' or minmax
+cfg.agg = 'min';                % or 'median'
+cfg.show_precoded = 0;
+
+% cfg.fec_lines = [2.2e-4 4.85e-3 2e-2]; % optional
+cfg.fec_lines = [];
+cfg.plot.custom_colors = [
+    clr.Paired.red;
+    clr.Paired.blue;
+    clr.Paired.green;
+    clr.Paired.orange;
+    clr.Paired.purple
+    ];
+
+cfg.plot.custom_colors_scatter = [
+    clr.Paired.lightred;
+    clr.Paired.lightblue;
+    clr.Paired.lightgreen;
+    clr.Paired.lightorange;
+    clr.Paired.lightpurple
+    ];
+
+
+% New styling knobs
+cfg.plot.use_cbrewer2 = true;
+cfg.plot.colormap = 'Paired';
+cfg.plot.paired_dark_first = false;        % dark for lines, light for scatter
+cfg.plot.lineWidth = 2.0;
+cfg.plot.errWidth  = 1.2;
+cfg.plot.scatterAlpha = 0.35;
+cfg.plot.legendLocation = 'best';
+cfg.plot.fecLineWidth = 2.4;              % thicker FEC limits
+cfg.plot.lineStyle_pre_emph_on = '-';
+cfg.plot.lineStyle_pre_emph_off = '-';
+
+%% PLOT NGMI
+
+% Common cfg
+cfg.show_precoded = 1;
+cfg.group_by = {'equalizer_structure','pre_emph'};
+cfg.x_axis = 'grossrate';
+cfg.y_axis = 'NGMI';  % 'BER' | 'GMI' | 'AIR' | ...
+cfg.y_scale = 'lin';
+cfg.plot.custom_colors_scatter = [];
+cfg.plot.use_cbrewer2 = false;
+cfg.fec_lines = [];
+cfg.agg = 'max'; 
+
+cfg.figure_number = 45;
+% fig = figure(cfg.figure_number); 
+
+lambda = 1310;
+% PAM 4 
+cfg.plot.custom_colors = clr.Paired.red;
+cfg.plot.custom_linetypes = {'-'};
+cfg.filters = struct('is_mpi',0,'pam_level',4, ...
+    'equalizer_structure',equalizer_structure.vnle_db_mlse, ...
+    'pre_emph',0,'wavelength',lambda);
+cfg.show_precoded = 1;
+a = plot_measurements_gpt(dataTable, cfg);
+ngmi_pam4 = a.lines(1).YData;
+tp = TransmissionPerformance;
+netrates_vnle = tp.calculateNetRate(baudrate.* m, ...
+                                      'NGMI', ngmi_pam4, ...
+                                      'BER', BER_VNLE);
+
+cfg.plot.custom_colors = clr.Paired.red;
+cfg.plot.custom_linetypes = {'--'};
+cfg.filters = struct('is_mpi',0,'pam_level',4, ...
+    'equalizer_structure',equalizer_structure.vnle_db_mlse, ...
+    'pre_emph',0,'wavelength',1293);
+cfg.show_precoded = 1;
+plot_measurements_gpt(dataTable, cfg);
+
+% PAM 6
+cfg.plot.custom_colors = clr.Paired.blue;
+cfg.plot.custom_linetypes = {'-'};
+cfg.filters = struct('is_mpi',0,'pam_level',6, ...
+    'equalizer_structure',equalizer_structure.vnle_pf_mlse, ...
+    'pre_emph',1,'wavelength',lambda);
+cfg.show_precoded = 0;
+plot_measurements_gpt(dataTable, cfg);
+
+cfg.plot.custom_colors = clr.Paired.blue;
+cfg.plot.custom_linetypes = {'--'};
+cfg.filters = struct('is_mpi',0,'pam_level',6, ...
+    'equalizer_structure',equalizer_structure.vnle_pf_mlse, ...
+    'pre_emph',1,'wavelength',1293);
+cfg.show_precoded = 0;
+plot_measurements_gpt(dataTable, cfg);
+
+% PAM 8
+cfg.plot.custom_colors = clr.Paired.green;
+cfg.plot.custom_linetypes = {'-'};
+cfg.filters = struct('is_mpi',0,'pam_level',8, ...
+    'equalizer_structure',equalizer_structure.vnle_pf_mlse, ...
+    'pre_emph',1,'wavelength',lambda);
+cfg.show_precoded = 0;
+plot_measurements_gpt(dataTable, cfg);
+
+cfg.plot.custom_colors = clr.Paired.green;
+cfg.plot.custom_linetypes = {'--'};
+cfg.filters = struct('is_mpi',0,'pam_level',8, ...
+    'equalizer_structure',equalizer_structure.vnle_pf_mlse, ...
+    'pre_emph',1,'wavelength',1293);
+cfg.show_precoded = 0;
+plot_measurements_gpt(dataTable, cfg);
+
+beautifyBERplot
+ylim([0.87,1.01]);
+% xlim([290,480]);
+
+%% PLOT AIR
+
+% Common cfg
+cfg.show_precoded = 1;
+cfg.group_by = {'equalizer_structure','pre_emph'};
+cfg.x_axis = 'grossrate';
+cfg.y_axis = 'AIR';  % 'BER' | 'GMI' | 'AIR' | ...
+cfg.y_scale = 'lin';
+cfg.plot.custom_colors_scatter = [];
+cfg.plot.use_cbrewer2 = false;
+cfg.fec_lines = [];
+cfg.agg = 'max'; 
+
+cfg.figure_number = 47;
+% fig = figure(cfg.figure_number); 
+
+lambda = 1310;
+
+% PAM 4 
+cfg.plot.custom_colors = clr.Paired.red;
+cfg.plot.custom_linetypes = {'-'};
+cfg.filters = struct('is_mpi',0,'pam_level',4, ...
+    'equalizer_structure',equalizer_structure.vnle_db_mlse, ...
+    'pre_emph',0,'wavelength',lambda);
+cfg.show_precoded = 1;
+plot_measurements_gpt(dataTable, cfg);
+
+
+
+cfg.plot.custom_colors = clr.Paired.red;
+cfg.plot.custom_linetypes = {'--'};
+cfg.filters = struct('is_mpi',0,'pam_level',4, ...
+    'equalizer_structure',equalizer_structure.vnle_db_mlse, ...
+    'pre_emph',0,'wavelength',1293);
+cfg.show_precoded = 1;
+plot_measurements_gpt(dataTable, cfg);
+
+% PAM 6
+cfg.plot.custom_colors = clr.Paired.blue;
+cfg.plot.custom_linetypes = {'-'};
+cfg.filters = struct('is_mpi',0,'pam_level',6, ...
+    'equalizer_structure',equalizer_structure.vnle_pf_mlse, ...
+    'pre_emph',1,'wavelength',lambda);
+cfg.show_precoded = 0;
+plot_measurements_gpt(dataTable, cfg);
+
+cfg.plot.custom_colors = clr.Paired.blue;
+cfg.plot.custom_linetypes = {'--'};
+cfg.filters = struct('is_mpi',0,'pam_level',6, ...
+    'equalizer_structure',equalizer_structure.vnle_pf_mlse, ...
+    'pre_emph',1,'wavelength',1293);
+cfg.show_precoded = 0;
+plot_measurements_gpt(dataTable, cfg);
+
+% PAM 8
+cfg.plot.custom_colors = clr.Paired.green;
+cfg.plot.custom_linetypes = {'-'};
+cfg.filters = struct('is_mpi',0,'pam_level',8, ...
+    'equalizer_structure',equalizer_structure.vnle_pf_mlse, ...
+    'pre_emph',1,'wavelength',lambda);
+cfg.show_precoded = 0;
+plot_measurements_gpt(dataTable, cfg);
+
+cfg.plot.custom_colors = clr.Paired.green;
+cfg.plot.custom_linetypes = {'--'};
+cfg.filters = struct('is_mpi',0,'pam_level',8, ...
+    'equalizer_structure',equalizer_structure.vnle_pf_mlse, ...
+    'pre_emph',1,'wavelength',1293);
+cfg.show_precoded = 0;
+plot_measurements_gpt(dataTable, cfg);
+
+ax = gca;
+
+beautifyBERplot
+
+ylim([275,435]);
+xlim([290,480]);
+
+
+%%
+
+
+
+

projects/HighSpeedExperiment_2024/Auswertung_JLT/final/compare_ber_complete_results.m

@@ -0,0 +1,170 @@
+database_type   = 'mysql';
+dataBase   = 'labor_highspeed';
+db = DBHandler("dataBase", [dataBase], "type", database_type);
+
+
+% M = 4;
+fp = QueryFilter();
+% fp.where('Runs', 'pam_level','EQUALS', M);
+fp.where('Runs', 'fiber_length','EQUALS', 2);
+fp.where('Runs', 'wavelength','EQUALS', 1310);
+% fp.where('Runs', 'db_mode','EQUALS', 1);         % 0 == high preemphasis // 1 == low preemphasis
+fp.where('Runs', 'rop_attenuation','EQUALS', 0);
+
+fields = db.getTableFieldNames('power_state_info');
+fields = [fields; db.getTableFieldNames('dashboard_ungrouped_alltime')]; %dashboard_ungrouped_after_nov_2025  dashboard_ungrouped_aug_nov_2025 
+[dataTable,~] = db.queryDB(fp, fields);
+
+%% 
+cfg = struct;
+cfg.x_axis = 'grossrate';          % 'symbol rate' | 'bitrate' | 'wavelength'  grossrate
+cfg.y_axis = 'BER';              % 'BER' | 'GMI' | 'AIR' | ...
+
+cfg.y_scale = 'auto';            % auto -> log for BER*, linear otherwise
+cfg.outlier = 'mad';             % simple, robust; 'none' or 'pctl' also available
+cfg.show_raw = false;
+cfg.show_spread = 'none';        % 'none' or 'iqr' or minmax
+cfg.agg = 'min';                % or 'median'
+cfg.show_precoded = 0;
+
+% cfg.fec_lines = [2.2e-4 4.85e-3 2e-2]; % optional
+cfg.fec_lines = [];
+cfg.plot.custom_colors = [
+    clr.Paired.red;
+    clr.Paired.blue;
+    clr.Paired.green;
+    clr.Paired.orange;
+    clr.Paired.purple
+];
+
+cfg.plot.custom_colors_scatter = [
+    clr.Paired.lightred;
+    clr.Paired.lightblue;
+    clr.Paired.lightgreen;
+    clr.Paired.lightorange;
+    clr.Paired.lightpurple
+];
+
+
+% New styling knobs
+cfg.plot.use_cbrewer2 = true;
+cfg.plot.colormap = 'Paired';
+cfg.plot.paired_dark_first = false;        % dark for lines, light for scatter
+cfg.plot.lineWidth = 2.0;
+cfg.plot.errWidth  = 1.2;
+cfg.plot.scatterAlpha = 0.35;
+cfg.plot.legendLocation = 'best';
+cfg.plot.fecLineWidth = 2.4;              % thicker FEC limits
+cfg.plot.lineStyle_pre_emph_on = '-';
+cfg.plot.lineStyle_pre_emph_off = '-';
+
+
+%% Grid configuration
+rows = 3;             % PAM 4,6,8
+cols = 4;             % DSP schemes
+pam  = [4 6 8];
+
+cfg.figure_number = 46;
+fig = figure(cfg.figure_number); clf;
+
+% Create extremely compact tile layout
+t = tiledlayout(rows, cols, ...
+    'TileSpacing','compact', ...
+    'Padding','compact');
+
+% Common cfg
+cfg.show_precoded = 1;
+cfg.group_by = {'equalizer_structure','pre_emph'};
+cfg.x_axis = 'grossrate';
+cfg.y_axis = 'BER';
+cfg.y_scale = 'log';
+cfg.plot.custom_colors_scatter = [];
+cfg.plot.use_cbrewer2 = false;
+cfg.fec_lines = [];
+% DSP scheme definitions ---------------------------------------------
+DSP(1).name  = 'vnle';
+DSP(1).eq    = equalizer_structure.vnle;
+DSP(1).color = clr.Paired.red;
+DSP(1).lightcolor = clr.Paired.lightred;
+
+DSP(2).name  = 'VNLE PF MLSE';
+DSP(2).eq    = equalizer_structure.vnle_pf_mlse;
+DSP(2).color = clr.Paired.green;
+DSP(2).lightcolor = clr.Paired.lightgreen;
+
+DSP(3).name  = 'VNLE DB MLSE';
+DSP(3).eq    = equalizer_structure.vnle_db_mlse;
+DSP(3).color = clr.Paired.blue;
+DSP(3).lightcolor = clr.Paired.lightblue;
+
+DSP(4).name  = 'ML MLSE';
+DSP(4).eq    = equalizer_structure.ml_mlse;
+DSP(4).color = clr.Paired.purple;
+DSP(4).lightcolor = clr.Paired.lightpurple;
+
+
+% === Main nested loop: rows = PAM format, columns = DSP scheme ===
+for r = 1:rows
+    M = pam(r);
+
+    for c = 1:cols
+        ax = nexttile(t, (r-1)*cols + c);
+        cfg.ax = ax;
+
+        % ---- pre-emph = 1 (solid) ----
+        cfg.plot.custom_colors = DSP(c).lightcolor;
+        cfg.plot.custom_linetypes = {'-'};
+        cfg.filters = struct('is_mpi',0,'pam_level',M, ...
+            'equalizer_structure',DSP(c).eq, ...
+            'pre_emph',1);
+        plot_measurements_gpt(dataTable, cfg);
+
+        % ---- pre-emph = 0 (dashed) ----
+        cfg.plot.custom_colors = DSP(c).color;
+        cfg.plot.custom_linetypes = {'-'};
+        cfg.filters.pre_emph = 0;
+        plot_measurements_gpt(dataTable, cfg);
+
+        if M == 4
+            ylim([1e-5 0.2]);
+        else
+            ylim([6e-4 0.2]);
+        end
+
+        % % FEC limits
+        yline([2.2e-4 4.85e-3 2e-2],'LineWidth',1.1,'Color',[0.2 0.2 0.2], ...
+            'LineStyle',':','HandleVisibility','off');
+
+        % Axes prettification
+        beautifyBERplot;
+
+        % ===== Remove redundant labels =====
+        if c > 1
+            ax.YLabel = [];
+        end
+        if r < rows
+            ax.XLabel = [];
+        end
+
+        grid(ax,'on'); box(ax,'on');
+    end
+end
+
+%this is just a ranom size but fits and is fixed now!
+pos = 1e3.*[0.0983    0.6110    1.4113    0.4733];
+set(fig, 'Position', pos)
+
+
+
+
+%% === EXPORT TO TIKZ ===
+outfile = 'C:\Users\Silas\Documents\latex\JLT_400G copy\media\matlab2tikz\compare_pre_emphasis.tikz';
+
+matlab2tikz(outfile, ...
+    'width','\fwidth', ...
+    'height','\fheight', ...
+    'showInfo',false, ...
+    'extraAxisOptions',{ ...
+        'legend style={font=\footnotesize}', ...
+        'legend columns=1' ...
+    } );

projects/HighSpeedExperiment_2024/Auswertung_JLT/final/compare_pre_emphasis.m

@@ -0,0 +1,112 @@
+database_type   = 'mysql';
+dataBase   = 'labor_highspeed';
+db = DBHandler("dataBase", [dataBase], "type", database_type);
+
+
+M = 4;
+fp = QueryFilter();
+fp.where('Runs', 'pam_level','EQUALS', M);
+fp.where('Runs', 'fiber_length','EQUALS', 2);
+fp.where('Runs', 'wavelength','EQUALS', 1310);
+% fp.where('Runs', 'db_mode','EQUALS', 1);         % 0 == high preemphasis // 1 == low preemphasis
+fp.where('Runs', 'rop_attenuation','EQUALS', 0);
+
+fields = db.getTableFieldNames('power_state_info');
+fields = [fields; db.getTableFieldNames('dashboard_ungrouped_aug_nov_2025')]; %dashboard_ungrouped_after_nov_2025  dashboard_ungrouped_aug_nov_2025 
+[dataTable,~] = db.queryDB(fp, fields);
+
+%% 
+cfg = struct;
+cfg.x_axis = 'grossrate';          % 'symbol rate' | 'bitrate' | 'wavelength'  grossrate
+cfg.y_axis = 'BER';              % 'BER' | 'GMI' | 'AIR' | ...
+
+cfg.y_scale = 'auto';            % auto -> log for BER*, linear otherwise
+cfg.outlier = 'mad';             % simple, robust; 'none' or 'pctl' also available
+cfg.show_raw = false;
+cfg.show_spread = 'none';        % 'none' or 'iqr' or minmax
+cfg.agg = 'min';                % or 'median'
+cfg.show_precoded = 0;
+% cfg.fec_lines = [2.2e-4 4.85e-3 2e-2]; % optional
+cfg.fec_lines = [];
+cfg.plot.custom_colors = [
+    clr.Paired.red;
+    clr.Paired.blue;
+    clr.Paired.green;
+    clr.Paired.orange;
+    clr.Paired.purple
+];
+
+cfg.plot.custom_colors_scatter = [
+    clr.Paired.lightred;
+    clr.Paired.lightblue;
+    clr.Paired.lightgreen;
+    clr.Paired.lightorange;
+    clr.Paired.lightpurple
+];
+
+
+% New styling knobs
+cfg.plot.use_cbrewer2 = true;
+cfg.plot.colormap = 'Paired';
+cfg.plot.paired_dark_first = false;        % dark for lines, light for scatter
+cfg.plot.lineWidth = 2.0;
+cfg.plot.errWidth  = 1.2;
+cfg.plot.scatterAlpha = 0.35;
+cfg.plot.legendLocation = 'best';
+cfg.plot.fecLineWidth = 2.4;              % thicker FEC limits
+cfg.plot.lineStyle_pre_emph_on = '-';
+cfg.plot.lineStyle_pre_emph_off = '-';
+
+%%
+cfg.figure_number = 42;
+
+
+% ---- VNLE, no pre-emph (solid red) ----
+cfg.plot.custom_colors = [clr.Paired.red];
+cfg.plot.custom_linetypes = {'-'};
+cfg.filters = struct('is_mpi',0,'pam_level',M, ...
+    'equalizer_structure',equalizer_structure.vnle, ...
+    'pre_emph',0);
+plot_measurements_gpt(dataTable, cfg);
+
+% ---- VNLE, with pre-emph (dashed red) ----
+cfg.plot.custom_colors = [clr.Paired.red];
+cfg.plot.custom_linetypes = {'--'};
+cfg.filters.pre_emph = 1;
+plot_measurements_gpt(dataTable, cfg);
+
+% ---- VNLE PF MLSE, no pre-emph (solid green) ----
+cfg.plot.custom_colors = [clr.Paired.green];
+cfg.plot.custom_linetypes = {'-'};
+cfg.filters.equalizer_structure = equalizer_structure.vnle_pf_mlse;
+cfg.filters.pre_emph = 0;
+plot_measurements_gpt(dataTable, cfg);
+
+% ---- VNLE PF MLSE, with pre-emph (dashed green) ----
+cfg.plot.custom_colors = [clr.Paired.green];
+cfg.plot.custom_linetypes = {'--'};
+cfg.filters.pre_emph = 1;
+plot_measurements_gpt(dataTable, cfg);
+
+
+% === FEC LINES (no legend) ===
+yline([2.2e-4 4.85e-3 2e-2], ...
+    'LineWidth',1.5,'Color',[0.4 0.4 0.4], ...
+    'LineStyle',':','HandleVisibility','off');
+
+
+% === BEAUTIFY ===
+% beautifyBERplot;   % your function
+
+
+%% === EXPORT TO TIKZ ===
+outfile = 'C:\Users\Silas\Documents\latex\JLT_400G copy\media\matlab2tikz\compare_pre_emphasis.tikz';
+
+matlab2tikz(outfile, ...
+    'width','\fwidth', ...
+    'height','\fheight', ...
+    'showInfo',false, ...
+    'extraAxisOptions',{ ...
+        'legend style={font=\footnotesize}', ...
+        'legend columns=1' ...
+    } );

projects/HighSpeedExperiment_2024/Auswertung_JLT/final/generate_spectrum_plots.m

@@ -0,0 +1,100 @@
+dsp_options.storage_path    = 'Z:\2024\sioe_labor\';
+dsp_options.max_occurences = 1;
+database    = DBHandler("dataBase", 'labor_highspeed', "type",  'mysql' );
+
+rate = 390e9;
+
+%% 1 - PAM 4 with preemphasis
+fp = QueryFilter();
+M = 4;
+fp.where('Runs', 'pam_level','EQUALS', M);     
+fp.where('Runs', 'bitrate','EQUALS', rate);%360,390
+fp.where('Runs', 'fiber_length','EQUALS', 2);   
+fp.where('Runs', 'wavelength','EQUALS', 1310);         
+fp.where('Runs', 'db_mode','EQUALS', 0);              
+fp.where('Runs', 'rop_attenuation','EQUAL', 0);      
+
+[dataTable,~] = db.queryDB(fp, database.getTableFieldNames('Runs'));
+
+dataTable   = queryRunid(dataTable.run_id, database);
+fsym        = dataTable.symbolrate;
+M           = double(dataTable.pam_level);
+
+% Load and Sync signal data from DB
+[Tx_bits, Symbols, Scpe_cell, ~] = loadAndSyncSignalDataFromDb(dataTable, dsp_options);
+
+% Preprocess signal
+Scpe_sig = preprocessSignal(Scpe_cell{1}, Symbols, fsym);
+
+if rate == 390e9
+Scpe_sig.spectrum("fignum",200,"normalizeTo0dB",1,"displayname",'Rx','addDCoffset',-5.8);
+elseif rate == 300e9
+Scpe_sig.spectrum("fignum",200,"normalizeTo0dB",1,"displayname",'Rx','addDCoffset',-4.7);
+end
+ylim([-30,3]);
+xlim([-5,100]);
+Scpe_sig.spectrum("fignum",201,"normalizeTo0dB",0,"displayname",'Rx');
+
+
+%% 1 - PAM 4 without preemphasis
+fp = QueryFilter();
+M = 4;
+fp.where('Runs', 'pam_level','EQUALS', M);     
+fp.where('Runs', 'bitrate','EQUALS', rate);%360,390
+fp.where('Runs', 'fiber_length','EQUALS', 2);   
+fp.where('Runs', 'wavelength','EQUALS', 1310);         
+fp.where('Runs', 'db_mode','EQUALS', 1);              
+fp.where('Runs', 'rop_attenuation','EQUAL', 0);      
+
+[dataTable,~] = db.queryDB(fp, database.getTableFieldNames('Runs'));
+
+dataTable   = queryRunid(dataTable.run_id, database);
+fsym        = dataTable.symbolrate;
+M           = double(dataTable.pam_level);
+
+% Load and Sync signal data from DB
+[Tx_bits, Symbols, Scpe_cell, ~] = loadAndSyncSignalDataFromDb(dataTable, dsp_options);
+
+% Preprocess signal
+Scpe_sig = preprocessSignal(Scpe_cell{1}, Symbols, fsym);
+
+Scpe_sig.spectrum("fignum",200,"normalizeTo0dB",1,"displayname",'Rx','addDCoffset',0);
+ylim([-30,3]);
+xlim([-5,100]);
+Scpe_sig.spectrum("fignum",201,"normalizeTo0dB",0,"displayname",'Rx');
+
+
+
+if 0 
+    %% show freuqncy response of filter
+    
+    measure = 1;
+    
+    freqresp = ChannelFreqResp("Nacq",1024,"Navg",64,"Ncp",70,"f_ref",256e9);
+    %
+    Digi_sig = freqresp.buildOFDM();
+    
+    Digi_sig.spectrum("fignum",1112,"displayname",['maxamp:',num2str(maxamp)]);
+    
+    Digi_sig = Filter('filtdegree',3,"f_cutoff",70e9,"fs",256e9,"filterType",filtertypes.butterworth,"active",true).process(Digi_sig);
+    
+    Digi_sig = Filter('filtdegree',3,"f_cutoff",70e9,"fs",256e9,"filterType",filtertypes.bessel_inp,"active",true).process(Digi_sig);
+    
+    freqresp.estimate(Digi_sig,"fileName",'','save',false);
+    
+    freqresp.plot()
+    
+    a = gca;
+    a.YTick = [-30,-20,-10,0];
+    
+    %% system frex
+    
+    
+    precomp_filename ='lab_high_speed';
+    precomp_path = "C:\Users\Silas\Documents\MATLAB\Datensätze\sioe_labor\precomp";
+    freqresp = ChannelFreqResp("Nacq",1024,"Navg",64,"Ncp",63,'f_ref',92e9);
+    freqresp.load('loadPath', precomp_path, 'fileName', precomp_filename);
+    
+    fprintf('Plotting: %s\n', precomp_filename);
+    freqresp.plot();
+end

projects/HighSpeedExperiment_2024/Auswertung_JLT/final/plot_measurements_gpt.m

@@ -14,13 +14,13 @@ defaults = struct( ...
     'filters'     , struct, ...
     'agg'         , 'mean', ...
     'outlier'     , 'auto', ...
-    'mad_z'       , 3, ...
+    'mad_z'       , 4, ...
     'pct_limits'  , [2.5 97.5], ...
     'min_pts_x'   , 3, ...
     'show_raw'    , true, ...
     'show_precoded', [], ...
     'show_spread' , 'none', ...
-    'fec_lines'   , [2.2e-4 4.85e-3 2e-2], ...
+    'fec_lines'   , [], ...
     'plot', struct() ...
 );
 cfg = filldefaults(cfg, defaults);
@@ -75,6 +75,11 @@ T   = T(validXY, :);
 x_raw = x_raw(validXY);
 y_raw = y_raw(validXY);
 
+if mean(abs(y_raw)) > 1e8
+    %giga values
+    y_raw = y_raw.*1e-9;
+end
+
 if cfg.show_precoded && ismember('BER_precoded', T.Properties.VariableNames)
     y_raw_p = T.BER_precoded(validXY);
 else
@@ -92,8 +97,29 @@ nG = max(G);
 % ==== Colors (cbrewer2 'Paired' with dark/ light pairs) ====
 [cols_line, cols_scatter] = buildGroupColors(nG, cfg.plot);
 
-%% ---- Plotting
+%% ---- Axes / Figure handling (new unified logic)
-figure; hold on; grid on;
+
+% Priority:
+% 1) cfg.ax  → use existing axes (subplots/tiles)
+% 2) cfg.figure_number → select/create figure
+% 3) fallback: create new figure
+
+if isfield(cfg,'ax') && ~isempty(cfg.ax) && isgraphics(cfg.ax,'axes')
+    ax = cfg.ax;                     % use caller-provided axes
+    set(gcf,'CurrentAxes',ax);
+else
+    if isfield(cfg,'figure_number') && ~isempty(cfg.figure_number)
+        figure(cfg.figure_number);
+    else
+        figure;
+    end
+    ax = gca;                        % active axes
+end
+
+hold(ax,'on');
+grid(ax,'on');
+
+
 h.lines   = gobjects(nG,1);
 h.err     = gobjects(nG,1);
 h.scat    = gobjects(nG,1);
@@ -120,34 +146,32 @@ for gi = 1:nG
         if nnz(km) < cfg.min_pts_x, km = true(size(yy)); end
         yy = yy(km);
 
-        if strcmpi(cfg.agg,'median'), yu(k)=median(yy,'omitnan'); elseif strcmpi(cfg.agg,'mean'), yu(k)=mean(yy,'omitnan'); elseif strcmpi(cfg.agg,'min'), yu(k)=min(yy); end
+        if strcmpi(cfg.agg,'median'), yu(k)=median(yy,'omitnan'); elseif strcmpi(cfg.agg,'mean'), yu(k)=mean(yy,'omitnan'); elseif strcmpi(cfg.agg,'min'), yu(k)=min(yy); elseif strcmpi(cfg.agg,'max'), yu(k)=max(yy); end
         if strcmpi(cfg.show_spread,'iqr')
             q = prctile(yy,[25 75]);
             ylo(k) = max(yu(k)-q(1), eps);
             yhi(k) = max(q(2)-yu(k), eps);
+        elseif strcmpi(cfg.show_spread,'minmax')
+            ylo(k) = min(yy);
+            yhi(k) = max(yy);
         end
     end
 
     % sort
     [xu, ord] = sort(xu);
-    yu  = yu(ord); ylo = ylo(ord); yhi = yhi(ord);
+    yu  = yu(ord); 
+    ylo = ylo(ord); 
+    yhi = yhi(ord);
 
     % Styles
     % Decide if we style by pre_emph
-    canStyleByPre = cfg.plot.use_pre_emph_styling && ismember('pre_emph', T.Properties.VariableNames);
+    % --- LINE TYPE SELECTION (no pre-emphasis logic) ---
+    ls = cfg.plot.lineStyle_default;
 
-    if canStyleByPre
+    % User-defined override (cycled)
-        if any(strcmp(group_by,'pre_emph'))
+    if isfield(cfg.plot,'custom_linetypes') && ~isempty(cfg.plot.custom_linetypes)
-            % pre_emph is an explicit grouping key -> take it from the group table
+        L = cfg.plot.custom_linetypes;
-            pre = logical(grpTbl.pre_emph(gi));
+        ls = L{ mod(gi-1, numel(L)) + 1 };
-        else
-            % pre_emph not grouped, but available in the rows -> infer from the members of this group
-            pre = logical(mode(T.pre_emph(G==gi)));
-        end
-        ls = tern(pre, cfg.plot.lineStyle_pre_emph_on, cfg.plot.lineStyle_pre_emph_off);
-    else
-        % no pre-emph styling → use a single default style
-        ls = cfg.plot.lineStyle_default;
     end
 
     lbl = buildLabel(grpTbl(gi,:), group_by);
@@ -156,12 +180,12 @@ for gi = 1:nG
     colL = cols_line(gi,:);
     h.lines(gi) = plot(xu, yu, ...
         'LineWidth', cfg.plot.lineWidth, ...
-        'Marker', cfg.plot.marker, 'MarkerSize', 5, ...
+        'Marker', cfg.plot.marker, 'MarkerSize', 3, ...
         'Color', colL, 'LineStyle', ls, ...
         'DisplayName', char(lbl));
 
     % Spread (IQR) in line color
-    if strcmpi(cfg.show_spread,'iqr') && any(isfinite(ylo)) && any(isfinite(yhi))
+    if any(isfinite(ylo)) && any(isfinite(yhi))
         h.err(gi) = errorbar(xu, yu, ylo, yhi, 'LineStyle','none', ...
             'Color', colL, 'CapSize', cfg.plot.capSize, 'HandleVisibility','off');
         h.err(gi).LineWidth = cfg.plot.errWidth;
@@ -195,30 +219,38 @@ for gi = 1:nG
             km = outlierMask(yy, cfg, true);
             if nnz(km) < cfg.min_pts_x, km = true(size(yy)); end
             yy = yy(km);
-            if strcmpi(cfg.agg,'median'), ypu(k)=median(yy,'omitnan'); elseif strcmpi(cfg.agg,'mean'), ypu(k)=mean(yy,'omitnan'); elseif strcmpi(cfg.agg,'min'), ypu(k)=min(yy); end
+            if strcmpi(cfg.agg,'median'), ypu(k)=median(yy,'omitnan'); elseif strcmpi(cfg.agg,'mean'), ypu(k)=mean(yy,'omitnan'); elseif strcmpi(cfg.agg,'min'), ypu(k)=min(yy); elseif strcmpi(cfg.agg,'max'), ypu(k)=max(yy); end
         end
         h.lines_p(gi) = plot(xu, ypu, ...
             'LineWidth', max(1.2, cfg.plot.lineWidth-0.2), ...
-            'Marker', cfg.plot.marker_precoded, 'MarkerSize', 5, ...
+            'Marker', cfg.plot.marker_precoded, 'MarkerSize', 3, ...
             'Color', colL, 'LineStyle', ':', ...
             'DisplayName', [char(lbl) ' (precoded)']);
     end
+
+    
 end
 
 %% ---- Axes / Labels / FEC
 ylabel(cfg.y_axis, 'Interpreter','none');
 xlabel(x_label,    'Interpreter','none');
 set(gca, 'YScale', cfg.y_scale, 'FontSize', 11);
-legend('Location', cfg.plot.legendLocation); box on;
+% legend('Location', cfg.plot.legendLocation); box on;
+
+xticks(floor(xu));
+xlim([min(xu), max(xu)])
 
 if startsWith(cfg.y_axis,"BER",'IgnoreCase',true)
     for v = cfg.fec_lines
         yline(v, '--', 'Color', cfg.plot.fecColor, ...
             'LineWidth', cfg.plot.fecLineWidth, 'HandleVisibility','off');
     end
-    ylim([1e-4, 0.3]);
+    ylim([1e-5, 0.5]);
+    yticks([1e-5, 1e-4, 1e-3, 1e-2, 1e-1]);
 end
 
+
+
 end % ===== main =====
 
 
@@ -237,7 +269,11 @@ end
 end
 
 function out = tern(cond, a, b)
-if cond, out = a; else, out = b; end
+    if cond
+        out = a;
+    else
+        out = b;
+    end
 end
 
 function T2 = applyFilters(T, filters)
@@ -274,9 +310,12 @@ switch lower(whichX)
         if ~ismember('pam_level', T.Properties.VariableNames)
             error('bitrate requires "pam_level" column.');
         end
-        bits = log2(double(T.pam_level));
+        bits = floor(log2(double(T.pam_level))*10)/10;
         x = (T.symbolrate .* bits) * 1e-9;
-        label = 'Bitrate [Gb/s]';
+        label = 'Grossrate [Gb/s]';
+        case 'grossrate'
+            x = (T.grossrate) * 1e-9;
+            label = 'Grossrate [Gb/s]';
     otherwise
         if ~ismember(whichX, T.Properties.VariableNames)
             error('x_axis "%s" not found in table.', whichX);
@@ -317,38 +356,78 @@ for i = 1:numel(group_by)
     key = group_by{i};
     val = grpRow.(key);
     if iscell(val), val = val{1}; end
-    if islogical(val), val = tern(val,'pre-emph on','pre-emph off'); end
+    if islogical(val), val = tern(val,'w/','w/o'); end
-    parts(i) = sprintf('%s=%s', key, string(val));
+    if key == "equalizer_structure"
+        key = '';
+        val = upper(val);
+        val = strrep(val,'_',' ');
+    end
+    
+    if key == "pre_emph"
+        % key = strrep(key,'_','-');
+        val = [val, ' pre-emph.'];
+        key = ''; 
+    end
+    
+    parts(i) = sprintf('%s %s', key, string(val));
 end
 s = strjoin(parts, ', ');
 end
 
 function [cols_line, cols_scatter] = buildGroupColors(nG, plotcfg)
-% Build paired colors (dark for lines, light for scatter) using cbrewer2('Paired')
+
+% --- 1) User-provided custom colors -------------------------------
+if isfield(plotcfg,'custom_colors') && ~isempty(plotcfg.custom_colors)
+    C = plotcfg.custom_colors;
+    if size(C,1) < nG
+        error('custom_colors must have at least nG=%d rows.', nG);
+    end
+    cols_line = C(1:nG, :);
+
+    % Scatter colors: either user-provided or lightened
+    if isfield(plotcfg,'custom_colors_scatter') && ~isempty(plotcfg.custom_colors_scatter)
+        Cs = plotcfg.custom_colors_scatter;
+        if size(Cs,1) < nG
+            error('custom_colors_scatter must have at least nG=%d rows.', nG);
+        end
+        cols_scatter = Cs(1:nG, :);
+    else
+        % auto-lighten scatter colors
+        cols_scatter = zeros(nG,3);
+        for i = 1:nG
+            cols_scatter(i,:) = lightenColor(cols_line(i,:), 0.40);
+        end
+    end
+    return;
+end
+
+% --- 2) Standard behavior (using cbrewer2 or fallback) ------------
 useBrewer = plotcfg.use_cbrewer2 && exist('cbrewer2','file')==2;
 if useBrewer
-    N = max(2*nG, 12); % ensure pairs available
+    N = max(2*nG, 12);
     C = cbrewer2(plotcfg.colormap, N);
     cols_line    = zeros(nG,3);
     cols_scatter = zeros(nG,3);
     for i = 1:nG
         if plotcfg.paired_dark_first
-            dark = C(2*i-1, :); light = C(2*i, :);
+            dark  = C(2*i-1, :);
+            light = C(2*i,   :);
         else
-            light = C(2*i-1, :); dark = C(2*i, :);
+            light = C(2*i-1, :);
+            dark  = C(2*i,   :);
         end
         cols_line(i,:)    = dark;
         cols_scatter(i,:) = light;
     end
 else
-    % Fallback: lines() + lightened scatter
     C = lines(max(nG,7));
     cols_line    = C(1:nG,:);
     cols_scatter = zeros(nG,3);
     for i = 1:nG
-        cols_scatter(i,:) = lightenColor(cols_line(i,:), 0.5); % 50% toward white
+        cols_scatter(i,:) = lightenColor(cols_line(i,:), 0.50);
     end
 end
+
 end
 
 function c2 = lightenColor(c, fracTowardWhite)

projects/HighSpeedExperiment_2024/Auswertung_JLT/final/plot_rates.m

@@ -0,0 +1,34 @@
+
+path = "C:\Users\Silas\Documents\MATLAB\imdd_simulation\projects\HighSpeedExperiment_2024\Auswertung_JLT\final\rates.csv";
+
+%% === Read CSV into a table ===
+T = readtable(path, 'Delimiter', ';', 'DecimalSeparator', ',');
+
+%% === Column definitions ===
+x = T.X_Werte;
+pam_cols = {'PAM_2','PAM_4','PAM_6','PAM_8','PAM_12'};
+titles   = {'PAM-2','PAM-4','PAM-6','PAM-8','PAM-12'};
+
+% === Create subplots ===
+figure;hold on
+c = linspecer(6);
+for k = 1:numel(pam_cols)
+    
+    y = T.(pam_cols{k});
+    valid = ~isnan(y);
+
+    
+    % Scatter plot
+    s = scatter(x(valid), y(valid), 25, 'filled','MarkerEdgeColor',c(k,:),'MarkerFaceColor',c(k,:),'DisplayName',titles{k});
+
+    % Fit (2nd-order polynomial)
+    p = polyfit(x(valid), y(valid), 2);
+    xfit = linspace(min(x(valid)), max(x(valid)), 200);
+    yfit = polyval(p, xfit);
+
+    % Plot fit curve
+    plot(xfit, yfit, 'LineWidth', 1,'linestyle',':','Color',c(k,:),'HandleVisibility','off');
+
+    xlabel('baud rate [GBd]');
+    ylabel('net rate [Gb/s]');
+end

projects/HighSpeedExperiment_2024/Auswertung_JLT/final/rates.csv

@@ -0,0 +1,38 @@
+X-Werte;PAM-2;PAM-4;PAM-6;PAM-8;PAM-12
+224;204;;;;
+205,5;193,4;;;;
+205,1;189,7;;;;
+192;168;;;;
+240;;427,4;;;
+225;;420,5;;;
+210;;336;;;
+184;;332;;;
+192;;320;;;
+176;;306,0869565;;;
+190;;304;;;
+168;;294;;;
+156,2;;287,1;;;
+160,8;;286,9;;;
+170;;272;;;
+132;;250,9505703;;;
+112;;209,3457944;;;
+172;;337;;;
+216;;;474,6;;
+147,2;;;329,9;;
+132;;;319,7891753;;
+143,1;;;318;;
+160;;;377;;
+225;;;;562,5;
+200;;;;510;
+160;;;;438;
+180;;;;432;
+180;;;;432;
+144;;;;384;
+143,7;;;;363,4;
+144;;;;360;
+136;;;;353,859497;
+136;;;;342,7995295;
+128;;;;329,0488432;
+129,7;;;;311,2;
+160;;;;413;
+160;;;;;481,2

projects/HighSpeedExperiment_2024/Auswertung_JLT/final/run_plot_measurements.m

@@ -2,40 +2,59 @@ database_type   = 'mysql';
 dataBase   = 'labor_highspeed';%'C:\Users\Silas\Documents\MATLAB\Datensätze\sioe_labor\silas_labor_newdsp_newstructure.db';
 db = DBHandler("dataBase", [dataBase], "type", database_type);
 
-M = 4;
+M = 8;
 fp = QueryFilter();
 % fp.where('Runs', 'run_id','EQUALS', 987);
 fp.where('Runs', 'pam_level','EQUALS', M);
 % fp.where('Runs', 'symbolrate','EQUALS', 165e9); %150, 165, 180, 195, 210, 225, 240
-fp.where('Runs', 'fiber_length','EQUALS', 10);
+fp.where('Runs', 'fiber_length','EQUALS', 2);
 % fp.where('Runs', 'is_mpi','EQUALS', 0);
 % fp.where('Runs', 'power_pd_in','GREATER_THAN', 7);
 % fp.where('Runs', 'interference_path_length','EQUALS', 1000);
 % fp.where('Runs', 'loop_id','GREATER_THAN', 11);
 % fp.where('Runs', 'sir','EQUALS',18);
 fp.where('Runs', 'wavelength','EQUALS', 1310);
-fp.where('Runs', 'db_mode','EQUALS', 1);         % 0 == high preemphasis // 1 == low preemphasis
+% fp.where('Runs', 'db_mode','EQUALS', 1);         % 0 == high preemphasis // 1 == low preemphasis
 % fp.where('Runs', 'rop_attenuation','EQUALS', 0);
 
 fields = db.getTableFieldNames('power_state_info');
-fields = [fields; db.getTableFieldNames('dashboard_ungrouped_new')];
+fields = [fields; db.getTableFieldNames('dashboard_ungrouped_alltime')]; %dashboard_ungrouped_after_nov_2025  dashboard_ungrouped_aug_nov_2025 
 [dataTable,~] = db.queryDB(fp, fields);
 
+
 %% 
 cfg = struct;
-cfg.x_axis = 'symbolrate';          % 'symbolrate' | 'bitrate' | 'wavelength'
+cfg.x_axis = 'grossrate';          % 'symbol rate' | 'bitrate' | 'wavelength'  grossrate
 cfg.y_axis = 'BER';              % 'BER' | 'GMI' | 'AIR' | ...
-cfg.group_by = {'wavelength','equalizer_structure','pre_emph'};
+cfg.group_by = {'equalizer_structure','pre_emph'};
-cfg.filters = struct('is_mpi',0,'pam_level',M,'equalizer_structure',[equalizer_structure.ml_mlse,equalizer_structure.vnle,equalizer_structure.vnle_pf_mlse,equalizer_structure.vnle_db_mlse,equalizer_structure.dfe]);
+cfg.filters = struct('is_mpi',0,'pam_level',M,'equalizer_structure',[equalizer_structure.ml_mlse]);%,equalizer_structure.vnle_pf_mlse,equalizer_structure.vnle]);
 
 cfg.y_scale = 'auto';            % auto -> log for BER*, linear otherwise
 cfg.outlier = 'mad';             % simple, robust; 'none' or 'pctl' also available
-cfg.show_raw = true;
+cfg.show_raw = false;
-cfg.show_spread = 'none';        % 'none' or 'iqr'
+cfg.show_spread = 'none';        % 'none' or 'iqr' or minmax
-cfg.agg = 'mean';                % or 'median'
+cfg.agg = 'min';                % or 'median'
-cfg.show_precoded = 1;
+cfg.show_precoded = 0;
 cfg.fec_lines = [2.2e-4 4.85e-3 2e-2]; % optional
 
+cfg.figure_number = 42;
+cfg.plot.custom_colors = [
+    clr.Paired.red;
+    clr.Paired.blue;
+    clr.Paired.green;
+    clr.Paired.orange;
+    clr.Paired.purple
+];
+
+cfg.plot.custom_colors_scatter = [
+    clr.Paired.lightred;
+    clr.Paired.lightblue;
+    clr.Paired.lightgreen;
+    clr.Paired.lightorange;
+    clr.Paired.lightpurple
+];
+
+
 % New styling knobs
 cfg.plot.use_cbrewer2 = true;
 cfg.plot.colormap = 'Paired';
@@ -48,4 +67,10 @@ cfg.plot.fecLineWidth = 2.4;              % thicker FEC limits
 
 plot_measurements_gpt(dataTable, cfg);
 
-% beautifyBERplot()
+% beautifyBERplot()
+
+%% FIG PRE EMPHASIS
+
+
+
+

projects/HighSpeedExperiment_2024/Auswertung_JLT/run_dsp_from_db.m

@@ -1,6 +1,6 @@
 % === SETTINGS ===
 dsp_options.append_to_db = 0;
-dsp_options.max_occurences = 15;
+dsp_options.max_occurences = 5;
 
 experiment = "highspeed_2024";
 dsp_options.mode            = "load_run_id"; % 'simulate' & 'load_files'
@@ -42,15 +42,15 @@ fp = QueryFilter();
 % fp.where('Runs', 'run_id','EQUALS', 2776);
 M = 4;
 fp.where('Runs', 'pam_level','EQUALS', M);     
-% fp.where('Runs', 'bitrate','EQUALS', 300e9);%360,390
+fp.where('Runs', 'bitrate','EQUALS', 390e9);%360,390
 % fp.where('Runs', 'symbolrate','EQUALS', 195e9);
 fp.where('Runs', 'fiber_length','EQUALS', 2);   
 % fp.where('Runs', 'is_mpi','EQUALS', 0);                
 % fp.where('Runs', 'interference_path_length','EQUALS', 1000);      
 % fp.where('Runs', 'loop_id','GREATER_THAN', 11);   
 % fp.where('Runs', 'sir','EQUALS',18);  
-fp.where('Runs', 'wavelength','EQUAL', 1310);         
+fp.where('Runs', 'wavelength','EQUALS', 1310);         
-fp.where('Runs', 'db_mode','EQUALS', 1);              
+fp.where('Runs', 'db_mode','EQUALS', 0);              
 fp.where('Runs', 'rop_attenuation','EQUAL', 0);      
 % fp.where('Runs', 'power_pd_in','GREATER_THAN', 7);    
 

projects/HighSpeedExperiment_2024/auswertung/only_show_precomp.m

@@ -61,7 +61,7 @@ rcalpha     = 0.05;
 Pform       = Pulseformer("fsym",fsym,"fdac",4*fsym,"pulse","rrc","pulselength",16,"alpha",rcalpha);
 
 Pamsource = PAMsource(...
-    "fsym",fsym,"M",M,"order",19,"useprbs",1,...
+    "fsym",fsym,"M",M,"order",19,"useprbs",0,...
     "fs_out",fdac,...
     "applyclipping",0,"clipfactor",1.2,...
     "applypulseform",pulsef,"pulseformer",Pform,...
@@ -87,4 +87,5 @@ Digi_sig= Digi_sig.normalize("mode","rms");
 
 Digi_sig.spectrum("displayname","Strong Precomp","fignum",2223,"normalizeToNyquist",0,"normalizeTo0dB",0);
 
-
+ylim([-30,3]);
+xlim([-5,100]);

projects/HighSpeedExperiment_2024/bias_evaluation.m

@@ -26,11 +26,14 @@ clf
 hold on
 cols = cbrewer2('Set1',3);
 for l =  1:numel(lambda_vals)
+    figure()
     for m = 1:numel(M_vals)
        
         ber_ffe      = wh.getStoValue('ber_ffe',v_bias_vals,awg_vpp_vals(1),precomp_amp_max_vals(1),rop_atten_vals(1),M_vals(m),lambda_vals(l));
         ber         = wh.getStoValue('ber_collect',v_bias_vals,awg_vpp_vals(1),precomp_amp_max_vals(1),rop_atten_vals(1),M_vals(m),lambda_vals(l));
         exfo         = wh.getStoValue('exfo',v_bias_vals,awg_vpp_vals(1),precomp_amp_max_vals(1),rop_atten_vals(1),M_vals(m),lambda_vals(l));
+
+        lb         = wh.getStoValue('exfo',v_bias_vals,awg_vpp_vals(1),precomp_amp_max_vals(1),rop_atten_vals(1),M_vals(m),lambda_vals(l));
         
         for e = 1:numel(exfo)
             laser_pow(e) = exfo{e}.cur_power;
@@ -42,7 +45,7 @@ for l =  1:numel(lambda_vals)
         rx_logbook      = wh.getStoValue('rx_logbook',v_bias_vals(1),awg_vpp_vals(1),precomp_amp_max_vals(1),rop_atten_vals(1),M_vals(1),lambda_vals(1));
 
         
-        subplot(1,3,l)
+        
         hold on
         a = scatter(v_bias_vals,min(ber,[],2),40,'LineWidth',2,'Marker','.','DisplayName',['PAM ',num2str(M_vals(m))],'MarkerEdgeColor',cols(m,:));
         title([num2str(lambda_vals(l)),'nm'])
@@ -66,7 +69,7 @@ for l =  1:numel(lambda_vals)
 
         % Polynomial fit (e.g., second-order polynomial)
         [woutliers,n] = rmoutliers(  min(ber,[],2) );
-        p = polyfit( v_bias_vals(~n), log10(woutliers), 4);  % Adjust order as needed
+        p = polyfit( v_bias_vals(~n), log10(woutliers), 3);  % Adjust order as needed
         BER_fit = polyval(p, v_bias_vals);
 
 
@@ -93,6 +96,7 @@ for l =  1:numel(lambda_vals)
     end
 end
 
+%%
 
 
 filename = "Z:\2024\sioe\High Speed Messungen Oktober\bias_testing_and_b2b\PAM4_b2b_bias_sweep_20241023_191202_wh_BB_BIAS_FINAL.mat";

projects/ML_based_MLSE/wpd_datasets.csv

@@ -0,0 +1,9 @@
+FFE,,MLSE,,ML MLSE L=2,,ML MLSE L=5,
+X,Y,X,Y,X,Y,X,Y
+7.988476019722099,0.038632829886662855,7.9828552218736,0.02056096426419196,7.988825638727029,0.026145160025945406,7.982882115643211,0.01995262314968881
+8.984755714926044,0.02462092401494627,8.991855670103094,0.008868008219069292,8.991519497982967,0.012908315306800594,8.998027790228598,0.009002182769536628
+9.993487225459436,0.014339094903163154,9.988632900044824,0.0032424222072799827,9.994320932317347,0.005651632488900345,9.994751232631108,0.0034952501326754757
+10.989914836396235,0.007746944324122318,10.991730165844913,0.001020224273461357,10.997256835499776,0.002129417748571358,10.991689825190498,0.0010672369906432938
+12.005060510981624,0.0034952501326754757,12.001483639623487,0.00018978455660928717,11.994316450022412,0.0005679993334792185,12.007359928283282,0.0002680778116002006
+12.983254146122816,0.0013169376605490738,13.011492604213357,0.000026540740973404924,12.997722994173017,0.00012652429120320801,12.992384580905423,0.000049125201846734525
+13.99255042581802,0.0004081967712510506,14.00969520394442,0.000001975386920666194,13.995172568354999,0.00002183385565256239,14.015275661138503,0.0000038826695948713645

projects/standard_system/freqresp_test.m

@@ -1,28 +1,19 @@
-measure = 0;
+measure = 1;
+
+freqresp = ChannelFreqResp("Nacq",1024,"Navg",64,"Ncp",70,"f_ref",256e9);
+%
+Digi_sig = freqresp.buildOFDM();
+
+Digi_sig.spectrum("fignum",1112,"displayname",['maxamp:',num2str(maxamp)]);
+
+Digi_sig = Filter('filtdegree',3,"f_cutoff",70e9,"fs",256e9,"filterType",filtertypes.butterworth,"active",true).process(Digi_sig);
+
+Digi_sig = Filter('filtdegree',3,"f_cutoff",70e9,"fs",256e9,"filterType",filtertypes.bessel_inp,"active",true).process(Digi_sig);
 
 
-if measure
+freqresp.estimate(Digi_sig,"fileName",'','save',false);
-    freqresp = ChannelFreqResp("Nacq",1024,"Navg",64,"Ncp",70,"f_ref",256e9);
-    % 
-    Digi_sig = freqresp.buildOFDM();
-else
-    [Digi_sig,Symbols,Bits] = PAMsource("fsym",fsym,"M",M,"order",18,"useprbs",0,...
-            "fs_out",M8199.fdac,"applyclipping",1,"clipfactor",1.7,"applypulseform",1,"pulseformer",Pform,"randkey",pn_key,"mrds_code",usemrds,"mrds_blocklength",512).process();
-end
 
-Digi_sig.spectrum("fignum",1112,"displayname",['Signal']);
+freqresp.plot()
 
-maxamp = -1;
+a = gca;
-El_sig = freqresp.precomp(Digi_sig,"maxampdb",maxamp);
+a.YTick = [-30,-20,-10,0];
-
-El_sig.spectrum("fignum",1112,"displayname",['maxamp:',num2str(maxamp)]);
-
-El_sig = Filter('filtdegree',2,"f_cutoff",60e9,"fs",256e9,"filterType",filtertypes.butterworth,"active",true).process(El_sig);
-
-if measure
-    freqresp.estimate(El_sig,"fileName",'','save',false);
-end
-
-
-
-El_sig.spectrum("fignum",1112,"displayname",['after filter; maxamp:',num2str(maxamp)]);