new plots for Diss. Mostly AI gen. Few changes in actual codebase

Classes/00_signals/Signal.m

@@ -403,7 +403,7 @@ classdef Signal
                 % Divide by 2*pi for the f/fs axis where Nyquist is 0.5.
             end
 
-            p_lin = movmean(p_lin,10);
+            p_lin = movmean(p_lin,20);
 
             if options.normalizeTo0dB
                 p_lin = p_lin ./ max(p_lin);
@@ -1042,34 +1042,23 @@ classdef Signal
                 if isempty(finite_eye)
                     finite_eye = sig(isfinite(sig));
                 end
-                amp_min = min(finite_eye);
+                if isa(obj,'Opticalsignal')
-                amp_max = max(finite_eye);
+                    amp_min = min(finite_eye);
-                amp_center = (amp_max + amp_min) / 2;
+                    amp_max = max(finite_eye);
-                amp_span = amp_max - amp_min;
+                    amp_center = (amp_max + amp_min) / 2;
-                if amp_span == 0
+                    amp_span = amp_max - amp_min;
-                    amp_span = max(abs(amp_center),1);
+                    if amp_span == 0
-                end
+                        amp_span = max(abs(amp_center),1);
-                amp_margin = 0.08 * amp_span;
-                maxA = amp_center + amp_span/2 + amp_margin;
-                minA = amp_center - amp_span/2 - amp_margin;
-                if ~isa(obj,'Opticalsignal') && minA < 0 && maxA > 0
-                    targetStep = max(abs([minA maxA])) / 2;
-                    if targetStep > 0
-                        stepMagnitude = 10^floor(log10(targetStep));
-                        normalizedStep = targetStep / stepMagnitude;
-                        if normalizedStep <= 1
-                            tickStep = stepMagnitude;
-                        elseif normalizedStep <= 2
-                            tickStep = 2 * stepMagnitude;
-                        elseif normalizedStep <= 5
-                            tickStep = 5 * stepMagnitude;
-                        else
-                            tickStep = 10 * stepMagnitude;
-                        end
-                        axisLimit = 2 * tickStep;
-                        maxA = axisLimit;
-                        minA = -axisLimit;
                     end
+                    amp_margin = 0.08 * amp_span;
+                    maxA = amp_center + amp_span/2 + amp_margin;
+                    minA = amp_center - amp_span/2 - amp_margin;
+                else
+                    % Normalized electrical/digital eye display range.
+                    % Samples outside this range are clipped in the
+                    % histogram image so all eye plots use the same scale.
+                    minA = -3;
+                    maxA = 3;
                 end
 
                 % maxA = 0.12;
@@ -1109,13 +1098,13 @@ classdef Signal
                     max_ = abs(max(obj.signal(100:end-100)).^2);
                 elseif isa(obj,'Electricalsignal')
                     title(['Electrical Eye ',options.displayname])
-                    ylabel("Voltage in V");
+                    ylabel("Normalized amplitude");
                     yTickValues = linspace(maxA,minA,5);
                     min_ = min(obj.signal(100:end-100));
                     max_ = abs(max(obj.signal(100:end-100)));
                 else
                     title(['Digital Eye ',options.displayname])
-                    ylabel("Digital Signal Amplitude");
+                    ylabel("Normalized amplitude");
                     yTickValues = linspace(maxA,minA,5);
                     min_ = min(obj.signal(100:end-100));
                     max_ = abs(max(obj.signal(100:end-100)));

Classes/01_transmit/ChannelFreqResp.m

@@ -212,6 +212,81 @@ classdef ChannelFreqResp < handle
 
         end
 
+        function Target = apply(obj,Target,options)
+            % Apply the measured magnitude-only channel response.
+            arguments
+                obj
+                Target
+                options.fileName = ''
+                options.loadPath = ''
+                options.maxampdb double = 0
+            end
+
+            if isempty(obj.H)
+                obj.load("fileName",options.fileName,"loadPath",options.loadPath);
+            end
+
+            fstarget = Target.fs;
+            N_target = numel(Target.signal);
+
+            % Ignore measured DC attenuation when setting the response
+            % reference level.
+            H_measured = abs(obj.H(:)).';
+            H_measured_valid = isfinite(H_measured);
+            H_measured_dB = 20*log10(H_measured);
+
+            idx_old = (obj.faxis > 0) & ...
+                (obj.faxis < fstarget/2) & H_measured_valid;
+            H_reference_dB = max(H_measured_dB(idx_old));
+
+            H_measured_dB = H_measured_dB - H_reference_dB + options.maxampdb;
+            H_measured = 10.^(H_measured_dB/20);
+            H_measured(~H_measured_valid) = 0;
+
+            % Positive-frequency FFT bins, excluding DC and Nyquist.
+            N_positive = floor((N_target - 1)/2);
+            fnew = (1:N_positive)*fstarget/N_target;
+
+            f_old = obj.faxis(idx_old);
+            H_old = H_measured(idx_old);
+            H_interp = interp1(f_old,H_old,fnew,'linear');
+
+            % Match the edge handling used by the precompensation path.
+            nH = find(isfinite(H_interp),1,'first');
+            if isempty(nH)
+                error('ChannelFreqResp:InterpolationFailed', ...
+                    'The measured response does not overlap the target frequency grid.');
+            end
+            H_interp(1:nH-1) = H_interp(nH);
+
+            nH = find(isfinite(H_interp),1,'last');
+            H_interp(nH+1:end) = H_interp(nH);
+
+            % Real, zero-phase, conjugate-symmetric FFT response.
+            if mod(N_target,2) == 0
+                H_apply = [H_interp(1), H_interp, 0, fliplr(H_interp)];
+            else
+                H_apply = [H_interp(1), H_interp, fliplr(H_interp)];
+            end
+            H_apply = H_apply(:);
+
+            % Re-anchor the final interpolated response using only the
+            % positive-frequency bins, so DC attenuation is ignored.
+            H_apply_dB = 20*log10(abs(H_apply));
+            positive_bins = 2:(N_positive + 1);
+            H_apply_dB = H_apply_dB - max(H_apply_dB(positive_bins)) + options.maxampdb;
+            H_apply = 10.^(H_apply_dB/20);
+
+            obj.H_apply = H_apply;
+
+            % Apply the channel in the frequency domain and preserve shape.
+            signal_shape = size(Target.signal);
+            signal_in = real(Target.signal(:));
+            signal_out = real(ifft(fft(signal_in).*H_apply));
+            Target.signal = reshape(signal_out,signal_shape);
+
+        end
+
         function plot(obj)
 
             figure();

Classes/04_DSP/Equalizer/ML_MLSE_DUOBINARY.m

@@ -45,6 +45,8 @@ classdef ML_MLSE_DUOBINARY < handle
         valid
         valid_to_idx
         valid_from_idx
+        incoming_edge_idx
+        incoming_from_idx
         w
 
         % Fast lookup
@@ -124,6 +126,21 @@ classdef ML_MLSE_DUOBINARY < handle
             end
             [obj.valid_to_idx,obj.valid_from_idx] = find(obj.valid);
 
+            % Precompute compact incoming-transition lookup tables. Every
+            % trellis state has obj.S incoming transitions, so compare-select
+            % can operate on valid edges only instead of an nStates-by-nStates
+            % matrix for every symbol.
+            obj.incoming_edge_idx = zeros(obj.S, obj.nStates);
+            obj.incoming_from_idx = zeros(obj.S, obj.nStates, 'uint32');
+            incoming_count = zeros(obj.nStates, 1);
+            for edge_idx = 1:numel(obj.valid_to_idx)
+                to_idx = obj.valid_to_idx(edge_idx);
+                slot = incoming_count(to_idx) + 1;
+                obj.incoming_edge_idx(slot, to_idx) = edge_idx;
+                obj.incoming_from_idx(slot, to_idx) = obj.valid_from_idx(edge_idx);
+                incoming_count(to_idx) = slot;
+            end
+
             % --- Initialize weights
             if isempty(obj.w) || any(size(obj.w) ~= [obj.Nf+1,obj.nFeasible])
                 % obj.w = randn(obj.Nf+1,obj.nFeasible);
@@ -148,6 +165,8 @@ classdef ML_MLSE_DUOBINARY < handle
             % TRAINING
             % ==============================================================
             fprintf('\n--- Training mode ---\n');
+            obj.ber = nan(1, obj.epochs_tr);
+            obj.ce = nan(1, obj.epochs_tr);
             obj.equalize(X.signal, D.signal, obj.mu_tr, obj.epochs_tr, obj.len_tr, true);
             obj.e_tr = obj.e;
 
@@ -155,6 +174,7 @@ classdef ML_MLSE_DUOBINARY < handle
             % DECISION-DIRECTED / TESTING
             % ==============================================================
             fprintf('--- Decision-directed / detection mode ---\n');
+            obj.ber_dd = nan(1, obj.epochs_dd);
             [y, y_vit] = obj.equalize(X.signal, D.signal, obj.mu_dd, obj.epochs_dd, X.length, false);
 
             X_viterbi = X;
@@ -173,9 +193,18 @@ classdef ML_MLSE_DUOBINARY < handle
 
             for epoch = 1:epochs
                 pm = zeros(obj.nStates,1);
-                pred = zeros(nSymbols,obj.nStates,'uint32');
+                needTraceback = ~training || epoch == epochs;
-                pm_sto = nan(obj.nStates,nSymbols,'like',pm);
+                if needTraceback
+                    pred = zeros(nSymbols,obj.nStates,'uint32');
+                end
+                if debug && showPlots
+                    pm_sto = nan(obj.nStates,nSymbols,'like',pm);
+                end
                 CE_accum = 0;
+                if training
+                    CE_symbol = zeros(nSymbols,1);
+                    CE_smooth = zeros(nSymbols,1);
+                end
 
                 start_sample = 1;
                 end_sample   = N;
@@ -292,13 +321,24 @@ classdef ML_MLSE_DUOBINARY < handle
                     % ===================================================================
                     % DECODING MODE (Viterbi only)
                     % ===================================================================
-                    % Compare-Select (always executed)
+                    % Compare-select over valid incoming transitions only.
-                    vmat=inf(obj.nStates,obj.nStates);
+                    incoming_metrics = v_tilde(obj.incoming_edge_idx);
-                    vmat(obj.valid)=v_tilde;
+                    [pm_next, predecessor_slot] = min(incoming_metrics,[],1);
-                    [pm_next,pred(symbol,:)]=min(vmat,[],2);
+                    pm_next = pm_next.';
                     pm_next=pm_next-min(pm_next);
                     pm=pm_next;
-                    pm_sto(:,symbol)=pm;
+                    if needTraceback
+                        linear_idx = predecessor_slot + (0:obj.nStates-1) .* obj.S;
+                        pred(symbol,:) = obj.incoming_from_idx(linear_idx);
+                    end
+                    if debug && showPlots
+                        pm_sto(:,symbol)=pm;
+                    end
+                end
+
+                if training && ~needTraceback
+                    obj.ce(epoch)=CE_accum/symbol;
+                    continue
                 end
 
                 % --- Traceback

Datatypes/clr.m

@@ -14,6 +14,21 @@ classdef clr
 
         % Paired colormap
         Paired = struct( ...
+            'lblue',      [0.6510, 0.8078, 0.8902], ...
+            'dblue',      [0.1216, 0.4706, 0.7059], ...
+            'mblue',      [0.3863, 0.6392, 0.7981], ...
+            'lgreen',     [0.6980, 0.8745, 0.5412], ...
+            'dgreen',     [0.2000, 0.6275, 0.1725], ...
+            'mgreen',     [0.4490, 0.7510, 0.3569], ...
+            'lred',       [0.9843, 0.6039, 0.6000], ...
+            'dred',       [0.8902, 0.1020, 0.1098], ...
+            'mred',       [0.9373, 0.3530, 0.3549], ...
+            'lorange',    [0.9922, 0.7490, 0.4353], ...
+            'dorange',    [1.0000, 0.4980, 0.0000], ...
+            'morange',    [0.9961, 0.6235, 0.2176], ...
+            'llila',      [0.7922, 0.6980, 0.8392], ...
+            'dlila',      [0.4157, 0.2392, 0.6039], ...
+            'mlila',      [0.6040, 0.4686, 0.7216], ...
             'lightblue',  [0.6510, 0.8078, 0.8902], ...
             'blue',       [0.1216, 0.4706, 0.7059], ...
             'lightgreen', [0.6980, 0.8745, 0.5412], ...

Functions/EQ_blocks/duobinary_target.m

@@ -104,13 +104,13 @@ function [db_results] = duobinary_target(eq_, mlse_,M, rx_signal, tx_symbols, tx
             [bits_db,errors_db,ber_db,a]  = calc_ber(rx_bits_mlse.signal,tx_bits.signal,"skip_front",100,"skip_end",150,"returnErrorLocation",1);
             burst_db = count_error_bursts(a, 40);
     
-            cols = linspecer(8);
+            % cols = linspecer(8);
-            figure();hold on;
+            % figure();hold on;
-            stem(1:40,burst_db,'LineWidth',1,'Color',cols(4,:),'Marker','_','DisplayName','w/o diff. precoder');
+            % stem(1:40,burst_db,'LineWidth',1,'Color',cols(4,:),'Marker','_','DisplayName','w/o diff. precoder');
-            stem(1:40,burst_db_precoded,'LineWidth',1,'Color',cols(3,:),'Marker','.','LineStyle','-','DisplayName','w diff. precoder');
+            % stem(1:40,burst_db_precoded,'LineWidth',1,'Color',cols(3,:),'Marker','.','LineStyle','-','DisplayName','w diff. precoder');
-            xlabel('Bit Error Burst Length')
+            % xlabel('Bit Error Burst Length')
-            ylabel('Occurence')
+            % ylabel('Occurence')
-            set(gca, 'yscale', 'log');
+            % set(gca, 'yscale', 'log');
     end
     
     % M = numel(unique(tx_symbols.signal));
@@ -118,6 +118,8 @@ function [db_results] = duobinary_target(eq_, mlse_,M, rx_signal, tx_symbols, tx
     
     [bits_db,errors_db,ber_db,errorIndice_db] = calc_ber(rx_bits.signal,tx_bits.signal,"skip_front",100,"skip_end",150,"returnErrorLocation",1);
     
+    [snr_db_target, snr_db_target_lvl] = calc_snr(db_ref_sequence.signal, eq_noise.signal);
+
     alpha = arburg(eq_noise.signal,1);%pf_.coefficients(2);
     alpha = alpha(2); 
     
@@ -152,6 +154,8 @@ function [db_results] = duobinary_target(eq_, mlse_,M, rx_signal, tx_symbols, tx
     db_results.metrics.AIR = air_mlse;
     db_results.metrics.MLSE_dir = mlse_.DIR;
     db_results.metrics.Alpha = alpha;
+    db_results.metrics.SNR = snr_db_target;
+    db_results.metrics.SNR_level = snr_db_target_lvl;
     
     % Create DB results structure
     db_results.config = Equalizerstruct();
@@ -177,7 +181,10 @@ function [db_results] = duobinary_target(eq_, mlse_,M, rx_signal, tx_symbols, tx
     
         showEQNoisePSD(eq_noise,"fignum",250,"displayname",'Duobinary Target Noise after Equalization');
     
-        fprintf('DB tgt BER: %.2e \n',ber_db);
+        if options.decoding_mode == db_decoder.sequencedetection
+            fprintf('DB tgt BER: %.2e \n',ber_db); %not relevant for memoryless, wont work
+        end
+        fprintf('DB tgt BER precoded: %.2e \n',ber_db_diff_precoded);
     
         figure(341); clf;
         tx_symbols_uncoded = Duobinary().decode(db_ref_sequence);

Functions/EQ_blocks/vnle_postfilter_mlse.m

@@ -50,6 +50,11 @@ eq_signal_hd = PAMmapper(M, 0).quantize(eq_signal_sd);
 
 [tx_symbols_pr,~] = pf_.process(tx_symbols, eq_noise);
 
+% Calc SNR of Partial Response Signal 
+pr_noise = tx_symbols_pr-mlse_sig_sd;
+[snr_partial_response, ~] = calc_snr(tx_symbols_pr.signal, pr_noise.signal);
+
+
 if 0 %tx_symbols.fs > 190e9
     if pf_.ncoeff == 1
             if pf_.coefficients(2) < 0
@@ -83,7 +88,7 @@ mlse_sig_hd = PAMmapper(M, 0, "eth_style", options.eth_style_symbol_mapping).qua
 
 %% Calculate performance metrics
 % VNLE metrics
-[snr_vnle, snr_vnle_lvl] = calc_snr(tx_symbols.signal, eq_noise.signal);
+[snr_full_response, snr_vnle_lvl] = calc_snr(tx_symbols.signal, eq_noise.signal);
 % [gmi_vnle] = calc_air(eq_signal_sd, tx_symbols, "skip_front", 10000, "skip_end", 10000);
 
 %calculate bitwise GMI
@@ -131,7 +136,7 @@ ffe_results.metrics.numBits = numbits.vnle;
 ffe_results.metrics.numBitErr = errors.vnle;
 ffe_results.metrics.BER_precoded = bers.vnle_precoded;
 ffe_results.metrics.numBitErr_precoded = errors.vnle_precoded;
-ffe_results.metrics.SNR = snr_vnle;
+ffe_results.metrics.SNR = snr_full_response;
 ffe_results.metrics.SNR_level = snr_vnle_lvl;
 ffe_results.metrics.STD = std_vnle_total;
 ffe_results.metrics.STD_level = std_vnle_lvl;
@@ -165,7 +170,7 @@ mlse_results.metrics.numBits = numbits.mlse;
 mlse_results.metrics.numBitErr = errors.mlse;
 mlse_results.metrics.BER_precoded = bers.mlse_precoded;
 mlse_results.metrics.numBitErr_precoded = errors.mlse_precoded;
-% mlse_results.metrics.SNR = NaN;
+mlse_results.metrics.SNR = snr_partial_response;
 mlse_results.metrics.GMI = gmi_mlse;
 mlse_results.metrics.AIR = air_mlse;
 % mlse_results.metrics.EVM = NaN;

Functions/EQ_recipes/dsp_400g_recipe.m

@@ -225,6 +225,7 @@ else
         ml_mlse_db_results.config.comment = 'function: ML-based MLSE; duobinary encoded';
         ml_mlse_db_results.recipe_config = collectRecipeConfig("ml_mlse_db", ml_mlse_db_equalizer, p, options);
         output.mlmlse_db_package = ml_mlse_db_results;
+        ml_mlse_db_results.metrics.print;
     end
 
     if p.run_mlse_db
@@ -275,10 +276,10 @@ p = struct();
 p.run_ffe = false;
 p.run_vnle = false;
 p.run_dfe = false;
-p.run_vnle_mlse = false;
+p.run_vnle_mlse = true;
-p.run_dbtgt = false;
+p.run_dbtgt = true;
-p.run_ml_mlse = true;     % non-encoded and precoded branches
+p.run_ml_mlse = false;     % non-encoded and precoded branches
-p.run_ml_mlse_db = true;  % db_encoded: ML-based MLSE
+p.run_ml_mlse_db = false;  % db_encoded: ML-based MLSE
 p.run_mlse_db = true;     % db_encoded: conventional MLSE
 
 
@@ -321,7 +322,7 @@ p.decoding_mode = [];
 
 p.ml_mlse_mu_tr = 0.03;
 p.ml_mlse_mu_dd = 0.03;
-p.ml_mlse_epochs_tr = 100;
+p.ml_mlse_epochs_tr = 150;
 p.ml_mlse_epochs_dd = 1;
 p.ml_mlse_len_tr = [];
 p.ml_mlse_order = 11;
@@ -376,20 +377,22 @@ end
 
 function dbtgt_results = runDuobinaryTarget(eq_dbtgt, mlse_db, ...
         Scpe_sig, Symbols, Tx_bits, options, p)
-if isempty(p.decoding_mode)
+
-    dbtgt_results = duobinary_target(eq_dbtgt, mlse_db, options.M, ...
+    if isempty(p.decoding_mode)
-        Scpe_sig, Symbols, Tx_bits, ...
+        dbtgt_results = duobinary_target(eq_dbtgt, mlse_db, options.M, ...
-        "precode_mode", options.duob_mode, ...
+            Scpe_sig, Symbols, Tx_bits, ...
-        "showAnalysis", options.debug_plots, ...
+            "precode_mode", options.duob_mode, ...
-        "postFFE", []);
+            "showAnalysis", options.debug_plots, ...
-else
+            "postFFE", []);
-    dbtgt_results = duobinary_target(eq_dbtgt, mlse_db, options.M, ...
+    else
-        Scpe_sig, Symbols, Tx_bits, ...
+        dbtgt_results = duobinary_target(eq_dbtgt, mlse_db, options.M, ...
-        "precode_mode", options.duob_mode, ...
+            Scpe_sig, Symbols, Tx_bits, ...
-        "showAnalysis", options.debug_plots, ...
+            "precode_mode", options.duob_mode, ...
-        "postFFE", [], ...
+            "showAnalysis", options.debug_plots, ...
-        "decoding_mode", p.decoding_mode);
+            "postFFE", [], ...
-end
+            "decoding_mode", p.decoding_mode);
+    end
+
 end
 
 function mlse = buildMlse(M, duobMode, p, mode)

Functions/EQ_visuals/showEQNoisePSD.m

@@ -30,7 +30,7 @@ end
 
     % Ensure the figure is ready before calling spectrum
     eq_noise = eq_noise - mean(eq_noise.signal);
-    eq_noise.spectrum("displayname", options.displayname, "fignum", fig.Number, "normalizeTo0dB", 0,"color",options.color,"fft_length",4096);
+    eq_noise.spectrum("displayname", options.displayname, "fignum", fig.Number, "normalizeTo0dB", 0,"color",options.color,"fft_length",4096,"normalizeToDC",0);
 
     if ~isnan(options.postfilter_taps)
         % Hold on to the figure for further plotting

Functions/EQ_visuals/showLevelHistogram.m

@@ -5,7 +5,8 @@ arguments
     options.fignum (1,1) double = NaN % Default to NaN if not provided
     options.displayname (1,:) char = '' % Default to an empty string if not provided
     options.ref_symbol_uncoded = []
-    options.nbins (1,1) double = 1000
+    options.nbins (1,1) double = 200
+    options.legendLabels = []
 end
 
     if isa(eq_signal,'Signal')
@@ -21,6 +22,7 @@ end
     eq_signal = eq_signal(:);
     ref_symbols = ref_symbols(:);
     ref_symbol_uncoded = options.ref_symbol_uncoded(:);
+    legend_labels = string(options.legendLabels);
 
     assert(numel(eq_signal) == numel(ref_symbols), ...
         'showLevelHistogram:LengthMismatch', ...
@@ -66,11 +68,16 @@ end
         for lvl = 1:numel(constellation)
             intermediate = received_sd(lvl,:);
             cnt(lvl) = round(numel(intermediate(~isnan(intermediate)))./numel(eq_signal),3).*100;
+            if isempty(legend_labels)
+                display_name = ['Lvl ',num2str(lvl),' ; ',num2str(cnt(lvl)),' '];
+            else
+                display_name = char(legend_labels(lvl));
+            end
             hold on
             warning off
             histogram(received_sd(lvl,:),options.nbins, ...
                 "EdgeAlpha",0, ...
-                "DisplayName",['Lvl ',num2str(lvl),' ; ',num2str(cnt(lvl)),' '], ...
+                "DisplayName",display_name, ...
                 "FaceColor",lvlcol(lvl,:), ...
                 "Normalization","pdf");
             warning on
@@ -90,7 +97,7 @@ end
         rm_idx = mid + (-1:2); % two before mid and two after (2x2 removal centered)
         rm_idx = max(1,min(size(lvlcol,1),rm_idx));
         lvlcol(rm_idx,:) = [];
-        lvlcol = lvlcol(1:numel(sir_group_labels),:);
+        % lvlcol = lvlcol(1:numel(sir_group_labels),:);
 
         for db_lvl = 1:numel(db_constellation)
             db_mask = ref_symbols == db_constellation(db_lvl);
@@ -99,12 +106,20 @@ end
             cnt = round(nnz(ref_symbol_uncoded == mapped_class)./numel(eq_signal),3).*100;
 
             if db_lvl == findFirstMappedDbLevel(ref_symbols,ref_symbol_uncoded,db_constellation,mapped_class)
-                display_name = ['p(y|x_',num2str(class_idx),') ; ',num2str(cnt),' '];
+                if isempty(legend_labels)
-                display_name = ['p(y|x_',num2str(class_idx),')'];
+                    display_name = ['p(y|x_',num2str(class_idx),') ; ',num2str(cnt),' '];
+                    display_name = ['p(y|x_',num2str(class_idx),')'];
+                else
+                    display_name = char(legend_labels(class_idx));
+                end
                 handle_visibility = "on";
             else
-                display_name = ['p(y|x_',num2str(class_idx),') ; ',num2str(cnt),' '];
+                if isempty(legend_labels)
-                display_name = ['p(y|x_',num2str(class_idx),')'];
+                    display_name = ['p(y|x_',num2str(class_idx),') ; ',num2str(cnt),' '];
+                    display_name = ['p(y|x_',num2str(class_idx),')'];
+                else
+                    display_name = char(legend_labels(class_idx));
+                end
                 handle_visibility = "off";
             end
 
@@ -123,7 +138,7 @@ end
         end
     end
     xlim([-3 3]);
-    legend
+    legend("Interpreter", "latex");
     grid on
 
     % view([90 -90]);

Functions/Job_Processing/loadAndSyncRunSignals.m

@@ -3,7 +3,11 @@ function [Bits, Symbols, Scpe_cell, found_sync] = loadAndSyncRunSignals(dataTabl
 %
 % Inputs:
 %   dataTable - one-row table with run metadata and signal file paths
-%   options   - struct with storage_path, start_occurence and max_occurences
+%   options   - scalar struct with the following fields:
+%       storage_path    - root directory containing the signal files.
+%       start_occurence - first synchronized occurrence to return (default: 1).
+%       max_occurences  - maximum number of synchronized occurrences to return
+%                         (default: 1).
 %
 % Outputs:
 %   Bits       - transmitted bit reference
@@ -11,6 +15,14 @@ function [Bits, Symbols, Scpe_cell, found_sync] = loadAndSyncRunSignals(dataTabl
 %   Scpe_cell  - synchronized received signal occurrences
 %   found_sync - true when a valid synchronization was found
 
+arguments
+    dataTable
+    options
+    % options.storage_path 
+    % options.start_occurence = 1
+    % options.max_occurences = 1
+end
+
 found_sync = 0;
 tempLocalStorage = 1;
 Scpe_cell = {};
@@ -130,7 +142,7 @@ end
 function Scpe_cell = selectSyncedOccurrences(Scpe_cell, options)
 available_occurences = length(Scpe_cell);
 start_occurence = floor(getOption(options, 'start_occurence', 1));
-max_occurences = floor(getOption(options, 'max_occurences', available_occurences));
+max_occurences = floor(getOption(options, 'max_occurences', 1));
 
 if available_occurences < 1
     warning('loadAndSyncRunSignals:NoSyncedOccurrences', ...

Functions/Metrics/calc_snr.m

@@ -29,15 +29,21 @@ function [snr_all, snr_per_level] = calc_snr(tx_signal, eq_noise)
     
     % Get the unique amplitude levels in the transmitted signal
     levels = unique(tx_signal);
+    snr_per_level = zeros(numel(levels),1);
 
-    % Preallocate an array to store the SNR for each unique level
+    try
-    % Loop over each unique level to compute the SNR for that level
+        % Preallocate an array to store the SNR for each unique level
-    for i = 1:length(levels)
+        % Loop over each unique level to compute the SNR for that level
-        % Find indices where tx_signal equals the current level
+        for i = 1:length(levels)
-        idx = (tx_signal == levels(i));
+            % Find indices where tx_signal equals the current level
+            idx = (tx_signal == levels(i));
         
-        % Compute the SNR for these indices
+            % Compute the SNR for these indices
-        snr_per_level(i) = snr(tx_signal(idx), eq_noise(idx));
+            snr_per_level(i) = snr(tx_signal(idx), eq_noise(idx));
         
+        end
+    catch ME
+        % Handle any errors that occur during SNR calculation
+        % warning('Error calculating SNR for level %d: %s', levels(i), ME.message);
     end
 end

Functions/frequency_wavelength/calcWavelengthPlan.m

@@ -0,0 +1,24 @@
+function channelplan_nm = calcWavelengthPlan(N, df_hz, center_nm)
+
+vec = [N:-1:1]-(N/2+0.5);
+
+channelplan_hz = nm2hz(center_nm) + (vec * df_hz) ;
+
+channelplan_nm = hz2nm(channelplan_hz);
+
+%  dfft = 1.367053998632946e+07; %hz
+%  a = diff(channelplan_hz)./2./dfft;
+
+end
+
+function hz = nm2hz(nm)
+    wavelen_in_m = nm.* 1e-9; 
+    hz =  (299792458 ./ wavelen_in_m); %frequency in Terahertz
+end
+
+function nm = hz2nm(hz)
+    m =  (299792458 ./ hz); %wavelength in meter
+    nm = m .* 10^9;
+end
+
+

Functions/frequency_wavelength/df2dw.m

@@ -0,0 +1,4 @@
+function dw = df2dw(df,f)
+    %delta frequency to delta wavelength
+    dw = 299792458 .* df ./ f.^2;
+end

Functions/frequency_wavelength/dw2df.m

@@ -0,0 +1,4 @@
+function df = dw2df(dw,w)
+    %delta wavelength to delta frequency
+    df = 299792458 .* dw ./ w.^2;
+end

Functions/frequency_wavelength/getSweepWavelengths.m

@@ -0,0 +1,7 @@
+function positions = getSweepWavelengths(N, df_hz, StartNm)
+    positions = zeros(1, N);
+    for i = 1:N
+        position = (299792458 / (299792458 / (StartNm * 1e-9) + (i - 1) * df_hz)) * 1e9;
+        positions(i) = position;
+    end
+end

Functions/frequency_wavelength/hz2nm.m

@@ -0,0 +1,4 @@
+function nm = hz2nm(hz)
+    m =  (299792458 ./ hz); %wavelength in meter
+    nm = m .* 10^9;
+end

Functions/frequency_wavelength/nm2hz.m

@@ -0,0 +1,4 @@
+function hz = nm2hz(nm)
+    wavelen_in_m = nm.* 1e-9; 
+    hz =  (299792458 ./ wavelen_in_m); %frequency in Hertz
+end

Functions/frequency_wavelength/nm2thz.m

@@ -0,0 +1,4 @@
+function thz = nm2thz(nm)
+    wavelen_in_m = nm.* 1e-9; 
+    thz =  (299792458 ./ wavelen_in_m) .*1e-12; %frequency in Terahertz
+end

Functions/frequency_wavelength/thz2nm.m

@@ -0,0 +1,4 @@
+function nm = thz2nm(thz)
+    freq_in_hz = thz.* 1e12; 
+    nm =  (299792458 ./ freq_in_hz) .*1e9; %wavelength in nanometer
+end

Functions/mat2tikz_improved.m

@@ -16,6 +16,10 @@ matlab2tikz(char(filename), ...
     'height', '\fheight', ...
     'showInfo', false, ...
     'extraAxisOptions', { ...
+        'clip=true',...
+        'clip marker paths=true',...
+        'grid style={dashed, draw=gray80, line width=0.25pt}',...
+        'minor grid style={densely dotted, draw=gray80, line width=0.25pt}',...
         'xlabel style={font=\color{white!15!black}\small}', ...
         'ylabel style={font=\color{white!15!black}\small}', ...
         'scaled ticks=false', ...

Functions/saveDirectoryInfo.m

@@ -0,0 +1,30 @@
+function outputFile = saveDirectoryInfo(directoryPath)
+% Save metadata for all files and subdirectories under directoryPath.
+
+directoryPath = string(directoryPath);
+
+if ~isfolder(directoryPath)
+    error("Directory does not exist: %s", directoryPath);
+end
+
+% Recursively list all files and subdirectories
+info = dir(fullfile(directoryPath, "**", "*"));
+
+% Remove "." and ".." entries
+info = info(~ismember({info.name}, {'.', '..'}));
+
+% Create an output filename in MATLAB's current folder
+[~, folderName] = fileparts(char(directoryPath));
+if isempty(folderName)
+    folderName = 'directory';
+end
+
+timestamp = datestr(now, 'yyyymmdd_HHMMSS');
+outputFile = fullfile(pwd, ...
+    sprintf('directory_info_%s_%s.mat', folderName, timestamp));
+
+% Save the path and directory information
+save(outputFile, 'directoryPath', 'info');
+
+fprintf('Saved information to:\n%s\n', outputFile);
+end

Tests/04_DSP/Equalizer/ML_MLSE_DUOBINARY_test.m

@@ -46,6 +46,27 @@ classdef ML_MLSE_DUOBINARY_test < IMDDTestCase
                 txSymbols.signal(11:end-10), "AbsTol", 1e-12);
         end
 
+        function intermediateTrainingEpochsKeepWeightsWithoutTracebackBer(testCase)
+            [~, ~, txPrecoded, txEncoded] = makePam4Fixture(512);
+
+            eq = ML_MLSE_DUOBINARY( ...
+                "sps", 1, ...
+                "order", 1, ...
+                "len_tr", length(txEncoded), ...
+                "epochs_tr", 2, ...
+                "epochs_dd", 1, ...
+                "mu_tr", 0.01, ...
+                "mu_dd", 0.01, ...
+                "adaptive_mu", false, ...
+                "L", 1);
+
+            eq.process(txEncoded, txPrecoded);
+
+            testCase.verifyTrue(isnan(eq.ber(1)));
+            testCase.verifyTrue(isfinite(eq.ber(2)));
+            testCase.verifyTrue(all(isfinite(eq.ce)));
+        end
+
         function resultWrapperReportsBothPrecodedAndOriginalBer(testCase)
             [txBits, ~, txPrecoded, txEncoded] = makePam4Fixture(32000);
 

projects/AWG_output_power_simulation/output_power.m

@@ -5,25 +5,32 @@ fdac = 256e9;%fsym;
 fadc = 256e9;
 fsym = ([32:16:240].*1e9);
 
-%fsym = 160e9;
+% %fsym = 160e9;
-% 1) PRBS Generation
+% % 1) PRBS Generation
-O = 18; %order of prbs
+% O = 18; %order of prbs
-N = 2^(O-1); %length of prbs
+% N = 2^(O-1); %length of prbs
-[~,seed] = prbs(O,1); %initialize first seed of prbs
+% [~,seed] = prbs(O,1); %initialize first seed of prbs
-bitpattern=[];
+% bitpattern=[];
+% 
+% for i = 1:log2(M)
+%     [bitpattern(:,i),seed] = prbs(O,N,seed);
+% end
+% 
+% 
+% if M == 6
+%     bitpattern = reshape(bitpattern,[],1);
+%     bitpattern = bitpattern(1:end-mod(length(bitpattern),5));
+% end
 
-for i = 1:log2(M)
+bits = Signalgenerator( ...
-    [bitpattern(:,i),seed] = prbs(O,N,seed);
+    "form", signalform.prms, ...
-end
+    "M", M, ...
+    "order", 17).process();
+% symbols = PAMmapper(4, 0).map(bits);
 
 
-if M == 6
-    bitpattern = reshape(bitpattern,[],1);
-    bitpattern = bitpattern(1:end-mod(length(bitpattern),5));
-end
-
 % 2 ) Build Inf. signal class
-bits = Informationsignal(bitpattern);
+% bits = Informationsignal(bitpattern);
 
 % 5) AWG (lowpass, quantization, sample and hold)
 kover = 8;
@@ -131,7 +138,7 @@ ylabel("Vpp in V")
 legend
 ylim([0.3 1.4])
 
-
+%%
 figure(7)
 hold on
 scatter(fsym.*1e-9,powerlist1,'DisplayName','M8199B','MarkerFaceColor',cols(1,:),'MarkerEdgeColor',cols(1,:),'LineWidth',2);

projects/Advanced_DSP_for_400G_IMDD_experiments/Auswertung_JLT/final/FIGURE_EYES.m

@@ -1,5 +1,5 @@
-dsp_options.storage_path    = 'Z:\2024\sioe_labor\';
+dsp_options.storage_path    = 'W:\labdata\sioe_labor\';
-dsp_options.max_occurences = 1;
+dsp_options.max_occurences = 10;
 database    = DBHandler("dataBase", 'labor_highspeed', "type",  'mysql' );
 
 
@@ -7,34 +7,32 @@ cols = cbrewer2('BuPu',25);
 cols = [cols(end-10:2:end,:)];
 cols = cbrewer2('Set1',6);
 
-fignum = 200;
-fig=figure(fignum);clf;
-
 dbmode = 0;
 
 % 1 - PAM 4 with preemphasis
 fp = QueryFilter();
-M = 8;
+M = 4;
-rate = [360e9];
+% rate = [300e9];
 fp.where('Runs', 'pam_level','EQUALS', M);
 fp.where('Runs', 'bitrate','EQUALS', rate);%360,390
+% fp.where('Runs', 'symbolrate','EQUALS',165e9);
 fp.where('Runs', 'fiber_length','EQUALS', 2);
 fp.where('Runs', 'wavelength','EQUALS', 1310);
 fp.where('Runs', 'db_mode','EQUALS', dbmode);
 fp.where('Runs', 'rop_attenuation','EQUAL', 0);
 
 [dataTable,~] = database.queryDB(fp, database.getTableFieldNames('Runs'));
-
+dataTable = dataTable(1,:);
-dataTable   = queryRunid(dataTable.run_id, database);
+% dataTable   = queryRunid(dataTable.run_id, database);
 fsym        = dataTable.symbolrate;
 M           = double(dataTable.pam_level);
 duob_mode   = db_mode(strrep(dataTable.db_mode,'"',''));
 
 % Load and Sync signal data from DB
-[Tx_bits, Symbols, Scpe_cell, ~] = loadAndSyncRunSignals(dataTable, dsp_options);
+[Tx_bits, Symbols, Scpe_cell, ~] = loadAndSyncRunSignals(dataTable,dsp_options);
 
 Scpe_sig_syncd = Scpe_cell{1};
-Scpe_sig_syncd.eye(fsym,M,"fignum",rate.*1e-9*M+1,"displayname",' Eye of Signal');
+% Scpe_sig_syncd.eye(fsym,M,"fignum",rate.*1e-9*M+1,"displayname",' Eye of Signal');
 %%%%%% SNR CHEAT - Avges the measured signal occurences found after correlation in "tsynch" %%%%%%
 average_signals = 1;
 if average_signals
@@ -46,16 +44,19 @@ if average_signals
     scope_mean = scope_mean ./ n;
     Scpe_sig_avg.signal = scope_mean;
 
-    Scpe_sig_avg.spectrum("displayname","Scope PSD","fignum",20,"normalizeTo0dB",1);
+    % Scpe_sig_avg.spectrum("displayname","Scope PSD","fignum",20,"normalizeTo0dB",1);
-    Scpe_sig_avg.plot("displayname","Scope raw signal","fignum",27,"clear",1);
+    % Scpe_sig_avg.plot("displayname","Scope raw signal","fignum",27,"clear",1);
     Scpe_sig_avg = Scpe_sig_avg.*1.25;
-    Scpe_sig_avg.eye(fsym,M,"fignum",rate.*1e-9*M,"displayname",' Eye of AVG Signal');
+    % Scpe_sig_avg.eye(fsym,M,"fignum",rate.*1e-9*M,"displayname",' Eye of AVG Signal');
+    Scpe_sig = Scpe_sig_avg.normalize("mode","rms");
 end
 
-% Preprocess signal
+% Scpe_sig = preprocessSignal(Scpe_sig_avg, Symbols, fsym);
-Scpe_sig = preprocessSignal(Scpe_sig_avg, Symbols, fsym);
 
-Scpe_sig.eye(fsym,M,"fignum",M*10);
+
+%% Eye of Preprocess signal
+
+% Scpe_sig.eye(fsym,M,"fignum",M*10);
 
 
 
@@ -71,8 +72,67 @@ Scpe_sig.eye(fsym,M,"fignum",M*10);
 %         'legend style={font=\footnotesize}', ...
 %         'legend columns=1' ...
 %     } );
+%% Simply FFE
 
-%%
+len_tr = 4096*2;
+% combine and minimize repeated params
+mu_ffe = [0.0001,0.0008,0.001];
+mu_dd  = 0.05;
+mu_dc  = 0.005;
+
+% single ffe_order used
+ffe_order = [50];
+
+% map into p for FFE init (compact)
+p.epochs_tr    = 5;
+p.epochs_dd    = 5;
+p.len_tr       = 4096*2;
+p.ffe_mu_tr    = mu_ffe(1);
+p.ffe_mu_dd    = mu_dd;
+p.ffe_order    = ffe_order;
+p.eq_sps       = 2;
+p.optimize_mus = true;
+p.dd_mode      = true;
+p.ffe_adaption = 1;
+p.mu_dc        = mu_dc;
+
+% Initialize FFE with mapped parameters
+eq_ffe = FFE("epochs_tr", p.epochs_tr, ...
+    "epochs_dd", p.epochs_dd, ...
+    "len_tr", p.len_tr, ...
+    "mu_dd", p.ffe_mu_dd, ...
+    "mu_tr", p.ffe_mu_tr, ...
+    "order", p.ffe_order(1), ...
+    "sps", p.eq_sps, ...
+    "decide", false, ...
+    "optmize_mus", p.optimize_mus, ...
+    "dd_mode", p.dd_mode, ...
+    "adaption_technique", p.ffe_adaption, ...
+    "dc_tracking_mu", p.mu_dc);
+
+mu_ffe      = [0.0001, 0.0008, 0.001];
+mu_dfe      = 0.0004;
+eq_ffe = EQ("Ne", [50,0,0], ...
+    "Nb", [0,0,0], ...
+    "training_length", p.len_tr, ...
+    "training_loops", p.epochs_tr, ...
+    "dd_loops", p.epochs_dd, ...
+    "K", 2, ...
+    "DCmu", p.mu_dc, ...
+    "DDmu", [mu_ffe mu_dfe], ...
+    "DFEmu", 0.005, ...
+    "FFEmu", 0, ...
+    "plotfinal", 0, ...
+    "ideal_dfe", false);
+
+[ffe_results, equalized_signal] = ffe(eq_ffe, M, Scpe_sig, Symbols, Tx_bits, ...
+    "precode_mode", dbmode, ...
+    "showAnalysis", 0, ...
+    "postFFE", [], ...
+    "eth_style_symbol_mapping", 0);
+
+equalized_signal.eye(fsym,M,"fignum",M*2);
+%% Duobinary
 
 if duob_mode == db_mode.no_db && M == 6 %only for PAM-6 and no duobinary precoding, otherwise leads to false sequence estimation
     trellexlusion = 1;
@@ -102,178 +162,4 @@ dbt_results = duobinary_target(eq_, mlse_db_, M, Scpe_sig, Symbols, Tx_bits, ...
     'showAnalysis', 1,...
     "postFFE", []);
 
-%% === FINAL FIGURE SIZE ===
 
-% Existing figure numbers
-figEye   = 249;
-figConst = 341;
-
-% Find axes in the source figures
-srcAxEye   = findobj(figEye, 'Type', 'axes');
-srcAxConst = findobj(figConst, 'Type', 'axes');
-
-% Create new combined figure
-figCombined = figure;
-t = tiledlayout(figCombined, 1, 2);
-t.TileSpacing = 'compact';
-t.Padding = 'compact';
-
-% ------------------------------------------------------------
-% LEFT TILE: EYE DIAGRAM
-% ------------------------------------------------------------
-ax1 = nexttile(t, 1);
-hold(ax1, 'on')
-
-% Copy children (images, lines, patches, hist objects, etc.)
-copyobj(srcAxEye.Children, ax1);
-
-% Copy labels and title
-ax1.XLabel.String = srcAxEye.XLabel.String;
-ax1.YLabel.String = srcAxEye.YLabel.String;
-ax1.Title.String  = srcAxEye.Title.String;
-
-% Copy axis limits
-ax1.XLim = srcAxEye.XLim;
-ax1.YLim = srcAxEye.YLim;
-ax1.YDir = srcAxEye.YDir;
-
-% Copy ticks + labels EXACTLY (including remapped/scaled ones)
-ax1.XTick      = srcAxEye.XTick;
-ax1.XTickLabel = srcAxEye.XTickLabel;
-ax1.YTick      = srcAxEye.YTick;
-ax1.YTickLabel = srcAxEye.YTickLabel;
-
-% Copy colormap + clim (important for density eye)
-colormap(ax1, colormap(srcAxEye.Parent)); 
-ax1.CLim = srcAxEye.CLim;
-
-% Copy any style props that matter
-ax1.TickDir     = srcAxEye.TickDir;
-ax1.TickLength  = srcAxEye.TickLength;
-ax1.FontSize    = srcAxEye.FontSize;
-ax1.Box         = srcAxEye.Box;
-
-grid(ax1,'on');
-
-
-% ------------------------------------------------------------
-% RIGHT TILE: CONSTELLATION HISTOGRAM
-% ------------------------------------------------------------
-ax2 = nexttile(t, 2);
-hold(ax2, 'on')
-
-copyobj(srcAxConst.Children, ax2);
-
-% Copy labels and title
-ax2.XLabel.String = srcAxConst.XLabel.String;
-ax2.YLabel.String = srcAxConst.YLabel.String;
-ax2.Title.String  = srcAxConst.Title.String;
-
-% The histogram uses the same y-axis as the eye
-% Extract mapping from eye
-rawTicks      = ax1.YTick;
-rawLabelsCell = ax1.YTickLabel;
-trueVoltages  = str2double(rawLabelsCell);
-
-% Apply true voltages to the histogram axis
-ax2.XTick      = flip(trueVoltages);
-ax2.XTickLabel = flip(rawLabelsCell);
-
-% Set histogram y-limits to match the actual voltages
-ax2.XLim = [min(trueVoltages) max(trueVoltages)];
-
-% Ensure eye diagram prints the same (we *do not* touch ax1.YLim)
-ax1.XTickLabel = rawLabelsCell;
-
-
-% Copy colormap (your histogram uses same palette)
-colormap(ax2, colormap(srcAxConst.Parent));
-
-% Style properties
-ax2.TickDir     = srcAxConst.TickDir;
-ax2.TickLength  = srcAxConst.TickLength;
-ax2.FontSize    = srcAxConst.FontSize;
-ax2.Box         = srcAxConst.Box;
-
-grid(ax2,'on');
-
-% ============================================================
-% remove right y-axis completely
-% ============================================================
-ax2.XAxis.Visible = 'off';     % hides ticks + labels + axis line
-
-% BUT we still keep the YTick positions internally for alignment:
-% ax2.YTick = <values already set earlier> ;
-
-
-% ============================================================
-% minimize distance between the two plots
-% ============================================================
-t.TileSpacing = 'none';      % no space between tiles
-t.Padding     = 'none';      % no outer padding
-
-% Also reduce internal padding for each axis
-ax1.Position(3) = ax1.Position(3) + 0.02;   % widen eye a bit
-ax2.Position(1) = ax2.Position(1) - 0.02;   % pull histogram closer
-
-
-% Keep left axis grid visible
-ax2.YGrid = 'off';
-
-%
-%  =====================================================================
-% FINAL POLISHING: unified visual style
-% =======================================================================
-
-% --- unified font size ---
-FS = 12;
-set([ax1 ax2], 'FontSize', FS);
-
-% --- unified axis line width (outline stroke thickness) ---
-LW = 1.0;
-set([ax1 ax2], 'LineWidth', LW);
-
-% --- unified tick length ---
-TL = [.015 .015];
-set([ax1 ax2], 'TickLength', TL);
-
-% --- unified grid style ---
-set([ax1 ax2], 'XGrid', 'on', 'YGrid', 'on');
-set([ax1 ax2], 'GridLineStyle', '--');
-set([ax1 ax2], 'GridAlpha', 0.2);
-
-% --- remove right y-axis ticks and labels ---
-ax2.YAxis.Visible = 'off';
-
-% --- copy colormap + CLim from the eye to histogram (synchronize look) ---
-colormap(ax1, colormap(srcAxEye.Parent));
-colormap(ax2, colormap(srcAxEye.Parent));
-ax2.CLim = ax1.CLim;
-
-% --- minimal spacing between tiles ---
-t.TileSpacing = 'none';
-t.Padding     = 'none';
-
-
-% --- pull the panels together (touching boundary effect) ---
-pos1 = ax1.Position;
-pos2 = ax2.Position;
-
-% Shift histogram left until the outlines touch
-pos2(1) = pos1(1) + pos1(3) - 0.002;   % 0.002 = fine overlap control
-ax2.Position = pos2;
-
-% Expand histogram slightly, remove white band
-pos2 = ax2.Position;
-pos2(3) = pos2(3) + 0.01;
-ax2.Position = pos2;
-
-% Ensure the left plot stays correct after the move
-ax1.Position = pos1;
-
-% --- enforce same visible outline ---
-% For ax2, create a fake left spine (since YAxis is hidden)
-ax2.Box = 'on';   % keep outline but no ticks on the right
-ax1.Box = 'on';
-
-ax2.View = [90 -90];

projects/Advanced_DSP_for_400G_IMDD_experiments/Auswertung_JLT/final/FIGURE_Spectra.m

@@ -1,4 +1,4 @@
-dsp_options.storage_path    = 'Z:\2024\sioe_labor\';
+dsp_options.storage_path    = 'W:\labdata\sioe_labor\';
 dsp_options.max_occurences = 1;
 % database    = DBHandler("dataBase", 'labor_highspeed', "type",  'mysql' );
 dsp_options.database_type   = "mysql";
@@ -18,51 +18,64 @@ cols = cbrewer2('BuPu',25);
 cols = [cols(end-10:2:end,:)];
 cols = cbrewer2('Set1',6);
 
-fignum = 200;
+% fignum = 200;
-fig=figure(fignum);clf;
+% fig=figure(fignum);clf;
 
 for dbmode = 0%length(rates)
 
 
     if 1
-    rcalpha     = 0.05;
+        rcalpha     = 0.05;
-    fsym = rates/2;
+        fsym = rates/2;
-    pulsef = 1;
+        pulsef = 1;
-    Pform       = Pulseformer("fsym",fsym,"fdac",4*fsym,"pulse","rrc","pulselength",16,"alpha",rcalpha);
+        Pform       = Pulseformer("fsym",fsym,"fdac",4*fsym,"pulse","rrc","pulselength",16,"alpha",rcalpha);
 
-    Pamsource = PAMsource(...
+        Pamsource = PAMsource(...
-        "fsym",fsym,"M",4,"order",18,"useprbs",0,...
+            "fsym",fsym,"M",4,"order",18,"useprbs",0,...
-        "fs_out",fdac,...
+            "fs_out",256e9,...
-        "applyclipping",0,"clipfactor",1.2,...
+            "applyclipping",0,"clipfactor",1.2,...
-        "applypulseform",pulsef,"pulseformer",Pform,...
+            "applypulseform",pulsef,"pulseformer",Pform,...
-        "randkey",20,...
+            "randkey",20,...
-        "db_precode",dbmode,"db_encode",0,...
+            "duobinary_mode",dbmode,...
-        "mrds_code",0,"mrds_blocklength",512);
+            "mrds_code",0,"mrds_blocklength",512);
 
-    [Digi_sig,Symbols,Bits] = Pamsource.process();
+        [Digi_sig,Symbols,Bits] = Pamsource.process();
 
-    Digi_sig = Digi_sig.normalize("mode","rms");
+        Digi_sig = Digi_sig.normalize("mode","rms");
 
-    %%% 1) PLOT FULL RESPONSE SIGNAL
+        %%% 1) PLOT FULL RESPONSE SIGNAL
-    Digi_sig.spectrum("displayname","Full Response","fignum",fignum+dbmode,"normalizeToNyquist",0,"normalizeTo0dB",0,"color",[0.2,0.2,0.2],"linestyle",'-','addDCoffset',0,'normalizeToDC',1);
+        Digi_sig.spectrum("displayname","Full Response","fignum",fignum+dbmode,"normalizeToNyquist",0,"normalizeTo0dB",0,"color",clr.Paired.dgreen,"linestyle",'-','addDCoffset',0,'normalizeToDC',1);
 
 
-    %%% 2) PLOT PREEMPH. TX SIGNAL
+        %%% 2) PLOT PREEMPH. TX SIGNAL
-    if dbmode == 0
+        if dbmode == 0
-        maxamp = -37;
+            maxamp = -37;
-        precomp_est = ChannelFreqResp("Nacq",2048,"Navg",100,"Ncp",63,'f_ref',Digi_sig.fs);
+            precomp_est = ChannelFreqResp("Nacq",2048,"Navg",100,"Ncp",63,'f_ref',Digi_sig.fs);
 
-        precomp_path = "W:\labdata\sioe_labor\precomp";
+            precomp_path = "W:\labdata\sioe_labor\precomp";
-        precomp_fn = "lab_high_speed";
+            precomp_fn = "lab_high_speed";
-        Digi_sig_pre = precomp_est.precomp(Digi_sig,'maxampdb',maxamp,'loadPath',precomp_path,'fileName',precomp_fn);
+            Digi_sig_pre = precomp_est.precomp(Digi_sig,'maxampdb',maxamp,'loadPath',precomp_path,'fileName',precomp_fn);
 
-        Digi_sig_pre = Digi_sig_pre.resample("fs_out",fdac);
+            Digi_sig_pre = Digi_sig_pre.resample("fs_out",256e9);
 
-        Digi_sig_pre= Digi_sig_pre.normalize("mode","rms");
+            Digi_sig_pre= Digi_sig_pre.normalize("mode","rms");
 
-        Digi_sig_pre.spectrum("displayname","Strong Precomp","fignum",fignum+dbmode,"normalizeToNyquist",0,"normalizeTo0dB",0,"color",[0,0,0],"linestyle",'-.','addDCoffset',0,'normalizeToDC',1);
+            Digi_sig_pre.spectrum("displayname","Tx w/ pre-emph.","fignum",fignum+dbmode,"normalizeToNyquist",0,"normalizeTo0dB",0,"color",clr.Paired.dred,"linestyle",'-.','addDCoffset',0,'normalizeToDC',1);
-    end
+        elseif dbmode == 2
 
+            maxamp = -38;
+            precomp_est = ChannelFreqResp("Nacq",2048,"Navg",100,"Ncp",63,'f_ref',Digi_sig.fs);
+
+            precomp_path = "W:\labdata\sioe_labor\precomp";
+            precomp_fn = "lab_high_speed";
+            Digi_sig_pre = precomp_est.precomp(Digi_sig,'maxampdb',maxamp,'loadPath',precomp_path,'fileName',precomp_fn);
+
+            Digi_sig_pre = Digi_sig_pre.resample("fs_out",256e9);
+
+            Digi_sig_pre= Digi_sig_pre.normalize("mode","rms");
+
+            Digi_sig_pre.spectrum("displayname","Strong Precomp","fignum",fignum+dbmode,"normalizeToNyquist",0,"normalizeTo0dB",0,"color",[0,0,0],"linestyle",'-.','addDCoffset',0,'normalizeToDC',1);
+        end
     end
 
     % 1 - PAM 4 with preemphasis
@@ -70,7 +83,7 @@ for dbmode = 0%length(rates)
     M = 4;
     fp.where('Runs', 'pam_level','EQUALS', M);
     fp.where('Runs', 'bitrate','EQUALS', rates);%360,390
-    fp.where('Runs', 'fiber_length','EQUALS', 2);   
+    fp.where('Runs', 'fiber_length','EQUALS', 10);
     fp.where('Runs', 'wavelength','EQUALS', 1310);  %1327.4
     fp.where('Runs', 'db_mode','EQUALS', dbmode);
     fp.where('Runs', 'rop_attenuation','EQUAL', 0);
@@ -89,14 +102,18 @@ for dbmode = 0%length(rates)
     Scpe_sig = Scpe_cell{1};
 
     %%% 3) PLOT DB Tgt. SIGNAL
-    if 1
+    if dbmode ~= 2
         DB_Symbols = Duobinary().encode(Symbols);
-        DB_Symbols.spectrum("fignum",fignum+dbmode,"normalizeTo0dB",1,"displayname",'DB-Response','addDCoffset',0,'color',clr.Set1.blue,'normalizeToNyquist',0,'linestyle','--');
+    else
+        DB_Symbols = Symbols;
     end
+    DB_Symbols.spectrum("fignum",fignum+dbmode,"normalizeTo0dB",1,"displayname",'DB response','addDCoffset',0,'color',clr.Paired.dblue,'normalizeToNyquist',0,'linestyle','-');
+    
 
     %%% 4) Plot RX Signal
+    Scpe_sig = Scpe_sig - mean(Scpe_sig.signal);
     Scpe_sig.spectrum("fignum",fignum+dbmode,"normalizeTo0dB",1,"displayname",'Rx','addDCoffset',1,'color',[0,0,0],'normalizeToNyquist',0,'linestyle',':');
-    Scpe_sig.eye(fsym,M,"fignum",47,"displayname",' Eye of AVG Signal');
+    % Scpe_sig.eye(fsym,M,"fignum",47,"displayname",' Eye of AVG Signal');
     % xline(Symbols.fs/2.*1e-9,'Color',cols(r,:),'HandleVisibility','off');
 
     average_signals = 1;
@@ -113,8 +130,8 @@ for dbmode = 0%length(rates)
         Symbols.spectrum("fignum",20,"normalizeTo0dB",1,"displayname",'Full Response','addDCoffset',0,'color',clr.Set1.red,'normalizeToNyquist',0,'linestyle','--');
         DB_Symbols.spectrum("fignum",20,"normalizeTo0dB",1,"displayname",'DB-Response','addDCoffset',0,'color',clr.Set1.blue,'normalizeToNyquist',0,'linestyle','--');
         Scpe_sig_avg.spectrum("displayname","Scope PSD","fignum",20,"normalizeTo0dB",1,"addDCoffset",5);
-        Scpe_sig_avg.plot("displayname","Scope raw signal","fignum",27,"clear",1);
+        % Scpe_sig_avg.plot("displayname","Scope raw signal","fignum",27,"clear",1);
-        Scpe_sig_avg.eye(fsym,M,"fignum",48,"displayname",' Eye of AVG Signal');
+        % Scpe_sig_avg.eye(fsym,M,"fignum",48,"displayname",' Eye of AVG Signal');
     end
 
 
@@ -128,9 +145,9 @@ for dbmode = 0%length(rates)
     xticks(-100:20:100);
     yticks(-20:10:10);
 
-    beautifyBERplot("logscale",0,"setmarkers",0)
+    beautifyBERplot("logscale",0,"setmarkers",0,"setcolors",0,"changemarkers",0)
-    pos = [100.3333  991.6667  358.0000  192.6667];
+    % pos = [100.3333  991.6667  358.0000  192.6667];
-    set(fig, 'Position', pos);
+    % set(fig, 'Position', pos);
 
     %%%%%%%%%%%%
     drawnow;
@@ -164,7 +181,7 @@ for dbmode = 0%length(rates)
 
     %%% DB TARGET
     db_ref_sequence = Duobinary().encode(Symbols);
-     eq_    = EQ("Ne",ffe_order,"Nb",dfe_order,"training_length",len_tr,"training_loops",5,"dd_loops",5,"K",2,"DCmu",mu_dc,"DDmu",[mu_ffe mu_dfe],"DFEmu",0.005,"FFEmu",0,"plotfinal",0,"ideal_dfe",0);
+    eq_    = EQ("Ne",ffe_order,"Nb",dfe_order,"training_length",len_tr,"training_loops",5,"dd_loops",5,"K",2,"DCmu",mu_dc,"DDmu",[mu_ffe mu_dfe],"DFEmu",0.005,"FFEmu",0,"plotfinal",0,"ideal_dfe",0);
     [eq_signal, db_noise] = eq_.process(Scpe_sig,db_ref_sequence);
 
     % db_noise.signal = db_noise.signal - mean(db_noise.signal);
@@ -187,8 +204,8 @@ for dbmode = 0%length(rates)
     yticks(-50:10:10);
 
     beautifyBERplot("logscale",0,"setmarkers",0)
-    pos = [100.3333  991.6667  358.0000  192.6667];
+    % pos = [100.3333  991.6667  358.0000  192.6667];
-    set(fig, 'Position', pos);
+    % set(fig, 'Position', pos);
 
 end
 

projects/Advanced_DSP_for_400G_IMDD_experiments/Auswertung_JLT/final/FIGURE_WAVELENGTH_VS_BAUDRATE.m

@@ -1,160 +0,0 @@
-%% ============================================================
-%  PARAMETERS
-% ============================================================
-database_type = 'mysql';
-db = DBHandler("dataBase", "labor_highspeed", "type", database_type);
-
-pam_level = 4;                    % FIXED for this figure
-baudrates = [300e9 330e9 360e9 390e9];
-fiberL = 10;
-
-fields = [
-    db.getTableFieldNames('power_state_info');
-    db.getTableFieldNames('dashboard_ungrouped_alltime')
-];
-
-%% ============================================================
-%  DEFINE DSP SCHEMES
-% ============================================================
-curves = struct;
-
-curves(1).name  = 'VNLE';
-curves(1).eq    = equalizer_structure.vnle;
-curves(1).color = clr.Paired.red;
-
-curves(2).name  = 'PF + MLSE';
-curves(2).eq    = equalizer_structure.vnle_pf_mlse;
-curves(2).color = clr.Paired.green;
-
-curves(3).name  = 'DB-target + MLSE';
-curves(3).eq    = equalizer_structure.vnle_db_mlse;
-curves(3).color = clr.Paired.blue;
-
-curves(4).name  = 'ML-based MLSE';
-curves(4).eq    = equalizer_structure.ml_mlse;
-curves(4).color = clr.Paired.purple;
-
-
-%% ============================================================
-%  ANALYSIS — results(b, k):  b = baudrate index, k = DSP scheme index
-% ============================================================
-results = struct;
-
-for b = 1:length(baudrates)
-
-    Rb = baudrates(b);
-
-    % --- query matching runs ---
-    fp = QueryFilter();
-    fp.where('Runs','pam_level','EQUALS', pam_level);
-    fp.where('Runs','fiber_length','EQUALS', fiberL);
-    fp.where('Runs','bitrate','EQUALS', Rb);
-    fp.where('Runs','is_mpi','EQUALS', 0);
-
-    [dataTable, ~] = db.queryDB(fp, fields);
-
-    for k = 1:numel(curves)
-
-        %% ---- DECIDE PRE-EMPH & PRECoded RULES for PAM-4 ----
-        pre_emph = decide_preemph(pam_level, curves(k).eq);
-        use_precoded = decide_precoded(pam_level, curves(k).eq);
-
-        %% ---- SETUP ANALYSIS CONFIG ----
-        cfg = struct;
-        cfg.x_axis = 'wavelength';
-        cfg.y_axis = 'BER';
-        cfg.agg    = 'min';
-        cfg.outlier = 'none';
-        % cfg.group_by = {'wavelength'};
-        cfg.show_raw = false;
-
-        cfg.filters = struct( ...
-            'pam_level', pam_level, ...
-            'is_mpi', 0, ...
-            'bitrate', Rb, ...
-            'fiber_length', fiberL, ...
-            'equalizer_structure', curves(k).eq, ...
-            'pre_emph', pre_emph);
-
-        %% ---- RUN ANALYSIS ----
-        A = analyze_measurements_gpt(dataTable, cfg);
-
-        results(b,k).wavelength = A.group{1}.x;
-
-        if use_precoded
-            results(b,k).ber = A.group{1}.y_precoded;
-        else
-            results(b,k).ber = A.group{1}.y;
-        end
-    end
-end
-
-
-%% ============================================================
-%  PLOT — 1×4 (one tile per baudrate)
-% ============================================================
-fig = figure(); clf;
-tiledlayout(1,4,'TileSpacing','compact','Padding','compact');
-
-lw = 1.8;
-ms = 6;
-
-for b = 1:length(baudrates)
-    nexttile; hold on;
-
-    for k = 1:numel(curves)
-        plot(results(b,k).wavelength, results(b,k).ber, ...
-            '-o', ...
-            'Color', curves(k).color, ...
-            'MarkerFaceColor', curves(k).color, ...
-            'MarkerSize', ms, ...
-            'LineWidth', lw, ...
-            'DisplayName', curves(k).name);
-    end
-
-    set(gca,'YScale','log');
-    grid on;
-    xlabel('Wavelength [nm]');
-    ylabel('BER');
-    ylim([1e-4 0.1]);
-    title(sprintf('PAM-%d @ %.0f GBd',pam_level, baudrates(b)/1e9));
-    legend('Location','best');
-    beautifyBERplot();
-end
-
-% Optional figure size
-pos = 1e3.*[0.1 0.55 1.4 0.32];
-set(fig, 'Position', pos);
-
-
-%% ============================================================
-% DECISION LOGIC (INLINE FUNCTIONS)
-% ============================================================
-
-function pe = decide_preemph(M, eq)
-    % PRE-EMPH RULES:
-    switch M
-        case 4
-            if eq == equalizer_structure.vnle
-                pe = 1;     % PAM4: VNLE → pre-emph on
-            else
-                pe = 0;     % PAM4: all others → off
-            end
-        case {6,8}
-            pe = 1;         % PAM6/8: all → pre-emph on
-        otherwise
-            pe = 0;
-    end
-end
-
-
-function flag = decide_precoded(M, eq)
-    % PRE-CODE RULES:
-    if eq == equalizer_structure.vnle_db_mlse
-        flag = 1;                         % Always for DB-target
-    elseif eq == equalizer_structure.ml_mlse && M == 4
-        flag = 1;                         % PAM4: ML-based → precoded
-    else
-        flag = 0;
-    end
-end

projects/Advanced_DSP_for_400G_IMDD_experiments/Auswertung_JLT/final/generate_spectrum_plots.m

@@ -107,14 +107,14 @@ if 1
     fprintf('Plotting: %s\n', precomp_filename);
     freqresp.plot();
 
-    outfile = 'C:\Users\Silas\Documents\latex\JLT_400G copy\media\matlab2tikz\spectrum_2.tikz';
+%     outfile = 'C:\Users\Silas\Documents\latex\JLT_400G copy\media\matlab2tikz\spectrum_2.tikz';
-matlab2tikz(outfile, ...
+% matlab2tikz(outfile, ...
-    'width','\fwidth', ...
+%     'width','\fwidth', ...
-    'height','\fheight', ...
+%     'height','\fheight', ...
-    'showInfo',false, ...
+%     'showInfo',false, ...
-    'extraAxisOptions',{ ...
+%     'extraAxisOptions',{ ...
-        'legend style={font=\footnotesize}', ...
+%         'legend style={font=\footnotesize}', ...
-        'legend columns=1' ...
+%         'legend columns=1' ...
-    });
+%     });
 
 end

projects/Advanced_DSP_for_400G_IMDD_experiments/Auswertung_JLT/power_vs_wavelength.m

@@ -8,6 +8,7 @@ fp.where('power_state_info', 'pam_level','EQUALS', 4);
 fp.where('power_state_info', 'db_mode','EQUALS', 0);
 % fp.where('power_state_info', 'fiber_length','EQUALS', 1);
 fp.where('power_state_info', 'is_mpi','EQUALS', 0);
+fp.where('rop_attenuation', 'is_mpi','EQUALS', 0);
 
 fields =  db.getTableFieldNames('power_state_info');
 [dataTable,~] = db.queryDB(fp, fields);
@@ -60,7 +61,7 @@ for fl = 1:numel(fiber_len)
 
     %
     dname = sprintf('%s;  %d km',y_variable, fiber_len(fl));
-    h2 = plot(fl_filtered_.(x_variable), fl_filtered_.(['mean_',y_variable]), 'LineWidth', 1, 'MarkerSize', 4,'Marker','o','LineStyle','-','Color',cols(fl,:),'MarkerFaceColor',cols(fl,:),'DisplayName',dname);
+    h2 = scatter(fl_filtered_.(x_variable), fl_filtered_.(['mean_',y_variable]), 36, 'Marker','o', 'MarkerEdgeColor',cols(fl,:), 'MarkerFaceColor',cols(fl,:), 'DisplayName',dname);
 
     h2.DataTipTemplate.DataTipRows(end+1) = ...
         dataTipTextRow('run\_id', run_ids);
@@ -94,3 +95,28 @@ yline([4.85e-3, 2e-2],'--','LineWidth',1,'HandleVisibility','off');
 posH = get(f, 'Position');        % [left, bottom, width, height]
 newPos = [posH(1), posH(2), 750, 300];
 set(f, 'Position', newPos);
+
+%% Average laser power over all measurements for each wavelength
+valid_rows = ~ismissing(dataTable.wavelength) & ...
+             ~ismissing(dataTable.power_laser);
+laser_measurements = dataTable(valid_rows, :);
+
+laser_power_by_wavelength = groupsummary( ...
+    laser_measurements, ...
+    'wavelength', ...
+    'mean', ...
+    'power_mzm');
+laser_power_by_wavelength = sortrows( ...
+    laser_power_by_wavelength, 'wavelength', 'ascend');
+
+f_all = figure(4);
+clf(f_all);
+scatter(laser_power_by_wavelength.wavelength, ...
+        laser_power_by_wavelength.mean_power_mzm, ...
+        36, 'o', 'filled');
+grid on;
+xlabel('Wavelength in nm', 'FontSize', 12);
+ylabel('Average laser power in dB', 'FontSize', 12);
+title('Average laser power over all measurements', ...
+    'FontSize', 14, 'FontWeight', 'bold');
+set(gca, 'FontSize', 11);

projects/Advanced_DSP_for_400G_IMDD_experiments/bias_evaluation.m

@@ -1,5 +1,5 @@
 
-filename = "Z:\2024\sioe\High Speed Messungen Oktober\bias_5km\PAMX_5km_20241025_204334_wh.mat";
+filename = "W:\labdata\sioe_labor\bias_5km\PAMX_5km_20241025_204334_wh.mat";
 
 a = load(filename);
 wh = a.obj;
@@ -30,7 +30,7 @@ for l =  1:numel(lambda_vals)
     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_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));

projects/Diss/400G_revisit/FIGURE_EQ_NOISE_VS_BAUDRATE.m

@@ -0,0 +1,158 @@
+% Minimal all-time database plot: PAM-4 baudrate sweep versus VNLE noise.
+% The dashed curves are the Burg postfilter responses estimated by
+% VNLE + postfilter + MLSE.
+
+%% SettingsC:\Users\Silas\Documents\MATLAB\imdd_simulation\projects\Advanced_DSP_for_400G_IMDD_experiments\Auswertung_JLT\final\FIGURE_EQ_NOISE_VS_BAUDRATE.m
+M = 4;
+bitrate = [390e9];   % [] -> all matching baudrates in the DB
+
+dsp_options.storage_path = "W:\labdata\sioe_labor\";
+dsp_options.max_occurences = 1; % standard routine: first synchronized signal
+
+fiber_length = 10;
+wavelength = 1310;
+is_mpi = 0;
+db_mode_filter = int32(db_mode.no_db);
+rop_attenuation = 0;
+
+vnle_order = [50 5 5];
+dfe_order = [0 0 0];
+training_length = 4096*2;
+postfilter_order = 1;
+
+%% Query the all-time database
+db = DBHandler( ...
+    "dataBase", "labor_highspeed", ...
+    "type", "mysql", ...
+    "server", "192.168.178.192", ...
+    "user", "silas", ...
+    "password", "silas");
+
+fp = QueryFilter();
+fp.where('Runs', 'pam_level', SqlOperator.EQUALS, M);
+fp.where('Runs', 'fiber_length', SqlOperator.EQUALS, fiber_length);
+fp.where('Runs', 'wavelength', SqlOperator.EQUALS, wavelength);
+fp.where('Runs', 'is_mpi', SqlOperator.EQUALS, is_mpi);
+fp.where('Runs', 'db_mode', 'LESS_THAN', 2);
+fp.where('Runs', 'rop_attenuation', SqlOperator.EQUALS, rop_attenuation);
+% fp.where('Runs', 'symbolrate','EQUALS', 180e9);
+% if ~isempty(baudrate_GBd)
+%     fp.where('Runs', 'symbolrate', SqlOperator.IN, baudrate_GBd*1e9);
+% end
+
+fields = [db.getTableFieldNames('dashboard_ungrouped_alltime')];
+fields = unique(fields, 'stable');
+[runs, ~] = db.queryDB(fp, fields);
+
+if ~isempty(bitrate)
+    runs = runs(ismember(runs.bitrate, bitrate), :);
+end
+
+if isempty(runs)
+    error('FIGURE_EQ_NOISE_VS_BAUDRATE:NoData', ...
+        'No PAM-%d runs matched the selected baudrate range.', M);
+end
+
+run_ids = unique(runs.run_id, 'stable');
+
+%% One plot: VNLE residual noise and Burg tap response
+fig = figure(220);
+clf(fig);
+hold on;
+max_fs = 0;
+
+for runIndex = 1:numel(run_ids)
+    runData = queryRunid(run_ids(runIndex), db);
+    fsym = double(runData.symbolrate(1));
+    bitrate = double(runData.bitrate(1));
+
+    dsp_options.max_occurences = 20;
+    dsp_options.start_occurence = 2;
+    [Tx_bits, Symbols, Scpe_cell, found_sync] = loadAndSyncRunSignals(runData, dsp_options);
+    if ~found_sync || isempty(Scpe_cell)
+        warning('Skipping run %g: no synchronized signal found.', runData.run_id(1));
+        continue
+    end
+
+    useavg = 0;
+    Scpe_sig = averageScopeSignals(Scpe_cell, useavg, 1);
+    Scpe_sig = preprocessSignal(Scpe_sig, Symbols, fsym);
+    Scpe_sig = Scpe_sig.normalize("mode", "rms");
+
+    % VNLE: retain the difference between equalizer output and reference.
+    eq_vnle = EQ( ...
+        "Ne", vnle_order, ...
+        "Nb", dfe_order, ...
+        "training_length", training_length, ...
+        "training_loops", 5, ...
+        "dd_loops", 5, ...
+        "K", 2, ...
+        "DCmu", 0.001, ...
+        "DDmu", [0.0004 0.0004 0.0004 0.0004], ...
+        "DFEmu", 0.05, ...
+        "FFEmu", 0, ...
+        "plotfinal", 0, ...
+        "ideal_dfe", 1);
+
+    % eq_ = FFE("epochs_tr",5,"epochs_dd",5,"len_tr",len_tr, ...
+    %     "mu_dd",1e-1,"mu_tr",0.4,"order",50, ...
+    %     "sps",2,"decide",0,"optmize_mus",1,"dd_mode",1, ...
+    %     "adaption_technique","nlms","dc_tracking_mu",1.021e-05);
+
+
+    [equalized_signal, eq_noise] = eq_vnle.process(Scpe_sig, Symbols);
+
+
+    postfilter_order = 3;
+    pf = Postfilter("ncoeff", postfilter_order, "useBurg", 1);
+    [mlse_sig_sd,whitened_noise] = pf.process(equalized_signal, eq_noise);
+
+    % mlse = MLSE( ...
+    %     "DIR", [0 0], ...
+    %     "duobinary_output", 0, ...
+    %     "M", M, ...
+    %     "trellis_states", PAMmapper(M, 0).levels);
+    % 
+    % [results, ~] = vnle_postfilter_mlse( ...
+    %     eq_vnle, pf, mlse, M, Scpe_sig, Symbols, Tx_bits, ...
+    %     "precode_mode", db_mode.no_db, ...
+    %     "showAnalysis", 0, ...
+    %     "postFFE", [], ...
+    %     "eth_style_symbol_mapping", 0);
+
+    eq_noise = eq_noise - mean(eq_noise.signal);
+    fig = figure(220+runIndex);
+    showEQNoisePSD(eq_noise, ...
+        "fignum", fig.Number, ...
+        "displayname", sprintf('%.0f Gbps: VNLE Noise', bitrate*1e-9), ...
+        "postfilter_taps", pf.coefficients, ...
+        "colormode", "qualitative");
+    whitened_noise = whitened_noise - mean(whitened_noise.signal);
+    whitened_noise.spectrum("displayname", 'Whitened Noise', "fignum", fig.Number, "normalizeTo0dB", 0,"fft_length",4096,"normalizeToDC",0);
+
+    max_fs = max(max_fs, eq_noise.fs);
+end
+
+xlabel('Frequency in GHz');
+ylabel('normalized to 0 dB');
+title('Noise of soft decision signal (not MLSE)');
+grid on;
+grid minor;
+legend('show', 'Interpreter', 'none', 'Location', 'best');
+xlim([-max_fs/2 max_fs/2]*1e-9);
+ylim([-20 0]);
+
+function signalOut = averageScopeSignals(scopeCell, averageSignals, gain)
+signalOut = scopeCell{1};
+if ~averageSignals
+    return
+end
+
+commonLength = min(cellfun(@(s) numel(s.signal), scopeCell));
+scopeMean = zeros(commonLength, 1);
+for idx = 1:numel(scopeCell)
+    scopeMean = scopeMean + scopeCell{idx}.signal(1:commonLength);
+end
+scopeMean = scopeMean ./ numel(scopeCell);
+signalOut.signal = gain .* scopeMean;
+end

projects/Diss/400G_revisit/PLOT_BER_BEST_ALGOS_WITH_DUOBINARY_SIGNALING.m

@@ -8,7 +8,7 @@ clear; clc;
 
 %% 1) Query data
 
-selectedPamLevel = 8;
+selectedPamLevels = [4, 6, 8];
 selectedFiberLengthKm = 10;
 selectedWavelengthNm = 1310;
 selectedRopAttenuation = 0;     % set [] to use all ROP attenuation values
@@ -33,7 +33,6 @@ db.refresh();
 
 fp = QueryFilter();
 fp.where('Runs', 'fiber_length', 'EQUALS', selectedFiberLengthKm);
-fp.where('Runs', 'pam_level', 'EQUALS', selectedPamLevel);
 fp.where('Runs', 'wavelength', 'EQUALS', selectedWavelengthNm);
 if ~isempty(selectedRopAttenuation)
     fp.where('Runs', 'rop_attenuation', 'EQUALS', selectedRopAttenuation);
@@ -66,6 +65,8 @@ for fieldIdx = 1:numel(numericFields)
     end
 end
 
+data = data(ismember(data.pam_level, selectedPamLevels), :);
+
 if ~ismember("precomp_amp", string(data.Properties.VariableNames))
     warning("plot_best_algos:NoPrecompAmp", ...
         "Runs.precomp_amp was not returned. Falling back to pre_emphasis = (db_mode == 0).");
@@ -85,6 +86,9 @@ if ismember("equalizer_structure", string(duobinaryRows.Properties.VariableNames
         equalizerMask(duobinaryRows.equalizer_structure, ...
         equalizer_structure.db_encoded), :);
 end
+
+duobinaryRows = duobinaryRows(datetime(duobinaryRows.date_of_processing)>datetime("2026-01-01 00:00:00"),:);
+
 duobinaryPlotData = buildDuobinarySignalingRows(duobinaryRows);
 duobinaryPlotData = duobinaryPlotData(isfinite(duobinaryPlotData.BER_plot) & ...
     duobinaryPlotData.BER_plot > 0 & ...
@@ -117,70 +121,75 @@ if isempty(availableStyles)
     return
 end
 
-fig = figure(); clf;
+fig = figure(432); clf;
-ax = axes(fig); hold(ax, "on");
+t = tiledlayout(fig, 1, numel(selectedPamLevels), ...
+    "TileSpacing", "compact", ...
+    "Padding", "compact");
 
-for styleIdx = 1:height(availableStyles)
+for pamIdx = 1:numel(selectedPamLevels)
-    style = availableStyles(styleIdx, :);
+    selectedPamLevel = selectedPamLevels(pamIdx);
-    rowMask = bestPlotData.algorithm_key == style.algorithm_key;
+    ax = nexttile(t); hold(ax, "on");
-    if ~any(rowMask)
+    pamMask = bestPlotData.pam_level == selectedPamLevel;
-        continue
+
+    for styleIdx = 1:height(availableStyles)
+        style = availableStyles(styleIdx, :);
+        rowMask = pamMask & bestPlotData.algorithm_key == style.algorithm_key;
+        if ~any(rowMask)
+            continue
+        end
+
+        algoData = sortrows(bestPlotData(rowMask, :), "grossrate_Gbps");
+
+        if showRawEntries
+            scatter(ax, algoData.grossrate_Gbps, algoData.BER_plot, ...
+                9, ...
+                "Marker", ".", ...
+                "MarkerEdgeColor", style.color, ...
+                "MarkerFaceColor", style.color, ...
+                "MarkerEdgeAlpha", 0.25, ...
+                "MarkerFaceAlpha", 0.25, ...
+                "HandleVisibility", "off");
+        end
+
+        if showBestLine
+            plot(ax, algoData.grossrate_Gbps, algoData.BER_plot, ...
+                "LineStyle", style.lineStyle, ...
+                "Marker", style.marker, ...
+                "MarkerSize", 5, ...
+                "LineWidth", 1.5, ...
+                "Color", style.color, ...
+                "MarkerFaceColor", style.markerFaceColor, ...
+                "MarkerEdgeColor", style.color, ...
+                "DisplayName", style.name);
+        end
     end
 
-    algoData = sortrows(bestPlotData(rowMask, :), "grossrate_Gbps");
+    yline(ax, [2.2e-4, 4.85e-3, 2e-2], ...
+        "LineWidth", 1, ...
+        "LineStyle", "--", ...
+        "Color", [0.25 0.25 0.25], ...
+        "HandleVisibility", "off");
 
-    if showRawEntries
+    % title(ax, sprintf("PAM-%d, %.0f km, %.0f nm", ...
-        scatter(ax, algoData.grossrate_Gbps, algoData.BER_plot, ...
+    %     selectedPamLevel, selectedFiberLengthKm, selectedWavelengthNm));
-            9, ...
+    xlabel(ax, "Gross rate [Gb/s]");
-            "Marker", ".", ...
+    ylabel(ax, "BER");
-            "MarkerEdgeColor", style.color, ...
+    set(ax, "YScale", "log");
-            "MarkerFaceColor", style.color, ...
+    ylim(ax, [8e-5, 0.1]);
-            "MarkerEdgeAlpha", 0.25, ...
+    grid(ax, "on");
-            "MarkerFaceAlpha", 0.25, ...
+    box(ax, "on");
-            "HandleVisibility", "off");
-    end
 
-    if showBestLine
+    xticks(ax, 300:30:480);
-        plot(ax, algoData.grossrate_Gbps, algoData.BER_plot, ...
+    xlim(ax, [300, 480]);
-            "LineStyle", style.lineStyle, ...
+
-            "Marker", style.marker, ...
+    legend(ax, "Location", "northeast", "Interpreter", "none");
-            "MarkerSize", 5, ...
+    if exist("beautifyBERplot", "file")
-            "LineWidth", 1.5, ...
+        beautifyBERplot("logscale", true, "setcolors", false, ...
-            "Color", style.color, ...
+            "setmarkers", false, "changemarkers", false);
-            "MarkerFaceColor", style.markerFaceColor, ...
-            "MarkerEdgeColor", style.color, ...
-            "DisplayName", style.name);
     end
 end
 
-yline(ax, [2.2e-4, 4.85e-3, 2e-2], ...
+set(fig, "Position", 1e3 .* [0.1070 0.5497 1.0585 0.2282]);
-    "LineWidth", 1, ...
-    "LineStyle", "--", ...
-    "Color", [0.25 0.25 0.25], ...
-    "HandleVisibility", "off");
-
-title(ax, sprintf("PAM-%d, %.0f km, %.0f nm", ...
-    selectedPamLevel, selectedFiberLengthKm, selectedWavelengthNm));
-xlabel(ax, "Gross rate [Gb/s]");
-ylabel(ax, "BER");
-set(ax, "YScale", "log");
-ylim(ax, [1e-5, maxBerForPlot]);
-grid(ax, "on");
-box(ax, "on");
-
-xTicks = unique(bestPlotData.grossrate_Gbps(isfinite(bestPlotData.grossrate_Gbps)));
-if ~isempty(xTicks)
-    xticks(ax, xTicks);
-    xlim(ax, [min(xTicks), max(xTicks)]);
-end
-
-legend(ax, "Location", "best", "Interpreter", "none");
-if exist("beautifyBERplot", "file")
-    beautifyBERplot("logscale", true, "setcolors", false, ...
-        "setmarkers", false, "changemarkers", false);
-end
-
-set(fig, "Position", 1e3 .* [0.1000 0.5500 0.7200 0.4200]);
 
 %% Local helpers
 
@@ -220,7 +229,7 @@ styles = table( ...
      "VNLE + PF + MLSE"; ...
      "VNLE DBt. + MLSE"; ...
      "ML pre-EQ + Viterbi"; ...
-     "Duobinary signaling"], ...
+     "DBS + VNLE + MLSE"], ...
     ["o"; "square"; "diamond"; "^"; "v"], ...
     ["-"; "-"; "-"; "-"; "-"], ...
     ["w"; "w"; "w"; "w"; "w"], ...
@@ -322,7 +331,7 @@ value = double(enumEntry);
 end
 
 function bestData = bestBerByAlgorithmAndGrossRate(data)
-groupVars = ["algorithm_key", "grossrate_Gbps"];
+groupVars = ["pam_level", "algorithm_key", "grossrate_Gbps"];
 groupId = findgroups(data(:, groupVars));
 keepIdx = NaN(max(groupId), 1);
 

projects/Diss/400G_revisit/PLOT_BER_VS_ALGO.m

@@ -8,7 +8,7 @@ clear; clc;
 %% 1) Gather data
 
 selectedPamLevel = 4;
-selectedFiberLengthKm = 10;
+selectedFiberLengthKm = 2;
 selectedWavelength =1310;         % set [] to use all wavelengths
 selectedRopAttenuation = [];     % set [] to use all ROP attenuation values
 selectedIsMpi = [];              % set [] to use all entries
@@ -98,7 +98,7 @@ if isempty(availableEqStyles)
     return
 end
 
-fig = figure(401); clf;
+fig = figure(); clf;
 tiledlayout(1, height(availableEqStyles), ...
     "TileSpacing", "compact", ...
     "Padding", "compact");

projects/Diss/400G_revisit/PLOT_DUOBINARY_DETECTION_BER_VS_BITRATE.m

@@ -14,7 +14,9 @@ selectedWavelengthNm = 1310;
 selectedRopAttenuation = 0;
 selectedIsMpi = 0;
 selectedDbMode = db_mode.db_encoded;
-selectedEqualizerStructure = equalizer_structure.db_encoded;
+selectedEqualizerStructures = [ ...
+    equalizer_structure.db_encoded, ...
+    equalizer_structure.ml_mlse];
 
 maxBerForPlot = 0.5;
 showRawEntries = false;
@@ -60,8 +62,13 @@ end
 
 data = data(ismember(data.pam_level, selectedPamLevels), :);
 if ismember("equalizer_structure", string(data.Properties.VariableNames)) && ...
-        ~isempty(selectedEqualizerStructure)
+        ~isempty(selectedEqualizerStructures)
-    data = data(equalizerMask(data.equalizer_structure, selectedEqualizerStructure), :);
+    eqMask = false(height(data), 1);
+    for eqIdx = 1:numel(selectedEqualizerStructures)
+        eqMask = eqMask | equalizerMask(data.equalizer_structure, ...
+            selectedEqualizerStructures(eqIdx));
+    end
+    data = data(eqMask, :);
 end
 
 plotData = buildDetectionMetricRows(data);
@@ -150,6 +157,9 @@ for pamIdx = 1:numel(availablePamLevels)
         xlim(ax, [min(xTicks), max(xTicks)]);
     end
 
+    xticks(ax, 300:30:480);
+    xlim(ax, [300, 480]);
+
     legend(ax, "Location", "best", "Interpreter", "none");
     if exist("beautifyBERplot", "file")
         beautifyBERplot("logscale", true, "setcolors", false, ...
@@ -182,31 +192,52 @@ values = double(values);
 end
 
 function plotData = buildDetectionMetricRows(data)
-baseRows = data(isfinite(data.BER), :);
+dbEncodedRows = data(equalizerMask(data.equalizer_structure, ...
+    equalizer_structure.db_encoded), :);
+baseRows = dbEncodedRows(isfinite(dbEncodedRows.BER), :);
 baseRows.detection_type = repmat("VNLE + MLSE", height(baseRows), 1);
 baseRows.BER_plot = baseRows.BER;
 
 if ismember("BER_precoded", string(data.Properties.VariableNames))
-    memorylessRows = data(isfinite(data.BER_precoded), :);
+    memorylessRows = dbEncodedRows(isfinite(dbEncodedRows.BER_precoded), :);
     memorylessRows.detection_type = repmat("VNLE + memoryless", ...
         height(memorylessRows), 1);
     memorylessRows.BER_plot = memorylessRows.BER_precoded;
-    plotData = [baseRows; memorylessRows];
 else
     warning("plot_duobinary_detection:NoPrecodedBer", ...
-        "BER_precoded was not returned. Plotting only VNLE + MLSE rows.");
+        "BER_precoded was not returned. Plotting only BER rows.");
-    plotData = baseRows;
+    memorylessRows = dbEncodedRows([], :);
 end
+
+mlMlseRows = data(equalizerMask(data.equalizer_structure, ...
+    equalizer_structure.ml_mlse), :);
+if ismember("BER_precoded", string(data.Properties.VariableNames))
+    mlMlsePrecodedRows = mlMlseRows(isfinite(mlMlseRows.BER_precoded), :);
+    mlMlsePrecodedRows.detection_type = repmat( ...
+        "ML pre-EQ + Viterbi", ...
+        height(mlMlsePrecodedRows), 1);
+    mlMlsePrecodedRows.BER_plot = mlMlsePrecodedRows.BER_precoded;
+else
+    mlMlsePrecodedRows = mlMlseRows([], :);
+end
+
+plotData = [baseRows; memorylessRows; mlMlsePrecodedRows];
 end
 
 function styles = defaultDetectionStyles()
 styles = table( ...
-    ["VNLE + MLSE"; "VNLE + memoryless"], ...
+    ["VNLE + MLSE"; ...
-    ["VNLE + MLSE"; "VNLE + memoryless"], ...
+     "VNLE + memoryless"; ...
-    ["o"; "square"], ...
+     "ML pre-EQ + Viterbi"], ...
-    ["-"; "--"], ...
+    ["VNLE + MLSE"; ...
-    ["w"; "none"], ...
+     "VNLE + memoryless"; ...
-    [clr.Paired.blue; clr.Paired.orange], ...
+     "ML pre-EQ + Viterbi"], ...
+    ["o"; "square"; "^"], ...
+    ["-"; "--"; "-"], ...
+    ["w"; "none"; "w"], ...
+    [clr.Paired.blue; ...
+     clr.Paired.orange; ...
+     clr.Paired.purple], ...
     'VariableNames', ["detection_type", "name", "marker", ...
     "lineStyle", "markerFaceColor", "color"]);
 end

projects/Diss/400G_revisit/PLOT_EYES_400G_REVISIT.m

@@ -0,0 +1,384 @@
+%% 400G revisit: eye comparison for PAM-4/6/8
+% The native Signal.eye() method is used for the eye display. Optional TikZ
+% export is configured below and uses mat2tikz_improved().
+%
+% db_mode_setting:
+%   0 - no duobinary processing; use the copied FFE configuration
+%   1 - DB-targeted VNLE; the VNLE target is Duobinary().encode(Symbols)
+%   2 - DB-encoded data; equalize the stored DB-encoded Symbols with a VNLE
+
+clc;
+
+%% Configuration
+M_values = [4];
+selectedBitrate = 360e9;
+selectedFiberLengthKm = 10;
+selectedWavelengthNm = 1310;
+selectedRopAttenuation = 0;
+selectedIsMpi = 0;
+db_mode_setting = 2;             % Set to 0, 1, or 2.
+
+average_signals = 1;
+show_histograms = true;
+export_tikz = 0;
+max_occurences = 10;
+histogram_figure_base = 600;
+eye_figure_base = 500;
+psd_figure_base = 700;
+
+% PSD colors follow the established DSP algorithm styles. The target is
+% black and the received waveform is grey.
+dsp_styles = defaultAlgorithmStyles();
+psd_color_target = [0, 0, 0];
+psd_color_received = [0.3500, 0.3500, 0.3500];
+psd_color_equalized = dsp_styles.color(dsp_styles.algorithm_key == "vnle", :);
+
+tikz_root = 'C:\Users\Silas\Documents\6971e0b65b380ca6d71c837f\04_Experimental_Evaluation\tikz\400g';
+tikz_eye_folder = fullfile(tikz_root, 'eyes');
+tikz_histogram_folder = fullfile(tikz_root, 'histograms');
+tikz_psd_folder = fullfile(tikz_root, 'psd');
+
+% The averaging/gain/normalization follows FIGURE_EYES.m.
+average_gain = 1.25;
+
+% Common equalizer parameters copied from FIGURE_EYES.m.
+len_tr = 4096*2;
+training_loops = 5;
+dd_loops = 5;
+eq_K = 2;
+mu_dc = 0.005;
+mu_ffe = [0.0001, 0.0008, 0.001];
+mu_dfe = 0.0004;
+
+if ~ismember(db_mode_setting, [0, 1, 2])
+    error('PLOT_EYES_400G_REVISIT:InvalidDbMode', ...
+        'db_mode_setting must be 0, 1, or 2.');
+end
+
+if export_tikz
+    if ~exist(tikz_eye_folder, 'dir')
+        mkdir(tikz_eye_folder);
+    end
+    if ~exist(tikz_histogram_folder, 'dir')
+        mkdir(tikz_histogram_folder);
+    end
+    if ~exist(tikz_psd_folder, 'dir')
+        mkdir(tikz_psd_folder);
+    end
+end
+
+%% Database setup
+dsp_options = struct();
+dsp_options.storage_path = 'W:\labdata\sioe_labor\';
+dsp_options.start_occurence = 1;
+dsp_options.max_occurences = max_occurences;
+
+database = DBHandler( ...
+    "dataBase", "labor_highspeed", ...
+    "type", "mysql", ...
+    "server", "192.168.178.192", ...
+    "user", "silas", ...
+    "password", "silas");
+
+%% DSP phase: query, synchronize, equalize, and collect all signals
+selectedRuns = [];
+eyeSignals = cell(size(M_values));
+rawSignals = cell(size(M_values));
+eyeReferences = cell(size(M_values));
+symbolRates = NaN(size(M_values));
+
+for mIdx = 1:numel(M_values)
+    M = M_values(mIdx);
+
+    fp = QueryFilter();
+    fp.where('Runs', 'fiber_length', 'EQUALS', selectedFiberLengthKm);
+    fp.where('Runs', 'wavelength', 'EQUALS', selectedWavelengthNm);
+    fp.where('Runs', 'rop_attenuation', 'EQUALS', selectedRopAttenuation);
+    fp.where('Runs', 'is_mpi', 'EQUALS', selectedIsMpi);
+    fp.where('Runs', 'pam_level', 'EQUALS', M);
+    fp.where('Runs', 'db_mode', 'EQUALS', db_mode_setting);
+    if ~isempty(selectedBitrate)
+        fp.where('Runs', 'bitrate', 'EQUALS', selectedBitrate);
+    end
+
+    [dataTable, ~] = database.queryDB(fp, database.getTableFieldNames('Runs'));
+    if isempty(dataTable)
+        error('PLOT_EYES_400G_REVISIT:MissingRun', ...
+            'No run found for PAM-%d with the selected filters.', M);
+    end
+
+    dataTable = sortrows(dataTable, {'bitrate', 'run_id'});
+    dataTable = dataTable(1, :);
+    if isempty(selectedRuns)
+        selectedRuns = dataTable;
+    else
+        selectedRuns = [selectedRuns; dataTable]; %#ok<AGROW>
+    end
+
+    fsym = double(dataTable.symbolrate(1));
+    symbolRates(mIdx) = fsym;
+    [~, Symbols, Scpe_cell, found_sync] = ...
+        loadAndSyncRunSignals(dataTable, dsp_options);
+
+    if ~found_sync || isempty(Scpe_cell)
+        error('PLOT_EYES_400G_REVISIT:SynchronizationFailed', ...
+            'Could not synchronize the selected PAM-%d run.', M);
+    end
+
+    Scpe_sig = averageScopeSignals(Scpe_cell, average_signals, average_gain);
+    Scpe_sig = preprocessSignal(Scpe_sig, Symbols, fsym);
+    Scpe_sig = Scpe_sig.normalize("mode", "rms");
+
+    switch db_mode_setting
+        case 0
+            % Simply FFE, copied from FIGURE_EYES.m.
+            eq_ = EQ("Ne", [50, 0, 0], ...
+                "Nb", [0, 0, 0], ...
+                "training_length", len_tr, ...
+                "training_loops", training_loops, ...
+                "dd_loops", dd_loops, ...
+                "K", eq_K, ...
+                "DCmu", mu_dc, ...
+                "DDmu", [mu_ffe, mu_dfe], ...
+                "DFEmu", 0.005, ...
+                "FFEmu", 0, ...
+                "plotfinal", 0, ...
+                "ideal_dfe", false);
+            referenceForEye = Symbols;
+
+        case 1
+            % DB-targeted VNLE: train against the DB waveform generated
+            % from the stored (precoded but not DB-encoded) symbols.
+            eq_ = makeVnle(len_tr, training_loops, dd_loops, eq_K, ...
+                mu_dc, mu_ffe, mu_dfe);
+            referenceForEye = Duobinary().encode(Symbols, "M", M);
+
+        case 2
+            % DB-encoded data: the stored Symbols already contain the DB
+            % encoded reference waveform used by the VNLE.
+            eq_ = makeVnle(len_tr, training_loops, dd_loops, eq_K, ...
+                mu_dc, mu_ffe, mu_dfe);
+            referenceForEye = Symbols;
+    end
+
+    [equalized_signal, ~] = eq_.process(Scpe_sig, referenceForEye);
+    eyeSignals{mIdx} = equalized_signal;
+    rawSignals{mIdx} = Scpe_sig;
+    eyeReferences{mIdx} = referenceForEye;
+    
+    fprintf('PAM-%d: run %d, %.3f GBd, db_mode %d\n', ...
+        M, dataTable.run_id(1), fsym*1e-9, db_mode_setting);
+end
+
+
+%% Plotting and export phase
+show_histograms = 1;
+showEye = 1;
+showPSD = 1;
+
+for mIdx = 1:numel(M_values)
+    M = M_values(mIdx);
+    fsym = symbolRates(mIdx);
+    rawSignal = rawSignals{mIdx};
+    equalized_signal = eyeSignals{mIdx};
+    referenceForEye = eyeReferences{mIdx};
+
+    if showPSD
+        psdFigure = psd_figure_base + mIdx + db_mode_setting;
+        figure(psdFigure); clf;
+
+        switch db_mode_setting
+            case 0
+                referencePsdName = sprintf('PAM-%d reference', M);
+                equalizedPsdName = 'FFE output';
+                psd_color_equalized = dsp_styles.color( ...
+                    dsp_styles.algorithm_key == "vnle", :);
+            case 1
+                referencePsdName = 'DB-target reference';
+                equalizedPsdName = 'DB-targeted VNLE output';
+                psd_color_equalized = dsp_styles.color( ...
+                    dsp_styles.algorithm_key == "vnle_db_mlse", :);
+            case 2
+                referencePsdName = 'DB-encoded reference';
+                equalizedPsdName = 'DB-encoded VNLE output';
+                psd_color_equalized = dsp_styles.color( ...
+                    dsp_styles.algorithm_key == "db_encoded", :);
+        end
+
+        referenceForEye.spectrum( ...
+            "fignum", psdFigure, ...
+            "show_onesided", 1, ...
+            "fft_length", 4096, ...
+            "displayname", referencePsdName, ...
+            "color", psd_color_target);
+        rawSignal.spectrum( ...
+            "fignum", psdFigure, ...
+            "show_onesided", 1, ...
+            "fft_length", 4096, ...
+            "displayname", 'Received signal', ...
+            "color", psd_color_received);
+        equalized_signal.spectrum( ...
+            "fignum", psdFigure, ...
+            "show_onesided", 1, ...
+            "fft_length", 4096, ...
+            "displayname", equalizedPsdName, ...
+            "color", psd_color_equalized);
+
+        eq_noise = equalized_signal - referenceForEye;
+        showEQNoisePSD(eq_noise, ...
+            "fignum", 800, ...
+            "displayname", sprintf('%.0f Gbps: VNLE Noise', selectedBitrate), ...
+            "colormode", "diverging");
+
+        % PSDs are line-only, irrespective of the marker styles used by
+        % algorithm comparison plots.
+        set(findall(gca, 'Type', 'Line'), 'Marker', 'none');
+
+        figure(psdFigure);
+        title(sprintf('PSD comparison: %.0f GBd PAM-%d', fsym*1e-9, M), ...
+            'Interpreter', 'none');
+        legend('Location', 'best', 'Interpreter', 'none');
+        grid on;
+        box on;
+
+        if export_tikz
+            baudrateLabel = sprintf('%.0fGBd', fsym*1e-9);
+            psdFilename = fullfile(tikz_psd_folder, ...
+                sprintf('psd_pam_%d_%s_db_mode_%d.tikz', ...
+                M, baudrateLabel, db_mode_setting));
+            mat2tikz_improved(psdFilename);
+        end
+
+    end
+
+    if showEye 
+        % Use the native Signal eye implementation for the displayed eye.
+        eyeFigure = eye_figure_base + mIdx+ db_mode_setting;
+        equalized_signal.eye(fsym, M, ...
+            "fignum", eyeFigure, ...
+            "displayname", sprintf('PAM-%d, db_mode = %d', M, db_mode_setting));
+        figure(eyeFigure);
+        set(gcf, "Position", [100 + 430*(mIdx - 1), 100, 400, 360]);
+        stripEyeAxes(gca);
+
+
+        if export_tikz
+            baudrateLabel = sprintf('%.0fGBd', fsym*1e-9);
+            eyeFilename = fullfile(tikz_eye_folder, ...
+                sprintf('eye_pam_%d_%s_db_mode_%d.tikz', ...
+                M, baudrateLabel, db_mode_setting));
+            mat2tikz_improved(eyeFilename);
+        end
+
+    end
+
+    if show_histograms || export_tikz
+        histogramFigure = histogram_figure_base + M + db_mode_setting;
+        plotHistogram(equalized_signal, referenceForEye, ...
+            M, histogramFigure, db_mode_setting, histogramLegendLabels(M));
+
+        if export_tikz
+            figure(histogramFigure);
+            histogramFilename = fullfile(tikz_histogram_folder, ...
+                sprintf('histogram_pam_%d_%s_db_mode_%d.tikz', ...
+                M, baudrateLabel, db_mode_setting));
+            mat2tikz_improved(histogramFilename,"cleanfigure",1);
+        end
+    end
+end
+
+%% Local functions
+function signalOut = averageScopeSignals(scopeCell, averageSignals, gain)
+signalOut = scopeCell{1};
+if ~averageSignals
+    return
+end
+
+commonLength = min(cellfun(@(s) numel(s.signal), scopeCell));
+scopeMean = zeros(commonLength, 1);
+for idx = 1:numel(scopeCell)
+    scopeMean = scopeMean + scopeCell{idx}.signal(1:commonLength);
+end
+scopeMean = scopeMean ./ numel(scopeCell);
+signalOut.signal = gain .* scopeMean;
+end
+
+function eq_ = makeVnle(lenTr, trainingLoops, ddLoops, eqK, muDc, muFfe, muDfe)
+eq_ = EQ("Ne", [50, 5, 5], ...
+    "Nb", [0, 0, 0], ...
+    "training_length", lenTr, ...
+    "training_loops", trainingLoops, ...
+    "dd_loops", ddLoops, ...
+    "K", eqK, ...
+    "DCmu", muDc, ...
+    "DDmu", [muFfe, muDfe], ...
+    "DFEmu", 0.005, ...
+    "FFEmu", 0, ...
+    "plotfinal", 0, ...
+    "ideal_dfe", true);
+end
+
+function plotHistogram(equalizedSignal, referenceForEye, M, figureNumber, ...
+        dbModeSetting, legendLabels)
+figure(figureNumber); clf;
+if dbModeSetting ~= 0
+    uncodedReference = Duobinary().decode(referenceForEye, "M", M);
+    showLevelHistogram(equalizedSignal, referenceForEye, ...
+        "fignum", figureNumber, ...
+        "ref_symbol_uncoded", uncodedReference, ...
+        "legendLabels", legendLabels);
+else
+    showLevelHistogram(equalizedSignal, referenceForEye, ...
+        "fignum", figureNumber, ...
+        "legendLabels", legendLabels);
+end
+title(sprintf('PAM-%d histogram, db\_mode = %d', M, dbModeSetting));
+end
+
+function labels = histogramLegendLabels(M)
+labels = arrayfun(@(idx) sprintf('$p(z|d=d_{%d})$', idx), ...
+    1:M, 'UniformOutput', false);
+end
+
+function stripEyeAxes(ax)
+title(ax, '');
+xlabel(ax, '');
+ylabel(ax, '');
+set(ax, ...
+    'XTick', [], ...
+    'YTick', [], ...
+    'XTickLabel', [], ...
+    'YTickLabel', [], ...
+    'XMinorTick', 'off', ...
+    'YMinorTick', 'off');
+grid(ax, 'off');
+end
+
+function styles = defaultAlgorithmStyles()
+styles = table( ...
+    ["vnle"; ...
+     "vnle_pf_mlse"; ...
+     "vnle_db_mlse"; ...
+     "ml_mlse"; ...
+     "db_encoded"], ...
+    [equalizer_structure.vnle; ...
+     equalizer_structure.vnle_pf_mlse; ...
+     equalizer_structure.vnle_db_mlse; ...
+     equalizer_structure.ml_mlse; ...
+     equalizer_structure.db_encoded], ...
+    ["VNLE"; ...
+     "VNLE + PF + MLSE"; ...
+     "VNLE DBt. + MLSE"; ...
+     "ML pre-EQ + Viterbi"; ...
+     "DBS + VNLE + MLSE"], ...
+    ["o"; "square"; "diamond"; "^"; "v"], ...
+    ["-"; "-"; "-"; "-"; "-"], ...
+    ["w"; "w"; "w"; "w"; "w"], ...
+    [clr.Paired.red; ...
+     clr.Paired.green; ...
+     clr.Paired.blue; ...
+     clr.Paired.purple; ...
+     clr.Paired.orange], ...
+    'VariableNames', ["algorithm_key", "eq", "name", "marker", ...
+    "lineStyle", "markerFaceColor", "color"]);
+end

projects/Diss/400G_revisit/PLOT_MEMORYLESS_DBTGT_VS_VNLE_DB_MLSE.m

@@ -0,0 +1,168 @@
+%% Memoryless DB-target BER versus baudrate for PAM4/6/8
+clear; clc;
+
+warehouseFile = "C:\Users\Silas\Documents\MATLAB\imdd_simulation\projects\Diss\400G_revisit\results_duobinary_eq_memoryless_2km_pam468.mat";
+pamLevels = [4, 6, 8];
+
+%% Load warehouse and matching run metadata
+S = load(warehouseFile, "wh");
+wh = S.wh;
+
+db = DBHandler("dataBase", "labor_highspeed", ...
+    "type", "mysql", ...
+    "server", "192.168.178.192", ...
+    "user", "silas", ...
+    "password", "silas");
+
+fp = QueryFilter();
+fp.where('Runs', 'fiber_length', 'EQUALS', 2);
+fp.where('Runs', 'wavelength', 'EQUALS', 1310);
+fp.where('Runs', 'rop_attenuation', 'EQUALS', 0);
+fp.where('Runs', 'is_mpi', 'EQUALS', 0);
+fp.where('Runs', 'db_mode', 'EQUALS', 0);
+
+[runTable, ~] = db.queryDB(fp, db.getTableFieldNames('Runs'));
+warehouseRunIds = warehouseIds(wh);
+runTable = runTable(ismember(double(runTable.run_id), warehouseRunIds), :);
+
+%% Extract BER precoded from dbtgt_package
+warehouseRows = zeros(0, 3); % PAM level, baudrate [GBd], BER precoded
+for k = 1:numel(wh.sto.dbtgt_package)
+    [phys, realizationResults] = wh.getPhysAndValueByLinIndex( ...
+        "dbtgt_package", k);
+    if ~isfield(phys, "run_id")
+        continue
+    end
+
+    runRow = find(double(runTable.run_id) == double(phys.run_id), 1);
+    if isempty(runRow)
+        continue
+    end
+
+    for realization = 1:numel(realizationResults)
+        package = realizationResults{realization};
+        berPrecoded = readMetric(package, "BER_precoded");
+        if isfinite(berPrecoded) && berPrecoded > 0
+            warehouseRows(end+1, :) = [ ...
+                double(runTable.pam_level(runRow)), ...
+                double(runTable.grossrate(runRow)) * 1e-9, ...
+                berPrecoded]; %#ok<AGROW>
+        end
+    end
+end
+
+warehouseCurve = minByBaudrate(warehouseRows, "BER_precoded");
+
+%% Load database BER and BER precoded for VNLE + DB target/MLSE
+selectedFields = db.getTableFieldNames('dashboard_ungrouped_alltime');
+[databaseRows, ~] = db.queryDB(fp, selectedFields);
+
+databaseRows = databaseRows(ismember(double(databaseRows.pam_level), pamLevels), :);
+databaseRows = databaseRows(equalizerMask( ...
+    databaseRows.equalizer_structure, equalizer_structure.vnle_db_mlse), :);
+
+berRows = databaseRows(isfinite(double(databaseRows.BER)) & ...
+    double(databaseRows.BER) > 0, :);
+berPrecodedRows = databaseRows(isfinite(double(databaseRows.BER_precoded)) & ...
+    double(databaseRows.BER_precoded) > 0, :);
+
+databaseBerCurve = minByBaudrate( ...
+    [double(berRows.pam_level), double(berRows.grossrate) * 1e-9, ...
+    double(berRows.BER)], "BER");
+databaseBerPrecodedCurve = minByBaudrate( ...
+    [double(berPrecodedRows.pam_level), ...
+    double(berPrecodedRows.grossrate) * 1e-9, ...
+    double(berPrecodedRows.BER_precoded)], "BER_precoded");
+
+%% Plot: three curves per PAM format
+figure(470); clf;
+tiledlayout(1, 3, "TileSpacing", "compact", "Padding", "compact");
+
+for pamLevel = pamLevels
+    ax = nexttile; hold(ax, "on");
+
+    plotCurve(ax, warehouseCurve, pamLevel, "BER_precoded", ...
+        "o-", "precode + memoryless");
+    plotCurve(ax, databaseBerCurve, pamLevel, "BER", ...
+        "s-", "DBt. + MLSE");
+    plotCurve(ax, databaseBerPrecodedCurve, pamLevel, "BER_precoded", ...
+        "s--", "precode + DBt. + MLSE");
+
+    ylim([1e-4, 1e-1]);
+    title(ax, sprintf("PAM-%d", pamLevel));
+    xlabel(ax, "Baudrate [GBd]");
+    ylabel(ax, "BER");
+    set(ax, "YScale", "log");
+    grid(ax, "on");
+    box(ax, "on");
+    legend(ax, "Location", "best", "Interpreter", "none");
+end
+
+%% Local helpers
+function runIds = warehouseIds(wh)
+runIds = zeros(0, 1);
+for k = 1:numel(wh.sto.dbtgt_package)
+    [phys, ~] = wh.getPhysAndValueByLinIndex("dbtgt_package", k);
+    if isfield(phys, "run_id")
+        runIds(end+1, 1) = double(phys.run_id); %#ok<AGROW>
+    end
+end
+runIds = unique(runIds);
+end
+
+function value = readMetric(package, metricName)
+value = NaN;
+if isempty(package) || ~isstruct(package) || ~isfield(package, "metrics")
+    return
+end
+
+metrics = package.metrics;
+if isstruct(metrics) && isfield(metrics, metricName)
+    value = double(metrics.(metricName));
+elseif isobject(metrics) && isprop(metrics, metricName)
+    value = double(metrics.(metricName));
+end
+end
+
+function curve = minByBaudrate(rows, metricName)
+if isempty(rows)
+    curve = table(zeros(0, 1), zeros(0, 1), ...
+        'VariableNames', ["pam_level", "baudrate_GBd"]);
+    curve.(metricName) = zeros(0, 1);
+    return
+end
+
+curve = table(rows(:, 1), rows(:, 2), rows(:, 3), ...
+    'VariableNames', ["pam_level", "baudrate_GBd", metricName]);
+curve = groupsummary(curve, ["pam_level", "baudrate_GBd"], ...
+    "min", metricName);
+curve.Properties.VariableNames(end) = metricName;
+end
+
+function plotCurve(ax, curve, pamLevel, metricName, style, label)
+if isempty(curve) || ~ismember(metricName, string(curve.Properties.VariableNames))
+    return
+end
+
+rows = curve(curve.pam_level == pamLevel, :);
+if isempty(rows)
+    return
+end
+
+rows = sortrows(rows, "baudrate_GBd");
+plot(ax, rows.baudrate_GBd, rows.(metricName), style, ...
+    "LineWidth", 1.3, "MarkerSize", 5, "DisplayName", label);
+end
+
+function mask = equalizerMask(values, target)
+if isa(values, "equalizer_structure")
+    mask = values == target;
+elseif isnumeric(values)
+    mask = double(values) == double(target);
+else
+    valuesString = string(values);
+    mask = valuesString == string(target) | ...
+        str2double(valuesString) == double(target);
+end
+mask = mask(:);
+end

projects/Diss/400G_revisit/PLOT_MLSE_N_TAP_BER_BY_DB_MODE.m

@@ -0,0 +1,307 @@
+%% Minimal BERp plot for MLSE postfilter orders and duobinary modes
+clear; clc;
+
+%% Configuration
+warehouseFile = "C:\Users\Silas\Documents\MATLAB\imdd_simulation\projects\Diss\400G_revisit\mlse_n_tap_pam4.mat";
+pfValues = [1, 2, 3];
+
+%% Load warehouse and query run metadata
+loadedData = load(warehouseFile, "wh");
+wh = loadedData.wh;
+wh.showInfo;
+
+db = DBHandler("dataBase", "labor_highspeed", ...
+    "type", "mysql", ...
+    "server", "192.168.178.192", ...
+    "user", "silas", ...
+    "password", "silas");
+
+warehouseRunIds = getWarehouseRunIds(wh, "mlse_package");
+runTable = queryRunsById(db, warehouseRunIds);
+if isempty(runTable)
+    error("plot_mlse_n_tap:NoRunOverlap", ...
+        "The DB returned no metadata for the warehouse run_ids %s.", ...
+        mat2str(warehouseRunIds));
+end
+
+%% Extract minimum BERp for every run_id and pf_ncoeffs
+plotData = warehouseToTable(wh, runTable, pfValues);
+hasBerp = isfinite(plotData.BERp) & plotData.BERp > 0;
+hasBer = isfinite(plotData.BER) & plotData.BER > 0;
+if ~any(hasBerp | hasBer)
+    error("plot_mlse_n_tap:NoBerp", ...
+        "No positive BER or BER_precoded values were found in mlse_package.");
+end
+
+berpData = plotData(hasBerp, :);
+berpData = groupsummary(berpData, ...
+    ["db_mode", "pf_ncoeffs", "bitrate_Gbps"], "min", "BERp");
+berData = plotData(hasBer, :);
+berData = groupsummary(berData, ...
+    ["db_mode", "pf_ncoeffs", "bitrate_Gbps"], "min", "BER");
+
+vnleData = vnleBerTable(wh, runTable);
+vnleBerData = vnleData(isfinite(vnleData.BER) & vnleData.BER > 0, :);
+if ~isempty(vnleBerData)
+    vnleBerData = groupsummary(vnleBerData, ...
+        ["db_mode", "bitrate_Gbps"], "min", "BER");
+end
+vnleBerpData = vnleData(isfinite(vnleData.BERp) & vnleData.BERp > 0, :);
+if ~isempty(vnleBerpData)
+    vnleBerpData = groupsummary(vnleBerpData, ...
+        ["db_mode", "bitrate_Gbps"], "min", "BERp");
+end
+
+%% Plot db_mode = 0 and db_mode = 1 in separate panels
+fig = figure(461); clf;
+tiledlayout(1, 2, "TileSpacing", "compact", "Padding", "compact");
+markers = ["o", "square", "diamond"];
+
+for dbMode = [1, 0]
+    ax = nexttile; hold(ax, "on");
+    colors = modeColors(dbMode);
+
+    for pfIdx = 1:numel(pfValues)
+        pf = pfValues(pfIdx);
+        berpMask = berpData.db_mode == dbMode & ...
+            berpData.pf_ncoeffs == pf;
+        if any(berpMask)
+            curveData = sortrows(berpData(berpMask, :), "bitrate_Gbps");
+            plot(ax, curveData.bitrate_Gbps, curveData.min_BERp, ...
+                "LineStyle", "--", ...
+                "LineWidth", 1.3, ...
+                "Marker", markers(pfIdx), ...
+                "MarkerSize", 5, ...
+                "Color", colors(pfIdx, :), ...
+                "DisplayName", sprintf("L = %d, precoded",pf));
+        end
+
+        berMask = berData.db_mode == dbMode & ...
+            berData.pf_ncoeffs == pf;
+        if any(berMask)
+            curveData = sortrows(berData(berMask, :), "bitrate_Gbps");
+            plot(ax, curveData.bitrate_Gbps, curveData.min_BER, ...
+                "LineStyle", "-", ...
+                "LineWidth", 1.3, ...
+                "Marker", markers(pfIdx), ...
+                "MarkerSize", 5, ...
+                "Color", colors(pfIdx, :), ...
+                "DisplayName", sprintf("L = %d",pf));
+        end
+    end
+
+    vnleBerMask = vnleBerData.db_mode == dbMode;
+    if any(vnleBerMask)
+        curveData = sortrows(vnleBerData(vnleBerMask, :), "bitrate_Gbps");
+        plot(ax, curveData.bitrate_Gbps, curveData.min_BER, ...
+            "LineStyle", "-", ...
+            "LineWidth", 1.5, ...
+            "Color", clr.Set1.gray, ...
+            "DisplayName", sprintf("VNLE"));
+    end
+
+    vnleBerpMask = vnleBerpData.db_mode == dbMode;
+    if any(vnleBerpMask)
+        curveData = sortrows(vnleBerpData(vnleBerpMask, :), "bitrate_Gbps");
+        plot(ax, curveData.bitrate_Gbps, curveData.min_BERp, ...
+            "LineStyle", "--", ...
+            "LineWidth", 1.5, ...
+            "Color", clr.Set1.gray, ...
+            "DisplayName", sprintf("VNLE precoded"));
+    end
+
+    yline(ax, [2.2e-4, 4.85e-3, 2e-2], ...
+        "LineStyle", "--", ...
+        "LineWidth", 0.8, ...
+        "Color", [0.25, 0.25, 0.25], ...
+        "HandleVisibility", "off");
+    title(ax, sprintf("db\\_mode = %d", dbMode));
+    xlabel(ax, "Gross rate [Gb/s]");
+    ylabel(ax, "BER");
+    set(ax, "YScale", "log");
+    ylim(ax, [3e-4, 0.1]);
+    xlim([360, 410])
+    grid(ax, "on");
+    box(ax, "on");
+    legend(ax, "Location", "best", "Interpreter", "none");
+    beautifyBERplot("setcolors",false,"setmarkers",false);
+end
+
+set(fig, "Position", [100, 500, 1050, 380]);
+
+%% Local helpers
+
+function colors = modeColors(dbMode)
+switch dbMode
+    case 0
+        colors = [clr.Paired.dred; clr.Paired.dblue; clr.Paired.dgreen];
+    case 1
+        colors = [clr.Paired.dred; clr.Paired.dblue; clr.Paired.dgreen];
+    otherwise
+        error("plot_mlse_n_tap:UnknownDbMode", ...
+            "Unsupported db_mode: %d.", dbMode);
+end
+end
+
+function runIds = getWarehouseRunIds(wh, storageName)
+runIds = zeros(0, 1);
+if ~isfield(wh.sto, storageName)
+    return
+end
+
+storageValues = wh.sto.(storageName);
+for linIdx = 1:numel(storageValues)
+    [phys, ~] = wh.getPhysAndValueByLinIndex(storageName, linIdx);
+    if isfield(phys, "run_id")
+        runIds(end+1, 1) = double(phys.run_id); %#ok<AGROW>
+    end
+end
+runIds = unique(runIds);
+end
+
+function runTable = queryRunsById(db, runIds)
+runTable = table();
+fields = db.getTableFieldNames('Runs');
+
+for runIdx = 1:numel(runIds)
+    fp = QueryFilter();
+    fp.where('Runs', 'run_id', 'EQUALS', runIds(runIdx));
+    [oneRun, ~] = db.queryDB(fp, fields);
+    if isempty(oneRun)
+        warning("plot_mlse_n_tap:MissingRunMetadata", ...
+            "No DB metadata found for warehouse run_id %d.", runIds(runIdx));
+        continue
+    end
+
+    if isempty(runTable)
+        runTable = oneRun;
+    else
+        runTable = [runTable; oneRun]; %#ok<AGROW>
+    end
+end
+
+if ~isempty(runTable) && ismember("db_mode", string(runTable.Properties.VariableNames))
+    runTable = runTable(double(runTable.db_mode) < 2, :);
+end
+end
+
+function plotData = warehouseToTable(wh, runTable, pfValues)
+runIdCol = zeros(0, 1);
+dbModeCol = zeros(0, 1);
+pfCol = zeros(0, 1);
+bitrateCol = zeros(0, 1);
+berCol = zeros(0, 1);
+berpCol = zeros(0, 1);
+
+storageValues = wh.sto.mlse_package;
+for linIdx = 1:numel(storageValues)
+    [phys, storedValue] = wh.getPhysAndValueByLinIndex("mlse_package", linIdx);
+    if ~isfield(phys, "run_id") || ~isfield(phys, "pf_ncoeffs")
+        continue
+    end
+
+    pf = double(phys.pf_ncoeffs);
+    if ~ismember(pf, pfValues)
+        continue
+    end
+
+    runId = double(phys.run_id);
+    rowIdx = find(double(runTable.run_id) == runId, 1, "first");
+    if isempty(rowIdx)
+        continue
+    end
+
+    ber = minMetricValue(storedValue, "BER");
+    berp = minMetricValue(storedValue, "BER_precoded");
+    if (~isfinite(ber) || ber <= 0) && ...
+            (~isfinite(berp) || berp <= 0)
+        continue
+    end
+
+    runIdCol(end+1, 1) = runId; %#ok<AGROW>
+    dbModeCol(end+1, 1) = double(runTable.db_mode(rowIdx)); %#ok<AGROW>
+    pfCol(end+1, 1) = pf; %#ok<AGROW>
+    bitrateCol(end+1, 1) = double(runTable.bitrate(rowIdx)) .* 1e-9; %#ok<AGROW>
+    berCol(end+1, 1) = ber; %#ok<AGROW>
+    berpCol(end+1, 1) = berp; %#ok<AGROW>
+end
+
+plotData = table(runIdCol, dbModeCol, pfCol, bitrateCol, berCol, berpCol, ...
+    'VariableNames', ["run_id", "db_mode", "pf_ncoeffs", ...
+    "bitrate_Gbps", "BER", "BERp"]);
+end
+
+function plotData = vnleBerTable(wh, runTable)
+plotData = table(zeros(0, 1), zeros(0, 1), zeros(0, 1), zeros(0, 1), zeros(0, 1), ...
+    'VariableNames', ["run_id", "db_mode", "bitrate_Gbps", "BER", "BERp"]);
+if ~isfield(wh.sto, "vnle_package")
+    return
+end
+
+runIdCol = zeros(0, 1);
+dbModeCol = zeros(0, 1);
+bitrateCol = zeros(0, 1);
+berCol = zeros(0, 1);
+berpCol = zeros(0, 1);
+storageValues = wh.sto.vnle_package;
+
+for linIdx = 1:numel(storageValues)
+    [phys, storedValue] = wh.getPhysAndValueByLinIndex("vnle_package", linIdx);
+    if ~isfield(phys, "run_id")
+        continue
+    end
+
+    runId = double(phys.run_id);
+    rowIdx = find(double(runTable.run_id) == runId, 1, "first");
+    if isempty(rowIdx)
+        continue
+    end
+
+    ber = minMetricValue(storedValue, "BER");
+    berp = minMetricValue(storedValue, "BER_precoded");
+    if (~isfinite(ber) || ber <= 0) && ...
+            (~isfinite(berp) || berp <= 0)
+        continue
+    end
+
+    runIdCol(end+1, 1) = runId; %#ok<AGROW>
+    dbModeCol(end+1, 1) = double(runTable.db_mode(rowIdx)); %#ok<AGROW>
+    bitrateCol(end+1, 1) = double(runTable.bitrate(rowIdx)) .* 1e-9; %#ok<AGROW>
+    berCol(end+1, 1) = ber; %#ok<AGROW>
+    berpCol(end+1, 1) = berp; %#ok<AGROW>
+end
+
+plotData = table(runIdCol, dbModeCol, bitrateCol, berCol, berpCol, ...
+    'VariableNames', ["run_id", "db_mode", "bitrate_Gbps", "BER", "BERp"]);
+end
+
+function minValue = minMetricValue(value, metricName)
+minValue = NaN;
+if isempty(value)
+    return
+end
+if ~iscell(value)
+    value = {value};
+end
+
+metricValues = NaN(1, numel(value));
+for idx = 1:numel(value)
+    package = value{idx};
+    if ~isstruct(package) || ~isfield(package, "metrics")
+        continue
+    end
+
+    metrics = package.metrics;
+    fieldName = char(metricName);
+    if isstruct(metrics) && isfield(metrics, fieldName)
+        metricValues(idx) = metrics.(fieldName);
+    elseif isobject(metrics) && isprop(metrics, fieldName)
+        metricValues(idx) = metrics.(fieldName);
+    end
+end
+
+metricValues = metricValues(isfinite(metricValues) & metricValues > 0);
+if ~isempty(metricValues)
+    minValue = min(metricValues);
+end
+end

projects/Diss/400G_revisit/PLOT_NGMI_AIR_GMI_RATES_BEST_ALGOS_WITH_DUOBINARY_SIGNALING.m

@@ -0,0 +1,407 @@
+%% Best NGMI, GMI, AIR and FEC rates over symbol rate
+% The normal algorithms are reduced to the best result per algorithm,
+% PAM format and symbol rate.  Duobinary signaling is added as a separate
+% algorithm and is restricted to the post-2026 processing results.
+%
+% The figure has one column per PAM format and one row per metric:
+% BER, NGMI, GMI, AIR, NGMI-based SD+HD NDR, and the best BER-based NDR.
+% NDR values are calculated from the measured BER/NGMI using
+% TransmissionPerformance.
+
+clear; clc;
+
+%% 1) Query data
+
+selectedPamLevels = [4, 6, 8];
+selectedFiberLengthKm = 10;
+selectedWavelengthNm = 1310;
+selectedRopAttenuation = 0;
+selectedIsMpi = 0;
+
+normalDbModes = [double(db_mode.no_db), double(db_mode.db_precoded)];
+duobinaryDbMode = double(db_mode.db_encoded);
+
+showRawEntries = false;
+maxBerForPlot = 0.5;
+
+algoStyles = defaultAlgorithmStyles();
+
+db = DBHandler( ...
+    "dataBase", "labor_highspeed", ...
+    "type", "mysql", ...
+    "server", "192.168.178.192", ...
+    "user", "silas", ...
+    "password", "silas");
+db.refresh();
+
+fp = QueryFilter();
+fp.where('Runs', 'fiber_length', 'EQUALS', selectedFiberLengthKm);
+fp.where('Runs', 'wavelength', 'EQUALS', selectedWavelengthNm);
+fp.where('Runs', 'rop_attenuation', 'EQUALS', selectedRopAttenuation);
+fp.where('Runs', 'is_mpi', 'EQUALS', selectedIsMpi);
+
+selectedFields = db.getTableFieldNames('dashboard_ungrouped_alltime');
+selectedFields = appendMissingFields(selectedFields, {'Runs.precomp_amp'});
+[rawData, query] = db.queryDB(fp, selectedFields);
+disp(query);
+fprintf("Fetched %d rows.\n", height(rawData));
+
+%% 2) Clean data and keep the requested algorithms
+
+data = rawData;
+numericFields = ["result_id", "run_id", "eq_id", "bitrate", "grossrate", ...
+    "symbolrate", "pam_level", "wavelength", "fiber_length", "db_mode", ...
+    "rop_attenuation", "precomp_amp", "is_mpi", "numBits", "numBitErr", ...
+    "BER", "numBitErr_precoded", "BER_precoded", "GMI", "AIR", "NGMI"];
+for fieldIdx = 1:numel(numericFields)
+    fieldName = numericFields(fieldIdx);
+    if ismember(fieldName, string(data.Properties.VariableNames))
+        data.(char(fieldName)) = numericColumn(data.(char(fieldName)));
+    end
+end
+
+data = data(ismember(data.pam_level, selectedPamLevels), :);
+
+normalRows = data(ismember(data.db_mode, normalDbModes), :);
+normalPlotData = buildNormalMetricRows(normalRows);
+
+duobinaryRows = data(data.db_mode == duobinaryDbMode, :);
+if ismember("equalizer_structure", string(duobinaryRows.Properties.VariableNames))
+    duobinaryRows = duobinaryRows( ...
+        equalizerMask(duobinaryRows.equalizer_structure, ...
+        equalizer_structure.db_encoded), :);
+end
+
+% Duobinary results before this date are not comparable to the current set.
+if ismember("date_of_processing", string(duobinaryRows.Properties.VariableNames))
+    duobinaryRows.date_of_processing = datetime(string(duobinaryRows.date_of_processing));
+    duobinaryRows = duobinaryRows(datetime(duobinaryRows.date_of_processing)>datetime("2026-01-01 00:00:00"),:);
+else
+    warning("plot_best_metrics:NoProcessingDate", ...
+        "date_of_processing was not returned; no duobinary date filtering was applied.");
+end
+
+duobinaryPlotData = buildDuobinaryMetricRows(duobinaryRows);
+plotData = [normalPlotData; duobinaryPlotData];
+if isempty(plotData)
+    warning("plot_best_metrics:NoRows", ...
+        "No rows remain after the database and PAM-format filters.");
+    return
+end
+
+plotData = addDerivedMetrics(plotData);
+plotData = plotData(plotData.symbolrate_GBd > 0 & ...
+    isfinite(plotData.symbolrate_GBd), :);
+
+fprintf("Remaining metric rows: %d\n", height(plotData));
+disp(groupcounts(plotData, ["algorithm_key", "pam_level", "precode"]));
+
+%% 3) Calculate BER-/NGMI-dependent net rates
+
+tp = TransmissionPerformance;
+grossRate = double(plotData.grossrate);
+ngmi = double(plotData.NGMI);
+ber = double(plotData.BER_plot);
+
+ngmi(~isfinite(ngmi) | ngmi < 0 | ngmi > 1.05) = NaN;
+ber(~isfinite(ber) | ber <= 0 | ber > maxBerForPlot) = NaN;
+
+ndr = tp.calculateNetRate(grossRate, "NGMI", ngmi, "BER", ber);
+plotData.NDR_SDHD = columnVector(ndr.SDHD.NetRate) .* 1e-9;
+
+berBasedRates = [ ...
+    columnVector(ndr.STAIR.NetRate); ...
+    columnVector(ndr.HD.NetRate); ...
+    columnVector(ndr.KP4.NetRate); ...
+    columnVector(ndr.KP4_hamming.NetRate); ...
+    columnVector(ndr.O_FEC.NetRate)];
+plotData.NDR_BER_BEST = max(reshape(berBasedRates, height(plotData), []), [], 2, "omitnan") .* 1e-9;
+
+%% 4) Keep the best row for every plotted metric and group
+
+metricDefinitions = struct( ...
+    "field", {"BER_plot", "NGMI", "GMI", "AIR_Gbps", "NDR_SDHD", "NDR_BER_BEST"}, ...
+    "label", {"BER", "NGMI", "GMI [bit/sym]", "AIR [Gb/s]", ...
+        "SD+HD NDR [Gb/s]", "Best BER-FEC NDR [Gb/s]"}, ...
+    "scale", {"log", "linear", "linear", "linear", "linear", "linear"});
+
+bestMetricData = cell(numel(metricDefinitions), 1);
+for metricIdx = 1:numel(metricDefinitions)
+    bestMetricData{metricIdx} = bestMetricRows(plotData, ...
+        metricDefinitions(metricIdx).field);
+end
+
+availableStyles = algoStyles(hasAlgorithmRows(plotData, algoStyles), :);
+if isempty(availableStyles)
+    warning("plot_best_metrics:NoSelectedAlgorithms", ...
+        "None of the configured algorithm styles match the queried rows.");
+    return
+end
+
+%% 5) Plot one figure: metric rows x PAM columns
+
+fig = figure(433); clf;
+t = tiledlayout(fig, numel(metricDefinitions), numel(selectedPamLevels), ...
+    "TileSpacing", "compact", ...
+    "Padding", "compact");
+
+for metricIdx = 1:numel(metricDefinitions)
+    metric = metricDefinitions(metricIdx);
+    metricData = bestMetricData{metricIdx};
+
+    for pamIdx = 1:numel(selectedPamLevels)
+        selectedPamLevel = selectedPamLevels(pamIdx);
+        ax = nexttile(t); hold(ax, "on");
+        pamMask = metricData.pam_level == selectedPamLevel;
+
+        for styleIdx = 1:height(availableStyles)
+            style = availableStyles(styleIdx, :);
+            rowMask = pamMask & metricData.algorithm_key == style.algorithm_key;
+            if ~any(rowMask)
+                continue
+            end
+
+            algoData = sortrows(metricData(rowMask, :), "symbolrate_GBd");
+            y = algoData.(metric.field);
+            valid = isfinite(y);
+            if ~any(valid)
+                continue
+            end
+
+            if showRawEntries
+                scatter(ax, algoData.symbolrate_GBd(valid), y(valid), ...
+                    9, ...
+                    "Marker", ".", ...
+                    "MarkerEdgeColor", style.color, ...
+                    "MarkerFaceColor", style.color, ...
+                    "MarkerEdgeAlpha", 0.25, ...
+                    "MarkerFaceAlpha", 0.25, ...
+                    "HandleVisibility", "off");
+            end
+
+            plot(ax, algoData.symbolrate_GBd(valid), y(valid), ...
+                "LineStyle", style.lineStyle, ...
+                "Marker", style.marker, ...
+                "MarkerSize", 4, ...
+                "LineWidth", 1.35, ...
+                "Color", style.color, ...
+                "MarkerFaceColor", style.markerFaceColor, ...
+                "MarkerEdgeColor", style.color, ...
+                "DisplayName", style.name);
+        end
+
+        formatMetricAxis(ax, metric, selectedPamLevel);
+
+        if metricIdx == 1 && pamIdx == 1
+            legend(ax, "Location", "southwest", "Interpreter", "none");
+        end
+    end
+end
+
+title(t, sprintf("Best information metrics, %.0f km, %.0f nm", ...
+    selectedFiberLengthKm, selectedWavelengthNm));
+set(fig, "Position", 1e3 .* [0.08 0.04 1.18 0.86]);
+
+%% Local helpers
+
+function fields = appendMissingFields(fields, extraFields)
+fields = cellstr(fields);
+extraFields = cellstr(extraFields);
+for idx = 1:numel(extraFields)
+    if ~any(strcmp(fields, extraFields{idx}))
+        fields{end+1, 1} = extraFields{idx}; %#ok<AGROW>
+    end
+end
+end
+
+function values = numericColumn(values)
+if iscell(values)
+    values = string(values);
+end
+if isstring(values) || ischar(values)
+    values = str2double(values);
+end
+values = double(values);
+end
+
+function values = columnVector(values)
+values = double(values(:));
+end
+
+function styles = defaultAlgorithmStyles()
+styles = table( ...
+    ["vnle"; "vnle_pf_mlse"; "vnle_db_mlse"; "ml_mlse"; "db_encoded"], ...
+    ["VNLE"; "VNLE + PF + MLSE"; "VNLE DBt. + MLSE"; ...
+        "ML pre-EQ + Viterbi"; "DBS + VNLE + MLSE"], ...
+    ["o"; "square"; "diamond"; "^"; "v"], ...
+    ["-"; "-"; "-"; "-"; "-"], ...
+    ["w"; "w"; "w"; "w"; "w"], ...
+    [clr.Paired.red; clr.Paired.green; clr.Paired.blue; ...
+        clr.Paired.purple; clr.Paired.orange], ...
+    'VariableNames', ["algorithm_key", "name", "marker", ...
+        "lineStyle", "markerFaceColor", "color"]);
+end
+
+function plotData = buildNormalMetricRows(data)
+baseRows = data(isfinite(data.BER), :);
+baseRows.precode = false(height(baseRows), 1);
+baseRows.BER_plot = baseRows.BER;
+baseRows.algorithm_key = algorithmKeyFromEqualizer(baseRows.equalizer_structure);
+baseRows = baseRows(baseRows.algorithm_key ~= "", :);
+
+if ismember("BER_precoded", string(data.Properties.VariableNames))
+    precodedRows = data(isfinite(data.BER_precoded), :);
+    precodedRows.precode = true(height(precodedRows), 1);
+    precodedRows.BER_plot = precodedRows.BER_precoded;
+    precodedRows.algorithm_key = algorithmKeyFromEqualizer( ...
+        precodedRows.equalizer_structure);
+    precodedRows = precodedRows(precodedRows.algorithm_key ~= "", :);
+    plotData = [baseRows; precodedRows];
+else
+    warning("plot_best_metrics:NoPrecodedBer", ...
+        "BER_precoded was not returned; plotting only BER rows.");
+    plotData = baseRows;
+end
+end
+
+function plotData = buildDuobinaryMetricRows(data)
+plotData = data(isfinite(data.BER), :);
+plotData.precode = false(height(plotData), 1);
+plotData.BER_plot = plotData.BER;
+plotData.algorithm_key = repmat("db_encoded", height(plotData), 1);
+end
+
+function plotData = addDerivedMetrics(plotData)
+plotData.symbolrate_GBd = double(plotData.symbolrate) .* 1e-9;
+plotData.grossrate_Gbps = double(plotData.grossrate) .* 1e-9;
+
+% AIR is stored in bit/s.  Reconstruct it from GMI when the stored value is
+% missing or outside the physically meaningful range.
+plotData.AIR_Gbps = numericOrNaN(plotData, "AIR") .* 1e-9;
+gmi = numericOrNaN(plotData, "GMI");
+symbolrate = double(plotData.symbolrate);
+grossrate = double(plotData.grossrate);
+fallbackAir = gmi .* symbolrate .* 1e-9;
+useFallback = ~isfinite(plotData.AIR_Gbps) | plotData.AIR_Gbps < 0 | ...
+    (isfinite(grossrate) & plotData.AIR_Gbps > grossrate .* 1.05e-9);
+plotData.AIR_Gbps(useFallback) = fallbackAir(useFallback);
+
+plotData.GMI = gmi;
+plotData.NGMI = numericOrNaN(plotData, "NGMI");
+end
+
+function values = numericOrNaN(data, fieldName)
+if ismember(fieldName, string(data.Properties.VariableNames))
+    values = numericColumn(data.(char(fieldName)));
+else
+    values = NaN(height(data), 1);
+end
+values = values(:);
+end
+
+function algorithmKey = algorithmKeyFromEqualizer(equalizerColumn)
+if isnumeric(equalizerColumn) || islogical(equalizerColumn)
+    eqNumeric = double(equalizerColumn);
+    algorithmKey = strings(size(eqNumeric));
+    knownKeys = ["vnle", "vnle_pf_mlse", "vnle_db_mlse", "ml_mlse"];
+    knownValues = [double(equalizer_structure.vnle), ...
+        double(equalizer_structure.vnle_pf_mlse), ...
+        double(equalizer_structure.vnle_db_mlse), ...
+        double(equalizer_structure.ml_mlse)];
+    for idx = 1:numel(knownKeys)
+        algorithmKey(eqNumeric == knownValues(idx)) = knownKeys(idx);
+    end
+    return
+end
+
+algorithmKey = lower(string(equalizerColumn));
+algorithmKey(~ismember(algorithmKey, ...
+    ["vnle", "vnle_pf_mlse", "vnle_db_mlse", "ml_mlse"])) = "";
+end
+
+function mask = equalizerMask(equalizerColumn, eqValue)
+if isnumeric(equalizerColumn) || islogical(equalizerColumn)
+    mask = double(equalizerColumn) == double(eqValue);
+else
+    mask = lower(string(equalizerColumn)) == lower(string(eqValue));
+end
+end
+
+function bestData = bestMetricRows(data, metricField)
+valid = isfinite(data.(metricField));
+if strcmp(metricField, "BER_plot")
+    valid = valid & data.(metricField) > 0;
+elseif strcmp(metricField, "NGMI")
+    valid = valid & data.(metricField) >= 0 & data.(metricField) <= 1.05;
+else
+    valid = valid & data.(metricField) >= 0;
+end
+
+candidateData = data(valid, :);
+if isempty(candidateData)
+    bestData = candidateData;
+    return
+end
+
+groupVars = ["pam_level", "algorithm_key", "symbolrate_GBd"];
+groupId = findgroups(candidateData(:, groupVars));
+keepIdx = zeros(max(groupId), 1);
+for curGroup = 1:max(groupId)
+    rowIdx = find(groupId == curGroup);
+    values = candidateData.(metricField)(rowIdx);
+    if strcmp(metricField, "BER_plot")
+        [~, localIdx] = min(values);
+    else
+        [~, localIdx] = max(values);
+    end
+    keepIdx(curGroup) = rowIdx(localIdx(1));
+end
+bestData = sortrows(candidateData(keepIdx, :), groupVars);
+end
+
+function keep = hasAlgorithmRows(data, algoStyles)
+keep = false(height(algoStyles), 1);
+for idx = 1:height(algoStyles)
+    keep(idx) = any(data.algorithm_key == algoStyles.algorithm_key(idx));
+end
+end
+
+function formatMetricAxis(ax, metric, pamLevel)
+set(ax, "FontSize", 8, "TickLabelInterpreter", "none");
+xlabel(ax, "Symbol rate [GBd]");
+ylabel(ax, metric.label);
+xlim(ax, [95 245]);
+xticks(ax, 100:20:240);
+grid(ax, "on");
+grid(ax, "minor");
+box(ax, "on");
+
+switch metric.field
+    case "BER_plot"
+        set(ax, "YScale", "log");
+        ylim(ax, [1e-5 0.2]);
+        yline(ax, [2.2e-4 4.85e-3 2e-2], ...
+            "LineWidth", 0.8, "LineStyle", ":", ...
+            "Color", [0.25 0.25 0.25], "HandleVisibility", "off");
+    case "NGMI"
+        ylim(ax, [0.45 1.02]);
+    case "GMI"
+        set(ax, "YScale", "linear");
+        ylim(ax, [0 max(3.2, log2(pamLevel) + 0.15)]);
+    otherwise
+        set(ax, "YScale", "linear");
+        ylim(ax, [0 500]);
+        yline(ax, 400, "LineWidth", 0.8, "LineStyle", "--", ...
+            "Color", [0.25 0.25 0.25], "HandleVisibility", "off");
+end
+
+if pamLevel == 4
+    title(ax, "PAM-4");
+elseif pamLevel == 6
+    title(ax, "PAM-6");
+elseif pamLevel == 8
+    title(ax, "PAM-8");
+else
+    title(ax, sprintf("PAM-%d", pamLevel));
+end
+end

projects/Diss/400G_revisit/PLOT_REPROCESSED_DSP400G_WAREHOUSE_ANALYSIS.m

@@ -0,0 +1,471 @@
+%% Analysis plots for the reprocessed dsp_400g_recipe warehouse
+% Source warehouse is produced by RUN_REPROCESS_BAUDRATE_FILES_DSP400G.m.
+
+clear; clc;
+
+%% 1) Configuration and warehouse loading
+
+warehouseFile = "D:\baudrate_sweep_b2b\PAMX_b2b_baudrate20241024_210648_dsp400g_reprocessed_wh.mat";
+
+selectedRopAttenForBaudrate = 0;
+selectedEqForRopCurves = "mlse";     % "ffe", "mlse", or "db"
+acquisitionAggregation = "min";      % "min", "median", or "mean"
+fecThreshold = 1e-2;
+polyfitOrderMax = 4;
+showRateAsDatarate = false;
+showRawRopMarkers = true;
+showPolynomialFits = true;
+
+loadedData = load(warehouseFile);
+if isfield(loadedData, "wh")
+    wh = loadedData.wh;
+elseif isfield(loadedData, "obj")
+    wh = loadedData.obj;
+else
+    error("plot_reprocessed_wh:NoWarehouse", ...
+        "Warehouse file must contain a variable named wh or obj.");
+end
+
+wh.showInfo;
+
+eqStyles = defaultEqStyles();
+availableEqStyles = eqStyles(hasWarehouseStorage(wh, eqStyles.storage), :);
+if isempty(availableEqStyles)
+    error("plot_reprocessed_wh:NoEqStorage", ...
+        "None of the configured BER storages are present in wh.sto.");
+end
+
+rawData = warehouseToTable(wh, availableEqStyles);
+rawData = rawData(isfinite(rawData.ber) & rawData.ber > 0, :);
+allData = aggregateAcquisitions(rawData, acquisitionAggregation);
+[allData.rop_axis, ropAxisLabel] = deriveRopAxis(allData);
+
+fprintf("Loaded %d finite acquisition BER rows from warehouse.\n", height(rawData));
+fprintf("Aggregated to %d grouped BER rows using acquisitionAggregation = %s.\n", ...
+    height(allData), acquisitionAggregation);
+disp(groupcounts(allData, ["M", "eq"]));
+
+pamVals = sort(unique(allData.M).');
+fsymVals = sort(unique(allData.fsym).');
+ropAttenVals = sort(unique(allData.rop_atten).');
+ropAxisVals = sort(unique(allData.rop_axis(isfinite(allData.rop_axis))).');
+
+%% 2) BER versus baud rate at fixed ROP attenuation
+
+fig = figure(450); clf;
+tiledlayout(1, numel(pamVals), ...
+    "TileSpacing", "compact", ...
+    "Padding", "compact");
+
+for pamIdx = 1:numel(pamVals)
+    pamLevel = pamVals(pamIdx);
+    ax = nexttile; hold(ax, "on");
+
+    for eqIdx = 1:height(availableEqStyles)
+        eqStyle = availableEqStyles(eqIdx, :);
+        rowMask = allData.M == pamLevel & ...
+            allData.eq == eqStyle.eq & ...
+            allData.rop_atten == selectedRopAttenForBaudrate;
+        if ~any(rowMask)
+            continue
+        end
+
+        curData = sortrows(allData(rowMask, :), "fsym_GBd");
+        plot(ax, curData.fsym_GBd, curData.ber, ...
+            "LineStyle", eqStyle.lineStyle, ...
+            "Marker", eqStyle.marker, ...
+            "MarkerSize", 5, ...
+            "LineWidth", 1.4, ...
+            "Color", eqStyle.color, ...
+            "MarkerFaceColor", "w", ...
+            "MarkerEdgeColor", eqStyle.color, ...
+            "DisplayName", eqStyle.name);
+    end
+
+    plotFecLines(ax, fecThreshold);
+
+    title(ax, sprintf("PAM-%d, ROP atten. %.1f dB", ...
+        pamLevel, selectedRopAttenForBaudrate));
+    xlabel(ax, "Symbol rate [GBd]");
+    ylabel(ax, "BER");
+    set(ax, "YScale", "log");
+    ylim(ax, [1e-5, 0.5]);
+    grid(ax, "on");
+    box(ax, "on");
+    legend(ax, "Location", "best", "Interpreter", "none");
+    applyBerStyle();
+end
+
+set(fig, "Position", 1e3 .* [0.1000 0.5500 1.4113 0.3200]);
+
+%% 3) ROP attenuation curves for one EQ scheme
+
+selectedRopEqStyle = availableEqStyles(availableEqStyles.eq == selectedEqForRopCurves, :);
+if isempty(selectedRopEqStyle)
+    error("plot_reprocessed_wh:MissingSelectedEq", ...
+        "selectedEqForRopCurves = %s is not available in this warehouse.", ...
+        selectedEqForRopCurves);
+end
+
+fig = figure(451); clf;
+tiledlayout(1, numel(pamVals), ...
+    "TileSpacing", "compact", ...
+    "Padding", "compact");
+
+rateColors = rateColorMap(numel(fsymVals));
+for pamIdx = 1:numel(pamVals)
+    pamLevel = pamVals(pamIdx);
+    ax = nexttile; hold(ax, "on");
+
+    for fsymIdx = 1:numel(fsymVals)
+        fsym = fsymVals(fsymIdx);
+        rowMask = allData.M == pamLevel & ...
+            allData.eq == selectedRopEqStyle.eq & ...
+            allData.fsym == fsym;
+        if ~any(rowMask)
+            continue
+        end
+
+        curData = sortrows(allData(rowMask, :), "rop_axis");
+        curveColor = rateColors(fsymIdx, :);
+        displayName = sprintf("%.0f GBd", fsym .* 1e-9);
+
+        if showRawRopMarkers
+            plot(ax, curData.rop_axis, curData.ber, ...
+                "LineStyle", "none", ...
+                "Marker", "o", ...
+                "MarkerSize", 3, ...
+                "LineWidth", 0.8, ...
+                "Color", curveColor, ...
+                "MarkerFaceColor", "w", ...
+                "MarkerEdgeColor", curveColor, ...
+                "DisplayName", displayName);
+        end
+
+        if showPolynomialFits
+            [xFit, yFit] = fitLogBerCurve(curData.rop_axis, ...
+                curData.ber, polyfitOrderMax);
+            if ~isempty(xFit)
+                plot(ax, xFit, yFit, ...
+                    "LineStyle", "-", ...
+                    "LineWidth", 1.1, ...
+                    "Color", curveColor, ...
+                    "HandleVisibility", "off");
+            end
+        end
+    end
+
+    title(ax, sprintf("PAM-%d, %s", pamLevel, selectedRopEqStyle.name));
+    xlabel(ax, ropAxisLabel);
+    ylabel(ax, "BER");
+    set(ax, "YScale", "log");
+    ylim(ax, [1e-5, 0.5]);
+    xlim(ax, [min(ropAxisVals), max(ropAxisVals)]);
+    plotFecLines(ax, fecThreshold);
+    grid(ax, "on");
+    box(ax, "on");
+    legend(ax, "Location", "best", "Interpreter", "none");
+    applyBerStyle();
+end
+
+set(fig, "Position", 1e3 .* [0.1000 0.5500 1.4113 0.3200]);
+
+%% 4) Required ROP attenuation at FEC threshold versus baud rate
+
+fecData = computeFecCrossings(allData, availableEqStyles, fecThreshold, ...
+    polyfitOrderMax);
+if isempty(fecData)
+    warning("plot_reprocessed_wh:NoFecCrossings", ...
+        "No FEC crossings were found for threshold %.3g.", fecThreshold);
+else
+    fig = figure(452); clf;
+    tiledlayout(1, numel(pamVals), ...
+        "TileSpacing", "compact", ...
+        "Padding", "compact");
+
+    for pamIdx = 1:numel(pamVals)
+        pamLevel = pamVals(pamIdx);
+        ax = nexttile; hold(ax, "on");
+
+        for eqIdx = 1:height(availableEqStyles)
+            eqStyle = availableEqStyles(eqIdx, :);
+            rowMask = fecData.M == pamLevel & fecData.eq == eqStyle.eq;
+            if ~any(rowMask)
+                continue
+            end
+
+            curData = sortrows(fecData(rowMask, :), "fsym_GBd");
+            if showRateAsDatarate
+                xData = curData.datarate_Gbps;
+                xLabelText = "Datarate [Gb/s]";
+            else
+                xData = curData.fsym_GBd;
+                xLabelText = "Symbol rate [GBd]";
+            end
+
+            plot(ax, xData, curData.required_rop_axis, ...
+                "LineStyle", eqStyle.lineStyle, ...
+                "Marker", eqStyle.marker, ...
+                "MarkerSize", 5, ...
+                "LineWidth", 1.4, ...
+                "Color", eqStyle.color, ...
+                "MarkerFaceColor", "w", ...
+                "MarkerEdgeColor", eqStyle.color, ...
+                "DisplayName", eqStyle.name);
+        end
+
+        title(ax, sprintf("PAM-%d, BER = %.2g", pamLevel, fecThreshold));
+        xlabel(ax, xLabelText);
+        ylabel(ax, "Required " + ropAxisLabel);
+        grid(ax, "on");
+        box(ax, "on");
+        legend(ax, "Location", "best", "Interpreter", "none");
+    end
+
+    set(fig, "Position", 1e3 .* [0.1000 0.5500 1.4113 0.3200]);
+end
+
+%% Local helpers
+
+function styles = defaultEqStyles()
+styles = table( ...
+    ["ffe"; "mlse"; "db"], ...
+    ["ber_ffe"; "ber_mlse"; "ber_db"], ...
+    ["FFE"; "VNLE + PF + MLSE"; "VNLE DBt. + MLSE"], ...
+    ["o"; "square"; "diamond"], ...
+    ["-"; "-"; "-"], ...
+    [clr.Paired.red; clr.Paired.green; clr.Paired.blue], ...
+    'VariableNames', ["eq", "storage", "name", "marker", ...
+    "lineStyle", "color"]);
+end
+
+function keep = hasWarehouseStorage(wh, storageNames)
+stoFields = string(fieldnames(wh.sto));
+keep = ismember(storageNames, stoFields);
+end
+
+function data = warehouseToTable(wh, eqStyles)
+lastIdx = wh.getLastLinIndice();
+rows = cell(lastIdx * height(eqStyles), 11);
+rowIdx = 0;
+
+for eqIdx = 1:height(eqStyles)
+    eqStyle = eqStyles(eqIdx, :);
+    for linIdx = 1:lastIdx
+        [phys, value] = wh.getPhysAndValueByLinIndex(eqStyle.storage, linIdx);
+        if isempty(value) || ~isnumeric(value) || ~isscalar(value)
+            continue
+        end
+
+        fsym = double(phys.fsym);
+        pamLevel = double(phys.M);
+        ropAtten = double(phys.rop_atten);
+        acquisitionIdx = double(phys.acquisition_idx);
+        ropValue = getOptionalStoredScalarByLinIndex(wh, "rop", linIdx);
+        pdInValue = getOptionalStoredScalarByLinIndex(wh, "pd_in", linIdx);
+
+        rowIdx = rowIdx + 1;
+        rows(rowIdx, :) = { ...
+            fsym, ...
+            fsym .* 1e-9, ...
+            ropAtten, ...
+            pamLevel, ...
+            acquisitionIdx, ...
+            eqStyle.eq, ...
+            eqStyle.storage, ...
+            double(value), ...
+            ropValue, ...
+            pdInValue, ...
+            fsym .* floor(log2(pamLevel) * 10) / 10 .* 1e-9};
+    end
+end
+
+rows = rows(1:rowIdx, :);
+data = cell2table(rows, 'VariableNames', ...
+    ["fsym", "fsym_GBd", "rop_atten", "M", "acquisition_idx", ...
+    "eq", "storage", "ber", "rop_dBm", "pd_in_dBm", "datarate_Gbps"]);
+data.eq = string(data.eq);
+data.storage = string(data.storage);
+end
+
+function data = aggregateAcquisitions(rawData, aggregationMode)
+groupVars = ["fsym", "fsym_GBd", "rop_atten", "M", "eq", ...
+    "storage", "rop_dBm", "pd_in_dBm", "datarate_Gbps"];
+
+switch aggregationMode
+    case "min"
+        data = groupsummary(rawData, groupVars, "min", "ber");
+        data.ber = data.min_ber;
+        data = removevars(data, "min_ber");
+    case "median"
+        data = groupsummary(rawData, groupVars, "median", "ber");
+        data.ber = data.median_ber;
+        data = removevars(data, "median_ber");
+    case "mean"
+        data = groupsummary(rawData, groupVars, "mean", "ber");
+        data.ber = data.mean_ber;
+        data = removevars(data, "mean_ber");
+    otherwise
+        error("plot_reprocessed_wh:UnknownAggregation", ...
+            "Unknown acquisitionAggregation: %s", aggregationMode);
+end
+end
+
+function value = getOptionalStoredScalarByLinIndex(wh, storageName, linIdx)
+value = NaN;
+if ~isfield(wh.sto, storageName)
+    return
+end
+
+storedValue = wh.sto.(storageName){linIdx};
+if isnumeric(storedValue) && isscalar(storedValue)
+    value = double(storedValue);
+end
+end
+
+function [ropAxis, ropAxisLabel] = deriveRopAxis(data)
+if ismember("rop_dBm", string(data.Properties.VariableNames)) && ...
+        any(isfinite(data.rop_dBm))
+    ropAxis = data.rop_dBm;
+    ropAxisLabel = "ROP [dBm]";
+elseif ismember("pd_in_dBm", string(data.Properties.VariableNames)) && ...
+        any(isfinite(data.pd_in_dBm))
+    ropAxis = data.pd_in_dBm;
+    ropAxisLabel = "PD input power [dBm]";
+else
+    ropAxis = data.rop_atten;
+    ropAxisLabel = "ROP attenuation [dB]";
+end
+end
+
+function cmap = rateColorMap(numColors)
+anchors = [ ...
+    clr.Paired.lightblue; ...
+    clr.Paired.blue; ...
+    clr.Paired.green; ...
+    clr.Paired.orange; ...
+    clr.Paired.red; ...
+    clr.Paired.purple];
+if numColors <= size(anchors, 1)
+    cmap = anchors(1:numColors, :);
+    return
+end
+
+xAnchor = linspace(0, 1, size(anchors, 1));
+xQuery = linspace(0, 1, numColors);
+cmap = interp1(xAnchor, anchors, xQuery, "linear");
+end
+
+function [xFit, yFit] = fitLogBerCurve(x, y, maxOrder)
+valid = isfinite(x) & isfinite(y) & y > 0;
+x = x(valid);
+y = y(valid);
+
+if numel(unique(x)) < 2
+    xFit = [];
+    yFit = [];
+    return
+end
+
+[x, orderIdx] = sort(x(:));
+y = y(orderIdx);
+fitOrder = min(maxOrder, numel(unique(x)) - 1);
+coeff = polyfit(x, log10(y), fitOrder);
+xFit = linspace(min(x), max(x), 300).';
+yFit = 10 .^ polyval(coeff, xFit);
+end
+
+function fecData = computeFecCrossings(data, eqStyles, fecThreshold, maxOrder)
+pamVals = unique(data.M).';
+fsymVals = unique(data.fsym).';
+rows = cell(height(eqStyles) * numel(pamVals) * numel(fsymVals), 6);
+rowIdx = 0;
+
+for eqIdx = 1:height(eqStyles)
+    eqStyle = eqStyles(eqIdx, :);
+    for pamIdx = 1:numel(pamVals)
+        pamLevel = pamVals(pamIdx);
+        for fsymIdx = 1:numel(fsymVals)
+            fsym = fsymVals(fsymIdx);
+            rowMask = data.eq == eqStyle.eq & ...
+                data.M == pamLevel & ...
+                data.fsym == fsym;
+            if ~any(rowMask)
+                continue
+            end
+
+            curData = sortrows(data(rowMask, :), "rop_axis");
+            requiredRopAxis = fecCrossingFromCurve( ...
+                curData.rop_axis, curData.ber, fecThreshold, maxOrder);
+            if ~isfinite(requiredRopAxis)
+                continue
+            end
+
+            rowIdx = rowIdx + 1;
+            rows(rowIdx, :) = { ...
+                fsym, ...
+                fsym .* 1e-9, ...
+                pamLevel, ...
+                eqStyle.eq, ...
+                requiredRopAxis, ...
+                fsym .* floor(log2(pamLevel) * 10) / 10 .* 1e-9};
+        end
+    end
+end
+
+if rowIdx == 0
+    fecData = table();
+else
+    rows = rows(1:rowIdx, :);
+    fecData = cell2table(rows, 'VariableNames', ...
+        ["fsym", "fsym_GBd", "M", "eq", "required_rop_axis", ...
+        "datarate_Gbps"]);
+    fecData.eq = string(fecData.eq);
+end
+end
+
+function requiredRopAtten = fecCrossingFromCurve( ...
+    ropAtten, ber, fecThreshold, maxOrder)
+[xFit, yFit] = fitLogBerCurve(ropAtten, ber, maxOrder);
+requiredRopAtten = NaN;
+
+if isempty(xFit)
+    return
+end
+
+crossingMask = isfinite(yFit) & yFit > 0;
+xFit = xFit(crossingMask);
+yFit = yFit(crossingMask);
+if numel(xFit) < 2
+    return
+end
+
+delta = log10(yFit) - log10(fecThreshold);
+crossingIdx = find(delta(1:end-1) .* delta(2:end) <= 0, 1, "first");
+if isempty(crossingIdx)
+    return
+end
+
+x1 = xFit(crossingIdx);
+x2 = xFit(crossingIdx + 1);
+y1 = delta(crossingIdx);
+y2 = delta(crossingIdx + 1);
+requiredRopAtten = x1 - y1 .* (x2 - x1) ./ (y2 - y1);
+end
+
+function plotFecLines(ax, fecThreshold)
+xl = xlim(ax);
+h = plot(ax, xl, [fecThreshold, fecThreshold], ...
+    "LineStyle", "--", ...
+    "LineWidth", 1, ...
+    "Color", [0.25 0.25 0.25], ...
+    "HandleVisibility", "off");
+h.Annotation.LegendInformation.IconDisplayStyle = "off";
+end
+
+function applyBerStyle()
+if exist("beautifyBERplot", "file")
+    beautifyBERplot("logscale", true, "setcolors", false, ...
+        "setmarkers", false, "changemarkers", false);
+end
+end

projects/Diss/400G_revisit/PLOT_ROP_BEST_ALGOS_WITH_DUOBINARY_SIGNALING.m

@@ -0,0 +1,377 @@
+%% 400G BER over ROP: best normal algorithms plus duobinary signaling
+% Normal algorithms are reduced to the best BER per ROP point across
+% db_mode 0/1, pre-emphasis on/off, and BER/BER_precoded result variants.
+% Duobinary signaling uses db_mode = 2 and only the sequence-detection BER
+% stored in the BER field.
+
+clear; clc;
+
+%% 1) Query data
+
+selectedPamLevels = [4, 6, 8];
+selectedFiberLengthKm = 1;
+selectedWavelengthNm = 1310;
+selectedBitrateGbps = 360;
+selectedIsMpi = 0;              % set [] to use all entries
+maxPowerPdIn = [];              % set a numeric limit to enable
+
+normalDbModes = [double(db_mode.no_db)];
+duobinaryDbMode = double(db_mode.db_encoded);
+
+maxBerForPlot = 0.5;
+showRawEntries = false;
+showBestLine = true;
+
+algoStyles = defaultAlgorithmStyles();
+
+db = DBHandler( ...
+    "dataBase", "labor_highspeed", ...
+    "type", "mysql", ...
+    "server", "192.168.178.192", ...
+    "user", "silas", ...
+    "password", "silas");
+db.refresh();
+
+fp = QueryFilter();
+fp.where('Runs', 'fiber_length', 'EQUALS', selectedFiberLengthKm);
+fp.where('Runs', 'wavelength', 'EQUALS', selectedWavelengthNm);
+fp.where('Runs', 'bitrate', 'EQUALS', selectedBitrateGbps .* 1e9);
+if ~isempty(selectedIsMpi)
+    fp.where('Runs', 'is_mpi', 'EQUALS', selectedIsMpi);
+end
+if ~isempty(maxPowerPdIn)
+    fp.where('Runs', 'power_pd_in', 'LESS_THAN', maxPowerPdIn);
+end
+
+selectedFields = [ ...
+    db.getTableFieldNames('power_state_info'); ...
+    db.getTableFieldNames('dashboard_ungrouped_alltime')];
+selectedFields = appendMissingFields(selectedFields, ...
+    {'Runs.precomp_amp'; 'Runs.is_mpi'; 'Runs.power_pd_in'});
+selectedFields = selectedFields(:);
+
+[rawData, query] = db.queryDB(fp, selectedFields);
+disp(query);
+fprintf("Fetched %d 400G ROP result rows.\n", height(rawData));
+
+%% 2) Clean data and build the five plotted curves
+
+data = rawData;
+numericFields = ["result_id", "run_id", "eq_id", "bitrate", "grossrate", ...
+    "symbolrate", "pam_level", "wavelength", "fiber_length", "db_mode", ...
+    "rop_attenuation", "precomp_amp", "is_mpi", "power_rop", ...
+    "power_mzm", "power_pd_in", "voa_atten", "numBits", "numBitErr", ...
+    "BER", "numBitErr_precoded", "BER_precoded", "STD", "STDrx", ...
+    "GMI", "AIR", "NGMI", "EVM", "Alpha"];
+for fieldIdx = 1:numel(numericFields)
+    fieldName = numericFields(fieldIdx);
+    if ismember(fieldName, string(data.Properties.VariableNames))
+        data.(char(fieldName)) = numericColumn(data.(char(fieldName)));
+    end
+end
+
+data = data(ismember(data.pam_level, selectedPamLevels), :);
+
+if ~ismember("precomp_amp", string(data.Properties.VariableNames))
+    warning("plot_rop_best_algos:NoPrecompAmp", ...
+        "Runs.precomp_amp was not returned. Falling back to pre_emphasis = (db_mode == 0).");
+    data.pre_emphasis = data.db_mode == double(db_mode.no_db);
+else
+    data.pre_emphasis = derivePreEmphasis(data.precomp_amp, data.db_mode);
+end
+
+normalRows = data(ismember(data.db_mode, normalDbModes), :);
+normalPlotData = buildNormalMetricRows(normalRows);
+normalPlotData = normalPlotData(isfinite(normalPlotData.BER_plot) & ...
+    normalPlotData.BER_plot > 0 & normalPlotData.BER_plot < maxBerForPlot, :);
+
+duobinaryRows = data(data.db_mode == duobinaryDbMode, :);
+if ismember("equalizer_structure", string(duobinaryRows.Properties.VariableNames))
+    duobinaryRows = duobinaryRows( ...
+        equalizerMask(duobinaryRows.equalizer_structure, ...
+        equalizer_structure.db_encoded), :);
+end
+duobinaryPlotData = buildDuobinarySignalingRows(duobinaryRows);
+duobinaryPlotData = duobinaryPlotData(isfinite(duobinaryPlotData.BER_plot) & ...
+    duobinaryPlotData.BER_plot > 0 & ...
+    duobinaryPlotData.BER_plot < maxBerForPlot, :);
+
+plotData = [normalPlotData; duobinaryPlotData];
+if isempty(plotData)
+    warning("plot_rop_best_algos:NoRows", ...
+        "No rows remain after length/PAM/rate/BER filtering.");
+    return
+end
+
+[plotData.rop_axis, ropAxisLabel] = deriveRopAxis(plotData);
+plotData.rop_axis = round(plotData.rop_axis, 4);
+plotData.bitrate_Gbps = plotData.bitrate .* 1e-9;
+plotData.grossrate_Gbps = plotData.grossrate .* 1e-9;
+plotData = plotData(isfinite(plotData.rop_axis), :);
+
+fprintf("Remaining candidate BER rows: %d\n", height(plotData));
+disp(groupcounts(plotData, ["algorithm_key", "db_mode", "pre_emphasis", "precode"]));
+
+bestPlotData = bestBerByAlgorithmAndRop(plotData);
+fprintf("Keeping %d best-BER rows across PAM/algorithm/ROP groups.\n", ...
+    height(bestPlotData));
+disp(groupcounts(bestPlotData, "algorithm_key"));
+
+%% 3) Plot one 1x3 figure with five lines per PAM
+
+availableStyles = algoStyles(hasAlgorithmRows(bestPlotData, algoStyles), :);
+if isempty(availableStyles)
+    warning("plot_rop_best_algos:NoSelectedAlgorithms", ...
+        "None of the configured algorithm styles match the queried rows.");
+    return
+end
+
+fig = figure(432); clf;
+t = tiledlayout(fig, 1, numel(selectedPamLevels), ...
+    "TileSpacing", "compact", ...
+    "Padding", "compact");
+
+for pamIdx = 1:numel(selectedPamLevels)
+    selectedPamLevel = selectedPamLevels(pamIdx);
+    ax = nexttile(t); hold(ax, "on");
+    pamMask = bestPlotData.pam_level == selectedPamLevel;
+
+    for styleIdx = 1:height(availableStyles)
+        style = availableStyles(styleIdx, :);
+        rowMask = pamMask & bestPlotData.algorithm_key == style.algorithm_key;
+        if ~any(rowMask)
+            continue
+        end
+
+        algoData = sortrows(bestPlotData(rowMask, :), "rop_axis");
+
+        if showRawEntries
+            scatter(ax, algoData.rop_axis, algoData.BER_plot, ...
+                9, ...
+                "Marker", ".", ...
+                "MarkerEdgeColor", style.color, ...
+                "MarkerFaceColor", style.color, ...
+                "MarkerEdgeAlpha", 0.25, ...
+                "MarkerFaceAlpha", 0.25, ...
+                "HandleVisibility", "off");
+        end
+
+        if showBestLine
+            plot(ax, algoData.rop_axis, algoData.BER_plot, ...
+                "LineStyle", style.lineStyle, ...
+                "Marker", style.marker, ...
+                "MarkerSize", 5, ...
+                "LineWidth", 1.5, ...
+                "Color", style.color, ...
+                "MarkerFaceColor", style.markerFaceColor, ...
+                "MarkerEdgeColor", style.color, ...
+                "DisplayName", style.name);
+        end
+    end
+
+    yline(ax, [2.2e-4, 4.85e-3, 2e-2], ...
+        "LineWidth", 1, ...
+        "LineStyle", "--", ...
+        "Color", [0.25 0.25 0.25], ...
+        "HandleVisibility", "off");
+
+    xlabel(ax, ropAxisLabel);
+    ylabel(ax, "BER");
+    set(ax, "YScale", "log");
+    ylim(ax, [8e-5, 0.1]);
+    grid(ax, "on");
+    box(ax, "on");
+
+    xTicks = unique(bestPlotData.rop_axis(pamMask & ...
+        isfinite(bestPlotData.rop_axis)));
+    if ~isempty(xTicks)
+        if isscalar(xTicks)
+            xlim(ax, xTicks + [-0.5, 0.5]);
+        else
+            xlim(ax, [min(xTicks), max(xTicks)]);
+        end
+    end
+
+    legend(ax, "Location", "northeast", "Interpreter", "none");
+    if exist("beautifyBERplot", "file")
+        beautifyBERplot("logscale", true, "setcolors", false, ...
+            "setmarkers", false, "changemarkers", false);
+    end
+end
+
+set(fig, "Position", 1e3 .* [0.1070 0.5497 1.0585 0.2282]);
+
+%% Local helpers
+
+function fields = appendMissingFields(fields, extraFields)
+fields = cellstr(fields);
+extraFields = cellstr(extraFields);
+for idx = 1:numel(extraFields)
+    if ~any(strcmp(fields, extraFields{idx}))
+        fields{end+1, 1} = extraFields{idx}; %#ok<AGROW>
+    end
+end
+end
+
+function values = numericColumn(values)
+if iscell(values)
+    values = string(values);
+end
+if isstring(values) || ischar(values)
+    values = str2double(values);
+end
+values = double(values);
+end
+
+function styles = defaultAlgorithmStyles()
+styles = table( ...
+    ["vnle"; ...
+     "vnle_pf_mlse"; ...
+     "vnle_db_mlse"; ...
+     "ml_mlse"; ...
+     "db_encoded"], ...
+    [equalizer_structure.vnle; ...
+     equalizer_structure.vnle_pf_mlse; ...
+     equalizer_structure.vnle_db_mlse; ...
+     equalizer_structure.ml_mlse; ...
+     equalizer_structure.db_encoded], ...
+    ["VNLE"; ...
+     "VNLE + PF + MLSE"; ...
+     "VNLE DBt. + MLSE"; ...
+     "ML pre-EQ + Viterbi"; ...
+     "DBS + VNLE + MLSE"], ...
+    ["o"; "square"; "diamond"; "^"; "v"], ...
+    ["-"; "-"; "-"; "-"; "-"], ...
+    ["w"; "w"; "w"; "w"; "w"], ...
+    [clr.Paired.red; ...
+     clr.Paired.green; ...
+     clr.Paired.blue; ...
+     clr.Paired.purple; ...
+     clr.Paired.orange], ...
+    'VariableNames', ["algorithm_key", "eq", "name", "marker", ...
+    "lineStyle", "markerFaceColor", "color"]);
+end
+
+function preEmphasis = derivePreEmphasis(precompAmp, dbMode)
+preEmphasis = false(size(dbMode));
+
+validPrecomp = isfinite(precompAmp);
+preEmphasis(validPrecomp) = precompAmp(validPrecomp) > -45;
+
+missingPrecomp = ~validPrecomp;
+preEmphasis(missingPrecomp) = dbMode(missingPrecomp) == double(db_mode.no_db);
+end
+
+function plotData = buildNormalMetricRows(data)
+baseRows = data(isfinite(data.BER), :);
+baseRows.precode = false(height(baseRows), 1);
+baseRows.BER_plot = baseRows.BER;
+baseRows.algorithm_key = algorithmKeyFromEqualizer(baseRows.equalizer_structure);
+baseRows = baseRows(baseRows.algorithm_key ~= "", :);
+
+if ismember("BER_precoded", string(data.Properties.VariableNames))
+    precodedRows = data(isfinite(data.BER_precoded), :);
+    precodedRows.precode = true(height(precodedRows), 1);
+    precodedRows.BER_plot = precodedRows.BER_precoded;
+    precodedRows.algorithm_key = algorithmKeyFromEqualizer( ...
+        precodedRows.equalizer_structure);
+    precodedRows = precodedRows(precodedRows.algorithm_key ~= "", :);
+    plotData = [baseRows; precodedRows];
+else
+    warning("plot_rop_best_algos:NoPrecodedBer", ...
+        "BER_precoded was not returned. Plotting only BER rows for normal algorithms.");
+    plotData = baseRows;
+end
+end
+
+function plotData = buildDuobinarySignalingRows(data)
+plotData = data(isfinite(data.BER), :);
+plotData.precode = false(height(plotData), 1);
+plotData.BER_plot = plotData.BER;
+plotData.algorithm_key = repmat("db_encoded", height(plotData), 1);
+end
+
+function [ropAxis, label] = deriveRopAxis(data)
+if ismember("power_mzm", string(data.Properties.VariableNames)) && ...
+        any(isfinite(data.power_mzm))
+    ropAxis = data.power_mzm;
+    label = "ROP [dBm]";
+elseif ismember("power_pd_in", string(data.Properties.VariableNames)) && ...
+        any(isfinite(data.power_pd_in))
+    ropAxis = data.power_pd_in;
+    label = "PD input power [dBm]";
+else
+    ropAxis = data.rop_attenuation;
+    label = "ROP attenuation [dB]";
+end
+end
+
+function algorithmKey = algorithmKeyFromEqualizer(equalizerColumn)
+eqNumeric = equalizerNumeric(equalizerColumn);
+algorithmKey = strings(size(eqNumeric));
+
+algorithmKey(eqNumeric == enumValue(equalizer_structure.vnle)) = "vnle";
+algorithmKey(eqNumeric == enumValue(equalizer_structure.vnle_pf_mlse)) = ...
+    "vnle_pf_mlse";
+algorithmKey(eqNumeric == enumValue(equalizer_structure.vnle_db_mlse)) = ...
+    "vnle_db_mlse";
+algorithmKey(eqNumeric == enumValue(equalizer_structure.ml_mlse)) = "ml_mlse";
+end
+
+function mask = equalizerMask(equalizerColumn, eqValue)
+eqNumeric = equalizerNumeric(equalizerColumn);
+mask = eqNumeric == enumValue(eqValue);
+end
+
+function eqNumeric = equalizerNumeric(equalizerColumn)
+if isa(equalizerColumn, "equalizer_structure")
+    eqNumeric = double(equalizerColumn);
+elseif isnumeric(equalizerColumn)
+    eqNumeric = double(equalizerColumn);
+else
+    equalizerString = string(equalizerColumn);
+    eqNumeric = str2double(equalizerString);
+
+    enumNames = ["vnle", "ffe", "dfe", "vnle_pf_mlse", ...
+        "vnle_db_mlse", "db_encoded", "ml_mlse"];
+    enumValues = [ ...
+        enumValue(equalizer_structure.vnle), ...
+        enumValue(equalizer_structure.ffe), ...
+        enumValue(equalizer_structure.dfe), ...
+        enumValue(equalizer_structure.vnle_pf_mlse), ...
+        enumValue(equalizer_structure.vnle_db_mlse), ...
+        enumValue(equalizer_structure.db_encoded), ...
+        enumValue(equalizer_structure.ml_mlse)];
+
+    for idx = 1:numel(enumNames)
+        missingNumeric = isnan(eqNumeric);
+        eqNumeric(missingNumeric & equalizerString == enumNames(idx)) = ...
+            enumValues(idx);
+    end
+end
+end
+
+function value = enumValue(enumEntry)
+value = double(enumEntry);
+end
+
+function bestData = bestBerByAlgorithmAndRop(data)
+groupVars = ["pam_level", "algorithm_key", "rop_axis"];
+groupId = findgroups(data(:, groupVars));
+keepIdx = NaN(max(groupId), 1);
+
+for curGroup = 1:max(groupId)
+    rowIdx = find(groupId == curGroup);
+    [~, localBestIdx] = min(data.BER_plot(rowIdx));
+    keepIdx(curGroup) = rowIdx(localBestIdx);
+end
+
+bestData = sortrows(data(keepIdx, :), groupVars);
+end
+
+function keep = hasAlgorithmRows(data, algoStyles)
+keep = false(height(algoStyles), 1);
+for idx = 1:height(algoStyles)
+    keep(idx) = any(data.algorithm_key == algoStyles.algorithm_key(idx));
+end
+end

projects/Diss/400G_revisit/PLOT_SNR_BER_DUOBINARY_PARTIAL_RESPONSE.m

@@ -0,0 +1,317 @@
+%% PAM4/6/8 SNR and uncoded BER versus symbolrate
+clear; clc;
+
+warehouseFile = "C:\Users\Silas\Documents\MATLAB\imdd_simulation\projects\Diss\400G_revisit\results_snr_duobinary_and_partialresponse_pam468_10km.mat";
+pamLevels = [4, 6, 8];
+storageNames = ["mlse_package", "vnle_package", ...
+    "dbtgt_package", "mlse_db_package"];
+techniqueNames = ["MLSE", "VNLE", "DB target", ...
+    "duobinary signaling"];
+
+%% Load warehouse and matching run metadata
+S = load(warehouseFile, "wh");
+wh = S.wh;
+
+db = DBHandler("dataBase", "labor_highspeed", ...
+    "type", "mysql", ...
+    "server", "192.168.178.192", ...
+    "user", "silas", ...
+    "password", "silas");
+
+fp = QueryFilter();
+fp.where('Runs', 'fiber_length', 'EQUALS', 10);
+fp.where('Runs', 'wavelength', 'EQUALS', 1310);
+fp.where('Runs', 'rop_attenuation', 'EQUALS', 0);
+fp.where('Runs', 'is_mpi', 'EQUALS', 0);
+
+[runTable, ~] = db.queryDB(fp, db.getTableFieldNames('Runs'));
+runTable = runTable(ismember(double(runTable.pam_level), pamLevels), :);
+
+%% Extract package metrics
+techniqueCol = strings(0, 1);
+pamCol = zeros(0, 1);
+dbModeCol = zeros(0, 1);
+symbolrateCol = zeros(0, 1);
+snrCol = zeros(0, 1);
+berCol = zeros(0, 1);
+
+for techniqueIdx = 1:numel(storageNames)
+    storageName = storageNames(techniqueIdx);
+    if ~isfield(wh.sto, storageName)
+        continue
+    end
+
+    for k = 1:numel(wh.sto.(storageName))
+        [phys, realizationResults] = wh.getPhysAndValueByLinIndex( ...
+            storageName, k);
+        if ~isfield(phys, "run_id") || isempty(realizationResults)
+            continue
+        end
+
+        runRow = find(double(runTable.run_id) == double(phys.run_id), 1);
+        if isempty(runRow)
+            continue
+        end
+
+        for realization = 1:numel(realizationResults)
+            package = realizationResults{realization};
+            snr = readMetric(package, "SNR");
+            ber = readMetric(package, "BER");
+            if ~isfinite(snr) && ~isfinite(ber)
+                continue
+            end
+
+            techniqueCol(end+1, 1) = techniqueNames(techniqueIdx); %#ok<AGROW>
+            pamCol(end+1, 1) = double(runTable.pam_level(runRow)); %#ok<AGROW>
+            dbModeCol(end+1, 1) = double(runTable.db_mode(runRow)); %#ok<AGROW>
+            symbolrateCol(end+1, 1) = double(runTable.symbolrate(runRow)) * 1e-9; %#ok<AGROW>
+            snrCol(end+1, 1) = snr; %#ok<AGROW>
+            berCol(end+1, 1) = ber; %#ok<AGROW>
+        end
+    end
+end
+
+data = table(techniqueCol, pamCol, dbModeCol, symbolrateCol, snrCol, berCol, ...
+    'VariableNames', ["technique", "pam_level", "db_mode", ...
+    "symbolrate_GBd", "SNR", "BER"]);
+
+% SNR: maximum realization value at each PAM/mode/symbolrate point.
+snrData = data(isfinite(data.SNR), :);
+snrData = groupsummary(snrData, ...
+    ["technique", "pam_level", "db_mode", "symbolrate_GBd"], ...
+    "max", "SNR");
+snrData.Properties.VariableNames(end) = "SNR";
+
+% BER: minimum positive, uncoded BER at each PAM/mode/symbolrate point.
+berData = data(isfinite(data.BER) & data.BER > 0, :);
+berData = groupsummary(berData, ...
+    ["technique", "pam_level", "db_mode", "symbolrate_GBd"], ...
+    "min", "BER");
+berData.Properties.VariableNames(end) = "BER";
+
+%% SNR figure: one tile per technique, PAM4/6/8 together
+figure(472); clf;
+tiledlayout(1, numel(pamLevels), "TileSpacing", "compact", "Padding", "compact");
+for pamLevel = pamLevels
+    ax = nexttile; hold(ax, "on");
+    plotMetric(ax, snrData, pamLevel, techniqueNames, "SNR");
+    title(ax, sprintf("PAM-%d", pamLevel));
+    xlabel(ax, "Symbolrate [GBd]");
+    ylabel(ax, "SNR [dB]");
+    ylim(ax, [15, 25]);
+    grid(ax, "on");
+    box(ax, "on");
+    legend(ax, "Location", "best", "Interpreter", "none");
+    if exist("beautifyBERplot", "file")
+        beautifyBERplot("changemarkers", 0, "setcolors", false);
+    end
+end
+
+%% BER figure: one tile per PAM format
+figure(473); clf;
+tiledlayout(1, numel(pamLevels), "TileSpacing", "compact", "Padding", "compact");
+for pamLevel = pamLevels
+    ax = nexttile; hold(ax, "on");
+    plotMetric(ax, berData, pamLevel, techniqueNames, "BER");
+    title(ax, sprintf("PAM-%d", pamLevel));
+    xlabel(ax, "Symbolrate [GBd]");
+    ylabel(ax, "BER");
+    set(ax, "YScale", "log");
+    grid(ax, "on");
+    box(ax, "on");
+    legend(ax, "Location", "best", "Interpreter", "none");
+end
+
+%% Shared SNR figure: one tile per technique, PAM4/6/8 together
+figure(474); clf;
+tiledlayout(1, 4, "TileSpacing", "compact", "Padding", "compact");
+
+ax = nexttile; hold(ax, "on");
+plotTechniqueSNR(ax, snrData, "VNLE", pamLevels, ...
+    [0, 1], [clr.Paired.lred; clr.Paired.dred]);
+title(ax, "Full Response");
+
+ax = nexttile; hold(ax, "on");
+plotTechniqueSNR(ax, snrData, "MLSE", pamLevels, ...
+    [0, 1], [clr.Paired.lblue; clr.Paired.dblue]);
+title(ax, "Partial Response");
+
+ax = nexttile; hold(ax, "on");
+plotTechniqueSNR(ax, snrData, "DB target", pamLevels, ...
+    [0, 1], [clr.Paired.lgreen; clr.Paired.dgreen]);
+title(ax, "Duobinary Target");
+
+ax = nexttile; hold(ax, "on");
+plotTechniqueSNR(ax, snrData, "duobinary signaling", pamLevels, ...
+    2, clr.Paired.dlila);
+title(ax, "Duobinary Signaling");
+
+%% Shared BER figure: one tile per technique, PAM4/6/8 together
+figure(475); clf;
+tiledlayout(1, 4, "TileSpacing", "compact", "Padding", "compact");
+
+ax = nexttile; hold(ax, "on");
+plotTechniqueBER(ax, berData, "VNLE", pamLevels, ...
+    [0, 1], [clr.Paired.lred; clr.Paired.dred]);
+title(ax, "VNLE");
+
+ax = nexttile; hold(ax, "on");
+plotTechniqueBER(ax, berData, "MLSE", pamLevels, ...
+    [0, 1], [clr.Paired.lblue; clr.Paired.dblue]);
+title(ax, "MLSE");
+
+ax = nexttile; hold(ax, "on");
+plotTechniqueBER(ax, berData, "DB target", pamLevels, ...
+    [0, 1], [clr.Paired.lgreen; clr.Paired.dgreen]);
+title(ax, "DBt.");
+
+ax = nexttile; hold(ax, "on");
+plotTechniqueBER(ax, berData, "duobinary signaling", pamLevels, ...
+    2, clr.Paired.dlila);
+title(ax, "DB signaling");
+
+%% Local helpers
+function value = readMetric(package, metricName)
+value = NaN;
+if isempty(package) || ~isstruct(package) || ~isfield(package, "metrics")
+    return
+end
+
+metrics = package.metrics;
+if isstruct(metrics) && isfield(metrics, metricName)
+    value = double(metrics.(metricName));
+elseif isobject(metrics) && isprop(metrics, metricName)
+    value = double(metrics.(metricName));
+end
+end
+
+function plotMetric(ax, data, pamLevel, techniqueNames, metricName)
+markers = ["o", "s", "diamond", "^"];
+lineStyles = ["-", "--", ":"];
+
+for techniqueIdx = 1:numel(techniqueNames)
+    for dbMode = 0:2
+        rows = data(data.pam_level == pamLevel & ...
+            data.technique == techniqueNames(techniqueIdx) & ...
+            data.db_mode == dbMode, :);
+        if isempty(rows)
+            continue
+        end
+
+        rows = sortrows(rows, "symbolrate_GBd");
+        plot(ax, rows.symbolrate_GBd, rows.(metricName), ...
+            "LineStyle", lineStyles(dbMode + 1), ...
+            "Marker", markers(techniqueIdx), ...
+            "MarkerSize", 5, ...
+            "LineWidth", 1.3, ...
+            "Color", pamModeColor(pamLevel, dbMode), ...
+            "DisplayName", sprintf("%s, %s", ...
+            techniqueNames(techniqueIdx), modeLabel(dbMode)));
+    end
+end
+end
+
+function plotTechniqueSNR(ax, data, techniqueName, pamLevels, dbModes, colors)
+markers = ["square", "hexagram", "*"];
+lineStyles = ["-", "--", ":"];
+
+for modeIdx = 1:numel(dbModes)
+    dbMode = dbModes(modeIdx);
+    for pamIdx = 1:numel(pamLevels)
+        pamLevel = pamLevels(pamIdx);
+        rows = data(data.technique == techniqueName & ...
+            data.pam_level == pamLevel & data.db_mode == dbMode, :);
+        if isempty(rows)
+            continue
+        end
+
+        rows = sortrows(rows, "symbolrate_GBd");
+        plot(ax, rows.symbolrate_GBd, rows.SNR, ...
+            "LineStyle", lineStyles(dbMode + 1), ...
+            "Marker", markers(pamIdx), ...
+            "MarkerSize", 6, ...
+            "LineWidth", 1.3, ...
+            "Color", pamModeColor(pamLevel, dbMode), ...
+            "DisplayName", sprintf("%s, PAM-%d", ...
+            modeLabel(dbMode), pamLevel));
+    end
+end
+
+xlabel(ax, "Symbolrate [GBd]");
+ylabel(ax, "SNR [dB]");
+ylim(ax, [13, 24]);
+grid(ax, "on");
+box(ax, "on");
+legend(ax, "Location", "best", "Interpreter", "none");
+end
+
+function plotTechniqueBER(ax, data, techniqueName, pamLevels, dbModes, colors)
+markers = ["square", "hexagram", "*"];
+lineStyles = ["-", "--", ":"];
+
+for modeIdx = 1:numel(dbModes)
+    dbMode = dbModes(modeIdx);
+    for pamIdx = 1:numel(pamLevels)
+        pamLevel = pamLevels(pamIdx);
+        rows = data(data.technique == techniqueName & ...
+            data.pam_level == pamLevel & data.db_mode == dbMode, :);
+        if isempty(rows)
+            continue
+        end
+
+        rows = sortrows(rows, "symbolrate_GBd");
+        plot(ax, rows.symbolrate_GBd, rows.BER, ...
+            "LineStyle", lineStyles(dbMode + 1), ...
+            "Marker", markers(pamIdx), ...
+            "MarkerSize", 6, ...
+            "LineWidth", 1.3, ...
+            "Color", pamModeColor(pamLevel, dbMode), ...
+            "DisplayName", sprintf("%s, PAM-%d", ...
+            modeLabel(dbMode), pamLevel));
+    end
+end
+
+xlabel(ax, "Symbolrate [GBd]");
+ylabel(ax, "BER");
+set(ax, "YScale", "log");
+ylim(ax, [1e-4, 1e-1]);
+grid(ax, "on");
+box(ax, "on");
+legend(ax, "Location", "best", "Interpreter", "none");
+end
+
+function color = pamModeColor(pamLevel, dbMode)
+switch pamLevel
+    case 4
+        lightColor = clr.Paired.lgreen;
+        darkColor = clr.Paired.dgreen;
+    case 6
+        lightColor = clr.Paired.lblue;
+        darkColor = clr.Paired.dblue;
+    case 8
+        lightColor = clr.Paired.lred;
+        darkColor = clr.Paired.dred;
+    otherwise
+        error("plot_pam_comparison:UnknownPam", ...
+            "Unsupported PAM level %d.", pamLevel);
+end
+
+if dbMode == 0
+    color = lightColor;
+else
+    color = darkColor;
+end
+end
+
+function label = modeLabel(dbMode)
+switch dbMode
+    case 0
+        label = "with preemphasis";
+    case 1
+        label = "no preemphasis";
+    case 2
+        label = "db encoded";
+    otherwise
+        label = sprintf("db\_mode = %d", dbMode);
+end
+end

projects/Diss/400G_revisit/PLOT_WAREHOUSE_BAUDRATE_ROP_ANALYSIS.m

@@ -0,0 +1,440 @@
+%% Warehouse baud-rate and ROP analysis for FFE, MLSE, and duobinary target
+% Template source:
+% projects/Diss/400G_revisit/auswertung_baudrate.mlx
+
+clear; clc;
+
+%% 1) Configuration and warehouse loading
+
+warehouseFile = "W:\labdata\sioe_labor\baudrate_sweep_b2b\PAMX_b2b_baudrate20241024_210648_wh_final.mat";
+
+selectedRopAttenForBaudrate = 0;
+selectedEqForRopCurves = "mlse";     % "ffe", "mlse", or "db"
+fecThreshold = 2.2e-2;
+polyfitOrderMax = 4;
+showRateAsDatarate = false;
+showRawRopMarkers = true;
+showPolynomialFits = true;
+
+loadedData = load(warehouseFile);
+if isfield(loadedData, "obj")
+    wh = loadedData.obj;
+elseif isfield(loadedData, "wh")
+    wh = loadedData.wh;
+else
+    error("plot_warehouse:NoWarehouse", ...
+        "Warehouse file must contain a variable named obj or wh.");
+end
+
+wh.showInfo;
+
+fsymVals = double(wh.parameter.fsym.values(:).');
+ropAttenVals = double(wh.parameter.rop_atten.values(:).');
+pamVals = sort(double(wh.parameter.M.values(:).'));
+
+eqStyles = defaultEqStyles();
+availableEqStyles = eqStyles(hasWarehouseStorage(wh, eqStyles.storage), :);
+if isempty(availableEqStyles)
+    error("plot_warehouse:NoEqStorage", ...
+        "None of the configured BER storages are present in wh.sto.");
+end
+
+allData = warehouseToTable(wh, fsymVals, ropAttenVals, pamVals, availableEqStyles);
+allData = allData(isfinite(allData.ber) & allData.ber > 0, :);
+
+fprintf("Loaded %d finite BER rows from warehouse.\n", height(allData));
+disp(groupcounts(allData, ["M", "eq"]));
+
+for eqIdx = 1:height(availableEqStyles)
+    if ~any(allData.eq == availableEqStyles.eq(eqIdx))
+        warning("plot_warehouse:NoPositiveBer", ...
+            "Storage %s exists, but contains no positive BER values to plot.", ...
+            availableEqStyles.storage(eqIdx));
+    end
+end
+
+%% 2) BER versus baud rate at fixed ROP attenuation
+
+fig = figure(440); clf;
+tiledlayout(1, numel(pamVals), ...
+    "TileSpacing", "compact", ...
+    "Padding", "compact");
+
+for pamIdx = 1:numel(pamVals)
+    pamLevel = pamVals(pamIdx);
+    ax = nexttile; hold(ax, "on");
+
+    for eqIdx = 1:height(availableEqStyles)
+        eqStyle = availableEqStyles(eqIdx, :);
+        rowMask = allData.M == pamLevel & ...
+            allData.eq == eqStyle.eq & ...
+            allData.rop_atten == selectedRopAttenForBaudrate;
+        if ~any(rowMask)
+            continue
+        end
+
+        curData = sortrows(allData(rowMask, :), "fsym_GBd");
+        plot(ax, curData.fsym_GBd, curData.ber, ...
+            "LineStyle", eqStyle.lineStyle, ...
+            "Marker", eqStyle.marker, ...
+            "MarkerSize", 5, ...
+            "LineWidth", 1.4, ...
+            "Color", eqStyle.color, ...
+            "MarkerFaceColor", "w", ...
+            "MarkerEdgeColor", eqStyle.color, ...
+            "DisplayName", eqStyle.name);
+    end
+
+    yline(ax, fecThreshold, ...
+        "LineStyle", "--", ...
+        "LineWidth", 1, ...
+        "Color", [0.25 0.25 0.25], ...
+        "HandleVisibility", "off");
+
+    title(ax, sprintf("PAM-%d, ROP atten. %.1f dB", ...
+        pamLevel, selectedRopAttenForBaudrate));
+    xlabel(ax, "Symbol rate [GBd]");
+    ylabel(ax, "BER");
+    set(ax, "YScale", "log");
+    ylim(ax, [1e-5, 0.5]);
+    grid(ax, "on");
+    box(ax, "on");
+    legend(ax, "Location", "best", "Interpreter", "none");
+    applyBerStyle();
+end
+
+set(fig, "Position", 1e3 .* [0.1000 0.5500 1.4113 0.3200]);
+
+%% 3) ROP attenuation curves for one EQ scheme
+
+selectedRopEqStyle = availableEqStyles(availableEqStyles.eq == selectedEqForRopCurves, :);
+if isempty(selectedRopEqStyle)
+    error("plot_warehouse:MissingSelectedEq", ...
+        "selectedEqForRopCurves = %s is not available in this warehouse.", ...
+        selectedEqForRopCurves);
+end
+
+fig = figure(441); clf;
+tiledlayout(1, numel(pamVals), ...
+    "TileSpacing", "compact", ...
+    "Padding", "compact");
+
+rateColors = rateColorMap(numel(fsymVals));
+for pamIdx = 1:numel(pamVals)
+    pamLevel = pamVals(pamIdx);
+    ax = nexttile; hold(ax, "on");
+
+    for fsymIdx = 1:numel(fsymVals)
+        fsym = fsymVals(fsymIdx);
+        rowMask = allData.M == pamLevel & ...
+            allData.eq == selectedRopEqStyle.eq & ...
+            allData.fsym == fsym;
+        if ~any(rowMask)
+            continue
+        end
+
+        curData = sortrows(allData(rowMask, :), "rop_atten");
+        curveColor = rateColors(fsymIdx, :);
+        displayName = sprintf("%.0f GBd", fsym .* 1e-9);
+
+        if showRawRopMarkers
+            plot(ax, curData.rop_atten, curData.ber, ...
+                "LineStyle", "none", ...
+                "Marker", "o", ...
+                "MarkerSize", 3, ...
+                "LineWidth", 0.8, ...
+                "Color", curveColor, ...
+                "MarkerFaceColor", "w", ...
+                "MarkerEdgeColor", curveColor, ...
+                "DisplayName", displayName);
+        end
+
+        if showPolynomialFits
+            [xFit, yFit] = fitLogBerCurve(curData.rop_atten, ...
+                curData.ber, polyfitOrderMax);
+            if ~isempty(xFit)
+                plot(ax, xFit, yFit, ...
+                    "LineStyle", "-", ...
+                    "LineWidth", 1.1, ...
+                    "Color", curveColor, ...
+                    "HandleVisibility", "off");
+            end
+        end
+    end
+
+    yline(ax, fecThreshold, ...
+        "LineStyle", "--", ...
+        "LineWidth", 1, ...
+        "Color", [0.25 0.25 0.25], ...
+        "HandleVisibility", "off");
+
+    title(ax, sprintf("PAM-%d, %s", pamLevel, selectedRopEqStyle.name));
+    xlabel(ax, "ROP attenuation [dB]");
+    ylabel(ax, "BER");
+    set(ax, "YScale", "log");
+    ylim(ax, [1e-5, 0.5]);
+    xlim(ax, [min(ropAttenVals), max(ropAttenVals)]);
+    grid(ax, "on");
+    box(ax, "on");
+    legend(ax, "Location", "best", "Interpreter", "none");
+    applyBerStyle();
+end
+
+set(fig, "Position", 1e3 .* [0.1000 0.5500 1.4113 0.3200]);
+
+%% 4) Required power at FEC threshold versus baud rate
+
+fecData = computeFecCrossings(allData, availableEqStyles, fecThreshold, ...
+    polyfitOrderMax);
+if isempty(fecData)
+    warning("plot_warehouse:NoFecCrossings", ...
+        "No FEC crossings were found for threshold %.3g.", fecThreshold);
+else
+    fig = figure(442); clf;
+    tiledlayout(1, numel(pamVals), ...
+        "TileSpacing", "compact", ...
+        "Padding", "compact");
+
+    for pamIdx = 1:numel(pamVals)
+        pamLevel = pamVals(pamIdx);
+        ax = nexttile; hold(ax, "on");
+
+        for eqIdx = 1:height(availableEqStyles)
+            eqStyle = availableEqStyles(eqIdx, :);
+            rowMask = fecData.M == pamLevel & fecData.eq == eqStyle.eq;
+            if ~any(rowMask)
+                continue
+            end
+
+            curData = sortrows(fecData(rowMask, :), "fsym_GBd");
+            if showRateAsDatarate
+                xData = curData.datarate_Gbps;
+                xLabelText = "Datarate [Gb/s]";
+            else
+                xData = curData.fsym_GBd;
+                xLabelText = "Symbol rate [GBd]";
+            end
+
+            plot(ax, xData, curData.required_rop_dBm, ...
+                "LineStyle", eqStyle.lineStyle, ...
+                "Marker", eqStyle.marker, ...
+                "MarkerSize", 5, ...
+                "LineWidth", 1.4, ...
+                "Color", eqStyle.color, ...
+                "MarkerFaceColor", "w", ...
+                "MarkerEdgeColor", eqStyle.color, ...
+                "DisplayName", eqStyle.name);
+        end
+
+        title(ax, sprintf("PAM-%d, BER = %.2g", pamLevel, fecThreshold));
+        xlabel(ax, xLabelText);
+        ylabel(ax, "Required ROP [dBm]");
+        grid(ax, "on");
+        box(ax, "on");
+        legend(ax, "Location", "best", "Interpreter", "none");
+    end
+
+    set(fig, "Position", 1e3 .* [0.1000 0.5500 1.4113 0.3200]);
+end
+
+%% Local helpers
+
+function styles = defaultEqStyles()
+styles = table( ...
+    ["ffe"; "mlse"; "db"], ...
+    ["ber_ffe"; "ber_mlse"; "ber_db"], ...
+    ["FFE"; "MLSE"; "Duobinary target"], ...
+    ["o"; "square"; "diamond"], ...
+    ["-"; "-"; "-"], ...
+    [clr.Paired.red; clr.Paired.green; clr.Paired.blue], ...
+    'VariableNames', ["eq", "storage", "name", "marker", ...
+    "lineStyle", "color"]);
+end
+
+function keep = hasWarehouseStorage(wh, storageNames)
+stoFields = string(fieldnames(wh.sto));
+keep = ismember(storageNames, stoFields);
+end
+
+function data = warehouseToTable(wh, fsymVals, ropAttenVals, pamVals, eqStyles)
+rows = {};
+
+for eqIdx = 1:height(eqStyles)
+    eqStyle = eqStyles(eqIdx, :);
+    for pamIdx = 1:numel(pamVals)
+        pamLevel = pamVals(pamIdx);
+        for fsymIdx = 1:numel(fsymVals)
+            fsym = fsymVals(fsymIdx);
+
+            berValues = wh.getStoValue(eqStyle.storage, fsym, ...
+                ropAttenVals, pamLevel);
+            ropValues = getOptionalStoValues(wh, "rop", fsym, ...
+                ropAttenVals, pamLevel);
+            pdInValues = getOptionalStoValues(wh, "pd_in", fsym, ...
+                ropAttenVals, pamLevel);
+
+            berValues = berValues(:);
+            ropValues = ropValues(:);
+            pdInValues = pdInValues(:);
+
+            for ropIdx = 1:numel(ropAttenVals)
+                rows(end+1, :) = { ... %#ok<AGROW>
+                    fsym, ...
+                    fsym .* 1e-9, ...
+                    ropAttenVals(ropIdx), ...
+                    pamLevel, ...
+                    eqStyle.eq, ...
+                    eqStyle.storage, ...
+                    berValues(ropIdx), ...
+                    ropValues(ropIdx), ...
+                    pdInValues(ropIdx), ...
+                    fsym .* floor(log2(pamLevel) * 10) / 10 .* 1e-9};
+            end
+        end
+    end
+end
+
+data = cell2table(rows, 'VariableNames', ...
+    ["fsym", "fsym_GBd", "rop_atten", "M", "eq", "storage", ...
+    "ber", "rop_dBm", "pd_in_dBm", "datarate_Gbps"]);
+data.eq = string(data.eq);
+data.storage = string(data.storage);
+end
+
+function values = getOptionalStoValues(wh, storageName, fsym, ropAttenVals, pamLevel)
+if ismember(storageName, string(fieldnames(wh.sto)))
+    values = wh.getStoValue(storageName, fsym, ropAttenVals, pamLevel);
+else
+    values = nan(size(ropAttenVals));
+end
+end
+
+function cmap = rateColorMap(numColors)
+anchors = [ ...
+    clr.Paired.lightblue; ...
+    clr.Paired.blue; ...
+    clr.Paired.green; ...
+    clr.Paired.orange; ...
+    clr.Paired.red; ...
+    clr.Paired.purple];
+if numColors <= size(anchors, 1)
+    cmap = anchors(1:numColors, :);
+    return
+end
+
+xAnchor = linspace(0, 1, size(anchors, 1));
+xQuery = linspace(0, 1, numColors);
+cmap = interp1(xAnchor, anchors, xQuery, "linear");
+end
+
+function [xFit, yFit] = fitLogBerCurve(x, y, maxOrder)
+valid = isfinite(x) & isfinite(y) & y > 0;
+x = x(valid);
+y = y(valid);
+
+if numel(unique(x)) < 2
+    xFit = [];
+    yFit = [];
+    return
+end
+
+[x, orderIdx] = sort(x(:));
+y = y(orderIdx);
+fitOrder = min(maxOrder, numel(unique(x)) - 1);
+coeff = polyfit(x, log10(y), fitOrder);
+xFit = linspace(min(x), max(x), 300).';
+yFit = 10 .^ polyval(coeff, xFit);
+end
+
+function fecData = computeFecCrossings(data, eqStyles, fecThreshold, maxOrder)
+rows = {};
+pamVals = unique(data.M).';
+fsymVals = unique(data.fsym).';
+
+for eqIdx = 1:height(eqStyles)
+    eqStyle = eqStyles(eqIdx, :);
+    for pamIdx = 1:numel(pamVals)
+        pamLevel = pamVals(pamIdx);
+        for fsymIdx = 1:numel(fsymVals)
+            fsym = fsymVals(fsymIdx);
+            rowMask = data.eq == eqStyle.eq & ...
+                data.M == pamLevel & ...
+                data.fsym == fsym;
+            if ~any(rowMask)
+                continue
+            end
+
+            curData = sortrows(data(rowMask, :), "rop_atten");
+            [requiredRopAtten, requiredRop] = fecCrossingFromCurve( ...
+                curData.rop_atten, curData.ber, curData.rop_dBm, ...
+                fecThreshold, maxOrder);
+            if ~isfinite(requiredRop)
+                continue
+            end
+
+            rows(end+1, :) = { ... %#ok<AGROW>
+                fsym, ...
+                fsym .* 1e-9, ...
+                pamLevel, ...
+                eqStyle.eq, ...
+                requiredRopAtten, ...
+                requiredRop, ...
+                fsym .* floor(log2(pamLevel) * 10) / 10 .* 1e-9};
+        end
+    end
+end
+
+if isempty(rows)
+    fecData = table();
+else
+    fecData = cell2table(rows, 'VariableNames', ...
+        ["fsym", "fsym_GBd", "M", "eq", "required_rop_atten", ...
+        "required_rop_dBm", "datarate_Gbps"]);
+    fecData.eq = string(fecData.eq);
+end
+end
+
+function [requiredRopAtten, requiredRop] = fecCrossingFromCurve( ...
+    ropAtten, ber, rop, fecThreshold, maxOrder)
+[xFit, yFit] = fitLogBerCurve(ropAtten, ber, maxOrder);
+requiredRopAtten = NaN;
+requiredRop = NaN;
+
+if isempty(xFit)
+    return
+end
+
+crossingMask = isfinite(yFit) & yFit > 0;
+xFit = xFit(crossingMask);
+yFit = yFit(crossingMask);
+if numel(xFit) < 2
+    return
+end
+
+delta = log10(yFit) - log10(fecThreshold);
+crossingIdx = find(delta(1:end-1) .* delta(2:end) <= 0, 1, "first");
+if isempty(crossingIdx)
+    return
+end
+
+x1 = xFit(crossingIdx);
+x2 = xFit(crossingIdx + 1);
+y1 = delta(crossingIdx);
+y2 = delta(crossingIdx + 1);
+requiredRopAtten = x1 - y1 .* (x2 - x1) ./ (y2 - y1);
+
+validRop = isfinite(ropAtten) & isfinite(rop);
+if nnz(validRop) >= 2
+    requiredRop = interp1(ropAtten(validRop), rop(validRop), ...
+        requiredRopAtten, "linear", "extrap");
+else
+    requiredRop = requiredRopAtten;
+end
+end
+
+function applyBerStyle()
+if exist("beautifyBERplot", "file")
+    beautifyBERplot("logscale", true, "setcolors", false, ...
+        "setmarkers", false, "changemarkers", false);
+end
+end

projects/Diss/400G_revisit/PLOT_WAVELENGTH_BEST_ALGOS_WITH_DUOBINARY_SIGNALING.m

@@ -0,0 +1,691 @@
+%% 400G BER over wavelength: best normal algorithms plus duobinary signaling
+% Normal algorithms are reduced to the best BER per wavelength across
+% db_mode 0/1, pre-emphasis on/off, and BER/BER_precoded result variants.
+% Duobinary signaling uses db_mode = 2 and only the sequence-detection BER
+% stored in the BER field.
+
+clear; clc;
+
+%% 1) Query data
+
+selectedPamLevels = [4, 6, 8];
+selectedFiberLengthKm = 5;
+selectedBitratesGbps = 300:30:480; % set [] to use all available bitrates
+selectedRopAttenuation = 0;     % set [] to use all ROP attenuation values
+selectedIsMpi = 0;              % set [] to use all entries
+
+normalDbModes = [double(db_mode.no_db), double(db_mode.db_precoded)];
+duobinaryDbMode = double(db_mode.db_encoded);
+
+maxBerForPlot = 0.5;
+showRawEntries = false;
+showBestLine = true;
+showPolynomialFits = true;
+polyfitOrder = 4;
+fecThreshold = 2e-2;
+
+algoStyles = defaultAlgorithmStyles();
+areaResults = cell(numel(selectedPamLevels), 1);
+
+for pamIdx = 1:numel(selectedPamLevels)
+    selectedPamLevel = selectedPamLevels(pamIdx);
+
+db = DBHandler( ...
+    "dataBase", "labor_highspeed", ...
+    "type", "mysql", ...
+    "server", "192.168.178.192", ...
+    "user", "silas", ...
+    "password", "silas");
+db.refresh();
+
+fp = QueryFilter();
+fp.where('Runs', 'fiber_length', 'EQUALS', selectedFiberLengthKm);
+fp.where('Runs', 'pam_level', 'EQUALS', selectedPamLevel);
+if ~isempty(selectedRopAttenuation)
+    fp.where('Runs', 'rop_attenuation', 'EQUALS', selectedRopAttenuation);
+end
+if ~isempty(selectedIsMpi)
+    fp.where('Runs', 'is_mpi', 'EQUALS', selectedIsMpi);
+end
+
+selectedFields = db.getTableFieldNames('dashboard_ungrouped_alltime');
+selectedFields = appendMissingFields(selectedFields, ...
+    {'Runs.precomp_amp'; 'Runs.is_mpi'});
+selectedFields = selectedFields(:);
+
+[rawData, query] = db.queryDB(fp, selectedFields);
+disp(query);
+fprintf("Fetched %d wavelength-sweep result rows.\n", height(rawData));
+
+%% 2) Clean data and build the five plotted curves
+
+data = rawData;
+numericFields = ["result_id", "run_id", "eq_id", "bitrate", "grossrate", ...
+    "symbolrate", "pam_level", "wavelength", "fiber_length", "db_mode", ...
+    "rop_attenuation", "precomp_amp", "is_mpi", "numBits", "numBitErr", ...
+    "BER", "numBitErr_precoded", "BER_precoded", "STD", "STDrx", ...
+    "GMI", "AIR", "NGMI", "EVM", "Alpha"];
+for fieldIdx = 1:numel(numericFields)
+    fieldName = numericFields(fieldIdx);
+    if ismember(fieldName, string(data.Properties.VariableNames))
+        data.(char(fieldName)) = numericColumn(data.(char(fieldName)));
+    end
+end
+
+data.bitrate_Gbps = data.bitrate .* 1e-9;
+if ~isempty(selectedBitratesGbps)
+    data = data(ismember(round(data.bitrate_Gbps, 6), selectedBitratesGbps), :);
+end
+
+if ~ismember("precomp_amp", string(data.Properties.VariableNames))
+    warning("plot_wavelength_best_algos:NoPrecompAmp", ...
+        "Runs.precomp_amp was not returned. Falling back to pre_emphasis = (db_mode == 0).");
+    data.pre_emphasis = data.db_mode == double(db_mode.no_db);
+else
+    data.pre_emphasis = derivePreEmphasis(data.precomp_amp, data.db_mode);
+end
+
+normalRows = data(ismember(data.db_mode, normalDbModes), :);
+normalPlotData = buildNormalMetricRows(normalRows);
+normalPlotData = normalPlotData(isfinite(normalPlotData.BER_plot) & ...
+    normalPlotData.BER_plot > 0 & normalPlotData.BER_plot < maxBerForPlot, :);
+
+duobinaryRows = data(data.db_mode == duobinaryDbMode, :);
+if ismember("equalizer_structure", string(duobinaryRows.Properties.VariableNames))
+    duobinaryRows = duobinaryRows( ...
+        equalizerMask(duobinaryRows.equalizer_structure, ...
+        equalizer_structure.db_encoded), :);
+end
+duobinaryPlotData = buildDuobinarySignalingRows(duobinaryRows);
+duobinaryPlotData = duobinaryPlotData(isfinite(duobinaryPlotData.BER_plot) & ...
+    duobinaryPlotData.BER_plot > 0 & ...
+    duobinaryPlotData.BER_plot < maxBerForPlot, :);
+
+plotData = [normalPlotData; duobinaryPlotData];
+if isempty(plotData)
+    warning("plot_wavelength_best_algos:NoRows", ...
+        "No rows remain after length/PAM/rate/BER filtering.");
+    continue
+end
+
+plotData.bitrate_Gbps = plotData.bitrate .* 1e-9;
+plotData.grossrate_Gbps = plotData.grossrate .* 1e-9;
+
+fprintf("Remaining candidate BER rows: %d\n", height(plotData));
+disp(groupcounts(plotData, ["algorithm_key", "db_mode", "pre_emphasis", "precode"]));
+
+bestPlotData = bestBerByAlgorithmAndWavelength(plotData);
+fprintf("Keeping %d best-BER rows across algorithm/wavelength groups.\n", ...
+    height(bestPlotData));
+disp(groupcounts(bestPlotData, "algorithm_key"));
+
+%% 3) Plot one tile per algorithm
+
+availableStyles = algoStyles(hasAlgorithmRows(bestPlotData, algoStyles), :);
+if isempty(availableStyles)
+    warning("plot_wavelength_best_algos:NoSelectedAlgorithms", ...
+        "None of the configured algorithm styles match the queried rows.");
+    continue
+end
+
+fig = figure(432 + pamIdx); clf;
+t = tiledlayout(fig, 1, height(availableStyles), ...
+    "TileSpacing","compact", ...
+    "Padding", "compact");
+
+availableBitratesGbps = unique(bestPlotData.bitrate_Gbps(isfinite( ...
+    bestPlotData.bitrate_Gbps))).';
+bitrateMarkers = bitrateMarkerSet(numel(availableBitratesGbps));
+
+for styleIdx = 1:height(availableStyles)
+    style = availableStyles(styleIdx, :);
+    ax = nexttile(t); hold(ax, "on");
+    bitrateColors = sequentialColors(style.color, numel(availableBitratesGbps), ...
+        style.algorithm_key);
+
+    for bitrateIdx = 1:numel(availableBitratesGbps)
+        bitrateGbps = availableBitratesGbps(bitrateIdx);
+        rowMask = bestPlotData.algorithm_key == style.algorithm_key & ...
+            bestPlotData.bitrate_Gbps == bitrateGbps;
+        if ~any(rowMask)
+            continue
+        end
+
+        algoData = sortrows(bestPlotData(rowMask, :), "wavelength");
+        curveColor = bitrateColors(bitrateIdx, :);
+
+        if showRawEntries
+            scatter(ax, algoData.wavelength, algoData.BER_plot, ...
+                9, ...
+                "Marker", ".", ...
+                "MarkerEdgeColor", curveColor, ...
+                "MarkerFaceColor", curveColor, ...
+                "MarkerEdgeAlpha", 0.25, ...
+                "MarkerFaceAlpha", 0.25, ...
+                "HandleVisibility", "off");
+        end
+
+        if showBestLine
+            plot(ax, algoData.wavelength, algoData.BER_plot, ...
+                "LineStyle", style.lineStyle, ...
+                "Marker", bitrateMarkers(bitrateIdx), ...
+                "MarkerSize", 2.5, ...
+                "LineWidth", 1.0, ...
+                "Color", curveColor, ...
+                "MarkerFaceColor", style.markerFaceColor, ...
+                "MarkerEdgeColor", curveColor, ...
+                "HandleVisibility", "off");
+        end
+
+        if showPolynomialFits
+            [xFit, yFit] = fitLogBerCurve(algoData.wavelength, ...
+                algoData.BER_plot, polyfitOrder);
+            if ~isempty(xFit)
+                plot(ax, xFit, yFit, ...
+                    "LineStyle", ":", ...
+                    "LineWidth", 1.1, ...
+                    "Color", curveColor, ...
+                    "HandleVisibility", "off");
+            end
+        end
+    end
+
+    % title(ax, style.name, "Interpreter", "none");
+    xlabel(ax, "Wavelength [nm]");
+    ylabel(ax, "BER");
+    set(ax, "YScale", "log");
+    
+    if selectedPamLevel == 4
+        ylim(ax, [1e-6, 0.3]);
+    elseif selectedPamLevel == 6
+        ylim(ax, [1e-4, 0.3]);
+    elseif selectedPamLevel == 8
+        ylim(ax, [1e-4, 0.3]);
+    end
+
+    grid(ax, "on");
+    box(ax, "on");
+
+    if styleIdx > 1
+        ylabel(ax, "");
+        yticklabels(ax, {});
+    end
+
+    xTicks = unique(bestPlotData.wavelength(isfinite(bestPlotData.wavelength)));
+    xTicks = xTicks(1:2:end);
+    xTicks_own = [1300,1310,1320];
+    set(ax, "XTick", xTicks_own);
+    
+    if ~isempty(xTicks)
+        xlim(ax, [min(xTicks)-1, max(xTicks)+1]);
+    end
+
+    plotFecLines(ax, fecThreshold);
+
+    if exist("beautifyBERplot", "file")
+        beautifyBERplot("logscale", true, "setcolors", false, ...
+            "setmarkers", false, "changemarkers", false);
+    end
+
+    text(ax, 0.02, 0.02, style.name, ...
+        "Units", "normalized", ...
+        "HorizontalAlignment", "left", ...
+        "VerticalAlignment", "bottom", ...
+        "BackgroundColor", "white", ...
+        "EdgeColor", [0.60 0.60 0.60], ...
+        "LineWidth", 0.5, ...
+        "Margin", 2, ...
+        "FontSize", 8, ...
+        "Interpreter", "none", ...
+        "Clipping", "on");
+
+end
+set(fig, "Position", 1e3 .* [0.1070 0.5497 1.4113 0.3253]);
+
+wavelengthTikzPath = sprintf( ...
+    "C:/Users/Silas/Documents/6971e0b65b380ca6d71c837f/04_Experimental_Evaluation/tikz/400g/10km_wavelength_compare_pam%d.tikz", ...
+    selectedPamLevel);
+% mat2tikz_improved(wavelengthTikzPath, "cleanfigure", 0);
+
+areaData = computePermissibleWavelengthAreas(bestPlotData, availableStyles, ...
+    fecThreshold, polyfitOrder);
+if isempty(areaData)
+    warning("plot_wavelength_best_algos:NoPermissibleAreas", ...
+        "No measured wavelength samples are at or below the BER threshold %.3g.", ...
+        fecThreshold);
+else
+    areaResults{pamIdx} = areaData;
+end
+end
+
+%% 4) Permissible wavelength area versus gross rate for all PAM levels
+
+areaFig = figure(436); clf;
+areaLayout = tiledlayout(areaFig, 1, 3, ...
+    "TileSpacing", "compact", ...
+    "Padding", "compact");
+
+for pamIdx = 1:numel(selectedPamLevels)
+    areaAx = nexttile(areaLayout); hold(areaAx, "on");
+    areaData = areaResults{pamIdx};
+
+    if isempty(areaData)
+        grid(areaAx, "on");
+        box(areaAx, "on");
+    else
+        for styleIdx = 1:height(algoStyles)
+            style = algoStyles(styleIdx, :);
+            rowMask = areaData.algorithm_key == style.algorithm_key;
+            if ~any(rowMask)
+                continue
+            end
+
+            algoAreaData = sortrows(areaData(rowMask, :), "grossrate_Gbps");
+            plot(areaAx, algoAreaData.grossrate_Gbps, ...
+                algoAreaData.permissible_wavelength_area_nm, ...
+                "LineStyle", style.lineStyle, ...
+                "Marker", style.marker, ...
+                "MarkerSize", 5, ...
+                "LineWidth", 1.4, ...
+                "Color", style.color, ...
+                "MarkerFaceColor", style.markerFaceColor, ...
+                "MarkerEdgeColor", style.color, ...
+                "DisplayName", style.name, ...
+                "HandleVisibility", "on");
+        end
+    end
+    ylim([5 35]);
+    xlabel(areaAx, "Gross rate [Gb/s]");
+    if pamIdx == 1
+        ylabel(areaAx, "Permissible wavelength area [nm]");
+    else
+        ylabel(areaAx, "");
+        % Ensure yticklabels refers to the function, not a variable
+        if exist("yticklabels", "var")
+            clear yticklabels
+        end
+        yticks(areaAx,[5:5:35]);
+        yticklabels(areaAx, "");
+    end
+    grid(areaAx, "on");
+    box(areaAx, "on");
+    text(areaAx, 0.2, 0.06, sprintf("PAM%d", selectedPamLevels(pamIdx)), ...
+        "Units", "normalized", ...
+        "HorizontalAlignment", "left", ...
+        "VerticalAlignment", "bottom", ...
+        "BackgroundColor", "white", ...
+        "EdgeColor", [0.60 0.60 0.60], ...
+        "LineWidth", 0.5, ...
+        "Margin", 2, ...
+        "FontSize", 8, ...
+        "Interpreter", "none", ...
+        "Clipping", "on");
+
+end
+legend
+set(areaFig, "Position", 1e3 .* [0.3500 0.3500 0.7000 0.8000]);
+% mat2tikz_improved( ...
+%     "C:/Users/Silas/Documents/6971e0b65b380ca6d71c837f/04_Experimental_Evaluation/tikz/400g/10km_permissible_wavelength.tikz", ...
+%     "cleanfigure", 0);
+
+%% Local helpers
+
+function fields = appendMissingFields(fields, extraFields)
+fields = cellstr(fields);
+extraFields = cellstr(extraFields);
+for idx = 1:numel(extraFields)
+    if ~any(strcmp(fields, extraFields{idx}))
+        fields{end+1, 1} = extraFields{idx}; %#ok<AGROW>
+    end
+end
+end
+
+function values = numericColumn(values)
+if iscell(values)
+    values = string(values);
+end
+if isstring(values) || ischar(values)
+    values = str2double(values);
+end
+values = double(values);
+end
+
+function styles = defaultAlgorithmStyles()
+styles = table( ...
+    ["vnle"; ...
+     "vnle_pf_mlse"; ...
+     "vnle_db_mlse"; ...
+     "ml_mlse"; ...
+     "db_encoded"], ...
+    [equalizer_structure.vnle; ...
+     equalizer_structure.vnle_pf_mlse; ...
+     equalizer_structure.vnle_db_mlse; ...
+     equalizer_structure.ml_mlse; ...
+     equalizer_structure.db_encoded], ...
+    ["VNLE"; ...
+     "VNLE + PF + MLSE"; ...
+     "VNLE DBt. + MLSE"; ...
+     "ML pre-EQ + Viterbi"; ...
+     "DBS + VNLE + MLSE"], ...
+    ["o"; "square"; "diamond"; "^"; "v"], ...
+    ["-"; "-"; "-"; "-"; "-"], ...
+    ["w"; "w"; "w"; "w"; "w"], ...
+    [clr.Paired.red; ...
+     clr.Paired.green; ...
+     clr.Paired.blue; ...
+     clr.Paired.purple; ...
+     clr.Paired.orange], ...
+    'VariableNames', ["algorithm_key", "eq", "name", "marker", ...
+    "lineStyle", "markerFaceColor", "color"]);
+end
+
+function preEmphasis = derivePreEmphasis(precompAmp, dbMode)
+preEmphasis = false(size(dbMode));
+
+validPrecomp = isfinite(precompAmp);
+preEmphasis(validPrecomp) = precompAmp(validPrecomp) > -45;
+
+missingPrecomp = ~validPrecomp;
+preEmphasis(missingPrecomp) = dbMode(missingPrecomp) == double(db_mode.no_db);
+end
+
+function plotData = buildNormalMetricRows(data)
+baseRows = data(isfinite(data.BER), :);
+baseRows.precode = false(height(baseRows), 1);
+baseRows.BER_plot = baseRows.BER;
+baseRows.algorithm_key = algorithmKeyFromEqualizer(baseRows.equalizer_structure);
+baseRows = baseRows(baseRows.algorithm_key ~= "", :);
+
+if ismember("BER_precoded", string(data.Properties.VariableNames))
+    precodedRows = data(isfinite(data.BER_precoded), :);
+    precodedRows.precode = true(height(precodedRows), 1);
+    precodedRows.BER_plot = precodedRows.BER_precoded;
+    precodedRows.algorithm_key = algorithmKeyFromEqualizer( ...
+        precodedRows.equalizer_structure);
+    precodedRows = precodedRows(precodedRows.algorithm_key ~= "", :);
+    plotData = [baseRows; precodedRows];
+else
+    warning("plot_wavelength_best_algos:NoPrecodedBer", ...
+        "BER_precoded was not returned. Plotting only BER rows for normal algorithms.");
+    plotData = baseRows;
+end
+end
+
+function plotData = buildDuobinarySignalingRows(data)
+plotData = data(isfinite(data.BER), :);
+plotData.precode = false(height(plotData), 1);
+plotData.BER_plot = plotData.BER;
+plotData.algorithm_key = repmat("db_encoded", height(plotData), 1);
+end
+
+function algorithmKey = algorithmKeyFromEqualizer(equalizerColumn)
+eqNumeric = equalizerNumeric(equalizerColumn);
+algorithmKey = strings(size(eqNumeric));
+
+algorithmKey(eqNumeric == enumValue(equalizer_structure.vnle)) = "vnle";
+algorithmKey(eqNumeric == enumValue(equalizer_structure.vnle_pf_mlse)) = ...
+    "vnle_pf_mlse";
+algorithmKey(eqNumeric == enumValue(equalizer_structure.vnle_db_mlse)) = ...
+    "vnle_db_mlse";
+algorithmKey(eqNumeric == enumValue(equalizer_structure.ml_mlse)) = "ml_mlse";
+end
+
+function mask = equalizerMask(equalizerColumn, eqValue)
+eqNumeric = equalizerNumeric(equalizerColumn);
+mask = eqNumeric == enumValue(eqValue);
+end
+
+function eqNumeric = equalizerNumeric(equalizerColumn)
+if isa(equalizerColumn, "equalizer_structure")
+    eqNumeric = double(equalizerColumn);
+elseif isnumeric(equalizerColumn)
+    eqNumeric = double(equalizerColumn);
+else
+    equalizerString = string(equalizerColumn);
+    eqNumeric = str2double(equalizerString);
+
+    enumNames = ["vnle", "ffe", "dfe", "vnle_pf_mlse", ...
+        "vnle_db_mlse", "db_encoded", "ml_mlse"];
+    enumValues = [ ...
+        enumValue(equalizer_structure.vnle), ...
+        enumValue(equalizer_structure.ffe), ...
+        enumValue(equalizer_structure.dfe), ...
+        enumValue(equalizer_structure.vnle_pf_mlse), ...
+        enumValue(equalizer_structure.vnle_db_mlse), ...
+        enumValue(equalizer_structure.db_encoded), ...
+        enumValue(equalizer_structure.ml_mlse)];
+
+    for idx = 1:numel(enumNames)
+        missingNumeric = isnan(eqNumeric);
+        eqNumeric(missingNumeric & equalizerString == enumNames(idx)) = ...
+            enumValues(idx);
+    end
+end
+end
+
+function value = enumValue(enumEntry)
+value = double(enumEntry);
+end
+
+function bestData = bestBerByAlgorithmAndWavelength(data)
+groupVars = ["algorithm_key", "bitrate_Gbps", "wavelength"];
+groupId = findgroups(data(:, groupVars));
+keepIdx = NaN(max(groupId), 1);
+
+for curGroup = 1:max(groupId)
+    rowIdx = find(groupId == curGroup);
+    [~, localBestIdx] = min(data.BER_plot(rowIdx));
+    keepIdx(curGroup) = rowIdx(localBestIdx);
+end
+
+bestData = sortrows(data(keepIdx, :), groupVars);
+end
+
+function [xFit, yFit, fitModel] = fitLogBerCurve(x, y, maxOrder)
+valid = isfinite(x) & isfinite(y) & y > 0;
+x = x(valid);
+y = y(valid);
+
+[x, orderIdx] = sort(x(:));
+y = y(orderIdx);
+[x, uniqueIdx] = unique(x);
+y = y(uniqueIdx);
+if numel(x) < 2
+    xFit = [];
+    yFit = [];
+    fitModel = [];
+    return
+end
+
+% Keep the requested fourth-order fit when enough wavelength points exist.
+% With fewer than five unique points, use the highest identifiable order.
+fitOrder = min(maxOrder, numel(x) - 1);
+[coefficients, ~, mu] = polyfit(x, log10(y), fitOrder);
+fitModel.coefficients = coefficients;
+fitModel.mu = mu;
+xFit = linspace(min(x), max(x), 300).';
+yFit = 10 .^ polyval(coefficients, (xFit - mu(1)) ./ mu(2));
+end
+
+function areaData = computePermissibleWavelengthAreas(data, algoStyles, ...
+    fecThreshold, maxOrder)
+grossrateValues = unique(data.grossrate_Gbps(isfinite( ...
+    data.grossrate_Gbps))).';
+wavelengthGrid = unique(data.wavelength(isfinite(data.wavelength))).';
+rows = cell(height(algoStyles) * numel(grossrateValues), 5);
+rowIdx = 0;
+
+for styleIdx = 1:height(algoStyles)
+    style = algoStyles(styleIdx, :);
+    algorithmMask = data.algorithm_key == style.algorithm_key;
+
+    for grossrateIdx = 1:numel(grossrateValues)
+        grossrateGb = grossrateValues(grossrateIdx);
+        rowMask = algorithmMask & data.grossrate_Gbps == grossrateGb;
+        if ~any(rowMask)
+            continue
+        end
+
+        curveData = sortrows(data(rowMask, :), "wavelength");
+        [wavelengthMin, wavelengthMax] = permissibleWavelengthRange( ...
+            curveData.wavelength, curveData.BER_plot, fecThreshold, ...
+            maxOrder, wavelengthGrid);
+        if any(~isfinite([wavelengthMin, wavelengthMax]))
+            continue
+        end
+
+        rowIdx = rowIdx + 1;
+        rows(rowIdx, :) = { ...
+            style.algorithm_key, ...
+            grossrateGb, ...
+            wavelengthMin, ...
+            wavelengthMax, ...
+            wavelengthMax - wavelengthMin};
+    end
+end
+
+if rowIdx == 0
+    areaData = table();
+else
+    rows = rows(1:rowIdx, :);
+    areaData = cell2table(rows, "VariableNames", ...
+        ["algorithm_key", "grossrate_Gbps", ...
+        "wavelength_min_allowed_nm", "wavelength_max_allowed_nm", ...
+        "permissible_wavelength_area_nm"]);
+    areaData.algorithm_key = string(areaData.algorithm_key);
+end
+end
+
+function [wavelengthMin, wavelengthMax] = permissibleWavelengthRange(x, y, ...
+    fecThreshold, maxOrder, wavelengthGrid)
+wavelengthMin = NaN;
+wavelengthMax = NaN;
+valid = isfinite(x) & isfinite(y) & y > 0;
+x = x(valid);
+y = y(valid);
+if isempty(x)
+    return
+end
+
+[x, orderIdx] = sort(x(:));
+y = y(orderIdx);
+[x, uniqueIdx] = unique(x);
+y = y(uniqueIdx);
+wavelengthGrid = sort(wavelengthGrid(:));
+if isempty(wavelengthGrid)
+    return
+end
+
+globalRange = [wavelengthGrid(1), wavelengthGrid(end)];
+edgeTolerance = max(1e-9, 1e-9 .* max(abs(globalRange)));
+missingLeftEdge = x(1) > globalRange(1) + edgeTolerance;
+missingRightEdge = x(end) < globalRange(2) - edgeTolerance;
+
+% If all observed points are below the FEC, use the complete sweep span
+% instead of requiring polynomial roots outside the observed range.
+if all(y <= fecThreshold)
+    wavelengthMin = globalRange(1);
+    wavelengthMax = globalRange(2);
+    return
+end
+
+[~, ~, fitModel] = fitLogBerCurve(x, y, maxOrder);
+if isempty(fitModel)
+    return
+end
+
+xRange = [x(1), x(end)];
+crossingCoefficients = fitModel.coefficients;
+crossingCoefficients(end) = crossingCoefficients(end) - log10(fecThreshold);
+rootsAtThreshold = roots(crossingCoefficients);
+realRoots = real(rootsAtThreshold(abs(imag(rootsAtThreshold)) < ...
+    1e-7 .* max(1, abs(real(rootsAtThreshold)))));
+realRoots = realRoots .* fitModel.mu(2) + fitModel.mu(1);
+realRoots = sort(realRoots(realRoots >= xRange(1) & realRoots <= xRange(2)));
+if isempty(realRoots)
+    return
+end
+
+% Include the observed boundaries in the interval search. This lets each
+% side be handled independently: a side that remains below FEC uses the
+% corresponding observed edge, while a side that crosses FEC uses its root.
+intervalEdges = [xRange(1); realRoots(:); xRange(2)];
+intervalWidths = diff(intervalEdges);
+intervalIsAllowed = false(size(intervalWidths));
+thresholdLogBer = log10(fecThreshold);
+for intervalIdx = 1:numel(intervalEdges)-1
+    midpoint = mean(intervalEdges(intervalIdx:intervalIdx + 1));
+    normalizedMidpoint = (midpoint - fitModel.mu(1)) ./ fitModel.mu(2);
+    intervalIsAllowed(intervalIdx) = polyval(fitModel.coefficients, ...
+        normalizedMidpoint) <= thresholdLogBer;
+end
+
+allowedIntervals = find(intervalIsAllowed);
+if isempty(allowedIntervals)
+    return
+end
+
+[~, widestAllowedIdx] = max(intervalWidths(allowedIntervals));
+selectedInterval = allowedIntervals(widestAllowedIdx);
+wavelengthMin = intervalEdges(selectedInterval);
+wavelengthMax = intervalEdges(selectedInterval + 1);
+
+% A missing terminal wavelength sample is treated as below FEC when the
+% permissible interval reaches that side of the observed curve.
+if selectedInterval == 1 && missingLeftEdge
+    wavelengthMin = globalRange(1);
+end
+if selectedInterval == numel(intervalWidths) && missingRightEdge
+    wavelengthMax = globalRange(2);
+end
+end
+
+function keep = hasAlgorithmRows(data, algoStyles)
+keep = false(height(algoStyles), 1);
+for idx = 1:height(algoStyles)
+    keep(idx) = any(data.algorithm_key == algoStyles.algorithm_key(idx));
+end
+end
+
+function plotFecLines(ax, fecLevels)
+xl = xlim(ax);
+for idx = 1:numel(fecLevels)
+    h = plot(ax, xl, [fecLevels(idx), fecLevels(idx)], ...
+        "LineWidth", 1, ...
+        "LineStyle", "--", ...
+        "Color", [0.25 0.25 0.25], ...
+        "HandleVisibility", "off");
+    h.Annotation.LegendInformation.IconDisplayStyle = "off";
+end
+end
+
+function markers = bitrateMarkerSet(n)
+markerOptions = ["o", "square", "diamond", "^", "v", ">", "<"];
+if n <= numel(markerOptions)
+    markers = markerOptions(1:n);
+else
+    markers = markerOptions(mod(0:n-1, numel(markerOptions)) + 1);
+end
+end
+
+function colors = sequentialColors(baseColor, n, algorithmKey)
+if n <= 1
+    colors = baseColor;
+    return
+end
+
+lightBlend = linspace(0.72, 0.00, n).';
+darkBlend = linspace(0.00, 0.35, n).';
+if algorithmKey == "db_encoded"
+    lightBlend = linspace(0.62, 0.00, n).';
+    darkBlend = linspace(0.00, 0.12, n).';
+end
+
+colors = zeros(n, 3);
+for idx = 1:n
+    color = (1 - lightBlend(idx)) .* baseColor + lightBlend(idx) .* [1 1 1];
+    color = (1 - darkBlend(idx)) .* color;
+    colors(idx, :) = color;
+end
+colors = flip(colors);
+end

projects/Diss/400G_revisit/REPLOT_OPT_FILT_ANALYSIS_BY_PAM.m

@@ -0,0 +1,85 @@
+%% Replot opt_filt_analysis.fig grouped by PAM level
+clear; close all; clc;
+
+figPath = fullfile(fileparts(mfilename("fullpath")), "opt_filt_analysis.fig");
+figIn = openfig(figPath, "invisible");
+
+srcAx = findall(figIn, "Type", "axes");
+srcAx = srcAx(1);
+srcLines = flipud(findall(srcAx, "Type", "line"));
+
+% Get every plotted datapoint and its display name.
+data = arrayfun(@(h) struct( ...
+    "XData", h.XData, ...
+    "YData", h.YData, ...
+    "DisplayName", string(h.DisplayName)), srcLines);
+displayNames = string({data.DisplayName})';
+disp(displayNames);
+
+selectedEqType = "ffe";  % choose "ffe" or "mlse"
+eqtype = ["ffe", "mlse"];
+eqGroup = repmat("", size(displayNames));
+for k = 1:numel(eqtype)
+    eqGroup(contains(lower(displayNames), eqtype(k))) = eqtype(k);
+end
+if ~ismember(selectedEqType, eqtype)
+    error("selectedEqType must be either 'ffe' or 'mlse'.");
+end
+
+keep = eqGroup == selectedEqType;
+srcLines = srcLines(keep);
+data = data(keep);
+displayNames = displayNames(keep);
+
+pamLevels = ["pam4", "pam6", "pam8"];
+pamGroup = repmat("", size(displayNames));
+for k = 1:numel(pamLevels)
+    pamGroup(contains(lower(displayNames), pamLevels(k))) = pamLevels(k);
+end
+
+% Group by the first part of the display name.
+groupLabels = ["A", "B", "C", "D", "E"];
+groupGroup = repmat("", size(displayNames));
+nameLower = lower(displayNames);
+groupGroup(startsWith(nameLower, "120 gb") | ...
+    startsWith(nameLower, "144 gb") | startsWith(nameLower, "170 gb")) = "A";
+groupGroup(startsWith(nameLower, "optfil")) = "B";
+groupGroup(startsWith(nameLower, "thormax")) = "C";
+groupGroup(startsWith(nameLower, "thormax optfil")) = "E";
+groupGroup(startsWith(nameLower, "thormax optfil ohne fl")) = "D";
+
+groupColors = [clr.Paired.red; clr.Paired.blue; clr.Paired.green; ...
+    clr.Paired.orange; clr.Paired.purple];
+groupStyles = {"-", "--", ":", ":", ":"};
+groupMarkers = {"o", "s", "^", "d", "v"};
+
+figOut = figure("Name", "opt_filt_analysis by " + upper(selectedEqType) + " and PAM");
+layout = tiledlayout(figOut, 1, 3, "TileSpacing", "compact", "Padding", "compact");
+
+for k = 1:numel(pamLevels)
+    ax = nexttile(layout);
+    hold(ax, "on");
+
+    for lineIdx = find(pamGroup == pamLevels(k))'
+        newLine = copyobj(srcLines(lineIdx), ax);
+        groupIdx = find(groupLabels == groupGroup(lineIdx), 1);
+        newLine.Color = groupColors(groupIdx, :);
+        newLine.Marker = groupMarkers{groupIdx};
+        newLine.LineWidth = 1;
+        newLine.LineStyle = groupStyles{groupIdx};
+        newLine.MarkerSize = 3;
+        newLine.DisplayName = groupGroup(lineIdx);
+    end
+
+    ax.XScale = srcAx.XScale;
+    ax.YScale = srcAx.YScale;
+    title(ax, upper(pamLevels(k)));
+    xlabel(ax, srcAx.XLabel.String);
+    ylabel(ax, srcAx.YLabel.String);
+    grid(ax, "on");
+    legend(ax, "show", "Interpreter", "none", "Location", "best");
+
+    beautifyBERplot("setcolors", false, "setmarkers", false);
+end
+
+close(figIn);

projects/Diss/400G_revisit/RUN_REPROCESS_BAUDRATE_FILES_DSP400G.m

@@ -0,0 +1,430 @@
+%% Reprocess baudrate-sweep MAT files with dsp_400g_recipe
+% File naming convention:
+% PAMX_b2b_baudrate20241024_210648PAM_4_fsym_100_bits.mat
+% PAMX_b2b_baudrate20241024_210648PAM_4_fsym_100_symbols.mat
+% PAMX_b2b_baudrate20241024_210648PAM_4_fsym_100_rop_0_5_rx_signal.mat
+
+clear; clc;
+
+%% Configuration
+
+dataDir = "D:\baudrate_sweep_b2b";
+filePrefix = "PAMX_b2b_baudrate20241024_210648";
+outputFile = fullfile(dataDir, filePrefix + "_dsp400g_reprocessed_wh.mat");
+originalWarehouseFile = fullfile(dataDir, filePrefix + "_wh_final.mat");
+
+pamLevels = [4, 6, 8];
+fsymGBd = 100:6:196;
+ropAtten = 0:0.5:7;
+% ropAtten = 0:0.5:7;
+
+useParallel = true;
+batchSize = 24;              % warehouse writes happen after each batch
+maxJobs = inf;               % use a small number for smoke tests
+saveEveryBatches = 1;
+debugPlots = false;
+storeDspOutput = false;      % full output objects can make the warehouse very large
+copyOriginalPowerMetadata = true;
+
+recipeParams = struct( ...
+    "run_ffe", true, ...
+    "run_vnle_mlse", true, ...
+    "run_dbtgt", true, ...
+    "run_ml_mlse", true, ...
+    "run_ml_mlse_db", false, ...
+    "run_mlse_db", false, ...
+    "plot_input_signal", false, ...
+    "plot_output_signals", false);
+
+%% Discover all file/acquisition jobs
+
+jobs = buildJobList(dataDir, filePrefix, pamLevels, fsymGBd, ropAtten);
+if isempty(jobs)
+    error("reprocess:NoJobs", "No processable RX acquisition jobs were found.");
+end
+
+if isfinite(maxJobs)
+    jobs = jobs(1:min(numel(jobs), maxJobs));
+end
+
+maxAcquisitionIdx = max([jobs.acquisition_idx]);
+fprintf("Discovered %d acquisition jobs, max acquisition index S{%d}.\n", ...
+    numel(jobs), maxAcquisitionIdx);
+
+powerLookup = loadOriginalPowerLookup(originalWarehouseFile, ...
+    copyOriginalPowerMetadata);
+
+%% Build output warehouse
+
+params = struct();
+params.fsym = fsymGBd .* 1e9;
+params.rop_atten = ropAtten;
+params.M = pamLevels;
+params.acquisition_idx = 1:maxAcquisitionIdx;
+
+wh = DataStorage(params);
+wh.addStorage("ber_ffe");
+wh.addStorage("ber_mlse");
+wh.addStorage("ber_db");
+wh.addStorage("ber_ffe_precoded");
+wh.addStorage("ber_mlse_precoded");
+wh.addStorage("ber_db_precoded");
+wh.addStorage("rop");
+wh.addStorage("pd_in");
+wh.addStorage("rx_file");
+wh.addStorage("status");
+wh.addStorage("error_message");
+if storeDspOutput
+    wh.addStorage("dsp_output");
+end
+
+parallelEnabled = useParallel && ensureParallelPool();
+if parallelEnabled
+    pool = gcp("nocreate");
+    fprintf("Processing with parfor on %d workers.\n", pool.NumWorkers);
+else
+    fprintf("Processing serially.\n");
+end
+
+%% Process jobs in parallel batches, write warehouse serially
+
+numBatches = ceil(numel(jobs) / batchSize);
+for batchIdx = 1:numBatches
+    firstJob = (batchIdx - 1) * batchSize + 1;
+    lastJob = min(batchIdx * batchSize, numel(jobs));
+    batchJobs = jobs(firstJob:lastJob);
+    batchResults = cell(numel(batchJobs), 1);
+
+    fprintf("Batch %d/%d: jobs %d-%d of %d\n", ...
+        batchIdx, numBatches, firstJob, lastJob, numel(jobs));
+
+    if parallelEnabled
+        parfor localIdx = 1:numel(batchJobs)
+            batchResults{localIdx} = processOneJob( ...
+                batchJobs(localIdx), recipeParams, debugPlots, storeDspOutput);
+        end
+    else
+        for localIdx = 1:numel(batchJobs)
+            batchResults{localIdx} = processOneJob( ...
+                batchJobs(localIdx), recipeParams, debugPlots, storeDspOutput);
+        end
+    end
+
+    for localIdx = 1:numel(batchResults)
+        wh = writeResultToWarehouse(wh, batchResults{localIdx}, ...
+            storeDspOutput, powerLookup);
+    end
+
+    if mod(batchIdx, saveEveryBatches) == 0 || batchIdx == numBatches
+        save(outputFile, "wh", "recipeParams", "dataDir", "filePrefix", ...
+            "jobs", "storeDspOutput", "copyOriginalPowerMetadata", ...
+            "originalWarehouseFile", "-v7.3");
+        fprintf("Saved checkpoint to %s\n", outputFile);
+    end
+end
+
+fprintf("Saved reprocessed warehouse to %s\n", outputFile);
+wh.showInfo;
+
+%% Local helpers
+
+function jobs = buildJobList(dataDir, filePrefix, pamLevels, fsymGBd, ropAtten)
+jobs = struct( ...
+    "M", {}, ...
+    "fsym_GBd", {}, ...
+    "fsym", {}, ...
+    "rop_atten", {}, ...
+    "acquisition_idx", {}, ...
+    "bits_file", {}, ...
+    "symbols_file", {}, ...
+    "rx_file", {});
+
+for M = pamLevels
+    for fsymGb = fsymGBd
+        fsym = fsymGb .* 1e9;
+        bitsFile = fullfile(dataDir, sprintf("%sPAM_%d_fsym_%d_bits.mat", ...
+            filePrefix, M, fsymGb));
+        symbolsFile = fullfile(dataDir, sprintf("%sPAM_%d_fsym_%d_symbols.mat", ...
+            filePrefix, M, fsymGb));
+
+        if ~isfile(bitsFile) || ~isfile(symbolsFile)
+            warning("reprocess:MissingReference", ...
+                "Skipping PAM-%d %.0f GBd: missing bits or symbols file.", ...
+                M, fsymGb);
+            continue
+        end
+
+        for rop = ropAtten
+            rxFile = fullfile(dataDir, sprintf("%sPAM_%d_fsym_%d_rop_%s_rx_signal.mat", ...
+                filePrefix, M, fsymGb, ropToken(rop)));
+            if ~isfile(rxFile)
+                warning("reprocess:MissingRx", "Missing RX file: %s", rxFile);
+                continue
+            end
+
+            numAcquisitions = acquisitionCount(rxFile);
+            for acqIdx = 1:numAcquisitions
+                jobs(end+1) = struct( ... %#ok<AGROW>
+                    "M", M, ...
+                    "fsym_GBd", fsymGb, ...
+                    "fsym", fsym, ...
+                    "rop_atten", rop, ...
+                    "acquisition_idx", acqIdx, ...
+                    "bits_file", bitsFile, ...
+                    "symbols_file", symbolsFile, ...
+                    "rx_file", rxFile);
+            end
+        end
+    end
+end
+end
+
+function numAcq = acquisitionCount(rxFile)
+info = whos("-file", rxFile, "S");
+if isempty(info)
+    warning("reprocess:MissingS", "RX file has no variable S: %s", rxFile);
+    numAcq = 0;
+else
+    numAcq = prod(info.size);
+end
+end
+
+function result = processOneJob(job, recipeParams, debugPlots, storeDspOutput)
+result = emptyJobResult(job);
+try
+    bitsData = load(job.bits_file, "Bits");
+    symbolsData = load(job.symbols_file, "Symbols");
+    ScpeSigRaw = loadRxSignal(job.rx_file, job.acquisition_idx);
+    dataTable = makeRecipeDataTable(job);
+
+    fprintf("PAM-%d, %.0f GBd, ROP atten %.1f dB, S{%d}\n", ...
+        job.M, job.fsym_GBd, job.rop_atten, job.acquisition_idx);
+
+    dspOut = dsp_400g_recipe(ScpeSigRaw, symbolsData.Symbols, bitsData.Bits, ...
+        "fsym", job.fsym, ...
+        "M", job.M, ...
+        "duob_mode", db_mode.no_db, ...
+        "dataTable", dataTable, ...
+        "userParameters", recipeParams, ...
+        "debug_plots", debugPlots);
+
+    result.ber_ffe = extractBer(dspOut, "ffe_package", "BER");
+    result.ber_mlse = extractBer(dspOut, "mlse_package", "BER");
+    result.ber_db = extractBer(dspOut, "dbtgt_package", "BER");
+    result.ber_ffe_precoded = extractBer(dspOut, "ffe_package", "BER_precoded");
+    result.ber_mlse_precoded = extractBer(dspOut, "mlse_package", "BER_precoded");
+    result.ber_db_precoded = extractBer(dspOut, "dbtgt_package", "BER_precoded");
+    result.status = "ok";
+    if storeDspOutput
+        result.dsp_output = dspOut;
+    end
+catch err
+    result.status = "failed";
+    result.error_message = string(err.message);
+    warning("reprocess:DspFailed", ...
+        "DSP failed for PAM-%d %.0f GBd ROP %.1f dB S{%d}: %s", ...
+        job.M, job.fsym_GBd, job.rop_atten, job.acquisition_idx, err.message);
+end
+end
+
+function result = emptyJobResult(job)
+result = struct( ...
+    "M", job.M, ...
+    "fsym", job.fsym, ...
+    "fsym_GBd", job.fsym_GBd, ...
+    "rop_atten", job.rop_atten, ...
+    "acquisition_idx", job.acquisition_idx, ...
+    "rx_file", job.rx_file, ...
+    "ber_ffe", NaN, ...
+    "ber_mlse", NaN, ...
+    "ber_db", NaN, ...
+    "ber_ffe_precoded", NaN, ...
+    "ber_mlse_precoded", NaN, ...
+    "ber_db_precoded", NaN, ...
+    "status", "not_run", ...
+    "error_message", "", ...
+    "dsp_output", []);
+end
+
+function wh = writeResultToWarehouse(wh, result, storeDspOutput, powerLookup)
+idx = {result.fsym, result.rop_atten, result.M, result.acquisition_idx};
+[ropValue, pdInValue] = lookupOriginalPower(powerLookup, ...
+    result.fsym, result.rop_atten, result.M);
+
+wh.addValueToStorage(result.ber_ffe, "ber_ffe", idx{:});
+wh.addValueToStorage(result.ber_mlse, "ber_mlse", idx{:});
+wh.addValueToStorage(result.ber_db, "ber_db", idx{:});
+wh.addValueToStorage(result.ber_ffe_precoded, "ber_ffe_precoded", idx{:});
+wh.addValueToStorage(result.ber_mlse_precoded, "ber_mlse_precoded", idx{:});
+wh.addValueToStorage(result.ber_db_precoded, "ber_db_precoded", idx{:});
+wh.addValueToStorage(ropValue, "rop", idx{:});
+wh.addValueToStorage(pdInValue, "pd_in", idx{:});
+wh.addValueToStorage(char(result.rx_file), "rx_file", idx{:});
+wh.addValueToStorage(char(result.status), "status", idx{:});
+wh.addValueToStorage(char(result.error_message), "error_message", idx{:});
+if storeDspOutput
+    wh.addValueToStorage(result.dsp_output, "dsp_output", idx{:});
+end
+end
+
+function powerLookup = loadOriginalPowerLookup(originalWarehouseFile, enabled)
+powerLookup = struct("enabled", false, "data", table());
+if ~enabled
+    return
+end
+if ~isfile(originalWarehouseFile)
+    warning("reprocess:MissingOriginalWarehouse", ...
+        "Original warehouse not found, storing NaN for rop/pd_in: %s", ...
+        originalWarehouseFile);
+    return
+end
+
+loadedData = load(originalWarehouseFile);
+if isfield(loadedData, "wh")
+    originalWh = loadedData.wh;
+elseif isfield(loadedData, "obj")
+    originalWh = loadedData.obj;
+else
+    warning("reprocess:NoOriginalWarehouseObject", ...
+        "Original warehouse file contains neither wh nor obj: %s", ...
+        originalWarehouseFile);
+    return
+end
+
+requiredStorages = ["rop", "pd_in"];
+availableStorages = string(fieldnames(originalWh.sto));
+if ~all(ismember(requiredStorages, availableStorages))
+    warning("reprocess:MissingPowerStorage", ...
+        "Original warehouse has no complete rop/pd_in storage. Storing NaN.");
+    return
+end
+
+fsymVals = double(originalWh.parameter.fsym.values(:).');
+ropAttenVals = double(originalWh.parameter.rop_atten.values(:).');
+pamVals = double(originalWh.parameter.M.values(:).');
+rows = cell(numel(fsymVals) * numel(ropAttenVals) * numel(pamVals), 5);
+rowIdx = 0;
+
+for pamLevel = pamVals
+    for fsym = fsymVals
+        for ropAtten = ropAttenVals
+            rowIdx = rowIdx + 1;
+            rows(rowIdx, :) = { ...
+                fsym, ...
+                ropAtten, ...
+                pamLevel, ...
+                getOriginalScalar(originalWh, "rop", fsym, ropAtten, pamLevel), ...
+                getOriginalScalar(originalWh, "pd_in", fsym, ropAtten, pamLevel)};
+        end
+    end
+end
+
+powerLookup.enabled = true;
+powerLookup.data = cell2table(rows, 'VariableNames', ...
+    ["fsym", "rop_atten", "M", "rop", "pd_in"]);
+fprintf("Loaded %d original rop/pd_in metadata rows from %s\n", ...
+    height(powerLookup.data), originalWarehouseFile);
+end
+
+function value = getOriginalScalar(originalWh, storageName, fsym, ropAtten, pamLevel)
+value = NaN;
+try
+    rawValue = originalWh.getStoValue(storageName, fsym, ropAtten, pamLevel);
+catch
+    return
+end
+if isnumeric(rawValue) && isscalar(rawValue)
+    value = double(rawValue);
+end
+end
+
+function [ropValue, pdInValue] = lookupOriginalPower(powerLookup, fsym, ropAtten, pamLevel)
+ropValue = NaN;
+pdInValue = NaN;
+if ~powerLookup.enabled || isempty(powerLookup.data)
+    return
+end
+
+match = powerLookup.data.fsym == fsym & ...
+    powerLookup.data.rop_atten == ropAtten & ...
+    powerLookup.data.M == pamLevel;
+if ~any(match)
+    return
+end
+
+firstMatch = find(match, 1, "first");
+ropValue = powerLookup.data.rop(firstMatch);
+pdInValue = powerLookup.data.pd_in(firstMatch);
+end
+
+function sig = loadRxSignal(rxFile, acquisitionIdx)
+rxData = load(rxFile, "S");
+if ~iscell(rxData.S) || isempty(rxData.S)
+    error("RX file %s does not contain a nonempty cell array S.", rxFile);
+end
+if acquisitionIdx > numel(rxData.S)
+    error("Requested acquisition S{%d}, but %s only contains %d acquisitions.", ...
+        acquisitionIdx, rxFile, numel(rxData.S));
+end
+sig = rxData.S{acquisitionIdx};
+end
+
+function token = ropToken(rop)
+token = strrep(sprintf("%.1f", rop), ".", "_");
+token = regexprep(token, "_0$", "");
+end
+
+function dataTable = makeRecipeDataTable(job)
+dataTable = table();
+dataTable.run_id = makeRunId(job.M, job.fsym, job.rop_atten, job.acquisition_idx);
+dataTable.pam_level = job.M;
+dataTable.symbolrate = job.fsym;
+dataTable.bitrate = job.fsym .* log2(job.M);
+dataTable.grossrate = dataTable.bitrate;
+dataTable.fiber_length = 0;
+dataTable.wavelength = 1310;
+dataTable.rop_attenuation = job.rop_atten;
+dataTable.acquisition_idx = job.acquisition_idx;
+dataTable.rx_file = string(job.rx_file);
+end
+
+function runId = makeRunId(M, fsym, rop, acquisitionIdx)
+runId = M .* 1e10 + round(fsym .* 1e-6) .* 1e2 + ...
+    round(rop .* 10) .* 10 + acquisitionIdx;
+end
+
+function ber = extractBer(dspOut, packageName, metricName)
+ber = NaN;
+if ~isfield(dspOut, packageName)
+    return
+end
+pkg = dspOut.(packageName);
+if ~isfield(pkg, "metrics")
+    return
+end
+
+if isobject(pkg.metrics) && isprop(pkg.metrics, metricName)
+    ber = pkg.metrics.(metricName);
+elseif isstruct(pkg.metrics) && isfield(pkg.metrics, metricName)
+    ber = pkg.metrics.(metricName);
+end
+end
+
+function ok = ensureParallelPool()
+ok = false;
+try
+    pool = gcp("nocreate");
+    if ~isempty(pool) && contains(string(class(pool)), "ThreadPool")
+        delete(pool);
+        pool = [];
+    end
+    if isempty(pool)
+        pool = parpool("local");
+    end
+    ok = ~isempty(pool);
+catch err
+    warning("reprocess:NoParallelPool", ...
+        "Parallel pool unavailable, falling back to serial processing: %s", ...
+        err.message);
+end
+end

projects/Diss/400G_revisit/RX_sprectra.m

@@ -0,0 +1,97 @@
+
+
+
+% === 400G DSP settings ===
+dsp_options = struct();
+dsp_options.mode = "run_id";
+dsp_options.recipe = @dsp_400g_recipe;
+dsp_options.append_to_db = false;
+% dsp_options.append_mpi_reduction_db = false;
+dsp_options.start_occurence = 1;
+dsp_options.max_occurences = 3;
+dsp_options.debug_plots = false;
+
+
+
+dsp_options.database_type = "mysql";
+dsp_options.dataBase = "labor_highspeed";
+
+if ismac
+    dsp_options.storage_path = "/Volumes/media/labdata/sioe_labor";
+else
+    dsp_options.storage_path = "W:\labdata\sioe_labor";
+end
+dsp_options.server = "192.168.178.192";
+dsp_options.port = 3306;
+dsp_options.user = "silas";
+dsp_options.password = "silas";
+
+db = DBHandler("dataBase", [dsp_options.dataBase], ...
+    "type", dsp_options.database_type, ...
+    "server", dsp_options.server, ...
+    "user", dsp_options.user, ...
+    "password", dsp_options.password);
+
+%% Load normal Signal w/o preemphasis
+fp = QueryFilter();
+fp.where('Runs','fiber_length','EQUALS', 10);
+fp.where('Runs','wavelength','EQUALS', 1310);
+fp.where('Runs','bitrate','EQUALS', 420e9);
+fp.where('Runs','pam_level','EQUALS', 4);
+fp.where('Runs','rop_attenuation','EQUALS', 0);
+fp.where('Runs','is_mpi','EQUALS', 0);
+fp.where('Runs', 'db_mode','EQUALS', 0);
+
+fields = db.getTableFieldNames('Runs');
+[dataTable, query] = db.queryDB(fp, fields);
+
+[~, Symbols_preemph, Scpe_cell_preemph, ~] = loadAndSyncRunSignals(dataTable(1,:), dsp_options);
+ScopeSignal = Scpe_cell_preemph{1};
+ScopeSignal_preemph = preprocessSignal(ScopeSignal, Symbols_preemph, Symbols_preemph.fs);
+
+%% Load normal Signal w/o preemphasis
+fp = QueryFilter();
+fp.where('Runs','fiber_length','EQUALS', 10);
+fp.where('Runs','wavelength','EQUALS', 1310);
+fp.where('Runs','bitrate','EQUALS', 420e9);
+fp.where('Runs','pam_level','EQUALS', 4);
+fp.where('Runs','rop_attenuation','EQUALS', 0);
+fp.where('Runs','is_mpi','EQUALS', 0);
+fp.where('Runs', 'db_mode','EQUALS', 1);
+
+fields = db.getTableFieldNames('Runs');
+[dataTable, query] = db.queryDB(fp, fields);
+
+[~, Symbols, Scpe_cell, ~] = loadAndSyncRunSignals(dataTable(1,:), dsp_options);
+ScopeSignal = Scpe_cell{1};
+
+
+
+ScopeSignal_no_preemph = preprocessSignal(ScopeSignal, Symbols, Symbols.fs);
+
+
+
+%% Duobinary 
+fp = QueryFilter();
+fp.where('Runs','fiber_length','EQUALS', 10);
+fp.where('Runs','wavelength','EQUALS', 1310);
+fp.where('Runs','bitrate','EQUALS', 420e9);
+fp.where('Runs','pam_level','EQUALS', 4);
+fp.where('Runs','rop_attenuation','EQUALS', 0);
+fp.where('Runs','is_mpi','EQUALS', 0);
+fp.where('Runs', 'db_mode','EQUALS', 2);
+
+fields = db.getTableFieldNames('Runs');
+[dataTable, query] = db.queryDB(fp, fields);
+
+[~, Symbols_db, Scpe_cell_db, found_sync] = loadAndSyncRunSignals(dataTable(1,:), dsp_options);
+ScopeSignal = Scpe_cell_db{1};
+ScopeSignal_DB = preprocessSignal(ScopeSignal, Symbols_db, Symbols_db.fs);
+
+
+%%
+
+
+ScopeSignal_no_preemph.spectrum("displayname",'Full Response w/o preemphasis','fignum',2,'normalizeTo0dB',0,'color',clr.Paired.dblue);
+ScopeSignal_preemph.spectrum("displayname",'Full Response w/ preemphasis','fignum',2,'normalizeTo0dB',0,'color',clr.Paired.dgreen);
+ScopeSignal_DB.spectrum("displayname",'DB Response w/ preemphasis','fignum',2,'normalizeTo0dB',0,'color',clr.Paired.dorange);

projects/Diss/400G_revisit/TX_spectra.m

@@ -0,0 +1,115 @@
+
+rates = [420e9];
+rcalpha = 0.05;
+fsym = rates/2;
+apply_pulsef = 1;
+
+M = 4;
+
+
+%% Normal Tx Signal
+duob_mode = db_mode.no_db;
+
+Pform = Pulseformer("fsym",fsym,"fdac",4*fsym,"pulse","rrc","pulselength",16,"alpha",rcalpha);
+
+[Digi_sig,~,~] = PAMsource(...
+    "fsym",fsym,"M",M,"order",21,"useprbs",0,...
+    "fs_out",256e9,...
+    "applyclipping",0,"clipfactor",1.5,...
+    "applypulseform",apply_pulsef,"pulseformer",Pform,...
+    "randkey",1,...
+    'duobinary_mode',duob_mode,...
+    "mrds_code",0,"mrds_blocklength",512).process();
+Digi_sig= Digi_sig.normalize("mode","oneone");
+Digi_sig = Digi_sig-mean(Digi_sig.signal);
+
+
+maxamp = -28; %optimized for DB!
+precomp_est = ChannelFreqResp("Nacq",2048,"Navg",100,"Ncp",63,'f_ref',Digi_sig.fs);
+precomp_path = "W:\labdata\sioe_labor\precomp";
+precomp_fn = "lab_high_speed";
+Digi_sig_pre = precomp_est.precomp(Digi_sig,'maxampdb',maxamp,'loadPath',precomp_path,'fileName',precomp_fn);
+Digi_sig_pre.signal = reshape(Digi_sig_pre.signal,[],1);
+Digi_sig_pre = Digi_sig_pre.resample("fs_out",256e9);
+Digi_sig_pre= Digi_sig_pre.normalize("mode","oneone");
+Digi_sig_pre = Digi_sig_pre-mean(Digi_sig_pre.signal);
+
+
+
+% precomp_est.plot
+Digi_sig_rx = precomp_est.apply(...
+    Digi_sig,'maxampdb',0,'loadPath',precomp_path,'fileName',precomp_fn);
+
+Digi_sig_pre_rx = precomp_est.apply(...
+    Digi_sig_pre,'maxampdb',0,'loadPath',precomp_path,'fileName',precomp_fn);
+
+Digi_sig.spectrum(...
+    "displayname",'Tx w/o pre-emphasis',...
+    "fignum",2,"normalizeTo0dB",0,"color",[0,0,0]);
+Digi_sig_pre.spectrum(...
+    "displayname",'Tx w/ pre-emphasis',...
+    "fignum",2,"normalizeTo0dB",0,"color",clr.Paired.lblue);
+
+Digi_sig_rx.spectrum(...
+    "displayname",'Rx w/o pre-emphasis',...
+    "fignum",2,"normalizeTo0dB",0,"color",clr.Paired.dred);
+
+
+
+
+
+Digi_sig_pre_rx.spectrum(...
+    "displayname",'Rx w/ pre-emphasis',...
+    "fignum",2,"normalizeTo0dB",0,"color",clr.Paired.dblue);
+
+
+
+
+%% Duobinary Encoded Tx Signal
+duob_mode = db_mode.db_encoded;
+
+Pform = Pulseformer("fsym",fsym,"fdac",4*fsym,"pulse","rrc","pulselength",16,"alpha",rcalpha);
+
+[Digi_sig_DB,Symbols,Tx_bits] = PAMsource(...
+    "fsym",fsym,"M",M,"order",21,"useprbs",0,...
+    "fs_out",256e9,...
+    "applyclipping",0,"clipfactor",1.5,...
+    "applypulseform",apply_pulsef,"pulseformer",Pform,...
+    "randkey",1,...
+    'duobinary_mode',duob_mode,...
+    "mrds_code",0,"mrds_blocklength",512).process();
+Digi_sig_DB= Digi_sig_DB.normalize("mode","oneone");
+
+maxamp = -38; %optimized for DB!
+precomp_est = ChannelFreqResp("Nacq",2048,"Navg",100,"Ncp",63,'f_ref',Digi_sig_DB.fs);
+precomp_path = "W:\labdata\sioe_labor\precomp";
+precomp_fn = "lab_high_speed";
+Digi_sig_DB_pre = precomp_est.precomp(Digi_sig_DB,'maxampdb',maxamp,'loadPath',precomp_path,'fileName',precomp_fn);
+Digi_sig_DB_pre.signal = reshape(Digi_sig_DB_pre.signal,[],1);
+Digi_sig_DB_pre = Digi_sig_DB_pre.resample("fs_out",256e9);
+Digi_sig_DB_pre = Digi_sig_DB_pre.normalize("mode","oneone");
+
+%% 
+
+AWG_ = M8199B("kover",4);
+% AWG_ = AWG("fdac",256e9,"f_cutoff",fsym,"lpf_active",0,"kover",4,"bit_resolution",12,"upsampling_method","samplehold","precomp_sinc_rolloff",1);
+
+
+
+El_sig = AWG_.process(Digi_sig);
+El_sig_preemph = AWG_.process(Digi_sig_pre);
+El_sig_channel = AWG_.process(Digi_sig_channel);
+
+
+
+El_sig.spectrum("displayname",'Full Response w/o preemphasis','fignum',1,'normalizeTo0dB',0,'color',clr.Paired.lblue);
+El_sig_preemph.spectrum("displayname",'Full Response w/ preemphasis','fignum',1,'normalizeTo0dB',0,'color',clr.Paired.dblue);
+El_sig_channel.spectrum("displayname",'Full Response w/ measured channel','fignum',1,'normalizeTo0dB',0,'color',clr.Paired.blue);
+
+
+El_sig_DB_preemph = AWG_.process(Digi_sig_DB_pre);
+El_sig_DB = AWG_.process(Digi_sig_DB);
+
+
+El_sig_DB.spectrum("displayname",'DB Response  w/o preemphasis','fignum',1,'normalizeTo0dB',0,'color',clr.Paired.lorange);
+El_sig_DB_preemph.spectrum("displayname",'DB Response  w/ preemphasis','fignum',1,'normalizeTo0dB',0,'color',clr.Paired.dorange);

projects/Diss/400G_revisit/investigate_400g_algorithms.m

@@ -5,9 +5,11 @@ dsp_options.recipe = @dsp_400g_recipe;
 dsp_options.append_to_db = false;
 % dsp_options.append_mpi_reduction_db = false;
 dsp_options.start_occurence = 1;
-dsp_options.max_occurences = 1;
+dsp_options.max_occurences = 3;
 dsp_options.debug_plots = false;
 
+
+
 dsp_options.database_type = "mysql";
 dsp_options.dataBase = "labor_highspeed";
 
@@ -34,15 +36,15 @@ maxRunIds = 1;                   % keep small until the recipe settings are sett
 fp = QueryFilter();
 fp.where('Runs','fiber_length','EQUALS', 10);
 fp.where('Runs','wavelength','EQUALS', 1310);
-fp.where('Runs','bitrate','EQUALS', 330e9);
+% fp.where('Runs','bitrate','LESS_THAN', 480e9);
-fp.where('Runs','pam_level','EQUALS', 4);
+% fp.where('Runs','pam_level','EQUALS', 4);
 fp.where('Runs','rop_attenuation','EQUALS', 0);
 fp.where('Runs','is_mpi','EQUALS', 0);
-fp.where('Runs', 'db_mode','EQUALS', 2);
+% fp.where('Runs', 'db_mode','EQUALS', 2);
 
 fields = db.getTableFieldNames('Runs');
 [dataTable, query] = db.queryDB(fp, fields);
-disp(query);
+% disp(query);
 
 dataTable = sortrows(dataTable, {'bitrate', 'run_id'});
 
@@ -60,21 +62,12 @@ fprintf("Selected %d run_id(s): %s\n", numel(run_ids), mat2str(run_ids));
 %% Parameter sweep
 
 dsp_options.userParameters = struct();
-dsp_options.userParameters.run_ml_mlse_db = true;
-dsp_options.userParameters.run_mlse_db = true;
-
-% Enable/disable equalizer branches.
-% dsp_options.userParameters.run_ffe = false;
-% dsp_options.userParameters.run_vnle = false;
-% dsp_options.userParameters.run_dfe = false;
-% dsp_options.userParameters.run_vnle_mlse = true;
-% dsp_options.userParameters.run_dbtgt = true;
 
 % Examples for parameter loops. DataStorage expands every vector-valued field.
 % dsp_options.userParameters.len_tr = 4096*2;
-% dsp_options.userParameters.pf_ncoeffs = 1;
+% dsp_options.userParameters.pf_ncoeffs = [1,2,3];
 
-% dsp_options.userParameters.decoding_mode = [db_decoder.memoryless,db_decoder.sequencedetection];
+dsp_options.userParameters.decoding_mode = [db_decoder.sequencedetection];
 % dsp_options.userParameters.pf_ncoeffs = [1, 2, 3];
 % dsp_options.userParameters.mu_dc = [0, 1e-5, 1e-4];
 % dsp_options.userParameters.run_ml_mlse_db = [false, true];
@@ -93,7 +86,7 @@ fprintf("-> [ %d run_id(s) x %d userParam combination(s) = %d job(s) ] x %d real
 
 %% Run
 
-[results, wh] = submitJobs(run_ids, dsp_options, processingMode.serial, ...
+[results, wh] = submitJobs(run_ids, dsp_options, processingMode.parallel, ...
     "wh", wh, ...
     "waitbar", true);
 
@@ -102,6 +95,7 @@ fprintf("-> [ %d run_id(s) x %d userParam combination(s) = %d job(s) ] x %d real
 
 printBerSummary(wh);
 plotBerVsBitrateQuick(wh, dataTable);
+plotMlseBerPrecodedVsBitrateByPf(wh, dataTable);
 
 function printBerSummary(wh)
 storageNames = fieldnames(wh.sto);
@@ -182,7 +176,7 @@ for storageIdx = 1:numel(storageNames)
             end
 
             modeData = sortrows(plotData(rowMask, :), "bitrate_Gbps");
-            summaryData = groupsummary(modeData, "bitrate_Gbps", "median", "BER");
+            summaryData = groupsummary(modeData, "bitrate_Gbps", "min", "BER");
             summaryData = sortrows(summaryData, "bitrate_Gbps");
             color = quickPlotColor(modeIdx);
             marker = markers(1 + mod(storageIdx - 1, numel(markers)));
@@ -196,7 +190,7 @@ for storageIdx = 1:numel(storageNames)
                 "MarkerEdgeAlpha", 0.25, ...
                 "HandleVisibility", "off");
 
-            plot(ax, summaryData.bitrate_Gbps, summaryData.median_BER, ...
+            plot(ax, summaryData.bitrate_Gbps, summaryData.min_BER, ...
                 "LineStyle", lineStyles(metricIdx), ...
                 "Marker", marker, ...
                 "MarkerSize", 5, ...
@@ -279,6 +273,108 @@ if ~isempty(plotData)
 end
 end
 
+function plotMlseBerPrecodedVsBitrateByPf(wh, dataTable)
+storageName = "mlse_package";
+if ~isfield(wh.sto, storageName)
+    fprintf("No %s storage available for BERp plot.\n", storageName);
+    return
+end
+
+runIds = dataTable.run_id(:);
+bitrates = dataTable.bitrate(:);
+pfCol = zeros(0, 1);
+bitrateCol = zeros(0, 1);
+berpCol = zeros(0, 1);
+
+storageValues = wh.sto.(storageName);
+for linIdx = 1:numel(storageValues)
+    [phys, storedValue] = wh.getPhysAndValueByLinIndex(storageName, linIdx);
+    if ~isfield(phys, "pf_ncoeffs")
+        continue
+    end
+
+    berp = extractMinMetricValue(storedValue, "BER_precoded");
+    if ~isfinite(berp) || berp <= 0
+        continue
+    end
+
+    runId = resolveRunId(phys, runIds);
+    bitrate = resolveBitrate(runId, runIds, bitrates);
+    if ~isfinite(bitrate)
+        continue
+    end
+
+    pfCol(end+1, 1) = double(phys.pf_ncoeffs); %#ok<AGROW>
+    bitrateCol(end+1, 1) = double(bitrate) * 1e-9; %#ok<AGROW>
+    berpCol(end+1, 1) = double(berp); %#ok<AGROW>
+end
+
+if isempty(berpCol)
+    fprintf("No BERp values available for %s.\n", storageName);
+    return
+end
+
+plotData = table(pfCol, bitrateCol, berpCol, ...
+    'VariableNames', ["pf_ncoeffs", "bitrate_Gbps", "BERp"]);
+summaryData = groupsummary(plotData, ["pf_ncoeffs", "bitrate_Gbps"], ...
+    "min", "BERp");
+
+fig = figure(403); clf;
+ax = axes(fig); hold(ax, "on");
+pfValues = [1, 2, 3];
+markers = ["o", "square", "diamond"];
+colors = lines(numel(pfValues));
+
+for pfIdx = 1:numel(pfValues)
+    pfValue = pfValues(pfIdx);
+    rowMask = summaryData.pf_ncoeffs == pfValue;
+    if ~any(rowMask)
+        continue
+    end
+
+    curveData = sortrows(summaryData(rowMask, :), "bitrate_Gbps");
+    plot(ax, curveData.bitrate_Gbps, curveData.min_BERp, ...
+        "LineWidth", 1.3, ...
+        "Marker", markers(pfIdx), ...
+        "MarkerSize", 5, ...
+        "Color", colors(pfIdx, :), ...
+        "DisplayName", sprintf("pf\\_ncoeffs = %d", pfValue));
+end
+
+xlabel(ax, "Bitrate [Gb/s]");
+ylabel(ax, "min BERp");
+title(ax, "MLSE BERp vs bitrate");
+set(ax, "YScale", "log");
+grid(ax, "on");
+box(ax, "on");
+legend(ax, "Location", "best", "Interpreter", "none");
+set(fig, "Position", [1200, 450, 560, 360]);
+end
+
+function minValue = extractMinMetricValue(value, metricName)
+minValue = NaN;
+if isempty(value)
+    return
+end
+if ~iscell(value)
+    value = {value};
+end
+
+metricValues = NaN(1, numel(value));
+for packageIdx = 1:numel(value)
+    package = value{packageIdx};
+    if ~isstruct(package) || ~isfield(package, "metrics")
+        continue
+    end
+    metricValues(packageIdx) = readMetricValue(package.metrics, metricName);
+end
+
+metricValues = metricValues(isfinite(metricValues) & metricValues > 0);
+if ~isempty(metricValues)
+    minValue = min(metricValues);
+end
+end
+
 function metricRows = extractBerMetricRows(values)
 metricNames = strings(0, 1);
 berValues = zeros(0, 1);

projects/Lab_oband_laser_and_amp_analysis/amplifier_gain_analysis.m

@@ -0,0 +1,274 @@
+%AMPLIFIER_GAIN_ANALYSIS Compare the Aeon SOA and Thorlabs PDFA gain.
+%
+% The first figure shows gain versus wavelength for the pump levels that
+% are available in the wavelength-sweep warehouses. The second figure
+% shows gain versus pump level at -10 dBm input power and 1310 nm. The
+% third and fourth figures show output power and OSNR versus wavelength.
+% The fifth figure estimates the optical noise figure from the ASE level.
+%
+% The 2 dB setup correction follows amplifier_input_output_curve.m:
+%   gain = Pout - (Pin - 2 dB) = Pout - Pin + 2 dB.
+
+scriptDir = fileparts(mfilename("fullpath"));
+repoDir = fileparts(fileparts(scriptDir));
+warehouseClassDir = fullfile(repoDir, "Classes", "Warehouse_class", "classes");
+if ~contains(string(path), warehouseClassDir)
+    addpath(warehouseClassDir);
+end
+
+inputPowerDb = -10;
+inputPowerCorrectionDb = 2;
+correctedInputPowerDb = inputPowerDb - inputPowerCorrectionDb;
+wavelengthForPumpSweepNm = 1310;
+osaResolutionNm = 0.1;
+
+% Wavelength-dependent measurements: pump values are 50, 75, and 100 %.
+lambdaSweepAeon = load(fullfile(scriptDir, "aeon_soa_measurement_lambda_plaser_pump.mat"), "wh");
+lambdaSweepThorlabs = load(fullfile(scriptDir, "thorlabs_pdfa_measurement_lambda_plaser_pump.mat"), "wh");
+whAeonLambda = lambdaSweepAeon.wh;
+whThorlabsLambda = lambdaSweepThorlabs.wh;
+
+% Pump-level measurements: pump values are available from 0 to 100 % in 5 % steps.
+pumpSweepAeon = load(fullfile(scriptDir, "aeon_soa_measurement_pump_level_sweep.mat"), "wh");
+pumpSweepThorlabs = load(fullfile(scriptDir, "thorlabs_pdfa_measurement_pump_level_sweep.mat"), "wh");
+whAeonPump = pumpSweepAeon.wh;
+whThorlabsPump = pumpSweepThorlabs.wh;
+
+if ~ismember(inputPowerDb, whAeonLambda.parameter.laserpower.values)
+    error("Input power %g dBm is not present in the wavelength-sweep warehouse.", inputPowerDb);
+end
+if ~ismember(wavelengthForPumpSweepNm, whAeonPump.parameter.lambda.values)
+    error("Wavelength %g nm is not present in the pump-sweep warehouse.", wavelengthForPumpSweepNm);
+end
+
+% The warehouse uses physical values as query arguments. Vector queries
+% return one row per requested physical value.
+wavelengthsNm = whAeonLambda.parameter.lambda.values;
+pumpLevelsLambda = whAeonLambda.parameter.pump.values;
+pumpLevelsSweep = whAeonPump.parameter.pump.values;
+
+%% Gain versus wavelength
+
+figure("Name", "Amplifier gain versus wavelength", "Color", "w");
+tiledlayout(1, 2, "TileSpacing", "compact", "Padding", "compact");
+
+lambdaWarehouses = {whAeonLambda, whThorlabsLambda};
+amplifierNames = ["Aeon SOA", "Thorlabs PDFA"];
+
+for amplifierIndex = 1:numel(lambdaWarehouses)
+    nexttile;
+    hold on;
+    colors = lines(numel(pumpLevelsLambda));
+    wh = lambdaWarehouses{amplifierIndex};
+
+    for pumpIndex = 1:numel(pumpLevelsLambda)
+        pumpLevel = pumpLevelsLambda(pumpIndex);
+
+        signalOutputDb = wh.getStoValue("psig_osa", inputPowerDb, wavelengthsNm, pumpLevel);
+        totalOutputDb = wh.getStoValue("psig_total", inputPowerDb, wavelengthsNm, pumpLevel);
+
+        signalGainDb = signalOutputDb - correctedInputPowerDb;
+        totalGainDb = totalOutputDb - correctedInputPowerDb;
+
+        plot(wavelengthsNm, signalGainDb, "-", "Color", colors(pumpIndex, :), ...
+            "LineWidth", 1.5, ...
+            "DisplayName", sprintf("Pump %g%%: signal", pumpLevel));
+        plot(wavelengthsNm, totalGainDb, "--", "Color", colors(pumpIndex, :), ...
+            "LineWidth", 1.2, ...
+            "DisplayName", sprintf("Pump %g%%: total", pumpLevel));
+    end
+
+    title(amplifierNames(amplifierIndex), "Interpreter", "none");
+    xlabel("Wavelength [nm]", "Interpreter", "none");
+    ylabel("Gain [dB]", "Interpreter", "none");
+    grid on;
+    box on;
+    legend("Location", "best", "Interpreter", "none");
+end
+
+sgtitle(sprintf("Gain versus wavelength at P_{in} = %g dBm (2 dB setup correction)", inputPowerDb), ...
+    "Interpreter", "tex");
+
+%% Gain versus pump level at -10 dBm input power
+
+figure("Name", "Amplifier gain versus pump level", "Color", "w");
+hold on;
+colors = lines(numel(lambdaWarehouses));
+pumpWarehouses = {whAeonPump, whThorlabsPump};
+
+for amplifierIndex = 1:numel(pumpWarehouses)
+    wh = pumpWarehouses{amplifierIndex};
+
+    signalOutputDb = wh.getStoValue("psig_osa", inputPowerDb, wavelengthForPumpSweepNm, pumpLevelsSweep);
+    totalOutputDb = wh.getStoValue("psig_total", inputPowerDb, wavelengthForPumpSweepNm, pumpLevelsSweep);
+
+    signalGainDb = signalOutputDb - correctedInputPowerDb;
+    totalGainDb = totalOutputDb - correctedInputPowerDb;
+
+    plot(pumpLevelsSweep, signalGainDb, "-", "Color", colors(amplifierIndex, :), ...
+        "LineWidth", 1.6, ...
+        "DisplayName", amplifierNames(amplifierIndex) + " - signal");
+    plot(pumpLevelsSweep, totalGainDb, "--", "Color", colors(amplifierIndex, :), ...
+        "LineWidth", 1.3, ...
+        "DisplayName", amplifierNames(amplifierIndex) + " - total");
+end
+
+title(sprintf("Gain versus pump level at P_{in} = %g dBm, %g nm", ...
+    inputPowerDb, wavelengthForPumpSweepNm), "Interpreter", "tex");
+xlabel("Pump level [percent]", "Interpreter", "none");
+ylabel("Gain [dB]", "Interpreter", "none");
+grid on;
+box on;
+legend("Location", "best", "Interpreter", "none");
+
+%% Output power versus wavelength
+
+figure("Name", "Amplifier output power versus wavelength", "Color", "w");
+tiledlayout(1, 2, "TileSpacing", "compact", "Padding", "compact");
+
+for amplifierIndex = 1:numel(lambdaWarehouses)
+    nexttile;
+    hold on;
+    colors = lines(numel(pumpLevelsLambda));
+    wh = lambdaWarehouses{amplifierIndex};
+    legendHandles = gobjects(numel(pumpLevelsLambda), 1);
+
+    for pumpIndex = 1:numel(pumpLevelsLambda)
+        pumpLevel = pumpLevelsLambda(pumpIndex);
+
+        signalOutputDb = wh.getStoValue("psig_osa", inputPowerDb, wavelengthsNm, pumpLevel);
+        totalOutputDb = wh.getStoValue("psig_total", inputPowerDb, wavelengthsNm, pumpLevel);
+
+        plot(wavelengthsNm, signalOutputDb, "-", "Color", colors(pumpIndex, :), ...
+            "LineWidth", 1.5, ...
+            "DisplayName", sprintf("Pump %g%%: signal", pumpLevel));
+        plot(wavelengthsNm, totalOutputDb, "--", "Color", colors(pumpIndex, :), ...
+            "LineWidth", 1.2, ...
+            "DisplayName", sprintf("Pump %g%%: total", pumpLevel));
+    end
+
+    title(amplifierNames(amplifierIndex), "Interpreter", "none");
+    xlabel("Wavelength [nm]", "Interpreter", "none");
+    ylabel("P_{out} [dBm]", "Interpreter", "tex");
+    grid on;
+    box on;
+    legend("Location", "best", "Interpreter", "none");
+end
+
+sgtitle(sprintf("Output power versus wavelength at P_{in} = %g dBm", inputPowerDb), ...
+    "Interpreter", "tex");
+
+%% OSNR versus wavelength
+
+figure("Name", "Amplifier OSNR versus wavelength", "Color", "w");
+tiledlayout(1, 2, "TileSpacing", "compact", "Padding", "compact");
+
+for amplifierIndex = 1:numel(lambdaWarehouses)
+    nexttile;
+    hold on;
+    colors = lines(numel(pumpLevelsLambda));
+    wh = lambdaWarehouses{amplifierIndex};
+
+    for pumpIndex = 1:numel(pumpLevelsLambda)
+        pumpLevel = pumpLevelsLambda(pumpIndex);
+
+        % osnr_osa is calculated from spectrum_osa during measurement.
+        osnrResults = wh.getStoValue("osnr_osa", inputPowerDb, wavelengthsNm, pumpLevel);
+        osnrDb = cellfun(@(result) result.corrected_dB, osnrResults);
+
+        plot(wavelengthsNm, osnrDb, "-", "Color", colors(pumpIndex, :), ...
+            "LineWidth", 1.5, ...
+            "DisplayName", sprintf("Pump %g%%", pumpLevel));
+    end
+
+    title(amplifierNames(amplifierIndex), "Interpreter", "none");
+    xlabel("Wavelength [nm]", "Interpreter", "none");
+    ylabel("OSNR [dB]", "Interpreter", "none");
+    grid on;
+    box on;
+    legend("Location", "best", "Interpreter", "none");
+end
+
+sgtitle(sprintf("OSNR versus wavelength at P_{in} = %g dBm", inputPowerDb), ...
+    "Interpreter", "tex");
+
+%% Noise figure versus wavelength
+
+% The stored pase_osa values are OSA power readings per resolution
+% bandwidth. The measurement script configured the OSA to 0.1 nm.
+hPlanck = 6.62607015e-34;
+speedOfLight = 299792458;
+lambdaMeters = wavelengthsNm(:) .* 1e-9;
+opticalFrequencyHz = speedOfLight ./ lambdaMeters;
+opticalNoiseBandwidthHz = speedOfLight ./ lambdaMeters.^2 .* (osaResolutionNm * 1e-9);
+quantumNoisePowerW = hPlanck .* opticalFrequencyHz .* opticalNoiseBandwidthHz;
+
+figure("Name", "Amplifier noise figure versus wavelength", "Color", "w");
+tiledlayout(1, 2, "TileSpacing", "compact", "Padding", "compact");
+
+for amplifierIndex = 1:numel(lambdaWarehouses)
+    nexttile;
+    hold on;
+    colors = lines(numel(pumpLevelsLambda));
+    wh = lambdaWarehouses{amplifierIndex};
+
+    for pumpIndex = 1:numel(pumpLevelsLambda)
+        pumpLevel = pumpLevelsLambda(pumpIndex);
+
+        signalOutputDb = wh.getStoValue("psig_osa", inputPowerDb, wavelengthsNm, pumpLevel);
+        aseOutputDb = wh.getStoValue("pase_osa", inputPowerDb, wavelengthsNm, pumpLevel);
+
+        gainDb = signalOutputDb - correctedInputPowerDb;
+        linearGain = 10.^(gainDb ./ 10);
+        asePowerW = 10.^((aseOutputDb - 30) ./ 10);
+
+        % Exact estimate including the amplified input shot-noise term.
+        noiseFactor = 1 ./ linearGain + ...
+            asePowerW ./ (linearGain .* quantumNoisePowerW);
+        noiseFigureDb = 10 .* log10(noiseFactor);
+
+        legendHandles(pumpIndex) = plot(wavelengthsNm(:), noiseFigureDb, "-", ...
+            "Color", colors(pumpIndex, :), ...
+            "LineWidth", 1.5, ...
+            "DisplayName", sprintf("Pump %g%%", pumpLevel));
+    end
+
+    title(amplifierNames(amplifierIndex), "Interpreter", "none");
+    xlabel("Wavelength [nm]", "Interpreter", "none");
+    ylabel("Noise figure [dB]", "Interpreter", "none");
+    grid on;
+    box on;
+    legend(legendHandles, "Location", "best", "Interpreter", "none");
+end
+
+sgtitle(sprintf("Estimated noise figure versus wavelength at P_{in} = %g dBm", inputPowerDb), ...
+    "Interpreter", "tex");
+
+%% Final figure: Thorlabs gain versus wavelength
+
+figure("Name", "Thorlabs PDFA gain versus wavelength", "Color", "w");
+hold on;
+colors = lines(numel(pumpLevelsLambda));
+gainHandles = gobjects(numel(pumpLevelsLambda), 1);
+
+for pumpIndex = 1:numel(pumpLevelsLambda)
+    pumpLevel = pumpLevelsLambda(pumpIndex);
+
+    signalOutputDb = whThorlabsLambda.getStoValue( ...
+        "psig_osa", inputPowerDb, wavelengthsNm, pumpLevel);
+
+    gainDb = signalOutputDb - correctedInputPowerDb;
+
+    gainHandles(pumpIndex) = plot(wavelengthsNm, gainDb, "-", ...
+        "Color", colors(pumpIndex, :), ...
+        "LineWidth", 1.6, ...
+        "DisplayName", sprintf("Pump %g%%: gain", pumpLevel));
+end
+
+title(sprintf("Thorlabs PDFA: gain versus wavelength at P_{in} = %g dBm", ...
+    inputPowerDb), "Interpreter", "tex");
+xlabel("Wavelength [nm]", "Interpreter", "none");
+ylabel("Gain [dB]", "Interpreter", "none");
+grid on;
+box on;
+legend(gainHandles, "Location", "best", "Interpreter", "none");

projects/Lab_oband_laser_and_amp_analysis/available_output_power_vs_wavelength.m

@@ -0,0 +1,87 @@
+%AVAILABLE_OUTPUT_POWER_VS_WAVELENGTH Plot achieved laser output power.
+%
+% laser_outputpower_sweep_2_many_averages.mat contains the requested
+% wavelength and laser-power values. The corresponding 20-trace
+% measurements are stored in the local FIG file and are averaged here.
+
+scriptDir = fileparts(mfilename("fullpath"));
+
+parameterData = load(fullfile(scriptDir, "laser_outputpower_sweep_2_many_averages.mat"));
+laserparams = parameterData.laserparams;
+averagesPerSetpoint = 20;
+
+measurementFigure = openfig( ...
+    fullfile(scriptDir, "available_output_power_exfo_t100_oband_20_averages.fig"), ...
+    "invisible");
+measurementAxes = findall(measurementFigure, "Type", "axes");
+measurementLines = findall(measurementAxes, "Type", "line");
+
+numberOfSetpoints = numel(laserparams.laserpower);
+numberOfWavelengths = numel(laserparams.lambda);
+expectedLineCount = numberOfSetpoints * averagesPerSetpoint;
+if numel(measurementLines) ~= expectedLineCount
+    close(measurementFigure);
+    error("Expected %d measurement traces, found %d.", ...
+        expectedLineCount, numel(measurementLines));
+end
+
+measuredLambda = measurementLines(1).XData(:).';
+if numel(measuredLambda) ~= numberOfWavelengths || ...
+        any(abs(measuredLambda - laserparams.lambda) > 1e-9)
+    close(measurementFigure);
+    error("Measurement wavelengths do not match laserparams.lambda.");
+end
+
+achievedPowerDbm = zeros(numberOfSetpoints, numberOfWavelengths);
+for setpointIndex = 1:numberOfSetpoints
+    firstLine = (setpointIndex - 1) * averagesPerSetpoint + 1;
+    traces = zeros(averagesPerSetpoint, numberOfWavelengths);
+
+    for averageIndex = 1:averagesPerSetpoint
+        trace = measurementLines(firstLine + averageIndex - 1).YData(:).';
+        traces(averageIndex, :) = trace;
+    end
+
+    achievedPowerDbm(setpointIndex, :) = mean(traces, 1, "omitnan");
+end
+close(measurementFigure);
+
+% The measurement traces are stored in descending output-power order.
+% Sort them so they match the ascending laserparams.laserpower order.
+[~, sortIndex] = sort(mean(achievedPowerDbm, 2, "omitnan"));
+achievedPowerDbm = achievedPowerDbm(sortIndex, :);
+
+figure("Name", "Available laser output power", "Color", "w");
+hold on;
+colors = lines(numberOfSetpoints);
+annotationX = laserparams.lambda(end) - 1;
+
+for setpointIndex = 1:numberOfSetpoints
+    yline(laserparams.laserpower(setpointIndex), ":", ...
+        "Color", [0.65 0.65 0.65], "HandleVisibility", "off");
+    plot(laserparams.lambda, achievedPowerDbm(setpointIndex, :), "-", ...
+        "Color", colors(setpointIndex, :), "LineWidth", 1.6, ...
+        "DisplayName", sprintf("Target %g dBm: measured", ...
+        laserparams.laserpower(setpointIndex)));
+    text(annotationX, laserparams.laserpower(setpointIndex), ...
+        sprintf("P_{set} = %g dBm", laserparams.laserpower(setpointIndex)), ...
+        "Color", colors(setpointIndex, :), "Interpreter", "tex", ...
+        "HorizontalAlignment", "right", "VerticalAlignment", "bottom", ...
+        "HandleVisibility", "off");
+end
+
+title("Available laser output power versus wavelength", "Interpreter", "none");
+xlabel("Wavelength [nm]", "Interpreter", "none");
+ylabel("Achieved output power [dBm]", "Interpreter", "none");
+grid on;
+box on;
+legend("Location", "northwest", "Interpreter", "none");
+
+% Export the same figure with the repository-local matlab2tikz version.
+repoDir = fileparts(fileparts(scriptDir));
+addpath(fullfile(repoDir, "Libs", "mat2tikz", "src"));
+tikzOutputFile = fullfile(scriptDir, "available_output_power_vs_wavelength.tikz");
+matlab2tikz(char(tikzOutputFile), ...
+    'showInfo', false, ...
+    'showHiddenStrings', true, ...
+    'extraAxisOptions', {'legend style={font=\footnotesize}'});

projects/Lab_oband_laser_and_amp_analysis/available_output_power_vs_wavelength.tikz

@@ -0,0 +1,350 @@
+% This file was created by matlab2tikz.
+%
+\definecolor{mycolor1}{rgb}{0.89412,0.10196,0.10980}%
+\definecolor{mycolor2}{rgb}{0.21569,0.49412,0.72157}%
+\definecolor{mycolor3}{rgb}{0.30196,0.68627,0.29020}%
+\definecolor{mycolor4}{rgb}{0.59608,0.30588,0.63922}%
+\definecolor{mycolor5}{rgb}{1.00000,0.49804,0.00000}%
+\definecolor{mycolor6}{rgb}{0.12941,0.12941,0.12941}%
+%
+\begin{tikzpicture}
+
+\begin{axis}[%
+width=6.458in,
+height=5.094in,
+at={(1.083in,0.688in)},
+scale only axis,
+xmin=1260,
+xmax=1360,
+xlabel style={font=\color{mycolor6}},
+xlabel={Wavelength [nm]},
+ymin=-2,
+ymax=12,
+ylabel style={font=\color{mycolor6}},
+ylabel={Achieved output power [dBm]},
+axis background/.style={fill=white},
+title style={font=\bfseries\color{mycolor6}},
+title={Available laser output power versus wavelength},
+xmajorgrids,
+ymajorgrids,
+grid style={dashed},
+legend style={at={(0.03,0.97)}, anchor=north west, legend cell align=left, align=left},
+legend style={font=\footnotesize}
+]
+\addplot [color=white!65!black, dotted, forget plot]
+  table[row sep=crcr]{%
+1260	0\\
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+};
+\addplot [color=mycolor1, line width=1.6pt]
+  table[row sep=crcr]{%
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+\addlegendentry{Target 0 dBm: measured}
+
+\node[above left, align=right, inner sep=0, font=\color{mycolor1}]
+at (axis cs:1359,0) {$\text{P}_{\text{set}}\text{ = 0 dBm}$};
+\addplot [color=white!65!black, dotted, forget plot]
+  table[row sep=crcr]{%
+1260	3\\
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+\addplot [color=mycolor2, line width=1.6pt]
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+1350	3.0701560325\\
+1352	3.1103352335\\
+1354	3.148218037\\
+1356	3.137503138\\
+1358	3.1635465145\\
+1360	3.1890315515\\
+};
+\addlegendentry{Target 3 dBm: measured}
+
+\node[above left, align=right, inner sep=0, font=\color{mycolor2}]
+at (axis cs:1359,3) {$\text{P}_{\text{set}}\text{ = 3 dBm}$};
+\addplot [color=white!65!black, dotted, forget plot]
+  table[row sep=crcr]{%
+1260	6\\
+1360	6\\
+};
+\addplot [color=mycolor3, line width=1.6pt]
+  table[row sep=crcr]{%
+1260	5.987181772\\
+1262	6.01080855\\
+1264	6.0196549575\\
+1266	6.0658400605\\
+1268	6.0468314485\\
+1270	6.0572872865\\
+1272	6.0622857945\\
+1274	6.0605621715\\
+1276	6.056511485\\
+1278	6.075664353\\
+1280	6.0551906125\\
+1282	6.0599489405\\
+1284	6.0755984025\\
+1286	6.0270936715\\
+1288	6.0354817275\\
+1290	6.022740339\\
+1292	6.002313234\\
+1294	5.980794718\\
+1296	5.976163088\\
+1298	5.950657563\\
+1300	5.9223667825\\
+1302	5.935413683\\
+1304	5.9015896255\\
+1306	5.8993098045\\
+1308	5.891102095\\
+1310	5.881858564\\
+1312	5.8940111635\\
+1314	5.903941552\\
+1316	5.888497728\\
+1318	5.857725498\\
+1320	5.8567185045\\
+1322	5.861671574\\
+1324	5.8387118195\\
+1326	5.833706753\\
+1328	5.868907057\\
+1330	5.8273320035\\
+1332	5.8389400305\\
+1334	5.876151523\\
+1336	5.8620020595\\
+1338	5.892156925\\
+1340	5.9586369025\\
+1342	5.9567924075\\
+1344	5.982374356\\
+1346	6.0375119525\\
+1348	6.0890175215\\
+1350	6.086149783\\
+1352	6.1184705185\\
+1354	6.1594823235\\
+1356	6.1509530645\\
+1358	6.180046173\\
+1360	6.201404003\\
+};
+\addlegendentry{Target 6 dBm: measured}
+
+\node[above left, align=right, inner sep=0, font=\color{mycolor3}]
+at (axis cs:1359,6) {$\text{P}_{\text{set}}\text{ = 6 dBm}$};
+\addplot [color=white!65!black, dotted, forget plot]
+  table[row sep=crcr]{%
+1260	8\\
+1360	8\\
+};
+\addplot [color=mycolor4, line width=1.6pt]
+  table[row sep=crcr]{%
+1260	6.031553038\\
+1262	6.475926562\\
+1264	6.9678239935\\
+1266	7.3812834605\\
+1268	7.6372069015\\
+1270	7.9191694625\\
+1272	8.0705430165\\
+1274	8.075813651\\
+1276	8.083409099\\
+1278	8.084946346\\
+1280	8.070698563\\
+1282	8.072232142\\
+1284	8.0797347955\\
+1286	8.0427192865\\
+1288	8.0515738335\\
+1290	8.0293537885\\
+1292	8.003326676\\
+1294	7.9976869805\\
+1296	7.99008813\\
+1298	7.9492751595\\
+1300	7.9346835125\\
+1302	7.9539901195\\
+1304	7.9017661065\\
+1306	7.911127979\\
+1308	7.907037724\\
+1310	7.896197244\\
+1312	7.907979363\\
+1314	7.9250423625\\
+1316	7.8998658815\\
+1318	7.869535715\\
+1320	7.8711403195\\
+1322	7.8730818405\\
+1324	7.845561009\\
+1326	7.85929528\\
+1328	7.8721726815\\
+1330	7.843708335\\
+1332	7.872582495\\
+1334	7.8930589925\\
+1336	7.882136431\\
+1338	7.920374461\\
+1340	7.9612389245\\
+1342	7.968047289\\
+1344	8.002771872\\
+1346	8.054855834\\
+1348	8.0969126465\\
+1350	8.1158346705\\
+1352	8.1537042675\\
+1354	8.181075273\\
+1356	8.1743607905\\
+1358	8.184566916\\
+1360	8.231713996\\
+};
+\addlegendentry{Target 8 dBm: measured}
+
+\node[above left, align=right, inner sep=0, font=\color{mycolor4}]
+at (axis cs:1359,8) {$\text{P}_{\text{set}}\text{ = 8 dBm}$};
+\addplot [color=white!65!black, dotted, forget plot]
+  table[row sep=crcr]{%
+1260	10\\
+1360	10\\
+};
+\addplot [color=mycolor5, line width=1.6pt]
+  table[row sep=crcr]{%
+1260	5.7017284215\\
+1262	6.1986312315\\
+1264	6.7501614225\\
+1266	7.1907112785\\
+1268	7.478677345\\
+1270	7.8060430325\\
+1272	8.1067171935\\
+1274	8.276471823\\
+1276	8.4638177645\\
+1278	8.6111332305\\
+1280	8.743436757\\
+1282	8.832386923\\
+1284	8.91278028\\
+1286	9.04439012185\\
+1288	9.04376373615\\
+1290	9.0798988258\\
+1292	9.03395511625\\
+1294	8.9921718725\\
+1296	9.0235644005\\
+1298	8.984754639\\
+1300	9.14610934125\\
+1302	9.13106503035\\
+1304	9.2086507995\\
+1306	9.19881023815\\
+1308	9.265719913\\
+1310	9.09915279415\\
+1312	9.26554581525\\
+1314	9.52831931645\\
+1316	9.6669975241\\
+1318	9.7107443498\\
+1320	9.7898754663\\
+1322	9.83403242775\\
+1324	9.8726901865\\
+1326	9.8822262349\\
+1328	9.88426970855\\
+1330	9.84195532625\\
+1332	9.87982448925\\
+1334	9.90844454246\\
+1336	9.89706352885\\
+1338	9.9274772081\\
+1340	9.991583686247\\
+1342	9.983836191075\\
+1344	10.01432601913\\
+1346	10.08652218347\\
+1348	10.1116048911\\
+1350	10.1206856349\\
+1352	10.1690383129\\
+1354	10.191050599\\
+1356	10.19157208575\\
+1358	10.21642409705\\
+1360	10.24591036845\\
+};
+\addlegendentry{Target 10 dBm: measured}
+
+\node[above left, align=right, inner sep=0, font=\color{mycolor5}]
+at (axis cs:1359,10) {$\text{P}_{\text{set}}\text{ = 10 dBm}$};
+\end{axis}
+\end{tikzpicture}%

projects/Lab_oband_laser_and_amp_analysis/data_analysis_and_plot_scripts/lambda_vs_spectrum.m

@@ -1,6 +1,6 @@
-wh_aeon = load("C:\Users\Silas\Documents\MATLAB\imdd_simulation\projects\Lab_analysis\aeon_soa_measurement_lambda_plaser_pump.mat");
+wh_aeon = load("C:\Users\Silas\Documents\MATLAB\imdd_simulation\projects\Lab_oband_laser_and_amp_analysis\aeon_soa_measurement_lambda_plaser_pump.mat");
 wh_aeon = wh_aeon.wh;
-wh_thor = load("C:\Users\Silas\Documents\MATLAB\imdd_simulation\projects\Lab_analysis\thorlabs_pdfa_measurement_lambda_plaser_pump.mat");
+wh_thor = load("C:\Users\Silas\Documents\MATLAB\imdd_simulation\projects\Lab_oband_laser_and_amp_analysis\thorlabs_pdfa_measurement_lambda_plaser_pump.mat");
 wh_thor = wh_thor.wh;
 
 % Silas' custom "warehouse" datatype
@@ -36,6 +36,7 @@ for p = 1:numel(plasers)
             plot(wavelength_osa,spectrum_osa,'DisplayName',sprintf('P_{in}: %d dB ',plasers(p)),'Color',cols(ccnt+1,:));
                
             
+
             ylim([-60, 20]);
             beautifyBERplot("logscale",false,"setmarkers",0,"setcolors",0);
         end

projects/MLSE_ML_based/minimal_example_huawei/minimal_example_ml_mlse.m

@@ -0,0 +1,193 @@
+
+if 1
+    % A) RUN FULL LOOP
+    M_format = [2,4,6,8];
+    snr = 10:25;
+else
+    % B) RUN FOR DEBUG AND TEST
+    M_format = 4;
+    snr = 20;
+end
+
+for m = 1:length(M_format)
+    % --- Parameters ---
+    M        = M_format(m);  % PAM order (e.g., 2,4,8)
+    Nsym     = 1e5;          % number of symbols
+    h        = [1, 0.5, 0.2];     % Impulse response to remove
+
+    b = log2(M);
+    if M == 6 b = 5; end
+    rng(1);
+    bits_tx = logical(randi([0 1], Nsym, b, 'uint8'));
+
+    tx_symbols = pammap(bits_tx,M);
+
+    if M == 6
+        states = unique(tx_symbols);
+        pam6transitions = combvec(states',states')'; % pam6transitions =
+        bitmapping = pamdemap(reshape(pam6transitions',1,[])',M);
+    else
+        bitmapping = pamdemap(unique(tx_symbols),M);
+    end
+
+    scaling = sqrt(sum(unique(tx_symbols).^2)/numel(unique(tx_symbols)));
+    tx_symbols = tx_symbols ./ scaling;
+
+    % apply impulse response to signal
+    y_filt = filter(h, 1, tx_symbols);
+
+    for s = 1:length(snr)
+
+        % apply noise
+        y = awgn(y_filt,snr(s),"measured",1);
+        y = Electricalsignal(y);
+
+        % apply ml-MLSE
+        adaptive_mu = 0;
+        mu_lms = 0.15;
+        ml_mlse_equalizer = ML_MLSE("epochs_tr",50,"epochs_dd",1,"len_tr",length(y)/2,...
+            "mu_dd",mu_lms,"mu_tr",mu_lms,"order",11,"sps",1,...
+            "L",2,"delta",4,"adaptive_mu",adaptive_mu);
+
+        [ml_mlse_estimate,~] = ml_mlse_equalizer.process(y,tx_symbols);
+        rx_symbols = ml_mlse_estimate .* scaling;
+        bits_rx = pamdemap(rx_symbols,M);
+        
+        BER_ml(m,s) = nnz(bits_tx ~= bits_rx) / numel(bits_tx);
+        fprintf('BER = %.2e \n', BER_ml(m,s));
+
+        % apply bcjr
+        BCJR = MLSE("DIR",h,"duobinary_output",0,"M",M,"trellis_states",unique(tx_symbols));
+        [viterbi_estimate,LLR,GMI(m,s)] = BCJR.process(y,tx_symbols,bits_tx,bitmapping);
+
+        % decode LLR's
+        bits_LLR = LLR > 0;
+
+        % demap viterbi symbols sequence
+        rx_symbols = viterbi_estimate .* scaling;
+        bits_rx = pamdemap(rx_symbols,M);
+
+        % BER calc
+        BER_vit(m,s) = nnz(bits_tx ~= bits_LLR) / numel(bits_tx);
+        fprintf('BER LLR = %.2e \n', BER_vit(m,s));
+
+        BER_llr(m,s) = nnz(bits_tx ~= bits_rx) / numel(bits_tx);
+        fprintf('BER = %.2e \n', BER_llr(m,s));
+    end
+end
+%%
+figure();hold on
+for m = 1:length(M_format)
+    p=plot(snr,BER_llr(m,:),'DisplayName',sprintf('Viterbi: PAM %d',M_format(m)));
+    plot(snr,BER_ml(m,:),'DisplayName',sprintf('ML-Based: PAM %d',M_format(m)),'LineStyle',':','Color',p.Color);
+end
+ylabel('BER');
+xlabel('SNR')
+title('BER vs. SNR');
+set(gca, 'XScale', 'linear', ...
+    'YScale', 'log', ...
+    'TickLabelInterpreter', 'latex', ...
+    'FontSize', 11);
+
+%%
+figure();hold on
+for m = 1:length(M_format)
+    plot(snr,GMI(m,:),'DisplayName',sprintf('GMI PAM %d',M_format(m)))
+end
+ylabel('GMI');
+xlabel('SNR')
+title('GMI vs. SNR');
+set(gca, 'XScale', 'linear', ...
+    'YScale', 'linear', ...
+    'TickLabelInterpreter', 'latex', ...
+    'FontSize', 11);
+
+function symbols = pammap(bits,M)
+bits = logical(bits);
+if M == 2
+    symbols = bits;
+elseif M == 4
+    symbols= 2*bits(:,1) + (bits(:,1)==bits(:,2));
+    symbols=2*symbols-3;
+
+elseif M == 6
+
+    m = 1;
+
+    if size(bits,2)>size(bits,1)
+        bits = bits'; %vector aufrecht stellen
+    end
+    bits = reshape(bits',1,[])';
+    thres = [-3 5;-1 5;-3 -5;-1 -5;-5 3;-5 1;-5 -3;-5 -1;-1 3;-1 1;-1 -3;-1 -1;-3 3;-3 1;-3 -3;-3 -1;3 5;1 5;3 -5;1 -5;5 3;5 1;5 -3;5 -1;1 3;1 1;1 -3;1 -1;3 3;3 1;3 -3;3 -1];
+    % LUT based mapping
+    for k = 1:5:fix(length(bits)/5)*5
+        symbols(m:m+1,1) = thres(bin2dec(int2str(bits(k:k+4)'))+1,:);
+        m = m+2;
+    end
+
+elseif M == 8
+    x1 = bits(:,1);
+    x2 = (bits(:,1)==bits(:,3));
+    x3 = x2~=bits(:,2);
+
+    symbols = 4*x1 + 2*x2 + x3;
+    symbols=2*symbols-7;
+end
+end
+
+function bits = pamdemap(symbols,M)
+
+if M == 2
+    thres=0;
+elseif M == 4
+    thres=[-2,0,2];
+elseif M == 6
+    thres = [-3 5;-1 5;-3 -5;-1 -5;-5 3;-5 1;-5 -3;-5 -1;-1 3;-1 1;-1 -3;-1 -1;-3 3;-3 1;-3 -3;-3 -1;3 5;1 5;3 -5;1 -5;5 3;5 1;5 -3;5 -1;1 3;1 1;1 -3;1 -1;3 3;3 1;3 -3;3 -1];
+elseif M == 8
+    thres=-6:2:6;
+end
+
+if M ~= 6
+    symbols = symbols';
+    a = squeeze(repmat(real(symbols),[1 1 length(thres)])); %Eingangssignal in 3 spalten
+    b = squeeze(repmat(reshape(thres(:).',[1 1 length(thres)]),[1 length(symbols) 1])); %Threshold in 3 Spalten
+    comp_real = a > b; %check for each symbol/ sampling if it exeeds the obj.thresholdseshold 1, 2 or 3
+    comp_real=repmat(real(symbols),[1 1 length(thres)]) > repmat(reshape(thres(:).',[1 1 length(thres)]),[1 length(symbols) 1]);
+    s1=size(comp_real,1);
+    s2=size(comp_real,2);
+end
+
+if M == 2
+    data_out=abs(comp_real(:,:,1));
+elseif M == 4
+    data_out=[comp_real(:,:,2); ones(s1,s2) - comp_real(:,:,1) + comp_real(:,:,3)];
+elseif M == 6
+
+    if size(symbols,2) > 1
+        symbols = symbols.';
+    end
+
+    if length(symbols)/2 ~= round(length(symbols)/2)
+        symbols = [symbols;0];
+    end
+
+    m = 1;
+    for n = 1:2:length(symbols)
+        dist = sqrt((symbols(n)-thres(:,1)).^2+(symbols(n+1)-thres(:,2)).^2);
+        [~,dd_idx] = min(dist);
+        %                 dec_out(n:n+1) = LUT(dd_idx,:);
+        data_out(m:m+4) = bitget(dd_idx-1,5:-1:1);
+        m = m+5;
+    end
+
+    data_out = reshape(data_out',5,[]);
+
+elseif M == 8
+    data_out=[comp_real(:,:,4);
+        comp_real(:,:,1)-comp_real(:,:,3)+comp_real(:,:,5)-comp_real(:,:,7);
+        1-comp_real(:,:,2)+comp_real(:,:,6)];
+end
+
+bits = data_out';
+
+end