Scattered stuff from Silas during Dissertation

Functions/EQ_visuals/showLevelHistogram.m

@@ -4,6 +4,8 @@ arguments
     ref_symbols
     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
 end
 
     if isa(eq_signal,'Signal')
@@ -12,6 +14,20 @@ end
     if isa(ref_symbols,'Signal')
         ref_symbols = ref_symbols.signal;
     end
+    if isa(options.ref_symbol_uncoded,'Signal')
+        options.ref_symbol_uncoded = options.ref_symbol_uncoded.signal;
+    end
+
+    eq_signal = eq_signal(:);
+    ref_symbols = ref_symbols(:);
+    ref_symbol_uncoded = options.ref_symbol_uncoded(:);
+
+    assert(numel(eq_signal) == numel(ref_symbols), ...
+        'showLevelHistogram:LengthMismatch', ...
+        'eq_signal and ref_symbols must have the same number of samples.');
+    assert(isempty(ref_symbol_uncoded) || numel(ref_symbol_uncoded) == numel(eq_signal), ...
+        'showLevelHistogram:LengthMismatch', ...
+        'options.ref_symbol_uncoded must have the same number of samples as eq_signal.');
 
     % Determine the figure number to use or create a new figure
     if isnan(options.fignum)
@@ -22,31 +38,70 @@ end
 
     eq_signal = max(min(eq_signal,3),-3);
 
-    %%% Separate Classes
-    constellation = unique(ref_symbols);
-    received_sd = NaN(numel(constellation),length(ref_symbols));
-    lvlcol = cbrewer2('Paired',numel(constellation)*2);
-    lvlcol = lvlcol(2:2:end,:);
-    lvlcol = linspecer(numel(constellation));
-    % lvlcol = cbrewer2('Set1',numel(constellation));
-    for lvl = 1:numel(constellation)
-        %Separate the equalized signal into the
-        %respective levels based on the actually
-        %transmitted level!
-        received_sd(lvl,ref_symbols==constellation(lvl)) = eq_signal(ref_symbols==constellation(lvl));
-    end
-    
-    % scaling = PAMmapper(numel(constellation),0).get_scaling;
-    
-    %%% FFE histogram 
+    %%% histogram 
     clf
-    for lvl = 1:numel(constellation)
-        intermediate = received_sd(lvl,:);
-        cnt(lvl) = round(numel(intermediate(~isnan(intermediate)))./length(eq_signal),3).*100;
-        hold on
-        warning off
-        histogram(received_sd(lvl,:),1000,"EdgeAlpha",0,'DisplayName',['Lvl ',num2str(lvl),' ; ',num2str(cnt(lvl)),' '],'FaceColor',lvlcol(lvl,:),'Normalization','pdf');
-        warning on
+    if isempty(ref_symbol_uncoded)
+        % Normal mode: split the received signal by the actually
+        % transmitted reference level.
+        constellation = unique(ref_symbols);
+        received_sd = NaN(numel(constellation),numel(ref_symbols));
+        lvlcol = linspecer(numel(constellation));
+
+        for lvl = 1:numel(constellation)
+            class_mask = ref_symbols == constellation(lvl);
+            received_sd(lvl,class_mask) = eq_signal(class_mask);
+        end
+
+        for lvl = 1:numel(constellation)
+            intermediate = received_sd(lvl,:);
+            cnt(lvl) = round(numel(intermediate(~isnan(intermediate)))./numel(eq_signal),3).*100;
+            hold on
+            warning off
+            histogram(received_sd(lvl,:),options.nbins, ...
+                "EdgeAlpha",0, ...
+                "DisplayName",['Lvl ',num2str(lvl),' ; ',num2str(cnt(lvl)),' '], ...
+                "FaceColor",lvlcol(lvl,:), ...
+                "Normalization","pdf");
+            warning on
+        end
+    else
+        % Plot p(y | x_n): y is the noisy observation and x_n is the
+        % uncoded PAM class. For duobinary this naturally gives multi-modal
+        % PDFs because one x_n class can map to multiple DB amplitudes. Each
+        % DB lobe is drawn separately so the DB-level structure stays visible.
+        db_constellation = unique(ref_symbols);
+        classes = unique(ref_symbol_uncoded);
+        lvlcol = linspecer(numel(classes));
+
+        for db_lvl = 1:numel(db_constellation)
+            db_mask = ref_symbols == db_constellation(db_lvl);
+            mapped_class = mode(ref_symbol_uncoded(db_mask));
+            [~,class_idx] = min(abs(classes - mapped_class));
+            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),' '];
+                display_name = ['p(y|x_',num2str(class_idx),')'];
+                handle_visibility = "on";
+            else
+                display_name = ['p(y|x_',num2str(class_idx),') ; ',num2str(cnt),' '];
+                display_name = ['p(y|x_',num2str(class_idx),')'];
+                handle_visibility = "off";
+            end
+
+            weighted_lobe = NaN(size(eq_signal));
+            weighted_lobe(db_mask) = eq_signal(db_mask);
+
+            hold on
+            warning off
+            histogram(weighted_lobe,options.nbins, ...
+                "EdgeAlpha",0, ...
+                "DisplayName",display_name, ...
+                "FaceColor",lvlcol(class_idx,:), ...
+                "HandleVisibility",handle_visibility, ...
+                "Normalization","pdf");
+            warning on
+        end
     end
     xlim([-3 3]);
     legend
@@ -58,3 +113,15 @@ end
 
 end
 
+function first_db_lvl = findFirstMappedDbLevel(ref_symbols,ref_symbol_uncoded,db_constellation,mapped_class)
+    first_db_lvl = NaN;
+
+    for db_lvl = 1:numel(db_constellation)
+        db_mask = ref_symbols == db_constellation(db_lvl);
+        if mode(ref_symbol_uncoded(db_mask)) == mapped_class
+            first_db_lvl = db_lvl;
+            return
+        end
+    end
+end
+