Many changes for 400G DSP

Minimal Example
...

Classes/00_signals/Signal.m

@@ -349,13 +349,13 @@ classdef Signal
 
             % spectrum_plot(obj.signal,options.fsamp,options.figurename,options.displayname);
 
-            N = 2^(nextpow2(length(obj.signal))-2);
+            N = 2^(nextpow2(length(obj.signal))-9);
 
             if options.normalizeToNyquist==0
-                [p_lin,w] = pwelch(obj.signal,hanning(N),N/2,N,obj.fs,"centered","power","mean");
+                [p_lin,w] = pwelch(obj.signal,hanning(N),N/2,N,obj.fs,"centered","psd","mean");
                 w=w.*1e-9;
             else
-                [p_lin,w] = pwelch(obj.signal,hanning(N),N/2,N,"centered","power","mean");
+                [p_lin,w] = pwelch(obj.signal,hanning(N),N/2,N,"centered","psd","mean");
                 % p_lin = smooth(p_lin,0.05,'rloess');
             end
 
@@ -365,7 +365,7 @@ classdef Signal
                 p_dbm = 10*log10(p_lin); %dB to dBm in case of "power"
                 ylab = "normalized to 0 dB";
             else
-                p_dbm = 10*log10(p_lin)+30; %dB to dBm in case of "power"
+                p_dbm = 10*log10(p_lin); %dB to dBm in case of "power"
                 ylab = "Power (dBm)";
             end
 
@@ -401,6 +401,125 @@ classdef Signal
 
         end
 
+        function move_it_spectrum(obj,options)
+            arguments
+                obj
+                options.fignum
+                options.displayname = "";
+                options.color = [];
+                options.normalizeToNyquist = 0;
+                options.normalizeTo0dB = 0;
+            end
+
+            data_in = obj.signal;
+
+            if size(data_in,1) > size(data_in,2)
+                data_in = data_in';
+            end
+
+            for pol = 1:size(data_in,1)
+
+                %compute FFT of input
+                Data_in = fft( data_in(pol,:) );
+
+                %psd = Data_in.*conj(Data_in);
+                psd = Data_in;
+
+                %Use only magnitude of FFT (which was complex)
+                psd = abs(psd);
+
+                %Shift the spectrum to yield
+                psd = fftshift(psd);
+
+                %divide by N
+                psd = psd/length(data_in(pol,:));
+
+                psd_plot = 20*log10(psd);
+
+                % psd_plot = psd_plot - max(psd_plot);
+
+
+                %smoothing
+                % psd_smoothed = smooth(psd,1000);
+                %
+                % psd_smoothed = 10*log10(psd_smoothed);
+
+                % psd_smoothed = psd_smoothed - max(psd_smoothed);
+
+                carrier_power_time_dbm = 20*log10(   mean(abs(data_in)) .^2  )+30; % dB -> +30 -> dBm
+                carrier_power_freq_dbm = max(psd_plot);
+
+
+                % psd_plot = psd_plot - max(psd_plot);
+
+                %% cspr
+                c = mean(data_in).^2;
+                s = mean(data_in.^2);
+                cspr = 10*log10(c / s);
+
+                testParseval = 1;
+
+                if testParseval == 1
+
+                    E_FreqDomain =1/length(psd) * sum((psd.*length(psd)).^2);
+
+                    %test parseval
+                    E_TimeDomain = sum( (data_in(pol,:).^2) );
+
+                    if isequal(round(E_FreqDomain,1),round(E_TimeDomain,1))
+                        disp('Parseval is right!');
+                    else
+                        % disp('Something is wrong here?!');
+                    end
+                end
+
+                figure(options.fignum);  % If figure does not exist, create new figure
+
+                if 1
+                    %Frequency Axis
+                    freq_vec = linspace(-obj.fs/2,obj.fs/2,length(psd));
+                    freq_vec = reshape(freq_vec,size(psd_plot));
+
+
+                    if nargin == 4
+                        p = plot(freq_vec*1e-9,psd_plot,'Linewidth',0.5,'DisplayName',options.displayname);
+                        % plot(freq_vec*1e-9,psd_smoothed','Linewidth',1,'Color',[0 0 0],'DisplayName',[char(varargin{2}),' smoothed']);
+
+                    else
+                        p = plot(freq_vec*1e-9,psd_plot,'Linewidth',0.5);
+                        % plot(freq_vec*1e-9,psd_smoothed','Linewidth',1,'Color',[1 1 1],'LineStyle',':');
+
+                    end
+
+                    %xlim([freq_vec(1)/1e9-2 freq_vec(end)/1e9+2])
+                    xlabel('frequency [GHz]')
+                else
+                    %Wavelength Axis
+                    freq_vec = physconst('LightSpeed')*linspace(-obj.fs/2,obj.fs/2,length(psd))./((physconst('LightSpeed')/1310e-9)^2)*1e9;
+                    freq_vec = freq_vec+1310;
+                    if nargin == 4
+                        plot(freq_vec',psd_plot,'Linewidth',0.5,'DisplayName',options.displayname)
+                    else
+                        plot(freq_vec,psd_plot','Linewidth',0.5);
+                    end
+
+                    %xlim([freq_vec(1)/1e9-2 freq_vec(end)/1e9+2])
+                    xlabel('wavelength [nm]')
+                end
+                hold on
+
+
+            end
+
+            % xlim([-150 150])
+            % ylim([-100,0]);
+            ylabel('magnitude [dBm]')
+            legend
+            grid minor;
+
+
+        end
+
         %% Power of signal
         function pow = power(obj,options)
 
@@ -544,7 +663,7 @@ classdef Signal
             
             %Cut occurences of ref signal from signal (only positive shifts)
             S = {};
-            for c = shifts(shifts>0)
+            for c = shifts(shifts>=0)
                 sig = obj.delay(-c,'mode','samples');
                 sig.signal = sig.signal(1:length(b));
                 S{end+1,1} = sig;
@@ -557,7 +676,7 @@ classdef Signal
             end
 
             %return/keep the sinal with the highest correlation (only within positive shifts)
-            [~,idx]=max(pks(shifts>0));
+            [~,idx]=max(pks(shifts>=0));
             obj.signal = S{idx}.signal;
             %put signal with highest corr. to first index in S array
             swap = S{1};