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Classes/Warehouse_class/functions/fwm_plots/plotBerVsZDW.m
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300
Classes/Warehouse_class/functions/fwm_plots/plotBerVsZDW.m
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function plotBerVsZDW(wh,plotJob)
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fig = findall(groot, 'Type', 'figure', 'Name', plotJob.figName);
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if isvalid(fig)
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figure(fig)
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fig = get(fig);
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AxesMain = fig.CurrentAxes;
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hold on
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else
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fig = figure('name',char(plotJob.figName));
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AxesMain = gca;
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hold on
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end
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col = plotJob.color;
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% we want to fetch all realizations
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realization = wh.parameter.realization.values(1:end);
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% get all xAxis values
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xAxis = wh.parameter.p_out.values;
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% get all center wavelengths
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wavelengths = wh.parameter.center_wavelength.values;
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% totber = NaN(numel(realization),1,numel(xAxis),numel(wavelengths));
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% ber = zeros(numel(realization),plotJob.ch,numel(xAxis),numel(wavelengths));
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%get BER values for query
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for w = 2:numel(wavelengths)
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for xl = 1:numel(xAxis)
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c_wavelen = wavelengths(w);
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p_out = xAxis(xl);
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% dim1 : realiz; dim2: channels, dim3: rop, dim4, c_wavelength
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temp = removeZeros(wh.getStoValue('ber',plotJob.l,plotJob.d,plotJob.sgm,string(plotJob.pol),plotJob.p_in,p_out,plotJob.pmd,plotJob.gamma,realization,plotJob.ch,c_wavelen,plotJob.channelspacing,plotJob.randzdw));
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ber(1:size(temp,1),:,xl,w) = temp;
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end
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end
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hdfec = 3.8e-3.*ones(size(xAxis));
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zdw_ = [];
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zdw_chann = [];
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zdw_tot = [];
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cf_tot = [];
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cf_ = [];
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S = [];
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Stot = [];
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S_chann = [];
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cf_chann = [];
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cnt = 0;
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%get fec thresholds
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%linear = squeeze(linear);
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for c_wavelen = 1:size(ber,4)
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for realiz = 1:size(ber,1)
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for chann = 1:size(ber,2)
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%finde Schnittpunkt zwischen FEC und BER Kurve
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temp_ber = squeeze(ber(realiz,chann,:,c_wavelen)).';
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if ~all(temp_ber == 0)
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%nur wenn nicht alles nullen sind
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crossing_ch = InterX([hdfec;xAxis],[temp_ber;xAxis]);
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else
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continue
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end
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%Req. FEC Ergebnis einsortieren
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if ~isempty(crossing_ch)
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if crossing_ch(2) == 0
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print("d")
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end
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S(realiz,chann,c_wavelen) = crossing_ch(2);
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else
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S(realiz,chann,c_wavelen) = -1;
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cnt = cnt +1;
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end
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end
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end
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end
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temp_max = -inf;
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for i = 1:plotJob.ch
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hold on
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%S:: 1.dim: realiz; 2.dim: channel; 3.dim: center wavelength
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%squeeze a channel:
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temp_data = squeeze(S(:,i,:));
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%remove realizations that have no entry (only zero)
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temp_data = removeZeros(temp_data);
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%replace zeros with NAN (e.g. for the wavelengths that have missing realizations)
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temp_data(temp_data==0) = NaN;
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%plot required ROP for channel and all realizations that cross the
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%FEC limit
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scatter(wavelengths,temp_data ,5,plotJob.color,'Marker','.');
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% %plot mean per channel
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% temp_mean = mean(temp_data,'omitnan');
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% hold on
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% plot(wavelengths,temp_mean,'Marker','*');
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%get max overall value
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temp_max = max(temp_max,max(temp_data));
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end
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%plot mean overall
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mean_overall = squeeze(mean(S,2));
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mean_overall(mean_overall==0) = NaN;
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%mean_overall(mean_overall==-1) = NaN;
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mean_overall=mean(mean_overall,1,'omitnan');
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plot(wavelengths,mean_overall,'Color',plotJob.color);
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%plot max overall
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scatter(wavelengths,temp_max ,35,plotJob.color,'Marker','v');
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%plot channel positions
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hold on
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chpos = calcWavelengthPlan(plotJob.ch, 400e9, 1310);
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xline(chpos,'LineWidth',2,'Alpha',0.2);
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chpos = calcWavelengthPlan(plotJob.ch, 400e9, chpos(4));
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xline(chpos,'LineWidth',2,'Alpha',0.2);
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fig.Position = plotJob.Position;
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ylabel('Penalty in dB');
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xlabel('Wavelength in nm');
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xlim([min(wavelengths),max(wavelengths) ]);
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grid minor;
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set(gca, 'color', 'none');
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legend = [];
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fontsize(AxesMain,8,"points")
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fig.Position = plotJob.Position;
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fig.Units = "centimeters";
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fig.Position = [2 2 8.5 7];
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set(AxesMain,'TickLabelInterpreter','latex')
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set(AxesMain.Legend,'Interpreter','latex')
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%
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%
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%
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%
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%
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% distinct_cf = unique(cf_chann);
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%
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% for i = 1:length(distinct_cf)
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% indices = find(cf_chann==distinct_cf(i));
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% cf(i) = distinct_cf(i);
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% worst_fec_cross(i) = max(S_chann(indices));
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% avg_fec_cross(i) = mean(S_chann(indices));
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% end
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%
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% avg_fec_cross = smooth(avg_fec_cross,5);
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%
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% figure(224)
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% hold on
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% scatter(cf_,S,10.*abs(S-mean(S)).*ones(size(S)),'DisplayName',['AVG'],'MarkerEdgeColor',col,'MarkerFaceColor',col,'Marker','.');
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% hold on
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% scatter(cf(2:end),worst_fec_cross(2:end),15,'DisplayName',['Worst'],'MarkerEdgeColor',col,'MarkerFaceColor',col,'Marker','.','HandleVisibility','off');
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% plot(cf(2:end),avg_fec_cross(2:end),'DisplayName',['AVG'],'LineWidth',1,'LineStyle','-','Color',col,'Marker','none','MarkerFaceColor',col,'MarkerSize',2);
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% plot(cf(2:end),worst_fec_cross(2:end),'DisplayName',['AVG'],'LineWidth',0.5,'LineStyle','-','Color',col,'Marker','none','MarkerFaceColor',col,'MarkerSize',2);
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% ghzgrid = hz2nm(nm2hz(1310)+[0:1:20].*400e9);
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% set(gca,'xtick',sort(ghzgrid))
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% xlim([min(cf(cf~=0)), 1310.1]);
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%
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%
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% % With matlab internal errorbar function...
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% figure(221)
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% %plot(cf,avg_fec_cross,'DisplayName',['AVG'],'LineWidth',1,'Color',col,'Marker','none','MarkerFaceColor',col,'MarkerSize',2);
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% hold on
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% %plot(cf_tot,min(S_chann(1:length(cf_tot),:),[],2),'DisplayName',['AVG'],'LineWidth',1,'LineStyle',':','Color',col,'Marker','^','MarkerFaceColor',col,'MarkerSize',2);
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% plot(cf,worst_fec_cross,'DisplayName',['AVG'],'LineWidth',2,'LineStyle','-','Color',col,'Marker','none','MarkerFaceColor',col,'MarkerSize',2);
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% ghzgrid = hz2nm(nm2hz(1310)+[0:1:20].*400e9);
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% set(gca,'xtick',sort(ghzgrid))
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% xlim([1302, 1310.1]);
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% xline(ghzgrid,'LineStyle',':','Color',[.7 .7 .7]);
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%with
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% Stot = movmean(Stot,5);
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% figure(222)
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% [hl,hp] = boundedline(cf_tot,Stot,[(Stot'-min(S_chann(1:length(cf_tot),:),[],2)),(max(S_chann(1:length(cf_tot),:),[],2)-Stot')], 'alpha','Color',col,'transparency', 0.05);
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% ho = outlinebounds(hl,hp);
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% set(ho, 'linestyle', ':', 'color', col, 'marker', '.','linewidth',0.5);
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% hold on
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%
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% ghzgrid = hz2nm(nm2hz(1310)+[0:1:12].*400e9);
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% xline(ghzgrid);
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%plot the total ber
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% %figure(22);
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% hold on;
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% b= movmean(Stot,3);
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% plot(AxesMain,cf_tot,b,'LineWidth',2,'DisplayName',[plotJob.dataStatArg,' Ch.: ', plotJob.displayname],'Color',col,'Marker','o');
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% hold on
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%scatter(AxesMain,zdw_,S,'Marker','+','MarkerEdgeColor',col,'MarkerFaceAlpha',0.4,'MarkerEdgeAlpha',0.4,'LineWidth',0.5,'Parent', AxesMain(1),'DisplayName',[plotJob.dataStatArg,' Ch.: ', plotJob.displayname]);
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%ylim(AxesMain,[-9.3 -7]);
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% for i = 1:numel(chp)
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% hold on
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% xline(AxesMain,chp(i),'Color',colr(i,:),'DisplayName',['CH: ', num2str(i)],'LineWidth',1.5);
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% hold off
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% end
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%
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% a = movmean(sortrows([zdw_; S]'),10,'Endpoints','discard');
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%
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% sorted = sortrows([zdw_; S]');
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% figure(2)
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% scatter(sorted(:,1),sorted(:,2))
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%
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% ber_sorted = sort(S);
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% mean(ber_sorted);
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% std(ber_sorted);
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% z1 = [];
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% penalty = mean(ber_sorted):0.01:mean(ber_sorted)+2;
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% for i = 1:length(penalty)
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% l = penalty(i);
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% if i == 1
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% z1 = [z1 sum(ber_sorted(1,:)<l ) / length(ber_sorted) ];
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% else
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% z1 = [z1 sum(ber_sorted(1,:)<l & ber_sorted(1,:)>l-0.01) / length(ber_sorted) ];
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% end
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%
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% end
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%
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% penalty_higherthan = 0.5;
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% probability = sum(z1(find(penalty>mean(ber_sorted)+penalty_higherthan)));
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% disp(['A penalty of more than 1dB has a probability of: ', num2str(probability)]);
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% %
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% stem(AxesMain,penalty,z1,"filled",'Marker','o','MarkerSize',2,'Color',col);
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%
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%
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% [f1,x1]=ecdf(S(end,:));
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% %figure(23);plot(AxesMain,x1,f1,'r','LineWidth',3, 'Color',col);
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%
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% %plot(AxesMain,a(:,1),a(:,2),'Color',col+1,'Parent', AxesMain(1));
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%
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% % histogram(AxesMain,S,1000,'EdgeColor','none','FaceAlpha',0.4);
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%
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%
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%
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% %
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% %scatter(AxesMain,zdw_,S,'Marker','+','MarkerEdgeColor',col,'MarkerFaceAlpha',0.4,'MarkerEdgeAlpha',0.4,'LineWidth',0.5,'Parent', AxesMain(1),'DisplayName',[plotJob.dataStatArg,' Ch.: ', plotJob.displayname]);
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% hold on
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% %scatter(AxesMain,zdw_chann(:,1),mean(S_chann,2),'Marker','diamond','MarkerEdgeColor',col,'MarkerFaceAlpha',0.6,'LineWidth',7,'MarkerFaceColor',col,'Parent', AxesMain(1),'DisplayName',[plotJob.dataStatArg,' Ch.: ', plotJob.displayname]);
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% hold off
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% %
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% % for rlz = 1:size(S,2)
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% % zdwval = zdw_(rlz);
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% % feccrossing = S(rlz);
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% % scatter(AxesMain,zdwval,feccrossing,10,'MarkerEdgeColor',col,'MarkerFaceColor',col,'Parent', AxesMain(1),'DisplayName',[plotJob.dataStatArg,' Ch.: ', plotJob.displayname]);
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% % end
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%
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% xline([1302.03471732576,1304.30061112288,1306.57440520904,1308.85614097425,1311.14586009814,1313.44360455251,1315.74941660391,1318.06333881618]);
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end
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function vec = removeZeros(vec)
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% Find rows that contain only zeros
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rows_to_remove = all(vec == 0, 2);
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% Remove rows with only zeros
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vec(rows_to_remove, :) = [];
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end
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