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new par function

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This commit is contained in:
silas (home)
2025-12-31 12:46:56 +01:00
parent 45c9fc2b14
commit 2354d7ac44
3 changed files with 590 additions and 151 deletions
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282
projects/WDM/WDM_auswertung.m
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@@ -1,68 +1,68 @@
%saved like this: output_ffe{ch,rop,realiz,eval_distance}
try
rop = res.settings.rop; % 12 points
wavelengthplan = res.settings.wavelengthplan;
catch
wavelengthplan = [1295,1305,1315,1325];
wavelengthplan = calcWavelengthPlan(16,400e9,1310);
rop = -8.25:0.75:0;
end
N = length(wavelengthplan);
dims = size(res.ffe);
rop = res.settings.rop;
wavelengthplan = res.settings.wavelengthplan;
N_distances = dims(4); %usually 2km and 10km are evaualted
distances = res.eval_dist_km; %[2,10]
N_ch = length(wavelengthplan); %16 channels
figure(); hold on;
cols = cbrewer2('set2',N); % one color per wavelength (Ch)
cols = cbrewer2('set2',N_ch); % one color per wavelength (Ch)
fec = 2.2e-4;
fec = 3.8e-3;
Sffe = cell(1,N);
Svnle = cell(1,N);
Smlse = cell(1,N);
Sdbt = cell(1,N);
Sffe = cell(1,N_ch);
Svnle = cell(1,N_ch);
Smlse = cell(1,N_ch);
Sdbt = cell(1,N_ch);
% Choose your quantile band. For your old style, use 0.04/0.99:
qLow = 0.0; % lower quantile (e.g., 0.04 for old script)
qHigh = 1; % upper quantile (e.g., 0.99 for old script)
cols = linspecer(N); % one color per wavelength (Ch)
cols = cbrewer2('set1',N);
cols = linspecer(N_ch); % one color per wavelength (Ch)
cols = cbrewer2('RdBu',N_ch);
for l = 1:N
% Slice 12x50 cell arrays
ffe_cells = reshape(squeeze(res.ffe(l,:,:)),length(rop),[]);
vnle_cells = reshape(squeeze(res.vnle(l,:,:)),length(rop),[]);
mlse_cells = reshape(squeeze(res.mlse(l,:,:)),length(rop),[]);
dbt_cells = reshape(squeeze(res.dbt(l,:,:)),length(rop),[]);
for eval_ptr = 2
for ch = 1:N_ch
[Sffe{l}, noX_ffe] = fecCrossings(rop, ffe_cells, fec);
% Slice 12x50 cell arrays
ffe_cells = reshape(squeeze(res.ffe(ch,:,:,eval_ptr)),length(rop),[]);
vnle_cells = reshape(squeeze(res.vnle(ch,:,:,eval_ptr)),length(rop),[]);
mlse_cells = reshape(squeeze(res.mlse(ch,:,:,eval_ptr)),length(rop),[]);
dbt_cells = reshape(squeeze(res.dbt(ch,:,:,eval_ptr)),length(rop),[]);
[Svnle{l}, noX_ffe] = fecCrossings(rop, vnle_cells, fec);
[Sffe{ch}, noX_ffe] = fecCrossings(rop, ffe_cells, fec);
[Smlse{l}, noX_ffe] = fecCrossings(rop, mlse_cells, fec);
[Svnle{ch}, noX_ffe] = fecCrossings(rop, vnle_cells, fec);
[Sdbt{l}, noX_ffe] = fecCrossings(rop, dbt_cells, fec);
[Smlse{ch}, noX_ffe] = fecCrossings(rop, mlse_cells, fec);
% Extract BER matrices using only complete realizations (12/12 ROP filled)
ffe_mat = extractCompleteBER(ffe_cells); % 12 x K_ffe
vnle_mat = extractCompleteBER(vnle_cells); % 12 x K_vnle
mlse_mat = extractCompleteBER(mlse_cells); % 12 x K_mlse
mlse_alpha_mat = extractCompleteAlphas(mlse_cells); % 12 x K_mlse
dbt_mat = extractCompleteBER(dbt_cells); % 12 x K_dbt
[Sdbt{ch}, noX_ffe] = fecCrossings(rop, dbt_cells, fec);
showLegend = 1; % one legend entry per technique
% Extract BER matrices using only complete realizations (12/12 ROP filled)
ffe_mat = extractCompleteBER(ffe_cells); % 12 x K_ffe
vnle_mat = extractCompleteBER(vnle_cells); % 12 x K_vnle
mlse_mat = extractCompleteBER(mlse_cells); % 12 x K_mlse
mlse_alpha_mat = extractCompleteAlphas(mlse_cells); % 12 x K_mlse
dbt_mat = extractCompleteBER(dbt_cells); % 12 x K_dbt
% Plot shaded band + mean line with boundedline
% plotBandMeanBL(rop, ffe_mat, cols(l,:), sprintf('FFE @ %.1d nm',round(wavelengthplan(l))), qLow, qHigh, '--s', showLegend);
% scatter(Sffe,fec.*ones(size(Sffe)),20,'v','MarkerFaceColor','black');
showLegend = 1; % one legend entry per technique
% plotBandMeanBL(rop, vnle_mat, cols(l,:), sprintf('VNLE @ %.1d nm',round(wavelengthplan(l))), qLow, qHigh, '--x', showLegend);
% Plot shaded band + mean line with boundedline
% plotBandMeanBL(rop, ffe_mat, cols(ch,:), sprintf('FFE @ %.1d nm',round(wavelengthplan(l))), qLow, qHigh, '--s', showLegend);
% scatter(Sffe,fec.*ones(size(Sffe)),20,'v','MarkerFaceColor','black');
plotBandMeanBL(rop, mlse_mat, cols(l,:), sprintf('VNLE+PF+MLSE @ %.1d nm',round(wavelengthplan(l))), qLow, qHigh, '-o', showLegend);
% plotBandMeanBL(rop, vnle_mat, cols(ch,:), sprintf('VNLE @ %.1d nm',round(wavelengthplan(l))), qLow, qHigh, '--x', showLegend);
% plotBandMeanBL(rop, dbt_mat, cols(l,:), sprintf('DBt.+MLSE @ %.1d nm',round(wavelengthplan(l))), qLow, qHigh, '--v', showLegend);
% plotBandMeanBL(rop, mlse_mat, cols(ch,:), sprintf('VNLE+PF+MLSE @ %.1d nm',round(wavelengthplan(ch))), qLow, qHigh, '-o', showLegend);
set(gca,'XScale','linear','YScale','log','TickLabelInterpreter','latex','FontSize',11);
yline([3.8e-3, 2.2e-4], 'HandleVisibility','off','LineWidth',1.5);
% plotBandMeanBL(rop, dbt_mat, cols(ch,:), sprintf('DBt.+MLSE @ %.1d nm',round(wavelengthplan(l))), qLow, qHigh, '--v', showLegend);
set(gca,'XScale','linear','YScale','log','TickLabelInterpreter','latex','FontSize',11);
yline([3.8e-3, 2.2e-4], 'HandleVisibility','off','LineWidth',1.5);
end
end
ylabel('BER');
@@ -76,23 +76,23 @@ legend show;
%% VIOLIN
S_cell = Sdbt;
S_cell =Smlse;
S_cell = Smlse;
S_cell = {Svnle,Smlse,Sdbt};
S_cell = {Svnle};
figure(5); hold on;
for i = 1:length(S_cell)
% Pad to rectangular matrix: rows = realizations, cols = wavelengths
Kmax = max(cellfun(@numel, S_cell{i}));
S_mat = NaN(Kmax, N);
for l = 1:N
k = numel(S_cell{i}{l});
S_mat = NaN(Kmax, N_ch);
for ch = 1:N_ch
k = numel(S_cell{i}{ch});
if k > 0
S_mat(1:k, l) = S_cell{i}{l};
S_mat(1:k, ch) = S_cell{i}{ch};
end
end
% --- Violin plot over wavelengths (columns) ---
cols=linspecer(3);
catLabels = arrayfun(@(nm) sprintf('%d nm', nm), wavelengthplan, 'UniformOutput', false);
vs = violinplot(S_mat, catLabels, ...
@@ -105,9 +105,9 @@ for i = 1:length(S_cell)
'ShowData', true, ...
'ShowBox', false, ...
'Bandwidth', 0.05);
ylim([floor(min(S_mat,[],'all')), ceil(max(S_mat,[],'all'))])
% ylim([-8 0]);
% ylim([-8 0]);
ylabel('ROP at FEC crossing');
title(sprintf('RROP to cross BER %.2e', fec));
grid on; box on;
@@ -115,51 +115,43 @@ for i = 1:length(S_cell)
end
%% ================= helper =================
function plotBandMeanBL(x, Y, color, techLabel, qLow, qHigh, lineSpec, showLegend)
% Y: (nPoints x nRealizations)
% Remove realizations that are entirely zero (like removeZeros behavior)
badCols = all(Y == 0, 1);
Y(:, badCols) = [];
Y(Y==0) = 1e-8;
% Stats across realizations
mu = mean(Y, 2, 'omitnan'); % mean line
lo = quantile(Y, qLow, 2); % lower bound
hi = quantile(Y, qHigh, 2); % upper bound
% Y: (nPoints x nRealizations)
% Remove realizations that are entirely zero (like removeZeros behavior)
badCols = all(Y == 0, 1);
Y(:, badCols) = [];
% Convert to asymmetric distances required by boundedline:
% b(:,1) = distance to lower side; b(:,2) = distance to upper side
b = [mu - lo, hi - mu];
Y(Y==0) = 1e-8;
% Stats across realizations
mu = mean(Y, 2, 'omitnan'); % mean line
lo = quantile(Y, qLow, 2); % lower bound
hi = quantile(Y, qHigh, 2); % upper bound
% Call boundedline with alpha shading
[hl, hp] = boundedline(x(:), mu(:), b, lineSpec, 'alpha', ...
'transparency', 0.18);
% Color styling
set(hl, 'Color', color, 'LineWidth', 1.4, 'MarkerSize', 4);
set(hp, 'FaceColor', color, 'HandleVisibility','off'); % patch hidden in legend
% Convert to asymmetric distances required by boundedline:
% b(:,1) = distance to lower side; b(:,2) = distance to upper side
b = [mu - lo, hi - mu];
% Single legend entry per technique (use first wavelength only)
if showLegend
set(hl, 'DisplayName', techLabel);
else
set(hl, 'HandleVisibility','off');
end
% Call boundedline with alpha shading
[hl, hp] = boundedline(x(:), mu(:), b, lineSpec, 'alpha', ...
'transparency', 0.18);
% Color styling
set(hl, 'Color', color, 'LineWidth', 1.4, 'MarkerSize', 4);
set(hp, 'FaceColor', color, 'HandleVisibility','off'); % patch hidden in legend
% Optional: outline the bounds if outlinebounds is available
if exist('outlinebounds','file') == 2
ho = outlinebounds(hl, hp);
set(ho, 'linestyle', ':', 'color', color, 'linewidth', 1, ...
'HandleVisibility','off');
end
% Single legend entry per technique (use first wavelength only)
if showLegend
set(hl, 'DisplayName', techLabel);
else
set(hl, 'HandleVisibility','off');
end
% Optional: outline the bounds if outlinebounds is available
if exist('outlinebounds','file') == 2
ho = outlinebounds(hl, hp);
set(ho, 'linestyle', ':', 'color', color, 'linewidth', 1, ...
'HandleVisibility','off');
end
end
function [S, noCrossingMask, Y_keep] = fecCrossings(rop, cells12xR, fec)
@@ -173,52 +165,52 @@ function [S, noCrossingMask, Y_keep] = fecCrossings(rop, cells12xR, fec)
% noCrossingMask 1xK logical mask: true if no crossing for that realization
% Y_keep 12xK numeric BER matrix used for the crossing detection
% 1) keep only complete realization columns
Y = extractCompleteBER(cells12xR); % -> 12 x K
if isempty(Y)
S = [];
noCrossingMask = [];
Y_keep = Y;
return;
end
% 1) keep only complete realization columns
Y = extractCompleteBER(cells12xR); % -> 12 x K
if isempty(Y)
S = [];
noCrossingMask = [];
Y_keep = Y;
return;
end
% 2) optionally drop realizations with mean BER > 0.1
ok = mean(Y,1,'omitnan') <= 0.1;
Y = Y(:, ok);
if isempty(Y)
S = [];
noCrossingMask = [];
Y_keep = Y;
return;
end
% 2) optionally drop realizations with mean BER > 0.1
ok = mean(Y,1,'omitnan') <= 0.1;
Y = Y(:, ok);
if isempty(Y)
S = [];
noCrossingMask = [];
Y_keep = Y;
return;
end
% 3) find crossings per realization
nR = size(Y,2);
S = nan(1,nR);
noCrossingMask = true(1,nR);
% 3) find crossings per realization
nR = size(Y,2);
S = nan(1,nR);
noCrossingMask = true(1,nR);
rop = rop(:); % ensure column
for j = 1:nR
y = Y(:,j);
rop = rop(:); % ensure column
for j = 1:nR
y = Y(:,j);
% sign change from >fec to <=fec (first time it drops below FEC)
above = (y > fec);
idx = find(above(1:end-1) & ~above(2:end), 1, 'first');
% sign change from >fec to <=fec (first time it drops below FEC)
above = (y > fec);
idx = find(above(1:end-1) & ~above(2:end), 1, 'first');
if ~isempty(idx)
% linear interpolation between (x1,y1) and (x2,y2)
x1 = rop(idx); y1 = y(idx);
x2 = rop(idx+1); y2 = y(idx+1);
if ~isempty(idx)
% linear interpolation between (x1,y1) and (x2,y2)
x1 = rop(idx); y1 = y(idx);
x2 = rop(idx+1); y2 = y(idx+1);
if isfinite(y1) && isfinite(y2) && y2 ~= y1
t = (fec - y1) / (y2 - y1);
S(j) = x1 + t*(x2 - x1);
noCrossingMask(j) = false;
end
if isfinite(y1) && isfinite(y2) && y2 ~= y1
t = (fec - y1) / (y2 - y1);
S(j) = x1 + t*(x2 - x1);
noCrossingMask(j) = false;
end
end
end
Y_keep = Y;
Y_keep = Y;
end
@@ -226,28 +218,28 @@ end
function Y = extractCompleteBER(cellSlice)
% cellSlice: 12xR cell array; each cell should be a struct with .metrics.BER
% Keep only those realization columns where ALL 12 ROP entries are valid.
if isempty(cellSlice), Y = []; return; end
nR = size(cellSlice,2);
keep = false(1,nR);
for r = 1:nR
col = cellSlice(:,r);
keep(r) = all(cellfun(@(c) ~isempty(c) , col));
end
if ~any(keep), Y = []; return; end
Y = cellfun(@(c) c.metrics.BER, cellSlice(:,keep), 'UniformOutput', true);
if isempty(cellSlice), Y = []; return; end
nR = size(cellSlice,2);
keep = false(1,nR);
for r = 1:nR
col = cellSlice(:,r);
keep(r) = all(cellfun(@(c) ~isempty(c) , col));
end
if ~any(keep), Y = []; return; end
Y = cellfun(@(c) c.metrics.BER, cellSlice(:,keep), 'UniformOutput', true);
end
function Y = extractCompleteAlphas(cellSlice)
% cellSlice: 12xR cell array; each cell should be a struct with .metrics.BER
% Keep only those realization columns where ALL 12 ROP entries are valid.
if isempty(cellSlice), Y = []; return; end
nR = size(cellSlice,2);
keep = false(1,nR);
for r = 1:nR
col = cellSlice(:,r);
keep(r) = all(cellfun(@(c) ~isempty(c) , col));
end
if ~any(keep), Y = []; return; end
Y = cellfun(@(c) c.metrics.Alpha, cellSlice(:,keep), 'UniformOutput', true);
if isempty(cellSlice), Y = []; return; end
nR = size(cellSlice,2);
keep = false(1,nR);
for r = 1:nR
col = cellSlice(:,r);
keep(r) = all(cellfun(@(c) ~isempty(c) , col));
end
if ~any(keep), Y = []; return; end
Y = cellfun(@(c) c.metrics.Alpha, cellSlice(:,keep), 'UniformOutput', true);
end