few changes in WDM stuff
cleaned up the base system... but its not yet a good minimal example...
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silas (home)
199
projects/WDM/plot_BER_vs_ROP.m
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199
projects/WDM/plot_BER_vs_ROP.m
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%% =========================
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% Routine A: BER vs ROP plots
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%% =========================
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function S = plot_BER_vs_ROP(res, varargin)
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% S = plot_BER_vs_ROP(res, 'fec', 3.8e-3, 'eval_list', [], 'colormap', 'Spectral')
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%
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% Creates one BER-vs-ROP figure per evaluated distance.
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% Returns S struct with FEC crossings: S.Sffe, S.Sdfe, S.Svnle, S.Smlse, S.Sdbt
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%
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% res.* assumed: res.ffe{ch,rop,realiz,eval_distance} etc.
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p = inputParser;
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p.addParameter('fec', 3.8e-3, @(x)isnumeric(x)&&isscalar(x));
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p.addParameter('eval_list', [], @(x)isnumeric(x));
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p.addParameter('colormap', 'Spectral', @(x)ischar(x) || isstring(x));
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p.parse(varargin{:});
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fec = p.Results.fec;
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% -------------------- Basic metadata --------------------
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rop = res.settings.rop(:);
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wavelengthplan = res.settings.wavelengthplan(:);
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distances = res.eval_dist_km(:);
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N_ch = numel(wavelengthplan);
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N_rop = numel(rop);
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% -------------------- Determine dims robustly --------------------
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dims = size(res.ffe);
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if numel(dims) < 4, dims(end+1:4) = 1; end
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N_distances = dims(4);
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if numel(distances) ~= N_distances
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distances = (1:N_distances).';
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end
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% -------------------- Choose eval distances --------------------
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eval_list = p.Results.eval_list;
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if isempty(eval_list)
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eval_list = 1:N_distances;
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end
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% -------------------- Colors --------------------
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try
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cols = cbrewer2(char(p.Results.colormap), N_ch);
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catch
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cols = linspecer(N_ch);
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end
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% -------------------- Crossings containers --------------------
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S = struct();
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S.rop = rop;
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S.wavelengthplan = wavelengthplan;
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S.distances = distances;
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S.fec = fec;
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S.Sffe = cell(N_distances, N_ch);
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S.Sdfe = cell(N_distances, N_ch);
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S.Svnle = cell(N_distances, N_ch);
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S.Smlse = cell(N_distances, N_ch);
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S.Sdbt = cell(N_distances, N_ch);
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% -------------------- Plot per distance --------------------
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for eval_ptr = eval_list
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figure('Name', sprintf('BER vs ROP @ %s', distLabel(distances, eval_ptr)));
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hold on;
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for ch = 1:N_ch
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% Extract cell slices
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ffe_cells = sliceCells4D(res.ffe , ch, eval_ptr, N_rop);
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dfe_cells = sliceCells4D(res.dfe , ch, eval_ptr, N_rop);
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vnle_cells = sliceCells4D(res.vnle, ch, eval_ptr, N_rop);
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mlse_cells = sliceCells4D(res.mlse, ch, eval_ptr, N_rop);
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dbt_cells = sliceCells4D(res.dbt , ch, eval_ptr, N_rop);
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% Crossings (only depends on cells)
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[S.Sffe{eval_ptr,ch}, ~] = fecCrossings(rop, ffe_cells, fec);
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[S.Sdfe{eval_ptr,ch}, ~] = fecCrossings(rop, dfe_cells, fec);
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[S.Svnle{eval_ptr,ch}, ~] = fecCrossings(rop, vnle_cells, fec);
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[S.Smlse{eval_ptr,ch}, ~] = fecCrossings(rop, mlse_cells, fec);
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[S.Sdbt{eval_ptr,ch}, ~] = fecCrossings(rop, dbt_cells, fec);
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% BER matrices (complete realizations only)
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ffe_mat = extractCompleteBER(ffe_cells); % N_rop x K
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if ~isempty(ffe_mat)
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% Your current style: plot each realization curve (no boundedline)
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plot(rop, ffe_mat, 'Color', cols(ch,:), ...
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'DisplayName', sprintf('FFE @ %dnm', round(wavelengthplan(ch))));
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end
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end
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set(gca,'XScale','linear','YScale','log', ...
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'TickLabelInterpreter','latex','FontSize',11);
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yline([3.8e-3, 2.2e-4], 'HandleVisibility','off','LineWidth',1.5);
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ylabel('BER');
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xlabel('ROP [dB]');
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title(sprintf('BER vs. ROP @ %s', distLabel(distances, eval_ptr)));
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xlim([min(rop) max(rop)]);
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ylim([1e-5 0.3]);
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grid on;
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legend show;
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beautifyBERplot;
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end
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end
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%% =========================
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% Shared helpers (unchanged)
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%% =========================
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function cells2D = sliceCells4D(C4, ch, eval_ptr, N_rop)
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dims = size(C4);
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if numel(dims) < 4, dims(end+1:4) = 1; end
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N_realiz = dims(3);
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cells2D = cell(N_rop, N_realiz);
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chMax = dims(1);
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ropMax = dims(2);
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rMax = dims(3);
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eMax = dims(4);
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if ch > chMax || eval_ptr > eMax
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return;
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end
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ropUse = min(N_rop, ropMax);
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rUse = min(N_realiz, rMax);
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tmp = squeeze(C4(ch, 1:ropUse, 1:rUse, eval_ptr));
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tmp = reshape(tmp, ropUse, rUse);
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cells2D(1:ropUse, 1:rUse) = tmp;
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end
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function lbl = distLabel(distances, eval_ptr)
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if eval_ptr <= numel(distances)
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d = distances(eval_ptr);
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if isfinite(d)
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lbl = sprintf('%.0f km', d);
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return;
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end
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end
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lbl = sprintf('eval\\_%d', eval_ptr);
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end
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function [S, noCrossingMask] = fecCrossings(rop, cellsNxR, fec)
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Y = extractCompleteBER(cellsNxR);
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if isempty(Y)
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S = [];
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noCrossingMask = [];
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return;
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end
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ok = mean(Y,1,'omitnan') <= 0.1;
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Y = Y(:, ok);
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if isempty(Y)
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S = [];
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noCrossingMask = [];
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return;
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end
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nR = size(Y,2);
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S = nan(1,nR);
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noCrossingMask = true(1,nR);
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rop = rop(:);
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for j = 1:nR
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y = Y(:,j);
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above = (y > fec);
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idx = find(above(1:end-1) & ~above(2:end), 1, 'first');
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if ~isempty(idx)
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x1 = rop(idx); y1 = y(idx);
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x2 = rop(idx+1); y2 = y(idx+1);
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if isfinite(y1) && isfinite(y2) && y2 ~= y1
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t = (fec - y1) / (y2 - y1);
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S(j) = x1 + t*(x2 - x1);
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noCrossingMask(j) = false;
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end
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end
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end
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end
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function Y = extractCompleteBER(cellSlice)
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if isempty(cellSlice), Y = []; return; end
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nR = size(cellSlice,2);
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keep = false(1,nR);
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for r = 1:nR
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col = cellSlice(:,r);
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keep(r) = all(cellfun(@(c) ~isempty(c), col));
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end
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if ~any(keep), Y = []; return; end
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Y = cellfun(@(c) c.metrics.BER, cellSlice(:,keep), 'UniformOutput', true);
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end
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