few changes in WDM stuff
cleaned up the base system... but its not yet a good minimal example...
This commit is contained in:
silas (home)
@@ -1,325 +1,12 @@
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%% Robust eval/plot script for res.* (handles missing/partial dims)
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% res.ffe stored like: output_ffe{ch, rop, realiz, eval_distance}
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% BUT: some dimensions may be singleton or not fully filled (e.g. only 0 km, only 1 realization)
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filename = "C:\Users\Silas\Documents\MATLAB\Datensätze\FWM_2025\WDM_20260106_131152_n261_14408161_10km_16ch_400ghz_co_alpha0_5.mat";
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filename = "C:\Users\Silas\Documents\MATLAB\Datensätze\FWM_2025\WDM_20260106_131152_n262_14408165_10km_16ch_400ghz_co_alpha-0_5.mat";
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filename = "C:\Users\Silas\Documents\MATLAB\Datensätze\FWM_2025\WDM_20260106_134921_n223_14409338_10km_16ch_400ghz_co_alpha0_0.mat";
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res = load(filename,'res');
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res = res.res;
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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(:); % can be [0], [2 10], etc.
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%%
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% Routine A: plot BER curves and compute crossings
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S = plot_BER_vs_ROP(res, 'fec', 3.8e-3);
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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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% Ensure we have 4D addressing even if MATLAB collapses trailing singletons
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dims = size(res.ffe);
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if numel(dims) < 4
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dims(end+1:4) = 1;
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end
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N_realiz = dims(3);
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N_distances = dims(4);
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% If res.eval_dist_km length differs from dims(4), trust dims(4)
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if numel(distances) ~= N_distances
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% best-effort fallback
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distances = (1:N_distances).';
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end
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% -------------------- Plot settings --------------------
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fec = 3.8e-3; % choose one; you can switch to 2.2e-4 if needed
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qLow = 0.00;
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qHigh = 1.00;
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% Color per wavelength/channel
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try
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cols = ccbrewer2('Set1', N_ch);
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catch
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cols = linspecer(N_ch);
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end
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% Containers for FEC crossings per channel (per eval distance)
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Sffe = cell(N_distances, N_ch);
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Sdfe = cell(N_distances, N_ch);
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Svnle = cell(N_distances, N_ch);
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Smlse = cell(N_distances, N_ch);
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Sdbt = cell(N_distances, N_ch);
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% -------------------- Choose which eval distances to plot --------------------
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% If you want all: eval_list = 1:N_distances;
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% If you want a specific distance (e.g., last): eval_list = N_distances;
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eval_list = 1;%1:N_distances;
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% -------------------- BER vs ROP figures (one figure per eval 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 robustly: [N_rop x N_realiz] ----
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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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% ---- FEC crossings (works with incomplete columns) ----
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[Sffe{eval_ptr,ch}, ~] = fecCrossings(rop, ffe_cells, fec);
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[Sdfe{eval_ptr,ch}, ~] = fecCrossings(rop, dfe_cells, fec);
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[Svnle{eval_ptr,ch}, ~] = fecCrossings(rop, vnle_cells, fec);
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[Smlse{eval_ptr,ch}, ~] = fecCrossings(rop, mlse_cells, fec);
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[Sdbt{eval_ptr,ch}, ~] = fecCrossings(rop, dbt_cells, fec);
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% ---- Extract BER matrices using only complete realizations ----
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ffe_mat = extractCompleteBER(ffe_cells); % N_rop x K
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dfe_mat = extractCompleteBER(dfe_cells);
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vnle_mat = extractCompleteBER(vnle_cells);
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mlse_mat = extractCompleteBER(mlse_cells);
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dbt_mat = extractCompleteBER(dbt_cells);
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showLegend = (ch == 1); % one legend entry per technique
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% Plot bands + mean (only if non-empty)
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if ~isempty(ffe_mat)
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plotBandMeanBL(rop, ffe_mat, cols(ch,:), sprintf('FFE @ %dnm', round(wavelengthplan(ch))), qLow, qHigh, '--s', showLegend);
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end
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% if ~isempty(dfe_mat)
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% plotBandMeanBL(rop, dfe_mat, cols(ch,:), sprintf('DFE @ %dnm', round(wavelengthplan(ch))), qLow, qHigh, '-o', showLegend);
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% end
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% if ~isempty(vnle_mat)
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% plotBandMeanBL(rop, vnle_mat, cols(ch,:), sprintf('VNLE @ %dnm', round(wavelengthplan(ch))), qLow, qHigh, '--x', showLegend);
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% end
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% if ~isempty(mlse_mat)
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% plotBandMeanBL(rop, mlse_mat, cols(ch,:), sprintf('VNLE+PF+MLSE @ %dnm', round(wavelengthplan(ch))), qLow, qHigh, '-o', showLegend);
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% end
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% if ~isempty(dbt_mat)
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% plotBandMeanBL(rop, dbt_mat, cols(ch,:), sprintf('DBt+MLSE @ %dnm', round(wavelengthplan(ch))), qLow, qHigh, '--v', showLegend);
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% end
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end
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set(gca,'XScale','linear','YScale','log','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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end
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%% -------------------- VIOLIN of ROP at FEC crossing --------------------
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% Build technique groups; each group is {N_distances x N_ch} cell entries
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% You can pick a distance to show (e.g., eval_ptr=1 for 0 km, or last)
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eval_ptr_violin = min(N_distances, max(1, N_distances)); % default: last available
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% eval_ptr_violin = 1;
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% Choose which technique(s) to show
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techNames = {'VNLE'};
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S_groups = {Svnle(eval_ptr_violin,:)};
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% Only plot if violinplot exists
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if exist('violinplot','file') == 2
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figure('Name', sprintf('FEC crossing violin @ %s', distLabel(distances, eval_ptr_violin))); hold on;
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colsTech = linspecer(numel(S_groups));
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for i = 1:numel(S_groups)
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S_cell = S_groups{i}; % 1 x N_ch cell, each cell is 1xK crossings
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% Pad to rectangular: rows = realizations (max K), cols = wavelengths (N_ch)
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Kmax = max(cellfun(@numel, S_cell));
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if isempty(Kmax) || Kmax == 0
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continue;
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end
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S_mat = zeros(Kmax, N_ch);
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for ch = 1:N_ch
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k = numel(S_cell{ch});
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if k > 0
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S_mat(1:k, ch) = S_cell{ch}(:);
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end
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end
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catLabels = arrayfun(@(nm) sprintf('%d nm', nm), round(wavelengthplan), 'UniformOutput', false);
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violinplot(S_mat, catLabels, ...
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'ViolinColor', colsTech(i,:), ...
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'ViolinAlpha', 0.10, ...
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'MarkerSize', 20, ...
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'ShowMedian', true, ...
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'EdgeColor', colsTech(i,:), ...
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'ShowWhiskers', false, ...
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'ShowData', true, ...
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'ShowBox', false, ...
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'Bandwidth', 0.05);
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% Add a legend proxy
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plot(nan, nan, 'o', 'Color', colsTech(i,:), 'DisplayName', techNames{i});
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end
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ylim([-10,-6])
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ylabel('ROP at FEC crossing');
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title(sprintf('ROP to cross BER %.2e @ %s', fec, distLabel(distances, eval_ptr_violin)));
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grid on; box on;
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legend show;
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else
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fprintf('violinplot.m not found on path -> skipping violin plot.\n');
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end
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%% ================= helpers =================
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function cells2D = sliceCells4D(C4, ch, eval_ptr, N_rop)
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% Returns a [N_rop x N_realiz] cell array (with N_realiz inferred)
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% Works even if trailing dimensions are singleton.
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%
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% If C4 is smaller than expected, missing entries are returned as [].
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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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% bounds (in case stored arrays are smaller)
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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; % all empty
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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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% Extract and place into a consistent sized cell matrix
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tmp = squeeze(C4(ch, 1:ropUse, 1:rUse, eval_ptr));
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% squeeze may return vector/empty if rUse==1 etc. Normalize:
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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 plotBandMeanBL(x, Y, color, techLabel, qLow, qHigh, lineSpec, showLegend)
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% Y: (nPoints x nRealizations)
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if isempty(Y), return; end
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% Remove realizations that are entirely zero
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badCols = all(Y == 0, 1);
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Y(:, badCols) = [];
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if isempty(Y), return; end
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% Avoid log(0)
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Y(Y==0) = 1e-8;
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mu = mean(Y, 2, 'omitnan');
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lo = quantile(Y, qLow, 2);
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hi = quantile(Y, qHigh, 2);
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b = [mu - lo, hi - mu];
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% boundedline optional; fallback to simple plot if missing
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if 0%exist('boundedline','file') == 2
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[hl, hp] = boundedline(x(:), mu(:), b, lineSpec, 'alpha', 'transparency', 0.18);
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set(hl, 'Color', color, 'LineWidth', 1.4, 'MarkerSize', 4);
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set(hp, 'FaceColor', color, 'HandleVisibility','off');
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else
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hl = plot(x(:), mu(:), lineSpec, 'LineWidth', 1.4, 'MarkerSize', 4);
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set(hl, 'Color', color);
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end
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if showLegend
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set(hl, 'DisplayName', techLabel);
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else
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set(hl, 'HandleVisibility','off');
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end
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if 0%exist('outlinebounds','file') == 2 && exist('boundedline','file') == 2
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ho = outlinebounds(hl, hp);
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set(ho, 'linestyle', ':', 'color', color, 'linewidth', 1, 'HandleVisibility','off');
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end
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end
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function [S, noCrossingMask] = fecCrossings(rop, cellsNxR, fec)
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% cellsNxR: N_rop x R cell array; each cell is struct with .metrics.BER
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Y = extractCompleteBER(cellsNxR); % -> N_rop x K
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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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% Keep only those realization columns where ALL N_rop entries are non-empty
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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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function Y = extractCompleteAlphas(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.Alpha, cellSlice(:,keep), 'UniformOutput', true);
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end
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%% Routine B: violin plot (independent)
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plot_FEC_violin(res, 'tech','VNLE', 'fec',3.8e-3, 'eval_ptr',3, 'ylim',[-10 -3]);
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