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ML Equalizer works now.

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Not yet perfectly integrated into all the routines
This commit is contained in:
Silas Oettinghaus
2025-11-12 09:24:02 +01:00
parent 39bc8243fc
commit 0080cb2264
44 changed files with 5289 additions and 2868 deletions
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235
Classes/04_DSP/Equalizer/ML_MLSE.m
View File

@@ -1,13 +1,41 @@
classdef ML_MLSE < handle
% Implementation of plain and simple FFE.
% 1) Training mode (stable performance when you use NLMS)
% 2) Decision directed mode
%
%LMS: mu in order of 0.0001 for acceptable convergence speed
%NLMS: mu in order of 0.01 for acceptable convergence speed
%RLS: mu is lambda -> 0.99 -> 1 (has a strong dependency on this! use a loop to find out best values)
%
% FFE("epochs_tr",5,"epochs_dd",2,"len_tr",2^13,"mu_dd",mu_dd,"mu_tr",mu_tr,"order",25,"sps",2,"decide",0, "adaption",adaption_method(adaption),"dd_mode",use_dd_mode);
% ALGORITHM DESCRIBED IN:
% W. Lanneer and Y. Lefevre, “Machine Learning-Based Pre-Equalizers for
% Maximum Likelihood Sequence Estimation in High-Speed PONs,”
% in 2023 31st European Signal Processing Conference
% Further ML Refs:
% https://machinelearningmastery.com/cross-entropy-for-machine-learning/
% https://docs.pytorch.org/docs/stable/generated/torch.nn.CrossEntropyLoss.html
% The central idea is to overcome the (white-) noise assumption within the previously described
% Viterbi algorithm, more precisely a closed-loop optimization is proposed that finds a suitable
% filter-set to directly compute the branch metrics c_k (s,s^' ). These can directly be used to
% carry out the conventional Viterbi algorithm. The system consists of S^L S=F linear FIR filters,
% combined with one bias coefficient respectively. These filters take the received input samples to
% compute the branch metrics estimates (c_k ) ̂(s,s^' ) according toThe central idea is to overcome
% the (white-) noise assumption within the previously described Viterbi algorithm, more precisely
% a closed-loop optimization is proposed that finds a suitable filter-set to directly compute the
% branch metrics c_k (s,s^' ). These can directly be used to carry out the conventional Viterbi
% algorithm. The system consists of S^L S=F linear FIR filters, combined with one bias coefficient
% respectively. These filters take the received input samples to compute the branch metrics
% estimates. Finally, the usual Viterbi is carried out...
% Recommended Settings and some findings:
% Requires many training epochs. According to ML people, 100,200 or
% even up to 1000 epochs are normal for ML-convergence
% The mu parameter _can_ be adaptive - using the cross entropy and when
% analyzing the isolated training it looks very promisig. However, is
% later use I found this is not as stable as a fixed learning rate.
% mu = 0.1 worked good for me
% Longer orders/ filter length are not always better. For me order=11
% was good.
% Delay factor (delta) is good when the order is also increased. With
% order = 11, a delta of =4 shows good results
properties
sps % usually 2
@@ -24,6 +52,8 @@ classdef ML_MLSE < handle
mu_dd %weight update in dd mode
epochs_dd
adaptive_mu
constellation
L %viterbi memory length
@@ -50,11 +80,13 @@ classdef ML_MLSE < handle
w
% --- New: fast state lookup ---
true_to_state_idx
state_dict % containers.Map: key(sequence)->state index
key_fmt = '%.8g_'; % key format for sequence strings
nSym % |constellation|
ber = []
ce = ones(1,1);
end
methods
@@ -72,6 +104,8 @@ classdef ML_MLSE < handle
options.mu_dd = 1e-5;
options.epochs_dd = 5;
options.adaptive_mu = 1;
options.delta = 0;
options.traceback_depth = 1024;
@@ -180,11 +214,12 @@ classdef ML_MLSE < handle
X_viterbi = X_viterbi.logbookentry(lbdesc); % append to logbook
end
function [y,y_vit] = equalize(obj,x,d,mu,epochs,N,training)
function [y,y_ref] = equalize(obj,x,d,mu,epochs,N,training)
% ==============================================================
% FFE + Whitening + ML-Based Branch Metric Estimation + Viterbi
% ==============================================================
debug = 1;
showPlots = 1;
% --- Input padding and preallocation
y = zeros(N,1);
@@ -200,7 +235,8 @@ classdef ML_MLSE < handle
v_tilde = zeros(1,obj.nFeasible);
pred = zeros(nSymbols, obj.nStates, 'uint32');
pm_sto = nan(obj.nStates, nSymbols,'like',pm);
CE_accum = 0;
%%% START IDX
if training
@@ -210,7 +246,7 @@ classdef ML_MLSE < handle
start_sample = 1;
end_sample = start_sample + (ceil(N/obj.sps)-1)*obj.sps;
else
start_sample = 1;
start_sample = 1;%obj.len_tr;
end_sample = N;
end
@@ -251,34 +287,72 @@ classdef ML_MLSE < handle
% ===== Gradient update (Algorithm 1) =====
if 1 %training
% previous "to" becomes current "from" (shift-register)
true_from_state_idx = true_to_state_idx;
% --- Build current "to" state from ABSOLUTE symbol index
if sym_idx >= obj.L
curr_seq = d(sym_idx-obj.L+1 : sym_idx); % [d_k-L+1 ... d_k]
key_to = obj.seq_key(flip(curr_seq)); % -> [d_k ... d_k-L+1]
if isKey(obj.state_dict, key_to)
true_to_state_idx = obj.state_dict(key_to);
else
% Fall back safely (should not happen with proper constellation)
true_to_state_idx = true_from_state_idx;
end
else
% Not enough history yet for a full L-symbol state
% keep previous 'to' and 'from'
true_to_state_idx = true_to_state_idx;
true_from_state_idx = true_from_state_idx;
% --- allocate storage once
if epoch == 1 && symbol == 1
obj.true_to_state_idx = ones(ceil(N/obj.sps),1,'uint32');
end
% Dirac delta over correct extended transition (from,to)
% --- previous "to" becomes current "from"
if symbol > 1
true_from_state_idx = obj.true_to_state_idx(symbol-1);
else
true_from_state_idx = 1;
end
% --- compute or reuse "to" state
if epoch == 1
% only compute in first epoch
if sym_idx >= obj.L
key_to = obj.seq_key(flip(d(sym_idx-obj.L+1 : sym_idx)));
if isKey(obj.state_dict, key_to)
obj.true_to_state_idx(symbol) = obj.state_dict(key_to);
else
obj.true_to_state_idx(symbol) = true_from_state_idx;
end
else
obj.true_to_state_idx(symbol) = true_from_state_idx;
end
end
% --- reuse cached state from second epoch onward
true_to_state_idx = obj.true_to_state_idx(symbol);
% --- ensure valid (from,to)
dirac = zeros(obj.nFeasible,1);
dirac(obj.valid_from_idx==true_from_state_idx & ...
obj.valid_to_idx ==true_to_state_idx) = 1;
mask = obj.valid_from_idx==true_from_state_idx & ...
obj.valid_to_idx ==true_to_state_idx;
if any(mask)
dirac(mask) = 1;
else
idx = find(obj.valid_from_idx==true_from_state_idx,1,'first');
dirac(idx) = 1;
obj.true_to_state_idx(symbol) = obj.valid_to_idx(idx);
end
% softmax over -v_tilde (numerically safe shift)
p = exp(-(v_tilde - max(v_tilde)));
p = p./(sum(p)+eps);
v_shift = -(v_tilde - min(v_tilde)); % shift to small positive numbers
v_shift = min(v_shift, 100); % clamp exponent argument (≈ exp(50)=3e21)
expv = exp(v_shift);
p = expv ./ (sum(expv) + eps);
% for logging only:
CE_symbol(symbol) = -log(p(dirac==1) + eps);
if sym_idx > obj.L
CE_smooth(symbol) = 0.01*CE_symbol(symbol) + 0.99*CE_smooth(symbol-1);
else
if epoch > 1
CE_smooth(symbol) = obj.ce(end); %use ce from last epoch or =1 for very first round?!
else
CE_smooth(symbol) = CE_symbol(symbol);
end
end
CE_accum = CE_symbol(symbol) + CE_accum;
% gradient term (t - p)
dmp = (dirac - p)'; % 1×nFeasible
@@ -288,10 +362,14 @@ classdef ML_MLSE < handle
% Start updates only when the ABSOLUTE symbol index has ≥ L history
if sym_idx >= obj.L
if obj.adaptive_mu
mu_eff = CE_smooth(sym_idx);
mu_eff = max(min(mu_eff, 0.2), 1e-4);
else
mu_eff = mu;
end
obj.w = obj.w - ones(size(dL_Dw,1),1).*mu .* dL_Dw; % (Nf+1)×nFeasible
% obj.w = obj.w - mu * dL_Dw; % (Nf+1)×nFeasible
obj.w = obj.w - mu_eff .* dL_Dw; % (Nf+1)×nFeasible
end
% if debug && epoch > 2
@@ -335,42 +413,69 @@ classdef ML_MLSE < handle
viterbi_path(n-1) = pred(n, viterbi_path(n));
end
y_vit = obj.first_sym(viterbi_path);
y_ref = d(start_symbol:end);
y = obj.first_sym(viterbi_path);
if debug %&& training
if debug && training
sym_start = start_symbol;
sym_end = start_symbol + symbol - 1;
ref_slice = d(sym_start : sym_end);
err = sum(y ~= ref_slice(1:numel(y)));
ref_bits = PAMmapper(obj.S,0).demap(ref_slice);
eq_bits = PAMmapper(obj.S,0).demap(y);
[~, ~, ber, ~] = calc_ber(ref_bits, eq_bits, "skip_front", 10, "skip_end", 10, "returnErrorLocation", 1);
fprintf('Epoch: %d - BER: %.1e \n',epoch, ber);
obj.ber(epoch) = ber;
try
ref_bits = PAMmapper(obj.S,0).demap(ref_slice);
eq_bits = PAMmapper(obj.S,0).demap(y);
[~, ~, ber, ~] = calc_ber(ref_bits, eq_bits, "skip_front", 10, "skip_end", 10, "returnErrorLocation", 1);
fprintf('Epoch: %d - BER: %.1e \n',epoch, ber);
obj.ber(epoch) = ber;
catch
ser = err./length(y);
fprintf('Epoch: %d - SER: %.1e \n',epoch, ser);
end
% ser = err./length(y);
% fprintf('Epoch: %d - SER: %.1e \n',epoch, ser);
obj.ce(epoch) = CE_accum./symbol;
figure(10);
subplot(2,2,1:2);
heatmap(obj.w);
title('Filter')
subplot(2,2,3);
v_tildemat = NaN(obj.nStates, obj.nStates);
v_tildemat(obj.valid) = v_tilde; % log-domain scores
heatmap(v_tildemat);
title('Path Metrics (v_tilde)')
subplot(2,2,4);
scatter(1:symbol,pm_sto,1,'.')
% plot(1:symbol,pm_sto,'LineStyle','none')
title('Path Metric Winners')
drawnow
if showPlots
figure(10);clf
subplot(3,2,1:2);
heatmap(obj.w);
title('Filter')
subplot(3,2,3);
v_tildemat = NaN(obj.nStates, obj.nStates);
v_tildemat(obj.valid) = v_tilde; % log-domain scores
heatmap(v_tildemat);
title('Path Metrics (v_tilde)')
subplot(3,2,4);
scatter(1:symbol,pm_sto,1,'.')
title('Path Metric Winners')
subplot(3,2,5);hold on
scatter(1:symbol,CE_symbol,1,'.');
scatter(1:symbol,CE_smooth,1,'.')
title('Cross Entropy')
subplot(3,2,6); hold on
% Left y-axis: Cross Entropy (linear)
yyaxis left
scatter(1:length(obj.ce), obj.ce, 10, 's', 'filled')
ylabel('Cross Entropy')
% Right y-axis: BER (logarithmic)
yyaxis right
scatter(1:length(obj.ber), obj.ber, 10, 'd', 'filled')
set(gca, 'YScale', 'log')
ylabel('BER (log scale)')
xlim([1, epochs])
xlabel('Epoch')
title('Cross Entropy // BER')
grid on
drawnow
end
end
end
end

2
Classes/04_DSP/Sequence Detection/MLSE.m
View File

@@ -118,7 +118,7 @@ classdef MLSE < handle
elseif trellis_state_mode == 2 %simply use the states from the ref signal (should be a robust option)
obj.trellis_states = reshape(unique(data_ref),size(obj.trellis_states));
obj.trellis_states = reshape(unique(data_ref),1,length(unique(data_ref)));
elseif trellis_state_mode == 3 %use_statistical_levels

4
Classes/DataBaseHandler/Metricstruct.m
View File

@@ -16,9 +16,9 @@ classdef Metricstruct
SNR (1,1) double {mustBeNumeric} = NaN
SNR_level (:,1) double {mustBeNumeric} = []
STD (1,1) double {mustBeNumeric} = NaN
STD_level (:,1) double {mustBeNumeric, mustBeNonnegative} = []
STD_level (:,1) double = []
STDrx (1,1) double {mustBeNumeric} = NaN
STDrx_level (:,1) double {mustBeNumeric, mustBeNonnegative} = []
STDrx_level (:,1) double = []
EVM (1,1) double {mustBeNumeric} = NaN
EVM_level (:,1) double {mustBeNumeric} = []

502
Classes/Warehouse_class/functions/fwm_plots/CompleteRoutine.m → Classes/Warehouse_class/functions/phase_predist_plots/fwm_plots/CompleteRoutine.m
View File

@@ -1,251 +1,251 @@
% Script, that shows the data management routine :-)
loadExistingWareHouse = 0;
if loadExistingWareHouse
[file, path] = uigetfile();
wh = load([path filesep file]);
wh = wh.wh;
wh.showInfo;
else
% 1) Define all your parameters, best practice directly constructs a
% structure
params = struct;
params.l = [2,10];
params.dispersion = [0];
params.sgm = [0];
% params.pol = ["YXYXYXYX","YXXYYXXY","YYYYYYYY"];
params.pol = ["alternated","paired","copolarized"];
params.p_in = [3];
params.p_out = [-12,-11,-10,-9,-8,-7,-6,-5,-4,-3,-2];
params.pmd = [0.1];
params.gamma = [0.0023];
params.realization = [1:20];
params.numchannels = [16];
params.center_wavelength = floor([getSweepWavelengths(35, 50e9, 1310)] .* 1000) ./ 1000 ;
params.center_wavelength = [1285 1287 1290 1292 1295];
params.center_wavelength = 1310;
params.channelspacing = [400e9];
params.random_zdw = [0];
%wh = warehouse :-)
wh = DataStorage(params);
wh.showInfo;
wh.addStorage("ber");
wh.addStorage("totalBer");
end
%2) Simulate a bunch of data - TO BE IMPLEMENTED HERE - for now use scripts
%from Sebastian
%3) Once the simulation folder is around, specifiy path and analyze dirs
path = uigetdir('C:\Users\Silas\Documents\MATLAB\Raw_Cluster_Simulations');
allMat = getAllFilesInFolder(path,'.mat');
allErr = getAllFilesInFolder(path,'.err');
%allMat = dir([path filesep '*.mat']);
%allErr = dir([path filesep '*.err']);
if numel(allMat) == 0
warning('You defined an empty folder. Could not locate any .mat file.')
else
fprintf('%-20s', 'Err Files:'); fprintf('%-12s', num2str(numel(allErr))); fprintf('\n');
fprintf('%-20s', 'Mat Files:'); fprintf('%-12s', num2str(numel(allMat))); fprintf('\n');
fprintf('%-20s', 'Missing Mat Files:'); fprintf('%-12s', num2str(numel(allErr)-numel(allMat))); fprintf('\n');
end
%4) Now load that data
f = waitbar(0,'Please wait...');
cnt = 0;
for num = 1:numel(allMat)
fileName = allMat(num).name;
fileFolder = allMat(num).path;
fileExt = allMat(num).ext;
%
matFile = load([fileFolder filesep fileName fileExt]);
matFile = matFile.loop_data;
% ____________________________________
% FIND THE DATAPOINT CURRENTLY LOADED
zdw = 1310;
channelplan = "symmetric";
channelspacing = str2double(strrep(regexp(fileName,'(_chsp)+([\d]*)','match'),'_chsp','')).*1e9;
numchannels = str2double(strrep(regexp(fileName,'(ch)+(_)+([\d]*)','match'),'ch_',''));
center_wavelength = str2double(insertAfter(strrep(regexp(fileName,'(lambda)+([\d]*)','match'),'lambda',''),4,'.'));
center_wavelength = floor(center_wavelength * 1000) / 1000;
if center_wavelength == 2192
continue
end
center_wavelength = 1310;
random_zdw = str2double(strrep(regexp(fileName,'(rzwd)+([\d])','match'),'rzwd',''));
l = str2double(strrep(regexp(fileName,'([L])+(_)+([\d]*)','match'),'L_',''));
d = str2double(strrep(regexp(fileName,'([D])+(_)+([\d]*)','match'),'D_',''));
if d == 0
sgm = false;
else
sgm = true;
end
if numel(regexp(fileName,'(YYYY)','match')) > 1
pol = "copolarized";
elseif numel(regexp(fileName,'(YXXY)','match')) > 1
pol = "paired";
elseif numel(regexp(fileName,'(YXYX)','match')) > 1
pol = "alternated";
else
pol = "copolarized";
end
p_in = str2double(strrep(regexp(fileName,'(pow_)+([-,\d]{1})','match'),'pow_',''));
pmd = 0.1;
gamma = 0.0023;
realiz = str2double(strrep(regexp(fileName,'(r)+([-,\d]{1,3})','match'),'r',''));
% ____________________________________
% Get the information you want from current file
rop=[];
ber = [];
for pow = 2:12
module_number = '';
for p = 1:11 %11 because there are 11 ROP branches in model
% get ROP
if p == 1
p_out = matFile.dp_optatten_para.atten;
else
p_out = matFile.("dp_optatten__"+(p)+"_para").atten;
end
p_out = round(p_out-10*log10(numel(matFile.config.parameters.common.wavelengthPlan)));
for c = 1:numel(matFile.config.parameters.common.wavelengthPlan)
ber(c) = matFile.("prms_compare_wdm__"+(p+1)+"_out"){1,c}.ber;
end
totalBer = matFile.("prms_compare_wdm__"+(p+1)+"_out"){1,end}.totalBer;
if totalBer > 0.2 && channelspacing == 400e9 && pol == "alternated"
disp("stopping here");
pause;
end
% ____________________________________
% Add value to warehouse at the correct position
wh.addValueToStorage(ber,'ber',l,d,sgm,pol,p_in,p_out,pmd,gamma,realiz,numchannels, center_wavelength,channelspacing,random_zdw);
wh.getStoValue('ber',l,d,sgm,pol,p_in,p_out,pmd,gamma,realiz,numchannels, center_wavelength,channelspacing,random_zdw);
wh.addValueToStorage(totalBer,'totalBer',l,d,sgm,pol,p_in,p_out,pmd,gamma,realiz,numchannels,center_wavelength,channelspacing,random_zdw);
end
end
waitbar(num/numel(allMat),f,'Loading your data');
end
close(f)
% 4) Hey! the warehouse is here and (hopefully) filled with data :-)
% Create a save dialog
defaultDir = 'C:\Users\Silas\Documents\MATLAB\Raw_Cluster_Simulations\';
defaultExt = '*.mat';
[filename, pathname] = uiputfile(fullfile(defaultDir, defaultExt),'', 'wh.mat');
% Check if the user pressed Cancel
if isequal(filename, 0) || isequal(pathname, 0)
disp('Save operation canceled.');
else
% Save the variable to the selected file
save(fullfile(pathname, filename), 'wh');
disp(['Variable "wh" saved to: ', fullfile(pathname, filename)]);
end
function matFileStructArray = getAllFilesInFolder(folderPath,extension)
% Get a list of all files in the current folder
currentFolderFiles = dir(fullfile(folderPath, '*'));
% Exclude '.' and '..' directories
currentFolderFiles = currentFolderFiles(~ismember({currentFolderFiles.name}, {'.', '..'}));
% Initialize the structure array for .mat files
matFileStructArray = struct('path', {}, 'name', {}, 'ext', {});
% Loop over each file in the current folder
for i = 1:length(currentFolderFiles)
currentFile = currentFolderFiles(i);
% Check if the current item is a file and has a .mat extension
if ~currentFile.isdir && endsWith(currentFile.name, extension, 'IgnoreCase', true)
% If it's a .mat file, add it to the structure array
[matFileStructArray(end + 1).path,matFileStructArray(end+1).name, matFileStructArray(end+1).ext] = fileparts(fullfile(folderPath, currentFile.name));
elseif currentFile.isdir
% If it's a directory, recursively call the function
subfolderPath = fullfile(folderPath, currentFile.name);
subfolderMatFiles = getAllFilesInFolder(subfolderPath,extension);
% Add .mat files from the subfolder to the structure array
matFileStructArray = [matFileStructArray, subfolderMatFiles];
end
end
end
% Script, that shows the data management routine :-)
loadExistingWareHouse = 0;
if loadExistingWareHouse
[file, path] = uigetfile();
wh = load([path filesep file]);
wh = wh.wh;
wh.showInfo;
else
% 1) Define all your parameters, best practice directly constructs a
% structure
params = struct;
params.l = [2,10];
params.dispersion = [0];
params.sgm = [0];
% params.pol = ["YXYXYXYX","YXXYYXXY","YYYYYYYY"];
params.pol = ["alternated","paired","copolarized"];
params.p_in = [3];
params.p_out = [-12,-11,-10,-9,-8,-7,-6,-5,-4,-3,-2];
params.pmd = [0.1];
params.gamma = [0.0023];
params.realization = [1:20];
params.numchannels = [16];
params.center_wavelength = floor([getSweepWavelengths(35, 50e9, 1310)] .* 1000) ./ 1000 ;
params.center_wavelength = [1285 1287 1290 1292 1295];
params.center_wavelength = 1310;
params.channelspacing = [400e9];
params.random_zdw = [0];
%wh = warehouse :-)
wh = DataStorage(params);
wh.showInfo;
wh.addStorage("ber");
wh.addStorage("totalBer");
end
%2) Simulate a bunch of data - TO BE IMPLEMENTED HERE - for now use scripts
%from Sebastian
%3) Once the simulation folder is around, specifiy path and analyze dirs
path = uigetdir('C:\Users\Silas\Documents\MATLAB\Raw_Cluster_Simulations');
allMat = getAllFilesInFolder(path,'.mat');
allErr = getAllFilesInFolder(path,'.err');
%allMat = dir([path filesep '*.mat']);
%allErr = dir([path filesep '*.err']);
if numel(allMat) == 0
warning('You defined an empty folder. Could not locate any .mat file.')
else
fprintf('%-20s', 'Err Files:'); fprintf('%-12s', num2str(numel(allErr))); fprintf('\n');
fprintf('%-20s', 'Mat Files:'); fprintf('%-12s', num2str(numel(allMat))); fprintf('\n');
fprintf('%-20s', 'Missing Mat Files:'); fprintf('%-12s', num2str(numel(allErr)-numel(allMat))); fprintf('\n');
end
%4) Now load that data
f = waitbar(0,'Please wait...');
cnt = 0;
for num = 1:numel(allMat)
fileName = allMat(num).name;
fileFolder = allMat(num).path;
fileExt = allMat(num).ext;
%
matFile = load([fileFolder filesep fileName fileExt]);
matFile = matFile.loop_data;
% ____________________________________
% FIND THE DATAPOINT CURRENTLY LOADED
zdw = 1310;
channelplan = "symmetric";
channelspacing = str2double(strrep(regexp(fileName,'(_chsp)+([\d]*)','match'),'_chsp','')).*1e9;
numchannels = str2double(strrep(regexp(fileName,'(ch)+(_)+([\d]*)','match'),'ch_',''));
center_wavelength = str2double(insertAfter(strrep(regexp(fileName,'(lambda)+([\d]*)','match'),'lambda',''),4,'.'));
center_wavelength = floor(center_wavelength * 1000) / 1000;
if center_wavelength == 2192
continue
end
center_wavelength = 1310;
random_zdw = str2double(strrep(regexp(fileName,'(rzwd)+([\d])','match'),'rzwd',''));
l = str2double(strrep(regexp(fileName,'([L])+(_)+([\d]*)','match'),'L_',''));
d = str2double(strrep(regexp(fileName,'([D])+(_)+([\d]*)','match'),'D_',''));
if d == 0
sgm = false;
else
sgm = true;
end
if numel(regexp(fileName,'(YYYY)','match')) > 1
pol = "copolarized";
elseif numel(regexp(fileName,'(YXXY)','match')) > 1
pol = "paired";
elseif numel(regexp(fileName,'(YXYX)','match')) > 1
pol = "alternated";
else
pol = "copolarized";
end
p_in = str2double(strrep(regexp(fileName,'(pow_)+([-,\d]{1})','match'),'pow_',''));
pmd = 0.1;
gamma = 0.0023;
realiz = str2double(strrep(regexp(fileName,'(r)+([-,\d]{1,3})','match'),'r',''));
% ____________________________________
% Get the information you want from current file
rop=[];
ber = [];
for pow = 2:12
module_number = '';
for p = 1:11 %11 because there are 11 ROP branches in model
% get ROP
if p == 1
p_out = matFile.dp_optatten_para.atten;
else
p_out = matFile.("dp_optatten__"+(p)+"_para").atten;
end
p_out = round(p_out-10*log10(numel(matFile.config.parameters.common.wavelengthPlan)));
for c = 1:numel(matFile.config.parameters.common.wavelengthPlan)
ber(c) = matFile.("prms_compare_wdm__"+(p+1)+"_out"){1,c}.ber;
end
totalBer = matFile.("prms_compare_wdm__"+(p+1)+"_out"){1,end}.totalBer;
if totalBer > 0.2 && channelspacing == 400e9 && pol == "alternated"
disp("stopping here");
pause;
end
% ____________________________________
% Add value to warehouse at the correct position
wh.addValueToStorage(ber,'ber',l,d,sgm,pol,p_in,p_out,pmd,gamma,realiz,numchannels, center_wavelength,channelspacing,random_zdw);
wh.getStoValue('ber',l,d,sgm,pol,p_in,p_out,pmd,gamma,realiz,numchannels, center_wavelength,channelspacing,random_zdw);
wh.addValueToStorage(totalBer,'totalBer',l,d,sgm,pol,p_in,p_out,pmd,gamma,realiz,numchannels,center_wavelength,channelspacing,random_zdw);
end
end
waitbar(num/numel(allMat),f,'Loading your data');
end
close(f)
% 4) Hey! the warehouse is here and (hopefully) filled with data :-)
% Create a save dialog
defaultDir = 'C:\Users\Silas\Documents\MATLAB\Raw_Cluster_Simulations\';
defaultExt = '*.mat';
[filename, pathname] = uiputfile(fullfile(defaultDir, defaultExt),'', 'wh.mat');
% Check if the user pressed Cancel
if isequal(filename, 0) || isequal(pathname, 0)
disp('Save operation canceled.');
else
% Save the variable to the selected file
save(fullfile(pathname, filename), 'wh');
disp(['Variable "wh" saved to: ', fullfile(pathname, filename)]);
end
function matFileStructArray = getAllFilesInFolder(folderPath,extension)
% Get a list of all files in the current folder
currentFolderFiles = dir(fullfile(folderPath, '*'));
% Exclude '.' and '..' directories
currentFolderFiles = currentFolderFiles(~ismember({currentFolderFiles.name}, {'.', '..'}));
% Initialize the structure array for .mat files
matFileStructArray = struct('path', {}, 'name', {}, 'ext', {});
% Loop over each file in the current folder
for i = 1:length(currentFolderFiles)
currentFile = currentFolderFiles(i);
% Check if the current item is a file and has a .mat extension
if ~currentFile.isdir && endsWith(currentFile.name, extension, 'IgnoreCase', true)
% If it's a .mat file, add it to the structure array
[matFileStructArray(end + 1).path,matFileStructArray(end+1).name, matFileStructArray(end+1).ext] = fileparts(fullfile(folderPath, currentFile.name));
elseif currentFile.isdir
% If it's a directory, recursively call the function
subfolderPath = fullfile(folderPath, currentFile.name);
subfolderMatFiles = getAllFilesInFolder(subfolderPath,extension);
% Add .mat files from the subfolder to the structure array
matFileStructArray = [matFileStructArray, subfolderMatFiles];
end
end
end

500
Classes/Warehouse_class/functions/fwm_plots/CompleteRoutine_DifferentChannels_Fig3.m → Classes/Warehouse_class/functions/phase_predist_plots/fwm_plots/CompleteRoutine_DifferentChannels_Fig3.m
View File

@@ -1,250 +1,250 @@
% Script, that shows the data management routine :-)
loadExistingWareHouse = 0;
if loadExistingWareHouse
[file, path] = uigetfile();
wh = load([path filesep file]);
wh = wh.wh;
wh.showInfo;
else
% 1) Define all your parameters, best practice directly constructs a
% structure
params = struct;
params.l = [2, 10];
params.dispersion = [0, 3];
params.sgm = [0, 1];
% params.pol = ["YXYXYXYX","YXXYYXXY","YYYYYYYY"];
params.pol = ["alternated","paired","copolarized"];
params.p_in = [3];
params.p_out = [-12,-11,-10,-9,-8,-7,-6,-5,-4,-3,-2];
params.pmd = [0.1];
params.gamma = [0.0023];
params.realization = [1:20];
params.numchannels = [1,2,4,8,16];
params.center_wavelength = floor([getSweepWavelengths(35, 50e9, 1310)] .* 1000) ./ 1000 ;
params.center_wavelength = [1285 1287 1290 1292 1295];
params.center_wavelength = 1310;
params.channelspacing = [400e9];
params.random_zdw = [0,1];
%wh = warehouse :-)
wh = DataStorage(params);
wh.showInfo;
wh.addStorage("ber");
wh.addStorage("totalBer");
end
%2) Simulate a bunch of data - TO BE IMPLEMENTED HERE - for now use scripts
%from Sebastian
%3) Once the simulation folder is around, specifiy path and analyze dirs
path = uigetdir('C:\Users\Silas\Documents\MATLAB\Raw_Cluster_Simulations');
allMat = getAllFilesInFolder(path,'.mat');
allErr = getAllFilesInFolder(path,'.err');
%allMat = dir([path filesep '*.mat']);
%allErr = dir([path filesep '*.err']);
if numel(allMat) == 0
warning('You defined an empty folder. Could not locate any .mat file.')
else
fprintf('%-20s', 'Err Files:'); fprintf('%-12s', num2str(numel(allErr))); fprintf('\n');
fprintf('%-20s', 'Mat Files:'); fprintf('%-12s', num2str(numel(allMat))); fprintf('\n');
fprintf('%-20s', 'Missing Mat Files:'); fprintf('%-12s', num2str(numel(allErr)-numel(allMat))); fprintf('\n');
end
%4) Now load that data
f = waitbar(0,'Please wait...');
cnt = 0;
for num = 1:numel(allMat)
fileName = allMat(num).name;
fileFolder = allMat(num).path;
fileExt = allMat(num).ext;
%
matFile = load([fileFolder filesep fileName fileExt]);
matFile = matFile.loop_data;
% ____________________________________
% FIND THE DATAPOINT CURRENTLY LOADED
zdw = 1310;
channelplan = "symmetric";
channelspacing = str2double(strrep(regexp(fileName,'(_chsp)+([\d]*)','match'),'_chsp','')).*1e9;
numchannels = str2double(strrep(regexp(fileName,'(ch)+(_)+([\d]*)','match'),'ch_',''));
center_wavelength = str2double(insertAfter(strrep(regexp(fileName,'(lambda)+([\d]*)','match'),'lambda',''),4,'.'));
center_wavelength = floor(center_wavelength * 1000) / 1000;
if center_wavelength == 2192
continue
end
center_wavelength = 1310;
random_zdw = str2double(strrep(regexp(fileName,'(rzwd)+([\d])','match'),'rzwd',''));
l = str2double(strrep(regexp(fileName,'([L])+(_)+([\d]*)','match'),'L_',''));
d = str2double(strrep(regexp(fileName,'([D])+(_)+([\d]*)','match'),'D_',''));
if d == 0
sgm = false;
else
sgm = true;
end
if numel(regexp(fileName,'(YYYY)','match')) > 1
pol = "copolarized";
elseif numel(regexp(fileName,'(YXXY)','match')) > 1
pol = "paired";
elseif numel(regexp(fileName,'(YXYX)','match')) > 1
pol = "alternated";
else
pol = "copolarized";
end
p_in = str2double(strrep(regexp(fileName,'(pow_)+([-,\d]{1})','match'),'pow_',''));
pmd = 0.1;
gamma = 0.0023;
realiz = str2double(strrep(regexp(fileName,'(r)+([-,\d]{1,3})','match'),'r',''));
% ____________________________________
% Get the information you want from current file
rop=[];
ber = [];
for pow = 2:12
module_number = '';
for p = 1:11 %11 because there are 11 ROP branches in model
% get ROP
if p == 1
p_out = matFile.dp_optatten_para.atten;
else
p_out = matFile.("dp_optatten__"+(p)+"_para").atten;
end
p_out = round(p_out-10*log10(numel(matFile.config.parameters.common.wavelengthPlan)));
for c = 1:numel(matFile.config.parameters.common.wavelengthPlan)
ber(c) = matFile.("prms_compare_wdm__"+(p+1)+"_out"){1,c}.ber;
end
totalBer = matFile.("prms_compare_wdm__"+(p+1)+"_out"){1,end}.totalBer;
if totalBer > 0.2 && channelspacing == 400e9 && pol == "alternated"
disp("stopping here");
pause;
end
% ____________________________________
% Add value to warehouse at the correct position
wh.addValueToStorage(ber,'ber',l,d,sgm,pol,p_in,p_out,pmd,gamma,realiz,numchannels, center_wavelength,channelspacing,random_zdw);
wh.getStoValue('ber',l,d,sgm,pol,p_in,p_out,pmd,gamma,realiz,numchannels, center_wavelength,channelspacing,random_zdw);
wh.addValueToStorage(totalBer,'totalBer',l,d,sgm,pol,p_in,p_out,pmd,gamma,realiz,numchannels,center_wavelength,channelspacing,random_zdw);
end
end
waitbar(num/numel(allMat),f,'Loading your data');
end
close(f)
% 4) Hey! the warehouse is here and (hopefully) filled with data :-)
% Create a save dialog
defaultDir = 'C:\Users\Silas\Documents\MATLAB\Raw_Cluster_Simulations\';
defaultExt = '*.mat';
[filename, pathname] = uiputfile(fullfile(defaultDir, defaultExt),'', 'wh.mat');
% Check if the user pressed Cancel
if isequal(filename, 0) || isequal(pathname, 0)
disp('Save operation canceled.');
else
% Save the variable to the selected file
save(fullfile(pathname, filename), 'wh');
disp(['Variable "wh" saved to: ', fullfile(pathname, filename)]);
end
function matFileStructArray = getAllFilesInFolder(folderPath,extension)
% Get a list of all files in the current folder
currentFolderFiles = dir(fullfile(folderPath, '*'));
% Exclude '.' and '..' directories
currentFolderFiles = currentFolderFiles(~ismember({currentFolderFiles.name}, {'.', '..'}));
% Initialize the structure array for .mat files
matFileStructArray = struct('path', {}, 'name', {}, 'ext', {});
% Loop over each file in the current folder
for i = 1:length(currentFolderFiles)
currentFile = currentFolderFiles(i);
% Check if the current item is a file and has a .mat extension
if ~currentFile.isdir && endsWith(currentFile.name, extension, 'IgnoreCase', true)
% If it's a .mat file, add it to the structure array
[matFileStructArray(end + 1).path,matFileStructArray(end+1).name, matFileStructArray(end+1).ext] = fileparts(fullfile(folderPath, currentFile.name));
elseif currentFile.isdir
% If it's a directory, recursively call the function
subfolderPath = fullfile(folderPath, currentFile.name);
subfolderMatFiles = getAllFilesInFolder(subfolderPath,extension);
% Add .mat files from the subfolder to the structure array
matFileStructArray = [matFileStructArray, subfolderMatFiles];
end
end
end
% Script, that shows the data management routine :-)
loadExistingWareHouse = 0;
if loadExistingWareHouse
[file, path] = uigetfile();
wh = load([path filesep file]);
wh = wh.wh;
wh.showInfo;
else
% 1) Define all your parameters, best practice directly constructs a
% structure
params = struct;
params.l = [2, 10];
params.dispersion = [0, 3];
params.sgm = [0, 1];
% params.pol = ["YXYXYXYX","YXXYYXXY","YYYYYYYY"];
params.pol = ["alternated","paired","copolarized"];
params.p_in = [3];
params.p_out = [-12,-11,-10,-9,-8,-7,-6,-5,-4,-3,-2];
params.pmd = [0.1];
params.gamma = [0.0023];
params.realization = [1:20];
params.numchannels = [1,2,4,8,16];
params.center_wavelength = floor([getSweepWavelengths(35, 50e9, 1310)] .* 1000) ./ 1000 ;
params.center_wavelength = [1285 1287 1290 1292 1295];
params.center_wavelength = 1310;
params.channelspacing = [400e9];
params.random_zdw = [0,1];
%wh = warehouse :-)
wh = DataStorage(params);
wh.showInfo;
wh.addStorage("ber");
wh.addStorage("totalBer");
end
%2) Simulate a bunch of data - TO BE IMPLEMENTED HERE - for now use scripts
%from Sebastian
%3) Once the simulation folder is around, specifiy path and analyze dirs
path = uigetdir('C:\Users\Silas\Documents\MATLAB\Raw_Cluster_Simulations');
allMat = getAllFilesInFolder(path,'.mat');
allErr = getAllFilesInFolder(path,'.err');
%allMat = dir([path filesep '*.mat']);
%allErr = dir([path filesep '*.err']);
if numel(allMat) == 0
warning('You defined an empty folder. Could not locate any .mat file.')
else
fprintf('%-20s', 'Err Files:'); fprintf('%-12s', num2str(numel(allErr))); fprintf('\n');
fprintf('%-20s', 'Mat Files:'); fprintf('%-12s', num2str(numel(allMat))); fprintf('\n');
fprintf('%-20s', 'Missing Mat Files:'); fprintf('%-12s', num2str(numel(allErr)-numel(allMat))); fprintf('\n');
end
%4) Now load that data
f = waitbar(0,'Please wait...');
cnt = 0;
for num = 1:numel(allMat)
fileName = allMat(num).name;
fileFolder = allMat(num).path;
fileExt = allMat(num).ext;
%
matFile = load([fileFolder filesep fileName fileExt]);
matFile = matFile.loop_data;
% ____________________________________
% FIND THE DATAPOINT CURRENTLY LOADED
zdw = 1310;
channelplan = "symmetric";
channelspacing = str2double(strrep(regexp(fileName,'(_chsp)+([\d]*)','match'),'_chsp','')).*1e9;
numchannels = str2double(strrep(regexp(fileName,'(ch)+(_)+([\d]*)','match'),'ch_',''));
center_wavelength = str2double(insertAfter(strrep(regexp(fileName,'(lambda)+([\d]*)','match'),'lambda',''),4,'.'));
center_wavelength = floor(center_wavelength * 1000) / 1000;
if center_wavelength == 2192
continue
end
center_wavelength = 1310;
random_zdw = str2double(strrep(regexp(fileName,'(rzwd)+([\d])','match'),'rzwd',''));
l = str2double(strrep(regexp(fileName,'([L])+(_)+([\d]*)','match'),'L_',''));
d = str2double(strrep(regexp(fileName,'([D])+(_)+([\d]*)','match'),'D_',''));
if d == 0
sgm = false;
else
sgm = true;
end
if numel(regexp(fileName,'(YYYY)','match')) > 1
pol = "copolarized";
elseif numel(regexp(fileName,'(YXXY)','match')) > 1
pol = "paired";
elseif numel(regexp(fileName,'(YXYX)','match')) > 1
pol = "alternated";
else
pol = "copolarized";
end
p_in = str2double(strrep(regexp(fileName,'(pow_)+([-,\d]{1})','match'),'pow_',''));
pmd = 0.1;
gamma = 0.0023;
realiz = str2double(strrep(regexp(fileName,'(r)+([-,\d]{1,3})','match'),'r',''));
% ____________________________________
% Get the information you want from current file
rop=[];
ber = [];
for pow = 2:12
module_number = '';
for p = 1:11 %11 because there are 11 ROP branches in model
% get ROP
if p == 1
p_out = matFile.dp_optatten_para.atten;
else
p_out = matFile.("dp_optatten__"+(p)+"_para").atten;
end
p_out = round(p_out-10*log10(numel(matFile.config.parameters.common.wavelengthPlan)));
for c = 1:numel(matFile.config.parameters.common.wavelengthPlan)
ber(c) = matFile.("prms_compare_wdm__"+(p+1)+"_out"){1,c}.ber;
end
totalBer = matFile.("prms_compare_wdm__"+(p+1)+"_out"){1,end}.totalBer;
if totalBer > 0.2 && channelspacing == 400e9 && pol == "alternated"
disp("stopping here");
pause;
end
% ____________________________________
% Add value to warehouse at the correct position
wh.addValueToStorage(ber,'ber',l,d,sgm,pol,p_in,p_out,pmd,gamma,realiz,numchannels, center_wavelength,channelspacing,random_zdw);
wh.getStoValue('ber',l,d,sgm,pol,p_in,p_out,pmd,gamma,realiz,numchannels, center_wavelength,channelspacing,random_zdw);
wh.addValueToStorage(totalBer,'totalBer',l,d,sgm,pol,p_in,p_out,pmd,gamma,realiz,numchannels,center_wavelength,channelspacing,random_zdw);
end
end
waitbar(num/numel(allMat),f,'Loading your data');
end
close(f)
% 4) Hey! the warehouse is here and (hopefully) filled with data :-)
% Create a save dialog
defaultDir = 'C:\Users\Silas\Documents\MATLAB\Raw_Cluster_Simulations\';
defaultExt = '*.mat';
[filename, pathname] = uiputfile(fullfile(defaultDir, defaultExt),'', 'wh.mat');
% Check if the user pressed Cancel
if isequal(filename, 0) || isequal(pathname, 0)
disp('Save operation canceled.');
else
% Save the variable to the selected file
save(fullfile(pathname, filename), 'wh');
disp(['Variable "wh" saved to: ', fullfile(pathname, filename)]);
end
function matFileStructArray = getAllFilesInFolder(folderPath,extension)
% Get a list of all files in the current folder
currentFolderFiles = dir(fullfile(folderPath, '*'));
% Exclude '.' and '..' directories
currentFolderFiles = currentFolderFiles(~ismember({currentFolderFiles.name}, {'.', '..'}));
% Initialize the structure array for .mat files
matFileStructArray = struct('path', {}, 'name', {}, 'ext', {});
% Loop over each file in the current folder
for i = 1:length(currentFolderFiles)
currentFile = currentFolderFiles(i);
% Check if the current item is a file and has a .mat extension
if ~currentFile.isdir && endsWith(currentFile.name, extension, 'IgnoreCase', true)
% If it's a .mat file, add it to the structure array
[matFileStructArray(end + 1).path,matFileStructArray(end+1).name, matFileStructArray(end+1).ext] = fileparts(fullfile(folderPath, currentFile.name));
elseif currentFile.isdir
% If it's a directory, recursively call the function
subfolderPath = fullfile(folderPath, currentFile.name);
subfolderMatFiles = getAllFilesInFolder(subfolderPath,extension);
% Add .mat files from the subfolder to the structure array
matFileStructArray = [matFileStructArray, subfolderMatFiles];
end
end
end

830
Classes/Warehouse_class/functions/fwm_plots/automate_JLT_plots.m → Classes/Warehouse_class/functions/phase_predist_plots/fwm_plots/automate_JLT_plots.m
View File

@@ -1,415 +1,415 @@
%automate plots
[file, path] = uigetfile("C:\Users\Silas\Documents\MATLAB\Datensätze\Raw_Cluster_Simulations\session_februar_24\wh_mi_nacht.mat");
wh = load([path filesep file]);
wh = wh.wh;
% fields = fieldnames(wh.parameter);
% for k = 1:numel(fields)
% oldParam = wh.parameter.(fields{k});
% % copy over the properties to your new class
% wh.parameter.(fields{k}) = StorageParameter(...
% oldParam.Name, oldParam.values);
% end
%
plotJob = struct();
width = 350;
height = 200;
plotJob.Position = [100 100 width 100+height];
cols = cbrewer2("paired",12);
plotJob.color = cols(1,:);
plotJob.l = 2;
plotJob.ch = 16;
plotJob.d = 0;
plotJob.sgm = 0;
plotJob.pol = "copolarized";
plotJob.p_in = 3;
plotJob.gamma = 0.0023;
plotJob.pmd = 0.1;
plotJob.channelspacing = 400e9;
plotJob.randzdw = 0;
plotJob.plot_ber_curve = 0;
plotJob.plot_3dber_curve = 0;
plotJob.plot_violin = 1;
plotJob.plot_wavelength_sweep = 0;
plotJob.plot_wavelength_sweep_failure_rate = 0;
plotJob.dataStatArg = 'Lineplot with quartiles';
plotJob.plotTypeArg = 'Lines';
plotJob.displayname = 'a';
plotJob.title = 'title';
plotJob.figName = '16 Chann';
plotJob.xAxisLabel = 'ROP per Channel in dBm';
plotJob.yAxisLabel = 'BER';
%%
% createbercurves(wh,plotJob)
P = [3,6];
for i = 1:2
plotJob.p_in = P(i);
createviolinplots(wh,plotJob);
end
% createsweepplots(wh,plotJob);
%% 1
function createbercurves(wh,plotJob)
width = 1650;
height = 400;
s = 100;
e = 100;
cols = cbrewer2("paired",12);
numRows = 2;
numCols = 4;
plotJob.figName = '16 Chann_200G';
plotJob.channelspacing = 400e9;
plotJob.ch = 16;
Len = [2,2,2,2,10,10,10,10];
Pol = ["copolarized","alternated","paired","copolarized","copolarized","alternated","paired","copolarized"];
Title = ["Co Polarized","Alternating Pol. Interl.","Paired Pol. Interl.","Link Segmentation",];
D = [0,0,0,3,0,0,0,3];
Sgm = [0,0,0,1,0,0,0,1];
colidx = [4,8,6];
P_launch = [3,6];
fig = figure('Name',plotJob.figName);
fig.Position = plotJob.Position;
fig.Units = "centimeters";
fig.Position = [0 0 18 7];
t = tiledlayout(numRows,numCols,'TileSpacing','compact','Padding','compact');
for idx = 1:(numRows * numCols)
% Create subplot
% sp = subplot(numRows, numCols, idx);
nexttile;
plotJob.l = Len(idx);
plotJob.pol = Pol(idx);
plotJob.d = D(idx);
plotJob.sgm = Sgm(idx);
plotJob.randzdw = 1;
for i = 1:length(P_launch)
plotJob.p_in = P_launch(i);
plotJob.color = cols(colidx(i),:);
hold on
plotCurve(wh, plotJob);
end
%
if idx ~= 1 && idx ~= 5 % For example, hide y-axis for subplot 1
set(gca, 'YTickLabel',[]); % Hide y-axis ticks and labels
set(gca,'YGrid','on');
set(gca, 'YLabel', []);
end
if idx ~= 5 && idx ~= 6 && idx ~= 7 && idx ~= 8
set(gca, 'XLabel', []);
set(gca, 'XTickLabel', []);
end
grid on
g = gca;
pos = g.Position;
if idx <= 4
title(Title(idx),'FontSize',8);
% a = annotation('textbox', pos-[0.0020 -0.1434 0.0947 0.3121], 'String', "FEC: 3.8e-3","LineStyle","none","FontSize",8,'LineWidth',0.1,'Interpreter','latex',"FontUnits","points",'Vert','middle','FitBoxToText','on');
% a = annotation('textbox', pos, 'String', "2 km","LineStyle","none","FontSize",8,'LineWidth',0.1,'Interpreter','latex',"FontUnits","points",'Vert','bottom','FitBoxToText','on');
else
% a = annotation('textbox', pos, 'String', "FEC: 3.8e-3","LineStyle","none","FontSize",8,'LineWidth',0.1,'Interpreter','latex',"FontUnits","points",'Vert','middle','FitBoxToText','on');
% a = annotation('textbox', pos, 'String', "10 km","LineStyle","none","FontSize",8,'LineWidth',0.1,'Interpreter','latex',"FontUnits","points",'Vert','bottom','FitBoxToText','on');
end
end
% Create textbox
annotation(fig,'textbox',...
[0.0696078431372547 0.246851385390432 0.0656862745098043 0.0453400503778337],...
'String','10 km',...
'LineStyle','none',...
'Interpreter','latex',...
'FontSize',8,...
'FitBoxToText','off');
% Create textbox
annotation(fig,'textbox',...
[0.288235294117647 0.239294710327459 0.0656862745098043 0.0453400503778338],...
'String','10 km',...
'LineStyle','none',...
'Interpreter','latex',...
'FontSize',8,...
'FitBoxToText','off');
% Create textbox
annotation(fig,'textbox',...
[0.516666666666666 0.241813602015117 0.0656862745098042 0.0453400503778338],...
'String','10 km',...
'LineStyle','none',...
'Interpreter','latex',...
'FontSize',8,...
'FitBoxToText','off');
% Create textbox
annotation(fig,'textbox',...
[0.742156862745097 0.236775818639802 0.0656862745098042 0.0453400503778339],...
'String','10 km',...
'LineStyle','none',...
'Interpreter','latex',...
'FontSize',8,...
'FitBoxToText','off');
% Create textbox
annotation(fig,'textbox',...
[0.071996471804854 0.578899159967702 0.0656862745098039 0.0453400503778341],...
'String',{'2 km'},...
'LineStyle','none',...
'Interpreter','latex',...
'FontSize',8,...
'FitBoxToText','off');
% Create textbox
annotation(fig,'textbox',...
[0.29596893566113 0.576253721089996 0.0656862745098041 0.0453400503778341],...
'String',{'2 km'},...
'LineStyle','none',...
'Interpreter','latex',...
'FontSize',8,...
'FitBoxToText','off');
% Create textbox
annotation(fig,'textbox',...
[0.524883914268912 0.580785315705112 0.0656862745098041 0.0453400503778341],...
'String',{'2 km'},...
'LineStyle','none',...
'Interpreter','latex',...
'FontSize',8,...
'FitBoxToText','off');
% Create textbox
annotation(fig,'textbox',...
[0.753758338909501 0.581291504465311 0.0656862745098037 0.0453400503778341],...
'String',{'2 km'},...
'LineStyle','none',...
'Interpreter','latex',...
'FontSize',8,...
'FitBoxToText','off');
a=sgtitle(['N=',num2str(plotJob.ch),'; $\Delta f_{\mathrm{ch}}$= ',num2str(plotJob.channelspacing*1e-9),' GHz'],'FontSIze',10);
a.Interpreter = "latex";
lgd = legend('$P_{\mathrm{in}}=0$ dBm','$P_{\mathrm{in}}=3$ dBm','$P_{\mathrm{in}}=6$ dBm','Interpreter','latex');
lgd.NumColumns = 3;
lgd.Layout.Tile = 'south';
copygraphics(t,'BackgroundColor','none');
end
%% 2
function createviolinplots(wh,plotJob)
width = 350;
height = 200;
s = 100;
e = 100;
cols = cbrewer2("paired",12);
numRows = 1;
numCols = 4;
plotJob.ch = 16;
plotJob.randzdw = 1;
Pol = ["copolarized","copolarized","alternated","paired",];
Title = ["Co Pol.","Link Segmentation","Paired Pol. Interl.","Alternating Pol. Interl."];
D = [0,3,0,0];
Sgm = [0,1,0,0];
colidx = [3];
Len = [10];
fig = findall(groot, 'Type', 'figure', 'Name', plotJob.figName);
if isvalid(fig)
figure(fig)
% fig = get(fig);
AxesMain = fig.CurrentAxes;
hold on
% t = tiledlayout(1,4,'TileSpacing','compact','Padding','compact');
else
fig = figure('name',char(plotJob.figName));
AxesMain = gca;
hold on; grid on;
% t = tiledlayout(1,4,'TileSpacing','compact','Padding','compact');
end
for idx = 1:(numRows * numCols)
% Create subplot
subplot(numRows, numCols, idx);
plotJob.pol = Pol(idx);
plotJob.d = D(idx);
plotJob.sgm = Sgm(idx);
for i = 1
plotJob.color = cols(colidx(i),:);
plotJob.l = Len(i);
hold on
plotViolin(wh, plotJob);
end
if idx ~= 1 % For example, hide y-axis for subplot 1
%set(gca, 'YTickLabel',[]); % Hide y-axis ticks and labels
set(gca, 'YGrid','on');
set(gca, 'YLabel', []);
end
if idx <= 4
title(Title(idx));
end
end
% Create textbox
annotation(fig,'textbox',...
[0.300019607843137 0.816120906801009 0.108803921568628 0.0906801007556676],...
'String','$P_{\mathrm{in}}=3$ dBm',...
'LineStyle','none',...
'Interpreter','latex',...
'FontSize',8,...
'FitBoxToText','off');
% Create textbox
annotation(fig,'textbox',...
[0.530411764705882 0.81612090680101 0.108803921568628 0.0906801007556676],...
'String','$P_{\mathrm{in}}=3$ dBm',...
'LineStyle','none',...
'Interpreter','latex',...
'FontSize',8,...
'FitBoxToText','off');
% Create textbox
annotation(fig,'textbox',...
[0.755901960784313 0.816120906801011 0.108803921568628 0.0906801007556676],...
'String','$P_{\mathrm{in}}=3$ dBm',...
'LineStyle','none',...
'Interpreter','latex',...
'FontSize',8,...
'FitBoxToText','off');
% Create textbox
annotation(fig,'textbox',...
[0.0696274509803918 0.584382871536529 0.108803921568628 0.0906801007556676],...
'String','$P_{\mathrm{in}}=3$ dBm',...
'LineStyle','none',...
'Interpreter','latex',...
'FontSize',8,...
'FitBoxToText','off');
% lgd = legend('$P_{\mathrm{in}}=0$ dBm','$P_{\mathrm{in}}=3$ dBm','$P_{\mathrm{in}}=6$ dBm','Interpreter','latex');
% lgd.NumColumns = 3;
% lgd.Layout.Tile = 'south';
end
%% 3
function createsweepplots(wh,plotJob)
width = 650;
height = 200;
s = 100;
e = 100;
plotJob.Position = [0 0 width e+height];
cols = cbrewer2("paired",12);
numRows = 1;
numCols = 4;
plotJob.channelspacing = 200e9;
plotJob.ch = 16;
plotJob.randzdw = 1;
plotJob.l = 10;
plotJob.p_in = 3;
Pol = ["copolarized","alternated","paired","copolarized"];
Title = ["Co Polarized","Alternating Pol. Interl.","Paired Pol. Interl.","Link Segmentation",];
D = [0,0,0,3];
Sgm = [0,0,0,1];
Channelspacing = [200e9, 200e9];
PlotTypeArg = ["--","-"];
colidx = [6,8,2,4];
Len = [2,10];
plotJob.figName = [num2str(plotJob.ch),num2str(plotJob.channelspacing*1e-9),num2str(plotJob.p_in),'...'];
plotJob.figName = "10km 400ghz";
fig = findall(groot, 'Type', 'figure', 'Name', plotJob.figName);
if isvalid(fig)
figure(fig)
fig = get(fig);
AxesMain = fig.CurrentAxes;
hold on
else
fig = figure('name',char(plotJob.figName));
AxesMain = gca;
hold on
end
fig.Position = plotJob.Position;
fig.Units = "centimeters";
fig.Position = [0 0 18 7];
for j = 1
plotJob.channelspacing = Channelspacing(j);
plotJob.plotTypeArg = PlotTypeArg(j);
for idx = 1:4
plotJob.color = cols(colidx(idx),:);
plotJob.pol = Pol(idx);
plotJob.d = D(idx);
plotJob.sgm = Sgm(idx);
plotJob.displayname = [char(plotJob.pol)];
hold on
plotBerVsZdwFailureRate(wh, plotJob);
end
end
legend('Location', 'southoutside', 'Orientation', 'horizontal');
%plot channel positions
hold on
chpos = calcWavelengthPlan(plotJob.ch, plotJob.channelspacing, 1310);
xline(chpos,'LineWidth',2,'Alpha',0.4,'HandleVisibility','off');
chpos = calcWavelengthPlan(plotJob.ch, plotJob.channelspacing, chpos(4));
xline(chpos,'LineWidth',2,'LineStyle','--','Alpha',0.1,'HandleVisibility','off');
title(['N=',num2str(plotJob.ch),' $\Delta f_{\mathrm{ch}}$= ',num2str(plotJob.channelspacing*1e-9),' GHz'],'FontSize',10,'Interpreter','latex');
end
%automate plots
[file, path] = uigetfile("C:\Users\Silas\Documents\MATLAB\Datensätze\Raw_Cluster_Simulations\session_februar_24\wh_mi_nacht.mat");
wh = load([path filesep file]);
wh = wh.wh;
% fields = fieldnames(wh.parameter);
% for k = 1:numel(fields)
% oldParam = wh.parameter.(fields{k});
% % copy over the properties to your new class
% wh.parameter.(fields{k}) = StorageParameter(...
% oldParam.Name, oldParam.values);
% end
%
plotJob = struct();
width = 350;
height = 200;
plotJob.Position = [100 100 width 100+height];
cols = cbrewer2("paired",12);
plotJob.color = cols(1,:);
plotJob.l = 2;
plotJob.ch = 16;
plotJob.d = 0;
plotJob.sgm = 0;
plotJob.pol = "copolarized";
plotJob.p_in = 3;
plotJob.gamma = 0.0023;
plotJob.pmd = 0.1;
plotJob.channelspacing = 400e9;
plotJob.randzdw = 0;
plotJob.plot_ber_curve = 0;
plotJob.plot_3dber_curve = 0;
plotJob.plot_violin = 1;
plotJob.plot_wavelength_sweep = 0;
plotJob.plot_wavelength_sweep_failure_rate = 0;
plotJob.dataStatArg = 'Lineplot with quartiles';
plotJob.plotTypeArg = 'Lines';
plotJob.displayname = 'a';
plotJob.title = 'title';
plotJob.figName = '16 Chann';
plotJob.xAxisLabel = 'ROP per Channel in dBm';
plotJob.yAxisLabel = 'BER';
%%
% createbercurves(wh,plotJob)
P = [3,6];
for i = 1:2
plotJob.p_in = P(i);
createviolinplots(wh,plotJob);
end
% createsweepplots(wh,plotJob);
%% 1
function createbercurves(wh,plotJob)
width = 1650;
height = 400;
s = 100;
e = 100;
cols = cbrewer2("paired",12);
numRows = 2;
numCols = 4;
plotJob.figName = '16 Chann_200G';
plotJob.channelspacing = 400e9;
plotJob.ch = 16;
Len = [2,2,2,2,10,10,10,10];
Pol = ["copolarized","alternated","paired","copolarized","copolarized","alternated","paired","copolarized"];
Title = ["Co Polarized","Alternating Pol. Interl.","Paired Pol. Interl.","Link Segmentation",];
D = [0,0,0,3,0,0,0,3];
Sgm = [0,0,0,1,0,0,0,1];
colidx = [4,8,6];
P_launch = [3,6];
fig = figure('Name',plotJob.figName);
fig.Position = plotJob.Position;
fig.Units = "centimeters";
fig.Position = [0 0 18 7];
t = tiledlayout(numRows,numCols,'TileSpacing','compact','Padding','compact');
for idx = 1:(numRows * numCols)
% Create subplot
% sp = subplot(numRows, numCols, idx);
nexttile;
plotJob.l = Len(idx);
plotJob.pol = Pol(idx);
plotJob.d = D(idx);
plotJob.sgm = Sgm(idx);
plotJob.randzdw = 1;
for i = 1:length(P_launch)
plotJob.p_in = P_launch(i);
plotJob.color = cols(colidx(i),:);
hold on
plotCurve(wh, plotJob);
end
%
if idx ~= 1 && idx ~= 5 % For example, hide y-axis for subplot 1
set(gca, 'YTickLabel',[]); % Hide y-axis ticks and labels
set(gca,'YGrid','on');
set(gca, 'YLabel', []);
end
if idx ~= 5 && idx ~= 6 && idx ~= 7 && idx ~= 8
set(gca, 'XLabel', []);
set(gca, 'XTickLabel', []);
end
grid on
g = gca;
pos = g.Position;
if idx <= 4
title(Title(idx),'FontSize',8);
% a = annotation('textbox', pos-[0.0020 -0.1434 0.0947 0.3121], 'String', "FEC: 3.8e-3","LineStyle","none","FontSize",8,'LineWidth',0.1,'Interpreter','latex',"FontUnits","points",'Vert','middle','FitBoxToText','on');
% a = annotation('textbox', pos, 'String', "2 km","LineStyle","none","FontSize",8,'LineWidth',0.1,'Interpreter','latex',"FontUnits","points",'Vert','bottom','FitBoxToText','on');
else
% a = annotation('textbox', pos, 'String', "FEC: 3.8e-3","LineStyle","none","FontSize",8,'LineWidth',0.1,'Interpreter','latex',"FontUnits","points",'Vert','middle','FitBoxToText','on');
% a = annotation('textbox', pos, 'String', "10 km","LineStyle","none","FontSize",8,'LineWidth',0.1,'Interpreter','latex',"FontUnits","points",'Vert','bottom','FitBoxToText','on');
end
end
% Create textbox
annotation(fig,'textbox',...
[0.0696078431372547 0.246851385390432 0.0656862745098043 0.0453400503778337],...
'String','10 km',...
'LineStyle','none',...
'Interpreter','latex',...
'FontSize',8,...
'FitBoxToText','off');
% Create textbox
annotation(fig,'textbox',...
[0.288235294117647 0.239294710327459 0.0656862745098043 0.0453400503778338],...
'String','10 km',...
'LineStyle','none',...
'Interpreter','latex',...
'FontSize',8,...
'FitBoxToText','off');
% Create textbox
annotation(fig,'textbox',...
[0.516666666666666 0.241813602015117 0.0656862745098042 0.0453400503778338],...
'String','10 km',...
'LineStyle','none',...
'Interpreter','latex',...
'FontSize',8,...
'FitBoxToText','off');
% Create textbox
annotation(fig,'textbox',...
[0.742156862745097 0.236775818639802 0.0656862745098042 0.0453400503778339],...
'String','10 km',...
'LineStyle','none',...
'Interpreter','latex',...
'FontSize',8,...
'FitBoxToText','off');
% Create textbox
annotation(fig,'textbox',...
[0.071996471804854 0.578899159967702 0.0656862745098039 0.0453400503778341],...
'String',{'2 km'},...
'LineStyle','none',...
'Interpreter','latex',...
'FontSize',8,...
'FitBoxToText','off');
% Create textbox
annotation(fig,'textbox',...
[0.29596893566113 0.576253721089996 0.0656862745098041 0.0453400503778341],...
'String',{'2 km'},...
'LineStyle','none',...
'Interpreter','latex',...
'FontSize',8,...
'FitBoxToText','off');
% Create textbox
annotation(fig,'textbox',...
[0.524883914268912 0.580785315705112 0.0656862745098041 0.0453400503778341],...
'String',{'2 km'},...
'LineStyle','none',...
'Interpreter','latex',...
'FontSize',8,...
'FitBoxToText','off');
% Create textbox
annotation(fig,'textbox',...
[0.753758338909501 0.581291504465311 0.0656862745098037 0.0453400503778341],...
'String',{'2 km'},...
'LineStyle','none',...
'Interpreter','latex',...
'FontSize',8,...
'FitBoxToText','off');
a=sgtitle(['N=',num2str(plotJob.ch),'; $\Delta f_{\mathrm{ch}}$= ',num2str(plotJob.channelspacing*1e-9),' GHz'],'FontSIze',10);
a.Interpreter = "latex";
lgd = legend('$P_{\mathrm{in}}=0$ dBm','$P_{\mathrm{in}}=3$ dBm','$P_{\mathrm{in}}=6$ dBm','Interpreter','latex');
lgd.NumColumns = 3;
lgd.Layout.Tile = 'south';
copygraphics(t,'BackgroundColor','none');
end
%% 2
function createviolinplots(wh,plotJob)
width = 350;
height = 200;
s = 100;
e = 100;
cols = cbrewer2("paired",12);
numRows = 1;
numCols = 4;
plotJob.ch = 16;
plotJob.randzdw = 1;
Pol = ["copolarized","copolarized","alternated","paired",];
Title = ["Co Pol.","Link Segmentation","Paired Pol. Interl.","Alternating Pol. Interl."];
D = [0,3,0,0];
Sgm = [0,1,0,0];
colidx = [3];
Len = [10];
fig = findall(groot, 'Type', 'figure', 'Name', plotJob.figName);
if isvalid(fig)
figure(fig)
% fig = get(fig);
AxesMain = fig.CurrentAxes;
hold on
% t = tiledlayout(1,4,'TileSpacing','compact','Padding','compact');
else
fig = figure('name',char(plotJob.figName));
AxesMain = gca;
hold on; grid on;
% t = tiledlayout(1,4,'TileSpacing','compact','Padding','compact');
end
for idx = 1:(numRows * numCols)
% Create subplot
subplot(numRows, numCols, idx);
plotJob.pol = Pol(idx);
plotJob.d = D(idx);
plotJob.sgm = Sgm(idx);
for i = 1
plotJob.color = cols(colidx(i),:);
plotJob.l = Len(i);
hold on
plotViolin(wh, plotJob);
end
if idx ~= 1 % For example, hide y-axis for subplot 1
%set(gca, 'YTickLabel',[]); % Hide y-axis ticks and labels
set(gca, 'YGrid','on');
set(gca, 'YLabel', []);
end
if idx <= 4
title(Title(idx));
end
end
% Create textbox
annotation(fig,'textbox',...
[0.300019607843137 0.816120906801009 0.108803921568628 0.0906801007556676],...
'String','$P_{\mathrm{in}}=3$ dBm',...
'LineStyle','none',...
'Interpreter','latex',...
'FontSize',8,...
'FitBoxToText','off');
% Create textbox
annotation(fig,'textbox',...
[0.530411764705882 0.81612090680101 0.108803921568628 0.0906801007556676],...
'String','$P_{\mathrm{in}}=3$ dBm',...
'LineStyle','none',...
'Interpreter','latex',...
'FontSize',8,...
'FitBoxToText','off');
% Create textbox
annotation(fig,'textbox',...
[0.755901960784313 0.816120906801011 0.108803921568628 0.0906801007556676],...
'String','$P_{\mathrm{in}}=3$ dBm',...
'LineStyle','none',...
'Interpreter','latex',...
'FontSize',8,...
'FitBoxToText','off');
% Create textbox
annotation(fig,'textbox',...
[0.0696274509803918 0.584382871536529 0.108803921568628 0.0906801007556676],...
'String','$P_{\mathrm{in}}=3$ dBm',...
'LineStyle','none',...
'Interpreter','latex',...
'FontSize',8,...
'FitBoxToText','off');
% lgd = legend('$P_{\mathrm{in}}=0$ dBm','$P_{\mathrm{in}}=3$ dBm','$P_{\mathrm{in}}=6$ dBm','Interpreter','latex');
% lgd.NumColumns = 3;
% lgd.Layout.Tile = 'south';
end
%% 3
function createsweepplots(wh,plotJob)
width = 650;
height = 200;
s = 100;
e = 100;
plotJob.Position = [0 0 width e+height];
cols = cbrewer2("paired",12);
numRows = 1;
numCols = 4;
plotJob.channelspacing = 200e9;
plotJob.ch = 16;
plotJob.randzdw = 1;
plotJob.l = 10;
plotJob.p_in = 3;
Pol = ["copolarized","alternated","paired","copolarized"];
Title = ["Co Polarized","Alternating Pol. Interl.","Paired Pol. Interl.","Link Segmentation",];
D = [0,0,0,3];
Sgm = [0,0,0,1];
Channelspacing = [200e9, 200e9];
PlotTypeArg = ["--","-"];
colidx = [6,8,2,4];
Len = [2,10];
plotJob.figName = [num2str(plotJob.ch),num2str(plotJob.channelspacing*1e-9),num2str(plotJob.p_in),'...'];
plotJob.figName = "10km 400ghz";
fig = findall(groot, 'Type', 'figure', 'Name', plotJob.figName);
if isvalid(fig)
figure(fig)
fig = get(fig);
AxesMain = fig.CurrentAxes;
hold on
else
fig = figure('name',char(plotJob.figName));
AxesMain = gca;
hold on
end
fig.Position = plotJob.Position;
fig.Units = "centimeters";
fig.Position = [0 0 18 7];
for j = 1
plotJob.channelspacing = Channelspacing(j);
plotJob.plotTypeArg = PlotTypeArg(j);
for idx = 1:4
plotJob.color = cols(colidx(idx),:);
plotJob.pol = Pol(idx);
plotJob.d = D(idx);
plotJob.sgm = Sgm(idx);
plotJob.displayname = [char(plotJob.pol)];
hold on
plotBerVsZdwFailureRate(wh, plotJob);
end
end
legend('Location', 'southoutside', 'Orientation', 'horizontal');
%plot channel positions
hold on
chpos = calcWavelengthPlan(plotJob.ch, plotJob.channelspacing, 1310);
xline(chpos,'LineWidth',2,'Alpha',0.4,'HandleVisibility','off');
chpos = calcWavelengthPlan(plotJob.ch, plotJob.channelspacing, chpos(4));
xline(chpos,'LineWidth',2,'LineStyle','--','Alpha',0.1,'HandleVisibility','off');
title(['N=',num2str(plotJob.ch),' $\Delta f_{\mathrm{ch}}$= ',num2str(plotJob.channelspacing*1e-9),' GHz'],'FontSize',10,'Interpreter','latex');
end

0
Classes/Warehouse_class/functions/fwm_plots/automate_PTL_plot_new.m → Classes/Warehouse_class/functions/phase_predist_plots/fwm_plots/automate_PTL_plot_new.m
View File

166
Classes/Warehouse_class/functions/fwm_plots/dispersion_only.m → Classes/Warehouse_class/functions/phase_predist_plots/fwm_plots/dispersion_only.m
View File

@@ -1,83 +1,83 @@
%automate plots
[file, path] = uigetfile("C:\Users\Silas\Documents\MATLAB\Datensätze\Raw_Cluster_Simulations\");
wh = load([path filesep file]);
wh = wh.wh;
plotJob = struct();
width = 350;
height = 200;
plotJob.Position = [100 100 width 100+height];
cols = cbrewer2("paired",12);
plotJob.color = cols(1,:);
plotJob.l = 1;
plotJob.ch = 1;
plotJob.sgm = 1;
plotJob.pol = "copolarized";
plotJob.p_in = 3;
plotJob.gamma = 0.0023;
plotJob.pmd = 0.1;
plotJob.channelspacing = 400e9;
plotJob.randzdw = 0;
plotJob.plot_ber_curve = 1;
plotJob.plot_3dber_curve = 0;
plotJob.plot_violin = 0;
plotJob.plot_wavelength_sweep = 0;
plotJob.plot_wavelength_sweep_failure_rate = 0;
plotJob.dataStatArg = 'Lineplot with quartiles';
plotJob.plotTypeArg = 'Lines';
plotJob.displayname = 'a';
plotJob.title = 'title';
plotJob.figName = '1 Chann__';
plotJob.xAxisLabel = 'ROP per Channel in dBm';
plotJob.yAxisLabel = 'BER';
plotJob.d = 0;
xAxis = wh.parameter.p_out.values;
D = wh.parameter.dispersion.values;
figure()
ber_ = [];
for d_ = 0:39
if d_ == 0
plotJob.sgm = 0;
ber_(d_+1,:) = wh.getStoValue('ber',plotJob.l,d_,plotJob.sgm,string(plotJob.pol),plotJob.p_in,xAxis,plotJob.pmd,plotJob.gamma,1,plotJob.ch,1310,plotJob.channelspacing,plotJob.randzdw)';
else
plotJob.sgm = 1;
ber_(d_+1,:) = wh.getStoValue('ber',plotJob.l,d_,plotJob.sgm,string(plotJob.pol),plotJob.p_in,xAxis,plotJob.pmd,plotJob.gamma,1,plotJob.ch,1310,plotJob.channelspacing,plotJob.randzdw)';
end
hold on
plot(xAxis,ber_(d_+1,:))
set(gca,'yscale','log');
end
yline(3.8e-3);
hdfec = 3.8e-3.*ones(size(xAxis));
for i = 1:size(ber_,1)
ber_series = ber_(i,:);
a = InterX([hdfec(:)';xAxis],[ber_series;xAxis]);
cross(i) = a(2);
end
col = cbrewer2('Paired',8);
figure()
plot(D,cross,'Marker','o','MarkerSize',5,'MarkerEdgeColor',[1,1,1],'MarkerFaceColor',col(2,:),'Color',col(1,:),'LineWidth',1);
grid minor
xlabel('Accumulated Dispersion')
ylabel('Required ROP to reach FEC limit in dB')
line([D(16),D(16)],[-10,cross(16)],'linestyle','--')
line([0,D(16)],[cross(16),cross(16)],'linestyle','--')
line([D(29),D(29)],[-10,cross(29)],'linestyle','--')
line([0,D(29)],[cross(29),cross(29)],'linestyle','--')
%automate plots
[file, path] = uigetfile("C:\Users\Silas\Documents\MATLAB\Datensätze\Raw_Cluster_Simulations\");
wh = load([path filesep file]);
wh = wh.wh;
plotJob = struct();
width = 350;
height = 200;
plotJob.Position = [100 100 width 100+height];
cols = cbrewer2("paired",12);
plotJob.color = cols(1,:);
plotJob.l = 1;
plotJob.ch = 1;
plotJob.sgm = 1;
plotJob.pol = "copolarized";
plotJob.p_in = 3;
plotJob.gamma = 0.0023;
plotJob.pmd = 0.1;
plotJob.channelspacing = 400e9;
plotJob.randzdw = 0;
plotJob.plot_ber_curve = 1;
plotJob.plot_3dber_curve = 0;
plotJob.plot_violin = 0;
plotJob.plot_wavelength_sweep = 0;
plotJob.plot_wavelength_sweep_failure_rate = 0;
plotJob.dataStatArg = 'Lineplot with quartiles';
plotJob.plotTypeArg = 'Lines';
plotJob.displayname = 'a';
plotJob.title = 'title';
plotJob.figName = '1 Chann__';
plotJob.xAxisLabel = 'ROP per Channel in dBm';
plotJob.yAxisLabel = 'BER';
plotJob.d = 0;
xAxis = wh.parameter.p_out.values;
D = wh.parameter.dispersion.values;
figure()
ber_ = [];
for d_ = 0:39
if d_ == 0
plotJob.sgm = 0;
ber_(d_+1,:) = wh.getStoValue('ber',plotJob.l,d_,plotJob.sgm,string(plotJob.pol),plotJob.p_in,xAxis,plotJob.pmd,plotJob.gamma,1,plotJob.ch,1310,plotJob.channelspacing,plotJob.randzdw)';
else
plotJob.sgm = 1;
ber_(d_+1,:) = wh.getStoValue('ber',plotJob.l,d_,plotJob.sgm,string(plotJob.pol),plotJob.p_in,xAxis,plotJob.pmd,plotJob.gamma,1,plotJob.ch,1310,plotJob.channelspacing,plotJob.randzdw)';
end
hold on
plot(xAxis,ber_(d_+1,:))
set(gca,'yscale','log');
end
yline(3.8e-3);
hdfec = 3.8e-3.*ones(size(xAxis));
for i = 1:size(ber_,1)
ber_series = ber_(i,:);
a = InterX([hdfec(:)';xAxis],[ber_series;xAxis]);
cross(i) = a(2);
end
col = cbrewer2('Paired',8);
figure()
plot(D,cross,'Marker','o','MarkerSize',5,'MarkerEdgeColor',[1,1,1],'MarkerFaceColor',col(2,:),'Color',col(1,:),'LineWidth',1);
grid minor
xlabel('Accumulated Dispersion')
ylabel('Required ROP to reach FEC limit in dB')
line([D(16),D(16)],[-10,cross(16)],'linestyle','--')
line([0,D(16)],[cross(16),cross(16)],'linestyle','--')
line([D(29),D(29)],[-10,cross(29)],'linestyle','--')
line([0,D(29)],[cross(29),cross(29)],'linestyle','--')

102
Classes/Warehouse_class/functions/fwm_plots/dispersion_validation_miniskript.m → Classes/Warehouse_class/functions/phase_predist_plots/fwm_plots/dispersion_validation_miniskript.m
View File

@@ -1,52 +1,52 @@
wh = load("C:\Users\Silas\Documents\MATLAB\Datensätze\Raw_Cluster_Simulations\session_dispersion_validation\wh_with_variation.mat");
wh = wh.wh;
lambda = 1295;
figure(3)
plot(xAxis,getber(wh,lambda),'DisplayName',['w:', num2str(lambda), 'variation']);
yline(3.8e-3,'HandleVisibility','off');
legend
set(gca,'yscale','log');
grid(gca,'on');
grid(gca,'minor');
grid minor
fontsize(gca,8,"points")
fig.Units = "centimeters";
fig.Position = [2 2 8.5 7];
set(gca,'TickLabelInterpreter','latex')
ylim([1e-5,0.5]);
xlim([min(xAxis),-3]);
wh = load("C:\Users\Silas\Documents\MATLAB\Datensätze\Raw_Cluster_Simulations\session_dispersion_validation\wh_no_variation.mat");
wh = wh.wh;
figure(3)
hold on
plot(xAxis,getber(wh,lambda),'DisplayName',['w:', num2str(lambda), 'no variation']);
yline(3.8e-3,'HandleVisibility','off');
legend
set(gca,'yscale','log');
grid(gca,'on');
grid(gca,'minor');
grid minor
fontsize(gca,8,"points")
fig.Units = "centimeters";
fig.Position = [2 2 8.5 7];
set(gca,'TickLabelInterpreter','latex')
ylim([1e-5,0.5]);
xlim([min(xAxis),-3]);
function ber = getber(wh,lambda)
realization = wh.parameter.realization.values(1:end);
xAxis = wh.parameter.p_out.values;
ber = [];
for xl = 1:numel(xAxis)
p_out = xAxis(xl);
temp = wh.getStoValue('ber',10,0,0,"copolarized",3,p_out,0.1,0.0023,realization,1,lambda,400e9,1);
ber(xl) = mean(temp,'all');
end
wh = load("C:\Users\Silas\Documents\MATLAB\Datensätze\Raw_Cluster_Simulations\session_dispersion_validation\wh_with_variation.mat");
wh = wh.wh;
lambda = 1295;
figure(3)
plot(xAxis,getber(wh,lambda),'DisplayName',['w:', num2str(lambda), 'variation']);
yline(3.8e-3,'HandleVisibility','off');
legend
set(gca,'yscale','log');
grid(gca,'on');
grid(gca,'minor');
grid minor
fontsize(gca,8,"points")
fig.Units = "centimeters";
fig.Position = [2 2 8.5 7];
set(gca,'TickLabelInterpreter','latex')
ylim([1e-5,0.5]);
xlim([min(xAxis),-3]);
wh = load("C:\Users\Silas\Documents\MATLAB\Datensätze\Raw_Cluster_Simulations\session_dispersion_validation\wh_no_variation.mat");
wh = wh.wh;
figure(3)
hold on
plot(xAxis,getber(wh,lambda),'DisplayName',['w:', num2str(lambda), 'no variation']);
yline(3.8e-3,'HandleVisibility','off');
legend
set(gca,'yscale','log');
grid(gca,'on');
grid(gca,'minor');
grid minor
fontsize(gca,8,"points")
fig.Units = "centimeters";
fig.Position = [2 2 8.5 7];
set(gca,'TickLabelInterpreter','latex')
ylim([1e-5,0.5]);
xlim([min(xAxis),-3]);
function ber = getber(wh,lambda)
realization = wh.parameter.realization.values(1:end);
xAxis = wh.parameter.p_out.values;
ber = [];
for xl = 1:numel(xAxis)
p_out = xAxis(xl);
temp = wh.getStoValue('ber',10,0,0,"copolarized",3,p_out,0.1,0.0023,realization,1,lambda,400e9,1);
ber(xl) = mean(temp,'all');
end
end

120
Classes/Warehouse_class/functions/fwm_plots/generatePlots.m → Classes/Warehouse_class/functions/phase_predist_plots/fwm_plots/generatePlots.m
View File

@@ -1,61 +1,61 @@
function generatePlots(wh,plotJob)
% 0) Test for valid query:
p_out = wh.parameter.p_out.values(1);
realization = 9;
if 1 %~isempty(wh.getStoValue('ber',plotJob.l,plotJob.d,plotJob.sgm,string(plotJob.pol),plotJob.p_in,p_out,plotJob.pmd,plotJob.gamma,realization,plotJob.ch,1310))
% test violin
baseName = plotJob.figName;
width = 350;
height = 200;
s = 100;
e = 100;
if plotJob.plot_ber_curve
plotJob.Position = [100 100 width e+height];
plotJob.figName = [baseName, ' zdwvsber'];
plotCurve(wh, plotJob);
end
if plotJob.plot_3dber_curve
plotJob.Position = [100 100 width e+height];
plotJob.figName = [baseName, ' zdwvsber'];
plot3dCurve(wh, plotJob);
end
if plotJob.plot_wavelength_sweep
plotJob.Position = [100 100 width e+height];
plotJob.figName = [baseName, ' zdwvsber'];
plotBerVsZDW(wh, plotJob);
end
if plotJob.plot_wavelength_sweep_failure_rate
plotJob.Position = [100 100 width e+height];
plotJob.figName = [baseName, ' zdwvsber'];
plotBerVsZdwFailureRate(wh, plotJob);
end
if plotJob.plot_violin
plotJob.Position = [s+width 100 width e+height];
plotJob.figName = [baseName, ' violin'];
plotViolin(wh, plotJob);
end
if 0
%2) plotHistogram
plotJob.Position = [s+2*width 100 width e+height];
plotJob.figName = [baseName, ' FEC crossing'];
plotHistogram(wh,plotJob)
end
else
warndlg('The requested Datapoint is not available... This can occur for some edgecase constellations... ')
end
function generatePlots(wh,plotJob)
% 0) Test for valid query:
p_out = wh.parameter.p_out.values(1);
realization = 9;
if 1 %~isempty(wh.getStoValue('ber',plotJob.l,plotJob.d,plotJob.sgm,string(plotJob.pol),plotJob.p_in,p_out,plotJob.pmd,plotJob.gamma,realization,plotJob.ch,1310))
% test violin
baseName = plotJob.figName;
width = 350;
height = 200;
s = 100;
e = 100;
if plotJob.plot_ber_curve
plotJob.Position = [100 100 width e+height];
plotJob.figName = [baseName, ' zdwvsber'];
plotCurve(wh, plotJob);
end
if plotJob.plot_3dber_curve
plotJob.Position = [100 100 width e+height];
plotJob.figName = [baseName, ' zdwvsber'];
plot3dCurve(wh, plotJob);
end
if plotJob.plot_wavelength_sweep
plotJob.Position = [100 100 width e+height];
plotJob.figName = [baseName, ' zdwvsber'];
plotBerVsZDW(wh, plotJob);
end
if plotJob.plot_wavelength_sweep_failure_rate
plotJob.Position = [100 100 width e+height];
plotJob.figName = [baseName, ' zdwvsber'];
plotBerVsZdwFailureRate(wh, plotJob);
end
if plotJob.plot_violin
plotJob.Position = [s+width 100 width e+height];
plotJob.figName = [baseName, ' violin'];
plotViolin(wh, plotJob);
end
if 0
%2) plotHistogram
plotJob.Position = [s+2*width 100 width e+height];
plotJob.figName = [baseName, ' FEC crossing'];
plotHistogram(wh,plotJob)
end
else
warndlg('The requested Datapoint is not available... This can occur for some edgecase constellations... ')
end
end

496
Classes/Warehouse_class/functions/fwm_plots/plot3dCurve.m → Classes/Warehouse_class/functions/phase_predist_plots/fwm_plots/plot3dCurve.m
View File

@@ -1,248 +1,248 @@
function plotCurve(wh,plotJob)
%PLOTCURVE Summary of this function goes here
% Detailed explanation goes here
fig = findall(groot, 'Type', 'figure', 'Name', plotJob.figName);
if isvalid(fig)
figure(fig)
fig = get(fig);
AxesMain = fig.CurrentAxes;
hold on
else
fig = figure('name',char(plotJob.figName));
AxesMain = gca;
hold on
end
col = plotJob.color;
% we want to fetch all realizations
if plotJob.pmd == 0
realization = 499;
% realization = 0:7;
else
realization = wh.parameter.realization.values(1:end);
end
realization = wh.parameter.realization.values(1:end);
% get all xAxis values
xAxis = wh.parameter.p_out.values;
% Fetch Data from Warehouse
for xl = 1:numel(xAxis)
p_out = xAxis(xl);
if string(plotJob.dataStatArg) == "Worst"
temp = wh.getStoValue('ber',plotJob.l,plotJob.d,plotJob.sgm,string(plotJob.pol),plotJob.p_in,p_out,plotJob.pmd,plotJob.gamma,realization,plotJob.ch,1310,plotJob.channelspacing,plotJob.randzdw);
temp = removeZeros(temp);
ber(xl) = max(temp,[],'all');
linew = 1.0;
markersz = 3;
linestyle = '-';
elseif string(plotJob.dataStatArg) == "AVG"
temp = wh.getStoValue('ber',plotJob.l,plotJob.d,plotJob.sgm,string(plotJob.pol),plotJob.p_in,p_out,plotJob.pmd,plotJob.gamma,realization,plotJob.ch,1310,plotJob.channelspacing,plotJob.randzdw);
temp = removeZeros(temp);
ber(xl) = mean(temp,'all');
linew = 1.0;
markersz = 3;
linestyle = '-';
elseif string(plotJob.dataStatArg) == "Best"
temp = wh.getStoValue('ber',plotJob.l,plotJob.d,plotJob.sgm,string(plotJob.pol),plotJob.p_in,p_out,plotJob.pmd,plotJob.gamma,realization,plotJob.ch,1310,plotJob.channelspacing,plotJob.randzdw);
temp = removeZeros(temp);
ber(xl) = min(temp,[],'all');
linew = 1.0;
markersz = 3;
linestyle = '-';
elseif string(plotJob.dataStatArg) == "All Channels; mean(PMD Realizations)"
temp = wh.getStoValue('ber',plotJob.l,plotJob.d,plotJob.sgm,string(plotJob.pol),plotJob.p_in,p_out,plotJob.pmd,plotJob.gamma,realization,plotJob.ch,1310,plotJob.channelspacing,plotJob.randzdw);
temp = removeZeros(temp);
ber(:,xl) = mean(temp,1,"omitnan").';
linew = 1;
markersz = 3;
linestyle = '--';
elseif string(plotJob.dataStatArg) == "Lineplot with quartiles"
temp = wh.getStoValue('ber',plotJob.l,plotJob.d,plotJob.sgm,string(plotJob.pol),plotJob.p_in,p_out,plotJob.pmd,plotJob.gamma,realization,plotJob.ch,1310,plotJob.channelspacing,plotJob.randzdw);
temp = removeZeros(temp);
ber(xl) = mean(temp,"all","omitnan").';
upperq(xl) = quantile(temp,0.9,"all");
lowerq(xl) = quantile(temp,0.1,"all");
if lowerq(xl) == 0
lowerq(xl) = lowerq(xl-1);
end
% upperq(xl) = 0.5*std(tmp,1,'all','omitnan');
% lowerq(xl) = 0.5*std(tmp,1,'all','omitnan');
% upperq(xl) = max(dataNoNans);
% lowerq(xl) = min(dataNoNans);
% upperq(xl) = mean(tmp,"all","omitnan") + 1.96 * (std(tmp,1,'all','omitnan')/sqrt(numel(tmp)));
% lowerq(xl) = mean(tmp,"all","omitnan") - 1.96 * (std(tmp,1,'all','omitnan')/sqrt(numel(tmp)));
linew = 1;
markersz = 1;
linestyle = '-';
elseif string(plotJob.dataStatArg) == "All Channels ;All PMD Realizations"
tmp = reshape(wh.getStoValue('ber',plotJob.l,plotJob.d,plotJob.sgm,string(plotJob.pol),plotJob.p_in,p_out,plotJob.pmd,plotJob.gamma,realization,plotJob.ch,1310,plotJob.channelspacing,plotJob.randzdw).',[],1);
ber(1:size(tmp,1),xl) = tmp;
linew = 0.3;
markersz = 2;
linestyle = ':';
end
end
xAxis = xAxis;
% Plot Data
if string(plotJob.plotTypeArg) == "Scatter"
for rlz = 1:size(ber,1)
if rlz < size(ber,1)
scatter(xAxis,ber(rlz,:),markersz,'MarkerEdgeColor',col,'MarkerFaceColor',col,'Parent', AxesMain(1),'HandleVisibility','off');
else
scatter(xAxis,ber(rlz,:),markersz,'MarkerEdgeColor',col,'MarkerFaceColor',col,'Parent', AxesMain(1),'DisplayName',[plotJob.dataStatArg,' Ch.: ', plotJob.displayname]);
end
end
elseif string(plotJob.plotTypeArg) == "Lines"
% if ~anynan(ber)
% [xAxis,ber] = interpCurve(xAxis, ber);
% end
for rlz = 1:size(ber,1)
%
if (string(plotJob.dataStatArg) == "All Channels ;All PMD Realizations")||(string(plotJob.dataStatArg) == "All Channels; mean(PMD Realizations)")
ch = mod(rlz,plotJob.ch);
if ch == 0; ch = plotJob.ch; end
else
ch = plotJob.dataStatArg;
end
if rlz <= size(ber,1)
s = plot3(xAxis,repmat(ch,1,numel(xAxis)),ber(rlz,:),linestyle,'Marker',"o",'MarkerSize',markersz,'MarkerFaceColor',plotJob.color,'LineWidth',linew,'Color',col,'Parent', AxesMain,'HandleVisibility','off');
s.DataTipTemplate.Interpreter = "latex";
s.DataTipTemplate.DataTipRows(1).Label = "Ch: ";
s.DataTipTemplate.DataTipRows(1).Value = repmat(ch,size(ber));
s.DataTipTemplate.DataTipRows(1);
s.DataTipTemplate.DataTipRows(2) = [];
else
if string(plotJob.dataStatArg) == "Lineplot with quartiles"
[hl,hp] = boundedline(xAxis,ber(rlz,:),([(ber(rlz,:)-lowerq(rlz,:));upperq(rlz,:)-ber(rlz,:)]'),'-*', 'alpha','Color',col,'transparency', 0.2);
hp.LineWidth = 1.2;
ho = outlinebounds(hl,hp);
set(ho, 'linestyle', ':', 'color', col);
else
s = plot(xAxis,ber(rlz,:),linestyle,'Marker',"o",'MarkerFaceColor',col,'MarkerSize',markersz,'LineWidth',linew,'Color',col,'Parent', AxesMain,'DisplayName',[plotJob.displayname]);
s.DataTipTemplate.Interpreter = "latex";
s.DataTipTemplate.DataTipRows(1).Label = "Ch: ";
s.DataTipTemplate.DataTipRows(1).Value = repmat(string(ch),size(ber));
s.DataTipTemplate.DataTipRows(1)
s.DataTipTemplate.DataTipRows(2) = [];
end
end
end
end
% Draw FEC Threshold Line
%get x data of first children:
%get all linear Values
if 0
linear = wh.getStoValue('ber',plotJob.l,plotJob.d,plotJob.sgm,string(plotJob.pol),plotJob.p_in,wh.parameter.p_out.values,0,0,499,"symmetric");
linear = mean(linear,2);
lincurve = findall(AxesMain, 'Type', 'line','DisplayName','Linear Baseline');
%
if isempty(lincurve)
xdata = AxesMain.Children(1).XData;
hdfec = 3.8e-3.*ones(size(xdata));
plot(xdata,linear,'-','Marker',"o",'MarkerSize',3,'LineWidth',4,'Color',[0.6400 0.6400 0.6400],'MarkerFaceColor',[0.6400 0.6400 0.6400],'Parent', AxesMain,'DisplayName','Linear Baseline');
%h = get(gca,'Children');
%set(gca,'Children',[h(2) h(1)])
end
end
feccurve = findall(AxesMain, 'Type', 'line','DisplayName','FEC $3.8*10^{-3}$');
%
if isempty(feccurve)
xdata = xAxis;
hdfec = 3.8e-3.*ones(size(xdata));
for ch = 1:plotJob.ch
plot3(xdata,repmat(ch,1,numel(xAxis)),hdfec,':','MarkerSize',4,'Color','black','MarkerFaceColor','black','LineWidth',0.5,'Parent', AxesMain,'DisplayName','FEC $3.8*10^{-3}$','HandleVisibility','off');
end
%h = get(gca,'Children');
%set(gca,'Children',[h(2) h(1)])
end
% Figure Settings
%title(AxesMain,plotJob.title,"Interpreter","none");
xlabel(AxesMain,plotJob.xAxisLabel,"Interpreter","none");
ylabel(AxesMain,plotJob.yAxisLabel,"Interpreter","none");
set(AxesMain,'zscale','log');
grid(AxesMain,'on');
grid(AxesMain,'minor');
grid minor
view(AxesMain,[42.0619302949062 23.4176470588235]);
%legend(AxesMain);
fontsize(AxesMain,8,"points")
fontname(AxesMain,"Arial")
fig.Position = plotJob.Position;
fig.Units = "centimeters";
fig.Position = [2 2 8.5 7];
set(AxesMain,'TickLabelInterpreter','none')
set(AxesMain.Legend,'Interpreter','none')
% set(gcf,'Units','centimeters')
% set(gcf,'Position',[2 2 9 4.5])
zlim([1e-4,0.3]);
xlim([min(xAxis),-3]);
annotation('textbox', [0.125, 0.32, 0.1, 0.1], 'String', "FEC 3.8e-3","LineStyle","none","FontSize",8,"FontUnits","points")
hold off
end
function vec = removeZeros(vec)
% Find rows that contain only zeros
rows_to_remove = all(vec == 0, 2);
% Remove rows with only zeros
vec(rows_to_remove, :) = [];
end
function plotCurve(wh,plotJob)
%PLOTCURVE Summary of this function goes here
% Detailed explanation goes here
fig = findall(groot, 'Type', 'figure', 'Name', plotJob.figName);
if isvalid(fig)
figure(fig)
fig = get(fig);
AxesMain = fig.CurrentAxes;
hold on
else
fig = figure('name',char(plotJob.figName));
AxesMain = gca;
hold on
end
col = plotJob.color;
% we want to fetch all realizations
if plotJob.pmd == 0
realization = 499;
% realization = 0:7;
else
realization = wh.parameter.realization.values(1:end);
end
realization = wh.parameter.realization.values(1:end);
% get all xAxis values
xAxis = wh.parameter.p_out.values;
% Fetch Data from Warehouse
for xl = 1:numel(xAxis)
p_out = xAxis(xl);
if string(plotJob.dataStatArg) == "Worst"
temp = wh.getStoValue('ber',plotJob.l,plotJob.d,plotJob.sgm,string(plotJob.pol),plotJob.p_in,p_out,plotJob.pmd,plotJob.gamma,realization,plotJob.ch,1310,plotJob.channelspacing,plotJob.randzdw);
temp = removeZeros(temp);
ber(xl) = max(temp,[],'all');
linew = 1.0;
markersz = 3;
linestyle = '-';
elseif string(plotJob.dataStatArg) == "AVG"
temp = wh.getStoValue('ber',plotJob.l,plotJob.d,plotJob.sgm,string(plotJob.pol),plotJob.p_in,p_out,plotJob.pmd,plotJob.gamma,realization,plotJob.ch,1310,plotJob.channelspacing,plotJob.randzdw);
temp = removeZeros(temp);
ber(xl) = mean(temp,'all');
linew = 1.0;
markersz = 3;
linestyle = '-';
elseif string(plotJob.dataStatArg) == "Best"
temp = wh.getStoValue('ber',plotJob.l,plotJob.d,plotJob.sgm,string(plotJob.pol),plotJob.p_in,p_out,plotJob.pmd,plotJob.gamma,realization,plotJob.ch,1310,plotJob.channelspacing,plotJob.randzdw);
temp = removeZeros(temp);
ber(xl) = min(temp,[],'all');
linew = 1.0;
markersz = 3;
linestyle = '-';
elseif string(plotJob.dataStatArg) == "All Channels; mean(PMD Realizations)"
temp = wh.getStoValue('ber',plotJob.l,plotJob.d,plotJob.sgm,string(plotJob.pol),plotJob.p_in,p_out,plotJob.pmd,plotJob.gamma,realization,plotJob.ch,1310,plotJob.channelspacing,plotJob.randzdw);
temp = removeZeros(temp);
ber(:,xl) = mean(temp,1,"omitnan").';
linew = 1;
markersz = 3;
linestyle = '--';
elseif string(plotJob.dataStatArg) == "Lineplot with quartiles"
temp = wh.getStoValue('ber',plotJob.l,plotJob.d,plotJob.sgm,string(plotJob.pol),plotJob.p_in,p_out,plotJob.pmd,plotJob.gamma,realization,plotJob.ch,1310,plotJob.channelspacing,plotJob.randzdw);
temp = removeZeros(temp);
ber(xl) = mean(temp,"all","omitnan").';
upperq(xl) = quantile(temp,0.9,"all");
lowerq(xl) = quantile(temp,0.1,"all");
if lowerq(xl) == 0
lowerq(xl) = lowerq(xl-1);
end
% upperq(xl) = 0.5*std(tmp,1,'all','omitnan');
% lowerq(xl) = 0.5*std(tmp,1,'all','omitnan');
% upperq(xl) = max(dataNoNans);
% lowerq(xl) = min(dataNoNans);
% upperq(xl) = mean(tmp,"all","omitnan") + 1.96 * (std(tmp,1,'all','omitnan')/sqrt(numel(tmp)));
% lowerq(xl) = mean(tmp,"all","omitnan") - 1.96 * (std(tmp,1,'all','omitnan')/sqrt(numel(tmp)));
linew = 1;
markersz = 1;
linestyle = '-';
elseif string(plotJob.dataStatArg) == "All Channels ;All PMD Realizations"
tmp = reshape(wh.getStoValue('ber',plotJob.l,plotJob.d,plotJob.sgm,string(plotJob.pol),plotJob.p_in,p_out,plotJob.pmd,plotJob.gamma,realization,plotJob.ch,1310,plotJob.channelspacing,plotJob.randzdw).',[],1);
ber(1:size(tmp,1),xl) = tmp;
linew = 0.3;
markersz = 2;
linestyle = ':';
end
end
xAxis = xAxis;
% Plot Data
if string(plotJob.plotTypeArg) == "Scatter"
for rlz = 1:size(ber,1)
if rlz < size(ber,1)
scatter(xAxis,ber(rlz,:),markersz,'MarkerEdgeColor',col,'MarkerFaceColor',col,'Parent', AxesMain(1),'HandleVisibility','off');
else
scatter(xAxis,ber(rlz,:),markersz,'MarkerEdgeColor',col,'MarkerFaceColor',col,'Parent', AxesMain(1),'DisplayName',[plotJob.dataStatArg,' Ch.: ', plotJob.displayname]);
end
end
elseif string(plotJob.plotTypeArg) == "Lines"
% if ~anynan(ber)
% [xAxis,ber] = interpCurve(xAxis, ber);
% end
for rlz = 1:size(ber,1)
%
if (string(plotJob.dataStatArg) == "All Channels ;All PMD Realizations")||(string(plotJob.dataStatArg) == "All Channels; mean(PMD Realizations)")
ch = mod(rlz,plotJob.ch);
if ch == 0; ch = plotJob.ch; end
else
ch = plotJob.dataStatArg;
end
if rlz <= size(ber,1)
s = plot3(xAxis,repmat(ch,1,numel(xAxis)),ber(rlz,:),linestyle,'Marker',"o",'MarkerSize',markersz,'MarkerFaceColor',plotJob.color,'LineWidth',linew,'Color',col,'Parent', AxesMain,'HandleVisibility','off');
s.DataTipTemplate.Interpreter = "latex";
s.DataTipTemplate.DataTipRows(1).Label = "Ch: ";
s.DataTipTemplate.DataTipRows(1).Value = repmat(ch,size(ber));
s.DataTipTemplate.DataTipRows(1);
s.DataTipTemplate.DataTipRows(2) = [];
else
if string(plotJob.dataStatArg) == "Lineplot with quartiles"
[hl,hp] = boundedline(xAxis,ber(rlz,:),([(ber(rlz,:)-lowerq(rlz,:));upperq(rlz,:)-ber(rlz,:)]'),'-*', 'alpha','Color',col,'transparency', 0.2);
hp.LineWidth = 1.2;
ho = outlinebounds(hl,hp);
set(ho, 'linestyle', ':', 'color', col);
else
s = plot(xAxis,ber(rlz,:),linestyle,'Marker',"o",'MarkerFaceColor',col,'MarkerSize',markersz,'LineWidth',linew,'Color',col,'Parent', AxesMain,'DisplayName',[plotJob.displayname]);
s.DataTipTemplate.Interpreter = "latex";
s.DataTipTemplate.DataTipRows(1).Label = "Ch: ";
s.DataTipTemplate.DataTipRows(1).Value = repmat(string(ch),size(ber));
s.DataTipTemplate.DataTipRows(1)
s.DataTipTemplate.DataTipRows(2) = [];
end
end
end
end
% Draw FEC Threshold Line
%get x data of first children:
%get all linear Values
if 0
linear = wh.getStoValue('ber',plotJob.l,plotJob.d,plotJob.sgm,string(plotJob.pol),plotJob.p_in,wh.parameter.p_out.values,0,0,499,"symmetric");
linear = mean(linear,2);
lincurve = findall(AxesMain, 'Type', 'line','DisplayName','Linear Baseline');
%
if isempty(lincurve)
xdata = AxesMain.Children(1).XData;
hdfec = 3.8e-3.*ones(size(xdata));
plot(xdata,linear,'-','Marker',"o",'MarkerSize',3,'LineWidth',4,'Color',[0.6400 0.6400 0.6400],'MarkerFaceColor',[0.6400 0.6400 0.6400],'Parent', AxesMain,'DisplayName','Linear Baseline');
%h = get(gca,'Children');
%set(gca,'Children',[h(2) h(1)])
end
end
feccurve = findall(AxesMain, 'Type', 'line','DisplayName','FEC $3.8*10^{-3}$');
%
if isempty(feccurve)
xdata = xAxis;
hdfec = 3.8e-3.*ones(size(xdata));
for ch = 1:plotJob.ch
plot3(xdata,repmat(ch,1,numel(xAxis)),hdfec,':','MarkerSize',4,'Color','black','MarkerFaceColor','black','LineWidth',0.5,'Parent', AxesMain,'DisplayName','FEC $3.8*10^{-3}$','HandleVisibility','off');
end
%h = get(gca,'Children');
%set(gca,'Children',[h(2) h(1)])
end
% Figure Settings
%title(AxesMain,plotJob.title,"Interpreter","none");
xlabel(AxesMain,plotJob.xAxisLabel,"Interpreter","none");
ylabel(AxesMain,plotJob.yAxisLabel,"Interpreter","none");
set(AxesMain,'zscale','log');
grid(AxesMain,'on');
grid(AxesMain,'minor');
grid minor
view(AxesMain,[42.0619302949062 23.4176470588235]);
%legend(AxesMain);
fontsize(AxesMain,8,"points")
fontname(AxesMain,"Arial")
fig.Position = plotJob.Position;
fig.Units = "centimeters";
fig.Position = [2 2 8.5 7];
set(AxesMain,'TickLabelInterpreter','none')
set(AxesMain.Legend,'Interpreter','none')
% set(gcf,'Units','centimeters')
% set(gcf,'Position',[2 2 9 4.5])
zlim([1e-4,0.3]);
xlim([min(xAxis),-3]);
annotation('textbox', [0.125, 0.32, 0.1, 0.1], 'String', "FEC 3.8e-3","LineStyle","none","FontSize",8,"FontUnits","points")
hold off
end
function vec = removeZeros(vec)
% Find rows that contain only zeros
rows_to_remove = all(vec == 0, 2);
% Remove rows with only zeros
vec(rows_to_remove, :) = [];
end

598
Classes/Warehouse_class/functions/fwm_plots/plotBerVsZDW.m → Classes/Warehouse_class/functions/phase_predist_plots/fwm_plots/plotBerVsZDW.m
View File

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

312
Classes/Warehouse_class/functions/fwm_plots/plotBerVsZdwFailureRate.m → Classes/Warehouse_class/functions/phase_predist_plots/fwm_plots/plotBerVsZdwFailureRate.m
View File

@@ -1,157 +1,157 @@
function plotBerVsZdwFailureRate(wh,plotJob)
fig = findall(groot, 'Type', 'figure', 'Name', plotJob.figName);
if isvalid(fig)
figure(fig)
fig = get(fig);
AxesMain = fig.CurrentAxes;
hold on
else
fig = figure('name',char(plotJob.figName));
AxesMain = gca;
hold on
end
col = plotJob.color;
% we want to fetch all realizations
realization = wh.parameter.realization.values(1:end);
% get all xAxis values
xAxis = wh.parameter.p_out.values;
% get all center wavelengths
wavelengths = wh.parameter.center_wavelength.values;
%wavelengths = wavelengths(2:end);
% totber = NaN(numel(realization),1,numel(xAxis),numel(wavelengths));
% ber = zeros(numel(realization),plotJob.ch,numel(xAxis),numel(wavelengths));
%get BER values for query
for w = 1:numel(wavelengths)
for xl = 1:numel(xAxis)
c_wavelen = wavelengths(w);
p_out = xAxis(xl);
% dim1 : realiz; dim2: channels, dim3: rop, dim4, c_wavelength
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));
ber(1:size(temp,1),:,xl,w) = temp;
end
end
hdfec = 3.8e-3.*ones(size(xAxis));
zdw_ = [];
zdw_chann = [];
zdw_tot = [];
cf_tot = [];
cf_ = [];
S = [];
Stot = [];
S_chann = [];
cf_chann = [];
cnt = 0;
%get fec thresholds
%linear = squeeze(linear);
for c_wavelen = 1:size(ber,4)
for realiz = 1:size(ber,1)
for chann = 1:size(ber,2)
%finde Schnittpunkt zwischen FEC und BER Kurve
temp_ber = squeeze(ber(realiz,chann,:,c_wavelen)).';
if ~all(temp_ber == 0)
%nur wenn nicht alles nullen sind
crossing_ch = InterX([hdfec;xAxis],[temp_ber;xAxis]);
else
continue
end
%Req. FEC Ergebnis einsortieren
if ~isempty(crossing_ch)
if crossing_ch(2) == 0
print("d")
end
S(realiz,chann,c_wavelen) = crossing_ch(2);
else
S(realiz,chann,c_wavelen) = -1;
cnt = cnt +1;
end
end
end
end
temp_max = -inf;
sum_FEC_not_crossed=[];
sum_FEC_crossed=[];
threshold = plotJob.p_in - 10;
for i = 1:plotJob.ch
hold on
%S:: 1.dim: realiz; 2.dim: channel; 3.dim: center wavelength
%squeeze a channel:
temp_data = squeeze(S(:,i,:));
%remove realizations that have no entry (only zero)
temp_data = removeZeros(temp_data);
%replace zeros with NAN (e.g. for the wavelengths that have missing realizations)
temp_data(temp_data==0) = NaN;
%for current channel
FEC_crossed = temp_data < threshold & ~isnan(temp_data);
FEC_not_crossed = temp_data >= threshold & ~isnan(temp_data);
%sum over channels for overall picture
sum_FEC_not_crossed(i,:) = sum(FEC_not_crossed);
sum_FEC_crossed(i,:) = sum(FEC_crossed);
failure_rate_channelwise(i,:) = sum_FEC_not_crossed(i,:)./ ( sum_FEC_crossed(i,:) + sum_FEC_not_crossed(i,:));
end
failure_rate_total = sum(sum_FEC_not_crossed,1) ./ ( sum(sum_FEC_crossed,1) + sum(sum_FEC_not_crossed,1) );
% plot failure rate (nbetween 0 and 1)
plot(wavelengths,failure_rate_total,'Color',plotJob.color,'LineWidth',1,'LineStyle',plotJob.plotTypeArg,'Marker','x','MarkerSize',5,'MarkerFaceColor',plotJob.color,'DisplayName',plotJob.displayname);
%plot max overall
%scatter(wavelengths,failure_rate_channelwise ,35,plotJob.color,'Marker','.');
ylabel('Failure Rate of Link');
xlabel('Wavelength in nm');
xlim([min(wavelengths),max(wavelengths) ]);
ylim([0,1]);
grid minor;
set(gca, 'color', 'none');
legend = [];
% fontsize(AxesMain,8,"points")
fig.Position = plotJob.Position;
fig.Units = "centimeters";
fig.Position = [0 0 12 5 7];
try
set(AxesMain,'TickLabelInterpreter','latex')
set(AxesMain.Legend,'Interpreter','latex')
end
end
function vec = removeZeros(vec)
% Find rows that contain only zeros
rows_to_remove = all(vec == 0, 2);
% Remove rows with only zeros
vec(rows_to_remove, :) = [];
function plotBerVsZdwFailureRate(wh,plotJob)
fig = findall(groot, 'Type', 'figure', 'Name', plotJob.figName);
if isvalid(fig)
figure(fig)
fig = get(fig);
AxesMain = fig.CurrentAxes;
hold on
else
fig = figure('name',char(plotJob.figName));
AxesMain = gca;
hold on
end
col = plotJob.color;
% we want to fetch all realizations
realization = wh.parameter.realization.values(1:end);
% get all xAxis values
xAxis = wh.parameter.p_out.values;
% get all center wavelengths
wavelengths = wh.parameter.center_wavelength.values;
%wavelengths = wavelengths(2:end);
% totber = NaN(numel(realization),1,numel(xAxis),numel(wavelengths));
% ber = zeros(numel(realization),plotJob.ch,numel(xAxis),numel(wavelengths));
%get BER values for query
for w = 1:numel(wavelengths)
for xl = 1:numel(xAxis)
c_wavelen = wavelengths(w);
p_out = xAxis(xl);
% dim1 : realiz; dim2: channels, dim3: rop, dim4, c_wavelength
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));
ber(1:size(temp,1),:,xl,w) = temp;
end
end
hdfec = 3.8e-3.*ones(size(xAxis));
zdw_ = [];
zdw_chann = [];
zdw_tot = [];
cf_tot = [];
cf_ = [];
S = [];
Stot = [];
S_chann = [];
cf_chann = [];
cnt = 0;
%get fec thresholds
%linear = squeeze(linear);
for c_wavelen = 1:size(ber,4)
for realiz = 1:size(ber,1)
for chann = 1:size(ber,2)
%finde Schnittpunkt zwischen FEC und BER Kurve
temp_ber = squeeze(ber(realiz,chann,:,c_wavelen)).';
if ~all(temp_ber == 0)
%nur wenn nicht alles nullen sind
crossing_ch = InterX([hdfec;xAxis],[temp_ber;xAxis]);
else
continue
end
%Req. FEC Ergebnis einsortieren
if ~isempty(crossing_ch)
if crossing_ch(2) == 0
print("d")
end
S(realiz,chann,c_wavelen) = crossing_ch(2);
else
S(realiz,chann,c_wavelen) = -1;
cnt = cnt +1;
end
end
end
end
temp_max = -inf;
sum_FEC_not_crossed=[];
sum_FEC_crossed=[];
threshold = plotJob.p_in - 10;
for i = 1:plotJob.ch
hold on
%S:: 1.dim: realiz; 2.dim: channel; 3.dim: center wavelength
%squeeze a channel:
temp_data = squeeze(S(:,i,:));
%remove realizations that have no entry (only zero)
temp_data = removeZeros(temp_data);
%replace zeros with NAN (e.g. for the wavelengths that have missing realizations)
temp_data(temp_data==0) = NaN;
%for current channel
FEC_crossed = temp_data < threshold & ~isnan(temp_data);
FEC_not_crossed = temp_data >= threshold & ~isnan(temp_data);
%sum over channels for overall picture
sum_FEC_not_crossed(i,:) = sum(FEC_not_crossed);
sum_FEC_crossed(i,:) = sum(FEC_crossed);
failure_rate_channelwise(i,:) = sum_FEC_not_crossed(i,:)./ ( sum_FEC_crossed(i,:) + sum_FEC_not_crossed(i,:));
end
failure_rate_total = sum(sum_FEC_not_crossed,1) ./ ( sum(sum_FEC_crossed,1) + sum(sum_FEC_not_crossed,1) );
% plot failure rate (nbetween 0 and 1)
plot(wavelengths,failure_rate_total,'Color',plotJob.color,'LineWidth',1,'LineStyle',plotJob.plotTypeArg,'Marker','x','MarkerSize',5,'MarkerFaceColor',plotJob.color,'DisplayName',plotJob.displayname);
%plot max overall
%scatter(wavelengths,failure_rate_channelwise ,35,plotJob.color,'Marker','.');
ylabel('Failure Rate of Link');
xlabel('Wavelength in nm');
xlim([min(wavelengths),max(wavelengths) ]);
ylim([0,1]);
grid minor;
set(gca, 'color', 'none');
legend = [];
% fontsize(AxesMain,8,"points")
fig.Position = plotJob.Position;
fig.Units = "centimeters";
fig.Position = [0 0 12 5 7];
try
set(AxesMain,'TickLabelInterpreter','latex')
set(AxesMain.Legend,'Interpreter','latex')
end
end
function vec = removeZeros(vec)
% Find rows that contain only zeros
rows_to_remove = all(vec == 0, 2);
% Remove rows with only zeros
vec(rows_to_remove, :) = [];
end

102
Classes/Warehouse_class/functions/fwm_plots/plotChannelSpacingAna.m → Classes/Warehouse_class/functions/phase_predist_plots/fwm_plots/plotChannelSpacingAna.m
View File

@@ -1,51 +1,51 @@
function plotChannelSpacingAna(wh,plotJob)
xAxis = wh.parameter.p_out.values;
realization = wh.parameter.realization.values(1:end);
channelsp = wh.parameter.channelspacing.values(1:end);
channelsp = [200 400].*1e9;
for ch = 1:2
channspacing = channelsp(ch);
for xl = 1:numel(xAxis)
p_out = xAxis(xl);
curber = wh.getStoValue('ber',plotJob.l,plotJob.d,plotJob.sgm,string(plotJob.pol),plotJob.p_in,p_out,plotJob.pmd,plotJob.gamma,realization,plotJob.numchannels,channspacing);
curzdw = wh.getStoValue('zdw',plotJob.l,plotJob.d,plotJob.sgm,string(plotJob.pol),plotJob.p_in,p_out,plotJob.pmd,plotJob.gamma,realization,plotJob.numchannels,channspacing);
ber(1:size(curber,1),1:size(curber,2),xl) = curber;
zdw(1:size(curber,1),1,xl) = curzdw;
end
ber = squeeze(mean(ber,1));
zdw = squeeze(mean(zdw,1));
hdfec = 3.8e-3.*ones(size(xAxis));
S = [];
wavelength={};
zdw_ = [];
zdw_chann = [];
zdw_tot = [];
S = [];
S_chann = [];
wl = round([1302.03471732576,1304.30061112288,1306.57440520904,1308.85614097425,1311.14586009814,1313.44360455251,1315.74941660391,1318.06333881618],2);
wl = 1:16;
wl = [1.2930 1.2953 1.2975 1.2998 1.3020 1.3043 1.3066 1.3089 1.3111 1.3134 1.3157 1.3181 1.3204 1.3227 1.3251 1.3274];
a = InterX([hdfec(:)';xAxis],[mean(ber,1);xAxis]);
if ~isempty(a)
s(ch) = a(2);
else
s(ch) = NaN;
end
end
figure(2224)
hold on
plot(channelsp,s,'LineWidth',1,'Color',plotJob.color,'Marker','o');
function plotChannelSpacingAna(wh,plotJob)
xAxis = wh.parameter.p_out.values;
realization = wh.parameter.realization.values(1:end);
channelsp = wh.parameter.channelspacing.values(1:end);
channelsp = [200 400].*1e9;
for ch = 1:2
channspacing = channelsp(ch);
for xl = 1:numel(xAxis)
p_out = xAxis(xl);
curber = wh.getStoValue('ber',plotJob.l,plotJob.d,plotJob.sgm,string(plotJob.pol),plotJob.p_in,p_out,plotJob.pmd,plotJob.gamma,realization,plotJob.numchannels,channspacing);
curzdw = wh.getStoValue('zdw',plotJob.l,plotJob.d,plotJob.sgm,string(plotJob.pol),plotJob.p_in,p_out,plotJob.pmd,plotJob.gamma,realization,plotJob.numchannels,channspacing);
ber(1:size(curber,1),1:size(curber,2),xl) = curber;
zdw(1:size(curber,1),1,xl) = curzdw;
end
ber = squeeze(mean(ber,1));
zdw = squeeze(mean(zdw,1));
hdfec = 3.8e-3.*ones(size(xAxis));
S = [];
wavelength={};
zdw_ = [];
zdw_chann = [];
zdw_tot = [];
S = [];
S_chann = [];
wl = round([1302.03471732576,1304.30061112288,1306.57440520904,1308.85614097425,1311.14586009814,1313.44360455251,1315.74941660391,1318.06333881618],2);
wl = 1:16;
wl = [1.2930 1.2953 1.2975 1.2998 1.3020 1.3043 1.3066 1.3089 1.3111 1.3134 1.3157 1.3181 1.3204 1.3227 1.3251 1.3274];
a = InterX([hdfec(:)';xAxis],[mean(ber,1);xAxis]);
if ~isempty(a)
s(ch) = a(2);
else
s(ch) = NaN;
end
end
figure(2224)
hold on
plot(channelsp,s,'LineWidth',1,'Color',plotJob.color,'Marker','o');

588
Classes/Warehouse_class/functions/fwm_plots/plotCurve.m → Classes/Warehouse_class/functions/phase_predist_plots/fwm_plots/plotCurve.m
View File

@@ -1,294 +1,294 @@
function plotCurve(wh,plotJob)
%PLOTCURVE Summary of this function goes here
% Detailed explanation goes here
fig = findall(groot, 'Type', 'figure', 'Name', plotJob.figName);
if isvalid(fig)
figure(fig)
% fig = get(fig);
AxesMain = fig.CurrentAxes;
hold on
else
fig = figure('name',char(plotJob.figName));
AxesMain = gca;
hold on
end
col = plotJob.color;
% we want to fetch all realizations
if plotJob.pmd == 0
realization = 499;
% realization = 0:7;
else
realization = wh.parameter.realization.values(1:end);
end
realization = wh.parameter.realization.values(1:end);
% get all xAxis values
xAxis = wh.parameter.p_out.values;
markerstyle = 'o';
linestyle = '-';
% Fetch Data from Warehouse
for xl = 1:numel(xAxis)
p_out = xAxis(xl);
if string(plotJob.dataStatArg) == "Worst"
temp = wh.getStoValue('ber',plotJob.l,plotJob.d,plotJob.sgm,string(plotJob.pol),plotJob.p_in,p_out,plotJob.pmd,plotJob.gamma,realization,plotJob.ch,1310,plotJob.channelspacing,plotJob.randzdw);
temp = removeZeros(temp);
ber(xl) = quantile(temp,0.9,"all");
% ber(xl) = max(temp,[],'all');
linew = 1.0;
markersz = plotJob.markersize;
markerstyle = plotJob.markerstyle;
linestyle = plotJob.linestyle;
elseif string(plotJob.dataStatArg) == "AVG"
temp = wh.getStoValue('ber',plotJob.l,plotJob.d,plotJob.sgm,string(plotJob.pol),plotJob.p_in,p_out,plotJob.pmd,plotJob.gamma,realization,plotJob.ch,1310,plotJob.channelspacing,plotJob.randzdw);
temp = removeZeros(temp);
ber(xl) = mean(temp,'all');
linew = 1.0;
markersz = plotJob.markersize;
markerstyle = plotJob.markerstyle;
linestyle = plotJob.linestyle;
elseif string(plotJob.dataStatArg) == "Best"
temp = wh.getStoValue('ber',plotJob.l,plotJob.d,plotJob.sgm,string(plotJob.pol),plotJob.p_in,p_out,plotJob.pmd,plotJob.gamma,realization,plotJob.ch,1310,plotJob.channelspacing,plotJob.randzdw);
temp = removeZeros(temp);
ber(xl) = min(temp,[],'all');
linew = 1.0;
markersz = plotJob.markersize;
markerstyle = plotJob.markerstyle;
linestyle = plotJob.linestyle;
elseif string(plotJob.dataStatArg) == "All Channels; mean(PMD Realizations)"
temp = wh.getStoValue('ber',plotJob.l,plotJob.d,plotJob.sgm,string(plotJob.pol),plotJob.p_in,p_out,plotJob.pmd,plotJob.gamma,realization,plotJob.ch,1310,plotJob.channelspacing,plotJob.randzdw);
temp = removeZeros(temp);
ber(:,xl) = mean(temp,1,"omitnan").';
linew = 1;
markersz = 1;
markerstyle = plotJob.markerstyle;
linestyle = plotJob.linestyle;
elseif string(plotJob.dataStatArg) == "Lineplot with quartiles"
temp = wh.getStoValue('ber',plotJob.l,plotJob.d,plotJob.sgm,string(plotJob.pol),plotJob.p_in,p_out,plotJob.pmd,plotJob.gamma,realization,plotJob.ch,1310,plotJob.channelspacing,plotJob.randzdw);
temp = removeZeros(temp);
ber(xl) = mean(temp,"all","omitnan").';
upperq(xl) = quantile(temp,0.99,"all");
lowerq(xl) = quantile(temp,0.04,"all");
% upperq(xl) = 0.5*std(tmp,1,'all','omitnan');
% lowerq(xl) = 0.5*std(tmp,1,'all','omitnan');
upperq(xl) = max(temp(:));
lowerq(xl) = min(temp(:));
if lowerq(xl) == 0
lowerq(xl) = 1e-8;
end
% upperq(xl) = mean(tmp,"all","omitnan") + 1.96 * (std(tmp,1,'all','omitnan')/sqrt(numel(tmp)));
% lowerq(xl) = mean(tmp,"all","omitnan") - 1.96 * (std(tmp,1,'all','omitnan')/sqrt(numel(tmp)));
linew = 1;
markersz = 1;
linestyle = '-';
elseif string(plotJob.dataStatArg) == "All Channels ;All PMD Realizations"
raw_fetch = wh.getStoValue('ber',plotJob.l,plotJob.d,plotJob.sgm,string(plotJob.pol),plotJob.p_in,p_out,plotJob.pmd,plotJob.gamma,realization,plotJob.ch,1310,plotJob.channelspacing,plotJob.randzdw).';
tmp = reshape(raw_fetch,[],1);
ber(1:size(tmp,1),xl) = tmp;
ber_per_chann(:,:,xl) = raw_fetch;
linew = 0.3;
markersz = 2;
linestyle = ':';
end
end
%routine to remove total outliers (here those wehere the rop curve has a mean BER greater than 0.1)
% ber_per_chann_clean = NaN(size(ber_per_chann));
% for ch = 1:size(ber_per_chann,1)
% bla = squeeze(ber_per_chann(ch,:,:));
% ber_per_chann(ch,find(mean(bla,2)>0.25),:) = NaN;
% cleaned = rmoutliers(bla,"mean",'ThresholdFactor',2);
%
% ber_per_chann_clean(ch,1:size(cleaned,1),1:size(cleaned,2)) = cleaned;
%
% end
%
% ber = [];
% for rop = 1:size(ber_per_chann,3)
% temp = squeeze(ber_per_chann_clean(:,:,rop));
% ber(rop) = mean(temp,"all","omitnan").';
% upperq(rop) = quantile(temp,0.9,"all");
% lowerq(rop) = quantile(temp,0.1,"all");
% end
xAxis = xAxis;
% Plot Data
if string(plotJob.plotTypeArg) == "Scatter"
for rlz = 1:size(ber,1)
if rlz < size(ber,1)
scatter(xAxis,ber(rlz,:),markersz,'MarkerEdgeColor',col,'MarkerFaceColor',col,'Parent', AxesMain(1),'HandleVisibility','off');
else
scatter(xAxis,ber(rlz,:),markersz,'MarkerEdgeColor',col,'MarkerFaceColor',col,'Parent', AxesMain(1),'DisplayName',[plotJob.dataStatArg,' Ch.: ', plotJob.displayname]);
end
end
elseif string(plotJob.plotTypeArg) == "Lines"
% if ~anynan(ber)
% [xAxis,ber] = interpCurve(xAxis, ber);
% end
cols = cbrewer2('RdBu',size(ber,1));
for rlz = 1:size(ber,1)
%
if (string(plotJob.dataStatArg) == "All Channels ;All PMD Realizations")||(string(plotJob.dataStatArg) == "All Channels; mean(PMD Realizations)")
ch = mod(rlz,plotJob.ch);
if ch == 0; ch = plotJob.ch; end
else
ch = plotJob.dataStatArg;
end
if rlz < size(ber,1)
col = cols(rlz,:);
s = plot(xAxis,ber(rlz,:),linestyle,'Marker',"none",'MarkerSize',markersz,'LineWidth',linew,'Color',col,'Parent', AxesMain,'HandleVisibility','off');
s.DataTipTemplate.Interpreter = "latex";
s.DataTipTemplate.DataTipRows(1).Label = "Ch: ";
s.DataTipTemplate.DataTipRows(1).Value = repmat(ch,size(ber));
s.DataTipTemplate.DataTipRows(1);
s.DataTipTemplate.DataTipRows(2) = [];
else
if string(plotJob.dataStatArg) == "Lineplot with quartiles"
[hl,hp] = boundedline(xAxis,ber(rlz,:),([(ber(rlz,:)-lowerq(rlz,:));upperq(rlz,:)-ber(rlz,:)]'),'-o','alpha','Color',col,'transparency', 0.06,'linewidth',0.7);
hl.MarkerFaceColor = col;
hl.MarkerSize = 2;
set(hp,'HandleVisibility','off');
%hp.LineWidth = 1.2;
ho = outlinebounds(hl,hp);
set(ho, 'linestyle', ':', 'color', col,'Linewidth',0.6);
set(ho,'HandleVisibility','off');
% errorbar(xAxis,ber(rlz,:),ber(rlz,:)-lowerq(rlz,:),upperq(rlz,:)-ber(rlz,:),'-o','Color',col,'linewidth',0.7);
else
s = plot(xAxis,ber(rlz,:),linestyle,'Marker',markerstyle,'MarkerFaceColor',col,'MarkerSize',markersz,'LineWidth',linew,'Color',col,'Parent', AxesMain,'DisplayName',[plotJob.displayname]);
s.DataTipTemplate.Interpreter = "latex";
s.DataTipTemplate.DataTipRows(1).Label = "Ch: ";
s.DataTipTemplate.DataTipRows(1).Value = repmat(string(ch),size(ber));
s.DataTipTemplate.DataTipRows(1)
s.DataTipTemplate.DataTipRows(2) = [];
end
end
end
end
% Draw FEC Threshold Line
%get x data of first children:
%get all linear Values
if 0
linear = wh.getStoValue('ber',plotJob.l,plotJob.d,plotJob.sgm,string(plotJob.pol),plotJob.p_in,wh.parameter.p_out.values,0,0,499,"symmetric");
linear = mean(linear,2);
lincurve = findall(AxesMain, 'Type', 'line','DisplayName','Linear Baseline');
%
if isempty(lincurve)
xdata = AxesMain.Children(1).XData;
hdfec = 3.8e-3.*ones(size(xdata));
plot(xdata,linear,'-','Marker',"o",'MarkerSize',3,'LineWidth',4,'Color',[0.6400 0.6400 0.6400],'MarkerFaceColor',[0.6400 0.6400 0.6400],'Parent', AxesMain,'DisplayName','Linear Baseline');
%h = get(gca,'Children');
%set(gca,'Children',[h(2) h(1)])
end
end
feccurve = findall(AxesMain, 'Type', 'line','DisplayName','FEC $3.8*10^{-3}$');
%
if isempty(feccurve)
xdata = AxesMain.Children(1).XData;
hdfec = 3.8e-3.*ones(size(xdata));
plot(xdata,hdfec,'--','MarkerSize',4,'Color','black','MarkerFaceColor','black','LineWidth',1,'Parent', AxesMain,'DisplayName','FEC $3.8*10^{-3}$','HandleVisibility','off');
%h = get(gca,'Children');
%set(gca,'Children',[h(2) h(1)])
end
% Figure Settings
%title(AxesMain,plotJob.title,"Interpreter","none");
xlabel(AxesMain,plotJob.xAxisLabel,"Interpreter","latex");
ylabel(AxesMain,plotJob.yAxisLabel,"Interpreter","latex");
set(AxesMain,'yscale','log');
grid(AxesMain,'on');
grid(AxesMain,'minor');
grid minor
%legend(AxesMain);
fontsize(AxesMain,8,"points")
% fontname(AxesMain,"Arial")
% fig.Position = plotJob.Position;
% fig.Units = "centimeters";
% fig.Position = [2 2 8.5 7];
set(AxesMain,'TickLabelInterpreter','latex')
set(AxesMain.Legend,'Interpreter','latex')
% set(gcf,'Units','centimeters')
% set(gcf,'Position',[2 2 9 4.5])
ylim([1e-5,0.3]);
xlim([-10,-4]);
% annotation('textbox', [0.125, 0.32, 0.1, 0.1], 'String', "FEC 3.8e-3","LineStyle","none","FontSize",8,"FontUnits","points")
hold off
end
function vec = removeZeros(vec)
% Find rows that contain only zeros
rows_to_remove = all(vec == 0, 2);
% Remove rows with only zeros
vec(rows_to_remove, :) = [];
end
function plotCurve(wh,plotJob)
%PLOTCURVE Summary of this function goes here
% Detailed explanation goes here
fig = findall(groot, 'Type', 'figure', 'Name', plotJob.figName);
if isvalid(fig)
figure(fig)
% fig = get(fig);
AxesMain = fig.CurrentAxes;
hold on
else
fig = figure('name',char(plotJob.figName));
AxesMain = gca;
hold on
end
col = plotJob.color;
% we want to fetch all realizations
if plotJob.pmd == 0
realization = 499;
% realization = 0:7;
else
realization = wh.parameter.realization.values(1:end);
end
realization = wh.parameter.realization.values(1:end);
% get all xAxis values
xAxis = wh.parameter.p_out.values;
markerstyle = 'o';
linestyle = '-';
% Fetch Data from Warehouse
for xl = 1:numel(xAxis)
p_out = xAxis(xl);
if string(plotJob.dataStatArg) == "Worst"
temp = wh.getStoValue('ber',plotJob.l,plotJob.d,plotJob.sgm,string(plotJob.pol),plotJob.p_in,p_out,plotJob.pmd,plotJob.gamma,realization,plotJob.ch,1310,plotJob.channelspacing,plotJob.randzdw);
temp = removeZeros(temp);
ber(xl) = quantile(temp,0.9,"all");
% ber(xl) = max(temp,[],'all');
linew = 1.0;
markersz = plotJob.markersize;
markerstyle = plotJob.markerstyle;
linestyle = plotJob.linestyle;
elseif string(plotJob.dataStatArg) == "AVG"
temp = wh.getStoValue('ber',plotJob.l,plotJob.d,plotJob.sgm,string(plotJob.pol),plotJob.p_in,p_out,plotJob.pmd,plotJob.gamma,realization,plotJob.ch,1310,plotJob.channelspacing,plotJob.randzdw);
temp = removeZeros(temp);
ber(xl) = mean(temp,'all');
linew = 1.0;
markersz = plotJob.markersize;
markerstyle = plotJob.markerstyle;
linestyle = plotJob.linestyle;
elseif string(plotJob.dataStatArg) == "Best"
temp = wh.getStoValue('ber',plotJob.l,plotJob.d,plotJob.sgm,string(plotJob.pol),plotJob.p_in,p_out,plotJob.pmd,plotJob.gamma,realization,plotJob.ch,1310,plotJob.channelspacing,plotJob.randzdw);
temp = removeZeros(temp);
ber(xl) = min(temp,[],'all');
linew = 1.0;
markersz = plotJob.markersize;
markerstyle = plotJob.markerstyle;
linestyle = plotJob.linestyle;
elseif string(plotJob.dataStatArg) == "All Channels; mean(PMD Realizations)"
temp = wh.getStoValue('ber',plotJob.l,plotJob.d,plotJob.sgm,string(plotJob.pol),plotJob.p_in,p_out,plotJob.pmd,plotJob.gamma,realization,plotJob.ch,1310,plotJob.channelspacing,plotJob.randzdw);
temp = removeZeros(temp);
ber(:,xl) = mean(temp,1,"omitnan").';
linew = 1;
markersz = 1;
markerstyle = plotJob.markerstyle;
linestyle = plotJob.linestyle;
elseif string(plotJob.dataStatArg) == "Lineplot with quartiles"
temp = wh.getStoValue('ber',plotJob.l,plotJob.d,plotJob.sgm,string(plotJob.pol),plotJob.p_in,p_out,plotJob.pmd,plotJob.gamma,realization,plotJob.ch,1310,plotJob.channelspacing,plotJob.randzdw);
temp = removeZeros(temp);
ber(xl) = mean(temp,"all","omitnan").';
upperq(xl) = quantile(temp,0.99,"all");
lowerq(xl) = quantile(temp,0.04,"all");
% upperq(xl) = 0.5*std(tmp,1,'all','omitnan');
% lowerq(xl) = 0.5*std(tmp,1,'all','omitnan');
upperq(xl) = max(temp(:));
lowerq(xl) = min(temp(:));
if lowerq(xl) == 0
lowerq(xl) = 1e-8;
end
% upperq(xl) = mean(tmp,"all","omitnan") + 1.96 * (std(tmp,1,'all','omitnan')/sqrt(numel(tmp)));
% lowerq(xl) = mean(tmp,"all","omitnan") - 1.96 * (std(tmp,1,'all','omitnan')/sqrt(numel(tmp)));
linew = 1;
markersz = 1;
linestyle = '-';
elseif string(plotJob.dataStatArg) == "All Channels ;All PMD Realizations"
raw_fetch = wh.getStoValue('ber',plotJob.l,plotJob.d,plotJob.sgm,string(plotJob.pol),plotJob.p_in,p_out,plotJob.pmd,plotJob.gamma,realization,plotJob.ch,1310,plotJob.channelspacing,plotJob.randzdw).';
tmp = reshape(raw_fetch,[],1);
ber(1:size(tmp,1),xl) = tmp;
ber_per_chann(:,:,xl) = raw_fetch;
linew = 0.3;
markersz = 2;
linestyle = ':';
end
end
%routine to remove total outliers (here those wehere the rop curve has a mean BER greater than 0.1)
% ber_per_chann_clean = NaN(size(ber_per_chann));
% for ch = 1:size(ber_per_chann,1)
% bla = squeeze(ber_per_chann(ch,:,:));
% ber_per_chann(ch,find(mean(bla,2)>0.25),:) = NaN;
% cleaned = rmoutliers(bla,"mean",'ThresholdFactor',2);
%
% ber_per_chann_clean(ch,1:size(cleaned,1),1:size(cleaned,2)) = cleaned;
%
% end
%
% ber = [];
% for rop = 1:size(ber_per_chann,3)
% temp = squeeze(ber_per_chann_clean(:,:,rop));
% ber(rop) = mean(temp,"all","omitnan").';
% upperq(rop) = quantile(temp,0.9,"all");
% lowerq(rop) = quantile(temp,0.1,"all");
% end
xAxis = xAxis;
% Plot Data
if string(plotJob.plotTypeArg) == "Scatter"
for rlz = 1:size(ber,1)
if rlz < size(ber,1)
scatter(xAxis,ber(rlz,:),markersz,'MarkerEdgeColor',col,'MarkerFaceColor',col,'Parent', AxesMain(1),'HandleVisibility','off');
else
scatter(xAxis,ber(rlz,:),markersz,'MarkerEdgeColor',col,'MarkerFaceColor',col,'Parent', AxesMain(1),'DisplayName',[plotJob.dataStatArg,' Ch.: ', plotJob.displayname]);
end
end
elseif string(plotJob.plotTypeArg) == "Lines"
% if ~anynan(ber)
% [xAxis,ber] = interpCurve(xAxis, ber);
% end
cols = cbrewer2('RdBu',size(ber,1));
for rlz = 1:size(ber,1)
%
if (string(plotJob.dataStatArg) == "All Channels ;All PMD Realizations")||(string(plotJob.dataStatArg) == "All Channels; mean(PMD Realizations)")
ch = mod(rlz,plotJob.ch);
if ch == 0; ch = plotJob.ch; end
else
ch = plotJob.dataStatArg;
end
if rlz < size(ber,1)
col = cols(rlz,:);
s = plot(xAxis,ber(rlz,:),linestyle,'Marker',"none",'MarkerSize',markersz,'LineWidth',linew,'Color',col,'Parent', AxesMain,'HandleVisibility','off');
s.DataTipTemplate.Interpreter = "latex";
s.DataTipTemplate.DataTipRows(1).Label = "Ch: ";
s.DataTipTemplate.DataTipRows(1).Value = repmat(ch,size(ber));
s.DataTipTemplate.DataTipRows(1);
s.DataTipTemplate.DataTipRows(2) = [];
else
if string(plotJob.dataStatArg) == "Lineplot with quartiles"
[hl,hp] = boundedline(xAxis,ber(rlz,:),([(ber(rlz,:)-lowerq(rlz,:));upperq(rlz,:)-ber(rlz,:)]'),'-o','alpha','Color',col,'transparency', 0.06,'linewidth',0.7);
hl.MarkerFaceColor = col;
hl.MarkerSize = 2;
set(hp,'HandleVisibility','off');
%hp.LineWidth = 1.2;
ho = outlinebounds(hl,hp);
set(ho, 'linestyle', ':', 'color', col,'Linewidth',0.6);
set(ho,'HandleVisibility','off');
% errorbar(xAxis,ber(rlz,:),ber(rlz,:)-lowerq(rlz,:),upperq(rlz,:)-ber(rlz,:),'-o','Color',col,'linewidth',0.7);
else
s = plot(xAxis,ber(rlz,:),linestyle,'Marker',markerstyle,'MarkerFaceColor',col,'MarkerSize',markersz,'LineWidth',linew,'Color',col,'Parent', AxesMain,'DisplayName',[plotJob.displayname]);
s.DataTipTemplate.Interpreter = "latex";
s.DataTipTemplate.DataTipRows(1).Label = "Ch: ";
s.DataTipTemplate.DataTipRows(1).Value = repmat(string(ch),size(ber));
s.DataTipTemplate.DataTipRows(1)
s.DataTipTemplate.DataTipRows(2) = [];
end
end
end
end
% Draw FEC Threshold Line
%get x data of first children:
%get all linear Values
if 0
linear = wh.getStoValue('ber',plotJob.l,plotJob.d,plotJob.sgm,string(plotJob.pol),plotJob.p_in,wh.parameter.p_out.values,0,0,499,"symmetric");
linear = mean(linear,2);
lincurve = findall(AxesMain, 'Type', 'line','DisplayName','Linear Baseline');
%
if isempty(lincurve)
xdata = AxesMain.Children(1).XData;
hdfec = 3.8e-3.*ones(size(xdata));
plot(xdata,linear,'-','Marker',"o",'MarkerSize',3,'LineWidth',4,'Color',[0.6400 0.6400 0.6400],'MarkerFaceColor',[0.6400 0.6400 0.6400],'Parent', AxesMain,'DisplayName','Linear Baseline');
%h = get(gca,'Children');
%set(gca,'Children',[h(2) h(1)])
end
end
feccurve = findall(AxesMain, 'Type', 'line','DisplayName','FEC $3.8*10^{-3}$');
%
if isempty(feccurve)
xdata = AxesMain.Children(1).XData;
hdfec = 3.8e-3.*ones(size(xdata));
plot(xdata,hdfec,'--','MarkerSize',4,'Color','black','MarkerFaceColor','black','LineWidth',1,'Parent', AxesMain,'DisplayName','FEC $3.8*10^{-3}$','HandleVisibility','off');
%h = get(gca,'Children');
%set(gca,'Children',[h(2) h(1)])
end
% Figure Settings
%title(AxesMain,plotJob.title,"Interpreter","none");
xlabel(AxesMain,plotJob.xAxisLabel,"Interpreter","latex");
ylabel(AxesMain,plotJob.yAxisLabel,"Interpreter","latex");
set(AxesMain,'yscale','log');
grid(AxesMain,'on');
grid(AxesMain,'minor');
grid minor
%legend(AxesMain);
fontsize(AxesMain,8,"points")
% fontname(AxesMain,"Arial")
% fig.Position = plotJob.Position;
% fig.Units = "centimeters";
% fig.Position = [2 2 8.5 7];
set(AxesMain,'TickLabelInterpreter','latex')
set(AxesMain.Legend,'Interpreter','latex')
% set(gcf,'Units','centimeters')
% set(gcf,'Position',[2 2 9 4.5])
ylim([1e-5,0.3]);
xlim([-10,-4]);
% annotation('textbox', [0.125, 0.32, 0.1, 0.1], 'String', "FEC 3.8e-3","LineStyle","none","FontSize",8,"FontUnits","points")
hold off
end
function vec = removeZeros(vec)
% Find rows that contain only zeros
rows_to_remove = all(vec == 0, 2);
% Remove rows with only zeros
vec(rows_to_remove, :) = [];
end

300
Classes/Warehouse_class/functions/fwm_plots/plotHistogram.m → Classes/Warehouse_class/functions/phase_predist_plots/fwm_plots/plotHistogram.m
View File

@@ -1,151 +1,151 @@
function plotHistogram(wh,plotJob)
fig = findall(groot, 'Type', 'figure', 'Name', plotJob.figName);
if isvalid(fig)
figure(fig)
fig = get(fig);
AxesMain = fig.CurrentAxes;
hold on
else
fig = figure('name',char(plotJob.figName));
AxesMain = gca;
hold on
end
col = plotJob.color;
% we want to fetch all realizations
realization = wh.parameter.realization.values(1:end);
% get all xAxis values
xAxis = wh.parameter.p_out.values;
% Fetch Data from Warehouse
for xl = 1:numel(xAxis)
p_out = xAxis(xl);
if string(plotJob.dataStatArg) == "Worst"
ber(xl) = max(wh.getStoValue('ber',plotJob.l,plotJob.d,plotJob.sgm,string(plotJob.pol),plotJob.p_in,p_out,plotJob.pmd,plotJob.gamma,realization,string(plotJob.channelplan),string(plotJob.dsp)),[],'all');
linew = 2.0;
markersz = 3;
linestyle = '-';
elseif string(plotJob.dataStatArg) == "AVG"
ber(xl) = mean(wh.getStoValue('ber',plotJob.l,plotJob.d,plotJob.sgm,string(plotJob.pol),plotJob.p_in,p_out,plotJob.pmd,plotJob.gamma,realization,string(plotJob.channelplan),string(plotJob.dsp)),'all');
linew = 2.0;
markersz = 3;
linestyle = ':';
elseif string(plotJob.dataStatArg) == "Best"
ber(xl) = min(wh.getStoValue('ber',plotJob.l,plotJob.d,plotJob.sgm,string(plotJob.pol),plotJob.p_in,p_out,plotJob.pmd,plotJob.gamma,realization,string(plotJob.channelplan),string(plotJob.dsp)),[],'all');
linew = 2.0;
markersz = 3;
linestyle = ':';
elseif string(plotJob.dataStatArg) == "All Channels; mean(PMD Realizations)"
tmp = wh.getStoValue('ber',plotJob.l,plotJob.d,plotJob.sgm,string(plotJob.pol),plotJob.p_in,p_out,plotJob.pmd,plotJob.gamma,realization,string(plotJob.channelplan),string(plotJob.dsp));
if numel(tmp(tmp==0)) ~= 0
disp('Removed all zero values!');
tmp(tmp==0) = NaN;
end
ber(:,xl) = mean(tmp,1,"omitnan").';
linew = 0.7;
markersz = 2;
linestyle = '-';
elseif string(plotJob.dataStatArg) == "All Channels ;All PMD Realizations"
tmp = reshape(wh.getStoValue('ber',plotJob.l,plotJob.d,plotJob.sgm,string(plotJob.pol),plotJob.p_in,p_out,plotJob.pmd,plotJob.gamma,realization,string(plotJob.channelplan),string(plotJob.dsp)).',[],1);
ber(1:size(tmp,1),xl) = tmp;
linew = 0.3;
markersz = 2;
linestyle = ':';
end
end
disp('Removed all zero values!');
ber(ber==0) = NaN;
if ~anynan(ber)
[xAxis,ber] = interpCurve(xAxis, ber);
end
% plot FEC Crossing as histogram
hdfec = 3.8e-3.*ones(size(xAxis));
S = [];
for i = 1:size(ber,1)
a = InterX([hdfec;xAxis],[ber(i,:);xAxis]);
if ~isempty(a)
S(:,i) = a;
end
end
%% SUB 1
AxesMain = subplot(2,1,1);
hold on
if ~isempty(S)
histogram(S(end,:),300,'Normalization','probability','FaceColor',col,'EdgeColor',col,'Parent',AxesMain,'DisplayName',[plotJob.dataStatArg,' Ch.: ', plotJob.displayname],'FaceAlpha',0.4,'EdgeAlpha',0.4);
end
xlim([-3 ,9 ]);
ylim([0 .10]);
% Figure Settings
title(AxesMain,['$P_{in}:$ ',num2str(plotJob.p_in-9), 'dBm; L : ', num2str(plotJob.l),'Km'],'Interpreter','latex');
xlabel(AxesMain,plotJob.xAxisLabel,'Interpreter','latex');
ylabel('PDF')
grid(AxesMain,'on');
grid(AxesMain,'minor');
%legend(AxesMain,'Interpreter','latex');
fontsize(AxesMain,24,"pixels")
hold off
%% SUB 2
AxesMain = subplot(2,1,2);
if ~isempty(S)
hold on
[f1,x1]=ecdf(S(end,:));
plot(x1,f1,'r','LineWidth',3, 'Color',col,'DisplayName',[plotJob.dataStatArg,' Ch.: ', plotJob.displayname]);
end
xlim([-3 ,9 ]);
ylim([0 1]);
% Figure Settings
title(AxesMain,['$P_{in}:$ ',num2str(plotJob.p_in-9), 'dBm; L : ', num2str(plotJob.l),'Km'],'Interpreter','latex');
xlabel(AxesMain,plotJob.xAxisLabel,'Interpreter','latex');
ylabel('CDF')
grid(AxesMain,'on');
grid(AxesMain,'minor');
fontsize(AxesMain,24,"pixels")
%legend(AxesMain,'Interpreter','latex');
fig.Position = plotJob.Position;
hold off
function plotHistogram(wh,plotJob)
fig = findall(groot, 'Type', 'figure', 'Name', plotJob.figName);
if isvalid(fig)
figure(fig)
fig = get(fig);
AxesMain = fig.CurrentAxes;
hold on
else
fig = figure('name',char(plotJob.figName));
AxesMain = gca;
hold on
end
col = plotJob.color;
% we want to fetch all realizations
realization = wh.parameter.realization.values(1:end);
% get all xAxis values
xAxis = wh.parameter.p_out.values;
% Fetch Data from Warehouse
for xl = 1:numel(xAxis)
p_out = xAxis(xl);
if string(plotJob.dataStatArg) == "Worst"
ber(xl) = max(wh.getStoValue('ber',plotJob.l,plotJob.d,plotJob.sgm,string(plotJob.pol),plotJob.p_in,p_out,plotJob.pmd,plotJob.gamma,realization,string(plotJob.channelplan),string(plotJob.dsp)),[],'all');
linew = 2.0;
markersz = 3;
linestyle = '-';
elseif string(plotJob.dataStatArg) == "AVG"
ber(xl) = mean(wh.getStoValue('ber',plotJob.l,plotJob.d,plotJob.sgm,string(plotJob.pol),plotJob.p_in,p_out,plotJob.pmd,plotJob.gamma,realization,string(plotJob.channelplan),string(plotJob.dsp)),'all');
linew = 2.0;
markersz = 3;
linestyle = ':';
elseif string(plotJob.dataStatArg) == "Best"
ber(xl) = min(wh.getStoValue('ber',plotJob.l,plotJob.d,plotJob.sgm,string(plotJob.pol),plotJob.p_in,p_out,plotJob.pmd,plotJob.gamma,realization,string(plotJob.channelplan),string(plotJob.dsp)),[],'all');
linew = 2.0;
markersz = 3;
linestyle = ':';
elseif string(plotJob.dataStatArg) == "All Channels; mean(PMD Realizations)"
tmp = wh.getStoValue('ber',plotJob.l,plotJob.d,plotJob.sgm,string(plotJob.pol),plotJob.p_in,p_out,plotJob.pmd,plotJob.gamma,realization,string(plotJob.channelplan),string(plotJob.dsp));
if numel(tmp(tmp==0)) ~= 0
disp('Removed all zero values!');
tmp(tmp==0) = NaN;
end
ber(:,xl) = mean(tmp,1,"omitnan").';
linew = 0.7;
markersz = 2;
linestyle = '-';
elseif string(plotJob.dataStatArg) == "All Channels ;All PMD Realizations"
tmp = reshape(wh.getStoValue('ber',plotJob.l,plotJob.d,plotJob.sgm,string(plotJob.pol),plotJob.p_in,p_out,plotJob.pmd,plotJob.gamma,realization,string(plotJob.channelplan),string(plotJob.dsp)).',[],1);
ber(1:size(tmp,1),xl) = tmp;
linew = 0.3;
markersz = 2;
linestyle = ':';
end
end
disp('Removed all zero values!');
ber(ber==0) = NaN;
if ~anynan(ber)
[xAxis,ber] = interpCurve(xAxis, ber);
end
% plot FEC Crossing as histogram
hdfec = 3.8e-3.*ones(size(xAxis));
S = [];
for i = 1:size(ber,1)
a = InterX([hdfec;xAxis],[ber(i,:);xAxis]);
if ~isempty(a)
S(:,i) = a;
end
end
%% SUB 1
AxesMain = subplot(2,1,1);
hold on
if ~isempty(S)
histogram(S(end,:),300,'Normalization','probability','FaceColor',col,'EdgeColor',col,'Parent',AxesMain,'DisplayName',[plotJob.dataStatArg,' Ch.: ', plotJob.displayname],'FaceAlpha',0.4,'EdgeAlpha',0.4);
end
xlim([-3 ,9 ]);
ylim([0 .10]);
% Figure Settings
title(AxesMain,['$P_{in}:$ ',num2str(plotJob.p_in-9), 'dBm; L : ', num2str(plotJob.l),'Km'],'Interpreter','latex');
xlabel(AxesMain,plotJob.xAxisLabel,'Interpreter','latex');
ylabel('PDF')
grid(AxesMain,'on');
grid(AxesMain,'minor');
%legend(AxesMain,'Interpreter','latex');
fontsize(AxesMain,24,"pixels")
hold off
%% SUB 2
AxesMain = subplot(2,1,2);
if ~isempty(S)
hold on
[f1,x1]=ecdf(S(end,:));
plot(x1,f1,'r','LineWidth',3, 'Color',col,'DisplayName',[plotJob.dataStatArg,' Ch.: ', plotJob.displayname]);
end
xlim([-3 ,9 ]);
ylim([0 1]);
% Figure Settings
title(AxesMain,['$P_{in}:$ ',num2str(plotJob.p_in-9), 'dBm; L : ', num2str(plotJob.l),'Km'],'Interpreter','latex');
xlabel(AxesMain,plotJob.xAxisLabel,'Interpreter','latex');
ylabel('CDF')
grid(AxesMain,'on');
grid(AxesMain,'minor');
fontsize(AxesMain,24,"pixels")
%legend(AxesMain,'Interpreter','latex');
fig.Position = plotJob.Position;
hold off
end

410
Classes/Warehouse_class/functions/fwm_plots/plotViolin.m → Classes/Warehouse_class/functions/phase_predist_plots/fwm_plots/plotViolin.m
View File

@@ -1,206 +1,206 @@
function plotViolin(wh,plotJob)
fig = findall(groot, 'Type', 'figure', 'Name', plotJob.figName);
if isvalid(fig)
figure(fig)
fig = get(fig);
AxesMain = fig.CurrentAxes;
hold on
else
fig = figure('name',char(plotJob.figName));
AxesMain = gca;
hold on
end
%% Violin
col = plotJob.color;
% we want to fetch all realizations
if plotJob.pmd == 0
realization = 1;
else
realization = wh.parameter.realization.values(1:end);
end
%realization = 0:8;
% get all xAxis values
xAxis = wh.parameter.p_out.values;
% ber = NaN(500,16,10);
% zdw = NaN(500,1,10);
%get BER values for query
for xl = 1:numel(xAxis)
p_out = xAxis(xl);
curber = wh.getStoValue('ber',plotJob.l,plotJob.d,plotJob.sgm,string(plotJob.pol),plotJob.p_in,p_out,plotJob.pmd,plotJob.gamma,realization,plotJob.ch,1310,plotJob.channelspacing,plotJob.randzdw);
curber= removeZeros(curber);
ber(1:size(curber,1),1:size(curber,2),xl) = curber;
end
% to remove outliers set the percentile range
% a = squeeze(mean(ber,2));
% out = isoutlier(mean(a,2),"percentiles",[0 100]);
% ber = ber(~out,:,:);
% disp(sum(out));
hdfec = 3.8e-3.*ones(size(xAxis));
S = [];
wavelength={};
S = [];
S_chann = [];
wl = calcWavelengthPlan(plotJob.ch,plotJob.channelspacing,1310);
%get fec thresholds
% [C,ia,ib] =intersect(linx,xAxis);
% linear = squeeze(linear);
%ber(ber==0) = NaN;
S_chann_no_crossing = zeros(1,plotJob.ch);
for chann = 1:size(ber,2)
for realiz = 1:size(ber,1)
ber_series = squeeze(ber(realiz,chann,:)).';
if mean(ber_series) > 0.1
continue
end
a = InterX([hdfec(:)';xAxis],[ber_series;xAxis]);
if ~isempty(a)
S_chann(realiz,chann) = a(2);
% if a(2) > -7 && string(plotJob.pol) == "copolarized"
% continue
% end
S(end+1) = a(2);
wavelength{end+1} = num2str(wl(chann));
else
S(end+1) = 0;
wavelength{end+1} = num2str(wl(chann));
S_chann_no_crossing(realiz,chann) = 1;
S_chann(realiz,chann) = -1;
end
end
end
threshold = -6;
FEC_crossed = sum(S_chann < threshold & ~isnan(S_chann),1);
FEC_not_crossed = sum(S_chann >= threshold & ~isnan(S_chann),1);
failure_rate = FEC_not_crossed ./ (FEC_crossed + FEC_not_crossed) ;
S_chann(S_chann==0) = NaN;
total_avg = mean(S_chann,"all","omitnan");
%figure(2024)
%C = flip(cbrewer2('Spectral',8));
if numel(S) <= numel(wl)
vs = scatter(1:numel(S),S,50,'o','MarkerEdgeColor','black','MarkerFaceColor',plotJob.color,'LineWidth',1,'HandleVisibility','off');
%vs = scatter(1,mean(S),50,'o','MarkerEdgeColor','black','MarkerFaceColor',plotJob.color,'LineWidth',1);
else
vs = violinplot(S,wavelength,...
'ViolinColor',plotJob.color,...
'ViolinAlpha',0.1,...
'MarkerSize',1,...
'ShowMedian',false,...
'EdgeColor',plotJob.color,...
'ShowWhiskers',false,...
'ShowData',false,...
'ShowBox',false,...
'Bandwidth',0.051 ...
);
hold on
partly_failed = boolean(ceil(failure_rate));
avg = mean(S_chann,1,"omitnan");
notfailed = ~partly_failed .* avg;
notfailed(notfailed==0) = NaN;
scatter(1:size(S_chann,2),notfailed,10,'Marker','x','MarkerEdgeColor','black','MarkerFaceColor',plotJob.color,'LineWidth',0.5,'HandleVisibility','off');
hold on
partly_failed = partly_failed.*avg;
partly_failed(partly_failed==0) = NaN;
s=scatter(1:numel(failure_rate),partly_failed,10,'Marker','x','LineWidth',0.5,'HandleVisibility','off','MarkerEdgeColor','red');
s.DataTipTemplate.Interpreter = "latex";
s.DataTipTemplate.DataTipRows(1).Label = "Fail Rate: ";
s.DataTipTemplate.DataTipRows(1).Value = failure_rate;
s.DataTipTemplate.DataTipRows(2) = [];
hold off
end
% ax = gca;
% ax.XTicks
hold on
yline(total_avg,'LineWidth',1,'LineStyle','--','DisplayName','System Avg.')
fig.Position = plotJob.Position;
xticklabels(1:16);
ylabel('Penalty in dB');
xlabel('Channel Number');
ylim([-9.3,-3]);
xlim([0,plotJob.ch+1]);
% grid minor;
set(gca, 'color', 'none');
legend = [];
fontsize(AxesMain,8,"points")
fig.Position = plotJob.Position;
fig.Units = "centimeters";
fig.Position = [2 2 8.5 7];
set(AxesMain,'TickLabelInterpreter','latex')
set(AxesMain.Legend,'Interpreter','latex')
if 0
ber_sorted = sort(S);
z1 = [];
penalty = mean(ber_sorted):0.01:mean(ber_sorted)+2;
for i = 1:length(penalty)
l = penalty(i);
if i == 1
z1 = [z1 sum(ber_sorted(1,:)<l ) / length(ber_sorted) ];
else
z1 = [z1 sum(ber_sorted(1,:)<l & ber_sorted(1,:)>l-0.01) / length(ber_sorted) ];
end
end
penalty_higherthan = 0.5;
probability = sum(z1(find(penalty>mean(ber_sorted)+penalty_higherthan)));
disp(['A penalty of more than 0.5 dB has a probability of: ', num2str(probability)]);
end
end
function vec = removeZeros(vec)
% Find rows that contain only zeros
rows_to_remove = all(vec == 0, 2);
% Remove rows with only zeros
vec(rows_to_remove, :) = [];
function plotViolin(wh,plotJob)
fig = findall(groot, 'Type', 'figure', 'Name', plotJob.figName);
if isvalid(fig)
figure(fig)
fig = get(fig);
AxesMain = fig.CurrentAxes;
hold on
else
fig = figure('name',char(plotJob.figName));
AxesMain = gca;
hold on
end
%% Violin
col = plotJob.color;
% we want to fetch all realizations
if plotJob.pmd == 0
realization = 1;
else
realization = wh.parameter.realization.values(1:end);
end
%realization = 0:8;
% get all xAxis values
xAxis = wh.parameter.p_out.values;
% ber = NaN(500,16,10);
% zdw = NaN(500,1,10);
%get BER values for query
for xl = 1:numel(xAxis)
p_out = xAxis(xl);
curber = wh.getStoValue('ber',plotJob.l,plotJob.d,plotJob.sgm,string(plotJob.pol),plotJob.p_in,p_out,plotJob.pmd,plotJob.gamma,realization,plotJob.ch,1310,plotJob.channelspacing,plotJob.randzdw);
curber= removeZeros(curber);
ber(1:size(curber,1),1:size(curber,2),xl) = curber;
end
% to remove outliers set the percentile range
% a = squeeze(mean(ber,2));
% out = isoutlier(mean(a,2),"percentiles",[0 100]);
% ber = ber(~out,:,:);
% disp(sum(out));
hdfec = 3.8e-3.*ones(size(xAxis));
S = [];
wavelength={};
S = [];
S_chann = [];
wl = calcWavelengthPlan(plotJob.ch,plotJob.channelspacing,1310);
%get fec thresholds
% [C,ia,ib] =intersect(linx,xAxis);
% linear = squeeze(linear);
%ber(ber==0) = NaN;
S_chann_no_crossing = zeros(1,plotJob.ch);
for chann = 1:size(ber,2)
for realiz = 1:size(ber,1)
ber_series = squeeze(ber(realiz,chann,:)).';
if mean(ber_series) > 0.1
continue
end
a = InterX([hdfec(:)';xAxis],[ber_series;xAxis]);
if ~isempty(a)
S_chann(realiz,chann) = a(2);
% if a(2) > -7 && string(plotJob.pol) == "copolarized"
% continue
% end
S(end+1) = a(2);
wavelength{end+1} = num2str(wl(chann));
else
S(end+1) = 0;
wavelength{end+1} = num2str(wl(chann));
S_chann_no_crossing(realiz,chann) = 1;
S_chann(realiz,chann) = -1;
end
end
end
threshold = -6;
FEC_crossed = sum(S_chann < threshold & ~isnan(S_chann),1);
FEC_not_crossed = sum(S_chann >= threshold & ~isnan(S_chann),1);
failure_rate = FEC_not_crossed ./ (FEC_crossed + FEC_not_crossed) ;
S_chann(S_chann==0) = NaN;
total_avg = mean(S_chann,"all","omitnan");
%figure(2024)
%C = flip(cbrewer2('Spectral',8));
if numel(S) <= numel(wl)
vs = scatter(1:numel(S),S,50,'o','MarkerEdgeColor','black','MarkerFaceColor',plotJob.color,'LineWidth',1,'HandleVisibility','off');
%vs = scatter(1,mean(S),50,'o','MarkerEdgeColor','black','MarkerFaceColor',plotJob.color,'LineWidth',1);
else
vs = violinplot(S,wavelength,...
'ViolinColor',plotJob.color,...
'ViolinAlpha',0.1,...
'MarkerSize',1,...
'ShowMedian',false,...
'EdgeColor',plotJob.color,...
'ShowWhiskers',false,...
'ShowData',false,...
'ShowBox',false,...
'Bandwidth',0.051 ...
);
hold on
partly_failed = boolean(ceil(failure_rate));
avg = mean(S_chann,1,"omitnan");
notfailed = ~partly_failed .* avg;
notfailed(notfailed==0) = NaN;
scatter(1:size(S_chann,2),notfailed,10,'Marker','x','MarkerEdgeColor','black','MarkerFaceColor',plotJob.color,'LineWidth',0.5,'HandleVisibility','off');
hold on
partly_failed = partly_failed.*avg;
partly_failed(partly_failed==0) = NaN;
s=scatter(1:numel(failure_rate),partly_failed,10,'Marker','x','LineWidth',0.5,'HandleVisibility','off','MarkerEdgeColor','red');
s.DataTipTemplate.Interpreter = "latex";
s.DataTipTemplate.DataTipRows(1).Label = "Fail Rate: ";
s.DataTipTemplate.DataTipRows(1).Value = failure_rate;
s.DataTipTemplate.DataTipRows(2) = [];
hold off
end
% ax = gca;
% ax.XTicks
hold on
yline(total_avg,'LineWidth',1,'LineStyle','--','DisplayName','System Avg.')
fig.Position = plotJob.Position;
xticklabels(1:16);
ylabel('Penalty in dB');
xlabel('Channel Number');
ylim([-9.3,-3]);
xlim([0,plotJob.ch+1]);
% grid minor;
set(gca, 'color', 'none');
legend = [];
fontsize(AxesMain,8,"points")
fig.Position = plotJob.Position;
fig.Units = "centimeters";
fig.Position = [2 2 8.5 7];
set(AxesMain,'TickLabelInterpreter','latex')
set(AxesMain.Legend,'Interpreter','latex')
if 0
ber_sorted = sort(S);
z1 = [];
penalty = mean(ber_sorted):0.01:mean(ber_sorted)+2;
for i = 1:length(penalty)
l = penalty(i);
if i == 1
z1 = [z1 sum(ber_sorted(1,:)<l ) / length(ber_sorted) ];
else
z1 = [z1 sum(ber_sorted(1,:)<l & ber_sorted(1,:)>l-0.01) / length(ber_sorted) ];
end
end
penalty_higherthan = 0.5;
probability = sum(z1(find(penalty>mean(ber_sorted)+penalty_higherthan)));
disp(['A penalty of more than 0.5 dB has a probability of: ', num2str(probability)]);
end
end
function vec = removeZeros(vec)
% Find rows that contain only zeros
rows_to_remove = all(vec == 0, 2);
% Remove rows with only zeros
vec(rows_to_remove, :) = [];
end

114
Classes/Warehouse_class/functions/fwm_plots/plot_ber_distribution.m → Classes/Warehouse_class/functions/phase_predist_plots/fwm_plots/plot_ber_distribution.m
View File

@@ -1,58 +1,58 @@
%automate plots
% [file, path] = uigetfile("C:\Users\Silas\Documents\MATLAB\Raw_Cluster_Simulations\session_januar24\wh_complete_at_1310.mat");
% wh = load([path filesep file]);
% wh = wh.wh;
plotJob = struct();
plotJob.l = 10;
plotJob.ch = 16;
plotJob.d = 3;
plotJob.sgm = 1;
plotJob.pol = "copolarized";
plotJob.p_in = 3;
plotJob.gamma = 0.0023;
plotJob.pmd = 0.1;
plotJob.channelspacing = 400e9;
plotJob.randzdw = 0;
ber_per_chann = [];
% get all xAxis values
xAxis = wh.parameter.p_out.values;
realization = wh.parameter.realization.values(1:end);
% Fetch Data from Warehouse
for xl = 1:numel(xAxis)
p_out = xAxis(xl);
raw_fetch = wh.getStoValue('ber',plotJob.l,plotJob.d,plotJob.sgm,string(plotJob.pol),plotJob.p_in,p_out,plotJob.pmd,plotJob.gamma,realization,plotJob.ch,1310,plotJob.channelspacing,plotJob.randzdw).';
ber_per_chann(:,:,xl) = raw_fetch;
end
%%
figure(2023);
for ch = [1,floor(plotJob.ch/2),ceil(plotJob.ch/2)+1,plotJob.ch] %1:15:size(ber_per_chann,1)
for p = 5%1:size(ber_per_chann,3)
% Extract data for the current row
row_data = squeeze(ber_per_chann(ch,:,p));
[f, xi] = ksdensity(row_data);
% Identify the peak point
[max_density, max_index] = max(f);
peak_x = xi(max_index);
end
% Create a histogram plot for the current row with a unique color
plot(xi, f, 'LineWidth', 2, 'DisplayName', ['Ch. ', num2str(ch)],'LineStyle','--');
%histogram(row_data,100, 'DisplayName', ['Channel ', num2str(ch)], 'EdgeColor', 'none');
hold on; % Hold the plot for the next iteration
text(peak_x, max_density, ['Ch ', num2str(ch)], 'VerticalAlignment', 'bottom', 'HorizontalAlignment', 'left');
end
legend show
%automate plots
% [file, path] = uigetfile("C:\Users\Silas\Documents\MATLAB\Raw_Cluster_Simulations\session_januar24\wh_complete_at_1310.mat");
% wh = load([path filesep file]);
% wh = wh.wh;
plotJob = struct();
plotJob.l = 10;
plotJob.ch = 16;
plotJob.d = 3;
plotJob.sgm = 1;
plotJob.pol = "copolarized";
plotJob.p_in = 3;
plotJob.gamma = 0.0023;
plotJob.pmd = 0.1;
plotJob.channelspacing = 400e9;
plotJob.randzdw = 0;
ber_per_chann = [];
% get all xAxis values
xAxis = wh.parameter.p_out.values;
realization = wh.parameter.realization.values(1:end);
% Fetch Data from Warehouse
for xl = 1:numel(xAxis)
p_out = xAxis(xl);
raw_fetch = wh.getStoValue('ber',plotJob.l,plotJob.d,plotJob.sgm,string(plotJob.pol),plotJob.p_in,p_out,plotJob.pmd,plotJob.gamma,realization,plotJob.ch,1310,plotJob.channelspacing,plotJob.randzdw).';
ber_per_chann(:,:,xl) = raw_fetch;
end
%%
figure(2023);
for ch = [1,floor(plotJob.ch/2),ceil(plotJob.ch/2)+1,plotJob.ch] %1:15:size(ber_per_chann,1)
for p = 5%1:size(ber_per_chann,3)
% Extract data for the current row
row_data = squeeze(ber_per_chann(ch,:,p));
[f, xi] = ksdensity(row_data);
% Identify the peak point
[max_density, max_index] = max(f);
peak_x = xi(max_index);
end
% Create a histogram plot for the current row with a unique color
plot(xi, f, 'LineWidth', 2, 'DisplayName', ['Ch. ', num2str(ch)],'LineStyle','--');
%histogram(row_data,100, 'DisplayName', ['Channel ', num2str(ch)], 'EdgeColor', 'none');
hold on; % Hold the plot for the next iteration
text(peak_x, max_density, ['Ch ', num2str(ch)], 'VerticalAlignment', 'bottom', 'HorizontalAlignment', 'left');
end
legend show
%%