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ecoc measurements

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This commit is contained in:
Silas Labor Zizou
2025-04-13 16:29:12 +02:00
parent 00f1c557c0
commit 0236103b13
19 changed files with 709 additions and 359 deletions
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30
Classes/00_signals/Signal.m
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@@ -703,7 +703,8 @@ classdef Signal
end
if options.debug_plots
figure()
figure(121212);clf
subplot(1,2,1);
findpeaks(abs(co./max(co)),'MinPeakDistance',length(b)/2,'MinPeakHeight',0.2,'NPeaks',maxpeaknum,'SortStr','descend')
end
@@ -711,7 +712,7 @@ classdef Signal
shifts = lags(pkpos);
shifts = shifts(shifts>=0);
% shifts = shifts(shifts>=0);
if numel(shifts) > 0
@@ -720,25 +721,21 @@ classdef Signal
isFlipped = 1;
end
for c = shifts(shifts>=0)
for c = shifts
sig = obj.delay(-c,'mode','samples');
sig.signal = sig.signal(1:length(b)).*-isFlipped;
S{end+1,1} = sig;
end
%
%return/keep the sinal with the highest correlation (only within positive shifts)
[~,idx]=max(pks(shifts>=0));
[~,idx]=max(pks);
obj.signal = S{idx}.signal;
%put signal with highest corr. to first index in S array
swap = S{1};
S{1} = S{idx};
S{idx} = swap;
for c = 1:numel(shifts(shifts>0))
for c = 1:numel(shifts)
S{c}.logbook = [];
end
@@ -750,11 +747,14 @@ classdef Signal
%plot all synced signals and the ref signal
if options.debug_plots
figure;hold on;
figure(121212);hold on;
subplot(1,2,2);
for i = 1:size(S,1)
hold on
plot(S{i}.normalize('mode','oneone').signal(1000:1100),'LineWidth',0.1,'Color',[0.2157 0.4941 0.7216]);
plot(b(1000:1100),'LineWidth',1);
end
drawnow;
end
@@ -913,14 +913,12 @@ classdef Signal
elseif mode == 1
% generate eye diagram using histogram
maxA = max(sig(100:end-100));
minA = min(sig(100:end-100));
maxA = max(sig(100:end-100))*2;
minA = min(sig(100:end-100))*2;
% maxA = 0.0015;
% minA = 0;
difference= maxA-minA;
data_ind_y=round((eye_mat-minA)/difference*(histpoints-1)) +1;
@@ -940,11 +938,9 @@ classdef Signal
% beautify
cm=flip(cbrewer2("RdYlBu",4096));
% cm=flip(cbrewer2("RdBu",4096));
cm(1,:) = [1,1,1];
cm(1,:) = [0,0,0];
cm(1,:) = [1,1,1]; % set zeros to white => clean background
colormap(cm);
% colormap('turbo');
ax.Colormap(1,:) = [1,1,1];
% ax.CLim = [0 50];
if isa(obj,'Opticalsignal')
title(['Optical Eye ',options.displayname])

23
Classes/01_transmit/ChannelFreqResp.m
View File

@@ -38,6 +38,9 @@ classdef ChannelFreqResp < handle
Nfft
df
faxis
fileName
path
end
methods (Access=public)
@@ -194,7 +197,9 @@ classdef ChannelFreqResp < handle
obj.H_apply = H_inv;
Target.signal = real((ifft( ( fft(real( Target.signal' )) .* H_inv ) )));
H_inv = reshape(H_inv,size(Target.signal));
Target.signal = real((ifft( ( fft(real( Target.signal )) .* H_inv ) )));
Target.signal = Target.signal';
end
@@ -250,8 +255,18 @@ classdef ChannelFreqResp < handle
% Havg_smooth = smooth(Havg,10);
symaxis = (obj.faxis-(obj.f_ref/2))/1e9;
Havg = fftshift(Havg);
%Havg = smooth(Havg);
plot(symaxis, 20*log10(abs(Havg)),'LineWidth',0.5);
Havg = smooth(Havg);
Havg = Havg./max(Havg);
if ~isempty(obj.fileName)
dpname = obj.fileName;
else
dpname = 'Measured System response';
end
plot(symaxis, 20*log10(abs(Havg)),'LineWidth',0.5,'DisplayName',dpname);
legend('Interpreter','latex')
grid on;
@@ -368,6 +383,8 @@ classdef ChannelFreqResp < handle
end
fprintf('Frequency response information successfully loaded from %s\n', fullFileName);
obj.fileName = options.fileName;
obj.path = options.loadPath;
end
end

50
Classes/01_transmit/PAMsource.m
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@@ -11,6 +11,7 @@ classdef PAMsource
db_precode
db_encode
duobinary_mode
mrds_code
mrds_blocklength
@@ -38,6 +39,7 @@ classdef PAMsource
options.db_precode = 0;
options.db_encode = 0;
options.duobinary_mode = db_mode.no_db;
options.mrds_code = 0;
options.mrds_blocklength = 512;
@@ -103,7 +105,6 @@ classdef PAMsource
para.method = 1;
data_in = [];
global loop;
loop = 0;
@@ -134,43 +135,52 @@ classdef PAMsource
symbols.fs = obj.fsym;
%%%%%% Duobinary %%%%%%%%%%%
if obj.db_precode
symbols = Duobinary().precode(symbols);
switch obj.duobinary_mode
case db_mode.no_db
case db_mode.db_precoded
symbols = Duobinary().precode(symbols);
case db_mode.db_encoded
symbols = Duobinary().precode(symbols);
symbols = Duobinary().encode(symbols);
end
if obj.db_encode
symbols = Duobinary().encode(symbols);
end
% figure(12);hold on;histogram(symbols.signal,'Normalization','probability');
%%%%%% MRDS %%%%%%%%%%%
if obj.mrds_code
symbols = MRDS_coding("blocklength",obj.mrds_blocklength).encode(symbols);
end
%%%%%% SAVE MIN-MAX FOR CLIP %%%%%%%%%%%
if obj.applyclipping
sym_min = min(symbols.signal);
sym_max = max(symbols.signal);
end
%%%%% Pulse-forming %%%%%%
if obj.applypulseform
%%% MY CODE
digi_sig = obj.pulseformer.process(symbols);
if 0
digi_sig = obj.pulseformer.process(symbols);
%%% MOVEIT WRAPPER BETA
% symbols.spectrum("fignum",111,"displayname","1) RAW SIGNAL");
%
% pulsf = Moveit_wrapper('pulsef');
% pulsf.para.alpharacos = obj.pulseformer.alpha;
% pulsf.para.f_sym = obj.fsym;
% pulsf.para.fs = obj.fsym;
% pulsf.para.pulse = 2;
%
% digi_sig = pulsf.process(symbols);
else
%%% MOVEIT WRAPPER BETA
% symbols.spectrum("fignum",111,"displayname","1) RAW SIGNAL");
pulsf = Moveit_wrapper('pulsef');
pulsf.para.alpharacos = obj.pulseformer.alpha;
pulsf.para.f_sym = obj.pulseformer.fsym;
pulsf.para.fs = obj.pulseformer.fdac;
pulsf.para.pulse = 1;
digi_sig = pulsf.process(symbols);
digi_sig.fs = obj.pulseformer.fdac;
end
% Design raised cosine filter with given order in symbols
% digi_sig = symbols;
% sps = 4;

45
Classes/01_transmit/Pulseformer.m
View File

@@ -6,10 +6,8 @@ classdef Pulseformer
end
properties(Access=public)
fs
fdac
fsym
matched_sps
output_sps
pulse
pulselength
alpha
@@ -22,10 +20,8 @@ classdef Pulseformer
% Detailed explanation goes here
arguments
options.fs double
options.fdac double
options.fsym double
options.matched_sps double
options.output_sps double
options.pulse pulseform = pulseform.rc
options.pulselength double {mustBeInteger} = 32
options.alpha double = 0.05
@@ -54,11 +50,7 @@ classdef Pulseformer
signalclass_in = signalclass_in.logbookentry(lbdesc);
% write fs to signal
if obj.matched
signalclass_in.fs = obj.fsym .* obj.output_sps;%.* (obj.fdac./obj.fsym);
else
signalclass_in.fs = obj.fs;%.* (obj.fdac./obj.fsym);
end
signalclass_in.fs = obj.fdac;%.* (obj.fdac./obj.fsym);
% write to output
signalclass_out = signalclass_in;
@@ -85,19 +77,15 @@ classdef Pulseformer
data_out
end
if ~isempty(obj.output_sps)
obj.fsym = obj.fsym.*obj.output_sps;
end
if ~rem(obj.fs,obj.fsym)
if ~rem(obj.fdac,obj.fsym)
%ist ein Vielfaches
sps = obj.fs / obj.fsym;
sps = obj.fdac / obj.fsym;
p = sps;
q = 1;
else
%ist kein Vielfaches
p = obj.fsym / gcd(obj.fs, obj.fsym); %upsampling p->->->
q = obj.fs/ gcd(obj.fs, obj.fsym); %downsampling <-q
p = obj.fsym / gcd(obj.fdac, obj.fsym); %upsampling p->->->
q = obj.fdac/ gcd(obj.fdac, obj.fsym); %downsampling <-q
sps= q; %sps während dem pulse shaping
end
@@ -117,7 +105,6 @@ classdef Pulseformer
end
manual_cyclic_convolution = 0;
upsample_filter = 0;
upfirdn_convolution = 1;
if manual_cyclic_convolution
@@ -135,28 +122,16 @@ classdef Pulseformer
data_out=ifft( fft(symbolov.') .* repmat( H,size(data_in,1),1 ).' ).';
data_out = circshift(data_out,[0 -(obj.pulselength*sps)]);
if rem(obj.fs,obj.fsym)
if rem(obj.fdac,obj.fsym)
data_out = data_out(1:q:end);
end
end
if upsample_filter
data_out_ = upsample(data_in,p);
mfOutput = filter(h, 1, data_out_); % Matched filter output
figure()
hold on
stem(mfOutput(1:1000),'Marker','o','MarkerSize',1,'LineStyle','-','LineWidth',1);
stem(data_out_(1:1000),'Marker','o','MarkerSize',1,'LineStyle','-','LineWidth',1);
end
if upfirdn_convolution
%Apply Filter using Matlab build in fctn.
data_out_ = upfirdn(data_in,h,p,q);
%cut signal, which is longer due to fir filter
@@ -183,7 +158,7 @@ classdef Pulseformer
% scale = max(max([abs(real(data_out)) abs(imag(data_out))])); %find max value from real and imag part
% data_out = data_out./scale;
data_out = data_out';
% data_out = data_out';
%Check output integrity
if abs(round(p/q * length(data_in)) - length(data_out)) > 4

20
Classes/05_Lab/AwgKeysight.m
View File

@@ -69,16 +69,16 @@ classdef AwgKeysight
obj.sampleMemorySize = 512000;
case awg_model.M8199A
obj.numChannels = 4;
obj.waveformGranularity = 512;
obj.sampleMemorySize = 1024000; %to check
obj.waveformGranularity = 256;
obj.sampleMemorySize = 512000; %see documentation "strg+f: granularity"
case awg_model.M8199A_ILV
obj.numChannels = 2;
obj.waveformGranularity = 512;
obj.sampleMemorySize = 1024000; %to check
obj.waveformGranularity = 512; %see documentation "strg+f: granularity"
obj.sampleMemorySize = 1024000;
case awg_model.M8199B
obj.numChannels = 2;
obj.waveformGranularity = 512;
obj.sampleMemorySize = 1024000; %to check
obj.waveformGranularity = 512; %see documentation "strg+f: granularity"
obj.sampleMemorySize = 1024000;
end
end
@@ -175,7 +175,10 @@ classdef AwgKeysight
% The waveform granularity is e.g. 128. This means that the waveform length must be a multiple of this granularity. The minimum waveform length is 128 samples.
if rem(length(signal{s}),obj.waveformGranularity) ~= 0
signal{s} = [signal{s} signal{s}(:,1:(obj.waveformGranularity-rem(length(signal{s}),obj.waveformGranularity)))];
fill_length = (obj.waveformGranularity-rem(length(signal{s}),obj.waveformGranularity));
segment__fill_samples = signal{s}(:,1:fill_length);
signal{s} = [signal{s} segment__fill_samples];
debug = 0;
if debug
@@ -196,7 +199,7 @@ classdef AwgKeysight
siglen = min(length(signal{s}),obj.sampleMemorySize);
signal{s} = signal{s}(1:siglen);
if siglen==obj.sampleMemorySize
warning(['Signal ',num2str(s),' was truncated to ',num2str(obj.sampleMemorySize),' to fit into AWG sample memory'])
warning(['Signal ',num2str(s),' too long was truncated to ',num2str(obj.sampleMemorySize),' to fit into AWG sample memory! Reduce Num Symbols or Sampling Rate!'])
end
@@ -362,6 +365,7 @@ classdef AwgKeysight
writeline(visaobj,char(command));
writeline(visaobj,':syst:err?');
err_aw=readline(visaobj);
assert(strfind(err_aw,"No error"),['AWG System Error? after command: ', char(command)])

27
Classes/05_Lab/OptAtten.m
View File

@@ -53,7 +53,29 @@ classdef OptAtten < handle
try
%connect to device
v = visadev('TCPIP::134.245.243.248::INSTR');
ipAddress = 'TCPIP::134.245.243.248::INSTR';
maxRetries = 5;
pauseTime = 2; % seconds between retries
v = [];
success = false;
for attempt = 1:maxRetries
try
v = visadev(ipAddress);
success = true;
break; % Exit loop if successful
catch ME
fprintf('Connection attempt %d failed: %s\n', attempt, ME.message);
pause(pauseTime);
end
end
if ~success
error(' Could not connect to device after %d attempts.', maxRetries);
end
debug = 0;
if debug
@@ -315,7 +337,8 @@ classdef OptAtten < handle
p3 = obj.power_state(3);
p4 = obj.power_state(4);
if options.silent == 0
delete(v);
if options.silent ~= 0
fprintf("\n CH1: %.2f dB | CH2: %.2f dB | CH3: %.2f dB | CH4: %.2f dB\n \n",p1, p2, p3, p4);
end
end

24
Classes/05_Lab/Thor_PDFA.m
View File

@@ -32,14 +32,30 @@ classdef Thor_PDFA < handle
end
end
obj.getStatus();
end
function o = connectSerial(obj)
% Connect to the PDFA
o = serialport(obj.serialport_number, 9600);
configureTerminator(o, "CR", "CR"); % Set the terminator to carriage return (CR)
flush(o);
try
% Connect to the PDFA
o = serialport(obj.serialport_number, 9600);
configureTerminator(o, "CR", "CR"); % Set the terminator to carriage return (CR)
flush(o);
catch ME
disp(['Error connecting to PDFA: ', ME.message]);
% List available serial ports
availablePorts = serialportlist("available");
if isempty(availablePorts)
disp('No available serial ports found.');
else
disp('Available serial ports:');
disp(availablePorts);
end
end
end

54
Classes/DataBaseHandler/DBHandler.m
View File

@@ -217,12 +217,31 @@ classdef DBHandler < handle
end
% Append the new row to the database table
try
sqlwrite(obj.conn, tableName, newRow);
% disp(['Successfully appended new row to the table ', tableName]);
catch e
error('Failed to append to the table %s: %s', tableName, e.message);
% Parameters for retry logic
maxRetries = 5;
basePause = 0.05; % seconds
attempt = 0;
success = false;
while ~success && attempt <= maxRetries
try
sqlwrite(obj.conn, tableName, newRow);
success = true; % Write successful
catch e
if contains(e.message, 'database is locked') || contains(e.message, 'cannot rollback transaction')
attempt = attempt + 1;
pauseTime = basePause * (1 + rand()); % Add random jitter to reduce collision chance
fprintf('Database locked. Retry %d/%d after %.3f seconds...\n', attempt, maxRetries, pauseTime);
pause(pauseTime);
else
error('Failed to append to the table %s: %s', tableName, e.message);
end
end
end
if ~success
error('Failed to append to table %s after %d retries due to database lock.', tableName, maxRetries);
end
% Retrieve the measurement_id of the newly inserted row for linking other tables
@@ -539,27 +558,38 @@ classdef DBHandler < handle
end
end
% --- Adaptive FROM Clause ---
% Use "Runs" as the main table and add LEFT JOINs for every other table in obj.tables
% (except "sqlite_sequence") that has a run_id field.
mainTable = 'Runs';
fromClause = ['FROM ', mainTable, ' '];
% Prepare join buffers
normalJoins = '';
equalizerJoin = '';
tableNamesAll = fieldnames(obj.tables);
for t = 1:numel(tableNamesAll)
tableName = tableNamesAll{t};
if strcmpi(tableName, mainTable) || strcmpi(tableName, 'sqlite_sequence')
continue;
end
if isfield(obj.tables.(tableName), 'run_id')
% most tables are directly linked to runs table
fromClause = [fromClause, 'LEFT JOIN ', tableName, ' ON ', mainTable, '.run_id = ', tableName, '.run_id '];
% Direct join to Runs
normalJoins = [normalJoins, 'LEFT JOIN ', tableName, ' ON ', mainTable, '.run_id = ', tableName, '.run_id '];
elseif isfield(obj.tables.(tableName), 'eq_id')
% equalizer is only linked to results table
fromClause = [fromClause, 'LEFT JOIN ', tableName, ' ON ', 'Results', '.eqParam_id = ', tableName, '.eq_id '];
% Equalizer depends on Results, collect this join separately
equalizerJoin = ['LEFT JOIN ', tableName, ' ON Results.eqParam_id = ', tableName, '.eq_id '];
end
end
% Combine joins: normal joins first, Equalizer last
fromClause = [fromClause, normalJoins, equalizerJoin];
% --- WHERE Clause Construction ---
baseQuery = [selectClause, ' ', fromClause, 'WHERE '];
filterClauses = [];

11
Classes/Moveit_wrapper.m
View File

@@ -49,29 +49,30 @@ classdef Moveit_wrapper < handle
isSignalClass = 0;
if isa(signal_in,"Signal")
signal_out = signal_in;
signalclass_out = signal_in;
signal_in = signal_in.signal;
isSignalClass = 1;
end
% signal_in = signal_in.';
signal_in = signal_in.';
% INIT MOVEIT
global loop;
loop = 0;
signal_out = obj.moveit_init(signal_in);
signal_init = obj.moveit_init(signal_in);
% RUN MOVEIT
global loop;
loop = 1;
signal_out = obj.moveit_init(signal_out);
signal_out = obj.moveit_simulation_computation(signal_in);
if isSignalClass
% append to logbook
signalclass_out.signal = signal_out;
signal_out=signalclass_out;
lbdesc = ['Logbookentry'];
signal_out = signal_out.logbookentry(lbdesc);
signal_out.signal = signal_out;
end
end

33
Functions/EQ_structures/vnle_postfilter_mlse.m
View File

@@ -19,7 +19,9 @@ end
[eq_signal_sd,eq_noise] = eq_.process(rx_signal,tx_symbols);
if ~isempty(options.postFFE)
tic
[eq_signal_sd,eq_noise] = options.postFFE.process(eq_signal_sd,tx_symbols);
toc
end
eq_signal_hd = PAMmapper(M,0).quantize(eq_signal_sd);
@@ -237,29 +239,32 @@ if options.showAnalysis
% fprintf(['VNLE EVM lvl: ',repmat('%.3f ',1,numel(evm_lvl)),' \n'],evm_lvl);
fprintf('VNLE BER: %.2e \n',ber_vnle);
fprintf('MLSE BER: %.2e \n',ber_mlse);
% fprintf('VNLE BER: %.2e \n',ber_vnle);
%
% fprintf('MLSE BER: %.2e \n',ber_mlse);
figure(336);clf;
showEQNoisePSD(eq_noise,"fignum",336,"displayname",'Residual Noise after VNLE','postfilter_taps',pf_.coefficients);
% figure(337);clf;
% rx_signal.spectrum("normalizeTo0dB",1,"fignum",337,"displayname",'Rx Signal');
rx_signal.spectrum("normalizeTo0dB",1,"fignum",337,"displayname",'Rx Signal');
% figure(338);clf;
% showEQcoefficients('n1',eq_.e,'n2',eq_.e2,'n3',eq_.e3,"displayname",'Coefficients','fignum',338);
tx_symbols.spectrum("normalizeTo0dB",1,"fignum",337,'displayname','Tx Signal');
if ~isempty(options.postFFE)
showEQcoefficients('n1',options.postFFE.e,"displayname",'Coefficients','fignum',338);
end
showLevelHistogram(eq_signal_sd,tx_symbols)
% showLevelHistogram(mlse_sig_sd,tx_symbols)
showEQfilter(eq_.e,eq_signal_sd.fs.*2);
showEQcoefficients('n1',eq_.e,'n2',eq_.e2,'n3',eq_.e3,"displayname",'Coefficients');
figure(340);clf;
eq_signal_sd.eye(eq_signal_sd.fs,M,"fignum",340);
showEQNoiseSNR(tx_symbols,eq_noise,"displayname",'vnle snr','fignum',101);
figure(341);clf;
showLevelHistogram(eq_signal_sd,tx_symbols,"fignum",341);
%%% EQ SNR Spectrum %230
%snr
% showErrorBurstCount(eq_signal_sd,tx_symbols)
% autoArrangeFigures(3,3,2)
end

4
Functions/EQ_visuals/showEQcoefficients.m
View File

@@ -53,8 +53,8 @@ function showEQcoefficients(options)
for i = 1:numSubplots
subplot(1, numSubplots, i);
stem(coeffs{i}, 'Color', options.color, 'LineWidth', 1, ...
'Marker', '.', 'MarkerSize', 10);
stem(coeffs{i}, 'Color', options.color, 'LineWidth', 0.1, ...
'Marker', '.', 'MarkerSize', 1);
title(titles{i});
ylim([-1, 1]); % Set y-axis limits to [-1, 1]
grid on;

2
Functions/EQ_visuals/showEQfilter.m
View File

@@ -14,7 +14,7 @@ function showEQfilter(coefficients,fs)
H = H(1:half_nfft);
% Plot the magnitude and phase responses.
figure;
figure(339);
% Magnitude response (in dB)
subplot(2,1,1);

2
Functions/Lab_helper/holdAndShowValue.m
View File

@@ -15,7 +15,7 @@ function holdAndShowValue()
'ButtonPushedFcn', @(src, event) closeWindow());
% Initialize the timer
updateTimer = timer('ExecutionMode', 'fixedRate', 'Period', 1, ...
updateTimer = timer('ExecutionMode', 'fixedRate', 'Period', 0.1, ...
'TimerFcn', @(src, event) updatePowerValues());
% Start the timer

39
Functions/Lab_helper/loadFreqResp.m
View File

@@ -1,9 +1,34 @@
% Define the precomp path
precomp_path = "C:\Users\sioe\Documents\MATLAB\imdd_simulation\projects\ECOC_2025\";
precomp_path = "D:\kiel_dsp\imdd_simulation\projects\HighSpeed_ETH";
precomp_filename = "lab_high_speed_nachtschichtmzm";
% precomp_filename = "lab_high_speed";
% precomp_filename = "lab_high_speed";
% Step 1: Find all valid files (assume .mat files for ChannelFreqResp)
fileList = dir(fullfile(precomp_path, '*.mat'));
fileNames = {fileList.name};
freqresp = ChannelFreqResp("Nacq",1024,"Navg",64,"Ncp",63,'f_ref',92e9);
freqresp.load('loadPath',precomp_path,'fileName',precomp_filename);
freqresp.plot();
% Check if any files found
if isempty(fileNames)
error('No valid .mat files found in the specified folder.');
end
% Step 2: Let user select which files to plot
[selection, ok] = listdlg( ...
'PromptString', 'Select Transfer Functions to Plot:', ...
'SelectionMode', 'multiple', ...
'ListString', fileNames);
% Check if user pressed OK
if ~ok || isempty(selection)
disp('No files selected. Exiting.');
return;
end
% Step 3: Loop over selected files and plot
for idx = selection
precomp_filename = erase(fileNames{idx}, '.mat'); % Remove .mat extension
freqresp = ChannelFreqResp("Nacq",1024,"Navg",64,"Ncp",63,'f_ref',92e9);
freqresp.load('loadPath', precomp_path, 'fileName', precomp_filename);
fprintf('Plotting: %s\n', precomp_filename);
freqresp.plot();
end

6
projects/ECOC_2025/dsp_standalone.m
View File

@@ -1,9 +1,9 @@
basePath = 'C:\Users\sioe\Documents\MATLAB\imdd_simulation\projects\ECOC_2025\';
database_name='ecoc2025.db';
savePath = 'Z:\2025\ECOC Silas\ecoc_2025\';
databasePath = 'Z:\2025\ECOC Silas\';
database_name = 'ecoc2025_loops.db';
db = DBHandler("pathToDB", [databasePath, database_name]);
num_occ = 1;
run_par = false;
run_id = 562;

44
projects/ECOC_2025/estimate_linewidth.m Normal file
View File

@@ -0,0 +1,44 @@
% Parameters
reclen = 133169152;
Scp_long = ScopeKeysight("model","DSAZ634A",'autoscale',0,"fadc","GSa_160","channel",[0,0,1,0],"recordLen",reclen,"removeDC",1,"extRef",1);
Scpe_sig_raw = Scp_long.read("channel",[0,0,1,0]);
Scpe_sig_raw = Scpe_sig_raw{3};
signal = Scpe_sig_raw.signal;
Fs = Scpe_sig_raw.fs; % Sampling rate [Hz]
N = length(signal); % Number of samples
f_center = 20e9; % Frequency of interest (~20 GHz)
% Create time vector
t = (0:N-1)' / Fs;
% Mix down to baseband
signal_mix = signal .* exp(-1j * 2 * pi * f_center * t);
% Low-pass filter (optional but recommended)
% Design a filter with bandwidth ~ linewidth * safety margin
BW = 1000e6; % 100 MHz bandwidth for example
% Decimate (reduce sampling rate)
decimation_factor = 10;%floor(Fs / (2 * BW));
signal_decim = downsample(signal_mix, decimation_factor);
Fs_decim = Fs / decimation_factor;
% FFT of downmixed signal
Nfft = 2^nextpow2(length(signal_decim) * 4); % Zero-pad
spectrum = fft(signal_decim .* blackmanharris(length(signal_decim)), Nfft);
freq = (0:Nfft-1) * (Fs_decim / Nfft);
% Only positive frequencies
halfIdx = 1:floor(Nfft/2);
spectrum_half = abs(spectrum(halfIdx));
freq_half = freq(halfIdx);
% Plot
figure;
plot(freq_half / 1e6, 20*log10(spectrum_half));
xlabel('Frequency (MHz)');
ylabel('Magnitude (dB)');
title('Zoomed Spectrum around 20 GHz');
grid on;

212
projects/ECOC_2025/measure_run_script.m
View File

@@ -2,16 +2,11 @@
savePath = 'Z:\2025\ECOC Silas\ecoc_2025\';
current_folder = 'precomp_optimization_friday';
fullFolderPath = fullfile(savePath, current_folder);
if ~exist(fullFolderPath, 'dir')
mkdir(fullFolderPath);
end
basePath = 'C:\Users\sioe\Documents\MATLAB\imdd_simulation\projects\ECOC_2025\';
database_name='ecoc2025.db';
db = DBHandler("pathToDB",[basePath,database_name]);
precomp_path = "C:\Users\sioe\Documents\MATLAB\imdd_simulation\projects\ECOC_2025\";
precomp_fn = "precomp_1km_1mm_cable_70ghz_pd_shf_t850_2p8_bias_shot2";
precomp_mode = 2; %0=do nothing ; 1= measure; 2=precomp active
@@ -24,9 +19,6 @@ referenceFields = fieldnames(db.tables.Configurations);
assert(isequal(fieldnames(conf), referenceFields), 'Fieldnames do not match the reference structure!');
currentTime = datetime('now', 'Format', 'yyyyMMdd_HHmmss');
timeStr = char(currentTime);
filename = sprintf('%s_PAM_%d_R_%d',timeStr,conf.pam_level,conf.symbolrate.*1e-9);
%% Lab Automation
@@ -38,7 +30,6 @@ if run_lab_automation
dcs.set("voltage",[conf.v_bias, 5]);
[v_bias_meas,i_bias_meas]=dcs.readVals();
end
% Laser
if confPrev.laser_power ~= conf.laser_power
laser = Exfo_laser("mainframe_channel",1,"safety_mode",0,"connection_id",'10','lab_interface','gpib');
@@ -55,7 +46,7 @@ if run_lab_automation
pdfa = Thor_PDFA("safety_mode",0,"serialport_number",'COM15');
% Construct AWG and Scope Modules %%%%%%
fdac = 256e9;
fdac = 224e9;
fadc = 160e9;
Scp = ScopeKeysight("model","DSAZ634A",'autoscale',1,"fadc","GSa_160","channel",[0,0,1,0],"recordLen",5000000,"removeDC",1,"extRef",1);
Awg = AwgKeysight("model","M8199A_ILV","fdac",fdac,"scaletodac",[1,1],"skews",[0,0],"voltages",[0,conf.v_awg]);
@@ -65,108 +56,151 @@ end
%% Signal generation and transmission
if 0% awg_upload_required || isempty(loop_id)
%%%%% Symbol Generation %%%%%%
Pform = Pulseformer("fsym",conf.symbolrate,"fdac",8*conf.symbolrate,"pulse","rc","pulselength",16,"alpha",conf.pulsef_alpha);
%%%%% Symbol Generation %%%%%%
Pform = Pulseformer("fsym",conf.symbolrate,"fdac",8*conf.symbolrate,"pulse","rc","pulselength",16,"alpha",conf.pulsef_alpha);
Pamsource = PAMsource(...
"fsym",conf.symbolrate,"M",conf.pam_level,"order",19,"useprbs",1,...
"fs_out",fdac,...
"applyclipping",0,...
"clipfactor",4,...
"applypulseform",1,...
"pulseformer",Pform,...
"randkey",1,...
"duobinary_mode", conf.db_mode);
Pamsource = PAMsource(...
"fsym",conf.symbolrate,"M",conf.pam_level,"order",19,"useprbs",1,...
"fs_out",fdac,...
"applyclipping",0,...
"clipfactor",4,...
"applypulseform",1,...
"pulseformer",Pform,...
"randkey",1,...
"duobinary_mode", conf.db_mode);
conf.pam_source = Pamsource;
confPrev = conf;
conf.pam_source = Pamsource;
upload_required = ~isequal(Pamsource, confPrev.pam_source);
confPrev = conf;
[Digi_sig,Symbols,Bits] = Pamsource.process();
[Digi_sig,Symbols,Bits] = Pamsource.process();
%%%%% Precompensation Routine %%%%%%
if precomp_mode == 1 % measure channel
precomp_est = ChannelFreqResp("Nacq",2048,"Navg",100,"Ncp",63,'f_ref',fdac);
Digi_sig = precomp_est.buildOFDM();
upload_required = 1;
elseif precomp_mode == 2 % apply precomp
precomp_est = ChannelFreqResp("Nacq",2048,"Navg",100,"Ncp",63,'f_ref',Digi_sig.fs);
Digi_sig = precomp_est.precomp(Digi_sig,'maxampdb',conf.precomp_amp,'loadPath',precomp_path,'fileName',precomp_fn);
end
%%%%% Precompensation Routine %%%%%%
if precomp_mode == 1 % measure channel
precomp_est = ChannelFreqResp("Nacq",2048,"Navg",100,"Ncp",63,'f_ref',fdac);
Digi_sig = precomp_est.buildOFDM();
elseif precomp_mode == 2 % apply precomp
precomp_est = ChannelFreqResp("Nacq",2048,"Navg",100,"Ncp",63,'f_ref',Digi_sig.fs);
Digi_sig = precomp_est.precomp(Digi_sig,'maxampdb',conf.precomp_amp,'loadPath',precomp_path,'fileName',precomp_fn);
end
Digi_sig.spectrum("displayname",'Tx Spectrum','fignum',10,'normalizeTo0dB',0);
% Digi_sig.spectrum("displayname",'Tx Spectrum','fignum',10,'normalizeTo0dB',0);
%%%%% Resample to DAC rate %%%%%%
Digi_sig = Digi_sig.resample("fs_out",Awg.fdac);
%%%%% Resample to DAC rate %%%%%%
Digi_sig = Digi_sig.resample("fs_out",Awg.fdac);
% [~,~,Scpe_sig_raw,~] = A2S.process("signal2",Digi_sig);
% [~,~,Scpe_sig_raw,~] = A2S.process("signal2",Digi_sig);
if upload_required || confPrev.v_awg ~= conf.v_awg
Awg.upload("signal2",Digi_sig);
end
Scpe_sig_raw = Scp.read("channel",[0,0,1,0]);
Scpe_sig_raw = Scpe_sig_raw{[0,0,1,0]==1};
%%%%% Precompensation Routine %%%%%%
% Precompensation Routine (optional)
if precomp_mode == 1
% Scpe_sig_resampled = Scpe_sig_raw.resample("fs_in",fadc,"fs_out",2*fsym);
precomp_est.estimate(Scpe_sig_raw,"save",true,"savePath",precomp_path,"fileName",precomp_fn);
Scpe_sig_raw = Scp.read("channel",[0,0,1,0]);
Scpe_sig_raw = Scpe_sig_raw{[0,0,1,0]==1};
precomp_est.estimate(Scpe_sig_raw, "save", true, "savePath", precomp_path, "fileName", precomp_fn);
precomp_est.plot();
return;
return; % End routine if precomp mode is active
end
Scpe_sig_raw.spectrum("displayname",'Rx Spectrum','fignum',10,'normalizeTo0dB',0);
Scpe_sig_raw.plot("clear",1,"displayname",'Rx Signal','fignum',11);
%% Save static TX data (only once)
currentTime = datetime('now', 'Format', 'yyyyMMdd_HHmmss');
timeStr = char(currentTime);
base_filename = sprintf('%s_PAM_%d_R_%d', timeStr, conf.pam_level, round(conf.symbolrate.*1e-9));
%% %%%%% Save Routine %%%%%%%%%%%%%%%%%%%%%%%%%
tx_bits_path = [filesep, current_folder, filesep, base_filename, '_bits'];
save([savePath, tx_bits_path], "Bits");
tx_bits_path=[filesep,current_folder,filesep,filename,'_bits'];
save([savePath,tx_bits_path],"Bits");
tx_symbols_path=[filesep,current_folder,filesep,filename,'_symbols'];
save([savePath,tx_symbols_path],"Symbols");
tx_signal_path=[filesep,current_folder,filesep,filename,'_signal'];
save([savePath,tx_signal_path],"Digi_sig");
rx_raw_path = [filesep,current_folder,filesep,filename,'_rx_signal_raw'];
save([savePath,rx_raw_path],"Scpe_sig_raw");
tx_symbols_path = [filesep, current_folder, filesep, base_filename, '_symbols'];
save([savePath, tx_symbols_path], "Symbols");
tx_signal_path = [filesep, current_folder, filesep, base_filename, '_signal'];
save([savePath, tx_signal_path], "Digi_sig");
n_recording = 2; % Or any number you want
for recIdx = 1:n_recording
fprintf('Recording %d / %d\n', recIdx, n_recording);
%% Acquire Scope Signal
Scpe_sig_raw = Scp.read("channel",[0,0,1,0]);
Scpe_sig_raw = Scpe_sig_raw{[0,0,1,0]==1};
% Precompensation Routine (optional)
if precomp_mode == 1
precomp_est.estimate(Scpe_sig_raw, "save", true, "savePath", precomp_path, "fileName", precomp_fn);
precomp_est.plot();
return; % End routine if precomp mode is active
end
% Plot spectrum and time domain (optional)
% Scpe_sig_raw.spectrum("displayname", 'Rx Spectrum', 'fignum', 10, 'normalizeTo0dB', 0);
Scpe_sig_raw.plot("clear", 1, "displayname", 'Rx Signal', 'fignum', 11);
%% Save Routine
currentTime = datetime('now', 'Format', 'yyyyMMdd_HHmmss');
timeStr = char(currentTime);
filename = sprintf('%s_PAM_%d_R_%d_rec%02d', timeStr, conf.pam_level, round(conf.symbolrate.*1e-9), recIdx); % Added recIdx
rx_raw_path = [filesep, current_folder, filesep, filename, '_rx_signal_raw'];
save([savePath, rx_raw_path], "Scpe_sig_raw");
% Table 1: Append to Runs
newRun = db.tables.Runs;
newRun.run_id = NaN;
newRun.date_of_run = datetime(currentTime, 'InputFormat', 'yyyyMMdd_HHmmss');
newRun.tx_bits_path = tx_bits_path;
newRun.tx_symbols_path = tx_symbols_path;
newRun.rx_sync_path = [];
newRun.rx_raw_path = rx_raw_path;
newRun.filename = filename;
newRun.tx_signal_path = tx_signal_path;
run_id = db.appendToTable('Runs', newRun);
% Check if loop_id is already created
if isempty(loop_id)
newLoop = db.tables.LoopControl;
newLoop.loop_id = NaN;
newLoop.date_of_loop = datetime('now', 'Format', 'yyyy-MM-dd HH:mm:ss');
newLoop.description = 'Automated parameter sweep';
loop_id = db.appendToTable('LoopControl', newLoop);
% Table 2: Append to Configurations
conf.configuration_id = NaN;
conf.run_id = run_id;
db.appendToTable('Configurations', conf);
fprintf('LoopControl entry created: loop_id = %d\n', loop_id);
end
% Table 3: Append to Measurements
meas = db.tables.Measurements;
meas.measurement_id = NaN; % Auto-increment, leave empty
meas.run_id = run_id;
meas.power_laser = laser.cur_power;
meas.power_rop = [];
meas.power_pd_in = voa.power_state(2);
meas.power_mpi_interference = voa.power_state(4);
meas.power_mpi_signal = voa.power_state(3);
meas.voa_class = voa;
meas.pdfa_class = pdfa;
meas.laser_class = laser;
assert(isequal(fieldnames(meas), fieldnames(db.tables.Measurements)), 'Fieldnames of "meas" do not match the reference structure!');
db.appendToTable('Measurements', meas);
%% Append to Runs Table
newRun = db.tables.Runs;
newRun.run_id = NaN;
newRun.loop_id = loop_id;
newRun.date_of_run = datetime(currentTime, 'InputFormat', 'yyyyMMdd_HHmmss');
newRun.tx_bits_path = tx_bits_path;
newRun.tx_symbols_path = tx_symbols_path;
newRun.rx_sync_path = []; % Leave empty for now
newRun.rx_raw_path = rx_raw_path;
newRun.filename = filename;
newRun.tx_signal_path = tx_signal_path;
%% %%%%% DSP Routine %%%%%%%%%%%%%%%%%%%%%%%%%
run_id = db.appendToTable('Runs', newRun);
[out, ~] = submit_dsp(run_id, basePath, database_name, savePath,"parallel",parallel_dsp,'max_occurences',max_occurences);
%% Append to Configurations Table
conf.configuration_id = NaN;
conf.run_id = run_id;
db.appendToTable('Configurations', conf);
%% Append to Measurements Table
meas = db.tables.Measurements;
meas.measurement_id = NaN;
meas.run_id = run_id;
meas.power_laser = laser.cur_power;
meas.power_rop = [];
meas.power_pd_in = voa.power_state(2);
meas.power_mpi_interference = voa.power_state(4);
meas.power_mpi_signal = voa.power_state(3);
meas.voa_class = voa;
meas.pdfa_class = pdfa;
meas.laser_class = laser;
% Ensure consistency
assert(isequal(fieldnames(meas), fieldnames(db.tables.Measurements)), 'Fieldnames of "meas" do not match the reference structure!');
db.appendToTable('Measurements', meas);
%% Submit DSP Routine
% [out, ~] = submit_dsp(run_id, basePath, database_name, savePath, ...
% "parallel", parallel_dsp, "max_occurences", max_occurences);
end

295
projects/ECOC_2025/plots_from_database/plot_mpi_trial.m
View File

@@ -1,7 +1,7 @@
basePath = 'C:\Users\sioe\Documents\MATLAB\imdd_simulation\projects\ECOC_2025\';
database_name = 'ecoc2025.db';
database_name = 'ecoc2025_loops.db';
database = DBHandler("pathToDB", [basePath, database_name]);
filterParams = database.tables;
@@ -10,14 +10,14 @@ filterParams.Configurations = struct( ...
'fiber_length', 0, ...
'db_mode', '"no_db"', ...
'interference_attenuation', [], ...
'interference_path_length', 0.06, ...
'interference_path_length', 50, ...
'is_mpi', 1, ...
'pam_level', 4, ...
'wavelength', 1310, ...
'precomp_amp', [], ...
'signal_attenuation', [], ...
'v_awg', 0.9, ...
'v_bias', 2.8 ...
'v_awg', 0.95, ...
'v_bias', 2.5 ...
);
% filterParams.EqualizerParameters.diff_precode = int32(db_mode.db_encoded);
@@ -29,12 +29,12 @@ selectedFields = {'Configurations.run_id' 'Runs.date_of_run' 'Runs.rx_raw_path'
'Measurements.power_mpi_interference' 'Measurements.power_mpi_signal' 'Results.BER' 'Results.BER_precoded' 'Results.SNR' 'Results.GMI' 'Results.Alpha' 'Results.date_of_processing'};
[dataTable,sql_query] = database.queryDB(filterParams, selectedFields);
dataTable.SIR = dataTable.power_mpi_signal - dataTable.power_mpi_interference;
dataTable.SIR = round(-6 - dataTable.power_mpi_interference);
dataTable = cleanUpTable(dataTable);
% Filter by time
startTime = datetime('2025-04-11 14:40:00', 'InputFormat', 'yyyy-MM-dd HH:mm:ss');
stopTime = datetime('2025-04-11 15:30:00', 'InputFormat', 'yyyy-MM-dd HH:mm:ss');
startTime = datetime('2025-04-12 18:00:00', 'InputFormat', 'yyyy-MM-dd HH:mm:ss');
stopTime = datetime('2025-04-13 19:30:00', 'InputFormat', 'yyyy-MM-dd HH:mm:ss');
dataTable.date_of_run = datetime(dataTable.date_of_run, 'InputFormat', 'yyyy-MM-dd HH:mm:ss.SSSSSS');
dataTable.date_of_processing = datetime(dataTable.date_of_processing, 'InputFormat', 'yyyy-MM-dd HH:mm:ss.SSSSSS');
dataTable = dataTable(dataTable.date_of_processing > startTime, :);
@@ -46,21 +46,23 @@ x_var = 'SIR';
loop_var = 'eq_id';
fixedVars = {'eq_id',x_var};
% dataTableGrpd_mean = groupIt(fixedVars,dataTable);
[dataTable, outliersTable] = removeGroupOutliers(dataTable, fixedVars, y_var);
dataTableGrpd_mean = groupIt(fixedVars, dataTable, @mean);
dataTableGrpd_min = groupIt(fixedVars, dataTable, @min);
dataTableGrpd_max = groupIt(fixedVars, dataTable, @max);
plotRealizations = 1;
% Create a new figure
mkr = '*';
mkr = '.';
figure();
hold on
unique_loop_var = unique(dataTable.(loop_var));
cols = linspecer(numel(unique_loop_var)); % Ensure color count matches
for i = 1:numel(unique_loop_var)
for i = 1:2%1:numel(unique_loop_var)
% Prepare filtered data for this loop variable
loopValue = unique_loop_var(i);
@@ -139,7 +141,7 @@ ylabel(y_var);
title([x_var, ' vs. ', y_var]);
if y_var == 'BER'
yline(3.8e-3, 'LineWidth', 1, 'LineStyle', '--', 'HandleVisibility', 'off');
yline(4e-4, 'LineWidth', 1, 'LineStyle', '--', 'HandleVisibility', 'off');
ylim([1e-5, 0.1]);
end
@@ -163,57 +165,58 @@ function resultTable = groupIt(fixedVars, dataTable, aggregationFunction)
% Output:
% resultTable - Grouped and aggregated table
% Group data
[G, groupKeys] = findgroups(dataTable(:, fixedVars));
% Group data
[G, groupKeys] = findgroups(dataTable(:, fixedVars));
% Prepare aggregation
varNames = dataTable.Properties.VariableNames;
nVars = numel(varNames);
aggData = cell(height(groupKeys), nVars);
groupCount = zeros(height(groupKeys), 1); % Store number of rows in each group
% Prepare aggregation
varNames = dataTable.Properties.VariableNames;
nVars = numel(varNames);
aggData = cell(height(groupKeys), nVars);
groupCount = zeros(height(groupKeys), 1); % Store number of rows in each group
% Loop over groups
for i = 1:height(groupKeys)
idx = (G == i); % Logical index for group i
groupCount(i) = sum(idx); % Count rows in group
% Loop over groups
for i = 1:height(groupKeys)
idx = (G == i); % Logical index for group i
groupCount(i) = sum(idx); % Count rows in group
% Loop over each variable
for j = 1:nVars
colData = dataTable.(varNames{j});
% Loop over each variable
for j = 1:nVars
colData = dataTable.(varNames{j});
if isnumeric(colData)
% Numeric: apply aggregation function (skip empty groups safely)
if any(idx)
aggData{i, j} = aggregationFunction(colData(idx));
if isnumeric(colData)
% Numeric: apply aggregation function (skip empty groups safely)
if any(idx)
% aggData{i, j} = rmoutliers(double(colData(idx)));
aggData{i, j} = aggregationFunction(colData(idx));
else
aggData{i, j} = NaN;
end
else
% Non-numeric: take first non-empty value
if iscell(colData)
nonEmptyIdx = find(idx & ~cellfun(@isempty, colData), 1);
if ~isempty(nonEmptyIdx)
aggData{i, j} = colData{nonEmptyIdx};
else
aggData{i, j} = NaN;
aggData{i, j} = [];
end
else
% Non-numeric: take first non-empty value
if iscell(colData)
nonEmptyIdx = find(idx & ~cellfun(@isempty, colData), 1);
if ~isempty(nonEmptyIdx)
aggData{i, j} = colData{nonEmptyIdx};
else
aggData{i, j} = [];
end
nonEmptyIdx = find(idx, 1);
if ~isempty(nonEmptyIdx)
aggData{i, j} = colData(nonEmptyIdx);
else
nonEmptyIdx = find(idx, 1);
if ~isempty(nonEmptyIdx)
aggData{i, j} = colData(nonEmptyIdx);
else
aggData{i, j} = [];
end
aggData{i, j} = [];
end
end
end
end
end
% Convert aggregated data to table
resultTable = cell2table(aggData, 'VariableNames', varNames);
% Convert aggregated data to table
resultTable = cell2table(aggData, 'VariableNames', varNames);
% Add group size as new column
resultTable.nRows = groupCount;
% Add group size as new column
resultTable.nRows = groupCount;
end
@@ -233,27 +236,27 @@ function addDatatips(sc, varargin)
% pair_one = {'Attenuation', attenuationVector};
% addDatatips(sc, pair_one);
numPoints = numel(sc.XData);
numPoints = numel(sc.XData);
for k = 1:length(varargin)
pair = varargin{k};
for k = 1:length(varargin)
pair = varargin{k};
if ~iscell(pair) || numel(pair) ~= 2
error('Each pair must be a 1x2 cell array: {label, value}.');
end
label = pair{1};
value = pair{2};
% If value is a vector, ensure its length is either 1 or equal to the number of scatter points.
if isvector(value) && numel(value) ~= 1 && numel(value) ~= numPoints
error('The vector for "%s" must be a scalar or have %d elements matching the scatter data points.', label, numPoints);
end
% Create a new data tip row using the provided label and vector.
newRow = dataTipTextRow(label, value);
sc.DataTipTemplate.DataTipRows(end+1) = newRow;
if ~iscell(pair) || numel(pair) ~= 2
error('Each pair must be a 1x2 cell array: {label, value}.');
end
label = pair{1};
value = pair{2};
% If value is a vector, ensure its length is either 1 or equal to the number of scatter points.
if isvector(value) && numel(value) ~= 1 && numel(value) ~= numPoints
error('The vector for "%s" must be a scalar or have %d elements matching the scatter data points.', label, numPoints);
end
% Create a new data tip row using the provided label and vector.
newRow = dataTipTextRow(label, value);
sc.DataTipTemplate.DataTipRows(end+1) = newRow;
end
end
@@ -274,69 +277,135 @@ function cleanedTable = cleanUpTable(inputTable)
% Output:
% cleanedTable - Cleaned MATLAB table with proper numeric types
cleanedTable = inputTable;
varNames = cleanedTable.Properties.VariableNames;
cleanedTable = inputTable;
varNames = cleanedTable.Properties.VariableNames;
for i = 1:numel(varNames)
col = cleanedTable.(varNames{i});
for i = 1:numel(varNames)
col = cleanedTable.(varNames{i});
% Case 1: If it's a cell array (likely mixed strings/struct)
if iscell(col)
% Convert struct 'NaN' entries to string 'NaN'
col = cellfun(@(x) convertStructToString(x), col, 'UniformOutput', false);
% Case 1: If it's a cell array (likely mixed strings/struct)
if iscell(col)
% Convert struct 'NaN' entries to string 'NaN'
col = cellfun(@(x) convertStructToString(x), col, 'UniformOutput', false);
% Try to convert string numbers to actual numbers
numericCol = str2double(col);
% Try to convert string numbers to actual numbers
numericCol = str2double(col);
if all(isnan(numericCol) == strcmpi(col, 'NaN') | cellfun(@isempty, col))
% If conversion is successful (NaNs correspond to 'NaN' strings), use it
cleanedTable.(varNames{i}) = numericCol;
else
% Else, try to convert to datetime
try
cleanedTable.(varNames{i}) = datetime(col, 'InputFormat', 'yyyy-MM-dd HH:mm:ss.SSSSSS');
catch
% If it fails, leave as cell array of strings
cleanedTable.(varNames{i}) = string(col);
end
if all(isnan(numericCol) == strcmpi(col, 'NaN') | cellfun(@isempty, col))
% If conversion is successful (NaNs correspond to 'NaN' strings), use it
cleanedTable.(varNames{i}) = numericCol;
else
% Else, try to convert to datetime
try
cleanedTable.(varNames{i}) = datetime(col, 'InputFormat', 'yyyy-MM-dd HH:mm:ss.SSSSSS');
catch
% If it fails, leave as cell array of strings
cleanedTable.(varNames{i}) = string(col);
end
end
% Case 2: If it's already a string array
elseif isstring(col)
numericCol = str2double(col);
if all(isnan(numericCol) == strcmpi(col, "NaN"))
cleanedTable.(varNames{i}) = numericCol;
else
% Try convert to datetime
try
cleanedTable.(varNames{i}) = datetime(col, 'InputFormat', 'yyyy-MM-dd HH:mm:ss.SSSSSS');
catch
% Leave as string
end
elseif isstring(col)
numericCol = str2double(col);
if all(isnan(numericCol) == strcmpi(col, "NaN"))
cleanedTable.(varNames{i}) = numericCol;
else
% Try convert to datetime
try
cleanedTable.(varNames{i}) = datetime(col, 'InputFormat', 'yyyy-MM-dd HH:mm:ss.SSSSSS');
catch
% Leave as string
end
end
% Case 3: If it's already numeric, keep as is
elseif isnumeric(col)
continue;
elseif isnumeric(col)
continue;
% Case 4: If it's datetime, keep as is
elseif isdatetime(col)
continue;
elseif isdatetime(col)
continue;
else
% Catch-all for unexpected types, convert to string
cleanedTable.(varNames{i}) = string(col);
end
else
% Catch-all for unexpected types, convert to string
cleanedTable.(varNames{i}) = string(col);
end
end
end
function out = convertStructToString(x)
% Helper function to convert struct NaN to string 'NaN'
if isstruct(x)
out = "NaN";
elseif isstring(x) || ischar(x)
out = string(x);
else
out = x;
end
if isstruct(x)
out = "NaN";
elseif isstring(x) || ischar(x)
out = string(x);
else
out = x;
end
end
function [cleanedTable, outliersTable] = removeGroupOutliers(dataTable, fixedVars, y_var)
% Group the data
[G, groupKeys] = findgroups(dataTable(:, fixedVars));
% Initialize logical index to keep rows
keepIdx = true(height(dataTable), 1);
% Prepare storage for outliers
outlierRecords = [];
% Loop over each group
for groupIdx = 1:height(groupKeys)
% Find indices of current group
groupRows = (G == groupIdx);
% Extract y-values of this group
y_values = dataTable.(y_var)(groupRows);
% Skip groups with fewer than 3 points (optional)
if sum(groupRows) < 3
continue;
end
% Detect outliers
outlierMask = isoutlier(y_values, 'quartiles');
% If any outliers found, collect their data
if any(outlierMask)
groupData = dataTable(groupRows, :);
% Prepare table for current group outliers
outlierGroupTable = groupData(outlierMask, :);
% Add group key values for traceability
for k = 1:numel(fixedVars)
outlierGroupTable.(['Group_', fixedVars{k}]) = repmat(groupKeys{groupIdx, k}, height(outlierGroupTable), 1);
end
% Append to collection
outlierRecords = [outlierRecords; outlierGroupTable]; %#ok<AGROW>
end
% Mark outliers for removal
groupRowIdx = find(groupRows);
keepIdx(groupRowIdx(outlierMask)) = false;
end
% Apply mask to dataTable
cleanedTable = dataTable(keepIdx, :);
% Prepare output: if no outliers, return empty table
if isempty(outlierRecords)
outliersTable = table();
else
outliersTable = outlierRecords;
end
nRemoved = sum(~keepIdx);
nTotalOriginal = height(dataTable) + nRemoved;
percentageRemoved = (nRemoved / nTotalOriginal) * 100;
fprintf('Removed %d outliers from the data table (%.2f%% of total %d entries).\n', ...
nRemoved, percentageRemoved, nTotalOriginal);
end

101
projects/run_loop.m Normal file
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% loop_records.m
% === Prepare base configuration ===
% databasePath = 'C:\Users\sioe\Documents\MATLAB\imdd_simulation\projects\ECOC_2025\';
databasePath = 'Z:\2025\ECOC Silas\';
database_name = 'ecoc2025_loops.db';
db = DBHandler("pathToDB", [databasePath, database_name]);
conf = db.tables.Configurations;
confPrev = db.tables.Configurations;
awg_upload_required = 0;
% Define vector parameters directly in conf:
conf.unique_elab_id = "20250408-842b0a3078172b48dd032795226fbe683190afc4";
conf.symbolrate = 112e9;
conf.bitrate = conf.symbolrate .* floor(log2(6)*10)/10;
conf.pam_level = 4;
conf.db_mode = db_mode.no_db;
conf.pulsef_alpha = 0.2;
conf.v_bias = 2.5;
conf.v_awg = 0.95;
conf.precomp_amp = -64; %-64
conf.wavelength = 1310;
conf.laser_power = 11;
conf.fiber_length = 0;
conf.pd_in_desired = 9;
conf.is_mpi = 1;
conf.signal_attenuation = 0;
conf.interference_path_length = 1000; %m
conf.interference_attenuation = [40,20:-1:0];
conf.pam_source = [];
if conf.is_mpi
current_folder = ['mpi_',num2str(conf.interference_path_length),'m_pam',num2str(conf.pam_level)];
else
current_folder = 'testing';
end
% Init empty loop id
loop_id = [];
% === Detect vector fields automatically ===
paramNames = fieldnames(conf);
vectorParams = struct();
scalarConf = conf;
parallel_dsp = false;
max_occurences = 1;
for i = 1:numel(paramNames)
thisName = paramNames{i};
thisValue = conf.(thisName);
if isnumeric(thisValue) && numel(thisValue) > 1
vectorParams.(thisName) = thisValue;
parallel_dsp = true;
max_occurences = 10;
else
scalarConf.(thisName) = thisValue;
end
end
vectorFieldNames = fieldnames(vectorParams);
if isempty(vectorFieldNames)
% No vector parameters, single run
fprintf('Running single measurement (no parameter sweep)\n');
confRequest = scalarConf;
confRequest.bitrate = confRequest.symbolrate * floor(log2(confRequest.pam_level) * 10) / 10;
measure_run_script
else
% Vector parameters found, run parameter sweep
vectorValues = struct2cell(vectorParams);
nParams = numel(vectorValues);
grid = cell(1, nParams);
[grid{:}] = ndgrid(vectorValues{:});
totalRuns = numel(grid{1});
fprintf('Total runs: %d\n', totalRuns);
for runIdx = 1:totalRuns
confRequest = scalarConf;
paramDisplayCell = cell(1, nParams);
for vIdx = 1:nParams
fieldName = vectorFieldNames{vIdx};
paramValue = grid{vIdx}(runIdx);
confRequest.(fieldName) = paramValue;
if isnumeric(paramValue)
paramDisplayCell{vIdx} = sprintf('%s = %.4g', fieldName, paramValue);
else
paramDisplayCell{vIdx} = sprintf('%s = %s', fieldName, char(paramValue));
end
end
fprintf('Running measurement: %s\n', strjoin(paramDisplayCell, ', '));
confRequest.bitrate = confRequest.symbolrate * floor(log2(confRequest.pam_level) * 10) / 10;
% measure_run("config",confRun,"parallel",parallel_dsp,"max_occurences",max_occurences);
measure_run_script;
end
end
disp('- LOOP FINISHED - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - ')
fprintf('\n')