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Merge branch 'main' of https://cau-git.rz.uni-kiel.de/nt/mitarbeiter/silas/imdd_simulation

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This commit is contained in:
Silas Labor Zizou
2025-04-08 13:29:35 +02:00
parent f93d61f5d8 e86930335e
commit 1e35c24a8c
66 changed files with 4709 additions and 784 deletions
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65
Classes/00_signals/Signal.m
View File

@@ -359,10 +359,10 @@ classdef Signal
end
if options.normalizeToNyquist == 0
[p_lin,w] = pwelch(obj.signal,hanning(options.fft_length),options.fft_length/2,options.fft_length,obj.fs,"centered","psd","mean");
[p_lin,w] = pwelch(obj.signal,hanning(options.fft_length),options.fft_length/2,options.fft_length,obj.fs,"centered","power","mean");
w = w.*1e-9;
else
[p_lin,w] = pwelch(obj.signal,hanning(options.fft_length),options.fft_length/2,options.fft_length,"centered","psd","mean");
[p_lin,w] = pwelch(obj.signal,hanning(options.fft_length),options.fft_length/2,options.fft_length,"centered","power","mean");
end
if options.normalizeTo0dB
@@ -411,8 +411,9 @@ classdef Signal
try
ylim([max(min(floor(min(p_dbm))-3, ax.YLim(1)),-40), min(max(ceil(max(p_dbm))+3, ax.YLim(2)),10)]);
catch
ylim([min(floor(min(p_dbm))-3, ax.YLim(1)), max(ceil(max(p_dbm))+3, ax.YLim(2))]);
ylim([floor(min(p_dbm))-3, ceil(max(p_dbm))+3]);
end
ylim([floor(min(p_dbm))-3, ceil(max(p_dbm))+3]);
yticks(-200:10:10);
grid on; grid minor;
legend
@@ -655,13 +656,22 @@ classdef Signal
end
%%
function [obj,S,isFlipped] = tsynch(obj,options)
function [obj,S,isFlipped,sequenceFound] = tsynch(obj,options)
% time sync and cut
arguments
obj Signal
options.reference Signal
options.fs_ref = 0;
options.debug_plots = 0;
end
S = {};
isFlipped=0;
sequenceFound = 0;
%normalize the signal
a = obj.normalize("mode","oneone").signal;
@@ -679,29 +689,46 @@ classdef Signal
%estimate start pos of signal
maxpeaknum = floor(length(a)/length(b));
[pks,pkpos] = findpeaks(abs(co./max(co)),'MinPeakDistance',length(b)/2,'MinPeakHeight',0.2,'NPeaks',maxpeaknum,'SortStr','descend');
try
[pks,pkpos,w,p] = findpeaks(abs(co./max(co)),'MinPeakDistance',length(b)/2,'MinPeakHeight',0.2,'NPeaks',maxpeaknum,'SortStr','descend');
catch
warning(['Error in findpeaks, ususally the seuqnece is too short. Max peak num: ', num2str(maxpeaknum)]);
return
end
if mean(w) > 10 || mean(p) > 10
return
else
sequenceFound = 1;
end
if options.debug_plots
figure()
findpeaks(abs(co./max(co)),'MinPeakDistance',length(b)/2,'MinPeakHeight',0.2,'NPeaks',maxpeaknum,'SortStr','descend')
end
shifts = lags(pkpos);
shifts = shifts(shifts>=0);
S = {};
isFlipped=0;
if numel(shifts) > 0
%Cut occurences of ref signal from signal (only positive shifts)
if all(sign(co(pkpos)))
isFlipped = 1;
end
for c = shifts(shifts>=0)
sig = obj.delay(-c,'mode','samples');
sig.signal = sig.signal(1:length(b));
sig.signal = sig.signal(1:length(b)).*-isFlipped;
S{end+1,1} = sig;
end
%
if all(sign(co(pkpos)))
isFlipped = 1;
end
%return/keep the sinal with the highest correlation (only within positive shifts)
[~,idx]=max(pks(shifts>=0));
@@ -722,8 +749,7 @@ classdef Signal
end
%plot all synced signals and the ref signal
debug = 0;
if debug
if options.debug_plots
figure;hold on;
for i = 1:size(S,1)
plot(S{i}.normalize('mode','oneone').signal(1000:1100),'LineWidth',0.1,'Color',[0.2157 0.4941 0.7216]);
@@ -735,6 +761,12 @@ classdef Signal
end
%%
function obj = filter(obj,a,b)
@@ -850,7 +882,10 @@ classdef Signal
sig = obj.signal;
end
x = (sig); %% make input signal rea)l
startpos = floor(0.1*length(sig));
endpos = floor(0.9*length(sig));
endpos = min(endpos,startpos+200000);
x = sig(startpos:endpos); %% make input signal rea)l
x = resample(x,fsym*histpoints_horizontal/2,obj.fs); %% up sample to original fsym rate

11
Classes/01_transmit/ChannelFreqResp.m
View File

@@ -241,10 +241,13 @@ classdef ChannelFreqResp < handle
xlim([0.2 .5*max(obj.faxis)*1e-9]); grid on;
%%% plot for publication
figure(1234);hold all;box on;title('Magnitude Freq. Response');
%xlim([0.2 .5*max(obj.faxis)*1e-9]);
%ylim([-40, 2]);
Havg_smooth = smooth(Havg,50);
figure(1234);
hold all;
box on;
title('Magnitude Freq. Response');
xlim([0.2 .5*max(obj.faxis)*1e-9]);
ylim([-40, 2]);
% Havg_smooth = smooth(Havg,10);
symaxis = (obj.faxis-(obj.f_ref/2))/1e9;
Havg = fftshift(Havg);
%Havg = smooth(Havg);

278
Classes/01_transmit/PAMmapper.m
View File

@@ -8,28 +8,38 @@ classdef PAMmapper
thresholds
levels
scaling
eth_style
end
methods
function obj = PAMmapper(M, unipolar)
function obj = PAMmapper(M, unipolar, options)
%PAMMAPPER Construct an instance of this class
% Detailed explanation goes here
arguments
M
unipolar
options.eth_style = 0;
end
obj.M = M;
obj.unipolar = unipolar;
obj.thresholds = obj.get_demodulation_thresholds();
obj.levels = obj.get_levels();
obj.scaling = rms(obj.get_levels());
obj.eth_style = options.eth_style;
end
function out = map(obj,signal_in)
if isa(signal_in,'Signal')
signal_in.signal = obj.map_(signal_in.signal);
signal_in.signal = obj.map_(signal_in.signal);
% signal_in = signal_in.normalize("mode","rms");
lbdesc = ['Map bat stream to PAM ',num2str(obj.M),' symbols'];
signal_in = signal_in.logbookentry(lbdesc,obj);
@@ -37,19 +47,19 @@ classdef PAMmapper
else
out = signal_in;
end
end
function signal_out = demap(obj,signal_in)
issignalclass = 0;
if isa(signal_in,'Signal')
signalclass = signal_in;
signal_in = signal_in.signal;
issignalclass = 1;
signalclass = signal_in;
signal_in = signal_in.signal;
issignalclass = 1;
end
signal_out = obj.demap_(signal_in);
signal_out = obj.demap_(signal_in);
if issignalclass
lbdesc = ['Demap PAM ',num2str(obj.M),' symbols to bit stream'];
@@ -58,7 +68,7 @@ classdef PAMmapper
signal_in.signal = signal_out;
signal_out = signal_in;
end
end
function pam_sig = map_(obj,bitpattern)
@@ -66,50 +76,114 @@ classdef PAMmapper
switch obj.M
case 2
% 2-ASK: BPSK / OOK
pam_sig=bitpattern(:,1);
if obj.unipolar==0
pam_sig=2*pam_sig-1;
if ~obj.eth_style
pam_sig = bitpattern(:,1);
if obj.unipolar==0
pam_sig=2*pam_sig-1;
end
else
pam_sig = -2*bitpattern(:,1) + 1;
end
case 4
% 4-ASK:
pam_sig=2*bitpattern(:,1)+(bitpattern(:,1)==bitpattern(:,2));
if ~obj.eth_style
pam_sig=2*bitpattern(:,1)+(bitpattern(:,1)==bitpattern(:,2));
if obj.unipolar==0
pam_sig=2*pam_sig-3;
if obj.unipolar==0
pam_sig=2*pam_sig-3;
end
else
pam_sig = (2*bitpattern(:,1)-1).*(-2*bitpattern(:,2)+3);
end
pam_sig = pam_sig/sqrt(5);
case 6
m = 1;
if size(bitpattern,2)>size(bitpattern,1)
bitpattern = bitpattern'; %vector aufrecht stellen
end
% LUT based mapping
for k = 1:5:fix(length(bitpattern)/5)*5
pam_sig(m:m+1,1) = obj.thresholds(bin2dec(int2str(bitpattern(k:k+4)'))+1,:);
m = m+2;
if ~obj.eth_style
m = 1;
if size(bitpattern,2)>size(bitpattern,1)
bitpattern = bitpattern'; %vector aufrecht stellen
end
% LUT based mapping
for k = 1:5:fix(length(bitpattern)/5)*5
pam_sig(m:m+1,1) = obj.thresholds(bin2dec(int2str(bitpattern(k:k+4)'))+1,:);
m = m+2;
end
else
bitsPerSymbol = reshape(bitpattern,5,[]).'; % reorder 5 bits per symbol
normFactor = 1;
%====================32 QAM===================%
%=============================================%
% Coding %
% 01000 01001 |11001 11000 %
% | %
% 01010 01110 01100 |11100 11110 11010 %
% | %
% 01011 01111 01101 |11101 11111 11011 %
% --------------------|------------------- %
% 00011 00111 00101 |10101 10111 10011 %
% | %
% 00010 00110 00100 |10100 10110 10010 %
% | %
% 00000 00001 |10001 10000 %
%=============================================%
% modulate three LSB first in first Quadrant
% first bit inverts real part if 0
% second bit inverts imaginary part if 0
LSB_symbols = normFactor*(...
+(1+1i) *(bitsPerSymbol(:,3)==1 & bitsPerSymbol(:,4)==0 & bitsPerSymbol(:,5)==1)...
+(3+1i) *(bitsPerSymbol(:,3)==1 & bitsPerSymbol(:,4)==1 & bitsPerSymbol(:,5)==1)...
+(5+1i) *(bitsPerSymbol(:,3)==0 & bitsPerSymbol(:,4)==1 & bitsPerSymbol(:,5)==1)...
+(1+3i) *(bitsPerSymbol(:,3)==1 & bitsPerSymbol(:,4)==0 & bitsPerSymbol(:,5)==0)...
+(3+3i) *(bitsPerSymbol(:,3)==1 & bitsPerSymbol(:,4)==1 & bitsPerSymbol(:,5)==0)...
+(5+3i) *(bitsPerSymbol(:,3)==0 & bitsPerSymbol(:,4)==1 & bitsPerSymbol(:,5)==0)...
+(1+5i) *(bitsPerSymbol(:,3)==0 & bitsPerSymbol(:,4)==0 & bitsPerSymbol(:,5)==1)...
+(3+5i) *(bitsPerSymbol(:,3)==0 & bitsPerSymbol(:,4)==0 & bitsPerSymbol(:,5)==0));
Re = real(LSB_symbols);
Im = imag(LSB_symbols);
% if first bit== 0 => invert real part
% if second bit== 0 => invert imag part
modData2 = Re.*(bitsPerSymbol(:,1)*2-1) + 1i*Im.*(bitsPerSymbol(:,2)*2-1);
Re = real(modData2(1:end/2));
Im = imag(modData2(1:end/2));
pam_sig = zeros(length(Re)*2,1);
pam_sig(1:2:length(Re)*2) = Re;
pam_sig(2:2:length(Im)*2) = Im;
end
pam_sig = pam_sig/sqrt(10);
case 8
% 8-ASK:
x1 = bitpattern(:,1);
x2 = (bitpattern(:,1)==bitpattern(:,3));
x3 = x2~=bitpattern(:,2);
if ~obj.eth_style
x1 = bitpattern(:,1);
x2 = (bitpattern(:,1)==bitpattern(:,3));
x3 = x2~=bitpattern(:,2);
pam_sig = 4*x1 + 2*x2 + x3;
pam_sig = 4*x1 + 2*x2 + x3;
if obj.unipolar==0
pam_sig=2*pam_sig-7;
end
else
pam_sig = (bitpattern(:,1)*2-1).*(4+(2*bitpattern(:,2)-1).*(-2*bitpattern(:,3)+3));
if obj.unipolar==0
pam_sig=2*pam_sig-7;
end
pam_sig = pam_sig/sqrt(21);
case 16
% 16-ASK:
x1 = bitpattern(:,1);
@@ -143,7 +217,7 @@ classdef PAMmapper
% case 16
% thres = [-10 -8 -6 -4 -2 0 2 4 6 8 10];
% end
switch obj.M
@@ -166,12 +240,12 @@ classdef PAMmapper
thres = thres .* 1/sqrt(5);
case 6 %PAM 6
case 6 %PAM 6
thres = [-3 5;-1 5;-3 -5;-1 -5;-5 3;-5 1;-5 -3;-5 -1;-1 3;-1 1;-1 -3;-1 -1;-3 3;-3 1;-3 -3;-3 -1;3 5;1 5;3 -5;1 -5;5 3;5 1;5 -3;5 -1;1 3;1 1;1 -3;1 -1;3 3;3 1;3 -3;3 -1];
% thres = [-4 -2 0 2 4];
% thres = thres ./ sqrt(10);
case 8
% 8-ASK
if obj.unipolar==0
@@ -179,7 +253,7 @@ classdef PAMmapper
elseif obj.unipolar==1
thres=0.5:6.5;
end
thres=thres./sqrt(21);
case 16
@@ -210,65 +284,115 @@ classdef PAMmapper
end
function [data_out] = demap_(obj,data_in)
data_in= data_in';
if obj.M ~= 6
% create output
if ~isempty(obj.thresholds)
a = squeeze(repmat(real(data_in),[1 1 length(obj.thresholds)])); %Eingangssignal in 3 spalten
b = squeeze(repmat(reshape(obj.thresholds(:).',[1 1 length(obj.thresholds)]),[1 length(data_in) 1])); %Threshold in 3 Spalten
comp_real = a > b; %check for each symbol/ sampling if it exeeds the obj.thresholdseshold 1, 2 or 3
comp_real=repmat(real(data_in),[1 1 length(obj.thresholds)]) > repmat(reshape(obj.thresholds(:).',[1 1 length(obj.thresholds)]),[1 length(data_in) 1]);
else
comp_real=[];
end
s1=size(comp_real,1);
s2=size(comp_real,2);
end
switch obj.M
case 2
% 2-ASK
data_out=comp_real(:,:,1);
if ~obj.eth_style
data_out=comp_real(:,:,1);
else
data_out=abs(comp_real(:,:,1)-1);
end
case 4
% 4-ASK
data_out=[comp_real(:,:,2); ones(s1,s2) - comp_real(:,:,1) + comp_real(:,:,3)];
if ~obj.eth_style
data_out=[comp_real(:,:,2); ones(s1,s2) - comp_real(:,:,1) + comp_real(:,:,3)];
else
data_out= [(data_in>=0); (abs(data_in)<=1)];
end
case 6
data_in = data_in/(sqrt(mean(abs(data_in).^2)));
data_in = data_in*sqrt(10);
if ~obj.eth_style
data_in = data_in/(sqrt(mean(abs(data_in).^2)));
data_in = data_in*sqrt(10);
if size(data_in,2) > 1
data_in = data_in.';
end
if length(data_in)/2 ~= round(length(data_in)/2)
data_in = [data_in;0];
end
m = 1;
for n = 1:2:length(data_in)
dist = sqrt((data_in(n)-obj.thresholds(:,1)).^2+(data_in(n+1)-obj.thresholds(:,2)).^2);
[~,dd_idx] = min(dist);
% dec_out(n:n+1) = LUT(dd_idx,:);
data_out(m:m+4) = bitget(dd_idx-1,5:-1:1);
m = m+5;
end
else
data_in= data_in';
rxSym = data_in(1:2:end) + 1i*data_in(2:2:end); % 16×1
% Decode the sign bits (bits 1 & 2).
rxBit1 = double(real(rxSym) > 0);
rxBit2 = double(imag(rxSym) > 0);
% Undo the quadrant inversion and normalization.
rxSym_corr = abs(real(rxSym)) + 1i*abs(imag(rxSym));
normFactor = 1/sqrt(10);
rxSym_unscaled = rxSym_corr / normFactor;
cand = [1+1i, 3+1i, 5+1i, 1+3i, 3+3i, 5+3i, 1+5i, 3+5i];
candBits = [1 0 1;
1 1 1;
0 1 1;
1 0 0;
1 1 0;
0 1 0;
0 0 1;
0 0 0];
d = abs(rxSym_unscaled - cand).^2; % 32×8 distances
[~, idx] = min(d, [], 2);
rxLSB = candBits(idx,:); % 32×3
decodedSymbols = [rxBit1, rxBit2, rxLSB];
data_out = reshape(decodedSymbols.', [], 1).';
if size(data_in,2) > 1
data_in = data_in.';
end
if length(data_in)/2 ~= round(length(data_in)/2)
data_in = [data_in;0];
end
m = 1;
for n = 1:2:length(data_in)
dist = sqrt((data_in(n)-obj.thresholds(:,1)).^2+(data_in(n+1)-obj.thresholds(:,2)).^2);
[~,dd_idx] = min(dist);
% dec_out(n:n+1) = LUT(dd_idx,:);
data_out(m:m+4) = bitget(dd_idx-1,5:-1:1);
m = m+5;
end
case 8
% 8-ASK
data_out=[comp_real(:,:,4);
comp_real(:,:,1)-comp_real(:,:,3)+comp_real(:,:,5)-comp_real(:,:,7);
1-comp_real(:,:,2)+comp_real(:,:,6)];
if ~obj.eth_style
data_out=[comp_real(:,:,4);
comp_real(:,:,1)-comp_real(:,:,3)+comp_real(:,:,5)-comp_real(:,:,7);
1-comp_real(:,:,2)+comp_real(:,:,6)];
else
data_out = [(data_in>=0); (abs(data_in)>(4/sqrt(21))); (abs(data_in)>=(2/sqrt(21)))&(abs(data_in)<=(6/sqrt(21)))];
end
case 16
% 16-ASK
@@ -289,21 +413,21 @@ classdef PAMmapper
data_in Signal
options.symbol_levels = []
end
%A) normally return the preproduct of the decision
a = squeeze(repmat(real(data_in.signal),[1 1 length(obj.thresholds)])); %Eingangssignal in 3 spalten
b = squeeze(repmat(reshape(obj.thresholds(:).',[1 1 length(obj.thresholds)]),[1 length(data_in.signal) 1])); %Threshold in 3 Spalten
comp_real = a > b; %check for each symbol/ sampling if it exeeds the obj.thresholdseshold 1, 2 or 3
data_out = data_in;
data_out.signal = sum(comp_real,2);
%Option: return the actual level values/ just map onto given
%symbol levels
if ~isempty(options.symbol_levels)
data_out.signal = options.symbol_levels(data_out.signal+1);
end
end
function [out] = separate_pamlevels(obj,data_in)
@@ -312,7 +436,7 @@ classdef PAMmapper
a = squeeze(repmat(real(data_in.signal),[1 1 length(obj.thresholds)])); %Eingangssignal in 3 spalten
b = squeeze(repmat(reshape(obj.thresholds(:).',[1 1 length(obj.thresholds)]),[1 length(data_in.signal) 1])); %Threshold in 3 Spalten
comp_real = a > b; %check for each symbol/ sampling if it exeeds the obj.thresholdseshold 1, 2 or 3
comp_real_sum = sum(comp_real,2);
comp_real_sum = sum(comp_real,2);
out = NaN(length(data_in),length(obj.thresholds)+1);
@@ -323,7 +447,7 @@ classdef PAMmapper
end
function [Signal_out] = quantize(obj,Signal_in)
constellation = obj.get_levels();
constellation = constellation ./ rms(constellation);
@@ -331,9 +455,9 @@ classdef PAMmapper
if isa(Signal_in,'Signal')
issignalclass = 1;
Sig_class = Signal_in;
Signal_in = Signal_in.signal;
Signal_in = Signal_in.signal;
end
[~,high_dim_sig] = max(size(Signal_in));
[~,high_dim_const] = max(size(constellation));
@@ -346,7 +470,7 @@ classdef PAMmapper
Signal_out = constellation(symbol_idx);
Signal_out = reshape(Signal_out,size(Signal_in));
if issignalclass
if issignalclass
Sig_class.signal = Signal_out;
Signal_out = Sig_class;
end
@@ -355,6 +479,10 @@ classdef PAMmapper
end
function bitmap = showBitMapping(obj)
bitmap = obj.demap([obj.levels ./ obj.scaling]');
end
end
end

59
Classes/01_transmit/PAMsource.m
View File

@@ -71,18 +71,17 @@ classdef PAMsource
function [digi_sig,symbols,bits] = process(obj)
%%%%% PRBS Generation in correct shape for Modulation Format %%%%%%
O = obj.order; %order of prbs
N = 2^(O-1); %length of prbs
[~,seed] = prbs(O,1); %initialize first seed of prbs
bitpattern=[];
if obj.useprbs
% for i = 1:log2(obj.M)
% [bitpattern(:,i),seed] = prbs(O,N,seed);
% end
% O = obj.order; %order of prbs
% N = 2^(O-1); %length of prbs
% [~,seed] = prbs(O,1); %initialize first seed of prbs
% % for i = 1:log2(obj.M)
% % [bitpattern(:,i),seed] = prbs(O,N,seed);
% % end
%%%%% MOVE-IT PRMS %%%%
state = struct();
para = struct();
@@ -103,6 +102,8 @@ classdef PAMsource
para.reset_prms = 0;
para.method = 1;
data_in = [];
global loop;
loop = 0;
@@ -116,6 +117,7 @@ classdef PAMsource
else
s = RandStream('twister','Seed',obj.randkey);
for i = 1:log2(obj.M)
N = 2^(obj.order-1); %length of prbs
bitpattern(:,i) = randi(s,[0 1], N, 1);
end
end
@@ -151,23 +153,52 @@ classdef PAMsource
sym_max = max(symbols.signal);
end
% symbols.move_it_spectrum("fignum",222,"displayname","Symbols only");
% symbols.spectrum("fignum",222,"displayname","Symbols only","normalizeTo0dB",1);
%%%%% Pulse-forming %%%%%%
if obj.applypulseform
%%% MY CODE
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);
% Design raised cosine filter with given order in symbols
% digi_sig = symbols;
% sps = 4;
% nsym = 128;
% rctFilt3 = comm.RaisedCosineTransmitFilter(...
% Shape='Square root', ...
% RolloffFactor=1, ...
% FilterSpanInSymbols=nsym, ...
% OutputSamplesPerSymbol=sps);
%
% digi_sig.signal = rctFilt3([symbols.signal; zeros(nsym/2,1)]);
% % Correct for propagation delay by removing filter transients
% fltDelay = nsym / (2*obj.fsym);
% digi_sig.signal = digi_sig.signal(fltDelay*sps*obj.fsym+1:end);
%
% digi_sig.fs = sps .* symbols.fs;
else
digi_sig = symbols;
end
%%%%% Re-sample to f DAC %%%%%%
digi_sig = digi_sig.resample("fs_in",digi_sig.fs,"fs_out",obj.fs_out,"n",10,"beta",5);
% digi_sig.spectrum("fignum",111,"displayname","after pulseforming");
%%%%% Re-sample to f DAC %%%%%%
n = 10;
digi_sig = digi_sig.resample("fs_in",digi_sig.fs,"fs_out",obj.fs_out,"n",n,"beta",5);
% digi_sig.spectrum("fignum",111,"displayname",['3) Shaped + Resampled; n: ',num2str(n)]);
%%%%% Hard clip digital signal to PAM range before DAC %%%%%%
if obj.applyclipping

146
Classes/01_transmit/Pulseformer.m
View File

@@ -3,13 +3,17 @@ classdef Pulseformer
% Detailed explanation goes here
properties(Access=public)
fdac
end
properties(Access=private)
properties(Access=public)
fs
fsym
matched_sps
output_sps
pulse
pulselength
rrcalpha
alpha
matched
end
methods (Access=public)
@@ -18,11 +22,14 @@ classdef Pulseformer
% Detailed explanation goes here
arguments
options.fdac double
options.fs double
options.fsym double
options.pulse pulseform = pulseform.rrc
options.matched_sps double
options.output_sps double
options.pulse pulseform = pulseform.rc
options.pulselength double {mustBeInteger} = 32
options.rrcalpha double = 0.05
options.alpha double = 0.05
options.matched = 0;
end
%
@@ -47,7 +54,11 @@ classdef Pulseformer
signalclass_in = signalclass_in.logbookentry(lbdesc);
% write fs to signal
signalclass_in.fs = obj.fdac;
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
% write to output
signalclass_out = signalclass_in;
@@ -74,60 +85,99 @@ classdef Pulseformer
data_out
end
if ~rem(obj.fdac,obj.fsym)
if ~isempty(obj.output_sps)
obj.fsym = obj.fsym.*obj.output_sps;
end
if ~rem(obj.fs,obj.fsym)
%ist ein Vielfaches
sps = obj.fdac / obj.fsym;
up = sps;
dn = 1;
sps = obj.fs / obj.fsym;
p = sps;
q = 1;
else
%ist kein Vielfaches
up = obj.fdac / gcd(obj.fdac, obj.fsym);
dn = obj.fsym / gcd(obj.fdac, obj.fsym);
sps= up;
p = obj.fsym / gcd(obj.fs, obj.fsym); %upsampling p->->->
q = obj.fs/ gcd(obj.fs, obj.fsym); %downsampling <-q
sps= q; %sps während dem pulse shaping
end
if obj.pulse == pulseform.rrc
%Bau das Filter (hier rrc)
racos_len = obj.pulselength*2;
alpha = obj.rrcalpha;
h = rcosdesign(alpha,racos_len,sps,"normal");
h = h./ max(h);
if obj.pulse == pulseform.rc
filtertype = 'normal';
elseif pulseform.rrc
filtertype = 'sqrt';
end
% Apply filter the long way (from move_it)
% block length in samples
data_in = data_in';
blen = length(data_in)*sps;
% oversample symbol sequence
symbolov=zeros(size(data_in,1),blen);
symbolov(:,1:sps:blen-sps+1)=data_in;
%Bau das Filter (hier rc)
racos_len = obj.pulselength*2;
h = rcosdesign(obj.alpha,racos_len,sps,filtertype);
% h = h./ max(h);
H=fft(h,blen);
% Convolution of Bit sequence with impulse response
if obj.matched
h = conj(fliplr(h));
end
manual_cyclic_convolution = 0;
upsample_filter = 0;
upfirdn_convolution = 1;
% cyclic convolution
data_out=ifft( fft(symbolov.') .* repmat( H,size(data_in,1),1 ).' ).';
if manual_cyclic_convolution
data_out = circshift(data_out,[0 -(obj.pulselength*sps)]);
% Apply filter the long way (from move_it)
data_in = data_in';
blen = length(data_in)*sps;
% oversample symbol sequence
symbolov=zeros(size(data_in,1),blen);
symbolov(:,1:sps:blen-sps+1)=data_in;
H=fft(h,blen);
% Convolution of Bit sequence with impulse response
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)
data_out = data_out(1:q:end);
end
if rem(obj.fdac,obj.fsym)
data_out = data_out(1:dn:end); %!
end
if upsample_filter
data_out_ = upsample(data_in,p);
% %Apply Filter using Matlab build in fctn.
% h = rcosdesign(alpha,racos_len,sps);
% h = h./ max(h);
%data_out_ = upfirdn(data_in,h,up,dn);
%
% %cut signal, which is longer due to fir filter
% st = round(up/dn*racos_len/2); %we need to cut y_out
% en = round(st + (length(data_in)*up/dn) -1);
% data_out = data_out(st:en);
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
st = round(p/q*racos_len/2); %we need to cut y_out
en = round(st + (length(data_in)*p/q));
data_out = data_out_(st:en);
end
if upfirdn_convolution && manual_cyclic_convolution
figure()
subplot(2,1,1)
title("Convolution vs. Upfirdn and Cut")
hold on
% plot(data_out_(1:200),'DisplayName','Matlab upfirdn');
plot(data_out(1:200),'DisplayName','By Hand cyclic convolution')
subplot(2,1,2)
hold on
plot(data_out(1:2000),'DisplayName','OUT');
plot(data_in(1:2000),'DisplayName','IN');
end
%scaling?! see pulsef module line 696
% scale = max(max([abs(real(data_out)) abs(imag(data_out))])); %find max value from real and imag part
@@ -136,7 +186,7 @@ classdef Pulseformer
data_out = data_out';
%Check output integrity
if abs(round(up/dn * length(data_in)) - length(data_out)) > 4
if abs(round(p/q * length(data_in)) - length(data_out)) > 4
warning('Check signal length after pulse shaping');
%disp('Check signal length after pulse shaping');
end

24
Classes/04_DSP/Coding/Duobinary.m
View File

@@ -26,7 +26,9 @@ classdef Duobinary
M = numel(u);
%make unipolar
if M == 4
if M == 2
data = data;
elseif M == 4
data = data .* sqrt(5);
elseif M == 6
data = data .* sqrt(10);
@@ -59,7 +61,9 @@ classdef Duobinary
bk = bk .* 2;
bk = bk + b;
if M == 4
if M == 2
bk = bk;
elseif M == 4
bk = bk ./ sqrt(5);
elseif M == 6
bk = bk ./ sqrt(10);
@@ -100,7 +104,9 @@ classdef Duobinary
end
%make unipolar
if options.M == 4
if options.M == 2
data = data;
elseif options.M == 4
data = data .* sqrt(5);
elseif options.M == 6
data = data .* sqrt(10);
@@ -140,7 +146,9 @@ classdef Duobinary
mean_power = sum((unique_points .^ 2) .* probabilities);
scaling_factor = sqrt(mean_power);
if options.M == 4
if options.M == 2
data = data ./ sqrt(0.5);
elseif options.M == 4
data = data ./ sqrt(2.5); % 7-level constellation weighted with probability after DB code i.e. mean([-3 3 -2 -2 2 2 -1 -1 -1 1 1 1 0 0 0 0].^2) = 2.5 --> sqrt(2.5) == rms(constellation)
elseif options.M == 6
data = data ./ sqrt(5.8);
@@ -186,7 +194,9 @@ classdef Duobinary
end
%make unipolar
if I == 7 || I == 6
if I == 3
data = data .* 0.5;
elseif I == 7 || I == 6
data = data .* sqrt(2.5);
elseif I == 11
data = data .* sqrt(5.8);
@@ -206,7 +216,9 @@ classdef Duobinary
data = data .* 2;
data = data - round(mean(data));
if M == 4
if M == 2
data = data;
elseif M == 4
data = data ./ sqrt(5);
elseif M == 6
data = data ./ sqrt(10);

14
Classes/04_DSP/Equalizer/FFE.m
View File

@@ -101,6 +101,17 @@ classdef FFE < handle
end
x = [zeros(floor(obj.order/2),1); x; zeros(obj.order,1)];
if training
mask = ones(obj.order,1);
else
mask = zeros(obj.order,1);
mask(900:end) = 1;
mask(ceil(length(obj.e)/2)) = 1;
end
mask = ones(obj.order,1);
for epoch = 1 : epochs
symbol = 0;
@@ -110,7 +121,7 @@ classdef FFE < handle
U = x(obj.order+sample-1:-1:sample);
y(symbol,1) = obj.e.' * U; % Calculating output of LMS __ * |
y(symbol,1) = (obj.e.*mask).' * U; % Calculating output of LMS __ * |
if training
d_hat(symbol,1) = d(symbol);
@@ -129,7 +140,6 @@ classdef FFE < handle
normalizationfactor = (U.' * U);
obj.e = obj.e - err(symbol) * U / normalizationfactor; % Weight update rule of NLMS
end
obj.error(epoch,symbol) = err(symbol) * err(symbol)'; % Instantaneous square error

21
Classes/04_DSP/Equalizer/Postfilter.m
View File

@@ -43,12 +43,12 @@ classdef Postfilter < handle
if ~isnan(options.useBurg) && options.useBurg
disp('using burg alg')
% disp('using burg alg')
obj.coefficients = arburg(noiseclass_in.signal,obj.ncoeff);
elseif ~isempty(options.coefficients)
disp('using given taps')
% disp('using given taps')
obj.coefficients = options.coefficients;
obj.useBurg = 0;
@@ -67,22 +67,29 @@ classdef Postfilter < handle
end
function showFilter(obj,noiseclass_in,options)
function showFilter(obj,options)
arguments
obj
noiseclass_in
options.noiseclass_in =[]
options.fignum = 121
options.color = []
end
% noiseclass_in.spectrum('displayname','Noise PSD shifted to 0dBm','fignum',options.fignum,'normalizeTo0dB',1);
if ~isempty(options.noiseclass_in)
len = length(options.noiseclass_in);
fs = options.noiseclass_in.fs;
else
len = 1024;
fs = 1;
end
figure(options.fignum)
[h,w] = freqz(1,obj.coefficients,length(noiseclass_in),"whole",noiseclass_in.fs);
[h,w] = freqz(1,obj.coefficients,len,"whole",fs);
h = h/max(abs(h));
hold on
w_ = (w - noiseclass_in.fs/2);
w_ = (w - fs/2);
if isempty(options.color)
plot(w_.*1e-9,20*log10(fftshift(abs(h))),'DisplayName',['Burg Coeffs: ', num2str(round(obj.coefficients,2)), ' '],'LineWidth',2);

52
Classes/04_DSP/Sequence Detection/MLSE.m
View File

@@ -70,7 +70,7 @@ classdef MLSE < handle
%%%% Separate the equalized signal into the respective levels based on the actually transmitted level
constellation = unique(data_ref);
decisionLevels = (constellation(1:end-1) + constellation(2:end)) / 2;
tx_bits = PAMmapper(numel(constellation),0).demap(data_ref);
tx_bits = PAMmapper(numel(constellation),0,"eth_style",1).demap(data_ref);
% impulse respnse i.e. [0.5, 1.0000]
@@ -188,10 +188,50 @@ classdef MLSE < handle
end
% Compute soft output PAM4 stream from the metric_sym
soft_output = zeros(length(data_in),1); % Expected symbol value per stage
symbol_prob = zeros(length(data_in), length(states)); % Store full probability distribution (optional)
llp = llp';
for n = 1:length(data_in)
metrics = llp(n, :); % A posteriori metric for each PAM4 candidate
% For numerical stability, subtract the maximum metric before exponentiating
maxMetric = min(metrics);
expMetrics = exp(metrics - maxMetric);
probs = expMetrics / sum(expMetrics); % Normalize to get probabilities
symbol_prob(n, :) = probs; % (Optional) store distribution for analysis
% Compute the soft output as the expected value of the PAM4 symbols
soft_output(n) = sum(probs .* constellation');
end
% Number of symbols and bits per symbol
num_symbols = constellation;
num_bits = 2; % 2 bits per symbol
bit_mapping = PAMmapper(4,0,"eth_style",1).showBitMapping; % Each row corresponds to the symbol above
% Initialize LLR storage
llr = zeros(num_bits, length(data_in));
% Compute bit-wise LLRs
for bit_idx = 1:num_bits
% Find indices where bit is 0 and where it is 1
idx_bit_0 = find(bit_mapping(:,bit_idx) == 0);
idx_bit_1 = find(bit_mapping(:,bit_idx) == 1);
% Sum over log-probabilities (Max-Log approximation: using min instead of sum)
llr(:,bit_idx) = min(llp(:,idx_bit_1), [], 1) - min(llp(:,idx_bit_0), [], 1);
end
% Convert LLR values to a hard-decision bit stream
bit_stream = llr < 0;
[~,~,ber_llr,~] = calc_ber(bit_stream',tx_bits,"skip_front",100,"skip_end",150,"returnErrorLocation",1);
fprintf('LLR BER : %.2e \n',ber_llr);
% directly decide based on lowest LLP index
[~,llp_based_state_seq]=min(llp);
LLP_EST(1:length(data_in)) = constellation(llp_based_state_seq);
rx_bits = PAMmapper(numel(constellation),0).demap(LLP_EST');
rx_bits = PAMmapper(numel(constellation),0,"eth_style",1).demap(LLP_EST');
[~,~,ber_llp,~] = calc_ber(rx_bits,tx_bits,"skip_front",100,"skip_end",150,"returnErrorLocation",1);
fprintf('LLP BER : %.2e \n',ber_llp);
% [~,~,ber_llp,~] = calc_ber(circshift(rx_bits,1),tx_bits,"skip_front",100,"skip_end",150,"returnErrorLocation",1);
@@ -200,7 +240,7 @@ classdef MLSE < handle
% fprintf('LLP BER -1: %.2e \n',ber_llp);
%%%% DECIDE based on Viterbi traceback
rx_bits = PAMmapper(numel(constellation),0).demap(VITERBI_ESTIMATION_SYMBOLS');
rx_bits = PAMmapper(numel(constellation),0,"eth_style",1).demap(VITERBI_ESTIMATION_SYMBOLS');
[~,~,ber_viterbi,~] = calc_ber(rx_bits,tx_bits,"skip_front",100,"skip_end",150,"returnErrorLocation",1);
fprintf('Viterbi BER: %.2e \n',ber_viterbi);
% [~,~,ber_viterbi,~] = calc_ber(circshift(rx_bits,1),tx_bits,"skip_front",100,"skip_end",150,"returnErrorLocation",1);
@@ -209,14 +249,14 @@ classdef MLSE < handle
% directly decide based on the FW path metrics
[~,fw_direct_state_seq]=min(pm_survivor_fw);
FW_EST(1:length(data_in)) = constellation(fw_direct_state_seq);
rx_bits = PAMmapper(numel(constellation),0).demap(FW_EST');
rx_bits = PAMmapper(numel(constellation),0,"eth_style",1).demap(FW_EST');
[~,~,ber_fw,~] = calc_ber(rx_bits,tx_bits,"skip_front",100,"skip_end",150,"returnErrorLocation",1);
fprintf('FW BER: %.2e \n',ber_fw);
% directly decide based on the BW path metrics
[~,bw_direct_state_seq]=min(pm_survivor_bw);
BW_EST(1:length(data_in)) = constellation(bw_direct_state_seq(2:end));
rx_bits = PAMmapper(numel(constellation),0).demap(BW_EST');
rx_bits = PAMmapper(numel(constellation),0,"eth_style",1).demap(BW_EST');
[~,~,ber_bw,~] = calc_ber(rx_bits,tx_bits,"skip_front",100,"skip_end",150,"returnErrorLocation",1);
fprintf('BW BER: %.2e \n',ber_bw);
% [~,~,ber_viterbi,~] = calc_ber(circshift(rx_bits,1),tx_bits,"skip_front",100,"skip_end",150,"returnErrorLocation",1);
@@ -224,6 +264,8 @@ classdef MLSE < handle
% [~,~,ber_viterbi,~] = calc_ber(circshift(rx_bits,-1),tx_bits,"skip_front",100,"skip_end",150,"returnErrorLocation",1);
% fprintf('BW BER: %.2e \n',ber_viterbi);
PAMmapper(4,0,"eth_style",1).showBitMapping
%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%
tx_symbolpos = zeros(numel(constellation),length(data_ref));

32
Classes/04_DSP/TransmissionPerformance.m
View File

@@ -59,8 +59,19 @@ classdef TransmissionPerformance
1.03e-2, 9.29e-3, 8.33e-3, 7.54e-3, 7.04e-3, 4.70e-3];
%% LUT for KP4-FEC and Inner Code https://grouper.ieee.org/groups/802/3/dj/public/23_03/patra_3dj_01b_2303.pdf
CODE_RATE_KP4_AND_INNER = [0.885799];
BERTHRESHOLDS_KP4_AND_INNER = 4.85e-3;
% https://www.ieee802.org/3/bs/public/14_11/parthasarathy_3bs_01a_1114.pdf
CODE_RATE_KP4 = [1/(1+0.052)];%Reed-Solomon RS(544, 514) == KP4
BERTHRESHOLDS_KP4 = 2.2e-4;
CODE_RATE_HDFEC = [1/(1+0.067)]; %Beyond 300 Gbps Short-Reach Links Using TFLN MZMs With 500 mVpp and Linear Equalization
BERTHRESHOLDS_HDFEC = 3.8e-3;
CODE_RATE_O_FEC = [1/(1+0.153)]; %Stefano im Meeting
BERTHRESHOLDS_O_FEC = 2e-2;
@@ -151,6 +162,11 @@ classdef TransmissionPerformance
netrates.KP4_hamming.NetRate = NaN(1, numMeasurements);
netrates.KP4_hamming.CodeRate = NaN(1, numMeasurements);
netrates.KP4_hamming.Threshold = NaN(1, numMeasurements);
netrates.O_FEC.GrossRate = NaN(1, numMeasurements);
netrates.O_FEC.NetRate = NaN(1, numMeasurements);
netrates.O_FEC.CodeRate = NaN(1, numMeasurements);
netrates.O_FEC.Threshold = NaN(1, numMeasurements);
end
% Process each measurement individually.
@@ -204,6 +220,22 @@ classdef TransmissionPerformance
netrates.KP4_hamming.Threshold(i) = obj.BERTHRESHOLDS_KP4_AND_INNER(idxBER);
end
idxBER = [];
for j = length(obj.BERTHRESHOLDS_O_FEC):-1:1
if ber(i) <= obj.BERTHRESHOLDS_O_FEC(j)
idxBER = j;
break;
end
end
if ~isempty(idxBER)
codeRate = obj.CODE_RATE_O_FEC(idxBER);
netrates.O_FEC.NetRate(i) = grossRate(i) * codeRate;
netrates.O_FEC.GrossRate(i) = grossRate(i) ;
netrates.O_FEC.CodeRate(i) = codeRate;
netrates.O_FEC.Threshold(i) = obj.BERTHRESHOLDS_O_FEC(idxBER);
end
end

614
Classes/DataBaseHandler/DBHandler.m
View File

@@ -45,15 +45,15 @@ classdef DBHandler < handle
else
error('DB seems to be corrupt')
end
end
function obj = refresh(obj)
% Get table names and the first rows of each table to understand the structure
obj.getTableNames();
obj.getTables();
obj.getDistinctValues();
% Get table names and the first rows of each table to understand the structure
obj.getTableNames();
obj.getTables();
obj.getDistinctValues();
end
function obj = getTableNames(obj)
@@ -187,10 +187,11 @@ classdef DBHandler < handle
if isstruct(newRow)
fields = fieldnames(newRow);
emptyFields = structfun(@isempty,newRow);
if sum(emptyFields)>0
newRow.(fields{emptyFields==1}) = NaN;
disp(['In Table: ',tableName,': ',fields{emptyFields==1},' was empty, is now NaN ',newRow.(fields{emptyFields==1})])
if sum(emptyFields) > 0
emptyFieldNames = fields(emptyFields); % use () to get a cell array
for idx = 1:numel(emptyFieldNames)
newRow.(emptyFieldNames{idx}) = NaN;
end
end
newRow = struct2table(newRow);
end
@@ -274,87 +275,168 @@ classdef DBHandler < handle
end
end
function addBEREntry(obj, berValue, occurrence, runID, ffe, dfe, mlse, pf, eqType, ffe_order, dfe_order, len_tr, mu_ffe, mu_dfe, mu_dc, comment)
% addBEREntry Adds a BER entry linked to an existing or new Equalizer entry.
% Usage:
% addBEREntry(runID, eq, ffe, dfe, mlse, pf, eqType, ffe_order, dfe_order, len_tr, mu_ffe, mu_dfe, mu_dc, berValue, comment)
if isempty(pf)
postfilter_taps = [];
function resultID = addProcessingResult(obj, run_id, resultData, eqParamsData)
% addProcessingResult Adds a processing result and links it to an EqualizerParameters entry.
%
% Inputs:
% run_id: A run_id from the main table to connect the BER with.
%
% resultData: A struct with fields corresponding to the ProcessingResults table.
%
% eqParamsData: A struct with fields corresponding to the EqualizerParameters table,
% except 'eq_id' and 'config_hash'. These fields are used to compute
% a hash and check for an existing configuration.
%
% Output:
% resultID: The result_id of the newly inserted ProcessingResults entry.
% 1. Compute hash for equalizer parameters
jsonStr = jsonencode(eqParamsData);
md = java.security.MessageDigest.getInstance('MD5');
md.update(uint8(jsonStr));
hashBytes = typecast(md.digest, 'uint8');
hashStr = lower(dec2hex(hashBytes)');
hashStr = lower(strtrim(hashStr(:)')); % Convert to a lowercase string
% Add hash to equalizer parameters
eqParamsData.config_hash = hashStr;
% 2. Check if an equalizer configuration with the same hash exists
queryStr = sprintf('SELECT eq_id FROM EqualizerParameters WHERE config_hash = ''%s''', eqParamsData.config_hash);
existingEntry = obj.fetch(queryStr);
if ~isempty(existingEntry)
% Use existing eq_id
eq_id = existingEntry{1,1};
else
postfilter_taps = pf.burg_coeff;
% Insert the new equalizer configuration and get its eq_id
eq_id = obj.appendToTable('EqualizerParameters', eqParamsData);
end
% Create equalizer data struct for searching and adding if necessary
equalizerData = struct( ...
'ffe', jsonencode(ffe), ...
'dfe', jsonencode(dfe), ...
'mlse', jsonencode(mlse), ...
'pf', jsonencode(pf), ...
'eq_type', string(eqType), ...
'ffe_order', jsonencode(ffe_order), ...
'dfe_order', jsonencode(dfe_order), ...
'postfilter_taps',jsonencode(postfilter_taps),...
'len_tr', len_tr, ...
'mu_ffe', jsonencode(mu_ffe), ...
'mu_dfe', mu_dfe, ...
'mu_dc', mu_dc, ...
'comment', comment ...
);
% 3. Add the equalizer configuration reference and run_id to resultData
resultData.eqParam_id = eq_id;
resultData.run_id = run_id;
% Check if exact Equalizer and BER entries already exist in the DB ...
selectedFields = {'Runs.run_id','BERs.ber_id','Equalizer.eq_id','BERs.ber',['BERs.occurrence' ...
'']};
filterParams = obj.tables;
filterParams.Equalizer = equalizerData;
[dataTable,sql_query] = obj.queryDB(filterParams, selectedFields);
% 4. Compute hash for the processing result
tempResultData = rmfield(resultData, 'date_of_processing');
resultJsonStr = jsonencode(tempResultData);
md2 = java.security.MessageDigest.getInstance('MD5'); % Create a new MD5 instance
md2.update(uint8(resultJsonStr));
resultHashBytes = typecast(md2.digest, 'uint8');
resultHashStr = lower(dec2hex(resultHashBytes)');
resultHashStr = lower(strtrim(resultHashStr(:)')); % Convert to a lowercase string
% get or insert Equalizer
if ~isempty(dataTable)
% Equalizer entry already exists, use the existing eq_id
cur_eq_id = dataTable.eq_id;
else
% Insert the new Equalizer entry
cur_eq_id = obj.appendToTable('Equalizer', equalizerData);
% Add the result hash to resultData
resultData.result_hash = resultHashStr;
% 5. Check if an identical processing result already exists
queryStr2 = sprintf('SELECT result_id FROM Results WHERE result_hash = ''%s''', resultData.result_hash);
existingResult = obj.fetch(queryStr2);
if ~isempty(existingResult)
% If the result exists, return its result_id without inserting a new row
resultID = existingResult{1,1};
warning(['Result already exists: ResultID: ',num2str(resultID),'| EQ ID: ',num2str(eq_id),' Run ID: ' num2str(run_id)])
return;
end
% skip if already here or insert BER entry
if ~isempty(dataTable)
% 6. Insert the processing result
resultID = obj.appendToTable('Results', resultData);
end
% A BER entry with the same eq_id, run_id, and occurrence already exists
existingBERValue = dataTable.ber;
function recalcHashes(obj)
% recalcHashes Recalculate hashes for all rows in the Results and EqualizerParameters tables.
%
% For EqualizerParameters, the hash is computed from all fields except
% 'eq_id' and 'config_hash'.
%
% For Results, the hash is computed from all fields except 'result_id',
% 'result_hash', and 'date_of_processing'.
% Compare the existing BER value with the new BER value
if existingBERValue == berValue
fprintf('The BER entry %.2e || -- eq_id: %d -- run_id: %d -- occurrence: %d already exists. \n',berValue, cur_eq_id, runID, occurrence);
else
fprintf('Already found BER for EQ: %.2e ~= %.2e || -- eq_id: %d -- run_id: %d -- occurrence: %d already exists.\n', berValue, existingBERValue, cur_eq_id, runID, occurrence);
% Recalculate hashes for EqualizerParameters
eqParamsRows = obj.fetch('SELECT * FROM EqualizerParameters');
for i = 1:height(eqParamsRows)
rowStruct = table2struct(eqParamsRows(i,:)); % Convert the table row to a struct
% Remove fields not part of the hash computation
if isfield(rowStruct, 'eq_id')
rowStruct = rmfield(rowStruct, 'eq_id');
end
if isfield(rowStruct, 'config_hash')
rowStruct = rmfield(rowStruct, 'config_hash');
end
else
% No such BER entry exists, insert the new BER entry
berData = struct( ...
'run_id', runID, ...
'eq_id', cur_eq_id, ...
'ber', berValue, ...
'occurrence', occurrence ...
);
obj.appendToTable('BERs', berData);
% Compute MD5 hash from the JSON representation
jsonStr = jsonencode(rowStruct);
md = java.security.MessageDigest.getInstance('MD5');
md.update(uint8(jsonStr));
hashBytes = typecast(md.digest, 'uint8');
hashStr = lower(dec2hex(hashBytes)');
hashStr = lower(strtrim(hashStr(:)'));
% Update the config_hash field using the eq_id from the table row
eq_id = eqParamsRows.eq_id(i);
updateQuery = sprintf('UPDATE EqualizerParameters SET config_hash = ''%s'' WHERE eq_id = %d', hashStr, eq_id);
obj.executeSQL(updateQuery);
end
% Fetch all rows from the Results table using queryDB with no filters
Results = obj.tables.Results;
if isstruct(Results)
newFields = {};
fNames = fieldnames(Results);
for i = 1:numel(fNames)
newFields{end+1} = ['Results.' fNames{i}];
end
Results = newFields;
end
[resultsRows, ~] = obj.queryDB(obj.tables, Results);
for i = 1:height(resultsRows)
rowStruct = table2struct(resultsRows(i, :)); % Convert the row to a struct
% Remove fields not used in the hash calculation
if isfield(rowStruct, 'result_id')
rowStruct = rmfield(rowStruct, 'result_id');
end
if isfield(rowStruct, 'result_hash')
rowStruct = rmfield(rowStruct, 'result_hash');
end
if isfield(rowStruct, 'date_of_processing')
rowStruct = rmfield(rowStruct, 'date_of_processing');
end
% Compute MD5 hash from the JSON representation
jsonStr = jsonencode(rowStruct);
md = java.security.MessageDigest.getInstance('MD5');
md.update(uint8(jsonStr));
hashBytes = typecast(md.digest, 'uint8');
hashStr = lower(dec2hex(hashBytes)');
hashStr = lower(strtrim(hashStr(:)'));
% Access the result_id from the table row and update the hash
result_id = resultsRows.result_id(i);
updateQuery = sprintf('UPDATE Results SET result_hash = ''%s'' WHERE result_id = %d', ...
hashStr, result_id);
obj.executeSQL(updateQuery);
end
end
function executeSQL(obj, query)
% This method executes an SQL statement using MATLAB's execute function.
execute(obj.conn, query);
end
function answer = fetch(obj,query)
answer = fetch(obj.conn,query);
end
@@ -405,15 +487,46 @@ classdef DBHandler < handle
function query = constructSQLQuery(obj, filterParams, selectedFields)
% constructSQLQuery Constructs the SQL query based on filter parameters and selected fields.
%
% If selectedFields is provided as a struct, it is converted to a cell array.
% The conversion takes the field names and creates entries like:
% {'selectedFields.fieldName'} for each field.
% Construct the SELECT clause dynamically based on user selection
% Input check for selectedFields: if it's a struct, convert it to a cell array.
if isstruct(selectedFields)
newFields = {};
tableNames = fieldnames(selectedFields);
for t = 1:numel(tableNames)
tableStruct = selectedFields.(tableNames{t});
fieldNames = fieldnames(tableStruct);
for f = 1:numel(fieldNames)
if isequal(tableStruct.(fieldNames{f}), 1)
newFields{end+1} = sprintf('%s.%s', tableNames{t}, fieldNames{f});
end
end
end
selectedFields = newFields;
end
% Construct the SELECT clause dynamically based on user selection.
% (Assuming that when provided as a cell array, each entry is of the form
% 'TableName.fieldName' or, in our conversion case, 'selectedFields.fieldName'.)
selectClause = 'SELECT DISTINCT ';
for i = 1:numel(selectedFields)
fieldParts = strsplit(selectedFields{i}, '.');
tableName = fieldParts{1};
fieldName = fieldParts{2};
% If the field comes from the struct conversion, its first part is 'selectedFields'
% and the actual field name is in the second part.
if strcmp(fieldParts{1}, 'selectedFields')
tableName = fieldParts{1}; % not used for type checking below
fieldName = fieldParts{2};
else
tableName = fieldParts{1};
fieldName = fieldParts{2};
end
if isnumeric(obj.tables.(tableName).(fieldName))
% Decide on COALESCE depending on the field type.
% If the table is known in obj.tables and the field is numeric, use 'NaN'.
if isfield(obj.tables, tableName) && isfield(obj.tables.(tableName), fieldName) && isnumeric(obj.tables.(tableName).(fieldName))
selectClause = [selectClause, 'COALESCE(', selectedFields{i}, ', ''NaN'') AS ', fieldName];
else
selectClause = [selectClause, 'COALESCE(', selectedFields{i}, ', '''') AS ', fieldName];
@@ -426,235 +539,300 @@ classdef DBHandler < handle
end
end
% Construct the FROM and WHERE clause
baseQuery = [selectClause, 'FROM Runs ' ...
'LEFT JOIN Configurations ON Runs.run_id = Configurations.run_id ' ...
'LEFT JOIN Measurements ON Runs.run_id = Measurements.run_id ' ...
'WHERE '];
% 'LEFT JOIN BERs ON Runs.run_id = BERs.run_id ' ...
% 'LEFT JOIN Equalizer ON BERs.eq_id = Equalizer.eq_id ' ...
% --- 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, ' '];
tableNamesAll = fieldnames(obj.tables);
for t = 1:numel(tableNamesAll)
tableName = tableNamesAll{t};
if strcmpi(tableName, mainTable) || strcmpi(tableName, 'sqlite_sequence')
continue;
end
% Loop through each table in filterParams
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 '];
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 '];
end
end
% --- WHERE Clause Construction ---
baseQuery = [selectClause, ' ', fromClause, 'WHERE '];
filterClauses = [];
tableNames_ = fieldnames(filterParams);
for t = 1:numel(tableNames_)
tableName = tableNames_{t};
tableParams = filterParams.(tableName);
% Loop through each parameter in the table
fieldNames = fieldnames(tableParams);
for i = 1:numel(fieldNames)
fieldName = fieldNames{i};
value = tableParams.(fieldName);
% Construct the full column name in the format "tableName.fieldName"
fullName = sprintf('%s.%s', tableName, fieldName);
% Handle different types of values for SQL query construction
% Handle various types of values for SQL query construction
if isempty(value)
% Skip this parameter if it is empty (include all values)
continue;
elseif isnumeric(value) && isnan(value)
% If value is NaN, use IS NULL in SQL
filterClause = sprintf('%s IS NULL', fullName);
elseif isnumeric(value) && ~isEnumeration(value)
filterClause = sprintf('%s = %f', fullName, value);
elseif islogical(value) || (isnumeric(value) && ismember(value, [0, 1])) && ~isEnumeration(value)
filterClause = sprintf('%s = %d', fullName, value);
elseif ischar(value) || isstring(value)
filterClause = sprintf('%s = ''%s''', fullName, char(value)); %nicht nach string suchen sondern nach chararray -> 'bla' statt "bla"
filterClause = sprintf('%s = ''%s''', fullName, char(value));
elseif isEnumeration(value)
filterClause = sprintf('%s = ''%s''', fullName, value);
else
error('Unsupported data type for field "%s".', fullName);
end
% Add the constructed filter clause to the list
filterClauses = [filterClauses, filterClause, ' AND '];
end
end
% Remove trailing ' AND ' from the filter clauses if any filters were added
% Remove trailing ' AND ' if any filters were added.
if ~isempty(filterClauses)
filterClauses = filterClauses(1:end-5);
end
% Construct the final SQL query
if isempty(filterClauses)
query = [selectClause, 'FROM Runs ' ...
'LEFT JOIN Configurations ON Runs.run_id = Configurations.run_id ' ...
'LEFT JOIN Measurements ON Runs.run_id = Measurements.run_id ' ...
'LEFT JOIN BERs ON Runs.run_id = BERs.run_id'];
query = [selectClause, ' ', fromClause, 'WHERE ', filterClauses];
else
query = [baseQuery, filterClauses];
query = [selectClause, ' ', fromClause];
end
end
function selectedFields = promptSelectFields(obj)
% promptSelectFields Prompts the user to select fields from multiple tables to include in the SELECT statement using settingsdlg.
% promptSelectFields Prompts the user to select fields from multiple tables
% using a custom checkbox GUI with scrolling.
%
% The function builds a list of all fields (formatted as 'TableName.fieldName')
% and displays each as a checkbox inside an inner container panel. The container's
% height is set to accommodate all checkboxes, so the scrollable panel shows scrollbars.
% When the user clicks the "Select" button, the selected fields are returned.
% If none are selected, all fields are returned.
% Get all possible fields from all tables (excluding sqlite_sequence)
% Get all possible tables (excluding sqlite_sequence)
tableNames = fieldnames(obj.tables);
tableNames = setdiff(tableNames, {'sqlite_sequence'}); % Remove sqlite_sequence
% Prepare the inputs for settingsdlg
promptSettings = {};
allFieldsFullName = {};
convertedFieldNames = {};
tableNames = setdiff(tableNames, {'sqlite_sequence'});
% Build a single cell array of all field names with table prefix.
allFields = {};
for i = 1:numel(tableNames)
tableFields = fieldnames(obj.tables.(tableNames{i}));
for j = 1:numel(tableFields)
fieldName = tableFields{j};
fullName = sprintf('%s.%s', tableNames{i}, fieldName);
convertedName = strrep(fullName, '.', '_'); % Replace '.' with '_'
allFieldsFullName{end + 1} = fullName; % Add full name to the list
convertedFieldNames{end + 1} = convertedName; % Store the converted name
% Add the field name and checkbox setting to the prompt
promptSettings{end + 1} = {sprintf('Include %s', fullName), convertedName};
promptSettings{end + 1} = false; % Default: not selected
fields = fieldnames(obj.tables.(tableNames{i}));
for j = 1:numel(fields)
allFields{end+1} = sprintf('%s.%s', tableNames{i}, fields{j});
end
end
numFields = numel(allFields);
% Create the settings dialog
[settings, button] = settingsdlg(...
'title', 'Select Fields for the SQL Query', ...
'description', 'Check the boxes for the fields you want to include in the SELECT statement.', ...
promptSettings{:} ...
);
% Create the main figure.
fig = uifigure('Name', 'Select Fields', 'Position', [100, 100, 400, 600]);
% If the user cancels, default to selecting all fields
if strcmp(button, 'cancel')
selectedFields = allFieldsFullName;
return;
% Create a scrollable panel.
scrollPanel = uipanel(fig, 'Position', [10, 60, 380, 530], 'Scrollable', 'on');
% Define checkbox dimensions.
checkboxHeight = 30;
spacing = 5;
totalHeight = numFields * (checkboxHeight + spacing);
% Create an inner container panel with height larger than the scrollPanel's height.
container = uipanel(scrollPanel, 'Position', [0, 0, scrollPanel.Position(3), totalHeight]);
% Create checkboxes using absolute positioning in the container.
checkboxes = gobjects(numFields, 1);
for i = 1:numFields
% Calculate the vertical position.
% The origin (0,0) is at the bottom left of the container.
yPos = totalHeight - i*(checkboxHeight + spacing) + spacing;
checkboxes(i) = uicheckbox(container, ...
'Text', allFields{i}, ...
'Value', false, ...
'Position', [10, yPos, container.Position(3)-20, checkboxHeight]);
end
% Parse user input into selectedFields
% Create a "Select" button in the main figure.
btn = uibutton(fig, 'Text', 'Select', ...
'Position', [150, 10, 100, 30], ...
'ButtonPushedFcn', @(btn, event) uiresume(fig));
% Wait for the user to click the button.
uiwait(fig);
% Retrieve the selected fields.
selectedFields = {};
for i = 1:numel(allFieldsFullName)
convertedName = convertedFieldNames{i};
if isfield(settings, convertedName) && settings.(convertedName) % Add to selectedFields if the checkbox was selected
selectedFields{end + 1} = allFieldsFullName{i}; %#ok<AGROW>
for i = 1:numFields
if checkboxes(i).Value
selectedFields{end+1} = checkboxes(i).Text;
end
end
% If no fields are selected, default to selecting all fields
% If no fields are selected, default to all fields.
if isempty(selectedFields)
selectedFields = allFieldsFullName;
selectedFields = allFields;
end
% Close the figure.
delete(fig);
end
function filterParams = promptFilterParameters(obj)
% promptFilterParameters Prompts the user to enter filter parameters using the settingsdlg framework.
% promptFilterParameters Prompts the user to enter filter parameters using a
% custom scrollable UI with dropdowns.
%
% For each table (excluding 'sqlite_sequence'), each field that has distinct
% values is displayed as a label and a dropdown. The dropdown items are built
% from the distinct values (with "All" prepended). The output is a struct where,
% for each table, each field is set to the chosen value (or [] if "All" is selected).
% Get all possible parameters from all tables (excluding sqlite_sequence)
tableNames_ = fieldnames(obj.tables);
tableNames_ = setdiff(tableNames_, {'sqlite_sequence'}); % Remove sqlite_sequence
% Get all tables except 'sqlite_sequence'
tableNames = fieldnames(obj.tables);
tableNames = setdiff(tableNames, {'sqlite_sequence'});
% Prepare the inputs for settingsdlg with sections and separators
promptSettings = {};
allFieldsFullName = {};
convertedFieldNames = {};
% Precompute layout constants.
heightPerTableLabel = 30;
heightPerField = 40; % vertical space for a field (label + dropdown)
spacing = 5;
for i = 1:numel(tableNames_)
% Add a separator for each table section
promptSettings{end + 1} = 'separator';
promptSettings{end + 1} = tableNames_{i};
% Get all fields from the current table
tableFields = fieldnames(obj.tables.(tableNames_{i}));
% Prepare each field to be added to the dialog
% Compute total required height.
totalHeight = 0;
for i = 1:numel(tableNames)
totalHeight = totalHeight + heightPerTableLabel;
tableName = tableNames{i};
tableFields = fieldnames(obj.tables.(tableName));
for j = 1:numel(tableFields)
fieldName = tableFields{j};
fullName = sprintf('%s.%s', tableNames_{i}, fieldName);
convertedName = strrep(fullName, '.', '_'); % Replace '.' with '_'
% Skip fields that do not have distinct values stored
if ~isfield(obj.distinctValues.(tableNames_{i}), fieldName)
continue;
% Only include fields that have distinct values stored.
if isfield(obj.distinctValues.(tableName), fieldName)
totalHeight = totalHeight + heightPerField;
end
% Get the distinct values for the field
distinctValues_ = obj.distinctValues.(tableNames_{i}).(fieldName);
% Prepare distinct values for dropdown
if isempty(distinctValues_)
% If there are no distinct values, use only an "All" entry
distinctValues_ = {'All'};
else
% Ensure distinctValues is a cell array of strings
if isnumeric(distinctValues_)
distinctValues_ = arrayfun(@(x) num2str(x), distinctValues_, 'UniformOutput', false);
elseif isstring(distinctValues_)
distinctValues_ = cellstr(distinctValues_);
elseif iscell(distinctValues_) && ~iscellstr(distinctValues_)
distinctValues_ = cellfun(@num2str, distinctValues_, 'UniformOutput', false);
end
% Add an "All" option at the beginning of the distinct values list
distinctValues_ = [{'All'}; distinctValues_];
end
allFieldsFullName{end + 1} = fullName; % Add full name to the list
convertedFieldNames{end + 1} = convertedName; % Store the converted name
% Add the field name and value setting to the prompt
promptSettings{end + 1} = {sprintf('%s', fullName), convertedName};
promptSettings{end + 1} = distinctValues_; % Add distinct values as dropdown options
end
end
% Create the settings dialog
[settings, button] = settingsdlg(...
'title', 'Input Parameters for Filtering', ...
'description', 'Enter the values for each field to filter. Select "All" to include all values.', ...
promptSettings{:} ...
);
% Create the main UI figure.
fig = uifigure('Name', 'Input Parameters for Filtering', 'Position', [100, 100, 500, 600]);
% If the user cancels, return an empty struct
if strcmp(button, 'cancel')
% Set a CloseRequestFcn so that closing the figure calls uiresume.
fig.CloseRequestFcn = @(src, event) uiresume(src);
% Create a scrollable panel inside the figure.
scrollPanel = uipanel(fig, 'Position', [10, 60, 480, 530], 'Scrollable', 'on');
% Create an inner container panel with a height set to totalHeight.
container = uipanel(scrollPanel, 'Position', [0, 0, scrollPanel.Position(3), totalHeight]);
% Prepare cell arrays to store dropdown handles and corresponding table/field names.
dropdownHandles = {};
dropdownTableNames = {};
dropdownFieldNames = {};
% Set the starting Y coordinate (filling from top to bottom).
currentY = totalHeight;
% Maximum number of dropdown items.
maxItems = 100;
for i = 1:numel(tableNames)
% Create a label for the table name.
uilabel(container, ...
'Text', tableNames{i}, ...
'FontWeight', 'bold', ...
'Position', [10, currentY - heightPerTableLabel + spacing, 200, heightPerTableLabel - spacing]);
currentY = currentY - heightPerTableLabel;
tableName = tableNames{i};
tableFields = fieldnames(obj.tables.(tableName));
for j = 1:numel(tableFields)
fieldName = tableFields{j};
if ~isfield(obj.distinctValues.(tableName), fieldName)
continue; % Skip if no distinct values are stored.
end
% Retrieve distinct values for the field.
distinctValues_ = obj.distinctValues.(tableName).(fieldName);
if ~isempty(distinctValues_) && numel(distinctValues_) > maxItems
distinctValues_ = distinctValues_(1:maxItems);
end
if isempty(distinctValues_)
items = {'All'};
else
if isnumeric(distinctValues_)
items = cellfun(@num2str, num2cell(distinctValues_), 'UniformOutput', false);
elseif isstring(distinctValues_)
items = cellstr(distinctValues_);
elseif iscell(distinctValues_) && ~iscellstr(distinctValues_)
items = cellfun(@num2str, distinctValues_, 'UniformOutput', false);
else
items = distinctValues_;
end
items = items(:)'; % Ensure row vector
items = [{'All'}, items];
end
% Create a label for the field.
uilabel(container, ...
'Text', sprintf('%s:', fieldName), ...
'HorizontalAlignment', 'right', ...
'Position', [10, currentY - 25, 150, 25]);
% Create a dropdown for the field.
dd = uidropdown(container, ...
'Items', items, ...
'Value', 'All', ...
'Position', [170, currentY - 25, 200, 25]);
% Store the dropdown handle and its associated table/field.
dropdownHandles{end+1} = dd;
dropdownTableNames{end+1} = tableName;
dropdownFieldNames{end+1} = fieldName;
currentY = currentY - heightPerField;
end
end
% Create a "Submit" button at the bottom of the figure.
btn = uibutton(fig, 'Text', 'Submit', ...
'Position', [200, 10, 100, 30], ...
'ButtonPushedFcn', @(btn, event) uiresume(fig));
% Wait until the user clicks "Submit" or closes the figure.
uiwait(fig);
% If the figure was closed (and thus no longer valid), return an empty struct.
if ~isvalid(fig)
filterParams = struct();
return;
end
% Parse user input into filterParams structure
% Build the filterParams struct from the dropdown selections.
filterParams = struct();
for i = 1:numel(allFieldsFullName)
value = settings.(convertedFieldNames{i});
% Split full name to get table and field names
fieldParts = strsplit(allFieldsFullName{i}, '.');
tableName = fieldParts{1};
fieldName = fieldParts{2};
% If the table does not exist in the filterParams struct, create it
for k = 1:numel(dropdownHandles)
tableName = dropdownTableNames{k};
fieldName = dropdownFieldNames{k};
value = dropdownHandles{k}.Value;
if ~isfield(filterParams, tableName)
filterParams.(tableName) = struct();
end
% Assign values to the respective fields under each table
% If "All" is selected, assign empty; otherwise, try converting to numeric.
if strcmp(value, 'All')
filterParams.(tableName).(fieldName) = []; % Set to empty to include all values
elseif isnumeric(value) && isnan(value)
filterParams.(tableName).(fieldName) = NaN; % Use NaN to handle as NULL
filterParams.(tableName).(fieldName) = [];
else
filterParams.(tableName).(fieldName) = value; % Use the entered value
numValue = str2double(value);
if ~isnan(numValue)
filterParams.(tableName).(fieldName) = numValue;
else
filterParams.(tableName).(fieldName) = value;
end
end
end
% Close the figure.
delete(fig);
end
end
end

180
Classes/Moveit_wrapper.m Normal file
View File

@@ -0,0 +1,180 @@
classdef Moveit_wrapper < handle
%
properties(Access=public)
moveit_function_name
para
state = struct()
comment
end
methods (Access=public)
function obj = Moveit_wrapper(moveit_function_name,options)
%
arguments
moveit_function_name
options.para
end
obj.moveit_function_name = moveit_function_name;
fn = fieldnames(options);
for n = 1:numel(fn)
try
obj.(fn{n}) = options.(fn{n});
end
end
% Ensure the function exists
if ~exist(obj.moveit_function_name, 'file')
error('Function "%s" does not exist.', obj.moveit_function_name);
end
% Step 1: Get default parameters by calling moveit module
if isempty(obj.para)
global loop;
loop = 0; % Request parameter structure
[obj.para, obj.comment] = feval(obj.moveit_function_name);
end
end
function signal_out = process(obj,signal_in)
arguments
obj
signal_in = []
end
isSignalClass = 0;
if isa(signal_in,"Signal")
signal_out = signal_in;
signal_in = signal_in.signal;
isSignalClass = 1;
end
% signal_in = signal_in.';
% INIT MOVEIT
global loop;
loop = 0;
signal_out = obj.moveit_init(signal_in);
% RUN MOVEIT
global loop;
loop = 1;
signal_out = obj.moveit_init(signal_out);
if isSignalClass
% append to logbook
lbdesc = ['Logbookentry'];
signal_out = signal_out.logbookentry(lbdesc);
signal_out.signal = signal_out;
end
end
function open_settings(obj)
% Opens a settings dialog for modifying Moveit parameters with appropriate input types.
% Inserts separators when the level value changes.
fieldNames = fieldnames(obj.para);
settingsCell = {};
previousLevel = -inf; % Track previous level for separators
% Create input arguments for settingsdlg
for i = 1:numel(fieldNames)
fieldName = fieldNames{i};
value = obj.para.(fieldName);
% Get description from comment structure if available
if isfield(obj.comment, fieldName)
description = obj.comment.(fieldName);
else
description = fieldName; % Default to field name if no description
end
% Get level for this parameter
if isfield(obj.comment.level, fieldName)
currentLevel = obj.comment.level.(fieldName);
else
currentLevel = 1; % Default level
end
% Insert separator if the level changes
if currentLevel ~= previousLevel
settingsCell{end+1} = 'separator';
settingsCell{end+1} = ['Level ', num2str(currentLevel)];
end
previousLevel = currentLevel;
% Determine input type from obj.comment.type
if 1
inputType = obj.comment.type.(fieldName);
else
inputType = 'number'; % Default type
end
% Add field description
settingsCell{end+1} = {description; fieldName};
% Define the input type
if strcmp(inputType, 'boolean')
% Checkbox input
settingsCell{end+1} = logical(value); % Enable checkbox
elseif contains(inputType, '|')
% Dropdown selection (options separated by '|')
dropdownOptions = strsplit(inputType, '|');
settingsCell{end+1} = dropdownOptions;
else
% Default: Numeric input
settingsCell{end+1} = value;
end
end
% Open settings dialog
[newValues, button] = settingsdlg(...
'title', ['Settings: ', obj.moveit_function_name], ...
'description', ['Adjust parameters for ', obj.moveit_function_name], ...
settingsCell{:} ...
);
% Update obj.para with new values only if "OK" was pressed
if strcmp(button, 'OK')
fieldNames = fieldnames(newValues);
for i = 1:numel(fieldNames)
if fieldNames{i}
end
obj.para.(fieldNames{i}) = newValues.(fieldNames{i});
end
end
end
end
methods (Access=private)
function data_out = moveit_init(obj,data_in)
arguments(Input)
obj
data_in double
end
% Step 2: Initialize the function
[data_out, obj.state] = feval(obj.moveit_function_name, data_in, obj.state, obj.para);
end
function data_out = moveit_simulation_computation(obj,data_in)
arguments(Input)
obj
data_in double
end
% Step 3: Process input signal
[data_out, obj.state] = feval(obj.moveit_function_name, data_in, obj.state, obj.para);
end
end
end

2
Classes/Warehouse_class/classes/DataStorage.m
View File

@@ -89,7 +89,7 @@ classdef DataStorage < handle
for p = 1:numel(obj.fn)
name = obj.fn(p);
values = obj.inputParams.(name);
obj.parameter.(name) = Parameter(name,values);
obj.parameter.(name) = StorageParameter(name,values);
end
end

4
Classes/Warehouse_class/classes/Parameter.m → Classes/Warehouse_class/classes/StorageParameter.m
View File

@@ -1,4 +1,4 @@
classdef Parameter < handle
classdef StorageParameter < handle
%PARAMETER Summary of this class goes here
% Detailed explanation goes here
@@ -12,7 +12,7 @@ classdef Parameter < handle
end
methods
function obj = Parameter(name, values)
function obj = StorageParameter(name, values)
%PARAMETER Construct
obj.name = name;
obj.values = values;