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Changes from mwork PC.

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PDP 2025

MPI analysis

new focus on database and SQL
This commit is contained in:
Silas Oettinghaus
2025-03-21 08:11:40 +01:00
parent 402e491506
commit 74066d0669
36 changed files with 2234 additions and 620 deletions
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19
Classes/00_signals/Signal.m
View File

@@ -656,7 +656,7 @@ 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
@@ -664,6 +664,14 @@ classdef Signal
options.fs_ref = 0;
options.debug_plots = 0;
end
S = {};
isFlipped=0;
sequenceFound = 0;
%normalize the signal
a = obj.normalize("mode","oneone").signal;
@@ -681,7 +689,11 @@ 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');
[pks,pkpos,w,p] = findpeaks(abs(co./max(co)),'MinPeakDistance',length(b)/2,'MinPeakHeight',0.2,'NPeaks',maxpeaknum,'SortStr','descend');
if mean(w) > 10 || mean(p) > 10
return
end
if options.debug_plots
figure()
@@ -692,9 +704,6 @@ classdef Signal
shifts = shifts(shifts>=0);
S = {};
isFlipped=0;
if numel(shifts) > 0
%Cut occurences of ref signal from signal (only positive shifts)

215
Classes/01_transmit/PAMmapper.m
View File

@@ -24,7 +24,7 @@ classdef PAMmapper
obj.M = M;
obj.unipolar = unipolar;
obj.thresholds = obj.get_demodulation_thresholds();
obj.levels = obj.get_levels();
@@ -36,10 +36,10 @@ classdef PAMmapper
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);
@@ -47,19 +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'];
@@ -68,7 +68,7 @@ classdef PAMmapper
signal_in.signal = signal_out;
signal_out = signal_in;
end
end
function pam_sig = map_(obj,bitpattern)
@@ -89,7 +89,7 @@ classdef PAMmapper
% 4-ASK:
if ~obj.eth_style
pam_sig=2*bitpattern(:,1)+(bitpattern(:,1)==bitpattern(:,2));
if obj.unipolar==0
pam_sig=2*pam_sig-3;
end
@@ -100,15 +100,65 @@ classdef PAMmapper
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);
@@ -120,9 +170,9 @@ classdef PAMmapper
x1 = bitpattern(:,1);
x2 = (bitpattern(:,1)==bitpattern(:,3));
x3 = x2~=bitpattern(:,2);
pam_sig = 4*x1 + 2*x2 + x3;
if obj.unipolar==0
pam_sig=2*pam_sig-7;
end
@@ -133,7 +183,7 @@ classdef PAMmapper
end
pam_sig = pam_sig/sqrt(21);
case 16
% 16-ASK:
x1 = bitpattern(:,1);
@@ -167,7 +217,7 @@ classdef PAMmapper
% case 16
% thres = [-10 -8 -6 -4 -2 0 2 4 6 8 10];
% end
switch obj.M
@@ -190,12 +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
@@ -203,7 +253,7 @@ classdef PAMmapper
elseif obj.unipolar==1
thres=0.5:6.5;
end
thres=thres./sqrt(21);
case 16
@@ -234,23 +284,26 @@ 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
@@ -273,34 +326,70 @@ classdef PAMmapper
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
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)];
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
@@ -324,21 +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)
@@ -347,7 +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);
@@ -358,7 +447,7 @@ classdef PAMmapper
end
function [Signal_out] = quantize(obj,Signal_in)
constellation = obj.get_levels();
constellation = constellation ./ rms(constellation);
@@ -366,9 +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));
@@ -381,7 +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
@@ -390,6 +479,10 @@ classdef PAMmapper
end
function bitmap = showBitMapping(obj)
bitmap = obj.demap([obj.levels ./ obj.scaling]');
end
end
end

43
Classes/01_transmit/Pulseformer.m
View File

@@ -6,8 +6,10 @@ classdef Pulseformer
end
properties(Access=public)
fdac
fs
fsym
matched_sps
output_sps
pulse
pulselength
alpha
@@ -20,8 +22,10 @@ classdef Pulseformer
% Detailed explanation goes here
arguments
options.fdac double
options.fs 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
@@ -50,7 +54,11 @@ classdef Pulseformer
signalclass_in = signalclass_in.logbookentry(lbdesc);
% write fs to signal
signalclass_in.fs = obj.fdac;%.* (obj.fdac./obj.fsym);
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;
@@ -77,15 +85,19 @@ 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;
sps = obj.fs / obj.fsym;
p = sps;
q = 1;
else
%ist kein Vielfaches
p = obj.fsym / gcd(obj.fdac, obj.fsym); %upsampling p->->->
q = obj.fdac/ gcd(obj.fdac, obj.fsym); %downsampling <-q
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
@@ -105,6 +117,7 @@ classdef Pulseformer
end
manual_cyclic_convolution = 0;
upsample_filter = 0;
upfirdn_convolution = 1;
if manual_cyclic_convolution
@@ -122,16 +135,28 @@ 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.fdac,obj.fsym)
if rem(obj.fs,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

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

4
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;

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));

23
Classes/04_DSP/TransmissionPerformance.m
View File

@@ -70,7 +70,7 @@ classdef TransmissionPerformance
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+0.15)]; %Stefano im Meeting
CODE_RATE_O_FEC = [1/(1+0.153)]; %Stefano im Meeting
BERTHRESHOLDS_O_FEC = 2e-2;
@@ -162,6 +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.
@@ -215,6 +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

616
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 +539,302 @@ 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

23
Classes/Moveit_wrapper.m
View File

@@ -39,17 +39,22 @@ classdef Moveit_wrapper < handle
end
function signalclass_out = process(obj,signal_in)
function signal_out = process(obj,signal_in)
arguments
obj
signal_in = []
end
isSignalClass = 0;
if isa(signal_in,"Signal")
signalclass_out = signal_in;
signal_out = signal_in;
signal_in = signal_in.signal;
isSignalClass = 1;
end
input_len = length(signal_in);
signal_in = signal_in.';
% signal_in = signal_in.';
% INIT MOVEIT
global loop;
@@ -59,18 +64,14 @@ classdef Moveit_wrapper < handle
% RUN MOVEIT
global loop;
loop = 1;
signal_out = obj.moveit_init(signal_out);
% CHECK IF SIGNAL CHANGED
if input_len ~= length(signal_out)
warning(['Signal length changed in moveit function: ', obj.moveit_function_name]);
end
signal_out = obj.moveit_init(signal_out);
if isSignalClass
% append to logbook
lbdesc = ['Logbookentry'];
signalclass_out = signalclass_out.logbookentry(lbdesc);
signalclass_out.signal = signal_out;
signal_out = signal_out.logbookentry(lbdesc);
signal_out.signal = signal_out;
end
end