% Get the script folder
scriptFolder = fileparts(mfilename('fullpath'));

% Find the HDF5 file in the folder
files = dir(fullfile(scriptFolder, '*.h5'));
if isempty(files)
    error('No HDF5 files found in the script folder.');
end

% Select the first matching file (modify as needed)
filename = files(6).name;
% filename = 'Pmod_8p0023dBm_P_PD_6p4776dBm_W03C34-0409E03_64GBd_2PAM__20250218T181323.h5';

% Extract parameters from the filename using an updated regex
tokens = regexp(filename, 'Pmod_([-0-9p]+)dBm_P_PD_([-0-9p]+)dBm_.*?_(\d+)GBd_(\d+)PAM__\d+T\d+', 'tokens');
if isempty(tokens)
    error('Filename format not recognized.');
end

tokens = tokens{1};

% Convert values
P_laser = str2double(strrep(tokens{1}, 'p', '.'));
P_pd = str2double(strrep(tokens{2}, 'p', '.'));
fsym = str2double(tokens{3}) * 1e9; % Convert GBd to Hz
M = str2double(tokens{4});

% Display results
fprintf('Loaded file: %s\n', filename);
fprintf('P_laser: %.3f dBm\n', P_laser);
fprintf('P_pd: %.3f dBm\n', P_pd);
fprintf('fsym: %.3f Hz\n', fsym);
fprintf('M: %d\n', M);

%%% Load Data
folder = "/Users/silasoettinghaus/Documents/MATLAB/imdd_simulation/projects/Messung_Zürich";

filepath = fullfile(folder,filename);
ief_ = h5info(filepath);

fs_rx = h5readatt(filepath,'/','fs'); %sampling frequency at Rx
fs_tx = h5readatt(filepath, '/','fs_Tx'); %sampling frequency at Tx
fsym = h5readatt(filepath, '/','R'); %Baudrate
M = h5readatt(filepath, '/','M'); % PAM- 'M'
ROF = h5readatt(filepath, '/','ROF');
PulseShape =h5readatt(filepath, '/','PulseShape');

yOrg = h5readatt(filepath, ief_.Groups(4).Groups(1).Name, 'YOrg');
yInc = h5readatt(filepath, ief_.Groups(4).Groups(1).Name, 'YInc');

plotDisplayName = sprintf('P_{cw} = %.3f dBm, P_{PD} = %.3f dBm, f_{sym} = %.3f GBd, M = %d', ...
                    P_laser, P_pd, fsym / 1e9, M);

dataRx = double(h5read(filepath, '/Waveforms/Channel 2/Channel 2Data')); % rohdaten des CH4
bitsTx = h5read(filepath, '/Settings/dataTx'); %Binär
bitsTx = reshape(bitsTx,log2(M),[])';


%%% Build Tx Signal (Bits, Pam Map, Symbols)
Tx_bits = Informationsignal(bitsTx);
Tx_symbols = PAMmapper(M,0,"eth_style",1).map(Tx_bits);
Tx_symbols.fs = fsym;
% Tx_symbols.plot("fignum",1,"displayname",'Rx Signal');
% Tx_symbols.move_it_spectrum("fignum",2,"displayname",'tx spectrum');
% Tx_symbols.spectrum("fignum",3,"displayname",'Rx Signal','normalizeTo0dB',0);


%%% Build Rx Signal (Rx, normalize,remove mean)
dataRx = dataRx*yInc+yOrg;
Rx_Sig = Informationsignal(dataRx,"fs",fs_rx);
Rx_Sig = Rx_Sig.normalize("mode","rms");
% Rx_Sig.power();
% Rx_Sig.eye(fsym,M,"fignum",4,"displayname",'eye diagram');
% Rx_Sig.plot("fignum",5,"displayname",'Rx Signal');
% Rx_Sig.move_it_spectrum("fignum",6,"displayname",'tx spectrum');
Rx_Sig.spectrum("fignum",3,"displayname",'Rx Signal','normalizeTo0dB',0);

%%%%%% Sample to 2x fsym %%%%%%
Rx_Sig_resamp = Rx_Sig.resample("fs_out",2*fsym);

%%%%%% Sync Rx signal with reference (S is a cell array with all occurences) %%%%%%
[Rx_Sig_sync,S,isFlipped] = Rx_Sig_resamp.tsynch("reference",Tx_symbols,"fs_ref",fsym,"debug_plots",0);

eq_vnle_dfe     = EQ("Ne",[50,7,7],"Nb",[0,0,0],"training_length",4096*2,"training_loops",5,"dd_loops",5,"K",2,"DCmu",0.05,"DDmu",[0.0004 0.0004 0.0004 0.0004 ],"DFEmu",0.005,"FFEmu",0,"plotfinal",1,"ideal_dfe",0);

[result] = vnle(eq_vnle_dfe,M,Rx_Sig_sync,Tx_symbols,Tx_bits,"precode_mode",db_mode.no_db,"showAnalysis",1,'eth_style',1);