% function  [ber] = imdd_labdata_example(varargin)
    
% TX 
    M               = 4;
    fsym            = 224e9;
    f_nyquist       = fsym/2;
    apply_pulsef    = 0;
    fdac            = 2*fsym;%256e9;
    fadc            = 2*fsym;%256e9;
    fdac            = 256e9;
    fadc            = 256e9;
    random_key      = 1;
    db_precode      = 1;
    db_encode       = 0;
    rcalpha         = 0.05;
    kover           = 16;
    vbias_rel       = 0.5;
    u_pi            = 2.9;
    vbias           = -vbias_rel*u_pi;
    laser_wavelength    = 1293;
    laser_linewidth     = 0;
    tx_bw_nyquist   = 1.5;

% Channel
    link_length     = 0;

% RX
    rop = -7.5;
    rx_bw_nyquist = 1.5;

% EQ
    eq_mode = equalizer_structure.vnle_pf_mlse;
    ffe_order=[50,0,0];
    vnle_order=[50,7,7];
    dfe_order = [0 0 0];

    len_tr = 4096*2;
    mu_ffe = [0.0004 0.0004 0.0004];
    mu_dfe = 0.0004;
    mu_dc = 0.05;

    dfe_ = sum(dfe_order)>0;

    % 
    % % Parse optional input arguments
    % if ~isempty(varargin)
    %     var_s = varargin{1};
    %     if isstruct(var_s)
    %         fields = fieldnames(var_s);
    %         for i = 1:numel(fields)
    %             eval([fields{i}, ' = ',  num2str( var_s.(fields{i}) ), ';']);
    %             fprintf("%s <-- %.2f \n", fields{i}, var_s.(fields{i}));
    %         end
    %     else
    %         error('Optional variables should be passed as a struct.');
    %     end
    % end

    basePath = 'C:\Users\Silas\Documents\MATLAB\Datensätze\sioe_labor\';
    useGui = 0;
    db = DBHandler("pathToDB",[basePath,'silas_labor.db']);
    filterParams = db.tables;
    % filterParams.Runs.run_id = 2958; % no db
    % filterParams.Runs.run_id = 2937; % no db
        filterParams.Configurations = struct( ...
        'bitrate',          300e9, ...
        'db_mode',          0, ...
        'fiber_length',     1, ...
        'interference_attenuation', [], ...
        'interference_path_length', [], ...
        'is_mpi',           0, ...
        'pam_level',        4, ...
        'precomp_amp',      [], ...
        'rop_attenuation',  0, ...
        'symbolrate',       [], ...
        'v_awg',            [], ...
        'v_bias',           [], ...
        'wavelength',       1310 ...
        );
    selectedFields = {'Runs.run_id','Runs.tx_bits_path', 'Runs.tx_symbols_path', 'Runs.rx_sync_path','Runs.rx_raw_path',...
        'Configurations.db_mode','Configurations.pam_level','Configurations.bitrate','Configurations.fiber_length','Configurations.wavelength','Configurations.precomp_amp','BERs.ber'};

    [dataTable,sql_query] = db.queryDB(filterParams, selectedFields);
    [~, uniqueIdx] = unique(dataTable.run_id);  % Get unique run_id indices
    dataTable = dataTable(uniqueIdx,:);  % Extract unique configurations for each run_id
    fprintf('Found %d entries for requested Configuration. IDs are: %s \n \n',size(dataTable,1),jsonencode(dataTable.run_id(1:min(size(dataTable,1),100))));

    tx_bits     = load([basePath, char(dataTable.tx_bits_path(1))]);
    tx_bits     = tx_bits.Bits;
    tx_symbols  = load([basePath, char(dataTable.tx_symbols_path(1))]);
    tx_symbols  = tx_symbols.Symbols;
    
    rx_sync     = load([basePath, char(dataTable.rx_sync_path(1))]);
    rx_sync     = rx_sync.S;

    fsym = tx_symbols.fs;
    
    %%%%%% Sample to 2x fsym %%%%%%
    Scpe_sig =  rx_sync{1}.resample("fs_in",rx_sync{1}.fs,"fs_out",2*fsym);

    %%%%%% Sync Rx signal with reference %%%%%%
    [Scpe_sig,S] = Scpe_sig.tsynch("reference",tx_symbols,"fs_ref",fsym);

    Scpe_sig.spectrum("displayname",'Rx (Scpe+Sync+Resample)','fignum',100,'normalizeTo0dB',0);
    
    Scpe_sig = Filter('filtdegree',4,"f_cutoff",tx_symbols.fs.*0.6,"fs",Scpe_sig.fs,"filterType",filtertypes.gaussian,"active",true).process(Scpe_sig);

    Scpe_sig.spectrum("displayname",'Rx (Scpe+Sync+Resample+LPF)','fignum',100,'normalizeTo0dB',0);

    %%% EQUALIZING
    ber = struct();
    switch eq_mode

        case equalizer_structure.ffe

            %FFE
            if db_precode
                Bits_ = PAMmapper(M,0).demap(Symbols);
            else
                Bits_ = Bits;
            end

            eq_ffe = EQ("Ne",ffe_order,"Nb",dfe_order,"training_length",len_tr,"training_loops",5,"dd_loops",5,"K",2,"DCmu",mu_dc,"DDmu",[mu_ffe mu_dfe],"DFEmu",0.005,"FFEmu",0,"plotfinal",0,"ideal_dfe",1);
            eq_ffe     = FFE("epochs_tr",5,"epochs_dd",5,"len_tr",len_tr,"mu_dd",mu_ffe(1),"mu_tr",0,"order",ffe_order(1),"sps",2,"decide",0);
            eq_ffe     = FFE_DCremoval("epochs_tr",5,"epochs_dd",5,"len_tr",len_tr,"mu_dd",mu_ffe(1),"mu_tr",0,"order",ffe_order(1),"sps",2,"decide",0,"dc_buffer_len",512,"mu_dc",0.05);

            [eq_sig,eq_noise,ber.ber_ffe,totalErrors] = vnle( eq_ffe,M,Scpe_sig ,Symbols, Bits_);
            eq_noise.spectrum("displayname",'Noise Spectrum after FFE','fignum',41,'normalizeTo0dB',0);

        case equalizer_structure.vnle
            %VNLE
            eq_vnle = EQ("Ne",vnle_order,"Nb",dfe_order,"training_length",len_tr,"training_loops",5,"dd_loops",5,"K",2,"DCmu",mu_dc,"DDmu",[mu_ffe mu_dfe],"DFEmu",0.005,"FFEmu",0,"plotfinal",0,"ideal_dfe",1);
            [eq_sig,eq_noise,ber.ber_vnle,totalErrors] = vnle(eq_vnle,M,Scpe_sig ,Symbols, Bits_);
            eq_noise.spectrum("displayname",'Noise Spectrum after VNLE','fignum',41,'normalizeTo0dB',0);
        case equalizer_structure.vnle_pf_mlse

            %VNLE + PF + MLSE
            eq_mlse     = EQ("Ne",vnle_order,"Nb",dfe_order,"training_length",len_tr,"training_loops",5,"dd_loops",5,"K",2,"DCmu",mu_dc,"DDmu",[mu_ffe mu_dfe],"DFEmu",0.005,"FFEmu",0,"plotfinal",0,"ideal_dfe",1);
            pf_         = Postfilter("ncoeff",1);
            mlse_       = MLSE("DIR",[0,0],"duobinary_output",0,"M",[],"trellis_states",[]);
            [eq_sig,eq_noise,ber.ber_mlse,totalErrors] = vnle_postfilter_mlse(eq_mlse , pf_, mlse_,M, Scpe_sig ,Symbols, Bits_);
            pf_.showFilter(eq_noise);

            eq_noise.spectrum("displayname",'Noise Spectrum after VNLE+PF','fignum',41,'normalizeTo0dB',0);

        case equalizer_structure.db_precoded

            %EQ targets DB => less precompensation; pre-coded
            mlse_db_pre = MLSE("DIR",[1,1],"duobinary_output",1,"M",M,"trellis_states",PAMmapper(M,0).levels);
            eq_db_pre = EQ("Ne",vnle_order,"Nb",dfe_order,"training_length",len_tr,"training_loops",5,"dd_loops",5,"K",2,"DCmu",mu_dc,"DDmu",[mu_ffe mu_dfe],"DFEmu",0.005,"FFEmu",0,"plotfinal",0,"ideal_dfe",1);
            [eq_sig,eq_noise,ber.ber_db,totalErrors] = duobinary_target(eq_db_pre, mlse_db_pre,M, Scpe_sig ,Symbols, Bits);
            eq_noise.spectrum("displayname",'Noise Spectrum after DB','fignum',41,'normalizeTo0dB',0);
            %->append BER to DB

        case equalizer_structure.db_encoded

            %db signaling => db encoded
            mlse_db_enc = MLSE("DIR",[1,1],"duobinary_output",1,"M",M,"trellis_states",PAMmapper(M,0).levels);
            eq_db_enc = EQ("Ne",vnle_order,"Nb",dfe_order,"training_length",len_tr,"training_loops",5,"dd_loops",5,"K",2,"DCmu",mu_dc,"DDmu",[mu_ffe mu_dfe],"DFEmu",0.005,"FFEmu",0,"plotfinal",0,"ideal_dfe",1);
            [eq_sig,eq_noise,ber.ber_db_enc,totalErrors] = duobinary_signaling(eq_db_enc, mlse_db_enc,M, Scpe_sig ,Symbols, Bits);
            %->append BER to DB
    end

    fprintf('BER FFE: %.2e \n',ber.ber_mlse);
    % % El_sig.spectrum("displayname",'Tx Spectrum','fignum',10,'normalizeTo0dB',1);
    % Scpe_sig.spectrum("displayname",'Rx Spectrum','fignum',100,'normalizeTo0dB',1);
    
    
    
    

% end