function output = mpi_recipe_dev(Scpe_sig_raw, Symbols, Tx_bits, options)
%mpi_recipe_dev Minimal example recipe for the DSP job framework.
%   This recipe intentionally performs only light preprocessing and records
%   summary values. It demonstrates the recipe interface without running a
%   full equalizer chain.

    arguments
        Scpe_sig_raw
        Symbols
        Tx_bits
        options.fsym
        options.M
        options.duob_mode
        options.dataTable table
        options.userParameters struct = struct()
        options.debug_plots (1,1) logical = false
    end

    Scpe_sig = preprocessSignal(Scpe_sig_raw, Symbols, options.fsym, ...
        "mode", "auto", ...
        "debug_plots", options.debug_plots);
    
   
    eq_settings = { ...
        "epochs_tr", 5, ...
        "epochs_dd", 5, ...
        "len_tr", 4096, ...
        "mu_tr",0.04, ...
        "mu_dd",0.012, ...
        "mu_dc", 0.012, ...
        "adaptive_dc_enabled", 0, ...
        "order", 25, ...
        "sps", 2, ...
        "decide", 0, ...
        "optmize_mus", 0, ...
        "dd_mode", 1, ...
        "adaption_technique", "nlms", ...
        "plot_mu_optimization", options.debug_plots,...
        "save_debug",true};

    eq_ffe = FFE(eq_settings{:});
    
    showLevelScatter(Scpe_sig_raw, Symbols, ...
        "fsym", options.fsym, ...
        "fignum", 400, ...
        "normalize", true);

    % Scpe_sig_raw.spectrum("normalizeTo0dB",1,"fft_length",4096*4,"fignum",401);

    %options.dataTable.sir;

    %% NORMAL FFE
    if  1

        [ffe_results,equalized_signal] = ffe(eq_ffe, options.M, Scpe_sig, Symbols, Tx_bits, ...
            "precode_mode", options.duob_mode, ...
            'showAnalysis', options.debug_plots, ...
            "postFFE", [], ...
            "eth_style_symbol_mapping", 0);
        
        ffe_results.metrics.print("description",sprintf('Normal FFE; SIR %d dB',options.dataTable.sir));
        output.ffe_package = ffe_results;

        [~, avg_for_lvl] = showLevelScatter(equalized_signal, Symbols, ...
            "fsym", options.fsym, ...
            "fignum", 401, ...
            "normalize", true);

        output.ffe_debug = struct();
        dbg = eq_ffe.debug_struct;



        smooth_len = 501;
        output.ffe_debug.smoothing_window = smooth_len;
        error_first_s = movmean(dbg.error_first_epoch(:),smooth_len,"omitnan");
        error_last_s = movmean(dbg.error(:),smooth_len,"omitnan");
        mu_dc_eff_s = movmean(dbg.mu_dc_eff(:),smooth_len,"omitnan");
        e_dc_eff_s = movmean(dbg.e_dc_eff(:),smooth_len,"omitnan");

        figure(460); clf;
        tiledlayout(2,1,"TileSpacing","compact","Padding","compact");

        nexttile;
        semilogy(error_first_s + eps,"DisplayName","first epoch");
        hold on;
        semilogy(error_last_s + eps,"DisplayName","last epoch");
        grid on;
        ylabel("error");
        title("FFE debug error");
        legend("Location","best");

        nexttile;hold on
        % plot(eq_sig_mov,"DisplayName","err dc eff");
        plot(mu_dc_eff_s,"DisplayName","mu DC - either fixed or adaptive");
        e_dc_scale = max(abs(e_dc_eff_s),[],"omitnan") + eps;
        plot(-1.*e_dc_eff_s./e_dc_scale,"DisplayName","Inverted DC-tracking; Value that is subtracted during EQ");
        avg_lvl_dc=mean(avg_for_lvl,1,"omitnan");
        plot(avg_lvl_dc./0.01,"DisplayName","Smoothed EQ output signal; calc'd by showLevelScatter");
        grid on;
        xlabel("Symbol");
        ylabel("mu dc eff");
        title("Effective adaptive DC step");
        legend

        inv_dc_track = -e_dc_eff_s(:);
        avg_lvl_dc = avg_lvl_dc(:);
        xcorr_len = min(numel(inv_dc_track),numel(avg_lvl_dc));
        inv_dc_xcorr = inv_dc_track(1:xcorr_len);
        avg_lvl_xcorr = avg_lvl_dc(1:xcorr_len);
        inv_dc_xcorr = fillmissing(inv_dc_xcorr,"linear","EndValues","nearest");
        avg_lvl_xcorr = fillmissing(avg_lvl_xcorr,"linear","EndValues","nearest");
        inv_dc_xcorr = inv_dc_xcorr - mean(inv_dc_xcorr,"omitnan");
        avg_lvl_xcorr = avg_lvl_xcorr - mean(avg_lvl_xcorr,"omitnan");
        [dc_level_xcorr,dc_level_lags] = xcorr(inv_dc_xcorr,avg_lvl_xcorr,"coeff");
        [dc_level_corr,dc_level_idx] = max(dc_level_xcorr);
        dc_level_delay_symbols = dc_level_lags(dc_level_idx);
        output.ffe_debug.dc_level_delay_symbols = dc_level_delay_symbols;
        output.ffe_debug.dc_level_delay_corr = dc_level_corr;
        output.ffe_debug.dc_level_lags = dc_level_lags;
        output.ffe_debug.dc_level_xcorr = dc_level_xcorr;
        fprintf("FFE debug: xcorr(inv DC tracking, avg level) delay=%d symbols, corr=%6.3f\n", ...
            dc_level_delay_symbols,dc_level_corr);

        figure(461); clf;
        plot(dc_level_lags,dc_level_xcorr,"DisplayName","xcorr");
        hold on;
        plot(dc_level_delay_symbols,dc_level_corr,"ro","DisplayName","max");
        grid on;
        xlabel("Lag in symbols");
        ylabel("Correlation coefficient");
        title(sprintf("Delay estimate: %d symbols (corr %.3f)",dc_level_delay_symbols,dc_level_corr));
        legend("Location","best");


    end




    
    %% MPI Reduction 
    if 1

        % dc_buffer_len = 0;
        % ffe_buffer_len = 0;
        % smoothing_buffer_length = options.userParameters.smoothing_length;
        % smoothing_buffer_update = 1;
        
        % eq_ffe_dcr = FFE_DCremoval_adaptive_mu(eq_settings{:}, ...
        %     "dc_buffer_len",dc_buffer_len, ...
        %     "ffe_buffer_len",ffe_buffer_len,...
        %     "smoothing_buffer_length",smoothing_buffer_length,...
        %     "smoothing_buffer_update",smoothing_buffer_update);

        eq_ = FFE_DCremoval("epochs_tr",5,"epochs_dd",3,"len_tr",4096*2,"mu_dd",...
            0.0002,"mu_tr",0,"order",25,"sps",2,"decide",0,...
            "mu_dc",0.005,"dc_buffer_len",1);
        
        ffe_results_dcr = ffe(eq_, options.M, Scpe_sig, Symbols, Tx_bits, ...
            "precode_mode", options.duob_mode, ...
            'showAnalysis', options.debug_plots, ...
            "postFFE", [], ...
            "eth_style_symbol_mapping", 0);
        
        ffe_results_dcr.metrics.print("description",'FFE DCR');
        output.ffe_dcr_package = ffe_results_dcr;
    end
end