imdd_silas/projects/Diss/MPI_revisit/investigate_mpi_algorithms.m

% === DSP settings ===
dsp_options = struct();
dsp_options.mode = "run_id";
dsp_options.recipe = @mpi_recipe_dev;
dsp_options.append_to_db = false;
dsp_options.start_occurence = 5;
dsp_options.max_occurences = 1;
dsp_options.debug_plots = false;

write_mpi_reduction_db = 0;
stream_mpi_reduction_db = write_mpi_reduction_db;
mpi_reduction_study_name = "pam6_8_sweep";
mpi_reduction_writer_path = fullfile(fileparts(mfilename('fullpath')),"db");
addpath(mpi_reduction_writer_path);

dsp_options.database_type = "mysql"; 

dsp_options.dataBase = "labor";


if ismac
    dsp_options.storage_path = "/Volumes/media/labdata/ECOC Silas/ecoc_2025";
else
    dsp_options.storage_path = "W:\labdata\ECOC Silas\ecoc_2025";
end
dsp_options.server = "192.168.178.192";
dsp_options.port = 3306;
dsp_options.user = "silas";
dsp_options.password = "silas";
dsp_options.append_mpi_reduction_db = write_mpi_reduction_db && stream_mpi_reduction_db;
dsp_options.mpi_reduction_study_name = mpi_reduction_study_name;
dsp_options.mpi_reduction_writer_path = mpi_reduction_writer_path;

db = DBHandler("dataBase", [dsp_options.dataBase],...
    "type", dsp_options.database_type,...
    "server", dsp_options.server,...
    "user", dsp_options.user, "password", dsp_options.password);

%%
pamformats = [4,6,8];
baudrates = [112e9,96e9,72e9];

for i = 1
    
    B = baudrates(i);
    M = pamformats(i);
    
    fp = QueryFilter();
    fp.where('Runs','run_id','GREATER_EQUAL',3153);
    fp.where('Runs', 'symbolrate','EQUALS',B); % 72 96 112
    fp.where('Runs', 'fiber_length',              'EQUALS', 0);
    fp.where('Runs', 'interference_path_length',  'EQUALS', 1000);
    fp.where('Runs', 'sir',                       'LESS_EQUAL', 20);
    fp.where('Runs', 'db_mode',                   'EQUALS', '"no_db"');
    % fp.where('Runs', 'is_mpi',                    'EQUALS', 1);
    fp.where('Runs', 'pam_level',                 'EQUALS', M);
    % fp.where('Runs', 'v_bias',                    'EQUALS', 2.65);
    
    [dataTable,~] = db.queryDB(fp, db.getTableFieldNames('Runs'));
    
    [~, sortIdx] = sort(dataTable.sir, 'descend');
    dataTable = dataTable(sortIdx, :);

    desired_sir = [15,22,26,30,38];
    desired_sir = [22,38];
    % exclude_sr = [112e9];
    % % Filter dataTable to only keep rows with sir in desired_sir
    isDesired = ~ismember(dataTable.symbolrate, desired_sir);
    dataTable = dataTable(isDesired, :);
    % dataTable = dataTable(1,:);

    run_ids = dataTable.run_id;

    %% === Warehouse setup ===
    dsp_options.userParameters = struct();
    dsp_options.userParameters.block_update = 1;%[1,2,4,8,16,32,64,112,224,448,448*2,1024,2048,4096,8192,16384];%%logspace(-3.8,-1,22);%[linspace(2,4096,22)];
    % dsp_options.userParameters.hpf = [2e6:0.5e6:10e6];
    % dsp_options.userParameters.bufferlen = [112,224,448,448*2,1024,2048,4096,8192,16384];
    wh = DataStorage(dsp_options.userParameters);
    
    %%
    n_realizations = (dsp_options.max_occurences - dsp_options.start_occurence + 1);
    n_userparams = prod(wh.dim);
    n_run_ids = numel(run_ids);
    parallel_jobs = n_userparams * n_run_ids;
    queried_jobs = n_realizations * n_userparams * n_run_ids;
    
    fprintf("-> [ %d run_id(s) × %d userParam combination(s) = %d parallel job(s) ] × %d realizations = %d total jobs \n", ...
        n_run_ids, n_userparams, parallel_jobs, n_realizations, queried_jobs);
    
    %% === Run ===
    % submitJobs returns the raw per-job results and the filled Warehouse. For a
    % single run_id and remove_dc = [0, 1], results is a 2-by-1 cell array.
    [results, wh] = submitJobs(run_ids, dsp_options, processingMode.serial, ...
        "wh", wh, ...
        "waitbar", true);

    %%
    
    if write_mpi_reduction_db && ~stream_mpi_reduction_db
        db.refresh();
        appendMpiReductionWarehouse(db, wh, run_ids, dsp_options, ...
            "study_name", mpi_reduction_study_name);
    end
    
    % savepath = fullfile("C:","Users","Silas","Documents","MATLAB","imdd_simulation","projects","Diss","MPI_revisit","algorithms",sprintf("pam_%d_results.mat",M));
    % save(wh,savepath)


end

%% Analyze

storageNames = fieldnames(wh.sto);

x_base = dataTable.sir(:).';
x_base = dsp_options.userParameters.block_update;
x_base = dsp_options.userParameters.bufferlen;
% x_base = dsp_options.userParameters.hpf;
figure(2029); hold on
for storage_idx = 1:numel(storageNames)
    storageName = storageNames{storage_idx};
    result = wh.sto.(storageName);
    result = result(:).';
    
    % Each stored entry is a package cell containing one or more occurrences.
    ber_all = cell(1,numel(result));
    for result_idx = 1:numel(result)
        packageCell = result{result_idx};
        if isempty(packageCell)
            ber_all{result_idx} = NaN;
            continue
        end
    
        ber_values = nan(1,numel(packageCell));
        for package_idx = 1:numel(packageCell)
            if isstruct(packageCell{package_idx}) && isfield(packageCell{package_idx},"metrics")
                ber_values(package_idx) = packageCell{package_idx}.metrics.BER;
            end
        end
        ber_all{result_idx} = ber_values;
    end
    
    maxPackages = max(cellfun(@numel,ber_all));
    ber_mat = nan(maxPackages,numel(ber_all));
    for k = 1:numel(ber_all)
        ber_mat(1:numel(ber_all{k}),k) = ber_all{k};
    end
    ber = mean(ber_mat,1,"omitnan");
    
    x = x_base;
    if numel(x) ~= numel(ber)
        x = 1:numel(ber);
    end
    
    h = plot(x,ber,"DisplayName",storageName);
    for k = 1:numel(x)
        scatter(repmat(x(k),maxPackages,1),ber_mat(:,k), ...
            "MarkerEdgeColor",h.Color, ...
            "HandleVisibility","off");
    end
end

beautifyBERplot("logscale",true,"setcolors",false,"setmarkers",true);
legend("Location","best","Interpreter","none");