% === 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 = 2;
dsp_options.max_occurences = 1;
dsp_options.debug_plots = false;

dsp_options.database_type = "mysql";

dsp_options.dataBase = "labor";
dsp_options.storage_path = "W:\labdata\ECOC Silas\ecoc_2025";

dsp_options.server = "192.168.178.192";
dsp_options.port = 3306;
dsp_options.user = "silas";
dsp_options.password = "silas";

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

%%
fp = QueryFilter();
fp.where('Runs','run_id','GREATER_EQUAL',3153);
fp.where('Runs', 'symbolrate',                'EQUALS', 112e9);
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', 4);
% fp.where('Runs', 'v_bias',                    'EQUALS', 2.65);

[dataTable,~] = db.queryDB(fp, db.getTableFieldNames('Runs'));

% [~, uniqueSirRows] = unique(dataTable.sir, "stable");
% dataTable = dataTable(uniqueSirRows, :);

[~, sortIdx] = sort(dataTable.sir, 'descend');
dataTable = dataTable(sortIdx, :);
dataTable = dataTable(1, :);
run_ids = dataTable.run_id;

if isempty(run_ids)
    error("run_minimal_recipe:MissingRunIds", ...
        "Set run_ids to one or more known run IDs before running this example.");
end

%% === Warehouse setup ===
dsp_options.userParameters = struct();
% dsp_options.userParameters.smoothing_length = [0,linspace(100,1000,10),2500,5000,10000];
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);

%% Analyze

storageNames = fieldnames(wh.sto);
result = wh.sto.(storageNames{1});
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 = dataTable.sir(:).';
if numel(x) ~= numel(ber)
    x = 1:numel(ber);
end

figure(2026); clf; hold on
plot(x,ber);
for k = 1:numel(x)
    scatter(repmat(x(k),maxPackages,1),ber_mat(:,k))
end
beautifyBERplot("logscale",true,"setcolors",false,"setmarkers",true);