dsp_options.database_type = "mysql";
dsp_options.dataBase = "labor";
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, "port", dsp_options.port, ...
    "user", dsp_options.user, "password", dsp_options.password);

fp = QueryFilter();
% fp.where('Runs', 'symbolrate','EQUALS', 112e9);
[dataTable,~] = db.queryDB(fp, db.getTableFieldNames('Runs'));

%% TOTAL RUNS

totalRuns = height(dataTable);

%% Difference between "opti" and not opti (before and after run_id = 2661)

fp = QueryFilter();
fp.where('Runs','run_id','LESS_THAN',3153);
fp.where('Runs', 'db_mode','EQUALS', '"no_db"');
% fp.where('Runs', 'interference_path_length','EQUALS', 300);
[dataTable_1,~] = db.queryDB(fp, db.getTableFieldNames('Runs'));

fp = QueryFilter();
fp.where('Runs','run_id','GREATER_EQUAL',3153);
% fp.where('Runs', 'interference_path_length','EQUALS', 300);
[dataTable_2,~] = db.queryDB(fp, db.getTableFieldNames('Runs'));

%% prepare x/y and plotting without forcing datetime priority for x
% simplified: assume columns exist and no datetime special cases
xCol = 'symbolrate';
yCol = 'v_awg';

% get x and y (fallback to NaN vectors of appropriate length)
if ismember(xCol, dataTable_1.Properties.VariableNames)
    x1 = dataTable_1.(xCol);
else
    x1 = NaN(height(dataTable_1),1);
end
if ismember(xCol, dataTable_2.Properties.VariableNames)
    x2 = dataTable_2.(xCol);
else
    x2 = NaN(height(dataTable_2),1);
end

if ismember(yCol, dataTable_1.Properties.VariableNames)
    y1 = dataTable_1.(yCol);
else
    y1 = NaN(height(dataTable_1),1);
end
if ismember(yCol, dataTable_2.Properties.VariableNames)
    y2 = dataTable_2.(yCol);
else
    y2 = NaN(height(dataTable_2),1);
end

% convert text to numeric where needed
toNum = @(v) double(string(v));
if iscell(x1) || isstring(x1) || ischar(x1), x1 = toNum(x1); end
if iscell(x2) || isstring(x2) || ischar(x2), x2 = toNum(x2); end
if iscell(y1) || isstring(y1) || ischar(y1), y1 = toNum(y1); end
if iscell(y2) || isstring(y2) || ischar(y2), y2 = toNum(y2); end

% simple scatter plots side-by-side
figure;
subplot(1,2,1);
scatter(x1, y1, 36, 'b', 'filled');
xlabel(xCol); ylabel(yCol); title('dataTable\_1'); grid on;

subplot(1,2,2);
scatter(x2, y2, 36, 'r', 'filled');
xlabel(xCol); ylabel(yCol); title('dataTable\_2'); grid on;

linkaxes(findall(gcf,'Type','axes'),'y');

%% Count interference path lengths by PAM and symbolrate

pamCol = 'pam_level';
iplCol = 'interference_path_length';
rateCol = 'symbolrate';
pamLevels = [2, 4, 6, 8];

% Current analysis uses only the post-opti/post-threshold runs.
% Use [dataTable_1; dataTable_2] here if the pre-threshold runs should be included.
allData = dataTable_2;

requiredCols = {pamCol, iplCol, rateCol};
missingCols = setdiff(requiredCols, allData.Properties.VariableNames);
if ~isempty(missingCols)
    error('Missing required column(s): %s', strjoin(missingCols, ', '));
end

pam = double(string(allData.(pamCol)));
ipl = double(string(allData.(iplCol)));
symbolrate = double(string(allData.(rateCol)));

validRows = ~isnan(pam) & ~isnan(ipl) & ~isnan(symbolrate);
iplValues = unique(ipl(validRows));
symbolrateValues = unique(symbolrate(validRows));

if isempty(iplValues) || isempty(symbolrateValues)
    error('No valid rows found for PAM/interference_path_length/symbolrate plotting.');
end

iplCategories = categorical(string(iplValues), string(iplValues), string(iplValues));
symbolrateLabels = compose('%.0f GBd', symbolrateValues*1e-9);

figure('Units', 'normalized', 'Position', [0.05 0.1 0.9 0.7]);
tiledlayout(1, 5, 'TileSpacing', 'compact', 'Padding', 'compact');

for k = 1:numel(pamLevels)
    ax = nexttile;
    pamMask = validRows & pam == pamLevels(k);
    counts = zeros(numel(iplValues), numel(symbolrateValues));
    for rateIdx = 1:numel(symbolrateValues)
        for iplIdx = 1:numel(iplValues)
            counts(iplIdx, rateIdx) = sum(pamMask ...
                & ipl == iplValues(iplIdx) ...
                & symbolrate == symbolrateValues(rateIdx));
        end
    end

    bar(ax, iplCategories, counts, 'stacked');
    xlabel(ax, 'interference\_path\_length');
    ylabel(ax, 'count');
    title(ax, sprintf('PAM %d', pamLevels(k)));
    xtickangle(ax, 45);
    grid(ax, 'on');
end

axAll = nexttile;
countsAll = zeros(numel(iplValues), numel(symbolrateValues));
for rateIdx = 1:numel(symbolrateValues)
    for iplIdx = 1:numel(iplValues)
        countsAll(iplIdx, rateIdx) = sum(validRows ...
            & ipl == iplValues(iplIdx) ...
            & symbolrate == symbolrateValues(rateIdx));
    end
end

bar(axAll, iplCategories, countsAll, 'stacked');
xlabel(axAll, 'interference\_path\_length');
ylabel(axAll, 'count');
title(axAll, 'All PAMs');
xtickangle(axAll, 45);
grid(axAll, 'on');

lgd = legend(axAll, symbolrateLabels, 'Location', 'eastoutside');
title(lgd, 'symbolrate');