156 lines
4.9 KiB
Matlab
156 lines
4.9 KiB
Matlab
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dsp_options.database_type = "mysql";
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dsp_options.dataBase = "labor";
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dsp_options.server = "192.168.178.192";
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dsp_options.port = 3306;
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dsp_options.user = "silas";
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dsp_options.password = "silas";
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db = DBHandler("dataBase", dsp_options.dataBase, "type", dsp_options.database_type, ...
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"server", dsp_options.server, "port", dsp_options.port, ...
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"user", dsp_options.user, "password", dsp_options.password);
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fp = QueryFilter();
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% fp.where('Runs', 'symbolrate','EQUALS', 112e9);
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[dataTable,~] = db.queryDB(fp, db.getTableFieldNames('Runs'));
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%% TOTAL RUNS
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totalRuns = height(dataTable);
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%% Difference between "opti" and not opti (before and after run_id = 2661)
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fp = QueryFilter();
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fp.where('Runs','run_id','LESS_THAN',3153);
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fp.where('Runs', 'db_mode','EQUALS', '"no_db"');
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% fp.where('Runs', 'interference_path_length','EQUALS', 300);
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[dataTable_1,~] = db.queryDB(fp, db.getTableFieldNames('Runs'));
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fp = QueryFilter();
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fp.where('Runs','run_id','GREATER_EQUAL',3153);
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% fp.where('Runs', 'interference_path_length','EQUALS', 300);
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[dataTable_2,~] = db.queryDB(fp, db.getTableFieldNames('Runs'));
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%% prepare x/y and plotting without forcing datetime priority for x
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% simplified: assume columns exist and no datetime special cases
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xCol = 'symbolrate';
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yCol = 'v_awg';
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% get x and y (fallback to NaN vectors of appropriate length)
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if ismember(xCol, dataTable_1.Properties.VariableNames)
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x1 = dataTable_1.(xCol);
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else
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x1 = NaN(height(dataTable_1),1);
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end
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if ismember(xCol, dataTable_2.Properties.VariableNames)
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x2 = dataTable_2.(xCol);
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else
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x2 = NaN(height(dataTable_2),1);
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end
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if ismember(yCol, dataTable_1.Properties.VariableNames)
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y1 = dataTable_1.(yCol);
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else
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y1 = NaN(height(dataTable_1),1);
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end
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if ismember(yCol, dataTable_2.Properties.VariableNames)
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y2 = dataTable_2.(yCol);
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else
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y2 = NaN(height(dataTable_2),1);
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end
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% convert text to numeric where needed
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toNum = @(v) double(string(v));
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if iscell(x1) || isstring(x1) || ischar(x1), x1 = toNum(x1); end
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if iscell(x2) || isstring(x2) || ischar(x2), x2 = toNum(x2); end
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if iscell(y1) || isstring(y1) || ischar(y1), y1 = toNum(y1); end
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if iscell(y2) || isstring(y2) || ischar(y2), y2 = toNum(y2); end
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% simple scatter plots side-by-side
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figure;
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subplot(1,2,1);
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scatter(x1, y1, 36, 'b', 'filled');
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xlabel(xCol); ylabel(yCol); title('dataTable\_1'); grid on;
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subplot(1,2,2);
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scatter(x2, y2, 36, 'r', 'filled');
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xlabel(xCol); ylabel(yCol); title('dataTable\_2'); grid on;
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linkaxes(findall(gcf,'Type','axes'),'y');
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%% Count interference path lengths by PAM and symbolrate
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pamCol = 'pam_level';
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iplCol = 'interference_path_length';
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rateCol = 'symbolrate';
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pamLevels = [2, 4, 6, 8];
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% Current analysis uses only the post-opti/post-threshold runs.
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% Use [dataTable_1; dataTable_2] here if the pre-threshold runs should be included.
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allData = dataTable_2;
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requiredCols = {pamCol, iplCol, rateCol};
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missingCols = setdiff(requiredCols, allData.Properties.VariableNames);
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if ~isempty(missingCols)
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error('Missing required column(s): %s', strjoin(missingCols, ', '));
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end
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pam = double(string(allData.(pamCol)));
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ipl = double(string(allData.(iplCol)));
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symbolrate = double(string(allData.(rateCol)));
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validRows = ~isnan(pam) & ~isnan(ipl) & ~isnan(symbolrate);
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iplValues = unique(ipl(validRows));
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symbolrateValues = unique(symbolrate(validRows));
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if isempty(iplValues) || isempty(symbolrateValues)
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error('No valid rows found for PAM/interference_path_length/symbolrate plotting.');
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end
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iplCategories = categorical(string(iplValues), string(iplValues), string(iplValues));
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symbolrateLabels = compose('%.0f GBd', symbolrateValues*1e-9);
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figure('Units', 'normalized', 'Position', [0.05 0.1 0.9 0.7]);
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tiledlayout(1, 5, 'TileSpacing', 'compact', 'Padding', 'compact');
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for k = 1:numel(pamLevels)
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ax = nexttile;
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pamMask = validRows & pam == pamLevels(k);
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counts = zeros(numel(iplValues), numel(symbolrateValues));
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for rateIdx = 1:numel(symbolrateValues)
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for iplIdx = 1:numel(iplValues)
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counts(iplIdx, rateIdx) = sum(pamMask ...
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& ipl == iplValues(iplIdx) ...
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& symbolrate == symbolrateValues(rateIdx));
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end
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end
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bar(ax, iplCategories, counts, 'stacked');
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xlabel(ax, 'interference\_path\_length');
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ylabel(ax, 'count');
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title(ax, sprintf('PAM %d', pamLevels(k)));
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xtickangle(ax, 45);
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grid(ax, 'on');
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end
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axAll = nexttile;
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countsAll = zeros(numel(iplValues), numel(symbolrateValues));
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for rateIdx = 1:numel(symbolrateValues)
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for iplIdx = 1:numel(iplValues)
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countsAll(iplIdx, rateIdx) = sum(validRows ...
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& ipl == iplValues(iplIdx) ...
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& symbolrate == symbolrateValues(rateIdx));
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end
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end
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bar(axAll, iplCategories, countsAll, 'stacked');
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xlabel(axAll, 'interference\_path\_length');
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ylabel(axAll, 'count');
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title(axAll, 'All PAMs');
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xtickangle(axAll, 45);
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grid(axAll, 'on');
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lgd = legend(axAll, symbolrateLabels, 'Location', 'eastoutside');
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title(lgd, 'symbolrate');
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