144 lines
5.0 KiB
C
144 lines
5.0 KiB
C
#include <vector>
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void constHisto(std::vector<double> ×, std::vector<double> &means, TH1F* hist, std::vector<double> &binEdges) {
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// Initialize vectors to store bin contents and counts
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std::vector<double> binContents(binEdges.size() - 1, 0.0);
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std::vector<int> binCounts(binEdges.size() - 1, 0);
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// Loop through data and fill the histogram
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for (size_t i = 0; i < times.size(); ++i) {
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double val = means[i];
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for (size_t j = 0; j < binEdges.size() - 1; ++j) {
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if (times[i] >= binEdges[j] && times[i] < binEdges[j + 1]) {
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binContents[j] += val;
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binCounts[j]++;
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break;
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}
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}
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}
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// Calculate the means for each bin and set the bin content
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for (size_t i = 0; i < binEdges.size() - 1; ++i) {
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double binMean = (binCounts[i] > 0) ? binContents[i] / binCounts[i] : 0;
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hist->SetBinContent(i + 1, binMean); // Set the bin content to the mean
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}
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}
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void QueueOccup() {
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// Define your bin edges
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gROOT->SetBatch(kTRUE);
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std::vector<double> binEdges;
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for (int i = 0; i <= 30; i++) {
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binEdges.push_back(i);
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if (i>=6) binEdges.push_back(i + 0.5);
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}
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//gROOT->SetBatch(kTRUE);
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auto f100 = "./queue_occup_1kmean_20ms_timeout50ms_100clients.csv";
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auto f100_df = ROOT::RDF::MakeCsvDataFrame(f100, true, ';');
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auto f200 = "./queue_occup_1kmean_20ms_timeout50ms_200clients.csv";
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auto f200_df = ROOT::RDF::MakeCsvDataFrame(f200, true, ';');
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auto f500 = "./queue_occup_1kmean_20ms_timeout50ms_500clients.csv";
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auto f500_df = ROOT::RDF::MakeCsvDataFrame(f500, true, ';');
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auto f1000 = "./queue_occup_1kmean_20ms_timeout50ms_1000clients.csv";
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auto f1000_df = ROOT::RDF::MakeCsvDataFrame(f1000, true, ';');
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//gStyle->SetOptTitle(kFALSE);
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gStyle->SetOptStat(0);
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auto canvas = new TCanvas("c", "c", 1400, 1000);
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//canvas->SetLogx();
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canvas->SetGrid();
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canvas->SetLogy();
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//filteredEvents.Histo1D({"invMass", "CMS Opendata: #mu#mu mass;#mu#mu mass [GeV];Events", 512, 2, 110}, "m");
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auto timesResult100 = f100_df.Take<double>("times");
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auto meansResult100 = f100_df.Take<double>("means");
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std::vector<double> times100 = timesResult100.GetValue();
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std::vector<double> means100 = meansResult100.GetValue();
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// Create a histogram with custom binning
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TH1F *h100 = new TH1F("h100","Custom Histogram", binEdges.size() - 1, &binEdges[0]);
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constHisto(times100, means100, h100, binEdges);
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h100->SetLineWidth(3);
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//filteredEvents.Histo1D({"invMass", "CMS Opendata: #mu#mu mass;#mu#mu mass [GeV];Events", 512, 2, 110}, "m");
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auto timesResult200 = f200_df.Take<double>("times");
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auto meansResult200 = f200_df.Take<double>("means");
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std::vector<double> times200 = timesResult200.GetValue();
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std::vector<double> means200 = meansResult200.GetValue();
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// Create a histogram with custom binning
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TH1F *h200 = new TH1F("h200","Custom Histogram", binEdges.size() - 1, &binEdges[0]);
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constHisto(times200, means200, h200, binEdges);
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h200->SetLineWidth(3);
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//filteredEvents.Histo1D({"invMass", "CMS Opendata: #mu#mu mass;#mu#mu mass [GeV];Events", 512, 2, 110}, "m");
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auto timesResult500 = f500_df.Take<double>("times");
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auto meansResult500 = f500_df.Take<double>("means");
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std::vector<double> times500 = timesResult500.GetValue();
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std::vector<double> means500 = meansResult500.GetValue();
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// Create a histogram with custom binning
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TH1F *h500 = new TH1F("h500", "", binEdges.size() - 1, &binEdges[0]);
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constHisto(times500, means500, h500, binEdges);
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h500->SetLineWidth(3);
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//filteredEvents.Histo1D({"invMass", "CMS Opendata: #mu#mu mass;#mu#mu mass [GeV];Events", 512, 2, 110}, "m");
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auto timesResult1000 = f1000_df.Take<double>("times");
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auto meansResult1000 = f1000_df.Take<double>("means");
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std::vector<double> times1000 = timesResult1000.GetValue();
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std::vector<double> means1000 = meansResult1000.GetValue();
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// Create a histogram with custom binning
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TH1F *h1000 = new TH1F("h1000", "Custom Histogram", binEdges.size() - 1, &binEdges[0]);
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constHisto(times1000, means1000, h1000, binEdges);
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h1000->SetLineWidth(3);
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h1000->GetYaxis()->SetRangeUser(2., 150000.);
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h1000->GetXaxis()->SetRangeUser(5., 30.);
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gStyle->SetPalette(1);
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h1000->SetTitle("Queue occupancy over time; Time [s];Queue Size [elements];");
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h1000->Draw("plc");
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h500->Draw("same plc");
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h200->Draw("same plc");
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h100->Draw("same plc");
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//gStyle->SetLegendTextSize(0.01);
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auto leg = new TLegend(0.64,0.62,0.9,0.77);
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leg->SetHeader("Num Clients", "c");
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leg->AddEntry("h100","100 Clients","lp");
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leg->AddEntry("h200","200 Clients","lp");
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leg->AddEntry("h500","500 Clients","lp");
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leg->AddEntry("h1000","1000 Clients","lp");
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leg->Draw();
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//canvas->BuildLegend(0.65,0.2,0.86,0.32, "Connection Method");
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canvas->Print("MeanQueueOccupation.png");
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gROOT->SetBatch(kFALSE);
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gApplication->Terminate(0);
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} |