public static void main(String args[]) {
DescriptiveStatistics stats = DescriptiveStatistics.newInstance();
/* stats.addValue(2);
stats.addValue(23);
stats.addValue(28);
stats.addValue(69);
stats.addValue(87);
stats.addValue(111);
stats.addValue(125);*/
stats.addValue(2);
stats.addValue(4);
stats.addValue(6);
double p25 = stats.getPercentile(25);
double p50 = stats.getPercentile(50);
double p75 = stats.getPercentile(75);
// System.out.println(stats.toString());
double delta = p75 - p25;
double center = p25 + (delta / 2);
double spread = delta / 2;
System.out.println("p25:" + p25 + " - p50:" + p50 + " - p75:" + p75);
System.out.println("center: " + center + " - spread: " + spread);
}
/** * Contains all the performance results obtained during log replay analysis. Can be used to retrieve * values for the performance metrics and to get extended visualizations. * * @see PerformanceMeasurer * @author Peter T.G. Hornix ([email protected]) */ public class PerformanceLogReplayResult extends LogReplayAnalysisResult { // DescriptiveStatistics-object in which throughput times can be stored private DescriptiveStatistics timeStats = DescriptiveStatistics.newInstance(); // SummaryStatistics to obtain mean inter arrival times private SummaryStatistics arrivalStats = SummaryStatistics.newInstance(); // number of log traces that can be replayed normally private int properFrequency; public PerformanceLogReplayResult( AnalysisConfiguration analysisOptions, PetriNet net, LogReader log, LogReplayAnalysisMethod method) { // call the constructor of the superclass super(analysisOptions, net, log, method); } /** * Initializes the diagnostic data structures needed to store the measurements taken during the * log replay analysis. */ protected void initDiagnosticDataStructures() { replayedLog = new ExtendedLogReader(inputLogReader); replayedPetriNet = new ExtendedPetriNet(inputPetriNet, replayedLog.getLogTraceIDs()); } // ////////////////////////////METRICS-RELATED // METHODS/////////////////////////// /** * Calculates the average, min ad max throughput time out of the throughput times of all traces in * piList. Next to this, the arrival rate is calculated. All metrics are based on the process * instances in piList only * * @param piList ArrayList: the process instances used * @param fitOption int: the fit option used (how to deal with non-conformance) * @throws Exception */ public void calculateMetrics(ArrayList piList, int fitOption) throws Exception { properFrequency = 0; timeStats.clear(); arrivalStats.clear(); ArrayList arrivalDates = new ArrayList(); ListIterator lit = piList.listIterator(); while (lit.hasNext()) { ExtendedLogTrace currentTrace = (ExtendedLogTrace) lit.next(); if (currentTrace.hasProperlyTerminated() && currentTrace.hasSuccessfullyExecuted()) { properFrequency++; } try { long tp = (currentTrace.getEndDate().getTime() - currentTrace.getBeginDate().getTime()); if (fitOption == 0) { // timeStats based on all traces timeStats.addValue(tp); arrivalDates.add(currentTrace.getBeginDate()); } if (currentTrace.hasProperlyTerminated() && currentTrace.hasSuccessfullyExecuted()) { if (fitOption == 1) { // timeStats based on fitting traces only timeStats.addValue(tp); arrivalDates.add(currentTrace.getBeginDate()); } } } catch (NullPointerException ex) { ex.printStackTrace(); } } Date[] arrivals = (Date[]) arrivalDates.toArray(new Date[0]); // make sure arrivaldates are sorted Arrays.sort(arrivals); if (arrivals.length > 1) { for (int i = 1; i < arrivals.length; i++) { long t1 = arrivals[i].getTime(); long t2 = arrivals[i - 1].getTime(); long iat = arrivals[i].getTime() - arrivals[i - 1].getTime(); if (iat >= 0) { arrivalStats.addValue(iat); } } } } /** * Exports the throughput times of all process instances in piList to a comma-seperated text-file. * * @param piList ArrayList: the process instances used * @param file File: the file to which the times are exported * @param divider long: the time divider used * @param sort String: the time sort used * @param fitOption int: the fit option used (how to deal with non-conformance) * @throws IOException */ public void exportToFile(ArrayList piList, File file, long divider, String sort, int fitOption) throws IOException { Writer output = new BufferedWriter(new FileWriter(file)); String line = "Log Trace,Throughput time (" + sort + ")\n"; output.write(line); ListIterator lit = piList.listIterator(); while (lit.hasNext()) { ExtendedLogTrace currentTrace = (ExtendedLogTrace) lit.next(); try { double tp = (currentTrace.getEndDate().getTime() - currentTrace.getBeginDate().getTime()) * 1.0 / divider; if (fitOption == 0) { // times based on all traces line = currentTrace.getName() + "," + tp + "\n"; // write line to the file output.write(line); } if (fitOption == 1 && currentTrace.hasProperlyTerminated() && currentTrace.hasSuccessfullyExecuted()) { // times based on fitting traces only line = currentTrace.getName() + "," + tp + "\n"; // write line to the file output.write(line); } } catch (NullPointerException npe) { } } // close the file output.close(); } // ////////////////////////////GET // METHODS/////////////////////////////////////// /** * Calculates and returns the stdev in throughput time out of the throughput times in timeStats. * (make sure calculateProcessMetrics() is called before this method). * * @return double */ public double getStdevThroughputTime() { return timeStats.getStandardDeviation(); } /** * Calculates the average of the (fastestpercentage) fast traces, the (slowestPercentage) slow * traces and the (100% - fastestPercentage - slowestPercentage) normal speed traces and returns * these averages in an array, where [0]: avg fast throughput time [1]: avg slow throughput time * [2]: avg middle throughput time * * @param fastestPercentage double: the percentage of measurements that is to be counted as fast * @param slowestPercentage double: the percentage of measurements that is to be counted as slow * @return double[] */ public double[] getAverageTimes(double fastestPercentage, double slowestPercentage) { // initialize arrays double[] timeList = timeStats.getSortedValues(); double[] avgTimes = new double[3]; long total = 0; // obtain the number of fast , slow, normal traces int[] sizes = getSizes(fastestPercentage, slowestPercentage); int fastSize = sizes[0], slowSize = sizes[1], middleSize = sizes[2]; for (int i = 0; i < fastSize; i++) { total += timeList[i]; } // calculate average of the fastest traces double avgFastestTime = 0.0; if (fastSize != 0) { avgFastestTime = (total * 1.0) / fastSize; } // calculate average of the slowest traces int upperSize = timeList.length - slowSize; total = 0; for (int i = upperSize; i < timeList.length; i++) { total += timeList[i]; } double avgSlowestTime = 0.0; if (slowSize > 0) { avgSlowestTime = (total * 1.0) / slowSize; } // calculate the middle/normal-speed traces total = 0; for (int i = fastSize; i < upperSize; i++) { total += timeList[i]; } double avgMiddleTime = 0.0; if (middleSize > 0) { avgMiddleTime = (total * 1.0) / middleSize; } avgTimes[0] = avgFastestTime; avgTimes[1] = avgSlowestTime; avgTimes[2] = avgMiddleTime; return avgTimes; } /** * Returns an array containing the number of process instances that are considered to be fast, * i.e. have a low throughput time (place 0 in array), the number of process instances that are * slow (place 1 in array) and the number of process instances that are considered to be of normal * speed (place 2 in array). Based on fastestPercentage, slowestPercentage and timeList (thus * method calculateProcessMetrics() should be called before this one) * * @param fastestPercentage double: the percentage of measurements that is to be counted as fast * @param slowestPercentage double: the percentage of measurements that is to be counted as slow * @return int[] */ public int[] getSizes(double fastestPercentage, double slowestPercentage) { int[] sizes = new int[3]; String sizeString; int length = timeStats.getValues().length; sizeString = Math.round((length * fastestPercentage) / 100.0) + ""; sizes[0] = Integer.parseInt(sizeString); if (sizes[0] != length) { sizeString = Math.round((length * slowestPercentage) / 100.0) + ""; sizes[1] = Integer.parseInt(sizeString); if ((sizes[0] + sizes[1]) > length) { // Make sure that sizes[0] + sizes[1] remains smaller than // the number of measurements in timeList (rounding could mess // this up) sizes[1] = length - sizes[0]; } } else { sizes[1] = 0; } sizes[2] = length - sizes[0] - sizes[1]; return sizes; } /** * Calculates and returns the arrival rate of the traces in piList * * @return double */ public double getArrivalRate() { double arrivalRate = 0; if (arrivalStats.getN() > 0 && arrivalStats.getMean() != 0) { // mean arrivalRate is 1 divided by the mean of the inter-arrival // times arrivalRate = 1 / arrivalStats.getMean(); } return arrivalRate; } /** * Returns the arrival Stats of the traces in piList * * @return SummaryStatistics */ public SummaryStatistics getArrivalStats() { return arrivalStats; } /** * Returns the mean throughput time * * @return double */ public double getMeanThroughputTime() { return timeStats.getMean(); } /** * Returns the minimal throughput time. Note that method calculateProcessMetrics() should be * called before this method. * * @return double */ public double getMinThroughputTime() { return timeStats.getMin(); } /** * Returns the maximal throughput time * * @return double */ public double getMaxThroughputTime() { return timeStats.getMax(); } /** * returns the number of cases that execute successfully and complete properly * * @return int */ public int getProperFrequency() { return (properFrequency); } // ////////////////////////////GRAPPA-RELATED // METHODS/////////////////////////// /** * Creates a visualization of the performance analysis results. Note that a change of the display * state by the user will have no effect before calling this methods. This is intended to prevent * unnecessary cloning of the extended petri net, which actually delivers the custom visualization * of the performance analysis results. * * @param selectedInstances The process instances that have been selected for updating the * visualization. * @return The visualization wrapped in a ModelGraphPanel. */ public ModelGraphPanel getVisualization(ArrayList selectedInstances) { // sets the currentlySelectedInstances attribute, which is necessary // because // the writeToDot() method has a fixed interface, though the // visualization should // be able to take them into account ((ExtendedPetriNet) replayedPetriNet).currentlySelectedInstances = selectedInstances; ModelGraphPanel myResultVisualization; myResultVisualization = ((ExtendedPetriNet) replayedPetriNet).getGrappaVisualization(); return myResultVisualization; } }