List of usage examples for org.apache.commons.math3.stat.descriptive.moment StandardDeviation StandardDeviation
public StandardDeviation()
From source file:com.musicg.experiment.test.Test1.java
/** * @param args//from w w w .java2 s . c o m */ public static void main(String[] args) { String filename = "audio_work/lala.wav"; // create a wave object Wave wave = null; try { wave = new Wave(filename); } catch (IOException e) { // TODO Auto-generated catch block e.printStackTrace(); } // TimeDomainRepresentations int fftSampleSize = 1024; int overlapFactor = 1; Spectrogram spectrogram = new Spectrogram(wave, fftSampleSize, overlapFactor); int fps = spectrogram.getFramesPerSecond(); double unitFrequency = spectrogram.getUnitFrequency(); // set boundary int highPass = 100; int lowerBoundary = (int) (highPass / unitFrequency); int lowPass = 4000; int upperBoundary = (int) (lowPass / unitFrequency); // end set boundary double[][] spectrogramData = spectrogram.getNormalizedSpectrogramData(); double[][] absoluteSpectrogramData = spectrogram.getAbsoluteSpectrogramData(); double[][] boundedSpectrogramData = new double[spectrogramData.length][]; // SpectralCentroid sc=new SpectralCentroid(); StandardDeviation sd = new StandardDeviation(); ArrayRankDouble arrayRankDouble = new ArrayRankDouble(); // zrc short[] amps = wave.getSampleAmplitudes(); int numFrame = amps.length / 1024; double[] zcrs = new double[numFrame]; for (int i = 0; i < numFrame; i++) { short[] temp = new short[1024]; System.arraycopy(amps, i * 1024, temp, 0, temp.length); int numZC = 0; int size = temp.length; for (int j = 0; j < size - 1; j++) { if ((temp[j] >= 0 && temp[j + 1] < 0) || (temp[j] < 0 && temp[j + 1] >= 0)) { numZC++; } } zcrs[i] = numZC; } // end zcr for (int i = 0; i < spectrogramData.length; i++) { double[] temp = new double[upperBoundary - lowerBoundary + 1]; System.arraycopy(spectrogramData[i], lowerBoundary, temp, 0, temp.length); int maxIndex = arrayRankDouble.getMaxValueIndex(temp); // sc.setValues(temp); double sdValue = sd.evaluate(temp); System.out.println(i + " " + (double) i / fps + "s\t" + maxIndex + "\t" + sdValue + "\t" + zcrs[i]); boundedSpectrogramData[i] = temp; } // Graphic render GraphicRender render = new GraphicRender(); render.setHorizontalMarker(61); render.setVerticalMarker(200); render.renderSpectrogramData(boundedSpectrogramData, filename + ".jpg"); PitchHandler ph = new PitchHandler(); for (int frame = 0; frame < absoluteSpectrogramData.length; frame++) { System.out.print("frame " + frame + ": "); double[] temp = new double[upperBoundary - lowerBoundary + 1]; double sdValue = sd.evaluate(temp); double passSd = 0.1; if (sdValue < passSd) { System.arraycopy(spectrogramData[frame], lowerBoundary, temp, 0, temp.length); double maxFrequency = arrayRankDouble.getMaxValueIndex(temp) * unitFrequency; double passFrequency = 400; int numRobust = 2; double[] robustFrequencies = new double[numRobust]; double nthValue = arrayRankDouble.getNthOrderedValue(temp, numRobust, false); int count = 0; for (int b = lowerBoundary; b <= upperBoundary; b++) { if (spectrogramData[frame][b] >= nthValue) { robustFrequencies[count++] = b * unitFrequency; if (count >= numRobust) { break; } } } double passIntensity = 1000; double intensity = 0; for (int i = 0; i < absoluteSpectrogramData[frame].length; i++) { intensity += absoluteSpectrogramData[frame][i]; } intensity /= absoluteSpectrogramData[frame].length; System.out.print(" intensity: " + intensity + " pitch: " + maxFrequency); if (intensity > passIntensity && maxFrequency > passFrequency) { double p = ph.getHarmonicProbability(robustFrequencies); System.out.print(" P: " + p); } } System.out.print(" zcr:" + zcrs[frame]); System.out.println(); } }
From source file:hyperheuristics.main.comparisons.ComputeIndicators.java
public static void main(String[] args) throws IOException, InterruptedException { int[] numberOfObjectivesArray = new int[] { 2, 4 }; String[] problems = new String[] { "OO_MyBatis", "OA_AJHsqldb", "OA_AJHotDraw", "OO_BCEL", "OO_JHotDraw", "OA_HealthWatcher", // "OA_TollSystems", "OO_JBoss" }; String[] heuristicFunctions = new String[] { LowLevelHeuristic.CHOICE_FUNCTION, LowLevelHeuristic.MULTI_ARMED_BANDIT, LowLevelHeuristic.RANDOM }; String[] algorithms = new String[] { "NSGA-II", // "SPEA2" };// w ww . j a v a 2 s.c o m MetricsUtil metricsUtil = new MetricsUtil(); DecimalFormat decimalFormatter = new DecimalFormat("0.00E0"); Mean mean = new Mean(); StandardDeviation standardDeviation = new StandardDeviation(); InvertedGenerationalDistance igd = new InvertedGenerationalDistance(); GenerationalDistance gd = new GenerationalDistance(); Spread spread = new Spread(); Coverage coverage = new Coverage(); for (int objectives : numberOfObjectivesArray) { try (FileWriter IGDWriter = new FileWriter("experiment/IGD_" + objectives + ".tex"); FileWriter spreadWriter = new FileWriter("experiment/SPREAD_" + objectives + ".tex"); FileWriter GDWriter = new FileWriter("experiment/GD_" + objectives + ".tex"); FileWriter coverageWriter = new FileWriter("experiment/COVERAGE_" + objectives + ".tex")) { StringBuilder latexTableBuilder = new StringBuilder(); latexTableBuilder.append("\\documentclass{paper}\n").append("\n") .append("\\usepackage[T1]{fontenc}\n").append("\\usepackage[latin1]{inputenc}\n") .append("\\usepackage[hidelinks]{hyperref}\n").append("\\usepackage{tabulary}\n") .append("\\usepackage{booktabs}\n").append("\\usepackage{multirow}\n") .append("\\usepackage{amsmath}\n").append("\\usepackage{mathtools}\n") .append("\\usepackage{graphicx}\n").append("\\usepackage{array}\n") .append("\\usepackage[linesnumbered,ruled,inoutnumbered]{algorithm2e}\n") .append("\\usepackage{subfigure}\n").append("\\usepackage[hypcap]{caption}\n") .append("\\usepackage{pdflscape}\n").append("\n").append("\\begin{document}\n").append("\n") .append("\\begin{landscape}\n").append("\n"); pfKnown: { latexTableBuilder.append("\\begin{table}[!htb]\n").append("\t\\centering\n") .append("\t\\def\\arraystretch{1.5}\n") // .append("\t\\setlength{\\tabcolsep}{10pt}\n") // .append("\t\\fontsize{8pt}{10pt}\\selectfont\n") .append("\t\\caption{INDICATOR found for $PF_{known}$ for ").append(objectives) .append(" objectives}\n").append("\t\\label{tab:INDICATOR ").append(objectives) .append(" objectives}\n").append("\t\\begin{tabulary}{\\linewidth}{c"); for (String algorithm : algorithms) { latexTableBuilder.append("c"); for (String heuristicFunction : heuristicFunctions) { latexTableBuilder.append("c"); } } latexTableBuilder.append("}\n").append("\t\t\\toprule\n").append("\t\t\\textbf{System}"); for (String algorithm : algorithms) { latexTableBuilder.append(" & \\textbf{").append(algorithm).append("}"); for (String heuristicFunction : heuristicFunctions) { latexTableBuilder.append(" & \\textbf{").append(algorithm).append("-") .append(heuristicFunction).append("}"); } } latexTableBuilder.append("\\\\\n").append("\t\t\\midrule\n"); for (String problem : problems) { NonDominatedSolutionList trueFront = new NonDominatedSolutionList(); pfTrueComposing: { for (String algorithm : algorithms) { SolutionSet mecbaFront = metricsUtil.readNonDominatedSolutionSet( "resultado/" + algorithm.toLowerCase().replaceAll("-", "") + "/" + problem + "_Comb_" + objectives + "obj/All_FUN_" + algorithm.toLowerCase().replaceAll("-", "") + "-" + problem); trueFront.addAll(mecbaFront); for (String hyperHeuristic : heuristicFunctions) { SolutionSet front = metricsUtil.readNonDominatedSolutionSet( "experiment/" + algorithm + "/" + objectives + "objectives/" + hyperHeuristic + "/" + problem + "/FUN.txt"); trueFront.addAll(front); } } } double[][] trueFrontMatrix = trueFront.writeObjectivesToMatrix(); HashMap<String, Double> igdMap = new HashMap<>(); HashMap<String, Double> gdMap = new HashMap<>(); HashMap<String, Double> spreadMap = new HashMap<>(); HashMap<String, Double> coverageMap = new HashMap<>(); for (String algorithm : algorithms) { double[][] mecbaFront = metricsUtil .readFront("resultado/" + algorithm.toLowerCase().replaceAll("-", "") + "/" + problem + "_Comb_" + objectives + "obj/All_FUN_" + algorithm.toLowerCase().replaceAll("-", "") + "-" + problem); igdMap.put(algorithm, igd.invertedGenerationalDistance(mecbaFront, trueFrontMatrix, objectives)); gdMap.put(algorithm, gd.generationalDistance(mecbaFront, trueFrontMatrix, objectives)); spreadMap.put(algorithm, spread.spread(mecbaFront, trueFrontMatrix, objectives)); coverageMap.put(algorithm, coverage.coverage(mecbaFront, trueFrontMatrix)); for (String heuristic : heuristicFunctions) { double[][] heuristicFront = metricsUtil.readFront("experiment/" + algorithm + "/" + objectives + "objectives/" + heuristic + "/" + problem + "/FUN.txt"); igdMap.put(algorithm + "-" + heuristic, igd .invertedGenerationalDistance(heuristicFront, trueFrontMatrix, objectives)); gdMap.put(algorithm + "-" + heuristic, gd.generationalDistance(heuristicFront, trueFrontMatrix, objectives)); spreadMap.put(algorithm + "-" + heuristic, spread.spread(heuristicFront, trueFrontMatrix, objectives)); coverageMap.put(algorithm + "-" + heuristic, coverage.coverage(heuristicFront, trueFrontMatrix)); } } latexTableBuilder.append("\t\t").append(problem); String latexTable = latexTableBuilder.toString(); latexTableBuilder = new StringBuilder(); latexTable = latexTable.replaceAll("O[OA]\\_", "").replaceAll("ChoiceFunction", "CF") .replaceAll("MultiArmedBandit", "MAB"); IGDWriter.write(latexTable.replaceAll("INDICATOR", "IGD")); spreadWriter.write(latexTable.replaceAll("INDICATOR", "Spread")); GDWriter.write(latexTable.replaceAll("INDICATOR", "GD")); coverageWriter.write(latexTable.replaceAll("INDICATOR", "Coverage")); String bestHeuristicIGD = "NULL"; String bestHeuristicGD = "NULL"; String bestHeuristicSpread = "NULL"; String bestHeuristicCoverage = "NULL"; getBest: { double bestMeanIGD = Double.POSITIVE_INFINITY; double bestMeanGD = Double.POSITIVE_INFINITY; double bestMeanSpread = Double.NEGATIVE_INFINITY; double bestMeanCoverage = Double.NEGATIVE_INFINITY; for (String heuristic : igdMap.keySet()) { double heuristicIGD = igdMap.get(heuristic); double heuristicGD = gdMap.get(heuristic); double heuristicSpread = spreadMap.get(heuristic); double heuristicCoverage = coverageMap.get(heuristic); if (heuristicIGD < bestMeanIGD) { bestMeanIGD = heuristicIGD; bestHeuristicIGD = heuristic; } if (heuristicGD < bestMeanGD) { bestMeanGD = heuristicGD; bestHeuristicGD = heuristic; } if (heuristicSpread > bestMeanSpread) { bestMeanSpread = heuristicSpread; bestHeuristicSpread = heuristic; } if (heuristicCoverage > bestMeanCoverage) { bestMeanCoverage = heuristicCoverage; bestHeuristicCoverage = heuristic; } } } StringBuilder igdBuilder = new StringBuilder(); StringBuilder gdBuilder = new StringBuilder(); StringBuilder spreadBuilder = new StringBuilder(); StringBuilder coverageBuilder = new StringBuilder(); String[] newHeuristicFunctions = new String[heuristicFunctions.length * algorithms.length + algorithms.length]; fulfillNewHeuristics: { int i = 0; for (String algorithm : algorithms) { newHeuristicFunctions[i++] = algorithm; for (String heuristicFunction : heuristicFunctions) { newHeuristicFunctions[i++] = algorithm + "-" + heuristicFunction; } } } for (String heuristic : newHeuristicFunctions) { igdBuilder.append(" & "); boolean bold = heuristic.equals(bestHeuristicIGD) || igdMap.get(heuristic).equals(igdMap.get(bestHeuristicIGD)); if (bold) { igdBuilder.append("\\textbf{"); } igdBuilder.append(decimalFormatter.format(igdMap.get(heuristic))); if (bold) { igdBuilder.append("}"); } gdBuilder.append(" & "); bold = heuristic.equals(bestHeuristicGD) || gdMap.get(heuristic).equals(gdMap.get(bestHeuristicGD)); if (bold) { gdBuilder.append("\\textbf{"); } gdBuilder.append(decimalFormatter.format(gdMap.get(heuristic))); if (bold) { gdBuilder.append("}"); } spreadBuilder.append(" & "); bold = heuristic.equals(bestHeuristicSpread) || spreadMap.get(heuristic).equals(spreadMap.get(bestHeuristicSpread)); if (bold) { spreadBuilder.append("\\textbf{"); } spreadBuilder.append(decimalFormatter.format(spreadMap.get(heuristic))); if (bold) { spreadBuilder.append("}"); } coverageBuilder.append(" & "); bold = heuristic.equals(bestHeuristicCoverage) || coverageMap.get(heuristic).equals(coverageMap.get(bestHeuristicCoverage)); if (bold) { coverageBuilder.append("\\textbf{"); } coverageBuilder.append(decimalFormatter.format(coverageMap.get(heuristic))); if (bold) { coverageBuilder.append("}"); } } IGDWriter.write(igdBuilder + "\\\\\n"); spreadWriter.write(spreadBuilder + "\\\\\n"); GDWriter.write(gdBuilder + "\\\\\n"); coverageWriter.write(coverageBuilder + "\\\\\n"); } latexTableBuilder = new StringBuilder(); latexTableBuilder.append("\t\t\\bottomrule\n").append("\t\\end{tabulary}\n") .append("\\end{table}\n\n"); } averages: { latexTableBuilder.append("\\begin{table}[!htb]\n").append("\t\\centering\n") .append("\t\\def\\arraystretch{1.5}\n") // .append("\t\\setlength{\\tabcolsep}{10pt}\n") // .append("\t\\fontsize{8pt}{10pt}\\selectfont\n") .append("\t\\caption{INDICATOR averages found for ").append(objectives) .append(" objectives}\n").append("\t\\label{tab:INDICATOR ").append(objectives) .append(" objectives}\n").append("\t\\begin{tabulary}{\\linewidth}{c"); for (String algorithm : algorithms) { latexTableBuilder.append("c"); for (String heuristicFunction : heuristicFunctions) { latexTableBuilder.append("c"); } } latexTableBuilder.append("}\n").append("\t\t\\toprule\n").append("\t\t\\textbf{System}"); for (String algorithm : algorithms) { latexTableBuilder.append(" & \\textbf{").append(algorithm).append("}"); for (String heuristicFunction : heuristicFunctions) { latexTableBuilder.append(" & \\textbf{").append(algorithm).append("-") .append(heuristicFunction).append("}"); } } latexTableBuilder.append("\\\\\n").append("\t\t\\midrule\n"); for (String problem : problems) { NonDominatedSolutionList trueFront = new NonDominatedSolutionList(); pfTrueComposing: { for (String algorithm : algorithms) { SolutionSet mecbaFront = metricsUtil.readNonDominatedSolutionSet( "resultado/" + algorithm.toLowerCase().replaceAll("-", "") + "/" + problem + "_Comb_" + objectives + "obj/All_FUN_" + algorithm.toLowerCase().replaceAll("-", "") + "-" + problem); trueFront.addAll(mecbaFront); for (String hyperHeuristic : heuristicFunctions) { SolutionSet front = metricsUtil.readNonDominatedSolutionSet( "experiment/" + algorithm + "/" + objectives + "objectives/" + hyperHeuristic + "/" + problem + "/FUN.txt"); trueFront.addAll(front); } } } double[][] trueFrontMatrix = trueFront.writeObjectivesToMatrix(); HashMap<String, double[]> igdMap = new HashMap<>(); HashMap<String, double[]> gdMap = new HashMap<>(); HashMap<String, double[]> spreadMap = new HashMap<>(); HashMap<String, double[]> coverageMap = new HashMap<>(); mocaito: { for (String algorithm : algorithms) { double[] mecbaIGDs = new double[EXECUTIONS]; double[] mecbaGDs = new double[EXECUTIONS]; double[] mecbaSpreads = new double[EXECUTIONS]; double[] mecbaCoverages = new double[EXECUTIONS]; for (int i = 0; i < EXECUTIONS; i++) { double[][] mecbaFront = metricsUtil.readFront("resultado/" + algorithm.toLowerCase().replaceAll("-", "") + "/" + problem + "_Comb_" + objectives + "obj/FUN_" + algorithm.toLowerCase().replaceAll("-", "") + "-" + problem + "-" + i + ".NaoDominadas"); mecbaIGDs[i] = igd.invertedGenerationalDistance(mecbaFront, trueFrontMatrix, objectives); mecbaGDs[i] = gd.generationalDistance(mecbaFront, trueFrontMatrix, objectives); mecbaSpreads[i] = spread.spread(mecbaFront, trueFrontMatrix, objectives); mecbaCoverages[i] = coverage.coverage(mecbaFront, trueFrontMatrix); } igdMap.put(algorithm, mecbaIGDs); gdMap.put(algorithm, mecbaGDs); spreadMap.put(algorithm, mecbaSpreads); coverageMap.put(algorithm, mecbaCoverages); } } for (String algorithm : algorithms) { for (String heuristic : heuristicFunctions) { double[] hhIGDs = new double[EXECUTIONS]; double[] hhGDs = new double[EXECUTIONS]; double[] hhSpreads = new double[EXECUTIONS]; double[] hhCoverages = new double[EXECUTIONS]; for (int i = 0; i < EXECUTIONS; i++) { double[][] hhFront = metricsUtil .readFront("experiment/" + algorithm + "/" + objectives + "objectives/" + heuristic + "/" + problem + "/EXECUTION_" + i + "/FUN.txt"); hhIGDs[i] = igd.invertedGenerationalDistance(hhFront, trueFrontMatrix, objectives); hhGDs[i] = gd.generationalDistance(hhFront, trueFrontMatrix, objectives); hhSpreads[i] = spread.spread(hhFront, trueFrontMatrix, objectives); hhCoverages[i] = coverage.coverage(hhFront, trueFrontMatrix); } igdMap.put(algorithm + "-" + heuristic, hhIGDs); gdMap.put(algorithm + "-" + heuristic, hhGDs); spreadMap.put(algorithm + "-" + heuristic, hhSpreads); coverageMap.put(algorithm + "-" + heuristic, hhCoverages); } } HashMap<String, HashMap<String, Boolean>> igdResult = KruskalWallisTest.test(igdMap); HashMap<String, HashMap<String, Boolean>> gdResult = KruskalWallisTest.test(gdMap); HashMap<String, HashMap<String, Boolean>> spreadResult = KruskalWallisTest.test(spreadMap); HashMap<String, HashMap<String, Boolean>> coverageResult = KruskalWallisTest .test(coverageMap); latexTableBuilder.append("\t\t").append(problem); String latexTable = latexTableBuilder.toString(); latexTable = latexTable.replaceAll("O[OA]\\_", "").replaceAll("ChoiceFunction", "CF") .replaceAll("MultiArmedBandit", "MAB"); IGDWriter.write(latexTable.replaceAll("INDICATOR", "IGD")); spreadWriter.write(latexTable.replaceAll("INDICATOR", "Spread")); GDWriter.write(latexTable.replaceAll("INDICATOR", "GD")); coverageWriter.write(latexTable.replaceAll("INDICATOR", "Coverage")); latexTableBuilder = new StringBuilder(); String bestHeuristicIGD = "NULL"; String bestHeuristicGD = "NULL"; String bestHeuristicSpread = "NULL"; String bestHeuristicCoverage = "NULL"; getBest: { double bestMeanIGD = Double.POSITIVE_INFINITY; double bestMeanGD = Double.POSITIVE_INFINITY; double bestMeanSpread = Double.NEGATIVE_INFINITY; double bestMeanCoverage = Double.NEGATIVE_INFINITY; for (String heuristic : igdMap.keySet()) { double heuristicMeanIGD = mean.evaluate(igdMap.get(heuristic)); double heuristicMeanGD = mean.evaluate(gdMap.get(heuristic)); double heuristicMeanSpread = mean.evaluate(spreadMap.get(heuristic)); double heuristicMeanCoverage = mean.evaluate(coverageMap.get(heuristic)); if (heuristicMeanIGD < bestMeanIGD) { bestMeanIGD = heuristicMeanIGD; bestHeuristicIGD = heuristic; } if (heuristicMeanGD < bestMeanGD) { bestMeanGD = heuristicMeanGD; bestHeuristicGD = heuristic; } if (heuristicMeanSpread > bestMeanSpread) { bestMeanSpread = heuristicMeanSpread; bestHeuristicSpread = heuristic; } if (heuristicMeanCoverage > bestMeanCoverage) { bestMeanCoverage = heuristicMeanCoverage; bestHeuristicCoverage = heuristic; } } } StringBuilder igdBuilder = new StringBuilder(); StringBuilder gdBuilder = new StringBuilder(); StringBuilder spreadBuilder = new StringBuilder(); StringBuilder coverageBuilder = new StringBuilder(); String[] newHeuristicFunctions = new String[heuristicFunctions.length * algorithms.length + algorithms.length]; fulfillNewHeuristics: { int i = 0; for (String algorithm : algorithms) { newHeuristicFunctions[i++] = algorithm; for (String heuristicFunction : heuristicFunctions) { newHeuristicFunctions[i++] = algorithm + "-" + heuristicFunction; } } } for (String heuristic : newHeuristicFunctions) { igdBuilder.append(" & "); boolean bold = heuristic.equals(bestHeuristicIGD) || !igdResult.get(heuristic).get(bestHeuristicIGD); if (bold) { igdBuilder.append("\\textbf{"); } igdBuilder.append(decimalFormatter.format(mean.evaluate(igdMap.get(heuristic))) + " (" + decimalFormatter.format(standardDeviation.evaluate(igdMap.get(heuristic))) + ")"); if (bold) { igdBuilder.append("}"); } gdBuilder.append(" & "); bold = heuristic.equals(bestHeuristicGD) || !gdResult.get(heuristic).get(bestHeuristicGD); if (bold) { gdBuilder.append("\\textbf{"); } gdBuilder.append(decimalFormatter.format(mean.evaluate(gdMap.get(heuristic))) + " (" + decimalFormatter.format(standardDeviation.evaluate(gdMap.get(heuristic))) + ")"); if (bold) { gdBuilder.append("}"); } spreadBuilder.append(" & "); bold = heuristic.equals(bestHeuristicSpread) || !spreadResult.get(heuristic).get(bestHeuristicSpread); if (bold) { spreadBuilder.append("\\textbf{"); } spreadBuilder.append(decimalFormatter.format(mean.evaluate(spreadMap.get(heuristic))) + " (" + decimalFormatter.format(standardDeviation.evaluate(spreadMap.get(heuristic))) + ")"); if (bold) { spreadBuilder.append("}"); } coverageBuilder.append(" & "); bold = heuristic.equals(bestHeuristicCoverage) || !coverageResult.get(heuristic).get(bestHeuristicCoverage); if (bold) { coverageBuilder.append("\\textbf{"); } coverageBuilder .append(decimalFormatter.format(mean.evaluate(coverageMap.get(heuristic)))) .append(" (") .append(decimalFormatter .format(standardDeviation.evaluate(coverageMap.get(heuristic)))) .append(")"); if (bold) { coverageBuilder.append("}"); } } IGDWriter.write(igdBuilder + "\\\\\n"); spreadWriter.write(spreadBuilder + "\\\\\n"); GDWriter.write(gdBuilder + "\\\\\n"); coverageWriter.write(coverageBuilder + "\\\\\n"); } latexTableBuilder.append("\t\t\\bottomrule\n").append("\t\\end{tabulary}\n") .append("\\end{table}\n\n"); } latexTableBuilder.append("\\end{landscape}\n\n").append("\\end{document}"); String latexTable = latexTableBuilder.toString(); IGDWriter.write(latexTable); spreadWriter.write(latexTable); GDWriter.write(latexTable); coverageWriter.write(latexTable); } } }
From source file:jp.ac.tohoku.ecei.sb.metabolomeqc.basiccorrector.helper.CoefficientOfVariation.java
public static double evaluate(double[] values) { double mean = DoubleStream.of(values).sum() / values.length; StandardDeviation standardDeviation = new StandardDeviation(); double sd = standardDeviation.evaluate(values, mean); return sd / mean; }
From source file:com.facebook.presto.benchmark.driver.Stat.java
public Stat(double[] values) { mean = new Mean().evaluate(values); standardDeviation = new StandardDeviation().evaluate(values); median = new Median().evaluate(values); }
From source file:com.itemanalysis.psychometrics.statistics.Bootstrap.java
public Bootstrap(double lower, double upper) { this.lower = lower; this.upper = upper; percentile = new Percentile(); stdDev = new StandardDeviation(); }
From source file:com.biomeris.i2b2.export.engine.misc.ObservationAggregator.java
public ObservationAggregator() { super();/* w w w . ja va 2 s .c o m*/ mean = new Mean(); median = new Median(); standardDeviation = new StandardDeviation(); numericValues = new ArrayList<>(); stringValues = new ArrayList<>(); }
From source file:com.itemanalysis.psychometrics.polycor.PearsonCorrelation.java
public PearsonCorrelation() { covariance = new Covariance(); sdX = new StandardDeviation(); sdY = new StandardDeviation(); }
From source file:com.itemanalysis.psychometrics.kernel.ScottsBandwidth.java
public double value() { StandardDeviation sd = new StandardDeviation(); double q3 = pcntl.evaluate(x, 75.0); double q1 = pcntl.evaluate(x, 25.0); double IQR = (q3 - q1) / 1.34; double s = sd.evaluate(x); double N = (double) x.length; double m = Math.min(s, IQR); return 1.06 * m * Math.pow(N, -1.0 / 5.0) * adjustmentFactor; }
From source file:com.cloudera.oryx.app.traffic.Endpoint.java
protected Endpoint(String path, double relativeProb) { Preconditions.checkArgument(relativeProb > 0.0); this.path = path; this.relativeProb = relativeProb; meanTimeMS = new Mean(); stdevTimeMS = new StandardDeviation(); }
From source file:com.itemanalysis.psychometrics.kernel.SimplePluginBandwidthTest.java
@Test public void testValue() throws Exception { System.out.print("SimplePluginBandwidthTest: "); StandardDeviation sd = new StandardDeviation(); for (int i = 0; i < x.length; i++) { sd.increment(x[i]);/*from ww w. j av a2s . c om*/ } SimplePluginBandwidth bw = new SimplePluginBandwidth(sd, 1.0); System.out.println(bw.value()); assertEquals("Reference bandwidth test", 6.09603513572289, bw.value(), 1.0e-10); }