Examples of org.apache.commons.math.stat.descriptive.moment.Mean.evaluate()

Package org.apache.commons.math.stat.descriptive.moment

Class org.apache.commons.math.stat.descriptive.moment.Mean

Examples of org.apache.commons.math.stat.descriptive.moment.Mean.evaluate()

org.apache.commons.math.stat.descriptive.moment.Mean.evaluate()
Returns the arithmetic mean of the entries in the specified portion of the input array, or Double.NaN if the designated subarray is empty.
Throws IllegalArgumentException if the array is null.

See {@link Mean} for details on the computing algorithm.
@param values the input array @param begin index of the first array element to include @param length the number of elements to include @return the mean of the values or Double.NaN if length = 0 @throws IllegalArgumentException if the array is null or the array indexparameters are not valid

                  LocalizedFormats.DIMENSIONS_MISMATCH_SIMPLE, length, yArray.length);
        } else if (length < 2) {
            throw MathRuntimeException.createIllegalArgumentException(
                  LocalizedFormats.INSUFFICIENT_DIMENSION, length, 2);
        } else {
            double xMean = mean.evaluate(xArray);
            double yMean = mean.evaluate(yArray);
            for (int i = 0; i < length; i++) {
                double xDev = xArray[i] - xMean;
                double yDev = yArray[i] - yMean;
                result += (xDev * yDev - result) / (i + 1);

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        } else if (length < 2) {
            throw MathRuntimeException.createIllegalArgumentException(
                  LocalizedFormats.INSUFFICIENT_DIMENSION, length, 2);
        } else {
            double xMean = mean.evaluate(xArray);
            double yMean = mean.evaluate(yArray);
            for (int i = 0; i < length; i++) {
                double xDev = xArray[i] - xMean;
                double yDev = yArray[i] - yMean;
                result += (xDev * yDev - result) / (i + 1);
            }

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      for(int j=0;j<chemScores.size();j++) cs[j] = chemScores.get(j);
      double [] ncs = new double[nonChemScores.size()];
      for(int j=0;j<nonChemScores.size();j++) ncs[j] = nonChemScores.get(j);
      double [] as = new double[allScores.size()];
      for(int j=0;j<allScores.size();j++) as[j] = allScores.get(j);
      System.out.println(mean.evaluate(cs) + "\t" + stdev.evaluate(cs));
      System.out.println(mean.evaluate(ncs) + "\t" + stdev.evaluate(ncs));
      cmeans.add(mean.evaluate(cs));
      cstdevs.add(stdev.evaluate(cs));
      ncmeans.add(mean.evaluate(ncs));
      ncstdevs.add(stdev.evaluate(ncs));

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      double [] ncs = new double[nonChemScores.size()];
      for(int j=0;j<nonChemScores.size();j++) ncs[j] = nonChemScores.get(j);
      double [] as = new double[allScores.size()];
      for(int j=0;j<allScores.size();j++) as[j] = allScores.get(j);
      System.out.println(mean.evaluate(cs) + "\t" + stdev.evaluate(cs));
      System.out.println(mean.evaluate(ncs) + "\t" + stdev.evaluate(ncs));
      cmeans.add(mean.evaluate(cs));
      cstdevs.add(stdev.evaluate(cs));
      ncmeans.add(mean.evaluate(ncs));
      ncstdevs.add(stdev.evaluate(ncs));
      System.out.println();

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      for(int j=0;j<nonChemScores.size();j++) ncs[j] = nonChemScores.get(j);
      double [] as = new double[allScores.size()];
      for(int j=0;j<allScores.size();j++) as[j] = allScores.get(j);
      System.out.println(mean.evaluate(cs) + "\t" + stdev.evaluate(cs));
      System.out.println(mean.evaluate(ncs) + "\t" + stdev.evaluate(ncs));
      cmeans.add(mean.evaluate(cs));
      cstdevs.add(stdev.evaluate(cs));
      ncmeans.add(mean.evaluate(ncs));
      ncstdevs.add(stdev.evaluate(ncs));
      System.out.println();
      ccount = cs.length;

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      for(int j=0;j<allScores.size();j++) as[j] = allScores.get(j);
      System.out.println(mean.evaluate(cs) + "\t" + stdev.evaluate(cs));
      System.out.println(mean.evaluate(ncs) + "\t" + stdev.evaluate(ncs));
      cmeans.add(mean.evaluate(cs));
      cstdevs.add(stdev.evaluate(cs));
      ncmeans.add(mean.evaluate(ncs));
      ncstdevs.add(stdev.evaluate(ncs));
      System.out.println();
      ccount = cs.length;
      nccount = ncs.length;
    }

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        throws IllegalArgumentException {
        Mean mean = new Mean();
        double result = 0d;
        int length = xArray.length;
        if(length == yArray.length && length > 1) {
            double xMean = mean.evaluate(xArray);
            double yMean = mean.evaluate(yArray);
            for (int i = 0; i < length; i++) {
                double xDev = xArray[i] - xMean;
                double yDev = yArray[i] - yMean;
                result += (xDev * yDev - result) / (i + 1);

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        Mean mean = new Mean();
        double result = 0d;
        int length = xArray.length;
        if(length == yArray.length && length > 1) {
            double xMean = mean.evaluate(xArray);
            double yMean = mean.evaluate(yArray);
            for (int i = 0; i < length; i++) {
                double xDev = xArray[i] - xMean;
                double yDev = yArray[i] - yMean;
                result += (xDev * yDev - result) / (i + 1);
            }

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        values[i++] = rc.doubleValue();
      }
      StandardDeviation stdDev = new StandardDeviation();
      Mean mean = new Mean();
      double std = stdDev.evaluate(values);
      double m = mean.evaluate(values);
      System.out.println("mean: " + m + " std dev: " + std);
      //Assert.assertTrue(std < 0.1 * m);
      assertEquals(31000, count);
    }
  }

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  }
  
  public static Double mean(double[] values)
  {
    Mean meanCalculator = new Mean();
    return meanCalculator.evaluate(values);
  }
  
  public static Double median(double[] values)
  {
    Median medianCalculator = new Median();

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