Example usage for org.apache.commons.math3.stat.descriptive DescriptiveStatistics getVariance

List of usage examples for org.apache.commons.math3.stat.descriptive DescriptiveStatistics getVariance

Introduction

In this page you can find the example usage for org.apache.commons.math3.stat.descriptive DescriptiveStatistics getVariance.

Prototype

public double getVariance() 

Source Link

Document

Returns the (sample) variance of the available values.

Usage

From source file:com.github.jessemull.microflexbigdecimal.stat.SampleVarianceWeightsTest.java

/**
 * Tests the aggregated plate statistics method using an array.
 *///from w w  w  . j  ava  2 s  . com
@Test
public void testAggregatedSetArray() {

    WellSet[] setArray = new WellSet[array.length];

    for (int i = 0; i < setArray.length; i++) {
        setArray[i] = array[i].dataSet();
    }

    Map<WellSet, BigDecimal> aggregatedReturnedMap = variance.setsAggregated(setArray, weights, mc);
    Map<WellSet, BigDecimal> aggregatedResultMap = new TreeMap<WellSet, BigDecimal>();

    for (WellSet set : setArray) {

        List<BigDecimal> resultList = new ArrayList<BigDecimal>();

        for (Well well : set) {

            List<BigDecimal> input = well.data();

            for (int i = 0; i < input.size(); i++) {
                resultList.add(input.get(i).multiply(new BigDecimal(weights[i])));
            }

        }

        double[] inputAggregated = new double[resultList.size()];

        for (int i = 0; i < resultList.size(); i++) {
            inputAggregated[i] = resultList.get(i).doubleValue();
        }

        DescriptiveStatistics statAggregated = new DescriptiveStatistics(inputAggregated);
        double resultAggregatedDouble = statAggregated.getVariance();

        BigDecimal aggregatedResult = new BigDecimal(resultAggregatedDouble, mc);
        aggregatedResultMap.put(set, aggregatedResult);
    }

    for (WellSet set : setArray) {

        BigDecimal result = aggregatedResultMap.get(set);
        BigDecimal returned = aggregatedReturnedMap.get(set);

        BigDecimal[] corrected = correctRoundingErrors(result, returned);

        assertEquals(corrected[0], corrected[1]);
    }

}

From source file:com.github.jessemull.microflexbiginteger.stat.SampleVarianceWeightsTest.java

/**
 * Tests the aggregated plate statistics method using the values between the indices of
 * the collection.//from www .  ja v  a2  s .c  om
 */
@Test
public void testAggregatedSetCollectionIndices() {

    int begin = random.nextInt(arrayIndices[0].first().size() - 4);
    int end = begin + random.nextInt(3) + 3;

    List<WellSet> collection = new ArrayList<WellSet>();

    for (Plate plate : arrayIndices) {
        collection.add(plate.dataSet());
    }

    Map<WellSet, BigDecimal> aggregatedReturnedMap = variance.setsAggregated(collection, weightsIndices, begin,
            end - begin, mc);
    Map<WellSet, BigDecimal> aggregatedResultMap = new TreeMap<WellSet, BigDecimal>();

    for (WellSet set : collection) {

        List<BigDecimal> resultList = new ArrayList<BigDecimal>();

        for (Well well : set) {

            List<BigDecimal> input = well.toBigDecimal().subList(begin, end);

            for (int i = 0; i < input.size(); i++) {
                resultList.add(input.get(i).multiply(new BigDecimal(weightsIndices[i])));
            }

        }

        double[] inputAggregated = new double[resultList.size()];

        for (int i = 0; i < resultList.size(); i++) {
            inputAggregated[i] = resultList.get(i).doubleValue();
        }

        DescriptiveStatistics statAggregated = new DescriptiveStatistics(inputAggregated);
        double resultAggregatedDouble = statAggregated.getVariance();

        BigDecimal aggregatedResult = new BigDecimal(resultAggregatedDouble, mc);
        aggregatedResultMap.put(set, aggregatedResult);
    }

    for (WellSet set : collection) {

        BigDecimal result = aggregatedResultMap.get(set);
        BigDecimal returned = aggregatedReturnedMap.get(set);
        BigDecimal[] corrected = correctRoundingErrors(result, returned);

        assertEquals(corrected[0], corrected[1]);
    }
}

From source file:com.github.jessemull.microflex.stat.statbiginteger.SampleVarianceBigIntegerWeightsTest.java

/**
 * Tests the aggregated plate statistics method using the values between the indices of
 * the array.//from   w  ww .  j a  v a 2s  .  c om
 */
@Test
public void testAggregatedSetArrayIndices() {

    int begin = random.nextInt(arrayIndices[0].first().size() - 4);
    int end = begin + random.nextInt(3) + 3;

    WellSetBigInteger[] setArrayIndices = new WellSetBigInteger[arrayIndices.length];

    for (int i = 0; i < setArrayIndices.length; i++) {
        setArrayIndices[i] = arrayIndices[i].dataSet();
    }

    Map<WellSetBigInteger, BigDecimal> aggregatedReturnedMap = variance.setsAggregated(setArrayIndices,
            weightsIndices, begin, end - begin, mc);
    Map<WellSetBigInteger, BigDecimal> aggregatedResultMap = new TreeMap<WellSetBigInteger, BigDecimal>();

    for (WellSetBigInteger set : setArrayIndices) {

        List<BigDecimal> resultList = new ArrayList<BigDecimal>();

        for (WellBigInteger well : set) {

            List<BigDecimal> input = well.toBigDecimal().subList(begin, end);

            for (int i = 0; i < input.size(); i++) {
                resultList.add(input.get(i).multiply(new BigDecimal(weightsIndices[i])));
            }

        }

        double[] inputAggregated = new double[resultList.size()];

        for (int i = 0; i < resultList.size(); i++) {
            inputAggregated[i] = resultList.get(i).doubleValue();
        }

        DescriptiveStatistics statAggregated = new DescriptiveStatistics(inputAggregated);
        double resultAggregatedDouble = statAggregated.getVariance();

        BigDecimal aggregatedResult = new BigDecimal(resultAggregatedDouble, mc);

        aggregatedResultMap.put(set, aggregatedResult);
    }

    for (WellSetBigInteger plate : setArrayIndices) {

        BigDecimal result = aggregatedResultMap.get(plate);
        BigDecimal returned = aggregatedReturnedMap.get(plate);
        BigDecimal[] corrected = correctRoundingErrors(result, returned);

        assertEquals(corrected[0], corrected[1]);
    }
}

From source file:com.github.jessemull.microflexbiginteger.stat.SampleVarianceWeightsTest.java

/**
 * Tests the aggregated plate statistics method using the values between the indices of
 * the array./* w w  w . ja v a 2  s.c  o m*/
 */
@Test
public void testAggregatedSetArrayIndices() {

    int begin = random.nextInt(arrayIndices[0].first().size() - 4);
    int end = begin + random.nextInt(3) + 3;

    WellSet[] setArrayIndices = new WellSet[arrayIndices.length];

    for (int i = 0; i < setArrayIndices.length; i++) {
        setArrayIndices[i] = arrayIndices[i].dataSet();
    }

    Map<WellSet, BigDecimal> aggregatedReturnedMap = variance.setsAggregated(setArrayIndices, weightsIndices,
            begin, end - begin, mc);
    Map<WellSet, BigDecimal> aggregatedResultMap = new TreeMap<WellSet, BigDecimal>();

    for (WellSet set : setArrayIndices) {

        List<BigDecimal> resultList = new ArrayList<BigDecimal>();

        for (Well well : set) {

            List<BigDecimal> input = well.toBigDecimal().subList(begin, end);

            for (int i = 0; i < input.size(); i++) {
                resultList.add(input.get(i).multiply(new BigDecimal(weightsIndices[i])));
            }

        }

        double[] inputAggregated = new double[resultList.size()];

        for (int i = 0; i < resultList.size(); i++) {
            inputAggregated[i] = resultList.get(i).doubleValue();
        }

        DescriptiveStatistics statAggregated = new DescriptiveStatistics(inputAggregated);
        double resultAggregatedDouble = statAggregated.getVariance();

        BigDecimal aggregatedResult = new BigDecimal(resultAggregatedDouble, mc);

        aggregatedResultMap.put(set, aggregatedResult);
    }

    for (WellSet plate : setArrayIndices) {

        BigDecimal result = aggregatedResultMap.get(plate);
        BigDecimal returned = aggregatedReturnedMap.get(plate);
        BigDecimal[] corrected = correctRoundingErrors(result, returned);

        assertEquals(corrected[0], corrected[1]);
    }
}

From source file:com.github.jessemull.microflex.stat.statbigdecimal.SampleVarianceBigDecimalWeightsTest.java

/**
 * Tests the aggregated plate statistics method using the values between the indices of
 * the collection./*from w w w  .  j ava 2s .  co m*/
 */
@Test
public void testAggregatedSetCollectionIndices() {

    int begin = random.nextInt(arrayIndices[0].first().size() - 4);
    int end = begin + random.nextInt(3) + 3;

    List<WellSetBigDecimal> collection = new ArrayList<WellSetBigDecimal>();

    for (PlateBigDecimal plate : arrayIndices) {
        collection.add(plate.dataSet());
    }

    Map<WellSetBigDecimal, BigDecimal> aggregatedReturnedMap = variance.setsAggregated(collection,
            weightsIndices, begin, end - begin, mc);
    Map<WellSetBigDecimal, BigDecimal> aggregatedResultMap = new TreeMap<WellSetBigDecimal, BigDecimal>();

    for (WellSetBigDecimal set : collection) {

        List<BigDecimal> resultList = new ArrayList<BigDecimal>();

        for (WellBigDecimal well : set) {

            List<BigDecimal> input = well.data().subList(begin, end);

            for (int i = 0; i < input.size(); i++) {
                resultList.add(input.get(i).multiply(new BigDecimal(weightsIndices[i])));
            }

        }

        double[] inputAggregated = new double[resultList.size()];

        for (int i = 0; i < resultList.size(); i++) {
            inputAggregated[i] = resultList.get(i).doubleValue();
        }

        DescriptiveStatistics statAggregated = new DescriptiveStatistics(inputAggregated);
        double resultAggregatedDouble = statAggregated.getVariance();

        BigDecimal aggregatedResult = new BigDecimal(resultAggregatedDouble, mc);
        aggregatedResultMap.put(set, aggregatedResult);
    }

    for (WellSetBigDecimal set : collection) {

        BigDecimal result = aggregatedResultMap.get(set);
        BigDecimal returned = aggregatedReturnedMap.get(set);
        BigDecimal[] corrected = correctRoundingErrors(result, returned);

        assertEquals(corrected[0], corrected[1]);
    }
}

From source file:com.github.jessemull.microflexbigdecimal.stat.SampleVarianceWeightsTest.java

/**
 * Tests the aggregated plate statistics method using the values between the indices of
 * the collection./*  ww w  .j  a v a  2  s  .  c  o  m*/
 */
@Test
public void testAggregatedSetCollectionIndices() {

    int begin = random.nextInt(arrayIndices[0].first().size() - 4);
    int end = begin + random.nextInt(3) + 3;

    List<WellSet> collection = new ArrayList<WellSet>();

    for (Plate plate : arrayIndices) {
        collection.add(plate.dataSet());
    }

    Map<WellSet, BigDecimal> aggregatedReturnedMap = variance.setsAggregated(collection, weightsIndices, begin,
            end - begin, mc);
    Map<WellSet, BigDecimal> aggregatedResultMap = new TreeMap<WellSet, BigDecimal>();

    for (WellSet set : collection) {

        List<BigDecimal> resultList = new ArrayList<BigDecimal>();

        for (Well well : set) {

            List<BigDecimal> input = well.data().subList(begin, end);

            for (int i = 0; i < input.size(); i++) {
                resultList.add(input.get(i).multiply(new BigDecimal(weightsIndices[i])));
            }

        }

        double[] inputAggregated = new double[resultList.size()];

        for (int i = 0; i < resultList.size(); i++) {
            inputAggregated[i] = resultList.get(i).doubleValue();
        }

        DescriptiveStatistics statAggregated = new DescriptiveStatistics(inputAggregated);
        double resultAggregatedDouble = statAggregated.getVariance();

        BigDecimal aggregatedResult = new BigDecimal(resultAggregatedDouble, mc);
        aggregatedResultMap.put(set, aggregatedResult);
    }

    for (WellSet set : collection) {

        BigDecimal result = aggregatedResultMap.get(set);
        BigDecimal returned = aggregatedReturnedMap.get(set);
        BigDecimal[] corrected = correctRoundingErrors(result, returned);

        assertEquals(corrected[0], corrected[1]);
    }
}

From source file:com.github.jessemull.microflex.stat.statbigdecimal.SampleVarianceBigDecimalWeightsTest.java

/**
 * Tests the aggregated plate statistics method using the values between the indices of
 * the array./*  w  ww .j ava  2  s.c o  m*/
 */
@Test
public void testAggregatedSetArrayIndices() {

    int begin = random.nextInt(arrayIndices[0].first().size() - 4);
    int end = begin + random.nextInt(3) + 3;

    WellSetBigDecimal[] setArrayIndices = new WellSetBigDecimal[arrayIndices.length];

    for (int i = 0; i < setArrayIndices.length; i++) {
        setArrayIndices[i] = arrayIndices[i].dataSet();
    }

    Map<WellSetBigDecimal, BigDecimal> aggregatedReturnedMap = variance.setsAggregated(setArrayIndices,
            weightsIndices, begin, end - begin, mc);
    Map<WellSetBigDecimal, BigDecimal> aggregatedResultMap = new TreeMap<WellSetBigDecimal, BigDecimal>();

    for (WellSetBigDecimal set : setArrayIndices) {

        List<BigDecimal> resultList = new ArrayList<BigDecimal>();

        for (WellBigDecimal well : set) {

            List<BigDecimal> input = well.data().subList(begin, end);

            for (int i = 0; i < input.size(); i++) {
                resultList.add(input.get(i).multiply(new BigDecimal(weightsIndices[i])));
            }

        }

        double[] inputAggregated = new double[resultList.size()];

        for (int i = 0; i < resultList.size(); i++) {
            inputAggregated[i] = resultList.get(i).doubleValue();
        }

        DescriptiveStatistics statAggregated = new DescriptiveStatistics(inputAggregated);
        double resultAggregatedDouble = statAggregated.getVariance();

        BigDecimal aggregatedResult = new BigDecimal(resultAggregatedDouble, mc);

        aggregatedResultMap.put(set, aggregatedResult);
    }

    for (WellSetBigDecimal plate : setArrayIndices) {

        BigDecimal result = aggregatedResultMap.get(plate);
        BigDecimal returned = aggregatedReturnedMap.get(plate);
        BigDecimal[] corrected = correctRoundingErrors(result, returned);

        assertEquals(corrected[0], corrected[1]);
    }
}

From source file:com.github.jessemull.microflexbigdecimal.stat.SampleVarianceWeightsTest.java

/**
 * Tests the aggregated plate statistics method using the values between the indices of
 * the array./*from  w ww  .  ja va2s .c o  m*/
 */
@Test
public void testAggregatedSetArrayIndices() {

    int begin = random.nextInt(arrayIndices[0].first().size() - 4);
    int end = begin + random.nextInt(3) + 3;

    WellSet[] setArrayIndices = new WellSet[arrayIndices.length];

    for (int i = 0; i < setArrayIndices.length; i++) {
        setArrayIndices[i] = arrayIndices[i].dataSet();
    }

    Map<WellSet, BigDecimal> aggregatedReturnedMap = variance.setsAggregated(setArrayIndices, weightsIndices,
            begin, end - begin, mc);
    Map<WellSet, BigDecimal> aggregatedResultMap = new TreeMap<WellSet, BigDecimal>();

    for (WellSet set : setArrayIndices) {

        List<BigDecimal> resultList = new ArrayList<BigDecimal>();

        for (Well well : set) {

            List<BigDecimal> input = well.data().subList(begin, end);

            for (int i = 0; i < input.size(); i++) {
                resultList.add(input.get(i).multiply(new BigDecimal(weightsIndices[i])));
            }

        }

        double[] inputAggregated = new double[resultList.size()];

        for (int i = 0; i < resultList.size(); i++) {
            inputAggregated[i] = resultList.get(i).doubleValue();
        }

        DescriptiveStatistics statAggregated = new DescriptiveStatistics(inputAggregated);
        double resultAggregatedDouble = statAggregated.getVariance();

        BigDecimal aggregatedResult = new BigDecimal(resultAggregatedDouble, mc);

        aggregatedResultMap.put(set, aggregatedResult);
    }

    for (WellSet plate : setArrayIndices) {

        BigDecimal result = aggregatedResultMap.get(plate);
        BigDecimal returned = aggregatedReturnedMap.get(plate);
        BigDecimal[] corrected = correctRoundingErrors(result, returned);

        assertEquals(corrected[0], corrected[1]);
    }
}

From source file:com.github.jessemull.microflex.stat.statbiginteger.PopulationVarianceBigIntegerWeightsTest.java

/**
 * Tests the aggregated plate statistics method.
 *//*from w  ww .j ava  2s. c  o  m*/
@Test
public void testAggregatedPlate() {

    for (PlateBigInteger plate : array) {

        List<BigDecimal> resultList = new ArrayList<BigDecimal>();
        BigDecimal aggregatedReturned = variance.platesAggregated(plate, weights, mc);

        for (WellBigInteger well : plate) {

            List<BigDecimal> input = well.toBigDecimal();

            for (int i = 0; i < input.size(); i++) {
                resultList.add(input.get(i).multiply(new BigDecimal(weights[i])));
            }

        }

        double[] inputAggregated = new double[resultList.size()];

        for (int i = 0; i < resultList.size(); i++) {
            inputAggregated[i] = resultList.get(i).doubleValue();
        }

        DescriptiveStatistics statAggregated = new DescriptiveStatistics(inputAggregated);
        double resultAggregatedDouble = statAggregated.getVariance();
        resultAggregatedDouble *= resultList.size() - 1;
        resultAggregatedDouble /= resultList.size();

        BigDecimal aggregatedResult = new BigDecimal(resultAggregatedDouble, mc);

        BigDecimal[] corrected = correctRoundingErrors(aggregatedResult, aggregatedReturned);
        assertEquals(corrected[0], corrected[1]);
    }
}

From source file:com.github.jessemull.microflex.stat.statbiginteger.PopulationVarianceBigIntegerWeightsTest.java

/**
 * Tests the aggregated plate statistics method.
 *///from   ww w . j a  v a 2 s  . c om
@Test
public void testAggregatedSet() {

    for (PlateBigInteger plate : array) {

        List<BigDecimal> resultList = new ArrayList<BigDecimal>();
        BigDecimal aggregatedReturned = variance.setsAggregated(plate.dataSet(), weights, mc);

        for (WellBigInteger well : plate) {

            List<BigDecimal> input = well.toBigDecimal();

            for (int i = 0; i < input.size(); i++) {
                resultList.add(input.get(i).multiply(new BigDecimal(weights[i])));
            }

        }

        double[] inputAggregated = new double[resultList.size()];

        for (int i = 0; i < resultList.size(); i++) {
            inputAggregated[i] = resultList.get(i).doubleValue();
        }

        DescriptiveStatistics statAggregated = new DescriptiveStatistics(inputAggregated);
        double resultAggregatedDouble = statAggregated.getVariance();
        resultAggregatedDouble *= resultList.size() - 1;
        resultAggregatedDouble /= resultList.size();

        BigDecimal aggregatedResult = new BigDecimal(resultAggregatedDouble, mc);

        BigDecimal[] corrected = correctRoundingErrors(aggregatedResult, aggregatedReturned);
        assertEquals(corrected[0], corrected[1]);
    }
}