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

Introduction

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

Prototype

public double getPopulationVariance() 

Source Link

Document

Returns the <a href="http://en.wikibooks.org/wiki/Statistics/Summary/Variance"> population variance</a> of the available values.

Usage

From source file:com.github.jessemull.microflex.stat.statdouble.PopulationVarianceDoubleWeightsTest.java

/**
 * Tests the aggregated plate statistics method using a collection.
 *//*from  w  w w .  j a v a  2s .co  m*/
@Test
public void testAggregatedSetCollection() {

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

    for (PlateDouble plate : array) {
        collection.add(plate.dataSet());
    }

    Map<WellSetDouble, Double> aggregatedReturnedMap = variance.setsAggregated(collection, weights);
    Map<WellSetDouble, Double> aggregatedResultMap = new TreeMap<WellSetDouble, Double>();

    for (WellSetDouble set : collection) {

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

        for (WellDouble well : set) {

            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 aggregatedResult = statAggregated.getPopulationVariance();

        aggregatedResultMap.put(set, aggregatedResult);
    }

    for (WellSetDouble set : collection) {

        double result = Precision.round(aggregatedResultMap.get(set), precision);
        double returned = Precision.round(aggregatedReturnedMap.get(set), precision);

        assertTrue(result == returned);
    }
}

---

From source file:com.github.jessemull.microflex.stat.statinteger.PopulationVarianceIntegerWeightsTest.java

/**
 * Tests the aggregated plate statistics method.
 *//* w  w w . j  a  va2 s  .co  m*/
@Test
public void testAggregatedPlate() {

    for (PlateInteger plate : array) {

        List<BigDecimal> resultList = new ArrayList<BigDecimal>();
        double aggregatedReturned = Precision.round(variance.platesAggregated(plate, weights), precision);

        for (WellInteger 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 resultAggregated = Precision.round(statAggregated.getPopulationVariance(), precision);

        assertTrue(resultAggregated == aggregatedReturned);
    }
}

---

From source file:com.github.jessemull.microflex.stat.statinteger.PopulationVarianceIntegerWeightsTest.java

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

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

    List<PlateInteger> collection = Arrays.asList(arrayIndices);
    Map<PlateInteger, Double> aggregatedReturnedMap = variance.platesAggregated(collection, weightsIndices,
            begin, end - begin);

    Map<PlateInteger, Double> aggregatedResultMap = new TreeMap<PlateInteger, Double>();

    for (PlateInteger plate : collection) {

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

        for (WellInteger well : plate) {

            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 aggregatedResult = statAggregated.getPopulationVariance();

        aggregatedResultMap.put(plate, aggregatedResult);
    }

    for (PlateInteger plate : collection) {

        double result = Precision.round(aggregatedResultMap.get(plate), precision);
        double returned = Precision.round(aggregatedReturnedMap.get(plate), precision);

        assertTrue(result == returned);
    }
}

---

From source file:com.github.jessemull.microflex.stat.statinteger.PopulationVarianceIntegerWeightsTest.java

/**
 * Tests the aggregated plate statistics method using a collection.
 *///from  ww  w.  j av  a  2s.c  o  m
@Test
public void testAggregatedSetCollection() {

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

    for (PlateInteger plate : array) {
        collection.add(plate.dataSet());
    }

    Map<WellSetInteger, Double> aggregatedReturnedMap = variance.setsAggregated(collection, weights);
    Map<WellSetInteger, Double> aggregatedResultMap = new TreeMap<WellSetInteger, Double>();

    for (WellSetInteger set : collection) {

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

        for (WellInteger well : set) {

            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 aggregatedResult = statAggregated.getPopulationVariance();

        aggregatedResultMap.put(set, aggregatedResult);
    }

    for (WellSetInteger set : collection) {

        double result = Precision.round(aggregatedResultMap.get(set), precision);
        double returned = Precision.round(aggregatedReturnedMap.get(set), precision);

        assertTrue(result == returned);
    }
}

---

From source file:com.github.jessemull.microflexdouble.stat.PopulationVarianceWeightsTest.java

/**
 * Tests the aggregated plate statistics method.
 *//*from   w w w . ja v  a2 s.co m*/
@Test
public void testAggregatedSet() {

    for (Plate plate : array) {

        List<BigDecimal> resultList = new ArrayList<BigDecimal>();
        double aggregatedReturned = Precision.round(variance.setsAggregated(plate.dataSet(), weights),
                precision);

        for (Well 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 aggregatedResult = Precision.round(statAggregated.getPopulationVariance(), precision);

        assertTrue(aggregatedResult == aggregatedReturned);
    }
}

---

From source file:com.github.jessemull.microflexdouble.stat.PopulationVarianceWeightsTest.java

/**
 * Tests the aggregated plate statistics method using an array.
 *//* w  w  w.  j  av  a2 s  .c o m*/
@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, Double> aggregatedReturnedMap = variance.setsAggregated(setArray, weights);
    Map<WellSet, Double> aggregatedResultMap = new TreeMap<WellSet, Double>();

    for (WellSet set : setArray) {

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

        for (Well well : set) {

            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 aggregatedResult = statAggregated.getPopulationVariance();

        aggregatedResultMap.put(set, aggregatedResult);
    }

    for (WellSet set : setArray) {

        double result = Precision.round(aggregatedResultMap.get(set), precision);
        double returned = Precision.round(aggregatedReturnedMap.get(set), precision);

        assertTrue(result == returned);
    }

}

---

From source file:com.github.jessemull.microflex.stat.statdouble.PopulationVarianceDoubleWeightsTest.java

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

    for (PlateDouble plate : array) {

        List<BigDecimal> resultList = new ArrayList<BigDecimal>();
        double aggregatedReturned = Precision.round(variance.setsAggregated(plate.dataSet(), weights),
                precision);

        for (WellDouble 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 aggregatedResult = Precision.round(statAggregated.getPopulationVariance(), precision);

        assertTrue(aggregatedResult == aggregatedReturned);
    }
}

---

From source file:com.github.jessemull.microflex.stat.statdouble.PopulationVarianceDoubleWeightsTest.java

/**
 * Tests the aggregated plate statistics method using an array.
 *///ww  w.j  a va  2s .c  o  m
@Test
public void testAggregatedSetArray() {

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

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

    Map<WellSetDouble, Double> aggregatedReturnedMap = variance.setsAggregated(setArray, weights);
    Map<WellSetDouble, Double> aggregatedResultMap = new TreeMap<WellSetDouble, Double>();

    for (WellSetDouble set : setArray) {

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

        for (WellDouble well : set) {

            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 aggregatedResult = statAggregated.getPopulationVariance();

        aggregatedResultMap.put(set, aggregatedResult);
    }

    for (WellSetDouble set : setArray) {

        double result = Precision.round(aggregatedResultMap.get(set), precision);
        double returned = Precision.round(aggregatedReturnedMap.get(set), precision);

        assertTrue(result == returned);
    }

}

---

From source file:com.github.jessemull.microflex.stat.statinteger.PopulationVarianceIntegerWeightsTest.java

/**
 * Tests the aggregated plate statistics method.
 *///  w w  w.  jav a2  s . c o  m
@Test
public void testAggregatedSet() {

    for (PlateInteger plate : array) {

        List<BigDecimal> resultList = new ArrayList<BigDecimal>();
        double aggregatedReturned = Precision.round(variance.setsAggregated(plate.dataSet(), weights),
                precision);

        for (WellInteger 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 aggregatedResult = Precision.round(statAggregated.getPopulationVariance(), precision);

        assertTrue(aggregatedResult == aggregatedReturned);
    }
}

---

From source file:com.github.jessemull.microflex.stat.statinteger.PopulationVarianceIntegerWeightsTest.java

/**
 * Tests the aggregated plate statistics method using an array.
 */// ww w.j a v a 2  s .  co  m
@Test
public void testAggregatedSetArray() {

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

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

    Map<WellSetInteger, Double> aggregatedReturnedMap = variance.setsAggregated(setArray, weights);
    Map<WellSetInteger, Double> aggregatedResultMap = new TreeMap<WellSetInteger, Double>();

    for (WellSetInteger set : setArray) {

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

        for (WellInteger well : set) {

            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 aggregatedResult = statAggregated.getPopulationVariance();

        aggregatedResultMap.put(set, aggregatedResult);
    }

    for (WellSetInteger set : setArray) {

        double result = Precision.round(aggregatedResultMap.get(set), precision);
        double returned = Precision.round(aggregatedReturnedMap.get(set), precision);

        assertTrue(result == returned);
    }

}

---

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