Example usage 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.microflex.stat.statinteger.SampleVarianceIntegerWeightsTest.java

/**
 * Tests the aggregated plate statistics method using the values between the indices of
 * the collection./*from   w  w  w  .j  a va2s.c  o  m*/
 */
@Test
public void testAggregatedSetCollectionIndices() {

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

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

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

    Map<WellSetInteger, Double> aggregatedReturnedMap = variance.setsAggregated(collection, weightsIndices,
            begin, end - begin);
    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().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.getVariance();

        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.microflex.stat.statinteger.SampleVarianceIntegerWeightsTest.java

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

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

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

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

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

    for (WellSetInteger set : setArrayIndices) {

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

        for (WellInteger 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 aggregatedResult = statAggregated.getVariance();

        aggregatedResultMap.put(set, aggregatedResult);
    }

    for (WellSetInteger plate : setArrayIndices) {

        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.microflexbigdecimal.stat.SampleVarianceTest.java

/**
 * Tests set calculation using indices./*from  w  w w .  java  2 s. c o m*/
 */
@Test
public void testSetIndices() {

    for (Plate plate : arrayIndices) {

        int size = arrayIndices[0].first().size();
        int begin = random.nextInt(size - 5);
        int end = (begin + 4) + random.nextInt(size - (begin + 4) + 1);

        Map<Well, BigDecimal> resultMap = new TreeMap<Well, BigDecimal>();
        Map<Well, BigDecimal> returnedMap = variance.set(plate.dataSet(), begin, end - begin, mc);

        for (Well well : plate) {

            double[] input = new double[well.size()];
            int index = 0;

            for (BigDecimal bd : well) {
                input[index++] = bd.doubleValue();
            }

            double[] inputArray = ArrayUtils.subarray(input, begin, end);

            DescriptiveStatistics stat = new DescriptiveStatistics(inputArray);
            double resultDouble = stat.getVariance();

            BigDecimal result = new BigDecimal(resultDouble);

            resultMap.put(well, result);
        }

        for (Well well : plate) {

            BigDecimal result = resultMap.get(well);
            BigDecimal returned = returnedMap.get(well);

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

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

---

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

/**
 * Tests the plate statistics method using the values between the indices.
 *///from  w w w . ja va2s  .  co  m
@Test
public void testPlateIndices() {

    for (Plate plate : arrayIndices) {

        int size = arrayIndices[0].first().size();
        int begin = random.nextInt(size - 5);
        int end = (begin + 4) + random.nextInt(size - (begin + 4) + 1);

        Map<Well, BigDecimal> resultMap = new TreeMap<Well, BigDecimal>();
        Map<Well, BigDecimal> returnedMap = variance.plate(plate, begin, end - begin, mc);

        for (Well well : plate) {

            double[] input = new double[well.size()];
            int index = 0;

            for (BigInteger bi : well) {
                input[index++] = bi.doubleValue();
            }

            double[] inputArray = ArrayUtils.subarray(input, begin, end);

            DescriptiveStatistics stat = new DescriptiveStatistics(inputArray);
            double resultDouble = stat.getVariance();

            BigDecimal result = new BigDecimal(resultDouble);

            resultMap.put(well, result);
        }

        for (Well well : plate) {

            BigDecimal result = resultMap.get(well);
            BigDecimal returned = returnedMap.get(well);

            BigDecimal[] corrected = correctRoundingErrors(result, returned);
            assertEquals(corrected[0], corrected[1]);
        }
    }
}

---

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

/**
 * Tests the aggregated plate statistics method using the values between the indices.
 *//*www  .  j  a  v a2s. co m*/
@Test
public void testAggregatedPlateIndices() {

    for (Plate plate : arrayIndices) {

        int begin = random.nextInt(plate.first().size() - 4);
        int end = begin + random.nextInt(3) + 3;

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

        for (Well 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 resultAggregated = Precision.round(statAggregated.getVariance(), precision);

        assertTrue(resultAggregated == aggregatedReturned);
    }
}

---

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

/**
 * Tests the aggregated plate statistics method using the values between the indices.
 *//*www. j a  v a  2s . c om*/
@Test
public void testAggregatedSetIndices() {

    for (Plate plate : arrayIndices) {

        int begin = random.nextInt(plate.first().size() - 4);
        int end = begin + random.nextInt(3) + 3;

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

        for (Well 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 resultAggregated = Precision.round(statAggregated.getVariance(), precision);

        assertTrue(resultAggregated == aggregatedReturned);
    }
}

---

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

/**
 * Tests the aggregated plate statistics method using the values between the indices of
 * the collection.//from  w w w .j  a v  a2  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, Double> aggregatedReturnedMap = variance.setsAggregated(collection, weightsIndices, begin,
            end - begin);
    Map<WellSet, Double> aggregatedResultMap = new TreeMap<WellSet, Double>();

    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 aggregatedResult = statAggregated.getVariance();

        aggregatedResultMap.put(set, aggregatedResult);
    }

    for (WellSet 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.SampleVarianceWeightsTest.java

/**
 * Tests the aggregated plate statistics method using the values between the indices of
 * the array./*  w  w  w . jav a2  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, Double> aggregatedReturnedMap = variance.setsAggregated(setArrayIndices, weightsIndices, begin,
            end - begin);
    Map<WellSet, Double> aggregatedResultMap = new TreeMap<WellSet, Double>();

    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 aggregatedResult = statAggregated.getVariance();

        aggregatedResultMap.put(set, aggregatedResult);
    }

    for (WellSet plate : setArrayIndices) {

        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.statbiginteger.SampleVarianceBigIntegerTest.java

/**
 * Tests the plate statistics method using the values between the indices.
 *//*from w  w  w. ja va2  s  .  com*/
@Test
public void testPlateIndices() {

    for (PlateBigInteger plate : arrayIndices) {

        int size = arrayIndices[0].first().size();
        int begin = random.nextInt(size - 5);
        int end = (begin + 4) + random.nextInt(size - (begin + 4) + 1);

        Map<WellBigInteger, BigDecimal> resultMap = new TreeMap<WellBigInteger, BigDecimal>();
        Map<WellBigInteger, BigDecimal> returnedMap = variance.plate(plate, begin, end - begin, mc);

        for (WellBigInteger well : plate) {

            double[] input = new double[well.size()];
            int index = 0;

            for (BigInteger bi : well) {
                input[index++] = bi.doubleValue();
            }

            double[] inputArray = ArrayUtils.subarray(input, begin, end);

            DescriptiveStatistics stat = new DescriptiveStatistics(inputArray);
            double resultDouble = stat.getVariance();

            BigDecimal result = new BigDecimal(resultDouble);

            resultMap.put(well, result);
        }

        for (WellBigInteger well : plate) {

            BigDecimal result = resultMap.get(well);
            BigDecimal returned = returnedMap.get(well);

            BigDecimal[] corrected = correctRoundingErrors(result, returned);
            assertEquals(corrected[0], corrected[1]);
        }
    }
}

---

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

/**
 * Tests the aggregated plate statistics method using the values between the indices.
 *//*from ww  w . j a v a2  s  .c o m*/
@Test
public void testAggregatedPlateIndices() {

    for (PlateDouble plate : arrayIndices) {

        int begin = random.nextInt(plate.first().size() - 4);
        int end = begin + random.nextInt(3) + 3;

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

        for (WellDouble 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 resultAggregated = Precision.round(statAggregated.getVariance(), precision);

        assertTrue(resultAggregated == aggregatedReturned);
    }
}

---

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