Java tutorial
/** * Licensed to the Apache Software Foundation (ASF) under one * or more contributor license agreements. See the NOTICE file * distributed with this work for additional information * regarding copyright ownership. The ASF licenses this file * to you under the Apache License, Version 2.0 (the * "License"); you may not use this file except in compliance * with the License. You may obtain a copy of the License at * * http://www.apache.org/licenses/LICENSE-2.0 * * Unless required by applicable law or agreed to in writing, * software distributed under the License is distributed on an * "AS IS" BASIS, WITHOUT WARRANTIES OR CONDITIONS OF ANY * KIND, either express or implied. See the License for the * specific language governing permissions and limitations * under the License. */ /* -------------------------------- Package --------------------------------- */ package com.github.jessemull.microflex.stat.statbigdecimal; /* ------------------------------ Dependencies ------------------------------ */ import static org.junit.Assert.*; import java.io.OutputStream; import java.io.PrintStream; import java.math.BigDecimal; import java.math.MathContext; import java.math.RoundingMode; import java.util.ArrayList; import java.util.Arrays; import java.util.List; import java.util.TreeMap; import java.util.Map; import java.util.Random; import org.apache.commons.lang3.ArrayUtils; import org.apache.commons.math3.stat.descriptive.DescriptiveStatistics; import org.junit.AfterClass; import org.junit.BeforeClass; import org.junit.FixMethodOrder; import org.junit.Test; import org.junit.runners.MethodSorters; import com.github.jessemull.microflex.bigdecimalflex.plate.PlateBigDecimal; import com.github.jessemull.microflex.bigdecimalflex.plate.WellBigDecimal; import com.github.jessemull.microflex.bigdecimalflex.plate.WellSetBigDecimal; import com.github.jessemull.microflex.bigdecimalflex.stat.PopulationVarianceBigDecimal; import com.github.jessemull.microflex.util.RandomUtil; /** * This class tests the methods in the population variance big decimal class. * * @author Jesse L. Mull * @update Updated Oct 18, 2016 * @address http://www.jessemull.com * @email hello@jessemull.com */ @FixMethodOrder(MethodSorters.NAME_ASCENDING) public class PopulationVarianceBigDecimalWeightsTest { /* ---------------------------- Local Fields -----------------------------*/ /* Minimum and maximum values for random well and lists */ private static BigDecimal minValue = new BigDecimal(0); // Minimum big decimal value for wells private static BigDecimal maxValue = new BigDecimal(10); // Maximum big decimal value for wells private static Random random = new Random(); // Generates random integers private static MathContext mc = new MathContext(10, RoundingMode.HALF_DOWN); // The math context for input values private static MathContext contextWeights = new MathContext(2, RoundingMode.HALF_DOWN); // The math context for weights /* The addition operation */ private static PopulationVarianceBigDecimal variance = new PopulationVarianceBigDecimal(); /* Random objects and numbers for testing */ private static int rows = 5; private static int columns = 4; private static int length = 5; private static int lengthIndices = 10; private static int plateNumber = 10; private static int plateNumberIndices = 5; private static PlateBigDecimal[] array = new PlateBigDecimal[plateNumber]; private static PlateBigDecimal[] arrayIndices = new PlateBigDecimal[plateNumberIndices]; private static double[] weights = new double[length]; private static double[] weightsIndices = new double[lengthIndices]; /* Value of false redirects System.err */ private static boolean error = true; private static PrintStream originalOut = System.out; /** * Generates random objects and numbers for testing. */ @BeforeClass public static void setUp() { if (error) { System.setErr(new PrintStream(new OutputStream() { public void write(int x) { } })); } for (int j = 0; j < array.length; j++) { PlateBigDecimal plate = RandomUtil.randomPlateBigDecimal(rows, columns, minValue, maxValue, length, "Plate1-" + j); array[j] = plate; } for (int j = 0; j < arrayIndices.length; j++) { PlateBigDecimal plateIndices = RandomUtil.randomPlateBigDecimal(rows, columns, minValue, maxValue, lengthIndices, "Plate1-" + j); arrayIndices[j] = plateIndices; } for (int i = 0; i < weights.length; i++) { double randomDouble = random.nextDouble(); weights[i] = new BigDecimal(randomDouble + "", contextWeights).doubleValue(); } for (int i = 0; i < weightsIndices.length; i++) { double randomDouble = random.nextDouble(); weightsIndices[i] = new BigDecimal(randomDouble + "", contextWeights).doubleValue(); } } /** * Toggles system error. */ @AfterClass public static void restoreErrorOut() { System.setErr(originalOut); } /* ---------------- Well statistics for all plate wells ----------------- */ /** * Tests the plate statistics method. */ @Test public void testPlate() { for (PlateBigDecimal plate : array) { Map<WellBigDecimal, BigDecimal> resultMap = new TreeMap<WellBigDecimal, BigDecimal>(); Map<WellBigDecimal, BigDecimal> returnedMap = variance.plate(plate, weights, mc); for (WellBigDecimal well : plate) { double[] input = new double[well.size()]; int index = 0; for (BigDecimal bd : well) { input[index] = bd.doubleValue() * weights[index]; index++; } DescriptiveStatistics stat = new DescriptiveStatistics(input); double resultDouble = stat.getVariance(); resultDouble *= well.size() - 1; resultDouble /= well.size(); BigDecimal result = new BigDecimal(resultDouble, mc); resultMap.put(well, result); } for (WellBigDecimal well : plate) { BigDecimal result = resultMap.get(well); BigDecimal returned = returnedMap.get(well); BigDecimal[] corrected = correctRoundingErrors(result, returned); assertEquals(corrected[0], corrected[1]); } } } /** * Tests the plate statistics method using the values between the indices. */ @Test public void testPlateIndices() { for (PlateBigDecimal plate : arrayIndices) { int begin = random.nextInt(plate.first().size() - 4); int end = begin + random.nextInt(3) + 3; Map<WellBigDecimal, BigDecimal> resultMap = new TreeMap<WellBigDecimal, BigDecimal>(); Map<WellBigDecimal, BigDecimal> returnedMap = variance.plate(plate, ArrayUtils.subarray(weightsIndices, begin, end), begin, end - begin, mc); for (WellBigDecimal well : plate) { double[] input = new double[well.size()]; int index = 0; for (BigDecimal bd : well) { input[index] = bd.doubleValue() * weightsIndices[index]; index++; } DescriptiveStatistics stat = new DescriptiveStatistics(ArrayUtils.subarray(input, begin, end)); double resultDouble = stat.getPopulationVariance(); BigDecimal result = new BigDecimal(resultDouble, mc); resultMap.put(well, result); } for (WellBigDecimal well : plate) { BigDecimal result = resultMap.get(well); BigDecimal returned = returnedMap.get(well); BigDecimal[] corrected = correctRoundingErrors(result, returned); assertEquals(corrected[0], corrected[1]); } } } /* --------------------- Aggregated plate statistics ------------------- */ /** * Tests the aggregated plate statistics method. */ @Test public void testAggregatedPlate() { for (PlateBigDecimal plate : array) { List<BigDecimal> resultList = new ArrayList<BigDecimal>(); BigDecimal aggregatedReturned = variance.platesAggregated(plate, weights, mc); for (WellBigDecimal well : plate) { 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(); resultAggregatedDouble *= resultList.size() - 1; resultAggregatedDouble /= resultList.size(); BigDecimal aggregatedResult = new BigDecimal(resultAggregatedDouble, mc); BigDecimal[] corrected = correctRoundingErrors(aggregatedResult, aggregatedReturned); assertEquals(corrected[0], corrected[1]); } } /** * Tests the aggregated plate statistics method using a collection. */ @Test public void testAggregatedPlateCollection() { List<PlateBigDecimal> collection = Arrays.asList(array); Map<PlateBigDecimal, BigDecimal> aggregatedReturnedMap = variance.platesAggregated(collection, weights, mc); Map<PlateBigDecimal, BigDecimal> aggregatedResultMap = new TreeMap<PlateBigDecimal, BigDecimal>(); for (PlateBigDecimal plate : collection) { List<BigDecimal> resultList = new ArrayList<BigDecimal>(); for (WellBigDecimal well : plate) { 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(); resultAggregatedDouble *= resultList.size() - 1; resultAggregatedDouble /= resultList.size(); BigDecimal aggregatedResult = new BigDecimal(resultAggregatedDouble, mc); aggregatedResultMap.put(plate, aggregatedResult); } for (PlateBigDecimal plate : collection) { BigDecimal result = aggregatedResultMap.get(plate); BigDecimal returned = aggregatedReturnedMap.get(plate); BigDecimal[] corrected = correctRoundingErrors(result, returned); assertEquals(corrected[0], corrected[1]); } } /** * Tests the aggregated plate statistics method using an array. */ @Test public void testAggregatedPlateArray() { Map<PlateBigDecimal, BigDecimal> aggregatedReturnedMap = variance.platesAggregated(array, weights, mc); Map<PlateBigDecimal, BigDecimal> aggregatedResultMap = new TreeMap<PlateBigDecimal, BigDecimal>(); for (PlateBigDecimal plate : array) { List<BigDecimal> resultList = new ArrayList<BigDecimal>(); for (WellBigDecimal well : plate) { 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(); resultAggregatedDouble *= resultList.size() - 1; resultAggregatedDouble /= resultList.size(); BigDecimal aggregatedResult = new BigDecimal(resultAggregatedDouble, mc); aggregatedResultMap.put(plate, aggregatedResult); } for (PlateBigDecimal plate : array) { BigDecimal result = aggregatedResultMap.get(plate); BigDecimal returned = aggregatedReturnedMap.get(plate); BigDecimal[] corrected = correctRoundingErrors(result, returned); assertEquals(corrected[0], corrected[1]); } } /** * Tests the aggregated plate statistics method using the values between the indices. */ @Test public void testAggregatedPlateIndices() { for (PlateBigDecimal plate : arrayIndices) { int begin = random.nextInt(plate.first().size() - 4); int end = begin + random.nextInt(3) + 3; List<BigDecimal> resultList = new ArrayList<BigDecimal>(); BigDecimal aggregatedReturned = variance.platesAggregated(plate, weightsIndices, begin, end - begin, mc); for (WellBigDecimal well : plate) { 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(); resultAggregatedDouble *= resultList.size() - 1; resultAggregatedDouble /= resultList.size(); BigDecimal aggregatedResult = new BigDecimal(resultAggregatedDouble, mc); BigDecimal[] corrected = correctRoundingErrors(aggregatedResult, aggregatedReturned); assertEquals(corrected[0], corrected[1]); } } /** * Tests the aggregated plate statistics method using the values between the indices of * the collection. */ @Test public void testAggregatedPlateCollectionIndices() { int begin = random.nextInt(arrayIndices[0].first().size() - 4); int end = begin + random.nextInt(3) + 3; List<PlateBigDecimal> collection = Arrays.asList(arrayIndices); Map<PlateBigDecimal, BigDecimal> aggregatedReturnedMap = variance.platesAggregated(collection, weightsIndices, begin, end - begin, mc); Map<PlateBigDecimal, BigDecimal> aggregatedResultMap = new TreeMap<PlateBigDecimal, BigDecimal>(); for (PlateBigDecimal plate : collection) { List<BigDecimal> resultList = new ArrayList<BigDecimal>(); for (WellBigDecimal well : plate) { 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(); resultAggregatedDouble *= resultList.size() - 1; resultAggregatedDouble /= resultList.size(); BigDecimal aggregatedResult = new BigDecimal(resultAggregatedDouble, mc); aggregatedResultMap.put(plate, aggregatedResult); } for (PlateBigDecimal plate : collection) { BigDecimal result = aggregatedResultMap.get(plate); BigDecimal returned = aggregatedReturnedMap.get(plate); BigDecimal[] corrected = correctRoundingErrors(result, returned); assertEquals(corrected[0], corrected[1]); } } /** * Tests the aggregated plate statistics method using the values between the indices of * the array. */ @Test public void testAggregatedPlateArrayIndices() { int begin = random.nextInt(arrayIndices[0].first().size() - 4); int end = begin + random.nextInt(3) + 3; Map<PlateBigDecimal, BigDecimal> aggregatedReturnedMap = variance.platesAggregated(arrayIndices, weightsIndices, begin, end - begin, mc); Map<PlateBigDecimal, BigDecimal> aggregatedResultMap = new TreeMap<PlateBigDecimal, BigDecimal>(); for (PlateBigDecimal plate : arrayIndices) { List<BigDecimal> resultList = new ArrayList<BigDecimal>(); for (WellBigDecimal well : plate) { 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(); resultAggregatedDouble *= resultList.size() - 1; resultAggregatedDouble /= resultList.size(); BigDecimal aggregatedResult = new BigDecimal(resultAggregatedDouble, mc); aggregatedResultMap.put(plate, aggregatedResult); } for (PlateBigDecimal plate : arrayIndices) { BigDecimal result = aggregatedResultMap.get(plate); BigDecimal returned = aggregatedReturnedMap.get(plate); BigDecimal[] corrected = correctRoundingErrors(result, returned); assertEquals(corrected[0], corrected[1]); } } /* --------------- Well statistics for all wells in a set -------------- */ /** * Tests set calculation. */ @Test public void testSet() { for (PlateBigDecimal plate : array) { Map<WellBigDecimal, BigDecimal> resultMap = new TreeMap<WellBigDecimal, BigDecimal>(); Map<WellBigDecimal, BigDecimal> returnedMap = variance.set(plate.dataSet(), weights, mc); for (WellBigDecimal well : plate) { double[] input = new double[well.size()]; int index = 0; for (BigDecimal bd : well) { input[index] = bd.doubleValue() * weights[index]; index++; } DescriptiveStatistics stat = new DescriptiveStatistics(input); double resultDouble = stat.getVariance(); resultDouble *= well.size() - 1; resultDouble /= well.size(); BigDecimal result = new BigDecimal(resultDouble, mc); resultMap.put(well, result); } for (WellBigDecimal well : plate) { BigDecimal result = resultMap.get(well); BigDecimal returned = returnedMap.get(well); BigDecimal[] corrected = correctRoundingErrors(result, returned); assertEquals(corrected[0], corrected[1]); } } } /** * Tests set calculation using indices. */ @Test public void testSetIndices() { for (PlateBigDecimal plate : arrayIndices) { int begin = random.nextInt(plate.first().size() - 4); int end = begin + random.nextInt(3) + 3; Map<WellBigDecimal, BigDecimal> resultMap = new TreeMap<WellBigDecimal, BigDecimal>(); Map<WellBigDecimal, BigDecimal> returnedMap = variance.set(plate.dataSet(), ArrayUtils.subarray(weightsIndices, begin, end), begin, end - begin, mc); for (WellBigDecimal well : plate) { double[] input = new double[well.size()]; int index = 0; for (BigDecimal bd : well) { input[index] = bd.doubleValue() * weightsIndices[index]; index++; } DescriptiveStatistics stat = new DescriptiveStatistics(ArrayUtils.subarray(input, begin, end)); double resultDouble = stat.getPopulationVariance(); BigDecimal result = new BigDecimal(resultDouble, mc); resultMap.put(well, result); } for (WellBigDecimal well : plate) { BigDecimal result = resultMap.get(well); BigDecimal returned = returnedMap.get(well); BigDecimal[] corrected = correctRoundingErrors(result, returned); assertEquals(corrected[0], corrected[1]); } } } /* ---------------------- Aggregated set statistics -------------------- */ /** * Tests the aggregated plate statistics method. */ @Test public void testAggregatedSet() { for (PlateBigDecimal plate : array) { List<BigDecimal> resultList = new ArrayList<BigDecimal>(); BigDecimal aggregatedReturned = variance.setsAggregated(plate.dataSet(), weights, mc); for (WellBigDecimal well : plate) { 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(); resultAggregatedDouble *= resultList.size() - 1; resultAggregatedDouble /= resultList.size(); BigDecimal aggregatedResult = new BigDecimal(resultAggregatedDouble, mc); BigDecimal[] corrected = correctRoundingErrors(aggregatedResult, aggregatedReturned); assertEquals(corrected[0], corrected[1]); } } /** * Tests the aggregated plate statistics method using a collection. */ @Test public void testAggregatedSetCollection() { List<WellSetBigDecimal> collection = new ArrayList<WellSetBigDecimal>(); for (PlateBigDecimal plate : array) { collection.add(plate.dataSet()); } Map<WellSetBigDecimal, BigDecimal> aggregatedReturnedMap = variance.setsAggregated(collection, weights, 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(); 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); 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]); } } /** * Tests the aggregated plate statistics method using an array. */ @Test public void testAggregatedSetArray() { WellSetBigDecimal[] setArray = new WellSetBigDecimal[array.length]; for (int i = 0; i < setArray.length; i++) { setArray[i] = array[i].dataSet(); } Map<WellSetBigDecimal, BigDecimal> aggregatedReturnedMap = variance.setsAggregated(setArray, weights, mc); Map<WellSetBigDecimal, BigDecimal> aggregatedResultMap = new TreeMap<WellSetBigDecimal, BigDecimal>(); for (WellSetBigDecimal set : setArray) { List<BigDecimal> resultList = new ArrayList<BigDecimal>(); for (WellBigDecimal 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(); resultAggregatedDouble *= resultList.size() - 1; resultAggregatedDouble /= resultList.size(); BigDecimal aggregatedResult = new BigDecimal(resultAggregatedDouble, mc); aggregatedResultMap.put(set, aggregatedResult); } for (WellSetBigDecimal set : setArray) { BigDecimal result = aggregatedResultMap.get(set); BigDecimal returned = aggregatedReturnedMap.get(set); BigDecimal[] corrected = correctRoundingErrors(result, returned); assertEquals(corrected[0], corrected[1]); } } /** * Tests the aggregated plate statistics method using the values between the indices. */ @Test public void testAggregatedSetIndices() { for (PlateBigDecimal plate : arrayIndices) { int begin = random.nextInt(plate.first().size() - 4); int end = begin + random.nextInt(3) + 3; List<BigDecimal> resultList = new ArrayList<BigDecimal>(); BigDecimal aggregatedReturned = variance.setsAggregated(plate.dataSet(), weightsIndices, begin, end - begin, mc); for (WellBigDecimal well : plate) { 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(); resultAggregatedDouble *= resultList.size() - 1; resultAggregatedDouble /= resultList.size(); BigDecimal aggregatedResult = new BigDecimal(resultAggregatedDouble, mc); BigDecimal[] corrected = correctRoundingErrors(aggregatedResult, aggregatedReturned); assertEquals(corrected[0], corrected[1]); } } /** * Tests the aggregated plate statistics method using the values between the indices of * the collection. */ @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(); resultAggregatedDouble *= resultList.size() - 1; resultAggregatedDouble /= resultList.size(); 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]); } } /** * Tests the aggregated plate statistics method using the values between the indices of * the array. */ @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(); resultAggregatedDouble *= resultList.size() - 1; resultAggregatedDouble /= resultList.size(); 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]); } } /* -------------------------- Well statistics -------------------------- */ /** * Tests well calculation. */ @Test public void testWell() { for (PlateBigDecimal plate : array) { for (WellBigDecimal well : plate) { double[] input = new double[well.size()]; int index = 0; for (BigDecimal bd : well) { input[index] = bd.doubleValue() * weights[index]; index++; } DescriptiveStatistics stat = new DescriptiveStatistics(input); double resultDouble = stat.getPopulationVariance(); BigDecimal returned = variance.well(well, weights, mc); BigDecimal result = new BigDecimal(resultDouble, mc); BigDecimal[] corrected = correctRoundingErrors(result, returned); assertEquals(corrected[0], corrected[1]); } } } /** * Tests well calculation using indices. */ @Test public void testWellIndices() { for (PlateBigDecimal plate : arrayIndices) { for (WellBigDecimal well : plate) { double[] input = new double[well.size()]; int index = 0; for (BigDecimal bd : well) { input[index] = bd.doubleValue() * weightsIndices[index]; index++; } int begin = random.nextInt(well.size() - 4); int end = begin + random.nextInt(3) + 3; DescriptiveStatistics stat = new DescriptiveStatistics(ArrayUtils.subarray(input, begin, end)); double resultDouble = stat.getPopulationVariance(); BigDecimal returned = variance.well(well, ArrayUtils.subarray(weightsIndices, begin, end), begin, end - begin, mc); BigDecimal result = new BigDecimal(resultDouble, mc); BigDecimal[] corrected = correctRoundingErrors(returned, result); assertEquals(corrected[0], corrected[1]); } } } /*---------------------------- Helper Methods ----------------------------*/ /** * Corrects any rounding errors due to differences in the implementation of * the statistic between the Apache and MicroFlex libraries * @param BigDecimal the first result * @param BigDecimal the second result * @return corrected results */ private static BigDecimal[] correctRoundingErrors(BigDecimal bd1, BigDecimal bd2) { BigDecimal[] array = new BigDecimal[2]; int scale = mc.getPrecision(); while (!bd1.equals(bd2) && scale > mc.getPrecision() / 4) { bd1 = bd1.setScale(scale, RoundingMode.HALF_DOWN); bd2 = bd2.setScale(scale, RoundingMode.HALF_DOWN); if (bd1.subtract(bd1.ulp()).equals(bd2)) { bd1 = bd1.subtract(bd1.ulp()); } if (bd1.add(bd1.ulp()).equals(bd2)) { bd1 = bd1.add(bd1.ulp()); } scale--; } array[0] = bd1; array[1] = bd2; return array; } }