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.statdouble; /* ------------------------------ Dependencies ------------------------------ */ import static org.junit.Assert.*; import java.io.OutputStream; import java.io.PrintStream; import java.math.BigDecimal; 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.apache.commons.math3.util.Precision; 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.doubleflex.plate.PlateDouble; import com.github.jessemull.microflex.doubleflex.plate.WellDouble; import com.github.jessemull.microflex.doubleflex.plate.WellSetDouble; import com.github.jessemull.microflex.doubleflex.stat.GeometricMeanDouble; import com.github.jessemull.microflex.util.RandomUtil; /** * This class tests the methods in the mean double 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 GeometricMeanDoubleWeightsTest { /* ---------------------------- Local Fields -----------------------------*/ /* Minimum and maximum values for random well and lists */ private static double minValue = 0; // Minimum double value for wells private static double maxValue = 100; // Maximum double value for wells private static Random random = new Random(); // Generates random integers private static int precision = 10; // Precision for results /* The addition operation */ private static GeometricMeanDouble mean = new GeometricMeanDouble(); /* 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 PlateDouble[] array = new PlateDouble[plateNumber]; private static PlateDouble[] arrayIndices = new PlateDouble[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++) { PlateDouble plate = RandomUtil.randomPlateDouble(rows, columns, minValue, maxValue, length, "Plate1-" + j); array[j] = plate; } for (int j = 0; j < arrayIndices.length; j++) { PlateDouble plateIndices = RandomUtil.randomPlateDouble(rows, columns, minValue, maxValue, lengthIndices, "Plate1-" + j); arrayIndices[j] = plateIndices; } for (int i = 0; i < weights.length; i++) { weights[i] = random.nextDouble(); } for (int i = 0; i < weightsIndices.length; i++) { weightsIndices[i] = random.nextDouble(); } } /** * 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 (PlateDouble plate : array) { Map<WellDouble, Double> resultMap = new TreeMap<WellDouble, Double>(); Map<WellDouble, Double> returnedMap = mean.plate(plate, weights); for (WellDouble well : plate) { double[] input = new double[well.size()]; int index = 0; for (double db : well) { input[index] = db * weights[index]; index++; } DescriptiveStatistics stat = new DescriptiveStatistics(input); double result = stat.getGeometricMean(); resultMap.put(well, result); } for (WellDouble well : plate) { double result = Precision.round(resultMap.get(well), precision); double returned = Precision.round(returnedMap.get(well), precision); assertTrue(result == returned); } } } /** * Tests the plate statistics method using the values between the indices. */ @Test public void testPlateIndices() { for (PlateDouble plate : arrayIndices) { int begin = random.nextInt(plate.first().size() - 4); int end = begin + random.nextInt(3) + 3; Map<WellDouble, Double> resultMap = new TreeMap<WellDouble, Double>(); Map<WellDouble, Double> returnedMap = mean.plate(plate, ArrayUtils.subarray(weightsIndices, begin, end), begin, end - begin); for (WellDouble well : plate) { double[] input = new double[well.size()]; int index = 0; for (double db : well) { input[index] = db * weightsIndices[index]; index++; } DescriptiveStatistics stat = new DescriptiveStatistics(ArrayUtils.subarray(input, begin, end)); double result = stat.getGeometricMean(); resultMap.put(well, result); } for (WellDouble well : plate) { double result = Precision.round(resultMap.get(well), precision); double returned = Precision.round(returnedMap.get(well), precision); assertTrue(result == returned); } } } /* --------------------- Aggregated plate statistics ------------------- */ /** * Tests the aggregated plate statistics method. */ @Test public void testAggregatedPlate() { for (PlateDouble plate : array) { List<BigDecimal> resultList = new ArrayList<BigDecimal>(); double aggregatedReturned = Precision.round(mean.platesAggregated(plate, 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 resultAggregated = Precision.round(statAggregated.getGeometricMean(), precision); assertTrue(resultAggregated == aggregatedReturned); } } /** * Tests the aggregated plate statistics method using a collection. */ @Test public void testAggregatedPlateCollection() { List<PlateDouble> collection = Arrays.asList(array); Map<PlateDouble, Double> aggregatedReturnedMap = mean.platesAggregated(collection, weights); Map<PlateDouble, Double> aggregatedResultMap = new TreeMap<PlateDouble, Double>(); for (PlateDouble plate : collection) { List<BigDecimal> resultList = new ArrayList<BigDecimal>(); 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 = statAggregated.getGeometricMean(); aggregatedResultMap.put(plate, aggregatedResult); } for (PlateDouble plate : collection) { double result = Precision.round(aggregatedResultMap.get(plate), precision); double returned = Precision.round(aggregatedReturnedMap.get(plate), precision); assertTrue(result == returned); } } /** * Tests the aggregated plate statistics method using an array. */ @Test public void testAggregatedPlateArray() { Map<PlateDouble, Double> aggregatedReturnedMap = mean.platesAggregated(array, weights); Map<PlateDouble, Double> aggregatedResultMap = new TreeMap<PlateDouble, Double>(); for (PlateDouble plate : array) { List<BigDecimal> resultList = new ArrayList<BigDecimal>(); 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 = statAggregated.getGeometricMean(); aggregatedResultMap.put(plate, aggregatedResult); } for (PlateDouble plate : array) { double result = Precision.round(aggregatedResultMap.get(plate), precision); double returned = Precision.round(aggregatedReturnedMap.get(plate), precision); assertTrue(result == returned); } } /** * Tests the aggregated plate statistics method using the values between the indices. */ @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(mean.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.getGeometricMean(), precision); assertTrue(resultAggregated == aggregatedReturned); } } /** * 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<PlateDouble> collection = Arrays.asList(arrayIndices); Map<PlateDouble, Double> aggregatedReturnedMap = mean.platesAggregated(collection, weightsIndices, begin, end - begin); Map<PlateDouble, Double> aggregatedResultMap = new TreeMap<PlateDouble, Double>(); for (PlateDouble plate : collection) { List<BigDecimal> resultList = new ArrayList<BigDecimal>(); 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 aggregatedResult = statAggregated.getGeometricMean(); aggregatedResultMap.put(plate, aggregatedResult); } for (PlateDouble plate : collection) { double result = Precision.round(aggregatedResultMap.get(plate), precision); double returned = Precision.round(aggregatedReturnedMap.get(plate), precision); assertTrue(result == returned); } } /** * 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<PlateDouble, Double> aggregatedReturnedMap = mean.platesAggregated(arrayIndices, weightsIndices, begin, end - begin); Map<PlateDouble, Double> aggregatedResultMap = new TreeMap<PlateDouble, Double>(); for (PlateDouble plate : arrayIndices) { List<BigDecimal> resultList = new ArrayList<BigDecimal>(); 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 aggregatedResult = statAggregated.getGeometricMean(); aggregatedResultMap.put(plate, aggregatedResult); } for (PlateDouble plate : arrayIndices) { double result = Precision.round(aggregatedResultMap.get(plate), precision); double returned = Precision.round(aggregatedReturnedMap.get(plate), precision); assertTrue(result == returned); } } /* --------------- Well statistics for all wells in a set -------------- */ /** * Tests set calculation. */ @Test public void testSet() { for (PlateDouble plate : array) { Map<WellDouble, Double> resultMap = new TreeMap<WellDouble, Double>(); Map<WellDouble, Double> returnedMap = mean.set(plate.dataSet(), weights); for (WellDouble well : plate) { double[] input = new double[well.size()]; int index = 0; for (double db : well) { input[index] = db * weights[index]; index++; } DescriptiveStatistics stat = new DescriptiveStatistics(input); double result = stat.getGeometricMean(); resultMap.put(well, result); } for (WellDouble well : plate) { double result = Precision.round(resultMap.get(well), precision); double returned = Precision.round(returnedMap.get(well), precision); assertTrue(result == returned); } } } /** * Tests set calculation using indices. */ @Test public void testSetIndices() { for (PlateDouble plate : arrayIndices) { int begin = random.nextInt(plate.first().size() - 4); int end = begin + random.nextInt(3) + 3; Map<WellDouble, Double> resultMap = new TreeMap<WellDouble, Double>(); Map<WellDouble, Double> returnedMap = mean.set(plate.dataSet(), ArrayUtils.subarray(weightsIndices, begin, end), begin, end - begin); for (WellDouble well : plate) { double[] input = new double[well.size()]; int index = 0; for (double db : well) { input[index] = db * weightsIndices[index]; index++; } DescriptiveStatistics stat = new DescriptiveStatistics(ArrayUtils.subarray(input, begin, end)); double result = stat.getGeometricMean(); resultMap.put(well, result); } for (WellDouble well : plate) { double result = Precision.round(resultMap.get(well), precision); double returned = Precision.round(returnedMap.get(well), precision); assertTrue(result == returned); } } } /* ---------------------- Aggregated set statistics -------------------- */ /** * Tests the aggregated plate statistics method. */ @Test public void testAggregatedSet() { for (PlateDouble plate : array) { List<BigDecimal> resultList = new ArrayList<BigDecimal>(); double aggregatedReturned = Precision.round(mean.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.getGeometricMean(), precision); assertTrue(aggregatedResult == aggregatedReturned); } } /** * Tests the aggregated plate statistics method using a collection. */ @Test public void testAggregatedSetCollection() { List<WellSetDouble> collection = new ArrayList<WellSetDouble>(); for (PlateDouble plate : array) { collection.add(plate.dataSet()); } Map<WellSetDouble, Double> aggregatedReturnedMap = mean.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.getGeometricMean(); 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); } } /** * Tests the aggregated plate statistics method using an array. */ @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 = mean.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.getGeometricMean(); 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); } } /** * Tests the aggregated plate statistics method using the values between the indices. */ @Test public void testAggregatedSetIndices() { 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(mean.setsAggregated(plate.dataSet(), 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.getGeometricMean(), precision); assertTrue(resultAggregated == aggregatedReturned); } } /** * 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<WellSetDouble> collection = new ArrayList<WellSetDouble>(); for (PlateDouble plate : arrayIndices) { collection.add(plate.dataSet()); } Map<WellSetDouble, Double> aggregatedReturnedMap = mean.setsAggregated(collection, weightsIndices, begin, end - begin); 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().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.getGeometricMean(); 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); } } /** * 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; WellSetDouble[] setArrayIndices = new WellSetDouble[arrayIndices.length]; for (int i = 0; i < setArrayIndices.length; i++) { setArrayIndices[i] = arrayIndices[i].dataSet(); } Map<WellSetDouble, Double> aggregatedReturnedMap = mean.setsAggregated(setArrayIndices, weightsIndices, begin, end - begin); Map<WellSetDouble, Double> aggregatedResultMap = new TreeMap<WellSetDouble, Double>(); for (WellSetDouble set : setArrayIndices) { List<BigDecimal> resultList = new ArrayList<BigDecimal>(); for (WellDouble 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.getGeometricMean(); aggregatedResultMap.put(set, aggregatedResult); } for (WellSetDouble plate : setArrayIndices) { double result = Precision.round(aggregatedResultMap.get(plate), precision); double returned = Precision.round(aggregatedReturnedMap.get(plate), precision); assertTrue(result == returned); } } /* -------------------------- Well statistics -------------------------- */ /** * Tests well calculation. */ @Test public void testWell() { for (PlateDouble plate : array) { for (WellDouble well : plate) { double[] input = new double[well.size()]; int index = 0; for (double db : well) { input[index] = db * weights[index]; index++; } DescriptiveStatistics stat = new DescriptiveStatistics(input); double result = Precision.round(stat.getGeometricMean(), precision); double returned = Precision.round(mean.well(well, weights), precision); assertTrue(result == returned); } } } /** * Tests well calculation using indices. */ @Test public void testWellIndices() { for (PlateDouble plate : arrayIndices) { for (WellDouble well : plate) { double[] input = new double[well.size()]; int index = 0; for (double db : well) { input[index] = db * 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 result = Precision.round(stat.getGeometricMean(), precision); double returned = Precision.round( mean.well(well, ArrayUtils.subarray(weightsIndices, begin, end), begin, end - begin), precision); assertTrue(result == returned); } } } }