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/***************************************************************************
* Copyright 2014 Kieker Project (http://kieker-monitoring.net)
*
* Licensed 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 teetime.util;
import java.util.ArrayList;
import java.util.Collections;
import java.util.LinkedHashMap;
import java.util.List;
import java.util.Map;
import java.util.Map.Entry;
import java.util.concurrent.TimeUnit;
import teetime.examples.throughput.TimestampObject;
/**
* @author Christian Wulf
* @since 1.10
*/
public class StatisticsUtil {
/**
* @since 1.10
*/
private StatisticsUtil() {
// utility class
}
public static void calculateAvg(final List<Long> durations) {
}
public static void printStatistics(final long overallDurationInNs, final List<TimestampObject> timestampObjects) {
System.out.println("Duration: " + TimeUnit.NANOSECONDS.toMillis(overallDurationInNs) + " ms");
final List<Long> sortedDurationsInNs = new ArrayList<Long>(timestampObjects.size() / 2);
long sumInNs = 0;
for (int i = timestampObjects.size() / 2; i < timestampObjects.size(); i++) {
final TimestampObject timestampObject = timestampObjects.get(i);
final long durationInNs = timestampObject.getStopTimestamp() - timestampObject.getStartTimestamp();
// sortedDurationsInNs.set(i - (timestampObjects.size() / 2), durationInNs);
sortedDurationsInNs.add(durationInNs);
sumInNs += durationInNs;
}
final Map<Double, Long> quintileValues = StatisticsUtil.calculateQuintiles(sortedDurationsInNs);
final long avgDurInNs = sumInNs / (timestampObjects.size() / 2);
System.out.println("avg duration: " + TimeUnit.NANOSECONDS.toMicros(avgDurInNs) + " µs");
final long confidenceWidthInNs = StatisticsUtil.calculateConfidenceWidth(sortedDurationsInNs, avgDurInNs);
System.out.println("confidenceWidth: " + confidenceWidthInNs + " ns");
System.out.println("[" + TimeUnit.NANOSECONDS.toMicros(avgDurInNs - confidenceWidthInNs) + " µs, "
+ TimeUnit.NANOSECONDS.toMicros(avgDurInNs + confidenceWidthInNs) + " µs]");
public static void printQuintiles(final Map<Double, Long> quintileValues) {
for (final Entry<Double, Long> entry : quintileValues.entrySet()) {
System.out.println((entry.getKey() * 100) + " % : " + TimeUnit.NANOSECONDS.toNanos(entry.getValue()) + " ns");
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public static long calculateConfidenceWidth(final List<Long> durations, final long avgDurInNs) {
final double z = 1.96; // for alpha = 0.05
final double variance = MathUtil.getVariance(durations, avgDurInNs);
final long confidenceWidthInNs = (long) MathUtil.getConfidenceWidth(z, variance, durations.size());
return confidenceWidthInNs;
}
public static long calculateConfidenceWidth(final List<Long> durations) {
return StatisticsUtil.calculateConfidenceWidth(durations, StatisticsUtil.calculateAverage(durations));
}
public static long calculateAverage(final List<Long> durations) {
long sumNs = 0;
for (final Long value : durations) {
sumNs += value;
}
return sumNs / durations.size();
}
public static Map<Double, Long> calculateQuintiles(final List<Long> durationsInNs) {
Collections.sort(durationsInNs);
final Map<Double, Long> quintileValues = new LinkedHashMap<Double, Long>();
final double[] quintiles = { 0.00, 0.25, 0.50, 0.75, 1.00 };
for (final double quintile : quintiles) {
final int index = (int) ((durationsInNs.size() - 1) * quintile);
quintileValues.put(quintile, durationsInNs.get(index));
}
return quintileValues;
}