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/*
*
* 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 org.apache.qpid.disttest.results.aggregation;
import java.util.Collection;
import java.util.concurrent.CopyOnWriteArrayList;
public class SeriesStatistics
{
private long _minValue;
private long _maxValue;
private double _mean;
private double _standardDeviation;
private Collection<Long> _series = new CopyOnWriteArrayList<Long>();
public SeriesStatistics()
{
super();
}
public SeriesStatistics(Collection<Long> messageLatencies)
{
setMessageLatencies(messageLatencies);
}
public void addMessageLatencies(Collection<Long> messageLatencies)
{
if (messageLatencies != null)
{
_series.addAll(messageLatencies);
}
}
public void setMessageLatencies(Collection<Long> messageLatencies)
{
_series = messageLatencies;
aggregate();
}
public void aggregate()
{
if (_series != null && _series.size() > 0)
{
long minLatency = Long.MAX_VALUE;
long maxLatency = Long.MIN_VALUE;
long totalLatency = 0;
for (Long latency : _series)
{
totalLatency += latency;
minLatency = Math.min(minLatency, latency);
maxLatency = Math.max(maxLatency, latency);
}
_mean = ((double) totalLatency) / (double) _series.size();
_minValue = minLatency;
_maxValue = maxLatency;
double sum = 0;
for (Long latency : _series)
{
double diff = latency - _mean;
sum += diff * diff;
}
long size = _series.size() == 1 ? 1: _series.size() - 1;
_standardDeviation = Math.sqrt(sum / (double) size);
}
else
{
_mean = 0;
_minValue = 0;
_maxValue = 0;
_standardDeviation = 0;
}
}
public long getMinimum()
{
return _minValue;
}
public long getMaximum()
{
return _maxValue;
}
public double getAverage()
{
return _mean;
}
public double getStandardDeviation()
{
return _standardDeviation;
}
}
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