/*
* Created on Oct 08, 2004
* Created by Alon Rohter
* Copyright (C) 2004, 2005, 2006 Aelitis, All Rights Reserved.
*
* This program is free software; you can redistribute it and/or
* modify it under the terms of the GNU General Public License
* as published by the Free Software Foundation; either version 2
* of the License, or (at your option) any later version.
* This program is distributed in the hope that it will be useful,
* but WITHOUT ANY WARRANTY; without even the implied warranty of
* MERCHANTABILITY or FITNESS FOR A PARTICULAR PURPOSE. See the
* GNU General Public License for more details.
* You should have received a copy of the GNU General Public License
* along with this program; if not, write to the Free Software
* Foundation, Inc., 59 Temple Place - Suite 330, Boston, MA 02111-1307, USA.
*
* AELITIS, SAS au capital de 46,603.30 euros
* 8 Allee Lenotre, La Grille Royale, 78600 Le Mesnil le Roi, France.
*
*/
package com.aelitis.azureus.core.util.average;
/**
* Generates different types of averages.
*/
public abstract class AverageFactory {
/**
* Create a simple running average.
*/
public static RunningAverage RunningAverage() {
return new RunningAverage();
}
/**
* Create a moving average, that moves over the given number of periods.
*/
public static MovingAverage MovingAverage(int periods) {
return new MovingAverage(periods);
}
/**
* Create a moving average, that moves over the given number of periods and gives immediate
* results (i.e. after the first update of X the average will be X
*/
public static MovingImmediateAverage MovingImmediateAverage(int periods) {
return new MovingImmediateAverage(periods);
}
/**
* Create an exponential moving average, smoothing over the given number
* of periods, using a default smoothing weight value of 2/(1 + periods).
*/
public static ExponentialMovingAverage ExponentialMovingAverage(int periods) {
return new ExponentialMovingAverage(periods);
}
/**
* Create an exponential moving average, with the given smoothing weight.
* Larger weigths (closer to 1.0) will give more influence to
* recent data and smaller weights (closer to 0.00) will provide
* smoother averaging (give more influence to older data).
*/
public static ExponentialMovingAverage ExponentialMovingAverage(float weight) {
return new ExponentialMovingAverage(weight);
}
}