001/** 002 * Copyright (c) 2011, The University of Southampton and the individual contributors. 003 * All rights reserved. 004 * 005 * Redistribution and use in source and binary forms, with or without modification, 006 * are permitted provided that the following conditions are met: 007 * 008 * * Redistributions of source code must retain the above copyright notice, 009 * this list of conditions and the following disclaimer. 010 * 011 * * Redistributions in binary form must reproduce the above copyright notice, 012 * this list of conditions and the following disclaimer in the documentation 013 * and/or other materials provided with the distribution. 014 * 015 * * Neither the name of the University of Southampton nor the names of its 016 * contributors may be used to endorse or promote products derived from this 017 * software without specific prior written permission. 018 * 019 * THIS SOFTWARE IS PROVIDED BY THE COPYRIGHT HOLDERS AND CONTRIBUTORS "AS IS" AND 020 * ANY EXPRESS OR IMPLIED WARRANTIES, INCLUDING, BUT NOT LIMITED TO, THE IMPLIED 021 * WARRANTIES OF MERCHANTABILITY AND FITNESS FOR A PARTICULAR PURPOSE ARE 022 * DISCLAIMED. IN NO EVENT SHALL THE COPYRIGHT OWNER OR CONTRIBUTORS BE LIABLE FOR 023 * ANY DIRECT, INDIRECT, INCIDENTAL, SPECIAL, EXEMPLARY, OR CONSEQUENTIAL DAMAGES 024 * (INCLUDING, BUT NOT LIMITED TO, PROCUREMENT OF SUBSTITUTE GOODS OR SERVICES; 025 * LOSS OF USE, DATA, OR PROFITS; OR BUSINESS INTERRUPTION) HOWEVER CAUSED AND ON 026 * ANY THEORY OF LIABILITY, WHETHER IN CONTRACT, STRICT LIABILITY, OR TORT 027 * (INCLUDING NEGLIGENCE OR OTHERWISE) ARISING IN ANY WAY OUT OF THE USE OF THIS 028 * SOFTWARE, EVEN IF ADVISED OF THE POSSIBILITY OF SUCH DAMAGE. 029 */ 030package org.openimaj.ml.timeseries.aggregator; 031 032import org.openimaj.math.matrix.MatrixUtils; 033import org.openimaj.ml.timeseries.IncompatibleTimeSeriesException; 034import org.openimaj.ml.timeseries.processor.interpolation.LinearInterpolationProcessor; 035import org.openimaj.ml.timeseries.series.DoubleSynchronisedTimeSeriesCollection; 036import org.openimaj.ml.timeseries.series.DoubleTimeSeries; 037import Jama.Matrix; 038 039public class MeanSquaredDifferenceAggregator implements SynchronisedTimeSeriesCollectionAggregator<DoubleTimeSeries, DoubleSynchronisedTimeSeriesCollection, Double>{ 040 041 @Override 042 public Double aggregate(DoubleSynchronisedTimeSeriesCollection series) { 043 Matrix squarediffs = null; 044 int size = 0; 045 for (DoubleTimeSeries ds: series.allseries()) { 046 if(squarediffs == null){ 047 squarediffs = new Matrix(new double[][]{ds.getData()}); 048 } 049 else{ 050 squarediffs = squarediffs.minus(new Matrix(new double[][]{ds.getData()})); 051 squarediffs = squarediffs.arrayTimes(squarediffs ); 052 } 053 size = ds.size(); 054 } 055 return MatrixUtils.sum(squarediffs)/size; 056 } 057 058 public static Double error(DoubleTimeSeries ... series) throws IncompatibleTimeSeriesException { 059 DoubleTimeSeries first = series[0]; 060 long[] importantTimes = first.getTimes(); 061 DoubleSynchronisedTimeSeriesCollection aaplinterp = new DoubleSynchronisedTimeSeriesCollection(); 062 int i = 0; 063 for (DoubleTimeSeries doubleTimeSeries : series) { 064 if(i!=0){ 065 doubleTimeSeries = doubleTimeSeries.process(new LinearInterpolationProcessor(importantTimes)); 066 } 067 aaplinterp.addTimeSeries("" + i++, doubleTimeSeries); 068 } 069 return new MeanSquaredDifferenceAggregator().aggregate(aaplinterp); 070 } 071 072}