001 /* 002 * Licensed to the Apache Software Foundation (ASF) under one or more 003 * contributor license agreements. See the NOTICE file distributed with 004 * this work for additional information regarding copyright ownership. 005 * The ASF licenses this file to You under the Apache License, Version 2.0 006 * (the "License"); you may not use this file except in compliance with 007 * the License. You may obtain a copy of the License at 008 * 009 * http://www.apache.org/licenses/LICENSE-2.0 010 * 011 * Unless required by applicable law or agreed to in writing, software 012 * distributed under the License is distributed on an "AS IS" BASIS, 013 * WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied. 014 * See the License for the specific language governing permissions and 015 * limitations under the License. 016 */ 017 package org.apache.commons.math3.filter; 018 019 import org.apache.commons.math3.exception.DimensionMismatchException; 020 import org.apache.commons.math3.exception.NoDataException; 021 import org.apache.commons.math3.exception.NullArgumentException; 022 import org.apache.commons.math3.linear.Array2DRowRealMatrix; 023 import org.apache.commons.math3.linear.ArrayRealVector; 024 import org.apache.commons.math3.linear.RealMatrix; 025 import org.apache.commons.math3.linear.RealVector; 026 027 /** 028 * Default implementation of a {@link ProcessModel} for the use with a {@link KalmanFilter}. 029 * 030 * @since 3.0 031 * @version $Id: DefaultProcessModel.java 1416643 2012-12-03 19:37:14Z tn $ 032 */ 033 public class DefaultProcessModel implements ProcessModel { 034 /** 035 * The state transition matrix, used to advance the internal state estimation each time-step. 036 */ 037 private RealMatrix stateTransitionMatrix; 038 039 /** 040 * The control matrix, used to integrate a control input into the state estimation. 041 */ 042 private RealMatrix controlMatrix; 043 044 /** The process noise covariance matrix. */ 045 private RealMatrix processNoiseCovMatrix; 046 047 /** The initial state estimation of the observed process. */ 048 private RealVector initialStateEstimateVector; 049 050 /** The initial error covariance matrix of the observed process. */ 051 private RealMatrix initialErrorCovMatrix; 052 053 /** 054 * Create a new {@link ProcessModel}, taking double arrays as input parameters. 055 * 056 * @param stateTransition 057 * the state transition matrix 058 * @param control 059 * the control matrix 060 * @param processNoise 061 * the process noise matrix 062 * @param initialStateEstimate 063 * the initial state estimate vector 064 * @param initialErrorCovariance 065 * the initial error covariance matrix 066 * @throws NullArgumentException 067 * if any of the input arrays is {@code null} 068 * @throws NoDataException 069 * if any row / column dimension of the input matrices is zero 070 * @throws DimensionMismatchException 071 * if any of the input matrices is non-rectangular 072 */ 073 public DefaultProcessModel(final double[][] stateTransition, 074 final double[][] control, 075 final double[][] processNoise, 076 final double[] initialStateEstimate, 077 final double[][] initialErrorCovariance) 078 throws NullArgumentException, NoDataException, DimensionMismatchException { 079 080 this(new Array2DRowRealMatrix(stateTransition), 081 new Array2DRowRealMatrix(control), 082 new Array2DRowRealMatrix(processNoise), 083 new ArrayRealVector(initialStateEstimate), 084 new Array2DRowRealMatrix(initialErrorCovariance)); 085 } 086 087 /** 088 * Create a new {@link ProcessModel}, taking double arrays as input parameters. 089 * <p> 090 * The initial state estimate and error covariance are omitted and will be initialized by the 091 * {@link KalmanFilter} to default values. 092 * 093 * @param stateTransition 094 * the state transition matrix 095 * @param control 096 * the control matrix 097 * @param processNoise 098 * the process noise matrix 099 * @throws NullArgumentException 100 * if any of the input arrays is {@code null} 101 * @throws NoDataException 102 * if any row / column dimension of the input matrices is zero 103 * @throws DimensionMismatchException 104 * if any of the input matrices is non-rectangular 105 */ 106 public DefaultProcessModel(final double[][] stateTransition, 107 final double[][] control, 108 final double[][] processNoise) 109 throws NullArgumentException, NoDataException, DimensionMismatchException { 110 111 this(new Array2DRowRealMatrix(stateTransition), 112 new Array2DRowRealMatrix(control), 113 new Array2DRowRealMatrix(processNoise), null, null); 114 } 115 116 /** 117 * Create a new {@link ProcessModel}, taking double arrays as input parameters. 118 * 119 * @param stateTransition 120 * the state transition matrix 121 * @param control 122 * the control matrix 123 * @param processNoise 124 * the process noise matrix 125 * @param initialStateEstimate 126 * the initial state estimate vector 127 * @param initialErrorCovariance 128 * the initial error covariance matrix 129 */ 130 public DefaultProcessModel(final RealMatrix stateTransition, 131 final RealMatrix control, 132 final RealMatrix processNoise, 133 final RealVector initialStateEstimate, 134 final RealMatrix initialErrorCovariance) { 135 this.stateTransitionMatrix = stateTransition; 136 this.controlMatrix = control; 137 this.processNoiseCovMatrix = processNoise; 138 this.initialStateEstimateVector = initialStateEstimate; 139 this.initialErrorCovMatrix = initialErrorCovariance; 140 } 141 142 /** {@inheritDoc} */ 143 public RealMatrix getStateTransitionMatrix() { 144 return stateTransitionMatrix; 145 } 146 147 /** {@inheritDoc} */ 148 public RealMatrix getControlMatrix() { 149 return controlMatrix; 150 } 151 152 /** {@inheritDoc} */ 153 public RealMatrix getProcessNoise() { 154 return processNoiseCovMatrix; 155 } 156 157 /** {@inheritDoc} */ 158 public RealVector getInitialStateEstimate() { 159 return initialStateEstimateVector; 160 } 161 162 /** {@inheritDoc} */ 163 public RealMatrix getInitialErrorCovariance() { 164 return initialErrorCovMatrix; 165 } 166 }