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 */ 017package org.apache.commons.math4.legacy.filter; 018 019import org.apache.commons.math4.legacy.exception.DimensionMismatchException; 020import org.apache.commons.math4.legacy.exception.NoDataException; 021import org.apache.commons.math4.legacy.exception.NullArgumentException; 022import org.apache.commons.math4.legacy.linear.Array2DRowRealMatrix; 023import org.apache.commons.math4.legacy.linear.ArrayRealVector; 024import org.apache.commons.math4.legacy.linear.RealMatrix; 025import org.apache.commons.math4.legacy.linear.RealVector; 026 027/** 028 * Default implementation of a {@link ProcessModel} for the use with a {@link KalmanFilter}. 029 * 030 * @since 3.0 031 */ 032public class DefaultProcessModel implements ProcessModel { 033 /** 034 * The state transition matrix, used to advance the internal state estimation each time-step. 035 */ 036 private final RealMatrix stateTransitionMatrix; 037 038 /** 039 * The control matrix, used to integrate a control input into the state estimation. 040 */ 041 private final RealMatrix controlMatrix; 042 043 /** The process noise covariance matrix. */ 044 private final RealMatrix processNoiseCovMatrix; 045 046 /** The initial state estimation of the observed process. */ 047 private final RealVector initialStateEstimateVector; 048 049 /** The initial error covariance matrix of the observed process. */ 050 private final RealMatrix initialErrorCovMatrix; 051 052 /** 053 * Create a new {@link ProcessModel}, taking double arrays as input parameters. 054 * 055 * @param stateTransition 056 * the state transition matrix 057 * @param control 058 * the control matrix 059 * @param processNoise 060 * the process noise matrix 061 * @param initialStateEstimate 062 * the initial state estimate vector 063 * @param initialErrorCovariance 064 * the initial error covariance matrix 065 * @throws NullArgumentException 066 * if any of the input arrays is {@code null} 067 * @throws NoDataException 068 * if any row / column dimension of the input matrices is zero 069 * @throws DimensionMismatchException 070 * if any of the input matrices is non-rectangular 071 */ 072 public DefaultProcessModel(final double[][] stateTransition, 073 final double[][] control, 074 final double[][] processNoise, 075 final double[] initialStateEstimate, 076 final double[][] initialErrorCovariance) 077 throws NullArgumentException, NoDataException, DimensionMismatchException { 078 079 this(new Array2DRowRealMatrix(stateTransition), 080 new Array2DRowRealMatrix(control), 081 new Array2DRowRealMatrix(processNoise), 082 new ArrayRealVector(initialStateEstimate), 083 new Array2DRowRealMatrix(initialErrorCovariance)); 084 } 085 086 /** 087 * Create a new {@link ProcessModel}, taking double arrays as input parameters. 088 * <p> 089 * The initial state estimate and error covariance are omitted and will be initialized by the 090 * {@link KalmanFilter} to default values. 091 * 092 * @param stateTransition 093 * the state transition matrix 094 * @param control 095 * the control matrix 096 * @param processNoise 097 * the process noise matrix 098 * @throws NullArgumentException 099 * if any of the input arrays is {@code null} 100 * @throws NoDataException 101 * if any row / column dimension of the input matrices is zero 102 * @throws DimensionMismatchException 103 * if any of the input matrices is non-rectangular 104 */ 105 public DefaultProcessModel(final double[][] stateTransition, 106 final double[][] control, 107 final double[][] processNoise) 108 throws NullArgumentException, NoDataException, DimensionMismatchException { 109 110 this(new Array2DRowRealMatrix(stateTransition), 111 new Array2DRowRealMatrix(control), 112 new Array2DRowRealMatrix(processNoise), null, null); 113 } 114 115 /** 116 * Create a new {@link ProcessModel}, taking double arrays as input parameters. 117 * 118 * @param stateTransition 119 * the state transition matrix 120 * @param control 121 * the control matrix 122 * @param processNoise 123 * the process noise matrix 124 * @param initialStateEstimate 125 * the initial state estimate vector 126 * @param initialErrorCovariance 127 * the initial error covariance matrix 128 */ 129 public DefaultProcessModel(final RealMatrix stateTransition, 130 final RealMatrix control, 131 final RealMatrix processNoise, 132 final RealVector initialStateEstimate, 133 final RealMatrix initialErrorCovariance) { 134 this.stateTransitionMatrix = stateTransition; 135 this.controlMatrix = control; 136 this.processNoiseCovMatrix = processNoise; 137 this.initialStateEstimateVector = initialStateEstimate; 138 this.initialErrorCovMatrix = initialErrorCovariance; 139 } 140 141 /** {@inheritDoc} */ 142 @Override 143 public RealMatrix getStateTransitionMatrix() { 144 return stateTransitionMatrix; 145 } 146 147 /** {@inheritDoc} */ 148 @Override 149 public RealMatrix getControlMatrix() { 150 return controlMatrix; 151 } 152 153 /** {@inheritDoc} */ 154 @Override 155 public RealMatrix getProcessNoise() { 156 return processNoiseCovMatrix; 157 } 158 159 /** {@inheritDoc} */ 160 @Override 161 public RealVector getInitialStateEstimate() { 162 return initialStateEstimateVector; 163 } 164 165 /** {@inheritDoc} */ 166 @Override 167 public RealMatrix getInitialErrorCovariance() { 168 return initialErrorCovMatrix; 169 } 170}