| /* |
| * 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.commons.math4.filter; |
| |
| import org.apache.commons.math4.exception.DimensionMismatchException; |
| import org.apache.commons.math4.exception.NoDataException; |
| import org.apache.commons.math4.exception.NullArgumentException; |
| import org.apache.commons.math4.linear.Array2DRowRealMatrix; |
| import org.apache.commons.math4.linear.ArrayRealVector; |
| import org.apache.commons.math4.linear.RealMatrix; |
| import org.apache.commons.math4.linear.RealVector; |
| |
| /** |
| * Default implementation of a {@link ProcessModel} for the use with a {@link KalmanFilter}. |
| * |
| * @since 3.0 |
| */ |
| public class DefaultProcessModel implements ProcessModel { |
| /** |
| * The state transition matrix, used to advance the internal state estimation each time-step. |
| */ |
| private final RealMatrix stateTransitionMatrix; |
| |
| /** |
| * The control matrix, used to integrate a control input into the state estimation. |
| */ |
| private final RealMatrix controlMatrix; |
| |
| /** The process noise covariance matrix. */ |
| private final RealMatrix processNoiseCovMatrix; |
| |
| /** The initial state estimation of the observed process. */ |
| private final RealVector initialStateEstimateVector; |
| |
| /** The initial error covariance matrix of the observed process. */ |
| private final RealMatrix initialErrorCovMatrix; |
| |
| /** |
| * Create a new {@link ProcessModel}, taking double arrays as input parameters. |
| * |
| * @param stateTransition |
| * the state transition matrix |
| * @param control |
| * the control matrix |
| * @param processNoise |
| * the process noise matrix |
| * @param initialStateEstimate |
| * the initial state estimate vector |
| * @param initialErrorCovariance |
| * the initial error covariance matrix |
| * @throws NullArgumentException |
| * if any of the input arrays is {@code null} |
| * @throws NoDataException |
| * if any row / column dimension of the input matrices is zero |
| * @throws DimensionMismatchException |
| * if any of the input matrices is non-rectangular |
| */ |
| public DefaultProcessModel(final double[][] stateTransition, |
| final double[][] control, |
| final double[][] processNoise, |
| final double[] initialStateEstimate, |
| final double[][] initialErrorCovariance) |
| throws NullArgumentException, NoDataException, DimensionMismatchException { |
| |
| this(new Array2DRowRealMatrix(stateTransition), |
| new Array2DRowRealMatrix(control), |
| new Array2DRowRealMatrix(processNoise), |
| new ArrayRealVector(initialStateEstimate), |
| new Array2DRowRealMatrix(initialErrorCovariance)); |
| } |
| |
| /** |
| * Create a new {@link ProcessModel}, taking double arrays as input parameters. |
| * <p> |
| * The initial state estimate and error covariance are omitted and will be initialized by the |
| * {@link KalmanFilter} to default values. |
| * |
| * @param stateTransition |
| * the state transition matrix |
| * @param control |
| * the control matrix |
| * @param processNoise |
| * the process noise matrix |
| * @throws NullArgumentException |
| * if any of the input arrays is {@code null} |
| * @throws NoDataException |
| * if any row / column dimension of the input matrices is zero |
| * @throws DimensionMismatchException |
| * if any of the input matrices is non-rectangular |
| */ |
| public DefaultProcessModel(final double[][] stateTransition, |
| final double[][] control, |
| final double[][] processNoise) |
| throws NullArgumentException, NoDataException, DimensionMismatchException { |
| |
| this(new Array2DRowRealMatrix(stateTransition), |
| new Array2DRowRealMatrix(control), |
| new Array2DRowRealMatrix(processNoise), null, null); |
| } |
| |
| /** |
| * Create a new {@link ProcessModel}, taking double arrays as input parameters. |
| * |
| * @param stateTransition |
| * the state transition matrix |
| * @param control |
| * the control matrix |
| * @param processNoise |
| * the process noise matrix |
| * @param initialStateEstimate |
| * the initial state estimate vector |
| * @param initialErrorCovariance |
| * the initial error covariance matrix |
| */ |
| public DefaultProcessModel(final RealMatrix stateTransition, |
| final RealMatrix control, |
| final RealMatrix processNoise, |
| final RealVector initialStateEstimate, |
| final RealMatrix initialErrorCovariance) { |
| this.stateTransitionMatrix = stateTransition; |
| this.controlMatrix = control; |
| this.processNoiseCovMatrix = processNoise; |
| this.initialStateEstimateVector = initialStateEstimate; |
| this.initialErrorCovMatrix = initialErrorCovariance; |
| } |
| |
| /** {@inheritDoc} */ |
| @Override |
| public RealMatrix getStateTransitionMatrix() { |
| return stateTransitionMatrix; |
| } |
| |
| /** {@inheritDoc} */ |
| @Override |
| public RealMatrix getControlMatrix() { |
| return controlMatrix; |
| } |
| |
| /** {@inheritDoc} */ |
| @Override |
| public RealMatrix getProcessNoise() { |
| return processNoiseCovMatrix; |
| } |
| |
| /** {@inheritDoc} */ |
| @Override |
| public RealVector getInitialStateEstimate() { |
| return initialStateEstimateVector; |
| } |
| |
| /** {@inheritDoc} */ |
| @Override |
| public RealMatrix getInitialErrorCovariance() { |
| return initialErrorCovMatrix; |
| } |
| } |