    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.RealMatrix;
    024
    025    /**
    026     * Default implementation of a {@link MeasurementModel} for the use with a {@link KalmanFilter}.
    027     *
    028     * @since 3.0
    029     * @version $Id: DefaultMeasurementModel.java 1416643 2012-12-03 19:37:14Z tn $
    030     */
    031    public class DefaultMeasurementModel implements MeasurementModel {
    032
    033        /**
    034         * The measurement matrix, used to associate the measurement vector to the
    035         * internal state estimation vector.
    036         */
    037        private RealMatrix measurementMatrix;
    038
    039        /**
    040         * The measurement noise covariance matrix.
    041         */
    042        private RealMatrix measurementNoise;
    043
    044        /**
    045         * Create a new {@link MeasurementModel}, taking double arrays as input parameters for the
    046         * respective measurement matrix and noise.
    047         *
    048         * @param measMatrix
    049         *            the measurement matrix
    050         * @param measNoise
    051         *            the measurement noise matrix
    052         * @throws NullArgumentException
    053         *             if any of the input matrices is {@code null}
    054         * @throws NoDataException
    055         *             if any row / column dimension of the input matrices is zero
    056         * @throws DimensionMismatchException
    057         *             if any of the input matrices is non-rectangular
    058         */
    059        public DefaultMeasurementModel(final double[][] measMatrix, final double[][] measNoise)
    060                throws NullArgumentException, NoDataException, DimensionMismatchException {
    061            this(new Array2DRowRealMatrix(measMatrix), new Array2DRowRealMatrix(measNoise));
    062        }
    063
    064        /**
    065         * Create a new {@link MeasurementModel}, taking {@link RealMatrix} objects
    066         * as input parameters for the respective measurement matrix and noise.
    067         *
    068         * @param measMatrix the measurement matrix
    069         * @param measNoise the measurement noise matrix
    070         */
    071        public DefaultMeasurementModel(final RealMatrix measMatrix, final RealMatrix measNoise) {
    072            this.measurementMatrix = measMatrix;
    073            this.measurementNoise = measNoise;
    074        }
    075
    076        /** {@inheritDoc} */
    077        public RealMatrix getMeasurementMatrix() {
    078            return measurementMatrix;
    079        }
    080
    081        /** {@inheritDoc} */
    082        public RealMatrix getMeasurementNoise() {
    083            return measurementNoise;
    084        }
    085    }