1 /*
2 * Licensed to the Apache Software Foundation (ASF) under one or more
3 * contributor license agreements. See the NOTICE file distributed with
4 * this work for additional information regarding copyright ownership.
5 * The ASF licenses this file to You under the Apache License, Version 2.0
6 * (the "License"); you may not use this file except in compliance with
7 * the License. You may obtain a copy of the License at
8 *
9 * https://www.apache.org/licenses/LICENSE-2.0
10 *
11 * Unless required by applicable law or agreed to in writing, software
12 * distributed under the License is distributed on an "AS IS" BASIS,
13 * WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
14 * See the License for the specific language governing permissions and
15 * limitations under the License.
16 */
17
18 /*
19 * This is not the original file distributed by the Apache Software Foundation
20 * It has been modified by the Hipparchus project
21 */
22 package org.hipparchus.optim.nonlinear.vector.leastsquares;
23
24 import org.hipparchus.linear.RealMatrix;
25 import org.hipparchus.linear.RealVector;
26 import org.hipparchus.optim.nonlinear.vector.leastsquares.LeastSquaresProblem.Evaluation;
27
28 /**
29 * Applies a dense weight matrix to an evaluation.
30 *
31 */
32 class DenseWeightedEvaluation extends AbstractEvaluation {
33
34 /** the unweighted evaluation */
35 private final Evaluation unweighted;
36 /** reference to the weight square root matrix */
37 private final RealMatrix weightSqrt;
38
39 /**
40 * Create a weighted evaluation from an unweighted one.
41 *
42 * @param unweighted the evalutation before weights are applied
43 * @param weightSqrt the matrix square root of the weight matrix
44 */
45 DenseWeightedEvaluation(final Evaluation unweighted,
46 final RealMatrix weightSqrt) {
47 // weight square root is square, nR=nC=number of observations
48 super(weightSqrt.getColumnDimension());
49 this.unweighted = unweighted;
50 this.weightSqrt = weightSqrt;
51 }
52
53 /* apply weights */
54
55 /** {@inheritDoc} */
56 @Override
57 public RealMatrix getJacobian() {
58 return weightSqrt.multiply(this.unweighted.getJacobian());
59 }
60
61 /** {@inheritDoc} */
62 @Override
63 public RealVector getResiduals() {
64 return this.weightSqrt.operate(this.unweighted.getResiduals());
65 }
66
67 /* delegate */
68
69 /** {@inheritDoc} */
70 @Override
71 public RealVector getPoint() {
72 return unweighted.getPoint();
73 }
74
75 }