1 /*
2 * Copyright (C) 2012 Alberto Irurueta Carro (alberto@irurueta.com)
3 *
4 * Licensed under the Apache License, Version 2.0 (the "License");
5 * you may not use this file except in compliance with the License.
6 * You may obtain a copy of the License at
7 *
8 * http://www.apache.org/licenses/LICENSE-2.0
9 *
10 * Unless required by applicable law or agreed to in writing, software
11 * distributed under the License is distributed on an "AS IS" BASIS,
12 * WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
13 * See the License for the specific language governing permissions and
14 * limitations under the License.
15 */
16 package com.irurueta.algebra;
17
18 /**
19 * Class in charge of computing one norms of arrays and matrices.
20 * One norm is defined as the maximum column sum on a matrix or array.
21 * For the case of arrays, this library considers arrays as column matrices
22 * with one column and array length rows.
23 */
24 public class OneNormComputer extends NormComputer {
25
26 /**
27 * Constructor of this class.
28 */
29 public OneNormComputer() {
30 super();
31 }
32
33 /**
34 * Returns norm type being used by this class.
35 *
36 * @return Norm type being used by this class.
37 */
38 @Override
39 public NormType getNormType() {
40 return NormType.ONE_NORM;
41 }
42
43 /**
44 * Computes norm of provided matrix.
45 *
46 * @param m matrix being used for norm computation.
47 * @return norm of provided matrix.
48 */
49 @SuppressWarnings("DuplicatedCode")
50 public static double norm(final Matrix m) {
51 final var rows = m.getRows();
52 final var columns = m.getColumns();
53 double colSum;
54 var maxColSum = 0.0;
55
56 for (var j = 0; j < columns; j++) {
57 colSum = 0.0;
58 for (var i = 0; i < rows; i++) {
59 colSum += Math.abs(m.getElementAt(i, j));
60 }
61
62 maxColSum = Math.max(colSum, maxColSum);
63 }
64
65 return maxColSum;
66 }
67
68 /**
69 * Computes norm of provided matrix.
70 *
71 * @param m Matrix being used for norm computation.
72 * @return Norm of provided matrix.
73 */
74 @Override
75 public double getNorm(final Matrix m) {
76 return norm(m);
77 }
78
79 /**
80 * Computes norm of provided array.
81 *
82 * @param array array being used for norm computation.
83 * @return norm of provided vector.
84 */
85 public static double norm(final double[] array) {
86 var colSum = 0.0;
87
88 for (final var value : array) {
89 colSum += Math.abs(value);
90 }
91
92 return colSum;
93 }
94
95 /**
96 * Computes norm of provided array and stores the jacobian into provided
97 * instance.
98 *
99 * @param array array being used for norm computation.
100 * @param jacobian instance where jacobian will be stored. Must be 1xN,
101 * where N is length of array.
102 * @return norm of provided vector.
103 * @throws WrongSizeException if provided jacobian is not 1xN, where N is
104 * length of array.
105 */
106 public static double norm(final double[] array, final Matrix jacobian) throws WrongSizeException {
107 if (jacobian != null && (jacobian.getRows() != 1 || jacobian.getColumns() != array.length)) {
108 throw new WrongSizeException("jacobian must be 1xN, where N is length of array");
109 }
110
111 final var norm = norm(array);
112
113 if (jacobian != null) {
114 jacobian.fromArray(array);
115 if (norm != 0.0) {
116 jacobian.multiplyByScalar(1.0 / norm);
117 } else {
118 jacobian.initialize(Double.MAX_VALUE);
119 }
120 }
121
122 return norm;
123 }
124
125 /**
126 * Computes norm of provided array.
127 *
128 * @param array Array being used for norm computation.
129 * @return Norm of provided vector.
130 */
131 @Override
132 public double getNorm(final double[] array) {
133 return norm(array);
134 }
135 }