1 /*
2 * Copyright (C) 2016 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.numerical.robust;
17
18 import java.util.BitSet;
19
20 /**
21 * Base class defining inlier data for a robust estimator.
22 */
23 public abstract class InliersData {
24
25 /**
26 * Residuals obtained for each sample of data.
27 */
28 protected double[] residuals;
29
30 /**
31 * Number of inliers found on current iteration.
32 */
33 protected int numInliers;
34
35 /**
36 * Returns efficient array indicating which samples are considered inliers
37 * and which ones aren't or null if inliers are not kept.
38 *
39 * @return array indicating which samples are considered inliers and which
40 * ones aren't, or null.
41 */
42 public abstract BitSet getInliers();
43
44 /**
45 * Returns residuals obtained for each sample of data or null if residuals
46 * are not kept.
47 *
48 * @return residuals obtained for each sample of data.
49 */
50 public double[] getResiduals() {
51 return residuals;
52 }
53
54 /**
55 * Returns number of inliers found.
56 *
57 * @return number of inliers found.
58 */
59 public int getNumInliers() {
60 return numInliers;
61 }
62 }