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
23 package org.hipparchus.linear;
24
25 import org.hipparchus.FieldElement;
26
27
28 /**
29 * Interface handling decomposition algorithms that can solve A × X = B.
30 * <p>
31 * Decomposition algorithms decompose an A matrix has a product of several specific
32 * matrices from which they can solve A × X = B in least squares sense: they find X
33 * such that ||A × X - B|| is minimal.
34 * <p>
35 * Some solvers like {@link FieldLUDecomposition} can only find the solution for
36 * square matrices and when the solution is an exact linear solution, i.e. when
37 * ||A × X - B|| is exactly 0. Other solvers can also find solutions
38 * with non-square matrix A and with non-null minimal norm. If an exact linear
39 * solution exists it is also the minimal norm solution.
40 *
41 * @param <T> the type of the field elements
42 */
43 public interface FieldDecompositionSolver<T extends FieldElement<T>> {
44
45 /** Solve the linear equation A × X = B for matrices A.
46 * <p>The A matrix is implicit, it is provided by the underlying
47 * decomposition algorithm.</p>
48 * @param b right-hand side of the equation A × X = B
49 * @return a vector X that minimizes the two norm of A × X - B
50 * @throws org.hipparchus.exception.MathIllegalArgumentException
51 * if the matrices dimensions do not match or the decomposed matrix
52 * is singular.
53 */
54 FieldVector<T> solve(FieldVector<T> b);
55
56 /** Solve the linear equation A × X = B for matrices A.
57 * <p>The A matrix is implicit, it is provided by the underlying
58 * decomposition algorithm.</p>
59 * @param b right-hand side of the equation A × X = B
60 * @return a matrix X that minimizes the two norm of A × X - B
61 * @throws org.hipparchus.exception.MathIllegalArgumentException
62 * if the matrices dimensions do not match or the decomposed matrix
63 * is singular.
64 */
65 FieldMatrix<T> solve(FieldMatrix<T> b);
66
67 /**
68 * Check if the decomposed matrix is non-singular.
69 * @return true if the decomposed matrix is non-singular
70 */
71 boolean isNonSingular();
72
73 /** Get the inverse (or pseudo-inverse) of the decomposed matrix.
74 * @return inverse matrix
75 * @throws org.hipparchus.exception.MathIllegalArgumentException
76 * if the decomposed matrix is singular.
77 */
78 FieldMatrix<T> getInverse();
79
80 /**
81 * Returns the number of rows in the matrix.
82 *
83 * @return rowDimension
84 * @since 2.0
85 */
86 int getRowDimension();
87
88 /**
89 * Returns the number of columns in the matrix.
90 *
91 * @return columnDimension
92 * @since 2.0
93 */
94 int getColumnDimension();
95
96 }