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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    *      http://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  package org.apache.commons.math4.legacy.linear;
19  
20  import org.apache.commons.math4.legacy.core.FieldElement;
21  
22  
23  /**
24   * Interface handling decomposition algorithms that can solve A × X = B.
25   * <p>Decomposition algorithms decompose an A matrix has a product of several specific
26   * matrices from which they can solve A &times; X = B in least squares sense: they find X
27   * such that ||A &times; X - B|| is minimal.</p>
28   * <p>Some solvers like {@link FieldLUDecomposition} can only find the solution for
29   * square matrices and when the solution is an exact linear solution, i.e. when
30   * ||A &times; X - B|| is exactly 0. Other solvers can also find solutions
31   * with non-square matrix A and with non-null minimal norm. If an exact linear
32   * solution exists it is also the minimal norm solution.</p>
33   *
34   * @param <T> the type of the field elements
35   * @since 2.0
36   */
37  public interface FieldDecompositionSolver<T extends FieldElement<T>> {
38  
39      /** Solve the linear equation A &times; X = B for matrices A.
40       * <p>The A matrix is implicit, it is provided by the underlying
41       * decomposition algorithm.</p>
42       * @param b right-hand side of the equation A &times; X = B
43       * @return a vector X that minimizes the two norm of A &times; X - B
44       * @throws org.apache.commons.math4.legacy.exception.DimensionMismatchException
45       * if the matrices dimensions do not match.
46       * @throws SingularMatrixException
47       * if the decomposed matrix is singular.
48       */
49      FieldVector<T> solve(FieldVector<T> b);
50  
51      /** Solve the linear equation A &times; X = B for matrices A.
52       * <p>The A matrix is implicit, it is provided by the underlying
53       * decomposition algorithm.</p>
54       * @param b right-hand side of the equation A &times; X = B
55       * @return a matrix X that minimizes the two norm of A &times; X - B
56       * @throws org.apache.commons.math4.legacy.exception.DimensionMismatchException
57       * if the matrices dimensions do not match.
58       * @throws SingularMatrixException
59       * if the decomposed matrix is singular.
60       */
61      FieldMatrix<T> solve(FieldMatrix<T> b);
62  
63      /**
64       * Check if the decomposed matrix is non-singular.
65       * @return true if the decomposed matrix is non-singular
66       */
67      boolean isNonSingular();
68  
69      /** Get the inverse (or pseudo-inverse) of the decomposed matrix.
70       * @return inverse matrix
71       * @throws SingularMatrixException
72       * if the decomposed matrix is singular.
73       */
74      FieldMatrix<T> getInverse();
75  }