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1 | // Created on: 1991-05-13 |
2 | // Created by: Laurent PAINNOT |
3 | // Copyright (c) 1991-1999 Matra Datavision |
4 | // Copyright (c) 1999-2014 OPEN CASCADE SAS |
5 | // |
6 | // This file is part of Open CASCADE Technology software library. |
7 | // |
8 | // This library is free software; you can redistribute it and/or modify it under |
9 | // the terms of the GNU Lesser General Public License version 2.1 as published |
10 | // by the Free Software Foundation, with special exception defined in the file |
11 | // OCCT_LGPL_EXCEPTION.txt. Consult the file LICENSE_LGPL_21.txt included in OCCT |
12 | // distribution for complete text of the license and disclaimer of any warranty. |
13 | // |
14 | // Alternatively, this file may be used under the terms of Open CASCADE |
15 | // commercial license or contractual agreement. |
16 | |
17 | #ifndef _math_SVD_HeaderFile |
18 | #define _math_SVD_HeaderFile |
19 | |
20 | #include <Standard.hxx> |
21 | #include <Standard_DefineAlloc.hxx> |
22 | #include <Standard_Handle.hxx> |
23 | |
24 | #include <Standard_Boolean.hxx> |
25 | #include <math_Matrix.hxx> |
26 | #include <math_Vector.hxx> |
27 | #include <Standard_Integer.hxx> |
28 | #include <Standard_Real.hxx> |
29 | #include <Standard_OStream.hxx> |
30 | class StdFail_NotDone; |
31 | class Standard_DimensionError; |
32 | class math_Matrix; |
33 | |
34 | |
35 | //! SVD implements the solution of a set of N linear equations |
36 | //! of M unknowns without condition on N or M. The Singular |
37 | //! Value Decomposition algorithm is used. For singular or |
38 | //! nearly singular matrices SVD is a better choice than Gauss |
39 | //! or GaussLeastSquare. |
40 | class math_SVD |
41 | { |
42 | public: |
43 | |
44 | DEFINE_STANDARD_ALLOC |
45 | |
46 | |
47 | |
48 | //! Given as input an n X m matrix A with n < m, n = m or n > m |
49 | //! this constructor performs the Singular Value Decomposition. |
50 | Standard_EXPORT math_SVD(const math_Matrix& A); |
51 | |
52 | //! Returns true if the computations are successful, otherwise returns false. |
53 | Standard_Boolean IsDone() const; |
54 | |
55 | |
56 | //! Given the input Vector B this routine solves the set of linear |
57 | //! equations A . X = B. |
58 | //! Exception NotDone is raised if the decomposition of A was not done |
59 | //! successfully. |
60 | //! Exception DimensionError is raised if the range of B is not |
61 | //! equal to the rowrange of A. |
62 | //! Exception DimensionError is raised if the range of X is not |
63 | //! equal to the colrange of A. |
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64 | Standard_EXPORT void Solve (const math_Vector& B, math_Vector& X, const Standard_Real Eps = 1.0e-6); |
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65 | |
66 | //! Computes the inverse Inv of matrix A such as A * Inverse = Identity. |
67 | //! Exceptions |
68 | //! StdFail_NotDone if the algorithm fails (and IsDone returns false). |
69 | //! Standard_DimensionError if the ranges of Inv are |
70 | //! compatible with the ranges of A. |
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71 | Standard_EXPORT void PseudoInverse (math_Matrix& Inv, const Standard_Real Eps = 1.0e-6); |
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72 | |
73 | //! Prints information on the current state of the object. |
74 | //! Is used to redefine the operator <<. |
75 | Standard_EXPORT void Dump (Standard_OStream& o) const; |
76 | |
77 | |
78 | |
79 | |
80 | protected: |
81 | |
82 | |
83 | |
84 | |
85 | |
86 | private: |
87 | |
88 | |
89 | |
90 | Standard_Boolean Done; |
91 | math_Matrix U; |
92 | math_Matrix V; |
93 | math_Vector Diag; |
94 | Standard_Integer RowA; |
95 | |
96 | |
97 | }; |
98 | |
99 | |
100 | #include <math_SVD.lxx> |
101 | |
102 | |
103 | |
104 | |
105 | |
106 | #endif // _math_SVD_HeaderFile |